基于EOS/MODIS数据的NDVI与EVI比较研究   总被引：24，自引：0，他引：24  

李红军  郑力  雷玉平  李春强  周戡 《地理科学进展》2007,26(1):26-32

作为NOAA/AVHRR 归一化植被指数(NDVI) 的延续和发展, EOS/MODIS 归一化植被指 数(NDVI) 和增强植被指数( EVI) 在许多领域得到广泛应用。应用数理统计和地统计学方法对二 者进行的对比研究表明: NDVI 在植被生长旺盛期容易达到饱和, 而EVI 则能克服这一现象, 比 较真实地反映植被的生长变化过程; 相同空间分辨率下, EVI 取值范围、标准差与变异系数均高 于NDVI, NDVI 数据比较均一, 其空间相关性高于EVI, EVI 更能反映研究区域内植被空间差异。 关键词:MODIS; 归一化植被指数(NDVI) ; 增强植被指数( EVI) ; 对比  相似文献   

基于Mann-Kendall方法的胶东半岛海岸带归一化植被指数趋势分析   总被引：7，自引：0，他引：7  

刘亚龙  王庆  毕景芝  张明明  邢前国  施平 《海洋学报》2010,32(3):79-87

利用1998—2008年SPOT/VEGETATION逐旬共372期归一化植被指数时间序列影像数据,引入Mann-Kendall非参数趋势检验方法,分析了胶东半岛最近10 a来的归一化植被指数变化趋势。结果表明,最近10 a来,胶东半岛归一化植被指数变化趋势以衰减区域居主导地位,其中有明显衰减变化趋势的区域占半岛总面积的19.3%,有明显增强变化趋势的区域仅占半岛总面积的2.8%。归一化植被指数衰减区域在空间上沿海岸线呈环状分布,从沿海岸到远离海岸,归一化植被指数增强趋势逐渐明显,衰减最明显的区域大部分位于半岛沿海30 km以内,植被增强趋势最明显区域位于半岛中部山地及沿海防护林地区。人类活动及其空间分布是归一化植被指数变化的主要因素,其中沿海城市化、工业化和海岸湿地开发利用程度的提高导致归一化植被指数衰减,而山地植被保护和海岸防护林建设导致归一化植被指数增强。  相似文献   

银川平原植被生长与地下水关系研究   总被引：15，自引：1，他引：14  

金晓媚  万力  张幼宽  薛忠歧  殷瑛 《地学前缘》2007,14(3):197-203

干旱区植被生长与地下水的关系是生态水文地质学研究的热点之一。西北内陆干旱地区降水稀少,植被的生长发育与地下水的关系极为密切,从大尺度上研究地下水变化的生态效应问题对生态环境的保护和恢复具有重要的意义。借助遥感方法,结合地下水观测数据,在区域尺度上定量地研究了中国银川平原地区地下水埋深及矿化度与植被生长的关系。结果表明:适宜植被生长的地下水埋深范围约为1~6m,当地下水位埋深为3.5m左右时,植被长势最好。而在水位埋深为3.5m左右的地区,植被生长的相对好坏又受地下水矿化度的影响。当地下水矿化度为0.9g/L时对该地区植被的生长最为有利。  相似文献   

黄河流域NDVI/土地利用对蒸散发时空变化的影响   总被引：2，自引：0，他引：2  

谷佳贺  薛华柱  董国涛  周利娟  李静茹  党素珍  李尚志 《干旱区地理》2021,(1):158-167

基于蒸散发(ET)、归一化植被指数(NDVI)及土地利用数据利用M-K检验、Sen趋势分析等方法,研究2001—2015年黄河流域ET时空分布及不同植被覆盖/土地利用下的ET变化规律.结果 表明:(1)黄河流域年均ET呈东南高西北低的空间分布格局,与植被覆盖和土地利用的关系具有较好的一致性;(2)黄河流域ET、NDVI...  相似文献   

A comparison of frameworks for separating the impacts of human activities and climate change on river flow in existing records and different near-future scenarios     

Soghra Andaryani  Vahid Nourani  James Ball  Saeed Jahanbakhsh Asl  Hamidreza Keshtkar  Dennis Trolle 《水文研究》2021,35(7):e14301

  相似文献   

An assessment of land degradation in the Save catchment of Zimbabwe     

Julia Mambo  Emma Archer 《Area》2007,39(3):380-391

The lack of reliable baseline information on land degradation is a hindrance towards its monitoring and mitigation. Of particular interest is the identification of areas susceptible to degradation. In this study, remote sensing and GIS technologies were applied to detect and map susceptibility to land degradation in Buhera district, in Save catchment, Zimbabwe. Data used included Landsat TM and ETM imagery for 1992 and 2002, agro-ecological zones, vegetation cover and population density. The study identified five preliminary categories of degradation susceptibility ranging from very high to low.  相似文献   

利用NOAA NDVI数据集监测冬小麦生育期的研究   总被引：34，自引：2，他引：34  

辛景峰  宇振荣  P.M.Driessen 《遥感学报》2001,5(6):442-447

探索了利用NDVI研究作物生育期的方法，对黄淮海冬麦区的返青期、抽穗期、成熟期进行了估测，并利用地面实际观测资料进行了验证。结果表明，NDVI数据对大范围农作物生育期监测是可行的。冬小麦遥感反青期由南到北依次推迟，符合春季绿波由南到北推移规律。对冬小麦遥感生育期年际变化分析表明，黄淮海平原返青期变化相对较大，而抽穗期和成熟期变化较小。根据历年月平均温度与返青期分析，冬小麦返青日期与2月份平均温度密切相关。对于局部地区，利用5d合成1km分辨率数据，且按农业生态分区分别制定生育期判别标准，估测效果将更好。  相似文献   

应用遥感数据研究中国植被生态系统与气候的关系   总被引：48，自引：2，他引：48  

赵茂盛  符淙斌  延晓冬  温刚 《地理学报》2001,56(3):287-296

应用1982-1994年NOAA/AVHRR的归一化植被指数（NDVI）资料和587个气象台站的数据对我国不同类型植被生态系统和气候的关系进行研究，首先将我国的植被类型划分为21类，在此基础上分别研究了不同时间尺度下我国不同区域，不同植被类型和气候的关系。结果表明：在多年平均状态下，植被生态系统NDVI水平主要受水分条件的影响；年内变化上，温度对植被生态系统季相变化化起着比降水略大的作用，年降水量造成了植被季相响应的差异，在年际变化上，分别研究了4个季节和整个生长期尺度上的关系，一般情形为温度和降水对植被的年际波动起着大致相反的作用，不同植被类型在不同的生长时期（季节）对气候的变化响应方式也不同，发现在植被的生长期，我国南方和北方的植被生态系统对温度和降水的响应方式相反；同时存在2个植被-气候敏感区，分别为我国北方的典型草原到森林的过渡区和云南中部部分区域。  相似文献   

Spatiotemporal characteristics of white mold and impacts on yield in soybean fields in South Dakota     

Confiance Mfuka  Emmanuel Byamukama  Xiaoyang Zhang 《地球空间信息科学学报》2020,23(2):182-193

ABSTRACT

White mold of soybeans is one of the most important fungal diseases that affect soybean production in South Dakota. However, there is a lack of information on the spatial characteristics of the disease and relationship with soybean yield. This relationship can be explored with the Normalized Difference Vegetation Index (NDVI) derived from Landsat 8 and a fusion of Landsat 8 and the Moderate Resolution Imaging Spectroradiometer (MODIS) images. This study investigated the patterns of yield in two soybean fields infected with white mold between 2016 and 2017, and estimated yield loss caused by white mold. Results show evidence of clustering in the spatial distribution of yield (Moran’s I = 0.38; p < 0.05 in 2016 and Moran’s I = 0.45; p < 0.05 in 2017) that can be explained by the spatial distribution of white mold in the observed fields. Yield loss caused by white mold was estimated at 36% in 2016 and 56% in 2017 for the worse disease pixels, with the most accurate period for estimating this loss on 21 August and 8 September for 2016 field and 2017 field, respectively. This study shows the potential of free remotely sensed satellite data in estimating yield loss caused by white mold.  相似文献   

Multi-scale remote sensing to support insurance policies in agriculture: from mid-term to instantaneous deductions     

Sarvia F  De Petris S  Borgogno-Mondino E 《地理信息系统科学与遥感》2020,57(6):770-784

ABSTRACT

Climate change is today one of the biggest issues for farmers. The increasing number of natural disasters and change of seasonal trends is making insurance companies more interested in new technologies that can somehow support them in quantifying and mapping risks. Remotely sensed data, with special focus on free ones, can certainly provide the most of information they need, making possible to better calibrate insurance fees in space and time. In this work, a prototype of service based on free remotely sensed data is proposed with the aim of supporting insurance companies’ strategies. The service is thought to calibrate annual insurance rates, longing for their reduction at such level that new customers could be attracted. The study moves from the entire Piemonte region (NW Italy), to specifically focus onto the Cuneo province (Southern Piemonte), which is mainly devoted to agriculture. MODIS MOD13Q1-v6 and Sentinel-2 L2A image time series were jointly used. NDVI maps from MODIS data were useful to describe the midterm phenological trends of main crops at regional level in the period 2000–2018; differently, Sentinel-2 data permitted to map local crop differences at field level in 2016 and 2017 years. With reference to MODIS data, the average phenological behavior of main crop classes in the area, obtained from the CORINE Land Cover map Level 3, was considered using a time series decomposition approach. Trend analyses showed that the most of the crop classes alternated three phases (about 7 years) suggesting that, presently, this is probably the time horizon to be considered to tune mid-term algorithms for risk estimates in the agricultural context. Crop classes trends were consequently split into three phases and each of them modeled by a first-order polynomial function used to update correspondent insurance risk rate. Sentinel-2 data were used to map phenological anomalies at field level for the 2016 and 2017 growing seasons; shifts from class average behavior were considered to locally and temporarily tune insurance premium around its average trend as described at the previous step. Synthesizing, one can say that this approach, integrating MODIS and Sentnel-2 data, makes possible to locally and temporarily calibrate premiums of indexed insurance policies by describing the average trends of crop performance (NDVI) at regional level by MODIS data and refining it at field and specific crop level by Sentinel-2 data.  相似文献