利用NOAA AVHRR植被指数数据集分析黑河流域季候特征

利用 NOAA AVHRR的全球归一化植被指数（NDVI）的高时间分辨率数据集，建立了黑河流域 1992-1993和1995-1996两个年度的NDVI数据，范围在96．45°～102．8 °E，35．4°～43．5°N之间。对此数据进行主成分分析（PCA）．提取了前4个主成分分量，分析了黑河流域季候变化特征。结果表明，第一主成分展示了黑河流域NDVI值在分析时段内的综合空间分布结构、累积状况以及地域差异；第二主成分反映黑河流域的NDVI变化不但具有明显的年周期，而且表现出强烈的季节性，是冬夏分明的季节因素所导致；第三主成分主要指征了平原人工绿洲区显著的农作物生长期；第四主成分反映出山区自然植被与平原人工绿洲植被具有明显不同的生长期和物候特征，该成分可以被用于区分不同的地表覆盖类型。

Seasonal Dynamics of Terrestrial Net Primary Production in Response to Climate Changes in China

Study on seasonal responses of terrestrial net primary production (NPP) to climate changes is to help understand feedback between climate systems and terrestrial ecosystems and mechanisms of increased NPP in the northern middle and high latitudes. In this study, time series dataset of normalized difference vegetation index (NDVI) and corresponding ground-based information on vegetation, climate, soil, and solar radiation, together with an ecological process model, were used to explore the seasonal trends of terrestrial NPP and their geographical differences in China from 1982 to 1999. As the results,. seasonal total NPP in China showed a significant increase for all four seasons (spring, summer, autumn and winter) during the past 18 years. The spring NPP indicated the largest increase rate, while the summer NPP was with the largest increase in magnitude. The response of NPP to climate changes varied with different vegetation types. The increased NPP was primarily led by an advanced growing season for broadleaf evergreen forest, needle-leaf evergreen forest, and needle-leaf deciduous forest, whilst that was mainly due to enhanced vegetation activity (amplitude of growth cycle) during growing season for broadleaf deciduous forest, broadleaf and needle-leaf mixed forest, broadleaf trees with groundcover, perennial grasslands, broadleaf shrubs with grasslands, tundra, desert, and cultivation. The regions with the largest increase in spring NPP appeared mainly in eastern China, while the areas with the largest increase in summer NPP occurred in most parts of Northwestern China, Qinghai-Xizang Plateau, Mts. Xiaoxinganling-Changbaishan, Sanjiang Plain, Songliao Plain, Sichuan Basin, Leizhou Peninsula, part of the middle and lower Yangtze River, and southeastern mountainous areas of China. In autumn, the largest NPP increase appeared in Yunnan Plateau-Eastern Xizang and the areas around Hulun Lake. Such different ways of the NPP responses depended on regional climate attributes and their changes.

An Assessment of Urban Heat Island Effect using Remote Sensing Data

Characteristics of urban heat island （UHI） effect and its cause are investigated by using MODIS data in April 2004. Surface parameters from the MODIS data have surface temperature （ts） albedo（α）, and normalized difference vegetation index （NDVI）. Their heterogeneities over urban and rural area are analyzed based on land cover classification, and their relations are also presented in order to explain the UHI effect. The results show that there exists obvious the UHI effect. Ts over urban areas are by 10.83 % higher than those over rural area, and NDVI and α over urban area are by 62 % and 18.75 % less than those over rural area, respectively. Surface temperature has significantly negative correlation with NDVI and their correlation coefficient is -0.73. Correlation between NDVI and albedo is determined by the spectrum of light. Difference in vegetation cover is the primary cause of the UHI effect.

Examining Forest Net Primary Productivity Dynamics and Driving Forces in Northeastern China During 1982–2010

Forest net primary productivity （NPP） is a key parameter for forest monitoring and management. In this study, monthly and annual forest NPP in the northeastern China from 1982 to 2010 were simulated by using Carnegie-Ames-Stanford Approach （CASA） model with normalized difference vegetation index （NDVI） sequences derived from Advanced Very High Resolution Radiometer （AVHRR） Global Invento y Modeling and Mapping Studies （GIMMS） and Terra Moderate Resolution Imaging Spectroradiometer （MODIS） products. To address the problem of data inconsistency between AVHRR and MODIS data, a per-pixel unary linear regres- sion model based on least ~;quares method was developed to derive the monthly NDVI sequences. Results suggest that estimated forest NPP has mean relative error of 18.97% compared to observed NPP from forest inventory. Forest NPP in the northeastern China in- creased significantly during the twenty-nine years. The results of seasonal dynamic show that more clear increasing trend of forest NPP occurred in spring and awmnn. This study also examined the relationship between forest NPP and its driving forces including the climatic and anthropogenic factors. In spring and winter, temperature played the most pivotal role in forest NPR In autumn, precipitation acted as the most importanl factor affecting forest NPP, while solar radiation played the most important role in the summer. Evaportran- spiration had a close correlation with NPP for coniferous forest, mixed coniferous broadleaved forest, and broadleaved deciduous forest. Spatially, forest NPP in the Da Hinggan Mountains was more sensitive to climatic changes than in the other ecological functional re- gions. In addition to climalie change, the degradation and improvement of forests had important effects on forest NPP. Results in this study are helpful for understanding the regional carbon sequestration and can enrich the cases for the monitoring of vegetation during long time series.

Vegetation Change of Ecotone in West of Northeast China Plain Using Time-series Remote Sensing Data

Multi-temporal series of satellite SPOT-VEGETATION normalized difference vegetation index (NDVI) and normalized difference water index (NDWI) data from 1998 to 2007 were used for analyzing vegetation change of the ecotone in the west of the Northeast China Plain. The yearly and monthly maximal values,anomalies and change rates of NDVI and NDWI were calculated to reveal the interannual and seasonal changes in vegetation cover and vegetation water content. Linear regression method was adopted to characterize the trends in vegetation change. The yearly maximal NDVI decreased from 0.41 in 1998 to 0.37 in 2007,implying the decreasing trend of vegetation activity. There was a significant decrease of maximal NDVI in spring and summer over the study period,while an increase trend was observed in autumn. The vegetation-improved regions and vegetation-degraded regions occupied 17.03% and 20.30% of the study area,respectively. The maximal NDWI over growing season dropped by 0.027 in 1998–2007,and about 15.15% of the study area showed a decreasing trend of water content. Vegetation water stress in autumn was better than that in spring. Vegetation cover and water content variations were sensitive to annual precipitation,autumn precipitation and summer temperature. The vegetation degradation trend in this ecotone might be induced by the warm-drying climate especially continuous spring and summer drought in the recent ten years.

The Relationship between Normalized Difference Vegetation Index(NDVI) and Climate Factors in the Semiarid Region:A Case Study in Yalu Tsangpo River Basin of Qinghai-Tibet Plateau

The Yalu Tsangpo River basin is a typical semi-arid and cold region in the Qinghai-Tibet Plateau, where significant climate change has been detected in the past decades. The objective of this paper is to demonstrate how the regional vegetation, especially the typical plant types, responds to the climate changes. In this study, the model of gravity center has been firstly introduced to analyze the spatial-temporal relationship between NDVI and climate factors considering the time-lag effect. The results show that the vegetation grown has been positively influenced by the rainfall and precipitation both in moving tracks of gravity center and time-lag effect especially for the growing season during the past thirteen years. The herbs and shrubs are inclined to be influenced by the change of rainfall and temperature, which is indicated by larger positive correlation coefficients at the 0.05 confidence level and shorter lagging time. For the soil moisture, the significantly negative relationship of NDV-PDI indicates that the growth and productivity of the vegetation are closely related to the short-term soil water, with the correlation coefficients reaching the maximum value of o.81 at Lag 0-1. Among the typicalvegetation types of plateau, the shrubs of low mountain, steppe and meadow are more sensitive to the change of soil moisture with coefficients of -0.95, -0.93, -0.92, respectively. These findings reveal that the spatial and temporal heterogeneity between NDVI and climatic factors are of great ecological significance and practical value for the protection of eco-environment in Qinghai-Tibet Plateau.

Driving force and changing trends of vegetation phenology in the Loess Plateau of China from 2000 to 2010

Changes in vegetation phenology are key indicators of the response of ecosystems to climate change.Therefore,knowledge of growing seasons is essential to predict ecosystem changes,especially for regions with a fragile ecosystem such as the Loess Plateau.In this study,based on the normalized difference vegetation index(NDVI) data,we estimated and analyzed the vegetation phenology in the Loess Plateau from 2000 to 2010 for the beginning,length,and end of the growing season,measuring changes in trends and their relationship to climatic factors.The results show that for 54.84% of the vegetation,the trend was an advancement of the beginning of the growing season(BGS),while for 67.64% the trend was a delay in the end of the growing season(EGS).The length of the growing season(LGS) was extended for 66.28% of the vegetation in the plateau.While the temperature is important for the vegetation to begin the growing season in this region,warmer climate may lead to drought and can become a limiting factor for vegetation growth.We found that increasedprecipitation benefits the advancement of the BGS in this area.Areas with a delayed EGS indicated that the appropriate temperature and rainfall in autumn or winter enhanced photosynthesis and extended the growth process.A positive correlation with precipitation was found for 76.53% of the areas with an extended LGS,indicating that precipitation is one of the key factors in changes in the vegetation phenology in this water-limited region.Precipitation plays an important role in determining the phenological activities of the vegetation in arid and semiarid areas,such as the Loess Plateau.The extended growing season will significantly influence both the vegetation productivity and the carbon fixation capacity in this region.

Clipping Alters the Response of Biomass Production to Experimental Warming: A Case Study in an Alpine Meadow on the Tibetan Plateau, China

Predicting how human activity will influence the response of alpine grasslands to future warming has many uncertainties.In this study, a field experiment with controlled warming and clipping was conducted in an alpine meadow at three elevations（4313 m, 4513 m and 4693 m） in Northern Tibet to test the hypothesis that clipping would alter warming effect on biomass production.Open top chambers（OTCs） were used to increase temperature since July,2008 and the OTCs increased air temperature by approximately 0.9o C ~ 1.8o C during the growing in2012.Clipping was conducted three times one year during growing season and the aboveground parts of all live plants were clipped to approximately 0.01 m in height using scissors since 2009.Gross primary production（GPP） was calculated from the Moderate-Resolution Imaging Spectroradiometer GPP algorithm and aboveground plant production was estimated using the surface-measured normalized difference vegetation index in 2012.Warming decreased the GPP, aboveground biomass（AGB） and aboveground net primary production（ANPP） at all three elevations when clipping was not applied.In contrast, warming increased AGB at all three elevations, GPP at the two lower elevations and ANPP at the two higher elevations when clipping was applied.These findings show that clipping reduced the negative effect of warming on GPP, AGB and ANPP, suggesting that clipping may reduce the effect of climate warming on GPP, AGB and ANPP in alpine meadows on the Tibetan Plateau, and therefore, may be a viable strategy for mitigating the effects of climate change on grazing and animal husbandry on the Tibetan Plateau.

Assessment of Human Impacts on Vegetation in Built-up Areas in China Based on AVHRR,MODIS and DMSP_OLS Nighttime Light Data,1992–2010

Since the reform and opening-up program started in 1978,the level of urbanization has increased rapidly in China.Rapid urban expansion and restructuring have had significant impacts on the ecological environment especially within built-up areas.In this study,ArcGIS 10,ENVI 4.5,and Visual FoxPro 6.0 were used to analyze the human impacts on vegetation in the built-up areas of 656Chinese cities from 1992 to 2010.Firstly,an existing algorithm was refined to extract the boundaries of the built-up areas based on the Defense Meteorological Satellite Program Operational Linescan System(DMSP_OLS)nighttime light data.This improved algorithm has the advantages of high accuracy and speed.Secondly,a mathematical model(Human impacts(HI))was constructed to measure the impacts of human factors on vegetation during rapid urbanization based on Advanced Very High Resolution Radiometer(AVHRR)Normalized Difference Vegetation Index(NDVI)and Moderate Resolution Imaging Spectroradiometer(MODIS)NDVI.HI values greater than zero indicate relatively beneficial effects while values less than zero indicate proportionally adverse effects.The results were analyzed from four aspects:the size of cities(metropolises,large cities,medium-sized cities,and small cities),large regions(the eastern,central,western,and northeastern China),administrative divisions of China(provinces,autonomous regions,and municipalities)and vegetation zones(humid and semi-humid forest zone,semi-arid steppe zone,and arid desert zone).Finally,we discussed how human factors impacted on vegetation changes in the built-up areas.We found that urban planning policies and developmental stages impacted on vegetation changes in the built-up areas.The negative human impacts followed an inverted′U′shape,first rising and then falling with increase of urban scales.China′s national policies,social and economic development affected vegetation changes in the built-up areas.The findings can provide a scientific basis for municipal planning departments,a decision-making reference for government,and scientific guidance for sustainable development in China.

Influence of urbanization on the thermal environment of meteorological station:Satellite-observed evidence

In this paper, five national meteorological stations in Anhui province are taken as typical examples to explore the effects of local urbanization on their thermal environment by using Landsat data from 1990 to 2010. Satellite-based land use/land cover(LULC), land surface temperature(LST), normalized difference vegetation index(NDVI) are used to investigate the effects. The study shows that LULC around meteorological stations changed significantly due to urban expansion. Fast urbanization is the main factor that affects the spatial-temporal distribution of thermal environment around meteorological stations. Moreover, the normalized LST and NDVI exhibit strong inverse correlations around meteorological stations, so the variability of LST can be monitored through evaluating the variability of NDVI. In addition, station-relocation plays an important role in improving representativeness of thermal environment. Notably, the environment representativeness was improved, but when using the data from the station to study climate change, the relocation-induced inhomogeneous data should be considered and adjusted. Consequently,controlling the scale and layout of the urban buildings and constructions around meteorological stations is an effective method to ameliorate observational thermal environment and to improve regional representativeness of station observation. The present work provides observational evidences that high resolution Landsat images can be used to evaluate the thermal environment of meteorological stations.

A Study on the Effects of the Surrounding Faults on Water Loss in the Zoige Wetland,China

The Zoige wetland is the biggest alpine wetland in the world,and an important water resource of the Yellow River.Due to natural and human factors,the Zoige wetland has been seriously degraded.Existing studies on the Zoige wetland mainly focus on the macro features of the wetland,while the influence of the surrounding faults on the Zoige wetland degradation is rarely studied.This study uses terrain data to analyze the cover change and the water loss caused by the Wqie-Seji fault based on the distributed hydrological model.The simulated water loss demonstrates that the Normalized Difference Vegetation Index(NDVI) is the most important factor for inducing water loss.The fault is also a factor that cannot be neglected,which has caused 33% of the wetland water loss.Therefore,it is of importance to study the influence of the fault on the wetland degradation.

Dynamic Monitoring of Soil Erosion for Upper Stream of Miyun Reservoir in the Last 30 Years

The Revised Universal Soil Loss Equation （RUSLE） was applied to assess the spatial distribution and dynamic properties of soil loss with geographic information system （GIS） and remote sensing （RS） technologies. To improve the accuracy of soil-erosion estimates, a new C-factor estimation model was developed based on land cover and time series normalized difference vegetation index （NDVI） datasets. The new C-factor was then applied in the RUSLE to integrate rainfall, soil, vegetation, and topography data of different periods, and thus monitor the distribution of soil erosion patterns and their dynamics during a 3o-year period of the upstream watershed of Miynn Reservoir （UWMR）, China. The results showed that the new C-factor estimation method, which considers land cover status and dynamics, and explicitly incorporates within-land cover variability, was more rational, quantitative, and reliable. An average annual soil loss in UWMR of 25.68, 21.04, and 16.8o t ha-1 a-1 was estimated for 1990, 2000 and 2010, respectively, corroborated by comparing spatial and temporal variation in sediment yield. Between 2000 and 2010, a 1.38% average annual increase was observed in the area of lands that lost less than 5 t ha-1 a^-1, while during 1990-2000 such lands only increased on average by o.46%. Areas that classified as severe, very severe and extremely severe accounted for 5.68% of the total UWMR in 2010, and primarily occurred in dry areas or grasslands of sloping fields. The reason for the change in rate of soil loss is explained by an increased appreciation of soil conservation by developers and planners. Moreover,we recommend that UWMR watershed adopt further conservation measures such as terraced plowing of dry land, afforestation, or grassland enclosures as part of a concerted effort to reduce on-going soil erosion.

More than Carbon Stocks:A Case Study of Ecosystem-based Benefits of REDD+ in Indonesia

During the 15th Conference of the Parties （COP 15）, Parties agreed that reducing emissions from deforesta- tion and forest degradation and enhancing ＇removals of greenhouse gas emission by forests＇ （REDD＋） in developing countries through positive incentives under the United Nations Framework Convention on Climate Change （UNFCCC） was capable of dealing with global emissions. As REDD＋ seeks to lower emissions by stopping deforestation and for- est degradation with an international payment tier according to baseline scenarios, opportunities for ecosystem benefits such as slowing habitat fragmentation, conservation of forest biodiversity, soil conservation may be also part of this effort. The primary objective of this study is to evaluate ecosystem-based benefits of REDD＋, and to identify the rela- tionships with carbon stock changes. To achieve this goal, high resolution satellite images are combined with Normal- ized Difference Vegetation Index （NDVI） to identify historical deforestation in study area of Central Kalimantan, In- donesia. The carbon emissions for the period of 2000-2005 and 2005-2009 are 2.73 ×10^5 t CO2 and 1.47× 10^6 t CO2 respectively, showing an increasing trend in recent years. Dring 2005-2009, number of patches （NP）, patch density （PD）, mean shape index distribution （SHAPE_MN） increased 30.8%, 30.7% and 7.6%. Meanwhile, largest patch index （LPI）, mean area （AREA MN）, area-weighted mean of shape index distribution （SHAPE_AM）, neighbor distance （ENN_MN） and interspersion and juxtaposition index （IJI） decreased by 55.3%, 29.7%, 15.8%, 53.4% and 21.5% re- spectively. The area regarding as positive correlation between carbon emissions and soil erosion was approximately 8.9 x l03 ha corresponding to 96.0% of the changing forest. These results support the view that there are strong syner- gies among carbon loss, forest fragmentation and soil erosion in tropical forests. Such mechanism of REDD＋ is likely to present opportunities for multiple benefits that fall outside the scope of carbon stocks.

Effects of Normalized Difference Vegetation Index and Related Wavebands′ Characteristics on Detecting Spatial Heterogeneity Using Variogram-based Analysis

Spatial heterogeneity is widely used in diverse applications, such as recognizing ecological process, guiding ecological restoration, managing land use, etc. Many researches have focused on the inherent scale multiplicity of spatial heterogeneity by using various environmental variables. How these variables affect their corresponding spatial heterogeneities, however, have received little attention. In this paper, we examined the effects of characteristics of normalized difference vegetation index （NDVI） and its related bands variable images, namely red and near infrared （NIR）, on their corresponding spatial heterogeneity detection based on variogram models. In a coastal wetland region, two groups of study sites with distinct fractal vegetation cover were tested and analyzed. The results show that： l） in high fractal vegetation cover （H-FVC） area, NDV! and NIR variables display a similar ability in detecting the spatial he- terogeneity caused by vegetation growing status structure; 2） in low fractal vegetation cover （L-FVC） area, the NIR and red variables outperform NDVI in the survey of soil spatial heterogeneity; and 3） generally, NIR variable is ubiquitously applicable for vegetation spatial heterogeneity investigation in different fractal vegetation covers. Moreover, as variable selection for remote sensing applications should fully take the characteristics of variables and the study object into account, the proposed variogram analysis method can make the variable selection objectively and scientifically, especially in studies related to spatial heterogeneity using remotely sensed data.

Variation of Thornthwaite Moisture Index in Hengduan Mountains, China

The Thornthwaite moisture index, an index of the supply of water （precipitation） in an area relative to the climatic demand for water （potential evapotranspiration）, was used to examine the spatial and temporal variation of drought and to verify the influence of environmental factors on the drought in the Hengduan Mountains, China. Results indicate that the Thornthwaite moisture index in the Hengduan Mountains had been increasing since 1960 with a rate of 0.1938/yr. Annual Thomthwaite moisture index in Hengduan Mountains was between -97.47 and 67.43 and the spatial heterogeneity was obvious in different seasons. Thomthwaite moisture index was high in the north and low in the south, and the monsoon rainfall had a significant impact on its spatial distribution. The tendency rate of Thomthwaite moisture index variation varied in different seasons, and the increasing trends in spring were greater than that in summer and autumn. However, the Thomthwaite moisture index decreased in winter. Thomthwaite moisture index increased greatly in the north and there was a small growth in the south of Hengduan Mountains. The increase of precipitation and decrease of evaporation lead to the increase of Thomthwaite moisture index. Thornthwaite moisture index has strong correlation with vegetation coverage. It can be seen that the correlation between Normalized Difference Vegetation Index （NDVI） and Thomthwaite moisture index was positive in spring and summer, but negative in autumn and winter. Correlation between Thornthwaite moisture index and relative soil relative moisture content was positive in spring, summer and autumn, but negative in winter. The typical mountainous terrain affect the distribu- tion of temperature, precipitation, wind speed and other meteorological factors in this region, and then affect the spatial distribution of Thomthwaite moisture index. The unique ridge-gorge terrain caused the continuity of water-heat distribution from the north to south, and the water-heat was stronger than that from the east to west part, and thus determined the spatial distribution of Thornthwaite mois- ture index. The drought in the Hengduan Mountains area is mainly due to the unstable South Asian monsoon rainfall time.

STUDY ON THE INTERACTION BETWEEN NDVI PROFILE AND THE GROWING STATUS OF CROPS

Daily and ten-day Normalized Difference Vegetation Index( NDVI) of crops were retrieved from meteorological satellite NOAA AVHRR images. The temporal variations of the NDVI were analyzed during the whole growing season, and thus the principle of the interaction between NDVI profile and the growing status of crops was discussed. As a case in point, the relationship between integral NDVI and winter wheat yield of Henan Province in 1999 had been analyzed. By putting integral NDVI values of 60 sample counties into the winter wheat yield-integral NDVI coordination, scattering map was plotted. It demonstrated that integral NDVI had a close relation with winter wheat yield. These relation could be described with linear, cubic polynomial, and exponential regression, and the cubic polynomial regression was the best way. In general, NDVI reflects growing status of green vegetation, so crop monitoring and crop yield estimation could be realized by using remote sensing technique on the basis of time serial NDVI data together with agriculture calendars.

Mapping Soil Salinity Using a Similarity-based Prediction Approach:A Case Study in Huanghe River Delta,China

Spatial distribution of soil salinity can be estimated based on its environmental factors because soil salinity is strongly affected and indicated by environmental factors. Different with other properties such as soil texture, soil salinity varies with short-term time. Thus, how to choose powerful environmental predictors is especially important for soil salinity. This paper presents a similarity-based prediction approach to map soil salinity and detects powerful environmental predictors for the Huanghe(Yellow) River Delta area in China. The similarity-based approach predicts the soil salinities of unsampled locations based on the environmental similarity between unsampled and sampled locations. A dataset of 92 points with salt data at depth of 30–40 cm was divided into two subsets for prediction and validation. Topographical parameters, soil textures, distances to irrigation channels and to the coastline, land surface temperature from Moderate Resolution Imaging Spectroradiometer(MODIS), Normalized Difference Vegetation Indices(NDVIs) and land surface reflectance data from Landsat Thematic Mapper(TM) imagery were generated. The similarity-based prediction approach was applied on several combinations of different environmental factors. Based on three evaluation indices including the correlation coefficient(CC) between observed and predicted values, the mean absolute error and the root mean squared error we found that elevation, distance to irrigation channels, soil texture, night land surface temperature, NDVI, and land surface reflectance Band 5 are the optimal combination for mapping soil salinity at the 30–40 cm depth in the study area(with a CC value of 0.69 and a root mean squared error value of 0.38). Our results indicated that the similarity-based prediction approach could be a vital alternative to other methods for mapping soil salinity, especially for area with limited observation data and could be used to monitor soil salinity distributions in the future.

Vegetation Dynamics and Its Relationship with Climatic Factors in the Changbai Mountain Natural Reserve

This study examined the temporal variation of the Normalized Difference Vegetation Index （NDVI） and its relationship with climatic factors in the Changbai Mountain Natural Reserve （CMNR） during 2000 - 2009. The results showed as follows. The average NDVI values increased at a rate of 0.0024 year-1. The increase rate differed with vegetation types, such as 0.0034 year-1 for forest and 0.0017 year-1 for tundra. Trend analyses revealed a consistent NDVI increase at the start and end of the growing season but little variation or decrease observed in July during the study period. The NDVI in CMNR showed a stronger correlation with temperature than with precipitation, especially in spring and autumn. A stronger correlation was observed between NDVI and temperature in the tundra zone （2,000-2,600m） than in the coniferous forest （1,100-1,700m） and Korean pine-broadleaved mixed forest （7oo-1,1oom） zones. The results indicate that vegetation at higher elevations is more sensitive to temperature change. NDVI variation had a strong correlation with temperature change （r=0.7311, p〈0.01） but less significant correlation with precipitation change. The result indicates that temperature can serve as a main indicator of vegetation sensitivity in the CMNR.

A Simple Method to Extract Tropical Monsoon Forests Using NDVI Based on MODIS Data:A Case Study in South Asia and Peninsula Southeast Asia

Distribution of monsoon forests is important for the research of carbon and water cycles in the tropical regions. In this paper, a simple approach is proposed to map monsoon forests using the Normalized Difference Vegetation lndex （NDVI） derived from the Moderate Resolution Imaging Spectroradiometer （MODIS） data. Owing to the high contrast of greenness between wet season and dry season, the monsoon forest can be easily discriminated from other forests by combining the maximum and minimum annual NDVI. The MODIS-based monsoon forest maps （MODMF） from 2000 to 2009 are derived and evaluated using the ground-truth dataset. The MODMF achieves an average producer accuracy of 80.0% and the Kappa statistic of 0.719. The variability of MODMF among different years is compared with that calculated from MODIS land cover products （MCD 12Q 1）. The results show that the coefficient of variation of total monsoon forest area in MODMF is 7.3%, which is far lower than that in MCD12Q1 with 24.3%. Moreover, the pixels in MODMv which can be identified for 7 to 9 times between 200l and 2009 account for 53.1%, while only 7.9% ofMCD12QI pixels have this frequency. Additionally, the monsoon forest areas estimated in MODMF, Global Land Cover 2000 （GLC2000）, MCDI2Q1 and University of Maryland （UMD） products are compared with the statistical dataset at national level, which reveals that MODMv has the highest R^2 of 0.95 and the lowest RMSE of 14 014 km^2. This algorithm is simple but reliable for mapping the monsoon forests without complex classification techniques.

Spatial-temporal Changes of Vegetation Cover in Guizhou Province, Southern China

Guizhou Province is an important karst area in the world and a fragile ecological area in China. Ecological risk assessment is very necessary to be conducted in this region. This study investigates different characteristics of the spatial-temporal changes of vegetation cover in Guizhou Province of Southern China using the data set of SPOT VEGETATION(1999–2015) at spatial resolution of 1-km and temporal resolution of 10-day. The coefficient of variation, the Theil-Sen median trend analysis, and the Mann-Kendall test are used to investigate the spatial-temporal change of vegetation cover and its future trend. Results show that: 1) the spatial distribution pattern of vegetation cover in Guizhou Plateau is high in the east whereas low in the west. The average annual normalized difference vegetation index(NDVI) from west to east is higher than that from south to north. 2) Average annual NDVI improved obviously in the past 17 years. The growth rate of average annual NDVI is 0.028/10 yr, which is slower than that of vegetation in the country(0.048/10 yr) from 1998 to 2007. Average annual NDVI in karst area is lower than that in non-karst area. However, the growing rate of average annual NDVI in karst area(0.030/10 yr) is faster than that in non-karst area(0.023/10 yr), indicating that vegetation coverage increases more rapidly in karst area. 3) Vegetation coverage in the study area is stable overall, but fluctuates in the local scales. 4) Vegetation coverage presents a continuous increasing trend. The Hurst exponent of NDVI in different vegetation types has an obvious threshold in various elevations. 5) The proportion of vegetation cover with sustainable increase is higher than that of vegetation cover with sustainable decrease. The improvement in vegetation cover may expand to most parts of the study area.