共查询到20条相似文献，搜索用时 15 毫秒
1.
干旱区生态系统极易受到气候及土地利用变化的影响,其生物多样性格局及其形成机制是重要的生态学问题。基于新疆地区鸟类及哺乳动物物种多样性数据,结合气候、地形和长时间序列的植被遥感参数产品FAPAR数据等,主要在不同的土地利用类型及海拔带上采用单因子相关分析方法探讨了物种丰富度格局的形成机制。总体来说,不同生境类型中,植被遥感参数因子(DHI、NDVI等)与两种类群物种丰富度分布的相关性强于与气候因子(温度、降水)的相关性。具体而言,植被遥感参数因子中,基于FAPAR的生境指数因子与丰富度的相关性大于基于植被指数的因子(DHI_cumNDVI_cumEVI_cum);气候因子中,在草地生境或者较低的海拔上,年均降水因子对于丰富度分布的解释力强于年均温度因子。这表明在新疆地区,影响鸟类与哺乳类动物物种丰富度分布的主导理论是生境异质性假说与环境稳定性假说,其解释力在多种生境内均强于生产力与环境热量。 相似文献
2.
MODIS NDVI和AVHRR NDVI 对草原植被变化监测差异 总被引：5，自引：0，他引：5
以草地作为研究载体,对比分析草原植被AVHRR NDVI和MODIS NDVI两种NDVI序列的年内、年际变化特征,讨论两种NDVI序列对降水量、平均气温和水汽压3种气候因子的响应差异,为合理选择NDVI序列对植被进行监测研究提供参考。结果表明：(1)两种NDVI序列所反映的草原植被年内变化趋势相似,但MODIS NDVI对各类草原的区分度优于AVHRR NDVI;(2)两种NDVI序列所反映的2000年—2003年草原植被年际变化差异明显。较之于MODIS NDVI,AVHRR NDVI变化趋势分类图表现出更强的植被改善趋势,植被改善面积在AVHRR NDVI变化趋势分类图中占94.25%,在MODIS NDVI中为83.33%;两种NDVI变化趋势分类图反映的植被变化趋势吻合度为52.88%。(3)两种NDVI序列与水汽压、降水量相关性差异显著。MODIS NDVI与各站点平均气温的相关系数均大于GIMMS NDVI;而MODIS NDVI与水汽压的相关系数83%(10个站点)小于GIMMS NDVI,与降水量的相关系数67%(8个站点)小于GIMMS NDVI。 相似文献
3.
Mapping and monitoring net primary productivity with AVHRR NDVI time-series: statistical equivalence of cumulative vegetation indices 总被引：1，自引：0，他引：1
Carlo Ricotta Giancarlo Avena Alessandra De Palma 《ISPRS Journal of Photogrammetry and Remote Sensing》1999,54(5-6)
In the last two decades, numerous investigators have proposed cumulative vegetation indices (i.e., functions which encode the cumulative effect of NDVI maximum value composite time-series into a single variable) for net primary productivity (NPP) mapping and monitoring on a regional to continental basis. In this paper, we investigate the relationships among three of the most commonly used cumulative vegetation indices, expanding on the definition of equivalence of remotely sensed vegetation indices for decision making. We consider two cumulative vegetation indices as equivalent, if the value of one index is statistically predictable from the value of the other index. Using an annual time-series of broad-scale AVHRR NDVI monthly maximum value composites of the island of Corsica (France), we show that the pairwise linear association among the analysed cumulative vegetation indices shows coefficients of determination (R2) higher than 0.99. That is, knowing the value of one index is statistically equivalent to knowing the value of the other indices for application purposes. 相似文献
4.
Estimates of forest aboveground biomass are fundamental for carbon monitoring and accounting; delivering information at very high spatial resolution is especially valuable for local management, conservation and selective logging purposes. In tropical areas, hosting large biomass and biodiversity resources which are often threatened by unsustainable anthropogenic pressures, frequent forest resources monitoring is needed. Lidar is a powerful tool to estimate aboveground biomass at fine resolution; however its application in tropical forests has been limited, with high variability in the accuracy of results. Lidar pulses scan the forest vertical profile, and can provide structure information which is also linked to biodiversity. In the last decade the remote sensing of biodiversity has received great attention, but few studies focused on the use of lidar for assessing tree species richness in tropical forests.This research aims at estimating aboveground biomass and tree species richness using discrete return airborne lidar in Ghana forests. We tested an advanced statistical technique, Multivariate Adaptive Regression Splines (MARS), which does not require assumptions on data distribution or on the relationships between variables, being suitable for studying ecological variables.We compared the MARS regression results with those obtained by multilinear regression and found that both algorithms were effective, but MARS provided higher accuracy either for biomass (R2 = 0.72) and species richness (R2 = 0.64). We also noted strong correlation between biodiversity and biomass field values. Even if the forest areas under analysis are limited in extent and represent peculiar ecosystems, the preliminary indications produced by our study suggest that instrument such as lidar, specifically useful for pinpointing forest structure, can also be exploited as a support for tree species richness assessment. 相似文献
5.
机载激光雷达及高光谱的森林乔木物种多样性遥感监测 总被引：1，自引：0，他引：1
利用机载LiDAR和高光谱数据并结合37个地面调查样本数据,基于结构差异与光谱变异理论,通过相关分析法分别筛选了3个最优林冠结构参数和6个最优光谱指数,在单木尺度上利用自适应C均值模糊聚类算法,在神农架国家自然保护区开展森林乔木物种多样性监测,实现了森林乔木物种多样性的区域成图。研究结果表明,(1)基于结合形态学冠层控制的分水岭算法可以获得较高精度的单木分割结果(R~2=0.88,RMSE=13.17,P0.001);(2)基于LiDAR数据提取的9个结构参数中,95%百分位高度、冠层盖度和植被穿透率为最优结构参数,与Shannon-Wiener指数的相关性达到R~2=0.39—0.42(P0.01);(3)基于机载高光谱数据筛选的16个常用的植被指数中,CRI、OSAVI、Narrow band NDVI、SR、Vogelmann index1、PRI与Shannon-Wiener指数的相关性最高(R~2=0.37—0.45,P0.01);(4)在研究区,利用以30 m×30 m为窗口的自适应模糊C均值聚类算法可预测的最大森林乔木物种数为20,物种丰富度的预测精度为R~2=0.69,RMSE=3.11,Shannon-Wiener指数的预测精度为R~2=0.70,RMSE=0.32。该研究在亚热带森林开展乔木物种多样性监测,是在区域尺度上进行物种多样性成图的重要实践,可有效补充森林生物多样性本底数据的调查手段,有助于实现生物多样性的长期动态监测及科学分析森林物种多样性的现状和变化趋势。 相似文献
6.
以福建省为研究区,以中等分辨率MODIS NDVI遥感数据、气象数据及其他辅助数据为数据源,基于植被净初级生产力(net primary productivity,NPP)光能利用率估算模型——CASA,定量研究了该区域历史序列(2001—2012年)NPP时空变化格局,探索其主要影响因素。结果表明:2001—2012年该区域NPP总体呈现下降趋势,2003年和2005年为历年变化下降率最大的两年;该区域NPP时空分布特征明显,在空间上表现为由南向北递减的空间分布格局,且沿海经济发达区域NPP普遍较低;时间上表现为春秋两季具有相同的空间分布,夏季具有最高的NPP,占全年NPP的56%,冬季平均NPP在120gC·m~(-2)·a~(-1)以下;降水和温度与NPP的线性相关性较小,且线性相关性随空间位置的不同而有所差异;福建省NPP对气候因子的响应随空间位置的变化而变化,在不同的区域,其主要的胁迫因子不同,NPP总体受到辐射量的驱动因素要比其他胁迫因子强。 相似文献
7.
Climate oscillation modes can shape weather across the globe due to atmospheric teleconnections. We built on the findings of a recent study to assess whether the impacts of teleconnections are detectable and significant in the early season dynamics of highland pastures across five rayons in Kyrgyzstan. Specifically, since land surface phenology (LSP) has already shown to be influenced by snow cover seasonality and terrain, we investigated here how much more explanatory and predictive power information about climatic oscillation modes might add to explain variation in LSP. We focused on seasonal values of five climate oscillation indices that influence vegetation dynamics in Central Asia. We characterized the phenology in highland pastures with metrics derived from LSP modeling using Landsat NDVI time series together with MODIS land surface temperature (LST) data: Peak Height (PH), the maximum modeled NDVI and Thermal Time to Peak (TTP), the quantity of accumulated growing degree-days based on LST required to reach PH. Next, we calculated two metrics of snow cover seasonality from MODIS snow cover composites: last date of snow (LDoS), and the number of snow covered dates (SCD). For terrain features, we derived elevation, slope, and TRASP index as linearization of aspect. First, we used Spearman’s rank correlation to assess the geographical differentiation of land surface phenology metrics responses to environmental variables. PH showed weak correlations with TTP (positive in western but negative in eastern rayons), and moderate relationships with LDoS and SCD only in one northeastern rayon. Slope was weakly related to PH, while TRASP showed a consistent moderate negative correlation with PH. A significant but weak negative correlation was found between PH and SCAND JJA, and a significant weak positive correlation with MEI MAM. TTP showed consistently strong negative relationships with LDoS, SCD, and elevation. Very weak positive correlations with TTP were found for EAWR DJF, AMO DJF, and MEI DJF in western rayons only. Second, we used Partial Least Squares regression to investigate the role of oscillation modes altogether. PLS modelling of TTP showed that thermal time accumulation could be explained mostly by elevation and snow cover metrics, leading to reduced models explaining 55 to 70% of observed variation in TTP. Variable selection indicated that NAO JJA, AMO JJA and SCAND MAM had significant relationships with TTP, but their input of predictive power was neglible. PLS models were able to explain up to 29% of variability in PH. SCAND JJA and MEI MAM were shown to be significant predictors, but adding them into models did not influence modeling performance. We concluded the impacts of climate oscillation anomalies were not detectable or significant in mountain pastures using LSP metrics at fine spatial resolution. Rather, at a 30 m resolution, the indirect effects of seasonal climatic oscillations are overridden by terrain influences (mostly elevation) and snow cover timing. Whether climate oscillation mode indices can provide some new and useful information about growing season conditions remains a provocative question, particularly in light of the multiple environmental challenges facing the agropastoralism livelihood in montane Central Asia. 相似文献
8.
基于MODIS-NDVI的内蒙古植被变化遥感监测 总被引：2，自引：0，他引：2
本文利用2002-2006年5-8月的MODIS 1B数据,建立NDVI时间序列,并结合气象数据中的月均温、月降水量、滞后1月和滞后2月累计降水量对内蒙古地区植被生长季NDVI的月际、年际变化规律以及NDVI变化同气候因子的相关性进行了分析。结果表明:月际变化上,5-8月NDVI不断增加,NDVI变化率5-6月>6-7月>7-8月;年际变化上,2002-2006年间,草地的波动性最大;在与气候因子的相关性上:滞后2月降水>滞后1月降水>月均温>月降水量;对于林地和草地来说,各种相关系数高纬高于低纬,对于农耕地来说各种相关系数基本相当;对于沙地来说,各种相关系数均不高,这与其植被稀少且几乎无变化有关。 相似文献
9.
Cenk Donmez Suha Berberoglu Paul J. Curran 《International Journal of Applied Earth Observation and Geoinformation》2011
The aim of this study is to use full spatial resolution Envisat MERIS data to drive an ecosystem productivity model for pine forests along the Mediterranean coast of Turkey. The Carnegie, Ames, Stanford Approach (CASA) terrestrial biogeochemical model, designed to simulate the terrestrial carbon cycle using satellite sensor and meteorological data, was used to estimate annual regional fluxes in terrestrial net primary productivity (NPP). At its core this model is based on light-use efficiency, influenced by temperature, rainfall and solar radiation. Present climate data was generated from 50 climate stations within the watershed using co-kriging. Regional scale pseudo-warming data for year 2070 were derived using a Regional Climate Model (RCM) these data were used to downscale the GCM General Circulation Model for the research area as part of an international research project called Impact of Climate Changes on Agricultural Production Systems in Arid Areas (ICCAP). Outputs of climate data can be moderated using the four variables of percent tree cover, land cover, soil texture and NDVI. This study employed 47 MERIS images recorded between March 2003 and September 2005 to derive percent tree cover, land cover and NDVI. Envisat MERIS data hold great potential for estimating NPP with the CASA model because of the appropriateness of both its spatial and its spectral resolution. 相似文献
10.
Vinay Kumar Sehgal Surabhi Jain Pramod Kumar Aggarwal Somnath Jha 《Journal of the Indian Society of Remote Sensing》2011,39(3):373-381
In this study, an attempt has been made to derive the spatial patterns of temporal trends in phenology metrics and productivity
of crops grown, at disaggregated level in Indo-Gangetic Plains of India (IGP), which are helpful in understanding the impact
of climatic, ecological and socio-economic drivers. The NOAA-AVHRR NDVI PAL dataset from 1981 to 2001 was stacked as per the
crop year and subjected to Savitzky-Golay filtering. For crop pixels, maximum and minimum values of normalized difference
vegetation index (NDVI), their time of occurrence and total duration of kharif (June-October) and rabi (November–April) crop seasons were derived for each crop year and later subjected to pixel-wise regression with time to derive
the rate and direction of change. The maximum NDVI value showed increasing trends across IGP during both kharif and rabi seasons indicating a general increase in productivity of crops. The trends in time of occurrence of peak NDVI during kharif dominated with rice showed that the maximum vegetative growth stage was happening early with time during study period across
most of Punjab, North Haryana, Parts of Central and East Uttar Pradesh and some parts of Bihar and West Bengal. Only central
parts of Haryana showed a delay in occurrence of maximum vegetative stage with time. During rabi, no significant trends in occurrence of peak NDVI were observed in most of Punjab and Haryana except in South Punjab and
North Haryana where early occurrence of peak NDVI with time was observed. Most parts of Central and Eastern Uttar Pradesh,
North Bihar and West Bengal showed a delay in occurrence of peak NDVI with time. In general, the rice dominating system was
showing an increase in duration with time in Punjab, Haryana, Western Uttar Pradesh, Central Uttar Pradesh and South Bihar
whereas in some parts of North Bihar and West Bengal a decrease in the duration with time was also observed. During rabi season, except Punjab, the wheat dominating system was showing a decreasing trend in crop duration with time. 相似文献
11.
Szilárd Szabó László Elemér Zoltán Kovács Zoltán Püspöki Ádám Kertész Sudhir Kumar Singh 《地理信息系统科学与遥感》2019,56(4):624-644
Understanding climate change and revealing its future paths on a local level is a great challenge for the future. Beside the expanding sets of available climatic data, satellite images provide a valuable source of information. In our study we aimed to reveal whether satellite data are an appropriate way to identify global trends, given their shorter available time range. We used the CARPATCLIM (CC) database (1961–2010) and the MODIS NDVI images (2000–2016) and evaluated the time period covered by both (2000–2010). We performed a regression analysis between the NDVI and CC variables, and a time series analysis for the 1961–2008 and 2000–2008 periods at all data points. The results justified the belief that maximum temperature (TMAX), potential evapotranspiration and aridity all have a strong correlation with the NDVI; furthermore, the short period trend of TMAX can be described with a functional connection with its long period trend. Consequently, TMAX is an appropriate tool as an explanatory variable for NDVI spatial and temporal variance. Spatial pattern analysis revealed that with regression coefficients, macro-regions reflected topography (plains, hills and mountains), while in the case of time series regression slopes, it justified a decreasing trend from western areas (Transdanubia) to eastern ones (The Great Hungarian Plain). This is an important consideration for future agricultural and land use planning; i.e. that western areas have to allow for greater effects of climate change. 相似文献
12.
This paper develops a localized approach to elastic net logistic regression, extending previous research describing a localized elastic net as an extension to a localized ridge regression or a localized lasso. All such models have the objective to capture data relationships that vary across space. Geographically weighted elastic net logistic regression is first evaluated through a simulation experiment and shown to provide a robust approach for local model selection and alleviating local collinearity, before application to two case studies: county-level voting patterns in the 2016 USA presidential election, examining the spatial structure of socio-economic factors associated with voting for Trump, and a species presence–absence data set linked to explanatory environmental and climatic factors at gridded locations covering mainland USA. The approach is compared with other logistic regressions. It improves prediction for the election case study only which exhibits much greater spatial heterogeneity in the binary response than the species case study. Model comparisons show that standard geographically weighted logistic regression over-estimated relationship non-stationarity because it fails to adequately deal with collinearity and model selection. Results are discussed in the context of predictor variable collinearity and selection and the heterogeneities that were observed. Ongoing work is investigating locally derived elastic net parameters. 相似文献
13.
Geo-spatial approach for phytodiversity characterization in Panna National Park (part), M.P. (India)
Panna National Park is situated in the north-central part of Madhya Pradesh, India. Landscape parameters like fragmentation,
porosity, patchiness and jaxtaposition have been analysed for disturbance gradient characterization. Disturbance on biodiversity
due to human activities has been studied both qualitatively and quantitatively. The species richness is highest in northern
mixed dry deciduous forest followed by dry deciduous open scrub and southern tropical dry deciduous teak forest. Species richness
of the open thorny dry deciduous forest with grasses is found to be the lowest. Disturbance analysis indicates that 22.02%
of the southern slightly moist teak forests are highly disturbed whereas Anogeissus forest and Riverine forest have 17.04% and 12.41% of the area under high disturbance, respectively. A total of 88 field sample
plots were laid to enumerate trees, shrubs, herbs, climbers, etc. Biological richness parameters such as Shannon-Wiener biodiversity
index, biodiversity value, ecosystem uniqueness were derived from field data. High biological richness is found in northern
mixed dry deciduous forest and mixed dry deciduous forest with bamboo. More than 99% of such areas are falling under medium
to high biological richness. Nearly 55% of the gentle and flat to gentle, slope categories were found to have low biological
richness.
Phytosociological analysis of sampled field data indicated that the number of trees per unit area is the lowest in the Savannah.
In inaccessible areas, the species richness and number of trees per unit area is very high. Main forces causing disturbance
are search for diamonds, dams on river Ken, settlements in and around the park, grazing and resource utilization by villagers
for fodder, animal grazing, fuel-wood, timber, etc. 相似文献
14.
Christopher A Williams Niall P Hanan Jason C Neff Robert J Scholes Joseph A Berry Scott A Denning David F Baker 《Carbon balance and management》2007,2(1):3-13
The African continent has a large and growing role in the global carbon cycle, with potentially important climate change implications.
However, the sparse observation network in and around the African continent means that Africa is one of the weakest links
in our understanding of the global carbon cycle. Here, we combine data from regional and global inventories as well as forward
and inverse model analyses to appraise what is known about Africa's continental-scale carbon dynamics. With low fossil emissions
and productivity that largely compensates respiration, land conversion is Africa's primary net carbon release, much of it
through burning of forests. Savanna fire emissions, though large, represent a short-term source that is offset by ensuing
regrowth. While current data suggest a near zero decadal-scale carbon balance, interannual climate fluctuations (especially
drought) induce sizeable variability in net ecosystem productivity and savanna fire emissions such that Africa is a major
source of interannual variability in global atmospheric CO2. Considering the continent's sizeable carbon stocks, their seemingly high vulnerability to anticipated climate and land use
change, as well as growing populations and industrialization, Africa's carbon emissions and their interannual variability
are likely to undergo substantial increases through the 21st century. 相似文献
15.
Sébastien Rapinel Clémence Rozo Pauline Delbosc Damien Arvor Alban Thomas Jan-Bernard Bouzillé 《地理信息系统科学与遥感》2020,57(1):60-73
ABSTRACTMonitoring the structural and functional dimensions of natural vegetation is a critical issue to ensure effective management of biodiversity. While coarse-resolution satellite image time-series have been used extensively to monitor vegetation physiognomies, their potential to describe plant species composition remains understudied. The objective of this study is to assess the potential of annual time-series of MODIS images to discriminate combinations of plant communities, called “vegetation series,” and characterize their structural and functional dimensions at the landscape scale. Twelve vegetation series were mapped in a 16 574 ha study area in a Mediterranean context located in Corsica (France). First, the structural dimension of vegetation series was examined using a random forest (RF) model calibrated with a reference field map to (i) measure the importance of each MODIS image in discriminating vegetation series; (ii) quantify the influence of the number of dates on model accuracy; and (iii) map the vegetation series with the optimal subset of MODIS images. Second, the functional dimension of vegetation series was analyzed by ordinating three functional indices through principal component analysis. These indices were the annual sum of normalized difference vegetation index (NDVI), the annual amplitude of NDVI, and the date of maximum NDVI, considered as a proxy for annual primary production, seasonality of carbon fluxes, and vegetation phenology, respectively. Results showed that (i) vegetation series were mapped accurately (median Kappa index 0.70, median overall accuracy 0.76), preferably using images acquired from February to August; (ii) at least 10 MODIS images were required to achieve sufficient accuracy; and (iii) a functional gradient was detected, ranging from high annual net primary production with low seasonality of carbon fluxes and early phenology in Mediterranean vegetation series to low annual net primary production with high seasonality of carbon fluxes and late phenology in alpine vegetation series. 相似文献
16.
2000—2010年神东矿区植被NPP的变化特征及影响因素分析 总被引：1，自引：0，他引：1
基于EOS/MODIS NPP数据集,对神东矿区植被净初级生产力(NPP)变化的时空特征及主要影响因素进行分析。研究表明,2000—2010年,神东矿区植被年NPP主要介于(98~160)g C/(m2·a)区间,11 a平均值为139.80 g C/(m2·a),低于同期全国植被年平均NPP值360.97 g C/(m2·a)约61.3%,低于同期矿区10 km缓冲区年平均NPP值142.49 g C/(m2·a)约2%,同时也低于同纬度对比区域年均NPP值161.97 g C/(m2·a)约13.7%。11 a NPP值一元线性回归分析表明,3个区域2000—2010年平均NPP变化趋势及斜率特征大致相符,相关系数均达到0.94以上;植被NPP与同期气候因子的相关性分析表明,神东矿区植被年NPP与年降水量相关系数较大,为0.716。 相似文献
17.
18.
针对鄂尔多斯高原植被覆盖变化受干旱胁迫的状况,该文结合降水和气温的协同变化,以2000-2012年生长季的MODIS-NDVI数据和同期降水、温度和帕尔默干旱指数为依据,采用线性趋势分析、标准偏差分析和相关性分析等方法,对鄂尔多斯高原植被与气候变化的相关关系和干旱异常变化对植被动态的影响进行了研究.结果表明:鄂尔多斯高原生长季及季节(春季、夏季和秋季)植被归一化植被指数主要受降水的控制和干旱的制约,秋季归一化植被指数更多地受到夏季干旱的影响.与气象因子的空间相关分析表明,春季温度上升有利于研究区北部归一化植被指数像元的增加.在荒漠草原和沙漠地区,夏季干旱与归一化植被指数的相关关系最强.秋季降水对典型草原归一化植被指数的提升显著. 相似文献
19.
Climate dominantly controls vegetation over most regions at most times, and vegetation responses to climate change are often asymmetric with temporal effects. However, systematic analysis of the time-lag and time-accumulation effects of climate on vegetation growth, has rarely been conducted, in particular for different vegetation growing phases. Thus, this study aimed to leverage normalized difference vegetation index (NDVI) to determine the spatiotemporal patterns of climatic effects on global vegetation growth considering various scenarios of time-lag and/or accumulation effects. The results showed that (i) climatic factors have time-lag and -accumulation effects as well as their combined effects on global vegetation growth for the whole growing season and its subphases (i.e., the growing and senescent phases). However, these effects vary with climatic factors, vegetation types, and regions. Compared with those of temperature, both precipitation and solar radiation display more significant time-accumulation effects in the whole growing season worldwide, but behave differently in the growing and senescent phases in the middle-high latitudes of the Northern Hemisphere; (ii) compared to the scenario without time effects, considering time-lag and -accumulation effects as well as their combined effects increased by 17 %, 15 %, and 19 % the overall explanatory power of vegetation growth by climate change for the whole growing season, the growing phase, and senescent phase, respectively; (iii) considering the time-lag and -accumulation effects as well as their combined effects, climate change controls 70 % of areas with a significant NDVI variation from 1982 to 2015, and the primary driving factor was temperature, followed by solar radiation and precipitation. This study highlights the significant time-lag and -accumulation effects of climatic factors on global vegetation growth. We suggest that these effects need to be incorporated into dynamic vegetation models to better understand vegetation growth under accelerating climate change. 相似文献
20.
研究采矿扰动区内植被变化规律,能够为矿区生态修复提供理论依据。本文以山西省西山煤田为研究区,通过设立对比试验区,利用MODIS/NDVI（2001-2019年）结合同期的气温、降水气候因子,分别从植被指数的时空变化及与气象因子之间的关系等方面展开对比,用于探究采矿扰动区内植被变化情况。研究结果表明：①19年来西山煤田与间接影响区及校验区的植被均呈增加趋势,但西山煤田相比于校验区NDVI均值低11.42%。②西山煤田相较于自然生态条件下植被增长率为-5.53%。③西山煤田与校验区的NDVI值均受到气温、降水两种气象因子的影响,但是与降水的相关性更高,即受降水影响更大。 相似文献