Temporal and Spatial Analysis of Water Extent in Poyang Lake using HJ-1 data

He Haixia, Tang Tong
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引用次数: 1

Abstract

Temporal and Spatial Analysis of Water Extent in Poyang Lake is significant to reveal ecological environment evolution and drought formation mechanism and the influence in the Poyang lake basin. Water extent is the key index to characterize the scale and intensity of drought disaster. The seasonal water change of Poyang Lake is obvious. There is high landscape heterogeneity because the terrain features distribution is highly complex and discontinuous in the dry season. At the same time spectral characteristics of water and its surroundings are complicated in that the microscopic formation mechanism of water is complicated. It is difficult to perform water information extraction. The commonly used water information extraction methods such as classification method, image segmentation method, threshold method, region growing method can't meet the requirements on the efficiency and accuracy. In this paper, Water information extraction and validation of 2011 was performed using HJ-1 CCD data based on decision tree method. Then temporal and spatial analysis of water extent was performed. At last, the relationship between the water extent and disaster loss information was analyzed. The results indicated that the decision tree method significantly improved the efficiency and accuracy compared to the traditional classification method and visual interpretation. It spent 2 hour in extracting water of dry season which need 2 days using visual interpretation method. The accuracy of the method was 94.5 percent of the accuracy using visual interpretation. It can meet the requirement of disaster reduction and solve the problem in dynamic extracting water extent of high landscape heterogeneity. There is high correlation between the temporal and spatial change of the water extent and the drought event.
基于HJ-1数据的鄱阳湖水量时空分析
鄱阳湖水量的时空分析对揭示鄱阳湖流域生态环境演变、干旱形成机制及其影响具有重要意义。水分程度是表征干旱灾害规模和强度的关键指标。鄱阳湖的季节水量变化明显。旱季地形特征分布高度复杂、不连续,景观异质性强。同时,水及其周围环境的光谱特征也很复杂,水的微观形成机制也很复杂。水信息的提取是一个难点。常用的水信息提取方法如分类法、图像分割法、阈值法、区域生长法等在效率和精度上都不能满足要求。本文利用基于决策树方法的HJ-1 CCD数据,对2011年水文信息进行了提取与验证。在此基础上,进行了水范围的时空分析。最后,分析了水位与灾害损失信息之间的关系。结果表明,与传统的分类方法和目视判读方法相比,决策树方法显著提高了分类效率和准确率。旱季取水2小时,目视解译法取水2天。该方法的准确率为目视判读准确率的94.5%。它既能满足减灾的要求,又能解决景观异质性高的动态提取水量的问题。干旱区水位的时空变化与干旱事件具有高度的相关性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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