测量的区域土地覆盖格局研基于多尺度遥感究

 利用1km、4km和8km 3种空间分辨率的NOAA/AVHRR数字影像,对中国NECT样带西部地区进行了土地覆盖分类及其景观特征的比较研究。重点比较了几种空间分辨率遥感数据分类结果边界的一致性和空间差异,以及影像所记录的景观格局的差异。为进一步在不同尺度上研究景观变化过程以及尺度转换研究奠定了基础。研究表明：3种空间分辨率的遥感影像所反映的区域土地覆盖的宏观空间格局是一致的,但类型的边界、每一类型斑块的形状和数量均产生较大的差异;经过对反映景观空间结构的4种指标（分维数、破碎度、多样性、优势度）的比较显示出随着遥感影像空间分辨率的变化,影像所反映的景观结构发生了较大的变化。其中,各覆盖类型的分维数表现出最大差异,表征着空间分辨率的变化对斑块复杂程度的影响最大。     

测量的区域土地覆盖格局研基于多尺度遥感究

利用1km、4km和8km 3种空间分辨率的NOAA/AVHRR数字影像,对中国NECT样带西部地区进行了土地覆盖分类及其景观特征的比较研究。重点比较了几种空间分辨率遥感数据分类结果边界的一致性和空间差异,以及影像所记录的景观格局的差异。为进一步在不同尺度上研究景观变化过程以及尺度转换研究奠定了基础。研究表明：3种空间分辨率的遥感影像所反映的区域土地覆盖的宏观空间格局是一致的,但类型的边界、每一类型斑块的形状和数量均产生较大的差异;经过对反映景观空间结构的4种指标（分维数、破碎度、多样性、优势度）的比较显示出随着遥感影像空间分辨率的变化,影像所反映的景观结构发生了较大的变化。其中,各覆盖类型的分维数表现出最大差异,表征着空间分辨率的变化对斑块复杂程度的影响最大。     

Fractal geometry: a tool for describing spatial patterns of plant communities

Vegetation is a fractal because it exhibits variation over a continuum of scales. The spatial structure of sandrim, bryophyte, pocosin, suburban lawn, forest tree, and forest understory communities was analyzed with a combination of ordination and geostatistical methods. The results either suggest appropriate quadrat sizes and spacings for vegetation research, or they reveal that a sampling design compatible with classical statistics is impossible. The fractal dimensions obtained from these analyses are generally close to 2, implying weak spatial dependence. The fractal dimension is not a constant function of scale, implying that patterns of spatial variation at one scale cannot be extrapolated to other scales.     

Using a sub-pixel mapping model to improve the accuracy of landscape pattern indices

The assessment of landscape spatial patterns is a key issue in landscape management. Landscape pattern indices (LPIs) are tools appropriate for analyzing landscape spatial patterns. LPIs are often derived from raster land cover maps that are extracted from remotely sensed data through hard classification. However, pixel-based hard classification methods suffer from the mixed pixel problem (in which pixels contain more than one land cover class), making for inaccurate classification maps and LPIs. In addition, LPIs generated by hard classification methods are characterized by grain sizes (the sampling unit sizes) that limit the derived landscape pattern to a certain scale. Sub-pixel mapping (SPM) models can enable fine-scale estimation of the spatial patterns of land cover classes without requiring additional data; hence, this is an appropriate downscaling method for land cover mapping. The fraction images generated by soft classification estimate the area proportion of each land cover class within each pixel, and using these images as input enables SPM models to alleviate the mixed pixel problem. At the same time, by transforming fraction images into a finer-scaled hard classification map, SPM models can minimize the influence of grain size on LPIs calculation. In this research, simulated landscape thematic patterns that can provide different landscape spatial patterns, eight commonly used LPIs and a SPM model that maximizes the spatial dependence between neighbouring sub-pixels were applied to assess the efficiency of deriving LPIs from sub-pixel model maps. Results showed that the SPM model can more precisely characterize landscape patterns than hard classification methods can. Landscape fragmentation, class abundance, the uncertainty in SPM, and the spatial resolution of the remotely sensed data influenced LPIs derived from sub-pixel maps. The largest patch index, landscape division, and patch cohesion derived from remotely sensed data with different spatial resolutions through the SPM model were suitable for inter-comparison, whereas the patch density, mean patch area, edge density, landscape shape index, and area-weighted mean shape index derived from the sub-pixel maps were sensitive to the spatial resolution of the remotely sensed data.     

A cloud-based toolbox for the versatile environmental annotation of biodiversity data

A vast range of research applications in biodiversity sciences requires integrating primary species, genetic, or ecosystem data with other environmental data. This integration requires a consideration of the spatial and temporal scale appropriate for the data and processes in question. But a versatile and scale flexible environmental annotation of biodiversity data remains constrained by technical hurdles. Existing tools have streamlined the intersection of occurrence records with gridded environmental data but have remained limited in their ability to address a range of spatial and temporal grains, especially for large datasets. We present the Spatiotemporal Observation Annotation Tool (STOAT), a cloud-based toolbox for flexible biodiversity–environment annotations. STOAT is optimized for large biodiversity datasets and allows user-specified spatial and temporal resolution and buffering in support of environmental characterizations that account for the uncertainty and scale of data and of relevant processes. The tool offers these services for a growing set of near global, remotely sensed, or modeled environmental data, including Landsat, MODIS, EarthEnv, and CHELSA. STOAT includes a user-friendly, web-based dashboard that provides tools for annotation task management and result visualization, linked to Map of Life, and a dedicated R package (rstoat) for programmatic access. We demonstrate STOAT functionality with several examples that illustrate phenological variation and spatial and temporal scale dependence of environmental characteristics of birds at a continental scale. We expect STOAT to facilitate broader exploration and assessment of the scale dependence of observations and processes in ecology.

In ecology and evolution, processes, data collection, and inference or prediction usually occur at different scales in space and time. This study introduces a cloud-based toolbox for the flexible fusion of biodiversity records with remotely sensed and other environmental information that supports an assessment and accounting of such scale dependencies.     

Spatial leaf distribution and self-thinning exponent of<Emphasis Type="Italic"> Pinus banksiana</Emphasis> and<Emphasis Type="Italic"> Populus tremuloides</Emphasis>

A hypothesis that the pattern of spatial leaf distribution in forest canopies is numerically related to the exponent of the self-thinning relationship in even-aged monocultures was tested by evaluating the crown fractal dimension of Pinus banksiana (jack pine) and Populus tremuloides (quaking aspen) in Wood Buffalo National Park, Canada. Pure species stands that were considered the most dense for a given mean tree size were measured to establish the empirical self-thinning relationships. The value of the self-thinning exponent was estimated as –1.42 with 95% Confidence Interval (CI) (–1.47, –1.36) for Pinus banksiana, and –1.29 with 95% CI (–1.45, –1.14) for Populus tremuloides. For each species the box dimension of spatial leaf distribution was estimated from unit cylinders described by sequentially lowering in forest canopies, horizontal flaps of one of various diameters attached to the top of a height-measuring pole. The box dimension appeared as 1.95 (1.84, 2.06) for Pinus banksiana, and 2.24 (2.05, 2.43) for Populus tremuloides. By assuming that the box dimension is equivalent to the fractal dimension at the inter-population level, the self-thinning exponent was predicted to be –1.53 (–1.62, –1.45) for Pinus banksiana, and –1.33 (–1.45, –1.23) for Populus tremuloides. The empirical exponent was equivalent to that predicted from the box fractal dimension, as judged by the 95% CI of the dimensions. We conclude that spatial patterns of leaf distribution in forest canopies, as being characterized by the box fractal dimension, are closely related to the value of the self-thinning exponent in the dense monocultures of the species we examined.     

辽宁东部山区林地生态分类系统

以数字高程模型和SPOT-5遥感数据为数据源,通过地理信息系统的空间分析,在辽宁东部山区有代表性实验区域内,完成了生态土地类型(ELT)和生态土地类型相(ELTP)两个等级的分类和绘图,构成了生态分类系统(ECS)等级结构中最低的两个层次.实验区域内共得到5种ELT和34种ELTP.ELT的划分以环境特征为基础,表征了植被分布的潜在状况和森林生态系统潜在的生产力.ELTP是对ELT的再划分,是生态分类系统的最小单元,相当于我国林业区划中的小班.ELTP既包含ELT中的环境信息又包含现存植被构成的信息,具有空间精准、生态学含义明确的优点.在森林管理活动中,采用ELTP代替小班可以从景观尺度科学地指导森林经营计划编制,调整森林管理方式,实现对森林生态系统的有效管理.     

Assessing ecological habitat structure from local to landscape scales using synthetic aperture radar

Ecological studies need accurate environmental data such as vegetation characterization, landscape structure and organization, to predict and explain the spatial distribution of biodiversity. Few ecological studies use remote sensing data to assess the biophysical or structural properties of vegetation to understand species distribution. To date, synthetic aperture radar (SAR) data have seldom been used for ecological applications. However, these sensors provide data allowing access to the inner structure of vegetation which is a key information in ecology. The objective of this article is to compare the predictive power of ecological habitat structure variables derived from a TerraSAR-X image, an aerial photograph and a SPOT-5 image for species distribution. The test was run with a hedgerow network in Brittany and assessed the spatial distribution of the forest ground carabid beetles which inhabit these hedgerows. The results confirmed that radar and optical images can be indifferently used to extract hedgerow network and derived landscape metrics (hedgerow density, network grain) useful to explain the spatial distribution of forest carabid beetles. In comparison with passive optical remotely sensed data, VHSR SAR images provide new data to characterize vegetation structure and more particularly hedgerow canopy cover, a variable known to explain the spatial distribution of carabid beetles in an agricultural landscape, but not yet quantified at a fine scale. The hedgerow canopy cover derived from the SAR image is a strong predictor of the abundance of forest carabid beetles at two scales i.e., a local scale and a landscape scale.     

Reconciling the contribution of environmental and stochastic structuring of tropical forest diversity through the lens of imaging spectroscopy

Both niche and stochastic dispersal processes structure the extraordinary diversity of tropical plants, but determining their relative contributions has proven challenging. We address this question using airborne imaging spectroscopy to estimate canopy β‐diversity for an extensive region of a Bornean rainforest and challenge these data with models incorporating niches and dispersal. We show that remotely sensed and field‐derived estimates of pairwise dissimilarity in community composition are closely matched, proving the applicability of imaging spectroscopy to provide β‐diversity data for entire landscapes of over 1000 ha containing contrasting forest types. Our model reproduces the empirical data well and shows that the ecological processes maintaining tropical forest diversity are scale dependent. Patterns of β‐diversity are shaped by stochastic dispersal processes acting locally whilst environmental processes act over a wider range of scales.     

Vegetation structure and greenness in Central Africa from Modis multi-temporal data

African forests within the Congo Basin are generally mapped at a regional scale as broad-leaved evergreen forests, with the main distinction being between terra-firme and swamp forest types. At the same time, commercial forest inventories, as well as national maps, have highlighted a strong spatial heterogeneity of forest types. A detailed vegetation map generated using consistent methods is needed to inform decision makers about spatial forest organization and their relationships with environmental drivers in the context of global change. We propose a multi-temporal remotely sensed data approach to characterize vegetation types using vegetation index annual profiles. The classifications identified 22 vegetation types (six savannas, two swamp forests, 14 forest types) improving existing vegetation maps. Among forest types, we showed strong variations in stand structure and deciduousness, identifying (i) two blocks of dense evergreen forests located in the western part of the study area and in the central part on sandy soils; (ii) semi-deciduous forests are located in the Sangha River interval which has experienced past fragmentation and human activities. For all vegetation types enhanced vegetation index profiles were highly seasonal and strongly correlated to rainfall and to a lesser extent, to light regimes. These results are of importance to predict spatial variations of carbon stocks and fluxes, because evergreen/deciduous forests (i) have contrasted annual dynamics of photosynthetic activity and foliar water content and (ii) differ in community dynamics and ecosystem processes.     

Assessing canopy health of native eucalypt forests

Summary   The assessment of forest health is an essential part of the monitoring of ecological sustainability in managed native forests. In Australia, unfortunately, very limited quantitative information on forest health is actually obtained for management and reporting purposes. In this article, we summarize current approaches used in Australia to assess native forest health and some recent developments in the application of remotely acquired digital imagery for classifying canopy health. In a recent study examining Bell miner associated dieback (BMAD), high-resolution airborne imagery was successfully manipulated to present severity categories for BMAD affected canopy. The potential of remotely sensed imagery lies not in map production but in the statistical modelling capacity of this spatial information, particularly when added to climatic and terrain-based spatial data sets. There are several statistical approaches to modelling these spatial datasets and in this article, we discuss our approach to producing a preliminary BMAD model. The importance of ground-based assessments is also emphasized and we recommend tree crown condition as a key health attribute for the spatial modelling of forests. Although significant progress has been made in the application of remote sensing technologies, the structural complexity of native forests means that there are still technical issues that require resolving before this approach becomes operationally routine.     

不同尺度下城市景观综合指数的空间变异特征研究

在GIS与RS技术支持下,采用5 m分辨率的SPOT遥感图像数据,从城市土地利用角度,利用半变异函数对不同尺度的景观多样性、聚集度与分维数的空间变异进行了定量分析.结果表明,不同尺度下3种指数的空间变异具有相似特征,各个尺度上都具有空间依赖性,尺度越小,空间依赖性越大,空间变异的细节更显著,空间自相关性对总体变异的贡献逐渐增加,但尺度过小,有时会破坏景观内部结构.不同指数的半变异函数模型在相同尺度上差异显著,说明不同景观指数在不同尺度下的半变异函数模型不具可比性.就研究上海市内部土地利用结构而言,1 km的幅度是较合适的空间尺度.景观指数空间变异特征是尺度的函数,尺度对景观格局的影响不能忽视.景观综合指数对尺度响应的生态过程揭示了上海城市空间结构的规律性:在小尺度上的复杂无规律性,中尺度上的多中心性和大尺度上的圈层结构性,但各个尺度是相互依赖的,没有绝对界限.     

天然黄山松种群格局的分形特征——计盒维数与信息维数

采用计盒维数和信息维数对屏南和寿宁不同群落的天然黄山松(Pinus taiwanensis)种群格局的分形特征进行比较分析.结果表明,天然黄山松种群格局具有分形特征,其计盒维数值在1.299 8～1.862 6之间,不同群落的大小次序为Q3>Q1>Q2>Q4>Q7>Q8>Q5>Q6;信息维数值在1.205 7～1.863 7之间,大小次序是Q3>Q1>Q2>Q4>Q8>Q7>Q5>Q6,屏南天然黄山松近纯林黄山松种群的计盒维数和信息维数均高于寿宁混交林,计盒维数定量描述种群占据水平空间的能力和程度,信息维数揭示种群格局强度的尺度变化及个体分布的非均匀程度,分形维数值的高低与群落环境、种群密度、种群在群落中的优势地位、个体的聚集程度及幼树个体数量等相关.黄山松种群格局分形维数随海拔呈现上下波动变化,1 250～1 270 m是更适生的海拔范围.此外,黄山松种群格局的分形特征存在一定的尺度范围,其拐点尺度是分形范围的下限尺度.     

Fine-scale spatial patterns in populations of the clonal moss Hylocomium splendens partly reflect structuring processes in the boreal forest floor

Spatial patterns of important population or individual characteristics are expected to reflect structuring ecosystem processes to the extent that populations with strikingly different spatial patterns most likely have been structured by different processes. Few studies of spatial pattern in plant assemblages, bryophyte assemblages in particular, still exist and pattern has only vaguely been linked with process. In this study we describe fine-scale spatial variation in size and the occurrence of terminated (non-branching) segments in 21 Norwegian populations of the dominant boreal forest moss Hylocomium splendens, in search for general patterns of spatial structure. All Hylocomium splendens segments in the investigated plots were followed for a 10-year period; their size (dry mass, estimated from in situ measurements) and fate (terminated or ramifying) were recorded annually. The spatial structure of size and terminating segments at scales from 0.5 to 16 cm was described for each population as fractal dimension profiles, derived from semi-variograms. For about one half of the populations size and terminating segments could be assigned to a specific spatial pattern, the predicted outcome of one of three main structuring processes: (i) negative spatial dependence (fractal dimension F>3.0) on the scale of individuals (below 2 cm), indicative of negative interactions; (ii) positive spatial dependence (F<3.0) on the scale of individuals, indicative of positive interactions; and (iii) positive spatial dependence on broader (4–8 cm) scales, indicative of structuring by environmental factors or patchy disturbance. Patterns (i) and (iii) were observed both for size and terminated segments more often than expected. Fractal dimension profiles for size obtained separately for each year revealed temporal patterns of spatial structure that tended to be invariant over years. Negative spatial dependence of size, possibly due to large size difference between buried segments and other segments during self thinning, was typical of populations rapidly growing in number. Positive spatial dependence with a range of influence by the spatial process of 4–8 cm was observed in plots with sparse bryophyte cover and high cover of deciduous litter, probably due to accumulation of litter in depressions between shoots or groups of shoots. The main finding of this study is that different populations of the same species in the same type of ecosystem can be spatially structured in different ways. This accords with a model for the studied system as consisting of a mosaic of cells, of spatial extent of a few cm or larger, intergrading in space and temporally dynamic, the population characteristics of each cell being shaped by several structuring processes that vary, temporally and spatially, in their relative importance.     

Assessing edge effect on the spatial distribution of selected forest biochemical properties derived using the Worldview data in Dukuduku forests,South Africa

This work explores the potential of the high‐resolution WorldView‐2 sensor in quantifying edge effects on the spatial distribution of selected forest biochemical properties in fragmented Dukuduku forest in KwaZulu‐Natal, South Africa. Specifically, we sought to map fragmented patches within forested areas in Dukuduku area, using very high spatial resolution WorldView‐2 remotely sensed data and to statistically determine the effect of these fragmented patches on the spatial distribution of selected forest biochemical properties. Edge effects on carbon, LAI and foliar nitrogen were quantified based on the models derived by Omer et al. (IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2015, 8, 4825). Edge effect statistical results on the spatial distribution of carbon, LAI and nitrogen showed significant (α = 0.05) variations with change in distance from fragmented patches (>150 m²). Forest foliar carbon concentrations significantly (p‐value = 0.016) increased from 44.8% to 45.3% with increasing distance (25–375 m) from fragmented patches. A similar trend was observed for LAI. Nevertheless, for nitrogen the results show that its concentration significantly (p = 0.016) decreased with increase in distance from the fragmented patches. Overall, the findings of this work underscore the invaluable potential and strength of WorldView‐2 data set in assessing edge effect on the spatial distribution of selected forest biochemical properties.     

Integrating vegetation field surveys with remotely sensed data

Summary   This paper explores data compatibility issues arising from the assessment of remnant native vegetation condition using satellite remote sensing and field-based data. Space-borne passive remote sensing is increasingly used as a way of providing a total sample and synoptic overview of the spectral and spatial characteristics of native vegetation canopies at a regional scale. However, integrating field-collected data often not designed for integration with remotely sensed data can lead to data compatibility issues. Subsequent problems associated with the integration of unsuited datasets can contribute to data uncertainty and result in inconclusive findings. It is these types of problems (and potential solutions) that form the basis of this paper. In other words, how can field surveys be designed to support and improve compatibility with remotely sensed total surveys? Key criteria were identified for consideration when designing field-based surveys of native vegetation condition (and other similar applications) with the intent to incorporate remotely sensed data. The criteria include recommendations for the siting of plots, the need for reference location plots, the number of sample sites and plot size and distribution, within a study area. The difficulties associated with successfully integrating these data are illustrated using real examples taken from a study of the vegetation in the Little River Catchment, New South Wales, Australia.     

莲花山主要森林群落空间格局的分形特征

应用信息维数对莲花山主要森林群落的空间格局进行了研究.结果表明:森林群落的格局强度尺度变化程度由高至低的次序为:岷江冷杉一糙皮桦一白桦群落(Q4)1.84＞云杉-紫果云杉-糙皮桦群落(Q2)1.53＞岷江冷杉群落(Q3)1.14＞紫果云杉-云杉-岷江冷杉群落(Q7)1.10＞华山松群落(Q5)0.99＞岷江冷杉人工林(Q1)0.82＞辽东栎群落(Q6)0.45;群落格局信息维数的差异反映了更新状况的差异,揭示出群落个体分布的非均匀性状况.综合3种分形维数,确定各亚高山寒温性森林群落生长与更新状况的次序为Q4＞Q2＞Q3＞Q7＞Q5＞Q1＞Q6.各群落总体平均记盒维数为1.76,关联维数为1.71,信息维数为1.12;各森林群落生长状况较好,个体聚集程度较低,更新状况一般.分形维数谱将不同森林群落的空间结构特征明确区分开来.     

Predicting krill swarm characteristics important for marine predators foraging off East Antarctica

Open ocean predator‐prey interactions are often difficult to interpret because of a lack of information on prey fields at scales relevant to predator behaviour. Hence, there is strong interest in identifying the biological and physical factors influencing the distribution and abundance of prey species, which may be of broad predictive use for conservation planning and evaluating effects of environmental change. This study focuses on a key Southern Ocean prey species, Antarctic krill Euphausia superba, using acoustic observations of individual swarms (aggregations) from a large‐scale survey off East Antarctica. We developed two sets of statistical models describing swarm characteristics, one set using underway survey data for the explanatory variables, and the other using their satellite remotely sensed analogues. While survey data are in situ and contemporaneous with the swarm data, remotely sensed data are all that is available for prediction and inference about prey distribution in other areas or at other times. The fitted models showed that the primary biophysical influences on krill swarm characteristics included daylight (solar elevation/radiation) and proximity to the Antarctic continental slope, but there were also complex relationships with current velocities and gradients. Overall model performance was similar regardless of whether underway or remotely sensed predictors were used. We applied the latter models to generate regional‐scale spatial predictions using a 10‐yr remotely‐sensed time series. This retrospective modelling identified areas off east Antarctica where relatively dense krill swarms were consistently predicted during austral mid‐summers, which may underpin key foraging areas for marine predators. Spatiotemporal predictions along Antarctic predator satellite tracks, from independent studies, illustrate the potential for uptake into further quantitative modelling of predator movements and foraging. The approach is widely applicable to other krill‐dependent ecosystems, and our findings are relevant to similar efforts examining biophysical linkages elsewhere in the Southern Ocean and beyond.     

遗传算法支持下土地利用空间分形特征尺度域的识别

针对土地利用空间分形特征只存在于有限尺度域的现象,采用无标度区内离散点拟合的离差平方和平均值最小作为目标函数,提出了一种基于遗传算法的土地利用空间分形特征尺度域的识别方法,用于准确计算分形维数的有效区间范围。以武汉市武昌区水域空间分形特征为例,利用Quickbird多光谱遥感影像提取土地利用空间信息,重点讨论了基于遗传算法识别土地利用空间分形特征尺度域范围的总体思路、适应度函数和遗传算子等环节;然后分别从测定系数、标准差和无标度区间3个角度,将其同人工判断法、相关系数法以及强化系数法进行对比讨论;并结合研究区域实际的水域空间分布格局,分析不同方法计算所得半径维数的合理性。结果表明,土地利用分形特征尺度域的范围对分形维数计算结果有较大影响;相对于传统计算方法来说,遗传算法在尺度无标度区间识别上具有更高的精度,可以为土地利用空间格局分形特征的研究提供客观指导意见。     

植被演替过程中种群格局动态的分形分析

该文根据“空间代替时间”的原则和对马尾松(Pinus massoniana)种群的重要值-平均胸径的变动趋势的分析,确定5个森林群落为广东省黑石顶自然保护区森林群落演替的一个时间序列;并在此基础上,运用分形理论的计盒维数和信息维数,对演替过程中马尾松种群空间格局的动态进行了分形分析。结果表明,马尾松种群的计盒维数和信息维数2个参数值均呈递减趋势,与其个体数、重要值变动趋势一致。在群落的演替过程中,马尾松种群的空间占据能力不断下降,种群呈衰退趋势。随其在群落中的优势地位逐渐被其它种群取代,群落将由以马尾松占绝对优势的单优群落演替为多优常绿阔叶林群落。分析结果同时表明,分形分析是群落演替过程中种群空间格局动态研究的有效方法,分形维数则能反映种群格局的尺度变化规律。