Remote sensing techniques for surveying and change detection of Cassava area

Abstract

The study’s primary objectives about remote sensing techniques for surveying and change detecting of cassava area were to classify cassava area and its change in 2015-2020. To fulfill the objectives, cassava area and other land use in 2015 and 2020 classified from Landsat 8 data with supervised classification technique. The results detected its change with the post-classification comparison technique. As a result, cassava areas in 2015 and 2020 were 155,944.69 rai or 62.13%, 156,438.00 rai or 62.33% of the study area, and a kappa hat coefficient was about 82.49 and 81.29, respectively. Meanwhile, cassava area change detected during 2015 to 2020 wasn’t changed by approximately 124,281.56 rai, cassava area changed to another agricultural land about 31,376.25 rai, forest land 235.13 rai and water body about 51.75 rai. In contrast, cassava area changed from agricultural land, forest land, and waterbody approximately 31,929.19 rai, 89.44 rai, and 137.81 rai.