Abstract
This paper focuses on the Landsat 8 satellite image classification of the OLI sensor via the remote sensing software Erdas Imagine in order to calculate the land cover surface and to establish the mapping of the special reserve Kalambatritra of Madagascar for the year 2018. For this, we adopted the methodology of satellite image processing based on supervised classification algorithms. The processing was moved to spectral preparation and improvement of spatial resolution using the blue, green, red, near infrared and panchromatic channels. Then, a comparison study of the supervised classification algorithms was done to obtain a more accurate result. The validation of the classification results was performed using several reference points, a previous national processing result already validated in the field and the Google earth image of the same year. After repeating the classification several times, we obtained accuracies of 77%, 75%, 88%, 84% and 90% with Kappa indices of 0.64, 0.61, 0.80, 0.76 and 0.84 for the Spectral Angle Mapper, Spectral Correlation Mapper, Maximum Likelihood, Mahalanobis Distance and Minimum Distance. Based on these results, the minimum distance showed a higher accuracy and gave us 13462.1842 ha of forest area, 16798.8006 ha of prairie for the year 2018.
Highlights
Supervised classification is a very important means in satellite image processing for mapping land use and determining forest area
Several scientific works have carried out experiments on these images such as the article used Landsat 7 ETM+ image to detect a wetland in Malagasy forest [1], and used SPOT images to detect land use changes in the humid forest [2]
We need a satellite image that we choose from the Landsat 8 satellite image year 2018 because this image is free of charge and its characteristic is highly suitable for forest area classification
Summary
Supervised classification is a very important means in satellite image processing for mapping land use and determining forest area. For this purpose, images from SPOT, Landsat, Terra, Sentinel satellites are useful and allow this work because they are rich in spectral and spatial information at the same time. Our Kalambatritra study area is located in the South-East zone of Madagascar It is characterized as low altitude dense forest. This zone is often victim to human acts such as charcoal, Tavy cultivation, bushfires. We carry out the treatments with the ERDAS imagine The results of our experiments show that the precision can be higher with the algorithm of minimum distance with a Kappa index of 0.84
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