From pollen percentage to vegetation cover: evaluation of the Landscape Reconstruction Algorithm in western Norway

The Landscape Reconstruction Algorithm (LRA) with the two models REVEALS and LOVE is developed to transform pollen percentage data to vegetation cover. This paper presents the first study to evaluate LRA in a region with large topographic variations within a short distances. The REVEALS model estimates regional vegetation abundance based on pollen assemblages from large lakes (100–500 ha). Pollen surface samples from one large and 28 small lakes are used together with a combination of regionally derived pollen productivity estimates and available estimates from other regions of Europe. The results show a good relationship between REVEALS‐estimated forest cover and vegetation abundance based on the CORINE land‐cover data. The REVEALS results using various sets of pollen assemblages from small lakes were comparable to those using one large lake. Local vegetation abundance using the LOVE model was estimated around 26 lakes. For common taxa, such as Pinus and Poaceae, the LOVE‐based estimates of plant abundance match well with the distance‐weighted plant abundances based on vegetation maps. Our results indicate that the LRA approach is effective for reconstruction of long‐term vegetation changes in western Norway and other regions with high topographic relief when no major gradients exist in the pollen data.     

Assessment of Constraint Factors of Resources and Environment of Sustainable Development in the Beijing-Tianjin-Hebeiregion: Based on the Framework of Landscape Sustainability Science

The Beijing-Tianjin-Hebei (BTH) region is an important engine for China’s socioeconomic development. Timely and effectively assessing constraint factors of resources and environment is of great significance for the sustainability assessment and the sustainable development of this region. However, comprehensive assessment research considering key resource and environmental constraints are still lacking. In this study, therefore, the limiting factors of resources and the environment in the BTH region were assessed based on the framework of landscape sustainability science. First, we chose five limiting factors, including topographic condition, geological environment, water resource, land resource, and atmospheric environment, to assess the constraints of resources and the environment using the single-factor evaluation method and the multi-factor comprehensive evaluation method. Based on the results, we divided the whole region into five subregions, i.e., the ecological conservation subregion, the geological disaster subregion, the water resource scarcity subregion, the atmospheric pollution subregion, and the cropland protection subregion. The results revealed that the northern BTH region was highly constrained by topographic conditions, the central BTH region was strongly constrained by geological environment and water resources, whereas the southern BTH region was constrained mainly by land resources and atmospheric environment. In addition, water resource was the main limiting factor for regional population growth and economic development. In 2010, the water resource scarcity subregion had a total population of 39.59 million, an urban population of 76.90%, and a gross domestic product of 2 455.57 billion yuan. We argue that the sustainable development of the BTH region should explicitly consider the resource and environmental limiting factors, implement land use optimization according to local conditions, maintain multiple land use types and diverse management strategies, based on the perspective of “strong sustainability”, so as to promote the regional sustainable development.     

Monitoring land changes in an urban area using satellite imagery,GIS and landscape metrics

Monitoring land changes is an important activity in landscape planning and resource management. In this study, we analyze urban land changes in Atlanta metropolitan area through the combined use of satellite imagery, geographic information systems (GIS), and landscape metrics. The study site is a fast-growing large metropolis in the United States, which contains a mosaic of complex landscape types. Our method consisted of two major components: remote sensing-based land classification and GIS-based land change analysis. Specifically, we adopted a stratified image classification strategy combined with a GIS-based spatial reclassification procedure to map land classes from Landsat Thematic Mapper (TM) scenes acquired in two different years. Then, we analyzed the spatial variation and expansion of urban land changes across the entire metropolitan area through post classification change detection and a variety of GIS-based operations. We further examined the size, pattern, and nature of land changes using landscape metrics to examine the size, pattern, and nature of land changes. This study has demonstrated the usefulness of integrating remote sensing with GIS and landscape metrics in land change analysis that allows the characterization of spatial patterns and helps reveal the underlying processes of urban land changes. Our results indicate a transition of urbanization patterns in the study site with a limited outward expansion despite the dominant suburbanization process.     

Detection of foreclosure-related landscape management changes using Landsat

The volume of properties affected by foreclosure over the past decade suggests the potential for dramatic change in vegetation cover due to changes in management. Yet, the specific pathology of each foreclosure, the temporal asynchrony among foreclosures, and differences in the area available for vegetation growth across properties presents challenges to observing and measuring change. This paper develops and tests a difference in deviations approach that compares the parcel NDVI to a neighborhood norm before and after foreclosure. The difference in deviations approach addresses the challenges of separating parcel-level change corresponding to foreclosure and identifies changes on both small and large parcels. The method relies on a time series of Landsat Normalized Difference Vegetation Index (NDVI) data, individual home foreclosure records and property tax assessment data for Maricopa County, Arizona from 2002 to 2012. To establish the level of difference associated with observable landscape change, we use a probit regression model, coding Google Earth images for properties across the range of observed deviations of difference. The basic assumption underlying the approach is that if foreclosure coincides with a change in management, it will lead to changes in vegetation structure and thus, NDVI values. We estimate that 13% of home foreclosures in Maricopa County over the period from 2002 to 2012 resulted in declines in vegetation whereas 6.5% resulted in vegetation increases. Future uses of this method for understanding landscape management in residential landscapes are discussed.     

Satellite monitoring of urbanization and environmental impacts—A comparison of Stockholm and Shanghai

This study investigates urbanization and its potential environmental consequences in Shanghai and Stockholm metropolitan areas over two decades. Changes in land use/land cover are estimated from support vector machine classifications of Landsat mosaics with grey-level co-occurrence matrix features. Landscape metrics are used to investigate changes in landscape composition and configuration and to draw preliminary conclusions about environmental impacts. Speed and magnitude of urbanization is calculated by urbanization indices and the resulting impacts on the environment are quantified by ecosystem services. Growth of urban areas and urban green spaces occurred at the expense of cropland in both regions. Alongside a decrease in natural land cover, urban areas increased by approximately 120% in Shanghai, nearly ten times as much as in Stockholm, where the most significant land cover change was a 12% urban expansion that mostly replaced agricultural areas. From the landscape metrics results, it appears that fragmentation in both study regions occurred mainly due to the growth of high density built-up areas in previously more natural/agricultural environments, while the expansion of low density built-up areas was for the most part in conjunction with pre-existing patches. Urban growth resulted in ecosystem service value losses of approximately 445 million US dollars in Shanghai, mostly due to the decrease in natural coastal wetlands while in Stockholm the value of ecosystem services changed very little. Total urban growth in Shanghai was 1768 km² and 100 km² in Stockholm. The developed methodology is considered a straight-forward low-cost globally applicable approach to quantitatively and qualitatively evaluate urban growth patterns that could help to address spatial, economic and ecological questions in urban and regional planning.     

APPLICATION OF PATTERN RECOGNITION TO SPECIATION DATA OF HEAVY METALS IN SUSPENDED PARTICULATES OF URBAN AIR

In order to get a better knowledge of the air pollution levels of the urban air of Barcelona,twelvesamples from three stations of the air-monitoring control network were analysed.Each control station isrepresentative of a different environmental situation.Thus the station at Plaa Molina responds to asimple domestic and urban traffic situation;the station at Poble Nou to the influence of medium andsmall industries,mainly metallurgical;and the station at Montcada to a zone in which there existimportant industries,a cement factory,two highways and railroads.The total content of unsedimentable particles,three inorganic anions(chlorides,sulphates andnitrates)and six heavy metals(Fe,Pb,Cu,Mn,Cr and Cd)were determined on all the samples obtainedduring the same period of time.The use of an analytical scheme of sequential extraction has alsopermitted the subdivision of the total content of each metal into the following four fractions:(1)solubleor exchangeable;(2)associated with carbonates and/or with iron and manganese oxides;(3)bound toorganic matter;and(4)residual.The use of principal component analysis applied to the data as a whole showed the associations andcorrelations between the various parameters as well as between the different above mentioned fractions.The predominant presence of Cd in the‘soluble or exchangeable’fraction is confirmed,while the othermetals are mainly associated with the‘carbonates and/or Fe and Mn oxides’and‘bound to organicmatter’fractions.Hierarchical cluster analysis applied to the twelve samples showed clearly the presence of threedifferent classes closely related to the origin(station)of the samples.Thus it becomes feasible to proposefor each station a possible profile of the content in terms of the different parameters considered.     

遥感图象的马尔柯夫随机场模型的纹理识别方法

本文讨论了马尔柯夫随机场图象模型及邻域选择方法,提出了8邻域5特征参数的马尔柯夫随机场图象模型以及一套完整而有效的特征参数的估计算法,将这些特征参数变成可视图象从而实现了视算。对8类不同纹理的标准图象进行分类试验,其识别(分类)的平均正确率达97.57％。     

Variations in species richness in hay-meadow vegetation at Voss,west Norway,in relation to long-term management practices

Because of its species-rich hay meadows and old pollards that are traditionally managed, Ulvund in Myrkdalen, Voss, is one of 14 areas in Hordaland county that are considered to be of special interest for cultural landscape conservation. The spatial patterns of species richness were investigated in hay meadows at Ulvund. Two main types of vegetation were recognised in managed meadows. Unfertilised and species-rich areas with a rather short field layer were situated in the steep parts of the meadows. Fertilised and species-poor areas with a high field layer were situated on flat or gently sloping areas. This spatial pattern is recognised in other west Norwegian hay meadows as well and is very likely linked to historical differences in land management; the flatter areas were formerly used as heavily fertilised permanent tilled fields for grain production, while the steep areas were used for hay production. As the conservation value largely lies in small, localized parts of the farms, conservation management actions can also be localized and thus feasible under modern conditions.     

Outside the boundary - Land use changes in the surroundings of urban nature reserves

The importance of the landscape surrounding a protected area for sustaining its values is frequently discussed in conservation literature. Studies on the interactions of urbanisation and nature conservation at the global scale suggest that protected nature attracts urbanisation, and that this in turn might negatively impact the area. However, studies specifically addressing such land use dynamics at city scale are largely missing. In this study we examine the change in proportion of built up area in two zones (500 m and 1000 m) surrounding 15 urban nature reserves in southern Sweden. By using comprehensive maps from the last 50 years, we compared the zones to the overall urbanisation in the cities to reveal discrepancies in land use surrounding the nature reserves. We found that the amount of built up area in the buffer zones surrounding nature reserves followed the same trend as the corresponding cities and this relation was stable over time, although the positive relationship was not significant. The establishment of nature reserves had no detectable effect on surrounding land use, however two distinguished groups of reserves were identified with either more or less built up area in buffers zones compared to cities. These differences were related to specific local drivers such as land ownership, land use history and nature reserve location. In contrast to earlier studies at global scale, our study did not show that nature reserves attract urbanisation. Instead, we stress that the great variety of contextual factors at the city scale makes quantitative analysis of this kind extremely difficult. However, a general neglect from planning and nature conservation agencies to recognise nature reserves’ dependence on the surrounding landscape configuration could be detrimental to sustain their values in the long-term. Hence we suggest that zones surrounding nature-protected areas should be planned and managed according to local land use history and current landscape conditions to enable and enhance necessary cross-boundary interactions.