Evaluation of seasonal water body extents in Central Asia over the past 27 years derived from medium-resolution remote sensing data |
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| Institution: | 1. Department of Remote Sensing, University of Wuerzburg, Germany;2. German Aerospace Center (DLR), German Remote Sensing Data Center (DFD), Wessling, Germany;3. National Hydrometeorological Service of the Republic of Kazakhstan, Kazakhstan;4. Institute of Geography of the Republic of Kazakhstan, Kazakhstan;1. State Key Laboratory of Desert & Oasis Ecology, Xinjiang Institute of Ecology & Geography, Chinese Academy of Sciences, Urumqi, 830010, China;2. University of Chinese Academy of Sciences, Beijing, 10049, China;3. Department of Engineering, University of California, Merced, USA;1. Department of Geoinformation, Faculty of Geoinformation and Real Estate, Universiti Teknologi Malaysia, 81310 UTM Skudai, Johor, Malaysia;2. Remote Sensing and GIS Centre, Sari University of Agricultural Sciences and Natural Resources, Sari, Iran;3. Institute of Geospatial Science & Technology (INSTeG), Universiti Teknologi Malaysia, 81310 UTM Skudai, Johor, Malaysia;1. Department of Geography and Resource Management, The Chinese University of Hong Kong, Shatin 999077, Hong Kong;2. Institute of Space and Earth Information Science, The Chinese University of Hong Kong, Shatin 999077, Hong Kong;3. Department of Land Surveying and Geo-Informatics, The Hong Kong Polytechnic University, Kowloon 999077, Hong Kong;4. Department of Geography, University of Cambridge, CB2 3EN Cambridge, United Kingdom;1. School of Electronics Engineering and Computer Science, Peking University, Beijing 100871, China;2. Department of Ecology, College of Urban and Environmental Sciences, and Key Laboratory for Earth Surface Processes of the Ministry of Education, Peking University, Beijing 100871, China;3. Institute of Remote Sensing and Geographical Information Systems, Peking University, Beijing 100871, China;1. Key Laboratory of Watershed Geographic Sciences, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, China;2. State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Hohai University, Nanjing 210098, China;3. College of Hydrology and Water Resources, Hohai University, Nanjing 211100, China;4. Department of Geography and Geospatial Sciences, Kansas State University, Manhattan, KS 66506, USA;5. Department of Earth Sciences, The University of Hong Kong, Hong Kong, China |
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| Abstract: | In this study medium resolution remote sensing data of the AVHRR and MODIS sensors were used for derivation of inland water bodies extents over a period from 1986 till 2012 for the region of Central Asia. Daily near-infrared (NIR) spectra from the AVHRR sensor with 1.1 km spatial resolution and 8-day NIR composites from the MODIS sensor with 250 m spatial resolution for the months April, July and September were used as input data. The methodological approach uses temporal dynamic thresholds for individual data sets, which allows detection of water pixel independent from differing conditions or sensor differences. The individual results are summed up and combined to monthly composites of areal extent of water bodies. The presented water masks for the months April, July, and September were chosen to detect seasonal patterns as well as inter-annual dynamics and show diverse behaviour of static, decreasing, or dynamic water bodies in the study region. The size of the Southern Aral Sea, as the most popular example for an ecologic catastrophe, is decreasing significantly throughout all seasons (R2 0.96 for April; 0.97 for July; 0.96 for September). Same is true for shallow natural lakes in the northern Kazakhstan, exemplary the Tengiz-Korgalzhyn lake system, which have been shrinking in the last two decades due to drier conditions (R2 0.91 for July; 0.90 for September). On the contrary, water reservoirs show high seasonality and are very dynamic within one year in their areal extent with maximum before growing season and minimum after growing season. Furthermore, there are water bodies such as Alakol-Sasykol lake system and natural mountainous lakes which have been stable in their areal extent throughout the entire time period. Validation was performed based on several Landsat images with 30 m resolution and reveals an overall accuracy of 83% for AVHRR and 91% for MODIS monthly water masks. The results should assist for climatological and ecological studies, land and water management, and as input data for different modelling applications. |
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| Keywords: | Water bodies Central Asia Medium resolution satellite data Time-series |
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