High Resolution Land Cover Mapping and Crop Classification in the Loukkos Watershed (Northern Morocco): An Approach Using SAR Sentinel-1 Time Series

Abstract

Remote sensing has become more and more a reliable tool for mapping land cover and monitoring cropland. Much of the work done in this field uses optical remote sensing data. In Morocco, active remote sensing data remain under-exploited despite their importance in monitoring spatial and temporal dynamics of land cover and crops even during cloudy weather. This study aims to explore the potential of C-band Sentinel-1 data in the production of a high-resolution land cover mapping and crop classification within the irrigated Loukkos watershed agricultural landscape in northern Morocco. The work was achieved by using 33 dual-polarized images in vertical-vertical (VV) and vertical-horizontal (VH) polarizations. The images were acquired in ascending orbits between April 16 and October 25, 2020, with the purpose to track the backscattering behavior of the main crops and other land cover classes in the study area. The results showed that the backscatter increased with the phenological development of the monitored crops (rice, watermelon, peanuts, and winter crops), strongly for the VH and VV bands, and slightly for the VH/VV ratio. The other classes (water, built-up, forest, fruit trees, permanent vegetation, greenhouses, and bare lands) did not show significant variation during this period. Based on the backscattering analysis and the field data, a supervised classification was carried out, using the Random Forest Classifier (RF) algorithm. Results showed that radiometric characteristics and 6 days’ time resolution covered by Sentinel-1 constellation gave a high classification accuracy by dual-polarization with Radar Ratio (VH/VV) or Radar Vegetation Index and textural features (between 74.07% and 75.19%). Accordingly, this study proves that the Sentinel-1 data provide useful information and a high potential for multi-temporal analyses of crop monitoring, and reliable land cover mapping which could be a practical source of information for various purposes in order to undertake food security issues.

Cartografía de cobertura del suelo mediante datos de teledetección en la planicie de desborde del río Apure (Venezuela)

“…Mediante la aplicación de tecnologías con el uso de drones, Sistemas de Posicionamiento Global (GPS), software, plataformas digitales de mapeo y manejo de datos, usadas en el territorio. En este contexto se ha utilizado la teledetección, que ha demostrado ser efectiva y se ha convertido en una herramienta cada vez más fiable en análisis y cartografía de diferentes coberturas: vegetación (Nie et al, 2018, El Mortaji et al, 2022, agua (Di Vittorio y Georgakakos, 2018), suelo (Bansal et al, 2018), entre otros. Siendo el mapeo de los tipos de suelo una de las aplicaciones más comunes (Argañaraz y Entraigas, 2011), debido a que es esencial para la generación de información acerca de su distribución en el espacio.…”