Corn and Soybean Recognition and an Estimation of the Planted Area, Using Remote Sensing in Dasht-e-naz Agro-industrial Company



Nowadays, remote sensing comes under the title of management method for precision farming. For provision of the land cover and therefore land use map use must be made of satellite images. For an assessment of the type of agricultural crops it is required to have satellite images of high resolution. From specifications of the satellite images one is to produce maps with varied scales. In this research, satellite images of IRS_1C, 1D within panchromatic and multispectral limits were employed. Satellite images were processed through PCI_GEOMATICA software. For an assessment of the types of the agricultural crops Leaf Area Index (LAI) was employed. Based upon the passing time of the satellite, the time for gathering information from the field was determined as 5/9/2006. Taking samples in latitude and longitude was recorded through GPS system. Following the process of exploitation of information the relationships among the bands were estimated and LAI determined. LAI comparison with ground-related information was carried out and analyzed. Then, through an assessment of the type of the agricultural crop corn and soybean were recognized through LAI. The results of this research indicated that LAI (index) could be used for a distinction of filed plant covering. It was proved that LAI could be used as a fruitful management tool in farm management planning and operations.