Please use this identifier to cite or link to this item: http://hdl.handle.net/2381/38786
Title: Mapping Forest Cover and Forest Cover Change with Airborne S-Band Radar
Authors: Ningthoujam, Ramesh K.
Tansey, Kevin
Balzter, Heiko
Morrison, K.
Johnson, Sarah C. M.
Gerard, F.
George, C.
Burbidge, G.
Doody, S.
Veck, N.
Llewellyn, G. M.
Blythe, T.
First Published: 8-Jul-2016
Publisher: MDPI
Citation: Remote Sensing, 2016, 8(7), 577;
Abstract: Assessments of forest cover, forest carbon stocks and carbon emissions from deforestation and degradation are increasingly important components of sustainable resource management, for combating biodiversity loss and in climate mitigation policies. Satellite remote sensing provides the only means for mapping global forest cover regularly. However, forest classification with optical data is limited by its insensitivity to three-dimensional canopy structure and cloud cover obscuring many forest regions. Synthetic Aperture Radar (SAR) sensors are increasingly being used to mitigate these problems, mainly in the L-, C- and X-band domains of the electromagnetic spectrum. S-band has not been systematically studied for this purpose. In anticipation of the British built NovaSAR-S satellite mission, this study evaluates the benefits of polarimetric S-band SAR for forest characterisation. The Michigan Microwave Canopy Scattering (MIMICS-I) radiative transfer model is utilised to understand the scattering mechanisms in forest canopies at S-band. The MIMICS-I model reveals strong S-band backscatter sensitivity to the forest canopy in comparison to soil characteristics across all polarisations and incidence angles. Airborne S-band SAR imagery over the temperate mixed forest of Savernake Forest in southern England is analysed for its information content. Based on the modelling results, S-band HH- and VV-polarisation radar backscatter and the Radar Forest Degradation Index (RFDI) are used in a forest/non-forest Maximum Likelihood classification at a spatial resolution of 6 m (70% overall accuracy, κ = 0.41) and 20 m (63% overall accuracy, κ = 0.27). The conclusion is that S-band SAR such as from NovaSAR-S is likely to be suitable for monitoring forest cover and its changes.
DOI Link: 10.3390/rs8070577
ISSN: 2072-4292
eISSN: 2072-4292
Links: http://www.mdpi.com/2072-4292/8/7/577
http://hdl.handle.net/2381/38786
Version: Publisher Version
Status: Peer-reviewed
Type: Journal Article
Rights: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).
Appears in Collections:Published Articles, Dept. of Geography

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