SENTINEL-1 AND SENTINEL-2 TIME SERIES PROCESSING CHAINS FOR CYCLONE IMPACT MONITORING IN SOUTH WEST INDIAN OCEAN

Nevertheless, different representation models for satellite images can be defined, i.e., based on complex network models, which may allow to discover new relations between the

The method is applied using two intra-annual multispectral or NDVI time series of SPOT5 Take5 (18 dates) and Sentinel-2 (7 dates) to predict the Shannon and the Simpson indices of

The seasonal restitution of the areas of inundated rice and other irrigated crops from multi-temporal high resolution satellite remote sensing is thus a promising method for

Radar data are mainly sensitive to soil moisture and soil roughness, and has also been evaluated for its ability to perform texture measurements. The aim of

Using the tree classification method based on the SVM with the mean value, variance, and correlation length for both VV and VH polarization as input, three classes,

A Decision Tree classification is then used to produce irrigation maps with several simulations based on these parameters, for three specific cases: a classification based on mean

This study proposes a method for detecting irrigated and rainfed plots in a temperate area (southwestern France) jointly using optical (Sentinel-2), radar (Sentinel-1)

In this study we mapped rice areas in the Camargue region using Sentinel-1 SAR backscattering time series and two classification approaches: random forest and decision tree.. We