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水土流失区生态变化的遥感评估
引用本文:徐涵秋. 水土流失区生态变化的遥感评估[J]. 农业工程学报, 2013, 29(7): 91-97.
作者姓名:徐涵秋
作者单位:1. 福建省水土流失遥感监测评估与灾害防治重点实验室,福州 3501082. 福州大学环境与资源学院,福州 3501083. 福州大学遥感信息工程研究所,福州 350108
基金项目:国家科技支撑项目(2013BAC08B01);福建省自然科学基金项目(2011J01269)
摘    要:水土流失是世界面临的一个严峻问题,它已给全球的生态造成了严重的威胁,及时快速地监测水土流失区的生态变化已显得尤为重要。为此,该文提出遥感生态指数(RSEI)来监测水土流失区的生态变化。该指数选取了绿度、湿度、热度和干度作为四大生态指标,并分别以遥感植被指数、湿度分量、地表温度和土壤-建筑指数为代表。同时采用主成分变换技术来集成各个指标,使各指标的权重是由数据本身的性质来决定,而不是人为的设定。将RSEI应用于福建长汀水土流失区的结果表明,RSEI指数可以定量地评价水土流失区生态修复的效果。数据显示,该区经过20多年的水土流失治理,RSEI生态指数值上升了17%,生态为优良的等级所占的面积比例从33.9%上升到52.3%,总体反映了该区的生态质量有了较明显的提高。

关 键 词:生态  遥感  遥感生态指数(RSEI)  主成分分析  长汀
收稿时间:2012-09-16
修稿时间:2013-03-03

Assessment of ecological change in soil loss area using remote sensing technology
Xu Hanqiu. Assessment of ecological change in soil loss area using remote sensing technology[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2013, 29(7): 91-97.
Authors:Xu Hanqiu
Affiliation:Xu Hanqiu 1,2,3 (1.Fujian Provincial Key Laboratory of Remote Sensing of Soil Erosion and Disaster Protection, Fuzhou 350108, China; 2. College of Environment and Resources, Fuzhou University, Fuzhou 350108, China 3. Institute of Remote Sensing Information Engineering, Fuzhou University, Fuzhou 350108, China)
Abstract:Abstract: Severe soil loss has caused ecological degradation for the global ecosystem, thus it is a major problem facing the world today. Timely and fast monitoring ecological changes in soil loss regions has become an increasing concern. This paper develops a remote sensing assessment method of soil erosion-induced changes in regional ecological quality based ecological index (RSEI). The proposed index combines four indicators from existing remote-sensing indices/components to represent greenness, dryness, wetness and heat, which are the important ecological indicators frequently used in assessing regional ecological status. The four remote-sensing indices/components are the normalized difference vegetation index (NDVI), soil index (SI), wetness component of the tasseled cap transformation (Wet), and land surface temperature (LST). The principal component analysis (PCA) was utilized to compress the four indicators into one index - RSEI, in order to assess overall ecological status. The new index, RSEI, was thus constructed using the first component as it was proved to have effectively combined the most information of the four indicators. The application of the RSEI in Hetian basin area in Changting county of Fujian province, one of the most serious reddish soil erosion areas in southern China, showed that the RSEI can quantitatively assess the ecological effects of soil loss treatment in the area and easily detect spatial and temporal changes of the ecological quality through a time period from 1988 to 2010. The application utilized three Landsat TM images of 1988, 2004 and 2010. The four indicators (NDVI, SI, Wet and LST) of each year were retrieved from the images and then combined through the PCA transform to form the RSEIs for the study years. The RSEI-based analysis indicated that after a more than 20 years fight for soil loss in the area by the local people and government, the ecological quality of the area has been significantly improved. This is suggested by an increase in the mean RSEI value from 0.5 in 1988 to 0.59 in 2010, accompanied by a decrease in low level RSEI area from 66.1% to 47.7%, and an increase of high level RSEI area from 33.9% to 52.3% in this duration. Quantitative analysis reveals that the greenness indicator represented by NDVI contributes most to the RSEI change among the four indicators used for generating the index. This suggests that the biological restore of soil erosion areas by planting tree and grass is an effective way to soil-erosion treatment for Hetian basin.
Keywords:ecology   remote sensing   remote sensing based ecology index(RSEI)   principal component analysis   Changting
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