Spatial Objectives Research Articles

Forest structure optimization using evolutionary programming and landscape ecology metrics

A new design framework is introduced for forest structure optimization based on a genetic algorithm landscape encoding and landscape ecology metrics. Landscape ecology is an important interface between the forest management community, which is a traditional user of operations research methods, and the biological conservation community which is relatively new to OR methods and whose goals are increasingly allied with the spatial ecology concepts emerging from landscape ecology. Deforestation and forest fragmentation are increasingly recognized as the underlying drivers of global biodiversity loss, hence forestry management will need to explicitly incorporate spatial ecology objectives. A deforestation model is presented which simulates a landscape progressively fragmenting by the incremental removal of forest patches. Principal components analysis (PCA) of multiple deforestation simulations captures the relative influence of the mean proximity index and the mean nearest neighbour distance, two widely used landscape ecology metrics. An evolutionary programming method based on a genetic encoding of landscape structure is used to optimize forest patch selection by maximizing landscape performance with respect to single and multiple landscape ecology metrics weighted according to the PCA. This optimization approach is envisioned as a key component of a new forestry OR paradigm for designing multi-use landscape systems, incorporating both biodiversity and community needs.

Examining the performance of six heuristic optimisation techniques in different forest planning problems

The existence of multiple decision-makers and goals, spatial and non-linear forest management objectives and the combinatorial nature of forest planning problems are reasons that support the use of heuristic optimisation algorithms in forest planning instead of the more traditional LP methods. A heuristic is a search algorithm that does not necessarily find the global optimum but it can produce relatively good solutions within reasonable time. The performance of different heuristics may vary depending on the complexity of the planning problem. This study tested six heuristic optimisation techniques in five different, increasingly difficult planning problems. The heuristics were evaluated with respect to the objective function value that the techniques were able to find, and the time they consumed in the optimisation process. The tested optimisation techniques were 1) random ascent (RA), 2) Hero sequential ascent technique (Hero), 3) simulated annealing (SA), 4) a hybrid of SA and Hero (SA+Hero), 5) tabu search (TS) and 6) genetic algorithm (GA). The results, calculated as averages of 100 repeated optimisations, were very similar for all heuristics with respect to the objective function value but the time consumption of the heuristics varied considerably. During the time the slowest techniques (SA or GA) required for convergence, the optimisation could have been repeated about 200 times with the fastest technique (Hero). The SA+Hero and SA techniques found the best solutions for non-spatial planning problems, while GA was the best in the most difficult problems. The results suggest that, especially in spatial planning problems, it is a benefit if the method performs more complicated moves than selecting one of the neighbouring solutions. It may also be beneficial to combine two or more heuristic techniques.

Demographischer Wandel

Spatial planning and the bodies responsible for the provision of public amenities / infrastructure services must adapt early and to regionally different extents to a general population decline, to ageing and to the internationalisation of the population. The adaptation requirements resulting from the spatial dimension of demographic change call for a positioning of spatial planning: starting with an examination of spatial planning models and objectives with open results, for instance the maintenance of the postulate of equivalent living conditions, to an examination of the procedures and instruments to fulfil the co-ordination task of spatial planning at the different spatial levels. Demonstration projects also play an important role as an action area of the Federal Government. They provide the opportunity to develop and test innovative policy approaches of spatial planning in collaboration with local protagonists in the regions. The article presents the current demonstration projects of spatial planning in the thematic focus “Infrastructure and Demographic Change” and reports on first results. Strategies and concepts to safeguard an appropriate regional supply of infrastructure are in the centre of interest in this context.

Spatial modeling of harvest constraints on wood supply versus wildlife habitat objectives.

We studied the effects of spatial and temporal timber harvesting constraints on competing objectives of sustaining wildlife habitat supply and meeting timber harvest objectives in a boreal mixedwood forest. A hierarchical modeling approach was taken, where strategic and tactical level models were used to project blocking and scheduling of harvest blocks. Harvest block size and proximity, together with short- and long-term temporal constraints, were adjusted in a factorial manner to allow creation of response-surface models. A new measure of the habitat mosaic was defined to describe the emergent pattern of habitat across the landscape. These models, together with multiple linear regression, were used to provide insight on convergence or divergence between spatial objectives. For example, green-up delay (defined as time required before a harvest block adjacent to a previously logged block can be scheduled for harvest) had an adverse effect on the amount of annual harvest area that could be allocated and blocked spatially, and habitat supply responded in an opposite direction to that of wood supply, where caribou, moose wintering, and marten habitat supply increased when harvest blocks were further apart, maximum block size smaller, and both a green-up delay and mesoscale stratification were applied. Although there was no "solution space" free of conflicts, the analysis suggests that application of the mesoscale stratification, together with a diversity of harvest block sizes and a between-harvest block proximity of 250 m, will perform relatively well with respect to wood supply objectives, and at the same time create a less fragmented landscape that better reflects natural forest patterns.

Selecting forest reserves with a multiobjective spatial algorithm

Abstract We applied a multiobjective spatial heuristic algorithm in a landscape area of 10 000 ha in eastern Finland, to select forest stands that would best complement the existing reserves in terms of achievement of conservation objectives while minimizing costs. Several non-spatial and spatial objectives for quality, area, and spatial distribution of forests were defined in cooperation with forest managers. Furthermore, existing reserves were pre-selected. The cost of each stand was calculated on the basis of the economic value of forest land and timber. The algorithm calculated cost–benefit ratios for the stands on the basis of how well each stand fulfilled the non-spatial and spatial objectives and at what cost. In every cycle, the algorithm selected the stand with the best cost–benefit ratio. A comparison between solutions, one without and three with differently weighted spatial objectives, showed that the network of selected stands was more clustered with than without spatial objectives. The use of the spatial objectives increased costs and the area slightly, and the non-spatial objectives were met almost equally in all solutions. The network of selected stands in one 2100 ha sub-region was more clustered when stands were selected from the whole region rather than only from that sub-region.

Comparison of methods of snow cover mapping by analysing the solar spectrum of satellite remote sensing data in China

Three methods, supervised classification (SC), digital number (DN) statistics and Normalized Difference Snow Index (NDSI), are used to map snow cover and then calculate snow cover area. Data sets from Landsat TM, Moderate Resolution Imaging Spectroradiometer (MODIS) and NOAA/AVHRR are selected because these sensors of different spatial resolution provide the most up to date remote sensing data for China. The results show that the best method for obtaining the snow index is different for each of these sensor products because of their different spatial and temporal resolutions and objectives of application. Reflectivity threshold statistics (RTs) should be used if the data series is incomplete; whereas SC needs a relatively accurate signature file for classification. A valid and rational method has been certified which selects NDSI for extracting snow pixels. Meanwhile, we introduce the brightness compensation method for decreasing the impact of topographic shading on distinguishing of snow pixels.

Method for Selection of Old‐Forest Reserves

Abstract: We used a multi‐objective greedy heuristic algorithm in a landscape area of 96,000 ha in northern Finland to select old‐forest stands that would best complement existing reserves in terms of achievement of conservation objectives while minimizing costs. Several quantitative nonspatial and spatial objectives for quality, proportion of area, and spatial distribution of old forests were specified in cooperation with foresters and conservation planners. The cost of each stand was calculated on the basis of the economic value of forest land. The algorithm calculated cost‐benefit ratios for the stands on the basis of how well each stand satisfied the objectives and at what cost. In every cycle, the algorithm selected the stand with the best cost‐benefit ratio. The algorithm included three spatial functions—continuous area, connectivity, and isolation—that were used to determine the spatial distribution of the stands. In addition, an option for preselection of stands (e.g., existing reserves) was included. A comparison between two solutions, one with and one without spatial objectives, showed that the network of selected old‐forest stands was less fragmented and more evenly distributed with use of the spatial objectives. The use of spatial objectives did not increase costs or the area needed, and the nonspatial objectives were met in both solutions. The nonspatial and spatial objectives are defined by the user, so the algorithm can be applied to other multi‐objective problems.

Future directions for SDI development

Understanding the role of spatial data infrastructure (SDI) in the society is important to acceptance of the concept and its alignment with spatial industry objectives. Much has been done to describe and understand the components and operation of different aspects of SDIs and their integration into the spatial data community. However, what is often miss-understood is that the role SDI plays is by necessity greater than the sum of individual components of SDI and stakeholder groups.SDI is fundamentally about facilitation and coordination of the exchange and sharing of spatial data between stakeholders in the spatial data community. To this end, the authors propose that the roles of SDI have been pursued through two different approaches: product- and process-based. Both approaches have value, but contribute to the evolution, uptake and utilization of the SDI concept in different ways. They provide different frameworks for dealing with SDI mandates for the objectives of spatial data access and sharing.This paper reviews the nature and concept of SDI, including the components, which have helped to build the current understanding about the importance of an infrastructure to support the interactions of the spatial data community. Several examples of how SDIs have been described are offered to aid understanding of their complexity. The need for descriptions to represent the discrepancies between the role and deliverables of an SDI, and thus, contribute to a simpler, but dynamic, understanding of the complexity of the SDI concept, are postulated. The transition between the understanding of SDIs from product-based to process-based approaches is investigated, with a review of the positions taken by current SDI initiatives throughout the world. A model of how these approaches provide a framework to meet the mandates of the relevant jurisdictions is proposed, and factors contributing to the success of such positions in the future are discussed.

The performance of alternative spatial objective types in forest planning calculations: a case for flying squirrel and moose

This study examined the characteristics and performance of three different types of spatial objectives in multi-objective forest planning. These types were tested with a case study problem that aimed at improvements in the spatial pattern of the habitats of flying squirrel ( Pteromys volans) and moose ( Alces alces). In the first step, the habitats were determined by using a stand-level habitat suitability index (HSI). Stands in which the HSI exceeded a user-specified limit were considered as habitats. In the forest level problem formulations, the spatial objective types were included in the multi-objective forest-planning model, which was solved by using a heuristic optimization technique. The first type of spatial objective was the proportion of a specified type of stand boundary of the total boundary length. For flying squirrel, the aim was to increase the boundaries between neighboring stands, which were both suitable for breeding and foraging. For moose, the aim was to increase the amount of edge, i.e. the boundary between winter-foraging habitats and other areas. The second spatial objective type was the spatial autocorrelation of HSI. It was maximized for flying squirrel and minimized for moose. Whereas maximization of spatial autocorrelation tends to cluster similar stands, its minimization produces a pattern where neighboring stands often have different characteristics. The third spatial objective type was a weighted mean of the stand-level HSI. The weight depended on the stand location being highest for current habitat patches and decreased as the distance to them increased. This objective, which tends to cluster habitat patches, was applied to flying squirrel only. The spatial objective types were tested in six forest areas located in north Karelia, Finland, ranging from 404.6 to 984.8 ha in area. The first spatial objective resulted in a large area of habitat exceeding the threshold HSI value with a good spatial pattern. The second spatial objective yielded a clearly lower total habitat area but a good spatial pattern, and a good connectivity of the flying squirrels’ habitats. The third objective resulted in a slightly improved spatial pattern of the flying squirrels’ habitats.

The spatial structure of forests in the optimization calculations of forest planning — a landscape ecological perspective

This article reviews an array of forest planning approaches where spatial objectives are taken into account in optimization. According to ecological arguments, factors at the level of landscape affect ecological processes and the abundance of species, as a result of which the related objectives, such as those that are quantitative, are also spatial. This article is concerned with the ability of the studies under review to respond to the ecological goals at the level of landscape, especially to the negative effects of habitat fragmentation. Three factors were included in the studies reviewed: reduction in the area of certain habitats, reduction in the size of habitat patches, and weakening connections between them. The fragmentation of habitats has been approached from a landscape perspective and also from that of species-specific habitat needs. Although optimization can become very complicated, it is technically possible to include spatial objectives in planning where several private forest owners are involved simultaneously.

Spatial stratification in forest modelling

This paper discusses the concept of spatial stratification (SS) as applied to forest modelling in general, and spatial forest modelling in particular. SS is a way of providing a geographically explicit forest description in forest modelling, or a way of accommodating spatially explicit management objectives and interventions. In the former, called a priori SS, stands of a forest landscape are spatially aggregated into a set of stand clusters which become input to forest modelling. The latter, called dynamic SS, utilizes stands as the input forest description upon which various spatial aggregations occur throughout forest modelling. Distinctions between the two alternative approaches are highlighted and implementation considerations are examined within the forest landscape management design context. The paper concludes that: (i) modelling techniques are directly linked to forest stratification approaches; and (ii) a priori stratification is seriously limited in spatial modelling for landscape management design where multiple and often conflicting spatial objectives exist. In view of these findings, the paper outlines an alternative spatial forest modelling approach using a combination of dynamic SS and heuristic optimization. Key words: spatial stratification, spatial forest modelling, heuristic optimization, forest management

Issues in public policy evaluation: the case of regional policy

This paper notes the recent growth of public policy evaluation studies and pays particular attention to those policies with avowed spatial objectives. It seeks to establish the general nature of these diverse studies and their relationship to geographical analysis. A case study examining the evaluation of regional policy in the U.K. is used to demonstrate the nature of the issues in public policy evaluation and to explore the role of geography in the rapidly growing domain, known most commonly as ‘policy analysis’.

The role of some central government agencies in urban economic regeneration

Lawless P. (1981) The role of some central government agencies in urban economic regeneration, Reg. Studies 15, 1–14. This paper attempts to define the extent to which three central government agencies, the Department of Industry, the National Enterprise Board, and the Manpower Services Commission, expressed, explicitly or otherwise, an urban dimension in the 1977–1979 period. This paper concludes that, although spatial objectives remain largely muted in the operational programmes of these institutions, there is some evidence that a more obvious inner-city dimension was becoming apparent, particularly in one or two Partnership areas, by 1978–1979. Potential conflicts between national and urban economic development, and between previous Labour and likely Conservative policies are outline.

The Spatial Components of Anglo-African Development Plans, 1943–1956

(1981). The Spatial Components of Anglo-African Development Plans, 1943–1956. Canadian Journal of African Studies / Revue canadienne des etudes africaines: Vol. 15, No. 3, pp. 527-538.