Inter Islamic Network on Space Sciences and Technology


  • Azerbaijan
  • Bangladesh
  • Egypt
  • Indonesia
  • Iran
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Technical Projects / Land Change Modeling based on Satellite Remote Sensing

 Land Change Modeling based on Satellite Remote Sensing


1. Scope. Scope of the project encompasses conception and development of a spatial land change model with consequent systematic and formal studies of possible future urban sprawl developments and trends for major cities of ISNET countries to provide a basis for the preparation and evaluation of requisite urban policies.

2. Overall Objectives. To examine the spatio-temporal patterns of urban Land Use / Land Cover (LULC) changes using Satellite Remote Sensing (SRS) data i.e. PRSS-1 and / or any other available data along with allied Geospatial data layers and future simulations for major cities of ISNET countries to expound their implications for urban sustainability.

3. Technical Description.

  1. Land change modeling is an innovative land planning and decision support tool for land change analysis and prediction. This type of modeling is used to model the changes in LULC over the past and predict the future trends in urbanization by incorporating dynamic variables that drive or explain change.
  2. By using satellite dat for temporal images, land cover maps for various years are generated by known classification methodologies (supervised or unsupervised). Then, by approximating the reasonable change in each pixel, the transition potential maps are generated. For any year, a prediction map can be produced by using artificial neural networks complimented with secondary datasets i.e. (road networks, Digital Elevation Models, water lines, Hillshades and slopes / aspect etc).
  3. Work flow of the proposed land change model shall comprise following components:
    • (1) Creating maps of urbanization by comparing LULC maps at two or more time periods.
    • Analysis of relationships between urbanization and drivers in order to select "best" explanatory variables (termed as 'driving factors')
    • Calibration of the model.
    • (4) Assessment of the model performance (comparison between actual and predicted maps for previous years).
    • (5) Simulation (running the model to obtain a map of urban growth which predicts the urbanization for the given target ADI over a given time period)
4. Expected Benefits. Following benefits could be expected from this project:-
  1. Capacity building of the member countries in use of Remote Sensing and GIS for natural resources monitoring and use of modern data dissemination techniques.
  2. Obtained results and the developed methodical approaches will be important in increasing monitoring efficiency in other socioeconomic areas and will serve food security.
  3. The study and management of soil and ecological condition will save time and financial resources in efficient use. It will be useful in preparation of measures and government programs for the improving soil-ecological condition.
  4. It will serve collection, easily usage, protection and transmission through the network of relevant knowledge in a single Database.


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