Multi-scaled analysis of spatial-temporal evolution of vegetation ecological quality in the karst area of Guangxi
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摘要: 为更客观监测评估喀斯特地区植被生态质量状况及阐明植被生态质量不同时间尺度的时空异质性特征，基于多年植被净初级生产力（NPP）、湿润指数（MI），建立植被净初级生产力极大值（NPPm）边缘函数，并结合植被覆盖度，构建出广西喀斯特地区植被综合生态质量模型（MQI），以分析2000—2019年该地区植被生态质量多尺度时空演变特征。结果表明：（1）植被NPPm是随气候条件变化的动态值，不同植被类型生产潜力对气候条件的响应不同，其中农田植被响应最敏感，灌草次之、森林最弱；（2）广西喀斯特地区月份与季度植被生态质量指数呈抛物线形式，年度植被生态质量指数呈波动式增加，年际植被生态质量发展经历了缓慢增长、逐步增长、迅速增长、显著提升4个演变阶段，且植被生态质量由广西喀斯特地区东北部向西南部、北部向南部逐渐递增，总体良好；（3）2000—2019年，广西喀斯特地区植被生态改善指数为0.71/20 a，98.83%的区域植被生态质量在20 a期间呈上升趋势，大部区域植被生态改善良好，这主要得益于退耕还林、石漠化治理工程和良好气候条件；（4）此植被生态质量模型区域适宜性较高，能精细化、精准化反映广西喀斯特地区植被生态质量的时空演变特征。Abstract:
The karst area in Guangxi is characterized by its extensive and typical landform development, covering a total area of 8.334 million hectares, 18.9% of the total karst area in Southwest China and 35.1% of the total land area in Guangxi. This area is marked by poor and shallow soil, dominated by shrubs, shrub-grass, and grasslands as its vegetation. Therefore, it is subject to climate changes and meteorological disasters with a weak disaster-bearing capacity. The area is a typical ecologically vulnerable region in the southwest of China, and it is also the focus area for the Guangxi government to carry out ecological protection and restoration and rural revitalization. The scientific and rational assessment of vegetation ecological quality and its spatial-temporal evolution in the karst area is crucial for ecological restoration and governance, and the achievement of the "dual-carbon" goal. In order to monitor and assess the status of vegetation ecological quality in karst areas more objectively, and to clarify the spatial-temporal heterogeneity of vegetation ecological quality at different time scales, this study took the vegetation in the karst area of Guangxi as object. Based on the principle of "similar habitat" for vegetation ecological restoration, the "3S" technology was used to monitor and assess the vegetation ecological quality in the study area at different spatial and temporal scales. Firstly, the climate data was used to calculate the multi-year moisture index (MI) of the study area and delineate the climate gradient. Secondly, the maximum net primary productivity (NPPm) of the vegetation in the corresponding period was calculated. The correlation between MI and NPPm of the vegetation was analyzed, and the NPPm edge function of different vegetation types was constructed to determine the natural "baseline" of the potential productivity of vegetation within the climate gradient. Then a comprehensive vegetation quality model (MQI) for the karst area of Guangxi was built. Finally, the ecological quality index of vegetation was respectively calculated at monthly, quarterly, annual, and interannual scales to conduct a multi-scaled analyze of spatial-temporal evolution of vegetation ecological quality in the study area from 2000 to 2019. The results showed that: (1) There were obvious differences in the potential of vegetation ecological restoration under different climatic conditions in the karst area of Guangxi. The NPPm was a dynamic value that changes with climatic conditions, and different vegetation types responded differently to climatic conditions. Among these types, farmland vegetation was the most sensitive, followed by shrub-grass, and forest was the least affected. (2) There were significant temporal and spatial differences in the vegetation ecological quality at monthly, quarterly, annual, and interannual scales in the karst area of Guangxi. Temporally, the ecological quality indexes of vegetation at monthly and quarterly scales followed a parabolic pattern, and the annual index showed an increasing trend with fluctuation. The interannual evolution of vegetation ecological quality experienced four stages: slow growth, gradual growth, rapid growth, and significant growth. Spatially, vegetation ecological quality gradually increased from the northeastern to the southwestern part and from the northern to the southern part of the study area, with an overall high ecological quality. (3) There was a significant improvement in vegetation ecological quality in the karst area of Guangxi. From 2000 to 2019, the index of vegetation ecological improvement was 0.71/20a in the study area, with 98.83% of the regional vegetation ecological quality showing an upward trend over the 20-year period. Most of the improvement of regional vegetation ecology was favorable, primarily attributed to the national policies of returning farmland to forests, projects of rocky desertification control, and the favorable climate conditions in Guangxi. (4) The model for vegetation ecological quality of the study area exhibits high regional suitability and is able to finely and accurately reflect the spatial-temporal evolution characteristics of vegetation ecological quality in the study area. -
图 2 2000—2019年广西喀斯特地区年湿润指数平均值（a）与年植被NPP极大平均值图（b）
Figure 2. Distribution of MI (a) and NPPm from 2000 to 2019 (b)
图 3 2000—2019年广西喀斯特地区植被NPPm与湿润指数关系（a.森林；b.灌草；c.农田）
Figure 3. Relationship between NPPm and MI in the karst area of Guangxi from 2000 to 2019 （a. forest; b. thickets and grass; c. farmland）
图 4 2000—2019年广西喀斯特地区植被生态质量指数变化图（a.年度；b.季度；c.月份）
Figure 4. Change of vegetation ecological quality in the karst area of Guangxi from 2000 to 2019 (a. year; b. quarter; c. month)
图 5 2000—2019年广西喀斯特地区植被生态质量空间变异分布图（a.2000—2004年；b.2005—2009年；c.2010—2014年；d.2015—2019年）
Figure 5. Spatial variation distribution of vegetation ecological quality in the karst area of Guangxi (a. 2000–2004; b. 2005–2009; c. 2010–2014; d. 2015–2019)
图 6 2000—2019年不同时段广西喀斯特地区植被生态改善程度分布图
Figure 6. Distribution of improvement degree of vegetation ecologiy in the karst area of Guangxi in different periods from 2000 to 2019
表 1 广西喀斯特地区植被NPPm边缘函数
Table 1. Edge function of NPPm in the karst area of Guangxi
植被类型 NPPm(Y) MI（X） 模型 决定系数（R2） 森林 FOR_NPPm MI Y=347.1X3−1 844.3X2+3 052.4X−359 0.8653 灌草 GRS_NPPm MI Y=264.73X3−1 394.3X2+2 308.4X 0.9046 农田 FAR_NPPm MI Y=162.6X3−860.98X2+1 370.5X+462.97 0.8087 
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表 2 2000—2019年各时段广西喀斯特地区植被生态质量等级面积及比例统计
Table 2. Statistics of grade, area and proportion of vegetation ecological quality in the karst area of Guangxi in different periods from 2000 to 2019
生态质量
指数（MQi）等级 2000—2004年 2005—2009年 2010—2014年 2015—2019年 面积/km2 比例/% 面积/km2 比例/% 面积/km2 比例/% 面积/km2 比例/% ≤20 差 217.32 0.32 324.00 0.47 254.86 0.37 139.29 0.20 ＞20~40 偏差 2 353.64 3.43 4 535.71 6.61 1 709.94 2.49 493.29 0.72 ＞40~60 偏好 22 429.71 32.71 31 385.14 45.77 20 758.29 30.27 4 844.31 7.06 ＞60~70 较好 36 439.83 53.14 29 519.90 43.05 40 829.98 59.54 28 947.34 42.21 ~70 好 7 136.19 10.40 2 811.94 4.10 5 023.63 7.33 34 152.38 49.80
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表 3 2000—2019年广西不同时段植被生态改善面积及占比统计
Table 3. Statistics of improvement degree of vegetation ecology and proportion in the karst area of Guangxi in different periods from 2000 to 2019
生态改善
指数（MQc）等级 2000—2004年 2000—2009年 2000—2014年 2000—2019年 面积/km2 比例/% 面积/km2 比例/% 面积/km2 比例/% 面积/km2 比例/% ≤−1.0 明显变差 20 746.45 30.25 4 906.76 7.16 206.44 0.30 22.13 0.03 ＞−1.0~−0.5 变差 9 395.92 13.70 14 903.45 21.74 2 735.87 3.99 68.61 0.10 ＞−0.5~0.0 略变差 10 217.86 14.90 24 474.07 35.70 22 824.12 33.28 697.48 1.04 ＞0.0~0.5 略变好 9 452.25 13.78 17 591.07 25.66 33 262.74 48.51 14 192.59 21.12 ＞0.5~1.0 变好 7 416.11 10.81 5 564.83 8.12 8 535.98 12.45 41 638.30 61.96 ＞1.0 明显变好 11 348.10 16.56 1 111.00 1.62 1 007.09 1.47 10 578.78 15.75
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表 4 2000—2019年不同时段广西喀斯特地区植被生态质量对比
Table 4. Comparative analysis of the indexes of vegetation ecological quality in the karst area of Guangxi in different periods from 2000 to 2019
时段/年 植被生态质量 森林 灌草 农田 均值 2000—2004 Qi 57.83 59.05 51.00 55.96 MQi 62.19 63.87 57.68 61.25 2000—2004 Qc −0.05 −0.37 −0.18 −0.20 MQc −0.07 −0.43 −0.24 −0.25 2005—2009 Qi 55.67 56.59 48.92 53.73 MQi 60.86 61.08 55.13 59.02 2000—2009 Qc −0.05 −0.20 −0.14 −0.13 MQc −0.08 −0.24 −0.19 −0.17 2010—2014 Qi 58.33 59.06 51.57 56.49 MQi 65.93 64.79 60.22 63.65 2000—2014 Qc 0.20 0.05 0.12 0.12 MQc 0.25 0.07 0.15 0.15 2015—2019 Qi 66.77 65.42 58.22 63.47 MQi 71.76 70.76 67.75 70.09 2000—2019 Qc 0.26 0.09 0.14 0.16 MQc 0.81 0.68 0.73 0.74
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[1] Yuan Fei, Bauer M E. Comparison of impervious surface area and normalized difference vegetation index as indicators of surface urban heat island effects in Landsat imagery[J]. Remote Sensing of Environment, 2007, 106(3):375-386. doi: 10.1016/j.rse.2006.09.003 [2] Wright C K, De Beurs K M, Henebry G M. Combined analysis of land cover change and NDVI trends in the Northern Eurasian grain belt[J]. Frontiers of Earth Science, 2012, 6(2):177-187. doi: 10.1007/s11707-012-0327-x [3] 吕妍, 张黎, 闫慧敏, 任小丽, 王军邦, 牛忠恩, 顾峰雪, 何洪林. 中国西南喀斯特地区植被变化时空特征及其成因[J]. 生态学报, 2018, 38(24):8774-8786.LYU Yan, ZHANG Li, YAN Huimin, REN Xiaoli, WANG Junbang, NIU Zhongen, GU Fengxue, HE Honglin. Spatial and temporal patterns of changing vegetation and the influence of environmental factors in the karst region of Southwest China[J]. Acta Ecologica Sinica, 2018, 38(24):8774-8786. [4] 毛留喜, 李朝生, 侯英雨. 2006年上半年全国生态气象监测与评估研究[J]. 气象, 2006, 32(12):88-95, 141-142. doi: 10.3969/j.issn.1000-0526.2006.12.015MAO Liuxi, LI Chaosheng, HOU Yingyu. China meteorologically-driven ecological monitoring and assessment in the first half of 2006[J]. Meteorological Monthly, 2006, 32(12):88-95, 141-142. doi: 10.3969/j.issn.1000-0526.2006.12.015 [5] 毛留喜, 钱拴, 侯英雨. 2006年夏季川渝高温干旱的生态气象监测与评估[J]. 气象, 2007, 33(3):83-88, 132-133. doi: 10.3969/j.issn.1000-0526.2007.03.012MAO Liuxi, QIAN Shuan, HOU Yingyu. Study on the meteorologically-driven ecological monitoring and assessment of high temperature and drought of Sichuan-Chongqing area in summer 2006[J]. Meteorological Monthly, 2007, 33(3):83-88, 132-133. doi: 10.3969/j.issn.1000-0526.2007.03.012 [6] 钱拴, 毛留喜, 侯英雨. 北方草地生态气象综合监测预测技术及其应用[J]. 气象, 2008, 34(11):62-68, 130. doi: 10.7519/j.issn.1000-0526.2008.11.009QIAN Shuan, MAO Liuxi, HOU Yingyu. Technology and application of ecology meteorological synthetic monitoring and predicting for northern grassland in China[J]. Meteorological Monthly, 2008, 34(11):62-68, 130. doi: 10.7519/j.issn.1000-0526.2008.11.009 [7] 徐涵秋. 城市遥感生态指数的创建及其应用[J]. 生态学报, 2013, 33(24):7853-7862.XU Hanqiu. A remote sensing urban ecological index and its application[J]. Acta Ecologica Sinica, 2013, 33(24):7853-7862. [8] 钱拴, 延昊, 吴门新. 植被综合生态质量时空变化动态监测评价模型[J]. 生态学报, 2020, 40(18):1-11.QIAN Shuan, YAN Hao, WU Menxin. Dynamic monitoring and evaluation model for spatio-temporal change of comprehensive ecological quality of vegetation[J]. Acta Ecologica Sinica, 2020, 40(18):1-11. [9] 宋美杰, 罗艳云, 段利民. 基于改进遥感生态指数模型的锡林郭勒草原生态环境评价[J]. 干旱区研究, 2019, 36(6):1521-1527. doi: 10.13866/j.azr.2019.06.22SONG Meijie, LUO Yanyun, DUAN Limin. Evaluation of ecological environment in the Xilin Gol Steppe based on modified remote sensing ecological index model[J]. Arid Zone Research, 2019, 36(6):1521-1527. doi: 10.13866/j.azr.2019.06.22 [10] 邓晨晖, 白红英, 高山, 刘荣娟, 马新萍, 黄晓月, 孟清. 秦岭植被覆盖时空变化及其对气候变化与人类活动的双重响应[J]. 自然资源学报, 2018, 33(3):425-438. doi: 10.11849/zrzyxb.20170139DENG Chenhui, BAI Hongying, GAO Shan, LIU Rongjuan, MA Xinping, HUANG Xiaoyue, MENG Qing. Spatial-temporal variation of the vegetation coverage in Qinling Mountains and its dual response to climate change and human activities[J]. Journal of Natural Resources, 2018, 33(3):425-438. doi: 10.11849/zrzyxb.20170139 [11] 陈燕丽, 黄敏堂, 莫伟华. 基于MODIS NDVI的广西西南典型生态区植被变化对比监测[J]. 气象科学, 2015, 35(1):93-99. doi: 10.3969/2014jms.0017CHEN Yanli, HUANG Mintang, MO Weihua. Vegetation variation in typical ecological sections of southwest Guangxi based on MODIS NDVI data[J]. Journal of the Meteorological Sciences, 2015, 35(1):93-99. doi: 10.3969/2014jms.0017 [12] 童晓伟, 王克林, 岳跃民. 桂西北喀斯特区域植被变化趋势及其对气候和地形的响应[J]. 生态学报, 2014, 34(12):3425-3434.TONG Xiaowei, WANG Kelin, YUE Yuemin. Trends in vegetation and their responses to climate and topography in northwest Guangxi[J]. Acta Ecologica Sinica, 2014, 34(12):3425-3434. [13] 叶骏菲, 陈燕丽, 莫伟华, 莫建飞, 樊俏丽. 典型喀斯特区植被变化及其与气象因子的关系: 以广西百色市为例[J]. 沙漠与绿洲气象, 2019, 13(5):106-113.YE Junfei, CHEN Yanli, MO Weihua, MO Jianfei, FAN Qiaoli. Vegetation variation and its relationship with meteorological factors in typical karst area: A case study in Baise City of Guangxi[J]. Desert and Oasis Meteorology, 2019, 13(5):106-113. [14] 董丹, 倪健. 利用CASA模型模拟西南喀斯特植被净第一性生产力[J]. 生态学报, 2011, 31(7):1855-1866.DONG Dan, NI Jian. Modeling changes of net primary productivity of karst vegetation in Southwestern China using the CASA model[J]. Acta Ecologica Sinica, 2011, 31(7):1855-1866. [15] 莫建飞, 莫伟华, 陈燕丽. 基于净初级生产力的广西喀斯特区生物多样性维护功能评价[J]. 科学技术与工程, 2019, 19(29):371-377. doi: 10.3969/j.issn.1671-1815.2019.29.060MO Jianfei, MO Weihua, CHEN Yanli. Evaluation of biodiversity maintenance function in karst area of Guangxi based on NPP[J]. Science Technology and Engineering, 2019, 19(29):371-377. doi: 10.3969/j.issn.1671-1815.2019.29.060 [16] 马炳鑫, 靖娟利, 徐勇, 何宏昌, 刘兵. 2000—2019年滇黔桂岩溶区植被NPP时空变化及与气候变化的关系研究[J]. 生态环境学报, 2021, 30(12):2285-2293. doi: 10.16258/j.cnki.1674-5906.2021.12.002MA Bingxin, JING Juanli, XU Yong, HE Hongchang, LIU Bing. Spatial-temporal changes of NPP and its relationship with climate change in karst areas of Yunnan, Guizhou and Guangxi from 2000 to 2019[J]. Ecology and Environmental Sciences, 2021, 30(12):2285-2293. doi: 10.16258/j.cnki.1674-5906.2021.12.002 [17] 苏宗明, 李先琨. 广西岩溶植被类型及其分类系统[J]. 广西植物, 2003, 23(4):289-293. doi: 10.3969/j.issn.1000-3142.2003.04.001SU Zongming, LI Xiankun. The types of natural vegetation in karst region of Guangxi and its classified system[J]. Guihaia, 2003, 23(4):289-293. doi: 10.3969/j.issn.1000-3142.2003.04.001 [18] 林辉. 林业遥感[M]. 北京: 中国林业出版社, 2011.LIN Hui.Remote sensing of forestry[M].Beijing:China Forestry Press,2011. [19] Yan H, Wang S Q, Billesbach D, Oechel W, Bohrer G, Meyers T, Martin T A, Matamala R, Phillips RP, Rahman F . Improved global simulations of gross primary product based on a new definition of water stress factor and a separate treatment of C3 and C4 plants[J]. Ecological Modelling, 2015, 297:42-59. doi: 10.1016/j.ecolmodel.2014.11.002 [20] 郭铌. 植被指数及其研究进展[J]. 干旱气象, 2003, 21(4):71-75.GUO Ni. Vegetation index and its advances[J]. Arid Meteorology, 2003, 21(4):71-75. [21] 张学玲, 张莹, 牛德奎, 张文元, 李志, 李真真, 郭晓敏. 基于TM NDVI的武功山山地草甸植被覆盖度时空变化研究[J]. 生态学报, 2018, 38(7):2414-2424.ZHANG Xueling, ZHANG Ying, NIU Dekui, ZHANG Wenyuan, LI Zhi, LI Zhenzhen, GUO Xiaomin. Spatial-temporal dynamics of upland meadow coverage on Wugong mountain based on TM NDVI[J]. Acta Ecologica Sinica, 2018, 38(7):2414-2424. [22] Laughlin D C. Applying trait-based models to achieve functional targets for theory-driven ecological restoration[J]. Ecology Letters, 2014, 17(7):771-784. doi: 10.1111/ele.12288 [23] 王红岩. 基于NPP和植被降水利用效率土地退化遥感评价与监测技术研究[D]. 北京: 中国林业科学研究院, 2013.WANG Hongyan. Assessment and monitoring of land degradation using NPP and vegetation rain efficency[D]. Beijing: China Academy of Forestry, 2013. [24] Thornthwaite C W. An approach toward a rational classification of climate[J]. Geograhpical Review, 1948, 38(1):55-94. doi: 10.2307/210739 [25] 张月丛, 赵志强, 李双成. 基于SPOT NDVI的华北北部地表植被覆盖变化趋势[J]. 地理研究, 2008, 27(4): 745-754, 973.ZHANG Yuecong, ZHAO Zhiqiang, LI Shuangcheng. Indicating variation of surface vegetation cover using SPOT NDVI in the northern part of North China[J]. Geographical Research, 2008, 27 (4): 745-754, 973. [26] 全国农业气象标准化技术委员会. 陆地植被气象与生态质量监测评价等级: QX/T 494-2019[S]. 北京: 中国标准出版社, 2019.National Technical Committee of Agricultural Meteorology Standardization. Grade of monitoring and evaluating for terrestrial vegetation meteorology and ecological quality: QX/T 494-2019[S]. Beijing: Standard Press of China, 2019. [27] 王冰, 杨胜天. 基于NOAA/AVHRR的贵州喀斯特地区植被覆盖变化研究[J]. 中国岩溶, 2006, 25(2):157-162.WANG Bing, YANG Shengtian. Change in vegetation cover in Guizhou karst regions based on NOAA/AVHRR[J]. Carsologica Sinica, 2006, 25(2):157-162. [28] 熊康宁, 黎平, 周忠发. 喀斯特石漠化的遥感—GIS典型研究: 以贵州省为例[M]. 北京: 地质出版社, 2002.XIONG Kangning, LI Ping, ZHOU Zhongfa. Remote sensing—GIS model of rocky desertification in karst: A case study of Guizhou[M]. Beijing: Geology Press, 2002. [29] 王剑波, 吴柏海, 曾以禹. 林业与极端天气灾害:走基于生态系统的综合风险管理之路[J]. 林业经济, 2012, 11(11):24-29.WANG Jianbo, WU Baihai, ZENG Yiyu. Forestry and natural disaster: Toward the ecosystem-based approaches for integrate risk management[J]. Forestry Economics, 2012, 11(11):24-29. [30] 陈燕丽, 蒙良莉, 黄肖寒. 基于SPEI的广西喀斯特地区1971—2017 年干旱时空演变[J]. 干旱气象, 2019, 37(3):353-362.CHEN Yanli, MENG Liangli, HUANG Xiaohan. Temporal and spatial distributions of drought in Guangxi karst area during 1971–2017 based on standardized precipitation evapotranspiration index[J]. Journal of Arid Meteorology, 2019, 37(3):353-362. [31] 王祝雄, 闫宏伟, 莫沫. 做好灾后调查评估科学组织灾后重建:广西壮族自治区灾后林业恢复重建调研报告[J]. 林业经济, 2008, 4(4):21-24.WANG Zhuxiong, YAN Hongwei, MO Mo. Do a good job in post-disaster assessment survey scientific organizations reconstruction: Research report on forestry restoration after Guangxi Zhuang nature reserve disaster[J]. Forestry Economy, 2008, 4(4):21-24. [32] 马华, 王云琦, 王力. 近20 a广西石漠化区植被覆盖度与气候变化和农村经济发展的耦合关系[J]. 山地学报, 2014, 32(1):38-45.MA Hua, WANG Yunqi, WANG Li. Vegetation cover and climate change and rural economic development in relations during last 20 years in karst region of Guangxi[J]. Mountain Research, 2014, 32(1):38-45. [33] 黄文华, 刘家开. 2012年广西林业10件大事及最具影响力的10项工作[J]. 广西林业, 2013(4):7. doi: 10.3969/j.issn.1004-0390.2013.04.005HUANG Wenhua,LIU Jiakai. 10 major events and 10 most influential tasks of Guangxi forestry in 2012[J]. Forestry of Guangxi, 2013(4):7. doi: 10.3969/j.issn.1004-0390.2013.04.005 [34] 陈燕丽, 莫建飞, 莫伟华. 近30年广西喀斯特地区石漠化时空演变[J]. 广西科学, 2018, 25(5):625-631. doi: 10.13656/j.cnki.gxkx.20181031.001CHEN Yanli, MO Jianfei, MO Weihua. Temporal and spatial distributions of rocky desertification in Guangxi karst area in the past 30 years[J]. Guangxi Sciences, 2018, 25(5):625-631. doi: 10.13656/j.cnki.gxkx.20181031.001 [35] Tong X W, Brandt M, Yue Y M. Increased vegetation growth and carbon stock in China karst via ecological engineering[J]. Nature Sustainability, 2018, 11(1):44-50. doi: 10.3390/su11010044 [36] Chen Yanli, Mo Weihua, Huang Yonglin, MO Jianfei, Huang Xiaohan, Wen Xiumei. Changes in vegetation and assessment of meteorological conditions in ecologically fragile karst areas[J]. Journal of Meteorological Research, 2021, 35(1):172-183. [37] 冯国艳, 马明国. 西南地区2001—2014年植被变化时空格局[J]. 中国岩溶, 2018, 37(6):866-874.FENG Guoyan, MA Mingguo. Spatial-temporal pattern of vegetation changes in Southwest China during 2001–2014[J]. Carsologica Sinica, 2018, 37(6):866-874. [38] 盛叶子, 曾蒙秀, 林德根, 彭海军, 朱丽东, 李凤全, 余奕泓, 王能静. 2000—2014 年人类活动对贵州省植被净初级生产力的影响[J]. 中国岩溶, 2020, 39(1):62-70. doi: 10.11932/karst2020y01SHENG Yezi, ZENG Mengxiu, LIN Degen, PENG Haijun, ZHU Lidong, LI Fengquan, YU Yihong, WANG Nengjing. Impacts of human activities on net primary productivity of vegetation in Guizhou Province from 2000 to 2014[J]. Carsologica Sinica, 2020, 39(1):62-70. doi: 10.11932/karst2020y01 [39] 吴跃, 周忠发, 赵馨, 但雨生, 黄登红. 基于遥感计算云平台高原山区植被覆盖时空演变研究:以贵州省为例[J]. 中国岩溶, 2020, 39(2):196-205. doi: 10.11932/karst2020y16WU Yue, ZHOU Zhongfa, ZHAO Xin, DAN Yusheng, HUANG Denghong. Spatiotemporal variation of vegetation coverage in plateau mountainous areas based on remote sensing cloud computing platform: A case study of Guizhou Province[J]. Carsologica Sinica, 2020, 39(2):196-205. doi: 10.11932/karst2020y16 -
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