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Article

New JAXA High-Resolution Land Use/Land Cover Map for Vietnam Aiming for Natural Forest and Plantation Forest Monitoring

1
Viet Nam Institute of Meteorology, Hydrology and Climate Change, No.23–62 Alley, Nguyen Chi Thanh Road, Dong Da District, Hanoi 117257, Vietnam
2
Graduate School of Life and Environmental Sciences, University of Tsukuba, Tennoudai 1-1-1, Tsukuba, Ibaraki 305-8572, Japan
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VNU Center for Development in Hoa Lac, Vietnam National University, Hanoi, Thach Hoa Commune, Thach That District, Hanoi 155500, Vietnam
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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. 2020, 12(17), 2707; https://doi.org/10.3390/rs12172707
Received: 23 July 2020 / Revised: 17 August 2020 / Accepted: 19 August 2020 / Published: 21 August 2020
Highly detailed and accurate forest maps are important for various applications including forest monitoring, forestry policy, climate change, and biodiversity loss. This study demonstrates a comprehensive and geographically transferable approach to produce a 12 category high-resolution land use/land cover (LULC) map over mainland Vietnam in 2016 by remote sensing data. The map included several natural forest categories (evergreen broadleaf, deciduous (mostly deciduous broadleaf), and coniferous (mostly evergreen coniferous)) and one category representing all popular plantation forests in Vietnam such as acacia (Acacia mangium, Acacia auriculiformis, Acacia hybrid), eucalyptus (Eucalyptus globulus), rubber (Hevea brasiliensis), and others. The approach combined the advantages of various sensor data by integrating their posterior probabilities resulting from applying a probabilistic classifier (comprised of kernel density estimation and Bayesian inference) to each datum individually. By using different synthetic aperture radar (SAR) images (PALSAR-2/ScanSAR, PALSAR-2 mosaic, Sentinel-1), optical images (Sentinel-2, Landsat-8) and topography data (AW3D30), the resultant map achieved 85.6% for the overall accuracy. The major forest classes including evergreen broadleaf forests and plantation forests had a user’s accuracy and producer’s accuracy ranging from 86.0% to 95.3%. Our map identified 9.55 × 106 ha (±0.16 × 106 ha) of natural forests and 3.89 × 106 ha (±0.11 × 106 ha) of plantation forests over mainland Vietnam, which were close to the Vietnamese government’s statistics (with differences of less than 8%). This study’s result provides a reliable input/reference to support forestry policy and land sciences in Vietnam. View Full-Text
Keywords: plantation forest; natural forest; Vietnam; acacia; eucalyptus; rubber; land use/land cover mapping; high resolution; PALSAR-2; Sentinel plantation forest; natural forest; Vietnam; acacia; eucalyptus; rubber; land use/land cover mapping; high resolution; PALSAR-2; Sentinel
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MDPI and ACS Style

Hoang, T.T.; Truong, V.T.; Hayashi, M.; Tadono, T.; Nasahara, K.N. New JAXA High-Resolution Land Use/Land Cover Map for Vietnam Aiming for Natural Forest and Plantation Forest Monitoring. Remote Sens. 2020, 12, 2707. https://doi.org/10.3390/rs12172707

AMA Style

Hoang TT, Truong VT, Hayashi M, Tadono T, Nasahara KN. New JAXA High-Resolution Land Use/Land Cover Map for Vietnam Aiming for Natural Forest and Plantation Forest Monitoring. Remote Sensing. 2020; 12(17):2707. https://doi.org/10.3390/rs12172707

Chicago/Turabian Style

Hoang, Thanh T., Van T. Truong, Masato Hayashi, Takeo Tadono, and Kenlo N. Nasahara 2020. "New JAXA High-Resolution Land Use/Land Cover Map for Vietnam Aiming for Natural Forest and Plantation Forest Monitoring" Remote Sensing 12, no. 17: 2707. https://doi.org/10.3390/rs12172707

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