Combining multiple shaded reliefs with hypsometric colouring and digital orthophotos using free and open-source software

In this paper we combined layers created from several terrain rendering techniques, namely a shaded relief rendered in the free and open-source 3D computer graphics software Blender, a hillshade created in the free and opensource Geographic Information System (GIS) software QGIS, a hypsometric coloured Digital Elevation Model (DEM) and a draped digital orthophoto. Following a recent trend in the cartographic community towards using Blender, we tried to improve the standard relief visualization in common GIS software by blending it with a shaded relief rendered in Blender. Using different QGIS blending modes and opacity values we achieved different graphic visualizations. To compare and evaluate the suitability of different rendering techniques we chose national park Risnjak located in Croatia because of its specific and diverse terrain landforms. After comparing different input layers and parameter sets, we selected the blending combination which is best suited for visualizing terrain characteristics of all Croatian national parks. The result is a shaded relief created for every national park which is combined from a shaded relief rendered in Blender, a hillshade created in QGIS, a hypsometric coloured DEM and a draped digital orthophoto.

UPDATING LANDSLIDE INVENTORY MAPS USING HIGH RESOLUTION DIGITAL ORTHOPHOTOS AND DIGITAL SURFACE AND ELEVATION MODELING: THE CASE STUDY OF BRUSQUE CITY, SANTA CATARINA STATE, BRAZIL

This study reports the updating of the landslide inventory map of Brusque city, State of Santa Catarina, Southern Brazil. Twenty-six digital orthophotos acquired in 2010 with a ground resolution of 0.4 meters were analyzed together with shaded relief images obtained by Digital Surface and Digital Elevation modelling with spatial resolution of 1 meter. These remote sensing products were treated, analyzed and visualized in a Geographic Information System – GIS environment. The landslide inventory included a total of 500 landslides, corresponding to a mean density of 1.76 landslides per km2. The total area of landslide occurrences is 0.81 km2, which corresponds to 0.29% of the study area. 0.22 km2 of the total area landslides occur inside the urban perimeter and 0.59 km2 outside Brusque. The geological context and the occurrence of landslides were analyzed together: 277 landslides affect altered metamorphic rocks, 179 landslides granite, and 44 landslides unconsolidated sediments. The updated landslide inventory map showed that 80% of mapped landslides occur in areas of high and moderate susceptibility.

Land Cover Classification Using SegNet with Slope, Aspect, and Multidirectional Shaded Relief Images Derived from Digital Surface Model

Most object detection, recognition, and classification are performed using optical imagery. Images are unable to fully represent the real-world due to the limited range of the visible light spectrum reflected light from the surfaces of the objects. In this regard, physical and geometrical information from other data sources would compensate for the limitation of the optical imagery and bring a synergistic effect for training deep learning (DL) models. In this paper, we propose to classify terrain features using convolutional neural network (CNN) based SegNet model by utilizing 3D geospatial data including infrared (IR) orthoimages, digital surface model (DSM), and derived information. The slope, aspect, and shaded relief images (SRIs) were derived from the DSM and were used as training data for the DL model. The experiments were carried out using the Vaihingen and Potsdam dataset provided by the German Society for Photogrammetry, Remote Sensing and Geoinformation (DGPF) through the International Society for Photogrammetry and Remote Sensing (ISPRS). The dataset includes IR orthoimages, DSM, airborne LiDAR data, and label data. The motivation of utilizing 3D data and derived information for training the DL model is that real-world objects are 3D features. The experimental results demonstrate that the proposed approach of utilizing and integrating various informative feature data could improve the performance of the DL for semantic segmentation. In particular, the accuracy of building classification is higher compared with other natural objects because derived information could provide geometric characteristics. Intersection-of-union (IoU) of the buildings for the test data and the new unseen data with combining all derived data were 84.90% and 52.45%, respectively.

Comparative Analysis of Ellipsoidal Height and Shuttle Radar Topographic Mission Elevation

Ellipsoidal elevation represents a precise geospatial data type within the analysis and modelling of various hydrological and ecological phenomenon required in preserving the human environment. Likewise, Shuttle Radar Topographic Mission (SRTM) has created an unparalleled data set of global elevations that are freely available for modelling ubiquitous environmental applications. This research aims to carry out a comparative analysis of ellipsoidal heights and SRTM heights with the following objectives: downloading DEM’s (SRTM) data covering the study area, determining the spot heights within the boundary in conventional method, extract DEM’S heights within the boundary of the study area, and compared the heights in the conventional method with DEM’S heights. South GPS and Leica Total Station were used to acquire data for control extension and spot heightening respectively while the elevation of SRTM data was obtained by transforming the X and Y data from GPS observationto Longitude and Latitude before using ArcGIS 10.6 to extract the elevation of the boundary pillar and all the spot heights which were relatively compared in terms of its products- heights, contour, 3-D wireframe, 3-D surface model, and overlaid of contour on shaded relief. The results of the study showed that vertical difference using conventional method and SRTM dataset ranges between -2.345m to 11.026m. Also, the hypothesis tested using a two-tail student t-test and F-test revealed that one mean is not significantly different from the other at 95% confidence level. The research recommends that the products obtained for the two systems can be used interchangeably. Keywords: Shuttle radar topographic mission, Ellipsoidal elevation, contour, 3D wireframe, 3D surface model

A Method for Extracting Some Key Terrain Features from Shaded Relief of Digital Terrain Models

Detection of terrain features (ridges, spurs, cliffs, and peaks) is a basic research topic in digital elevation model (DEM) analysis and is essential for learning about factors that influence terrain surfaces, such as geologic structures and geomorphologic processes. Detection of terrain features based on general geomorphometry is challenging and has a high degree of uncertainty, mostly due to a variety of controlling factors on surface evolution in different regions. Currently, there are different computational techniques for obtaining detailed information about terrain features using DEM analysis. One of the most common techniques is numerically identifying or classifying terrain elements where regional topologies of the land surface are constructed by using DEMs or by combining derivatives of DEM. The main drawbacks of these techniques are that they cannot differentiate between ridges, spurs, and cliffs, or result in a high degree of false positives when detecting spur lines. In this paper, we propose a new method for automatically detecting terrain features such as ridges, spurs, cliffs, and peaks, using shaded relief by controlling altitude and azimuth of illumination sources on both smooth and rough surfaces. In our proposed method, we use edge detection filters based on azimuth angle on shaded relief to identify specific terrain features. Results show that the proposed method performs similar to or in some cases better (when detecting spurs than current terrain features detection methods, such as geomorphon, curvature, and probabilistic methods.

DETECTION OF TERRAIN STRUCTURES IN AIRBORNE LASER SCANNING DATA USING DEEP LEARNING

Automated recognition of terrain structures is a major research problem in many application areas. These structures can be investigated in raster products such as Digital Elevation Models (DEMs) generated from Airborne Laser Scanning (ALS) data. Following the success of deep learning and computer vision techniques on color images, researchers have focused on the application of such techniques in their respective fields. One example is detection of structures in DEM data. DEM data can be used to train deep learning models, but recently, Du et al. (2019) proposed a multi-modal deep learning approach (hereafter referred to as MM) proving that combination of geomorphological information help improve the performance of deep learning models. They reported that combining DEM, slope, and RGB-shaded relief gives the best result among other combinations consisting of curvature, flow accumulation, topographic wetness index, and grey-shaded relief. In this work, we approve and build on top of this approach. First, we use MM and show that combinations of other information such as sky view factors, (simple) local relief models, openness, and local dominance improve model performance even further. Secondly, based on the recently proposed HR-Net (Sun et al., 2019), we build a tinier, Multi-Modal High Resolution network called MM-HR, that outperforms MM. MM-HR learns with fewer parameters (4 millions), and gives an accuracy of 84:2 percent on ZISM50m data compared to 79:2 percent accuracy by MM which learns with more parameters (11 millions). On the dataset of archaeological mining structures from Harz, the top accuracy by MM-HR is 91:7 percent compared to 90:2 by MM.

Zoneamento geoambiental do município de Barrocas/BA: contribuições para o ordenamento territorial

Esta pesquisa tem como objetivo realizar o Zoneamento Geoambiental do município de Barrocas/BA, pautado na identificação dos geossistemas e das geofácies presentes no território municipal, buscando analisar a inter-relação dinâmica entre os elementos do meio físico-natural e a intervenção antrópica, como subsidio ao ordenamento territorial. Para se chegar ao objetivo proposto, foi preciso seguir a hierarquização taxonômica e sistêmica proposta por Georges Bertrand, tomando por base a morfologia. Por meio de ferramentas georreferênciadas e modelos de relevo sombreado pôde-se analisar os padrões texturais e a rugosidade do relevo, fazendo a vetorização de polígonos, discriminando as unidades geoambientais in loco. Desse modo, identificou-se em Barrocas dois Geossistemas (Serra do Barandão e Superfície de aplainamento/pedimentada) e seis geofácies (Cimeira estrutural conservada, Cimeira estrutural dissecada, Superfície dissecada em colinas, Serras rebaixadas, Planície aluvial inclinada e uma Superfície de desestruturação artificial). A posteriori, propôs-se um esboço de ordenamento territorial com vista a sustentabilidade ambiental no intuito de subsidiar usos mais sustentáveis para as terras do município em questão. Ressalta-se que o zoneamento, é de grande importância, sendo um poderoso instrumento de informações ao processo de gestão do território, sendo o município o laboratório ideal para sua aplicação, por se tratar de uma escala de planejamento e gestão territorial/ambiental. Mediante a análise da dinâmica da paisagem, constatou-se quão intensa tem se dado a atuação antropogênica no território barroquense, contudo, verificou-se que os sistemas ambientais ainda resistem, observando-se que o tempo está permitindo o processo de regeneração e adaptação dos geossistemas mantendo-os em funcionalidade. Geoenvironmental zoning of the municipality of Barrocas/BA: contributions to land use planningABSTRACTThis research aimed to carry out the Geoenvironmental Zoning of the municipality of Barrocas/BA, based on the identification of geosystems and geofacies present in the municipal territory, seeking to analyze the dynamic interrelationship between the elements of the physical-natural environment and the anthropic intervention, as a subsidy to land use planning.To reach the proposed objective, it was necessary to follow the taxonomic and systemic hierarchy proposed by Georges Bertrand, based on morphology. Through georeferenced tools and shaded relief models, it was possible to analyze the textural patterns and the roughness of the relief, making the vectorization of polygons, discriminating the geoenvironmental units in loco. Thus, two geosystems were identified in Barrocas (Serra do Barandão and Pedimented surface) and six geofacies (Conserved structural summit, Dissected structural summit, Surface dissected in hills, Lowered saws, Colluvium-alluvial ramp and an Artificial disruption surface). A posteriori, an outline of territorial planning was proposed with a view to environmental sustainability in order to subsidize more sustainable uses for the lands of the municipality in question. It is noteworthy that zoning is of great importance, being a powerful information tool for the territory management process, the municipality being the ideal laboratory for its application, as it is a territorial / environmental planning and management scale. Through the analysis of the landscape dynamics, it was verified how intense the anthropogenic performance has been in the Baroque territory, however, it was found that the environmental systems still resist, observing that time is allowing the process of regeneration and adaptation of the geosystems keeping them in functionality.Keywords: Geosystem. Geoenvironmental Zoning. Land use planning