25 October 2016 Biophysical indicators based on satellite images in an irrigated area at the São Francisco River Basin, Brazil
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Abstract
The Jaíba Irrigated Perimeter is a large irrigated agriculture area, located in the region Forest Jaíba between the São Francisco and Verde Grande rivers, in the Brazilian semi-arid region. In 2014, irrigators this the region face losses in the interruption of new plantings in irrigated areas due to water scarcity. The objective of this study is combine the model to estimate the Monteith BIO with the SAFER algorithm in the case of obtaining ET, to analyze the dynamics of natural vegetation and irrigated crops in water scarcity period. For application of the model are necessary data from meteorological stations and satellite images. Were used 23 satellite images of MODIS with spatial resolution of 250m and temporal 16 days, of 2014 year. For analyze the results, we used central pivots irrigation mask of Minas Gerais state, Brazil. In areas with irrigated agriculture with central pivot, the mean values of BIO over the year 2014 were 88.96 kg.ha-1.d-1. The highest values occurred between April 23 and May 8, with BIO 139 kg.ha-1.d-1. For areas with natural vegetation, the average BIO was 88.34 kg.ha-1.d-1 with lower values in September. Estimates of ET varied with the lowest values of ET observed in natural vegetation 1.91±1.22 mm.d-1 and the highest values in irrigated area is observed 3.51±0.97 mm.d-1. Results of this study can assist in monitoring of river basins, contributing to the management irrigated agriculture, with the trend of scarcity of water resources and increasing conflicts for the water use.
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Janice F. Leivas, Janice F. Leivas, Antônio Heriberto C. Teixeira, Antônio Heriberto C. Teixeira, Gustavo Bayma-Silva, Gustavo Bayma-Silva, Carlos Cesar Ronquim, Carlos Cesar Ronquim, João Batista Ribeiro da Silva Reis, João Batista Ribeiro da Silva Reis, } "Biophysical indicators based on satellite images in an irrigated area at the São Francisco River Basin, Brazil", Proc. SPIE 9998, Remote Sensing for Agriculture, Ecosystems, and Hydrology XVIII, 99981N (25 October 2016); doi: 10.1117/12.2241320; https://doi.org/10.1117/12.2241320
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