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Use of Linear Spectral Mixture Model to Estimate Rice Planted Area Based on MODIS Data 被引量:2
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作者 WANG Lei Satoshi UCHID 《Rice science》 SCIE 2008年第2期131-136,共6页
MODIS (Moderate Resolution Imaging Spectroradiometer) is a key instrument aboard the Terra (EOS AM) and Aqua (EOS PM) satellites. Linear spectral mixture models are applied to MOIDS data for the sub-pixel classi... MODIS (Moderate Resolution Imaging Spectroradiometer) is a key instrument aboard the Terra (EOS AM) and Aqua (EOS PM) satellites. Linear spectral mixture models are applied to MOIDS data for the sub-pixel classification of land covers. Shaoxing county of Zhejiang Province in China was chosen to be the study site and early rice was selected as the study crop. The derived proportions of land covers from MODIS pixel using linear spectral mixture models were compared with unsupervised classification derived from TM data acquired on the same day, which implies that MODIS data could be used as satellite data source for rice cultivation area estimation, possibly rice growth monitoring and yield forecasting on the regional scale. 展开更多
关键词 RICE planted area Moderate Resolution Imaging Spectroradiometer Thematic Mapper data mixed pixel linear spectral mixture model
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Change of impervious surface area and its impacts on urban landscape:an example of Shenyang between 2010 and 2017 被引量:1
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作者 Wen Wu Chunlin Li +2 位作者 Miao Liu Yuanman Hu Chunliang Xiu 《Ecosystem Health and Sustainability》 SCIE 2020年第1期69-81,68,共14页
Introduction:One of the most striking features of urbanization is the replacement of the original natural land cover type by artificial impervious surface area(ISA).However,the extent of the contribution of various en... Introduction:One of the most striking features of urbanization is the replacement of the original natural land cover type by artificial impervious surface area(ISA).However,the extent of the contribution of various environmental factors,especially the growth of 3D space to ISA expansion,and the scope and mechanism of their influences in dramatically expanding cities,are yet to be determined.The boosted regression tree(BRT)model was adopted to analyze the main influencing factors and driving mechanisms of ISA change in Shenyang,China between 2010 and 2017.Outcomes:The nearly complete-coverage ISA(≥0.7)increased from 42%in 2010 to 47%in 2017.The percentage of landscape with a high ISA fraction increased,while the landscape evenness and diversity of ISA decreased.The BRT analysis revealed that elevation,regional population density,and landscape class had the largest influences on the change of urban ISA,contributing 22.55%,18.16%,and 11.18%to the model,respectively.Conclusion:Overall,topographic and socioeconomic factors had the greatest influence on urban ISA change in Shenyang,followed by land use type and building pattern indices.The trend of high aggregation was strong in large commercial and residential areas.The 3D expansion of the city had an influence on its areal expansion. 展开更多
关键词 Urban impervious surface landscape pattern boosted regression tree linear spectral mixture model driver analysis
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