Abstract
Abstract: The objective of this work was to evaluate the applicability of time series of the enhanced vegetation index (EVI), from the moderate resolution imaging spectroradiometer (Modis), in the mapping of irrigated areas in the Northeastern region of Brazil. Annual time series from 2006 to 2015 were classified with the iterative self-organizing data analysis technique (Isodata) algorithm, generating a binary map of irrigated and nonirrigated areas for each year. In the Sertão region, the classification showed an average kappa coefficient of 0.66, underestimating the irrigated area by 7.6%, compared with data of the 2006 agricultural census. In regions more humid than the Sertão, such as Agreste and Zona da Mata Nordestina, the methodology showed limitations to distinguish irrigated areas from natural vegetation, presenting average kappa coefficients of 0.26 and 0.00, respectively. The EVI time series from Modis are applicable for the mapping of irrigated areas in the Sertão of the Northeastern region of Brazil.
Highlights
The monitoring of irrigated agriculture, including information on its spatial and temporal distribution, is essential for the management of water resources, hydrological watershed modeling, and agricultural and environmental planning (Biggs et al, 2006; Ozdogan et al, 2010).Usually, quantitative information about irrigated areas is derived from census data based on which it is impossible to depict the interannual dynamics of these areas (Dheeravath et al, 2010)
In Brazil, Embrapa carried out studies at a national level in partnership with Agência Nacional de Águas (ANA) using images from the Landsat satellite
The objective of this work was to evaluate the applicability of time series of the enhanced vegetation index (EVI), from the moderate resolution imaging spectroradiometer (Modis),in the mapping of irrigated areas in the Northeastern region of Brazil
Summary
The monitoring of irrigated agriculture, including information on its spatial and temporal distribution, is essential for the management of water resources, hydrological watershed modeling, and agricultural and environmental planning (Biggs et al, 2006; Ozdogan et al, 2010).Usually, quantitative information about irrigated areas is derived from census data based on which it is impossible to depict the interannual dynamics of these areas (Dheeravath et al, 2010). The monitoring of irrigated agriculture, including information on its spatial and temporal distribution, is essential for the management of water resources, hydrological watershed modeling, and agricultural and environmental planning (Biggs et al, 2006; Ozdogan et al, 2010). Initiatives of the International Water Management Institute stand out (Thenkabail et al, 2009), including global mapping of irrigated areas at 10 km spatial resolution. In Brazil, Embrapa carried out studies at a national level in partnership with Agência Nacional de Águas (ANA) using images from the Landsat satellite. These studies were limited to the mapping of areas irrigated by the central pivot system (ANA, 2016).
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