Mapping soil organic carbon under erosion processes using remote sensing

被引:16
|
作者
Suleymanov, Azamat [1 ]
Gabbasova, Ilyusya [1 ]
Suleymanov, Ruslan [1 ,2 ]
Abakumov, Evgeny [3 ,4 ]
Polyakov, Vyacheslav [3 ]
Liebelt, Peter [5 ]
机构
[1] Russian Acad Sci, Ufa Inst Biol, Ufa Fed Res Ctr, Lab Soil Sci, Pr Oktyabrya 69, Ufa 450054, Russia
[2] Bashkir State Univ, Dept Geodesy Cartog & Geog Informat Syst, Zaki Validi 32, Ufa 450076, Russia
[3] St Petersburg State Univ, Fac Biol, Dept Appl Ecol, 16th Line Vasilievsky Isl 29, St Petersburg 199034, Russia
[4] All Russia Inst Agr Microbiol, Lab Microbiol Monitoring & Bioremediat Soils, Sh Podbelsky 3, St Petersburg 196608, Russia
[5] Martin Luther Univ Halle Wittenberg, Von Seckendorff Pl 4, Halle 06120, Germany
关键词
Soil organic carbon; remote sensing; sentinel; erosion; humic acids; 13C-NMR; REFLECTANCE SPECTROSCOPY; TUNDRA SOILS; C-13; NMR; MATTER; VEGETATION; PREDICTION; MANAGEMENT; TEMPERATE; RESONANCE; ECOSYSTEM;
D O I
10.15201/hungeobull.70.1.4
中图分类号
P9 [自然地理学]; K9 [地理];
学科分类号
0705 ; 070501 ;
摘要
This study aimed to map soil organic carbon under erosion processes on an arable field in the Republic of Bashkortostan (Russia). To estimate the spatial distribution of organic carbon in the Haplic Chemozem topsoil, we applied Sentinel-2A satellite data and the linear regression method. We used 13 satellite bands and 15 calcu-lated spectral indices for regression modelling. A regression model with an average prediction level has been created (R2 = 0.58, RMSE = 0.56, RPD = 1.61). Based on the regression model, cartographic materials for organic carbon content have been created. Water flows and erosion processes were determined using the calculated Flow Accumulation model. The relationship between organic carbon, biological activity, and erosion conditions is shown. The 13C-NMR spectroscopy method was used to estimate the content and nature of humic substances of different soil samples. Based on the 13C-NMR analysis, a correlation was established with the spectral reflectiv-ity of eroded and non-eroded soils. It was revealed that the effect of soil organic carbon on spectral reflectivity depends not only on the quantity but also on the quality of humic substances and soil formation conditions.
引用
收藏
页码:49 / 64
页数:16
相关论文
共 50 条
  • [1] Remote Sensing for Soil Organic Carbon Mapping and Monitoring
    van Wesemael, Bas
    Chabrillat, Sabine
    Dias, Adrian Sanz
    Berger, Michael
    Szantoi, Zoltan
    [J]. REMOTE SENSING, 2023, 15 (14)
  • [2] Geospatial Mapping of Soil Organic Carbon Using Regression Kriging and Remote Sensing
    Kumar, Navneet
    Velmurugan, Ayyamperumal
    Hamm, Nicholas A. S.
    Dadhwal, Vinay Kumar
    [J]. JOURNAL OF THE INDIAN SOCIETY OF REMOTE SENSING, 2018, 46 (05) : 705 - 716
  • [3] Geospatial Mapping of Soil Organic Carbon Using Regression Kriging and Remote Sensing
    Navneet Kumar
    Ayyamperumal Velmurugan
    Nicholas A. S. Hamm
    Vinay Kumar Dadhwal
    [J]. Journal of the Indian Society of Remote Sensing, 2018, 46 : 705 - 716
  • [4] Soil organic carbon mapping using remote sensing techniques and multivariate regression model
    Bhunia, Gouri Sankar
    Shit, Pravat Kumar
    Pourghasemi, Hamid Reza
    [J]. GEOCARTO INTERNATIONAL, 2019, 34 (02) : 215 - 226
  • [5] Digital mapping of soil organic carbon using remote sensing data: A systematic review
    Pouladi, Nastaran
    Gholizadeh, Asa
    Khosravi, Vahid
    Boruvka, Lubos
    [J]. CATENA, 2023, 232
  • [6] Exploring the driving forces and digital mapping of soil organic carbon using remote sensing and soil texture
    Hamzehpour, Nikou
    Shafizadeh-Moghadam, Hossein
    Valavi, Roozbeh
    [J]. CATENA, 2019, 182
  • [7] Mapping surface soil organic carbon for crop fields with remote sensing
    Chen, F
    Kissel, DE
    West, LT
    Rickman, D
    Luvall, JC
    Adkins, W
    [J]. JOURNAL OF SOIL AND WATER CONSERVATION, 2005, 60 (01) : 51 - 57
  • [8] Open Remote Sensing Data in Digital Soil Organic Carbon Mapping: A Review
    Radocaj, Dorijan
    Gasparovic, Mateo
    Jurisic, Mladen
    [J]. AGRICULTURE-BASEL, 2024, 14 (07):
  • [9] Soil Organic Carbon Mapping from Remote Sensing: The Effect of Crop Residues
    Dvorakova, Klara
    Shi, Pu
    Limbourg, Quentin
    van Wesemael, Bas
    [J]. REMOTE SENSING, 2020, 12 (12)
  • [10] Mapping and prediction of soil organic carbon by an advanced geostatistical technique using remote sensing and terrain data
    Mallik, Santanu
    Bhowmik, Tridip
    Mishra, Umesh
    Paul, Niladri
    [J]. GEOCARTO INTERNATIONAL, 2022, 37 (08) : 2198 - 2214