Estimating above-ground biomass in sub-tropical buffer zone community Forests, Nepal, using Sentinel 2 data

Simple item page
dc.contributor.authorPandit, Santa
dc.contributor.authorTsuyuki, Satoshi
dc.contributor.authorDube, Timothy
dc.date.accessioned2018-05-15T11:52:18Z
dc.date.available2018-05-15T11:52:18Z
dc.date.issued2018
dc.description.abstractAccurate assessment of above-ground biomass (AGB) is important for the sustainable management of forests, especially buffer zone (areas within the protected area, where restrictions are placed upon resource use and special measure are undertaken to intensify the conservation value of protected area) areas with a high dependence on forest products. This study presents a new AGB estimation method and demonstrates the potential of medium-resolution Sentinel-2 Multi-Spectral Instrument (MSI) data application as an alternative to hyperspectral data in inaccessible regions. Sentinel-2 performance was evaluated for a buffer zone community forest in Parsa National Park, Nepal, using field-based AGB as a dependent variable, as well as spectral band values and spectral-derived vegetation indices as independent variables in the Random Forest (RF) algorithm. The 10-fold cross-validation was used to evaluate model effectiveness. The effect of the input variable number on AGB prediction was also investigated. The model using all extracted spectral information plus all derived spectral vegetation indices provided better AGB estimates (R2 = 0.81 and RMSE = 25.57 t ha-1). Incorporating the optimal subset of key variables did not improve model variance but reduced the error slightly. This result is explained by the technically-advanced nature of Sentinel-2, which includes fine spatial resolution (10, 20 m) and strategically-positioned bands (red-edge), conducted in flat topography with an advanced machine learning algorithm. However, assessing its transferability to other forest types with varying altitude would enable future performance and interpretability assessments of Sentinel-2.en_US
dc.identifier.citationPandit, S. et al. (2018). Estimating above-ground biomass in sub-tropical buffer zone community Forests, Nepal, using Sentinel 2 data. Remote Sensing, 10: 601en_US
dc.identifier.issn2072-4292
dc.identifier.urihttp://dx.doi.org/10.3390/rs10040601
dc.identifier.urihttp://hdl.handle.net/10566/3672
dc.language.isoenen_US
dc.privacy.showsubmitterFALSE
dc.publisherMDPIen_US
dc.status.ispeerreviewedTRUE
dc.status.ispeerreviewed© 2018 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
dc.subjectAbove-ground biomass (AGB)en_US
dc.subjectMedium-resolutionen_US
dc.subjectRandom forest (RF)en_US
dc.subjectSentinel-2en_US
dc.subjectSustainable managementen_US
dc.titleEstimating above-ground biomass in sub-tropical buffer zone community Forests, Nepal, using Sentinel 2 dataen_US
dc.typeArticleen_US

Files

Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
Pandit_Estimating-above-ground_2018.pdf
Size:
18.49 MB
Format:
Adobe Portable Document Format
Description:
Download
License bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
1.71 KB
Format:
Item-specific license agreed upon to submission
Description:
Download

Collections

Research Articles (Earth Sciences)