| Quantitative assessment of desertification using landsat data on a regional scale - a case study in the ordos plateau, china. | |
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MedLine Citation:
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PMID: 22573984 Owner: NLM Status: In-Data-Review |
Abstract/OtherAbstract:
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Desertification is a serious threat to the ecological environment and social economy in our world and there is a pressing need to develop a reasonable and reproducible method to assess it at different scales. In this paper, the Ordos Plateau in China was selected as the research region and a quantitative method for desertification assessment was developed by using Landsat MSS and TM/ETM+ data on a regional scale. In this method, NDVI, MSDI and land surface albedo were selected as assessment indicators of desertification to represent land surface conditions from vegetation biomass, landscape pattern and micrometeorology. Based on considering the effects of vegetation type and time of images acquired on assessment indictors, assessing rule sets were built and a decision tree approach was used to assess desertification of Ordos Plateau in 1980, 1990 and 2000. The average overall accuracy of three periods was higher than 90%. The results showed that although some local places of Ordos Plateau experienced an expanding trend of desertification, the trend of desertification of Ordos Plateau was an overall decrease in from 1980 to 2000. By analyzing the causes of desertification processes, it was found that climate change could benefit for the reversion of desertification from 1980 to 1990 at a regional scale and human activities might explain the expansion of desertification in this period; however human conservation activities were the main driving factor that induced the reversion of desertification from 1990 to 2000. |
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Authors:
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Duanyang Xu; Xiangwu Kang; Dongsheng Qiu; Dafang Zhuang; Jianjun Pan |
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Publication Detail:
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Type: Journal Article Date: 2009-03-12 |
Journal Detail:
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Title: Sensors (Basel, Switzerland) Volume: 9 ISSN: 1424-8220 ISO Abbreviation: Sensors (Basel) Publication Date: 2009 |
Date Detail:
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Created Date: 2012-05-10 Completed Date: - Revised Date: - |
Medline Journal Info:
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Nlm Unique ID: 101204366 Medline TA: Sensors (Basel) Country: Switzerland |
Other Details:
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Languages: eng Pagination: 1738-53 Citation Subset: - |
Affiliation:
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Collage of Resources and Environmental Sciences, Nanjing Agricultural University, Nanjing 210095, Jiangsu Province, P.R. China; E-Mails: duanyang_xu@126.com (D.X.); jpan@njau.edu.cn (J.P.). |
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From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine
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