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1.
东亚土地覆盖对ENSO事件的响应特征   总被引:3,自引:0,他引:3  
香宝  刘纪远 《遥感学报》2003,7(4):316-320
对1982—1993年气候年际变化的强信号——ENSO进行了确认及再分类。以美国地质调查局EROS中心提供的AVHRR 8km NDVI为数据源,应用地理信息系统技术,计算了1982—1993年每年夏季(5—9月)NDVI平均影像。在此基础上用数据断面分析法对ENSO年东亚地区土地覆盖的空间分布进行了分析,再用主成分分析法对同一时间序列NDVI平均影像进行了运算,发现其第7主成分影像所反映的土地覆盖分布与数据断面分析法所反映的结果是一致的。对此,进一步分析了第7主成分的特征向量与代表ENSO变化特征的南方涛动指数(SOI)之间的关系,进而,对ENSO驱动下的东亚地区土地覆盖年际变化的空间分布特征进行了总结。  相似文献   

2.
香宝  刘纪远 《遥感学报》2003,7(3):316-320
对1982—1993年气候年际变化的强信号——ENSO进行了确认及再分类。以美国地质调查局EROS中心提供的AVHRR 8km NDVI为数据源,应用地理信息系统技术,计算了1982—1993年每年夏季(5—9月)NDVI平均影像。在此基础上用数据断面分析法对ENSO年东亚地区土地覆盖的空间分布进行了分析,再用主成分分析法对同一时间序列NDVI平均影像进行了运算,发现其第7主成分影像所反映的土地覆盖分布与数据断面分析法所反映的结果是一致的。对此,进一步分析了第7主成分的特征向量与代表ENSO变化特征的南方  相似文献   

3.
Erosion reduces soil productivity and causes negative downstream impacts. Erosion processes occur on areas with erodible soils and sloping terrain when high-intensity rainfall coincides with limited vegetation cover. Timing of erosion events has implications on the selection of satellite imagery, used to describe spatial patterns of protective vegetation cover. This study proposes a method for erosion risk mapping with multi-temporal and multi-resolution satellite data. The specific objectives of the study are: (1) to determine when during the year erosion risk is highest using coarse-resolution data, and (2) to assess the optimal timing of available medium-resolution images to spatially represent vegetation cover during the high erosion risk period. Analyses were performed for a 100-km2 pasture area in the Brazilian Cerrados. The first objective was studied by qualitatively comparing three-hourly TRMM rainfall estimates with MODIS NDVI time series for one full year (August 2002–August 2003). November and December were identified as the months with highest erosion risk. The second objective was examined with a time series of six available ASTER images acquired in the same year. Persistent cloud cover limited image acquisition during high erosion risk periods. For each ASTER image the NDVI was calculated and classified into five equally sized classes. Low NDVI was related to high erosion risk and vice versa. A DEM was used to set approximately flat zones to very low erosion risk. The six resulting risk maps were compared with erosion features, visually interpreted from a fine-resolution QuickBird image. Results from the October ASTER image gave highest accuracy (84%), showing that erosion risk mapping in the Brazilian Cerrados can best be performed with images acquired shortly before the first erosion events. The presented approach that uses coarse-resolution temporal data for determining erosion periods and medium-resolution data for effective erosion risk mapping is fast and straightforward. It shows good potential for successful application in other areas with high spatial and temporal variability of vegetation cover.  相似文献   

4.
The aim of this study is to use full spatial resolution Envisat MERIS data to drive an ecosystem productivity model for pine forests along the Mediterranean coast of Turkey. The Carnegie, Ames, Stanford Approach (CASA) terrestrial biogeochemical model, designed to simulate the terrestrial carbon cycle using satellite sensor and meteorological data, was used to estimate annual regional fluxes in terrestrial net primary productivity (NPP). At its core this model is based on light-use efficiency, influenced by temperature, rainfall and solar radiation. Present climate data was generated from 50 climate stations within the watershed using co-kriging. Regional scale pseudo-warming data for year 2070 were derived using a Regional Climate Model (RCM) these data were used to downscale the GCM General Circulation Model for the research area as part of an international research project called Impact of Climate Changes on Agricultural Production Systems in Arid Areas (ICCAP). Outputs of climate data can be moderated using the four variables of percent tree cover, land cover, soil texture and NDVI. This study employed 47 MERIS images recorded between March 2003 and September 2005 to derive percent tree cover, land cover and NDVI. Envisat MERIS data hold great potential for estimating NPP with the CASA model because of the appropriateness of both its spatial and its spectral resolution.  相似文献   

5.
An extensive land cover change was triggered by a series of typhoons, especially Typhoon Morakot in 2009 in Taiwan. The normalized difference vegetation index (NDVI) series from multiple satellite images were applied to monitor the change processes of land cover. This study applied spatiotemporal analysis tools, including empirical orthogonal functions (EOF), and multiple variograms in analyzing space–time NDVI data, and detected the effects of large chronological disturbances in the characteristics of land cover changes. Spatiotemporal analysis delineated the temporal patterns and spatial variability of NDVI caused by these large typhoons. Results showed that mean of NDVI decreased but spatial variablity of NDVI increased after typhoons in the study area. The EOF can clarify the major component of NDVI variations and identify the core area of the NDVI changes. Various approaches showed consistent results that Typhoon Morakot significantly lowered the NDVI in land cover change process. Furthermore, the spatiotemporal analysis is an effective monitoring tool, which advocates the use of the index for the quantification of land cover change and resilience.  相似文献   

6.
现有像元二分模型MODIS植被覆盖度模型因其形式简单、适用性较强的特点被广泛应用于区域植被覆盖度(FVC)的估算。然而,研究表明在沙漠和低植被覆盖的西部干旱区,从250 m的影像上很难精准地获取NDVIveg(全植被覆盖植被指数)和NDVIsoil(全裸土区植被指数)参数。利用常用的直方图累计法获取模型所需参数NDVIveg和NDVIsoil,估算结果存在普遍高估现象。为此,本文首先引入同期获取的GF-2号卫星数据,从GF-2号影像上提取植被覆盖像元;然后,利用Pixel Aggregate方法重采样至250 m分辨率,获取250 m空间分辨率下纯植被和纯裸土像元;最后,将纯植被和纯裸土像元各自空间位置相对应的MODIS NDVI数据最大值作为模型所需NDVIveg和NDVIsoil参数,实现研究区内植被覆盖度的估算。试验通过与线性回归法、多项式回归法和直方图累计像元二分模型法估算结果进行精度对比,结果表明:利用GF-2影像辅助的像元二分模型,精准地获取了低植被覆盖区NDVIveg和NDVIsoil模型参数,提高了干旱区植被覆盖度的估算精度,并有效地抑制了受稀疏植被影响NDVI在干旱区普遍偏高问题导致的FVC高估的现象。  相似文献   

7.
Multitemporal NOAA/AVHRR NDVI images and monthly temperature and precipitation data were obtained across Yangtze River basin covering the period 1981–2001. The spatial and temporal patterns of NDVI are the same, while spatial analysis shows that the NDVI is influenced by the vegetation types growing in the study regions, and NDVI presents an increasing trend during the study period in the whole basin. The climate indicators play an important role in the changes of vegetation cover in the river basin. In the two Indicators, temperature has a significant effect on the NDVI values than precipitation in the whole basin. However, in the 11 subbasins, the different rules are shown in different subbasins.  相似文献   

8.
Many remote sensing applications are predicated on the fact that there is a known relationship between climate and vegetation dynamics as monitored from space. However, few studies investigate vegetation index variation on individual homogeneous land cover units as they relate to specific climate and environmental influences at the local scale. This study focuses on the relationship between the Palmer Drought Severity Index (PDSI) and different vegetation types through the derivation of vegetation indices from Landsat 7 ETM+ data (NDVI, Tasseled Cap, and SAVI). A series of closely spaced through time images from 1999 to 2002 were selected, classified, and analyzed for an area in northeastern Ohio. Supervised classification of the images allowed us to monitor the response in individual land cover classes to changing climate conditions, and compare these individual changes to those over the entire larger areas. Specifically, the images were compared using linear regression techniques at various time lags to PDSI values for these areas collected by NOAA. Although NDVI is a robust indicator of vegetation greenness and vigor, it may not be the best index to use, depending on the type of vegetation studied and the scale of analysis used. A combination of NDVI and other prominent vegetation indices can be used to detect subtle drought conditions by specifically identifying various time lags between climate condition and vegetation response.  相似文献   

9.
1983—1992年中国陆地植被NDVI演变特征的变化矢量分析   总被引:32,自引:2,他引:32  
以NDVI时序资料为基本数据源,综合应用变化矢量分析和主成分分析方法对1983年至1992年中国陆地植被NDVI的变化强度、变化类型及空间结构变化特征进行了分析。研究结果表明在此期间中国陆地植被NDVI变化有以下特点:(1)十年间NDVI变化东西分异明显,东部变化幅度远大于西部。NDVI变化整体表现为稳中略增,增加区主要分布在台湾、福建、四川、河南等地;减少区主要分布在云南省和新疆北部等地。(2)空间结构信息表现了景观异质性,其变化主要发生在南方,反映了植被的生长和衰老过程及地形(山脉走向)变化。  相似文献   

10.
Species richness, or simply the number of species in a given area, is commonly used as an important indicator of biological diversity. Spatial variability in species richness has been postulated to depend upon environmental factors such as climate and climatic variability, which in turn may affect net primary productivity. The Advanced Very High Resolution Radiometer (AVHRR) derived Normalized Difference Vegetation Index (NDVI) has been shown to be correlated with climatic variables including rainfall, actual evapotranspiration and net primary productivity. To determine factors favoring high species richness, we examined the relationship between interannual NDVI variables and species richness of birds at a quarter degree scale (55 × 55 km). Results revealed a strong positive correlation between species richness and maximum average NDVI. Conversely, species richness showed negative correlation with standard deviation of maximum NDVI and the coefficient of variation. Though these relationships are indirect, they apparently operate through the green vegetation cover. Understanding such relationships can help in mapping and monitoring biological diversity, as well as in estimating changes in species richness in response to global climatic change.  相似文献   

11.
Expansion and heterogeneous clustering of commercial horticulture within the central highlands of Kenya after the mid-1990s impact watersheds and the sustainable resource management. This is distressing since climate conditions for world horticultural regions are projected to change, making such farming extremely difficult and costly to the environment. To understand the scope of impact on vegetation, the study evaluated (1) interannual variability in averaged normalized difference vegetation index (NDVI); (2) trends in average annual NDVI before and after 1990 – the presumed onset of rapid horticulture; and (3) relationship between the average annual NDVI and large-scale commercial farms, population density, and mean annual rainfall in subwatersheds. Time-series analysis of long-term Global Inventory Modeling and Mapping Studies NDVI data were analyzed as indicator of vegetation condition. NDVI trends before 1990s (1982–1989) and after 1990s (1990–2006) were evaluated to determine the slope (sign), and the Spearman’s correlation coefficient (strength). Overall, results show considerable variations in vegetation condition due largely to mixed factors including intensive farming activities, drought, and rainfall variation. Statistical analysis shows significant differences in slopes before 1990 and after 1990 (p < 0.05 and p < 0.1 respectively). Negative (decline) trends were common after 1990, linked to increased commercial horticulture and related anthropogenic disturbances on land cover. There was decline in vegetation over densely populated subwatersheds, though low NDVI values in 1984 and 2000 were the effect of severe droughts. Understanding the linkage between vegetation responses to the effects of human-induced pressure at the subwatershed scale can help natural resource managers approach conservation measures more effectively.  相似文献   

12.
中国陆地生态系统脆弱带遥感模型   总被引:4,自引:0,他引:4  
本研究通过对我国陆地生态系统8个典型样地的植被指数取样实验和图像计算结果发现,这8个样地植被指数随着水、热因子的季节变化,在时间和空间上具有一定的“绿波推移”和“景观更替”规律。在中国东部湿润的季风区(样地1-3),随着纬度的增高,其月平均植被指数与月平均气温有较大的相关。发现降水相对丰沛的地带,热量和光照条件的变化成为植被生长和变化的自然限制因子;而在中国北方森林-森林草原-典型昌原-荒漠草原-荒漠地带上,随着从东部(湿润地区)到西部(干旱地区)干湿条件的更替,月平均植被指数与降水多寡有较大的正相关关系。在8个样地上都呈现出共同的规律,即定向风的分布与植被指数的分布在时间和空间上具有逆相分布的“套合关系”。尤其在时间上有相逆套合关系,这正是中国北方沙尘暴和沙漠化加剧的自然原因。本研究定量地给出了我国陆地不同经纬度带生态系统脆弱季节和累积时间的分布。  相似文献   

13.
Detecting soil salinity changes and its impact on vegetation cover are necessary to understand the relationships between these changes in vegetation cover. This study aims to determine the changes in soil salinity and vegetation cover in Al Hassa Oasis over the past 28 years and investigates whether the salinity change causing the change in vegetation cover. Landsat time series data of years 1985, 2000 and 2013 were used to generate Normalized Difference Vegetation Index (NDVI) and Soil Salinity Index (SI) images, which were then used in image differencing to identify vegetation and salinity change/no-change for two periods. Soil salinity during 2000–2013 exhibits much higher increase compared to 1985–2000, while the vegetation cover declined to 6.31% for the same period. Additionally, highly significant (p < 0.0001) negative relationships found between the NDVI and SI differencing images, confirmed the potential long-term linkage between the changes in soil salinity and vegetation cover.  相似文献   

14.
The coarse resolution satellite data have been widely used for regional and global studies as they provide high temporal frequency. The information contained in the coarse resolution pixels are mostly mixture of several components. The extraction of information contained in a pixel find its role in Geosphere-Biosphere context. The present study address the utility of constrained least square model applied to coarse spatial resolution data from NOAA-AVHRR for generating fraction images of vegetation, soil and water/shade. The red and near-infrared channels have been used to run the constrained least square model to generate fraction images. The derived fraction images are related to normalised difference vegetation index (NDVI) for model validation. The results suggest that vegetation fraction components are strongly correlated with NDVI values (r2=0.98). The soil fractions (r2=?0.84) and water/shade fractions (42=?0.97) are negatively correlated with NDVI. The relationship between the fraction images and NDVI show the potential of the model in deriving sub-pixel component information using coarse resolution data.  相似文献   

15.
基于K-T变换的NDVI提取方法研究   总被引:1,自引:0,他引:1  
阐述了K-T变换的原理及其在植被信息提取方面的优点。将基于K-T变换提取的NDVI结果与直接在TM影像上提取的NDVI结果进行比较。实验结果表明,基于K-T变换的NDVI提取方法得到的结果图像纹理清晰、光谱保持能力强,对于区域植被覆盖信息提取,进而对生态环境变化、荒漠化等研究具有较重要的意义。  相似文献   

16.
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   

17.
Tropical forest mapping is one of the major environmental concerns at global and regional scales in which remote sensing techniques are firmly involved. This study examines the use of the variogram function to analyse forest cover fragmentation at different image scales. Two main aspects are considered here: (1) analysis of the spatial variability structure of the forest cover observed at three different scales using fine, medium and coarse spatial resolution images; and (2) the study of the relationship between rescaled images from the finest spatial resolution and those of the medium and coarse spatial resolutions. Both aspects are analysed using the variogram function as a basic tool to calculate and interpret the spatial variability of the forest cover. An example is presented for a Brazilian tropical forest zone using satellite images of different spatial resolutions acquired by Landsat TM (30 m), Resurs MSU (160 m) and ERS ATSR (1000 m). The results of this study contribute to establishing a suitable spatial resolution of remotely sensed data for tropical forest cover monitoring.  相似文献   

18.
基于遥感的长沙市城市热岛与土地利用/覆盖变化研究   总被引:9,自引:0,他引:9  
基于多时相Landsat TM/ETM+影像,首先计算长沙市地表亮度温度,然后利用NDVI(归一化植被指数)、MNDWI(改进 的归一化水体指数)、NDBI(归一化建筑指数)和NDBaI(归一化裸土指数)4个指数,采用决策树分类方法对长沙市影像进行 土地利用/覆盖分类。在此基础上,对长沙市城市热岛的空间分布特征、时空演变特征以及城市热岛与土地利用/覆盖变化和各种影 响因子之间的关系进行研究。结果表明,随着长沙市城区范围的不断扩张,城市热岛范围也不断增大; 土地利用/覆盖类型的变化 会改变地表温度的空间分布,城市用地和裸地是城市热岛强度的主要贡献因素,水体和林地具有较好的降温作用。地表温度与4种 归一化指数的回归分析表明,它们之间存在明显的相关性,不同土地利用/覆盖类型的地表温度存在较大差异。  相似文献   

19.
20.
多时相MODIS影像水田信息提取研究   总被引:5,自引:0,他引:5  
水稻种植及其分布信息是土地覆被变化、作物估产、甲烷排放、粮食安全和水资源管理分析的重要数据源。基于遥感的水田利用监测中,通常采用时序NDVI植被指数法和影像分类法分别进行AVHRR和TM影像的水田信息获取。针对8天合成MODIS陆地表面反射比数据的特点和水稻生长特征,选取水稻种植前的休耕期、秧苗移植期、秧苗生长期和成熟期等多时相MODIS地表反射率影像数据,通过归一化植被指数、增强植被指数及利用对土壤湿度和植被水分含量较敏感的短波红外波段计算得到的陆表水指数进行水田信息获取。将提取结果与基于ETM+影像的国土资源调查水田数据,通过网格化计算处理并进行对比分析,结果表明,利用MODIS影像的8天合成地表反射率数据,进行区域甚至全国的水田利用监测是可行的。  相似文献   

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