Multi-source remote sensing data product analysis: Investigating anthropogenic and naturogenic impacts on mangroves in southeast asia
Sakti A.D.a, Fauzi A.I.b, Wilwatikta F.N.c, Rajagukguk Y.S.a, Sudhana S.A.a, Yayusman L.F.a, Syahid L.N.a, Sritarapipat T.d, Principe J.A.e, Quynh Trang N.T.f, Sulistyawati E.a, Utami I.g, Arief C.W.h, Wikantika K.a
a Remote Sensing and Geographic Information Science Research Group, Faculty of Earth Sciences and Technology, Institut Teknologi Bandung, Bandung, 40132, Indonesia
b Department of Geomatics Engineering, Faculty of Regional and Infrastructure Technology, Institut Teknologi Sumatera, Lampung, 35365, Indonesia
c Esri Indonesia, Jakarta, 12560, Indonesia
d School of Geoinformatics, Suranaree University of Technology, Nakhon Ratchasima, 30000, Thailand
e Department of Geodetic Engineering, University of The Philippines Diliman, Diliman, Quezon City, 1101, Philippines
f Department of Remote sensing, GIS and GPS, Vietnam Space Technology Institute, Hanoi, 100000, Viet Nam
g Biology Department, Faculty of Applied Science and Technology, Ahmad Dahlan University, Yogyakarta, 55166, Indonesia
h Center for Environment and Sustainability Science, Universitas Padjadjaran, Bandung, 40132, Indonesia
Abstract
© 2020 by the authors.This study investigated the drivers of degradation in Southeast Asian mangroves through multi-source remote sensing data products. The degradation drivers that affect approximately half of this area are unidentified; therefore, naturogenic and anthropogenic impacts on these mangroves were studied. Various global land cover (GLC) products were harmonized and examined to identify major anthropogenic changes affecting mangrove habitats. To investigate the naturogenic factors, the impact of the water balance was evaluated using the Normalized Difference Vegetation Index (NDVI), and evapotranspiration and precipitation data. Vegetation indices’ response in deforested mangrove regions depends significantly on the type of drivers. A trend analysis and break point detection of percentage of tree cover (PTC), percentage of non-tree vegetation (PNTV), and percentage of non-vegetation (PNV) datasets can aid in measuring, estimating, and tracing the drivers of change. The assimilation of GLC products suggests that agriculture and fisheries are the predominant drivers of mangrove degradation. The relationship between water balance and degradation shows that naturogenic drivers have a wider impact than anthropogenic drivers, and degradation in particular regions is likely to be a result of the accumulation of various drivers. In large-scale studies, remote sensing data products could be integrated as a remarkably powerful instrument in assisting evidence-based policy making.
Author keywords
Anthropogenic changes,Anthropogenic impacts,Large-scale studies,Mangrove habitats,Normalized difference vegetation index,Precipitation data,Remote sensing data,Vegetation index
Indexed keywords
Anthropogenic,Deforestation depletion,Mangrove sustainability,Natural water balance,Southeast Asia
Funding details
[{‘$’: ‘Funding: This project was funded by Kurita Asia Research Grant (19Pid017) provided by Kurita Water and Environment Foundation, and PMDSU scholarship from the Ministry of Research, Technology and Higher Education Indonesia (RisetDikti).’}, {‘$’: ‘This project was funded by Kurita Asia Research Grant (19Pid017) provided by Kurita Water and Environment Foundation, and PMDSU scholarship from the Ministry of Research, Technology and Higher Education Indonesia (RisetDikti). The authors are grateful to acknowledge the support from KuritaWater and Environment Foundation and the Ministry of Research, Technology and Higher Education Indonesia. We also thank the anonymous reviewers whose valuable comments greatly helped us to prepare an improved and clearer version of this paper. All persons and institutes who kindly made their data available for this analysis are acknowledged.’}, {‘$’: ‘Acknowledgments: The authors are grateful to acknowledge the support from Kurita Water and Environment Foundation and the Ministry of Research, Technology and Higher Education Indonesia. We also thank the anonymous reviewers whose valuable comments greatly helped us to prepare an improved and clearer version of this paper. All persons and institutes who kindly made their data available for this analysis are acknowledged.’}]