Dynamic monitoring of carbon storage of the terrestrial ecosystem in Songhua River Basin from 1986 to 2022 based on land use and land cover change

doi:10.17521/cjpe.2023.0300

Abstract

Abstract:

Aims The dynamic monitoring of basin-scale land use and land cover changes and carbon stock estimation of the terrestrial ecosystem can provide suggestions for optimizing land utilization, enhancing terrestrial ecosystem carbon storage, and achieving the “dual carbon” objective.

Methods Based on the Landsat 5 TM and Landsat 8 OLI images from 1986 to 2022, this study employed random forest to obtain ten land use and land cover maps of the Songhua River Basin with high accuracy and conducted dynamic monitoring of land use and land cover change and its ecosystem carbon storage using an integrated valuation of ecosystem services and trade-offs (InVEST) model, Mann-Kendall tests, and Theil-Sen median trend analysis.

Important findings Results showed that farmland has the largest area in the basin, followed by forest land, grasslands, unused lands, water, construction land, sparse forest land, and shrub land. Among them, farmland, forest, and grassland are the dominant land use types in the study area. During the 1986-2022 period, the farmland expanded by 11 462.68 km² while forest land decreased by 18 567.21 km²; the construction land experienced the most significant change rate of 5.3% with an increased area of 3 505.82 km²; the change rate of the sparse forest is 4.7%, ranking second after construction land but having minimal impact on the overall basin due to limited area changes. The change rate of unused land was 4.5%, with an increased area of 5 385.43 km². There was evident spatial heterogeneity in the distribution of the terrestrial ecosystem carbon stocks within the Songhua River Basin, with high carbon stocks predominantly found in Da Hinggan Mountains and Xiao Hinggan Mountains as well as the Changbai Mountains. The median carbon stock values were observed in the Hinggan League, Songnen Plain, and Sanjiang Plain. In contrast, the areas with low carbon values were observed in Daqing and Baicheng. Over the 36 years, there was an overall decline in carbon storage within the basin, primarily concentrated in the regions initially characterized by high carbon stock values. However, the area with increased carbon stock is scattered in the basin. Notably, three recovery instances of ecosystem carbon stock occurred in 1994, 2002, and 2018 within the Songhua River Basin, all related to the changes in forest land. Based on ensuring no reduction of current forest land, it is recommended to expand forest land and continue implementing forestry projects to effectively prevent further depletion of terrestrial ecosystem carbon storage in the Songhua River Basin.

Key words: carbon storage, InVEST model, land use/land cover change, classification, Songhua River Basin

ZHANG Zhi-Yang, ZHAO Ying-Hui, ZHEN Zhen. Dynamic monitoring of carbon storage of the terrestrial ecosystem in Songhua River Basin from 1986 to 2022 based on land use and land cover change[J]. Chin J Plant Ecol, 2024, 48(10): 1274-1290.

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Figures/Tables 13

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年份 Year	陆地卫星 Landsat	传感器 Sensor	空间分辨率 Spatial resolution (m)	影像数量 Number of images
1986, 1990, 1994, 1998, 2002, 2006, 2010	Landsat 5	TM	30	6 274
2014, 2018, 2022	Landsat 8	OLI	30	3 132

年份 Year	陆地卫星 Landsat	传感器 Sensor	空间分辨率 Spatial resolution (m)	影像数量 Number of images
1986, 1990, 1994, 1998, 2002, 2006, 2010	Landsat 5	TM	30	6 274
2014, 2018, 2022	Landsat 8	OLI	30	3 132

分类系统 Classification system	面积占比 Proportion of area (%)	样本数量 Number of samples	根据目视解译调整后样本数 Adjusted sample according to visual interpretation
耕地 Farmland	38.9	1 945	2 165
有林地 Forest land	37.5	1 875	1 833
草地 Grassland	9.2	460	375
水域 Water	1.8	90	122
建设用地 Construction land	2.5	125	130
未利用地 Unused land	6.5	325	205
灌木林地 Shrub land	1.7	85	70
疏林地 Sparse forest land	1.9	95	100
总计 Sum	100	5 000	5 000

分类系统 Classification system	面积占比 Proportion of area (%)	样本数量 Number of samples	根据目视解译调整后样本数 Adjusted sample according to visual interpretation
耕地 Farmland	38.9	1 945	2 165
有林地 Forest land	37.5	1 875	1 833
草地 Grassland	9.2	460	375
水域 Water	1.8	90	122
建设用地 Construction land	2.5	125	130
未利用地 Unused land	6.5	325	205
灌木林地 Shrub land	1.7	85	70
疏林地 Sparse forest land	1.9	95	100
总计 Sum	100	5 000	5 000

特征(个数) Feature (number)	Landsat 5 TM	特征(个数) Feature (number)	Landsat 8 OLI
原始波段 Original band (6)	B_i (i = 1, 2, 3, 4, 5, 7)	原始波段 Original band (7)	B_i (i = 1, 2, 3, 4, 5, 6, 7)
波段组合 Band combination (6)	B24, B345, B53, B547, B74, VIS234	波段组合 Band combination (10)	Albedo, B₄/Albedo, B24, B74, B76, B547, B65, B345, B53, VIS234
植被指数 Vegetation index (16)	ARVI, DVI, EVI, LSWI, MSAVI, MSR, MVI5, MVI7, NDVI, NDWI, NLI, PVI, RDVI, RVI, SAVI, SLAVI	植被指数 Vegetation index (18)	NDVI, RDVI, NLI, MVI7, MVI5, SLAVI, MSR, PVI, MSAVI, ARVI, SAVI, ND563, EVI, RVI, DVI, NDWI, NDBI, LSWI
纹理特征 Texture feature (102)	B_i_asm, B_i_contrast, B_i_corr, B_i_dent, B_i_diss, B_i_dvar, B_i_ent, B_i_idm, B_i_imcorr1, B_i_imcorr2, B_i_inertia, B_i_prom, B_i_savg, B_i_sent, B_i_shade, B_i_svar, B_i_var	纹理特征 Texture feature (119)	B_i_asm, B_i_contrast, B_i_corr, B_i_dent, B_i_diss, B_i_dvar, B_i_ent, B_i_idm, B_i_imcorr1, B_i_imcorr2, B_i_inertia, B_i_prom, B_i_savg, B_i_sent, B_i_shade, B_i_svar, B_i_var