The Land Use and Cover Area frame Statistical survey (LUCAS) aimed at the collecting harmonised data about the state of land use/cover over the extent of European Union (EU). Among these 2·105 land ...use/cover observations selected for validation, a topsoil survey was conducted at about 10% of these sites. Topsoil sampling locations were selected as to be representative of European landscape using a Latin hypercube stratified random sampling, taking into account CORINE land cover 2000, the Shuttle Radar Topography Mission (SRTM) DEM and its derived slope, aspect and curvature.
In this study we will discuss how the LUCAS topsoil database can be used to map soil properties at continental scale over the geographical extent of Europe. Several soil properties were predicted using hybrid approaches like regression kriging. In this paper we describe the prediction of topsoil texture and related derived physical properties. Regression models were fitted using, along other variables, remotely sensed data coming from the MODIS sensor. The high temporal resolution of MODIS allowed detecting changes in the vegetative response due to soil properties, which can then be used to map soil features distribution. We will also discuss the prediction of intrinsically collinear variables like soil texture which required the use of models capable of dealing with multivariate constrained dependent variables like Multivariate Adaptive Regression Splines (MARS).
Cross validation of the fitted models proved that the LUCAS dataset constitutes a good sample for mapping purposes leading to cross-validation R2 between 0.47 and 0.50 for soil texture and normalized errors between 4 and 10%.
•The LUCAS harmonised soil survey comprising 20,000 observations was used in this study.•Soil texture and coarse fragments were mapped over the extent of Europe using MARS.•MARS modelled soil texture with good accuracy whilst constraining their values.•AWC, soil bulk density and USDA textural classes were derived from soil texture maps.•These maps constitute a first approximation of the GlobalSoilMap products for Europe.
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•Global peatland area contains uncertainties due to current mapping techniques.•Low bulk density of peat allows airborne radiometric data to discriminate between peat and non-peat ...soils.•Machine learning classification with these data can be used to update current peatland area maps.•Local peatlands can be delineated beneath grassland and forestry cover.
Peatlands account for approx. 4.23 million km2 of the land surface of Earth and between 5 % and 20 % of the global soil carbon stock, however much uncertainty exists. The release of carbon from modified peatlands is significant and affects the global carbon balance. The importance of conservation and rehabilitation of peatlands is clear. Global estimates currently use national scale mapping strategies that vary depending on available resources and national interest. The most up-to-date methods rely on satellite remote sensing data, which detect peat based on a multiband spectral signature, or reflected radar backscatter. However, satellite data may not be capable of detecting peat under landcover such as pasture or forest. Airborne geophysical surveys provide relevant subsurface information to update or redefine peatland extent maps at a national scale. Radiometric surveys, which measure the naturally occurring geologically sourced potassium, uranium, and thorium, offer the largest potential. Modelling of gamma ray attenuation shows that peat has a distinctive attenuation signature, due to its low bulk density, when considering all recorded radiometric data. This study exploits this signature by combining airborne radiometric data in a machine learning framework and training an artificial neural network to detect those data which have been acquired over previously mapped peatlands. A ∼95 % predictability is achieved. The trained neural network can be then used to predict the extent of all peatlands within a region, including forested and agriculturally modified peatlands, and an updated peatland map can be produced. This methodology has implications for global carbon stock assessment and rehabilitation projects where similar datasets exist or are planned, by updating the extent and boundary positions of current peatlands and uncovering previously unknown peatlands under forestry or grasslands.
Monitoring of land cover (LC) provides important information of actual land use (LU) and landscape dynamics. LC research results depend on the size of the area, purpose and applied methodology. ...CORINE Land Cover (CLC) data is one of the most important sources of LU data from a European perspective. Our research compares official CLC data (third hierarchical level of nomenclature at a scale of 1:100,000) and national statistics (NS) of LU in Slovakia between 2000 and 2018 at national, county, and local levels. The most significant differences occurred in arable land and permanent grassland, which is also related to the recording method and the development of agricultural land management. Due to the abandonment of agricultural areas, a real recorded increase in forest cover due to forest succession was not introduced in the official records of Land register. New modification of CLC methodology for identifying LC classes at a scale of 1:10,000 and fifth hierarchical level of CLC is firstly applied for local case studies representing lowland, basin, and mountain landscape. The size of the least identified and simultaneously recorded area was established at 0.1 ha the minimum width of a polygon was established at 10 m, the minimum recorded width of linear elements such as communications was established at 2 m. The use of the fifth CLC level in the case studies areas generated average boundary density 17.2 km/km2, comparing to the 2.6 km/km2 of the third level. Therefore, when measuring the density of spatial information by the polygon boundary lengths, the fifth level carries 6.6 times more information than the third level. Detailed investigation of LU affords better verification of national statistics data at a local level. This study also contributes to a more detailed recording of the current state of the Central European landscape and its changes.
This study investigated the urban growth dynamics of urban regions. The study area was the Marmara Region, one of the most densely populated and ecologically diverse areas in Turkey. Using CORINE ...land cover data for 2006, 2012, and 2018, the study utilized multiple correspondence analyses and cluster analyses, to analyze land cover changes. The resulting maps, visualized in GIS, revealed the rapid urban transformation of the regional structure, formerly comprised of four distinct areas, into a more complex structure, in which densification and sprawl occur simultaneously. Our findings demonstrated a dissonance between the spatial dynamics of the Marmara Region during the study period, and the capacity and scope of the simultaneously initiated regional policies and mega-projects. This uncoordinated approach has endangered the region’s sustainable development. The paper, therefore, discusses the importance of land use planning and transboundary collaboration for sustainable regional development. Beyond the local case, the results contribute to critical theories in regional planning by linking theory and practice.
This study explores the historical occurrence of wetland ecosystems in Greece by using recurring Phragmites australis (common reed) burnings as an indicator. Phragmites australis, a plant closely ...associated with wetlands, provides excellent insights into wetland distribution. We establish a substantial association between reed fires and historical wetland existence in Greece using geographical and statistical analysis, with these fires exhibiting remarkable constancy across time. Using Corine land-cover (CLC) data, we extend our analysis into land-use dynamics, demonstrating that places with the highest reed-bed-fire rates were originally wetlands, particularly those converted into permanent irrigated land and areas with complex agriculture patterns. We find spatial commonalities between reed fires and past wetland existence by analyzing fire occurrence across three main categories: reed fires, agricultural land fires, and grassland fires. Historical records of wetland conversion into agricultural land (or land reclamation works) in locations such as Yianitsa and Kopaida give context to our findings. Visualizations confirm the clustering of reed fires around these converted agricultural regions. In summary, our study offers a unique indicator based on Phragmites australis burnings that can be used to identify previous wetland-type ecosystems, with Mediterranean-wide implications. Despite data constraints, this study adds to the conversation about wetland preservation and sustainable land-use management.
Water resources is crucial for the continuity of life. Therefore, mapping water resources is required. Successful analysis of remotely sensed images can provide reliable information for water ...researches. However, it is very complex process to ensure that the maps created are not affected by shadows, cloud or other noise. In addition, it is necessary to successfully map all water types in various geographies. It is important that the method used is practical so that scientists who are not image analysts can use the large data pool provided by satellite images. In this paper, a novel algorithm for water body extraction from Landsat imagery is proposed. In this method, Corine data are used as auxiliary data to automatically generate training data. Four study areas with different characteristics, from different parts of the world, are used to test the proposed method. The results obtained are compared with other automatic classification methods.
Soil erosion in mountainous regions is a key issue in land use planning, and this is particularly true in the Alps where intense anthropogenic influences at low elevations and abandonment in higher ...regions often coexist to affect soils. Natural hazard and risk assessment are essential given the density of settlements and associated facilities. Soil loss due to water erosion is very common and is becoming more frequent as a consequence of climate change which affects precipitation regimes, frequency of extreme meteorological events, snow melt and vegetation. In this study, we describe the production of a map showing susceptibility to soil erosion in the Aosta Valley (northwest Italian Alps). Most research on slope instability has focused on rock failures, but we investigated upper soil horizons by analysing chemical and physical properties, which could contribute to slope instability. The steps involved in creating the map are explained, and these involved GIS overlay, sampling, soil description, selection of relevant chemical and physical indicators of soil susceptibility to erosion, and overall erosion susceptibility assessment. The resultant indicator values correspond well with field observations to thus validate the methodology and demonstrate its usefulness in land use planning and management in Alpine areas.
A spatially distributed soil erosion and sediment delivery model (WATEM/SEDEM) was applied to the Scheldt River Basin (19,000 km
2) using SRTM elevation data with a 3″ resolution, and CORINE Land ...Cover data which are available at a resolution of 100 m. Transport capacity coefficients in the model were first calibrated using observed sediment yield data and WATEM/SEDEM predictions made with a higher resolution DEM derived from contour maps. When optimal transport capacity values are used, the calibrated model with SRTM data has an overall model efficiency of 0.79 for area-specific sediment yield and 0.95 for total sediment yield.
R-square values between observed and predicted sediment yields are >
0.8. Optimal calibration values are much smaller than those obtained from a higher resolution model, illustrating the need for recalibrating distributed models when input data with different accuracies or resolution are used. Application of the calibrated model to the Scheldt River Basin estimated the total sediment supply from hillslopes to the river channels in the basin at 1.9
×
10
6 t year
−
1
. Model results indicate a large spatial variability in hillslope sediment delivery, with the major sediment sources situated in the upper parts of the river basin. It is shown that the decrease in area-specific sediment yield with increasing catchment area can already be explained by the increasing importance of lower slope gradients in the lower parts of the river basin, without taking into account of floodplain sediment storage.
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