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1.
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.  相似文献   

2.
准确认识三江源植被生产力月度尺度的时空格局变化,对三江源畜牧业生产以及生态保护政策制定具有重要意义,可稳定获取的重访周期为4 d的16 m分辨率GF-1/WFV数据使中等空间分辨率的月度NPP产品生产成为可能。本文建立了一套以GF-1/WFV为基本数据源的中等空间分辨率草地月度NPP估算技术方法,并评估了其在三江源地区应用的可行性。在黄河源区玛多县的实验表明以GF-1/WFV为基础,以MODIS13Q1数据为补充,可以获得覆盖全区的中等空间分辨率月度NDVI数据,据其反演得到的草地NPP,地面验证精度在70%以上,优于MODIS NPP产品精度,且能更为详细地反映草地生产力变化的空间差异,在青海三江源地区利用GF-1/WFV数据生产中等空间分辨率的草地月度NPP产品是可行的。  相似文献   

3.
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 (700-1,100m) 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.  相似文献   

4.
The normalized difference vegetation index(NDVI) is one of the key input variables for developing drought indices.However,the NDVI quickly saturates in high vegetation surfaces,and thus,the generalization of a drought index over different ecosystems becomes a challenge.This paper presents a novel,dynamic stretching algorithm to overcome the saturation effect in NDVI.A scaling transformation function to eliminate saturation effects when the vegetation fraction(VF) is large is proposed.Dynamic range adjustment is conducted using three coefficients,namely,the normalization factor(a),the stretching range controlling factor(m),and the stretching size controlling factor(e).The results show that the stretched NDVI(S-NDVI) is more sensitive to vegetation fraction than NDVI when the VF is large,ranging from 0.75 to 1.00.Moreover,the saturation effect in NDVI is effectively removed by using the S-NDVI.Further analysis suggests that there is a good linear correlation between the S-NDVI and the leaf area index(LAI).At the same time,the proposed S-NDVI significantly reduces or even eliminates the saturation effect over high biomass.A comparative analysis is performed between drought indices derived from NDVI and S-NDVI,respectively.In the experiment,reflectance data from the moderate resolution imaging spectroradiometer(MODIS) products and in-situ observation data from the meteorological sites at a regional scale are used.In this study,the coefficient of determination(R2) of the stretched drought index(S-DI) is above 0.5,indicating the reliability of the proposed algorithm with surface soil moisture content.Thus,the S-DI is suggested to be used as a drought index in extended regions,thus regional heterogeneity should be taken into account when applying stretching method.  相似文献   

5.
干旱区植被覆盖度提取模型的建立   总被引:26,自引:1,他引:25  
本文通过分析遥感提取植被覆盖度的经验模型法、植被指数法和混合像元分解法,归纳了它们各自的优势、精度和存在的问题,指出了影响应用较广泛的植被指数转换法精度是全植被覆盖像元的选取。在此基础上提出了植被指数转换法的改进模型一利用高分辨率卫星图像的最大NDVI值作为均一像元的NDVI值替换中等分辨率卫星图像的NDVI值,建立植被覆盖度提取模型,从而通过中等分辨率卫星图像获取大范围植被覆盖度的方法。经实践检验,该方法简单、实用,适合于利用中等分辨率卫星图像进行大范围宏观监测。  相似文献   

6.
1 Introduction Vegetation is an important component of terrestrial eco- system, it plays an important role in global matter and energy cycle, carbon balance and climate change. CO2 has effects on global warming, photosynthesis function, Net Primary Productivity (NPP) and earth environmental condition. NPP is one of the important biophysical variables of vegetation activity, and is a beginning link of biogeochemical carbon cycle. Vegetation absorbs CO2 from atmosphere through photosynthesi…  相似文献   

7.
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 30-year period of the upstream watershed of Miyun 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 16.80 t ha-1a-1was 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-1a-1,while during 1990-2000 such lands only increased on average by 0.46%.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.  相似文献   

8.
Vegetation is the main component of the terrestrial ecosystem and plays a key role in global climate change. Remotely sensed vegetation indices are widely used to detect vegetation trends at large scales. To understand the trends of vegetation cover, this research examined the spatial-temporal trends of global vegetation by employing the normalized difference vegetation index(NDVI) from the Advanced Very High Resolution Radiometer(AVHRR) Global Inventory Modeling and Mapping Studies(GIMMS) time series(1982–2015). Ten samples were selected to test the temporal trend of NDVI, and the results show that in arid and semi-arid regions, NDVI showed a deceasing trend, while it showed a growing trend in other regions. Mann-Kendal(MK) trend test results indicate that 83.37% of NDVI pixels exhibited positive trends and that only 16.63% showed negative trends(P 0.05) during the period from 1982 to 2015. The increasing NDVI trends primarily occurred in tree-covered regions because of forest growth and re-growth and also because of vegetation succession after a forest disturbance. The increasing trend of the NDVI in cropland regions was primarily because of the increasing cropland area and the improvement in planting techniques. This research describes the spatial vegetation trends at a global scale over the past 30+ years, especially for different land cover types.  相似文献   

9.
The fraction of photosynthetically active radiation(FPAR) is a key variable in the assessment of vegetation productivity and land ecosystem carbon cycles.Based on ground-measured corn hyperspectral reflectance and FPAR data over Northeast China,the correlations between corn-canopy FPAR and hyperspectral reflectance were analyzed,and the FPAR estimation performances using vegetation index(VI) and neural network(NN) methods with different two-band-combination hyperspectral reflectance were investigated.The results indicated that the corncanopy FPAR retained almost a constant value in an entire day.The negative correlations between FPAR and visible and shortwave infrared reflectance(SWIR) bands are stronger than the positive correlations between FPAR and near-infrared band reflectance(NIR).For the six VIs,the normalized difference vegetation index(NDVI) and simple ratio(SR) performed best for estimating corn FPAR(the maximum R2 of 0.8849 and 0.8852,respectively).However,the NN method esti-mated results(the maximum R2 is 0.9417) were obviously better than all of the VIs.For NN method,the two-band combinations showing the best corn FPAR estimation performances were from the NIR and visible bands;for VIs,however,they were from the SWIR and NIR bands.As for both the methods,the SWIR band performed exceptionally well for corn FPAR estimation.This may be attributable to the fact that the reflectance of the SWIR band were strongly controlled by leaf water content,which is a key component of corn photosynthesis and greatly affects the absorption of photosynthetically active radiation(APAR),and makes further impact on corn-canopy FPAR.  相似文献   

10.
中国西北地区植被NDVI的时空变化及其影响因子分析   总被引:6,自引:0,他引:6  
利用GIMMS/NDVI数据分析了中国西北地区1982-2006年植被NDVI时空变化特征及其影响因子。近25年来,中国西北地区年均植被NDVI增速为0.5%/10a,并存在明显的空间差异。天山、阿尔泰山、祁连山、青海的中东部等地区植被NDVI显著增加;青海南部地区、陕西和宁夏交界地区、甘肃部分地区,以及新疆部分地区的植被NDVI下降。从不同植被类型看:林地、草地和耕地的年均NDVI都在提高。研究表明:中国西北地区植被NDVI变化是各种自然和人为因素综合作用的结果。植被NDVI与气温、降水的年际变化整体上都呈弱的正相关。但与其年内变化则都呈显著的线性关系,当月均温量超过20℃时,植被NDVI呈下降趋势;当月降水量在0100mm期间,植被NDVI随降水线性增长,当月降水量超过100mm之后,不再有明显的增长趋势。农业生产水平提高和植被生态建设等人类活动对西北地区植被NDVI增加有重要影响。  相似文献   

11.
DisTrad(Disaggregation procedure for radiometric surface temperature)模型是常用于遥感地表温度空间分辨率提升的主要模型之一。DisTrad模型常面向空间范围有限、地形相对平坦的研究区域,且常选用植被参数(如植被指数或植被覆盖度等)作为关键参数。然而在空间范围较大、地形起伏地区,地表温度的空间变异可能无法完全通过植被参数解释。本研究选取四川盆地及毗邻地区为研究区,通过模拟数据研究DisTrad模型在地形起伏区地表温度空间分辨率提升中的适用性。数字高程模型(Digital Elevation Model,DEM)、归一化差值植被指数(Normalized Difference Vegetation Index,NDVI)等参数,采用滑动窗口逐步回归,将空间分辨率为6km的地表温度提升至空间分辨率为1km。研究结果表明,改进的模型在平原及海拔较低的高原地区提升获得的地表温度空间分辨率具有较高精度,均方根误差(Root Mean Square Error,RMSE)为0.5K左右;在地形起伏较大的地区,RMSE为4K,验证了改进的模型提升的可行性。  相似文献   

12.
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.  相似文献   

13.
中国北方草原区生产力在区域碳水循环、农牧业发展中举足轻重。归一化植被指数(Normalized Difference Vegetation Index,NDVI)广泛应用于生产力的计算,然而目前来源众多的NDVI数据反映中国北方草原植被时空动态的一致性仍未可知。本研究利用2000—2015年3个来源NDVI数据集(MODIS NDVI、GIMMS NDVI和SPOT NDVI)并以国际上公认的数据准确性较高的MODIS NDVI为基准对比分析了中国北方草原区NDVI时空动态的一致性,并选取适宜的NDVI产品揭示研究区NDVI长期的时空格局。结果表明:整个中国北方草原区以及部分草原类型(高寒草甸、高寒草原、高寒荒漠、温带荒漠草原)GIMMS NDVI和MODIS NDVI 2套数据集无论是数值范围,还是年际波动和变化趋势具有较高一致性(二者在高寒草甸、高寒草原、高寒荒漠、温带荒漠草原的相关系数分别为0.60、0.47、0.51、0.74),而SPOT NDVI数值远高于其他2个数据集,尤其是在青藏高原草原区,SPOT NDVI数值每年较另外两套数据集约偏高0.15,表明该区域使用SPOT数据应慎重。部分温带草原类型(典型草原和草甸草原)GIMMS NDVI和SPOT NDVI数据集在年际波动以及变化趋势上具有较高的一致性(相关系数分别为0.85和0.60),但温带草原区3种数据集NDVI数值范围整体相差不大,小于0.06。基于上述结果,本研究进一步采用时间序列最长且与MODIS NDVI一致性最好的GIMMS NDVI分析了研究区NDVI的时空动态,发现1982—2015年中国北方草原区NDVI整体呈增加趋势,25%的区域达显著水平(p<0.05),主要集中在温带草原区;高寒草原区NDVI大部分区域变化不显著且有一定比例的区域NDVI呈显著下降趋势。本研究可以为模型数据集选择和预测中国北方草原区植被对未来气候变化的响应提供科学依据。  相似文献   

14.
Daily and ten-day Normalized Difference Vegetation Index(NDVI) of crops were retrieved from meteorological statellite NOAA AVHRR images ,The temporal variations of the NDVI were analyzed during the whole growing season,and thus the principle of the interaction between NDIV 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.  相似文献   

15.
近十几年来,随着城市化进程加剧,准确获取城市植被的分布信息,是城市气候和地表能量平衡研究的重要内容。高空间分辨率遥感影像数据,为精确获取和动态监测城市植被提供了重要资料。本研究利用资源三号数据对长江三角洲地区城市植被进行光谱特征分析与提取,提出一种城市植被的自动化信息提取算法—分离面法(Hyperplanes for Plant Extraction Methodology,HPEM)。结果表明:在假彩色反射率空间,植被与NDVI值低的背景有很好的分离性,而在真彩色反射率空间,植被与NDVI值高的背景有很好的分离性;HPEM能很好地避免NDVI最佳阈值法中将建筑物误分为植被的问题,其精度明显优于NDVI最佳阈值法,Kappa系数从0.85提高到0.90,总的错分与漏分误差从21.15%降低到14.18%。可见,本文的HPEM方法能有效提高城市植被信息自动提取的精度。  相似文献   

16.
In this study,the Surface Energy Balance Algorithms for Land(SEBAL) model and Moderate Resolution Imaging Spectroradiometer(MODIS) products from Terra satellite were combined with meteorological data to estimate evapotranspiration(ET) over the Sanjiang Plain,Northeast China.Land cover/land use was classified by using a recursive partitioning and regression tree with MODIS Normalized Difference Vegetation Index(NDVI) time series data,which were reconstructed based on the Savitzky-Golay filtering approach.The MODIS product Quality Assessment Science Data Sets(QA-SDS) was analyzed and all scenes with valid data covering more than 75% of the Sanjiang Plain were selected for the SEBAL modeling.This provided 12 overpasses during 184-day growing season from May 1st to October 31st,2006.Daily ET estimated by the SEBAL model was misestimaed at the range of-11.29% to 27.57% compared with that measured by Eddy Covariance system(10.52% on average).The validation results show that seasonal ET from the SEBAL model is comparable to that from ground observation within 8.86% of deviation.Our results reveal that the time series daily ET of different land cover/use increases from vegetation on-going until June or July and then decreases as vegetation senesced.Seasonal ET is lower in dry farmland(average(Ave):491 mm) and paddy field(Ave:522 mm) and increases in wetlands to more than 586 mm.As expected,higher seasonal ET values are observed for the Xingkai Lake in the southeastern part of the Sanjiang Plain(Ave:823 mm),broadleaf forest(Ave:666 mm) and mixed wood(Ave:622 mm) in the southern/western Sanjiang Plain.The ET estimation with SEBAL using MODIS products can provide decision support for operational water management issues.  相似文献   

17.
各类光学植被指数已成功地应用于各种植被监测与作物产量估算中,但这些指数易受大气状况的影响。由星载微波辐射计得到的植被光学厚度数据(VOD)与植被密度、含水量密切相关,数据可全天候获得,在农业遥感监测中呈现着巨大的潜力。作为来自不同传感器的遥感数据,微波遥感数据与光学遥感数据可以提供不同波长范围内的植被信息。为了更准确地进行作物产量估算,本研究提出将微波遥感数据与光学遥感数据共同应用于冬小麦单产估算中。研究选择L波段微波辐射计SMAP卫星的VOD数据与MODIS的标准归一化植被指数NDVI、增强型植被指数EVI、叶面积指数LAI、光合有效辐射分量FPAR数据作为研究变量,分别使用BP神经网络、GA-BP神经网络和PSO-BP神经网络建立冬小麦产量估算模型。结果表明: 3种神经网络回归模型的P值均小于0.001,通过了显著性检验。GA-BP神经网络回归模型的估算值与真实值在3种神经网络回归模型中表现了最高的相关性(R=0.755)与最低的均方根误差(RMSE=529.145 kg/hm2),平均绝对误差(MAE=425.168 kg/hm2)和平均相对误差(MRE=6.530%)。为了分析多源遥感数据的结合在作物产量估算中的优势,研究同时构建了仅使用NDVI和LAI,使用NDVI、EVI、LAI、FPAR等光学数据进行冬小麦产量估算的3种GA-BP神经网络回归模型作为对比。结果表明,使用微波遥感数据与光学遥感数建立的GA-BP神经网络回归模型较上述3种作为对比的GA-BP神经网络回归模型的相关系数R值分别提高了0.163,0.229与0.056,均方根误差RMSE分别降低了122.334、158.462和46.923 kg/hm2,使用多源遥感数据的组合可以很好地提高作物产量估算的准确性。  相似文献   

18.
Estimation of evapotranspiration(ET) for mountain ecosystem is of absolute importance since it serves as an important component in balancing the hydrologic cycle.The present study evaluates the performance of original and location specific calibrated Hargreaves equation(HARG) with the estimates of Food and Agricultural Organization(FAO)Penman Monteith(PM) method for higher altitudes in East Sikkim,India.The results show that the uncalibrated HARG model underestimates ET_0 by 0.35 mm day~(-1) whereas the results are significantly improved by regional calibration of the model.In addition,this paper also presents the variability in the trajectory associated with the climatic variables with the changing climate in the study site.Nonparametric Mann-Kendall(MK) test was used to investigate and understand the mean monthly trendof eight climatic parameters including reference evapotranspiration(ET_0) for the period of 1985-2009.Trend of ET_0 was estimated for the calculations done by FAO PM equation.The outcomes of the trend analysis show significant increasing(p ≤ 0.05) trend represented by higher Z-values,through MK test,for net radiation(Rn),maximum temperature(Tmax) and minimum temperature(Tmin),especially in the first months of the year.Whereas,significant(0.01 ≥ p ≤0.05) decreasing trend in vapor pressure deficit(VPD)and precipitation(P) is observed throughout the year.Declining trend in sunshine duration,VPD and ET_0 is found in spring(March- May) and monsoon(June –November) season.The result displays significant(0.01≤ p ≤ 0.05) decreasing ET_0 trend between(June- December) except in July,exhibiting the positive relation with VPD followed by sunshine duration at the station.Overall,the study emphasizes the importance of trend analysis of ET_0 and other climaticvariables for efficient planning and managing the agricultural practices,in identifying the changes in the meteorological parameters and to accurately assess the hydrologic water balance of the hilly regions.  相似文献   

19.
In this paper,an updated vegetation map of the permafrost zone in the Qinghai-Tibet Plateau(QTP) was delineated.The vegetation map model was extracted from vegetation sampling with remote sensing(RS) datasets by decision tree method.The spatial resolution of the map is 1 km×1 km,and in it the alpine swamp meadow is firstly distinguished in the high-altitude areas.The results showed that the total vegetated area in the permafrost zone of the QTP is 1,201,751 km~2.In the vegetated region,50,260 km~2 is the areas of alpine swamp meadow,583,909 km~2 for alpine meadow,332,754 km~2 for alpine steppe,and 234,828 km~2 for alpine desert.This updated vegetation map in permafrost zone of QTP could provide more details about the distribution of alpine vegetation types for studying the vegetation mechanisms in the land surface processes of highaltitude areas.  相似文献   

20.
1982-2006年加纳植被覆盖时空变化及其气候影响   总被引:1,自引:0,他引:1  
非洲陆地生态系统是气候变化的高敏感区,研究该区域植被覆盖变化及其控制因素,对深刻认识气候变化的影响具有重要意义。本文利用1982-2006年植被指数(NDVI)数据,研究位于非洲西部热带地区的加纳共和国植被覆盖的时空变化特征,结合同期的气温和降水量数据,分析其植被活动对气候变化的响应特征。研究结果表明,加纳86.4%的植被覆盖区NDVI在25 a间都呈现不同程度的增加趋势。20世纪80年代初和21世纪初这2个时期,NDVI值大于0.4的面积百分比呈增加趋势;NDVI值大于0.5的面积百分比从26%增加到38.2%;NDVI值在0.4-0.5之间的面积百分比从47.5%增加到51.9%。NDVI受降水量控制的区域占总区域面积的57.2%,而受气温控制的面积占总区域面积的42.8%。总的来看,加纳植被覆盖对降水量变化的敏感程度强于气温变化。  相似文献   

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