Use Of Spatial Data Sets Research Articles

Spatial databases and techniques to assist with prescribed fire management in the south-east Queensland bioregion

This paper identifies key fire history and fire-related spatial databases that can be utilised for effective planning and assessment of prescribed burns in south-eastern Queensland. To ensure that appropriate fire regimes are maintained for specific management objectives (e.g. biodiversity conservation or risk management), and to assist fire managers with planning prescribed fire and post-fire assessments, we describe, using case studies and existing tools, the application of remote sensing data and derived burned area products together with field data to potentially: (1) improve mapping of fire-prone areas; (2) improve the accuracy of mapping burned areas; (3) monitor temporal changes in fuel structure; and (4) map post-fire severity. This study utilised data collected from aerial and satellite-based multispectral, microwave and laser (LiDAR) sensors. There are several spatial databases and analytical methods available that are not currently used by fire management agencies in this region. For example, the methods to estimate fuel, such as LiDAR, are underutilised and unburned patches within a burned area are not routinely mapped. Better use of spatial datasets could lead to an improved understanding of variables such as fuel status, resulting in more efficient use of fire management resources.

Modelling impacts of forest bioenergy use on ecosystem sustainability: Lammi LTER region, southern Finland

Increasing the use of forest biomass for energy production is an important mitigation strategy against climate change. Sustainable use of natural resources requires that these policies are evaluated, planned and implemented, taking into account the boundary conditions of the ecological systems affected. This paper describes the development and application of a quantitative modelling framework for evaluating integrated impacts of forest biomass removal scenarios on four key environmental sustainability/ecosystem service indicators: (i) carbon sequestration and balance, (ii) soil nutrient balances (base cations and nitrogen), (iii) nutrient leaching to surface waters (nitrogen and phosphorus), and (iv) dead wood biomass (used as proxy indicator for impacts on species diversity). The system is based on the use of spatial data sets, mass balance calculations, loading coefficients and dynamic modelling. The approach is demonstrated using data from an intensively studied region (Hämeenlinna municipality) encompassing the Lammi LTER (Long-Term Ecosystem Research) site in southern Finland. Forest biomass removal scenarios were derived from a management-oriented large-scale forestry model (MELA) based on sample plot and stand-level data from national forest inventories. These scenarios have been developed to guide future Finnish forest management with respect to bioenergy use. Using harvest residues for district heat production reduced fossil carbon emissions but also the carbon sink of forests in the case study area. Calculations of the net removal of base cations of the different scenarios ranged between −36 to −43meqm−2a−1, indicating that the supply of base cations (soil weathering+deposition) would be enough to sustain also energy-wood harvesting. Greatly increased nutrient removal values and increasing nitrogen limitation problems were however predicted. Clear-cuttings and site preparation were predicted to increase the load of total nitrogen (4.0%) and total phosphorus (4.5%) to surface waters, compared with background leaching. The amount of dead wood has been identified as a key factor for forest species diversity in Finland. A scenario maximising harvest residues used for bioenergy production, would decrease stem dead wood biomass by about 40%, compared with a business-as-usual scenario. Clear trade-off situations could be observed in the case study area between maximising the use of energy-wood and minimising impacts on species diversity, soil carbon and nutrient stores, and nutrient leaching. The developed model system allows seeking for optimised solutions with respect to different management options and sustainability considerations.

Evaluating the fitness for use of spatial data sets to promote quality in ecological assessment and monitoring

This article proposes and illustrates a practical methodological framework to evaluate the fitness for use of spatial data sets for environmental and ecological applications, focusing on user requirements for specified application contexts. The methodology is based on the use of metadata to analyze similarity between the data characteristics and the user’s needs or expectations for several quality indicators. Additionally, the concept of ‘critical factors’ is introduced in this framework, allowing users to define which quality indicators have greater importance given their own requirements or expectations and the specified application contexts. The proposed methodology further allows integrating and interconnecting the spatial data quality (SDQ) evaluation methodology with metadata geoportals in WebGIS platforms, facilitating its operation by users from non-spatial disciplines and with often limited expertise on this subject. Examples of the evaluation of fitness for use for specific application contexts within the project BIO_SOS (‘Biodiversity Multi-SOurce Monitoring System: From Space To Species’ FP7 project) are presented. By providing a prompt and straightforward evaluation tool, the proposed methodology can encourage the implementation of SDQ evaluation routines in ecological assessment and monitoring programs, promoting a more adequate use of geospatial data and ultimately contributing to well-supported policy and management decisions.

Using fuzzy cognitive maps to describe current system dynamics and develop land cover scenarios: a case study in the Brazilian Amazon

In this study we developed a methodology to identify and quantify the relationships among determinants of land cover change using a regional case study in the Brazilian Amazon. The method is based on the application of fuzzy cognitive maps (FCMs), a semi-quantitative tool that provides a structured assessment of key feedbacks in scenario analysis. Novel to the application of FCMs is the use of spatial data-sets as the main input to build a cognitive map. Identification of interactions between land cover determinants and strengths is based on an empirical analysis of spatially explicit data and literature review. Expert knowledge is adopted to identify the strengths and weaknesses of the method. Potential pitfalls, such as spatial autocorrelation and scale issues, identified are intrinsic to the empirical data analysis. The outputs of the resulting FCMs are compared to the outputs of spatially explicit models under similar scenarios of change. The proposed method is said to be robust and reproducible when compared with participatory approaches, and it can endorse the consistency between demand and allocation in scenario analysis to be used in spatially explicit models.

Spatial prioritization of revegetation sites for dryland salinity management: an analytical framework using GIS

To address the limited application of analytical and modelling techniques in prioritizing revegetation sites for dryland salinity (saline land) management, a case study of the Hodgson Creek catchment in Queensland, Australia, was conducted. An analytical framework was developed, incorporating the use of spatial datasets (Landsat 7 image, DEM, soil map, and salinity map), which were processed using digital image processing techniques and a geographic information system (GIS). Revegetation sites were mapped and their priority determined based on recharge area, land use/cover and sub‐catchment salinity. The analytical framework presented here enhances the systematic use of land information, widens the scope for scenario testing, and improves the testing of alternative revegetation options. The spatial patterns of revegetation sites could provide an additional set of information relevant in the design of revegetation strategies.

Testing of a GIS model ofEucalyptus Iargiflorens health on a semiarid, saline floodplain

Irrigated agriculture has resulted in substantial changes in water flows to the lower reaches of the River Murray. These changes have led to large-scale occurrences of dieback in Eucalyptus largiflorens (black box) woodlands as well as increased inputs of salt to the river. Management options to address problems of this scale call for the use of spatial data sets via geographic information systems (GIS). A GIS exists for one floodplain of the River Murray at Chowilla, and a simple model predicted six health classes of Eucalyptus largiflorens based on groundwater salinity, flooding frequency, and groundwater depth.To determine the usefulness of the model for vegetation management, the quality of both the model and the GIS data sets were tested. Success of the testing procedure was judged by the degree of spatial matching between the model's predictions of health and that assessed from aerial photographs and by field truthing. Analyses at 80 sites showed that tree health was significantly greater where groundwater salinity was less than 40 dS/m or flooding occurred more frequently than 1 in 10 years or depth to groundwater exceeded 4 m. Testing of the GIS data sets found that vegetation was misclassified at 15% of sites. Association was shown between GIS-predicted values and field-truthed values of groundwater salinity but not groundwater depth. The GIS model of health is a useful starting point for future vegetation management and can be further improved by increasing the quality of the data coverages and further refining of the model to optimize parameters and thresholds.

Design of a Lineage-Based Meta-Data Base for GIS

A conceptual design is presented for a lineage meta-data base system that documents data sources and geographic information system (GIS) transformations applied to derive cartographic products. Artificial intelligence techniques of semantic networks are used to organize input-output relationships between map layers, and frames are used for storing lineage attributes characterizing source, intermediate, and product layers. An example indicates that a lineage meta-data base enables GIS users to determine the fitness for use of spatial data sets.