Linking linear programming and spatial simulation models to predict landscape effects of forest management alternatives

Forest management planners require analytical tools to assess the effects of alternative strategies on the sometimes disparate benefits from forests such as timber production and wildlife habitat. We assessed the spatial patterns of alternative management strategies by linking two models that were developed for different purposes. We used a linear programming model (Spectrum) to optimize timber harvest schedules, then a simulation model (HARVEST) to project those schedules in a spatially explicit way and produce maps from which the spatial pattern of habitat could be calculated. We demonstrated the power of this approach by evaluating alternative plans developed for a national forest plan revision in Wisconsin, USA. The amount of forest interior habitat was inversely related to the amount of timber cut, and increased under the alternatives compared to the current plan. The amount of edge habitat was positively related to the amount of timber cut, and increased under all alternatives. The amount of mature northern hardwood interior and edge habitat increased for all alternatives, but mature pine habitat area varied. Mature age classes of all forest types increased, and young classes decreased under all alternatives. The average size of patches (defined by age class) generally decreased. These results are consistent with the design goals of each of the alternatives, but reveal that the spatial differences among the alternatives are modest. These complementary models are valuable for quantifying and comparing the spatial effects of alternative management strategies.     

Factors affecting private forest landowner interest in ecosystem management: linking spatial and survey data

Many factors influence forest landowner management decisions. This study examines landowner decisions regarding participation in ecosystem management activities, such as a landscape corridor cutting across their private lands. Landscape corridors are recognized worldwide as an important tool in biodiversity conservation. For ecosystem management activities to occur in areas dominated by a multitude of small private forest landholdings, landowner participation and cooperation is necessary. Data from a survey of landowners combined with an analysis of their land's spatial attributes is used to assess their interest in ecosystem management. Results suggest that spatial attributes are not good predictors of an owner's interest in ecosystem management. Other factors such as attitudes and opinions about the environment are more effective in explaining landowner interest. The results have implications for any land manager using GIS data and implementing ecosystem management activities on private forestland.     

Landscape planning: A method applied to a growth management example

This article is the first in a series of three. These articles were prepared to document the growth management process undertaken in Teller County, Colorado, USA. In this article, an 11-step method for landscape planning is proposed. In step 1, an issue, or set of related issues, is identified as posing a problem and/or opportunity to people and/or the environment. In step 2, a goal, or several goals, is established to address the problem or opportunity. In steps 3 and 4, inventories and analyses of biophysical and sociocultural processes are conducted, first at the regional level and then at the local level. Step 5 involves detailed studies (such as suitability analyses) that link the inventory and analysis information to the problems or opportunities and goals. Detailed studies link regional and local information to specific sites. Thus, this method involves a regional-local-specific site hierarchy. In step 6, concepts are developed that lead to a landscape plan in step 7. During step 8, the plan is explained through a systematic educational and citizen involvement effort to the affected public. In step 9, detailed designs are developed that again are explained to the specific individuals who will be impacted by the designs. It is in step 10 when the plan and designs are implemented. Step 11 involves the administration of the plan. The method is illustrated through an example of growth management planning for Teller County and the city of Woodland Park, Colorado. Paper 1 in a series of 3.     

An introduction to digital methods in remote sensing of forested ecosystems: Focus on the Pacific Northwest,USA

Aerial photography has been routinely used for several decades by natural resource scientists and managers to map and monitor the condition of forested landscapes. Recently, along with the emergence of concepts in managing forests as ecosystems, has come a significant shift in emphasis from smaller to larger spatial scales and the widespread use of geographic information systems. These developments have precipitated an increasing need for vegetation information derived from other remote sensing imagery, especially digital data acquired from high-elevation aircraft and satellite platforms. This paper introduces fundamental concepts in digital remote sensing and describes numerous applications of the technology. The intent is to provide a balanced, nontechnical view, discussing the shortcomings, successes, and future potential for digital remote sensing of forested ecosystems.     

Towards an Integrated Approach to Natural Hazards Risk Assessment Using GIS: With Reference to Bushfires

This paper develops a GIS-based integrated approach to risk assessment in natural hazards, with reference to bushfires. The challenges for undertaking this approach have three components: data integration, risk assessment tasks, and risk decision-making. First, data integration in GIS is a fundamental step for subsequent risk assessment tasks and risk decision-making. A series of spatial data integration issues within GIS such as geographical scales and data models are addressed. Particularly, the integration of both physical environmental data and socioeconomic data is examined with an example linking remotely sensed data and areal census data in GIS. Second, specific risk assessment tasks, such as hazard behavior simulation and vulnerability assessment, should be undertaken in order to understand complex hazard risks and provide support for risk decision-making. For risk assessment tasks involving heterogeneous data sources, the selection of spatial analysis units is important. Third, risk decision-making concerns spatial preferences and/or patterns, and a multicriteria evaluation (MCE)-GIS typology for risk decision-making is presented that incorporates three perspectives: spatial data types, data models, and methods development. Both conventional MCE methods and artificial intelligence-based methods with GIS are identified to facilitate spatial risk decision-making in a rational and interpretable way. Finally, the paper concludes that the integrated approach can be used to assist risk management of natural hazards, in theory and in practice.     

A Knowledge-Based Systems Approach to Design of Spatial Decision Support Systems for Environmental Management

/ This paper describes a framework for designing spatial decision support systems for environmental management using a knowledge-based systems approach. An architecture for knowledge-based spatial decision supportsystems (KBSDSS) is presented that integrates knowledge-based systems with geographical information systems (GIS) and other problem-solving techniques. A method based on spatial influence diagrams is developed for representation of environmental problems. The spatial influence diagram provides an interface through which knowledge-based systems techniques can be applied to build capabilities for problem formulation, automated design, and execution of a solution process. In addition to the flexibility and developmental advantages of knowledge-based systems, the KBSDSS incorporates expert knowledge to provide assistance for structuring spatial influence diagrams and executing a solution process that automatically integrates the GIS, data base, knowledge base, and different types of models. The framework is illustrated with a system, known as the Islay Land Use Decision Support System (ILUDSS), designed to assist planners in strategic planning of land use for the development of the island of Islay, off the west coast of Scotland.KEY WORDS: Geographical information systems; Spatial decision support systems; Knowledge-based systems; Spatial influence diagrams; Environmental management     

Remote sensing for land management and planning

The primary role of remote sensing in land management and planning has been to provide information concerning the physical characteristics of the land which influence the management of individual land parcels or the allocation of lands to various uses These physical characteristics have typically been assessed through aerial photography, which is used to develop resource maps and to monitor changing environmental conditions These uses are well developed and currently well integrated into the planning infrastructure at local, state, and federal levels in the United States.Many newly emerging uses of remote sensing involve digital images which are collected, stored, and processed automatically by electromechanical scanning devices and electronic computers Some scanning devices operate from aircraft or spacecraft to scan ground scenes directly; others scan conventional aerial transparencies to yield digital images. Digital imagery offers the potential for computer-based automated map production, a process that can significantly increase the amount and timeliness of information available to land managers and planners.Future uses of remote sensing in land planning and management will involve geographic information systems, which store resource information in a geocoded format. Geographic information systems allow the automated integration of disparate types of resource data through various types of spatial models so that with accompanying sample ground data, information in the form of thematic maps and/ or aerially aggregated statistics can be produced Key issues confronting the development and integration of geographic information systems into planning pathways are restoration and rectification of digital images, automated techniques for combining both quantitative and qualitative types of data in information-extracting procedures, and the compatibility of alternative data storage modes     

A landscape ecological approach to address scaling problems in conservation management and monitoring

Management of many African game reserves is today often still an art based on experience and intuition, rather than a science. Decision-making is based on an informal integration of accumulated individual knowledge and keen field observations. Data are generally poorly captured and curated. Until fairly recently, denominators of biological parameters (such as the unit of land or unit of plant production used as measurement) have generally been treated as being homogenous. The patchiness of landscapes and the issue of ecological scaling were ignored, often because of a lack of appropriate technical tools. The ecological data available on the 49,000-ha Songimvelo Game Reserve (SGR) result from a number of discrete survey and monitoring projects undertaken by different researchers, with different objectives, at different spatial and temporal scales. A landscape ecological approach towards research and monitoring is appropriate for an area of the size and diversity of the SGR. A combination of a database approach and spatial representation was used to consolidate and integrate data across temporal and spatial scales. Herbivore spatial and temporal distribution patterns were explored across three spatial scales. An understanding was achieved of the importance of landscape patchiness in controlling resource availability for herbivores. This insight is important in guiding management and monitoring of the SGR by placing perceived patch overutilization in its proper landscape context. The landscape ecological approach bridges the traditional scale-independent view to a more contemporary scale-related understanding of ecosystem diversity and functioning.     

A Conceptual Model for Defining and Assessing Land Management Units Using a Fuzzy Modeling Approach in GIS Environment

Appropriate land management decisions are important for current and future use of the land to ensure its sustainability. This requires that land management units (LMUs) be specified to enable the identification of specific parameters employed in decision making processes. This paper presents the development of a conceptual model, within geographic information systems (GIS), for defining and assessing LMUs from available biophysical information. The model consists of two main components (sub-models): land quality-based suitability analysis and soil erosion estimation. Using a fuzzy set methodology, the first sub-model was constructed to derive a land suitability index (LSI) for a cropping land utilization type. The LSI thus highlights the suitability grades of every pixel in the study area on a continuous basis. A sub-model of soil erosion was established based on the Revised Universal Soil Loss Equation (RUSLE) utilising the same spatial data bases employed for structuring the LSI. Using a soil loss tolerance principle, a fuzzy membership function of average annual soil loss (called soil loss index, SLI) was established, leading to compatibility between LSI and SLI for data integration. LMUs were then derived from various combinations of LSI and SLI. The methodology developed shows the significance of the model for refining available land suitability evaluation systems, which take no account of expected land degradation (from erosion) due to a nominated land use. It also provides a valuable guideline for cost-effective GIS applications in the identification and assessment of homogeneous land units, using available spatial information sets, at a finer scale.