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   

基于谱间关系的MODIS遥感影像水体提取研究   总被引：10，自引：0，他引：10  

丁莉东  吴昊  王长健  覃志豪  章其祥 《测绘与空间地理信息》2006,29(6):25-27

水是地球上万物的命脉所在,水体提取对于水资源调查、洪水灾害预测评估和环境监测等有着重要作用。而可见光和近红外波段水体与植被、城市和土壤光谱反射率的差异是利用遥感手段提取水体的基本原理。本文利用谱间关系法进行MOD IS图像的水体提取。结果表明,用于提取水体的谱间关系法比归一化植被指数(NDVI)法快速,但谱间关系法有把云错误地当作水体提取的缺点。  相似文献   

辽宁省耕地植被指数变化特征分析   总被引：1，自引：2，他引：1  

武晋雯  纪瑞鹏  张玉书  杨素英 《气象科学》2006,26(3):279-285

利用NOAA/AVHRR资料通道1(0.58~0.68μm)、通道2(0.725~1.1μm)数据计算归一化植被指数(NDVI),对辽宁省5个气候区内1999~2004年208个旱田监测点和84个水田监测点的作物生长状况进行连续监测,分析NDVI年际、旬际变化特征。结果表明:辽宁耕地(旱田、水田)植被指数年际间差异明显,造成旱田年际变化以及地区差异的主要原因是降水时空分布不均匀的结果,因此旱田2004年NDVI达到近年最大,2001年较低;而造成水田年际差异以及地区差异的原因是受水田用水状况以及光温条件的影响,水田2003年NDVI最大,2001年较低。在整个生长季内(5~9月份),辽宁耕地植被指数呈单峰型变化,从5月上旬开始到6月中旬是缓慢增长阶段,6月下旬到8月下旬快速增长并达到最大,之后又迅速降低;2004年耕地植被指数旬变化趋势与6 a平均植被指数旬变化趋势基本相同,但作物生长前期NDVI较6 a平均值低,主要原因是受到2004年春夏之交严重干旱的影响。  相似文献   

Study on NDVI- T _s space by combining LAI and evapotranspiration     

Han Lijuan  Wang Pengxin  Yang Hua  Liu Shaomin  Wang Jindi 《中国科学D辑(英文版)》2006,49(7):747-754

This paper focuses on interpreting the different spatial relationships between NDVI and T _s, a triangular or a trapezoid, and on analyzing transformation conditions, the physical and ecological meanings of the vegetation index-surface temperature space as well. Further, we use the Temperature-Vegetation Dryness Index (TVDI) to explain the existent meaning of a triangular space after NDVI reaches its saturated state by employing the relationships between NDVI, LAI and evapotranspiration. The specific relations between NDVI and T _s are useful for describing, validating and updating land surface models.  相似文献   

额济纳荒漠绿洲植被生态需水量研究   总被引：14，自引：0，他引：14  

赵文智  常学礼  何志斌  张智慧 《中国科学D辑》2006,36(6):559-566

荒漠绿洲的生态需水量主要指维持荒漠绿洲植被正常生长所需要消耗的水量.采用3S技术与野外生产力测定相结合的方法, 通过建立植被归一化指数(NDVI)、生产力、蒸腾系数之间的关系方程, 计算了额济纳荒漠绿洲的植被生态需水量.结果表明, 维持额济纳绿洲现状的需水量为1.53×10⁸ m³, 若使现有的植被恢复到目前最高生产力水平的生态需水量为3.49×10⁸ m³. 考虑到城镇居民生活用水、河道输水损失、绿洲植被耗水、绿洲内农田用水和降水补充等, 额济纳旗绿洲维持现状需要黑河下泄水量(狼心山)为1.93~2.23×10⁸ m³之间, 若使现有的植被恢复到目前最高生产力水平, 需要黑河下泄水量(狼心山)为4.28~5.17×10⁸ m³之间.  相似文献   

 AMSR-E微波极化指数与MODIS植被指数关系研究     

毛克彪  唐华俊  周清波  陈仲新  陈佑启  赵登忠 《国土资源遥感》2007,18(1):27-31

首先，利用辐射传输方程对微波极化指数（MPI，Microwave Polarization Index)进行推导，以AMSR-E像元经纬度为控制条件，采集与之对应的MODIS植被指数（ LAI/NDVI），并将其平均值作为AMSR-E对应像元的值； 然后，对AMSR-E微波极化指数与LAI/NDVI进行相关分析。结果表明，MPI与LAI/NDVI之间存在着指数关系，而且频率越低，相关性越好。  相似文献   

基于NDVI背景场的雪盖制图算法探索   总被引：5，自引：0，他引：5  

梁继  张新焕  王建 《遥感学报》2007,11(1):85-93

NDSI算法提取MSS雪盖面积时,受到MSS影像缺少短波红外波段的局限。为充分精确提取MSS影像的雪盖面积,本文探索一种以NDVI为背景场的雪盖制图新思路。该方法首先在辐射校正时利用6S模型反演地表反射率,然后根据各地物的光谱特性差异和NDVI特性差异,在ENVI软件SPECTRAL模块中创建冰雪光谱阈值查找表。通过ETM＋和TM影像的三个例证,详细阐明该算法流程以及查找表的创建,并以NDSI对其雪盖制图进行精度验证。结果一致表明,与常规的分类方法（最大似然法）相比较,本文探索的NDVI背景场算法有更高的总体精度和Kappa系数。  相似文献   

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  

周小成  励惠国  汪小钦 《遥感学报》2007,11(4):617-624

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