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1.
以雅鲁藏布江源区为研究对象,以Landsat5 TM图像为数据源,根据不同草地类型的波段组合特征,结合源区1∶100万植被类型图、DEM和NDVI数据,构建草地判别规则,利用决策树分类法对雅鲁藏布江源区草地类型进行遥感识别。研究结果表明:①不同类型草地因其生境不同,利用不同波段组合特征进行草地类型识别能够达到较好的效果;②与传统的监督分类法相比,基于波段组合特征的决策树分类法具有较高的识别精度(总体精度提高了15.4%,Kappa系数提高了0.225);③在海拔4 400~5 000 m区域内,固沙草草原面积最大,其次为矮嵩草和小嵩草混生草甸,再次为变色锦鸡儿和金露梅灌丛,藏北嵩草草甸面积最小。  相似文献   

2.
西藏高原典型草地地上生物量遥感估算   总被引:3,自引:0,他引:3  
准确估算草地地上生物量对合理规划区域畜牧业、评估草地植被的生态效益有重要意义.利用每月两次的野外调查资料和对应的MODIS植被指数,以GIS空间数据处理技术和多元统计分析方法等为手段,建立了西藏高寒草甸、高寒草原和温性草原3个典型草地类型的地上生物量遥感估算模型和方法.结果表明:MODIS植被指数更适合于高寒草甸和高寒草原的地上生物量估算,对于高寒草甸,最佳估算模型是基于归一化植被指数(normalized difference vegetation index,NDVI)的三次多项式,其相关系数为0.82;对高寒草原,则是基于增强型植被指数(enhanced vegetation index,EVI)的三次多项式,相关系数达0.83;由于温性草原存在很强的空间异质性,估算效果较其他2个草地类型差.MODIS植被指数对草地生长期鲜草生物量的估算和模拟效果要优于总地上生物量.在生长期,高寒草甸和高寒草原的鲜草生物量与植被指数之间的相关系数都大于0.8,最高达0.92;对温性草原,两者的相关系数也均大于0.67,其中,NDVI是高寒草甸和温性草原鲜草生物量估算的最佳植被指数,对高寒草原则是EVI.对同一草地类型,由于地上生物量差异较小,使得相比其他模型,线性或多项式回归模型更适合于西藏高原草地地上生物量的估算.  相似文献   

3.
王欣  晋锐  杜培军  梁昊 《遥感学报》2018,22(3):508-520
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   

4.
Google Earth Engine云平台及植被遥感案例研究   总被引:1,自引:0,他引:1  
植被物候是全球变化的敏感指示器,对陆表物质和能量交换产生显著影响.植被物候遥感分析存在数据收集困难、提取方法实现复杂等问题,谷歌地球云计算平台(Google Earth Engine,GEE)为基于遥感大数据的物候分析提供了有利条件.本文分析了GEE平台的数据源、开发接口和应用场景,然后基于GEE中的长时序植被指数数据集NDVI3g,在像素级别采用导数法提取分析了中国东北地区的植被物候变化情况,发现该区域春季返青期推迟,秋季衰落期提前.实验说明了基于GEE进行复杂地学计算的可行性和适用性,但是在算法验证方面存在改进的空间.  相似文献   

5.
范德芹  朱文泉  潘耀忠  姜楠 《遥感学报》2013,17(5):1158-1174
归一化差值植被指数NDVI(Normalized Difference Vegetation Index)时序数据已被广泛应用于植被变化监测、植被物候识别和土地覆盖分类等领域,但受观测条件限制,NDVI原始数据中包含大量噪声,在实际应用时需对其进行检测并去除。目前常用的NDVI数据去噪重建方法主要包括阈值检测法、滤波拟合法及曲线拟合法3类。各方法在应用时均需根据不同的土地覆盖类型或特定的研究区域设置一定数量的经验参数,对噪声的定义缺乏客观标准;此外,这3类方法都没有进行专门的噪声检测,在进行NDVI数据重建时只是根据经验进行噪声判断。本文提出了一种基于狄克松(Dixon)检验法、适用于对小样本进行检测的数理统计噪声检测方法,该方法首先对同一像元、同一时段、不同年份的NDVI时序数据进行统计分析,然后再结合质量评估数据的分析结果,最终给出NDVI是否异常的判断。运用狄克松检验法对噪声进行检测,然后结合已有的两种数据重建方法--变权重滤波法和Savitzky-Golay方法,基于2001年-2010年250 m分辨率的MODIS NDVI时序数据,对覆盖中国55种植被类型共520个测试样点及洞庭湖测试区域进行了NDVI时序数据重建实验,结果表明,狄克松检验法降低了对先验知识的依赖程度,应用该方法对NDVI时序数据中的噪声进行检测预处理后,可以有效提高变权重和Savitzky-Golay方法的数据重建质量。  相似文献   

6.
地表生物量对农作物估产、植被长势评估具有很重要的意义。随着遥感技术的发展与应用,遥感为生物量估算提供了一种新的手段。本文以唐山市为例,利用小麦种植区的MODIS遥感影像数据和同期野外调查获得的16组32个生物量数据,对比分析了归一化植被指数(NDVI)、增强型植被指数(EVI)与小麦生物量多个回归方程的相关系数,进而建立了NDVI、EVI与小麦生物量的线性回归模型。结果显示,使用MODIS数据的植被指数能够很好地对研究区地上生物量进行估算,其中使用EVI的三次函数模型拟合精度最高,并且对每组数据进行平均处理会使模型精度进一步提高。  相似文献   

7.
为弥补、修正构建Landsat 8归一化植被指数(normalized differential vegetation index,NDVI)长时间序列中因云层覆盖、影像质量与重访周期导致的数据缺失问题,交互比较高分一号(GF-1)与Landsat 8两类传感器的植被探测能力,并对其植被指数的定量关系进行研究,探讨以GF-1局部镶嵌或全局替换Landsat 8缺失数据构建时序NDVI的可行性。结果显示,Landsat 8与GF-1具有NDVI差异性,具体表现为Landsat 8探测地物信号更强,而GF-1获取地物信息量更多;相同空间分辨率(30 m)下两传感器NDVI数据呈现高度线性相关,经方程转换后,GF-1的NDVI拟合数据与Landsat 8的NDVI关系增强;同时,两传感器的NDVI数据存在区域差异性,且拟合数据可以有效减少差异程度。实验表明,此方法可实现Landsat 8高分辨率时序NDVI的构建,具有一定应用价值。  相似文献   

8.
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   

9.
范菁  余维泽  吴炜  沈瑛 《遥感学报》2017,21(5):749-756
在多云多雨的地区,光学遥感存在着获取无云数据困难的难题,这会导致时间序列应用中可用数据匮乏。因此,本文面向稀疏时间序列遥感数据,根据噪声造成遥感影像上归一化差分植被指数(NDVI)被低估的事实,提出了一种知识引导的拟合方法。首先,在遥感影像预处理的基础上,利用先验知识和时序差分法对噪声进行识别和剔除;然后,采用高斯二阶模型对原始数据进行拟合;最后,根据拟合残差更新权重,进行迭代拟合,重复上述过程直至获得稳定的结果。本文以Landsat 8 OLI作为数据源,对浙江省杭州地区的森林数据进行拟合,结果表明:在稀疏时间序列数据的情况下,本文方法与MODIS数据拟合结果的相关系数达到0.92,关键时点(如NDVI峰值点等)的时间误差在5 d;相比当前主流方法的0.88与8 d具有更高的精度。  相似文献   

10.
基于TM和ETM+遥感图像,分析唐山市绿地分布结构及变化趋势,对唐山市植被信息进行提取,为城市规划提供科学依据及技术支持.利用归一化差值植被指数(NDVI)计算植被信息图;设定合适的NDVI阈值参数和近红外波段的阈值参数,精确判定植被像元,并生成唐山市几个区域的植被信息结果图;利用1999-2009年3个时间段的植被信息图合成植被信息动态变化图,对植被信息动态变化图进行分析.结果表明,近10 a来,唐山市城区以公园为主的植被覆盖面积增加,城南南湖生态建设作用明显,唐山城区范围正在向外围扩展.  相似文献   

11.
Snow effects on alpine vegetation in the Qinghai-Tibetan Plateau   总被引:1,自引:0,他引:1  
Understanding the relationships between snow and vegetation is important for interpretation of the responses of alpine ecosystems to climate changes. The Qinghai-Tibetan Plateau is regarded as an ideal area due to its undisturbed features with low population and relatively high snow cover. We used 500 m Moderate Resolution Imaging Spectroradiometer (MODIS) datasets during 2001–2010 to examine the snow–vegetation relationships, specifically, (1) the influence of snow melting date on vegetation green-up date and (2) the effects of snow cover duration on vegetation greenness. The results showed that the alpine vegetation responded strongly to snow phenology (i.e., snow melting date and snow cover duration) over large areas of the Qinghai-Tibetan Plateau. Snow melting date and vegetation green-up date were significantly correlated (p < 0.1) in 39.9% of meadow areas (accounting for 26.2% of vegetated areas) and 36.7% of steppe areas (28.1% of vegetated areas). Vegetation growth was influenced by different seasonal snow cover durations (SCDs) in different regions. Generally, the December–February and March–May SCDs played a significantly role in vegetation growth, both positively and negatively, depending on different water source regions. Snow's positive impact on vegetation was larger than the negative impact.  相似文献   

12.
Using satellite-observed Normalized Difference Vegetation Index (NDVI) data and Rotated Empirical Orthogonal Function (REOF) method, we analyzed the spatio-temporal variation of vegetation during growing seasons from May to September in the Three-River Source Region, alpine meadow in the Qinghai-Tibetan Plateau from 1982 to 2006. We found that NDVI in the centre and east of the region, where the vegetation cover is low, showed a consistent but slight increase before 2003 and remarkable increase in 2004 and 2005. Impact factors analysis indicted that among air temperature, precipitation, humid index, soil surface temperature, and soil temperature at 10 cm and 20 cm depth, annual variation of NDVI was highly positive correlated with the soil surface temperature of the period from March to July. Further analysis revealed that the correlation between the vegetation and temperature was insignificant before 1995, but statistically significant from 1995. The study indicates that temperature is the major controlling factor of vegetation change in the Three-River Source Region, and the currently increase of temperature may increase vegetation coverage and/or density in the area. In addition, ecological restoration project started from 2005 in Three-River Source Region has a certain role in promoting the recovery of vegetation.  相似文献   

13.
Monitoring phenological change in agricultural land improves our understanding of the adaptation of crops to a warmer climate. Winter wheat–maize and winter wheat–cotton double-cropping are practised in most agricultural areas in the North China Plain. A curve-fitting method is presented to derive winter wheat phenology from SPOT-VEGETATION S10 normalized difference vegetation index (NDVI) data products. The method uses a double-Gaussian model to extract two phenological metrics, the start of season (SOS) and the time of maximum NDVI (MAXT). The results are compared with phenological records at local agrometeorological stations. The SOS and MAXT have close agreement with in situ observations of the jointing date and milk-in-kernel date respectively. The phenological metrics detected show spatial variations that are consistent with known phenological characteristics. This study indicates that time-series analysis with satellite data could be an effective tool for monitoring the phenology of crops and its spatial distribution in a large agricultural region.  相似文献   

14.
ABSTRACT

Monitoring the structural and functional dimensions of natural vegetation is a critical issue to ensure effective management of biodiversity. While coarse-resolution satellite image time-series have been used extensively to monitor vegetation physiognomies, their potential to describe plant species composition remains understudied. The objective of this study is to assess the potential of annual time-series of MODIS images to discriminate combinations of plant communities, called “vegetation series,” and characterize their structural and functional dimensions at the landscape scale. Twelve vegetation series were mapped in a 16 574 ha study area in a Mediterranean context located in Corsica (France). First, the structural dimension of vegetation series was examined using a random forest (RF) model calibrated with a reference field map to (i) measure the importance of each MODIS image in discriminating vegetation series; (ii) quantify the influence of the number of dates on model accuracy; and (iii) map the vegetation series with the optimal subset of MODIS images. Second, the functional dimension of vegetation series was analyzed by ordinating three functional indices through principal component analysis. These indices were the annual sum of normalized difference vegetation index (NDVI), the annual amplitude of NDVI, and the date of maximum NDVI, considered as a proxy for annual primary production, seasonality of carbon fluxes, and vegetation phenology, respectively. Results showed that (i) vegetation series were mapped accurately (median Kappa index 0.70, median overall accuracy 0.76), preferably using images acquired from February to August; (ii) at least 10 MODIS images were required to achieve sufficient accuracy; and (iii) a functional gradient was detected, ranging from high annual net primary production with low seasonality of carbon fluxes and early phenology in Mediterranean vegetation series to low annual net primary production with high seasonality of carbon fluxes and late phenology in alpine vegetation series.  相似文献   

15.
基于NOAA时间序列数据分析的中国西部荒漠化监测   总被引:2,自引:0,他引:2  
利用1982~2000年的NOAAAVHRR10日合成时间序列数据,对中国西部干旱半干旱区的沙漠边缘及荒漠化多年动态变化进行了分析。  相似文献   

16.
This study investigated rice cropping practices and rice growing areas in the Vietnamese Mekong Delta using MODIS 250 × 250 m normalized difference vegetation index (NDVI) data acquired during the 2002 and 2007 rice cropping seasons. Data processing was conducted in five main steps: (1) constructing time-series MODIS NDVI data; (2) noise filtering of the time-series MODIS NDVI data using empirical mode decomposition (EMD); (3) extracting and evaluating phenological rice training patterns from the smooth time profiles of NDVI; (4) classifying rice cropping systems using support vector machines (SVMs); and (5) conducting an error analysis using ground reference data and government rice statistics. The results indicated that EMD was an efficient filter for noise removal in the time-series MODIS NDVI data. The filtered temporal NDVI profile characterized the distinct behaviors of the rice cropping systems. The estimated sowing and harvesting dates were compared with the field-survey data and indicated root mean square error (RMSE) values of 7.5 and 8.2 days, respectively. The comparison results between the 2002 classification map and the ground reference data indicated that the overall accuracy for the 2002 data was 92.9% with a Kappa coefficient of 0.89, while in 2007 these values were 93.8% and 0.90, respectively. At the district level, there was good agreement between the MODIS-based estimated areas and government rice statistics for 2002 and 2007 (R 2 ≥ 0.85). An investigation of changes in cropping practices from 2002 to 2007 showed that 12.9% of the area used for double-cropped irrigated rice in 2002 had been converted to triple-cropped irrigated rice by 2007, whereas 27.4% of the area used for triple-cropped irrigated rice in 2002 had been converted to double-cropped irrigated rice by 2007.  相似文献   

17.
针对鄂尔多斯高原植被覆盖变化受干旱胁迫的状况,该文结合降水和气温的协同变化,以2000-2012年生长季的MODIS-NDVI数据和同期降水、温度和帕尔默干旱指数为依据,采用线性趋势分析、标准偏差分析和相关性分析等方法,对鄂尔多斯高原植被与气候变化的相关关系和干旱异常变化对植被动态的影响进行了研究.结果表明:鄂尔多斯高原生长季及季节(春季、夏季和秋季)植被归一化植被指数主要受降水的控制和干旱的制约,秋季归一化植被指数更多地受到夏季干旱的影响.与气象因子的空间相关分析表明,春季温度上升有利于研究区北部归一化植被指数像元的增加.在荒漠草原和沙漠地区,夏季干旱与归一化植被指数的相关关系最强.秋季降水对典型草原归一化植被指数的提升显著.  相似文献   

18.
In the last two decades, numerous investigators have proposed cumulative vegetation indices (i.e., functions which encode the cumulative effect of NDVI maximum value composite time-series into a single variable) for net primary productivity (NPP) mapping and monitoring on a regional to continental basis. In this paper, we investigate the relationships among three of the most commonly used cumulative vegetation indices, expanding on the definition of equivalence of remotely sensed vegetation indices for decision making. We consider two cumulative vegetation indices as equivalent, if the value of one index is statistically predictable from the value of the other index. Using an annual time-series of broad-scale AVHRR NDVI monthly maximum value composites of the island of Corsica (France), we show that the pairwise linear association among the analysed cumulative vegetation indices shows coefficients of determination (R2) higher than 0.99. That is, knowing the value of one index is statistically equivalent to knowing the value of the other indices for application purposes.  相似文献   

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