全部 标题 作者
关键词 摘要

OALib Journal期刊
ISSN: 2333-9721
费用:99美元

查看量下载量

相关文章

更多...

Forest Dynamics with Sentinel 2 in Antanambe between 2005 and 2016 with the Snap Tool

DOI: 10.4236/ars.2021.103006, PP. 92-101

Keywords: Random Forest, Detection Change, Remote Sensing, Forest, Madagascar

Full-Text   Cite this paper   Add to My Lib

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.

References

[1]  Bouvier, M., Durrieu, S., Fournier, R.A. and Renaud, J.P. (2015) Generalizing Predictive Models of Forest Inventory Attributes Using an Area-Based Approach with Airborne LiDAR Data. Remote Sensing of Environment, 156, 322-334.
https://doi.org/10.1016/j.rse.2014.10.004
[2]  Giri, C. and Muhlhausen, J. (2008) Mangrove Forest Distributions and Dynamics in Madagascar (1975-2005). Sensors, 8, 2104-2117.
https://doi.org/10.3390/s8042104
[3]  Grinand, C., Rakotomalala, F., Gond, V., Vaudry, R., Bernoux, M. and Vieilledent, G. (2013) Estimating Deforestation in Tropical Humid and Dry Forests in Madagascar from 2000 to 2010 Using Multi-Date Landsat Satellite Images and the Random Forests Classifier. Remote Sensing of Environment, 139, 68-80.
https://doi.org/10.1016/j.rse.2013.07.008
[4]  Hajalalaina, A.R., Grizonnet, M., Delaitre, E., Rakotondraompiana, S. and Herve, D. (2013) Discrimination des zones humides en foret malgache, proposition d’une methodologie multiresolution et multisource utilisant orfeo toolbox. Revue Française de Photogrammétrie et de Télédétection, 201, 37-48.
https://doi.org/10.52638/rfpt.2013.44
[5]  Razafinimaro, A., Hajalalaina, A.R., Reziky, Z.T., Delaitre, E. and Andrianarivo, A. (2021) Landsat8 Satellite Image Classification with ERDAS for Mapping the Kalambatritra Special Reserve. American Journal of Remote Sensing, 9, 16.
[6]  Waeber, P.O., Wilmé, L., Ramamonjisoa, B., Garcia, C., Rakotomalala, D., Rabemananjara, Z.H., Kull, C.A., Ganzhorn, J.U. and Sorg, J.P. (2015) Dry Forests in Madagascar: Neglected and under Pressure. International Forestry Review, 17, 127-148.
https://doi.org/10.1505/146554815815834822
[7]  WCS, ONE, MNP, ETC (2014) Analyse Historique de la déforestation: 2005-2010-2013.
https://bnc-redd.mg/images/documents/rapports/20170822/141210-FCC_051013_PERR-FH_2014.pdf
[8]  Gandhi, G.M., Parthiban, S., Thummalu, N. and Christy, A. (2015) Ndvi: Vegetation Change Detection Using Remote Sensing and Gis—A Case Study of Vellore District. Procedia Computer Science, 57, 1199-1210.
https://doi.org/10.1016/j.procs.2015.07.415
[9]  Ngom, R. and Gosselin, P. (2013) Development of a Remote Sensing-Based Method to Map Likelihood of Common Ragweed (Ambrosia artemisiifolia) Presence in Urban Areas. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 7, 126-139.
https://doi.org/10.1109/JSTARS.2013.2254469
[10]  Perumal, K. and Bhaskaran, R. (2010) Supervised Classification Performance of Multispectral Images. arXiv:1002.4046.
[11]  Breiman, L. (2001) Random Forests. Machine Learning, 45, 5-32.
https://doi.org/10.1023/A:1010933404324
[12]  Dalmiya, C.P., Santhi, N. and Sathyabama, B. (2019) A Novel Feature Descriptor for Automatic Change Detection in Remote Sensing Images. The Egyptian Journal of Remote Sensing and Space Science, 22, 183-192.
https://doi.org/10.1016/j.ejrs.2018.03.005
[13]  Stehman, S.V. and Foody, G.M. (2019) Key Issues in Rigorous Accuracy Assessment of Land Cover Products. Remote Sensing of Environment, 231, 111199.
https://doi.org/10.1016/j.rse.2019.05.018
[14]  Negassa, M.D., Mallie, D.T. and Gemeda, D.O. (2020) Forest Cover Change Detection Using Geographic Information Systems and Remote Sensing Techniques: A Spatio-Temporal Study on Komto Protected Forest Priority Area, East Wollega Zone, Ethiopia. Environmental Systems Research, 9, 1.

Full-Text

Contact Us

service@oalib.com

QQ:3279437679

WhatsApp +8615387084133