A New Pansharpening Method Based on Spatial and Spectral Sparsity Priors.

PubMed

He, Xiyan; Condat, Laurent; Bioucas-Diaz, Jose; Chanussot, Jocelyn; Xia, Junshi

2014-06-27

The development of multisensor systems in recent years has led to great increase in the amount of available remote sensing data. Image fusion techniques aim at inferring high quality images of a given area from degraded versions of the same area obtained by multiple sensors. This paper focuses on pansharpening, which is the inference of a high spatial resolution multispectral image from two degraded versions with complementary spectral and spatial resolution characteristics: a) a low spatial resolution multispectral image; and b) a high spatial resolution panchromatic image. We introduce a new variational model based on spatial and spectral sparsity priors for the fusion. In the spectral domain we encourage low-rank structure, whereas in the spatial domain we promote sparsity on the local differences. Given the fact that both panchromatic and multispectral images are integrations of the underlying continuous spectra using different channel responses, we propose to exploit appropriate regularizations based on both spatial and spectral links between panchromatic and the fused multispectral images. A weighted version of the vector Total Variation (TV) norm of the data matrix is employed to align the spatial information of the fused image with that of the panchromatic image. With regard to spectral information, two different types of regularization are proposed to promote a soft constraint on the linear dependence between the panchromatic and the fused multispectral images. The first one estimates directly the linear coefficients from the observed panchromatic and low resolution multispectral images by Linear Regression (LR) while the second one employs the Principal Component Pursuit (PCP) to obtain a robust recovery of the underlying low-rank structure. We also show that the two regularizers are strongly related. The basic idea of both regularizers is that the fused image should have low-rank and preserve edge locations. We use a variation of the recently proposed Split Augmented Lagrangian Shrinkage (SALSA) algorithm to effectively solve the proposed variational formulations. Experimental results on simulated and real remote sensing images show the effectiveness of the proposed pansharpening method compared to the state-of-the-art.

A Multispectral Image Creating Method for a New Airborne Four-Camera System with Different Bandpass Filters

PubMed Central

Li, Hanlun; Zhang, Aiwu; Hu, Shaoxing

2015-01-01

This paper describes an airborne high resolution four-camera multispectral system which mainly consists of four identical monochrome cameras equipped with four interchangeable bandpass filters. For this multispectral system, an automatic multispectral data composing method was proposed. The homography registration model was chosen, and the scale-invariant feature transform (SIFT) and random sample consensus (RANSAC) were used to generate matching points. For the difficult registration problem between visible band images and near-infrared band images in cases lacking manmade objects, we presented an effective method based on the structural characteristics of the system. Experiments show that our method can acquire high quality multispectral images and the band-to-band alignment error of the composed multiple spectral images is less than 2.5 pixels. PMID:26205264

High Spatial Resolution Commercial Satellite Imaging Product Characterization

NASA Technical Reports Server (NTRS)

Ryan, Robert E.; Pagnutti, Mary; Blonski, Slawomir; Ross, Kenton W.; Stnaley, Thomas

2005-01-01

NASA Stennis Space Center's Remote Sensing group has been characterizing privately owned high spatial resolution multispectral imaging systems, such as IKONOS, QuickBird, and OrbView-3. Natural and man made targets were used for spatial resolution, radiometric, and geopositional characterizations. Higher spatial resolution also presents significant adjacency effects for accurate reliable radiometry.

The investigation of classification methods of high-resolution imagery

Treesearch

Tracey S. Frescino; Gretchen G. Moisen; Larry DeBlander; Michel Guerin

2007-01-01

As remote-sensing technology advances, high-resolution imagery, such as Quickbird and photography from the National Agriculture Imagery Program (NAIP), is becoming more readily available for use in forestry applications. Quickbird imagery is currently the highest resolution imagery commercially available. It consists of 2.44-m (8-ft) resolution multispectral bands...

Enhancing Spatial Resolution of Remotely Sensed Imagery Using Deep Learning

NASA Astrophysics Data System (ADS)

Beck, J. M.; Bridges, S.; Collins, C.; Rushing, J.; Graves, S. J.

2017-12-01

Researchers at the Information Technology and Systems Center at the University of Alabama in Huntsville are using Deep Learning with Convolutional Neural Networks (CNNs) to develop a method for enhancing the spatial resolutions of moderate resolution (10-60m) multispectral satellite imagery. This enhancement will effectively match the resolutions of imagery from multiple sensors to provide increased global temporal-spatial coverage for a variety of Earth science products. Our research is centered on using Deep Learning for automatically generating transformations for increasing the spatial resolution of remotely sensed images with different spatial, spectral, and temporal resolutions. One of the most important steps in using images from multiple sensors is to transform the different image layers into the same spatial resolution, preferably the highest spatial resolution, without compromising the spectral information. Recent advances in Deep Learning have shown that CNNs can be used to effectively and efficiently upscale or enhance the spatial resolution of multispectral images with the use of an auxiliary data source such as a high spatial resolution panchromatic image. In contrast, we are using both the spatial and spectral details inherent in low spatial resolution multispectral images for image enhancement without the use of a panchromatic image. This presentation will discuss how this technology will benefit many Earth Science applications that use remotely sensed images with moderate spatial resolutions.

A Method of Spatial Mapping and Reclassification for High-Spatial-Resolution Remote Sensing Image Classification

PubMed Central

Wang, Guizhou; Liu, Jianbo; He, Guojin

2013-01-01

This paper presents a new classification method for high-spatial-resolution remote sensing images based on a strategic mechanism of spatial mapping and reclassification. The proposed method includes four steps. First, the multispectral image is classified by a traditional pixel-based classification method (support vector machine). Second, the panchromatic image is subdivided by watershed segmentation. Third, the pixel-based multispectral image classification result is mapped to the panchromatic segmentation result based on a spatial mapping mechanism and the area dominant principle. During the mapping process, an area proportion threshold is set, and the regional property is defined as unclassified if the maximum area proportion does not surpass the threshold. Finally, unclassified regions are reclassified based on spectral information using the minimum distance to mean algorithm. Experimental results show that the classification method for high-spatial-resolution remote sensing images based on the spatial mapping mechanism and reclassification strategy can make use of both panchromatic and multispectral information, integrate the pixel- and object-based classification methods, and improve classification accuracy. PMID:24453808

Design of a multi-spectral imager built using the compressive sensing single-pixel camera architecture

NASA Astrophysics Data System (ADS)

McMackin, Lenore; Herman, Matthew A.; Weston, Tyler

2016-02-01

We present the design of a multi-spectral imager built using the architecture of the single-pixel camera. The architecture is enabled by the novel sampling theory of compressive sensing implemented optically using the Texas Instruments DLP™ micro-mirror array. The array not only implements spatial modulation necessary for compressive imaging but also provides unique diffractive spectral features that result in a multi-spectral, high-spatial resolution imager design. The new camera design provides multi-spectral imagery in a wavelength range that extends from the visible to the shortwave infrared without reduction in spatial resolution. In addition to the compressive imaging spectrometer design, we present a diffractive model of the architecture that allows us to predict a variety of detailed functional spatial and spectral design features. We present modeling results, architectural design and experimental results that prove the concept.

NASA Cold Land Processes Experiment (CLPX 2002/03): Spaceborne remote sensing

Treesearch

Robert E. Davis; Thomas H. Painter; Don Cline; Richard Armstrong; Terry Haran; Kyle McDonald; Rick Forster; Kelly Elder

2008-01-01

This paper describes satellite data collected as part of the 2002/03 Cold Land Processes Experiment (CLPX). These data include multispectral and hyperspectral optical imaging, and passive and active microwave observations of the test areas. The CLPX multispectral optical data include the Advanced Very High Resolution Radiometer (AVHRR), the Landsat Thematic Mapper/...

APPLICATION OF MULTISPECTRAL TECHNIQUES TO THE PRECISE IDENTIFICATION OF ALDEHYDES IN THE ENVIRONMENT

EPA Science Inventory

By using gas chromatography coupled with low- and high-resolution electron impact mass spectrometry, low- and high-resolution chemical ionization mass spectrometry, and Fourier transform infrared spectroscopy, eight straight-chain aldehydes were identified in a water sample taken...

Overview of Sentinel-2

NASA Astrophysics Data System (ADS)

Fernandez, Valerie; Martimort, Philippe; Spoto, Francois; Sy, Omar; Laberinti, Paolo

2013-10-01

GMES is a joint initiative of the European Commission (EC) and the European Space Agency (ESA), designed to establish a European capacity for the provision and use of operational monitoring information for environment and security applications. ESA's role in GMES is to provide the definition and the development of the space- and ground-related system elements. GMES Sentinel-2 mission provides continuity to services relying on multi-spectral highresolution optical observations over global terrestrial surfaces. The key mission objectives for Sentinel-2 are: (1) to provide systematic global acquisitions of high-resolution multi-spectral imagery with a high revisit frequency, (2) to provide enhanced continuity of multi-spectral imagery provided by the SPOT series of satellites, and (3) to provide observations for the next generation of operational products such as landcover maps, land change detection maps, and geophysical variables. Consequently, Sentinel-2 will directly contribute to the Land Monitoring, Emergency Response, and Security services. The corresponding user requirements have driven the design towards a dependable multi-spectral Earthobservation system featuring the MSI with 13 spectral bands spanning from the visible and the near infrared to the short wave infrared. The spatial resolution varies from 10 m to 60 m depending on the spectral band with a 290 km field of view. This unique combination of high spatial resolution, wide field of view and large spectral coverage will represent a major step forward compared to current multi-spectral missions. The mission foresees a series of satellites, each having a 7.25-year lifetime (extendable to 12 years) over a 20-year period starting with the launch of Sentinel-2A foreseen by mid-2014. During full operations two identical satellites will be maintained in the same sun synchronous orbit with a phase delay of 180° providing a revisit time of five days at the equator.

An automated procedure for detection of IDP's dwellings using VHR satellite imagery

NASA Astrophysics Data System (ADS)

Jenerowicz, Malgorzata; Kemper, Thomas; Soille, Pierre

2011-11-01

This paper presents the results for the estimation of dwellings structures in Al Salam IDP Camp, Southern Darfur, based on Very High Resolution multispectral satellite images obtained by implementation of Mathematical Morphology analysis. A series of image processing procedures, feature extraction methods and textural analysis have been applied in order to provide reliable information about dwellings structures. One of the issues in this context is related to similarity of the spectral response of thatched dwellings' roofs and the surroundings in the IDP camps, where the exploitation of multispectral information is crucial. This study shows the advantage of automatic extraction approach and highlights the importance of detailed spatial and spectral information analysis based on multi-temporal dataset. The additional data fusion of high-resolution panchromatic band with lower resolution multispectral bands of WorldView-2 satellite has positive influence on results and thereby can be useful for humanitarian aid agency, providing support of decisions and estimations of population especially in situations when frequent revisits by space imaging system are the only possibility of continued monitoring.

Imaging the small animal cardiovascular system in real-time with multispectral optoacoustic tomography

NASA Astrophysics Data System (ADS)

Taruttis, Adrian; Herzog, Eva; Razansky, Daniel; Ntziachristos, Vasilis

2011-03-01

Multispectral Optoacoustic Tomography (MSOT) is an emerging technique for high resolution macroscopic imaging with optical and molecular contrast. We present cardiovascular imaging results from a multi-element real-time MSOT system recently developed for studies on small animals. Anatomical features relevant to cardiovascular disease, such as the carotid arteries, the aorta and the heart, are imaged in mice. The system's fast acquisition time, in tens of microseconds, allows images free of motion artifacts from heartbeat and respiration. Additionally, we present in-vivo detection of optical imaging agents, gold nanorods, at high spatial and temporal resolution, paving the way for molecular imaging applications.

Back in Time

NASA Technical Reports Server (NTRS)

1998-01-01

Under a Jet Propulsion Laboratory SBIR (Small Business Innovative Research), Cambridge Research and Instrumentation Inc., developed a new class of filters for the construction of small, low-cost multispectral imagers. The VariSpec liquid crystal enables users to obtain multi-spectral, ultra-high resolution images using a monochrome CCD (charge coupled device) camera. Application areas include biomedical imaging, remote sensing, and machine vision.

Results of the spatial resolution simulation for multispectral data (resolution brochures)

NASA Technical Reports Server (NTRS)

1982-01-01

The variable information content of Earth Resource products at different levels of spatial resolution and in different spectral bands is addressed. A low-cost brochure that scientists and laymen could use to visualize the effects of increasing the spatial resolution of multispectral scanner images was produced.

High performance multi-spectral interrogation for surface plasmon resonance imaging sensors.

PubMed

Sereda, A; Moreau, J; Canva, M; Maillart, E

2014-04-15

Surface plasmon resonance (SPR) sensing has proven to be a valuable tool in the field of surface interactions characterization, especially for biomedical applications where label-free techniques are of particular interest. In order to approach the theoretical resolution limit, most SPR-based systems have turned to either angular or spectral interrogation modes, which both offer very accurate real-time measurements, but at the expense of the 2-dimensional imaging capability, therefore decreasing the data throughput. In this article, we show numerically and experimentally how to combine the multi-spectral interrogation technique with 2D-imaging, while finding an optimum in terms of resolution, accuracy, acquisition speed and reduction in data dispersion with respect to the classical reflectivity interrogation mode. This multi-spectral interrogation methodology is based on a robust five parameter fitting of the spectral reflectivity curve which enables monitoring of the reflectivity spectral shift with a resolution of the order of ten picometers, and using only five wavelength measurements per point. In fine, such multi-spectral based plasmonic imaging system allows biomolecular interaction monitoring in a linear regime independently of variations of buffer optical index, which is illustrated on a DNA-DNA model case. © 2013 Elsevier B.V. All rights reserved.

The absolute calibration of KOMPSAT-3 and 3A high spatial resolution satellites using radiometric tarps and MFRSR measurments

NASA Astrophysics Data System (ADS)

Yeom, J. M.

2017-12-01

Recently developed Korea Multi-Purpose Satellite-3A (KOMPSAT-3A), which is a continuation of the KOMPSAT-1, 2 and 3 earth observation satellite (EOS) programs from the Korea Aerospace Research Institute (KARI) was launched on March, 25 2015 on a Dnepr-1 launch vehicle from the Jasny Dombarovsky site in Russia. After launched, KARI performed in-orbit-test (IOT) including radiometric calibration for 6 months from 14 Apr. to 4 Sep. 2015. KOMPSAT-3A is equipped with two distinctive sensors; one is a high resolution multispectral optical sensor, namely the Advances Earth Image Sensor System-A (AEISS-A) and the other is the Scanner Infrared Imaging System (SIIS). In this study, we focused on the radiometric calibration of AEISS-A. The multispectral wavelengths of AEISS-A are covering three visible regions: blue (450 - 520 nm), green (520 - 600 nm), red (630 - 690 nm), one near infrared (760 - 900 nm) with a 2.0 m spatial resolution at nadir, whereas the panchromatic imagery (450 - 900 nm) has a 0.5 m resolution. Those are the same spectral response functions were same with KOMPSAT-3 multispectral and panchromatic bands but the spatial resolutions are improved. The main mission of KOMPSAT-3A is to develop for Geographical Information System (GIS) applications in environmental, agriculture, and oceanographic sciences, as well as natural hazard monitoring.

HPT: A High Spatial Resolution Multispectral Sensor for Microsatellite Remote Sensing

PubMed Central

Takahashi, Yukihiro; Sakamoto, Yuji; Kuwahara, Toshinori

2018-01-01

Although nano/microsatellites have great potential as remote sensing platforms, the spatial and spectral resolutions of an optical payload instrument are limited. In this study, a high spatial resolution multispectral sensor, the High-Precision Telescope (HPT), was developed for the RISING-2 microsatellite. The HPT has four image sensors: three in the visible region of the spectrum used for the composition of true color images, and a fourth in the near-infrared region, which employs liquid crystal tunable filter (LCTF) technology for wavelength scanning. Band-to-band image registration methods have also been developed for the HPT and implemented in the image processing procedure. The processed images were compared with other satellite images, and proven to be useful in various remote sensing applications. Thus, LCTF technology can be considered an innovative tool that is suitable for future multi/hyperspectral remote sensing by nano/microsatellites. PMID:29463022

Retrieval of methanol absorption parameters at terahertz frequencies using multispectral fitting

NASA Astrophysics Data System (ADS)

Slocum, David M.; Xu, Li-Hong; Giles, Robert H.; Goyette, Thomas M.

2015-12-01

A high-resolution broadband study of the methanol absorption spectrum was performed at 1.480-1.495 THz. The transmittance was recorded under both self- and air-broadening conditions for multiple pressures at a resolution of 500 kHz. A multispectral fitting analysis was then performed. The transition frequency, absolute intensity, self- and air-broadening coefficients, and self- and air-induced pressure shifts were retrieved for 221 absorption lines using the multispectral fitting routine. Observed in the data were two different series of transitions, both a b-type Q-branch with K = - 7 ← - 6 and an a-type R-branch with J = 31 ← 30 . The retrieved frequency position values were compared with values from spectral databases and trends within the different series were identified. An analysis of the precision of the fitting routine was also performed.

Atmospheric Correction Prototype Algorithm for High Spatial Resolution Multispectral Earth Observing Imaging Systems

NASA Technical Reports Server (NTRS)

Pagnutti, Mary

2006-01-01

This viewgraph presentation reviews the creation of a prototype algorithm for atmospheric correction using high spatial resolution earth observing imaging systems. The objective of the work was to evaluate accuracy of a prototype algorithm that uses satellite-derived atmospheric products to generate scene reflectance maps for high spatial resolution (HSR) systems. This presentation focused on preliminary results of only the satellite-based atmospheric correction algorithm.

Using Unmanned Aerial Vehicles in Postfire Vegetation Survey Campaigns through Large and Heterogeneous Areas: Opportunities and Challenges.

PubMed

Fernández-Guisuraga, José Manuel; Sanz-Ablanedo, Enoc; Suárez-Seoane, Susana; Calvo, Leonor

2018-02-14

This study evaluated the opportunities and challenges of using drones to obtain multispectral orthomosaics at ultra-high resolution that could be useful for monitoring large and heterogeneous burned areas. We conducted a survey using an octocopter equipped with a Parrot SEQUOIA multispectral camera in a 3000 ha framework located within the perimeter of a megafire in Spain. We assessed the quality of both the camera raw imagery and the multispectral orthomosaic obtained, as well as the required processing capability. Additionally, we compared the spatial information provided by the drone orthomosaic at ultra-high spatial resolution with another image provided by the WorldView-2 satellite at high spatial resolution. The drone raw imagery presented some anomalies, such as horizontal banding noise and non-homogeneous radiometry. Camera locations showed a lack of synchrony of the single frequency GPS receiver. The georeferencing process based on ground control points achieved an error lower than 30 cm in X-Y and lower than 55 cm in Z. The drone orthomosaic provided more information in terms of spatial variability in heterogeneous burned areas in comparison with the WorldView-2 satellite imagery. The drone orthomosaic could constitute a viable alternative for the evaluation of post-fire vegetation regeneration in large and heterogeneous burned areas.

Using Unmanned Aerial Vehicles in Postfire Vegetation Survey Campaigns through Large and Heterogeneous Areas: Opportunities and Challenges

PubMed Central

2018-01-01

This study evaluated the opportunities and challenges of using drones to obtain multispectral orthomosaics at ultra-high resolution that could be useful for monitoring large and heterogeneous burned areas. We conducted a survey using an octocopter equipped with a Parrot SEQUOIA multispectral camera in a 3000 ha framework located within the perimeter of a megafire in Spain. We assessed the quality of both the camera raw imagery and the multispectral orthomosaic obtained, as well as the required processing capability. Additionally, we compared the spatial information provided by the drone orthomosaic at ultra-high spatial resolution with another image provided by the WorldView-2 satellite at high spatial resolution. The drone raw imagery presented some anomalies, such as horizontal banding noise and non-homogeneous radiometry. Camera locations showed a lack of synchrony of the single frequency GPS receiver. The georeferencing process based on ground control points achieved an error lower than 30 cm in X-Y and lower than 55 cm in Z. The drone orthomosaic provided more information in terms of spatial variability in heterogeneous burned areas in comparison with the WorldView-2 satellite imagery. The drone orthomosaic could constitute a viable alternative for the evaluation of post-fire vegetation regeneration in large and heterogeneous burned areas. PMID:29443914

Investigation of a high speed data handling system for use with multispectral aircraft scanners

NASA Technical Reports Server (NTRS)

Kelly, W. L.; Meredith, B. D.

1978-01-01

A buffer memory data handling technique for use with multispectral aircraft scanners is presented which allows digital data generated at high data rates to be recorded on magnetic tape. A digital memory is used to temporarily store the data for subsequent recording at slower rates during the passive time of the scan line, thereby increasing the maximum data rate recording capability over real-time recording. Three possible implementations are described and the maximum data rate capability is defined in terms of the speed capability of the key hardware components. The maximum data rates can be used to define the maximum ground resolution achievable by a multispectral aircraft scanner using conventional data handling techniques.

Automated road network extraction from high spatial resolution multi-spectral imagery

NASA Astrophysics Data System (ADS)

Zhang, Qiaoping

For the last three decades, the Geomatics Engineering and Computer Science communities have considered automated road network extraction from remotely-sensed imagery to be a challenging and important research topic. The main objective of this research is to investigate the theory and methodology of automated feature extraction for image-based road database creation, refinement or updating, and to develop a series of algorithms for road network extraction from high resolution multi-spectral imagery. The proposed framework for road network extraction from multi-spectral imagery begins with an image segmentation using the k-means algorithm. This step mainly concerns the exploitation of the spectral information for feature extraction. The road cluster is automatically identified using a fuzzy classifier based on a set of predefined road surface membership functions. These membership functions are established based on the general spectral signature of road pavement materials and the corresponding normalized digital numbers on each multi-spectral band. Shape descriptors of the Angular Texture Signature are defined and used to reduce the misclassifications between roads and other spectrally similar objects (e.g., crop fields, parking lots, and buildings). An iterative and localized Radon transform is developed for the extraction of road centerlines from the classified images. The purpose of the transform is to accurately and completely detect the road centerlines. It is able to find short, long, and even curvilinear lines. The input image is partitioned into a set of subset images called road component images. An iterative Radon transform is locally applied to each road component image. At each iteration, road centerline segments are detected based on an accurate estimation of the line parameters and line widths. Three localization approaches are implemented and compared using qualitative and quantitative methods. Finally, the road centerline segments are grouped into a road network. The extracted road network is evaluated against a reference dataset using a line segment matching algorithm. The entire process is unsupervised and fully automated. Based on extensive experimentation on a variety of remotely-sensed multi-spectral images, the proposed methodology achieves a moderate success in automating road network extraction from high spatial resolution multi-spectral imagery.

Estimating chlorophyll with thermal and broadband multispectral high resolution imagery from an unmanned aerial system using relevance vector machines for precision agriculture

NASA Astrophysics Data System (ADS)

Elarab, Manal; Ticlavilca, Andres M.; Torres-Rua, Alfonso F.; Maslova, Inga; McKee, Mac

2015-12-01

Precision agriculture requires high-resolution information to enable greater precision in the management of inputs to production. Actionable information about crop and field status must be acquired at high spatial resolution and at a temporal frequency appropriate for timely responses. In this study, high spatial resolution imagery was obtained through the use of a small, unmanned aerial system called AggieAirTM. Simultaneously with the AggieAir flights, intensive ground sampling for plant chlorophyll was conducted at precisely determined locations. This study reports the application of a relevance vector machine coupled with cross validation and backward elimination to a dataset composed of reflectance from high-resolution multi-spectral imagery (VIS-NIR), thermal infrared imagery, and vegetative indices, in conjunction with in situ SPAD measurements from which chlorophyll concentrations were derived, to estimate chlorophyll concentration from remotely sensed data at 15-cm resolution. The results indicate that a relevance vector machine with a thin plate spline kernel type and kernel width of 5.4, having LAI, NDVI, thermal and red bands as the selected set of inputs, can be used to spatially estimate chlorophyll concentration with a root-mean-squared-error of 5.31 μg cm-2, efficiency of 0.76, and 9 relevance vectors.

Pansharpening Techniques to Detect Mass Monument Damaging in Iraq

NASA Astrophysics Data System (ADS)

Baiocchi, V.; Bianchi, A.; Maddaluno, C.; Vidale, M.

2017-05-01

The recent mass destructions of monuments in Iraq cannot be monitored with the terrestrial survey methodologies, for obvious reasons of safety. For the same reasons, it's not advisable the use of classical aerial photogrammetry, so it was obvious to think to the use of multispectral Very High Resolution (VHR) satellite imagery. Nowadays VHR satellite images resolutions are very near airborne photogrammetrical images and usually they are acquired in multispectral mode. The combination of the various bands of the images is called pan-sharpening and it can be carried on using different algorithms and strategies. The correct pansharpening methodology, for a specific image, must be chosen considering the specific multispectral characteristics of the satellite used and the particular application. In this paper a first definition of guidelines for the use of VHR multispectral imagery to detect monument destruction in unsafe area, is reported. The proposed methodology, agreed with UNESCO and soon to be used in Libya for the coastal area, has produced a first report delivered to the Iraqi authorities. Some of the most evident examples are reported to show the possible capabilities of identification of damages using VHR images.

Application of Multilayer Perceptron with Automatic Relevance Determination on Weed Mapping Using UAV Multispectral Imagery

PubMed Central

Tamouridou, Afroditi A.; Lagopodi, Anastasia L.; Kashefi, Javid; Kasampalis, Dimitris; Kontouris, Georgios; Moshou, Dimitrios

2017-01-01

Remote sensing techniques are routinely used in plant species discrimination and of weed mapping. In the presented work, successful Silybum marianum detection and mapping using multilayer neural networks is demonstrated. A multispectral camera (green-red-near infrared) attached on a fixed wing unmanned aerial vehicle (UAV) was utilized for the acquisition of high-resolution images (0.1 m resolution). The Multilayer Perceptron with Automatic Relevance Determination (MLP-ARD) was used to identify the S. marianum among other vegetation, mostly Avena sterilis L. The three spectral bands of Red, Green, Near Infrared (NIR) and the texture layer resulting from local variance were used as input. The S. marianum identification rates using MLP-ARD reached an accuracy of 99.54%. Τhe study had an one year duration, meaning that the results are specific, although the accuracy shows the interesting potential of S. marianum mapping with MLP-ARD on multispectral UAV imagery. PMID:29019957

Application of Multilayer Perceptron with Automatic Relevance Determination on Weed Mapping Using UAV Multispectral Imagery.

PubMed

Tamouridou, Afroditi A; Alexandridis, Thomas K; Pantazi, Xanthoula E; Lagopodi, Anastasia L; Kashefi, Javid; Kasampalis, Dimitris; Kontouris, Georgios; Moshou, Dimitrios

2017-10-11

Remote sensing techniques are routinely used in plant species discrimination and of weed mapping. In the presented work, successful Silybum marianum detection and mapping using multilayer neural networks is demonstrated. A multispectral camera (green-red-near infrared) attached on a fixed wing unmanned aerial vehicle (UAV) was utilized for the acquisition of high-resolution images (0.1 m resolution). The Multilayer Perceptron with Automatic Relevance Determination (MLP-ARD) was used to identify the S. marianum among other vegetation, mostly Avena sterilis L. The three spectral bands of Red, Green, Near Infrared (NIR) and the texture layer resulting from local variance were used as input. The S. marianum identification rates using MLP-ARD reached an accuracy of 99.54%. Τhe study had an one year duration, meaning that the results are specific, although the accuracy shows the interesting potential of S. marianum mapping with MLP-ARD on multispectral UAV imagery.

Object-based habitat mapping using very high spatial resolution multispectral and hyperspectral imagery with LiDAR data

NASA Astrophysics Data System (ADS)

Onojeghuo, Alex Okiemute; Onojeghuo, Ajoke Ruth

2017-07-01

This study investigated the combined use of multispectral/hyperspectral imagery and LiDAR data for habitat mapping across parts of south Cumbria, North West England. The methodology adopted in this study integrated spectral information contained in pansharp QuickBird multispectral/AISA Eagle hyperspectral imagery and LiDAR-derived measures with object-based machine learning classifiers and ensemble analysis techniques. Using the LiDAR point cloud data, elevation models (such as the Digital Surface Model and Digital Terrain Model raster) and intensity features were extracted directly. The LiDAR-derived measures exploited in this study included Canopy Height Model, intensity and topographic information (i.e. mean, maximum and standard deviation). These three LiDAR measures were combined with spectral information contained in the pansharp QuickBird and Eagle MNF transformed imagery for image classification experiments. A fusion of pansharp QuickBird multispectral and Eagle MNF hyperspectral imagery with all LiDAR-derived measures generated the best classification accuracies, 89.8 and 92.6% respectively. These results were generated with the Support Vector Machine and Random Forest machine learning algorithms respectively. The ensemble analysis of all three learning machine classifiers for the pansharp QuickBird and Eagle MNF fused data outputs did not significantly increase the overall classification accuracy. Results of the study demonstrate the potential of combining either very high spatial resolution multispectral or hyperspectral imagery with LiDAR data for habitat mapping.

Evaluation of eelgrass beds mapping using a high-resolution airborne multispectral scanner

USGS Publications Warehouse

Su, H.; Karna, D.; Fraim, E.; Fitzgerald, M.; Dominguez, R.; Myers, J.S.; Coffland, B.; Handley, L.R.; Mace, T.

2006-01-01

Eelgrass (Zostera marina) can provide vital ecological functions in stabilizing sediments, influencing current dynamics, and contributing significant amounts of biomass to numerous food webs in coastal ecosystems. Mapping eelgrass beds is important for coastal water and nearshore estuarine monitoring, management, and planning. This study demonstrated the possible use of high spatial (approximately 5 m) and temporal (maximum low tide) resolution airborne multispectral scanner on mapping eelgrass beds in Northern Puget Sound, Washington. A combination of supervised and unsupervised classification approaches were performed on the multispectral scanner imagery. A normalized difference vegetation index (NDVI) derived from the red and near-infrared bands and ancillary spatial information, were used to extract and mask eelgrass beds and other submerged aquatic vegetation (SAV) in the study area. We evaluated the resulting thematic map (geocoded, classified image) against a conventional aerial photograph interpretation using 260 point locations randomly stratified over five defined classes from the thematic map. We achieved an overall accuracy of 92 percent with 0.92 Kappa Coefficient in the study area. This study demonstrates that the airborne multispectral scanner can be useful for mapping eelgrass beds in a local or regional scale, especially in regions for which optical remote sensing from space is constrained by climatic and tidal conditions. ?? 2006 American Society for Photogrammetry and Remote Sensing.

Globally scalable generation of high-resolution land cover from multispectral imagery

NASA Astrophysics Data System (ADS)

Stutts, S. Craig; Raskob, Benjamin L.; Wenger, Eric J.

2017-05-01

We present an automated method of generating high resolution ( 2 meter) land cover using a pattern recognition neural network trained on spatial and spectral features obtained from over 9000 WorldView multispectral images (MSI) in six distinct world regions. At this resolution, the network can classify small-scale objects such as individual buildings, roads, and irrigation ponds. This paper focuses on three key areas. First, we describe our land cover generation process, which involves the co-registration and aggregation of multiple spatially overlapping MSI, post-aggregation processing, and the registration of land cover to OpenStreetMap (OSM) road vectors using feature correspondence. Second, we discuss the generation of land cover derivative products and their impact in the areas of region reduction and object detection. Finally, we discuss the process of globally scaling land cover generation using cloud computing via Amazon Web Services (AWS).

Tamarisk Mapping and Monitoring Using High Resolution Satellite Imagery

Treesearch

Jason W. San Souci; John T. Doyle

2006-01-01

QuickBird high resolution multispectral satellite imagery (60 cm GSD, 4 spectral bands) and calibrated products from DigitalGlobe’s AgroWatch program were used as inputs to Visual Learning System’s Feature Analyst automated feature extraction software to map localized occurrences of pervasive and aggressive Tamarisk (Tamarix ramosissima), an invasive...

A multispectral study of an extratropical cyclone with Nimbus 3 medium resolution infrared radiometer data

NASA Technical Reports Server (NTRS)

Holub, R.; Shenk, W. E.

1973-01-01

Four registered channels (0.2 to 4, 6.5 to 7, 10 to 11, and 20 to 23 microns) of the Nimbus 3 Medium Resolution Infrared Radiometer (MRIR) were used to study 24-hr changes in the structure of an extratropical cyclone during a 6-day period in May 1969. Use of a stereographic-horizon map projection insured that the storm was mapped with a single perspective throughout the series and allowed the convenient preparation of 24-hr difference maps of the infrared radiation fields. Single-channel and multispectral analysis techniques were employed to establish the positions and vertical slopes of jetstreams, large cloud systems, and major features of middle and upper tropospheric circulation. Use of these techniques plus the difference maps and continuity of observation allowed the early detection of secondary cyclones developing within the circulation of the primary cyclone. An automated, multispectral cloud-type identification technique was developed, and comparisons that were made with conventional ship reports and with high-resolution visual data from the image dissector camera system showed good agreement.

Sharpening advanced land imager multispectral data using a sensor model

USGS Publications Warehouse

Lemeshewsky, G.P.; ,

2005-01-01

The Advanced Land Imager (ALI) instrument on NASA's Earth Observing One (EO-1) satellite provides for nine spectral bands at 30m ground sample distance (GSD) and a 10m GSD panchromatic band. This report describes an image sharpening technique where the higher spatial resolution information of the panchromatic band is used to increase the spatial resolution of ALI multispectral (MS) data. To preserve the spectral characteristics, this technique combines reported deconvolution deblurring methods for the MS data with highpass filter-based fusion methods for the Pan data. The deblurring process uses the point spread function (PSF) model of the ALI sensor. Information includes calculation of the PSF from pre-launch calibration data. Performance was evaluated using simulated ALI MS data generated by degrading the spatial resolution of high resolution IKONOS satellite MS data. A quantitative measure of performance was the error between sharpened MS data and high resolution reference. This report also compares performance with that of a reported method that includes PSF information. Preliminary results indicate improved sharpening with the method reported here.

The Panoramic Camera (PanCam) Instrument for the ESA ExoMars Rover

NASA Astrophysics Data System (ADS)

Griffiths, A.; Coates, A.; Jaumann, R.; Michaelis, H.; Paar, G.; Barnes, D.; Josset, J.

The recently approved ExoMars rover is the first element of the ESA Aurora programme and is slated to deliver the Pasteur exobiology payload to Mars by 2013. The 0.7 kg Panoramic Camera will provide multispectral stereo images with 65° field-of- view (1.1 mrad/pixel) and high resolution (85 µrad/pixel) monoscopic "zoom" images with 5° field-of-view. The stereo Wide Angle Cameras (WAC) are based on Beagle 2 Stereo Camera System heritage. The Panoramic Camera instrument is designed to fulfil the digital terrain mapping requirements of the mission as well as providing multispectral geological imaging, colour and stereo panoramic images, solar images for water vapour abundance and dust optical depth measurements and to observe retrieved subsurface samples before ingestion into the rest of the Pasteur payload. Additionally the High Resolution Camera (HRC) can be used for high resolution imaging of interesting targets detected in the WAC panoramas and of inaccessible locations on crater or valley walls.

The Multispectral Atmospheric Mapping Sensor (MAMS): Instrument description, calibration and data quality

NASA Technical Reports Server (NTRS)

Jedlovec, G. J.; Menzel, W. P.; Atkinson, R.; Wilson, G. S.; Arvesen, J.

1986-01-01

A new instrument has been developed to produce high resolution imagery in eight visible and three infared spectral bands from an aircraft platform. An analysis of the data and calibration procedures has shown that useful data can be obtained at up to 50 m resolution with a 2.5 milliradian aperture. Single sample standard errors for the measurements are 0.5, 0.2, and 0.9 K for the 6.5, 11.1, and 12.3 micron spectral bands, respectively. These errors are halved when a 5.0 milliradian aperture is used to obtain 100 m resolution data. Intercomparisons with VAS and AVHRR measurements show good relative calibration. MAMS development is part of a larger program to develop multispectral Earth imaging capabilities from space platforms during the 1990s.

DEIMOS-2: cost-effective, very-high resolution multispectral imagery

NASA Astrophysics Data System (ADS)

Pirondini, Fabrizio; López, Julio; González, Enrique; González, José Antonio

2014-10-01

ELECNOR DEIMOS is a private Spanish company, part of the Elecnor industrial group, which owns and operates DEIMOS-1, the first Spanish Earth Observation satellite. DEIMOS-1, launched in 2009, is among the world leading sources of high resolution data. On June 19th, 2014 ELECNOR DEIMOS launched its second satellite, DEIMOS-2, which is a very-high resolution, agile satellite capable of providing 75-cm pan-sharpened imagery, with a 12kmwide swath. The DEIMOS-2 camera delivers multispectral imagery in 5 bands: Panchromatic, G, R, B and NIR. DEIMOS-2 is the first European satellite completely owned by private capital, which is capable of providing submetric multispectral imagery. The whole end-to-end DEIMOS-2 system is designed to provide a cost-effective, dependable and highly responsive service to cope with the increasing need of fast access to very-high resolution imagery. The same 24/7 commercial service which is now available for DEIMOS-1, including tasking, download, processing and delivery, will become available for DEIMOS-2 as well, as soon as the satellite enters into commercial operations, at the end of its in-orbit commissioning. The DEIMOS-2 satellite has been co-developed by ELECNOR DEIMOS and SATREC-I (South Korea), and it has been integrated and tested in the new ELECNOR DEIMOS Satellite Systems premises in Puertollano (Spain). The DEIMOS-2 ground segment, which includes four receiving/commanding ground stations in Spain, Sweden and Canada, has been completely developed in-house by ELECNOR DEIMOS, based on its Ground Segment for Earth Observation (gs4EO®) suite. In this paper we describe the main features of the DEIMOS-2 system, with emphasis on its initial operations and the quality of the initial imagery, and provide updated information on its mission status.

Multisensor Super Resolution Using Directionally-Adaptive Regularization for UAV Images

PubMed Central

Kang, Wonseok; Yu, Soohwan; Ko, Seungyong; Paik, Joonki

2015-01-01

In various unmanned aerial vehicle (UAV) imaging applications, the multisensor super-resolution (SR) technique has become a chronic problem and attracted increasing attention. Multisensor SR algorithms utilize multispectral low-resolution (LR) images to make a higher resolution (HR) image to improve the performance of the UAV imaging system. The primary objective of the paper is to develop a multisensor SR method based on the existing multispectral imaging framework instead of using additional sensors. In order to restore image details without noise amplification or unnatural post-processing artifacts, this paper presents an improved regularized SR algorithm by combining the directionally-adaptive constraints and multiscale non-local means (NLM) filter. As a result, the proposed method can overcome the physical limitation of multispectral sensors by estimating the color HR image from a set of multispectral LR images using intensity-hue-saturation (IHS) image fusion. Experimental results show that the proposed method provides better SR results than existing state-of-the-art SR methods in the sense of objective measures. PMID:26007744

Multisensor Super Resolution Using Directionally-Adaptive Regularization for UAV Images.

PubMed

Kang, Wonseok; Yu, Soohwan; Ko, Seungyong; Paik, Joonki

2015-05-22

In various unmanned aerial vehicle (UAV) imaging applications, the multisensor super-resolution (SR) technique has become a chronic problem and attracted increasing attention. Multisensor SR algorithms utilize multispectral low-resolution (LR) images to make a higher resolution (HR) image to improve the performance of the UAV imaging system. The primary objective of the paper is to develop a multisensor SR method based on the existing multispectral imaging framework instead of using additional sensors. In order to restore image details without noise amplification or unnatural post-processing artifacts, this paper presents an improved regularized SR algorithm by combining the directionally-adaptive constraints and multiscale non-local means (NLM) filter. As a result, the proposed method can overcome the physical limitation of multispectral sensors by estimating the color HR image from a set of multispectral LR images using intensity-hue-saturation (IHS) image fusion. Experimental results show that the proposed method provides better SR results than existing state-of-the-art SR methods in the sense of objective measures.

Mutual information registration of multi-spectral and multi-resolution images of DigitalGlobe's WorldView-3 imaging satellite

NASA Astrophysics Data System (ADS)

Miecznik, Grzegorz; Shafer, Jeff; Baugh, William M.; Bader, Brett; Karspeck, Milan; Pacifici, Fabio

2017-05-01

WorldView-3 (WV-3) is a DigitalGlobe commercial, high resolution, push-broom imaging satellite with three instruments: visible and near-infrared VNIR consisting of panchromatic (0.3m nadir GSD) plus multi-spectral (1.2m), short-wave infrared SWIR (3.7m), and multi-spectral CAVIS (30m). Nine VNIR bands, which are on one instrument, are nearly perfectly registered to each other, whereas eight SWIR bands, belonging to the second instrument, are misaligned with respect to VNIR and to each other. Geometric calibration and ortho-rectification results in a VNIR/SWIR alignment which is accurate to approximately 0.75 SWIR pixel at 3.7m GSD, whereas inter-SWIR, band to band registration is 0.3 SWIR pixel. Numerous high resolution, spectral applications, such as object classification and material identification, require more accurate registration, which can be achieved by utilizing image processing algorithms, for example Mutual Information (MI). Although MI-based co-registration algorithms are highly accurate, implementation details for automated processing can be challenging. One particular challenge is how to compute bin widths of intensity histograms, which are fundamental building blocks of MI. We solve this problem by making the bin widths proportional to instrument shot noise. Next, we show how to take advantage of multiple VNIR bands, and improve registration sensitivity to image alignment. To meet this goal, we employ Canonical Correlation Analysis, which maximizes VNIR/SWIR correlation through an optimal linear combination of VNIR bands. Finally we explore how to register images corresponding to different spatial resolutions. We show that MI computed at a low-resolution grid is more sensitive to alignment parameters than MI computed at a high-resolution grid. The proposed modifications allow us to improve VNIR/SWIR registration to better than ¼ of a SWIR pixel, as long as terrain elevation is properly accounted for, and clouds and water are masked out.

Approaching bathymetry estimation from high resolution multispectral satellite images using a neuro-fuzzy technique

NASA Astrophysics Data System (ADS)

Corucci, Linda; Masini, Andrea; Cococcioni, Marco

2011-01-01

This paper addresses bathymetry estimation from high resolution multispectral satellite images by proposing an accurate supervised method, based on a neuro-fuzzy approach. The method is applied to two Quickbird images of the same area, acquired in different years and meteorological conditions, and is validated using truth data. Performance is studied in different realistic situations of in situ data availability. The method allows to achieve a mean standard deviation of 36.7 cm for estimated water depths in the range [-18, -1] m. When only data collected along a closed path are used as a training set, a mean STD of 45 cm is obtained. The effect of both meteorological conditions and training set size reduction on the overall performance is also investigated.

CMOS Time-Resolved, Contact, and Multispectral Fluorescence Imaging for DNA Molecular Diagnostics

PubMed Central

Guo, Nan; Cheung, Ka Wai; Wong, Hiu Tung; Ho, Derek

2014-01-01

Instrumental limitations such as bulkiness and high cost prevent the fluorescence technique from becoming ubiquitous for point-of-care deoxyribonucleic acid (DNA) detection and other in-field molecular diagnostics applications. The complimentary metal-oxide-semiconductor (CMOS) technology, as benefited from process scaling, provides several advanced capabilities such as high integration density, high-resolution signal processing, and low power consumption, enabling sensitive, integrated, and low-cost fluorescence analytical platforms. In this paper, CMOS time-resolved, contact, and multispectral imaging are reviewed. Recently reported CMOS fluorescence analysis microsystem prototypes are surveyed to highlight the present state of the art. PMID:25365460

Wetland Vegetation Integrity Assessment with Low Altitude Multispectral Uav Imagery

NASA Astrophysics Data System (ADS)

Boon, M. A.; Tesfamichael, S.

2017-08-01

The use of multispectral sensors on Unmanned Aerial Vehicles (UAVs) was until recently too heavy and bulky although this changed in recent times and they are now commercially available. The focus on the usage of these sensors is mostly directed towards the agricultural sector where the focus is on precision farming. Applications of these sensors for mapping of wetland ecosystems are rare. Here, we evaluate the performance of low altitude multispectral UAV imagery to determine the state of wetland vegetation in a localised spatial area. Specifically, NDVI derived from multispectral UAV imagery was used to inform the determination of the integrity of the wetland vegetation. Furthermore, we tested different software applications for the processing of the imagery. The advantages and disadvantages we experienced of these applications are also shortly presented in this paper. A JAG-M fixed-wing imaging system equipped with a MicaScene RedEdge multispectral camera were utilised for the survey. A single surveying campaign was undertaken in early autumn of a 17 ha study area at the Kameelzynkraal farm, Gauteng Province, South Africa. Structure-from-motion photogrammetry software was used to reconstruct the camera position's and terrain features to derive a high resolution orthoretified mosaic. MicaSense Atlas cloud-based data platform, Pix4D and PhotoScan were utilised for the processing. The WET-Health level one methodology was followed for the vegetation assessment, where wetland health is a measure of the deviation of a wetland's structure and function from its natural reference condition. An on-site evaluation of the vegetation integrity was first completed. Disturbance classes were then mapped using the high resolution multispectral orthoimages and NDVI. The WET-Health vegetation module completed with the aid of the multispectral UAV products indicated that the vegetation of the wetland is largely modified ("D" PES Category) and that the condition is expected to deteriorate (change score) in the future. However a lower impact score were determined utilising the multispectral UAV imagery and NDVI. The result is a more accurate estimation of the impacts in the wetland.

Airborne multispectral detection of regrowth cotton fields

NASA Astrophysics Data System (ADS)

Westbrook, John K.; Suh, Charles P.-C.; Yang, Chenghai; Lan, Yubin; Eyster, Ritchie S.

2015-01-01

Effective methods are needed for timely areawide detection of regrowth cotton plants because boll weevils (a quarantine pest) can feed and reproduce on these plants beyond the cotton production season. Airborne multispectral images of regrowth cotton plots were acquired on several dates after three shredding (i.e., stalk destruction) dates. Linear spectral unmixing (LSU) classification was applied to high-resolution airborne multispectral images of regrowth cotton plots to estimate the minimum detectable size and subsequent growth of plants. We found that regrowth cotton fields can be identified when the mean plant width is ˜0.2 m for an image resolution of 0.1 m. LSU estimates of canopy cover of regrowth cotton plots correlated well (r2=0.81) with the ratio of mean plant width to row spacing, a surrogate measure of plant canopy cover. The height and width of regrowth plants were both well correlated (r2=0.94) with accumulated degree-days after shredding. The results will help boll weevil eradication program managers use airborne multispectral images to detect and monitor the regrowth of cotton plants after stalk destruction, and identify fields that may require further inspection and mitigation of boll weevil infestations.

High-resolution satellite imagery is an important yet underutilized resource in conservation biology.

PubMed

Boyle, Sarah A; Kennedy, Christina M; Torres, Julio; Colman, Karen; Pérez-Estigarribia, Pastor E; de la Sancha, Noé U

2014-01-01

Technological advances and increasing availability of high-resolution satellite imagery offer the potential for more accurate land cover classifications and pattern analyses, which could greatly improve the detection and quantification of land cover change for conservation. Such remotely-sensed products, however, are often expensive and difficult to acquire, which prohibits or reduces their use. We tested whether imagery of high spatial resolution (≤5 m) differs from lower-resolution imagery (≥30 m) in performance and extent of use for conservation applications. To assess performance, we classified land cover in a heterogeneous region of Interior Atlantic Forest in Paraguay, which has undergone recent and dramatic human-induced habitat loss and fragmentation. We used 4 m multispectral IKONOS and 30 m multispectral Landsat imagery and determined the extent to which resolution influenced the delineation of land cover classes and patch-level metrics. Higher-resolution imagery more accurately delineated cover classes, identified smaller patches, retained patch shape, and detected narrower, linear patches. To assess extent of use, we surveyed three conservation journals (Biological Conservation, Biotropica, Conservation Biology) and found limited application of high-resolution imagery in research, with only 26.8% of land cover studies analyzing satellite imagery, and of these studies only 10.4% used imagery ≤5 m resolution. Our results suggest that high-resolution imagery is warranted yet under-utilized in conservation research, but is needed to adequately monitor and evaluate forest loss and conversion, and to delineate potentially important stepping-stone fragments that may serve as corridors in a human-modified landscape. Greater access to low-cost, multiband, high-resolution satellite imagery would therefore greatly facilitate conservation management and decision-making.

Multispectral image enhancement processing for microsat-borne imager

NASA Astrophysics Data System (ADS)

Sun, Jianying; Tan, Zheng; Lv, Qunbo; Pei, Linlin

2017-10-01

With the rapid development of remote sensing imaging technology, the micro satellite, one kind of tiny spacecraft, appears during the past few years. A good many studies contribute to dwarfing satellites for imaging purpose. Generally speaking, micro satellites weigh less than 100 kilograms, even less than 50 kilograms, which are slightly larger or smaller than the common miniature refrigerators. However, the optical system design is hard to be perfect due to the satellite room and weight limitation. In most cases, the unprocessed data captured by the imager on the microsatellite cannot meet the application need. Spatial resolution is the key problem. As for remote sensing applications, the higher spatial resolution of images we gain, the wider fields we can apply them. Consequently, how to utilize super resolution (SR) and image fusion to enhance the quality of imagery deserves studying. Our team, the Key Laboratory of Computational Optical Imaging Technology, Academy Opto-Electronics, is devoted to designing high-performance microsat-borne imagers and high-efficiency image processing algorithms. This paper addresses a multispectral image enhancement framework for space-borne imagery, jointing the pan-sharpening and super resolution techniques to deal with the spatial resolution shortcoming of microsatellites. We test the remote sensing images acquired by CX6-02 satellite and give the SR performance. The experiments illustrate the proposed approach provides high-quality images.

Design tradeoffs for a Multispectral Linear Array (MLA) instrument

NASA Technical Reports Server (NTRS)

Mika, A. M.

1982-01-01

The heart of the multispectral linear array (MLA) design problem is to develop an instrument concept which concurrently provides a wide field-of-view with high resolution, spectral separation with precise band-to band registration, and excellent radiometric accuracy. Often, these requirements have conflicting design implications which can only be resolved by careful tradeoffs that consider performance, cost, fabrication feasibility and development risk. The key design tradeoffs for an MLA instrument are addressed, and elements of a baseline instrument concept are presented.

SPEKTROP DPU: optoelectronic platform for fast multispectral imaging

NASA Astrophysics Data System (ADS)

Graczyk, Rafal; Sitek, Piotr; Stolarski, Marcin

2010-09-01

In recent years it easy to spot and increasing need of high-quality Earth imaging in airborne and space applications. This is due fact that government and local authorities urge for up to date topological data for administrative purposes. On the other hand, interest in environmental sciences, push for ecological approach, efficient agriculture and forests management are also heavily supported by Earth images in various resolutions and spectral ranges. "SPEKTROP DPU: Opto-electronic platform for fast multi-spectral imaging" paper describes architectural datails of data processing unit, part of universal and modular platform that provides high quality imaging functionality in aerospace applications.

Forest Stand Segmentation Using Airborne LIDAR Data and Very High Resolution Multispectral Imagery

NASA Astrophysics Data System (ADS)

Dechesne, Clément; Mallet, Clément; Le Bris, Arnaud; Gouet, Valérie; Hervieu, Alexandre

2016-06-01

Forest stands are the basic units for forest inventory and mapping. Stands are large forested areas (e.g., ≥ 2 ha) of homogeneous tree species composition. The accurate delineation of forest stands is usually performed by visual analysis of human operators on very high resolution (VHR) optical images. This work is highly time consuming and should be automated for scalability purposes. In this paper, a method based on the fusion of airborne laser scanning data (or lidar) and very high resolution multispectral imagery for automatic forest stand delineation and forest land-cover database update is proposed. The multispectral images give access to the tree species whereas 3D lidar point clouds provide geometric information on the trees. Therefore, multi-modal features are computed, both at pixel and object levels. The objects are individual trees extracted from lidar data. A supervised classification is performed at the object level on the computed features in order to coarsely discriminate the existing tree species in the area of interest. The analysis at tree level is particularly relevant since it significantly improves the tree species classification. A probability map is generated through the tree species classification and inserted with the pixel-based features map in an energetical framework. The proposed energy is then minimized using a standard graph-cut method (namely QPBO with α-expansion) in order to produce a segmentation map with a controlled level of details. Comparison with an existing forest land cover database shows that our method provides satisfactory results both in terms of stand labelling and delineation (matching ranges between 94% and 99%).

Quadrilinear CCD sensors for the multispectral channel of spaceborne imagers

NASA Astrophysics Data System (ADS)

Materne, Alex; Gili, Bruno; Laubier, David; Gimenez, Thierry

2001-12-01

The PLEIADES-HR Earth Observation satellites will combine a high resolution panchromatic channel -- 0.7 m at nadir -- and a multispectral channel allowing a 2.8 m resolution. This paper presents the main specifications, design and performances of a 52 microns pitch quadrilinear CCD sensor developed by ATMEL under CNES contract, for the multispectral channel of the PLEIADES-HR instrument. The monolithic CCD device includes four lines of 1500 pixels, each line dedicated to a narrow spectral band within blue to near infra red spectrum. The design of the photodiodes and CCD registers, with larger size than those developed up to now for CNES spaceborne imagers, needed some specific structures to break the large equipotential areas where charge do not flow properly. Results are presented on the options which were experimented to improve sensitivity, maintain transfer efficiency and reduce power dissipation. The four spectral bands are achieved by four stripe filters made by SAGEM-REOSC PRODUCTS on a glass substrate, to be assembled on the sensor window. Line to line spacing on the silicon die takes into account the results of straylight analysis. A mineral layer, with high optical absorption performances is deposited between photosensitive lines to further reduce straylight.

Cogongrass inventory and management.

DOT National Transportation Integrated Search

2007-08-01

A field study was conducted from 2005-2006 to test broad scale classification of cogongrass (Imperata cylindrica (L.) Beauv.) on Mississippi highway rights of ways with aerial imagery. Four mosaics of high resolution multispectral images of median an...

Fusion of MultiSpectral and Panchromatic Images Based on Morphological Operators.

PubMed

Restaino, Rocco; Vivone, Gemine; Dalla Mura, Mauro; Chanussot, Jocelyn

2016-04-20

Nonlinear decomposition schemes constitute an alternative to classical approaches for facing the problem of data fusion. In this paper we discuss the application of this methodology to a popular remote sensing application called pansharpening, which consists in the fusion of a low resolution multispectral image and a high resolution panchromatic image. We design a complete pansharpening scheme based on the use of morphological half gradients operators and demonstrate the suitability of this algorithm through the comparison with state of the art approaches. Four datasets acquired by the Pleiades, Worldview-2, Ikonos and Geoeye-1 satellites are employed for the performance assessment, testifying the effectiveness of the proposed approach in producing top-class images with a setting independent of the specific sensor.

Automatic Registration of GF4 Pms: a High Resolution Multi-Spectral Sensor on Board a Satellite on Geostationary Orbit

NASA Astrophysics Data System (ADS)

Gao, M.; Li, J.

2018-04-01

Geometric correction is an important preprocessing process in the application of GF4 PMS image. The method of geometric correction that is based on the manual selection of geometric control points is time-consuming and laborious. The more common method, based on a reference image, is automatic image registration. This method involves several steps and parameters. For the multi-spectral sensor GF4 PMS, it is necessary for us to identify the best combination of parameters and steps. This study mainly focuses on the following issues: necessity of Rational Polynomial Coefficients (RPC) correction before automatic registration, base band in the automatic registration and configuration of GF4 PMS spatial resolution.

Hybrid Image Fusion for Sharpness Enhancement of Multi-Spectral Lunar Images

NASA Astrophysics Data System (ADS)

Awumah, Anna; Mahanti, Prasun; Robinson, Mark

2016-10-01

Image fusion enhances the sharpness of a multi-spectral (MS) image by incorporating spatial details from a higher-resolution panchromatic (Pan) image [1,2]. Known applications of image fusion for planetary images are rare, although image fusion is well-known for its applications to Earth-based remote sensing. In a recent work [3], six different image fusion algorithms were implemented and their performances were verified with images from the Lunar Reconnaissance Orbiter (LRO) Camera. The image fusion procedure obtained a high-resolution multi-spectral (HRMS) product from the LRO Narrow Angle Camera (used as Pan) and LRO Wide Angle Camera (used as MS) images. The results showed that the Intensity-Hue-Saturation (IHS) algorithm results in a high-spatial quality product while the Wavelet-based image fusion algorithm best preserves spectral quality among all the algorithms. In this work we show the results of a hybrid IHS-Wavelet image fusion algorithm when applied to LROC MS images. The hybrid method provides the best HRMS product - both in terms of spatial resolution and preservation of spectral details. Results from hybrid image fusion can enable new science and increase the science return from existing LROC images.[1] Pohl, Cle, and John L. Van Genderen. "Review article multisensor image fusion in remote sensing: concepts, methods and applications." International journal of remote sensing 19.5 (1998): 823-854.[2] Zhang, Yun. "Understanding image fusion." Photogramm. Eng. Remote Sens 70.6 (2004): 657-661.[3] Mahanti, Prasun et al. "Enhancement of spatial resolution of the LROC Wide Angle Camera images." Archives, XXIII ISPRS Congress Archives (2016).

D Land Cover Classification Based on Multispectral LIDAR Point Clouds

NASA Astrophysics Data System (ADS)

Zou, Xiaoliang; Zhao, Guihua; Li, Jonathan; Yang, Yuanxi; Fang, Yong

2016-06-01

Multispectral Lidar System can emit simultaneous laser pulses at the different wavelengths. The reflected multispectral energy is captured through a receiver of the sensor, and the return signal together with the position and orientation information of sensor is recorded. These recorded data are solved with GNSS/IMU data for further post-processing, forming high density multispectral 3D point clouds. As the first commercial multispectral airborne Lidar sensor, Optech Titan system is capable of collecting point clouds data from all three channels at 532nm visible (Green), at 1064 nm near infrared (NIR) and at 1550nm intermediate infrared (IR). It has become a new source of data for 3D land cover classification. The paper presents an Object Based Image Analysis (OBIA) approach to only use multispectral Lidar point clouds datasets for 3D land cover classification. The approach consists of three steps. Firstly, multispectral intensity images are segmented into image objects on the basis of multi-resolution segmentation integrating different scale parameters. Secondly, intensity objects are classified into nine categories by using the customized features of classification indexes and a combination the multispectral reflectance with the vertical distribution of object features. Finally, accuracy assessment is conducted via comparing random reference samples points from google imagery tiles with the classification results. The classification results show higher overall accuracy for most of the land cover types. Over 90% of overall accuracy is achieved via using multispectral Lidar point clouds for 3D land cover classification.

Natural Resource Assessments in Afghanistan Through High Resolution Digital Elevation Modeling and Multi-spectral Image Analysis

NASA Technical Reports Server (NTRS)

Chirico, Peter G.

2007-01-01

This viewgraph presentation provides USGS/USAID natural resource assessments in Afghanistan through the mapping of coal, oil and natural gas, minerals, hydrologic resources and earthquake and flood hazards.

Precision Viticulture from Multitemporal, Multispectral Very High Resolution Satellite Data

NASA Astrophysics Data System (ADS)

Kandylakis, Z.; Karantzalos, K.

2016-06-01

In order to exploit efficiently very high resolution satellite multispectral data for precision agriculture applications, validated methodologies should be established which link the observed reflectance spectra with certain crop/plant/fruit biophysical and biochemical quality parameters. To this end, based on concurrent satellite and field campaigns during the veraison period, satellite and in-situ data were collected, along with several grape samples, at specific locations during the harvesting period. These data were collected for a period of three years in two viticultural areas in Northern Greece. After the required data pre-processing, canopy reflectance observations, through the combination of several vegetation indices were correlated with the quantitative results from the grape/must analysis of grape sampling. Results appear quite promising, indicating that certain key quality parameters (like brix levels, total phenolic content, brix to total acidity, anthocyanin levels) which describe the oenological potential, phenolic composition and chromatic characteristics can be efficiently estimated from the satellite data.

Examples of Level Products Possible from Existing Assets

NASA Technical Reports Server (NTRS)

Quattrochi, Dale A.

2012-01-01

How do patterns of human environmental and infectious diseases respond to leading environmental changes, particularly to urban growth and change and the associated impacts of urbanization? We use HyspIRI high spatial resolution, multispectral, and multitemporal TIR data to track energy balance and energy flux characteristics for changing land covers/land uses through time to provide synoptic views of impacts on surface energy fluxes, emissivity and temperature and HyspIRI data in conjunction with spatial growth models to project land cover/land use changes in the future to assess impacts on natural and human ecosystems. We use multispectral thermal IR land cover maps at a high spatial resolution (60m) on a weekly basis for long-term validation of surface energy responses and changes in emissivity and integration of HyspIRI TIR data with spatial modeling to assess changes in land cover/land use through time and subsequent changes in thermal energy responses

Compressive hyperspectral and multispectral imaging fusion

NASA Astrophysics Data System (ADS)

Espitia, Óscar; Castillo, Sergio; Arguello, Henry

2016-05-01

Image fusion is a valuable framework which combines two or more images of the same scene from one or multiple sensors, allowing to improve the resolution of the images and increase the interpretable content. In remote sensing a common fusion problem consists of merging hyperspectral (HS) and multispectral (MS) images that involve large amount of redundant data, which ignores the highly correlated structure of the datacube along the spatial and spectral dimensions. Compressive HS and MS systems compress the spectral data in the acquisition step allowing to reduce the data redundancy by using different sampling patterns. This work presents a compressed HS and MS image fusion approach, which uses a high dimensional joint sparse model. The joint sparse model is formulated by combining HS and MS compressive acquisition models. The high spectral and spatial resolution image is reconstructed by using sparse optimization algorithms. Different fusion spectral image scenarios are used to explore the performance of the proposed scheme. Several simulations with synthetic and real datacubes show promising results as the reliable reconstruction of a high spectral and spatial resolution image can be achieved by using as few as just the 50% of the datacube.

Combined use of LiDAR data and multispectral earth observation imagery for wetland habitat mapping

NASA Astrophysics Data System (ADS)

Rapinel, Sébastien; Hubert-Moy, Laurence; Clément, Bernard

2015-05-01

Although wetlands play a key role in controlling flooding and nonpoint source pollution, sequestering carbon and providing an abundance of ecological services, the inventory and characterization of wetland habitats are most often limited to small areas. This explains why the understanding of their ecological functioning is still insufficient for a reliable functional assessment on areas larger than a few hectares. While LiDAR data and multispectral Earth Observation (EO) images are often used separately to map wetland habitats, their combined use is currently being assessed for different habitat types. The aim of this study is to evaluate the combination of multispectral and multiseasonal imagery and LiDAR data to precisely map the distribution of wetland habitats. The image classification was performed combining an object-based approach and decision-tree modeling. Four multispectral images with high (SPOT-5) and very high spatial resolution (Quickbird, KOMPSAT-2, aerial photographs) were classified separately. Another classification was then applied integrating summer and winter multispectral image data and three layers derived from LiDAR data: vegetation height, microtopography and intensity return. The comparison of classification results shows that some habitats are better identified on the winter image and others on the summer image (overall accuracies = 58.5 and 57.6%). They also point out that classification accuracy is highly improved (overall accuracy = 86.5%) when combining LiDAR data and multispectral images. Moreover, this study highlights the advantage of integrating vegetation height, microtopography and intensity parameters in the classification process. This article demonstrates that information provided by the synergetic use of multispectral images and LiDAR data can help in wetland functional assessment

Synthesis of Multispectral Bands from Hyperspectral Data: Validation Based on Images Acquired by AVIRIS, Hyperion, ALI, and ETM+

NASA Technical Reports Server (NTRS)

Blonksi, Slawomir; Gasser, Gerald; Russell, Jeffrey; Ryan, Robert; Terrie, Greg; Zanoni, Vicki

2001-01-01

Multispectral data requirements for Earth science applications are not always studied rigorously studied before a new remote sensing system is designed. A study of the spatial resolution, spectral bandpasses, and radiometric sensitivity requirements of real-world applications would focus the design onto providing maximum benefits to the end-user community. To support systematic studies of multispectral data requirements, the Applications Research Toolbox (ART) has been developed at NASA's Stennis Space Center. The ART software allows users to create and assess simulated datasets while varying a wide range of system parameters. The simulations are based on data acquired by existing multispectral and hyperspectral instruments. The produced datasets can be further evaluated for specific end-user applications. Spectral synthesis of multispectral images from hyperspectral data is a key part of the ART software. In this process, hyperspectral image cubes are transformed into multispectral imagery without changes in spatial sampling and resolution. The transformation algorithm takes into account spectral responses of both the synthesized, broad, multispectral bands and the utilized, narrow, hyperspectral bands. To validate the spectral synthesis algorithm, simulated multispectral images are compared with images collected near-coincidentally by the Landsat 7 ETM+ and the EO-1 ALI instruments. Hyperspectral images acquired with the airborne AVIRIS instrument and with the Hyperion instrument onboard the EO-1 satellite were used as input data to the presented simulations.

Progressive Vector Quantization on a massively parallel SIMD machine with application to multispectral image data

NASA Technical Reports Server (NTRS)

Manohar, Mareboyana; Tilton, James C.

1994-01-01

A progressive vector quantization (VQ) compression approach is discussed which decomposes image data into a number of levels using full search VQ. The final level is losslessly compressed, enabling lossless reconstruction. The computational difficulties are addressed by implementation on a massively parallel SIMD machine. We demonstrate progressive VQ on multispectral imagery obtained from the Advanced Very High Resolution Radiometer instrument and other Earth observation image data, and investigate the trade-offs in selecting the number of decomposition levels and codebook training method.

Determination of atmospheric moisture structure and infrared cooling rates from high resolution MAMS radiance data

NASA Technical Reports Server (NTRS)

Menzel, W. Paul; Moeller, Christopher C.; Smith, William L.

1991-01-01

This program has applied Multispectral Atmospheric Mapping Sensor (MAMS) high resolution data to the problem of monitoring atmospheric quantities of moisture and radiative flux at small spatial scales. MAMS, with 100-m horizontal resolution in its four infrared channels, was developed to study small scale atmospheric moisture and surface thermal variability, especially as related to the development of clouds, precipitation, and severe storms. High-resolution Interferometer Sounder (HIS) data has been used to develop a high spectral resolution retrieval algorithm for producing vertical profiles of atmospheric temperature and moisture. The results of this program are summarized and a list of publications resulting from this contract is presented. Selected publications are attached as an appendix.

Integrated change detection and temporal trajectory analysis of coastal wetlands using high spatial resolution Korean Multi-Purpose Satellite series imagery

NASA Astrophysics Data System (ADS)

Nguyen, Hoang Hai; Tran, Hien; Sunwoo, Wooyeon; Yi, Jong-hyuk; Kim, Dongkyun; Choi, Minha

2017-04-01

A series of multispectral high-resolution Korean Multi-Purpose Satellite (KOMPSAT) images was used to detect the geographical changes in four different tidal flats between the Yellow Sea and the west coast of South Korea. The method of unsupervised classification was used to generate a series of land use/land cover (LULC) maps from satellite images, which were then used as input for temporal trajectory analysis to detect the temporal change of coastal wetlands and its association with natural and anthropogenic activities. The accurately classified LULC maps of KOMPSAT images, with overall accuracy ranging from 83.34% to 95.43%, indicate that these multispectral high-resolution satellite data are highly applicable to the generation of high-quality thematic maps for extracting wetlands. The result of the trajectory analysis showed that, while the variation of the tidal flats in the Gyeonggi and Jeollabuk provinces was well correlated with the regular tidal regimes, the reductive trajectory of the wetland areas belonging to the Saemangeum province was caused by a high degree of human-induced activities including large reclamation and urbanization. The conservation of the Jeungdo Wetland Protected Area in the Jeollanam province revealed that effective social and environmental policies could help in protecting coastal wetlands from degradation.

High Spatial Resolution Thermal Satellite Technologies

NASA Technical Reports Server (NTRS)

Ryan, Robert

2003-01-01

This document in the form of viewslides, reviews various low-cost alternatives to high spatial resolution thermal satellite technologies. There exists no follow-on to Landsat 7 or ASTER high spatial resolution thermal systems. This document reviews the results of the investigation in to the use of new technologies to create a low-cost useful alternative. Three suggested technologies are examined. 1. Conventional microbolometer pushbroom modes offers potential for low cost Landsat Data Continuity Mission (LDCM) thermal or ASTER capability with at least 60-120 ground sampling distance (GSD). 2. Backscanning could produce MultiSpectral Thermal Imager performance without cooled detectors. 3. Cooled detector could produce hyperspectral thermal class system or extremely high spatial resolution class instrument.

SPLASSH: Open source software for camera-based high-speed, multispectral in-vivo optical image acquisition

PubMed Central

Sun, Ryan; Bouchard, Matthew B.; Hillman, Elizabeth M. C.

2010-01-01

Camera-based in-vivo optical imaging can provide detailed images of living tissue that reveal structure, function, and disease. High-speed, high resolution imaging can reveal dynamic events such as changes in blood flow and responses to stimulation. Despite these benefits, commercially available scientific cameras rarely include software that is suitable for in-vivo imaging applications, making this highly versatile form of optical imaging challenging and time-consuming to implement. To address this issue, we have developed a novel, open-source software package to control high-speed, multispectral optical imaging systems. The software integrates a number of modular functions through a custom graphical user interface (GUI) and provides extensive control over a wide range of inexpensive IEEE 1394 Firewire cameras. Multispectral illumination can be incorporated through the use of off-the-shelf light emitting diodes which the software synchronizes to image acquisition via a programmed microcontroller, allowing arbitrary high-speed illumination sequences. The complete software suite is available for free download. Here we describe the software’s framework and provide details to guide users with development of this and similar software. PMID:21258475

Verification of small-scale water vapor features in VAS imagery using high resolution MAMS imagery. [VISSR Atmospheric Sounder - Multispectral Atmospheric Mapping Sensor

NASA Technical Reports Server (NTRS)

Menzel, Paul W.; Jedlovec, Gary; Wilson, Gregory

1986-01-01

The Multispectral Atmospheric Mapping Sensor (MAMS), a modification of NASA's Airborne Thematic Mapper, is described, and radiances from the MAMS and the VISSR Atmospheric Sounder (VAS) are compared which were collected simultaneously on May 18, 1985. Thermal emission from the earth atmosphere system in eight visible and three infrared spectral bands (12.3, 11.2 and 6.5 microns) are measured by the MAMS at up to 50 m horizontal resolution, and the infrared bands are similar to three of the VAS infrared bands. Similar radiometric performance was found for the two systems, though the MAMS showed somewhat less attenuation from water vapor than VAS because its spectral bands are shifted to shorter wavelengths away from the absorption band center.

Validating MODIS and Sentinel-2 NDVI Products at a Temperate Deciduous Forest Site Using Two Independent Ground-Based Sensors.

PubMed

Lange, Maximilian; Dechant, Benjamin; Rebmann, Corinna; Vohland, Michael; Cuntz, Matthias; Doktor, Daniel

2017-08-11

Quantifying the accuracy of remote sensing products is a timely endeavor given the rapid increase in Earth observation missions. A validation site for Sentinel-2 products was hence established in central Germany. Automatic multispectral and hyperspectral sensor systems were installed in parallel with an existing eddy covariance flux tower, providing spectral information of the vegetation present at high temporal resolution. Normalized Difference Vegetation Index (NDVI) values from ground-based hyperspectral and multispectral sensors were compared with NDVI products derived from Sentinel-2A and Moderate-resolution Imaging Spectroradiometer (MODIS). The influence of different spatial and temporal resolutions was assessed. High correlations and similar phenological patterns between in situ and satellite-based NDVI time series demonstrated the reliability of satellite-based phenological metrics. Sentinel-2-derived metrics showed better agreement with in situ measurements than MODIS-derived metrics. Dynamic filtering with the best index slope extraction algorithm was nevertheless beneficial for Sentinel-2 NDVI time series despite the availability of quality information from the atmospheric correction procedure.

Validating MODIS and Sentinel-2 NDVI Products at a Temperate Deciduous Forest Site Using Two Independent Ground-Based Sensors

PubMed Central

Lange, Maximilian; Rebmann, Corinna; Cuntz, Matthias; Doktor, Daniel

2017-01-01

Quantifying the accuracy of remote sensing products is a timely endeavor given the rapid increase in Earth observation missions. A validation site for Sentinel-2 products was hence established in central Germany. Automatic multispectral and hyperspectral sensor systems were installed in parallel with an existing eddy covariance flux tower, providing spectral information of the vegetation present at high temporal resolution. Normalized Difference Vegetation Index (NDVI) values from ground-based hyperspectral and multispectral sensors were compared with NDVI products derived from Sentinel-2A and Moderate-resolution Imaging Spectroradiometer (MODIS). The influence of different spatial and temporal resolutions was assessed. High correlations and similar phenological patterns between in situ and satellite-based NDVI time series demonstrated the reliability of satellite-based phenological metrics. Sentinel-2-derived metrics showed better agreement with in situ measurements than MODIS-derived metrics. Dynamic filtering with the best index slope extraction algorithm was nevertheless beneficial for Sentinel-2 NDVI time series despite the availability of quality information from the atmospheric correction procedure. PMID:28800065

Assessing very high resolution UAV imagery for monitoring forest health during a simulated disease outbreak

NASA Astrophysics Data System (ADS)

Dash, Jonathan P.; Watt, Michael S.; Pearse, Grant D.; Heaphy, Marie; Dungey, Heidi S.

2017-09-01

Research into remote sensing tools for monitoring physiological stress caused by biotic and abiotic factors is critical for maintaining healthy and highly-productive plantation forests. Significant research has focussed on assessing forest health using remotely sensed data from satellites and manned aircraft. Unmanned aerial vehicles (UAVs) may provide new tools for improved forest health monitoring by providing data with very high temporal and spatial resolutions. These platforms also pose unique challenges and methods for health assessments must be validated before use. In this research, we simulated a disease outbreak in mature Pinus radiata D. Don trees using targeted application of herbicide. The objective was to acquire a time-series simulated disease expression dataset to develop methods for monitoring physiological stress from a UAV platform. Time-series multi-spectral imagery was acquired using a UAV flown over a trial at regular intervals. Traditional field-based health assessments of crown health (density) and needle health (discolouration) were carried out simultaneously by experienced forest health experts. Our results showed that multi-spectral imagery collected from a UAV is useful for identifying physiological stress in mature plantation trees even during the early stages of tree stress. We found that physiological stress could be detected earliest in data from the red edge and near infra-red bands. In contrast to previous findings, red edge data did not offer earlier detection of physiological stress than the near infra-red data. A non-parametric approach was used to model physiological stress based on spectral indices and was found to provide good classification accuracy (weighted kappa = 0.694). This model can be used to map physiological stress based on high-resolution multi-spectral data.

Computational multispectral video imaging [Invited].

PubMed

Wang, Peng; Menon, Rajesh

2018-01-01

Multispectral imagers reveal information unperceivable to humans and conventional cameras. Here, we demonstrate a compact single-shot multispectral video-imaging camera by placing a micro-structured diffractive filter in close proximity to the image sensor. The diffractive filter converts spectral information to a spatial code on the sensor pixels. Following a calibration step, this code can be inverted via regularization-based linear algebra to compute the multispectral image. We experimentally demonstrated spectral resolution of 9.6 nm within the visible band (430-718 nm). We further show that the spatial resolution is enhanced by over 30% compared with the case without the diffractive filter. We also demonstrate Vis-IR imaging with the same sensor. Because no absorptive color filters are utilized, sensitivity is preserved as well. Finally, the diffractive filters can be easily manufactured using optical lithography and replication techniques.

The Need for High Spatial Resolution Multispectral Thermal Remote Sensing Data In Urban Heat Island Research

NASA Technical Reports Server (NTRS)

Quattrochi, Dale A.; Luvall, Jeffrey C.

2006-01-01

Although the study of the Urban Heat Island (UHI) effect dates back to the early 1800's when Luke Howard discovered London s heat island, it has only been with the advent of thermal remote sensing systems that the extent, characteristics, and impacts of the UHI have become to be understood. Analysis of the UHI effect is important because above all, this phenomenon can directly influence the health and welfare of urban residents. For example, in 1995, over 700 people died in Chicago due to heat-related causes. UHI s are characterized by increased temperature in comparison to rural areas and mortality rates during a heat wave increase exponentially with the maximum temperature, an effect that is exacerbated by the UHI. Aside from the direct impacts of the UHI on temperature, UHI s can produce secondary effects on local meteorology, including altering local wind patterns, increased development of clouds and fog, and increasing rates of precipitation either over, or downwind, of cities. Because of the extreme heterogeneity of the urban surface, in combination with the sprawl associated with urban growth, thermal infrared (TIR) remote sensing data have become of significant importance in understanding how land cover and land use characteristics affect the development and intensification of the UHI. TIR satellite data have been used extensively to analyze the surface temperature regimes of cities to help observe and measure the impacts of surface temperatures across the urban landscape. However, the spatial scales at which satellite TIR data are collected are for the most part, coarse, with the finest readily available TIR data collected by the Landsat ETM+ sensor at 60m spatial resolution. For many years, we have collected high spatial resolution (10m) data using an airborne multispectral TIR sensor over a number of cities across the United States. These high resolution data have been used to develop an understanding of how discrete surfaces across the urban environment (e.g., rooftops, pavements) interact from a surface-lower atmosphere energy flux perspective, to force the development of the UHI. Moreover, the airborne TIR sensor we used in our UHI studies was a multispectral sensor that had six channels in the 8-12pm range. The advantages of collecting multispectral TIR data became readily evident as a valuable tool for better calculation of unique surface thermal energy responses for urban materials over the 8-12 micrometer region, and also for getting a better handle on surface emissivity characteristics for these discrete surfaces. In this presentation, we will provide evidence on the virtues of how high spatial resolution multispectral TIR data can provide for better analysis of the UHI that cannot now be attained via TIR data obtained from satellites. Furthermore, we wish to provide compelling evidence on why future TIR satellite sensors should collect data at fine spatial resolutions (e.g. less than or equal to 30m) to better allow for measurement of surface thermal energy fluxes from discrete urban surfaces, and to better understand how surface fluxes from different urban materials in cities around the world in different climatic regimes, affect development of the UHI characteristics.

The High Resolution Stereo Camera (HRSC): 10 Years of Imaging Mars

NASA Astrophysics Data System (ADS)

Jaumann, R.; Neukum, G.; Tirsch, D.; Hoffmann, H.

2014-04-01

The HRSC Experiment: Imagery is the major source for our current understanding of the geologic evolution of Mars in qualitative and quantitative terms.Imaging is required to enhance our knowledge of Mars with respect to geological processes occurring on local, regional and global scales and is an essential prerequisite for detailed surface exploration. The High Resolution Stereo Camera (HRSC) of ESA's Mars Express Mission (MEx) is designed to simultaneously map the morphology, topography, structure and geologic context of the surface of Mars as well as atmospheric phenomena [1]. The HRSC directly addresses two of the main scientific goals of the Mars Express mission: (1) High-resolution three-dimensional photogeologic surface exploration and (2) the investigation of surface-atmosphere interactions over time; and significantly supports: (3) the study of atmospheric phenomena by multi-angle coverage and limb sounding as well as (4) multispectral mapping by providing high-resolution threedimensional color context information. In addition, the stereoscopic imagery will especially characterize landing sites and their geologic context [1]. The HRSC surface resolution and the digital terrain models bridge the gap in scales between highest ground resolution images (e.g., HiRISE) and global coverage observations (e.g., Viking). This is also the case with respect to DTMs (e.g., MOLA and local high-resolution DTMs). HRSC is also used as cartographic basis to correlate between panchromatic and multispectral stereo data. The unique multi-angle imaging technique of the HRSC supports its stereo capability by providing not only a stereo triplet but also a stereo quintuplet, making the photogrammetric processing very robust [1, 3]. The capabilities for three dimensional orbital reconnaissance of the Martian surface are ideally met by HRSC making this camera unique in the international Mars exploration effort.

Single-Image Super Resolution for Multispectral Remote Sensing Data Using Convolutional Neural Networks

NASA Astrophysics Data System (ADS)

Liebel, L.; Körner, M.

2016-06-01

In optical remote sensing, spatial resolution of images is crucial for numerous applications. Space-borne systems are most likely to be affected by a lack of spatial resolution, due to their natural disadvantage of a large distance between the sensor and the sensed object. Thus, methods for single-image super resolution are desirable to exceed the limits of the sensor. Apart from assisting visual inspection of datasets, post-processing operations—e.g., segmentation or feature extraction—can benefit from detailed and distinguishable structures. In this paper, we show that recently introduced state-of-the-art approaches for single-image super resolution of conventional photographs, making use of deep learning techniques, such as convolutional neural networks (CNN), can successfully be applied to remote sensing data. With a huge amount of training data available, end-to-end learning is reasonably easy to apply and can achieve results unattainable using conventional handcrafted algorithms. We trained our CNN on a specifically designed, domain-specific dataset, in order to take into account the special characteristics of multispectral remote sensing data. This dataset consists of publicly available SENTINEL-2 images featuring 13 spectral bands, a ground resolution of up to 10m, and a high radiometric resolution and thus satisfying our requirements in terms of quality and quantity. In experiments, we obtained results superior compared to competing approaches trained on generic image sets, which failed to reasonably scale satellite images with a high radiometric resolution, as well as conventional interpolation methods.

Multi-Spectral Stereo Atmospheric Remote Sensing (STARS) for Retrieval of Cloud Properties and Cloud-Motion Vectors

NASA Astrophysics Data System (ADS)

Kelly, M. A.; Boldt, J.; Wilson, J. P.; Yee, J. H.; Stoffler, R.

2017-12-01

The multi-spectral STereo Atmospheric Remote Sensing (STARS) concept has the objective to provide high-spatial and -temporal-resolution observations of 3D cloud structures related to hurricane development and other severe weather events. The rapid evolution of severe weather demonstrates a critical need for mesoscale observations of severe weather dynamics, but such observations are rare, particularly over the ocean where extratropical and tropical cyclones can undergo explosive development. Coincident space-based measurements of wind velocity and cloud properties at the mesoscale remain a great challenge, but are critically needed to improve the understanding and prediction of severe weather and cyclogenesis. STARS employs a mature stereoscopic imaging technique on two satellites (e.g. two CubeSats, two hosted payloads) to simultaneously retrieve cloud motion vectors (CMVs), cloud-top temperatures (CTTs), and cloud geometric heights (CGHs) from multi-angle, multi-spectral observations of cloud features. STARS is a pushbroom system based on separate wide-field-of-view co-boresighted multi-spectral cameras in the visible, midwave infrared (MWIR), and longwave infrared (LWIR) with high spatial resolution (better than 1 km). The visible system is based on a pan-chromatic, low-light imager to resolve cloud structures under nighttime illumination down to ¼ moon. The MWIR instrument, which is being developed as a NASA ESTO Instrument Incubator Program (IIP) project, is based on recent advances in MWIR detector technology that requires only modest cooling. The STARS payload provides flexible options for spaceflight due to its low size, weight, power (SWaP) and very modest cooling requirements. STARS also meets AF operational requirements for cloud characterization and theater weather imagery. In this paper, an overview of the STARS concept, including the high-level sensor design, the concept of operations, and measurement capability will be presented.

Higher resolution satellite remote sensing and the impact on image mapping

USGS Publications Warehouse

Watkins, Allen H.; Thormodsgard, June M.

1987-01-01

Recent advances in spatial, spectral, and temporal resolution of civil land remote sensing satellite data are presenting new opportunities for image mapping applications. The U.S. Geological Survey's experimental satellite image mapping program is evolving toward larger scale image map products with increased information content as a result of improved image processing techniques and increased resolution. Thematic mapper data are being used to produce experimental image maps at 1:100,000 scale that meet established U.S. and European map accuracy standards. Availability of high quality, cloud-free, 30-meter ground resolution multispectral data from the Landsat thematic mapper sensor, along with 10-meter ground resolution panchromatic and 20-meter ground resolution multispectral data from the recently launched French SPOT satellite, present new cartographic and image processing challenges.The need to fully exploit these higher resolution data increases the complexity of processing the images into large-scale image maps. The removal of radiometric artifacts and noise prior to geometric correction can be accomplished by using a variety of image processing filters and transforms. Sensor modeling and image restoration techniques allow maximum retention of spatial and radiometric information. An optimum combination of spectral information and spatial resolution can be obtained by merging different sensor types. These processing techniques are discussed and examples are presented.

Enhancing hyperspectral spatial resolution using multispectral image fusion: A wavelet approach

NASA Astrophysics Data System (ADS)

Jazaeri, Amin

High spectral and spatial resolution images have a significant impact in remote sensing applications. Because both spatial and spectral resolutions of spaceborne sensors are fixed by design and it is not possible to further increase the spatial or spectral resolution, techniques such as image fusion must be applied to achieve such goals. This dissertation introduces the concept of wavelet fusion between hyperspectral and multispectral sensors in order to enhance the spectral and spatial resolution of a hyperspectral image. To test the robustness of this concept, images from Hyperion (hyperspectral sensor) and Advanced Land Imager (multispectral sensor) were first co-registered and then fused using different wavelet algorithms. A regression-based fusion algorithm was also implemented for comparison purposes. The results show that the fused images using a combined bi-linear wavelet-regression algorithm have less error than other methods when compared to the ground truth. In addition, a combined regression-wavelet algorithm shows more immunity to misalignment of the pixels due to the lack of proper registration. The quantitative measures of average mean square error show that the performance of wavelet-based methods degrades when the spatial resolution of hyperspectral images becomes eight times less than its corresponding multispectral image. Regardless of what method of fusion is utilized, the main challenge in image fusion is image registration, which is also a very time intensive process. Because the combined regression wavelet technique is computationally expensive, a hybrid technique based on regression and wavelet methods was also implemented to decrease computational overhead. However, the gain in faster computation was offset by the introduction of more error in the outcome. The secondary objective of this dissertation is to examine the feasibility and sensor requirements for image fusion for future NASA missions in order to be able to perform onboard image fusion. In this process, the main challenge of image registration was resolved by registering the input images using transformation matrices of previously acquired data. The composite image resulted from the fusion process remarkably matched the ground truth, indicating the possibility of real time onboard fusion processing.

Hyperspectral Super-Resolution of Locally Low Rank Images From Complementary Multisource Data.

PubMed

Veganzones, Miguel A; Simoes, Miguel; Licciardi, Giorgio; Yokoya, Naoto; Bioucas-Dias, Jose M; Chanussot, Jocelyn

2016-01-01

Remote sensing hyperspectral images (HSIs) are quite often low rank, in the sense that the data belong to a low dimensional subspace/manifold. This has been recently exploited for the fusion of low spatial resolution HSI with high spatial resolution multispectral images in order to obtain super-resolution HSI. Most approaches adopt an unmixing or a matrix factorization perspective. The derived methods have led to state-of-the-art results when the spectral information lies in a low-dimensional subspace/manifold. However, if the subspace/manifold dimensionality spanned by the complete data set is large, i.e., larger than the number of multispectral bands, the performance of these methods mainly decreases because the underlying sparse regression problem is severely ill-posed. In this paper, we propose a local approach to cope with this difficulty. Fundamentally, we exploit the fact that real world HSIs are locally low rank, that is, pixels acquired from a given spatial neighborhood span a very low-dimensional subspace/manifold, i.e., lower or equal than the number of multispectral bands. Thus, we propose to partition the image into patches and solve the data fusion problem independently for each patch. This way, in each patch the subspace/manifold dimensionality is low enough, such that the problem is not ill-posed anymore. We propose two alternative approaches to define the hyperspectral super-resolution through local dictionary learning using endmember induction algorithms. We also explore two alternatives to define the local regions, using sliding windows and binary partition trees. The effectiveness of the proposed approaches is illustrated with synthetic and semi real data.

Random-Forest Classification of High-Resolution Remote Sensing Images and Ndsm Over Urban Areas

NASA Astrophysics Data System (ADS)

Sun, X. F.; Lin, X. G.

2017-09-01

As an intermediate step between raw remote sensing data and digital urban maps, remote sensing data classification has been a challenging and long-standing research problem in the community of remote sensing. In this work, an effective classification method is proposed for classifying high-resolution remote sensing data over urban areas. Starting from high resolution multi-spectral images and 3D geometry data, our method proceeds in three main stages: feature extraction, classification, and classified result refinement. First, we extract color, vegetation index and texture features from the multi-spectral image and compute the height, elevation texture and differential morphological profile (DMP) features from the 3D geometry data. Then in the classification stage, multiple random forest (RF) classifiers are trained separately, then combined to form a RF ensemble to estimate each sample's category probabilities. Finally the probabilities along with the feature importance indicator outputted by RF ensemble are used to construct a fully connected conditional random field (FCCRF) graph model, by which the classification results are refined through mean-field based statistical inference. Experiments on the ISPRS Semantic Labeling Contest dataset show that our proposed 3-stage method achieves 86.9% overall accuracy on the test data.

Medium-sized aperture camera for Earth observation

NASA Astrophysics Data System (ADS)

Kim, Eugene D.; Choi, Young-Wan; Kang, Myung-Seok; Kim, Ee-Eul; Yang, Ho-Soon; Rasheed, Ad. Aziz Ad.; Arshad, Ahmad Sabirin

2017-11-01

Satrec Initiative and ATSB have been developing a medium-sized aperture camera (MAC) for an earth observation payload on a small satellite. Developed as a push-broom type high-resolution camera, the camera has one panchromatic and four multispectral channels. The panchromatic channel has 2.5m, and multispectral channels have 5m of ground sampling distances at a nominal altitude of 685km. The 300mm-aperture Cassegrain telescope contains two aspheric mirrors and two spherical correction lenses. With a philosophy of building a simple and cost-effective camera, the mirrors incorporate no light-weighting, and the linear CCDs are mounted on a single PCB with no beam splitters. MAC is the main payload of RazakSAT to be launched in 2005. RazakSAT is a 180kg satellite including MAC, designed to provide high-resolution imagery of 20km swath width on a near equatorial orbit (NEqO). The mission objective is to demonstrate the capability of a high-resolution remote sensing satellite system on a near equatorial orbit. This paper describes the overview of the MAC and RarakSAT programmes, and presents the current development status of MAC focusing on key optical aspects of Qualification Model.

High temporal resolution aerosol retrieval using Geostationary Ocean Color Imager: application and initial validation

NASA Astrophysics Data System (ADS)

Zhang, Yuhuan; Li, Zhengqiang; Zhang, Ying; Hou, Weizhen; Xu, Hua; Chen, Cheng; Ma, Yan

2014-01-01

The Geostationary Ocean Color Imager (GOCI) provides multispectral imagery of the East Asia region hourly from 9:00 to 16:00 local time (GMT+9) and collects multispectral imagery at eight spectral channels (412, 443, 490, 555, 660, 680, 745, and 865 nm) with a spatial resolution of 500 m. Thus, this technology brings significant advantages to high temporal resolution environmental monitoring. We present the retrieval of aerosol optical depth (AOD) in northern China based on GOCI data. Cross-calibration was performed against Moderate Resolution Imaging Spectrometer (MODIS) data in order to correct the land calibration bias of the GOCI sensor. AOD retrievals were then accomplished using a look-up table (LUT) strategy with assumptions of a quickly varying aerosol and a slowly varying surface with time. The AOD retrieval algorithm calculates AOD by minimizing the surface reflectance variations of a series of observations in a short period of time, such as several days. The monitoring of hourly AOD variations was implemented, and the retrieved AOD agreed well with AErosol RObotic NETwork (AERONET) ground-based measurements with a good R2 of approximately 0.74 at validation sites at the cities of Beijing and Xianghe, although intercept bias may be high in specific cases. The comparisons with MODIS products also show a good agreement in AOD spatial distribution. This work suggests that GOCI imagery can provide high temporal resolution monitoring of atmospheric aerosols over land, which is of great interest in climate change studies and environmental monitoring.

Integrating optical satellite data and airborne laser scanning in habitat classification for wildlife management

NASA Astrophysics Data System (ADS)

Nijland, W.; Coops, N. C.; Nielsen, S. E.; Stenhouse, G.

2015-06-01

Wildlife habitat selection is determined by a wide range of factors including food availability, shelter, security and landscape heterogeneity all of which are closely related to the more readily mapped landcover types and disturbance regimes. Regional wildlife habitat studies often used moderate resolution multispectral satellite imagery for wall to wall mapping, because it offers a favourable mix of availability, cost and resolution. However, certain habitat characteristics such as canopy structure and topographic factors are not well discriminated with these passive, optical datasets. Airborne laser scanning (ALS) provides highly accurate three dimensional data on canopy structure and the underlying terrain, thereby offers significant enhancements to wildlife habitat mapping. In this paper, we introduce an approach to integrate ALS data and multispectral images to develop a new heuristic wildlife habitat classifier for western Alberta. Our method combines ALS direct measures of canopy height, and cover with optical estimates of species (conifer vs. deciduous) composition into a decision tree classifier for habitat - or landcover types. We believe this new approach is highly versatile and transferable, because class rules can be easily adapted for other species or functional groups. We discuss the implications of increased ALS availability for habitat mapping and wildlife management and provide recommendations for integrating multispectral and ALS data into wildlife management.

Classification of cloud fields based on textural characteristics

NASA Technical Reports Server (NTRS)

Welch, R. M.; Sengupta, S. K.; Chen, D. W.

1987-01-01

The present study reexamines the applicability of texture-based features for automatic cloud classification using very high spatial resolution (57 m) Landsat multispectral scanner digital data. It is concluded that cloud classification can be accomplished using only a single visible channel.

Multisensor Analysis of Spectral Dimensionality and Soil Diversity in the Great Central Valley of California.

PubMed

Sousa, Daniel; Small, Christopher

2018-02-14

Planned hyperspectral satellite missions and the decreased revisit time of multispectral imaging offer the potential for data fusion to leverage both the spectral resolution of hyperspectral sensors and the temporal resolution of multispectral constellations. Hyperspectral imagery can also be used to better understand fundamental properties of multispectral data. In this analysis, we use five flight lines from the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) archive with coincident Landsat 8 acquisitions over a spectrally diverse region of California to address the following questions: (1) How much of the spectral dimensionality of hyperspectral data is captured in multispectral data?; (2) Is the characteristic pyramidal structure of the multispectral feature space also present in the low order dimensions of the hyperspectral feature space at comparable spatial scales?; (3) How much variability in rock and soil substrate endmembers (EMs) present in hyperspectral data is captured by multispectral sensors? We find nearly identical partitions of variance, low-order feature space topologies, and EM spectra for hyperspectral and multispectral image composites. The resulting feature spaces and EMs are also very similar to those from previous global multispectral analyses, implying that the fundamental structure of the global feature space is present in our relatively small spatial subset of California. Finally, we find that the multispectral dataset well represents the substrate EM variability present in the study area - despite its inability to resolve narrow band absorptions. We observe a tentative but consistent physical relationship between the gradation of substrate reflectance in the feature space and the gradation of sand versus clay content in the soil classification system.

Multisensor Analysis of Spectral Dimensionality and Soil Diversity in the Great Central Valley of California

PubMed Central

Small, Christopher

2018-01-01

Planned hyperspectral satellite missions and the decreased revisit time of multispectral imaging offer the potential for data fusion to leverage both the spectral resolution of hyperspectral sensors and the temporal resolution of multispectral constellations. Hyperspectral imagery can also be used to better understand fundamental properties of multispectral data. In this analysis, we use five flight lines from the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) archive with coincident Landsat 8 acquisitions over a spectrally diverse region of California to address the following questions: (1) How much of the spectral dimensionality of hyperspectral data is captured in multispectral data?; (2) Is the characteristic pyramidal structure of the multispectral feature space also present in the low order dimensions of the hyperspectral feature space at comparable spatial scales?; (3) How much variability in rock and soil substrate endmembers (EMs) present in hyperspectral data is captured by multispectral sensors? We find nearly identical partitions of variance, low-order feature space topologies, and EM spectra for hyperspectral and multispectral image composites. The resulting feature spaces and EMs are also very similar to those from previous global multispectral analyses, implying that the fundamental structure of the global feature space is present in our relatively small spatial subset of California. Finally, we find that the multispectral dataset well represents the substrate EM variability present in the study area – despite its inability to resolve narrow band absorptions. We observe a tentative but consistent physical relationship between the gradation of substrate reflectance in the feature space and the gradation of sand versus clay content in the soil classification system. PMID:29443900

Classification Accuracy Increase Using Multisensor Data Fusion

NASA Astrophysics Data System (ADS)

Makarau, A.; Palubinskas, G.; Reinartz, P.

2011-09-01

The practical use of very high resolution visible and near-infrared (VNIR) data is still growing (IKONOS, Quickbird, GeoEye-1, etc.) but for classification purposes the number of bands is limited in comparison to full spectral imaging. These limitations may lead to the confusion of materials such as different roofs, pavements, roads, etc. and therefore may provide wrong interpretation and use of classification products. Employment of hyperspectral data is another solution, but their low spatial resolution (comparing to multispectral data) restrict their usage for many applications. Another improvement can be achieved by fusion approaches of multisensory data since this may increase the quality of scene classification. Integration of Synthetic Aperture Radar (SAR) and optical data is widely performed for automatic classification, interpretation, and change detection. In this paper we present an approach for very high resolution SAR and multispectral data fusion for automatic classification in urban areas. Single polarization TerraSAR-X (SpotLight mode) and multispectral data are integrated using the INFOFUSE framework, consisting of feature extraction (information fission), unsupervised clustering (data representation on a finite domain and dimensionality reduction), and data aggregation (Bayesian or neural network). This framework allows a relevant way of multisource data combination following consensus theory. The classification is not influenced by the limitations of dimensionality, and the calculation complexity primarily depends on the step of dimensionality reduction. Fusion of single polarization TerraSAR-X, WorldView-2 (VNIR or full set), and Digital Surface Model (DSM) data allow for different types of urban objects to be classified into predefined classes of interest with increased accuracy. The comparison to classification results of WorldView-2 multispectral data (8 spectral bands) is provided and the numerical evaluation of the method in comparison to other established methods illustrates the advantage in the classification accuracy for many classes such as buildings, low vegetation, sport objects, forest, roads, rail roads, etc.

Techniques for automatic large scale change analysis of temporal multispectral imagery

NASA Astrophysics Data System (ADS)

Mercovich, Ryan A.

Change detection in remotely sensed imagery is a multi-faceted problem with a wide variety of desired solutions. Automatic change detection and analysis to assist in the coverage of large areas at high resolution is a popular area of research in the remote sensing community. Beyond basic change detection, the analysis of change is essential to provide results that positively impact an image analyst's job when examining potentially changed areas. Present change detection algorithms are geared toward low resolution imagery, and require analyst input to provide anything more than a simple pixel level map of the magnitude of change that has occurred. One major problem with this approach is that change occurs in such large volume at small spatial scales that a simple change map is no longer useful. This research strives to create an algorithm based on a set of metrics that performs a large area search for change in high resolution multispectral image sequences and utilizes a variety of methods to identify different types of change. Rather than simply mapping the magnitude of any change in the scene, the goal of this research is to create a useful display of the different types of change in the image. The techniques presented in this dissertation are used to interpret large area images and provide useful information to an analyst about small regions that have undergone specific types of change while retaining image context to make further manual interpretation easier. This analyst cueing to reduce information overload in a large area search environment will have an impact in the areas of disaster recovery, search and rescue situations, and land use surveys among others. By utilizing a feature based approach founded on applying existing statistical methods and new and existing topological methods to high resolution temporal multispectral imagery, a novel change detection methodology is produced that can automatically provide useful information about the change occurring in large area and high resolution image sequences. The change detection and analysis algorithm developed could be adapted to many potential image change scenarios to perform automatic large scale analysis of change.

Performance of 4x5120 Element Visible and 2x2560 Element Shortwave Infrared Multispectral Focal Planes

NASA Astrophysics Data System (ADS)

Tower, J. R.; Cope, A. D.; Pellion, L. E.; McCarthy, B. M.; Strong, R. T.; Kinnard, K. F.; Moldovan, A. G.; Levine, P. A.; Elabd, H.; Hoffman, D. M.

1985-12-01

Performance measurements of two Multispectral Linear Array focal planes are presented. Both pushbroom sensors have been developed for application in remote sensing instruments. A buttable, four-spectral-band, linear-format charge coupled device (CCD) and a but-table, two-spectral-band, linear-format, shortwave infrared charge coupled device (IRCCD) have been developed under NASA funding. These silicon integrated circuits may be butted end to end to provide very-high-resolution multispectral focal planes. The visible CCD is organized as four sensor lines of 1024 pixels each. Each line views the scene in a different spectral window defined by integral optical bandpass filters. A prototype focal plane with five devices, providing 4x5120-pixel resolution has been demonstrated. The high quantum efficiency of the backside-illuminated CCD technology provides excellent signal-to-noise performance and unusually high MTF across the entire visible and near-IR spectrum. The shortwave infrared (SWIR) sensor is organized as two line sensors of 512 detectors each. The SWIR (1-2.5 μm) spectral windows may be defined by bandpass filters placed in close proximity to the devices. The dual-band sensor consists of Schottky barrier detectors read out by CCD multiplexers. This monolithic sensor operates at 125°K with radiometric performance. A prototype five-device focal plane providing 2x2560 detectors has been demonstrated. The devices provide very high uniformity, and excellent MTF across the SWIR band.

Spatial resolution enhancement of terrestrial features using deconvolved SSM/I microwave brightness temperatures

NASA Technical Reports Server (NTRS)

Farrar, Michael R.; Smith, Eric A.

1992-01-01

A method for enhancing the 19, 22, and 37 GHz measurements of the SSM/I (Special Sensor Microwave/Imager) to the spatial resolution and sampling density of the high resolution 85-GHz channel is presented. An objective technique for specifying the tuning parameter, which balances the tradeoff between resolution and noise, is developed in terms of maximizing cross-channel correlations. Various validation procedures are performed to demonstrate the effectiveness of the method, which hopefully will provide researchers with a valuable tool in multispectral applications of satellite radiometer data.

Multispectral Resampling of Seagrass Species Spectra: WorldView-2, Quickbird, Sentinel-2A, ASTER VNIR, and Landsat 8 OLI

NASA Astrophysics Data System (ADS)

Wicaksono, Pramaditya; Salivian Wisnu Kumara, Ignatius; Kamal, Muhammad; Afif Fauzan, Muhammad; Zhafarina, Zhafirah; Agus Nurswantoro, Dwi; Noviaris Yogyantoro, Rifka

2017-12-01

Although spectrally different, seagrass species may not be able to be mapped from multispectral remote sensing images due to the limitation of their spectral resolution. Therefore, it is important to quantitatively assess the possibility of mapping seagrass species using multispectral images by resampling seagrass species spectra to multispectral bands. Seagrass species spectra were measured on harvested seagrass leaves. Spectral resolution of multispectral images used in this research was adopted from WorldView-2, Quickbird, Sentinel-2A, ASTER VNIR, and Landsat 8 OLI. These images are widely available and can be a good representative and baseline for previous or future remote sensing images. Seagrass species considered in this research are Enhalus acoroides (Ea), Thalassodendron ciliatum (Tc), Thalassia hemprichii (Th), Cymodocea rotundata (Cr), Cymodocea serrulata (Cs), Halodule uninervis (Hu), Halodule pinifolia (Hp), Syringodum isoetifolium (Si), Halophila ovalis (Ho), and Halophila minor (Hm). Multispectral resampling analysis indicate that the resampled spectra exhibit similar shape and pattern with the original spectra but less precise, and they lose the unique absorption feature of seagrass species. Relying on spectral bands alone, multispectral image is not effective in mapping these seagrass species individually, which is shown by the poor and inconsistent result of Spectral Angle Mapper (SAM) classification technique in classifying seagrass species using seagrass species spectra as pure endmember. Only Sentinel-2A produced acceptable classification result using SAM.

Sea ice-atmospheric interaction: Application of multispectral satellite data in polar surface energy flux estimates

NASA Technical Reports Server (NTRS)

Steffen, Konrad; Key, J.; Maslanik, J.; Schweiger, A.

1993-01-01

This is the third annual report on: Sea Ice-Atmosphere Interaction - Application of Multispectral Satellite Data in Polar Surface Energy Flux Estimates. The main emphasis during the past year was on: radiative flux estimates from satellite data; intercomparison of satellite and ground-based cloud amounts; radiative cloud forcing; calibration of the Advanced Very High Resolution Radiometer (AVHRR) visible channels and comparison of two satellite derived albedo data sets; and on flux modeling for leads. Major topics covered are arctic clouds and radiation; snow and ice albedo, and leads and modeling.

Calibration of the Multi-Spectral Solar Telescope Array multilayer mirrors and XUV filters

NASA Technical Reports Server (NTRS)

Allen, Maxwell J.; Willis, Thomas D.; Kankelborg, Charles C.; O'Neal, Ray H.; Martinez-Galarce, Dennis S.; Deforest, Craig E.; Jackson, Lisa; Lindblom, Joakim; Walker, Arthur B. C., Jr.; Barbee, Troy W., Jr.

1993-01-01

The Multi-Spectral Solar Telescope Array (MSSTA), a rocket-borne solar observatory, was successfully flown in May, 1991, obtaining solar images in eight XUV and FUV bands with 12 compact multilayer telescopes. Extensive measurements have recently been carried out on the multilayer telescopes and thin film filters at the Stanford Synchrotron Radiation Laboratory. These measurements are the first high spectral resolution calibrations of the MSSTA instruments. Previous measurements and/or calculations of telescope throughputs have been confirmed with greater accuracy. Results are presented on Mo/Si multilayer bandpass changes with time and experimental potassium bromide and tellurium filters.

Hyperspectral and multispectral satellite sensors for mapping chlorophyll content in a Mediterranean Pinus sylvestris L. plantation

NASA Astrophysics Data System (ADS)

Navarro-Cerrillo, Rafael Mª; Trujillo, Jesus; de la Orden, Manuel Sánchez; Hernández-Clemente, Rocío

2014-02-01

A new generation of narrow-band hyperspectral remote sensing data offers an alternative to broad-band multispectral data for the estimation of vegetation chlorophyll content. This paper examines the potential of some of these sensors comparing red-edge and simple ratio indices to develop a rapid and cost-effective system for monitoring Mediterranean pine plantations in Spain. Chlorophyll content retrieval was analyzed with the red-edge R750/R710 index and the simple ratio R800/R560 index using the PROSPECT-5 leaf model and the Discrete Anisotropic Radiative Transfer (DART) and experimental approach. Five sensors were used: AHS, CHRIS/Proba, Hyperion, Landsat and QuickBird. The model simulation results obtained with synthetic spectra demonstrated the feasibility of estimating Ca + b content in conifers using the simple ratio R800/R560 index formulated with different full widths at half maximum (FWHM) at the leaf level. This index yielded a r2 = 0.69 for a FWHM of 30 nm and r2 = 0.55 for a FWHM of 70 nm. Experimental results compared the regression coefficients obtained with various multispectral and hyperspectral images with different spatial resolutions at the stand level. The strongest relationships where obtained using high-resolution hyperspectral images acquired with the AHS sensor (r2 = 0.65) while coarser spatial and spectral resolution images yielded a lower root mean square error (QuickBird r2 = 0.42; Landsat r2 = 0.48; Hyperion r2 = 0.56; CHRIS/Proba r2 = 0.57). This study shows the need to estimate chlorophyll content in forest plantations at the stand level with high spatial and spectral resolution sensors. Nevertheless, these results also show the accuracy obtained with medium-resolution sensors when monitoring physiological processes. Generating biochemical maps at the stand level could play a critical rule in the early detection of forest decline processes enabling their use in precision forestry.

Land cover classification in multispectral imagery using clustering of sparse approximations over learned feature dictionaries

DOE PAGES

Moody, Daniela I.; Brumby, Steven P.; Rowland, Joel C.; ...

2014-12-09

We present results from an ongoing effort to extend neuromimetic machine vision algorithms to multispectral data using adaptive signal processing combined with compressive sensing and machine learning techniques. Our goal is to develop a robust classification methodology that will allow for automated discretization of the landscape into distinct units based on attributes such as vegetation, surface hydrological properties, and topographic/geomorphic characteristics. We use a Hebbian learning rule to build spectral-textural dictionaries that are tailored for classification. We learn our dictionaries from millions of overlapping multispectral image patches and then use a pursuit search to generate classification features. Land cover labelsmore » are automatically generated using unsupervised clustering of sparse approximations (CoSA). We demonstrate our method on multispectral WorldView-2 data from a coastal plain ecosystem in Barrow, Alaska. We explore learning from both raw multispectral imagery and normalized band difference indices. We explore a quantitative metric to evaluate the spectral properties of the clusters in order to potentially aid in assigning land cover categories to the cluster labels. In this study, our results suggest CoSA is a promising approach to unsupervised land cover classification in high-resolution satellite imagery.« less

Comparing Individual Tree Segmentation Based on High Resolution Multispectral Image and Lidar Data

NASA Astrophysics Data System (ADS)

Xiao, P.; Kelly, M.; Guo, Q.

2014-12-01

This study compares the use of high-resolution multispectral WorldView images and high density Lidar data for individual tree segmentation. The application focuses on coniferous and deciduous forests in the Sierra Nevada Mountains. The tree objects are obtained in two ways: a hybrid region-merging segmentation method with multispectral images, and a top-down and bottom-up region-growing method with Lidar data. The hybrid region-merging method is used to segment individual tree from multispectral images. It integrates the advantages of global-oriented and local-oriented region-merging strategies into a unified framework. The globally most-similar pair of regions is used to determine the starting point of a growing region. The merging iterations are constrained within the local vicinity, thus the segmentation is accelerated and can reflect the local context. The top-down region-growing method is adopted in coniferous forest to delineate individual tree from Lidar data. It exploits the spacing between the tops of trees to identify and group points into a single tree based on simple rules of proximity and likely tree shape. The bottom-up region-growing method based on the intensity and 3D structure of Lidar data is applied in deciduous forest. It segments tree trunks based on the intensity and topological relationships of the points, and then allocate other points to exact tree crowns according to distance. The accuracies for each method are evaluated with field survey data in several test sites, covering dense and sparse canopy. Three types of segmentation results are produced: true positive represents a correctly segmented individual tree, false negative represents a tree that is not detected and assigned to a nearby tree, and false positive represents that a point or pixel cluster is segmented as a tree that does not in fact exist. They respectively represent correct-, under-, and over-segmentation. Three types of index are compared for segmenting individual tree from multispectral image and Lidar data: recall, precision and F-score. This work explores the tradeoff between the expensive Lidar data and inexpensive multispectral image. The conclusion will guide the optimal data selection in different density canopy areas for individual tree segmentation, and contribute to the field of forest remote sensing.

Generalized assorted pixel camera: postcapture control of resolution, dynamic range, and spectrum.

PubMed

Yasuma, Fumihito; Mitsunaga, Tomoo; Iso, Daisuke; Nayar, Shree K

2010-09-01

We propose the concept of a generalized assorted pixel (GAP) camera, which enables the user to capture a single image of a scene and, after the fact, control the tradeoff between spatial resolution, dynamic range and spectral detail. The GAP camera uses a complex array (or mosaic) of color filters. A major problem with using such an array is that the captured image is severely under-sampled for at least some of the filter types. This leads to reconstructed images with strong aliasing. We make four contributions in this paper: 1) we present a comprehensive optimization method to arrive at the spatial and spectral layout of the color filter array of a GAP camera. 2) We develop a novel algorithm for reconstructing the under-sampled channels of the image while minimizing aliasing artifacts. 3) We demonstrate how the user can capture a single image and then control the tradeoff of spatial resolution to generate a variety of images, including monochrome, high dynamic range (HDR) monochrome, RGB, HDR RGB, and multispectral images. 4) Finally, the performance of our GAP camera has been verified using extensive simulations that use multispectral images of real world scenes. A large database of these multispectral images has been made available at http://www1.cs.columbia.edu/CAVE/projects/gap_camera/ for use by the research community.

Novelty Detection Classifiers in Weed Mapping: Silybum marianum Detection on UAV Multispectral Images.

PubMed

Alexandridis, Thomas K; Tamouridou, Afroditi Alexandra; Pantazi, Xanthoula Eirini; Lagopodi, Anastasia L; Kashefi, Javid; Ovakoglou, Georgios; Polychronos, Vassilios; Moshou, Dimitrios

2017-09-01

In the present study, the detection and mapping of Silybum marianum (L.) Gaertn. weed using novelty detection classifiers is reported. A multispectral camera (green-red-NIR) on board a fixed wing unmanned aerial vehicle (UAV) was employed for obtaining high-resolution images. Four novelty detection classifiers were used to identify S. marianum between other vegetation in a field. The classifiers were One Class Support Vector Machine (OC-SVM), One Class Self-Organizing Maps (OC-SOM), Autoencoders and One Class Principal Component Analysis (OC-PCA). As input features to the novelty detection classifiers, the three spectral bands and texture were used. The S. marianum identification accuracy using OC-SVM reached an overall accuracy of 96%. The results show the feasibility of effective S. marianum mapping by means of novelty detection classifiers acting on multispectral UAV imagery.

Design and development of an airborne multispectral imaging system

NASA Astrophysics Data System (ADS)

Kulkarni, Rahul R.; Bachnak, Rafic; Lyle, Stacey; Steidley, Carl W.

2002-08-01

Advances in imaging technology and sensors have made airborne remote sensing systems viable for many applications that require reasonably good resolution at low cost. Digital cameras are making their mark on the market by providing high resolution at very high rates. This paper describes an aircraft-mounted imaging system (AMIS) that is being designed and developed at Texas A&M University-Corpus Christi (A&M-CC) with the support of a grant from NASA. The approach is to first develop and test a one-camera system that will be upgraded into a five-camera system that offers multi-spectral capabilities. AMIS will be low cost, rugged, portable and has its own battery power source. Its immediate use will be to acquire images of the Coastal area in the Gulf of Mexico for a variety of studies covering vast spectra from near ultraviolet region to near infrared region. This paper describes AMIS and its characteristics, discusses the process for selecting the major components, and presents the progress.

Giant Raman scattering from J-aggregated dyes inside carbon nanotubes for multispectral imaging

NASA Astrophysics Data System (ADS)

Gaufrès, E.; Tang, N. Y.-Wa; Lapointe, F.; Cabana, J.; Nadon, M.-A.; Cottenye, N.; Raymond, F.; Szkopek, T.; Martel, R.

2014-01-01

Raman spectroscopy uses visible light to acquire vibrational fingerprints of molecules, thus making it a powerful tool for chemical analysis in a wide range of media. However, its potential for optical imaging at high resolution is severely limited by the fact that the Raman effect is weak. Here, we report the discovery of a giant Raman scattering effect from encapsulated and aggregated dye molecules inside single-walled carbon nanotubes. Measurements performed on rod-like dyes such as α-sexithiophene and β-carotene, assembled inside single-walled carbon nanotubes as highly polarizable J-aggregates, indicate a resonant Raman cross-section of (3 +/- 2) × 10-21 cm2 sr-1, which is well above the cross-section required for detecting individual aggregates at the highest optical resolution. Free from fluorescence background and photobleaching, this giant Raman effect allows the realization of a library of functionalized nanoprobe labels for Raman imaging with robust detection using multispectral analysis.

MSS D Multispectral Scanner System

NASA Technical Reports Server (NTRS)

Lauletta, A. M.; Johnson, R. L.; Brinkman, K. L. (Principal Investigator)

1982-01-01

The development and acceptance testing of the 4-band Multispectral Scanners to be flown on LANDSAT D and LANDSAT D Earth resources satellites are summarized. Emphasis is placed on the acceptance test phase of the program. Test history and acceptance test algorithms are discussed. Trend data of all the key performance parameters are included and discussed separately for each of the two multispectral scanner instruments. Anomalies encountered and their resolutions are included.

From local spectral measurements to maps of vegetation cover and biomass on the Qinghai-Tibet-Plateau: Do we need hyperspectral information?

NASA Astrophysics Data System (ADS)

Meyer, Hanna; Lehnert, Lukas W.; Wang, Yun; Reudenbach, Christoph; Nauss, Thomas; Bendix, Jörg

2017-03-01

Though the relevance of pasture degradation on the Qinghai-Tibet Plateau (QTP) is widely postulated, its extent is still unknown. Due to the enormous spatial extent, remote sensing provides the only possibility to investigate pasture degradation via frequently used proxies such as vegetation cover and aboveground biomass (AGB). However, unified remote sensing approaches are still lacking. This study tests the applicability of hyper- and multispectral in situ measurements to map vegetation cover and AGB on regional scales. Using machine learning techniques, it is tested whether the full hyperspectral information is needed or if multispectral information is sufficient to accurately estimate pasture degradation proxies. To regionalize pasture degradation proxies, the transferability of the locally derived ML-models to high resolution multispectral satellite data is assessed. 1183 hyperspectral measurements and vegetation records were performed at 18 locations on the QTP. Random Forests models with recursive feature selection were trained to estimate vegetation cover and AGB using narrow-band indices (NBI) as predictors. Separate models were calculated using NBI from hyperspectral data as well as from the same data resampled to WorldView-2, QuickBird and RapidEye channels. The hyperspectral results were compared to the multispectral results. Finally, the models were applied to satellite data to map vegetation cover and AGB on a regional scale. Vegetation cover was accurately predicted by Random Forest if hyperspectral measurements were used (cross validated R2 = 0.89). In contrast, errors in AGB estimations were considerably higher (cross validated R2 = 0.32). Only small differences in accuracy were observed between the models based on hyperspectral compared to multispectral data. The application of the models to satellite images generally resulted in an increase of the estimation error. Though this reflects the challenge of applying in situ measurements to satellite data, the results still show a high potential to map pasture degradation proxies on the QTP. Thus, this study presents robust methodology to remotely detect and monitor pasture degradation at high spatial resolutions.

Simultaneous multispectral reflectance imaging and laser speckle flowmetry of cerebral blood flow and oxygen metabolism in focal cerebral ischemia

PubMed Central

Jones, Phill B.; Shin, Hwa Kyoung; Boas, David A.; Hyman, Bradley T.; Moskowitz, Michael A.; Ayata, Cenk; Dunn, Andrew K.

2009-01-01

Real-time investigation of cerebral blood flow (CBF), and oxy- and deoxyhemoglobin concentration (HbO, HbR) dynamics has been difficult until recently due to limited spatial and temporal resolution of techniques like laser Doppler flowmetry and magnetic resonance imaging (MRI). The combination of laser speckle flowmetry (LSF) and multispectral reflectance imaging (MSRI) yields high-resolution spatiotemporal maps of hemodynamic and metabolic changes in response to functional cortical activation. During acute focal cerebral ischemia, changes in HbO and HbR are much larger than in functional activation, resulting in the failure of the Beer-Lambert approximation to yield accurate results. We describe the use of simultaneous LSF and MSRI, using a nonlinear Monte Carlo fitting technique, to record rapid changes in CBF, HbO, HbR, and cerebral metabolic rate of oxygen (CMRO2) during acute focal cerebral ischemia induced by distal middle cerebral artery occlusion (dMCAO) and reperfusion. This technique captures CBF and CMRO2 changes during hemodynamic and metabolic events with high temporal and spatial resolution through the intact skull and demonstrates the utility of simultaneous LSF and MSRI in mouse models of cerebrovascular disease. PMID:19021335

Semantic segmentation of forest stands of pure species combining airborne lidar data and very high resolution multispectral imagery

NASA Astrophysics Data System (ADS)

Dechesne, Clément; Mallet, Clément; Le Bris, Arnaud; Gouet-Brunet, Valérie

2017-04-01

Forest stands are the basic units for forest inventory and mapping. Stands are defined as large forested areas (e.g., ⩾ 2 ha) of homogeneous tree species composition and age. Their accurate delineation is usually performed by human operators through visual analysis of very high resolution (VHR) infra-red images. This task is tedious, highly time consuming, and should be automated for scalability and efficient updating purposes. In this paper, a method based on the fusion of airborne lidar data and VHR multispectral images is proposed for the automatic delineation of forest stands containing one dominant species (purity superior to 75%). This is the key preliminary task for forest land-cover database update. The multispectral images give information about the tree species whereas 3D lidar point clouds provide geometric information on the trees and allow their individual extraction. Multi-modal features are computed, both at pixel and object levels: the objects are individual trees extracted from lidar data. A supervised classification is then performed at the object level in order to coarsely discriminate the existing tree species in each area of interest. The classification results are further processed to obtain homogeneous areas with smooth borders by employing an energy minimum framework, where additional constraints are joined to form the energy function. The experimental results show that the proposed method provides very satisfactory results both in terms of stand labeling and delineation (overall accuracy ranges between 84 % and 99 %).

Accuracy comparison in mapping water bodies using Landsat images and Google Earth Images

NASA Astrophysics Data System (ADS)

Zhou, Z.; Zhou, X.

2016-12-01

A lot of research has been done for the extraction of water bodies with multiple satellite images. The Water Indexes with the use of multi-spectral images are the mostly used methods for the water bodies' extraction. In order to extract area of water bodies from satellite images, accuracy may depend on the spatial resolution of images and relative size of the water bodies. To quantify the impact of spatial resolution and size (major and minor lengths) of the water bodies on the accuracy of water area extraction, we use Georgetown Lake, Montana and coalbed methane (CBM) water retention ponds in the Montana Powder River Basin as test sites to evaluate the impact of spatial resolution and the size of water bodies on water area extraction. Data sources used include Landsat images and Google Earth images covering both large water bodies and small ponds. Firstly we used water indices to extract water coverage from Landsat images for both large lake and small ponds. Secondly we used a newly developed visible-index method to extract water coverage from Google Earth images covering both large lake and small ponds. Thirdly, we used the image fusion method in which the Google Earth Images are fused with multi-spectral Landsat images to obtain multi-spectral images of the same high spatial resolution as the Google earth images. The actual area of the lake and ponds are measured using GPS surveys. Results will be compared and the optimal method will be selected for water body extraction.

Wide field-of-view dual-band multispectral muzzle flash detection

NASA Astrophysics Data System (ADS)

Montoya, J.; Melchor, J.; Spiliotis, P.; Taplin, L.

2013-06-01

Sensor technologies are undergoing revolutionary advances, as seen in the rapid growth of multispectral methodologies. Increases in spatial, spectral, and temporal resolution, and in breadth of spectral coverage, render feasible sensors that function with unprecedented performance. A system was developed that addresses many of the key hardware requirements for a practical dual-band multispectral acquisition system, including wide field of view and spectral/temporal shift between dual bands. The system was designed using a novel dichroic beam splitter and dual band-pass filter configuration that creates two side-by-side images of a scene on a single sensor. A high-speed CMOS sensor was used to simultaneously capture data from the entire scene in both spectral bands using a short focal-length lens that provided a wide field-of-view. The beam-splitter components were arranged such that the two images were maintained in optical alignment and real-time intra-band processing could be carried out using only simple arithmetic on the image halves. An experiment related to limitations of the system to address multispectral detection requirements was performed. This characterized the system's low spectral variation across its wide field of view. This paper provides lessons learned on the general limitation of key hardware components required for multispectral muzzle flash detection, using the system as a hardware example combined with simulated multispectral muzzle flash and background signatures.

Learning Low-Rank Decomposition for Pan-Sharpening With Spatial-Spectral Offsets.

PubMed

Yang, Shuyuan; Zhang, Kai; Wang, Min

2017-08-25

Finding accurate injection components is the key issue in pan-sharpening methods. In this paper, a low-rank pan-sharpening (LRP) model is developed from a new perspective of offset learning. Two offsets are defined to represent the spatial and spectral differences between low-resolution multispectral and high-resolution multispectral (HRMS) images, respectively. In order to reduce spatial and spectral distortions, spatial equalization and spectral proportion constraints are designed and cast on the offsets, to develop a spatial and spectral constrained stable low-rank decomposition algorithm via augmented Lagrange multiplier. By fine modeling and heuristic learning, our method can simultaneously reduce spatial and spectral distortions in the fused HRMS images. Moreover, our method can efficiently deal with noises and outliers in source images, for exploring low-rank and sparse characteristics of data. Extensive experiments are taken on several image data sets, and the results demonstrate the efficiency of the proposed LRP.

Light-Weight Multispectral Uav Sensors and Their Capabilities for Predicting Grain Yield and Detecting Plant Diseases

NASA Astrophysics Data System (ADS)

Nebiker, S.; Lack, N.; Abächerli, M.; Läderach, S.

2016-06-01

In this paper we investigate the performance of new light-weight multispectral sensors for micro UAV and their application to selected tasks in agronomical research and agricultural practice. The investigations are based on a series of flight campaigns in 2014 and 2015 covering a number of agronomical test sites with experiments on rape, barley, onion, potato and other crops. In our sensor comparison we included a high-end multispectral multiSPEC 4C camera with bandpass colour filters and reference channel in zenith direction and a low-cost, consumer-grade Canon S110 NIR camera with Bayer pattern colour filters. Ground-based reference measurements were obtained using a terrestrial hyperspectral field spectrometer. The investigations show that measurements with the high-end system consistently match very well with ground-based field spectrometer measurements with a mean deviation of just 0.01-0.04 NDVI values. The low-cost system, while delivering better spatial resolutions, expressed significant biases. The sensors were subsequently used to address selected agronomical questions. These included crop yield estimation in rape and barley and plant disease detection in potato and onion cultivations. High levels of correlation between different vegetation indices and reference yield measurements were obtained for rape and barley. In case of barley, the NDRE index shows an average correlation of 87% with reference yield, when species are taken into account. With high geometric resolutions and respective GSDs of down to 2.5 cm the effects of a thrips infestation in onion could be analysed and potato blight was successfully detected at an early stage of infestation.

Polarimetric Multispectral Imaging Technology

NASA Technical Reports Server (NTRS)

Cheng, L.-J.; Chao, T.-H.; Dowdy, M.; Mahoney, C.; Reyes, G.

1993-01-01

The Jet Propulsion Laboratory is developing a remote sensing technology on which a new generation of compact, lightweight, high-resolution, low-power, reliable, versatile, programmable scientific polarimetric multispectral imaging instruments can be built to meet the challenge of future planetary exploration missions. The instrument is based on the fast programmable acousto-optic tunable filter (AOTF) of tellurium dioxide (TeO2) that operates in the wavelength range of 0.4-5 microns. Basically, the AOTF multispectral imaging instrument measures incoming light intensity as a function of spatial coordinates, wavelength, and polarization. Its operation can be in either sequential, random access, or multiwavelength mode as required. This provides observation flexibility, allowing real-time alternation among desired observations, collecting needed data only, minimizing data transmission, and permitting implementation of new experiments. These will result in optimization of the mission performance with minimal resources. Recently we completed a polarimetric multispectral imaging prototype instrument and performed outdoor field experiments for evaluating application potentials of the technology. We also investigated potential improvements on AOTF performance to strengthen technology readiness for applications. This paper will give a status report on the technology and a prospect toward future planetary exploration.

Image sharpening for mixed spatial and spectral resolution satellite systems

NASA Technical Reports Server (NTRS)

Hallada, W. A.; Cox, S.

1983-01-01

Two methods of image sharpening (reconstruction) are compared. The first, a spatial filtering technique, extrapolates edge information from a high spatial resolution panchromatic band at 10 meters and adds it to the low spatial resolution narrow spectral bands. The second method, a color normalizing technique, is based on the ability to separate image hue and brightness components in spectral data. Using both techniques, multispectral images are sharpened from 30, 50, 70, and 90 meter resolutions. Error rates are calculated for the two methods and all sharpened resolutions. The results indicate that the color normalizing method is superior to the spatial filtering technique.

High Resolution Multispectral and Hyperspectral Data Fusion for Advanced Geospatial Information Products

DTIC Science & Technology

2005-09-30

Barbara, Newport, and San Diego Harbor. The MSI instrumentation was provided under a cooperative agreement with the Applanix Systems Integration Group...part of the Applanix Position and Orientation System (POS AV; http://www.applanix.com/products/posav_index.php), which was being evaluated as a

High Resolution Multispectral and Hyperspectral Data Fusion for Advanced Geospatial Information Products

DTIC Science & Technology

2007-03-01

instrumentation was provided under a cooperative agreement with the Applanix Systems Integration Group (ASIG), a subsidiary of the Trimble Corporation. This MSI...system (Digital Sensor System; http://www.applanix.com/products/dss index.php) was provided as part of the Applanix Position and Orientation System (POS

Decision-Tree, Rule-Based, and Random Forest Classification of High-Resolution Multispectral Imagery for Wetland Mapping and Inventory

EPA Science Inventory

Efforts are increasingly being made to classify the world’s wetland resources, an important ecosystem and habitat that is diminishing in abundance. There are multiple remote sensing classification methods, including a suite of nonparametric classifiers such as decision-tree...

Measurement Sets and Sites Commonly Used for High Spatial Resolution Image Product Characterization

NASA Technical Reports Server (NTRS)

Pagnutti, Mary

2006-01-01

Scientists within NASA's Applied Sciences Directorate have developed a well-characterized remote sensing Verification & Validation (V&V) site at the John C. Stennis Space Center (SSC). This site has enabled the in-flight characterization of satellite high spatial resolution remote sensing system products form Space Imaging IKONOS, Digital Globe QuickBird, and ORBIMAGE OrbView, as well as advanced multispectral airborne digital camera products. SSC utilizes engineered geodetic targets, edge targets, radiometric tarps, atmospheric monitoring equipment and their Instrument Validation Laboratory to characterize high spatial resolution remote sensing data products. This presentation describes the SSC characterization capabilities and techniques in the visible through near infrared spectrum and examples of calibration results.

A parallel method of atmospheric correction for multispectral high spatial resolution remote sensing images

NASA Astrophysics Data System (ADS)

Zhao, Shaoshuai; Ni, Chen; Cao, Jing; Li, Zhengqiang; Chen, Xingfeng; Ma, Yan; Yang, Leiku; Hou, Weizhen; Qie, Lili; Ge, Bangyu; Liu, Li; Xing, Jin

2018-03-01

The remote sensing image is usually polluted by atmosphere components especially like aerosol particles. For the quantitative remote sensing applications, the radiative transfer model based atmospheric correction is used to get the reflectance with decoupling the atmosphere and surface by consuming a long computational time. The parallel computing is a solution method for the temporal acceleration. The parallel strategy which uses multi-CPU to work simultaneously is designed to do atmospheric correction for a multispectral remote sensing image. The parallel framework's flow and the main parallel body of atmospheric correction are described. Then, the multispectral remote sensing image of the Chinese Gaofen-2 satellite is used to test the acceleration efficiency. When the CPU number is increasing from 1 to 8, the computational speed is also increasing. The biggest acceleration rate is 6.5. Under the 8 CPU working mode, the whole image atmospheric correction costs 4 minutes.

Using a trichromatic CCD camera for spectral skylight estimation.

PubMed

López-Alvarez, Miguel A; Hernández-Andrés, Javier; Romero, Javier; Olmo, F J; Cazorla, A; Alados-Arboledas, L

2008-12-01

In a previous work [J. Opt. Soc. Am. A 24, 942-956 (2007)] we showed how to design an optimum multispectral system aimed at spectral recovery of skylight. Since high-resolution multispectral images of skylight could be interesting for many scientific disciplines, here we also propose a nonoptimum but much cheaper and faster approach to achieve this goal by using a trichromatic RGB charge-coupled device (CCD) digital camera. The camera is attached to a fish-eye lens, hence permitting us to obtain a spectrum of every point of the skydome corresponding to each pixel of the image. In this work we show how to apply multispectral techniques to the sensors' responses of a common trichromatic camera in order to obtain skylight spectra from them. This spectral information is accurate enough to estimate experimental values of some climate parameters or to be used in algorithms for automatic cloud detection, among many other possible scientific applications.

Three-Dimensional Reconstruction from Single Image Base on Combination of CNN and Multi-Spectral Photometric Stereo.

PubMed

Lu, Liang; Qi, Lin; Luo, Yisong; Jiao, Hengchao; Dong, Junyu

2018-03-02

Multi-spectral photometric stereo can recover pixel-wise surface normal from a single RGB image. The difficulty lies in that the intensity in each channel is the tangle of illumination, albedo and camera response; thus, an initial estimate of the normal is required in optimization-based solutions. In this paper, we propose to make a rough depth estimation using the deep convolutional neural network (CNN) instead of using depth sensors or binocular stereo devices. Since high-resolution ground-truth data is expensive to obtain, we designed a network and trained it with rendered images of synthetic 3D objects. We use the model to predict initial normal of real-world objects and iteratively optimize the fine-scale geometry in the multi-spectral photometric stereo framework. The experimental results illustrate the improvement of the proposed method compared with existing methods.

Three-Dimensional Reconstruction from Single Image Base on Combination of CNN and Multi-Spectral Photometric Stereo

PubMed Central

Lu, Liang; Qi, Lin; Luo, Yisong; Jiao, Hengchao; Dong, Junyu

2018-01-01

Multi-spectral photometric stereo can recover pixel-wise surface normal from a single RGB image. The difficulty lies in that the intensity in each channel is the tangle of illumination, albedo and camera response; thus, an initial estimate of the normal is required in optimization-based solutions. In this paper, we propose to make a rough depth estimation using the deep convolutional neural network (CNN) instead of using depth sensors or binocular stereo devices. Since high-resolution ground-truth data is expensive to obtain, we designed a network and trained it with rendered images of synthetic 3D objects. We use the model to predict initial normal of real-world objects and iteratively optimize the fine-scale geometry in the multi-spectral photometric stereo framework. The experimental results illustrate the improvement of the proposed method compared with existing methods. PMID:29498703

Advanced Multispectral Scanner (AMS) study. [aircraft remote sensing

NASA Technical Reports Server (NTRS)

1978-01-01

The status of aircraft multispectral scanner technology was accessed in order to develop preliminary design specifications for an advanced instrument to be used for remote sensing data collection by aircraft in the 1980 time frame. The system designed provides a no-moving parts multispectral scanning capability through the exploitation of linear array charge coupled device technology and advanced electronic signal processing techniques. Major advantages include: 10:1 V/H rate capability; 120 deg FOV at V/H = 0.25 rad/sec; 1 to 2 rad resolution; high sensitivity; large dynamic range capability; geometric fidelity; roll compensation; modularity; long life; and 24 channel data acquisition capability. The field flattening techniques of the optical design allow wide field view to be achieved at fast f/nos for both the long and short wavelength regions. The digital signal averaging technique permits maximization of signal to noise performance over the entire V/H rate range.

Synergistic use of multispectral satellite data for monitoring land surface change

NASA Technical Reports Server (NTRS)

Choudhury, Bhaskar J.

1991-01-01

Observations by the Advanced Very High Resolution Radiometer (AVHRR) onboard the NOAA satellites were used to compute visible and near infrared reflectances and surface temperature, while passive microwave observations at 37 GHz frequency by the Scanning Multichannel Microwave Radiometer (SMMR) and Special Sensor Microwave Imager (SSM/I) on board, respectively, the Nimbus-7 and DMSP-F8 satellites were used to compute polarization difference. These observations were analyzed along transects from rainforest to desert over northern Africa for the period 1979-1987, which included an unprecedented drought during 1984 over the Sahel zone. Model simulations were made to understand the interrelationship among multispectral data.

Evaluation of airborne image data for mapping riparian vegetation within the Grand Canyon

USGS Publications Warehouse

Davis, Philip A.; Staid, Matthew I.; Plescia, Jeffrey B.; Johnson, Jeffrey R.

2002-01-01

This study examined various types of remote-sensing data that have been acquired during a 12-month period over a portion of the Colorado River corridor to determine the type of data and conditions for data acquisition that provide the optimum classification results for mapping riparian vegetation. Issues related to vegetation mapping included time of year, number and positions of wavelength bands, and spatial resolution for data acquisition to produce accurate vegetation maps versus cost of data. Image data considered in the study consisted of scanned color-infrared (CIR) film, digital CIR, and digital multispectral data, whose resolutions from 11 cm (photographic film) to 100 cm (multispectral), that were acquired during the Spring, Summer, and Fall seasons in 2000 for five long-term monitoring sites containing riparian vegetation. Results show that digitally acquired data produce higher and more consistent classification accuracies for mapping vegetation units than do film products. The highest accuracies were obtained from nine-band multispectral data; however, a four-band subset of these data, that did not include short-wave infrared bands, produced comparable mapping results. The four-band subset consisted of the wavelength bands 0.52-0.59 µm, 0.59-0.62 µm, 0.67-0.72 µm, and 0.73-0.85 µm. Use of only three of these bands that simulate digital CIR sensors produced accuracies for several vegetation units that were 10% lower than those obtained using the full multispectral data set. Classification tests using band ratios produced lower accuracies than those using band reflectance for scanned film data; a result attributed to the relatively poor radiometric fidelity maintained by the film scanning process, whereas calibrated multispectral data produced similar classification accuracies using band reflectance and band ratios. This suggests that the intrinsic band reflectance of the vegetation is more important than inter-band reflectance differences in attaining high mapping accuracies. These results also indicate that radiometrically calibrated sensors that record a wide range of radiance produce superior results and that such sensors should be used for monitoring purposes. When texture (spatial variance) at near-infrared wavelength is combined with spectral data in classification, accuracy increased most markedly (20-30%) for the highest resolution (11-cm) CIR film data, but decreased in its effect on accuracy in lower-resolution multi-spectral image data; a result observed in previous studies (Franklin and McDermid 1993, Franklin et al. 2000, 2001). While many classification unit accuracies obtained from the 11-cm film CIR band with texture data were in fact higher than those produced using the 100-cm, nine-band multispectral data with texture, the 11-cm film CIR data produced much lower accuracies than the 100-cm multispectral data for the more sparsely populated vegetation units due to saturation of picture elements during the film scanning process in vegetation units with a high proportion of alluvium. Overall classification accuracies obtained from spectral band and texture data range from 36% to 78% for all databases considered, from 57% to 71% for the 11-cm film CIR data, and from 54% to 78% for the 100-cm multispectral data. Classification results obtained from 20-cm film CIR band and texture data, which were produced by applying a Gaussian filter to the 11-cm film CIR data, showed increases in accuracy due to texture that were similar to those observed using the original 11-cm film CIR data. This suggests that data can be collected at the lower resolution and still retain the added power of vegetation texture. Classification accuracies for the riparian vegetation units examined in this study do not appear to be influenced by season of data acquisition, although data acquired under direct sunlight produced higher overall accuracies than data acquired under overcast conditions. The latter observation, in addition to the importance of band reflectance for classification, implies that data should be acquired near summer solstice when sun elevation and reflectance is highest and when shadows cast by steep canyon walls are minimized.

Combining kriging, multispectral and multimodal microscopy to resolve malaria-infected erythrocyte contents.

PubMed

Dabo-Niang, S; Zoueu, J T

2012-09-01

In this communication, we demonstrate how kriging, combine with multispectral and multimodal microscopy can enhance the resolution of malaria-infected images and provide more details on their composition, for analysis and diagnosis. The results of this interpolation applied to the two principal components of multispectral and multimodal images illustrate that the examination of the content of Plasmodium falciparum infected human erythrocyte is improved. © 2012 The Authors Journal of Microscopy © 2012 Royal Microscopical Society.

The influence of multispectral scanner spatial resolution on forest feature classification

NASA Technical Reports Server (NTRS)

Sadowski, F. G.; Malila, W. A.; Sarno, J. E.; Nalepka, R. F.

1977-01-01

Inappropriate spatial resolution and corresponding data processing techniques may be major causes for non-optimal forest classification results frequently achieved from multispectral scanner (MSS) data. Procedures and results of empirical investigations are studied to determine the influence of MSS spatial resolution on the classification of forest features into levels of detail or hierarchies of information that might be appropriate for nationwide forest surveys and detailed in-place inventories. Two somewhat different, but related studies are presented. The first consisted of establishing classification accuracies for several hierarchies of features as spatial resolution was progressively coarsened from (2 meters) squared to (64 meters) squared. The second investigated the capabilities for specialized processing techniques to improve upon the results of conventional processing procedures for both coarse and fine resolution data.

Radiometric Calibration Assessment of Commercial High Spatial Resolution Multispectral Image Products

NASA Technical Reports Server (NTRS)

Holekamp, Kara; Aaron, David; Thome, Kurtis

2006-01-01

Radiometric calibration of commercial imaging satellite products is required to ensure that science and application communities can better understand their properties. Inaccurate radiometric calibrations can lead to erroneous decisions and invalid conclusions and can limit intercomparisons with other systems. To address this calibration need, satellite at-sensor radiance values were compared to those estimated by each independent team member to determine the sensor's radiometric accuracy. The combined results of this evaluation provide the user community with an independent assessment of these commercially available high spatial resolution sensors' absolute calibration values.

Multispectral multisensor image fusion using wavelet transforms

USGS Publications Warehouse

Lemeshewsky, George P.

1999-01-01

Fusion techniques can be applied to multispectral and higher spatial resolution panchromatic images to create a composite image that is easier to interpret than the individual images. Wavelet transform-based multisensor, multiresolution fusion (a type of band sharpening) was applied to Landsat thematic mapper (TM) multispectral and coregistered higher resolution SPOT panchromatic images. The objective was to obtain increased spatial resolution, false color composite products to support the interpretation of land cover types wherein the spectral characteristics of the imagery are preserved to provide the spectral clues needed for interpretation. Since the fusion process should not introduce artifacts, a shift invariant implementation of the discrete wavelet transform (SIDWT) was used. These results were compared with those using the shift variant, discrete wavelet transform (DWT). Overall, the process includes a hue, saturation, and value color space transform to minimize color changes, and a reported point-wise maximum selection rule to combine transform coefficients. The performance of fusion based on the SIDWT and DWT was evaluated with a simulated TM 30-m spatial resolution test image and a higher resolution reference. Simulated imagery was made by blurring higher resolution color-infrared photography with the TM sensors' point spread function. The SIDWT based technique produced imagery with fewer artifacts and lower error between fused images and the full resolution reference. Image examples with TM and SPOT 10-m panchromatic illustrate the reduction in artifacts due to the SIDWT based fusion.

High-quality infrared imaging with graphene photodetectors at room temperature.

PubMed

Guo, Nan; Hu, Weida; Jiang, Tao; Gong, Fan; Luo, Wenjin; Qiu, Weicheng; Wang, Peng; Liu, Lu; Wu, Shiwei; Liao, Lei; Chen, Xiaoshuang; Lu, Wei

2016-09-21

Graphene, a two-dimensional material, is expected to enable broad-spectrum and high-speed photodetection because of its gapless band structure, ultrafast carrier dynamics and high mobility. We demonstrate a multispectral active infrared imaging by using a graphene photodetector based on hybrid response mechanisms at room temperature. The high-quality images with optical resolutions of 418 nm, 657 nm and 877 nm and close-to-theoretical-limit Michelson contrasts of 0.997, 0.994, and 0.996 have been acquired for 565 nm, 1550 nm, and 1815 nm light imaging measurements by using an unbiased graphene photodetector, respectively. Importantly, by carefully analyzing the results of Raman mapping and numerical simulations for the response process, the formation of hybrid photocurrents in graphene detectors is attributed to the synergistic action of photovoltaic and photo-thermoelectric effects. The initial application to infrared imaging will help promote the development of high performance graphene-based infrared multispectral detectors.

Kite aerial photography for low-cost, ultra-high spatial resolution multi-spectral mapping of intertidal landscapes.

PubMed

Bryson, Mitch; Johnson-Roberson, Matthew; Murphy, Richard J; Bongiorno, Daniel

2013-01-01

Intertidal ecosystems have primarily been studied using field-based sampling; remote sensing offers the ability to collect data over large areas in a snapshot of time that could complement field-based sampling methods by extrapolating them into the wider spatial and temporal context. Conventional remote sensing tools (such as satellite and aircraft imaging) provide data at limited spatial and temporal resolutions and relatively high costs for small-scale environmental science and ecologically-focussed studies. In this paper, we describe a low-cost, kite-based imaging system and photogrammetric/mapping procedure that was developed for constructing high-resolution, three-dimensional, multi-spectral terrain models of intertidal rocky shores. The processing procedure uses automatic image feature detection and matching, structure-from-motion and photo-textured terrain surface reconstruction algorithms that require minimal human input and only a small number of ground control points and allow the use of cheap, consumer-grade digital cameras. The resulting maps combine imagery at visible and near-infrared wavelengths and topographic information at sub-centimeter resolutions over an intertidal shoreline 200 m long, thus enabling spatial properties of the intertidal environment to be determined across a hierarchy of spatial scales. Results of the system are presented for an intertidal rocky shore at Jervis Bay, New South Wales, Australia. Potential uses of this technique include mapping of plant (micro- and macro-algae) and animal (e.g. gastropods) assemblages at multiple spatial and temporal scales.

Geo-oculus: high resolution multi-spectral earth imaging mission from geostationary orbit

NASA Astrophysics Data System (ADS)

Vaillon, L.; Schull, U.; Knigge, T.; Bevillon, C.

2017-11-01

Geo-Oculus is a GEO-based Earth observation mission studied by Astrium for ESA in 2008-2009 to complement the Sentinel missions, the space component of the GMES (Global Monitoring for Environment & Security). Indeed Earth imaging from geostationary orbit offers new functionalities not covered by existing LEO observation missions, like real-time monitoring and fast revisit capability of any location within the huge area in visibility of the satellite. This high revisit capability is exploited by the Meteosat meteorogical satellites, but with a spatial resolution (500 m nadir for the third generation) far from most of GMES needs (10 to 100 m). To reach such ground resolution from GEO orbit with adequate image quality, large aperture instruments (> 1 m) and high pointing stability (<< 1 μrad) are required, which are the major challenges of such missions. To address the requirements from the GMES user community, the Geo-Oculus mission is a combination of routine observations (daily systematic coverage of European coastal waters) with "on-demand" observation for event monitoring (e.g. disasters, fires and oil slicks). The instrument is a large aperture imaging telescope (1.5 m diameter) offering a nadir spatial sampling of 10.5 m (21 m worst case over Europe, below 52.5°N) in a PAN visible channel used for disaster monitoring. The 22 multi-spectral channels have resolutions over Europe ranging from 40 m in UV/VNIR (0.3 to 1 μm) to 750 m in TIR (10-12 μm).

Kite Aerial Photography for Low-Cost, Ultra-high Spatial Resolution Multi-Spectral Mapping of Intertidal Landscapes

PubMed Central

Bryson, Mitch; Johnson-Roberson, Matthew; Murphy, Richard J.; Bongiorno, Daniel

2013-01-01

Intertidal ecosystems have primarily been studied using field-based sampling; remote sensing offers the ability to collect data over large areas in a snapshot of time that could complement field-based sampling methods by extrapolating them into the wider spatial and temporal context. Conventional remote sensing tools (such as satellite and aircraft imaging) provide data at limited spatial and temporal resolutions and relatively high costs for small-scale environmental science and ecologically-focussed studies. In this paper, we describe a low-cost, kite-based imaging system and photogrammetric/mapping procedure that was developed for constructing high-resolution, three-dimensional, multi-spectral terrain models of intertidal rocky shores. The processing procedure uses automatic image feature detection and matching, structure-from-motion and photo-textured terrain surface reconstruction algorithms that require minimal human input and only a small number of ground control points and allow the use of cheap, consumer-grade digital cameras. The resulting maps combine imagery at visible and near-infrared wavelengths and topographic information at sub-centimeter resolutions over an intertidal shoreline 200 m long, thus enabling spatial properties of the intertidal environment to be determined across a hierarchy of spatial scales. Results of the system are presented for an intertidal rocky shore at Jervis Bay, New South Wales, Australia. Potential uses of this technique include mapping of plant (micro- and macro-algae) and animal (e.g. gastropods) assemblages at multiple spatial and temporal scales. PMID:24069206

Forest Stand Canopy Structure Attribute Estimation from High Resolution Digital Airborne Imagery

Treesearch

Demetrios Gatziolis

2006-01-01

A study of forest stand canopy variable assessment using digital, airborne, multispectral imagery is presented. Variable estimation involves stem density, canopy closure, and mean crown diameter, and it is based on quantification of spatial autocorrelation among pixel digital numbers (DN) using variogram analysis and an alternative, non-parametric approach known as...

Object-Based Paddy Rice Mapping Using HJ-1A/B Data and Temporal Features Extracted from Time Series MODIS NDVI Data

PubMed Central

Singha, Mrinal; Wu, Bingfang; Zhang, Miao

2016-01-01

Accurate and timely mapping of paddy rice is vital for food security and environmental sustainability. This study evaluates the utility of temporal features extracted from coarse resolution data for object-based paddy rice classification of fine resolution data. The coarse resolution vegetation index data is first fused with the fine resolution data to generate the time series fine resolution data. Temporal features are extracted from the fused data and added with the multi-spectral data to improve the classification accuracy. Temporal features provided the crop growth information, while multi-spectral data provided the pattern variation of paddy rice. The achieved overall classification accuracy and kappa coefficient were 84.37% and 0.68, respectively. The results indicate that the use of temporal features improved the overall classification accuracy of a single-date multi-spectral image by 18.75% from 65.62% to 84.37%. The minimum sensitivity (MS) of the paddy rice classification has also been improved. The comparison showed that the mapped paddy area was analogous to the agricultural statistics at the district level. This work also highlighted the importance of feature selection to achieve higher classification accuracies. These results demonstrate the potential of the combined use of temporal and spectral features for accurate paddy rice classification. PMID:28025525

Object-Based Paddy Rice Mapping Using HJ-1A/B Data and Temporal Features Extracted from Time Series MODIS NDVI Data.

PubMed

Singha, Mrinal; Wu, Bingfang; Zhang, Miao

2016-12-22

Accurate and timely mapping of paddy rice is vital for food security and environmental sustainability. This study evaluates the utility of temporal features extracted from coarse resolution data for object-based paddy rice classification of fine resolution data. The coarse resolution vegetation index data is first fused with the fine resolution data to generate the time series fine resolution data. Temporal features are extracted from the fused data and added with the multi-spectral data to improve the classification accuracy. Temporal features provided the crop growth information, while multi-spectral data provided the pattern variation of paddy rice. The achieved overall classification accuracy and kappa coefficient were 84.37% and 0.68, respectively. The results indicate that the use of temporal features improved the overall classification accuracy of a single-date multi-spectral image by 18.75% from 65.62% to 84.37%. The minimum sensitivity (MS) of the paddy rice classification has also been improved. The comparison showed that the mapped paddy area was analogous to the agricultural statistics at the district level. This work also highlighted the importance of feature selection to achieve higher classification accuracies. These results demonstrate the potential of the combined use of temporal and spectral features for accurate paddy rice classification.

Constraints on methane emissions in North America from future geostationary remote-sensing measurements

DOE PAGES

Bousserez, Nicolas; Henze, Daven K.; Rooney, Brigitte; ...

2016-05-20

The success of future geostationary (GEO) satellite observation missions depends on our ability to design instruments that address their key scientific objectives. Here, an Observation System Simulation Experiment (OSSE) is performed to quantify the constraints on methane (CH 4) emissions in North America obtained from shortwave infrared (SWIR), thermal infrared (TIR), and multi-spectral (SWIR+TIR) measurements in geostationary orbit and from future SWIR low-Earth orbit (LEO) measurements. Furthermore, we used an efficient stochastic algorithm to compute the information content of the inverted emissions at high spatial resolution (0.5° × 0.7°) in a variational framework using the GEOS-Chem chemistry-transport model and itsmore » adjoint. Our results show that at sub-weekly timescales, SWIR measurements in GEO orbit can constrain about twice as many independent flux patterns than in LEO orbit, with a degree of freedom for signal (DOF) for the inversion of 266 and 115, respectively. Comparisons between TIR GEO and SWIR LEO configurations reveal that poor boundary layer sensitivities for the TIR measurements cannot be compensated for by the high spatiotemporal sampling of a GEO orbit. The benefit of a multi-spectral instrument compared to current SWIR products in a GEO context is shown for sub-weekly timescale constraints, with an increase in the DOF of about 50 % for a 3-day inversion. Our results further suggest that both the SWIR and multi-spectral measurements on GEO orbits could almost fully resolve CH 4 fluxes at a spatial resolution of at least 100 km × 100 km over source hotspots (emissions > 4 × 10 5 kg day -1). The sensitivity of the optimized emission scaling factors to typical errors in boundary and initial conditions can reach 30 and 50 % for the SWIR GEO or SWIR LEO configurations, respectively, while it is smaller than 5 % in the case of a multi-spectral GEO system. Our results demonstrate that multi-spectral measurements from a geostationary satellite platform would address the need for higher spatiotemporal constraints on CH 4 emissions while greatly mitigating the impact of inherent uncertainties in source inversion methods on the inferred fluxes.« less

Constraints on methane emissions in North America from future geostationary remote-sensing measurements

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bousserez, Nicolas; Henze, Daven K.; Rooney, Brigitte

The success of future geostationary (GEO) satellite observation missions depends on our ability to design instruments that address their key scientific objectives. Here, an Observation System Simulation Experiment (OSSE) is performed to quantify the constraints on methane (CH 4) emissions in North America obtained from shortwave infrared (SWIR), thermal infrared (TIR), and multi-spectral (SWIR+TIR) measurements in geostationary orbit and from future SWIR low-Earth orbit (LEO) measurements. Furthermore, we used an efficient stochastic algorithm to compute the information content of the inverted emissions at high spatial resolution (0.5° × 0.7°) in a variational framework using the GEOS-Chem chemistry-transport model and itsmore » adjoint. Our results show that at sub-weekly timescales, SWIR measurements in GEO orbit can constrain about twice as many independent flux patterns than in LEO orbit, with a degree of freedom for signal (DOF) for the inversion of 266 and 115, respectively. Comparisons between TIR GEO and SWIR LEO configurations reveal that poor boundary layer sensitivities for the TIR measurements cannot be compensated for by the high spatiotemporal sampling of a GEO orbit. The benefit of a multi-spectral instrument compared to current SWIR products in a GEO context is shown for sub-weekly timescale constraints, with an increase in the DOF of about 50 % for a 3-day inversion. Our results further suggest that both the SWIR and multi-spectral measurements on GEO orbits could almost fully resolve CH 4 fluxes at a spatial resolution of at least 100 km × 100 km over source hotspots (emissions > 4 × 10 5 kg day -1). The sensitivity of the optimized emission scaling factors to typical errors in boundary and initial conditions can reach 30 and 50 % for the SWIR GEO or SWIR LEO configurations, respectively, while it is smaller than 5 % in the case of a multi-spectral GEO system. Our results demonstrate that multi-spectral measurements from a geostationary satellite platform would address the need for higher spatiotemporal constraints on CH 4 emissions while greatly mitigating the impact of inherent uncertainties in source inversion methods on the inferred fluxes.« less

Mapping vegetation cover and biomass on the Qinghai-Tibet-Plateau using hyperspectral measurements and multispectral satellite images

NASA Astrophysics Data System (ADS)

Meyer, Hanna; Lehnert, Lukas W.; Wang, Yun; Reudenbach, Christoph; Nauss, Thomas; Bendix, Jörg

2016-04-01

Pastoralism is the dominant land-use on the Qinghai-Tibet-Plateau (QTP) providing the major economic resource for the local population. However, the pastures are highly supposed to be affected by ongoing degradation whose extent is still disputed. This study uses hyperspectral in situ measurements and multispectral satellite images to assess vegetation cover and above ground biomass (AGB) as proxies of pasture degradation on a regional scale. Using Random Forests in conjunction with recursive feature selection as modeling tool, it is tested whether the full hyperspectral information is needed or if multispectral information is sufficient to accurately estimate vegetation cover and AGB. To regionalize pasture degradation proxies, the transferability of the locally derived models to high resolution multispectral satellite data is assessed. For this purpose, 1183 hyperspectral measurements and vegetation records were sampled at 18 locations on the QTP. AGB was determined on 25 0.5x0.5m plots. Proxies for pasture degradation were derived from the spectra by calculating narrow-band indices (NBI). Using the NBI as predictor variables vegetation cover and AGB were modeled. Models were calculated using the hyperspectral data as well as the same data resampled to WorldView-2, QuickBird and RapidEye channels. The hyperspectral results were compared to the multispectral results. Finally, the models were applied to satellite data to map vegetation cover and AGB on a regional scale. Vegetation cover was accurately predicted by Random Forest if hyperspectral measurements were used. In contrast, errors in AGB estimations were considerably higher. Only small differences in accuracy were observed between the models based on hyper- compared to multispectral data. The application of the models to satellite images generally resulted in an increase of the estimation error. Though this reflects the challenge of applying in situ measurements to satellite data, the results still show a high potential to map pasture degradation proxies on the QTP even for larger scales.

Assessing suitability of multispectral satellites for mapping benthic macroalgal cover in turbid coastal waters by means of model simulations

NASA Astrophysics Data System (ADS)

Kutser, Tiit; Vahtmäe, Ele; Martin, Georg

2006-04-01

One of the objectives of monitoring benthic algal cover is to observe short- and long-term changes in species distribution and structure of coastal benthic habitats as indicators of ecological state. Mapping benthic algal cover with conventional methods (diving) provides great accuracy and high resolution, yet is very expensive and is limited by the time and manpower necessary. We measured reflectance spectra of three indicator species for the Baltic Sea: Cladophora glomerata (green macroalgae), Furcellaria lumbricalis (red macroalgae), and Fucus vesiculosus (brown macroalgae) and used a bio-optical model in an attempt to estimate whether these algae are separable from each other and sandy bottom or deep water by means of satellite remote sensing. Our modelling results indicate that to some extent it is possible to map the studied species with multispectral satellite sensors in turbid waters. However, the depths where the macroalgae can be detected are often shallower than the maximum depths where the studied species usually grow. In waters deeper than just a few meters, the differences between the studied bottom types are seen only in band 2 (green) of the multispectral sensors under investigation. It means that multispectral sensors are capable of detecting difference in brightness only in one band which is insufficient for recognition of different bottom types in waters where no or few in situ data are available. Configuration of MERIS spectral bands allows the recognition of red, green and brown macroalgae based on their spectral signatures provided the algal belts are wider than MERIS spatial resolution. Commercial stock of F. lumbricalis in West-Estonian Archipelago covers area where MERIS 300 m spatial resolution is adequate. However, strong attenuation of light in the water column and signal to noise ratio of the sensor do not allow mapping of Furcellaria down to maximum depths where it occurs.

Landsat multispectral sharpening using a sensor system model and panchromatic image

USGS Publications Warehouse

Lemeshewsky, G.P.; ,

2003-01-01

The thematic mapper (TM) sensor aboard Landsats 4, 5 and enhanced TM plus (ETM+) on Landsat 7 collect imagery at 30-m sample distance in six spectral bands. New with ETM+ is a 15-m panchromatic (P) band. With image sharpening techniques, this higher resolution P data, or as an alternative, the 10-m (or 5-m) P data of the SPOT satellite, can increase the spatial resolution of the multispectral (MS) data. Sharpening requires that the lower resolution MS image be coregistered and resampled to the P data before high spatial frequency information is transferred to the MS data. For visual interpretation and machine classification tasks, it is important that the sharpened data preserve the spectral characteristics of the original low resolution data. A technique was developed for sharpening (in this case, 3:1 spatial resolution enhancement) visible spectral band data, based on a model of the sensor system point spread function (PSF) in order to maintain spectral fidelity. It combines high-pass (HP) filter sharpening methods with iterative image restoration to reduce degradations caused by sensor-system-induced blurring and resembling. Also there is a spectral fidelity requirement: sharpened MS when filtered by the modeled degradations should reproduce the low resolution source MS. Quantitative evaluation of sharpening performance was made by using simulated low resolution data generated from digital color-IR aerial photography. In comparison to the HP-filter-based sharpening method, results for the technique in this paper with simulated data show improved spectral fidelity. Preliminary results with TM 30-m visible band data sharpened with simulated 10-m panchromatic data are promising but require further study.

Benthic Habitat Mapping Using Multispectral High-Resolution Imagery: Evaluation of Shallow Water Atmospheric Correction Techniques.

PubMed

Eugenio, Francisco; Marcello, Javier; Martin, Javier; Rodríguez-Esparragón, Dionisio

2017-11-16

Remote multispectral data can provide valuable information for monitoring coastal water ecosystems. Specifically, high-resolution satellite-based imaging systems, as WorldView-2 (WV-2), can generate information at spatial scales needed to implement conservation actions for protected littoral zones. However, coastal water-leaving radiance arriving at the space-based sensor is often small as compared to reflected radiance. In this work, complex approaches, which usually use an accurate radiative transfer code to correct the atmospheric effects, such as FLAASH, ATCOR and 6S, have been implemented for high-resolution imagery. They have been assessed in real scenarios using field spectroradiometer data. In this context, the three approaches have achieved excellent results and a slightly superior performance of 6S model-based algorithm has been observed. Finally, for the mapping of benthic habitats in shallow-waters marine protected environments, a relevant application of the proposed atmospheric correction combined with an automatic deglinting procedure is presented. This approach is based on the integration of a linear mixing model of benthic classes within the radiative transfer model of the water. The complete methodology has been applied to selected ecosystems in the Canary Islands (Spain) but the obtained results allow the robust mapping of the spatial distribution and density of seagrass in coastal waters and the analysis of multitemporal variations related to the human activity and climate change in littoral zones.

Benthic Habitat Mapping Using Multispectral High-Resolution Imagery: Evaluation of Shallow Water Atmospheric Correction Techniques

PubMed Central

Eugenio, Francisco; Marcello, Javier; Martin, Javier

2017-01-01

Remote multispectral data can provide valuable information for monitoring coastal water ecosystems. Specifically, high-resolution satellite-based imaging systems, as WorldView-2 (WV-2), can generate information at spatial scales needed to implement conservation actions for protected littoral zones. However, coastal water-leaving radiance arriving at the space-based sensor is often small as compared to reflected radiance. In this work, complex approaches, which usually use an accurate radiative transfer code to correct the atmospheric effects, such as FLAASH, ATCOR and 6S, have been implemented for high-resolution imagery. They have been assessed in real scenarios using field spectroradiometer data. In this context, the three approaches have achieved excellent results and a slightly superior performance of 6S model-based algorithm has been observed. Finally, for the mapping of benthic habitats in shallow-waters marine protected environments, a relevant application of the proposed atmospheric correction combined with an automatic deglinting procedure is presented. This approach is based on the integration of a linear mixing model of benthic classes within the radiative transfer model of the water. The complete methodology has been applied to selected ecosystems in the Canary Islands (Spain) but the obtained results allow the robust mapping of the spatial distribution and density of seagrass in coastal waters and the analysis of multitemporal variations related to the human activity and climate change in littoral zones. PMID:29144444

Comparing the Potential of Multispectral and Hyperspectral Data for Monitoring Oil Spill Impact.

PubMed

Khanna, Shruti; Santos, Maria J; Ustin, Susan L; Shapiro, Kristen; Haverkamp, Paul J; Lay, Mui

2018-02-12

Oil spills from offshore drilling and coastal refineries often cause significant degradation of coastal environments. Early oil detection may prevent losses and speed up recovery if monitoring of the initial oil extent, oil impact, and recovery are in place. Satellite imagery data can provide a cost-effective alternative to expensive airborne imagery or labor intensive field campaigns for monitoring effects of oil spills on wetlands. However, these satellite data may be restricted in their ability to detect and map ecosystem recovery post-spill given their spectral measurement properties and temporal frequency. In this study, we assessed whether spatial and spectral resolution, and other sensor characteristics influence the ability to detect and map vegetation stress and mortality due to oil. We compared how well three satellite multispectral sensors: WorldView2, RapidEye and Landsat EMT+, match the ability of the airborne hyperspectral AVIRIS sensor to map oil-induced vegetation stress, recovery, and mortality after the DeepWater Horizon oil spill in the Gulf of Mexico in 2010. We found that finer spatial resolution (3.5 m) provided better delineation of the oil-impacted wetlands and better detection of vegetation stress along oiled shorelines in saltmarsh wetland ecosystems. As spatial resolution become coarser (3.5 m to 30 m) the ability to accurately detect and map stressed vegetation decreased. Spectral resolution did improve the detection and mapping of oil-impacted wetlands but less strongly than spatial resolution, suggesting that broad-band data may be sufficient to detect and map oil-impacted wetlands. AVIRIS narrow-band data performs better detecting vegetation stress, followed by WorldView2, RapidEye and then Landsat 15 m (pan sharpened) data. Higher quality sensor optics and higher signal-to-noise ratio (SNR) may also improve detection and mapping of oil-impacted wetlands; we found that resampled coarser resolution AVIRIS data with higher SNR performed better than either of the three satellite sensors. The ability to acquire imagery during certain times (midday, low tide, etc.) or a certain date (cloud-free, etc.) is also important in these tidal wetlands; WorldView2 imagery captured at high-tide detected a narrower band of shoreline affected by oil likely because some of the impacted wetland was below the tideline. These results suggest that while multispectral data may be sufficient for detecting the extent of oil-impacted wetlands, high spectral and spatial resolution, high-quality sensor characteristics, and the ability to control time of image acquisition may improve assessment and monitoring of vegetation stress and recovery post oil spills.

Comparing the Potential of Multispectral and Hyperspectral Data for Monitoring Oil Spill Impact

PubMed Central

Santos, Maria J.; Ustin, Susan L.; Haverkamp, Paul J.; Lay, Mui

2018-01-01

Oil spills from offshore drilling and coastal refineries often cause significant degradation of coastal environments. Early oil detection may prevent losses and speed up recovery if monitoring of the initial oil extent, oil impact, and recovery are in place. Satellite imagery data can provide a cost-effective alternative to expensive airborne imagery or labor intensive field campaigns for monitoring effects of oil spills on wetlands. However, these satellite data may be restricted in their ability to detect and map ecosystem recovery post-spill given their spectral measurement properties and temporal frequency. In this study, we assessed whether spatial and spectral resolution, and other sensor characteristics influence the ability to detect and map vegetation stress and mortality due to oil. We compared how well three satellite multispectral sensors: WorldView2, RapidEye and Landsat EMT+, match the ability of the airborne hyperspectral AVIRIS sensor to map oil-induced vegetation stress, recovery, and mortality after the DeepWater Horizon oil spill in the Gulf of Mexico in 2010. We found that finer spatial resolution (3.5 m) provided better delineation of the oil-impacted wetlands and better detection of vegetation stress along oiled shorelines in saltmarsh wetland ecosystems. As spatial resolution become coarser (3.5 m to 30 m) the ability to accurately detect and map stressed vegetation decreased. Spectral resolution did improve the detection and mapping of oil-impacted wetlands but less strongly than spatial resolution, suggesting that broad-band data may be sufficient to detect and map oil-impacted wetlands. AVIRIS narrow-band data performs better detecting vegetation stress, followed by WorldView2, RapidEye and then Landsat 15 m (pan sharpened) data. Higher quality sensor optics and higher signal-to-noise ratio (SNR) may also improve detection and mapping of oil-impacted wetlands; we found that resampled coarser resolution AVIRIS data with higher SNR performed better than either of the three satellite sensors. The ability to acquire imagery during certain times (midday, low tide, etc.) or a certain date (cloud-free, etc.) is also important in these tidal wetlands; WorldView2 imagery captured at high-tide detected a narrower band of shoreline affected by oil likely because some of the impacted wetland was below the tideline. These results suggest that while multispectral data may be sufficient for detecting the extent of oil-impacted wetlands, high spectral and spatial resolution, high-quality sensor characteristics, and the ability to control time of image acquisition may improve assessment and monitoring of vegetation stress and recovery post oil spills. PMID:29439504

WorldView-2 and the evolution of the DigitalGlobe remote sensing satellite constellation: introductory paper for the special session on WorldView-2

NASA Astrophysics Data System (ADS)

Anderson, Neal T.; Marchisio, Giovanni B.

2012-06-01

Over the last decade DigitalGlobe (DG) has built and launched a series of remote sensing satellites with steadily increasing capabilities: QuickBird, WorldView-1 (WV-1), and WorldView-2 (WV-2). Today, this constellation acquires over 2.5 million km2 of imagery on a daily basis. This paper presents the configuration and performance capabilities of each of these satellites, with emphasis on the unique spatial and spectral capabilities of WV-2. WV-2 employs high-precision star tracker and inertial measurement units to achieve a geolocation accuracy of 5 m Circular Error, 90% confidence (CE90). The native resolution of WV-2 is 0.5 m GSD in the panchromatic band and 2 m GSD in 8 multispectral bands. Four of the multispectral bands match those of the Landsat series of satellites; four new bands enable novel and expanded applications. We are rapidly establishing and refreshing a global database of very high resolution (VHR) 8-band multispectral imagery. Control moment gyroscopes (CMGs) on both WV-1 and WV-2 improve collection capacity and provide the agility to capture multi-angle sequences in rapid succession. These capabilities result in a rich combination of image features that can be exploited to develop enhanced monitoring solutions. Algorithms for interpretation and analysis can leverage: 1) broader and more continuous spectral coverage at 2 m resolution; 2) textural and morphological information from the 0.5 m panchromatic band; 3) ancillary information from stereo and multi-angle collects, including high precision digital elevation models; 4) frequent revisits and time-series collects; and 5) the global reference image archives. We introduce the topic of creative fusion of image attributes, as this provides a unifying theme for many of the papers in this WV-2 Special Session.

Heterodyne frequency-domain multispectral diffuse optical tomography of breast cancer in the parallel-plane transmission geometry

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ban, H. Y.; Kavuri, V. C., E-mail: venk@physics.up

Purpose: The authors introduce a state-of-the-art all-optical clinical diffuse optical tomography (DOT) imaging instrument which collects spatially dense, multispectral, frequency-domain breast data in the parallel-plate geometry. Methods: The instrument utilizes a CCD-based heterodyne detection scheme that permits massively parallel detection of diffuse photon density wave amplitude and phase for a large number of source–detector pairs (10{sup 6}). The stand-alone clinical DOT instrument thus offers high spatial resolution with reduced crosstalk between absorption and scattering. Other novel features include a fringe profilometry system for breast boundary segmentation, real-time data normalization, and a patient bed design which permits both axial and sagittalmore » breast measurements. Results: The authors validated the instrument using tissue simulating phantoms with two different chromophore-containing targets and one scattering target. The authors also demonstrated the instrument in a case study breast cancer patient; the reconstructed 3D image of endogenous chromophores and scattering gave tumor localization in agreement with MRI. Conclusions: Imaging with a novel parallel-plate DOT breast imager that employs highly parallel, high-resolution CCD detection in the frequency-domain was demonstrated.« less

Intelligent image processing for vegetation classification using multispectral LANDSAT data

NASA Astrophysics Data System (ADS)

Santos, Stewart R.; Flores, Jorge L.; Garcia-Torales, G.

2015-09-01

We propose an intelligent computational technique for analysis of vegetation imaging, which are acquired with multispectral scanner (MSS) sensor. This work focuses on intelligent and adaptive artificial neural network (ANN) methodologies that allow segmentation and classification of spectral remote sensing (RS) signatures, in order to obtain a high resolution map, in which we can delimit the wooded areas and quantify the amount of combustible materials present into these areas. This could provide important information to prevent fires and deforestation of wooded areas. The spectral RS input data, acquired by the MSS sensor, are considered in a random propagation remotely sensed scene with unknown statistics for each Thematic Mapper (TM) band. Performing high-resolution reconstruction and adding these spectral values with neighbor pixels information from each TM band, we can include contextual information into an ANN. The biggest challenge in conventional classifiers is how to reduce the number of components in the feature vector, while preserving the major information contained in the data, especially when the dimensionality of the feature space is high. Preliminary results show that the Adaptive Modified Neural Network method is a promising and effective spectral method for segmentation and classification in RS images acquired with MSS sensor.

An Overview of the CBERS-2 Satellite and Comparison of the CBERS-2 CCD Data with the L5 TM Data

NASA Technical Reports Server (NTRS)

Chandler, Gyanesh

2007-01-01

CBERS satellite carries on-board a multi sensor payload with different spatial resolutions and collection frequencies. HRCCD (High Resolution CCD Camera), IRMSS (Infrared Multispectral Scanner), and WFI (Wide-Field Imager). The CCD and the WFI camera operate in the VNIR regions, while the IRMSS operates in SWIR and thermal region. In addition to the imaging payload, the satellite carries a Data Collection System (DCS) and Space Environment Monitor (SEM).

Radiometric calibration of the Earth observing system's imaging sensors

NASA Technical Reports Server (NTRS)

Slater, P. N.

1987-01-01

Philosophy, requirements, and methods of calibration of multispectral space sensor systems as applicable to the Earth Observing System (EOS) are discussed. Vicarious methods for calibration of low spatial resolution systems, with respect to the Advanced Very High Resolution Radiometer (AVHRR), are then summarized. Finally, a theoretical introduction is given to a new vicarious method of calibration using the ratio of diffuse-to-global irradiance at the Earth's surfaces as the key input. This may provide an additional independent method for in-flight calibration.

Measurement of two-dimensional thickness of micro-patterned thin film based on image restoration in a spectroscopic imaging reflectometer.

PubMed

Kim, Min-Gab; Kim, Jin-Yong

2018-05-01

In this paper, we introduce a method to overcome the limitation of thickness measurement of a micro-patterned thin film. A spectroscopic imaging reflectometer system that consists of an acousto-optic tunable filter, a charge-coupled-device camera, and a high-magnitude objective lens was proposed, and a stack of multispectral images was generated. To secure improved accuracy and lateral resolution in the reconstruction of a two-dimensional thin film thickness, prior to the analysis of spectral reflectance profiles from each pixel of multispectral images, the image restoration based on an iterative deconvolution algorithm was applied to compensate for image degradation caused by blurring.

Monitoring forest land from high altitude and from space

NASA Technical Reports Server (NTRS)

1971-01-01

Forest inventory, forest stress, and standardization and calibration studies are presented. These include microscale photointerpretation of forest and nonforest land classes, multiseasonal film densities for automated forest and nonforest land classification, trend and spread of bark beetle infestations from 1968 through 1971, aerial photography for determining optimum levels of stand density to reduce such infestations, use of airborne spectrometers and multispectral scanners for previsual detection of Ponderosa pine trees under stress from insects and diseases, establishment of an earth resources technology satellite test site in the Black Hills and the identification of natural resolution targets, detection of root disease impact on forest stands by sequential orbital and suborbital multispectral photography, and calibration of color aerial photography.

Some practical aspects of lossless and nearly-lossless compression of AVHRR imagery

NASA Technical Reports Server (NTRS)

Hogan, David B.; Miller, Chris X.; Christensen, Than Lee; Moorti, Raj

1994-01-01

Compression of Advanced Very high Resolution Radiometers (AVHRR) imagery operating in a lossless or nearly-lossless mode is evaluated. Several practical issues are analyzed including: variability of compression over time and among channels, rate-smoothing buffer size, multi-spectral preprocessing of data, day/night handling, and impact on key operational data applications. This analysis is based on a DPCM algorithm employing the Universal Noiseless Coder, which is a candidate for inclusion in many future remote sensing systems. It is shown that compression rates of about 2:1 (daytime) can be achieved with modest buffer sizes (less than or equal to 2.5 Mbytes) and a relatively simple multi-spectral preprocessing step.

Spatial arrangement of color filter array for multispectral image acquisition

NASA Astrophysics Data System (ADS)

Shrestha, Raju; Hardeberg, Jon Y.; Khan, Rahat

2011-03-01

In the past few years there has been a significant volume of research work carried out in the field of multispectral image acquisition. The focus of most of these has been to facilitate a type of multispectral image acquisition systems that usually requires multiple subsequent shots (e.g. systems based on filter wheels, liquid crystal tunable filters, or active lighting). Recently, an alternative approach for one-shot multispectral image acquisition has been proposed; based on an extension of the color filter array (CFA) standard to produce more than three channels. We can thus introduce the concept of multispectral color filter array (MCFA). But this field has not been much explored, particularly little focus has been given in developing systems which focuses on the reconstruction of scene spectral reflectance. In this paper, we have explored how the spatial arrangement of multispectral color filter array affects the acquisition accuracy with the construction of MCFAs of different sizes. We have simulated acquisitions of several spectral scenes using different number of filters/channels, and compared the results with those obtained by the conventional regular MCFA arrangement, evaluating the precision of the reconstructed scene spectral reflectance in terms of spectral RMS error, and colorimetric ▵E*ab color differences. It has been found that the precision and the the quality of the reconstructed images are significantly influenced by the spatial arrangement of the MCFA and the effect will be more and more prominent with the increase in the number of channels. We believe that MCFA-based systems can be a viable alternative for affordable acquisition of multispectral color images, in particular for applications where spatial resolution can be traded off for spectral resolution. We have shown that the spatial arrangement of the array is an important design issue.

Meteorological satellite data: A tool to describe the health of the world's agriculture

NASA Technical Reports Server (NTRS)

Gray, T. I., Jr.; Mccrary, D. G. (Principal Investigator); Scott, L.

1981-01-01

Local area coverage data acquired aboard the TIROS-N satellite family by the advanced very high resolution radiometer systems was examined to determine the agricultural information current. Albedo differences between channel 2 and channel 1 of the advanced very high resolution radiometer LAC (called EVI) are shown to be closely correlated to the Ashburn vegetative index produced from LANDSAT multispectral scanner data which have been shown to vary in response to "greenness", soil moisture, and crop production. The statistical correlation between the EVI and the Ashburn Vegetative Index (+ or - 1 deg) is 0.86.

Pancam Imaging of the Mars Exploration Rover Landing Sites in Gusev Crater and Meridiani Planum

NASA Technical Reports Server (NTRS)

Bell, J. F., III; Squyres, S. W.; Arvidson, R. E.; Arneson, H. M.; Bass, D.; Cabrol, N.; Calvin, W.; Farmer, J.; Farrand, W. H.

2004-01-01

The Mars Exploration Rovers carry four Panoramic Camera (Pancam) instruments (two per rover) that have obtained high resolution multispectral and stereoscopic images for studies of the geology, mineralogy, and surface and atmospheric physical properties at both rover landing sites. The Pancams are also providing significant mission support measurements for the rovers, including Sun-finding for rover navigation, hazard identification and digital terrain modeling to help guide long-term rover traverse decisions, high resolution imaging to help guide the selection of in situ sampling targets, and acquisition of education and public outreach imaging products.

Time-of-Flight Microwave Camera.

PubMed

Charvat, Gregory; Temme, Andrew; Feigin, Micha; Raskar, Ramesh

2015-10-05

Microwaves can penetrate many obstructions that are opaque at visible wavelengths, however microwave imaging is challenging due to resolution limits associated with relatively small apertures and unrecoverable "stealth" regions due to the specularity of most objects at microwave frequencies. We demonstrate a multispectral time-of-flight microwave imaging system which overcomes these challenges with a large passive aperture to improve lateral resolution, multiple illumination points with a data fusion method to reduce stealth regions, and a frequency modulated continuous wave (FMCW) receiver to achieve depth resolution. The camera captures images with a resolution of 1.5 degrees, multispectral images across the X frequency band (8 GHz-12 GHz), and a time resolution of 200 ps (6 cm optical path in free space). Images are taken of objects in free space as well as behind drywall and plywood. This architecture allows "camera-like" behavior from a microwave imaging system and is practical for imaging everyday objects in the microwave spectrum.

Analysis of multispectral and hyperspectral longwave infrared (LWIR) data for geologic mapping

NASA Astrophysics Data System (ADS)

Kruse, Fred A.; McDowell, Meryl

2015-05-01

Multispectral MODIS/ASTER Airborne Simulator (MASTER) data and Hyperspectral Thermal Emission Spectrometer (HyTES) data covering the 8 - 12 μm spectral range (longwave infrared or LWIR) were analyzed for an area near Mountain Pass, California. Decorrelation stretched images were initially used to highlight spectral differences between geologic materials. Both datasets were atmospherically corrected using the ISAC method, and the Normalized Emissivity approach was used to separate temperature and emissivity. The MASTER data had 10 LWIR spectral bands and approximately 35-meter spatial resolution and covered a larger area than the HyTES data, which were collected with 256 narrow (approximately 17nm-wide) spectral bands at approximately 2.3-meter spatial resolution. Spectra for key spatially-coherent, spectrally-determined geologic units for overlap areas were overlain and visually compared to determine similarities and differences. Endmember spectra were extracted from both datasets using n-dimensional scatterplotting and compared to emissivity spectral libraries for identification. Endmember distributions and abundances were then mapped using Mixture-Tuned Matched Filtering (MTMF), a partial unmixing approach. Multispectral results demonstrate separation of silica-rich vs non-silicate materials, with distinct mapping of carbonate areas and general correspondence to the regional geology. Hyperspectral results illustrate refined mapping of silicates with distinction between similar units based on the position, character, and shape of high resolution emission minima near 9 μm. Calcite and dolomite were separated, identified, and mapped using HyTES based on a shift of the main carbonate emissivity minimum from approximately 11.3 to 11.2 μm respectively. Both datasets demonstrate the utility of LWIR spectral remote sensing for geologic mapping.

Global High Resolution Mineral Maps Of The Moon Using Data From the Kaguya Multiband Imager and LRO Diviner Lunar Radiometer

NASA Astrophysics Data System (ADS)

Lucey, P. G.; Lemelin, M.; Ohtake, M.; Gaddis, L. R.; Greenhagen, B. T.; Yamamoto, S.; Hare, T. M.; Taylor, J.; Martel, L.; Norman, J.

2016-12-01

We combine visible and near-IR multispectral data from the Kaguya Multiband Imager (MI) with thermal infrared multispectral data from the LRO Diviner Lunar Radiometer Experiment to produce global mineral abundance data at 60-m resolution. The base data set applies a radiative transfer mixing model to the Kaguya MI data to produce global maps of plagioclase, low-Ca pyroxene, high-Ca pyroxene and olivine. Diviner thermal multispectral data are highly sensitive to the ratio of plagioclase to mafic minerals and provide independent data to both validate and improve confidence in the derived mineral abundances. The data set is validated using a new set of mineral abundances derived for lunar soils from all lunar sampling sites resolvable using MI data. Modal abundances are derived using X-ray diffraction patterns analyzed with quantitative Rietveldt analysis. Modal abundances were derived from 124 soils from 47 individual Apollo sampling stations. Some individual soil locations within sampling stations can be resolved increasing the total number of resolved locations to 56. With quantitative mineral abundances we can examine the distribution of classically defined lunar rock types in unprecedented detail. In the Feldspathic Highlands Terrane (FHT) the crust is dominated in surface area by noritic anorthosite consistent with a highly mixed composition. Classically defined anorthosite is widespread in the FHT, but much less abundant than the mafic anorthosites. The Procellarum KREEP Terrane and the South Pole Aitken Basin are more noritic than the FHT as previously recognized with abundant norite exposed. While dunite is not found, varieties of troctolitic rocks are widespread in basin rings, especially Crisium, Humorum and Moscoviense, and also occur in the core of the FHT. Only troctolites and anorthosites appear consistently concentrated in basin rings. We have barely scratched the surface of the full resolution data, but have completed an inventory of rock types on basin rings and find in most cases they are dominated by mixed anorthositic rocks similar to the rest of the crust suggesting the rings may be partly mantled by background noritic anorthosite. The major exception is Orientale with its highly anorthositic inner ring.

A targeted illumination optical fiber probe for high resolution fluorescence imaging and optical switching

NASA Astrophysics Data System (ADS)

Shinde, Anant; Perinchery, Sandeep Menon; Murukeshan, Vadakke Matham

2017-04-01

An optical imaging probe with targeted multispectral and spatiotemporal illumination features has applications in many diagnostic biomedical studies. However, these systems are mostly adapted in conventional microscopes, limiting their use for in vitro applications. We present a variable resolution imaging probe using a digital micromirror device (DMD) with an achievable maximum lateral resolution of 2.7 μm and an axial resolution of 5.5 μm, along with precise shape selective targeted illumination ability. We have demonstrated switching of different wavelengths to image multiple regions in the field of view. Moreover, the targeted illumination feature allows enhanced image contrast by time averaged imaging of selected regions with different optical exposure. The region specific multidirectional scanning feature of this probe has facilitated high speed targeted confocal imaging.

Sputnik Planum, in Color

NASA Image and Video Library

2015-10-15

This high-resolution image captured by NASA's New Horizons spacecraft combines blue, red and infrared images taken by the Ralph/Multispectral Visual Imaging Camera (MVIC). The bright expanse is the western lobe of the "heart," informally called Sputnik Planum, which has been found to be rich in nitrogen, carbon monoxide and methane ices. http://photojournal.jpl.nasa.gov/catalog/PIA20007

Pattern recognition: A basis for remote sensing data analysis

NASA Technical Reports Server (NTRS)

Swain, P. H.

1973-01-01

The theoretical basis for the pattern-recognition-oriented algorithms used in the multispectral data analysis software system is discussed. A model of a general pattern recognition system is presented. The receptor or sensor is usually a multispectral scanner. For each ground resolution element the receptor produces n numbers or measurements corresponding to the n channels of the scanner.

High-spatial resolution multispectral and panchromatic satellite imagery for mapping perennial desert plants

NASA Astrophysics Data System (ADS)

Alsharrah, Saad A.; Bruce, David A.; Bouabid, Rachid; Somenahalli, Sekhar; Corcoran, Paul A.

2015-10-01

The use of remote sensing techniques to extract vegetation cover information for the assessment and monitoring of land degradation in arid environments has gained increased interest in recent years. However, such a task can be challenging, especially for medium-spatial resolution satellite sensors, due to soil background effects and the distribution and structure of perennial desert vegetation. In this study, we utilised Pleiades high-spatial resolution, multispectral (2m) and panchromatic (0.5m) imagery and focused on mapping small shrubs and low-lying trees using three classification techniques: 1) vegetation indices (VI) threshold analysis, 2) pre-built object-oriented image analysis (OBIA), and 3) a developed vegetation shadow model (VSM). We evaluated the success of each approach using a root of the sum of the squares (RSS) metric, which incorporated field data as control and three error metrics relating to commission, omission, and percent cover. Results showed that optimum VI performers returned good vegetation cover estimates at certain thresholds, but failed to accurately map the distribution of the desert plants. Using the pre-built IMAGINE Objective OBIA approach, we improved the vegetation distribution mapping accuracy, but this came at the cost of over classification, similar to results of lowering VI thresholds. We further introduced the VSM which takes into account shadow for further refining vegetation cover classification derived from VI. The results showed significant improvements in vegetation cover and distribution accuracy compared to the other techniques. We argue that the VSM approach using high-spatial resolution imagery provides a more accurate representation of desert landscape vegetation and should be considered in assessments of desertification.

Portable Multispectral Colorimeter for Metallic Ion Detection and Classification

PubMed Central

Jaimes, Ruth F. V. V.; Borysow, Walter; Gomes, Osmar F.; Salcedo, Walter J.

2017-01-01

This work deals with a portable device system applied to detect and classify different metallic ions as proposed and developed, aiming its application for hydrological monitoring systems such as rivers, lakes and groundwater. Considering the system features, a portable colorimetric system was developed by using a multispectral optoelectronic sensor. All the technology of quantification and classification of metallic ions using optoelectronic multispectral sensors was fully integrated in the embedded hardware FPGA ( Field Programmable Gate Array) technology and software based on virtual instrumentation (NI LabView®). The system draws on an indicative colorimeter by using the chromogen reagent of 1-(2-pyridylazo)-2-naphthol (PAN). The results obtained with the signal processing and pattern analysis using the method of the linear discriminant analysis, allows excellent results during detection and classification of Pb(II), Cd(II), Zn(II), Cu(II), Fe(III) and Ni(II) ions, with almost the same level of performance as for those obtained from the Ultravioled and visible (UV-VIS) spectrophotometers of high spectral resolution. PMID:28788082

Portable Multispectral Colorimeter for Metallic Ion Detection and Classification.

PubMed

Braga, Mauro S; Jaimes, Ruth F V V; Borysow, Walter; Gomes, Osmar F; Salcedo, Walter J

2017-07-28

This work deals with a portable device system applied to detect and classify different metallic ions as proposed and developed, aiming its application for hydrological monitoring systems such as rivers, lakes and groundwater. Considering the system features, a portable colorimetric system was developed by using a multispectral optoelectronic sensor. All the technology of quantification and classification of metallic ions using optoelectronic multispectral sensors was fully integrated in the embedded hardware FPGA ( Field Programmable Gate Array) technology and software based on virtual instrumentation (NI LabView ® ). The system draws on an indicative colorimeter by using the chromogen reagent of 1-(2-pyridylazo)-2-naphthol (PAN). The results obtained with the signal processing and pattern analysis using the method of the linear discriminant analysis, allows excellent results during detection and classification of Pb(II), Cd(II), Zn(II), Cu(II), Fe(III) and Ni(II) ions, with almost the same level of performance as for those obtained from the Ultravioled and visible (UV-VIS) spectrophotometers of high spectral resolution.

Coastal modification of a scene employing multispectral images and vector operators.

PubMed

Lira, Jorge

2017-05-01

Changes in sea level, wind patterns, sea current patterns, and tide patterns have produced morphologic transformations in the coastline area of Tamaulipas Sate in North East Mexico. Such changes generated a modification of the coastline and variations of the texture-relief and texture of the continental area of Tamaulipas. Two high-resolution multispectral satellite Satellites Pour l'Observation de la Terre images were employed to quantify the morphologic change of such continental area. The images cover a time span close to 10 years. A variant of the principal component analysis was used to delineate the modification of the land-water line. To quantify changes in texture-relief and texture, principal component analysis was applied to the multispectral images. The first principal components of each image were modeled as a discrete bidimensional vector field. The divergence and Laplacian vector operators were applied to the discrete vector field. The divergence provided the change of texture, while the Laplacian produced the change of texture-relief in the area of study.

Data fusion in data scarce areas using a back-propagation artificial neural network model: a case study of the South China Sea

NASA Astrophysics Data System (ADS)

Wang, Zheng; Mao, Zhihua; Xia, Junshi; Du, Peijun; Shi, Liangliang; Huang, Haiqing; Wang, Tianyu; Gong, Fang; Zhu, Qiankun

2018-06-01

The cloud cover for the South China Sea and its coastal area is relatively large throughout the year, which limits the potential application of optical remote sensing. A HJ-charge-coupled device (HJ-CCD) has the advantages of wide field, high temporal resolution, and short repeat cycle. However, this instrument suffers from its use of only four relatively low-quality bands which can't adequately resolve the features of long wavelengths. The Landsat Enhanced Thematic Mapper-plus (ETM+) provides high-quality data, however, the Scan Line Corrector (SLC) stopped working and caused striping of remote sensed images, which dramatically reduced the coverage of the ETM+ data. In order to combine the advantages of the HJ-CCD and Landsat ETM+ data, we adopted a back-propagation artificial neural network (BP-ANN) to fuse these two data types for this study. The results showed that the fused output data not only have the advantage of data intactness for the HJ-CCD, but also have the advantages of the multi-spectral and high radiometric resolution of the ETM+ data. Moreover, the fused data were analyzed qualitatively, quantitatively and from a practical application point of view. Experimental studies indicated that the fused data have a full spatial distribution, multi-spectral bands, high radiometric resolution, a small difference between the observed and fused output data, and a high correlation between the observed and fused data. The excellent performance in its practical application is a further demonstration that the fused data are of high quality.

Semiconductor Laser Multi-Spectral Sensing and Imaging

PubMed Central

Le, Han Q.; Wang, Yang

2010-01-01

Multi-spectral laser imaging is a technique that can offer a combination of the laser capability of accurate spectral sensing with the desirable features of passive multispectral imaging. The technique can be used for detection, discrimination, and identification of objects by their spectral signature. This article describes and reviews the development and evaluation of semiconductor multi-spectral laser imaging systems. Although the method is certainly not specific to any laser technology, the use of semiconductor lasers is significant with respect to practicality and affordability. More relevantly, semiconductor lasers have their own characteristics; they offer excellent wavelength diversity but usually with modest power. Thus, system design and engineering issues are analyzed for approaches and trade-offs that can make the best use of semiconductor laser capabilities in multispectral imaging. A few systems were developed and the technique was tested and evaluated on a variety of natural and man-made objects. It was shown capable of high spectral resolution imaging which, unlike non-imaging point sensing, allows detecting and discriminating objects of interest even without a priori spectroscopic knowledge of the targets. Examples include material and chemical discrimination. It was also shown capable of dealing with the complexity of interpreting diffuse scattered spectral images and produced results that could otherwise be ambiguous with conventional imaging. Examples with glucose and spectral imaging of drug pills were discussed. Lastly, the technique was shown with conventional laser spectroscopy such as wavelength modulation spectroscopy to image a gas (CO). These results suggest the versatility and power of multi-spectral laser imaging, which can be practical with the use of semiconductor lasers. PMID:22315555

Semiconductor laser multi-spectral sensing and imaging.

PubMed

Le, Han Q; Wang, Yang

2010-01-01

Multi-spectral laser imaging is a technique that can offer a combination of the laser capability of accurate spectral sensing with the desirable features of passive multispectral imaging. The technique can be used for detection, discrimination, and identification of objects by their spectral signature. This article describes and reviews the development and evaluation of semiconductor multi-spectral laser imaging systems. Although the method is certainly not specific to any laser technology, the use of semiconductor lasers is significant with respect to practicality and affordability. More relevantly, semiconductor lasers have their own characteristics; they offer excellent wavelength diversity but usually with modest power. Thus, system design and engineering issues are analyzed for approaches and trade-offs that can make the best use of semiconductor laser capabilities in multispectral imaging. A few systems were developed and the technique was tested and evaluated on a variety of natural and man-made objects. It was shown capable of high spectral resolution imaging which, unlike non-imaging point sensing, allows detecting and discriminating objects of interest even without a priori spectroscopic knowledge of the targets. Examples include material and chemical discrimination. It was also shown capable of dealing with the complexity of interpreting diffuse scattered spectral images and produced results that could otherwise be ambiguous with conventional imaging. Examples with glucose and spectral imaging of drug pills were discussed. Lastly, the technique was shown with conventional laser spectroscopy such as wavelength modulation spectroscopy to image a gas (CO). These results suggest the versatility and power of multi-spectral laser imaging, which can be practical with the use of semiconductor lasers.

Multi-spectral confocal microendoscope for in-vivo imaging

NASA Astrophysics Data System (ADS)

Rouse, Andrew Robert

The concept of in-vivo multi-spectral confocal microscopy is introduced. A slit-scanning multi-spectral confocal microendoscope (MCME) was built to demonstrate the technique. The MCME employs a flexible fiber-optic catheter coupled to a custom built slit-scan confocal microscope fitted with a custom built imaging spectrometer. The catheter consists of a fiber-optic imaging bundle linked to a miniature objective and focus assembly. The design and performance of the miniature objective and focus assembly are discussed. The 3mm diameter catheter may be used on its own or routed though the instrument channel of a commercial endoscope. The confocal nature of the system provides optical sectioning with 3mum lateral resolution and 30mum axial resolution. The prism based multi-spectral detection assembly is typically configured to collect 30 spectral samples over the visible chromatic range. The spectral sampling rate varies from 4nm/pixel at 490nm to 8nm/pixel at 660nm and the minimum resolvable wavelength difference varies from 7nm to 18nm over the same spectral range. Each of these characteristics are primarily dictated by the dispersive power of the prism. The MCME is designed to examine cellular structures during optical biopsy and to exploit the diagnostic information contained within the spectral domain. The primary applications for the system include diagnosis of disease in the gastro-intestinal tract and female reproductive system. Recent data from the grayscale imaging mode are presented. Preliminary multi-spectral results from phantoms, cell cultures, and excised human tissue are presented to demonstrate the potential of in-vivo multi-spectral imaging.

Remote Sensing for Crop Water Management: From ET Modelling to Services for the End Users

PubMed Central

Calera, Alfonso; Campos, Isidro; Osann, Anna; D’Urso, Guido; Menenti, Massimo

2017-01-01

The experiences gathered during the past 30 years support the operational use of irrigation scheduling based on frequent multi-spectral image data. Currently, the operational use of dense time series of multispectral imagery at high spatial resolution makes monitoring of crop biophysical parameters feasible, capturing crop water use across the growing season, with suitable temporal and spatial resolutions. These achievements, and the availability of accurate forecasting of meteorological data, allow for precise predictions of crop water requirements with unprecedented spatial resolution. This information is greatly appreciated by the end users, i.e., professional farmers or decision-makers, and can be provided in an easy-to-use manner and in near-real-time by using the improvements achieved in web-GIS methodologies (Geographic Information Systems based on web technologies). This paper reviews the most operational and explored methods based on optical remote sensing for the assessment of crop water requirements, identifying strengths and weaknesses and proposing alternatives to advance towards full operational application of this methodology. In addition, we provide a general overview of the tools, which facilitates co-creation and collaboration with stakeholders, paying special attention to these approaches based on web-GIS tools. PMID:28492515

Remote Sensing for Crop Water Management: From ET Modelling to Services for the End Users.

PubMed

Calera, Alfonso; Campos, Isidro; Osann, Anna; D'Urso, Guido; Menenti, Massimo

2017-05-11

The experiences gathered during the past 30 years support the operational use of irrigation scheduling based on frequent multi-spectral image data. Currently, the operational use of dense time series of multispectral imagery at high spatial resolution makes monitoring of crop biophysical parameters feasible, capturing crop water use across the growing season, with suitable temporal and spatial resolutions. These achievements, and the availability of accurate forecasting of meteorological data, allow for precise predictions of crop water requirements with unprecedented spatial resolution. This information is greatly appreciated by the end users, i.e., professional farmers or decision-makers, and can be provided in an easy-to-use manner and in near-real-time by using the improvements achieved in web-GIS methodologies (Geographic Information Systems based on web technologies). This paper reviews the most operational and explored methods based on optical remote sensing for the assessment of crop water requirements, identifying strengths and weaknesses and proposing alternatives to advance towards full operational application of this methodology. In addition, we provide a general overview of the tools, which facilitates co-creation and collaboration with stakeholders, paying special attention to these approaches based on web-GIS tools.

Multipurpose Hyperspectral Imaging System

NASA Technical Reports Server (NTRS)

Mao, Chengye; Smith, David; Lanoue, Mark A.; Poole, Gavin H.; Heitschmidt, Jerry; Martinez, Luis; Windham, William A.; Lawrence, Kurt C.; Park, Bosoon

2005-01-01

A hyperspectral imaging system of high spectral and spatial resolution that incorporates several innovative features has been developed to incorporate a focal plane scanner (U.S. Patent 6,166,373). This feature enables the system to be used for both airborne/spaceborne and laboratory hyperspectral imaging with or without relative movement of the imaging system, and it can be used to scan a target of any size as long as the target can be imaged at the focal plane; for example, automated inspection of food items and identification of single-celled organisms. The spectral resolution of this system is greater than that of prior terrestrial multispectral imaging systems. Moreover, unlike prior high-spectral resolution airborne and spaceborne hyperspectral imaging systems, this system does not rely on relative movement of the target and the imaging system to sweep an imaging line across a scene. This compact system (see figure) consists of a front objective mounted at a translation stage with a motorized actuator, and a line-slit imaging spectrograph mounted within a rotary assembly with a rear adaptor to a charged-coupled-device (CCD) camera. Push-broom scanning is carried out by the motorized actuator which can be controlled either manually by an operator or automatically by a computer to drive the line-slit across an image at a focal plane of the front objective. To reduce the cost, the system has been designed to integrate as many as possible off-the-shelf components including the CCD camera and spectrograph. The system has achieved high spectral and spatial resolutions by using a high-quality CCD camera, spectrograph, and front objective lens. Fixtures for attachment of the system to a microscope (U.S. Patent 6,495,818 B1) make it possible to acquire multispectral images of single cells and other microscopic objects.

High-emulation mask recognition with high-resolution hyperspectral video capture system

NASA Astrophysics Data System (ADS)

Feng, Jiao; Fang, Xiaojing; Li, Shoufeng; Wang, Yongjin

2014-11-01

We present a method for distinguishing human face from high-emulation mask, which is increasingly used by criminals for activities such as stealing card numbers and passwords on ATM. Traditional facial recognition technique is difficult to detect such camouflaged criminals. In this paper, we use the high-resolution hyperspectral video capture system to detect high-emulation mask. A RGB camera is used for traditional facial recognition. A prism and a gray scale camera are used to capture spectral information of the observed face. Experiments show that mask made of silica gel has different spectral reflectance compared with the human skin. As multispectral image offers additional spectral information about physical characteristics, high-emulation mask can be easily recognized.

Multispectral imaging of the ocular fundus using light emitting diode illumination

NASA Astrophysics Data System (ADS)

Everdell, N. L.; Styles, I. B.; Calcagni, A.; Gibson, J.; Hebden, J.; Claridge, E.

2010-09-01

We present an imaging system based on light emitting diode (LED) illumination that produces multispectral optical images of the human ocular fundus. It uses a conventional fundus camera equipped with a high power LED light source and a highly sensitive electron-multiplying charge coupled device camera. It is able to take pictures at a series of wavelengths in rapid succession at short exposure times, thereby eliminating the image shift introduced by natural eye movements (saccades). In contrast with snapshot systems the images retain full spatial resolution. The system is not suitable for applications where the full spectral resolution is required as it uses discrete wavebands for illumination. This is not a problem in retinal imaging where the use of selected wavelengths is common. The modular nature of the light source allows new wavelengths to be introduced easily and at low cost. The use of wavelength-specific LEDs as a source is preferable to white light illumination and subsequent filtering of the remitted light as it minimizes the total light exposure of the subject. The system is controlled via a graphical user interface that enables flexible control of intensity, duration, and sequencing of sources in synchrony with the camera. Our initial experiments indicate that the system can acquire multispectral image sequences of the human retina at exposure times of 0.05 s in the range of 500-620 nm with mean signal to noise ratio of 17 dB (min 11, std 4.5), making it suitable for quantitative analysis with application to the diagnosis and screening of eye diseases such as diabetic retinopathy and age-related macular degeneration.

Multispectral imaging of the ocular fundus using light emitting diode illumination.

PubMed

Everdell, N L; Styles, I B; Calcagni, A; Gibson, J; Hebden, J; Claridge, E

2010-09-01

We present an imaging system based on light emitting diode (LED) illumination that produces multispectral optical images of the human ocular fundus. It uses a conventional fundus camera equipped with a high power LED light source and a highly sensitive electron-multiplying charge coupled device camera. It is able to take pictures at a series of wavelengths in rapid succession at short exposure times, thereby eliminating the image shift introduced by natural eye movements (saccades). In contrast with snapshot systems the images retain full spatial resolution. The system is not suitable for applications where the full spectral resolution is required as it uses discrete wavebands for illumination. This is not a problem in retinal imaging where the use of selected wavelengths is common. The modular nature of the light source allows new wavelengths to be introduced easily and at low cost. The use of wavelength-specific LEDs as a source is preferable to white light illumination and subsequent filtering of the remitted light as it minimizes the total light exposure of the subject. The system is controlled via a graphical user interface that enables flexible control of intensity, duration, and sequencing of sources in synchrony with the camera. Our initial experiments indicate that the system can acquire multispectral image sequences of the human retina at exposure times of 0.05 s in the range of 500-620 nm with mean signal to noise ratio of 17 dB (min 11, std 4.5), making it suitable for quantitative analysis with application to the diagnosis and screening of eye diseases such as diabetic retinopathy and age-related macular degeneration.

Satellite image fusion based on principal component analysis and high-pass filtering.

PubMed

Metwalli, Mohamed R; Nasr, Ayman H; Allah, Osama S Farag; El-Rabaie, S; Abd El-Samie, Fathi E

2010-06-01

This paper presents an integrated method for the fusion of satellite images. Several commercial earth observation satellites carry dual-resolution sensors, which provide high spatial resolution or simply high-resolution (HR) panchromatic (pan) images and low-resolution (LR) multi-spectral (MS) images. Image fusion methods are therefore required to integrate a high-spectral-resolution MS image with a high-spatial-resolution pan image to produce a pan-sharpened image with high spectral and spatial resolutions. Some image fusion methods such as the intensity, hue, and saturation (IHS) method, the principal component analysis (PCA) method, and the Brovey transform (BT) method provide HR MS images, but with low spectral quality. Another family of image fusion methods, such as the high-pass-filtering (HPF) method, operates on the basis of the injection of high frequency components from the HR pan image into the MS image. This family of methods provides less spectral distortion. In this paper, we propose the integration of the PCA method and the HPF method to provide a pan-sharpened MS image with superior spatial resolution and less spectral distortion. The experimental results show that the proposed fusion method retains the spectral characteristics of the MS image and, at the same time, improves the spatial resolution of the pan-sharpened image.

MONSTIR II: A 32-channel, multispectral, time-resolved optical tomography system for neonatal brain imaging

NASA Astrophysics Data System (ADS)

Cooper, Robert J.; Magee, Elliott; Everdell, Nick; Magazov, Salavat; Varela, Marta; Airantzis, Dimitrios; Gibson, Adam P.; Hebden, Jeremy C.

2014-05-01

We detail the design, construction and performance of the second generation UCL time-resolved optical tomography system, known as MONSTIR II. Intended primarily for the study of the newborn brain, the system employs 32 source fibres that sequentially transmit picosecond pulses of light at any four wavelengths between 650 and 900 nm. The 32 detector channels each contain an independent photo-multiplier tube and temporally correlated photon-counting electronics that allow the photon transit time between each source and each detector position to be measured with high temporal resolution. The system's response time, temporal stability, cross-talk, and spectral characteristics are reported. The efficacy of MONSTIR II is demonstrated by performing multi-spectral imaging of a simple phantom.

Detection of particulate air pollution plumes from major point sources using ERTS-1 imagery

NASA Technical Reports Server (NTRS)

Lyons, W. A.; Pease, S. R.

1973-01-01

The Earth Resources Technology Satellite (ERTS-1) launched by NASA in July 1972 has been providing thousands of high resolution multispectral images of interest to geographers, cartographers, hydrologists, and agroculturists. It has been found possible to detect the long-range (over 50 km) transport of suspected particulate plumes from the Chicago-Gary steel mill complex over Lake Michigan. The observed plumes are readily related to known steel mills, a cement plant, refineries, and fossil-fuel power plants. This has important ramifications when discussing the interregional transport of atmospheric pollutants. Analysis reveals that the Multispectral Scanner Band 5 (0.6 to 0.7 micrometer) provides the best overall contrast between the smoke and the underlying water surface.

Multiplexing and de-multiplexing with scattering media for large field of view and multispectral imaging

NASA Astrophysics Data System (ADS)

Sahoo, Sujit Kumar; Tang, Dongliang; Dang, Cuong

2018-02-01

Large field of view multispectral imaging through scattering medium is a fundamental quest in optics community. It has gained special attention from researchers in recent years for its wide range of potential applications. However, the main bottlenecks of the current imaging systems are the requirements on specific illumination, poor image quality and limited field of view. In this work, we demonstrated a single-shot high-resolution colour-imaging through scattering media using a monochromatic camera. This novel imaging technique is enabled by the spatial, spectral decorrelation property and the optical memory effect of the scattering media. Moreover the use of deconvolution image processing further annihilate above-mentioned drawbacks arise due iterative refocusing, scanning or phase retrieval procedures.

Core segment 15008 - Regolith stratigraphy at Apennine Front Station 2 using multispectral imaging

NASA Technical Reports Server (NTRS)

Pieters, C. M.; Meloy, A.; Hawke, B. R.; Nagle, J. S.

1982-01-01

High precision multispectral images for Apennine Front core segment 15008 are presented. These data have a spatial resolution less than approximately 0.5 mm and are analyzed for their compositional information using image analysis techniques. The stratigraphy of the regolith sampled by 15008 is documented here as three distinct zones, the most prominent of which is a feldspathic fragment-rich zone with a chaotic fabric that occurs between 10 and 18 cm depth. It is suggested that this material is the primary rim crest deposit of the local 10 m crater. Above this zone the stratigraphy is more horizontal in nature. Below this zone the soil is observed to be relatively homogeneous with no distinctive structure to 23 cm depth.

Landsat-4 MSS and Thematic Mapper data quality and information content analysis

NASA Technical Reports Server (NTRS)

Anuta, P. E.; Bartolucci, L. A.; Dean, M. E.; Lozano, D. F.; Malaret, E.; Mcgillem, C. D.; Valdes, J. A.; Valenzuela, C. R.

1984-01-01

Landsat-4 Thematic Mapper and Multispectral Scanner data were analyzed to obtain information on data quality and information content. Geometric evaluations were performed to test band-to-band registration accuracy. Thematic Mapper overall system resolution was evaluated using scene objects which demonstrated sharp high contrast edge responses. Radiometric evaluation included detector relative calibration, effects of resampling, and coherent noise effects. Information content evaluation was carried out using clustering, principal components, transformed divergence separability measure, and numerous supervised classifiers on data from Iowa and Illinois. A detailed spectral class analysis (multispectral classification) was carried out on data from the Des Moines, IA area to compare the information content of the MSS and TM for a large number of scene classes.

Scaling Sap Flow Results Over Wide Areas Using High-Resolution Aerial Multispectral Digital Imaging, Leaf Area Index (LAI) and MODIS Satellite Imagery in Saltcedar Stands on the Lower Colorado River

NASA Astrophysics Data System (ADS)

Murray, R.; Neale, C.; Nagler, P. L.; Glenn, E. P.

2008-12-01

Heat-balance sap flow sensors provide direct estimates of water movement through plant stems and can be used to accurately measure leaf-level transpiration (EL) and stomatal conductance (GS) over time scales ranging from 20-minutes to a month or longer in natural stands of plants. However, their use is limited to relatively small branches on shrubs or trees, as the gauged stem section needs to be uniformly heated by the heating coil to produce valid measurements. This presents a scaling problem in applying the results to whole plants, stands of plants, and larger landscape areas. We used high-resolution aerial multispectral digital imaging with green, red and NIR bands as a bridge between ground measurements of EL and GS, and MODIS satellite imagery of a flood plain on the Lower Colorado River dominated by saltcedar (Tamarix ramosissima). Saltcedar is considered to be a high-water-use plant, and saltcedar removal programs have been proposed to salvage water. Hence, knowledge of actual saltcedar ET rates is needed on western U.S. rivers. Scaling EL and GS to large landscape units requires knowledge of leaf area index (LAI) over large areas. We used a LAI model developed for riparian habitats on Bosque del Apache, New Mexico, to estimate LAI at our study site on the Colorado River. We compared the model estimates to ground measurements of LAI, determined with a Li-Cor LAI-2000 Plant Canopy Analyzer calibrated by leaf harvesting to determine Specific Leaf Area (SLA) (m2 leaf area per g dry weight leaves) of the different species on the floodplain. LAI could be adequately predicted from NDVI from aerial multispectral imagery and could be cross-calibrated with MODIS NDVI and EVI. Hence, we were able to project point measurements of sap flow and LAI over multiple years and over large areas of floodplain using aerial multispectral imagery as a bridge between ground and satellite data. The methods are applicable to riparian corridors throughout the western U.S.

Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Katawas mineral district in Afghanistan: Chapter N in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

USGS Publications Warehouse

Davis, Philip A.; Cagney, Laura E.

2013-01-01

The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Katawas mineral district, which has gold deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420-500 nanometer, nm), green (520-600 nm), red (610-690 nm), and near-infrared (760-890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520-770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©AXA, 2008), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such, the DS products match JAXA criteria for value added products, which are not copyrighted, according to the ALOS end-user license agreement. The selection criteria for the satellite imagery used in our mosaics were images having (1) the highest solar-elevation angles (near summer solstice) and (2) the least cloud, cloud-shadow, and snow cover. The multispectral and panchromatic data were orthorectified with ALOS satellite ephemeris data, a process which is not as accurate as orthorectification using digital elevation models (DEMs); however, the ALOS processing center did not have a precise DEM. As a result, the multispectral and panchromatic image pairs were generally not well registered to the surface and not coregistered well enough to perform resolution enhancement on the multispectral data. Therefore, it was necessary to (1) register the 10-m AVNIR multispectral imagery to a well-controlled Landsat image base, (2) mosaic the individual multispectral images into a single image of the entire area of interest, (3) register each panchromatic image to the registered multispectral image base, and (4) mosaic the individual panchromatic images into a single image of the entire area of interest. The two image-registration steps were facilitated using an automated control-point algorithm developed by the USGS that allows image coregistration to within one picture element. Before rectification, the multispectral and panchromatic images were converted to radiance values and then to relative-reflectance values using the methods described in Davis (2006). Mosaicking the multispectral or panchromatic images started with the image with the highest sun-elevation angle and the least atmospheric scattering, which was treated as the standard image. The band-reflectance values of all other multispectral or panchromatic images within the area were sequentially adjusted to that of the standard image by determining band-reflectance correspondence between overlapping images using linear least-squares analysis. The resolution of the multispectral image mosaic was then increased to that of the panchromatic image mosaic using the SPARKLE logic, which is described in Davis (2006). Each of the four-band images within the resolution-enhanced image mosaic was individually subjected to a local-area histogram stretch algorithm (described in Davis, 2007), which stretches each band's picture element based on the digital values of all picture elements within a 315-m radius. The final databases, which are provided in this DS, are three-band, color-composite images of the local-area-enhanced, natural-color data (the blue, green, and red wavelength bands) and color-infrared data (the green, red, and near-infrared wavelength bands). All image data were initially projected and maintained in Universal Transverse Mercator (UTM) map projection using the target area's local zone (42 for Katawas) and the WGS84 datum. The final image mosaics are provided as embedded geotiff images, which can be read and used by most geographic information system (GIS) and image-processing software. The tiff world files (tfw) are provided, even though they are generally not needed for most software to read an embedded geotiff image. Within the Katawas study area, one subarea was designated for detailed field investigation (that is, the Gold subarea); this subarea was extracted from the area's image mosaic and is provided as a separate embedded geotiff image.

Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Takhar mineral district in Afghanistan: Chapter Q in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

USGS Publications Warehouse

Davis, Philip A.; Cagney, Laura E.

2013-01-01

The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Takhar mineral district, which has industrial evaporite deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA, 2008), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such, the DS products match JAXA criteria for value added products, which are not copyrighted, according to the ALOS end-user license agreement. The selection criteria for the satellite imagery used in our mosaics were images having (1) the highest solar-elevation angles (near summer solstice) and (2) the least cloud, cloud-shadow, and snow cover. The multispectral and panchromatic data were orthorectified with ALOS satellite ephemeris data, a process which is not as accurate as orthorectification using digital elevation models (DEMs); however, the ALOS processing center did not have a precise DEM. As a result, the multispectral and panchromatic image pairs were generally not well registered to the surface and not coregistered well enough to perform resolution enhancement on the multispectral data. Therefore, it was necessary to (1) register the 10-m AVNIR multispectral imagery to a well-controlled Landsat image base, (2) mosaic the individual multispectral images into a single image of the entire area of interest, (3) register each panchromatic image to the registered multispectral image base, and (4) mosaic the individual panchromatic images into a single image of the entire area of interest. The two image-registration steps were facilitated using an automated control-point algorithm developed by the USGS that allows image coregistration to within one picture element. Before rectification, the multispectral and panchromatic images were converted to radiance values and then to relative-reflectance values using the methods described in Davis (2006). Mosaicking the multispectral or panchromatic images started with the image with the highest sun-elevation angle and the least atmospheric scattering, which was treated as the standard image. The band-reflectance values of all other multispectral or panchromatic images within the area were sequentially adjusted to that of the standard image by determining band-reflectance correspondence between overlapping images using linear least-squares analysis. The resolution of the multispectral image mosaic was then increased to that of the panchromatic image mosaic using the SPARKLE logic, which is described in Davis (2006). Each of the four-band images within the resolution-enhanced image mosaic was individually subjected to a local-area histogram stretch algorithm (described in Davis, 2007), which stretches each band’s picture element based on the digital values of all picture elements within a 315-m radius. The final databases, which are provided in this DS, are three-band, color-composite images of the local-area-enhanced, natural-color data (the blue, green, and red wavelength bands) and color-infrared data (the green, red, and near-infrared wavelength bands). All image data were initially projected and maintained in Universal Transverse Mercator (UTM) map projection using the target area’s local zone (42 for Takhar) and the WGS84 datum. The final image mosaics for the Takhar area are provided as embedded geotiff images, which can be read and used by most geographic information system (GIS) and image-processing software. The tiff world files (tfw) are provided, even though they are generally not needed for most software to read an embedded geotiff image.

Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the North Takhar mineral district in Afghanistan: Chapter D in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

USGS Publications Warehouse

Davis, Philip A.; Cagney, Laura E.

2012-01-01

The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the North Takhar mineral district, which has placer gold deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA,2006,2008), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such, the DS products match JAXA criteria for value added products, which are not copyrighted, according to the ALOS end-user license agreement. The selection criteria for the satellite imagery used in our mosaics were images having (1) the highest solar-elevation angles (near summer solstice) and (2) the least cloud, cloud-shadow, and snow cover. The multispectral and panchromatic data were orthorectified with ALOS satellite ephemeris data, a process which is not as accurate as orthorectification using digital elevation models (DEMs); however, the ALOS processing center did not have a precise DEM. As a result, the multispectral and panchromatic image pairs were generally not well registered to the surface and not coregistered well enough to perform resolution enhancement on the multispectral data. Therefore, it was necessary to (1) register the 10-m AVNIR multispectral imagery to a well-controlled Landsat image base, (2) mosaic the individual multispectral images into a single image of the entire area of interest, (3) register each panchromatic image to the registered multispectral image base, and (4) mosaic the individual panchromatic images into a single image of the entire area of interest. The two image-registration steps were facilitated using an automated control-point algorithm developed by the USGS that allows image coregistration to within one picture element. Before rectification, the multispectral and panchromatic images were converted to radiance values and then to relative-reflectance values using the methods described in Davis (2006). Mosaicking the multispectral or panchromatic images started with the image with the highest sun-elevation angle and the least atmospheric scattering, which was treated as the standard image. The band-reflectance values of all other multispectral or panchromatic images within the area were sequentially adjusted to that of the standard image by determining band-reflectance correspondence between overlapping images using linear least-squares analysis. The resolution of the multispectral image mosaic was then increased to that of the panchromatic image mosaic using the SPARKLE logic, which is described in Davis (2006). Each of the four-band images within the resolution-enhanced image mosaic was individually subjected to a local-area histogram stretch algorithm (described in Davis, 2007), which stretches each band’s picture element based on the digital values of all picture elements within a 315-m radius. The final databases, which are provided in this DS, are three-band, color-composite images of the local-area-enhanced, natural-color data (the blue, green, and red wavelength bands) and color-infrared data (the green, red, and near-infrared wavelength bands). All image data were initially projected and maintained in Universal Transverse Mercator (UTM) map projection using the target area’s local zone (42 for North Takhar) and the WGS84 datum. The final image mosaics were subdivided into nine overlapping tiles or quadrants because of the large size of the target area. The nine image tiles (or quadrants) for the North Takhar area are provided as embedded geotiff images, which can be read and used by most geographic information system (GIS) and image-processing software. The tiff world files (tfw) are provided, even though they are generally not needed for most software to read an embedded geotiff image.

Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Baghlan mineral district in Afghanistan: Chapter P in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

USGS Publications Warehouse

Davis, Philip A.; Cagney, Laura E.

2013-01-01

The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Baghlan mineral district, which has industrial clay and gypsum deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA, 2006, 2007, 2008), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such, the DS products match JAXA criteria for value added products, which are not copyrighted, according to the ALOS end-user license agreement. The selection criteria for the satellite imagery used in our mosaics were images having (1) the highest solar-elevation angles (near summer solstice) and (2) the least cloud, cloud-shadow, and snow cover. The multispectral and panchromatic data were orthorectified with ALOS satellite ephemeris data, a process which is not as accurate as orthorectification using digital elevation models (DEMs); however, the ALOS processing center did not have a precise DEM. As a result, the multispectral and panchromatic image pairs were generally not well registered to the surface and not coregistered well enough to perform resolution enhancement on the multispectral data. Therefore, it was necessary to (1) register the 10-m AVNIR multispectral imagery to a well-controlled Landsat image base, (2) mosaic the individual multispectral images into a single image of the entire area of interest, (3) register each panchromatic image to the registered multispectral image base, and (4) mosaic the individual panchromatic images into a single image of the entire area of interest. The two image-registration steps were facilitated using an automated control-point algorithm developed by the USGS that allows image coregistration to within one picture element. Before rectification, the multispectral and panchromatic images were converted to radiance values and then to relative-reflectance values using the methods described in Davis (2006). Mosaicking the multispectral or panchromatic images started with the image with the highest sun-elevation angle and the least atmospheric scattering, which was treated as the standard image. The band-reflectance values of all other multispectral or panchromatic images within the area were sequentially adjusted to that of the standard image by determining band-reflectance correspondence between overlapping images using linear least-squares analysis. The resolution of the multispectral image mosaic was then increased to that of the panchromatic image mosaic using the SPARKLE logic, which is described in Davis (2006). Each of the four-band images within the resolution-enhanced image mosaic was individually subjected to a local-area histogram stretch algorithm (described in Davis, 2007), which stretches each band’s picture element based on the digital values of all picture elements within a 315-m radius. The final databases, which are provided in this DS, are three-band, color-composite images of the local-area-enhanced, natural-color data (the blue, green, and red wavelength bands) and color-infrared data (the green, red, and near-infrared wavelength bands). All image data were initially projected and maintained in Universal Transverse Mercator (UTM) map projection using the target area’s local zone (42 for Baghlan) and the WGS84 datum. The final image mosaics were subdivided into two overlapping tiles or quadrants because of the large size of the target area. The two image tiles (or quadrants) for the Baghlan area are provided as embedded geotiff images, which can be read and used by most geographic information system (GIS) and image-processing software. The tiff world files (tfw) are provided, even though they are generally not needed for most software to read an embedded geotiff image.

Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Uruzgan mineral district in Afghanistan: Chapter V in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

USGS Publications Warehouse

Davis, Philip A.

2013-01-01

The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Uruzgan mineral district, which has tin and tungsten deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA, 2008, 2009), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such, the DS products match JAXA criteria for value added products, which are not copyrighted, according to the ALOS end-user license agreement. The selection criteria for the satellite imagery used in our mosaics were images having (1) the highest solar-elevation angles (near summer solstice) and (2) the least cloud, cloud-shadow, and snow cover. The multispectral and panchromatic data were orthorectified with ALOS satellite ephemeris data, a process which is not as accurate as orthorectification using digital elevation models (DEMs); however, the ALOS processing center did not have a precise DEM. As a result, the multispectral and panchromatic image pairs were generally not well registered to the surface and not coregistered well enough to perform resolution enhancement on the multispectral data. Therefore, it was necessary to (1) register the 10-m AVNIR multispectral imagery to a well-controlled Landsat image base, (2) mosaic the individual multispectral images into a single image of the entire area of interest, (3) register each panchromatic image to the registered multispectral image base, and (4) mosaic the individual panchromatic images into a single image of the entire area of interest. The two image-registration steps were facilitated using an automated control-point algorithm developed by the USGS that allows image coregistration to within one picture element. Before rectification, the multispectral and panchromatic images were converted to radiance values and then to relative-reflectance values using the methods described in Davis (2006). Mosaicking the multispectral or panchromatic images started with the image with the highest sun-elevation angle and the least atmospheric scattering, which was treated as the standard image. The band-reflectance values of all other multispectral or panchromatic images within the area were sequentially adjusted to that of the standard image by determining band-reflectance correspondence between overlapping images using linear least-squares analysis. The resolution of the multispectral image mosaic was then increased to that of the panchromatic image mosaic using the SPARKLE logic, which is described in Davis (2006). Each of the four-band images within the resolution-enhanced image mosaic was individually subjected to a local-area histogram stretch algorithm (described in Davis, 2007), which stretches each band’s picture element based on the digital values of all picture elements within a 500-m radius. The final databases, which are provided in this DS, are three-band, color-composite images of the local-area-enhanced, natural-color data (the blue, green, and red wavelength bands) and color-infrared data (the green, red, and near-infrared wavelength bands). All image data were initially projected and maintained in Universal Transverse Mercator (UTM) map projection using the target area’s local zone (42 for Uruzgan) and the WGS84 datum. The final image mosaics were subdivided into eight overlapping tiles or quadrants because of the large size of the target area. The eight image tiles (or quadrants) for the Uruzgan area are provided as embedded geotiff images, which can be read and used by most geographic information system (GIS) and image-processing software. The tiff world files (tfw) are provided, even though they are generally not needed for most software to read an embedded geotiff image.

Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Parwan mineral district in Afghanistan: Chapter CC in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

USGS Publications Warehouse

Davis, Philip A.

2013-01-01

The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Parwan mineral district, which has gold and copper deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA,2006, 2007), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such, the DS products match JAXA criteria for value added products, which are not copyrighted, according to the ALOS end-user license agreement. elevation angles (near summer solstice) and (2) the least cloud, cloud-shadow, and snow cover. The multispectral and panchromatic data were orthorectified with ALOS satellite ephemeris data, a process which is not as accurate as orthorectification using digital elevation models (DEMs); however, the ALOS processing center did not have a precise DEM. As a result, the multispectral and panchromatic image pairs were generally not well registered to the surface and not coregistered well enough to perform resolution enhancement on the multispectral data. Therefore, it was necessary to (1) register the 10-m AVNIR multispectral imagery to a well-controlled Landsat image base, (2) mosaic the individual multispectral images into a single image of the entire area of interest, (3) register each panchromatic image to the registered multispectral image base, and (4) mosaic the individual panchromatic images into a single image of the entire area of interest. The two image-registration steps were facilitated using an automated control-point algorithm developed by the USGS that allows image coregistration to within one picture element. Before rectification, the multispectral and panchromatic images were converted to radiance values and then to relative-reflectance values using the methods described in Davis (2006). Mosaicking the multispectral or panchromatic images started with the image with the highest sun-elevation angle and the least atmospheric scattering, which was treated as the standard image. The band-reflectance values of all other multispectral or panchromatic images within the area were sequentially adjusted to that of the standard image by determining band-reflectance correspondence between overlapping images using linear least-squares analysis. The resolution of the multispectral image mosaic was then increased to that of the panchromatic image mosaic using the SPARKLE logic, which is described in Davis (2006). Each of the four-band images within the resolution-enhanced image mosaic was individually subjected to a local-area histogram stretch algorithm (described in Davis, 2007), which stretches each band’s picture element based on the digital values of all picture elements within a 500-m radius. The final databases, which are provided in this DS, are three-band, color-composite images of the local-area-enhanced, natural-color data (the blue, green, and red wavelength bands) and color-infrared data (the green, red, and near-infrared wavelength bands). All image data were initially projected and maintained in Universal Transverse Mercator (UTM) map projection using the target area’s local zone (42 for Parwan) and the WGS84 datum. The final image mosaics were subdivided into two overlapping tiles or quadrants because of the large size of the target area. The two image tiles (or quadrants) for the North Bamyan area are provided as embedded geotiff images, which can be read and used by most geographic information system (GIS) and image-processing software. The tiff world files (tfw) are provided, even though they are generally not needed for most software to read an embedded geotiff image.

Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Ghazni2 mineral district in Afghanistan: Chapter EE in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

USGS Publications Warehouse

Davis, Philip A.

2014-01-01

The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Ghazni2 mineral district, which has spectral reflectance anomalies indicative of gold, mercury, and sulfur deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420-500 nanometer, nm), green (520-600 nm), red (610-690 nm), and near-infrared (760-890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520-770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency ((c)JAXA, 2008, 2009), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such, the DS products match JAXA criteria for value added products, which are not copyrighted, according to the ALOS end-user license agreement. The selection criteria for the satellite imagery used in our mosaics were images having (1) the highest solar-elevation angles (near summer solstice) and (2) the least cloud, cloud-shadow, and snow cover. The multispectral and panchromatic data were orthorectified with ALOS satellite ephemeris data, a process which is not as accurate as orthorectification using digital elevation models (DEMs); however, the ALOS processing center did not have a precise DEM. As a result, the multispectral and panchromatic image pairs were generally not well registered to the surface and not coregistered well enough to perform resolution enhancement on the multispectral data. Therefore, it was necessary to (1) register the 10-m AVNIR multispectral imagery to a well-controlled Landsat image base, (2) mosaic the individual multispectral images into a single image of the entire area of interest, (3) register each panchromatic image to the registered multispectral image base, and (4) mosaic the individual panchromatic images into a single image of the entire area of interest. The two image-registration steps were facilitated using an automated control-point algorithm developed by the USGS that allows image coregistration to within one picture element. Before rectification, the multispectral and panchromatic images were converted to radiance values and then to relative-reflectance values using the methods described in Davis (2006). Mosaicking the multispectral or panchromatic images started with the image with the highest sun-elevation angle and the least atmospheric scattering, which was treated as the standard image. The band-reflectance values of all other multispectral or panchromatic images within the area were sequentially adjusted to that of the standard image by determining band-reflectance correspondence between overlapping images using linear least-squares analysis. The resolution of the multispectral image mosaic was then increased to that of the panchromatic image mosaic using the SPARKLE logic, which is described in Davis (2006). Each of the four-band images within the resolution-enhanced image mosaic was individually subjected to a local-area histogram stretch algorithm (described in Davis, 2007), which stretches each band's picture element based on the digital values of all picture elements within a 500-m radius. The final databases, which are provided in this DS, are three-band, color-composite images of the local-area-enhanced, natural-color data (the blue, green, and red wavelength bands) and color-infrared data (the green, red, and near-infrared wavelength bands). All image data were initially projected and maintained in Universal Transverse Mercator (UTM) map projection using the target area's local zone (42 for Ghazni2) and the WGS84 datum. The images for the Ghazni2 area are provided as embedded geotiff images, which can be read and used by most geographic information system (GIS) and image-processing software. The tiff world files (tfw) are provided, even though they are generally not needed for most software to read an embedded geotiff image.

Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Ghazni1 mineral district in Afghanistan: Chapter DD in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

USGS Publications Warehouse

Davis, Philip A.

2014-01-01

The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Ghazni1 mineral district, which has spectral reflectance anomalies indicative of clay, aluminum, gold, silver, mercury, and sulfur deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420-500 nanometer, nm), green (520-600 nm), red (610-690 nm), and near-infrared (760-890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520-770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency ((c)JAXA, 2008, 2009), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such, the DS products match JAXA criteria for value added products, which are not copyrighted, according to the ALOS end-user license agreement. The selection criteria for the satellite imagery used in our mosaics were images having (1) the highest solar-elevation angles (near summer solstice) and (2) the least cloud, cloud-shadow, and snow cover. The multispectral and panchromatic data were orthorectified with ALOS satellite ephemeris data, a process which is not as accurate as orthorectification using digital elevation models (DEMs); however, the ALOS processing center did not have a precise DEM. As a result, the multispectral and panchromatic image pairs were generally not well registered to the surface and not coregistered well enough to perform resolution enhancement on the multispectral data. Therefore, it was necessary to (1) register the 10-m AVNIR multispectral imagery to a well-controlled Landsat image base, (2) mosaic the individual multispectral images into a single image of the entire area of interest, (3) register each panchromatic image to the registered multispectral image base, and (4) mosaic the individual panchromatic images into a single image of the entire area of interest. The two image-registration steps were facilitated using an automated control-point algorithm developed by the USGS that allows image coregistration to within one picture element. Before rectification, the multispectral and panchromatic images were converted to radiance values and then to relative-reflectance values using the methods described in Davis (2006). Mosaicking the multispectral or panchromatic images started with the image with the highest sun-elevation angle and the least atmospheric scattering, which was treated as the standard image. The band-reflectance values of all other multispectral or panchromatic images within the area were sequentially adjusted to that of the standard image by determining band-reflectance correspondence between overlapping images using linear least-squares analysis. The resolution of the multispectral image mosaic was then increased to that of the panchromatic image mosaic using the SPARKLE logic, which is described in Davis (2006). Each of the four-band images within the resolution-enhanced image mosaic was individually subjected to a local-area histogram stretch algorithm (described in Davis, 2007), which stretches each band's picture element based on the digital values of all picture elements within a 500-m radius. The final databases, which are provided in this DS, are three-band, color-composite images of the local-area-enhanced, natural-color data (the blue, green, and red wavelength bands) and color-infrared data (the green, red, and near-infrared wavelength bands). All image data were initially projected and maintained in Universal Transverse Mercator (UTM) map projection using the target area's local zone (42 for Ghazni1) and the WGS84 datum. The images for the Ghazni1 area are provided as embedded geotiff images, which can be read and used by most geographic information system (GIS) and image-processing software. The tiff world files (tfw) are provided, even though they are generally not needed for most software to read an embedded geotiff image.

Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Balkhab mineral district in Afghanistan: Chapter B in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

USGS Publications Warehouse

Davis, Philip A.; Cagney, Laura E.

2012-01-01

The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Balkhab mineral district, which has copper deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420-500 nanometer, nm), green (520-600 nm), red (610-690 nm), and near-infrared (760-890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520-770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA,2007,2008), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such, the DS products match JAXA criteria for value added products, which are not copyrighted, according to the ALOS end-user license agreement. The selection criteria for the satellite imagery used in our mosaics were images having (1) the highest solar-elevation angles (near summer solstice) and (2) the least cloud, cloud-shadow, and snow cover. The multispectral and panchromatic data were orthorectified with ALOS satellite ephemeris data, a process which is not as accurate as orthorectification using digital elevation models (DEMs); however, the ALOS processing center did not have a precise DEM. As a result, the multispectral and panchromatic image pairs were generally not well registered to the surface and not coregistered well enough to perform resolution enhancement on the multispectral data. Therefore, it was necessary to (1) register the 10-m AVNIR multispectral imagery to a well-controlled Landsat image base, (2) mosaic the individual multispectral images into a single image of the entire area of interest, (3) register each panchromatic image to the registered multispectral image base, and (4) mosaic the individual panchromatic images into a single image of the entire area of interest. The two image-registration steps were facilitated using an automated control-point algorithm developed by the USGS that allows image coregistration to within one picture element. Before rectification, the multispectral and panchromatic images were converted to radiance values and then to relative-reflectance values using the methods described in Davis (2006). Mosaicking the multispectral or panchromatic images started with the image with the highest sun-elevation angle and the least atmospheric scattering, which was treated as the standard image. The band-reflectance values of all other multispectral or panchromatic images within the area were sequentially adjusted to that of the standard image by determining band-reflectance correspondence between overlapping images using linear least-squares analysis. The resolution of the multispectral image mosaic was then increased to that of the panchromatic image mosaic using the SPARKLE logic, which is described in Davis (2006). Each of the four-band images within the resolution-enhanced image mosaic was individually subjected to a local-area histogram stretch algorithm (described in Davis, 2007), which stretches each band's picture element based on the digital values of all picture elements within a 315-m radius. The final databases, which are provided in this DS, are three-band, color-composite images of the local-area-enhanced, natural-color data (the blue, green, and red wavelength bands) and color-infrared data (the green, red, and near-infrared wavelength bands). All image data were initially projected and maintained in Universal Transverse Mercator (UTM) map projection using the target area's local zone (42 for Balkhab) and the WGS84 datum. The final image mosaics were subdivided into two overlapping tiles or quadrants because of the large size of the target area. The two image tiles (or quadrants) for the Balkhab area are provided as embedded geotiff images, which can be read and used by most geographic information system (GIS) and image-processing software. The tiff world files (tfw) are provided, even though they are generally not needed for most software to read an embedded geotiff image. Within the Balkhab study area, one subarea was designated for detailed field investigations (that is, the Balkhab Prospect subarea); this subarea was extracted from the area's image mosaic and is provided as separate embedded geotiff images.

Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the South Helmand mineral district in Afghanistan: Chapter O in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

USGS Publications Warehouse

Davis, Philip A.; Cagney, Laura E.

2013-01-01

The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the South Helmand mineral district, which has travertine deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA, 2008, 2010), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such, the DS products match JAXA criteria for value added products, which are not copyrighted, according to the ALOS end-user license agreement. The selection criteria for the satellite imagery used in our mosaics were images having (1) the highest solar-elevation angles (near summer solstice) and (2) the least cloud, cloud-shadow, and snow cover. The multispectral and panchromatic data were orthorectified with ALOS satellite ephemeris data, a process which is not as accurate as orthorectification using digital elevation models (DEMs); however, the ALOS processing center did not have a precise DEM. As a result, the multispectral and panchromatic image pairs were generally not well registered to the surface and not coregistered well enough to perform resolution enhancement on the multispectral data. Therefore, it was necessary to (1) register the 10-m AVNIR multispectral imagery to a well-controlled Landsat image base, (2) mosaic the individual multispectral images into a single image of the entire area of interest, (3) register each panchromatic image to the registered multispectral image base, and (4) mosaic the individual panchromatic images into a single image of the entire area of interest. The two image-registration steps were facilitated using an automated control-point algorithm developed by the USGS that allows image coregistration to within one picture element. Before rectification, the multispectral and panchromatic images were converted to radiance values and then to relative-reflectance values using the methods described in Davis (2006). Mosaicking the multispectral or panchromatic images started with the image with the highest sun-elevation angle and the least atmospheric scattering, which was treated as the standard image. The band-reflectance values of all other multispectral or panchromatic images within the area were sequentially adjusted to that of the standard image by determining band-reflectance correspondence between overlapping images using linear least-squares analysis. The resolution of the multispectral image mosaic was then increased to that of the panchromatic image mosaic using the SPARKLE logic, which is described in Davis (2006). Each of the four-band images within the resolution-enhanced image mosaic was individually subjected to a local-area histogram stretch algorithm (described in Davis, 2007), which stretches each band’s picture element based on the digital values of all picture elements within a 500-m radius. The final databases, which are provided in this DS, are three-band, color-composite images of the local-area-enhanced, natural-color data (the blue, green, and red wavelength bands) and color-infrared data (the green, red, and near-infrared wavelength bands). All image data were initially projected and maintained in Universal Transverse Mercator (UTM) map projection using the target area’s local zone (41 for South Helmand) and the WGS84 datum. The final image mosaics were subdivided into eight overlapping tiles or quadrants because of the large size of the target area. The eight image tiles (or quadrants) for the South Helmand area are provided as embedded geotiff images, which can be read and used by most geographic information system (GIS) and image-processing software. The tiff world files (tfw) are provided, even though they are generally not needed for most software to read an embedded geotiff image.

Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Bakhud mineral district in Afghanistan: Chapter U in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

USGS Publications Warehouse

Davis, Philip A.; Cagney, Laura E.; Davis, Philip A.

2013-01-01

The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Bakhud mineral district, which has industrial fluorite deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA,2006,2007, 2008), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such, the DS products match JAXA criteria for value added products, which are not copyrighted, according to the ALOS end-user license agreement. The selection criteria for the satellite imagery used in our mosaics were images having (1) the highest solar-elevation angles (near summer solstice) and (2) the least cloud, cloud-shadow, and snow cover. The multispectral and panchromatic data were orthorectified with ALOS satellite ephemeris data, a process which is not as accurate as orthorectification using digital elevation models (DEMs); however, the ALOS processing center did not have a precise DEM. As a result, the multispectral and panchromatic image pairs were generally not well registered to the surface and not coregistered well enough to perform resolution enhancement on the multispectral data. Therefore, it was necessary to (1) register the 10-m AVNIR multispectral imagery to a well-controlled Landsat image base, (2) mosaic the individual multispectral images into a single image of the entire area of interest, (3) register each panchromatic image to the registered multispectral image base, and (4) mosaic the individual panchromatic images into a single image of the entire area of interest. The two image-registration steps were facilitated using an automated control-point algorithm developed by the USGS that allows image coregistration to within one picture element. Before rectification, the multispectral and panchromatic images were converted to radiance values and then to relative-reflectance values using the methods described in Davis (2006). Mosaicking the multispectral or panchromatic images started with the image with the highest sun-elevation angle and the least atmospheric scattering, which was treated as the standard image. The band-reflectance values of all other multispectral or panchromatic images within the area were sequentially adjusted to that of the standard image by determining band-reflectance correspondence between overlapping images using linear least-squares analysis. The resolution of the multispectral image mosaic was then increased to that of the panchromatic image mosaic using the SPARKLE logic, which is described in Davis (2006). Each of the four-band images within the resolution-enhanced image mosaic was individually subjected to a local-area histogram stretch algorithm (described in Davis, 2007), which stretches each band’s picture element based on the digital values of all picture elements within a 315-m radius. The final databases, which are provided in this DS, are three-band, color-composite images of the local-area-enhanced, natural-color data (the blue, green, and red wavelength bands) and color-infrared data (the green, red, and near-infrared wavelength bands). All image data were initially projected and maintained in Universal Transverse Mercator (UTM) map projection using the target area’s local zone (41 for Bakhud) and the WGS84 datum. The final image mosaics were subdivided into nine overlapping tiles or quadrants because of the large size of the target area. The nine image tiles (or quadrants) for the Bakhud area are provided as embedded geotiff images, which can be read and used by most geographic information system (GIS) and image-processing software. The tiff world files (tfw) are provided, even though they are generally not needed for most software to read an embedded geotiff image.

Linear mixing model applied to coarse resolution satellite data

NASA Technical Reports Server (NTRS)

Holben, Brent N.; Shimabukuro, Yosio E.

1992-01-01

A linear mixing model typically applied to high resolution data such as Airborne Visible/Infrared Imaging Spectrometer, Thematic Mapper, and Multispectral Scanner System is applied to the NOAA Advanced Very High Resolution Radiometer coarse resolution satellite data. The reflective portion extracted from the middle IR channel 3 (3.55 - 3.93 microns) is used with channels 1 (0.58 - 0.68 microns) and 2 (0.725 - 1.1 microns) to run the Constrained Least Squares model to generate fraction images for an area in the west central region of Brazil. The derived fraction images are compared with an unsupervised classification and the fraction images derived from Landsat TM data acquired in the same day. In addition, the relationship betweeen these fraction images and the well known NDVI images are presented. The results show the great potential of the unmixing techniques for applying to coarse resolution data for global studies.

Fourier Spectral Filter Array for Optimal Multispectral Imaging.

PubMed

Jia, Jie; Barnard, Kenneth J; Hirakawa, Keigo

2016-04-01

Limitations to existing multispectral imaging modalities include speed, cost, range, spatial resolution, and application-specific system designs that lack versatility of the hyperspectral imaging modalities. In this paper, we propose a novel general-purpose single-shot passive multispectral imaging modality. Central to this design is a new type of spectral filter array (SFA) based not on the notion of spatially multiplexing narrowband filters, but instead aimed at enabling single-shot Fourier transform spectroscopy. We refer to this new SFA pattern as Fourier SFA, and we prove that this design solves the problem of optimally sampling the hyperspectral image data.

Spatial, spectral and temporal patterns of tropical forest cover change as observed with multiple scales of optical satellite data.

Treesearch

D.J. Hayes; W.B. Cohen

2006-01-01

This article describes the development of a methodology for scaling observations of changes in tropical forest cover to large areas at high temporal frequency from coarse-resolution satellite imagery. The approach for estimating proportional forest cover change as a continuous variable is based on a regression model that relates multispectral, multitemporal Moderate...

Ground truth spectrometry and imagery of eruption clouds to maximize utility of satellite imagery

NASA Technical Reports Server (NTRS)

Rose, William I.

1993-01-01

Field experiments with thermal imaging infrared radiometers were performed and a laboratory system was designed for controlled study of simulated ash clouds. Using AVHRR (Advanced Very High Resolution Radiometer) thermal infrared bands 4 and 5, a radiative transfer method was developed to retrieve particle sizes, optical depth and particle mass involcanic clouds. A model was developed for measuring the same parameters using TIMS (Thermal Infrared Multispectral Scanner), MODIS (Moderate Resolution Imaging Spectrometer), and ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer). Related publications are attached.

Multispectral high-resolution hologram generation using orthographic projection images

NASA Astrophysics Data System (ADS)

Muniraj, I.; Guo, C.; Sheridan, J. T.

2016-08-01

We present a new method of synthesizing a digital hologram of three-dimensional (3D) real-world objects from multiple orthographic projection images (OPI). A high-resolution multiple perspectives of 3D objects (i.e., two dimensional elemental image array) are captured under incoherent white light using synthetic aperture integral imaging (SAII) technique and their OPIs are obtained respectively. The reference beam is then multiplied with the corresponding OPI and integrated to form a Fourier hologram. Eventually, a modified phase retrieval algorithm (GS/HIO) is applied to reconstruct the hologram. The principle is validated experimentally and the results support the feasibility of the proposed method.

The Multi-Spectral Imaging Diagnostic on Alcator C-MOD and TCV

NASA Astrophysics Data System (ADS)

Linehan, B. L.; Mumgaard, R. T.; Duval, B. P.; Theiler, C. G.; TCV Team

2017-10-01

The Multi-Spectral Imaging (MSI) diagnostic is a new instrument that captures simultaneous spectrally filtered images from a common sight view while maintaining a large tendue and high spatial resolution. The system uses a polychromator layout where each image is sequentially filtered. This procedure yields a high transmission for each spectral channel with minimal vignetting and aberrations. A four-wavelength system was installed on Alcator C-Mod and then moved to TCV. The system uses industrial cameras to simultaneously image the divertor region at 95 frames per second at f/# 2.8 via a coherent fiber bundle (C-Mod) or a lens-based relay optic (TCV). The images are absolutely calibrated and spatially registered enabling accurate measurement of atomic line ratios and absolute line intensities. The images will be used to study divertor detachment by imaging impurities and Balmer series emissions. Furthermore, the large field of view and an ability to support many types of detectors opens the door for other novel approaches to optically measuring plasma with high temporal, spatial, and spectral resolution. Such measurements will allow for the study of Stark broadening and divertor turbulence. Here, we present the first measurements taken with this cavity imaging system. USDoE awards DE-FC02-99ER54512 and award DE-AC05-06OR23100, ORISE, administered by ORAU.

Time-of-Flight Microwave Camera

PubMed Central

Charvat, Gregory; Temme, Andrew; Feigin, Micha; Raskar, Ramesh

2015-01-01

Microwaves can penetrate many obstructions that are opaque at visible wavelengths, however microwave imaging is challenging due to resolution limits associated with relatively small apertures and unrecoverable “stealth” regions due to the specularity of most objects at microwave frequencies. We demonstrate a multispectral time-of-flight microwave imaging system which overcomes these challenges with a large passive aperture to improve lateral resolution, multiple illumination points with a data fusion method to reduce stealth regions, and a frequency modulated continuous wave (FMCW) receiver to achieve depth resolution. The camera captures images with a resolution of 1.5 degrees, multispectral images across the X frequency band (8 GHz–12 GHz), and a time resolution of 200 ps (6 cm optical path in free space). Images are taken of objects in free space as well as behind drywall and plywood. This architecture allows “camera-like” behavior from a microwave imaging system and is practical for imaging everyday objects in the microwave spectrum. PMID:26434598

Time-of-Flight Microwave Camera

NASA Astrophysics Data System (ADS)

Charvat, Gregory; Temme, Andrew; Feigin, Micha; Raskar, Ramesh

2015-10-01

Microwaves can penetrate many obstructions that are opaque at visible wavelengths, however microwave imaging is challenging due to resolution limits associated with relatively small apertures and unrecoverable “stealth” regions due to the specularity of most objects at microwave frequencies. We demonstrate a multispectral time-of-flight microwave imaging system which overcomes these challenges with a large passive aperture to improve lateral resolution, multiple illumination points with a data fusion method to reduce stealth regions, and a frequency modulated continuous wave (FMCW) receiver to achieve depth resolution. The camera captures images with a resolution of 1.5 degrees, multispectral images across the X frequency band (8 GHz-12 GHz), and a time resolution of 200 ps (6 cm optical path in free space). Images are taken of objects in free space as well as behind drywall and plywood. This architecture allows “camera-like” behavior from a microwave imaging system and is practical for imaging everyday objects in the microwave spectrum.

Beyond RGB: Very high resolution urban remote sensing with multimodal deep networks

NASA Astrophysics Data System (ADS)

Audebert, Nicolas; Le Saux, Bertrand; Lefèvre, Sébastien

2018-06-01

In this work, we investigate various methods to deal with semantic labeling of very high resolution multi-modal remote sensing data. Especially, we study how deep fully convolutional networks can be adapted to deal with multi-modal and multi-scale remote sensing data for semantic labeling. Our contributions are threefold: (a) we present an efficient multi-scale approach to leverage both a large spatial context and the high resolution data, (b) we investigate early and late fusion of Lidar and multispectral data, (c) we validate our methods on two public datasets with state-of-the-art results. Our results indicate that late fusion make it possible to recover errors steaming from ambiguous data, while early fusion allows for better joint-feature learning but at the cost of higher sensitivity to missing data.

Linear mixing model applied to coarse spatial resolution data from multispectral satellite sensors

NASA Technical Reports Server (NTRS)

Holben, Brent N.; Shimabukuro, Yosio E.

1993-01-01

A linear mixing model was applied to coarse spatial resolution data from the NOAA Advanced Very High Resolution Radiometer. The reflective component of the 3.55-3.95 micron channel was used with the two reflective channels 0.58-0.68 micron and 0.725-1.1 micron to run a constrained least squares model to generate fraction images for an area in the west central region of Brazil. The fraction images were compared with an unsupervised classification derived from Landsat TM data acquired on the same day. The relationship between the fraction images and normalized difference vegetation index images show the potential of the unmixing techniques when using coarse spatial resolution data for global studies.

Data collection and simulation of high range resolution laser radar for surface mine detection

NASA Astrophysics Data System (ADS)

Steinvall, Ove; Chevalier, Tomas; Larsson, Håkan

2006-05-01

Rapid and efficient detection of surface mines, IED's (Improvised Explosive Devices) and UXO (Unexploded Ordnance) is of high priority in military conflicts. High range resolution laser radars combined with passive hyper/multispectral sensors offer an interesting concept to help solving this problem. This paper reports on laser radar data collection of various surface mines in different types of terrain. In order to evaluate the capability of 3D imaging for detecting and classifying the objects of interest a scanning laser radar was used to scan mines and surrounding terrain with high angular and range resolution. These data were then fed into a laser radar model capable of generating range waveforms for a variety of system parameters and combinations of different targets and backgrounds. We can thus simulate a potential system by down sampling to relevant pixel sizes and laser/receiver characteristics. Data, simulations and examples will be presented.

Gyrocopter-Based Remote Sensing Platform

NASA Astrophysics Data System (ADS)

Weber, I.; Jenal, A.; Kneer, C.; Bongartz, J.

2015-04-01

In this paper the development of a lightweight and highly modularized airborne sensor platform for remote sensing applications utilizing a gyrocopter as a carrier platform is described. The current sensor configuration consists of a high resolution DSLR camera for VIS-RGB recordings. As a second sensor modality, a snapshot hyperspectral camera was integrated in the aircraft. Moreover a custom-developed thermal imaging system composed of a VIS-PAN camera and a LWIR-camera is used for aerial recordings in the thermal infrared range. Furthermore another custom-developed highly flexible imaging system for high resolution multispectral image acquisition with up to six spectral bands in the VIS-NIR range is presented. The performance of the overall system was tested during several flights with all sensor modalities and the precalculated demands with respect to spatial resolution and reliability were validated. The collected data sets were georeferenced, georectified, orthorectified and then stitched to mosaics.

Simulation of Thematic Mapper performance as a function of sensor scanning parameters

NASA Technical Reports Server (NTRS)

Johnson, R. H.; Shah, N. J.; Schmidt, N. F.

1975-01-01

The investigation and results of the Thematic Mapper Instrument Performance Study are described. The Thematic Mapper is the advanced multispectral scanner initially planned for the Earth Observation Satellite and now planned for LANDSAT D. The use of existing digital airborne scanner data obtained with the Modular Multispectral Scanner (M2S) at Bendix provided an opportunity to simulate the effects of variation of design parameters of the Thematic Mapper. Analysis and processing of this data on the Bendix Multispectral Data Analysis System were used to empirically determine categorization performance on data generated with variations of the sampling period and scan overlap parameters of the Thematic Mapper. The Bendix M2S data, with a 2.5 milliradian instantaneous field of view and a spatial resolution (pixel size) of 10-m from 13,000 ft altitude, allowed a direct simulation of Thematic Mapper data with a 30-m resolution. The flight data chosen were obtained on 30 June 1973 over agricultural test sites in Indiana.

A fast and automatic mosaic method for high-resolution satellite images

NASA Astrophysics Data System (ADS)

Chen, Hongshun; He, Hui; Xiao, Hongyu; Huang, Jing

2015-12-01

We proposed a fast and fully automatic mosaic method for high-resolution satellite images. First, the overlapped rectangle is computed according to geographical locations of the reference and mosaic images and feature points on both the reference and mosaic images are extracted by a scale-invariant feature transform (SIFT) algorithm only from the overlapped region. Then, the RANSAC method is used to match feature points of both images. Finally, the two images are fused into a seamlessly panoramic image by the simple linear weighted fusion method or other method. The proposed method is implemented in C++ language based on OpenCV and GDAL, and tested by Worldview-2 multispectral images with a spatial resolution of 2 meters. Results show that the proposed method can detect feature points efficiently and mosaic images automatically.

Multispectral laser imaging for advanced food analysis

NASA Astrophysics Data System (ADS)

Senni, L.; Burrascano, P.; Ricci, M.

2016-07-01

A hardware-software apparatus for food inspection capable of realizing multispectral NIR laser imaging at four different wavelengths is herein discussed. The system was designed to operate in a through-transmission configuration to detect the presence of unwanted foreign bodies inside samples, whether packed or unpacked. A modified Lock-In technique was employed to counterbalance the significant signal intensity attenuation due to transmission across the sample and to extract the multispectral information more efficiently. The NIR laser wavelengths used to acquire the multispectral images can be varied to deal with different materials and to focus on specific aspects. In the present work the wavelengths were selected after a preliminary analysis to enhance the image contrast between foreign bodies and food in the sample, thus identifying the location and nature of the defects. Experimental results obtained from several specimens, with and without packaging, are presented and the multispectral image processing as well as the achievable spatial resolution of the system are discussed.

Evaluation of ikonos satellite imagery for detecting ice storm damage to oak forests in Eastern Kentucky

Treesearch

W. Henry McNab; Tracy Roof

2006-01-01

Ice storms are a recurring landscape-scale disturbance in the eastern U.S. where they may cause varying levels of damage to upland hardwood forests. High-resolution Ikonos imagery and semiautomated detection of ice storm damage may be an alternative to manually interpreted aerial photography. We evaluated Ikonos multispectral, winter and summer imagery as a tool for...

Get the Picture?

NASA Technical Reports Server (NTRS)

1998-01-01

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.

Design study for multi-channel tape recorder system, volume 1

NASA Technical Reports Server (NTRS)

1972-01-01

The means of storing multispectral, high resolution sensor data on an Earth observing satellite are studied. It is concluded that this is best done digitally on a multi-track, longitudinal, magnetic tape recorder. The machine proposed will store 8 X 10 to the 10th power bits of data on 1040 m of 51 mm-wide magnetic tape mounted on two co-planar reels.

An Object-Oriented Classification Method on High Resolution Satellite Data

DTIC Science & Technology

2004-11-01

25th ACRS 2004 Chiang Mai , Thailand 347 Data Processing B-4.6 AN OBJECT-ORIENTED CLASSIFICATION METHOD ON...unlimited 13. SUPPLEMENTARY NOTES Proceedings of the 25th Asian Conference on Remote Sensing, Held in Chiang Mai , Thailand on 22-26 November 2004...panchromatic (left) and multispectral (right) 25th ACRS 2004 Chiang Mai , Thailand 349 Data Processing B-4.6 First of all, the

Predicting plot basal area and tree density in mixed-conifer forest from lidar and Advanced Land Imager (ALI) data

Treesearch

Andrew T. Hudak; Jeffrey S. Evans; Michael J. Falkowski; Nicholas L. Crookston; Paul E. Gessler; Penelope Morgan; Alistair M. S. Smith

2005-01-01

Multispectral satellite imagery are appealing for their relatively low cost, and have demonstrated utility at the landscape level, but are typically limited at the stand level by coarse resolution and insensitivity to variation in vertical canopy structure. In contrast, lidar data are less affected by these difficulties, and provide high structural detail, but are less...

High Spatial Resolution Airborne Multispectral Thermal Infrared Remote Sensing Data for Analysis of Urban Landscape Characteristics

NASA Technical Reports Server (NTRS)

Quattrochi, Dale A.; Luvall, Jeffrey C.; Estes, Maurice G., Jr.; Arnold, James E. (Technical Monitor)

2000-01-01

We have used airborne multispectral thermal infrared (TIR) remote sensing data collected at a high spatial resolution (i.e., 10m) over several cities in the United States to study thermal energy characteristics of the urban landscape. These TIR data provide a unique opportunity to quantify thermal responses from discrete surfaces typical of the urban landscape and to identify both the spatial arrangement and patterns of thermal processes across the city. The information obtained from these data is critical to understanding how urban surfaces drive or force development of the Urban Heat Island (UHI) effect, which exists as a dome of elevated air temperatures that presides over cities in contrast to surrounding non-urbanized areas. The UHI is most pronounced in the summertime where urban surfaces, such as rooftops and pavement, store solar radiation throughout the day, and release this stored energy slowly after sunset creating air temperatures over the city that are in excess of 2-4'C warmer in contrast with non-urban or rural air temperatures. The UHI can also exist as a daytime phenomenon with surface temperatures in downtown areas of cities exceeding 38'C. The implications of the UHI are significant, particularly as an additive source of thermal energy input that exacerbates the overall production of ground level ozone over cities. We have used the Airborne Thermal and Land Applications Sensor (ATLAS), flown onboard a Lear 23 jet aircraft from the NASA Stennis Space Center, to acquire high spatial resolution multispectral TIR data (i.e., 6 bandwidths between 8.2-12.2 (um) over Huntsville, Alabama, Atlanta, Georgia, Baton Rouge, Louisiana, Salt Lake City, Utah, and Sacramento, California. These TIR data have been used to produce maps and other products, showing the spatial distribution of heating and cooling patterns over these cities to better understand how the morphology of the urban landscape affects development of the UHI. In turn, these data have been used by government officials, urban planners, and other decision-makers, to make more informed decisions on how to mitigate the UHI and its subsequent impacts.

Commercial Applications Multispectral Sensor System

NASA Technical Reports Server (NTRS)

Birk, Ronald J.; Spiering, Bruce

1993-01-01

NASA's Office of Commercial Programs is funding a multispectral sensor system to be used in the development of remote sensing applications. The Airborne Terrestrial Applications Sensor (ATLAS) is designed to provide versatility in acquiring spectral and spatial information. The ATLAS system will be a test bed for the development of specifications for airborne and spaceborne remote sensing instrumentation for dedicated applications. This objective requires spectral coverage from the visible through thermal infrared wavelengths, variable spatial resolution from 2-25 meters; high geometric and geo-location accuracy; on-board radiometric calibration; digital recording; and optimized performance for minimized cost, size, and weight. ATLAS is scheduled to be available in 3rd quarter 1992 for acquisition of data for applications such as environmental monitoring, facilities management, geographic information systems data base development, and mineral exploration.

Simulation of Sentinel-2A Red Edge Bands with RPAS Based Multispectral Data

NASA Astrophysics Data System (ADS)

Davids, Corine; Storvold, Rune; Haarpaintner, Jorg; Arnason, Kolbeinn

2016-08-01

Very high spatial and spectral resolution multispectral data was collected over the Hallormstađur test site in eastern Iceland using a fixed wing remotely piloted aerial system as part of the EU FP7 project North State (www.northstatefp7.eu). The North State project uses forest variable estimates derived from optical and radar satellite data as either input or validation for carbon flux models. The RPAS data from the Hallormsstađur forest test site in Iceland is here used to simulate Landsat and Sentinel-2A data and to explore the advantages of the new Sentinel-2A red edge bands for forest vegetation mapping. Simple supervised classification shows that the inclusion of the red edge bands improves the tree species classification considerably.

The Effect of Remote Sensor Spatial Resolution in Monitoring U.S. Army Training Maneuver Sites

DTIC Science & Technology

1990-12-01

THE EFFECT OF REMOTE SENSOR SPATIAL RESOLUTION IN MONITORING U.S. ARMY...Multispectral Scanner with 6.5 meter spatial resolution provided the most effective digital data set for enhancing tank trails. However, this Airborne Scanner...primary objective of this research was to determine the capabilities and limitations of remote sensor systems having different spatial resolutions to

Increasing the UAV data value by an OBIA methodology

NASA Astrophysics Data System (ADS)

García-Pedrero, Angel; Lillo-Saavedra, Mario; Rodriguez-Esparragon, Dionisio; Rodriguez-Gonzalez, Alejandro; Gonzalo-Martin, Consuelo

2017-10-01

Recently, there has been a noteworthy increment of using images registered by unmanned aerial vehicles (UAV) in different remote sensing applications. Sensors boarded on UAVs has lower operational costs and complexity than other remote sensing platforms, quicker turnaround times as well as higher spatial resolution. Concerning this last aspect, particular attention has to be paid on the limitations of classical algorithms based on pixels when they are applied to high resolution images. The objective of this study is to investigate the capability of an OBIA methodology developed for the automatic generation of a digital terrain model of an agricultural area from Digital Elevation Model (DEM) and multispectral images registered by a Parrot Sequoia multispectral sensor board on a eBee SQ agricultural drone. The proposed methodology uses a superpixel approach for obtaining context and elevation information used for merging superpixels and at the same time eliminating objects such as trees in order to generate a Digital Terrain Model (DTM) of the analyzed area. Obtained results show the potential of the approach, in terms of accuracy, when it is compared with a DTM generated by manually eliminating objects.

Airborne Thermal Infrared Multispectral Scanner (TIMS) images over disseminated gold deposits, Osgood Mountains, Humboldt County, Nevada

NASA Technical Reports Server (NTRS)

Krohn, M. Dennis

1986-01-01

The U.S. Geological Survey (USGS) acquired airborne Thermal Infrared Multispectral Scanner (TIMS) images over several disseminated gold deposits in northern Nevada in 1983. The aerial surveys were flown to determine whether TIMS data could depict jasperoids (siliceous replacement bodies) associated with the gold deposits. The TIMS data were collected over the Pinson and Getchell Mines in the Osgood Mountains, the Carlin, Maggie Creek, Bootstrap, and other mines in the Tuscarora Mountains, and the Jerritt Canyon Mine in the Independence Mountains. The TIMS data seem to be a useful supplement to conventional geochemical exploration for disseminated gold deposits in the western United States. Siliceous outcrops are readily separable in the TIMS image from other types of host rocks. Different forms of silicification are not readily separable, yet, due to limitations of spatial resolution and spectral dynamic range. Features associated with the disseminated gold deposits, such as the large intrusive bodies and fault structures, are also resolvable on TIMS data. Inclusion of high-resolution thermal inertia data would be a useful supplement to the TIMS data.

An Improved Pansharpening Method for Misaligned Panchromatic and Multispectral Data

PubMed Central

Jing, Linhai; Tang, Yunwei; Ding, Haifeng

2018-01-01

Numerous pansharpening methods were proposed in recent decades for fusing low-spatial-resolution multispectral (MS) images with high-spatial-resolution (HSR) panchromatic (PAN) bands to produce fused HSR MS images, which are widely used in various remote sensing tasks. The effect of misregistration between MS and PAN bands on quality of fused products has gained much attention in recent years. An improved method for misaligned MS and PAN imagery is proposed, through two improvements made on a previously published method named RMI (reduce misalignment impact). The performance of the proposed method was assessed by comparing with some outstanding fusion methods, such as adaptive Gram-Schmidt and generalized Laplacian pyramid. Experimental results show that the improved version can reduce spectral distortions of fused dark pixels and sharpen boundaries between different image objects, as well as obtain similar quality indexes with the original RMI method. In addition, the proposed method was evaluated with respect to its sensitivity to misalignments between MS and PAN bands. It is certified that the proposed method is more robust to misalignments between MS and PAN bands than the other methods. PMID:29439502

An Improved Pansharpening Method for Misaligned Panchromatic and Multispectral Data.

PubMed

Li, Hui; Jing, Linhai; Tang, Yunwei; Ding, Haifeng

2018-02-11

Numerous pansharpening methods were proposed in recent decades for fusing low-spatial-resolution multispectral (MS) images with high-spatial-resolution (HSR) panchromatic (PAN) bands to produce fused HSR MS images, which are widely used in various remote sensing tasks. The effect of misregistration between MS and PAN bands on quality of fused products has gained much attention in recent years. An improved method for misaligned MS and PAN imagery is proposed, through two improvements made on a previously published method named RMI (reduce misalignment impact). The performance of the proposed method was assessed by comparing with some outstanding fusion methods, such as adaptive Gram-Schmidt and generalized Laplacian pyramid. Experimental results show that the improved version can reduce spectral distortions of fused dark pixels and sharpen boundaries between different image objects, as well as obtain similar quality indexes with the original RMI method. In addition, the proposed method was evaluated with respect to its sensitivity to misalignments between MS and PAN bands. It is certified that the proposed method is more robust to misalignments between MS and PAN bands than the other methods.

Evaluation of commercial available fusion algorithms for Geoeye data

NASA Astrophysics Data System (ADS)

Vaiopoulos, Aristides D.; Nikolakopoulos, Konstantinos G.

2013-10-01

In this study ten commercial available fusion techniques and more especially the Ehlers, Gram-Schmidt, High Pass Filter, Local Mean Matching (LMM), Local Mean and Variance Matching (LMVM), Modified IHS (ModIHS), Pansharp, PCA, HCS (Hyperspherical Color Space) and Wavelet were used for the fusion of Geoeye panchromatic and multispectral data. The panchromatic data have a spatial resolution of 0.5m while the multispectral data have a spatial resolution of 2.0m. The optical result, the statistical parameters and different quality indexes such as ERGAS, Q, entropy were examined and the results are presented. The broader area of Pendeli mountain near to the city of Athens Greece and more especially two sub areas with different characteristics were chosen for the comparison. The first sub area is located at the edge of the urban fabric and combines at the same time the characteristics of an urban and a rural area. The second sub area comprises a large open quarry and it is suitable to examine which fused product is more suitable for mine monitoring.

Characterization of previously unidentified lunar pyroclastic deposits using Lunar Reconnaissance Orbiter Camera (LROC) data

USGS Publications Warehouse

Gustafson, J. Olaf; Bell, James F.; Gaddis, Lisa R.R.; Hawke, B. Ray Ray; Giguere, Thomas A.

2012-01-01

We used a Lunar Reconnaissance Orbiter Camera (LROC) global monochrome Wide-angle Camera (WAC) mosaic to conduct a survey of the Moon to search for previously unidentified pyroclastic deposits. Promising locations were examined in detail using LROC multispectral WAC mosaics, high-resolution LROC Narrow Angle Camera (NAC) images, and Clementine multispectral (ultraviolet-visible or UVVIS) data. Out of 47 potential deposits chosen for closer examination, 12 were selected as probable newly identified pyroclastic deposits. Potential pyroclastic deposits were generally found in settings similar to previously identified deposits, including areas within or near mare deposits adjacent to highlands, within floor-fractured craters, and along fissures in mare deposits. However, a significant new finding is the discovery of localized pyroclastic deposits within floor-fractured craters Anderson E and F on the lunar farside, isolated from other known similar deposits. Our search confirms that most major regional and localized low-albedo pyroclastic deposits have been identified on the Moon down to ~100 m/pix resolution, and that additional newly identified deposits are likely to be either isolated small deposits or additional portions of discontinuous, patchy deposits.

An algorithm for retrieving rock-desertification from multispectral remote sensing images

NASA Astrophysics Data System (ADS)

Xia, Xueqi; Tian, Qingjiu; Liao, Yan

2009-06-01

Rock-desertification is a typical environmental and ecological problem in Southwest China. As remote sensing is an important means of monitoring spatial variation of rock-desertification, a method is developed for measurement and information retrieval of rock-desertification from multi-spectral high-resolution remote sensing images. MNF transform is applied to 4-band IKONOS multi-spectral remotely sensed data to reduce the number of spectral dimensions to three. In the 3-demension endmembers are extracted and analyzed. It is found that various vegetations group into a line defined as "vegetation line", in which "dark vegetations", such as coniferous forest and broadleaf forest, continuously change to "bright vegetations", such as grasses. It is presumed that is caused by deferent proportion of shadow mixed in leaves or branches in various types of vegetation. Normalized distance between the endmember of rocks and the vegetation line is defined as Geometric Rock-desertification Index (GRI), which was used to scale rock-desertification. The case study with ground truth validation in Puding, Guizhou province showed successes and the advantages of this method.

Current and Future Applications of Multispectral (RGB) Satellite Imagery for Weather Analysis and Forecasting Applications

NASA Technical Reports Server (NTRS)

Molthan, Andrew L.; Fuell, Kevin K.; LaFontaine, Frank; McGrath, Kevin; Smith, Matt

2013-01-01

Current and future satellite sensors provide remotely sensed quantities from a variety of wavelengths ranging from the visible to the passive microwave, from both geostationary and low ]Earth orbits. The NASA Short ]term Prediction Research and Transition (SPoRT) Center has a long history of providing multispectral imagery from the Moderate Resolution Imaging Spectroradiometer (MODIS) aboard NASA fs Terra and Aqua satellites in support of NWS forecast office activities. Products from MODIS have recently been extended to include a broader suite of multispectral imagery similar to those developed by EUMETSAT, based upon the spectral channels available from the Spinning Enhanced Visible and Infrared Imager (SEVIRI) aboard METEOSAT ]9. This broader suite includes products that discriminate between air mass types associated with synoptic ]scale features, assists in the identification of dust, and improves upon paired channel difference detection of fog and low cloud events. Future instruments will continue the availability of these products and also expand upon current capabilities. The Advanced Baseline Imager (ABI) on GOES ]R will improve the spectral, spatial, and temporal resolution of our current geostationary capabilities, and the recent launch of the Suomi National Polar ]Orbiting Partnership (S ]NPP) carries instruments such as the Visible Infrared Imager Radiometer Suite (VIIRS), the Cross ]track Infrared Sounder (CrIS), and the Advanced Technology Microwave Sounder (ATMS), which have unrivaled spectral and spatial resolution, as precursors to the JPSS era (i.e., the next generation of polar orbiting satellites. New applications from VIIRS extend multispectral composites available from MODIS and SEVIRI while adding new capabilities through incorporation of additional CrIS channels or information from the Near Constant Contrast or gDay ]Night Band h, which provides moonlit reflectance from clouds and detection of fires or city lights. This presentation will present a review of SPoRT, CIRA, and NRL collaborations regarding multispectral satellite imagery and recent applications within the operational forecasting environment

Quality evaluation of different fusion techniques applied on Worldview-2 data

NASA Astrophysics Data System (ADS)

Vaiopoulos, Aristides; Nikolakopoulos, Konstantinos G.

2015-10-01

In the current study a Worldview-2 image was used for fusion quality assessment. The bundle image was collected on July 2014 over Araxos area in Western Peloponnese. Worldview-2 is the first satellite that collects at the same time a panchromatic (Pan) image and 8 band multispectral (MS) image. The Pan data have a spatial resolution of 0.46m while the MS data have a spatial resolution of 1.84m. In contrary to the respective Pan band of Ikonos and Quickbird that range between 0.45 and 0.90 micrometers the Worldview Pan band is narrower and ranges between 0.45 and 0.8 micrometers. The MS bands include four conventional visible and near-infrared bands common to multispectral satellites like Ikonos Quickbird, Geoeye Landsat-7 etc., and four new bands. Thus, it is quite interesting to investigate the assessment of commonly used fusion algorithms with Worldview-2 data. Twelve fusion techniques and more especially the Ehlers, Gram-Schmidt, Color Normalized, High Pass Filter, Hyperspherical Color Space, Local Mean Matching (LMM), Local Mean and Variance Matching (LMVM), Modified IHS (ModIHS), Pansharp, Pansharp2, PCA and Wavelet were used for the fusion of Worldview-2 panchromatic and multispectral data. The optical result, the statistical parameters and different quality indexes such as ERGAS, Q and entropy difference were examined and the results are presented. The quality control was evaluated both in spectral and spatial domain.

Monitoring Geothermal Features in Yellowstone National Park with ATLAS Multispectral Imagery

NASA Technical Reports Server (NTRS)

Spruce, Joseph; Berglund, Judith

2000-01-01

The National Park Service (NPS) must produce an Environmental Impact Statement for each proposed development in the vicinity of known geothermal resource areas (KGRAs) in Yellowstone National Park. In addition, the NPS monitors indicator KGRAs for environmental quality and is still in the process of mapping many geothermal areas. The NPS currently maps geothermal features with field survey techniques. High resolution aerial multispectral remote sensing in the visible, NIR, SWIR, and thermal spectral regions could enable YNP geothermal features to be mapped more quickly and in greater detail In response, Yellowstone Ecosystems Studies, in partnership with NASA's Commercial Remote Sensing Program, is conducting a study on the use of Airborne Terrestrial Applications Sensor (ATLAS) multispectral data for monitoring geothermal features in the Upper Geyser Basin. ATLAS data were acquired at 2.5 meter resolution on August 17, 2000. These data were processed into land cover classifications and relative temperature maps. For sufficiently large features, the ATLAS data can map geothermal areas in terms of geyser pools and hot springs, plus multiple categories of geothermal runoff that are apparently indicative of temperature gradients and microbial matting communities. In addition, the ATLAS maps clearly identify geyserite areas. The thermal bands contributed to classification success and to the computation of relative temperature. With masking techniques, one can assess the influence of geothermal features on the Firehole River. Preliminary results appear to confirm ATLAS data utility for mapping and monitoring geothermal features. Future work will include classification refinement and additional validation.

On the Role of Urban and Vegetative Land Cover in the Identification of Tornado Damage Using Dual-Resolution Multispectral Satellite Imagery

NASA Astrophysics Data System (ADS)

Kingfield, D.; de Beurs, K.

2014-12-01

It has been demonstrated through various case studies that multispectral satellite imagery can be utilized in the identification of damage caused by a tornado through the change detection process. This process involves the difference in returned surface reflectance between two images and is often summarized through a variety of ratio-based vegetation indices (VIs). Land cover type plays a large contributing role in the change detection process as the reflectance properties of vegetation can vary based on several factors (e.g. species, greenness, density). Consequently, this provides the possibility for a variable magnitude of loss, making certain land cover regimes less reliable in the damage identification process. Furthermore, the tradeoff between sensor resolution and orbital return period may also play a role in the ability to detect catastrophic loss. Moderate resolution imagery (e.g. Moderate Resolution Imaging Spectroradiometer (MODIS)) provides relatively coarse surface detail with a higher update rate which could hinder the identification of small regions that underwent a dynamic change. Alternatively, imagery with higher spatial resolution (e.g. Landsat) have a longer temporal return period between successive images which could result in natural recovery underestimating the absolute magnitude of damage incurred. This study evaluates the role of land cover type and sensor resolution on four high-end (EF3+) tornado events occurring in four different land cover groups (agriculture, forest, grassland, urban) in the spring season. The closest successive clear images from both Landsat 5 and MODIS are quality controlled for each case. Transacts of surface reflectance across a homogenous land cover type both inside and outside the damage swath are extracted. These metrics are synthesized through the calculation of six different VIs to rank the calculated change metrics by land cover type, sensor resolution and VI.

Current Usage and Future Prospects of Multispectral (RGB) Satellite Imagery in Support of NWS Forecast Offices and National Centers

NASA Technical Reports Server (NTRS)

Molthan, Andrew L.; Fuell, Kevin K.; Knaff, John; Lee, Thomas

2012-01-01

Current and future satellite sensors provide remotely sensed quantities from a variety of wavelengths ranging from the visible to the passive microwave, from both geostationary and low-Earth orbits. The NASA Short-term Prediction Research and Transition (SPoRT) Center has a long history of providing multispectral imagery from the Moderate Resolution Imaging Spectroradiometer (MODIS) aboard NASA s Terra and Aqua satellites in support of NWS forecast office activities. Products from MODIS have recently been extended to include a broader suite of multispectral imagery similar to those developed by EUMETSAT, based upon the spectral channel s available from the Spinning Enhanced Visible and InfraRed Imager (SEVIRI) aboard METEOSAT-9. This broader suite includes products that discriminate between air mass types associated with synoptic-scale features, assists in the identification of dust, and improves upon paired channel difference detection of fog and low cloud events. Similarly, researchers at NOAA/NESDIS and CIRA have developed air mass discrimination capabilities using channels available from the current GOES Sounders. Other applications of multispectral composites include combinations of high and low frequency, horizontal and vertically polarized passive microwave brightness temperatures to discriminate tropical cyclone structures and other synoptic-scale features. Many of these capabilities have been transitioned for evaluation and operational use at NWS Weather Forecast Offices and National Centers through collaborations with SPoRT and CIRA. Future instruments will continue the availability of these products and also expand upon current capabilities. The Advanced Baseline Imager (ABI) on GOES-R will improve the spectral, spatial, and temporal resolution of our current geostationary capabilities, and the recent launch of the Suomi National Polar-Orbiting Partnership (S-NPP) carries instruments such as the Visible Infrared Imager Radiometer Suite (VIIRS), the Cross-track Infrared Sounder (CrIS), and the Advanced Technology Microwave Sounder (ATMS), which have unrivaled spectral and spatial resolution, as precursors to the JPSS era (i.e., the next generation of polar orbiting satellites). At the same time, new image manipulation and display capabilities are available within AWIPS II, the next generation of the NWS forecaster decision support system. This presentation will present a review of SPoRT, CIRA, and NRL collaborations regarding multispectral satellite imagery and articulate an integrated and collaborative path forward with Raytheon AWIPS II development staff for integrating current and future capabilities that support new satellite instrumentation and the AWIPS II decision support system.

Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Kunduz mineral district in Afghanistan: Chapter S in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

USGS Publications Warehouse

Davis, Philip A.; Arko, Scott A.; Harbin, Michelle L.

2013-01-01

The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Kunduz mineral district, which has celestite deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA,2007,2008,2009), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such, the DS products match JAXA criteria for value added products, which are not copyrighted, according to the ALOS end-user license agreement. The selection criteria for the satellite imagery used in our mosaics were images having (1) the highest solar-elevation angles (near summer solstice) and (2) the least cloud, cloud-shadow, and snow cover. The multispectral and panchromatic data were orthorectified with ALOS satellite ephemeris data, a process which is not as accurate as orthorectification using digital elevation models (DEMs); however, the ALOS processing center did not have a precise DEM. As a result, the multispectral and panchromatic image pairs were generally not well registered to the surface and not coregistered well enough to perform resolution enhancement on the multispectral data. For this particular area, PRISM image orthorectification was performed by the Alaska Satellite Facility, applying its photogrammetric software to PRISM stereo images with vertical control points obtained from the digital elevation database produced by the Shuttle Radar Topography Mission (Farr and others, 2007) and horizontal adjustments based on a controlled Landsat image base (Davis, 2006). The 10-m AVNIR multispectral imagery was then coregistered to the orthorectified PRISM images and individual multispectral and panchromatic images were mosaicked into single images of the entire area of interest. The image coregistration was facilitated using an automated control-point algorithm developed by the USGS that allows image coregistration to within one picture element. Before rectification, the multispectral and panchromatic images were converted to radiance values and then to relative-reflectance values using the methods described in Davis (2006). Mosaicking the multispectral or panchromatic images started with the image with the highest sun-elevation angle and the least atmospheric scattering, which was treated as the standard image. The band-reflectance values of all other multispectral or panchromatic images within the area were sequentially adjusted to that of the standard image by determining band-reflectance correspondence between overlapping images using linear least-squares analysis. The resolution of the multispectral image mosaic was then increased to that of the panchromatic image mosaic using the SPARKLE logic, which is described in Davis (2006). Each of the four-band images within the resolution-enhanced image mosaic was individually subjected to a local-area histogram stretch algorithm (described in Davis, 2007), which stretches each band’s picture element based on the digital values of all picture elements within a 500-m radius. The final databases, which are provided in this DS, are three-band, color-composite images of the local-area-enhanced, natural-color data (the blue, green, and red wavelength bands) and color-infrared data (the green, red, and near-infrared wavelength bands). All image data were initially projected and maintained in Universal Transverse Mercator (UTM) map projection using the target area’s local zone (42 for Kunduz) and the WGS84 datum. The final image mosaics were subdivided into five overlapping tiles or quadrants because of the large size of the target area. The five image tiles (or quadrants) for the Kunduz area are provided as embedded geotiff images, which can be read and used by most geographic information system (GIS) and image-processing software. The tiff world files (tfw) are provided, even though they are generally not needed for most software to read an embedded geotiff image.

Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Tourmaline mineral district in Afghanistan: Chapter J in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

USGS Publications Warehouse

Davis, Philip A.; Cagney, Laura E.; Arko, Scott A.; Harbin, Michelle L.

2012-01-01

The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Tourmaline mineral district, which has tin deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA,2008), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such, the DS products match JAXA criteria for value added products, which are not copyrighted, according to the ALOS end-user license agreement. The selection criteria for the satellite imagery used in our mosaics were images having (1) the highest solar-elevation angles (near summer solstice) and (2) the least cloud, cloud-shadow, and snow cover. The multispectral and panchromatic data were orthorectified with ALOS satellite ephemeris data, a process which is not as accurate as orthorectification using digital elevation models (DEMs); however, the ALOS processing center did not have a precise DEM. As a result, the multispectral and panchromatic image pairs were generally not well registered to the surface and not coregistered well enough to perform resolution enhancement on the multispectral data. For this particular area, PRISM image orthorectification was performed by the Alaska Satellite Facility, applying its photogrammetric software to PRISM stereo images with vertical control points obtained from the digital elevation database produced by the Shuttle Radar Topography Mission (Farr and others, 2007) and horizontal adjustments based on a controlled Landsat image base (Davis, 2006). The 10-m AVNIR multispectral imagery was then coregistered to the orthorectified PRISM images and individual multispectral and panchromatic images were mosaicked into single images of the entire area of interest. The image coregistration was facilitated using an automated control-point algorithm developed by the USGS that allows image coregistration to within one picture element. Before rectification, the multispectral and panchromatic images were converted to radiance values and then to relative-reflectance values using the methods described in Davis (2006). Mosaicking the multispectral or panchromatic images started with the image with the highest sun-elevation angle and the least atmospheric scattering, which was treated as the standard image. The band-reflectance values of all other multispectral or panchromatic images within the area were sequentially adjusted to that of the standard image by determining band-reflectance correspondence between overlapping images using linear least-squares analysis. The resolution of the multispectral image mosaic was then increased to that of the panchromatic image mosaic using the SPARKLE logic, which is described in Davis (2006). Each of the four-band images within the resolution-enhanced image mosaic was individually subjected to a local-area histogram stretch algorithm (described in Davis, 2007), which stretches each band's picture element based on the digital values of all picture elements within a 500-m radius. The final databases, which are provided in this DS, are three-band, color-composite images of the local-area-enhanced, natural-color data (the blue, green, and red wavelength bands) and color-infrared data (the green, red, and near-infrared wavelength bands). All image data were initially projected and maintained in Universal Transverse Mercator (UTM) map projection using the target area's local zone (41 for Tourmaline) and the WGS84 datum. The final image mosaics were subdivided into four overlapping tiles or quadrants because of the large size of the target area. The four image tiles (or quadrants) for the Tourmaline area are provided as embedded geotiff images, which can be read and used by most geographic information system (GIS) and image-processing software. The tiff world files (tfw) are provided, even though they are generally not needed for most software to read an embedded geotiff image.

Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Dudkash mineral district in Afghanistan: Chapter R in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

USGS Publications Warehouse

Davis, Philip A.; Arko, Scott A.; Harbin, Michelle L.

2013-01-01

The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Dudkash mineral district, which has industrial mineral deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA,2006,2007,2008,2009), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such, the DS products match JAXA criteria for value added products, which are not copyrighted, according to the ALOS end-user license agreement. The selection criteria for the satellite imagery used in our mosaics were images having (1) the highest solar-elevation angles (near summer solstice) and (2) the least cloud, cloud-shadow, and snow cover. The multispectral and panchromatic data were orthorectified with ALOS satellite ephemeris data, a process which is not as accurate as orthorectification using digital elevation models (DEMs); however, the ALOS processing center did not have a precise DEM. As a result, the multispectral and panchromatic image pairs were generally not well registered to the surface and not coregistered well enough to perform resolution enhancement on the multispectral data. For this particular area, PRISM image orthorectification was performed by the Alaska Satellite Facility, applying its photogrammetric software to PRISM stereo images with vertical control points obtained from the digital elevation database produced by the Shuttle Radar Topography Mission (Farr and others, 2007) and horizontal adjustments based on a controlled Landsat image base (Davis, 2006). The 10-m AVNIR multispectral imagery was then coregistered to the orthorectified PRISM images and individual multispectral and panchromatic images were mosaicked into single images of the entire area of interest. The image coregistration was facilitated using an automated control-point algorithm developed by the USGS that allows image coregistration to within one picture element. Before rectification, the multispectral and panchromatic images were converted to radiance values and then to relative-reflectance values using the methods described in Davis (2006). Mosaicking the multispectral or panchromatic images started with the image with the highest sun-elevation angle and the least atmospheric scattering, which was treated as the standard image. The band-reflectance values of all other multispectral or panchromatic images within the area were sequentially adjusted to that of the standard image by determining band-reflectance correspondence between overlapping images using linear least-squares analysis. The resolution of the multispectral image mosaic was then increased to that of the panchromatic image mosaic using the SPARKLE logic, which is described in Davis (2006). Each of the four-band images within the resolution-enhanced image mosaic was individually subjected to a local-area histogram stretch algorithm (described in Davis, 2007), which stretches each band’s picture element based on the digital values of all picture elements within a 500-m radius. The final databases, which are provided in this DS, are three-band, color-composite images of the local-area-enhanced, natural-color data (the blue, green, and red wavelength bands) and color-infrared data (the green, red, and near-infrared wavelength bands). All image data were initially projected and maintained in Universal Transverse Mercator (UTM) map projection using the target area’s local zone (42 for Dudkash) and the WGS84 datum. The final image mosaics were subdivided into eight overlapping tiles or quadrants because of the large size of the target area. The eight image tiles (or quadrants) for the Dudkash area are provided as embedded geotiff images, which can be read and used by most geographic information system (GIS) and image-processing software. The tiff world files (tfw) are provided, even though they are generally not needed for most software to read an embedded geotiff image.

Inverse analysis of non-uniform temperature distributions using multispectral pyrometry

NASA Astrophysics Data System (ADS)

Fu, Tairan; Duan, Minghao; Tian, Jibin; Shi, Congling

2016-05-01

Optical diagnostics can be used to obtain sub-pixel temperature information in remote sensing. A multispectral pyrometry method was developed using multiple spectral radiation intensities to deduce the temperature area distribution in the measurement region. The method transforms a spot multispectral pyrometer with a fixed field of view into a pyrometer with enhanced spatial resolution that can give sub-pixel temperature information from a "one pixel" measurement region. A temperature area fraction function was defined to represent the spatial temperature distribution in the measurement region. The method is illustrated by simulations of a multispectral pyrometer with a spectral range of 8.0-13.0 μm measuring a non-isothermal region with a temperature range of 500-800 K in the spot pyrometer field of view. The inverse algorithm for the sub-pixel temperature distribution (temperature area fractions) in the "one pixel" verifies this multispectral pyrometry method. The results show that an improved Levenberg-Marquardt algorithm is effective for this ill-posed inverse problem with relative errors in the temperature area fractions of (-3%, 3%) for most of the temperatures. The analysis provides a valuable reference for the use of spot multispectral pyrometers for sub-pixel temperature distributions in remote sensing measurements.

[A Method to Reconstruct Surface Reflectance Spectrum from Multispectral Image Based on Canopy Radiation Transfer Model].

PubMed

Zhao, Yong-guang; Ma, Ling-ling; Li, Chuan-rong; Zhu, Xiao-hua; Tang, Ling-li

2015-07-01

Due to the lack of enough spectral bands for multi-spectral sensor, it is difficult to reconstruct surface retlectance spectrum from finite spectral information acquired by multi-spectral instrument. Here, taking into full account of the heterogeneity of pixel from remote sensing image, a method is proposed to simulate hyperspectral data from multispectral data based on canopy radiation transfer model. This method first assumes the mixed pixels contain two types of land cover, i.e., vegetation and soil. The sensitive parameters of Soil-Leaf-Canopy (SLC) model and a soil ratio factor were retrieved from multi-spectral data based on Look-Up Table (LUT) technology. Then, by combined with a soil ratio factor, all the parameters were input into the SLC model to simulate the surface reflectance spectrum from 400 to 2 400 nm. Taking Landsat Enhanced Thematic Mapper Plus (ETM+) image as reference image, the surface reflectance spectrum was simulated. The simulated reflectance spectrum revealed different feature information of different surface types. To test the performance of this method, the simulated reflectance spectrum was convolved with the Landsat ETM + spectral response curves and Moderate Resolution Imaging Spectrometer (MODIS) spectral response curves to obtain the simulated Landsat ETM+ and MODIS image. Finally, the simulated Landsat ETM+ and MODIS images were compared with the observed Landsat ETM+ and MODIS images. The results generally showed high correction coefficients (Landsat: 0.90-0.99, MODIS: 0.74-0.85) between most simulated bands and observed bands and indicated that the simulated reflectance spectrum was well simulated and reliable.

Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Nalbandon mineral district in Afghanistan: Chapter L in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

USGS Publications Warehouse

Davis, Philip A.; Cagney, Laura E.

2013-01-01

The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Nalbandon mineral district, which has lead and zinc deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA, 2007, 2008, 2010), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such, the DS products match JAXA criteria for value added products, which are not copyrighted, according to the ALOS end-user license agreement. The selection criteria for the satellite imagery used in our mosaics were images having (1) the highest solar-elevation angles (near summer solstice) and (2) the least cloud, cloud-shadow, and snow cover. The multispectral and panchromatic data were orthorectified with ALOS satellite ephemeris data, a process which is not as accurate as orthorectification using digital elevation models (DEMs); however, the ALOS processing center did not have a precise DEM. As a result, the multispectral and panchromatic image pairs were generally not well registered to the surface and not coregistered well enough to perform resolution enhancement on the multispectral data. Therefore, it was necessary to (1) register the 10-m AVNIR multispectral imagery to a well-controlled Landsat image base, (2) mosaic the individual multispectral images into a single image of the entire area of interest, (3) register each panchromatic image to the registered multispectral image base, and (4) mosaic the individual panchromatic images into a single image of the entire area of interest. The two image-registration steps were facilitated using an automated control-point algorithm developed by the USGS that allows image coregistration to within one picture element. Before rectification, the multispectral and panchromatic images were converted to radiance values and then to relative-reflectance values using the methods described in Davis (2006). Mosaicking the multispectral or panchromatic images started with the image with the highest sun-elevation angle and the least atmospheric scattering, which was treated as the standard image. The band-reflectance values of all other multispectral or panchromatic images within the area were sequentially adjusted to that of the standard image by determining band-reflectance correspondence between overlapping images using linear least-squares analysis. The resolution of the multispectral image mosaic was then increased to that of the panchromatic image mosaic using the SPARKLE logic, which is described in Davis (2006). Each of the four-band images within the resolution-enhanced image mosaic was individually subjected to a local-area histogram stretch algorithm (described in Davis, 2007), which stretches each band’s picture element based on the digital values of all picture elements within a 500-m radius. The final databases, which are provided in this DS, are three-band, color-composite images of the local-area-enhanced, natural-color data (the blue, green, and red wavelength bands) and color-infrared data (the green, red, and near-infrared wavelength bands). All image data were initially projected and maintained in Universal Transverse Mercator (UTM) map projection using the target area’s local zone (41 for Nalbandon) and the WGS84 datum. The final image mosaics were subdivided into ten overlapping tiles or quadrants because of the large size of the target area. The ten image tiles (or quadrants) for the Nalbandon area are provided as embedded geotiff images, which can be read and used by most geographic information system (GIS) and image-processing software. The tiff world files (tfw) are provided, even though they are generally not needed for most software to read an embedded geotiff image. Within the Nalbandon study area, two subareas were designated for detailed field investigations (that is, the Nalbandon District and Gharghananaw-Gawmazar subareas); these subareas were extracted from the area’s image mosaic and are provided as separate embedded geotiff images.

Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Zarkashan mineral district in Afghanistan: Chapter G in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

USGS Publications Warehouse

Davis, Philip A.; Cagney, Laura E.

2012-01-01

The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Zarkashan mineral district, which has copper and gold deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA,2006,2007, 2008), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such, the DS products match JAXA criteria for value added products, which are not copyrighted, according to the ALOS end-user license agreement. The selection criteria for the satellite imagery used in our mosaics were images having (1) the highest solar-elevation angles (near summer solstice) and (2) the least cloud, cloud-shadow, and snow cover. The multispectral and panchromatic data were orthorectified with ALOS satellite ephemeris data, a process which is not as accurate as orthorectification using digital elevation models (DEMs); however, the ALOS processing center did not have a precise DEM. As a result, the multispectral and panchromatic image pairs were generally not well registered to the surface and not coregistered well enough to perform resolution enhancement on the multispectral data. Therefore, it was necessary to (1) register the 10-m AVNIR multispectral imagery to a well-controlled Landsat image base, (2) mosaic the individual multispectral images into a single image of the entire area of interest, (3) register each panchromatic image to the registered multispectral image base, and (4) mosaic the individual panchromatic images into a single image of the entire area of interest. The two image-registration steps were facilitated using an automated control-point algorithm developed by the USGS that allows image coregistration to within one picture element. Before rectification, the multispectral and panchromatic images were converted to radiance values and then to relative-reflectance values using the methods described in Davis (2006). Mosaicking the multispectral or panchromatic images started with the image with the highest sun-elevation angle and the least atmospheric scattering, which was treated as the standard image. The band-reflectance values of all other multispectral or panchromatic images within the area were sequentially adjusted to that of the standard image by determining band-reflectance correspondence between overlapping images using linear least-squares analysis. The resolution of the multispectral image mosaic was then increased to that of the panchromatic image mosaic using the SPARKLE logic, which is described in Davis (2006). Each of the four-band images within the resolution-enhanced image mosaic was individually subjected to a local-area histogram stretch algorithm (described in Davis, 2007), which stretches each band’s picture element based on the digital values of all picture elements within a 315-m radius. The final databases, which are provided in this DS, are three-band, color-composite images of the local-area-enhanced, natural-color data (the blue, green, and red wavelength bands) and color-infrared data (the green, red, and near-infrared wavelength bands). All image data were initially projected and maintained in Universal Transverse Mercator (UTM) map projection using the target area’s local zone (42 for Zarkashan) and the WGS84 datum. The final image mosaics were subdivided into two overlapping tiles or quadrants because of the large size of the target area. The two image tiles (or quadrants) for the Zarkashan area are provided as embedded geotiff images, which can be read and used by most geographic information system (GIS) and image-processing software. The tiff world files (tfw) are provided, even though they are generally not needed for most software to read an embedded geotiff image. Within the Zarkashan study area, three subareas were designated for detailed field investigations (that is, the Mine Area, Bolo Gold Prospect, and Luman-Tamaki Gold Prospect subareas); these subareas were extracted from the area’s image mosaic and are provided as separate embedded geotiff images.

Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Kandahar mineral district in Afghanistan: Chapter Z in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

USGS Publications Warehouse

Davis, Philip A.

2013-01-01

The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Kandahar mineral district, which has bauxite deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420-500 nanometer, nm), green (520-600 nm), red (610-690 nm), and near-infrared (760-890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520-770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency ((c)JAXA,2006,2007,2008), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such, the DS products match JAXA criteria for value added products, which are not copyrighted, according to the ALOS end-user license agreement. The selection criteria for the satellite imagery used in our mosaics were images having (1) the highest solar- elevation angles (near summer solstice) and (2) the least cloud, cloud-shadow, and snow cover. The multispectral and panchromatic data were orthorectified with ALOS satellite ephemeris data, a process which is not as accurate as orthorectification using digital elevation models (DEMs); however, the ALOS processing center did not have a precise DEM. As a result, the multispectral and panchromatic image pairs were generally not well registered to the surface and not coregistered well enough to perform resolution enhancement on the multispectral data. Therefore, it was necessary to (1) register the 10-m AVNIR multispectral imagery to a well-controlled Landsat image base, (2) mosaic the individual multispectral images into a single image of the entire area of interest, (3) register each panchromatic image to the registered multispectral image base, and (4) mosaic the individual panchromatic images into a single image of the entire area of interest. The two image- registration steps were facilitated using an automated control-point algorithm developed by the USGS that allows image coregistration to within one picture element. Before rectification, the multispectral and panchromatic images were converted to radiance values and then to relative- reflectance values using the methods described in Davis (2006). Mosaicking the multispectral or panchromatic images started with the image with the highest sun-elevation angle and the least atmospheric scattering, which was treated as the standard image. The band-reflectance values of all other multispectral or panchromatic images within the area were sequentially adjusted to that of the standard image by determining band-reflectance correspondence between overlapping images using linear least-squares analysis. The resolution of the multispectral image mosaic was then increased to that of the panchromatic image mosaic using the SPARKLE logic, which is described in Davis (2006). Each of the four-band images within the resolution-enhanced image mosaic was individually subjected to a local-area histogram stretch algorithm (described in Davis, 2007), which stretches each band's picture element based on the digital values of all picture elements within a 500-m radius. The final databases, which are provided in this DS, are three-band, color-composite images of the local-area- enhanced, natural-color data (the blue, green, and red wavelength bands) and color-infrared data (the green, red, and near-infrared wavelength bands). All image data were initially projected and maintained in Universal Transverse Mercator (UTM) map projection using the target area's local zone (42 for Kandahar) and the WGS84 datum. The final image mosaics were subdivided into eight overlapping tiles or quadrants because of the large size of the target area. The eight image tiles (or quadrants) for the Kandahar area are provided as embedded geotiff images, which can be read and used by most geographic information system (GIS) and image-processing software. The tiff world files (tfw) are provided, even though they are generally not needed for most software to read an embedded geotiff image. Within the Kandahar study area, two subareas were designated for detailed field investigations (that is, the Obatu-Shela and Sekhab-Zamto Kalay subareas); these subareas were extracted from the area's image mosaic and are provided as separate embedded geotiff images.

Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Khanneshin mineral district in Afghanistan: Chapter A in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

USGS Publications Warehouse

Davis, Philip A.; Cagney, Laura E.; Arko, Scott A.; Harbin, Michelle L.

2012-01-01

The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Khanneshin mineral district, which has uranium, thorium, rare-earth-element, and apatite deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420-500 nanometer, nm), green (520-600 nm), red (610-690 nm), and near-infrared (760-890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520-770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA,2007,2008,2010), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such, the DS products match JAXA criteria for value added products, which are not copyrighted, according to the ALOS end-user license agreement. The selection criteria for the satellite imagery used in our mosaics were images having (1) the highest solar-elevation angles (near summer solstice) and (2) the least cloud, cloud-shadow, and snow cover. The multispectral and panchromatic data were orthorectified with ALOS satellite ephemeris data, a process which is not as accurate as orthorectification using digital elevation models (DEMs); however, the ALOS processing center did not have a precise DEM. As a result, the multispectral and panchromatic image pairs were generally not well registered to the surface and not coregistered well enough to perform resolution enhancement on the multispectral data. Therefore, it was necessary to (1) register the 10-m AVNIR multispectral imagery to a well-controlled Landsat image base, (2) mosaic the individual multispectral images into a single image of the entire area of interest, (3) register each panchromatic image to the registered multispectral image base, and (4) mosaic the individual panchromatic images into a single image of the entire area of interest. The two image-registration steps were facilitated using an automated control-point algorithm developed by the USGS that allows image coregistration to within one picture element. Before rectification, the multispectral and panchromatic images were converted to radiance values and then to relative-reflectance values using the methods described in Davis (2006). Mosaicking the multispectral or panchromatic images started with the image with the highest sun-elevation angle and the least atmospheric scattering, which was treated as the standard image. The band-reflectance values of all other multispectral or panchromatic images within the area were sequentially adjusted to that of the standard image by determining band-reflectance correspondence between overlapping images using linear least-squares analysis. The resolution of the multispectral image mosaic was then increased to that of the panchromatic image mosaic using the SPARKLE logic, which is described in Davis (2006). Each of the four-band images within the resolution-enhanced image mosaic was individually subjected to a local-area histogram stretch algorithm (described in Davis, 2007), which stretches each band's picture element based on the digital values of all picture elements within a 500-m radius. The final databases, which are provided in this DS, are three-band, color-composite images of the local-area-enhanced, natural-color data (the blue, green, and red wavelength bands) and color-infrared data (the green, red, and near-infrared wavelength bands). All image data were initially projected and maintained in Universal Transverse Mercator (UTM) map projection using the target area's local zone (41 for Khanneshin) and the WGS84 datum. The final image mosaics were subdivided into nine overlapping tiles or quadrants because of the large size of the target area. The nine image tiles (or quadrants) for the Khanneshin area are provided as embedded geotiff images, which can be read and used by most geographic information system (GIS) and image-processing software. The tiff world files (tfw) are provided, even though they are generally not needed for most software to read an embedded geotiff image. Within the Khanneshin study area, one subarea was designated for detailed field investigations (that is, the Khanneshin volcano subarea); this subarea was extracted from the area's image mosaic and is provided as separate embedded geotiff images.

Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Panjsher Valley mineral district in Afghanistan: Chapter M in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

USGS Publications Warehouse

Davis, Philip A.; Cagney, Laura E.

2013-01-01

The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Panjsher Valley mineral district, which has emerald and silver-iron deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA, 2009, 2010), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such, the DS products match JAXA criteria for value added products, which are not copyrighted, according to the ALOS end-user license agreement. The selection criteria for the satellite imagery used in our mosaics were images having (1) the highest solar-elevation angles (near summer solstice) and (2) the least cloud, cloud-shadow, and snow cover. The multispectral and panchromatic data were orthorectified with ALOS satellite ephemeris data, a process which is not as accurate as orthorectification using digital elevation models (DEMs); however, the ALOS processing center did not have a precise DEM. As a result, the multispectral and panchromatic image pairs were generally not well registered to the surface and not coregistered well enough to perform resolution enhancement on the multispectral data. Therefore, it was necessary to (1) register the 10-m AVNIR multispectral imagery to a well-controlled Landsat image base, (2) mosaic the individual multispectral images into a single image of the entire area of interest, (3) register each panchromatic image to the registered multispectral image base, and (4) mosaic the individual panchromatic images into a single image of the entire area of interest. The two image-registration steps were facilitated using an automated control-point algorithm developed by the USGS that allows image coregistration to within one picture element. Before rectification, the multispectral and panchromatic images were converted to radiance values and then to relative-reflectance values using the methods described in Davis (2006). Mosaicking the multispectral or panchromatic images started with the image with the highest sun-elevation angle and the least atmospheric scattering, which was treated as the standard image. The band-reflectance values of all other multispectral or panchromatic images within the area were sequentially adjusted to that of the standard image by determining band-reflectance correspondence between overlapping images using linear least-squares analysis. The resolution of the multispectral image mosaic was then increased to that of the panchromatic image mosaic using the SPARKLE logic, which is described in Davis (2006). Each of the four-band images within the resolution-enhanced image mosaic was individually subjected to a local-area histogram stretch algorithm (described in Davis, 2007), which stretches each band’s picture element based on the digital values of all picture elements within a 315-m radius. The final databases, which are provided in this DS, are three-band, color-composite images of the local-area-enhanced, natural-color data (the blue, green, and red wavelength bands) and color-infrared data (the green, red, and near-infrared wavelength bands). All image data were initially projected and maintained in Universal Transverse Mercator (UTM) map projection using the target area’s local zone (42 for Panjsher Valley) and the WGS84 datum. The final image mosaics were subdivided into two overlapping tiles or quadrants because of the large size of the target area. The two image tiles (or quadrants) for the Panjsher Valley area are provided as embedded geotiff images, which can be read and used by most geographic information system (GIS) and image-processing software. The tiff world files (tfw) are provided, even though they are generally not needed for most software to read an embedded geotiff image. Within the Panjsher Valley study area, two subareas were designated for detailed field investigations (that is, the Emerald and Silver-Iron subareas); these subareas were extracted from the area’s image mosaic and are provided as separate embedded geotiff images.

Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Farah mineral district in Afghanistan: Chapter FF in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

USGS Publications Warehouse

Davis, Philip A.

2014-01-01

The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Farah mineral district, which has spectral reflectance anomalies indicative of copper, zinc, lead, silver, and gold deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420-500 nanometer, nm), green (520-600 nm), red (610-690 nm), and near-infrared (760-890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520-770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency ((c)JAXA, 2007, 2008, 2010), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such, the DS products match JAXA criteria for value added products, which are not copyrighted, according to the ALOS end-user license agreement. The selection criteria for the satellite imagery used in our mosaics were images having (1) the highest solar-elevation angles (near summer solstice) and (2) the least cloud, cloud-shadow, and snow cover. The multispectral and panchromatic data were orthorectified with ALOS satellite ephemeris data, a process which is not as accurate as orthorectification using digital elevation models (DEMs); however, the ALOS processing center did not have a precise DEM. As a result, the multispectral and panchromatic image pairs were generally not well registered to the surface and not coregistered well enough to perform resolution enhancement on the multispectral data. Therefore, it was necessary to (1) register the 10-m AVNIR multispectral imagery to a well-controlled Landsat image base, (2) mosaic the individual multispectral images into a single image of the entire area of interest, (3) register each panchromatic image to the registered multispectral image base, and (4) mosaic the individual panchromatic images into a single image of the entire area of interest. The two image-registration steps were facilitated using an automated control-point algorithm developed by the USGS that allows image coregistration to within one picture element. Before rectification, the multispectral and panchromatic images were converted to radiance values and then to relative-reflectance values using the methods described in Davis (2006). Mosaicking the multispectral or panchromatic images started with the image with the highest sun-elevation angle and the least atmospheric scattering, which was treated as the standard image. The band-reflectance values of all other multispectral or panchromatic images within the area were sequentially adjusted to that of the standard image by determining band-reflectance correspondence between overlapping images using linear least-squares analysis. The resolution of the multispectral image mosaic was then increased to that of the panchromatic image mosaic using the SPARKLE logic, which is described in Davis (2006). Each of the four-band images within the resolution-enhanced image mosaic was individually subjected to a local-area histogram stretch algorithm (described in Davis, 2007), which stretches each band's picture element based on the digital values of all picture elements within a 500-m radius. The final databases, which are provided in this DS, are three-band, color-composite images of the local-area-enhanced, natural-color data (the blue, green, and red wavelength bands) and color-infrared data (the green, red, and near-infrared wavelength bands). All image data were initially projected and maintained in Universal Transverse Mercator (UTM) map projection using the target area's local zone (41 for Farah) and the WGS84 datum. The final image mosaics were subdivided into four overlapping tiles or quadrants because of the large size of the target area. The four image tiles (or quadrants) for the Farah area are provided as embedded geotiff images, which can be read and used by most geographic information system (GIS) and image-processing software. The tiff world files (tfw) are provided, even though they are generally not needed for most software to read an embedded geotiff image. Within the Farah study area, five subareas were designated for detailed field investigations (that is, the FarahA through FarahE subareas); these subareas were extracted from the area’s image mosaic and are provided as separate embedded geotiff images.

Remote Sensing-Based, 5-m, Vegetation Distributions, Kougarok Study Site, Seward Peninsula, Alaska, ca. 2009 - 2016

DOE Office of Scientific and Technical Information (OSTI.GOV)

Langford, Zachary; Kumar, Jitendra; Hoffman, Forrest

A multi-sensor remote sensing-based deep learning approach was developed for generating high-resolution (5~m) vegetation maps for the western Alaskan Arctic on the Seward Peninsula, Alaska. This data was developed using the fusion of hyperspectral, multispectral, and terrain datasets. The current data is located in the Kougarok watershed but we plan to expand this over the Seward Peninsula.

Landsat imagery: a unique resource

USGS Publications Warehouse

Miller, H.; Sexton, N.; Koontz, L.

2011-01-01

Landsat satellites provide high-quality, multi-spectral imagery of the surface of the Earth. These moderate-resolution, remotely sensed images are not just pictures, but contain many layers of data collected at different points along the visible and invisible light spectrum. These data can be manipulated to reveal what the Earth’s surface looks like, including what types of vegetation are present or how a natural disaster has impacted an area (Fig. 1).

Mapping ephemeral stream networks in desert environments using very-high-spatial-resolution multispectral remote sensing

DOE PAGES

Hamada, Yuki; O'Connor, Ben L.; Orr, Andrew B.; ...

2016-03-26

In this paper, understanding the spatial patterns of ephemeral streams is crucial for understanding how hydrologic processes influence the abundance and distribution of wildlife habitats in desert regions. Available methods for mapping ephemeral streams at the watershed scale typically underestimate the size of channel networks. Although remote sensing is an effective means of collecting data and obtaining information on large, inaccessible areas, conventional techniques for extracting channel features are not sufficient in regions that have small topographic gradients and subtle target-background spectral contrast. By using very high resolution multispectral imagery, we developed a new algorithm that applies landscape information tomore » map ephemeral channels in desert regions of the Southwestern United States where utility-scale solar energy development is occurring. Knowledge about landscape features and structures was integrated into the algorithm using a series of spectral transformation and spatial statistical operations to integrate information about landscape features and structures. The algorithm extracted ephemeral stream channels at a local scale, with the result that approximately 900% more ephemeral streams was identified than what were identified by using the U.S. Geological Survey’s National Hydrography Dataset. The accuracy of the algorithm in detecting channel areas was as high as 92%, and its accuracy in delineating channel center lines was 91% when compared to a subset of channel networks that were digitized by using the very high resolution imagery. Although the algorithm captured stream channels in desert landscapes across various channel sizes and forms, it often underestimated stream headwaters and channels obscured by bright soils and sparse vegetation. While further improvement is warranted, the algorithm provides an effective means of obtaining detailed information about ephemeral streams, and it could make a significant contribution toward improving the hydrological modelling of desert environments.« less

Mapping ephemeral stream networks in desert environments using very-high-spatial-resolution multispectral remote sensing

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hamada, Yuki; O'Connor, Ben L.; Orr, Andrew B.

In this paper, understanding the spatial patterns of ephemeral streams is crucial for understanding how hydrologic processes influence the abundance and distribution of wildlife habitats in desert regions. Available methods for mapping ephemeral streams at the watershed scale typically underestimate the size of channel networks. Although remote sensing is an effective means of collecting data and obtaining information on large, inaccessible areas, conventional techniques for extracting channel features are not sufficient in regions that have small topographic gradients and subtle target-background spectral contrast. By using very high resolution multispectral imagery, we developed a new algorithm that applies landscape information tomore » map ephemeral channels in desert regions of the Southwestern United States where utility-scale solar energy development is occurring. Knowledge about landscape features and structures was integrated into the algorithm using a series of spectral transformation and spatial statistical operations to integrate information about landscape features and structures. The algorithm extracted ephemeral stream channels at a local scale, with the result that approximately 900% more ephemeral streams was identified than what were identified by using the U.S. Geological Survey’s National Hydrography Dataset. The accuracy of the algorithm in detecting channel areas was as high as 92%, and its accuracy in delineating channel center lines was 91% when compared to a subset of channel networks that were digitized by using the very high resolution imagery. Although the algorithm captured stream channels in desert landscapes across various channel sizes and forms, it often underestimated stream headwaters and channels obscured by bright soils and sparse vegetation. While further improvement is warranted, the algorithm provides an effective means of obtaining detailed information about ephemeral streams, and it could make a significant contribution toward improving the hydrological modelling of desert environments.« less

Remote sensing of the Canadian Arctic: Modelling biophysical variables

NASA Astrophysics Data System (ADS)

Liu, Nanfeng

It is anticipated that Arctic vegetation will respond in a variety of ways to altered temperature and precipitation patterns expected with climate change, including changes in phenology, productivity, biomass, cover and net ecosystem exchange. Remote sensing provides data and data processing methodologies for monitoring and assessing Arctic vegetation over large areas. The goal of this research was to explore the potential of hyperspectral and high spatial resolution multispectral remote sensing data for modelling two important Arctic biophysical variables: Percent Vegetation Cover (PVC) and the fraction of Absorbed Photosynthetically Active Radiation (fAPAR). A series of field experiments were conducted to collect PVC and fAPAR at three Canadian Arctic sites: (1) Sabine Peninsula, Melville Island, NU; (2) Cape Bounty Arctic Watershed Observatory (CBAWO), Melville Island, NU; and (3) Apex River Watershed (ARW), Baffin Island, NU. Linear relationships between biophysical variables and Vegetation Indices (VIs) were examined at different spatial scales using field spectra (for the Sabine Peninsula site) and high spatial resolution satellite data (for the CBAWO and ARW sites). At the Sabine Peninsula site, hyperspectral VIs exhibited a better performance for modelling PVC than multispectral VIs due to their capacity for sampling fine spectral features. The optimal hyperspectral bands were located at important spectral features observed in Arctic vegetation spectra, including leaf pigment absorption in the red wavelengths and at the red-edge, leaf water absorption in the near infrared, and leaf cellulose and lignin absorption in the shortwave infrared. At the CBAWO and ARW sites, field PVC and fAPAR exhibited strong correlations (R2 > 0.70) with the NDVI (Normalized Difference Vegetation Index) derived from high-resolution WorldView-2 data. Similarly, high spatial resolution satellite-derived fAPAR was correlated to MODIS fAPAR (R2 = 0.68), with a systematic overestimation of 0.08, which was attributed to PAR absorption by soil that could not be excluded from the fAPAR calculation. This research clearly demonstrates that high spectral and spatial resolution remote sensing VIs can be used to successfully model Arctic biophysical variables. The methods and results presented in this research provided a guide for future studies aiming to model other Arctic biophysical variables through remote sensing data.

Object-oriented recognition of high-resolution remote sensing image

NASA Astrophysics Data System (ADS)

Wang, Yongyan; Li, Haitao; Chen, Hong; Xu, Yuannan

2016-01-01

With the development of remote sensing imaging technology and the improvement of multi-source image's resolution in satellite visible light, multi-spectral and hyper spectral , the high resolution remote sensing image has been widely used in various fields, for example military field, surveying and mapping, geophysical prospecting, environment and so forth. In remote sensing image, the segmentation of ground targets, feature extraction and the technology of automatic recognition are the hotspot and difficulty in the research of modern information technology. This paper also presents an object-oriented remote sensing image scene classification method. The method is consist of vehicles typical objects classification generation, nonparametric density estimation theory, mean shift segmentation theory, multi-scale corner detection algorithm, local shape matching algorithm based on template. Remote sensing vehicles image classification software system is designed and implemented to meet the requirements .

Potential of the multispectral synergism for observing ozone pollution combining measurements of IASI-NG and UVNS onboard EPS-SG

NASA Astrophysics Data System (ADS)

Costantino, Lorenzo; Cuesta, Juan; Emili, Emanuele; Foret, Gilles; Dufour, Gaëlle; Eremenko, Maxim; Chailleux, Yohann; Beekmann, Matthias; Flaud, Jean-Marie

2016-04-01

Current and future satellite observations offer a great potential for monitoring air quality on daily and global basis. However, measurements from currently in orbit sensors offer a limited capacity to probe surface concentrations of gaseous pollutants such as tropospheric ozone. Using single-band approaches based on IASI spaceborne thermal infrared measurements, only ozone down to the lower troposphere (3-4 km of altitude at lowest) may be observed (Eremenko et al., 2008). A recent multispectral method combining IASI and GOME-2 (both onboard MetOp satellites) spectra, respectively from the IR and UV, has shown enhanced sensitivity for probing ozone at the lowermost troposphere, but with maximum sensitivity around 2 km at lowest (Cuesta et al., 2013). Future spatial missions will be launched in the upcoming years, such as EPS-SG, carrying new generation sensors like IASI-NG and UVNS that will enhance the capacity to observe ozone pollution, and particularly when combining them through a multispectral synergism. This work presents an analysis of the potential of the multispectral synergism of IASI-NG and UVNS future spaceborne measurements for observing ozone pollution, performed in the framework of SURVEYOZON project (funded by the French Space Agency, CNES). For this, we develop a simulator of synthetic multispectral retrievals or pseudo-observations (referred as OSSE, Observing System Simulation Experiment) derived from IASI-NG+UVNS that will be compared to those from IASI+GOME2. In the first step of the OSSE, we create a pseudo-reality with simulations from the chemical-transport model MOCAGE (provided by CERFACS laboratory), where real O3 data from IASI and surface network stations have been assimilated for a realistic representation of ozone variability at the surface and the free troposphere. We focus on the high pollution event occurred in Europe on 10 July 2010. We use the coupled algorithms KOPRA+VLIDORT to simulate the spectra emitted, scattered and absorbed by the surface and atmospheric components and simulate the spectral measurements of IASI and GOME2. These spectra as used to retrieve O3 profiles that are then compared with the pseudo-reality. These pseudo-observations enable us to estimate the performances and associated errors of the innovative multispectral methodology implemented with IASI-NG (with finer spectral resolution and lower noise than IASI) and UVNS (with lower noise and finer horizontal resolution than GOME-2). In a second step, these pseudo-observations will be used to quantify the improvement in regional air pollution forecasts, when assimilating this new multispectral O3 product in a second chemical transport model (CHIMERE) independent from MOCAGE.

Retrieval of cloud cover parameters from multispectral satellite images

NASA Technical Reports Server (NTRS)

Arking, A.; Childs, J. D.

1985-01-01

A technique is described for extracting cloud cover parameters from multispectral satellite radiometric measurements. Utilizing three channels from the AVHRR (Advanced Very High Resolution Radiometer) on NOAA polar orbiting satellites, it is shown that one can retrieve four parameters for each pixel: cloud fraction within the FOV, optical thickness, cloud-top temperature and a microphysical model parameter. The last parameter is an index representing the properties of the cloud particle and is determined primarily by the radiance at 3.7 microns. The other three parameters are extracted from the visible and 11 micron infrared radiances, utilizing the information contained in the two-dimensional scatter plot of the measured radiances. The solution is essentially one in which the distributions of optical thickness and cloud-top temperature are maximally clustered for each region, with cloud fraction for each pixel adjusted to achieve maximal clustering.

UAV lidar and hyperspectral fusion for forest monitoring in the southwestern USA

USGS Publications Warehouse

Sankey, Temuulen T.; Donager, Jonathon; McVay, Jason L.; Sankey, Joel B.

2017-01-01

Forest vegetation classification and structure measurements are fundamental steps for planning, monitoring, and evaluating large-scale forest changes including restoration treatments. High spatial and spectral resolution remote sensing data are critically needed to classify vegetation and measure their 3-dimensional (3D) canopy structure at the level of individual species. Here we test high-resolution lidar, hyperspectral, and multispectral data collected from unmanned aerial vehicles (UAV) and demonstrate a lidar-hyperspectral image fusion method in treated and control forests with varying tree density and canopy cover as well as in an ecotone environment to represent a gradient of vegetation and topography in northern Arizona, U.S.A. The fusion performs better (88% overall accuracy) than either data type alone, particularly for species with similar spectral signatures, but different canopy sizes. The lidar data provides estimates of individual tree height (R2 = 0.90; RMSE = 2.3 m) and crown diameter (R2 = 0.72; RMSE = 0.71 m) as well as total tree canopy cover (R2 = 0.87; RMSE = 9.5%) and tree density (R2 = 0.77; RMSE = 0.69 trees/cell) in 10 m cells across thin only, burn only, thin-and-burn, and control treatments, where tree cover and density ranged between 22 and 50% and 1–3.5 trees/cell, respectively. The lidar data also produces highly accurate digital elevation model (DEM) (R2 = 0.92; RMSE = 0.75 m). In comparison, 3D data derived from the multispectral data via structure-from-motion produced lower correlations with field-measured variables, especially in dense and structurally complex forests. The lidar, hyperspectral, and multispectral sensors, and the methods demonstrated here can be widely applied across a gradient of vegetation and topography for monitoring landscapes undergoing large-scale changes such as the forests in the southwestern U.S.A.

Efficient single-pixel multispectral imaging via non-mechanical spatio-spectral modulation.

PubMed

Li, Ziwei; Suo, Jinli; Hu, Xuemei; Deng, Chao; Fan, Jingtao; Dai, Qionghai

2017-01-27

Combining spectral imaging with compressive sensing (CS) enables efficient data acquisition by fully utilizing the intrinsic redundancies in natural images. Current compressive multispectral imagers, which are mostly based on array sensors (e.g, CCD or CMOS), suffer from limited spectral range and relatively low photon efficiency. To address these issues, this paper reports a multispectral imaging scheme with a single-pixel detector. Inspired by the spatial resolution redundancy of current spatial light modulators (SLMs) relative to the target reconstruction, we design an all-optical spectral splitting device to spatially split the light emitted from the object into several counterparts with different spectrums. Separated spectral channels are spatially modulated simultaneously with individual codes by an SLM. This no-moving-part modulation ensures a stable and fast system, and the spatial multiplexing ensures an efficient acquisition. A proof-of-concept setup is built and validated for 8-channel multispectral imaging within 420~720 nm wavelength range on both macro and micro objects, showing a potential for efficient multispectral imager in macroscopic and biomedical applications.

Roi-Orientated Sensor Correction Based on Virtual Steady Reimaging Model for Wide Swath High Resolution Optical Satellite Imagery

NASA Astrophysics Data System (ADS)

Zhu, Y.; Jin, S.; Tian, Y.; Wang, M.

2017-09-01

To meet the requirement of high accuracy and high speed processing for wide swath high resolution optical satellite imagery under emergency situation in both ground processing system and on-board processing system. This paper proposed a ROI-orientated sensor correction algorithm based on virtual steady reimaging model for wide swath high resolution optical satellite imagery. Firstly, the imaging time and spatial window of the ROI is determined by a dynamic search method. Then, the dynamic ROI sensor correction model based on virtual steady reimaging model is constructed. Finally, the corrected image corresponding to the ROI is generated based on the coordinates mapping relationship which is established by the dynamic sensor correction model for corrected image and rigours imaging model for original image. Two experimental results show that the image registration between panchromatic and multispectral images can be well achieved and the image distortion caused by satellite jitter can be also corrected efficiently.

Detection of rice sheath blight using an unmanned aerial system with high-resolution color and multispectral imaging.

PubMed

Zhang, Dongyan; Zhou, Xingen; Zhang, Jian; Lan, Yubin; Xu, Chao; Liang, Dong

2018-01-01

Detection and monitoring are the first essential step for effective management of sheath blight (ShB), a major disease in rice worldwide. Unmanned aerial systems have a high potential of being utilized to improve this detection process since they can reduce the time needed for scouting for the disease at a field scale, and are affordable and user-friendly in operation. In this study, a commercialized quadrotor unmanned aerial vehicle (UAV), equipped with digital and multispectral cameras, was used to capture imagery data of research plots with 67 rice cultivars and elite lines. Collected imagery data were then processed and analyzed to characterize the development of ShB and quantify different levels of the disease in the field. Through color features extraction and color space transformation of images, it was found that the color transformation could qualitatively detect the infected areas of ShB in the field plots. However, it was less effective to detect different levels of the disease. Five vegetation indices were then calculated from the multispectral images, and ground truths of disease severity and GreenSeeker measured NDVI (Normalized Difference Vegetation Index) were collected. The results of relationship analyses indicate that there was a strong correlation between ground-measured NDVIs and image-extracted NDVIs with the R2 of 0.907 and the root mean square error (RMSE) of 0.0854, and a good correlation between image-extracted NDVIs and disease severity with the R2 of 0.627 and the RMSE of 0.0852. Use of image-based NDVIs extracted from multispectral images could quantify different levels of ShB in the field plots with an accuracy of 63%. These results demonstrate that a customer-grade UAV integrated with digital and multispectral cameras can be an effective tool to detect the ShB disease at a field scale.

The Multispectral Imaging Science Working Group. Volume 1: Executive summary

NASA Technical Reports Server (NTRS)

Cox, S. C. (Editor)

1982-01-01

Results of the deliberations of the six multispectral imaging science working groups (Botany, Geography, Geology, Hydrology, Imaging Science and Information Science) are summarized. Consideration was given to documenting the current state of knowledge in terrestrial remote sensing without the constraints of preconceived concepts such as possible band widths, number of bands, and radiometric or spatial resolutions of present or future systems. The findings of each working group included a discussion of desired capabilities and critical developmental issues.

Backthinned TDI CCD image sensor design and performance for the Pleiades high resolution Earth observation satellites

NASA Astrophysics Data System (ADS)

Materne, A.; Bardoux, A.; Geoffray, H.; Tournier, T.; Kubik, P.; Morris, D.; Wallace, I.; Renard, C.

2017-11-01

The PLEIADES-HR Earth observing satellites, under CNES development, combine a 0.7m resolution panchromatic channel, and a multispectral channel allowing a 2.8 m resolution, in 4 spectral bands. The 2 satellites will be placed on a sun-synchronous orbit at an altitude of 695 km. The camera operates in push broom mode, providing images across a 20 km swath. This paper focuses on the specifications, design and performance of the TDI detectors developed by e2v technologies under CNES contract for the panchromatic channel. Design drivers, derived from the mission and satellite requirements, architecture of the sensor and measurement results for key performances of the first prototypes are presented.

High-fidelity video and still-image communication based on spectral information: natural vision system and its applications

NASA Astrophysics Data System (ADS)

Yamaguchi, Masahiro; Haneishi, Hideaki; Fukuda, Hiroyuki; Kishimoto, Junko; Kanazawa, Hiroshi; Tsuchida, Masaru; Iwama, Ryo; Ohyama, Nagaaki

2006-01-01

In addition to the great advancement of high-resolution and large-screen imaging technology, the issue of color is now receiving considerable attention as another aspect than the image resolution. It is difficult to reproduce the original color of subject in conventional imaging systems, and that obstructs the applications of visual communication systems in telemedicine, electronic commerce, and digital museum. To breakthrough the limitation of conventional RGB 3-primary systems, "Natural Vision" project aims at an innovative video and still-image communication technology with high-fidelity color reproduction capability, based on spectral information. This paper summarizes the results of NV project including the development of multispectral and multiprimary imaging technologies and the experimental investigations on the applications to medicine, digital archives, electronic commerce, and computer graphics.

MTI science, data products, and ground-data processing overview

NASA Astrophysics Data System (ADS)

Szymanski, John J.; Atkins, William H.; Balick, Lee K.; Borel, Christoph C.; Clodius, William B.; Christensen, R. Wynn; Davis, Anthony B.; Echohawk, J. C.; Galbraith, Amy E.; Hirsch, Karen L.; Krone, James B.; Little, Cynthia K.; McLachlan, Peter M.; Morrison, Aaron; Pollock, Kimberly A.; Pope, Paul A.; Novak, Curtis; Ramsey, Keri A.; Riddle, Emily E.; Rohde, Charles A.; Roussel-Dupre, Diane C.; Smith, Barham W.; Smith, Kathy; Starkovich, Kim; Theiler, James P.; Weber, Paul G.

2001-08-01

The mission of the Multispectral Thermal Imager (MTI) satellite is to demonstrate the efficacy of highly accurate multispectral imaging for passive characterization of urban and industrial areas, as well as sites of environmental interest. The satellite makes top-of-atmosphere radiance measurements that are subsequently processed into estimates of surface properties such as vegetation health, temperatures, material composition and others. The MTI satellite also provides simultaneous data for atmospheric characterization at high spatial resolution. To utilize these data the MTI science program has several coordinated components, including modeling, comprehensive ground-truth measurements, image acquisition planning, data processing and data interpretation and analysis. Algorithms have been developed to retrieve a multitude of physical quantities and these algorithms are integrated in a processing pipeline architecture that emphasizes automation, flexibility and programmability. In addition, the MTI science team has produced detailed site, system and atmospheric models to aid in system design and data analysis. This paper provides an overview of the MTI research objectives, data products and ground data processing.

Configuration and Specifications of AN Unmanned Aerial Vehicle for Precision Agriculture

NASA Astrophysics Data System (ADS)

Erena, M.; Montesinos, S.; Portillo, D.; Alvarez, J.; Marin, C.; Fernandez, L.; Henarejos, J. M.; Ruiz, L. A.

2016-06-01

Unmanned Aerial Vehicles (UAVs) with multispectral sensors are increasingly attractive in geosciences for data capture and map updating at high spatial and temporal resolutions. These autonomously-flying systems can be equipped with different sensors, such as a six-band multispectral camera (Tetracam mini-MCA-6), GPS Ublox M8N, and MEMS gyroscopes, and miniaturized sensor systems for navigation, positioning, and mapping purposes. These systems can be used for data collection in precision viticulture. In this study, the efficiency of a light UAV system for data collection, processing, and map updating in small areas is evaluated, generating correlations between classification maps derived from remote sensing and production maps. Based on the comparison of the indices derived from UAVs incorporating infrared sensors with those obtained by satellites (Sentinel 2A and Landsat 8), UAVs show promise for the characterization of vineyard plots with high spatial variability, despite the low vegetative coverage of these crops. Consequently, a procedure for zoning map production based on UAV/UV images could provide important information for farmers.

Evaluation of DOD Priority Species at Risk (SAR) and Applications for Remote Sensing

DTIC Science & Technology

2009-02-01

Species Type Common Name Scientific Name Fort McClellan AL fish coldwater darter Etheostoma ditrema Camp Shelby MS crustacean Camp Shelby burrowing...plant in the Aster family that exhibits mat-forming growth characteristics (Figure 15). B. tetraneuris in- habits barren, light colored shale and...vegetated areas within Fort Lewis, WA have the poten- tial to be mapped using high-resolution multispectral imagery. Other open (i.e., disturbed) habited

Developing Remote Sensing Capabilities for Meter-Scale Sea Ice Properties

DTIC Science & Technology

2013-09-30

such as MODIS . APPROACH 1. Task and acquire high resolution panchromatic and multispectral optical (e.g. Quickbird, Worldview, National Assets...does not display a currently valid OMB control number. 1. REPORT DATE 30 SEP 2013 2. REPORT TYPE 3. DATES COVERED 00-00-2013 to 00-00-2013 4...cloud cover , an excessive percentage of the imagery acquired over drifting sites was cloud covered , and the vendor did not delay acquisitions or

A preliminary comparison of Landsat Thematic Mapper and SPOT-1 HRV multispectral data for estimating coniferous forest volume

NASA Technical Reports Server (NTRS)

Ripple, W. J.; Wang, S.; Isaacson, D. L.; Paine, D. P.

1991-01-01

Digital Landsat Thematic Mapper (TM) and SPOT high-resolution visible (HRV) images of coniferous forest canopies were compared in their relationship to forest wood volume using correlation and regression analyses. Significant inverse relationships were found between softwood volume and the spectral bands from both sensors (P less than 0.01). The highest correlations were between the log of softwood volume and the near-infrared bands.

LANDSAT D to test thematic mapper, inaugurate operational system

NASA Technical Reports Server (NTRS)

1982-01-01

NASA will launch the Landsat D spacecraft on July 9, 1982 aboard a new, up-rated Delta 3920 expendable launch vehicle. LANDSAT D will incorporate two highly sophisticated sensors; the flight proven multispectral scanner; and a new instrument expected to advance considerably the remote sensing capabilities of Earth resources satellites. The new sensor, the thematic mapper, provides data in seven spectral (light) bands with greatly improved spectral, spatial and radiometric resolution.

Method using in vivo quantitative spectroscopy to guide design and optimization of low-cost, compact clinical imaging devices: emulation and evaluation of multispectral imaging systems

NASA Astrophysics Data System (ADS)

Saager, Rolf B.; Baldado, Melissa L.; Rowland, Rebecca A.; Kelly, Kristen M.; Durkin, Anthony J.

2018-04-01

With recent proliferation in compact and/or low-cost clinical multispectral imaging approaches and commercially available components, questions remain whether they adequately capture the requisite spectral content of their applications. We present a method to emulate the spectral range and resolution of a variety of multispectral imagers, based on in-vivo data acquired from spatial frequency domain spectroscopy (SFDS). This approach simulates spectral responses over 400 to 1100 nm. Comparing emulated data with full SFDS spectra of in-vivo tissue affords the opportunity to evaluate whether the sparse spectral content of these imagers can (1) account for all sources of optical contrast present (completeness) and (2) robustly separate and quantify sources of optical contrast (crosstalk). We validate the approach over a range of tissue-simulating phantoms, comparing the SFDS-based emulated spectra against measurements from an independently characterized multispectral imager. Emulated results match the imager across all phantoms (<3 % absorption, <1 % reduced scattering). In-vivo test cases (burn wounds and photoaging) illustrate how SFDS can be used to evaluate different multispectral imagers. This approach provides an in-vivo measurement method to evaluate the performance of multispectral imagers specific to their targeted clinical applications and can assist in the design and optimization of new spectral imaging devices.

Computer-aided analysis of Skylab multispectral scanner data in mountainous terrain for land use, forestry, water resource, and geologic applications

NASA Technical Reports Server (NTRS)

Hoffer, R. M. (Principal Investigator)

1975-01-01

The author has identified the following significant results. One of the most significant results of this Skylab research involved the geometric correction and overlay of the Skylab multispectral scanner data with the LANDSAT multispectral scanner data, and also with a set of topographic data, including elevation, slope, and aspect. The Skylab S192 multispectral scanner data had distinct differences in noise level of the data in the various wavelength bands. Results of the temporal evaluation of the SL-2 and SL-3 photography were found to be particularly important for proper interpretation of the computer-aided analysis of the SL-2 and SL-3 multispectral scanner data. There was a quality problem involving the ringing effect introduced by digital filtering. The modified clustering technique was found valuable when working with multispectral scanner data involving many wavelength bands and covering large geographic areas. Analysis of the SL-2 scanner data involved classification of major cover types and also forest cover types. Comparison of the results obtained wth Skylab MSS data and LANDSAT MSS data indicated that the improved spectral resolution of the Skylab scanner system enabled a higher classification accuracy to be obtained for forest cover types, although the classification performance for major cover types was not significantly different.

A sampling procedure to guide the collection of narrow-band, high-resolution spatially and spectrally representative reflectance data. [satellite imagery of earth resources

NASA Technical Reports Server (NTRS)

Brand, R. R.; Barker, J. L.

1983-01-01

A multistage sampling procedure using image processing, geographical information systems, and analytical photogrammetry is presented which can be used to guide the collection of representative, high-resolution spectra and discrete reflectance targets for future satellite sensors. The procedure is general and can be adapted to characterize areas as small as minor watersheds and as large as multistate regions. Beginning with a user-determined study area, successive reductions in size and spectral variation are performed using image analysis techniques on data from the Multispectral Scanner, orbital and simulated Thematic Mapper, low altitude photography synchronized with the simulator, and associated digital data. An integrated image-based geographical information system supports processing requirements.

NASA's small spacecraft technology initiative _Clark_ spacecraft

NASA Astrophysics Data System (ADS)

Hayduk, Robert J.; Scott, Walter S.; Walberg, Gerald D.; Butts, James J.; Starr, Richard D.

1996-11-01

The Small Satellite Technology Initiative (SSTI) is a National Aeronautics and Space Administration (NASA) program to demonstrate smaller, high technology satellites constructed rapidly and less expensively. Under SSTI, NASA funded the development of "Clark," a high technology demonstration satellite to provide 3-m resolution panchromatic and 15-m resolution multispectral images, as well as collect atmospheric constituent and cosmic x-ray data. The 690-Ib. satellite, to be launched in early 1997, will be in a 476 km, circular, sun-synchronous polar orbit. This paper describes the program objectives, the technical characteristics of the sensors and satellite, image processing, archiving and distribution. Data archiving and distribution will be performed by NASA Stennis Space Center and by the EROS Data Center, Sioux Falls, South Dakota, USA.

a New Object-Based Framework to Detect Shodows in High-Resolution Satellite Imagery Over Urban Areas

NASA Astrophysics Data System (ADS)

Tatar, N.; Saadatseresht, M.; Arefi, H.; Hadavand, A.

2015-12-01

In this paper a new object-based framework to detect shadow areas in high resolution satellite images is proposed. To produce shadow map in pixel level state of the art supervised machine learning algorithms are employed. Automatic ground truth generation based on Otsu thresholding on shadow and non-shadow indices is used to train the classifiers. It is followed by segmenting the image scene and create image objects. To detect shadow objects, a majority voting on pixel-based shadow detection result is designed. GeoEye-1 multi-spectral image over an urban area in Qom city of Iran is used in the experiments. Results shows the superiority of our proposed method over traditional pixel-based, visually and quantitatively.

Land use change detection based on multi-date imagery from different satellite sensor systems

NASA Technical Reports Server (NTRS)

Stow, Douglas A.; Collins, Doretta; Mckinsey, David

1990-01-01

An empirical study is conducted to assess the accuracy of land use change detection using satellite image data acquired ten years apart by sensors with differing spatial resolutions. The primary goals of the investigation were to (1) compare standard change detection methods applied to image data of varying spatial resolution, (2) assess whether to transform the raster grid of the higher resolution image data to that of the lower resolution raster grid or vice versa in the registration process, (3) determine if Landsat/Thermatic Mapper or SPOT/High Resolution Visible multispectral data provide more accurate detection of land use changes when registered to historical Landsat/MSS data. It is concluded that image ratioing of multisensor, multidate satellite data produced higher change detection accuracies than did principal components analysis, and that it is useful as a land use change enhancement method.

Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the South Bamyan mineral district in Afghanistan

USGS Publications Warehouse

Davis, Philip A.; Davis, Philip A.

2013-01-01

The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the South Bamyan mineral district, which has areas with a spectral reflectance anomaly that require field investigation. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA,2006,2007, 2008),but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such, the DS products match JAXA criteria for value added products, which are not copyrighted, according to the ALOS end-user license agreement. The selection criteria for the satellite imagery used in our mosaics were images having (1) the highest solar-elevation angles (near summer solstice) and (2) the least cloud, cloud-shadow, and snow cover. The multispectral and panchromatic data were orthorectified with ALOS satellite ephemeris data, a process which is not as accurate as orthorectification using digital elevation models (DEMs); however, the ALOS processing center did not have a precise DEM. As a result, the multispectral and panchromatic image pairs were generally not well registered to the surface and not coregistered well enough to perform resolution enhancement on the multispectral data. Therefore, it was necessary to (1) register the 10-m AVNIR multispectral imagery to a well-controlled Landsat image base, (2) mosaic the individual multispectral images into a single image of the entire area of interest, (3) register each panchromatic image to the registered multispectral image base, and (4) mosaic the individual panchromatic images into a single image of the entire area of interest. The two image-registration steps were facilitated using an automated control-point algorithm developed by the USGS that allows image coregistration to within one picture element. Before rectification, the multispectral and panchromatic images were converted to radiance values and then to relative-reflectance values using the methods described in Davis (2006). Mosaicking the multispectral or panchromatic images started with the image with the highest sun-elevation angle and the least atmospheric scattering, which was treated as the standard image. The band-reflectance values of all other multispectral or panchromatic images within the area were sequentially adjusted to that of the standard image by determining band-reflectance correspondence between overlapping images using linear least-squares analysis. The resolution of the multispectral image mosaic was then increased to that of the panchromatic image mosaic using the SPARKLE logic, which is described in Davis (2006). Each of the four-band images within the resolution-enhanced image mosaic was individually subjected to a local-area histogram stretch algorithm (described in Davis, 2007), which stretches each band's picture element based on the digital values of all picture elements within a 500-m radius. The final databases, which are provided in this DS, are three-band, color-composite images of the local-area-enhanced, natural-color data (the blue, green, and red wavelength bands) and color-infrared data (the green, red, and near-infrared wavelength bands). All image data were initially projected and maintained in Universal Transverse Mercator (UTM) map projection using the target area's local zone (42 for South Bamyan) and the WGS84 datum. The final image mosaics for the South Bamyan area are provided as embedded geotiff images, which can be read and used by most geographic information system (GIS) and image-processing software. The tiff world files (tfw) are provided, even though they are generally not needed for most software to read an embedded geotiff image.

The Effectiveness of Hydrothermal Alteration Mapping based on Hyperspectral Data in Tropical Region

NASA Astrophysics Data System (ADS)

Muhammad, R. R. D.; Saepuloh, A.

2016-09-01

Hyperspectral remote sensing could be used to characterize targets at earth's surface based on their spectra. This capability is useful for mapping and characterizing the distribution of host rocks, alteration assemblages, and minerals. Contrary to the multispectral sensors, the hyperspectral identifies targets with high spectral resolution. The Wayang Windu Geothermal field in West Java, Indonesia was selected as the study area due to the existence of surface manifestation and dense vegetation environment. Therefore, the effectiveness of hyperspectral remote sensing in tropical region was targeted as the study objective. The Spectral Angle Mapper (SAM) method was used to detect the occurrence of clay minerals spatially from Hyperion data. The SAM references of reflectance spectra were obtained from field observation at altered materials. To calculate the effectiveness of hyperspectral data, we used multispectral data from Landsat-8. The comparison method was conducted by comparing the SAM's rule images from Hyperion and Landsat-8, resulting that hyperspectral was more accurate than multispectral data. Hyperion SAM's rule images showed lower value compared to Landsat-8, the significant number derived from using Hyperion was about 24% better. This inferred that the hyperspectral remote sensing is preferable for mineral mapping even though vegetation covered study area.

Multispectral and hyperspectral measurements of soldier's camouflage equipment

NASA Astrophysics Data System (ADS)

Kastek, Mariusz; Piątkowski, Tadeusz; Dulski, Rafal; Chamberland, Martin; Lagueux, Philippe; Farley, Vincent

2012-06-01

In today's electro-optic warfare era, it is more than vital for one nation's defense to possess the most advanced measurement and signature intelligence (MASINT) capabilities. This is critical to gain a strategic advantage in the planning of the military operations and deployments. The thermal infrared region of the electromagnetic spectrum is a key region that is exploited for infrared reconnaissance and surveillance missions. The Military University of Technology has conducted an intensive measurement campaign of various soldier's camouflage devices in the scope of building a database of infrared signatures. One of today's key technologies required to perform signature measurements has become infrared hyperspectral and broadband/multispectral imaging sensors. The Telops Hyper-Cam LW product represents a unique commercial offering with outstanding performances and versatility for the collection of hyperspectral infrared images. The Hyper-Cam allows for the infrared imagery of a target (320 × 256 pixels) at a very high spectral resolution (down to 0.25 cm-1). Moreover, the Military University of Technology has made use of a suite of scientific grade commercial infrared cameras to further measure and assess the targets from a broadband/multispectral perspective. The experiment concept and measurement results are presented in this paper.

A Comparative Study of Landsat TM and SPOT HRG Images for Vegetation Classification in the Brazilian Amazon.

PubMed

Lu, Dengsheng; Batistella, Mateus; de Miranda, Evaristo E; Moran, Emilio

2008-01-01

Complex forest structure and abundant tree species in the moist tropical regions often cause difficulties in classifying vegetation classes with remotely sensed data. This paper explores improvement in vegetation classification accuracies through a comparative study of different image combinations based on the integration of Landsat Thematic Mapper (TM) and SPOT High Resolution Geometric (HRG) instrument data, as well as the combination of spectral signatures and textures. A maximum likelihood classifier was used to classify the different image combinations into thematic maps. This research indicated that data fusion based on HRG multispectral and panchromatic data slightly improved vegetation classification accuracies: a 3.1 to 4.6 percent increase in the kappa coefficient compared with the classification results based on original HRG or TM multispectral images. A combination of HRG spectral signatures and two textural images improved the kappa coefficient by 6.3 percent compared with pure HRG multispectral images. The textural images based on entropy or second-moment texture measures with a window size of 9 pixels × 9 pixels played an important role in improving vegetation classification accuracy. Overall, optical remote-sensing data are still insufficient for accurate vegetation classifications in the Amazon basin.

Lineshape test on overlapped transitions (R9F1, R9F2) of the 2v3 band of 12CH4 by frequency-stabilized cavity ring-down spectroscopy

NASA Astrophysics Data System (ADS)

Yang, L.; Lin, H.; Plimmer, M. D.; Feng, X. J.; Zhang, J. T.

2018-05-01

The performances of a multi-spectral fit for the spectra of pressure-broadened overlapping lines (R9F1, R9F2) of 12CH4 in binary mixtures with N2 were studied by applying different lineshape models, from the simplest Voigt profile (VP) to the Harmann-Tran profile (HTP). Line-mixing was approximated in the first order in the spectral fits. Data were acquired using a high-resolution cavity ring-down spectrometer of minimum detectable absorption coefficient of 2.8 × 10-12 cm-1. The lines were observed with a signal-to-noise ratio of 19 365 for pressures from 5 to 40 kPa. The study reveals that the multi-spectral fits using the HTP and the speed-dependent Nelkin-Ghatak profile (SDNGP) yield the best among all tested. The two models gave the maximum relative residuals of less than 0.065 %. All things considered, the HTP and the SDNGP appear to be the most reliable models for treating the present case of multi-spectral fitting of unresolved dual-component spectra.

A Comparative Study of Landsat TM and SPOT HRG Images for Vegetation Classification in the Brazilian Amazon

PubMed Central

Lu, Dengsheng; Batistella, Mateus; de Miranda, Evaristo E.; Moran, Emilio

2009-01-01

Complex forest structure and abundant tree species in the moist tropical regions often cause difficulties in classifying vegetation classes with remotely sensed data. This paper explores improvement in vegetation classification accuracies through a comparative study of different image combinations based on the integration of Landsat Thematic Mapper (TM) and SPOT High Resolution Geometric (HRG) instrument data, as well as the combination of spectral signatures and textures. A maximum likelihood classifier was used to classify the different image combinations into thematic maps. This research indicated that data fusion based on HRG multispectral and panchromatic data slightly improved vegetation classification accuracies: a 3.1 to 4.6 percent increase in the kappa coefficient compared with the classification results based on original HRG or TM multispectral images. A combination of HRG spectral signatures and two textural images improved the kappa coefficient by 6.3 percent compared with pure HRG multispectral images. The textural images based on entropy or second-moment texture measures with a window size of 9 pixels × 9 pixels played an important role in improving vegetation classification accuracy. Overall, optical remote-sensing data are still insufficient for accurate vegetation classifications in the Amazon basin. PMID:19789716

The Importance of Chaos and Lenticulae on Europa for the JIMO Mission

NASA Technical Reports Server (NTRS)

Spaun, Nicole A.

2003-01-01

The Galileo Solid State Imaging (SSI) experiment provided high-resolution images of Europa's surface allowing identification of surface features barely distinguishable at Voyager's resolution. SSI revealed the visible pitting on Europa's surface to be due to large disrupted features, chaos, and smaller sub-circular patches, lenticulae. Chaos features contain a hummocky matrix material and commonly contain dislocated blocks of ridged plains. Lenticulae are morphologically interrelated and can be divided into three classes: domes, spots, and micro-chaos. Domes are broad, upwarped features that generally do not disrupt the texture of the ridged plains. Spots are areas of low albedo that are generally smooth in texture compared to other units. Micro-chaos are disrupted features with a hummocky matrix material, resembling that observed within chaos regions. Chaos and lenticulae are ubiquitous in the SSI regional map observations, which average approximately 200 meters per pixel (m/pxl) in resolution, and appear in several of the ultra-high resolution, i.e., better than 50 m/pxl, images of Europa as well. SSI also provided a number of multi-spectral observations of chaos and lenticulae. Using this dataset we have undertaken a thorough study of the morphology, size, spacing, stratigraphy, and color of chaos and lenticulae to determine their properties and evaluate models of their formation. Geological mapping indicates that chaos and micro-chaos have a similar internal morphology of in-situ degradation suggesting that a similar process was operating during their formation. The size distribution denotes a dominant size of 4-8 km in diameter for features containing hummocky material (i.e., chaos and micro-chaos). Results indicate a dominant spacing of 15 - 36 km apart. Chaos and lenticulae are generally among the youngest features stratigraphically observed on the surface, suggesting a recent change in resurfacing style. Also, the reddish non-icy materials on Europa's surface have high concentrations in many chaos and lenticulae features. Nonetheless, a complete global map of the distribution of chaos and lenticulae is not possible with the SSI dataset. Only <20% of the surface has been imaged at 200 m/pxl or better resolution, mostly of the near-equatorial regions. Color and ultra-high-res images have much less surface coverage. Thus we suggest that full global imaging of Europa at 200 m/pxl or better resolution, preferably in multi-spectral wavelengths, should be a high priority for the JIMO mission.

Whole-body and multispectral photoacoustic imaging of adult zebrafish

NASA Astrophysics Data System (ADS)

Huang, Na; Xi, Lei

2016-10-01

Zebrafish is a top vertebrate model to study developmental biology and genetics, and it is becoming increasingly popular for studying human diseases due to its high genome similarity to that of humans and the optical transparency in embryonic stages. However, it becomes difficult for pure optical imaging techniques to volumetric visualize the internal organs and structures of wild-type zebrafish in juvenile and adult stages with excellent resolution and penetration depth. Even with the establishment of mutant lines which remain transparent over the life cycle, it is still a challenge for pure optical imaging modalities to image the whole body of adult zebrafish with micro-scale resolution. However, the method called photoacoustic imaging that combines all the advantages of the optical imaging and ultrasonic imaging provides a new way to image the whole body of the zebrafish. In this work, we developed a non-invasive photoacoustic imaging system with optimized near-infrared illumination and cylindrical scanning to image the zebrafish. The lateral and axial resolution yield to 80 μm and 600 μm, respectively. Multispectral strategy with wavelengths from 690 nm to 930 nm was employed to image various organs inside the zebrafish. From the reconstructed images, most major organs and structures inside the body can be precisely imaged. Quantitative and statistical analysis of absorption for organs under illumination with different wavelengths were carried out.

Screening photoswitching properties of synthesized BODIPY-based fluorophores for multispectral superresolution microscopy (MSSRM) (Conference Presentation)

NASA Astrophysics Data System (ADS)

Bittel, Amy M.; Saldivar, Isaac S.; Nan, Xiaolin; Gibbs, Summer L.

2016-02-01

Single-molecule localization microscopy (SMLM) utilizes photoswitchable fluorophores to detect biological entities with 10-20 nm resolution. Multispectral superresolution microscopy (MSSRM) extends SMLM functionality by improving its spectral resolution up to 5 fold facilitating imaging of multicomponent cellular structures or signaling pathways. Current commercial fluorophores are not ideal for MSSRM as they are not designed to photoswitch and do not adequately cover the visible and far-red spectral regions required for MSSRM imaging. To obtain optimal MSSRM spatial and spectral resolution, fluorophores with narrow emission spectra and controllable photoswitching properties are necessary. Herein, a library of BODIPY-based fluorophores was synthesized and characterized to create optimal photoswitchable fluorophores for MSSRM. BODIPY was chosen as the core structure as it is photostable, has high quantum yield, and controllable photoswitching. The BODIPY core was modified through the addition of various aromatic moieties, resulting in a spectrally diverse library. Photoswitching properties were characterized using a novel polyvinyl alcohol (PVA) based film methodology to isolate single molecules. The PVA film methodology enabled photoswitching assessment without the need for protein conjugation, greatly improving screening efficiency of the BODIPY library. Additionally, image buffer conditions were optimized for the BODIPY-based fluorophores through systematic testing of oxygen scavenger systems, redox components, and additives. Through screening the photoswitching properties of BODIPY-based compounds in PVA films with optimized imaging buffer we identified novel fluorophores well suited for SMLM and MSSRM.

Multispectral imaging determination of pigment concentration profiles in meat

NASA Astrophysics Data System (ADS)

Sáenz Gamasa, Carlos; Hernández Salueña, Begoña; Alberdi Odriozola, Coro; Alfonso Ábrego, Santiago; Berrogui Arizu, Miguel; Diñeiro Rubial, José Manuel

2006-01-01

The possibility of using multispectral techniques to determine the concentration profiles of myoglobin derivatives as a function of the distance to the meat surface during meat oxygenation is demonstrated. Reduced myoglobin (Mb) oxygenated oxymyoglobin (MbO II) and oxidized Metmyoglobin (MMb) concentration profiles are determined with a spatial resolutions better than of 0.01235 mm/pixel. Pigment concentrations are calculated using (K/S) ratios at isobestic points (474, 525, 572 and 610 nm) of the three forms of myoglobin pigments. This technique greatly improves previous methods, based on visual determination of pigment layers by their color, which allowed only estimations of pigment layer position and width. The multispectral technique avoids observer and illumination related bias in the pigment layer determination.

Observation of SO2 degassing at Stromboli volcano using a hyperspectral thermal infrared imager

NASA Astrophysics Data System (ADS)

Smekens, Jean-François; Gouhier, Mathieu

2018-05-01

Thermal infrared (TIR) imaging is a common tool for the monitoring of volcanic activity. Broadband cameras with increasing sampling frequency give great insight into the physical processes taking place during effusive and explosive event, while Fourier transform infrared (FTIR) methods provide high resolution spectral information used to assess the composition of volcanic gases but are often limited to a single point of interest. Continuing developments in detector technology have given rise to a new class of hyperspectral imagers combining the advantages of both approaches. In this work, we present the results of our observations of volcanic activity at Stromboli volcano with a ground-based imager, the Telops Hyper-Cam LW, when used to detect emissions of sulfur dioxide (SO2) produced at the vent, with data acquired at Stromboli volcano (Italy) in early October of 2015. We have developed an innovative technique based on a curve-fitting algorithm to quickly extract spectral information from high-resolution datasets, allowing fast and reliable identification of SO2. We show in particular that weak SO2 emissions, such as inter-eruptive gas puffing, can be easily detected using this technology, even with poor weather conditions during acquisition (e.g., high relative humidity, presence of fog and/or ash). Then, artificially reducing the spectral resolution of the instrument, we recreated a variety of commonly used multispectral configurations to examine the efficiency of four qualitative SO2 indicators based on simple Brightness Temperature Difference (BTD). Our results show that quickly changing conditions at the vent - including but not limited to the presence of summit fog - render the establishment of meaningful thresholds for BTD indicators difficult. Building on those results, we propose recommendations on the use of multispectral imaging for SO2 monitoring and routine measurements from ground-based instruments.

Tracking stormwater discharge plumes and water quality of the Tijuana River with multispectral aerial imagery

NASA Astrophysics Data System (ADS)

Svejkovsky, Jan; Nezlin, Nikolay P.; Mustain, Neomi M.; Kum, Jamie B.

2010-04-01

Spatial-temporal characteristics and environmental factors regulating the behavior of stormwater runoff from the Tijuana River in southern California were analyzed utilizing very high resolution aerial imagery, and time-coincident environmental and bacterial sampling data. Thirty nine multispectral aerial images with 2.1-m spatial resolution were collected after major rainstorms during 2003-2008. Utilizing differences in color reflectance characteristics, the ocean surface was classified into non-plume waters and three components of the runoff plume reflecting differences in age and suspended sediment concentrations. Tijuana River discharge rate was the primary factor regulating the size of the freshest plume component and its shorelong extensions to the north and south. Wave direction was found to affect the shorelong distribution of the shoreline-connected fresh plume components much more strongly than wind direction. Wave-driven sediment resuspension also significantly contributed to the size of the oldest plume component. Surf zone bacterial samples collected near the time of each image acquisition were used to evaluate the contamination characteristics of each plume component. The bacterial contamination of the freshest plume waters was very high (100% of surf zone samples exceeded California standards), but the oldest plume areas were heterogeneous, including both polluted and clean waters. The aerial imagery archive allowed study of river runoff characteristics on a plume component level, not previously done with coarser satellite images. Our findings suggest that high resolution imaging can quickly identify the spatial extents of the most polluted runoff but cannot be relied upon to always identify the entire polluted area. Our results also indicate that wave-driven transport is important in distributing the most contaminated plume areas along the shoreline.

Assessing carotid atherosclerosis by fiber-optic multispectral photoacoustic tomography

NASA Astrophysics Data System (ADS)

Hui, Jie; Li, Rui; Wang, Pu; Phillips, Evan; Bruning, Rebecca; Liao, Chien-Sheng; Sturek, Michael; Goergen, Craig J.; Cheng, Ji-Xin

2015-03-01

Atherosclerotic plaque at the carotid bifurcation is the underlying cause of the majority of ischemic strokes. Noninvasive imaging and quantification of the compositional changes preceding gross anatomic changes within the arterial wall is essential for diagnosis of disease. Current imaging modalities such as duplex ultrasound, computed tomography, positron emission tomography are limited by the lack of compositional contrast and the detection of flow-limiting lesions. Although high-resolution magnetic resonance imaging has been developed to characterize atherosclerotic plaque composition, its accessibility for wide clinical use is limited. Here, we demonstrate a fiber-based multispectral photoacoustic tomography system for excitation of lipids and external acoustic detection of the generated ultrasound. Using sequential ultrasound imaging of ex vivo preparations we achieved ~2 cm imaging depth and chemical selectivity for assessment of human arterial plaques. A multivariate curve resolution alternating least squares analysis method was applied to resolve the major chemical components, including intravascular lipid, intramuscular fat, and blood. These results show the promise of detecting carotid plaque in vivo through esophageal fiber-optic excitation of lipids and external acoustic detection of the generated ultrasound. This imaging system has great potential for serving as a point-ofcare device for early diagnosis of carotid artery disease in the clinic.

Selected configuration tradeoffs of contour optical instruments

NASA Astrophysics Data System (ADS)

Warren, J.; Strohbehn, K.; Murchie, S.; Fort, D.; Reynolds, E.; Heyler, G.; Peacock, K.; Boldt, J.; Darlington, E.; Hayes, J.; Henshaw, R.; Izenberg, N.; Kardian, C.; Lees, J.; Lohr, D.; Mehoke, D.; Schaefer, E.; Sholar, T.; Spisz, T.; Willey, C.; Veverka, J.; Bell, J.; Cochran, A.

2003-01-01

The Comet Nucleus Tour (CONTOUR) is a low-cost NASA Discovery mission designed to conduct three close flybys of comet nuclei. Selected configuration tradeoffs conducted to balance science requirements with low mission cost are reviewed. The tradeoffs discussed focus on the optical instruments and related spacecraft considerations. Two instruments are under development. The CONTOUR Forward Imager (CFI) is designed to perform optical navigation, moderate resolution nucleus/jet imaging, and imaging of faint molecular emission bands in the coma. The CONTOUR Remote Imager and Spectrometer (CRISP) is designed to obtain high-resolution multispectral images of the nucleus, conduct spectral mapping of the nucleus surface, and provide a backup optical navigation capability. Tradeoffs discussed are: (1) the impact on the optical instruments of not using reaction wheels on the spacecraft, (2) the improved performance and simplification gained by implementing a dedicated star tracker instead of including this function in CFI, (3) the improved flexibility and robustness of switching to a low frame rate tracker for CRISP, (4) the improved performance and simplification of replacing a visible imaging spectrometer by enhanced multispectral imaging in CRISP, and (5) the impact on spacecraft resources of these and other tradeoffs.

Early Results from the Odyssey THEMIS Investigation

NASA Technical Reports Server (NTRS)

Christensen, Philip R.; Bandfield, Joshua L.; Bell, James F., III; Hamilton, Victoria E.; Ivanov, Anton; Jakosky, Bruce M.; Kieffer, Hugh H.; Lane, Melissa D.; Malin, Michael C.; McConnochie, Timothy

2003-01-01

The Thermal Emission Imaging System (THEMIS) began studying the surface and atmosphere of Mars in February, 2002 using thermal infrared (IR) multi-spectral imaging between 6.5 and 15 m, and visible/near-IR images from 450 to 850 nm. The infrared observations continue a long series of spacecraft observations of Mars, including the Mariner 6/7 Infrared Spectrometer, the Mariner 9 Infrared Interferometer Spectrometer (IRIS), the Viking Infrared Thermal Mapper (IRTM) investigations, the Phobos Termoscan, and the Mars Global Surveyor Thermal Emission Spectrometer (MGS TES). The THEMIS investigation's specific objectives are to: (1) determine the mineralogy of localized deposits associated with hydrothermal or sub-aqueous environments, and to identify future landing sites likely to represent these environments; (2) search for thermal anomalies associated with active sub-surface hydrothermal systems; (3) study small-scale geologic processes and landing site characteristics using morphologic and thermophysical properties; (4) investigate polar cap processes at all seasons; and (5) provide a high spatial resolution link to the global hyperspectral mineral mapping from the TES investigation. THEMIS provides substantially higher spatial resolution IR multi-spectral images to complement TES hyperspectral (143-band) global mapping, and regional visible imaging at scales intermediate between the Viking and MGS cameras.

Unmanned Aerial System (UAS)-based phenotyping of soybean using multi-sensor data fusion and extreme learning machine

NASA Astrophysics Data System (ADS)

Maimaitijiang, Maitiniyazi; Ghulam, Abduwasit; Sidike, Paheding; Hartling, Sean; Maimaitiyiming, Matthew; Peterson, Kyle; Shavers, Ethan; Fishman, Jack; Peterson, Jim; Kadam, Suhas; Burken, Joel; Fritschi, Felix

2017-12-01

Estimating crop biophysical and biochemical parameters with high accuracy at low-cost is imperative for high-throughput phenotyping in precision agriculture. Although fusion of data from multiple sensors is a common application in remote sensing, less is known on the contribution of low-cost RGB, multispectral and thermal sensors to rapid crop phenotyping. This is due to the fact that (1) simultaneous collection of multi-sensor data using satellites are rare and (2) multi-sensor data collected during a single flight have not been accessible until recent developments in Unmanned Aerial Systems (UASs) and UAS-friendly sensors that allow efficient information fusion. The objective of this study was to evaluate the power of high spatial resolution RGB, multispectral and thermal data fusion to estimate soybean (Glycine max) biochemical parameters including chlorophyll content and nitrogen concentration, and biophysical parameters including Leaf Area Index (LAI), above ground fresh and dry biomass. Multiple low-cost sensors integrated on UASs were used to collect RGB, multispectral, and thermal images throughout the growing season at a site established near Columbia, Missouri, USA. From these images, vegetation indices were extracted, a Crop Surface Model (CSM) was advanced, and a model to extract the vegetation fraction was developed. Then, spectral indices/features were combined to model and predict crop biophysical and biochemical parameters using Partial Least Squares Regression (PLSR), Support Vector Regression (SVR), and Extreme Learning Machine based Regression (ELR) techniques. Results showed that: (1) For biochemical variable estimation, multispectral and thermal data fusion provided the best estimate for nitrogen concentration and chlorophyll (Chl) a content (RMSE of 9.9% and 17.1%, respectively) and RGB color information based indices and multispectral data fusion exhibited the largest RMSE 22.6%; the highest accuracy for Chl a + b content estimation was obtained by fusion of information from all three sensors with an RMSE of 11.6%. (2) Among the plant biophysical variables, LAI was best predicted by RGB and thermal data fusion while multispectral and thermal data fusion was found to be best for biomass estimation. (3) For estimation of the above mentioned plant traits of soybean from multi-sensor data fusion, ELR yields promising results compared to PLSR and SVR in this study. This research indicates that fusion of low-cost multiple sensor data within a machine learning framework can provide relatively accurate estimation of plant traits and provide valuable insight for high spatial precision in agriculture and plant stress assessment.

Multispectral scanner system for ERTS: Four band scanner system. Volume 2: Engineering model panoramic pictures and engineering tests

NASA Technical Reports Server (NTRS)

1972-01-01

This document is Volume 2 of three volumes of the Final Report for the four band Multispectral Scanner System (MSS). The results are contained of an analysis of pictures of actual outdoor scenes imaged by the engineering model MSS for spectral response, resolution, noise, and video correction. Also included are the results of engineering tests on the MSS for reflectance and saturation from clouds. Finally, two panoramic pictures of Yosemite National Park are provided.

Mapping soil types from multispectral scanner data.

NASA Technical Reports Server (NTRS)

Kristof, S. J.; Zachary, A. L.

1971-01-01

Multispectral remote sensing and computer-implemented pattern recognition techniques were used for automatic ?mapping' of soil types. This approach involves subjective selection of a set of reference samples from a gray-level display of spectral variations which was generated by a computer. Each resolution element is then classified using a maximum likelihood ratio. Output is a computer printout on which the researcher assigns a different symbol to each class. Four soil test areas in Indiana were experimentally examined using this approach, and partially successful results were obtained.

Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

USGS Publications Warehouse

Davis, Philip A.

2012-01-01

The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This DS consists of the locally enhanced ALOS image mosaics for each of the 24 mineral project areas (referred to herein as areas of interest), whose locality names, locations, and main mineral occurrences are shown on the index map of Afghanistan (fig. 1). ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420-500 nanometer, nm), green (520-600 nm), red (610-690 nm), and near-infrared (760-890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520-770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency, but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such, the DS products match JAXA criteria for value added products, which are not copyrighted, according to the ALOS end-user license agreement. The selection criteria for the satellite imagery used in our mosaics were images having (1) the highest solar-elevation angles (near summer solstice) and (2) the least cloud, cloud-shadow, and snow cover. The multispectral and panchromatic data were orthorectified with ALOS satellite ephemeris data, a process which is not as accurate as orthorectification using digital elevation models (DEMs); however, the ALOS processing center did not have a precise DEM. As a result, the multispectral and panchromatic image pairs were generally not well registered to the surface and not coregistered well enough to perform resolution enhancement on the multispectral data. Therefore, it was necessary to (1) register the 10-m AVNIR multispectral imagery to a well-controlled Landsat image base, (2) mosaic the individual multispectral images into a single image of the entire area of interest, (3) register each panchromatic image to the registered multispectral image base, and (4) mosaic the individual panchromatic images into a single image of the entire area of interest. The two image-registration steps were facilitated using an automated control-point algorithm developed by the USGS that allows image coregistration to within one picture element. PRISM image orthorectification for one-half of the target areas was performed by the Alaska Satellite Facility, applying its photogrammetric software to PRISM stereo images with vertical control points obtained from the digital elevation database produced by the Shuttle Radar Topography Mission (Farr and others, 2007) and horizontal adjustments based on a controlled Landsat image base (Davis, 2006). Before rectification, the multispectral and panchromatic images were converted to radiance values and then to relative-reflectance values using the methods described in Davis (2006). Mosaicking the multispectral or panchromatic images started with the image with the highest sun-elevation angle and the least atmospheric scattering, which was treated as the standard image. The band-reflectance values of all other multispectral or panchromatic images within the area were sequentially adjusted to that of the standard image by determining band-reflectance correspondence between overlapping images using linear least-squares analysis. The resolution of the multispectral image mosaic was then increased to that of the panchromatic image mosaic using SPARKLE logic, which is described in Davis (2006). Each of the four-band images within each resolution-enhanced image mosaic was individually subjected to a local-area histogram stretch algorithm (described in Davis, 2007), which stretches each band's picture element based on the digital values of all picture elements within a specified radius that was usually 500 m. The final databases, which are provided in this DS, are three-band, color-composite images of the local-area-enhanced, natural-color data (the blue, green, and red wavelength bands) and color-infrared data (the green, red, and near-infrared wavelength bands). All image data were initially projected and maintained in Universal Transverse Mercator (UTM) map projection using the target area's local zone (either 41 or 42) and the WGS84 datum. Most final image mosaics were subdivided into overlapping tiles or quadrants because of the large size of the target areas. The image tiles (or quadrants) for each area of interest are provided as embedded geotiff images, which can be read and used by most geographic information system (GIS) and image-processing software. The tiff world files (tfw) are provided, even though they are generally not needed for most software to read an embedded geotiff image. Approximately one-half of the study areas have at least one subarea designated for detailed field investigations; the subareas were extracted from the area's image mosaic and are provided as separate embedded geotiff images.

Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Dusar-Shaida mineral district in Afghanistan: Chapter I in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

USGS Publications Warehouse

Davis, Philip A.; Arko, Scott A.; Harbin, Michelle L.

2012-01-01

The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Dusar-Shaida mineral district, which has copper and tin deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA,2008), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such, the DS products match JAXA criteria for value added products, which are not copyrighted, according to the ALOS end-user license agreement. The selection criteria for the satellite imagery used in our mosaics were images having (1) the highest solar-elevation angles (near summer solstice) and (2) the least cloud, cloud-shadow, and snow cover. The multispectral and panchromatic data were orthorectified with ALOS satellite ephemeris data, a process which is not as accurate as orthorectification using digital elevation models (DEMs); however, the ALOS processing center did not have a precise DEM. As a result, the multispectral and panchromatic image pairs were generally not well registered to the surface and not coregistered well enough to perform resolution enhancement on the multispectral data. For this particular area, PRISM image orthorectification was performed by the Alaska Satellite Facility, applying its photogrammetric software to PRISM stereo images with vertical control points obtained from the digital elevation database produced by the Shuttle Radar Topography Mission (Farr and others, 2007) and horizontal adjustments based on a controlled Landsat image base (Davis, 2006). The 10-m AVNIR multispectral imagery was then coregistered to the orthorectified PRISM images and individual multispectral and panchromatic images were mosaicked into single images of the entire area of interest. The image coregistration was facilitated using an automated control-point algorithm developed by the USGS that allows image coregistration to within one picture element. Before rectification, the multispectral and panchromatic images were converted to radiance values and then to relative-reflectance values using the methods described in Davis (2006). Mosaicking the multispectral or panchromatic images started with the image with the highest sun-elevation angle and the least atmospheric scattering, which was treated as the standard image. The band-reflectance values of all other multispectral or panchromatic images within the area were sequentially adjusted to that of the standard image by determining band-reflectance correspondence between overlapping images using linear least-squares analysis. The resolution of the multispectral image mosaic was then increased to that of the panchromatic image mosaic using the SPARKLE logic, which is described in Davis (2006). Each of the four-band images within the resolution-enhanced image mosaic was individually subjected to a local-area histogram stretch algorithm (described in Davis, 2007), which stretches each band’ picture element based on the digital values of all picture elements within a 315-m radius. The final databases, which are provided in this DS, are three-band, color-composite images of the local-area-enhanced, natural-color data (the blue, green, and red wavelength bands) and color-infrared data (the green, red, and near-infrared wavelength bands). All image data were initially projected and maintained in Universal Transverse Mercator (UTM) map projection using the target area’ local zone (41 for Dusar-Shaida) and the WGS84 datum. The final image mosaics were subdivided into eight overlapping tiles or quadrants because of the large size of the target area. The eight image tiles (or quadrants) for the Dusar-Shaida area are provided as embedded geotiff images, which can be read and used by most geographic information system (GIS) and image-processing software. The tiff world files (tfw) are provided, even though they are generally not needed for most software to read an embedded geotiff image. Within the Dusar-Shaida study area, three subareas were designated for detailed field investigations (that is, the Dahana-Misgaran, Kaftar VMS, and Shaida subareas); these subareas were extracted from the area’ image mosaic and are provided as separate embedded geotiff images.

Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Kundalyan mineral district in Afghanistan: Chapter H in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

USGS Publications Warehouse

Davis, Philip A.; Cagney, Laura E.; Arko, Scott A.; Harbin, Michelle L.

2012-01-01

The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Kundalyan mineral district, which has porphyry copper and gold deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA,2008), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such, the DS products match JAXA criteria for value added products, which are not copyrighted, according to the ALOS end-user license agreement. The selection criteria for the satellite imagery used in our mosaics were images having (1) the highest solar-elevation angles (near summer solstice) and (2) the least cloud, cloud-shadow, and snow cover. The multispectral and panchromatic data were orthorectified with ALOS satellite ephemeris data, a process which is not as accurate as orthorectification using digital elevation models (DEMs); however, the ALOS processing center did not have a precise DEM. As a result, the multispectral and panchromatic image pairs were generally not well registered to the surface and not coregistered well enough to perform resolution enhancement on the multispectral data. For this particular area, PRISM image orthorectification was performed by the Alaska Satellite Facility, applying its photogrammetric software to PRISM stereo images with vertical control points obtained from the digital elevation database produced by the Shuttle Radar Topography Mission (Farr and others, 2007) and horizontal adjustments based on a controlled Landsat image base (Davis, 2006). The 10-m AVNIR multispectral imagery was then coregistered to the orthorectified PRISM images and individual multispectral and panchromatic images were mosaicked into single images of the entire area of interest. The image coregistration was facilitated using an automated control-point algorithm developed by the USGS that allows image coregistration to within one picture element. Before rectification, the multispectral and panchromatic images were converted to radiance values and then to relative-reflectance values using the methods described in Davis (2006). Mosaicking the multispectral or panchromatic images started with the image with the highest sun-elevation angle and the least atmospheric scattering, which was treated as the standard image. The band-reflectance values of all other multispectral or panchromatic images within the area were sequentially adjusted to that of the standard image by determining band-reflectance correspondence between overlapping images using linear least-squares analysis. The resolution of the multispectral image mosaic was then increased to that of the panchromatic image mosaic using the SPARKLE logic, which is described in Davis (2006). Each of the four-band images within the resolution-enhanced image mosaic was individually subjected to a local-area histogram stretch algorithm (described in Davis, 2007), which stretches each band’s picture element based on the digital values of all picture elements within a 500-m radius. The final databases, which are provided in this DS, are three-band, color-composite images of the local-area-enhanced, natural-color data (the blue, green, and red wavelength bands) and color-infrared data (the green, red, and near-infrared wavelength bands). All image data were initially projected and maintained in Universal Transverse Mercator (UTM) map projection using the target area’s local zone (42 for Kundalyan) and the WGS84 datum. The final image mosaics were subdivided into five overlapping tiles or quadrants because of the large size of the target area. The five image tiles (or quadrants) for the Kundalyan area are provided as embedded geotiff images, which can be read and used by most geographic information system (GIS) and image-processing software. The tiff world files (tfw) are provided, even though they are generally not needed for most software to read an embedded geotiff image. Within the Kundalyan study area, three subareas were designated for detailed field investigations (that is, the Baghawan-Garangh, Charsu-Ghumbad, and Kunag Skarn subareas); these subareas were extracted from the area’s image mosaic and are provided as separate embedded geotiff images.

Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Herat mineral district in Afghanistan: Chapter T in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

USGS Publications Warehouse

Davis, Philip A.; Arko, Scott A.; Harbin, Michelle L.

2013-01-01

The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Herat mineral district, which has barium and limestone deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA,2007,2008,2009), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such, the DS products match JAXA criteria for value added products, which are not copyrighted, according to the ALOS end-user license agreement. The selection criteria for the satellite imagery used in our mosaics were images having (1) the highest solar-elevation angles (near summer solstice) and (2) the least cloud, cloud-shadow, and snow cover. The multispectral and panchromatic data were orthorectified with ALOS satellite ephemeris data, a process which is not as accurate as orthorectification using digital elevation models (DEMs); however, the ALOS processing center did not have a precise DEM. As a result, the multispectral and panchromatic image pairs were generally not well registered to the surface and not coregistered well enough to perform resolution enhancement on the multispectral data. For this particular area, PRISM image orthorectification was performed by the Alaska Satellite Facility, applying its photogrammetric software to PRISM stereo images with vertical control points obtained from the digital elevation database produced by the Shuttle Radar Topography Mission (Farr and others, 2007) and horizontal adjustments based on a controlled Landsat image base (Davis, 2006). The 10-m AVNIR multispectral imagery was then coregistered to the orthorectified PRISM images and individual multispectral and panchromatic images were mosaicked into single images of the entire area of interest. The image coregistration was facilitated using an automated control-point algorithm developed by the USGS that allows image coregistration to within one picture element. Before rectification, the multispectral and panchromatic images were converted to radiance values and then to relative-reflectance values using the methods described in Davis (2006). Mosaicking the multispectral or panchromatic images started with the image with the highest sun-elevation angle and the least atmospheric scattering, which was treated as the standard image. The band-reflectance values of all other multispectral or panchromatic images within the area were sequentially adjusted to that of the standard image by determining band-reflectance correspondence between overlapping images using linear least-squares analysis. The resolution of the multispectral image mosaic was then increased to that of the panchromatic image mosaic using the SPARKLE logic, which is described in Davis (2006). Each of the four-band images within the resolution-enhanced image mosaic was individually subjected to a local-area histogram stretch algorithm (described in Davis, 2007), which stretches each band's picture element based on the digital values of all picture elements within a 1,000-m radius. The final databases, which are provided in this DS, are three-band, color-composite images of the local-area-enhanced, natural-color data (the blue, green, and red wavelength bands) and color-infrared data (the green, red, and near-infrared wavelength bands). All image data were initially projected and maintained in Universal Transverse Mercator (UTM) map projection using the target area's local zone (41 for Herat) and the WGS84 datum. The final image mosaics were subdivided into eight overlapping tiles or quadrants because of the large size of the target area. The eight image tiles (or quadrants) for the Herat area are provided as embedded geotiff images, which can be read and used by most geographic information system (GIS) and image-processing software. The tiff world files (tfw) are provided, even though they are generally not needed for most software to read an embedded geotiff image. Within the Herat study area, one subarea was designated for detailed field investigations (that is, the Barium-Limestone subarea); this subarea was extracted from the area's image mosaic and is provided as separate embedded geotiff images.

Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Badakhshan mineral district in Afghanistan: Chapter F in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

USGS Publications Warehouse

Davis, Philip A.; Arko, Scott A.; Harbin, Michelle L.

2012-01-01

The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Badakhshan mineral district, which has gold deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420-500 nanometer, nm), green (520-600 nm), red (610-690 nm), and near-infrared (760-890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520-770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency ((c)JAXA,2007,2008), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such, the DS products match JAXA criteria for value added products, which are not copyrighted, according to the ALOS end-user license agreement. The selection criteria for the satellite imagery used in our mosaics were images having (1) the highest solar-elevation angles (near summer solstice) and (2) the least cloud, cloud-shadow, and snow cover. The multispectral and panchromatic data were orthorectified with ALOS satellite ephemeris data, a process which is not as accurate as orthorectification using digital elevation models (DEMs); however, the ALOS processing center did not have a precise DEM. As a result, the multispectral and panchromatic image pairs were generally not well registered to the surface and not coregistered well enough to perform resolution enhancement on the multispectral data. For this particular area, PRISM image orthorectification was performed by the Alaska Satellite Facility, applying its photogrammetric software to PRISM stereo images with vertical control points obtained from the digital elevation database produced by the Shuttle Radar Topography Mission (Farr and others, 2007) and horizontal adjustments based on a controlled Landsat image base (Davis, 2006). The 10-m AVNIR multispectral imagery was then coregistered to the orthorectified PRISM images and individual multispectral and panchromatic images were mosaicked into single images of the entire area of interest. The image coregistration was facilitated using an automated control-point algorithm developed by the USGS that allows image coregistration to within one picture element. Before rectification, the multispectral and panchromatic images were converted to radiance values and then to relative-reflectance values using the methods described in Davis (2006). Mosaicking the multispectral or panchromatic images started with the image with the highest sun-elevation angle and the least atmospheric scattering, which was treated as the standard image. The band-reflectance values of all other multispectral or panchromatic images within the area were sequentially adjusted to that of the standard image by determining band-reflectance correspondence between overlapping images using linear least-squares analysis. The resolution of the multispectral image mosaic was then increased to that of the panchromatic image mosaic using the SPARKLE logic, which is described in Davis (2006). Each of the four-band images within the resolution-enhanced image mosaic was individually subjected to a local-area histogram stretch algorithm (described in Davis, 2007), which stretches each band’s picture element based on the digital values of all picture elements within a 500-m radius. The final databases, which are provided in this DS, are three-band, color-composite images of the local-area-enhanced, natural-color data (the blue, green, and red wavelength bands) and color-infrared data (the green, red, and near-infrared wavelength bands). All image data were initially projected and maintained in Universal Transverse Mercator (UTM) map projection using the target area’s local zone (42 for Badakhshan) and the WGS84 datum. The final image mosaics were subdivided into six overlapping tiles or quadrants because of the large size of the target area. The six image tiles (or quadrants) for the Badakhshan area are provided as embedded geotiff images, which can be read and used by most geographic information system (GIS) and image-processing software. The tiff world files (tfw) are provided, even though they are generally not needed for most software to read an embedded geotiff image. Within the Badakhshan study area, three subareas were designated for detailed field investigations (that is, the Bharak, Fayz-Abad, and Ragh subareas); these subareas were extracted from the area’s image mosaic and are provided as separate embedded geotiff images.

Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Kharnak-Kanjar mineral district in Afghanistan: Chapter K in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

USGS Publications Warehouse

Davis, Philip A.; Arko, Scott A.; Harbin, Michelle L.

2012-01-01

The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Kharnak-Kanjar mineral district, which has mercury deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA,2007,2008,2010), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such, the DS products match JAXA criteria for value added products, which are not copyrighted, according to the ALOS end-user license agreement. The selection criteria for the satellite imagery used in our mosaics were images having (1) the highest solar-elevation angles (near summer solstice) and (2) the least cloud, cloud-shadow, and snow cover. The multispectral and panchromatic data were orthorectified with ALOS satellite ephemeris data, a process which is not as accurate as orthorectification using digital elevation models (DEMs); however, the ALOS processing center did not have a precise DEM. As a result, the multispectral and panchromatic image pairs were generally not well registered to the surface and not coregistered well enough to perform resolution enhancement on the multispectral data. For this particular area, PRISM image orthorectification was performed by the Alaska Satellite Facility, applying its photogrammetric software to PRISM stereo images with vertical control points obtained from the digital elevation database produced by the Shuttle Radar Topography Mission (Farr and others, 2007) and horizontal adjustments based on a controlled Landsat image base (Davis, 2006). The 10-m AVNIR multispectral imagery was then coregistered to the orthorectified PRISM images and individual multispectral and panchromatic images were mosaicked into single images of the entire area of interest. The image coregistration was facilitated using an automated control-point algorithm developed by the USGS that allows image coregistration to within one picture element. Before rectification, the multispectral and panchromatic images were converted to radiance values and then to relative-reflectance values using the methods described in Davis (2006). Mosaicking the multispectral or panchromatic images started with the image with the highest sun-elevation angle and the least atmospheric scattering, which was treated as the standard image. The band-reflectance values of all other multispectral or panchromatic images within the area were sequentially adjusted to that of the standard image by determining band-reflectance correspondence between overlapping images using linear least-squares analysis. The resolution of the multispectral image mosaic was then increased to that of the panchromatic image mosaic using the SPARKLE logic, which is described in Davis (2006). Each of the four-band images within the resolution-enhanced image mosaic was individually subjected to a local-area histogram stretch algorithm (described in Davis, 2007), which stretches each band's picture element based on the digital values of all picture elements within a 1,000-m radius. The final databases, which are provided in this DS, are three-band, color-composite images of the local-area-enhanced, natural-color data (the blue, green, and red wavelength bands) and color-infrared data (the green, red, and near-infrared wavelength bands). All image data were initially projected and maintained in Universal Transverse Mercator (UTM) map projection using the target area's local zone (41 for Kharnak-Kanjar) and the WGS84 datum. The final image mosaics were subdivided into eight overlapping tiles or quadrants because of the large size of the target area. The eight image tiles (or quadrants) for the Kharnak-Kanjar area are provided as embedded geotiff images, which can be read and used by most geographic information system (GIS) and image-processing software. The tiff world files (tfw) are provided, even though they are generally not needed for most software to read an embedded geotiff image. Within the Kharnak-Kanjar study area, three subareas were designated for detailed field investigations (that is, the Koh-e-Katif Passaband, Panjshah-Mullayan, and Sahebdad-Khanjar subareas); these subareas were extracted from the area's image mosaic and are provided as separate embedded geotiff images.

Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Haji-Gak mineral district in Afghanistan: Chapter C in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

USGS Publications Warehouse

Davis, Philip A.; Cagney, Laura E.; Arko, Scott A.; Harbin, Michelle L.

2012-01-01

The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Haji-Gak mineral district, which has iron ore deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420-500 nanometer, nm), green (520-600 nm), red (610-690 nm), and near-infrared (760-890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520-770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency ((c)JAXA,2006,2007), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such, the DS products match JAXA criteria for value added products, which are not copyrighted, according to the ALOS end-user license agreement. The selection criteria for the satellite imagery used in our mosaics were images having (1) the highest solar-elevation angles (near summer solstice) and (2) the least cloud, cloud-shadow, and snow cover. The multispectral and panchromatic data were orthorectified with ALOS satellite ephemeris data, a process which is not as accurate as orthorectification using digital elevation models (DEMs); however, the ALOS processing center did not have a precise DEM. As a result, the multispectral and panchromatic image pairs were generally not well registered to the surface and not coregistered well enough to perform resolution enhancement on the multispectral data. For this particular area, PRISM image orthorectification was performed by the Alaska Satellite Facility, applying its photogrammetric software to PRISM stereo images with vertical control points obtained from the digital elevation database produced by the Shuttle Radar Topography Mission (Farr and others, 2007) and horizontal adjustments based on a controlled Landsat image base (Davis, 2006). The 10-m AVNIR multispectral imagery was then co-registered to the orthorectified PRISM images and individual multispectral and panchromatic images were mosaicked into single images of the entire area of interest. The image-coregistration was facilitated using an automated control-point algorithm developed by the USGS that allows image coregistration to within one picture element. Before rectification, the multispectral and panchromatic images were converted to radiance values and then to relative-reflectance values using the methods described in Davis (2006). Mosaicking the multispectral or panchromatic images started with the image with the highest sun-elevation angle and the least atmospheric scattering, which was treated as the standard image. The band-reflectance values of all other multispectral or panchromatic images within the area were sequentially adjusted to that of the standard image by determining band-reflectance correspondence between overlapping images using linear least-squares analysis. The resolution of the multispectral image mosaic was then increased to that of the panchromatic image mosaic using the SPARKLE logic, which is described in Davis (2006). Each of the four-band images within the resolution-enhanced image mosaic was individually subjected to a local-area histogram stretch algorithm (described in Davis, 2007), which stretches each band's picture element based on the digital values of all picture elements within a 500-m radius. The final databases, which are provided in this DS, are three-band, color-composite images of the local-area-enhanced, natural-color data (the blue, green, and red wavelength bands) and color-infrared data (the green, red, and near-infrared wavelength bands). All image data were initially projected and maintained in Universal Transverse Mercator (UTM) map projection using the target area's local zone (42 for Haji-Gak) and the WGS84 datum. The final image mosaics were subdivided into three overlapping tiles or quadrants because of the large size of the target area. The three image tiles (or quadrants) for the Haji-Gak area are provided as embedded geotiff images, which can be read and used by most geographic information system (GIS) and image-processing software. The tiff world files (tfw) are provided, even though they are generally not needed for most software to read an embedded geotiff image. Within the Haji-Gak study area, three subareas were designated for detailed field investigations (that is, the Haji-Gak Prospect, Farenjal, and NE Haji-Gak subareas); these subareas were extracted from the area's image mosaic and are provided as separate embedded geotiff images.

Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Aynak mineral district in Afghanistan: Chapter E in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

USGS Publications Warehouse

Davis, Philip A.; Cagney, Laura E.; Arko, Scott A.; Harbin, Michelle L.

2012-01-01

The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Aynak mineral district, which has copper deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency ((c)JAXA,2008,2010), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such, the DS products match JAXA criteria for value added products, which are not copyrighted, according to the ALOS end-user license agreement. The selection criteria for the satellite imagery used in our mosaics were images having (1) the highest solar-elevation angles (near summer solstice) and (2) the least cloud, cloud-shadow, and snow cover. The multispectral and panchromatic data were orthorectified with ALOS satellite ephemeris data, a process which is not as accurate as orthorectification using digital elevation models (DEMs); however, the ALOS processing center did not have a precise DEM. As a result, the multispectral and panchromatic image pairs were generally not well registered to the surface and not coregistered well enough to perform resolution enhancement on the multispectral data. For this particular area, PRISM image orthorectification was performed by the Alaska Satellite Facility, applying its photogrammetric software to PRISM stereo images with vertical control points obtained from the digital elevation database produced by the Shuttle Radar Topography Mission (Farr and others, 2007) and horizontal adjustments based on a controlled Landsat image base (Davis, 2006). The 10-m AVNIR multispectral imagery was then coregistered to the orthorectified PRISM images and individual multispectral and panchromatic images were mosaicked into single images of the entire area of interest. The image coregistration was facilitated using an automated control-point algorithm developed by the USGS that allows image coregistration to within one picture element. Before rectification, the multispectral and panchromatic images were converted to radiance values and then to relative-reflectance values using the methods described in Davis (2006). Mosaicking the multispectral or panchromatic images started with the image with the highest sun-elevation angle and the least atmospheric scattering, which was treated as the standard image. The band-reflectance values of all other multispectral or panchromatic images within the area were sequentially adjusted to that of the standard image by determining band-reflectance correspondence between overlapping images using linear least-squares analysis. The resolution of the multispectral image mosaic was then increased to that of the panchromatic image mosaic using the SPARKLE logic, which is described in Davis (2006). Each of the four-band images within the resolution-enhanced image mosaic was individually subjected to a local-area histogram stretch algorithm (described in Davis, 2007), which stretches each band’s picture element based on the digital values of all picture elements within a 315-m radius. The final databases, which are provided in this DS, are three-band, color-composite images of the local-area-enhanced, natural-color data (the blue, green, and red wavelength bands) and color-infrared data (the green, red, and near-infrared wavelength bands). All image data were initially projected and maintained in Universal Transverse Mercator (UTM) map projection using the target area’s local zone (42 for Aynak) and the WGS84 datum. The final image mosaics were subdivided into four overlapping tiles or quadrants because of the large size of the target area. The four image tiles (or quadrants) for the Aynak area are provided as embedded geotiff images, which can be read and used by most geographic information system (GIS) and image-processing software. The tiff world files (tfw) are provided, even though they are generally not needed for most software to read an embedded geotiff image. Within the Aynak study area, five subareas were designated for detailed field investigations (that is, the Bakhel-Charwaz, Kelaghey-Kakhay, Kharuti-Dawrankhel, Logar Valley, and Yagh-Darra/Gul-Darra subareas); these subareas were extracted from the area’s image mosaic and are provided as separate embedded geotiff images.

Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Ghunday-Achin mineral district in Afghanistan, in Davis, P.A, compiler, Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

USGS Publications Warehouse

Davis, Philip A.; Arko, Scott A.; Harbin, Michelle L.; Davis, Philip A.

2013-01-01

The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Ghunday-Achin mineral district, which has magnesite and talc deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA,2008,2009), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such, the DS products match JAXA criteria for value added products, which are not copyrighted, according to the ALOS end-user license agreement. The selection criteria for the satellite imagery used in our mosaics were images having (1) the highest solar-elevation angles (near summer solstice) and (2) the least cloud, cloud-shadow, and snow cover. The multispectral and panchromatic data were orthorectified with ALOS satellite ephemeris data, a process which is not as accurate as orthorectification using digital elevation models (DEMs); however, the ALOS processing center did not have a precise DEM. As a result, the multispectral and panchromatic image pairs were generally not well registered to the surface and not coregistered well enough to perform resolution enhancement on the multispectral data. For this particular area, PRISM image orthorectification was performed by the Alaska Satellite Facility, applying its photogrammetric software to PRISM stereo images with vertical control points obtained from the digital elevation database produced by the Shuttle Radar Topography Mission (Farr and others, 2007) and horizontal adjustments based on a controlled Landsat image base (Davis, 2006). The 10-m AVNIR multispectral imagery was then coregistered to the orthorectified PRISM images and individual multispectral and panchromatic images were mosaicked into single images of the entire area of interest. The image coregistration was facilitated using an automated control-point algorithm developed by the USGS that allows image coregistration to within one picture element. Before rectification, the multispectral and panchromatic images were converted to radiance values and then to relative-reflectance values using the methods described in Davis (2006). Mosaicking the multispectral or panchromatic images started with the image with the highest sun-elevation angle and the least atmospheric scattering, which was treated as the standard image. The band-reflectance values of all other multispectral or panchromatic images within the area were sequentially adjusted to that of the standard image by determining band-reflectance correspondence between overlapping images using linear least-squares analysis. The resolution of the multispectral image mosaic was then increased to that of the panchromatic image mosaic using the SPARKLE logic, which is described in Davis (2006). Each of the four-band images within the resolution-enhanced image mosaic was individually subjected to a local-area histogram stretch algorithm (described in Davis, 2007), which stretches each band’s picture element based on the digital values of all picture elements within a 500-m radius. The final databases, which are provided in this DS, are three-band, color-composite images of the local-area-enhanced, natural-color data (the blue, green, and red wavelength bands) and color-infrared data (the green, red, and near-infrared wavelength bands). All image data were initially projected and maintained in Universal Transverse Mercator (UTM) map projection using the target area’s local zone (42 for Ghunday-Achin) and the WGS84 datum. The final image mosaics were subdivided into six overlapping tiles or quadrants because of the large size of the target area. The six image tiles (or quadrants) for the Ghunday-Achin area are provided as embedded geotiff images, which can be read and used by most geographic information system (GIS) and image-processing software. The tiff world files (tfw) are provided, even though they are generally not needed for most software to read an embedded geotiff image. Within the Ghunday-Achin study area, two subareas were designated for detailed field investigations (that is, the Achin-Magnesite and Ghunday-Mamahel subareas); these subareas were extracted from the area’s image mosaic and are provided as separate embedded geotiff images.

Detecting Uniform Areas for Vicarious Calibration using Landsat TM Imagery: A Study using the Arabian and Saharan Deserts

NASA Technical Reports Server (NTRS)

Hilbert, Kent; Pagnutti, Mary; Ryan, Robert; Zanoni, Vicki

2002-01-01

This paper discusses a method for detecting spatially uniform sites need for radiometric characterization of remote sensing satellites. Such information is critical for scientific research applications of imagery having moderate to high resolutions (<30-m ground sampling distance (GSD)). Previously published literature indicated that areas with the African Saharan and Arabian deserts contained extremely uniform sites with respect to spatial characteristics. We developed an algorithm for detecting site uniformity and applied it to orthorectified Landsat Thematic Mapper (TM) imagery over eight uniform regions of interest. The algorithm's results were assessed using both medium-resolution (30-m GSD) Landsat 7 ETM+ and fine-resolution (<5-m GSD) IKONOS multispectral data collected over sites in Libya and Mali. Fine-resolution imagery over a Libyan site exhibited less than 1 percent nonuniformity. The research shows that Landsat TM products appear highly useful for detecting potential calibration sites for system characterization. In particular, the approach detected spatially uniform regions that frequently occur at multiple scales of observation.

Simulating Visible/Infrared Imager Radiometer Suite Normalized Difference Vegetation Index Data Using Hyperion and MODIS

NASA Technical Reports Server (NTRS)

Ross, Kenton W.; Russell, Jeffrey; Ryan, Robert E.

2006-01-01

The success of MODIS (the Moderate Resolution Imaging Spectrometer) in creating unprecedented, timely, high-quality data for vegetation and other studies has created great anticipation for data from VIIRS (the Visible/Infrared Imager Radiometer Suite). VIIRS will be carried onboard the joint NASA/Department of Defense/National Oceanic and Atmospheric Administration NPP (NPOESS (National Polar-orbiting Operational Environmental Satellite System) Preparatory Project). Because the VIIRS instruments will have lower spatial resolution than the current MODIS instruments 400 m versus 250 m at nadir for the channels used to generate Normalized Difference Vegetation Index data, scientists need the answer to this question: how will the change in resolution affect vegetation studies? By using simulated VIIRS measurements, this question may be answered before the VIIRS instruments are deployed in space. Using simulated VIIRS products, the U.S. Department of Agriculture and other operational agencies can then modify their decision support systems appropriately in preparation for receipt of actual VIIRS data. VIIRS simulations and validations will be based on the ART (Application Research Toolbox), an integrated set of algorithms and models developed in MATLAB(Registerd TradeMark) that enables users to perform a suite of simulations and statistical trade studies on remote sensing systems. Specifically, the ART provides the capability to generate simulated multispectral image products, at various scales, from high spatial hyperspectral and/or multispectral image products. The ART uses acquired ( real ) or synthetic datasets, along with sensor specifications, to create simulated datasets. For existing multispectral sensor systems, the simulated data products are used for comparison, verification, and validation of the simulated system s actual products. VIIRS simulations will be performed using Hyperion and MODIS datasets. The hyperspectral and hyperspatial properties of Hyperion data will be used to produce simulated MODIS and VIIRS products. Hyperion-derived MODIS data will be compared with near-coincident MODIS collects to validate both spectral and spatial synthesis, which will ascertain the accuracy of converting from MODIS to VIIRS. MODIS-derived VIIRS data is needed for global coverage and for the generation of time series for regional and global investigations. These types of simulations will have errors associated with aliasing for some scene types. This study will help quantify these errors and will identify cases where high-quality, MODIS-derived VIIRS data will be available.

Design and analysis of optical systems for the Stanford/MSFC Multi-Spectral Solar Telescope Array

NASA Astrophysics Data System (ADS)

Hadaway, James B.; Johnson, R. Barry; Hoover, Richard B.; Lindblom, Joakim F.; Walker, Arthur B. C., Jr.

1989-07-01

This paper reports on the design and the theoretical ray trace analysis of the optical systems which will comprise the primary imaging components for the Stanford/MSFC Multi-Spectral Solar Telescope Array (MSSTA). This instrument is being developed for ultra-high resolution investigations of the sun from a sounding rocket. Doubly reflecting systems of sphere-sphere, ellipsoid-sphere (Dall-Kirkham), paraboloid-hyperboloid (Cassegrain), and hyperboloid-hyperboloid (Ritchey-Chretien) configurations were analyzed. For these mirror systems, ray trace analysis was performed and through-focus spot diagrams, point spread function plots, and geometrical and diffraction MTFs were generated. The results of these studies are presented along with the parameters of the Ritchey-Chretien optical system selected for the MSSTA flight. The payload, which incorporates seven of these Ritchey-Chretien systems, is now being prepared for launch in late September 1989.

Analyses of the cloud contents of multispectral imagery from LANDSAT 2: Mesoscale assessments of cloud and rainfall over the British Isles

NASA Technical Reports Server (NTRS)

Barrett, E. C.; Grant, C. K. (Principal Investigator)

1977-01-01

The author has identified the following significant results. It was demonstrated that satellites with sufficiently high resolution capability in the visible region of the electromagnetic spectrum could be used to check the accuracy of estimates of total cloud amount assessed subjectively from the ground, and to reveal areas of performance in which corrections should be made. It was also demonstrated that, in middle latitude in summer, cloud shadow may obscure at least half as much again of the land surface covered by an individual LANDSAT frame as the cloud itself. That proportion would increase with latitude and/or time of year towards the winter solstice. Analyses of sample multispectral images for six different categories of clouds in summer revealed marked differences between the reflectance characteristics of cloud fields in the visible/near infrared region of the spectrum.

Design and analysis of optical systems for the Stanford/MSFC Multi-Spectral Solar Telescope Array

NASA Technical Reports Server (NTRS)

Hadaway, James B.; Johnson, R. Barry; Hoover, Richard B.; Lindblom, Joakim F.; Walker, Arthur B. C., Jr.

1989-01-01

This paper reports on the design and the theoretical ray trace analysis of the optical systems which will comprise the primary imaging components for the Stanford/MSFC Multi-Spectral Solar Telescope Array (MSSTA). This instrument is being developed for ultra-high resolution investigations of the sun from a sounding rocket. Doubly reflecting systems of sphere-sphere, ellipsoid-sphere (Dall-Kirkham), paraboloid-hyperboloid (Cassegrain), and hyperboloid-hyperboloid (Ritchey-Chretien) configurations were analyzed. For these mirror systems, ray trace analysis was performed and through-focus spot diagrams, point spread function plots, and geometrical and diffraction MTFs were generated. The results of these studies are presented along with the parameters of the Ritchey-Chretien optical system selected for the MSSTA flight. The payload, which incorporates seven of these Ritchey-Chretien systems, is now being prepared for launch in late September 1989.

Lunar and Planetary Science XXXV: Lunar Remote Sensing: Seeing the Big Picture

NASA Technical Reports Server (NTRS)

2004-01-01

The session "Lunar Remote Sensing: Seeing the Big Picture" contained the following reports:Approaches for Approximating Topography in High Resolution, Multispectral Data; Verification of Quality and Compatibility for the Newly Calibrated Clementine NIR Data Set; Near Infrared Spectral Properties of Selected Nearside and Farside Sites ; Global Comparisons of Mare Volcanism from Clementine Near-Infrared Data; Testing the Relation Between UVVIS Color and TiO2 Composition in the Lunar Maria; Color Reflectance Trends in the Mare: Implications for Mapping Iron with Multispectral Images ; The Composition of the Lunar Megaregolith: Some Initial Results from Global Mapping; Global Images of Mg-Number Derived from Clementine Data; The Origin of Lunar Crater Rays; Properties of Lunar Crater Ejecta from New 70-cm Radar Observations ; Permanent Sunlight at the Lunar North Pole; and ESA s SMART-1 Mission to the Moon: Goals, Status and First Results.

LANDSAT-4 MSS and Thematic Mapper data quality and information content analysis

NASA Technical Reports Server (NTRS)

Anuta, P.; Bartolucci, L.; Dean, E.; Lozano, F.; Malaret, E.; Mcgillem, C. D.; Valdes, J.; Valenzuela, C.

1984-01-01

LANDSAT-4 thematic mapper (TM) and multispectral scanner (MSS) data were analyzed to obtain information on data quality and information content. Geometric evaluations were performed to test band-to-band registration accuracy. Thematic mapper overall system resolution was evaluated using scene objects which demonstrated sharp high contrast edge responses. Radiometric evaluation included detector relative calibration, effects of resampling, and coherent noise effects. Information content evaluation was carried out using clustering, principal components, transformed divergence separability measure, and supervised classifiers on test data. A detailed spectral class analysis (multispectral classification) was carried out to compare the information content of the MSS and TM for a large number of scene classes. A temperature-mapping experiment was carried out for a cooling pond to test the quality of thermal-band calibration. Overall TM data quality is very good. The MSS data are noisier than previous LANDSAT results.

Development of a multispectral autoradiography using a coded aperture

NASA Astrophysics Data System (ADS)

Noto, Daisuke; Takeda, Tohoru; Wu, Jin; Lwin, Thet T.; Yu, Quanwen; Zeniya, Tsutomu; Yuasa, Tetsuya; Hiranaka, Yukio; Itai, Yuji; Akatsuka, Takao

2000-11-01

Autoradiography is a useful imaging technique to understand biological functions using tracers including radio isotopes (RI's). However, it is not easy to describe the distribution of different kinds of tracers simultaneously by conventional autoradiography using X-ray film or Imaging plate. Each tracer describes each corresponding biological function. Therefore, if we can simultaneously estimate distribution of different kinds of tracer materials, the multispectral autoradiography must be a quite powerful tool to better understand physiological mechanisms of organs. So we are developing a system using a solid state detector (SSD) with high energy- resolution. Here, we introduce an imaging technique with a coded aperture to get spatial and spectral information more efficiently. In this paper, the imaging principle is described, and its validity and fundamental property are discussed by both simulation and phantom experiments with RI's such as 201Tl, 99mTc, 67Ga, and 123I.

Surface temperature statistics over Los Angeles - The influence of land use

NASA Technical Reports Server (NTRS)

Dousset, Benedicte

1991-01-01

Surface temperature statistics from 84 NOAA AVHRR (Advanced Very High Resolution Radiometer) satellite images of the Los Angeles basin are interpreted as functions of the corresponding urban land-cover classified from a multispectral SPOT image. Urban heat islands observed in the temperature statistics correlate well with the distribution of industrial and fully built areas. Small cool islands coincide with highly watered parks and golf courses. There is a significant negative correlation between the afternoon surface temperature and a vegetation index computed from the SPOT image.

LANDSAT-4 Scientific Characterization: Early Results Symposium

NASA Technical Reports Server (NTRS)

1983-01-01

Radiometric calibration, geometric accuracy, spatial and spectral resolution, and image quality are examined for the thematic mapper and the multispectral band scanner on LANDSAT 4. Sensor performance is evaluated.

Smoothing and gap-filling of high resolution multi-spectral time series: Example of Landsat data

NASA Astrophysics Data System (ADS)

Vuolo, Francesco; Ng, Wai-Tim; Atzberger, Clement

2017-05-01

This paper introduces a novel methodology for generating 15-day, smoothed and gap-filled time series of high spatial resolution data. The approach is based on templates from high quality observations to fill data gaps that are subsequently filtered. We tested our method for one large contiguous area (Bavaria, Germany) and for nine smaller test sites in different ecoregions of Europe using Landsat data. Overall, our results match the validation dataset to a high degree of accuracy with a mean absolute error (MAE) of 0.01 for visible bands, 0.03 for near-infrared and 0.02 for short-wave-infrared. Occasionally, the reconstructed time series are affected by artefacts due to undetected clouds. Less frequently, larger uncertainties occur as a result of extended periods of missing data. Reliable cloud masks are highly warranted for making full use of time series.

An evaluation of simulated Thematic Mapper data and Landsat MSS data for discriminating suburban and regional land use and land cover

NASA Technical Reports Server (NTRS)

Toll, D. L.

1984-01-01

An airborne multispectral scanner, operating in the same spectral channels as the Landsat Thematic Mapper (TM), was used in a region east of Denver, CO, for a simulation test performed in the framework of using TM to discriminate the level I and level II classes. It is noted that at the 30-m spatial resolution of the Thematic Mapper Simulator (TMS) the overall discrimination for such classes as commercial/industrial land, rangeland, irrigated sod, irrigated alfalfa, and irrigated pasture was superior to that of the Landsat Multispectral Scanner, primarily due to four added spectral bands. For residential and other spectrally heterogeneous classes, however, the higher resolution of TMS resulted in increased variability within the class and a larger spectral overlap.

Multispectral and Panchromatic used Enhancement Resolution and Study Effective Enhancement on Supervised and Unsupervised Classification Land – Cover

NASA Astrophysics Data System (ADS)

Salman, S. S.; Abbas, W. A.

2018-05-01

The goal of the study is to support analysis Enhancement of Resolution and study effect on classification methods on bands spectral information of specific and quantitative approaches. In this study introduce a method to enhancement resolution Landsat 8 of combining the bands spectral of 30 meters resolution with panchromatic band 8 of 15 meters resolution, because of importance multispectral imagery to extracting land - cover. Classification methods used in this study to classify several lands -covers recorded from OLI- 8 imagery. Two methods of Data mining can be classified as either supervised or unsupervised. In supervised methods, there is a particular predefined target, that means the algorithm learn which values of the target are associated with which values of the predictor sample. K-nearest neighbors and maximum likelihood algorithms examine in this work as supervised methods. In other hand, no sample identified as target in unsupervised methods, the algorithm of data extraction searches for structure and patterns between all the variables, represented by Fuzzy C-mean clustering method as one of the unsupervised methods, NDVI vegetation index used to compare the results of classification method, the percent of dense vegetation in maximum likelihood method give a best results.

Creating Orthographically Rectified Satellite Multi-Spectral Imagery with High Resolution Digital Elevation Model from LiDAR: A Tutorial

DTIC Science & Technology

2014-08-15

challenges. ERDC develops innovative solutions in civil and military engineering, geospatial sciences, water resources, and environmental sciences for...GRL TR-14-1 iv Abstract Orthoimages are used to produce image- map products for navigation and planning, and serve as source data for advanced...resulting mosaic covers a wider area and contains less visible seams, which makes the map easier to understand. RPC replace the actual sensor model while

Multispectral glancing incidence X-ray telescope

NASA Technical Reports Server (NTRS)

Hoover, Richard B. (Inventor)

1990-01-01

A multispectral glancing incidence X-ray telescope is illustrated capable of broadband, high-resolution imaging of solar and stellar X-ray and extreme ultraviolet radiation sources which includes a primary optical system preferably of the Wolter I type having a primary mirror system (20, 22). The primary optical system further includes an optical axis (24) having a primary focus (F1) at which the incoming radiation is focused by the primary mirrors. A plurality of ellipsoidal mirrors (30a, 30b, 30cand 30d) are carried at an inclination to the optical axis behind the primary focus (F1). A rotating carrier (32) is provided on which the ellipsoidal mirrors are carried so that a desired one of the ellipsoidal mirrors may be selectively positioned in front of the incoming radiation beam (26). In the preferred embodiment, each of the ellipsoidal mirrors has an identical concave surface carrying a layered synthetic microstructure coating tailored to reflect a desired wavelength of 1.5 .ANG. or longer. Each of the identical ellipsoidal mirrors has a second focus (F2) at which a detector (16) is carried. Thus the different wavelength image is focused upon the detector irregardless of which mirror is positioned in front of the radiation beam. In this manner, a plurality of low wavelengths in a wavelength band generally less than 30 angstroms can be imaged with a high resolution.

Object-based locust habitat mapping using high-resolution multispectral satellite data in the southern Aral Sea basin

NASA Astrophysics Data System (ADS)

Navratil, Peter; Wilps, Hans

2013-01-01

Three different object-based image classification techniques are applied to high-resolution satellite data for the mapping of the habitats of Asian migratory locust (Locusta migratoria migratoria) in the southern Aral Sea basin, Uzbekistan. A set of panchromatic and multispectral Système Pour l'Observation de la Terre-5 satellite images was spectrally enhanced by normalized difference vegetation index and tasseled cap transformation and segmented into image objects, which were then classified by three different classification approaches: a rule-based hierarchical fuzzy threshold (HFT) classification method was compared to a supervised nearest neighbor classifier and classification tree analysis by the quick, unbiased, efficient statistical trees algorithm. Special emphasis was laid on the discrimination of locust feeding and breeding habitats due to the significance of this discrimination for practical locust control. Field data on vegetation and land cover, collected at the time of satellite image acquisition, was used to evaluate classification accuracy. The results show that a robust HFT classifier outperformed the two automated procedures by 13% overall accuracy. The classification method allowed a reliable discrimination of locust feeding and breeding habitats, which is of significant importance for the application of the resulting data for an economically and environmentally sound control of locust pests because exact spatial knowledge on the habitat types allows a more effective surveying and use of pesticides.

UAV remote sening for precision agriculture

NASA Astrophysics Data System (ADS)

Vigneau, Nathalie; Chéron, Corentin; Mainfroy, Florent; Faroux, Romain

2014-05-01

Airinov offers to farmers, scientists and experimenters (plant breeders, etc.) its technical skills about UAVs, cartography and agronomic remote sensing. The UAV is a 2-m-wingspan flying wing. It can carry away either a RGB camera or a multispectral sensor, which records reflectance in 4 spectral bands. The spectral characteristics of the sensor are modular. Each spectral band is comprised between 400 and 850 nm and the FWHM (Full Width at Half Maximum) is between 10 and 40 nm. The spatial resolution varies according to sensor, flying height and user needs from 15cm/px for multispectral sensor at 150m to 1.5cm/px for RGB camera at 50m. The flight is totally automatic thanks to on-board autopilot, IMU (Inertial Measurement Unit) and GPS. Data processing (unvignetting, mosaicking, correction in reflectance) leads to agronomic variables as LAI (Leaf Area Index) or chlorophyll content for barley, wheat, rape and maize as well as vegetation indices as NDVI (Normalized Difference Vegetation Index). Using these data, Airinov can product advices for farmers as nitrogen preconisation for rape. For scientists, Airinov offers trial plot monitoring by micro-plots vectorisation and numerical data exctraction micro-plot by micro-plot. This can lead to kinetic curve for LAI or NDVI to compare cover establishment for different genotypes for example. Airinov's system is a new way to monitor plots with a lot of data (biophysical or biochemical parameters) at high rate, high spatial resolution and high precision.

A comparison of multi-spectral, multi-angular, and multi-temporal remote sensing datasets for fractional shrub canopy mapping in Arctic Alaska

USGS Publications Warehouse

Selkowitz, D.J.

2010-01-01

Shrub cover appears to be increasing across many areas of the Arctic tundra biome, and increasing shrub cover in the Arctic has the potential to significantly impact global carbon budgets and the global climate system. For most of the Arctic, however, there is no existing baseline inventory of shrub canopy cover, as existing maps of Arctic vegetation provide little information about the density of shrub cover at a moderate spatial resolution across the region. Remotely-sensed fractional shrub canopy maps can provide this necessary baseline inventory of shrub cover. In this study, we compare the accuracy of fractional shrub canopy (> 0.5 m tall) maps derived from multi-spectral, multi-angular, and multi-temporal datasets from Landsat imagery at 30 m spatial resolution, Moderate Resolution Imaging SpectroRadiometer (MODIS) imagery at 250 m and 500 m spatial resolution, and MultiAngle Imaging Spectroradiometer (MISR) imagery at 275 m spatial resolution for a 1067 km2 study area in Arctic Alaska. The study area is centered at 69 ??N, ranges in elevation from 130 to 770 m, is composed primarily of rolling topography with gentle slopes less than 10??, and is free of glaciers and perennial snow cover. Shrubs > 0.5 m in height cover 2.9% of the study area and are primarily confined to patches associated with specific landscape features. Reference fractional shrub canopy is determined from in situ shrub canopy measurements and a high spatial resolution IKONOS image swath. Regression tree models are constructed to estimate fractional canopy cover at 250 m using different combinations of input data from Landsat, MODIS, and MISR. Results indicate that multi-spectral data provide substantially more accurate estimates of fractional shrub canopy cover than multi-angular or multi-temporal data. Higher spatial resolution datasets also provide more accurate estimates of fractional shrub canopy cover (aggregated to moderate spatial resolutions) than lower spatial resolution datasets, an expected result for a study area where most shrub cover is concentrated in narrow patches associated with rivers, drainages, and slopes. Including the middle infrared bands available from Landsat and MODIS in the regression tree models (in addition to the four standard visible and near-infrared spectral bands) typically results in a slight boost in accuracy. Including the multi-angular red band data available from MISR in the regression tree models, however, typically boosts accuracy more substantially, resulting in moderate resolution fractional shrub canopy estimates approaching the accuracy of estimates derived from the much higher spatial resolution Landsat sensor. Given the poor availability of snow and cloud-free Landsat scenes in many areas of the Arctic and the promising results demonstrated here by the MISR sensor, MISR may be the best choice for large area fractional shrub canopy mapping in the Alaskan Arctic for the period 2000-2009.

The impact of integrating WorldView-2 sensor and environmental variables in estimating plantation forest species aboveground biomass and carbon stocks in uMgeni Catchment, South Africa

NASA Astrophysics Data System (ADS)

Dube, Timothy; Mutanga, Onisimo

2016-09-01

Reliable and accurate mapping and extraction of key forest indicators of ecosystem development and health, such as aboveground biomass (AGB) and aboveground carbon stocks (AGCS) is critical in understanding forests contribution to the local, regional and global carbon cycle. This information is critical in assessing forest contribution towards ecosystem functioning and services, as well as their conservation status. This work aimed at assessing the applicability of the high resolution 8-band WorldView-2 multispectral dataset together with environmental variables in quantifying AGB and aboveground carbon stocks for three forest plantation species i.e. Eucalyptus dunii (ED), Eucalyptus grandis (EG) and Pinus taeda (PT) in uMgeni Catchment, South Africa. Specifically, the strength of the Worldview-2 sensor in terms of its improved imaging agilities is examined as an independent dataset and in conjunction with selected environmental variables. The results have demonstrated that the integration of high resolution 8-band Worldview-2 multispectral data with environmental variables provide improved AGB and AGCS estimates, when compared to the use of spectral data as an independent dataset. The use of integrated datasets yielded a high R2 value of 0.88 and RMSEs of 10.05 t ha-1 and 5.03 t C ha-1 for E. dunii AGB and carbon stocks; whereas the use of spectral data as an independent dataset yielded slightly weaker results, producing an R2 value of 0.73 and an RMSE of 18.57 t ha-1 and 09.29 t C ha-1. Similarly, high accurate results (R2 value of 0.73 and RMSE values of 27.30 t ha-1 and 13.65 t C ha-1) were observed from the estimation of inter-species AGB and carbon stocks. Overall, the findings of this work have shown that the integration of new generation multispectral datasets with environmental variables provide a robust toolset required for the accurate and reliable retrieval of forest aboveground biomass and carbon stocks in densely forested terrestrial ecosystems.

Characterization of Urban Landscape Using Super-Resolution UAS Data, Multiple Textural Scales and Data-Mining Techniques

NASA Astrophysics Data System (ADS)

Voss, M.; Blundell, B.

2015-12-01

Characterization of urban environments is a high priority for the U.S. Army as battlespaces have transitioned from the predominantly open spaces of the 20th century to urban areas where soldiers have reduced situational awareness due to the diversity and density of their surroundings. Creating high-resolution urban terrain geospatial information will improve mission planning and soldier effectiveness. In this effort, super-resolution true-color imagery was collected with an Altivan NOVA unmanned aerial system over the Muscatatuck Urban Training Center near Butlerville, Indiana on September 16, 2014. Multispectral texture analysis using different algorithms was conducted for urban surface characterization at a variety of scales. Training samples extracted from the true-color and texture images. These data were processed using a variety of meta-algorithms with a decision tree classifier to create a high-resolution urban features map. In addition to improving accuracy over traditional image classification methods, this technique allowed the determination of the most significant textural scales in creating urban terrain maps for tactical exploitation.

FFT-enhanced IHS transform method for fusing high-resolution satellite images

USGS Publications Warehouse

Ling, Y.; Ehlers, M.; Usery, E.L.; Madden, M.

2007-01-01

Existing image fusion techniques such as the intensity-hue-saturation (IHS) transform and principal components analysis (PCA) methods may not be optimal for fusing the new generation commercial high-resolution satellite images such as Ikonos and QuickBird. One problem is color distortion in the fused image, which causes visual changes as well as spectral differences between the original and fused images. In this paper, a fast Fourier transform (FFT)-enhanced IHS method is developed for fusing new generation high-resolution satellite images. This method combines a standard IHS transform with FFT filtering of both the panchromatic image and the intensity component of the original multispectral image. Ikonos and QuickBird data are used to assess the FFT-enhanced IHS transform method. Experimental results indicate that the FFT-enhanced IHS transform method may improve upon the standard IHS transform and the PCA methods in preserving spectral and spatial information. ?? 2006 International Society for Photogrammetry and Remote Sensing, Inc. (ISPRS).

Classification by Using Multispectral Point Cloud Data

NASA Astrophysics Data System (ADS)

Liao, C. T.; Huang, H. H.

2012-07-01

Remote sensing images are generally recorded in two-dimensional format containing multispectral information. Also, the semantic information is clearly visualized, which ground features can be better recognized and classified via supervised or unsupervised classification methods easily. Nevertheless, the shortcomings of multispectral images are highly depending on light conditions, and classification results lack of three-dimensional semantic information. On the other hand, LiDAR has become a main technology for acquiring high accuracy point cloud data. The advantages of LiDAR are high data acquisition rate, independent of light conditions and can directly produce three-dimensional coordinates. However, comparing with multispectral images, the disadvantage is multispectral information shortage, which remains a challenge in ground feature classification through massive point cloud data. Consequently, by combining the advantages of both LiDAR and multispectral images, point cloud data with three-dimensional coordinates and multispectral information can produce a integrate solution for point cloud classification. Therefore, this research acquires visible light and near infrared images, via close range photogrammetry, by matching images automatically through free online service for multispectral point cloud generation. Then, one can use three-dimensional affine coordinate transformation to compare the data increment. At last, the given threshold of height and color information is set as threshold in classification.

Multispectral and Textural Properties and Diversity of Soils in Gusev Crater and Meridiani Planum from Mars Exploration Rover Pancam and MI Data

NASA Astrophysics Data System (ADS)

Bell, J. F.; Fraeman, A. A.; Grossman, L.; Herkenhoff, K. E.; Sullivan, R. J.; Mer/Athena Science Team

2010-12-01

The Mars Exploration Rovers Spirit and Opportunity have enabled more than six and a half years of detailed, in situ field study of two specific landing sites and traverse paths within Gusev crater and Meridiani Planum, respectively. Much of the study has relied on high-resolution, multispectral imaging of fine-grained regolith components--the dust, sand, cobbles, clasts, and other components collectively referred to as "soil"--at both sites using the rovers' Panoramic Camera (Pancam) and Microscopic Imager (MI) imaging systems. As of early September 2010, the Pancam systems have acquired more than 1300 and 1000 "13 filter" multispectral imaging sequences of surfaces in Gusev and Meridiani, respectively, with each sequence consisting of co-located images at 11 unique narrowband wavelengths between 430 nm and 1009 nm and having a maximum spatial resolution of about 500 microns per pixel. The MI systems have acquired more than 5900 and 6500 monochromatic images, respectively, at about 31 microns per pixel scale. Pancam multispectral image cubes are calibrated to radiance factor (I/F, where I is the measured radiance and π*F is the incident solar irradiance) using observations of the onboard calibration targets, and then corrected to relative reflectance (assuming Lambertian photometric behavior) for comparison with laboratory rock and mineral measurements. Specifically, Pancam spectra can be used to detect the possible presence of some iron-bearing minerals (e.g., some ferric oxides/oxyhydroxides and pyroxenes) as well as structural water or OH in some hydrated alteration products, providing important inputs on the choice of targets for more quantitative compositional and mineralogic follow-up using the rover's other in situ and remote sensing analysis tools. Pancam 11-band spectra are being analyzed using a variety of standard as well as specifically-tailored analysis methods, including color ratio and band depth parameterizations, spectral similarity and principal components clustering, and simple visual inspection based on correlations with false color unit boundaries and textural variations seen in both Pancam and MI imaging. Approximately 20 distinct spectral classes of fine-grained surface components were identified at each site based on these methods. In this presentation we describe these spectral classes, their geologic and textural context and distribution based on supporting high-res MI and other Pancam imaging, and their potential compositional/mineralogic interpretations based on a variety of rover data sets.

Differentiating aquatic plant communities in a eutrophic river using hyperspectral and multispectral remote sensing

USGS Publications Warehouse

Tian, Y.Q.; Yu, Q.; Zimmerman, M.J.; Flint, S.; Waldron, M.C.

2010-01-01

This study evaluates the efficacy of remote sensing technology to monitor species composition, areal extent and density of aquatic plants (macrophytes and filamentous algae) in impoundments where their presence may violate water-quality standards. Multispectral satellite (IKONOS) images and more than 500 in situ hyperspectral samples were acquired to map aquatic plant distributions. By analyzing field measurements, we created a library of hyperspectral signatures for a variety of aquatic plant species, associations and densities. We also used three vegetation indices. Normalized Difference Vegetation Index (NDVI), near-infrared (NIR)-Green Angle Index (NGAI) and normalized water absorption depth (DH), at wavelengths 554, 680, 820 and 977 nm to differentiate among aquatic plant species composition, areal density and thickness in cases where hyperspectral analysis yielded potentially ambiguous interpretations. We compared the NDVI derived from IKONOS imagery with the in situ, hyperspectral-derived NDVI. The IKONOS-based images were also compared to data obtained through routine visual observations. Our results confirmed that aquatic species composition alters spectral signatures and affects the accuracy of remote sensing of aquatic plant density. The results also demonstrated that the NGAI has apparent advantages in estimating density over the NDVI and the DH. In the feature space of the three indices, 3D scatter plot analysis revealed that hyperspectral data can differentiate several aquatic plant associations. High-resolution multispectral imagery provided useful information to distinguish among biophysical aquatic plant characteristics. Classification analysis indicated that using satellite imagery to assess Lemna coverage yielded an overall agreement of 79% with visual observations and >90% agreement for the densest aquatic plant coverages. Interpretation of biophysical parameters derived from high-resolution satellite or airborne imagery should prove to be a valuable approach for assessing the effectiveness of management practices for controlling aquatic plant growth in inland waters, as well as for routine monitoring of aquatic plants in lakes and suitable lentic environments. ?? 2010 Blackwell Publishing Ltd.

Optimized lighting method of applying shaped-function signal for increasing the dynamic range of LED-multispectral imaging system

NASA Astrophysics Data System (ADS)

Yang, Xue; Hu, Yajia; Li, Gang; Lin, Ling

2018-02-01

This paper proposes an optimized lighting method of applying a shaped-function signal for increasing the dynamic range of light emitting diode (LED)-multispectral imaging system. The optimized lighting method is based on the linear response zone of the analog-to-digital conversion (ADC) and the spectral response of the camera. The auxiliary light at a higher sensitivity-camera area is introduced to increase the A/D quantization levels that are within the linear response zone of ADC and improve the signal-to-noise ratio. The active light is modulated by the shaped-function signal to improve the gray-scale resolution of the image. And the auxiliary light is modulated by the constant intensity signal, which is easy to acquire the images under the active light irradiation. The least square method is employed to precisely extract the desired images. One wavelength in multispectral imaging based on LED illumination was taken as an example. It has been proven by experiments that the gray-scale resolution and the accuracy of information of the images acquired by the proposed method were both significantly improved. The optimum method opens up avenues for the hyperspectral imaging of biological tissue.

Optimized lighting method of applying shaped-function signal for increasing the dynamic range of LED-multispectral imaging system.

PubMed

Yang, Xue; Hu, Yajia; Li, Gang; Lin, Ling

2018-02-01

This paper proposes an optimized lighting method of applying a shaped-function signal for increasing the dynamic range of light emitting diode (LED)-multispectral imaging system. The optimized lighting method is based on the linear response zone of the analog-to-digital conversion (ADC) and the spectral response of the camera. The auxiliary light at a higher sensitivity-camera area is introduced to increase the A/D quantization levels that are within the linear response zone of ADC and improve the signal-to-noise ratio. The active light is modulated by the shaped-function signal to improve the gray-scale resolution of the image. And the auxiliary light is modulated by the constant intensity signal, which is easy to acquire the images under the active light irradiation. The least square method is employed to precisely extract the desired images. One wavelength in multispectral imaging based on LED illumination was taken as an example. It has been proven by experiments that the gray-scale resolution and the accuracy of information of the images acquired by the proposed method were both significantly improved. The optimum method opens up avenues for the hyperspectral imaging of biological tissue.

Optimal attributes for the object based detection of giant reed in riparian habitats: A comparative study between Airborne High Spatial Resolution and WorldView-2 imagery

NASA Astrophysics Data System (ADS)

Fernandes, Maria Rosário; Aguiar, Francisca C.; Silva, João M. N.; Ferreira, Maria Teresa; Pereira, José M. C.

2014-10-01

Giant reed is an aggressive invasive plant of riparian ecosystems in many sub-tropical and warm-temperate regions, including Mediterranean Europe. In this study we tested a set of geometric, spectral and textural attributes in an object based image analysis (OBIA) approach to map giant reed invasions in riparian habitats. Bagging Classification and Regression Tree were used to select the optimal attributes and to build the classification rules sets. Mapping accuracy was performed using landscape metrics and the Kappa coefficient to compare the topographical and geometric similarity between the giant reed patches obtained with the OBIA map and with a validation map derived from on-screen digitizing. The methodology was applied in two high spatial resolution images: an airborne multispectral imagery and the newly WorldView-2 imagery. A temporal coverage of the airborne multispectral images was radiometrically calibrated with the IR-Mad transformation and used to assess the influence of the phenological variability of the invader. We found that optimal attributes for giant reed OBIA detection are a combination of spectral, geometric and textural information, with different scoring selection depending on the spectral and spatial characteristics of the imagery. WorldView-2 showed higher mapping accuracy (Kappa coefficient of 77%) and spectral attributes, including the newly yellow band, were preferentially selected, although a tendency to overestimate the total invaded area, due to the low spatial resolution (2 m of pixel size vs. 50 cm) was observed. When airborne images were used, geometric attributes were primarily selected and a higher spatial detail of the invasive patches was obtained, due to the higher spatial resolution. However, in highly heterogeneous landscapes, the low spectral resolution of the airborne images (4 bands instead of the 8 of WorldView-2) reduces the capability to detect giant reed patches. Giant reed displays peculiar spectral and geometric traits, at leaf, canopy and stand level, which makes the OBIA approach a very suitable technique for management purposes.

Conifer health classification for Colorado, 2008

USGS Publications Warehouse

Cole, Christopher J.; Noble, Suzanne M.; Blauer, Steven L.; Friesen, Beverly A.; Curry, Stacy E.; Bauer, Mark A.

2010-01-01

Colorado has undergone substantial changes in forests due to urbanization, wildfires, insect-caused tree mortality, and other human and environmental factors. The U.S. Geological Survey Rocky Mountain Geographic Science Center evaluated and developed a methodology for applying remotely-sensed imagery for assessing conifer health in Colorado. Two classes were identified for the purposes of this study: healthy and unhealthy (for example, an area the size of a 30- x 30-m pixel with 20 percent or greater visibly dead trees was defined as ?unhealthy?). Medium-resolution Landsat 5 Thematic Mapper imagery were collected. The normalized, reflectance-converted, cloud-filled Landsat scenes were merged to form a statewide image mosaic, and a Normalized Difference Vegetation Index (NDVI) and Renormalized Difference Infrared Index (RDII) were derived. A supervised maximum likelihood classification was done using the Landsat multispectral bands, the NDVI, the RDII, and 30-m U.S. Geological Survey National Elevation Dataset (NED). The classification was constrained to pixels identified in the updated landcover dataset as coniferous or mixed coniferous/deciduous vegetation. The statewide results were merged with a separate health assessment of Grand County, Colo., produced in late 2008. Sampling and validation was done by collecting field data and high-resolution imagery. The 86 percent overall classification accuracy attained in this study suggests that the data and methods used successfully characterized conifer conditions within Colorado. Although forest conditions for Lodgepole Pine (Pinus contorta) are easily characterized, classification uncertainty exists between healthy/unhealthy Ponderosa Pine (Pinus ponderosa), Pi?on (Pinus edulis), and Juniper (Juniperus sp.) vegetation. Some underestimation of conifer mortality in Summit County is likely, where recent (2008) cloud-free imagery was unavailable. These classification uncertainties are primarily due to the spatial and temporal resolution of Landsat, and of the NLCD derived from this sensor. It is believed that high- to moderate-resolution multispectral imagery, coupled with field data, could significantly reduce the uncertainty rates. The USGS produced a four-county follow-up conifer health assessment using high-resolution RapidEye remotely sensed imagery and field data collected in 2009.

Evaluating an image-fusion algorithm with synthetic-image-generation tools

NASA Astrophysics Data System (ADS)

Gross, Harry N.; Schott, John R.

1996-06-01

An algorithm that combines spectral mixing and nonlinear optimization is used to fuse multiresolution images. Image fusion merges images of different spatial and spectral resolutions to create a high spatial resolution multispectral combination. High spectral resolution allows identification of materials in the scene, while high spatial resolution locates those materials. In this algorithm, conventional spectral mixing estimates the percentage of each material (called endmembers) within each low resolution pixel. Three spectral mixing models are compared; unconstrained, partially constrained, and fully constrained. In the partially constrained application, the endmember fractions are required to sum to one. In the fully constrained application, all fractions are additionally required to lie between zero and one. While negative fractions seem inappropriate, they can arise from random spectral realizations of the materials. In the second part of the algorithm, the low resolution fractions are used as inputs to a constrained nonlinear optimization that calculates the endmember fractions for the high resolution pixels. The constraints mirror the low resolution constraints and maintain consistency with the low resolution fraction results. The algorithm can use one or more higher resolution sharpening images to locate the endmembers to high spatial accuracy. The algorithm was evaluated with synthetic image generation (SIG) tools. A SIG developed image can be used to control the various error sources that are likely to impair the algorithm performance. These error sources include atmospheric effects, mismodeled spectral endmembers, and variability in topography and illumination. By controlling the introduction of these errors, the robustness of the algorithm can be studied and improved upon. The motivation for this research is to take advantage of the next generation of multi/hyperspectral sensors. Although the hyperspectral images will be of modest to low resolution, fusing them with high resolution sharpening images will produce a higher spatial resolution land cover or material map.

Earth imaging and scientific observations by SSTI ``Clark'' a NASA technology demonstration spacecraft

NASA Astrophysics Data System (ADS)

Hayduk, Robert J.; Scott, Walter S.; Walberg, Gerald D.; Butts, James J.; Starr, Richard D.

1997-01-01

The Small Satellite Technology Initiative (SSTI) is a National Aeronautics and Space Administration (NASA) program to demonstrate smaller, high technology satellites constructed rapidly and less expensively. Under SSTI, NASA funded the development of ``Clark,'' a high technology demonstration satellite to provide 3-m resolution panchromatic and 15-m resolution multispectral images, as well as collect atmospheric constituent and cosmic x-ray data. The 690-lb. satellite, to be launched in early 1997, will be in a 476 km, circular, sun-synchronous polar orbit. This paper describes the program objectives, the technical characteristics of the sensors and satellite, image processing, archiving and distribution. Data archiving and distribution will be performed by NASA Stennis Space Center and by the EROS Data Center, Sioux Falls, South Dakota, USA.

High resolution observations of low contrast phenomena from an Advanced Geosynchronous Platform (AGP)

NASA Technical Reports Server (NTRS)

Maxwell, M. S.

1984-01-01

Present technology allows radiometric monitoring of the Earth, ocean and atmosphere from a geosynchronous platform with good spatial, spectral and temporal resolution. The proposed system could provide a capability for multispectral remote sensing with a 50 m nadir spatial resolution in the visible bands, 250 m in the 4 micron band and 1 km in the 11 micron thermal infrared band. The diffraction limited telescope has a 1 m aperture, a 10 m focal length (with a shorter focal length in the infrared) and linear and area arrays of detectors. The diffraction limited resolution applies to scenes of any brightness but for a dark low contrast scenes, the good signal to noise ratio of the system contribute to the observation capability. The capabilities of the AGP system are assessed for quantitative observations of ocean scenes. Instrument and ground system configuration are presented and projected sensor capabilities are analyzed.

Wavelet compression techniques for hyperspectral data

NASA Technical Reports Server (NTRS)

Evans, Bruce; Ringer, Brian; Yeates, Mathew

1994-01-01

Hyperspectral sensors are electro-optic sensors which typically operate in visible and near infrared bands. Their characteristic property is the ability to resolve a relatively large number (i.e., tens to hundreds) of contiguous spectral bands to produce a detailed profile of the electromagnetic spectrum. In contrast, multispectral sensors measure relatively few non-contiguous spectral bands. Like multispectral sensors, hyperspectral sensors are often also imaging sensors, measuring spectra over an array of spatial resolution cells. The data produced may thus be viewed as a three dimensional array of samples in which two dimensions correspond to spatial position and the third to wavelength. Because they multiply the already large storage/transmission bandwidth requirements of conventional digital images, hyperspectral sensors generate formidable torrents of data. Their fine spectral resolution typically results in high redundancy in the spectral dimension, so that hyperspectral data sets are excellent candidates for compression. Although there have been a number of studies of compression algorithms for multispectral data, we are not aware of any published results for hyperspectral data. Three algorithms for hyperspectral data compression are compared. They were selected as representatives of three major approaches for extending conventional lossy image compression techniques to hyperspectral data. The simplest approach treats the data as an ensemble of images and compresses each image independently, ignoring the correlation between spectral bands. The second approach transforms the data to decorrelate the spectral bands, and then compresses the transformed data as a set of independent images. The third approach directly generalizes two-dimensional transform coding by applying a three-dimensional transform as part of the usual transform-quantize-entropy code procedure. The algorithms studied all use the discrete wavelet transform. In the first two cases, a wavelet transform coder was used for the two-dimensional compression. The third case used a three dimensional extension of this same algorithm.

Improving Understanding of Spatial Heterogeneity in Mountain Ecohydrology with Multispectral Unmanned Aerial Systems (UAS).

NASA Astrophysics Data System (ADS)

Wigmore, O.; Molotch, N. P.

2017-12-01

Mountain regions are a critical component of the hydrologic system. These regions are extremely heterogeneous, with dramatic topographic, climatic, ecologic and hydrologic variations occurring over very short distances. This heterogeneity makes understanding changes in these environments difficult. Commonly used satellite data are often too coarse to resolve processes at appropriate scales and point measurements are typically unrepresentative of the wider region. The rapid rise of Unmanned Aerial Systems (UAS) offers a potential solution to the scale-related inadequacies of satellite and ground-based observing systems. Using UAS, spatially distributed datasets can be collected at high resolution (i.e. cm), on demand, and can therefore facilitate improved understanding of mountain ecohydrology. We deployed a custom built multispectral - visible (RGB), near infrared (NIR) and thermal infrared (TIR) - UAS at a weekly interval over the Niwot Ridge Long Term Ecological Research (NWT LTER) saddle catchment at 3500masl in the Colorado Rockies. This system was used to map surface water pathways, land cover and topography, and quantify ecohydrologic variables including, snow depth, vegetation productivity and surface soil moisture at 5-50cm resolution across an 80ha study area. This presentation will discuss the techniques, methods and merits of using UAS derived multispectral data for ecohydrologic research in mountain regions. We will also present preliminary findings from our survey time series at NWT LTER and a discussion of the potential insights that these datasets can provide. Key questions to be addressed are: 1) how does spatial variability in snow depth impact soil moisture and vegetation productivity, 2) how can UAS help us to identify ecohydrologic `hotspots' and `hot moments' across heterogeneous landscapes.

Lock-in imaging with synchronous digital mirror demodulation

NASA Astrophysics Data System (ADS)

Bush, Michael G.

2010-04-01

Lock-in imaging enables high contrast imaging in adverse conditions by exploiting a modulated light source and homodyne detection. We report results on a patent pending lock-in imaging system fabricated from commercial-off-theshelf parts utilizing standard cameras and a spatial light modulator. By leveraging the capabilities of standard parts we are able to present a low cost, high resolution, high sensitivity camera with applications in search and rescue, friend or foe identification (IFF), and covert surveillance. Different operating modes allow the same instrument to be utilized for dual band multispectral imaging or high dynamic range imaging, increasing the flexibility in different operational settings.

Imaging During MESSENGER's Second Flyby of Mercury

NASA Astrophysics Data System (ADS)

Chabot, N. L.; Prockter, L. M.; Murchie, S. L.; Robinson, M. S.; Laslo, N. R.; Kang, H. K.; Hawkins, S. E.; Vaughan, R. M.; Head, J. W.; Solomon, S. C.; MESSENGER Team

2008-12-01

During MESSENGER's second flyby of Mercury on October 6, 2008, the Mercury Dual Imaging System (MDIS) will acquire 1287 images. The images will include coverage of about 30% of Mercury's surface not previously seen by spacecraft. A portion of the newly imaged terrain will be viewed during the inbound portion of the flyby. On the outbound leg, MDIS will image additional previously unseen terrain as well as regions imaged under different illumination geometry by Mariner 10. These new images, when combined with images from Mariner 10 and from MESSENGER's first Mercury flyby, will enable the first regional- resolution global view of Mercury constituting a combined total coverage of about 96% of the planet's surface. MDIS consists of both a Wide Angle Camera (WAC) and a Narrow Angle Camera (NAC). During MESSENGER's second Mercury flyby, the following imaging activities are planned: about 86 minutes before the spacecraft's closest pass by the planet, the WAC will acquire images through 11 different narrow-band color filters of the approaching crescent planet at a resolution of about 5 km/pixel. At slightly less than 1 hour to closest approach, the NAC will acquire a 4-column x 11-row mosaic with an approximate resolution of 450 m/pixel. At 8 minutes after closest approach, the WAC will obtain the highest-resolution multispectral images to date of Mercury's surface, imaging a portion of the surface through 11 color filters at resolutions of about 250-600 m/pixel. A strip of high-resolution NAC images, with a resolution of approximately 100 m/pixel, will follow these WAC observations. The NAC will next acquire a 15-column x 13- row high-resolution mosaic of the northern hemisphere of the departing planet, beginning approximately 21 minutes after closest approach, with resolutions of 140-300 m/pixel; this mosaic will fill a large gore in the Mariner 10 data. At about 42 minutes following closest approach, the WAC will acquire a 3x3, 11-filter, full- planet mosaic with an average resolution of 2.5 km/pixel. Two NAC mosaics of the entire departing planet will be acquired beginning about 66 minutes after closest approach, with resolutions of 500-700 m/pixel. About 89 minutes following closest approach, the WAC will acquire a multispectral image set with a resolution of about 5 km/pixel. Following this WAC image set, MDIS will continue to acquire occasional images with both the WAC and NAC until 20 hours after closest approach, at which time the flyby data will begin being transmitted to Earth.

Forest cover of North America in the 1970s mapped using Landsat MSS data

NASA Astrophysics Data System (ADS)

Feng, M.; Sexton, J. O.; Channan, S.; Townshend, J. R.

2015-12-01

The distribution and changes in Earth's forests impact hydrological, biogeochemical, and energy fluxes, as well as ecosystems' capacity to support biodiversity and human economies. Long-term records of forest cover are needed across a broad range of investigation, including climate and carbon-cycle modeling, hydrological studies, habitat analyzes, biological conservation, and land-use planning. Satellite-based observations enable mapping and monitoring of forests at ecologically and economically relevant resolutions and continental or even global extents. Following early forest-mapping efforts using coarser resolution remote sensing data such as the Advanced Very High Resolution Radiometer (AVHRR) and MODerate-resolution Imaging Spectroradiometer (MODIS), forests have been mapped regionally at < 100-m resolution using Landsat Thematic Mapper (TM) and Enhanced Thematic Mapper Plus (ETM+). These "Landsat-class" sensors offer precise calibration, but they provide observations only over the past three decades—a relatively short period for delineating the long-term changes of forests. Starting in 1971, the Multispectral Scanner (MSS) was the first generation of sensors aboard the Landsat satellites. MSS thus provides a unique resource to extend observations by at least a decade longer in history than records based on Landsat TM and ETM+. Leveraging more recent Landsat-based forest-cover products developed by the Global Land Cover Facility (GLCF) as reference, we developed an automated approach to detect forests using MSS data by leveraging the multispectral and phenological characteristics of forests observed in MSS time-series. The forest-cover map is produced with layers representing the year of observation, detection of forest-cover change relative to 1990, and the uncertainty of forest-cover and -change layers. The approach has been implemented with open-source libraries to facilitate processing large volumes of Landsat MSS images on high-performance computing machines. As the first result of our global mapping effort, we present the forest cover for North America. More than 25,000 Landsat MSS scenes were processed to provide a 120-meter resolution forest cover for North America, which will be made publicly available on the GLCF website (http://www.landcover.org).

Photogrammetric Processing Using ZY-3 Satellite Imagery

NASA Astrophysics Data System (ADS)

Kornus, W.; Magariños, A.; Pla, M.; Soler, E.; Perez, F.

2015-03-01

This paper evaluates the stereoscopic capacities of the Chinese sensor ZiYuan-3 (ZY-3) for the generation of photogrammetric products. The satellite was launched on January 9, 2012 and carries three high-resolution panchromatic cameras viewing in forward (22º), nadir (0º) and backward direction (-22º) and an infrared multi-spectral scanner (IRMSS), which is slightly looking forward (6º). The ground sampling distance (GSD) is 2.1m for the nadir image, 3.5m for the two oblique stereo images and 5.8m for the multispectral image. The evaluated ZY-3 imagery consists of a full set of threefold-stereo and a multi-spectral image covering an area of ca. 50km x 50km north-west of Barcelona, Spain. The complete photogrammetric processing chain was executed including image orientation, the generation of a digital surface model (DSM), radiometric image correction, pansharpening, orthoimage generation and digital stereo plotting. All 4 images are oriented by estimating affine transformation parameters between observed and nominal RPC (rational polynomial coefficients) image positions of 17 ground control points (GCP) and a subsequent calculation of refined RPC. From 10 independent check points RMS errors of 2.2m, 2.0m and 2.7m in X, Y and H are obtained. Subsequently, a DSM of 5m grid spacing is generated fully automatically. A comparison with the Lidar data results in an overall DSM accuracy of approximately 3m. In moderate and flat terrain higher accuracies in the order of 2.5m and better are achieved. In a next step orthoimages from the high resolution nadir image and the multispectral image are generated using the refined RPC geometry and the DSM. After radiometric corrections a fused high resolution colour orthoimage with 2.1m pixel size is created using an adaptive HSL method. The pansharpen process is performed after the individual geocorrection due to the different viewing angles between the two images. In a detailed analysis of the colour orthoimage artifacts are detected covering an area of 4691ha, corresponding to less than 2% of the imaged area. Most of the artifacts are caused by clouds (4614ha). A minor part (77ha) is affected by colour patch, stripping or blooming effects. For the final qualitative analysis on the usability of the ZY-3 imagery for stereo plotting purposes stereo combinations of the nadir and an oblique image are discarded, mainly due to the different pixel size, which produces difficulties in the stereoscopic vision and poor accuracy in positioning and measuring. With the two oblique images a level of detail equivalent to 1:25.000 scale is achieved for transport network, hydrography, vegetation and elements to model the terrain as break lines. For settlement, including buildings and other constructions a lower level of detail is achieved equivalent to 1:50.000 scale.

Earth resources data systems design: S192 instrument measurements and characteristics

NASA Technical Reports Server (NTRS)

Goldstein, A. S.

1972-01-01

The design, development, and characteristics of the S192 instrument for use with the earth resources data systems are discussed. Subjects presented are: (1) multispectral scanner measurements, (2) measurement characteristics, (3) calibration and aligment, (4) operating modes, and (5) time tagging and references. The S192 will obtain high spatial resolution, quantitative line scan imagery data of the radiation reflected and emitted by selected test sites in up to 13 spectral bands of visible, near infrared, and thermal infrared regions of the electromagnetic spectrum.

Comparison of the Spectral Properties of Pansharpened Images Generated from AVNIR-2 and Prism Onboard Alos

NASA Astrophysics Data System (ADS)

Matsuoka, M.

2012-07-01

A considerable number of methods for pansharpening remote-sensing images have been developed to generate higher spatial resolution multispectral images by the fusion of lower resolution multispectral images and higher resolution panchromatic images. Because pansharpening alters the spectral properties of multispectral images, method selection is one of the key factors influencing the accuracy of subsequent analyses such as land-cover classification or change detection. In this study, seven pixel-based pansharpening methods (additive wavelet intensity, additive wavelet principal component, generalized Laplacian pyramid with spectral distortion minimization, generalized intensity-hue-saturation (GIHS) transform, GIHS adaptive, Gram-Schmidt spectral sharpening, and block-based synthetic variable ratio) were compared using AVNIR-2 and PRISM onboard ALOS from the viewpoint of the preservation of spectral properties of AVNIR-2. A visual comparison was made between pansharpened images generated from spatially degraded AVNIR-2 and original images over urban, agricultural, and forest areas. The similarity of the images was evaluated in terms of the image contrast, the color distinction, and the brightness of the ground objects. In the quantitative assessment, three kinds of statistical indices, correlation coefficient, ERGAS, and Q index, were calculated by band and land-cover type. These scores were relatively superior in bands 2 and 3 compared with the other two bands, especially over urban and agricultural areas. Band 4 showed a strong dependency on the land-cover type. This was attributable to the differences in the observing spectral wavelengths of the sensors and local scene variances.

Fusion and quality analysis for remote sensing images using contourlet transform

NASA Astrophysics Data System (ADS)

Choi, Yoonsuk; Sharifahmadian, Ershad; Latifi, Shahram

2013-05-01

Recent developments in remote sensing technologies have provided various images with high spatial and spectral resolutions. However, multispectral images have low spatial resolution and panchromatic images have low spectral resolution. Therefore, image fusion techniques are necessary to improve the spatial resolution of spectral images by injecting spatial details of high-resolution panchromatic images. The objective of image fusion is to provide useful information by improving the spatial resolution and the spectral information of the original images. The fusion results can be utilized in various applications, such as military, medical imaging, and remote sensing. This paper addresses two issues in image fusion: i) image fusion method and ii) quality analysis of fusion results. First, a new contourlet-based image fusion method is presented, which is an improvement over the wavelet-based fusion. This fusion method is then applied to a case study to demonstrate its fusion performance. Fusion framework and scheme used in the study are discussed in detail. Second, quality analysis for the fusion results is discussed. We employed various quality metrics in order to analyze the fusion results both spatially and spectrally. Our results indicate that the proposed contourlet-based fusion method performs better than the conventional wavelet-based fusion methods.

BTDI detector technology for reconnaissance application

NASA Astrophysics Data System (ADS)

Hilbert, Stefan; Eckardt, Andreas; Krutz, David

2017-11-01

The Institute of Optical Sensor Systems (OS) at the Robotics and Mechatronics Center of the German Aerospace Center (DLR) has more than 30 years of experience with high-resolution imaging technology. This paper shows the institute's scientific results of the leading-edge detector design in a BTDI (Bidirectional Time Delay and Integration) architecture. This project demonstrates an approved technological design for high or multi-spectral resolution spaceborne instruments. DLR OS and BAE Systems were driving the technology of new detectors and the FPA design for future projects, new manufacturing accuracy in order to keep pace with ambitious scientific and user requirements. Resulting from customer requirements and available technologies the current generation of space borne sensor systems is focusing on VIS/NIR high spectral resolution to meet the requirements on earth and planetary observation systems. The combination of large swath and high-spectral resolution with intelligent control applications and new focal plane concepts opens the door to new remote sensing and smart deep space instruments. The paper gives an overview of the detector development and verification program at DLR on detector module level and key parameters like SNR, linearity, spectral response, quantum efficiency, PRNU, DSNU and MTF.

Detection of artificially ripened mango using spectrometric analysis

NASA Astrophysics Data System (ADS)

Mithun, B. S.; Mondal, Milton; Vishwakarma, Harsh; Shinde, Sujit; Kimbahune, Sanjay

2017-05-01

Hyperspectral sensing has been proven to be useful to determine the quality of food in general. It has also been used to distinguish naturally and artificially ripened mangoes by analyzing the spectral signature. However the focus has been on improving the accuracy of classification after performing dimensionality reduction, optimum feature selection and using suitable learning algorithm on the complete visible and NIR spectrum range data, namely 350nm to 1050nm. In this paper we focus on, (i) the use of low wavelength resolution and low cost multispectral sensor to reliably identify artificially ripened mango by selectively using the spectral information so that classification accuracy is not hampered at the cost of low resolution spectral data and (ii) use of visible spectrum i.e. 390nm to 700 nm data to accurately discriminate artificially ripened mangoes. Our results show that on a low resolution spectral data, the use of logistic regression produces an accuracy of 98.83% and outperforms other methods like classification tree, random forest significantly. And this is achieved by analyzing only 36 spectral reflectance data points instead of the complete 216 data points available in visual and NIR range. Another interesting experimental observation is that we are able to achieve more than 98% classification accuracy by selecting only 15 irradiance values in the visible spectrum. Even the number of data needs to be collected using hyper-spectral or multi-spectral sensor can be reduced by a factor of 24 for classification with high degree of confidence

Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the North Bamyan mineral district in Afghanistan

USGS Publications Warehouse

Davis, Philip A.; Davis, Philip A.

2013-01-01

The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the North Bamyan mineral district, which has copper deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA,2006,2007, 2008), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such, the DS products match JAXA criteria for value added products, which are not copyrighted, according to the ALOS end-user license agreement. The selection criteria for the satellite imagery used in our mosaics were images having (1) the highest solar-elevation angles (near summer solstice) and (2) the least cloud, cloud-shadow, and snow cover. The multispectral and panchromatic data were orthorectified with ALOS satellite ephemeris data, a process which is not as accurate as orthorectification using digital elevation models (DEMs); however, the ALOS processing center did not have a precise DEM. As a result, the multispectral and panchromatic image pairs were generally not well registered to the surface and not coregistered well enough to perform resolution enhancement on the multispectral data. Therefore, it was necessary to (1) register the 10-m AVNIR multispectral imagery to a well-controlled Landsat image base, (2) mosaic the individual multispectral images into a single image of the entire area of interest, (3) register each panchromatic image to the registered multispectral image base, and (4) mosaic the individual panchromatic images into a single image of the entire area of interest. The two image-registration steps were facilitated using an automated control-point algorithm developed by the USGS that allows image coregistration to within one picture element. Before rectification, the multispectral and panchromatic images were converted to radiance values and then to relative-reflectance values using the methods described in Davis (2006). Mosaicking the multispectral or panchromatic images started with the image with the highest sun-elevation angle and the least atmospheric scattering, which was treated as the standard image. The band-reflectance values of all other multispectral or panchromatic images within the area were sequentially adjusted to that of the standard image by determining band-reflectance correspondence between overlapping images using linear least-squares analysis. The resolution of the multispectral image mosaic was then increased to that of the panchromatic image mosaic using the SPARKLE logic, which is described in Davis (2006). Each of the four-band images within the resolution-enhanced image mosaic was individually subjected to a local-area histogram stretch algorithm (described in Davis, 2007), which stretches each band's picture element based on the digital values of all picture elements within a 500-m radius. The final databases, which are provided in this DS, are three-band, color-composite images of the local-area-enhanced, natural-color data (the blue, green, and red wavelength bands) and color-infrared data (the green, red, and near-infrared wavelength bands). All image data were initially projected and maintained in Universal Transverse Mercator (UTM) map projection using the target area's local zone (42 for North Bamyan) and the WGS84 datum. The final image mosaics were subdivided into two overlapping tiles or quadrants because of the large size of the target area. The two image tiles (or quadrants) for the North Bamyan area are provided as embedded geotiff images, which can be read and used by most geographic information system (GIS) and image-processing software. The tiff world files (tfw) are provided, even though they are generally not needed for most software to read an embedded geotiff image.

Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Ahankashan mineral district in Afghanistan

USGS Publications Warehouse

Davis, Philip A.; Davis, Philip A.

2013-01-01

The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Ahankashan mineral district, which has copper and gold deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA,2007,2008, 2009, 2010),but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such, the DS products match JAXA criteria for value added products, which are not copyrighted, according to the ALOS end-user license agreement. The selection criteria for the satellite imagery used in our mosaics were images having (1) the highest solar-elevation angles (near summer solstice) and (2) the least cloud, cloud-shadow, and snow cover. The multispectral and panchromatic data were orthorectified with ALOS satellite ephemeris data, a process which is not as accurate as orthorectification using digital elevation models (DEMs); however, the ALOS processing center did not have a precise DEM. As a result, the multispectral and panchromatic image pairs were generally not well registered to the surface and not coregistered well enough to perform resolution enhancement on the multispectral data. Therefore, it was necessary to (1) register the 10-m AVNIR multispectral imagery to a well-controlled Landsat image base, (2) mosaic the individual multispectral images into a single image of the entire area of interest, (3) register each panchromatic image to the registered multispectral image base, and (4) mosaic the individual panchromatic images into a single image of the entire area of interest. The two image-registration steps were facilitated using an automated control-point algorithm developed by the USGS that allows image coregistration to within one picture element. Before rectification, the multispectral and panchromatic images were converted to radiance values and then to relative-reflectance values using the methods described in Davis (2006). Mosaicking the multispectral or panchromatic images started with the image with the highest sun-elevation angle and the least atmospheric scattering, which was treated as the standard image. The band-reflectance values of all other multispectral or panchromatic images within the area were sequentially adjusted to that of the standard image by determining band-reflectance correspondence between overlapping images using linear least-squares analysis. The resolution of the multispectral image mosaic was then increased to that of the panchromatic image mosaic using the SPARKLE logic, which is described in Davis (2006). Each of the four-band images within the resolution-enhanced image mosaic was individually subjected to a local-area histogram stretch algorithm (described in Davis, 2007), which stretches each band's picture element based on the digital values of all picture elements within a 500-m radius. The final databases, which are provided in this DS, are three-band, color-composite images of the local-area-enhanced, natural-color data (the blue, green, and red wavelength bands) and color-infrared data (the green, red, and near-infrared wavelength bands). All image data were initially projected and maintained in Universal Transverse Mercator (UTM) map projection using the target area's local zone (41 for Ahankashan) and the WGS84 datum. The final image mosaics were subdivided into five overlapping tiles or quadrants because of the large size of the target area. The five image tiles (or quadrants) for the Ahankashan area are provided as embedded geotiff images, which can be read and used by most geographic information system (GIS) and image-processing software. The tiff world files (tfw) are provided, even though they are generally not needed for most software to read an embedded geotiff image.

Pan Sharpening Quality Investigation of Turkish In-Operation Remote Sensing Satellites: Applications with Rasat and GÖKTÜRK-2 Images

NASA Astrophysics Data System (ADS)

Ozendi, Mustafa; Topan, Hüseyin; Cam, Ali; Bayık, Çağlar

2016-10-01

Recently two optical remote sensing satellites, RASAT and GÖKTÜRK-2, launched successfully by the Republic of Turkey. RASAT has 7.5 m panchromatic, and 15 m visible bands whereas GÖKTÜRK-2 has 2.5 m panchromatic and 5 m VNIR (Visible and Near Infrared) bands. These bands with various resolutions can be fused by pan-sharpening methods which is an important application area of optical remote sensing imagery. So that, the high geometric resolution of panchromatic band and the high spectral resolution of VNIR bands can be merged. In the literature there are many pan-sharpening methods. However, there is not a standard framework for quality investigation of pan-sharpened imagery. The aim of this study is to investigate pan-sharpening performance of RASAT and GÖKTÜRK-2 images. For this purpose, pan-sharpened images are generated using most popular pan-sharpening methods IHS, Brovey and PCA at first. This procedure is followed by quantitative evaluation of pan-sharpened images using Correlation Coefficient (CC), Root Mean Square Error (RMSE), Relative Average Spectral Error (RASE), Spectral Angle Mapper (SAM) and Erreur Relative Globale Adimensionnelle de Synthése (ERGAS) metrics. For generation of pan-sharpened images and computation of metrics SharpQ tool is used which is developed with MATLAB computing language. According to metrics, PCA derived pan-sharpened image is the most similar one to multispectral image for RASAT, and Brovey derived pan-sharpened image is the most similar one to multispectral image for GÖKTÜRK-2. Finally, pan-sharpened images are evaluated qualitatively in terms of object availability and completeness for various land covers (such as urban, forest and flat areas) by a group of operators who are experienced in remote sensing imagery.

Incorporation of satellite remote sensing pan-sharpened imagery into digital soil prediction and mapping models to characterize soil property variability in small agricultural fields

NASA Astrophysics Data System (ADS)

Xu, Yiming; Smith, Scot E.; Grunwald, Sabine; Abd-Elrahman, Amr; Wani, Suhas P.

2017-01-01

Soil prediction models based on spectral indices from some multispectral images are too coarse to characterize spatial pattern of soil properties in small and heterogeneous agricultural lands. Image pan-sharpening has seldom been utilized in Digital Soil Mapping research before. This research aimed to analyze the effects of pan-sharpened (PAN) remote sensing spectral indices on soil prediction models in smallholder farm settings. This research fused the panchromatic band and multispectral (MS) bands of WorldView-2, GeoEye-1, and Landsat 8 images in a village in Southern India by Brovey, Gram-Schmidt and Intensity-Hue-Saturation methods. Random Forest was utilized to develop soil total nitrogen (TN) and soil exchangeable potassium (Kex) prediction models by incorporating multiple spectral indices from the PAN and MS images. Overall, our results showed that PAN remote sensing spectral indices have similar spectral characteristics with soil TN and Kex as MS remote sensing spectral indices. There is no soil prediction model incorporating the specific type of pan-sharpened spectral indices always had the strongest prediction capability of soil TN and Kex. The incorporation of pan-sharpened remote sensing spectral data not only increased the spatial resolution of the soil prediction maps, but also enhanced the prediction accuracy of soil prediction models. Small farms with limited footprint, fragmented ownership and diverse crop cycle should benefit greatly from the pan-sharpened high spatial resolution imagery for soil property mapping. Our results show that multiple high and medium resolution images can be used to map soil properties suggesting the possibility of an improvement in the maps' update frequency. Additionally, the results should benefit the large agricultural community through the reduction of routine soil sampling cost and improved prediction accuracy.

Feature extraction based on extended multi-attribute profiles and sparse autoencoder for remote sensing image classification

NASA Astrophysics Data System (ADS)

Teffahi, Hanane; Yao, Hongxun; Belabid, Nasreddine; Chaib, Souleyman

2018-02-01

The satellite images with very high spatial resolution have been recently widely used in image classification topic as it has become challenging task in remote sensing field. Due to a number of limitations such as the redundancy of features and the high dimensionality of the data, different classification methods have been proposed for remote sensing images classification particularly the methods using feature extraction techniques. This paper propose a simple efficient method exploiting the capability of extended multi-attribute profiles (EMAP) with sparse autoencoder (SAE) for remote sensing image classification. The proposed method is used to classify various remote sensing datasets including hyperspectral and multispectral images by extracting spatial and spectral features based on the combination of EMAP and SAE by linking them to kernel support vector machine (SVM) for classification. Experiments on new hyperspectral image "Huston data" and multispectral image "Washington DC data" shows that this new scheme can achieve better performance of feature learning than the primitive features, traditional classifiers and ordinary autoencoder and has huge potential to achieve higher accuracy for classification in short running time.

Statistical correction of lidar-derived digital elevation models with multispectral airborne imagery in tidal marshes

USGS Publications Warehouse

Buffington, Kevin J.; Dugger, Bruce D.; Thorne, Karen M.; Takekawa, John Y.

2016-01-01

Airborne light detection and ranging (lidar) is a valuable tool for collecting large amounts of elevation data across large areas; however, the limited ability to penetrate dense vegetation with lidar hinders its usefulness for measuring tidal marsh platforms. Methods to correct lidar elevation data are available, but a reliable method that requires limited field work and maintains spatial resolution is lacking. We present a novel method, the Lidar Elevation Adjustment with NDVI (LEAN), to correct lidar digital elevation models (DEMs) with vegetation indices from readily available multispectral airborne imagery (NAIP) and RTK-GPS surveys. Using 17 study sites along the Pacific coast of the U.S., we achieved an average root mean squared error (RMSE) of 0.072 m, with a 40–75% improvement in accuracy from the lidar bare earth DEM. Results from our method compared favorably with results from three other methods (minimum-bin gridding, mean error correction, and vegetation correction factors), and a power analysis applying our extensive RTK-GPS dataset showed that on average 118 points were necessary to calibrate a site-specific correction model for tidal marshes along the Pacific coast. By using available imagery and with minimal field surveys, we showed that lidar-derived DEMs can be adjusted for greater accuracy while maintaining high (1 m) resolution.

Comparison of FLAASH and QUAC atmospheric correction methods for Resourcesat-2 LISS-IV data

NASA Astrophysics Data System (ADS)

Saini, V.; Tiwari, R. K.; Gupta, R. P.

2016-05-01

The LISS-IV sensor aboard Resourcesat-2 is a modern relatively high resolution multispectral sensor having immense potential for generation of good quality land use land cover maps. It generates data in high (10-bit) radiometric resolution and 5.8 m spatial resolution and has three bands in the visible-near infrared region. This is of particular importance to global community as the data are provided at highly competitive prices. However, no literature describing the atmospheric correction of Resourcesat-2-LISS-IV data could be found. Further, without atmospheric correction full radiometric potential of any remote sensing data remains underutilized. The FLAASH and QUAC module of ENVI software are highly used by researchers for atmospheric correction of popular remote sensing data such as Landsat, SPOT, IKONOS, LISS-I, III etc. This article outlines a methodology for atmospheric correction of Resourcesat-2-LISS-IV data. Also, a comparison of reflectance from different atmospheric correction modules (FLAASH and QUAC) with TOA and standard data has been made to determine the best suitable method for reflectance estimation for this sensor.

Lunar UV-visible-IR mapping interferometric spectrometer

NASA Technical Reports Server (NTRS)

Smith, W. Hayden; Haskin, L.; Korotev, R.; Arvidson, R.; Mckinnon, W.; Hapke, B.; Larson, S.; Lucey, P.

1992-01-01

Ultraviolet-visible-infrared mapping digital array scanned interferometers for lunar compositional surveys was developed. The research has defined a no-moving-parts, low-weight and low-power, high-throughput, and electronically adaptable digital array scanned interferometer that achieves measurement objectives encompassing and improving upon all the requirements defined by the LEXSWIG for lunar mineralogical investigation. In addition, LUMIS provides a new, important, ultraviolet spectral mapping, high-spatial-resolution line scan camera, and multispectral camera capabilities. An instrument configuration optimized for spectral mapping and imaging of the lunar surface and provide spectral results in support of the instrument design are described.

CRISM's Global Mapping of Mars, Part 1

NASA Technical Reports Server (NTRS)

2007-01-01

After a year in Mars orbit, CRISM has taken enough images to allow the team to release the first parts of a global spectral map of Mars to the Planetary Data System (PDS), NASA's digital library of planetary data.

CRISM's global mapping is called the 'multispectral survey.' The team uses the word 'survey' because a reason for gathering this data set is to search for new sites for targeted observations, high-resolution views of the surface at 18 meters per pixel in 544 colors. Another reason for the multispectral survey is to provide contextual information. Targeted observations have such a large data volume (about 200 megabytes apiece) that only about 1% of Mars can be imaged at CRISM's highest resolution. The multispectral survey is a lower data volume type of observation that fills in the gaps between targeted observations, allowing scientists to better understand their geologic context.

The global map is built from tens of thousands of image strips each about 10 kilometers (6.2 miles) wide and thousands of kilometers long. During the multispectral survey, CRISM returns data from only 72 carefully selected wavelengths that cover absorptions indicative of the mineral groups that CRISM is looking for on Mars. Data volume is further decreased by binning image pixels inside the instrument to a scale of about 200 meters (660 feet) per pixel. The total reduction in data volume per square kilometer is a factor of 700, making the multispectral survey manageable to acquire and transmit to Earth. Once on the ground, the strips of data are mosaicked into maps. The multispectral survey is too large to show the whole planet in a single map, so the map is divided into 1,964 'tiles,' each about 300 kilometers (186 miles) across. There are three versions of each tile, processed to progressively greater levels to strip away the obscuring effects of the dusty atmosphere and to highlight mineral variations in surface materials.

This is the first version of tile 750, one of 209 tiles just delivered to the PDS. It shows a part of the planet called Tyrrhena Terra in the ancient, heavily cratered highlands. The colored strips are CRISM multispectral survey data acquired over several months, in which each pixel has a calibrated 72-color spectrum of Mars. The three wavelengths shown are 2.53, 1.50, and 1.08 micrometers in the red, green, and blue image planes respectively. At these wavelengths, rocky areas appear brown, dusty areas appear tan, and regions with hazy atmosphere appear bluish. Note that there is a large difference in brightness between strips, because there is no correction for the lighting conditions at the time of each observation. The gray areas between the strips are from an earlier mosaic of the planet taken by the Thermal Emission Imaging System (THEMIS) instrument on Mars Odyssey, and are included only for context. Ultimately the multispectral survey will cover nearly all of this area.

CRISM is one of six science instruments on NASA's Mars Reconnaissance Orbiter. Led by The Johns Hopkins University Applied Physics Laboratory, Laurel, Md., the CRISM team includes expertise from universities, government agencies and small businesses in the United States and abroad. NASA's Jet Propulsion Laboratory, a division of the California Institute of Technology in Pasadena, manages the Mars Reconnaissance Orbiter and the Mars Science Laboratory for NASA's Science Mission Directorate, Washington. Lockheed Martin Space Systems, Denver, built the orbiter.

CRISM's Global Mapping of Mars, Part 2

NASA Technical Reports Server (NTRS)

2007-01-01

After a year in Mars orbit, CRISM has taken enough images to allow the team to release the first parts of a global spectral map of Mars to the Planetary Data System (PDS), NASA's digital library of planetary data.

CRISM's global mapping is called the 'multispectral survey.' The team uses the word 'survey' because a reason for gathering this data set is to search for new sites for targeted observations, high-resolution views of the surface at 18 meters per pixel in 544 colors. Another reason for the multispectral survey is to provide contextual information. Targeted observations have such a large data volume (about 200 megabytes apiece) that only about 1% of Mars can be imaged at CRISM's highest resolution. The multispectral survey is a lower data volume type of observation that fills in the gaps between targeted observations, allowing scientists to better understand their geologic context.

The global map is built from tens of thousands of image strips each about 10 kilometers (6.2 miles) wide and thousands of kilometers long. During the multispectral survey, CRISM returns data from only 72 carefully selected wavelengths that cover absorptions indicative of the mineral groups that CRISM is looking for on Mars. Data volume is further decreased by binning image pixels inside the instrument to a scale of about 200 meters (660 feet) per pixel. The total reduction in data volume per square kilometer is a factor of 700, making the multispectral survey manageable to acquire and transmit to Earth. Once on the ground, the strips of data are mosaicked into maps. The multispectral survey is too large to show the whole planet in a single map, so the map is divided into 1,964 'tiles,' each about 300 kilometers (186 miles) across. There are three versions of each tile, processed to progressively greater levels to strip away the obscuring effects of the dusty atmosphere and to highlight mineral variations in surface materials.

This is the first version of tile 750, one of 209 tiles just delivered to the PDS. It shows a part of the planet called Tyrrhena Terra in the ancient, heavily cratered highlands. The colored strips are CRISM multispectral survey data acquired over several months, in which each pixel has a calibrated 72-color spectrum of Mars. The three wavelengths shown are 2.53, 1.50, and 1.08 micrometers in the red, green, and blue image planes respectively. At these wavelengths, rocky areas appear brown, dusty areas appear tan, and regions with hazy atmosphere appear bluish. Note that there is a large difference in brightness between strips, because there is no correction for the lighting conditions at the time of each observation. The gray areas between the strips are from an earlier mosaic of the planet taken by the Thermal Emission Imaging System (THEMIS) instrument on Mars Odyssey, and are included only for context. Ultimately the multispectral survey will cover nearly all of this area.

CRISM is one of six science instruments on NASA's Mars Reconnaissance Orbiter. Led by The Johns Hopkins University Applied Physics Laboratory, Laurel, Md., the CRISM team includes expertise from universities, government agencies and small businesses in the United States and abroad. NASA's Jet Propulsion Laboratory, a division of the California Institute of Technology in Pasadena, manages the Mars Reconnaissance Orbiter and the Mars Science Laboratory for NASA's Science Mission Directorate, Washington. Lockheed Martin Space Systems, Denver, built the orbiter.

Sub-hectare crop area mapped wall-to-wall in Tigray Ethiopia with HEC processing of WorldView sub-meter panchromatic image texture

NASA Astrophysics Data System (ADS)

Neigh, C. S. R.; Carroll, M.; Wooten, M.; McCarty, J. L.; Powell, B.; Husak, G. J.; Enenkel, M.; Hain, C.

2017-12-01

Global food production in the developing world occurs within sub-hectare fields that are difficult to identify with moderate resolution satellite imagery. Knowledge about the distribution of these fields is critical in food security programs. We developed a semi-automated image segmentation approach using wall-to-wall sub-meter imagery with high-end computing (HEC) to map crop area (CA) throughout Tigray, Ethiopia that encompasses over 41,000 km2. Our approach tested multiple HEC processing streams to reduce processing time and minimize mapping error. We applied multiple resolution smoothing kernels to capture differences in land surface texture associated to CA. Typically, very-small fields (mean < 2 ha) have a smooth image roughness compared to natural scrub/shrub woody vegetation at the 1 m scale and these features can be segmented in panchromatic imagery with multi-level histogram thresholding. We found multi-temporal very-high resolution (VHR) panchromatic imagery with multi-spectral VHR and moderate resolution imagery are sufficient in extracting critical CA information needed in food security programs. We produced a 2011 ‒ 2015 CA map using over 3,000 WorldView-1 panchromatic images wall-to-wall in 1/2° mosaics for Tigray, Ethiopia in 1 week. We evaluated CA estimates with nearly 3,000 WorldView-2 2 m multispectral 250 × 250 m image subsets, with seven expert interpretations, and with in-situ global positioning system (GPS) photography. Our CA estimates ranged from 32 to 41% in sub-regions of Tigray with median maximum per bin commission and omission errors of 11% and 1% respectively, with most of the error occurring in bins less than 15%. This empirical, simple, and low direct cost approach via U.S. government license agreement and HEC could be a viable big-data methodology to extract wall-to-wall CA for other regions of the world that have very-small agriculture fields with similar image texture.

X ray imaging microscope for cancer research

NASA Technical Reports Server (NTRS)

Hoover, Richard B.; Shealy, David L.; Brinkley, B. R.; Baker, Phillip C.; Barbee, Troy W., Jr.; Walker, Arthur B. C., Jr.

1991-01-01

The NASA technology employed during the Stanford MSFC LLNL Rocket X Ray Spectroheliograph flight established that doubly reflecting, normal incidence multilayer optics can be designed, fabricated, and used for high resolution x ray imaging of the Sun. Technology developed as part of the MSFC X Ray Microscope program, showed that high quality, high resolution multilayer x ray imaging microscopes are feasible. Using technology developed at Stanford University and at the DOE Lawrence Livermore National Laboratory (LLNL), Troy W. Barbee, Jr. has fabricated multilayer coatings with near theoretical reflectivities and perfect bandpass matching for a new rocket borne solar observatory, the Multi-Spectral Solar Telescope Array (MSSTA). Advanced Flow Polishing has provided multilayer mirror substrates with sub-angstrom (rms) smoothnesss for the astronomical x ray telescopes and x ray microscopes. The combination of these important technological advancements has paved the way for the development of a Water Window Imaging X Ray Microscope for cancer research.

Automated detection and mapping of crown discolouration caused by jack pine budworm with 2.5 m resolution multispectral imagery

NASA Astrophysics Data System (ADS)

Leckie, Donald G.; Cloney, Ed; Joyce, Steve P.

2005-05-01

Jack pine budworm ( Choristoneura pinus pinus (Free.)) is a native insect defoliator of mainly jack pine ( Pinus banksiana Lamb.) in North America east of the Rocky Mountains. Periodic outbreaks of this insect, which generally last two to three years, can cause growth loss and mortality and have an important impact ecologically and economically in terms of timber production and harvest. The jack pine budworm prefers to feed on current year needles. Their characteristic feeding habits cause discolouration or reddening of the canopy. This red colouration is used to map the distribution and intensity of defoliation that has taken place that year (current defoliation). An accurate and consistent map of the distribution and intensity of budworm defoliation (as represented by the red discolouration) at the stand and within stand level is desirable. Automated classification of multispectral imagery, such as is available from airborne and new high resolution satellite systems, was explored as a viable tool for objectively classifying current discolouration. Airborne multispectral imagery was acquired at a 2.5 m resolution with the Multispectral Electro-optical Imaging Sensor (MEIS). It recorded imagery in six nadir looking spectral bands specifically designed to detect discolouration caused by budworm and a near-infrared band viewing forward at 35° was also used. A 2200 nm middle infrared image was acquired with a Daedalus scanner. Training and test areas of different levels of discolouration were created based on field observations and a maximum likelihood supervized classification was used to estimate four classes of discolouration (nil-trace, light, moderate and severe). Good discrimination was achieved with an overall accuracy of 84% for the four discolouration levels. The moderate discolouration class was the poorest at 73%, because of confusion with both the severe and light classes. Accuracy on a stand basis was also good, and regional and within stand discolouration patterns were portrayed well. Only three or four well-placed spectral bands were needed for a good classification. A narrow red band, a near-infrared and short wave infrared band were most useful. A forward looking band did not improve discolouration estimation, but further testing is needed to confirm this result. This method of detecting and classifying discolouration appears to provide a mapping capability useful for conducting jack pine budworm discolouration surveys and integrating this information into decision support systems, forest inventory, growth and yield predictions and the forest management decision-making process.

Korea Earth Observation Satellite Program

NASA Astrophysics Data System (ADS)

Baek, Myung-Jin; Kim, Zeen-Chul

via Korea Aerospace Research Institute (KARI) as the prime contractor in the area of Korea earth observation satellite program to enhance Korea's space program development capability. In this paper, Korea's on-going and future earth observation satellite programs are introduced: KOMPSAT- 1 (Korea Multi Purpose Satellite-1), KOMPSAT-2 and Communication, Broadcasting and Meteorological Satellite (CBMS) program. KOMPSAT-1 satellite successfully launched in December 1999 with Taurus launch vehicle. Since launch, KOMPSAT-1 is downlinking images of Korea Peninsular every day. Until now, KOMPSAT-1 has been operated more than 2 and half years without any major hardware malfunction for the mission operation. KOMPSAT-1 payload has 6.6m panchromatic spatial resolution at 685 km on-orbit and the spacecraft bus had NASA TOMS-EP (Total Ozone Mapping Spectrometer-Earth Probe) spacecraft bus heritage designed and built by TRW, U.S.A.KOMPSAT-1 program was international co-development program between KARI and TRW funded by Korean Government. be launched in 2004. Main mission objective is to provide geo-information products based on the multi-spectral high resolution sensor called Multi-Spectral Camera (MSC) which will provide 1m panchromatic and 4m multi-spectral high resolution images. ELOP of Israel is the prime contractor of the MSC payload system and KARI is the total system prime contractor including spacecraft bus development and ground segment. KARI also has the contract with Astrium of Europe for the purpose of technical consultation and hardware procurement. Based on the experience throughout KOMPSAT-1 and KOMPSAT-2 space system development, Korea is expecting to establish the infrastructure of developing satellite system. Currently, KOMPSAT-2 program is in the critical design stage. are scheduled to launch in 2008 and in 2014, respectively. The mission of CBMS consists of two areas. One is of space technology test for the communications mission, and the other is of a real- time environmental observation for meteorological mission on the geosynchronous orbit for public services. The CBMS is expected to weigh about 2 ~ 2.5 tons, and 6 channels of Ka-band and S- band transponder are equipped for communications service and observation payloads such as meteorological and ocean sensors. To increase the reliability of the first CBMS, a cooperative development with advanced foreign companies of the space business is being considered.

Application and evaluation of ISVR method in QuickBird image fusion

NASA Astrophysics Data System (ADS)

Cheng, Bo; Song, Xiaolu

2014-05-01

QuickBird satellite images are widely used in many fields, and applications have put forward high requirements for the integration of the spatial information and spectral information of the imagery. A fusion method for high resolution remote sensing images based on ISVR is identified in this study. The core principle of ISVS is taking the advantage of radicalization targeting to remove the effect of different gain and error of satellites' sensors. Transformed from DN to radiance, the multi-spectral image's energy is used to simulate the panchromatic band. The linear regression analysis is carried through the simulation process to find a new synthetically panchromatic image, which is highly linearly correlated to the original panchromatic image. In order to evaluate, test and compare the algorithm results, this paper used ISVR and other two different fusion methods to give a comparative study of the spatial information and spectral information, taking the average gradient and the correlation coefficient as an indicator. Experiments showed that this method could significantly improve the quality of fused image, especially in preserving spectral information, to maximize the spectral information of original multispectral images, while maintaining abundant spatial information.

Applying Lidar and High-Resolution Multispectral Imagery for Improved Quantification and Mapping of Tundra Vegetation Structure and Distribution in the Alaskan Arctic

NASA Astrophysics Data System (ADS)

Greaves, Heather E.

Climate change is disproportionately affecting high northern latitudes, and the extreme temperatures, remoteness, and sheer size of the Arctic tundra biome have always posed challenges that make application of remote sensing technology especially appropriate. Advances in high-resolution remote sensing continually improve our ability to measure characteristics of tundra vegetation communities, which have been difficult to characterize previously due to their low stature and their distribution in complex, heterogeneous patches across large landscapes. In this work, I apply terrestrial lidar, airborne lidar, and high-resolution airborne multispectral imagery to estimate tundra vegetation characteristics for a research area near Toolik Lake, Alaska. Initially, I explored methods for estimating shrub biomass from terrestrial lidar point clouds, finding that a canopy-volume based algorithm performed best. Although shrub biomass estimates derived from airborne lidar data were less accurate than those from terrestrial lidar data, algorithm parameters used to derive biomass estimates were similar for both datasets. Additionally, I found that airborne lidar-based shrub biomass estimates were just as accurate whether calibrated against terrestrial lidar data or harvested shrub biomass--suggesting that terrestrial lidar potentially could replace destructive biomass harvest. Along with smoothed Normalized Differenced Vegetation Index (NDVI) derived from airborne imagery, airborne lidar-derived canopy volume was an important predictor in a Random Forest model trained to estimate shrub biomass across the 12.5 km2 covered by our lidar and imagery data. The resulting 0.80 m resolution shrub biomass maps should provide important benchmarks for change detection in the Toolik area, especially as deciduous shrubs continue to expand in tundra regions. Finally, I applied 33 lidar- and imagery-derived predictor layers in a validated Random Forest modeling approach to map vegetation community distribution at 20 cm resolution across the data collection area, creating maps that will enable validation of coarser maps, as well as study of fine-scale ecological processes in the area. These projects have pushed the limits of what can be accomplished for vegetation mapping using airborne remote sensing in a challenging but important region; it is my hope that the methods explored here will illuminate potential paths forward as landscapes and technologies inevitably continue to change.

Phenological dynamics of arctic tundra vegetation and its implications on satellite imagery interpretation

NASA Astrophysics Data System (ADS)

Juutinen, Sari; Aurela, Mika; Mikola, Juha; Räsänen, Aleksi; Virtanen, Tarmo

2016-04-01

Remote sensing is a key methodology when monitoring the responses of arctic ecosystems to climatic warming. The short growing season and rapid vegetation development, however, set demands to the timing of image acquisition in the arctic. We used multispectral very high spatial resolution satellite images to study the effect of vegetation phenology on the spectral reflectance and image interpretation in the low arctic tundra in coastal Siberia (Tiksi, 71°35'39"N, 128°53'17"E). The study site mainly consists of peatlands, tussock, dwarf shrub, and grass tundra, and stony areas with some lichen and shrub patches. We tested the hypotheses that (1) plant phenology is responsive to the interannual weather variation and (2) the phenological state of vegetation has an impact on satellite image interpretation and the ability to distinguish between the plant communities. We used an empirical transfer function with temperature sums as drivers to reconstruct daily leaf area index (LAI) for the different plant communities for years 2005, and 2010-2014 based on measured LAI development in summer 2014. Satellite images, taken during growing seasons, were acquired for two years having late and early spring, and short and long growing season, respectively. LAI dynamics showed considerable interannual variation due to weather variation, and particularly the relative contribution of graminoid dominated communities was sensitive to these phenology shifts. We have also analyzed the differences in the reflectance values between the two satellite images taking account the LAI dynamics. These results will increase our understanding of the pitfalls that may arise from the timing of image acquisition when interpreting the vegetation structure in a heterogeneous tundra landscape. Very high spatial resolution multispectral images are available at reasonable cost, but not in high temporal resolution, which may lead to compromises when matching ground truth and the imagery. On the other hand, to identify existing plant communities, high resolution images are needed due fragmented nature of tundra vegetation communities. Temporal differences in the phenology among different plant functional types may also obscure the image interpretations when using spatially low resolution images in heterogeneous landscapes. Phenological features of plant communities should be acknowledged, when plant functional or community type based classifications are used in models to estimate global greenhouse gas emissions and when monitoring changes in vegetation are monitored, for example to indicate permafrost thawing or changes in growing season lengths.

Optimizing spectral resolutions for the classification of C3 and C4 grass species, using wavelengths of known absorption features

NASA Astrophysics Data System (ADS)

Adjorlolo, Clement; Cho, Moses A.; Mutanga, Onisimo; Ismail, Riyad

2012-01-01

Hyperspectral remote-sensing approaches are suitable for detection of the differences in 3-carbon (C3) and four carbon (C4) grass species phenology and composition. However, the application of hyperspectral sensors to vegetation has been hampered by high-dimensionality, spectral redundancy, and multicollinearity problems. In this experiment, resampling of hyperspectral data to wider wavelength intervals, around a few band-centers, sensitive to the biophysical and biochemical properties of C3 or C4 grass species is proposed. The approach accounts for an inherent property of vegetation spectral response: the asymmetrical nature of the inter-band correlations between a waveband and its shorter- and longer-wavelength neighbors. It involves constructing a curve of weighting threshold of correlation (Pearson's r) between a chosen band-center and its neighbors, as a function of wavelength. In addition, data were resampled to some multispectral sensors-ASTER, GeoEye-1, IKONOS, QuickBird, RapidEye, SPOT 5, and WorldView-2 satellites-for comparative purposes, with the proposed method. The resulting datasets were analyzed, using the random forest algorithm. The proposed resampling method achieved improved classification accuracy (κ=0.82), compared to the resampled multispectral datasets (κ=0.78, 0.65, 0.62, 0.59, 0.65, 0.62, 0.76, respectively). Overall, results from this study demonstrated that spectral resolutions for C3 and C4 grasses can be optimized and controlled for high dimensionality and multicollinearity problems, yet yielding high classification accuracies. The findings also provide a sound basis for programming wavebands for future sensors.

The Prototype HyspIRI Thermal Infrared Radiometer (PHyTIR): A High Speed, Multispectral, Thermal Instrument Development in Support of HyspIRI-TIR

NASA Technical Reports Server (NTRS)

Hook, Simon

2011-01-01

The Prototype HyspIRI Thermal Infrared Radiometer (PHyTIR) is being developed as part of the risk reduction activities associated with the Hyperspectral Infrared Imager (HyspIRI). The HyspIRI mission was recommended by the National Research Council Decadal Survey and includes a visible shortwave infrared (SWIR) pushboom spectrometer and a multispectral whiskbroom thermal infrared (TIR) imager. 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. The HyspIRI TIR system will have 60m ground resolution, better than 200mK noise equivalent delta temperature (NEDT), 0.5C absolute temperature resolution with a 5-day repeat from LEO orbit. PHyTIR addresses the technology readiness level (TRL) of certain key subsystems of the TIR imager, primarily the detector assembly and scanning mechanism. PHyTIR will use Mercury Cadmium Telluride (MCT) technology at the focal plane and operate in time delay integration mode. A custom read out integrated circuit (ROIC) will provide the high speed readout hence allowing the high data rates needed for the 5 day repeat. PHyTIR will also demonstrate a newly developed interferometeric metrology system. This system 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 post-processing (e.g. geo-rectification computations).

Characterization of instream hydraulic and riparian habitat conditions and stream temperatures of the Upper White River Basin, Washington, using multispectral imaging systems

USGS Publications Warehouse

Black, Robert W.; Haggland, Alan; Crosby, Greg

2003-01-01

Instream hydraulic and riparian habitat conditions and stream temperatures were characterized for selected stream segments in the Upper White River Basin, Washington. An aerial multispectral imaging system used digital cameras to photograph the stream segments across multiple wavelengths to characterize fish habitat and temperature conditions. All imageries were georeferenced. Fish habitat features were photographed at a resolution of 0.5 meter and temperature imageries were photographed at a 1.0-meter resolution. The digital multispectral imageries were classified using commercially available software. Aerial photographs were taken on September 21, 1999. Field habitat data were collected from August 23 to October 12, 1999, to evaluate the measurement accuracy and effectiveness of the multispectral imaging in determining the extent of the instream habitat variables. Fish habitat types assessed by this method were the abundance of instream hydraulic features such as pool and riffle habitats, turbulent and non-turbulent habitats, riparian composition, the abundance of large woody debris in the stream and riparian zone, and stream temperatures. Factors such as the abundance of instream woody debris, the location and frequency of pools, and stream temperatures generally are known to have a significant impact on salmon. Instream woody debris creates the habitat complexity necessary to maintain a diverse and healthy salmon population. The abundance of pools is indicative of a stream's ability to support fish and other aquatic organisms. Changes in water temperature can affect aquatic organisms by altering metabolic rates and oxygen requirements, altering their sensitivity to toxic materials and affecting their ability to avoid predators. The specific objectives of this project were to evaluate the use of an aerial multispectral imaging system to accurately identify instream hydraulic features and surface-water temperatures in the Upper White River Basin, to use the multispectral system to help establish baseline instream/riparian habitat conditions in the study area, and to qualitatively assess the imaging system for possible use in other Puget Sound rivers. For the most part, all multispectral imagery-based estimates of total instream riffle and pool area were less than field measurements. The imagery-based estimates for riffle habitat area ranged from 35.5 to 83.3 percent less than field measurements. Pool habitat estimates ranged from 139.3 percent greater than field measurements to 94.0 percent less than field measurements. Multispectral imagery-based estimates of turbulent habitat conditions ranged from 9.3 percent greater than field measurements to 81.6 percent less than field measurements. Multispectral imagery-based estimates of non-turbulent habitat conditions ranged from 27.7 to 74.1 percent less than field measurements. The absolute average percentage of difference between field and imagery-based habitat type areas was less for the turbulent and non-turbulent habitat type categories than for pools and riffles. The estimate of woody debris by multispectral imaging was substantially different than field measurements; percentage of differences ranged from +373.1 to -100 percent. Although the total area of riffles, pools, and turbulent and non-turbulent habitat types measured in the field were all substantially higher than those estimated from the multispectral imagery, the percentage of composition of each habitat type was not substantially different between the imagery-based estimates and field measurements.

A review of future remote sensing satellite capabilities

NASA Technical Reports Server (NTRS)

Calabrese, M. A.

1980-01-01

Existing, planned and future NASA capabilities in the field of remote sensing satellites are reviewed in relation to the use of remote sensing techniques for the identification of irrigated lands. The status of the currently operational Landsat 2 and 3 satellites is indicated, and it is noted that Landsat D is scheduled to be in operation in two years. The orbital configuration and instrumentation of Landsat D are discussed, with particular attention given to the thematic mapper, which is expected to improve capabilities for small field identification and crop discrimination and classification. Future possibilities are then considered, including a multi-spectral resource sampler supplying high spatial and temporal resolution data possibly based on push-broom scanning, Shuttle-maintained Landsat follow-on missions, a satellite to obtain high-resolution stereoscopic data, further satellites providing all-weather radar capability and the Large Format Camera.

A new hyperspectral image compression paradigm based on fusion

NASA Astrophysics Data System (ADS)

Guerra, Raúl; Melián, José; López, Sebastián.; Sarmiento, Roberto

2016-10-01

The on-board compression of remote sensed hyperspectral images is an important task nowadays. One of the main difficulties is that the compression of these images must be performed in the satellite which carries the hyperspectral sensor. Hence, this process must be performed by space qualified hardware, having area, power and speed limitations. Moreover, it is important to achieve high compression ratios without compromising the quality of the decompress image. In this manuscript we proposed a new methodology for compressing hyperspectral images based on hyperspectral image fusion concepts. The proposed compression process has two independent steps. The first one is to spatially degrade the remote sensed hyperspectral image to obtain a low resolution hyperspectral image. The second step is to spectrally degrade the remote sensed hyperspectral image to obtain a high resolution multispectral image. These two degraded images are then send to the earth surface, where they must be fused using a fusion algorithm for hyperspectral and multispectral image, in order to recover the remote sensed hyperspectral image. The main advantage of the proposed methodology for compressing remote sensed hyperspectral images is that the compression process, which must be performed on-board, becomes very simple, being the fusion process used to reconstruct image the more complex one. An extra advantage is that the compression ratio can be fixed in advanced. Many simulations have been performed using different fusion algorithms and different methodologies for degrading the hyperspectral image. The results obtained in the simulations performed corroborate the benefits of the proposed methodology.

Earth mapping - aerial or satellite imagery comparative analysis

NASA Astrophysics Data System (ADS)

Fotev, Svetlin; Jordanov, Dimitar; Lukarski, Hristo

Nowadays, solving the tasks for revision of existing map products and creation of new maps requires making a choice of the land cover image source. The issue of the effectiveness and cost of the usage of aerial mapping systems versus the efficiency and cost of very-high resolution satellite imagery is topical [1, 2, 3, 4]. The price of any remotely sensed image depends on the product (panchromatic or multispectral), resolution, processing level, scale, urgency of task and on whether the needed image is available in the archive or has to be requested. The purpose of the present work is: to make a comparative analysis between the two approaches for mapping the Earth having in mind two parameters: quality and cost. To suggest an approach for selection of the map information sources - airplane-based or spacecraft-based imaging systems with very-high spatial resolution. Two cases are considered: area that equals approximately one satellite scene and area that equals approximately the territory of Bulgaria.

NAOMI instrument: a product line of compact and versatile cameras designed for high resolution missions in Earth observation

NASA Astrophysics Data System (ADS)

Luquet, Ph.; Chikouche, A.; Benbouzid, A. B.; Arnoux, J. J.; Chinal, E.; Massol, C.; Rouchit, P.; De Zotti, S.

2017-11-01

EADS Astrium is currently developing a new product line of compact and versatile instruments for high resolution missions in Earth Observation. First version has been developed in the frame of the ALSAT-2 contract awarded by the Algerian Space Agency (ASAL) to EADS Astrium. The Silicon Carbide Korsch-type telescope coupled with a multilines detector array offers a 2.5 m GSD in PAN band at Nadir @ 680 km altitude (10 m GSD in the four multispectral bands) with a 17.5 km swath width. This compact camera - 340 (W) x 460 (L) x 510 (H) mm3, 13 kg - is embarked on a Myriade-type small platform. The electronics unit accommodates video, housekeeping, and thermal control functions and also a 64 Gbit mass memory. Two satellites are developed; the first one is planned to be launched on mid 2009. Several other versions of the instrument have already been defined with enhanced resolution or/and larger field of view.

Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Overview

USGS Publications Warehouse

,

2008-01-01

The National Aeronautics and Space Administration (NASA) launched Terra, the Earth Observing System's (EOS) flagship satellite platform on December 18, 1999. The polar-orbiting Terra contains five remote sensing instruments, which enable the scientific study and analyses of global terrestrial processes and manifestations of global change. One of the five instruments is the multispectral Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), which is built in Japan by a consortium of government, industry, and research groups. It has three spectral bands in the visible near-infrared region (VNIR), six bands in the shortwave infrared region (SWIR), and five bands in the thermal infrared region (TIR), with 15-, 30-, and 90-meter ground resolutions, respectively. This combination of wide spectral coverage and high spatial resolution allows ASTER to discriminate among a wide variety of surface materials. The VNIR subsystem also has a backward-viewing telescope for high-resolution (15-meter) stereoscopic observation in the along-track direction, which facilitates the generation of digital elevation models (DEM).

Multispectral atmospheric mapping sensor of mesoscale water vapor features

NASA Technical Reports Server (NTRS)

Menzel, P.; Jedlovec, G.; Wilson, G.; Atkinson, R.; Smith, W.

1985-01-01

The Multispectral atmospheric mapping sensor was checked out for specified spectral response and detector noise performance in the eight visible and three infrared (6.7, 11.2, 12.7 micron) spectral bands. A calibration algorithm was implemented for the infrared detectors. Engineering checkout flights on board the ER-2 produced imagery at 50 m resolution in which water vapor features in the 6.7 micron spectral band are most striking. These images were analyzed on the Man computer Interactive Data Access System (McIDAS). Ground truth and ancillary data was accessed to verify the calibration.

NEOCE: a new external occulting coronagraph experiment for ultimate observations of the chromosphere, corona and interface

NASA Astrophysics Data System (ADS)

Damé, Luc; Fineschi, Silvano; Kuzin, Sergey; Von Fay-Siebenburgen, Erdélyi Robert

Several ground facilities and space missions are currently dedicated to the study of the Sun at high resolution and of the solar corona in particular. However, and despite significant progress with the advent of space missions and UV, EUV and XUV direct observations of the hot chromosphere and million-degrees coronal plasma, much is yet to be achieved in the understanding of these high temperatures, fine dynamic dissipative structures and of the coronal heating in general. Recent missions have shown the definite role of a wide range of waves and of the magnetic field deep in the inner corona, at the chromosphere-corona interface, where dramatic and physically fundamental changes occur. The dynamics of the chromosphere and corona is controlled and governed by the emerging magnetic field. Accordingly, the direct measurement of the chromospheric and coronal magnetic fields is of prime importance. The solar corona consists of many localised loop-like structures or threads with the plasmas brightening and fading independently. The plasma evolution in each thread is believed to be related to the formation of filaments, each one being dynamic, in a non-equilibrium state. The mechanism sustaining this dynamics, oscillations or waves (Alfvén or other magneto-plasma waves), requires both very high-cadence, multi-spectral observations, and high resolution and coronal magnetometry. This is foreseen in the future Space Mission NEOCE (New External Occulting Coronagraph Experiment), the ultimate new generation high-resolution coronagraphic heliospheric mission, to be proposed for ESA M4. NEOCE, an evolution of the HiRISE mission, is ideally placed at the L5 Lagrangian point (for a better follow-up of CMEs), and provides FUV imaging and spectro-imaging, EUV and XUV imaging and spectroscopy, and ultimate coronagraphy by a remote external occulter (two satellites in formation flying 375 m apart minimizing scattered light) allowing to characterize temperature, densities and velocities up to the solar upper chromosphere, transition zone and inner corona with, in particular, 2D very high resolution multi-spectral imaging-spectroscopy and direct coronal magnetic field measurement: a unique set of tools to understand the structuration and onset of coronal heating. We give a detailed account of the proposed mission profile, and its major scientific objectives and model payload (in particular of the SuperASPIICS package of visible, NIR and UV, Lyman-Alpha and OVI, coronagraphs).

Using WorldView-2 Imagery to Track Flooding in Thailand in a Multi-Asset Sensorweb

NASA Technical Reports Server (NTRS)

McLaren, David; Doubleday, Joshua; Chien, Steve

2012-01-01

For the flooding seasons of 2011-2012 multiple space assets were used in a "sensorweb" to track major flooding in Thailand. Worldview-2 multispectral data was used in this effort and provided extremely high spatial resolution (2m / pixel) multispectral (8 bands at 0.45-1.05 micrometer spectra) data from which mostly automated workflows derived surface water extent and volumetric water information for use by a range of NGO and national authorities. We first describe how Worldview-2 and its data was integrated into the overall flood tracking sensorweb. We next describe the use of Support Vector Machine learning techniques that were used to derive surface water extent classifiers. Then we describe the fusion of surface water extent and digital elevation map (DEM) data to derive volumetric water calculations. Finally we discuss key future work such as speeding up the workflows and automating the data registration process (the only portion of the workflow requiring human input).

Using Multitemporal and Multispectral Airborne Lidar to Assess Depth of Peat Loss and Correspondence With a New Active Normalized Burn Ratio for Wildfires

NASA Astrophysics Data System (ADS)

Chasmer, L. E.; Hopkinson, C. D.; Petrone, R. M.; Sitar, M.

2017-12-01

Accuracy of depth of burn (an indicator of consumption) in peatland soils using prefire and postfire airborne light detection and ranging (lidar) data is determined within a wetland-upland forest environment near Fort McMurray, Alberta, Canada. The relationship between peat soil burn depth and an "active" normalized burn ratio (ANBR) is also examined beneath partially and fully burned forest and understory canopies using state-of-the-art active reflectance from a multispectral lidar compared with normalized burn ratio (NBR) derived from Landsat 7 ETM+. We find significant correspondence between depth of burn, lidar-derived ANBR, and difference NBR (dNBR) from Landsat. However, low-resolution optical imagery excludes peatland burn losses in transition zones, which are highly sensitive to peat loss via combustion. The findings presented here illustrate the utility of this new remote sensing technology for expanding an area of research where it has previously been challenging to spatially detect and quantify such wildfire burn losses.

Super-resolved linear fluorescence localization microscopy using photostable fluorophores: A virtual microscopy study

NASA Astrophysics Data System (ADS)

Birk, Udo; Szczurek, Aleksander; Cremer, Christoph

2017-12-01

Current approaches to overcome the conventional limit of the resolution potential of light microscopy (of about 200 nm for visible light), often suffer from non-linear effects, which render the quantification of the image intensities in the reconstructions difficult, and also affect the quantification of the biological structure under investigation. As an attempt to face these difficulties, we discuss a particular method of localization microscopy which is based on photostable fluorescent dyes. The proposed method can potentially be implemented as a fast alternative for quantitative localization microscopy, circumventing the need for the acquisition of thousands of image frames and complex, highly dye-specific imaging buffers. Although the need for calibration remains in order to extract quantitative data (such as the number of emitters), multispectral approaches are largely facilitated due to the much less stringent requirements on imaging buffers. Furthermore, multispectral acquisitions can be readily obtained using commercial instrumentation such as e.g. the conventional confocal laser scanning microscope.

Estimation of Mangrove Forest Aboveground Biomass Using Multispectral Bands, Vegetation Indices and Biophysical Variables Derived from Optical Satellite Imageries: Rapideye, Planetscope and SENTINEL-2

NASA Astrophysics Data System (ADS)

Balidoy Baloloy, Alvin; Conferido Blanco, Ariel; Gumbao Candido, Christian; Labadisos Argamosa, Reginal Jay; Lovern Caboboy Dumalag, John Bart; Carandang Dimapilis, Lee, , Lady; Camero Paringit, Enrico

2018-04-01

Aboveground biomass estimation (AGB) is essential in determining the environmental and economic values of mangrove forests. Biomass prediction models can be developed through integration of remote sensing, field data and statistical models. This study aims to assess and compare the biomass predictor potential of multispectral bands, vegetation indices and biophysical variables that can be derived from three optical satellite systems: the Sentinel-2 with 10 m, 20 m and 60 m resolution; RapidEye with 5m resolution and PlanetScope with 3m ground resolution. Field data for biomass were collected from a Rhizophoraceae-dominated mangrove forest in Masinloc, Zambales, Philippines where 30 test plots (1.2 ha) and 5 validation plots (0.2 ha) were established. Prior to the generation of indices, images from the three satellite systems were pre-processed using atmospheric correction tools in SNAP (Sentinel-2), ENVI (RapidEye) and python (PlanetScope). The major predictor bands tested are Blue, Green and Red, which are present in the three systems; and Red-edge band from Sentinel-2 and Rapideye. The tested vegetation index predictors are Normalized Differenced Vegetation Index (NDVI), Soil-adjusted Vegetation Index (SAVI), Green-NDVI (GNDVI), Simple Ratio (SR), and Red-edge Simple Ratio (SRre). The study generated prediction models through conventional linear regression and multivariate regression. Higher coefficient of determination (r2) values were obtained using multispectral band predictors for Sentinel-2 (r2 = 0.89) and Planetscope (r2 = 0.80); and vegetation indices for RapidEye (r2 = 0.92). Multivariate Adaptive Regression Spline (MARS) models performed better than the linear regression models with r2 ranging from 0.62 to 0.92. Based on the r2 and root-mean-square errors (RMSE's), the best biomass prediction model per satellite were chosen and maps were generated. The accuracy of predicted biomass maps were high for both Sentinel-2 (r2 = 0.92) and RapidEye data (r2 = 0.91).

Area-to-point regression kriging for pan-sharpening

NASA Astrophysics Data System (ADS)

Wang, Qunming; Shi, Wenzhong; Atkinson, Peter M.

2016-04-01

Pan-sharpening is a technique to combine the fine spatial resolution panchromatic (PAN) band with the coarse spatial resolution multispectral bands of the same satellite to create a fine spatial resolution multispectral image. In this paper, area-to-point regression kriging (ATPRK) is proposed for pan-sharpening. ATPRK considers the PAN band as the covariate. Moreover, ATPRK is extended with a local approach, called adaptive ATPRK (AATPRK), which fits a regression model using a local, non-stationary scheme such that the regression coefficients change across the image. The two geostatistical approaches, ATPRK and AATPRK, were compared to the 13 state-of-the-art pan-sharpening approaches summarized in Vivone et al. (2015) in experiments on three separate datasets. ATPRK and AATPRK produced more accurate pan-sharpened images than the 13 benchmark algorithms in all three experiments. Unlike the benchmark algorithms, the two geostatistical solutions precisely preserved the spectral properties of the original coarse data. Furthermore, ATPRK can be enhanced by a local scheme in AATRPK, in cases where the residuals from a global regression model are such that their spatial character varies locally.

Ultrahigh resolution photographic films for X-ray/EUV/FUV astronomy

NASA Technical Reports Server (NTRS)

Hoover, Richard B.; Walker, Arthur B. C., Jr.; Deforest, Craig E.; Watts, Richard; Tarrio, Charles

1993-01-01

The quest for ultrahigh resolution full-disk images of the sun at soft X-ray/EUV/FUV wavelengths has increased the demand for photographic films with broad spectral sensitivity, high spatial resolution, and wide dynamic range. These requirements were made more stringent by the recent development of multilayer telescopes and coronagraphs capable of operating at normal incidence at soft X-ray/EUV wavelengths. Photographic films are the only detectors now available with the information storage capacity and dynamic range such as is required for recording images of the solar disk and corona simultaneously with sub arc second spatial resolution. During the Stanford/MSFC/LLNL Rocket X-Ray Spectroheliograph and Multi-Spectral Solar Telescope Array (MSSTA) programs, we utilized photographic films to obtain high resolution full-disk images of the sun at selected soft X-ray/EUV/FUV wavelengths. In order to calibrate our instrumentation for quantitative analysis of our solar data and to select the best emulsions and processing conditions for the MSSTA reflight, we recently tested several photographic films. These studies were carried out at the NIST SURF II synchrotron and the Stanford Synchrotron Radiation Laboratory. In this paper, we provide the results of those investigations.

Application of LC and LCoS in Multispectral Polarized Scene Projector (MPSP)

NASA Astrophysics Data System (ADS)

Yu, Haiping; Guo, Lei; Wang, Shenggang; Lippert, Jack; Li, Le

2017-02-01

A Multispectral Polarized Scene Projector (MPSP) had been developed in the short-wave infrared (SWIR) regime for the test & evaluation (T&E) of spectro-polarimetric imaging sensors. This MPSP generates multispectral and hyperspectral video images (up to 200 Hz) with 512×512 spatial resolution with active spatial, spectral, and polarization modulation with controlled bandwidth. It projects input SWIR radiant intensity scenes from stored memory with user selectable wavelength and bandwidth, as well as polarization states (six different states) controllable on a pixel level. The spectral contents are implemented by a tunable filter with variable bandpass built based on liquid crystal (LC) material, together with one passive visible and one passive SWIR cholesteric liquid crystal (CLC) notch filters, and one switchable CLC notch filter. The core of the MPSP hardware is the liquid-crystal-on-silicon (LCoS) spatial light modulators (SLMs) for intensity control and polarization modulation.

Mapping lipid and collagen by multispectral photoacoustic imaging of chemical bond vibration

NASA Astrophysics Data System (ADS)

Wang, Pu; Wang, Ping; Wang, Han-Wei; Cheng, Ji-Xin

2012-09-01

Photoacoustic microscopy using vibrational overtone absorption as a contrast mechanism allows bond-selective imaging of deep tissues. Due to the spectral similarity of molecules in the region of overtone vibration, it is difficult to interrogate chemical components using photoacoustic signal at single excitation wavelength. Here we demonstrate that lipids and collagen, two critical markers for many kinds of diseases, can be distinguished by multispectral photoacoustic imaging of the first overtone of C-H bond. A phantom consisting of rat-tail tendon and fat was constructed to demonstrate this technique. Wavelengths between 1650 and 1850 nm were scanned to excite both the first overtone and combination bands of C-H bonds. B-scan multispectral photoacoustic images, in which each pixel contains a spectrum, were analyzed by a multivariate curve resolution-alternating least squares algorithm to recover the spatial distribution of collagen and lipids in the phantom.

Mapping lipid and collagen by multispectral photoacoustic imaging of chemical bond vibration.

PubMed

Wang, Pu; Wang, Ping; Wang, Han-Wei; Cheng, Ji-Xin

2012-09-01

Photoacoustic microscopy using vibrational overtone absorption as a contrast mechanism allows bond-selective imaging of deep tissues. Due to the spectral similarity of molecules in the region of overtone vibration, it is difficult to interrogate chemical components using photoacoustic signal at single excitation wavelength. Here we demonstrate that lipids and collagen, two critical markers for many kinds of diseases, can be distinguished by multispectral photoacoustic imaging of the first overtone of C-H bond. A phantom consisting of rat-tail tendon and fat was constructed to demonstrate this technique. Wavelengths between 1650 and 1850 nm were scanned to excite both the first overtone and combination bands of C-H bonds. B-scan multispectral photoacoustic images, in which each pixel contains a spectrum, were analyzed by a multivariate curve resolution-alternating least squares algorithm to recover the spatial distribution of collagen and lipids in the phantom.

Contribution of space platforms to a ground and airborne remote sensing programme over active Italian volcanoes

NASA Technical Reports Server (NTRS)

Cassinis, R. (Principal Investigator); Lechi, G. M.; Marino, C. M.; Tonelli, A. M.

1974-01-01

The author has identified the following significant results. A method has been suggested for the forecasting of the lateral eruptions of Mount Etna, through the multispectral analysis of the vegetation behavior. Unknown geological lineaments which seem to be related to deep crustal movements have been discovered using the ERTS-1 imagery. Results in the geological field were obtained in the study of the general structure of the Alpine range. In the field of official vegetation classification, ERTS-1 images were used for a preliminary study of rice fields in northern Italy. Very good experimental results have been obtained using the Skylab multispectral photographs. In the field of hydrogeology and soil type discrimination discoveries of unknown paleoriver beds have been made in the northeastern part of the Po Valley using the multispectral imagery of SL3. The superior resolution of Skylab was a fundamental element for the success of this investigation.

Workshop on the Use of Future Multispectral Imaging Capabilities for Lithologic Mapping: Workshop summary

NASA Technical Reports Server (NTRS)

Settle, M.; Adams, J.

1982-01-01

Improved orbital imaging capabilities from the standpoint of different scientific disciplines, such as geology, botany, hydrology, and geography were evaluated. A discussion on how geologists might exploit the anticipated measurement capabilities of future orbital imaging systems to discriminate and characterize different types of geologic materials exposed at the Earth's surface is presented. Principle objectives are to summarize past accomplishments in the use of multispectral imaging techniques for lithologic mapping; to identify critical gaps in earlier research efforts that currently limit the ability to extract useful information about the physical and chemical characteristics of geological materials from orbital multispectral surveys; and to define major thresholds, resolution and sensitivity within the visible and infrared portions of the electromagnetic spectrum which, if achieved would result in significant improvement in our ability to discriminate and characterize different geological materials exposed at the Earth's surface.

Terrain Categorization using LIDAR and Multi-Spectral Data

DTIC Science & Technology

2007-01-01

the same spatial resolution cell will be distinguished. 3. PROCESSING The LIDAR data set used in this study was from a discrete-return...smoothing in the spatial dimension. While it was possible to distinguish different classes of materials using this technique, the spatial resolution was...alone and a combination of the two data-types. Results are compared to significant ground truth information. Keywords: LIDAR, multi- spectral

Forest cover type analysis of New England forests using innovative WorldView-2 imagery

NASA Astrophysics Data System (ADS)

Kovacs, Jenna M.

For many years, remote sensing has been used to generate land cover type maps to create a visual representation of what is occurring on the ground. One significant use of remote sensing is the identification of forest cover types. New England forests are notorious for their especially complex forest structure and as a result have been, and continue to be, a challenge when classifying forest cover types. To most accurately depict forest cover types occurring on the ground, it is essential to utilize image data that have a suitable combination of both spectral and spatial resolution. The WorldView-2 (WV2) commercial satellite, launched in 2009, is the first of its kind, having both high spectral and spatial resolutions. WV2 records eight bands of multispectral imagery, four more than the usual high spatial resolution sensors, and has a pixel size of 1.85 meters at the nadir. These additional bands have the potential to improve classification detail and classification accuracy of forest cover type maps. For this reason, WV2 imagery was utilized on its own, and in combination with Landsat 5 TM (LS5) multispectral imagery, to evaluate whether these image data could more accurately classify forest cover types. In keeping with recent developments in image analysis, an Object-Based Image Analysis (OBIA) approach was used to segment images of Pawtuckaway State Park and nearby private lands, an area representative of the typical complex forest structure found in the New England region. A Classification and Regression Tree (CART) analysis was then used to classify image segments at two levels of classification detail. Accuracies for each forest cover type map produced were generated using traditional and area-based error matrices, and additional standard accuracy measures (i.e., KAPPA) were generated. The results from this study show that there is value in analyzing imagery with both high spectral and spatial resolutions, and that WV2's new and innovative bands can be useful for the classification of complex forest structures.

Impervious surfaces mapping using high resolution satellite imagery

NASA Astrophysics Data System (ADS)

Shirmeen, Tahmina

In recent years, impervious surfaces have emerged not only as an indicator of the degree of urbanization, but also as an indicator of environmental quality. As impervious surface area increases, storm water runoff increases in velocity, quantity, temperature and pollution load. Any of these attributes can contribute to the degradation of natural hydrology and water quality. Various image processing techniques have been used to identify the impervious surfaces, however, most of the existing impervious surface mapping tools used moderate resolution imagery. In this project, the potential of standard image processing techniques to generate impervious surface data for change detection analysis using high-resolution satellite imagery was evaluated. The city of Oxford, MS was selected as the study site for this project. Standard image processing techniques, including Normalized Difference Vegetation Index (NDVI), Principal Component Analysis (PCA), a combination of NDVI and PCA, and image classification algorithms, were used to generate impervious surfaces from multispectral IKONOS and QuickBird imagery acquired in both leaf-on and leaf-off conditions. Accuracy assessments were performed, using truth data generated by manual classification, with Kappa statistics and Zonal statistics to select the most appropriate image processing techniques for impervious surface mapping. The performance of selected image processing techniques was enhanced by incorporating Soil Brightness Index (SBI) and Greenness Index (GI) derived from Tasseled Cap Transformed (TCT) IKONOS and QuickBird imagery. A time series of impervious surfaces for the time frame between 2001 and 2007 was made using the refined image processing techniques to analyze the changes in IS in Oxford. It was found that NDVI and the combined NDVI--PCA methods are the most suitable image processing techniques for mapping impervious surfaces in leaf-off and leaf-on conditions respectively, using high resolution multispectral imagery. It was also found that IS data generated by these techniques can be refined by removing the conflicting dry soil patches using SBI and GI obtained from TCT of the same imagery used for IS data generation. The change detection analysis of the IS time series shows that Oxford experienced the major changes in IS from the year 2001 to 2004 and 2006 to 2007.

Intensity-hue-saturation-based image fusion using iterative linear regression

NASA Astrophysics Data System (ADS)

Cetin, Mufit; Tepecik, Abdulkadir

2016-10-01

The image fusion process basically produces a high-resolution image by combining the superior features of a low-resolution spatial image and a high-resolution panchromatic image. Despite its common usage due to its fast computing capability and high sharpening ability, the intensity-hue-saturation (IHS) fusion method may cause some color distortions, especially when a large number of gray value differences exist among the images to be combined. This paper proposes a spatially adaptive IHS (SA-IHS) technique to avoid these distortions by automatically adjusting the exact spatial information to be injected into the multispectral image during the fusion process. The SA-IHS method essentially suppresses the effects of those pixels that cause the spectral distortions by assigning weaker weights to them and avoiding a large number of redundancies on the fused image. The experimental database consists of IKONOS images, and the experimental results both visually and statistically prove the enhancement of the proposed algorithm when compared with the several other IHS-like methods such as IHS, generalized IHS, fast IHS, and generalized adaptive IHS.

The research of road and vehicle information extraction algorithm based on high resolution remote sensing image

NASA Astrophysics Data System (ADS)

Zhou, Tingting; Gu, Lingjia; Ren, Ruizhi; Cao, Qiong

2016-09-01

With the rapid development of remote sensing technology, the spatial resolution and temporal resolution of satellite imagery also have a huge increase. Meanwhile, High-spatial-resolution images are becoming increasingly popular for commercial applications. The remote sensing image technology has broad application prospects in intelligent traffic. Compared with traditional traffic information collection methods, vehicle information extraction using high-resolution remote sensing image has the advantages of high resolution and wide coverage. This has great guiding significance to urban planning, transportation management, travel route choice and so on. Firstly, this paper preprocessed the acquired high-resolution multi-spectral and panchromatic remote sensing images. After that, on the one hand, in order to get the optimal thresholding for image segmentation, histogram equalization and linear enhancement technologies were applied into the preprocessing results. On the other hand, considering distribution characteristics of road, the normalized difference vegetation index (NDVI) and normalized difference water index (NDWI) were used to suppress water and vegetation information of preprocessing results. Then, the above two processing result were combined. Finally, the geometric characteristics were used to completed road information extraction. The road vector extracted was used to limit the target vehicle area. Target vehicle extraction was divided into bright vehicles extraction and dark vehicles extraction. Eventually, the extraction results of the two kinds of vehicles were combined to get the final results. The experiment results demonstrated that the proposed algorithm has a high precision for the vehicle information extraction for different high resolution remote sensing images. Among these results, the average fault detection rate was about 5.36%, the average residual rate was about 13.60% and the average accuracy was approximately 91.26%.

The application of a geometric optical canopy reflectance model to semiarid shrub vegetation

NASA Technical Reports Server (NTRS)

Franklin, Janet; Turner, Debra L.

1992-01-01

Estimates are obtained of the average plant size and density of shrub vegetation on the basis of SPOT High Resolution Visible Multispectral imagery from Chihuahuan desert areas, using the Li and Strahler (1985) model. The aggregated predictions for a number of stands within a class were accurate to within one or two standard errors of the observed average value. Accuracy was highest for those classes of vegetation where the nonrandom scrub pattern was characterized for the class on the basis of the average coefficient of the determination of density.

A preliminary comparison of Landsat Thematic Mapper and SPOT-1 HRV multispectral data for estimating coniferous forest volume

NASA Technical Reports Server (NTRS)

Ripple, William J.; Wang, S.; Isaacson, Dennis L.; Paine, D. P.

1995-01-01

Digital Landsat Thematic Mapper (TM) and Satellite Probatoire d'Observation de la Terre (SPOT) High Resolution Visible (HRV) images of coniferous forest canopies were compared in their relationship to forest wood volume using correlation and regression analyses. Significant inverse relationships were found between softwood volume and the spectral bands from both sensors (P less than 0.01). The highest correlations were between the log of softwood volume and the near-infrared bands (HRV band 3, r = -0.89; TM band 4, r = -0.83).

Galileo infrared imaging spectroscopy measurements at venus

USGS Publications Warehouse

Carlson, R.W.; Baines, K.H.; Encrenaz, Th.; Taylor, F.W.; Drossart, P.; Kamp, L.W.; Pollack, James B.; Lellouch, E.; Collard, A.D.; Calcutt, S.B.; Grinspoon, D.; Weissman, P.R.; Smythe, W.D.; Ocampo, A.C.; Danielson, G.E.; Fanale, F.P.; Johnson, T.V.; Kieffer, H.H.; Matson, D.L.; McCord, T.B.; Soderblom, L.A.

1991-01-01

During the 1990 Galileo Venus flyby, the Near Infrared Mapping Spectrometer investigated the night-side atmosphere of Venus in the spectral range 0.7 to 5.2 micrometers. Multispectral images at high spatial resolution indicate substantial cloud opacity variations in the lower cloud levels, centered at 50 kilometers altitude. Zonal and meridional winds were derived for this level and are consistent with motion of the upper branch of a Hadley cell. Northern and southern hemisphere clouds appear to be markedly different. Spectral profiles were used to derive lower atmosphere abundances of water vapor and other species.

Multiple directed graph large-class multi-spectral processor

NASA Technical Reports Server (NTRS)

Casasent, David; Liu, Shiaw-Dong; Yoneyama, Hideyuki

1988-01-01

Numerical analysis techniques for the interpretation of high-resolution imaging-spectrometer data are described and demonstrated. The method proposed involves the use of (1) a hierarchical classifier with a tree structure generated automatically by a Fisher linear-discriminant-function algorithm and (2) a novel multiple-directed-graph scheme which reduces the local maxima and the number of perturbations required. Results for a 500-class test problem involving simulated imaging-spectrometer data are presented in tables and graphs; 100-percent-correct classification is achieved with an improvement factor of 5.

MAMS: High resolution atmospheric moisture/surface properties

NASA Technical Reports Server (NTRS)

Jedlovec, Gary J.; Guillory, Anthony R.; Suggs, Ron; Atkinson, Robert J.; Carlson, Grant S.

1991-01-01

Multispectral Atmospheric Mapping Sensor (MAMS) data collected from a number of U2/ER2 aircraft flights were used to investigate atmospheric and surface (land) components of the hydrologic cycle. Algorithms were developed to retrieve surface and atmospheric geophysical parameters which describe the variability of atmospheric moisture, its role in cloud and storm development, and the influence of surface moisture and heat sources on convective activity. Techniques derived with MAMS data are being applied to existing satellite measurements to show their applicability to regional and large process studies and their impact on operational forecasting.

Towards developing Kentucky's landscape change maps

USGS Publications Warehouse

Zourarakis, D.P.; Lambert, S.C.; Palmer, M.

2003-01-01

The Kentucky Landscape Snapshot Project, a NASA-funded project, was established to provide a first baseline land cover/land use map for Kentucky. Through this endeavor, change detection will be institutionalized, thus aiding in decision-making at the local, state, and federal planning levels. 2002 Landsat 7 imaginery was classified following and Anderson Level III scheme, providing an enhancement over the 1992 USGS National Land Cover Data Set. Also as part of the deliverables, imperviousness and canopy closure layers were produced with the aid of IKONOS high resolution, multispectral imagery.

Combined Landsat-8 and Sentinel-2 Burned Area Mapping

NASA Astrophysics Data System (ADS)

Huang, H.; Roy, D. P.; Zhang, H.; Boschetti, L.; Yan, L.; Li, Z.

2017-12-01

Fire products derived from coarse spatial resolution satellite data have become an important source of information for the multiple user communities involved in fire science and applications. The advent of the MODIS on NASA's Terra and Aqua satellites enabled systematic production of 500m global burned area maps. There is, however, an unequivocal demand for systematically generated higher spatial resolution burned area products, in particular to examine the role of small-fires for various applications. Moderate spatial resolution contemporaneous satellite data from Landsat-8 and the Sentinel-2A and -2B sensors provide the opportunity for detailed spatial mapping of burned areas. Combined, these polar-orbiting systems provide 10m to 30m multi-spectral global coverage more than once every three days. This NASA funded research presents results to prototype a combined Landsat-8 Sentinel-2 burned area product. The Landsat-8 and Sentinel-2 pre-processing, the time-series burned area mapping algorithm, and preliminary results and validation using high spatial resolution commercial satellite data over Africa are presented.

CMOS-TDI detector technology for reconnaissance application

NASA Astrophysics Data System (ADS)

Eckardt, Andreas; Reulke, Ralf; Jung, Melanie; Sengebusch, Karsten

2014-10-01

The Institute of Optical Sensor Systems (OS) at the Robotics and Mechatronics Center of the German Aerospace Center (DLR) has more than 30 years of experience with high-resolution imaging technology. This paper shows the institute's scientific results of the leading-edge detector design CMOS in a TDI (Time Delay and Integration) architecture. This project includes the technological design of future high or multi-spectral resolution spaceborne instruments and the possibility of higher integration. DLR OS and the Fraunhofer Institute for Microelectronic Circuits and Systems (IMS) in Duisburg were driving the technology of new detectors and the FPA design for future projects, new manufacturing accuracy and on-chip processing capability in order to keep pace with the ambitious scientific and user requirements. In combination with the engineering research, the current generation of space borne sensor systems is focusing on VIS/NIR high spectral resolution to meet the requirements on earth and planetary observation systems. The combination of large-swath and high-spectral resolution with intelligent synchronization control, fast-readout ADC (analog digital converter) chains and new focal-plane concepts opens the door to new remote-sensing and smart deep-space instruments. The paper gives an overview of the detector development status and verification program at DLR, as well as of new control possibilities for CMOS-TDI detectors in synchronization control mode.

Improving the analysis of biogeochemical patterns associated with internal waves in the strait of Gibraltar using remote sensing images

NASA Astrophysics Data System (ADS)

Navarro, Gabriel; Vicent, Jorge; Caballero, Isabel; Gómez-Enri, Jesús; Morris, Edward P.; Sabater, Neus; Macías, Diego; Bolado-Penagos, Marina; Gomiz, Juan Jesús; Bruno, Miguel; Caldeira, Rui; Vázquez, Águeda

2018-05-01

High Amplitude Internal Waves (HAIWs) are physical processes observed in the Strait of Gibraltar (the narrow channel between the Atlantic Ocean and the Mediterranean Sea). These internal waves are generated over the Camarinal Sill (western side of the strait) during the tidal outflow (toward the Atlantic Ocean) when critical hydraulic conditions are established. HAIWs remain over the sill for up to 4 h until the outflow slackens, being then released (mostly) towards the Mediterranean Sea. These have been previously observed using Synthetic Aperture Radar (SAR), which captures variations in surface water roughness. However, in this work we use high resolution optical remote sensing, with the aim of examining the influence of HAIWs on biogeochemical processes. We used hyperspectral images from the Hyperspectral Imager for the Coastal Ocean (HICO) and high spatial resolution (10 m) images from the MultiSpectral Instrument (MSI) onboard the Sentinel-2A satellite. This work represents the first attempt to examine the relation between internal wave generation and the water constituents of the Camarinal Sill using hyperspectral and high spatial resolution remote sensing images. This enhanced spatial and spectral resolution revealed the detailed biogeochemical patterns associated with the internal waves and suggests local enhancements of productivity associated with internal waves trains.

Object Manifold Alignment for Multi-Temporal High Resolution Remote Sensing Images Classification

NASA Astrophysics Data System (ADS)

Gao, G.; Zhang, M.; Gu, Y.

2017-05-01

Multi-temporal remote sensing images classification is very useful for monitoring the land cover changes. Traditional approaches in this field mainly face to limited labelled samples and spectral drift of image information. With spatial resolution improvement, "pepper and salt" appears and classification results will be effected when the pixelwise classification algorithms are applied to high-resolution satellite images, in which the spatial relationship among the pixels is ignored. For classifying the multi-temporal high resolution images with limited labelled samples, spectral drift and "pepper and salt" problem, an object-based manifold alignment method is proposed. Firstly, multi-temporal multispectral images are cut to superpixels by simple linear iterative clustering (SLIC) respectively. Secondly, some features obtained from superpixels are formed as vector. Thirdly, a majority voting manifold alignment method aiming at solving high resolution problem is proposed and mapping the vector data to alignment space. At last, all the data in the alignment space are classified by using KNN method. Multi-temporal images from different areas or the same area are both considered in this paper. In the experiments, 2 groups of multi-temporal HR images collected by China GF1 and GF2 satellites are used for performance evaluation. Experimental results indicate that the proposed method not only has significantly outperforms than traditional domain adaptation methods in classification accuracy, but also effectively overcome the problem of "pepper and salt".

The Effect of Shadow Area on Sgm Algorithm and Disparity Map Refinement from High Resolution Satellite Stereo Images

NASA Astrophysics Data System (ADS)

Tatar, N.; Saadatseresht, M.; Arefi, H.

2017-09-01

Semi Global Matching (SGM) algorithm is known as a high performance and reliable stereo matching algorithm in photogrammetry community. However, there are some challenges using this algorithm especially for high resolution satellite stereo images over urban areas and images with shadow areas. As it can be seen, unfortunately the SGM algorithm computes highly noisy disparity values for shadow areas around the tall neighborhood buildings due to mismatching in these lower entropy areas. In this paper, a new method is developed to refine the disparity map in shadow areas. The method is based on the integration of potential of panchromatic and multispectral image data to detect shadow areas in object level. In addition, a RANSAC plane fitting and morphological filtering are employed to refine the disparity map. The results on a stereo pair of GeoEye-1 captured over Qom city in Iran, shows a significant increase in the rate of matched pixels compared to standard SGM algorithm.

Radiometric calibration of hyper-spectral imaging spectrometer based on optimizing multi-spectral band selection

NASA Astrophysics Data System (ADS)

Sun, Li-wei; Ye, Xin; Fang, Wei; He, Zhen-lei; Yi, Xiao-long; Wang, Yu-peng

2017-11-01

Hyper-spectral imaging spectrometer has high spatial and spectral resolution. Its radiometric calibration needs the knowledge of the sources used with high spectral resolution. In order to satisfy the requirement of source, an on-orbit radiometric calibration method is designed in this paper. This chain is based on the spectral inversion accuracy of the calibration light source. We compile the genetic algorithm progress which is used to optimize the channel design of the transfer radiometer and consider the degradation of the halogen lamp, thus realizing the high accuracy inversion of spectral curve in the whole working time. The experimental results show the average root mean squared error is 0.396%, the maximum root mean squared error is 0.448%, and the relative errors at all wavelengths are within 1% in the spectral range from 500 nm to 900 nm during 100 h operating time. The design lays a foundation for the high accuracy calibration of imaging spectrometer.

Color imaging of Mars by the High Resolution Imaging Science Experiment (HiRISE)

USGS Publications Warehouse

Delamere, W.A.; Tornabene, L.L.; McEwen, A.S.; Becker, K.; Bergstrom, J.W.; Bridges, N.T.; Eliason, E.M.; Gallagher, D.; Herkenhoff, K. E.; Keszthelyi, L.; Mattson, S.; McArthur, G.K.; Mellon, M.T.; Milazzo, M.; Russell, P.S.; Thomas, N.

2010-01-01

HiRISE has been producing a large number of scientifically useful color products of Mars and other planetary objects. The three broad spectral bands, coupled with the highly sensitive 14 bit detectors and time delay integration, enable detection of subtle color differences. The very high spatial resolution of HiRISE can augment the mineralogic interpretations based on multispectral (THEMIS) and hyperspectral datasets (TES, OMEGA and CRISM) and thereby enable detailed geologic and stratigraphic interpretations at meter scales. In addition to providing some examples of color images and their interpretation, we describe the processing techniques used to produce them and note some of the minor artifacts in the output. We also provide an example of how HiRISE color products can be effectively used to expand mineral and lithologic mapping provided by CRISM data products that are backed by other spectral datasets. The utility of high quality color data for understanding geologic processes on Mars has been one of the major successes of HiRISE. ?? 2009 Elsevier Inc.

Comparison of three different methods to merge multiresolution and multispectral data: Landsat TM and SPOT panchromatic

USGS Publications Warehouse

Chavez, P.S.; Sides, S.C.; Anderson, J.A.

1991-01-01

The merging of multisensor image data is becoming a widely used procedure because of the complementary nature of various data sets. Ideally, the method used to merge data sets with high-spatial and high-spectral resolution should not distort the spectral characteristics of the high-spectral resolution data. This paper compares the results of three different methods used to merge the information contents of the Landsat Thematic Mapper (TM) and Satellite Pour l'Observation de la Terre (SPOT) panchromatic data. The comparison is based on spectral characteristics and is made using statistical, visual, and graphical analyses of the results. The three methods used to merge the information contents of the Landsat TM and SPOT panchromatic data were the Hue-Intensity-Saturation (HIS), Principal Component Analysis (PCA), and High-Pass Filter (HPF) procedures. The HIS method distorted the spectral characteristics of the data the most. The HPF method distorted the spectral characteristics the least; the distortions were minimal and difficult to detect. -Authors

Utilization of LANDSAT images in cartography

NASA Technical Reports Server (NTRS)

Dejesusparada, N. (Principal Investigator); Alburquerque, P. C. G.

1981-01-01

The use of multispectral imagery obtained from LANDSAT for mapping purposes is discussed with emphasis on geometric rectification, image resolution, and systematic topographic mapping. A method is given for constructing 1:250,000 scale maps. The limitations for satellite cartography are examined.

Mapping Glacier Dynamics and Proglacial Wetlands with a Multispectral UAV at 5000m in the Cordillera Blanca, Peru

NASA Astrophysics Data System (ADS)

Wigmore, O.; Mark, B. G.

2015-12-01

The glaciers of the Cordillera Blanca, Peru are rapidly retreating as a result of rising temperatures, transforming the hydrology and impacting the socio-economic and environmental systems of the Rio Santa basin. Documenting the heterogeneous spatial patterns of these changes to understand processes of water storage and flow is hindered by technologic and logistic challenges. Highly complex topography, cloud cover and coarse spatial resolution limit the application of satellite data while airborne data collection remains costly and potentially dangerous. However, recent developments have made Unmanned Aerial Vehicle (UAV) technology a viable and potentially transformative method for studying glacier dynamics and proglacial hydrology. The extreme altitudes (4000-6700m) of the Cordillera Blanca limit the use of 'off the shelf' UAVs. Therefore we developed a low cost multispectral (visible, near-infrared and thermal infrared) multirotor UAV capable of conducting fully autonomous aerial surveys at elevations over 5000m within the glacial valleys of the Cordillera Blanca. Using this platform we have completed repeat aerial surveys (in 2014 and 2015) of the debris covered Llaca Glacier, generating highly accurate 10-20cm DEM's and 5cm orthomosaics using a structure from motion workflow. Analysis of these data reveals a highly dynamic system with some areas of the glacier losing as much as 16m of vertical elevation, while other areas have gained up to 5m of elevation over one year. The magnitude and direction of these changes appears to be associated with the presence of debris free ice faces and meltwater ponds. Additionally, we have mapped proglacial meadow and wetland systems. Thermal mosaics at 10-20cm resolution are providing novel insights into the hydrologic pathways of glacier meltwater including mapping the distribution of artesian springs that feed these wetland systems. The high spatial resolution of these UAV datasets facilitates a better understanding of the spatial variability in and controls on glacier dynamics and proglacial surface/subsurface hydrology within the Cordillera Blanca. We discuss the technical details of the platform, the challenges of conducting UAV surveys at high elevation and share insights from our findings at Llaca Glacier and within the proglacial wetland systems.

Determining coniferous forest cover and forest fragmentation with NOAA-9 advanced very high resolution radiometer data

NASA Technical Reports Server (NTRS)

Ripple, William J.

1995-01-01

NOAA-9 satellite data from the Advanced Very High Resolution Radiometer (AVHRR) were used in conjunction with Landsat Multispectral Scanner (MSS) data to determine the proportion of closed canopy conifer forest cover in the Cascade Range of Oregon. A closed canopy conifer map, as determined from the MSS, was registered with AVHRR pixels. Regression was used to relate closed canopy conifer forest cover to AVHRR spectral data. A two-variable (band) regression model accounted for more variance in conifer cover than the Normalized Difference Vegetation Index (NDVI). The spectral signatures of various conifer successional stages were also examined. A map of Oregon was produced showing the proportion of closed canopy conifer cover for each AVHRR pixel. The AVHRR was responsive to both the percentage of closed canopy conifer cover and the successional stage in these temperate coniferous forests in this experiment.

Aircraft MSS data registration and vegetation classification of wetland change detection

USGS Publications Warehouse

Christensen, E.J.; Jensen, J.R.; Ramsey, Elijah W.; Mackey, H.E.

1988-01-01

Portions of the Savannah River floodplain swamp were evaluated for vegetation change using high resolution (5a??6 m) aircraft multispectral scanner (MSS) data. Image distortion from aircraft movement prevented precise image-to-image registration in some areas. However, when small scenes were used (200-250 ha), a first-order linear transformation provided registration accuracies of less than or equal to one pixel. A larger area was registered using a piecewise linear method. Five major wetland classes were identified and evaluated for change. Phenological differences and the variable distribution of vegetation limited wetland type discrimination. Using unsupervised methods and ground-collected vegetation data, overall classification accuracies ranged from 84 per cent to 87 per cent for each scene. Results suggest that high-resolution aircraft MSS data can be precisely registered, if small areas are used, and that wetland vegetation change can be accurately detected and monitored.

Discriminating heavy aerosol, clouds, and fires during SCAR-B: Application of airborne multispectral MAS data

NASA Astrophysics Data System (ADS)

King, Michael D.; Tsay, Si-Chee; Ackerman, Steven A.; Larsen, North F.

1998-12-01

A multispectral scanning spectrometer was used to obtain measurements of the reflection function and brightness temperature of smoke, clouds, and terrestrial surfaces at 50 discrete wavelengths between 0.55 and 14.2 μm. These observations were obtained from the NASA ER-2 aircraft as part of the Smoke, Clouds, and Radiation-Brazil (SCAR-B) campaign, conducted over a 1500×1500 km region of cerrado and rain forest throughout Brazil between August 16 and September 11, 1995. Multispectral images of the reflection function and brightness temperature in 10 distinct bands of the MODIS airborne simulator (MAS) were used to derive a confidence in clear sky (or alternatively the probability of cloud), shadow, fire, and heavy aerosol. In addition to multispectral imagery, monostatic lidar data were obtained along the nadir ground track of the aircraft and used to assess the accuracy of the cloud mask results. This analysis shows that the cloud and aerosol mask being developed for operational use on the moderate-resolution imaging spectroradiometer (MODIS), and tested using MAS data in Brazil, is quite capable of separating cloud, aerosol, shadow, and fires during daytime conditions over land.

Radiometric characterization of hyperspectral imagers using multispectral sensors

NASA Astrophysics Data System (ADS)

McCorkel, Joel; Thome, Kurt; Leisso, Nathan; Anderson, Nikolaus; Czapla-Myers, Jeff

2009-08-01

The Remote Sensing Group (RSG) at the University of Arizona has a long history of using ground-based test sites for the calibration of airborne and satellite based sensors. Often, ground-truth measurements at these tests sites are not always successful due to weather and funding availability. Therefore, RSG has also employed automated ground instrument approaches and cross-calibration methods to verify the radiometric calibration of a sensor. The goal in the cross-calibration method is to transfer the calibration of a well-known sensor to that of a different sensor. This work studies the feasibility of determining the radiometric calibration of a hyperspectral imager using multispectral imagery. The work relies on the Moderate Resolution Imaging Spectroradiometer (MODIS) as a reference for the hyperspectral sensor Hyperion. Test sites used for comparisons are Railroad Valley in Nevada and a portion of the Libyan Desert in North Africa. Hyperion bands are compared to MODIS by band averaging Hyperion's high spectral resolution data with the relative spectral response of MODIS. The results compare cross-calibration scenarios that differ in image acquisition coincidence, test site used for the calibration, and reference sensor. Cross-calibration results are presented that show agreement between the use of coincident and non-coincident image pairs within 2% in most bands as well as similar agreement between results that employ the different MODIS sensors as a reference.

Radiometric Characterization of Hyperspectral Imagers using Multispectral Sensors

NASA Technical Reports Server (NTRS)

McCorkel, Joel; Kurt, Thome; Leisso, Nathan; Anderson, Nikolaus; Czapla-Myers, Jeff

2009-01-01

The Remote Sensing Group (RSG) at the University of Arizona has a long history of using ground-based test sites for the calibration of airborne and satellite based sensors. Often, ground-truth measurements at these test sites are not always successful due to weather and funding availability. Therefore, RSG has also automated ground instrument approaches and cross-calibration methods to verify the radiometric calibration of a sensor. The goal in the cross-calibration method is to transfer the calibration of a well-known sensor to that of a different sensor, This work studies the feasibility of determining the radiometric calibration of a hyperspectral imager using multispectral a imagery. The work relies on the Moderate Resolution Imaging Spectroradiometer (M0DIS) as a reference for the hyperspectral sensor Hyperion. Test sites used for comparisons are Railroad Valley in Nevada and a portion of the Libyan Desert in North Africa. Hyperion bands are compared to MODIS by band averaging Hyperion's high spectral resolution data with the relative spectral response of M0DlS. The results compare cross-calibration scenarios that differ in image acquisition coincidence, test site used for the calibration, and reference sensor. Cross-calibration results are presented that show agreement between the use of coincident and non-coincident image pairs within 2% in most brands as well as similar agreement between results that employ the different MODIS sensors as a reference.

Integration of aerial remote sensing imaging data in a 3D-GIS environment

NASA Astrophysics Data System (ADS)

Moeller, Matthias S.

2003-03-01

For some years sensor systems have been available providing digital images of a new quality. Especially aerial stereo scanners acquire digital multispectral images with an extremely high ground resolution of about 0.10 - 0.15m and provide in addition a Digital Surface Models (DSM). These imaging products both can be used for a detailed monitoring at scales up to 1:500. The processed georeferenced multispectral orthoimages can be readily integrated into GIS making them useful for a number of applications. The DSM, derived from forward and backward facing sensors of an aerial imaging system provides a ground resolution of 0.5 m and can be used for 3D visualization purposes. In some cases it is essential, to store the ground elevation as a Digital Terrain Model (DTM) and also the height of 3-dimensional objects in a separated database. Existing automated algorithms do not work precise for the extraction of DTM from aerial scanner DSM. This paper presents a new approach which combines the visible image data and the DSM data for the generation of DTM with a reliable geometric accuracy. Already existing cadastral data can be used as a knowledge base for the extraction of building heights in cities. These elevation data is the essential source for a GIS based urban information system with a 3D visualization component.

Experimental Demonstration of Adaptive Infrared Multispectral Imaging using Plasmonic Filter Array.

PubMed

Jang, Woo-Yong; Ku, Zahyun; Jeon, Jiyeon; Kim, Jun Oh; Lee, Sang Jun; Park, James; Noyola, Michael J; Urbas, Augustine

2016-10-10

In our previous theoretical study, we performed target detection using a plasmonic sensor array incorporating the data-processing technique termed "algorithmic spectrometry". We achieved the reconstruction of a target spectrum by extracting intensity at multiple wavelengths with high resolution from the image data obtained from the plasmonic array. The ultimate goal is to develop a full-scale focal plane array with a plasmonic opto-coupler in order to move towards the next generation of versatile infrared cameras. To this end, and as an intermediate step, this paper reports the experimental demonstration of adaptive multispectral imagery using fabricated plasmonic spectral filter arrays and proposed target detection scenarios. Each plasmonic filter was designed using periodic circular holes perforated through a gold layer, and an enhanced target detection strategy was proposed to refine the original spectrometry concept for spatial and spectral computation of the data measured from the plasmonic array. Both the spectrum of blackbody radiation and a metal ring object at multiple wavelengths were successfully reconstructed using the weighted superposition of plasmonic output images as specified in the proposed detection strategy. In addition, plasmonic filter arrays were theoretically tested on a target at extremely high temperature as a challenging scenario for the detection scheme.

Multispectral Resource Sampler Workshop

NASA Technical Reports Server (NTRS)

1979-01-01

The utility of the multispectral resource sampler (MRS) was examined by users in the following disciplines: agriculture, atmospheric studies, engineering, forestry, geology, hydrology/oceanography, land use, and rangelands/soils. Modifications to the sensor design were recommended and the desired types of products and number of scenes required per month were indicated. The history, design, capabilities, and limitations of the MRS are discussed as well as the multilinear spectral array technology which it uses. Designed for small area inventory, the MRS can provide increased temporal, spectral, and spatial resolution, facilitate polarization measurement and atmospheric correction, and test onboard data compression techniques. The advantages of using it along with the thematic mapper are considered.

The PanCam instrument on the 2018 Exomars rover: Science Implementation Strategy and Integrated Surface Operations Concept

NASA Astrophysics Data System (ADS)

Schmitz, Nicole; Jaumann, Ralf; Coates, Andrew; Griffiths, Andrew; Hauber, Ernst; Trauthan, Frank; Paar, Gerhard; Barnes, Dave; Bauer, Arnold; Cousins, Claire

2010-05-01

Geologic context as a combination of orbital imaging and surface vision, including range, resolution, stereo, and multispectral imaging, is commonly regarded as basic requirement for remote robotic geology and forms the first tier of any multi-instrument strategy for investigating and eventually understanding the geology of a region from a robotic platform. Missions with objectives beyond a pure geologic survey, e.g. exobiology objectives, require goal-oriented operational procedures, where the iterative process of scientific observation, hypothesis, testing, and synthesis, performed via a sol-by-sol data exchange with a remote robot, is supported by a powerful vision system. Beyond allowing a thorough geological mapping of the surface (soil, rocks and outcrops) in 3D, using wide angle stereo imagery, such a system needs to be able to provide detailed visual information on targets of interest in high resolution, thereby enabling the selection of science targets and samples for further analysis with a specialized in-situ instrument suite. Surface vision for ESA's upcoming ExoMars rover will come from a dedicated Panoramic Camera System (PanCam). As integral part of the Pasteur payload package, the PanCam is designed to support the search for evidence of biological processes by obtaining wide angle multispectral stereoscopic panoramic images and high resolution RGB images from the mast of the rover [1]. The camera system will consist of two identical wide-angle cameras (WACs), which are arranged on a common pan-tilt mechanism, with a fixed stereo base length of 50 cm. The WACs are being complemented by a High Resolution Camera (HRC), mounted between the WACs, which allows a magnification of selected targets by a factor of ~8 with respect to the wide-angle optics. The high-resolution images together with the multispectral and stereo capabilities of the camera will be of unprecedented quality for the identification of water-related surface features (such as sedimentary rocks) and form one key to a successful implementation of ESA's multi-level strategy for the ExoMars Reference Surface Mission. A dedicated PanCam Science Implementation Strategy is under development, which connects the PanCam science objectives and needs of the ExoMars Surface Mission with the required investigations, planned measurement approach and sequence, and connected mission requirements. First step of this strategy is obtaining geological context to enable the decision where to send the rover. PanCam (in combination with Wisdom) will be used to obtain ground truth by a thorough geomorphologic mapping of the ExoMars rover's surroundings in near and far range in the form of (1) RGB or monochromatic full (i.e. 360°) or partial stereo panoramas for morphologic and textural information and stereo ranging, (2) mosaics or single images with partly or full multispectral coverage to assess the mineralogy of surface materials as well as their weathering state and possible past or present alteration processes and (3) small-scale high-resolution information on targets/features of interest, and distant or inaccessible sites. This general survey phase will lead to the identification of surface features like outcrops, ridges and troughs and the characterization of different rock and surface units based on their morphology, distribution, and spectral and physical properties. Evidence of water-bearing minerals, water-altered rocks or even water-lain sediments seen in the large-scale wide angle images will then allow for preselecting those targets/features considered relevant for detailed analysis and definition of their geologic context. Detailed characterization and, subsequently, selection of those preselected targets/features for further analysis will then be enabled by color high-resolution imagery, followed by the next tier of contact instruments to enable a decision on whether or not to acquire samples for further analysis. During the following drill/analysis phase, PanCam's High Resolution Camera will characterize the sample in the sample tray and observe the sample discharge into the Core Sample Transfer Mechanism. Key parts of this science strategy have been tested under laboratory conditions in two geology blind tests [2] and during two field test campaigns in Svalbard, using simulated mission conditions, an ExoMars representative Payload (ExoMars and MSL instrument breadboards), and Mars analog settings [3, 4]. The experiences gained are being translated into operational sequences, and, together with the science implementation strategy, form a first version of a PanCam Surface Operations plan. References: [1] Griffiths, A.D. et al. (2006) International Journal of Astrobiology 5 (3): 269-275, doi:10.1017/ S1473550406003387. [2] Pullan, D. et al. (2009) EPSC Abstracts, Vol. 4, EPSC2009-514. [3] Schmitz, N. et al. (2009) Geophysical Research Abstracts, Vol. 11, EGU2009-10621-2. [4] Cousins, C. et al. (2009) EPSC Abstracts, Vol. 4, EPSC2009-813.

Does the Data Resolution/origin Matter? Satellite, Airborne and Uav Imagery to Tackle Plant Invasions

NASA Astrophysics Data System (ADS)

Müllerová, Jana; Brůna, Josef; Dvořák, Petr; Bartaloš, Tomáš; Vítková, Michaela

2016-06-01

Invasive plant species represent a serious threat to biodiversity and landscape as well as human health and socio-economy. To successfully fight plant invasions, new methods enabling fast and efficient monitoring, such as remote sensing, are needed. In an ongoing project, optical remote sensing (RS) data of different origin (satellite, aerial and UAV), spectral (panchromatic, multispectral and color), spatial (very high to medium) and temporal resolution, and various technical approaches (object-, pixelbased and combined) are tested to choose the best strategies for monitoring of four invasive plant species (giant hogweed, black locust, tree of heaven and exotic knotweeds). In our study, we address trade-offs between spectral, spatial and temporal resolutions required for balance between the precision of detection and economic feasibility. For the best results, it is necessary to choose best combination of spatial and spectral resolution and phenological stage of the plant in focus. For species forming distinct inflorescences such as giant hogweed iterative semi-automated object-oriented approach was successfully applied even for low spectral resolution data (if pixel size was sufficient) whereas for lower spatial resolution satellite imagery or less distinct species with complicated architecture such as knotweed, combination of pixel and object based approaches was used. High accuracies achieved for very high resolution data indicate the possible application of described methodology for monitoring invasions and their long-term dynamics elsewhere, making management measures comparably precise, fast and efficient. This knowledge serves as a basis for prediction, monitoring and prioritization of management targets.

Sentinel-2A image quality commissioning phase final results: geometric calibration and performances

NASA Astrophysics Data System (ADS)

Languille, F.; Gaudel, A.; Dechoz, C.; Greslou, D.; de Lussy, F.; Trémas, T.; Poulain, V.; Massera, S.

2016-10-01

In the frame of the Copernicus program of the European Commission, Sentinel-2 offers multispectral high-spatial-resolution optical images over global terrestrial surfaces. In cooperation with ESA, the Centre National d'Etudes Spatiales (CNES) is in charge of the image quality of the project, and so ensures the CAL/VAL commissioning phase during the months following the launch. Sentinel-2 is a constellation of 2 satellites on a polar sun-synchronous orbit with a revisit time of 5 days (with both satellites), a high field of view - 290km, 13 spectral bands in visible and shortwave infrared, and high spatial resolution - 10m, 20m and 60m. The Sentinel-2 mission offers a global coverage over terrestrial surfaces. The satellites acquire systematically terrestrial surfaces under the same viewing conditions in order to have temporal images stacks. The first satellite was launched in June 2015. Following the launch, the CAL/VAL commissioning phase is then lasting during 6 months for geometrical calibration. This paper will point on observations and results seen on Sentinel-2 images during commissioning phase. It will provide explanations about Sentinel-2 products delivered with geometric corrections. This paper will detail calibration sites, and the methods used for geometrical parameters calibration and will present linked results. The following topics will be presented: viewing frames orientation assessment, focal plane mapping for all spectral bands, results on geolocation assessment, and multispectral registration. There is a systematic images recalibration over a same reference which is a set of S2 images produced during the 6 months of CAL/VAL. This set of images will be presented as well as the geolocation performance and the multitemporal performance after refining over this ground reference.

Compression of multispectral fluorescence microscopic images based on a modified set partitioning in hierarchal trees

NASA Astrophysics Data System (ADS)

Mansoor, Awais; Robinson, J. Paul; Rajwa, Bartek

2009-02-01

Modern automated microscopic imaging techniques such as high-content screening (HCS), high-throughput screening, 4D imaging, and multispectral imaging are capable of producing hundreds to thousands of images per experiment. For quick retrieval, fast transmission, and storage economy, these images should be saved in a compressed format. A considerable number of techniques based on interband and intraband redundancies of multispectral images have been proposed in the literature for the compression of multispectral and 3D temporal data. However, these works have been carried out mostly in the elds of remote sensing and video processing. Compression for multispectral optical microscopy imaging, with its own set of specialized requirements, has remained under-investigated. Digital photography{oriented 2D compression techniques like JPEG (ISO/IEC IS 10918-1) and JPEG2000 (ISO/IEC 15444-1) are generally adopted for multispectral images which optimize visual quality but do not necessarily preserve the integrity of scientic data, not to mention the suboptimal performance of 2D compression techniques in compressing 3D images. Herein we report our work on a new low bit-rate wavelet-based compression scheme for multispectral fluorescence biological imaging. The sparsity of signicant coefficients in high-frequency subbands of multispectral microscopic images is found to be much greater than in natural images; therefore a quad-tree concept such as Said et al.'s SPIHT1 along with correlation of insignicant wavelet coefficients has been proposed to further exploit redundancy at high-frequency subbands. Our work propose a 3D extension to SPIHT, incorporating a new hierarchal inter- and intra-spectral relationship amongst the coefficients of 3D wavelet-decomposed image. The new relationship, apart from adopting the parent-child relationship of classical SPIHT, also brought forth the conditional "sibling" relationship by relating only the insignicant wavelet coefficients of subbands at the same level of decomposition. The insignicant quadtrees in dierent subbands in the high-frequency subband class are coded by a combined function to reduce redundancy. A number of experiments conducted on microscopic multispectral images have shown promising results for the proposed method over current state-of-the-art image-compression techniques.

Forest Classification Accuracy as Influenced by Multispectral Scanner Spatial Resolution. [Sam Houston National Forest, Texas

NASA Technical Reports Server (NTRS)

Nalepka, R. F. (Principal Investigator); Sadowski, F. E.; Sarno, J. E.

1976-01-01

The author has identified the following significant results. A supervised classification within two separate ground areas of the Sam Houston National Forest was carried out for two sq meters spatial resolution MSS data. Data were progressively coarsened to simulate five additional cases of spatial resolution ranging up to 64 sq meters. Similar processing and analysis of all spatial resolutions enabled evaluations of the effect of spatial resolution on classification accuracy for various levels of detail and the effects on area proportion estimation for very general forest features. For very coarse resolutions, a subset of spectral channels which simulated the proposed thematic mapper channels was used to study classification accuracy.

Markov-random-field-based super-resolution mapping for identification of urban trees in VHR images

NASA Astrophysics Data System (ADS)

Ardila, Juan P.; Tolpekin, Valentyn A.; Bijker, Wietske; Stein, Alfred

2011-11-01

Identification of tree crowns from remote sensing requires detailed spectral information and submeter spatial resolution imagery. Traditional pixel-based classification techniques do not fully exploit the spatial and spectral characteristics of remote sensing datasets. We propose a contextual and probabilistic method for detection of tree crowns in urban areas using a Markov random field based super resolution mapping (SRM) approach in very high resolution images. Our method defines an objective energy function in terms of the conditional probabilities of panchromatic and multispectral images and it locally optimizes the labeling of tree crown pixels. Energy and model parameter values are estimated from multiple implementations of SRM in tuning areas and the method is applied in QuickBird images to produce a 0.6 m tree crown map in a city of The Netherlands. The SRM output shows an identification rate of 66% and commission and omission errors in small trees and shrub areas. The method outperforms tree crown identification results obtained with maximum likelihood, support vector machines and SRM at nominal resolution (2.4 m) approaches.

[Comparison of precision in retrieving soybean leaf area index based on multi-source remote sensing data].

PubMed

Gao, Lin; Li, Chang-chun; Wang, Bao-shan; Yang Gui-jun; Wang, Lei; Fu, Kui

2016-01-01

With the innovation of remote sensing technology, remote sensing data sources are more and more abundant. The main aim of this study was to analyze retrieval accuracy of soybean leaf area index (LAI) based on multi-source remote sensing data including ground hyperspectral, unmanned aerial vehicle (UAV) multispectral and the Gaofen-1 (GF-1) WFV data. Ratio vegetation index (RVI), normalized difference vegetation index (NDVI), soil-adjusted vegetation index (SAVI), difference vegetation index (DVI), and triangle vegetation index (TVI) were used to establish LAI retrieval models, respectively. The models with the highest calibration accuracy were used in the validation. The capability of these three kinds of remote sensing data for LAI retrieval was assessed according to the estimation accuracy of models. The experimental results showed that the models based on the ground hyperspectral and UAV multispectral data got better estimation accuracy (R² was more than 0.69 and RMSE was less than 0.4 at 0.01 significance level), compared with the model based on WFV data. The RVI logarithmic model based on ground hyperspectral data was little superior to the NDVI linear model based on UAV multispectral data (The difference in E(A), R² and RMSE were 0.3%, 0.04 and 0.006, respectively). The models based on WFV data got the lowest estimation accuracy with R2 less than 0.30 and RMSE more than 0.70. The effects of sensor spectral response characteristics, sensor geometric location and spatial resolution on the soybean LAI retrieval were discussed. The results demonstrated that ground hyperspectral data were advantageous but not prominent over traditional multispectral data in soybean LAI retrieval. WFV imagery with 16 m spatial resolution could not meet the requirements of crop growth monitoring at field scale. Under the condition of ensuring the high precision in retrieving soybean LAI and working efficiently, the approach to acquiring agricultural information by UAV remote sensing could yet be regarded as an optimal plan. Therefore, in the case of more and more available remote sensing information sources, agricultural UAV remote sensing could become an important information resource for guiding field-scale crop management and provide more scientific and accurate information for precision agriculture research.

Multispectral Image Compression Based on DSC Combined with CCSDS-IDC

PubMed Central

Li, Jin; Xing, Fei; Sun, Ting; You, Zheng

2014-01-01

Remote sensing multispectral image compression encoder requires low complexity, high robust, and high performance because it usually works on the satellite where the resources, such as power, memory, and processing capacity, are limited. For multispectral images, the compression algorithms based on 3D transform (like 3D DWT, 3D DCT) are too complex to be implemented in space mission. In this paper, we proposed a compression algorithm based on distributed source coding (DSC) combined with image data compression (IDC) approach recommended by CCSDS for multispectral images, which has low complexity, high robust, and high performance. First, each band is sparsely represented by DWT to obtain wavelet coefficients. Then, the wavelet coefficients are encoded by bit plane encoder (BPE). Finally, the BPE is merged to the DSC strategy of Slepian-Wolf (SW) based on QC-LDPC by deep coupling way to remove the residual redundancy between the adjacent bands. A series of multispectral images is used to test our algorithm. Experimental results show that the proposed DSC combined with the CCSDS-IDC (DSC-CCSDS)-based algorithm has better compression performance than the traditional compression approaches. PMID:25110741

Multispectral image compression based on DSC combined with CCSDS-IDC.

PubMed

Li, Jin; Xing, Fei; Sun, Ting; You, Zheng

2014-01-01

Remote sensing multispectral image compression encoder requires low complexity, high robust, and high performance because it usually works on the satellite where the resources, such as power, memory, and processing capacity, are limited. For multispectral images, the compression algorithms based on 3D transform (like 3D DWT, 3D DCT) are too complex to be implemented in space mission. In this paper, we proposed a compression algorithm based on distributed source coding (DSC) combined with image data compression (IDC) approach recommended by CCSDS for multispectral images, which has low complexity, high robust, and high performance. First, each band is sparsely represented by DWT to obtain wavelet coefficients. Then, the wavelet coefficients are encoded by bit plane encoder (BPE). Finally, the BPE is merged to the DSC strategy of Slepian-Wolf (SW) based on QC-LDPC by deep coupling way to remove the residual redundancy between the adjacent bands. A series of multispectral images is used to test our algorithm. Experimental results show that the proposed DSC combined with the CCSDS-IDC (DSC-CCSDS)-based algorithm has better compression performance than the traditional compression approaches.

Crop classification using temporal stacks of multispectral satellite imagery

NASA Astrophysics Data System (ADS)

Moody, Daniela I.; Brumby, Steven P.; Chartrand, Rick; Keisler, Ryan; Longbotham, Nathan; Mertes, Carly; Skillman, Samuel W.; Warren, Michael S.

2017-05-01

The increase in performance, availability, and coverage of multispectral satellite sensor constellations has led to a drastic increase in data volume and data rate. Multi-decadal remote sensing datasets at the petabyte scale are now available in commercial clouds, with new satellite constellations generating petabytes/year of daily high-resolution global coverage imagery. The data analysis capability, however, has lagged behind storage and compute developments, and has traditionally focused on individual scene processing. We present results from an ongoing effort to develop satellite imagery analysis tools that aggregate temporal, spatial, and spectral information and can scale with the high-rate and dimensionality of imagery being collected. We investigate and compare the performance of pixel-level crop identification using tree-based classifiers and its dependence on both temporal and spectral features. Classification performance is assessed using as ground-truth Cropland Data Layer (CDL) crop masks generated by the US Department of Agriculture (USDA). The CDL maps contain 30m spatial resolution, pixel-level labels for around 200 categories of land cover, but are however only available post-growing season. The analysis focuses on McCook county in South Dakota and shows crop classification using a temporal stack of Landsat 8 (L8) imagery over the growing season, from April through October. Specifically, we consider the temporal L8 stack depth, as well as different normalized band difference indices, and evaluate their contribution to crop identification. We also show an extension of our algorithm to map corn and soy crops in the state of Mato Grosso, Brazil.

A multispectral sorting device for isolating single wheat kernels with high protein content

USDA-ARS?s Scientific Manuscript database

Automated sorting of single wheat kernels according to protein content was demonstrated using two novel multispectral sorting devices with different spectral ranges; 470-1070 nm (silicone based detector) and 910nm-1550 nm (InGaAs based detector). The multispectral data were acquired by rapidly (~12...

Study of the structure changes caused by volcanic activity in Mexico applying the lineament analysis to the Aster (Terra) satellite data.

NASA Astrophysics Data System (ADS)

Arellano-Baeza, A. A.; Garcia, R. V.; Trejo-Soto, M.; Molina-Sauceda, E.

Mexico is one of the most volcanically active regions in North America Volcanic activity in central Mexico is associated with the subduction of the Cocos and Rivera plates beneath the North American plate Periods of enhanced microseismic activity associated with the volcanic activity of the Colima and Popocapetl volcanoes are compared to some periods of low microseismic activity We detected changes in the number and orientation of lineaments associated with the microseismic activity due to lineament analysis of a temporal sequence of high resolution satellite images of both volcanoes 15 m resolution multispectral images provided by the ASTER VNIR instrument were used The Lineament Extraction and Stripes Statistic Analysis LESSA software package was employed for the lineament extraction

Backside illuminated CMOS-TDI line scanner for space applications

NASA Astrophysics Data System (ADS)

Cohen, O.; Ben-Ari, N.; Nevo, I.; Shiloah, N.; Zohar, G.; Kahanov, E.; Brumer, M.; Gershon, G.; Ofer, O.

2017-09-01

A new multi-spectral line scanner CMOS image sensor is reported. The backside illuminated (BSI) image sensor was designed for continuous scanning Low Earth Orbit (LEO) space applications including A custom high quality CMOS Active Pixels, Time Delayed Integration (TDI) mechanism that increases the SNR, 2-phase exposure mechanism that increases the dynamic Modulation Transfer Function (MTF), very low power internal Analog to Digital Converters (ADC) with resolution of 12 bit per pixel and on chip controller. The sensor has 4 independent arrays of pixels where each array is arranged in 2600 TDI columns with controllable TDI depth from 8 up to 64 TDI levels. A multispectral optical filter with specific spectral response per array is assembled at the package level. In this paper we briefly describe the sensor design and present some electrical and electro-optical recent measurements of the first prototypes including high Quantum Efficiency (QE), high MTF, wide range selectable Full Well Capacity (FWC), excellent linearity of approximately 1.3% in a signal range of 5-85% and approximately 1.75% in a signal range of 2-95% out of the signal span, readout noise of approximately 95 electrons with 64 TDI levels, negligible dark current and power consumption of less than 1.5W total for 4 bands sensor at all operation conditions .

The ASTER emergency scheduling system: A new project linking near-real-time satellite monitoring of disasters to the acquisition of high-resolution remote sensing data

NASA Astrophysics Data System (ADS)

Ramsey, M.; Dehn, J.; Wessels, R.; Byrnes, J.; Duda, K.; Maldonado, L.; Dwyer, J.

2004-12-01

Numerous government agencies and university partnerships are currently utilizing orbital instruments with high-temporal/low-spatial resolution (e.g. MODIS, AVHRR) to monitor hazards. These hazards are varied and include both natural (volcanic eruptions, severe weather, wildfires, earthquake damage) and anthropogenic (environmental damage, urban terrorism). Although monitoring a hazardous situation is critical, a key strategy of NASA's Earth science program is to develop a scientific understanding of the Earth system and its responses to changes, as well as to improve prediction of hazard onset. In order to develop a quantitative scientific basis from which to model transient geological and climatological hazards, much higher spatial/spectral resolution datasets are required. Such datasets are sparse, currently available from certain government (e.g. ASTER, Hyperion) and commercial (e.g. IKONOS, QuickBird) instruments. However, only ASTER has the capability to acquire high spatial resolution data from the visible to thermal infrared (TIR) wavelength region in conjunction with digital elevation models (DEM) generation. These capabilities are particularly useful for numerous aspects of volcanic remote sensing. For example, multispectral TIR data are critical for monitoring low temperature anomalies and mapping both chemical and textural variations on volcanic surfaces. Because ASTER data are scheduled in advance and the raw data are sent to Japan for calibration processing, rapid acquisition of hazards becomes problematic. However, a "rapid response" mode does exist for ASTER data scheduling and processing, but its availability is limited and requires significant human interaction. A newly-funded NASA ASTER science team project seeks to link this ASTER rapid response pathway to larger-scale monitoring alerts, which are already in-place and in-use by other organizations. By refining the initial event detection criteria and improving interfaces between these organizations and the ASTER project, we expect to minimize lag time and use existing monitoring tools as triggers for the emergency response of ASTER. The first phase of this project will be integrated into the Alaska Volcano Observatory's current near-real-time volcanic monitoring system, which relies on high temporal/low spatial resolution orbital data. This synergy will allow small-scale activity to be targeted for science and response, and a calibration baseline between each sensor to be established. If successful, this will be the first time that high spatial resolution, multispectral satellite data will be routinely scheduled, acquired, and analyzed in a "rapid response" mode within an existing hazard monitoring framework. Initial testing of this system is now underway using data from previous eruptions in the north Pacific region, and modifications to the rapid data flow procedure within the ASTER science and support structure has begun.

Hyperspectral remote sensing of wild oyster reefs

NASA Astrophysics Data System (ADS)

Le Bris, Anthony; Rosa, Philippe; Lerouxel, Astrid; Cognie, Bruno; Gernez, Pierre; Launeau, Patrick; Robin, Marc; Barillé, Laurent

2016-04-01

The invasion of the wild oyster Crassostrea gigas along the western European Atlantic coast has generated changes in the structure and functioning of intertidal ecosystems. Considered as an invasive species and a trophic competitor of the cultivated conspecific oyster, it is now seen as a resource by oyster farmers following recurrent mass summer mortalities of oyster spat since 2008. Spatial distribution maps of wild oyster reefs are required by local authorities to help define management strategies. In this work, visible-near infrared (VNIR) hyperspectral and multispectral remote sensing was investigated to map two contrasted intertidal reef structures: clusters of vertical oysters building three-dimensional dense reefs in muddy areas and oysters growing horizontally creating large flat reefs in rocky areas. A spectral library, collected in situ for various conditions with an ASD spectroradiometer, was used to run Spectral Angle Mapper classifications on airborne data obtained with an HySpex sensor (160 spectral bands) and SPOT satellite HRG multispectral data (3 spectral bands). With HySpex spectral/spatial resolution, horizontal oysters in the rocky area were correctly classified but the detection was less efficient for vertical oysters in muddy areas. Poor results were obtained with the multispectral image and from spatially or spectrally degraded HySpex data, it was clear that the spectral resolution was more important than the spatial resolution. In fact, there was a systematic mud deposition on shells of vertical oyster reefs explaining the misclassification of 30% of pixels recognized as mud or microphytobenthos. Spatial distribution maps of oyster reefs were coupled with in situ biomass measurements to illustrate the interest of a remote sensing product to provide stock estimations of wild oyster reefs to be exploited by oyster producers. This work highlights the interest of developing remote sensing techniques for aquaculture applications in coastal areas.

4482 Element Multispectral Hybrid PV/PC HgCdTe IRFPA for High Resolution Coverage of 3.7 - 15.4 Micrometers for the AIRS Instrument

NASA Technical Reports Server (NTRS)

Rutter, James; Libonate, Scott; Denley, Brian; Gurnee, Mark N.; Robillard, Gene

1996-01-01

The Atmospheric Infrared Sounder (AIRS) is a key facility instrument in the NASA Earth Observing System (EOS) program, being implemented to obtain comprehensive long-term measurements of earth processes affecting global change. The instrument performs passive IR remote sensing using a high resolution grating spectrometer with a wide spectral coverage (3.7 - 15.4 m) directing radiation onto a hybrid HgCdTe IRFPA operating at 58K in a vacuum package cooled to 155K. The hybrid HgCdTe FPA consists of twelve modules, 10 with multiplexed photovoltaic detectors and two with individually leaded out photoconductive detectors. The complex FPA has a large optical footprint, 53 mm x 66 mm, and receives energy dispersed from the grating through a precision filter assembly containing 17 narrow band filters. The backside illuminated PV detector arrays are fabricated from P-on-n double layer LPE grown heterojunction detectors in a bilinear format of 50 m x 100 m detectors, with from 232 to 420 detectors per module. For the MWIR bands four PV modules cover the 3.7 m to 8.22 m region. Low detector capacitance and low noise preamplifiers in the ROIC are key to achieving high sensitivities in these bands. Uniform quantum efficiencies and detectivities exceeding 3E13 cm-rtHz/W have been achieved. The LWIR region is covered by six PV modules spanning 8.8 m to 13.75 m. High detector resistance and very low ROIC preamplifier input noise are key to achieving high sensitivity. A detectivity exceeding 2E11 cm-rtHz/W has been achieved at the longest wavelength. Two additional PC modules cover the longest spectral bands out to 15.4 m. This high performance multispectral focal plane has been built and integrated with the dewar assembly, and is currently being integrated with the complete AIRS sensor.

A Multispectral Analysis of the Flamsteed Region of Oceanus Procellarum

NASA Astrophysics Data System (ADS)

Heather, D. J.; Dunkin, S. K.; Spudis, P. D.; Bussey, D. B. J.

1999-01-01

The Flamsteed area of Oceanus Procellarum is representative of basalts that have yet to be sampled. They studied the area in detail using telescopic data to identify seven distinct mare flows. This diversity makes the Flamsteed region an ideal candidate for Clementine multispectral studies. The region studied here is far smaller than that covered, but the higher spatial resolution of the Clementine data will allow us to make a fresh interpretation of the nature of our restricted area before expanding to encompass the surrounding regions. The primary aim of this work is to use Clementine UV-VIS data to analyze flows on a smaller scale and determine the stratigraphy of the mare, using impact craters as probes to measure the thickness of mare lavas wherever possible. We used the Clementine UV-VIS data to produce a multispectral image of the Flamsteed area from 0.60N to 16.06S and 308.34E to 317.12E. The data were processed at a resolution of 200 m/pixel using the ISIS software program (available through the USGS), and the photometric coefficients tabulated. In addition to the multispectral image, a "true color" image, FeO map using the algorithms, and a Ti02 map using the algorithms were generated. In conjunction with a 750-nm Clementine mosaic and Lunar Orbiter photographs, these images formed the dataset used for this analysis. For more details on the data-reduction procedure used, please contact the authors. The area studied here lies in the southeastern portion of Oceanus Procellarum, and covers approximately 134,500 square km, extending from the mare-highland boundary (to the south) up to and including the Flamsteed P ring. The number of spectrally distinct flows in the area is striking in the Clementine mosaics, ranging from high-Ti flows in and around Flamsteed P to low-Ti flows at the edges of the mare-highland boundaries. From a preliminary analysis, we have identified at least five flows in the multispectral image alone. Sunshine and Pieters found three distinct flows within the Flamsteed P ring using high resolution CCD images from a groundbased telescope. We find evidence for only two: a younger high-Ti flow overlying an older lower-Ti flow. However, we have not yet reduced the data for the most eastern part of the ring, and it is possible that further flow(s) could be found in our missing section. The low-Ti flows at some of the mare highland contacts to the south are exceptionally bright in the 750/415 nm channel of the multispectral image. These areas correlate with intermediate FeO and Ti02 content, and seem to be the oldest flows visible on the surface, probably extending over a large area beneath the later flows. Boundaries were defined according to multispectral and albedo properties. Detailed studies of the Ti02 map and maturity data (taken through observations of crater densities from the Orbiter frames and an optical maturity image produced using the algorithm of Lucey et al., will improve this map. Work is continuing in an attempt to delineate clearer flow boundaries. The primary aim of this work is to determine the thickness of the mare flows as one moves out from the highland boundary into Oceanus Procellarum. First-order indications of thickness can be obtained by searching for highland outcrops within the maria. The Flamsteed area shows many such outcrops, and the lavas must be quite thin close to these. A more absolute idea of basalt thickness can be obtained by calculating the depths of craters that have dug through the lavas to expose highland material below. These craters can be identified from multispectral images and 5-point spectra. Previous work has suggested that a cyan color in the multispectral frame represents highland material, and that yellows and greens are freshly excavated basalts. However, we have recently found that a cyan color can also result from a freshly excavated high-Ti basalt. In order to differentiate between the high-Ti and highland signature, it is necessary to look at the FeO and Ti02 frames and plot 5-point spectra to look for the absorption at 0.95 mm that is characteristic of pyroxenes in the basalts. These observations have shown there to be candidate craters in the Flamsteed region which have excavated highland material. The example crater displays a basaltic signature with a clear O.95 micron absorption in its south wall and ejecta, while the absorption in the north wall and ejecta is far weaker. The northern deposits are also relatively low in Ti02 and FeO, and probably represent a mix of basaltic and highland material. The crater is 8 km in diameter, so will have excavated to a depth of about 800mm (using the depth:diameter ratio of 1:10 given by Croft); this is therefore an upper limit to the thickness of the basalts at the crater's northern edge. In addition, there are several areas where craters close together excavate spectrally distinct materials. These may indicate boundaries of subsurface mare flows, and will allow for a more detailed stratigraphic picture to be constructed. We intend to map the lava flow and crater distribution across the Flamsteed region, using craters to deduce depths to the highland-mare contact where possible. Flamsteed will then be combined with adjoining areas of Oceanus Procellarum, gradually developing a complete picture of the stratigraphy and basalt thickness across the basin. This work will form part of a continuing project in which we aim to study maria across the whole Moon, providing a global perspective of lunar volcanic history. Additional information is contained in the original.

Multimodality molecular imaging and extracellular vesicle release based genetic profiling with porphyrin nanodroplets (Conference Presentation)

NASA Astrophysics Data System (ADS)

Zemp, Roger J.; Paproski, Robert J.

2017-03-01

For emerging tissue-engineering applications, transplants, and cell-based therapies it is important to assess cell viability and function in vivo in deep tissues. Bioluminescence and fluorescence methods are poorly suited to deep monitoring applications with high resolution and require genetically-engineered reporters which are not always feasible. We report on a method for imaging cell viability using deep, high-resolution photoacoustic imaging. We use an exogenous dye, Resazurin, itself weakly fluorescent until it is reduced from blue to a pink color with bright red fluorescence. Upon cell death fluorescence is lost and an absorption shift is observed. The irreversible reaction of resazurin to resorufin is proportional to aerobic respiration. We detect colorimetric absorption shifts using multispectral photoacoustic imaging and quantify the fraction of viable cells. SKOV-3 cells with and without ±80oC heat treatment were imaged after Resazurin treatment. High 575nm:620nm ratiometric absorption and photoacoustic signals in viable cells were observed with a much lower ratio in low-viability populations.

Skylab and ERTS-1 investigations of coastal land use and water properties. [Delaware Bay

NASA Technical Reports Server (NTRS)

Klemas, V. (Principal Investigator); Bartlett, D.; Rogers, R.

1974-01-01

The author has identified the following significant results. ERTS-1 multispectral scanner and Skylab's S190A, S190B, and S192 data products were evaluated for their utility in studying current circulation, suspended sediment concentrations and pollution dispersal in Delaware Bay and in mapping coastal vegetation and land use. Imagery from the ERTS-1 MSS, S190A and S190B cameras shows considerable detail in water structure, circulation, suspended sediment distribution and within waste disposal plumes in shelf waters. These data products were also used in differentiating and mapping twelve coastal vegetation and land use classes. The spatial resolution of the S190A multispectral facility appears to be about 30 to 70 meters while that of the S190B earth terrain camera is about 10 to 30 meters. Such resolution, along with good cartographic quality, indicates a considerable potential for mapping coastal land use and monitoring water properties in estuaries and on the continental shelf. The ERTS-1 MSS has a resolution of about 70-100 meters. Moreover, its regular 18-day cycle permits observation of important changes, including the environmental impact of coastal zone development on coastal vegetation and ecology.

Delineating Tree Types in a Complex Tropical Forest Setting Using High Resolution Multispectral Satellite Imagery

NASA Astrophysics Data System (ADS)

Cross, M.

2016-12-01

An improved process for the identification of tree types from satellite imagery for tropical forests is needed for more accurate assessments of the impact of forests on the global climate. La Selva Biological Station in Costa Rica was the tropical forest area selected for this particular study. WorldView-3 imagery was utilized because of its high spatial, spectral and radiometric resolution, its availability, and its potential to differentiate species in a complex forest setting. The first-step was to establish confidence in the high spatial and high radiometric resolution imagery from WorldView-3 in delineating tree types within a complex forest setting. In achieving this goal, ASD field spectrometer data were collected of specific tree species to establish solid ground control within the study site. The spectrometer data were collected from the top of each specific tree canopy utilizing established towers located at La Selva Biological Station so as to match the near-nadir view of the WorldView-3 imagery. The ASD data was processed utilizing the spectral response functions for each of the WorldView-3 bands to convert the ASD data into a band specific reflectivity. This allowed direct comparison of the ASD spectrometer reflectance data to the WorldView-3 multispectral imagery. The WorldView-3 imagery was processed to surface reflectance using two standard atmospheric correction procedures and the proprietary DigitalGlobe Atmospheric Compensation (AComp) product. The most accurate correction process was identified through comparison to the spectrometer data collected. A series of statistical measures were then utilized to access the accuracy of the processed imagery and which imagery bands are best suited for tree type identification. From this analysis, a segmentation/classification process was performed to identify individual tree type locations within the study area. It is envisioned the results of this study will improve traditional forest classification processes, provide more accurate assessments of species density and distribution, facilitate a more accurate biomass estimate of the tropical forest which will impact the accuracy of tree carbon storage estimates, and ultimately assist in developing a better overall characterization of tropical rainforest dynamics.

Hybrid method for building extraction in vegetation-rich urban areas from very high-resolution satellite imagery

NASA Astrophysics Data System (ADS)

Jayasekare, Ajith S.; Wickramasuriya, Rohan; Namazi-Rad, Mohammad-Reza; Perez, Pascal; Singh, Gaurav

2017-07-01

A continuous update of building information is necessary in today's urban planning. Digital images acquired by remote sensing platforms at appropriate spatial and temporal resolutions provide an excellent data source to achieve this. In particular, high-resolution satellite images are often used to retrieve objects such as rooftops using feature extraction. However, high-resolution images acquired over built-up areas are associated with noises such as shadows that reduce the accuracy of feature extraction. Feature extraction heavily relies on the reflectance purity of objects, which is difficult to perfect in complex urban landscapes. An attempt was made to increase the reflectance purity of building rooftops affected by shadows. In addition to the multispectral (MS) image, derivatives thereof namely, normalized difference vegetation index and principle component (PC) images were incorporated in generating the probability image. This hybrid probability image generation ensured that the effect of shadows on rooftop extraction, particularly on light-colored roofs, is largely eliminated. The PC image was also used for image segmentation, which further increased the accuracy compared to segmentation performed on an MS image. Results show that the presented method can achieve higher rooftop extraction accuracy (70.4%) in vegetation-rich urban areas compared to traditional methods.

Compression of regions in the global advanced very high resolution radiometer 1-km data set

NASA Technical Reports Server (NTRS)

Kess, Barbara L.; Steinwand, Daniel R.; Reichenbach, Stephen E.

1994-01-01

The global advanced very high resolution radiometer (AVHRR) 1-km data set is a 10-band image produced at USGS' EROS Data Center for the study of the world's land surfaces. The image contains masked regions for non-land areas which are identical in each band but vary between data sets. They comprise over 75 percent of this 9.7 gigabyte image. The mask is compressed once and stored separately from the land data which is compressed for each of the 10 bands. The mask is stored in a hierarchical format for multi-resolution decompression of geographic subwindows of the image. The land for each band is compressed by modifying a method that ignores fill values. This multi-spectral region compression efficiently compresses the region data and precludes fill values from interfering with land compression statistics. Results show that the masked regions in a one-byte test image (6.5 Gigabytes) compress to 0.2 percent of the 557,756,146 bytes they occupy in the original image, resulting in a compression ratio of 89.9 percent for the entire image.

Fluid Lensing and Applications to Remote Sensing of Aquatic Environments

NASA Technical Reports Server (NTRS)

Chirayath, Ved

2017-01-01

The use of fluid lensing technology on UAVs is presented as a novel means for 3D imaging of aquatic ecosystems from above the water's surface at the centimeter scale. Preliminary results are presented from airborne fluid lensing campaigns conducted over the coral reefs of Ofu Island, American Samoa (2013) and the stromatolite reefs of Shark Bay, Western Australia (2014), covering a combined area of 15km2. These reef ecosystems were revealed with centimetre-scale 2D resolution, and an accompanying 3D bathymetry model was derived using fluid lensing, Structure from Motion and UAV position data. Data products were validated from in-situ survey methods including underwater calibration targets, depth measurements and millimetre-scale high-dynamic range gigapixel photogrammetry. Fluid lensing is an experimental technology that uses water transmitting wavelengths to passively image underwater objects at high-resolution by exploiting time-varying optical lensing events caused by surface waves. Fluid lensing data are captured from low-altitude, cost-effective electric UAVs to achieve multispectral imagery and bathymetry models at the centimetre scale over regional areas. As a passive system, fluid lensing is presently limited by signal-to-noise ratio and water column inherent optical properties to approximately 10 m depth over visible wavelengths in clear waters. The datasets derived from fluid lensing present the first centimetre-scale images of a reef acquired from above the ocean surface, without wave distortion. The 3D multispectral data distinguish coral, fish and invertebrates in American Samoa, and reveal previously undocumented, morphologically distinct, stromatolite structures in Shark Bay. These findings suggest fluid lensing and multirotor electric drones represent a promising advance in the remote sensing of aquatic environments at the centimetre scale, or 'reef scale' relevant to the conservation of reef ecosystems. Pending further development and validation of fluid lensing methods, these technologies present a solution for large-scale 3D surveys of shallow aquatic habitats with centimetre-scale spatial resolution and hourly temporal sampling.

Comparing different approaches for an effective monitoring of forest fires based on MSG/SEVIRI images

NASA Astrophysics Data System (ADS)

Laneve, Giovanni

2010-05-01

The remote sensing sensors on board of geostationary satellite, as consequence of the high frequency of the observations, allow, in principle, the monitoring of these phenomena characterized by a fast dynamics. The only condition for is that the events to be monitored should be enough strong to be recognizable notwithstanding the low spatial resolution of the present geostationary systems (MSG/SEVIRI, GOES Imager, MTSAT). Apart from meteorological phenomena other events, like those associated with forest fires and/or volcanic eruption, are characterized by a very fast dynamics. These events are also associated with a very strong signal that make them observable by geostationary satellite in a quasi-continuous way. However, in order to make possible the detection of small fires by using the low resolution multi-spectral imagery provided by geostationary sensor like SEVIRI (3x3 km2 at the equator) new algorithms, capable to exploit it high observation frequency, has been developed. This paper is devoted to show the results obtained by comparing some of these algorithms trying to highlight their advantages and limits. The algorithms herein considered are these developed by CRPSM (SFIDE®), UNIBAS/CNR (RST-FIRES) and ESA-ESRIN (MDIFRM). In general, the new approaches proposed by each one of them are capable to promptly detect small fires making possible an operational utilization of the satellite based fire detection system in the fire fighting phases. In fact, these algorithms are quite different from these introduced in the past and specifically devoted to fire detection using low resolution multi-spectral imagery on LEO (Low Earth Orbit) satellite. Thanks to these differences they are capable of detecting sub-hectare (0.2 ha) forest fires providing an useful instrument for monitoring quasi-continuously forest fires, estimating the FRP (Fire Radiative Power), evaluating the burned biomass, retrieving the emission in the atmosphere.

Multispectral Palmprint Recognition Using a Quaternion Matrix

PubMed Central

Xu, Xingpeng; Guo, Zhenhua; Song, Changjiang; Li, Yafeng

2012-01-01

Palmprints have been widely studied for biometric recognition for many years. Traditionally, a white light source is used for illumination. Recently, multispectral imaging has drawn attention because of its high recognition accuracy. Multispectral palmprint systems can provide more discriminant information under different illuminations in a short time, thus they can achieve better recognition accuracy. Previously, multispectral palmprint images were taken as a kind of multi-modal biometrics, and the fusion scheme on the image level or matching score level was used. However, some spectral information will be lost during image level or matching score level fusion. In this study, we propose a new method for multispectral images based on a quaternion model which could fully utilize the multispectral information. Firstly, multispectral palmprint images captured under red, green, blue and near-infrared (NIR) illuminations were represented by a quaternion matrix, then principal component analysis (PCA) and discrete wavelet transform (DWT) were applied respectively on the matrix to extract palmprint features. After that, Euclidean distance was used to measure the dissimilarity between different features. Finally, the sum of two distances and the nearest neighborhood classifier were employed for recognition decision. Experimental results showed that using the quaternion matrix can achieve a higher recognition rate. Given 3000 test samples from 500 palms, the recognition rate can be as high as 98.83%. PMID:22666049

Multispectral palmprint recognition using a quaternion matrix.

PubMed

Xu, Xingpeng; Guo, Zhenhua; Song, Changjiang; Li, Yafeng

2012-01-01

Palmprints have been widely studied for biometric recognition for many years. Traditionally, a white light source is used for illumination. Recently, multispectral imaging has drawn attention because of its high recognition accuracy. Multispectral palmprint systems can provide more discriminant information under different illuminations in a short time, thus they can achieve better recognition accuracy. Previously, multispectral palmprint images were taken as a kind of multi-modal biometrics, and the fusion scheme on the image level or matching score level was used. However, some spectral information will be lost during image level or matching score level fusion. In this study, we propose a new method for multispectral images based on a quaternion model which could fully utilize the multispectral information. Firstly, multispectral palmprint images captured under red, green, blue and near-infrared (NIR) illuminations were represented by a quaternion matrix, then principal component analysis (PCA) and discrete wavelet transform (DWT) were applied respectively on the matrix to extract palmprint features. After that, Euclidean distance was used to measure the dissimilarity between different features. Finally, the sum of two distances and the nearest neighborhood classifier were employed for recognition decision. Experimental results showed that using the quaternion matrix can achieve a higher recognition rate. Given 3000 test samples from 500 palms, the recognition rate can be as high as 98.83%.

Estimation and mapping of above-ground biomass of mangrove forests and their replacement land uses in the Philippines using Sentinel imagery

NASA Astrophysics Data System (ADS)

Castillo, Jose Alan A.; Apan, Armando A.; Maraseni, Tek N.; Salmo, Severino G.

2017-12-01

The recent launch of the Sentinel-1 (SAR) and Sentinel-2 (multispectral) missions offers a new opportunity for land-based biomass mapping and monitoring especially in the tropics where deforestation is highest. Yet, unlike in agriculture and inland land uses, the use of Sentinel imagery has not been evaluated for biomass retrieval in mangrove forest and the non-forest land uses that replaced mangroves. In this study, we evaluated the ability of Sentinel imagery for the retrieval and predictive mapping of above-ground biomass of mangroves and their replacement land uses. We used Sentinel SAR and multispectral imagery to develop biomass prediction models through the conventional linear regression and novel Machine Learning algorithms. We developed models each from SAR raw polarisation backscatter data, multispectral bands, vegetation indices, and canopy biophysical variables. The results show that the model based on biophysical variable Leaf Area Index (LAI) derived from Sentinel-2 was more accurate in predicting the overall above-ground biomass. In contrast, the model which utilised optical bands had the lowest accuracy. However, the SAR-based model was more accurate in predicting the biomass in the usually deficient to low vegetation cover non-forest replacement land uses such as abandoned aquaculture pond, cleared mangrove and abandoned salt pond. These models had 0.82-0.83 correlation/agreement of observed and predicted value, and root mean square error of 27.8-28.5 Mg ha-1. Among the Sentinel-2 multispectral bands, the red and red edge bands (bands 4, 5 and 7), combined with elevation data, were the best variable set combination for biomass prediction. The red edge-based Inverted Red-Edge Chlorophyll Index had the highest prediction accuracy among the vegetation indices. Overall, Sentinel-1 SAR and Sentinel-2 multispectral imagery can provide satisfactory results in the retrieval and predictive mapping of the above-ground biomass of mangroves and the replacement non-forest land uses, especially with the inclusion of elevation data. The study demonstrates encouraging results in biomass mapping of mangroves and other coastal land uses in the tropics using the freely accessible and relatively high-resolution Sentinel imagery.

Mapping bathymetry in an active surf zone with the WorldView2 multispectral satellite

NASA Astrophysics Data System (ADS)

Trimble, S. M.; Houser, C.; Brander, R.; Chirico, P.

2015-12-01

Rip currents are strong, narrow seaward flows of water that originate in the surf zones of many global beaches. They are related to hundreds of international drownings each year, but exact numbers are difficult to calculate due to logistical difficulties in obtaining accurate incident reports. Annual average rip current fatalities are estimated to be ~100, 53 and 21 in the United States (US), Costa Rica, and Australia respectively. Current warning systems (e.g. National Weather Service) do not account for fine resolution nearshore bathymetry because it is difficult to capture. The method shown here could provide frequent, high resolution maps of nearshore bathymetry at a scale required for improved rip prediction and warning. This study demonstrates a method for mapping bathymetry in the surf zone (20m deep and less), specifically within rip channels, because rips form at topographically low spots in the bathymetry as a result of feedback amongst waves, substrate, and antecedent bathymetry. The methods employ the Digital Globe WorldView2 (WV2) multispectral satellite and field measurements of depth to generate maps of the changing bathymetry at two embayed, rip-prone beaches: Playa Cocles, Puerto Viejo de Talamanca, Costa Rica, and Bondi Beach, Sydney, Australia. WV2 has a 1.1 day pass-over rate with 1.84m ground pixel resolution of 8 bands, including 'yellow' (585-625 nm) and 'coastal blue' (400-450 nm). The data is used to classify bottom type and to map depth to the return in multiple bands. The methodology is tested at each site for algorithm consistency between dates, and again for applicability between sites.

The Rich Color Variations of Pluto

NASA Image and Video Library

2015-09-24

NASA's New Horizons spacecraft captured this high-resolution enhanced color view of Pluto on July 14, 2015. The image combines blue, red and infrared images taken by the Ralph/Multispectral Visual Imaging Camera (MVIC). Pluto's surface sports a remarkable range of subtle colors, enhanced in this view to a rainbow of pale blues, yellows, oranges, and deep reds. Many landforms have their own distinct colors, telling a complex geological and climatological story that scientists have only just begun to decode. The image resolves details and colors on scales as small as 0.8 miles (1.3 kilometers). http://photojournal.jpl.nasa.gov/catalog/PIA19952

Multispectral and geomorphic studies of processed Voyager 2 images of Europa

NASA Technical Reports Server (NTRS)

Meier, T. A.

1984-01-01

High resolution images of Europa taken by the Voyager 2 spacecraft were used to study a portion of Europa's dark lineations and the major white line feature Agenor Linea. Initial image processing of images 1195J2-001 (violet filter), 1198J2-001 (blue filter), 1201J2-001 (orange filter), and 1204J2-001 (ultraviolet filter) was performed at the U.S.G.S. Branch of Astrogeology in Flagstaff, Arizona. Processing was completed through the stages of image registration and color ratio image construction. Pixel printouts were used in a new technique of linear feature profiling to compensate for image misregistration through the mapping of features on the printouts. In all, 193 dark lineation segments were mapped and profiled. The more accurate multispectral data derived by this method was plotted using a new application of the ternary diagram, with orange, blue, and violet relative spectral reflectances serving as end members. Statistical techniques were then applied to the ternary diagram plots. The image products generated at LPI were used mainly to cross-check and verify the results of the ternary diagram analysis.

Evolving forest fire burn severity classification algorithms for multispectral imagery

NASA Astrophysics Data System (ADS)

Brumby, Steven P.; Harvey, Neal R.; Bloch, Jeffrey J.; Theiler, James P.; Perkins, Simon J.; Young, Aaron C.; Szymanski, John J.

2001-08-01

Between May 6 and May 18, 2000, the Cerro Grande/Los Alamos wildfire burned approximately 43,000 acres (17,500 ha) and 235 residences in the town of Los Alamos, NM. Initial estimates of forest damage included 17,000 acres (6,900 ha) of 70-100% tree mortality. Restoration efforts following the fire were complicated by the large scale of the fire, and by the presence of extensive natural and man-made hazards. These conditions forced a reliance on remote sensing techniques for mapping and classifying the burn region. During and after the fire, remote-sensing data was acquired from a variety of aircraft-based and satellite-based sensors, including Landsat 7. We now report on the application of a machine learning technique, implemented in a software package called GENIE, to the classification of forest fire burn severity using Landsat 7 ETM+ multispectral imagery. The details of this automatic classification are compared to the manually produced burn classification, which was derived from field observations and manual interpretation of high-resolution aerial color/infrared photography.

Image processing using Gallium Arsenide (GaAs) technology

NASA Technical Reports Server (NTRS)

Miller, Warner H.

1989-01-01

The need to increase the information return from space-borne imaging systems has increased in the past decade. The use of multi-spectral data has resulted in the need for finer spatial resolution and greater spectral coverage. Onboard signal processing will be necessary in order to utilize the available Tracking and Data Relay Satellite System (TDRSS) communication channel at high efficiency. A generally recognized approach to the increased efficiency of channel usage is through data compression techniques. The compression technique implemented is a differential pulse code modulation (DPCM) scheme with a non-uniform quantizer. The need to advance the state-of-the-art of onboard processing was recognized and a GaAs integrated circuit technology was chosen. An Adaptive Programmable Processor (APP) chip set was developed which is based on an 8-bit slice general processor. The reason for choosing the compression technique for the Multi-spectral Linear Array (MLA) instrument is described. Also a description is given of the GaAs integrated circuit chip set which will demonstrate that data compression can be performed onboard in real time at data rate in the order of 500 Mb/s.

Satellite Map of Port-au-Prince, Haiti-2010-Natural Color

USGS Publications Warehouse

Cole, Christopher J.; Sloan, Jeff

2010-01-01

The U.S. Geological Survey produced 1:24,000-scale post-earthquake image base maps incorporating high- and medium-resolution remotely sensed imagery following the 7.0 magnitude earthquake near the capital city of Port au Prince, Haiti, on January 12, 2010. Commercial 2.4-meter multispectral QuickBird imagery was acquired by DigitalGlobe on January 15, 2010, following the initial earthquake. Ten-meter multispectral ALOS AVNIR-2 imagery was collected by the Japanese Space Agency (JAXA) on January 12, 2010. These data were acquired under the Remote Sensing International Charter, a global team of space and satellite agencies that provide timely imagery in support of emergency response efforts worldwide. The images shown on this map were employed to support earthquake response efforts, specifically for use in determining ground deformation, damage assessment, and emergency management decisions. The raw, unprocessed imagery was geo-corrected, mosaicked, and reproduced onto a cartographic 1:24,000-scale base map. These maps are intended to provide a temporally current representation of post-earthquake ground conditions, which may be of use to decision makers and to the general public.

Satellite Map of Port-au-Prince, Haiti-2010-Infrared

USGS Publications Warehouse

Cole, Christopher J.; Sloan, Jeff

2010-01-01

The U.S. Geological Survey produced 1:24,000-scale post-earthquake image base maps incorporating high- and medium-resolution remotely sensed imagery following the 7.0 magnitude earthquake near the capital city of Port au Prince, Haiti, on January 12, 2010. Commercial 2.4-meter multispectral QuickBird imagery was acquired by DigitalGlobe on January 15, 2010, following the initial earthquake. Ten-meter multispectral ALOS AVNIR-2 imagery was collected by the Japanese Space Agency (JAXA) on January 12, 2010. These data were acquired under the Remote Sensing International Charter, a global team of space and satellite agencies that provide timely imagery in support of emergency response efforts worldwide. The images shown on this map were employed to support earthquake response efforts, specifically for use in determining ground deformation, damage assessment, and emergency management decisions. The raw, unprocessed imagery was geo-corrected, mosaicked, and reproduced onto a cartographic 1:24,000-scale base map. These maps are intended to provide a temporally current representation of post-earthquake ground conditions, which may be of use to decision makers and to the general public.

Interactive digital image manipulation system

NASA Technical Reports Server (NTRS)

Henze, J.; Dezur, R.

1975-01-01

The system is designed for manipulation, analysis, interpretation, and processing of a wide variety of image data. LANDSAT (ERTS) and other data in digital form can be input directly into the system. Photographic prints and transparencies are first converted to digital form with an on-line high-resolution microdensitometer. The system is implemented on a Hewlett-Packard 3000 computer with 128 K bytes of core memory and a 47.5 megabyte disk. It includes a true color display monitor, with processing memories, graphics overlays, and a movable cursor. Image data formats are flexible so that there is no restriction to a given set of remote sensors. Conversion between data types is available to provide a basis for comparison of the various data. Multispectral data is fully supported, and there is no restriction on the number of dimensions. In this way multispectral data collected at more than one point in time may simply be treated as a data collected with twice (three times, etc.) the number of sensors. There are various libraries of functions available to the user: processing functions, display functions, system functions, and earth resources applications functions.

SIRF: Simultaneous Satellite Image Registration and Fusion in a Unified Framework.

PubMed

Chen, Chen; Li, Yeqing; Liu, Wei; Huang, Junzhou

2015-11-01

In this paper, we propose a novel method for image fusion with a high-resolution panchromatic image and a low-resolution multispectral (Ms) image at the same geographical location. The fusion is formulated as a convex optimization problem which minimizes a linear combination of a least-squares fitting term and a dynamic gradient sparsity regularizer. The former is to preserve accurate spectral information of the Ms image, while the latter is to keep sharp edges of the high-resolution panchromatic image. We further propose to simultaneously register the two images during the fusing process, which is naturally achieved by virtue of the dynamic gradient sparsity property. An efficient algorithm is then devised to solve the optimization problem, accomplishing a linear computational complexity in the size of the output image in each iteration. We compare our method against six state-of-the-art image fusion methods on Ms image data sets from four satellites. Extensive experimental results demonstrate that the proposed method substantially outperforms the others in terms of both spatial and spectral qualities. We also show that our method can provide high-quality products from coarsely registered real-world IKONOS data sets. Finally, a MATLAB implementation is provided to facilitate future research.

High resolution critical habitat mapping and classification of tidal freshwater wetlands in the ACE Basin

NASA Astrophysics Data System (ADS)

Strickland, Melissa Anne

In collaboration with the South Carolina Department of Natural Resources ACE Basin National Estuarine Research Reserve (ACE Basin NERR), the tidal freshwater ecosystems along the South Edisto River in the ACE Basin are being accurately mapped and classified using a LIDAR-Remote Sensing Fusion technique that integrates LAS LIDAR data into texture images and then merges the elevation textures and multispectral imagery for very high resolution mapping. This project discusses the development and refinement of an ArcGIS Toolbox capable of automating protocols and procedures for marsh delineation and microhabitat identification. The result is a high resolution habitat and land use map used for the identification of threatened habitat. Tidal freshwater wetlands are also a critical habitat for colonial wading birds and an accurate assessment of community diversity and acreage of this habitat type in the ACE Basin will support SCDNR's conservation and protection efforts. The maps developed by this study will be used to better monitor the freshwater/saltwater interface and establish a baseline for an ACE NERR monitoring program to track the rates and extent of alterations due to projected environmental stressors. Preliminary ground-truthing in the field will provide information about the accuracy of the mapping tool.

Multispectral Coatings

DTIC Science & Technology

2010-01-01

failure, whereas the polymer nanocomposite gave ductile failure with less surface damage. Task 2. Highly reflective self-assembled coatings . The...AFRL-RX-WP-TR-2010-4036 MULTISPECTRAL COATINGS Eric Grulke University of Kentucky Thad Druffel Optical Dynamics JANUARY...REPORT TYPE 3. DATES COVERED (From - To) January 2010 Final 28 November 2005 – 30 September 2008 4. TITLE AND SUBTITLE MULTISPECTRAL COATINGS 5a

The development of a specialized processor for a space-based multispectral earth imager

NASA Astrophysics Data System (ADS)

Khedr, Mostafa E.

2008-10-01

This work was done in the Department of Computer Engineering, Lvov Polytechnic National University, Lvov, Ukraine, as a thesis entitled "Space Imager Computer System for Raw Video Data Processing" [1]. This work describes the synthesis and practical implementation of a specialized computer system for raw data control and processing onboard a satellite MultiSpectral earth imager. This computer system is intended for satellites with resolution in the range of one meter with 12-bit precession. The design is based mostly on general off-the-shelf components such as (FPGAs) plus custom designed software for interfacing with PC and test equipment. The designed system was successfully manufactured and now fully functioning in orbit.

Geology team

NASA Technical Reports Server (NTRS)

1982-01-01

Evaluating of the combined utility of narrowband and multispectral imaging in both the infrared and visible for the lithologic identification of geologic materials, and of the combined utility of multispectral imaging in the visible and infrared for lithologic mapping on a global bases are near term recommendations for future imaging capabilities. Long term recommendations include laboratory research into methods of field sampling and theoretical models of microscale mixing. The utility of improved spatial and spectral resolutions and radiometric sensitivity is also suggested for the long term. Geobotanical remote sensing research should be conducted to (1) separate geological and botanical spectral signatures in individual picture elements; (2) study geobotanical correlations that more fully simulate natural conditions; and use test sites designed to test specific geobotanical hypotheses.

Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Nuristan mineral district in Afghanistan

USGS Publications Warehouse

Davis, Philip A.; Cagney, Laura E.; Arko, Scott A.; Harbin, Michelle L.; Davis, Philip A.

2013-01-01

The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Nuristan mineral district, which has gem, lithium, and cesium deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA,2008,2009), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such, the DS products match JAXA criteria for value added products, which are not copyrighted, according to the ALOS end-user license agreement. The selection criteria for the satellite imagery used in our mosaics were images having (1) the highest solar-elevation angles (near summer solstice) and (2) the least cloud, cloud-shadow, and snow cover. The multispectral and panchromatic data were orthorectified with ALOS satellite ephemeris data, a process which is not as accurate as orthorectification using digital elevation models (DEMs); however, the ALOS processing center did not have a precise DEM. As a result, the multispectral and panchromatic image pairs were generally not well registered to the surface and not coregistered well enough to perform resolution enhancement on the multispectral data. For this particular area, PRISM image orthorectification was performed by the Alaska Satellite Facility, applying its photogrammetric software to PRISM stereo images with vertical control points obtained from the digital elevation database produced by the Shuttle Radar Topography Mission (Farr and others, 2007) and horizontal adjustments based on a controlled Landsat image base (Davis, 2006). The 10-m AVNIR multispectral imagery was then coregistered to the orthorectified PRISM images and individual multispectral and panchromatic images were mosaicked into single images of the entire area of interest. The image coregistration was facilitated using an automated control-point algorithm developed by the USGS that allows image coregistration to within one picture element. Before rectification, the multispectral and panchromatic images were converted to radiance values and then to relative-reflectance values using the methods described in Davis (2006). Mosaicking the multispectral or panchromatic images started with the image with the highest sun-elevation angle and the least atmospheric scattering, which was treated as the standard image. The band-reflectance values of all other multispectral or panchromatic images within the area were sequentially adjusted to that of the standard image by determining band-reflectance correspondence between overlapping images using linear least-squares analysis. All available panchromatic images for this area had significant cloud and snow cover that precluded their use for resolution enhancement of the multispectral image data. Each of the four-band images within the 10-m image mosaic was individually subjected to a local-area histogram stretch algorithm (described in Davis, 2007), which stretches each band’s picture element based on the digital values of all picture elements within a 500-m radius. The final databases, which are provided in this DS, are three-band, color-composite images of the local-area-enhanced, natural-color data (the blue, green, and red wavelength bands) and color-infrared data (the green, red, and near-infrared wavelength bands). All image data were initially projected and maintained in Universal Transverse Mercator (UTM) map projection using the target area’s local zone (42 for Nuristan) and the WGS84 datum. The final image mosaics for the Nuristan area are provided as embedded geotiff images, which can be read and used by most geographic information system (GIS) and image-processing software. The tiff world files (tfw) are provided, even though they are generally not needed for most software to read an embedded geotiff image.

Unmixing chromophores in human skin with a 3D multispectral optoacoustic mesoscopy system

NASA Astrophysics Data System (ADS)

Schwarz, Mathias; Aguirre, Juan; Soliman, Dominik; Buehler, Andreas; Ntziachristos, Vasilis

2016-03-01

The absorption of visible light by human skin is governed by a number of natural chromophores: Eumelanin, pheomelanin, oxyhemoglobin, and deoxyhemoglobin are the major absorbers in the visible range in cutaneous tissue. Label-free quantification of these tissue chromophores is an important step of optoacoustic (photoacoustic) imaging towards clinical application, since it provides relevant information in diseases. In tumor cells, for instance, there are metabolic changes (Warburg effect) compared to healthy cells, leading to changes in oxygenation in the environment of tumors. In malignant melanoma changes in the absorption spectrum have been observed compared to the spectrum of nonmalignant nevi. So far, optoacoustic imaging has been applied to human skin mostly in single-wavelength mode, providing anatomical information but no functional information. In this work, we excited the tissue by a tunable laser source in the spectral range from 413-680 nm with a repetition rate of 50 Hz. The laser was operated in wavelengthsweep mode emitting consecutive pulses at various wavelengths that allowed for automatic co-registration of the multispectral datasets. The multispectral raster-scan optoacoustic mesoscopy (MSOM) system provides a lateral resolution of <60 μm independent of wavelength. Based on the known absorption spectra of melanin, oxyhemoglobin, and deoxyhemoglobin, three-dimensional absorption maps of all three absorbers were calculated from the multispectral dataset.

A climatology of visible surface reflectance spectra

NASA Astrophysics Data System (ADS)

Zoogman, Peter; Liu, Xiong; Chance, Kelly; Sun, Qingsong; Schaaf, Crystal; Mahr, Tobias; Wagner, Thomas

2016-09-01

We present a high spectral resolution climatology of visible surface reflectance as a function of wavelength for use in satellite measurements of ozone and other atmospheric species. The Tropospheric Emissions: Monitoring of Pollution (TEMPO) instrument is planned to measure backscattered solar radiation in the 290-740 nm range, including the ultraviolet and visible Chappuis ozone bands. Observation in the weak Chappuis band takes advantage of the relative transparency of the atmosphere in the visible to achieve sensitivity to near-surface ozone. However, due to the weakness of the ozone absorption features this measurement is more sensitive to errors in visible surface reflectance, which is highly variable. We utilize reflectance measurements of individual plant, man-made, and other surface types to calculate the primary modes of variability of visible surface reflectance at a high spectral resolution, comparable to that of TEMPO (0.6 nm). Using the Moderate-resolution Imaging Spectroradiometer (MODIS) Bidirection Reflectance Distribution Function (BRDF)/albedo product and our derived primary modes we construct a high spatial resolution climatology of wavelength-dependent surface reflectance over all viewing scenes and geometries. The Global Ozone Monitoring Experiment-2 (GOME-2) Lambertian Equivalent Reflectance (LER) product provides complementary information over water and snow scenes. Preliminary results using this approach in multispectral ultraviolet+visible ozone retrievals from the GOME-2 instrument show significant improvement to the fitting residuals over vegetated scenes.

Quasi-microscope concept for planetary missions.

PubMed

Huck, F O; Arvidson, R E; Burcher, E E; Giat, O; Wall, S D

1977-09-01

Viking lander cameras have returned stereo and multispectral views of the Martian surface with a resolution that approaches 2 mm/lp in the near field. A two-orders-of-magnitude increase in resolution could be obtained for collected surface samples by augmenting these cameras with auxiliary optics that would neither impose special camera design requirements nor limit the cameras field of view of the terrain. Quasi-microscope images would provide valuable data on the physical and chemical characteristics of planetary regoliths.

Vital-dye enhanced fluorescence imaging of gastrointestinal mucosa: metaplasia, neoplasia, inflammation

PubMed Central

Muldoon, Timothy J; Polydorides, Alexandros D; Maru, Dipen M; Harpaz, Noam; Harris, Michael T; Hofstettor, Wayne; Hiotis, Spiros P; Kim, Sanghyun A; Ky, Alex J; Anandasabapathy, Sharmila; Richards-Kortum, Rebecca

2012-01-01

Background Confocal endomicroscopy has revolutionized endoscopy by offering sub-cellular images of gastrointestinal epithelium; however, field-of-view is limited. There is a need for multi-scale endoscopy platforms that use widefield imaging to better direct placement of high-resolution probes. Design Feasibility Study Objective This study evaluates the feasibility of a single agent, proflavine hemisulfate, as a contrast medium during both widefield and high resolution imaging to characterize morphologic changes associated with a variety of gastrointestinal conditions. Setting U.T. M.D. Anderson Cancer Center (Houston, TX) and Mount Sinai Medical Center (New York, NY) Patients, Interventions, and Main Outcome Measurements Surgical specimens were obtained from 15 patients undergoing esophagectomy/colectomy. Proflavine, a vital fluorescent dye, was applied topically. Specimens were imaged with a widefield multispectral microscope and a high-resolution microendoscope. Images were compared to histopathology. Results Widefield-fluorescence imaging enhanced visualization of morphology, including the presence and spatial distribution of glands, glandular distortion, atrophy and crowding. High-resolution imaging of widefield-abnormal areas revealed that neoplastic progression corresponded to glandular heterogeneity and nuclear crowding in dysplasia, with glandular effacement in carcinoma. These widefield and high-resolution image features correlated well with histopathology. Limitations This imaging approach must be validated in vivo with a larger sample size. Conclusions Multi-scale proflavine-enhanced fluorescence imaging can delineate epithelial changes in a variety of gastrointestinal conditions. Distorted glandular features seen with widefield imaging could serve as a critical ‘bridge’ to high-resolution probe placement. An endoscopic platform combining the two modalities with a single vital-dye may facilitate point-of-care decision-making by providing real-time, in vivo diagnoses. PMID:22301343

Vital-dye enhanced fluorescence imaging of GI mucosa: metaplasia, neoplasia, inflammation.

PubMed

Thekkek, Nadhi; Muldoon, Timothy; Polydorides, Alexandros D; Maru, Dipen M; Harpaz, Noam; Harris, Michael T; Hofstettor, Wayne; Hiotis, Spiros P; Kim, Sanghyun A; Ky, Alex Jenny; Anandasabapathy, Sharmila; Richards-Kortum, Rebecca

2012-04-01

Confocal endomicroscopy has revolutionized endoscopy by offering subcellular images of the GI epithelium; however, the field of view is limited. Multiscale endoscopy platforms that use widefield imaging are needed to better direct the placement of high-resolution probes. Feasibility study. This study evaluated the feasibility of a single agent, proflavine hemisulfate, as a contrast medium during both widefield and high-resolution imaging to characterize the morphologic changes associated with a variety of GI conditions. The University of Texas MD Anderson Cancer Center, Houston, Texas, and Mount Sinai Medical Center, New York, New York. PATIENTS, INTERVENTIONS, AND MAIN OUTCOME MEASUREMENTS: Resected specimens were obtained from 15 patients undergoing EMR, esophagectomy, or colectomy. Proflavine hemisulfate, a vital fluorescent dye, was applied topically. The specimens were imaged with a widefield multispectral microscope and a high-resolution microendoscope. The images were compared with histopathologic examination. Widefield fluorescence imaging enhanced visualization of morphology, including the presence and spatial distribution of glands, glandular distortion, atrophy, and crowding. High-resolution imaging of widefield abnormal areas revealed that neoplastic progression corresponded to glandular heterogeneity and nuclear crowding in dysplasia, with glandular effacement in carcinoma. These widefield and high-resolution image features correlated well with the histopathologic features. This imaging approach must be validated in vivo with a larger sample size. Multiscale proflavine-enhanced fluorescence imaging can delineate epithelial changes in a variety of GI conditions. Distorted glandular features seen with widefield imaging could serve as a critical bridge to high-resolution probe placement. An endoscopic platform combining the two modalities with a single vital dye may facilitate point-of-care decision making by providing real-time, in vivo diagnoses. Copyright © 2012 American Society for Gastrointestinal Endoscopy. Published by Mosby, Inc. All rights reserved.

Fusing Unmanned Aerial Vehicle Imagery with High Resolution Hydrologic Modeling (Invited)

NASA Astrophysics Data System (ADS)

Vivoni, E. R.; Pierini, N.; Schreiner-McGraw, A.; Anderson, C.; Saripalli, S.; Rango, A.

2013-12-01

After decades of development and applications, high resolution hydrologic models are now common tools in research and increasingly used in practice. More recently, high resolution imagery from unmanned aerial vehicles (UAVs) that provide information on land surface properties have become available for civilian applications. Fusing the two approaches promises to significantly advance the state-of-the-art in terms of hydrologic modeling capabilities. This combination will also challenge assumptions on model processes, parameterizations and scale as land surface characteristics (~0.1 to 1 m) may now surpass traditional model resolutions (~10 to 100 m). Ultimately, predictions from high resolution hydrologic models need to be consistent with the observational data that can be collected from UAVs. This talk will describe our efforts to develop, utilize and test the impact of UAV-derived topographic and vegetation fields on the simulation of two small watersheds in the Sonoran and Chihuahuan Deserts at the Santa Rita Experimental Range (Green Valley, AZ) and the Jornada Experimental Range (Las Cruces, NM). High resolution digital terrain models, image orthomosaics and vegetation species classification were obtained from a fixed wing airplane and a rotary wing helicopter, and compared to coarser analyses and products, including Light Detection and Ranging (LiDAR). We focus the discussion on the relative improvements achieved with UAV-derived fields in terms of terrain-hydrologic-vegetation analyses and summer season simulations using the TIN-based Real-time Integrated Basin Simulator (tRIBS) model. Model simulations are evaluated at each site with respect to a high-resolution sensor network consisting of six rain gauges, forty soil moisture and temperature profiles, four channel runoff flumes, a cosmic-ray soil moisture sensor and an eddy covariance tower over multiple summer periods. We also discuss prospects for the fusion of high resolution models with novel observations from UAVs, including synthetic aperture radar and multispectral imagery.

Development of low-cost high-performance multispectral camera system at Banpil

NASA Astrophysics Data System (ADS)

Oduor, Patrick; Mizuno, Genki; Olah, Robert; Dutta, Achyut K.

2014-05-01

Banpil Photonics (Banpil) has developed a low-cost high-performance multispectral camera system for Visible to Short- Wave Infrared (VIS-SWIR) imaging for the most demanding high-sensitivity and high-speed military, commercial and industrial applications. The 640x512 pixel InGaAs uncooled camera system is designed to provide a compact, smallform factor to within a cubic inch, high sensitivity needing less than 100 electrons, high dynamic range exceeding 190 dB, high-frame rates greater than 1000 frames per second (FPS) at full resolution, and low power consumption below 1W. This is practically all the feature benefits highly desirable in military imaging applications to expand deployment to every warfighter, while also maintaining a low-cost structure demanded for scaling into commercial markets. This paper describes Banpil's development of the camera system including the features of the image sensor with an innovation integrating advanced digital electronics functionality, which has made the confluence of high-performance capabilities on the same imaging platform practical at low cost. It discusses the strategies employed including innovations of the key components (e.g. focal plane array (FPA) and Read-Out Integrated Circuitry (ROIC)) within our control while maintaining a fabless model, and strategic collaboration with partners to attain additional cost reductions on optics, electronics, and packaging. We highlight the challenges and potential opportunities for further cost reductions to achieve a goal of a sub-$1000 uncooled high-performance camera system. Finally, a brief overview of emerging military, commercial and industrial applications that will benefit from this high performance imaging system and their forecast cost structure is presented.

Applications systems verification and transfer project. Volume 2: Operational applications of satellite snow-cover observations and data-collection systems in the Arizona test site

NASA Technical Reports Server (NTRS)

Schumann, H. H.

1981-01-01

Ground surveys and aerial observations were used to monitor rapidly changing moisture conditions in the Salt-Verde watershed. Repetitive satellite snow cover observations greatly reduce the necessity for routine aerial snow reconnaissance flights over the mountains. High resolution, multispectral imagery provided by LANDSAT satellite series enabled rapid and accurate mapping of snow-cover distributions for small- to medium-sized subwatersheds; however, the imagery provided only one observation every 9 days of about a third of the watershed. Low resolution imagery acquired by the ITOSa dn SMS/GOES meteorological satellite series provides the daily synoptic observation necessary to monitor the rapid changes in snow-covered area in the entire watershed. Short term runoff volumes can be predicted from daily sequential snow cover observations.

Monitoring algal blooms in drinking water reservoirs using the Landsat-8 Operational Land Imager

EPA Science Inventory

In this study, we demonstrated that the Landsat-8 Operational Land Imager (OLI) sensor is a powerful tool that can provide periodic and system-wide information on the condition of drinking water reservoirs. The OLI is a multispectral radiometer (30 m spatial resolution) that allo...

Measurement of replication structures at the nanometer scale using super-resolution light microscopy

PubMed Central

Baddeley, D.; Chagin, V. O.; Schermelleh, L.; Martin, S.; Pombo, A.; Carlton, P. M.; Gahl, A.; Domaing, P.; Birk, U.; Leonhardt, H.; Cremer, C.; Cardoso, M. C.

2010-01-01

DNA replication, similar to other cellular processes, occurs within dynamic macromolecular structures. Any comprehensive understanding ultimately requires quantitative data to establish and test models of genome duplication. We used two different super-resolution light microscopy techniques to directly measure and compare the size and numbers of replication foci in mammalian cells. This analysis showed that replication foci vary in size from 210 nm down to 40 nm. Remarkably, spatially modulated illumination (SMI) and 3D-structured illumination microscopy (3D-SIM) both showed an average size of 125 nm that was conserved throughout S-phase and independent of the labeling method, suggesting a basic unit of genome duplication. Interestingly, the improved optical 3D resolution identified 3- to 5-fold more distinct replication foci than previously reported. These results show that optical nanoscopy techniques enable accurate measurements of cellular structures at a level previously achieved only by electron microscopy and highlight the possibility of high-throughput, multispectral 3D analyses. PMID:19864256

Monitoring Ephemeral Streams Using Airborne Very High Resolution Multispectral Remote Sensing in Arid Environments

NASA Astrophysics Data System (ADS)

Hamada, Y.; O'Connor, B. L.

2012-12-01

Development in arid environments often results in the loss and degradation of the ephemeral streams that provide habitat and critical ecosystem functions such as water delivery, sediment transport, and groundwater recharge. Quantification of these ecosystem functions is challenging because of the episodic nature of runoff events in desert landscapes and the large spatial scale of watersheds that potentially can be impacted by large-scale development. Low-impact development guidelines and regulatory protection of ephemeral streams are often lacking due to the difficulty of accurately mapping and quantifying the critical functions of ephemeral streams at scales larger than individual reaches. Renewable energy development in arid regions has the potential to disturb ephemeral streams at the watershed scale, and it is necessary to develop environmental monitoring applications for ephemeral streams to help inform land management and regulatory actions aimed at protecting and mitigating for impacts related to large-scale land disturbances. This study focuses on developing remote sensing methodologies to identify and monitor impacts on ephemeral streams resulting from the land disturbance associated with utility-scale solar energy development in the desert southwest of the United States. Airborne very high resolution (VHR) multispectral imagery is used to produce stereoscopic, three-dimensional landscape models that can be used to (1) identify and map ephemeral stream channel networks, and (2) support analyses and models of hydrologic and sediment transport processes that pertain to the critical functionality of ephemeral streams. Spectral and statistical analyses are being developed to extract information about ephemeral channel location and extent, micro-topography, riparian vegetation, and soil moisture characteristics. This presentation will demonstrate initial results and provide a framework for future work associated with this project, for developing the necessary field measurements necessary to verify remote sensing landscape models, and for generating hydrologic models and analyses.

An Assessment of Differences in Tree Cover Measurements between Landsat and Lidar-derived Products

NASA Astrophysics Data System (ADS)

Tang, H.; Song, X. P.; Armston, J.; Hancock, S.; Duncanson, L.; Zhao, F. A.; Schaaf, C.; Strahler, A. H.; Huang, C.; Hansen, M.; Goetz, S. J.; Dubayah, R.

2016-12-01

Tree cover is one of the most important canopy structural variables describe interactions between atmosphere and biosphere, and is also linked to the function and quality of ecosystem services. Large-area tree cover measurements are traditionally based on multispectral satellite imagery, and there are several global products available at high to medium spatial resolution (30m-1km). Recent developments in lidar remote sensing, including the upcoming Global Ecosystem Dynamics Investigation (GEDI) lidar, offers an alternative means to map tree cover over broad geographical extents. However, differences in the definition of tree cover and the retrieval method can result in large discrepancies between products derived from multispectral imagery and lidar data, and can potentially impact their further use in ecosystem modelling and above-ground biomass mapping. To separate the effects of cover definition and retrieval method, we first conducted a meta-analysis of several tree cover data sets across different biogeographic regions using three publicly available Landsat-based tree cover products (GLCF, NLCD and GLAD), and two waveform and discrete return airborne lidar products. We found that, whereas Landsat products had low-moderate agreements (up to 40% mean difference) on tree cover estimates particularly at the high end (e.g. >80%), airborne lidar can provide more accurate and consistent measurements (mean difference < 5%) when compared with field data. The differences among Landsat products were mainly due to low measurement accuracy and those among lidar products were caused by different definitions of tree cover (e.g. crown cover vs. fractional cover). We further recommended the use of lidar data as a complement or alternative to ultra-fine resolution images in training/validating Landsat-class images for large-area tree cover mapping.

Use of high resolution satellite images for monitoring of earthquakes and volcano activity.

NASA Astrophysics Data System (ADS)

Arellano-Baeza, Alonso A.

Our studies have shown that the strain energy accumulation deep in the Earth's crust that precedes a strong earthquake can be detected by applying a lineament extraction technique to the high-resolution multispectral satellite images. A lineament is a straight or a somewhat curved feature in a satellite image, which it is possible to detect by a special processing of images based on directional filtering and or Hough transform. We analyzed tens of earthquakes occurred in the Pacific coast of the South America with the Richter scale magnitude ˜4.5, using ASTER/TERRA multispectral satellite images for detection and analysis of changes in the system of lineaments previous to a strong earthquake. All events were located in the regions with small seasonal variations and limited vegetation to facilitate the tracking of features associated with the seismic activity only. It was found that the number and orientation of lineaments changed significantly about one month before an earthquake approximately, and a few months later the system returns to its initial state. This effect increases with the earthquake magnitude. It also was shown that the behavior of lineaments associated to the volcano seismic activity is opposite to that obtained previously for earthquakes. This discrepancy can be explained assuming that in the last case the main reason of earthquakes is compression and accumulation of strength in the Earth's crust due to subduction of tectonic plates, whereas in the first case we deal with the inflation of a volcano edifice due to elevation of pressure and magma intrusion. The results obtained made it possible to include this research as a part of scientific program of Chilean Remote Sensing Satellite mission to be launched in 2010.

Remote Sensing of Atlanta's Urban Sprawl and the Distribution of Land Cover and Surface Temperatures

NASA Technical Reports Server (NTRS)

Laymon, Charles A.; Estes, Maurice G., Jr.; Quattrochi, Dale A.; Arnold, James E. (Technical Monitor)

2001-01-01

Between 1973 and 1992, an average of 20 ha of forest was lost each day to urban expansion of Atlanta, Georgia. Urban surfaces have very different thermal properties than natural surfaces-storing solar energy throughout the day and continuing to release it as sensible heat well after sunset. The resulting heat island effect serves as catalysts for chemical reactions from vehicular exhaust and industrialization leading to a deterioration in air quality. In this study, high spatial resolution multispectral remote sensing data has been used to characterize the type, thermal properties, and distribution of land surface materials throughout the Atlanta metropolitan area. Ten-meter data were acquired with the Advanced Thermal and Land Applications Sensor (ATLAS) on May 11 and 12, 1997. ATLAS is a 15-channel multispectral scanner that incorporates the Landsat TM bands with additional bands in the middle reflective infrared and thermal infrared range. The high spatial resolution permitted discrimination of discrete surface types (e.g., concrete, asphalt), individual structures (e.g., buildings, houses) and their associated thermal characteristics. There is a strong temperature contrast between vegetation and anthropomorphic features. Vegetation has a modal temperature at about 20 C, whereas asphalt shingles, pavement, and buildings have a modal temperature of about 39 C. Broad-leaf vegetation classes are indistinguishable on a thermal basis alone. There is slightly more variability (plus or minus 5 C) among the urban surfaces. Grasses, mixed vegetation and mixed urban surfaces are intermediate in temperature and are characterized by broader temperature distributions with modes of about 29 C. Thermal maps serve as a basis for understanding the distribution of "hotspots", i.e., how landscape features and urban fabric contribute the most heat to the lower atmosphere.

Remote Sensing of Atlanta's Urban Sprawl and the Distribution of Land Cover and Surface Temperature

NASA Technical Reports Server (NTRS)

Laymon, Charles A.; Estes, Maurice G., Jr.; Quattrochi, Dale A.; Goodman, H. Michael (Technical Monitor)

2001-01-01

Between 1973 and 1992, an average of 20 ha of forest was lost each day to urban expansion of Atlanta, Georgia. Urban surfaces have very different thermal properties than natural surfaces-storing solar energy throughout the day and continuing to release it as sensible heat well after sunset. The resulting heat island effect serves as catalysts for chemical reactions from vehicular exhaust and industrialization leading to a deterioration in air quality. In this study, high spatial resolution multispectral remote sensing data has been used to characterize the type, thermal properties, and distribution of land surface materials throughout the Atlanta metropolitan area. Ten-meter data were acquired with the Advanced Thermal and Land Applications Sensor (ATLAS) on May 11 and 12, 1997. ATLAS is a 15-channel multispectral scanner that incorporates the Landsat TM bands with additional bands in the middle reflective infrared and thermal infrared range. The high spatial resolution permitted discrimination of discrete surface types (e.g., concrete, asphalt), individual structures (e.g., buildings, houses) and their associated thermal characteristics. There is a strong temperature contrast between vegetation and anthropomorphic features. Vegetation has a modal temperature at about 20 C, whereas asphalt shingles, pavement, and buildings have a modal temperature of about 39 C. Broad-leaf vegetation classes are indistinguishable on a thermal basis alone. There is slightly more variability (+/-5 C) among the urban surfaces. Grasses, mixed vegetation and mixed urban surfaces are intermediate in temperature and are characterized by broader temperature distributions with modes of about 29 C. Thermal maps serve as a basis for understanding the distribution of "hotspots", i.e., how landscape features and urban fabric contribute the most heat to the lower atmosphere.

SkySat-1: very high-resolution imagery from a small satellite

NASA Astrophysics Data System (ADS)

Murthy, Kiran; Shearn, Michael; Smiley, Byron D.; Chau, Alexandra H.; Levine, Josh; Robinson, M. Dirk

2014-10-01

This paper presents details of the SkySat-1 mission, which is the first microsatellite-class commercial earth- observation system to generate sub-meter resolution panchromatic imagery, in addition to sub-meter resolution 4-band pan-sharpened imagery. SkySat-1 was built and launched for an order of magnitude lower cost than similarly performing missions. The low-cost design enables the deployment of a large imaging constellation that can provide imagery with both high temporal resolution and high spatial resolution. One key enabler of the SkySat-1 mission was simplifying the spacecraft design and instead relying on ground- based image processing to achieve high-performance at the system level. The imaging instrument consists of a custom-designed high-quality optical telescope and commercially-available high frame rate CMOS image sen- sors. While each individually captured raw image frame shows moderate quality, ground-based image processing algorithms improve the raw data by combining data from multiple frames to boost image signal-to-noise ratio (SNR) and decrease the ground sample distance (GSD) in a process Skybox calls "digital TDI". Careful qual-ity assessment and tuning of the spacecraft, payload, and algorithms was necessary to generate high-quality panchromatic, multispectral, and pan-sharpened imagery. Furthermore, the framing sensor configuration en- abled the first commercial High-Definition full-frame rate panchromatic video to be captured from space, with approximately 1 meter ground sample distance. Details of the SkySat-1 imaging instrument and ground-based image processing system are presented, as well as an overview of the work involved with calibrating and validating the system. Examples of raw and processed imagery are shown, and the raw imagery is compared to pre-launch simulated imagery used to tune the image processing algorithms.

Low cost, multiscale and multi-sensor application for flooded area mapping

NASA Astrophysics Data System (ADS)

Giordan, Daniele; Notti, Davide; Villa, Alfredo; Zucca, Francesco; Calò, Fabiana; Pepe, Antonio; Dutto, Furio; Pari, Paolo; Baldo, Marco; Allasia, Paolo

2018-05-01

Flood mapping and estimation of the maximum water depth are essential elements for the first damage evaluation, civil protection intervention planning and detection of areas where remediation is needed. In this work, we present and discuss a methodology for mapping and quantifying flood severity over floodplains. The proposed methodology considers a multiscale and multi-sensor approach using free or low-cost data and sensors. We applied this method to the November 2016 Piedmont (northwestern Italy) flood. We first mapped the flooded areas at the basin scale using free satellite data from low- to medium-high-resolution from both the SAR (Sentinel-1, COSMO-Skymed) and multispectral sensors (MODIS, Sentinel-2). Using very- and ultra-high-resolution images from the low-cost aerial platform and remotely piloted aerial system, we refined the flooded zone and detected the most damaged sector. The presented method considers both urbanised and non-urbanised areas. Nadiral images have several limitations, in particular in urbanised areas, where the use of terrestrial images solved this limitation. Very- and ultra-high-resolution images were processed with structure from motion (SfM) for the realisation of 3-D models. These data, combined with an available digital terrain model, allowed us to obtain maps of the flooded area, maximum high water area and damaged infrastructures.

Low Altitude AVIRIS Data for Mapping Landform Types on West Ship Island, Mississippi

NASA Technical Reports Server (NTRS)

Spruce, Joseph; Otvos, Ervin; Giardino, Marco

2002-01-01

A chain of barrier islands provides protection against hurricanes and severe storms along the south and southeastern shores of the United States. Barrier island landform types can be spectrally similar and as small as a few meters across, making highly detailed maps difficult to produce. To determine whether high-resolution airborne hyperspectral imagery could provide detailed maps of barrier island landform types, we used low-altitude hyperspectral and multispectral imagery to map surface environments of West Ship Island, Mississippi. We employed 3.4-meter AVIRIS hyperspectral imagery acquired in July 1999 and 0.5-meter ADAR multispectral data acquired in November 1997. The data were co-registered to digital ortho aerial imagery, and the AVIRIS data was scaled to ground reflectance using ATREM software. Unsupervised classification of AVIRIS and ADAR data proceeded using ISODATA clustering techniques. The resulting landform maps were field-checked and compared to aerial photography and digital elevation maps. Preliminary analyses indicated that the AVIRIS classification mapped more landform types, while the ADAR-based map enabled smaller patches to be identified. Used together, these maps provided a means to assess landform distributions of West Ship Island before and after Hurricane Gorges. Classification accuracy is being addressed through photo-interpretation and field surveys of sample areas selected with stratified random sampling.

Low Altitude AVIRIS Data for Mapping Landform Types on West Ship Island, Mississippi

NASA Technical Reports Server (NTRS)

Spruce, Joseph; Otvos, Ervin; Giardino, Marco

2003-01-01

A chain of barrier islands provides protection against hurricanes and severe storms along the southern and southeastern shores of the Unites States. Barrier island landform types can be spectrally similar and as small as a few meters across, making highly detailed maps difficult to produce. To determine whether high-resolution airborne hyperspectral imagery could provide detailed maps of barrier island landform types, we used low-altitude hyperspectral and multispectral imagery to map surface environments of West Ship Island, Mississippi. We employed 3.4 meter AVIRIS hyperspectral imagery acquired in July 1999 and 0.5 meter ADAR multispectral data acquired in November 1997. The data were co-registered to digital ortho aerial imagery, and the AVIRIS data was scaled to ground reflectance using ATREM software. Unsupervised classification of AVIRIS and ADAR data proceeded using ISODATA clustering techniques. The resulting landform maps were field-checked and compared to aerial photography and digital elevation maps. Preliminary analyses indicated that the AVIRIS classification mapped more landform types, while the ADAR-based map enabled smaller patches to be identified. Used together, these maps provided a means to assess landform distributions of West Ship Island before and after Hurricane Georges. Classification accuracy is being assessed through photo-interpretation and field surveys of sample areas selected with stratified random sampling.

Experimental Demonstration of Adaptive Infrared Multispectral Imaging using Plasmonic Filter Array

PubMed Central

Jang, Woo-Yong; Ku, Zahyun; Jeon, Jiyeon; Kim, Jun Oh; Lee, Sang Jun; Park, James; Noyola, Michael J.; Urbas, Augustine

2016-01-01

In our previous theoretical study, we performed target detection using a plasmonic sensor array incorporating the data-processing technique termed “algorithmic spectrometry”. We achieved the reconstruction of a target spectrum by extracting intensity at multiple wavelengths with high resolution from the image data obtained from the plasmonic array. The ultimate goal is to develop a full-scale focal plane array with a plasmonic opto-coupler in order to move towards the next generation of versatile infrared cameras. To this end, and as an intermediate step, this paper reports the experimental demonstration of adaptive multispectral imagery using fabricated plasmonic spectral filter arrays and proposed target detection scenarios. Each plasmonic filter was designed using periodic circular holes perforated through a gold layer, and an enhanced target detection strategy was proposed to refine the original spectrometry concept for spatial and spectral computation of the data measured from the plasmonic array. Both the spectrum of blackbody radiation and a metal ring object at multiple wavelengths were successfully reconstructed using the weighted superposition of plasmonic output images as specified in the proposed detection strategy. In addition, plasmonic filter arrays were theoretically tested on a target at extremely high temperature as a challenging scenario for the detection scheme. PMID:27721506

In-vivo morphologic and spectroscopic investigation of Psoriasis

NASA Astrophysics Data System (ADS)

Kapsokalyvas, Dimitrios; Cicchi, Riccardo; Bruscino, Nicola; Alfieri, Domenico; Massi, Daniela; Lotti, Torello; Pavone, Francesco S.

2011-07-01

Psoriasis is an autoimmune disease of the skin characterized by hyperkeratosis, hyperproliferation of the epidermis, inflammatory cell accumulation and increased dilatation of dermal papillary blood vessels. Cases of psoriasis were investigated in vivo with optical means in order to evaluate the potential of in vivo optical biopsy. A Polarization Multispectral Dermoscope was employed for the macroscopic observation. Features such as the 'dotted' blood vessels pattern was observed with high contrast. High resolution image sections of the epidermis and the dermis were produced with a custom made Multiphoton Microscope. Imaging extended from the surface of the lesion down to the papillary dermis, at a depth of 200 μm. In the epidermis, a characteristic morphology of the stratum corneum found only in Psoriasis was revealed. Additionally, the cytoplasmic area of the cells in the stratum spinosum layer was found to be smaller than normal. In the dermis the morphological features were more pronounced, where the elongated dermal papillae dominated the papillary layer. Their length exceeds 100μm, which is a far greater value compared to that of healthy skin. These in vivo observations are consistent with the ex vivo histopathological observations, supporting both the applicability and potentiality of multispectral dermoscopy and multiphoton microscopy in the field of in vivo optical investigation and biopsy of skin.

Selecting a spatial resolution for estimation of per-field green leaf area index

NASA Technical Reports Server (NTRS)

Curran, Paul J.; Williamson, H. Dawn

1988-01-01

For any application of multispectral scanner (MSS) data, a user is faced with a number of choices concerning the characteristics of the data; one of these is their spatial resolution. A pilot study was undertaken to determine the spatial resolution that would be optimal for the per-field estimation of green leaf area index (GLAI) in grassland. By reference to empirically-derived data from three areas of grassland, the suitable spatial resolution was hypothesized to lie in the lower portion of a 2-18 m range. To estimate per-field GLAI, airborne MSS data were collected at spatial resolutions of 2 m, 5 m and 10 m. The highest accuracies of per-field GLAI estimation were achieved using MSS data with spatial resolutions of 2 m and 5 m.

Semantic Segmentation of Convolutional Neural Network for Supervised Classification of Multispectral Remote Sensing

NASA Astrophysics Data System (ADS)

Xue, L.; Liu, C.; Wu, Y.; Li, H.

2018-04-01

Semantic segmentation is a fundamental research in remote sensing image processing. Because of the complex maritime environment, the classification of roads, vegetation, buildings and water from remote Sensing Imagery is a challenging task. Although the neural network has achieved excellent performance in semantic segmentation in the last years, there are a few of works using CNN for ground object segmentation and the results could be further improved. This paper used convolution neural network named U-Net, its structure has a contracting path and an expansive path to get high resolution output. In the network , We added BN layers, which is more conducive to the reverse pass. Moreover, after upsampling convolution , we add dropout layers to prevent overfitting. They are promoted to get more precise segmentation results. To verify this network architecture, we used a Kaggle dataset. Experimental results show that U-Net achieved good performance compared with other architectures, especially in high-resolution remote sensing imagery.

An orbiting multispectral scanner for overland and oceanographic applications.

NASA Technical Reports Server (NTRS)

Peacock, K.; Withrington, R. J.

1971-01-01

Description of the major features of a multispectral scanner designed to perform overland and oceanographic surveys from space. The instrument uses an image plane conical scanner and contains independent spectrometers for land and ocean applications. The overland spectrometer has a spatial resolution of 200 ft and has six spectral bands in the atmospheric windows between 0.5 and 2.4 microns. The oceanographic spectrometer has a spatial resolution of 1200 ft and possesses 24 spectral bands equally spaced and in registration over the wavelength range from 0.4 to 0.8 micron. A thermal band of 600-ft resolution is used with a spectral range from 10.5 to 12.6 microns. The swath width of the scan is 100 nautical miles from an altitude of 500 nautical miles. The system has two modes of operation which are selectable by ground command. The six bands of overland data plus the thermal band data can be transmitted, or the 24 bands of oceanographic data plus data from two of the overland bands and the thermal band can be transmitted. The performance is described by the minimum detectable reflectance difference and the effects of sun angle and target reflectivity variations are discussed. The sensitivity is related to the variation of the ocean reflectivity in the presence of chlorophyll and to typical agricultural targets.

Multispectral medical image fusion in Contourlet domain for computer based diagnosis of Alzheimer's disease.

PubMed

Bhateja, Vikrant; Moin, Aisha; Srivastava, Anuja; Bao, Le Nguyen; Lay-Ekuakille, Aimé; Le, Dac-Nhuong

2016-07-01

Computer based diagnosis of Alzheimer's disease can be performed by dint of the analysis of the functional and structural changes in the brain. Multispectral image fusion deliberates upon fusion of the complementary information while discarding the surplus information to achieve a solitary image which encloses both spatial and spectral details. This paper presents a Non-Sub-sampled Contourlet Transform (NSCT) based multispectral image fusion model for computer-aided diagnosis of Alzheimer's disease. The proposed fusion methodology involves color transformation of the input multispectral image. The multispectral image in YIQ color space is decomposed using NSCT followed by dimensionality reduction using modified Principal Component Analysis algorithm on the low frequency coefficients. Further, the high frequency coefficients are enhanced using non-linear enhancement function. Two different fusion rules are then applied to the low-pass and high-pass sub-bands: Phase congruency is applied to low frequency coefficients and a combination of directive contrast and normalized Shannon entropy is applied to high frequency coefficients. The superiority of the fusion response is depicted by the comparisons made with the other state-of-the-art fusion approaches (in terms of various fusion metrics).

Multispectral medical image fusion in Contourlet domain for computer based diagnosis of Alzheimer’s disease

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bhateja, Vikrant, E-mail: bhateja.vikrant@gmail.com, E-mail: nhuongld@hus.edu.vn; Moin, Aisha; Srivastava, Anuja

Computer based diagnosis of Alzheimer’s disease can be performed by dint of the analysis of the functional and structural changes in the brain. Multispectral image fusion deliberates upon fusion of the complementary information while discarding the surplus information to achieve a solitary image which encloses both spatial and spectral details. This paper presents a Non-Sub-sampled Contourlet Transform (NSCT) based multispectral image fusion model for computer-aided diagnosis of Alzheimer’s disease. The proposed fusion methodology involves color transformation of the input multispectral image. The multispectral image in YIQ color space is decomposed using NSCT followed by dimensionality reduction using modified Principal Componentmore » Analysis algorithm on the low frequency coefficients. Further, the high frequency coefficients are enhanced using non-linear enhancement function. Two different fusion rules are then applied to the low-pass and high-pass sub-bands: Phase congruency is applied to low frequency coefficients and a combination of directive contrast and normalized Shannon entropy is applied to high frequency coefficients. The superiority of the fusion response is depicted by the comparisons made with the other state-of-the-art fusion approaches (in terms of various fusion metrics).« less

Multiscale assessment of landscape structure in heterogeneous forested area

NASA Astrophysics Data System (ADS)

Simoniello, T.; Pignatti, S.; Carone, M. T.; Fusilli, L.; Lanfredi, M.; Coppola, R.; Santini, F.

2010-05-01

The characterization of landscape structure in space or time is fundamental to infer ecological processes (Ingegnoli, 2002). Landscape pattern arrangements strongly influence forest ecological functioning and biodiversity, as an example landscape fragmentation can induce habitat degradation reducing forest species populations or limiting their recolonization. Such arrangements are spatially correlated and scale-dependent, therefore they have distinctive operational-scales at which they can be best characterized (Wu, 2004). In addition, the detail of the land cover classification can have substantial influences on resulting pattern quantification (Greenberg et al.2001). In order to evaluate the influence of the observational scales and labelling details, we investigated a forested area (Pollino National Park; southern Italy) by analyzing the patch arrangement derived from three remote sensing sensors having different spectral and spatial resolutions. In particular, we elaborated data from the hyperspectral MIVIS (102 bands; ~7m) and Hyperion (220 bands; 30m), and the multispectral Landsat-TM (7 bands; 30m). Moreover, to assess the landscape evolution we investigated the hierarchical structure of the study area (landscape, class, patch) by elaborating two Landsat-TM acquired in 1987 and 1998. Preprocessed data were classified by adopting a supervised procedure based on the Minimum Distance classifier. The obtained labelling correspond to Corine level 5 for the high resolution MIVIS data, to Corine level 4 for Hyperion and to an intermediate level 4-3 for TM data. The analysis was performed by taking into account patch density, diversity and evenness at landscape level; mean patch size and interdispersion at class level; patch structure and perimeter regularity at patch level. The three sensors described a landscape with a quite high level of richness and distribution. The high spectral and spatial resolution of MIVIS data provided the highest diversity level (SHDI = 2.05), even if the results obtained for TM were not so different (1.93), Hyperion showed the lowest value (1.79). The obtained evenness index was similar for all the landscapes (~ 0.72). At class level, the interdispersion increases as the spatial and spectral resolution power decrease. Due to the low labelling detail, TM classes represent an aggregation of MIVIS and Hyperion classes; therefore they result larger and more diffused over the territory favouring higher interspersion values in the computation. The investigation of the patch structure highlighted the highest MIVIS capability in describing the patch articulation; Hyperion and TM showed quite similar situation. The historical analysis based on TM imagery showed a fragmentation process for some forested patches (mainly beeches): an increase of structure complexity (higher FRACT) is coupled with a higher patch number and an extension reduction. On the whole, the obtained results showed that the multispectral Landsat-TM images represent a good data source for supporting studies on landscape structure of forested areas and that for analyzing the articulation of particular species the high spectral resolution needs to be coupled with a high spatial resolution, i.e. Hyperion sampling is not adequate for such a purpose.

Field Geology/Processes

NASA Technical Reports Server (NTRS)

Allen, Carlton; Jakes, Petr; Jaumann, Ralf; Marshall, John; Moses, Stewart; Ryder, Graham; Saunders, Stephen; Singer, Robert

1996-01-01

The field geology/process group examined the basic operations of a terrestrial field geologist and the manner in which these operations could be transferred to a planetary lander. Four basic requirements for robotic field geology were determined: geologic content; surface vision; mobility; and manipulation. Geologic content requires a combination of orbital and descent imaging. Surface vision requirements include range, resolution, stereo, and multispectral imaging. The minimum mobility for useful field geology depends on the scale of orbital imagery. Manipulation requirements include exposing unweathered surfaces, screening samples, and bringing samples in contact with analytical instruments. To support these requirements, several advanced capabilities for future development are recommended. Capabilities include near-infrared reflectance spectroscopy, hyper-spectral imaging, multispectral microscopy, artificial intelligence in support of imaging, x ray diffraction, x ray fluorescence, and rock chipping.

Computer classification of remotely sensed multispectral image data by extraction and classification of homogeneous objects

NASA Technical Reports Server (NTRS)

Kettig, R. L.

1975-01-01

A method of classification of digitized multispectral images is developed and experimentally evaluated on actual earth resources data collected by aircraft and satellite. The method is designed to exploit the characteristic dependence between adjacent states of nature that is neglected by the more conventional simple-symmetric decision rule. Thus contextual information is incorporated into the classification scheme. The principle reason for doing this is to improve the accuracy of the classification. For general types of dependence this would generally require more computation per resolution element than the simple-symmetric classifier. But when the dependence occurs in the form of redundance, the elements can be classified collectively, in groups, therby reducing the number of classifications required.

Derivation of high spatial resolution albedo from UAV digital imagery: application over the Greenland Ice Sheet

NASA Astrophysics Data System (ADS)

Ryan, Jonathan C.; Hubbard, Alun; Box, Jason E.; Brough, Stephen; Cameron, Karen; Cook, Joseph M.; Cooper, Matthew; Doyle, Samuel H.; Edwards, Arwyn; Holt, Tom; Irvine-Fynn, Tristram; Jones, Christine; Pitcher, Lincoln H.; Rennermalm, Asa K.; Smith, Laurence C.; Stibal, Marek; Snooke, Neal

2017-05-01

Measurements of albedo are a prerequisite for modelling surface melt across the Earth's cryosphere, yet available satellite products are limited in spatial and/or temporal resolution. Here, we present a practical methodology to obtain centimetre resolution albedo products with accuracies of 5% using consumer-grade digital camera and unmanned aerial vehicle (UAV) technologies. Our method comprises a workflow for processing, correcting and calibrating raw digital images using a white reference target, and upward and downward shortwave radiation measurements from broadband silicon pyranometers. We demonstrate the method with a set of UAV sorties over the western, K-sector of the Greenland Ice Sheet. The resulting albedo product, UAV10A1, covers 280 km2, at a resolution of 20 cm per pixel and has a root-mean-square difference of 3.7% compared to MOD10A1 and 4.9% compared to ground-based broadband pyranometer measurements. By continuously measuring downward solar irradiance, the technique overcomes previous limitations due to variable illumination conditions during and between surveys over glaciated terrain. The current miniaturization of multispectral sensors and incorporation of upward facing radiation sensors on UAV packages means that this technique will likely become increasingly attractive in field studies and used in a wide range of applications for high temporal and spatial resolution surface mapping of debris, dust, cryoconite and bioalbedo and for directly constraining surface energy balance models.

Multispectral Passive Microwave Correlations with an Antecedent Precipitation Index Using the Nimbus 7 SMMR.

DTIC Science & Technology

1984-08-01

M.D. Smallwood , 1981: An evaluation of the spatial resolution of soil moisture information. NASA CR-166724, Goddard Space Flight Center, Greenbelt, MD...Thesis, Dept of Meteor- ology, Univ. of Okla., Norman , 59 pp. Theis, S.W., 1979: Surface soil moisture estimation with the Electri- cally Scanning

Smartphone-based multispectral imaging: system development and potential for mobile skin diagnosis.

PubMed

Kim, Sewoong; Cho, Dongrae; Kim, Jihun; Kim, Manjae; Youn, Sangyeon; Jang, Jae Eun; Je, Minkyu; Lee, Dong Hun; Lee, Boreom; Farkas, Daniel L; Hwang, Jae Youn

2016-12-01

We investigate the potential of mobile smartphone-based multispectral imaging for the quantitative diagnosis and management of skin lesions. Recently, various mobile devices such as a smartphone have emerged as healthcare tools. They have been applied for the early diagnosis of nonmalignant and malignant skin diseases. Particularly, when they are combined with an advanced optical imaging technique such as multispectral imaging and analysis, it would be beneficial for the early diagnosis of such skin diseases and for further quantitative prognosis monitoring after treatment at home. Thus, we demonstrate here the development of a smartphone-based multispectral imaging system with high portability and its potential for mobile skin diagnosis. The results suggest that smartphone-based multispectral imaging and analysis has great potential as a healthcare tool for quantitative mobile skin diagnosis.

Multispectral imaging with vertical silicon nanowires

PubMed Central

Park, Hyunsung; Crozier, Kenneth B.

2013-01-01

Multispectral imaging is a powerful tool that extends the capabilities of the human eye. However, multispectral imaging systems generally are expensive and bulky, and multiple exposures are needed. Here, we report the demonstration of a compact multispectral imaging system that uses vertical silicon nanowires to realize a filter array. Multiple filter functions covering visible to near-infrared (NIR) wavelengths are simultaneously defined in a single lithography step using a single material (silicon). Nanowires are then etched and embedded into polydimethylsiloxane (PDMS), thereby realizing a device with eight filter functions. By attaching it to a monochrome silicon image sensor, we successfully realize an all-silicon multispectral imaging system. We demonstrate visible and NIR imaging. We show that the latter is highly sensitive to vegetation and furthermore enables imaging through objects opaque to the eye. PMID:23955156

Calibration of passive remote observing optical and microwave instrumentation; Proceedings of the Meeting, Orlando, FL, Apr. 3-5, 1991

NASA Technical Reports Server (NTRS)

Guenther, Bruce W. (Editor)

1991-01-01

Various papers on the calibration of passive remote observing optical and microwave instrumentation are presented. Individual topics addressed include: on-board calibration device for a wide field-of-view instrument, calibration for the medium-resolution imaging spectrometer, cryogenic radiometers and intensity-stabilized lasers for EOS radiometric calibrations, radiometric stability of the Shuttle-borne solar backscatter ultraviolet spectrometer, ratioing radiometer for use with a solar diffuser, requirements of a solar diffuser and measurements of some candidate materials, reflectance stability analysis of Spectralon diffuse calibration panels, stray light effects on calibrations using a solar diffuser, radiometric calibration of SPOT 23 HRVs, surface and aerosol models for use in radiative transfer codes. Also addressed are: calibrated intercepts for solar radiometers used in remote sensor calibration, radiometric calibration of an airborne multispectral scanner, in-flight calibration of a helicopter-mounted Daedalus multispectral scanner, technique for improving the calibration of large-area sphere sources, remote colorimetry and its applications, spatial sampling errors for a satellite-borne scanning radiometer, calibration of EOS multispectral imaging sensors and solar irradiance variability.

Laboratory Measurement of Bidirectional Reflectance of Radiometric Tarps

NASA Technical Reports Server (NTRS)

Knowlton, Kelly

2006-01-01

Objectives: a) To determine the magnitude of radiometric tarp BRDF; b) To determine whether an ASD FieldSpec Pro spectroradiometer can be used to perform the experiment. Radiometric tarps with nominal reflectance values of 52%, 35%, and 3.5%, deployed for IKONOS. QuickBird, and OrbView-3 overpasses Ground-based spectroradiometric measurements of tarp and Spectralon@ panel taken during overpass using ASD FieldSpec Pro spectroradiometer, and tarp reflectance calculated. Reflectance data used in atmospheric radiative transfer model (MODTRAN) to predict satellite at-sensor radiance for radiometric calibration. Reflectance data also used to validate atmospheric correction of high-spatial-resolution multispectral image products

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ellis, J.E.; Swift, D.M.; Hart, T.C.

Landsat multi-spectral scanner (MSS) imagery was used to develop a vegetation type-biomass map of the 84,000 Km/sup 2/ Turkana District, Kenya. NOAA satellite advanced very high resolution radiometry (AVHRR) imagery was overlaid on the MSS map to trace the seasonal and annual dynamics of vegetation communities used by Turkana pastoral nomads, 1981-1984. Four regions (sub-sectional territories) were compared with respect to peak herbaceous biomass, woody canopy cover, and seasonal fluxes in total green biomass. Results demonstrated major variations among regions and between wet and dry season ranges within regions. Pastoral land use patterns appear to minimize effects of seasonal vegetationmore » fluxes on livestock herds.« less

Aircraft and satellite thermographic systems for wildfire mapping and assessment

NASA Technical Reports Server (NTRS)

Brass, J. A.; Arvesen, J. C.; Ambrosia, V. G.; Riggan, P. J.; Myers, J. S.

1987-01-01

Two complementary sensors, the DAEDALUS DEI-1260 Multispectral Scanner aboard the NASA U-2 aircraft and the Advanced Very High Resolution Radiometer aboard National Oceanographic and Atmospheric Administration orbiting satellites were tested for their applicability in monitoring and predicting parameters such as fire location, temperature and rate of spread, soil heating and cooling rates, and plume characteristics and dimensions. In addition, the satellite system was tested for its ability to extend the relationships found between fire characteristics and biospheric consequences to regional and global scales. An overall system design is presented, and special requirements are documented for the application of this system for fire research and management.

Earth Observatory Satellite system definition study. Report 5: System design and specifications. Volume 5: Specification for EROS operations control center

NASA Technical Reports Server (NTRS)

1974-01-01

The functional, performance, and design requirements for the Operations Control Center (OCC) of the Earth Observatory Satellite (EOS) system are presented. The OCC controls the operations of the EOS satellite to acquire mission data consisting of: (1) thematic mapper data, (2) multispectral scanner data on EOS-A, or High Resolution Pointable Imager data on EOS-B, and (3) data collection system (DCS) data. The various inputs to the OCC are identified. The functional requirements of the OCC are defined. The specific systems and subsystems of the OCC are described and block diagrams are provided.

Thematic mapper studies of Andean volcanoes

NASA Technical Reports Server (NTRS)

Francis, P. W.

1986-01-01

The primary objective was to identify all the active volcanoes in the Andean region of Bolivia. Morphological features of the Tata Sabaya volcano, Bolivia, were studied with the thematic mapper. Details include marginal levees on lava and pyroclastic flows, and summit crater structure. Valley glacier moraine deposits, not easily identified on the multispectral band scanner, were also unambiguous, and provide useful marker horizons on large volcanic edifices which were built up in preglacial times but which were active subsequently. With such high resolution imagery, it is not only possible to identify potentially active volcanoes, but also to use standard photogeological interpretation to outline the history of individual volcanoes.

Airborne multicamera system for geo-spatial applications

NASA Astrophysics Data System (ADS)

Bachnak, Rafic; Kulkarni, Rahul R.; Lyle, Stacey; Steidley, Carl W.

2003-08-01

Airborne remote sensing has many applications that include vegetation detection, oceanography, marine biology, geographical information systems, and environmental coastal science analysis. Remotely sensed images, for example, can be used to study the aftermath of episodic events such as the hurricanes and floods that occur year round in the coastal bend area of Corpus Christi. This paper describes an Airborne Multi-Spectral Imaging System that uses digital cameras to provide high resolution at very high rates. The software is based on Delphi 5.0 and IC Imaging Control's ActiveX controls. Both time and the GPS coordinates are recorded. Three successful test flights have been conducted so far. The paper present flight test results and discusses the issues being addressed to fully develop the system.

Pan-sharpening algorithm to remove thin cloud via mask dodging and nonsampled shift-invariant shearlet transform

NASA Astrophysics Data System (ADS)

Shi, Cheng; Liu, Fang; Li, Ling-Ling; Hao, Hong-Xia

2014-01-01

The goal of pan-sharpening is to get an image with higher spatial resolution and better spectral information. However, the resolution of the pan-sharpened image is seriously affected by the thin clouds. For a single image, filtering algorithms are widely used to remove clouds. These kinds of methods can remove clouds effectively, but the detail lost in the cloud removal image is also serious. To solve this problem, a pan-sharpening algorithm to remove thin cloud via mask dodging and nonsampled shift-invariant shearlet transform (NSST) is proposed. For the low-resolution multispectral (LR MS) and high-resolution panchromatic images with thin clouds, a mask dodging method is used to remove clouds. For the cloud removal LR MS image, an adaptive principal component analysis transform is proposed to balance the spectral information and spatial resolution in the pan-sharpened image. Since the clouds removal process causes the detail loss problem, a weight matrix is designed to enhance the details of the cloud regions in the pan-sharpening process, but noncloud regions remain unchanged. And the details of the image are obtained by NSST. Experimental results over visible and evaluation metrics demonstrate that the proposed method can keep better spectral information and spatial resolution, especially for the images with thin clouds.