Topographic Attributes Research Articles

Sensitivity of digital elevation models: The scenario from two tropical mountain river basins of the Western Ghats, India

The paper evaluates sensitivity of various spaceborne digital elevation models (DEMs), viz., Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), Shuttle Radar Topography Mapping Mission (SRTM) and Global Multi-resolution Terrain Elevation Data 2010 (GMTED), in comparison with the DEM (TOPO) derived from contour data of 20 m interval of Survey of India topographic sheets of 1: 50,000 scale. Several topographic attributes, such as elevation (above mean sea level), relative relief, slope, aspect, curvature, slope-length and -steepness (LS) factor, terrain ruggedness index (TRI), topographic wetness index (TWI), hypsometric integral (Ihyp) and drainage network attributes (stream number and stream length) of two tropical mountain river basins, viz., Muthirapuzha River Basin and Pambar River Basin are compared to evaluate the variations. Though the basins are comparable in extent, they differ in respect of terrain characteristics and climate. The results suggest that ASTER and SRTM provide equally reliable representation of topography portrayed by TOPO and the topographic attributes extracted from the spaceborne DEMs are in agreement with those derived from TOPO. Despite the coarser resolution, SRTM shows relatively higher vertical accuracy (RMSE = 23 and 20 m respectively in MRB and PRB) compared to ASTER (RMSE = 33 and 24 m) and GMTED (RMSE = 59 and 48 m). Vertical accuracy of all the spaceborne DEMs is influenced by relief of the terrain as well as type of vegetation. Further, GMTED shows significant deviation for most of the attributes, indicating its inability for mountain-river-basin-scale studies.

TERRESTRIAL LASER SCANNER DATA TO SUPPORT COASTAL EROSION ANALYSIS: THE CONERO CASE STUDY

Abstract. In this work a detailed TLS survey was carried out in summer 2012, in the Conero Regional Park (Marche, province of Ancona), along the "spiaggia San Michele" and "spiaggia Sassi Neri". These areas present several sections affected by erosion, rock falls and slope failures. They also belong to a very prestigious place for tourism during the summer season; therefore, deriving a risk map for these areas is really useful. Thanks to the TLS survey, it was possible to obtain a centimetre resolution DTM covering a reach of about 1.5 km of the coast. This high resolution DTM was used to derive some primary topographic attributes that allowed to arrange a preliminary discussion about the likely unstable areas. These topographic information and results will also serve as the reference point for future yearly TLS surveys, which will absolutely help in recognizing any micro changes and slope failures, improving the risk maps.

Comparative performance assessment of cenosphere and barium sulphate based friction composites

Friction composites utilising cenosphere and barium sulphate as major fillers were fabricated both separately and in combination. Thermal analysis revealed initial degradation temperature >500°C irrespective of the composition. Mechanical properties viz. hardness, compressibility and shear strength were found to be well above the standard values as per the industrial practice. Dynamic mechanical response demonstrated improved storage and loss moduli for barium sulphate based composites. Tribological assessment conforming to the regulation-90 as per the Economic Commission for Europe (ECE) norms revealed improved wear resistance, enhanced recovery, lower disc temperature rise and reduced friction fluctuation for cenospheres based composites. Composites containing both fillers showed cenospheres dominated tribological response. Empirical correlation between wear, friction coefficients and dynamic mechanical properties as temperature controlled parameters was developed to predict wear. Worn surface analysis of the brake pads was carried out by scanning electron microscope (SEM) to visually analyse the associated wear mechanism at the braking interface through various topographical attributes viz. primary and secondary contact plateaus.

Exploring spatiotemporal patterns and physical controls of soil moisture at various spatial scales

Soil moisture variability of various spatial scales is analyzed based on empirical orthogonal function (EOF) method using soil moisture datasets with various spatial resolutions: 1 km eco-hydrological model simulation, 0.25° passive microwave (Advanced Microwave Scanning Radiometer for the Earth Observing System, AMSR-E) dataset, and 0.5° land surface model simulation from Climate Predictor Center (CPC). All three datasets generate EOFs that explain similar variances with those generated from in situ observations from agro-meteorological network. Using AMSR-E product and eco-hydrological model simulation, it is found that the primary spatial pattern of soil moisture obtained from watershed scale has a strong connection to topographic attributes, followed by soil texture and rainfall variability, as suggested by the correlation between the primary EOF mode (EOF1) of soil moisture and landscape attributes. However, the EOF analysis of both AMSR-E and CPC datasets at regional scale reaches the conclusion that soil texture indices, such as sand and clay content, is of higher importance to soil moisture EOF1 spatial pattern (explaining 61 % variance) than topography is. Furthermore, correlation between soil moisture EOF1 and soil property is higher in spring than in autumn, which indicates that soil water-holding and drainage capabilities are more important under dry conditions. At national scale, the combined effects of topographic feature and soil property are clearly exhibited in EOF1. The study results reveal that different emphases should be placed on accurate acquisition of landscape attributes for soil moisture estimation according to various spatial scales.

Atributos topográficos na diferenciação de Argissolos

A topografia do terreno controla muitos processos hidrológicos, geomorfológicos e pedológicos, influenciando a radiação solar, precipitação pluvial, escoamento superficial, evaporação, regime de umidade do solo e tipo de vegetação, entre outros. Desta maneira, atributos topográficos derivados de um modelo digital de elevação foram utilizados para explicar a diferenciação de solos com horizonte B textural da região de ''Mar de Morros'', no noroeste do Estado do Rio de Janeiro. Foram estudados oito perfis de solo (quatro Argissolos Vermelhos e quatro Argissolos Vermelho-Amarelos), desenvolvidos de granulitos noríticos nos municípios de São José de Ubá e Itaperuna. Os dados dos atributos topográficos em cada perfil de solo (elevação, declividade, aspecto, plano e perfil de curvatura, radiação solar e índice topográfico combinado) foram extraídos, utilizando-se uma janela de 7 x 7 pixels, com os perfis ocupando o centro dessa janela. Os Argissolos que ocorrem nas encostas noroeste e nordeste recebem maior quantidade de radiação solar (mais quentes e secas) e por isto são vermelhos, eutróficos e não apresentam horizonte B latossólico, enquanto os solos das encostas sudeste (relativamente mais frias e úmidas) são vermelho-amarelados, distróficos e com horizonte B latossólico. A radiação solar, a declividade e o aspecto são os atributos topográficos relacionados com as diferenças entre os perfis de solos estudados. Os atributos topográficos analisados pelas técnicas multivariadas apresentaram-se efetivos para a distinção entre os Argissolos Vermelho-Amarelos distróficos e os Argissolos Vermelhos eutróficos, exceto o P7 (PVe). Estudos relacionando a influência da radiação solar na pedogênese são escassos em condições tropicais e, embora menos atuante em regiões tropicais, foi a radiação solar que determinou diretamente a diferenciação dos solos da área estudada.

Emprego de atributos topográficos no mapeamento da susceptibilidade a processos geoambientais na bacia do rio Jacareí, Paraná

O presente trabalho realizou o mapeamento da susceptibilidade a processos geoambientais na bacia do rio Jacareí, localizada na Serra do Mar Paranaense. A escolha da área justifica-se por essa ter sido fortemente afetada por processos de movimentos de massa ocorridos no dia 11 de março de 2011, que ocasionaram diversos danos e prejuízos à população da região. A cartografia foi realizada por meio da análise digital do relevo, com o emprego dos atributos topográficos que mostraram melhor relação com os processos, sendo eles: hipsometria, declividade, plano de curvatura e índice topográfico de umidade. A legenda do mapa foi organizada em dez classes, contemplando os processos de escorregamentos, corridas de detritos e inundações associadas a corridas de lama, com níveis de susceptibilidade moderada, alta e muito alta.

Assessment of flora diversity in a minor river valley using ecological indicator values, Geographical Information Systems and Digital Elevation Models

Abstract Ellenberg indicator values (EIV) have been widely used to estimate habitat variables from floristic data and to predict vegetation composition based on habitat properties. Geographical Information Systems (GIS) and Digital Elevation Models (DEM) are valuable tools for studying the relationships between topographic and ecological characters of river systems. A 3-meter resolution DEM was derived for a. 3-km-long break section of the Szum River (SE Poland) from a 1:10,000 topographic map. Data on the diversity and ecological requirements of the local vascular flora were obtained while making floristic charts for 32 sections of the river valley (each 200 m long) and physical and chemical soil measurements; next, the data were translated into EIV. The correlations of the primary and secondary topographic attributes of the valley, species richness, and EIV (adapted for the Polish vascular flora) were assessed for all species recognized in each valley section. The total area and proportion of a flat area, mean slope, slope curvature, solar radiation (SRAD), and topographic wetness index (TWI) are the most important factors influencing local flora richness and diversity. The highest correlations were found for three ecological indicators, namely light, soil moisture, and soil organic content. The DEM seems to be useful in determination of correlations between topographic and ecological attributes along a minor river valley.

Vertical Variation of Nonpoint Source Pollutants in the Three Gorges Reservoir Region

Nonpoint source (NPS) pollution is considered the main reason for water deterioration, but there has been no attempt to incorporate vertical variations of NPS pollution into watershed management, especially in mountainous areas. In this study, the vertical variations of pollutant yields were explored in the Three Gorges Reservoir Region (TGRR) and the relationships between topographic attributes and pollutant yields were established. Based on our results, the pollutant yields decreased significantly from low altitude to median altitude and leveled off rapidly from median altitude to high altitude, indicating logarithmic relationships between pollutant yields and altitudes. The pollutant yields peaked at an altitude of 200–500 m, where agricultural land and gentle slopes (0–8°) are concentrated. Unlike the horizontal distributions, these vertical variations were not always related to precipitation patterns but did vary obviously with land uses and slopes. This paper also indicates that altitude data and proportions of land use could be a reliable estimate of NPS yields at different altitudes, with significant implications for land use planning and watershed management.

Relationships between grain protein, Zn, Cu, Fe and Mn contents in wheat and soil and topographic attributes

The knowledge on the relationships of protein and micronutrient concentration in wheat grain with edaphic characteristics could provide valuable information for site-specific fertilization of crops for producing grains denser in micronutrients such as iron (Fe) and zinc (Zn) in rain-fed agriculture. In this study, we used soil properties and topographic parameters in the artificial neural network (ANN) methodology as a power tool for improving models for predicting wheat grain micronutrient and protein contents in the hilly regions of western Iran. Soil and grain samples were collected from 1 m2 plots using the stratified random method, whereas the slope positions were considered as the basis of soil sampling, at 100 selected points. The mean grain Zn, Fe, Cu (copper) and Mn (manganese) concentrations were 37.02, 65.86, 14.79 and 44.93 mg–1 kg–1, respectively, and mean grain protein was 13.76%. Application of the ANN models for predicting Zn, Fe, Cu, Mn and protein contents in grains improved prediction by 96.77%, 95.45%, 124.13%, 125% and 109.75%, respectively, over the multiple linear regression (MLR) models.The topographic parameters wetness index, plan curvature and shaded relief, selected soil properties total nitrogen (TN), soil organic matter, available phosphorus and DTPA-extractable micronutrients were identified as the most important parameters for explaining the variability in wheat grain quality at the study area.

Estimating wet soil aggregate stability from easily available properties in a highly mountainous watershed

A comparison study was carried out with the purpose of verifying when the adaptive neuro-fuzzy inference system (ANFIS), artificial neural network (ANN), generalized linear model (GLM), and multiple linear regression (MLR) models are appropriate for prediction of soil wet aggregate stability (as quantified by the mean weight diameter, MWD) in a highly mountainous watershed (Bazoft watershed, southwestern Iran). Three different sets of easily available properties were used as inputs. The first set (denoted as SP) consisted of soil properties including clay content, calcium carbonate equivalent, and soil organic matter content. The second set (denoted as TVA) included topographic attributes (slope and aspect) and the normalized difference vegetation index (NDVI). The third set (denoted as STV) was a combination of soil properties, slope, and NDVI. The ANN and ANFIS models predicted MWD more accurately than the GLM and MLR models. Estimation of MWD using TVA data set resulted in the lowest model efficiency values. The observed model efficiency values for the developed MLR, GLM, ANN, and ANFIS models using the SP data set were 60.76, 62.98, 77.68 and 77.15, respectively. Adding slope and NDVI to soil data (i.e. STV data set) improved the predictions of all four methods. The obtained correlation coefficient values between the predicted and measured MWD for the developed MLR, GLM, ANN, and ANFIS models using STV data set were 0.24, 0.35, 0.84 and 0.73, respectively. In conclusion, the ANN and ANFIS models showed greater potential in predicting soil aggregate stability from soil and site characteristics, whereas linear regression methods did not perform well.

Hydrogels for Two‐Photon Polymerization: A Toolbox for Mimicking the Extracellular Matrix

AbstractThe natural extracellular matrix (ECM) represents a complex and dynamic environment. It provides numerous spatio‐temporal signals mediating many cellular functions including morphogenesis, adhesion, proliferation and differentiation. The cell–ECM interaction is bidirectional. Cells dynamically receive and process information from the ECM and remodel it at the same time. Theses complex interactions are still not fully understood. For better understanding, it is indispensable to deconstruct the ECM up to the point of investigating isolated characteristics and cell responses to physical, chemical and topographical cues. Two‐photon polymerization (2PP) allows the exact reconstruction of cell specific sites in 3D at micro‐ and nanometer precision. Processing biocompatible synthetic and naturally‐derived hydrogels, the microenvironment of cells can be designed to specifically investigate their behavior in respect to key chemical, mechanical and topographical attributes. Moreover, 3D manipulation can be performed in the presence of cells, guiding biological tissue formation in all stages of its development. Here, advances in 2PP microfabrication of synthetic and naturally based hydrogels are reviewed. Key components of photopolymerizable hydrogel precursors, their structure–property relationships and their polymerization mechanisms are presented. Furthermore, it is shown how biocompatible 2PP fabricated constructs can act as biologically relevant matrices to study cell functions and tissue development.

Soil carbon sequestration as affected by slope aspect under restoration treatments of a degraded alfisol in the Indian sub-tropics

Rehabilitation of degraded lands needs appropriate mix of land use and erosion control measures, and is often associated with carbon (C) sequestration in the soil profile. However, topographic attributes play a deterministic role in the rate of C accretion in degraded sloping lands. This study was carried out to assess the effect of slope aspect on soil C sequestration, soil aggregation and soil moisture retention in aggradation phase of a denuded land in eastern India. Eight treatments of horti-silvi-pastural system integrated with in-situ moisture conservation were taken in randomized block design during 2000 to 2006. Indigofera teysmanni was taken as the silviculture component and hedgerows of the species were used uniformly for all the treatments. A significant interaction effect of the rehabilitation system and slope aspect was observed for residual soil moisture content, soil organic C (SOC) content, SOC stock, size distribution of aggregates and C content in aggregate fractions. Treatments with trenches of 0.45×0.45×1.0m dimension at 0.5mu/s of fruit plants conserved significantly higher soil moisture even at 87mm of evaporativity. On an average, the north facing (NF) aspect had 1.13 and 0.75g 100g−1 higher soil moisture than the east facing (EF) aspect in the 0–15cm and 15–30cm soil depths, respectively. The SOC concentration was higher by 11–12% in the NF than the EF aspect. In the 0–30cm soil profile, the SOC stock varied from 31.55 to 37.91Mgha−1 in the EF aspect and from 35.01 to 41.28Mgha−1 in the NF aspect, as compared to the initial stock of 18.19 and 19.06Mgha−1 in the two aspects, respectively. The NF aspect had 0.35 to 3.17Mgha−1 higher SOC stock in the 0–15cm soil, 0.64 to 3.03Mgha−1 in the 15–30cm soil and 1.85 to 4.59Mgha−1 in the whole 0–30cm soil profile. Averaged over all the rehabilitation systems, the NF aspect accumulated extra C to the tune of 0.19, 0.18 and 0.36Mgha−1yr−1 than the EF aspect in the 0–15, 15–30 and 0–30cm soil layers, respectively. Under all the systems and slope aspects, small macroaggregates (>250μm) constituted the highest proportion, with values varying from 50.4–65.4% in the EF to 61.7–71.7% in the NF aspect. The C content in small macroaggregates was also higher than that in microaggregates and silt+clay size fractions. The study indicates slope aspect to be a significant factor in soil C sequestration, which also affects the aggregation pattern of soils under recovery.

A GIS-based approach for gully erosion susceptibility modelling: a test in Sicily, Italy

The aim of this study is to analyze the susceptibility conditions to gully erosion phenomena in the Magazzolo River basin and to test a method that allows for driving the factors selection. The study area is one of the largest (225 km2) watershed of southern Sicily and it is mostly characterized by gentle slopes carved into clayey and evaporitic sediments, except for the northern sector where carbonatic rocks give rise to steep slopes. In order to obtain a quantitative evaluation of gully erosion susceptibility, statistical relationships between the spatial distributions of gullies affecting the area and a set of twelve environmental variables were analyzed. Stereoscopic analysis of aerial photographs dated 2000, and field surveys carried out in 2006, allowed us to map about a thousand landforms produced by linear water erosion processes, classifiable as ephemeral and permanent gullies. The linear density of the gullies, computed on each of the factors classes, was assumed as the function expressing the susceptibility level of the latter. A 40-m digital elevation model (DEM) prepared from 1:10,000-scale topographic maps was used to compute the values of nine topographic attributes (primary: slope, aspect, plan curvature, profile curvature, general curvature, tangential curvature; secondary: stream power index; topographic wetness index; LS-USLE factor); from available thematic maps and field checks three other physical attributes (lithology, soil texture, land use) were derived. For each of these variables, a 40-m grid layer was generated, reclassifying the topographic variables according to their standard deviation values. In order to evaluate the controlling role of the selected predictive variables, one-variable susceptibility models, based on the spatial relationships between each single factor and gullies, were produced and submitted to a validation procedure. The latter was carried out by evaluating the predictive performance of models trained on one half of the landform archive and tested on the other. Large differences of accuracy were verified by computing geometric indexes of the validation curves (prediction and success rate curves; ROC curves) drawn for each one-variable model; in particular, soil texture, general curvature and aspect demonstrated a weak or a null influence on the spatial distribution of gullies within the studied area, while, on the contrary, tangential curvature, stream power index and plan curvature showed high predictive skills. Hence, predictive models were produced on a multi-variable basis, by variously combining the one-variable models. The validation of the multi-variables models, which generally indicated quite satisfactory results, were used as a sensitivity analysis tool to evaluate differences in the prediction results produced by changing the set of combined physical attributes. The sensitivity analysis pointed out that by increasing the number of combined environmental variables, an improvement of the susceptibility assessment is produced; this is true with the exception of adding to the multi-variables models a variable, as slope aspect, not correlated to the target variable. The addition of this attribute produces effects on the validation curves that are not distinguishable from noise and, as a consequence, the slope aspect was excluded from the final multi-variables model used to draw the gully erosion susceptibility map of the Magazzolo River basin. In conclusion, the research showed that the validation of one-variable models can be used as a tool for selecting factors to be combined to prepare the best performing multi-variables gully erosion susceptibility model.

지형조건에 따른 제주도의 일사량 분포 추정

The solar radiation is the primary energy source that drives many of the earth`s physical and biological processes and climate change. Understanding its importance to the solar radiation observation is a key to understanding a broad range of natural processes, agricultural, energy and human activities. The purpose of this study is to estimate solar radiation using sunshine duration, and to estimate distribution of solar radiation using a topography factor considering surface slope and aspect in complex terrain. The result of regression analysis between ratio of solar radiation and sunshine duration from 2001 to 2010 shows high value of 0.878. Regression analyses indicated that topographic attributes including elevation, slope and aspect had significant effects on solar radiation. The variation of topographic factor with aspect and slope for the summer and winter are considered. The highest month of daily mean solar radiation at Jeju island appears in April of 20.61 , and the lowest month appears in December of 6.90 . These results provided useful quantitative information about the influence of topography on solar radiation in the island region.

Relationships between soil depth and terrain attributes in a semi arid hilly region in western Iran

Soil depth generally varies in mountainous regions in rather complex ways. Conventional soil survey methods for evaluating the soil depth in mountainous and hilly regions require a lot of time, effort and consequently relatively large budget to perform. This study was conducted to explore the relationships between soil depth and topographic attributes in a hilly region in western Iran. For this, one hundred sampling points were selected using randomly stratified methodology, and considering all geomorphic surfaces including summit, shoulder, backslope, footslope and toeslope; and soil depth was actually measured. Eleven primary and secondary topographic attributes were derived from the digital elevation model (DEM) at the study area. The result of multiple linear regression indicated that slope, wetness index, catchment area and sediment transport index, which were included in the model, could explain about 76 % of total variability in soil depth at the selected site. This proposed approach may be applicable to other hilly regions in the semi-arid areas at a larger scale.

Using an automatic resistivity profiler soil sensor on-the-go in precision viticulture.

Spatial information on vineyard soil properties can be useful in precision viticulture. In this paper a combination of high resolution soil spatial information of soil electrical resistivity (ER) and ancillary topographic attributes, such as elevation and slope, were integrated to assess the spatial variability patterns of vegetative growth and yield of a commercial vineyard (Vitis vinifera L. cv. Tempranillo) located in the wine-producing region of La Rioja, Spain. High resolution continuous geoelectrical mapping was accomplished by an Automatic Resistivity Profiler (ARP) on-the-go sensor with an on-board GPS system; rolling electrodes enabled ER to be measured for a depth of investigation approximately up to 0.5, 1 and 2 m. Regression analysis and cluster analysis algorithm were used to jointly process soil resistivity data, landscape attributes and grapevine variables. ER showed a structured variability that matched well with trunk circumference spatial pattern and yield. Based on resistivity and a simple terrain attribute uniform management units were delineated. Once a spatial relationship to target variables is found, the integration of point measurement with continuous soil resistivity mapping is a useful technique to identify within-plots areas of vineyard with similar status.

Soil prediction using artificial neural networks and topographic attributes

Because relief maps show a strict relationship with soils at different spatial levels, distributions of soil units can be inferred from digital topography analyses. Geoprocessing techniques can be used to create parametric relief representations from digital terrain models (DTMs), and these models can be used to calculate primary and secondary topographical attributes, such as the elevation, profile and plan curvature, slope, stream power index, topographic wetness index, and sediment transport index. The classic method of pedological cartography is onerous and time-consuming; as an alternative, pedometric techniques favor the recognition of preliminary mapping units. In this study, a multilayered perceptron artificial neural network (ANN) with an error backpropagation algorithm was used, where topographical and geological attributes were used as input parameters. The classified map was validated by comparison with two preexisting conventional ground maps of the study area. The kappa (K) index, global exactness (GE), and exactness from the point of view of the producer and user were considered in the comparison. The quality of the soil units classified by the ANN was satisfactory, based on the K and GE values from the comparison.

A regional inventory of rock glaciers and protalus ramparts in the central Italian Alps

We present a regional inventory of rock glaciers (n=1514) and protalus ramparts (228) for the Lombardy region, central Italian Alps. To identify and classify the landforms we inspect three sequential air-orthophoto mosaics and a 2m-DSM, and conduct confirmatory field work. The inventory forms an empirical basis to analyze: (i) the relative contribution of hillslope (i.e., talus slopes) and glacial (i.e., moraines) sediment stores to rock glacier sediment supply; (ii) linkages between the landforms inventoried and local topographic attributes; (iii) the spatial variability of periglacial activity in relation to a parsimonious set of environmental variables (i.e., elevation, precipitation, and lithology); and (iv) the effects of the Pleistocene–Holocene climatic transition on the distribution of intact and relict landforms. This analysis reveals that the elevation of rock glacier termini can vary over 200m as a function of slope aspect. In turn, the distribution of rock glaciers among aspect categories is controlled by the structure of the valley network that promotes NW and SE exposures. Talus rock glaciers prevail numerically over the glacier-related typology, even though the latter population appears to have increased during the Holocene. Relict and intact rock glaciers have distinct spatial patterns in that the former display, on average, a 400-m elevation drop and a less clustered distribution towards northern aspects, suggesting that they have developed in more “permafrost-prone” climatic conditions. Analyzing the study region through a 27.5km-grid has been instrumental for showing that the rock glacier specific area and terminus elevation are: (i) positively correlated with terrain elevation; and (ii) negatively correlated with mean annual precipitation. As a consequence, in relation to Holocene generalized atmospheric temperature rise, intact rock glaciers have progressively disappeared from the wetter and milder portions of the central Italian Alps. Analysis of rock glacier occurrence across litho-tectonic sectors does not provide conclusive dependences and requires further analysis. This inventory, which represents a necessary preliminary step for modelling the spatial distribution of discontinuous permafrost at the regional scale, fills a critical geographic gap in the context of ongoing permafrost research in the European Alps (e.g., PermaNET).

Soil-Landscape Modeling and Remote Sensing to Provide Spatial Representation of Soil Attributes for an Ethiopian Watershed

Information about the spatial distribution of soil properties is necessary for natural resources modeling; however, the cost of soil surveys limits the development of high-resolution soil maps. The objective of this study was to provide an approach for predicting soil attributes. Topographic attributes and the normalized difference vegetation index (NDVI) were used to provide information about the spatial distribution of soil properties using clustering and statistical techniques for the 56 km2Gumara-Maksegnit watershed in Ethiopia. Multiple linear regression models implemented within classified subwatersheds explained 6–85% of the variations in soil depth, texture, organic matter, bulk density, pH, total nitrogen, available phosphorous, and stone content. The prediction model was favorably comparable with the interpolation using the inverse distance weighted algorithm. The use of satellite images improved the prediction. The soil depth prediction accuracy dropped gradually from 98% when 180 field observations were used to 65% using only 25 field observations. Soil attributes were predicted with acceptable accuracy even with a low density of observations (1-2 observations/2 km2). This is because the model utilizes topographic and satellite data to support the statistical prediction of soil properties between two observations. Hence, the use of DEM and remote sensing with minimum field data provides an alternative source of spatially continuous soil attributes.

Mapping the porosity of international border to pedestrian traffic: a comparative data classification approach to a study of the border region in Austria, Italy, and Slovenia

National borders play an important role in everyday life. Interest in border studies has increased with recent changes in geographical locations of the border or the fluctuation of the permeability of the border between some countries, such as in the European Union. Whether the nations are trying to increase traffic flow of the border or to implement stricter border control, having appropriate information of the border is crucial for effective policymaking. The objective of this research was to identify areas of high porosity, or high permeability, for pedestrians along the southern national border region in Carinthia, Austria using terrain, land use, and road data along with geocomputational methods. Two unsupervised classification methods, the fuzzy K-means clustering and the Self-Organizing Map, were applied to segment the border into homogeneous zones according to topographic and infrastructural attributes. The fuzzy K-means clustering method was chosen for its ability to allow for a continuous approach to classification. With this method, an object can belong, with different degrees of membership, to multiple classes, which is a more realistic reflection of the natural world than discrete clustering, where each object can only belong to one class. However, the fuzzy K-means clustering method does have disadvantages, i.e. the user must determine the number of classes and the input parameters are required to be in continuous format. The second classification method, the Self-Organizing Map, is a type of artificial neural network and was chosen for its ability to automatically determine the number of classes and handle categorical data. The Self-Organizing Map is unique because it can transform high dimensional data into low dimensional display while preserving the topology and spatial distribution of the input parameters. The results of the two classification methods suggest that the fuzzy K-means classification is more effective than the Self-Organizing Map for this situation. However, more research is needed to determine the fit of these algorithms for particular spatial data classification tasks. The results obtained from this research provide an insight into the permeability of the border region of Carinthia, Slovenia, and Italy to pedestrian traffic and can be potentially useful for decision making processes for tourism development and road transportation management in that region. Furthermore, the approach presented in this article can be applied to other national borders to identify zones permeable to pedestrian traffic.