Does anyone know of structured and published methodologies for the identification of agricultural crop areas irrigated by Landsat8 images?
I am trying to develop a workflow to identify these areas from the surface temperature estimated by Landsat8 images. At this moment, the point is to model a process that compares the pixel context with the objective of identifying cold regions within hot regions.
How about using Evapotranspiration (ET) as a means to identify irrigated fields and possibly differentiate it from fallow, scrubland and recently harvested fields? Vegetation index (VI) and land surface temperature (LST) have been used in studies to calculate ET rates. Look at the ET map at the end of this web page https://earthobservatory.nasa.gov/Features/WaterWatchers/page4.php
Do you think such an ET map would be useful for your study?
Dear sir
You can use series of Landsat data in decision tree classifier to identify croplands.
Prezado,
Caso as áreas estejam descobertas (com solo exposto), tente um índice normalizado para destacar a umidade a partir de uma série histórica. Tente ainda, separar previamente as áreas identificando padrões geométricos típicos de áreas agricultáveis com o ENVI (classificação orientada ao objeto) para só então diferenciá-las.
Bons estudos.
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