title: Comparison of sampling designs for estimating deforestation from landsat TM and MODIS imagery: a case study in Mato Grosso, Brazil.
abstract: 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.
authors.affiliation: School of Remote Sensing, Nanjing University of Information Science & Technology, Nanjing 210044, China.
authors.forename: Shanyou
authors.initials: S
authors.lastname: Zhu
authors.affiliation: School of Remote Sensing, Nanjing University of Information Science & Technology, Nanjing 210044, China.
authors.forename: Hailong
authors.initials: H
authors.lastname: Zhang
authors.affiliation: Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China.
authors.forename: Ronggao
authors.initials: R
authors.lastname: Liu
authors.affiliation: School of Remote Sensing, Nanjing University of Information Science & Technology, Nanjing 210044, China.
authors.forename: Yun
authors.initials: Y
authors.lastname: Cao
authors.affiliation: School of Remote Sensing, Nanjing University of Information Science & Technology, Nanjing 210044, China.
authors.forename: Guixin
authors.initials: G
authors.lastname: Zhang
mesh_terms: D000383:Agriculture / Q000379:methods; D000465:Algorithms; D001938:Brazil; D003247:Conservation of Natural Resources / Q000379:methods*; D016468:Forestry / Q000379:methods; D005843:Geography; D008962:Models, Theoretical; D015203:Reproducibility of Results; D012107:Research Design / Q000592:standards*; D014197:Trees / Q000502:physiology