Drivers of forestland change in the Qinba Mountain region of Shaanxi based on the Logistic regression model

DENG Yuanjie, HOU Mengyang, ZHANG Xiao, JIA Lei, LI Yuanyuan, YAO Shunbo, GONG Zhiwen, LIU Guangquan

JOURNAL OF NANJING FORESTRY UNIVERSITY ›› 2022, Vol. 46 ›› Issue (1) : 106-114.

PDF(3454 KB)
PDF(3454 KB)
JOURNAL OF NANJING FORESTRY UNIVERSITY ›› 2022, Vol. 46 ›› Issue (1) : 106-114. DOI: 10.12302/j.issn.1000-2006.202009045

Drivers of forestland change in the Qinba Mountain region of Shaanxi based on the Logistic regression model

Author information +
History +

Abstract

【Objective】 This study sought to clarify the spatio-temporal changes in forest land and its drivers in the Qinba Mountain region of Shaanxi Province, China, and provide basis for forest land protection and sustainable utilization of forest land resource. 【Method】 Using remote-sensing and monitoring data of land use, this study first analyzed the spatio-temporal characteristics of forest land changes and landscape patterns in the Qinba Mountain region from 2000 to 2018. Then, we selected three categories (i.e., natural, socio-economic and geographic) including 12 influencing factors to conduct driving force analysis of increase and decrease to forestland in the Qinba Mountain region via Logistic regression model. 【Result】 From 2000 to 2018, the forested land area primarily experienced a net increase, where the total increase was 39 951.72 hm2; this was mainly converted from cultivated land. Specifically, the conversion of cultivated land to forested land was 218 300 hm2, accounting for 94% of the total forested land area. Natural and geographical drivers were the most important forces driving forested land change in the Qinba Mountain region. The dominant drivers of increase in forest land included factors such as altitude, distance to town, slope-temperature, soil organic matter content, slope ≥25°, and distance to rural residential areas. The dominant drivers for decreased forested land included factors such as altitude, slope of 15°-25°, distance to town, and distance to road. 【Conclusion】 Effective implementation of ecological restoration program such as the Grain for Green program is an important reason for the increase of forested land in the Qinba Mountain region. The decrease in forested land was caused by the combination of natural and geographic drivers in the context of a rapidly developing society and economy.

Key words

forestland change / drivers / Logistic model / Qinba Mountain region of Shaanxi Province

Cite this article

Download Citations
DENG Yuanjie , HOU Mengyang , ZHANG Xiao , et al . Drivers of forestland change in the Qinba Mountain region of Shaanxi based on the Logistic regression model[J]. JOURNAL OF NANJING FORESTRY UNIVERSITY. 2022, 46(1): 106-114 https://doi.org/10.12302/j.issn.1000-2006.202009045

References

[1]
FAO. The state of the world’s forests 2018-forest pathways to sustainable development[M]. Rome. Lincence: CC By-NC-SA 3.0 IGO, 2018.
[2]
张清雨, 白红英, 孙华, 等. 近30年秦岭东西两县区森林景观类型的时空变化[J]. 环境科学学报, 2010, 30(5):1101-1106.
ZHANG Q Y, BAI H Y, SUN H, et al. Spatial-temporal changes of forest landscape types in the eastern and western counties of Qinling Mountain during the last 30 years[J]. Acta Sci Circumstantiae, 2010, 30(5):1101-1106. DOI: 10.13671/j.hjkxxb.2010.05.001.
[3]
庞国锦, 董晓峰, 宋翔, 等. “三北”防护林建设以来河西走廊林地变化的遥感监测[J]. 中国沙漠, 2012, 32(2):539-544.
PANG G J, DONG X F, SONG X, et al. Remote sensing monitoring of forest land change in Hexi Corridor since construction of the Three-north Shelterbelt Project[J]. J Desert Res, 2012, 32(2):539-544.
[4]
郭少壮, 白红英, 孟清, 等. 秦岭地区林地与草地景观格局变化及其驱动因素[J]. 生态学报, 2020, 40(1):130-140.
GUO S Z, BAI H Y, MENG Q, et al. Landscape pattern changes of woodland and grassland and its driving forces in Qinling Mountains[J]. Acta Ecol Sin, 2020, 40(1):130-140. DOI: 10.5846/stxb201811072418.
[5]
陈文静, 杨从从. 2001—2017年青海省NDVI时空变化特征及其对气候因子的响应[J]. 森林工程, 2020, 36(5):54-61.
CHEN W J, YANG C C. Spatiotemporal change characteristics of NDVI and its response to climate factors in Qinghai from 2001 to 2017[J]. Forest Engineering, 2020, 36(5):54-61.
[6]
张译, 郑新奇. 2000—2015年河北省林地时空变化特征及驱动力[J]. 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[J]. Res Soil and Water Conserv, 2018, 25(2):269-273. DOI: 10.13869/j.cnki.rswc.20171030.001.
[7]
谢花林. 典型农牧交错区土地利用变化驱动力分析[J]. 农业工程学报, 2008, 24(10):56-62.
XIE H L. Driving force analysis of land use changes in the typical farming-pastoral ecotone[J]. Trans Chin Soc Agric Eng, 2008, 24(10):56-62.
[8]
谢花林, 李波. 基于logistic回归模型的农牧交错区土地利用变化驱动力分析:以内蒙古翁牛特旗为例[J]. 地理研究, 2008, 27(2):294-304.
XIE H L, LI B. Driving forces analysis of land-use pattern changes based on logistic regression model in the farming-pastoral zone: a case study of Ongiud Banner,Inner Mongolia[J]. Geogr Res, 2008, 27(2):294-304. DOI: 10.3321/j.issn:1000-0585.2008.02.007.
[9]
SHAHBAZIAN Z, FARAMARZI M, ROSTAMI N, et al. Integrating logistic regression and cellular automata-Markov models with the experts’ perceptions for detecting and simulating land use changes and their driving forces[J]. Environ Monit and Assess, 2019, 191(7):422. DOI: 10.1007/s10661-019-7555-4.
[10]
李云龙, 韩美, 孔祥伦, 等. 近30年来黄河三角洲耕地轨迹转化及驱动力研究[J]. 中国人口·资源与环境, 2019, 29(9):136-143.
LI Y L, HAN M, KONG X L, et al. Study on transformation trajectory and driving factors of cultivated land in the Yellow River Delta in recent 30 years[J]. China Popul, Resour and Environ, 2019, 29(9):136-143. DOI: 10.12062/cpre.20190601.
[11]
袁磊, 杨昆. 土地利用变化驱动力多尺度因素的定量影响分析[J]. 中国土地科学, 2016, 30(12):63-70.
YUAN L, YANG K. An analysis of quantitative impacts of multi-scale factors on driving forces in land use change[J]. China Land Sci, 2016, 30(12):63-70. DOI: 10.11994/zgtdkx.20161219.132637.
[12]
杨丽, 傅春. 赣南生态屏障区林地变化的空间驱动力分析[J]. 地理与地理信息科学, 2018, 34(6):58-62.
YANG L, FU C. Spatial driving force analysis of forest land change in Gannan ecological security zone[J]. Geogr Geo Inf Sci, 2018, 34(6):58-62. DOI: 10.3969/j.issn.1672-0504.2018.06.009.
[13]
XIE X, XIE H L, FAN Y H. Spatiotemporal patterns and drivers of forest change from 1985-2000 in the Beijing-Tianjin-Hebei region of China[J]. J of Resour and Ecol, 2016, 7(4):301-308. DOI: 10.5814/j.issn.1674-764x.2016.04.009.
[14]
LIU J Y, LIU M L, ZHUANG D F, et al. Study on spatial pattern of land-use change in China during 1995-2000[J]. Sci China Ser D: Earth Sci, 2003, 46(4):373-384.DOI: 10.1360/03yd9033.
[15]
刘纪远, 宁佳, 匡文慧, 等. 2010—2015年中国土地利用变化的时空格局与新特征[J]. 地理学报, 2018, 73(5):789-802.
Abstract
土地利用/覆被变化是人类活动对地球表层及全球变化影响研究的重要内容。本文基于Landsat 8 OLI、GF-2等遥感图像和人机交互解译方法,获取的土地利用数据实现了中国2010-2015年土地利用变化遥感动态监测。应用土地利用动态度、年变化率等指标,从全国和分区角度揭示了2010-2015年中国土地利用变化的时空特征。结果表明:2010-2015年中国建设用地面积共增加24.6×10<sup>3</sup> km<sup>2</sup>,耕地面积共减少4.9×10<sup>3</sup> km<sup>2</sup>,林草用地面积共减少16.4×10<sup>3</sup> km<sup>2</sup>。2010-2015年与2000-2010年相比,中国土地利用变化的区域空间格局基本一致,但分区变化呈现新的特征。东部建设用地持续扩张和耕地面积减少,变化速率有所下降;中部建设用地扩张和耕地面积减少速度增加;西部建设用地扩张明显加速,耕地面积增速进一步加快,林草面积减少速率增加;东北地区建设用地扩展持续缓慢,耕地面积稳中有升,水旱田转换突出,林草面积略有下降。从“十二五”期间国家实施的主体功能区布局来看,东部地区的土地利用变化特征与优化和重点开发区的国土空间格局管控要求基本吻合;中部和西部地区则面临对重点生态功能区和农产品主产区相关土地利用类型实现有效保护的严峻挑战,必须进一步加大对国土空间开发格局的有效管控。
LIU J Y, NING J, KUANG W H, et al. Spatio-temporal patterns and characteristics of land-use change in China during 2010-2015[J]. Acta Geogr Sin, 2018, 73(5):789-802.DOI: 10.11821/dlxb201805001.
[16]
刘纪远. 中国资源环境遥感宏观调查与动态研究[M]. 北京: 中国科学技术出版社, 1996.
LIU J Y. Macro-scale survey and dynamic study of natural resources and environment of China by remote sensing[M]. Beijing: China Science and Technology Press, 1996.
[17]
邓元杰, 姚顺波, 侯孟阳, 等. 长江流域中上游植被NDVI时空变化及其地形分异效应[J]. 长江流域资源与环境, 2020, 29(1):66-78.
DENG Y J, YAO S B, HOU M Y, et al. Temporal and spatial variation of vegetation NDVI and its topographic differentiation effect in the middle and upper reaches of the Yangtze River basin[J]. Resour and Environ in the Yangtze Basin, 2020, 29(1):66-78. DOI: 10.11870/cjlyzyyhj202001007.
[18]
梅纳德斯科特. 应用Logistic回归分析[M]. 上海: 上海人民出版社, 2012.
SCOTT M. Applied Logistic regression analysis[M]. Shanghai: Shanghai People’s Press, 2012.
[19]
HANLEY J A, MCNEIL B J. The meaning and use of the area under a receiver operating characteristic (ROC) curve[J]. Radiology, 1982, 143(1):29-36.DOI: 10.1148/radiology.143.1.7063747.
[20]
张碧桃, 周忠学. 秦巴山区土地利用变化对农业生态系统服务的影响——以汉中盆地为例[J]. 陕西师范大学学报(自然科学版), 2020, 48(1):21-31.
ZHANG B T, ZHOU Z X. Impact of land use change on agro-ecosystem services in Qinba Mountain area—a case study of Hanzhong Basin[J]. J Shaanxi Norm Univ (Nat Sci Ed), 2020, 48(1):21-31. DOI: 10.15983/j.cnki.jsnu.2020.04.003.
[21]
王宏, 阎建忠, 李惠莲. 中国14个连片特困地区的森林转型及其解释[J]. 地理学报, 2018, 73(7):1253-1267.
Abstract
利用MODIS土地覆盖数据,分析了2002-2013年中国14个连片特困地区森林转型的特点,探明了连片特困地区林地变化的趋势及其空间异质性。在此基础上,选择空间变量,建立线性回归模型探究林地面积变化的影响因素,得出连片特困地区森林转型所遵循的路径。结果表明,2002-2013年间,中国14个连片特困地区林地面积净增加106554.75 km<sup>2</sup>,增长率为11.93%,森林进入转型后期,即森林面积净增加阶段;秦巴山区、武陵山区、西藏地区东南部、四省藏区东部、燕山—太行山区东部是林地增长的热点区域,而林地增长冷点区域则主要分布在800 mm等降水量线以北的广大区域、大别山区和滇桂黔石漠化区东部;非农人口的增加以及林业工程的实施都对林地面积的增加有显著的促进作用,中国14个连片特困地区的森林转型主要遵循着经济发展路径和国家森林政策路径。在连片特困地区,应加快小城镇建设的步伐,同时依托其丰富的自然资源,因地制宜地发展乡村生态旅游业;国家森林政策方面,应将连片特困地区作为生态建设重点区域,切实保护中国的森林资源。
WANG H, YAN J Z, LI H L. Forest transition and its explanation in contiguous destitute areas of China[J]. Acta Geogr Sin, 2018, 73(7):1253-1267. DOI: 10.11821/dlxb201807006.
[22]
鲁亚楠, 姚顺波. 基于经济和政策双重作用的南方集体林区土地利用时空变化[J]. 南京林业大学学报(自然科学版), 2018, 42(5):163-171.
LU Y N, YAO S B. Spatial-temporal dynamic characteristics for land use of the southern collective forest region based on the function of economy and policy[J]. J Nanjing For Univ (Nat Sci Ed), 2018, 42(5):163-171. DOI: 10.3969/j.issn.1000-2006.201710023.
[23]
张静, 任志远. 秦巴山区土地利用时空格局及地形梯度效应[J]. 农业工程学报, 2016, 32(14):250-257.
ZHANG J, REN Z Y. Spatiotemporal pattern and terrain gradient effect of land use change in Qinling-Bashan Mountains[J]. Trans Chin Soc Agric Eng, 2016, 32(14):250-257. DOI: 10.11975 / j.issn.1002-6819.2016.14.033.
[24]
XIE H L, HE Y F, ZHANG N, et al. Spatiotemporal changes and fragmentation of forest land in Jiangxi Province, China[J]. J For Econ, 2017, 29:4-13. DOI: 10.1016/j.jfe.2017.08.004.
[25]
BRYAN B A, GAO L, YE Y Q, et al. China’s response to a national land-system sustainability emergency[J]. Nature, 2018, 559(7713):193-204. DOI: 10.1038/s41586-018-0280-2.
[26]
杨艳蓉, 张增信, 张金池, 等. 长江中下游地区植被覆盖与区域气候变化的关系研究[J]. 南京林业大学学报(自然科学版), 2013, 37(6):89-95.
YANG Y R, ZHANG Z X, ZHANG J C, et al. A study on the relationship between vegetation coverage and regional climate change in middle and lower reaches of Yangtze River[J]. J Nanjing For Univ (Nat Sci Ed), 2013, 37(6):89-95.DOI: 10.3969/j.issn.1000-2006.2013.06.018.
[27]
张善红, 白红英, 高翔, 等. 太白山植被指数时空变化及其对区域温度的响应[J]. 自然资源学报, 2011, 26(8):1377-1386.
ZHANG S H, BAI H Y, GAO X, et al. Spatial-temporal changes of vegetation index and its responses to regional temperature in Taibai Mountain[J]. J Nat Resour, 2011, 26(8):1377-1386. DOI: 10.11849/zrzyxb.2011.08.012.
[28]
CHEN L, HUANG J G, ALAM S A, et al. Drought causes reduced growth of trembling aspen in western Canada[J]. Glob Chang Biol, 2017, 23(7):2887-2902. DOI: 10.1111/gcb.13595.
[29]
王钰莹, 孙娇, 刘政鸿, 等. 陕南秦巴山区厚朴群落土壤肥力评价[J]. 生态学报, 2016, 36(16):5133-5141.
WANG Y Y, SUN J, LIU Z H, et al. Soil fertility quality assessment of Magnolia officinalis communities in Qinba Mountains[J]. Acta Ecol Sin, 2016, 36(16):5133-5141. DOI: 10.5846/stxb201502020266.
[30]
李国平, 杨雷, 刘生胜. 国家重点生态功能区县域生态环境质量空间溢出效应研究[J]. 中国地质大学学报(社会科学版), 2016, 16(1):10-19.
LI G P, YANG L, LIU S S. Study on spatial spillover of ecological environment quality in county area of state key ecological function area[J]. J China Univ of Geosci (Soc Sci Ed), 2016, 16(1):10-19. DOI: 10.16493/j.cnki.42-1627/c.2016.01.002.
[31]
喻永红. 退耕还林可持续性研究——以重庆万州为例[D]. 杭州:浙江大学, 2014.
YU Y H. Research on the viability of the grain for green project: a case study of Wanzhou District in Chongqing[D]. Hangzhou: Zhejiang University, 2014.

RIGHTS & PERMISSIONS

Copyright reserved © 2022
PDF(3454 KB)

Accesses

Citation

Detail

Sections
Recommended
The full text is translated into English by AI, aiming to facilitate reading and comprehension. The core content is subject to the explanation in Chinese.

/