Geir-Harald Strand

Heterogeneity as a measure of spatial pattern for monitoring agricultural landscapes

The Norwegian monitoring programme for agricultural landscapes is a sample-based programme that aims to document the current state and patterns of change in the agricultural landscape for the entire country. For this broad geographical coverage an indicator approach is the most cost-effective methodology. Landscape metrics are used as indicators in the monitoring programme based on the assumed importance of landscape composition and spatial pattern for a number of countryside interests. However, although indicators have been used successfully over a long period of time in various disciplines, their use in landscape monitoring is relatively new and there is little empirical data with which to assess their validity. This paper provides information on the performance of landscape diversity and landscape heterogeneity indices as estimated by specific biodiversity measures. Preliminary results show increasing numbers of breeding bird species and numbers of vascular plant species with increasing landscape diversity and heterogeneity, two indices that capture information on landscape content and structure. Overall, the heterogeneity index provided a better surrogate for species richness than the diversity index.

The effect of field experience on the accuracy of identifying land cover types in aerial photographs

Abstract The purpose of this study was to examine the contribution of field experience to the attribute accuracy of land cover maps based on interpretation of aerial photographs. A senior photogrammetrist using true colour aerial photographs delineated land cover polygons in two areas with similar, but not identical, land cover features. Ten experts with long experience from interpretation of aerial photographs were then asked to label these land cover polygons. The experts fell into two broad categories: ‘field trotters’ and ‘photogrammetrists’ according to their professional background. After completing the labelling of the polygons in the first area, all experts spent 1 day in the field in order to compare their results to ground truth. The fieldwork was supervised by a vegetation ecologist. After the field session, the experts proceeded to label the polygons in the second area. The results did not reveal statistically significant differences between the two groups. Neither did any of the groups improve their performance as a result of the fieldwork.

Comparison of variance estimation methods for use with two-dimensional systematic sampling of land use/land cover data

Systematic sampling is more precise than simple random sampling when spatial autocorrelation is present and the sampling effort is equal, but there is no unbiased method to estimate the variance from a systematic sample. The objective of this paper is to assess selected variance estimation methods and evaluate the influence of spatial structure on the results. These methods are treated as models and a complete enumeration of Norway was used as the modeling environment. The paper demonstrates that the advantage of systematic sampling is closely related to autocorrelation in the material, but also that the improvement is influenced by periodicity and drift in the variables. Variance estimation by stratification with the smallest possible strata gave the best overall results but may underestimate the variance when spatial autocorrelation is absent. Treating the sample as a simple random sample is a safe and conservative alternative when spatial autocorrelation is absent or unknown. Display Omitted Demonstrates the advantage of systematic sampling over simple random sampling.Local estimators of variance superior to variance calculated as simple random sample.The improvement is linked to the presence of spatial autocorrelation.Stratification using small non-overlapping neighborhoods gave the best results.Variance may be underestimated when the spatial autocorrelation is weak.

The Norwegian area frame survey of land cover and outfield land resources

There is a growing demand for reliable information about land cover and land resources. The Norwegian area frame survey of land cover and outfield land resources (AR18X18) is a response to this demand. AR18X18 provides unbiased land cover and land resource statistics and constitutes a baseline for studying changes in outfield land resources in Norway and a framework for a national land resource accounting system for the outfields. The area frame survey uses a systematic sampling technique with 0.9 km2 sample plots at 18 km intervals. A complete wall-to-wall land cover map of an entire plot surveyed is obtained in situ by a team of fieldworkers equipped with aerial photographs. The use of sample plots with extended coverage (0.9 km2) ensures that the survey also deals with local variation, thus strengthening the estimates well beyond simple point sampling. The article documents the methodology used in the survey, followed by a discussion of issues raised by the choice of methodology. These issues include the problem of calculating uncertainty and a confidence interval for the estimates, the focus on common rather than rare land cover categories, and the prospect of downscaling the results in order to obtain statistics for subnational regions.

Estimation of the difference in crown vigour for 2280 coniferous trees in Norway from 1989 to 1994, adjusted for the effects of ageing

The considerable deposition of airborne pollutants over Norway has caused concern about the effect on the countrys conifer forests. Monitoring of the forest vitality is carried out as an annual assessment of the crown vigour of a representative sample of conifer trees. Crown vigour is a subjective and imprecise indicator, but reasonably precise when change is concerned. A method is described where the expected decline in vitality due to ageing is removed. The remaining, age-adjusted change in crown vigour is then assessed under the prevalent hypothesis of ongoing forest decline. The uncertainties involved with the method are discussed in the conclusion.

Uncertainty in classification and delineation of landscapes

A landscape region can be drawn on a map as a geographic feature with distinct boundaries. Reality is, however, that the change from one landscape to another usually is gradual and that landscapes therefore have uncertain or undetermined boundaries. A thematic map of landscape regions is therefore a too simple model of the landscape. An alternative approach is to consider landscape categories as purely theoretical concepts. With this perspective, a particular geographical location can be more or less affiliated with a number of different landscape categories. Such a conception of landscape does not lead to a traditional thematic map of uniform, non-overlapping regions, but to a landscape model composed of multiple overlapping probability surfaces. This article shows how such a landscape model can be established using binary logistic regression. The method is tested and the result is assessed against an existing landscape map of Norway much used in policy impact analysis in this country. The overall objective is to develop a data driven landscape model that can supplement, elucidate and for some purposes maybe even replace, the qualitative landscape description represented by the traditional landscape map.

Kriging the potential tree level in Norway

The tree line is the upper margin of the subalpine forest where the trees become dwarfed or are absent (Howard &,Mitchell 1985). On topographic maps, the tree line divides the landscape into two uniform regions which are often referred to as ‘above’ and ‘below’ the tree line. The teminology implies a notion of the tree line as the physical manifestation of a continuous surface describing a potential tree level. The tree level exists globally, while the tree line only appears as a contour line where the tree level intersects the topography. The tree level can be thought of as a continuous but invisible surface. This surface cuts through the landscape along the tree line. The area below this surface is described as ‘below the tree line’, while areas above the surface are ‘above the tree line’.

Large-scale variations in radial tree growth in Norway: An application of median polish for spatial trend detection

Abstract Radial growth was measured on 11,452 Norway spruce ( Picea abies ) trees on a systematic random sample of 1492 forest inventory sites in Norway. The data were decomposed using median polish and examined for spatial trends. Radial growth was higher than average in the far south and lower than average in the north. This latitudinal trend followed a linear gradient in the eastern, continental parts of the country. A similar but less smooth gradient was also found in the western, coastal region. Summary points were used to characterize and compare the two gradients. Radial tree growth in the western region was consistently lower than in the eastern region, but the shapes of the two gradients were almost identical. These may be explained as an effect of a climatic gradient shared by the two regions, with high radial growth broadly corresponding to a warmer climate and a longer growing season. Norway spruce is at the limit of its geographical range near the western coast of Norway, which may explain the generally lower growth rate here. The results do not support the hypothesis that widespread forest decline is taking place in Norway, but surprisingly high growth in the extreme south of the country may be related to the fertilizing effect of airborne nitrogen deposition. Median polish of geographical data was found to perform well as an alternative technique for spatial trend detection.

Composition and spatial structure of dwarf shrub heath in Norway

ABSTRACT Detailed descriptions of individual vegetation types shown on vegetation maps can improve the ways in which the composition and spatial structure within the types are understood. The authors therefore examined dwarf shrub heath, a vegetation type covering large areas and found in many parts of the Norwegian mountains. They used data from point samples obtained in a wall-to-wall area frame survey. The point sampling method provided data that gave a good understanding of the composition and structure of the vegetation type, but also revealed a difference between variation within the vegetation type itself (intra-class variation) and variation resulting from the inclusion of other types of vegetation inside the map polygons (landscape variation). Intra-class variation reflected differences in the botanical composition of the vegetation type itself, whereas landscape variation represented differences in the land-cover composition of the broader landscape in which the vegetation type was found. Both types of variation were related to environmental gradients. The authors conclude that integrated point sampling method is an efficient way to achieve increased understanding of the content of a vegetation map and can be implemented as a supporting activity during a survey.

Evaluation of Landscape-Level Grazing Capacity for Domestic Sheep in Alpine Rangelands

Abstract Balancing the number of grazing animals with the level of plant resources is a core issue in grazing management. Complete, full-coverage vegetation surveys are often used for this purpose, but these are expensive undertakings. We have presented a method to downscale information from regional sampling surveys by poststratification using a land cover map derived from satellite-based measures of reflectance values. This approach opens new prospects for landscape-level evaluation of productivity. We applied this method to eight grazing districts (19–245 km2) in Setesdal Vesthei, Norway, in 2006. Sheep densities in three of eight grazing districts of Setesdal Vesthei fluctuated above the estimated grazing capacity. We fitted 43 sheep with Global Positioning System collars in two contrasting grazing districts in 2007–2008 to assess their selection of the land cover productivity classes in the map used for poststratification. In the area with high vegetation coverage, sheep selection increased in areas with an overall higher productivity, supporting the main basis of the approach. However, in the grazing districts with lower vegetation coverage, selection was higher for areas of overall low vegetation productivity. The likely explanation is the presence of small areas of snow bed vegetation with high-quality forage in areas with a generally rocky surface. Our study provides a first step toward a grazing capacity evaluation to achieve a sustainable management of sheep on alpine ranges of Scandinavia, and our approach is likely applicable to other open alpine ranges in the northern hemisphere.