Project: Pan Moroccan Yield and Precipitation Gaps Platform and App (PAMOCPP) • Development of a new hybrid model for corn yield gap estimation using Deep neural network (DNN) and AQUACROP, Sentinel-2 reflectance, sentinel -1 ARD (VV, VH, VVVH), Crop biophysical variables derived from MODIS (LAI and Fpar), weather data obtained from CFSv2, and field scale Statistics;

Project: Corn monitoring using Remote Sensing and Machine Learning

- installation of a geoservice for the spatiotemporal monitoring of crops;- installation of a geoservice for the management and audit of agricultural water.

Contribution to the study of the potential of Machine Learning algorithms for the prediction of phytomass from remote sensing indicators (biophysical variables and vegetation indices)- Phyto-ecological inventory of the region SOUSS MASSA and DRAA Morocco;- Application of the radiative transfer model (PROSAIL) to extract the biophysical variables: LAI, FAPAR, Chlorophyll ab, Canopy water content, and Fraction covered by vegetation through an ANN neural network;- Extraction of NDVI, SAVI, MSAVI, ATSAVI vegetation indices from a cloud-free SENTINEL 2A image using the S2cloudless algorithm on the Google Earth Engine(GEE) platform;- Preparation and visualization (data wrangling), and analysis of geospatial databases using the tidyverse,dplyr and ggplot libraries;- Evaluation of algorithms (Multiple linear regression, regularization method, dimension reduction method:Principal Component Regression (PCR), Partial Least Squares Regression (PLSR), tree models: Bagged trees, Random forest) for predicting phytomass.

Contribution to the elaboration of a development plan for rangelands and livestock in the DRAA-TAFILALT region Morocco- Development of a monitoring and evaluation system : Logical Framework, Objectives Tree, and DPSIR framework;- Selection and prioritization of indicators;- Elaboration of matrices adapted to the study context

- Description and analysis of plant and animal production systems- Description and socio-economic analysis of a farm- Supervision of farmers