Near real‑time detection of crop fields with Modis images

Abstract

The objective of this work was to develop a method to identify and monitor, in near real‑time, crop field areas cultivated with temporary summer crops, using Modis orbital images, in the state of Rio Grande do Sul, Brazil. The methodology was called near real‑time detection of crop fields (DATQuaR) and uses Modis sensor images of the NDVI and EVI vegetation indices (VIs) from 16‑day composites. Four different metrics were used to aggregate the values of VIs per pixel, in the bimonthly periods evaluated: average, maximum, minimum, and median. To generate the images (ImDATQuaR), the aggregated image for the previous period was subtracted from the aggregated image for the monitored period. These images were classified by slicing and compared with the reference classes obtained by the visual interpretation of randomly selected pixels in Landsat images. Each ImDATQuaR image generated two DATQuaR maps: one with a 3x3 pixel window mode filter and another without filtering. The best DATQuaR map is produced using EVI images and filtering – by subtracting the image of minimum value for the previous period from the image of maximum value for the monitored period – and achieves agreement with the reference over 81%.