Urban mapping validation in Venice using satellite and aircraft data
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urban mapping↗
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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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Upper Atmosphere Research Satellite (UARS) Microwave Limb Sounder (MLS) mapping - Validation, early results and applications
The results of limitation studies performed with the UARS MLS are presented. A consistent set of algorithms allows the extraction of the spectral coefficients in time and longitude from asynoptically sampled satellite data and the subsequent reconstruction of synoptic maps from that spectral information. In addition to providing synoptic maps, the asynoptic technique allows the use of standard spectral analysis tools such as autocorrelation and cross correlation.
Elson, Lee S.↗
Terrestrial Demonstration of Orbital Mapping and Validation Capabilities Over a Lunar Surface Analog
The Lunar Navigation Maps (LuNaMaps) project has improved existing tools and processes and developed new tools and processes to support the generation and validation of navigation maps of the lunar surface from orbital imagery. To demonstrate the advancements made through the LuNaMaps project, we conducted a terrestrial demonstration obtaining “orbital” imagery of the Lunar Surface Proving Ground (LSPG) at Astrobotic’s test facility in Mojave California. The LSPG is a 100 m by 100 m pad built to mimic the features and appearance of the lunar surface. In this paper we describe the planning and results of the test, including the capture of imagery for building the maps, the map building processes, building of a “truth map” using traditional surveying tools, and the map validation processes. We demonstrate how the built map compares to the “truth map” and how the validation processes provided insight to this comparison. Additionally, we describe an upcoming partner test in which the navigation maps will be used in a terrain relative navigation (TRN) technology demonstration over the same LSPG surface.
mapping↗
The Importance of Measurement Errors for Deriving Accurate Reference Leaf Area Index Maps for Validation of Moderate-Resolution Satellite LAI Products
The validation of moderate-resolution satellite leaf area index (LAI) products such as those operationally generated from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor data requires reference LAI maps developed from field LAI measurements and fine-resolution satellite data. Errors in field measurements and satellite data determine the accuracy of the reference LAI maps. This paper describes a method by which reference maps of known accuracy can be generated with knowledge of errors in fine-resolution satellite data. The method is demonstrated with data from an international field campaign in a boreal coniferous forest in northern Sweden, and Enhanced Thematic Mapper Plus images. The reference LAI map thus generated is used to assess modifications to the MODIS LAI/fPAR algorithm recently implemented to derive the next generation of the MODIS LAI/fPAR product for this important biome type.
Huang, Dong↗
Tsunami Squares: Earthquake driven inundation mapping and validation by comparison to the Regional Ocean Modeling System
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David P. Grzan↗
Global Ionospheric Mapping using GPS: Validation and Future Prospects
Many applications resulting from GPS Mapping are discussed. These include Ionospheric, tropospheric, and space-borne applications. Also included are types of Ionospheric models, examples of GPS maps and the validation of Ionospheric Maps.
Wilson, Brian D.↗
Astrobee's Multi-year Activities at the International Space Station's Japanese Experimental Module
The Astrobee free-flying robots recently completed their third successful year of operations, housed in the Japanese Experimental Module (JEM) on the International Space Station. We summarize the three years of operation, giving special attention to JAXA's 1st and 2nd Kibo Robot Programming Challenge (RPC) and the mapping processes and tools that make Astrobees' autonomous operation possible. The JEM is an ever changing, dynamic environment where light settings, cargo, payloads, and crew members constantly move and interact with one another. The 1st JAXA Kibo RPC event, a collaboration between JAXA and NASA, was held in 2020. Students from several countries in the Asia-Pacific region competed in programming challenges with a simulated Astrobee. The finalists were then invited to run their code on an actual Astrobee in the JEM. For the final round, students programmed Astrobee to visit three different locations to obtain data that would instruct the robot to complete a final task with the participation of ISS crew. The first competition was a tremendous success, leading to an equally successful 2nd JAXA Kibo RPC in 2021 with even larger participation. The 3rd JAXA Kibo RPC will occur in 2022 expanding further to incorporate US participants. These activities led to several firsts in Astrobee’s history: operation of an Astrobee free-flying robot without crew supervision in preparation for on-orbit operations, autonomous image acquisition towards updates of the navigation map, non-NASA code running on the robot (both from JAXA and participating students), two heterogeneous free-flying robots from two different space agencies working together (Int-Ball and Astrobee) during the final event in 2020, the first payload using Astrobee, and having Astrobee controlled from a non-NASA location (Tsukuba Space Center). The preparation towards these activities involved constant evaluation of the different components of Astrobee's systems, specially mapping and localization. The paper describes the evolution of these systems such as the improvements made in localization to reduce localization drift by using graph-based optimization instead of the extended Kalman Filter localizer. Additionally, it reports on the mapping process and analysis tools created to validate map consistency across different activities in the constantly changing JEM environment. These enhancements have enabled the Astrobee facility to successfully execute over 100 ISS activities supporting over a dozen researchers and partners around the world.
Astrobee↗
Method for Pre-Conditioning a Measured Surface Height Map for Model Validation
This software allows one to up-sample or down-sample a measured surface map for model validation, not only without introducing any re-sampling errors, but also eliminating the existing measurement noise and measurement errors. Because the re-sampling of a surface map is accomplished based on the analytical expressions of Zernike-polynomials and a power spectral density model, such re-sampling does not introduce any aliasing and interpolation errors as is done by the conventional interpolation and FFT-based (fast-Fourier-transform-based) spatial-filtering method. Also, this new method automatically eliminates the measurement noise and other measurement errors such as artificial discontinuity. The developmental cycle of an optical system, such as a space telescope, includes, but is not limited to, the following two steps: (1) deriving requirements or specs on the optical quality of individual optics before they are fabricated through optical modeling and simulations, and (2) validating the optical model using the measured surface height maps after all optics are fabricated. There are a number of computational issues related to model validation, one of which is the "pre-conditioning" or pre-processing of the measured surface maps before using them in a model validation software tool. This software addresses the following issues: (1) up- or down-sampling a measured surface map to match it with the gridded data format of a model validation tool, and (2) eliminating the surface measurement noise or measurement errors such that the resulted surface height map is continuous or smoothly-varying. So far, the preferred method used for re-sampling a surface map is two-dimensional interpolation. The main problem of this method is that the same pixel can take different values when the method of interpolation is changed among the different methods such as the "nearest," "linear," "cubic," and "spline" fitting in Matlab. The conventional, FFT-based spatial filtering method used to eliminate the surface measurement noise or measurement errors can also suffer from aliasing effects. During re-sampling of a surface map, this software preserves the low spatial-frequency characteristic of a given surface map through the use of Zernike-polynomial fit coefficients, and maintains mid- and high-spatial-frequency characteristics of the given surface map by the use of a PSD model derived from the two-dimensional PSD data of the mid- and high-spatial-frequency components of the original surface map. Because this new method creates the new surface map in the desired sampling format from analytical expressions only, it does not encounter any aliasing effects and does not cause any discontinuity in the resultant surface map.
Sidick, Erkin↗
The magnetic state of the Earth (according to the magnetic maps for 1880.0 published by the German Naval Office)
Publication of the magnetic maps in 1880 has made it possible to make the first continuation of the foundations for the Earth's magnetism established by Gauss in the general theory of Earth magnetism. A new calculation based on the maps valid for 1880, makes it possible to express the changes which have occurred over the last 50 years in numbers and only within the liability limits of the maps themselves.
Icilius, G. V. Q.↗
Techniques for Down-Sampling a Measured Surface Height Map for Model Validation
This software allows one to down-sample a measured surface map for model validation, not only without introducing any re-sampling errors, but also eliminating the existing measurement noise and measurement errors. The software tool of the current two new techniques can be used in all optical model validation processes involving large space optical surfaces
Sidick, Erkin↗
Midwest Water Resources II: Evaluating Evapotranspiration with NASA Earth Observations and In Situ Observations to Understand Water Balance in Midwest Agriculture
Seasonal water variability in the midwestern United States extensively affects the agricultural community, as it impacts irrigation schedules, growing seasons, and overall ecosystem function. Evapotranspiration (ET) is a critical climatic variable in the water cycle and is used to evaluate spatiotemporal trends in drought and flood conditions. The NASA DEVELOP team partnered with the United States Department of Agriculture (USDA) Midwest Climate Hub, the Minnesota Department of Agriculture, the Illinois State Water Survey, and Michigan State University to compare remotely sensed ET products with in situ observations from January 2001 through December 2020. Remotely sensed actual ET (aET) data were sourced from NASA’s Terra Moderate Resolution Imaging Spectroradiometer (MODIS), and reference ET (refET) data were derived from the Gridded Surface Meteorological (gridMET) dataset. For in situ comparison, aET data were downloaded from the AmeriFlux database while refET data were collected from the Illinois Climate Network and Michigan State University’s Enviro-weather database. For a holistic assessment of ET, this project generated comparisons between remotely sensed and in situ observations, calculated descriptive statistics for validation between refET datasets, and spatially produced statistical validation maps regarding in situ sites. The temporal and spatial gaps of AmeriFlux data limited aET analysis. This comparative assessment of ET products across the Midwest can be used by project partners to assess regional water trends and guide future land management decisions.
Addison Pletcher↗
Objective assessment of Advanced Very High Resolution Radiometer data for land cover mapping
The validity of using data from the Advanced Very High Resolution Radiometer (AVHRR) of the satellites NOAA-6 and NOAA-7 for land cover mapping is assessed by making comparisons with much higher resolution LANDSAT multi-spectral scanner (MSS) data. Near synchronous data for both systems are analysed for test sites in the Imperial Valley, California, the Nile Delta, and southern Italy. The results strongly indicate that despite the very coarse resolution of the AVHRR data compared with conventional MSS data they are sufficiently strongly correlated to suggest that the former have significant potential for land cover mapping, especially at small scales and for large areas. Hence the outstanding benefits of AVHRR data, namely their high temporal frequency, relative cheapness and low data volumes for image processing, may readily be taken advantage of for such tasks.
Townshend, J. R. G.↗
Validation of Land Cover Maps Utilizing Astronaut Acquired Imagery
This report is produced in accordance with the requirements outlined in the NASA Research Grant NAG9-1032 titled "Validation of Land Cover Maps Utilizing Astronaut Acquired Imagery". This grant funds the Remote Sensing Research Unit of the University of California, Santa Barbara. This document summarizes the research progress and accomplishments to date and describes current on-going research activities. Even though this grant has technically expired, in a contractual sense, work continues on this project. Therefore, this summary will include all work done through and 5 May 1999. The principal goal of this effort is to test the accuracy of a sub-regional portion of an AVHRR-based land cover product. Land cover mapped to three different classification systems, in the southwestern United States, have been subjected to two specific accuracy assessments. One assessment utilizing astronaut acquired photography, and a second assessment employing Landsat Thematic Mapper imagery, augmented in some cases, high aerial photography. Validation of these three land cover products has proceeded using a stratified sampling methodology. We believe this research will provide an important initial test of the potential use of imagery acquired from Shuttle and ultimately the International Space Station (ISS) for the operational validation of the Moderate Resolution Imaging Spectrometer (MODIS) land cover products.
Estes, John E.↗
Validation of Satellite Snow Cover Maps in North America and Norway
Satellite-derived snow maps from NASA's Earth Observing System Moderate Resolution Imaging Spectroradiometer (MODIS) have been produced since February of 2000. The global maps are available daily at 500-m resolution, and at a climate-modeling grid (CMG) resolution of 1/20 deg (approximately 5.6 km). We compared the 8-day composite CMG MODIS-derived global maps from November 1,2001, through March 21,2002, and daily CMG maps from February 26 - March 5,2002, with National Oceanic and Atmospheric Administration (NOAA) Interactive Multisensor Snow and Ice Mapping System (IMS) 25-km resolution maps for North America. For the Norwegian study area, national snow maps, based on synoptic measurements as well as visual interpretation of AVHRR images, published by the Det Norske Meteorologiske Institutt (Norwegian Meteorological Institute) (MI) maps, as well as Landsat ETM+ images were compared with the MODIS maps. The MODIS-derived maps agreed over most areas with the IMS or MI maps, however, there are important areas of disagreement between the maps, especially when the 8-day composite maps were used. It is concluded that MODIS daily CMG maps should be studied for validation purposes rather than the 8-day composite maps, despite the limitations imposed by cloud obscuration when using the daily maps.
Hall, Dorothy K.↗
Comparison of Model Prediction with Measurements of Galactic Background Noise at L-Band
The spectral window at L-band (1.413 GHz) is important for passive remote sensing of surface parameters such as soil moisture and sea surface salinity that are needed to understand the hydrological cycle and ocean circulation. Radiation from celestial (mostly galactic) sources is strong in this window and an accurate accounting for this background radiation is often needed for calibration. Modem radio astronomy measurements in this spectral window have been converted into a brightness temperature map of the celestial sky at L-band suitable for use in correcting passive measurements. This paper presents a comparison of the background radiation predicted by this map with measurements made with several modem L-band remote sensing radiometers. The agreement validates the map and the procedure for locating the source of down-welling radiation.
LeVine, David M.↗
The LuNaMaps Project: Advancing Capabilities for Developing and Validating Digital Elevation Models of Rocky Surfaces from Orbital Data
Both navigation and surface science can benefit from the ability to generate high resolution and accurate maps of the surface of the Moon and other solar system bodies. The primary way these maps are generated is through the use of orbital imagery and ranging data. Traditionally, the process of using orbital imagery and ranging data is tedious and labor-intensive. Additionally, once maps have been built, there has generally been limited effort in developing standards by which to verify the accuracy and quality of the generated maps. The Lunar Navigation Maps (LuNaMaps) project is a NASA Game Changing Development (GCD) project which over the last 4 years has aimed to address these issues both for the Moon and for other rocky solar system bodies. This has been accomplished through development of new and existing capabilities including: a suite of methods and tools to combine all sources of orbital imagery; a benchmark data set as well as basic requirements for high-fidelity simulations of precision landing functions; tools to synthetically enhance map products with lander-scale features for use in the development and testing of hazard detection systems; methods and tools to evaluate the accuracy of developed digital elevation maps (DEMs) and their quality for use in terrain relative navigation scenarios; and tools to realistically render image and lidar data. In this work, we provide an overview of the capabilities developed through LuNaMaps, demonstrating its use for processing existing lunar data, and describing how it can be applied to other use cases. We additionally provide preliminary results showing the application of the developed tools and processes to the generation of elevation maps of the Lunar Surface Proving Grounds (LSPG) lunar analog at Astrobotic’s Mojave testing facility using “orbital imagery” captured by a drone. In this terrestrial demonstration, we have the benefit of being able to compare the results to a ground truth model of the LSPG. We finally describe plans to use the newly created maps in a terrestrial terrain relative navigation demonstration over the LSPG in early 2025.
optical navigation↗
Georgia Disasters II: Evaluating the Impacts of Hurricane Irma on Georgia Heirs Property Owners Using NASA Earth Observations
Heirs property owners are especially vulnerable to natural and manmade disasters. This group of people have inherited property left with no clear title and thus have unclear group ownership with the other legal owners, which are all spouses, children, etc. of past owners. After Hurricane Irma made landfall in Georgia in September of 2017, heirs property owners became more likely to be denied access to federal relief due to the legal status of their property title. To observe how this group was impacted by Hurricane Irma, the NASA DEVELOP team partnered with The Georgia Heirs Property Law Center (The Center), a non-profit law firm that works with heirs properties owners. The team used computer assisted mass appraisal (CAMA) data to identify likely heirs property owners. They cross referenced this map with a flood map produced with surface reflectance and backscatter imagery from Landsat 8 OLI, Sentinel-2 MSI, and Sentinel-1 C-SAR, sensors to identify communities in need of relief or assistance. The flood extent maps were validated against United States Geological Survey (USGS) Hurricane Irma High Water Mark in situ data taken the same day Irma crossed into Georgia. To further evaluate the impacted group, the team correlated the flood and heirs property likelihood maps to FEMA denials based on titles issues. The team’s end products were handed off to the Georgia Heirs Property Law Center for use in community outreach, educational materials, and to help direct where The Center can work to prioritize its limited legal resources.
Shakirah Rogers↗
Resolution Enhancement of MODIS-Derived Water Indices for Studying Persistent Flooding
Monitoring coastal marshes for persistent flooding and salinity stress is a high priority issue in Louisiana. Remote sensing can identify environmental variables that can be indicators of marsh habitat conditions, and offer timely and relatively accurate information for aiding wetland vegetation management. Monitoring activity accuracy is often limited by mixed pixels which occur when areas represented by the pixel encompasses more than one cover type. Mixtures of marsh grasses and open water in 250m Moderate Resolution Imaging Spectroradiometer (MODIS) data can impede flood area estimation. Flood mapping of such mixtures requires finer spatial resolution data to better represent the cover type composition within 250m MODIS pixel. Fusion of MODIS and Landsat can improve both spectral and temporal resolution of time series products to resolve rapid changes from forcing mechanisms like hurricane winds and storm surge. For this study, using a method for estimating sub-pixel values from a MODIS time series of a Normalized Difference Water Index (NDWI), using temporal weighting, was implemented to map persistent flooding in Louisiana coastal marshes. Ordinarily NDWI computed from daily 250m MODIS pixels represents a mixture of fragmented marshes and water. Here, sub-pixel NDWI values were derived for MODIS data using Landsat 30-m data. Each MODIS pixel was disaggregated into a mixture of the eight cover types according to the classified image pixels falling inside the MODIS pixel. The Landsat pixel means for each cover type inside a MODIS pixel were computed for the Landsat data preceding the MODIS image in time and for the Landsat data succeeding the MODIS image. The Landsat data were then weighted exponentially according to closeness in date to the MODIS data. The reconstructed MODIS data were produced by summing the product of fractional cover type with estimated NDWI values within each cover type. A new daily time series was produced using both the reconstructed 250-m MODIS, with enhanced features, and the approximated daily 30-m high-resolution image based on Landsat data. The algorithm was developed and tested over the Calcasieu-Sabine Basin, which was heavily inundated by storm surge from Hurricane Ike to study the extent and duration of flooding following the storm. Time series for 2000-2009, covering flooding events by Hurricane Rita in 2005 and Hurricane Ike in 2008, were derived. High resolution images were formed for all days in 2008 between the first cloud free Landsat scene and the last cloud-free Landsat scene. To refine and validate flooding maps, each time series was compared to Louisiana Coastwide Reference Monitoring System (CRMS) station water levels adjusted to marsh to optimize thresholds for MODIS-derived time series of NDWI. Seasonal fluctuations were adjusted by subtracting ten year average NDWI for marshes, excluding the hurricane events. Results from different NDWI indices and a combination of indices were compared. Flooding persistence that was mapped with higher-resolution data showed some improvement over the original MODIS time series estimates. The advantage of this novel technique is that improved mapping of extent and duration of inundation can be provided.
Underwood, L. W.↗