An assessment of seasonal changes in forests using the segmentation and cluster analysis of Landsat space images
https://doi.org/10.25587/2587-8751-2023-4-79-98
Abstract
For the purposes of monitoring the state of forest ecosystems, it is most effective to use the capabilities of remote methods. On multispectral Landsat satellite images (a time series of summer and autumn images for 2000, 2001, 2013, 2014) of the territory of the Olekminsky State Nature Reserve, fragments of forests dominated by Gmelin larch (Larix gmelinii Rupr.) with an area of 250 km2 (scale 1:5000). Then the polygons were saved at three levels of segmentation (scaling) – 4, 16, 64 with scales of 1:2500, 1:1250, 1:625. During decryption, uncontrolled classification of polygons using the ISODATA (Iterative Self-Organizing Data Analysis Technigue) method into 2,4,10 classes was carried out. Classification into two classes was used to calculate the forest cover index. Seasonal changes were determined by the difference in the forest cover index values of the polygons in summer and autumn. It has been shown that the greater the difference, the greater the proportion of larch in mixed forest stands. Distribution curves of forest cover index values were constructed for polygons of the 3rd scaling level. Based on the results of classification into 4, 10 classes, statistical processing was carried out with the calculation of indicators of difference and similarity of polygons - dispersion of the general population and Fisher's test (F-test). The results of changes in population dispersion and F-test at different levels of segmentation and in different years are considered.
About the Authors
Yu. F. Rozhkov
Olyokminsky State Nature Reserve
Russian Federation
Russian Federation
Rozhkov Yurii Filippovich – Candidate of Chemical Sciences, Deputy Director for Scientific Research
Olyokminsk
M. Yu. Kondakova
Hydrochemical Institute
Russian Federation
Russian Federation
Kondakova Maria Yuryevna – Candidate of Biological Sciences, Senior Researcher
Rostov-on-Don
References
1. Zhirin, V.M. Ekologo-dinamicheskoe issledovanie lesoobrazovatel'nogo processa po kosmicheskim snimkam/ V.M. Zhirin, S. V. Knyazeva, S. P. Ejdlina.- Tekst: neposredstvennyj // Lesovedenie, 2013, No 5, P. 76-85.
2. Zhirin, V.M. Dinamika spektral'noj yarkosti porodno-vozrastnoj struktury grupp tipov lesa na kosmicheskih snimkah Landsat/ V.M. Zhirin, S. V. Knyazeva, S. P. Ejdlina. - Tekst: neposredstvennyj // Lesovedenie, 2014, No 5, P. 3-12
3. Vasilevich, M.I. Primenenie sputnikovyh metodov issledovanij v monitoringe sostoyaniya lesnyh fitocenozov v zone vybrosov promyshlennogo predpriyatiya/ M.I. Vasilevich, V.V. Elsakov, V.M. Shchanov. - Tekst: neposredstvennyj // Sovremennye problemy distancionnogo zondirovaniya Zemli iz kosmosa .- 2014.- Vol.11, No 1.-P. 30-42.
4. Tokareva, O.S. Ocenka dinamiki sostoyaniya rastenij- bioindikatorov atmosfernogo zagryazneniya na osnove dannyh distancionnogo zondirovaniya / O.S. Tokareva , I.V. Kas'yanov.- Tekst: neposredstvennyj // Vestnik nauki Sibiri. 2011. No 1 (1), P. 268-272
5. Krylov, A.M. Distancionnyj monitoring sostoyaniya lesov po dannym kosmicheskoj s"emki/ A.M. Krylov, N.A. Vladimirova.- Tekst: neposredstvennyj // Geomatika .- 2011, No 3,- P. 53-57
6. Marks, A. Monitoring lesov s pomoshch'yu gruppirovki sputnikov Rapid Eye / A. Marks.- Tekst: neposredstvennyj // Geomatika .- 2011, No 3.- P. 58-66
7. Yaldygina, N.B. Ispol'zovanie programmnogo kompleksa ENVI dlya resheniya zadach lesnogo hozyajstva / N.B. Yaldygina.- Tekst : neposredstvennyj // Geomatika .- 2011, No 3.- P. 34-39
8. Labutina, I.A. Praktikum po kursu «Deshifrirovanie aerokosmicheskih snimkov»/ I.A. Labutina , E.A. Baldina .- Tekst: neposredstvennyj : Uchebnoe posobie. - M.: Geograficheskij fakul'tet MGU.- 2013, 168 p.
9. Plotnikov, D.E. Vydelenie sezonno-odnorodnyh oblastej na osnove analiza vremennyh serij sputnikovyh izobrazhenij / D.E. Plotnikov, P.A. Kolbudaev, S.A. Bartalyov.- Tekst: neposredstvennyj // Komp'yuternaya optika. – 2018. – Vol. 42, No 3. – P. 447-456. – DOI: 10.18287/2412-6179-2018-42-3-447-456.
10. Lashchinskij, N. N. Ocenka struktury rastitel'nogo pokrova i ego antropogennoj transformacii na osnove obrabotki kosmosnimkov Quickbird (Novosibirskij Akademgorodok) / N. N. Lashchinskij, I. D. Zol'nikov, N. V. Glushkova // Issledovanie Zemli iz kosmosa.- 2013.- No 1.- P. 71–78.-Tekst : neposredstvennyj.
11. Knyazeva, S. V. Metodicheskie podhody k ocenke harakteristik lesov po dannym sputnikovoj s"emki sverhvysokogo prostranstvennogo razresheniya v opticheskom diapazone / S. V. Knyazeva, A. D. Nikitina , E. I. Belova, A. S. Plotnikova, E. S. Podol'skaya, K. A. Kovganko.-Tekst: neposredstvennyj // Lesovedenie.- 2021.- No 6.- P. 645–672.
12. Hossain M.D., Chen D. Segmentation for Object-Based Image Analysis (OBIA): A review of algorithms and challenges from remote sensing perspective // ISPRS J. Photogrammetry and Remote Sensing. 2019. V.150. P. 115–134.
13. Fu G., Zhao H., Li C., Shi L. Segmentation for High-Resolution Optical Remote Sensing Imagery Using Improved Quadtree and Region Adjacency Graph Technique // Remote Sens. 2013. No. 5. P. 3259–3279. doi:10.3390/rs5073259. URL: www.mdpi.com/2072-4292/5/7/3259/pdf
14. Ivanov, E.S. Nekotorye prilozheniya segmentacii snimkov Dzz / E.S. Ivanov // Covremennye problemy distancionnogo zondirovaniya Zemli iz kosmosa.-2016. Vol. 13.No 1.- S. 105–116.- Tekst: neposredstvennyj.
15. Butusov, O.B. Mul'tifraktal'naya segmentaciya landshaftov na kosmicheskom izobrazhenii / O.B.Butusov, N.I.Redikul'ceva, O.P. Nikiforova.- Tekst: neposredstvennyj // Mezhdunarodnyj nauchno-issledovatel'skij zhurnal.- 2017.-No 12 (66). Part 2.- P. 196-203 DOI: https://doi.org/10.23670/IRJ.2017.66.216
16. Makarenko, N. G. Mul'tifraktal'naya segmentaciya dannyh distancionnogo zondirovaniya / N.G.Makarenko, O. A. Kruglun, I. N. Makarenko [i dr.].- Tekst: neposredstvennyj // Issledovanie Zemli iz kosmosa .-2008.- No 3.- P. 18–26
17. Shovengerdt, R.A. Distancionnoe zondirovanie. Modeli i metody obrabotki izobrazhenij / R.A. Shovengerdt. – Moskva: Tekhnosfera, 2010.- 560 p.- Tekst: neposredstvennyj.
18. Shumakov, F.T. Klassifikaciya kosmicheskih snimkov s ispol'zovaniem metodov klasternogo analiza / F.T. Shumakov, V.A. Tolstohat'ko, A.Yu. Malec // Vostochno-Evropejskij zhurnal peredovyh tekhnologij.- 2011. No. 3/4 (51).- P. 58-62.- Tekst: neposredstvennyj.
19. Rozhkov, Yu.F. Sravnitel'naya harakteristika lesnyh massivov s ispol'zovaniem segmentacii i klasternogo analiza snimkov Landsat / YU.F. Rozhkov.- Tekst: neposredstvennyj //Vestnik SVFU. Seriya Nauki o Zemle.-2021 .No 4 (24) .- P. 33-43.
20. Isaev, A.S. Ispol'zovanie sputnikovyh dannyh dlya monitoringa bioraznoobraziya lesov / A.S.Isaev , S.V. Knyazeva, M.Yu. Puzachenko [i dr.] .- Tekst: neposredstvennyj // Issledovanie Zemli iz kosmosa.- 2009. No 2.- P. 1-12.
21. Mandel'brot, B.B. Fraktal'naya geometriya prirody/ B.B.Mandel'brot.- Moskva: Institut komp'yuternyh issledovanij. -2002.- 656 p.- Tekst: neposredstvennyj.
22. Mandelbrot, B.B. The fractal geometry of trees and other natural phenomena/ B.B. Mandelbrot // Buffon Bicentenary Symposium on Geometrical Probability, ed. R.Miles & J.Serra. Lecture Notes in Biomathematics.- 1978. V.23.- P. 235-249.
23. Rozhkov, Yu.F. Ocenka processa vosstanovleniya lesov posle pozhara s ispol'zovaniem segmentacii i klasternogo analiza snimkov Landsat / YU.F. Rozhkov, M.Yu. Kondakova.- Tekst: neposredstvennyj //Vestnik SVFU. Seriya Nauki o Zemle.-2023 .No 2 (30) .- P. 72-87.
Review
For citations:
Rozhkov Yu.F., Kondakova M.Yu. An assessment of seasonal changes in forests using the segmentation and cluster analysis of Landsat space images. Vestnik of North-Eastern Federal University Series "Earth Sciences". 2023;(4):79-98. (In Russ.) https://doi.org/10.25587/2587-8751-2023-4-79-98
Views:
132
Email this article 