Chin J Plant Ecol ›› 2024, Vol. 48 ›› Issue (10): 1274-1290.DOI: 10.17521/cjpe.2023.0300 cstr: 32100.14.cjpe.2023.0300
Special Issue: 全球变化与生态系统; 生态系统碳水能量通量; 碳储量
• Research Articles • Previous Articles Next Articles
ZHANG Zhi-Yang, ZHAO Ying-Hui, ZHEN Zhen*()
Received:
2023-10-20
Accepted:
2024-03-06
Online:
2024-10-20
Published:
2024-12-03
Contact:
ZHEN Zhen
Supported by:
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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URL: https://www.plant-ecology.com/EN/10.17521/cjpe.2023.0300
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 |
Table 1 Information of Landsat series images applied in Songhua River Basin from 1986 to 2022
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 |
Table 2 Classification system and number of samples of different classes in Songhua River Basin from 1986 to 2022
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) | Bi (i = 1, 2, 3, 4, 5, 7) | 原始波段 Original band (7) | Bi (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) | Bi_asm, Bi_contrast, Bi_corr, Bi_dent, Bi_diss, Bi_dvar, Bi_ent, Bi_idm, Bi_imcorr1, Bi_imcorr2, Bi_inertia, Bi_prom, Bi_savg, Bi_sent, Bi_shade, Bi_svar, Bi_var | 纹理特征 Texture feature (119) | Bi_asm, Bi_contrast, Bi_corr, Bi_dent, Bi_diss, Bi_dvar, Bi_ent, Bi_idm, Bi_imcorr1, Bi_imcorr2, Bi_inertia, Bi_prom, Bi_savg, Bi_sent, Bi_shade, Bi_svar, Bi_var |
Table 3 Extracted features of Landsat images in Songhua River Basin from 1986 to 2022
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) | Bi (i = 1, 2, 3, 4, 5, 7) | 原始波段 Original band (7) | Bi (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) | Bi_asm, Bi_contrast, Bi_corr, Bi_dent, Bi_diss, Bi_dvar, Bi_ent, Bi_idm, Bi_imcorr1, Bi_imcorr2, Bi_inertia, Bi_prom, Bi_savg, Bi_sent, Bi_shade, Bi_svar, Bi_var | 纹理特征 Texture feature (119) | Bi_asm, Bi_contrast, Bi_corr, Bi_dent, Bi_diss, Bi_dvar, Bi_ent, Bi_idm, Bi_imcorr1, Bi_imcorr2, Bi_inertia, Bi_prom, Bi_savg, Bi_sent, Bi_shade, Bi_svar, Bi_var |
土地利用 类型 Land use type | 地上生物 碳密度 Above-ground carbon density | 地下生物 碳密度 Underground carbon density | 土壤碳密度 Soil carbon density | 死亡有机质 碳密度 Dead organic matter carbon density |
---|---|---|---|---|
耕地 Farmland | 7.32 (17.0) | 34.73 (80.7) | 101.87 (108.4) | 4.23 (9.82) |
有林地 Forest land | 18.24 (42.4) | 49.87 (115.9) | 149.24 (158.8) | 6.07 (14.11) |
草地 Grassland | 15.19 (35.3) | 37.22 (86.5) | 93.89 (99.9) | 3.13 (7.28) |
水域 Water | 0.13 (0.3) | 0 (0) | 0 (0) | 0 (0) |
建设用地 Construction land | 1.08 (2.5) | 11.83 (27.5) | 0 (0) | 0 (0) |
未利用地 Unused land | 0.56 (1.30) | 0 (0) | 20.30 (21.60) | 0 (0) |
灌木林地 Shrub land | 3.42 | 1.62 | 91.70 | 3.48 |
疏林地 Sparse forest land | 5.47 (12.72) | 14.96 (34.77) | 149.24 (158.80) | 6.07 (14.11) |
Table 4 Modified carbon densities of different land use types in Songhua River Basin (t∙hm-2)
土地利用 类型 Land use type | 地上生物 碳密度 Above-ground carbon density | 地下生物 碳密度 Underground carbon density | 土壤碳密度 Soil carbon density | 死亡有机质 碳密度 Dead organic matter carbon density |
---|---|---|---|---|
耕地 Farmland | 7.32 (17.0) | 34.73 (80.7) | 101.87 (108.4) | 4.23 (9.82) |
有林地 Forest land | 18.24 (42.4) | 49.87 (115.9) | 149.24 (158.8) | 6.07 (14.11) |
草地 Grassland | 15.19 (35.3) | 37.22 (86.5) | 93.89 (99.9) | 3.13 (7.28) |
水域 Water | 0.13 (0.3) | 0 (0) | 0 (0) | 0 (0) |
建设用地 Construction land | 1.08 (2.5) | 11.83 (27.5) | 0 (0) | 0 (0) |
未利用地 Unused land | 0.56 (1.30) | 0 (0) | 20.30 (21.60) | 0 (0) |
灌木林地 Shrub land | 3.42 | 1.62 | 91.70 | 3.48 |
疏林地 Sparse forest land | 5.47 (12.72) | 14.96 (34.77) | 149.24 (158.80) | 6.07 (14.11) |
特征 Feature | Landsat 5 TM (41) | 特征 Feature | Landsat 8 OLI (59) |
---|---|---|---|
原始波段 Original band (6) | Bi (i = 1, 2, 3, 4, 5, 7) | 原始波段 Original band (7) | Bi (i = 1, 2, 3, 4, 5, 6, 7) |
波段组合 Band combination (6) | B547, B53, B24, B74, B345, VIS234 | 波段组合 Band combination (11) | B76, B74, ND563, B547, B65, B53, B4/Albedo, B24, VIS234, Albedo, B345 |
植被指数 Vegetation index (16) | SLAVI, NDWI, SAVI, MSR, PVI, NLI, ARVI, LSWI, DVI, RDVI, RVI, NDVI, MVI5, MVI7, EVI, MSAVI | 植被指数 Vegetation index (17) | NDBI, SLAVI, NDWI, NDVI, PVI, SAVI, ARVI, MSR, LSWI, NLI, MSAVI, EVI、RVI, RDVI, MVI5, MVI7, DVI |
纹理特征 Texture feature (13) | B3_savg, B4_savg, B7_savg, B2_savg, B1_savg, B5_savg, B4_shade, B5_shade, B4_corr, B4_imcorr1, B5_idm, B3_shade, B5_imcorr1 | 纹理特征 Texture feature (24) | B6_savg, B3_savg, B4_savg, B7_savg, B2_savg, B1_savg, B6_shade, B5_savg, B2_shade, B6_asm, B3_shade, B5_idm, B6_idm, B7_shade, B5_corr, B5_sent, B5_imcorr2, B5_var, B4_corr, B5_shade, B1_shade, B3_imcorr1, B3_corr, B5_ent |
Table 5 After filtrating classification feature distribution in Songhua River Basin from 1986 to 2022
特征 Feature | Landsat 5 TM (41) | 特征 Feature | Landsat 8 OLI (59) |
---|---|---|---|
原始波段 Original band (6) | Bi (i = 1, 2, 3, 4, 5, 7) | 原始波段 Original band (7) | Bi (i = 1, 2, 3, 4, 5, 6, 7) |
波段组合 Band combination (6) | B547, B53, B24, B74, B345, VIS234 | 波段组合 Band combination (11) | B76, B74, ND563, B547, B65, B53, B4/Albedo, B24, VIS234, Albedo, B345 |
植被指数 Vegetation index (16) | SLAVI, NDWI, SAVI, MSR, PVI, NLI, ARVI, LSWI, DVI, RDVI, RVI, NDVI, MVI5, MVI7, EVI, MSAVI | 植被指数 Vegetation index (17) | NDBI, SLAVI, NDWI, NDVI, PVI, SAVI, ARVI, MSR, LSWI, NLI, MSAVI, EVI、RVI, RDVI, MVI5, MVI7, DVI |
纹理特征 Texture feature (13) | B3_savg, B4_savg, B7_savg, B2_savg, B1_savg, B5_savg, B4_shade, B5_shade, B4_corr, B4_imcorr1, B5_idm, B3_shade, B5_imcorr1 | 纹理特征 Texture feature (24) | B6_savg, B3_savg, B4_savg, B7_savg, B2_savg, B1_savg, B6_shade, B5_savg, B2_shade, B6_asm, B3_shade, B5_idm, B6_idm, B7_shade, B5_corr, B5_sent, B5_imcorr2, B5_var, B4_corr, B5_shade, B1_shade, B3_imcorr1, B3_corr, B5_ent |
分类器 Classifier | 精度 Accuracy (%) | 耕地 Farmland | 有林地 Forest land | 草地 Grassland | 水域 Water | 建设用地 Construction land | 未利用地 Unused land | 灌木林地 Shrubland | 疏林地 Sparse forest land |
---|---|---|---|---|---|---|---|---|---|
RF | UA | 96.31 ± 0.80 | 96.44 ± 1.09 | 93.15 ± 1.28 | 97.39 ± 2.00 | 95.37 ± 2.76 | 94.18 ± 1.55 | 100.00 ± 0.00 | 98.68 ± 1.07 |
PA | 98.54 ± 0.45 | 98.70 ± 0.34 | 87.94 ± 2.30 | 91.82 ± 2.79 | 93.15 ± 2.81 | 85.24 ± 2.13 | 69.82 ± 2.59 | 80.00 ± 1.63 | |
OA | 96.11 ± 0.51 | ||||||||
CART | UA | 96.13 ± 0.60 | 96.79 ± 0.72 | 84.40 ± 1.40 | 92.92 ± 2.56 | 92.24 ± 2.57 | 83.64 ± 3.17 | 72.35 ± 5.74 | 73.71 ± 5.68 |
PA | 96.27 ± 0.62 | 96.44 ± 0.44 | 84.09 ± 2.20 | 90.31 ± 2.37 | 91.41 ± 1.86 | 78.65 ± 1.68 | 80.51 ± 1.16 | 82.04 ± 1.42 | |
OA | 94.95 ± 0.51 | ||||||||
SVM | UA | 92.06 ± 1.70 | 92.52 ± 2.44 | 78.60 ± 4.30 | 94.96 ± 2.28 | 94.22 ± 2.40 | 88.73 ± 2.68 | 80.23 ± 6.45 | 78.55 ± 5.41 |
PA | 95.53 ± 0.91 | 95.75 ± 0.53 | 73.02 ± 6.85 | 86.32 ± 1.11 | 83.02 ± 2.85 | 63.97 ± 3.53 | 59.14 ± 10.38 | 61.30 ± 10.79 | |
OA | 90.93 ± 1.25 |
Table 6 Average classification accuracy in Songhua River Basin from 1986 to 2022 (mean ± SD)
分类器 Classifier | 精度 Accuracy (%) | 耕地 Farmland | 有林地 Forest land | 草地 Grassland | 水域 Water | 建设用地 Construction land | 未利用地 Unused land | 灌木林地 Shrubland | 疏林地 Sparse forest land |
---|---|---|---|---|---|---|---|---|---|
RF | UA | 96.31 ± 0.80 | 96.44 ± 1.09 | 93.15 ± 1.28 | 97.39 ± 2.00 | 95.37 ± 2.76 | 94.18 ± 1.55 | 100.00 ± 0.00 | 98.68 ± 1.07 |
PA | 98.54 ± 0.45 | 98.70 ± 0.34 | 87.94 ± 2.30 | 91.82 ± 2.79 | 93.15 ± 2.81 | 85.24 ± 2.13 | 69.82 ± 2.59 | 80.00 ± 1.63 | |
OA | 96.11 ± 0.51 | ||||||||
CART | UA | 96.13 ± 0.60 | 96.79 ± 0.72 | 84.40 ± 1.40 | 92.92 ± 2.56 | 92.24 ± 2.57 | 83.64 ± 3.17 | 72.35 ± 5.74 | 73.71 ± 5.68 |
PA | 96.27 ± 0.62 | 96.44 ± 0.44 | 84.09 ± 2.20 | 90.31 ± 2.37 | 91.41 ± 1.86 | 78.65 ± 1.68 | 80.51 ± 1.16 | 82.04 ± 1.42 | |
OA | 94.95 ± 0.51 | ||||||||
SVM | UA | 92.06 ± 1.70 | 92.52 ± 2.44 | 78.60 ± 4.30 | 94.96 ± 2.28 | 94.22 ± 2.40 | 88.73 ± 2.68 | 80.23 ± 6.45 | 78.55 ± 5.41 |
PA | 95.53 ± 0.91 | 95.75 ± 0.53 | 73.02 ± 6.85 | 86.32 ± 1.11 | 83.02 ± 2.85 | 63.97 ± 3.53 | 59.14 ± 10.38 | 61.30 ± 10.79 | |
OA | 90.93 ± 1.25 |
面积 Area (km2) | 2022年 Year 2022 | ||||||||
---|---|---|---|---|---|---|---|---|---|
耕地 Farmland | 有林地 Forest land | 草地 Grassland | 水域 Water | 建设用地 Construction land | 未利用地 Unused land | 灌木林地 Shrub land | 疏林地 Sparse forest land | ||
1986年 Year 1986 | 耕地 Farmland | 207 453.66 | 13 937.97 | 9 681.31 | 2 551.13 | 5 555.53 | 7 654.9 | 2.48 | 99.93 |
有林地 Forest land | 30 620.98 | 196 805.08 | 8 890.87 | 455.72 | 170.39 | 673.10 | 1.80 | 254.39 | |
草地 Grassland | 12 618.49 | 7 737.45 | 14 586.81 | 165.69 | 152.94 | 326.89 | 2.86 | 146.23 | |
水域 Water | 1 982.64 | 84.02 | 115.34 | 7 485.19 | 454.06 | 2 005.93 | 0.00 | 0.36 | |
建设用地 Construction land | 2 104.01 | 53.70 | 141.51 | 404.59 | 2 091.40 | 972.07 | 0.03 | 0.47 | |
未利用地 Unused land | 3 500.47 | 420.91 | 515.34 | 967.51 | 847.69 | 4 927.76 | 0.05 | 0.97 | |
灌木林地 Shrubland | 14.55 | 9.37 | 17.75 | 0.07 | 0.10 | 0.11 | 0.05 | 0.24 | |
疏林地 Sparse forest land | 108.25 | 256.62 | 191.59 | 3.30 | 1.49 | 5.37 | 0.06 | 6.60 |
Table 7 Land use/cover change and its changes in Songhua River Basin from 1986 to 2022 (km2)
面积 Area (km2) | 2022年 Year 2022 | ||||||||
---|---|---|---|---|---|---|---|---|---|
耕地 Farmland | 有林地 Forest land | 草地 Grassland | 水域 Water | 建设用地 Construction land | 未利用地 Unused land | 灌木林地 Shrub land | 疏林地 Sparse forest land | ||
1986年 Year 1986 | 耕地 Farmland | 207 453.66 | 13 937.97 | 9 681.31 | 2 551.13 | 5 555.53 | 7 654.9 | 2.48 | 99.93 |
有林地 Forest land | 30 620.98 | 196 805.08 | 8 890.87 | 455.72 | 170.39 | 673.10 | 1.80 | 254.39 | |
草地 Grassland | 12 618.49 | 7 737.45 | 14 586.81 | 165.69 | 152.94 | 326.89 | 2.86 | 146.23 | |
水域 Water | 1 982.64 | 84.02 | 115.34 | 7 485.19 | 454.06 | 2 005.93 | 0.00 | 0.36 | |
建设用地 Construction land | 2 104.01 | 53.70 | 141.51 | 404.59 | 2 091.40 | 972.07 | 0.03 | 0.47 | |
未利用地 Unused land | 3 500.47 | 420.91 | 515.34 | 967.51 | 847.69 | 4 927.76 | 0.05 | 0.97 | |
灌木林地 Shrubland | 14.55 | 9.37 | 17.75 | 0.07 | 0.10 | 0.11 | 0.05 | 0.24 | |
疏林地 Sparse forest land | 108.25 | 256.62 | 191.59 | 3.30 | 1.49 | 5.37 | 0.06 | 6.60 |
土地利用类型 Land use/cover type | 由其他地类转入面积 From other land use into area (km2) | IRLi (%) | 向其他地类转移面积 Transfer area to other land use (km2) | TRLi (%) | 变化面积 Area of change (km2) | CCLi (%) |
---|---|---|---|---|---|---|
耕地 Farmland | 50 949.39 | 0.6 | 39 483.25 | 0.4 | 90 432.64 | 1.0 |
有林地 Forest land | 22 500.04 | 0.3 | 41 067.25 | 0.5 | 63 567.29 | 0.8 |
草地 Grassland | 19 553.71 | 1.5 | 21 150.55 | 1.6 | 40 704.26 | 3.1 |
水域 Water | 4 548.01 | 1.0 | 4 642.35 | 1.1 | 9 190.36 | 2.1 |
建设用地 Construction land | 7 182.20 | 3.5 | 3 676.38 | 1.8 | 10 858.58 | 5.3 |
未利用地 Unused land | 11 638.37 | 2.9 | 6 252.94 | 1.6 | 17 891.31 | 4.5 |
灌木林地 Shrubland | 7.28 | 0.5 | 42.19 | 2.8 | 49.47 | 3.3 |
疏林地 Sparse forest land | 502.59 | 2.4 | 465.03 | 2.3 | 967.62 | 4.7 |
Table 8 Land use/cover type change and its change rate in Songhua River Basin from 1986 to 2022
土地利用类型 Land use/cover type | 由其他地类转入面积 From other land use into area (km2) | IRLi (%) | 向其他地类转移面积 Transfer area to other land use (km2) | TRLi (%) | 变化面积 Area of change (km2) | CCLi (%) |
---|---|---|---|---|---|---|
耕地 Farmland | 50 949.39 | 0.6 | 39 483.25 | 0.4 | 90 432.64 | 1.0 |
有林地 Forest land | 22 500.04 | 0.3 | 41 067.25 | 0.5 | 63 567.29 | 0.8 |
草地 Grassland | 19 553.71 | 1.5 | 21 150.55 | 1.6 | 40 704.26 | 3.1 |
水域 Water | 4 548.01 | 1.0 | 4 642.35 | 1.1 | 9 190.36 | 2.1 |
建设用地 Construction land | 7 182.20 | 3.5 | 3 676.38 | 1.8 | 10 858.58 | 5.3 |
未利用地 Unused land | 11 638.37 | 2.9 | 6 252.94 | 1.6 | 17 891.31 | 4.5 |
灌木林地 Shrubland | 7.28 | 0.5 | 42.19 | 2.8 | 49.47 | 3.3 |
疏林地 Sparse forest land | 502.59 | 2.4 | 465.03 | 2.3 | 967.62 | 4.7 |
Fig. 4 Map of changes in carbon storage in Songhua River Basin from 1986 to 2022. A, Carbon Storage. B, M-K mutation test. UB is distribution in time series k of UBk; UF is distribution in time series k of UFk.
Fig. 5 Significant distribution of carbon storage trends in Songhua River Basin during 1986-2022. CM, Changbai Mountain; DH, Da Hinggan Mountains; XH, Xiao Hinggan Mountains. BS, basically stable; DD, dramatic decline; DI, dramatic increased; SD, significant decline; SI, significant increased; SSD, slight significant decline; SSI, slight significant increased.
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