Research Papers  Abstracts 

 

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Remote Sensing and GIS Applications in Crop Sector

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Abstract

 

Availability of timely and precise information on the area and size of crops is the basic need for sound agricultural development planning and policy formulation. The main constraints in collection of data are inordinate time lags, quality concerns and a heavy overhead expenditure on manpower and wherewithal.

With introduction of RS/GIS technology in agriculture sector, Ministry of Food, Agriculture and Livestock (MINFAL) mandated Pakistan Space and upper Atmosphere Research commission (SUPARCO) to devise a satellite based Crop Reporting and Forecasting system in collaboration with stakeholders. Three contiguous districts of Bahawalpur, Rahim Yar Khan and Ghotki in the cotton –wheat cropping system were selected. Images of the program areas were obtained through constellation of SPOT satellites with resolution of 2.5 and 5 meter in panchromatic and 10 meter in multispectral mode during June, July and September 2005 for cotton and December 2005 and January 2006 for wheat crop. Ground Truthing Surveys were carried out in 15 villages from among the area frame villages, in vogue. The digitization of irrigation /communication networks and mosaicing, merging, integration, processing of the data /development of algorithm was carried out at Space Application and Research Center, Islamabd. The results were reported to MINFAL. The cotton data showed a divergence of 2.4 percent from the area reported by provinces, with lag of three months. Similar results have also been reported for wheat crop.

SUPARCO in cooperation with MINFAL and Planning Commission of Pakistan intends to further expand the program to other provinces/areas and also cover additional crops. Yield forecasting models are also being developed. The aim is to develop algorithms to provide a synoptic view of cropping systems in Pakistan by gathering temporal satellite data. This will help to minimize /alleviate the gaps in timely availability of data and also address the data quality concerns.

 
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