DOCSLIB.ORG

Statistical Model and Estimation of Inland Riverine Turbidity with Landsat 8 OLI Images: a Case Study

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Statistical Model and Estimation of Inland Riverine Turbidity with Landsat 8 OLI Images: a Case Study ENVIRONMENTAL ENGINEERING SCIENCE ORIGINAL ARTICLE Volume 00, Number 00, 2017 ª Mary Ann Liebert, Inc. DOI: 10.1089/ees.2016.0540 Statistical Model and Estimation of Inland Riverine Turbidity with Landsat 8 OLI Images: A Case Study Xin Shen1–3 and Qi Feng,4,5,* 1State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan, China. 2Collaborative Innovation Center of Geospatial Technology, Wuhan, China. 3School of Resources and Environmental Sciences, Wuhan University, Wuhan, China. 4Institute of Geodesy and Geophysics, Chinese Academy of Sciences, Wuhan, China. 5Key Laboratory for Environment and Disaster Monitoring and Evaluation, Hubei, China. Received: October 27, 2016 Accepted in revised form: May 25, 2017 Abstract The Landsat 8 Operational Land Imager (OLI) was investigated for its performance in monitoring dynamic riverine surface water turbidity. China’s Hanjiang River, the largest tributary of the Yangtze River, was used as a case study. Field surveys conducted between April 2013 and January 2014 show a wide range of turbidity (15.8–130.2 nephelometric turbidity units). A practical exponential retrieval algorithm used in conjunction with OLI bands on Landsat 8 was developed to assess compatibility between satellite remote sensing reflectance and in situ measured data. Results obtained for the study area accurately match in situ data at most stations (R2 > 0.90) for the validation phase. It was found that Landsat 8 OLI imagery can be used to estimate turbidity in inland riverine systems when a suitable retrieval algorithm is applied. In addition, algal blooms in the riverine system can be detected by OLI imagery. Keywords: algae bloom; Landsat 8; Hanjiang River; riverine systems; turbidity Introduction with high spectral resolution and sensitivity, which makes them suitable for studies of some inland water bodies such as urbidity (Tur) is considered a key water quality vari- large lakes or reservoirs (Shi et al., 2014, 2015; Zhang et al., able due to its impact on light suppression, biochemical T 2016a), their spatial resolution is typically too coarse to ad- oxygen demand, sediment-associated contaminant transport, equately investigate riverine features, making them unsuit- and suspended sediment loads, which affect organisms and able for monitoring water quality variations in these systems inland riverine habitats (Lawler et al., 2006; Davies-Colley (Ghabavati et al., 2008; Onderka and Peka´rova´, 2008; Yu et al., 2011; Jones et al., 2012). Owing to unique optical et al., 2012). properties of turbidity, this parameter can be estimated from Landsat sensors, such as the Landsat 5 (Thematic Mapper) remotely sensed data, thus achieving wide spatial and tem- and Landsat 7 (Enhanced Thematic Mapper Plus), may have poral coverage compared with traditional sampling methods longer revisit times and lower spectral and radiometric res- (Simis et al., 2007; Guttler et al., 2013). olution than ocean-specific instruments, but possess higher Well-established algorithms for recurrent ocean sensor spatial resolution. Accordingly, those sensors have been used monitoring of turbidity exist, employing reflectance in the for inland water studies (Vincent et al., 2004; Ma et al., blue and green color regions of oceans (Gordon and Franz, Onderka and Peka´rova´, 2008; Kuster, 2012). 2008; Neukermans et al., 2012). However, these algorithms After the retirement of Landsat 5, the failure of Landsat 6, may not be appropriate for inland water systems such as and limitations with Landsat 7, the Landsat 8 satellite was rivers due to differing optical properties of sea water bodies Downloaded by University of Connecticut e-journal package NERL from online.liebertpub.com at 07/05/17. For personal use only. launched on February 11, 2013, and operations began on May (Le et al., 2011; Yacobi et al., 2011; Li et al., 2012). Al- 30 of the same year. With its nine bands, Landsat 8 imagery though some ocean color sensors possess short revisit times provides sufficient spatial resolution, in which features such as islands within rivers and bridges spanning rivers can be easily distinguished as highly reflective structures before a *Corresponding author: Key Laboratory for Environment and Disaster Monitoring and Evaluation, Hubei, China. Phone: +86- dark background (Vanhellemont and Ruddick, 2014). Com- 027-6888-1075; Fax: +86-027-6888-1362; E-mail: fengqi@asch pared with previous Landsat missions, Landsat 8 also offers .whigg.ac.cn higher signal-to-noise ratios. This is primarily the result of 1 2 SHEN AND FENG longer integration times associated with the push broom readily available imagery from Landsat 8 together with scanner as well as improved quantization (NASA, 2016; published literature to assess water turbidity changes in the USGS, 2016). Because of inclusion of the Operational Land inland riverine system. Imager (OLI), Landsat 8 has the potential to become the first Landsat sensor with the radiometric resolution necessary for Study Area and Data Processing retrieval of chlorophyll and suspended material constituents Study area in oceans and lakes (Gerace et al., 2013; Pahlevan and Schott, 2013; Wu et al., 2015; Zhang et al., 2016b). However, few The Hanjiang River (historically called the Hanshui River) studies have applied Landsat 8 images to retrieve riverine is a major tributary of the Yangtze River and has a total length water quality parameters. of 1,577 km. The river originates in the mountainous region Rapid economic development and anthropogenic activity of southwestern Shaanxi and flows eastward across the in and around Hanjiang River have increased ecological southern expanse of the province. The Qin Mountains are pressure on its water quality, which is of great environ- north of the mouth of the river. Further north is the Wei River, mental importance to Hubei Province (Liu and Yu, 1992; the largest tributary of the Yellow River, which forms the Wang et al., 2004; Guo et al., 2014). In addition, the Dan- southern boundary of the Ordos Loop. The Daba Mountains to jiangkou Dam, which is on the upstream of the Hanjiang the south of the river act as a natural boundary that separates River and was originally constructed in 1958, has since Shaanxi Province from Sichuan Province and Chongqing City. been raised, and the Danjiangkou Reservoir, created by the The river flows southeastward through Hubei Province, construction of Danjiangkou Dam, has been used as part of connecting with the Yangtze River at Wuhan, the provincial the South-to-North Water Diversion Project (SNWDP) since capital. 2014. Research has shown the probability that algal blooms In the study area (Fig. 1), the main cities along the Han- will increase in the mid-downstream region of the Hanjiang jiang River are Qianjiang City (population 1.1 million) to the River after completion of the SNWDP (Xie et al., 2004). west and Xiantao City (population 1.2 million) to the east. Therefore, comprehensive monitoring is needed to address Both cities are located in the mid-downstream region of changes in water quality in this area. Accordingly, the ob- Hanjiang River. The area belongs to the subtropical monsoon jectives of this study are to apply and evaluate the use of climate zone, with mild climate characterized by four distinct Downloaded by University of Connecticut e-journal package NERL from online.liebertpub.com at 07/05/17. For personal use only. FIG. 1. Mosaic map made with Landsat 8 image (Red: 630–680 nm, Green: 525–600 nm, Blue: 450–515 nm) collected on June 13, 2013, showing the study area and location of Hanjiang River in China. Yellow points represent the data of 15 samples for modeling of each image. Yellow cross represents the data of 5 samples for validation of each image. RIVERINE TURBIDITY MONITORING BY LANDSAT 8 3 Table 1. Description of In Situ Turbidity Within Study Area Sampling Turbidity Mean Standard Sampling date number Sampling time range (NTU) value (NTU) deviation (NTU) April 26, 2013 20 02:46UTC–05:39UTC 20.8–49.7 32.3 7.10 June 13, 2013 20 01:52UTC–05:06UTC 39.3–54.4 47.5 4.66 November 20, 2013 20 02:44UTC–06:04UTC 15.8–25.9 20.3 2.62 January 23, 2014 20 01:45UTC–04:56UTC 47.2–130.2 75.5 29.15 NTU, nephelometric turbidity units. seasons, abundant rainfall, a long (256 days) frost-free pe- at 30-m spatial resolution, and one panchromatic channel at riod, 2002.6 annual average sunshine hours, and an average 15-m spatial resolution. Five good-quality Level 1T OLI annual temperature of 16.3°C. The division into seasons is images were obtained from the U.S. Geological Survey based on an average temperature below 10°C during winter, a (USGS) website (http://earthexplorer.usgs gov). The images temperature above 22°C during summer, and temperatures covering the area downstream of the Hanjiang River were between 10°C and 22°C during spring and autumn. Spring examined in detail (Table 2). With reference to some pub- lasts from roughly mid-March to mid-May (about 70 days), lished literatures (Shi et al., 2015; Zhang et al., 2016b), tur- summer from late May to mid-September (about 120 days), bidity was investigated using OLI band 1 (433–453 nm, autumn from late September to mid-November (about which was not featured on previous Landsat satellites), band 65 days), and winter from late November to early March 2 (450–515 nm), band 3 (525–600 nm), band 4 (630–680 nm), (about 110 days). In the study area, the southern part of the and band 5 (845–885 nm). Hanjiang River is characterized by industrial installations, including auto part, pharmaceutical, chemical, electronic, and nonwoven fabric factories, while the northern part of the Data preprocessing of OLI imagery river is mainly characterized by aquaculture and farming. Standard Landsat 8 OLI images consist of quantized, ca- librated, and scaled digital numbers (DNs) representing Field survey data multispectral image data, which are delivered in 16-bit un- Four field surveys were conducted in the study area be- signed integer format.
Load more

Recommended publications
  • Ecosystem Services Changes Between 2000 and 2015 in the Loess Plateau, China: a Response to Ecological Restoration
    RESEARCH ARTICLE Ecosystem services changes between 2000 and 2015 in the Loess Plateau, China: A response to ecological restoration Dan Wu1, Changxin Zou1, Wei Cao2*, Tong Xiao3, Guoli Gong4 1 Nanjing Institute of Environmental Sciences, Ministry of Environmental Protection, Nanjing, China, 2 Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing, China, 3 Satellite Environment Center, Ministry of Environmental Protection, Beijing, China, 4 Shanxi Academy of Environmental Planning, Taiyuan, China a1111111111 a1111111111 * [email protected] a1111111111 a1111111111 a1111111111 Abstract The Loess Plateau of China is one of the most severe soil and water loss areas in the world. Since 1999, the Grain to Green Program (GTGP) has been implemented in the region. This OPEN ACCESS study aimed to analyze spatial and temporal variations of ecosystem services from 2000 to Citation: Wu D, Zou C, Cao W, Xiao T, Gong G 2015 to assess the effects of the GTGP, including carbon sequestration, water regulation, (2019) Ecosystem services changes between 2000 soil conservation and sand fixation. During the study period, the area of forest land and and 2015 in the Loess Plateau, China: A response grassland significantly expanded, while the area of farmland decreased sharply. Ecosystem to ecological restoration. PLoS ONE 14(1): services showed an overall improvement with localized deterioration. Carbon sequestration, e0209483. https://doi.org/10.1371/journal. pone.0209483 water regulation and soil conservation increased substantially. Sand fixation showed a decreasing trend mainly because of decreased wind speeds. There were synergies Editor: Debjani Sihi, Oak Ridge National Laboratory, UNITED STATES between carbon sequestration and water regulation, and tradeoffs between soil conserva- tion and sand fixation.
    [Show full text]
  • (Leech, 1890) (Lepidoptera: Hesperiidae) with Description of Female Genitalia and Taxonomic Notes
    © Entomologica Fennica. 31 August 2016 Distribution of Onryza maga (Leech, 1890) (Lepidoptera: Hesperiidae) with description of female genitalia and taxonomic notes Guoxi Xue, Yufei Li, Zihao Liu, Meng Li & Yingdang Ren Xue, G. X., Li, Y.F., Liu, Z. H., Li, M. & Ren, Y.D. 2016: Distribution of Onryza maga (Leech, 1890) (Lepidoptera: Hesperiidae) with description of female geni- talia and taxonomic notes. — Entomol. Fennica 27: 70–76. For more than twenty years, Hainan, Vietnam, Myanmar, Thailand, Malaysia, Singapore and Indonesia have been erroneously reported in Chinese literature as belonging to the distribution range of Onryza maga (Leech 1890). Based upon a careful survey of specimens and relevant literature, these regions are omitted from the known range of this species. Onryza maga maga is found from northeast Guizhou, south Henan and Qinling-Daba Mountains in Shaanxi of China, its oc- currence in Hunan is confirmed. The adults are redescribed and the variability of wing patterns is discussed. Female genitalia are illustrated and described for the first time. Some biological information and an updated distribution map of the species are provided. G. X. Xue & M. Li, School of Food and Bioengineering, Zhengzhou University of Light Industry, No. 5 Dongfeng Road, Zhengzhou, Henan, 450002, P. R. China; Corresponding author’s e-mail: [email protected] Y. F. Li, School of Medicine, Xi’an Jiaotong University, No. 76 Yanta West Road, Xi’an, Shaanxi, 710061, P. R. China Z. H. Liu, School of Physics, University of Science and Technology of China, No. 96 Jinzhai Road, Hefei, Anhui, 230026, P. R. China Y. D.
    [Show full text]
  • Preparing the Shaanxi-Qinling Mountains Integrated Ecosystem Management Project (Cofinanced by the Global Environment Facility)
    Technical Assistance Consultant’s Report Project Number: 39321 June 2008 PRC: Preparing the Shaanxi-Qinling Mountains Integrated Ecosystem Management Project (Cofinanced by the Global Environment Facility) Prepared by: ANZDEC Limited Australia For Shaanxi Province Development and Reform Commission This consultant’s report does not necessarily reflect the views of ADB or the Government concerned, and ADB and the Government cannot be held liable for its contents. (For project preparatory technical assistance: All the views expressed herein may not be incorporated into the proposed project’s design. FINAL REPORT SHAANXI QINLING BIODIVERSITY CONSERVATION AND DEMONSTRATION PROJECT PREPARED FOR Shaanxi Provincial Government And the Asian Development Bank ANZDEC LIMITED September 2007 CURRENCY EQUIVALENTS (as at 1 June 2007) Currency Unit – Chinese Yuan {CNY}1.00 = US $0.1308 $1.00 = CNY 7.64 ABBREVIATIONS ADB – Asian Development Bank BAP – Biodiversity Action Plan (of the PRC Government) CAS – Chinese Academy of Sciences CASS – Chinese Academy of Social Sciences CBD – Convention on Biological Diversity CBRC – China Bank Regulatory Commission CDA - Conservation Demonstration Area CNY – Chinese Yuan CO – company CPF – country programming framework CTF – Conservation Trust Fund EA – Executing Agency EFCAs – Ecosystem Function Conservation Areas EIRR – economic internal rate of return EPB – Environmental Protection Bureau EU – European Union FIRR – financial internal rate of return FDI – Foreign Direct Investment FYP – Five-Year Plan FS – Feasibility
    [Show full text]
  • GIS Assessment of the Status of Protected Areas in East Asia
    CIS Assessment of the Status of Protected Areas in East Asia Compiled and edited by J. MacKinnon, Xie Yan, 1. Lysenko, S. Chape, I. May and C. Brown March 2005 IUCN V 9> m The World Conservation Union UNEP WCMC Digitized by the Internet Archive in 20/10 with funding from UNEP-WCMC, Cambridge http://www.archive.org/details/gisassessmentofs05mack GIS Assessment of the Status of Protected Areas in East Asia Compiled and edited by J. MacKinnon, Xie Yan, I. Lysenko, S. Chape, I. May and C. Brown March 2005 UNEP-WCMC IUCN - The World Conservation Union The designation of geographical entities in this book, and the presentation of the material, do not imply the expression of any opinion whatsoever on the part of UNEP, UNEP-WCMC, and IUCN concerning the legal status of any country, territory, or area, or of its authorities, or concerning the delimitation of its frontiers or boundaries. UNEP-WCMC or its collaborators have obtained base data from documented sources believed to be reliable and made all reasonable efforts to ensure the accuracy of the data. UNEP-WCMC does not warrant the accuracy or reliability of the base data and excludes all conditions, warranties, undertakings and terms express or implied whether by statute, common law, trade usage, course of dealings or otherwise (including the fitness of the data for its intended use) to the fullest extent permitted by law. The views expressed in this publication do not necessarily reflect those of UNEP, UNEP-WCMC, and IUCN. Produced by: UNEP World Conservation Monitoring Centre and IUCN, Gland, Switzerland and Cambridge, UK Cffti IUCN UNEP WCMC The World Conservation Union Copyright: © 2005 UNEP World Conservation Monitoring Centre Reproduction of this publication for educational or other non-commercial purposes is authorized without prior written permission from the copyright holder provided the source is fully acknowledged.
    [Show full text]
  • Hubei Shennongjia
    ASIA / PACIFIC HUBEI SHENNONGJIA CHINA Laojunshan Component of the property - © IUCN Bruce Jefferies China - Hubei Shennongjia WORLD HERITAGE NOMINATION – IUCN TECHNICAL EVALUATION HUBEI SHENNONGJIA (CHINA) – ID 1509 IUCN RECOMMENDATION TO WORLD HERITAGE COMMITTEE: To inscribe the property under natural criteria. Key paragraphs of Operational Guidelines: Paragraph 77: Nominated property meets World Heritage criteria. Paragraph 78: Nominated property meets integrity and protection and management requirements. 1. DOCUMENTATION S. and Hong Qian. Global Significance of Plant Diversity in China. In The Plants of China: A a) Date nomination received by IUCN: 16 March Companion to the Flora of China (2015). Huang, J. H., 2015 Chen, J.H., Ying, J.S., and Ke‐Ping M. Features and distribution patterns of Chinese endemic seed plant b) Additional information officially requested from species. Journal of Systematics and Evolution 49, no. and provided by the State Party: On 6 September 2 (2011): 81-94. Li, Y. (2004). The effect of forest 2015, the State Party responded to issues which arose clear-cutting on habitat use in Sichuan snub-nosed during the course of the IUCN field evaluation mission. monkey (Rhinopithecus roxellana) in Shennongjia The letter, with accompanying maps, addressed a Nature Reserve, China. Primates 45.1 69-72.. López- range of issues and confirmed extensions to the Pujol, J., et al. (2011). Mountains of Southern China as nominated area and buffer zone in the Badong County “plant museums” and “plant cradles”: evolutionary and area. Following the IUCN World Heritage Panel a conservation insights. Mountain Research and progress report was sent to the State Party on 16 Development,31(3), 261-269.
    [Show full text]
  • R Graphics Output
    China China LEGEND Previously sampled Malaise trap site Ecoregion Alashan Plateau semi−desert North Tibetan Plateau−Kunlun Mountains alpine desert Altai alpine meadow and tundra Northeast China Plain deciduous forests Altai montane forest and forest steppe Northeast Himalayan subalpine conifer forests Altai steppe and semi−desert Northern Indochina subtropical forests Amur meadow steppe Northern Triangle subtropical forests Bohai Sea saline meadow Northwestern Himalayan alpine shrub and meadows Central China Loess Plateau mixed forests Nujiang Langcang Gorge alpine conifer and mixed forests Central Tibetan Plateau alpine steppe Ordos Plateau steppe Changbai Mountains mixed forests Pamir alpine desert and tundra Changjiang Plain evergreen forests Qaidam Basin semi−desert Da Hinggan−Dzhagdy Mountains conifer forests Qilian Mountains conifer forests Daba Mountains evergreen forests Qilian Mountains subalpine meadows Daurian forest steppe Qin Ling Mountains deciduous forests East Siberian taiga Qionglai−Minshan conifer forests Eastern Gobi desert steppe Rock and Ice Eastern Himalayan alpine shrub and meadows Sichuan Basin evergreen broadleaf forests Eastern Himalayan broadleaf forests South China−Vietnam subtropical evergreen forests Eastern Himalayan subalpine conifer forests Southeast Tibet shrublands and meadows Emin Valley steppe Southern Annamites montane rain forests Guizhou Plateau broadleaf and mixed forests Suiphun−Khanka meadows and forest meadows Hainan Island monsoon rain forests Taklimakan desert Helanshan montane conifer forests
    [Show full text]
  • Pn Wave Velocity and Anisotropy Underneath the Central
    Journal of Asian Earth Sciences 184 (2019) 103941 Contents lists available at ScienceDirect Journal of Asian Earth Sciences journal homepage: www.elsevier.com/locate/jseaes Pn wave velocity and anisotropy underneath the central segment of the North-South Seismic Belt in China T ⁎ Guangbao Dua,b, Qingju Wua, Xuemei Zhangb, , Jing Hec, Liye Zoub, Yangyang Fengd, Jie Liub, Fabio Romanellie a Key Laboratory of Seismic Observation and Geophysical Imaging, Institute of Geophysics, China Earthquake Administration, Beijing 100081, China b China Earthquake Networks Center, Beijing 100045, China c Key Laboratory of Crustal Dynamics, Institute of Crustal Dynamics, China Earthquake Administration, Beijing 100085, China d The Inner Mongolia Autonomous Region Seismological Bureau, Hohhot 010051, China e Department of Mathematics and Geosciences, University of Trieste, Trieste 34127 Italy ARTICLE INFO ABSTRACT Keywords: We present a Pn wave velocity and anisotropy model of the central segment of the North-South Seismic Belt in Pn wave China, where there are numerous stable basins and active faults, making this segment attractive for extensive Velocity heterogeneity studies. The model was obtained by a tomographic analysis of 49,973 Pn wave phase readings collected by the Anisotropy China Earthquake Networks Center and temporary stations in Yunnan and Sichuan. The tomographic velocity Uppermost mantle model shows that the average Pn wave velocity is 8.06 km/s; prominent high-velocity (high-V) anomalies are Central segment of the North-South Seismic visible under the Sichuan Basin, the Zoige Basin and the Ordos block, which clearly outline their tectonic Belt margins. A pronounced low-velocity (low-V) zone is observed from the Songpan-Ganzi block to the Chuan-Dian and Daliangshan blocks, suggesting the presence of hot material upwelling.
    [Show full text]
  • A New Species of Odorrana (Anura, Ranidae) from Hunan Province, China
    ZooKeys 1024: 91–115 (2021) A peer-reviewed open-access journal doi: 10.3897/zookeys.1024.56399 RESEarch arTICLE https://zookeys.pensoft.net Launched to accelerate biodiversity research A new species of Odorrana (Anura, Ranidae) from Hunan Province, China Bing Zhang1, Yuan Li1, Ke Hu1, Pipeng Li2, Zhirong Gu3, Nengwen Xiao4, Daode Yang1 1 Institute of Wildlife Conservation, Central South University of Forestry and Technology, Changsha 410004, China 2 Institute of Herpetology, Shenyang Normal University, Shenyang 110034, China 3 Bureau of Hunan Badagongshan National Nature Reserve, Sangzhi 427100, China 4 State Environmental Protection Key Labo- ratory of Regional Eco-process and Function Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China Corresponding author: Daode Yang ([email protected]) Academic editor: A. Crottini | Received 12 July 2020 | Accepted 30 December 2020 | Published 15 March 2021 http://zoobank.org/756CA7F5-A4C1-4759-AB64-8C147F6C9A6A Citation: Zhang B, Li Y, Hu K, Li P, Gu Z, Xiao N, Yang D (2021) A new species of Odorrana (Anura, Ranidae) from Hunan Province, China. ZooKeys 1024: 91–115. https://doi.org/10.3897/zookeys.1024.56399 Abstract A new species, Odorrana sangzhiensis sp. nov., is described, based on five specimens from Sangzhi County, Zhangjiajie City, Hunan Province, China. Molecular phylogenetic analyses, based on mitochondrial 12S rRNA and 16S rRNA gene sequences, strongly support the new species as a monophyletic group nested into the O. schmackeri species complex. The new
    [Show full text]
  • 1. Brief Introduction to the Institute of Geology
    -1- The Institute of Geology, Chinese Academy of Geological Sciences (CAGS) Preface The Institute of Geology, Chinese Academy of Geological Sciences (CAGS), is a national public scientific research institution and is mainly engaged in national fundamental, public, strategic and frontier geological survey and geoscientific research. Entering the new century, and in particular during the past 5 years, the Institute has made notable progress in scientific research, personnel training and international cooperation, with increasing cooperation and exchange activities, expanded fields of cooperation, abundant output of new research results, and an increased number of papers published in “Nature”, “Science” and other high-impact international scientific journals. In the light of this new situation and in order to publicize, in a timely manner, annual progress and achievements of the Institute to enhance its international reputation, an English version of the Institute’s Annual Report has been published since 2010. Similar to previous reports, the Annual Report 2015 includes the following 7 parts: (1) Introduction to the Institute of Geology, CAGS; (2) Ongoing Research Projects; (3) Research Achievements and Important Progress; (4) International Cooperation and Academic Exchange; (5) Important Academic Activities in 2015; (6) Postgraduate Education; (7) Publications. In order to avoid confusion in the meaning of Chinese and foreign names, all family names in this Report are capitalized. We express our sincere gratitude to colleagues of related research departments and centers of the Institute for their support and efforts in compiling this Report and providing related material – a written record of the hard work of the Institute’s scientific research personnel for the year 2015.
    [Show full text]
  • Spatial Pattern of Forest Carbon Storage in the Vertical and Horizontal Directions Based on HJ-CCD Remote Sensing Imagery
    remote sensing Article Spatial Pattern of Forest Carbon Storage in the Vertical and Horizontal Directions Based on HJ-CCD Remote Sensing Imagery Kaisheng Luo School of Remote Sensing and Geomatics Engineering, Nanjing University of Information Science and Technology, Nanjing 210044, China; [email protected]; Tel.: +86-188-6095-7185 Received: 15 January 2019; Accepted: 27 March 2019; Published: 2 April 2019 Abstract: To provide a comprehensive understanding of the spatial distribution of forest carbon reserves, this study explores carbon storage and its spatial pattern in the horizontal and vertical directions on a provincial scale using HJ-CCD remote sensing imagery. Results show that carbon storage in the forests of Hubei Province was 784.46 Tg. In the horizontal direction, Enshi Prefecture contributed the most, with a contribution rate of 22.01%, followed by Yichang (18.74%), Shiyan (15.21%), and Xiangfan (10.61%). Coniferous forests contributed the most to the total carbon reserves of the forests, with a contribution rate of 71.34%, followed by broadleaf forests (25.36%), and mixed forests (3.30%). In the vertical direction, the environmental difference in the vertical direction of the forest ecosystem led to the obvious stratification of carbon storage in the vertical direction, that is: soil layer > tree canopy layer > shrub layer > litter layer. The soil layer had the largest carbon storage, contributing 76.63%, followed by the tree canopy layer (19.05%), shrub layer (2.39%), and litter layer (1.93%). The different contributing layers of coniferous, broadleaf, and mixed forests to carbon storage followed the same order: soil layer > tree canopy layer > shrub layer > litter layer.
    [Show full text]
  • Downloaded from the Worldclim Website ( Accessed on 5 January 2021)
    Article Population Demographic History of a Rare and Endangered Tree Magnolia sprengeri Pamp. in East Asia Revealed by Molecular Data and Ecological Niche Analysis Tong Zhou 1,†, Xiao-Juan Huang 1,†, Shou-Zhou Zhang 2 , Yuan Wang 1, Ying-Juan Wang 1, Wen-Zhe Liu 1, Ya-Ling Wang 3,*, Jia-Bin Zou 4,* and Zhong-Hu Li 1,* 1 Key Laboratory of Resource Biology and Biotechnology in Western China, Ministry of Education, College of Life Sciences, Northwest University, Xi’an 710069, China; [email protected] (T.Z.); [email protected] (X.-J.H.); [email protected] (Y.W.); [email protected] (Y.-J.W.); [email protected] (W.-Z.L.) 2 Fairylake Botanical Garden, Shenzhen and Chinese Academy of Sciences, Shenzhen 518004, China; [email protected] 3 Xi’an Botanical Garden, Xi’an 710061, China 4 National Engineering Laboratory for Resource Developing of Endangered Chinese Crude Drugs in Northwest of China, Key Laboratory of the Ministry of Education for Medicinal Resources and Natural Pharmaceutical Chemistry, College of Life Sciences, Shaanxi Normal University, Xi’an 710119, China * Correspondence: [email protected] (Y.-L.W.); [email protected] (J.-B.Z.); [email protected] (Z.-H.L.); Tel.: +86-29-88302411 (Z.-H.L.) † Correspondence: two authors contributed equally to this study. Abstract: Quaternary climate and environment oscillations have profoundly shaped the population Citation: Zhou, T.; Huang, X.-J.; dynamic history and geographic distributions of current plants. However, how the endangered and Zhang, S.-Z.; Wang, Y.; Wang, Y.-J.; rare tree species respond to the climatic and environmental fluctuations in the subtropical regions of Liu, W.-Z.; Wang, Y.-L.; Zou, J.-B.; Li, China in East Asia still needs elucidation.
    [Show full text]
  • A Global Overview of Protected Areas on the World Heritage List of Particular Importance for Biodiversity
    A GLOBAL OVERVIEW OF PROTECTED AREAS ON THE WORLD HERITAGE LIST OF PARTICULAR IMPORTANCE FOR BIODIVERSITY A contribution to the Global Theme Study of World Heritage Natural Sites DRAFT Text and Tables compiled by Gemma Smith and Janina Jakubowska Maps compiled by Ian May UNEP World Conservation Monitoring Centre Cambridge, UK July 2000 I >\~ l lUCN UNEP WCMC The World Conservation Union Disclaimer: The contents of this report and associated maps do not necessarily reflect the views or policies of UNEP-WCMC or contributory organisations. The designations employed and the presentations do not imply the expressions of any opinion whatsoever on the part of UNEP-WCMC or contributory organisations concerning the legal status of any country, territory, city or area or its authority, or concerning the delimitation of its frontiers or boundaries. 1 TABLE OF CONTENTS EXECUTIVE SUMMARY INTRODUCTION 1.0 Overview 1 2.0 Issues TO Consider 1 3.0 What IS Biodiversity? 2 4.0 Assessment methodology 3 5.0 Current World Heritage Sites 4 5.1 Criterion (IV) 4 5.2 World Heritage Sites IN Danger 4 5.3 Case Studies 5 6.0 Biogeographical Coverage 5 6.1 Udvardy Biogeographical Provinces 5 6.2 Bailey's Ecoregions 6 7.0 Key Prioritisation Programme Areas 6 7.1 WWF Global 200 Ecoregions 6 7.2 Centres of Plant Diversity (CPD) 6 7.3 Conservation International - Biodiversity Hotspots 7 7.4 Vavilov Centres of Plant Genetic Diversity 8 7.5 Endemic Bird Areas (EBAs) 8 8.0 Key Areas for Identified Species 9 8.1 Critically Endangered Taxa 9 8.2 Marine Turtles 9 9.0 Key Habitat Areas 1 9.1 Ramsar sites 11 9.2 Marine Biodiversity 1 9.3 Coral Reefs and Mangroves 1 10.0 Key Findings 12 11.0 Possible Future World Heritage Sites 13 12.0 Limitations of THE study 14 13.0 Conclusions AND Recommendations for Future Work 15 REFERENCES TABLES Table 1 .
    [Show full text]