DocumentCode
76089
Title
South America Land Use and Land Cover Assessment and Preliminary Analysis of Their Impacts on Regional Atmospheric Modeling Studies
Author
Capucim, Mauricio N. ; Brand, Veronika S. ; Machado, Carolyne B. ; Martins, Leila D. ; Allasia, Daniel G. ; Homann, Camila T. ; de Freitas, Edmilson D. ; Da Silva Dias, Maria A. F. ; Andrade, Maria F. ; Martins, Jorge A.
Author_Institution
Fed. Univ. of Technol. of Parana, Londrina, Brazil
Volume
8
Issue
3
fYear
2015
fDate
Mar-15
Firstpage
1185
Lastpage
1198
Abstract
Data provided by two important sources of information on land use and land cover (LULC), MODIS-2009 and GLOBCOVER-2009, were analyzed for South America in order to assess differences related to their application in numerical modeling studies. Even though on a South American basis, the two databases showed a Pearson correlation coefficient above 85%, on a regional analysis, the correlation stayed within the range of 0%-100%, depending on the territorial unit analyzed. Significant differences were observed in most of the land cover classes, with only forested areas presenting a good level of agreement. In terms of territorial units, only areas in the Amazon region, where forest cover is predominant, showed significant correlation levels. Crops and urban classes presented the greatest differences between the two analyzed files. Results of meteorological simulations indicated that such observed discrepancies are able to cause strong impacts on modeling scenarios and important bias on simulated variables, being a crucial feature for weather and climate forecast and diagnostic.
Keywords
climatology; land cover; land use; numerical analysis; terrain mapping; vegetation; weather forecasting; Amazon region; GLOBCOVER-2009 data; MODIS-2009 data; Pearson correlation coefficient; South America; crops class; forested areas; land cover classes; land use; meteorological simulations; numerical modeling studies; regional analysis; regional atmospheric modeling; territorial unit; territorial units; urban class; weather-climate forecast; Databases; Earth; MODIS; Meteorology; Predictive models; South America; Vegetation mapping; Agriculture; earth; image analysis; simulation; urban areas;
fLanguage
English
Journal_Title
Selected Topics in Applied Earth Observations and Remote Sensing, IEEE Journal of
Publisher
ieee
ISSN
1939-1404
Type
jour
DOI
10.1109/JSTARS.2014.2363368
Filename
6975100
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