共查询到20条相似文献，搜索用时 15 毫秒
1.
《International Journal of Digital Earth》2013,6(5):439-455
Abstract The purpose of this paper is to develop Advanced Very High Resolution Radiometer (AVHRR) Global Inventory Modelling and Mapping Studies (GIMMS) Normalised Difference Vegetation Index (NDVI; AVHRR GIMMS NDVI for short) based fraction of absorbed photosynthetically active radiation (FPAR) from 1982 to 2006 and focus on their seasonal and spatial patterns analysis. The available relationship between FPAR and NDVI was used to calculate FPAR values from 1982 to 2006 and validated by Moderate-resolution Imaging Spectroradiometer (MODIS) FPAR product. Then, the seasonal dynamic patterns were analysed, as well as the driving force of climatic factors. Results showed that there was an agreement between FPAR values from this study and those of the MODIS product in seasonal dynamic, and the spatial patterns of FPAR vary with vegetation type distribution and seasonal cycles. The time series of average FPAR revealed a strong seasonal variation, regular periodic variations from January 1982 to December 2006, and opposite patterns between the Northern and Southern Hemispheres. Evergreen vegetation FPAR values were close to 0.7. A clear single-peak curve was observed between 30°N and 80°N – an area covered by deciduous vegetation. In the Southern Hemisphere, the time series fluctuations of FPAR averaged by 0.7° latitude zones were not clear compared to those in the Northern Hemisphere. A significant positive correlation (P<0.01) was observed between the seasonal variation of temperature and precipitation and FPAR over most other global meteorological sites. 相似文献
2.
针对不同的数据源及时间和空间尺度会使植被覆盖度及其与气象因子影响的结果有所差别这一情况,该文基于青藏高原1982-2012年GIMMS NDVI和2001-2013年MODIS NDVI遥感数据集,结合研究区内12个典型的气象站点数据,进行了青藏高原地区植被覆盖时空动态变化规律及其与气象因子响应的时序分析,并利用重合时间段的数据对比分析了两种传感器在青藏高原地区对植被动态变化监测方面的差异.结果表明:近30年来,青藏高原地区植被呈整体改善趋势,尤其是高海拔地区;不同阶段植被的变化趋势有所不同;两种传感器在反映植被动态变化趋势上差异显著,但两者与气候因子的响应规律相同. 相似文献
3.
Global warming associated with climate change is one of the greatest challenges of today’s world. Increasing emissions of the greenhouse gas CO2 are considered as a major contributing factor to global warming. One regulating factor of CO2 exchange between atmosphere and land surface is vegetation. Measurements of land cover changes in combination with modelling the Gross Primary Productivity (GPP) can contribute to determine important sources and sinks of CO2.The aim of this study is to accurately model the GPP for a region in West Africa with a spatial resolution of 250 m, and the differentiation of GPP based on woody and herbaceous vegetation. For this purpose, the Regional Biomass Model (RBM) was applied, which is based on a Light Use Efficiency (LUE) approach. The focus was on the spatial enhancement of the RBM from the original 1000–250 m spatial resolution (RBM+). The adaptation to the 250 m scale included the modification of two main input parameters: (1) the fraction of absorbed Photosynthetically Active Radiation (FPAR) based on the 1000 m MODIS MOD15A2 FPAR product which was downscaled to 250 m using MODIS NDVI time series; (2) the fractional cover of woody and herbaceous vegetation, which was improved by using a multi-scale approach. For validation and regional adjustments of GPP and the input parameters, in situ data from a climate station and eddy covariance measurements were integrated.The results of this approach show that the input parameters could be improved significantly: downscaling considerably reduces data gaps of the original FPAR product and the improved dataset differed less than 5.0% from the original data for cloud free regions. The RMSE of the fractional vegetation cover varied between 5.1 and 12.7%. Modelled GPP showed a slight overestimation in comparison to eddy covariance measurements. The in situ data was exceeded by 8.8% for 2005 and by 2.0% for 2006. The model results were converted to NPP and also agreed well with previous NPP measurements reported from different studies. Altogether a high accuracy and suitability of the regionally adjusted and downscaled model RBM+ can be concluded. The differentiation between vegetation growth forms allows a separation of long-term and short-term carbon storage based on woody and herbaceous vegetation, respectively. 相似文献
4.
Driven by various natural and anthropogenic factors, Poyang Lake, the largest freshwater lake in China, has experienced significant land use/cover changes in the past few decades. The aim of this study is to investigate the spatial–temporal patterns of abrupt changes and detect their potential drivers in Poyang Lake, using time-series Moderate Resolution Imaging Spectroradiometer (MODIS) 16-day maximum value composite vegetation indices between 2000 and 2012. The breaks for additive seasonal and trend (BFAST) method was applied to the smoothed time-series normalized difference vegetation index (NDVI), to detect the timing and magnitude of abrupt changes in the trend component. Large part of Poyang Lake (98.9% for trend component) has experienced abrupt changes in the past 13 years, and the change patterns, including the distributions in timing and magnitudes of major abrupt trend changes between water bodies and land areas were clearly differentiated. Most water bodies had abrupt increasing NDVI changes between 2010 and 2011, caused by the sequential severe flooding and drought in the two years. In contrast, large parts of the surrounding land areas had abrupt decreasing NDVI changes. Large decreasing changes occurred around 2003 at the city of Nanchang, which were driven by urbanization. These results revealed spatial–temporal land cover changing patterns and potential drivers in the wetland ecosystem of Poyang Lake. 相似文献
5.
Iraq contains the Great Mesopotamian alluvial plain of the Euphrates and Tigris rivers. Its regional vegetation phenological patterns are worthy of investigation because relatively little is known about the phenology of semi-arid environments, and because their inter-annual variation is expected to be driven by uncertain rainfall and varied topography. The aim of this research was to assess and map the spatial variation in key land surface phenology (LSP) parameters over the last decade and their relation with elevation. It is the first study mapping land surface phenology during last decade over the whole of Iraq, and one of only a few studies on vegetation phenology in a semi-arid environment. Time-series of Moderate Resolution Imaging Spectroradiometer (MODIS) normalised difference vegetation index (NDVI) data at 250 m spatial resolution and 8 day temporal resolution, were employed to map the spatial variation in three LSP parameters for the major vegetation types in Iraq during 2001–2012. LSP parameters were defined by inflection points after smoothing the vegetation phenological signals using the Fourier technique. The estimated key LSP parameters indicated that the relatively shorter length of season (LOS) in the north of Iraq resulted from a delayed start of season (SOS). Greater spatial variation occurred in the SOS than end of season (EOS), which may be due to the spatial distribution of rainfall and temperature as a function of elevation. A positive correlation was observed for SOS and EOS with elevation for all major land cover types with EOS producing the largest positive correlation (R2 = 0.685, R2 = 0.638 and R2 = 0.588, p < 0.05 in shrubland, cropland and grassland, respectively). The magnitude of delay in SOS and EOS increased in all land cover types along a rising elevation gradient where for each 500 m increase, SOS was delayed by around 25 or more days and EOS delayed by around 22 or more days, except for grassland. The SOS and EOS also varied temporally during the last decade, particularly the SOS in the lowland, north of the country where the standard deviation was around 80 to 120 days, due mainly to the practice of crop rotation and the traditional biennial cropping system. Thus, the results of this research emphasize the effect of elevation on key LSP parameters over Iraq, for all major vegetation types. 相似文献
6.
利用NOAA-AVHRR数据分析1982-2001年间中国植被的动态变化(英文) 总被引：1，自引：0，他引：1
The authors derived the normalized difference vegetation index (NDVI) from the NOAA/AVHRR Land dataset, at a spatial resolution of 8km and 15-day intervals, to investigate the vegetation variations in China during the period from 1982 to 2001. Then, GIS is used to examine the relationship between precipitation and the Normalized Difference Vegetation Index (NDVI) in China, and the value of NDVI is taken as a tool for drought monitoring. The results showed that in the study period, China’s vegetation cover h... 相似文献
7.
8.
Jixian Zhang Liu Zhengjun Sun Xiaoxia 《International Journal of Applied Earth Observation and Geoinformation》2009
The eco-environment in the Three Gorges Reservoir Area (TGRA) in China has received much attention due to the construction of the Three Gorges Hydropower Station. Land use/land cover changes (LUCC) are a major cause of ecological environmental changes. In this paper, the spatial landscape dynamics from 1978 to 2005 in this area are monitored and recent changes are analyzed, using the Landsat TM (MSS) images of 1978, 1988, 1995, 2000 and 2005. Vegetation cover fractions for a vegetation cover analysis are retrieved from MODIS/Terra imagery from 2000 to 2006, being the period before and after the rising water level of the reservoir. Several analytical indices have been used to analyze spatial and temporal changes. Results indicate that cropland, woodland, and grassland areas reduced continuously over the past 30 years, while river and built-up area increased by 2.79% and 4.45% from 2000 to 2005, respectively. The built-up area increased at the cost of decreased cropland, woodland and grassland. The vegetation cover fraction increased slightly. We conclude that significant changes in land use/land cover have occurred in the Three Gorges Reservoir Area. The main cause is a continuous economic and urban/rural development, followed by environmental management policies after construction of the Three Gorges Dam. 相似文献
9.
青藏高原地表冻融循环与植被返青期的变化趋势及其气候响应特征 总被引：1，自引：0，他引：1
青藏高原特殊的地理环境使其对全球气候变化十分敏感,所以研究其地表冻融循环和植被返青期的时空动态对于回顾和预测青藏高原对全球气候变化的响应具有重要意义。本文通过利用双指标地表冻融状态识别算法和被动微波亮温数据(SMMR、SSMI和SSMIS)来获取青藏高原长时间序列(1982年—2013年)逐日地表冻融状态,通过对GIMMS全球植被指数数据产品进行NDVI的滤波重建和返青期提取来获取青藏高原植被长时间序列(年份)的返青期;并且分析了地表冻融循环和植被返青期的变化趋势、相互关系及对青藏高原气候变化的响应特征。总体来看,在空间上,青藏高原的地表冻结集中发生在10月30日至次年4月2日,平均地表融化首日集中在5月12—27日,平均植被返青期集中在5月19—29日。植被返青期平均发生在地表融化首日后的3.94±5.58日,两者具有显著的相关关系(R=0.51,P=0.003)。青藏高原的地表融化首日和植被返青期在1982年—2013年间经历了推迟、提前再推迟的3个过程,融化时间和返青期在1982年—1987年分别以1.93±1.81 d/a和0.28±1.01 d/a的速度推迟;在1987年—2006年分别以0.67±0.20 d/a和0.13±0.16 d/a的速度提前;在2006年—2013年分别以0.97±0.84 d/a和1.04±0.52 d/a的速度推迟。中国气象局布设在青藏高原的CMA气象站的温度数据表明,高原的春季地表0 cm土壤温度呈持续上升的趋势,而植被返青期和地表融化首日并未持续提前,这可能是由几十年来高原不同地区降水等其他环境因素变化的差异造成。同时在气温持续升高期间,植被返青期的返青温度阈值也不断具有上升的趋势(R=0.72,P0.001),这可能与植被适应气候变化的自身调节能力有关。 相似文献
10.
The analysis and classification of land cover is one of the principal applications in terrestrial remote sensing. Due to the seasonal variability of different vegetation types and land surface characteristics, the ability to discriminate land cover types changes over time. Multi-temporal classification can help to improve the classification accuracies, but different constraints, such as financial restrictions or atmospheric conditions, may impede their application. The optimisation of image acquisition timing and frequencies can help to increase the effectiveness of the classification process. For this purpose, the Feature Importance (FI) measure of the state-of-the art machine learning method Random Forest was used to determine the optimal image acquisition periods for a general (Grassland, Forest, Water, Settlement, Peatland) and Grassland specific (Improved Grassland, Semi-Improved Grassland) land cover classification in central Ireland based on a 9-year time-series of MODIS Terra 16 day composite data (MOD13Q1). Feature Importances for each acquisition period of the Enhanced Vegetation Index (EVI) and Normalised Difference Vegetation Index (NDVI) were calculated for both classification scenarios. In the general land cover classification, the months December and January showed the highest, and July and August the lowest separability for both VIs over the entire nine-year period. This temporal separability was reflected in the classification accuracies, where the optimal choice of image dates outperformed the worst image date by 13% using NDVI and 5% using EVI on a mono-temporal analysis. With the addition of the next best image periods to the data input the classification accuracies converged quickly to their limit at around 8–10 images. The binary classification schemes, using two classes only, showed a stronger seasonal dependency with a higher intra-annual, but lower inter-annual variation. Nonetheless anomalous weather conditions, such as the cold winter of 2009/2010 can alter the temporal separability pattern significantly. Due to the extensive use of the NDVI for land cover discrimination, the findings of this study should be transferrable to data from other optical sensors with a higher spatial resolution. However, the high impact of outliers from the general climatic pattern highlights the limitation of spatial transferability to locations with different climatic and land cover conditions. The use of high-temporal, moderate resolution data such as MODIS in conjunction with machine-learning techniques proved to be a good base for the prediction of image acquisition timing for optimal land cover classification results. 相似文献
11.
The authors derived the normalized difference vegetation index (NDVI) from the NOAA/AVHRR Land dataset, at a spatial resolution of 8km and 15-day intervals, to investigate the vegetation variations in China during the period from 1982 to 2001. Then, GIS is used to examine the relationship between precipitation and the Normalized Difference Vegetation Index (NDVI) in China, and the value of NDVI is taken as a tool for drought monitoring. The results showed that in the study period, China’s vegetation cover had tended to increase, compared to the early 1980s; mean annual NDVI increased 3.8%. The agricultural regions (Henan, Hebei, Anhui and Shandong) and the west of China are marked by an increase, while the eastern coastal regions are marked by a decrease. The correlation between monthly NDVI and monthly precipitation/temperature in the period 1982 to 2001 is significantly positive (R2=0.80, R2=0.84); indicating the close coupling between climate conditions (precipitation and temperature) and land surface response patterns over China. Examination of NDVI time series reveals two periods: (1) 1982–1989, marked by low values below average NDVI and persistence of drought with a signature large-scale drought during the 1982 and 1989; and (2) 1990–2001, marked by a wetter trend with region-wide high values above average NDVI and a maximum level occurring in 1994 and 1998. 相似文献
12.
植被覆盖度与温度关系的MODIS高光谱研究 总被引：1，自引：0，他引：1
针对我国局部区域的植被覆盖度与气候变化研究仍然较少的现状,该文以四川盆地为例,利用MODIS高光谱数据,以植被覆盖度作为监测植被动态变化指标,根据皮尔逊相关系数分析植被覆盖度与气候的相关性,总结2003—2010年四川盆地植被覆盖度动态变化趋势,研究温度变化对植被覆盖度的影响。研究表明:植被覆盖度与温度为极强正相关,除地震等特殊情况,两者变化趋势相似,夏高冬低。 相似文献
13.
ABSTRACTFractional green vegetation cover (FVC) is a useful indicator for monitoring grassland status. Satellite imagery with coarse spatial but high temporal resolutions has been preferred to monitor seasonal and inter-annual FVC dynamics in wide geographic area such as Mongolian steppe. However, the coarse spatial resolution can cause a certain uncertainty in the satellite-based FVC estimation, which calls attention to develop a robust statistical test for the relationship between field FVC and satellite-derived vegetation indices. In the arid and semi-arid Mongolian steppe, nadir pointing digital camera images (DCI) were collected and used to produce a FVC dataset to support the evaluation of satellite-based FVC retrievals. An optimal DCI processing method was determined with respect to three color spaces (RGB, HIS, L*a*b*) and six green pixel classification algorithms, from which a country-wide dataset of DCI-FVC was produced and used for evaluating the accuracy of satellite-based FVC estimates from MODIS vegetation indices. We applied three empirical and three semi-empirical MODIS-FVC retrieval models. DCI data were collected from 96 sites across the Mongolian steppe from 2012 to 2014. The histogram algorithm using the hue (H) value of the HIS color space was the optimal DCI method (r2 = 0.94, percent root-mean-square-error (RMSE) = 7.1%). For MODIS-FVC retrievals, semi-empirical Baret model was the best-performing model with the highest r2 (0.69) and the lowest RMSE (49.7%), while the lowest MB (+1.1%) was found for the regression model with normalized difference vegetation index (NDVI). The high RMSE (>50% or so) is an issue requiring further enhancement of satellite-based FVC retrievals accounting for key plant and soil parameters relevant to the Mongolian steppe and for scale mismatch between sampling and MODIS data. 相似文献
14.
We use a linear unmixing approach to test how land use and forestry maps, in combination with the MODIS BRDF/albedo product, can be used to estimate land cover type albedos in boreal regions. Operational land use maps from three test areas in Finland and Canada were used to test the method. The resulting endmember albedo estimates had low standard errors of the mean and were realistic for the main land cover types. The estimated albedos were fairly consistent with albedo measurements conducted with a telescope mast and pure pixel albedos. Problems with the method are the possible errors in the land cover maps, lack of good quality winter MODIS albedo composites and the mismatch between the MODIS pixels and the true observation area. The results emphasize the role of tree species as determinant of forest albedo. Comprehensive spatial and temporal measurements of land cover albedo are usually not possible with in situ mast measurements, and the spatial resolution of MODIS albedo product is often too low to allow direct comparison of pixel albedos and land cover types in areas with heterogeneous vegetation. Hence, and since local forestry maps exist for most temperate and boreal regions, we believe that the proposed method will be useful in estimating average regional land cover type albedos as well as in tracking changes in them. 相似文献
15.
Yunqiao Shu Simon Stisen Karsten H. Jensen Inge Sandholt 《International Journal of Applied Earth Observation and Geoinformation》2011
Data from the first operational Chinese geostationary satellite Fengyun-2C (FY-2C) satellite are applied in combination with Moderate Resolution Imaging Spectroradiometer (MODIS) satellite products for the assessment of regional evapotranspiration over the North China Plain. The approach is based on the improved triangle method, where the temperature–vegetation index space includes thermal inertia. Two thermal infrared channels from FY-2C are used to estimate surface temperature (Ts) based on a split window algorithm originally proposed for the MSG-SEVIRI sensor. Subsequently the high temporal resolution of FY-2C data is exploited to give the morning rise in Ts. Combined with the 16 days composite MODIS vegetation indices product (MOD13) at a spatial resolution of 5 km, evaporative fraction (EF) is estimated by interpolation in the ΔTs–NDVI triangular-shaped scatter space. Finally, regional actual evapotranspiration (ET) is derived from the evaporative fraction and available energy estimated from MODIS surface albedo products MCD43. Spatial variations of estimated surface variables (Ts, EF and ET) corresponded well to land cover patterns and farmland management practices. Estimated ET and EF also compared well to lysimeter data collected for the period June 2005–September 2007. The improved triangle method was also applied to MODIS products for comparison. Estimates based on FY-2C products proved to provide slightly better results than those based on MODIS products. The consistency of the estimated spatial variation with other spatial data supports the use of FY-2C data for ET estimation using the improved triangle method. Of particular value is the high temporal frequency of image acquisitions from FY-2C which improves the likelihood of obtaining cloud free image acquisitions as compared to polar orbiting sensors like MODIS. 相似文献
16.
Currently there is a lack of knowledge on spatio-temporal patterns of land surface dynamics at medium spatial scale in southern Africa, even though this information is essential for better understanding of ecosystem response to climatic variability and human-induced land transformations. In this study, we analysed vegetation dynamics across a large area in southern Africa using the 14-years (2000–2013) of medium spatial resolution (250 m) MODIS-EVI time-series data. Specifically, we investigated temporal changes in the time series of key phenometrics including overall greenness, peak and timing of annual greenness over the monitoring period and study region. In order to specifically capture spatial and per pixel vegetation changes over time, we calculated trends in these phenometrics using a robust trend analysis method. The results showed that interannual vegetation dynamics followed precipitation patterns with clearly differentiated seasonality. The earliest peak greenness during 2000–2013 occurred at the end of January in the year 2000 and the latest peak greenness was observed at the mid of March in 2012. Specifically spatial patterns of long-term vegetation trends allowed mapping areas of (i) decrease or increase in overall greenness, (ii) decrease or increase of peak greenness, and (iii) shifts in timing of occurrence of peak greenness over the 14-year monitoring period. The observed vegetation decline in the study area was mainly attributed to human-induced factors. The obtained information is useful to guide selection of field sites for detailed vegetation studies and land rehabilitation interventions and serve as an input for a range of land surface models. 相似文献
17.
A remote sensing based land cover change assessment methodology is presented and applied to a case study of the Oil Sands Mining Development in Athabasca, Alta., Canada. The primary impact was assessed using an information extraction method applied to two LANDSAT scenes. The analysis based on derived land cover maps shows a decrease of natural vegetation in the study area (715,094 ha) for 2001 approximately −8.64% relative to 1992. Secondary assessment based on a key resources indicator (KRI), calculated using normalized difference vegetation index (NDVI measurements acquired by NOAA–AVHRR satellites), air temperature and global radiation was performed for a time period from 1990 to 2002. KRI trend analysis indicates a slightly decreasing trend in vegetation greenness in close proximity to the mining development. A good agreement between the time series of inter-annual variations in NDVI and air temperature is observed increasing the confidence of NDVI as an indicator for assessing vegetation productivity and its sensitivity to changes in local conditions. 相似文献
18.
Yonghong Zhang Ting Cao Xi Kan Jiangeng Wang Wei Tian 《Journal of the Indian Society of Remote Sensing》2017,45(5):887-897
The Qinghai-Tibetan Plateau (QTP) snow cover information acquisition of the high precision spatial and temporal characteristics is of great significance for the research on its land surface atmosphere coupled system and global climate change effects. The Moderate Resolution Imaging Spectro-radiometer (MODIS) daily snow cover products (MOD10A1 and MYD10A1) have been widely used in long time series of spatial and temporal variation analysis, but they are limited to be used because of high cloud cover ratio. In this paper, a 7-day rolling combination algorithm was presented to eliminate cloud obscuration, and the whole cloud amount falls below 7 %. The ground station in situ measurements verify that the overall precision is more than 90 %. The presented algorithm guaranteed the same spatial resolution and temporal resolution, and has higher precision than products MOD10A1 and MYD10A1. The MODIS 7-day rolling combination snow cover datasets products were obtained between 2003 and 2014 in the QTP, and the snow cover area of spatial and temporal variation was analyzed. The change characteristics of snow cover duration was also studied combining with the Digital Elevation Model data. Results show that the snow cover area of the whole QTP has a slowly decreased trend, but increases in autumn. Thus, the snow cover proportion of annual periodic and unstable in different elevations has the highest correlation with area of the elevation. 相似文献
19.
Optical Earth Observation data with moderate spatial resolutions, typically MODIS (Moderate Resolution Imaging Spectroradiometer), are of particular value to environmental applications due to their high temporal and spectral resolutions. Time-series of MODIS data capture dynamic phenomena of vegetation and its environment, and are considered as one of the most effective data sources for land cover mapping at a regional and national level. However, the time-series, multiple bands and their derivations such as NDVI constitute a large volume of data that poses a significant challenge for automated mapping of land cover while optimally utilizing the information it contains. In this study, time-series of 10-day cloud-free MODIS composites and its derivatives – NDVI and vegetation phenology information, are fully assessed to determine the optimal data sets for deriving land cover. Three groups of variable combinations of MODIS spectral information and its derived metrics are thoroughly explored to identify the optimal combinations for land cover identification using a data mining tool.The results, based on the assessment using time-series of MODIS data, show that in general using a longer time period of the time-series data and more spectral bands could lead to more accurate land cover identification than that of a shorter period of the time-series and fewer bands. However, we reveal that, with some optimal variable combinations of few bands and a shorter period of time-series data, the highest possible accuracy of land cover classification can be achieved. 相似文献
20.
The fraction of absorbed photosynthetically active radiation (FAPAR) is a key variable in productivity and carbon cycle models. The variety of available FAPAR satellite products from different space agencies leads to the necessity of assessing the existing differences between them before using into models. Discrepancies of four FAPAR products derived from MODIS, SEVIRI and MERIS (TOAVEG and MGVI algorithms), covering the Iberian Peninsula from July 2006 to June 2007 are here analyzed. The assessment is based on an intercomparison involving the spatial and temporal consistency between products and a statistical analysis across land cover types. In general, significant differences are found over the Iberian Peninsula concentrated on the temporal variation and absolute values. The MODIS and MERIS/MGVI FAPAR products clearly show the highest and lowest absolute values, respectively, along with the lowest intra-annual variation. When considering individual land cover types, the largest FAPAR disagreements among the analyzed products were found between MODIS-MERI/MGVI and MERIS/TOAVEG-MERIS/MGVI over broadleaf and needleaf forests, with discrepancies quantified by RMSE higher than 0.30 and absolute bias higher than 0.25. These discrepancies can lead to relative gross primary production differences up to 65%. 相似文献