近20年来肥城市林地时空变化及其驱动因子

doi:10.11707/j.1001-7488.LYKX20220731

摘要/Abstract

摘要：

目的: 提取肥城市不同时期的林地信息，分析林地时空变化特征，挖掘林地面积变化的驱动因子，为区域林地资源监测、管理和可持续发展提供参考。方法: 以肥城市为研究区，基于2000—2020年21期Landsat遥感数据，首先对Landsat遥感数据进行辐射定标、大气校正等预处理，采用决策树分类法对遥感数据进行土地类型解译，提取林地相关信息；然后揭示近20年来林地时空变化特征；最后构建新的环境压力模型（IPAT），分析林地面积变化的驱动因子。结果: 基于决策树规则提取的肥城市林地信息用户精度达94.7%，具有较高的解译精度。解译结果表明，近20年来林地面积在波动性中呈增长趋势，净增加17 463.54 hm²；增加的林地主要分布在肥城市中部和北部矿区，减少的林地则集中分布于中部林地的边缘部分，最终呈现中部和北部集中分布、其他地区零星分布的空间特征。改进的环境压力模型（IPAT）表明，林地禀赋价值是肥城市林地面积变化的主要驱动因子（贡献率超80.3%），富裕程度是次要驱动因素，二者贡献比例超过改进IPAT模型4个因子总贡献率的92%；林业产值对国内生产总值的贡献率和人口数量对林地面积变化的影响相对较小。结论: 基于决策树分类法对遥感数据解译能够准确提取肥城市林地信息并监测林地动态变化，林地禀赋价值对林地面积变化有显著影响。

关键词: 林地, Landsat数据, 林地禀赋价值, 变化, IPAT模型, 驱动因子

Abstract:

Objective: Monitoring forest resources and its spatio-temporal changes using time-series remote sensing datasets and extracting the driving factors has a great significance in achieving scientific management and efficient utilization of regional forest land resources. Method: This study identified Feicheng City, Shandong Province as a case study, extracted the distribution information of land type from 2000 to 2020 by decision tree classification based on the 21-period Landsat remote sensing datasets, which was preprocessed by radiation calibration and atmospheric correction, and also analyzed spatio-temporal change and its driving factors of forest based on the renovated IPAT model. Result: The extracted forest land information based on decision tree classification achieved a high accuracy, which yield more than 94.7% of user’s accuracy. In the past 20 years, the area of forest land fluctuated with a net increase of 17 463.54 hm², and the increased forest land was concentrated in the central parts and northern mining area of Feicheng City, while the decreased forest land was centralized in the edge part of the central forest land, thus indicating the spatial characteristics of concentrated distribution in the central and northern parts and sporadic distribution in other areas. The renovated IPAT model showed that the endowment value of forest land was the main driving factor for the area change in Feicheng City ( the contribution larger than 80.3%), and the degree of affluence was the secondary driving factor. The contribution of both factors exceeded 92% of the total contribution of the four factors in the renovated IPAT model. In contrast, forest industry and the population posed little influence. Conclusion: Forest resources could be accurately extracted and monitored based on decision tree classification, and the endowment value of forest land has significant influences on the spatio-temporal evolution of forest land.

Key words: forest land, Landsat dataset, forest land endowment value, change, IPAT model, driving factors

中图分类号:

S718.5

李祎,单博文,杨丽,覃钧,石雷. 近20年来肥城市林地时空变化及其驱动因子[J]. 林业科学, 2024, 60(7): 40-46.

Yi Li,Bowen Shan,Li Yang,Jun Qin,Lei Shi. Spatio-Temporal Change of Forest Lands of Feicheng City and Its Driving Factorsin the Past 20 Years[J]. Scientia Silvae Sinicae, 2024, 60(7): 40-46.

图/表 4

参考文献 0

	崔绿园, 李　晶, 邓晓娟, 等. 重点区域林地时空变化特征及驱动力分析. 中国农业大学学报, 2021, 26 (3): 164- 175. doi: 10.11841/j.issn.1007-4333.2021.03.17
	Cui L Y, Li J, Deng X J, et al. Analysis of spatial and temporal change characteristics of forest land and its driving forces in key areas. Journal of China Agricultural University, 2021, 26 (3): 164- 175. doi: 10.11841/j.issn.1007-4333.2021.03.17
	高明秀, 王瑷玲. 县域土地整治的路径探索·经验特色与未来走向: 以山东省肥城市为例. 安徽农业科学, 2015, 43 (35): 300- 303,307. doi: 10.3969/j.issn.0517-6611.2015.35.110
	Gao M X, Wang A L. Path exploration, empirical characteristics and future trend of land consolidation at county scale: taking Feicheng City of Shandong Province as an example. Journal of Anhui Agricultural Sciences, 2015, 43 (35): 300- 303,307. doi: 10.3969/j.issn.0517-6611.2015.35.110
	国家统计局农村社会经济调查司. 2019. 中国县域统计年鉴-2018-县市卷. 北京: 中国统计出版社.
	Agricultural Economic Survey Division, National Bureau of Statistics. 2019. China statistical yearbook (county-level). Beijing: China Statistics Press. ［in Chinese］
	蒋　鸥, 韩德军. 林地资源资产价值核算理论的探讨. 农业与技术, 2021, 41 (17): 63- 66.
	Jiang O, Han D J. Discussion on the theory of forest land resource asset value accounting. Agriculture and Technology, 2021, 41 (17): 63- 66.
	李秀芬, 苏　蕾, 张金鑫, 等. 晋西北防护林30年来时空变化特征及影响要素. 生态学杂志, 2013, 32 (9): 2382- 2389.
	Li X F, Su L, Zhang J X, et al. Spatiotemporal variation characteristics and influencing factors of protection forests after their 30 years construction in northwest Shanxi Province of China. Chinese Journal of Ecology, 2013, 32 (9): 2382- 2389.
	李伊彤, 荣丽华, 李文龙, 等. 生态重要性视角下东北林区县域生态安全格局研究——以呼伦贝尔市阿荣旗为例. 干旱区地理, 2022, 45 (5): 1615- 1625. doi: 10.12118/j.issn.1000-6060.2021.577
	Li Y T, Rong L H, Li W L, et al. Ecological security pattern at county level in northeast forest area of China from the perspective of ecological importance: a case of Arun banner in Hulun Buir City. Arid Land Geography, 2022, 45 (5): 1615- 1625. doi: 10.12118/j.issn.1000-6060.2021.577
	刘　康, 李月娥, 吴　群, 等. 基于Probit回归模型的经济发达地区土地利用变化驱动力分析: 以南京市为例. 应用生态学报, 2015, 26 (7): 2131- 2138.
	Liu K, Li Y E, Wu Q, et al. Driving force analysis of land use change in the developed area based on Probit regression model: a case study of Nanjing City, China. Chinese Journal of Applied Ecology, 2015, 26 (7): 2131- 2138.
	刘晓洁. 2015. 资源枯竭型城市经济转型模式研究——以山东省肥城市为例. 长春: 长春工业大学.
	Liu X J. 2015. Study on economic transformation mode of resource-exhausted cities: taking Feicheng city of Shandong Province as an example. Changchun: Changchun University of Technology. ［in Chinese］
	乔海燕, 马丹丹, 王　甜. 肥城市土地利用变化及驱动力分析. 北京测绘, 2020, 34 (3): 376- 380.
	Qiao H Y, Ma D D, Wang T. Analysis of land use change and driving force in Feicheng. Beijing Surveying and Mapping, 2020, 34 (3): 376- 380.
	孙海鹏, 陈哲晶, 王宇杰, 等. 有林地面积动态变化及经营发展分析. 内蒙古林业科技, 2000, 26 (1): 23- 25.
	Sun H P, Chen Z J, Wang Y J, et al. Dynamic change of forested area and analysis on management delopment. Inner Mongolia Forestry Science & Technology, 2000, 26 (1): 23- 25.
	泰安市统计局. 2021. 泰安市统计年鉴. 北京: 中国统计出版社.
	Taian Bureau of Statistics. 2021. Taian statical yearbook. Beijing: China Statistics Press. ［in Chinese］
	唐丽伟, 焦玉国, 徐　飞, 等. 肥城市采煤塌陷区治理模式探索研究. 山东国土资源, 2020, 36 (2): 56- 60. doi: 10.12128/j.issn.1672-6979.2020.02.009
	Tang L W, Jiao Y G, Xu F, et al. Study on management model of coal mining subsidence area in Feicheng City. Shandong Land and Resources, 2020, 36 (2): 56- 60. doi: 10.12128/j.issn.1672-6979.2020.02.009
	王秀兰, 包玉海. 土地利用动态变化研究方法探讨. 地理科学进展, 1999, 18 (1): 81- 87. doi: 10.3969/j.issn.1007-6301.1999.01.012
	Wang X L, Bao Y H. Study on the methods of land use dynamic change research. Progress in Geography, 1999, 18 (1): 81- 87. doi: 10.3969/j.issn.1007-6301.1999.01.012
	张力小, 梁　竞. 区域资源禀赋对资源利用效率影响研究. 自然资源学报, 2010, 25 (8): 1237- 1247. doi: 10.11849/zrzyxb.2010.08.001
	Zhang L X, Liang J. Effect of the regional resource endowment on resource utilization efficiency. Journal of Natural Resources, 2010, 25 (8): 1237- 1247. doi: 10.11849/zrzyxb.2010.08.001
	张姝婧, 唐丽华, 赵　凯. 环境库兹涅茨曲线模型假设下的森林资源与林业产业关系. 浙江农林大学学报, 2018, 35 (5): 885- 891. doi: 10.11833/j.issn.2095-0756.2018.05.013
	Zhang S J, Tang L H, Zhao K. Dynamic relationship between forest resources and forestry industry: an empirical analysis based on environmental Kuznets curve model. Journal of Zhejiang A & F University, 2018, 35 (5): 885- 891. doi: 10.11833/j.issn.2095-0756.2018.05.013
	张　译, 郑新奇. 2000—2015年河北省林地时空变化特征及驱动力. 水土保持研究, 2018, 25 (2): 269- 273.
	Zhang Y, Zheng X Q. Spatiotemporal patterns and drivers of forest change in Hebei Province from 2000 to 2015. Research of Soil and Water Conservation, 2018, 25 (2): 269- 273.
	赵同谦, 欧阳志云, 郑　华, 等. 中国森林生态系统服务功能及其价值评价. 自然资源学报, 2004, 19 (4): 480- 491. doi: 10.3321/j.issn:1000-3037.2004.04.010
	Zhao T Q, Ouyang Z Y, Zheng H, et al. Forest ecosystem services and their valuation in China. Journal of Natural Resources, 2004, 19 (4): 480- 491. doi: 10.3321/j.issn:1000-3037.2004.04.010
	郑朝菊, 曾　源, 赵玉金, 等. 2016.20世纪90年代以来中国西南地区土地覆被变化. 生态学报, 36(23): 7858−7869.
	Zheng Z J, Zeng Y, Zhao Y J, et al. 2016. Analysis of land cover changes in southwestern China since the 1990s. Acta Ecologica Sinica, 36(23): 7858−7869. ［in Chinese］
	周　维, 刘国华, 段兴武, 等. 滇金丝猴分布区森林面积变化的时空特征及其影响因素. 生态学报, 2022, 42 (2): 791- 803.
	Zhou W, Liu G H, Duan X W, et al. Spatio-temporal characteristics of forest area change and its determinants in the distribution area of Yunnan snub-nosed monkey (Rhinopithecus bieti). Acta Ecologica Sinica, 2022, 42 (2): 791- 803.
	Ajay D, Gangwal R P, Sangamwar A T. IPAT: a freely accessible software tool for analyzing multiple patent documents with inbuilt landscape visualizer. Pharmaceutical Patent Analyst, 2015, 4 (5): 377- 386. doi: 10.4155/ppa.15.25
	Culas R J. Deforestation and the environmental Kuznets curve: an institutional perspective. Ecological Economics, 2007, 61 (2/3): 429- 437.
	Ehrlich P R, Holdren J P. Impact of population growth. Science, 1971, 171 (3977): 1212- 1217. doi: 10.1126/science.171.3977.1212
	Li D Q, Lu D S, Wu M, et al. Examining land cover and greenness dynamics in Hangzhou Bay in 1985—2016 using landsat time-series data. Remote Sensing, 2018, 10 (1): 32.
	Liang L Z, Chen F, Shi L, et al. NDVI-derived forest area change and its driving factors in China. PLoS One, 2018, 13 (10): e0205885. doi: 10.1371/journal.pone.0205885
	Mather A S, Needle C L, Fairbairn J. Environmental kuznets curves and forest trends. Geography, 1999, 84 (1): 55- 65.
	Rodrigues P, Dorresteijn I, Guilherme J L, et al. Predicting the impacts of human population growth on forest mammals in the highlands of southwestern Ethiopia. Biological Conservation, 2021, 256, 109046. doi: 10.1016/j.biocon.2021.109046
	Shi L, Zhao S Q, Tang Z Y, et al. The changes in China’s forests: an analysis using the forest identity. PLoS One, 2011, 6 (6): e20778. doi: 10.1371/journal.pone.0020778
	Song X P, Hansen M C, Stehman S V, et al. Global land change from 1982 to 2016. Nature, 2018, 560, 639- 643. doi: 10.1038/s41586-018-0411-9
	Thomas N, Lucas R, Bunting P, et al. Distribution and drivers of global mangrove forest change, 1996—2010. PLoS One, 2017, 12 (6): e0179302. doi: 10.1371/journal.pone.0179302
	Zhang D W, Li Y S. Forest endowment, logging restrictions, and China’s wood products trade. China Economic Review, 2009, 20 (1): 46- 53. doi: 10.1016/j.chieco.2008.10.013
	Zhang Y Q, Uusivuori J, Kuuluvainen J. Econometric analysis of the causes of forest land use changes in Hainan, China. Canadian Journal of Forest Research, 2000, 30 (12): 1913- 1921. doi: 10.1139/x00-123

项目Item	人口 Population	富裕程度 Degree of affluence	林业产值贡献率 Contribution of forest industry	林地禀赋价值 Endowment value of forest land
绝对变化率 Absolute rate（%）	0.000 6	0.047 6	－0.015 0	－0.016 9
相对变化率 Relative rate（%）	0.032 4	1.042 8	0.624 0	6.942 1
林地面积变化的贡献率Contribution rate to forest land area（%）	0.374 7	12.067 6	7.220 6	80.337 2

[1]	朱教君,王高峰,张怀清,高添. 关于“气候智慧林业”研究的思考[J]. 林业科学, 2024, 60(7): 1-7.
[2]	李伟克,舒立福,王明玉,李威,司莉青,赵凤君,李笑笑,周暖阳. 黑龙江大兴安岭林区雷击火与人为火发生规律及变化趋势[J]. 林业科学, 2024, 60(4): 136-146.
[3]	赵杼祺, 胡振宏, 何鲜, 黄志群. 森林木质残体微生物群落构建机制研究进展[J]. 林业科学, 2024, 60(2): 106-117.
[4]	韩新生,刘广全,许浩,董立国,郭永忠,安钰,万海霞,王月玲. 宁夏黄土区典型坡面表层土壤有机碳含量的空间变化特征及尺度效应[J]. 林业科学, 2024, 60(1): 19-31.
[5]	伍冰晨,齐实,郭郑曦,胡译水. 基于最大熵模型的华蓥山林地浅表层滑坡风险析因[J]. 林业科学, 2024, 60(1): 32-46.
[6]	薛盼盼,缪宁,岳喜明,陶琼,张远东,冯秋红,毛康珊. 青藏高原东缘岷江冷杉径向生长对升温响应分异的坡向和海拔差异[J]. 林业科学, 2023, 59(7): 65-77.
[7]	韦雪蕾,张国钢,贾茹,姬云瑞,徐红英,杨泽玉,刘化金,刘宇霖,杨培宇. 黑龙江兴凯湖水鸟多样性变化及其影响因素[J]. 林业科学, 2023, 59(6): 118-129.
[8]	刘文浩,王晓,段文标,于澎涛,王彦辉,于艺鹏. 西宁市油松人工林生长季水量平衡特征[J]. 林业科学, 2023, 59(4): 46-56.
[9]	严铭海,王金池,黄清麟,庄崇洋,郑群瑞,卓鸣秀,官晓辉. 典型中亚热带天然阔叶林各林层林木高径比分布规律[J]. 林业科学, 2023, 59(4): 149-156.
[10]	何晨阳,闫峰,卢琦,焦岩. 2001—2020年埃及植被生长状况时空变化特征[J]. 林业科学, 2023, 59(3): 65-72.
[11]	赵世魁,郭晋平,张芸香. 暖温带山地天然次生林演替序列根系呼吸速率对林地增温的响应[J]. 林业科学, 2023, 59(2): 10-21.
[12]	王亚,王军辉,王福德,刘逸夫,谭灿灿,袁艳超,聂稳,刘建锋,常二梅,贾子瑞. 末次间冰期以来及未来气候情景下红皮云杉适生分布区模拟[J]. 林业科学, 2023, 59(12): 1-12.
[13]	张淑宁,陈俊兴,敖敦,红梅,张雅茜,包福海,王淋,乌云塔娜,白玉娥,包文泉. 气候变化背景下我国长柄扁桃潜在适生区预测[J]. 林业科学, 2023, 59(12): 25-36.
[14]	司莉青,王明玉,陈锋,舒立福,赵凤君,李伟克. 雷电分布特征与雷击森林火预警[J]. 林业科学, 2023, 59(10): 1-8.
[15]	游巍斌,李颖,周艳,何东进. 武夷山国家公园马尾松林改为茶园后影响表层土壤碳含量的林缘效应[J]. 林业科学, 2023, 59(10): 41-49.