To study certain impacts of meteorological hazards on agriculture and forestry and improve our understanding of certain preparedness issues, use of remote sensing data is a precious tool in obtaining spatial information on areas of interest where ground measurements are difficult. Moreover, additional information on the land may be essential in establishing its sensitivity to water excess or deficit, water and wind erosion, and the risks of soil degradation. In recent years, many investigations have demonstrated the capability of satellite-borne sensors to provide information on various crop indicators, which help to monitor and identify crop stress more effectively. For example during drought conditions, physiological changes within vegetation may become apparent, tte National Remote Sensing Agency (NRSA) in India is using a vegetation index to determine vigor of vegetation. Condition of the crop is affected by factors such as supply of water and nutrients, insect/pest attack, disease outbreak and weather conditions, ttese stresses cause physiological changes, which alter the spectral properties of leaf/canopy, tte task of crop condition assessment requires (i) detection of stress, (ii) differentiation of stressed crop from normal crop at a given time (iii) quantification of extent and severity of stress, and (iv) assessment of the production loss. Crop stress conditions are often better characterized through the use of spectral Vegetation Indices (VI) in comparison to use of individual spectral bands.
Many factors affect crops, most of which are time and space-dependent so that they can be represented as maps e.g. physiography, soil type, soil fertility, depth-to-ground water table, slope of the area, date of sowing and application of irrigation. All these factors can be represented in the form of maps, ttese maps can be combined (integrated) and analyzed using GIS to find the potentiality of the area for a particular crop and expected crop yield. It is a challenge that suitability of various crops can be estimated by integrating various factors affecting them under GIS environment, simultaneously evaluating agrometeorological risks and suggesting alternative crops or cropping systems for an area.
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