Land use mapping from CBERS-2 images with open source tools by applying different classification algorithms

Publication date: Available online 29 December 2015 Source:Physics and Chemistry of the Earth, Parts A/B/C Author(s): Antonio J. Sanhouse-Garcia, Jesús Gabriel Rangel-Peraza, Yaneth Bustos-Terrones, Alfonso García-Ferrer, Francisco J. Mesas-Carrascosa Land cover classification is often based on different characteristics between their classes, but with great homogeneity within each one of them. This cover is obtained through field work or by mean of processing satellite images. Field work involves high costs; therefore, digital image processing techniques have become an important alternative to perform this task. However, in some developing countries and particularly in Casacoima municipality in Venezuela, there is a lack of geographic information systems due to the lack of updated information and high costs in software license acquisition. This research proposes a low cost methodology to develop thematic mapping of local land use and types of coverage in areas with scarce resources. Thematic mapping was developed from CBERS-2 images and spatial information available on the network using open source tools. The supervised classification method per pixel and per region was applied using different classification algorithms and comparing them among themselves. Classification method per pixel was based on Maxver algorithms (maximum likelihood) and Euclidean distance (minimum distance), while per region classification was based on the Bhattacharya algorithm. Satisfac...
Source: Physics and Chemistry of the Earth, Parts ABC - Category: Science Source Type: research