Imagens do landsat- 8 no mapeamento de superfícies em área irrigada
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Data
2015-01-01
Autores
Santos, Jannaylton Éverton Oliveira [UNESP]
Nicolete, Donizeti Aparecido Pastori [UNESP]
Filgueiras, Roberto [UNESP]
Leda, Victor Costa [UNESP]
Zimback, Célia Regina Lopes [UNESP]
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Resumo
The study aims to analyze NDVI (Difference Vegetation Index Normalized) and SAVI (Soil Adjusted Vegetation Index) for two periods (rainy and dry) on irrigated area. The study area has constant expansion on irrigation center pivot, it is located near the Paranapanema - SP county. For this study we used two images of Landsat 8 orbital platform. The images were processed using QGIS 2.2 program. To obtain the indexes, it was held radiometric calibration, which is the transformation of digital numbers in corresponding physical, radiance and reflectance, and atmospheric correction using the DOS method (Dark Object Substraction). These procedures were performed on semi automatic classification plugin. After appropriate calibrations and corrections, it were computed the vegetation indexes. These gave allowance for monitoring agricultural crops in different management systems (irrigated and rainfed) and analysis of seasons (wet and dry). As an aid for monitoring areas, we merged a RGB 432 composition, with a panchromatic band. This product allowed a pre - analysis of conditions and types of land use in the study area. The maps obtained from NDVI and SAVI, allowed to infer about the physiological conditions and growth stages vegetation in different land uses. During the dry season, we found average rates which has lower values than the rainy season. This occurred, mainly, due to water stress conditions, which is characteristic of that season. Thus, the estimation of parameters for the study area were extremely valuable in analysis of vegetation conditions, on different scenarios, because through these, became possible to infer about the differences in seasons analized and different land uses. Then, these analisys served as an aid for farmers in decision making, regard the management of their areas, which is related to water requirements of crops.
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Palavras-chave
Agriculture monitoring, Center pivot, Remote sensing
Como citar
IRRIGA, v. 1, n. 2, p. 30-36, 2015.