Abstract
Satellite images are considered reliable data that preserve land cover information. In the field of remote sensing, these images allow relevant analyses of changes in space over time through the use of computer tools. In this study, we have applied the “discriminant” change detection algorithm. In this, we have verified its effectiveness in multi-temporal studies. Also, we have determined the change in forest dynamics in the Ikongo district of Madagascar between 2000 and 2015. During the treatments, we have used the Landsat TM satellite images for the years 2000, 2005 and 2010 as well as ETM+ for 2015. Thus, analyses carried out have allowed us to note that between 2000-2005, 1.4% of natural forest disappeared. And, between 2005-2010, forests degradation was 1.8%. Also, between 2010-2015, about 0.5% of the natural forest conserved in 2010 disappeared. Furthermore, we have found that the discriminant algorithm is considerably efficient in terms of monitoring the dynamics of forest cover change.
Highlights
We have found that the discriminant algorithm is considerably efficient in terms of monitoring the dynamics of forest cover change
Our study focuses on the implementation of the function change discriminant algorithm to detect change in the natural forest dynamics of Ikongo District
We set a main objective to evaluate the efficiency of this algorithm by analysing Multi-temporal satellite images
Summary
Since the last two decades, remote sensing has been widely used to detect changes. Thanks to the availability of satellite imagery researchers can perform multi-temporal and time series change studies [5] [6]. Computer-based techniques are able to determine the effects of a phenomenon in an area at different dates [7] [8]. The change detection algorithm is one of the techniques that can carry out this work. The forestry domain really requires the intervention of the change detection algorithm to quantify changes
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