REMOTE SENSING FOR CROPS IDENTIFICATION
Since 2012, the INEGI began using satellite images to identify crops and to be able to locate areas where they develop. To date, this activity has been developed as a research project in which different multispectral images and different tools for the processing of satellite images have been used. Supervised classification techniques have made possible to identify the surface of some important crops of annual cycle and some perennials, such as sorghum, corn, lemon, grape, potato, orange, among others. The use of this methodology allows exploring new ways of obtaining agricultural statistical information, as well as generating statistical data that can be used to validate or confirm crop coverage at specific places. To put this project into practice, after the initial investigations, we trained a small group of people, with whom we carried out some tests to know and evaluate the benefits or disadvantages of applying identification of crops through remote sensing. Between 2012 and 2018, INEGI has received support from institutions that are more advanced in the use of remote sensors, such as NASS from the USA, StatCanada and JRC of the European Union. Tests designed by INEGI have run on sites with different topographic and climatic conditions to better understand the spectral response of crops. This document presents some of the main results obtained.