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Remote Sens. 2012, 4(11), 3596-3618; doi:10.3390/rs4113596

A Quantitative Approach for Analyzing the Relationship between Urban Heat Islands and Land Cover

Remote Sensing Division (DSR), National Institute of Space Research (INPE), Avenida dos Astronautas, São José dos Campos-SP, 1758, Brazil
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Received: 30 September 2012 / Revised: 12 November 2012 / Accepted: 12 November 2012 / Published: 20 November 2012
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Abstract

With more than 80% of Brazilians living in cities, urbanization has had an important impact on climatic variations. São José dos Campos is located in a region experiencing rapid urbanization, which has produced a remarkable Urban Heat Island (UHI) effect. This effect influences the climate, environment and socio-economic development on a regional scale. In this study, the brightness temperatures and land cover types from Landsat TM images of São José dos Campos from 1986, 2001 and 2010 were analyzed for the spatial distribution of changes in temperature and land cover. A quantitative approach was used to explore the relationships among temperature, land cover areas and several indices, including the Normalized Difference Vegetation Index (NDVI), Normalized Difference Water Index (NDWI) and Normalized Difference Built-up Index (NDBI). The results showed that urban and bare areas correlated positively with high temperatures. Conversely, areas covered in vegetation and water correlated positively with low temperatures. The indices showed that correlations between the NDVI and NDWI and temperature were low (<0.5); however, a moderate correlation was found between the NDBI and temperature. View Full-Text
Keywords: heat island; land cover; brightness temperature; correlation matrix; NDVI; NDBI; NDWI heat island; land cover; brightness temperature; correlation matrix; NDVI; NDBI; NDWI
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This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

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MDPI and ACS Style

Ogashawara, I.; Bastos, V.S.B. A Quantitative Approach for Analyzing the Relationship between Urban Heat Islands and Land Cover. Remote Sens. 2012, 4, 3596-3618.

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