Features of the spectral display of larch in the autumn period on the materials of the Sentinel-2 survey

The study is devoted to revealing the peculiarities of spectral mapping of stands with participation and predominance of larch in the autumn period on the materials of Sentinel-2 imagery. The imaging range from 650.0 nm to 680.0 nm, corresponding to Sentinel-2 channel B4, was used to study the mapping of stands with larch participation and predominance. Phenological peculiarities of larch and associated hardwoods in the study area were used as a criterion for selecting the survey date. For field work, an area with larch participation and predominance was selected in the territory of 76 and 92 quarters of the Kepinsky district forestry of Arkhangelskoye lesnichestvo. For stand assessment, the method of constant radius circular plots (CRCP) was chosen. Geographical reference of the circular plots centers was carried out using a Garmin 62 GPS navigator. For the purposes of the study, 71 CRCPs were established. In October 2022 an unmanned aircraft survey was used to map larch crowns in the circular plots. Field survey materials were used to assess the accuracy of analytical larch identification based on detailed survey data. Phenological peculiarities of larch make it possible to identify this species on the detailed imagery materials with an accuracy of over 90%. A linear relationship between the increase in the spectral brightness of CRCP on the Sentinel-2 satellite image and the increase in the larch share was revealed. The complex of works carried out, including field work, the determination of individual larch crowns on a detailed survey and the analysis of their display on a satellite image, can be used to solve problems of determining the distribution area of larch in the Arkhangelsk region and the European North. The results of the study will contribute to the development of automated decryption methods.

1. Alekseev A.S., Chernikhovskii D.M. Identification of early stages of damage to spruce stands by bark beetle-typographer based on combined analysis of Sentinel-2B satellite survey materials and ground surveys. Izvestia Sankt-Peterburgskoj Lesotehniceskoj Akademii, 2023, no. 246, pp. 22–43. DOI: 10.21266/2079-4304.2023.246.22-43. (In Russ.)

2. Aleshko R.A., Shoshina K.V., Berezovsky V.V., Vasendina I.S., Vorontsov R.A., Desyatova T.O. Development of a methodology to determine the volume of timber using an unmanned aerial vehicle. Current problems in remote sensing of the earth from space, 2023, vol. 20, no. 4, pp. 111–120. DOI: 10.21046/2070-7401-2023-20-4-111-120. (In Russ.)

3. Babashkin N.M., Kadnichansky S.A., Nekhin S.S. Topographic aerial photography in Russia. Geomatics, 2016, no. 1 (30), pp. 30–36. (In Russ.)

4. Berlina N.G., Zanuzdayeva N.V. Nature calendar of the Lapland Biosphere Reserve. Materials of the International Scientific and Practical Conference, USPU, Yekaterinburg, 2015, pp. 88–100. (In Russ.)

5. Bogdanov A.P., Tretyakov S.V., Kopeikin M.A. Development of an algorithm for decrypting multispectral satellite images of medium resolution in order to isolate stands of larch. Bulletin of the Buryat State Agricultural Academy named after V.R. Filippov, 2023, no. 3(72), pp. 61–71. DOI: 10.34655/bgsha.2023.72.3.007. (In Russ.)

6. Grabska E., Hostert P., Pflugmacher D., Ostapowicz K. Forest Stand Species Mapping Using the Sentinel-2 Time Series. Remote Sens., 2019, vol. 11, no. 10, art. no. 1197. DOI: 10.3390/rs11101197.

7. Kishchenko I.T. The Effect of Climatic Factors on the Seasonal Development of Coniferous Forest-Forming Species in the Taiga Zone (Karelia). IVUZ. Lesnoy Zhurnal, 2020, no. 3, pp. 72–82. DOI: 10.37482/0536-1036-2020-3-72-82 (In Russ.)

8. Kollert A., Bremer M., Löw M., Rutzinger M. Exploring the Potential of Land Surface Phenology and Seasonal Cloud Free Composites of One Year of Sentinel-2 Imagery for Tree Species Mapping in a Mountainous Region. Int. J. Appl. Earth Obs. Geoinf., 2021, vol. 94, art. no. 102208. DOI: 10.1016/J.JAG.2020.102208.

9. Li X., Liu Z., Lin H., Wang G., Sun H., Long J., Zhang M. Estimating the Growing Stem Volume of Chinese Pine and Larch Plantations based on Fused Optical Data Using an Improved Variable Screening Method and Stacking Algorithm. Remote Sens., 2020, vol. 12, art. no. 871. DOI: 10.3390/rs12050871.

10. Monteiro A.T., Rosa S., Andreone F., Ndriantsoa S., Rakotonanahary T., Dawson J., Rabemananjara F.C.E., Rabibisoa N.H.C., Lucas R., Crottini A. Anthropogenic landscape change and amphibian diversity in tropical montane biodiversity hotspots: insights from satellite remote sensing in the Madagascar highlands. Environ. Dev. Sustain., 2023, vol. 27, pp. 7219–7242. DOI: 10.1007/s10668-023-04187-9.

11. Nakvasina E.N., Barabin A.I., Tikhonov P.R., Eliseev A.A. Larch in the Arkhangelsk North: biology, variability, conservation. Arkhangelsk: Arkh. STU, 2008. 216 p. (In Russ.)

12. Punalekar S.M., Planque C., Lucas R.M., Evans D., Correia V., Owers C.J., Poslajko P., Bunting P., Chognard S. National scale mapping of larch plantations for Wales using the Sentinel-2 data archive. Forest Ecology and Management, 2021, vol. 501, art. no. 119679. DOI: 10.1016/j.foreco.2021.119679.

13. Rees W.G., Tomaney J., Tutubalina O., Zharko V., Bartalev S. Estimation of Boreal Forest Growing Stock Volume in Russia from Sentinel-2 MSI and Land Cover Classification. Remote Sens., 2021, vol. 13, art. no. 4483. DOI: 10.3390/rs13214483.

14. Sentinel Hub. EO Browser. URL: https://www.sentinel-hub.com. (accessed October 16, 2023).

15. Shen Y., Zhang X., Wang W., Nemani R., Ye Y., Wang J. Fusing Geostationary Satellite Observations with Harmonized Landsat-8 and Sentinel-2 Time Series for Monitoring Field-Scale Land Surface Phenology. Remote Sens., 2021, vol. 13, art. no. 4465. DOI: 10.3390/rs13214465.

16. Shoshina K.V., Aleshko R.A., Berezovsky V.V., Vasendina I.S., Shoshin A.S., Guryev A.T. Thematic interpretation of aerial photographs of forest areas based on conceptual modeling. Onthology of designing, 2023, vol. 13, no. 3, pp. 437–454. DOI: 10.18287/2223-9537-2023-13-3-437-454. (In Russ.)

17. Vasina A.L., Talanova G.I. Analysis of long-term climatic and phenological data of the reserve «Malaya Sosva» (Northern Trans-Urals). Materials of the International scientific and practical conference, USPU, Yekaterinburg, 2015, pp. 100–111 (In Russ.)

18. Yu T., Pang Y., Liang X.J., Jia W., Bai Y., Fan Y.L., Chen D.S., Liu X.Z., Deng G., Li C.G., Sun X.N., Zhang Z.D., Jia W.W., Zhao Z.H., Wang X. China’s larch stock volume estimation using Sentinel-2 and LiDAR data. Geo-Spatial Inf. Sci., 2023, vol. 26, iss. 3, pp. 392–405. DOI: 10.1080/10095020.2022.2105754.

19. Zharko V.O., Bartalev S.A. Assessment of tree species recognition based on satellite data on seasonal changes in their spectral reflectance characteristics. Current problems in remote sensing of the earth from space, 2014, vol. 11, no. 3, pp. 159–170 (In Russ.).