TITLE:
Forest Dynamics with Sentinel 2 in Antanambe between 2005 and 2016 with the Snap Tool
AUTHORS:
Tsiorinantenaina René Rakotoarison, Aimé Richard Hajalalaina, Elysa Nambinintsoa Safidinirina
KEYWORDS:
Random Forest, Detection Change, Remote Sensing, Forest, Madagascar
JOURNAL NAME:
Advances in Remote Sensing,
Vol.10 No.3,
September
18,
2021
ABSTRACT: In order
to protect and sustainably manage the forest in Madagascar, which is currently one of the countries still covered by
forests, it is essential to use technological advances, particularly
with regard to remote sensing. It provides valuable data, and sometimes free
with a wide range of spatial, spectral and temporal resolutions to meet the
demands for information on forest resources that are increasingly numerous and
requires ever increasing levels of accuracy. The present work presents a
methodology for the analysis of forest dynamics in the Antanambe area for the
period 2005-2016 for monitoring forest degradation in this forest area to be
conserved. The Random Forest algorithm was used to classify a Sentinel 2 image
collected on November 07, 2016 and compare with a classification result with
LandSat 5 in 2005 to detect change. The per-pixel change detection of both
results captured the change map to better interpret the situation.