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1
Grodzynskyi, M. "Representation of soils in the landscapes maps." Visnyk of the Lviv University. Series Geography, no. 39 (December 11, 2011): 113–21. http://dx.doi.org/10.30970/vgg.2011.39.2169.
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Series (succession sequences) of soils that change each other over time and within the landscape units are proper objects for landscape mapping. The soil series give an idea of both retrospective state of a soil before its anthropogenic transformations and of tendencies of soil development in landscape complexes of various types. The names of soils as they are appeared in soil nomenclature of Soil science should not be duplicated in the legends of landscape maps. "Landscape" names for soils have to stress on their features and attributes that are of primary importance for vegetation, water, thermal and other ecological regimes of landscapes. The "landscape" names for different types of Albeluvisols and Phaeozems of Ukraine are suggested. Key words: soil, landscape, landscape map, landscape science.
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Bogdanova, M. D., M. I. Gerasimova, and V. A. Snytko. "Traditional approaches and new ideas of Maria Glazovskaya in thematic mapping." Geodesy and Cartography 947, no. 5 (June 20, 2019): 54–62. http://dx.doi.org/10.22389/0016-7126-2019-947-5-54-62.
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Professor Maria Glazovskaya (1912–2016) – an outstanding geographer, geochemist and soil scientist, made a prominent contribution to the formation and development of several aspects of thematic mapping both in conceptual and methodological issues. These aspects, namely, soil, landscape- and soil-geochemical, as well as ecological mapping, were derived from the knowledge on soils combined with the concepts of geochemical migrations facilities for certain chemical elements in soils and landscapes. Methodology of compilation of such maps presumes purposeful interpretation of diverse soil and landscape features, their expert evaluation and forecast of response reactions of soils and landscapes to certain technogenic loads. Maria Glazovskaya proposed innovative approaches to thematic mapping enabling her to compile original maps. She introduced the principle of “prognostic information capacity of natural factors”, which means that properties of landscape components contain information appropriate for evaluating the resilience of natural systems. The ideas and methods proposed by Maria Glazovskaya are now implemented in basic and applied thematic mapping.
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Ellili-Bargaoui, Yosra, Brendan Philip Malone, Didier Michot, Budiman Minasny, Sébastien Vincent, Christian Walter, and Blandine Lemercier. "Comparing three approaches of spatial disaggregation of legacy soil maps based on the Disaggregation and Harmonisation of Soil Map Units Through Resampled Classification Trees (DSMART) algorithm." SOIL 6, no. 2 (August 14, 2020): 371–88. http://dx.doi.org/10.5194/soil-6-371-2020.
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Abstract. Enhancing the spatial resolution of pedological information is a great challenge in the field of digital soil mapping (DSM). Several techniques have emerged to disaggregate conventional soil maps initially and are available at a coarser spatial resolution than required for solving environmental and agricultural issues. At the regional level, polygon maps represent soil cover as a tessellation of polygons defining soil map units (SMUs), where each SMU can include one or several soil type units (STUs) with given proportions derived from expert knowledge. Such polygon maps can be disaggregated at a finer spatial resolution by machine-learning algorithms, using the Disaggregation and Harmonisation of Soil Map Units Through Resampled Classification Trees (DSMART) algorithm. This study aimed to compare three approaches of the spatial disaggregation of legacy soil maps based on DSMART decision trees to test the hypothesis that the disaggregation of soil landscape distribution rules may improve the accuracy of the resulting soil maps. Overall, two modified DSMART algorithms (DSMART with extra soil profiles; DSMART with soil landscape relationships) and the original DSMART algorithm were tested. The quality of disaggregated soil maps at a 50 m resolution was assessed over a large study area (6775 km2) using an external validation based on 135 independent soil profiles selected by probability sampling, 755 legacy soil profiles and existing detailed 1:25 000 soil maps. Pairwise comparisons were also performed, using the Shannon entropy measure, to spatially locate the differences between disaggregated maps. The main results show that adding soil landscape relationships to the disaggregation process enhances the performance of the prediction of soil type distribution. Considering the three most probable STUs and using 135 independent soil profiles, the overall accuracy measures (the percentage of soil profiles where predictions meet observations) are 19.8 % for DSMART with expert rules against 18.1 % for the original DSMART and 16.9 % for DSMART with extra soil profiles. These measures were almost 2 times higher when validated using 3×3 windows. They achieved 28.5 % for DSMART with soil landscape relationships and 25.3 % and 21 % for original DSMART and DSMART with extra soil observations, respectively. In general, adding soil landscape relationships and extra soil observations constraints allow the model to predict a specific STU that can occur in specific environmental conditions. Thus, including global soil landscape expert rules in the DSMART algorithm is crucial for obtaining consistent soil maps with a clear internal disaggregation of SMUs across the landscape.
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Rinder, GE, E. Fritsch, and RW Fitzpatrick. "Computing procedures for mapping soil features at sub-catchment scale." Soil Research 32, no. 5 (1994): 908. http://dx.doi.org/10.1071/sr9940909.
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Procedures for detailed mapping of a large number of soil features in small landscape units displayed in either vertical cross section (i.e. soil toposequences) or horizontal plane (i.e. soil maps) are presented. Rom hand coloured drawings that display the soil-landscape features, an Apple Macintosh Computer, with Adobe Illustrator and Adobe Patterns and Textures programs, is used to produce high quality coloured maps ready for reproduction in any form (e.g. posters, publications, slides or overhead transparencies). The first step is to produce the detailed computer map with all soil features included. This detailed computer map is made up of the following three layers or bases: (i) a black linework and lettering base, (ii) a polygon base filled with black and white textures, and (iii) a polygon base filled with colours. The detailed computer map, saved as the master file, is very easily modified to generate more simplified and thematic maps by: (i) grouping soil features into larger soil components in order to display soil-landscapes in a more simplified form, (ii) deleting certain soil-landscape components in order to highlight specific soil features, and (iii) adding newly aquired information (e.g. chemical and hydrological data) to previous versions.
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Schmidt, Jochen, Phil Tonkin, and Allan Hewitt. "Quantitative soil - landscape models for the Haldon and Hurunui soil sets, New Zealand." Soil Research 43, no. 2 (2005): 127. http://dx.doi.org/10.1071/sr04074.
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Limited resources and large areas of steeplands with limited field access forced soil and land resource surveyors in New Zealand often to develop generalised models of soil–landscape relationships and to use these to produce soil maps by manual interpretation of aerial photographs and field survey. This method is subjective and non-reproducible. Recent studies showed the utility of digital information and analysis to complement manual soil survey. The study presents quantitative soil–landscape models for the Hurunui and Haldon soil sets (New Zealand), developed from conceptual soil–landscape models. Spatial modelling techniques, including terrain analysis and fuzzy classification, are applied to compute membership maps of landform components for the study areas. The membership maps can be used to derive a ‘hard’ classification of land components and uncertainty maps. A soil taxonomic model is developed based on field data (soil profiles), which attaches dominant soil profiles and soil properties, including their uncertainties, to the defined land components. The method presented in this study is proposed as a potential technique for modelling land components of steepland areas in New Zealand, in which the spatial soil variation is dominantly controlled by landform properties. A soil map was developed that includes the uncertainty in the fundamental definitions of landscape units and the variability of soil properties within landscape units.
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Matasova, I. Y. "LANDSCAPE AND GEOCHEMICAL CHARACTERISTICS OF THE BLACK SEA COAST OF RUSSIA." ECOLOGY ECONOMY INFORMATICS. GEOINFORMATION TECHNOLOGIES AND SPACE MONITORING 2, no. 5 (2020): 147–54. http://dx.doi.org/10.23885/2500-123x-2020-2-5-147-154.
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The article is devoted to the use of landscape-geochemical mapping to study the spatial structure of the Black sea coast of Russia. Landscape-geochemical map of Black sea coast of Russia is done as a result of a complex study of the South of Russia summarizing large volume of various materials geological, soil, geobotanical, geological trends and the official in the field work process. Topographical and geological maps of scale 1:200000–1:500000 were the basis for drawing up the map of geochemical landscapes. Using these data, it was possible to establish the main factors of landscape differentiation and make auxiliary maps that characterize the taxonomic parameters: 1-plant communities and types of nature management developed in the region; 2 – types of geochemical conditions in soils; 3 – geomorphological features; 5-soil-forming rocks. All these factors are taken into account at various taxonomic levels and are clearly shown on the map of geochemical landscapes. The area of the research area is approximately 8,300 km2 . The variety of natural conditions and the wide development of anthropogenic activities caused the complex landscape and geochemical structure of the studied territory Most of the territory of the Black sea coast of Russia is occupied by biogenic landscapes (5717.2 km2 or 69 %). Technogenic landscapes on the black sea coast of Russia are developed everywhere, but their largest area is on the Taman Peninsula and the area from Anapa to Novorossiysk. The map made it possible to assess the natural differentiation and specifics of the technogenic transformation of the studied territory. The objectivity of using the landscape-geochemical map as a basis for a comprehensive study of the territory is confirmed by the results of studying the features of migration and concentration of chemical elements in soils and rocks.
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Odgers, Nathan P., Karen W. Holmes, Ted Griffin, and Craig Liddicoat. "Derivation of soil-attribute estimations from legacy soil maps." Soil Research 53, no. 8 (2015): 881. http://dx.doi.org/10.1071/sr14274.
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It is increasingly necessary to apply quantitative techniques to legacy soil polygon maps given that legacy soil maps may be the only source of soil information over large areas. Spatial disaggregation provides a means of extracting information from legacy soil maps and enables us to downscale the original information to produce new soil class maps at finer levels of detail. This is a useful outcome in its own right; however, the disaggregated soil-class coverage can also be used to make digital maps of soil properties with associated estimates of uncertainty. In this work, we take the spatially disaggregated soil-class coverage for all of Western Australia and the agricultural region of South Australia and demonstrate its application in mapping clay content at six depth intervals in the soil profile. Estimates of uncertainty are provided in the form of the 90% prediction interval. The work can be considered an example of harmonisation to a common output specification. The validation results highlighted areas in the landscape and taxonomic spaces where more knowledge of soil properties is necessary.
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JONG, R. DE, and J. A. SHIELDS. "AVAILABLE WATER-HOLDING CAPACITY MAPS OF ALBERTA, SASKATCHEWAN AND MANITOBA." Canadian Journal of Soil Science 68, no. 1 (February 1, 1988): 157–63. http://dx.doi.org/10.4141/cjss88-015.
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Available water-holding capacity (AWC) maps of Alberta, Saskatchewan and Manitoba were derived from Soil Landscape maps (1:1 million scale) by substituting AWC classes for soil textural classes. The maps provide information required for the geographical interpretation of soil water and crop modelling analyses. Key words: Available water-holding capacity, maps, texture
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Yang, X., G. A. Chapman, J. M. Gray, and M. A. Young. "Delineating soil landscape facets from digital elevation models using compound topographic index in a geographic information system." Soil Research 45, no. 8 (2007): 569. http://dx.doi.org/10.1071/sr07058.
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Soil landscapes and their component facets (or sub-units) are fundamental information for land capability assessment and land use planning. The aim of the study was to delineate soil landscape facets from readily available digital elevation models (DEM) to assist soil constraint assessment for urban and regional planning in the coastal areas of New South Wales (NSW), Australia. The Compound Topographic Index (CTI) surfaces were computed from 25 m DEM using a D-infinity algorithm. The cumulative frequency distribution of CTI values within each soil landscape was examined to identify the values corresponding to the area specified for each unmapped facet within the soil landscape map unit. Then these threshold values and CTI surfaces were used to generate soil landscape facet maps for the entire coastal areas of NSW. Specific programs were developed for the above processes in a geographic information system so that they are automated, fast, and repeatable. The modelled facets were assessed by field validation and the overall accuracy reached 93%. The methodology developed in this study has been proven to be efficient in delineating soil landscape facets, and allowing for the identification of land constraints at levels of unprecedented detail for the coast of NSW.
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Miller, B. A., S. Koszinski, M. Wehrhan, and M. Sommer. "Comparison of spatial association approaches for landscape mapping of soil organic carbon stocks." SOIL 1, no. 1 (March 4, 2015): 217–33. http://dx.doi.org/10.5194/soil-1-217-2015.
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Abstract. The distribution of soil organic carbon (SOC) can be variable at small analysis scales, but consideration of its role in regional and global issues demands the mapping of large extents. There are many different strategies for mapping SOC, among which is to model the variables needed to calculate the SOC stock indirectly or to model the SOC stock directly. The purpose of this research is to compare direct and indirect approaches to mapping SOC stocks from rule-based, multiple linear regression models applied at the landscape scale via spatial association. The final products for both strategies are high-resolution maps of SOC stocks (kg m−2), covering an area of 122 km2, with accompanying maps of estimated error. For the direct modelling approach, the estimated error map was based on the internal error estimations from the model rules. For the indirect approach, the estimated error map was produced by spatially combining the error estimates of component models via standard error propagation equations. We compared these two strategies for mapping SOC stocks on the basis of the qualities of the resulting maps as well as the magnitude and distribution of the estimated error. The direct approach produced a map with less spatial variation than the map produced by the indirect approach. The increased spatial variation represented by the indirect approach improved R2 values for the topsoil and subsoil stocks. Although the indirect approach had a lower mean estimated error for the topsoil stock, the mean estimated error for the total SOC stock (topsoil + subsoil) was lower for the direct approach. For these reasons, we recommend the direct approach to modelling SOC stocks be considered a more conservative estimate of the SOC stocks' spatial distribution.
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Fleis, M. E., A. A. Nikiforova, M. V. Nyrtsov, M. M. Borisov, and A. G. Khropov. "Creation of a Multiscale Series of Soil-Landscape Maps in GIS." Izvestiya Rossiiskoi Akademii Nauk. Seriya Geograficheskaya., no. 1 (March 2, 2016): 147–55. http://dx.doi.org/10.15356/0373-2444-2016-1-147-155.
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Nikiforova, A. A., M. E. Fleis, and N. N. Kazantsev. "Multi-scale soil-landscape maps as the basis of geographic information systems for soil melioration." IOP Conference Series: Earth and Environmental Science 368 (November 28, 2019): 012038. http://dx.doi.org/10.1088/1755-1315/368/1/012038.
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Cruz-Cárdenas, Gustavo, Carlos Alberto Ortiz-Solorio, Enrique Ojeda-Trejo, Juan Felipe Martínez-Montoya, Erasto Domingo Sotelo-Ruiz, and Atenogenes Leobardo Licona-Vargas. "Computer-assisted cartography using topographic properties: precision and accuracy of local soil maps in central Mexico." Revista Brasileira de Ciência do Solo 35, no. 3 (June 2011): 683–91. http://dx.doi.org/10.1590/s0100-06832011000300003.
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Map units directly related to properties of soil-landscape are generated by local soil classes. Therefore to take into consideration the knowledge of farmers is essential to automate the procedure. The aim of this study was to map local soil classes by computer-assisted cartography (CAC), using several combinations of topographic properties produced by GIS (digital elevation model, aspect, slope, and profile curvature). A decision tree was used to find the number of topographic properties required for digital cartography of the local soil classes. The maps produced were evaluated based on the attributes of map quality defined as precision and accuracy of the CAC-based maps. The evaluation was carried out in Central Mexico using three maps of local soil classes with contrasting landscape and climatic conditions (desert, temperate, and tropical). In the three areas the precision (56 %) of the CAC maps based on elevation as topographical feature was higher than when based on slope, aspect and profile curvature. The accuracy of the maps (boundary locations) was however low (33 %), in other words, further research is required to improve this indicator.
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Kidd, Darren, Mathew Webb, Brendan Malone, Budiman Minasny, and Alex McBratney. "Eighty-metre resolution 3D soil-attribute maps for Tasmania, Australia." Soil Research 53, no. 8 (2015): 932. http://dx.doi.org/10.1071/sr14268.
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Until recently, Tasmanian environmental modelling and assessments requiring important soil inputs relied on conventionally derived soil polygons that were mapped up to 75 years ago. In the ‘Wealth from Water’ project, digital soil mapping (DSM) was used in a pilot project to map the suitability of 20 different agricultural enterprises over 70 000 ha. Following on from this, the Tasmanian Department of Primary Industries Parks Water and Environment has applied DSM to existing soil datasets to develop enterprise suitability predictions across the whole state in response to further expansion of irrigation schemes. The soil surfaces generated have conformed and contributed to the Terrestrial Ecosystem Research Network Soil and Landscape Grid of Australia, a superset of GlobalSoilMap.net specifications. The surfaces were generated at 80-m resolution for six standard depths and 13 soil properties (e.g. pH, EC, organic carbon, sand and silt percentages and coarse fragments), in addition to several Tasmanian enterprise-suitability soil-attribute parameters. The modelling used soil site data with available explanatory state-wide spatial variables, including the Shuttle Radar Topography Mission digital elevation model and derivatives, gamma-radiometrics, surface geology, and multi-spectral satellite imagery. The DSM has delivered realistic mapping for most attributes, with acceptable validation diagnostics and relatively low uncertainty ranges in data-rich areas, but performed marginally in terms of uncertainty ranges in areas such as the World Heritage-listed Southwest of the state, with a low existing soil site density. Version 1.0 soil-attribute maps form the foundations of a dynamic and evolving new infrastructure that will be improved and re-run with the future collection of new soil data. The Tasmanian mapping has provided a localised integration with the National Soil and Landscape Grid of Australia, and it will guide future investment in soil information capture by quantitatively targeting areas with both high uncertainties and important ecological or agricultural value.
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Schut, Peter, Scott Smith, Walter Fraser, Xiaoyuan Geng, and David Kroetsch. "Soil Landscapes of Canada: Building a National Framework for Environmental Information." GEOMATICA 65, no. 3 (September 2011): 293–309. http://dx.doi.org/10.5623/cig2011-045.
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The Soil Landscapes of Canada (SLC) is a national soil map and accompanying database of environmental information for all of Canada, produced and maintained by the Canadian Soil Information Service (CanSIS) which is a part of Agriculture and Agri-Food Canada. The SLC maps were originally published as a set of paper products for individual provinces and regions. The maps were digitized in CanSIS, using one of the first geographic information systems in the world, and linked to soil and landscape attribute tables to serve an evolving variety of spatial modelling applications. The SLCs form the lowest level of the National Ecological Framework for Canada. The latest public release of the SLC is version 3.2, which provides updated soil and landscape information for the agricultural areas of Canada. The SLC v3.2 digital coverage includes an extensive set of relational data tables. The component table lists the soil components in each agricultural polygon along with their predicted dominant slope, class, and extent. The soil component codes are also linked to soil attribute tables which define fundamental soil properties, such as classification and parent material, as well as a description of the soil horizons and key soil attributes to a depth of 100 cm. SLC v3.2 adds a new set of landform tables which identify the major landform type in each polygon and indicates the most likely soil components in the upper, mid slope, lower slope, and depressional positions. These soil and landform attributes are designed to support a wide variety of national and international environmental modelling applications, such as the prediction of soil quality change, soil carbon sequestration, and land productivity for different agricultural crops in response to agricultural policy, land management, and climate change scenarios. Future versions of the SLC are under development that will have improved spatial resolution and include soils data for areas beyond the present agricultural zone of Canada.
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Martsinkevich, Galina I., Natallia V. Hahina, Dzmitry M. Kurlovich, and Olga M. Kovalevskaya. "Structure and mapping of landscapes of the Pripyatsky National Park using geoinformation technologies." Journal of the Belarusian State University. Geography and Geology, no. 1 (June 8, 2021): 65–74. http://dx.doi.org/10.33581/2521-6740-2021-1-65-74.
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The article considers new approaches to the study of the structure of natural landscapes, the identification of typical and rare landscapes of Pripyatsky National Park and their mapping using GIS-technologies that allow the creation of digital landscape maps. The relevance of the work is to create the first digital maps for the Pripyatsky National Park, which can be used to expand the network of ecological routes, increase the number of objects of inspection of the territory by tourists, monitoring forests and swamps. The created digital landscape map reflects the hierarchical levels and structure of natural complexes in the rank of genera, species and tracts, as well as the principles of their selection, which correspond to scientific approaches to the classification of landscapes of the Belarusian school of landscape studies. As a result, the main factor of the selection of genera is the genesis, species – the nature of relief, tracts – features of relief and soil-vegetation cover. The mapping of landscapes of specially protected natural areas (SPNA) of the Republic of Belarus using GIS-technologies was first tested on the example of the Berezinsky Biosphere Reserve and three national parks (Narochansky, Braslavskie Ozera, Belovezhskaya Pushcha). The digital landscape map of the Pripyatsky National Park, which illustrates the territorial distribution of 4 genera, 19 types of landscapes and 3 types of tracts, helped to clarify the boundaries of landscape units and served as the basis for identifying typical and rare landscapes, which is especially important for identifying rare landscapes that have preserved their natural appearance and have a special nature conservation value and in need of special protection. A digital map of typical and rare landscapes shows that within the boundaries of the park are widely represented species of lake-swamp and alluvial terraced landscapes, typical for the Polesie region, rare landscapes are confined to the floodplain landscape of the Pripyat River with ridged relief, old lakes, floodplain oak forests and tall grass meadows. In general, the identified typical landscapes of the Pripyatsky National Park are representative of the Polesie landscape province and reflect its regional features, and rare ones are found only in this region and emphasize its individuality. Digital maps made it possible to reveal the complex structure of landscapes, to discover not only typical and rare landscapes, but also unique objects in the rank of a natural boundary, and thereby show a more diverse landscape structure of the park than is reflected in the Landscape map of the Republic of Belarus (2014).
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VOLD, T., M. W. SONDHEIM, and N. K. NAGPAL. "COMPUTER ASSISTED MAPPING OF SOIL EROSION POTENTIAL." Canadian Journal of Soil Science 65, no. 3 (August 1, 1985): 411–18. http://dx.doi.org/10.4141/cjss85-045.
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Soil erosion potential maps and summary statistics can be produced from existing information with relative ease with the aid of computers. Soil maps are digitized and survey information is stored as attributes for each soil. Algorithms are then prepared which evaluate the appropriate data base attributes (e.g. texture, slope) for each interpretation. Forty surface soil erosion potential maps were produced for the Lower Fraser Valley which identify the most erosion-prone areas and indicate average potential soil losses to be expected under assumed conditions. The algorithm developed follows the universal soil loss equation. Differences across the landscape in the R, K, and S factors are taken into account whereas the L factor is considered as a constant equal to 1.0. Worst conditions of bare soil (no crop cover, i.e. C = 1.0) and no erosion control practices (i.e. P = 1.0) are assumed. The five surface soil erosion potential classes are determined by a weighted average annual soil loss value based both on the upper 20 cm of mineral soil and on the proportion of the various soils in the polygon. A unique polygon number shown on the erosion potential map provides a link to computer tables which give additional information for each individual soil within that polygon. Key words: Erosion, computer mapping, USLE
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Shestakova, A. A. "Mapping patterns of distribution and modern conditions of permafrost landscapes in Yakutia." Geoinformatika, no. 4 (2020): 52–62. http://dx.doi.org/10.47148/1609-364x-2020-4-52-62.
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Digital thematic maps of the modern condition of permafrost landscapes of Yakutia on a scale of 1:1 500 000 have been compiled. A quantitative analysis of the patterns of their spatial distribution was carried out, the differentiation of permafrost landscapes by geocryological characteristics was made, and the areas that are most vulnerable to modern climate change and anthropogenic impacts were identified. The analysis of a series of digital thematic maps of the modern condition of permafrost landscapes in Yakutia showed that 34% of the total territory is occupied by landscapes with soil temperatures from −2 to −4 °C, the least common high-temperature permafrost landscapes (from 0 to −2 °C) – about 4% of the territory. Landscapes with active layer thickness values of about 1 m are spread over 36% of the territory, which is the highest indicator. Insignificant territories (up to 3%) are occupied by landscapes with active layer thickness of up to 3 and 3,5 m. The most widespread landscapes are those with low-ice deposits (less than 0,2) – 38,7%, and landscapes with heavy-ice deposits (more than 0,4) occupy 31%. The most dangerous process is thermokarst, which occurs in the interalassic and slightly drained types of terrain. Key words: permafrost landscape, temperature of soils, ice content of deposits, cryogenic processes, digital maps, GIS model.
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Miller, B. A., S. Koszinski, M. Wehrhan, and M. Sommer. "Comparison of spatial association approaches for landscape mapping of soil organic carbon stocks." SOIL Discussions 1, no. 1 (November 5, 2014): 757–802. http://dx.doi.org/10.5194/soild-1-757-2014.
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Abstract. The distribution of soil organic carbon (SOC) can be variable at small analysis scales, but consideration of its role in regional and global issues demands the mapping of large extents. There are many different strategies for mapping SOC, among which are to model the variables needed to calculate the SOC stock indirectly or to model the SOC stock directly. The purpose of this research is to compare direct and indirect approaches to mapping SOC stocks from rule-based, multiple linear regression models applied at the landscape scale via spatial association. The final products for both strategies are high-resolution maps of SOC stocks (kg m−2), covering an area of 122 km2, with accompanying maps of estimated error. For the direct modelling approach, the estimated error map was based on the internal error estimations from the model rules. For the indirect approach, the estimated error map was produced by spatially combining the error estimates of component models via standard error propagation equations. We compared these two strategies for mapping SOC stocks on the basis of the qualities of the resulting maps as well as the magnitude and distribution of the estimated error. The direct approach produced a map with less spatial variation than the map produced by the indirect approach. The increased spatial variation represented by the indirect approach improved R2 values for the topsoil and subsoil stocks. Although the indirect approach had a lower mean estimated error for the topsoil stock, the mean estimated error for the total SOC stock (topsoil + subsoil) was lower for the direct approach. For these reasons, we recommend the direct approach to modelling SOC stocks be considered a more conservative estimate of the SOC stocks' spatial distribution.
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Forouzangohar, Mohsen, Neville D. Crossman, Richard J. MacEwan, D. Dugal Wallace, and Lauren T. Bennett. "Ecosystem Services in Agricultural Landscapes: A Spatially Explicit Approach to Support Sustainable Soil Management." Scientific World Journal 2014 (2014): 1–13. http://dx.doi.org/10.1155/2014/483298.
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Soil degradation has been associated with a lack of adequate consideration of soil ecosystem services. We demonstrate a broadly applicable method for mapping changes in the supply of two priority soil ecosystem services to support decisions about sustainable land-use configurations. We used a landscape-scale study area of 302 km2in northern Victoria, south-eastern Australia, which has been cleared for intensive agriculture. Indicators representing priority soil services (soil carbon sequestration and soil water storage) were quantified and mapped under both a current and a future 25-year land-use scenario (the latter including a greater diversity of land uses and increased perennial crops and irrigation). We combined diverse methods, including soil analysis using mid-infrared spectroscopy, soil biophysical modelling, and geostatistical interpolation. Our analysis suggests that the future land-use scenario would increase the landscape-level supply of both services over 25 years. Soil organic carbon content and water storage to 30 cm depth were predicted to increase by about 11% and 22%, respectively. Our service maps revealed the locations of hotspots, as well as potential trade-offs in service supply under new land-use configurations. The study highlights the need to consider diverse land uses in sustainable management of soil services in changing agricultural landscapes.
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Saatchi, S., Y. Malhi, B. Zutta, W. Buermann, L. O. Anderson, A. M. Araujo, O. L. Phillips, et al. "Mapping landscape scale variations of forest structure, biomass, and productivity in Amazonia." Biogeosciences Discussions 6, no. 3 (June 4, 2009): 5461–505. http://dx.doi.org/10.5194/bgd-6-5461-2009.
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Abstract. Landscape and environmental variables such as topography, geomorphology, soil types, and climate are important factors affecting forest composition, structure, productivity, and biomass. Here, we combine a network of forest inventories with recently developed global data products from satellite observations in modeling the potential distributions of forest structure and productivity in Amazonia and examine how geomorphology, soil, and precipitation control these distributions. We use the RAINFOR network of forest plots distributed in lowland forests across Amazonia, and satellite observations of tree cover, leaf area index, phenology, moisture, and topographical variations. A maximum entropy estimation (Maxent) model is employed to predict the spatial distribution of several key forest structure parameters: basal area, fraction of large trees, fraction of palms, wood density, productivity, and above-ground biomass at 5 km spatial resolution. A series of statistical tests at selected thresholds as well as across all thresholds and jackknife analysis are used to examine the accuracy of distribution maps and the relative contributions of environmental variables. The final maps were interpreted using soil, precipitation, and geomorphological features of Amazonia and it was found that the length of dry season played a key role in impacting the distribution of all forest variables except the wood density. Soil type had a significant impact on the wood productivity. Most high productivity forests were distributed either on less infertile soils of western Amazonia and Andean foothills, on crystalline shields, and younger alluvial deposits. Areas of low elevation and high density of small rivers of Central Amazonia showed distinct features, hosting mainly forests with low productivity and smaller trees.
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Bazaglia Filho, Osmar, Rodnei Rizzo, Igo Fernando Lepsch, Hélio do Prado, Felipe Haenel Gomes, Jairo Antonio Mazza, and José Alexandre Melo Demattê. "Comparison between detailed digital and conventional soil maps of an area with complex geology." Revista Brasileira de Ciência do Solo 37, no. 5 (October 2013): 1136–48. http://dx.doi.org/10.1590/s0100-06832013000500003.
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Since different pedologists will draw different soil maps of a same area, it is important to compare the differences between mapping by specialists and mapping techniques, as for example currently intensively discussed Digital Soil Mapping. Four detailed soil maps (scale 1:10.000) of a 182-ha sugarcane farm in the county of Rafard, São Paulo State, Brazil, were compared. The area has a large variation of soil formation factors. The maps were drawn independently by four soil scientists and compared with a fifth map obtained by a digital soil mapping technique. All pedologists were given the same set of information. As many field expeditions and soil pits as required by each surveyor were provided to define the mapping units (MUs). For the Digital Soil Map (DSM), spectral data were extracted from Landsat 5 Thematic Mapper (TM) imagery as well as six terrain attributes from the topographic map of the area. These data were summarized by principal component analysis to generate the map designs of groups through Fuzzy K-means clustering. Field observations were made to identify the soils in the MUs and classify them according to the Brazilian Soil Classification System (BSCS). To compare the conventional and digital (DSM) soil maps, they were crossed pairwise to generate confusion matrices that were mapped. The categorical analysis at each classification level of the BSCS showed that the agreement between the maps decreased towards the lower levels of classification and the great influence of the surveyor on both the mapping and definition of MUs in the soil map. The average correspondence between the conventional and DSM maps was similar. Therefore, the method used to obtain the DSM yielded similar results to those obtained by the conventional technique, while providing additional information about the landscape of each soil, useful for applications in future surveys of similar areas.
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Maksymenko, N. V., V. O. Voronin, N. I. Cherkashyna, and S. P. Sonko. "Geochemical aspect of landscape planning in forestry." Journal of Geology, Geography and Geoecology 27, no. 1 (July 10, 2018): 81–87. http://dx.doi.org/10.15421/111833.
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One of the modern methods of spatially estimating anthropogenic impact on a given territory is landscape planning, including the stage of assessment of the conditions of a natural complex . The results of such an evaluation are used in environmental management. The aim of the work is to assess the ecological conditions of the Vasyshchivsky forest area by means of landscape and environmental planning. The aim is achieved by performing the following stages of work: assessment of the distribution and intensity of contamination sources in the Vasyshchivsky forest area; drawing a scheme showing parts of the territory with probable conflicts; making a soil and geochemical survey of the forest area to assess acidity distribution and total content of carbonates in the soil as the consequences of pollution of the forest ecosystem ; specification of geochemical characteristics of soils on the forest sites in the established location of former fires; forecast of limits of afte-r fire areas based on the analysis of cartographic works developed by the authors. The geochemical characteristics of the soils in Vasyshchivsky forest have been studied to identify the areas affected by fire, and the results of this study are given in this paper. During the inventory phase of landscape and environmental planning, a complete survey of the forest territory was conducted and a landscape map was drawn. Based on the authors’ matrices filled with conflicts of natural use, the areas with low, medium and high levels of conflict have been marked within the study area. Landscape and environmental planning has been evaluated by soil sampling outside the test points on the network and their laboratory analysis. The results of the evaluation phase were maps illustrating the geochemical situation in the forest soil cover. The article presents cartographic models of the spatial distribution of carbonates in the forest soils, water and salt extraction pH. The results of the study are part of an environmental assessment of Vasyshchivsky forest area. In future they will be used in restoration of the forest ecosystems after fire.
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Öztürk, Sevgi, Özge Vural, and Kaan Meydan. "Kırsal Alanlarda Peyzaj Karakter Analizi “Kastamonu-Gölköy ve Yakın Çevresi Örneği”." Turkish Journal of Agriculture - Food Science and Technology 8, no. 8 (August 30, 2020): 1720–25. http://dx.doi.org/10.24925/turjaf.v8i8.1720-1725.3480.
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The planning and management of landscapes have been reviewed in the European Landscape Convention (ELC) and the need to identify landscape character areas has been emphasized. The determination of Landscape Character Types (LCT) at the local level is of great importance in order to ensure sustainable development in rural areas, correct management of the shelter values and determination of usage strategies. In this study, which aims to evaluate rural settlements with character determination and sustainability approach, the landscape variables of Kastamonu-Gölköy settlement and its immediate surroundings are mapped and analysed with Landscape Character Analysis (LCA) approach. For this purpose, the geology, large soil groups, geomorphology, slope groups, are a usage maps of the area were digitized with Geographic Information Systems software and character types were determined by synthesizing them. As a result of the study, 133 landscape character types were determined. It is thought that the acquired character types will serve as a base in rural planning and landscape management studies carried out at the national and local level and will contribute to the formation of landscape policies.
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Cullum, Carola, Kevin H. Rogers, Gary Brierley, and Ed T. F. Witkowski. "Ecological classification and mapping for landscape management and science." Progress in Physical Geography: Earth and Environment 40, no. 1 (October 27, 2015): 38–65. http://dx.doi.org/10.1177/0309133315611573.
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There is growing demand for biogeographical landscape classifications and ecological maps that describe patterns of spatially co-varying biotic and abiotic ecosystem components. This demand is fuelled by increasing data availability and processing capacity, by institutional practices of land and water resource management and planning and by the growth of transdisciplinary science that requires the development of a shared conceptual framework through which to view landscape character and behaviour. Despite the widespread use of ecological maps, and the extent to which they have become embedded in institutional practice, policy and law, no standard approach to ecosystem mapping has emerged, such that there are many valid ways of mapping the same landscape. Consensus is possible only when there is agreement on the spatial entities to be mapped. We propose a way of defining such entities and identifying them in any given landscape. Landscapes are conceived in terms of a conceptual biophysical template that constrains a wide range of ecological processes at various hierarchical levels. The template is conceived as comprising co-evolved associations of soils, vegetation, topography and hydrology that form a dynamic mosaic characteristic of a particular topographic, climatic and geological context that is continually being shaped by many perturbations. We synthesise themes from vegetation, soil and river sciences, using hierarchy theory to frame a perspective that facilitates the definition of mappable landscape entities at three hierarchical levels of organisation. These entities are conceived as archetypal structural-functional units, with form and process linked in conceptual models that underpin each archetype. We describe how our approach has been used to map ecological entities in Kruger National Park, South Africa, showing how the proposed framework integrates key system components, providing transparent foundations for transdisciplinary approaches to landscape management and science.
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Basher, L. R. "Is pedology dead and buried?" Soil Research 35, no. 5 (1997): 979. http://dx.doi.org/10.1071/s96110.
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Pedology, the field study of soils as natural landscape bodies, has suffered serious cutbacks in stang and funding in many developed countries. Soil survey, a strong focus for pedology, has been most affected by this recession. The cutbacks to pedology reflect the reduction in funding for general purpose soil resource inventories and a decline in central government planning and land development, as well as changing needs for soil information and perceived failure of soil survey to respond by delivering relevant, timely information at affordable cost. A refocusing of research effort in pedology is required to contribute to research into environmental issues of sustainable land management, and global change processes and impacts. The adoption of modern, ecient approaches to collecting, analysing, interpreting and presenting field soil data will improve the fund-raising capability of pedology and enhance its institutional stature. The general purpose paper soil map and soil survey report has largely been superseded as a medium for presenting soil information. Increasingly, it will be replaced by computer-generated, special purpose, interpretive soil maps that are based on soil–landscape models and include more objective, statistically estimated information on soil variability. There is a continuing role for pedology to define the extent, distribution, properties, suitability, and vulnerability of soils as a basis for sustainable land management. There is a need for increasing focus on temporal changes in soil properties, greater attention to soil properties that determine soil functioning and influence soil use, and interpretation of the environmental record contained in soils and regolith.
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Terribile, F., A. Coppola, G. Langella, M. Martina, and A. Basile. "Potential and limitations of using soil mapping information to understand landscape hydrology." Hydrology and Earth System Sciences 15, no. 12 (December 22, 2011): 3895–933. http://dx.doi.org/10.5194/hess-15-3895-2011.
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Abstract. This paper addresses the following points: how can whole soil data from normally available soil mapping databases (both conventional and those integrated by digital soil mapping procedures) be usefully employed in hydrology? Answering this question requires a detailed knowledge of the quality and quantity of information embedded in and behind a soil map. To this end a description of the process of drafting soil maps was prepared (which is included in Appendix A of this paper). Then a detailed screening of content and availability of soil maps and database was performed, with the objective of an analytical evaluation of the potential and the limitations of soil data obtained through soil surveys and soil mapping. Then we reclassified the soil features according to their direct, indirect or low hydrologic relevance. During this phase, we also included information regarding whether this data was obtained by qualitative, semi-quantitative or quantitative methods. The analysis was performed according to two main points of concern: (i) the hydrological interpretation of the soil data and (ii) the quality of the estimate or measurement of the soil feature. The interaction between pedology and hydrology processes representation was developed through the following Italian case studies with different hydropedological inputs: (i) comparative land evaluation models, by means of an exhaustive itinerary from simple to complex modelling applications depending on soil data availability, (ii) mapping of soil hydrological behaviour for irrigation management at the district scale, where the main hydropedological input was the application of calibrated pedo-transfer functions and the Hydrological Function Unit concept, and (iii) flood event simulation in an ungauged basin, with the functional aggregation of different soil units for a simplified soil pattern. In conclusion, we show that special care is required in handling data from soil databases if full potential is to be achieved. Further, all the case studies agree on the appropriate degree of complexity of the soil hydrological model to be applied. We also emphasise that effective interaction between pedology and hydrology to address landscape hydrology requires (i) greater awareness of the hydrological community about the type of soil information behind a soil map or a soil database, (ii) the development of a better quantitative framework by the pedological community for evaluating hydrological features, and (iii) quantitative information on soil spatial variability.
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Kovář, Pavel. "Conceptions of Landscape-Ecological Relevance Emerged in the Czech Botany during the Second Half of Twentieth Century." Journal of Landscape Ecology 8, no. 3 (December 1, 2015): 40–50. http://dx.doi.org/10.1515/jlecol-2015-0013.
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Abstract This paper summarizes those substantial theoretical concepts or methods for applications within interdisciplinary or practical uses published by Czech autors (geobotanists = ecological botanists, plant ecologists and ecophysiologists) during the second half of the 20th century, that were internationally cited. All selected thematical clusters are of landscape-ecological relevance through various contexts. Examples include the concepts of (potential) reconstructed vegetation in maps (R. Neuhäusl, Z. Neuhäuslová), linear vegetation features (corridors in landscape) and deductive classification of vegetation (K. Kopecký), analysis of soil seed bank (Z. Kropáč), dependency of macrophyte plant stands on ecodynamics (S. Hejný), dynamic periodicity in segetal vegetation (Z. Kropáč, E. Hadač, S. Hejný), anemo-orographic system explaining species richness in mountain regions (J. Jeník), productivity in grassland ecosystems (M. Rychnovská, J. Květ), elementary landscape units based on homogenity and potential vegetation (E. Hadač), landscape dispensation phenomena (V. Ložek), afforestation of coastal sandy dunes – the Netherlands, and polluted areas - the Czech Republic (J. Fanta), invasive plants and invasions into landscapes (M. Rejmánek).
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Missiaen, T., I. Jongepier, K. Heirman, T. Soens, V. Gelorini, J. Verniers, J. Verhegge, and Ph Crombé. "Holocene landscape evolution of an estuarine wetland in relation to its human occupation and exploitation: Waasland Scheldt polders, northern Belgium." Netherlands Journal of Geosciences 96, no. 1 (August 30, 2016): 35–62. http://dx.doi.org/10.1017/njg.2016.24.
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AbstractThis paper describes the landscape evolution of the Waasland Scheldt polders in the north of Belgium from the Late Glacial – early Holocene to the present time, and the effects of this changing landscape on the human settlement. The regional landscape evolution has been visualised in a series of palaeogeographical maps for successive time frames. Two different map series were produced: a series of Holocene palaeogeographical reconstructions (11,000–950 cal BP) based on geotechnical, geological and archaeological data, and a series of post-Medieval landscape reconstructions (16th- to 19th-century) based on historical maps, land registers and soil data. Additional palaeoenvironmental information from fossil pollen and plant remains allowed reconstruction of the vegetation and wetland changes, particularly for the middle to late Holocene. Peat growth was the main key to understanding the landscape evolution of the Waasland Scheldt polders. Whereas the landscape evolution during the Holocene was mainly sea-level driven, the transformation of the landscape during the last millennium was largely due to human interventions.
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Zhao, Z., Q. Yang, G. Benoy, T. L. Chow, Z. Xing, H. W. Rees, and F. R. Meng. "Using artificial neural network models to produce soil organic carbon content distribution maps across landscapes." Canadian Journal of Soil Science 90, no. 1 (February 1, 2010): 75–87. http://dx.doi.org/10.4141/cjss08057.
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Soil organic carbon (SOC) content is an important soil quality indicator that plays an important role in regulating physical, chemical and biological properties of soil. Field assessment of SOC is time consuming and expensive. It is difficult to obtain high-resolution SOC distribution maps that are needed for landscape analysis of large areas. An artificial neural network (ANN) model was developed to predict SOC based on parameters derived from digital elevation model (DEM) together with soil properties extracted from widely available coarse resolution soil maps (1:1 000 000 scale). Field estimated SOC content data extracted from high-resolution soil maps (1:10 000 scale) in Black Brook Watershed in northwestern New Brunswick, Canada, were used to calibrate and validate the model. We found that vertical slope position (VSP) was the most important variable that determines distributions of SOC across the landscape. Other variables such as slope steepness, and potential solar radiation (PSR) also had significant influence on SOC distributions. The prediction of the selected two-input-node SOC model (VSP and coarse resolution soil map recorded SOC as inputs) had a correlation coefficient of 0.92 with measured values, and model predicted SOC values had 47.9% of the total points within ±0.5% of the measured values and 70.6% within ±1% of the measured values. The prediction od the selected four-input-node model (VSP, slope steepness, PSR and coarse resolution SOC values as inputs) had a correlation coefficient of 0.98 with measured values and model predicted SOC values had 75% of the total points within ±0.5% of the measured values and 87% within ±1% of the measured values. The prediction of the five-input-nodes model with soil drainage as additional input had a correlation coefficient of 0.99 with measured values, and model predicted SOC values had 87% of the total points within ±0.5% of the measured values and 98% of the total points within ±1% of the measured values. The calibrated SOC prediction model was used to produce a high-resolution SOC map for the Black Brook Watershed and the resulting SOC distribution map is considered to be realistic. Results indicated that DEM-derived hydrological parameters together with widely available coarse resolution soil map data could be used to produce high-resolution SOC maps with the ANN method.Key words: Soil organic carbon, artificial neural network model, high-resolution soil maps, digital elevation model, vertical slope position
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Leão, Marisol G. A. de, José Marques Júnior, Zigomar M. de Souza, Diego S. Siqueira, and Gener T. Pereira. "Terrain forms and spatial variability of soil properties in an area cultivatedwith citrus." Engenharia Agrícola 31, no. 4 (2011): 643–51. http://dx.doi.org/10.1590/s0100-69162011000400003.
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The technique of precision agriculture and soil-landscape allows delimiting areas for localized management, allowing a localized application of agricultural inputs and thereby may contribute to preservation of natural resources. Therefore, the objective of this work was to characterize the spatial variability of chemical properties and clay content in the context of soil-landscape relationship in a Latosol (Oxisol) under cultivation of citrus. Soil samples were collected at a depth of 0.0-0.2 m in an area of 83.5 ha planted with citrus, as a 50-m intervals grid, with 129 points in concave terrain and 206 points in flat terrain, totaling 335 points. Values for the variables that express the chemical characteristics and clay content of soil properties were analyzed with descriptive statistics and geostatistical modeling of semivariograms for making maps of kriging. The values of range and kriging maps indicated higher variability in the shape of concave topography (top segment) compared with the shape of flat topography (slope and hillside segments below). The identification of different forms of terrain proved to be efficient in understanding the spatial variability of chemical properties and clay content of soil under cultivation of citrus.
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Volkova, E. A., and I. T. Fedorova. "The map of ecological functions of the vegetation cover of Russia." Geobotanical mapping, no. 1993 (1995): 51–57. http://dx.doi.org/10.31111/geobotmap/1993.51.
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This map was compiled for the Ecological-Geographic Atlas of Russia. The Atlas has to show the ecological potential of natural landscapes which can be revealed by the series of factors determining the vital conditions of population. The map is the first attempt to analyse functional difference of the vegetation throughout such vast region as Russia. It is based on the analysis of both natural factors determining the vegetation distribution and the regulating influence of plant communities on environmental dynamics. So the first stage of creating this map is classification of vegetation in connection to environmental factors (edaphic, hydrologiс, cryologic, etc.). The second stage is evaluation of functional significance of vegetation categories. The main sources of this map are some regional maps of ecological functions of the vegetation and all available universal vegetation and landscape maps of Russia. Only environmental (landscape protective) but not resource and social functions are shown on this map because of its small scale and ecological purposes. These functions of vegetation can be subdivided into three groups: forming (oxygen–, sod–, chernozem–, peat-forming); protective (anti-erosion, anti-deflation, anti-denudation, anti-avalanche); stabilizing (runoff-regulation, water– and snow-accumulation, soil ice-stabilization, soil thermal-regulation, etc.). The legend of the map contains information about actual vegetation as well as its ecological functions peculiar to every unit shown on the map. All typological subdivisions of the vegetation are combined on the base of similar functions. Plant communities are grouped in the legend in zonal order. Mountain types have their own functions, that is why they are shown as independent units. Such maps reveal protective potential of the vegetation. They are important for prognosis of environmental dynamics under anthropogenic press and for protection and restoration of natural vegetation. In future the compiling of such type of maps in larger scale should supplement its content with resourceal and social functions of the vegetation. The most important of the latter are recreation and sanitary ones, which are mainly realized by biotic part of landscape.
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Sale, P. W. G., A. Brown, G. Maclaren, P. K. Derbyshire, and S. M. Veitch. "Pasture environments in Australia where reactive phosphate rock will be an effective phosphate fertiliser." Australian Journal of Experimental Agriculture 37, no. 8 (1997): 1051. http://dx.doi.org/10.1071/ea96119.
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Summary. Maps are constructed using Geographic Information Systems (GIS) computer technology to identify privately held land in the high rainfall zones of temperate and tropical Australia where highly reactive phosphate rocks (RPRs) are likely to be effective phosphorus (P) fertilisers for permanent pasture. Australia-wide RPR suitability maps were based on annual rainfall, soil pH and the P sorption capacity of the soil. The digitised soil map from the Atlas of Australian Soils and the soil profile acidity map derived from the Atlas, were used to identify land areas with suitable soil properties. The coarse scale of the Atlas, which has only the 1 dominant soil for each 100 ha minimum landscape unit, limits the precision in identifying specific land types. Reactive phosphate rock suitability maps for pasture land in Victoria were also developed using smaller land units and state-wide digitised soil maps for surface pH and surface texture. The GIS maps indicated that there are about 26.5 × 106 ha of land in the high rainfall pastoral zone of Australia that have sufficient annual rainfall and appropriate soil properties for RPR to become effective by the 4th year after changing from annual water-soluble P fertiliser to RPR fertiliser applications. Additional land with a lower rainfall might also be suitable if the soil surface is not excessively sandy. The area of high rainfall pasture land where RPR is likely to be as effective as water-soluble P fertiliser in the first year of application is around 3 × 106 ha. The major portion of this land is in North Queensland, with smaller areas in southern Victoria, in far north-west Tasmania and in the far south-west of Western Australia. More detailed GIS maps for Victoria indicate that RPRs would become as effective as water-soluble P fertiliser by the 4th year on more than 70% of private land where annual rainfall exceeds 700 mm.
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Blackford, Christopher, Brandon Heung, Ken Baldwin, Robert L. Fleming, Paul W. Hazlett, Dave M. Morris, Peter W. C. Uhlig, and Kara L. Webster. "Digital soil mapping workflow for forest resource applications: a case study in the Hearst Forest, Ontario." Canadian Journal of Forest Research 51, no. 1 (January 2021): 59–77. http://dx.doi.org/10.1139/cjfr-2020-0066.
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Accurate soil information is critically important for forest management planning and operations but is challenging to map. Digital soil mapping (DSM) improves upon the limitations of conventional soil mapping by explicitly linking a variety of environmental data layers to spatial soil point data sets to continuously predict soil variability across a landscape. Thus far, much DSM research has focussed on the development of ultrafine-resolution soil maps within agricultural systems; however, increasing availability of light detection and ranging (LiDAR) data presents new opportunities to apply DSM to support forest resource applications at multiple scales. This project describes a DSM workflow using LiDAR-derived elevation data and machine learning models (MLMs) to predict key forest soil attributes. A case study in the Hearst Forest in northeastern Ontario, Canada, is used to illustrate the workflow. We applied multiple MLMs to the Hearst Forest to predict soil moisture regime and textural class. Both qualitative and quantitative assessment pointed to the random forest MLM producing the best maps (63% accuracy for moisture regime and 66% accuracy for textural class). Where error occurred, soils were typically misclassified to neighbouring classes. This standardized, flexible workflow is a valuable tool for practitioners that want to undertake DSM as part of forest resource management and planning.
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Shange, Raymon S., Ramble O. Ankumah, Leonard Githinji, and Robert Zabawa. "Spatial Assessment of Selected Soil Properties within an Industrial Poultry Production Site." Air, Soil and Water Research 5 (January 2012): ASWR.S9268. http://dx.doi.org/10.4137/aswr.s9268.
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Waste resulting from industrial poultry production systems is becoming an increasingly significant environmental problem in the US, threatening both soil and water quality. The goal of this study was to assess the spatial variability and interactions of selected soil properties (physical, chemical, and biochemical), viz., particle size, pH, enzymatic activity, Soil Organic Carbon (SOC), and Total Nitrogen (TN), across an agricultural landscape used for industrial poultry production. The measured soil properties were separated according to biochemical constituents and soil texture based on the first two principal components, accounting for approximately 60% of the variability across the site. These principal components were then used to generate soil surface maps, indicating areas of possible catalytic activity. Surface maps showed possible increases in biochemical activity around areas of stored poultry litter, suggesting the utility of these methods in determining changes to soil management.
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Balkovič, J., G. Čemanová, J. Kollár, M. Kromka, and K. Harnová. "Mapping soils using the fuzzy approach and regression-kriging case study from the Považský Inovec Mountains, Slovakia." Soil and Water Research 2, No. 4 (January 7, 2008): 123–34. http://dx.doi.org/10.17221/2112-swr.
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The paper introduces a method of digital mapping of spatial distribution of soil typological units. It implements fuzzy k-means to classify the soil profile data (study area from the Považský Inovec Mountains, Slovakia) and regression-kriging with the selected digital terrain and remote sensing data to draw membership maps of soil typological units. Totally three soil typological units were identified: Haplic Cambisols (Skeletic, Dystric), Albic Stagnic Luvisols, and Haplic Stagnosols (Albic, Dystric). We analysed the membership values to these units with respect to terrain and remote sensing data. The membership values appeared as spatially smoothly dependant on the terrain gradients (linearly or exponentially) whereas the residua showed spatial autocorrelation. Based on regression and kriging analyses, the regression-kriging model was successfully deployed to draw raster membership maps. These maps yield coefficients of determination between R<sup>2</sup> = 56% (Albic Stagnic Luvisols) to R<sup>2</sup>= 79% (Haplic Cambisols (Skeletic, Dystric)) when evaluated by cross validation. The grid-based continuous soil map represents an alternative to the classical polygon soil maps and can offer a wide range of interpretations for landscape studies.
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Nielsen, Anne Birgitte. "Quantifying the relationship between pollen sedimentation in lakes and land cover using historical maps." Geological Survey of Denmark and Greenland (GEUS) Bulletin 7 (July 29, 2005): 49–52. http://dx.doi.org/10.34194/geusb.v7.4832.
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Pollen records from lake sediments have a great potential for providing information on the quantitative composition of past vegetation and land cover in the surrounding landscape. This can contribute to a better understanding of the development of the cultural landscape and interactions between human impact on the landscape and natural conditions like soil and climate. A good understanding of the history of cultural landscapes is necessary for choosing appropriate management strategies for areas dependent on cultural impact, such as heaths, meadows and dry pastures. It is also important for archaeological research concerning utilisation of the landscape in earlier periods. Furthermore, quantitative reconstructions are relevant for climate research. Here they can be used to test climate models, since model predictions of past climate can be translated into past vegetation, which can then be compared to pollen-based reconstructions. Past vegetation cover is also a necessary input to climate models, as it influences albedo, evapotranspiration and carbon storage and cycling. Quantifying vegetation from fossil pollen samples requires a detailed understanding of the way vegetation is reflected in pollen assemblages, including the approximate size of the area of vegetation represented. The relationship between pollen and vegetation is complicated by the fact that different plant species produce different amounts of pollen, and that pollen types are dispersed differently in the atmosphere, depending on their size, shape and weight. These pressing challenges in pollen analysis have attracted much attention in recent years. Models have been developed to describe and simulate species specific pollen dispersal, to quantitatively relate pollen proportions to plant abundance, as well as estimate pollen productivity and to quantify the pollen source area of different types of basins (Parsons & Prentice 1981; Prentice & Parsons 1983; Prentice 1985; Sugita 1993, 1994; Sugita et al. 1997, 1999; Broström 2002; Bunting et al. 2004). The Geological Survey of Denmark and Greenland (GEUS) has in recent years contributed to the development and validation of such models through the project AGRAR 2000(Odgaard 1999; Nielsen 2003), where quantitative estimates of past land cover in different regions of Denmark were one of the main objectives, and through participation in the international research network POLLANDCAL (POLlen LANdscape CALibration), funded by NORDFORSK (Nordic Research Board), which focuses on further model development, validation and application.
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Antonetti, Manuel, Rahel Buss, Simon Scherrer, Michael Margreth, and Massimiliano Zappa. "Mapping dominant runoff processes: an evaluation of different approaches using similarity measures and synthetic runoff simulations." Hydrology and Earth System Sciences 20, no. 7 (July 20, 2016): 2929–45. http://dx.doi.org/10.5194/hess-20-2929-2016.
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Abstract. The identification of landscapes with similar hydrological behaviour is useful for runoff and flood predictions in small ungauged catchments. An established method for landscape classification is based on the concept of dominant runoff process (DRP). The various DRP-mapping approaches differ with respect to the time and data required for mapping. Manual approaches based on expert knowledge are reliable but time-consuming, whereas automatic GIS-based approaches are easier to implement but rely on simplifications which restrict their application range. To what extent these simplifications are applicable in other catchments is unclear. More information is also needed on how the different complexities of automatic DRP-mapping approaches affect hydrological simulations. In this paper, three automatic approaches were used to map two catchments on the Swiss Plateau. The resulting maps were compared to reference maps obtained with manual mapping. Measures of agreement and association, a class comparison, and a deviation map were derived. The automatically derived DRP maps were used in synthetic runoff simulations with an adapted version of the PREVAH hydrological model, and simulation results compared with those from simulations using the reference maps. The DRP maps derived with the automatic approach with highest complexity and data requirement were the most similar to the reference maps, while those derived with simplified approaches without original soil information differed significantly in terms of both extent and distribution of the DRPs. The runoff simulations derived from the simpler DRP maps were more uncertain due to inaccuracies in the input data and their coarse resolution, but problems were also linked with the use of topography as a proxy for the storage capacity of soils. The perception of the intensity of the DRP classes also seems to vary among the different authors, and a standardised definition of DRPs is still lacking. Furthermore, we argue not to use expert knowledge for only model building and constraining, but also in the phase of landscape classification.
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Antonetti, M., R. Buss, S. Scherrer, M. Margreth, and M. Zappa. "Mapping dominant runoff processes: an evaluation of different approaches using similarity measures and synthetic runoff simulations." Hydrology and Earth System Sciences Discussions 12, no. 12 (December 18, 2015): 13257–99. http://dx.doi.org/10.5194/hessd-12-13257-2015.
Full textAbstract:
Abstract. The identification of landscapes with similar hydrological behaviour is useful for runoff predictions in small ungauged catchments. An established method for landscape classification is based on the concept of dominant runoff process (DRP). The various DRP mapping approaches differ with respect to the time and data required for mapping. Manual approaches based on expert knowledge are reliable but time-consuming, whereas automatic GIS-based approaches are easier to implement but rely on simplifications which restrict their application range. To what extent these simplifications are applicable in other catchments is unclear. More information is also needed on how the different complexity of automatic DRP mapping approaches affects hydrological simulations. In this paper, three automatic approaches were used to map two catchments on the Swiss Plateau. The resulting maps were compared to reference maps obtained with manual mapping. Measures of agreement and association, a class comparison and a deviation map were derived. The automatically derived DRP-maps were used in synthetic runoff simulations with an adapted version of the hydrological model PREVAH, and simulation results compared with those from simulations using the reference maps. The DRP-maps derived with the automatic approach with highest complexity and data requirement were the most similar to the reference maps, while those derived with simplified approaches without original soil information differed significantly in terms of both extent and distribution of the DRPs. The runoff simulations derived from the simpler DRP-maps were more uncertain due to inaccuracies in the input data and their coarse resolution, but problems were also linked with the use of topography as a proxy for the storage capacity of soils. The perception of the intensity of the DRP classes also seems to vary among the different authors, and a standardised definition of DRPs is still lacking. We therefore recommend not only using expert knowledge for model building and constraining but also trying to obtain spatially distributed landscape classifications that are as realistic as possible.
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Rahman, S., L. C. Munn, R. Zhang, and G. F. Vance. "Rocky Mountain forest soils: Evaluating spatial variability using conventional statistics and geostatistics." Canadian Journal of Soil Science 76, no. 4 (November 1, 1996): 501–7. http://dx.doi.org/10.4141/cjss96-062.
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Spatial variability of soils is a landscape attribute which soil scientists must identify and understand if they are to construct useful soils maps. This paper describes the spatial variability of soils in a forested watershed in the Medicine Bow Mountains, Wyoming, using both conventional statistics and geostatistics. Principle Components Analysis indicated that flow accumulation and aspect were the two terrain attributes that most economically described terrain variability. Thickness of A and B horizons, organic carbon and solum coarse fragments were variable in the study area (CVs of 40 to 58%). Simple correlation and regression analyses suggested there were no statistically significant relationships between soil properties (texture, pH, coarse fragments, organic carbon content) and terrain attributes (elevation, slope gradient, slope shape, flow accumulation, aspect). Geostatistical analysis indicated thickness and coarse fragment contents of the A and B horizons, and solum thickness were spatially independent variables; however, pH, organic carbon content, and solum coarse fragment content were spatially correlated. Spatial variability was described by both linear (pH and organic carbon content) and spherical (solum coarse fragment) models. Use of geostatistics provided insight into the nature of variability in soil properties across the landscape of the Libby Creek watershed when conventional statistics (analysis of variance and regression analysis) did not. Key words: Rocky Mountains, Medicine Bow Mountains, forest soils, spatial variability, principle component analysis, geostatistics
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Zhao, Zhengyong, Qi Yang, Xiaogang Ding, and Zisheng Xing. "Model Prediction of the Soil Moisture Regime and Soil Nutrient Regime Based on DEM-Derived Topo-Hydrologic Variables for Mapping Ecosites." Land 10, no. 5 (April 23, 2021): 449. http://dx.doi.org/10.3390/land10050449.
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Ecosites are required for stand-level forest management and can be determined within a two-dimensional edatopic grid with soil nutrient regimes (SNRs) and soil moisture regimes (SMRs) as coordinates. A new modeling method is introduced in this study to map high-resolution SNR and SMR and then to design ecosites in Nova Scotia, Canada. Using coarse-resolution soil maps and nine topo-hydrologic variables derived from high-resolution digital elevation model (DEM) data as model inputs, 511 artificial neural network (ANN) models were developed by a 10-fold cross-validation with 1507 field samples to estimate 10 m resolution SNR and SMR maps. The results showed that the optimal models for mapping SNR and SMR engaged eight and seven topo-hydrologic variables, together with three coarse-resolution soil maps, as model inputs, respectively; 82% of model-estimated SNRs were identical to field assessments, while this value was 61% for SMRs, and the produced ecosite maps had 67–68% correctness. According to the error matrix, the predicted SNR and SMR maps greatly alleviated poor prediction in the areas of extreme nutrient or moisture conditions (e.g., very poor or very rich, wet, or very dry). Thus, the new method for modeling high-resolution SNR and SMR could be used to produce ecosite maps in sites where accessibility is hard.
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Barone, Pier Matteo. "Bombed Archaeology: Towards a Precise Identification and a Safe Management of WWII’s Dangerous Unexploded Bombs." Heritage 2, no. 4 (September 24, 2019): 2704–11. http://dx.doi.org/10.3390/heritage2040167.
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The massive bombings during World War II (WWII) have had a lasting impact across the Italian landscape. The problem of dangerous unexploded bombs is particularly relevant since the bombsites are buried beneath the soil close to inhabited and/or touristic areas. Archaeological sites, such as Pompeii and Vulci, were heavily bombed, and nowadays, archaeologists excavate these bombs during their digs. Thus, there is a real risk to people’s safety. While the aerial photo collection is a powerful record of the landscapes of wartime Italy, plotting buried unexploded bomb hazard maps remains important in identifying their precise location in the modern landscape. Ground penetrating radar (GPR)—a non-destructive technique (NDT)—can help detect these bombs buried beneath the soil by providing an accurate horizontal and vertical position. Using aerial photos and NDTs, such as GPR, this future project explores the WWII human experience to preserve and manage the safety of both the archaeological heritage and involved users by using the data to create an open-access WebGIS platform.
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Musakwa, Walter, Shuai Wang, Fangli Wei, Olgah Lerato Malapane, Masala Makumule Thomas, Sydney Mavengahama, Hongwei Zeng, et al. "Survey of Community Livelihoods and Landscape Change along the Nzhelele and Levuvhu River Catchments in Limpopo Province, South Africa." Land 9, no. 3 (March 19, 2020): 91. http://dx.doi.org/10.3390/land9030091.
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Landscape-change studies have attracted increasing interest because of their importance to land management and the sustainable livelihoods of rural communities. However, empirical studies on landscape change and its drivers are often poorly understood, particularly, in small rural communities in developing countries such as South Africa. The present study surveyed local community livelihoods and perceptions of landscape change in the Nzhelele and Levuvhu river catchments in Limpopo Province, South Africa. These areas have experienced land reform and are also characterized by environmental degradation, poverty, inequality and environmental justice concerns among other issues. Land-cover maps derived from Landsat satellite imagery were used for purposes of correlating and validating the survey data findings and results. The survey results showed that education levels, working status and marital status have statistically significant effects on community livelihoods (indicated by levels of income, p < 0.05). Maize, fruits and vegetables are the main cultivated crop varieties in the study area, and these crops are mainly used for subsistence to meet household self-consumption requirements. Moreover, local community members and stakeholders argue that the landscape has changed over the past 20 years mainly as a result of urban expansion, deforestation, agricultural diversification and forestry intensification. These landscape changes were largely confirmed by the land-cover change maps derived from satellite imagery. Soil erosion as a result of landscape changes was identified as a major threat and hazard in the study area. Political, natural, economic and cultural factors have been identified as the major underlying drivers for the observed landscape changes. These results have implications for understanding landscape change, coupled with human–nature relationships as well as informing government policy with respect to advancing land management and further promotion of the sustainable livelihoods of rural communities. Overall, the study proposes a multiple stakeholders’ approach and ecosystem-based approach to promote the sustainable management of landscapes in rural areas.
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Thomas, M., R. W. Fitzpatrick, and G. S. Heinson. "An expert system to predict intricate saline - sodic subsoil patterns in upland South Australia." Soil Research 47, no. 6 (2009): 602. http://dx.doi.org/10.1071/sr08244.
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Digital soil mapping (DSM) offers apparent benefits over more labour-intensive and costly traditional soil survey. Large cartographic scale (e.g. 1 : 10 000 scale) soil maps are rare in Australia, especially in agricultural areas where they are needed to support detailed land evaluation and targeted land management decisions. We describe a DSM expert system using environmental correlation that applies a priori knowledge from a key area (128 ha) soil–landscape with a regionally repeating toposequence to predict the distribution of saline–sodic subsoil patterns in the surrounding upland farming region (2275 ha) in South Australia. Our predictive framework comprises interrelated and iterative steps, including: (i) consolidating a priori knowledge of the key area soil–landscape; (ii) refining existing mentally held and graphic soil–landscape models; (iii) selecting suitable environmental covariates compatible with geographic information systems (GIS) by interrogation via 3D visualisation using a GIS; (iv) transforming the existing soil–landscape models to a computer model; (v) applying the computer model to the environmental variables using the expert system; (vi) performing the predictive mapping; and (vii) validation. The environmental covariates selected include: digital terrain attributes of slope gradient, topographic wetness index and plan curvature, and airborne gamma-radiometric K%. We apply selected soil profile physiochemical data from a prior soil survey to validate mapping. Results showed that we correctly predicted the saline–sodic subsoils in 10 of 11 reference profiles in the region.
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Julich, S., L. Breuer, and H. G. Frede. "Integrating heterogeneous landscape characteristics into watershed scale modelling." Advances in Geosciences 31 (July 6, 2012): 31–38. http://dx.doi.org/10.5194/adgeo-31-31-2012.
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Abstract. Two versions of the SWAT-model with different dominating runoff generation processes have been applied. One version comprises the original available SWAT version where only the basic input data are used. In the second version SWAT has been modified, by the integration of an impermeable layer at the subbasin level, in order to better reflect the boundary between soil and bedrock that results in increased lateral flow in low mountain ranges. As well, since conventional German soil maps do not describe soil horizons beyond 2 m depth, we also added a 4 m fixed depth in the lowland areas in order to reflect the deep loess deposits in this region. The decision for the location of the impermeable and the additional loess layer was based on a GIS analysis of additional geologic information. This study revealed that both model versions produced acceptable and comparable results regarding the evaluated goodness of fit measures. The GLUE analysis showed that the SWAT model set up with additional information about the distribution of impervious soil layers and the loess depth in the lowlands produced the highest simulation quality and the lowest uncertainty. Moreover, SWAT II version was able to better represent the spatial extend of the dominating runoff processes best. This leads to the conclusion that the SWAT II version is better suited for scenario analysis than the original model version.
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Calderano Filho, Braz, Helena Polivanov, César da Silva Chagas, Waldir de Carvalho Júnior, Emílio Velloso Barroso, Antônio José Teixeira Guerra, and Sebastião Barreiros Calderano. "Artificial neural networks applied for soil class prediction in mountainous landscape of the Serra do Mar¹." Revista Brasileira de Ciência do Solo 38, no. 6 (December 2014): 1681–93. http://dx.doi.org/10.1590/s0100-06832014000600003.
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Soil information is needed for managing the agricultural environment. The aim of this study was to apply artificial neural networks (ANNs) for the prediction of soil classes using orbital remote sensing products, terrain attributes derived from a digital elevation model and local geology information as data sources. This approach to digital soil mapping was evaluated in an area with a high degree of lithologic diversity in the Serra do Mar. The neural network simulator used in this study was JavaNNS and the backpropagation learning algorithm. For soil class prediction, different combinations of the selected discriminant variables were tested: elevation, declivity, aspect, curvature, curvature plan, curvature profile, topographic index, solar radiation, LS topographic factor, local geology information, and clay mineral indices, iron oxides and the normalized difference vegetation index (NDVI) derived from an image of a Landsat-7 Enhanced Thematic Mapper Plus (ETM+) sensor. With the tested sets, best results were obtained when all discriminant variables were associated with geological information (overall accuracy 93.2 - 95.6 %, Kappa index 0.924 - 0.951, for set 13). Excluding the variable profile curvature (set 12), overall accuracy ranged from 93.9 to 95.4 % and the Kappa index from 0.932 to 0.948. The maps based on the neural network classifier were consistent and similar to conventional soil maps drawn for the study area, although with more spatial details. The results show the potential of ANNs for soil class prediction in mountainous areas with lithological diversity.
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Menges, Eric S., Rebecca W. Dolan, Roberta Pickert, Rebecca Yahr, and Doria R. Gordon. "Genetic Variation in Past and Current Landscapes: Conservation Implications Based on Six Endemic Florida Scrub Plants." International Journal of Ecology 2010 (2010): 1–12. http://dx.doi.org/10.1155/2010/503759.
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If genetic variation is often positively correlated with population sizes and the presence of nearby populations and suitable habitats, landscape proxies could inform conservation decisions without genetic analyses. For six Florida scrub endemic plants (Dicerandra frutescens, Eryngium cuneifolium, Hypericum cumulicola, Liatris ohlingerae, Nolina brittoniana, and Warea carteri), we relate two measures of genetic variation, expected heterozygosity and alleles per polymorphic locus (APL), to population size and landscape variables. Presettlement areas were estimated based on soil preferences and GIS soils maps. Four species showed no genetic patterns related to population or landscape factors. The other two species showed significant but inconsistent patterns. ForLiatris ohlingerae, APL was negatively related to population density and weakly, positively related to remaining presettlement habitat within 32 km. ForNolina brittoniana, APL increased with population size. The rather weak effects of population area/size and both past and current landscape structures suggest that genetic variation needs to be directly measured and not inferred for conservation planning.
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Yan, Jun Xia, and Jian Feng Zhang. "Consequences of Land Use in an Intensive Region in North China Plain." Advanced Materials Research 588-589 (November 2012): 1999–2002. http://dx.doi.org/10.4028/www.scientific.net/amr.588-589.1999.
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Land use changes and land intensification has played a more and more important role in food production. The environment has been influenced by it greatly. Land use data were derived from several sources: aerial photographs, current land use maps, Second National Soil Survey (SNSS) map, and fieldwork. The aerial photographs, 1:50,000 for both 1980 and 2006 were obtained from the Department of Surveys and Mapping (DSM). Bulk soil samples were collected at 79 sites across Quzhou district. Samples were collected again at the same locations in 2000 and 2006. To compare the soil data of 2006, 2000 and 1980, latitude and longitude of the sampling locations were recorded using the Global Position System at the time of soil collection. The samples site selection was done on behalf of the Second National Soil Survey. A great change had taken place in land use and land use intensification. The changes, which have converted natural landscapes into the use for human, have made a large proportion of the Quhzou’s landscape change greatly.
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Krechetnikova, E. O., V. V. Krechetnikov, I. E. Titov, and V. K. Kuznetsov. "Geoinformation system for designing adaptive landscape farming systems on the radioactively contaminated territory of the Tula research institute of agriculture." Geoinformatika, no. 4 (2020): 12–19. http://dx.doi.org/10.47148/1609-364x-2020-4-12-19.
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GIS project was developed for the radioactively contaminated territory of the Tulskii NII. It was created in order to project the adaptive landscape agricultures. It was based on the information on the concentrations of 137Cs radionuclide in soil, compiled over 16 years. Electronic maps have been developed to create a GIS project and included the location of agricultural lands; crop rotation systems; distribution of specific activity values for artificial 137Cs radionuclide in agricultural lands; agrochemical indexes (the humus content, potassium content, contribution of phosphorus, the acidity), soil types, relief. The created GIS project and the corresponding data bases will be used to collect, store and analyse the results of the survey in order to project the adaptive landscape agricultures. Key words: GIS project, adaptive landscape agriculture, agricultural lands, radiation safety.
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Osowiec, Michał. "Functioning of Hydrogenic Landscapes the Upper Włodawka River Catchment Basin." Miscellanea Geographica 13, no. 1 (December 1, 2008): 33–49. http://dx.doi.org/10.2478/mgrsd-2008-0004.
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Abstract In the dissertation, I analysed two aspects of the Polesie Lubelskie landscape. The first is the historical aspect – changes in the landscape in the 19th and 20th centuries. In evaluating such changes I relied on the existing maps and relevant literature. The second aspect is the contemporary functioning of the hydrogenic landscape, changes over the course of the year or seasonal changes. This is to allow an assessment of contemporary changes in the environment. The fieldwork focuses on three components or three factors of the environment: water, soil and vegetation. The water factor is analysed by measuring oscillation of the ground water table as well as the chemical content of river and ground waters. The soil component is examined to determine distribution of various soil types in the study area. Vegetation is analysed by spatial distribution of floral assemblages. I am researching chemical features such as the levels of Ca, HCO3−, Mg, N, P K, Fe, S, Cl, Si and pH.