A multiscale framework for landscape analysis: Object-specific analysis and upscaling

Landscapes are complex systems that require a multiscale approach to fully understand, manage, and predict their behavior. Remote sensing technologies represent the primary data source for landscape analysis, but suffer from the modifiable areal unit problem (MAUP). To reduce the effects of MAUP when using remote sensing data for multiscale analysis we present a novel analytical and upscaling framework based on the spatial influence of the dominant objects composing a scene. By considering landscapes as hierarchical in nature, we theorize how a multiscale extension of this object-specific framework may assist in automatically defining critical landscape thresholds, domains of scale, ecotone boundaries, and the grain and extent at which scale-dependent ecological models could be developed and applied through scale.     

Effects of changing scale on landscape pattern analysis: scaling relations

Landscape pattern is spatially correlated and scale-dependent. Thus, understanding landscape structure and functioning requires multiscale information, and scaling functions are the most precise and concise way of quantifying multiscale characteristics explicitly. The major objective of this study was to explore if there are any scaling relations for landscape pattern when it is measured over a range of scales (grain size and extent). The results showed that the responses of landscape metrics to changing scale fell into two categories when computed at the class level (i.e., for individual land cover types): simple scaling functions and unpredictable behavior. Similarly, three categories were found at the landscape level, with the third being staircase pattern, in a previous study when all land cover types were combined together. In general, scaling relations were more variable at the class level than at the landscape level, and more consistent and predictable with changing grain size than with changing extent at both levels. Considering that the landscapes under study were quite diverse in terms of both composition and configuration, these results seem robust. This study highlights the need for multiscale analysis in order to adequately characterize and monitor landscape heterogeneity, and provides insights into the scaling of landscape patterns. This revised version was published online in May 2005 with corrections to the Cover Date. This revised version was published online in July 2006 with corrections to the Cover Date.     

Analysis of landscape pattern change trajectories within areas of intensive agricultural use: case study in a watershed of southern Québec, Canada

This study aimed at capturing the spatial variability of landscape patterns and their trajectories of change from 1950 to 2000 within a watershed, which is representative of areas of intensive agricultural use. After an analysis of landscape features changes for the entire watershed based on aerial photographs, hierarchical clustering analysis provided a typology of landscape patterns for the cadastral lots. Following that, the trajectory of change of each lot was characterized (nature, importance, direction, rate of change). Seven types of landscape patterns are distinguished by the relative importance of different classes of landscape features and 51 trajectories of change were identified for the lots. The analysis shows that although the majority of lots were subjected to a homogenization of their landscape patterns since 1950, this trend is not entirely uniform and that since 2000 it occurs alongside trends towards diversification of certain landscape features on some lots. Furthermore, nearly a third of the lots are not following the main trajectories of change detected. Thus, the results suggest that extrinsic forces (policies, technologies) that are directing main changes in areas of intensive agricultural use toward uniformity could be modulated by internal forces (uses and values of the population). A better understanding of theses internal forces seems crucial to manage landscapes. From a methodology standpoint, although the hierarchical clustering analyses appear useful for understanding the spatial and temporal variability of landscape patterns, particular attention must be given to validating the typology chosen to characterize them.     

Combining farmers’ decision rules and landscape stochastic regularities for landscape modelling

Landscape spatial organization (LSO) strongly impacts many environmental issues. Modelling agricultural landscapes and describing meaningful landscape patterns are thus regarded as key-issues for designing sustainable landscapes. Agricultural landscapes are mostly designed by farmers. Their decisions dealing with crop choices and crop allocation to land can be generic and result in landscape regularities, which determine LSO. This paper comes within the emerging discipline called “landscape agronomy”, aiming at studying the organization of farming practices at the landscape scale. We here aim at articulating the farm and the landscape scales for landscape modelling. To do so, we develop an original approach consisting in the combination of two methods used separately so far: the identification of explicit farmer decision rules through on-farm surveys methods and the identification of landscape stochastic regularities through data-mining. We applied this approach to the Niort plain landscape in France. Results show that generic farmer decision rules dealing with sunflower or maize area and location within landscapes are consistent with spatiotemporal regularities identified at the landscape scale. It results in a segmentation of the landscape, based on both its spatial and temporal organization and partly explained by generic farmer decision rules. This consistency between results points out that the two modelling methods aid one another for land-use modelling at landscape scale and for understanding the driving forces of its spatial organization. Despite some remaining challenges, our study in landscape agronomy accounts for both spatial and temporal dimensions of crop allocation: it allows the drawing of new spatial patterns coherent with land-use dynamics at the landscape scale, which improves the links to the scale of ecological processes and therefore contributes to landscape ecology.     

A general model to quantify ecological integrity for landscape assessments and US application

Increasingly, natural resources agencies and organizations are using measures of ecological integrity to monitor and evaluate the status and condition of their landscapes, and numerous methods have been developed to map the pattern of human activities. In this paper I apply formal methods from decision theory to develop a transparent ecological indicator of landscape integrity. I developed a parsimonious set of stressors using an existing framework to minimize redundancy and overlap, mapping each variable as an individual data layer with values from 0 to 1.0, and then combined them using an “increasive” function called fuzzy sum. A novel detailed land use dataset is used to generate empirical measures of the degree of human modification to map important stressors such as land use, land cover, and presence, use, and distance from roads. I applied this general framework to the US and found that the overall average degree of human modification was 0.375. Regional variation was fairly predictable, but aggregation of these raw values into terrestrial or watershed units resulted in large differences at local to regional scales. I discuss three uses of these data by land managers to manage protected areas within a dynamic landscape context. This approach generates an internally-valid model that has a direct, empirical, and physical basis to estimate the degree of human modification.     

How perceived sensory dimensions of urban green spaces affect cultural ecosystem benefits: A study on Haizhu Wetland Park,China

Research exploring the relationship between human well-being and ecosystem functions by assessing cultural ecosystem benefits (CEBs) is a crucial and emerging field. However, quantifying CEB is challenging due to the lack of a uniform measurement scale. In addition, it is crucial to understand the factors that influence CEBs to enhance ecosystem functions and contribute to human well-being. While physical landscape features have been investigated, there is limited evidence supporting the link between perception-based landscape features and CEBs. Therefore, this study aimed to develop a CEBs measurement scale and investigate the impact of perceived sensory dimensions (PSDs) of urban green spaces (UGSs) on CEBs. We conducted a Public Participation GIS-survey (PPGIS) at Guangzhou National Haizhu Wetland Park. 1473 participants took part in our study and evaluated the CEBs provided by urban green spaces (UGSs). Using SPSS statistics and ArcMap tools, we found that PSDs of UGSs are significantly associated with CEB. Additionally, we confirmed that different levels within a PSD influence the levels of CEBs gained from UGSs. Our results indicate that creating serene, open, and natural UGSs is more effective than incorporating numerous cultural elements. In conclusion, this study introduces PSDs into the framework of CEB, which landscape architects can use to shape the specific environmental characteristics of UGSs and provide the CEBs required to support the well-being of urban populations.     

Modeling dissolved organic carbon in subalpine and alpine lakes with GIS and remote sensing

Current global trends in lake dissolved organic carbon (DOC) concentrations suggest a need for tools to more broadly measure and predict variation in DOC at regional landscape scales. This is particularly true for more remote subalpine and alpine regions where access is difficult and the minimal levels of anthropogenic watershed disturbance allow these systems to serve as valuable reference sites for long-term climate change. Here geographic information system (GIS) and remote sensing tools are used to develop simple predictive models that define relationships between watershed variables known to influence lake DOC concentrations and lake water color in the Absaroka-Beartooth Wilderness in Montana and Wyoming, USA. Variables examined include watershed area, topography, and vegetation cover. The resulting GIS model predicts DOC concentrations at the lake watershed scale with a high degree of accuracy (R ² = 0.92; P ≤ 0.001) by including two variables: vegetation coverage (representing sites of organic carbon fixation) and areas of low slope (0–5%) within the watershed (wetland sites of DOC production). Importantly, this latter variable includes not only surficially visible wetlands, but “cryptic” subsurface wetlands. Modeling with Advanced Land Imager satellite remote sensing data provided a weaker relationship with water color and DOC concentrations (R ² = 0.725; P ≤ 0.001). Model extrapolation is limited by small sample sizes but these models show promise in predicting lake DOC in subalpine and alpine regions.     

Agricultural land-use patterns and soil erosion vulnerability of watershed units in Vietnam’s northern highlands

Since the mid eighties, agricultural development and increased population growth in Vietnam’s northern highlands have modified land use patterns and thus, increased the runoff process and soil degradation induced by water erosion. In the last decade, Vietnamese literature has focused on the computation of soil losses over large areas. Most of these spatial and quantitative soil erosion studies do not consider the impact of agricultural land use diversity (spatial heterogeneity), particularly at the watershed scale, and the annual variability of seasonal landscape factors on soil erosion vulnerability and hence, landscape dynamics. We present an integrated approach combining field measurements and observations, GIS and modeling to determine the spatial and temporal dynamics of soil erosion vulnerability according to watershed units and hence, the impact of physical environment components and agricultural land use patterns on landscape evolution. Tables and graphics showing the cropping systems, the periods within a year, and the watershed units that are most vulnerable are presented. The double cultivation cycles for paddy rice fields not only imply two periods of land preparation and establishment that expose the soil surface to raindrop impacts, but also increased soil management practices that decrease the soil’s resistance to detachment. Despite the low levels of soil management practices for the shifting cultivation system, the near absence of soil conservation practices clearly increases their vulnerability. Hence, rainfed cropping systems, mainly soya and cassava, cultivated on sloping lands (hills and mountains) where soil erosion vulnerability is the highest represent the watershed units which are the most prone to soil loss.     

Landscape planning: a working method applied to a case study of soil conservation

A working method for landscape planning is proposed. There are 11 steps in this method. In step one, an issue (or set of related issues) is identified as posing a problem or an opportunity to people and/or the environment. In step two, a goal (or several goals) is established to address the problem. In steps three and four, ecological inventories and analyses are conducted at two scales, first at the regional level (drainage basins are suggested as an appropriate unit) and then at the landscape level (watersheds are recommended). These inventories and analyses consider human ecology as well as bio-physical processes. Step five involves detailed studies, such as suitability analyses, that link inventory and analysis information to the problem(s) and goal(s). In step six, concepts are developed that lead to a landscape (watershed) master plan in step seven. During step eight, the plan is explained through a systematic educational effort to the affected public. In step nine, detailed designs are developed. In step 10 the plan and designs are implemented. Step 11 involves administering and monitoring the plan. The method is explained through an example of soil conservation planning. The case study was undertaken in the Missouri Flat Creek watershed of the Palouse region in the Pacific Northwest (U.S.A.) to help achieve the goals for erosion control established by the federal Food Security Act of 1985 and state clean water legislation.     

Landscape services as a bridge between landscape ecology and sustainable development

Landscape ecology is in a position to become the scientific basis for sustainable landscape development. When spatial planning policy is decentralised, local actors need to collaborate to decide on the changes that have to be made in the landscape to better accommodate their perceptions of value. This paper addresses two prerequisites that landscape ecological science has to meet for it to be effective in producing appropriate knowledge for such bottom-up landscape-development processes—it must include a valuation component, and it must be suitable for use in collaborative decision-making on a local scale. We argue that landscape ecological research needs to focus more on these issues and propose the concept of landscape services as a unifying common ground where scientists from various disciplines are encouraged to cooperate in producing a common knowledge base that can be integrated into multifunctional, actor-led landscape development. We elaborate this concept into a knowledge framework, the structure–function–value chain, and expand the current pattern–process paradigm in landscape ecology with value in this way. Subsequently, we analyse how the framework could be applied and facilitate interdisciplinary research that is applicable in transdisciplinary landscape-development processes.     

Anthropogenic landscape changes in Central Europe and the role of bioindication

Anthropogenic landscape changes in Central Europe occurred in several stages. Characteristic features include an acceleration in the sequence of changes, a continual increase in the scope and complexity of ecologic problems, growing destabilization of the natural household and a rising proportion of irreversible changes.Various bioindication techniques are excellently suited for detecting and evaluating landscape changes, as reflected in a large number of case studies. Of these, a number are classified by the authors according to the following criteria: landscape features/components, structure of the test area, and time framework for the studies.Thorough changes must be brought about in man's relation with nature to remedy the aggrevated environmental situation, with these priorities: making human thinking and action compatible with the environment, transforming material production along ecological lines, and applying ecological principles to landscape management, for example in the form of landscape planning.     

Quantifying the spatial relationship between bird species’ distributions and landscape feature boundaries in southern Ontario, Canada

Understanding what features of the landscape affect species distribution is critical to effectively implement conservation strategies. This study investigates how a boundary analysis framework can be used to characterize the spatial association between boundaries (i.e., spatial locations of high rates of change) in bird species?? distributions and landscape features at the regional scale. The study area covers 92,000?km² in southern Ontario (Canada) and extends from the Great Lakes-St. Lawrence biome to the southern Canadian Shield biome. Landcover composition was derived from Ontario Land Cover data (1991?C1998; 7 types) and elevation data were derived from the Canada3D digital elevation model. Bird distributions were estimated using indicator kriging based on point counts obtained from the Ontario Breeding Bird Atlas data (2001?C2005; 60 species). Boundaries were delineated for both data types using a 10?×?10?km cell resolution. Spatial boundary overlap statistics were used to quantify the spatial relationship between landscape features and bird boundaries and tested using a randomization procedure. There was significant positive association and spatial overlap between delineated landscape feature boundaries and bird boundaries. The number of spatially overlapping cells between the two boundary types was 67 out of 164 (41?%) and 76?% of cells were within 11.42?km of each other. These results were statistically significant (P?<?0.001) and suggest a strong spatial relationship between high rates of change in landscape features and bird species?? distributions at the regional scale. A boundary analysis framework could be used to identify boundary shifts in response to climate change and anticipate changes in species distributions.     

Communities in context: the influences of multiscale environmental variation on local ant community structure

We explored the ways in which environmental variation at multiple spatial scales influences the organization of ant species into local communities. Ground-dwelling ants were sampled in sandhill habitat at 33 locations throughout northern Florida, USA. Variance partitioning of local, landscape, and regional datasets using partial redundancy analysis indicates that ant community composition is significantly influenced by environmental variability across all scales of analysis. Habitat generalists appear to replace habitat specialists at sites with high proportions of matrix habitat in the surrounding landscape. Conversely, habitat specialists appear to replace habitat generalists at sites with more sandhill habitat in the surrounding landscape and greater amounts of bare ground locally. Local niche differentiation leading to species-sorting, combined with the effects of spatially structured dispersal dynamics at landscape scales, may explain this pattern of community structure. Regional influences on local ant communities were correlated with geographical and environmental gradients at distinct regional scales. Therefore, local ant communities appear to be simultaneously structured by different processes that occur at separate spatial scales: local, landscape, and regional scales defined by spatial extent. Our results illustrate the importance of considering multiscale influences on patterns of organization in ecological communities. Electronic supplementary material The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

Comparative influence of isolation,landscape, and wetland characteristics on egg-mass abundance of two pool-breeding amphibian species

The distribution and abundance of species are shaped by local and landscape processes, but the dominant processes may differ with scale and increasing human disturbance. We investigated population responses of two pool-breeding amphibian species to differences in local and landscape characteristics in suburbanizing, southeastern New Hampshire, USA. In 2003 and 2004, we sampled 49 vernal pools for spotted salamander (Ambystoma maculatum) and wood frog (Lithobates sylvaticus) egg masses. Using egg masses as a proxy for breeding-female population size, we examined the relative influence of five land-use and three isolation variables at two scales (300 and 1000 m) and five wetland variables on egg-mass abundance. For both species, road density at the landscape scale (1000 m) and hydroperiod most strongly predicted egg-mass abundance, with abundance decreasing as roads became denser and hydroperiods shortened. Wetland isolation was also an important predictor, with abundance greatest at more isolated pools, suggesting that both species concentrate at isolated pools when alternative breeding sites are scarce. Surprisingly, no 300-m parameters were strongly associated with salamander egg-mass abundance, whereas several landscape parameters were. In suburbanizing areas, it is at least as important to consider landscape-scale road density as to consider hydroperiod when designing conservation plans for these species. Furthermore, both isolated and clustered pools provide these species important habitat and may require protection. Finally, the conceptual framework for spotted-salamander management must be expanded so that spatial configuration at the landscape scale becomes a regular, integrated component of conservation planning for this species.     

Temporal variation of characteristic scales in urban landscapes: an insight into the evolving internal structures of China’s two largest cities

Urbanization has induced profound landscape changes. While the spatiotemporal patterns of urban landscapes have been extensively studied, the manner by which the internal structures of already urbanized areas change remains little understood. Characteristic scales are an important measure of landscape structure, and they represent the typical spatial extents of landscape elements in hierarchies. In this study, we quantified temporal variations of the characteristic scales in the central urban landscapes of Beijing and Shanghai over an 18?year period. Using transect data from Landsat images, characteristic scales were identified through wavelet analysis and then classified into several discrete domains using the k-means clustering method. These characteristic scale domains appeared to correspond with the typical extents of the blocks and block clusters in the study areas. Results showed that the number of the characteristic scale domains changed within a small range of 3?C5 while the mean values of the characteristic scales within the domains showed substantial temporal variation. Larger characteristic scales were more variable than smaller ones in both cities. Distinguishing relative change rates of building forms, land use and street layout of urban landscapes allowed us to interpret these differences. The street layout of urban landscapes usually reacts slowly to the force of change, acting as the skeleton of the urban landscape. As a result, block sizes can remain relatively stable and corresponding characteristic scales present inheritance features. Land use and building forms are more susceptible to changes. Block clusters with flexible extents could result in significant variation of characteristic scales.     

Landscape changes and ecological studies in agricultural regions,Québec,Canada

Most landscape definitions in the western world are based on soil, climatic, or physiographic features and do not integrate humans as an integral part of the landscape. We present an approach where landscape types have been delineated in southern Québec, Canada based on current land use where anthropogenic and agricultural activities are concentrated as a practical application of the holistic approach in landscape definition. Landsat-TM satellite images were classified and the 27 habitat classes were regrouped into 5 general land cover classes (cash crop, dairy farming, forest, anthropogenic, wetlands) and overlaid onto soil landscape polygons to characterize natural boundary units. Cluster analyses were used to aggregate these polygons into seven agricultural types of land scape forming a gradient from urban and high-intensity cash crop farming activities to landscapes dominated by a mosaic of agriculture and forested areas. Multivariate analyses of raw data and of socio-economic and farming practices variables were used to describe the defined types of landscape and these were projected over three established land classification systems of southern Québec (Canadian ecoregions, North American Bird Conservation Initiative regions and Corn Heat Unit regions) to compare their similarity in terms of land cover and for planning of future ecological studies. Because agricultural landscapes are highly dynamic, they are bound to undergo changes in the near future. Our landscape delineation may serve as an experimental setup where land scape dynamics and wildlife populations and community structures could be monitored. Because the information we used to delineate and characterize agricultural landscape types is readily available in other countries, our approach could easily be adapted to similar data sources under and a wide variety of landscape types. This revised version was published online in July 2006 with corrections to the Cover Date.     

Development and use of a typology of mapping tools to assess their fitness for supporting management of ecosystem service provision

The importance of land use in affecting a range of ecosystem services (ES) provided from rural landscapes is increasingly recognised, creating an imperative for tools to assist in managing impacts of land use on ES provision. Many stakeholders, at a range of scales, are involved, including policy makers and implementers, land users and people receiving the services. Here, we develop a new and comprehensive typology of ES maps by expanding the basic stock-flow-receptor concept to create a set of map categories that embraces requirements for management of ES provision. We then use this typology as a framework for assessment of approaches to mapping ES. Most approaches have considered natural capital stocks of few services, at large scales (>1,000 km²) and coarse resolution (>100 m²). Emphasis has been on areas of ES generation, with little attention to flows, limiting the extent to which reception of services, interactions amongst services, and impacts on different stakeholders are considered. Most approaches focused on a bounded watershed or administrative unit, with little attention to landscape evolution, or to the definition of system boundaries that encompass flows from source to reception for different services. Although uncertainty is inherent in both input data and the services that are mapped, this is rarely acknowledged, quantified or presented. These features of current mapping approaches constrain their usefulness for informing the management of ES provision from rural landscapes. Key areas for future development are (1) maps at scales and resolutions that connect field scale management options to local landscape impacts; (2) mapping flows, and defining landscape boundaries, that include complete pathways, from source to reception; (3) calculating and presenting information on synergies and trade-offs amongst services; and (4) incorporating stakeholder knowledge and perspectives in the generation and interpretation of maps to bound and communicate uncertainty and improve their legitimacy.     

Selection of scale for Everglades landscape models

This article addresses the problem of determining the optimal “Model Grain” or spatial resolution (scale) for landscape modeling in the Everglades. Selecting an appropriate scale for landscape modeling is a critical task that is necessary before using spatial data for model development. How the landscape is viewed in a simulation model is dependent on the scale (cell size) in which it is created. Given that different processes usually have different rates of fluctuations (frequencies), the question of selection of an appropriate modeling scale is a difficult one and most relevant to developing spatial ecosystem models. The question of choosing the appropriate scale for modeling is addressed using the landscape indices (e.g., cover fraction, diversity index, fractal dimension, and transition probabilities) recently developed for quantifying overall characteristics of spatial patterns. A vegetation map of an Everglades impoundment area developed from SPOT satellite data was used in the analyses. The data from this original 20 × 20 m data set was spatially aggregated to a 40 × 40 m resolution and incremented by 40 meters on up to 1000 × 1000 m (i.e., 40, 80, 120, 160 … 1000) scale. The primary focus was on the loss of information and the variation of spatial indices as a function of broadening “Model Grain” or scale. Cover fraction and diversity indices with broadening scale indicate important features, such as tree islands and brush mixture communities in the landscape, nearly disappear at or beyond the 700 m scale. The fractal analyses indicate that the area perimeter relationship changes quite rapidly after about 100 m scale. These results and others reported in the paper should be useful for setting appropriate objectives and expectations for Everglades landscape models built to varying spatial scales.     

Relationships of dead wood patterns with biophysical characteristics and ownership according to scale in Coastal Oregon,USA

Dead wood patterns and dynamics vary with biophysical factors, disturbance history, ownership, and management practices; the relative importance of these factors is poorly understood, especially at landscape to regional scales. This study examined current dead wood amounts in the Coastal Province of Oregon, USA, at multiple spatial scales. Objectives were to: (1) describe current regional amounts of several characteristics of dead wood; (2) compare dead wood amounts across ownerships; (3) determine the relative importance, according to spatial scale, of biophysical and ownership characteristics, to regional dead wood abundance. Dead wood plot data were evaluated with respect to explanatory variables at four spatial scales of resolution: plots, subwatersheds, watersheds and subbasins. The relationships of dead wood characteristics with biophysical attributes and ownership were diverse and scale-specific. Region-wide dead wood abundance and types varied among ownerships, with public lands typically having higher amounts of dead wood and more large dead wood than private lands. Regression analysis of total dead wood volume indicated that ownership was important at the subbasin scale. Growing season moisture stress was important at plot, subwatershed, and watershed scales. Topography was important at the two coarser scales. Multivariate analysis of dead wood gradients showed that ownership was important at all scales, topography at the subbasin scale, historical vegetation at watershed and subbasin scales, and current vegetation at plot and subwatershed scales. Management for dead wood and related biodiversity at watershed to landscape scales should consider the distinct dynamics of snags and logs, the importance of historical effects, and the relevance of ownership patterns.