Terrain analysis using radar shape-from-shading

This paper develops a maximum a posteriori (MAP) probability estimation framework for shape-from-shading (SFS) from synthetic aperture radar (SAR) images. The aim is to use this method to reconstruct surface topography from a single radar image of relatively complex terrain. Our MAP framework makes explicit how the recovery of local surface orientation depends on the whereabouts of terrain edge features and the available radar reflectance information. To apply the resulting process to real world radar data, we require probabilistic models for the appearance of terrain features and the relationship between the orientation of surface normals and the radar reflectance. We show that the SAR data can be modeled using a Rayleigh-Bessel distribution and use this distribution to develop a maximum likelihood algorithm for detecting and labeling terrain edge features. Moreover, we show how robust statistics can be used to estimate the characteristic parameters of this distribution. We also develop an empirical model for the SAR reflectance function. Using the reflectance model, we perform Lambertian correction so that a conventional SFS algorithm can be applied to the radar data. The initial surface normal direction is constrained to point in the direction of the nearest ridge or ravine feature. Each surface normal must fall within a conical envelope whose axis is in the direction of the radar illuminant. The extent of the envelope depends on the corrected radar reflectance and the variance of the radar signal statistics. We explore various ways of smoothing the field of surface normals using robust statistics. Finally, we show how to reconstruct the terrain surface from the smoothed field of surface normal vectors. The proposed algorithm is applied to various SAR data sets containing relatively complex terrain structure

Memories: A Photo Feature

The following is a small selection of the photographs I took during my 12 months with UNPROFOR. In the Spring of 1993, WO Stebbings and myself were the first Terrain Analysis Team sent to UNPROFOR Headquarters, Zagreb, Croatia. We were actually the first Terrain Analysis Team in the Former Yugoslavia. We were the geographic experts for the mission and worked out of Zagreb. The nature of the job allowed us unlimited access to the complete UNPROFOR Theatre of Operations, which included: Croatia, Bosnia and Herzegovina, parts of Serbia and the Former Yugoslav Republic of Macedonia

Projected technological requirements for remote sensing of terrain variables

Contributions of remote sensing to hydrogeomorphology and terrain analysis are reviewed in order to identify characteristics that should receive support in system and sensor configuration planning. Fluvial morphological studies, peak discharge modeling, and hydrogeomorphic floodplain mapping using large scale (1:12,000) to small scale (1:750,000) orbital photography are discussed as well as quantitative assessment of terrain variables for specific applications

Identifying Locations Of Highly Eroded Agricultural Land In The Devils Lake Basin, ND Using GIS Terrain Analysis Modeling

Soil erosion modeling using terrain analysis holds great potential due to the simplicity of the models, and the ease in running the analysis in a GIS. Terrain analysis of the upper Devils Lake basin was conducted using a 3-meter Light Detection and Ranging-derived digital elevation model. Portions of the Mauvais Coulee and Calio Coulee watersheds in the basin were analyzed to evaluate soil erosion potential and determine if terrain analysis was an accurate tool for modeling erosion in this fairly flat landscape. The analysis used slope, flow accumulation, and stream power index (SPI) within a GIS to identify highly eroded areas. The study found that 1.5% of the 262.8 km2 study area exhibited channelized erosion. It was determined that the terrain analysis accurately identified 92 (79%) of the 116 survey points established for field verification. Finally, the findings support that the use of terrain analysis for erosion modeling in the Devils Lake basin is highly accurate, and can be a useful tool in locating and implementing best management practices (BMPs) to aid in the reduction of surface runoff entering Mauvais and Calio Coulees from channelized erosion

TERRAIN ANALYSIS IN CONSIDERATION OF SURFACE CURVATURE CONDITIONS

In digital relief models determination of the terrain curvature can be realized without difficulty with the aid of the formulae figuring in the paper. Visualizing the results on maps, the curvature conditions can also be studied visually. After a computer aided analysis of the results the algorithm in the paper orders the surface points into seven categories (plane, peak, pit, pass, ridge, valley, slope) and/or their sub-categories. In a digital form, the resulting image matrix can supply further computer aided processes ,with information, and visualized in a graphic way it gives a good image about terrain formation. The results can be utilized in different branches of agricultural planning, in environmental protection, hydrological modeling, etc

Active microwave remote sensing of earth/land, chapter 2

Geoscience applications of active microwave remote sensing systems are examined. Major application areas for the system include: (1) exploration of petroleum, mineral, and ground water resources, (2) mapping surface and structural features, (3) terrain analysis, both morphometric and genetic, (4) application in civil works, and (5) application in the areas of earthquake prediction and crustal movements. Although the success of radar surveys has not been widely publicized, they have been used as a prime reconnaissance data base for mineral exploration and land-use evaluation in areas where photography cannot be obtained

Overview of SAND-E: Semi-Autonomous Navigation for Detrital Environments

Rovers are the state of the art for the exploration and detection of past habitability and life on other worlds. One of the most basic functions of a rover is terrain navigation. Information collected by the rover is used autonomously to mitigate terrain hazards such large rocks, while humans qualitatively assess hazardous geologic terrain such as soil type and degree of rock cover. Planetary scientists use the same information to select targets such as drill sites, and for basic scientific analysis such as characterization of rock outcrops. Although the data is complementary, data from terrain analysis for navigation and terrain analysis for scientific investigations are poorly integrated. The lack of integration creates science and operation inefficiencies that limit exploration of habitable environments. As new modes of exploration come online, such as unmanned aerial systems (UAS) (e.g., the Mars Helicopter Scout and Titan Dragonfly), a need exists to integrate terrain data and science analysis to improve operational and scientific outcomes during exploration. We present an overview of a project aimed at evaluating the effectiveness and capability rover and UAS-based semi-automated terrain analysis using the Automated Soil Assessment Systems (ASAS) developed by Mission Control Space Services for navigating, selecting targets for sampling, and characterizing mafic detrital sediments along glacio-fluvial-aeolian sand transport pathways in Iceland. We describe recent advances in automated terrain analysis in sandy environments and scientific uses of terrain assessment from sandy environments. We assess fluvial and aeolian terrains in Iceland and show how terrain analysis data can inform scientific characterization of these environments

Development of Terrain Analysis Database Using Military Geographic Information System

The Information and Communication Technology (ICT) that includes military geospatial information will play a key role in the Revolution of Military Affair (RMA) for future warfare. The Terrain Analysis (TA) database is one of the military geospatial information that needs to be established in the Malaysian Armed Forces (MAF) in order to enable various Military Geographic Information System (MGIS) to perform analyses and produce Tactical Decision Aids (TDA) products. This study focused on the establishment of TA database structure that consisted of several layers namely Surface Configuration - Slope, Vegetation, Surface Material - Soils, Surface Drainage, Transportation and Obstacle Layers. A prototype T A database was established in order to evaluate the effectiveness of the database in generating Cross Country Movement (CCM) map. Results revealed that the topographic data from Department of Survey and Mapping Malaysia in Topologized Topographic Mapping (TTM) database, soil data from Department of Agriculture and the analyses of IKONOS imagery and ground data collection using GPS Geo Explorer 3 have contributed significantly to the development of prototype TA database. GIS technology was thoroughly utilized in implementing a user interface menu and CCM map from prototype TA database. Results showed that GIS technology has provided a powerful tool in successfully generating both products

Advanced Digital Terrain Analysis Using Roughness-Dissectivity Parameters in GIS

The local variation of terrain properties causes profound changes in the biosphere, microclimate, hydrologic cycle, and in the distribution of human activities on this planet. With the dawn of computerized technology, the terrain is represented in a digital form and new methods are needed to effectively describe, evaluate and quantify terrain properties. The purpose of this project is to develop new methods and procedures for terrain analyses within a GIS environment. The focus is to develop tools for capturing the local terrain variability. The selected parameters such as the hypsometric integral (modified Martonne’s index), roughness index, and basic statistical measures (mean, range and variance) are combined with newly developed dissectivity parameters, drainage lengths and landuse characteristics in one unified package and programmed in GIS using the ARC Macro Language (AML). The digital terrain data from this analysis can then be correlated with other spatial information to determine the influence of terrain properties on the ecosystem or other variables of interest including the human systems

Automated, on-board terrain analysis for precision landings

Advances in space robotics technology hinge to a large extent upon the development and deployment of sophisticated new vision-based methods for automated in-space mission operations and scientific survey. To this end, we have developed a new concept for automated terrain analysis that is based upon a generic image enhancement platform|multi-scale retinex (MSR) and visual servo (VS) processing. This pre-conditioning with the MSR and the vs produces a "canonical" visual representation that is largely independent of lighting variations, and exposure errors. Enhanced imagery is then processed with a biologically inspired two-channel edge detection process, followed by a smoothness based criteria for image segmentation. Landing sites can be automatically determined by examining the results of the smoothness-based segmentation which shows those areas in the image that surpass a minimum degree of smoothness. Though the msr has proven to be a very strong enhancement engine, the other elements of the approach|the vs, terrain map generation, and smoothness-based segmentation|are in early stages of development. Experimental results on data from the Mars Global Surveyor show that the imagery can be processed to automatically obtain smooth landing sites. In this paper, we describe the method used to obtain these landing sites, and also examine the smoothness criteria in terms of the imager and scene characteristics. Several examples of applying this method to simulated and real imagery are shown