Article information

2022 , Volume 27, ¹ 2, p.105-121

Dmitriev A.V., Chimitdorzhiev T.N., Dagurov P.N.

Optics and microwave detection of forest restoration after fires

The problem of large-scale assessment of forest restoration after artificial deforestation and wildfires is relevant in connection with climate change and the corresponding desire of the world community for further low-carbon development. One of the promising methods aimed at solving this problem is remote sensing of the Earth using space-based synthetic aperture radars (SAR). The paper proposes a comprehensive approach to assessing the dynamics of forest plantings growth using time series analysis of ALOS-2 PALSAR-2 and Sentinel-1 radars data, as well as Sentinel-2A/B optical sensors data. It is shown that with the help of model-based decomposition (Freeman–Durden decomposition) of fully polarimetric data in L-band (ALOS-2 PALSAR-2), the increasing of volume scattering component and the corresponding decrease in the surface component can confidently identify the growth of young forest. However, the data of ALOS-2 PALSAR-2 with dual polarization are not able to separate forest undergrowth from other types of vegetation over a seven-year observation interval. This is also true for the C-band. Thus, the polarimetric Cloud– Pottier decomposition of Sentinel-1 data allowing only separation for the areas with vegetation from the treeless ones. Time series analysis of radiometrically corrected radar backscattering at vertical co-polarization in this band, imaged in the winter period of time, allows reliable determining of the dynamics for the growth of forest plantations. The use of freely available Sentinel-2A/B multispectral sensors data makes it possible to further divide the identified undergrowth by species composition and exclude classification errors of radar data in treeless areas, which show an increasing of volume backscattering component on model-based polarimetric decompositions.

[full text] [link to elibrary.ru]

Keywords: reforestation, polarimetric decompositions, time series analysis, ALOS-2 PALSAR-2, Sentinel-1, Sentinel-2

doi: 10.25743/ICT.2022.27.2.009

Author(s):
Dmitriev Aleksey Valer'evich
PhD.
Position: Senior Research Scientist
Office: Institute of physical materials science SB RAS
Address: 670047, Russia, Ulan-Ude, Sakhyanovoy St., 6
Phone Office: (3012) 434-819
E-mail: dav@ipms.bscnet.ru
SPIN-code: 6686-0205

Chimitdorzhiev Tumen Namzhilovich
Dr. , Professor
Position: Head of Sector
Office: Institute of Physical Material Science of the SB RAS
Address: 670047, Russia, Ulan-Ude, 6, Sakhyanovoy str.
Phone Office: (3012) 416981
E-mail: tchimit@ipms.bscnet.ru
SPIN-code: 3968-0614

Dagurov Pavel Nikolaevich
Dr. , Associate Professor
Position: Leading research officer
Office: Institute of Physical Material Science of the SB RAS
Address: 670047, Russia, Ulan-Ude, 6, Sakhyanovoy str.
Phone Office: (3012) 434819
E-mail: pdagurov@gmail.com
SPIN-code: 4015-9893

References:

1. Bellassen V., Luyssaert S. Carbon sequestration: Managing forests in uncertain times. Nature. 2014; 506(7487):153–155. DOI:10.1038/506153a.

2. Jiang M., Medlyn B.E., Drake J.E., Duursma R.A., Anderson I.C., Barton C.V.M., Boer M.M., Carrillo Y., Castan˜eda-G´omez L., Collins L., Crous K.Y., De Kauwe M.G., dos Santos B.M., Emmerson K.M., Facey S.L., Gherlenda A.N., Gimeno T.E., Hasegawa S., Johnson S.N., K¨annaste A., Macdonald C.A., Mahmud K., Moore B.D., Nazaries L., Neilson E.H.J., Nielsen U.N., Niinemets U., Noh N.J., Ochoa-Hueso R.,¨ Pathare V.S., Pendall E., Pihlblad J., Pin˜eiro J., Powell J.R., Power S.A., Reich P.B., Renchon A.A., Riegler M., Rinnan R., Rymer P.D., Salom´on R.L., Singh B.K., Smith B., Tjoelker M.G., Walker J.K.M., Wujeska-Klause A., Yang J., Zaehle S., Ellsworth D.S. The fate of carbon in a mature forest under carbon dioxide enrichment. Nature. 2020;
580(7802):227–231. DOI:10.1038/s41586-020-2128-9.

3. Global biomass. Available at: https://www.eo4sd-forest.info/global-biomass (accessed January 17, 2022).

4. FAO. 2020. Global forest resources assessment 2020. Rome. Available at: https://www.fao.org/ forest-resources-assessment/fra-2020/maps/en (accessed January 17, 2022).

5. Pinnington E.M., Casella E., Dance S.L., Lawless A.S., Morison J.I.L., Nichols N.K., Wilkinson M., Quaife T.L. Understanding the effect of disturbance from selective felling on the carbon dynamics of a managed woodland by combining observations with model predictions. Journal of Geophysical Research: Biogeosciences. 2017; 122(4):886–902. DOI:10.1002/2017JG003760.

6. Pugh T.A.M., Lindeskog M., Smith B., Poulter B., Arneth A., Haverd V., Calle L. Role of forest regrowth in global carbon sink dynamics. Proceedings of the National Academy of Sciences. 2019; 116(10):4382–4387. DOI:10.1073/pnas.1810512116.

7. Chazdon R.L., Broadbent E.N., Rozendaal D.M.A., Bongers F., Zambrano A.M.A., Aide T.M., Balvanera P., Becknell J.M., Boukili V., Brancalion P.H.S., Craven D., Almeida-Cortez J.S., Cabral G.A.L., Jong Ben de, Denslow J.S., Dent D.H., DeWalt S.J., Dupuy J.M., Dur´an S.M., Esp´ırito-Santo M.M., Fandino M.C., C´esar R.G., Hall J.S., Hern´andez-Stefanoni J.L., Jakovac C.C., Junqueira A.B., Kennard D., Letcher S.G., Lohbeck M., Mart´ınez-Ramos M., Massoca P., Meave J.A., Mesquita R., Mora F., Mun˜oz R., Muscarella R., Nunes Y.R.F., Ochoa-Gaona S., Orihuela-Belmonte E., Pen˜aClaros M., P´erez-Garc´ıa E.A., Piotto D., Powers J.S., Rodr´ıguez-Velazquez J., RomeroP´erez I.E., Ru´ız J., Saldarriaga J.G., Sanchez-Azofeifa A., Schwartz N.B., Steininger M.K., Swenson N.G., Uriarte M., Breugel M., Wal H., Veloso M.D.M., Vester H., Vieira I.C.G., Bentos T.V., Williamson G.B., Poorter L. Carbon sequestration potential of second-growth forest regeneration in the Latin American tropics. Science Advances. 2016. DOI:10.1126/sciadv.1501639.

8. Lehmann E.A., Caccetta P., Lowell K., Mitchell A., Zhou Z.-S., Held A., Milne T., Tapley I. SAR and optical remote sensing: Assessment of complementarity and interoperability in the context of a large-scale operational forest monitoring system. Remote Sensing of Environment. 2015; 156:335–348. DOI:10.1016/j.rse.2014.09.034.

9. Chimitdorzhiev T.N., Dmitriev A.V., Kirbizhekova I.I., Sherhoeva A.A., Baltukhaev A.K., Dagurov P.N. Remote optical-microwave measurements of forest parameters: Modern state of research and experimental assessment of potentials. Sovremennye Problemy Distantsionnogo Zondirovaniya Zemli iz Kosmosa. 2018; 15(4):9–24. DOI:10.21046/2070-7401-2018-15-4-9-24.

10. Chimitdorzhiev T.N., Dmitriev A.V., Dagurov P.N. Technology of joint analysis of Sentinel-1 interferometric coherence time series and vegetation index based on Sentinel-2 data for monitoring agricultural fields. Sovremennye Problemy Distantsionnogo Zondirovaniya Zemli iz Kosmosa. 2020; 17(4):61–72. DOI:10.21046/2070-7401-2020-17-4-61-72.

11. Gorelick N., Hancher M., Dixon M., Ilyushchenko S., Thau D., Moore R. Google Earth Engine: Planetary-scale geospatial analysis for everyone. Remote Sensing of Environment. 2017; (202):18–27. DOI:10.1016/j.rse.2017.06.031.

12. Google Earth Engine. Available at: https://earthengine.google.com (accessed January 17, 2022).

13. Cloude S. Polarisation: Applications in remote sensing. OUP Oxford; 2009: 472.

14. Lee J.-S., Pottier E. Polarimetric radar imaging: From basics to applications. CRC Press: Boca Raton; 2009: 422.

15. Freeman A., Durden S.L. A three-component scattering model for polarimetric SAR data. IEEE Transactions on Geoscience and Remote Sensing. 1998; 36(3):963–973. DOI:10.1109/36.673687.

16. Small D. Flattening gamma: Radiometric terrain correction for SAR imagery. IEEE Transactions on Geoscience and Remote Sensing. 2011; 49(8):3081–3093. DOI:10.1109/TGRS.2011.2120616.

17. SNAP — ESA Sentinel Application Platform v8.0. Available at: http://step.esa.int (accessed January 17, 2022).

18. Dagurov P.N., Chimitdorzhiev T.N., Dmitriev A.V., Dobrynin S.I. Estimation of snow water equivalent from L-band radar interferometry: simulation and experiment. International Journal of Remote Sensing. 2020; 41(24):9328–9359. DOI:10.1080/01431161.2020.1798551.

19. Sentinel-2 Level-2A algorithm overview. Available at: https://sentinel.esa.int/web/sentinel/ technical-guides/sentinel-2-msi/level-2a/algorithm (accessed January 17, 2022).

Bibliography link:
Dmitriev A.V., Chimitdorzhiev T.N., Dagurov P.N. Optics and microwave detection of forest restoration after fires // Computational technologies. 2022. V. 27. ¹ 2. P. 105-121
Home| Scope| Editorial Board| Content| Search| Subscription| Rules| Contacts
ISSN 1560-7534
© 2024 FRC ICT