Quantification of spatial distribution of vegetation in the Qilian Mountain area with MODIS NDVI

The spatial distribution of vegetation in the Qilian Mountain area was quantified with remote sensing data. The MODIS NDVI values for June, July, August and September are the best indicators for the vegetation growth during a year in this area and thus were used in this study. The results obtained by analysing NDVI data for seven years from 2000 to 2006 clearly indicated that elevation and aspect, as a proxy for precipitation and temperature, are two very important factors for the vertical distribution of vegetation in Qilian Mountain area. In the Qilian Mountain area the vegetation growth is optimal between the elevations of 3200 m and 3600 m, with NDVI values larger than 0.50 and a peak value of?>0.56 around 3400 m. It is the combination of plentiful precipitation and suitable land surface temperature that provides less soil moisture stress and thus suitable conditions for vegetation growth in this range of elevations. The optimal vegetation growth is found in the shady slope between NW340° to NE70° with the largest NDVI value (>0.56) within the elevation range of 3200 m and 3600 m. The methodology developed in this study should be useful for similar ecological studies on vegetation distribution.     

Multi-scale object-based measurement of arid plant community structure

The measurement of plant community structure provides an extensive understanding of its function, succession and ecological process. The detection of plant community boundary is rather a challenge despite in situ work. Recent advances in object-based image analysis (OBIA) and machine learning algorithms offer new opportunities to address this challenge. This study presents a multi-scale segmentation approach to accurately identify the boundaries of each vegetation and plant community for mapping plant community structure. Initially, a very high resolution (VHR) Worldview-2 image of a desert area is hierarchically segmented from scale parameter 2 to 500. Afterward, the peak values of the standard deviation of brightness and normalized difference vegetation index (NDVI) across the segmentation scales are detected to determine the optimal segmentation scales of homogeneous single plant and plant community boundaries. A multi-scale classification of vegetation characterization with features of multiple bands, NDVI, grey-level co-occurrence matrix (GLCM) entropy and shape index is performed to identify dryland vegetation types. Finally, the four vegetation structural features on the type, diversity, object size and shape are calculated within the plant community boundaries and composed to plant community structure categories. Comparing the results with the object fitting index (FI) of the reference data, the validation indicates that the optimal segmentations of tree, shrub and plant communities are consistent with the identified peak values.     

Evaluation of the NDVI in plant community composition mapping: a case study of Tersakan Valley,Amasya County,Turkey

Mapping the composition of plant community types requires reliable spatial data obtained from field surveys and satellite‐derived indices. The normalized difference vegetation index (NDVI) is the simplest and most frequently used index in plant applications. If relationships between the NDVI and plant cover abundance are determined, this information can be used in the mapping process. In this study, we investigated these possible connections for mapping the plant community composition of Tersakan Valley in Turkey. We collected georeferenced cover‐abundance (Braun‐Blanquet, BB) data from 1077 quadrats in the field, and derived an NDVI raster map from a Landsat Enhanced Thematic Mapper Plus (ETM+) image. Then we classified this NDVI map by using various methods and class numbers. Using bivariate correlation analysis, we explored the relationships between 26 classified NDVI maps and BB, and chose the classified NDVI map with the strongest correlation. We further examined this relationship by using scatter plots, histograms and paired samples t‐tests. According to the results, the NDVI (equal‐interval 15) classes between 4 and 8 corresponded with the BB classes between 1 and 5, respectively. Using this relationship, the spatial distribution of 43 different plant community compositions were determined in geographic information systems (GIS). The results indicate that the NDVI has the potential to map plant community composition reliably.     

河谷型城市土地利用类型及格局的热环境效应遥感分析——以兰州市为例

以河谷型城市兰州为例,采用Landsat ETM+遥感影像为基本数据源,定量反演了地表温度（LST）和植被指数（NDVI）,利用GIS空间分析方法,分析了LST和NDVI 在不同土地利用类型之间的差异以及二者之间的定量关系,并引入多样性和聚集度指数,讨论了在不同土地利用的空间组合下,LST和NDVI 的空间差异及相互关系。结果显示:LST和NDVI具有明显的相关性,中心城区LST表现出热岛效应,而NDVI则为低谷效应;土地利用斑块和类型两种尺度水平上LST和NDVI均具有明显负相关的线性关系,城市内部不同土地类型所产生的热环境效应不同;土地利用多样性越丰富、聚集度越小的区域,其温度对地表植被覆盖的敏感性越弱。     

基于ETM＋的北京西部山区乔木群落结构研究

利用遥感技术结合地面调查的方法对2008年春季北京西部山区乔木群落的多样性进行了研究。提取归一化植被指数（NDVI）,并计算NDVI随时间的变化率（△NDVI）;利用地面调查数据计算研究区的健康指数、Mar-galef丰富度指数、Shannon-Wiener多样性指数和Simpson多样性指数,并分析△NDVI、健康指数和多样性指数之间的关系。结果表明：（1）健康指数和多样性指数之间存在正相关关系,群落多样性指数越高,群落的整体健康状况越好。（2）△NDVI与健康指数之间呈正相关关系,健康指数越高的群落,单位时间内NDVI的增加值越大,植被群落的生长变化越明显。（3）△NDVI的高低可以代表区域植被的健康程度,反映区域植物群落的丰富度、多样性。△NDVI的值越高,植被群落的健康程度越好,植被群落的丰富度、多样性指数越高。本文的研究较好的将遥感技术和地面调查相结合,对△NDVI与群落植被健康程度、多样性指数进行了研究和验证,为以后研究植被群落多样性提供了一定的借鉴。     

Land Cover Extraction in the Ejina Oasis by Hyperspectral Remote Sensing

The extraction of land surface coverage is the basis of ecological environment evaluation,vegetation change analysis and regional ecological and hydrological processes.Aerial hyperspectral remote sensing has great advantage in land surface coverage extraction,such as flexible,wide coverage,high spatial resolution and high spectral resolution.Research area has landscape characteristics of vegetation,landscape fragmentation and heterogeneity in Ejina Poplar Forest National Nature Reserve.Comparison and analysis of two methods of dimension reduction based on minimum noise transform and principal component analysis,three supervised classification methods based on maximum likelihood method,support vector machine and object\|oriented classification.Land surface coverage is extracted by NDVI threshold segmentation,minimum noise transform dimensionality reduction method and maximum likelihood classification method according to the characteristics of landscape fragmentation,heterogeneity and high redundancy of hyperspectral data based on the Airborne Hyperspectral Data of Ejina oasis in the lower reaches of Heihe.The land surface coverage results overall accuracy and Kappa coefficient are 87.95% and 0.885 by random sampling based on airborne remote sensing data.The results show that the classification results of high accuracy can provide effective parameters for ecological research.     

多云雾地区高时空分辨率植被覆盖度构建方法研究

针对多云雾地区高时空分辨率数据缺乏现状,提出了一套区域尺度高时空分辨率植被覆盖度数据构建方法.首先,通过时空适应反射率融合模型(STARFM)有效地将TM 的较高空间分辨率与MODIS的高时间分辨率融合在一起,构建了研究区植被生长峰值阶段的NDVI数据;然后,以植被生长峰值阶段的NDVI为输入,基于地表覆被类型,综合应用等密度和非密度亚像元模型对研究区的植被覆盖度进行估算.结果表明:①即使数据源存在大量的云雾,且存在一定的时相差异,研究区植被覆盖度的估算结果过渡自然,不存在明显的不接边效应;②以植被生长峰值阶段的NDVI数据为输入进行植被覆盖度估算,有效拉开了同一地表覆被类型不同覆盖度像元的NDVI梯度,提高了亚像元估算模型对输入数据的抗扰动性;③基于地表覆被类型,应用亚像元混合模型,能够提高植被覆盖度的估算精度.经野外实测数据验证,总体约８５％的估算精度表明,针对高时空分辨率遥感数据缺乏的多云雾区域,本研究提出的方法能够实现区域尺度植被覆盖度数据的构建.     

Monitoring and modelling land surface dynamics in Bermejo River Basin,Argentina: time series analysis of MODIS NDVI data

The purpose of this work was to monitor and model land surface phenology over the past ten years in the South American Bermejo River basin using the Moderate Resolution Imaging Spectroradiometer (MODIS) normalized difference vegetation index (NDVI) product. In order to do this, we evaluated the characteristics of the satellite data and information available on the study area's ecosystem to choose the best model to capture the temporal dynamics of NDVI in local vegetation (sufficiently complex to provide a good fit and simple enough so that each parameter has an immediate ecological meaning). An ecological interpretation of model parameters was provided. Different land surfaces showed distinct fluctuations over time in NDVI values, and this information was used to improve object-oriented classification. A decision tree classification was developed to identify spatial patterns of NDVI functional form and the fluctuations that these patterns presented from 2000 to 2010. We integrated inter-annual information in a final map that distinguishes stable areas from changing sites. Assuming that large inter-annual spatial-scale fluctuations were related to climatic events, we established how vegetated land surfaces within the study area responded to these. Our study was designed to emphasize the interpretation of the spatial and temporal scales of land surface phenology.     

Impacts of Urban land surface temperature on tract landscape pattern,physical and social variables

ABSTRACT

This paper first focuses on the study of the relationship between the urban heat island (UHI) and the selected physical variables (percentage of urban surface covers, Normalized Difference Vegetation Index (NDVI)) and social variables (population density (PDEN)), and then concentrates on the study of the relationship between UHI and the landscape spatial geometric patterns. The researched results discover that urban Land Surface Temperature (LST) is not only impacted by land cover composition, i.e. land use/cover, which is expressed in this paper as the PURB (commerce/industry/transportation), but also its spatial geometric configuration, i.e. various landscape geometric pattern metrics, which in this paper are expressed by compositional percentage of landscape area (PLAND), configurational edge density (ED), patch density (PD), landscape shape index (LSI), clumpiness index (CI), and Shannon’s diversity index (SHDI). The results show that the proportion of vegetation coverage out of a tract impacts its contribution to an entire UHI in Washington District of Columbia (DC), in particular, interspersing vegetation within a tract is capable of making a stronger mitigation effect to UHI than its concentrated form. Thus, a scatter spatial arrangement and distribution of vegetation is proposed to mitigate UHI effect.     

基于NDVI及DEM的青海湖北岸景观格局空间自相关分析

本文以青海湖北岸为研究区,利用2006年Landsat-5 TM数据,结合植被类型图、SRTM高程数据、1∶5万地形图等数据,获取了该区12类景观类型,分类总体精度为82.91%,Kappa系数为0.81。以NDVI均值、坡向均值、高程均值为区域观测值,计算研究区景观类型的空间自相关性的Moran指数,再根据局部Moran指数的空间集聚分布特征,分析这些景观类型之间的结构稳定性,表现为如下特征:第一,较稳定景观,格局类型包括河谷灌丛、山地灌丛、高寒沼泽、高寒草甸、河流、裸岩;第二,欠稳定景观,格局类型包括湖泊、温性草原、湖滨沼泽;第三,极不稳定景观,格局类型有沙地、石砾地、裸土地,如鸟岛、金沙湾,尕海地区的沙地。     

Spectral,spatial and temporal characteristics of Arctic tundra reflectance

Abstract

The objective was to quantify and analyse the spectral, spatial and temporal variability of solar radiation reflected from arctic tundra vegetation at a study site in the Brooks Range foothills of northern Alaska. Spectral radiance data from hand-held radiometers and the SPOT HRV sensor were sampled along hillslope transects (toposequences) and within four vegetation community types. The spatial trend of normalised difference vegetation index (NDVI) along the toposequences corresponded to variations in the abundance of green vegetation matter and in vegetation composition. A marked temporal increase in the NDVI occurred along the toposequences from the beginning of the growing season (mid-June) to peak green up (end of July). The spectral signatures of three tundra dominant vegetation communities, dry heath, moist tussock and wet sedge, were moderately separable, with dry heath being most separable. The overall separability of the major community types was similar at all times during the growing season, with the most divergent signatures occurring in late July during maximum greenness. Some of the important ecological features of the arctic tundra landscape are not resolved by the SPOT HRV sensor in multi-spectral mode, in spite of its high (20 m) spatial resolution.     

近10a新疆地区植被动态与R/S分析

利用SPOT VGT传感器的NDVI时序数据,采用时间序列谐波分析算法(HANTS)对NDVI数据进行去云预处理,基于趋势分析、Hurst指数分析等方法,研究了1999~2008年新疆植被覆盖的时空变化,分析了Hurst指数的空间分布规律及其在不同土地覆盖类型下的差异。结果表明：近10 a来,新疆植被总体呈现不显著的增加趋势且具有明显的空间差异性。R/S分析表明,新疆大部分地区植被变化将保持现在的趋势,局部地区具有反持续性。各土地覆盖类型Hurst指数均在0.63以上,沙漠、戈壁、裸地的Hurst指数明显高于其它土地覆盖类型,受人类活动影响较大的土地覆盖类型其Hurst指数较低,可持续性低于自然或半自然状态下的植被覆盖类型。     

Optimization spatial pattern method for vegetation landscape in bay based on AHP

Vegetation landscape is an important part of the Bay City, which plays an important role in the marine ecosystem, urban ecological security and residents' leisure and entertainment. Taking Shenzhen Bay Coastal Park as the research object, the optimization method for spatial pattern of vegetation landscape in Bay based on AHP was proposed in the paper. Through random image acquisition, 30 spatial patterns of plant landscape in the park were obtained; visual quality and ecological efficiency were used as the evaluation criteria, and 12 evaluation indexes were selected to build the evaluation system of spatial pattern of vegetation landscape in Bay based on AHP, and the weight value of each evaluation factor was determined and tested. The comprehensive evaluation score of vegetation landscape was determined by the comprehensive evaluation index method of vegetation landscape. According to the score, the quality grade of vegetation landscape was divided into grade I, II, III and IV. The results show that the quality of vegetation landscape in Shenzhen Bay Coastal Park is not up to grade I, 12 of them are up to grade II, accounting for 40.0%, 18 of them are up to grade III, accounting for 60.0%, and there is no landscape of grade IV, which shows that the quality of vegetation landscape in Shenzhen Bay Coastal Park is good, but there is no excellent plant landscape. Based on the evaluation results, the optimization strategy of spatial pattern of vegetation landscape in bay is proposed from the macro, meso and micro.     

Spectral modelling of multicomponent landscapes in the Sahel

Abstract

Certain landscapes in the Sahel and elsewhere consist of a ‘checkerboard’ arrangement of vegetated and non-vegetated areas in which there may be several spectrally distinct vegetation and bare ground components. When individual components form large spatially coherent patches, and the vertical dimension of the vegetation is small, spectral interactions between components are negligible. The influence of any one component on the average reflectance of the landscape can then be described by its spectral properties and relative area using simple additive mixture models. These models can be extended to the vegetation indices. The spatial average normalized difference vegetation index (NDVI) is a function of the brightness (red plus near-infrared reflectances), the NDVI and the fractional cover of the components. In landscapes where soil and vegetation can be considered the only components, the NDVI-brightness model can be inverted to obtain the NDVI of the vegetation. Aerial photoradiometer data from Mali, West Africa were used to determine the red and near-infrared component reflectances of soil and vegetation. The derived soil component reflectances were well correlated with ground measurements. The relationship between the vegetation component NDVI and plant cover was better than between the NDVI of the entire landscape and plant cover. The usefulness of this modelling approach depends on the existence of clearly distinguishable landscape components. The method resolves the spectral properties of individual components, but the vegetation component, while free of the effect of bare ground components, is still affected by the underlying soil.     

Relationship between satellite-derived land surface temperatures, arctic vegetation types, and NDVI

Arctic vegetation distribution is largely controlled by climate, particularly summer temperatures. Summer temperatures have been increasing in the Arctic and this trend is expected to continue. Arctic vegetation has been shown to change in response to increases in summer temperatures, which in turn affects arctic fauna, human communities and industries. An understanding of the relationship of existing plant communities to temperature is important in order to monitor change effectively. In addition, variation along existing climate gradients can help predict where and how vegetation changes may occur as climate warming continues. In this study we described the spatial relationship between satellite-derived land surface temperature (LST), circumpolar arctic vegetation, and normalized difference vegetation index (NDVI). LST, mapped as summer warmth index (SWI), accurately portrayed temperature gradients due to latitude, elevation and distance from the coast. The SWI maps also reflected NDVI patterns, though NDVI patterns were more complex due to the effects of lakes, different substrates and different-aged glacial surfaces. We found that for the whole Arctic, a 5 °C increase in SWI along the climate gradient corresponded to an increase in NDVI of approximately 0.07. This result supports and is of similar magnitude as temporal studies showing increases of arctic NDVI corresponding to increases in growing season temperatures over the length of the satellite record. The strongest positive relationship between NDVI and SWI occurred in partially vegetated and graminoid vegetation types. Recently deglaciated areas, areas with many water bodies, carbonate soil areas, and high mountains had lower NDVI values than predicted by SWI. Plant growth in these areas was limited by substrate factors as well as temperature, and thus is likely to respond less to climate warming than other areas.     

基于MODIS植被指数估算青海湖流域植被覆盖度研究

将MODIS数据合成的4种植被指数作为输入参数,采用像元二分模型对研究区的植被覆盖度进行估算,利用2006年的TM数据解译结果和2011年8月的野外实测数据对反演结果进行验证。结果显示:采用ND-VI估算的植被覆盖度比较符合研究区实地状况,样点估算精度达到87.13%;其他3种植被指数估算的植被覆盖度值比实际值低,尤其是对该区域典型植被草原草甸的覆盖度估算结果明显偏低。研究表明:2011年8月青海湖流域植被覆盖度以中高覆盖度为主,占整个流域面积的57%以上;植被覆盖度在空间上呈中部高、西北低的分布特点。     

塔里木河中游植被指数空间数据库设计

受环境因素与人类活动的影响,塔里木河中游地区近年植被长势及分布变化较大,通过对植被的动态监测分析,可为塔里木河生态保育对策的制定及植被保护研究提供科学依据.本文采用面向对象的Geodatabase模型,使用地理信息系统（GIS）对空间、属性数据的管理分析功能,以塔里木河中游为研究区,选取通过遥感图像处理平台ENVI计算得到的2000、2006、2010、2015年四期归一化植被指数（NDVI）为研究数据,通过使用ArcGIS对NDVI进行空间分布特征研究,设计出一种塔里木河中游植被指数空间数据库,以实现空间、属性数据的存储管理一体化.该植被指数空间数据库能直观的反映出研究区植被变化及生长情况.     

基于遥感的黑河流域植被物候空间格局提取分析

植被物候的检测对于认识自然季节现象的变化规律,服务农作物生产、全球变化、生态学应用方面具有重要价值。植被指数是描述植被数量、质量、植被长势和生物量指标的重要参数。利用SPOT VEGETATION NDVI时间序列数据,采用Savitzky-Golay滤波方法重建了NDVI的年内变化序列,并利用此数据提取了黑河流域植被物候空间分布格局。结果表明,采用此方法得到的植被物候信息和该区域的农事历信息符合较好。黑河流域植被物候具有明显的空间格局。上游的高寒草地区生长季长度较短。中游地区受人类活动影响严重,较为符合该区农作物生长信息。     

Observation of flooding and rice transplanting of paddy rice fields at the site to landscape scales in China using VEGETATION sensor data

A unique physical feature of paddy rice fields is that rice is grown on flooded soil. During the period of flooding and rice transplanting, there is a large proportion of surface water in a land surface consisting of water, vegetation and soils. The VEGETATION (VGT) sensor has four spectral bands that are equivalent to spectral bands of Landsat TM, and its mid-infrared spectral band is very sensitive to soil moisture and plant canopy water content. In this study we evaluated a VGT-derived normalized difference water index (NDWI VGT =(B3-MIR)/ (B3+MIR)) for describing temporal and spatial dynamics of surface moisture. Twenty-seven 10-day composites (VGT- S10) from 1 March to 30 November 1999 were acquired and analysed for a study area (175 km by 165 km) in eastern Jiangsu Province, China, where a winter wheat and paddy rice double cropping system dominates the landscape. We compared the temporal dynamics and spatial patterns of normalized difference vegetation index (NDVI VGT ) and NDWI VGT . The NDWI VGT temporal dynamics were sensitive enough to capture the substantial increases of surface water due to flooding and rice transplanting at paddy rice fields. A land use thematic map for the timing and location of flooding and rice transplanting was generated for the study area. Our results indicate that NDWI and NDVI temporal anomalies may provide a simple and effective tool for detection of flooding and rice transplanting across the landscape.     

基于NDVI序列影像的植被覆盖变化研究

归一化植被指数NDVI是地表植被覆盖特征的重要指标之一。以新疆石河子地区2003~2006年MODIS遥感数据反演的NDVI时间序列影像为例,分析研究了植被长势的年内和年际变化,将植被长势的年内变化和年际变化分为比前一年(月)好、比前一年(月)稍好、与前一年(月)持平、比前一年(月)稍差和比前一年(月)差5个等级,得到年内和年际间植被长势的动态分布图,从植被长势分布图中NDVI的变化可以看出年际和年内植被长势的变化。并应用变化矢量分析法对2003~2006年石河子地区NDVI的变化强度进行了分析,获得了植被覆盖变化强度分布情况,研究结果表明4 a内石河子地区植被覆盖未发生大的变化,植被系统基本稳定。