Introduction

Ever since satellite remotely sensed data was available in digital format, the use of computers for analysis and interpretation of the data took roots. As the data actually depicted the state of the land as it existed at the time of observation, it was like bringing the ground to the office in the form of a picture to be studied by the various specialists. Data sets available from a variety of satellites have opened up tremendous possibilities of extracting a variety of information. In several cases of resources studies, the technique is operational, catering to several varied needs in the area of management of natural resources.

Satellite Remote Sensing and GIS Applications in Agricultural Meteorology pp. 347-359

The major advantage in using satellite remotely sensed data is that it is the latest available at any given time.

Remote sensing techniques have been operationally used in many countries to provide basic information on crops, soils, water resources and the impact of drought and flood on agriculture. Integrated studies on soil and water conservation using remote sensing and GIS have been progressing with a view to raising agricultural production. In India procedures for pre-harvest acreage estimation of major crops such as wheat, rice and sorghum, using sampling and digital techniques based on remotely sensed data have improved greatly.

The question that arises is in what respect can remote sensing be used in agricultural information systems. In fact agricultural production encompasses myriad activities related to crops, soils, water resources, climate and local weather of the region. For some of the specific themes of these disciplines, remote sensing technology has been observed to be operational and in some others some more research may be needed to enable integration into the total agricultural information system.

Mainly, an agricultural resources inventory may need some knowledge of geology and geomorphology, forestry and vegetation, land use, and land degradation information, agricultural crops, water resources and agro-meteorology. The use of remote sensing data to obtain information and produce maps on a 1:50 000 scale is almost operational in all the aspects as mentioned above.

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