JAXA Annual Forest Cover Maps for Vietnam during 2015–2018 Using ALOS-2/PALSAR-2 and Auxiliary Data
1
Center for VNU Development at Hoa Lac Campus—Vietnam National University, Hanoi, Thach Hoa Commune, Thach That District, Hanoi 155500, Vietnam
2
Graduate School of Life and Environmental Sciences, University of Tsukuba, Tennoudai 1-1-1, Tsukuba, Ibaraki 305-8572, Japan
3
Hydraulic Construction Institute—Vietnam Academy for Water Resources, No. 3, Alley 95, Chua Boc Street, Dong Da district, Hanoi 116765, Vietnam
4
Earth Observation Research Center, Japan Aerospace Exploration Agency (JAXA), 2-1-1 Sengen, Tsukuba, Ibaraki 305-8505, Japan
5
Faculty of Life and Environmental Sciences, University of Tsukuba, Tennoudai 1-1-1, Tsukuba, Ibaraki 305-8572, Japan
*
Author to whom correspondence should be addressed.
Remote Sens. 2019, 11(20), 2412; https://doi.org/10.3390/rs11202412
Received: 21 September 2019 / Revised: 13 October 2019 / Accepted: 15 October 2019 / Published: 17 October 2019
(This article belongs to the Special Issue Advanced Geospatial Artificial Intelligence for Forest Modeling, Prediction, Conservation and Management)
Monitoring the temporal changes of forests is important for sustainable forest management. In this study, we investigated the potential of using multi-temporal synthetic aperture radar (SAR) images for mapping annual change in forest cover at a national scale. We assessed the robustness of using multi-temporal Phased Array L-band Synthetic Aperture Radar-2/Scanning Synthetic Aperture Radar (PALSAR-2/ScanSAR) mosaic images for forest mapping by comparison with single-temporal PALSAR-2 mosaic images for three test sites in North, Central, and Southern Vietnam. We then used a combination of multi-temporal PALSAR-2/ScanSAR images, multi-temporal Moderate Resolution Imaging Spectroradiometer (MODIS) Normalized Difference Vegetation Index (NDVI) images, and Shuttle Radar Topography Mission (SRTM) images to map annual forest cover for mainland Vietnam during 2015–2018. Average overall accuracies of our forest/non-forest (FNF) maps (86.6% ± 3.1%) were greater than recent maps of Japan Aerospace Exploration Agency (JAXA, (77.5% ± 3.2%)) and European Space Agency (ESA, (85.4% ± 1.6%)). Our estimates of mainland Vietnam’s forest area were close to that of the Vietnamese government. A comparison of the spatial distribution of forest estimated from JAXA and ESA FNF maps showed that our FNF map in 2015 agreed relatively well with the ESA map, with 77% of pixels being consistent. This study demonstrates the merit of using multi-temporal PALSAR-2/ScanSAR images for annual forest mapping at a national scale.
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Keywords:
forest cover; annual mapping; Vietnam; PALSAR-2; ScanSAR; MODIS NDVI; SRTM
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MDPI and ACS Style
Truong, V.T.; Hoang, T.T.; Cao, D.P.; Hayashi, M.; Tadono, T.; Nasahara, K.N. JAXA Annual Forest Cover Maps for Vietnam during 2015–2018 Using ALOS-2/PALSAR-2 and Auxiliary Data. Remote Sens. 2019, 11, 2412. https://doi.org/10.3390/rs11202412
AMA Style
Truong VT, Hoang TT, Cao DP, Hayashi M, Tadono T, Nasahara KN. JAXA Annual Forest Cover Maps for Vietnam during 2015–2018 Using ALOS-2/PALSAR-2 and Auxiliary Data. Remote Sensing. 2019; 11(20):2412. https://doi.org/10.3390/rs11202412
Chicago/Turabian StyleTruong, Van T.; Hoang, Thanh T.; Cao, Duong P.; Hayashi, Masato; Tadono, Takeo; Nasahara, Kenlo N. 2019. "JAXA Annual Forest Cover Maps for Vietnam during 2015–2018 Using ALOS-2/PALSAR-2 and Auxiliary Data" Remote Sens. 11, no. 20: 2412. https://doi.org/10.3390/rs11202412
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