Impact of data integration technique on historical land-use/land-cover change: Comparing historical maps with remote sensing data in the Belgian Ardennes

Historical reconstructions of land-use/cover change often require comparing maps derived from different sources. The objective of this study was to measure land-use/cover changes over the last 225 years at the scale of a Belgian landscape, Lierneux in Ardennes, on the basis of a heterogeneous time series of land cover data. The comparability between the land-cover maps was increased following a method of data integration by map generalisation. Two types of time series were built by integrating the maps either by reference to the initial map of the time series or by pair of successive maps. Land-cover change detection was performed on the initial time series without data integration and on the two types of integrated time series. Results reveal that land cover and landscape structure have been subject to profound changes in Lierneux since 1775, with an annual rate of change at the landscape level of up to 1.40%. The major land-cover change processes observed are expansion of grasslands-croplands and reforestation with coniferous species, leading to amore fragmented landscape structure. The annual rates of land-cover change estimated from integrated data are significantly different from the annual rates of change estimated without a prior integration of the data. There is a trade-off between going as far back in time as possibleversus performing change detection as accurately as possible. This revised version was published online in July 2006 with corrections to the Cover Date.     

Six key steps for functional landscape analyses of habitat change

Landscape Ecology - An important part of landscape ecology is to identify relationships between landscape characteristics and ecological processes. One common approach to this is relating raster...     

Effects of land-cover change on spatial pattern of forest communities in the Southern Appalachian Mountains (USA)

Landscape Ecology - Understanding the implications of past, present and future patterns of human land use for biodiversity and ecosystem function is increasingly important in landscape ecology. We...     

A multi-species approach for assessing the impact of land-cover changes on landscape connectivity

Context

Land-cover changes (LCCs) could impact wildlife populations through gains or losses of natural habitats and changes in the landscape mosaic. To assess such impacts, we need to focus on landscape connectivity from a diachronic perspective.

Objectives

We propose a method for assessing the impact of LCCs on landscape connectivity through a multi-species approach based on graph theory. To do this, we combine two approaches devised to spatialize the variation of multi-species connectivity and to quantify the importance of types of LCCs for single-species connectivity by highlighting the possible contradictory effects.

Methods

We begin with a list of landscape species and create virtual species with similar ecological requirements. We model the ecological network of these virtual species at two dates and compute the variation of a local and global connectivity metric to assess the impacts of the LCCs on their dispersal capacities.

Results

The spatial variation of multi-species connectivity showed that local impacts range from ?6.4% to +3.2%. The assessment of the impacts of types of LCCs showed a variation in global connectivity ranging from ?45.1% for open-area reptiles to +170.2% for natural open-area birds with low-dispersion capacities.

Conclusions

This generic approach can be reproduced in a large variety of spatial contexts by adapting the selection of the initial species. The proposed method could inform and guide conservation actions and landscape management strategies so as to enhance or maintain connectivity for species at a landscape scale.

     

Indices of landscape pattern

Landscape ecology deals with the patterning of ecosystems in space. Methods are needed to quantify aspects of spatial pattern that can be correlated with ecological processes. The present paper develops three indices of pattern derived from information theory and fractal geometry. Using digitized maps, the indices are calculated for 94 quadrangles covering most of the eastern United States. The indices are shown to be reasonably independent of each other and to capture major features of landscape pattern. One of the indices, the fractal dimension, is shown to be correlated with the degree of human manipulation of the landscape.     

Influence of land-use/land-cover change on landscape connectivity for an endemic threatened amphibian (Argenteohyla siemersi pederseni,Anura: Hylidae)

Context

Modifications in natural landcover generally result in a loss of habitat availability for wildlife and it’s persistence will depend largely on their spatial configuration and functional connections. Argenteohyla siemersi is a threatened and endemic amphibian whose habitat is composed of forest patches near rivers and water bodies edges.

Objectives

This study aimed to analyse the accessible habitat for this species and identify key elements to maintain its ecological network in two different types of land uses: an anthropized area with extensive cattle raising and a protected area.

Methods

The structural and functional characteristics of both landscapes were analyzed. The connectivity at landscape level and the contribution of each habitat patch were evaluated through simulation models with different dispersion distances in the context of the graph theory.

Results

In both landscapes, nine types of landcover were identified with different compositions. Remarkable differences were found in habitat connectivity for this amphibian species between both landscapes. As the percentage of dispersion distance increases, reachable habitat increases as well, although with higher percentages in the protected area. Two corridors were identified in the protected landscape and one in the rangeland one; patches and key links constituted all of them.

Conclusions

The present work provides spatially explicit results with a quantitative basis. It could be useful as a tool for the development of management plans aimed at guaranteeing the functionality of the ecological network for this endangered species and, therefore, contribute to its long-term conservation.

     

Analysis of land-cover transitions based on 17th and 18th century cadastral maps and aerial photographs

This paper explores the possibility of using non-geometric cadastral maps from the 17th and 18th century together with aerial photographs from 1945 and 1981 to analyse land-cover change in south-east Sweden. Habitats rich in plant species in the European rural landscape seem to be correlated with a long continuity of management. Accurate spatial data from historical data sources are fundamental to understand patterns of vegetation and biodiversity in the present-day landscape. However, traditional methods for rectification of non-geometric maps using corresponding points from orthophotos or modern maps are not satisfying, as internal inaccuracies will remain in the maps. This study presents a method to rectify the maps by local warping, thereby eliminating geometrical irregularities. Further, the land-cover changes were calculated and presented as transition matrices. The extent of arable fields and grasslands were analysed in relation to soil characteristics and continuity of management. The results show a dynamic relation between grassland and arable field, albeit the overall proportions remained almost the same between 17th and 18th centuries: 60% grassland to 32% arable field. The most substantial changes in land-cover were prior to 1945. Today there is 18% grasslands left in the study area, while 56% of the land-cover is arable field. Approximately 8% of present-day land-cover is semi-natural grassland 300 years of age or more. Compared to 300 years ago there is only 1% grassland left on peat and 2% on clay. In contrast, grassland covers associated with bare bedrock have been fairly stable in size. All semi-natural grasslands with a long continuity of management were situated on shallow soils, less than 50 cm depth. The major conclusions from this study are that (i) correctly rectified, old maps are very useful to address questions of land-cover changes in historical time, (ii) general trends in land use over 300 years in this hemi-boreal landscape seem to underestimate the full dynamics of land use change, and (iii) only a small proportion of the semi-natural grassland area had a 300 year continuity of management.     

Elasticity and loop analyses: tools for understanding forest landscape response to climatic change in spatial dynamic models

Spatially explicit dynamic forest landscape models have been important tools to study large-scale forest landscape response under global climatic change. However, the quantification of relative importance of different transition pathways among different forest types to forest landscape dynamics stands as a significant challenge. In this study, we propose a novel approach of elasticity and loop analyses to identify important transition pathways contributing to forest landscape dynamics. The elasticity analysis calculates the elasticity to measure the importance of one-directional transitions (transition from one forest type directly to another forest type); while the loop analysis is employed to measure the importance of different circular transition pathways (transition from one forest type through other forest types back to itself). We apply the proposed approach to a spatially explicit dynamic model, LANDIS-II, in a study of forest landscape response to climatic change in the Boundary Waters Canoe Area (BWCA) incorporating the uncertainties in climatic change predictions. Our results not only corroborate the findings of the previous studies on the most likely future forest compositions under simulated climatic variability, but also, through the novel application of the elasticity and loop analyses concepts, provide a quantitative assessment of the specific mechanisms leading to particular forest compositions, some of which might remain undetected with conventional model evaluation methods. By quantifying the importance of specific processes (transitions among forest types) to forest composition dynamics, the proposed approach can be a valuable tool for a more quantitative understanding of the relationship between processes and landscape composition/patterns.     

The influence of patch-delineation mismatches on multi-temporal landscape pattern analysis

Investigations of land-cover change often employ metrics designed to quantify changes in landscape structure through time, using analyses of land cover maps derived from the classification of remote sensing images from two or more time periods. Unfortunately, the validity of these landscape pattern analyses (LPA) can be compromised by the presence of spurious change, i.e., differences between map products caused by classification error rather than real changes on the ground. To reduce this problem, multi-temporal time series of land-cover maps can be constructed by updating (projecting forward in time) and backdating (projecting backward in time) an existing reference map, wherein regions of change are delineated through bi-temporal change analysis and overlaid onto the reference map. However, this procedure itself creates challenges, because sliver patches can occur in cases where the boundaries of the change regions do not exactly match the land-cover patches in the reference map. In this paper, we describe how sliver patches can inadvertently be created through the backdating and updating of land-cover maps, and document their impact on the magnitude and trajectory of four popular landscape metrics: number of patches (NP), edge density (ED), mean patch size (MPS), and mean shape index (MSI). In our findings, sliver patches led to significant distortions in both the value and temporal behaviour of metrics. In backdated maps, these distortions caused metric trajectories to appear more conservative, suggesting lower rates of change for ED and inverse trajectories for NP, MPS and MSI. In updated maps, slivers caused metric trajectories to appear more extreme and exaggerated, suggesting higher rates of change for all four metrics. Our research underscores the need to eliminate sliver patches from any study dealing with multi-temporal LPA.     

A review of models of landscape change

Models of landscape change may serve a variety of purposes, from exploring the interaction of natural processes to evaluating proposed management treatments. These models can be categorized as either whole landscape models, distributional landscape models, or spatial landscape models, depending on the amount of detail included in the models. Distributional models, while widely used, exclude spatial detail important for most landscape ecological research. Spatial models require substantial data, now more readily available, via remote sensing, and more easily manipulated, in geographical information systems. In spite of these technical advances, spatial modelling is poorly developed, largely because landscape change itself is poorly understood.To facilitate further development of landscape models I suggest (1) empirical multivariate studies of landscape change, (2) modelling of individual landscape processes, (3) explicit study of the effect of model scale on model behavior, and (4) scaling-up results of studies, on smaller land areas, that have landscape relevance.     

Forty-eight years of landscape change on two contiguous Ohio landscapes

This study analyzes the current and historic structure of two contiguous, rural landscapes covering approximately 242 km² in central Ohio, USA: a till plain landscape with relatively homogeneous topography and soils, and a moraine landscape with greater geomorphological diversity and heterogeneity. These landscapes were chosen because they were both heavily dominated by agriculture during 1900–1940 and were both initially surveyed by the metes-and-bounds system. They differed, however, in the temporal pattern of settlement and development and in the inherent agricultural capability of their soils. We combined analysis of aerial photographs from 1940, 1957, 1971, and 1988 with historical archives and other available mapped data in a GIS data base to facilitate analysis of both spatial and temporal patterns of change. On the moraine, the agricultural matrix decreased over time as forest, urban/suburban areas, and industry increased. In contrast, on the till plain agricultural landcover increased through 1988, with concommitant decreases in upland forest and oak savanna. The moraine landscape exhibited greater diversity and equitability than the till plain on each date. The till plain had its greatest diversity and equitability in 1940, whereas the moraine increased in diversity and equitability during each time period. The undulating topography of the moraine encouraged landcover dynamism rather than stability, whereas the more homogeneous till plain exhibited considerable inertia. Patch and matrix shape remained constant and predominantly angular over the 48 year study period. Differences in the physical environment, especially topography and soil capability, and the socioeconomic environment, especially agricultural policies and patterns of urbanization, resulted in these two contiguous landscapes having different trajectories of change. It is clear from this study that socioeconomic factors must be combined with the physical setting to fully understand patterns of change in human-dominated landscapes.     

The spatial pattern of a northern conifer-hardwood landscape

A geographic information system, fractal analyses, and statistical methods were used to examine the spatial distributions of old growth hemlock, northern hardwood, mixed hardwood/hemlock stands and wetlands with respect to each other and also soils and topography. Greater than 80% of the stands of any covertype were less than 20 ha in area. Nearly pure hemlock and northern hardwood stands were associated with soils having a fragipan, while mixed hardwood/hemlock stands were associated with sandier soils. Hemlock stands were distributed independently of hardwood and mixed hardwood/hemlock stands, but hardwood and mixed hardwood/hemlock stands were usually surrounded by hemlock. Bogs and lakes were usually surrounded by hemlock stands and are distributed independently of hardwood stands. The shapes of all stands vary from extremely simple to extremely complex, with a general tendency for hemlock stands to be more convoluted than hardwoods. The analyses suggest segregation across soil types and a disturbance regime favoring the establishment of hardwoods and mixed hardwood/hemlock stands in a hemlock matrix as reasons for the origin of the observed spatial patterns.     

Effects of changing spatial scale on the analysis of landscape pattern

The purpose of this study was to observe the effects of changing the grain (the first level of spatial resolution possible with a given data set) and extent (the total area of the study) of landscape data on observed spatial patterns and to identify some general rules for comparing measures obtained at different scales. Simple random maps, maps with contagion (i.e., clusters of the same land cover type), and actual landscape data from USGS land use (LUDA) data maps were used in the analyses. Landscape patterns were compared using indices measuring diversity (H), dominance (D) and contagion (C). Rare land cover types were lost as grain became coarser. This loss could be predicted analytically for random maps with two land cover types, and it was observed in actual landscapes as grain was increased experimentally. However, the rate of loss was influenced by the spatial pattern. Land cover types that were clumped disappeared slowly or were retained with increasing grain, whereas cover types that were dispersed were lost rapidly. The diversity index decreased linearly with increasing grain size, but dominance and contagion did not show a linear relationship. The indices D and C increased with increasing extent, but H exhibited a variable response. The indices were sensitive to the number (m) of cover types observed in the data set and the fraction of the landscape occupied by each cover type (P _k); both m and P _kvaried with grain and extent. Qualitative and quantitative changes in measurements across spatial scales will differ depending on how scale is defined. Characterizing the relationships between ecological measurements and the grain or extent of the data may make it possible to predict or correct for the loss of information with changes in spatial scale.     

Effects of changing scale on landscape pattern analysis: scaling relations

Landscape pattern is spatially correlated and scale-dependent. Thus, understanding landscape structure and functioning requires multiscale information, and scaling functions are the most precise and concise way of quantifying multiscale characteristics explicitly. The major objective of this study was to explore if there are any scaling relations for landscape pattern when it is measured over a range of scales (grain size and extent). The results showed that the responses of landscape metrics to changing scale fell into two categories when computed at the class level (i.e., for individual land cover types): simple scaling functions and unpredictable behavior. Similarly, three categories were found at the landscape level, with the third being staircase pattern, in a previous study when all land cover types were combined together. In general, scaling relations were more variable at the class level than at the landscape level, and more consistent and predictable with changing grain size than with changing extent at both levels. Considering that the landscapes under study were quite diverse in terms of both composition and configuration, these results seem robust. This study highlights the need for multiscale analysis in order to adequately characterize and monitor landscape heterogeneity, and provides insights into the scaling of landscape patterns. This revised version was published online in May 2005 with corrections to the Cover Date. This revised version was published online in July 2006 with corrections to the Cover Date.     

Scale dependence in quantification of land-cover and biomass change over Siberian boreal forest landscapes

We investigated the influence of remote sensing spatial resolution on estimates of characteristic land-cover change (LCC) and LCC-related above-ground biomass change (Δbiomass) in three study sites representative of the East Siberian boreal forest. Data included LCC estimated using an existing Landsat-derived land-cover dataset for 1990 and 2000, and above-ground standing biomass stocks simulated by the FAREAST forest succession model and applied on a pixel basis. At the base 60 m resolution, several landscape pattern metrics were derived to describe the characteristic LCC types. LCC data were progressively degraded to 240, 480, and 960 m. LCC proportions and Δbiomass were derived at each of the coarser resolutions and scale dependences of LCC and Δbiomass were analyzed. Compared to the base 60 m resolution, the Logged LCC type was highly scale dependent and was consistently underestimated at coarser resolutions. The Burned type was under- or over-estimated depending strongly on its patch size. Estimated at the base 60 m resolution, modeled biomass increased in two sites (i.e., 3.0 and 6.4 Mg C ha⁻¹ for the Tomsk and Krasnoyarsk sites, respectively) and declined slightly in one site (i.e., −0.5 Mg C ha⁻¹ for the Irkutsk site) between the two dates. At the degraded resolutions, the estimated Δbiomass increased to 3.3 and 7.0 Mg C ha⁻¹ for the Tomsk and Krasnoyarsk sites, while it declined to −0.8 Mg C ha⁻¹ for the Irkutsk site. Results indicate that LCC and Δbiomass values may be progressively amplified in either direction as resolution is degraded, depending on the mean patch size (MPS) of disturbances, and that the error of LCC and Δbiomass estimates also increases at coarser resolutions.     

Impact of agricultural subsidies on biodiversity at the landscape level

Agricultural management is a major factor driving the change of faunal richness in anthropogenic landscapes. Thus, there is an urgent need to develop tools that allow decision-makers to understand better intended and unintended effects of agricultural policy measures on biodiversity. Here we demonstrate the potential of such a tool by combining a socio-economic model with the biodiversity model GEPARD to forecast the response of bird and carabid species richness to two scenarios of agricultural subsidies: (1) subsidies based on production levels and prices and (2) direct income support that is independent of production levels. We focussed on farmland of the Lahn-Dill area, Germany, as an example of European regions with low intensity farming. GEPARD predicts faunal richness and is based on multi-scaled resource-selection functions. Under both scenarios the area of predicted losses in species richness of birds and carabids was larger than the area of predicted gains in species richness. However, the area with predicted losses of avian richness was smaller under the direct income support scenario than under the production-based subsidy scenario, whereas the area with predicted losses of carabid species richness was smaller under the production-based subsidy scenario than under the direct income support. Yet locally, richness gains of up to four species were predicted for carabids under both scenarios. We conclude that the sometimes contrasting and heterogeneous responses of birds and carabids at different localities suggest the need for spatially targeted subsidy schemes. With the help of the GIS-based approach presented in this study, prediction maps on potential changes in local and regional species richness can be easily generated.     

A factor analysis of landscape pattern and structure metrics

Fifty-five metrics of landscape pattern and structure were calculated for 85 maps of land use and land cover. A multivariate factor analysis was used to identify the common axes (or dimensions) of pattern and structure which were measured by a reduced set of 26 metrics. The first six factors explained about 87% of the variation in the 26 landscape metrics. These factors were interpreted as composite measures of average patch compaction, overall image texture, average patch shape, patch perimeter-area scaling, number of attribute classes, and large-patch density-area scaling. We suggest that these factors can be represented in a simpler way by six univariate metrics - average perimeter-area ratio, contagion, standardized patch shape, patch perimeter-area scaling, number of attribute classes, and large-patch density-area scaling.     

Neutral models for the analysis of broad-scale landscape pattern

The relationship between a landscape process and observed patterns can be rigorously tested only if the expected pattern in the absence of the process is known. We used methods derived from percolation theory to construct neutral landscape models,i.e., models lacking effects due to topography, contagion, disturbance history, and related ecological processes. This paper analyzes the patterns generated by these models, and compares the results with observed landscape patterns. The analysis shows that number, size, and shape of patches changes as a function of p, the fraction of the landscape occupied by the habitat type of interest, and m, the linear dimension of the map. The adaptation of percolation theory to finite scales provides a baseline for statistical comparison with landscape data. When USGS land use data (LUDA) maps are compared to random maps produced by percolation models, significant differences in the number, size distribution, and the area/perimeter (fractal dimension) indices of patches were found. These results make it possible to define the appropriate scales at which disturbance and landscape processes interact to affect landscape patterns.     

Temporal (1958–1995) pattern of change in a cultural landscape of northwestern Portugal: implications for fire occurrence

In this paper we test the hypothesis that landscape changes in a region of Northern Portugal (Minho) in the last 40 years could be predicted from socioeconomic and political history. The major predicted changes were related to agricultural abandonment and afforestation. We further predicted that these changes contributed to increased fire risk. Analysis of aerial photography for the years 1958, 1968, 1983 and 1995 in a study area of 3700 ha revealed a significant decline in agricultural areas and low shrublands and an increase in tall shrublands and forests. This represented a 20–40% increase in fuel accumulation at a landscape level, suggesting that the abandonment of farming activities is a major driving force of increasing fire occurrence in the region. With one exception, all the predictions were partly or totally confirmed. This study confirms that socioeconomic factors might explain a significant part of the variation in landscape composition across time, in the Mediterranean region.     

Impact of agricultural landscape structure on energy flow and water cycling

In long term studies the following climatological characteristics were measured or calculated: air and soil temperature, sunshine, wind speed, vapor pressure, saturation deficit, precipitation, humidity, incoming and reflected solar energy, energy emitted by active surfaces and primary production. Taking into account the relationships between climatological characteristics, the growth stages of vegetation, and relations between heat balance components, the fluxes of energy used for evapotranspiration, air, and soil heating were estimated in various ecosystems composing the agricultural landscape. The energy contained in biomass production of various crops was estimated also. Aggregate estimates of energy flow connected with evapotranspiration, and soil and air heating were calculated for eight model landscapes which differed by the plant cover structure. A higher variability of energy fluxes was observed for individual ecosystems than for agricultural land-scapes. It was shown that the structure of the plant cover has an important bearing on energy flow and water cycling both by direct and indirect influences. Shelterbelts are especially important in their influence on energy flow and water cycling.Studies carried out within the project CPBP.04.10.03.