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

Abstract

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

CLC Number:

S718.5

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.

Figures/Tables 4

References 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]	Jiaojun Zhu,G. Geoff Wang,Huaiqing Zhang,Tian Gao. On the Research of Climate-Smart Forestry [J]. Scientia Silvae Sinicae, 2024, 60(7): 1-7.
[2]	Zhao Zhuqi, Hu Zhenhong, He Xian, Huang Zhiqun. Research Progresses on the Dynamics of Microbial Community Establishment in Woody Debris [J]. Scientia Silvae Sinicae, 2024, 60(2): 106-117.
[3]	Xinsheng Han,Guangquan Liu,Hao Xu,Liguo Dong,Yongzhong Guo,Yu An,Haixia Wan,Yueling Wang. Spatial Variation and Scale Effect of Surface Soil Organic Carbon Content on Typical Slopes in the Loess Region, Ningxia [J]. Scientia Silvae Sinicae, 2024, 60(1): 19-31.
[4]	Panpan Xue,Ning Miao,Ximing Yue,Qiong Tao,Yuandong Zhang,Qiuhong Feng,Kangshan Mao. Divergence Phenomenon of Radial Growth of Minjiang Fir in Response to Warming at Different Slope Aspects and Elevations on the Eastern Margin of the Tibetan Plateau [J]. Scientia Silvae Sinicae, 2023, 59(7): 65-77.
[5]	Xuelei Wei,Guogang Zhang,Ru Jia,Yunrui Ji,Hongying Xu,Zeyu Yang,Huajin Liu,Yulin Liu,Peiyu Yang. Variation of Waterbird Diversity and Its Affecting Factors in Xingkai Lake, Heilongjiang Province [J]. Scientia Silvae Sinicae, 2023, 59(6): 118-129.
[6]	Minghai Yan,Jinchi Wang,Qinglin Huang,Chongyang Zhuang,Qunrui Zheng,Mingxiu Zhuo,Xiaohui Guan. Distribution Law of Tree Height-to-Diameter Ratio in Each Stratum of Typical Natural Broad-Leaved Forest in Mid-Subtropical Zone [J]. Scientia Silvae Sinicae, 2023, 59(4): 149-156.
[7]	Ya Wang,Junhui Wang,Fude Wang,Yifu Liu,Cancan Tan,Yanchao Yuan,Wen Nie,Jianfeng Liu,Ermei Chang,Zirui Jia. Simulation of Suitable Distribution Areas of Picea koraiensis in China Since the Last Interglacial and Under Future Climate Scenarios [J]. Scientia Silvae Sinicae, 2023, 59(12): 1-12.
[8]	Shuning Zhang,Junxing Chen,Dun Ao,Mei Hong,Yaqian Zhang,Fuhai Bao,Lin Wang,Tana Wuyun,Yu’e Bai,Wenquan Bao. Prediction of Potential Suitable Areas of Amygdalus pedunculata in China under Climate Change [J]. Scientia Silvae Sinicae, 2023, 59(12): 25-36.
[9]	Liqing Si,Mingyu Wang,Feng Chen,Lifu Shu,Fengjun Zhao,Weike Li. Distribution Characteristics of Lightning and the Warning of Lightning-Caused Forest Fires [J]. Scientia Silvae Sinicae, 2023, 59(10): 1-8.
[10]	Weibin You,Ying Li,Yan Zhou,Dongjin He. Edge Effect of Pinus massoniana Forest Converted into Tea Plantation on Topsoil Carbon Content in Wuyishan National Park [J]. Scientia Silvae Sinicae, 2023, 59(10): 41-49.
[11]	Chunxiang Cheng,Min Yu,Zijun Mao,Lianni Xie,Yongcheng Zhang,Tao Sun,Zuomin Xu,Shuang Wu,Qianni Li,Jia Xu. Spatial-Temporal Evolution and Patterns of Abrupt Changs of NPP in Heilongjiang Province in the Process of Ecological Protection and Restoration in China [J]. Scientia Silvae Sinicae, 2022, 58(7): 23-31.
[12]	Lianbei Wu,Weimin Zhang,Hongwei Tong. Research and Application of Forest Land Grading and Benchmark Price: a Case Study of Longquan County, Zhejiang Province [J]. Scientia Silvae Sinicae, 2022, 58(5): 151-160.
[13]	Jiandong Qi,Xinxin Tan. Net Carbon Exchange of the Forest of Korean Pine and Broad Leaved Forest Trees in Changbai Mountain and Its Simulation Based on Temporal Convolutional Network [J]. Scientia Silvae Sinicae, 2022, 58(2): 1-12.
[14]	Wenmei Liao,Jing Lin,Guanglai Zhang,Ting Tong. Formal and Informal Institutions: Impact Differences in Forest Land Circulation——Based on the Empirical Analysis of 1 086 Farmers in 5 Provinces [J]. Scientia Silvae Sinicae, 2022, 58(12): 89-103.
[15]	Youjing Zhang,Yueyang Li,Han Zhao,Yuwan Cheng,Wei Wang,Zaimin Jiang,Jing Cai. Relationship between Hydraulic Efficiency and Gas Exchange and Growth of Six Poplar Clones [J]. Scientia Silvae Sinicae, 2022, 58(11): 118-126.

Spatio-Temporal Change of Forest Lands of Feicheng City and Its Driving Factorsin the Past 20 Years

RichHTML

PDF (PC)

Knowledge

Abstract

Cite this article

share this article

Figures/Tables 4

References 0

Related Articles 15

Recommended Articles

Metrics

Comments