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Remote Sens. 2017, 9(12), 1253; https://doi.org/10.3390/rs9121253

Experiences from Large-Scale Forest Mapping of Sweden Using TanDEM-X Data

1
Swedish University of Agricultural Sciences (SLU), Department of Forest Resource Management, Umeå 901 83, Sweden
2
Horizon Geoscience Consulting, Belrose, NSW 2085, Australia
3
School of Land and Food, University of Tasmania, Hobart, TAS 7001, Australia
4
Chalmers University of Technology, Department of Space, Earth and Environment, Microwave and Optical Remote Sensing, Gothenburg 412 96, Sweden
*
Author to whom correspondence should be addressed.
Received: 12 October 2017 / Revised: 24 November 2017 / Accepted: 28 November 2017 / Published: 2 December 2017
(This article belongs to the Section Forest Remote Sensing)
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Abstract

This paper report experiences from the processing and mosaicking of 518 TanDEM-X image pairs covering the entirety of Sweden, with two single map products of above-ground biomass (AGB) and forest stem volume (VOL), both with 10 m resolution. The main objective was to explore the possibilities and overcome the challenges related to forest mapping extending a large number of adjacent satellite scenes. Hence, numerous examples are presented to illustrate challenges and possible solutions. To derive the forest maps, the observables backscatter, interferometric phase height and interferometric coherence, obtained from TanDEM-X, were evaluated using empirical robust linear regression models with reference data extracted from 2288 national forest inventory plots with a 10 m radius. The interferometric phase height was the single most important observable, to predict AGB and VOL. The mosaics were evaluated on different datasets with field-inventoried stands across Sweden. The root mean square error (RMSE) was about 21%–25% (27–30 tons/ha and 52–65 m3/ha) at the stand level. It was noted that the most influencing factors on the observables in this study were local temperature and geolocation errors that were challenging to robustly compensate against. Because of this variability at the scene-level, determinations of AGB and VOL for single stands are recommended to be used with care, as an equivalent accuracy is difficult to achieve for all different scenes, with varying acquisition conditions. Still, for the evaluated stands, the mosaics were of sufficient accuracy to be used for forest management at the stand level. View Full-Text
Keywords: TanDEM-X; forest; mosaic; synthetic aperture radar; volume; biomass; modelling TanDEM-X; forest; mosaic; synthetic aperture radar; volume; biomass; modelling
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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).
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Persson, H.J.; Olsson, H.; Soja, M.J.; Ulander, L.M.; Fransson, J.E. Experiences from Large-Scale Forest Mapping of Sweden Using TanDEM-X Data. Remote Sens. 2017, 9, 1253.

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