Spatiotemporal variation in vegetation coverage in Inner Mongolia and its response to human activities
Received date: 2023-10-23
Revised date: 2023-11-29
Online published: 2024-04-26
In the context of global climate change, the spatiotemporal characteristics of fractional vegetation coverage (FVC) serve as a crucial indicator for assessing ecological environment quality in various regions. However, the specific spatiotemporal variations, change trends, and underlying mechanisms of FVC response to human activities in Inner Mongolia remain undefined. Bridging this knowledge gap is essential for understanding ecological management outcomes and providing a scientific basis for local ecological policies and spatial planning. Using MOD13A1 NDVI data, land cover data, and nighttime light data spanning from 2000 to 2022, we calculated the annual maximum fractional vegetation coverage in Inner Mongolia and explored its spatiotemporal variations. Additionally, we illustrated the change trends in FVC. We conducted pixel-by-pixel correlation analysis to examine the response modes of FVC to human activities. Our findings reveal the following: (1) FVC distribution in Inner Mongolia demonstrated a decreasing trend from northeast to southwest, consistent with the overall precipitation changes in China. Notably, areas along the Yellow River, such as the Houtao Plain and the Qiantao Plain, exhibit relatively higher FVC due to abundant water resources and well-developed agriculture. Overall, FVC showed improvement with a growth rate of 0.0039·a-1, remaining relatively stable in most areas (64.02%) and significantly increasing in 31.64% of the region, all prefecture-level cities showing a positive average annual growth. (2) Changing trends in FVC were predominantly nonsignificant (65.62%), followed by a significant increase (17.36%), an extremely significant increase (13.43%), a significant decrease (3.27%), and an extremely significant decrease (0.32%). Regions experiencing significant and highly significant reductions displayed a strong spatial correlation with newly developed construction land. (3) Regarding human activities in Inner Mongolia, most regions (79.67%) showed no significant influence on FVC changes. In 12.80% of the regions, human activities positively impacted FVC, primarily in grassland and arable land areas surrounding urban zones. Conversely, 7.53% of the regions demonstrated a negative impact of human activities on FVC, chiefly in areas undergoing land cover transitions from arable land to construction land and newly added industrial and mining zones. While most regions showed no significant correlation between FVC variation and human activities, this does undermine the impact of ecological protection policies implemented in China like the “Ecological Protection Red Line” and “Arable Land Red Line.” The effectiveness of these measures lies in preventing land type conversion, such as grassland and arable land to other categories. This not only maintains the stability of FVC within protected areas but also regulates the intensity of human activities. However, the outcomes of these measures are not adequately reflected in nighttime light data. Therefore, while nighttime light data partially reflect the influence of human activity intensity on FVC, its limitations must be fully recognized in the comprehensive evaluation of ecological protection policies.
PEI Zhilin , CAO Xiaojuan , WANG Dong , LI Di , WANG Xin , BAI Aiyuan . Spatiotemporal variation in vegetation coverage in Inner Mongolia and its response to human activities[J]. Arid Zone Research, 2024 , 41(4) : 629 -638 . DOI: 10.13866/j.azr.2024.04.09
[1] | The intergovernmental panel on climate change (IPCC). climate change 2021—the physical science basis[J]. Chemistry International, 2021, 43(4): 22-23. |
[2] | Sellers Piers, Schimel David. Remote sensing of the land biosphere and biogeochemistry in the EOS era: Science priorities, methods and implementation-EOS land biosphere and biogeochemical cycles panels[J]. Global & Planetary Change, 1993, 7(4): 279-297. |
[3] | Parmesan C, Yohe G. A globally coherent fingerprint of climate change impacts across natural systems[J]. Nature, 2003, 421(6918): 37-42. |
[4] | 赵婷, 白红英, 邓晨晖, 等. 2000—2016年秦岭山地植被覆盖变化地形分异效应[J]. 生态学报, 2018, 39(12): 4499-4509. |
[Zhao Ting, Bai Hongying, Deng Chenhui, et al. Topographic differentiation effect on vegetation cover in the Qinling Mountains from 2000 to 2016[J]. Acta Ecologica Sinica, 2019, 39(12): 4499-4509.] | |
[5] | 裴志林, 杨勤科, 王春梅, 等. 黄河上游植被覆盖度空间分布特征及其影响因素[J]. 干旱区研究, 2019, 36(3): 546-555. |
[Pei Zhilin, Yang Qinke, Wang Chunmei, et al. Spatial distribution of vegetation coverage and its affecting factors in the upper reaches of the Yellow River[J]. Arid Zone Research, 2019, 36(3): 546-555.] | |
[6] | 孙根年, 王美红. 内蒙古植被覆盖与土地退化关系及空间结构研究[J]. 干旱区资源与环境, 2008, 22(2): 140-144. |
[Sun Gennian, Wang Meihong. Study on relation and distribution between vegetative coverage and land degradation in Inner Mongolia[J]. Journal of Arid Land Resource and Environment, 2008, 22(2): 140-144.] | |
[7] | John R, Chen J, Lu N, et al. Predicting plant diversity based on remote sensing products in the semi-arid region of Inner Mongolia[J]. Remote Sensing of Environment, 2008, 112(5): 2018-2032. |
[8] | 穆少杰, 李建龙, 陈奕兆, 等. 2001—2010年内蒙古植被覆盖度时空变化特征[J]. 地理学报, 2012, 67(9): 1255-1268. |
[Mu Shaojie, Li Jianlong, Chen Yizhao, et al. Spatial differences of variations of vegetation coverage in Inner Mongolia during 2001-2010[J]. Acta Geographica Sinica, 2012, 67(9): 1255-1268.] | |
[9] | 孙艳玲, 郭鹏, 延晓冬, 等. 内蒙古植被覆盖变化及其与气候, 人类活动的关系[J]. 自然资源学报, 2010, 25(3): 407-414. |
[Sun Yanling, Guo Peng, Yan Xiaodong, et al. Dynamics of vegetation cover and its relationship with climate change and human activities in Inner Mongolia[J]. Journal of Natural Resources, 2010, 25(3): 407-414.] | |
[10] | 田庆久, 闵祥军. 植被指数研究进展[J]. 地球科学进展, 1998, 13(4): 327-333. |
[Tian Qingjiu, Min Xiangjun. Advances in study on vegetation indices[J]. Advance in Earth Sciences, 1998, 13(4): 327-333.] | |
[11] | Tucker C J. Red and photographic infrared linear combinations for monitoring vegetation[J]. Remote Sensing and Environment, 1979, 8(2): 127-150. |
[12] | 付沙沙, 彭威, 邵爱梅, 等. 秦巴山区夏季NDVI变化特征及其对气候因子的响应[J]. 干旱区研究, 2023, 40(10): 1563-1574. |
[Fu Shasha, Peng Wei, Shao Aimei, et al. Variations in the NDVI characteristics during the summer and the climatic factor responses in the Qinling-Daba Mountains[J]. Arid Zone Research, 2023, 40(10): 1563-1574.] | |
[13] | 陈文裕, 夏丽华, 徐国良, 等. 2000-2020年珠江流域NDVI动态变化及影响因素研究[J]. 生态环境学报, 2022, 31(7): 1306-1316. |
[Chen Wenyu, Xia Lihua, Xu Guoliang, et al. Dynamic variation of NDVI and its influencing factors in the Pearl River basin from 2000 to 2020[J]. Ecology and Environmental Sciences, 2022, 31(7): 1306-1316.] | |
[14] | 何春阳, 李景刚, 陈晋, 等. 基于夜间灯光数据的环渤海地区城市化过程[J]. 地理学报, 2005, 60(3): 409-417. |
[He Chunyang, Li Jinggang, Chen Jin, et al. The urbanization model and process in Bohai Sea surrounding area in the 1990s by using DMSP/OLS data[J]. Acta Geographica Sinica, 2005, 60(3): 409-417.] | |
[15] | 董晨炜, 曹宇, 谭永忠. 基于夜间灯光数据的环杭州湾城市扩张及植被变化[J]. 应用生态学报, 2017, 28(1): 231-238. |
[Dong Chenwei, Cao Yu, Tan Yongzhong. Urban expansion and vegetation changes in Hangzhou Bay area using night-light data[J]. Chinese Journal of Applied Ecology, 2017, 28(1): 231-238.] | |
[16] | 赵忠旭, 张燕杰, 潘影, 等. 夜间灯光数据支持下西藏人类活动强度变化对生态系统调节服务的影响[J]. 地球信息科学学报, 2020, 22(7): 1544-1554. |
[Zhao Zhongxu, Zhang Yanjie, Pan Ying, et al. Changes in human activity intensity and influence on ecosystem regulating services: A study of Tibet based on night light data[J]. Journal of Geo-information Science, 2020, 22(7): 1544-1554.] | |
[17] | 卓莉, 陈晋, 史培军, 等. 基于夜间灯光数据的中国人口密度模拟[J]. 地理学报, 2005, 60(2): 266-276. |
[Zhuo Li, Chen Jin, Shi Peijun, et al. Modeling population density of China in 1998 based on DMSP/OLS nighttime light image[J]. Acta Geographica Sinica, 2005, 60(2): 266-276.] | |
[18] | 郑景云, 尹云鹤, 李炳元. 中国气候区划新方案[J]. 地理学报, 2010, 65(1): 3-12. |
[Zheng Jingyun, Yin Yunhe, Li Bingyuan. A new scheme for climate regionalization in China[J]. Acta Geographica Sinica, 2010, 65(1): 3-12.] | |
[19] | Chen Z, Yu B, Yang C, et al. An extended time series (2000—2018) of global NPP-VIIRS-like nighttime light data from a cross-sensor calibration[J]. Earth System Science Data, 2021, 13 (3): 889-906. |
[20] | Yang J, Huang X. The 30 m annual land cover dataset and its dynamics in China from 1990 to 2019[J]. Earth System Science Data, 2021, 13(8): 3907-3925. |
[21] | 谢秋霞, 孙林, 韦晶, 等. 基于遥感估算方法的干旱区植被覆盖度适应性评价[J]. 生态学杂志, 2016, 35(4): 1117-1124. |
[Xie Qiuxia, Sun Lin, Wei Jing, et al. Adaptive evaluation of vegetation coverage estimation in arid region based on remote sensing technology[J]. Chinese Journal of Ecology, 2016, 35(4): 1117-1124.] | |
[22] | 赵英时. 遥感应用分析原理与方法[M]. 北京: 科学出版社, 2003: 381-390. |
[Zhao Yingshi. Principles and Methods of Analysis of Remote Sensing Application[M]. Beijing: Science Press, 2013: 381-390.] | |
[23] | 宋怡, 马明国. 基于GIMMS AVHRR NDVI数据的中国寒旱区植被动态及其与气候因子的关系[J]. 遥感学报, 2008, 12(3): 499-505. |
[Song Yi, Ma Mingguo. Variation of AVHRR NDVI and its relationship with climate in chinese arid and cold regions[J]. Journal of Remote Sensing, 2008, 12(3): 499-505.] | |
[24] | 王涛, 白红英. 秦岭山地植被NDVI对气候变化与人类活动的响应[J]. 山地学报, 2017, 35(6): 778-789. |
[Wang Tao, Bai Hongying. Variation of vegetation NDVI in response to climate changes and human activities in Qinling Mountains[J]. Mountain Research, 2017, 35(6): 778-789.] | |
[25] | 高艳红, 许建伟, 张萌, 等. 中国400 mm等降水量变迁与干湿变化研究进展[J]. 地球科学进展, 2020, 35(11): 1101-1112. |
[Gao Yanhong, Xu Jianwei, Zhan Meng, et al. Advances in the study of the 400 mm isohyet migrations and wetness and dryness changes on the chinese mainland[J]. Advances in Earth Science, 2020, 35(11): 1101-1112.] | |
[26] | 张清雨, 吴绍洪, 赵东升, 等. 30年来内蒙古草地退化时空变化研究[J]. 农业科学与技术(英文), 2013, 14(4): 676-683. |
[Zhang Qingyu, Wu Shaohong, Zhao Dongsheng, et al. Temporal-spatial changes in Inner Mongolian grassland degradation during past three decades[J]. Agricultural Science & Technology, 2013, 14(4): 676-683.] | |
[27] | 郝璐, 高景民, 杨春燕. 内蒙古天然草地退化成因的多因素灰色关联分析[J]. 草业学报, 2006, 15(6): 26-31. |
[Hao Lu, Gao Jingmin, Yang Chunyan. Grey incidence analysis of factors affecting grassland degradation in Inner Mongolia[J]. Acta Prataculturae Sinica, 2016, 15(6): 26-31.] | |
[28] | 沈贝贝, 魏一博, 马磊超, 等. 内蒙古草原植被覆盖度时空格局变化及驱动因素分析[J]. 农业工程学报, 2022, 38(12): 118-126. |
[Shen Beibei, Wei Yibo, Ma Leichao, et al. Spatiotemporal changes and drivers of fractional vegetation cover in Inner Mongolia grassland of China[J]. Transactions of the Chinese Society of Agricultural Engineering, 2022, 38(12): 118-126.] | |
[29] | 仇保兴. 我国城市发展模式转型趋势——低碳生态城市[J]. 城市发展研究, 2009, 16(8): 1-6. |
[Qiu Baoxing. The transformation trends of urban development model in China-low carbon eco-city[J]. Urban Development Studies, 2009, 16(8): 1-6.] | |
[30] | 李鑫磊, 李瑞平, 王秀青, 等. 基于地理探测器的河套灌区林草植被覆盖度时空变化与驱动力分析[J]. 干旱区研究, 2023, 40(4): 623-635. |
[Li Xinlei, Li Ruiping, Wang Xiuqing, et al. Spatiotemporal change and analysis of factors driving forest-grass vegetation coverage in Hetao Irrigation District based on geographical detector[J]. Arid Zone Research, 2023, 40(4): 623-635.] |
/
〈 | 〉 |