An-Najah National University

mohnd naim mhmad miala

 

 
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  • Friday, February 13, 2009
  • Crop Area Estimation for the Northern West Bank, Palestine Using Satellite Remote Sensing
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  • CROP AREA ESTIMATION FOR THE NORTHERN WEST BANK, PALESTINE USING SATELLITE REMOTE SENSING

    AR. M. M. Ghodieh

     

    Dept. of Geography, An-Najah National University, Nablus, Palestine, [email protected]

     

    KEY WORDS: Crop, West Bank, Palestine, Remote Sensing, Spot, Classification

     

    ABSTRACT

    This paper investigates the use of satellite data for crop area estimation in the northern part of the West Bank, Palestine. The satellite data were obtained by the SPOT HRV (High Resolution Visible) on 19 May 1994. The satellite data were geometrically corrected to the Palestine Grid using 1: 50,000 Israeli topographic maps. The study investigated the ability of SPOT HRV data to produce accurate crop area estimation of the northern part of the West Bank that is characterized with small field sizes and complex physical environment. The study area was divided into five strata and training data were selected using field survey, aerial photographs, maps, and interviewing farmers.

     

    A land cover classification scheme appropriate to the study area was designed. Twenty three land cover classes were produced from the SPOT HRV classification. Land cover classes were developed to produce thematic land use classes. The classification accuracy obtained from SPOT HRV image classification was 81%. Classification results were assessed by using the known land use information obtained from the field during the training stage. The results were analyzed on stratum and crop type basis. Remote sensing and thematic agricultural perspectives were used in the analysis.

    Results of the study suggest that it is possible to improve image classification accuracy by using better spatial and spectral resolution imagery and the integration of remote sensing data with agricultural data using the Geographical Information Systems (GIS).

     
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