Digital Topographic Data Research Articles

Organization of geoinformation monitoring of geospatial data of green plants of the street and road network of the city of Odesa

The purpose of this work is the introduction of a permanent system of real-time observations of green spaces to update geospatial data. Methodology: To achieve this goal, we monitored green spaces with the help of GIS technologies, displaying up-to-date information for each plant and storing the history of changes in each object. This work is divided into two stages. The first stage involves making an inventory of green spaces and compiling an object passport. The second stage involves making real-time changes such as planting, pruning, uprooting a stump, damage due to natural disasters, etc. Thus, there is a database of green plants at any point in time and a chronology of plant care. By incorporating green spaces into the National Spatial Data Infrastructure (NSDI) using consistent methods, we can better understand their impact. Digital topographic data is essential in geoinformation systems for making informed management decisions, creating and maintaining cadastres for various purposes. Scientific novelty and practical significance: The issues of accounting for green spaces in settlements are becoming quite acute in the modern world. Equally important is the issue of maintaining the relevance of the data obtained. The geoportal, "Monitoring of green spaces in the city of Odesa," implements a permanent system of continuous observations to update the geospatial data of green spaces, and tracks changes for each individual tree. This will help in making management decisions regarding urban greening, significantly reduce budget costs for green management in the future, and control the quantity and quality of the work performed.

Interrelation between factors controlling sediment yield in the largest catchment of Peninsular India

The catchment area of the Godavari in Peninsular India shows complex heterogeneous morphologic, climatic, and geological settings. Although the sub-basins of the Godavari indicate a great spatial variation in sediment yield, the role of such morpho-climatic heterogeneity in the sediment yield variation is poorly understood. This study aims to analyze the role of geomorphology, lithology, precipitation, and land use on spatial sediment yield variation in the Godavari basin. Using digital topography data, with the aid of a Geographical Information System (GIS), we delineated 25 sub-basins based on gauging station locations and showed a wide variation of sediment yield, ranging from 28 to 3404 t km−2 yr−1. Several geomorphic attributes were found to be co-dependent; then, we utilized the partial least-square regression (PLSR) technique to recognize the relationship between controlling factors with sediment yield and established a predictive model. Furthermore, we quantitatively determined the most important first-order controlling factors using variable importance for the projection (VIP) method. The results of PLSR and VIP revealed that among 20 geomorphic variables, plan curvature (VIP = 1.61), profile curvature (1.61), LS factor (VIP = 1.51), topographic ruggedness index (VIP = 1.51), slope (VIP = 1.51), topographic wetness index (VIP = 1.29), and steepness index (VIP = 1.06) exert first-order control in sediment yield variation. Moreover, Mesozoic and Precambrian rocks in agricultural, forested, and bare-ground environments collectively play a crucial role under the influence of differential rainfall patterns in the spatial variation of sediment yield as indicated by VIP values higher than 1. Our optimal PLSR model explained 62% of the total variance in average sediment yield with a moderate predictive ability value (Q2 = 0.46). The insights obtained from the results of this study can be utilized for basin-specific erosion and hydrological modeling in a similar environment. Moreover, this study can be helpful to planners and policymakers for better erosion management and soil–water conservation measures in the Godavari basin.

Data Fusion for Satellite-Derived Earth Surface: The 2021 Topographic Map of Etna Volcano

We present a new automatic procedure for updating digital topographic data from multi-source satellite imagery, which consists in the production of Digital Surface Models (DSMs) from high resolution optical satellite images, followed by a context-aware fusion that exploits the complementary characteristics of the multi-source DSMs. The fused DSM minimizes blunders and artifacts due to occlusions (e.g., the presence of clouds, snow or ash plumes) in the source images, resulting in improved accuracy and quality versus those that are not merged. The procedure has been tested to produce the 2021 digital topography of Mt Etna, whose summit area is constantly changing and shows the new peak of 3347 m on the north rim of the South East Crater. We also employ the 2021 DSM to measure the volcanic deposits emplaced in the last five years, finding about 120 million cubic meters, with a yearly average volume of about 24 million cubic meters in agreement with the large eruptive rates registered at Mt Etna since the nineteen seventies. The flexibility and modularity of the presented procedure make it easily exportable to other environmental contexts, allowing for a fast and frequent reconstruction of topographic surfaces even in extreme environments.

Investigation of Forest Fire Characteristics in North Korea Using Remote Sensing Data and GIS

Forest fires cause damage to property and the environment around the world every year. North Korea has suffered from fires every year. Fires may lead to temporary or permanent damage to forest ecosystems, long-term site degradation, and alteration of hydrological regimes, producing detrimental impacts on economies, human health, and safety. In North Korea, fires cause serious damage to the affected mountainous environment. However, it is very difficult to obtain ground information or perform field checks because of the political isolation of North Korea. Thus, there are few studies that have investigated North Korean fires. In this situation, remote sensing techniques and digital topographic data can be used to investigate fire characteristics in North Korea. In this study, fire trends were analyzed using Moderate Resolution Imaging Spectroradiometer (MODIS) data from the Land Processes Distributed Active Archive Center (LPDAAC) from 2004 to 2015, and Landsat data were processed to estimate burned areas in South Hamgyong Province (SHP) and Gangwon Province (GWP) in North Korea. The burn severity of large fires in elevation, slope, and landform features was also analyzed to investigate large fire-burned areas using 30-m-resolution Global Digital Elevation Model (DEM) data from the United States National Aeronautics and Space Administration (NASA). After the results were compared and discussed, the following conclusions were derived. (1) In terms of location, fires in SHP were relatively concentrated along BaekDu-DaeGan (BDDG), while fires in GWP were scattered throughout the province. (2) In terms of size, the large fire-burned areas with an area greater than 1000 ha are significantly more frequent in SHP than in GWP. In brief, large fires occurred more frequently and were more serious in SHP than in GWP. (3) In terms of forest type, coniferous areas were more susceptible to damage from fires and large fires than deciduous areas in both GWP and SHP. This is attributed to the combustible resin within the coniferous trees. Particularly, when a crown fire occurs, it tends to spread rapidly throughout the coniferous forest. (4) Regarding landforms, most large fires occurred along windward-side open slopes, while there were very few fires in shallow valleys, high ridges, or U-shaped valleys. It is believed that cultivation in high-elevation terrain and a lack of fire-extinguishing equipment and systems allow large fires to spread quickly. North Korea is very susceptible to large fire damage and must develop preparation measures against such situations.

The processing workflow of semi-airborne transient electromagnetic data using geological modeling and three-dimensional numerical simulation – A case history in Yunnan, China

To overcome the limitations including the topography in survey area and the complex geometry of the target on conventional transient electromagnetic method (TEM) interpretation, we extend in this paper a workflow for processing semi-airborne TEM data. Based on the digital topography data, geologic sections and well logs, a 3D geologic model was built for numerical simulation. After mapping the geologic model to resistivity mesh, a mimetic finite volume with Krylov subspace method was used for calculating the influence coefficient of topography. This processing workflow was applied on a semi-airborne TEM survey for determining the thickness of cover layer on a hillside in Yunnan, China. The thickness of the cover layer inferred from the processed TEM data is consistent with the local geological sections. This workflow can not only process measured data, but also perform numerical simulation on the target area with complex topography and stratum structure.

Morphotectonic characterization along the eastern portion of the main trace of Magallanes-Fagnano Fault System in Tierra del Fuego, Argentina

The Magallanes-Fagnano Fault System (MFFS) constitutes the onshore segment of the transform boundary between the Scotia and South American plates. The objective of this study is to provide a characterization of the portion of the MFFS, extending from the eastern shore of the Fagnano Lake to the Atlantic coast of Argentina, from a geometric and morphotectonic approach. Detailed morphotectonic analyses of satellite images, plane recognition, digital topographic data, and field surveys allowed us to identify thirteen discrete fault sections. These sections were differentiated according to the morphological characteristics of scarps, natural exposures and other associated morphotectonic features. The main trace fault shows opposite north- and south-facing scarps alternating along strikes being descriptively characterized by their scarps, linear rivers and valleys, drainage anomalies (e.g. diverted, deflected or offset streams), behead meanders, wind gaps, sag ponds, pull-apart basins and linear ridges, among others features. The natural exposures of glacio-fluvial sand and gravel outcrops show Quaternary vertical and strike-slip deformation. It looks unlikely that the Magallanes-Fagnano Fault System (MFFS) could rupture along the entire ∼600 km length during an earthquake. Our results show that even large strike-slip faults may be divided into several discrete fault sections with distinctive morphotectonic features that could help to an increasing understanding of MFFS as a seismogenic source. In this way we suggest different fault sections as a contribution to the recognition of potential individual surface ruptures, which should be tested with further detailed data.

Rethinking the Landscape: Emerging Approaches to Archaeological Remote Sensing

An emerging arena of archaeological research is beginning to deploy remote sensing technologies—including aerial and satellite imagery, digital topographic data, and drone-acquired and terrestrial geophysical data—not only in support of conventional fieldwork but also as an independent means of exploring the archaeological landscape. This article provides a critical review of recent research that relies on an ever-growing arsenal of imagery and instruments to undertake innovative investigations: mapping regional-scale settlement histories, documenting ancient land use practices, revealing the complexity of settled spaces, building nuanced pictures of environmental contexts, and monitoring at-risk cultural heritage. At the same time, the disruptive nature of these technologies is generating complex new challenges and controversies surrounding data access and preservation, approaches to a deluge of information, and issues of ethical remote sensing. As we navigate these challenges, remote sensing technologies nonetheless offer revolutionary ways of interrogating the archaeological record and transformative insights into the human past.

Application of Machine Learning on Google Earth Engine to Produce Landslide Susceptibility Mapping (Case Study: Pacitan)

According to the Indonesian Disaster Management Agency (BNPB), Indonesia’s losses due to landslides were estimated around hundreds of billion rupiah in 2017. Making landslide as one of the catastrophes with the greatest risk of loss and leaving a couple regions prone to landslides in Indonesia, Pacitan region is one of them. Landslide delineation therefore represents a particularly beneficial application of evolving research trend in disaster reduction, especially for the vulnerable region. In the present times of open-access satellite data, cloud computing and machine-learning algorithms is frequently used for disaster prevention monitoring. By employing Google Earth Engine, this study focuses on the susceptibility of landslide occurrence using a random forest machine-learning framework applied to digital topographic data such as elevation, slope and aspect as the independent variables and landslide inventory data obtained from Ministry of Energy and Mineral Resources Republic of Indonesia as the dependent variable. This study data sets composed from 1000 random points in Pacitan region with 70:30 ratio for training and testing sample points. The model produced good result, with overall accuracy values of 0.94, kappa values of 0.79 and 0.80 for AUC value. This model also showed that elevation is the most important variable in the landslide susceptible area. The results of this study can be used to evaluate the potential future impacts of landslide and help to optimize the management of disaster reduction in the region of Pacitan.

Uncertainties in Digital Elevation Models from Global Advanced Land Observing Satellite (ALOS) digital topography data in the Indian subcontinent

The study of the Earth's topographic surface using digital topography is an important component of many problems in the Earth Sciences. The 30-m Shuttle Radar Topography Mission (SRTM) and the Advanced Land Observing Satellite (ALOS) global digital topography datasets have been the most recently available global digital topography datasets. Most users directly download the data/DEMs in their native form assuming a vertical error close to their mission goals. We demonstrate, through the use of 221 dual-frequency static Global Positioning System (GPS) independent ground control points, that the datasets typically have outliers and voids that increase the error by an order of magnitude. Filtering the voids, outliers, and correcting systematic errors significantly improved the vertical accuracy of the datasets. We concluded from our study that the ALOS data generated the most accurate DEM in the Indian subcontinent. This finding needs to be tested and confirmed worldwide for generating the best DEMs.

Controls on Streamflow Densities in Semiarid Rocky Mountain Catchments

Developing accurate stream maps requires both an improved understanding of the drivers of streamflow spatial patterns and field verification. This study examined streamflow locations in three semiarid catchments across an elevation gradient in the Colorado Front Range, USA. The locations of surface flow throughout each channel network were mapped in the field and used to compute active drainage densities. Field surveys of active flow were compared to National Hydrography Dataset High Resolution (NHD HR) flowlines, digital topographic data, and geologic maps. The length of active flow declined with stream discharge in each of the catchments, with the greatest decline in the driest catchment. Of the tributaries that did not dry completely, 60% had stable flow heads and the remaining tributaries had flow heads that moved downstream with drying. The flow heads were initiated at mean contributing areas of 0.1 km2 at the lowest elevation catchment and 0.5 km2 at the highest elevation catchment, leading to active drainage densities that declined with elevation and snow persistence. The field mapped drainage densities were less than half the drainage densities that were represented using NHD HR. Geologic structures influenced the flow locations, with multiple flow heads initiated along faults and some tributaries following either fault lines or lithologic contacts.

A Curvature‐Based Method for Measuring Valley Width Applied to Glacial and Fluvial Landscapes

AbstractValleys produced by glaciers are morphologically distinct from those created by rivers, but these differences are surprisingly difficult to automatically detect using digital topographic data. This contribution tests whether glacial and fluvial valleys can be discriminated using scaling between watershed area and valley width. We present a method for estimating valley width at each point in digital topographic data by determining the cross‐valley scale at which normalized principal curvature is minimized. We assess how well this approach measures valley width in synthetic valleys using artificial valley cross sections with random topographic noise. These width estimates are validated against manual measurements in glacial and fluvial valleys. Finally, we assess the sensitivity of these quantities to the pixel dimension of the input data to determine the detection limits of the method for moderate (20 m) and coarse‐resolution (>30 m) digital elevation models (DEMs). We find that valley widths are underpredicted by a factor of 2.5 to 4; nonetheless, they are well correlated with both synthetically prescribed and empirically measured widths and so can be used as reliable measures of valley width when scaled to account for this underprediction. We find clear distinctions between valley width‐catchment area relationships in glacial and nonglacial valleys, indicating that this methodology might be deployed globally to characterize the distribution and extent of glacial landscapes across Earth. In addition, this technique could be used to determine anomalous downstream width changes related to processes such as valley aggradation.

High-resolution mapping of floodplain topography from space: A case study in the Amazon

Terrain elevation is essential for land management, navigation, and earth science applications. Remote sensing advancements have led to an increase in the availability of a range of digital elevation models with global to quasi-global land coverage. However, the generation of these models in water bodies requires specialized approaches, such as the delimitation of the shorelines (isobaths) of lakes over time. Therefore, the processing costs are high in complex areas with many lakes. Currently, there is no systematic topographic mapping of lakes and channels in large and complex floodplains using remote sensing data. We present here the first high-resolution topographic mapping (30 m) of the non-forested portion of the middle-lower Amazon floodplain using a new method based on in-situ Amazon river water levels and a flood-frequency map derived from the Landsat Global Surface Water Dataset. Validation using locally derived bathymetry showed a root mean square error (RMSE) of 0.89 m for floodplain elevation and a good representation of spatial patterns with Pearson's correlation coefficient of 0.77. Our approach for improving topographic representation in open water areas is an alternative to SRTM3 DEM or MERIT DEM, which represents these areas as a flat surface. We also generated the Amazon River bathymetry using nautical charts from the Brazilian Navy (average RMSE of 7.5 m and bias of 5 m), and floodplain depths maps corresponding to the high- and low-water periods of the river flood wave. The results show that the storage volume in the open-water floodplain varies 104.3 km3 on average each year (from 11.9 km3 in low-water to 116.2 km3 in high-water). The method can be applied to any temporarily flooded area to provide the often missing underwater digital topographic data required for hydrological, ecological, and geomorphological studies. The data set developed in this study can be found at https://doi.org/10.17632/vn599y9szb.1.

Mapping Archaeological Site of Keraton Pleret Using Aerial Photograph

As a cultural heritage, Site of Keraton (Palace) Pleret becomes an essential relic in Javanese history and culture to preserve and deliver ancient information for the next generation sustainably. On the other hand, this preservation is dealing with quite rapid built-up area development. Mapping can be a significant effort as primary data in cultural preservation management. This study aims to make a detailed site map of the Keraton Pleret and identify the existing land use in each site component. Through remote sensing data interpretation and analysis, identification and mapping of archaeological sites done by matching previous archaeological documents, field conditions, digital orthophoto from aerial photography, and digital topographic data (digital surface models, DSM). Site components were identified firstly by matching the existence of the street network and river from a topographic map with orthophoto to obtain site orientation based on artificial infrastructure and existing natural features. It was followed by matching between Keraton Pleret blueprint document, previous archaeological information, and orthophoto to identify and locate each site component. Existing land use information obtained by orthophoto interpretation. Data analysis shows the compatibility between spatial data used in this research and previous documents to identify components and result in Keraton Pleret site map. At present, most of the Keraton Pleret site area has been converted to buildings and paddy fields, strengthen the need for archaeological sites management which alongside community activities.

Developing a Serious Game That Supports the Resolution of Social and Ecological Problems in the Toolset Environment of Cities: Skylines

Game engines are not only capable of creating virtual worlds or providing entertainment, but also of modelling actual geographical space and producing solutions that support the process of social participation. This article presents an authorial concept of using the environment of Cities: Skylines and the C# programming language to automate the process of importing official topographic data into the game engine and developing a prototype of a serious game that supports solving social and ecological problems. The model—developed using digital topographic data, digital terrain models, and CityGML 3D models—enabled the creation of a prototype of a serious game, later endorsed by the residents of the municipality, local authorities, as well as the Ministry of Investment and Economic Development.

The 3D modelling techniques of digital geological mapping

Digital geological mapping has been widely applied in regional geological surveying in China since 2004. Using geological mapping data obtained by the digital geological mapping technique to build 3D geological modelling is the trend of the future. Based on previous research, a new method of constructing 3D geological models of shallow surfaces by using digital geological mapping routes and topographic data is proposed in this paper. The key steps of this modelling method are described systematically in the paper. These steps include data pre-processing, construction of an original database, construction of geological boundaries, and model combination. In particular, we introduce in detail the model construction methodologies of the model boundary surface, digital elevation model (DEM) surface, Quaternary interface, fault plane, overlying residual stratum interface, layered geological interface, rock mass interface, and others. During the geological interface construction, we should follow two principles: (1) use the boundary and occurrence data as the main modelling data, and use the high-precision subsurface interface data as constraint data; (2) construct younger geological bodies first, and then construct older geological bodies. The next step is to compose sectionalised geological interfaces and use them to generate a geological interface of wider range. The interface construction progresses from small to large and is constantly constrained and continuously improved. Based on this new modelling method, we successfully constructed two 3D geological models, the 1:25,000 Xiaosuangou and the 1:50,000 Tuoshang models, and achieved good results. This modelling method has the advantages of simple realisation, high speed, high accuracy, and good applicability. Using this method to build 3D geological models can facilitate further development and utilisation of existing digital geological mapping data. The 3D geological models can be used as a new way of expressing the regional geological survey results, as well as the constraint data of deep 3D geological modelling in the future.

Harmonizing National Topographic Data Using an Automated Quality Validation Process

Harmonizing National Topographic Data Using an Automated Quality Validation Process

The Listafjorden–Drangedal Fault Complex of the Agder–Telemark Lineament Zone, southern Norway. A structural analysis based on remote sensing and potential field data

ABSTRACTThe Listafjord–Drangedal Fault Complex is a central structure in the NE-SW-trending Agder–Telemark Lineament Zone that dominates the structural grain and topography of southernmost tip of Norway. The fault can be followed for a distance of more than 170 km from the shelf area off Listafjorden–Fedafjorden in Vest Agder county to Drangedal in Telemark county. It has been analyzed by the use of digital topographic, remote sensing and potential field data, supported by field investigations. At least seven separate left-stepping fault segments have been identified. These are characterized by numerous internal fault lenses, separate fault strands and fault splays, partly displaying contrasting fault attitude and style of deformation. The northeastern termination of the Listafjord–Drangedal Fault Complex consists of fanning fault branches (horse-tailing), whereas its southwestern termination is buried below sediments in the continental shelf and remains obscure. The fault rocks of the various fault segments include cataclasites and mylonites that in places are interlayered with zones of fault gouge. By tentative correlation to the Hunnedalen dyke system in Rogaland, the age of initiation for the Listafjord–Drangedal Fault Complex is suggested to be Late Proterozoic. Parts of the fault complex were affected by at least two stages of faulting including (dextral?) shear and top-to-the-SE extension. The latter stage is assumed to be of post-Caledonian age, and recent seismic activity suggests that this ancient structural grain is still seismically active.

Supervised classification of landforms in Arctic mountains

AbstractErosional and sediment fluxes from Arctic mountains are lower than for temperate mountain ranges due to the influence of permafrost on geomorphic processes. As permafrost extent declines in Arctic mountains, the spatial distribution of geomorphic processes and rates will change. Improved access to high‐quality remotely sensed topographic data in the Arctic provides an opportunity to develop our understanding of the spatial distribution of Arctic geomorphological processes and landforms. Utilizing newly available Arctic digital topography data, we have developed a method for geomorphic mapping using a pixel‐based linear discriminant analysis method that could be applied across Arctic mountains. We trained our classifier using landforms within the Adventdalen catchment in Svalbard and applied it to two adjacent catchments and one in Alaska. Slope gradient, elevation–relief ratio and landscape roughness distinguish landforms to a first order with >80% accuracy. Our simple classification system has a similar overall accuracy when compared across our field sites. The simplicity and robustness of our classification suggest that it is possible to use it to understand the distribution of Arctic mountain landforms using extant digital topography data and without specialized classifications. Our preliminary assessments of the distribution of geomorphic processes within these catchments demonstrate the importance of post‐glacial hillslope processes in governing sediment movement in Arctic mountains.

SLOPE FAILURE RISK ASSESSMENT MODELING USING TOPOGRAPHIC DATA AND NUMERICAL CALCULATION OF SOIL CONSERVATION BY TREE ROOT SYSTEMS

Abstract. In Japan, the frequency of sudden heavy rain events has recently increased, causing slope failures that in turn increase rates of damage to transit infrastructure such as railways and roads. To reduce this damage, there is a need to identify locations near railroad tracks that are at risk of slope failure. Thus, an assessment that predicts whether or not damage will occur due to external forces such as heavy rains is required, rather than a simple relative risk assessment based on identifying locations similar to those damaged in previous events. In this study, we developed a method for time series stability assessment of slopes during heavy rains using digital topographic data. This method uses topographic data to estimate topsoil thickness, which contributes to stability, and soil strength, which is affected by the root systems of vegetation on slopes. Using differences in these parameters between tree species and forest type, we were able to calculate slope stability and simulate slope failure during rainfall. The simulations allowed us to evaluate locations along routes where previous failures occurred, and to identify at-risk locations that have not yet experienced slope failure. This approach will improve forest management based on risk assessments for intensifying heavy rains.

Short communication: The Topographic Analysis Kit (TAK) for TopoToolbox

Abstract. Quantitative analysis of digital topographic data is an increasingly important part of many studies in the geosciences. Initially, performing these analyses was a niche endeavor, requiring detailed domain knowledge and programming skills, but increasingly broad, flexible, open-source code bases have been developed to increasingly democratize topographic analysis. However, many of these analyses still require specific computing environments and/or moderate levels of knowledge of both the relevant programming language and the correct way to take these fundamental building blocks and conduct an efficient and effective topographic analysis. To partially address this, we have written the Topographic Analysis Kit (TAK), which leverages the power of one of these open code bases, TopoToolbox, to build a series of high-level topographic analysis tools to perform a variety of common topographic analyses. These analyses include the generation of maps of normalized channel steepness, or χ, and selection and statistical analysis of populations of watersheds. No programming skills or advanced mastery of MATLAB is required for effective use of TAK. In addition – to expand the utility of TAK along with the primary functions, which like the underlying TopoToolbox functions require MATLAB and several proprietary toolboxes to run – we provide compiled versions of these functions that use the free MATLAB Runtime Environment for users who do not have institutional access to MATLAB or all of the required toolboxes.