Science of the Total Environment 647 (2019) 606–618

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Science of the Total Environment

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Detection of illicit sand mining and the associated environmental effects in China's fourth largest freshwater lake using daytime and nighttime satellite images

Hongtao Duan a,⁎, Zhigang Cao a,b, Ming Shen a,b,DongLiua, Qitao Xiao a a Key Laboratory of Watershed Geographic Sciences, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, China b University of Chinese Academy of Sciences, Beijing 100049, China

HIGHLIGHTS GRAPHICAL ABSTRACT

• VIIRS DNB NTL data were used to moni- tor illegal sand mining activities in Lake Hongze. • Nighttime dredging activities were found to have significantly disturbed the lake water. • A method of evaluating the dredging in- tensity was proposed using daytime and nighttime satellite data. • The effectiveness of government poli- cies was scientifically evaluated.

article info abstract

Article history: Illegal sand mining activities are rampant in coastal and inland water around the world and result in increased Received 4 May 2018 water turbidity, reduced water transparency, damage to fish spawning sites and adverse effects on the health Received in revised form 21 July 2018 of aquatic ecosystems. However, many sand dredging vessels hide during the day and work at night, rendering Accepted 25 July 2018 conventional monitoring measures ineffective. In this study, illegal sand dredging activities and the associated Available online 26 July 2018 aquatic environmental effects were investigated in Lake Hongze (the fourth largest freshwater lake in China) Editor: F.M. Tack using both conventional daytime satellite data, including MODIS/Aqua and Landsat TM/ETM data as well as VIIRS Day/Night Band (DNB) nighttime light (NTL) data, the following results were obtained. (1) The Landsat Keywords: data revealed that sand dredging vessels first appeared in February 2012 and their number (monthly average: VIIRS DNB 658) peaked in 2016, and sand dredging stopped after March 2017. (2) The VIIRS NTL data were satisfactory Dredging activities for monitoring nighttime illegal dredging activities, and they more accurately reflected the temporal and spatial Remote sensing distribution characteristics of dredging vessels due to their high frequency. (3) Observations from the MODIS Light data data acquired since 2002 showed three distinct stages of changes in the suspended particulate matter (SPM) con- Lake Hongze centrations of Lake Hongze that were consistent with the temporal distributions of sand dredging vessels. (4) The contribution of dredging vessels to the increases in SPM concentration was quantitatively determined, and night- time sand dredging activities were found to have disturbed the waters more significantly. (5) The effectiveness of government measures implemented at various stages to control illegal sand dredging activities were

⁎ Corresponding author. E-mail address: [email protected] (H. Duan).

https://doi.org/10.1016/j.scitotenv.2018.07.359 0048-9697/© 2018 Elsevier B.V. All rights reserved. H. Duan et al. / Science of the Total Environment 647 (2019) 606–618 607

scientifically evaluated. This study provides technological support for government monitoring and the control of illegal sand dredging activities and can serve as a valuable reference for water bodies similar to Lake Hongze worldwide. © 2018 Elsevier B.V. All rights reserved.

1. Introduction difference vegetation index (NDVI) (Levin, 2017). In addition, satellite NTL data have been used to monitor the gross domestic products: the Sand mining is widespread in most developing and developed coun- total radiance derived from a smoothed annual image exhibited a high tries (Larson, 2018; Padmalal and Maya, 2014) because yellow sand correlation with gross domestic product at the state level (Zhao et al., found in river and lake sediments is used in high-quality building mate- 2017). Thus far, satellite NTL data have rarely been used to monitor ves- rials. However, sand mining activities, particularly uncontrolled sand sels (Kanjir et al., 2018). Satellite NTL data were used to monitor fishing mining activities, pose relatively large threats to the ecological environ- boats (Elvidge et al., 2015b) and the movements of commercial ice- ments of water bodies, the quality of drinking water sources and the breakers in Arctic shipping routes to indirectly estimate ice thicknesses safety of maritime transport and dams. Therefore, both central and along the shipping routes (Straka et al., 2015). In addition, NOAA's Earth local governments in most countries restrict sand mining operations. Observation Group (EOG) has worked since 2014 on algorithms to re- In China, governments at various levels have formulated laws and regu- port the locations of boats detected based on light in global VIIRS DNB lations to prohibit illegal sand mining. However, because sand mining images (https://www.ngdc.noaa.gov/eog/viirs/download_boat.html). generates high profits, illegal sand mining activities are rampant in re- Currently, however, no studies have reported using NTL data to monitor gions such as the Yangtze River Basin, the Yellow River Basin, the sand dredging vessels in inland lakes. Pearl River Basin and the Huaihe River Basin (Lai et al., 2014; Meng Situated in northern Jiangsu Province, China, at the junction of the et al., 2018; Zeng et al., 2018; Zhao et al., 2015). Illegal sand mining ac- middle and lower reaches of the Huaihe River, Lake Hongze (33°06′– tivities are typically covert, mobile and random; therefore, they are dif- 33°40′N, 118°10′–118°52′N) (Fig. 1) is the fourth largest freshwater ficult to detect. Some illegal sand dredging vessels hide during the day lake in China (Wang and Dou, 1998). Lake Hongze is not only a primary and work only at night. Thus, it is difficult for government administra- source of drinking water for nearby cities (e.g., Huai'an) but also an im- tions to enforce the relevant laws. portant hub in the Eastern Route of the South–North Water Transfer Satellite remote sensing is characterized by wide coverage, periodic- Project (SNWTP). The water quality of the lake plays a vital role in the ity and easy data acquisition and can be used to satisfactorily monitor transfer of clean water from the Yangtze River to the North China sand mining activities. Currently, relatively high-resolution (≥30 m) op- Plain. A large amount of high-quality yellow sand was discovered in tical satellite data such as those acquired by the Landsat Multispectral the bed of Lake Hongze in 2012, and this finding was soon followed Scanner (MSS), Thematic Mapper (TM) and Operational Land Imager by the appearance of a large number of sand dredging vessels. These (OLI) series sensors and the charge-coupled device (CCD) cameras on sand dredging activities pose a threat to safe drinking water and dam- board Chinese Huan Jing satellites (HJ-1-A/B) are used to monitor age the original ecological environment of the lake and the lakebed, sand dredging vessels and their activities. Relevant information is pri- resulting in increased turbidity in the lake and the deaths of fish and marily extracted based on the significant differences among sand shrimp (Yan, 2015). More importantly, they also pose a severe threat dredging vessels and their locations in normal water bodies using the to the safety of the dam along the eastern shore of the lake, directly en- near-infrared or shortwave infrared bands (Barnes et al., 2015; Li dangering the safety of the 20 million residents and the productivity of et al., 2014; Wu et al., 2007). Sand dredging vessels are generally the 2000 km2 of farmlands in the five cities downstream of the lake (in- approximately 10–20 m in length; therefore, moderate-resolution cluding Huai'an, Yangzhou and Taizhou). Therefore, illegal sand dredg- (≥250 m) data such as those acquired by the Moderate Resolution Imag- ing constitutes an extensive safety hazard. In fact, the central and local ing Spectroradiometer (MODIS) cannot be directly used to monitor governments have introduced multiple policies intended to control sand dredging vessels. Nevertheless, because sand dredging often re- sand dredging operations. However, no method has been developed sults in significant increases in suspended particulate matter (SPM) to effectively determine whether such policies produce an immediate concentrations in the relevant areas, sand dredging activities and their effect. effects can be indirectly analyzed through observations of turbid plumes In this study, daytime and nighttime multisource satellite data were (Cao et al., 2017; Kutser et al., 2007). Some illegal sand dredging vessels used to analyze sand dredging activities in Lake Hongze, China. The mainly work at night to evade government control; therefore, daytime main objectives were to: (1) use Landsat OLI and VIIRS DNB data to satellite data such as Landsat data are ineffective in identifying such monitor sand dredging vessels around the clock; (2) use Aqua MODIS operations. data to reveal the characteristics of changes in the SPM concentrations During nighttime operation, sand dredging vessels often gather between 2002 and 2017 and analyze the effects of sand dredging activ- closely, forming a well-lit area. This characteristic provides the possibil- ities on lake turbidity; and (3) evaluate the effectiveness of the policies ity for nighttime light (NTL) monitoring based on remote sensing. Satel- implemented to control sand dredging operations. This study has the lite NTL data, including those acquired by the Operational Linescan potential to provide support for monitoring illegal sand dredging activ- System from the first-generation satellite of the Defense Meteorological ities and for scientific lake management worldwide through multi- Satellite Program and those acquired by the Visible Infrared Imaging Ra- source satellite data. diometer Suite Day/Night Band (VIIRS DNB) sensor onboard the Suomi National Polar-orbiting Partnership satellite—a new-generation of NTL 2. Materials and methods image products—have traditionally been used to monitor nighttime city scenes and study the spatial expansion and economic development 2.1. Dredging ships retrieved from VIIRS DNB of cities (Hu et al., 2017; Wang et al., 2017). For example, satellite NTL data were used to study seasonal changes in the nighttime brightness The newest-generation satellite with nighttime light-observing sen- of cities. One study found that monthly changes in nighttime brightness sors, NPP-VIIRS DNB, was successfully launched on October 28, 2011. were positively correlated with monthly changes in snow cover and al- This satellite's increased spatial resolution (15 arc sec, 742 m × 742 m), bedo and negatively correlated with monthly changes in the normalized low light-imaging detection limits (~2 × 10−11 W·cm−2·sr−1)andhigh 608 H. Duan et al. / Science of the Total Environment 647 (2019) 606–618

Fig. 1. Lake Hongze and its location in China: (a) Landsat-8 OLI RGB composite (Bands 4, 3 and 2) image from April 8, 2014. P1, P2 and P3 are traditional sand miningareas(Cao et al., 2017). (b) Landsat-8 OLI SWIR band (Band 7) image from April 8, 2014. The highlighted spots on the water in Zoom1 and Zoom2 represent dredging vessels; (c) Dredging vessels during the day; (d) the location of Lake Hongze (red square) in China; (e) VIIRS DNB raw image from April 8, 2014. Note that the lights in yellow circles mainly represent nearby cities (Hongze County and Xuyi County) and villages according to visual inspection from historical Landsat images and local maps. Because they were not dredging vessels, the data associated were excluded from the study; (f) Lights from dredging vessels during the night. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.) radiometric quantization (14 bit) have resulted in dramatic improve- relatively significantly (Feng et al., 2012; Hu et al., 2010; Zhang et al., ments to observations of nighttime lights on Earth compared to those of 2016). Thus, in the VIIRS DNB images, because the radiance of the area its predecessors. In this paper, 2100 scenes of NPP-VIIRS DNB imagery be- where a sand dredging vessel is located is far higher than that of the tween February 2012 and December 2017 (Table 1) were downloaded lake background (Fig. 2a), there is a relatively large gradient between from the NASA archive web site (https://oceandata.sci.gsfc.nasa.gov/)to the dredging area and the lake background. Values near the maximum investigate the lights from dredging vessels. Before the study, we gradient at the boundary between sand dredging vessels and the established a set of visual data selection criteria that considered the im- water body formed the thresholds for distinguishing sand dredging ves- pact of weather on the data. The following specific criteria for determining sels from the water body. The data processing operation is as follows: invalid data were used. (1) The NTLs from Hongze County were used as a (1) The original VIIRS DNB radiance data were converted to data with reference (Fig. 1e).WhennoNTLsfromthecitycouldbeseeninanimage an order of magnitude of nW/cm2/sr by multiplying them by 109.The of a scene, the image was deemed invalid. (2) When the entire lake region resulting data were then subjected to a log10 transformation to en- appeared white in an image of a scene, the scene in that image was hance the image display (Fig. 2b). (2) An algorithm was used to iden- deemed to be covered by clouds. (3) When Lake Hongze appeared only tify sand dredging vessel areas from the log10-transformed data at the edge of an image, the image data generally had a high noise level (Elvidge et al., 2015a). (3) A gradient transformation was performed and could not be used. After the strict data selections, 716 scenes with on the log10-transformed data, and a gradient image corresponding valid DNB data (listed in Table 1) were adopted in this study. Each to the DNB light data was obtained (Fig. 2c). (4) The radiance in study month included N2 images with valid data. theoriginalradianceimagecorrespondingtothemaximumgradient The VIIRS DNB sensor is capable of detecting bright objects (radi- in the gradient image was determined and used as the threshold for ance: N2nW/cm2/sr) at night (Cao and Bai, 2014). The spatial resolution segregating the area illuminated by sand dredging vessels from the of the VIIRS DNB sensor is far greater than the length of sand dredging water body. Notably, in practice, each gradient image contained vessels (20–40 m). However, sand dredging vessels use powerful lights more than one maximum gradient, and those maximum gradients for illumination during nighttime operations, which causes the nearby were represented by a set of pixels with the same value distributed area within a certain range to be relatively bright (Choi et al., 1997). around the boundary between the lit area and the water body. As a result, the radiance in the dredging area is far higher than that of Thus, the average value of the radiance corresponding to those max- the background (e.g., the water body) in an image (Fig. 1e and f). In imum gradients was used as the threshold for sand dredging pixels. this study, sand dredging vessel areas were identified from the VIIRS (5) The areas affected by city and village lights were removed. Fi- DNB data using a gradient transform-based algorithm that can effec- nally, an image of the sand dredging vessel distribution was obtained tively separate two types of ground objects whose signals differ (Fig. 2d). H. Duan et al. / Science of the Total Environment 647 (2019) 606–618 609

2.2. Dredging vessels retrieved from Landsat data

A total of 134 cloud-free scenes of Landsat TM, ETM+, and OLI data collected between July 2000 and December 2017 (Table 1)were downloaded from the NASA archive web site (https://oceandata.sci. gsfc.nasa.gov/) and used monitor the dredging vessels during the day. The reflectance of dredging ships is high in the Landsat shortwave infra- red (SWIR) band, as indicated by a distinct contrast from the black water body (Fig. 1b). Therefore, the Landsat TM, ETM+ and OLI SWIR band (band 7) can be used to identify dredging vessels during the day. More details are provided in a previous paper (Cao et al., 2017).

2.3. SPM estimated from MODIS/Aqua

A total of 1857 cloud-free scenes of Aqua/MODIS L1A data collected between July 2002 and December 2017 were downloaded from the NASA archive web site (https://oceandata.sci.gsfc.nasa.gov/). The L1B data were generated from the L1A data using SeaDAS 7.3.2 software, indicates no data.

” fi

\ and the most recent updates to the calibration le were used “ (reprocessing version R2014.0; https://oceancolor.gsfc.nasa.gov/cms/

reprocessing). Because precise Rrs values were not retrieved for the long-term data, the Rrc values were derived after correction for Rayleigh tively, and scattering and gaseous absorption effects in the MODIS bands. Based on

the MODIS/Aqua Rrc data, the empirical algorithm proposed by (Cao et al., 2017) was adopted to estimate the SPM concentrations.

3. Results

3.1. Dredging vessels from Landsat

Figs. 3 and 4 show the temporal and spatial distributions of sand dredging vessels identified from the Landsat series data. Based on the Landsat TM data, a large number of sand dredging vessels appeared for the first time in February 2012 in the P2 zone (Figs. 3aand5a). Later, the sand dredging activities gradually expanded, and an increas- ing number of sand dredging vessels appeared. The number of sand dredging vessels increased from a monthly average of 112 in 2012 to a maximum monthly average of 658 in 2016, an annual average increase of 55.69% (Fig. 5a). Sand mining activities also expanded from the initial P2 zone to the entire central region and into the northwest arm of the lake (Fig. 3a–f). Specifically, beginning in the second half of 2014, the P3 zone became the primary dredging zone (Fig. 3c–e). After March 2017, the vessels stopped dredging sand and were berthed together in

that MODIS/Aqua, VIIRS DNB and Landsat are represented by M, V and L, respec the Hanqiao and Jieji areas (Fig. 3f). Seasonally (Fig. 4), significantly fewer sand dredging vessels worked during the summer rainy season (June and July) than during the winter dry season (December, January and February). Note that the Landsat se- ries images generally have a return period of 16 days, and they are sub- ject to relatively strong effects from cloudy and rainy weather (Table 1). Thus, although the Landsat images do not completely reflect the dredg- ing state in Lake Hongze, they can be used to analyze trends.

3.2. Dredging vessels from VIIRS DNB

The VIIRS DNB light image of the first scene of the Lake Hongze re- gion was acquired on March 21, 2012. By December 31, 2017, effective images with a total of 716 scenes had been acquired. Between 2012 and 2013, sand dredging vessels were active in the P2 zone within an area of b150 km2 (Fig. 3a and b). In 2014, lights from sand dredging ves- sels also appeared in the P1 zone and shortly thereafter spread into the P3 zone (Fig. 3c). After 2015, the P3 zone became a second main night- time sand dredging zone in addition to the P2 zone, and the total area of 2

MVLMVLMVLMVLMVLMVLMVLMVLMVLMVLMVLMVL sand mining increased to 177 km (Fig. 3d). Later, the total area of sand mining decreased significantly, to below 90 km2 (Fig. 3e and f). From March 2017 onward, no lights from sand dredging vessels were de- Year Jan20022003 /2004 112005 13 / / Feb2006 10 /2007 10 1 1 /2008 12 / / /2009 7 6 2 /2010 16 11 /2011 / 11 / 8 / Mar 1 /2012 / 13 6 / 12013 / 1 8 6 / 2 / /2014 13 / / / 11 142015 / 16 / 5 / / 11 52016 11 / 6 / / Apr / 8 132017 1 / 11 / / 6 / 16Total 15 13 / 1 2 / / / 3 9 9 / 1 / 175 4 / / 18 12 9 7 / / 1 56 2 8 7 7 9 / 1 1 8 / / 13 May 17 / 7 12 5 / / 13 2 / 114 14 16 1 / 11 1 / 12 1 / 55 1 / 4 9 / 13 / 2 11 2 / 2 11 11 2 14 7 8 / 2 / / 9 13 5 2 12 159 7 / / 10 13 Jun 1 12 64 6 / 17 / 1 16 / / / / / 11 9 / 14 1 18 7 / 6 / 12 / 1 2 12 166 1 / 14 1 2 8 17 1 / 6 66 2 12 1 10 9 13 / Jul / 6 1 / 9 13 16 16 1 / 2 10 / / 4 / / 11 2 154 11 / 2 4 6 10 13 / / 3 1 70 / / 20 / 2 1 / 7 2 / 12 5 13 8 1 / / 11 7 8 1 / 6 / Aug 7 1 96 17 13 1 8 7 / / / 3 / 39 / 1 1 12 3 / 6 11 8 9 8 6 / / 1 1 / / / / 3 / 5 1 1 129 / 7 7 5 / / / 12 1 1 Sep 5 7 / 1 54 8 5 9 1 13 7 5 / / / 9 / 9 1 / / 5 / 14 7 147 / 6 13 / / / 10 / / 1 8 / 13 / / 62 / / 14 15 12 / 4 1 16 10 / 1 / 14 6 10 Oct 12 / 12 8 / 1 / / / 4 14 161 13 / 5 / / 14 / 5 12 / 62 1 1 1 2 / 7 5 / 2 / / 9 1 12 14 11 2 1 10 13 10 15 / 16 1 6 190 / / 1 11 16 / Nov / 12 10 9 14 / / / 52 14 9 12 1 / / / 7 / 13 1 / / / 10 1 1 1 9 10 / 172 13 / 1 9 6 14 1 10 / 2 11 19 9 17 / 62 1 / 12 13 / Dec / 8 8 19 13 9 / 9 / / 16 / 10 / 2 / 194 15 1 7 1 15 / 1 / 1 9 / 1 74 / 10 1 / / 12 14 3 11 8 1 10 2 13 12 / 1 18 1 1 / 7 11 6 / 13 / / 14 / 6 / 10 / 8 / 6 1 6 1 / / / 1 1 15 1 12 / 9 7 1 10 / / 14 1 1 7 / 11 1 1 13 / 13 10 17 / / 1 8 19 1 12 12 13 13 / 8 / 1 / / 15 1 12 / / 1 8 1 1 1 / 13 1

Table 1 Numbers of MODIS/Aqua, VIIRS DNB and Landsat images used in this study. Note tected (Fig. 5b) due to a government policy that cracked down on illegal 610 H. Duan et al. / Science of the Total Environment 647 (2019) 606–618

D E

F  G 

Fig. 2. The identification of dredging regions in the VIIRS DNB (a) Raw SDR image; (b) Log10-transform image; and (c) Gradient image, as well as the (d) Pixels with dredging vessels in Lake Hongze. Note that the areas delineated in yellow circles were not analyzed in this study. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.) dredging. Notably, in addition to the three main sand dredging zones, Seasonally (Fig. 4), the largest lit zones identified from the NTL data sand dredging vessels also appeared sporadically in the south arm of appeared in the winter dry season (November and December) and in the lake. early spring (March), over a total area exceeding 350 km2. In contrast,

Fig. 3. The dredging vessels observed between 2012 and 2017 from VIIRS DNB and Landsat data. Note that the red points represent the dredging vessels observed from Landsat, the gray polygons represent the areas where lights were observed based on VIIRS DNB imagery, and the number indicates the statistical area of all dredging pixels. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.) H. Duan et al. / Science of the Total Environment 647 (2019) 606–618 611

226.81 km2 241.44 km2 354.5 km2

256.63 km2 298.25 km2 227.38 km2

193.63 km2 228.50 km2 212.19 km2

2 277.44 km2 352.25 km2 353.94 km

Fig. 4. Monthly maximum region of dredging pixels (gray polygons) from 2012 to 2017 derived from VIIRS NTL data. The solid circles in different colors represent the dredging vessels from Landsat in different years. Note that the Huai River zone was removed. the lit zones identified from the NTL data were significantly smaller in 3.3. SPM derived from MODIS/Aqua summer when the water level was relatively high (June through Sep- tember), with a total area of b230 km2. Overall, the trend identified Three distinct stages were observed for the annual characteristics from the VIIRS DNB data was consistent with that identified from the of the SPM concentrations in Lake Hongze (Fig. 5c and d). The SPM Landsat data. However, there were some differences between the concentrations were relatively low between 2002 and 2011 (average monthly trends identified from these two types of data. For example, over the entire lake: 22.06 ± 2.87 mg·L−1), increased significantly in the summer rainy months (June through September), because there between 2012 and 2017 (average: 24.34 ± 5.81 mg·L−1)andthen was, on average, less than one period of Landsat data available each began to decrease, approaching pre-2012 levels after March 2017 month (Table 1), the number of sand dredging vessels identified from (average: 20.29 ± 3.53 mg·L−1). Notably, before 2012, the average the Landsat data was small. Comparatively, the VIIRS data were ac- SPM concentration in the sand dredging zones (26.93 ± quired at a high frequency and more accurately reflected the number 4.80 mg·L−1) was not significantly different than (22.08% higher and locations of sand dredging vessels. than) the average SPM concentration for the entire lake. However, 612 H. Duan et al. / Science of the Total Environment 647 (2019) 606–618

   

Fig. 5. Annual monthly dredging vessels observed between 2012 and 2017 from: (a) Landsat data and (b) VIIRS DNB data. Note that Landsat provides the number of dredging vessels, whereas VIIRS DNB only provides the number of pixels with dredging vessels due to the coarse resolution (742 m × 742 m). The month marked on the green line represents the time when the government implemented control measures. (c) Annual monthly SPM concentrations in zones P1, P2, P3 and the entire lake; (d) their means; and (e) annual monthly precipitation and wind speed between 2002 and 2017. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.) during the sand dredging period after 2012, the average SPM con- Fig. 6a–c show the characteristics of the changes in SPM concentra- centration in the sand dredging zones (39.10 ± 11.39 mg·L−1) in- tions in the three zones before and after sand dredging. Overall, the creased significantly and was 60.64% higher than that in the whole SPM concentrations were higher during the sand dredging period be- lake. After March 2017, the average SPM concentration in the sand tween 2012 and 2016 than in the non-sand-dredging period except dredging zones began to decrease (30.24 ± 5.24 mg·L−1)but during the rainy season from June to July. After March 2017, when remained nearly 50% higher than that for the whole lake. In addi- sand dredging stopped, the SPM concentrations decreased significantly tion, during the non-sand-dredging period before 2012, the SPM and recovered to or, in some months, became even lower than the levels concentrations in the P1, P2 and P3 zones were similar; however, from the same period between 2002 and 2011. Seasonally, the SPM con- during the sand dredging period, the average SPM concentration centrations were high in the summer rainy season and low in the winter in the P2 and P3 zones (42.20 ± 11.61 mg·L−1)wassignificantly dry season from 2002 to 2011. However, the SPM concentrations were higher than that in the P1 zone (32.90 ± 7.95 mg·L−1), which significantly higher in winter than in summer, which did not change sig- agrees with the sand dredging vessel distribution data (Fig. 5aand nificantly observed for the period of 2012–2016. The SPM concentra- b). tions remained high in January and February 2017 but decreased after H. Duan et al. / Science of the Total Environment 647 (2019) 606–618 613

Fig. 6. Monthly SPM variations in different dredging periods between 2002 and 2017 from: (a) P1; (b) P2; and (c) P3. (d) Monthly precipitation (solid lines) and wind speed (dashed lines) in three dredging periods.

March 2017 when sand dredging stopped. Subsequently, the annual berthed in the sand dredging zones. This result likely occurred because trend of the SPM concentration in 2017 reverted to that during combined governmental forces guarded the inactive sand dredging ves- 2002–2011 (i.e., the SPM concentrations were high in summer sels starting in March 2017. All the sand dredging vessels were removed and low in winter). Note that the main environmental factors from the lake after July and August 2017. (e.g., precipitation and wind speed) that influenced the SPM con- centrations were generally consistent and did not change signifi- 4. Discussion cantly during the three periods (Fig. 6d). 4.1. Effects of dredging activities on SPM 3.4. Relationships between Landsat/VIIRS vessels and MODIS SPM Sand mining activities affect the temporal and spatial distribu- Sand dredging in Lake Hongze can be divided into three stages, tions of SPM concentrations because dredging operation discharge namely, before 2011 (no sand dredging), between 2012 and February large amounts of bottom sediment to the water around a sand dredg- 2017 (large-scale sand dredging) and after March 2017 (termination ing vessel after being dredged and filtered during the dredging pro- of sand dredging activities). Fig. 7 shows the SPM concentrations cess. This process significantly increases the SPM concentration (Fig. 7a–c), the daytime spatial distributions of sand dredging vessels throughout the entire sand dredging zone. In Lake Hongze, sand (Fig. 7d–f) and the nighttime spatial distributions of lights from sand dredging activities have two impacts (Cao et al., 2017). After 2012, dredging vessels (Fig. 7g–i) during these three periods. Overall, the the sand dredging activities resulted in a 21.07% increase in the aver- SPM concentrations increased in the sand dredging zones and the cen- age SPM concentration. Under normal water level (12.5 m) condi- tral region of the lake as the sand dredging vessels appeared and then tions, the sand dredging activities contributed to approximately increased significantly starting in 2012. After March 2017, when sand 3.04 billion m3 of sediment. In addition, sand dredging activities dredging stopped, the SPM concentrations began to decrease but led to changes in the seasonal characteristics of SPM concentrations. remained higher than during the non-sand-dredging period before Before sand dredging activities started, the SPM concentrations were 2012. In addition, sand dredging vessels were distributed within the high in summer and low in winter, but after sand dredging activities same general area during the day and at night during the sand dredging began, the SPM concentrations became high in winter and low in period. After March 2017, the VIIRS DNB data show no more lights in the summer. This result mainly occurred because the water level is nor- sand dredging zones, and the Landsat data show sand dredging vessels mally low during winter, which is conducive to the operation of sand 614 H. Duan et al. / Science of the Total Environment 647 (2019) 606–618

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Fig. 7. (a–c) the average SPM concentrations derived from MODIS Aqua; the frequency of dredging vessels derived from (d–f) Landsat and (g–i) VIIRS NTL data from 2002 to 2011, 2012–02/28/2017 and 03/01/2017–12/31/2017, respectively. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.) dredging vessels. As a result, the SPM concentrations increased and b show the number of sand dredging vessels and the increase in significantly in winter. In comparison, in summer (June), the opera- the SPM concentration derived from the Landsat and VIIRS data, respec- tion of sand dredging vessels was mainly affected by precipitation, tively. The number of sand dredging vessels derived from the Landsat and the SPM concentrations did not change significantly. The SPM data is weakly positively correlated to the increase in the SPM concen- concentrations were similar during the rainy season in both sand tration. The results obtained from the Landsat data also show that a sin- dredging and non-sand-dredging years (Fig. 6). As a result, the SPM gle sand dredging vessel can increase the SPM concentration by concentrations became significantly higher in winter than in approximately 12.82 mg/L and that the maximum number (400) of summer. sand dredging vessels increased the SPM concentration by approxi- Sand dredging vessels undeniably caused the waters of Lake Hongze mately 17.73 mg/L (Fig. 8a). Because an accurate corresponding rela- to become more turbid. However, is it possible to estimate the specific tionship between the VIIRS light data and the number of sand roles of the sand dredging vessels? In this study, the effects of natural dredging vessels could not be established, pixels were used as the unit factors on the SPM concentrations were assumed to have remained for statistical analysis. The results show that a single pixel is related to the same between 2002 and 2016. The monthly average SPM concen- a 16.29-mg/L increase in the SPM concentration, and the maximum trations in the period of 2002–2011, when no sand dredging activities number of pixels found (10) were related to a 12.79-mg/L increase in occurred, were used as the baseline, and the differences in the monthly the SPM concentration. The number of pixels is weakly negatively re- average SPM concentration between the periods of 2012–2016 and lated to the increase in the SPM concentration (Fig. 8b). Thus, both the 2002–2011 were considered to have been caused by sand dredging ves- number of sand dredging vessels derived from the Landsat data and sels. By conducting a regression of these differences considering the the number of pixels determined from the VIIRS light data are only number of sand dredging vessels in each month, the approximate ef- weakly correlated to the increase in the SPM concentration (r b 0.2, p fects of sand dredging vessels on the SPM were determined. Fig. 8a b 0.5). This result indicates that the process by which the number of H. Duan et al. / Science of the Total Environment 647 (2019) 606–618 615

Fig. 8. Relationships between monthly SPM variations (ΔSPM) and (a) the number of dredging vessels per month derived from Landsat and (b) the number of dredging vessels per month derived from VIIRS. Note that the units of Landsat and VIIRS data are the numbers of vessels and pixels, respectively. sand dredging vessels affects the increase in the SPM concentration is average SPM concentration at night when no dredging activities oc- complex and that a larger number of sand dredging vessels does not curred was the lowest—2.53 mg/L less than that during the day when necessarily result in a higher SPM concentration in the lake. Notably, there were no sand dredging vessels. This result occurred for two rea- sand dredging vessels often operate in clusters; therefore, simple linear sons. On one hand, because there were stronger winds and higher superposition is inaccurate. In addition, the assumption that the effects waves at night, dredging activities disturbed the waters at night more of natural factors on the turbidity of the waters remained the same be- intensively than during the day. Additionally, at night, the water distur- tween different months is inaccurate. Although the regular patterns of bance subsided immediately after sand dredging activities stopped. On precipitation and wind speed were generally the same before and the other hand, when there were lights at night, there must have been after 2012 (Figs. 5eand6d), some differences remained at the monthly sand dredging activities; when there were no lights at night and no level. Therefore, using the monthly data from the period of 2002–2011 sand dredging activities when the weather was fine (cloudy and as the baseline values to determine the relationship between the num- rainy-day images were removed from the data used in this study prior ber of sand dredging vessels and the increase in the SPM concentration to analysis), a government crackdown was likely underway. During a is a simplistic approach. Although there is uncertainty in this method, it crackdown, there might or might not have been sand dredging vessels suffices to provide a preliminary reference when no better alternative during the day, but in either case, there were no dredging activities exists. after March 2017 (Fig. 5a–c). Therefore, the observation of lights from Because daytime and nighttime dredging activities have different ef- sand dredging vessels at night can, to some extent, be used to character- fects on water turbidity, can we quantitatively distinguish the difference ize the intensity of sand dredging and their effects on water turbidity between them? Table 2 summarizes the months with and without sand levels. dredging activities determined from the VIIRS DNB and Landsat data. The average SPM concentration in the water at night when dredging 4.2. Effect of policy on dredging activities was active were highest and exceeded the concentration during the day by 1.12 mg/L when sand dredging vessels were present. The Sand dredging activities led to a significant increase in water turbid- ity, reduced the water transparency, damaged fish spawning sites and posed a serious threat to the safety of the ecological environment of Table 2 SPM concentrations during dredging and non-dredging months between 2012 and 2016. Lake Hongze. The local government clearly realized this problem and Note that the units for VIIRS, Landsat and SPM are number of dredging pixels, number of implemented policies to restrict such activities. The implementations dredging vessels and mg/L, respectively. of policies and crackdown efforts (Fig. 5a and b) occurred in three

Zones P1 P2 P3 stages. In stage 1, which began as early as August 14, 2014, upon receiv- ing approval from the Jiangsu provincial government, the Jiangsu Pro- VIIRS SPM VIIRS SPM VIIRS SPM vincial Water Resources Department, Transportation Department, Vessels 1.64 35.10 3.73 43.62 2.99 42.94 Public Security Department and Ocean and Fisheries Bureau jointly is- Non-vessels 29.50 36.74 37.75 sued a Notice and an Announcement prohibiting sand dredging in the Zones P1 P2 P3 waters of Lake Hongze and required all current sand dredging vessels to depart from the waters of Lake Hongze or to dismantle their sand Landsat SPM Landsat SPM Landsat SPM dredging equipment. Due to the lack of Landsat data from August and Vessels 79.75 34.96 149.58 42.01 133.56 41.32 September 2014, the situation during the day in those two months re- Non-vessels 30.67 40.81 40.11 mains unknown. However, the available Landsat data show that sand 616 H. Duan et al. / Science of the Total Environment 647 (2019) 606–618 dredging vessels (b100) continued to appear sporadically from October impounded, illegal sand dredging equipment was destroyed, and fines through December 2014, mainly in the P3 zone (Fig. 5a). Later, between were imposed. Regarding the effectiveness of these measures, the inten- January and February 2015, no sand dredging vessels were detected. sities of daytime and nighttime illegal sand dredging both decreased to However, beginning in March 2015, many dredging vessels were some extent; however, illegal sand dredging activities were still not again observed in the Landsat data. In contrast, the VIIRS DNB data completely eradicated. (Fig. 5b) show that there was no reduction in sand dredging activities In stage 3, with the completion of the first phase of the Eastern Route after August 2014 compared to the same period before August 2014. of the SNWTP and the start of the comprehensive water transfer opera- Moreover, September and October of 2014 were among the months in tion, the strategic position of Lake Hongze increased its importance as a which lights from dredging vessels at night were the brightest since water passage. In 2017, the “Sharp Sword 2017” plan was launched to 2012. One multi-ton illegal sand dredging vessel can bring in crack down on illegal sand dredging in Lake Hongze, and a long-term 20,000–30,000 yuan of net profits in 10 h. Thus, sand dredging can mechanism to prohibit sand dredging in Lake Hongze was established generate enormous profits within a short period of time. Therefore, and subsequently refined. All the illegal sand dredging vessels in the although law enforcement officials from various administrative depart- Lake Hongze region were registered for management and berthed to- ments conducted multiple crackdown operations, illegal sand dredging gether, and the sand dredging equipment on those vessels was re- activities always resurged. These illegal sand dredging vessels often moved. In addition, some offenders were arrested and sentenced. cruised on the lake during the day, awaiting opportunities to dredge Those efforts had a significant deterrent effect. Beginning in March sand at night without restraints. In May 2015, the Jiangsu Provincial 2017, large-scale sand dredging activities ceased, as validated by both Water Resources Department again convened a meeting to determine the Landsat and VIIRS DNB light data. measures to control sand dredging activities in Lake Hongze during Based on the Landsat and VIIRS daytime and nighttime data for sand the flood season. This meeting resulted in the launch of the “Sharp dredging vessels, to facilitate management by government agencies, we Sword 2015” plan, with the aim of cracking down on illegal sand dredg- designed an intensity monitoring method to determine the severity of ing activities in Lake Hongze. These measures were remarkably effective sand dredging activities and whether those activities had a relatively during the day; May 2015 exhibited a significant decrease in the num- large impact on water turbidity. In this approach, the intensity of sand ber of sand dredging vessels during the day. However, at night, Lake dredging activities is classified into four levels: high-intensity (when Hongze was still brightly lit, and there was no reduction in the scale of sand dredging vessels are operating both at night and during the day), illegal sand dredging. In fact, July 2015 was the month in which the larg- medium-intensity (when sand dredging vessels are operating at night est dredging areas appeared on all nights. In August 2015, sand dredging but not during the day), low-intensity (when sand dredging vessels vessels reappeared during the day, reaching nearly 400 vessels in the are operating during the day but not at night) and zero-intensity three main dredging zones. During this stage, the local government (when no sand dredging vessels are operating either during the day or did not introduce additional laws and regulations but instead chose to at night). By classifying the sand dredging activities in each month, patrol Lake Hongze during the day. The patrollers often only warned the average SPM concentrations when there were high-intensity, dredging vessels found on Lake Hongze to refrain from dredging or par- medium-intensity, low-intensity and no sand dredging activities were tially dismantled their dredging equipment. The crackdown efforts con- determined (41.67, 41.12, 34.23 and 33.03 mg/L, respectively). To a cer- tinued for less than two months, and as soon as the patrols diminished, tain extent, these results indicate that the classification is scientifically illegal dredging activities resurged at an increased intensity. Moreover, reasonable and can be used to characterize the intensity of sand dredg- daytime patrolling was ineffective in deterring illegal nighttime ing. Table 3 summarizes the evaluation of the monthly intensities of dredging. sand dredging in the three main sand dredging zones (P1, P2 and P3) In stage 2, the severity of sand dredging in Lake Hongze garnered from 2012 to 2017 using the above-mentioned classification method. considerable attention from China's central government. On August 9, Spatially, the highest intensity sand dredging activities occurred in the 2015, the Ministry of Water Resources, the Ministry of Land and Re- P2 zone, where high-risk months accounted for 61.54% of all the months sources, the Ministry of Transport of China as and the People's Govern- investigated. The months with low-intensity sand dredging activities ments of Jiangsu Province and Shandong Province jointly issued a notice accounted for only 20.51% of all the months, the lowest of the three completely prohibiting sand dredging activities in Lake Hongze and zones. On an interannual scale, starting in 2012, the intensity of sand Luoma Lake to Nansi Lake along the main water transport line of the dredging gradually began to increase. The proportion of months with Eastern Route of the SNWTP (No. 316 (2015) of the Ministry of Water high-intensity sand dredging activities increased from b1/3in2012to Resources) and implemented a responsibility system for administrative over 50% (52.38%) in 2014, peaked at over 80% between 2015 and leaders. Subsequently, the local government introduced laws and regu- 2016, and fell to below 20% in 2017. On an intermonthly scale, in all lations and undertook unprecedented efforts to control illegal dredging. three zones, January and February were the months with the highest- For example, in 2015, N800 patrols were conducted, over 120 crack- intensity sand dredging activities: the high-risk proportion exceeded down operations were organized, over 2200 units of sand dredging 70%. January and February comprise the winter low water level season, equipment were destroyed, and fines of over 7 million yuan were im- and low water levels are conducive to sand dredging. In contrast, June posed. In 2016, over 90 joint law enforcement operations were con- and July exhibited relatively few high-intensity sand dredging activities ducted, involving over 6000 personnel, over 750 vessels and 230 because these months constitute the summer rainy season, during vehicles were dispatched for law enforcement, 63 charges of illegal which neither the weather nor the water levels are favorable for sand sand dredging were filed, 15 sand dredging vessels were impounded, dredging. The relatively limited amount of available data for the rainy fines of over 4.5 million yuan were imposed, and over 4000 units of ille- season might have resulted in an underestimation. gal sand dredging equipment were destroyed. In over two years, a total Currently, illegal sand dredging activities in Lake Hongze are largely of 369 cases were filed, and 165 illegal sand dredging vessels were under control. Although sporadic illegal sand dredging activities have impounded. Fig. 5a and c also show that beginning in September been reported by the media and observed during field inspections, no 2015, the number of sand dredging vessels began to decrease. Specifi- large-scale illegal sand dredging activities have been noted in the re- cally, the abundance of NTLs in the data decreased significantly, mote sensing imagery, indicating that the current policies are highly ef- reflecting the increase in nighttime patrol efforts. However, illegal fective. However, greed and the pursuit of profits should never be sand dredging activities returned to their previous levels after Decem- underestimated or neglected. Based on previous experience, as soon ber. During this stage, the local government introduced laws and regu- as policies or law enforcement efforts are relaxed, there may be a resur- lations, implemented unprecedented control efforts and increased gence of illegal sand dredging activities, particularly at night. Therefore, nighttime patrols. Sand dredging vessels found in the lake were we believe that using satellite (e.g., Landsat and VIIRS) remote sensing H. Duan et al. / Science of the Total Environment 647 (2019) 606–618 617

Table 3 Dredging intensity levels in three zones of Lake Hongze established from Landsat and VIIRS observations between 2012 and 2017. Note that blue indicates zero-intensity (no vessels during the day or night), green indicates low-intensity (only vessels during the day), yellow indicates medium-intensity (only vessels during the night), red indicates high-intensity (vessels dur- ing the day and night), and white indicates insufficient available Landsat or VIIRS data.

Month Zone Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Year 2012 \ \ \ \ \ \ 2013 \ \ \ \ \ \ \ 2014 \ \ \ \ \ P1 2015 \ \ \ \ \ \ 2016 \ \ \ \ \ 2017 \ \ \ \

2012 \ \ \ \ \ \ 2013 \ \ \ \ \ \ \ 2014 \ \ \ \ \ P2 2015 \ \ \ \ \ \ 2016 \ \ \ \ \ 2017 \ \ \ \

2012 \ \ \ \ \ \ 2013 \ \ \ \ \ \ \ 2014 \ \ \ \ \ P3 2015 \ \ \ \ \ \ 2016 \ \ \ \ \ 2017 \ \ \ \

imagery in conjunction with the risk assessment method established in the sand mining zones were still brightly lit at night. Fig. 9 shows a dis- this study can provide scientific and technological support for the gov- tribution map of lakes in China with sizes N1km2 (Ma et al., 2010; Ma ernment to better detect and manage illegal sand dredging activities. et al., 2011) superimposed with synthetic VIIRS DNB light data from 2015. As illustrated in Fig. 9, illegal sand dredging activities are prevalent 4.3. Application to other lakes at night. Of the five largest freshwater lakes in China, illegal sand dredg- ing activities are prevalent in Poyang Lake and Dongting Lake as well as Businesses involved in sand dredging from water bodies such as riv- Lake Hongze. Moreover, Lake Luoma, a lake near Lake Hongze, was also ers, lakes and coastal waters provide large amounts of yellow sand re- significantly affected by illegal sand dredging activities. In fact, illegal quired for construction; such operations are ubiquitous in various sand dredging activities not only occur in lakes on the Jianghuai Plain countries across the world (Barnes et al., 2015; Kutser et al., 2007; but, according to media reports, also occur in a number of large rivers, Padmalal and Maya, 2014; Wu et al., 2007). However, disorderly and il- including the Yangtze River, the Pearl River and the Songhua River. legal sand dredging activities can significantly damage water bodies Therefore, we believe that remote sensing, particularly light remote (e.g., increase their turbidity, reduce their transparency, reduce their sensing, will play a significant role in future management efforts. primary productivity, damage their benthic environment and damage fish spawning sites). In addition, disturbances caused by sand dredging 5. Conclusions pose a threat to the safety of maritime transport and can even cause some dams and lakeshores to collapse, thereby posing a considerable Sand mining activities are rampant around the world and signifi- threat to the safety of downstream cities. Therefore, governments cantly affect the water quality of water bodies, the health of the associ- around the world strictly prohibit illegal sand dredging activities and ated ecosystems and the safety of adjacent dams. In this study, based on hope to improve the monitoring of sand dredging vessels and their the characteristics of illegal sand dredging vessels, which often hide activities. during the day and work at night, VIIRS DNB light data were used to Conventional daytime satellite remote sensing provides a conve- monitor the nighttime operations of illegal sand dredging vessels. The nient method for long-term, periodic monitoring of sand mining activi- results exhibited good agreement with those obtained using daytime ties over large areas, saves a tremendous amount of manpower and, in Landsat series data. Because the VIIRS satellite has a short revisit time, particular, plays an irreplaceable role in better understanding the tem- the VIIRS DNB data better represent the temporal and spatial distribu- poral and spatial distribution patterns and effects of sand mining activi- tion characteristics of sand dredging vessels. In addition, based on the ties (Cao et al., 2017). However, hiding during the day and mining at SPM concentration data acquired by the Aqua MODIS sensor, sand night is a common approach by which illegal sand miners evade restric- dredging operations were found to have a significant impact on water tions, and this strategy cannot be detected based on conventional day- turbidity. Specifically, nighttime sand dredging activities significantly time satellite monitoring. Lake Hongze is a typical example. The disturbed the lake water. Moreover, the study scientifically evaluated government continuously introduced policies to crack down on illegal the effectiveness of government policies, and proposed a method of sand dredging. Although sand dredging vessels no longer appeared dur- evaluating the intensity of sand dredging based on both daytime and ing the day on Lake Hongze due to the implementation of these policies, nighttime remote sensing data. This method has potential for 618 H. Duan et al. / Science of the Total Environment 647 (2019) 606–618

Fig. 9. The dredging vessel pixels observed from VIIRS NTL data on Chinese lakes. Note that the distribution of lights in the central channel of Lake Poyang and Lake Dongting. The lake borders are from Ma et al. (2011). widespread use in various fields. This study, for the first time, used NTL Kanjir, U., Greidanus, H., Oštir, K., 2018. Vessel detection and classification from spaceborne optical images: a literature survey. Remote Sens. Environ. 207, 1–26. data to investigate illegal sand dredging vessels and applied a combina- Kutser, T., Metsamaa, L., Vahtmäe, E., Aps, R., 2007. Operative monitoring of the extent of tion of various types of remote sensing data to evaluate the intensity dredging plumes in coastal ecosystems using MODIS satellite imagery. J. Coast. Res. and environmental effects of sand dredging. 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