Examining the Reliability of Survey Data with Remote Sensing and Geographic Information Systems to Improve Deforestation Modeling
Tropical deforestation has environmental consequences at local, regional and global scales. The Brazilian Amazon's deforestation resulted largely from conversion to farmland by landholders. These conversions caused deforestation that researchers have examined locally by interviews with landowners and regionally by satellite remote sensing. This paper merges data from these methods to validate survey-based deforestation levels with remote-sensing information. We determine household characteristics associated with misreporting of land use. After identifying errors, we modify the data to better estimate influences on local deforestation. Although individuals are not found to intentionally misrepresent land use, incorporating differences between the two data sources improves the estimations of deforestation.
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