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zsyzgx金蟲(chóng) (初入文壇)
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[求助]
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論文：Comparison of sampling designs for estimating deforestation from Landsat TM and MODIS imagery: a case study in Mato Grosso, Brazil 發(fā)表期刊：Scientific World Journal DOI：http://dx.doi.org/10.1155/2014/919456 |
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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 文獻(xiàn)號(hào): 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. 關(guān)鍵詞 KeyWords Plus:FOREST DISTURBANCE DETECTION; TROPICAL DEFORESTATION; SATELLITE DATA; COVER; AMAZON; STRATEGIES; VEGETATION; RECORD 作者信息 通訊作者地址: Zhu, SY (通訊作者) [顯示增強(qiáng)組織信息的名稱(chēng)] Nanjing Univ Informat Sci & Technol, Sch Remote Sensing, Nanjing 210044, Jiangsu, Peoples R China. 地址: [顯示增強(qiáng)組織信息的名稱(chēng)] [ 1 ] Nanjing Univ Informat Sci & Technol, Sch Remote Sensing, Nanjing 210044, Jiangsu, Peoples R China [顯示增強(qiáng)組織信息的名稱(chēng)] [ 2 ] Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China 電子郵件地址:zsyzgx@163.com 基金資助致謝 基金資助機(jī)構(gòu) 授權(quán)號(hào) Chinese 973 Project 2010CB950701 Natural Science Foundation of China 41001289 41201369 查看基金資助信息 出版商 HINDAWI PUBLISHING CORPORATION, 410 PARK AVENUE, 15TH FLOOR, #287 PMB, NEW YORK, NY 10022 USA 類(lèi)別 / 分類(lèi) 研究方向:Science & Technology - Other Topics Web of Science 類(lèi)別:Multidisciplinary Sciences 文獻(xiàn)信息 文獻(xiàn)類(lèi)型:Article 語(yǔ)種:English 入藏號(hào): WOS:000343579300001 ISSN: 1537-744X 期刊信息 Impact Factor (影響因子): Journal Citation Reports® 其他信息 IDS 號(hào): AR4TL Web of Science 核心合集中的 "引用的參考文獻(xiàn)": 39 Web of Science 核心合集中的 "被引頻次": 0 |
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