基于小波变换的武夷山自然保护区NDVI与地形因子多尺度空间相关分析

以武夷山自然保护区为研究区域,用海拔、坡度、坡向和NDVI作为地形和植被景观变量,研究了地形-植被关系的尺度依赖性问题;利用小波分析工具,分别构建地形、植被因子在不同尺度上的小波方差图,然后利用小波系数计算NDVI和地形因子相关性.结果表明:武夷山自然保护区内NDVI及其地形因子均存在至少2个清晰的尺度结构,并且均是较大尺度上的小波方差更大,地形-植被二者存在的较小尺度区间比较一致,而较大的尺度区间略有差异;地形因子在中高尺度上与NDVI的相关性更强,反映了地形因子作为大的宏观制约因素对NDVI起作用;坡度和坡向与NDVI的相关性随尺度变化规律复杂并且波动性非常大.本研究有助于揭示自然保护区境内地形.植被多尺度复杂相关关系,同时也表明小波分析为揭示自然要素的多尺度空间结构提供了强有力的工具.     

基于小波变换的土壤有机碳与其影响因子多尺度相关分析

基于GIS,采用小波变换和相关分析方法,以广东山区表层(0～20 cm)土壤有机碳密度及其影响因子(包括归一化植被指数NDVI、海拔、坡度和坡向)作为分析对象,选取4条样带,使用一维离散小波变换对分析对象进行多尺度分解,在栅格尺度上定量分析土壤有机碳密度与其影响因子相关关系的多尺度响应特征.结果表明: 研究区土壤有机碳密度与其影响因子具有不同程度的尺度相关性.NDVI在2、8和16 km尺度、海拔在8和16 km尺度下的控制作用最强;坡度的控制作用极弱,尺度相关性不显著;坡向在大于2 km尺度表现为随尺度增加而增大的负相关作用.不同样带的土壤有机碳密度受不同影响因子的制约,NDVI和海拔是影响广东山区土壤有机碳密度分布的主要因子,坡度和坡向仅在个别样带、较大尺度上起作用.     

基于空间小波变换的生态地理界线识别与定位

为了提高生态地理分界线识别和定位的客观性,探讨了通过空间小波变换获取多尺度模极大值定位过渡带的方法.以NDVI和降水作为小波多尺度分解的对象,应用db3小波核函数分别对49条样带的模极大值进行了多尺度检测,并在GIS中确定其地理坐标.研究结果表明:识别半干旱半湿润生态地理分界线的最佳空间尺度为20～40 km,小于这一尺度定位过程容易受到局部地表覆被因素如城市区域或地形的影响,大于这一尺度由于要素被过度平滑,造成定位不准;从定位点的聚集度分析,NDVI的定位效果好于降水,特别是在较大空间尺度上.而与综合自然地理区划方案中的半干旱半湿润分界线比较,从定位点的方向性、平均最短距离以及均衡度三项指标综合判断,小波变换对于降水过渡带的定位优于对NDVI的定位.研究证实,空间小变换与GIS结合是提高生态地理分界线识别与定位科学性的重要途径,是对专家系统划分界线方法的有力补充和完善.     

云南纵向岭谷区道路网络对生态系统影响的尺度效应

云南纵向岭谷区具有复杂的生态系统,其生物多样性在全球中具有重要地位,但是由于人类活动的影响,尤其是道路网络的发展及其导致的土地利用变化,使得该地区生态系统退化日益严重.选取2km×2km、4km×4km、6km×6km、… \,20km×20km网格进行多尺度相关分析和方差分析,研究云南纵向岭谷区道路网络与生态系统分布的相关性及其独立和交互作用,分析道路网络对生态系统影响的尺度效应.然后又进一步研究了道路网络和地形因子(比如海拔、坡度和坡向等)对生态系统的独立和交互作用.研究结果表明,道路网络与生态系统分布的相关性与路网等级有关,其相关程度与路网等级呈反比,随着尺度的变化,道路网络与生态系统分布的相关性表现为增强型、减弱型、质变型和无尺度效应这4种类型.在大多数尺度下,道路网络和地形因子对生态系统分布既有独立作用,也有交互作用.其中,高等级路网的独立作用比较显著,而低等级路网的独立作用不太显著.但是,随着尺度的增大,县乡路网、乡村路网和小路网对生态系统分布的独立和交互作用均显著,且表现出高度的相似性,表明地形对低等级道路具有明显的干扰或屏蔽效应.     

山地森林样带植被-环境关系的多尺度研究

为了评价和比较地形和其它“直接”环境因子对植被变化影响的大小 ,通过调查一条亚热带山地森林样带及其生境因子 ,分析不同层次植被的水平格局 ;并利用多元回归和 DCCA方法比较了诸生境因子对植被格局变化的影响及其与分析尺度相关的变化。结果表明 :( 1 )影响乔木、灌木和草本层植被格局变化的首要因子都是地形特征 ;最重要的土壤因子是土壤发生层厚度。在对林下物种构成的影响方面 ,坡向和坡度的作用大于林冠空隙度。 ( 2 )除坡向外 ,其它地形因子之间存在不同程度的相关性 ;林冠孔隙度和土壤理化属性分别与不同的地形特征显著相关 ,显示了地形对林隙干扰和土壤侵蚀过程的控制。乔、灌、草的覆盖度是生境条件的综合反映 ;它们与非生物因子的相关性显示了成熟林下灌木和草本层物种生态习性的整体差异。 ( 3)各分析尺度上诸生境因子间的相关关系基本稳定。但随尺度增大 ,生境的小尺度异质性被平滑掉。诸因子之间的相关显著性程度逐渐降低。 ( 4 )从 5× 5 m2到 5× 4 0 m2 ,立地因子对乔、灌、草 3层植被变化的解释量随尺度的倍增而接近成倍增长 ;但其主要原因是样方数量增加 ;分析尺度变化的影响小得多。 ( 5 )地形与土壤、光照等直接生境因子对植被格局解释量之和相当。但在不同尺度上 ,地形特征都是     

小波分析方法在心叶驼绒藜(Ceratoides ewersmanniana)空间格局尺度推绎研究中的应用

以古尔班通古特沙漠南缘莫索湾沙地选取相隔15km的两个200m×200m样地,以建群种心叶驼绒藜(Ceratoides ewersmanniana)及其生境地形为研究对象,应用小波分析定量研究了多尺度上空间格局的推绎以及空间异质性、空间格局依赖于尺度的变化关系。研究发现：小波分析尺度由1(5m)变化到4(20m)时,两个样地小尺度上的异质性和格局被合并到更大的尺度上,当小波分析的尺度大于等于5(25m)时,两个样地的格局变化平稳,对应地形（丘顶、丘坡、丘底）的基频稳定在110m左右,心叶驼绒藜的数量动态变化周期稳定在115～125m之间。结果表明：小波分析对信号整体特征的提取作用实现了小尺度上的信息到大尺度上的聚合。结合小波分析对信号突变点的检测,利用位置方差检验局部空间异质性程度,发现位置方差将大尺度上的格局分解到每个取样小样方,位置方差最大的地点对应的异质性也最强,实现了大尺度上的信息到小尺度上的分解。总结认为应用小波分析可以实现对空间格局的尺度推绎,具有对植被、环境的分布格局以及异质性有双重度量作用,由小波系数以及由其衍生的小波方差、位置方差来实现这种度量,图形表现直观,优越性明显。     

小波分析方法在心叶驼绒藜(Ceratoides ewersmanniana)空间格局尺度推绎研究中的应用

以古尔班通古特沙漠南缘莫索湾沙地选取相隔15km的两个200m×200m样地,以建群种心叶驼绒藜(Ceratoides ewersmanniana)及其生境地形为研究对象,应用小波分析定量研究了多尺度上空间格局的推绎以及空间异质性、空间格局依赖于尺度的变化关系。研究发现:小波分析尺度由1(5m)变化到4(20m)时,两个样地小尺度上的异质性和格局被合并到更大的尺度上,当小波分析的尺度大于等于5(25m)时,两个样地的格局变化平稳,对应地形(丘顶、丘坡、丘底)的基频稳定在110m左右,心叶驼绒藜的数量动态变化周期稳定在115～125m之间。结果表明:小波分析对信号整体特征的提取作用实现了小尺度上的信息到大尺度上的聚合。结合小波分析对信号突变点的检测,利用位置方差检验局部空间异质性程度,发现位置方差将大尺度上的格局分解到每个取样小样方,位置方差最大的地点对应的异质性也最强,实现了大尺度上的信息到小尺度上的分解。总结认为应用小波分析可以实现对空间格局的尺度推绎,具有对植被、环境的分布格局以及异质性有双重度量作用,由小波系数以及由其衍生的小波方差、位置方差来实现这种度量,图形表现直观,优越性明显。     

地形因子对森林景观格局多尺度效应分析

以TM影像和野外调查为数据源,3S技术为研究手段,分析了泰山的森林景观结构动态变化以及景观格局沿高程的分异。选择相对高差较大的区域设计了8个地形方位,采用3种由连续样方组成的辐射状样带,在遥感影像上进行信息采集,研究地形对森林景观格局的多尺度效应,分析了不同地形因子对森林景观分异的影响。结果表明,在景观尺度上,地形方位、海拔、山地类型是影响森林景观镶嵌格局的控制因素,坡向、坡度是重要因素,坡形、坡位是不明显因素。以TM影像为信息源,从森林景观分异和梯度分析上,首先要考虑海拔坡向指数、坡形坡位指数和海拔,并立足于地形方位。地形主要因子间存在着稳定的显著正相关,为森林分异多尺度格局提供了较强的综合解释能力。     

多尺度上的多物种多格局——以莫索湾沙漠四种灌木及其生境为例

植物的生长固然与自身特性有关,也与其生境中环境要素及其它物种相互作用相互影响,牵涉到生物格局、环境格局和景观格局的相互作用,已有研究表明,这种作用具有多尺度特性.量化这3种格局的某些重要特征,将有利于理解这种尺度行为对格局的影响,甚至量化格局在多尺度上的一些特性.在古尔班通古特沙漠南缘莫索湾沙地选取相隔15km的两个200m×200m样地,以心叶驼绒藜(Ceratoides ewersmanniana)、梭梭(Haloxylon ammodendron)、琵琶柴(Perosimonia soongorica)和沙拐枣(Calligonum mongolicum)及其生境地形和土壤理化性质为研究对象,联合小波分析(WAA)、点格局分析(PPA)和典范对应分析(CCA)研究莫索湾沙漠4种灌木种内的聚集性(成丛性)及其周期性、种间相互作用、边缘效应及其与生境地形和土壤理化性质的关系,发现表观上沙生植物分布非连续,但是可形成25～80m尺度范围的成丛性分布,且周期性出现,心叶驼绒藜周期为115～125m、梭梭周期为130～140m,研究表明,周期为110m的地形基频是植物成丛性周期形成的主因.琵琶柴和沙拐枣虽成丛分布,但未发现其周期,其周期可能在更大的幅度上存在;其次,东西方向的边缘量化检测结果表明:东西方向也存在功能边缘和结构边缘,不像南北边缘的位置是受到太阳辐射和遮阴作用影响,东西边缘的位置却是受到了垄状沙丘大小和地形的影响;再次,种间关系研究发现:4种灌木相互都是负相关,且在大多数尺度上是显著负相关.结果表明:荒漠植物通过成丛或聚集分布可以形成适合本物种生存的局部微生境.     

空间尺度对地形异质性-物种多样性关系的影响:粒度和幅度

空间尺度是影响我们理解生态学格局和过程的关键因素。目前已有多种关于物种多样性分布格局形成机制的假说且研究者未达成共识,原因之一是空间尺度对物种多样性分布格局的环境影响因子的解释力和相对重要性有重要影响。地形异质性是物种多样性分布格局的重要影响因素。本文综述了在地形异质性-物种多样性关系的研究中,不同空间粒度和幅度对研究结果的影响,以及可能的原因。尽管已认识到地形异质性-物种多样性关系的空间尺度效应,但粒度和幅度的具体影响仍未有统一结论。当前物种多样性分布格局研究未能覆盖较完整的尺度变化梯度。未来对地形异质性-物种多样性关系的研究需要同时考虑幅度和粒度的影响。建议结合可靠的模型和统计分析方法开展多尺度格局比较分析,以进一步阐明研究尺度对地形异质性-物种多样性关系的影响以及地形异质性起主导作用的空间尺度。     

广东山区土壤有机碳空间变异的尺度效应

研究土壤有机碳的尺度效应能够为区域生态环境保护和确定合理的土壤取样间距提供科学依据。采用土壤类型法估算了广东山区表层(0-20 cm)和全剖面(0-100 cm)土壤有机碳密度,选择4条采样带,获取采样间距为250 m的土壤有机碳密度序列,并利用离散小波变换工具对其进行多尺度分解,得到2×250 m、2²×250 m、2³×250 m、2⁴×250 m、2⁵×250 m和2⁶×250 m 6个分解尺度上的小波信息,计算小波信息方差。结果表明:土壤有机碳密度具有较强的空间异质性,其空间异质性的大小受控于不同尺度下土壤有机碳密度分布格局的主导因子影响程度;整体上在大于等于1 km的尺度,其空间异质性较强;各个样带特征尺度的差异与各样带的土壤和植被类型、地貌特征以及土地利用方式、耕作管理方式等人类活动干扰强度有关。     

Spatial relationships between NDVI and topographic factors at multiple scales in a watershed of the Minjiang River,China

Improvement in vegetation cover in the upper reaches of the Minjiang River protects major freshwater sources and constructs ecological barriers in the upstream of Yangtze River located in southwest China. However, the spatially varying relationships between normalized difference vegetation index (NDVI) and topographic factors at multiple scales remain unclear. In this study, the two-dimensional discrete wavelet transform (2D-DWT) and geographically weighted regression (GWR) were combined to build a framework for examining the complex spatial relationships between NDVI and topographic factors at multiple scales. Based on the gridded datasets of NDVI and digital elevation model (DEM) of a small watershed located in the upper reaches of the Minjiang River situated in southwest China, the influence of topographic factors on NDVI variation in each grid and which topographic variables correlated most with the NDVI at each location were analyzed in this study. The grid data were decomposed into smooth and detail components using 2D-DWT. The results revealed that elevation, slope, and aspect exhibited different scale effects on NDVI in different wavelet components. In the smooth components, the spatial correlation of NDVI with elevation, slope, and south-facing index (SFI) of aspect increased with the decomposition scale, whereas topographic factors had different degrees of influence on NDVI. Elevation was found to be the most important topographic factor that determined the spatial distribution of NDVI on both sides of the valley, and SFI exhibited the highest effect on NDVI when elevation was higher than 2500 m. In the detail components, the spatial distribution of the most important topographic factor affecting the NDVI was not evident at a smaller scale, whereas it became obvious at 480 m scale. SFI was found to be more important than elevation and slope at a larger scale. These results will help in understanding the complex relationship between NDVI and topographic factors and determining the appropriate topographic location for ecological restoration.     

中国东北地区主要植被类型NDVI变化与气候因子的关系

利用1982～1992年时间序列的NOAA/AVHRR8km×8km分辨率的归一化植被指数（Normalizeddifferencevegetationindex,NDVI）,将东经120°～135°、北纬40°～55°区域的土地覆盖类型分为10类。然后研究了各类型的NDVI年平均值的变化规律。结合该地区的19个气象站1982～1992年的年平均气温、年最高温度、年最低温度、年降水量和年相对湿度研究了各类型NDVI年平均值的变化与气候因子之间的关系,进一步阐明了气候因子是NDVI动态变化的主要原因。     

Multi-Scale Identification of Urban Landscape Structure Based on Two-Dimensional Wavelet Analysis: The Case of Metropolitan Beijing,China

Scale dependence is one of the major characteristics of landscape. Urban landscape is highly affected by human activities with a multi-scale structure, which makes the multi-scale identification of urban structure an obligation for urban spatial studies. Although there have been many previous studies on urban landscape structure, most of them have been conducted on a single scale, and the multi-scale effects of landscape patterns were rarely involved. Two-dimensional wavelet transforms can link spatial structures to scale and spatial locations, and maybe an effective method for the multi-scale analysis of landscape. In this paper, we applied two-dimensional discrete wavelet transform and wavelet variance to analyze the multi-scale spatial structure characteristics and the nested hierarchical structure of the metropolitan Beijing area. The results indicated that the spatial distribution and configuration of the patches were highly scattered at small scales, and the urban landscape exhibited a relatively complicated structure. At medium scales, a combination of the polycentric and sectorial structure was identified due to the prominence of dominant patches within each administrative district. At larger scales, the urban landscape pattern exhibits typical concentric ring characteristics. Two characteristic scales were detected by the wavelet variance in the south-north direction of the main urban zones, scale 4 (112m) and 8 (1792m) in Dongcheng District, scale 3 (56m) and 6 (448m) in Xicheng District, which were corresponding to the extent of middle-small blocks and large blocks respectively. One characteristic scale was detected in each of the suburb areas (Chaoyang, Haidian, and Fengtai District). The spatial structure of the main urban zones is more complex than that of the suburb areas, and it presents a typical hierarchical structure in the south-north direction. In general, the spatial structure of Beijing metropolitan area appears polycentric and concentric ring structure at large scales, the main urban area has nested hierarchies at different characteristic scales, and the wavelet method can effectively identify multi-scale characteristics of urban spatial structure.     

Spatial pattern of non-stationarity and scale-dependent relationships between NDVI and climatic factors—A case study in Qinghai-Tibet Plateau,China

Spatial non-stationarity and scale-dependence are important characteristics of the relationship between NDVI and climatic factors. To improve the reliability of model prediction, it is necessary to find the scales and spatial heterogeneity in which a stationary relationship is reached. In this paper, a geographically weighted regression (GWR) model was developed to define spatial non-stationarity and scale-dependent relationships between NDVI and climatic factors. The results indicate that the spatial scale of the stationary relationship for NDVI and both temperature and precipitation is 156 km over the whole Qinghai-Tibet Plateau. Both modeling performance and the spatial pattern of the GWR model are significantly better than global regression models such as OLS. Significant spatial heterogeneity of regression relationships between NDVI and climatic factors is revealed within the Qinghai-Tibet Plateau. We conclude that the dominant climatic factor influencing NDVI is not the same for all ecoregions within the study area. There are also different key scales of interaction between NDVI and the dominant climatic factor in these various ecoregions. Finally, model performance is different in the each eco-region. Therefore, this finding can provide a scientific basis for choosing a suitable scale and reliable models to solve scale-dependent problems in geography and ecology.     

祁连山南坡主要河谷NDVI时空变化及影响因素分析

为进一步保护祁连山生态环境及合理开发利用河流沿线的植被资源,该文基于MODIS数据的NDVI产品及DEM数据集,对祁连山南坡主要河流谷地2000—2018年植被生长季的NDVI时空分布特征进行了研究,并提取研究区的主要地形因子,分析其对河流谷地植被生长季NDVI的影响。结果表明:随着河流两侧缓冲区距离逐渐增大,各年份的NDVI值呈现先增加后平稳再减少的分布特点;2000—2018年研究区河谷NDVI的变化趋势基本一致,整体表现出2010年出现了近20年的峰值;祁连山南坡河流谷地NDVI值,从斜坡(16°~25°)至急坡(41°~45°)增加的速率最大,说明该区间为NDVI值突变区间。2000—2018年祁连山南坡主要河流谷地的NDVI时空分布,可能受地形、气温和降水等自然因素影响较大,其受人为干扰因素影响较小,其中降水并非影响研究区河谷植被NDVI分布的主导因素,而气温可能是影响研究区河谷植被NDVI分布的主导因素。在地形因子中,存在较适合植被生长的特定坡度区间,且太阳辐射能量的增加有利于植被的生长。     

Integrating ecology with biogeography using landscape characteristics: a case study of subtidal habitat across continental Australia

Aim We aimed to redress a current limitation of local ecological studies (i.e. piecemeal information on specific taxa) by integrating existing ecological knowledge with quantifiable patterns in primary habitat (i.e. composition, distribution and cover) from local to continental scales. By achieving this aim, we sought to provide a biogeographical framework for the interpretation of variation in the ecology of, and threats to, subtidal rocky landscapes. Location The subtidal rocky coast of continental Australia, with longitudinal comparisons spanning > 4000 km of southern coast (115°03′ E–153°60′ E) between latitudes of 33°05′ S and 35°36′ S, and latitudinal comparisons across 26°40′ S to 37°08′ S of eastern Australia. Methods The frequency and size of patches of major benthic habitat were quantified to indicate contemporary function (ecology) and to establish patterns that may result from contrasting regional‐scale processes (biogeography). This was achieved by quantifying the composition and patchiness of key subtidal habitats across the continent and relating them to the known ecology of subsets of locations in each region. A nested design of several spatial scales (1000s, 100s, 10–1 km) was adopted to distinguish patterns at local through to biogeographical scales. Results We show biogeography (in terms of longitude and latitude) to have a fundamental influence on the patterns of abundance and composition of subtidal habitats across regional (1000s of kilometres) to local (10s of kilometres to metres) scales. Across the continent, the most fundamental patterns related to (1) the proportion of rock covered by kelp forests, as related to particular functional groups of herbivores, and (2) the small‐scale heterogeneity (metres) that characterizes these forests. Main conclusions We interpret these results within a framework of alternative processes known to maintain habitat heterogeneity across these regions (e.g. productivity versus consumption as shapers of habitat structure). These interpretations illustrate how regional differences in ecological patterns and processes can create contradictory outcomes for the management of natural resources. We suggest that researchers and managers of natural resources alike may benefit from understanding local issues (e.g. the effects of fishing and its synergies with water pollution) in their biogeographical contexts.