Analysis of Relations Between Aboveground Biomass and Vegetation Indices Derived from Sentinel-2 Satellite Data

Authors

  • Tsolmon Altanchimeg Institute of Geography and Geoecology, Mongolian Academy of Sciences, Ulaanbaatar 15170, Mongolia https://orcid.org/0000-0002-0116-4862
  • Amarsaikhan Damdinsuren Institute of Geography and Geoecology, Mongolian Academy of Sciences, Ulaanbaatar 15170, Mongolia
  • Batchuluun Tseveen Department of Applied Mathematics, National University of Mongolia, Ulaanbaatar 14200, Mongolia
  • Byambadolgor Batdorj Institute of Geography and Geoecology, Mongolian Academy of Sciences, Ulaanbaatar 15170, Mongolia

DOI:

https://doi.org/10.5564/jimdt.v4i1.2666

Keywords:

Mongolia, remote sensing, allometric equation, regression model

Abstract

The aim of this research is to study the relationship between the estimated aboveground forest biomass and spectral vegetation indices derived from the visible and infrared  bands of multispectral Sentinel-2 satellite data. The study area is situated in Teshig soum of Bulgan aimag, the northern part of Mongolia and geographically it belongs to a forest-steppe  natural zone. To calculate the aboveground biomass in sampling plots, forest stand parameters such as diameter at breast height (DBH) and tree height (H) have been measured, and  allometric equations were used. In the final analysis, we investigated the relationship between the aboveground biomass measured at sampling plots and several predefined vegetation indices. The relationships between the aboveground biomass values and vegetation indices were explored by the use of a linear regression model. Of the outputs, the best results demonstrating the highest level of significance were obtained by the uses of the LAI (with  R2=0.61) and SR (with R2=0.59).   

Газрын Дээд Биомасс болон Sentinel-2 Дагуулын Мэдээнээс Тооцсон Ургамлын Индекс Хоорондын Хамаарлын Шинжилгээ   

Хураангуй: Судалгааны ажлын зорилго нь олон бүсчлэлийн Sentinel-2 дагуулын үзэгдэх гэрлийн болон ойрын нэл улаан туяаны мужийн сувгуудыг ашиглан тооцоолсон ургамлын индекс,  газрын дээд биомасс хоорондын хамаарлыг судлахад оршино. Судалгааны талбай болох Булган аймгийн Тэшиг сум нь Монгол орны хойд хэсэгт орших бөгөөд байгалийн бүс бүслүүрийн  хувьд ойт хээрийн бүсэд хамаарна. Газрын дээд биомассыг тооцоолохдоо дээж талбайгаас цээжний өндрийн диаметр (DBH) болон модны өндөр (H) зэрэг параметрүүдийг хэмжиж, аллометрийн тэгшитгэлийг ашигласан бөгөөд дээж талбай дээр хэмжсэн газрын дээд биомасс болон  ургамлын индексүүдийн хоорондын хамаарлыг шугаман регрессийн загвар ашиглан шинжил-  сэн болно. Судалгаанаас гарсан үр дүнгүүдээс өндөр ач холбогдолтой индексүүд нь ургамлын  навчны талбайн индекс LAI (R2=0.61), ойрын нэл улаан туяаны болон улаан гэрлийн сувгуудын  харьцаа SR (R2=0.59) байв. 

Түлхүүр үгс: Монгол, зайнаас тандах судлал, аллометрийн тэгшитгэл, регрессийн загвар 

Abstract
123
PDF 129

References

D. Ellison, C. E. Morris, B. Locatelli, D. Sheil, J. Cohen, D. Murdiyarso, V. Gutierrez, M. V.Noordwijk, I. F. Creed, J. Pokorny, D. Gaveau, D. V. Spracklen, A. B. T. Tobella, U. Ilstedt, A. J. Teuling, S. G. Gebrehiwot, D. C. Sands, B. Muys, B. Verbist, E. Springgay, Y. Sugandi, and C. A. Sullivan, “Trees, forests and water: Cool insights for a hot world,” Global Environmental Change, no. 43, pp. 51-61, 2017, doi: https://doi.org/10.1016/j.strueco.2017.07.001.

T. R. Karl, J. M. Melillo, and T. C. Peterson, “Global Climate Change Impacts in the United States,” Cambridge University Press, New York, 2009.

E. W. Chappelle, M. S. Kim, and J. E. McMurtrey III, “Ratio analysis of reflectance spectra (RARS): An algorithm for the remote estimation of the concentrations of chlorophyll A,chlorophyll B, and carotenoids in soybean leaves,” Remote Sensing of Environment, Vol. 39, no.3, pp. 239-247, 1992, doi: https://doi.org/10.1016/0034-4257(92)90089-3.

Y. He, X. Guo, and J. Wilmshurst, “Studying mixed grassland ecosystems I: suitable hyperspectral vegetation indices,” Canadian Journal of Remote Sensing, Vol. 32, no. 2, pp.98-107, 2006, doi: https://doi.org/10.5589/m06-009.

P. J. Pinter, Jr, J. L. Hatfield, J. S. Schepers, E. M. Barnes, M. S. Moran, C. S. Daughtry, and D. R. Upchurch, “Remote Sensing for Crop Management,” Photogrammetric Engineering & Remote Sensing, Vol. 69, pp. 647-664, 2003, doi: https://doi.org/10.14358/PERS.69.6.647.

Б. Байгаль орчин аялал жуулчлалын яам, “Монгол улсын олон зорилтот үндэсний ойн тооллого 2014-2016,” Улаанбаатар: Ministry of Environment and tourism, 2016.

M. Drusch, U. Del Bello, S. Carlier, O. Colin, V. Fernandez, F. Gasc´on, B. Hoersch, C. Isola, P. Laberinti, P. Martimort, A. Meygret, F. Spoto, O. Sy, F. Marchese, and P. G. Bargellini, “Sentinel-2: ESA’s Optical High-Resolution Mission for GMESOperational Services,” Remote Sensing of Environment, Vol. 120, pp. 25-36, 2012, doi: https://doi.org/10.1016/j.rse.2011.11.026.

Д. Чимидням, Д. Чүлтэм, Ц. Зандраабал, Ц. Гончиг, Ч. Цэвээ-Ойров, “Монгол орны ойн таксацын лавлах,” Улаанбаатар: Бэмби сан, 2012.

E. Boegh, H. Soegaard, N. H. Broge, K. M. Schelde, and N. O. Jensen, “Airborne multispectral data for quantifying leaf area index, nitrogen concentration, and photosynthetic efficiency in agriculture,” Remote Sensing of Environment, Vol. 81, no. 2-3, pp. 179-193, 2002, doi: https://doi.org/10.1016/S0034-4257(01)00342-X.

G. S. Birth, and G. R. McVey, “Measuring the Color of Growing Turf with a Reflectance Spectrophotometer,” Agronomy Journal, Vol. 60, no. 6, pp. 640-643, 1968, doi: https://doi.org/10.2134/agronj1968.00021962006000060016x.

J. M. Chen, and J. Cihlar, “Retrieving leaf area index of boreal conifer forests using Landsat TM images,” Remote Sensing of Environment, Vol. 55, no. 2, pp. 153-162, 1996, doi: https://doi.org/10.1016/0034-4257(95)00195-6.

A. A. Bannari , H. Asalhi, and P. M. Teillet, “Transformed difference vegetation index (TDVI) for vegetation cover mapping,” IEEE International Geoscience and Remote Sensing Symposium, pp. 3053-3055, 2005.

D. W. Hancock, and C. T. Dougherty, “Relationships between Blue- and Red-based Vegetation Indices and Leaf Area and Yield of Alfalfa,” Crop Science, Vol. 47, no. 6, pp. 2547-2556, 2007, doi: https://doi.org/10.2135/cropsci2007.01.0031.

R. P. Sripada, R. W. Heiniger, J. G. White, and R. Weisz, “«Aerial Color Infrared Photography for Determining Late-Season Nitrogen Requirements in Corn,” Agronomy journal, Vol. 97, no.5, pp. 1443-1451, 2005, doi: https://doi.org/10.2134/agronj2004.0314.

R. C. Francisco , C. S. P. Irene, and S. K. Eva, “A Log-Ratio Vegetation Index (LRVI) for Discrimination and Classification of Remote Sensing Data,” Silva Lusitana, Vol. 28, no. 1, pp. 45-70, 2020, doi: https://doi.org/10.1051/silu/20202801045.

A. A. Bannari, D. Morin, F. Bonn, and A. R. HUETE, “A review of vegetation indices,” Remote Sensing Reviews, Vol. 13, no. 1-2, pp. 95-120, 1995, doi: https://doi.org/10.1080/02757259509532298.

Downloads

Published

2022-12-26

How to Cite

Altanchimeg, T., Damdinsuren, A., Tseveen, B., & Batdorj, B. (2022). Analysis of Relations Between Aboveground Biomass and Vegetation Indices Derived from Sentinel-2 Satellite Data. Journal of Institute of Mathematics and Digital Technology, 4(1), 94–100. https://doi.org/10.5564/jimdt.v4i1.2666

Issue

Section

Articles