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Study of Forest Cover Change Dynamics between 2000 and 2015 in the Ikongo District of Madagascar Using Multi-Temporal Landsat Satellite Images 被引量:1

Study of Forest Cover Change Dynamics between 2000 and 2015 in the Ikongo District of Madagascar Using Multi-Temporal Landsat Satellite Images
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摘要 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<span><span><span style="font-family:;" "=""> </span></span></span><span style="font-family:Verdana;"><span style="font-family:Verdana;"><span style="font-family:Verdana;">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.</span></span></span> 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<span><span><span style="font-family:;" "=""> </span></span></span><span style="font-family:Verdana;"><span style="font-family:Verdana;"><span style="font-family:Verdana;">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.</span></span></span>
作者 Aimé Richard Hajalalaina Arisetra Razafinimaro Nicolas Ratolotriniaina Aimé Richard Hajalalaina;Arisetra Razafinimaro;Nicolas Ratolotriniaina(Department of Computer Science, Ecole de Management et d’Innovation Technologique (EMIT), University of Fianarantsoa, Fianarantsoa, Madagascar;Laboratoire d’Informatique et des Mathématiques Appliqués au Développement (LIMAD), University of Fianarantsoa, Fianarantsoa, Madagascar;Informatique-Géomatique, Mathematiques et Applications (IGMA), University of Fianarantsoa, Fianarantsoa, Madagascar)
出处 《Advances in Remote Sensing》 2021年第3期78-91,共14页 遥感技术进展(英文)
关键词 Remote Sensing Image Processing Change Detect MULTI-TEMPORAL LANDSAT Forest Covert Remote Sensing Image Processing Change Detect Multi-Temporal Landsat Forest Covert
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