A study of the spatiotemporal dynamic of land cover types and the driving forces of grassland area change in Gannan Prefecture and Northwest Sichuan based on CCI-LC data

doi:10.11686/cyxb2019263

Abstract

Abstract: Land cover change is key information when evaluating ecosystem health and such data is of great significance to planning sustainable development. Remote sensing is an effective way to achieve rapid and dynamic monitoring of land cover changes on a large scale. In this study, field measurement data and Landsat 8 OLI images were used to evaluate the classification accuracy of ESA Global land cover products (CCI-LC) in Gannan Prefecture and Northwest Sichuan, using the CCI-LC data to analyze the spatiotemporal dynamic of land cover types from 1992 to 2015, and the factors driving changes in grassland area changes was studied, considering both natural and artificial factors. The results indicated that: 1) The overall accuracy of CCI-LC products in Gannan Prefecture and Northwest Sichuan is 76.79%. Among the six land cover types (grassland, forest, bare land, water, permanent snow and ice, artificial surfaces), the user accuracy of grassland is the highest (94.88%). 2) From 1992 to 2015, the grassland area showed a generally decreasing trend, with a marked change during the period 1994-2001, with an overall decrease in area of 6760.53 km² and a rate of loss of -0.53%·year^-1. 3) From 1992 to 2000, the main changes in land cover types in the study area involved grassland, forest and artificial surfaces, and grassland area was mainly reduced in this period; from 2000 to 2010, the changes in land cover type in the study area were more diverse. The grassland cover was again reduced in most instances, but at a greatly reduced rate compared to 1992-2000; from 2010 to 2015, the transformation of land types was more complex, but a common pattern was transfer of grassland to forest and artificial surfaces. 4) Agricultural GDP and animal husbandry GDP are the main driving factors of grassland area change in Gannan Prefecture and Northwest Sichuan, and both of them are negatively correlated with grassland area. This study provides a macroscopic, rapid and low-cost remote sensing monitoring method to analyze the dynamic changes in land cover types over a long time period.

Key words: CCI-LC products, Gannan Prefecture and Northwest Sichuan, accuracy evaluation, change of land cover types, driving forces

LI Yuan-chun, GE Jing, HOU Meng-jing, GAO Hong-yuan, LIU Jie, BAO Xu-ying, YIN Jian-peng, GAO Jin-long, FENG Qi-sheng, LIANG Tian-gang. A study of the spatiotemporal dynamic of land cover types and the driving forces of grassland area change in Gannan Prefecture and Northwest Sichuan based on CCI-LC data[J]. Acta Prataculturae Sinica, 2020, 29(3): 1-15.

References

[1] Wang D T, Xu H J, Wang W X, et al. Responses of ecosystem service value to land use change in Gannan Tibetan Autonomous Prefecture. Journal of Anhui Agricultural Sciences, 2014, 42(28): 9973-9976.
王丹彤, 徐华君, 王文欣, 等. 甘南藏族自治州土地利用变化的生态系统服务价值响应. 安徽农业科学, 2014, 42(28): 9973-9976.
[2] Gou J J, Wang F, Yu E T, et al. Numerical simulation of the feedback of land-cover change on regional climate in the Loess Plateau. Arid Land Geography, 2017, 40(4): 850-859.
苟娇娇, 王飞, 于恩涛, 等. 黄土高原地区土地覆盖变化对气候的反馈作用数值模拟. 干旱区地理, 2017, 40(4): 850-859.
[3] Yang Q L, He Z W.Land use/land cover changes and their driving factors in Dunhuang City of Gansu Province during 2010-2013. Journal of Glaciology and Geocryology, 2016, 38(2): 558-566.
杨绮丽, 何政伟. 2000-2013年甘肃敦煌市土地利用变化及其驱动因素分析. 冰川冻土, 2016, 38(2): 558-566.
[4] Hansen M C, Loveland T R.A review of large area monitoring of land cover change using Landsat data. Remote Sensing of Environment, 2012, 122: 66-74.
[5] Yang S X, Feng Q S, Meng B P, et al. Temporal and spatial dynamics of alpine grassland biomass in the Three-River Headwater Region. Pratacultural Science, 2018, 35(5): 956-968.
杨淑霞, 冯琦胜, 孟宝平, 等. 三江源地区高寒草地地上生物量时空动态变化. 草业科学, 2018, 35(5): 956-968.
[6] Ma H X, Chen C C, Song Y Q, et al. Analysis of vegetation cover change and its driving factors over the past ten years in Qinghai Province. Research of Soil and Water Conservation, 2018, 25(6): 137-145.
马昊翔, 陈长成, 宋英强, 等. 青海省近10年草地植被覆盖动态变化及其驱动因素分析. 水土保持研究, 2018, 25(6): 137-145.
[7] Liu G L, Zhang L C, Zhang Q.Trajectory and driving forces of change in farmland in Nanjing during the period from 1985 to 2010. Journal of Ecology and Rural Environment, 2013, 29(6): 688-694.
刘桂林, 张落成, 张倩. 1985-2010年南京市耕地变化轨迹及驱动力分析. 生态与农村环境学报, 2013, 29(6): 688-694.
[8] Li C, Zeng H P.Research on land use change in Longchuan River Basin based on transfer matrix. Yangtze River, 2018, 49(17): 39-44.
李灿, 曾和平. 基于面积转移矩阵的龙川江流域土地利用变化研究. 人民长江, 2018, 49(17): 39-44.
[9] Dewan A M, Yamaguchi Y.Land use and land cover change in Greater Dhaka, Bangladesh: Using remote sensing to promote sustainable urbanization. Applied Geography, 2009, 29(3): 390-401.
[10] Li Y, Via Andrés, Yang W, et al. Effects of conservation policies on forest cover change in giant panda habitat regions, China. Land Use Policy, 2013, 33: 42-53.
[11] Falcucci A, Maiorano L, Boitani L.Changes in land-use/land-cover patterns in Italy and their implications for biodiversity conservation. Landscape Ecology, 2007, 22(4): 617-631.
[12] Zhang Y S, Chen J, Chen L J, et al. Characteristics of land cover change in Siberia based on GlobeLand30, 2000-2010. Progress in Geography, 2015, 34(10): 1324-1333.
张宇硕, 陈军, 陈利军, 等. 2000-2010年西伯利亚地表覆盖变化特征——基于GlobeLand30的分析. 地理科学进展, 2015, 34(10): 1324-1333.
[13] Bontemps S, Boettcher M, Brockmann C, et al. Multi-year global land cover mapping at 300 m and characterization for climate modelling: Achievements of the land cover component of the ESA climate change initiative. International Archives of the Photogrammetry, Remote Sensing & Spatial Information Sciences, 2015: 323-328.
[14] Yang Y, Xiao P, Feng X, et al. Accuracy assessment of seven global land cover datasets over China. ISPRS Journal of Photogrammetry and Remote Sensing, 2017, 125: 156-173.
[15] Liu Q H, Zhang Y L, Liu L S, et al. Accuracy evaluation of the seven land cover data in Qiangtang Plateau. Geographical Research, 2017, 36(11): 2061-2074.
刘琼欢, 张镱锂, 刘林山, 等. 七套土地覆被数据在羌塘高原的精度评价. 地理研究, 2017, 36(11): 2061-2074.
[16] Pan K W, Wu N, Pan K Z, et al. A discussion on the issues of the re-construction of ecological shelter zone on the upper reaches of Yangtze River. Acta Ecologica Sinica, 2003, 24(3): 617-629.
潘开文, 吴宁, 潘开忠, 等. 关于建设长江上游生态屏障的若干问题的讨论. 生态学报, 2003, 24(3): 617-629.
[17] Liu S.To determine the ecological compensation standard in the Yellow River water supply areas of Gannan based on contingent valuation method. Lanzhou: Northwest Normal University, 2011.
刘霜. 基于条件估值法的甘南黄河水源补给区生态补偿标准的确定. 兰州: 西北师范大学, 2011.
[18] Yang Q L, Ding P K, Xian W, et al. Evaluation on soil erosion susceptibility in northwest Sichuan region. Yangtze River, 2018, 49(10): 30-35.
杨青林, 丁鹏凯, 仙巍, 等. 川西北地区土壤侵蚀敏感性评价. 人民长江, 2018, 49(10): 30-35.
[19] Li W, Han P J, Zhao X Y.Sustainable development of tourism in a vulnerable ecological region: An emergy analysis of the Gannan Tibetan Autonomous Prefecture. Acta Ecologica Sinica, 2018, 38(16): 5894-5903.
李巍, 韩佩杰, 赵雪雁. 基于能值分析的生态脆弱区旅游业可持续发展研究——以甘南藏族自治州为例. 生态学报, 2018, 38(16): 5894-5903.
[20] Liu S, Xie Z H, Gao J Q, et al. Response of carbon and water cycles to climate change in the high-frigid ecotone: A case study of Gannan zone. Plateau Meteorology, 2018, 37(5): 1177-1187.
刘双, 谢正辉, 高骏强, 等. 高寒生态脆弱区冻土碳水循环对气候变化的响应——以甘南州为例. 高原气象, 2018, 37(5): 1177-1187.
[21] Ma J Z, Sun Q, Xiao Q, et al. Accuracy assessment and comparative analysis of GlobeLand30 dataset in Henan Province. Journal of Geo-Information Science, 2016, 18(11): 1563-1572.
马京振, 孙群, 肖强, 等. 河南省GlobeLand30数据精度评价及对比分析. 地球信息科学学报, 2016, 18(11): 1563-1572.
[22] Zhou H X.Study on the area of land use/land cover change and environmental thermal effect in the middle reaches of Hei River. Beijing: China University of Mining and Technology (Beijing), 2016.
周厚侠. 黑河中游区域土地利用/土地覆盖变化及环境热效应研究. 北京: 中国矿业大学(北京), 2016.
[23] Li X F, Liu L M, Qi X, et al. Land use change dynamics and driving forces of the vulnerable ecological region in northwestern Shanxi Province, China. Chinese Journal of Applied Ecology, 2014, 25(10): 2959-2967.
李秀芬, 刘利民, 齐鑫, 等. 晋西北生态脆弱区土地利用动态变化及驱动力. 应用生态学报, 2014, 25(10): 2959-2967.
[24] Fang F.The driving force of grassland changes and degradation intensification in inner Mongolia. Huhhot: Inner Mongolia University, 2018.
芳芳. 内蒙古牧草地面积变化及退化加剧的驱动力研究. 呼和浩特: 内蒙古大学, 2018.
[25] Hu B S, Cao G C, Ma Y F, et al. The dynamic monitoring and analysis on driving force of wetland based on GIS and RS-taking the Yeniugou River (Upstream of Heihe) as a case. Remote Sensing Information, 2011, (6): 98-102.
胡冰殊, 曹广超, 马燕飞, 等. 基于GIS和RS的湿地动态变化监测及驱动力分析-以黑河上游野牛沟河为例. 遥感信息, 2011, (6): 98-102.
[26] Li X J.Study on the impact of climate change and human activities on grassland evolution in Qilian Mountains. Xi’an: Shaanxi Normal University, 2018.
李肖娟. 气候变化和人类活动对祁连山草地演变影响程度的研究. 西安: 陕西师范大学, 2018.
[27] Gong L L, Liu D R, Yang N, et al. Comprehensive analysis on frost heave factors of subgrade soil in seasonally frozen ground region. Hydro-Science and Engineering, 2019, (1): 28-34.
巩丽丽, 刘德仁, 杨楠, 等. 季节性冻土区路基土体冻胀影响因素灰色关联分析. 水利水运工程学报, 2019, (1): 28-34.
[28] Tan T.Retain the memory and create the present-to commemorate the 40th anniversary of reform and opening up and 40 key words of China’s forestry industry. China Forestry Industry, 2018, (Z2): 14-57.
弹汰. 留住记忆,启创今朝-纪念改革开放40周年暨中国林业产业40个关键词. 中国林业产业, 2018, (Z2): 14-57.
[29] Zhang H.Performance evaluation and system innovation of the policy of converting farmland to forestry in Western China. Beijing: Minzu University of China, 2009.
张卉. 中国西部地区退耕还林政策绩效评价与制度创新. 北京: 中央民族大学, 2009.
[30] Rahmani A, Golian S, Brocca L.Multiyear monitoring of soil moisture over Iran through satellite and reanalysis soil moisture products. International Journal of Applied Earth Observation and Geoinformation, 2016, 48: 85-95.
[31] Peng J, Loew A, Zhang S, et al. Spatial downscaling of satellite soil moisture data using a vegetation temperature condition index. IEEE Transactions on Geoscience and Remote Sensing, 2015, 54(1): 1-9.
[32] Li W, Ciais P, Macbean N, et al. Major forest changes and land cover transitions based on plant functional types derived from the ESA CCI Land Cover product. International Journal of Applied Earth Observation and Geoinformation, 2016, 47: 30-39.
[33] Yang Y K.Accuracy assessment of large scale land cover datasets. Nanjing: Nanjing University, 2014.
杨永可. 大尺度土地覆盖数据集遥感评价研究. 南京: 南京大学, 2014.
[34] Zuo Y.Dynamic changes in land cover and landscape patterns of Anhui province based on global land cover products. Hefei: Anhui University, 2016.
左艳. 基于全球土地覆盖产品的安徽省土地覆盖和景观格局动态变化研究. 合肥: 安徽大学, 2016.
[35] Wu W B, Yang P, Zhang L, et al. Accuracy assessment of four global land cover datasets in China. Transactions of the Chinese Society of Agricultural Engineering, 2009, 25(12): 167-173.
吴文斌, 杨鹏, 张莉, 等. 四类全球土地覆盖数据在中国区域的精度评价. 农业工程学报, 2009, 25(12): 167-173.
[36] Lunetta R S, Knight J F, Ediriwickrema J, et al. Land-cover change detection using multi-temporal MODIS NDVI data. Remote Sensing of Environment, 2006, 105(2): 142-154.