[1] 刘腾艳, 毛方杰, 李雪建, 等. 浙江省竹林地上碳储量的时空动态模拟及影响因素[J]. 应用生态学报, 2019, 30(5): 1743−1753. LIU Tengyan, MAO Fangjie, LI Xuejian, et al. Spatiotemporal dynamic simulation on aboveground carbon storage of bamboo forest and its influence factors in Zhejiang Province, China[J]. Chinese Journal of Applied Ecology, 2019, 30(5): 1743−1753. DOI: 10.13287/j.1001-9332.201905.035.

LIU Tengyan, MAO Fangjie, LI Xuejian, et al. Spatiotemporal dynamic simulation on aboveground carbon storage of bamboo forest and its influence factors in Zhejiang Province, China[J]. Chinese Journal of Applied Ecology, 2019, 30(5): 1743−1753. DOI: 10.13287/j.1001-9332.201905.035.
[2] 那雪迎. 中国森林碳储量变化及固碳潜力的研究[J]. 现代园艺, 2024, 47(15): 59−63. NA Xueying. Changes in forest carbon stocks and carbon sequestration potential in China[J]. Contemporary Horticulture, 2024, 47(15): 59−63. DOI: 10.14051/j.cnki.xdyy.2024.15.047.

NA Xueying. Changes in forest carbon stocks and carbon sequestration potential in China[J]. Contemporary Horticulture, 2024, 47(15): 59−63. DOI: 10.14051/j.cnki.xdyy.2024.15.047.
[3] 李顺龙, 杜咏梅, 蒋敏元. 我国森林碳汇问题初探[J]. 林业财务与会计, 2004(7): 5−6. LI Shunlong, DU Yongmei, JIANG Minyuan. Preliminary study of forest carbon sinks in China[J]. Forestry Finance & Accounting, 2004(7): 5−6. DOI: 10.14153/j.cnki.lsck.2004.07.002.

LI Shunlong, DU Yongmei, JIANG Minyuan. Preliminary study of forest carbon sinks in China[J]. Forestry Finance & Accounting, 2004(7): 5−6. DOI: 10.14153/j.cnki.lsck.2004.07.002.
[4] 黄丽媛, 陈钦. 中国森林碳汇研究综述[C]//宋维明, 刘东生, 陈建成, 等. 低碳经济与林业发展论——中国林业学术论坛·第6辑. 北京: 中国林业出版社, 2009: 154−164. HUANG Liyuan, CHEN Qin. A study about theoretical basis and status of China forest carbon sinks[C]//SONG Weiming, LIU Dongsheng, CHEN Jiancheng, et al. Low-Carbon Economy and Forestry Development: Proceedings of China Forestry Academic Forum China (No. 6). Beijing: China Forestry Publishing House, 2009: 154−164.

HUANG Liyuan, CHEN Qin. A study about theoretical basis and status of China forest carbon sinks[C]//SONG Weiming, LIU Dongsheng, CHEN Jiancheng, et al. Low-Carbon Economy and Forestry Development: Proceedings of China Forestry Academic Forum China (No. 6). Beijing: China Forestry Publishing House, 2009: 154−164.
[5] 卫格冉, 李明泽, 全迎, 等. 基于地理加权随机森林的黑龙江省森林碳储量遥感估测[J]. 中南林业科技大学学报, 2024, 44(7): 64−76. WEI Geran, LI Mingze, QUAN Ying, et al. Geographically weighted random forest approach to predict forest carbon storage by remote sensing in Heilongjiang[J]. Journal of Central South University of Forestry & Technology, 2024, 44(7): 64−76. DOI: 10.14067/j.cnki.1673-923x.2024.07.008.

WEI Geran, LI Mingze, QUAN Ying, et al. Geographically weighted random forest approach to predict forest carbon storage by remote sensing in Heilongjiang[J]. Journal of Central South University of Forestry & Technology, 2024, 44(7): 64−76. DOI: 10.14067/j.cnki.1673-923x.2024.07.008.
[6] 龙依, 蒋馥根, 孙华, 等. 基于带宽优选地理加权回归模型的深圳市植被碳储量反演[J]. 生态学报, 2022, 42(12): 4933−4945. LONG Yi, JIANG Fugen, SUN Hua, et al. Estimating vegetation carbon storage based on optimal bandwidth selected from geographically weighted regression model in Shenzhen City[J]. Acta Ecologica Sinica, 2022, 42(12): 4933−4945. DOI: 10.5846/stxb202102260545.

LONG Yi, JIANG Fugen, SUN Hua, et al. Estimating vegetation carbon storage based on optimal bandwidth selected from geographically weighted regression model in Shenzhen City[J]. Acta Ecologica Sinica, 2022, 42(12): 4933−4945. DOI: 10.5846/stxb202102260545.
[7] FENG Rui, HU Liting, HU Xiaoyi, et al. Knowledge gaps are making it harder to formulate national climate policies[J]. Proceedings of the National Academy of Sciences of the United States of America, 2023, 120(23): e2218563120. DOI: 10.1073/pnas.2218563120.
[8] HUANG Bo, WU Bo, BARRY M. Geographically and temporally weighted regression for modeling spatio-temporal variation in house prices[J]. International Journal of Geographical Information Science, 2010, 24(3): 383−401. DOI: 10.1080/13658810802672469.
[9] 张小勇. 基于时空地理加权回归的森林碳储量分布研究[D]. 哈尔滨: 东北林业大学, 2023. ZHANG Xiaoyong. A Study of Forest Carbon Stock Distribution Based on Spatio-temporal Geographically Weighted Regression[D]. Harbin: Northeast Forestry University, 2023. DOI: 10.27009/d.cnki.gdblu.2023.000483.

ZHANG Xiaoyong. A Study of Forest Carbon Stock Distribution Based on Spatio-temporal Geographically Weighted Regression[D]. Harbin: Northeast Forestry University, 2023. DOI: 10.27009/d.cnki.gdblu.2023.000483.
[10] 王可月, 王轶夫, 陈馨, 等. 基于集成学习算法和Optuna调优的江西省森林碳储量遥感估测[J]. 生态学报, 2025, 45(2): 685−700. WANG Keyue, WANG Yifu, CHEN Xin, et al. Remote sensing estimation of forest carbon storage in Jiangxi Province based on ensemble learning algorithm and Optuna tuning[J]. Acta Ecologica Sinica, 2025, 45(2): 685−700. DOI: 10.20103/j.stxb.202403150536.

WANG Keyue, WANG Yifu, CHEN Xin, et al. Remote sensing estimation of forest carbon storage in Jiangxi Province based on ensemble learning algorithm and Optuna tuning[J]. Acta Ecologica Sinica, 2025, 45(2): 685−700. DOI: 10.20103/j.stxb.202403150536.
[11] 史川, 胥辉, 张成程. 滇中地区针叶林碳储量遥感反演及动态变化分析[J]. 现代农业研究, 2025, 31(3): 83−85. SHI Chuan, XU Hui, ZHANG Chengcheng. Remote sensing inversion and dynamic change analysis of carbon storage in coniferous forests in central Yunnan[J]. Modern Agriculture Research, 2025, 31(3): 83−85. DOI: 10.19704/j.cnki.xdnyyj.2025.03.017.

SHI Chuan, XU Hui, ZHANG Chengcheng. Remote sensing inversion and dynamic change analysis of carbon storage in coniferous forests in central Yunnan[J]. Modern Agriculture Research, 2025, 31(3): 83−85. DOI: 10.19704/j.cnki.xdnyyj.2025.03.017.
[12] LIU Minghao, LUO Xiaolin, QI Liai, et al. Simulation of the spatiotemporal distribution of PM2.5 concentration based on GTWR-XGBoost two-stage model: a case study of Chengdu Chongqing economic circle[J]. Atmosphere, 2023, 14(1): 115. DOI: 10.3390/atmos14010115.
[13] 张琦曼. “三江并流”世界自然遗产地生态连接度及空间分异研究[D]. 云南: 云南大学, 2015. ZHANG Qiman. Research on the Ecological Connectivity and Spatial Differentiation inThree Parallel Riversof Yunnan Protected Areas[D]. Kunming: Yunnan University, 2015.

ZHANG Qiman. Research on the Ecological Connectivity and Spatial Differentiation inThree Parallel Riversof Yunnan Protected Areas[D]. Kunming: Yunnan University, 2015.
[14] 杨博文, 刘凤莲, 陈洪敏. 三江并流区森林植被时空演变及驱动因素[J]. 森林工程, 2025, 41(1): 108−125. YANG Bowen, LIU Fenglian, CHEN Hongmin. Spatial-temporal evolution and driving factors of forest vegetation in the three parallel rivers region[J]. Forest Engineering, 2025, 41(1): 108−125. DOI: 10.7525/j.issn.1006-8023.2025.01.009.

YANG Bowen, LIU Fenglian, CHEN Hongmin. Spatial-temporal evolution and driving factors of forest vegetation in the three parallel rivers region[J]. Forest Engineering, 2025, 41(1): 108−125. DOI: 10.7525/j.issn.1006-8023.2025.01.009.
[15] 顾纯僖, 欧光龙, 刘畅, 等. 思茅松森林碳储量动态预测研究[J]. 西南林业大学学报(自然科学), 2024, 44(6): 150−157. GU Chunxi, OU Guanglong, LIU Chang, et al. Dynamic prediction of carbon storage in Pinus kesiya var. Langbianensis forest[J]. Journal of Southwest Forestry University (Natural Science), 2024, 44(6): 150−157. DOI: 10.11929/j.swfu.202309043.

GU Chunxi, OU Guanglong, LIU Chang, et al. Dynamic prediction of carbon storage in Pinus kesiya var. Langbianensis forest[J]. Journal of Southwest Forestry University (Natural Science), 2024, 44(6): 150−157. DOI: 10.11929/j.swfu.202309043.
[16] FANG Jingyun, CHEN Anping, PENG Changhui, et al. Changes in forest biomass carbon storage in China between 1949 and 1998[J]. Science, 2001, 292(5525): 2320−2322. DOI: 10.1126/science.1058629.
[17] 方精云, 刘国华, 徐嵩龄. 我国森林植被的生物量和净生产量[J]. 生态学报, 1996, 16(5): 497−508. FANG Jingyun, LIU Guohua, XU Songling. Biomass and net production of forest vegetation in China[J]. Acta Ecologica Sinica, 1996, 16(5): 497−508.

FANG Jingyun, LIU Guohua, XU Songling. Biomass and net production of forest vegetation in China[J]. Acta Ecologica Sinica, 1996, 16(5): 497−508.
[18] 涂宏涛, 周红斌, 马国强, 等. 基于第九次森林资源清查的云南森林碳储量特征研究[J]. 西北林学院学报, 2023, 38(3): 185−193. TU Hongtao, ZHOU Hongbin, MA Guoqiang, et al. Characteristics of forest carbon storage in Yunnan based on the ninth forest inventory data[J]. Journal of Northwest Forestry University, 2023, 38(3): 185−193. DOI: 10.3969/j.issn.1001-7461.2023.03.25.

TU Hongtao, ZHOU Hongbin, MA Guoqiang, et al. Characteristics of forest carbon storage in Yunnan based on the ninth forest inventory data[J]. Journal of Northwest Forestry University, 2023, 38(3): 185−193. DOI: 10.3969/j.issn.1001-7461.2023.03.25.
[19] 郭含茹, 张茂震, 徐丽华, 等. 基于地理加权回归的区域森林碳储量估计[J]. 浙江农林大学学报, 2015, 32(4): 497−508. GUO Hanru, ZHANG Maozhen, XU Lihua, et al. Geographically weighted regression based on estimation of regional forest carbon storage[J]. Journal of Zhejiang A&F University, 2015, 32(4): 497−508. DOI: 10.11833/j.issn.2095-0756.2015.04.002.

GUO Hanru, ZHANG Maozhen, XU Lihua, et al. Geographically weighted regression based on estimation of regional forest carbon storage[J]. Journal of Zhejiang A&F University, 2015, 32(4): 497−508. DOI: 10.11833/j.issn.2095-0756.2015.04.002.
[20] 王岩, 刘纪平, 赵阳阳, 等. 基于GTWR模型的3 km京津冀PM2.5时空分布和影响因素分析[J]. 测绘通报, 2024(6): 82−89. WANG Yan, LIU Jiping, ZHAO Yangyang, et al. Spatial and temporal distribution and influencing factors of PM2.5 in 3 km Beijing-Tianjin-Hebei region based on GTWR model[J]. Bulletin of Surveying and Mapping, 2024(6): 82−89. DOI: 10.13474/j.cnki.11-2246.2024.0615.

WANG Yan, LIU Jiping, ZHAO Yangyang, et al. Spatial and temporal distribution and influencing factors of PM2.5 in 3 km Beijing-Tianjin-Hebei region based on GTWR model[J]. Bulletin of Surveying and Mapping, 2024(6): 82−89. DOI: 10.13474/j.cnki.11-2246.2024.0615.
[21] 吴宇宏, 杜宁, 王莉, 等. 基于iLME+Geoi-RF模型的四川省PM2.5浓度估算[J]. 环境科学, 2021, 42(12): 5602−5615. WANG Yuhong, DU Ning, WANG Li, et al. Estimation of PM2.5 concentration in Sichuan Province based on improved linear mixed effect model and geo-intelligent random forest[J]. Environmental Science, 2021, 42(12): 5602−5615. DOI: 10.13227/j.hjkx.202102048.

WANG Yuhong, DU Ning, WANG Li, et al. Estimation of PM2.5 concentration in Sichuan Province based on improved linear mixed effect model and geo-intelligent random forest[J]. Environmental Science, 2021, 42(12): 5602−5615. DOI: 10.13227/j.hjkx.202102048.
[22] 许传青, 杨洋, 杨震, 等. 基于GTWR模型的昌平区肺结核发病影响因素分析[J]. 数学的实践与认识, 2025, 55(4): 173−185. XU Chuanqing, YANG Yang, YANG Zhen, et al. Analysis of factors influencing the incidence of tuberculosis in Changping District based on GTWR modeling[J]. Mathematics in Practice and Theory, 2025, 55(4): 173−185. DOI: 10.20266/j.math.24-0948.

XU Chuanqing, YANG Yang, YANG Zhen, et al. Analysis of factors influencing the incidence of tuberculosis in Changping District based on GTWR modeling[J]. Mathematics in Practice and Theory, 2025, 55(4): 173−185. DOI: 10.20266/j.math.24-0948.
[23] 顾丽, 杨惠媛, 曾友鼎, 等. 基于土地利用变化的中国陆地生态系统碳储量时空演变与预测[J]. 西北林学院学报, 2025, 40(3): 141−152. GU Li, YANG Huiyuan, ZENG Youding, et al. Spatio-temporal evolution and prediction of carbon storage in China’s terrestrial ecosystems based on land use change[J]. Journal of Northwest Forestry University, 2025, 40(3): 141−152. DOI: 10.3969/j.issn.1001-7461.2025.03.17.

GU Li, YANG Huiyuan, ZENG Youding, et al. Spatio-temporal evolution and prediction of carbon storage in China’s terrestrial ecosystems based on land use change[J]. Journal of Northwest Forestry University, 2025, 40(3): 141−152. DOI: 10.3969/j.issn.1001-7461.2025.03.17.
[24] YANG Bing, WU Sensen, YAN Zhen. Effects of climate change on corn yields: spatiotemporal evidence from geographically and temporally weighted regression model[J]. ISPRS International Journal of Geo-Information, 2022, 11(8): 433. DOI: 10.3390/ijgi11080433.
[25] 吴再昆, 周文武, 舒清态, 等. 基于ICESat-2/ATLAS数据的龙竹地上生物量估测[J]. 中南林业科技大学学报, 2025, 45(1): 48−57. WU Zaikun, ZHOU Wenwu, SHU Qingtai, et al. Estimation of aboveground biomass of Dendrocalamus giganteus based on ICESat-2/ATLAS data[J]. Journal of Central South University of Forestry & Technology, 2025, 45(1): 48−57. DOI: 10.14067/j.cnki.1673-923x.2025.01.006.

WU Zaikun, ZHOU Wenwu, SHU Qingtai, et al. Estimation of aboveground biomass of Dendrocalamus giganteus based on ICESat-2/ATLAS data[J]. Journal of Central South University of Forestry & Technology, 2025, 45(1): 48−57. DOI: 10.14067/j.cnki.1673-923x.2025.01.006.
[26] 汤浩藩, 许彦红, 艾建林. 云南省森林植被碳储量和碳密度及其空间分布格局[J]. 林业资源管理, 2019(5): 37−43. TANG Haofan, XU Yanhong, AI Jianlin. Carbon storage and carbon density of forest vegetation and their spatial distribution pattern in Yunnan Province[J]. Forest Resources Management, 2019(5): 37−43. DOI: 10.13466/j.cnki.lyzygl.2019.05.008.

TANG Haofan, XU Yanhong, AI Jianlin. Carbon storage and carbon density of forest vegetation and their spatial distribution pattern in Yunnan Province[J]. Forest Resources Management, 2019(5): 37−43. DOI: 10.13466/j.cnki.lyzygl.2019.05.008.
[27] CHENG Fengyun, OU Guanglong, WANG Meng, et al. Remote sensing estimation of forest carbon stock based on machine learning algorithms[J]. Forests, 2024, 15(4): 681. DOI: 10.3390/f15040681.
[28] 梁瑄, 李春波. 云南省森林碳汇现状与潜力分析[J]. 中国农学通报, 2023, 39(30): 47−53. LIANG Xuan, LI Chunbo. Analysis of current situation and potential of forest carbon sink in Yunnan Province[J]. Chinese Agricultural Science Bulletin, 2023, 39(30): 47−53. DOI: 10.11924/j.issn.1000-6850.casb2022-0909.

LIANG Xuan, LI Chunbo. Analysis of current situation and potential of forest carbon sink in Yunnan Province[J]. Chinese Agricultural Science Bulletin, 2023, 39(30): 47−53. DOI: 10.11924/j.issn.1000-6850.casb2022-0909.
[29] 范华鹏, 刘畅, 程锋云. 基于不同机器学习分类算法的滇西北森林碳储量估测[J/OL]. 西南林业大学学报(自然科学), 2025-04-25[2025-06-10]. https://link.cnki.net/urlid/53.1218.S.20250425.0101.002. FAN Huapeng, LIU Chang, CHENG Fengyun. The estimation of forest carbon storage in northwest Yunnan based on different machine learning classification algorithms[J/OL]. Journal of Southwest Forestry University, 2025-04-25[2025-06-10]. https://link.cnki.net/urlid/53.1218.S.20250425.0101.002.

FAN Huapeng, LIU Chang, CHENG Fengyun. The estimation of forest carbon storage in northwest Yunnan based on different machine learning classification algorithms[J/OL]. Journal of Southwest Forestry University, 2025-04-25[2025-06-10]. https://link.cnki.net/urlid/53.1218.S.20250425.0101.002.
[30] 穆喜云, 刘清旺, 庞勇, 等. 基于机载激光雷达的森林地上碳储量估测[J]. 东北林业大学学报, 2016, 44(11): 52−56. MU Xiyun, LIU Qingwang, PANG Yong, et al. Forest aboveground carbon storage using RF algorithmic model and airborne LiDAR data[J]. Journal of Northeast Forestry University, 2016, 44(11): 52−56. DOI: 10.13759/j.cnki.dlxb.2016.11.011.

MU Xiyun, LIU Qingwang, PANG Yong, et al. Forest aboveground carbon storage using RF algorithmic model and airborne LiDAR data[J]. Journal of Northeast Forestry University, 2016, 44(11): 52−56. DOI: 10.13759/j.cnki.dlxb.2016.11.011.