The New Valley Governorate suffers significantly due to its climatic and water conditions. In addition to soil salinity due to poor drainage, wind speed causes sandstorms, sand dunes move.Best practices can be identified for local policies and strategies for integrated natural resources management, sustainable agricultural management, and food security.Nowadays, technologies could not control entirely in environmental hazards but could use to manage it and reduce its consequences. Although this progress, many countries suffer from famines, and many people die from hunger. The coupling of satellite and ground data through dynamic yield prediction models can face environmental hazards and protect the community from famines. The single or multi RS parameters coupling with ground data to be inserted into simulation models to get acceptable results at regional and field scale could be improved by the rapid development of RS data in the last decades, and make it a powerful method towards large-scale data analysis and modeling. As well as, space-borne data improving, availability and diversity were adequate to precise requirements of earth observation, crop monitoring, biomass, and yield estimation and precision farming. The ET and yield data are required to produce water productivity for considered crops. Many models could be used to calculate ET from ground and satellite data (i.e., ET watch, SEBAL, SEBS, METRIC and ET look). The biomass will have measured as samples; on the other hand, the grain yield will be measured at the end of the plant life cycle. The selected samples will have harvested by the enumerator and weighed after processing appropriately, then the harvested yield rate will have calculated as the weight of the harvested crop divided by the area of the sample.The Vegetation Health Index (VHI), Crop Water Stress Index (CWSI), Leaf Area Index (LAI), Photosynthetic Active Radiation (PAR), Soil moisture, soil salinity, and biomass data will be integrated to estimate crop yield. The land surface temperature (LST) and normalized vegetation index (NDVI) will be used to indicate the VHI and CWSI. The MODIS, NOAA/AVHRR, Landsat8, Sentinel 1, 2, and 3 will be used as spaceborne data to produce vegetation and thermal parameters. The Ceptometr, thermal camera, infrared thermometer, Chlorophyll meter, TDR, ASD spectroradiometer and EM 38 will be used to measure physical parameters of soil and plant. Sustainable agriculture is a complicated process which resulted from many interacted variables. It is demanding numerous, affecting parameters beside reference series data analysis for long-term. A new innovative approach is required to settle a suitable methodology depend on multi-source parameters for precise Agri-ecosystems management practices. Using multi-source data will precise the monitoring, besides the power of remote sensing technologies in earth observation. Remote sensing technologies are promising, but still under developing in many fields. The results will be evaluated through field measurements and surveys. The main objective is Agri-systems management in the desert environment for sustainable agricultural development.