REMOTE SENSING BASED FATA AGRICULTURAL SYSTEM CHARACTERIZATION FOR FOOD SECURITY

Abstract

Natural resources data is prepared for modeling of various kinds. The prerequisite modeling data for food security was not available so there was a need to develop the basic data of the chosen region. This research study had filled the data gap needed to characterize the agriculture system in FATA. To measure the food security it’s vital to analyze the main component i.e. crop through the remotely sensed data. Remote sensing techniques was used to demonstrate the land resources including mapping of land use land cover (LULC), surface soil texture type and crops fields and crop type identification in the region of North Waziristan Agency, South Waziristan Agency and FR Dera Ismail Khan. From LULC classification results it is infer that the region is comprised mainly of bare land that is 63% of the total area followed by vegetation (22%), water (9%) and built up i.e. only 0.2% of the total area. The classification overall accuracy achieved was 0.81 and kappa statistics shows that accuracy is 0.75. Through surface soil texture classification it is found that there are four types of texture i.e. Clay, Clay Loam, Sandy Clay Loam, present in the region. Clay Loam covers the maximum region 79% whereas Clay, sandy clay loam and loam found were 20.2%, 0.91% and 0.19% respectively. Crop fields area identified in the region is only 2.7% and 3% of the total area of NWA and SWA respectively. In the season of Rabi wheat has been identified and NDVI values observed in the region for the certain crop in the whole season was 0.12 the lowest in the sowing season and 0.42 the highest values observed in the Heading stage. Rice crop is the identified crop for the season Kharif and the NDVI values range observed was 0.13 in the sowing and 0.42 in the heading or maturing stage.