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论文：Comparison of sampling designs for estimating deforestation from Landsat TM and MODIS imagery: a case study in Mato Grosso, Brazil 发表期刊：Scientific World Journal DOI：http://dx.doi.org/10.1155/2014/919456 |
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sunshan4379: 金币+8, 感谢应助！ 2014-11-26 16:17:48
sunshan4379: LS-EPI+1, 感谢应助！ 2014-11-26 16:19:09
感谢参与，应助指数 +1
sunshan4379: 金币+8, 感谢应助！ 2014-11-26 16:17:48
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Comparison of Sampling Designs for Estimating Deforestation from Landsat TM and MODIS Imagery: A Case Study in Mato Grosso, Brazil 作者:Zhu, SY (Zhu, Shanyou)[ 1 ] ; Zhang, HL (Zhang, Hailong)[ 1 ] ; Liu, RG (Liu, Ronggao)[ 2 ] ; Cao, Y (Cao, Yun)[ 1 ] ; Zhang, GX (Zhang, Guixin)[ 1 ] SCIENTIFIC WORLD JOURNAL 文献号: 919456 DOI: 10.1155/2014/919456 出版年: 2014 查看期刊信息 摘要 Sampling designs are commonly used to estimate deforestation over large areas, but comparisons between different sampling strategies are required. Using PRODES deforestation data as a reference, deforestation in the state of Mato Grosso in Brazil from 2005 to 2006 is evaluated using Landsat imagery and a nearly synchronous MODIS dataset. The MODIS-derived deforestation is used to assist in sampling and extrapolation. Three sampling designs are compared according to the estimated deforestation of the entire study area based on simple extrapolation and linear regression models. The results show that stratified sampling for strata construction and sample allocation using the MODIS-derived deforestation hotspots provided more precise estimations than simple random and systematic sampling. Moreover, the relationship between the MODIS-derived and TM-derived deforestation provides a precise estimate of the total deforestation area as well as the distribution of deforestation in each block. 关键词 KeyWords Plus:FOREST DISTURBANCE DETECTION; TROPICAL DEFORESTATION; SATELLITE DATA; COVER; AMAZON; STRATEGIES; VEGETATION; RECORD 作者信息 通讯作者地址: Zhu, SY (通讯作者) [显示增强组织信息的名称] Nanjing Univ Informat Sci & Technol, Sch Remote Sensing, Nanjing 210044, Jiangsu, Peoples R China. 地址: [显示增强组织信息的名称] [ 1 ] Nanjing Univ Informat Sci & Technol, Sch Remote Sensing, Nanjing 210044, Jiangsu, Peoples R China [显示增强组织信息的名称] [ 2 ] Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China 电子邮件地址:zsyzgx@163.com 基金资助致谢 基金资助机构 授权号 Chinese 973 Project 2010CB950701 Natural Science Foundation of China 41001289 41201369 查看基金资助信息 出版商 HINDAWI PUBLISHING CORPORATION, 410 PARK AVENUE, 15TH FLOOR, #287 PMB, NEW YORK, NY 10022 USA 类别 / 分类 研究方向:Science & Technology - Other Topics Web of Science 类别:Multidisciplinary Sciences 文献信息 文献类型:Article 语种:English 入藏号: WOS:000343579300001 ISSN: 1537-744X 期刊信息 Impact Factor (影响因子): Journal Citation Reports® 其他信息 IDS 号: AR4TL Web of Science 核心合集中的 "引用的参考文献": 39 Web of Science 核心合集中的 "被引频次": 0 |
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