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NASA NTRS1987

Aspects of Voyager photogrammetry

In January 1986, Voyager 2 took a series of pictures of Uranus and its satellites with the Imaging Science System (ISS) on board the spacecraft. Based on six stereo images from the ISS narrow-angle camera, a topographic map was compiled of the Southern Hemisphere of Miranda, one of Uranus' moons. Assuming a spherical figure, a 20-km surface relief is shown on the map. With three additional images from the ISS wide-angle camera, a control network of Miranda's Southern Hemisphere was established by analytical photogrammetry, producing 88 ground points for the control of multiple-model compilation on the AS-11AM analytical stereoplotter. Digital terrain data from the topographic map of Miranda have also been produced. By combining these data and the image data from the Voyager 2 mission, perspective views or even a movie of the mapped area can be made. The application of these newly developed techniques to Voyager 1 imagery, which includes a few overlapping pictures of Io and Ganymede, permits the compilation of contour maps or topographic profiles of these bodies on the analytical stereoplotters.

Wu, Sherman S. C.↗

NASA NTRSDate not supplied

GeoAI advances in specific landform mapping

Landform mapping (also referred to as geomorphology or geomorphometry) can be divided into two domains: general and specific (Evans 2012). Whereas general landform mapping categorizes all elements of the study area into landform classes, such as ridges, valleys, peaks, and depressions, the mapping of specific landforms requires the delineation (even if fuzzy) of individual landforms. The former is mainly driven by physical properties such as elevation, slope, and curvature. The latter, however, must consider the cognitive (human) reasoning that discriminates individual landforms in addition to these physical properties (Arundel and Sinha 2018). Both mapping forms are important. General geomorphometry is needed to understand geological and ecological processes and as boundary layer input to climate and environmental models. Specific geomorphometry supports such activities as disaster management and recovery, emergency response, transportation, and navigation. In the United States, individual landforms of interest are named in the U.S. Geological Survey (USGS) Geographic Names Information System, a point dataset captured specifically to digitize geographic names from the USGS Historical Topographic Map Collection (HTMC). Named landform extent is represented only by the name placement in the HTMC. Recent work has investigated CNN-based deep learning methods to capture these extents in machine-readable form. These studies first relied on physical properties (Arundel et al. 2020) and then included the HTMC as a band in RGB images in limited testing (Arundel et al. 2023). Results from the HTMC dataset surpassed those using just physical properties and using the HTMC alone performed best due to the hillshading and elevation (contour) data incorporated into the topographic maps. However, results fell short of an operational capacity to map all named landforms in the United States. Thus, our current work expands upon past research by focusing on the HTMC and physical information as inputs and the named landform label extents. Specifically, we propose to leverage pre-trained foundation models for segmentation and optical character recognition (OCR) models to jointly map landforms in the United States. Our approach aims to bridge the disparities among the independent information sources to facilitate informed decision-making. The modeling pipeline performs (1) segmentation using the physical information and (2) information extraction using OCR, in parallel. Then a computer vision approach merges the two branches into a labeled segmentation. References: Arundel, Samantha T., Wenwen Li, and Sizhe Wang. 2020. “GeoNat v1.0: A Dataset for Natural Feature Mapping with Artificial Intelligence and Supervised Learning.” Transactions in GIS 24 (3): 556–72. https://doi.org/10.1111/tgis.12633. Arundel, Samantha T, and Gaurav Sinha. 2018. “Validating GEOBIA Based Terrain Segmentation and Classification for Automated Delineation of Cognitively Salient Landforms BT - Proceedings of Workshops and Posters at the 13th International Conference on Spatial Information Theory (COSIT 2017).” In Proceedings of Workshops and Posters at the 13th International Conference on Spatial Information Theory (COSIT 2017), Lecture Notes in Geoinformation and Cartography, edited by Paolo Fogliaroni, Andrea Ballatore, and Eliseo Clementini, 9–14. Cham: Springer International Publishing. Arundel, Samantha T., Gaurav Sinha, Wenwen Li, David P. Martin, Kevin G. McKeehan, and Philip T. Thiem. 2023. “Historical Maps Inform Landform Cognition in Machine Learning.” Abstracts of the ICA 6 (August): 1–2. https://doi.org/10.5194/ica-abs-6-10-2023. Evans, Ian S. 2012. “Geomorphometry and Landform Mapping: What Is a Landform?” Geomorphology 137 (1): 94–106. https://doi.org/10.1016/j.geomorph.2010.09.029.

machine learning↗

NASA NTRSDate not supplied

GeoAI Advances in Specific Landform Mapping

machine learning↗

NASA NTRS1973

Correlation of ERTS MSS data and earth coordinate systems

Experience has revealed a problem in the analysis and interpretation of ERTS multispectral scanner (MSS) data. The problem is one of accurately correlating ERTS MSS pixels (picture elements) with analysis areas specified on aerial photographs or topographic maps for training recognition computers and/or evaluating recognition results. A computer-aided procedure to correlate coordinates from topographic maps and/or aerial photographs with ERTS data coordinates has been developed. In the procedure, a map transformation from earth coordinates to ERTS scan line and point numbers is calculated using selected ground control points and the method of least squares. The map transformation is then applied to the earth coordinates of selected areas to obtain the corresponding ERTS point and line numbers.

Malila, W. A.↗

NASA NTRS1974

Affine transformations from aerial photos to computer compatible tapes

During the development of a project to estimate wheat production, it became necessary to pull data, corresponding to particular fields in a test site, off an ERTS computer compatible tape. Aerial photographs and topographic maps were on hand for the test site. A method was devised, using an affine transformation, to relate the aerial photographs or topographic maps to the tapes. One can thereby access data on the tape corresponding to regions covered by only a few pixels. The theory can be used for the registration of two tapes for the same area and for the geometric correction of images.

Peet, F. G.↗

NASA NTRS1981

Topography of Martian central volcanoes

Results are presented of the topographic mapping of six large central volcanoes on Mars. Stereo images of the volcanoes Olympus Mons, Elysium Mons, Albor Tholus, Ceraunius Tholus, Uranius Tholus and Uranius Patera were acquired by Viking Orbiter 1, and pairs of images were compiled into topographic maps through the use of digital image measurement techniques. Olympus Mons is found to have the general form of a terrestrial basaltic shield constructed almost entirely from lava flows, however with an altitude of 20-23 km and flank slopes averaging about 4 deg; a high nominal density indicates that anomalously dense lithosphere underlies the shield. Uranius Patera is observed to be a similar feature of present relief about 2 km, with its lower flanks buried by later lava flood deposits. Elysium Mons has about 13 km of local relief with average slopes of 4.4 deg, although its upper flank slopes are significantly steeper than those of Olympus Mons, suggesting a shield volcano modified by a terminal phase of mixed volcanic activity. Albor Tholus is found to be a partially buried 3-km shield-like construct, while Ceranius and Uranius Tholus are steeper cone-like features with reliefs of about 6 and 2 km, respectively, which may be lava shield constructs modified by a terminal stage of explosive activity.

Blasius, K. B.↗

NASA NTRS1977

The use of the LANDSAT data collection system and imagery in reservoir management and operation

The author has identified the following significant results. An increase in the data collection system's (DCS) ability to function in the flood control mission with no additional manpower was demonstrated during the storms which struck New England during April and May of 1975 and August 1976. It was found that for this watershed, creditable flood hydrographs could be generated from DCS data. It was concluded that an ideal DCS for reservoir regulation would draw features from LANDSAT and GOES. MSS grayscale computer printout and a USGS topographic map were compared, yielding an optimum computer classification map of the wetland areas of the Merrimack River estuary. A classification accuracy of 75% was obtained for the wetlands unit, taking into account the misclassified and the unclassified pixels. The MSS band 7 grayscale printouts of the Franklin Falls reservoir showed good agreement to USGS topographic maps in total area of water depicted at the low water reservoir stage and at the maximum inundation level. Preliminary analysis of the LANDSAT digital data using the GISS computer algorithms showed that the radiance of snow cover/vegetation varied from approximately 20 mW/sq cm sr in nonvegetated areas to less than 4 mW/sq cm sr for densely covered forested area.

Cooper, S.↗

NASA NTRS2001

The Mars Orbiter Altimeter (MOLA) Investigation of the Shape and Topography of Mars

The Mars Orbiter Laser Altimeter (MOLA) is an instrument on the Mars Global Surveyor (MGS) spacecraft that has been orbiting Mars since September 1997. After some preliminary observations in Sept/Oct, 1997 and in the spring and summer of 1998, the MGS spacecraft entered its mapping orbit of 400 km above the surface of Mars in February 1999. MGS began a 2 year program of systematically mapping the planet with a camera (MOC), thermal emission spectrometer (TES), magnetometer (MAG), laser altimeter (MOLA), and a radio science investigation for gravity and radio occultations. MOLA has a 48mJ, 1064 nrn ND:YAG, diode pumped laser with a 8 nanosecond pulse width, a pulse rate of 10 Hz, and a range precision of less than 40 cm. MOLA has been operating almost continuously for over two years and obtained over 600 million measurements of the radius of Mars. Using very precise orbits for the MGS spacecraft derived from the Doppler and range tracking of MGS by the Deep Space Network a topographical map of Mars has been developed with an average radial accuracy of a meter and a horizontal accuracy of 100 meters. This topographical map has revealed a new Mars, a planet with some of the flattest areas in the solar system and one of the largest impact basins. MOLA has revealed clear evidence of the effect of past fluid action on the surface and found icecaps that contain as much water ice today as the icecap of Greenland.

Smith, David E.↗

NASA NTRS1973

Correlation of ERTS MSS data and earth coordinate systems

The author has identified the following significant results. Experience has revealed a problem in the analysis and interpretation of ERTS-1 multispectral scanner (MSS) data. The problem is one of accurately correlating ERTS-1 MSS pixels with analysis areas specified on aerial photographs or topographic maps for training recognition computers and/or evaluating recognition results. It is difficult for an analyst to accurately identify which ERTS-1 pixels on a digital image display belong to specific areas and test plots, especially when they are small. A computer-aided procedure to correlate coordinates from topographic maps and/or aerial photographs with ERTS-1 data coordinates has been developed. In the procedure, a map transformation from earth coordinates to ERTS-1 scan line and point numbers is calculated using selected ground control points nad the method of least squares. The map transformation is then applied to the earth coordinates of selected areas to obtain the corresponding ERTS-1 point and line numbers. An optional provision allows moving the boundaries of the plots inward by variable distances so the selected pixels will not overlap adjacent features.

Malila, W. A.↗

NASA NTRS1990

Radarclinometry of the earth and Venus from Space-Shuttle and Venera-15 imagery

A project to develop a line-integral approach to two-dimensional radarclinometry and to bring it to the status of producing topographic maps from real radar images is presented. Details of the methodology are discussed along with the specific areas where observations were taken. It is concluded that photoclinometry will never be as accurate as stereophotoclinometry, but is (by comparison) economical, rapid, and, when multiscopic paralactic images are not available, the only source of topographic information. The present technique is able to retrieve useful topographic information from even poor images. Furthermore, in future applications of photogrammetry, even when it is operating at the peak of its potential, photoclinometry will be utilized to provide the highest spatial frequencies in a topographic map.

Wildey, Robert L.↗

NASA NTRS2005

Simultaneous Conoscopic Holography and Raman Spectroscopy

A new instrument was developed for chemical characterization of surfaces that combines the analytical power of Raman spectroscopy with the three-dimensional topographic information provided by conoscopic holography. The figure schematically depicts the proposed hybrid instrument. The output of the conoscopic holographic portion of the instrument is a topographical map of the surface; the output of the Raman portion of the instrument is hyperspectral Raman data, from which the chemical and/or biological composition of the surface would be deduced. By virtue of the basic principles of design and operation of the instrument, the hyperspectral image data would be inherently spatially registered with the topographical data. In conoscopic holography, the object and reference beams of classical holography are replaced by the ordinary and extraordinary components generated by a single beam traveling through a birefringent, uniaxial crystal. In the basic conoscopic configuration, a laser light is projected onto a specimen and the resulting illuminated spot becomes a point source of diffuse light that propagates in every direction. The laser beam is rasterscanned in two dimensions (x and y) perpendicular to the beam axis (z), and at each x,y location, the pattern of interference between the ordinary and extraordinary rays is recorded. The recorded interferogram constitutes the conoscopic hologram. Of particular significance for the proposed instrument is that the conoscopic hologram contains information on the z coordinate (height) of the illuminated surface spot. Hence, a topographical map of the specimen is constructed point-by-point by rastering the laser beam in the x and y directions and correlating the x and y coordinates with the z information obtained from the interferograms. Conoscopic imaging is an established method, and conoscopic laboratory instruments for surface metrology are commercially available. In Raman spectroscopy of a surface, one measures the spectrum of laser light scattered inelastically from a laser-illuminated spot on the surface. The wavelengths of the inelastically scattered light differ from that of the incident laser beam by amounts that correspond to the energies of molecular vibrations. The resulting vibrational spectrum can be used to identify the molecules. Raman spectroscopy is a standard laboratory technique for identifying mineralogical, biological, and other specific chemical compositions.

Schramm, Harry F.↗

NASA NTRS1987

4-D display of satellite cloud images

A technique has been developed to display GOES satellite cloud images in perspective over a topographical map. Cloud heights are estimated using temperatures from an infrared (IR) satellite image, surface temperature observations, and a climatological model of vertical temperature profiles. Cloud levels are discriminated from each other and from the ground using a pattern recognition algorithm based on the brightness variance technique of Coakley and Bretherton. The cloud regions found by the pattern recognizer are rendered in three-dimensional perspective over a topographical map by an efficient remap of the visible image. The visible shades are mixed with an artificial shade based on the geometry of the cloud-top surface, in order to enhance the texture of the cloud top.

Hibbard, William L.↗

NASA NTRS1992

Topography of Apollinaris Patera and Ma'adim Vallis

Digital elevation models of the northern part of Ma'adim Vallis (603a41 607m/pix, 639a91 721m/pix), and Apollinaris Patera (603a42 612m/pix, 639a92 717m/pix), covering the area between 180 degrees to 190 degrees long and -2 degrees to -20 degrees lat. were obtained using a method described here. The results for the Ma'adim Vallis area show broad agreement with the United States Geological Survey (USGS) topographic map of the area with a channel depth of 1 to 2 km. A detailed study of the variations in the channel depth along its course and calculations of its discharge rate from channel cross section and slope are currently being undertaken. Results for Apollinaris Patera have been obtained, although the absolute heights relative to the Mars datum are not well constrained. However, the relative heights are sufficient for some analysis. Again, the topographic map is in reasonable agreement with the USGS map of the area, although there are significant differences.

Thornhill, G. D.↗

NASA NTRS1988

Satellite radar interferometry - Two-dimensional phase unwrapping

Interferometric synthetic aperture radar observations provide a means for obtaining high-resolution digital topographic maps from measurements of amplitude and phase of two complex radar images. The phase of the radar echoes may only be measured modulo 2 pi; however, the whole phase at each point in the image is needed to obtain elevations. An approach to 'unwrapping' the 2 pi ambiguities in the two-dimensional data set is presented. It is found that noise and geometrical radar layover corrupt measurements locally, and these local errors can propagate to form global phase errors that affect the entire image. It is shown that the local errors, or residues, can be readily identified and avoided in the global phase estimation. A rectified digital topographic map derived from the unwrapped phase values is presented.

Goldstein, Richard M.↗

NASA NTRS1973

Application of ecological, geological and oceanographic ERTS-1 imagery to Delaware's coastal resources planning

The author has identified the following significant results. Coastal vegetation species appearing in the ERTS-1 images taken of Delaware Bay have been correlated with ground truth vegetation maps and imagery obtained from high altitude overflights. Multispectral analysis of the high altitude photographs indicated that four major vegetation communities could be clearly discriminated from 60,000 feet altitude including: (1) salt marsh cord grass; (2) salt marsh hay and spike grass; (3) reed grass; and (4) high tide bush and sea myrtle. In addition, human impact can be detected in the form of fresh water impoundments built to attract water fowl, dredge-fill operations and other alterations of the coastal environment. Overlay maps matching the USGS topographic map size of 1:24,000 have been prepared showing the four wetland vegetation communities, fresh water impoundments, and alteration of wetlands by mosquito control ditching and dredge-fill operations. Using these maps, ERTS-1 images were examined by human interpreters and automated multispectral analyzers. Major plant communities of (1) Spartina alterniflora, (2) Spartina patens and Distichlis spicata, and (3) Iva frutescens and Baccharis halimifolia can be distinguished from each other and from surrounding uplands in ERTS-1 scanner bands 6 and 7.

Klemas, V.↗

NASA NTRS1986

Spaceborne imaging radar research in the 90's

The imaging radar experiments on SEASAT and on the space shuttle (SIR-A and SIR-B) have led to a wide interest in the use of spaceborne imaging radars in Earth and planetary sciences. The radar sensors provide unique and complimentary information to what is acquired with visible and infrared imagers. This includes subsurface imaging in arid regions, all weather observation of ocean surface dynamic phenomena, structural mapping, soil moisture mapping, stereo imaging and resulting topographic mapping. However, experiments up to now have exploited only a very limited range of the generic capability of radar sensors. With planned sensor developments in the late 80's and early 90's, a quantum jump will be made in our ability to fully exploit the potential of these sensors. These developments include: multiparameter research sensors such as SIR-C and X-SAR, long-term and global monitoring sensors such as ERS-1, JERS-1, EOS, Radarsat, GLORI and the spaceborne sounder, planetary mapping sensors such as the Magellan and Cassini/Titan mappers, topographic three-dimensional imagers such as the scanning radar altimeter and three-dimensional rain mapping. These sensors and their associated research are briefly described.

Elachi, Charles↗

DOE OSTI2024

Datasets and U-Net Model for "A Deep Learning Based Framework to Identify Undocumented Orphaned Oil and Gas Wells from Historical Maps: a Case Study for California and Oklahoma"

This dataset has results and the model associated with the publication Ciulla et al., (2024). It contains a U-Net semantic segmentation model (unet_model.h5) and associated code implemented in tensorflow 2.0 for the model training and identification of oil and gas well symbols in USGS historical topographic maps (HTMC). Given a quadrangle map (7.5 minutes), downloadable at this url: https://ngmdb.usgs.gov/topoview/, and a list of coordinates of the documented wells present in the area, the model returns the coordinates of oil and gas symbols in the HTMC maps. For reproducibility of our workflow, we provide a sample map in California and the documented well locations for the entire State of California (CalGEM_AllWells_20231128.csv) downloaded from https://www.conservation.ca.gov/calgem/maps/Pages/GISMapping2.aspx. Additionally, the locations of 1,301 potential undocumented orphaned wells identified using our deep learning framework or the counties of Los Angeles and Kern in California, and Osage and Oklahoma in Oklahoma are provided in the file found_potential_UOWs.zip. The results of the visual inspection of satellite imagery in Osage County is in the file visible_potential_UOWs.zip. The dataset also includes a custom tool to validate the detected symbols in the HTMC maps (vetting_tool.py). More details about the methodology can be found in the associated paper: Ciulla, F., Santos, A., Jordan, P., Kneafsey, T., Biraud, S.C., and Varadharajan, C. (2024) A Deep Learning Based Framework to Identify Undocumented Orphaned Oil and Gas Wells from Historical Maps: a Case Study for California and Oklahoma. Accepted for publication in Environmental Science and Technology. The geographical coordinates provided correspond to the locations of potential undocumented orphaned oil and gas wells (UOWs) extracted from historical maps. The actual presence of wells need to be confirmed with on-the-ground investigations. For your safety, do not attempt to visit or investigate these sites without appropriate safety training, proper equipment, and authorization from local authorities. Approaching these well sites without proper personal protective equipment (PPE) may pose significant health and safety risks. Oil and gas wells can emit hazardous gasses including methane, which is flammable, odorless and colorless, as well as hydrogen sulfide, which can be fatal even at low concentrations. Additionally, there may be unstable ground near the wellhead that may collapse around the wellbore. This dataset was prepared as an account of work sponsored by the United States Government. While this document is believed to contain correct information, neither the United States Government nor any agency thereof, nor the Regents of the University of California, nor any of their employees, makes any warranty, express or implied, or assumes any legal responsibility for the accuracy, completeness, or usefulness of any information, apparatus, product, or process disclosed, or represents that its use would not infringe privately owned rights. Reference herein to any specific commercial product, process, or service by its trade name, trademark, manufacturer, or otherwise, does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States Government or any agency thereof, or the Regents of the University of California. The views and opinions of authors expressed herein do not necessarily state or reflect those of the United States Government or any agency thereof or the Regents of the University of California.

Artificial Intelligence↗

NASA NTRS1973

Application of ecological geological and oceanographic ERTS-1 imagery to Delaware's coastal resources planning

The Author has identified the following significant results. Significant results obtained by analysis of digital ERTS-1 data are: (1) Statistical outputs indicating the reliability of discriminating eight coastal vegetation and land use classes on a given group of training sets included: (a) mean and standard deviation of response in each class chosen; (b) contribution tables indicating importance of each channel in discriminating each thematic class from the background; (c) scatter diagrams showing relationships of thematic spectral signatures in spectral space; and (d) classification table showing reliability (in percent) of identification of each thematic class. (2) Thematic color maps at a scale of 1:1,000,000 showing vegetation and land use categories for Delaware's entire coastal zone. (3) Thematic computer plots at specified smaller (i.e. 1:24,000) scales for comparison with existing map data such as U.S.G.S. topographic maps.

Klemas, V.↗