Landsat-8 (OLI) classification method based on tasseled cap transformation features

Abstract

The expected increase in world population requires a redoubling of efforts to increase agricultural yields including rice crop which is the main food of many countries of the world and in particular the countries of the Middle East. Therefore, estimating the size of the agricultural yield should be one of the first tasks of governments in the promotion of research to achieve food security and to study the obstacles resulting from environmental degradation. The Vegetation Indices (VIs) and the Tasseled Cap Transformation (TCT) features are particularly used to evaluate the presence and condition of vegetation, using satellite images. In this paper, new classification will introduced to harness these features to calculate the acreage of rice and compare them with the declared areas by the Ministry of Agriculture to make sure of their precisions. Typically, rice cultivation begins in the study area (Najaf Province) in mid-June and up to the top of the vegetative phase after 3 to 3.5 months (i.e. between September and October), then up to the harvest stage in thirty days (i.e. November). So, the present research will use Landsat-8 (Operational Land Imager OLI) images captured in September for the years 2013 and 2014 to ensure the validity of measurements. Among the many algorithms which have been developed for monitoring the biophysical characteristics of vegetation, only two of the six features of TCT (i.e. Brightness and Greenness have been adopted to use because they spectrally behave similarly like the Red and Infrared bands of the OLI images.