Monitoring and identification of spatiotemporal landscape changes in multiple remote sensing images by using a stratified conditional Latin hypercube sampling approach and geostatistical simulation

This study develops a stratified conditional Latin hypercube sampling (scLHS) approach for multiple, remotely sensed, normalized difference vegetation index (NDVI) images. The objective is to sample, monitor, and delineate spatiotemporal landscape changes, including spatial heterogeneity and variability, in a given area. The scLHS approach, which is based on the variance quadtree technique (VQT) and the conditional Latin hypercube sampling (cLHS) method, selects samples in order to delineate landscape changes from multiple NDVI images. The images are then mapped for calibration and validation by using sequential Gaussian simulation (SGS) with the scLHS selected samples. Spatial statistical results indicate that in terms of their statistical distribution, spatial distribution, and spatial variation, the statistics and variograms of the scLHS samples resemble those of multiple NDVI images more closely than those of cLHS and VQT samples. Moreover, the accuracy of simulated NDVI images based on SGS with scLHS samples is significantly better than that of simulated NDVI images based on SGS with cLHS samples and VQT samples, respectively. However, the proposed approach efficiently monitors the spatial characteristics of landscape changes, including the statistics, spatial variability, and heterogeneity of NDVI images. In addition, SGS with the scLHS samples effectively reproduces spatial patterns and landscape changes in multiple NDVI images.     

Analysis of agricultural drought using vegetation temperature condition index (VTCI) from Terra/MODIS satellite data

The most commonly used normalized difference vegetation index (NDVI) from remote sensing often fall short in real-time drought monitoring due to a lagged vegetation response to drought. Therefore, research recently emphasized on the use of combination of surface temperature and NDVI which provides vegetation and moisture conditions simultaneously. Since drought stress effects on agriculture are closely linked to actual evapotranspiration, we used a vegetation temperature condition index (VTCI) which is more closely related to crop water status and holds a key place in real-time drought monitoring and assessment. In this study, NDVI and land surface temperature (T _s) from MODIS 8-day composite data during cloud-free period (September–October) were adopted to construct an NDVI–T _s space, from which the VTCI was computed. The crop moisture index (based on estimates of potential evapotranspiration and soil moisture depletion) was calculated to represent soil moisture stress on weekly basis for 20 weather monitoring stations. Correlation and regression analysis were attempted to relate VTCI with crop moisture status and crop performance. VTCI was found to accurately access the degree and spatial extent of drought stress in all years (2000, 2002, and 2004). The temporal variation of VTCI also provides drought pattern changes over space and time. Results showed significant and positive relations between CMI (crop moisture index) and VTCI observed particularly during prominent drought periods which proved VTCI as an ideal index to monitor terminal drought at regional scale. VTCI had significant positive relationship with yield but weakly related to crop anomalies. Duration of terminal drought stress derived from VTCI has a significant negative relationship with yields of major grain and oilseeds crops, particularly, groundnut.     

Multi-scale spatial structure of heavy metals in agricultural soils in Beijing

To effectively investigate the spatial variability of heavy metals in soil, produce a higher quality spatial distribution map, and identify the potential pollution sources of heavy metals, geostatistics was employed to evaluate the effect of scale on spatial variability of heavy metals in Beijing agricultural soils. The results revealed that spatial variability of Cr, Ni, Zn, and Hg was dependent on scale. Validation of the optimality of theoretical semivariance and comparative analysis of the estimation accuracy demonstrated that the multi-scale nested model can reveal the spatial structure of heavy metals effectively and improve the estimation accuracy better than the single-scale method, thereby enabling production a higher quality spatial interpolation map. Thus, the multi-scale kriging nested model is a useful tool for revealing spatial variability of heavy metals in soils, while the spatial distribution maps allow the identification of hot spots with high concentrations of heavy metals.     

The effects of pipeline construction disturbance on soil properties and restoration cycle

Disturbance to the physical–chemical properties of soil caused by pipeline installation was evaluated using two soil quality indices to identify the scale of disturbance and the restoration cycle. The integrated soil quality index (SQI) was used to evaluate soil property changes in different pipeline zones (0, 10, 20, and 50 m from the pipeline) at sites 1 and 2. The soil restoration index (SRI) was used to estimate soil recovery from three pipelines with different recovery periods (2, 6, and 8 years) at site 3. The results showed that the adverse effects of pipeline construction on soil properties mainly occurred in the right-of-way (ROW) areas and the impaired zones were in the order trench?>?piling and working areas?>?20 and 50 m. The soil restoration cycle may be complete within 6 years of construction. At site 3, the SRI in the ROW area of a pipeline after 6 years of restoration was close to 100 %, showing full soil recovery. However, the SRI in the disturbed areas of a pipeline after 2 years of restoration was much lower than that after 6 years of restoration, indicating that the soil was still recovering from the disturbance. The topography may change the intensity of disturbance in different areas due to the movement patterns of heavy machinery and traffic routes. There were local variations in the SQI within the pipeline zones, with flat areas suffering greater disturbance than hilly areas, indicating that topography should be considered in a pipeline’s environmental impact assessment.     

Distribution of heavy metals in agricultural soils near a petrochemical complex in Guangzhou, China

The aim of the study was to investigate influence of an industrialized environment on the accumulation of heavy metals in agricultural soils. Seventy soil samples collected from surface layers (0-20 cm) and horizons of five selected pedons in the vicinity area of petrochemical complex in Guangzhou, China were analyzed for Zn, Cu, Pb, Cd, Hg and As concentrations, the horizontal and vertical variation of these metals were studied and geographic information system (GIS)-based mapping techniques were applied to generate spatial distribution maps. The mean concentrations of these heavy metals in the topsoils did not exceed the maximum allowable concentrations in agricultural soil of China with the exception of Hg. Significant differences between land-use types showed that Cu, Pb, Cd, Hg and As concentrations in topsoils were strongly influenced by agricultural practices and soil management. Within a radius of 1,300 m there were no marked decreasing trends for these element concentrations (except for Zn) with the increase of distance from the complex boundary, which reflected little influence of petroleum air emission on soil heavy metal accumulation. Concentrations of Zn, Cu, Pb, Cd, Hg and As in the five pedons, particularly in cultivated vegetable field and orchard, decreased with soil depth, indicating these elements mainly originated from anthropogenic sources. GIS mapping was a useful tool for evaluating spatial variability of heavy metals in the affected soil. The spatial distribution maps allowed the identification of hot-spot areas with high metal concentration. Effective measures should be taken to avoid or minimize heavy metal further contamination of soils and to remediate the contaminated areas in order to prevent pollutants affecting human health through agricultural products.     

A method to the impact assessment of the returning grazing land to grassland project on regional eco-environmental vulnerability

The Chinese government has conducted the Returning Grazing Land to Grassland Project (RGLGP) across large portions of grasslands from western China since 2003. In order to explore and understand the impact in the grassland's eco-environment during the RGLGP, we utilized Projection Pursuit Model (PPM) and Geographic Information System (GIS) to develop a spatial assessment model to examine the ecological vulnerability of the grassland. Our results include five indications: (1) it is practical to apply the spatial PPM on ecological vulnerability assessment for the grassland. This methodology avoids creating an artificial hypothesis, thereby providing objective results that successfully execute a multi-index assessment process and analysis under non-linear systems in eco-environments; (2) the spatial PPM is not only capable of evaluating regional eco-environmental vulnerability in a quantitative way, but also can quantitatively demonstrate the degree of effect in each evaluation index for regional eco-environmental vulnerability; (3) the eco-environment of the Xianshui River Basin falls into the medium range level. The normalized difference vegetation index (NDVI) and land use cover and change (LUCC) crucially influence the Xianshui River Basin's eco-environmental vulnerability. Generally, in the Xianshui River Basin, regional eco-environmental conditions improved during 2000 and 2010. The RGLGP positively affected NDVI and LUCC structure, thereby promoting the enhancement of the regional eco-environment; (4) the Xianshui River Basin divides its ecological vulnerability across different levels; therefore our study investigates three ecological regions and proposes specific suggestions for each in order to assist in eco-environmental protection and rehabilitation; and lastly that (5) the spatial PPM established by this study has the potential to be applied on all types of grassland eco-environmental vulnerability assessments under the RGLGP and under the similar conditions in the Returning Agriculture Land to Forest Project (RALFP). However, when establishing an eco-environmental vulnerability assessment model, it is necessary to choose suitable evaluation indexes in accordance with regional eco-environmental characteristics.     

1982—2022年黄土高原归一化植被指数变化的时空特征

长时间地表植被指数变化序列构建与分析是生态环境监测领域的重要内容。以我国生态工程建设重点地区——黄土高原为研究区，采用时间序列的方差匹配方法，融合了2套卫星遥感的归一化植被指数(NDVI)数据产品(GIMMS 3g和MODIS),建立了覆盖1982—2022年的黄土高原暖季(5—9月)NDVI数据集，揭示了其间黄土高原植被覆盖变化的时空特征。研究发现：黄土高原暖季NDVI呈现“先慢后快”的增加趋势，转折点大致出现在2002年，1982—2002年暖季NDVI增速仅为0.01/(10 a),2003—2022年增速高达0.06/(10 a),其中十八大以来增速尤为显著；暖季NDVI快速增加区域主要位于黄土高原中部，并向东北、西南方向延展，与“退耕还林(草)”重点区域范围基本一致；在黄土高原南部、东部和青海省东部一带，暖季NDVI呈缓慢下降趋势。过去40年间黄土高原NDVI增加与生态工程建设关系密切。     

Spatial variability of soil salinity in coastal saline soil at different scales in the Yellow River Delta,China

The objectives of this study were to explore the spatial variability of soil salinity in coastal saline soil at macro, meso and micro scales in the Yellow River delta, China. Soil electrical conductivities (ECs) were measured at 0–15, 15–30, 30–45 and 45–60 cm soil depths at 49 sampling sites during November 9 to 11, 2013. Soil salinity was converted from soil ECs based on laboratory analyses. Our results indicated that at the macro scale, soil salinity was high with strong variability in each soil layer, and the content increased and the variability weakened with increasing soil depth. From east to west in the region, the farther away from the sea, the lower the soil salinity was. The degrees of soil salinization in three deeper soil layers are 1.14, 1.24 and 1.40 times higher than that in the surface soil. At the meso scale, the sequence of soil salinity in different topographies, soil texture and vegetation decreased, respectively, as follows: depression >flatland >hillock >batture; sandy loam >light loam >medium loam >heavy loam >clay; bare land >suaeda salsa >reed >cogongrass >cotton >paddy >winter wheat. At the micro scale, soil salinity changed with elevation in natural micro-topography and with anthropogenic activities in cultivated land. As the study area narrowed down to different scales, the spatial variability of soil salinity weakened gradually in cultivated land and salt wasteland except the bare land.     

Assessing heavy metal pollution in the water level fluctuation zone of China’s Three Gorges Reservoir using geochemical and soil microbial approaches

The water level fluctuation zone (WLFZ) in the Three Gorges Reservoir is located in the intersection of terrestrial and aquatic ecosystems, and assessing heavy metal pollution in the drown zone is critical for ecological remediation and water conservation. In this study, soils were collected in June and September 2009 in natural recovery area and revegetation area of the WLFZ, and geochemical approaches including geoaccumulation index (I _geo) and factor analysis and soil microbial community structure were applied to assess the spatial variability and evaluate the influence of revegetation on metals in the WLFZ. Geochemical approaches demonstrated the moderate pollutant of Cd, the slight pollutant of Hg, and four types of pollutant sources including industrial and domestic wastewater, natural rock weathering, traffic exhaust, and crustal materials in the WLFZ. Our results also demonstrated significantly lower concentrations for elements of As, Cd, Pb, Zn, and Mn in the revegetation area. Moreover, soil microbial community structure failed to monitor the heavy metal pollution in such a relatively clean area. Our results suggest that revegetation plays an important role in controlling heavy metal pollution in the WLFZ of the Three Gorges Reservoir, China.     

铅锌冶炼厂周边土壤铅源的铅同位素示踪

以某铅锌冶炼厂周边土壤为研究对象,通过对其原料及周边土壤中铅含量的检测,结果显示：该冶炼厂周边土壤铅质量比在22.73mg/kg～126.51mg/kg之间,平均值为42.68mg/kg,是当地土壤铅背景值的1.85倍.采用铅质量比空间分布分析和同位素混合模型计算分析了冶炼厂周边土壤中铅的可能来源,分析表明：土壤铅质量比的空间分布及铅同位素比值与冶炼厂的焦化原料煤相近,焦化原料煤对周边土壤铅污染贡献最大.     

基于GIS的南京市典型蔬菜基地土壤重金属污染现状与评价

对南京市八卦洲蔬菜基地土壤中的铅、铬、铜和镉进行测定分析,利用不同的评价标准来评价其环境质量状况,同时借助GIS软件研究了污染指数的空间分布状况,并解析了其重金属污染的来源.结果表明,以自然背景值为评价标准,则蔬菜地土壤中的重金属都超过污染指标,其中镉为首要污染因子;以国标二级为评价标准,则除镉以外的三种重金属的单项污染指数值全都小于1,但其综合污染指数迭1.50,总体上属轻污染状况.南京化工因区、南京长江二桥和各种农业生产活动等可能是主要污染源.     

Monitoring and assessing of landscape heterogeneity at different scales

In numerous studies, spatial and spectral aggregations of pixel information using average values from imaging spectrometer data are suggested to derive spectral indices and the subsequent vegetation parameters that are derived from these. Currently, there are very few empirical studies that use hyperspectral data, to support the hypothesis for deriving land surface variables from different spectral and spatial scales. In the study at hand, for the first time ever, investigations were carried out on fundamental scaling issues using specific experimental test flights with a hyperspectral sensor to investigate how vegetation patterns change as an effect of (1) different spatial resolutions, (2) different spectral resolutions, (3) different spatial and spectral resolutions as well as (4) different spatial and spectral resolutions of originally recorded hyperspectral image data compared to spatial and spectral up- and downscaled image data. For these experiments, the hyperspectral sensor AISA-EAGLE/HAWK (DUAL) was mounted on an aircraft to collect spectral signatures over a very short time sequence of a particular day. In the first experiment, reflectance measurements were collected at three different spatial resolutions ranging from 1 to 3 m over a 2-h period in 1 day. In the second experiment, different spectral image data and different additional spatial data were collected over a 1-h period on a particular day from the same test area. The differently recorded hyperspectral data were then spatially and spectrally rescaled to synthesize different up- and down-rescaled images. The normalised difference vegetation index (NDVI) was determined from all image data. The NDVI heterogeneity of all images was compared based on methods of variography. The results showed that (a) the spatial NDVI patterns of up- and downscaled data do not correspond with the un-scaled image data, (b) only small differences were found between NDVI patterns determined from data recorded and resampled at different spectral resolutions and (c) the overall conclusion from the tests carried out is that the spatial resolution is more important in determining heterogeneity by means of NDVI than the depth of the spectral data. The implications behind these findings are that we need to exercise caution when interpreting and combining spatial structures and spectral indices derived from satellite images with differently recorded geometric resolutions.     

Impacts of climate warming on vegetation in Qaidam Area from 1990 to 2003

The observed warming trend in the Qaidam area, an arid basin surrounded by high mountains, has caused land surface dynamics that are detectable using remotely sensed data. In this paper, we detected land-cover changes in the Qaidam Area between 1990 and 2003 in attempt to depict its spatial variability. The land-cover changes were categorized into two trends: degradation and amelioration, and their spatial patterns were examined. Then we estimated the correlation coefficients between growing-season NDVI and several climatic factors with the consideration of duration and lagging effects. The results show that the inter-annual NDVI variations are positively correlated with May to July precipitations, but not significantly correlated with sunshine duration. We observed no obvious trend in precipitation or sunshine duration from 1990 to 2003. Thus, the authors suggest that their slight fluctuations may not be responsible to the decade-scaled land-cover changes. However, our results indicate a good positive relationship between the NDVI trend and climate warming in the ameliorated areas, but a negative one in the degraded areas. By statistical analyses, we found that degradations mainly occurred at the oasis boundaries and at lower elevations in the non-oasis regions where effective soil moisture might have been reduced by the warming-caused increase in evapotranspiration. At higher elevations where thermal condition acts as a major limiting factor, ameliorations were unequivocally detected, which is attributable to the direct facilitation by temperature increases. We suggest that the impacts of the observed climate warming on vegetation are spatially heterogeneous, depending on the combinations of thermal condition and moisture availability.     

A change vector analysis technique for monitoring land cover changes in Copsa Mica,Romania, in the period 1985–2011

During the communist regime, Romania’s planned economy focused exclusively on production neglecting the environment protection. The lack of less polluting production technologies and of environmental protection measures led to excessive pollution in certain industrialized areas. This is the case of the town of Copsa Mica in Sibiu County, which in 1987 was considered one of the most polluted towns in Europe. The present study assesses the change vector analysis (CVA) technique using a Landsat Thematic Mapper (TM) image time series to monitor land cover changes caused by carbon black and heavy metal pollution. CVA was applied to the tasseled cap greenness (TCG) and tasseled cap brightness (TCB) indices, as well as to the Normalized Difference Vegetation Index (NDVI) and bare soil index (BI). Various maps were generated for the periods 1985–1994, 1994–2003, 2003–2011, and 1985–2011, and threshold values were determined for the detection of land cover change/no change. The change direction and magnitude values were cross-tabulated and classified. The technique was assessed based on the change versus no-change error matrix. The results show that in the area of Copsa Mica, land cover changes occurred because of a considerable decrease in the area affected by carbon black and heavy metal pollution. The CVA technique proved efficient in monitoring the land cover changes caused by pollution and especially by carbon black pollution. Soil pollution by heavy metals is reflected in the bare soil surfaces present in the imagery.     

Spatial–temporal dynamics of NDVI and Chl-a concentration from 1998 to 2009 in the East coastal zone of China: integrating terrestrial and oceanic components

Annual normalized difference vegetation index (NDVI) and chlorophyll-a (Chl-a) concentration are the most important large-scale indicators of terrestrial and oceanic ecosystem net primary productivity. In this paper, the Sea-viewing Wide Field-of-view Sensor level 3 standard mapped image annual products from 1998 to 2009 are used to study the spatial–temporal characters of terrestrial NDVI and oceanic Chl-a concentration on two sides of the coastline of China by using the methods of mean value (M), coefficient of variation (CV), the slope of unary linear regression model (Slope), and the Hurst index (H). In detail, we researched and analyzed the spatial–temporal dynamics, the longitudinal zonality and latitudinal zonality, the direction, intensity, and persistency of historical changes. The results showed that: (1) spatial patterns of M and CV between NDVI and Chl-a concentration from 1998 to 2009 were very different. The dynamic variation of terrestrial NDVI was much mild, while the variation of oceanic Chl-a concentration was relatively much larger; (2) distinct longitudinal zonality was found for Chl-a concentration and NDVI due to their hypersensitivity to the distance to shoreline, and strong latitudinal zonality existed for Chl-a concentration while terrestrial NDVI had a very weak latitudinal zonality; (3) overall, the NDVI showed a slight decreasing trend while the Chl-a concentration showed a significant increasing trend in the past 12 years, and both of them exhibit strong self-similarity and long-range dependence which indicates opposite future trends between land and ocean.     

Field-scale monitoring of the long-term impact and sustainability of drainage water reuse on the west side of California's San Joaquin Valley

Diminishing freshwater resources have brought attention to the reuse of degraded water as a water resource rather than a disposal problem. Drainage water from tile-drained, irrigated agricultural land is degraded water that is often in large supply, but the long-term impact and sustainability of its reuse on soil is unknown. Similarly, nothing is known of the ramifications of terminating drainage water reuse. The objective of this study is (i) to monitor the long-term impact on soil chemical properties and thereby the sustainability of drainage water reuse on a marginally productive, saline-sodic, 32.4 ha field located on the west side of California's productive San Joaquin Valley and (ii) to assess spatially what happens to soil when drainage water reuse is terminated. The monitoring and assessment were based on spatial chemical data for soil collected during 10 years of irrigation with drainage water followed by 2 years of no applied irrigation water (only rainfall). Geo-referenced measurements of apparent soil electrical conductivity (EC(a)) were used to direct the soil sampling design to characterize spatial variability of impacted soil properties. Chemical analyses of soil samples were used (i) to characterize the spatial variability of salinity, Na, B, and Mo, which were previously identified as critical to the yield and quality of Bermuda grass (Cynodon dactylon (l.) Pers.) grown for livestock consumption and (ii) to monitor their change during the 12 year study. Soil samples were taken at 0.3 m increments to a depth of 1.2 m at each of 40 sample sites on five occasions: August 1999, April 2002, November 2004, August 2009, and May 2011. Drainage water varying in salinity (1.8-16.3 dS m(-1)), SAR (5.2-52.4), Mo (80-400 μg L(-1)), and B (0.4-15.1 mg L(-1)) was applied from July 2000 to June 2009. Results indicate that salts, Na, Mo, and B were leached from the root zone causing a significant improvement in soil quality from 1999 to 2009. Salinity and SAR returned to original levels or higher in less than two years after termination of irrigation. Boron and Mo showed significant increases. Long-term sustainability of drainage water reuse was supported by the results, but once application of irrigation water was terminated, the field quickly returned to its original saline-sodic condition.     

Soil fauna and soil microflora as possible indicators of soil pollution

Research on biological indicators of soil pollution is hampered by soil variability and temporal and spatial fluctuations of numbers of soil animals. These characters on the other hand promote a high biological diversity in the soil. A high diversity combined with persistent soil pollutants increases the chance to select good indicators. However research on these topics is still limited. Examples of specific indicators are the changed arthropod species patterns due to pesticide influence and the changed soil enzyme activity under the influence of specific heavy metals. Another approach is to look for organisms that give a general indication of soil pollution. In this respect the earthworm species Allolobophora caliginosa proved to be sensitive for different types of manure especially pig manure with copper, for sewage sludge, for municipal waste compost and for fly ash. A third way of indication is by organisms accumulating pollutants. For some heavy metals (Cd, Zn), earthworms are very efficient accumulators. More research is needed especially on the specific relation between biological responses and abiotic soil characteristics.     

Evaluating the difference between the normalized difference vegetation index and net primary productivity as the indicators of vegetation vigor assessment at landscape scale

Both the net primary productivity (NPP) and the normalized difference vegetation index (NDVI) are commonly used as indicators to characterize vegetation vigor, and NDVI has been used as a surrogate estimator of NPP in some cases. To evaluate the reliability of such surrogation, here we examined the quantitative difference between NPP and NDVI in their outcomes of vegetation vigor assessment at a landscape scale. Using Landsat ETM+ data and a process model, the Boreal Ecosystem Productivity Simulator, NPP distribution was mapped at a resolution of 90 m, and total NDVI during the growing season was calculated in Heihe River Basin, Northwest China in 2002. The results from a comparison between the NPP and NDVI classification maps show that there existed a substantial difference in terms of both area and spatial distribution between the assessment outcomes of these two indicators, despite that they are strongly correlated. The degree of difference can be influenced by assessment schemes, as well as the type of vegetation and ecozone. Overall, NDVI is not a good surrogate of NPP as the indicators of vegetation vigor assessment in the study area. Nonetheless, NDVI could serve as a fairish surrogate indicator under the condition that the target region has low vegetation cover and the assessment has relatively coarse classification schemes (i.e., the class number is small). It is suggested that the use of NPP and NDVI should be carefully selected in landscape assessment. Their differences need to be further evaluated across geographic areas and biomes.     

江苏沿海滩涂土壤重金属风险分析

以江苏沿海滩涂作为研究区,通过采样检测,结合统计分析方法和潜在生态风险指数,研究不同滩涂围垦类型下土壤/沉积物重金属总量、有效态含量及其潜在生态风险。研究结果表明：滩涂土壤重金属总体呈轻度污染,高值区位于养殖区和行道树林;不同土地利用类型下的重金属以中等偏下变异为主,空间异质性弱;重金属有效态与总量呈显著正相关;潜在生态风险主要由Cd、Hg贡献,64.78%和35.21%的土壤点位呈现Cd强度和中度生态风险,养殖池塘和农田重金属潜在生态风险最严重。     

Vegetation NDVI Linked to Temperature and Precipitation in the Upper Catchments of Yellow River

Vegetation in the upper catchment of Yellow River is critical for the ecological stability of the whole watershed. The dominant vegetation cover types in this region are grassland and forest, which can strongly influence the eco-environmental status of the whole watershed. The normalized difference vegetation index (NDVI) for grassland and forest has been calculated and its daily correlation models were deduced by Moderate Resolution Imaging Spectroradiometer products on 12 dates in 2000, 2003, and 2006. The responses of the NDVI values with the inter-annual grassland and forest to three climatic indices (i.e., yearly precipitation and highest and lowest temperature) were analyzed showing that, except for the lowest temperature, the yearly precipitation and highest temperature had close correlations with the NDVI values of the two vegetation communities. The value of correlation coefficients ranged from 0.815 to 0.951 (p?<?0.01). Furthermore, the interactions of NDVI values of vegetation with the climatic indicators at monthly interval were analyzed. The NDVI of vegetation and three climatic indices had strong positive correlations (larger than 0.733, p?<?0.01). The monthly correlations also provided the threshold values for the three climatic indictors, to be used for simulating vegetation growth grassland under different climate features, which is essential for the assessment of the vegetation growth and for regional environmental management.