In environmental monitoring, it is important that the monitoring system should emit early warnings when undesired events occur. These events may be sudden or of a more subtle nature. In the design of such monitoring systems, a proper balance between cost and risk must be achieved. There are 2 classic types of risk connected with early warning systems, namely the risk of not detecting significant changes and the risk of false alarms. The purpose of this paper is to describe a method for comparing the performance of different monitoring systems, considering the classic types of risk and cost. The method is applied to the monitoring of the lichen cover as a test case. The expected utility has been used as a measure of performance. When estimating the probabilities of the events, spatial microsimulation and Monte-Carlo simulation techniques have been used. The monitoring programs studied are based on satellite images, aerial photos, field samples, and land-cover maps. The major conclusions of this study are that standardized quality measures are extremely useful for evaluating the usability of environmental monitoring methods. In addition, when estimating gains and costs, spatial microsimulation techniques are useful. To improve the method, however, macroconstraints should also be used for aligning the simulation model.

Vegetation cover-change analysis requires selection of an appropriate set of variables for measuring and characterizing change. Satellite sensors like landsat tm offer the advantages of wide spatial coverage while providing land-cover information. This facilitates the monitoring of surface processes. This study discusses change detection in mountainous dry-heath communities in jämtland county, sweden, using satellite data. Landsat-5 tm and landsat-7 etm data from 1984, 1994 and 2000, respectively, were used. Different change detection methods were compared after the images had been radiometrically normalized, georeferenced and corrected for topographic effects. For detection of the classes change – no change the ndvi image differencing method was the most accurate with an overall accuracy of 94% (k = 0.87). Additional change information was extracted from an alternative method called ndvi regression analysis and vegetation change in 3 categories within mountainous dry-heath communities were detected. By applying a fuzzy set thresholding technique the overall accuracy was improved from of 65% (k = 0.45) to 74% (k = 0.59). The methods used generate a change product showing the location of changed areas in sensitive mountainous heath communities, and it also indicates the extent of the change (high, moderate and unchanged vegetation cover decrease). A total of 17% of the dry and extremely dry-heath vegetation within the study area has changed between 1984 and 2000. On average 4% of the studied heath communities have been classified as high change, i.e. have experienced “high vegetation cover decrease” during the period. The results show that the low alpine zone of the southern part of the study area shows the highest amount of “high vegetation cover decrease". The results also show that the main change occurred between 1994 and 2000.

Mountainous vegetation in general, and especially in subpolar regions, is sensitive, compared to vegetation in lowland areas, as mountainous vegetation has low resilience and low productivity. Mountainous areas have been perceived as being sensitive to mechanical damage. Quick methods with a high degree of accuracy are needed for the monitoring of mountainous areas and for planning the sustainable use of resources. The aim was i) to investigate if the dry dwarf shrub heath on hummocky moraine in the southern part of the mountains with a maritime climate and in open areas used for summer grazing, is susceptible to change; and ii) to test if high-resolution IKONOS-2 satellite data can, with a high degree of accuracy, be used for detection, and for quantification and mapping of erosion patches in montane vegetation. In which case, these data can substitute color infrared aerial photos for the early detection of changes. For the detection of changes, visual interpretations on high-quality printouts of IKONOS-2 satellite images from 2000 and of color infrared aerial photographs from 1975 were carried out and the results compared. Interpretations were verified in the field. The results show that for the period 1975–2000, erosion was in process on and around wind heaths, indicating that the wind heath and surrounding dry dwarf shrub heath in this landscape type of hummocky moraine are sensitive to mechanical damage by trampling and grazing, and thus susceptible to change. Most of the wind heaths and changes found were small (50–1000 m²). The results show that it is possible to detect, with good accuracy, detailed changes in the size and distribution of erosion patches and wind heaths by visual interpretation in single images of IKONOS-2 data. This implies that for monitoring these kinds of changes, these high-resolution (4 × 4 m pixel resolution) satellite data can substitute for color infrared aerial photographs.

Termination of fire along with active removal of deciduous trees in favor of conifers together with anthropogenic transformation of productive forest into agricultural land, have transformed northern European coniferous forests and reduced their deciduous component. Locally, however, in the villages, deciduous trees and stands were maintained, and have more recently regenerated on abandoned agricultural land. We hypothesize that the present distribution of the deciduous component is related to the village in-field/out-field zonation in different regions, which emerges from physical conditions and recent economic development expressed as land-use change. We analyzed the spatial distribution of deciduous stands in in-field and out-field zones of villages in 6 boreal/hemiboreal Swedish regions (Norrbotten, Ångermanland, Jämtland, Dalarna, Bergslagen, Småland). In each region 6 individual quadrates 5 × 5 km centered on village areas were selected. We found significant regional differences in the deciduous component (DEC) in different village zones. At the scale of villages Ångermanland had the highest mean proportion of DEC (17%) and Jämtland the lowest (2%). However, the amounts of the DEC varied systematically in in-field and out-field zones. DEC was highest in the in-field in the south (Småland), but generally low further north. By contrast, the amount of DEC in the out-field was highest in the north. The relative amount of DEC in the forest edge peaked in landscapes with the strongest decline in active agriculture (Ångermanland, Dalarna, Bergslagen). Because former and present local villages are vital for biodiversity linked to the deciduous component, our results indicate a need for integrated management of deciduous forest within entire landscapes. This study shows that simplified satellite data are useful for estimating the spatial distribution of deciduous trees and stands at the landscape scale. However, for detailed studies better thematic resolution is needed to determine biologically relevant differences in quality of deciduous stands.

The maintenance of biodiversity by securing representative and well-connected habitat networks in managed landscapes requires a wise combination of protection, management, and restoration of habitats at several scales. We suggest that the integration of natural and social sciences in the form of “Two-dimensional gap analysis” is an efficient tool for the implementation of biodiversity policies. The tool links biologically relevant “horizontal” ecological issues with “vertical” issues related to institutions and other societal issues. Using forest biodiversity as an example, we illustrate how one can combine ecological and institutional aspects of biodiversity conservation, thus facilitating environmentally sustainable regional development. In particular, we use regional gap analysis for identification of focal forest types, habitat modelling for ascertaining the functional connectivity of “green infrastructures”, as tools for the horizontal gap analysis. For the vertical dimension we suggest how the social sciences can be used for assessing the success in the implementation of biodiversity policies in real landscapes by identifying institutional obstacles while implementing policies. We argue that this interdisciplinary approach could be applied in a whole range of other environments including other terrestrial biota and aquatic ecosystems where functional habitat connectivity, nonlinear response to habitat loss and a multitude of economic and social interests co-occur in the same landscape.

Forest reflectance models are able to contribute to the interpretation of satellite images over forested areas. A multipurpose forest reflectance model, its basic ideas, model input and output options are briefly described. The possibility to apply the model in forest remote sensing is demonstrated through the following simulation examples: the age dependence of forest reflectance, the seasonal course of forest reflectance, defoliation effects on forest reflectance, sensitivity of chlorophyll and water indices with respect to leaf chlorophyll and water content, respectively, and uncertainties in these indices introduced by the variation in stand parameters. When used together with the atmospheric radiative transfer and sensor calibration models, the forest reflectance model is applicable in satellite-imagery-aided forest ecology and health assessment, forest inventory and management.

About 55% of the land area in Sweden is covered by forest. Presently, there is no uniform and geographically explicit description of the forest cover for Sweden. Independent data sources already existing are satellite data from Landsat TM and SPOT HRV, map masks and forest inventory plots. Together, they provide the possibility of computing estimates of forest variables such as stem volume and stand age. The accuracy for these estimations will be low on the pixel level, but higher on a stand level. This type of raster-based forest data is useful for authorities when planning how timber resources should be utilized or for monitoring purposes. The production line that was developed to create a countrywide database of forest variable estimates in a cost-efficient way is described. Accuracy of forest variable estimates for an area in southwestern Sweden was assessed at stand level. Results showed 33% overall root mean square error for the estimates of total wood volume, and 23% for the age estimates.

Habitat models may provide viable tools for co-management of large ungulates and forest resources, yet their applicability has not been comprehensively evaluated in managed forest. We examined 2 inherently different approaches to model the relative winter habitat suitability for moose (Alces alces) in the coastal area of northern Sweden. An empirical approach based on GPS positions of 15 female moose was used to scrutinize the assumptions and functional mechanisms of a process-oriented, conceptual approach, based on published material on the species' preferences for habitat components related to food and cover. For both model approaches habitat was described using estimates of forest-stand characteristics based on satellite imagery. The empirical model also included variables relating to topographic properties of the landscape as well as distances to landscape features. The output from both models was a habitat suitability index (HSI) score, enabling the models to be compared with each other. The models showed different results, highlighting the need to include the spatially explicit distribution of environmental variables in future conceptual, process-oriented models.

When seeking to resolve complex land-management issues, geographical assessment of resources that are in short supply or in dispute can aid the communication of knowledge and the understanding among and between different stakeholders. In this paper, we illustrate how remote sensing and GIS can be used to gather and compile information regarding land-use activities and patterns among reindeer herders and other land users (forestry, mining, tourism, etc) in northern Sweden. The project represents a novel user-oriented effort largely based on the work carried out by the principal end user, i.e. the reindeer herders themselves. The basis for development of land-use plans for reindeer husbandry, was the following: to collect and digitally systemize traditional ecological and landscape knowledge of reindeer habitat use; to integrate this information with results from field inventories and satellite-based vegetation classifications; to map activities of other land users. The resulting land-use plans provide information that can facilitate consultation between the reindeer herders and other stakeholders and can facilitate operational work in reindeer management. This project can serve as a model for participatory involvement and planning, bringing indigenous knowledge and advanced remote-sensing techniques together in an interactive process.

We describe an approach to estimation of the spatial distribution of reindeer (Rangifer tarandus). Spatial autocorrelation, inherent to the data describing the distribution of wildlife species, contains information that can be utilized to improve the effciency of field inventories. Our data included reindeer fecal pellet counts, satellite imagery and a digital terrain model. We applied ordinary logistic regression, autologistic regression, and the Gibbs sampler to predict spatial distribution of reindeer based on the combined data. A training set was used to compare the outcome for different field sampling designs for each method. Results suggested the possibility to reduce the number of plots by up to 75% with a 15% reduction in prediction accuracy (quality). We also showed that the Gibbs sampler outperformed, in terms of accuracy, the logistic regression. The outcome, however, was dependent on the spectral homogeneity of the area and on the relative position of the sampling design to the elevation curves. Our results justify the incorporation of spatial information when modeling the distribution of reindeer at finer scales (< 1 km).

In this paper we discuss information theoretical landscape indices based on data from digitized maps in grid format: measures based on Shannon's entropy, e.g. the measures of diversity and contagion; and measures based on conditional entropy, e.g. a new index which can be seen as an alternative to the measure of contagion that does not have the disadvantage of being highly correlated to the measure of diversity. We also introduce a measurement on how much information is contained in a coarse-scale map about a fine-scale map.

Long-term trends in the Secchi depth of the Baltic Sea have been interpreted in terms of eutrophication (1, 2). The spectral attenuation coefficient K_d (490) can be estimated from remote sensing data (3). Given the empirical and theoretical relationships between diffuse attenuation and Secchi depth, it is therefore possible to estimate the trophic state from remote sensing data. This paper considers relationships among remotely sensed and in-water measured K_d (490), and Secchi depth data obtained during dedicated sea-truthing campaigns in the eastern Baltic Proper in 1999 (4) and in the western Baltic Proper/Himmerfjärden area during 2001 and 2002. In-water measurements are used to establish the relationship between the PAR and the spectral attenuation coefficient in the Baltic Sea via regression analysis. The analysis showed that in the area of investigation K_d (490) is about 1.48 times higher than K_d (PAR). This relationship is then used to define the link between the photic zone depth and the remote sensing optical depth, K_d (490)⁻¹. The results show that the depth of the euphotic zone is about 6.8 times K_d (490)⁻¹. The regression analysis between K_d (PAR) and Secchi depth confirmed previous work that K_d (PAR) is about 1.7 of the inverse Secchi depth. Furthermore, an in-water algorithm between Secchi depth and K_d (490) is used to simulate a Secchi depth map of the Baltic Sea from SeaWiFS K_d (490) data. This map is verified against sea-truthing data. K_d (490) data derived from satellite is compared to in situ K_d (490), and the sources of error are discussed.

The dramatic bleaching events on the coral reefs recently have enhanced the need for environmental monitoring. Remote sensing is an important constituent for monitoring of reefs, and an invaluable complement to field observations. This paper discusses the possibilities and limitations of present high resolution satellites for mapping and monitoring coral reefs. The sensors with the best spatial and radiometric resolution available today, e.g. IKONOS, can be useful for mapping and monitoring of reefs, but they are too costly for global surveys. However, our coral bleaching studies indicate that massive bleaching could be detected even from satellites with lower resolution, like Landsat, SPOT, and IRS. They could also be useful for coarser, from a spatial and thematic point of view, global mapping and updating purposes. A more detailed monitoring requires both better spatial resolution and spectral resolution than today's sensors. In the future, it is necessary to construct a more reef specific sensor with a few specially selected narrow bands and a good spatial, radiometric and temporal resolution.

The village with its characteristic zones of different land use from the center to the periphery is a basic unit of Europe's cultural landscapes. However, loss of the authentic pre-industrial village structure characterized by a fine-grained structure of arable land and wooded grasslands is a threat to both cultural heritage and biodiversity in many rural landscapes. Therefore, it is important that the extent and rate of change of such authentic villages in a landscape can be monitored. We studied to what extent loss of authenticity with increasing time after abandonment can be assessed by quantitative analysis and visual interpretation of satellite images. The study was carried out in the Bieszczady Mountains, SE Poland in 1999. Using Landsat Thematic Mapper data from 1998, both the grain size of landscape elements (size of fields) and land-cover composition (encroachment of shrub and forest) were quantitatively described 6 type villages representing different stages of deterioration of the authentic village structure. Historical maps were used to delineate the border of the villages and the former extension of forest and open land was measured. The present land use and the degree of abandonment expressed as grain size and forest encroachment were mapped using satellite data. Deterioration occurred along 2 transformation paths: abandonment and ultimately becoming forest, or intensified agriculture, respectively. To validate these results we classified 22 other villages in a 1000 km² area by visual interpretation of the original satellite images into 1 of 4 types. We then collected historical data on human population changes over the past six decades. The classification of village authenticity was clearly related to the rate of human population decline. We address the importance of validating and applying this approach for rapid assessment of the authenticity of cultural landscapes in European regions being subject to ongoing as well as expected future change, related to expansion of the European Union. Finally, we argue that the village represents a scale at which integration of natural and social sciences is possible.