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At least 757 records · Page 42
All sourcesNASA NTRSDOE OSTI
NASA NTRS1974

The use of multispectral difference data for urban change detection

The current work describes an experiment in which ERTS-1 digital multispectral scanner data from two times was used to detect change in an urban scene. The computer analysis implementation approach explored here was to register image data from the two times and to subtract the data to form multispectral difference images. The difference imagery was then analyzed using statistical pattern recognition to separate and classify different types of change. Construction was successfully detected.

Anuta, P. E.↗
NASA NTRS1989

Shade images of forested areas obtained from LANDSAT MSS data

The pixel size in the present day Remote Sensing systems is large enough to include different types of land cover. Depending upon the target area, several components may be present within the pixel. In forested areas, generally, three main components are present: tree canopy, soil (understory), and shadow. The objective is to generate a shade (shadow) image of forested areas from multispectral measurements of LANDSAT MSS (Multispectral Scanner) data by implementing a linear mixing model, where shadow is considered as one of the primary components in a pixel. The shade images are related to the observed variation in forest structure, i.e., the proportion of inferred shadow in a pixel is related to different forest ages, forest types, and tree crown cover. The Constrained Least Squares (CLS) method is used to generate shade images for forest of eucalyptus and vegetation of cerrado using LANDSAT MSS imagery over Itapeva study area in Brazil. The resulted shade images may explain the difference on ages for forest of eucalyptus and the difference on three crown cover for vegetation of cerrado.

Shimabukuro, Yosio Edemir↗
NASA NTRS1973

In situ spectroradiometric quantification of ERTS data

The task of correlating in situ spectral reflectance measurements with ERTS imagery has commenced. A method of additive color analysis of a single multispectral band taken on different dates indicates that ERTS-1 bulk images have sufficient spatial and spectral fidelity to show indications of the presence of soil moisture in desert playas and changes in soil moisture with time. The chain of causality between soil moisture, in situ spectral reflectance, and ERTS multispectral scanner image density remains to be established during the subsequent phases of this study.

Yost, E.↗
NASA NTRS1987

Multispectral remote sensing as stratigraphic and structural tool, Wind River Basin and Big Horn Basin areas, Wyoming

The use of Landsat TM, Airborne Imaging Spectrometer, and airborne Thermal IR Multispectral Scanner data in the geological evaluation of two sites in central Wyoming is described and illustrated with diagrams, maps, photographs, sample images, and tables of numerical data. The value of the remotely sensed information on the areal variation of attitude, sequence, thickness, and lithology of exposed strata is demonstrated; details of the data analysis are given; and the specialized software packages employed are briefly characterized.

Lang, Harold R.↗
NASA NTRS1983

Geometric and radiometric characterization of LANDSAT-D thematic mapper and multispectral scanner data

A geometrically raw image of Washington, D.C. was acquired and radiometrically corrected. The data show little of the detector stripping common in earlier MSS images. The radiometrically corrected data have uniform means and standard deviations for the detectors in each band; however, the data for different detectors utilize a different pattern of DN levels, resulting in ubiquitous stripping of 1 DN amplitude. Band-to-band registration was assessed using color composites and small area correlation techniques. The spectral equivalency of the first four bands of the thematic mapper with the four bands of the MSS is being examined. Geometric analysis of the Washington, D.C. scene have started and a generalized routine for examining the contents of the label files and nonvideo data files was implemented. Several discrepancies from the documentation are described. Night scenes and daytime ocean scenes required for radiometric purposes were identified and the data ordered.

Kieffer, H. H.↗
NASA NTRS1984

Evaluation of Landsat-4 Thematic Mapper and multispectral scanner data quality

Landsat-4 image data quality was evaluated for test sites in Iowa and Illinois. Radiometric and geometric quality was tested and an applications evaluation was carried out using a cooling-pond thermal-mapping example. Geometric quality was found to be generally very good. Small errors were found in registration of the middle IR bands of the TM and the thermal IR band was found to be misregistered by one 120-meter pixel. Radiometric quality of the TM is excellent with only minor striping effects.

Bartolucci, L. A.↗
NASA NTRS2005

Mapping variations in weight percent silica measured from multispectral thermal infrared imagery - Examples from the Hiller Mountains, Nevada, USA and Tres Virgenes-La Reforma, Baja California Sur, Mexico

Remotely sensed multispectral thermal infrared (8-13 mu m) images are increasingly being used to map variations in surface silicate mineralogy. These studies utilize the shift to longer wavelengths in the main spectral feature in minerals in this wavelength region (reststrahlen band) as the mineralogy changes from felsic to mafic. An approach is described for determining the amount of this shift and then using the shift with a reference curve, derived from laboratory data, to remotely determine the weight percent SiO2 of the surface. The approach has broad applicability to many study areas and can also be fine-tuned to give greater accuracy in a particular study area if field samples are available. The approach was assessed using airborne multispectral thermal infrared images from the Hiller Mountains, Nevada, USA and the Tres Virgenes-La Reforma, Baja California Sur, Mexico. Results indicate the general approach slightly overestimates the weight percent SiO2 of low silica rocks (e.g. basalt) and underestimates the weight percent SiO2 of high silica rocks (e.g. granite). Fine tuning the general approach with measurements from field samples provided good results for both areas with errors in the recovered weight percent SiO2 of a few percent. The map units identified by these techniques and traditional mapping at the Hiller Mountains demonstrate the continuity of the crystalline rocks from the Hiller Mountains southward to the White Hills supporting the idea that these ranges represent an essentially continuous footwall block

Stock, Joann M.↗
NASA NTRS1973

Land use mapping and modelling for the Phoenix Quadrangle

The author has identified the following significant results. The land use of the Phoenix Quadrangle in Arizona had been mapped previously from aerial photographs and recorded in a computer data bank. During the ERTS experiment, changes in land use were detected, first with the ERTS-simulation photographs, then with the ERTS-1 images when they became available. In each case, the I2S color additive viewer was used as the primary image enhancement tool, operated in a multispectral mode. A search was made for a method of creating hard copy color composite images of the best combinations of multiband composites from ERTS-1, mostly by photographic and diazo processes. The I2S viewer was also used to enhance changes between successive images by quick flip techniques or by registering with different color filters. Improved interpretation of land use change resulted, and a map of changes in the Phoenix Quadrangle was compiled using magnified ERTS-1 images alone. The first level of a standard land use classification system was successfully used. Between the ERTS-1 images for August and November, some differences were detected that could be caused by seasonal characteristics of vegetation or by change in use.

Place, J. L.↗
NASA NTRS2024

Cape Hatteras Ecological Conservation: Delineating Shoreline and Mapping Change Along the Cape Hatteras National Seashore for Coastline Management and Transportation Corridor Adaptation Strategies

The National Park Service at Cape Hatteras National Seashore works to protect North Carolina’s Outer Banks where frequent storms bring heavy winds and flooding, leading to overwash events on the main highway, North Carolina Highway 12. Shorelines are susceptible to erosion directly affecting transportation and housing infrastructures. Storm events can disrupt transportation on NC-12 and ferry service from Ocracoke Island to Hatteras Island, leaving inhabitants stranded on Ocracoke Island for indefinite amounts of time. The National Park Service’s current decision-making practices involve mitigating infrastructure damage by enlisting the help of North Carolina’s Department of Transportation and finding ways to relocate this infrastructure, as well as dredging and sediment placement that support beach nourishment efforts. Our NASA DEVELOP team partnered with the National Park Service to explore the use of optical data to delineate shoreline and map coastline change from 2014 to 2024. We used Earth observations collected by Landsat 8 Operational Land Imager, Landsat 9 Operational Land Imager-2, and Sentinel-2 MultiSpectral instrument to support decision-making related to prioritizing strategic planning for transportation corridor adaptations including potential relocation of infrastructure, and beach nourishment efforts. We derived coastline maps by consolidating images from each year to create composite images for winter and summer coastline seasonal oscillation patterns. The results highlight shoreline loss over the ~10-year study period, and the difference in shoreline inundation in the winter and summer seasons. These observations create a better understanding of successful mitigation efforts and allow the National Park Service to continue to focus on plans for infrastructure updates.

Ella Haugen↗
NASA NTRS2011

High Speed, Multi-Channel, Thermal Instrument Development in Support of HyspIRI-TIR

The Jet Propulsion Laboratory is currently developing an end-to-end instrument which will provide a proof of concept prototype vehicle for a high data rate, multi-channel, thermal instrument in support of the Hyperspectral Infrared Imager (HyspIRI)-Thermal Infrared (TIR) space mission. HyspIRI mission was recommended by the National Research Council Decadal Survey (DS). The HyspIRI mission includes a visible shortwave infrared (SWIR) pushboom spectrometer and a multispectral whiskbroom thermal infrared (TIR) imager. The prototype testbed instrument addressed in this effort will only support the TIR. Data from the HyspIRI mission will be used to address key science questions related to the Solid Earth and Carbon Cycle and Ecosystems focus areas of the NASA Science Mission Directorate. Current designs for the HyspIRI-TIR space borne imager utilize eight spectral bands delineated with filters. The system will have 60m ground resolution, 200mK NEDT, 0.5C absolute temperature resolution with a 5-day repeat from LEO orbit. The prototype instrument will use mercury cadmium telluride (MCT) technology at the focal plane array in time delay integration mode. A custom read out integrated circuit (ROIC) will provide the high speed readout hence high data rates needed for the 5 day repeat. The current HyspIRI requirements dictate a ground knowledge measurement of 30m, so the prototype instrument will tackle this problem with a newly developed interferometeric metrology system. This will provide an absolute measurement of the scanning mirror to an order of magnitude better than conventional optical encoders. This will minimize the reliance on ground control points hence minimizing postprocessing (e.g. geo-rectification computations).

Multi-spectral↗
NASA NTRS1990

Imaging spectroscopy of the terrestrial environment; Proceedings of the Meeting, Orlando, FL, Apr. 16, 17, 1990

Topics presented include the evolution of the Airborne Visible/Infrared Imaging Spectrometer flight and ground data processing system, direct mineral identification with Geoscan Mk II Advanced Multispectral Scanner, a new approach to imaging spectroscopy, and a linear-wedge spectrometer. Also presented are the effects of moisture content and chemical composition on the near-infrared spectra of forest foliage, change detection in vegetation using 1989 AVIRIS data, and the inversion of high-spectral-resolution data.

Vane, Gregg↗
NASA NTRS1977

Techniques for the creation of land use maps and tabulations from Landsat imagery

Methods for creating color thematic maps and land use tabulations, employing both Landsat imagery and computer image processing, are discussed. The system, the Multiple Input Land Use System (MILUS) has been tested in the metropolitan section of Dayton, Ohio. Training areas for land use were first digitized by coordinates and then transformed onto an image of white lines on a black background. This image was added to a Landsat image of the same area. Then multispectral classification was performed. A tape of digitized census tract boundaries was computer interfaced to yield an image of tract boundaries on a background registered to the thematic land-use map. Using a data management system, the data were then used to produce figures for the area and percent of land use in each tract. Future work is expected to convert most of the steps into interactive processing. This would greatly reduce the time needed to edit and register the data sets.

Angelici, G. L.↗
NASA NTRS1998

Get the Picture?

Positive Systems has worked in conjunction with Stennis Space Center to design the ADAR System 5500. This is a four-band airborne digital imaging system used to capture multispectral imagery similar to that available from satellite platforms such as Landsat, SPOT and the new generation of high resolution satellites. Positive Systems has provided remote sensing services for the development of digital aerial camera systems and software for commercial aerial imaging applications.

Source record↗
NASA NTRS1993

Earth imaging results from Galileo's second encounter

The recent flyby of the Galileo spacecraft en route to Jupiter contributes a unique perspective to our view of our home planet. Imaging activities conducted during the second Earth encounter provide an important opportunity to assess new methods and approaches on familiar territory. These include unique multispectral observations, low light-level imaging (searches for aurorae, lightning and artificial lights on the nightside) and experiments with multiple exposure times to extend the effective radiometric resolution and dynamic range of the camera system. Galileo imaging data has the potential to make important contributions to terrestrial remote sensing. This is because the particular set of filters included in the Solid State Imaging system are not presently incorporated in any currently operating Earth-orbiting sensor system. The visible/near-infrared bandpasses of the SSI filters are well suited to remote sensing of geological, glaciological, botanical, and meteorological phenomena. Data from this and the previous Earth encounter may provide an extremely valuable reference point in time for comparison with similar data expected from EOS or other systems in the future, contributing directly to our knowledge of global change. The highest resolution imaging (0.2 km/pixel) during the December, 1992 encounter occurred over the central Andes; a five filter mosaic of visible and near infrared bands displays the remarkable spectral heterogeneity of this geologically diverse region. As Galileo departed the Earth, cooperative imaging with the Near Infrared Mapping Spectrometer (NIMS) instrument targeted Antarctica, Australia, and Indonesia at 1.0 to 2.5 km/pixel resolutions in the early morning local times near the terminator. The Antarctic data are of particular interest, potentially allowing ice grain size mapping using the 889 and 968 nm filters and providing an important means of calibrating the technique for application to the Galilean satellites. As the spacecraft receded further, regional scale imaging provided data which, along with data from the previous encounter, will enable the production of global multispectral mosaics of Earth in each of the SSI filters.

Greenberg, R.↗
NASA NTRS1974

Scene correction (precision techniques) of ERTS sensor data using digital image processing techniques

Techniques have been developed, implemented, and evaluated to process ERTS Return Beam Vidicon (RBV) and Multispectral Scanner (MSS) sensor data using digital image processing techniques. The RBV radiometry has been corrected to remove shading effects, and the MSS geometry and radiometry have been corrected to remove internal and external radiometric and geometric errors. The results achieved show that geometric mapping accuracy of about one picture element RMS and two picture elements (maximum) can be achieved by the use of nine ground control points. Radiometric correction of MSS and RBV sensor data has been performed to eliminate striping and shading effects to about one count accuracy. Image processing times on general purpose computers of the IBM 370/145 to 168 class are in the range of 29 to 3.2 minutes per MSS scene (4 bands). Photographic images of the fully corrected and annotated scenes have been generated from the processed data and have demonstrated excellent quality and information extraction potential.

Bernstein, R.↗
DOE OSTI2020

Mapping Vegetation at Species Level with High-Resolution Multispectral and Lidar Data Over a Large Spatial Area: A Case Study with Kudzu

Mapping vegetation species is critical to facilitate related quantitative assessment, and mapping invasive plants is important to enhance monitoring and management activities. Integrating high-resolution multispectral remote-sensing (RS) images and lidar (light detection and ranging) point clouds can provide robust features for vegetation mapping. However, using multiple sources of high-resolution RS data for vegetation mapping on a large spatial scale can be both computationally and sampling intensive. Here, we designed a two-step classification workflow to potentially decrease computational cost and sampling effort and to increase classification accuracy by integrating multispectral and lidar data in order to derive spectral, textural, and structural features for mapping target vegetation species. We used this workflow to classify kudzu, an aggressive invasive vine, in the entire Knox County (1362 km2) of Tennessee (U.S.). Object-based image analysis was conducted in the workflow. The first-step classification used 320 kudzu samples and extensive, coarsely labeled samples (based on national land cover) to generate an overprediction map of kudzu using random forest (RF). For the second step, 350 samples were randomly extracted from the overpredicted kudzu and labeled manually for the final prediction using RF and support vector machine (SVM). Computationally intensive features were only used for the second-step classification. SVM had constantly better accuracy than RF, and the producer’s accuracy, user’s accuracy, and Kappa for the SVM model on kudzu were 0.94, 0.96, and 0.90, respectively. SVM predicted 1010 kudzu patches covering 1.29 km2 in Knox County. We found the sample size of kudzu used for algorithm training impacted the accuracy and number of kudzu predicted. The proposed workflow could also improve sampling efficiency and specificity. Our workflow had much higher accuracy than the traditional method conducted in this research, and could be easily implemented to map kudzu in other regions as well as map other vegetation species.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2021

Spectral Synthesis for Geostationary Satellite-to-Satellite Translation

Earth-observing satellites carrying multispectral sensors are widely used to monitor the physical and biological states of the atmosphere, land, and oceans. These satellites have different vantage points above the Earth and different spectral imaging bands resulting in inconsistent imagery from one to another. This presents challenges in building downstream applications. What if we could generate synthetic bands for existing satellites from the union of all domains? We tackle the problem of generating synthetic spectral imagery for multispectral sensors as an unsupervised image-to-image translation problem modeled with a variational autoencoder (VAE) and generative adversarial network (GAN) architecture. Our approach introduces a novel shared spectral reconstruction loss to constrain the high-dimensional feature space of multispectral images. Simulated experiments performed by dropping one or more spectral bands show that cross-domain reconstruction outperforms measurements obtained from a second vantage point. Our proposed approach enables the synchronization of multispectral data and provides a basis for more homogeneous remote sensing datasets.

Geostationary satellites↗