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MODIS NDVI和AVHRR NDVI 对草原植被变化监测差异 总被引：5，自引：0，他引：5
以草地作为研究载体,对比分析草原植被AVHRR NDVI和MODIS NDVI两种NDVI序列的年内、年际变化特征,讨论两种NDVI序列对降水量、平均气温和水汽压3种气候因子的响应差异,为合理选择NDVI序列对植被进行监测研究提供参考。结果表明：(1)两种NDVI序列所反映的草原植被年内变化趋势相似,但MODIS NDVI对各类草原的区分度优于AVHRR NDVI;(2)两种NDVI序列所反映的2000年—2003年草原植被年际变化差异明显。较之于MODIS NDVI,AVHRR NDVI变化趋势分类图表现出更强的植被改善趋势,植被改善面积在AVHRR NDVI变化趋势分类图中占94.25%,在MODIS NDVI中为83.33%;两种NDVI变化趋势分类图反映的植被变化趋势吻合度为52.88%。(3)两种NDVI序列与水汽压、降水量相关性差异显著。MODIS NDVI与各站点平均气温的相关系数均大于GIMMS NDVI;而MODIS NDVI与水汽压的相关系数83%(10个站点)小于GIMMS NDVI,与降水量的相关系数67%(8个站点)小于GIMMS NDVI。 相似文献
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三峡库区近30年土地利用时空变化特征分析 总被引：6，自引：0，他引：6
利用三峡库区1975年、1987年、1995年、2000年和2005年的遥感影像数据,提取各期土地利用图。以各期土地利用图为基础图件,利用G IS技术,分析了三峡库区各期土地利用类型的数量、空间分布及变化趋势,分析表明库区的耕地、林地和草地都在减少,库区近30年建设用地和河流水面的增加最为明显。同时引入土地利用变化的景观特征指数、土地利用变化速度、土地利用程度指数来总结三峡库区近30年来土地利用变化的主要时空变化特征。采用多种特征指数相结合的研究方法,有利于了解三峡库区土地利用变化的特征,可以进一步指导库区的土地利用规划,为库区的生态环境保护提供参考。 相似文献
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本文利用2002年陕西省ETM卫星影像及相关植被地理信息,在其影像上选取覆盖全省包含不同地物类型的85个地面样地(Ground Truth),通过2003年陕西省MODIS卫星影像获取所选样地全年的NDVI时间序列曲线。采用决策树分类方法,结合NDVI时间序列曲线,实现基于时相和波谱信息的植被分类。最后通过混淆矩阵与Kappa系数等方法对分类结果进行正确率评价,结果表明,文中所给方法优于传统分类方法,所得结果与其他调查结果相一致。 相似文献
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基于傅立叶变换的混合分类模型用于NDVI时序影像分析 总被引：4，自引：0，他引：4
应用2004年MODIS的时序NDVI数据，在分析湖北省不同地物类型的NDVI曲线季节性变化特征的基础上，设置对应的阈值，先后将水体、居民地与其他地物类型分离开。将去除了水体和居民地影响的剩余的NDVI序列影像傅立叶变换的1／12频率分量引入到地表覆盖分类的特征空间中，与其最大值影像和平均值影像组合，经过归一量化处理后合成一个类似具有三波段的卫星影像。在合成后的影像上利用最大似然法对其他地类进行分类。研究表明，引入傅立叶变换的特殊频率分量是分析多时相MODIS数据及提取地表植被覆盖信息的有效工具。 相似文献
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基于MODIS-NDVI的内蒙古植被变化遥感监测 总被引：2，自引：0，他引：2
本文利用2002-2006年5-8月的MODIS 1B数据,建立NDVI时间序列,并结合气象数据中的月均温、月降水量、滞后1月和滞后2月累计降水量对内蒙古地区植被生长季NDVI的月际、年际变化规律以及NDVI变化同气候因子的相关性进行了分析。结果表明:月际变化上,5-8月NDVI不断增加,NDVI变化率5-6月>6-7月>7-8月;年际变化上,2002-2006年间,草地的波动性最大;在与气候因子的相关性上:滞后2月降水>滞后1月降水>月均温>月降水量;对于林地和草地来说,各种相关系数高纬高于低纬,对于农耕地来说各种相关系数基本相当;对于沙地来说,各种相关系数均不高,这与其植被稀少且几乎无变化有关。 相似文献
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针对在人类活动影响下,泰山地区植被覆盖面积变化情况,以陆地卫星(Landsat TM/OLI)遥感影像为研究基础影像,采用遥感图像处理平台(ENVI)和ArcGIS软件,对泰山地区1985、1995、2003、2008、2013、2018年的6期遥感影像,通过归一化指数(NDVI)对遥感影像植被信息进行反演,通过地形因子提取实现对高程、坡度、坡向信息的提取与绿色植物覆盖的综合分析.研究发现:泰山地区植被面积由西北向中南递减,周边农村区域植被覆盖大于中心城区;伴随海拔增高,植被面积呈倒"U"变化,多在100～500 m高程范围内;植被多分布在坡度较缓,向阳区域. 相似文献
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为了明确辽东湾植被长势的时空变化特征,本文针对传统的遥感影像信息提取速度缓慢、效率较低等问题,基于奥维互动地图(Ovid interactive map, OMAP)平台,利用Landsat遥感影像提取1990—2019年辽东湾生长季NDVI数据,采用一元线性回归对NDVI时空变化特征进行讨论。结果表明：1)以2010年为转折点,近30年来,辽东湾地表植被NDVI呈现先增后减再增的变化趋势,植被覆盖总面积变化较小,但中高植被覆盖区(0.6相似文献
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超贫磁铁矿的开发会对地表产生剧烈的扰动。为监测2001年以来长河矿区植被盖度的变化情况,本文分别采用2001年和2015年的Landsat TM和OLI影像数据,基于归一化植被指数(Normalized Difference Vegetation Index,NDVI)的像元二分模型对该地区的植被盖度进行定量估算,并分析其时空变化特征。结果显示:2001—2015年间,高级植被覆盖度区域面积减少了29.4 km~2,低级和中低级植被覆盖度区域面积增加了17.9 km~2;在变化幅度上,植被覆盖度中、大幅度增加区的面积为1.9 km~2,而中、大幅度减少区面积为25.6 km~2。空间特征分析表明,研究区内植被覆盖度变化较大的区域均与采矿活动区有紧密联系。 相似文献
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基于MODIS-NDVI数据和气象数据,研究了天津市蓟州区植被NDVI近16年的时空变化特征以及16年间气温、降水变化规律.研究结果表明,蓟州区2000-2015年年平均NDVI趋势为先降后升,最低值出现在2004年.月际NDVI均值与月平均降水量的相关性高于最大降水量的相关性,说明最低温度比最高温对植被的影响更大,月平均降水量比最大降水量对植被的影响更大.除去人类活动的影响,蓟州区县植被指数的变化主要归因于降水减少和温度增加,对于指导当地生产实践具有实际意义. 相似文献
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利用近18年贵州茂兰自然保护区的Landsat TM/ETM+/OLI数据，针对云覆盖对影像质量的影响，提出并使用了一种基于NDVI时间变换一致性的方法，构建出较为完整的研究区植被指数时间序列，实现了小区域尺度下长时间序列的植被覆盖变化研究，并采用一元线性回归模型和相关分析法探讨研究区植被覆盖变化趋势及其对气象因子的响应关系。得出结论：NDVI时间变换一致性处理方法可以有效地消除云覆盖的影响；研究区近18年植被覆盖状况良好且正呈缓慢上升趋势，气候因子与植被覆盖变化呈显著正相关关系，其中平均温度的影响在当月最强，而降水量和平均相对湿度的影响则存在滞后性。 相似文献
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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
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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
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Miguel A. Ortega-Huerta Enrique Martinez-Meyer Stephen L. Egbert Kevin P. Price A. Townsend Peterson 《国际地球制图》2013,28(3):7-20
Abstract An important methodological and analytical requirement for analyzing spatial relationships between regional habitats and species distributions in Mexico is the development of standard methods for mapping the country's land cover/land use formations. This necessarily involves the use of global data such as that produced by the Advanced Very High Resolution Radiometer (AVHRR). We created a nine‐band time‐series composite image from AVHRR Normalized Difference Vegetation Index (NDVI) bi‐weekly data. Each band represented the maximum NDVI for a particular month of either 1992 or 1993. We carried out a supervised classification approach, using the latest comprehensive land cover/vegetation map created by the Mexican National Institute of Geography (INEGI) as reference data. Training areas for 26 land cover/vegetation types were selected and digitized on the computer's screen by overlaying the INEGI vector coverage on the NDVI image. To obtain specific spectral responses for each vegetation type, as determined by its characteristic phenology and geographic location, the statistics of the spectral signatures were subjected to a cluster analysis. A total of 104 classes distributed among the 26 land cover types were used to perform the classification. Elevation data were used to direct classification output for pine‐oak and coastal vegetation types. The overall correspondence value of the classification proposed in this paper was 54%; however, for main vegetation formations correspondence values were higher (60‐80%). In order to obtain refinements in the proposed classification we recommend further analysis of the signature statistics and adding topographic data into the classification algorithm. 相似文献
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Forest cover plays a key role in climate change by influencing the carbon stocks, the hydrological cycle and the energy balance. Forest cover information can be determined from fine-resolution data, such as Landsat Enhanced Thematic Mapper Plus (ETM+). However, forest cover classification with fine-resolution data usually uses only one temporal data because successive data acquirement is difficult. It may achieve mis-classification result without involving vegetation growth information, because different vegetation types may have the similar spectral features in the fine-resolution data. To overcome these issues, a forest cover classification method using Landsat ETM+ data appending with time series Moderate-resolution Imaging Spectroradiometer (MODIS) Normalized Difference Vegetation Index (NDVI) data was proposed. The objective was to investigate the potential of temporal features extracted from coarse-resolution time series vegetation index data on improving the forest cover classification accuracy using fine-resolution remote sensing data. This method firstly fused Landsat ETM+ NDVI and MODIS NDVI data to obtain time series fine-resolution NDVI data, and then the temporal features were extracted from the fused NDVI data. Finally, temporal features combined with Landsat ETM+ spectral data was used to improve forest cover classification accuracy using supervised classifier. The study in North China region confirmed that time series NDVI features had significant effects on improving forest cover classification accuracy of fine resolution remote sensing data. The NDVI features extracted from time series fused NDVI data could improve the overall classification accuracy approximately 5% from 88.99% to 93.88% compared to only using single Landsat ETM+ data. 相似文献
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Anton Vrieling Steven M. de Jong Geert Sterk Silvio C. Rodrigues 《International Journal of Applied Earth Observation and Geoinformation》2008
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
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利用MERIS数据植被指数分析福建省植被长势季节变化 总被引：1，自引：0，他引：1
监测植被长势动态变化可以提供生态系统状况有价值的信息,可以检测到人类或气候作用引起的变化。本研究利用2004—2005年间10期MERIS影像数据,以福建省为例,探讨MERIS数据在区域植被长势季节变化监测中的应用效果;分析了MERIS数据用于区域植被季节变化监测时的数据处理方法;比较了MERIS数据几种植被指数,提出了利用10和8波段组合改进MERISNDVI的建议;利用多时相合成的NDVI简单分析了2004年夏季—2005年夏季三个季节的植被长势状况。结果表明,MERIS植被指数的时空变化有效反映了气候变化对植被长势的影响。 相似文献
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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