Remote sensing based water resources and agriculture spatial indicators system

Abstract

Integrated automated application for Water Resources and Agriculture Spatial Indicators System (WRASIS) using remote sensing Data was developed to monitor and assess different developments projects in agriculture field. This system is based on the analysis of remotely sensed time series data of (Agriculture Moderate Resolution Imaging Spectra-radiometer MODIS NDVI – Rain-Fall Estimate RFE 2.0). Three agriculture projects located in Sudan; White Nile sub-basin “Assalaya Project (AAP)”, Wadi Halfa (WHAP) at Atbara Basin, and Ginude agriculture project at Blue Nile sub-basin are taken for pilot study using this newly developed system which is includes GIS-based procedures for computing water and agriculture spatial indicators. The data used is derived from satellite images product at different spatial and temporal resolution. These products were extracted automatically and stored with their analyses and results in special database, which could be used with easily manner to obtain and compute indicators and perform statistical data analyses. WRASIS has specific tools to analyze and display data in a tabular form, classify maps and display statistical charts as well. WRASIS runs in three main phases; data-base preparation, model calculation (data analysis), and finally system tools and outputs. The outputs are either basic indicators (one indicator for one-time step) or advanced indicators. Many satellite images with diverse products and resolutions could be added to the system in data preparing phase for other applications at any area. In the present study and from monitoring and assessments of the three agriculture projects, the effect of supplementary irrigation is clear.

Keywords

• Normalized difference vegetation index
• Agriculture projects
• Remote sensing
• Rainfall