Terrain Mapping Research Articles

Mapping carbonate-hosted Pb-Zn mineralization zones in Yahyali Province (Eastern Taurus - Turkey) using ASTER data

The first record of the carbonate-hosted Pb-Zn deposits in Turkey dates back to the Roman period. The carbonate-hosted Pb-Zn deposits in Turkey are economically important and found in the Aladağlar - Zamantı Province. Mineral exploration and geological mapping through the utilization of the traditional geological method still remain very challenging in many high terrains (High mountains). In this study, Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) remote sensing data were used for mapping the carbonate-hosted Pb-Zn deposits in the Yahyali region of Turkey. The Band Ratio (BR), Least square fitting methοd (Ls–fit), Band Ratio Color Composite (BRCC), and Principal Cοmpοnent Analysis (PCA) were used tο map the Pb-Zn mineralization zone. The results of this investigation show the spatial distribution of Fe-Mg – OH/CO3, hydroxyl-bearing and iron oxide minerals. Field work and laboratory analysis were carried out to verify the occurrence of alteration zones and highly prospective locations and to confirm the availability of alteration and potential zones of carbonate-hosted Pb-Zn mineralization in the study area. Spatial correlation and distribution were observed between the previous geological map, active and abandoned mines, and the result obtained from the remote sensing data. Different techniques applied to the Aster data image in this study are recommended fοr carbonate-hosted Pb-Zn and lithological mapping in hostile terrains.

Map Making in Social Indoor Environment Through Robot Navigation Using Active SLAM

Robotics has come a long way from industrial robotic arms and is all set to enter our homes. The capability of a robot to navigate in an unknown human populated environment with obstacles and making map simultaneously is one of the significant characteristics in the domain of autonomous robotics. Further, the problem of robot navigating in a social environment while ensuring human safety and comfort through social norms needs to be addressed. This article presents a solution for mapping of unknown terrains with dynamic obstacles using simultaneous localization in social environments through Adaptive Squashing Function based artificial neural network training, which is able to track the target orientation angles more efficiently as compared to conventional fixed slope squashing function based backpropagation training algorithm. The performance of different state of the art techniques have been compared with proposed work through simulation models. Simulation results demonstrated the effectiveness of the proposed algorithm in complex environment where the proposed algorithm converged in less than 50% of the iterations taken by the exhaustive search algorithms and approximately 33% of the iterations taken by random search algorithm. Further, the proposed approach was tested in the real world settings, wherein the robot was deployed to create map for the Kalpana Chawla Center for Research in Space Science and Technology, Chandigarh University with mobile humans.

Online Path Planning Framework for UAV in Rural Areas

A motion strategy plays an important role in supporting autonomous Unmanned Aerial Vehicle (UAV) movement. Many studies have been conducted to improve the motion frameworks in terms of its robustness, safety and performance. Most of them worked on the prior known maps scenario where the area information was collected by Global Positioning System (GPS) and satellite cameras. Even though the scheme can provide high quality map, the computation of motion planning remains dependent on the communication signal. In the rural areas such as forests and mountains, where communication signal does not perform well, unclear and noisy terrain maps can be generated and lead to mission failure. Therefore, it is significant that an alternative framework to enhance autonomous UAV motion performance in these certain conditions should be developed. Our work focuses on developing a high performance path planner for autonomous UAV motion when communication signal does not work well in rural areas. The search mission problem in forest terrain has been implemented in 3D simulation as an evaluation. By conducting a simulation process repeatedly with different test cases for positions, time constraints, flight speed (3-11 m/s) and flight range, our path planning framework can achieve completeness between 90-100% and better performance compared to others.

Phase Unwrapping of Coarsely Sampled Maps Using Higher-Order Methods

We consider the problem of 2-D phase unwrapping that of reconstructing the absolute phase (up to a constant) given a noisy <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$2\pi $ </tex-math></inline-formula> -wrapped phase map as input. In particular, we present an algorithm that excels at unwrapping low-resolution phase maps, that is, maps obtained by coarsely sampling a field of view. Our key observation is that the magnitudes of higher-order differences on phase maps are typically much lower than corresponding first-order differences. We develop this insight into formulating “higher-order Itoh conditions.” Using this, we build an optimization-based framework that leverages higher-order information to estimate the first-order derivatives of the unwrapped phase with the aid of appropriate total variation and irrotationality-based regularizers. The first-order derivatives are then integrated using a minimum spanning tree (MST) approach to produce the unwrapped phase map. We compare the performance on synthetic terrain maps and real-world data obtained from interferometric synthetic aperture radar (InSAR) with other contemporary algorithms to demonstrate superior performance on key metrics such as absolute error, Feature SIMilarity (FSIM), and image sharpness for low-resolution phase maps.

Topographic SLAM Using a Single Terrain Altimeter in GNSS-Restricted Environment

In a Global Navigation Satellite System (GNSS)-restricted area, a mobile robot navigation system exploits surrounding environment information. For an aerial or underwater vehicle, undulating terrain of a land or seabed surface is a valuable information resource that leads to the development of terrain-referenced navigation (TRN) algorithms. However, due to the vast amount of a vehicle’s activity area, surveying all the regions to obtain a high-resolution terrain map is impractical and requires simultaneous localization and mapping (SLAM) as a highly desirable capability. This paper presents a topographic SLAM algorithm using only a single terrain altimeter, which is low-cost, computationally efficient, and sufficiently stable for long-term operation. The proposed rectangular panel map structure and update method enable robust and efficient SLAM. As terrain elevation changes are inherently nonlinear, an extended Kalman filter (EKF)-based SLAM filter is adopted. The feasibility and validity of the proposed algorithm are demonstrated through simulations using terrain elevation data from a real-world undersea environment.

INFORMATION TECHNOLOGIES OF COMPLEX ENVIRONMENTAL MONITORING BASED ON AEROSPACE AND GROUND RESEARCH DATA

The article considers the possibilities of using geoinformation systems and remote land sensing systems in detecting the development of degradation processes of the soil cover. The use of satellite technologies for the detection of soil degradation and timely response to these processes requires timely information and the availability of a database. The environmental safety system is aimed at forecasting and preventing emergency situations of technogenic and ecological nature. It includes the development of forecasting models and algorithms, as well as the allocation of resources to take immediate action in the event of such situations, as well as information about potential hazards, risks and possible consequences. With the use of geodetic surveying and computer processing of the surveying results, the coordinates of land plot plans were obtained. Satellite images were used to obtain data on changes in soil cover over a large area and on a large scale. Aerial photographs reveal small changes in soil structure, indicating signs of erosion or other degradation processes. Digital electronic terrain maps provide geographic information about an area, including geological and geomorphological features. They are used to combine other data, such as satellite images or aerial photographs, and create a comprehensive picture of the state of the soil. In the course of research, the system of ecological monitoring of soil cover using the method of infrared spectrophotometry was improved. The method of physico-chemical analysis of soil samples is substantiated and the dependence between the state of soil contamination by individual chemical elements and their genesis is established. The creation of a computer database and the use of space images in combination with other geo-information technologies really allows for effective monitoring and analysis of soil degradation and other agricultural objects.

Geological Terrain Mapping using Geographic Information System (GIS) and Drone Photogrammetry

The research area was conducted within the Bukit Persekutuan, Kuala Lumpur, and it was located at the latitude 3° 8'32.93"N and longitude 101°40'32.80"E. The researcher carried out geological terrain mapping to evaluate the research area in accordance with the geological terrain classification attributes of each thematic map produced, namely, Terrain map, slope gradient map, erosion, and instability map, as well as construction suitability map. The occurrence of landslide events within the research area becomes a major contributing factor to thoroughly conducting an investigation by field mapping and analysing using the Geographic Information System (GIS) technology. The application of Geographic Information System (GIS) and drone photogrammetry images play an essential role to analyze and process the data, thus, generate the thematic maps. The research area indicates that about 79.11% of the overall area was not appreciable with erosion, 8.58% contribute to the erosion, 11.00% of recent general instability, and 2.97% represent a landslide event. The suitability for development mapping illustrated Class I (23.40), Class II (36.37%), Class III (26.39%), and Class IV (15.50%) where it can be referred to the construction suitability classification system, the suitability for development was high in class I, moderate in class II, low in class III and not suitable in class IV.

Prediction and Validation of Landing Stability of a Lunar Lander by a Classification Map Based on Touchdown Landing Dynamics’ Simulation Considering Soft Ground

In this paper, a method for predicting the landing stability of a lunar lander by a classification map of the landing stability is proposed, considering the soft soil characteristics and the slope angle of the lunar surface. First, the landing stability condition in terms of the safe (=stable), sliding (=unstable), and tip-over (=statically unstable) possibilities was checked by dropping a lunar lander onto flat lunar surfaces through finite-element (FE) simulation according to the slope angle, friction coefficient, and soft/rigid ground, while the vertical touchdown velocity was maintained at 3 m/s. All of the simulation results were classified by a classification map with the aid of logistic regression, a machine-learning classification algorithm. Finally, the landing stability status was efficiently predicted by Monte Carlo (MC) simulation by just referring to the classification map for 10,000 input datasets, consisting of the friction coefficient, slope angles, and rigid/soft ground. To demonstrate the performance, two virtual lunar surfaces were employed based on a 3D terrain map of the LRO mission. Then, the landing stability was validated through landing simulation of an FE model of a lunar lander requiring high computation cost. The prediction results showed excellent agreement with those of landing simulations with a negligible computational cost of around a few seconds.

Visual SLAM-Based Robotic Mapping Method for Planetary Construction.

With the recent discovery of water-ice and lava tubes on the Moon and Mars along with the development of in-situ resource utilization (ISRU) technology, the recent planetary exploration has focused on rover (or lander)-based surface missions toward the base construction for long-term human exploration and habitation. However, a 3D terrain map, mostly based on orbiters’ terrain images, has insufficient resolutions for construction purposes. In this regard, this paper introduces the visual simultaneous localization and mapping (SLAM)-based robotic mapping method employing a stereo camera system on a rover. In the method, S-PTAM is utilized as a base framework, with which the disparity map from the self-supervised deep learning is combined to enhance the mapping capabilities under homogeneous and unstructured environments of planetary terrains. The overall performance of the proposed method was evaluated in the emulated planetary terrain and validated with potential results.

Accurate hyperspectral imaging of mineralised outcrops: An example from lithium-bearing pegmatites at Uis, Namibia

Efficient, socially acceptable and rapid methods of exploration are required to discover new deposits and enable the green energy transition. Sustainable exploration requires a combination of innovative thinking and new technologies. Hyperspectral imaging (HSI) is a rapidly developing technology and allows for fast and systematic mineral mapping, facilitating exploration of the Earth's surface at various scales on a variety of platforms. Newly available sensors allow data capture over a wide spectral range, and provide information about the abundance and spatial location of ore and pathfinder minerals in drill-core, hand samples and outcrops with mm to cm precision. Conversely, the complex geometries of the imaged surfaces affect the spectral quality and signal-to-noise ratio (SnR) of HSI data at these very narrow spatial samplings. Additionally, the complex mineral assemblages found in hydrothermally altered ore deposits can make interpretation of spectral results a challenge. In this contribution, we propose an innovative approach that integrates multiple sensors and scales of data acquisition to help disentangle complex mineralogy associated with lithium and tin mineralisation in the Uis pegmatite complex, Namibia. We train this method using hand samples and finally produce a three-dimensional (3D) point cloud for mapping lithium mineralisation in the open pit. We were able to identify and map lithium-bearing cookeite and montebrasite at outcrop scale. The accuracy of the approach was validated by drill-core data, XRD analysis and LIBS measurements. This approach facilitates efficient mapping of complex terrains, as well as important monitoring and optimisation of ore extraction. Our method can easily be adapted to other minerals relevant to the mining industry.

Micro-Topography Mapping through Terrestrial LiDAR in Densely Vegetated Coastal Environments

Terrestrial Light Detection And Ranging (LiDAR), also referred to as terrestrial laser scanning (TLS), has gained increasing popularity in terms of providing highly detailed micro-topography with millimetric measurement precision and accuracy. However, accurately depicting terrain under dense vegetation remains a challenge due to the blocking of signal and the lack of nearby ground. Without dependence on historical data, this research proposes a novel and rapid solution to map densely vegetated coastal environments by integrating terrestrial LiDAR with GPS surveys. To verify and improve the application of terrestrial LiDAR in coastal dense-vegetation areas, we set up eleven scans of terrestrial LiDAR in October 2015 along a sand berm with vegetation planted in Plaquemines Parish of Louisiana. At the same time, 2634 GPS points were collected for the accuracy assessment of terrain mapping and terrain correction. Object-oriented classification was applied to classify the whole berm into tall vegetation, low vegetation and bare ground, with an overall accuracy of 92.7% and a kappa value of 0.89. Based on the classification results, terrain correction was conducted for the tall-vegetation and low-vegetation areas, respectively. An adaptive correction factor was applied to the tall-vegetation area, and the 95th percentile error was calculated as the correction factor from the surface model instead of the terrain model for the low-vegetation area. The terrain correction method successfully reduced the mean error from 0.407 m to −0.068 m (RMSE errors from 0.425 m to 0.146 m) in low vegetation and from 0.993 m to −0.098 m (RMSE from 1.070 m to 0.144 m) in tall vegetation.

Strain/Stress Evaluation of Dorsa Geikie using Chandrayaan-2 Terrain Mapping Camera-2 and Other Data

The high-resolution panchromatic stereo camera Terrain Mapping Camera-2 (TMC-2) on-board the Indian Chandrayaan-2 mission sends images of the lunar surface at 5m resolution with a low to high sun-angle from an altitude of 100km. These images help identify subtle topographic variations and enable mapping of low-elevation landforms, one of which is a prominent ~220km long wrinkle ridge called the Dorsa Geikie (DG) lying within Mare Fecunditatis. The favourable resolutionof TMC-2 images and the digital elevation models provide opportunities for a detailed structural study of the DG and to reveal crustal shortening, cumulative contractional strain andpalaeostress regime responsible for thrust faulting for the first time.The time of deformation and formation of dorsa is also estimated for a holistic spatio-temporal understanding of deformation. This study presents initial analysis of the data received from TMC-2, and the accuracy of the results are likely to improve as the ingredients get amended and evolved in future

Assessing Repeatability and Reproducibility of Structure-from-Motion Photogrammetry for 3D Terrain Mapping of Riverbeds

Structure-from-Motion (SfM) photogrammetry is increasingly employed in geomorphological applications for change detection, but repeatability and reproducibility of this methodology are still insufficiently documented. This work aims to evaluate the influence of different survey acquisition and processing conditions, including the camera used for image collection, the number of Ground Control Points (GCPs) employed during Bundle Adjustment, GCP coordinate precision and Unmanned Aerial Vehicle flight mode. The investigation was carried out over three fluvial study areas characterized by distinct morphology, performing multiple flights consecutively and assessing possible differences among the resulting 3D models. We evaluated both residuals on check points and discrepancies between dense point clouds. Analyzing these metrics, we noticed high repeatability (Root Mean Square of signed cloud-to-cloud distances less than 2.1 cm) for surveys carried out under the same conditions. By varying the camera used, instead, contrasting results were obtained that appear to depend on the study site characteristics. In particular, lower reproducibility was highlighted for the surveys involving an area characterized by flat topography and homogeneous texturing. Moreover, this study confirms the importance of the number of GCPs entering in the processing workflow, with different impact depending on the camera used for the survey.

Evaluation of Street Lighting Efficiency Using a Mobile Measurement System

The issue concerns the initial stage of work on a method for performing a rapid assessment of the energy efficiency and illuminance of a street lighting installation. The proposed method is based on simultaneous measurement of illuminance from three lux meters placed on the roof of the vehicle. The data are acquired in road traffic, while the vehicle is driving. The proposed solution will allow in the future to quickly and reproducibly obtain data about the lighting parameters of the studied road section. The illumination values are localised using Global Navigation Satellite System (GNSS). Based on the collected measurement data, with the use of terrain maps, geographic information system (GIS) data and installation design documentation, it will be possible to determine in detail the parameters of energy efficiency indicators for a selected section of the street for the entire street according to the EN13201-5 standard. Preliminary tests were conducted on a section of about one kilometer of street illuminated in class C3. Detailed measurements reveal high variation of obtained energy indicators DP and DE for each road section. The reason for this condition is the variation of power, installation geometry and the presence of obstacles to light.

Digital multi-agent system for simulating natural fire fighting processes

A system for modeling and supporting decision-making on the use of forces and means to eliminate wildfires, based on a digital model, implemented in the software “Taiga-Analyst”, is proposed. The system works on the basis of agent-based simulation and allows you to select forces and means to fight a fire, simulate its propagation and elimination with reference to a digital terrain map using a geographic information system. The possibilities and scope of the “Taiga-Analyst” system are described. A decision-making scheme for fighting natural fires is shown, and the use of the system in the process of training fire safety specialists is described.

Addressing potential drought resiliency through high-resolution terrain and depression mapping

Increasing occurrences of droughts across Europe and elsewhere require landscape-wide water-retention assessments to evaluate water-supply sustainabilities for local and regional use. This article reports on the results of a study designed to digitally delineate, connect and categorize recurring depression wetness across a rurally cultured morainal landscape, at 1 m resolution. To do this, a digital terrain model (DTM, 1 m resolution) was used to locate and characterize each terrain-detectable depression by type, depth, area, and volume, together with their flow-channel connections and upslope flow-accumulation areas. In addition, historical 2008–2017 Google Earth images and a local daily weather report were used to index and verify weather- and season-induced changes in depression wetness based on ground coloration, vegetation coverage, and image date. Developing and applying these procedures by way of a case study revealed (i) that about 90% of the image-indexed depression wetness variations could mostly be attributed to DTM-determined depression type, area and depth, and (ii) that image-recognized wetness variations were consistent with weather-modelled soil moisture projections. The results so obtained can be used to quantify potential drought resiliency in terms water retention volumes per depression. Since the procedures as described have a broad application potential, they can be used globally for drought resiliency evaluations and agricultural water management.

GIS ANALYSIS OF DEM IN THE INTERESTS OF SPECIALIZED MAPPING OF MINING TERRAIN

Using the example of the Korshunovsky GOK quarry, the possibilities of processing publicly available SRTM C-SIR and ASTER GDEM DEM data and remote sensing materials obtained from LANDSAT and SENTINEL satellites in the SAGA GIS for specialized mapping of mountainous terrain are considered. The results of constructing derived geomorphometric maps based on DEM are presented. Restrictions on the use of the materials under consideration are justified.

Evaluating the VNIR-SWIR datasets of WorldView-3 for lithological mapping of a metamorphic-igneous terrain using support vector machine algorithm; a case study of Central Iran

• Evaluating the WV-3 data in lithological mapping of an area through confusion matrix. • Successfully discrimination of lithological units and boundaries with high accuracy. • Verifying the produced map by field observations, petrography, and spectroscopy. • Defining effect of each band of WV-3 in classification accuracy of individual class. • Finding SWIR-7 as the most significant band in raising the classification accuracy. WorldView-3 (WV-3) is the first high spatial resolution and super-spectral commercial satellite which has the capability in improvement of geological mapping. The VNIR-SWIR data of this satellite are evaluated in this study for mapping the lithological units of a metamorphic-igneous terrain in Chadormalu area, Central Iran, by the use of support vector machine (SVM) classification method. Applying principal component analysis (PCA) as an image transformation technique on the WV-3 data, and interpretation of its results, supported by field observations, petrography, and spectroscopy, lead to identifying training areas which are input to the SVM algorithm. This method not only produces a detailed lithological map of all exposed rock units, but also well discriminates diorite-gabbro diorite from granite, and gneissic granite from green schist and garnet mica schist, which are not revealed in 1:100,000 geological map of the area, published by Geological Survey of Iran (GSI), with overall accuracy of 88.36% and the Kappa coefficient of 0.86. Furthermore, the efficacy of each applied band of WV-3 is assessed in promoting classification accuracy using SVM method. Results show that band 7 of SWIR region has increased the overall accuracy 4.81% relative to SWIR dataset, and improves the classification accuracy of green schist and diorite. Moreover, bands 5, 6, and 8 of SWIR dataset are more efficient in improvement of the overall accuracies than other bands. This study concludes that WV-3 data provides a good facility to generate large scale geological maps owing to its high spatial and radiometric resolution and appropriate SWIR bands.

UAV navigation using opto-electronic and inertial means in GNSS-denied environment

The article presents an approach to improving navigation solution of unmanned aerial vehicle in GNSS-denied environment by means of optoelectronic and inertial measurements. An approach is based on locating and tracking keypoints on the underlying surface to correct inertial system errors. The approach is based on EKF-SLAM and can be applied both in the presence and in the absence of a terrain map. The simulation results of the optical-inertial navigation system readings are presented.

ON ONE APPROACH TO SOLVING THE TRAVELING SALESMAN PROBLEM FOR AUTONOMOUS UNMANNED AERIAL VEHICLE PLANNING OF TARGET FLIGHT PATHS

Objective. Develop a principle of constructing tools and procedures for optimal routing of targets by an autonomous uncrewed aerial vehicle, which have an acceptable complexity for implementation on an onboard computer. Methods . The rules for optimizing the terrain map with the located targets, creating a penalty matrix that considers the disturbing factors of the unstable air environment in the planning process, and building a reference tree for finding the minimum route for the accepted cost of flying around the targets. Results . A principle is proposed to develop effective procedures for planning minimum cost-effective routes to fly around targets in an unstable air environment. The basis for behavior planning is the optimization of the formal description of a given terrain map, which leads to a significant reduction in the number of alternatives compared in the process of searching for a minimum route to fly around targets. This, in turn, makes it possible to implement planning procedures on the onboard computer system of an autonomous uncrewed aerial vehicle. A statement is proved to justify the existence of a minimum route for the accepted cost of overflying targets in the formal description of the terrain map obtained as a result of converting its original representation based on the developed optimization rules. Conclusion . The considered approach effectively solves various types of issues reduced to the traveling salesman problem, including planning the minimum route of flying around targets by an autonomous uncrewed aerial vehicle in an unstable air environment under uncertainty conditions.