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ÂÛÎÄ£ºComparison of sampling designs for estimating deforestation from Landsat TM and MODIS imagery: a case study in Mato Grosso, Brazil ·¢±íÆÚ¿¯£ºScientific World Journal DOI£ºhttp://dx.doi.org/10.1155/2014/919456 |
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sunshan4379: ½ð±Ò+8, ¸ÐлӦÖú£¡ 2014-11-26 16:17:48
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sunshan4379: ½ð±Ò+8, ¸ÐлӦÖú£¡ 2014-11-26 16:17:48
sunshan4379: LS-EPI+1, ¸ÐлӦÖú£¡ 2014-11-26 16:19:09
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Comparison of Sampling Designs for Estimating Deforestation from Landsat TM and MODIS Imagery: A Case Study in Mato Grosso, Brazil ×÷Õß: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 ÎÄÏ׺Å: 919456 DOI: 10.1155/2014/919456 ³ö°æÄê: 2014 ²é¿´ÆÚ¿¯ÐÅÏ¢ ÕªÒª 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. ¹Ø¼ü´Ê KeyWords Plus:FOREST DISTURBANCE DETECTION; TROPICAL DEFORESTATION; SATELLITE DATA; COVER; AMAZON; STRATEGIES; VEGETATION; RECORD ×÷ÕßÐÅÏ¢ ͨѶ×÷ÕßµØÖ·: Zhu, SY (ͨѶ×÷Õß) [ÏÔʾÔöÇ¿×éÖ¯ÐÅÏ¢µÄÃû³Æ] Nanjing Univ Informat Sci & Technol, Sch Remote Sensing, Nanjing 210044, Jiangsu, Peoples R China. µØÖ·: [ÏÔʾÔöÇ¿×éÖ¯ÐÅÏ¢µÄÃû³Æ] [ 1 ] Nanjing Univ Informat Sci & Technol, Sch Remote Sensing, Nanjing 210044, Jiangsu, Peoples R China [ÏÔʾÔöÇ¿×éÖ¯ÐÅÏ¢µÄÃû³Æ] [ 2 ] Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China µç×ÓÓʼþµØÖ·:zsyzgx@163.com »ù½ð×ÊÖúÖÂл »ù½ð×ÊÖú»ú¹¹ ÊÚȨºÅ Chinese 973 Project 2010CB950701 Natural Science Foundation of China 41001289 41201369 ²é¿´»ù½ð×ÊÖúÐÅÏ¢ ³ö°æÉÌ HINDAWI PUBLISHING CORPORATION, 410 PARK AVENUE, 15TH FLOOR, #287 PMB, NEW YORK, NY 10022 USA Àà±ð / ·ÖÀà Ñо¿·½Ïò:Science & Technology - Other Topics Web of Science Àà±ð:Multidisciplinary Sciences ÎÄÏ×ÐÅÏ¢ ÎÄÏ×ÀàÐÍ:Article ÓïÖÖ:English Èë²ØºÅ: WOS:000343579300001 ISSN: 1537-744X ÆÚ¿¯ÐÅÏ¢ Impact Factor (Ó°ÏìÒò×Ó): Journal Citation Reports® ÆäËûÐÅÏ¢ IDS ºÅ: AR4TL Web of Science ºËÐĺϼ¯ÖÐµÄ "ÒýÓõIJο¼ÎÄÏ×": 39 Web of Science ºËÐĺϼ¯ÖÐµÄ "±»ÒýƵ´Î": 0 |
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