Characterization of crop rotations in irrigation areas of the Ebro Valley from temporal series of Landsat TM images

Jose A Martinez-Casasnovas; Almudena Martin-Montero

doi:10.1117/12.514008

24 February 2004 Characterization of crop rotations in irrigation areas of the Ebro Valley from temporal series of Landsat TM images

Jose A Martinez-Casasnovas, Almudena Martin-Montero

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Proceedings Volume 5232, Remote Sensing for Agriculture, Ecosystems, and Hydrology V; (2004) https://doi.org/10.1117/12.514008
Event: Remote Sensing, 2003, Barcelona, Spain

Abstract

The present paper presents a method to characterize typical crop rotations from temporal series analysis of land use maps derived from supervised classifications of Landsat TM images. The analysis is based on spatial cross-tabulation of land use maps in raster format. As a case study, a temporal land use map series from 1993 to 2000 of the Flumen irrigation area (Huesca, Spain) was considered. The spatial cross-tabulation analysis between each pair of consecutive land use maps, performed in Idrisi 32, yielded a two dimensional matrix that allowed the identification of the typical crop rotations in the study area. Those are rice - fallow land - rice, sunflower - winter cereals - alfalfa - corn, and others as winter cereal or sunflower - fallow land - corn or alfalfa. Rice appears as a typical crop in this area, in which it is usually associated to salt- and/or sodium-affected soils. Those typical rotations have been also spatially located and represented in a map following the crop changes from one year to another year that are registered in the cross-tabulation images. The method can be useful to identify tendencies in the temporal variation of crop rotations in agricultural areas, and to locate typical areas with salt- and/or sodium-affected soils by mapping rotations in which rice is the main crop.

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Jose A Martinez-Casasnovas and Almudena Martin-Montero "Characterization of crop rotations in irrigation areas of the Ebro Valley from temporal series of Landsat TM images", Proc. SPIE 5232, Remote Sensing for Agriculture, Ecosystems, and Hydrology V, (24 February 2004); https://doi.org/10.1117/12.514008

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KEYWORDS

Earth observing sensors

Landsat

Agriculture

Image classification

Raster graphics

Satellites

Remote sensing

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