青海高寒草甸退化演替中的植被指数

doi:10.7522/j.issn.1000-694X.2021.00007

摘要/Abstract

摘要：

随着气候变化和人为活动干扰，高寒草甸退化已成为青藏高原严重的生态环境问题，精准识别其退化程度并制定相应恢复策略，对实现高寒草甸可持续发展具有重要意义。目前，低空间分辨率MODIS数据为草地遥感监测的主要数据源，但难以满足景观破碎度或异质性较强地区的应用。本研究基于野外调查资料，利用多源遥感数据（MODIS、Landsat、Sentinel-2）研究不同空间分辨率归一化植被指数（NDVI）对高寒草甸退化演替的响应，为准确评估青藏高原高寒草甸退化程度提供依据。结果表明：（1）随着高寒草甸退化，植被群落优势种演化趋势为禾草—矮嵩草—小嵩草—杂草群落；植被高度和生物量先快速下降，然后缓慢下降或趋于稳定，植被覆盖度和NDVI的变化呈相反特征。（2）随着湿地草甸旱化，植被群落优势种从藏嵩草演变为矮嵩草或小嵩草，湿地旱化初期植被高度、生物量和覆盖度平均值略低于原生湿地，NDVI略大于原生湿地，差异不显著。（3）植被高度、覆盖度和生物量与Sentinel-2或Landsat的NDVI相关性均优于MODIS，说明Sentinel-2和Landsat的NDVI对高寒草甸退化演替过程更加敏感，采用该数据能更准确评估高寒草甸退化程度。

关键词: 高寒草甸, 湿地草甸, 归一化植被指数, 退化演替

Abstract:

With the climate change and disturbance of human activities， the degradation of Qinghai-Tibet plateau meadow has become a serious ecological and environmental problem. It is of great significance to accurately identify the degradation degree of meadow and formulate the corresponding strategies for restoration of degraded meadow to realize the sustainable development of alpine meadow. Currently， low spatial resolution MODIS data is the main data source for remote sensing monitoring of grassland degradation， but it is difficult to meet the application in areas with strong landscape fragmentation or heterogeneity. Based on field survey data， this study uses multi-source remote sensing data （MODIS， Landsat， and Sentinel-2） to study the response of the normalized vegetation index （NDVI） at different scales to the degraded succession of alpine meadows， and provides a basis for accurately assessing the degree of meadow degradation. The results showed that：（1） With the degradation of alpine meadows， the evolution trend of dominant species in the vegetation community was from gramineae grass， kobresia humilis， kobresia pygmaea to forbs community； vegetation height and biomass first declined rapidly， then slowly declined or tended to stable， while the vegetation coverage and NDVI changes have opposite characteristics. （2） With the drought of wetland meadows， the dominant species of vegetation community changes from kobresia tibetica to kobresia humilis or kobresia pygmaea. The average vegetation height， biomass and coverage of wetland are slightly lower than that of the original wetland at the initial stage of drought. NDVI is slightly larger than the original wetland， and the difference is not significant. （3） The correlation between meadow height， coverage and biomass and NDVI of Sentinel-2 or Landsat was better than MODIS， indicating that NDVI of Sentinel-2 and Landsat was more sensitive to degradation succession of alpine meadow， and the data could be used to evaluate the degradation degree of alpine meadow more accurately.

Key words: alpine meadow, wetland meadow, normalized vegetation index （NDVI）, degenerate succession

中图分类号:

Q948.5

邢学刚, 颜长珍, 逯军峰, 翟晓慧, 贾浩巍, 谢家丽. 青海高寒草甸退化演替中的植被指数[J]. 中国沙漠, 2021, 41(3): 203-213.

Xuegang Xing, Changzhen Yan, Junfeng Lu, Xiaohui Zhai, Haowei Jia, Jiali Xie. Response of vegetation index to degraded succession of alpine meadow in Qinghai， China[J]. Journal of Desert Research, 2021, 41(3): 203-213.

图/表 7

图1 研究区域和采样点分布

Fig.1 Distribution map of study area and sampling points

图2 采样点生物量、覆盖度和高度野外调查和室内处理

Fig.2 Field investigation and indoor treatment for biomass, coverage and height of sampling sites

表1 不同空间分辨率NDVI基本信息

Table 1 The information of NDVI with different spatial resolutions

数据类型	空间分辨率/m	所用影像
Sentinel-2_NDVI	10	Sentinel-2 MSI: MultiSpectral Instrument, Level-2A
Landsat_NDVI	30	Landsat 8 Surface Reflectance
MODIS_NDVI₂₅₀	250	MOD13Q1
MODIS_NDVI₅₀₀	500	MOD13A1
MODIS_NDVI₁₀₀₀	1000	MOD13A2

图3 不同退化阶段高寒草甸和湿地草甸的野外照片与NDVI可视化。1—7分别为野外拍摄照片、Landsat假彩色影像、Sentinel2_NDVI、Landsat_NDVI、MODIS_NDVI250、MODIS_NDVI500、MODIS_NDVI1000；白色点代表不同退化阶段高寒草甸和湿地草甸的采样点

Fig.3 Field photos and NDVI visualization of alpine meadows and wetland meadows at different degradation stages. Pictures from 1 to 7 are field photos, Landsat false color images, Sentinel-2_NDVI, Landsat_NDVI, MODIS_NDVI250, MODIS_NDVI500, and MODIS_NDVI1000, respectively; white dots represent the sampling point of alpine meadows and wetland meadow at different degradation stages

图4 不同退化阶段高寒草甸和湿地草甸的生物量、覆盖度和高度统计

Fig.4 Statistics of biomass, coverage and height of alpine meadow and wetland meadow in different degradation stages

图5 不同退化阶段高寒草甸和湿地草甸的植被NDVI统计

Fig.5 Vegetation NDVI statistical map of alpine meadow at different degradation stages

图6 高寒草甸高度、覆盖度和生物量与NDVI相关关系（A—E: Sentinel2_NDVI、Landsat_NDVI、MODIS_NDVI250、MODIS_NDVI500、MODIS_NDVI1000）

Fig.6 Correlation between height, coverage, biomass and NDVI of alpine meadow (A-E: Sentinel2_NDVI, Landsat_NDVI, MODIS_NDVI250, MODIS_NDVI500, MODIS_NDVI1000)

参考文献 37

1	Lin L，Li Y K，Xu X L，et al. Predicting parameters of degradation succession processes of Tibetan Kobresia grasslands ［J］.Solid Earth，2015，6（4）：1237-1246.
2	曹广民，林丽，张法伟，等.青藏高原高寒矮嵩草草甸稳定性的维持、丧失与恢复［J］.草业科学，2010，27（8）：34-38.
3	Harris R B.Rangeland degradation on the Qinghai-Tibetan plateau：a review of the evidence of its magnitude and causes［J］.Journal of Arid Environments，2010，74（1）：1-12.
4	Liu S，Zamanian K，Schleuss P M，et al.Degradation of Tibetan grasslands：consequences for carbon and nutrient cycles［J］.Agriculture Ecosystems & Environment，2018，252：93-104.
5	蒋志刚.探索青藏高原生物多样性分布格局与保育途径［J］.生物多样性，2018，26 （2）：107-110.
6	Qin Y，Yi S，Ren S，et al.Responses of typical grasslands in a semi-arid basin on the Qinghai-Tibetan Plateau to climate change and disturbances ［J］.Environmental Earth Sciences，2013，71：1421-1431.
7	Frauenfeld O W.Climate change and variability using European Centre for Medium-Range Weather Forecasts Reanalysis （ERA-40） temperatures on the Tibetan Plateau［J］.Journal of Geophysical Research Atmospheres，2005，110 （D2）：1-9.
8	李生辰，徐亮，郭英香，等.近34a青藏高原年降水变化及其分区［J］.中国沙漠，2007，27（2）：307-314.
9	Liang T G，Yang S X，Feng Q S，et al.Multi-factor modeling of above-ground biomass in alpine grassland：a case study in the Three-River Headwaters Region，China ［J］.Remote sensing of Environment，2016，186：164-172.
10	Chang X F，Zhu X X，Wang S P，et al.Impacts of management practices on soil organic carbon in degraded alpine meadows on the Tibetan Plateau ［J］.Biogeosciences，2014，11：3495-3503.
11	Li J，Yang Y，Li B，et al.Effects of Nitrogen and Phosphorus Fertilization on Soil Carbon Fractions in alpine meadows on the Qinghai-Tibetan Plateau ［J］.PLoS One，2014，9（7）：e103266.
12	Yan P，Dong G G，Zhang X B.Preliminary results of the study on wind erosion in the Qinghai-Tibetan Plateau using ¹³⁷Cs technique［J］.Chinese Ence Bulletin，2000，45（11）：1019-1025.
13	Wu R X，Qi C，Zhang J Q，et al.Impacts of burrows and mounds formed by plateau rodents on plant species diversity on the Qinghai-Tibetan Plateau［J］.Rangeland Journal，2015，37：117-123.
14	Yan L，Zhou G，Zhang F.Effects of different grazing intensities on grassland production in China：a meta-analysis［J］.PloS One，2013，8：1-9.
15	Lehnert L W，Meyer H，Meyer N，et al.A hyperspectral indicator system for rangeland degradation on the Tibetan Plateau：a case study towards spaceborne monitoring［J］.Ecological Indicators，2014，39：54-64.
16	Dong S K，Shang Z H，Gao J X，et al.Enhancing sustainability of grassland ecosystems through ecological restoration and grazing management in an era of climate change on Qinghai-Tibetan Plateau［J］.Agriculture，Ecosystems & Environment，2020，287：1-16.
17	Wang P，Deng X，Jiang S.Diffused impact of grassland degradation over space：a case study in Qinghai province［J］.Physics and Chemistry of the Earth，2017：166-171.
18	Zhang B P，Chen X D，Li B L，et al.Biodiversity and conservation in the Tibetan Plateau［J］.Journal of Geographical Sciences，2002，12（2）：135-143.
19	马玉寿，郎百宁，李青云，等.江河源区高寒草甸退化草地恢复与重建技术研究［J］.草业科学，2002（9）：1-5.
20	丁明军，张镱锂，刘林山，等.1982-2009年青藏高原草地覆盖度时空变化特征［J］.自然资源学报，2010，25（12）：2114-2122.
21	Wang Z，Zhang Y，Yang Y，et al.Quantitative assess the driving forces on the grassland degradation in the Qinghai-Tibet Plateau，in China［J］.Ecological Informatics，2016，33：32-44.
22	Zhu X，Cai F，Tian J，et al.Spatiotemporal fusion of multisource remote sensing data：literature survey，taxonomy，principles，applications，and future directions［J］.Remote Sensing，2018，10（4）：527.
23	李辉霞，刘淑珍.基于ETM+影像的草地退化评价模型研究：以西藏自治区那曲县为例［J］.中国沙漠，2007，27（3）：412-418.
24	王塞，王思诗，樊风雷.基于时间序列分割算法的雅鲁藏布江流域NDVI（1985-2018）变化模式研究［J］.生态学报，2020（19）：1-9.
25	You N，Dong J.Examining earliest identifiable timing of crops using all available Sentinel 1/2 imagery and Google Earth Engine［J］.ISPRS Journal of Photogrammetry and Remote Sensing，2020，161：109-123.
26	Liu L，Xiao X M，Qin Y W，et al.Mapping cropping intensity in China using time series Landsat and Sentinel-2 images and Google Earth Engine［J］.Remote Sensing of Environment，2020，239：1-10.
27	Singha M，Dong J，Sarmah S，et al.Identifying floods and flood-affected paddy rice fields in Bangladesh based on Sentinel-1 imagery and Google Earth Engine ［J］.ISPRS Journal of Photogrammetry and Remote Sensing，2020，166：278-293.
28	Zhu X，Jin C，Feng G，et al.An enhanced spatial and temporal adaptive reflectance fusion model for complex heterogeneous regions［J］.Remote Sensing of Environment，2010，114（11）：2610-2623.
29	Zhu X，Helmer E H，Gao F，et al.A flexible spatiotemporal method for fusing satellite images with different resolutions［J］.Remote Sensing of Environment，2016，172：165-177.
30	王海军，张勃，靳晓华，等.基于GIS的祁连山区气温和降水的时空变化分析［J］.中国沙漠，2009，29（6）：1196-1202.
31	高黎明，张乐乐.青海湖流域植被盖度时空变化研究［J］.地球信息科学学报，2019，21（9）：1318-1329.
32	李成阳，薛娴，赖炽敏，等.青藏高原退化高寒草甸生长季承载力［J］.中国沙漠，2018，38（6）：1330-1338.
33	后源，郭正刚，龙瑞军.黄河首曲湿地退化过程中植物群落组分及物种多样性的变化［J］.应用生态学报，2009，20（1）：27-32.
34	李宏林，徐当会，杜国祯.青藏高原高寒沼泽湿地在退化梯度上植物群落组成的改变对湿地水分状况的影响［J］.植物生态学报，2012，36（5）：403-410.
35	Li H L，Adrienne N，Xu D H，et al.Habitat-specific responses of leaf traits to soil water conditions in species from a novel alpine swamp meadow community［J］.Conservation Physiology，2015，3（1）.
36	Gao X X，Dong S K，Li S，et al.Using the random forest model and validated MODIS with the field spectrometer measurement promote the accuracy of estimating aboveground biomass and coverage of alpine grasslands on the Qinghai-Tibetan Plateau［J］.Ecological Indicators，2020，112：106-114.
37	Cao J，Adamowski J F，Deo R C，et al.Grassland degradation on the Qinghai-Tibetan Plateau：reevaluation of causative factors［J］.Rangeland Ecology & Management，2019，72：988-995.

[1]	高永道, 乔荣荣, 季树新, 白雪莲, 王理想, 常学礼. 内蒙古河套灌区作物种植结构变化及其驱动因素[J]. 中国沙漠, 2021, 41(3): 110-117.
[2]	李成阳, 薛娴, 赖炽敏, 尤全刚, 彭飞, 张文娟. 青藏高原退化高寒草甸生长季承载力[J]. 中国沙漠, 2018, 38(6): 1330-1338.
[3]	曹文侠, 李文, 李小龙, 徐长林, 师尚礼, 韩天虎. 施氮对高寒草甸草原植物群落和土壤养分的影响[J]. 中国沙漠, 2015, 35(3): 658-666.
[4]	张号, 屈建军, 张克存. 绿洲植被覆盖度遥感信息提取——以敦煌绿洲为例[J]. 中国沙漠, 2015, 35(2): 493-498.
[5]	张喆, 丁建丽, 李鑫, 鄢雪英. TVDI用于干旱区农业旱情监测的适宜性[J]. 中国沙漠, 2015, 35(1): 220-227.
[6]	高添, 徐斌, 杨秀春, 金云翔, 马海龙, 李金亚, 于海达. 蒙古西部草原地上生物量的遥感估算[J]. 中国沙漠, 2013, 33(2): 597-603.
[7]	杜灵通, 田庆久. 宁夏植被覆盖动态变化及与气候因子的关系[J]. 中国沙漠, 2012, 32(5): 1479-1485.
[8]	逯军峰, 董治宝, 胡光印, 宋翔, 魏振海. 甘肃省玛曲县土地沙漠化发展及其成因分析[J]. 中国沙漠, 2012, 32(3): 604-609.
[9]	孙小艳, 常学礼, 张宁, 韩艳. 不同取样单元对干旱区绿洲小麦地上生物量光谱估算模型的影响[J]. 中国沙漠, 2012, 32(2): 568-573.
[10]	杨光华;;;包安明*;陈曦;刘海隆;黄莹;代述勇;. 气候和土地利用变化对塔里木河干流区植被覆盖变化的影响[J]. 中国沙漠, 2010, 30(6): 1389-1397.
[11]	陈晓光;李剑萍;李志军;韩颖娟;陈葆德. 青海湖地区植被覆盖及其与气温降水变化的关系[J]. 中国沙漠, 2007, 27(5): 797-804.
[12]	卢玲, 李新, 程国栋. 利用NOAA AVHRR植被指数数据集分析黑河流域季候特征[J]. 中国沙漠, 2002, 22(2): 187-191.
[13]	姚德良, 李家春, 李新荣, 张景光, 刘立超. 干旱区陆面过程野外观测研究[J]. 中国沙漠, 2001, 21(3): 254-259.