Digital Elevation Models in Geomorphology

This chapter presents place of geomorphometry in contemporary geomorphology. The focus is on discussing digital elevation models (DEMs) that are the primary data source for the analysis. One has described the genesis and definition, main types, data sources and available free global DEMs. Then we focus on landform parameters, starting with primary morphometric parameters, then morphometric indices and at last examples of morphometric tools available in geographic information system (GIS) packages. The last section briefly discusses the landform classification systems which have arisen in recent years

A Common Origin for Ridge-and-Trough Terrain on Icy Satellites by Sluggish Lid Convection

Ridge-and-trough terrain is a common landform on outer Solar System icy satellites. Examples include Ganymede's grooved terrain, Europa's gray bands, Miranda's coronae, and several terrains on Enceladus. The conditions associated with the formation of each of these terrains are similar: heat flows of order tens to a hundred milliwatts per meter squared, and deformation rates of order $10^{-16}$ to $10^{-12}$ s$^{-1}$. Our prior work shows that the conditions associated with the formation of these terrains on Ganymede and the south pole of Enceladus are consistent with vigorous solid-state ice convection in a shell with a weak surface. We show that sluggish lid convection, an intermediate regime between the isoviscous and stagnant lid regimes, can create the heat flow and deformation rates appropriate for ridge and trough formation on a number of satellites, regardless of the ice shell thickness. For convection to deform their surfaces, the ice shells must have yield stresses similar in magnitude to the daily tidal stresses. Tidal and convective stresses deform the surface, and the spatial pattern of tidal cracking controls the locations of ridge-and-trough terrain.Comment: 45 pages, 7 figures; accepted for publication in Physics of the Earth and Planetary Interior

An Assessment of the Representation of Ecosystems in Global Protected Areas Using New Maps of World Climate Regions and World Ecosystems

Representation of ecosystems in protected area networks and conservation strategies is a core principle of global conservation priority setting approaches and a commitment in Aichi Target 11 of the Convention on Biological Diversity. The 2030 Sustainable Development Goals (SDGs) explicitly call for the conservation of terrestrial, freshwater, and marine ecosystems. Accurate ecosystem distribution maps are required to assess representation of ecosystems in protected areas, but standardized, high spatial resolution, and globally comprehensive ecosystem maps have heretofore been lacking. While macroscale global ecoregions maps have been used in global conservation priority setting exercises, they do not identify distinct localized ecosystems at the occurrence (patch) level, and instead describe large ecologically meaningful areas within which additional conservation planning and management are necessary. We describe a new set of maps of globally consistent climate regions and ecosystems at a much finer spatial resolution (250 m) than existing ecological regionalizations. We then describe a global gap analysis of the representation of these ecosystems in protected areas. The new map of terrestrial World Ecosystems was derived from the objective development and integration of 1) global temperature domains, 2) global moisture domains, 3) global landforms, and 4) 2015 global vegetation and land use. These new terrestrial World Ecosystems do not include either freshwater or marine ecosystems, but analog products for the freshwater and marine domains are in development. A total of 431 World Ecosystems were identified, and of these a total of 278 units were natural or semi-natural vegetation/environment combinations, including different kinds of forestlands, shrublands, grasslands, bare areas, and ice/snow regions. The remaining classes were different kinds of croplands and settlements. Of the 278 natural and semi-natural classes, 9 were not represented in global protected areas with a strict biodiversity conservation management objective (IUCN management categories I-IV), and an additional 206 were less than 8.5% protected (half way to the 17% Aichi Target 11 goal). Forty four classes were between 8.5% and 17% protected (more than half way towards the Aichi 17% target), and only 19 classes exceeded the 17% Aichi target. However, when all protected areas (IUCN management categories I-VI plus protected areas with no IUCN designation) were included in a separate global gap analysis, representation of ecosystems increases substantially, with a third of the ecosystems exceeding the 17% Aichi target, and another third between 8.5% and 17%. The overall protection (representation) of global ecosystems in protected areas is considerably less when assessed using only strictly conserved protected areas, and more if all protected areas are included in the analysis. Protected area effectiveness should be included in further evaluations of global ecosystem protection. The ecosystems with the highest representation in protected areas were often bare or sparsely vegetated and found in inhospitable environments (e.g. cold mountains, deserts), and the eight most protected ecosystems were all snow and ice ecosystems. In addition to the global gap analysis of World Ecosystems in protected areas, we report on the representation results for the ecosystems in each biogeographic realm (Neotropical, Nearctic, Afrotropical, Palearctic, Indomalayan, Australasian, and Oceania)

The national ecological network and a land morphology model. An application to Portugal

Doutoramento em Arquitetura Paisagista - Instituto Superior de AgronomiaOne of the most complex issues that modern society is facing is landscape transformation, its fragmentation and ecological simplification, resulting in loss of biodiversity and a decline in ecosystems’ quality. Recently, the concept and establishment of Ecological Networks (EN) have been seen as a solution towards nature conservation strategies targeting biodiversity and ecological connectivity, (re)focusing on the ecosystem approach and the “continuum naturale”. The research in this dissertation aims to clarify the potential of EN in the context of landscape planning and its importance and function within the Green Infrastructure (GI) concept, emerging from EU Biodiversity Strategy to 2020, as a fundamental strategically connected infrastructure of abiotic and biotic systems underlying the provision of multiple functions valuable to society. It also addresses the lack of mapping at the national level of ecological systems. The main research objectives are: 1) To develop a methodology to map the National Ecological Network (NEN) for mainland Portugal and 2) To develop a Land Morphology (LM) mapping method at the national level. LM classifies landforms according to their hydrological position in the watershed and represents a helpful evaluation tool for modelling natural systems. This thesis contributes to the understanding of: i) the NEN as a spatial network that defines areas of existing and potential ecological connectivity at various scales which provides the physical and biological conditions necessary to maintain or restore landscape’ ecological functions; ii) the importance of NEN as an ecologically based tool towards a more sustainable landscape planning, strengthening the notions of connectivity and multi-functionality of landscape; iii) the morphological approach to map Portuguese landforms as valuable tool to assist policy makers and planners in taking decisions based on a more thorough analysis of land value and its ecological functions; and iv) Mapping the wet system at national level may have an impact on clarifying concepts related to water resources and can be used as a preliminary delimitation of floodplains and potential flood risk areasN/

Classification and use of landform information to increase the accuracy of land condition monitoring in Western Australian pastoral rangelands

The aim of this research was to develop land unit scale data to assist land condition monitoring projects in pastoral rangelands in Western Australia. Landforms are a major components of land units and methods were explored to include landforms as a variable in land unit predictive modelling. Three land unit prediction models were tested, a Binary Weighted Overlay (BWO), a Fuzzy Weighted Overlay (FWO) and a Positive Weights of Evidence (PWofE) model

Uncertainties in Digital Elevation Models: Evaluation and Effects on Landform and Soil Type Classification

Digital elevation models (DEMs) are a widely used source for the digital representation of the Earth's surface in a wide range of scientific, industrial and military applications. Since many processes on Earth are influenced by the shape of the relief, a variety of different applications rely on accurate information about the topography. For instance, DEMs are used for the prediction of geohazards, climate modelling, or planning-relevant issues, such as the identification of suitable locations for renewable energies. Nowadays, DEMs can be acquired with a high geometric resolution and over large areas using various remote sensing techniques, such as photogrammetry, RADAR, or laser scanning (LiDAR). However, they are subject to uncertainties and may contain erroneous representations of the terrain. The quality and accuracy of the topographic representation in the DEM is crucial, as the use of an inaccurate dataset can negatively affect further results, such as the underestimation of landslide hazards due to a too flat representation of relief in the elevation model. Therefore, it is important for users to gain more knowledge about the accuracy of a terrain model to better assess the negative consequences of DEM uncertainties on further analysis results of a certain research application. A proper assessment of whether the purchase or acquisition of a highly accurate DEM is necessary or the use of an already existing and freely available DEM is sufficient to achieve accurate results is of great qualitative and economic importance. In this context, the first part of this thesis focuses on extending knowledge about the behaviour and presence of uncertainties in DEMs concerning terrain and land cover. Thus, the first two studies of this dissertation provide a comprehensive vertical accuracy analysis of twelve DEMs acquired from space with spatial resolutions ranging from 5 m to 90 m. The accuracy of these DEMs was investigated in two different regions of the world that are substantially different in terms of relief and land cover. The first study was conducted in the hyperarid Chilean Atacama Desert in northern Chile, with very sparse land cover and high elevation differences. The second case study was conducted in a mid-latitude region, the Rur catchment in the western part of Germany. This area has a predominantly flat to hilly terrain with relatively diverse and dense vegetation and land cover. The DEMs in both studies were evaluated with particular attention to the influence of relief and land cover on vertical accuracy. The change of error due to changing slope and land cover was quantified to determine an average loss of accuracy as a function of slope for each DEM. Additionally, these values were used to derive relief-adjusted error values for different land cover classes. The second part of this dissertation addresses the consequences that different spatial resolutions and accuracies in DEMs have on specific applications. These implications were examined in two exemplary case studies. In a geomorphometric case study, several DEMs were used to classify landforms by different approaches. The results were subsequently compared and the accuracy of the classification results with different DEMs was analysed. The second case study is settled within the field of digital soil mapping. Various soil types were predicted with machine learning algorithms (random forest and artificial neural networks) using numerous relief parameters derived from DEMs of different spatial resolutions. Subsequently, the influence of high and low resolution DEMs with the respectively derived land surface parameters on the prediction results was evaluated. The results on the vertical accuracy show that uncertainties in DEMs can have diverse reasons. Besides the spatial resolution, the acquisition technique and the degree of improvements made to the dataset significantly impact the occurrence of errors in a DEM. Furthermore, the relief and physical objects on the surface play a major role for uncertainties in DEMs. Overall, the results in steeper areas show that the loss of vertical accuracy is two to three times higher for a 90 m DEM than for DEMs of higher spatial resolutions. While very high resolution DEMs of 12 m spatial resolution or higher only lose about 1 m accuracy per 10° increase in slope steepness, 30 m DEMs lose about 2 m on average, and 90 m DEMs lose more than 3 m up to 6 m accuracy. However, the results also show significant differences for DEMs of identical spatial resolution depending on relief and land cover. With regard to different land cover classes, it can be stated that mid-latitude forested and water areas cause uncertainties in DEMs of about 6 m on average. Other tested land cover classes produced minor errors of about 1 – 2 m on average. The results of the second part of this contribution prove that a careful selection of an appropriate DEM is more crucial for certain applications than for others. The choice of different DEMs greatly impacted the landform classification results. Results from medium resolution DEMs (30 m) achieved up to 30 % lower overall accuracies than results from high resolution DEMs with a spatial resolution of 5 m. In contrast to the landform classification results, the predicted soil types in the second case study showed only minor accuracy differences of less than 2 % between the usage of a spatial high resolution DEM (15 m) and a low resolution 90 m DEM. Finally, the results of these two case studies were compared and discussed with other results from the literature in other application areas. A summary and assessment of the current state of knowledge about the impact of a particular chosen terrain model on the results of different applications was made. In summary, the vertical accuracy measures obtained for each DEM are a first attempt to determine individual error values for each DEM that can be interpreted independently of relief and land cover and can be better applied to other regions. This may help users in the future to better estimate the accuracy of a tested DEM in a particular landscape. The consequences of elevation model selection on further results are highly dependent on the topic of the study and the study area's level of detail. The current state of knowledge on the impact of uncertainties in DEMs on various applications could be established. However, the results of this work can be seen as a first step and more work is needed in the future to extend the knowledge of the effects of DEM uncertainties on further topics that have not been investigated to date

Spatial analysis of topography for glacier mapping in the Western Himalaya

Understanding climate change requires accurate assessment of the Earths cryosphere, as glacier fluctuations directly and indirectly reflect changes in radiative forcing and temperature and precipitation patterns. Direct assessment of alpine glaciers in high-mountains is notoriously difficult, and assessment from space represents the only practical alternative for assessing regional and global ice-fluctuation patterns. The mapping of debris-covered glaciers is especially problematic, as glacier surfaces exhibit spectral reflectance patterns similar to surrounding rock and sediment. Therefore, multispectral analysis of satellite imagery does not permit accurate delineation. Consequently, the use of satellite-derived topographic information and spatial analysis were evaluated for mapping the Raikot and Sachen Glaciers at Nanga Parbat mountain in the Pakistan Himalaya. Geomorphometric analyses were used to generate first- and secondorder topographic parameters. These were utilized to generate homogeneous elemental-form objects, which were evaluated for glacier mapping. Topo-sequence information was also examined and represents the slope-angle altitude function within slope facet objects. The results indicate that it is difficult to characterize the hierarchical topographic organization of glaciers using topographic parameters and elemental form objects. Even though only one level of the topographic hierarchy was attempted, elemental form objects appear to be more useful than topographic parameters, as they represent a combination of topographic information. In addition, elemental-form objects can be used to identify and map selected glacial features without further aggregation to another level in the hierarchy. Toposequence information was found to be of value in differentiating glacier versus non-glacier surfaces. Collectively these results indicate that spatial analysis of the topography can be used for glacier mapping, although accurate digital elevation models are required, along with more sophisticated approaches for quantitatively characterizing the topography. It is suggested that specific topographic primitives and glacier landforms be individually characterized and integrated into a landscape topographic hierarchy in order to accurately characterize and map debris-covered glaciers. Finally, special attention to the concept of scale must be formally accounted for in analysis procedures

Visualization of Uncertain Boundaries of Undersea Features

There have been several studies that detect, measure, analyze, and visualize the undersea features by using technologies in multiple disciplines including geography and oceanography. However, definitions of the undersea features often vary among the existing leading literature. Due to this reason the geographical boundary for a certain undersea feature is sometimes not identical among the definitions. In this study, we explore semantic uncertainty in the definitions of some undersea features and apply approaches from fuzzy-set theory and geographic information science on empirical bathymetric data to visualize the uncertain boundaries of the undersea features. Results from this study demonstrate that the representation based on the fuzzy-set approach can be useful for dealing with the semantic uncertainty of the undersea features

The usefulness of unsupervised classification methods for landscape typification: The case of Slovenia

Supervised and unsupervised classification methods can be a useful tool in determining various geographical spatial divisions, especially regionalizations and typifications. Because Slovenia is geographically very diverse, its divisions are a particularly significant and interesting research challenge. The main objective of this article is to determine the effectiveness of unsupervised classification methods, and therefore we compare the well-established landscape typology of Slovenia from 1996 with landscape typologies that were modeled using various unsupervised classification methods. Our results show that landscape typologies modeled using unsupervised classification methods deviate more from the original landscape typology of Slovenia than landscape typologies modeled using random and expert-supervised classification methods