Using Long-Term Earth Observation Data to Reveal the Factors Contributing to the Early 2020 Desert Locust Upsurge and the Resulting Vegetation Loss

remote sensing

Article Using Long-Term Earth Observation Data to Reveal the Factors Contributing to the Early 2020 Desert Locust Upsurge and the Resulting Vegetation Loss

Lei Wang 1, Wen Zhuo 1, Zhifang Pei 2, Xingyuan Tong 3, Wei Han 4,5 and Shibo Fang 1,3,*

1 State Key Laboratory of Severe Weather, Chinese Academy of Meteorological Sciences, Beijing 100081, China; [email protected] (L.W.); [email protected] (W.Z.) 2 College of Earth Science, Chengdu University of Technology, Chengdu 610059, China; [email protected] 3 Collaborative Innovation Centre on Forecast and Evaluation of Meteorological Disasters, Nanjing University of Information Science & Technology, Nanjing 210044, China; [email protected] 4 National Meteorological Center of China, Beijing 100081, China; [email protected] 5 Numerical Weather Prediction Center of Chinese Meteorological Administration, Beijing 100081, China * Correspondence: [email protected]

Abstract: Massive desert locust swarms have been threatening and devouring natural vegetation and agricultural crops in East Africa and West Asia since 2019, and the event developed into a rare and globally concerning locust upsurge in early 2020. The breeding, maturation, concentration and migration of locusts rely on appropriate environmental factors, mainly precipitation, temperature, vegetation coverage and land-surface soil moisture. Remotely sensed images and long-term meteorological observations across the desert locust invasion area were analyzed to explore the complex drivers, vegetation losses and growing trends during the locust upsurge in this study. The results revealed that (1) the intense precipitation events in the Arabian Peninsula during 2018 provided Citation: Wang, L.; Zhuo, W.; Pei, Z.; Tong, X.; Han, W.; Fang, S. Using suitable soil moisture and lush vegetation, thus promoting locust breeding, multiplication and gre- Long-Term Earth Observation Data to garization; (2) the regions affected by the heavy rainfall in 2019 shifted from the Arabian Peninsula to Reveal the Factors Contributing to the West Asia and Northeast Africa, thus driving the vast locust swarms migrating into those regions Early 2020 Desert Locust Upsurge and causing enormous vegetation loss; (3) the soil moisture and NDVI anomalies corresponded well and the Resulting Vegetation Loss. with the locust swarm movements; and (4) there was a low chance the eastwardly migrating locust Remote Sens. 2021, 13, 680. swarms would fly into the Indochina Peninsula and Southwest China. https://doi.org/10.3390/rs13040680 Keywords: desert locust upsurge; contributing factors; vegetation loss; long-term Earth observations; Academic Editor: Karel Charvat remote sensing Received: 5 January 2021 Accepted: 7 February 2021 Published: 13 February 2021 1. Introduction Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in The desert locust (Schistocerca gregaria) has been among the most devastating and published maps and institutional affil- notable pests that threaten local food security in Africa, the Middle East and Southwest Asia iations. since the beginning of recorded history [1]. Various large-scale crop protection strategies and preventive management strategies for desert locusts, such as chemical pesticides, field assessments and early warning systems, have been implemented by researchers and institutions since the 1950s [2]. Among them, the Food and Agriculture Organization of the United Nations (FAO) has played an important role in monitoring the timing, scale Copyright: © 2021 by the authors. Licensee MDPI, Basel, Switzerland. and location of invasions and breeding through its global Desert Locust Information This article is an open access article Service (DLIS) (http://www.fao.org/ag/locusts/en/activ/DLIS/index.html). Therefore, distributed under the terms and locust outbreaks and plagues have been successfully controlled, and the frequency of conditions of the Creative Commons intense and widespread locust infestations has declined significantly in the past several Attribution (CC BY) license (https:// decades [3]. The locust upsurge in early 2020 has been recognized as the worst infestation creativecommons.org/licenses/by/ in several decades for some East Africa and West Asia countries, such as Kenya, Ethiopia 4.0/). and Pakistan, and the hectares of damaged forests and farmlands are still increasing [4]. It

Remote Sens. 2021, 13, 680. https://doi.org/10.3390/rs13040680 https://www.mdpi.com/journal/remotesensing Remote Sens. 2021, 13, 680 2 of 19

is widely acknowledged that climatic conditions strongly influence locust outbreaks and upsurge processes [5–8]. Knowledge of the climatic drivers behind this unusual locust crisis is essential to further improve the early warning accuracy of outbreaks and potentially assist with socioeconomic loss assessments during the vastly damaging and lasting locust upsurge. Desert locust upsurges are initiated from a large number of contemporaneous outbreaks, which are supported by favorable conditions, including high rainfall, green vegetation, moistened soil, low-speed wind and appropriate land surface temperature [9]. Large-scale and long-term environmental variables over the seasonal breeding areas of locusts are necessary to forecast the spatial–temporal dynamics of locust outbreaks and develop effective control strategies [10]. Many previous studies have highlighted the advantages and efficiency of satellite platforms for collecting meteorological parameters and land surface observations at national and global scales. Satellite-based time series data, such as precipitation, land surface temperature and soil moisture, have been increasingly applied to estimate the location of desert locust breeding and recession areas and have been used to provide effective preventive management [11–16]. A deep understanding of the roles of various climatic features in desert locust breeding, multiplication, concentration and gregarization is needed to improve the reliability of the detection, prediction and simulation of the presence of locust outbreaks [5,17]. In general, the affecting factors vary during different life stages of the desert locust, and rainfall and temperature are commonly recognized as two of the most relevant parameters. According to Symmons, Cressman [18], the period of egg incubation and development decreases rapidly from approximately 26 to 10 days with increases in soil temperature from 24 to 37 °C, and hopper development occurs more quickly at high air temperatures, which indicates that high temperatures (approximately 30–37 °C) provide appropriate conditions for rapid desert locust population growth. Apart from the air and soil temperatures, rainfall events usually produce adequate soil moisture associated with egg laying and abundant herbaceous vegetation for increased survival of hoppers to the winged adult stage [13,19]. A longer and favorable rainy season in the breeding area drives the rapid maturation of populations, and two or three generations can be produced in rapid succession [20]. Vegetation coverage has remarkable effects on the associated changes in behavior, color, and shape as well as the formation of hopper bands and swarms when the population density of locusts is high [21]. The less uniform regions with relatively dense vegetation patches separated by extensive areas of bare land are likely to favor locust concentration and gregarization [13]. The migration of locust swarms occurs only when there are appropriate take-off wind speeds and wind directions. Generally, locust swarms take off when the wind speed is lower than 6 m/s, and the flight direction is downwind [18]. In addition, in high mountains and dense vegetation, locust swarms settle because their maximum flight height is 1700 m, and the swarms continue flying only when there is little or no vegetation [19]. The desert locust upsurge during 2019–2020 originated from the breeding areas in Northeast Africa and Southwest Asia and severely destroyed natural vegetation, food crops and forage in East Africa countries, especially Kenya, Ethiopia, and Somalia, as well as in the Indo-Pakistan border area, and the upsurge may threaten West Africa, East India, the Indochina Peninsula and Southwest China. This study aims (1) to identify the contributing factors of desert locust swarm formation and migration by collecting various environmental observations, including precipitation, soil moisture, air temperature and vegetation coverage; (2) to evaluate the impacts of locust swarms on local vegetation in the most damaged areas, mainly the border area of the Kenya, Ethiopia, and Somalia (K-E-S) and the Indo-Pakistan border area based on satellite remotely sensed vegetation indices; and (3) to identify the growing trend of locust swarms and estimate the chances of the desert locusts invading the Indochina Peninsula and eastern areas outside the current invasion border in the future considering that the desert locust swarms are still expanding and threatening neighboring countries and regions. For this purpose, the Remote Sens. 2021, 13, x FOR PEER REVIEW 3 of 19

Remote Sens. 2021, 13, 680 3 of 19 desert locusts invading the Indochina Peninsula and eastern areas outside the current invasion border in the future considering that the desert locust swarms are still expanding and threatening neighboring countries and regions. For this purpose, the historical pre- historicalcipitation, precipitation, soil moisture, soil vege moisture,tation vegetationcoverage coverageand elevation and elevation data in datathose in areas those areaswere weremapped. mapped.

2. Materials and Methods 2.1. Study Area 2.1. Study Area The study area is located in East Africa and West Asia, and the region was separated The study area is located in East Africa and West Asia, and the region was separated into three parts (Figure1) to analyze the contributing factors of the locust upsurge, evaluate into three parts (Figure 1) to analyze the contributing factors of the locust upsurge, eval- the locust’s impacts and identify the possibility of East India, the Indochina Peninsula and uate the locust’s impacts and identify the possibility of East India, the Indochina Peninsula Southwest China being affected by eastwardly migrating locust swarms in the future. Part and Southwest China being affected by eastwardly migrating locust swarms in the future. I includes the spring, summer and winter breeding areas of the desert locust in Northeast Part I includes the spring, summer and winter breeding areas of the desert locust in North- Africa and Southwest Asia. These breeding areas are located in the arid and semi-arid areaseast Africa of the and Sahara Southwest Desert, mainlyAsia. These on both breeding sides of areas the Red are Sea,located the middlein the arid of the and Arabian semi- Peninsula,arid areas of southwest the Sahara Yemen, Desert, northern mainly Somalia, on both southern sides of Pakistanthe Red Sea, and thethe Indo-Pakistanmiddle of the borderArabian area. Peninsula, The boundaries southwest ofYemen, the winter/spring northern Somalia, andsummer southern breeding Pakistan areas,and the as Indo- well asPakistan the invasion border and area. recession The boundaries areas, were of the acquired winter/spring from the and desert summer locust breeding guidelines areas, [18 as], andwell mappedas the invasion as Figure and1. Thisrecession region areas, is under were the acquired inﬂuence from of aridthe desert and semiarid locust guidelines climates, with[18], and an annual mapped rainfall as Figure lower 1. This than region 200 mm is [under22]. Part the IIinfluence includes of the arid severely and semiarid damaged cli- countriesmates, with and an regions, annual rainfall which includelower than the 200 summer mm [22]. breeding Part II area includes near thethe Indo-Pakistanseverely dam- borderaged countries and the and area regions, near the which border include of three the countries summer (Kenya,breeding Ethiopia area near and the Somalia) Indo-Paki- in Eaststan border Africa. and Part the III area includes near the breedingborder of areasthree countries of locust near(Kenya, the Ethiopia Indo-Pakistan and Somalia) border andin East the Africa. South Part Iran, III East includes India, the Southwest breeding China areas andof locust several near Southeast the Indo-Pakistan Asian countries, border whichand the have South recently Iran, East been India, threatened Southwest by highly China mobile and several and eastwardly Southeast migratingAsian countries, desert locustwhich swarms.have recently been threatened by highly mobile and eastwardly migrating desert locust swarms.

I II III

FigureFigure 1. The spatial distribution of the annual rainfall in the breedingbreeding area, recession areaarea andand invasion areaarea ofof thethe African desertdesert locust.locust.

2.2. Meteorological Observations 2.2.1. Precipitation Data from the GPCC The Global PrecipitationPrecipitation Climatology Climatology Centre Centre (GPCC) (GPCC) provides provides more more than than ten ten precipita- precip- tionitation datasets datasets with with long long temporal temporal coverage coverage (1891–present) (1891–present) and fourand spatialfour spatial resolutions resolutions (1.0◦, 2.5(1.0°,◦, 0.252.5°,◦, and0.25°, 0.5 and◦)(https://opendata.dwd.de/ 0.5°) (https://opendata.dwd.de/).). The GPCC The GPCC products products have been have widely been appliedwidely applied in drought in drought monitoring, monitoring, analysis analysis of trends of and trends extreme and extreme climatic climatic conditions, conditions, calibra- tioncalibration of satellite of satellite data and data hydrological and hydrological studies. studies. Their sampling Their sampling error of griddederror of monthlygridded precipitation data has been quantiﬁed by World Meteorological Organization (WMO) and investigated by GPCC for various regions of the world. The relative sampling error of

Remote Sens. 2021, 13, 680 4 of 19

gridded monthly precipitation is between ±5 to 20% if five rain gauges are used [23]. In addition, the GPCC’s approach of interpolating the anomalies instead of absolute values is more efficient to reduce the sampling error than the choice of the interpolation method itself [24]. In this study, the GPCC full data monthly product (version 2018) during 1891– 2016 at 0.25◦ generated by Schneider, Becker [25] was used as the historical reference as the most accurate in situ precipitation re-analysis data set of GPCC. The GPCC first-guess monthly product at 1.0◦ created by Ziese, Becker [26] was applied to map the precipitation of the study area (part I) in 2018 and 2019. The percentage ratio of the precipitation (PRP) was calculated using the following equation:

PRP = Precip/Precip_histor × 100% (1)

where Precip represents the monthly precipitation, and Precip_histor represents the historical reference of precipitation. PRP > 100% indicates greater rainfall than the average value, and PRP < 100% indicates relatively low precipitation in the current month of the year.

2.2.2. Land Surface Data from the ECMWF Various forecast models and assimilation systems were developed and employed to archive the historical meteorological data and re-analysis datasets by the European Centre for Medium-Range Weather Forecasts (ECMWF) (https://www.ecmwf.int/). The ERA5 dataset produced by the ECMWF provides detailed and near-real-time estimates of atmospheric, land surface, and oceanic climate variables from 1950 onwards at one- hour intervals, and its spatial resolutions are 31 km at the global level and 62 km for the ensemble of data assimilation (EDA). The spatial–temporal resolution has been signiﬁcantly enhanced, and uncertainty estimates are also included in the ERA5 dataset, compared with the ERA-Interim dataset [27]. This study applied the ERA5 land monthly averaged data to calculate and map the 2 m air temperature, 10 m wind speed, soil temperature (Level 1) and soil moisture (Level 1) in the recent decade of the study area (part III). Moreover, the 2 m air temperature dataset was used to calculate the anomaly percentage of the air temperature (APat) over the study area (part I) using the following equation:

APat = (ATi − AT_ave)/AT_ave × 100% (2)

◦ where ATi represents the monthly air temperature ( C) in the ith year, and AT_ave represents the average air temperature over the past decade. APat > 0 means that the current air temperature is higher than that in normal years, and APat < 0 demonstrates a relatively lower air temperature in the current month of the year.

2.3. Remotely Sensed Data 2.3.1. Soil Moisture Data from the Fengyun Satellite In recent years, passive microwave remote sensing has been widely applied as an effective approach to measure soil moisture dynamics over large areas under all weather conditions [28]. Currently, a large number of microwave-based satellite missions have been frequently employed for global soil moisture monitoring. Among them, the Microwave Radiometer Imager (MWRI) onboard the Fengyun-3C (FY-3C) satellite launched by the National Satellite Meteorological Center (NSMC) of China have been frequently employed to monitor the regional soil moisture, and its retrievals have been proven to have good consistency with the measured soil data [29]. The monthly FY-3C/MWRI soil moisture products (FY-3C VSM) with a spatial resolution of 25 km and presented on the global equal-area scalable earth (EASE) Grid 2.0 are available from May 2014 to the present on the website of the NSMC (satellite.nsmc.org.cn/). This study collected and generated those products to map the spatial–temporal variation patterns of the land surface soil moisture in the latter half of 2019 and early 2020 across the locust invasion and recession areas. Remote Sens. 2021, 13, 680 5 of 19

2.3.2. MODIS NDVI The normalized difference vegetation index (NDVI) products derived from Moderate Resolution Imaging Spectroradiometer (MODIS) are the most mature and widely used source for monitoring vegetation status [30,31]. In this study, the monthly MODIS NDVI products (MOD13A3, v006) at a 1 km spatial resolution for 2010-2020 were downloaded from the NASA website (https://ladsweb.modaps.eosdis.nasa.gov/). Ten tiles (h21v07, h21v08, h21v09, h22v07, h22v08, h22v09, h23v05, h23v06, h24v05 and h24v06) of the NDVI products were reprojected and mosaicked to calculate the NDVI anomaly and map the vegetation status in East Africa and the Indo-Pakistan border area during 2019-2020. The NDVI anomaly (NA) was deﬁned as the difference between the current NDVI and the average NDVI in recent years:

n NAi = NDVIi − ∑ NDVIi/n (3) i=1

where NAi represents the NDVI anomaly in the ith month, NDVIi represents the NDVI in the ith month, and n is the number of years and equals 11 (2010–2020) in the study.

2.3.3. DEM Data There are several existing digital elevation models (DEMs), including the Advanced Space-borne Thermal Emission and Reflection Radiometer (ASTER) Global DEM (G-DEM), the Shuttle Radar Topographic Mission (SRTM) DMEs, and the Global Multi-resolution Terrain Elevation Data (GMTED2010) dataset, which are freely available for terrain analysis [32,33]. The GMTED2010 was jointly published by the U.S. Geological Survey (USGS) and the U.S. National Geospatial-Intelligence Agency (NGA), at spatial resolutions of 1 km, 450 m and 225 m. The consistency and vertical accuracy of the GMTED2010 dataset has been significantly enhanced over the former GTOPO30 elevation model [33]. In addition, the GMTED2010 dataset is set as the default DEM data by the Environment for Visualizing Images (ENVI), and it is convenient to load and apply GMTED2010 for elevation data visualization and image processing workflows. Here, the GMTED2010 data were applied to map the geomorphic conditions over East India and Southwest China.

2.4. Analysis of the Climatic Anomalies’ Contributions to the Desert Locust Upsurge Generally, desert locust upsurges and plagues occur after several successful locust breeding events with appropriate climatic conditions [5]. The desert locust upsurge in early 2020 can be traced back to the formation of locust generations and the expansion of locust swarms during 2018 and 2019 [4]. Here, the precipitation and the percentage ratio of precipitation during 2018–2019 over the study area (part I) were mapped to analyze how the precipitation anomalies contributed to the successive multiplication and migration of locusts. Apart from precipitation, favorable land surface air temperature and soil moisture drive a sequence promoting successful breeding and growth of desert locust populations. In this paper, the spatial–temporal characteristics of those variables were depicted to indicate the relationship between the variables’ anomalies and the locust outbreaks and upsurge.

2.5. Evaluation of Impacts and Growing Trends of Desert Locust Upsurge Here, the MODIS NDVI and NDVI anomaly data across the two severely damaged regions, i.e., the Indo-Pakistan border and East Africa countries, including Kenya, Ethiopia, and Somalia, were generated to assess the impacts on the local vegetation caused by desert locust swarms. In addition, it has been widely acknowledged that tropical cyclones and tropical depressions over western India are closely related to climatic condition anomalies. In this study, the frequencies and variation trends of tropical cyclones and depressions in the past 30 years were analyzed to identify the potential risk of future desert locust outbreaks, upsurges and plagues. Remote Sens. 2021, 13, 680 6 of 19

3. Results 3.1. The Contribution of Climatic Conditions to the 2020 Desert Locust Upsurge 3.1.1. Precipitation and Its Anomalies The precipitation anomalies during 2018–2019 were caused by several rare cyclones and tropical storms, mainly cyclone Mekunu in May 2018, cyclone Luban in October 2018 and cyclonic storm Pawan in December 2019 [4]. Here, the precipitation and precipitation percentage ratio compared with the historical reference over the breeding areas of the desert locust are shown in Figure2. According to Figure2a,b, the precipitation in West Oman and East Yemen was between 100 and 300 mm, and the percentage ratio of the precipitation reached 500%, indicating significant abnormal precipitation amounts across the South Arabian Peninsula. As a result, several lakes formed in the interior along the border between Yemen and Oman and in the edges of the Empty Quarter (http://www. fao.org/ag/locusts/en/info/info/index.html), thus providing favorable conditions for locust breeding and reproduction. Figure2c,d indicate a remarkable precipitation anomaly over the most parts of the Empty Quarter, the interior of Sudan and Eritrea and the Red Sea coastal plains in October 2018, which strongly supported the formation of desert locust groups in these areas. Furthermore, the remarkable precipitation anomaly in the Empty Quarter, where the control operations for the growing desert locusts were unavailable, have significantly augmented the locusts’ development. The heavy rain brought by the two cyclones in May 2018 and October 2018 provided favorable breeding conditions beginning in June 2018 and enabled the continuous and successful breeding of multiple desert locust generations. In 2019, the total precipitation across the central of the Arabian Peninsula sharply declined to approximately 50% of the annual precipitation in normal years, while the precipitation percentage ratio in the Somalian Peninsula and West Asian countries, including the southwest Iran, Afghanistan, Pakistan and West India, reached 125%~500% compared with the historical reference (Figure2e,f). Among those areas, the southwest Iran, with the precipitation over 75 mm (Figure2e) and the precipitation anomaly reaching 125% (Figure2f) allowed a westward extension of the spring breeding area of the locusts, thus strongly supported the locusts’ breeding in spring and the invasion process of the swarms towards the Indo-Pakistan border at the beginning of the summer. In general, the abundant rain in those areas around the Arabian Peninsula forced the desert locusts from the Arabian Peninsula migrated towards northwest to the southwest Iran in early 2019, and then migrated to the Indo-Pakistan border after the successful spring breeding. In addition, it supported the southwardly migrated swarms into the East Africa in 2019. Then the numerous locust swarms appeared around the East Africa and the Indo-Pakistan border, thus triggering the locust upsurge in East Africa and West Asia. The swarms have been invading, spreading and laying eggs in the East Africa during 2020, and the swarms are expected to lay eggs and growing in numbers in north Somalia, which received heavy rainfalls from cyclone Gati in November 2020, as well as the other east African countries with sufficient rainfalls (Figure2g,h), thus increasing the risk of prolonging the desert locust upsurge in the area. Remote Sens. 2021, 13, x FOR PEER REVIEW 7 of 19 Remote Sens. 2021, 13, 680 7 of 19

(b) Precipitation percentage ratio in May 2018 (a) Precipitation in May 2018 (mm) (%)

(d) Precipitation percentage ratio in October (c) Precipitation in October 2018 (mm) 2018 (%)

(e) Precipitation during January to December (f) Precipitation percentage ratio during 2019 (mm) January to December 2019 (%)

(h) Precipitation percentage ratio in (g) Precipitation in November 2020 (mm) November 2020 (%)

Figure 2.Figure Precipitation 2. Precipitation and andits percentage its percentage ratio ratio overover part part I of I theof studythe study area during area during 2018–2020. 2018–2020

Remote Sens. 2021, 13, 680 8 of 19

3.1.2. Air Temperature and Its Anomalies Apart from rainfall events, a high air temperature and land surface soil temperature, especially the high temperatures in months from April to December, will significantly decrease the period of egg incubation and hopper development, thus providing appropriate conditions for the rapid development of each desert locust generation. Here, the 2-m air temperature as well as its anomaly compared to the past decade across the study area in the warmest month (June) and coldest month (December) in 2018 and 2019 are mapped as Figure3. According to Figure3, the study area in June 2018 and 2019 has experienced a high and favorable air temperature (30~40 ◦C) in the entire Arabian Peninsula, summer and spring breeding areas in the West Asia and the both sides of the Red Sea (Figure3a,e ), thus accelerating the locust breeding, development and migration. In December 2018 and 2019, a large proportion of the study area, including the south Arabian Peninsula, the winter breeding areas in both sides of the Red Sea and the north Somalia, still have an air temperature higher than 20 ◦C (Figure3c,g), which continued the locust production and migration in winter. Additionally, the study area has experienced slightly higher air temperatures in most parts compared with the averaging monthly air temperature of the past ten years under the influence of global climate change. In 2018, the south and west of the study area showed a negative air temperature anomaly in June (Figure3b) and December (Figure3d), respectively. The air temperatures in other areas were higher than the norms, especially the Arabian Peninsula, whose air temperature anomalies in December was generally more than 0.5%. The area with a higher air temperature in 2019 (Figure3f,h) was enlarged than 2018. In order to examine the variation trend of the air temperature during 2018–2019, the monthly average of the air temperature and its percentage ratio compared to the past decade across the locusts breeding area, including the Empty Quarter and the southwest Iran, in 2018 and 2019 were calculated and graphed as Figure4. According to this figure, the months from April to October have a favorable air temperature (25~30°C) for the breeding and migration of the locusts, as well as the development of the vegetation, during 2018–2019. Additionally, the study area has experienced a similar or higher air temperature in most of months compared with the averaging air temperature in the past ten years under the influence of global climate change. In 2018, only one month (January) out of twelve has a slightly lower air temperature percentage ratio than 100%, and the other monthly air temperature values in the months from February to December are close to or higher than the averaged air temperature, especially in the February and March 2018, with the air temperature percentage ratios greater than 106.0%. In 2019, the monthly air temperature percentage ratios in February, March and April are lower than 100%, while the air temperature s of the other nine months are greater than or equal to the air temperature norms in the past ten years. It is likely that a favorable and higher air temperature in the study area promotes and accelerates desert locust population maturation, the production of multiple generations and locust swarm migration, especially during the spring period. Remote Sens. 2021, 13, x FOR PEER REVIEW 8 of 19

the warmest month (June) and coldest month (December) in 2018 and 2019 are mapped as Figure 3. According to Figure 3, the study area in June 2018 and 2019 has experienced a high and favorable air temperature (30~40 °C) in the entire Arabian Peninsula, summer and spring breeding areas in the West Asia and the both sides of the Red Sea (Figure 3a,e), thus accelerating the locust breeding, development and migration. In December 2018 and 2019, a large proportion of the study area, including the south Arabian Peninsula, the winter breeding areas in both sides of the Red Sea and the north Somalia, still have an air temperature higher than 20°C (Figure 3c,g), which continued the locust production and migration in winter. Additionally, the study area has experienced slightly higher air temperatures in most parts compared with the averaging monthly air temperature of the past ten years under the influence of global climate change. In 2018, the south and west of the study area showed a negative air temperature anomaly in June (Figure 3b) and December (Figure 3d), respectively. The air temperatures in other areas were higher than the norms, Remote Sens. 2021, 13, 680 9 of 19 especially the Arabian Peninsula, whose air temperature anomalies in December was generally more than 0.5 %. The area with a higher air temperature in 2019 (Figure 3f,h) was enlarged than 2018.

(a) Air temperature in June 2018 (°C) (b) Air temperature anomaly in June 2018 (%)

(d) Air temperature anomaly in December (c) Air temperature in December 2018 (°C) 2018 (%)

Remote Sens. 2021, 13, x FOR PEER REVIEW 9 of 19

(e) Air temperature in June 2019 (°C) (f) Air temperature anomaly in June 2019 (%)

(h) Air temperature anomaly in December (g) Air temperature in December 2019 (°C) 2019 (%)

Figure 3. Air temperature and its anomaly over partpart I of the study area during 2018–2019.

Figure 4. Air temperature and its percentage ratio over part I of the study area during 2018– 2019

3.1.3. Land Surface Soil Moisture In general, the desert locusts tend to breed in and migrate between their summer and winter/spring breeding areas, such as the Red Sea coast, interior of the Saudi Arabia, South Sudan, South Iran and the Indo-Pakistan border, and they migrate between the regions with continuous rainfall. The continuous heavy rainfalls during the latter half of 2019 and

Remote Sens. 2021, 13, x FOR PEER REVIEW 9 of 19

(h) Air temperature anomaly in December (g) Air temperature in December 2019 (°C) 2019 (%) Figure 3. Air temperature and its anomaly over part I of the study area during 2018–2019.

In order to examine the variation trend of the air temperature during 2018-2019, the monthly average of the air temperature and its percentage ratio compared to the past decade across the locusts breeding area, including the Empty Quarter and the southwest Iran, in 2018 and 2019 were calculated and graphed as Figure 4. According to this Figure, the months from April to October have a favorable air temperature (25~30℃) for the breeding and migration of the locusts, as well as the development of the vegetation, during 2018– 2019. Additionally, the study area has experienced a similar or higher air temperature in most of months compared with the averaging air temperature in the past ten years under the influence of global climate change. In 2018, only one month (January) out of twelve has a slightly lower air temperature percentage ratio than 100%, and the other monthly air temperature values in the months from February to December are close to or higher Remote Sens. 2021, 13, x FOR PEER REVIEW 10 of 19 than the averaged air temperature, especially in the February and March 2018, with the air temperature percentage ratios greater than 106.0%. In 2019, the monthly air temperature percentage ratios in February, March and April are lower than 100%, while the air Remote Sens. 2021, 13, 680temperature searly of the 2020 other greatly nine months increased are gr theeater land than surface or equal soil to moisturethe air temperature over the surrounding regions10 of 19 norms in the pastoutside ten years.the Arabian It is likely Peninsula, that a favorable thus providing and higher favorable air temperature soil conditions in the and lush vegeta- study area promotes and accelerates desert locust population maturation, the production tion for the migration of desert locust swarms into West Asia and East Africa. The land of multiple generations and locust swarm migration, especially during the spring period. surface soil moisture (0~5 cm) from March 2019 to February 2020 retrieved from the Feng- yun-3C/MWRI soil moisture products and the movement of the desert locusts are shown in Figure 5. A large proportion of the Arabian Peninsula had a low soil moisture and experienced a drought condition during 2019 (Figure 5a–j). Therefore, the vast Arabian Pen- insula desert locust swarms had to migrate to find more green vegetation as food and more favorable soil conditions for egg laying and hopper development. Unlike the Arabian Peninsula, the West Asia and East Africa, including the summer locust breeding area near the Indo-Pakistan border and the winter locust breeding area in the Somalia Peninsula, had a favorable soil moisture (between 0.05~0.20 cm3/cm3) for the egg laying of locust from the spring 2019 to early 2020 (Figure 5), thus provided adequate food and environmental conditions for breeding and the development of the newly arrived locust swarms. Therefore, vast locust swarms gathered in the Indo-Pakistan border area since the spring 2019 (Figure 5a–c) and expanded gradually until January 2020 (Fig-

Figure 4. Airure temperature 5l). Then, andthe its number percentage of ratiolocust over swarms part I of decreased the study area dramatically during 2018– in February 2020 due Figure2019 4. Air temperatureto the local and and its percentageinternational ratio preventive over part I ofand the controlling study area during strategies, 2018–2019. as well as the lower soil moisture than the earlier months (Figure 5k). Regarding East Africa, the areas with 3.1.3. Land Surfacesoil moisture Soil Moisture distributed between 0.10~0.20 cm3/cm3 were located in Somalia, North 3.1.3. Land Surface Soil Moisture In general,Kenya the desert and locustsEast Ethiopia tend to brfromeed inOctober and migrate to Nove betweenmber their 2019 summer (Figure and 5h,i), thus allowing the winter/springswarms breedingIn general,to areas, move such thesoutheastwardly as desert the Red locusts Sea coast, into tend interior the to Somalia breed of the inSaudi Peninsula and Arabia, migrate and South conduct between successful their summer pro- Sudan, South ductionandIran winter/springand subsequently. the Indo-Pakistan breeding The bo Somaliarder, areas, and suchand they East as migrate the Et Redhiopia between Sea had coast, thebecome regions interior dr y of since the SaudiJanuary Arabia, 2020 with continuous(FigureSouth rainfall. Sudan, 5k), The and continuous South the drought Iran heavy and conditions rainfalls the Indo-Pakistan during had beenthe latter border,worsened half of and 2019 in theythe and next migrate two betweenmonths. The the regions with continuous rainfall. The continuous heavy rainfalls during the latter half of appropriate and moist regions had passed southwestwardly to South Kenya and Ethiopia 2019 and early 2020 greatly increased the land surface soil moisture over the surrounding during January and February 2020 (Figure 5k,l). Accordingly, the Somalia and East Ethi- regions outside the Arabian Peninsula, thus providing favorable soil conditions and lush opia desert locust swarms moved towards the southwest to those regions since the early vegetation for the migration of desert locust swarms into West Asia and East Africa. The 2020. Additionally, the area with a soil moisture between 0.10~0.15 cm3/cm3 in the winter land surface soil moisture (0~5 cm) from March 2019 to February 2020 retrieved from the breeding area in the Arabian Peninsula and the south Yemen was significantly enlarged Fengyun-3C/MWRI soil moisture products and the movement of the desert locusts are than the previous months in the early 2020, which led to the reappearance of vast swarms shown in Figure5. A large proportion of the Arabian Peninsula had a low soil moisture in this region (Figure 5k). It is obvious that the soil moisture distribution was highly rele- and experienced a drought condition during 2019 (Figure5a–j). Therefore, the vast Arabian vant to the distribution and movements of desert locust swarms. The spatial–temporal Peninsula desert locust swarms had to migrate to ﬁnd more green vegetation as food and variation patterns of the soil moisture across West Asia and East Africa corresponded well more favorable soil conditions for egg laying and hopper development. with the migration routine of the desert locust swarms.

(a) March 2019 (b) April 2019

Figure 5. Cont.

Remote Sens. 2021,, 13,, 680x FOR PEER REVIEW 11 of 19

(e) July 2019 (f) August 2019

(g) September 2019 (%) (h) October 2019 (%)

(i) November 2019 (%) (j) December 2019 (%)

Figure 5. Cont.

Remote Sens. 2021, 13, x 680 FOR PEER REVIEW 12 of 19

(k) January 2020 (%) (l) February 2020 (%)

FigureFigure 5. SoilSoil moisture moisture over over part part I of the study area during 2019–2020.

3.2. TheUnlike Impact the Assessment Arabian Peninsula, of Desert Locust the West Swarms Asia on and the East Local Africa, Vegetation including the summer 3.2.1.locust NDVI breeding Anomalies area near in East the Indo-PakistanAfrica border and the winter locust breeding area in the Somalia Peninsula, had a favorable soil moisture (between 0.05~0.20 cm3/cm3) Kenya, Ethiopia and Somalia are important agricultural countries in East Africa, for the egg laying of locust from the spring 2019 to early 2020 (Figure5), thus provided where forages, crops and food security have been seriously threatened by the vast desert adequate food and environmental conditions for breeding and the development of the locust swarms that have migrated from the Arabian Peninsula since the end of 2019. Fig- newly arrived locust swarms. Therefore, vast locust swarms gathered in the Indo-Pakistan ure 6 shows that the swarms have been gathered near the borders of Ethiopia, Somalia border area since the spring 2019 (Figure5a–c) and expanded gradually until January and Kenya (E-S-K border region) for a long time since December 2019. Therefore, in this 2020 (Figure5l). Then, the number of locust swarms decreased dramatically in February study, the NDVI anomaly variation patterns across this region from December 2019 to 2020 due to the local and international preventive and controlling strategies, as well as the May 2020 were mapped, to assess the impacts on local vegetation caused by this locust lower soil moisture than the earlier months (Figure5k). Regarding East Africa, the areas crisis,with soil as moistureshown in distributed Figure 6. Considering between 0.10~0.20 that the cm vegetation3/cm3 were loss located caused in Somalia, by the desert North locustKenya swarms and East cannot Ethiopia be detected from October in the NDVI to November anomaly maps 2019 (Figureuntil the5h,i), vast thuslocust allowing swarms havethe swarms settled tothe move area for southeastwardly a long time, the into locust the Somaliaswarm distributions Peninsula and and conduct movement successful were analyzedproduction one subsequently. or two months The Somalia prior and (http: East//www.fao.org/ag/locu Ethiopia had becomests/en/info/info/in- dry since January dex.html)2020 (Figure to 5identifyk), and the droughtareas destroyed conditions by hadthe locust been worsened swarms. Ac incording the next to two the months. move- mentThe appropriateof the swarms, and scattered moist regions locust hadbands passed and groups southwestwardly showed up in to north South Somalia Kenya and EastEthiopia Ethiopia during since January November and February2019, and 2020a nu (Figurember of5 swarmsk,l). Accordingly, became visible the Somalia and moved and southwardlyEast Ethiopia into desert Kenya locust in swarmsDecember moved 2019, towardswhich corresponded the southwest well to those with regionsthe areas since ex- hibitingthe early the 2020. negative Additionally, NDVI anomalies the area with from a De soilcember moisture 2019 between to February 0.10~0.15 2020 cm(Figure3/cm 6a–3 in c).the The winter desert breeding locust swarms area in the grew Arabian dramatical Peninsulaly and and severely the south damaged Yemen East was Africa signiﬁcantly begin- ningenlarged in January than the 2020, previous and the months swarms in in the So earlymalia 2020,migrated which towards led to thesouthwest reappearance to Kenya of andvast South swarms Ethiopia in this in region January, (Figure and5 thenk). It moved is obvious eastward that theto North soil moisture Uganda distributionin February 2020,was highlyrespectively. relevant Thus, to thethe distributionvast migrated and desert movements locust swarms of desert have locust been swarms.causing great The vegetationspatial–temporal losses in variation this area patterns by March of the2020 soil, especially moisture the across South West Ethiopia, Asia and where East a Africa large proportioncorresponded have well a NDVI with theanomaly migration lower routine than − of0.05 the (Figure desert locust6d). The swarms. proportion of the areas with negative NDVI anomalies increased significantly in Kenya during April and May 20203.2. The(Figure Impact 6e,f), Assessment which ofcorresponded Desert Locust Swarmswell to onthe the distribution Local Vegetation and southwestwards movement3.2.1. NDVI of Anomalies the desert inlocust East swarms Africa at earlier times, and with the subsequent onset of the monsoonKenya, Ethiopia rains. and Somalia are important agricultural countries in East Africa, where forages, crops and food security have been seriously threatened by the vast desert locust swarms that have migrated from the Arabian Peninsula since the end of 2019. Figure6 shows that the swarms have been gathered near the borders of Ethiopia, Somalia and Kenya (E-S-K border region) for a long time since December 2019. Therefore, in this study, the NDVI anomaly variation patterns across this region from December 2019 to May 2020 were mapped, to assess the impacts on local vegetation caused by this locust crisis, as shown in Figure6. Considering that the vegetation loss caused by the desert locust swarms cannot be detected in the NDVI anomaly maps until the vast locust swarms have settled the area for a long time, the locust swarm distributions and movement were analyzed one or two months prior (http://www.fao.org/ag/locusts/en/info/info/index.html ) to identify (a) December 2019 (b) January 2020 (c) February 2020

Remote Sens. 2021, 13, x FOR PEER REVIEW 12 of 19

(k) January 2020 (%) (l) February 2020 (%) Figure 5. Soil moisture over part I of the study area during 2019–2020.

3.2. The Impact Assessment of Desert Locust Swarms on the Local Vegetation 3.2.1. NDVI Anomalies in East Africa Kenya, Ethiopia and Somalia are important agricultural countries in East Africa, where forages, crops and food security have been seriously threatened by the vast desert locust swarms that have migrated from the Arabian Peninsula since the end of 2019. Fig- ure 6 shows that the swarms have been gathered near the borders of Ethiopia, Somalia and Kenya (E-S-K border region) for a long time since December 2019. Therefore, in this study, the NDVI anomaly variation patterns across this region from December 2019 to May 2020 were mapped, to assess the impacts on local vegetation caused by this locust crisis, as shown in Figure 6. Considering that the vegetation loss caused by the desert Remote Sens. 2021, 13, 680 locust swarms cannot be detected in the NDVI anomaly maps until the vast locust swarms13 of 19 have settled the area for a long time, the locust swarm distributions and movement were analyzed one or two months prior (http://www.fao.org/ag/locusts/en/info/info/in- thedex.html) areas destroyed to identify by the the areas locust destroyed swarms. by According the locust to swarms. the movement According of theto the swarms, move- scatteredment of the locust swarms, bands scattered and groups locust showed bands upand in groups north Somaliashowed andup in East north Ethiopia Somalia since and NovemberEast Ethiopia 2019, since and November a number 2019, of swarms and a becamenumber visibleof swarms and became moved southwardlyvisible and moved into Kenyasouthwardly in December into Kenya 2019, whichin December corresponded 2019, which well withcorresponded the areas exhibitingwell with thethe negativeareas ex- NDVIhibiting anomalies the negative from NDVI December anomalies 2019 tofrom February December 2020 2019 (Figure to February6a–c). The 2020 desert (Figure locust 6a– swarmsc). The desert grew dramaticallylocust swarms and grew severely dramatical damagedly and East severely Africa damaged beginning East in January Africa begin- 2020, andning the in swarmsJanuary in2020, Somalia and the migrated swarms towards in Somalia southwest migrated to Kenya towards and southwest South Ethiopia to Kenya in January,and South and Ethiopia then moved in January, eastward and to then North moved Uganda eastward in February to North 2020, Uganda respectively. in February Thus, the2020, vast respectively. migrated desert Thus, locust the vast swarms migrated have de beensert locust causing swarms great vegetation have been lossescausing in great this areavegetation by March losses 2020, in especiallythis area by the March South 2020 Ethiopia,, especially where the a large South proportion Ethiopia, havewhere a NDVIa large anomalyproportion lower have than a NDVI−0.05 anomaly (Figure 6lowerd). The than proportion −0.05 (Figure of the 6d). areas The with proportion negative of NDVI the ar- anomalieseas with negative increased NDVI signiﬁcantly anomalies in Kenyaincreased during significantly April and in May Kenya 2020 during (Figure April6e,f), and which May corresponded2020 (Figure well6e,f), to which the distribution corresponded and southwestwardswell to the distribution movement and of thesouthwestwards desert locust swarmsmovement at earlier of the times,desert and locust with swarms the subsequent at earlier onsettimes, of and the with monsoon the subsequent rains. onset of the monsoon rains.

Remote Sens. 2021, 13, x FOR PEER REVIEW 13 of 19

(a) December 2019 (b) January 2020 (c) February 2020

(d) March 2020 (e) April 2020 (f) May 2020

FigureFigure 6. 6.Spatial–temporal Spatial–temporal patterns patterns of of NDVI NDVI anomalies anomalies in in E-S-K E-S-K border border region region from from December December 2019 2019 to to May May 2020. 2020.

3.2.2.3.2.2. NDVINDVI AnomaliesAnomalies inin thethe Indo-PakistanIndo-Pakistan Border Border Area Area AccordingAccording toto the investigationthe investigation conducted conducted and published and published by the FAO (byhttp://www. the FAO fao.org/ag/locusts/en/info/info/index.html(http://www.fao.org/ag/locusts/en/info/info/index.html),), the locust the swarms locust started swarms to formstarted and to increasedform and rapidlyincreased beginning rapidly beginning in the middle in the of 2019middle in theof 2019 breeding in the area breeding around area the around Indo- Pakistanthe Indo-Pakistan border. The border. NDVI The anomalies NDVI anomalies during Julyduring 2019 July and 2019 May and 2020 May (Figure 2020 (Figure7a–k) indicated7a–k) indicated that the that most the damagedmost damaged vegetation vegetation was mainlywas mainly located located in the in summer the summer locust lo- breedingcust breeding area, area, where where the NDVIthe NDVI values values were were widely widely lower lower than than those those in in normal normal years. years. FigureFigure7 7demonstrates demonstrates severe severe vegetation vegetation losses losses in in the the summer summer breeding breeding area area during during July July 20192019 andand February February 20202020 (Figure (Figure7 a–h),7a–h), and and the the vegetation vegetation conditions conditions has has been been improved improved sincesince MayMay 20202020 inin thisthis areaarea (Figure (Figure7 f)7f) because because the the number number of of locust locust swarms swarms declined declined rapidlyrapidly since since February February 2020 2020 (Figure (Figure5l), 5l), due due to theto the intense intense and and successful successful control control strategies. strate- Togies. conclude, To conclude, the NDVI the anomaliesNDVI anomalies can used can to used reﬂect to the reflect impacts the ofimpacts the desert of the locust desert swarms locust whenswarms prior when movements prior movements are considered. are considered.

(a) July 2019 (b) August 2019 (c) September 2019

(d) October 2019 (e) November 2019 (f) December 2019

Remote Sens. 2021, 13, x FOR PEER REVIEW 13 of 19

(d) March 2020 (e) April 2020 (f) May 2020 Figure 6. Spatial–temporal patterns of NDVI anomalies in E-S-K border region from December 2019 to May 2020.

3.2.2. NDVI Anomalies in the Indo-Pakistan Border Area According to the investigation conducted and published by the FAO (http://www.fao.org/ag/locusts/en/info/info/index.html), the locust swarms started to form and increased rapidly beginning in the middle of 2019 in the breeding area around the Indo-Pakistan border. The NDVI anomalies during July 2019 and May 2020 (Figure 7a–k) indicated that the most damaged vegetation was mainly located in the summer locust breeding area, where the NDVI values were widely lower than those in normal years. Figure 7 demonstrates severe vegetation losses in the summer breeding area during July 2019 and February 2020 (Figure 7a–h), and the vegetation conditions has been improved Remote Sens. 2021, 13, 680 since May 2020 in this area (Figure 7f) because the number of locust14 swarms of 19 declined rapidly since February 2020 (Figure 5l), due to the intense and successful control strategies. To conclude, the NDVI anomalies can used to reflect the impacts of the desert locust swarms when prior movements are considered.

(a) July 2019 (b) August 2019 (c) September 2019

Remote Sens. 2021, 13, x FOR PEER REVIEW 14 of 19

(d) October 2019 (e) November 2019 (f) December 2019

(g) January 2020 (h) February 2020 (i) March 2020

(j) April 2020 (k) May 2020

Figure 7.Figure Spatial–temporal 7. Spatial–temporal patterns of patterns the NDVI of the anomalies NDVI anomalies near the Indo-Pakistan near the Indo-Pakistan border from border July 2019 from toJuly May 2020. 2019 to May 2020. 3.3. Possibility Analysis of Desert Locust Swarms Migrating into the Indochina Peninsula and 3.3. Possibility AnalysisSouthwest of Desert China Locust Swarms Migrating into the Indochina Peninsula and Southwest China Because the expanding and eastwardly migrating desert locust swarms have been Because thethreatening expanding East and India, eastwardly the Indochina migrating Peninsula desert and locust Southwest swarms China, have this been study mapped threatening East India,the spatial the Indochinadistribution Peninsula patterns of and the Southwest average soil China, moisture this and study high mapped vegetation coverage the spatial distributionduring patterns 2008-2019, of theas well average as the soil elevation moisture ac andross high the study vegetation area (part coverage III) (Figure 8), to during 2008-2019,analyze as well the as possibility the elevation of desert across locust the study swarms area flying (part to III) the (Figure Indochina8), to Peninsula and analyze the possibilitySouthwest of desert China. locustAccording swarms to the flying biological to the characteristics Indochina Peninsulaof desert locust, and desert locust Southwest China.swarms According take tooff the under biological suitable characteristics climatic conditions, of desert such locust, as air temperature desert locust (20~40 °C) and swarms take off underwind speed suitable (<6 m/s). climatic Generally, conditions, the maximum such as airflight temperature height is no (20~40 more than◦C) 1700 m, and and wind speed (<6they m/s). are easily Generally, restrained the by maximum heavy rain flight and heightflourishing is no vegetation more than [18]. 1700 According m, to Fig- and they are easilyure restrained 8a, the desert by locust heavy swarms rain and cannot flourishing continue vegetation moving northward [18]. According across the Himalayas to Figure8a, theand desert other locust high swarmsmountains cannot due to continue the restrictions moving caused northward by elevation across (>2000 the m). East India Himalayas and otherhas a high significantly mountains higher due toprecipitation the restrictions (>100 caused mm) than by elevation that in the (>2000 locust m). breeding areas (Figure 8b) and is widely covered by dense vegetation (Figure 8c), which will inhibit the eastward migration of locust swarms. The countries and regions near the locust swarms’ historical invasion borders, such as Nepal, Bhutan, Burma, Thailand and Yunnan Prov- ince of China, have high precipitation (>200 mm) and perennial vegetation coverage as high as 0.9 (Figure 7b,c). Thus, the arrival of locust swarms is likely to be stopped by heavy rainfall and scattered by dense vegetation. In addition, the desert locusts are likely to perish even after they migrated into the Nepal, east India and further eastwards due to the fungal growth and the natural infection promoted by the local humid tropical conditions. In this case, the chance that the desert locust swarm will migrate across the region with a high density of vegetation and continue flying into the Indochina Peninsula and South- west China is very low. In addition, the reproduction of desert locust requires appropriate soil moisture. Figure 8d demonstrates a much moister soil in the eastern area outside the invasion border and Figure 8d demonstrates a much moister soil in this area (>0.3 m3/m3) than in the summer and winter desert locust breeding areas (<0.2 m3/m3). Besides the appropriate soil moisture, the reproduction of the desert locusts has to be in the open areas of sandy soil with very low air humidity, which are not broadly exist beyond the east India. In conclusion, there is little chance that the desert locust swarms will migrate into

Remote Sens. 2021, 13, 680 15 of 19

East India has a signiﬁcantly higher precipitation (>100 mm) than that in the locust breeding areas (Figure8b) and is widely covered by dense vegetation (Figure8c), which will inhibit the eastward migration of locust swarms. The countries and regions near the locust swarms’ historical invasion borders, such as Nepal, Bhutan, Burma, Thailand and Yunnan Province of China, have high precipitation (>200 mm) and perennial vegetation coverage as high as 0.9 (Figure7b,c). Thus, the arrival of locust swarms is likely to be stopped by heavy rainfall and scattered by dense vegetation. In addition, the desert locusts are likely to perish even after they migrated into the Nepal, east India and further eastwards due to the fungal growth and the natural infection promoted by the local humid tropical conditions. In this case, the chance that the desert locust swarm will migrate across the region with a high density of vegetation and continue ﬂying into the Indochina Peninsula and Southwest China is very low. In addition, the reproduction of desert locust requires appropriate soil moisture. Figure8d demonstrates a much moister soil in the eastern area outside the invasion border and Figure8d demonstrates a much moister soil in this area (>0.3 m 3/m3) than in the summer and winter desert locust breeding areas (<0.2 m3/m3). Besides the

Remote Sens. 2021, 13, x FOR PEER REVIEWappropriate soil moisture, the reproduction of the desert locusts has to be in the open15 areas of 19 of sandy soil with very low air humidity, which are not broadly exist beyond the east India. In conclusion, there is little chance that the desert locust swarms will migrate into the Indochina Peninsula, Southeast China and the eastern areas outside the locusts’ historical theinvasion Indochina borders. Peninsula, Southeast China and the eastern areas outside the locusts’ historical invasion borders.

(a) Elevation (m) (b) Precipitation (mm)

FigureFigure 8. 8. TheThe spatial spatial distribution distribution of of climatic climatic factors factors ne nearar the the southwest southwest border border of China during 2008–2019.

4.4. Discussion Discussion 4.1.4.1. The The Importance Importance of of Long-term Long-Term Earth Earth Observations Observations InIn this this study, long-timelong-time seriesseries EarthEarth observation observation data, data, such such as as remotely remotely sensed sensed FY-3C FY- 3Csoil soil moisture moisture images, images, precipitation precipitation data fromdata GPCCfrom GPCC and air and temperature air temperature data from data ECMWF, from ECMWF,played important played important roles in theroles detection in the detection of the dynamic of the dynamic patterns patterns of climatic of climatic conditions con- ditionsduring during 2018–2020 2018–2020 across across desert desert locust locust breeding breeding and and invasion invasion areas. areas. In In other other words, words, a alarge large amount amount of of freely freely available available Earth Earth data data provided provided a convenienta convenient way way to mapto map the the spatial– spatial–temporaltemporal patterns patterns of those of those environmental environmental factors factors and and then then revealed revealed the the driving driving factors fac- torsdominating dominating the processthe process of desert of desert locust locust upsurges. upsurges. Additionally, Additionally, the the vegetation vegetation anomalies anom- aliesand theand average the average environmental environmental variables, variables, including including precipitation, precipitation, soil temperature,soil temperature, and and vegetation coverage, in the past decade were derived and generated from long-term Earth observation data and significantly benefited the evaluation of the impacts on local vegetation and the potential risk of this desert locust upsurge. It is very likely that the increasing amount of satellite remote sensing data and meteorological observations will greatly facilitate the analysis of desert locust upsurges and other natural disasters in the future. Despite of those advantages of the long-term Earth observation dataset and products, there are still some limitations and need to be further improved to achieve better estimates in the future. For example, the FY-3C soil moisture products are likely to overestimate the soil moisture in those areas covered by dense vegetation [30], thus different models should be established and compared to achieve more consistent soil moisture estimates in areas with green plants. There are still omissions errors with the MODIS NDVI images with a 250 m spatial resolution and could be improved using filters to better reflect the regional vegetation status. The precipitation and land surface parameters at the daily scale can be derived from the GPCC and re-analysis datasets from ECMWF. However, the spatial resolution of some commonly used datasets is low, such as the spatial resolution of the GPCC first-guess monthly product is 1.0°. Therefore, the downscaling and multivariate-based

Remote Sens. 2021, 13, 680 16 of 19

vegetation coverage, in the past decade were derived and generated from long-term Earth observation data and significantly benefited the evaluation of the impacts on local vegetation and the potential risk of this desert locust upsurge. It is very likely that the increasing amount of satellite remote sensing data and meteorological observations will greatly facilitate the analysis of desert locust upsurges and other natural disasters in the future. Despite of those advantages of the long-term Earth observation dataset and products, there are still some limitations and need to be further improved to achieve better estimates in the future. For example, the FY-3C soil moisture products are likely to overestimate the soil moisture in those areas covered by dense vegetation [30], thus different models should be established and compared to achieve more consistent soil moisture estimates in areas with green plants. There are still omissions errors with the MODIS NDVI images with a 250 m spatial resolution and could be improved using filters to better reflect the regional vegetation status. The precipitation and land surface parameters at the daily scale can be derived from the GPCC and re-analysis datasets from ECMWF. However, the spatial resolution of some commonly used datasets is low, such as the spatial resolution of the GPCC first-guess monthly product is 1.0◦. Therefore, the downscaling and multivariate- based models should be developed to improve the applicability of those meteorological datasets and remotely sensing products.

4.2. Implications of This Study on Desert Locust Control A deep understanding of desert locust upsurge mechanisms is of utmost importance for improving the accuracy of desert locust detection and building control operations to prevent locust upsurges in the future. The results of this study suggest that the frequent and heavy rainfall is likely to play a major role in the formation and migration of locust swarms. During the 2019–2020 desert upsurges, the exceptional heavy rainfalls in southwest Iran in early 2019 has strongly supported the earlier and successful spring breeding of locust swarms than normal years. The Horn of Africa also received unusually late rainfall in December 2019, which was brought by the cyclonic storm Pawan, thus promoted the breeding and multiplication of the desert locusts. Apart from that, the interior of Yemen and the south west Asia has received continuous rains under the impact of the cyclones and monsoon in 2019, respectively. Besides, the lack of in-time and effective survey and control operations in those remote areas also forced the recent locust upsurge, which indicated that the desert locust management should be further enhanced in those regions with unusual and continuous rainfalls. Desert locusts usually gather in areas with high soil moisture and good vegetation coverage before moving to the surrounding areas when their current habitat becomes dry. This information could be considered to create more effective locust management strategies. Moreover, there is a time difference between the timing of rainfall and the swarm movement, which indicates that accurate precipitation predictions may help detect potential swarm outbreaks in advance and should be applied in future research.

4.3. Future Conditions for Desert Locust Outbreaks and Upsurges Many researchers have linked the risk of ﬁres and pest and pathogen outbreaks to the frequency and severity of extreme climatic events [1,34]. Considering that desert locust upsurges are closely related to climatic condition anomalies caused by more frequent tropical cyclones and depressions, we analyzed the trends in tropical cyclone and depression frequencies around the Arabian Peninsula and western India during 1990–2019 using the ﬁve-year moving average method, as shown in Figure9. The annual frequency of cyclonic disturbances (maximum wind speed of 17 knots or more), cyclones (34 knots or more) and severe cyclones (48 knots or more) over the Bay of Bengal (BOB), Arabian Sea (AS) and land surface of India was published by the website of the India Meteorological Department (IMD) (www.imd.gov.in). According to Figure9, an increasing trend is observed in the frequency of tropical cyclones and tropical depressions around the Arabian Peninsula and Remote Sens. 2021, 13, 680 17 of 19

the West Indian Ocean, which will lead to more precipitation and environmental anomalies in the breeding areas of the desert locusts. If this trend continues as part of climate change, conditions are likely to become increasingly suitable for desert locust upsurges, which Remote Sens. 2021, 13, x FOR PEER REVIEW 17 of 19 means that the sensitivity of the disaster warning system should be enhanced, and more effective prevention and control measures will need to be developed.

8 16 7 14 6 12 5 10 4 8 3 6 Frequency

2 Frequency 4 1 2 0 0 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010 2012 2014 2016 2018 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010 2012 2014 2016 2018

(a) Tropical cyclones around the Arabian (b) Tropical cyclones and depressions around Peninsula western India

Figure 9. Trend in tropical cyclone and depressiondepression frequencies during 1990–2019; the trend line is the five-year ﬁve-year moving average.

4.4.4.4. Study Study Limitations Limitations and and Uncertainty Uncertainty Although multiple multiple environmental environmental factors factors associated associated with with desert desert locust locust breeding, breeding, development,development, multiplication, multiplication, gregarization gregarization and and migration, migration, as as well well as as the the biological biological charac- charac- teristicsteristics of desert locusts,locusts, havehave been been analyzed analyzed in in this this study, study, our our current current analyzes analyzes and and results re- sultsare qualitative. are qualitative. The numericalThe numerical analysis analysis between between the locusts’ the locusts’ activities activities and thoseand those climatic cli- maticconditions conditions were notwere conducted not conducted in this in study, this duestudy, to thedue fact to the that fact the that movement the movement and popula- and populationtion of the desert of the locustdesert was locust comprehensively was comprehe affectednsively byaffected many otherby many factors, other especially factors, thees- peciallycontrol andthe control management and management strategies. Besides,strategies there. Besides, was an there uncertain was an time uncertain lagging, time which lagging,could which be two could or three be two months, or three between months, the be arrivaltween ofthe locusts arrival and of locusts the visible and vegetationthe visible vegetationlosses on the losses satellite on the images. satellite Those images. issues Those could issues cause could uncertainties cause uncertainties for the quantitative for the quantitativecorrelation analysis correlation in this analysis study. in Apart this stud fromy. those Apart uncertainties, from those uncertainties, the quantitative the analysisquanti- tativewas also analysis limited was by also the limited lack of by high-quality the lack of and high-quality long-term and survey long-term data. Moresurvey survey data. Moredata, survey such as data, egg density,such as egg which density, is closely which related is closely to swarm related size, to swarm should size, be considered should be consideredto accurately to andaccurately quantitatively and quantitatively assess the a impactssess the of desertimpact locustof desert swarms. locust Theswarms. accuracy The accuracyand resolution and resolution of various of Earth various observation Earth obse datasetsrvation datasets should be should further be improved further improved as input asvariables. input variables. Meanwhile, Meanwhile, some factors, some factors, such as such the complexas the complex mechanism mechanism by which by which desert desertlocusts locusts respond respond and adapt and toadapt extreme to extreme climatic climatic events, events, were notwere considered not considered when evalu-when evaluatingating the chances the chances of desert of desert locusts locusts migrating migrating to the to Indochinathe Indochina Peninsula Peninsula and and Southwest South- westChina. China. Hence, Hence, genetically genetically evolved evolved desert desert locusts locusts or extreme or extreme drought drought events events outside outside the theinvasion invasion boundary boundary would would undisputedly undisputedly promote promote the the expansion expansion of the of the swarms. swarms. Therefore, There- fore,a deep a deep understanding understanding of the of relationship the relationship between between locust locust upsurges upsurges and multipleand multiple variables var- iablesis needed, is needed, and a and comprehensive a comprehensive time time series series analysis analysis approach approach should should be be employed employed to toforecast forecast the the occurrence occurrence and and potential potential risk risk from from desert desert locustlocust upsurgesupsurges inin the future and supportsupport global global food food security security measures. measures. 5. Conclusions 5. Conclusions This study applied heterogeneous Earth observation data to analyze the contributions This study applied heterogeneous Earth observation data to analyze the contribu- of climatic anomalies, impacts on the local vegetation and the growing trend of the recent tions of climatic anomalies, impacts on the local vegetation and the growing trend of the desert locust upsurge. The results showed that a sequence of higher-than-normal precipita- recent desert locust upsurge. The results showed that a sequence of higher-than-normal precipitation, air temperature and soil moisture during 2018-2020 provided a favorable environment for a number of successive generations of desert locust breeding that led to the observed locust upsurge in East Africa and West Asia in early 2020. Among those regions affected by desert locust swarms, Kenya, Ethiopia, Somalia and the Indo-Pakistan border areas have suffered the most. The vegetation losses in East Africa countries have greatly worsened since March 2020, and South and West Africa are still being threatened.

Remote Sens. 2021, 13, 680 18 of 19

tion, air temperature and soil moisture during 2018-2020 provided a favorable environment for a number of successive generations of desert locust breeding that led to the observed locust upsurge in East Africa and West Asia in early 2020. Among those regions affected by desert locust swarms, Kenya, Ethiopia, Somalia and the Indo-Pakistan border areas have suffered the most. The vegetation losses in East Africa countries have greatly worsened since March 2020, and South and West Africa are still being threatened. The desert locust crisis in West Asia originated from the summer breeding area along the Indo-Pakistan border and destroyed numerous vegetation in this region from December 2019 to February 2020, although the situation has been alleviated since March 2020. The biological characteristics of the desert locust, along with the historical climatic condition patterns across the study area (part III), were comprehensively analyzed. The results show that locust swarms are likely to be restrained by high mountains, heavy rainfall, dense vegetation and unfavorable soil moisture; thus, have little chance of entering the Indochina Peninsula and Southwest China. In addition, the frequencies of tropical cyclones and depressions in the western Indian Ocean have ﬂuctuated over the past 30 years and showed an increasing trend in recent years, which demonstrated that East Africa may be threatened and affected by severe desert locust outbreaks and upsurges more often in the future.

Author Contributions: Conceptualization, L.W. and S.F.; methodology, S.F.; software, L.W.; formal analysis, L.W.; resources, W.H.; data curation, Z.P. and X.T.; writing—original draft preparation, L.W.; writing—review and editing, S.F.; visualization, W.Z.; supervision, S.F.; funding acquisition, S.F. All authors have read and agreed to the published version of the manuscript. Funding: This research was funded by Ministry of Science and Technology of the People’s Republic of China, grant number 2019YFC1510205. The APC was funded by Chinese Academy of Meteorological Sciences, grand number 2019Z010. Institutional Review Board Statement: Not applicable. Informed Consent Statement: Not applicable. Data Availability Statement: Not applicable. Acknowledgments: This manuscript was supported by the National Key Research and Development Programs of China under Grant 2019YFC1510205 and the Fundamental Research Fund of Chinese Academy of Meteorological Sciences under Grant 2019Z010. Conﬂicts of Interest: The authors declare no conﬂict of interest.

References 1. Middleton, N.J.; Sternberg, T. Climate hazards in drylands: A review. Earth-Sci. Rev. 2013, 126, 48–57. [CrossRef] 2. Zhang, L.; Lecoq, M.; Latchininsky, A.; Hunter, D. Locust and Grasshopper Management. Ann. Rev. Entomol. 2019, 64, 15–34. [CrossRef][PubMed] 3. Arnold, v.H.; Cressman, K.; Magor, J.I. Preventing desert locust plagues: Optimizing management interventions. Entomol. Experiment. Appl. 2007, 122, 191–214. [CrossRef] 4. Madeleine, S. A Plague of Locusts has Descendedon East Africa. Climate Change May Be to Blame. Available online: https: //www.nationalgeographic.com/science/2020/02/locust-plague-climate-science-east-africa/ (accessed on 1 January 2021). 5. Vallebona, C.; Genesio, L.; Crisci, A.; Pasqui, M.; Vecchia, A.D.; Maracchi, G. Large-scale climatic patterns forcing desert locust upsurges in West Africa. Clim. Res. 2008, 37, 35–41. [CrossRef] 6. Wang, B.; Deveson, E.D.; Waters, C.; Spessa, A.; Lawton, D.; Feng, P.; Liu, D.L. Future climate change likely to reduce the Australian plague locust (Chortoicetes terminifera) seasonal outbreaks. Sci. Total. Environ. 2019, 668, 947–957. [CrossRef] 7. Tian, H.; Stige, L.C.; Cazelles, B.; Kausrud, K.L.; Svarverud, R.; Stenseth, N.C.; Zhang, Z. Reconstruction of a 1,910-y-long locust series reveals consistent associations with climate ﬂuctuations in China. Proc. Natl. Acad. Sci. USA 2011, 108, 14521–14526. [CrossRef][PubMed] 8. Meynard, C.N.; Lecoq, M.; Chapuis, M.P.; Piou, C. On the relative role of climate change and management in the current desert locust outbreak in East Africa. Glob. Chang. Biol. 2020, 26, 3753–3755. [CrossRef][PubMed] 9. Tratalos, J.A.; Cheke, R.A.; Healey, R.G.; Stenseth, N.C. Desert locust populations, rainfall and climate change: Insights from phenomenological models using gridded monthly data. Clim. Res. 2010, 43, 229–239. [CrossRef] 10. Veran, S.; Simpson, S.J.; Sword, G.A.; Deveson, E.; Piry, S.; Hins, J.E.; Berthier, K. Modeling spatiotemporal dynamics of outbreaking species: Inﬂuence of environment and migration in a locust. Ecology 2015, 96, 737–748. [CrossRef] Remote Sens. 2021, 13, 680 19 of 19

11. Dinku, T.; Ceccato, P.; Cressman, K.; Connor, S.J. Evaluating Detection Skills of Satellite Rainfall Estimates over Desert Locust Recession Regions. J. Appl. Meteorol. Clim. 2010, 49, 1322–1332. [CrossRef] 12. Gómez, D.; Salvador, P.; Sanz, J.; Casanova, C.; Taratiel, D.; Casanova, J.L. Machine learning approach to locate desert locust breeding areas based on ESA CCI soil moisture. J. Appl. Remote Sens. 2018, 12, 036011. [CrossRef] 13. Escorihuela, M.J.; Merlin, O.; Stefan, V.; Moyano, G.; Eweys, O.A.; Zribi, M.; Kamara, S.; Benahi, A.S.; Ebbe, M.A.B.; Chihrane, J.; et al. SMOS based high resolution soil moisture estimates for desert locust preventive management. Remote Sens. Appl. Soc. Environ. 2018, 11, 140–150. [CrossRef] 14. Piou, C.; Gay, P.-E.; Benahi, A.S.; Ebbe, M.A.O.B.; Chihrane, J.; Ghaout, S.; Cisse, S.; Diakite, F.; Lazar, M.; Cressman, K.; et al. Soil moisture from remote sensing to forecast desert locust presence. J. Appl. Ecol. 2018, 45, 966–975. [CrossRef] 15. Latchininsky, A.V. Locusts and remote sensing: A review. J. Appl. Remote Sens. 2013, 7, 075099. [CrossRef] 16. Hielkema, J.U.; Roffey, J.; Tucker, C.J. Assessment of ecological conditions associated with the 1980/81 desert locust plague upsurge in West Africa using environmental satellite data. Int. J. Remote Sens. 1986, 7, 1609–1622. [CrossRef] 17. Meynard, C.N.; Gay, P.E.; Lecoq, M.; Foucart, A.; Piou, C.; Chapuis, M.P. Climate-driven geographic distribution of the desert locust during recession periods: Subspecies’ niche differentiation and relative risks under scenarios of climate change. Glob. Chang. Biol. 2017, 23, 4739–4749. [CrossRef][PubMed] 18. Symmons, P.M.; Cressman, K. Desert Locust Guidelines; Food Agriculture Organization of the United Nations: Rome, Italy, 2001. 19. Shroder, J.F.; Sivanpillai, R. Biological and Environmental Hazards, Risks, and Disasters; Elsevier: Amsterdam, The Netherlands, 2015; Chapter 4. 20. Roffey, J.; Popov, G. Environmental and Behavioural Processes in a Desert Locust Outbreak. Nature 1968, 219, 446–450. [CrossRef] 21. Pener, M.P.; Simpson, S.J. Locust Phase Polyphenism: An Update. Adv. Insect Physiol. 2009, 36, 1–272. [CrossRef] 22. Kiage, L.M.; Liu, K. Palynological evidence of climate change and land degradation in the Lake Baringo area, Kenya, East Africa, since AD 1650. Palaeogeogr. Palaeoclim. Palaeoecol. 2009, 279, 60–72. [CrossRef] 23. Schneider, U.; Becker, A.; Finger, P.; Meyer-Christoffer, A.; Ziese, M.; Rudolf, B. GPCC’s new land surface precipitation climatology based on quality-controlled in situ data and its role in quantifying the global water cycle. Theor. Appl. Climatol. 2014, 115, 15–40. [CrossRef] 24. Becker, A.; Finger, P.; Meyer-Christoffer, A.; Rudolf, B. A description of the global land-surface precipitation data products of the Global Precipitation Climatology Centre with sample applications including centennial (trend) analysis from 1901 Cpresent. Earth Syst. Sci. Data Discuss. 2013, 5.[CrossRef] 25. Schneider, U.; Becker, A.; Finger, P.; Meyer-Christoffer, A.; Ziese, M. GPCC Full Data Monthly Product Version 2018 at 0.25◦: Monthly Land-Surface Precipitation from Rain-Gauges built on GTS-based and Historical Data. 2018. Available online: https: //www.dante-project.org/datasetPages/gpcc (accessed on 18 April 2019). 26. Ziese, M.; Becker, A.; Finger, P.; Meyer-Christoffer, A.; Rudolf, B.; Schneider, U. GPCC First Guess Product at 1.0◦: Near Real-Time First Guess monthly Land-Surface Precipitation from Rain-Gauges based on SYNOP Data. Available online: https: //opendata.dwd.de/climate_environment/GPCC/html/download_gate.html (accessed on 18 April 2019). 27. Hersbach, H.; Bell, B.; Berrisford, P.; Hirahara, S.; Horanyi, A.; Munoz-Sabater, J.; Nicolas, J.; Peubey, C.; Radu, R.; Schepers, D.; et al. The ERA5 global reanalysis. Q. J. R. Meteorol. Soc. 2020, 1–51. [CrossRef] 28. Sabaghya, S.; Walker, J.P.; Renzullo, L.J.; Jackson, T.J. Spatially enhanced passive microwave derived soil moisture: Capabilities and opportunities. Remote Sens. Environ. 2018, 209, 551–580. [CrossRef] 29. Zhu, Y.; Li, X.; Pearson, S.; Wu, D.; Sun, R.; Johnson, S.; Wheeler, J.; Fang, S. Evaluation of Fengyun-3C soil moisture products using in-Situ data from the Chinese Automatic Soil moisture Observation Stations: A case study in Henan Province, China. Water 2019, 11, 248. [CrossRef] 30. Wang, L.; Fang, S.; Pei, Z.; Zhu, Y.; Dao Nguyen, K.; Han, W. Using FengYun-3C VSM Data and Multivariate Models to Estimate Land Surface Soil Moisture. Remote Sens. 2020, 12, 1038. [CrossRef] 31. Brown, J.F.; Howard, D.; Wylie, B.; Frieze, A.; Ji, L.; Gacke, C. Application-Ready Expedited MODIS Data for Operational Land Surface Monitoring of Vegetation Condition. Remote Sens. 2015, 7, 16226–16240. [CrossRef] 32. Hayakawa, Y.S.; Oguchi, T.; Zhou, L. Comparison of new and existing global digital elevation models: ASTER G-DEM and SRTM-3. Geophys. Res. Lett. 2008, 35.[CrossRef] 33. Danielson, J.; Gesch, D. Global Multi-Resolution Terrain Elevation Data 2010 (GMTED2010); U.S. Geological Survey Open-File Report 2011-1073; US Department of the Interior, US Geological Survey: Washington, DC, USA, 2011; 26p. 34. Easterling, W.E.; Aggarwal, P.K.; Batima, P.; Brander, K.M.; Erda, L.; Howden, S.M.; Kirilenko, A.; Morton, J.; Soussana, J.-F.; Schmidhuber, J.; et al. Food, ﬁbre and forest products. In Climate Change 2007: Impacts, Adaptation and Vulnerability. Contribution of Working Group II to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change; Parry, M.L., Canziani, O.F., Palutikof, J.P., van der Linden, P.J., Hanson, C.E., Eds.; Cambridge University Press: Cambridge, UK, 2007; pp. 273–313.