Petter Pilesjö

Estimating the spatial scale of pollen dispersal in the cultural landscape of southern Sweden

The primary aim of the study was to estimate the spatial scale of pollen dispersal and deposition for pollen assemblages from moss polsters in the cultivated landscape of southern Sweden, as a mean to improve future studies of the pollen/vegetation relationship in the region, and interpretation of fossil pollen data in terms of past cultural landscapes. This can be done by estimating the ‘relevant source area of pollen’ (RSAP) defined as the area around the pollen sampling point beyond which the pollen-vegetation relationship does not improve. Forty-two sites from nonfertilized grasslands in the traditional open agricultural (Open Region) and semi-open forested (Semi-Open Region) regions of southern Sweden were selected. The vegetation survey was performed within a 1500 m radius area around the moss polsters sampling area. The extended R-value (ERV) model was used to evaluate the pollen-plant abundance relationship. The RSAP for moss polsters in the Open Region was estimated to c. 400 m from empirical data. In the Semi-Open Region, however, the likelihood function score, an indicator of the goodness-of-fit of the data to the ERV model, showed an unexpected pattern of change, making it difficult to evaluate the RSAP. Simulations using hypothetical landscapes suggest that systematic selection of sampling sites could cause this pattern. Simulations also demonstrate that the size of vegetation patches affect the RSAP, i.e., the larger the vegetation patches are, the larger the RSAP becomes. Similar RSAP for the Open and Semi-Open Regions is obtained in simulations using the same patch size, and random selection. In the actual vegetation, patch size is comparable in the two regions, which would suggest that the RSAP for moss polsters in the Semi-Open Region is c. 400 m as well.

On the ground estimation of vegetation cover in Australian rangelands

A number of field techniques were assessed on their reliability for estimating vegetation cover in Australian rangelands. The field sampling was undertaken using visual estimation, line intercepts, a crown cover model, and images acquired from a digital camera. The results from these methods were compared and analysed. The data obtained from these differing methods agree with each other in relative rather than absolute terms. This suggests that the methods can provide a reasonable basis for qualitative remote sensing studies, but are not suitable for quantitative investigations.

Investigating the use of Landsat thematic mapper data for estimation of forest leaf area index in southern Sweden

The study aims at investigating the use of Landsat thematic mapper (TM) for mapping leaf area index (LAI) in coniferous and deciduous forests in southern Sweden. LAI has been estimated in the field with optical measurements, allometric equations, and litter-trap data, and empirical relationships between LAI estimates and satellite-measured reflectances have been analysed. Several common vegetation indices and multiple regressions where estimated LAI is predicted as a function of various spectral bands are tested. The results indicate significant relationships between Landsat TM reflectances and parameters related to LAI, and the relationships are improved when separating coniferous and deciduous stands. The best relationships occur between Landsat TM data and the product of effective LAI as estimated with the LAI-2000 instrument and a needle clumping factor (LG), which explains about 80% of the variation in coniferous stands and about 50% of the variation in deciduous stands. The best single bands in coniferous stands are the middle-infrared bands (TM5 and TM7), and the best vegetation index is the moisture stress index (TM5/TM4). The best single band in deciduous stands is TM4, and the best vegetation index is the simple ratio (SR).

Are associations between socio-economic characteristics and exposure to air pollution a question of study area size? An example from Scania, Sweden

BackgroundNumerous studies have shown that exposure to air pollutants in the area of residence and the socio-economic status of an individual may be related. Therefore, when conducting an epidemiological study on the health effect of air pollution, socio-economy may act as a confounding factor. In this paper we examine to what extent socio-economic status and concentrations of NO2 in the county/region of Scania, southern Sweden, are associated and if such associations between these factors differ when studying them at county or city level. To perform this study we used high-resolution census data and modelled the annual exposure to NO2 using an emission database, a dispersion modelling program and a geographical information system (GIS).ResultsThe results from this study confirm that socio-economic status and the levels of NO2 in the area of residence are associated in some cities. The associations vary considerably between cities within the same county (Scania). Even for cities of similar sizes and population bases the associations observed are different. Studying the cities together or separately yields contradictory results, especially when education is used as a socio-economic indicator.ConclusionFour conclusions have been drawn from the results of this study. 1) Adjusting for socio-economy is important when investigating the health effects of air pollution. 2) The county of Scania seems to be heterogeneous regarding the association between air pollution and socio-economy. 3) The relationship between air pollution and socio-economy differs in the five cities included in our study, depending on whether they are analysed separately or together. It is therefore inadvisable to determine and analyse associations between socio-economy and exposure to air pollutants on county level. This study indicates that the size and choice of study area is of great importance. 4) The selection of socio-economic indices (in this study: country of birth and education level) is important.

Geospatial tools address emerging issues in spatial ecology: a review and commentary on the Special Issue

Spatial ecology focuses on the role of space and time in ecological processes and events from a local to a global scale and is particularly relevant in developing environmental policy and (mandated) monitoring goals. In other words, spatial ecology is where geography and ecology intersect, and high-quality geospatial data and analysis tools are required to address emerging issues in spatial ecology. In this commentary and review for the International Journal of GIS Special Issue on Spatial Ecology, we highlight selected current research priorities in spatial ecology and describe geospatial data and methods for addressing these tasks. Geoinformation research themes are identified in population ecology, community and landscape ecology, and ecosystem ecology, and these themes are further linked to the assessment of ecosystem services. Methods in spatial ecology benefit from explicit consideration of spatial autocorrelation, and applications discussed in this review include species distribution modeling, remote sensing of community and ecosystem properties, and models of climate change. The linkages of the Special Issue papers to these emerging issues are described.

Estimating Flow Distribution over Digital Elevation Models Using a Form-Based Algorithm

Abstract This paper discusses a new approach to estimate flow distribution over a continuous surface. This approach is based on the analysis of topographic form of a surface facet that dictates the flow distribution. In the case of a raster Digital Elevation Model (DEM), the facet consists of a centre cell and its eight neighbouring cells. If the form of the facet is convex, the water flow is divergent; thus the amount of flow is distributed to all cells that have a lower elevation. In the case of a concave or flat surface, the convergent flow is directed to the main drainage direction. Comparison between the results of this algorithm with the traditional ‘eight-move’ algorithm, which is widely used in todays commercial GIS software, indicated that the form-based algorithm yielded a more realistic results in estimating flow accumulation over the land surface, but produced less convincing results in deriving a drainage network.

A triangular form-based multiple flow algorithm to estimate overland flow distribution and accumulation on a digital elevation model

In this study, we present a newly developed method for the estimation of surface flow paths on a digital elevation model (DEM). The objective is to use a form-based algorithm, analyzing flow over single cells by dividing them into eight triangular facets and to estimate the surface flow paths on a raster DEM. For each cell on a gridded DEM, the triangular form-based multiple flow algorithm (TFM) was used to distribute flow to one or more of the eight neighbor cells, which determined the flow paths over the DEM. Because each of the eight facets covering a cell has a constant slope and aspect, the estimations of – for example – flow direction and divergence/convergence are more intuitive and less complicated than many traditional raster-based solutions. Experiments were undertaken by estimating the specific catchment area (SCA) over a number of mathematical surfaces, as well as on a real-world DEM. Comparisons were made between the derived SCA by the TFM algorithm with eight other algorithms reported in the literature. The results show that the TFM algorithm produced the closest outcomes to the theoretical values of the SCA compared with other algorithms, derived more consistent outcomes, and was less influenced by surface shapes. The real-world DEM test shows that the TFM was capable of modeling flow distribution without noticeable ‘artefacts’, and its ability to track flow paths makes it an appropriate platform for dynamic surface flow simulation. (Less)

Spatial Influence of Topographical Factors on Yield of Potato ( Solanum Tuberosum L.) in Central Sweden

This study has evaluated the sampling density for creation of high-resolution digital elevation models (DEMs) for precision agriculture purposes. The relationships between yield and topographical factors were investigated in a study area located in the central Sweden province of Dalarna. The DEM data sampling was carried out with a RTK-GPS system. A dense sampling scheme was employed and data was divided into two for both interpolation and validation. Kriging interpolation was used for DEM generation. From the DEM, topographical parameters were extracted and topographical indices were estimated. The indices were calculated with slope length and its vertical and horizontal components. The drainage area for a point of interest and the relationship of this area to the total drainage area were also estimated. The relationship of yield and the topographical parameters and indices was investigated using both circular and spatial statistics. A spatial regression was used to calculate a model for the relationship. Up to 20% of the yield could be explained in the final model for one of the fields.

On generating digital elevation models from liDAR data – resolution versus accuracy and topographic wetness index indices in northern peatlands

Abstract Global change and GHG emission modelling are dependent on accurate wetness estimations for predictions of e.g. methane emissions. This study aims to quantify how the slope, drainage area and the TWI vary with the resolution of DEMs for a flat peatland area. Six DEMs with spatial resolutions from 0.5 to 90 m were interpolated with four different search radiuses. The relationship between accuracy of the DEM and the slope was tested. The LiDAR elevation data was divided into two data sets. The number of data points facilitated an evaluation dataset with data points not more than 10 mm away from the cell centre points in the interpolation dataset. The DEM was evaluated using a quantile-quantile test and the normalized median absolute deviation. It showed independence of the resolution when using the same search radius. The accuracy of the estimated elevation for different slopes was tested using the 0.5 meter DEM and it showed a higher deviation from evaluation data for steep areas. The slope estimat...

Cropland changes in times of conflict, reconstruction, and economic development in Iraqi Kurdistan

The destruction of land and forced migration during the Anfal attacks against the Kurds in Iraq in the late 1980s has been reported to have severe consequences for agricultural development. A reconstruction program to aid people in returning to their lands was launched in 1991. To assess the agricultural situation in the Duhok governorate during the pre-Anfal (A), post-Anfal (B), reconstruction (C), and present (D) periods, we mapped winter crops by focusing on inter-annual variability in vegetation greenness, using satellite images. The results indicate a decrease in cultivated area between period A and B, and a small increase between period B and C. This supports reports of a decline in cultivated area related to the Anfal campaign, and indicates increased activity during the reconstruction program. Period D showed a potential recovery with a cropland area similar to period A.