Dynamic detection of water surface area of Ebinur Lake using multi-source satellite data (Landsat and Sentinel-1A) and its responses to changing environment
Dynamic detection of water surface area of Ebinur Lake using multi-source satellite data (Landsat and Sentinel-1A) and its responses to changing environment
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DOI：
10.1016/j.catena.2019.02.020
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发表时间：
2019-06
期刊：
影响因子：
6.2
通讯作者：
Jingzhe Wang;Jianli Ding;Guannan Li;Jing Liang;Danlin Yu;T. Aishan;Fang Zhang;Jinming Yang
中科院分区：
文献类型：
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作者：
Jingzhe Wang;Jianli Ding;Guannan Li;Jing Liang;Danlin Yu;T. Aishan;Fang Zhang;Jinming Yang
在干旱半干旱气候区，湖泊对于脆弱的生态环境和区域可持续发展至关重要。艾比湖是新疆准噶尔盆地生态屏障的重要组成部分，中国。由于近几十年来艾比湖及周边沼泽的巨大变化，艾比湖成为中国西北部具有代表性的生态退化地区。水体年内变化的检测及其对环境变化的响应对于区域生态安全和退化生态系统的恢复至关重要。为了利用合成孔径雷达(SAR)数据提取更准确的水体信息，进一步填补艾比湖月间动态监测的空白，基于归一化差分水体指数(NDWI)图像与Sentinel 1A数据的关系，提出了一种新的SAR水体指数(修正的Sentinel 1A型水体指数)。用最大类间方差法选择动态分类阈值，结果表明分类结果是可接受的，最优总体精度为99.94%，卡帕系数为0.9971。我们利用2017年2月9日至2018年2月4日的S1a数据对艾比湖表面积进行了时间序列分析。2017年4月22日湖面面积最大为965.29 km2，9月1日最小为750.37 km2，平均面积为831.51 km2。季节变化呈现出研究期内“急剧上升”-“显著下降”-“逐渐稳定”的阶段。水表面积与来水量高度相关(相关系数 = 为0.72，P<； 为0.001)。艾比湖水面面积的变化对于监测干旱半干旱地区环境条件变化对生态环境的影响至关重要。
In arid and semi-arid climatic areas, lakes are extremely essential for fragile ecological environment and regional sustainable development. Ebinur Lake is an important component of the ecological barrier of Junggar Basin, Xinjiang Uyghur Autonomous Region (XUAR), China. Due to the tremendous changes in Ebinur Lake and surrounding marshes during the last decades, Ebinur Lake becomes a representative ecological degradation region in northwestern China. The detection of the intra-annual variations of water body and its responses to changing environment are critical for regional ecological security and rehabilitation of degraded ecosystem. To extract more accurate water information using Synthetic Aperture Radar (SAR) data and further fill the gap of inter-month dynamic monitoring of Ebinur Lake, a new SAR water index (modified Sentinel 1A water index, MSWI) was proposed based on the relationship between normalized difference water index (NDWI) imageries and Sentinel 1A data. The dynamic thresholds of classification were selected using Otsu method and the results showed that the classification results were acceptable with the optimal overall accuracy of 99.94% and kappa coefficient of 0.9971, respectively. We conduct a time series analysis of surface areas of Ebinur Lake using S1A data from February 9th, 2017 to February 4th, 2018. The maximum lake surface area was 965.29 km2in April 22nd, 2017, while the minimum value was 750.37 km2in September 1st, 2017, and the mean area was 831.51 km2. The seasonal variations showed the stages of “sharp rising” – “significant decreasing” – “gradual stabilizing” in the study period. The water surface area was highly correlated with inflow water volume (correlation coefficient = 0.72,P< 0.001). The variation of Ebinur Lake's water surface area is crucial to monitor the resulting eco-environmental impacts under the changing environmental conditions in the arid and semi-arid areas.