The primary objective of this current paper is to design, develop and automate an approach called the Hypsometrical Approach (HA). This approach automated and developed as a decision support system using environmental indicators for managing and planning water resources. It servers to analyze and to make comparison of various current and future scenarios of different quantifiable indicators for any consideration and for various socio-economic aspects. It is also used as a decision tool to improve or at least to preserve environment and natural resources. HA needs to draw its data from different sources like satellite images and watershed information system such as watershed characteristics including equipment infrastructures (Drinking water supply, irrigation system), transportation infrastructures (Roads, dams), natural resources (Water, soils, and vegetation), human activities (Agriculture, urbanization and industry) and different socio-economic factors (Demography). Globally in this paper the automation of this Hypsometrical Approach is divided into two main parts, the first part based on identifying and extracting data pixel by pixel from classified satellite images using python programming language, and the second part related to the development of a system allowing users to generate and visualize different curves called hypsometrical curves developed using Java programming language. We can combine any hypsometrical curve with arithmetic operations (addition, multiplication, subtraction and division) in order to assess some other indicators such as water resources, watershed storage capacities, vegetation, soils and forest potentials curves. Briefly, the objective of automating hypsometrical approach is to make efficient decision to improve the socio-economic level and enhance sustainable development.
CropSAT – A Decision Support System for Practical Use of Satellite Images in Precision Agriculture
