Real-time Terrain Mapping

We present an interactive, real-time mapping system for digital elevation maps (DEMs), which allows Earth scientists to map and therefore understand the deformation of the continental crust at length scales of 10m to 1000km. Our system visualizes the surface of the Earth as a 3D~surface generated from a DEM, with a color texture generated from a registered multispectral image and vector-based mapping elements draped over it. We use a quadtree-based multiresolution method to be able to render high-resolution terrain mapping data sets of large spatial regions in real time. The main strength of our system is the combination of interactive rendering and interactive mapping directly onto the 3D~surface, with the ability to navigate the terrain and to change viewpoints arbitrarily during mapping. User studies and comparisons with commercially available mapping software show that our system improves mapping accuracy and efficiency, and also enables qualitatively different observations that are not possible to make with existing systems

Real Time Lidar Terrain Mapping and Analysis

Mapping terrain is difficult. Capturing river morphology or the shape of faults, cliffs or landslides can require a lot of time and manpower. An Unmanned Aerial Vehicle (UAV) equipped with a lidar sensor can examine entire landscapes at a time, capturing a detailed 3D view of nearly any geologic structure with very little error. Existing approaches allow for a UAV to follow a flight plan and capture data for later analysis. During analysis, though, the user will often find that the data gathered was unsatisfactory, necessitating another flight. This is a tedious workflow. This project aims to develop software for the real-time reception and analysis of data gathered by a lidar-equipped UAV. The user will view the incoming data and its analyses as the UAV is in flight and be able to correct the flight path accordingly. The user of the software will see an interactive model of the landscape with selected analyses shown in colors. The capability to easily map the environment will facilitate the improvement of many ecosystem services

A computational method to model radar return range in a polygonally based, computer-generated-imagery simulation

Described is a method for modeling a ground-mapping radar system for use in simulations where the terrain is in a polygonal form commonly used with computer generated imagery (CGI). The method employs a unique approach for rapidly rejecting polygons not visible to the radar to facilitate the real-time simulation of the radar return. This rapid rejection of the nonvisible polygons requires the precalculation and storage of a set of parameters that do not vary during the simulation. The calculation of a radar range as a function of the radar forward-looking angle to the CGI terrain is carried out only for the visible polygons. This method was used as part of a simulation for terrain-following helicopter operations on the vertical motion simulator at the NASA Ames Research Center. It proved to be an efficient means for returning real-time simulated radar range data

Adaptive Learning Terrain Estimation for Unmanned Aerial Vehicle Applications

For the past decade, terrain mapping research has focused on ground robots using occupancy grids and tree-like data structures, like Octomap and Quadtrees. Since flight vehicles have different constraints, ground-based terrain mapping research may not be directly applicable to the aerospace industry. To address this issue, Adaptive Learning Terrain Estimation algorithms have been developed with an aim towards aerospace applications. This thesis develops and tests Adaptive Learning Terrain Estimation algorithms using a custom test benchmark on representative aerospace cases: autonomous UAV landing and UAV flight through 3D urban environments. The fundamental objective of this thesis is to investigate the use of Adaptive Learning Terrain Estimation algorithms for aerospace applications and compare their performance to commonly used mapping techniques such as Quadtree and Octomap. To test the algorithms, point clouds were collected and registered in simulation and real environments. Then, the Adaptive Learning, Quadtree, and Octomap algorithms were applied to the data sets, both in real-time and offline. Finally, metrics of map size, accuracy, and running time were developed and implemented to quantify and compare the performance of the algorithms. The results show that Quadtree yields the computationally lightest maps, but it is not suitable for real-time implementation due to its lack of recursiveness. Adaptive Learning maps are computationally efficient due to the use of multiresolution grids. Octomap yields the most detailed maps, but it produces a high computational load. The results of the research show that Adaptive Learning algorithms have significant potential for real-time implementation in aerospace applications. Their low memory load and variable-sized grids make them viable candidates for future research and development

Real-Time Terrain Storage Generation from Multiple Sensors towards Mobile Robot Operation Interface

A mobile robot mounted with multiple sensors is used to rapidly collect 3D point clouds and video images so as to allow accurate terrain modeling. In this study, we develop a real-time terrain storage generation and representation system including a nonground point database (PDB), ground mesh database (MDB), and texture database (TDB). A voxel-based flag map is proposed for incrementally registering large-scale point clouds in a terrain model in real time. We quantize the 3D point clouds into 3D grids of the flag map as a comparative table in order to remove the redundant points. We integrate the large-scale 3D point clouds into a nonground PDB and a node-based terrain mesh using the CPU. Subsequently, we program a graphics processing unit (GPU) to generate the TDB by mapping the triangles in the terrain mesh onto the captured video images. Finally, we produce a nonground voxel map and a ground textured mesh as a terrain reconstruction result. Our proposed methods were tested in an outdoor environment. Our results show that the proposed system was able to rapidly generate terrain storage and provide high resolution terrain representation for mobile mapping services and a graphical user interface between remote operators and mobile robots

An evaluation of space acquired data as a tool for management to wildlife habitat in Alaska

The Bureau of Sport Fisheries and Wildlife ERTS experiment in Alaska attempts to yield information useful for three primary functions in the State. They are: (1) to test the feasibility of using ERTS data, in conjunction with aircraft acquired multispectral photography, to develop effective stratified sampling techniques, (2) to provide near real time assessment and evaluation of the quantity, quality, and distribution of waterfowl breeding habitat through frequent ERTS measurements of hydrologic, phenological and vegetational parameters, and (3) to provide basic mapping of vegetation and terrain in certain remote areas of the State for which little or no biological data now exist

Using Game Engine for Online 3D Terrain Visualization with Oil Palm Tree Data

Nowadays, cartography, otherwise known as mapping, are serving people in multiple aspects of livelihood and administration like planning, rescue, military, and tourism. The information is usually presented in the map by using legends, elevation, and contour.With the passage of time, many new methods of mapping are introduced which are divided into the non-digital and digital version.Another method used is the incorporation of 3D modelling in virtual aspect by simulating real-world data.In the recent years using the game engine is one of the important 3D modelling approaches obtained.The game engine has a lot more capabilities to simulate real-world terrains whereas using database support for terrain visualisation, new functionality can be used. This article discussed how to utilise game engine technology for developing 3D terrain visualisation with oil palm tree data.With the success of the system, it, therefore, gives benefits to potential visitors especially the manager of oil palm plantation, decision makers and planners to explore the online 3D terrain visualisation with oil palm tree data and manage it

TERRAIN AWARE IMAGE CLIPPING FOR REAL-TIME AERIAL MAPPING

Many remote sensing applications demand for a fast and efficient way of generating orthophoto maps from raw aerial images. One prerequisite is direct georeferencing, which allows to geolocate aerial images to their geographic position on the earth’s surface. But this is only half the story. When dealing with a large quantity of highly overlapping images, a major challenge is to select the most suitable image parts in order to generate seamless aerial maps of the captured area. This paper proposes a method that quickly determines such an optimal (rectangular) section for each single aerial image, which in turn can be used for generating seamless aerial maps. Its key approach is to clip aerial images depending on their geometric intersections with a terrain elevation model of the captured area, which is why we call it terrain aware image clipping (TAC). The method has a modest computational footprint and is therefore applicable even for rather limited embedded vision systems. It can be applied for both, real-time aerial mapping applications using data links as well as for rapid map generation right after landing without any postprocessing step. Referring to real-time applications, this method also minimizes transmission of redundant image data. The proposed method has already been demonstrated in several search-and-rescue scenarios and real-time mapping applications using a broadband data link and diffent kinds of camera and carrier systems. Moreover, a patent for this technology is pending

Parallel algorithms for interactive manipulation of digital terrain models

Interactive three-dimensional graphics applications, such as terrain data representation and manipulation, require extensive arithmetic processing. Massively parallel machines are attractive for this application since they offer high computational rates, and grid connected architectures provide a natural mapping for grid based terrain models. Presented here are algorithms for data movement on the massive parallel processor (MPP) in support of pan and zoom functions over large data grids. It is an extension of earlier work that demonstrated real-time performance of graphics functions on grids that were equal in size to the physical dimensions of the MPP. When the dimensions of a data grid exceed the processing array size, data is packed in the array memory. Windows of the total data grid are interactively selected for processing. Movement of packed data is needed to distribute items across the array for efficient parallel processing. Execution time for data movement was found to exceed that for arithmetic aspects of graphics functions. Performance figures are given for routines written in MPP Pascal