Investigating the Time Series OLI multi Spectral Sensor Data Capability with the Step by Step Method for Producing the Major Cultivation Map (A Case Study: Chadegan City)

Determining the cultivation crops area is important for properly supplying crops. The aim of this study was mapping the cultivation area crops in Chadian city for spring and summer during 2015 by using the time series data of the Landsat 8 satellite of OLI imagery. At first, the under cultivation area was determined by setting a low threshold in the marginal pixels of the agricultural rain fed in the spring image NDVI index. The area cultivated with wheat and alfalfa was prepared by subtracting spring and summer NDVI values. Cultivation maps, which were cultivated with potatoes, corn and orchards, were prepared using the supervised classification with the FISHER method in a step by step manner. Spring and summer cultivation maps were combined; finally, the major cultivation crops maps were produced by the hybrid classification method. Map accuracy assessment was done by producing error matrix and calculating kappa coefficient, total accuracy, commission and omission error, producer, and use accuracy; in all indices, they had an acceptable value, showing the capability of OLI and the used methods in separating each cultivation.