[1] Schlesinger W H. Evidence from chronosequence studies for a low carbon-storage potential of soils[J]. Nature, 348, 232-234(1990).

[2] Tang H M, Li C, Shi L H et al. Functional soil organic matter fraction in response to short-term tillage management under the double-cropping rice paddy field in southern of China[J]. Environmental Science and Pollution Research, 28, 48438-48449(2021).

[3] Odebiri O, Odindi J, Mutanga O. Basic and deep learning models in remote sensing of soil organic carbon estimation: a brief review[J]. International Journal of Applied Earth Observation and Geoinformation, 102, 102389(2021).

[4] Qi Y B, Wang Y Y, Chen Y et al. Soil organic matter prediction based on remote sensing data and random forest model in Shaanxi Province[J]. Journal of Natural Resources, 32, 1074-1086(2017).

[5] Meng X T, Bao Y L, Liu J G et al. Regional soil organic carbon prediction model based on a discrete wavelet analysis of hyperspectral satellite data[J]. International Journal of Applied Earth Observation and Geoinformation, 89, 102111(2020).

[6] Wang X, Zhang Y H, Atkinson P M et al. Predicting soil organic carbon content in Spain by combining Landsat TM and ALOS PALSAR images[J]. International Journal of Applied Earth Observation and Geoinformation, 92, 102182(2020).

[7] Lu Z J, Liu K B, Xin R et al. Spatial pattern inversion of soil surface organic matter in Qinggang County, Heilongjiang Province based on sentinel-2 image[J]. Heilongjiang Agricultural Sciences, 89-93(2022).

[8] Castaldi F, Hueni A, Chabrillat S et al. Evaluating the capability of the Sentinel 2 data for soil organic carbon prediction in croplands[J]. ISPRS Journal of Photogrammetry and Remote Sensing, 147, 267-282(2019).

[9] Pham T D, Yokoya N, Nguyen T T T et al. Improvement of mangrove soil carbon stocks estimation in North Vietnam using Sentinel-2 data and machine learning approach[J]. GIScience & Remote Sensing, 58, 68-87(2021).

[10] Yu L, Hong Y S, Geng L et al. Hyperspectral estimation of soil organic matter content based on partial least squares regression[J]. Transactions of the Chinese Society of Agricultural Engineering, 31, 103-109(2015).

[11] Zhai M T. Prediction of soil organic carbon based on in situ vis-NIR hyperspectral data in Poyang Lake wetland[D](2020).

[12] Niu Z W. Application study on soil organic carbon stock estimation based on improved temporal convolution network[D](2024).

[13] Yang J J, Lin N, Yu X X et al. Study on quantitative inversion of remote sensing for organic carbon in the typical black soil areas of Northeast China[J]. Geology and Resources, 29, 357-362(2020).

[14] Wang J W, Yuan H M, Jiang R F et al. Research advance in the determination of soil carbon by mid-infrared spectroscopy[J]. Chinese Journal of Soil Science, 52, 233-241(2021).

[15] Xie S G, Ding F J, Chen S G et al. Prediction of soil organic matter content based on characteristic band selection method[J]. Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy, 273, 120949(2022).

[16] Xiao S C, Gu W J[M]. Agriculture: changes in cultivated land area from 2012 to 2021(2023).

[17] Li H D, Gao X H, Tang M. Land cover classification for SPOT-6 image from decision fusion method[J]. Journal of Geo-Information Science, 23, 928-937(2021).

[18] Song Q, Gao X H, Song Y T et al. Estimation of soil organic carbon content in farmland based on UAV hyperspectral images: a case study of farmland in the Huangshui River Basin[J]. Remote Sensing for Natural Resources, 36, 160-172(2024).

[19] Zhao Q D, Ge X Y, Ding J L et al. Combination of fractional order differential and machine learning algorithm for spectral estimation of soil organic carbon content[J]. Laser & Optoelectronics Progress, 57, 153001(2020).

[20] Shang T H, Mao H X, Zhang J H et al. Hyperspctral estimation of soil organic matter content in Yinchuan Plain, China based on PCA sensitive band screening and SVM modeling[J]. Chinese Journal of Ecology, 40, 4128-4136(2021).

[21] Weng Y L, Qi H P, Fang H B et al. PLSR-based hyperspectral remote sensing retrieval of soil salinity of Chaka-Gonghe Basin in Qinghai Province[J]. Acta Pedologica Sinica, 47, 1255-1263(2010).

[22] Bao Q L, Ding J L, Wang J Z et al. Hyperspectral detection of soil organic matter content based on random forest algorithm[J]. Arid Land Geography, 42, 1404-1414(2019).

[23] Liu Z F, Lei H C, Sheng H Y. Remote sensing inversion of soil nutrient on farmland in Huangshui River Basin based on XGBoost model[J]. Arid Land Geography, 46, 1643-1653(2023).

[24] Chang C W, Laird D A, Mausbach M J et al. Near-infrared reflectance spectroscopy-principal components regression analyses of soil properties[J]. Soil Science Society of America Journal, 65, 480-490(2001).

[25] Xia X Q, Ji J F, Chen J et al. Analysis of soil physical and chemical properties by reflectance spectroscopy[J]. Earth Science Frontiers, 16, 354-362(2009).

[26] Zhang X Y, Li S J, Wang X et al. Quantitative inversion of soil total nitrogen in Suihua City of Heilongjiang in China using Sentinel-2 remote sensing images[J]. Transactions of the Chinese Society of Agricultural Engineering, 39, 144-151(2023).

[27] Liu Q, Wang M D, Guo L et al. Mapping of soil organic carbon density at farmland scale based on airborne hyperspectral images[J]. Journal of Remote Sensing, 28, 293-305(2024).

[28] Ma H J. Land use/land cover change detection in the Huangshui River Basin based on random forest[D](2020).

[29] Zou M L. Environmental variables influencing stoichiometric ratio of soil carbon, nitrogen and phosphorus under different land use types in the three gorges reservoir area[D](2022).

[30] Wang J L, Ouyang H, Wang Z H et al. Distribution of soil active organic carbon of alpine grassland on Qinghai-Tibet Plateau[J]. Acta Geographica Sinica, 64, 771-781(2009).

[31] Lü S L. Study on spatial heterogeneity of soil organic carbon and total nitrogen of alpine grassland and the influencing factors in Qinghai-Tibet Plateau[D](2018).

[32] Chen P N, Wang G A, Han J M et al. δ13C difference between plants and soil organic matter along the eastern slope of Mount Gongga[J]. Chinese Science Bulletin, 54, 3512-3520(2009).

[33] Tan G F, Wang Z F, Zhang Y L et al. Spatial differentiation of cropland soil organic carbon and influencing factors in the Yarlung Zangbo River, Nyangqu River and Lhasa River region of Tibet[J]. Chinese Journal of Ecology, 43, 1824-1832(2024).

[34] Nan Y F, Guo S L, Li N N et al. Soil organic carbon in croplands across different terrains in the Qinghai-Tibet Plateau[J]. Journal of Plant Nutrition and Fertilizers, 19, 946-954(2013).

[35] Zhang J H. Spatial distribution and mechanisms of soil organic carbon in middle of Heihe River, in arid area of Northwest China[D](2007).

[36] Zhou W, Xie L J, Yang H et al. Hyperspectral inversion of soil organic matter content in the three-rivers source region[J]. Chinese Journal of Soil Science, 52, 564-574(2021).

[37] Liu H J, Zhang X L, Zheng S F et al. Black soil organic matter predicting model based on field hyperspectral reflectance[J]. Spectroscopy and Spectral Analysis, 30, 3355-3358(2010).

[38] Tang A H, Yang G J, Yang Y et al. Estimation model of soil organic carbon content based on mid-infrared spectral characteristics enhancement and ensemble learning[J]. Transactions of the Chinese Society for Agricultural Machinery, 55, 382-390(2024).

[39] Xia C Z, Jiang Y Y, Zhang X Y et al. Estimation of soil organic matter in maize field of black soil area based on UAV hyperspectral image[J]. Spectroscopy and Spectral Analysis, 43, 2617-2626(2023).

[40] Yang L Y. Comparison of estimation methods for obtaining soil properties from hyperspectral data in the Sanjiang Yuan Regions[D](2016).

[41] Yang F, Huang L M, Li D C et al. Vertical distributions of soil organic and inorganic carbon and their controls along toposequences in an alpine region[J]. Acta Pedologica Sinica, 52, 1226-1236(2015).