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At least 307 records · Page 17

Analysis and quantification of errors in the geometric correction of satellite images

The quantitative use of remote sensing satellite images in many applications requires that the geometric distortion inherent in these images be corrected, or rectified, to a desired map projection. The most widely used technique relies on ground control points to empirically determine a mathematical coordinate transformation to correct the geometry. In this paper, using the method of least squares, expressions for the accuracy of the geometric transformation and of the rectification of the satellite image to a map projection are derived. Explicit relations between the global accuracy of the transformation and the number, location, and local accuracy of the ground control points are obtained. The results are applied to the correction of a Landsat MSS image.

Ford, G. E.↗

Hierarchical Image Segmentation of Remotely Sensed Data using Massively Parallel GNU-LINUX Software

A hierarchical set of image segmentations is a set of several image segmentations of the same image at different levels of detail in which the segmentations at coarser levels of detail can be produced from simple merges of regions at finer levels of detail. In [1], Tilton, et a1 describes an approach for producing hierarchical segmentations (called HSEG) and gave a progress report on exploiting these hierarchical segmentations for image information mining. The HSEG algorithm is a hybrid of region growing and constrained spectral clustering that produces a hierarchical set of image segmentations based on detected convergence points. In the main, HSEG employs the hierarchical stepwise optimization (HSWO) approach to region growing, which was described as early as 1989 by Beaulieu and Goldberg. The HSWO approach seeks to produce segmentations that are more optimized than those produced by more classic approaches to region growing (e.g. Horowitz and T. Pavlidis, [3]). In addition, HSEG optionally interjects between HSWO region growing iterations, merges between spatially non-adjacent regions (i.e., spectrally based merging or clustering) constrained by a threshold derived from the previous HSWO region growing iteration. While the addition of constrained spectral clustering improves the utility of the segmentation results, especially for larger images, it also significantly increases HSEG s computational requirements. To counteract this, a computationally efficient recursive, divide-and-conquer, implementation of HSEG (RHSEG) was devised, which includes special code to avoid processing artifacts caused by RHSEG s recursive subdivision of the image data. The recursive nature of RHSEG makes for a straightforward parallel implementation. This paper describes the HSEG algorithm, its recursive formulation (referred to as RHSEG), and the implementation of RHSEG using massively parallel GNU-LINUX software. Results with Landsat TM data are included comparing RHSEG with classic region growing.

Tilton, James C.↗

Compensation for Spherical Geometric and Absorption Effects on Lower Thermospheric Emission Intensities Derived from High Earth Orbit Images

Remote sensing of the atmosphere from high earth orbit is very attractive due to the large field of view obtained and a true global perspective. This viewpoint is complicated by earth curvature effects so that slant path enhancement and absorption effects, small from low earth orbit, become dominant even at small nadir view angles. The effect is further complicated by the large range of local times and solar zenith angles in a single image leading to a modulation of the image intensity by a significant portion of the diurnal height variation of the absorbing layer. The latter effect is significant in particular for mesospheric, stratospheric and auroral emissions due to their depth in the atmosphere. As a particular case, the emissions from atomic oxygen (130.4 and 135.6 nm) and molecular nitrogen (two LBH bands, LBHS from 140 to 160 nm and LBHL from 160 to 180 nm) as viewed from the Ultraviolet Imager (UVI) are examined. The LBH emissions are of particular interest since LBHS has significant 02 absorption while LBHL does not, In the case of auroral emissions this differential absorption, well examined in the nadir, gives information about the height of the emission and therefore the energy of the precipitating particles. Using simulations of the viewing geometry and images from the UVI we examine these effects and obtain correction factors to adjust to the nadir case with a significant improvement of the derived characteristic energy. There is a surprisingly large effect on the images from the 02 diurnal layer height changes. An empirical compensation to the nadir case is explored based on the local nadir and local zenith angles for each portion of the image. These compensations are demonstrated as applied to the above emissions in both auroral and dayglow images and compared to models. The extension of these findings to other instruments, emissions and spectral regions is examined.

Swift, W.↗

Multispectral Snapshot Imagers Onboard Small Satellite Formations for Multi-Angular Remote Sensing

Multispectral snapshot imagers are capable of producing 2D spatial images with a single exposure at selected, numerous wavelengths using the same camera, therefore operate differently from push broom or whiskbroom imagers. They are payloads of choice in multi-angular, multi-spectral imaging missions that use small satellites flying in controlled formation, to retrieve Earth science measurements dependent on the targets Bidirectional Reflectance-Distribution Function (BRDF). Narrow fields of view are needed to capture images with moderate spatial resolution. This paper quantifies the dependencies of the imagers optical system, spectral elements and camera on the requirements of the formation mission and their impact on performance metrics such as spectral range, swath and signal to noise ratio (SNR). All variables and metrics have been generated from a comprehensive, payload design tool. The baseline optical parameters selected (diameter 7 cm, focal length 10.5 cm, pixel size 20 micron, field of view 1.15 deg) and snapshot imaging technologies are available. The spectral components shortlisted were waveguide spectrometers, acousto-optic tunable filters (AOTF), electronically actuated Fabry-Perot interferometers, and integral field spectrographs. Qualitative evaluation favored AOTFs because of their low weight, small size, and flight heritage. Quantitative analysis showed that waveguide spectrometers perform better in terms of achievable swath (10-90 km) and SNR (greater than 20) for 86 wavebands, but the data volume generated will need very high bandwidth communication to downlink. AOTFs meet the external data volume caps well as the minimum spectral (wavebands) and radiometric (SNR) requirements, therefore are found to be currently feasible in spite of lower swath and SNR.

Nag, Sreeja↗

Electron-bombarded CCD detectors for ultraviolet atmospheric remote sensing

Electronic image sensors based on charge coupled devices operated in electron-bombarded mode, yielding real-time, remote-readout, photon-limited UV imaging capability are being developed. The sensors also incorporate fast-focal-ratio Schmidt optics and opaque photocathodes, giving nearly the ultimate possible diffuse-source sensitivity. They can be used for direct imagery of atmospheric emission phenomena, and for imaging spectrography with moderate spatial and spectral resolution. The current state of instrument development, laboratory results, planned future developments and proposed applications of the sensors in space flight instrumentation is described.

Carruthers, G. R.↗

Airborne Remote Sensing

NASA imaging technology has provided the basis for a commercial agricultural reconnaissance service. AG-RECON furnishes information from airborne sensors, aerial photographs and satellite and ground databases to farmers, foresters, geologists, etc. This service produces color "maps" of Earth conditions, which enable clients to detect crop color changes or temperature changes that may indicate fire damage or pest stress problems.

Source record↗

Coherent optical imaging of moving objects hidden in a heavily scattering random medium

Experimental results are presented that provide insight into the physics of statistical imaging in heavily scattering random media based on measured speckle correlations as a function of the change in position of a moving object. In this way, definitive interpretation of a rather complex and earlier theory is achieved, making this work an experimental complement to that theory paper []. Motion could be natural, where the set of positions is estimated or separately obtained, or directed, where a mechanical stage can be used to adjust the object's position. In the experiment, a coherent laser illuminates two scattering diffusers, while an object is translated between them in the resulting speckled field and images are collected in a transmission configuration. Results are shown for various objects of differing size and geometry, allowing the theory to be validated and interpreted with new understanding. This work demonstrates imaging opportunities, and applications include material characterization, environmental imaging and sensing, and deep-tissue imaging. Published by the American Physical Society 2025

Hastings, Ryan L. (ORCID:0009000095977807)↗

Wavelength tunable liquid crystal imaging filters for remote sensing from geosynchronous platforms

Recent advances in liquid crystal technology have enabled us to construct tunable birefringent filters with bandwidths between approximately 0.1 nm and 50 nm. The center wavelength of these filters can be selected electronically, in a few tens of milliseconds, with no moving parts. These liquid crystal tunable filters (LCTF's), together with existing CCD detectors, make possible a new generation of lightweight, rugged, high-resolution imaging spectrophotometers. Such instruments would be particularly interesting for remote sensing applications from geosynchronous platforms. Important advantages exist in the aperture, absence of image shift, power consumption, size, weight, and absence of high drive frequencies, compared to current instruments used or considered for multispectral scene analysis. In the present work, we have reviewed spectral requirements of planned NASA geosynchronous remote sensing missions and identified several applications of the liquid crystal tunable filter technology. We have modeled the LCTF performance in the visible and near-infrared, and carried out a literature study on space-hardening of the filter components, to evaluate the suitability of LCTF's for geosynchronous missions. We have also compared the power consumption, weight, size, reliability, and optical performance of an imaging spectrophotometer using a LCTF monochromator, to other instruments that have been put forward for remote sensing from geosynchronous platforms. We put forward some conceptual designs for LCTF's that seem to offer important reliability, over the mechanical filter wheels presently baselined for the HEPI and ALM experiments. The extremely wide acceptance angle achievable with LCTF's could also avoid the present need for large-aperture interference filters in the ALM (and LIS) experiments. Thermal vacuum testing and radiation damage analysis is required to investigate the space hardening of these new filters for geosynchronous flight.

Foukal, Peter↗

NeMO-Net & Fluid Lensing: The Neural Multi-Modal Observation & Training Network for Global Coral Reef Assessment Using Fluid Lensing Augmentation of NASA EOS Data

We present preliminary results from NASA NeMO-Net, the first neural multi-modal observation and training network for global coral reef assessment. NeMO-Net is an open-source deep convolutional neural network (CNN) and interactive active learning training software in development which will assess the present and past dynamics of coral reef ecosystems. NeMO-Net exploits active learning and data fusion of mm-scale remotely sensed 3D images of coral reefs captured using fluid lensing with the NASA FluidCam instrument, presently the highest-resolution remote sensing benthic imaging technology capable of removing ocean wave distortion, as well as hyperspectral airborne remote sensing data from the ongoing NASA CORAL mission and lower-resolution satellite data to determine coral reef ecosystem makeup globally at unprecedented spatial and temporal scales. Aquatic ecosystems, particularly coral reefs, remain quantitatively misrepresented by low-resolution remote sensing as a result of refractive distortion from ocean waves, optical attenuation, and remoteness. Machine learning classification of coral reefs using FluidCam mm-scale 3D data show that present satellite and airborne remote sensing techniques poorly characterize coral reef percent living cover, morphology type, and species breakdown at the mm, cm, and meter scales. Indeed, current global assessments of coral reef cover and morphology classification based on km-scale satellite data alone can suffer from segmentation errors greater than 40%, capable of change detection only on yearly temporal scales and decameter spatial scales, significantly hindering our understanding of patterns and processes in marine biodiversity at a time when these ecosystems are experiencing unprecedented anthropogenic pressures, ocean acidification, and sea surface temperature rise. NeMO-Net leverages our augmented machine learning algorithm that demonstrates data fusion of regional FluidCam (mm, cm-scale) airborne remote sensing with global low-resolution (m, km-scale) airborne and spaceborne imagery to reduce classification errors up to 80% over regional scales. Such technologies can substantially enhance our ability to assess coral reef ecosystems dynamics.

satellite data↗

NASA NeMO-Net

We present preliminary results from NASA NeMO-Net, the first neural multi-modal observation and training network for global coral reef assessment. NeMO-Net is an open-source deep convolutional neural network (CNN) and interactive active learning training software in development which will assess the present and past dynamics of coral reef ecosystems. NeMO-Net exploits active learning and data fusion of mm-scale remotely sensed 3D images of coral reefs captured using fluid lensing with the NASA FluidCam instrument, presently the highest-resolution remote sensing benthic imaging technology capable of removing ocean wave distortion, as well as hyperspectral airborne remote sensing data from the ongoing NASA CORAL mission and lower-resolution satellite data to determine coral reef ecosystem makeup globally at unprecedented spatial and temporal scales. Aquatic ecosystems, particularly coral reefs, remain quantitatively misrepresented by low- resolution remote sensing as a result of refractive distortion from ocean waves, optical attenuation, and remoteness. Machine learning classification of coral reefs using FluidCam mm-scale 3D data show that present satellite and airborne remote sensing techniques poorly characterize coral reef percent living cover, morphology type, and species breakdown at the mm, cm, and meter scales. Indeed, current global assessments of coral reef cover and morphology classification based on km-scale satellite data alone can suffer from segmentation errors greater than 40%, capable of change detection only on yearly temporal scales and decameter spatial scales, significantly hindering our understanding of patterns and processes in marine biodiversity at a time when these ecosystems are experiencing unprecedented anthropogenic pressures, ocean acidification, and sea surface temperature rise. NeMO-Net leverages our augmented machine learning algorithm that demonstrates data fusion of regional FluidCam (mm, cm-scale) airborne remote sensing with global low-resolution (m, km-scale) airborne and spaceborne imagery to reduce classification errors up to 80% over regional scales. Such technologies can substantially enhance our ability to assess coral reef ecosystems dynamics.

NASA↗

Airborne Remote Sensing for Earth Science Applications

Topics covered include: Passive Remote Sensing Methods, Imaging Spectroscopy Approach, Remote Measurement via Spectral Fitting, Imaging Spectroscopy Mapping Wetland Dominants 2010 LA (AVIRIS), Deepwater Horizon Response I, Deepwater Horizon Response II, AVIRIS Ocean Color Studies.

AVIRIS: Airborne Imaging Spectrometer↗

Fusing 4D coded thermoacoustic, electromagnetic, and acoustic/seismic wavefields for subsurface characterization and imaging of fluid flow in porous media

This research program aims to address critical challenges in subsurface exploration and monitoring of anthropogenic CO 2 storage by advancing quantitative dynamic sensing and imaging technologies. Two primary applications—petrophysical assessment of hydrocarbon reservoirs (C1) and CO 2 storage monitoring (C2)—require significant innovation to overcome three barriers (B1-B3). These barriers include the need for enhanced understanding of interactions between physical wave fields (thermoacoustic, electromagnetic, acoustic/seismic, and X-ray) with fluid-filled porous media, the development of multi-sensor data fusion for real-time imaging, and upscaling microscopic quantum effects for macroscopic observations. The project’s objective was to establish a unified 4D coded sensing and imaging approach, integrating EM, AC/S, and TA fields for multi-scale and multi-physics material characterization and subsurface imaging.

58 GEOSCIENCES↗

Image reconstruction by parametric cubic convolution

Cubic convolution, which has been discussed by Rifman and McKinnon (1974), was originally developed for the reconstruction of Landsat digital images. In the present investigation, the reconstruction properties of the one-parameter family of cubic convolution interpolation functions are considered and thee image degradation associated with reasonable choices of this parameter is analyzed. With the aid of an analysis in the frequency domain it is demonstrated that in an image-independent sense there is an optimal value for this parameter. The optimal value is not the standard value commonly referenced in the literature. It is also demonstrated that in an image-dependent sense, cubic convolution can be adapted to any class of images characterized by a common energy spectrum.

Park, S. K.↗

High-resolution CCD imagers using area-array CCD's for sensing spectral components of an optical line image

CCD imagers with a novel replicated-line-imager architecture are abutted to form an extended line sensor. The sensor is preceded by optics having a slit aperture and having an optical beam splitter or astigmatic lens for projecting multiple line images through an optical color-discriminating stripe filter to the CCD imagers. A very high resolution camera suitable for use in a satellite, for example, is thus provided. The replicated-line architecture of the imager comprises an area-array CCD, successive rows of which are illuminated by replications of the same line segment, as transmitted by respective color filter stripes. The charge packets formed by accumulation of photoresponsive charge in the area-array CCD are read out row by row. Each successive row of charge packets is then converted from parallel to serial format in a CCD line register and its amplitude sensed to generate a line of output signal.

Elabd, Hammam↗

Plasmonics-Enhanced Optical Imaging Systems for Bioenergy Research

This final report summarizes the key accomplishments of the project entitled “Plasmonics-Enhanced Optical Imaging Systems for Bioenergy Research”. The goal of this project is aimed at developing innovative and improved imaging instrumentation for visualization and quantitative characterization of biomarkers related to molecular processes and cellular function in living plants. This project focused on three specific aims: 1) Development of Advanced Multimodal Optical Sensing And Imaging Combinatory (MOSAIC) System for SERS biosensing and bioimaging. 2) Evaluation of MOSAIC technologies for sensing and imaging gene expression in plant systems using plasmonic nanoprobes. 3) Application of MOSAIC techniques to bioenergy research.

47 OTHER INSTRUMENTATION↗

Procurement specification color graphic camera system

The performance and design requirements for a Color Graphic Camera System are presented. The system is a functional part of the Earth Observation Department Laboratory System (EODLS) and will be interfaced with Image Analysis Stations. It will convert the output of a raster scan computer color terminal into permanent, high resolution photographic prints and transparencies. Images usually displayed will be remotely sensed LANDSAT imager scenes.

Prow, G. E.↗

Polarization Imaging Apparatus with Auto-Calibration

A polarization imaging apparatus measures the Stokes image of a sample. The apparatus consists of an optical lens set, a first variable phase retarder (VPR) with its optical axis aligned 22.5 deg, a second variable phase retarder with its optical axis aligned 45 deg, a linear polarizer, a imaging sensor for sensing the intensity images of the sample, a controller and a computer. Two variable phase retarders were controlled independently by a computer through a controller unit which generates a sequential of voltages to control the phase retardations of the first and second variable phase retarders. A auto-calibration procedure was incorporated into the polarization imaging apparatus to correct the misalignment of first and second VPRs, as well as the half-wave voltage of the VPRs. A set of four intensity images, I(sub 0), I(sub 1), I(sub 2) and I(sub 3) of the sample were captured by imaging sensor when the phase retardations of VPRs were set at (0,0), (pi,0), (pi,pi) and (pi/2,pi), respectively. Then four Stokes components of a Stokes image, S(sub 0), S(sub 1), S(sub 2) and S(sub 3) were calculated using the four intensity images.

Zou, Yingyin Kevin↗