Assessment of TanDEM-X DEM 2020 Data in Temperate and Boreal Forests and Their Application to Canopy Height Change

Author:

Schlund MichaelORCID,von Poncet Felicitas,Wessel Birgit,Schweisshelm Barbara,Kiefl Nadine

Abstract

AbstractSpace-borne digital elevation models (DEM) are considered as important proxy for canopy surface height and its changes in forests. Interferometric TanDEM-X DEMs were assessed regarding their accuracy in forests of Germany and Estonia. The interferometric synthetic aperture radar (InSAR) data for the new global TanDEM-X DEM 2020 coverage were acquired between 2017 and 2020. Each data acquisition was processed using the delta-phase approach for phase unwrapping and comprise an absolute height calibration. The results of the individual InSAR heights confirmed a substantial bias in forests. This was indicated by a mean error (ME) between – 5.74 and – 6.14 m associated with a root-mean-squared-error (RMSE) between 6.99 m and 7.40 m using airborne light detection and ranging (LiDAR) data as a reference. The bias was attributed to signal penetration, which was attempted to be compensated. The ME and RMSE improved substantially after the compensation to the range of – 0.54 to 0.84 m and 3.55 m to 4.52 m. Higher errors of the penetration depth compensated DEMs compared to the original DEMs were found in non-forested areas. This suggests to use the penetration compensation only in forests. The potential of the DEMs for estimating height changes was further assessed in a case study in Estonia. The canopy height change analysis in Estonia indicated an overall accuracy in terms of RMSE of 4.17 m and ME of – 0.93 m on pixel level comparing TanDEM-X and LiDAR height changes. The accuracy improved substantially at forest stand level to an RMSE of 2.84 m and an ME of – 1.48 m. Selective penetration compensation further improved the height change estimates to an RMSE of 2.14 m and an ME of – 0.83 m. Height loss induced by clearcutting was estimated with an ME of – 0.85 m and an RMSE of 3.3 m. Substantial regrowth resulted in an ME of – 0.46 m and an RMSE of 1.9 m. These results are relevant for exploiting multiple global acquisitions of TanDEM-X, in particular for estimating canopy height and its changes in European forests.

Funder

Bundesministerium für Wirtschaft und Energie

Publisher

Springer Science and Business Media LLC

Subject

Earth and Planetary Sciences (miscellaneous),Instrumentation,Geography, Planning and Development

Reference53 articles.

1. Abdullahi S, Kugler F, Pretzsch H (2016) Prediction of stem volume in complex temperate forest stands using TanDEM-X SAR data. Remote Sens Environ 174:197–211. https://doi.org/10.1016/j.rse.2015.12.012, http://www.sciencedirect.com/science/article/pii/S0034425715302339

2. Araza A, de Bruin S, Herold M, Quegan S, Labriere N, Rodriguez-Veiga P, Avitabile V, Santoro M, Mitchard ET, Ryan CM, Phillips OL, Willcock S, Verbeeck H, Carreiras J, Hein L, Schelhaas MJ, Pacheco-Pascagaza AM, da Conceição Bispo P, Laurin GV, Vieilledent G, Slik F, Wijaya A, Lewis SL, Morel A, Liang J, Sukhdeo H, Schepaschenko D, Cavlovic J, GilanH, Lucas R (2022) A comprehensive framework for assessing the accuracy and uncertainty of global above-ground biomass maps. Remote Sens Environ 272:112917. https://doi.org/10.1016/j.rse.2022.112917,https://www.sciencedirect.com/science/article/pii/S0034425722000311

3. Atkins JW, Walter JA, Stovall AEL, Fahey RT, Gough CM (2021) Power law scaling relationships link canopy structural complexity and height across forest types. Funct Ecol 36(3):713–726 https://doi.org/10.1111/1365-2435.13983, https://besjournals.onlinelibrary.wiley.com/doi/abs/10.1111/1365-2435.13983

4. Coops NC, Tompalski P, Goodbody TR, Queinnec M, Luther JE, Bolton DK, White JC, Wulder MA, van Lier OR, Hermosilla T (2021) Modelling lidar-derived estimates of forest attributes over space and time: a review of approaches and future trends. Remote Sens Environ 260:112477. https://doi.org/10.1016/j.rse.2021.112477, https://www.sciencedirect.com/science/article/pii/S0034425721001954

5. Copernicus Land Monitoring Service (CLMS) (2021) Copernicus Land Monitoring Service. High Resolution land cover characteristics. Tree-cover/forest and change 2015-2018. User Manual. European Environment Agency (EEA), European Union., Kongens Nytorv 6 - 1050 Copenhagen K. - Denmark, 1.2 edn, https://land.copernicus.eu/user-corner/technical-library/forest-2018-user-manual.pdf

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3