Use of plan curvature variations for the identification of ridges and channels on DEM

This paper proposes novel improvements in the traditional algorithms for the identification of ridge and channel (also called ravines) topographic features on raster digital elevation models (DEMs). The overall methodology consists of two main steps: (1) smoothing the DEM by applying a mean filter, and (2) detection of ridge and channel features as cells with positive and negative plan curvature respectively, along with a decline and incline in plan curvature away from the cell in direction orthogonal to the feature axis respectively. The paper demonstrates a simple approach to visualize the multi-scale structure of terrains and utilize it for semi-automated topographic feature identification. Despite its simplicity, the revised algorithm produced markedly superior outputs than a comparatively sophisticated feature extraction algorithm based on conic-section analysis of terrain

A semi-automated approach for GIS based generation of topographic attributes for landform classification

This paper presents LANDFORM, a customized GIS application for semi-automated classification of landform elements, based on landscape parameters. Using custom commands, topographic attributes like curvature or elevation percentile were derived from a Digital Elevation Model (DEM) and used as thresholds for the classification of Crests, Flats, Depressions and Simple Slopes. With a new method, Simple Slopes were further subdivided in Upper, Mid and Lower Slopes at significant breakpoints along slope profiles. The paper discusses the results of a fuzzy set algorithm that was used to compare the similarity between the map generated by LANDFORM and the visual photo- interpretation conducted by a soil expert over the same area. The classification results can be used in applications related to precision agriculture, land degradation studies, and spatial modelling applications where landform is identified as an influential factor in the processes under study

Effective identification of terrain positions from gridded DEM data using multimodal classification integration

Terrain positions are widely used to describe the Earth’s topographic features and play an important role in the studies of landform evolution, soil erosion and hydrological modeling. This work develops a new multimodal classification system with enhanced classification performance by integrating different approaches for terrain position identification. The adopted classification approaches include local terrain attribute (LA)-based and regional terrain attribute (RA)-based, rule-based and supervised, and pixel-based and object-oriented methods. Firstly, a double-level definition scheme is presented for terrain positions. Then, utilizing a hierarchical framework, a multimodal approach is developed by integrating different classification techniques. Finally, an assessment method is established to evaluate the new classification system from different aspects. The experimental results, obtained at a Loess Plateau region in northern China on a 5 m digital elevation model (DEM), show reasonably positional relationship, and larger inter-class and smaller intra-class variances. This indicates that identified terrain positions are consistent with the actual topography from both overall and local perspectives, and have relatively good integrity and rationality. This study demonstrates that the current multimodal classification system, developed by taking advantage of various classification methods, can reflect the geographic meanings and topographic features of terrain positions from different levels

Quantitative methods demonstrate that environment alone is an insufficient predictor of present-day language distributions in New Guinea

Environmental parameters constrain the distributions of plant and animal species. A key question is to what extent does environment influence human behavior. Decreasing linguistic diversity from the equator towards the poles suggests that ecological factors influence linguistic geography. However, attempts to quantify the role of environmental factors in shaping linguistic diversity remain inconclusive. To this end, we apply Ecological Niche Modelling methods to present-day language diversity in New Guinea. We define an Eco-Linguistic Niche (ELN) as the range of environmental conditions present in the territory of a population speaking a specific language or group of languages characterized by common language traits. In order to reconstruct the ELNs, we used Papuan and Austronesian language groups, transformed their geographical distributions into occurrence data, assembled available environmental data for New Guinea, and applied predictive architectures developed in the field of ecology to these data. We find no clear relationship between linguistic diversity and ELNs. This is particularly true when linguistic diversity is examined at the level of language groups. Language groups are variably dependent on environment and generally share their ELN with other language groups. This variability suggests that population dynamics, migration, linguistic drift, and socio-cultural mechanisms must be taken into consideration in order to better understand the myriad factors that shape language diversity.publishedVersio

Quantitative methods demonstrate that environment alone is an insufficient predictor of present-day language distributions in New Guinea

Environmental parameters constrain the distributions of plant and animal species. A key question is to what extent does environment influence human behavior. Decreasing linguistic diversity from the equator towards the poles suggests that ecological factors influence linguistic geography. However, attempts to quantify the role of environmental factors in shaping linguistic diversity remain inconclusive. To this end, we apply Ecological Niche Modelling methods to present-day language diversity in New Guinea. We define an Eco-Linguistic Niche (ELN) as the range of environmental conditions present in the territory of a population speaking a specific language or group of languages characterized by common language traits. In order to reconstruct the ELNs, we used Papuan and Austronesian language groups, transformed their geographical distributions into occurrence data, assembled available environmental data for New Guinea, and applied predictive architectures developed in the field of ecology to these data. We find no clear relationship between linguistic diversity and ELNs. This is particularly true when linguistic diversity is examined at the level of language groups. Language groups are variably dependent on environment and generally share their ELN with other language groups. This variability suggests that population dynamics, migration, linguistic drift, and socio-cultural mechanisms must be taken into consideration in order to better understand the myriad factors that shape language diversity

A fuzzy logic slope-form system for predictive soil mapping of a landscape-scale area with strong relief conditions

Peer Revie

Savanna aliens

Numerous alien plant species are invading African savannas causing loss of biodiversity and altering ecosystem functioning. The ecological factors and underlying mechanisms causing these invasions are poorly understood. This hinders invasive species management and biodiversity conservation. In this thesis, a range of approaches (i.e., field measurements, a greenhouse experiment, field experiments, a long-term burning experiment, remote sensing, and Geographical Information System (GIS) techniques) was used to understand how the availability of two key resources limiting primary productivity in African savannas (water and nutrients) and how major disturbances (i.e., fire, grazing) determine the invasion of these systems by alien plant species

New data structure and process model for automated watershed delineation

DEM analysis to delineate the stream network and its associated subwatersheds are the primary steps in the raster-based parameterization of watersheds. There are two widely used methods for delineating subwatersheds. One of these is the Upstream Catchment Area (UCA) method. The UCA method employs a user specified threshold value of upstream catchment area to delineate subwatersheds from the extracted network of streams. The other common technique is the nodal method. In this approach, subwatersheds are initiated at stream network nodes, where nodes occur at the upstream starting point of streams and at the point of intersection of streams in the network. The UCA approach and the Nodal approach do not permit watershed initiation at points of specific interests. They also fail to explicitly recognize drainage features other than single channel reaches. That is, they exclude water bodies, wetlands, braided channels and other important hydrologic features. TOPAZ (TOpographic PArameteriZation) [Garbrecht and Martz, 1992], is a typical program for raster based, automated drainage analysis. It initiates subwatersheds at source points and at points of intersection of drainage channels. TOPAZ treats lakes as spurious depressions arising out of errors in DEM, and removes them. This research addresses one important limitation of the currently used modeling techniques and tools. It adds the capability to initiate watershed delineation at points of specific interest other than junction and source points in the delineated networks from the Digital Elevation Models (DEMs). The research project evaluates qualitative and quantitative aspects of a new Object Oriented data structure and process model for raster format data analysis in spatial hydrology. The concept of incorporating a user-specified analysis in extraction and parameterization of watersheds is based on the need to have a tool to allow for studies specific to certain points in the stream network including gauging stations. It is also based on the need for an improved delineation of hydrologic features (water bodies) in hydrologic modeling. The research project developed an interface module for TOPAZ [Garbrecht and Martz, 1992] to offset the aforementioned disadvantages of the subwatershed delineation techniques. The research developed an internal hybrid, raster-based, Object Oriented data structure and processing model similar to that of vector data type. The new internal data structure permits further augmentation of the software tool. This internal data structure and algorithms provide an improved framework for discretization of the important hydrologic entities (water bodies) and the capability of extracting homogenous hydrological subwatersheds