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

Science.gov (United States)

Blonski, Slawomir; Glasser, Gerald; Russell, Jeffrey; Ryan, Robert; Terrie, Greg; Zanoni, Vicki

2003-01-01

Spectral band synthesis is a key step in the process of creating a simulated multispectral image from hyperspectral data. In this step, narrow hyperspectral bands are combined into broader multispectral bands. Such an approach has been used quite often, but to the best of our knowledge accuracy of the band synthesis simulations has not been evaluated thus far. Therefore, the main goal of this paper is to provide validation of the spectral band synthesis algorithm used in the ART software. The next section contains a description of the algorithm and an example of its application. Using spectral responses of AVIRIS, Hyperion, ALI, and ETM+, the following section shows how the synthesized spectral bands compare with actual bands, and it presents an evaluation of the simulation accuracy based on results of MODTRAN modeling. In the final sections of the paper, simulated images are compared with data acquired by actual satellite sensors. First, a Landsat 7 ETM+ image is simulated using an AVIRIS hyperspectral data cube. Then, two datasets collected with the Hyperion instrument from the EO-1 satellite are used to simulate multispectral images from the ALI and ETM+ sensors.

The development of a specialized processor for a space-based multispectral earth imager

Science.gov (United States)

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.

Assessing the accuracy of hyperspectral and multispectral satellite imagery for categorical and quantitative mapping of salinity stress in sugarcane fields

NARCIS (Netherlands)

Hamzeh, Saied; Naseri, Abd Ali; Alavipanah, Seyed Kazem; Bartholomeus, Harm; Herold, Martin

2016-01-01

This study evaluates the feasibility of hyperspectral and multispectral satellite imagery for categorical and quantitative mapping of salinity stress in sugarcane fields located in the southwest of Iran. For this purpose a Hyperion image acquired on September 2, 2010 and a Landsat7 ETM+ image

Fusion of Satellite Multispectral Images Based on Ground-Penetrating Radar (GPR Data for the Investigation of Buried Concealed Archaeological Remains

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Athos Agapiou

2017-06-01

Full Text Available The paper investigates the superficial layers of an archaeological landscape based on the integration of various remote sensing techniques. It is well known in the literature that shallow depths may be rich in archeological remains, which generate different signal responses depending on the applied technique. In this study three main technologies are examined, namely ground-penetrating radar (GPR, ground spectroscopy, and multispectral satellite imagery. The study aims to propose a methodology to enhance optical remote sensing satellite images, intended for archaeological research, based on the integration of ground based and satellite datasets. For this task, a regression model between the ground spectroradiometer and GPR is established which is then projected to a high resolution sub-meter optical image. The overall methodology consists of nine steps. Beyond the acquirement of the in-situ measurements and their calibration (Steps 1–3, various regression models are examined for more than 70 different vegetation indices (Steps 4–5. The specific data analysis indicated that the red-edge position (REP hyperspectral index was the most appropriate for developing a local fusion model between ground spectroscopy data and GPR datasets (Step 6, providing comparable results with the in situ GPR measurements (Step 7. Other vegetation indices, such as the normalized difference vegetation index (NDVI, have also been examined, providing significant correlation between the two datasets (R = 0.50. The model is then projected to a high-resolution image over the area of interest (Step 8. The proposed methodology was evaluated with a series of field data collected from the Vésztő-Mágor Tell in the eastern part of Hungary. The results were compared with in situ magnetic gradiometry measurements, indicating common interpretation results. The results were also compatible with the preliminary archaeological investigations of the area (Step 9. The overall

Mosaic of 10 m gridded multibeam bathymetry and bathymetry derived from multispectral IKONOS satellite imagery of Alamagan Island, Commonwealth of Northern Mariana Islands, USA

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Gridded multibeam bathymetry is integrated with bathymetry derived from multispectral IKONOS satellite data. Gridded (10 m cell size) multibeam bathymetry collected...

Mosaic of 5 m gridded multibeam bathymetry and bathymetry derived from multispectral IKONOS satellite imagery of Alamagan Island, Commonwealth of Northern Mariana Islands, USA

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Gridded multibeam bathymetry is integrated with bathymetry derived from multispectral IKONOS satellite data. Gridded (5 m cell size) multibeam bathymetry collected...

Performance Evaluation of Machine Learning Algorithms for Urban Pattern Recognition from Multi-spectral Satellite Images

Directory of Open Access Journals (Sweden)

Marc Wieland

2014-03-01

Full Text Available In this study, a classification and performance evaluation framework for the recognition of urban patterns in medium (Landsat ETM, TM and MSS and very high resolution (WorldView-2, Quickbird, Ikonos multi-spectral satellite images is presented. The study aims at exploring the potential of machine learning algorithms in the context of an object-based image analysis and to thoroughly test the algorithm’s performance under varying conditions to optimize their usage for urban pattern recognition tasks. Four classification algorithms, Normal Bayes, K Nearest Neighbors, Random Trees and Support Vector Machines, which represent different concepts in machine learning (probabilistic, nearest neighbor, tree-based, function-based, have been selected and implemented on a free and open-source basis. Particular focus is given to assess the generalization ability of machine learning algorithms and the transferability of trained learning machines between different image types and image scenes. Moreover, the influence of the number and choice of training data, the influence of the size and composition of the feature vector and the effect of image segmentation on the classification accuracy is evaluated.

Multispectral thermal imaging

Energy Technology Data Exchange (ETDEWEB)

Weber, P.G.; Bender, S.C.; Borel, C.C.; Clodius, W.B.; Smith, B.W. [Los Alamos National Lab., NM (United States). Space and Remote Sensing Sciences Group; Garrett, A.; Pendergast, M.M. [Westinghouse Savannah River Corp., Aiken, SC (United States). Savannah River Technology Center; Kay, R.R. [Sandia National Lab., Albuquerque, NM (United States). Monitoring Systems and Technology Center

1998-12-01

Many remote sensing applications rely on imaging spectrometry. Here the authors use imaging spectrometry for thermal and multispectral signatures measured from a satellite platform enhanced with a combination of accurate calibrations and on-board data for correcting atmospheric distortions. The approach is supported by physics-based end-to-end modeling and analysis, which permits a cost-effective balance between various hardware and software aspects. The goal is to develop and demonstrate advanced technologies and analysis tools toward meeting the needs of the customer; at the same time, the attributes of this system can address other applications in such areas as environmental change, agriculture, and volcanology.

The fusion of satellite and UAV data: simulation of high spatial resolution band

Science.gov (United States)

Jenerowicz, Agnieszka; Siok, Katarzyna; Woroszkiewicz, Malgorzata; Orych, Agata

2017-10-01

Remote sensing techniques used in the precision agriculture and farming that apply imagery data obtained with sensors mounted on UAV platforms became more popular in the last few years due to the availability of low- cost UAV platforms and low- cost sensors. Data obtained from low altitudes with low- cost sensors can be characterised by high spatial and radiometric resolution but quite low spectral resolution, therefore the application of imagery data obtained with such technology is quite limited and can be used only for the basic land cover classification. To enrich the spectral resolution of imagery data acquired with low- cost sensors from low altitudes, the authors proposed the fusion of RGB data obtained with UAV platform with multispectral satellite imagery. The fusion is based on the pansharpening process, that aims to integrate the spatial details of the high-resolution panchromatic image with the spectral information of lower resolution multispectral or hyperspectral imagery to obtain multispectral or hyperspectral images with high spatial resolution. The key of pansharpening is to properly estimate the missing spatial details of multispectral images while preserving their spectral properties. In the research, the authors presented the fusion of RGB images (with high spatial resolution) obtained with sensors mounted on low- cost UAV platforms and multispectral satellite imagery with satellite sensors, i.e. Landsat 8 OLI. To perform the fusion of UAV data with satellite imagery, the simulation of the panchromatic bands from RGB data based on the spectral channels linear combination, was conducted. Next, for simulated bands and multispectral satellite images, the Gram-Schmidt pansharpening method was applied. As a result of the fusion, the authors obtained several multispectral images with very high spatial resolution and then analysed the spatial and spectral accuracies of processed images.

Fusion of MultiSpectral and Panchromatic Images Based on Morphological Operators.

Science.gov (United States)

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.

Mosaic of gridded multibeam bathymetry, gridded LiDAR bathymetry and bathymetry derived from multispectral IKONOS satellite imagery of Tinian Island, Commonwealth of the Northern Marianas Islands, USA

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Gridded multibeam bathymetry is integrated with gridded LiDAR bathymetry and bathymetry derived from multispectral IKONOS satellite data. Gridded (5 m cell size)...

Multispectral data compression through transform coding and block quantization

Science.gov (United States)

Ready, P. J.; Wintz, P. A.

1972-01-01

Transform coding and block quantization techniques are applied to multispectral aircraft scanner data, and digitized satellite imagery. The multispectral source is defined and an appropriate mathematical model proposed. The Karhunen-Loeve, Fourier, and Hadamard encoders are considered and are compared to the rate distortion function for the equivalent Gaussian source and to the performance of the single sample PCM encoder.

Multispectral image pansharpening based on the contourlet transform

Energy Technology Data Exchange (ETDEWEB)

Amro, Israa; Mateos, Javier, E-mail: iamro@correo.ugr.e, E-mail: jmd@decsai.ugr.e [Departamento de Ciencias de la Computacion e I.A., Universidad de Granada, 18071 Granada (Spain)

2010-02-01

Pansharpening is a technique that fuses the information of a low resolution multispectral image (MS) and a high resolution panchromatic image (PAN), usually remote sensing images, to provide a high resolution multispectral image. In the literature, this task has been addressed from different points of view being one of the most popular the wavelets based algorithms. Recently, the contourlet transform has been proposed. This transform combines the advantages of the wavelets transform with a more efficient directional information representation. In this paper we propose a new pansharpening method based on contourlets, compare with its wavelet counterpart and assess its performance numerically and visually.

Acquisition performance of LAPAN-A3/IPB multispectral imager in real-time mode of operation

Science.gov (United States)

Hakim, P. R.; Permala, R.; Jayani, A. P. S.

2018-05-01

LAPAN-A3/IPB satellite was launched in June 2016 and its multispectral imager has been producing Indonesian coverage images. In order to improve its support for remote sensing application, the imager should produce images with high quality and quantity. To improve the quantity of LAPAN-A3/IPB multispectral image captured, image acquisition could be executed in real-time mode from LAPAN ground station in Bogor when the satellite passes west Indonesia region. This research analyses the performance of LAPAN-A3/IPB multispectral imager acquisition in real-time mode, in terms of image quality and quantity, under assumption of several on-board and ground segment limitations. Results show that with real-time operation mode, LAPAN-A3/IPB multispectral imager could produce twice as much as image coverage compare to recorded mode. However, the images produced in real-time mode will have slightly degraded quality due to image compression process involved. Based on several analyses that have been done in this research, it is recommended to use real-time acquisition mode whenever it possible, unless for some circumstances that strictly not allow any quality degradation of the images produced.

Generating Multispectral VIIRS Imagery in Near Real-Time for Use by the National Weather Service in Alaska

Science.gov (United States)

Broderson, D.; Dierking, C.; Stevens, E.; Heinrichs, T. A.; Cherry, J. E.

2016-12-01

The Geographic Information Network of Alaska (GINA) at the University of Alaska Fairbanks (UAF) uses two direct broadcast antennas to receive data from a number of polar-orbiting weather satellites, including the Suomi National Polar Partnership (S-NPP) satellite. GINA uses data from S-NPP's Visible Infrared Imaging Radiometer Suite (VIIRS) to generate a variety of multispectral imagery products developed with the needs of the National Weather Service operational meteorologist in mind. Multispectral products have two primary advantages over single-channel products. First, they can more clearly highlight some terrain and meteorological features which are less evident in the component single channels. Second, multispectral present the information from several bands through just one image, thereby sparing the meteorologist unnecessary time interrogating the component single bands individually. With 22 channels available from the VIIRS instrument, the number of possible multispectral products is theoretically huge. A small number of products will be emphasized in this presentation, with the products chosen based on their proven utility in the forecasting environment. Multispectral products can be generated upstream of the end user or by the end user at their own workstation. The advantage and disadvantages of both approaches will be outlined. Lastly, the technique of improving the appearance of multispectral imagery by correcting for atmospheric reflectance at the shorter wavelengths will be described.

Quaternion-Based Texture Analysis of Multiband Satellite Images: Application to the Estimation of Aboveground Biomass in the East Region of Cameroon.

Science.gov (United States)

Djiongo Kenfack, Cedrigue Boris; Monga, Olivier; Mpong, Serge Moto; Ndoundam, René

2018-03-01

Within the last decade, several approaches using quaternion numbers to handle and model multiband images in a holistic manner were introduced. The quaternion Fourier transform can be efficiently used to model texture in multidimensional data such as color images. For practical application, multispectral satellite data appear as a primary source for measuring past trends and monitoring changes in forest carbon stocks. In this work, we propose a texture-color descriptor based on the quaternion Fourier transform to extract relevant information from multiband satellite images. We propose a new multiband image texture model extraction, called FOTO++, in order to address biomass estimation issues. The first stage consists in removing noise from the multispectral data while preserving the edges of canopies. Afterward, color texture descriptors are extracted thanks to a discrete form of the quaternion Fourier transform, and finally the support vector regression method is used to deduce biomass estimation from texture indices. Our texture features are modeled using a vector composed with the radial spectrum coming from the amplitude of the quaternion Fourier transform. We conduct several experiments in order to study the sensitivity of our model to acquisition parameters. We also assess its performance both on synthetic images and on real multispectral images of Cameroonian forest. The results show that our model is more robust to acquisition parameters than the classical Fourier Texture Ordination model (FOTO). Our scheme is also more accurate for aboveground biomass estimation. We stress that a similar methodology could be implemented using quaternion wavelets. These results highlight the potential of the quaternion-based approach to study multispectral satellite images.

Preliminary analysis of the forest health state based on multispectral images acquired by Unmanned Aerial Vehicle

Directory of Open Access Journals (Sweden)

Czapski Paweł

2015-09-01

Full Text Available The main purpose of this publication is to present the current progress of the work associated with the use of a lightweight unmanned platforms for various environmental studies. Current development in information technology, electronics and sensors miniaturisation allows mounting multispectral cameras and scanners on unmanned aerial vehicle (UAV that could only be used on board aircraft and satellites. Remote Sensing Division in the Institute of Aviation carries out innovative researches using multisensory platform and lightweight unmanned vehicle to evaluate the health state of forests in Wielkopolska province. In this paper, applicability of multispectral images analysis acquired several times during the growing season from low altitude (up to 800m is presented. We present remote sensing indicators computed by our software and common methods for assessing state of trees health. The correctness of applied methods is verified using analysis of satellite scenes acquired by Landsat 8 OLI instrument (Operational Land Imager.

Ground truth measurements plan for the Multispectral Thermal Imager (MTI) satellite

Energy Technology Data Exchange (ETDEWEB)

Garrett, A.J.

2000-01-03

Sandia National Laboratories (SNL), Los Alamos National Laboratory (LANL), and the Savannah River Technology Center (SRTC) have developed a diverse group of algorithms for processing and analyzing the data that will be collected by the Multispectral Thermal Imager (MTI) after launch late in 1999. Each of these algorithms must be verified by comparison to independent surface and atmospheric measurements. SRTC has selected 13 sites in the continental U.S. for ground truth data collections. These sites include a high altitude cold water target (Crater Lake), cooling lakes and towers in the warm, humid southeastern US, Department of Energy (DOE) climate research sites, the NASA Stennis satellite Validation and Verification (V and V) target array, waste sites at the Savannah River Site, mining sites in the Four Corners area and dry lake beds in the southwestern US. SRTC has established mutually beneficial relationships with the organizations that manage these sites to make use of their operating and research data and to install additional instrumentation needed for MTI algorithm V and V.

Dimension Reduction of Multi-Spectral Satellite Image Time Series to Improve Deforestation Monitoring

Directory of Open Access Journals (Sweden)

Meng Lu

2017-10-01

Full Text Available In recent years, sequential tests for detecting structural changes in time series have been adapted for deforestation monitoring using satellite data. The input time series of such sequential tests is typically a vegetation index (e.g., NDVI, which uses two or three bands and ignores all other bands. Being limited to a vegetation index will not benefit from the richer spectral information provided by newly launched satellites and will bring two bottle-necks for deforestation monitoring. Firstly, it is hard to select a suitable vegetation index a priori. Secondly, a single vegetation index is typically affected by seasonal signals, noise and other natural dynamics, which decrease its power for deforestation detection. A novel multispectral time series change monitoring method that combines dimension reduction methods with a sequential hypothesis test is proposed to address these limitations. For each location, the proposed method automatically chooses a “suitable” index for deforestation monitoring. To demonstrate our approach, we implemented it in two study areas: a dry tropical forest in Bolivia (time series length: 444 with strong seasonality and a moist tropical forest in Brazil (time series length: 225 with almost no seasonality. Our method significantly improves accuracy in the presence of strong seasonality, in particular the temporal lag between disturbance and its detection.

Empirical water depth predictions in Dublin Bay based on satellite EO multispectral imagery and multibeam data using spatially weighted geographical analysis

Science.gov (United States)

Monteys, Xavier; Harris, Paul; Caloca, Silvia

2014-05-01

The coastal shallow water zone can be a challenging and expensive environment within which to acquire bathymetry and other oceanographic data using traditional survey methods. Dangers and limited swath coverage make some of these areas unfeasible to survey using ship borne systems, and turbidity can preclude marine LIDAR. As a result, an extensive part of the coastline worldwide remains completely unmapped. Satellite EO multispectral data, after processing, allows timely, cost efficient and quality controlled information to be used for planning, monitoring, and regulating coastal environments. It has the potential to deliver repetitive derivation of medium resolution bathymetry, coastal water properties and seafloor characteristics in shallow waters. Over the last 30 years satellite passive imaging methods for bathymetry extraction, implementing analytical or empirical methods, have had a limited success predicting water depths. Different wavelengths of the solar light penetrate the water column to varying depths. They can provide acceptable results up to 20 m but become less accurate in deeper waters. The study area is located in the inner part of Dublin Bay, on the East coast of Ireland. The region investigated is a C-shaped inlet covering an area of 10 km long and 5 km wide with water depths ranging from 0 to 10 m. The methodology employed on this research uses a ratio of reflectance from SPOT 5 satellite bands, differing to standard linear transform algorithms. High accuracy water depths were derived using multibeam data. The final empirical model uses spatially weighted geographical tools to retrieve predicted depths. The results of this paper confirm that SPOT satellite scenes are suitable to predict depths using empirical models in very shallow embayments. Spatial regression models show better adjustments in the predictions over non-spatial models. The spatial regression equation used provides realistic results down to 6 m below the water surface, with

Landsat sattelite multi-spectral image classification of land cover and land use changes for GIS-based urbanization analysis in irrigation districts of lower Rio Grande Valley of Texas

Science.gov (United States)

The Lower Rio Grande Valley in the south of Texas is experiencing rapid increase of population to bring up urban growth that continues influencing on the irrigation districts in the region. This study evaluated the Landsat satellite multi-spectral imagery to provide information for GIS-based urbaniz...

Multiscale, multispectral and multitemporal satellite data to identify archaeological remains in the archaeological area of Tiwanaku (Bolivia)

Science.gov (United States)

Masini, Nicola; Lasaponara, Rosa

2015-04-01

The aim of this paper is to investigate the cultural landscape of the archaeological area of Tiwanaku (Bolivia) using multiscale, multispectral and multitemporal satellite data. Geospatial analysis techniques were applied to the satellite data sets in order to enhance and map traces of past human activities and perform a spatial characterization of environmental and cultural patterns. In particular, in the Tiwanaku area, the approach based on local indicators of spatial autocorrelation (LISA) applied to ASTER data allowed us to identify traces of a possible ancient hydrographic network with a clear spatial relation with the well-known moat surrounding the core of the monumental area. The same approach applied to QuickBird data, allowed us to identify numerous traces of archaeological interest, in Mollo Kontu mound, less investigated than the monumental area. Some of these traces were in perfect accordance with the results of independent studies, other were completely unknown. As a whole, the detected features, composing a geometric pattern with roughly North-South orientation, closely match those of the other residential contexts at Tiwanaku. These new insights, captured from multitemporal ASTER and QuickBird data processing, suggested new questions on the ancient landscape and provided important information for planning future field surveys and archaeogeophyical investigations. Reference [1] Lasaponara R., Masini N. 2014. Beyond modern landscape features: New insights in thearchaeological area of Tiwanaku in Bolivia from satellite data. International Journal of Applied Earth Observation and Geoinformation, 26, 464-471, http://dx.doi.org/10.1016/j.jag.2013.09.00. [2] Tapete D., Cigna F., Masini N., Lasaponara R. 2013. Prospection and monitoring of the archaeological heritage of Nasca, Peru, with ENVISAT ASAR, Archaeological Prospection, 20, 133-147, doi: 10.1002/arp.1449. [3] Lasaponara R, N Masini, 2012 Satellite Remote Sensing, A New Tool for Archaeology (Series

Landscape functioning assessment using Landsat multispectral remote sensing data

OpenAIRE

Hesslerová, Petra

2009-01-01

The main aim of the dissertation thesis was to develop method, based on the use of multispectral satellite data and the theory of dissipation, allowing the analysis of landscape functioning. The theoretical basis is Prigogine's theory of dissipation and self-organization of structures in which energy dissipation is seen as the transformation of solar energy to other forms of energy. In this process the essential role play water availability and vegetation, which is able to bind solar radiatio...

Change detection and change monitoring of natural and man-made features in multispectral and hyperspectral satellite imagery

Science.gov (United States)

Moody, Daniela Irina

2018-04-17

An approach for land cover classification, seasonal and yearly change detection and monitoring, and identification of changes in man-made features may use a clustering of sparse approximations (CoSA) on sparse representations in learned dictionaries. A Hebbian learning rule may be used to build multispectral or hyperspectral, multiresolution dictionaries that are adapted to regional satellite image data. Sparse image representations of pixel patches over the learned dictionaries may be used to perform unsupervised k-means clustering into land cover categories. The clustering process behaves as a classifier in detecting real variability. This approach may combine spectral and spatial textural characteristics to detect geologic, vegetative, hydrologic, and man-made features, as well as changes in these features over time.

Preliminary hard and soft bottom seafloor substrate map derived from an supervised classification of bathymetry derived from multispectral World View-2 satellite imagery of Ni'ihau Island, Territory of Main Hawaiian Islands, USA

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Preliminary hard and soft seafloor substrate map derived from a supervised classification from multispectral World View-2 satellite imagery of Ni'ihau Island,...

UTILIZING SAR AND MULTISPECTRAL INTEGRATED DATA FOR EMERGENCY RESPONSE

Directory of Open Access Journals (Sweden)

S. Havivi

2016-06-01

Full Text Available Satellite images are used widely in the risk cycle to understand the exposure, refine hazard maps and quickly provide an assessment after a natural or man-made disaster. Though there are different types of satellite images (e.g. optical, radar these have not been combined for risk assessments. The characteristics of different remote sensing data type may be extremely valuable for monitoring and evaluating the impacts of disaster events, to extract additional information thus making it available for emergency situations. To base this approach, two different change detection methods, for two different sensor's data were used: Coherence Change Detection (CCD for SAR data and Covariance Equalization (CE for multispectral imagery. The CCD provides an identification of the stability of an area, and shows where changes have occurred. CCD shows subtle changes with an accuracy of several millimetres to centimetres. The CE method overcomes the atmospheric effects differences between two multispectral images, taken at different times. Therefore, areas that had undergone a major change can be detected. To achieve our goals, we focused on the urban areas affected by the tsunami event in Sendai, Japan that occurred on March 11, 2011 which affected the surrounding area, coastline and inland. High resolution TerraSAR-X (TSX and Landsat 7 images, covering the research area, were acquired for the period before and after the event. All pre-processed and processed according to each sensor. Both results, of the optical and SAR algorithms, were combined by resampling the spatial resolution of the Multispectral data to the SAR resolution. This was applied by spatial linear interpolation. A score representing the damage level in both products was assigned. The results of both algorithms, high level of damage is shown in the areas closer to the sea and shoreline. Our approach, combining SAR and multispectral images, leads to more reliable information and provides a

Estimation of Mangrove Forest Aboveground Biomass Using Multispectral Bands, Vegetation Indices and Biophysical Variables Derived from Optical Satellite Imageries: Rapideye, Planetscope and SENTINEL-2

Science.gov (United States)

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

Detecting weather radar clutter using satellite-based nowcasting products

DEFF Research Database (Denmark)

Jensen, Thomas B.S.; Gill, Rashpal S.; Overgaard, Søren

2006-01-01

This contribution presents the initial results from experiments with detection of weather radar clutter by information fusion with satellite based nowcasting products. Previous studies using information fusion of weather radar data and first generation Meteosat imagery have shown promising results...... for the detecting and removal of clutter. Naturally, the improved spatio-temporal resolution of the Meteosat Second Generation sensors, coupled with its increased number of spectral bands, is expected to yield even better detection accuracies. Weather radar data from three C-band Doppler weather radars...... Application Facility' of EUMETSAT and is based on multispectral images from the SEVIRI sensor of the Meteosat-8 platform. Of special interest is the 'Precipitating Clouds' product, which uses the spectral information coupled with surface temperatures from Numerical Weather Predictions to assign probabilities...

Observing lowermost tropospheric ozone pollution with a new multispectral synergic approach of IASI infrared and GOME-2 ultraviolet satellite measurements

Science.gov (United States)

Cuesta, Juan; Foret, Gilles; Dufour, Gaëlle; Eremenko, Maxim; Coman, Adriana; Gaubert, Benjamin; Beekmann, Matthias; Liu, Xiong; Cai, Zhaonan; Von Clarmann, Thomas; Spurr, Robert; Flaud, Jean-Marie

2014-05-01

Tropospheric ozone is currently one of the air pollutants posing greatest threats to human health and ecosystems. Monitoring ozone pollution at the regional, continental and global scale is a crucial societal issue. Only spaceborne remote sensing is capable of observing tropospheric ozone at such scales. The spatio-temporal coverage of new satellite-based instruments, such as IASI or GOME-2, offer a great potential for monitoring air quality by synergism with regional chemistry-transport models, for both inter-validation and full data assimilation. However, current spaceborne observations using single-band either UV or IR measurements show limited sensitivity to ozone in the atmospheric boundary layer, which is the major concern for air quality. Very recently, we have developed an innovative multispectral approach, so-called IASI+GOME-2, which combines IASI and GOME-2 observations, respectively in the IR and UV. This unique multispectral approach has allowed the observation of ozone plumes in the lowermost troposphere (LMT, below 3 km of altitude) over Europe, for the first time from space. Our first analyses are focused on typical ozone pollution events during the summer of 2009 over Europe. During these events, LMT ozone plumes at different regions are produced photo-chemically in the boundary layer, transported upwards to the free troposphere and also downwards from the stratosphere. We have analysed them using IASI+GOME-2 observations, in comparison with single-band methods (IASI, GOME-2 and OMI). Only IASI+GOME-2 depicts ozone plumes located below 3 km of altitude (both over land and ocean). Indeed, the multispectral sensitivity in the LMT is greater by 40% and it peaks at 2 to 2.5 km of altitude over land, thus at least 0.8 to 1 km below that for all single-band methods. Over Europe during the summer of 2009, IASI+GOME-2 shows 1% mean bias and 21% precision for direct comparisons with ozonesondes and also good agreement with CHIMERE model simulations

Object-based analysis of multispectral airborne laser scanner data for land cover classification and map updating

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Matikainen, Leena; Karila, Kirsi; Hyyppä, Juha; Litkey, Paula; Puttonen, Eetu; Ahokas, Eero

2017-06-01

During the last 20 years, airborne laser scanning (ALS), often combined with passive multispectral information from aerial images, has shown its high feasibility for automated mapping processes. The main benefits have been achieved in the mapping of elevated objects such as buildings and trees. Recently, the first multispectral airborne laser scanners have been launched, and active multispectral information is for the first time available for 3D ALS point clouds from a single sensor. This article discusses the potential of this new technology in map updating, especially in automated object-based land cover classification and change detection in a suburban area. For our study, Optech Titan multispectral ALS data over a suburban area in Finland were acquired. Results from an object-based random forests analysis suggest that the multispectral ALS data are very useful for land cover classification, considering both elevated classes and ground-level classes. The overall accuracy of the land cover classification results with six classes was 96% compared with validation points. The classes under study included building, tree, asphalt, gravel, rocky area and low vegetation. Compared to classification of single-channel data, the main improvements were achieved for ground-level classes. According to feature importance analyses, multispectral intensity features based on several channels were more useful than those based on one channel. Automatic change detection for buildings and roads was also demonstrated by utilising the new multispectral ALS data in combination with old map vectors. In change detection of buildings, an old digital surface model (DSM) based on single-channel ALS data was also used. Overall, our analyses suggest that the new data have high potential for further increasing the automation level in mapping. Unlike passive aerial imaging commonly used in mapping, the multispectral ALS technology is independent of external illumination conditions, and there are

Korea Earth Observation Satellite Program

Science.gov (United States)

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

Synergistic Exploitation of Hyper- and Multi-Spectral Precursor Sentinel Measurements to Determine Phytoplankton Functional Types (SynSenPFT

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Svetlana N. Losa

2017-07-01

Full Text Available We derive the chlorophyll a concentration (Chla for three main phytoplankton functional types (PFTs – diatoms, coccolithophores and cyanobacteria – by combining satellite multispectral-based information, being of a high spatial and temporal resolution, with retrievals based on high resolution of PFT absorption properties derived from hyperspectral satellite measurements. The multispectral-based PFT Chla retrievals are based on a revised version of the empirical OC-PFT algorithm applied to the Ocean Color Climate Change Initiative (OC-CCI total Chla product. The PhytoDOAS analytical algorithm is used with some modifications to derive PFT Chla from SCIAMACHY hyperspectral measurements. To combine synergistically these two PFT products (OC-PFT and PhytoDOAS, an optimal interpolation is performed for each PFT in every OC-PFT sub-pixel within a PhytoDOAS pixel, given its Chla and its a priori error statistics. The synergistic product (SynSenPFT is presented for the period of August 2002 March 2012 and evaluated against PFT Chla data obtained from in situ marker pigment data and the NASA Ocean Biogeochemical Model simulations and satellite information on phytoplankton size. The most challenging aspects of the SynSenPFT algorithm implementation are discussed. Perspectives on SynSenPFT product improvements and prolongation of the time series over the next decades by adaptation to Sentinel multi- and hyperspectral instruments are highlighted.

A Direct and Fast Methodology for Ship Recognition in Sentinel-2 Multispectral Imagery

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Henning Heiselberg

2016-12-01

Full Text Available The European Space Agency satellite Sentinel-2 provides multispectral images with pixel sizes down to 10 m. This high resolution allows for ship detection and recognition by determining a number of important ship parameters. We are able to show how a ship position, its heading, length and breadth can be determined down to a subpixel resolution. If the ship is moving, its velocity can also be determined from its Kelvin waves. The 13 spectrally different visual and infrared images taken using multispectral imagery (MSI are “fingerprints” that allow for the recognition and identification of ships. Furthermore, the multispectral image profiles along the ship allow for discrimination between the ship, its turbulent wakes, and the Kelvin waves, such that the ship’s length and breadth can be determined more accurately even when sailing. The ship’s parameters are determined by using satellite imagery taken from several ships, which are then compared to known values from the automatic identification system. The agreement is on the order of the pixel resolution or better.

Geometric Calibration and Radiometric Correction of the Maia Multispectral Camera

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Nocerino, E.; Dubbini, M.; Menna, F.; Remondino, F.; Gattelli, M.; Covi, D.

2017-10-01

Multispectral imaging is a widely used remote sensing technique, whose applications range from agriculture to environmental monitoring, from food quality check to cultural heritage diagnostic. A variety of multispectral imaging sensors are available on the market, many of them designed to be mounted on different platform, especially small drones. This work focuses on the geometric and radiometric characterization of a brand-new, lightweight, low-cost multispectral camera, called MAIA. The MAIA camera is equipped with nine sensors, allowing for the acquisition of images in the visible and near infrared parts of the electromagnetic spectrum. Two versions are available, characterised by different set of band-pass filters, inspired by the sensors mounted on the WorlView-2 and Sentinel2 satellites, respectively. The camera details and the developed procedures for the geometric calibrations and radiometric correction are presented in the paper.

Ship-Iceberg Discrimination in Sentinel-2 Multispectral Imagery by Supervised Classification

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Peder Heiselberg

2017-11-01

Full Text Available The European Space Agency Sentinel-2 satellites provide multispectral images with pixel sizes down to 10 m. This high resolution allows for fast and frequent detection, classification and discrimination of various objects in the sea, which is relevant in general and specifically for the vast Arctic environment. We analyze several sets of multispectral image data from Denmark and Greenland fall and winter, and describe a supervised search and classification algorithm based on physical parameters that successfully finds and classifies all objects in the sea with reflectance above a threshold. It discriminates between objects like ships, islands, wakes, and icebergs, ice floes, and clouds with accuracy better than 90%. Pan-sharpening the infrared bands leads to classification and discrimination of ice floes and clouds better than 95%. For complex images with abundant ice floes or clouds, however, the false alarm rate dominates for small non-sailing boats.

LANDSAT 8 MULTISPECTRAL AND PANSHARPENED IMAGERY PROCESSING ON THE STUDY OF CIVIL ENGINEERING ISSUES

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M. A. Lazaridou

2016-06-01

Full Text Available Scientific and professional interests of civil engineering mainly include structures, hydraulics, geotechnical engineering, environment, and transportation issues. Topics included in the context of the above may concern urban environment issues, urban planning, hydrological modelling, study of hazards and road construction. Land cover information contributes significantly on the study of the above subjects. Land cover information can be acquired effectively by visual image interpretation of satellite imagery or after applying enhancement routines and also by imagery classification. The Landsat Data Continuity Mission (LDCM – Landsat 8 is the latest satellite in Landsat series, launched in February 2013. Landsat 8 medium spatial resolution multispectral imagery presents particular interest in extracting land cover, because of the fine spectral resolution, the radiometric quantization of 12bits, the capability of merging the high resolution panchromatic band of 15 meters with multispectral imagery of 30 meters as well as the policy of free data. In this paper, Landsat 8 multispectral and panchromatic imageries are being used, concerning surroundings of a lake in north-western Greece. Land cover information is extracted, using suitable digital image processing software. The rich spectral context of the multispectral image is combined with the high spatial resolution of the panchromatic image, applying image fusion – pansharpening, facilitating in this way visual image interpretation to delineate land cover. Further processing concerns supervised image classification. The classification of pansharpened image preceded multispectral image classification. Corresponding comparative considerations are also presented.

Landsat 8 Multispectral and Pansharpened Imagery Processing on the Study of Civil Engineering Issues

Science.gov (United States)

Lazaridou, M. A.; Karagianni, A. Ch.

2016-06-01

Scientific and professional interests of civil engineering mainly include structures, hydraulics, geotechnical engineering, environment, and transportation issues. Topics included in the context of the above may concern urban environment issues, urban planning, hydrological modelling, study of hazards and road construction. Land cover information contributes significantly on the study of the above subjects. Land cover information can be acquired effectively by visual image interpretation of satellite imagery or after applying enhancement routines and also by imagery classification. The Landsat Data Continuity Mission (LDCM - Landsat 8) is the latest satellite in Landsat series, launched in February 2013. Landsat 8 medium spatial resolution multispectral imagery presents particular interest in extracting land cover, because of the fine spectral resolution, the radiometric quantization of 12bits, the capability of merging the high resolution panchromatic band of 15 meters with multispectral imagery of 30 meters as well as the policy of free data. In this paper, Landsat 8 multispectral and panchromatic imageries are being used, concerning surroundings of a lake in north-western Greece. Land cover information is extracted, using suitable digital image processing software. The rich spectral context of the multispectral image is combined with the high spatial resolution of the panchromatic image, applying image fusion - pansharpening, facilitating in this way visual image interpretation to delineate land cover. Further processing concerns supervised image classification. The classification of pansharpened image preceded multispectral image classification. Corresponding comparative considerations are also presented.

Low SWaP multispectral sensors using dichroic filter arrays

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Dougherty, John; Varghese, Ron

2015-06-01

The benefits of multispectral imaging are well established in a variety of applications including remote sensing, authentication, satellite and aerial surveillance, machine vision, biomedical, and other scientific and industrial uses. However, many of the potential solutions require more compact, robust, and cost-effective cameras to realize these benefits. The next generation of multispectral sensors and cameras needs to deliver improvements in size, weight, power, portability, and spectral band customization to support widespread deployment for a variety of purpose-built aerial, unmanned, and scientific applications. A novel implementation uses micro-patterning of dichroic filters1 into Bayer and custom mosaics, enabling true real-time multispectral imaging with simultaneous multi-band image acquisition. Consistent with color image processing, individual spectral channels are de-mosaiced with each channel providing an image of the field of view. This approach can be implemented across a variety of wavelength ranges and on a variety of detector types including linear, area, silicon, and InGaAs. This dichroic filter array approach can also reduce payloads and increase range for unmanned systems, with the capability to support both handheld and autonomous systems. Recent examples and results of 4 band RGB + NIR dichroic filter arrays in multispectral cameras are discussed. Benefits and tradeoffs of multispectral sensors using dichroic filter arrays are compared with alternative approaches - including their passivity, spectral range, customization options, and scalable production.

Mapping of Agricultural Crops from Single High-Resolution Multispectral Images—Data-Driven Smoothing vs. Parcel-Based Smoothing

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Asli Ozdarici-Ok

2015-05-01

Full Text Available Mapping agricultural crops is an important application of remote sensing. However, in many cases it is based either on hyperspectral imagery or on multitemporal coverage, both of which are difficult to scale up to large-scale deployment at high spatial resolution. In the present paper, we evaluate the possibility of crop classification based on single images from very high-resolution (VHR satellite sensors. The main objective of this work is to expose performance difference between state-of-the-art parcel-based smoothing and purely data-driven conditional random field (CRF smoothing, which is yet unknown. To fulfill this objective, we perform extensive tests with four different classification methods (Support Vector Machines, Random Forest, Gaussian Mixtures, and Maximum Likelihood to compute the pixel-wise data term; and we also test two different definitions of the pairwise smoothness term. We have performed a detailed evaluation on different multispectral VHR images (Ikonos, QuickBird, Kompsat-2. The main finding of this study is that pairwise CRF smoothing comes close to the state-of-the-art parcel-based method that requires parcel boundaries (average difference ≈ 2.5%. Our results indicate that a single multispectral (R, G, B, NIR image is enough to reach satisfactory classification accuracy for six crop classes (corn, pasture, rice, sugar beet, wheat, and tomato in Mediterranean climate. Overall, it appears that crop mapping using only one-shot VHR imagery taken at the right time may be a viable alternative, especially since high-resolution multitemporal or hyperspectral coverage as well as parcel boundaries are in practice often not available.

A multilevel multispectral data set analysis in the visible and infrared wavelength regions. [for land use remote sensing

Science.gov (United States)

Biehl, L. L.; Silva, L. F.

1975-01-01

Skylab multispectral scanner data, digitized Skylab color infrared (IR) photography, digitized Skylab black and white multiband photography, and Earth Resources Technology Satellite (ERTS) multispectral scanner data collected within a 24-hr time period over an area in south-central Indiana near Bloomington on June 9 and 10, 1973, were compared in a machine-aided land use analysis of the area. The overall classification performance results, obtained with nine land use classes, were 87% correct classification using the 'best' 4 channels of the Skylab multispectral scanner, 80% for the channels on the Skylab multispectral scanner which are spectrally comparable to the ERTS multispectral scanner, 88% for the ERTS multispectral scanner, 83% for the digitized color IR photography, and 76% for the digitized black and white multiband photography. The results indicate that the Skylab multispectral scanner may yield even higher classification accuracies when a noise-filtered multispectral scanner data set becomes available in the near future.

Modelling forest canopy height by integrating airborne LiDAR samples with satellite Radar and multispectral imagery

Science.gov (United States)

García, Mariano; Saatchi, Sassan; Ustin, Susan; Balzter, Heiko

2018-04-01

Spatially-explicit information on forest structure is paramount to estimating aboveground carbon stocks for designing sustainable forest management strategies and mitigating greenhouse gas emissions from deforestation and forest degradation. LiDAR measurements provide samples of forest structure that must be integrated with satellite imagery to predict and to map landscape scale variations of forest structure. Here we evaluate the capability of existing satellite synthetic aperture radar (SAR) with multispectral data to estimate forest canopy height over five study sites across two biomes in North America, namely temperate broadleaf and mixed forests and temperate coniferous forests. Pixel size affected the modelling results, with an improvement in model performance as pixel resolution coarsened from 25 m to 100 m. Likewise, the sample size was an important factor in the uncertainty of height prediction using the Support Vector Machine modelling approach. Larger sample size yielded better results but the improvement stabilised when the sample size reached approximately 10% of the study area. We also evaluated the impact of surface moisture (soil and vegetation moisture) on the modelling approach. Whereas the impact of surface moisture had a moderate effect on the proportion of the variance explained by the model (up to 14%), its impact was more evident in the bias of the models with bias reaching values up to 4 m. Averaging the incidence angle corrected radar backscatter coefficient (γ°) reduced the impact of surface moisture on the models and improved their performance at all study sites, with R2 ranging between 0.61 and 0.82, RMSE between 2.02 and 5.64 and bias between 0.02 and -0.06, respectively, at 100 m spatial resolution. An evaluation of the relative importance of the variables in the model performance showed that for the study sites located within the temperate broadleaf and mixed forests biome ALOS-PALSAR HV polarised backscatter was the most important

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

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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.

An improved feature extraction algorithm based on KAZE for multi-spectral image

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Yang, Jianping; Li, Jun

2018-02-01

Multi-spectral image contains abundant spectral information, which is widely used in all fields like resource exploration, meteorological observation and modern military. Image preprocessing, such as image feature extraction and matching, is indispensable while dealing with multi-spectral remote sensing image. Although the feature matching algorithm based on linear scale such as SIFT and SURF performs strong on robustness, the local accuracy cannot be guaranteed. Therefore, this paper proposes an improved KAZE algorithm, which is based on nonlinear scale, to raise the number of feature and to enhance the matching rate by using the adjusted-cosine vector. The experiment result shows that the number of feature and the matching rate of the improved KAZE are remarkably than the original KAZE algorithm.

Multispectral imaging for biometrics

Science.gov (United States)

Rowe, Robert K.; Corcoran, Stephen P.; Nixon, Kristin A.; Ostrom, Robert E.

2005-03-01

Automated identification systems based on fingerprint images are subject to two significant types of error: an incorrect decision about the identity of a person due to a poor quality fingerprint image and incorrectly accepting a fingerprint image generated from an artificial sample or altered finger. This paper discusses the use of multispectral sensing as a means to collect additional information about a finger that significantly augments the information collected using a conventional fingerprint imager based on total internal reflectance. In the context of this paper, "multispectral sensing" is used broadly to denote a collection of images taken under different polarization conditions and illumination configurations, as well as using multiple wavelengths. Background information is provided on conventional fingerprint imaging. A multispectral imager for fingerprint imaging is then described and a means to combine the two imaging systems into a single unit is discussed. Results from an early-stage prototype of such a system are shown.

Multispectral medical image fusion in Contourlet domain for computer based diagnosis of Alzheimer’s disease

International Nuclear Information System (INIS)

Bhateja, Vikrant; Moin, Aisha; Srivastava, Anuja; Bao, Le Nguyen; Lay-Ekuakille, Aimé; Le, Dac-Nhuong

2016-01-01

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

Energy Technology Data Exchange (ETDEWEB)

Bhateja, Vikrant, E-mail: bhateja.vikrant@gmail.com, E-mail: nhuongld@hus.edu.vn; Moin, Aisha; Srivastava, Anuja [Shri Ramswaroop Memorial Group of Professional Colleges (SRMGPC), Lucknow, Uttar Pradesh 226028 (India); Bao, Le Nguyen [Duytan University, Danang 550000 (Viet Nam); Lay-Ekuakille, Aimé [Department of Innovation Engineering, University of Salento, Lecce 73100 (Italy); Le, Dac-Nhuong, E-mail: bhateja.vikrant@gmail.com, E-mail: nhuongld@hus.edu.vn [Duytan University, Danang 550000 (Viet Nam); Haiphong University, Haiphong 180000 (Viet Nam)

2016-07-15

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).

Radiometric Cross-Calibration of GF-4 in Multispectral Bands

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Aixia Yang

2017-03-01

Full Text Available The GaoFen-4 (GF-4, launched at the end of December 2015, is China’s first high-resolution geostationary optical satellite. A panchromatic and multispectral sensor (PMS is onboard the GF-4 satellite. Unfortunately, the GF-4 has no onboard calibration assembly, so on-orbit radiometric calibration is required. Like the charge-coupled device (CCD onboard HuanJing-1 (HJ or the wide field of view sensor (WFV onboard GaoFen-1 (GF-1, GF-4 also has a wide field of view, which provides challenges for cross-calibration with narrow field of view sensors, like the Landsat series. A new technique has been developed and used to calibrate HJ-1/CCD and GF-1/WFV, which is verified viable. The technique has three key steps: (1 calculate the surface using the bi-directional reflectance distribution function (BRDF characterization of a site, taking advantage of its uniform surface material and natural topographic variation using Landsat Enhanced Thematic Mapper Plus (ETM+/Operational Land Imager (OLI imagery and digital elevation model (DEM products; (2 calculate the radiance at the top-of-the atmosphere (TOA with the simulated surface reflectance using the atmosphere radiant transfer model; and (3 fit the calibration coefficients with the TOA radiance and corresponding Digital Number (DN values of the image. This study attempts to demonstrate the technique is also feasible to calibrate GF-4 multispectral bands. After fitting the calibration coefficients using the technique, extensive validation is conducted by cross-validation using the image pairs of GF-4/PMS and Landsat-8/OLI with similar transit times and close view zenith. The validation result indicates a higher accuracy and frequency than that given by the China Centre for Resources Satellite Data and Application (CRESDA using vicarious calibration. The study shows that the new technique is also quite feasible for GF-4 multispectral bands as a routine long-term procedure.

Neural network multispectral satellite images classification of volcanic ash plumes in a cloudy scenario

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Matteo Picchiani

2015-03-01

Full Text Available This work shows the potential use of neural networks in the characterization of eruptive events monitored by satellite, through fast and automatic classification of multispectral images. The algorithm has been developed for the MODIS instrument and can easily be extended to other similar sensors. Six classes have been defined paying particular attention to image regions that represent the different surfaces that could possibly be found under volcanic ash clouds. Complex cloudy scenarios composed by images collected during the Icelandic eruptions of the Eyjafjallajökull (2010 and Grimsvötn (2011 volcanoes have been considered as test cases. A sensitivity analysis on the MODIS TIR and VIS channels has been performed to optimize the algorithm. The neural network has been trained with the first image of the dataset, while the remaining data have been considered as independent validation sets. Finally, the neural network classifier’s results have been compared with maps classified with several interactive procedures performed in a consolidated operational framework. This comparison shows that the automatic methodology proposed achieves a very promising performance, showing an overall accuracy greater than 84%, for the Eyjafjalla - jökull event, and equal to 74% for the Grimsvötn event. 

Operational Satellite-based Surface Oil Analyses (Invited)

Science.gov (United States)

Streett, D.; Warren, C.

2010-12-01

During the Deepwater Horizon spill, NOAA imagery analysts in the Satellite Analysis Branch (SAB) issued more than 300 near-real-time satellite-based oil spill analyses. These analyses were used by the oil spill response community for planning, issuing surface oil trajectories and tasking assets (e.g., oil containment booms, skimmers, overflights). SAB analysts used both Synthetic Aperture Radar (SAR) and high resolution visible/near IR multispectral satellite imagery as well as a variety of ancillary datasets. Satellite imagery used included ENVISAT ASAR (ESA), TerraSAR-X (DLR), Cosmo-Skymed (ASI), ALOS (JAXA), Radarsat (MDA), ENVISAT MERIS (ESA), SPOT (SPOT Image Corp.), Aster (NASA), MODIS (NASA), and AVHRR (NOAA). Ancillary datasets included ocean current information, wind information, location of natural oil seeps and a variety of in situ oil observations. The analyses were available as jpegs, pdfs, shapefiles and through Google, KML files and also available on a variety of websites including Geoplatform and ERMA. From the very first analysis issued just 5 hours after the rig sank through the final analysis issued in August, the complete archive is still publicly available on the NOAA/NESDIS website http://www.ssd.noaa.gov/PS/MPS/deepwater.html SAB personnel also served as the Deepwater Horizon International Disaster Charter Project Manager (at the official request of the USGS). The Project Manager’s primary responsibility was to acquire and oversee the processing and dissemination of satellite data generously donated by numerous private companies and nations in support of the oil spill response including some of the imagery described above. SAB has begun to address a number of goals that will improve our routine oil spill response as well as help assure that we are ready for the next spill of national significance. We hope to (1) secure a steady, abundant and timely stream of suitable satellite imagery even in the absence of large-scale emergencies such as

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

Science.gov (United States)

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

Satellite Earth observation data to identify climate and anthropogenic pressures on Bucharest periurban forests

Energy Technology Data Exchange (ETDEWEB)

Zoran, Maria; Savastru, Roxana; Savastru, Dan [National Institute of R& D for Optoelectronics, MG5 Bucharest-Magurele, 077125 Romania (Romania); Dida, Adrian [University Transylvania of Brasov, Brasov (Romania)

2016-03-25

Satellite Earth observation data in the visible and near-infrared (VNIR) wavelengths represent a useful source of information for forest systems monitoring through derived biogeophysical parameters (vegetation index, leaf area index, canopy cover, fraction of absorbed photosynthetically active radiation, chlorophyll content, net primary production, canopy water stress, etc.). Use of satellite remote sensing data to assess forest spatio-temporal changes due to climatic or anthropogenic stressors is an excellent example of the value of multispectral and multitemporal observations. Fusion technique was applied to time-series multispectral and multitemporal satellite imagery (NOAA AVHRR, MODIS Terra/Aqua, Landsat ETM and IKONOS satellite data) for periurban forest areas Cernica-Branesti, placed in the neighboring of Bucharest town, Romania, over 2002-2014 period.

Satellite Earth observation data to identify climate and anthropogenic pressures on Bucharest periurban forests

International Nuclear Information System (INIS)

Zoran, Maria; Savastru, Roxana; Savastru, Dan; Dida, Adrian

2016-01-01

Satellite Earth observation data in the visible and near-infrared (VNIR) wavelengths represent a useful source of information for forest systems monitoring through derived biogeophysical parameters (vegetation index, leaf area index, canopy cover, fraction of absorbed photosynthetically active radiation, chlorophyll content, net primary production, canopy water stress, etc.). Use of satellite remote sensing data to assess forest spatio-temporal changes due to climatic or anthropogenic stressors is an excellent example of the value of multispectral and multitemporal observations. Fusion technique was applied to time-series multispectral and multitemporal satellite imagery (NOAA AVHRR, MODIS Terra/Aqua, Landsat ETM and IKONOS satellite data) for periurban forest areas Cernica-Branesti, placed in the neighboring of Bucharest town, Romania, over 2002-2014 period.

Enhanced processing of SPOT multispectral satellite imagery for environmental monitoring and modelling

Energy Technology Data Exchange (ETDEWEB)

Clark, B.

2010-07-01

The Taita Hills in southeastern Kenya form the northernmost part of Africa's Eastern Arc Mountains, which have been identified by Conservation International as one of the top ten biodiversity hotspots on Earth. As with many areas of the developing world, over recent decades the Taita Hills have experienced significant population growth leading to associated major changes in land use and land cover (LULC), as well as escalating land degradation, particularly soil erosion. Multi-temporal medium resolution multispectral optical satellite data, such as imagery from the SPOT HRV, HRVIR, and HRG sensors, provides a valuable source of information for environmental monitoring and modelling at a landscape level at local and regional scales. However, utilization of multi-temporal SPOT data in quantitative remote sensing studies requires the removal of atmospheric effects and the derivation of surface reflectance factor (rho{sub s}). Furthermore, for areas of rugged terrain, such as the Taita Hills, topographic correction is necessary to derive comparable (rho{sub s}) throughout a SPOT scene. Reliable monitoring of LULC change over time and modelling of land degradation and human population distribution and abundance are of crucial importance to sustainable development, natural resource management, biodiversity conservation, and understanding and mitigating climate change and its impacts. The main purpose of this thesis was to develop and validate enhanced processing of SPOT satellite imagery for use in environmental monitoring and modelling at a landscape level, in regions of the developing world with limited ancillary data availability. The Taita Hills formed the application study site, whilst the Helsinki metropolitan region was used as a control site for validation and assessment of the applied atmospheric correction techniques, where multiangular (rho{sub s}) field measurements were taken and where horizontal visibility meteorological data concurrent with image

Optimal wavelength band clustering for multispectral iris recognition.

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Gong, Yazhuo; Zhang, David; Shi, Pengfei; Yan, Jingqi

2012-07-01

This work explores the possibility of clustering spectral wavelengths based on the maximum dissimilarity of iris textures. The eventual goal is to determine how many bands of spectral wavelengths will be enough for iris multispectral fusion and to find these bands that will provide higher performance of iris multispectral recognition. A multispectral acquisition system was first designed for imaging the iris at narrow spectral bands in the range of 420 to 940 nm. Next, a set of 60 human iris images that correspond to the right and left eyes of 30 different subjects were acquired for an analysis. Finally, we determined that 3 clusters were enough to represent the 10 feature bands of spectral wavelengths using the agglomerative clustering based on two-dimensional principal component analysis. The experimental results suggest (1) the number, center, and composition of clusters of spectral wavelengths and (2) the higher performance of iris multispectral recognition based on a three wavelengths-bands fusion.

Transition, Training, and Assessment of Multispectral Composite Imagery in Support of the NWS Aviation Forecast Mission

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Fuell, Kevin; Jedlovec, Gary; Leroy, Anita; Schultz, Lori

2015-01-01

The NASA/Short-term Prediction, Research, and Transition (SPoRT) Program works closely with NOAA/NWS weather forecasters to transition unique satellite data and capabilities into operations in order to assist with nowcasting and short-term forecasting issues. Several multispectral composite imagery (i.e. RGB) products were introduced to users in the early 2000s to support hydrometeorology and aviation challenges as well as incident support. These activities lead to SPoRT collaboration with the GOES-R Proving Ground efforts where instruments such as MODIS (Aqua, Terra) and S-NPP/VIIRS imagers began to be used as near-realtime proxies to future capabilities of the Advanced Baseline Imager (ABI). One of the composite imagery products introduced to users was the Night-time Microphysics RGB, originally developed by EUMETSAT. SPoRT worked to transition this imagery to NWS users, provide region-specific training, and assess the impact of the imagery to aviation forecast needs. This presentation discusses the method used to interact with users to address specific aviation forecast challenges, including training activities undertaken to prepare for a product assessment. Users who assessed the multispectral imagery ranged from southern U.S. inland and coastal NWS weather forecast offices (WFOs), to those in the Rocky Mountain Front Range region and West Coast, as well as highlatitude forecasters of Alaska. These user-based assessments were documented and shared with the satellite community to support product developers and the broad users of new generation satellite data.

Hyperspectral and multispectral data fusion based on linear-quadratic nonnegative matrix factorization

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Benhalouche, Fatima Zohra; Karoui, Moussa Sofiane; Deville, Yannick; Ouamri, Abdelaziz

2017-04-01

This paper proposes three multisharpening approaches to enhance the spatial resolution of urban hyperspectral remote sensing images. These approaches, related to linear-quadratic spectral unmixing techniques, use a linear-quadratic nonnegative matrix factorization (NMF) multiplicative algorithm. These methods begin by unmixing the observable high-spectral/low-spatial resolution hyperspectral and high-spatial/low-spectral resolution multispectral images. The obtained high-spectral/high-spatial resolution features are then recombined, according to the linear-quadratic mixing model, to obtain an unobservable multisharpened high-spectral/high-spatial resolution hyperspectral image. In the first designed approach, hyperspectral and multispectral variables are independently optimized, once they have been coherently initialized. These variables are alternately updated in the second designed approach. In the third approach, the considered hyperspectral and multispectral variables are jointly updated. Experiments, using synthetic and real data, are conducted to assess the efficiency, in spatial and spectral domains, of the designed approaches and of linear NMF-based approaches from the literature. Experimental results show that the designed methods globally yield very satisfactory spectral and spatial fidelities for the multisharpened hyperspectral data. They also prove that these methods significantly outperform the used literature approaches.

Water Mapping Using Multispectral Airborne LIDAR Data

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Yan, W. Y.; Shaker, A.; LaRocque, P. E.

2018-04-01

This study investigates the use of the world's first multispectral airborne LiDAR sensor, Optech Titan, manufactured by Teledyne Optech to serve the purpose of automatic land-water classification with a particular focus on near shore region and river environment. Although there exist recent studies utilizing airborne LiDAR data for shoreline detection and water surface mapping, the majority of them only perform experimental testing on clipped data subset or rely on data fusion with aerial/satellite image. In addition, most of the existing approaches require manual intervention or existing tidal/datum data for sample collection of training data. To tackle the drawbacks of previous approaches, we propose and develop an automatic data processing workflow for land-water classification using multispectral airborne LiDAR data. Depending on the nature of the study scene, two methods are proposed for automatic training data selection. The first method utilizes the elevation/intensity histogram fitted with Gaussian mixture model (GMM) to preliminarily split the land and water bodies. The second method mainly relies on the use of a newly developed scan line elevation intensity ratio (SLIER) to estimate the water surface data points. Regardless of the training methods being used, feature spaces can be constructed using the multispectral LiDAR intensity, elevation and other features derived from these parameters. The comprehensive workflow was tested with two datasets collected for different near shore region and river environment, where the overall accuracy yielded better than 96 %.

Assessing and mapping the severity of soil erosion using the 30-m Landsat multispectral satellite data in the former South African homelands of Transkei

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Seutloali, Khoboso E.; Dube, Timothy; Mutanga, Onisimo

2017-08-01

Soil erosion is increasingly recognised as the principal cause of land degradation, loss of agricultural land area and siltation of surrounding water waterbodies. Accurate and up-to-date soil erosion mapping is key in understanding its severity if these negative impacts are to be minimised and affected areas rehabilitated. The aim of this work was to map the severity of soil erosion, based on the 30-m Landsat series multispectral satellite data in the former South African homelands of Transkei between the year 1994 and 2010. Further, the study assessed if the observed soil erosion trends and morphology that existed in this area could be explained by biophysical factors (i.e. slope, stream erosivity, topographic wetness index) retrieved from the 30-m ASTER Digital Elevation Model (DEM). The results of this study indicate that the Transkei region experiences varying erosion levels from moderate to very severe. The large portion of the land area under the former homelands was largely affected by rill erosion with approximately 74% occurring in the year 1984 and 54% in 2010. The results also revealed specific thresholds of soil erosion drivers. These include steeper areas (≥30°), high stream power index greater than 2.0 (stream erosivity), relatively lower vegetation cover (≤15%) and low topographic wetness index (≤5%). The results of this work demonstrate the severity of soil erosion in the Southern African former homelands of Transkei for the year 1984 and 2010. Additionally, this work has demonstrated the significance of the 30-m Landsat multispectral sensor in examining soil erosion occurrence at a regional scale where in-depth field work still remains a challenging task.

Suspended sediment concentration and optical property observations of mixed-turbidity, coastal waters through multispectral ocean color inversion

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Multispectral satellite ocean color data from high-turbidity areas of the coastal ocean contain information about the surface concentrations and optical properties of suspended sediments and colored dissolved organic matter (CDOM). Empirical and semi-analytical inversion algorit...

An Approach for Unsupervised Change Detection in Multitemporal VHR Images Acquired by Different Multispectral Sensors

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Yady Tatiana Solano-Correa

2018-03-01

Full Text Available This paper proposes an approach for the detection of changes in multitemporal Very High Resolution (VHR optical images acquired by different multispectral sensors. The proposed approach, which is inspired by a recent framework developed to support the design of change-detection systems for single-sensor VHR remote sensing images, addresses and integrates in the general approach a strategy to effectively deal with multisensor information, i.e., to perform change detection between VHR images acquired by different multispectral sensors on two dates. This is achieved by the definition of procedures for the homogenization of radiometric, spectral and geometric image properties. These procedures map images into a common feature space where the information acquired by different multispectral sensors becomes comparable across time. Although the approach is general, here we optimize it for the detection of changes in vegetation and urban areas by employing features based on linear transformations (Tasseled Caps and Orthogonal Equations, which are shown to be effective for representing the multisensor information in a homogeneous physical way irrespectively of the considered sensor. Experiments on multitemporal images acquired by different VHR satellite systems (i.e., QuickBird, WorldView-2 and GeoEye-1 confirm the effectiveness of the proposed approach.

A survey of classical methods and new trends in pansharpening of multispectral images

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Katsaggelos Aggelos

2011-01-01

Full Text Available Abstract There exist a number of satellites on different earth observation platforms, which provide multispectral images together with a panchromatic image, that is, an image containing reflectance data representative of a wide range of bands and wavelengths. Pansharpening is a pixel-level fusion technique used to increase the spatial resolution of the multispectral image while simultaneously preserving its spectral information. In this paper, we provide a review of the pan-sharpening methods proposed in the literature giving a clear classification of them and a description of their main characteristics. Finally, we analyze how the quality of the pansharpened images can be assessed both visually and quantitatively and examine the different quality measures proposed for that purpose.

Computational multispectral video imaging [Invited].

Science.gov (United States)

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.

Removal of Optically Thick Clouds from Multi-Spectral Satellite Images Using Multi-Frequency SAR Data

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Robert Eckardt

2013-06-01

Full Text Available This study presents a method for the reconstruction of pixels contaminated by optical thick clouds in multi-spectral Landsat images using multi-frequency SAR data. A number of reconstruction techniques have already been proposed in the scientific literature. However, all of the existing techniques have certain limitations. In order to overcome these limitations, we expose the Closest Spectral Fit (CSF method proposed by Meng et al. to a new, synergistic approach using optical and SAR data. Therefore, the term Closest Feature Vector (CFV is introduced. The technique facilitates an elegant way to avoid radiometric distortions in the course of image reconstruction. Furthermore the cloud cover removal is independent from underlying land cover types and assumptions on seasonality, etc. The methodology is applied to mono-temporal, multi-frequency SAR data from TerraSAR-X (X-Band, ERS (C-Band and ALOS Palsar (L-Band. This represents a way of thinking about Radar data not as foreign, but as additional data source in multi-spectral remote sensing. For the assessment of the image restoration performance, an experimental framework is established and a statistical evaluation protocol is designed. The results show the potential of a synergistic usage of multi-spectral and SAR data to overcome the loss of data due to cloud cover.

TESTING OF LAND COVER CLASSIFICATION FROM MULTISPECTRAL AIRBORNE LASER SCANNING DATA

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K. Bakuła

2016-06-01

Full Text Available Multispectral Airborne Laser Scanning provides a new opportunity for airborne data collection. It provides high-density topographic surveying and is also a useful tool for land cover mapping. Use of a minimum of three intensity images from a multiwavelength laser scanner and 3D information included in the digital surface model has the potential for land cover/use classification and a discussion about the application of this type of data in land cover/use mapping has recently begun. In the test study, three laser reflectance intensity images (orthogonalized point cloud acquired in green, near-infrared and short-wave infrared bands, together with a digital surface model, were used in land cover/use classification where six classes were distinguished: water, sand and gravel, concrete and asphalt, low vegetation, trees and buildings. In the tested methods, different approaches for classification were applied: spectral (based only on laser reflectance intensity images, spectral with elevation data as additional input data, and spectro-textural, using morphological granulometry as a method of texture analysis of both types of data: spectral images and the digital surface model. The method of generating the intensity raster was also tested in the experiment. Reference data were created based on visual interpretation of ALS data and traditional optical aerial and satellite images. The results have shown that multispectral ALS data are unlike typical multispectral optical images, and they have a major potential for land cover/use classification. An overall accuracy of classification over 90% was achieved. The fusion of multi-wavelength laser intensity images and elevation data, with the additional use of textural information derived from granulometric analysis of images, helped to improve the accuracy of classification significantly. The method of interpolation for the intensity raster was not very helpful, and using intensity rasters with both first and

A Dynamic Enhancement With Background Reduction Algorithm: Overview and Application to Satellite-Based Dust Storm Detection

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Miller, Steven D.; Bankert, Richard L.; Solbrig, Jeremy E.; Forsythe, John M.; Noh, Yoo-Jeong; Grasso, Lewis D.

2017-12-01

This paper describes a Dynamic Enhancement Background Reduction Algorithm (DEBRA) applicable to multispectral satellite imaging radiometers. DEBRA uses ancillary information about the clear-sky background to reduce false detections of atmospheric parameters in complex scenes. Applied here to the detection of lofted dust, DEBRA enlists a surface emissivity database coupled with a climatological database of surface temperature to approximate the clear-sky equivalent signal for selected infrared-based multispectral dust detection tests. This background allows for suppression of false alarms caused by land surface features while retaining some ability to detect dust above those problematic surfaces. The algorithm is applicable to both day and nighttime observations and enables weighted combinations of dust detection tests. The results are provided quantitatively, as a detection confidence factor [0, 1], but are also readily visualized as enhanced imagery. Utilizing the DEBRA confidence factor as a scaling factor in false color red/green/blue imagery enables depiction of the targeted parameter in the context of the local meteorology and topography. In this way, the method holds utility to both automated clients and human analysts alike. Examples of DEBRA performance from notable dust storms and comparisons against other detection methods and independent observations are presented.

Object Classification Using Airborne Multispectral LiDAR Data

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PAN Suoyan

2018-02-01

Full Text Available Airborne multispectral LiDAR system,which obtains surface geometry and spectral data of objects,simultaneously,has become a fast effective,large-scale spatial data acquisition method.Multispectral LiDAR data are characteristics of completeness and consistency of spectrum and spatial geometric information.Support vector machine (SVM,a machine learning method,is capable of classifying objects based on small samples.Therefore,by means of SVM,this paper performs land cover classification using multispectral LiDAR data. First,all independent point cloud with different wavelengths are merged into a single point cloud,where each pixel contains the three-wavelength spectral information.Next,the merged point cloud is converted into range and intensity images.Finally,land-cover classification is performed by means of SVM.All experiments were conducted on the Optech Titan multispectral LiDAR data,containing three individual point cloud collected by 532 nm,1024 nm,and 1550 nm laser beams.Experimental results demonstrate that ①compared to traditional single-wavelength LiDAR data,multispectral LiDAR data provide a promising solution to land use and land cover applications;②SVM is a feasible method for land cover classification of multispectral LiDAR data.

Multispectral Palmprint Recognition Using a Quaternion Matrix

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Yafeng Li

2012-04-01

Full Text Available 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%.

Classification of multispectral or hyperspectral satellite imagery using clustering of sparse approximations on sparse representations in learned dictionaries obtained using efficient convolutional sparse coding

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Moody, Daniela; Wohlberg, Brendt

2018-01-02

An approach for land cover classification, seasonal and yearly change detection and monitoring, and identification of changes in man-made features may use a clustering of sparse approximations (CoSA) on sparse representations in learned dictionaries. The learned dictionaries may be derived using efficient convolutional sparse coding to build multispectral or hyperspectral, multiresolution dictionaries that are adapted to regional satellite image data. Sparse image representations of images over the learned dictionaries may be used to perform unsupervised k-means clustering into land cover categories. The clustering process behaves as a classifier in detecting real variability. This approach may combine spectral and spatial textural characteristics to detect geologic, vegetative, hydrologic, and man-made features, as well as changes in these features over time.

Multi-spectral optical scanners for commercial earth observation missions

Science.gov (United States)

Schröter, Karin; Engel, Wolfgang; Berndt, Klaus

2017-11-01

In recent years, a number of commercial Earth observation missions have been initiated with the aim to gather data in the visible and near-infrared wavelength range. Some of these missions aim at medium resolution (5 to 10 m) multi-spectral imaging with the special background of daily revisiting. Typical applications aim at monitoring of farming area for growth control and harvest prediction, irrigation control, or disaster monitoring such as hail damage in farming, or flood survey. In order to arrive at profitable business plans for such missions, it is mandatory to establish the space segment, i.e. the spacecraft with their opto -electronic payloads, at minimum cost while guaranteeing maximum reliability for mission success. As multiple spacecraft are required for daily revisiting, the solutions are typically based on micro-satellites. This paper presents designs for multi-spectral opto-electric scanners for this type of missions. These designs are drive n by minimum mass and power budgets of microsatellites, and the need for minimum cost. As a consequence, it is mandatory to arrive at thermally robust, compact telescope designs. The paper gives a comparison between refractive, catadioptric, and TMA optics. For mirror designs, aluminium and Zerodur mirror technologies are briefly discussed. State-of-the art focal plane designs are presented. The paper also addresses the choice of detector technologies such as CCDs and CMOS Active Pixel Sensors. The electronics of the multi-spectral scanners represent the main design driver regarding power consumption, reliability, and (most often) cost. It can be subdivided into the detector drive electronics, analog and digital data processing chains, the data mass memory unit, formatting and down - linking units, payload control electronics, and local power supply. The paper gives overviews and trade-offs between data compression strategies and electronics solutions, mass memory unit designs, and data formatting approaches

An integrated compact airborne multispectral imaging system using embedded computer

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Zhang, Yuedong; Wang, Li; Zhang, Xuguo

2015-08-01

An integrated compact airborne multispectral imaging system using embedded computer based control system was developed for small aircraft multispectral imaging application. The multispectral imaging system integrates CMOS camera, filter wheel with eight filters, two-axis stabilized platform, miniature POS (position and orientation system) and embedded computer. The embedded computer has excellent universality and expansibility, and has advantages in volume and weight for airborne platform, so it can meet the requirements of control system of the integrated airborne multispectral imaging system. The embedded computer controls the camera parameters setting, filter wheel and stabilized platform working, image and POS data acquisition, and stores the image and data. The airborne multispectral imaging system can connect peripheral device use the ports of the embedded computer, so the system operation and the stored image data management are easy. This airborne multispectral imaging system has advantages of small volume, multi-function, and good expansibility. The imaging experiment results show that this system has potential for multispectral remote sensing in applications such as resource investigation and environmental monitoring.

Multispectral biometrics systems and applications

CERN Document Server

Zhang, David; Gong, Yazhuo

2016-01-01

Describing several new biometric technologies, such as high-resolution fingerprint, finger-knuckle-print, multi-spectral backhand, 3D fingerprint, tongueprint, 3D ear, and multi-spectral iris recognition technologies, this book analyzes a number of efficient feature extraction, matching and fusion algorithms and how potential systems have been developed. Focusing on how to develop new biometric technologies based on the requirements of applications, and how to design efficient algorithms to deliver better performance, the work is based on the author’s research with experimental results under different challenging conditions described in the text. The book offers a valuable resource for researchers, professionals and postgraduate students working in the fields of computer vision, pattern recognition, biometrics, and security applications, amongst others.

Self-training-based spectral image reconstruction for art paintings with multispectral imaging.

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Xu, Peng; Xu, Haisong; Diao, Changyu; Ye, Zhengnan

2017-10-20

A self-training-based spectral reflectance recovery method was developed to accurately reconstruct the spectral images of art paintings with multispectral imaging. By partitioning the multispectral images with the k-means clustering algorithm, the training samples are directly extracted from the art painting itself to restrain the deterioration of spectral estimation caused by the material inconsistency between the training samples and the art painting. Coordinate paper is used to locate the extracted training samples. The spectral reflectances of the extracted training samples are acquired indirectly with a spectroradiometer, and the circle Hough transform is adopted to detect the circle measuring area of the spectroradiometer. Through simulation and a practical experiment, the implementation of the proposed method is explained in detail, and it is verified to have better reflectance recovery performance than that using the commercial target and is comparable to the approach using a painted color target.

Land cover classification of Landsat 8 satellite data based on Fuzzy Logic approach

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Taufik, Afirah; Sakinah Syed Ahmad, Sharifah

2016-06-01

The aim of this paper is to propose a method to classify the land covers of a satellite image based on fuzzy rule-based system approach. The study uses bands in Landsat 8 and other indices, such as Normalized Difference Water Index (NDWI), Normalized difference built-up index (NDBI) and Normalized Difference Vegetation Index (NDVI) as input for the fuzzy inference system. The selected three indices represent our main three classes called water, built- up land, and vegetation. The combination of the original multispectral bands and selected indices provide more information about the image. The parameter selection of fuzzy membership is performed by using a supervised method known as ANFIS (Adaptive neuro fuzzy inference system) training. The fuzzy system is tested for the classification on the land cover image that covers Klang Valley area. The results showed that the fuzzy system approach is effective and can be explored and implemented for other areas of Landsat data.

Multispectral image enhancement processing for microsat-borne imager

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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.

Multispectral Image Feature Points

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Cristhian Aguilera

2012-09-01

Full Text Available This paper presents a novel feature point descriptor for the multispectral image case: Far-Infrared and Visible Spectrum images. It allows matching interest points on images of the same scene but acquired in different spectral bands. Initially, points of interest are detected on both images through a SIFT-like based scale space representation. Then, these points are characterized using an Edge Oriented Histogram (EOH descriptor. Finally, points of interest from multispectral images are matched by finding nearest couples using the information from the descriptor. The provided experimental results and comparisons with similar methods show both the validity of the proposed approach as well as the improvements it offers with respect to the current state-of-the-art.

Simulation-based investigation of the generality of Lyzenga's multispectral bathymetry formula in Case-1 coral reef water

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Manessa, Masita Dwi Mandini; Kanno, Ariyo; Sagawa, Tatsuyuki; Sekine, Masahiko; Nurdin, Nurjannah

2018-01-01

Lyzenga's multispectral bathymetry formula has attracted considerable interest due to its simplicity. However, there has been little discussion of the effect that variation in optical conditions and bottom types-which commonly appears in coral reef environments-has on this formula's results. The present paper evaluates Lyzenga's multispectral bathymetry formula for a variety of optical conditions and bottom types. A noiseless dataset of above-water remote sensing reflectance from WorldView-2 images over Case-1 shallow coral reef water is simulated using a radiative transfer model. The simulation-based assessment shows that Lyzenga's formula performs robustly, with adequate generality and good accuracy, under a range of conditions. As expected, the influence of bottom type on depth estimation accuracy is far greater than the influence of other optical parameters, i.e., chlorophyll-a concentration and solar zenith angle. Further, based on the simulation dataset, Lyzenga's formula estimates depth when the bottom type is unknown almost as accurately as when the bottom type is known. This study provides a better understanding of Lyzenga's multispectral bathymetry formula under various optical conditions and bottom types.

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

Science.gov (United States)

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.

[Multispectral Radiation Algorithm Based on Emissivity Model Constraints for True Temperature Measurement].

Science.gov (United States)

Liang, Mei; Sun, Xiao-gang; Luan, Mei-sheng

2015-10-01

Temperature measurement is one of the important factors for ensuring product quality, reducing production cost and ensuring experiment safety in industrial manufacture and scientific experiment. Radiation thermometry is the main method for non-contact temperature measurement. The second measurement (SM) method is one of the common methods in the multispectral radiation thermometry. However, the SM method cannot be applied to on-line data processing. To solve the problems, a rapid inversion method for multispectral radiation true temperature measurement is proposed and constraint conditions of emissivity model are introduced based on the multispectral brightness temperature model. For non-blackbody, it can be drawn that emissivity is an increasing function in the interval if the brightness temperature is an increasing function or a constant function in a range and emissivity satisfies an inequality of emissivity and wavelength in that interval if the brightness temperature is a decreasing function in a range, according to the relationship of brightness temperatures at different wavelengths. The construction of emissivity assumption values is reduced from multiclass to one class and avoiding the unnecessary emissivity construction with emissivity model constraint conditions on the basis of brightness temperature information. Simulation experiments and comparisons for two different temperature points are carried out based on five measured targets with five representative variation trends of real emissivity. decreasing monotonically, increasing monotonically, first decreasing with wavelength and then increasing, first increasing and then decreasing and fluctuating with wavelength randomly. The simulation results show that compared with the SM method, for the same target under the same initial temperature and emissivity search range, the processing speed of the proposed algorithm is increased by 19.16%-43.45% with the same precision and the same calculation results.

A simple semi-automatic approach for land cover classification from multispectral remote sensing imagery.

Directory of Open Access Journals (Sweden)

Dong Jiang

Full Text Available Land cover data represent a fundamental data source for various types of scientific research. The classification of land cover based on satellite data is a challenging task, and an efficient classification method is needed. In this study, an automatic scheme is proposed for the classification of land use using multispectral remote sensing images based on change detection and a semi-supervised classifier. The satellite image can be automatically classified using only the prior land cover map and existing images; therefore human involvement is reduced to a minimum, ensuring the operability of the method. The method was tested in the Qingpu District of Shanghai, China. Using Environment Satellite 1(HJ-1 images of 2009 with 30 m spatial resolution, the areas were classified into five main types of land cover based on previous land cover data and spectral features. The results agreed on validation of land cover maps well with a Kappa value of 0.79 and statistical area biases in proportion less than 6%. This study proposed a simple semi-automatic approach for land cover classification by using prior maps with satisfied accuracy, which integrated the accuracy of visual interpretation and performance of automatic classification methods. The method can be used for land cover mapping in areas lacking ground reference information or identifying rapid variation of land cover regions (such as rapid urbanization with convenience.

Environmental Testing Philosophy for a Sandia National Laboratories' Small Satellite Project - A Retrospective

Energy Technology Data Exchange (ETDEWEB)

CAP,JEROME S.

2000-08-24

Sandia has recently completed the flight certification test series for the Multi-Spectral Thermal Imaging satellite (MTI), which is a small satellite for which Sandia was the system integrator. A paper was presented at the 16th Aerospace Testing Seminar discussing plans for performing the structural dynamics certification program for that satellite. The testing philosophy was originally based on a combination of system level vibroacoustic tests and component level shock and vibration tests. However, the plans evolved to include computational analyses using both Finite Element Analysis and Statistical Energy Analysis techniques. This paper outlines the final certification process and discuss lessons learned including both things that went well and things that should/could have been done differently.

An automated fog monitoring system for the Indo-Gangetic Plains based on satellite measurements

Science.gov (United States)

Patil, Dinesh; Chourey, Reema; Rizvi, Sarwar; Singh, Manoj; Gautam, Ritesh

2016-05-01

Fog is a meteorological phenomenon that causes reduction in regional visibility and affects air quality, thus leading to various societal and economic implications, especially disrupting air and rail transportation. The persistent and widespread winter fog impacts the entire the Indo-Gangetic Plains (IGP), as frequently observed in satellite imagery. The IGP is a densely populated region in south Asia, inhabiting about 1/6th of the world's population, with a strong upward pollution trend. In this study, we have used multi-spectral radiances and aerosol/cloud retrievals from Terra/Aqua MODIS data for developing an automated web-based fog monitoring system over the IGP. Using our previous and existing methodologies, and ongoing algorithm development for the detection of fog and retrieval of associated microphysical properties (e.g. fog droplet effective radius), we characterize the widespread fog detection during both daytime and nighttime. Specifically, for the night time fog detection, the algorithm employs a satellite-based bi-spectral brightness temperature difference technique between two spectral channels: MODIS band-22 (3.9μm) and band-31 (10.75μm). Further, we are extending our algorithm development to geostationary satellites, for providing continuous monitoring of the spatial-temporal variation of fog. We anticipate that the ongoing and future development of a fog monitoring system would be of assistance to air, rail and vehicular transportation management, as well as for dissemination of fog information to government agencies and general public. The outputs of fog detection algorithm and related aerosol/cloud parameters are operationally disseminated via http://fogsouthasia.com/.

A Novel Perceptual Hash Algorithm for Multispectral Image Authentication

Directory of Open Access Journals (Sweden)

Kaimeng Ding

2018-01-01

Full Text Available The perceptual hash algorithm is a technique to authenticate the integrity of images. While a few scholars have worked on mono-spectral image perceptual hashing, there is limited research on multispectral image perceptual hashing. In this paper, we propose a perceptual hash algorithm for the content authentication of a multispectral remote sensing image based on the synthetic characteristics of each band: firstly, the multispectral remote sensing image is preprocessed with band clustering and grid partition; secondly, the edge feature of the band subsets is extracted by band fusion-based edge feature extraction; thirdly, the perceptual feature of the same region of the band subsets is compressed and normalized to generate the perceptual hash value. The authentication procedure is achieved via the normalized Hamming distance between the perceptual hash value of the recomputed perceptual hash value and the original hash value. The experiments indicated that our proposed algorithm is robust compared to content-preserved operations and it efficiently authenticates the integrity of multispectral remote sensing images.

Mapping bathymetry in an active surf zone with the WorldView2 multispectral satellite

Science.gov (United States)

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.

Satellite-Based Sunshine Duration for Europe

Directory of Open Access Journals (Sweden)

Bodo Ahrens

2013-06-01

Full Text Available In this study, two different methods were applied to derive daily and monthly sunshine duration based on high-resolution satellite products provided by the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT Satellite Application Facility on Climate Monitoring using data from Meteosat Second Generation (MSG SEVIRI (Spinning Enhanced Visible and Infrared Imager. The satellite products were either hourly cloud type or hourly surface incoming direct radiation. The satellite sunshine duration estimates were not found to be significantly different using the native 15-minute temporal resolution of SEVIRI. The satellite-based sunshine duration products give additional spatial information over the European continent compared with equivalent in situ-based products. An evaluation of the satellite sunshine duration by product intercomparison and against station measurements was carried out to determine their accuracy. The satellite data were found to be within ±1 h/day compared to high-quality Baseline Surface Radiation Network or surface synoptic observations (SYNOP station measurements. The satellite-based products differ more over the oceans than over land, mainly because of the treatment of fractional clouds in the cloud type-based sunshine duration product. This paper presents the methods used to derive the satellite sunshine duration products and the performance of the different retrievals. The main benefits and disadvantages compared to station-based products are also discussed.

Optical detection of Prorocentrum donghaiense blooms based on multispectral reflectance

Institute of Scientific and Technical Information of China (English)

TAO Bangyi; PAN Delu; MAO Zhihua; SHEN Yuzhang; ZHU Qiankun; CHEN Jianyu

2013-01-01

Prorocentrum donghaiense is one of the most common red tide causative dinoflagellates in the Changjiang (Yangtze) River Estuary and the adjacent area of the East China Sea. It causes large-scale blooms in late spring and early summer that lead to widespread ecologic and economic damage. A means for distinguish-ing dinoflagellate blooms from diatom (Skeletonema costatum) blooms is desired. On the basis of measure-ments of remote sensing reflectance [Rrs(λ)] and inherent optical parameters, the potential of using a mul-tispectral approach is assessed for discriminating the algal blooms due to P. donghaiense from those due to S. costatum. The behavior of two reflectance ratios [R1 =Rrs(560)/Rrs(532) and R2 =Rrs(708)/Rrs(665)], suggests that differentiation of P. donghaiense blooms from diatom bloom types is possible from the current band setup of ocean color sensors. It is found that there are two reflectance ratio regimes that indicate a bloom is dominated by P. donghaiense: (1) R1 >1.55 and R2 1.75 and R2 ?1.0. Various sensitivity analyses are conducted to investigate the effects of the variation in varying levels of chlorophyll concentration and colored dissolved organic matter (CDOM) as well as changes in the backscattering ratio (bbp/bp) on the efficacy of this multispectral approach. Results indicate that the intensity and inherent op-tical properties of the algal species explain much of the behavior of the two ratios. Although backscattering influences the amplitude of Rrs(λ), especially in the 530 and 560 nm bands, the discrimination between P. donghaiense and diatoms is not significantly affected by the variation of bbp/bp. Since a CDOM(440) in coastal areas of the ECS is typically lower than 1.0 m−1 in most situations, the presence of CDOM does not interfere with this discrimination, even as SCDOM varies from 0.01 to 0.026 nm−1. Despite all of these effects, the dis-crimination of P. donghaiense blooms from diatom blooms based on multispectral

Rare earth-based low-index films for IR and multispectral thin film solutions

Science.gov (United States)

Stolze, Markus; Neff, Joe; Waibel, Friedrich

2017-10-01

Non-thoriated rare-earth fluoride based coating solutions involving DyF3 and YbF3 based films as well as non-wetting fluorohydrocarbon cap layers on such films, have been deposited, analyzed and partly optimized. Intermediate results for DyF3 based films from ion assisted e-gun deposition with O2 and N2 alone and as base for the non-wetting to-player as well as for YbF3 starting material with or without admixtures of CaF2 are discussed for low-loss LWIR and multispectral solutions.

New Spectral Index for Detecting Wheat Yellow Rust Using Sentinel-2 Multispectral Imagery

Directory of Open Access Journals (Sweden)

Qiong Zheng

2018-03-01

Full Text Available Yellow rust is one of the most destructive diseases for winter wheat and has led to a significant decrease in winter wheat quality and yield. Identifying and monitoring yellow rust is of great importance for guiding agricultural production over large areas. Compared with traditional crop disease discrimination methods, remote sensing technology has proven to be a useful tool for accomplishing such a task at large scale. This study explores the potential of the Sentinel-2 Multispectral Instrument (MSI, a newly launched satellite with refined spatial resolution and three red-edge bands, for discriminating between yellow rust infection severities (i.e., healthy, slight, and severe in winter wheat. The corresponding simulative multispectral bands for the Sentinel-2 sensor were calculated by the sensor’s relative spectral response (RSR function based on the in situ hyperspectral data acquired at the canopy level. Three Sentinel-2 spectral bands, including B4 (Red, B5 (Re1, and B7 (Re3, were found to be sensitive bands using the random forest (RF method. A new multispectral index, the Red Edge Disease Stress Index (REDSI, which consists of these sensitive bands, was proposed to detect yellow rust infection at different severity levels. The overall identification accuracy for REDSI was 84.1% and the kappa coefficient was 0.76. Moreover, REDSI performed better than other commonly used disease spectral indexes for yellow rust discrimination at the canopy scale. The optimal threshold method was adopted for mapping yellow rust infection at regional scales based on realistic Sentinel-2 multispectral image data to further assess REDSI’s ability for yellow rust detection. The overall accuracy was 85.2% and kappa coefficient was 0.67, which was found through validation against a set of field survey data. This study suggests that the Sentinel-2 MSI has the potential for yellow rust discrimination, and the newly proposed REDSI has great robustness and

New Spectral Index for Detecting Wheat Yellow Rust Using Sentinel-2 Multispectral Imagery.

Science.gov (United States)

Zheng, Qiong; Huang, Wenjiang; Cui, Ximin; Shi, Yue; Liu, Linyi

2018-03-15

Yellow rust is one of the most destructive diseases for winter wheat and has led to a significant decrease in winter wheat quality and yield. Identifying and monitoring yellow rust is of great importance for guiding agricultural production over large areas. Compared with traditional crop disease discrimination methods, remote sensing technology has proven to be a useful tool for accomplishing such a task at large scale. This study explores the potential of the Sentinel-2 Multispectral Instrument (MSI), a newly launched satellite with refined spatial resolution and three red-edge bands, for discriminating between yellow rust infection severities (i.e., healthy, slight, and severe) in winter wheat. The corresponding simulative multispectral bands for the Sentinel-2 sensor were calculated by the sensor's relative spectral response (RSR) function based on the in situ hyperspectral data acquired at the canopy level. Three Sentinel-2 spectral bands, including B4 (Red), B5 (Re1), and B7 (Re3), were found to be sensitive bands using the random forest (RF) method. A new multispectral index, the Red Edge Disease Stress Index (REDSI), which consists of these sensitive bands, was proposed to detect yellow rust infection at different severity levels. The overall identification accuracy for REDSI was 84.1% and the kappa coefficient was 0.76. Moreover, REDSI performed better than other commonly used disease spectral indexes for yellow rust discrimination at the canopy scale. The optimal threshold method was adopted for mapping yellow rust infection at regional scales based on realistic Sentinel-2 multispectral image data to further assess REDSI's ability for yellow rust detection. The overall accuracy was 85.2% and kappa coefficient was 0.67, which was found through validation against a set of field survey data. This study suggests that the Sentinel-2 MSI has the potential for yellow rust discrimination, and the newly proposed REDSI has great robustness and generalized ability

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

Science.gov (United States)

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

Science.gov (United States)

Davis, Philip A.

2012-01-01

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

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

Science.gov (United States)

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

2013-01-01

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

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

Science.gov (United States)

Davis, Philip A.

2013-01-01

, 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

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

Science.gov (United States)

Davis, Philip A.; Cagney, Laura E.

2013-01-01

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

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

Science.gov (United States)

Davis, Philip A.; Cagney, Laura E.

2013-01-01

, 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

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

Science.gov (United States)

Davis, Philip A.; Cagney, Laura E.

2013-01-01

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

Essential Technology and Application of Jitter Detection and Compensation for High Resolution Satellites

Directory of Open Access Journals (Sweden)

TONG Xiaohua

2017-10-01

Full Text Available Satellite jitter is a common and complex phenomenon for the on-orbit high resolution satellites, which may affect the mapping accuracy and quality of imagery. A framework of jitter detection and compensation integrating data processing of multiple sensors is proposed in this paper. Jitter detection is performed based on multispectral imagery, three-line-array imagery, dense ground control and attitude measurement data, and jitter compensation is conducted both on image and on attitude with the sensor model. The platform jitter of ZY-3 satellite is processed and analyzed using the proposed technology, and the results demonstrate the feasibility and reliability of jitter detection and compensation. The variation law analysis of jitter indicates that the frequencies of jitter of ZY-3 satellite hold in the range between 0.6 and 0.7 Hz, while the amplitudes of jitter of ZY-3 satellite drop from 1 pixel in the early stage to below 0.4 pixels and tend to remain stable in the following stage.

MultiSpec—a tool for multispectral hyperspectral image data analysis

Science.gov (United States)

Biehl, Larry; Landgrebe, David

2002-12-01

MultiSpec is a multispectral image data analysis software application. It is intended to provide a fast, easy-to-use means for analysis of multispectral image data, such as that from the Landsat, SPOT, MODIS or IKONOS series of Earth observational satellites, hyperspectral data such as that from the Airborne Visible-Infrared Imaging Spectrometer (AVIRIS) and EO-1 Hyperion satellite system or the data that will be produced by the next generation of Earth observational sensors. The primary purpose for the system was to make new, otherwise complex analysis tools available to the general Earth science community. It has also found use in displaying and analyzing many other types of non-space related digital imagery, such as medical image data and in K-12 and university level educational activities. MultiSpec has been implemented for both the Apple Macintosh ® and Microsoft Windows ® operating systems (OS). The effort was first begun on the Macintosh OS in 1988. The GLOBE ( http://www.globe.gov) program supported the development of a subset of MultiSpec for the Windows OS in 1995. Since then most (but not all) of the features in the Macintosh OS version have been ported to the Windows OS version. Although copyrighted, MultiSpec with its documentation is distributed without charge. The Macintosh and Windows versions and documentation on its use are available from the World Wide Web at URL: http://dynamo.ecn.purdue.edu/˜biehl/MultiSpec/ MultiSpec is copyrighted (1991-2001) by Purdue Research Foundation, West Lafayette, Indiana 47907.

14 CFR 141.91 - Satellite bases.

Science.gov (United States)

2010-01-01

... 14 Aeronautics and Space 3 2010-01-01 2010-01-01 false Satellite bases. 141.91 Section 141.91... OTHER CERTIFICATED AGENCIES PILOT SCHOOLS Operating Rules § 141.91 Satellite bases. The holder of a... assistant chief instructor is designated for each satellite base, and that assistant chief instructor is...

Earth mapping - aerial or satellite imagery comparative analysis

Science.gov (United States)

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.

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

Science.gov (United States)

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.

Data-intensive multispectral remote sensing of the nighttime Earth for environmental monitoring and emergency response

International Nuclear Information System (INIS)

Zhizhin, M; Poyda, A; Velikhov, V; Novikov, A; Polyakov, A

2016-01-01

All Most of the remote sensing applications rely on the daytime visible and infrared images of the Earth surface. Increase in the number of satellites, their spatial resolution as well as the number of the simultaneously observed spectral bands ensure a steady growth of the data volumes and computational complexity in the remote sensing sciences. Recent advance in the night time remote sensing is related to the enhanced sensitivity of the on-board instruments and to the unique opportunity to observe “pure” emitters in visible infrared spectra without contamination from solar heat and reflected light. A candidate set of the night-time emitters observable from the low-orbiting and geostationary satellites include steady state and temporal changes in the city and traffic electric lights, fishing boats, high-temperature industrial objects such as steel mills, oil cracking refineries and power plants, forest and agricultural fires, gas flares, volcanic eruptions and similar catastrophic events. Current satellite instruments can detect at night 10 times more of such objects compared to daytime. We will present a new data-intensive workflow of the night time remote sensing algorithms for map-reduce processing of visible and infrared images from the multispectral radiometers flown by the modern NOAA/NASA Suomi NPP and the USGS Landsat 8 satellites. Similar radiometers are installed on the new generation of the US geostationary GOES-R satellite to be launched in 2016. The new set of algorithms allows us to detect with confidence and track the abrupt changes and long-term trends in the energy of city lights, number of fishing boats, as well as the size, geometry, temperature of gas flares and to estimate monthly and early flared gas volumes by site or by country. For real-time analysis of the night time multispectral satellite images with global coverage we need gigabit network, petabyte data storage and parallel compute cluster with more than 20 nodes. To meet the

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

Science.gov (United States)

Davis, Philip A.

2014-01-01

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

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

Science.gov (United States)

Davis, Philip A.; Cagney, Laura E.

2013-01-01

, 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

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

Science.gov (United States)

Davis, Philip A.

2014-01-01

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

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

Science.gov (United States)

Davis, Philip A.; Cagney, Laura E.

2012-01-01

, 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

Lossless compression of multispectral images using spectral information

Science.gov (United States)

Ma, Long; Shi, Zelin; Tang, Xusheng

2009-10-01

Multispectral images are available for different purposes due to developments in spectral imaging systems. The sizes of multispectral images are enormous. Thus transmission and storage of these volumes of data require huge time and memory resources. That is why compression algorithms must be developed. A salient property of multispectral images is that strong spectral correlation exists throughout almost all bands. This fact is successfully used to predict each band based on the previous bands. We propose to use spectral linear prediction and entropy coding with context modeling for encoding multispectral images. Linear prediction predicts the value for the next sample and computes the difference between predicted value and the original value. This difference is usually small, so it can be encoded with less its than the original value. The technique implies prediction of each image band by involving number of bands along the image spectra. Each pixel is predicted using information provided by pixels in the previous bands in the same spatial position. As done in the JPEG-LS, the proposed coder also represents the mapped residuals by using an adaptive Golomb-Rice code with context modeling. This residual coding is context adaptive, where the context used for the current sample is identified by a context quantization function of the three gradients. Then, context-dependent Golomb-Rice code and bias parameters are estimated sample by sample. The proposed scheme was compared with three algorithms applied to the lossless compression of multispectral images, namely JPEG-LS, Rice coding, and JPEG2000. Simulation tests performed on AVIRIS images have demonstrated that the proposed compression scheme is suitable for multispectral images.

Evaluation of short-period rainfall estimates from Kalpana-1 satellite

Indian Academy of Sciences (India)

The INSAT Multispectral Rainfall Algorithm (IMSRA) technique for rainfall estimation, has recently been developed to meet the shortcomings of the Global Precipitation Index (GPI) technique of rainfall estimation from the data of geostationary satellites; especially for accurate short period rainfall estimates. This study ...

Use of satellite ocean color observations to refine understanding of global geochemical cycles

Science.gov (United States)

Walsh, J. J.; Dieterle, D. A.

1985-01-01

In October 1978, the first satellite-borne color sensor, the Coastal Zone Color Scanner (CZCS), was launched aboard Nimbus-7 with four visible and two infrared bands, permitting a sensitivity about 60 times that of the Landsat-1 multispectral scanner. The CZCS radiance data can be utilized to estimate ocean chlorophyll concentrations by detecting shifts in sea color, particularly in oceanic waters. The obtained data can be used in studies regarding problems of overfishing, and, in addition, in investigations concerning the consequences of man's accelerated extraction of nitrogen from the atmosphere and addition of carbon to the atmosphere. The satellite data base is considered along with a simulation analysis, and ships providing ground-truth chlorophyll measurements in the ocean.

Regression modeling and mapping of coniferous forest basal area and tree density from discrete-return lidar and multispectral data

Science.gov (United States)

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

2006-01-01

We compared the utility of discrete-return light detection and ranging (lidar) data and multispectral satellite imagery, and their integration, for modeling and mapping basal area and tree density across two diverse coniferous forest landscapes in north-central Idaho. We applied multiple linear regression models subset from a suite of 26 predictor variables derived...

CLASSIFICATION BY USING MULTISPECTRAL POINT CLOUD DATA

Directory of Open Access Journals (Sweden)

C. T. Liao

2012-07-01

Full Text Available 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.

Classification by Using Multispectral Point Cloud Data

Science.gov (United States)

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.

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

Science.gov (United States)

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

2013-01-01

. 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

Multitemporal satellite change detection investigations for documentation and valorization of cultural landscape

Science.gov (United States)

Lasaponara, R.; Masini, n.

2012-04-01

archaeological prospection. Int J Remote Sens 27: 3607-3614. Lasaponara R, Masini N (2006b) Identification of archaeological buried remains based on Normalized Difference Vegetation Index (NDVI) from Quickbird satellite data. IEEE Geosci Remote S 3(3): 325-328. Lasaponara R, Masini N (2007a) Detection of archaeological crop marks by using satellite QuickBird multispectral imagery. J Archaeol Sci 34: 214-21. Lasaponara R, Masini N (2007b) Improving satellite Quickbird - based identification of landscape archaeological features trough tasselled cup transformation and PCA. 21st CIPA Symposium, Atene, 1-6 giugno 2007. Lasaponara R, Masini N (2010) Facing the archaeological looting in Peru by local spatial autocorrelation statistics of Very high resolution satellite imagery. In: Taniar D et al (Eds), Proceedings of ICSSA, The 2010 International Conference on Computational Science and its Application (Fukuoka-Japan, March 23 - 26, 2010), Springer, Berlin, 261-269. Lasaponara R, Masini N (2011) Satellite Remote Sensing in Archaeology : past, present and future. J Archaeol Sc 38: 1995-2002. Lasaponara R, Masini N, Rizzo E, Orefici G (2011) New discoveries in the Piramide Naranjada in Cahuachi (Peru) using satellite, Ground Probing Radar and magnetic investigations. J Archaeol Sci 38: 2031-2039. Lasaponara R, Masini N, Scardozzi G (2008) Satellite based archaeological research in ancient territory of Hierapolis. 1st International EARSeL Workshop. Advances in Remote Sensing for Archaeology and Cultural Heritage Management", CNR, Rome, September 30-October 4, Aracne, Rome, pp.11-16. Lillesand T M, Kiefer R W (2000) Remote Sensing and Image interpretation. John Wiley and Sons, New York. Masini N, Lasaponara R (2006) Satellite-based recognition of landscape archaeological features related to ancient human transformation. J Geophys Eng 3: 230-235, doi:10.1088/1742-2132/3/3/004. Masini N, Lasaponara R (2007) Investigating the spectral capability of QuickBird data to detect archaeological

Satellite Map of Port-au-Prince, Haiti-2010-Infrared

Science.gov (United States)

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.

Application of support vector machine for classification of multispectral data

International Nuclear Information System (INIS)

Bahari, Nurul Iman Saiful; Ahmad, Asmala; Aboobaider, Burhanuddin Mohd

2014-01-01

In this paper, support vector machine (SVM) is used to classify satellite remotely sensed multispectral data. The data are recorded from a Landsat-5 TM satellite with resolution of 30x30m. SVM finds the optimal separating hyperplane between classes by focusing on the training cases. The study area of Klang Valley has more than 10 land covers and classification using SVM has been done successfully without any pixel being unclassified. The training area is determined carefully by visual interpretation and with the aid of the reference map of the study area. The result obtained is then analysed for the accuracy and visual performance. Accuracy assessment is done by determination and discussion of Kappa coefficient value, overall and producer accuracy for each class (in pixels and percentage). While, visual analysis is done by comparing the classification data with the reference map. Overall the study shows that SVM is able to classify the land covers within the study area with a high accuracy

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

Science.gov (United States)

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

2013-01-01

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

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

Science.gov (United States)

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

2013-01-01

. 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

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

Science.gov (United States)

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

2012-01-01

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

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

Science.gov (United States)

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

2012-01-01

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

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

Science.gov (United States)

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

2013-01-01

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

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

Science.gov (United States)

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

2012-01-01

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

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

Science.gov (United States)

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

2012-01-01

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

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

Science.gov (United States)

Davis, Philip A.; Davis, Philip A.

2013-01-01

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

Multispectral recordings and analysis of psoriasis lesions

DEFF Research Database (Denmark)

Clemmensen, Line Katrine Harder; Ersbøll, Bjarne Kjær

2006-01-01

An objective method to evaluate the severeness of psoriasis lesions is proposed. In order to obtain objectivity multi-spectral imaging is used. The multi-spectral images give rise to a large p, small n problem which is solved by use of elastic net model selection. The method is promising for furt......An objective method to evaluate the severeness of psoriasis lesions is proposed. In order to obtain objectivity multi-spectral imaging is used. The multi-spectral images give rise to a large p, small n problem which is solved by use of elastic net model selection. The method is promising...

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

Science.gov (United States)

Davis, Philip A.

2013-01-01

, 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

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

Science.gov (United States)

Davis, Philip A.

2013-01-01

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

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

Science.gov (United States)

Davis, Philip A.

2014-01-01

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

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

Science.gov (United States)

Davis, Philip A.; Cagney, Laura E.

2012-01-01

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

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

Science.gov (United States)

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

2012-01-01

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

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

Science.gov (United States)

Davis, Philip A.; Cagney, Laura E.

2013-01-01

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

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

Science.gov (United States)

Davis, Philip A.; Cagney, Laura E.

2012-01-01

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

Multispectral imaging based on a Smartphone with an external C-MOS camera for detection of seborrheic dermatitis on the scalp

Science.gov (United States)

Kim, Manjae; Kim, Sewoong; Hwang, Minjoo; Kim, Jihun; Je, Minkyu; Jang, Jae Eun; Lee, Dong Hun; Hwang, Jae Youn

2017-02-01

To date, the incident rates of various skin diseases have increased due to hereditary and environmental factors including stress, irregular diet, pollution, etc. Among these skin diseases, seborrheic dermatitis and psoriasis are a chronic/relapsing dermatitis involving infection and temporary alopecia. However, they typically exhibit similar symptoms, thus resulting in difficulty in discrimination between them. To prevent their associated complications and appropriate treatments for them, it is crucial to discriminate between seborrheic dermatitis and psoriasis with high specificity and sensitivity and further continuously/quantitatively to monitor the skin lesions during their treatment at other locations besides a hospital. Thus, we here demonstrate a mobile multispectral imaging system connected to a smartphone for selfdiagnosis of seborrheic dermatitis and further discrimination between seborrheic dermatitis and psoriasis on the scalp, which is the more challenging case. Using the system developed, multispectral imaging and analysis of seborrheic dermatitis and psoriasis on the scalp was carried out. It was here found that the spectral signatures of seborrheic dermatitis and psoriasis were discernable and thus seborrheic dermatitis on the scalp could be distinguished from psoriasis by using the system. In particular, the smartphone-based multispectral imaging and analysis moreover offered better discrimination between seborrheic dermatitis and psoriasis than the RGB imaging and analysis. These results suggested that the multispectral imaging system based on a smartphone has the potential for self-diagnosis of seborrheic dermatitis with high portability and specificity.

The role of multispectral scanners as data sources for EPA hydrologic models

Science.gov (United States)

Slack, R.; Hill, D.

1982-01-01

An estimated cost savings of 30% to 50% was realized from using LANDSAT-derived data as input into a program which simulates hydrologic and water quality processes in natural and man-made water systems. Data from the satellite were used in conjunction with EPA's 11-channel multispectral scanner to obtain maps for characterizing the distribution of turbidity plumes in Flathead Lake and to predict the effect of increasing urbanization in Montana's Flathead River Basin on the lake's trophic state. Multispectral data are also being studied as a possible source of the parameters needed to model the buffering capability of lakes in an effort to evaluate the effect of acid rain in the Adirondacks. Water quality in Lake Champlain, Vermont is being classified using data from the LANDSAT and the EPA MSS. Both contact-sensed and MSS data are being used with multivariate statistical analysis to classify the trophic status of 145 lakes in Illinois and to identify water sampling sites in Appalachicola Bay where contaminants threaten Florida's shellfish.

Satellite-based remote sensing of running water habitats at large riverscape scales: Tools to analyze habitat heterogeneity for river ecosystem management

Science.gov (United States)

Hugue, F.; Lapointe, M.; Eaton, B. C.; Lepoutre, A.

2016-01-01

We illustrate an approach to quantify patterns in hydraulic habitat composition and local heterogeneity applicable at low cost over very large river extents, with selectable reach window scales. Ongoing developments in remote sensing and geographical information science massively improve efficiencies in analyzing earth surface features. With the development of new satellite sensors and drone platforms and with the lowered cost of high resolution multispectral imagery, fluvial geomorphology is experiencing a revolution in mapping streams at high resolution. Exploiting the power of aerial or satellite imagery is particularly useful in a riverscape research framework (Fausch et al., 2002), where high resolution sampling of fluvial features and very large coverage extents are needed. This study presents a satellite remote sensing method that requires very limited field calibration data to estimate over various scales ranging from 1 m to many tens or river kilometers (i) spatial composition metrics for key hydraulic mesohabitat types and (ii) reach-scale wetted habitat heterogeneity indices such as the hydromorphological index of diversity (HMID). When the purpose is hydraulic habitat characterization applied over long river networks, the proposed method (although less accurate) is much less computationally expensive and less data demanding than two dimensional computational fluid dynamics (CFD). Here, we illustrate the tools based on a Worldview 2 satellite image of the Kiamika River, near Mont Laurier, Quebec, Canada, specifically over a 17-km river reach below the Kiamika dam. In the first step, a high resolution water depth (D) map is produced from a spectral band ratio (calculated from the multispectral image), calibrated with limited field measurements. Next, based only on known river discharge and estimated cross section depths at time of image capture, empirical-based pseudo-2D hydraulic rules are used to rapidly generate a two-dimensional map of flow velocity

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

Science.gov (United States)

Davis, Philip A.; Davis, Philip A.

2013-01-01

, 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

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

Science.gov (United States)

Davis, Philip A.; Davis, Philip A.

2013-01-01

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

Earth-based and Galileo SSI multispectral observations of eastern mare serenitatis and the Apollo 17 landing site

Science.gov (United States)

Hiesinger, H.; Jaumann, R.; Neukum, G.

1993-01-01

Both the Apollo 17 and the Mare Serenitatis region were observed by Galileo during its fly-by in December 1992. We used earth-based multispectral data to define mare units which then can be compared with the results of the Galileo SSI data evaluation.

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

Science.gov (United States)

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

2012-01-01

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

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

Science.gov (United States)

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

2012-01-01

, 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

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

Science.gov (United States)

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

2012-01-01

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

Framework of Jitter Detection and Compensation for High Resolution Satellites

Directory of Open Access Journals (Sweden)

Xiaohua Tong

2014-05-01

Full Text Available Attitude jitter is a common phenomenon in the application of high resolution satellites, which may result in large errors of geo-positioning and mapping accuracy. Therefore, it is critical to detect and compensate attitude jitter to explore the full geometric potential of high resolution satellites. In this paper, a framework of jitter detection and compensation for high resolution satellites is proposed and some preliminary investigation is performed. Three methods for jitter detection are presented as follows. (1 The first one is based on multispectral images using parallax between two different bands in the image; (2 The second is based on stereo images using rational polynomial coefficients (RPCs; (3 The third is based on panchromatic images employing orthorectification processing. Based on the calculated parallax maps, the frequency and amplitude of the detected jitter are obtained. Subsequently, two approaches for jitter compensation are conducted. (1 The first one is to conduct the compensation on image, which uses the derived parallax observations for resampling; (2 The second is to conduct the compensation on attitude data, which treats the influence of jitter on attitude as correction of charge-coupled device (CCD viewing angles. Experiments with images from several satellites, such as ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiaometer, LRO (Lunar Reconnaissance Orbiter and ZY-3 (ZiYuan-3 demonstrate the promising performance and feasibility of the proposed framework.

The multispectral instrument of the Sentinel2 program

Science.gov (United States)

Cazaubiel, V.; Chorvalli, Vincent; Miesch, Christophe

2017-11-01

The Sentinel-2 program will provide a permanent record of comprehensive data to help inform the agricul-tural sector (utilisation, coverage), forestry industry (population, damage, forest fires), disaster control (management, early warning) and humanitarian relief programmes. Sentinel-2 will also be able to observe natural disasters such as floods, volcanic eruptions, subsidence and landslides. In the Sentinel-2 mission programme, Astrium in Friedrichshafen is responsible for the satellite's system design and platform, as well as for satellite integration and testing. Astrium Toulouse will supply the Multi-Spectral imaging Instrument (MSI), and Astrium Spain will be in charge of the satellite's structure and will produce its thermal equipment and cable harness. The industrial core team also comprises Jena Optronik (Germany), Boostec (France), Sener and GMV (Spain). Sentinel-2 is intended to image the Earth's landmasses from its orbit for at least 7.25 years. In addition, its onboardresources will be designed so that the mission can be prolonged by an extra five years. From 2012 onwards, the 1.1-metric-ton satellite will circle the Earth in a sun-synchronous, polar orbit at an altitude of 786kilometres, fully covering the planet's landmasses in just ten days. The multi-spectral instrument (MSI) will generate optical images in 13 spectral channels in the visible and shortwave infrared range down to a resolution of 10 metres with an image width of 290 kilometres. The instrument is composed of two main parts: • The telescope assembly , combining in one instrument both VNIR and SWIR channels, is mounted on the upper plate of the Bus • The Video and Compression Electronic Units mounted inside the Bus. This telescope is based on a Three Mirror Anastigmat optical concept. This three mirror optical combination is corrected from spherical aberration, coma and astigmatism. It provides a large field of view with very good optical quality. The telescope mirrors and

Multi-spectral endogenous fluorescence imaging for bacterial differentiation

Science.gov (United States)

Chernomyrdin, Nikita V.; Babayants, Margarita V.; Korotkov, Oleg V.; Kudrin, Konstantin G.; Rimskaya, Elena N.; Shikunova, Irina A.; Kurlov, Vladimir N.; Cherkasova, Olga P.; Komandin, Gennady A.; Reshetov, Igor V.; Zaytsev, Kirill I.

2017-07-01

In this paper, the multi-spectral endogenous fluorescence imaging was implemented for bacterial differentiation. The fluorescence imaging was performed using a digital camera equipped with a set of visual bandpass filters. Narrowband 365 nm ultraviolet radiation passed through a beam homogenizer was used to excite the sample fluorescence. In order to increase a signal-to-noise ratio and suppress a non-fluorescence background in images, the intensity of the UV excitation was modulated using a mechanical chopper. The principal components were introduced for differentiating the samples of bacteria based on the multi-spectral endogenous fluorescence images.

Spot-5 multispectral image for 60-75 days of rice mapping

International Nuclear Information System (INIS)

Ramli, Mohd Amiruddin; Shariff, Abdul Rashid Mohamed; Bejo, Siti Khairunniza

2014-01-01

The objective of this study is to investigate the potential application of Spot-5 multispectral satellite data in monitoring rice cultivation areas in IADA (Integrated Agriculture Development Area) located at Kerian District, Perak Malaysia. Information of the rice cultivation areas is a global economic and environmental significance. Multi-spectral images acquired at high spatial resolution are an important tool, especially in agricultural applications. This paper addresses the relationship between normalize difference vegetation index (NDVI) and ancillary data acquired from Farmers Organization Authority (PPK) for 217 farmer's field in IADA Kerian. The results indicated that NDVI range 0.62 – 0.75 has a strong positive relationship with the ground survey area estimation with (r = 0.85; p <0.01) (r 2 = 0.722). The r 2 value of 0.722 indicated a statistically significant linear relationship between the rice area estimate using NDVI range 0.62 – 0.75 and on the ground surveyed data for 217 farmers' fields. The equation of unstandardized distribution can be described as Ŷ=0.0197+0.852x. The equation for standardized regression formula for this distribution is Ŷ= 0.850x. Thus, the results indicate that 60-75 days of rice area can be estimated from the following equation Ŷ=0.197+0.852x, where Ŷ is the predicted rice area and x is area calculated using NDVI range 0.62-0.75 in IADA Kerian Perak Malaysia. The results appear promising and rice mapping operations using SPOT-5 multispectral image data can be foreseen

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

Science.gov (United States)

Davis, Philip A.; Cagney, Laura E.

2013-01-01

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

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

Science.gov (United States)

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

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

Directory of Open Access Journals (Sweden)

Liang Lu

2018-03-01

Full Text Available 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.

Satellite Map of Port-au-Prince, Haiti-2010-Natural Color

Science.gov (United States)

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.

On the use of wavelet for extracting feature patterns from Multitemporal google earth satellite data sets

Science.gov (United States)

Lasaponara, R.

2012-04-01

, Masini N (2006b) Identification of archaeological buried remains based on Normalized Difference Vegetation Index (NDVI) from Quickbird satellite data. IEEE Geosci Remote S 3(3): 325-328. Lasaponara R, Masini N (2007a) Detection of archaeological crop marks by using satellite QuickBird multispectral imagery. J Archaeol Sci 34: 214-21. Lasaponara R, Masini N (2007b) Improving satellite Quickbird - based identification of landscape archaeological features trough tasselled cup transformation and PCA. 21st CIPA Symposium, Atene, 1-6 giugno 2007. Lasaponara R, Masini N (2010) Facing the archaeological looting in Peru by local spatial autocorrelation statistics of Very high resolution satellite imagery. In: Taniar D et al (Eds), Proceedings of ICSSA, The 2010 International Conference on Computational Science and its Application (Fukuoka-Japan, March 23 - 26, 2010), Springer, Berlin, 261-269. Lasaponara R, Masini N (2011) Satellite Remote Sensing in Archaeology : past, present and future. J Archaeol Sc 38: 1995-2002. Lasaponara R, Masini N, Rizzo E, Orefici G (2011) New discoveries in the Piramide Naranjada in Cahuachi (Peru) using satellite, Ground Probing Radar and magnetic investigations. J Archaeol Sci 38: 2031-2039. Lasaponara R, Masini N, Scardozzi G (2008) Satellite based archaeological research in ancient territory of Hierapolis. 1st International EARSeL Workshop. Advances in Remote Sensing for Archaeology and Cultural Heritage Management", CNR, Rome, September 30-October 4, Aracne, Rome, pp.11-16. Lillesand T M, Kiefer R W (2000) Remote Sensing and Image interpretation. John Wiley and Sons, New York. Masini N, Lasaponara R (2006) Satellite-based recognition of landscape archaeological features related to ancient human transformation. J Geophys Eng 3: 230-235, doi:10.1088/1742-2132/3/3/004. Masini N, Lasaponara R (2007) Investigating the spectral capability of QuickBird data to detect archaeological remains buried under vegetated and not vegetated areas. J Cult Heri 8 (1

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

Science.gov (United States)

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

2013-01-01

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

Multi-spectral confocal microendoscope for in-vivo imaging

Science.gov (United States)

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.

DeepSAT's CloudCNN: A Deep Neural Network for Rapid Cloud Detection from Geostationary Satellites

Science.gov (United States)

Kalia, S.; Li, S.; Ganguly, S.; Nemani, R. R.

2017-12-01

Cloud and cloud shadow detection has important applications in weather and climate studies. It is even more crucial when we introduce geostationary satellites into the field of terrestrial remotesensing. With the challenges associated with data acquired in very high frequency (10-15 mins per scan), the ability to derive an accurate cloud/shadow mask from geostationary satellite data iscritical. The key to the success for most of the existing algorithms depends on spatially and temporally varying thresholds, which better capture local atmospheric and surface effects.However, the selection of proper threshold is difficult and may lead to erroneous results. In this work, we propose a deep neural network based approach called CloudCNN to classifycloud/shadow from Himawari-8 AHI and GOES-16 ABI multispectral data. DeepSAT's CloudCNN consists of an encoder-decoder based architecture for binary-class pixel wise segmentation. We train CloudCNN on multi-GPU Nvidia Devbox cluster, and deploy the prediction pipeline on NASA Earth Exchange (NEX) Pleiades supercomputer. We achieved an overall accuracy of 93.29% on test samples. Since, the predictions take only a few seconds to segment a full multi-spectral GOES-16 or Himawari-8 Full Disk image, the developed framework can be used for real-time cloud detection, cyclone detection, or extreme weather event predictions.

VHR satellite imagery for humanitarian crisis management: a case study

Science.gov (United States)

Bitelli, Gabriele; Eleias, Magdalena; Franci, Francesca; Mandanici, Emanuele

2017-09-01

During the last years, remote sensing data along with GIS have been largely employed for supporting emergency management activities. In this context, the use of satellite images and derived map products has become more common also in the different phases of humanitarian crisis response. In this work very high resolution satellite imagery was processed to assess the evolution of Za'atari Refugee Camp, built in Jordan in 2012 by the UN Refugee Agency to host Syrian refugees. Multispectral satellite scenes of the Za'atari area were processed by means of object-based classifications. The main aim of the present work is the development of a semiautomated procedure for multi-temporal camp monitoring with particular reference to the dwellings detection. Whilst in the emergency mapping domain automation of feature extraction is widely investigated, in the field of humanitarian missions the information is often extracted by means of photointerpretation of the satellite data. This approach requires time for the interpretation; moreover, it is not reliable enough in complex situations, where features of interest are often small, heterogeneous and inconsistent. Therefore, the present paper discusses a methodology to obtain information for assisting humanitarian crisis management, using a semi-automatic classification approach applied to satellite imagery.

Adaptive Residual Interpolation for Color and Multispectral Image Demosaicking.

Science.gov (United States)

Monno, Yusuke; Kiku, Daisuke; Tanaka, Masayuki; Okutomi, Masatoshi

2017-12-01

Color image demosaicking for the Bayer color filter array is an essential image processing operation for acquiring high-quality color images. Recently, residual interpolation (RI)-based algorithms have demonstrated superior demosaicking performance over conventional color difference interpolation-based algorithms. In this paper, we propose adaptive residual interpolation (ARI) that improves existing RI-based algorithms by adaptively combining two RI-based algorithms and selecting a suitable iteration number at each pixel. These are performed based on a unified criterion that evaluates the validity of an RI-based algorithm. Experimental comparisons using standard color image datasets demonstrate that ARI can improve existing RI-based algorithms by more than 0.6 dB in the color peak signal-to-noise ratio and can outperform state-of-the-art algorithms based on training images. We further extend ARI for a multispectral filter array, in which more than three spectral bands are arrayed, and demonstrate that ARI can achieve state-of-the-art performance also for the task of multispectral image demosaicking.

Active Multispectral Band Selection and Reflectance Measurement System

National Research Council Canada - National Science Library

Rennich, Bradley

1999-01-01

.... To aid in the selection of these bands, a novel multispectral band selection technique is presented based on the cross-correlation of the material class reflectance spectra over a wavelength range of 1 - 5 microns...

An image compression method for space multispectral time delay and integration charge coupled device camera

International Nuclear Information System (INIS)

Li Jin; Jin Long-Xu; Zhang Ran-Feng

2013-01-01

Multispectral time delay and integration charge coupled device (TDICCD) image compression requires a low-complexity encoder because it is usually completed on board where the energy and memory are limited. The Consultative Committee for Space Data Systems (CCSDS) has proposed an image data compression (CCSDS-IDC) algorithm which is so far most widely implemented in hardware. However, it cannot reduce spectral redundancy in multispectral images. In this paper, we propose a low-complexity improved CCSDS-IDC (ICCSDS-IDC)-based distributed source coding (DSC) scheme for multispectral TDICCD image consisting of a few bands. Our scheme is based on an ICCSDS-IDC approach that uses a bit plane extractor to parse the differences in the original image and its wavelet transformed coefficient. The output of bit plane extractor will be encoded by a first order entropy coder. Low-density parity-check-based Slepian—Wolf (SW) coder is adopted to implement the DSC strategy. Experimental results on space multispectral TDICCD images show that the proposed scheme significantly outperforms the CCSDS-IDC-based coder in each band

Fusion of multispectral and panchromatic images using multirate filter banks

Institute of Scientific and Technical Information of China (English)

Wang Hong; Jing Zhongliang; Li Jianxun

2005-01-01

In this paper, an image fusion method based on the filter banks is proposed for merging a high-resolution panchromatic image and a low-resolution multispectral image. Firstly, the filter banks are designed to merge different signals with minimum distortion by using cosine modulation. Then, the filter banks-based image fusion is adopted to obtain a high-resolution multispectral image that combines the spectral characteristic of low-resolution data with the spatial resolution of the panchromatic image. Finally, two different experiments and corresponding performance analysis are presented. Experimental results indicate that the proposed approach outperforms the HIS transform, discrete wavelet transform and discrete wavelet frame.

Multispectral imaging of wok fried vegetables

DEFF Research Database (Denmark)

Løje, Hanne; Dissing, Bjørn Skovlund; Clemmensen, Line Katrine Harder

2011-01-01

This paper shows how multispectral images can be used to assess color change over time in wok fried vegetables. We present results where feature selection was performed with sparse methods from the multispectral images to detect the color changes of wok fried carrots and celeriac stored at +5°C...

Multivariate alteration detection (MAD) in multispectral, bi-temporal image data: A new approach to change detction studies

DEFF Research Database (Denmark)

Nielsen, Allan Aasbjerg; Conradsen, Knut

This paper introduces a new orthogonal transformation, the multivariate alteration detection (MAD) transformation, based on an established multivariate statistical technique canonical correlation analysis. The theory for canonical correlation analysis is sketched and a result necessary...... for the definition of the MAD transformation is proven. As opposed to traditional univariate change detection schemes our scheme transforms two sets of multivariate observations (e.g. two multispectral satellite images covering the same geographical area acquired at different points in time) into a difference...... between two linear combinations of the original variables explaining maximal change (i.e. the difference explaining maximal variance) in all variables simultaneously. The MAD transformation is invariant to linear scaling. The MAD transformation can be used iteratively. First, it can be used to detect...

Multi-spectral quantitative phase imaging based on filtration of light via ultrasonic wave

Science.gov (United States)

Machikhin, A. S.; Polschikova, O. V.; Ramazanova, A. G.; Pozhar, V. E.

2017-07-01

A new digital holographic microscopy scheme for multi-spectral quantitative phase imaging is proposed and implemented. It is based on acousto-optic filtration of wide-band low-coherence light at the entrance of a Mach-Zehnder interferometer, recording and digital processing of interferograms. The key requirements for the acousto-optic filter are discussed. The effectiveness of the technique is demonstrated by calculating the phase maps of human red blood cells at multiple wavelengths in the range 770-810 nm. The scheme can be used for the measurement of dispersion of thin films and biological samples.

Use of high resolution satellite images for monitoring of earthquakes and volcano activity.

Science.gov (United States)

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.

A novel multispectral glacier mapping method and its performance in Greenland

Science.gov (United States)

Citterio, M.; Fausto, R. S.; Ahlstrom, A. P.; Andersen, S. B.

2014-12-01

Multispectral land surface classification methods are widely used for mapping glacier outlines. Significant post-classification manual editing is typically required, and mapping glacier outlines over larger regions remains a rather labour intensive task. In this contribution we introduce a novel method for mapping glacier outlines from multispectral satellite imagery, requiring only minor manual editing.Over the last decade GLIMS (Global Land Ice Measurements from Space) improved the availability of glacier outlines, and in 2012 the Randolph Glacier Inventory (RGI) attained global coverage by compiling existing and new data sources in the wake of the Fifth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC AR5). With the launch of Landsat 8 in 2013 and the upcoming ESA (European Space Agency) Sentinel 2 missions, the availability of multispectral imagery may grow faster than our ability to process it into timely and reliable glacier outline products. Improved automatic classification methods would enable a full exploitation of these new data sources.We outline the theoretical basis of the proposed classification algorithm, provide a step by step walk-through from raw imagery to finished ice cover grids and vector glacier outlines, and evaluate the performance of the new method in mapping the outlines of glaciers, ice caps and the Greenland Ice Sheet from Landsat 8 OLI imagery. The classification output is compared against manually digitized ice margin positions, the RGI vectors, and the PROMICE (Programme for Monitoring of the Greenland Ice Sheet) aerophotogrammetric map of Greenland ice masses over a sector of the Disko Island surge cluster in West Greenland, the Qassimiut ice sheet lobe in South Greenland, and the A.P. Olsen ice cap in NE Greenland.

Wetland Vegetation Integrity Assessment with Low Altitude Multispectral Uav Imagery

Science.gov (United States)

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

Satellite-Based Precipitation Datasets

Science.gov (United States)

Munchak, S. J.; Huffman, G. J.

2017-12-01

Of the possible sources of precipitation data, those based on satellites provide the greatest spatial coverage. There is a wide selection of datasets, algorithms, and versions from which to choose, which can be confusing to non-specialists wishing to use the data. The International Precipitation Working Group (IPWG) maintains tables of the major publicly available, long-term, quasi-global precipitation data sets (http://www.isac.cnr.it/ ipwg/data/datasets.html), and this talk briefly reviews the various categories. As examples, NASA provides two sets of quasi-global precipitation data sets: the older Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) and current Integrated Multi-satellitE Retrievals for Global Precipitation Measurement (GPM) mission (IMERG). Both provide near-real-time and post-real-time products that are uniformly gridded in space and time. The TMPA products are 3-hourly 0.25°x0.25° on the latitude band 50°N-S for about 16 years, while the IMERG products are half-hourly 0.1°x0.1° on 60°N-S for over 3 years (with plans to go to 16+ years in Spring 2018). In addition to the precipitation estimates, each data set provides fields of other variables, such as the satellite sensor providing estimates and estimated random error. The discussion concludes with advice about determining suitability for use, the necessity of being clear about product names and versions, and the need for continued support for satellite- and surface-based observation.

New perspectives for satellite-based archaeological research in the ancient territory of Hierapolis (Turkey

Directory of Open Access Journals (Sweden)

R. Lasaponara

2008-11-01

Full Text Available This paper deals with the use of satellite QuickBird images to find traces of past human activity in the ancient territory of Hierapolis (Turkey. This is one of the most important archaeological sites in Turkey, and in 1988 it was inscribed in the UNESCO World Heritage list. Although over the years the archaeological site of Hierapolis has been excavated, restored and well documented, up to now the territory around the ancient urban area is still largely unknown. The current research project, still in progress, aims to search the area neighbouring Hierapolis believed to have been under the control of the city for a long time and, therefore, expected to be very rich in archaeological evidence. In order to investigate a large area around the ancient Hierapolis and discover potential archaeological remains, QuickBird images were adopted.

Results from satellite-based analysis allowed us to find several unknown rural settlements dating back to early Imperial Roman and the Byzantine age. Two significant test sites were focused on in this paper in order to characterize the different spectral responses observed for different types of archaeological features (shadow and soil marks. Principal Component Analysis and spectral indices were computed to enhance archaeological marks and make identification easier. The capability of the QuickBird data set (panchromatic, multispectral channel, PCA and spectral indices in searching for archaeological marks was assessed in a quantitative way by using a specific indicator.

Satellite-based laser windsounder

International Nuclear Information System (INIS)

Schultz, J.F.; Czuchlewski, S.J.; Quick, C.R.

1997-01-01

This is the final report of a one-year, Laboratory-Directed Research and Development (LDRD) project at the Los Alamos National Laboratory (LANL). The project''s primary objective is to determine the technical feasibility of using satellite-based laser wind sensing systems for detailed study of winds, aerosols, and particulates around and downstream of suspected proliferation facilities. Extensive interactions with the relevant operational organization resulted in enthusiastic support and useful guidance with respect to measurement requirements and priorities. Four candidate wind sensing techniques were evaluated, and the incoherent Doppler technique was selected. A small satellite concept design study was completed to identify the technical issues inherent in a proof-of-concept small satellite mission. Use of a Mach-Zehnder interferometer instead of a Fabry-Perot would significantly simplify the optical train and could reduce weight, and possibly power, requirements with no loss of performance. A breadboard Mach-Zehnder interferometer-based system has been built to verify these predictions. Detailed plans were made for resolving other issues through construction and testing of a ground-based lidar system in collaboration with the University of Wisconsin, and through numerical lidar wind data assimilation studies

Multispectral Image Road Extraction Based Upon Automated Map Conflation

Science.gov (United States)

Chen, Bin

Road network extraction from remotely sensed imagery enables many important and diverse applications such as vehicle tracking, drone navigation, and intelligent transportation studies. There are, however, a number of challenges to road detection from an image. Road pavement material, width, direction, and topology vary across a scene. Complete or partial occlusions caused by nearby buildings, trees, and the shadows cast by them, make maintaining road connectivity difficult. The problems posed by occlusions are exacerbated with the increasing use of oblique imagery from aerial and satellite platforms. Further, common objects such as rooftops and parking lots are made of materials similar or identical to road pavements. This problem of common materials is a classic case of a single land cover material existing for different land use scenarios. This work addresses these problems in road extraction from geo-referenced imagery by leveraging the OpenStreetMap digital road map to guide image-based road extraction. The crowd-sourced cartography has the advantages of worldwide coverage that is constantly updated. The derived road vectors follow only roads and so can serve to guide image-based road extraction with minimal confusion from occlusions and changes in road material. On the other hand, the vector road map has no information on road widths and misalignments between the vector map and the geo-referenced image are small but nonsystematic. Properly correcting misalignment between two geospatial datasets, also known as map conflation, is an essential step. A generic framework requiring minimal human intervention is described for multispectral image road extraction and automatic road map conflation. The approach relies on the road feature generation of a binary mask and a corresponding curvilinear image. A method for generating the binary road mask from the image by applying a spectral measure is presented. The spectral measure, called anisotropy-tunable distance (ATD

Multispectral code excited linear prediction coding and its application in magnetic resonance images.

Science.gov (United States)

Hu, J H; Wang, Y; Cahill, P T

1997-01-01

This paper reports a multispectral code excited linear prediction (MCELP) method for the compression of multispectral images. Different linear prediction models and adaptation schemes have been compared. The method that uses a forward adaptive autoregressive (AR) model has been proven to achieve a good compromise between performance, complexity, and robustness. This approach is referred to as the MFCELP method. Given a set of multispectral images, the linear predictive coefficients are updated over nonoverlapping three-dimensional (3-D) macroblocks. Each macroblock is further divided into several 3-D micro-blocks, and the best excitation signal for each microblock is determined through an analysis-by-synthesis procedure. The MFCELP method has been applied to multispectral magnetic resonance (MR) images. To satisfy the high quality requirement for medical images, the error between the original image set and the synthesized one is further specified using a vector quantizer. This method has been applied to images from 26 clinical MR neuro studies (20 slices/study, three spectral bands/slice, 256x256 pixels/band, 12 b/pixel). The MFCELP method provides a significant visual improvement over the discrete cosine transform (DCT) based Joint Photographers Expert Group (JPEG) method, the wavelet transform based embedded zero-tree wavelet (EZW) coding method, and the vector tree (VT) coding method, as well as the multispectral segmented autoregressive moving average (MSARMA) method we developed previously.

A combined use of multispectral and SAR images for ship detection and characterization through object based image analysis

Science.gov (United States)

Aiello, Martina; Gianinetto, Marco

2017-10-01

Marine routes represent a huge portion of commercial and human trades, therefore surveillance, security and environmental protection themes are gaining increasing importance. Being able to overcome the limits imposed by terrestrial means of monitoring, ship detection from satellite has recently prompted a renewed interest for a continuous monitoring of illegal activities. This paper describes an automatic Object Based Image Analysis (OBIA) approach to detect vessels made of different materials in various sea environments. The combined use of multispectral and SAR images allows for a regular observation unrestricted by lighting and atmospheric conditions and complementarity in terms of geographic coverage and geometric detail. The method developed adopts a region growing algorithm to segment the image in homogeneous objects, which are then classified through a decision tree algorithm based on spectral and geometrical properties. Then, a spatial analysis retrieves the vessels' position, length and heading parameters and a speed range is associated. Optimization of the image processing chain is performed by selecting image tiles through a statistical index. Vessel candidates are detected over amplitude SAR images using an adaptive threshold Constant False Alarm Rate (CFAR) algorithm prior the object based analysis. Validation is carried out by comparing the retrieved parameters with the information provided by the Automatic Identification System (AIS), when available, or with manual measurement when AIS data are not available. The estimation of length shows R2=0.85 and estimation of heading R2=0.92, computed as the average of R2 values obtained for both optical and radar images.

Quality assessment of butter cookies applying multispectral imaging

Science.gov (United States)

Andresen, Mette S; Dissing, Bjørn S; Løje, Hanne

2013-01-01

A method for characterization of butter cookie quality by assessing the surface browning and water content using multispectral images is presented. Based on evaluations of the browning of butter cookies, cookies were manually divided into groups. From this categorization, reference values were calculated for a statistical prediction model correlating multispectral images with a browning score. The browning score is calculated as a function of oven temperature and baking time. It is presented as a quadratic response surface. The investigated process window was the intervals 4–16 min and 160–200°C in a forced convection electrically heated oven. In addition to the browning score, a model for predicting the average water content based on the same images is presented. This shows how multispectral images of butter cookies may be used for the assessment of different quality parameters. Statistical analysis showed that the most significant wavelengths for browning predictions were in the interval 400–700 nm and the wavelengths significant for water prediction were primarily located in the near-infrared spectrum. The water prediction model was found to correctly estimate the average water content with an absolute error of 0.22%. From the images it was also possible to follow the browning and drying propagation from the cookie edge toward the center. PMID:24804036

Global trends in satellite-based emergency mapping

Science.gov (United States)

Voigt, Stefan; Giulio-Tonolo, Fabio; Lyons, Josh; Kučera, Jan; Jones, Brenda; Schneiderhan, Tobias; Platzeck, Gabriel; Kaku, Kazuya; Hazarika, Manzul Kumar; Czaran, Lorant; Li, Suju; Pedersen, Wendi; James, Godstime Kadiri; Proy, Catherine; Muthike, Denis Macharia; Bequignon, Jerome; Guha-Sapir, Debarati

2016-01-01

Over the past 15 years, scientists and disaster responders have increasingly used satellite-based Earth observations for global rapid assessment of disaster situations. We review global trends in satellite rapid response and emergency mapping from 2000 to 2014, analyzing more than 1000 incidents in which satellite monitoring was used for assessing major disaster situations. We provide a synthesis of spatial patterns and temporal trends in global satellite emergency mapping efforts and show that satellite-based emergency mapping is most intensively deployed in Asia and Europe and follows well the geographic, physical, and temporal distributions of global natural disasters. We present an outlook on the future use of Earth observation technology for disaster response and mitigation by putting past and current developments into context and perspective.

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

Science.gov (United States)

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

Use of high resolution satellite images for tracking of changes in the lineament structure, caused by earthquakes

OpenAIRE

Arellano-Baeza, A. A.; Garcia, R. V.; Trejo-Soto, M.

2007-01-01

Over the last decades strong efforts have been made to apply new spaceborn technologies to the study and possible forecast of strong earthquakes. In this study we use ASTER/TERRA multispectral satellite images for detection and analysis of changes in the system of lineaments previous to a strong earthquake. A lineament is a straight or a somewhat curved feature in an image, which it is possible to detect by a special processing of images based on directional filtering and or Hough transform. ...

Multispectral histogram normalization contrast enhancement

Science.gov (United States)

Soha, J. M.; Schwartz, A. A.

1979-01-01

A multispectral histogram normalization or decorrelation enhancement which achieves effective color composites by removing interband correlation is described. The enhancement procedure employs either linear or nonlinear transformations to equalize principal component variances. An additional rotation to any set of orthogonal coordinates is thus possible, while full histogram utilization is maintained by avoiding the reintroduction of correlation. For the three-dimensional case, the enhancement procedure may be implemented with a lookup table. An application of the enhancement to Landsat multispectral scanning imagery is presented.

RETRIEVAL OF AEROSOL MICROPHYSICAL PROPERTIES BASED ON THE OPTIMAL ESTIMATION METHOD: INFORMATION CONTENT ANALYSIS FOR SATELLITE POLARIMETRIC REMOTE SENSING MEASUREMENTS

Directory of Open Access Journals (Sweden)

W. Z. Hou

2018-04-01

Full Text Available This paper evaluates the information content for the retrieval of key aerosol microphysical and surface properties for multispectral single-viewing satellite polarimetric measurements cantered at 410, 443, 555, 670, 865, 1610 and 2250 nm over bright land. To conduct the information content analysis, the synthetic data are simulated by the Unified Linearized Vector Radiative Transfer Model (UNLVTM with the intensity and polarization together over bare soil surface for various scenarios. Following the optimal estimation theory, a principal component analysis method is employed to reconstruct the multispectral surface reflectance from 410 nm to 2250 nm, and then integrated with a linear one-parametric BPDF model to represent the contribution of polarized surface reflectance, thus further to decouple the surface-atmosphere contribution from the TOA measurements. Focusing on two different aerosol models with the aerosol optical depth equal to 0.8 at 550 nm, the total DFS and DFS component of each retrieval aerosol and surface parameter are analysed. The DFS results show that the key aerosol microphysical properties, such as the fine- and coarse-mode columnar volume concentration, the effective radius and the real part of complex refractive index at 550 nm, could be well retrieved with the surface parameters simultaneously over bare soil surface type. The findings of this study can provide the guidance to the inversion algorithm development over bright surface land by taking full use of the single-viewing satellite polarimetric measurements.

Retrieval of Aerosol Microphysical Properties Based on the Optimal Estimation Method: Information Content Analysis for Satellite Polarimetric Remote Sensing Measurements

Science.gov (United States)

Hou, W. Z.; Li, Z. Q.; Zheng, F. X.; Qie, L. L.

2018-04-01

This paper evaluates the information content for the retrieval of key aerosol microphysical and surface properties for multispectral single-viewing satellite polarimetric measurements cantered at 410, 443, 555, 670, 865, 1610 and 2250 nm over bright land. To conduct the information content analysis, the synthetic data are simulated by the Unified Linearized Vector Radiative Transfer Model (UNLVTM) with the intensity and polarization together over bare soil surface for various scenarios. Following the optimal estimation theory, a principal component analysis method is employed to reconstruct the multispectral surface reflectance from 410 nm to 2250 nm, and then integrated with a linear one-parametric BPDF model to represent the contribution of polarized surface reflectance, thus further to decouple the surface-atmosphere contribution from the TOA measurements. Focusing on two different aerosol models with the aerosol optical depth equal to 0.8 at 550 nm, the total DFS and DFS component of each retrieval aerosol and surface parameter are analysed. The DFS results show that the key aerosol microphysical properties, such as the fine- and coarse-mode columnar volume concentration, the effective radius and the real part of complex refractive index at 550 nm, could be well retrieved with the surface parameters simultaneously over bare soil surface type. The findings of this study can provide the guidance to the inversion algorithm development over bright surface land by taking full use of the single-viewing satellite polarimetric measurements.

Detecting Weather Radar Clutter by Information Fusion With Satellite Images and Numerical Weather Prediction Model Output

DEFF Research Database (Denmark)

Bøvith, Thomas; Nielsen, Allan Aasbjerg; Hansen, Lars Kai

2006-01-01

A method for detecting clutter in weather radar images by information fusion is presented. Radar data, satellite images, and output from a numerical weather prediction model are combined and the radar echoes are classified using supervised classification. The presented method uses indirect...... information on precipitation in the atmosphere from Meteosat-8 multispectral images and near-surface temperature estimates from the DMI-HIRLAM-S05 numerical weather prediction model. Alternatively, an operational nowcasting product called 'Precipitating Clouds' based on Meteosat-8 input is used. A scale...

Cloud-based processing of multi-spectral imaging data

Science.gov (United States)

Bernat, Amir S.; Bolton, Frank J.; Weiser, Reuven; Levitz, David

2017-03-01

Multispectral imaging holds great promise as a non-contact tool for the assessment of tissue composition. Performing multi - spectral imaging on a hand held mobile device would allow to bring this technology and with it knowledge to low resource settings to provide a state of the art classification of tissue health. This modality however produces considerably larger data sets than white light imaging and requires preliminary image analysis for it to be used. The data then needs to be analyzed and logged, while not requiring too much of the system resource or a long computation time and battery use by the end point device. Cloud environments were designed to allow offloading of those problems by allowing end point devices (smartphones) to offload computationally hard tasks. For this end we present a method where the a hand held device based around a smartphone captures a multi - spectral dataset in a movie file format (mp4) and compare it to other image format in size, noise and correctness. We present the cloud configuration used for segmenting images to frames where they can later be used for further analysis.

High-speed multispectral videography with a periscope array in a spectral shaper.

Science.gov (United States)

Hashimoto, Kazuki; Mizuno, Hikaru; Nakagawa, Keiichi; Horisaki, Ryoichi; Iwasaki, Atsushi; Kannari, Fumihiko; Sakuma, Ichiro; Goda, Keisuke

2014-12-15

We present a simple method for continuous snapshot multispectral imaging or multispectral videography that achieves high-speed spectral video recording without the need for mechanical scanning and much computation for datacube construction. The enabling component of this method is an array of periscopes placed in a prism-based spectral shaper that spectrally separates the image without image deformation. As a proof-of-principle demonstration, we show five-color multispectral video recording in the visible range (200×200 pixels per spectral image frame) at a record high frame rate of at least 2800 frames per second. Our experimental results indicate that this method holds promise for various industrial and biomedical applications such as remote sensing, food inspection, and endoscopy.

Design Considerations, Modeling and Analysis for the Multispectral Thermal Imager

International Nuclear Information System (INIS)

Borel, C.C.; Clodius, W.B.; Cooke, B.J.; Smith, B.W.; Weber, P.G.

1999-01-01

The design of remote sensing systems is driven by the need to provide cost-effective, substantive answers to questions posed by our customers. This is especially important for space-based systems, which tend to be expensive, and which generally cannot be changed after they are launched. We report here on the approach we employed in developing the desired attributes of a satellite mission, namely the Multispectral Thermal Imager. After an initial scoping study, we applied a procedure which we call: ''End-to-end modeling and analysis (EEM).'' We began with target attributes, translated to observable signatures and then propagated the signatures through the atmosphere to the sensor location. We modeled the sensor attributes to yield a simulated data stream, which was then analyzed to retrieve information about the original target. The retrieved signature was then compared to the original to obtain a figure of merit: hence the term ''end-to-end modeling and analysis.'' We base the EEM in physics to ensure high fidelity and to permit scaling. As the actual design of the payload evolves, and as real hardware is tested, we can update the EEM to facilitate trade studies, and to judge, for example, whether components that deviate from specifications are acceptable

SALIENCY BASED SEGMENTATION OF SATELLITE IMAGES

Directory of Open Access Journals (Sweden)

A. Sharma

2015-03-01

Full Text Available Saliency gives the way as humans see any image and saliency based segmentation can be eventually helpful in Psychovisual image interpretation. Keeping this in view few saliency models are used along with segmentation algorithm and only the salient segments from image have been extracted. The work is carried out for terrestrial images as well as for satellite images. The methodology used in this work extracts those segments from segmented image which are having higher or equal saliency value than a threshold value. Salient and non salient regions of image become foreground and background respectively and thus image gets separated. For carrying out this work a dataset of terrestrial images and Worldview 2 satellite images (sample data are used. Results show that those saliency models which works better for terrestrial images are not good enough for satellite image in terms of foreground and background separation. Foreground and background separation in terrestrial images is based on salient objects visible on the images whereas in satellite images this separation is based on salient area rather than salient objects.

Spatio-temporal monitoring of cotton cultivation using ground-based and airborne multispectral sensors in GIS environment.

Science.gov (United States)

Papadopoulos, Antonis; Kalivas, Dionissios; Theocharopoulos, Sid

2017-07-01

Multispectral sensor capability of capturing reflectance data at several spectral channels, together with the inherent reflectance responses of various soils and especially plant surfaces, has gained major interest in crop production. In present study, two multispectral sensing systems, a ground-based and an aerial-based, were applied for the multispatial and temporal monitoring of two cotton fields in central Greece. The ground-based system was Crop Circle ACS-430, while the aerial consisted of a consumer-level quadcopter (Phantom 2) and a modified Hero3+ Black digital camera. The purpose of the research was to monitor crop growth with the two systems and investigate possible interrelations between the derived well-known normalized difference vegetation index (NDVI). Five data collection campaigns were conducted during the cultivation period and concerned scanning soil and plants with the ground-based sensor and taking aerial photographs of the fields with the unmanned aerial system. According to the results, both systems successfully monitored cotton growth stages in terms of space and time. The mean values of NDVI changes through time as retrieved by the ground-based system were satisfactorily modelled by a second-order polynomial equation (R 2 0.96 in Field 1 and 0.99 in Field 2). Further, they were highly correlated (r 0.90 in Field 1 and 0.74 in Field 2) with the according values calculated via the aerial-based system. The unmanned aerial system (UAS) can potentially substitute crop scouting as it concerns a time-effective, non-destructive and reliable way of soil and plant monitoring.

Exploiting physical constraints for multi-spectral exo-planet detection

Science.gov (United States)

Thiébaut, Éric; Devaney, Nicholas; Langlois, Maud; Hanley, Kenneth

2016-07-01

We derive a physical model of the on-axis PSF for a high contrast imaging system such as GPI or SPHERE. This model is based on a multi-spectral Taylor series expansion of the diffraction pattern and predicts that the speckles should be a combination of spatial modes with deterministic chromatic magnification and weighting. We propose to remove most of the residuals by fitting this model on a set of images at multiple wavelengths and times. On simulated data, we demonstrate that our approach achieves very good speckle suppression without additional heuristic parameters. The residual speckles1, 2 set the most serious limitation in the detection of exo-planets in high contrast coronographic images provided by instruments such as SPHERE3 at the VLT, GPI4, 5 at Gemini, or SCExAO6 at Subaru. A number of post-processing methods have been proposed to remove as much as possible of the residual speckles while preserving the signal from the planets. These methods exploit the fact that the speckles and the planetary signal have different temporal and spectral behaviors. Some methods like LOCI7 are based on angular differential imaging8 (ADI), spectral differential imaging9, 10 (SDI), or on a combination of ADI and SDI.11 Instead of working on image differences, we propose to tackle the exo-planet detection as an inverse problem where a model of the residual speckles is fit on the set of multi-spectral images and, possibly, multiple exposures. In order to reduce the number of degrees of freedom, we impose specific constraints on the spatio-spectral distribution of stellar speckles. These constraints are deduced from a multi-spectral Taylor series expansion of the diffraction pattern for an on-axis source which implies that the speckles are a combination of spatial modes with deterministic chromatic magnification and weighting. Using simulated data, the efficiency of speckle removal by fitting the proposed multi-spectral model is compared to the result of using an approximation

Differential Spatio-temporal Multiband Satellite Image Clustering using K-means Optimization With Reinforcement Programming

Directory of Open Access Journals (Sweden)

Irene Erlyn Wina Rachmawan

2015-06-01

Full Text Available Deforestration is one of the crucial issues in Indonesia because now Indonesia has world's highest deforestation rate. In other hand, multispectral image delivers a great source of data for studying spatial and temporal changeability of the environmental such as deforestration area. This research present differential image processing methods for detecting nature change of deforestration. Our differential image processing algorithms extract and indicating area automatically. The feature of our proposed idea produce extracted information from multiband satellite image and calculate the area of deforestration by years with calculating data using temporal dataset. Yet, multiband satellite image consists of big data size that were difficult to be handled for segmentation. Commonly, K- Means clustering is considered to be a powerfull clustering algorithm because of its ability to clustering big data. However K-Means has sensitivity of its first generated centroids, which could lead into a bad performance. In this paper we propose a new approach to optimize K-Means clustering using Reinforcement Programming in order to clustering multispectral image. We build a new mechanism for generating initial centroids by implementing exploration and exploitation knowledge from Reinforcement Programming. This optimization will lead a better result for K-means data cluster. We select multispectral image from Landsat 7 in past ten years in Medawai, Borneo, Indonesia, and apply two segmentation areas consist of deforestration land and forest field. We made series of experiments and compared the experimental results of K-means using Reinforcement Programming as optimizing initiate centroid and normal K-means without optimization process. Keywords: Deforestration, Multispectral images, landsat, automatic clustering, K-means.

Object-Based Classification of Grasslands from High Resolution Satellite Image Time Series Using Gaussian Mean Map Kernels

Directory of Open Access Journals (Sweden)

Mailys Lopes

2017-07-01

Full Text Available This paper deals with the classification of grasslands using high resolution satellite image time series. Grasslands considered in this work are semi-natural elements in fragmented landscapes, i.e., they are heterogeneous and small elements. The first contribution of this study is to account for grassland heterogeneity while working at the object level by modeling its pixels distributions by a Gaussian distribution. To measure the similarity between two grasslands, a new kernel is proposed as a second contribution: the α -Gaussian mean kernel. It allows one to weight the influence of the covariance matrix when comparing two Gaussian distributions. This kernel is introduced in support vector machines for the supervised classification of grasslands from southwest France. A dense intra-annual multispectral time series of the Formosat-2 satellite is used for the classification of grasslands’ management practices, while an inter-annual NDVI time series of Formosat-2 is used for old and young grasslands’ discrimination. Results are compared to other existing pixel- and object-based approaches in terms of classification accuracy and processing time. The proposed method is shown to be a good compromise between processing speed and classification accuracy. It can adapt to the classification constraints, and it encompasses several similarity measures known in the literature. It is appropriate for the classification of small and heterogeneous objects such as grasslands.

Multispectral analytical image fusion

International Nuclear Information System (INIS)

Stubbings, T.C.

2000-04-01

With new and advanced analytical imaging methods emerging, the limits of physical analysis capabilities and furthermore of data acquisition quantities are constantly pushed, claiming high demands to the field of scientific data processing and visualisation. Physical analysis methods like Secondary Ion Mass Spectrometry (SIMS) or Auger Electron Spectroscopy (AES) and others are capable of delivering high-resolution multispectral two-dimensional and three-dimensional image data; usually this multispectral data is available in form of n separate image files with each showing one element or other singular aspect of the sample. There is high need for digital image processing methods enabling the analytical scientist, confronted with such amounts of data routinely, to get rapid insight into the composition of the sample examined, to filter the relevant data and to integrate the information of numerous separate multispectral images to get the complete picture. Sophisticated image processing methods like classification and fusion provide possible solution approaches to this challenge. Classification is a treatment by multivariate statistical means in order to extract analytical information. Image fusion on the other hand denotes a process where images obtained from various sensors or at different moments of time are combined together to provide a more complete picture of a scene or object under investigation. Both techniques are important for the task of information extraction and integration and often one technique depends on the other. Therefore overall aim of this thesis is to evaluate the possibilities of both techniques regarding the task of analytical image processing and to find solutions for the integration and condensation of multispectral analytical image data in order to facilitate the interpretation of the enormous amounts of data routinely acquired by modern physical analysis instruments. (author)

Online Multi-Spectral Meat Inspection

DEFF Research Database (Denmark)

Nielsen, Jannik Boll; Larsen, Anders Boesen Lindbo

2013-01-01

We perform an explorative study on multi-spectral image data from a prototype device developed for fast online quality inspection of meat products. Because the camera setup is built for speed, we sacrifice exact pixel correspondences between the different bands of the multi-spectral images. Our...... work is threefold as we 1) investigate the color distributions and construct a model to describe pork loins, 2) classify the different components in pork loins (meat, fat, membrane), and 3) detect foreign objects on the surface of pork loins. Our investigation shows that the color distributions can...

H31G-1596: DeepSAT's CloudCNN: A Deep Neural Network for Rapid Cloud Detection from Geostationary Satellites

Science.gov (United States)

Kalia, Subodh; Ganguly, Sangram; Li, Shuang; Nemani, Ramakrishna R.

2017-01-01

Cloud and cloud shadow detection has important applications in weather and climate studies. It is even more crucial when we introduce geostationary satellites into the field of terrestrial remote sensing. With the challenges associated with data acquired in very high frequency (10-15 mins per scan), the ability to derive an accurate cloud shadow mask from geostationary satellite data is critical. The key to the success for most of the existing algorithms depends on spatially and temporally varying thresholds,which better capture local atmospheric and surface effects.However, the selection of proper threshold is difficult and may lead to erroneous results. In this work, we propose a deep neural network based approach called CloudCNN to classify cloudshadow from Himawari-8 AHI and GOES-16 ABI multispectral data. DeepSAT's CloudCNN consists of an encoderdecoder based architecture for binary-class pixel wise segmentation. We train CloudCNN on multi-GPU Nvidia Devbox cluster, and deploy the prediction pipeline on NASA Earth Exchange (NEX) Pleiades supercomputer. We achieved an overall accuracy of 93.29% on test samples. Since, the predictions take only a few seconds to segment a full multispectral GOES-16 or Himawari-8 Full Disk image, the developed framework can be used for real-time cloud detection, cyclone detection, or extreme weather event predictions.

Color enhancement in multispectral image of human skin

Science.gov (United States)

Mitsui, Masanori; Murakami, Yuri; Obi, Takashi; Yamaguchi, Masahiro; Ohyama, Nagaaki

2003-07-01

Multispectral imaging is receiving attention in medical color imaging, as high-fidelity color information can be acquired by the multispectral image capturing. On the other hand, as color enhancement in medical color image is effective for distinguishing lesion from normal part, we apply a new technique for color enhancement using multispectral image to enhance the features contained in a certain spectral band, without changing the average color distribution of original image. In this method, to keep the average color distribution, KL transform is applied to spectral data, and only high-order KL coefficients are amplified in the enhancement. Multispectral images of human skin of bruised arm are captured by 16-band multispectral camera, and the proposed color enhancement is applied. The resultant images are compared with the color images reproduced assuming CIE D65 illuminant (obtained by natural color reproduction technique). As a result, the proposed technique successfully visualizes unclear bruised lesions, which are almost invisible in natural color images. The proposed technique will provide support tool for the diagnosis in dermatology, visual examination in internal medicine, nursing care for preventing bedsore, and so on.

Multispectral Thermal Imagery and Its Application to the Geologic Mapping of the Koobi Fora Formation, Northwestern Kenya

Energy Technology Data Exchange (ETDEWEB)

Green, Mary K. [Univ. of New Mexico, Albuquerque, NM (United States)

2005-12-01

The Koobi Fora Formation in northwestern Kenya has yielded more hominin fossils dated between 2.1 and 1.2 Ma than any other location on Earth. This research was undertaken to discover the spectral signatures of a portion of the Koobi Fora Formation using imagery from the DOE's Multispectral Thermal Imager (MTI) satellite. Creation of a digital geologic map from MTI imagery was a secondary goal of this research. MTI is unique amongst multispectral satellites in that it co-collects data from 15 spectral bands ranging from the visible to the thermal infrared with a ground sample distance of 5 meters per pixel in the visible and 20 meters in the infrared. The map was created in two stages. The first was to correct the base MTI image using spatial accuracy assessment points collected in the field. The second was to mosaic various MTI images together to create the final Koobi Fora map. Absolute spatial accuracy of the final map product is 73 meters. The geologic classification of the Koobi Fora MTI map also took place in two stages. The field work stage involved location of outcrops of different lithologies within the Koobi Fora Formation. Field descriptions of these outcrops were made and their locations recorded. During the second stage, a linear spectral unmixing algorithm was applied to the MTI mosaic. In order to train the linear spectra unmixing algorithm, regions of interest representing four different classes of geologic material (tuff, alluvium, carbonate, and basalt), as well as a vegetation class were defined within the MTI mosaic. The regions of interest were based upon the aforementioned field data as well as overlays of geologic maps from the 1976 Iowa State mapping project. Pure spectra were generated for each class from the regions of interest, and then the unmixing algorithm classified each pixel according to relative percentage of classes found within the pixel based upon the pure spectra values. A total of four unique combinations of geologic

Demonstration of wetland vegetation mapping in Florida from computer-processed satellite and aircraft multispectral scanner data

Science.gov (United States)

Butera, M. K.

1979-01-01

The success of remotely mapping wetland vegetation of the southwestern coast of Florida is examined. A computerized technique to process aircraft and LANDSAT multispectral scanner data into vegetation classification maps was used. The cost effectiveness of this mapping technique was evaluated in terms of user requirements, accuracy, and cost. Results indicate that mangrove communities are classified most cost effectively by the LANDSAT technique, with an accuracy of approximately 87 percent and with a cost of approximately 3 cent per hectare compared to $46.50 per hectare for conventional ground survey methods.

JPSS Preparations at the Satellite Proving Ground for Marine, Precipitation, and Satellite Analysis

Science.gov (United States)

Folmer, M. J.; Berndt, E.; Clark, J.; Orrison, A.; Kibler, J.; Sienkiewicz, J. M.; Nelson, J. A., Jr.; Goldberg, M.

2016-12-01

The National Oceanic and Atmospheric Administration (NOAA) Satellite Proving Ground (PG) for Marine, Precipitation, and Satellite Analysis (MPS) has been demonstrating and evaluating Suomi National Polar-orbiting Partnership (S-NPP) products along with other polar-orbiting satellite platforms in preparation for the Joint Polar Satellite System - 1 (JPSS-1) launch in March 2017. The first S-NPP imagery was made available to the MPS PG during the evolution of Hurricane Sandy in October 2012 and has since been popular in operations. Since this event the MPS PG Satellite Liaison has been working with forecasters on ways to integrate single-channel and multispectral imagery from the Visible Infrared Imaging Radiometer Suite (VIIRS), the Moderate Resolution Imaging Spectroradiometer (MODIS), and the Advanced Very High Resolution Radiometer (AVHRR)into operations to complement numerical weather prediction and geostationary satellite savvy National Weather Service (NWS) National Centers. Additional unique products have been introduced to operations to address specific forecast challenges, including the Cooperative Institute for Research in the Atmosphere (CIRA) Layered Precipitable Water, the National Environmental Satellite, Data, and Information Service (NESDIS) Snowfall Rate product, NOAA Unique Combined Atmospheric Processing System (NUCAPS) Soundings, ozone products from the Atmospheric Infrared Sounder (AIRS), Cross-track Infrared Sounder/Advanced Technology Microwave Sounder (CrIS/ATMS), and Infrared Atmospheric Sounding Interferometer (IASI). In addition, new satellite domains have been created to provide forecasters at the NWS Ocean Prediction Center and Weather Prediction Center with better quality imagery at high latitudes. This has led to research projects that are addressing forecast challenges such as tropical to extratropical transition and explosive cyclogenesis. This presentation will provide examples of how the MPS PG has been introducing and integrating

Satellite Monitoring of Accumulation of Strain in the Earth's Crust Related to Seismic and Volcanic Activity

Science.gov (United States)

Arellano-Baeza, A. A.

2009-12-01

Our studies have shown that the strain energy accumulation deep in the Earth’s crust that precedes seismic and volcanic activity 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 magnitude > 4 Mw, 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.

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

Science.gov (United States)

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.

Multispectral colormapping using penalized least square regression

DEFF Research Database (Denmark)

Dissing, Bjørn Skovlund; Carstensen, Jens Michael; Larsen, Rasmus

2010-01-01

The authors propose a novel method to map a multispectral image into the device independent color space CIE-XYZ. This method provides a way to visualize multispectral images by predicting colorvalues from spectral values while maintaining interpretability and is tested on a light emitting diode...... that the interpretability improves significantly but comes at the cost of slightly worse predictability....

A methodology for calibration of hyperspectral and multispectral satellite data in coastal areas

Science.gov (United States)

Pennucci, Giuliana; Fargion, Giulietta; Alvarez, Alberto; Trees, Charles; Arnone, Robert

2012-06-01

The objective of this work is to determine the location(s) in any given oceanic area during different temporal periods where in situ sampling for Calibration/Validation (Cal/Val) provides the best capability to retrieve accurate radiometric and derived product data (lowest uncertainties). We present a method to merge satellite imagery with in situ measurements, to determine the best in situ sampling strategy suitable for satellite Cal/Val and to evaluate the present in situ locations through uncertainty indices. This analysis is required to determine if the present in situ sites are adequate for assessing uncertainty and where additional sites and ship programs should be located to improve Calibration/Validation (Cal/Val) procedures. Our methodology uses satellite acquisitions to build a covariance matrix encoding the spatial-temporal variability of the area of interest. The covariance matrix is used in a Bayesian framework to merge satellite and in situ data providing a product with lower uncertainty. The best in situ location for Cal/Val is then identified by using a design principle (A-optimum design) that looks for minimizing the estimated variance of the merged products. Satellite products investigated in this study include Ocean Color water leaving radiance, chlorophyll, and inherent and apparent optical properties (retrieved from MODIS and VIIRS). In situ measurements are obtained from systems operated on fixed deployment platforms (e.g., sites of the Ocean Color component of the AErosol RObotic NETwork- AERONET-OC), moorings (e.g, Marine Optical Buoy-MOBY), ships or autonomous vehicles (such as Autonomous Underwater Vehicles and/or Gliders).

Ground test of satellite constellation based quantum communication

OpenAIRE

Liao, Sheng-Kai; Yong, Hai-Lin; Liu, Chang; Shentu, Guo-Liang; Li, Dong-Dong; Lin, Jin; Dai, Hui; Zhao, Shuang-Qiang; Li, Bo; Guan, Jian-Yu; Chen, Wei; Gong, Yun-Hong; Li, Yang; Lin, Ze-Hong; Pan, Ge-Sheng

2016-01-01

Satellite based quantum communication has been proven as a feasible way to achieve global scale quantum communication network. Very recently, a low-Earth-orbit (LEO) satellite has been launched for this purpose. However, with a single satellite, it takes an inefficient 3-day period to provide the worldwide connectivity. On the other hand, similar to how the Iridium system functions in classic communication, satellite constellation (SC) composed of many quantum satellites, could provide global...

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

Science.gov (United States)

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 (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).

Assessing exergy of forest ecosystem using airborne and satellite data

Science.gov (United States)

Brovkina, Olga; Fabianek, Tomas; Lukes, Petr; Zemek, Frantisek

2017-04-01

Interactions of the energy flows of forest ecosystem with environment are formed by a suite of forest structure, functions and pathways of self-control. According to recent thermodynamic theory for open systems, concept of exergy of solar radiation has been applied to estimate energy consumptions on evapotranspiration and biomass production in forest ecosystem or to indicate forest decline and human land use impact on ecosystem stability. However, most of the methods for exergy estimation in forest ecosystem is not stable and its physical meaning remains on the surface. This study was aimed to contribute to understanding the exergy of forest ecosystem using combination of remote sensing (RS) and eddy covariance technologies, specifically: 1/to explore exergy of solar radiation depending on structure of solar spectrum (number of spectral bands of RS data), and 2/to explore the relationship between exergy and flux tower eddy covariance measurements. Two study forest sites were located in Western Beskids in the Czech Republic. The first site was dominated by young Norway spruce, the second site was dominated by mature European beech. Airborne hyperspectral data in VNIR, SWIR and TIR spectral regions were acquired 9 times for study sites during a vegetation periods in 2015-2016. Radiometric, geometric and atmospheric corrections of airborne data were performed. Satellite multispectral Landsat-8 cloud-free 21 scenes were downloaded and atmospherically corrected for the period from April to November 2015-2016. Evapotranspiration and latent heat fluxes were collected from operating flux towers located on study sites according to date and time of remote sensing data acquisition. Exergy was calculated for each satellite and airborne scene using various combinations of spectral bands as: Ex=E^out (K+ln E^out/E^in )+R, where Ein is the incoming solar energy, Eout is the reflected solar energy, R = Ein-Eout is absorbed energy, Eout/Ein is albedo and K is the Kullback increment

Validation of an Innovative Satellite-Based UV Dosimeter

Science.gov (United States)

Morelli, Marco; Masini, Andrea; Simeone, Emilio; Khazova, Marina

2016-08-01

We present an innovative satellite-based UV (ultraviolet) radiation dosimeter with a mobile app interface that has been validated by exploiting both ground-based measurements and an in-vivo assessment of the erythemal effects on some volunteers having a controlled exposure to solar radiation.Both validations showed that the satellite-based UV dosimeter has a good accuracy and reliability needed for health-related applications.The app with this satellite-based UV dosimeter also includes other related functionalities such as the provision of safe sun exposure time updated in real-time and end exposure visual/sound alert. This app will be launched on the global market by siHealth Ltd in May 2016 under the name of "HappySun" and available both for Android and for iOS devices (more info on http://www.happysun.co.uk).Extensive R&D activities are on-going for further improvement of the satellite-based UV dosimeter's accuracy.

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

Science.gov (United States)

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.

Design and fabrication of multispectral optics using expanded glass map

Science.gov (United States)

Bayya, Shyam; Gibson, Daniel; Nguyen, Vinh; Sanghera, Jasbinder; Kotov, Mikhail; Drake, Gryphon; Deegan, John; Lindberg, George

2015-06-01

As the desire to have compact multispectral imagers in various DoD platforms is growing, the dearth of multispectral optics is widely felt. With the limited number of material choices for optics, these multispectral imagers are often very bulky and impractical on several weight sensitive platforms. To address this issue, NRL has developed a large set of unique infrared glasses that transmit from 0.9 to > 14 μm in wavelength and expand the glass map for multispectral optics with refractive indices from 2.38 to 3.17. They show a large spread in dispersion (Abbe number) and offer some unique solutions for multispectral optics designs. The new NRL glasses can be easily molded and also fused together to make bonded doublets. A Zemax compatible glass file has been created and is available upon request. In this paper we present some designs, optics fabrication and imaging, all using NRL materials.

Multispectral embedding-based deep neural network for three-dimensional human pose recovery

Science.gov (United States)

Yu, Jialin; Sun, Jifeng

2018-01-01

Monocular image-based three-dimensional (3-D) human pose recovery aims to retrieve 3-D poses using the corresponding two-dimensional image features. Therefore, the pose recovery performance highly depends on the image representations. We propose a multispectral embedding-based deep neural network (MSEDNN) to automatically obtain the most discriminative features from multiple deep convolutional neural networks and then embed their penultimate fully connected layers into a low-dimensional manifold. This compact manifold can explore not only the optimum output from multiple deep networks but also the complementary properties of them. Furthermore, the distribution of each hierarchy discriminative manifold is sufficiently smooth so that the training process of our MSEDNN can be effectively implemented only using few labeled data. Our proposed network contains a body joint detector and a human pose regressor that are jointly trained. Extensive experiments conducted on four databases show that our proposed MSEDNN can achieve the best recovery performance compared with the state-of-the-art methods.

A Space Based Solar Power Satellite System

Science.gov (United States)

Engel, J. M.; Polling, D.; Ustamujic, F.; Yaldiz, R.; et al.

2002-01-01

(SPoTS) supplying other satellites with energy. SPoTS is due to be commercially viable and operative in 2020. of Technology designed the SPoTS during a full-time design period of six weeks as a third year final project. The team, organized according to the principles of systems engineering, first conducted a literature study on space wireless energy transfer to select the most suitable candidates for use on the SPoTS. After that, several different system concepts have been generated and evaluated, the most promising concept being worked out in greater detail. km altitude. Each SPoTS satellite has a 50m diameter inflatable solar collector that focuses all received sunlight. Then, the received sunlight is further redirected by means of four pointing mirrors toward four individual customer satellites. A market-analysis study showed, that providing power to geo-stationary communication satellites during their eclipse would be most beneficial. At arrival at geo-stationary orbit, the focused beam has expended to such an extent that its density equals one solar flux. This means that customer satellites can continue to use their regular solar arrays during their eclipse for power generation, resulting in a satellite battery mass reduction. the customer satellites in geo-stationary orbit, the transmitted energy beams needs to be pointed with very high accuracy. Computations showed that for this degree of accuracy, sensors are needed, which are not mainstream nowadays. Therefore further research must be conducted in this area in order to make these high-accuracy-pointing systems commercially attractive for use on the SPoTS satellites around 2020. Total 20-year system lifetime cost for 18 SPoT satellites are estimated at approximately USD 6 billion [FY2001]. In order to compete with traditional battery-based satellite power systems or possible ground based wireless power transfer systems the price per kWh for the customer must be significantly lower than the present one

Reproducible high-resolution multispectral image acquisition in dermatology

Science.gov (United States)

Duliu, Alexandru; Gardiazabal, José; Lasser, Tobias; Navab, Nassir

2015-07-01

Multispectral image acquisitions are increasingly popular in dermatology, due to their improved spectral resolution which enables better tissue discrimination. Most applications however focus on restricted regions of interest, imaging only small lesions. In this work we present and discuss an imaging framework for high-resolution multispectral imaging on large regions of interest.

Multi Texture Analysis of Colorectal Cancer Continuum Using Multispectral Imagery.

Directory of Open Access Journals (Sweden)

Ahmad Chaddad

Full Text Available This paper proposes to characterize the continuum of colorectal cancer (CRC using multiple texture features extracted from multispectral optical microscopy images. Three types of pathological tissues (PT are considered: benign hyperplasia, intraepithelial neoplasia and carcinoma.In the proposed approach, the region of interest containing PT is first extracted from multispectral images using active contour segmentation. This region is then encoded using texture features based on the Laplacian-of-Gaussian (LoG filter, discrete wavelets (DW and gray level co-occurrence matrices (GLCM. To assess the significance of textural differences between PT types, a statistical analysis based on the Kruskal-Wallis test is performed. The usefulness of texture features is then evaluated quantitatively in terms of their ability to predict PT types using various classifier models.Preliminary results show significant texture differences between PT types, for all texture features (p-value < 0.01. Individually, GLCM texture features outperform LoG and DW features in terms of PT type prediction. However, a higher performance can be achieved by combining all texture features, resulting in a mean classification accuracy of 98.92%, sensitivity of 98.12%, and specificity of 99.67%.These results demonstrate the efficiency and effectiveness of combining multiple texture features for characterizing the continuum of CRC and discriminating between pathological tissues in multispectral images.

Sentinel-2: next generation satellites for optical land observation from space

Science.gov (United States)

Lautenschläger, G.; Gessner, R.; Gockel, W.; Haas, C.; Schweickert, G.; Bursch, S.; Welsch, M.; Sontag, H.

2013-10-01

The first Sentinel-2 satellites, which constitute the next generation of operational Earth observation satellites for optical land monitoring from space, are undergoing completion in the facilities at Astrium ready for launch end 2014. Sentinel-2 will feature a major breakthrough in the area of optical land observation since it will for the first time enable continuous and systematic acquisition of all land surfaces world-wide with the Multi-Spectral Instrument (MSI), thus providing the basis for a truly operational service. Flying in the same orbital plane and spaced at 180°, the constellation of two satellites, designed for an in-orbit nominal operational lifetime of 7 years each, will acquire all land surfaces in only 5 days at the equator. In order to support emergency operations, the satellites can further be operated in an extended observation mode allowing to image any point on Earth even on a daily basis. MSI acquires images in 13 spectral channels from Visible-to-Near Infrared (VNIR) to Short Wave Infrared (SWIR) with a swath of almost 300 km on ground and a spatial resolution up to 10 m. The data ensure continuity to the existing data sets produced by the series of Landsat and SPOT satellites, and will further provide detailed spectral information to enable derivation of biophysical or geophysical products. Excellent geometric image quality performances are achieved with geolocation better than 16 m, thanks to an innovative instrument design in conjunction with a high-performance satellite AOCS subsystem centered around a 2-band GPS receiver, high-performance star trackers and a fiberoptic gyro. To cope with the high data volume on-board, data are compressed using a state-of-the-art wavelet compression scheme. Thanks to a powerful mission data handling system built around a newly developed very large solid-state mass memory based on flash technology, on-board compression losses will be kept to a minimum. The Sentinel-2 satellite design features a highly

Multispectral Imaging for Determination of Astaxanthin Concentration in Salmonids

DEFF Research Database (Denmark)

Dissing, Bjørn Skovlund; Nielsen, Michael Engelbrecht; Ersbøll, Bjarne Kjær

2011-01-01

Multispectral imaging has been evaluated for characterization of the concentration of a specific cartenoid pigment; astaxanthin. 59 fillets of rainbow trout, Oncorhynchus mykiss, were filleted and imaged using a rapid multispectral imaging device for quantitative analysis. The multispectral imaging...... device captures reflection properties in 19 distinct wavelength bands, prior to determination of the true concentration of astaxanthin. The samples ranged from 0.20 to 4.34 mu g per g fish. A PLSR model was calibrated to predict astaxanthin concentration from novel images, and showed good results...... concentration in rainbow trout fillets....

Compact multispectral photodiode arrays using micropatterned dichroic filters

Science.gov (United States)

Chandler, Eric V.; Fish, David E.

2014-05-01

The next generation of multispectral instruments requires significant improvements in both spectral band customization and portability to support the widespread deployment of application-specific optical sensors. The benefits of spectroscopy are well established for numerous applications including biomedical instrumentation, industrial sorting and sensing, chemical detection, and environmental monitoring. In this paper, spectroscopic (and by extension hyperspectral) and multispectral measurements are considered. The technology, tradeoffs, and application fits of each are evaluated. In the majority of applications, monitoring 4-8 targeted spectral bands of optimized wavelength and bandwidth provides the necessary spectral contrast and correlation. An innovative approach integrates precision spectral filters at the photodetector level to enable smaller sensors, simplify optical designs, and reduce device integration costs. This method supports user-defined spectral bands to create application-specific sensors in a small footprint with scalable cost efficiencies. A range of design configurations, filter options and combinations are presented together with typical applications ranging from basic multi-band detection to stringent multi-channel fluorescence measurement. An example implementation packages 8 narrowband silicon photodiodes into a 9x9mm ceramic LCC (leadless chip carrier) footprint. This package is designed for multispectral applications ranging from portable color monitors to purpose- built OEM industrial and scientific instruments. Use of an eight-channel multispectral photodiode array typically eliminates 10-20 components from a device bill-of-materials (BOM), streamlining the optical path and shrinking the footprint by 50% or more. A stepwise design approach for multispectral sensors is discussed - including spectral band definition, optical design tradeoffs and constraints, and device integration from prototype through scalable volume production

Semiconductor Laser Multi-Spectral Sensing and Imaging

Directory of Open Access Journals (Sweden)

Han Q. Le

2010-01-01

Full Text Available 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.

Semiconductor laser multi-spectral sensing and imaging.

Science.gov (United States)

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.

Multispectral and polarimetric photodetection using a plasmonic metasurface

Science.gov (United States)

Pelzman, Charles; Cho, Sang-Yeon

2018-01-01

We present a metasurface-integrated Si 2-D CMOS sensor array for multispectral and polarimetric photodetection applications. The demonstrated sensor is based on the polarization selective extraordinary optical transmission from periodic subwavelength nanostructures, acting as artificial atoms, known as meta-atoms. The meta-atoms were created by patterning periodic rectangular apertures that support optical resonance at the designed spectral bands. By spatially separating meta-atom clusters with different lattice constants and orientations, the demonstrated metasurface can convert the polarization and spectral information of an optical input into a 2-D intensity pattern. As a proof-of-concept experiment, we measured the linear components of the Stokes parameters directly from captured images using a CMOS camera at four spectral bands. Compared to existing multispectral polarimetric sensors, the demonstrated metasurface-integrated CMOS system is compact and does not require any moving components, offering great potential for advanced photodetection applications.

Satellite-based Flood Modeling Using TRMM-based Rainfall Products

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Greg Easson

2007-12-01

Full Text Available Increasingly available and a virtually uninterrupted supply of satellite-estimatedrainfall data is gradually becoming a cost-effective source of input for flood predictionunder a variety of circumstances. However, most real-time and quasi-global satelliterainfall products are currently available at spatial scales ranging from 0.25o to 0.50o andhence, are considered somewhat coarse for dynamic hydrologic modeling of basin-scaleflood events. This study assesses the question: what are the hydrologic implications ofuncertainty of satellite rainfall data at the coarse scale? We investigated this question onthe 970 km2 Upper Cumberland river basin of Kentucky. The satellite rainfall productassessed was NASA’s Tropical Rainfall Measuring Mission (TRMM Multi-satellitePrecipitation Analysis (TMPA product called 3B41RT that is available in pseudo real timewith a latency of 6-10 hours. We observed that bias adjustment of satellite rainfall data canimprove application in flood prediction to some extent with the trade-off of more falsealarms in peak flow. However, a more rational and regime-based adjustment procedureneeds to be identified before the use of satellite data can be institutionalized among floodmodelers.

Leo satellite-based telecommunication network concepts

Science.gov (United States)

Aiken, John G.; Swan, Peter A.; Leopold, Ray J.

1991-01-01

Design considerations are discussed for Low Earth Orbit (LEO) satellite based telecommunications networks. The satellites are assumed to be connected to each other via intersatellite links. They are connected to the end user either directly or through gateways to other networks. Frequency reuse, circuit switching, packet switching, call handoff, and routing for these systems are discussed by analogy with terrestrial cellular (mobile radio) telecommunication systems.

Fine-tuning satellite-based rainfall estimates

Science.gov (United States)

Harsa, Hastuadi; Buono, Agus; Hidayat, Rahmat; Achyar, Jaumil; Noviati, Sri; Kurniawan, Roni; Praja, Alfan S.

2018-05-01

Rainfall datasets are available from various sources, including satellite estimates and ground observation. The locations of ground observation scatter sparsely. Therefore, the use of satellite estimates is advantageous, because satellite estimates can provide data on places where the ground observations do not present. However, in general, the satellite estimates data contain bias, since they are product of algorithms that transform the sensors response into rainfall values. Another cause may come from the number of ground observations used by the algorithms as the reference in determining the rainfall values. This paper describe the application of bias correction method to modify the satellite-based dataset by adding a number of ground observation locations that have not been used before by the algorithm. The bias correction was performed by utilizing Quantile Mapping procedure between ground observation data and satellite estimates data. Since Quantile Mapping required mean and standard deviation of both the reference and the being-corrected data, thus the Inverse Distance Weighting scheme was applied beforehand to the mean and standard deviation of the observation data in order to provide a spatial composition of them, which were originally scattered. Therefore, it was possible to provide a reference data point at the same location with that of the satellite estimates. The results show that the new dataset have statistically better representation of the rainfall values recorded by the ground observation than the previous dataset.

UAV MULTISPECTRAL SURVEY TO MAP SOIL AND CROP FOR PRECISION FARMING APPLICATIONS

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G. Sona

2016-06-01

Full Text Available New sensors mounted on UAV and optimal procedures for survey, data acquisition and analysis are continuously developed and tested for applications in precision farming. Procedures to integrate multispectral aerial data about soil and crop and ground-based proximal geophysical data are a recent research topic aimed to delineate homogeneous zones for the management of agricultural inputs (i.e., water, nutrients. Multispectral and multitemporal orthomosaics were produced over a test field (a 100 m x 200 m plot within a maize field, to map vegetation and soil indices, as well as crop heights, with suitable ground resolution. UAV flights were performed in two moments during the crop season, before sowing on bare soil, and just before flowering when maize was nearly at the maximum height. Two cameras, for color (RGB and false color (NIR-RG images, were used. The images were processed in Agisoft Photoscan to produce Digital Surface Model (DSM of bare soil and crop, and multispectral orthophotos. To overcome some difficulties in the automatic searching of matching points for the block adjustment of the crop image, also the scientific software developed by Politecnico of Milan was used to enhance images orientation. Surveys and image processing are described, as well as results about classification of multispectral-multitemporal orthophotos and soil indices.

Radiometric calibration of the reflective bands of NS001-Thematic Mapper Simulator (TMS) and modular multispectral radiometers (MMR)

Science.gov (United States)

Markham, Brian L.; Wood, Frank M., Jr.; Ahmad, Suraiya P.

1988-01-01

The NS001 Thematic Mapper Simulator scanner (TMS) and several modular multispectral radiometers (MMRs) are among the primary instruments used in the First ISLSCP (International Satellite Land Surface Climatology Project) Field Experiment (FIFE). The NS001 has a continuously variable gain setting. Calibration of the NS001 data is influenced by drift in the dark current level of up to six counts during a mirror scan at typical gain settings. The MMR instruments are being used in their 1 deg FOV configuration on the helicopter and 15 deg FOV on the ground.

Multispectral x-ray CT: multivariate statistical analysis for efficient reconstruction

DEFF Research Database (Denmark)

Kheirabadi, Mina; Mustafa, Wail; Lyksborg, Mark

2017-01-01

Recent developments in multispectral X-ray detectors allow for an efficient identification of materials based on their chemical composition. This has a range of applications including security inspection, which is our motivation. In this paper, we analyze data from a tomographic setup employing...

A Multispectral Photon-Counting Double Random Phase Encoding Scheme for Image Authentication

Directory of Open Access Journals (Sweden)

Faliu Yi

2014-05-01

Full Text Available In this paper, we propose a new method for color image-based authentication that combines multispectral photon-counting imaging (MPCI and double random phase encoding (DRPE schemes. The sparsely distributed information from MPCI and the stationary white noise signal from DRPE make intruder attacks difficult. In this authentication method, the original multispectral RGB color image is down-sampled into a Bayer image. The three types of color samples (red, green and blue color in the Bayer image are encrypted with DRPE and the amplitude part of the resulting image is photon counted. The corresponding phase information that has nonzero amplitude after photon counting is then kept for decryption. Experimental results show that the retrieved images from the proposed method do not visually resemble their original counterparts. Nevertheless, the original color image can be efficiently verified with statistical nonlinear correlations. Our experimental results also show that different interpolation algorithms applied to Bayer images result in different verification effects for multispectral RGB color images.

A multispectral photon-counting double random phase encoding scheme for image authentication.

Science.gov (United States)

Yi, Faliu; Moon, Inkyu; Lee, Yeon H

2014-05-20

In this paper, we propose a new method for color image-based authentication that combines multispectral photon-counting imaging (MPCI) and double random phase encoding (DRPE) schemes. The sparsely distributed information from MPCI and the stationary white noise signal from DRPE make intruder attacks difficult. In this authentication method, the original multispectral RGB color image is down-sampled into a Bayer image. The three types of color samples (red, green and blue color) in the Bayer image are encrypted with DRPE and the amplitude part of the resulting image is photon counted. The corresponding phase information that has nonzero amplitude after photon counting is then kept for decryption. Experimental results show that the retrieved images from the proposed method do not visually resemble their original counterparts. Nevertheless, the original color image can be efficiently verified with statistical nonlinear correlations. Our experimental results also show that different interpolation algorithms applied to Bayer images result in different verification effects for multispectral RGB color images.

Volcanic SO2 fluxes derived from satellite data: a survey using OMI, GOME-2, IASI and MODIS

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N. Theys

2013-06-01

Full Text Available Sulphur dioxide (SO2 fluxes of active degassing volcanoes are routinely measured with ground-based equipment to characterize and monitor volcanic activity. SO2 of unmonitored volcanoes or from explosive volcanic eruptions, can be measured with satellites. However, remote-sensing methods based on absorption spectroscopy generally provide integrated amounts of already dispersed plumes of SO2 and satellite derived flux estimates are rarely reported. Here we review a number of different techniques to derive volcanic SO2 fluxes using satellite measurements of plumes of SO2 and investigate the temporal evolution of the total emissions of SO2 for three very different volcanic events in 2011: Puyehue-Cordón Caulle (Chile, Nyamulagira (DR Congo and Nabro (Eritrea. High spectral resolution satellite instruments operating both in the ultraviolet-visible (OMI/Aura and GOME-2/MetOp-A and thermal infrared (IASI/MetOp-A spectral ranges, and multispectral satellite instruments operating in the thermal infrared (MODIS/Terra-Aqua are used. We show that satellite data can provide fluxes with a sampling of a day or less (few hours in the best case. Generally the flux results from the different methods are consistent, and we discuss the advantages and weaknesses of each technique. Although the primary objective of this study is the calculation of SO2 fluxes, it also enables us to assess the consistency of the SO2 products from the different sensors used.

Lattice algebra approach to multispectral analysis of ancient documents.

Science.gov (United States)

Valdiviezo-N, Juan C; Urcid, Gonzalo

2013-02-01

This paper introduces a lattice algebra procedure that can be used for the multispectral analysis of historical documents and artworks. Assuming the presence of linearly mixed spectral pixels captured in a multispectral scene, the proposed method computes the scaled min- and max-lattice associative memories to determine the purest pixels that best represent the spectra of single pigments. The estimation of fractional proportions of pure spectra at each image pixel is used to build pigment abundance maps that can be used for subsequent restoration of damaged parts. Application examples include multispectral images acquired from the Archimedes Palimpsest and a Mexican pre-Hispanic codex.

Changes of glacier, glacier-fed rivers and lakes in Altai Tavan Bogd National Park, Western Mongolia, based on multispectral satellite data from 1990 to 2017

Science.gov (United States)

Batsaikhan, B.; Lkhamjav, O.; Batsaikhan, N.

2017-12-01

Impacts on glaciers and water resource management have been altering through climate changes in Mongolia territory characterized by dry and semi-arid climate with low precipitation. Melting glaciers are early indicators of climate change unlike the response of the forests which is slower and takes place over a long period of time. Mountain glaciers are important environmental components of local, regional, and global hydrological cycles. The study calculates an overview of changes for glacier, glacier-fed rivers and lakes in Altai Tavan Bogd mountain, the Western Mongolia, based on the indexes of multispectral data and the methods typically applied in glacier studies. Were utilized an integrated approach of Normalized Difference Snow Index (NDSI) and Normalized Difference Water Index (NDWI) to combine Landsat, MODIS imagery and digital elevation model, to identify glacier cover are and quantify water storage change in lakes, and compared that with and climate parameters including precipitation, land surface temperature, evaporation, moisture. Our results show that melts of glacier at the study area has contributed to significantly increase of water storage of lakes in valley of The Altai Tavan Bogd mountain. There is hydrologic connection that lake basin is directly fed by glacier meltwater.

Novel instrumentation of multispectral imaging technology for detecting tissue abnormity

Science.gov (United States)

Yi, Dingrong; Kong, Linghua

2012-10-01

Multispectral imaging is becoming a powerful tool in a wide range of biological and clinical studies by adding spectral, spatial and temporal dimensions to visualize tissue abnormity and the underlying biological processes. A conventional spectral imaging system includes two physically separated major components: a band-passing selection device (such as liquid crystal tunable filter and diffraction grating) and a scientific-grade monochromatic camera, and is expensive and bulky. Recently micro-arrayed narrow-band optical mosaic filter was invented and successfully fabricated to reduce the size and cost of multispectral imaging devices in order to meet the clinical requirement for medical diagnostic imaging applications. However the challenging issue of how to integrate and place the micro filter mosaic chip to the targeting focal plane, i.e., the imaging sensor, of an off-shelf CMOS/CCD camera is not reported anywhere. This paper presents the methods and results of integrating such a miniaturized filter with off-shelf CMOS imaging sensors to produce handheld real-time multispectral imaging devices for the application of early stage pressure ulcer (ESPU) detection. Unlike conventional multispectral imaging devices which are bulky and expensive, the resulting handheld real-time multispectral ESPU detector can produce multiple images at different center wavelengths with a single shot, therefore eliminates the image registration procedure required by traditional multispectral imaging technologies.

Utilization of Multispectral Images for Meat Color Measurements

DEFF Research Database (Denmark)

Trinderup, Camilla Himmelstrup; Dahl, Anders Lindbjerg; Carstensen, Jens Michael

2013-01-01

This short paper describes how the use of multispectral imaging for color measurement can be utilized in an efficient and descriptive way for meat scientists. The basis of the study is meat color measurements performed with a multispectral imaging system as well as with a standard colorimeter...... of color and color variance than what is obtained by the standard colorimeter....

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

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Shruti Khanna

2018-02-01

Full Text Available 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

Satellite Remote Sensing For Aluminum And Nickel Laterites

Science.gov (United States)

Henderson, Frederick B.; Penfield, Glen T.; Grubbs, Donald K.

1984-08-01

The new LANDSAT-4,-5/Thematic Mapper (TM) land observational satellite remote sensing systems are providing dramatically new and important short wave infrared (SWIR) data, which combined with Landsat's Multi-Spectral Scanner (MSS) visible (VIS), very near infrared (VNIR), and thermal infrared (TI) data greatly improves regional geological mapping on a global scale. The TM will significantly improve clay, iron oxide, aluminum, and nickel laterite mapping capabilities over large areas of the world. It will also improve the ability to discriminate vegetation stress and species distribution associated with lateritic environments. Nickel laterites on Gag Island, Indonesia are defined by MSS imagery. Satellite imagery of the Cape Bougainville and the Darling Range, Australia bauxite deposits show the potential use of MSS data for exploration and mining applications. Examples of satellite syn-thetic aperture radar (SAR) for Jamaica document the use of this method for bauxite exploration. Thematic Mapper data will be combined with the French SPOT satellite's high spatial resolution and stereoscopic digital data, and U.S., Japanese, European, and Canadian Synthetic Aperture Radar (SAR) data to assist with logistics, mine development, and environ-mental concerns associated with aluminum and nickel lateritic deposits worldwide.

Multispectral Imaging of Wok-Fried Vegetables

DEFF Research Database (Denmark)

Clemmensen, Line Katrine Harder; Dissing, Bjørn Skovlund; Hyldig, Grethe

2012-01-01

Quality control in the food industry is often performed by measuring various chemical compounds in the food involved. The authors propose an imaging concept for acquiring high-quality multispectral images to evaluate optical reflection changes in carrots and celeriac over a period of 14 days....... For comparison, sensory analysis was performed on the same samples. Prior to multispectral image recording, the vegetables were prefried and frozen at -30 °C for 4 months. During the 14 days of image recording, the vegetables were kept at +5 °C. In this period, surface changes and thereby reflectance properties...

Multi-Spectral Remote Sensing of Phytoplankton Pigment Absorption Properties in Cyanobacteria Bloom Waters: A Regional Example in the Western Basin of Lake Erie

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Guoqing Wang

2017-12-01

Full Text Available Phytoplankton pigments absorb sunlight for photosynthesis, protect the chloroplast from damage caused by excess light energy, and influence the color of the water. Some pigments act as bio-markers and are important for separation of phytoplankton functional types. Among many efforts that have been made to obtain information on phytoplankton pigments from bio-optical properties, Gaussian curves decomposed from phytoplankton absorption spectrum have been used to represent the light absorption of different pigments. We incorporated the Gaussian scheme into a semi-analytical model and obtained the Gaussian curves from remote sensing reflectance. In this study, a series of sensitivity tests were conducted to explore the potential of obtaining the Gaussian curves from multi-spectral satellite remote sensing. Results showed that the Gaussian curves can be retrieved with 35% or less mean unbiased absolute percentage differences from MEdium Resolution Imaging Spectrometer (MERIS and Moderate Resolution Imaging Spectroradiometer (MODIS-like sensors. Further, using Lake Erie as an example, the spatial distribution of chlorophyll a and phycocyanin concentrations were obtained from the Gaussian curves and used as metrics for the spatial extent of an intense cyanobacterial bloom occurred in Lake Erie in 2014. The seasonal variations of Gaussian absorption properties in 2011 were further obtained from MERIS imagery. This study shows that it is feasible to obtain Gaussian curves from multi-spectral satellite remote sensing data, and the obtained chlorophyll a and phycocyanin concentrations from these Gaussian peak heights demonstrated potential application to monitor harmful algal blooms (HABs and identification of phytoplankton groups from satellite ocean color remote sensing semi-analytically.

An Algorithm for Pedestrian Detection in Multispectral Image Sequences

Science.gov (United States)

Kniaz, V. V.; Fedorenko, V. V.

2017-05-01

The growing interest for self-driving cars provides a demand for scene understanding and obstacle detection algorithms. One of the most challenging problems in this field is the problem of pedestrian detection. Main difficulties arise from a diverse appearances of pedestrians. Poor visibility conditions such as fog and low light conditions also significantly decrease the quality of pedestrian detection. This paper presents a new optical flow based algorithm BipedDetet that provides robust pedestrian detection on a single-borad computer. The algorithm is based on the idea of simplified Kalman filtering suitable for realization on modern single-board computers. To detect a pedestrian a synthetic optical flow of the scene without pedestrians is generated using slanted-plane model. The estimate of a real optical flow is generated using a multispectral image sequence. The difference of the synthetic optical flow and the real optical flow provides the optical flow induced by pedestrians. The final detection of pedestrians is done by the segmentation of the difference of optical flows. To evaluate the BipedDetect algorithm a multispectral dataset was collected using a mobile robot.

Multispectral Microimager for Astrobiology

Science.gov (United States)

Sellar, R. Glenn; Farmer, Jack D.; Kieta, Andrew; Huang, Julie

2006-01-01

A primary goal of the astrobiology program is the search for fossil records. The astrobiology exploration strategy calls for the location and return of samples indicative of environments conducive to life, and that best capture and preserve biomarkers. Successfully returning samples from environments conducive to life requires two primary capabilities: (1) in situ mapping of the mineralogy in order to determine whether the desired minerals are present; and (2) nondestructive screening of samples for additional in-situ testing and/or selection for return to laboratories for more in-depth examination. Two of the most powerful identification techniques are micro-imaging and visible/infrared spectroscopy. The design and test results are presented from a compact rugged instrument that combines micro-imaging and spectroscopic capability to provide in-situ analysis, mapping, and sample screening capabilities. Accurate reflectance spectra should be a measure of reflectance as a function of wavelength only. Other compact multispectral microimagers use separate LEDs (light-emitting diodes) for each wavelength and therefore vary the angles of illumination when changing wavelengths. When observing a specularly-reflecting sample, this produces grossly inaccurate spectra due to the variation in the angle of illumination. An advanced design and test results are presented for a multispectral microimager which demonstrates two key advances relative to previous LED-based microimagers: (i) acquisition of actual reflectance spectra in which the flux is a function of wavelength only, rather than a function of both wavelength and illumination geometry; and (ii) increase in the number of spectral bands to eight bands covering a spectral range of 468 to 975 nm.

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

Science.gov (United States)

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.

From Pixels to Population Stress: Global Multispectral Remote Sensing for Vulnerable Communities

Science.gov (United States)

Prashad, L.; Kaplan, E.; Letouze, E.; Kirkpatrick, R.; Luengo-Oroz, M.; Christensen, P. R.

2011-12-01

The Arizona State University (ASU) School of Earth and Space Exploration's Mars Space Flight Facility (MSFF) and 100 Cities Project, in collaboration with the United Nations Global Pulse initiative are utilizing NASA multispectral satellite data to visualize and analyze socioeconomic characteristics and human activity in Uganda. The Global Pulse initiative is exploring how new kinds of real-time data and innovative technologies can be leveraged to detect early social impacts of slow-onset crisis and global shocks. Global Pulse is developing a framework for real-time monitoring, assembling an open-source toolkit for analyzing new kinds of data and establishing a global network of country-level "Pulse Labs" where governments, UN agencies, academia and the private sector learn together how to harness the new world of "big data" to protect the vulnerable with targeted and agile policy responses. The ASU MSFF and 100 Cities Project are coordinating with the Global Pulse team to utilize NASA remote sensing data in this effort. Human behavior and socioeconomic parameters have been successfully studied via proxy through remote sensing of the physical environment by measuring the growth of city boundaries and transportation networks, crop health, soil moisture, and slum development from visible and infrared imagery. The NASA/ NOAA image of Earth's "Lights at Night" is routinely used to estimate economic development and population density. There are many examples of the conventional uses of remote sensing in humanitarian-related projects including the Famine Early Warning System Network (FEWS NET) and the UN's operational satellite applications programme (UNOSAT), which provides remote sensing for humanitarian and disaster relief. Since the Global Pulse project is focusing on new, innovative uses of technology for early crisis detection, we are focusing on three non-conventional uses of satellite remote sensing to understand what role NASA multispectral satellites can play

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

Science.gov (United States)

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.

User Validation of VIIRS Satellite Imagery

Directory of Open Access Journals (Sweden)

Don Hillger

2015-12-01

Full Text Available Visible/Infrared Imaging Radiometer Suite (VIIRS Imagery from the Suomi National Polar-orbiting Partnership (S-NPP satellite is the finest spatial resolution (375 m multi-spectral imagery of any operational meteorological satellite to date. The Imagery environmental data record (EDR has been designated as a Key Performance Parameter (KPP for VIIRS, meaning that its performance is vital to the success of a series of Joint Polar Satellite System (JPSS satellites that will carry this instrument. Because VIIRS covers the high-latitude and Polar Regions especially well via overlapping swaths from adjacent orbits, the Alaska theatre in particular benefits from VIIRS more than lower-latitude regions. While there are no requirements that specifically address the quality of the EDR Imagery aside from the VIIRS SDR performance requirements, the value of VIIRS Imagery to operational users is an important consideration in the Cal/Val process. As such, engaging a wide diversity of users constitutes a vital part of the Imagery validation strategy. The best possible image quality is of utmost importance. This paper summarizes the Imagery Cal/Val Team’s quality assessment in this context. Since users are a vital component to the validation of VIIRS Imagery, specific examples of VIIRS imagery applied to operational needs are presented as an integral part of the post-checkout Imagery validation.

Airborne multispectral identification of individual cotton plants using consumer-grade cameras

Science.gov (United States)

Although multispectral remote sensing using consumer-grade cameras has successfully identified fields of small cotton plants, improvements to detection sensitivity are needed to identify individual or small clusters of plants. The imaging sensor of consumer-grade cameras are based on a Bayer patter...

Compression of Multispectral Images with Comparatively Few Bands Using Posttransform Tucker Decomposition

Directory of Open Access Journals (Sweden)

Jin Li

2014-01-01

Full Text Available Up to now, data compression for the multispectral charge-coupled device (CCD images with comparatively few bands (MSCFBs is done independently on each multispectral channel. This compression codec is called a “monospectral compressor.” The monospectral compressor does not have a removing spectral redundancy stage. To fill this gap, we propose an efficient compression approach for MSCFBs. In our approach, the one dimensional discrete cosine transform (1D-DCT is performed on spectral dimension to exploit the spectral information, and the posttransform (PT in 2D-DWT domain is performed on each spectral band to exploit the spatial information. A deep coupling approach between the PT and Tucker decomposition (TD is proposed to remove residual spectral redundancy between bands and residual spatial redundancy of each band. Experimental results on multispectral CCD camera data set show that the proposed compression algorithm can obtain a better compression performance and significantly outperforms the traditional compression algorithm-based TD in 2D-DWT and 3D-DCT domain.

Optical burst switching based satellite backbone network

Science.gov (United States)

Li, Tingting; Guo, Hongxiang; Wang, Cen; Wu, Jian

2018-02-01

We propose a novel time slot based optical burst switching (OBS) architecture for GEO/LEO based satellite backbone network. This architecture can provide high speed data transmission rate and high switching capacity . Furthermore, we design the control plane of this optical satellite backbone network. The software defined network (SDN) and network slice (NS) technologies are introduced. Under the properly designed control mechanism, this backbone network is flexible to support various services with diverse transmission requirements. Additionally, the LEO access and handoff management in this network is also discussed.

Inverse analysis of non-uniform temperature distributions using multispectral pyrometry

Science.gov (United States)

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.

Generation of seismic base map using satellite images in the southern deltaic area, People`s Republic of Bangladesh; Eisei data ni motozuku jishin tansa base map no sakusei (Bangladesh nanbu delta no rei)

Energy Technology Data Exchange (ETDEWEB)

Kotera, Y [Japan Energy Corp., Tokyo (Japan); Ochi, M [Nikko Exploration and Development Co. Ltd., Tokyo (Japan); Hato, M [Earth Remote Sensing Data Analysis Center, Tokyo (Japan)

1997-05-27

Assuming a two-dimensional seismic survey in a mangrove jungle in the southeast part of People`s Republic of Bangladesh and trially making a basemap for the survey plan from images of satellites such as LANDSAT, the paper considered the use and marginal use in the case of using satellite remote sensing for such a use field. When utilizing water channels in the mangrove jungle in the southwest of Bangladesh and using the seismic survey method for shallow sea, it is important to grasp the distribution of channels in the planning stage of the survey. Satellite remote sensing data are extremely important for knowing the wide-regional information including factors of hourly variations. In the area for this survey, for directly recognizing the channel, it is good only if the difference in reflectance between water and substances except water is indicated in the image because of flatness of the topography. There was seen few difference in accuracy between the passive multispectral image and the active SAR image which is sensitive to topographical changes. 2 figs.

Multispectral Panoramic Imaging System, Phase I

Data.gov (United States)

National Aeronautics and Space Administration — International Electronic Machines Corporation, a leader in the design of precision imaging systems, will develop an innovative multispectral, panoramic imaging...

High resolution satellite imagery : from spies to pipeline management

Energy Technology Data Exchange (ETDEWEB)

Adam, S. [Canadian Geomatic Solutions Ltd., Calgary, AB (Canada); Farrell, M. [TransCanada Transmission, Calgary, AB (Canada)

2000-07-01

The launch of Space Imaging's IKONOS satellite in September 1999 has opened the door for corridor applications. The technology has been successfully implemented by TransCanada PipeLines in mapping over 1500 km of their mainline. IKONOS is the world's first commercial high resolution satellite which collects data at 1-meter black/white and 4-meter multi-spectral. Its use is regulated by the U.S. government. It is the best source of high resolution satellite image data. Other sources include the Indian Space Agency's IRS-1 C/D satellite and the Russian SPIN-2 which provides less reliable coverage. In addition, two more high resolution satellites may be launched this year to provide imagery every day of the year. IKONOS scenes as narrow as 5 km can be purchased. TransCanada conducted a pilot study to determine if high resolution satellite imagery is as effective as ortho-photos for identifying population structures within a buffer of TransCanada's east line right-of-way. The study examined three unique segments where residential, commercial, industrial and public features were compared. It was determined that IKONOS imagery is as good as digital ortho-photos for updating structures from low to very high density areas. The satellite imagery was also logistically easier than ortho-photos to acquire. This will be even more evident when the IKONOS image archives begins to grow. 4 tabs., 3 figs.

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

Science.gov (United States)

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.

Use of multispectral images and chemometrics in tomato seed studies

DEFF Research Database (Denmark)

Shrestha, Santosh; Deleuran, Lise Christina; Gislum, René

During the production of tomato seeds, green tomatoes are normally discarded before seed extraction irrespective of their maturity stage. Studies indicate that seeds from green tomatoes may reach be able to reach full germination capacity. Thus the potential of multispectral imaging for non......-destructive discrimination of seeds based on their germination capacity was investigated. A total of 840 seeds extracted from green and red tomatoes were divided into two sets; a training set and a test set consisting of 648 and 192 seeds respectively. Each set consisted of 96 seeds from green tomatoes. The multispectral...... images of the seeds were captured and normalized canonical discriminant analysis was used to analyse the images. Germination tests were performed and seeds that subsequently germinated were recorded as viable. The viable seeds were classified with 99% and 98% accuracy for the training and test set...

Ensemble classification of individual Pinus crowns from multispectral satellite imagery and airborne LiDAR

Science.gov (United States)

Kukunda, Collins B.; Duque-Lazo, Joaquín; González-Ferreiro, Eduardo; Thaden, Hauke; Kleinn, Christoph

2018-03-01

Distinguishing tree species is relevant in many contexts of remote sensing assisted forest inventory. Accurate tree species maps support management and conservation planning, pest and disease control and biomass estimation. This study evaluated the performance of applying ensemble techniques with the goal of automatically distinguishing Pinus sylvestris L. and Pinus uncinata Mill. Ex Mirb within a 1.3 km2 mountainous area in Barcelonnette (France). Three modelling schemes were examined, based on: (1) high-density LiDAR data (160 returns m-2), (2) Worldview-2 multispectral imagery, and (3) Worldview-2 and LiDAR in combination. Variables related to the crown structure and height of individual trees were extracted from the normalized LiDAR point cloud at individual-tree level, after performing individual tree crown (ITC) delineation. Vegetation indices and the Haralick texture indices were derived from Worldview-2 images and served as independent spectral variables. Selection of the best predictor subset was done after a comparison of three variable selection procedures: (1) Random Forests with cross validation (AUCRFcv), (2) Akaike Information Criterion (AIC) and (3) Bayesian Information Criterion (BIC). To classify the species, 9 regression techniques were combined using ensemble models. Predictions were evaluated using cross validation and an independent dataset. Integration of datasets and models improved individual tree species classification (True Skills Statistic, TSS; from 0.67 to 0.81) over individual techniques and maintained strong predictive power (Relative Operating Characteristic, ROC = 0.91). Assemblage of regression models and integration of the datasets provided more reliable species distribution maps and associated tree-scale mapping uncertainties. Our study highlights the potential of model and data assemblage at improving species classifications needed in present-day forest planning and management.

Skin condition measurement by using multispectral imaging system (Conference Presentation)

Science.gov (United States)

Jung, Geunho; Kim, Sungchul; Kim, Jae Gwan

2017-02-01

There are a number of commercially available low level light therapy (LLLT) devices in a market, and face whitening or wrinkle reduction is one of targets in LLLT. The facial improvement could be known simply by visual observation of face, but it cannot provide either quantitative data or recognize a subtle change. Clinical diagnostic instruments such as mexameter can provide a quantitative data, but it costs too high for home users. Therefore, we designed a low cost multi-spectral imaging device by adding additional LEDs (470nm, 640nm, white LED, 905nm) to a commercial USB microscope which has two LEDs (395nm, 940nm) as light sources. Among various LLLT skin treatments, we focused on getting melanin and wrinkle information. For melanin index measurements, multi-spectral images of nevus were acquired and melanin index values from color image (conventional method) and from multi-spectral images were compared. The results showed that multi-spectral analysis of melanin index can visualize nevus with a different depth and concentration. A cross section of wrinkle on skin resembles a wedge which can be a source of high frequency components when the skin image is Fourier transformed into a spatial frequency domain map. In that case, the entropy value of the spatial frequency map can represent the frequency distribution which is related with the amount and thickness of wrinkle. Entropy values from multi-spectral images can potentially separate the percentage of thin and shallow wrinkle from thick and deep wrinkle. From the results, we found that this low cost multi-spectral imaging system could be beneficial for home users of LLLT by providing the treatment efficacy in a quantitative way.

Network design consideration of a satellite-based mobile communications system

Science.gov (United States)

Yan, T.-Y.

1986-01-01

Technical considerations for the Mobile Satellite Experiment (MSAT-X), the ground segment testbed for the low-cost spectral efficient satellite-based mobile communications technologies being developed for the 1990's, are discussed. The Network Management Center contains a flexible resource sharing algorithm, the Demand Assigned Multiple Access scheme, which partitions the satellite transponder bandwidth among voice, data, and request channels. Satellite use of multiple UHF beams permits frequency reuse. The backhaul communications and the Telemetry, Tracking and Control traffic are provided through a single full-coverage SHF beam. Mobile Terminals communicate with the satellite using UHF. All communications including SHF-SHF between Base Stations and/or Gateways, are routed through the satellite. Because MSAT-X is an experimental network, higher level network protocols (which are service-specific) will be developed only to test the operation of the lowest three levels, the physical, data link, and network layers.

Planning for a data base system to support satellite conceptual design

Science.gov (United States)

Claydon, C. R.

1976-01-01

The conceptual design of an automated satellite design data base system is presented. The satellite catalog in the system includes data for all earth orbital satellites funded to the hardware stage for launch between 1970 and 1980, and provides a concise compilation of satellite capabilities and design parameters. The cost of satellite subsystems and components will be added to the base. Data elements are listed and discussed. Sensor and science and applications opportunities catalogs will be included in the data system. Capabilities of the BASIS storage, retrieval, and analysis system are used in the system design.

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

Science.gov (United States)

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.

Statistical Quality Assessment of Pre-fried Carrots Using Multispectral Imaging

DEFF Research Database (Denmark)

Sharifzadeh, Sara; Clemmensen, Line Katrine Harder; Løje, Hanne

2013-01-01

Multispectral imaging is increasingly being used for quality assessment of food items due to its non-invasive benefits. In this paper, we investigate the use of multispectral images of pre-fried carrots, to detect changes over a period of 14 days. The idea is to distinguish changes in quality from...

Highly Protable Airborne Multispectral Imaging System

Science.gov (United States)

Lehnemann, Robert; Mcnamee, Todd

2001-01-01

A portable instrumentation system is described that includes and airborne and a ground-based subsytem. It can acquire multispectral image data over swaths of terrain ranging in width from about 1.5 to 1 km. The system was developed especially for use in coastal environments and is well suited for performing remote sensing and general environmental monitoring. It includes a small,munpilotaed, remotely controlled airplance that carries a forward-looking camera for navigation, three downward-looking monochrome video cameras for imaging terrain in three spectral bands, a video transmitter, and a Global Positioning System (GPS) reciever.

New Capabilities in the Astrophysics Multispectral Archive Search Engine

Science.gov (United States)

Cheung, C. Y.; Kelley, S.; Roussopoulos, N.

The Astrophysics Multispectral Archive Search Engine (AMASE) uses object-oriented database techniques to provide a uniform multi-mission and multi-spectral interface to search for data in the distributed archives. We describe our experience of porting AMASE from Illustra object-relational DBMS to the Informix Universal Data Server. New capabilities and utilities have been developed, including a spatial datablade that supports Nearest Neighbor queries.

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

Science.gov (United States)

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.

Evaluating Multispectral Snowpack Reflectivity With Changing Snow Correlation Lengths

Science.gov (United States)

Kang, Do Hyuk; Barros, Ana P.; Kim, Edward J.

2016-01-01

This study investigates the sensitivity of multispectral reflectivity to changing snow correlation lengths. Matzler's ice-lamellae radiative transfer model was implemented and tested to evaluate the reflectivity of snow correlation lengths at multiple frequencies from the ultraviolet (UV) to the microwave bands. The model reveals that, in the UV to infrared (IR) frequency range, the reflectivity and correlation length are inversely related, whereas reflectivity increases with snow correlation length in the microwave frequency range. The model further shows that the reflectivity behavior can be mainly attributed to scattering rather than absorption for shallow snowpacks. The largest scattering coefficients and reflectivity occur at very small correlation lengths (approximately 10(exp -5 m) for frequencies higher than the IR band. In the microwave range, the largest scattering coefficients are found at millimeter wavelengths. For validation purposes, the ice-lamella model is coupled with a multilayer snow physics model to characterize the reflectivity response of realistic snow hydrological processes. The evolution of the coupled model simulated reflectivities in both the visible and the microwave bands is consistent with satellite-based reflectivity observations in the same frequencies. The model results are also compared with colocated in situ snow correlation length measurements (Cold Land Processes Field Experiment 2002-2003). The analysis and evaluation of model results indicate that the coupled multifrequency radiative transfer and snow hydrology modeling system can be used as a forward operator in a data-assimilation framework to predict the status of snow physical properties, including snow correlation length.

Absolute Radiometric Calibration of the GÖKTÜRK-2 Satellite Sensor Using Tuz GÖLÜ (landnet Site) from Ndvi Perspective

Science.gov (United States)

Sakarya, Ufuk; Hakkı Demirhan, İsmail; Seda Deveci, Hüsne; Teke, Mustafa; Demirkesen, Can; Küpçü, Ramazan; Feray Öztoprak, A.; Efendioğlu, Mehmet; Fehmi Şimşek, F.; Berke, Erdinç; Zübeyde Gürbüz, Sevgi

2016-06-01

TÜBİTAK UZAY has conducted a research study on the use of space-based satellite resources for several aspects of agriculture. Especially, there are two precision agriculture related projects: HASSAS (Widespread application of sustainable precision agriculture practices in Southeastern Anatolia Project Region (GAP) Project) and AKTAR (Smart Agriculture Feasibility Project). The HASSAS project aims to study development of precision agriculture practice in GAP region. Multi-spectral satellite imagery and aerial hyperspectral data along with ground measurements was collected to analyze data in an information system. AKTAR aims to develop models for irrigation, fertilization and spectral signatures of crops in Inner Anatolia. By the end of the project precision agriculture practices to control irrigation, fertilization, pesticide and estimation of crop yield will be developed. Analyzing the phenology of crops using NDVI is critical for the projects. For this reason, absolute radiometric calibration of the Red and NIR bands in space-based satellite sensors is an important issue. The Göktürk-2 satellite is an earth observation satellite which was designed and built in Turkey and was launched in 2012. The Göktürk-2 satellite sensor has a resolution 2.5 meters in panchromatic and 5 meters in R/G/B/NIR bands. The absolute radiometric calibration of the Göktürk-2 satellite sensor was performed via the ground-based measurements - spectra-radiometer, sun photometer, and meteorological station- in Tuz Gölü cal/val site in 2015. In this paper, the first ground-based absolute radiometric calibration results of the Göktürk-2 satellite sensor using Tuz Gölü is demonstrated. The absolute radiometric calibration results of this paper are compared with the published cross-calibration results of the Göktürk-2 satellite sensor utilizing Landsat 8 imagery. According to the experimental comparison results, the Göktürk-2 satellite sensor coefficients for red and NIR bands

ABSOLUTE RADIOMETRIC CALIBRATION OF THE GÖKTÜRK-2 SATELLITE SENSOR USING TUZ GÖLÜ (LANDNET SITE FROM NDVI PERSPECTIVE

Directory of Open Access Journals (Sweden)

U. Sakarya

2016-06-01

Full Text Available TÜBİTAK UZAY has conducted a research study on the use of space-based satellite resources for several aspects of agriculture. Especially, there are two precision agriculture related projects: HASSAS (Widespread application of sustainable precision agriculture practices in Southeastern Anatolia Project Region (GAP Project and AKTAR (Smart Agriculture Feasibility Project. The HASSAS project aims to study development of precision agriculture practice in GAP region. Multi-spectral satellite imagery and aerial hyperspectral data along with ground measurements was collected to analyze data in an information system. AKTAR aims to develop models for irrigation, fertilization and spectral signatures of crops in Inner Anatolia. By the end of the project precision agriculture practices to control irrigation, fertilization, pesticide and estimation of crop yield will be developed. Analyzing the phenology of crops using NDVI is critical for the projects. For this reason, absolute radiometric calibration of the Red and NIR bands in space-based satellite sensors is an important issue. The Göktürk-2 satellite is an earth observation satellite which was designed and built in Turkey and was launched in 2012. The Göktürk-2 satellite sensor has a resolution 2.5 meters in panchromatic and 5 meters in R/G/B/NIR bands. The absolute radiometric calibration of the Göktürk-2 satellite sensor was performed via the ground-based measurements - spectra-radiometer, sun photometer, and meteorological station- in Tuz Gölü cal/val site in 2015. In this paper, the first ground-based absolute radiometric calibration results of the Göktürk-2 satellite sensor using Tuz Gölü is demonstrated. The absolute radiometric calibration results of this paper are compared with the published cross-calibration results of the Göktürk-2 satellite sensor utilizing Landsat 8 imagery. According to the experimental comparison results, the Göktürk-2 satellite sensor coefficients for

An SDR based AIS receiver for satellites

DEFF Research Database (Denmark)

Larsen, Jesper Abildgaard; Mortensen, Hans Peter; Nielsen, Jens Frederik Dalsgaard

2011-01-01

For a few years now, there has been a high interest in monitoring the global ship traffic from space. A few satellite, capable of listening for ship borne AIS transponders have already been launched, and soon the AAUSAT3, carrying two different types of AIS receivers will also be launched. One...... of the AIS receivers onboard AAUSAT3 is an SDR based AIS receiver. This paper serves to describe the background of the AIS system, and how the SDR based receiver has been integrated into the AAUSAT3 satellite. Amongst some of the benefits of using an SDR based receiver is, that due to its versatility, new...... detection algorithms are easily deployed, and it is easily adapted the new proposed AIS transmission channels....

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

Directory of Open Access Journals (Sweden)

Francisco Eugenio

2017-11-01

Full Text Available 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.

GPS-based satellite tracking system for precise positioning

Science.gov (United States)

Yunck, T. P.; Melbourne, W. G.; Thornton, C. L.

1985-01-01

NASA is developing a Global Positioning System (GPS) based measurement system to provide precise determination of earth satellite orbits, geodetic baselines, ionospheric electron content, and clock offsets between worldwide tracking sites. The system will employ variations on the differential GPS observing technique and will use a network of nine fixed ground terminals. Satellite applications will require either a GPS flight receiver or an on-board GPS beacon. Operation of the system for all but satellite tracking will begin by 1988. The first major satellite application will be a demonstration of decimeter accuracy in determining the altitude of TOPEX in the early 1990's. By then the system is expected to yield long-baseline accuracies of a few centimeters and instantaneous time synchronization to 1 ns.

Monitoring temporal microstructural variations of skeletal muscle tissues by multispectral Mueller matrix polarimetry

Science.gov (United States)

Dong, Yang; He, Honghui; He, Chao; Ma, Hui

2017-02-01

Mueller matrix polarimetry is a powerful tool for detecting microscopic structures, therefore can be used to monitor physiological changes of tissue samples. Meanwhile, spectral features of scattered light can also provide abundant microstructural information of tissues. In this paper, we take the 2D multispectral backscattering Mueller matrix images of bovine skeletal muscle tissues, and analyze their temporal variation behavior using multispectral Mueller matrix parameters. The 2D images of the Mueller matrix elements are reduced to the multispectral frequency distribution histograms (mFDHs) to reveal the dominant structural features of the muscle samples more clearly. For quantitative analysis, the multispectral Mueller matrix transformation (MMT) parameters are calculated to characterize the microstructural variations during the rigor mortis and proteolysis processes of the skeletal muscle tissue samples. The experimental results indicate that the multispectral MMT parameters can be used to judge different physiological stages for bovine skeletal muscle tissues in 24 hours, and combining with the multispectral technique, the Mueller matrix polarimetry and FDH analysis can monitor the microstructural variation features of skeletal muscle samples. The techniques may be used for quick assessment and quantitative monitoring of meat qualities in food industry.

Determining the best phenological state for accurate mapping of Phragmites australis in wetlands using time series multispectral satellite data

Science.gov (United States)

Rupasinghe, P. A.; Markle, C. E.; Marcaccio, J. V.; Chow-Fraser, P.

2017-12-01

Phragmites australis (European common reed), is a relatively recent invader of wetlands and beaches in Ontario. It can establish large homogenous stands within wetlands and disperse widely throughout the landscape by wind and vehicular traffic. A first step in managing this invasive species includes accurate mapping and quantification of its distribution. This is challenging because Phragimtes is distributed in a large spatial extent, which makes the mapping more costly and time consuming. Here, we used freely available multispectral satellite images taken monthly (cloud free images as available) for the calendar year to determine the optimum phenological state of Phragmites that would allow it to be accurately identified using remote sensing data. We analyzed time series, Landsat-8 OLI and Sentinel-2 images for Big Creek Wildlife Area, ON using image classification (Support Vector Machines), Normalized Difference Vegetation Index (NDVI) and Normalized Difference Water Index (NDWI). We used field sampling data and high resolution image collected using Unmanned Aerial Vehicle (UAV; 8 cm spatial resolution) as training data and for the validation of the classified images. The accuracy for all land cover classes and for Phragmites alone were low at both the start and end of the calendar year, but reached overall accuracy >85% by mid to late summer. The highest classification accuracies for Landsat-8 OLI were associated with late July and early August imagery. We observed similar trends using the Sentinel-2 images, with higher overall accuracy for all land cover classes and for Phragmites alone from late July to late September. During this period, we found the greatest difference between Phragmites and Typha, commonly confused classes, with respect to near-infrared and shortwave infrared reflectance. Therefore, the unique spectral signature of Phragmites can be attributed to both the level of greenness and factors related to water content in the leaves during late

Assessment of satellite-based precipitation estimates over Paraguay

Science.gov (United States)

Oreggioni Weiberlen, Fiorella; Báez Benítez, Julián

2018-04-01

Satellite-based precipitation estimates represent a potential alternative source of input data in a plethora of meteorological and hydrological applications, especially in regions characterized by a low density of rain gauge stations. Paraguay provides a good example of a case where the use of satellite-based precipitation could be advantageous. This study aims to evaluate the version 7 of the Tropical Rainfall Measurement Mission Multi-Satellite Precipitation Analysis (TMPA V7; 3B42 V7) and the version 1.0 of the purely satellite-based product of the Climate Prediction Center Morphing Technique (CMORPH RAW) through their comparison with daily in situ precipitation measurements from 1998 to 2012 over Paraguay. The statistical assessment is conducted with several commonly used indexes. Specifically, to evaluate the accuracy of daily precipitation amounts, mean error (ME), root mean square error (RMSE), BIAS, and coefficient of determination (R 2) are used, and to analyze the capability to correctly detect different precipitation intensities, false alarm ratio (FAR), frequency bias index (FBI), and probability of detection (POD) are applied to various rainfall rates (0, 0.1, 0.5, 1, 2, 5, 10, 20, 40, 60, and 80 mm/day). Results indicate that TMPA V7 has a better performance than CMORPH RAW over Paraguay. TMPA V7 has higher accuracy in the estimation of daily rainfall volumes and greater precision in the detection of wet days (> 0 mm/day). However, both satellite products show a lower ability to appropriately detect high intensity precipitation events.

Multispectral mid-infrared imaging using frequency upconversion

DEFF Research Database (Denmark)

Sanders, Nicolai Højer; Dam, Jeppe Seidelin; Jensen, Ole Bjarlin

2013-01-01

It has recently been shown that it is possible to upconvert infrared images to the near infrared region with high quantum efficiency and low noise by three-wave mixing with a laser field [1]. If the mixing laser is single-frequency, the upconverted image is simply a band-pass filtered version...... parameter, allowing for fast tuning and hence potentially fast image acquisition, paving the way for upconversion based real time multispectral imaging. In the present realization the upconversion module consists of an external cavity tapered diode laser in a Littrow configuration with a computer controlled...

Do Red Edge and Texture Attributes from High-Resolution Satellite Data Improve Wood Volume Estimation in a Semi-Arid Mountainous Region?

DEFF Research Database (Denmark)

Schumacher, Paul; Mislimshoeva, Bunafsha; Brenning, Alexander

2016-01-01

to overcome this issue. However, clear recommendations on the suitability of specific proxies to provide accurate biomass information in semi-arid to arid environments are still lacking. This study contributes to the understanding of using multispectral high-resolution satellite data (RapidEye), specifically...... red edge and texture attributes, to estimate wood volume in semi-arid ecosystems characterized by scarce vegetation. LASSO (Least Absolute Shrinkage and Selection Operator) and random forest were used as predictive models relating in situ-measured aboveground standing wood volume to satellite data...

Multispectral Video-Microscope Modified for Skin Diagnostics

Directory of Open Access Journals (Sweden)

Rubins U.

2014-12-01

Full Text Available Commercial DinoLite AD413 digital microscope was modified for skin diagnostics purposes. The original LED ring (4 white and 4 ultraviolet light emitters of microscope was replaced by a custom-designed 16-LED ring module consisting of four LED groups (450, 545, 660 and 940 nm, and an onboard LED controller with USB hub was added. The video acquisition and LED switching are performed using custom-designed Matlab software which provides real-time spectral analysis of multi-spectral images and calculation of skin chromophore optical density. The developed multispectral video-microscope is mainly meant for diagnostics of skin malformations, e.g. skin cancerous lesions.

Science Applications of a Multispectral Microscopic Imager for the Astrobiological Exploration of Mars

Science.gov (United States)

Farmer, Jack D.; Sellar, R. Glenn; Swayze, Gregg A.; Blaney, Diana L.

2014-01-01

Abstract Future astrobiological missions to Mars are likely to emphasize the use of rovers with in situ petrologic capabilities for selecting the best samples at a site for in situ analysis with onboard lab instruments or for caching for potential return to Earth. Such observations are central to an understanding of the potential for past habitable conditions at a site and for identifying samples most likely to harbor fossil biosignatures. The Multispectral Microscopic Imager (MMI) provides multispectral reflectance images of geological samples at the microscale, where each image pixel is composed of a visible/shortwave infrared spectrum ranging from 0.46 to 1.73 μm. This spectral range enables the discrimination of a wide variety of rock-forming minerals, especially Fe-bearing phases, and the detection of hydrated minerals. The MMI advances beyond the capabilities of current microimagers on Mars by extending the spectral range into the infrared and increasing the number of spectral bands. The design employs multispectral light-emitting diodes and an uncooled indium gallium arsenide focal plane array to achieve a very low mass and high reliability. To better understand and demonstrate the capabilities of the MMI for future surface missions to Mars, we analyzed samples from Mars-relevant analog environments with the MMI. Results indicate that the MMI images faithfully resolve the fine-scale microtextural features of samples and provide important information to help constrain mineral composition. The use of spectral endmember mapping reveals the distribution of Fe-bearing minerals (including silicates and oxides) with high fidelity, along with the presence of hydrated minerals. MMI-based petrogenetic interpretations compare favorably with laboratory-based analyses, revealing the value of the MMI for future in situ rover-mediated astrobiological exploration of Mars. Key Words: Mars—Microscopic imager—Multispectral imaging�

Science applications of a multispectral microscopic imager for the astrobiological exploration of Mars.

Science.gov (United States)

Núñez, Jorge I; Farmer, Jack D; Sellar, R Glenn; Swayze, Gregg A; Blaney, Diana L

2014-02-01

Future astrobiological missions to Mars are likely to emphasize the use of rovers with in situ petrologic capabilities for selecting the best samples at a site for in situ analysis with onboard lab instruments or for caching for potential return to Earth. Such observations are central to an understanding of the potential for past habitable conditions at a site and for identifying samples most likely to harbor fossil biosignatures. The Multispectral Microscopic Imager (MMI) provides multispectral reflectance images of geological samples at the microscale, where each image pixel is composed of a visible/shortwave infrared spectrum ranging from 0.46 to 1.73 μm. This spectral range enables the discrimination of a wide variety of rock-forming minerals, especially Fe-bearing phases, and the detection of hydrated minerals. The MMI advances beyond the capabilities of current microimagers on Mars by extending the spectral range into the infrared and increasing the number of spectral bands. The design employs multispectral light-emitting diodes and an uncooled indium gallium arsenide focal plane array to achieve a very low mass and high reliability. To better understand and demonstrate the capabilities of the MMI for future surface missions to Mars, we analyzed samples from Mars-relevant analog environments with the MMI. Results indicate that the MMI images faithfully resolve the fine-scale microtextural features of samples and provide important information to help constrain mineral composition. The use of spectral endmember mapping reveals the distribution of Fe-bearing minerals (including silicates and oxides) with high fidelity, along with the presence of hydrated minerals. MMI-based petrogenetic interpretations compare favorably with laboratory-based analyses, revealing the value of the MMI for future in situ rover-mediated astrobiological exploration of Mars. Mars-Microscopic imager-Multispectral imaging-Spectroscopy-Habitability-Arm instrument.

A Cost Effective Multi-Spectral Scanner for Natural Gas Detection

Energy Technology Data Exchange (ETDEWEB)

Yudaya Sivathanu; Jongmook Lim; Vinoo Narayanan; Seonghyeon Park

2005-12-07

The objective of this project is to design, fabricate and demonstrate a cost effective, multi-spectral scanner for natural gas leak detection in transmission and distribution pipelines. During the first year of the project, a laboratory version of the multi-spectral scanner was designed, fabricated, and tested at EnUrga Inc. The multi-spectral scanner was also evaluated using a blind Department of Energy study at the Rocky Mountain Oilfield Testing Center. The performance of the scanner was inconsistent during the blind study. However, most of the leaks were outside the view of the multi-spectral scanner that was developed during the first year of the project. Therefore, a definite evaluation of the capability of the scanner was not obtained. Despite the results, sufficient number of plumes was detected fully confirming the feasibility of the multi-spectral scanner. During the second year, the optical design of the scanner was changed to improve the sensitivity of the system. Laboratory tests show that the system can reliably detect small leaks (20 SCFH) at 30 to 50 feet. A prototype scanner was built and evaluated during the second year of the project. Only laboratory evaluations were completed during the second year. The laboratory evaluations show the feasibility of using the scanner to determine natural gas pipeline leaks. Further field evaluations and optimization of the scanner are required before commercialization of the scanner can be initiated.

Multi sensor satellite imagers for commercial remote sensing

Science.gov (United States)

Cronje, T.; Burger, H.; Du Plessis, J.; Du Toit, J. F.; Marais, L.; Strumpfer, F.

2005-10-01

This paper will discuss and compare recent refractive and catodioptric imager designs developed and manufactured at SunSpace for Multi Sensor Satellite Imagers with Panchromatic, Multi-spectral, Area and Hyperspectral sensors on a single Focal Plane Array (FPA). These satellite optical systems were designed with applications to monitor food supplies, crop yield and disaster monitoring in mind. The aim of these imagers is to achieve medium to high resolution (2.5m to 15m) spatial sampling, wide swaths (up to 45km) and noise equivalent reflectance (NER) values of less than 0.5%. State-of-the-art FPA designs are discussed and address the choice of detectors to achieve these performances. Special attention is given to thermal robustness and compactness, the use of folding prisms to place multiple detectors in a large FPA and a specially developed process to customize the spectral selection with the need to minimize mass, power and cost. A refractive imager with up to 6 spectral bands (6.25m GSD) and a catodioptric imager with panchromatic (2.7m GSD), multi-spectral (6 bands, 4.6m GSD), hyperspectral (400nm to 2.35μm, 200 bands, 15m GSD) sensors on the same FPA will be discussed. Both of these imagers are also equipped with real time video view finding capabilities. The electronic units could be subdivided into the Front-End Electronics and Control Electronics with analogue and digital signal processing. A dedicated Analogue Front-End is used for Correlated Double Sampling (CDS), black level correction, variable gain and up to 12-bit digitizing and high speed LVDS data link to a mass memory unit.

Color and textural quality of packaged wild rocket measured by multispectral imaging

DEFF Research Database (Denmark)

Løkke, Mette Marie; Seefeldt, Helene Fast; Skov, Thomas

2013-01-01

Green color and texture are important attributes for the perception of freshness of wild rocket. Packaging of green leafy vegetables can postpone senescence and yellowing, but a drawback is the risk of anaerobic respiration leading to loss of tissue integrity and development of an olive-brown color....... The hypothesis underlying this paper is that color and textural quality of packaged wild rocket leaves can be predicted by multispectral imaging for faster evaluation of visual quality of leafy green vegetables in scientific experiments. Multispectral imaging was correlated to sensory evaluation of packaged wild...... rocket quality. CIELAB values derived from the multispectral images and from a spectrophotometer changed during storage, but the data were insufficient to describe variation in sensory perceived color and texture. CIELAB values from the multispectral images allowed for a more detailed determination...

Landsat satellite evidence of the decline of northern California bull kelp

Science.gov (United States)

Renshaw, A.; Houskeeper, H. F.; Kudela, R. M.

2017-12-01

Bull kelp (Nereocystis luetkeana), a species of canopy-forming brown macroalga dominant in the Pacific Northwest of North America, provides critical ecological services such as habitat for a diverse array of marine species, nutrient regulation, photosynthesis, and regional marine carbon cycling. Starting around 2014, annual aerial surveys of bull kelp forests along California's northern coastline conducted by the California Department of Fish and Wildlife (CDFW) have reported a sudden 93% reduction in bull kelp canopy area. Remote sensing using satellite imagery is a robust, highly accurate tool for detecting and quantifying the abundance of the canopy-forming giant kelp, Macrocystis pyrifera; however, it has not been successfully applied to measuring northern bull kelp forests. One of the main difficulties associated with bull kelp detection via satellite is the small surface area of bull kelp canopies. As a result, bull kelp beds often only constitute part of a satellite pixel, making it difficult to obtain a kelp reflectance signal significantly different than water's reflectance signal. As part of the NASA Student Airborne Research Program (SARP), we test a novel method for assessing bull kelp canopy using a multiple endmember spectral mixing analysis (MESMA) applied to Landsat 5 and Landsat 8 imagery from 2003-2016. Water and kelp spectral endmembers are selected along the northern California coastline from Havens Neck cape to Point Arena. MESMA results are ground truthed with the CDFW aerial multispectral imagery data. This project will present a satellite-based time series of bull kelp canopy area and evaluate canopy change in a northern California kelp ecosystem.

Application of multispectral imaging to determine quality attributes and ripeness stage in strawberry fruit.

Directory of Open Access Journals (Sweden)

Changhong Liu

Full Text Available Multispectral imaging with 19 wavelengths in the range of 405-970 nm has been evaluated for nondestructive determination of firmness, total soluble solids (TSS content and ripeness stage in strawberry fruit. Several analysis approaches, including partial least squares (PLS, support vector machine (SVM and back propagation neural network (BPNN, were applied to develop theoretical models for predicting the firmness and TSS of intact strawberry fruit. Compared with PLS and SVM, BPNN considerably improved the performance of multispectral imaging for predicting firmness and total soluble solids content with the correlation coefficient (r of 0.94 and 0.83, SEP of 0.375 and 0.573, and bias of 0.035 and 0.056, respectively. Subsequently, the ability of multispectral imaging technology to classify fruit based on ripeness stage was tested using SVM and principal component analysis-back propagation neural network (PCA-BPNN models. The higher classification accuracy of 100% was achieved using SVM model. Moreover, the results of all these models demonstrated that the VIS parts of the spectra were the main contributor to the determination of firmness, TSS content estimation and classification of ripeness stage in strawberry fruit. These results suggest that multispectral imaging, together with suitable analysis model, is a promising technology for rapid estimation of quality attributes and classification of ripeness stage in strawberry fruit.

Adjustment of Sentinel-2 Multi-Spectral Instrument (MSI) Red-Edge Band Reflectance to Nadir BRDF Adjusted Reflectance (NBAR) and Quantification of Red-Edge Band BRDF Effects

OpenAIRE

David P. Roy; Zhongbin Li; Hankui K. Zhang

2017-01-01

Optical wavelength satellite data have directional reflectance effects over non-Lambertian surfaces, described by the bidirectional reflectance distribution function (BRDF). The Sentinel-2 multi-spectral instrument (MSI) acquires data over a 20.6° field of view that have been shown to have non-negligible BRDF effects in the visible, near-infrared, and short wave infrared bands. MSI red-edge BRDF effects have not been investigated. In this study, they are quantified by an examination of 6.6 mi...

Target Detection Based on EBPSK Satellite Passive Radar

Directory of Open Access Journals (Sweden)

Lu Zeyuan

2015-05-01

Full Text Available Passive radar is a topic anti stealth technology with simple structure, and low cost. Radiation source model, signal transmission model, and target detection are the key points of passive radar technology research. The paper analyzes the characteristics of EBPSK signal modulation and target detection method aspect of spaceborne radiant source. By comparison with other satellite navigation and positioning system, the characteristics of EBPSK satellite passive radar system are analyzed. It is proved that the maximum detection range of EBPSK satellite signal can satisfy the needs of the proposed model. In the passive radar model, sparse representation is used to achieve high resolution DOA detection. The comparison with the real target track by simulation demonstrates that effective detection of airborne target using EBPSK satellite passive radar system based on sparse representation is efficient.

Cloud detection, classification and motion estimation using geostationary satellite imagery for cloud cover forecast

International Nuclear Information System (INIS)

Escrig, H.; Batlles, F.J.; Alonso, J.; Baena, F.M.; Bosch, J.L.; Salbidegoitia, I.B.; Burgaleta, J.I.

2013-01-01

Considering that clouds are the greatest causes to solar radiation blocking, short term cloud forecasting can help power plant operation and therefore improve benefits. Cloud detection, classification and motion vector determination are key to forecasting sun obstruction by clouds. Geostationary satellites provide cloud information covering wide areas, allowing cloud forecast to be performed for several hours in advance. Herein, the methodology developed and tested in this study is based on multispectral tests and binary cross correlations followed by coherence and quality control tests over resulting motion vectors. Monthly synthetic surface albedo image and a method to reject erroneous correlation vectors were developed. Cloud classification in terms of opacity and height of cloud top is also performed. A whole-sky camera has been used for validation, showing over 85% of agreement between the camera and the satellite derived cloud cover, whereas error in motion vectors is below 15%. - Highlights: ► A methodology for detection, classification and movement of clouds is presented. ► METEOSAT satellite images are used to obtain a cloud mask. ► The prediction of cloudiness is estimated with 90% in overcast conditions. ► Results for partially covered sky conditions showed a 75% accuracy. ► Motion vectors are estimated from the clouds with a success probability of 86%

Estimating the chlorophyll content in the waters of Guanabara Bay from the LANDSAT multispectral scanning digital data

Science.gov (United States)

Dejesusparada, N. (Principal Investigator); Bentancurt, J. J. V.; Herz, B. R.; Molion, L. B.

1980-01-01

Detection of water quality in Guanabara Bay using multispectral scanning digital data taken from LANDSAT satellites was examined. To test these processes, an empirical (statistical) approach was choosen to observe the degree of relationship between LANDSAT data and the in situ data taken simultaneously. The linear and nonlinear regression analyses were taken from among those developed by INPE in 1978. Results indicate that the major regression was in the number six MSS band, atmospheric effects, which indicated a correction coefficient of 0.99 and an average error of 6.59 micrograms liter. This error was similar to that obtained in the laboratory. The chlorophyll content was between 0 and 100 micrograms/liter, as taken from the MSS of LANDSAT.

Satellite Contamination and Materials Outgassing Knowledge base

Science.gov (United States)

Minor, Jody L.; Kauffman, William J. (Technical Monitor)

2001-01-01

Satellite contamination continues to be a design problem that engineers must take into account when developing new satellites. To help with this issue, NASA's Space Environments and Effects (SEE) Program funded the development of the Satellite Contamination and Materials Outgassing Knowledge base. This engineering tool brings together in one location information about the outgassing properties of aerospace materials based upon ground-testing data, the effects of outgassing that has been observed during flight and measurements of the contamination environment by on-orbit instruments. The knowledge base contains information using the ASTM Standard E- 1559 and also consolidates data from missions using quartz-crystal microbalances (QCM's). The data contained in the knowledge base was shared with NASA by government agencies and industry in the US and international space agencies as well. The term 'knowledgebase' was used because so much information and capability was brought together in one comprehensive engineering design tool. It is the SEE Program's intent to continually add additional material contamination data as it becomes available - creating a dynamic tool whose value to the user is ever increasing. The SEE Program firmly believes that NASA, and ultimately the entire contamination user community, will greatly benefit from this new engineering tool and highly encourages the community to not only use the tool but add data to it as well.

Mapping turbidity in the Charles River, Boston using a high-resolution satellite.

Science.gov (United States)

Hellweger, Ferdi L; Miller, Will; Oshodi, Kehinde Sarat

2007-09-01

The usability of high-resolution satellite imagery for estimating spatial water quality patterns in urban water bodies is evaluated using turbidity in the lower Charles River, Boston as a case study. Water turbidity was surveyed using a boat-mounted optical sensor (YSI) at 5 m spatial resolution, resulting in about 4,000 data points. The ground data were collected coincidently with a satellite imagery acquisition (IKONOS), which consists of multispectral (R, G, B) reflectance at 1 m resolution. The original correlation between the raw ground and satellite data was poor (R2 = 0.05). Ground data were processed by removing points affected by contamination (e.g., sensor encounters a particle floc), which were identified visually. Also, the ground data were corrected for the memory effect introduced by the sensor's protective casing using an analytical model. Satellite data were processed to remove pixels affected by permanent non-water features (e.g., shoreline). In addition, water pixels within a certain buffer distance from permanent non-water features were removed due to contamination by the adjacency effect. To determine the appropriate buffer distance, a procedure that explicitly considers the distance of pixels to the permanent non-water features was applied. Two automatic methods for removing the effect of temporary non-water features (e.g., boats) were investigated, including (1) creating a water-only mask based on an unsupervised classification and (2) removing (filling) all local maxima in reflectance. After the various processing steps, the correlation between the ground and satellite data was significantly better (R2 = 0.70). The correlation was applied to the satellite image to develop a map of turbidity in the lower Charles River, which reveals large-scale patterns in water clarity. However, the adjacency effect prevented the application of this method to near-shore areas, where high-resolution patterns were expected (e.g., outfall plumes).

Predicting Electron Population Characteristics in 2-D Using Multispectral Ground-Based Imaging

Science.gov (United States)

Grubbs, Guy; Michell, Robert; Samara, Marilia; Hampton, Donald; Jahn, Jorg-Micha

2018-01-01

Ground-based imaging and in situ sounding rocket data are compared to electron transport modeling for an active inverted-V type auroral event. The Ground-to-Rocket Electrodynamics-Electrons Correlative Experiment (GREECE) mission successfully launched from Poker Flat, Alaska, on 3 March 2014 at 11:09:50 UT and reached an apogee of approximately 335 km over the aurora. Multiple ground-based electron-multiplying charge-coupled device (EMCCD) imagers were positioned at Venetie, Alaska, and aimed toward magnetic zenith. The imagers observed the intensity of different auroral emission lines (427.8, 557.7, and 844.6 nm) at the magnetic foot point of the rocket payload. Emission line intensity data are correlated with electron characteristics measured by the GREECE onboard electron spectrometer. A modified version of the GLobal airglOW (GLOW) model is used to estimate precipitating electron characteristics based on optical emissions. GLOW predicted the electron population characteristics with 20% error given the observed spectral intensities within 10° of magnetic zenith. Predictions are within 30% of the actual values within 20° of magnetic zenith for inverted-V-type aurora. Therefore, it is argued that this technique can be used, at least in certain types of aurora, such as the inverted-V type presented here, to derive 2-D maps of electron characteristics. These can then be used to further derive 2-D maps of ionospheric parameters as a function of time, based solely on multispectral optical imaging data.

Utility of multispectral imaging for nuclear classification of routine clinical histopathology imagery

Directory of Open Access Journals (Sweden)

Harvey Neal R

2007-07-01

Full Text Available Abstract Background We present an analysis of the utility of multispectral versus standard RGB imagery for routine H&E stained histopathology images, in particular for pixel-level classification of nuclei. Our multispectral imagery has 29 spectral bands, spaced 10 nm within the visual range of 420–700 nm. It has been hypothesized that the additional spectral bands contain further information useful for classification as compared to the 3 standard bands of RGB imagery. We present analyses of our data designed to test this hypothesis. Results For classification using all available image bands, we find the best performance (equal tradeoff between detection rate and false alarm rate is obtained from either the multispectral or our "ccd" RGB imagery, with an overall increase in performance of 0.79% compared to the next best performing image type. For classification using single image bands, the single best multispectral band (in the red portion of the spectrum gave a performance increase of 0.57%, compared to performance of the single best RGB band (red. Additionally, red bands had the highest coefficients/preference in our classifiers. Principal components analysis of the multispectral imagery indicates only two significant image bands, which is not surprising given the presence of two stains. Conclusion Our results indicate that multispectral imagery for routine H&E stained histopathology provides minimal additional spectral information for a pixel-level nuclear classification task than would standard RGB imagery.

Multispectral image analysis for object recognition and classification

Science.gov (United States)

Viau, C. R.; Payeur, P.; Cretu, A.-M.

2016-05-01

Computer and machine vision applications are used in numerous fields to analyze static and dynamic imagery in order to assist or automate decision-making processes. Advancements in sensor technologies now make it possible to capture and visualize imagery at various wavelengths (or bands) of the electromagnetic spectrum. Multispectral imaging has countless applications in various fields including (but not limited to) security, defense, space, medical, manufacturing and archeology. The development of advanced algorithms to process and extract salient information from the imagery is a critical component of the overall system performance. The fundamental objective of this research project was to investigate the benefits of combining imagery from the visual and thermal bands of the electromagnetic spectrum to improve the recognition rates and accuracy of commonly found objects in an office setting. A multispectral dataset (visual and thermal) was captured and features from the visual and thermal images were extracted and used to train support vector machine (SVM) classifiers. The SVM's class prediction ability was evaluated separately on the visual, thermal and multispectral testing datasets.

Portable Multispectral Colorimeter for Metallic Ion Detection and Classification.

Science.gov (United States)

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.

Portable Multispectral Colorimeter for Metallic Ion Detection and Classification

Directory of Open Access Journals (Sweden)

Mauro S. Braga

2017-07-01

Full Text Available 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.

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

Science.gov (United States)

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.

[Responses of vegetation changes to climatic variations in Panxi area based on the MODIS multispectral data].

Science.gov (United States)

Shao, Huai-Yong; Wu, Jin-Hui; Liu, Meng; Yang, Wu-Nian

2014-01-01

It is an important research area to quantitatively studying the relationship between global climatic change and vegetation change based on the remote sensing technology. Panxi area is the ecological barrier of the upper reaches of the Yangtze River, and it is essential for the stability of the ecological environment of Sichuan as well as that of the whole China. The present article analyzes the vegetation change in 2001-2008 and the relationship between vegetation change and climatic variations of Panxi area, based on MODIS multispectral data and meteorological data. The results indicate that NDVI is positively correlated with temperature and precipitation. The precipitation is the major factor that affects the change of vegetation in the Panxi region and the trend of NDVI is similar with autumn precipitation; while at the same time the influence of climate has a one-month-time-lag.

Satellite derived bathymetry: mapping the Irish coastline

Science.gov (United States)

Monteys, X.; Cahalane, C.; Harris, P.; Hanafin, J.

2017-12-01

Ireland has a varied coastline in excess of 3000 km in length largely characterized by extended shallow environments. The coastal shallow water zone can be a challenging and costly environment in which to acquire bathymetry and other oceanographic data using traditional survey methods or airborne LiDAR techniques as demonstrated in the Irish INFOMAR program. Thus, large coastal areas in Ireland, and much of the coastal zone worldwide remain unmapped using modern techniques and is poorly understood. Earth Observations (EO) missions are currently being used to derive timely, cost effective, and quality controlled information for mapping and monitoring coastal environments. Different wavelengths of the solar light penetrate the water column to different depths and are routinely sensed by EO satellites. A large selection of multispectral imagery (MS) from many platforms were examined, as well as from small aircrafts and drones. A number of bays representing very different coastal environments were explored in turn. The project's workflow is created by building a catalogue of satellite and field bathymetric data to assess the suitability of imagery captured at a range of spatial, spectral and temporal resolutions. Turbidity indices are derived from the multispectral information. Finally, a number of spatial regression models using water-leaving radiance parameters and field calibration data are examined. Our assessment reveals that spatial regression algorithms have the potential to significantly improve the accuracy of the predictions up to 10m WD and offer a better handle on the error and uncertainty budget. The four spatial models investigated show better adjustments than the basic non-spatial model. Accuracy of the predictions is better than 10% WD at 95% confidence. Future work will focus on improving the accuracy of the predictions incorporating an analytical model in conjunction with improved empirical methods. The recently launched ESA Sentinel 2 will become the

An evaluation of the use of ERTS-1 satellite imagery for grizzly bear habitat analysis

Science.gov (United States)

Varney, J. R.; Craighead, J. J.; Sumner, J.

1973-01-01

Multispectral scanner images taken by the ERTS-1 satellite in August and October, 1972, were examined to determine if they would be useful in identifying and mapping favorable habitat for grizzly bears. It was possible to identify areas having a suitable mixture of alpine meadow and timber, and to eliminate those which did not meet the isolation requirements of grizzlies because of farming or grazing activity. High altitude timbered areas mapped from satellite imagery agreed reasonably well with the distribution of whitebark pine, an important food species. Analysis of satellite imagery appears to be a valuable supplement to present ground observation methods, since it allows the most important areas to be identified for intensive study and many others to be eliminated from consideration. A sampling plan can be developed from such data which will minimize field effort and overall program cost.

A comparison of autonomous techniques for multispectral image analysis and classification

Science.gov (United States)

Valdiviezo-N., Juan C.; Urcid, Gonzalo; Toxqui-Quitl, Carina; Padilla-Vivanco, Alfonso

2012-10-01

Multispectral imaging has given place to important applications related to classification and identification of objects from a scene. Because of multispectral instruments can be used to estimate the reflectance of materials in the scene, these techniques constitute fundamental tools for materials analysis and quality control. During the last years, a variety of algorithms has been developed to work with multispectral data, whose main purpose has been to perform the correct classification of the objects in the scene. The present study introduces a brief review of some classical as well as a novel technique that have been used for such purposes. The use of principal component analysis and K-means clustering techniques as important classification algorithms is here discussed. Moreover, a recent method based on the min-W and max-M lattice auto-associative memories, that was proposed for endmember determination in hyperspectral imagery, is introduced as a classification method. Besides a discussion of their mathematical foundation, we emphasize their main characteristics and the results achieved for two exemplar images conformed by objects similar in appearance, but spectrally different. The classification results state that the first components computed from principal component analysis can be used to highlight areas with different spectral characteristics. In addition, the use of lattice auto-associative memories provides good results for materials classification even in the cases where some spectral similarities appears in their spectral responses.

Introducing Multisensor Satellite Radiance-Based Evaluation for Regional Earth System Modeling

Science.gov (United States)

Matsui, T.; Santanello, J.; Shi, J. J.; Tao, W.-K.; Wu, D.; Peters-Lidard, C.; Kemp, E.; Chin, M.; Starr, D.; Sekiguchi, M.;

A Multispectral Micro-Imager for Lunar Field Geology

Science.gov (United States)

Nunez, Jorge; Farmer, Jack; Sellar, Glenn; Allen, Carlton

2009-01-01

Field geologists routinely assign rocks to one of three basic petrogenetic categories (igneous, sedimentary or metamorphic) based on microtextural and mineralogical information acquired with a simple magnifying lens. Indeed, such observations often comprise the core of interpretations of geological processes and history. The Multispectral Microscopic Imager (MMI) uses multi-wavelength, light-emitting diodes (LEDs) and a substrate-removed InGaAs focal-plane array to create multispectral, microscale reflectance images of geological samples (FOV 32 X 40 mm). Each pixel (62.5 microns) of an image is comprised of 21 spectral bands that extend from 470 to 1750 nm, enabling the discrimination of a wide variety of rock-forming minerals, especially Fe-bearing phases. MMI images provide crucial context information for in situ robotic analyses using other onboard analytical instruments (e.g. XRD), or for the selection of return samples for analysis in terrestrial labs. To further assess the value of the MMI as a tool for lunar exploration, we used a field-portable, tripod-mounted version of the MMI to image a variety of Apollo samples housed at the Lunar Experiment Laboratory, NASA s Johnson Space Center. MMI images faithfully resolved the microtextural features of samples, while the application of ENVI-based spectral end member mapping methods revealed the distribution of Fe-bearing mineral phases (olivine, pyroxene and magnetite), along with plagioclase feldspars within samples. Samples included a broad range of lithologies and grain sizes. Our MMI-based petrogenetic interpretations compared favorably with thin section-based descriptions published in the Lunar Sample Compendium, revealing the value of MMI images for astronaut and rover-mediated lunar exploration.

Automated Orthorectification of VHR Satellite Images by SIFT-Based RPC Refinement

Directory of Open Access Journals (Sweden)

Hakan Kartal

2018-06-01

Full Text Available Raw remotely sensed images contain geometric distortions and cannot be used directly for map-based applications, accurate locational information extraction or geospatial data integration. A geometric correction process must be conducted to minimize the errors related to distortions and achieve the desired location accuracy before further analysis. A considerable number of images might be needed when working over large areas or in temporal domains in which manual geometric correction requires more labor and time. To overcome these problems, new algorithms have been developed to make the geometric correction process autonomous. The Scale Invariant Feature Transform (SIFT algorithm is an image matching algorithm used in remote sensing applications that has received attention in recent years. In this study, the effects of the incidence angle, surface topography and land cover (LC characteristics on SIFT-based automated orthorectification were investigated at three different study sites with different topographic conditions and LC characteristics using Pleiades very high resolution (VHR images acquired at different incidence angles. The results showed that the location accuracy of the orthorectified images increased with lower incidence angle images. More importantly, the topographic characteristics had no observable impacts on the location accuracy of SIFT-based automated orthorectification, and the results showed that Ground Control Points (GCPs are mainly concentrated in the “Forest” and “Semi Natural Area” LC classes. A multi-thread code was designed to reduce the automated processing time, and the results showed that the process performed 7 to 16 times faster using an automated approach. Analyses performed on various spectral modes of multispectral data showed that the arithmetic data derived from pan-sharpened multispectral images can be used in automated SIFT-based RPC orthorectification.

Reflectance of Antarctic surfaces from multispectral radiometers: The correction of atmospheric effects

International Nuclear Information System (INIS)

Zibordi, G.; Maracci, G.

1993-01-01

Monitoring reflectance of polar icecaps has relevance in climate studies. In fact, climate changes produce variations in the morphology of ice and snow covers, which are detectable as surface reflectance change. Surface reflectance can be retrieved from remotely sensed data. However, absolute values independent of atmospheric turbidity and surface altitude can only be obtained after removing masking effects of the atmosphere. An atmospheric correction model, accounting for surface and sensor altitudes above sea level, is described and validated through data detected over Antarctic surfaces with a Barnes Modular Multispectral Radiometer having bands overlapping those of the Landsat Thematic Mapper. The model is also applied in a sensitivity analysis to investigate error induced in reflectance obtained from satellite data by indeterminacy in optical parameters of atmospheric constituents. Results show that indeterminacy in the atmospheric water vapor optical thickness is the main source of nonaccuracy in the retrieval of surface reflectance from data remotely sensed over Antarctic regions

Simultaneous hierarchical segmentation and vectorization of satellite images through combined data sampling and anisotropic triangulation

Energy Technology Data Exchange (ETDEWEB)

Grazzini, Jacopo [Los Alamos National Laboratory; Prasad, Lakshman [Los Alamos National Laboratory; Dillard, Scott [PNNL

2010-10-21

The automatic detection, recognition , and segmentation of object classes in remote sensed images is of crucial importance for scene interpretation and understanding. However, it is a difficult task because of the high variability of satellite data. Indeed, the observed scenes usually exhibit a high degree of complexity, where complexity refers to the large variety of pictorial representations of objects with the same semantic meaning and also to the extensive amount of available det.ails. Therefore, there is still a strong demand for robust techniques for automatic information extraction and interpretation of satellite images. In parallel, there is a growing interest in techniques that can extract vector features directly from such imagery. In this paper, we investigate the problem of automatic hierarchical segmentation and vectorization of multispectral satellite images. We propose a new algorithm composed of the following steps: (i) a non-uniform sampling scheme extracting most salient pixels in the image, (ii) an anisotropic triangulation constrained by the sampled pixels taking into account both strength and directionality of local structures present in the image, (iii) a polygonal grouping scheme merging, through techniques based on perceptual information , the obtained segments to a smaller quantity of superior vectorial objects. Besides its computational efficiency, this approach provides a meaningful polygonal representation for subsequent image analysis and/or interpretation.

Use of Multispectral Imaging in Varietal Identification of Tomato

DEFF Research Database (Denmark)

Shrestha, Santosh; Deleuran, Lise Christina; Olesen, Merete Halkjær

2015-01-01

Abstract: Multispectral imaging is an emerging non-destructive technology. In this work its potential for varietal discrimination and identification of tomato cultivars of Nepal was investigated. Two sample sets were used for the study, one with two parents and their crosses and other with eleven...... obtained provide an opportunity of using multispectral imaging technology as a primary tool in a scientific community for identification/discrimination of plant varieties in regard to genetic purity and plant variety protection/registration.......Abstract: Multispectral imaging is an emerging non-destructive technology. In this work its potential for varietal discrimination and identification of tomato cultivars of Nepal was investigated. Two sample sets were used for the study, one with two parents and their crosses and other with eleven...... cultivars to study parents and offspring relationship and varietal identification respectively. Normalized canonical discriminant analysis (nCDA) and principal component analysis (PCA) were used to analyze and compare the results for parents and offspring study. Both the results showed clear discrimination...

The high resolution optical instruments for the Pleiades HR Earth observation satellites

Science.gov (United States)

Gaudin-Delrieu, Catherine; Lamard, Jean-Luc; Cheroutre, Philippe; Bailly, Bruno; Dhuicq, Pierre; Puig, Olivier

2017-11-01

Coming after the SPOT satellites series, PLEIADESHR is a CNES optical high resolution satellite dedicated to Earth observation, part of a larger optical and radar multi-sensors system, ORFEO, which is developed in cooperation between France and Italy for dual Civilian and Defense use. The development of the two PLEIADES-HR cameras was entrusted by CNES to Thales Alenia Space. This new generation of instrument represents a breakthrough in comparison with the previous SPOT instruments owing to a significant step in on-ground resolution, which approaches the capabilities of aerial photography. The PLEIADES-HR instrument program benefits from Thales Alenia Space long and successful heritage in Earth observation from space. The proposed solution benefits from an extensive use of existing products, Cannes Space Optics Centre facilities, unique in Europe, dedicated to High Resolution instruments. The optical camera provides wide field panchromatic images supplemented by 4 multispectral channels with narrow spectral bands. The optical concept is based on a four mirrors Korsch telescope. Crucial improvements in detector technology, optical fabrication and electronics make it possible for the PLEIADES-HR instrument to achieve the image quality requirements while respecting the drastic limitations of mass and volume imposed by the satellite agility needs and small launchers compatibility. The two flight telescopes were integrated, aligned and tested. After the integration phase, the alignment, mainly based on interferometric measurements in vacuum chamber, was successfully achieved within high accuracy requirements. The wave front measurements show outstanding performances, confirmed, after the integration of the PFM Detection Unit, by MTF measurements on the Proto-Flight Model Instrument. Delivery of the proto flight model occurred mi-2008. The FM2 Instrument delivery is planned Q2-2009. The first optical satellite launch of the PLEIADES-HR constellation is foreseen

Radiometric and geometric assessment of data from the RapidEye constellation of satellites

Science.gov (United States)

Chander, Gyanesh; Haque, Md. Obaidul; Sampath, Aparajithan; Brunn, A.; Trosset, G.; Hoffmann, D.; Roloff, S.; Thiele, M.; Anderson, C.

2013-01-01

To monitor land surface processes over a wide range of temporal and spatial scales, it is critical to have coordinated observations of the Earth's surface using imagery acquired from multiple spaceborne imaging sensors. The RapidEye (RE) satellite constellation acquires high-resolution satellite images covering the entire globe within a very short period of time by sensors identical in construction and cross-calibrated to each other. To evaluate the RE high-resolution Multi-spectral Imager (MSI) sensor capabilities, a cross-comparison between the RE constellation of sensors was performed first using image statistics based on large common areas observed over pseudo-invariant calibration sites (PICS) by the sensors and, second, by comparing the on-orbit radiometric calibration temporal trending over a large number of calibration sites. For any spectral band, the individual responses measured by the five satellites of the RE constellation were found to differ B2B) alignment of the image data sets. The position accuracy was assessed by comparing the RE imagery against high-resolution aerial imagery, while the B2B characterization was performed by registering each band against every other band to ensure that the proper band alignment is provided for an image product. The B2B results indicate that the internal alignments of these five RE bands are in agreement, with bands typically registered to within 0.25 pixels of each other or better.

Registration of 3D and Multispectral Data for the Study of Cultural Heritage Surfaces

Science.gov (United States)

Chane, Camille Simon; Schütze, Rainer; Boochs, Frank; Marzani, Franck S.

2013-01-01

We present a technique for the multi-sensor registration of featureless datasets based on the photogrammetric tracking of the acquisition systems in use. This method is developed for the in situ study of cultural heritage objects and is tested by digitizing a small canvas successively with a 3D digitization system and a multispectral camera while simultaneously tracking the acquisition systems with four cameras and using a cubic target frame with a side length of 500 mm. The achieved tracking accuracy is better than 0.03 mm spatially and 0.150 mrad angularly. This allows us to seamlessly register the 3D acquisitions and to project the multispectral acquisitions on the 3D model. PMID:23322103

Satellite based wind resource assessment over the South China Sea

DEFF Research Database (Denmark)

Badger, Merete; Astrup, Poul; Hasager, Charlotte Bay

2014-01-01

variations are clearly visible across the domain; for instance sheltering effects caused by the land masses. The satellite based wind resource maps have two shortcomings. One is the lack of information at the higher vertical levels where wind turbines operate. The other is the limited number of overlapping...... years of WRF data – specifically the parameters heat flux, air temperature, and friction velocity – are used to calculate a long-term correction for atmospheric stability effects. The stability correction is applied to the satellite based wind resource maps together with a vertical wind profile...... from satellite synthetic aperture radar (SAR) data are particularly suitable for offshore wind energy applications because they offer a spatial resolution up to 500 m and include coastal seas. In this presentation, satellite wind maps are used in combination with mast observations and numerical...

Integration of Satellite Tracking Data and Satellite Images for Detailed Characteristics of Wildlife Habitats

Science.gov (United States)

Dobrynin, D. V.; Rozhnov, V. V.; Saveliev, A. A.; Sukhova, O. V.; Yachmennikova, A. A.

2017-12-01

Methods of analysis of the results got from satellite tracking of large terrestrial mammals differ in the level of their integration with additional geographic data. The reliable fine-scale cartographic basis for assessing specific wildlife habitats can be developed through the interpretation of multispectral remote sensing data and extrapolation of the results to the entire estimated species range. Topographic maps were ordinated according to classified features using self-organizing maps (Kohonen's SOM). The satellite image of the Ussuriiskyi Nature Reserve area was interpreted for the analysis of movement conditions for seven wild Amur tigers ( Panthera tigris altaica) equipped with GPS collars. 225 SOM classes for cartographic visualization are sufficient for the detailed mapping of all natural complexes that were identified as a result of interpretation. During snow-free periods, tigers preferred deciduous and shrub associations at lower elevations, as well as mixed forests in the valleys of streams that are adjacent to sparse forests and shrub watershed in the mountain ranges; during heavy snow periods, the animals preferred the entire range of plant communities in different relief types, except for open sites in meadows and abandoned fields at foothills. The border zones of different biotopes were typically used by the tigers during all seasons. Amur tigers preferred coniferous forests for long-term movements.

Satellites

International Nuclear Information System (INIS)

Burns, J.A.; Matthews, M.S.

1986-01-01

The present work is based on a conference: Natural Satellites, Colloquium 77 of the IAU, held at Cornell University from July 5 to 9, 1983. Attention is given to the background and origins of satellites, protosatellite swarms, the tectonics of icy satellites, the physical characteristics of satellite surfaces, and the interactions of planetary magnetospheres with icy satellite surfaces. Other topics include the surface composition of natural satellites, the cratering of planetary satellites, the moon, Io, and Europa. Consideration is also given to Ganymede and Callisto, the satellites of Saturn, small satellites, satellites of Uranus and Neptune, and the Pluto-Charon system

Multi-spectral and fluorescence diffuse optical tomography of breast cancer

Science.gov (United States)

Corlu, Alper

Multi-spectral and fluorescence diffuse optical tomography (DOT) techniques are explored and applied to image human breast cancer in vivo. Image reconstruction algorithms that utilize first and second order gradient information are described in detail. Breast DOT requires large computational memory and long run times. To this end, parallel computation techniques were developed appropriate to each reconstruction algorithm. A parallel plate DOT instrument developed for breast cancer imaging is described. The system relies heavily on continuous-wave (CW) transmission measurements and utilizes frequency domain (FD) measurements on the reemission side. However, traditional DOT image reconstruction methods based on CW measurements fail to separate tissue absorption and scattering uniquely. In this manuscript, multi-spectral DOT is shown to be capable of minimizing cross-talk and retrieving spectral parameters almost uniquely when the measurement wavelengths are optimized. A theoretical framework to select optimum wavelengths is provided, and tested with computer simulations. Results from phantom spectroscopy experiments and in vivo patient measurements support the notion that multi-spectral methods are superior to traditional DOT image reconstruction schemes. The same breast DOT instrument is improved and utilized to obtain the first in vivo images of human breast cancer based on fluorescence DOT (FDOT). To this end the fluorophore Indocyanine Green (ICG) is injected intravenously and fluorescence excitation and detection are accomplished in the soft-compression, parallel-plane, transmission geometry using laser sources at 786 nm and spectrally filtered CCD detection. Careful phantom and in vivo measurements are carried on to assure that the signals are due to ICG fluorescence, rather than tissue autofluorescence and excitation light leakage. An in vivo measurement protocol is designed to maximize the ICG contrast by acquiring full fluorescence tomographic scan during

Some results on the investigation of earth resources by aerial and polygon methods

Energy Technology Data Exchange (ETDEWEB)

Vinnichenko, N K; Tishchenko, A P

1980-01-01

Papers are presented on integrated aerial-satellite remote sensing systems, the resolution of TV scanning systems, the transfer of spectral contrasts in multispectral photography, and pseudocolor representation of multispectral aerial images. Consideration is also given to the use of spectral and physical-geographic characteristics of natural objects on the earth's surface for the interpretation of multispectral satellite photographs, the determination of the types and state of crops from multispectral aerial images, and the automated classification of agricultural objects from their multispectral aerial images.

Landsat 1-5 Multispectral Scanner V1

Data.gov (United States)

National Aeronautics and Space Administration — Abstract: The Landsat Multispectral Scanner (MSS) was a sensor onboard Landsats 1 through 5 and acquired images of the Earth nearly continuously from July 1972 to...

Multispectral Imaging in Cultural Heritage Conservation

Science.gov (United States)

Del Pozo, S.; Rodríguez-Gonzálvez, P.; Sánchez-Aparicio, L. J.; Muñoz-Nieto, A.; Hernández-López, D.; Felipe-García, B.; González-Aguilera, D.

2017-08-01

This paper sums up the main contribution derived from the thesis entitled "Multispectral imaging for the analysis of materials and pathologies in civil engineering, constructions and natural spaces" awarded by CIPA-ICOMOS for its connection with the preservation of Cultural Heritage. This thesis is framed within close-range remote sensing approaches by the fusion of sensors operating in the optical domain (visible to shortwave infrared spectrum). In the field of heritage preservation, multispectral imaging is a suitable technique due to its non-destructive nature and its versatility. It combines imaging and spectroscopy to analyse materials and land covers and enables the use of a variety of different geomatic sensors for this purpose. These sensors collect both spatial and spectral information for a given scenario and a specific spectral range, so that, their smaller storage units save the spectral properties of the radiation reflected by the surface of interest. The main goal of this research work is to characterise different construction materials as well as the main pathologies of Cultural Heritage elements by combining active and passive sensors recording data in different ranges. Conclusions about the suitability of each type of sensor and spectral range are drawn in relation to each particular case study and damage. It should be emphasised that results are not limited to images, since 3D intensity data from laser scanners can be integrated with 2D data from passive sensors obtaining high quality products due to the added value that metric brings to multispectral images.

MULTISPECTRAL IMAGING IN CULTURAL HERITAGE CONSERVATION

Directory of Open Access Journals (Sweden)

S. Del Pozo

2017-08-01

Full Text Available This paper sums up the main contribution derived from the thesis entitled "Multispectral imaging for the analysis of materials and pathologies in civil engineering, constructions and natural spaces" awarded by CIPA-ICOMOS for its connection with the preservation of Cultural Heritage. This thesis is framed within close-range remote sensing approaches by the fusion of sensors operating in the optical domain (visible to shortwave infrared spectrum. In the field of heritage preservation, multispectral imaging is a suitable technique due to its non-destructive nature and its versatility. It combines imaging and spectroscopy to analyse materials and land covers and enables the use of a variety of different geomatic sensors for this purpose. These sensors collect both spatial and spectral information for a given scenario and a specific spectral range, so that, their smaller storage units save the spectral properties of the radiation reflected by the surface of interest. The main goal of this research work is to characterise different construction materials as well as the main pathologies of Cultural Heritage elements by combining active and passive sensors recording data in different ranges. Conclusions about the suitability of each type of sensor and spectral range are drawn in relation to each particular case study and damage. It should be emphasised that results are not limited to images, since 3D intensity data from laser scanners can be integrated with 2D data from passive sensors obtaining high quality products due to the added value that metric brings to multispectral images.

Fingerprint enhancement using a multispectral sensor

Science.gov (United States)

Rowe, Robert K.; Nixon, Kristin A.

2005-03-01

The level of performance of a biometric fingerprint sensor is critically dependent on the quality of the fingerprint images. One of the most common types of optical fingerprint sensors relies on the phenomenon of total internal reflectance (TIR) to generate an image. Under ideal conditions, a TIR fingerprint sensor can produce high-contrast fingerprint images with excellent feature definition. However, images produced by the same sensor under conditions that include dry skin, dirt on the skin, and marginal contact between the finger and the sensor, are likely to be severely degraded. This paper discusses the use of multispectral sensing as a means to collect additional images with new information about the fingerprint that can significantly augment the system performance under both normal and adverse sample conditions. In the context of this paper, "multispectral sensing" is used to broadly denote a collection of images taken under different illumination conditions: different polarizations, different illumination/detection configurations, as well as different wavelength illumination. Results from three small studies using an early-stage prototype of the multispectral-TIR (MTIR) sensor are presented along with results from the corresponding TIR data. The first experiment produced data from 9 people, 4 fingers from each person and 3 measurements per finger under "normal" conditions. The second experiment provided results from a study performed to test the relative performance of TIR and MTIR images when taken under extreme dry and dirty conditions. The third experiment examined the case where the area of contact between the finger and sensor is greatly reduced.

Multi-spectral CCD camera system for ocean water color and seacoast observation

Science.gov (United States)

Zhu, Min; Chen, Shiping; Wu, Yanlin; Huang, Qiaolin; Jin, Weiqi

2001-10-01

One of the earth observing instruments on HY-1 Satellite which will be launched in 2001, the multi-spectral CCD camera system, is developed by Beijing Institute of Space Mechanics & Electricity (BISME), Chinese Academy of Space Technology (CAST). In 798 km orbit, the system can provide images with 250 m ground resolution and a swath of 500 km. It is mainly used for coast zone dynamic mapping and oceanic watercolor monitoring, which include the pollution of offshore and coast zone, plant cover, watercolor, ice, terrain underwater, suspended sediment, mudflat, soil and vapor gross. The multi- spectral camera system is composed of four monocolor CCD cameras, which are line array-based, 'push-broom' scanning cameras, and responding for four spectral bands. The camera system adapts view field registration; that is, each camera scans the same region at the same moment. Each of them contains optics, focal plane assembly, electrical circuit, installation structure, calibration system, thermal control and so on. The primary features on the camera system are: (1) Offset of the central wavelength is better than 5 nm; (2) Degree of polarization is less than 0.5%; (3) Signal-to-noise ratio is about 1000; (4) Dynamic range is better than 2000:1; (5) Registration precision is better than 0.3 pixel; (6) Quantization value is 12 bit.

Detecting early stage pressure ulcer on dark skin using multispectral imager

Science.gov (United States)

Yi, Dingrong; Kong, Linghua; Sprigle, Stephen; Wang, Fengtao; Wang, Chao; Liu, Fuhan; Adibi, Ali; Tummala, Rao

2010-02-01

We are developing a handheld multispectral imaging device to non-invasively inspect stage I pressure ulcers in dark pigmented skins without the need of touching the patient's skin. This paper reports some preliminary test results of using a proof-of-concept prototype. It also talks about the innovation's impact to traditional multispectral imaging technologies and the fields that will potentially benefit from it.

Building a satellite climate diagnostics data base for real-time climate monitoring

International Nuclear Information System (INIS)

Ropelewski, C.F.

1991-01-01

The paper discusses the development of a data base, the Satellite Climate Diagnostic Data Base (SCDDB), for real time operational climate monitoring utilizing current satellite data. Special attention is given to the satellite-derived quantities useful for monitoring global climate changes, the requirements of SCDDB, and the use of conventional meteorological data and model assimilated data in developing the SCDDB. Examples of prototype SCDDB products are presented. 10 refs

Nigeria's Satellite Programme Development: Prospects and Challenges

Science.gov (United States)

Akinyede, Joseph

, housing, defence and security and urban renewal, and large scale mapping community, NASRDA has embarked on the development of a higher resolution satellite NigeriaSat-2 which carries spatial resolution pay loads of 2.5 and 5 meters in panchromatic and multi-spectral bands respectively. In addition, the satellite has been designed to provide stereo-imaging capability. It also carries a 32m resolution payload to ensure the continuity of NigeriaSat-1 data beyond its 2008 lifespan. The launch of NigeriaSat-2 is being planned for 2009. Furthermore, Nigeria's concern over the incessant cloud cover of a large area of its southern part has informed NASRDA's quest to acquire capacity for SAR-based image interpretation and application to socio-economic development. The programme will eventually lead to the acquisition of a SAR-based micro-satellite (NigeriaSat-3) in the near future.

A near real-time satellite-based global drought climate data record

International Nuclear Information System (INIS)

AghaKouchak, Amir; Nakhjiri, Navid

2012-01-01

Reliable drought monitoring requires long-term and continuous precipitation data. High resolution satellite measurements provide valuable precipitation information on a quasi-global scale. However, their short lengths of records limit their applications in drought monitoring. In addition to this limitation, long-term low resolution satellite-based gauge-adjusted data sets such as the Global Precipitation Climatology Project (GPCP) one are not available in near real-time form for timely drought monitoring. This study bridges the gap between low resolution long-term satellite gauge-adjusted data and the emerging high resolution satellite precipitation data sets to create a long-term climate data record of droughts. To accomplish this, a Bayesian correction algorithm is used to combine GPCP data with real-time satellite precipitation data sets for drought monitoring and analysis. The results showed that the combined data sets after the Bayesian correction were a significant improvement compared to the uncorrected data. Furthermore, several recent major droughts such as the 2011 Texas, 2010 Amazon and 2010 Horn of Africa droughts were detected in the combined real-time and long-term satellite observations. This highlights the potential application of satellite precipitation data for regional to global drought monitoring. The final product is a real-time data-driven satellite-based standardized precipitation index that can be used for drought monitoring especially over remote and/or ungauged regions. (letter)

MULTISPECTRAL PANSHARPENING APPROACH USING PULSE-COUPLED NEURAL NETWORK SEGMENTATION

Directory of Open Access Journals (Sweden)

X. J. Li

2018-04-01

Full Text Available The paper proposes a novel pansharpening method based on the pulse-coupled neural network segmentation. In the new method, uniform injection gains of each region are estimated through PCNN segmentation rather than through a simple square window. Since PCNN segmentation agrees with the human visual system, the proposed method shows better spectral consistency. Our experiments, which have been carried out for both suburban and urban datasets, demonstrate that the proposed method outperforms other methods in multispectral pansharpening.

A multispectral scanner survey of the Idaho National Engineering Laboratory and the Hanford Reservation

International Nuclear Information System (INIS)

Brewster, S.B. Jr.; Howard, M.E.; Shines, J.E.

1994-09-01

An airborne multispectral scanner survey of selected sites on the Idaho National Engineering Laboratory and the Hanford Reservation was performed in mid-November 1993. Aerial multispectral scanner and photography data were acquired coincidentally with the Big O experiment at both locations. To illustrate two potential applications, the multispectral scanner data were digitally enhanced to facilitate the detection of soil disturbance and evidence of surface water transport. The main conclusion of this study was that multispectral data acquired under these conditions can be useful for soil disturbance detection. The imagery did not prove as useful, however, for direct indications of surface water transport. It was possible to infer some water transport patterns from dry water beds, but only if surface indications were present

Feasibility study and quality assessment of unmanned aircraft system-derived multispectral images

Science.gov (United States)

Chang, Kuo-Jen

2017-04-01

The purpose of study is to explore the precision and the applicability of UAS-derived multispectral images. In this study, the Micro-MCA6 multispectral camera was mounted on quadcopter. The Micro-MCA6 shoot images synchronized of each single band. By means of geotagged images and control points, the orthomosaic images of each single band generated firstly by 14cm resolution. The multispectral image was merged complete with 6 bands. In order to improve the spatial resolution, the 6 band image fused with 9cm resolution image taken from RGB camera. Quality evaluation of the image is verified of the each single band by using control points and check points. The standard deviations of errors are within 1 to 2 pixel resolution of each band. The quality of the multispectral image is compared with 3 cm resolution orthomosaic RGB image gathered from UAV in the same mission, as well. The standard deviations of errors are within 2 to 3 pixel resolution. The result shows that the errors resulting from the blurry and the band dislocation of the objects edge identification. To the end, the normalized difference vegetation index (NDVI) extracted from the image to explore the condition of vegetation and the nature of the environment. This study demonstrates the feasibility and the capability of the high resolution multispectral images.

Assessing satellite-based start-of-season trends in the US High Plains

International Nuclear Information System (INIS)

Lin, X; Sassenrath, G F; Hubbard, K G; Mahmood, R

2014-01-01

To adequately assess the effects of global warming it is necessary to address trends and impacts at the local level. This study examines phenological changes in the start-of-season (SOS) derived from satellite observations from 1982–2008 in the US High Plains region. The surface climate-based SOS was also evaluated. The averaged profiles of SOS from 37° to 49°N latitude by satellite- and climate-based methods were in reasonable agreement, especially for areas where croplands were masked out and an additional frost date threshold was adopted. The statistically significant trends of satellite-based SOS show a later spring arrival ranging from 0.1 to 4.9 days decade −1 over nine Level III ecoregions. We found the croplands generally exhibited larger trends (later arrival) than the non-croplands. The area-averaged satellite-based SOS for non-croplands (i.e. mostly grasslands) showed no significant trends. We examined the trends of temperatures, precipitation, and standardized precipitation index (SPI), as well as the strength of correlation between the satellite-based SOS and these climatic drivers. Our results indicate that satellite-based SOS trends are spatially and primarily related to annual maximum normalized difference vegetation index (NDVI, mostly in summertime) and/or annual minimum NDVI (mostly in wintertime) and these trends showed the best correlation with six-month SPI over the period 1982–2008 in the US High Plains region. (letter)

Mapping Urban Tree Canopy Cover Using Fused Airborne LIDAR and Satellite Imagery Data

Science.gov (United States)

Parmehr, Ebadat G.; Amati, Marco; Fraser, Clive S.

2016-06-01

Urban green spaces, particularly urban trees, play a key role in enhancing the liveability of cities. The availability of accurate and up-to-date maps of tree canopy cover is important for sustainable development of urban green spaces. LiDAR point clouds are widely used for the mapping of buildings and trees, and several LiDAR point cloud classification techniques have been proposed for automatic mapping. However, the effectiveness of point cloud classification techniques for automated tree extraction from LiDAR data can be impacted to the point of failure by the complexity of tree canopy shapes in urban areas. Multispectral imagery, which provides complementary information to LiDAR data, can improve point cloud classification quality. This paper proposes a reliable method for the extraction of tree canopy cover from fused LiDAR point cloud and multispectral satellite imagery data. The proposed method initially associates each LiDAR point with spectral information from the co-registered satellite imagery data. It calculates the normalised difference vegetation index (NDVI) value for each LiDAR point and corrects tree points which have been misclassified as buildings. Then, region growing of tree points, taking the NDVI value into account, is applied. Finally, the LiDAR points classified as tree points are utilised to generate a canopy cover map. The performance of the proposed tree canopy cover mapping method is experimentally evaluated on a data set of airborne LiDAR and WorldView 2 imagery covering a suburb in Melbourne, Australia.

Automated object-based classification of rain-induced landslides with VHR multispectral images in Madeira Island

Science.gov (United States)

Heleno, S.; Matias, M.; Pina, P.; Sousa, A. J.

2015-09-01

A method for semi-automatic landslide detection, with the ability to separate source and run-out areas, is presented in this paper. It combines object-based image analysis and a Support Vector Machine classifier on a GeoEye-1 multispectral image, sensed 3 days after the major damaging landslide event that occurred in Madeira island (20 February 2010), with a pre-event LIDAR Digital Elevation Model. The testing is developed in a 15 km2-wide study area, where 95 % of the landslides scars are detected by this supervised approach. The classifier presents a good performance in the delineation of the overall landslide area. In addition, fair results are achieved in the separation of the source from the run-out landslide areas, although in less illuminated slopes this discrimination is less effective than in sunnier east facing-slopes.

Vicarious Calibration of Beijing-1 Multispectral Imagers

Directory of Open Access Journals (Sweden)

Zhengchao Chen

2014-02-01

Full Text Available For on-orbit calibration of the Beijing-1 multispectral imagers (Beijing-1/MS, a field calibration campaign was performed at the Dunhuang calibration site during September and October of 2008. Based on the in situ data and images from Beijing-1 and Terra/Moderate Resolution Imaging Spectroradiometer (MODIS, three vicarious calibration methods (i.e., reflectance-based, irradiance-based, and cross-calibration were used to calculate the top-of-atmosphere (TOA radiance of Beijing-1. An analysis was then performed to determine or identify systematic and accidental errors, and the overall uncertainty was assessed for each individual method. The findings show that the reflectance-based method has an uncertainty of more than 10% if the aerosol optical depth (AOD exceeds 0.2. The cross-calibration method is able to reach an error level within 7% if the images are selected carefully. The final calibration coefficients were derived from the irradiance-based data for 6 September 2008, with an uncertainty estimated to be less than 5%.

Automated Detection of Buildings from Heterogeneous VHR Satellite Images for Rapid Response to Natural Disasters

Directory of Open Access Journals (Sweden)

Shaodan Li

2017-11-01

Full Text Available In this paper, we present a novel approach for automatically detecting buildings from multiple heterogeneous and uncalibrated very high-resolution (VHR satellite images for a rapid response to natural disasters. In the proposed method, a simple and efficient visual attention method is first used to extract built-up area candidates (BACs from each multispectral (MS satellite image. After this, morphological building indices (MBIs are extracted from all the masked panchromatic (PAN and MS images with BACs to characterize the structural features of buildings. Finally, buildings are automatically detected in a hierarchical probabilistic model by fusing the MBI and masked PAN images. The experimental results show that the proposed method is comparable to supervised classification methods in terms of recall, precision and F-value.

Research on orbit prediction for solar-based calibration proper satellite

Science.gov (United States)

Chen, Xuan; Qi, Wenwen; Xu, Peng

2018-03-01

Utilizing the mathematical model of the orbit mechanics, the orbit prediction is to forecast the space target's orbit information of a certain time based on the orbit of the initial moment. The proper satellite radiometric calibration and calibration orbit prediction process are introduced briefly. On the basis of the research of the calibration space position design method and the radiative transfer model, an orbit prediction method for proper satellite radiometric calibration is proposed to select the appropriate calibration arc for the remote sensor and to predict the orbit information of the proper satellite and the remote sensor. By analyzing the orbit constraint of the proper satellite calibration, the GF-1solar synchronous orbit is chose as the proper satellite orbit in order to simulate the calibration visible durance for different satellites to be calibrated. The results of simulation and analysis provide the basis for the improvement of the radiometric calibration accuracy of the satellite remote sensor, which lays the foundation for the high precision and high frequency radiometric calibration.

Near-infrared multispectral photoacoustic microscopy using a graded-index fiber amplifier

Directory of Open Access Journals (Sweden)

Takashi Buma

2016-09-01

Full Text Available We demonstrate optical resolution photoacoustic microscopy (OR-PAM of lipid-rich tissue using a multi-wavelength pulsed laser based on nonlinear fiber optics. 1047 nm laser pulses are converted to 1098, 1153, 1215, and 1270 nm pulses via stimulated Raman scattering in a graded-index multimode fiber. Multispectral PAM of a lipid phantom is demonstrated with our low-cost and simple technique.

Multispectral Landsat images of Antartica

Energy Technology Data Exchange (ETDEWEB)

Lucchitta, B.K.; Bowell, J.A.; Edwards, K.L.; Eliason, E.M.; Fergurson, H.M.

1988-01-01

The U.S. Geological Survey has a program to map Antarctica by using colored, digitally enhanced Landsat multispectral scanner images to increase existing map coverage and to improve upon previously published Landsat maps. This report is a compilation of images and image mosaic that covers four complete and two partial 1:250,000-scale quadrangles of the McMurdo Sound region.

A multispectral scanner survey of the Tonopah Test Range, Nevada. Date of survey: August 1993

International Nuclear Information System (INIS)

Brewster, S.B. Jr.; Howard, M.E.; Shines, J.E.

1994-08-01

The Multispectral Remote Sensing Department of the Remote Sensing Laboratory conducted an airborne multispectral scanner survey of a portion of the Tonopah Test Range, Nevada. The survey was conducted on August 21 and 22, 1993, using a Daedalus AADS1268 scanner and coincident aerial color photography. Flight altitudes were 5,000 feet (1,524 meters) above ground level for systematic coverage and 1,000 feet (304 meters) for selected areas of special interest. The multispectral scanner survey was initiated as part of an interim and limited investigation conducted to gather preliminary information regarding historical hazardous material release sites which could have environmental impacts. The overall investigation also includes an inventory of environmental restoration sites, a ground-based geophysical survey, and an aerial radiological survey. The multispectral scanner imagery and coincident aerial photography were analyzed for the detection, identification, and mapping of man-made soil disturbances. Several standard image enhancement techniques were applied to the data to assist image interpretation. A geologic ratio enhancement and a color composite consisting of AADS1268 channels 10, 7, and 9 (mid-infrared, red, and near-infrared spectral bands) proved most useful for detecting soil disturbances. A total of 358 disturbance sites were identified on the imagery and mapped using a geographic information system. Of these sites, 326 were located within the Tonopah Test Range while the remaining sites were present on the imagery but outside the site boundary. The mapped site locations are being used to support ongoing field investigations

SPECTRUM analysis of multispectral imagery in conjunction with wavelet/KLT data compression

Energy Technology Data Exchange (ETDEWEB)

Bradley, J.N.; Brislawn, C.M.

1993-12-01

The data analysis program, SPECTRUM, is used for fusion, visualization, and classification of multi-spectral imagery. The raw data used in this study is Landsat Thematic Mapper (TM) 7-channel imagery, with 8 bits of dynamic range per channel. To facilitate data transmission and storage, a compression algorithm is proposed based on spatial wavelet transform coding and KLT decomposition of interchannel spectral vectors, followed by adaptive optimal multiband scalar quantization. The performance of SPECTRUM clustering and visualization is evaluated on compressed multispectral data. 8-bit visualizations of 56-bit data show little visible distortion at 50:1 compression and graceful degradation at higher compression ratios. Two TM images were processed in this experiment: a 1024 x 1024-pixel scene of the region surrounding the Chernobyl power plant, taken a few months before the reactor malfunction, and a 2048 x 2048 image of Moscow and surrounding countryside.

A Comparative Study of Land Cover Classification by Using Multispectral and Texture Data

Directory of Open Access Journals (Sweden)

Salman Qadri

2016-01-01

Full Text Available The main objective of this study is to find out the importance of machine vision approach for the classification of five types of land cover data such as bare land, desert rangeland, green pasture, fertile cultivated land, and Sutlej river land. A novel spectra-statistical framework is designed to classify the subjective land cover data types accurately. Multispectral data of these land covers were acquired by using a handheld device named multispectral radiometer in the form of five spectral bands (blue, green, red, near infrared, and shortwave infrared while texture data were acquired with a digital camera by the transformation of acquired images into 229 texture features for each image. The most discriminant 30 features of each image were obtained by integrating the three statistical features selection techniques such as Fisher, Probability of Error plus Average Correlation, and Mutual Information (F + PA + MI. Selected texture data clustering was verified by nonlinear discriminant analysis while linear discriminant analysis approach was applied for multispectral data. For classification, the texture and multispectral data were deployed to artificial neural network (ANN: n-class. By implementing a cross validation method (80-20, we received an accuracy of 91.332% for texture data and 96.40% for multispectral data, respectively.

Tracking target objects orbiting earth using satellite-based telescopes

Science.gov (United States)

De Vries, Willem H; Olivier, Scot S; Pertica, Alexander J

2014-10-14

A system for tracking objects that are in earth orbit via a constellation or network of satellites having imaging devices is provided. An object tracking system includes a ground controller and, for each satellite in the constellation, an onboard controller. The ground controller receives ephemeris information for a target object and directs that ephemeris information be transmitted to the satellites. Each onboard controller receives ephemeris information for a target object, collects images of the target object based on the expected location of the target object at an expected time, identifies actual locations of the target object from the collected images, and identifies a next expected location at a next expected time based on the identified actual locations of the target object. The onboard controller processes the collected image to identify the actual location of the target object and transmits the actual location information to the ground controller.

Scheduling algorithm for data relay satellite optical communication based on artificial intelligent optimization

Science.gov (United States)

Zhao, Wei-hu; Zhao, Jing; Zhao, Shang-hong; Li, Yong-jun; Wang, Xiang; Dong, Yi; Dong, Chen

2013-08-01

Optical satellite communication with the advantages of broadband, large capacity and low power consuming broke the bottleneck of the traditional microwave satellite communication. The formation of the Space-based Information System with the technology of high performance optical inter-satellite communication and the realization of global seamless coverage and mobile terminal accessing are the necessary trend of the development of optical satellite communication. Considering the resources, missions and restraints of Data Relay Satellite Optical Communication System, a model of optical communication resources scheduling is established and a scheduling algorithm based on artificial intelligent optimization is put forwarded. According to the multi-relay-satellite, multi-user-satellite, multi-optical-antenna and multi-mission with several priority weights, the resources are scheduled reasonable by the operation: "Ascertain Current Mission Scheduling Time" and "Refresh Latter Mission Time-Window". The priority weight is considered as the parameter of the fitness function and the scheduling project is optimized by the Genetic Algorithm. The simulation scenarios including 3 relay satellites with 6 optical antennas, 12 user satellites and 30 missions, the simulation result reveals that the algorithm obtain satisfactory results in both efficiency and performance and resources scheduling model and the optimization algorithm are suitable in multi-relay-satellite, multi-user-satellite, and multi-optical-antenna recourses scheduling problem.

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

Science.gov (United States)

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.

Instantaneous Shoreline Extraction Utilizing Integrated Spectrum and Shadow Analysis From LiDAR Data and High-resolution Satellite Imagery

Science.gov (United States)

Lee, I.-Chieh

Shoreline delineation and shoreline change detection are expensive processes in data source acquisition and manual shoreline delineation. These costs confine the frequency and interval of shoreline mapping periods. In this dissertation, a new shoreline delineation approach was developed targeting on lowering the data source cost and reducing human labor. To lower the cost of data sources, we used the public domain LiDAR data sets and satellite images to delineate shorelines without the requirement of data sets being acquired simultaneously, which is a new concept in this field. To reduce the labor cost, we made improvements in classifying LiDAR points and satellite images. Analyzing shadow relations with topography to improve the satellite image classification performance is also a brand-new concept. The extracted shoreline of the proposed approach could achieve an accuracy of 1.495 m RMSE, or 4.452m at the 95% confidence level. Consequently, the proposed approach could successfully lower the cost and shorten the processing time, in other words, to increase the shoreline mapping frequency with a reasonable accuracy. However, the extracted shoreline may not compete with the shoreline extracted by aerial photogrammetric procedures in the aspect of accuracy. Hence, this is a trade-off between cost and accuracy. This approach consists of three phases, first, a shoreline extraction procedure based mainly on LiDAR point cloud data with multispectral information from satellite images. Second, an object oriented shoreline extraction procedure to delineate shoreline solely from satellite images; in this case WorldView-2 images were used. Third, a shoreline integration procedure combining these two shorelines based on actual shoreline changes and physical terrain properties. The actual data source cost would only be from the acquisition of satellite images. On the other hand, only two processes needed human attention. First, the shoreline within harbor areas needed to be

The method of multispectral image processing of phytoplankton processing for environmental control of water pollution

Science.gov (United States)

Petruk, Vasil; Kvaternyuk, Sergii; Yasynska, Victoria; Kozachuk, Anastasia; Kotyra, Andrzej; Romaniuk, Ryszard S.; Askarova, Nursanat

2015-12-01

The paper presents improvement of the method of environmental monitoring of water bodies based on bioindication by phytoplankton, which identify phytoplankton particles carried out on the basis of comparison array multispectral images using Bayesian classifier of solving function based on Mahalanobis distance. It allows to evaluate objectively complex anthropogenic and technological impacts on aquatic ecosystems.

Airborne Multi-Spectral Minefield Survey

Science.gov (United States)

2005-05-01

Swedish Defence Research Agency), GEOSPACE (Austria), GTD ( Ingenieria de Sistemas y Software Industrial, Spain), IMEC (Ineruniversity MicroElectronic...RTO-MP-SET-092 18 - 1 UNCLASSIFIED/UNLIMITED UNCLASSIFIED/UNLIMITED Airborne Multi-Spectral Minefield Survey Dirk-Jan de Lange, Eric den...actions is the severe lack of baseline information. To respond to this in a rapid way, cost-efficient data acquisition methods are a key issue. de

New multispectral MRI data fusion technique for white matter lesion segmentation: method and comparison with thresholding in FLAIR images

International Nuclear Information System (INIS)

Del C Valdes Hernandez, Maria; Ferguson, Karen J.; Chappell, Francesca M.; Wardlaw, Joanna M.

2010-01-01

Brain tissue segmentation by conventional threshold-based techniques may have limited accuracy and repeatability in older subjects. We present a new multispectral magnetic resonance (MR) image analysis approach for segmenting normal and abnormal brain tissue, including white matter lesions (WMLs). We modulated two 1.5T MR sequences in the red/green colour space and calculated the tissue volumes using minimum variance quantisation. We tested it on 14 subjects, mean age 73.3 ± 10 years, representing the full range of WMLs and atrophy. We compared the results of WML segmentation with those using FLAIR-derived thresholds, examined the effect of sampling location, WML amount and field inhomogeneities, and tested observer reliability and accuracy. FLAIR-derived thresholds were significantly affected by the location used to derive the threshold (P = 0.0004) and by WML volume (P = 0.0003), and had higher intra-rater variability than the multispectral technique (mean difference ± SD: 759 ± 733 versus 69 ± 326 voxels respectively). The multispectral technique misclassified 16 times fewer WMLs. Initial testing suggests that the multispectral technique is highly reproducible and accurate with the potential to be applied to routinely collected clinical MRI data. (orig.)

Evaluating the hydrological consistency of satellite based water cycle components

KAUST Repository

Lopez Valencia, Oliver Miguel

2016-06-15

Advances in multi-satellite based observations of the earth system have provided the capacity to retrieve information across a wide-range of land surface hydrological components and provided an opportunity to characterize terrestrial processes from a completely new perspective. Given the spatial advantage that space-based observations offer, several regional-to-global scale products have been developed, offering insights into the multi-scale behaviour and variability of hydrological states and fluxes. However, one of the key challenges in the use of satellite-based products is characterizing the degree to which they provide realistic and representative estimates of the underlying retrieval: that is, how accurate are the hydrological components derived from satellite observations? The challenge is intrinsically linked to issues of scale, since the availability of high-quality in-situ data is limited, and even where it does exist, is generally not commensurate to the resolution of the satellite observation. Basin-scale studies have shown considerable variability in achieving water budget closure with any degree of accuracy using satellite estimates of the water cycle. In order to assess the suitability of this type of approach for evaluating hydrological observations, it makes sense to first test it over environments with restricted hydrological inputs, before applying it to more hydrological complex basins. Here we explore the concept of hydrological consistency, i.e. the physical considerations that the water budget impose on the hydrologic fluxes and states to be temporally and spatially linked, to evaluate the reproduction of a set of large-scale evaporation (E) products by using a combination of satellite rainfall (P) and Gravity Recovery and Climate Experiment (GRACE) observations of storage change, focusing on arid and semi-arid environments, where the hydrological flows can be more realistically described. Our results indicate no persistent hydrological

SOFT project: a new forecasting system based on satellite data

Science.gov (United States)

Pascual, Ananda; Orfila, A.; Alvarez, Alberto; Hernandez, E.; Gomis, D.; Barth, Alexander; Tintore, Joaquim

2002-01-01

The aim of the SOFT project is to develop a new ocean forecasting system by using a combination of satellite dat, evolutionary programming and numerical ocean models. To achieve this objective two steps are proved: (1) to obtain an accurate ocean forecasting system using genetic algorithms based on satellite data; and (2) to integrate the above new system into existing deterministic numerical models. Evolutionary programming will be employed to build 'intelligent' systems that, learning form the past ocean variability and considering the present ocean state, will be able to infer near future ocean conditions. Validation of the forecast skill will be carried out by comparing the forecasts fields with satellite and in situ observations. Validation with satellite observations will provide the expected errors in the forecasting system. Validation with in situ data will indicate the capabilities of the satellite based forecast information to improve the performance of the numerical ocean models. This later validation will be accomplished considering in situ measurements in a specific oceanographic area at two different periods of time. The first set of observations will be employed to feed the hybrid systems while the second set will be used to validate the hybrid and traditional numerical model results.

Water Quality Determination of Küçükçekmece Lake, Turkey by Using Multispectral Satellite Data

Directory of Open Access Journals (Sweden)

Erhan Alparslan

2009-01-01

Full Text Available This study focuses on the analysis of the Landsat-5 TM + SPOT-Pan (1992, IRS-1C/D LISS + Pan (2000, and Landsat-5 TM (2006 satellite images that reflect the drastic land use/land cover changes in the Küçükçekmece Lake region, Istanbul. Landsat-5 TM satellite data dated 2006 was used for mapping water quality. A multiple regression analysis was carried out between the unitless planetary reflectance values derived from the satellite image and in situ water quality parameters chlorophyll a, total phosphorus, total nitrogen, turbidity, and biological and chemical oxygen demand measured at a number of stations homogenously distributed over the lake surface. The results of this study provided valuable information to local administrators on the water quality of Küçükçekmece Lake, which is a large water resource of the Istanbul Metropolitan Area. Results also show that such a methodology structured by use of reflectance values provided from satellite imagery, in situ water quality measurements, and basin land use/land cover characteristics obtained from images can serve as a powerful and rapid monitoring tool for the drinking water basins that suffer from rapid urbanization and pollution, all around the world.

Spatial Data Exploring by Satellite Image Distributed Processing

Science.gov (United States)

Mihon, V. D.; Colceriu, V.; Bektas, F.; Allenbach, K.; Gvilava, M.; Gorgan, D.

2012-04-01

Our society needs and environmental predictions encourage the applications development, oriented on supervising and analyzing different Earth Science related phenomena. Satellite images could be explored for discovering information concerning land cover, hydrology, air quality, and water and soil pollution. Spatial and environment related data could be acquired by imagery classification consisting of data mining throughout the multispectral bands. The process takes in account a large set of variables such as satellite image types (e.g. MODIS, Landsat), particular geographic area, soil composition, vegetation cover, and generally the context (e.g. clouds, snow, and season). All these specific and variable conditions require flexible tools and applications to support an optimal search for the appropriate solutions, and high power computation resources. The research concerns with experiments on solutions of using the flexible and visual descriptions of the satellite image processing over distributed infrastructures (e.g. Grid, Cloud, and GPU clusters). This presentation highlights the Grid based implementation of the GreenLand application. The GreenLand application development is based on simple, but powerful, notions of mathematical operators and workflows that are used in distributed and parallel executions over the Grid infrastructure. Currently it is used in three major case studies concerning with Istanbul geographical area, Rioni River in Georgia, and Black Sea catchment region. The GreenLand application offers a friendly user interface for viewing and editing workflows and operators. The description involves the basic operators provided by GRASS [1] library as well as many other image related operators supported by the ESIP platform [2]. The processing workflows are represented as directed graphs giving the user a fast and easy way to describe complex parallel algorithms, without having any prior knowledge of any programming language or application commands

Sequential optimization of a terrestrial biosphere model constrained by multiple satellite based products

Science.gov (United States)

Ichii, K.; Kondo, M.; Wang, W.; Hashimoto, H.; Nemani, R. R.

2012-12-01

Various satellite-based spatial products such as evapotranspiration (ET) and gross primary productivity (GPP) are now produced by integration of ground and satellite observations. Effective use of these multiple satellite-based products in terrestrial biosphere models is an important step toward better understanding of terrestrial carbon and water cycles. However, due to the complexity of terrestrial biosphere models with large number of model parameters, the application of these spatial data sets in terrestrial biosphere models is difficult. In this study, we established an effective but simple framework to refine a terrestrial biosphere model, Biome-BGC, using multiple satellite-based products as constraints. We tested the framework in the monsoon Asia region covered by AsiaFlux observations. The framework is based on the hierarchical analysis (Wang et al. 2009) with model parameter optimization constrained by satellite-based spatial data. The Biome-BGC model is separated into several tiers to minimize the freedom of model parameter selections and maximize the independency from the whole model. For example, the snow sub-model is first optimized using MODIS snow cover product, followed by soil water sub-model optimized by satellite-based ET (estimated by an empirical upscaling method; Support Vector Regression (SVR) method; Yang et al. 2007), photosynthesis model optimized by satellite-based GPP (based on SVR method), and respiration and residual carbon cycle models optimized by biomass data. As a result of initial assessment, we found that most of default sub-models (e.g. snow, water cycle and carbon cycle) showed large deviations from remote sensing observations. However, these biases were removed by applying the proposed framework. For example, gross primary productivities were initially underestimated in boreal and temperate forest and overestimated in tropical forests. However, the parameter optimization scheme successfully reduced these biases. Our analysis

Using multi-spectral sensors for vegetation mapping

CSIR Research Space (South Africa)

Van Deventer, Heidi

2016-07-01

Full Text Available Wetland and estuarine vegetation is often difficult to detect and separate from adjacent land covers with multispectral sensors for a number of reasons. The spatial resolution of space-borne sensors is often insufficient for these features which...

Multispectral televisional measuring control of the ecological state of waterbodies on the characteristics macrophytes

Science.gov (United States)

Petruk, Vasil; Kvaternyuk, Sergii; Kozachuk, Anastasia; Sailarbek, Saltanat; Gromaszek, Konrad

2015-12-01

Improved methods for multispectral measuring television monitoring of the ecological state of water bodies on the characteristics of macrophytes groups to assess complex human impact on their environment. Integral assessment of water pollution is based on research products of higher aquatic plants and their communities by optical methods.

Proposed systems configurations for a satellite based ISDN

Science.gov (United States)

Capece, M.; Pavesi, B.; Tozzi, P.; Galligan, K. P.

This paper summarizes concepts developed during a study for the ESA in which the evolution of ISDN capability and the impact in the satellite land mobile area are examined. Following the progressive steps of the expected ISDN implementation and the potential market penetration, a space based system capable of satisfying particular user services classes has been investigated. The approach used is to establish a comparison between the requirements of potential mobile users and the services already envisaged by ISDN, identifying the service subclasses that might be adopted in a mobile environment through a satellite system. Two system alternatives, with different ISDN compatibility, have been identified. The first option allows a partial compatibility, by providing the central stations of the earth segment with suitable interface units. The second option permits a full integration, operating on the satellite on-board capabilities.

A MEMS-based Adaptive AHRS for Marine Satellite Tracking Antenna

DEFF Research Database (Denmark)

Wang, Yunlong; Hussain, Dil Muhammed Akbar; Soltani, Mohsen

2015-01-01

Satellite tracking is a challenging task for marine applications. An attitude determination system should estimate the wave disturbances on the ship body accurately. To achieve this, an Attitude Heading Reference System (AHRS) based on Micro-Electro-Mechanical Systems (MEMS) sensors, composed...... of three-axis gyroscope, accelerometer and magnetometer, is developed for Marine Satellite Tracking Antenna (MSTA). In this paper, the attitude determination algorithm is improved using an adaptive mechanism that tunes the attitude estimator parameters based on an estimation of ship motion frequency...

Satellite-based technique for nowcasting of thunderstorms over ...

Indian Academy of Sciences (India)

Suman Goyal

2017-08-31

Aug 31, 2017 ... Due to inadequate radar network, satellite plays the dominant role for nowcast of these thunderstorms. In this study, a nowcast based algorithm ForTracc developed by Vila ... of actual development of cumulonimbus clouds, ... MCS over Indian region using Infrared Channel ... (2016) based on case study of.

Improving the automated detection of refugee/IDP dwellings using the multispectral bands of the WorldView-2 satellite

Science.gov (United States)

Kemper, Thomas; Gueguen, Lionel; Soille, Pierre

2012-06-01

The enumeration of the population remains a critical task in the management of refugee/IDP camps. Analysis of very high spatial resolution satellite data proofed to be an efficient and secure approach for the estimation of dwellings and the monitoring of the camp over time. In this paper we propose a new methodology for the automated extraction of features based on differential morphological decomposition segmentation for feature extraction and interactive training sample selection from the max-tree and min-tree structures. This feature extraction methodology is tested on a WorldView-2 scene of an IDP camp in Darfur Sudan. Special emphasis is given to the additional available bands of the WorldView-2 sensor. The results obtained show that the interactive image information tool is performing very well by tuning the feature extraction to the local conditions. The analysis of different spectral subsets shows that it is possible to obtain good results already with an RGB combination, but by increasing the number of spectral bands the detection of dwellings becomes more accurate. Best results were obtained using all eight bands of WorldView-2 satellite.

Guided Image Filtering-Based Pan-Sharpening Method: A Case Study of GaoFen-2 Imagery

Directory of Open Access Journals (Sweden)

Yalan Zheng

2017-12-01

Full Text Available GaoFen-2 (GF-2 is a civilian optical satellite self-developed by China equipped with both multispectral and panchromatic sensors, and is the first satellite in China with a resolution below 1 m. Because the pan-sharpening methods on GF-2 imagery have not been a focus of previous works, we propose a novel pan-sharpening method based on guided image filtering and compare the performance to state-of-the-art methods on GF-2 images. Guided image filtering was introduced to decompose and transfer the details and structures from the original panchromatic and multispectral bands. Thereafter, an adaptive model that considers the local spectral relationship was designed to properly inject spatial information back into the original spectral bands. Four pairs of GF-2 images acquired from urban, water body, cropland, and forest areas were selected for the experiments. Both quantitative and visual inspections were used for the assessment. The experimental results demonstrated that for GF-2 imagery acquired over different scenes, the proposed approach consistently achieves high spectral fidelity and enhances spatial details, thereby benefitting the potential classification procedures.

Automated Generation of the Alaska Coastline Using High-Resolution Satellite Imagery

Science.gov (United States)

Roth, G.; Porter, C. C.; Cloutier, M. D.; Clementz, M. E.; Reim, C.; Morin, P. J.

2015-12-01

Previous campaigns to map Alaska's coast at high resolution have relied on airborne, marine, or ground-based surveying and manual digitization. The coarse temporal resolution, inability to scale geographically, and high cost of field data acquisition in these campaigns is inadequate for the scale and speed of recent coastal change in Alaska. Here, we leverage the Polar Geospatial Center (PGC) archive of DigitalGlobe, Inc. satellite imagery to produce a state-wide coastline at 2 meter resolution. We first select multispectral imagery based on time and quality criteria. We then extract the near-infrared (NIR) band from each processed image, and classify each pixel as water or land with a pre-determined NIR threshold value. Processing continues with vectorizing the water-land boundary, removing extraneous data, and attaching metadata. Final coastline raster and vector products maintain the original accuracy of the orthorectified satellite data, which is often within the local tidal range. The repeat frequency of coastline production can range from 1 month to 3 years, depending on factors such as satellite capacity, cloud cover, and floating ice. Shadows from trees or structures complicate the output and merit further data cleaning. The PGC's imagery archive, unique expertise, and computing resources enabled us to map the Alaskan coastline in a few months. The DigitalGlobe archive allows us to update this coastline as new imagery is acquired, and facilitates baseline data for studies of coastal change and improvement of topographic datasets. Our results are not simply a one-time coastline, but rather a system for producing multi-temporal, automated coastlines. Workflows and tools produced with this project can be freely distributed and utilized globally. Researchers and government agencies must now consider how they can incorporate and quality-control this high-frequency, high-resolution data to meet their mapping standards and research objectives.

Multispectral LiDAR Data for Land Cover Classification of Urban Areas

Directory of Open Access Journals (Sweden)

Salem Morsy

2017-04-01

Full Text Available Airborne Light Detection And Ranging (LiDAR systems usually operate at a monochromatic wavelength measuring the range and the strength of the reflected energy (intensity from objects. Recently, multispectral LiDAR sensors, which acquire data at different wavelengths, have emerged. This allows for recording of a diversity of spectral reflectance from objects. In this context, we aim to investigate the use of multispectral LiDAR data in land cover classification using two different techniques. The first is image-based classification, where intensity and height images are created from LiDAR points and then a maximum likelihood classifier is applied. The second is point-based classification, where ground filtering and Normalized Difference Vegetation Indices (NDVIs computation are conducted. A dataset of an urban area located in Oshawa, Ontario, Canada, is classified into four classes: buildings, trees, roads and grass. An overall accuracy of up to 89.9% and 92.7% is achieved from image classification and 3D point classification, respectively. A radiometric correction model is also applied to the intensity data in order to remove the attenuation due to the system distortion and terrain height variation. The classification process is then repeated, and the results demonstrate that there are no significant improvements achieved in the overall accuracy.

Multispectral LiDAR Data for Land Cover Classification of Urban Areas.

Science.gov (United States)

Morsy, Salem; Shaker, Ahmed; El-Rabbany, Ahmed

2017-04-26

Airborne Light Detection And Ranging (LiDAR) systems usually operate at a monochromatic wavelength measuring the range and the strength of the reflected energy (intensity) from objects. Recently, multispectral LiDAR sensors, which acquire data at different wavelengths, have emerged. This allows for recording of a diversity of spectral reflectance from objects. In this context, we aim to investigate the use of multispectral LiDAR data in land cover classification using two different techniques. The first is image-based classification, where intensity and height images are created from LiDAR points and then a maximum likelihood classifier is applied. The second is point-based classification, where ground filtering and Normalized Difference Vegetation Indices (NDVIs) computation are conducted. A dataset of an urban area located in Oshawa, Ontario, Canada, is classified into four classes: buildings, trees, roads and grass. An overall accuracy of up to 89.9% and 92.7% is achieved from image classification and 3D point classification, respectively. A radiometric correction model is also applied to the intensity data in order to remove the attenuation due to the system distortion and terrain height variation. The classification process is then repeated, and the results demonstrate that there are no significant improvements achieved in the overall accuracy.

Multispectral imaging as a potential tool for seed health testing of spinach (Spinacia oleracea L.)

DEFF Research Database (Denmark)

Olesen, M. Halkjaer; Carstensen, Jens Michael; Boelt, B.

2011-01-01

Seed health tests are time consuming and require substantial training for characterization of pathogenic fungi on seed. A new approach to use a multispectral vision system for identifying surface properties of different fungal infections has been tested in spinach (Spinacia oleracea L.) at Aarhus...... University. Our study demonstrates that multispectral imaging with wavelengths ranging from 395-970 nm can be used to distinguish between uninfected spinach seeds and seeds infected with Verticillium spp., Fusarium spp., Stemphylium botryosum, Cladosporium spp. and Alternaria alternata. Analytical separation...... based on mean pixel intensity, Canonical Discriminant Analysis (CDA) and classification by Jeffries-Matusita (JM) distance illustrates that a combination of Near Infrared spectra (NIR) and Visual spectra (VIS) is able to identify uninfected seeds from infected seeds ranging from 80-100%. Classification...

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

Science.gov (United States)

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).

MERIS-based ocean colour classification with the discrete Forel-Ule scale

NARCIS (Netherlands)

Wernand, M.R.; Hommersom, A.; van der Woerd, H.J.

2013-01-01

Multispectral information from satellite borne ocean colour sensors is at present used to characterize natural waters via the retrieval of concentrations of the three dominant optical constituents; pigments of phytoplankton, non-algal particles and coloured dissolved organic matter. A limitation of

Mitigating the effect of optical back-scatter in multispectral underwater imaging

International Nuclear Information System (INIS)

Mortazavi, Halleh; Oakley, John P; Barkat, Braham

2013-01-01

Multispectral imaging is a very useful technique for extracting information from the underwater world. However, optical back-scatter changes the intensity value in each spectral band and this distorts the estimated spectrum. In this work, a filter is used to detect the level of optical back-scatter in each spectral band from a set of multispectral images. Extraction of underwater object spectra can be done by subtracting the estimated level of optical back-scatter and scaling the remainder in each spectral band from the captured image in the corresponding band. An experiment has been designed to show the performance of the proposed filter for correcting the set of multispectral underwater images and recovering the pixel spectra. The multispectral images are captured by a B/W CCD digital camera with a fast tunable liquid-crystal filter in 33 narrow spectral bands in clear and different levels of turbid water. Reference estimates for the optical back-scatter spectra are found by comparing a clear and a degraded set of multispectral images. The accuracy and consistency of the proposed method, the extended Oakley–Bu cost function, is examined by comparing the estimated values with the reference level of an optical back-scatter spectrum. The same comparison is made for the simple estimation approach. The results show that the simple method is not reliable and fail to estimate the level of optical back-scatter spectrum accurately. The results from processing experimental images in turbid water show that the effect of optical back-scatter can be mitigated in the image of each spectral band and, as a result, the spectra of the object can be recovered. However, for a very high level of turbid water the recovery is limited because of the effect of extinction. (paper)

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

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Mitch Bryson

Full Text Available 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.

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

Science.gov (United States)

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.

Developing and Evaluating RGB Composite MODIS Imagery for Applications in National Weather Service Forecast Offices

Science.gov (United States)

Oswald, Hayden; Molthan, Andrew L.

2011-01-01

Satellite remote sensing has gained widespread use in the field of operational meteorology. Although raw satellite imagery is useful, several techniques exist which can convey multiple types of data in a more efficient way. One of these techniques is multispectral compositing. The NASA Short-term Prediction Research and Transition (SPoRT) Center has developed two multispectral satellite imagery products which utilize data from the Moderate Resolution Imaging Spectroradiometer (MODIS) aboard NASA's Terra and Aqua satellites, based upon products currently generated and used by the European Organization for the Exploitation of Meteorological Satellites (EUMETSAT). The nighttime microphysics product allows users to identify clouds occurring at different altitudes, but emphasizes fog and low cloud detection. This product improves upon current spectral difference and single channel infrared techniques. Each of the current products has its own set of advantages for nocturnal fog detection, but each also has limiting drawbacks which can hamper the analysis process. The multispectral product combines each current product with a third channel difference. Since the final image is enhanced with color, it simplifies the fog identification process. Analysis has shown that the nighttime microphysics imagery product represents a substantial improvement to conventional fog detection techniques, as well as provides a preview of future satellite capabilities to forecasters.

Quantitatively differentiating microstructural variations of skeletal muscle tissues by multispectral Mueller matrix imaging

Science.gov (United States)

Dong, Yang; He, Honghui; He, Chao; Ma, Hui

2016-10-01

Polarized light is sensitive to the microstructures of biological tissues and can be used to detect physiological changes. Meanwhile, spectral features of the scattered light can also provide abundant microstructural information of tissues. In this paper, we take the backscattering polarization Mueller matrix images of bovine skeletal muscle tissues during the 24-hour experimental time, and analyze their multispectral behavior using quantitative Mueller matrix parameters. In the processes of rigor mortis and proteolysis of muscle samples, multispectral frequency distribution histograms (FDHs) of the Mueller matrix elements can reveal rich qualitative structural information. In addition, we analyze the temporal variations of the sample using the multispectral Mueller matrix transformation (MMT) parameters. The experimental results indicate that the different stages of rigor mortis and proteolysis for bovine skeletal muscle samples can be judged by these MMT parameters. The results presented in this work show that combining with the multispectral technique, the FDHs and MMT parameters can characterize the microstructural variation features of skeletal muscle tissues. The techniques have the potential to be used as tools for quantitative assessment of meat qualities in food industry.

Detection of Melanoma Metastases in Resected Human Lymph Nodes by Noninvasive Multispectral Photoacoustic Imaging

Directory of Open Access Journals (Sweden)

Gerrit Cornelis Langhout

2014-01-01

Full Text Available Objective. Sentinel node biopsy in patients with cutaneous melanoma improves staging, provides prognostic information, and leads to an increased survival in node-positive patients. However, frozen section analysis of the sentinel node is not reliable and definitive histopathology evaluation requires days, preventing intraoperative decision-making and immediate therapy. Photoacoustic imaging can evaluate intact lymph nodes, but specificity can be hampered by other absorbers such as hemoglobin. Near infrared multispectral photoacoustic imaging is a new approach that has the potential to selectively detect melanin. The purpose of the present study is to examine the potential of multispectral photoacoustic imaging to identify melanoma metastasis in human lymph nodes. Methods. Three metastatic and nine benign lymph nodes from eight melanoma patients were scanned ex vivo using a Vevo LAZR© multispectral photoacoustic imager and were spectrally analyzed per pixel. The results were compared to histopathology as gold standard. Results. The nodal volume could be scanned within 20 minutes. An unmixing procedure was proposed to identify melanoma metastases with multispectral photoacoustic imaging. Ultrasound overlay enabled anatomical correlation. The penetration depth of the photoacoustic signal was up to 2 cm. Conclusion. Multispectral three-dimensional photoacoustic imaging allowed for selective identification of melanoma metastases in human lymph nodes.

Overview of Boundary Layer Clouds Using Satellite and Ground-Based Measurements

Science.gov (United States)

Xi, B.; Dong, X.; Wu, P.; Qiu, S.

2017-12-01

A comprehensive summary of boundary layer clouds properties based on our few recently studies will be presented. The analyses include the global cloud fractions and cloud macro/micro- physical properties based on satellite measurements using both CERES-MODIS and CloudSat/Caliposo data products,; the annual/seasonal/diurnal variations of stratocumulus clouds over different climate regions (mid-latitude land, mid-latitude ocean, and Arctic region) using DOE ARM ground-based measurements over Southern great plain (SGP), Azores (GRW), and North slope of Alaska (NSA) sites; the impact of environmental conditions to the formation and dissipation process of marine boundary layer clouds over Azores site; characterizing Arctice mixed-phase cloud structure and favorable environmental conditions for the formation/maintainess of mixed-phase clouds over NSA site. Though the presentation has widely spread topics, we will focus on the representation of the ground-based measurements over different climate regions; evaluation of satellite retrieved cloud properties using these ground-based measurements, and understanding the uncertainties of both satellite and ground-based retrievals and measurements.

Remote sensing for greenhouse detection from stereo pairs of WorldView-2 satellite

Directory of Open Access Journals (Sweden)

M.A. Aguilar

2014-05-01

Full Text Available The successful launch of the first very high resolution (VHR satellites capable of capturing panchromatic imagery of the land surface with ground sample distance even lower than 1 m (e.g. IKONOS in 1999 or QuickBird in 2001 marked the beginning of a wholly new age in remote sensing. On January 4, 2010, images of WorldView-2 were placed on the market. Possibly it is the most sophisticated commercial VHR satellite currently orbiting the Earth and the exploitation of its data poses a challenge to researchers worldwide. Moreover, the practice of under plastic agriculture had a great development in the Mediterranean area during the past 60 years, especially in Almeria, acting as a key economic driver in the area. The goal of this work is the automatic greenhouse mapping by using Object Based Image Analysis (OBIA. The required input data will be a pan-sharpened orthoimage and a normalized digital surface model (nDSM for objects, both products generated from a WorldView-2 stereo pair. The attained results show that the very high resolution 8-band multispectral and the nDSM data improve the greenhouses automatic detection. In this way, overall accuracies higher than 90% can be achieved.

Mapping within-field variations of soil organic carbon content using UAV multispectral visible near-infrared images

Science.gov (United States)

Gilliot, Jean-Marc; Vaudour, Emmanuelle; Michelin, Joël

2016-04-01

This study was carried out in the framework of the PROSTOCK-Gessol3 project supported by the French Environment and Energy Management Agency (ADEME), the TOSCA-PLEIADES-CO project of the French Space Agency (CNES) and the SOERE PRO network working on environmental impacts of Organic Waste Products recycling on field crops at long time scale. The organic matter is an important soil fertility parameter and previous studies have shown the potential of spectral information measured in the laboratory or directly in the field using field spectro-radiometer or satellite imagery to predict the soil organic carbon (SOC) content. This work proposes a method for a spatial prediction of bare cultivated topsoil SOC content, from Unmanned Aerial Vehicle (UAV) multispectral imagery. An agricultural plot of 13 ha, located in the western region of Paris France, was analysed in April 2013, shortly before sowing while it was still bare soil. Soils comprised haplic luvisols, rendzic cambisols and calcaric or colluvic cambisols. The UAV platform used was a fixed wing provided by Airinov® flying at an altitude of 150m and was equipped with a four channels multispectral visible near-infrared camera MultiSPEC 4C® (550nm, 660nm, 735 nm and 790 nm). Twenty three ground control points (GCP) were sampled within the plot according to soils descriptions. GCP positions were determined with a centimetric DGPS. Different observations and measurements were made synchronously with the drone flight: soil surface description, spectral measurements (with ASD FieldSpec 3® spectroradiometer), roughness measurements by a photogrammetric method. Each of these locations was sampled for both soil standard physico-chemical analysis and soil water content. A Structure From Motion (SFM) processing was done from the UAV imagery to produce a 15 cm resolution multispectral mosaic using the Agisoft Photoscan® software. The SOC content was modelled by partial least squares regression (PLSR) between the

Assessment of a Bidirectional Reflectance Distribution Correction of Above-Water and Satellite Water-Leaving Radiance in Coastal Waters

Science.gov (United States)

Hlaing, Soe; Gilerson, Alexander; Harmal, Tristan; Tonizzo, Alberto; Weidemann, Alan; Arnone, Robert; Ahmed, Samir

2012-01-01

Water-leaving radiances, retrieved from in situ or satellite measurements, need to be corrected for the bidirectional properties of the measured light in order to standardize the data and make them comparable with each other. The current operational algorithm for the correction of bidirectional effects from the satellite ocean color data is optimized for typical oceanic waters. However, versions of bidirectional reflectance correction algorithms specifically tuned for typical coastal waters and other case 2 conditions are particularly needed to improve the overall quality of those data. In order to analyze the bidirectional reflectance distribution function (BRDF) of case 2 waters, a dataset of typical remote sensing reflectances was generated through radiative transfer simulations for a large range of viewing and illumination geometries. Based on this simulated dataset, a case 2 water focused remote sensing reflectance model is proposed to correct above-water and satellite water-leaving radiance data for bidirectional effects. The proposed model is first validated with a one year time series of in situ above-water measurements acquired by collocated multispectral and hyperspectral radiometers, which have different viewing geometries installed at the Long Island Sound Coastal Observatory (LISCO). Match-ups and intercomparisons performed on these concurrent measurements show that the proposed algorithm outperforms the algorithm currently in use at all wavelengths, with average improvement of 2.4% over the spectral range. LISCO's time series data have also been used to evaluate improvements in match-up comparisons of Moderate Resolution Imaging Spectroradiometer satellite data when the proposed BRDF correction is used in lieu of the current algorithm. It is shown that the discrepancies between coincident in-situ sea-based and satellite data decreased by 3.15% with the use of the proposed algorithm.

Semiautomated object-based classification of rain-induced landslides with VHR multispectral images on Madeira Island

Science.gov (United States)

Heleno, Sandra; Matias, Magda; Pina, Pedro; Sousa, António Jorge

2016-04-01

A method for semiautomated landslide detection and mapping, with the ability to separate source and run-out areas, is presented in this paper. It combines object-based image analysis and a support vector machine classifier and is tested using a GeoEye-1 multispectral image, sensed 3 days after a major damaging landslide event that occurred on Madeira Island (20 February 2010), and a pre-event lidar digital terrain model. The testing is developed in a 15 km2 wide study area, where 95 % of the number of landslides scars are detected by this supervised approach. The classifier presents a good performance in the delineation of the overall landslide area, with commission errors below 26 % and omission errors below 24 %. In addition, fair results are achieved in the separation of the source from the run-out landslide areas, although in less illuminated slopes this discrimination is less effective than in sunnier, east-facing slopes.

Satellite-based Tropical Cyclone Monitoring Capabilities

Science.gov (United States)

Hawkins, J.; Richardson, K.; Surratt, M.; Yang, S.; Lee, T. F.; Sampson, C. R.; Solbrig, J.; Kuciauskas, A. P.; Miller, S. D.; Kent, J.

2012-12-01

Satellite remote sensing capabilities to monitor tropical cyclone (TC) location, structure, and intensity have evolved by utilizing a combination of operational and research and development (R&D) sensors. The microwave imagers from the operational Defense Meteorological Satellite Program [Special Sensor Microwave/Imager (SSM/I) and the Special Sensor Microwave Imager Sounder (SSMIS)] form the "base" for structure observations due to their ability to view through upper-level clouds, modest size swaths and ability to capture most storm structure features. The NASA TRMM microwave imager and precipitation radar continue their 15+ yearlong missions in serving the TC warning and research communities. The cessation of NASA's QuikSCAT satellite after more than a decade of service is sorely missed, but India's OceanSat-2 scatterometer is now providing crucial ocean surface wind vectors in addition to the Navy's WindSat ocean surface wind vector retrievals. Another Advanced Scatterometer (ASCAT) onboard EUMETSAT's MetOp-2 satellite is slated for launch soon. Passive microwave imagery has received a much needed boost with the launch of the French/Indian Megha Tropiques imager in September 2011, basically greatly supplementing the very successful NASA TRMM pathfinder with a larger swath and more frequent temporal sampling. While initial data issues have delayed data utilization, current news indicates this data will be available in 2013. Future NASA Global Precipitation Mission (GPM) sensors starting in 2014 will provide enhanced capabilities. Also, the inclusion of the new microwave sounder data from the NPP ATMS (Oct 2011) will assist in mapping TC convective structures. The National Polar orbiting Partnership (NPP) program's VIIRS sensor includes a day night band (DNB) with the capability to view TC cloud structure at night when sufficient lunar illumination exits. Examples highlighting this new capability will be discussed in concert with additional data fusion efforts.

Delineation of wetland areas from high resolution WorldView-2 data by object-based method

International Nuclear Information System (INIS)

Hassan, N; Hamid, J R A; Adnan, N A; Jaafar, M

2014-01-01

Various classification methods are available that can be used to delineate land cover types. Object-based is one of such methods for delineating the land cover from satellite imageries. This paper focuses on the digital image processing aspects of discriminating wetland areas via object-based method using high resolution satellite multispectral WorldView-2 image data taken over part of Penang Island region. This research is an attempt to improve the wetland area delineation in conjunction with a range of classification techniques which can be applied to satellite data with high spatial and spectral resolution such as World View 2. The intent is to determine a suitable approach to delineate and map these wetland areas more appropriately. There are common parameters to take into account that are pivotal in object-based method which are the spatial resolution and the range of spectral channels of the imaging sensor system. The preliminary results of the study showed object-based analysis is capable of delineating wetland region of interest with an accuracy that is acceptable to the required tolerance for land cover classification

A multispectral scanner survey of the Rocky Flats Environmental Technology Site and surrounding area, Golden, Colorado

International Nuclear Information System (INIS)

Brewster, S.B. Jr.; Brickey, D.W.; Ross, S.L.; Shines, J.E.

1997-04-01

Aerial multispectral scanner imagery was collected of the Rocky Flats Environmental Technology Site in Golden, Colorado, on June 3, 5, 6, and 7, 1994, using a Daedalus AADS1268 multispectral scanner and coincident aerial color and color infrared photography. Flight altitudes were 4,500 feet (1372 meters) above ground level to match prior 1989 survey data; 2,000 feet (609 meters) above ground level for sitewide vegetation mapping; and 1,000 feet (304 meters) above ground level for selected areas of special interest. A multispectral survey was initiated to improve the existing vegetation classification map, to identify seeps and springs, and to generate ARC/INFO Geographic Information System compatible coverages of the vegetation and wetlands for the entire site including the buffer zone. The multispectral scanner imagery and coincident aerial photography were analyzed for the detection, identification, and mapping of vegetation and wetlands. The multispectral scanner data were processed digitally while the color and color infrared photography were manually photo-interpreted to define vegetation and wetlands. Several standard image enhancement techniques were applied to the multispectral scanner data to assist image interpretation. A seep enhancement was applied and a color composite consisting of multispectral scanner channels 11, 7, and 5 (thermal infrared, mid-infrared, and red bands, respectively) proved most useful for detecting seeps, seep zones, and springs. The predawn thermal infrared data were also useful in identifying and locating seeps. The remote sensing data, mapped wetlands, and ancillary Geographic Information System compatible data sets were spatially analyzed for seeps

Multispectral colour analysis for quantitative evaluation of pseudoisochromatic color deficiency tests

Science.gov (United States)

Ozolinsh, Maris; Fomins, Sergejs

2010-11-01

Multispectral color analysis was used for spectral scanning of Ishihara and Rabkin color deficiency test book images. It was done using tunable liquid-crystal LC filters built in the Nuance II analyzer. Multispectral analysis keeps both, information on spatial content of tests and on spectral content. Images were taken in the range of 420-720nm with a 10nm step. We calculated retina neural activity charts taking into account cone sensitivity functions, and processed charts in order to find the visibility of latent symbols in color deficiency plates using cross-correlation technique. In such way the quantitative measure is found for each of diagnostics plate for three different color deficiency carrier types - protanopes, deutanopes and tritanopes. Multispectral color analysis allows to determine the CIE xyz color coordinates of pseudoisochromatic plate design elements and to perform statistical analysis of these data to compare the color quality of available color deficiency test books.

Multispectral imaging reveals biblical-period inscription unnoticed for half a century.

Directory of Open Access Journals (Sweden)

Shira Faigenbaum-Golovin

Full Text Available Most surviving biblical period Hebrew inscriptions are ostraca-ink-on-clay texts. They are poorly preserved and once unearthed, fade rapidly. Therefore, proper and timely documentation of ostraca is essential. Here we show a striking example of a hitherto invisible text on the back side of an ostracon revealed via multispectral imaging. This ostracon, found at the desert fortress of Arad and dated to ca. 600 BCE (the eve of Judah's destruction by Nebuchadnezzar, has been on display for half a century. Its front side has been thoroughly studied, while its back side was considered blank. Our research revealed three lines of text on the supposedly blank side and four "new" lines on the front side. Our results demonstrate the need for multispectral image acquisition for both sides of all ancient ink ostraca. Moreover, in certain cases we recommend employing multispectral techniques for screening newly unearthed ceramic potsherds prior to disposal.

Radiometric Cross-Calibration of the Chilean Satellite FASat-C Using RapidEye and EO-1 Hyperion Data and a Simultaneous Nadir Overpass Approach

Directory of Open Access Journals (Sweden)

Carolina Barrientos

2016-07-01

Full Text Available The absolute radiometric calibration of a satellite sensor is the critical factor that ensures the usefulness of the acquired data for quantitative applications on remote sensing. This work presents the results of the first cross-calibration of the sensor on board the Sistema Satelital de Observación de la Tierra (SSOT Chilean satellite or Air Force Satellite FASat-C. RapidEye-MSI was chosen as the reference sensor, and a simultaneous Nadir Overpass Approach (SNO was applied. The biases caused by differences in the spectral responses of both instruments were compensated through an adjustment factor derived from EO-1 Hyperion data. Through this method, the variations affecting the radiometric response of New AstroSat Optical Modular Instrument (NAOMI-1, have been corrected based on collections over the Frenchman Flat calibration site. The results of a preliminary evaluation of the pre-flight and updated coefficients have shown a significant improvement in the accuracy of at-sensor radiances and TOA reflectances: an average agreement of 2.63% (RMSE was achieved for the multispectral bands of both instruments. This research will provide a basis for the continuity of calibration and validation tasks of future Chilean space missions.

Programmable Ultra-Lightweight System Adaptable Radio Satellite Base Station

Science.gov (United States)

Varnavas, Kosta; Sims, Herb

2015-01-01

With the explosion of the CubeSat, small sat, and nanosat markets, the need for a robust, highly capable, yet affordable satellite base station, capable of telemetry capture and relay, is significant. The Programmable Ultra-Lightweight System Adaptable Radio (PULSAR) is NASA Marshall Space Flight Center's (MSFC's) software-defined digital radio, developed with previous Technology Investment Programs and Technology Transfer Office resources. The current PULSAR will have achieved a Technology Readiness Level-6 by the end of FY 2014. The extensibility of the PULSAR will allow it to be adapted to perform the tasks of a mobile base station capable of commanding, receiving, and processing satellite, rover, or planetary probe data streams with an appropriate antenna.

Spatial clustering of pixels of a multispectral image

Science.gov (United States)

Conger, James Lynn

2014-08-19

A method and system for clustering the pixels of a multispectral image is provided. A clustering system computes a maximum spectral similarity score for each pixel that indicates the similarity between that pixel and the most similar neighboring. To determine the maximum similarity score for a pixel, the clustering system generates a similarity score between that pixel and each of its neighboring pixels and then selects the similarity score that represents the highest similarity as the maximum similarity score. The clustering system may apply a filtering criterion based on the maximum similarity score so that pixels with similarity scores below a minimum threshold are not clustered. The clustering system changes the current pixel values of the pixels in a cluster based on an averaging of the original pixel values of the pixels in the cluster.

Automated detection and mapping of crown discolouration caused by jack pine budworm with 2.5 m resolution multispectral imagery

Science.gov (United States)

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

Multi-spectral lifetime imaging: methods and applications

NARCIS (Netherlands)

Fereidouni, F.

2013-01-01

The aim of this PhD project is to further develop multispectral life time imaging hardware and analyses methods. The hardware system, Lambda-Tau, generates a considerable amount of data at high speed. To fully exploit the power of this new hardware, fast and reliable data analyses methods are

RIGOROUS GEOREFERENCING OF ALSAT-2A PANCHROMATIC AND MULTISPECTRAL IMAGERY

Directory of Open Access Journals (Sweden)

I. Boukerch

2013-04-01

Full Text Available The exploitation of the full geometric capabilities of the High-Resolution Satellite Imagery (HRSI, require the development of an appropriate sensor orientation model. Several authors studied this problem; generally we have two categories of geometric models: physical and empirical models. Based on the analysis of the metadata provided with ALSAT-2A, a rigorous pushbroom camera model can be developed. This model has been successfully applied to many very high resolution imagery systems. The relation between the image and ground coordinates by the time dependant collinearity involving many coordinates systems has been tested. The interior orientation parameters must be integrated in the model, the interior parameters can be estimated from the viewing angles corresponding to the pointing directions of any detector, these values are derived from cubic polynomials provided in the metadata. The developed model integrates all the necessary elements with 33 unknown. All the approximate values of the 33 unknowns parameters may be derived from the informations contained in the metadata files provided with the imagery technical specifications or they are simply fixed to zero, so the condition equation is linearized and solved using SVD in a least square sense in order to correct the initial values using a suitable number of well-distributed GCPs. Using Alsat-2A images over the town of Toulouse in the south west of France, three experiments are done. The first is about 2D accuracy analysis using several sets of parameters. The second is about GCPs number and distribution. The third experiment is about georeferencing multispectral image by applying the model calculated from panchromatic image.

Trellis-coded CPM for satellite-based mobile communications

Science.gov (United States)

Abrishamkar, Farrokh; Biglieri, Ezio

1988-01-01

Digital transmission for satellite-based land mobile communications is discussed. To satisfy the power and bandwidth limitations imposed on such systems, a combination of trellis coding and continuous-phase modulated signals are considered. Some schemes based on this idea are presented, and their performance is analyzed by computer simulation. The results obtained show that a scheme based on directional detection and Viterbi decoding appears promising for practical applications.

Smoothing of Fused Spectral Consistent Satellite Images with TV-based Edge Detection

DEFF Research Database (Denmark)

Sveinsson, Johannes; Aanæs, Henrik; Benediktsson, Jon Atli

2007-01-01

based on satellite data. Additionally, most conventional methods are loosely connected to the image forming physics of the satellite image, giving these methods an ad hoc feel. Vesteinsson et al. [1] proposed a method of fusion of satellite images that is based on the properties of imaging physics...... in a statistically meaningful way and was called spectral consistent panshapening (SCP). In this paper we improve this framework for satellite image fusion by introducing a better image prior, via data-dependent image smoothing. The dependency is obtained via total variation edge detection method.......Several widely used methods have been proposed for fusing high resolution panchromatic data and lower resolution multi-channel data. However, many of these methods fail to maintain the spectral consistency of the fused high resolution image, which is of high importance to many of the applications...

Engineering satellite-based navigation and timing global navigation satellite systems, signals, and receivers

CERN Document Server

Betz, J

2016-01-01

This book describes the design and performance analysis of satnav systems, signals, and receivers. It also provides succinct descriptions and comparisons of all the world’s satnav systems. Its comprehensive and logical structure addresses all satnav signals and systems in operation and being developed. Engineering Satellite-Based Navigation and Timing: Global Navigation Satellite Systems, Signals, and Receivers provides the technical foundation for designing and analyzing satnav signals, systems, and receivers. Its contents and structure address all satnav systems and signals: legacy, modernized, and new. It combines qualitative information with detailed techniques and analyses, providing a comprehensive set of insights and engineering tools for this complex multidisciplinary field. Part I describes system and signal engineering including orbital mechanics and constellation design, signal design principles and underlying considerations, link budgets, qua tifying receiver performance in interference, and e...

Dual light-emitting diode-based multichannel microscopy for whole-slide multiplane, multispectral and phase imaging.

Science.gov (United States)

Liao, Jun; Wang, Zhe; Zhang, Zibang; Bian, Zichao; Guo, Kaikai; Nambiar, Aparna; Jiang, Yutong; Jiang, Shaowei; Zhong, Jingang; Choma, Michael; Zheng, Guoan

2018-02-01

We report the development of a multichannel microscopy for whole-slide multiplane, multispectral and phase imaging. We use trinocular heads to split the beam path into 6 independent channels and employ a camera array for parallel data acquisition, achieving a maximum data throughput of approximately 1 gigapixel per second. To perform single-frame rapid autofocusing, we place 2 near-infrared light-emitting diodes (LEDs) at the back focal plane of the condenser lens to illuminate the sample from 2 different incident angles. A hot mirror is used to direct the near-infrared light to an autofocusing camera. For multiplane whole-slide imaging (WSI), we acquire 6 different focal planes of a thick specimen simultaneously. For multispectral WSI, we relay the 6 independent image planes to the same focal position and simultaneously acquire information at 6 spectral bands. For whole-slide phase imaging, we acquire images at 3 focal positions simultaneously and use the transport-of-intensity equation to recover the phase information. We also provide an open-source design to further increase the number of channels from 6 to 15. The reported platform provides a simple solution for multiplexed fluorescence imaging and multimodal WSI. Acquiring an instant focal stack without z-scanning may also enable fast 3-dimensional dynamic tracking of various biological samples. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

METHOD OF RADIOMETRIC DISTORTION CORRECTION OF MULTISPECTRAL DATA FOR THE EARTH REMOTE SENSING

Directory of Open Access Journals (Sweden)

A. N. Grigoriev

2015-07-01

Full Text Available The paper deals with technologies of ground secondary processing of heterogeneous multispectral data. The factors of heterogeneous data include uneven illumination of objects on the Earth surface caused by different properties of the relief. A procedure for the image restoration of spectral channels by means of terrain distortion compensation is developed. The object matter of this paper is to improve the quality of the results during image restoration of areas with large and medium landforms. Methods. Researches are based on the elements of the digital image processing theory, statistical processing of the observation results and the theory of multi-dimensional arrays. Main Results. The author has introduced operations on multidimensional arrays: concatenation and elementwise division. Extended model description for input data about the area is given. The model contains all necessary data for image restoration. Correction method for multispectral data radiometric distortions of the Earth remote sensing has been developed. The method consists of two phases: construction of empirical dependences for spectral reflectance on the relief properties and restoration of spectral images according to semiempirical data. Practical Relevance. Research novelty lies in developme nt of the application theory of multidimensional arrays with respect to the processing of multispectral data, together with data on the topography and terrain objects. The results are usable for development of radiometric data correction tools. Processing is performed on the basis of a digital terrain model without carrying out ground works connected with research of the objects reflective properties.

Extracting Urban Morphology for Atmospheric Modeling from Multispectral and SAR Satellite Imagery

Science.gov (United States)

Wittke, S.; Karila, K.; Puttonen, E.; Hellsten, A.; Auvinen, M.; Karjalainen, M.

2017-05-01

This paper presents an approach designed to derive an urban morphology map from satellite data while aiming to minimize the cost of data and user interference. The approach will help to provide updates to the current morphological databases around the world. The proposed urban morphology maps consist of two layers: 1) Digital Elevation Model (DEM) and 2) land cover map. Sentinel-2 data was used to create a land cover map, which was realized through image classification using optical range indices calculated from image data. For the purpose of atmospheric modeling, the most important classes are water and vegetation areas. The rest of the area includes bare soil and built-up areas among others, and they were merged into one class in the end. The classification result was validated with ground truth data collected both from field measurements and aerial imagery. The overall classification accuracy for the three classes is 91 %. TanDEM-X data was processed into two DEMs with different grid sizes using interferometric SAR processing. The resulting DEM has a RMSE of 3.2 meters compared to a high resolution DEM, which was estimated through 20 control points in flat areas. Comparing the derived DEM with the ground truth DEM from airborne LIDAR data, it can be seen that the street canyons, that are of high importance for urban atmospheric modeling are not detectable in the TanDEM-X DEM. However, the derived DEM is suitable for a class of urban atmospheric models. Based on the numerical modeling needs for regional atmospheric pollutant dispersion studies, the generated files enable the extraction of relevant parametrizations, such as Urban Canopy Parameters (UCP).

EXTRACTING URBAN MORPHOLOGY FOR ATMOSPHERIC MODELING FROM MULTISPECTRAL AND SAR SATELLITE IMAGERY

Directory of Open Access Journals (Sweden)

S. Wittke

2017-05-01

Full Text Available This paper presents an approach designed to derive an urban morphology map from satellite data while aiming to minimize the cost of data and user interference. The approach will help to provide updates to the current morphological databases around the world. The proposed urban morphology maps consist of two layers: 1 Digital Elevation Model (DEM and 2 land cover map. Sentinel-2 data was used to create a land cover map, which was realized through image classification using optical range indices calculated from image data. For the purpose of atmospheric modeling, the most important classes are water and vegetation areas. The rest of the area includes bare soil and built-up areas among others, and they were merged into one class in the end. The classification result was validated with ground truth data collected both from field measurements and aerial imagery. The overall classification accuracy for the three classes is 91 %. TanDEM-X data was processed into two DEMs with different grid sizes using interferometric SAR processing. The resulting DEM has a RMSE of 3.2 meters compared to a high resolution DEM, which was estimated through 20 control points in flat areas. Comparing the derived DEM with the ground truth DEM from airborne LIDAR data, it can be seen that the street canyons, that are of high importance for urban atmospheric modeling are not detectable in the TanDEM-X DEM. However, the derived DEM is suitable for a class of urban atmospheric models. Based on the numerical modeling needs for regional atmospheric pollutant dispersion studies, the generated files enable the extraction of relevant parametrizations, such as Urban Canopy Parameters (UCP.

Multispectral open-air intraoperative fluorescence imaging.

Science.gov (United States)

Behrooz, Ali; Waterman, Peter; Vasquez, Kristine O; Meganck, Jeff; Peterson, Jeffrey D; Faqir, Ilias; Kempner, Joshua

2017-08-01

Intraoperative fluorescence imaging informs decisions regarding surgical margins by detecting and localizing signals from fluorescent reporters, labeling targets such as malignant tissues. This guidance reduces the likelihood of undetected malignant tissue remaining after resection, eliminating the need for additional treatment or surgery. The primary challenges in performing open-air intraoperative fluorescence imaging come from the weak intensity of the fluorescence signal in the presence of strong surgical and ambient illumination, and the auto-fluorescence of non-target components, such as tissue, especially in the visible spectral window (400-650 nm). In this work, a multispectral open-air fluorescence imaging system is presented for translational image-guided intraoperative applications, which overcomes these challenges. The system is capable of imaging weak fluorescence signals with nanomolar sensitivity in the presence of surgical illumination. This is done using synchronized fluorescence excitation and image acquisition with real-time background subtraction. Additionally, the system uses a liquid crystal tunable filter for acquisition of multispectral images that are used to spectrally unmix target fluorescence from non-target auto-fluorescence. Results are validated by preclinical studies on murine models and translational canine oncology models.

True Colour Classification of Natural Waters with Medium-Spectral Resolution Satellites: SeaWiFS, MODIS, MERIS and OLCI

Directory of Open Access Journals (Sweden)

Hendrik J. van der Woerd

2015-10-01

Full Text Available The colours from natural waters differ markedly over the globe, depending on the water composition and illumination conditions. The space-borne “ocean colour” instruments are operational instruments designed to retrieve important water-quality indicators, based on the measurement of water leaving radiance in a limited number (5 to 10 of narrow (≈10 nm bands. Surprisingly, the analysis of the satellite data has not yet paid attention to colour as an integral optical property that can also be retrieved from multispectral satellite data. In this paper we re-introduce colour as a valuable parameter that can be expressed mainly by the hue angle (α. Based on a set of 500 synthetic spectra covering a broad range of natural waters a simple algorithm is developed to derive the hue angle from SeaWiFS, MODIS, MERIS and OLCI data. The algorithm consists of a weighted linear sum of the remote sensing reflectance in all visual bands plus a correction term for the specific band-setting of each instrument. The algorithm is validated by a set of 603 hyperspectral measurements from inland-, coastal- and near-ocean waters. We conclude that the hue angle is a simple objective parameter of natural waters that can be retrieved uniformly for all space-borne ocean colour instruments.

Science applications of a multispectral microscopic imager for the astrobiological exploration of Mars

Science.gov (United States)

Nunez, Jorge; Farmer, Jack; Sellar, R. Glenn; Swayze, Gregg A.; Blaney, Diana L.

2014-01-01

Future astrobiological missions to Mars are likely to emphasize the use of rovers with in situ petrologic capabilities for selecting the best samples at a site for in situ analysis with onboard lab instruments or for caching for potential return to Earth. Such observations are central to an understanding of the potential for past habitable conditions at a site and for identifying samples most likely to harbor fossil biosignatures. The Multispectral Microscopic Imager (MMI) provides multispectral reflectance images of geological samples at the microscale, where each image pixel is composed of a visible/shortwave infrared spectrum ranging from 0.46 to 1.73 μm. This spectral range enables the discrimination of a wide variety of rock-forming minerals, especially Fe-bearing phases, and the detection of hydrated minerals. The MMI advances beyond the capabilities of current microimagers on Mars by extending the spectral range into the infrared and increasing the number of spectral bands. The design employs multispectral light-emitting diodes and an uncooled indium gallium arsenide focal plane array to achieve a very low mass and high reliability. To better understand and demonstrate the capabilities of the MMI for future surface missions to Mars, we analyzed samples from Mars-relevant analog environments with the MMI. Results indicate that the MMI images faithfully resolve the fine-scale microtextural features of samples and provide important information to help constrain mineral composition. The use of spectral endmember mapping reveals the distribution of Fe-bearing minerals (including silicates and oxides) with high fidelity, along with the presence of hydrated minerals. MMI-based petrogenetic interpretations compare favorably with laboratory-based analyses, revealing the value of the MMI for future in situ rover-mediated astrobiological exploration of Mars.

LAKE ICE DETECTION IN LOW-RESOLUTION OPTICAL SATELLITE IMAGES

Directory of Open Access Journals (Sweden)

M. Tom

2018-05-01

Full Text Available Monitoring and analyzing the (decreasing trends in lake freezing provides important information for climate research. Multi-temporal satellite images are a natural data source to survey ice on lakes. In this paper, we describe a method for lake ice monitoring, which uses low spatial resolution (250 m–1000 m satellite images to determine whether a lake is frozen or not. We report results on four selected lakes in Switzerland: Sihl, Sils, Silvaplana and St. Moritz. These lakes have different properties regarding area, altitude, surrounding topography and freezing frequency, describing cases of medium to high difficulty. Digitized Open Street Map (OSM lake outlines are back-projected on to the image space after generalization. As a pre-processing step, the absolute geolocation error of the lake outlines is corrected by matching the projected outlines to the images. We define the lake ice detection as a two-class (frozen, non-frozen semantic segmentation problem. Several spectral channels of the multi-spectral satellite data are used, both reflective and emissive (thermal. Only the cloud-free (clean pixels which lie completely inside the lake are analyzed. The most useful channels to solve the problem are selected with xgboost and visual analysis of histograms of reference data, while the classification is done with non-linear support vector machine (SVM. We show experimentally that this straight-forward approach works well with both MODIS and VIIRS satellite imagery. Moreover, we show that the algorithm produces consistent results when tested on data from multiple winters.

Lake Ice Detection in Low-Resolution Optical Satellite Images

Science.gov (United States)

Tom, M.; Kälin, U.; Sütterlin, M.; Baltsavias, E.; Schindler, K.

2018-05-01

Monitoring and analyzing the (decreasing) trends in lake freezing provides important information for climate research. Multi-temporal satellite images are a natural data source to survey ice on lakes. In this paper, we describe a method for lake ice monitoring, which uses low spatial resolution (250 m-1000 m) satellite images to determine whether a lake is frozen or not. We report results on four selected lakes in Switzerland: Sihl, Sils, Silvaplana and St. Moritz. These lakes have different properties regarding area, altitude, surrounding topography and freezing frequency, describing cases of medium to high difficulty. Digitized Open Street Map (OSM) lake outlines are back-projected on to the image space after generalization. As a pre-processing step, the absolute geolocation error of the lake outlines is corrected by matching the projected outlines to the images. We define the lake ice detection as a two-class (frozen, non-frozen) semantic segmentation problem. Several spectral channels of the multi-spectral satellite data are used, both reflective and emissive (thermal). Only the cloud-free (clean) pixels which lie completely inside the lake are analyzed. The most useful channels to solve the problem are selected with xgboost and visual analysis of histograms of reference data, while the classification is done with non-linear support vector machine (SVM). We show experimentally that this straight-forward approach works well with both MODIS and VIIRS satellite imagery. Moreover, we show that the algorithm produces consistent results when tested on data from multiple winters.

System for critical infrastructure security based on multispectral observation-detection module

Science.gov (United States)

Trzaskawka, Piotr; Kastek, Mariusz; Życzkowski, Marek; Dulski, Rafał; Szustakowski, Mieczysław; Ciurapiński, Wiesław; Bareła, Jarosław

2013-10-01

Recent terrorist attacks and possibilities of such actions in future have forced to develop security systems for critical infrastructures that embrace sensors technologies and technical organization of systems. The used till now perimeter protection of stationary objects, based on construction of a ring with two-zone fencing, visual cameras with illumination are efficiently displaced by the systems of the multisensor technology that consists of: visible technology - day/night cameras registering optical contrast of a scene, thermal technology - cheap bolometric cameras recording thermal contrast of a scene and active ground radars - microwave and millimetre wavelengths that record and detect reflected radiation. Merging of these three different technologies into one system requires methodology for selection of technical conditions of installation and parameters of sensors. This procedure enables us to construct a system with correlated range, resolution, field of view and object identification. Important technical problem connected with the multispectral system is its software, which helps couple the radar with the cameras. This software can be used for automatic focusing of cameras, automatic guiding cameras to an object detected by the radar, tracking of the object and localization of the object on the digital map as well as target identification and alerting. Based on "plug and play" architecture, this system provides unmatched flexibility and simplistic integration of sensors and devices in TCP/IP networks. Using a graphical user interface it is possible to control sensors and monitor streaming video and other data over the network, visualize the results of data fusion process and obtain detailed information about detected intruders over a digital map. System provide high-level applications and operator workload reduction with features such as sensor to sensor cueing from detection devices, automatic e-mail notification and alarm triggering. The paper presents

MRO CRISM MULTISPECTRAL REDUCED DATA RECORD V1.0

Data.gov (United States)

National Aeronautics and Space Administration — This dataset contains CRISM Multispectral Reduced Data Records (MRDRs). MRDRs are organized into 30 subdirectories named by the Mars Chart containing the MRDR, e.g....

Satellite based Ocean Forecasting, the SOFT project

Science.gov (United States)

Stemmann, L.; Tintoré, J.; Moneris, S.

2003-04-01

The knowledge of future oceanic conditions would have enormous impact on human marine related areas. For such reasons, a number of international efforts are being carried out to obtain reliable and manageable ocean forecasting systems. Among the possible techniques that can be used to estimate the near future states of the ocean, an ocean forecasting system based on satellite imagery is developped through the Satelitte based Ocean ForecasTing project (SOFT). SOFT, established by the European Commission, considers the development of a forecasting system of the ocean space-time variability based on satellite data by using Artificial Intelligence techniques. This system will be merged with numerical simulation approaches, via assimilation techniques, to get a hybrid SOFT-numerical forecasting system of improved performance. The results of the project will provide efficient forecasting of sea-surface temperature structures, currents, dynamic height, and biological activity associated to chlorophyll fields. All these quantities could give valuable information on the planning and management of human activities in marine environments such as navigation, fisheries, pollution control, or coastal management. A detailed identification of present or new needs and potential end-users concerned by such an operational tool is being performed. The project would study solutions adapted to these specific needs.

[Surveying a zoological facility through satellite-based geodesy].

Science.gov (United States)

Böer, M; Thien, W; Tölke, D

2000-06-01

In the course of a thesis submitted for a diploma degree within the Fachhochschule Oldenburg the Serengeti Safaripark was surveyed in autumn and winter 1996/97 laying in the planning foundations for the application for licences from the controlling authorities. Taking into consideration the special way of keeping animals in the Serengeti Safaripark (game ranching, spacious walk-through-facilities) the intention was to employ the outstanding satellite based geodesy. This technology relies on special aerials receiving signals from 24 satellites which circle around the globe. These data are being gathered and examined. This examination produces the exact position of this aerial in a system of coordinates which allows depicting this point on a map. This procedure was used stationary (from a strictly defined point) as well as in the movement (in a moving car). Additionally conventional procedures were used when the satellite based geodesy came to its limits. Finally a detailed map of the Serengeti Safaripark was created which shows the position and size of stables and enclosures as well as wood and water areas and the sectors of the leisure park. Furthermore the established areas of the enclosures together with an already existing animal databank have flown into an information system with the help of which the stock of animals can be managed enclosure-orientated.

A Study on Satellite Diagnostic Expert Systems Using Case-Based Approach

Directory of Open Access Journals (Sweden)

Young-Tack Park

1997-06-01

Full Text Available Many research works are on going to monitor and diagnose diverse malfunctions of satellite systems as the complexity and number of satellites increase. Currently, many works on monitoring and diagnosis are carried out by human experts but there are needs to automate much of the routine works of them. Hence, it is necessary to study on using expert systems which can assist human experts routine work by doing automatically, thereby allow human experts devote their expertise more critical and important areas of monitoring and diagnosis. In this paper, we are employing artificial intelligence techniques to model human experts' knowledge and inference the constructed knowledge. Especially, case-based approaches are used to construct a knowledge base to model human expert capabilities which use previous typical exemplars. We have designed and implemented a prototype case-based system for diagnosing satellite malfunctions using cases. Our system remembers typical failure cases and diagnoses a current malfunction by indexing the case base. Diverse methods are used to build a more user friendly interface which allows human experts can build a knowledge base in as easy way.

Developing a sustainable satellite-based environmental monitoring system In Nigeria

Science.gov (United States)

Akinyede, J. O.; Adepoju, K. A.; Akinluyi, F. O.; Anifowose, A. Y. B.

2015-10-01

Increased anthropogenic activities over the year have remained a major factor of the Earth changing environment. This phenomenon has given rise to a number of environmental degraded sites that characterize the Nigeria's landscape. The human-induced elements include gully erosion, mangrove ecosystems degradation, desertification and deforestation, particularly in the south east, Niger Delta, north east and south west of Nigeria respectively, as well as river flooding/flood plain inundation and land degradation around Kainji lake area. Because of little or no effective management measures, the attendant environmental hazards have been extremely damaging to the infrastructures and socio-economic development of the affected area. Hence, a concerted effort, through integrated and space-based research, is being intensified to manage and monitor the environment in order to restore the stability, goods and services of the environment. This has justified Nigeria's investment in its space programme, especially the launch of NigeriaSat-1, an Earth observation micro-satellite in constellation with five (5) other similar satellites, Alsat-1, China DMC, Bilsat-1, DEMOS and UK DMC belonging to Algeria, China, Turkey, Spain and United Kingdom respectively. The use of data from these satellites, particularly NigeriaSat-1, in conjunction with associated technologies has proved to be very useful in understanding the influence of both natural and human activities on the Nigeria's ecosystems and environment. The results of some researches on specific applications of Nigerian satellites are presented in this paper. Appropriate sustainable land and water resources management in the affected areas, based on Nigeria's satellite data capture and integration, are also discussed.

Conical scan impact study. Volume 2: Small local user data processing facility. [multispectral band scanner design alternatives for earth resources data

Science.gov (United States)

Ebert, D. H.; Chase, P. E.; Dye, J.; Fahline, W. C.; Johnson, R. H.

1973-01-01

The impact of a conical scan versus a linear scan multispectral scanner (MSS) instrument on a small local-user data processing facility was studied. User data requirements were examined to determine the unique system rquirements for a low cost ground system (LCGS) compatible with the Earth Observatory Satellite (EOS) system. Candidate concepts were defined for the LCGS and preliminary designs were developed for selected concepts. The impact of a conical scan MSS versus a linear scan MSS was evaluated for the selected concepts. It was concluded that there are valid user requirements for the LCGS and, as a result of these requirements, the impact of the conical scanner is minimal, although some new hardware development for the LCGS is necessary to handle conical scan data.

Entropy-Based Block Processing for Satellite Image Registration

Directory of Open Access Journals (Sweden)

Ikhyun Lee

2012-11-01

Full Text Available Image registration is an important task in many computer vision applications such as fusion systems, 3D shape recovery and earth observation. Particularly, registering satellite images is challenging and time-consuming due to limited resources and large image size. In such scenario, state-of-the-art image registration methods such as scale-invariant feature transform (SIFT may not be suitable due to high processing time. In this paper, we propose an algorithm based on block processing via entropy to register satellite images. The performance of the proposed method is evaluated using different real images. The comparative analysis shows that it not only reduces the processing time but also enhances the accuracy.

Spatial and radiometric characterization of multi-spectrum satellite images through multi-fractal analysis

Science.gov (United States)

Alonso, Carmelo; Tarquis, Ana M.; Zúñiga, Ignacio; Benito, Rosa M.

2017-03-01

Several studies have shown that vegetation indexes can be used to estimate root zone soil moisture. Earth surface images, obtained by high-resolution satellites, presently give a lot of information on these indexes, based on the data of several wavelengths. Because of the potential capacity for systematic observations at various scales, remote sensing technology extends the possible data archives from the present time to several decades back. Because of this advantage, enormous efforts have been made by researchers and application specialists to delineate vegetation indexes from local scale to global scale by applying remote sensing imagery. In this work, four band images have been considered, which are involved in these vegetation indexes, and were taken by satellites Ikonos-2 and Landsat-7 of the same geographic location, to study the effect of both spatial (pixel size) and radiometric (number of bits coding the image) resolution on these wavelength bands as well as two vegetation indexes: the Normalized Difference Vegetation Index (NDVI) and the Enhanced Vegetation Index (EVI). In order to do so, a multi-fractal analysis of these multi-spectral images was applied in each of these bands and the two indexes derived. The results showed that spatial resolution has a similar scaling effect in the four bands, but radiometric resolution has a larger influence in blue and green bands than in red and near-infrared bands. The NDVI showed a higher sensitivity to the radiometric resolution than EVI. Both were equally affected by the spatial resolution. From both factors, the spatial resolution has a major impact in the multi-fractal spectrum for all the bands and the vegetation indexes. This information should be taken in to account when vegetation indexes based on different satellite sensors are obtained.

Fusion of LIDAR Data and Multispectral Imagery for Effective Building Detection Based on Graph and Connected Component Analysis

Science.gov (United States)

Gilani, S. A. N.; Awrangjeb, M.; Lu, G.

2015-03-01

Building detection in complex scenes is a non-trivial exercise due to building shape variability, irregular terrain, shadows, and occlusion by highly dense vegetation. In this research, we present a graph based algorithm, which combines multispectral imagery and airborne LiDAR information to completely delineate the building boundaries in urban and densely vegetated area. In the first phase, LiDAR data is divided into two groups: ground and non-ground data, using ground height from a bare-earth DEM. A mask, known as the primary building mask, is generated from the non-ground LiDAR points where the black region represents the elevated area (buildings and trees), while the white region describes the ground (earth). The second phase begins with the process of Connected Component Analysis (CCA) where the number of objects present in the test scene are identified followed by initial boundary detection and labelling. Additionally, a graph from the connected components is generated, where each black pixel corresponds to a node. An edge of a unit distance is defined between a black pixel and a neighbouring black pixel, if any. An edge does not exist from a black pixel to a neighbouring white pixel, if any. This phenomenon produces a disconnected components graph, where each component represents a prospective building or a dense vegetation (a contiguous block of black pixels from the primary mask). In the third phase, a clustering process clusters the segmented lines, extracted from multispectral imagery, around the graph components, if possible. In the fourth step, NDVI, image entropy, and LiDAR data are utilised to discriminate between vegetation, buildings, and isolated building's occluded parts. Finally, the initially extracted building boundary is extended pixel-wise using NDVI, entropy, and LiDAR data to completely delineate the building and to maximise the boundary reach towards building edges. The proposed technique is evaluated using two Australian data sets

Satellite Remote Sensing of Particulate Matter Air Quality: Progress, Potential and Pitfalls (Invited)

Science.gov (United States)

Christopher, S. A.

2009-12-01

Satellite Remote Sensing of Particulate Matter Air Quality: Progress, Potential and Pitfalls Abstract. Fine or respirable particles with particle aerodynamic diameters less than 2.5 µm (PM2.5) affect visibility, change cloud properties, reflect and absorb incoming solar radiation, affect human health and are ubiquitous in the atmosphere. These particles are injected into the atmosphere either as primary emissions or form into the atmosphere by gas to particle conversion. There are various sources of PM2.5 including emissions from automobiles, industrial exhaust, and agricultural fires. In 2006, the United States Environmental Protection Agency (EPA) made the standards stringent by changing the 24-hr averaged PM2.5 mass values from 65µgm-3 to 35µgm-3. This was primarily based on epidemiological studies that showed the long term health benefits of making the PM2.5 standards stringent. Typically PM2.5 mass concentration is measured from surface monitors and in the United States there are nearly 1000 such filter based daily and 600 contiguous stations managed by federal, state, local, and tribal agencies. Worldwide, there are few PM2.5 ground monitors since they are expensive to purchase, maintain and operate. Satellite remote sensing therefore provides a viable method for monitoring PM2.5 from space. Although, there are several hundred satellites currently in orbit and not all of them are suited for PM2.5 air quality assessments. Typically multi-spectral reflected solar radiation measurements from space-borne sensors are converted to aerosol optical depth (AOD) which is a measure of the column (surface to top of atmosphere) integrated extinction (absorption plus scattering). This column AOD (usually at 550 nm) is often converted to PM2.5 mass near the ground using various techniques. In this presentation we discuss the progress over the last decade on assessing PM2.5 from satellites; outline the potential and discuss the various pitfalls that one encounters. We

Dual multispectral and 3D structured light laparoscope

Science.gov (United States)

Clancy, Neil T.; Lin, Jianyu; Arya, Shobhit; Hanna, George B.; Elson, Daniel S.

2015-03-01

Intraoperative feedback on tissue function, such as blood volume and oxygenation would be useful to the surgeon in cases where current clinical practice relies on subjective measures, such as identification of ischaemic bowel or tissue viability during anastomosis formation. Also, tissue surface profiling may be used to detect and identify certain pathologies, as well as diagnosing aspects of tissue health such as gut motility. In this paper a dual modality laparoscopic system is presented that combines multispectral reflectance and 3D surface imaging. White light illumination from a xenon source is detected by a laparoscope-mounted fast filter wheel camera to assemble a multispectral image (MSI) cube. Surface shape is then calculated using a spectrally-encoded structured light (SL) pattern detected by the same camera and triangulated using an active stereo technique. Images of porcine small bowel were acquired during open surgery. Tissue reflectance spectra were acquired and blood volume was calculated at each spatial pixel across the bowel wall and mesentery. SL features were segmented and identified using a `normalised cut' algoritm and the colour vector of each spot. Using the 3D geometry defined by the camera coordinate system the multispectral data could be overlaid onto the surface mesh. Dual MSI and SL imaging has the potential to provide augmented views to the surgeon supplying diagnostic information related to blood supply health and organ function. Future work on this system will include filter optimisation to reduce noise in tissue optical property measurement, and minimise spot identification errors in the SL pattern.

Oximetry using multispectral imaging: theory and application

Science.gov (United States)

MacKenzie, Lewis E.; Harvey, Andrew R.

2018-06-01

Multispectral imaging (MSI) is a technique for measurement of blood oxygen saturation in vivo that can be applied using various imaging modalities to provide new insights into physiology and disease development. This tutorial aims to provide a thorough introduction to the theory and application of MSI oximetry for researchers new to the field, whilst also providing detailed information for more experienced researchers. The optical theory underlying two-wavelength oximetry, three-wavelength oximetry, pulse oximetry, and multispectral oximetry algorithms are described in detail. The varied challenges of applying MSI oximetry to in vivo applications are outlined and discussed, covering: the optical properties of blood and tissue, optical paths in blood vessels, tissue auto-fluorescence, oxygen diffusion, and common oximetry artefacts. Essential image processing techniques for MSI are discussed, in particular, image acquisition, image registration strategies, and blood vessel line profile fitting. Calibration and validation strategies for MSI are discussed, including comparison techniques, physiological interventions, and phantoms. The optical principles and unique imaging capabilities of various cutting-edge MSI oximetry techniques are discussed, including photoacoustic imaging, spectroscopic optical coherence tomography, and snapshot MSI.

Geospatial Analysis and Remote Sensing from Airplanes and Satellites for Cultural Resources Management

Science.gov (United States)

Giardino, Marco J.; Haley, Bryan S.

2005-01-01

Cultural resource management consists of research to identify, evaluate, document and assess cultural resources, planning to assist in decision-making, and stewardship to implement the preservation, protection and interpretation of these decisions and plans. One technique that may be useful in cultural resource management archaeology is remote sensing. It is the acquisition of data and derivative information about objects or materials (targets) located on the Earth's surface or in its atmosphere by using sensor mounted on platforms located at a distance from the targets to make measurements on interactions between the targets and electromagnetic radiation. Included in this definition are systems that acquire imagery by photographic methods and digital multispectral sensors. Data collected by digital multispectral sensors on aircraft and satellite platforms play a prominent role in many earth science applications, including land cover mapping, geology, soil science, agriculture, forestry, water resource management, urban and regional planning, and environmental assessments. Inherent in the analysis of remotely sensed data is the use of computer-based image processing techniques. Geographical information systems (GIS), designed for collecting, managing, and analyzing spatial information, are also useful in the analysis of remotely sensed data. A GIS can be used to integrate diverse types of spatially referenced digital data, including remotely sensed and map data. In archaeology, these tools have been used in various ways to aid in cultural resource projects. For example, they have been used to predict the presence of archaeological resources using modern environmental indicators. Remote sensing techniques have also been used to directly detect the presence of unknown sites based on the impact of past occupation on the Earth's surface. Additionally, remote sensing has been used as a mapping tool aimed at delineating the boundaries of a site or mapping previously

Automated segmentation of pigmented skin lesions in multispectral imaging

International Nuclear Information System (INIS)

Carrara, Mauro; Tomatis, Stefano; Bono, Aldo; Bartoli, Cesare; Moglia, Daniele; Lualdi, Manuela; Colombo, Ambrogio; Santinami, Mario; Marchesini, Renato

2005-01-01

The aim of this study was to develop an algorithm for the automatic segmentation of multispectral images of pigmented skin lesions. The study involved 1700 patients with 1856 cutaneous pigmented lesions, which were analysed in vivo by a novel spectrophotometric system, before excision. The system is able to acquire a set of 15 different multispectral images at equally spaced wavelengths between 483 and 951 nm. An original segmentation algorithm was developed and applied to the whole set of lesions and was able to automatically contour them all. The obtained lesion boundaries were shown to two expert clinicians, who, independently, rejected 54 of them. The 97.1% contour accuracy indicates that the developed algorithm could be a helpful and effective instrument for the automatic segmentation of skin pigmented lesions. (note)

Interference and deception detection technology of satellite navigation based on deep learning

Science.gov (United States)

Chen, Weiyi; Deng, Pingke; Qu, Yi; Zhang, Xiaoguang; Li, Yaping

2017-10-01

Satellite navigation system plays an important role in people's daily life and war. The strategic position of satellite navigation system is prominent, so it is very important to ensure that the satellite navigation system is not disturbed or destroyed. It is a critical means to detect the jamming signal to avoid the accident in a navigation system. At present, the detection technology of jamming signal in satellite navigation system is not intelligent , mainly relying on artificial decision and experience. For this issue, the paper proposes a method based on deep learning to monitor the interference source in a satellite navigation. By training the interference signal data, and extracting the features of the interference signal, the detection sys tem model is constructed. The simulation results show that, the detection accuracy of our detection system can reach nearly 70%. The method in our paper provides a new idea for the research on intelligent detection of interference and deception signal in a satellite navigation system.

Remote quantitative analysis of minerals based on multispectral line-calibrated laser-induced breakdown spectroscopy (LIBS).

Science.gov (United States)

Wan, Xiong; Wang, Peng

2014-01-01

Laser-induced breakdown spectroscopy (LIBS) is a feasible remote sensing technique used for mineral analysis in some unapproachable places where in situ probing is needed, such as analysis of radioactive elements in a nuclear leak or the detection of elemental compositions and contents of minerals on planetary and lunar surfaces. Here a compact custom 15 m focus optical component, combining a six times beam expander with a telescope, has been built, with which the laser beam of a 1064 nm Nd ; YAG laser is focused on remote minerals. The excited LIBS signals that reveal the elemental compositions of minerals are collected by another compact single lens-based signal acquisition system. In our remote LIBS investigations, the LIBS spectra of an unknown ore have been detected, from which the metal compositions are obtained. In addition, a multi-spectral line calibration (MSLC) method is proposed for the quantitative analysis of elements. The feasibility of the MSLC and its superiority over a single-wavelength determination have been confirmed by comparison with traditional chemical analysis of the copper content in the ore.

TREE SPECIES CLASSIFICATION OF BROADLEAVED FORESTS IN NAGANO, CENTRAL JAPAN, USING AIRBORNE LASER DATA AND MULTISPECTRAL IMAGES

Directory of Open Access Journals (Sweden)

S. Deng

2017-10-01

Full Text Available This study attempted to classify three coniferous and ten broadleaved tree species by combining airborne laser scanning (ALS data and multispectral images. The study area, located in Nagano, central Japan, is within the broadleaved forests of the Afan Woodland area. A total of 235 trees were surveyed in 2016, and we recorded the species, DBH, and tree height. The geographical position of each tree was collected using a Global Navigation Satellite System (GNSS device. Tree crowns were manually detected using GNSS position data, field photographs, true-color orthoimages with three bands (red-green-blue, RGB, 3D point clouds, and a canopy height model derived from ALS data. Then a total of 69 features, including 27 image-based and 42 point-based features, were extracted from the RGB images and the ALS data to classify tree species. Finally, the detected tree crowns were classified into two classes for the first level (coniferous and broadleaved trees, four classes for the second level (Pinus densiflora, Larix kaempferi, Cryptomeria japonica, and broadleaved trees, and 13 classes for the third level (three coniferous and ten broadleaved species, using the 27 image-based features, 42 point-based features, all 69 features, and the best combination of features identified using a neighborhood component analysis algorithm, respectively. The overall classification accuracies reached 90 % at the first and second levels but less than 60 % at the third level. The classifications using the best combinations of features had higher accuracies than those using the image-based and point-based features and the combination of all of the 69 features.

Wide area change detection with satellite imagery for locating underground nuclear testing

International Nuclear Information System (INIS)

Canty, M.J.; Jasani, B.; Schlittenhardt, J.

2001-01-01

With the advent of high resolution optical imagery from commercial earth observation satellites, the use of remote sensing data for verification of nuclear non-proliferation agreements is becoming increasingly attractive. Non-governmental organizations are routinely publishing high-quality imagery of sensitive nuclear installations round the world, and international verification authorities, such as the International Atomic Energy Agency (IAEA) or the Comprehensive Nuclear-Test-Ban Treaty Organization (CTBTO), will also want to make use, directly or indirectly, of this additional open source of information. Exact location of the sites of underground nuclear explosions is a task eminently suited to satellite imagery. Here both moderate resolutions for detecting signals in very large testing ranges as well as high resolution images for exact interpretation play important roles. We describe in our paper a particularly sensitive change detection procedure for bitemporal, multispectral satellite imagery which can be used to locate the spall zone of underground nuclear explosions with commercial satellite imagery. The method is based on the multivariate alteration detection (MAD) technique of Nielsen et al. Linear combinations of the spectral channels in two images of the same scene are chosen so as to minimize their positive correlation. This leads to a series of difference images - the so-called MAD components - which are mutually orthogonal (uncorrelated) and ordered according to decreasing variance in their pixel intensities. Since interesting changes in man-made structures may contribute minimally to the overall variance (as the latter may be dominated for instance by seasonal vegetation differences) it is often the case that such changes turn up in a higher order MAD component. This is because they will be uncorrelated with seasonal vegetation changes, stochastic image noise or other major contributions to the overall change signal. This in fact is one of the

Concentric circular ring and nanodisk optical antenna enhanced multispectral quantum dot infrared photodetector with spectral localization

International Nuclear Information System (INIS)

Zhang, Yingjie; Kemsri, Thitikorn; Li, Lin; Lu, Xuejun; Gu, Guiru

2017-01-01

In this paper, we report a concentric circular ring and nanodisk plasmonic optical antenna (POA) enhanced multispectral quantum dot infrared photodetector (QDIP). The circular ring and the nanodisk POA structures are designed to have plasmonic resonant wavelengths in the longwave infrared (LWIR) and the midwave infrared (MWIR) spectral regimes, respectively. The electric field ( E -field) distributions are simulated and show spectral localization due to the distinct plasmonic resonant wavelengths of the POA structures. The circular ring is found to enhance the E -fields in the nanodisk regions due to the mutual coupling. A concentric circular ring and nanodisk POA enhanced multispectral QDIP was fabricated and tested. Multispectral enhancement was observed. The enhancement is compared to that of a QDIP with only the circular ring POA structure. The experiment data agree with the simulation. The concentric circular ring and nanodisk POA provides a compact planar structure for multispectral QDIP enhancement. (paper)

Gigabit Satellite Network for NASA's Advanced Communication Technology Satellite (ACTS)

Science.gov (United States)

Hoder, Douglas; Bergamo, Marcos

1996-01-01

The advanced communication technology satellite (ACTS) gigabit satellite network provides long-haul point-to-point and point-to-multipoint full-duplex SONET services over NASA's ACTS. at rates up to 622 Mbit/s (SONET OC-12), with signal quality comparable to that obtained with terrestrial fiber networks. Data multiplexing over the satellite is accomplished using time-division multiple access (TDMA) techniques coordinated with the switching and beam hopping facilities provided by ACTS. Transmissions through the satellite are protected with Reed-Solomon encoding. providing virtually error-free transmission under most weather conditions. Unique to the system are a TDMA frame structure and satellite synchronization mechanism that allow: (a) very efficient utilization of the satellite capacity: (b) over-the-satellite dosed-loop synchronization of the network in configurations with up to 64 ground stations: and (c) ground station initial acquisition without collisions with existing signalling or data traffic. The user interfaces are compatible with SONET standards, performing the function of conventional SONET multiplexers and. as such. can be: readily integrated with standard SONET fiber-based terrestrial networks. Management of the network is based upon the simple network management protocol (SNMP). and includes an over-the-satellite signalling network and backup terrestrial internet (IP-based) connectivity. A description of the ground stations is also included.

COMPARISON OF RETINAL PATHOLOGY VISUALIZATION IN MULTISPECTRAL SCANNING LASER IMAGING.

Science.gov (United States)

Meshi, Amit; Lin, Tiezhu; Dans, Kunny; Chen, Kevin C; Amador, Manuel; Hasenstab, Kyle; Muftuoglu, Ilkay Kilic; Nudleman, Eric; Chao, Daniel; Bartsch, Dirk-Uwe; Freeman, William R

2018-03-16

To compare retinal pathology visualization in multispectral scanning laser ophthalmoscope imaging between the Spectralis and Optos devices. This retrospective cross-sectional study included 42 eyes from 30 patients with age-related macular degeneration (19 eyes), diabetic retinopathy (10 eyes), and epiretinal membrane (13 eyes). All patients underwent retinal imaging with a color fundus camera (broad-spectrum white light), the Spectralis HRA-2 system (3-color monochromatic lasers), and the Optos P200 system (2-color monochromatic lasers). The Optos image was cropped to a similar size as the Spectralis image. Seven masked graders marked retinal pathologies in each image within a 5 × 5 grid that included the macula. The average area with detected retinal pathology in all eyes was larger in the Spectralis images compared with Optos images (32.4% larger, P < 0.0001), mainly because of better visualization of epiretinal membrane and retinal hemorrhage. The average detection rate of age-related macular degeneration and diabetic retinopathy pathologies was similar across the three modalities, whereas epiretinal membrane detection rate was significantly higher in the Spectralis images. Spectralis tricolor multispectral scanning laser ophthalmoscope imaging had higher rate of pathology detection primarily because of better epiretinal membrane and retinal hemorrhage visualization compared with Optos bicolor multispectral scanning laser ophthalmoscope imaging.

Satellite Imagery Assisted Road-Based Visual Navigation System

Science.gov (United States)

Volkova, A.; Gibbens, P. W.

2016-06-01

There is a growing demand for unmanned aerial systems as autonomous surveillance, exploration and remote sensing solutions. Among the key concerns for robust operation of these systems is the need to reliably navigate the environment without reliance on global navigation satellite system (GNSS). This is of particular concern in Defence circles, but is also a major safety issue for commercial operations. In these circumstances, the aircraft needs to navigate relying only on information from on-board passive sensors such as digital cameras. An autonomous feature-based visual system presented in this work offers a novel integral approach to the modelling and registration of visual features that responds to the specific needs of the navigation system. It detects visual features from Google Earth* build a feature database. The same algorithm then detects features in an on-board cameras video stream. On one level this serves to localise the vehicle relative to the environment using Simultaneous Localisation and Mapping (SLAM). On a second level it correlates them with the database to localise the vehicle with respect to the inertial frame. The performance of the presented visual navigation system was compared using the satellite imagery from different years. Based on comparison results, an analysis of the effects of seasonal, structural and qualitative changes of the imagery source on the performance of the navigation algorithm is presented. * The algorithm is independent of the source of satellite imagery and another provider can be used

Multi-spectral Image Analysis for Astaxanthin Coating Classification

DEFF Research Database (Denmark)

Ljungqvist, Martin Georg; Ersbøll, Bjarne Kjær; Nielsen, Michael Engelbrecht

2011-01-01

Industrial quality inspection using image analysis on astaxanthin coating in aquaculture feed pellets is of great importance for automatic production control. In this study multi-spectral image analysis of pellets was performed using LDA, QDA, SNV and PCA on pixel level and mean value of pixels...

Moving object detection in video satellite image based on deep learning

Science.gov (United States)

Zhang, Xueyang; Xiang, Junhua

2017-11-01

Moving object detection in video satellite image is studied. A detection algorithm based on deep learning is proposed. The small scale characteristics of remote sensing video objects are analyzed. Firstly, background subtraction algorithm of adaptive Gauss mixture model is used to generate region proposals. Then the objects in region proposals are classified via the deep convolutional neural network. Thus moving objects of interest are detected combined with prior information of sub-satellite point. The deep convolution neural network employs a 21-layer residual convolutional neural network, and trains the network parameters by transfer learning. Experimental results about video from Tiantuo-2 satellite demonstrate the effectiveness of the algorithm.

Object-Based Assessment of Satellite Precipitation Products

Directory of Open Access Journals (Sweden)

Jingjing Li

2016-06-01

Full Text Available An object-based verification approach is employed to assess the performance of the commonly used high-resolution satellite precipitation products: Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN, Climate Prediction center MORPHing technique (CMORPH, and Tropical Rainfall Measurement Mission (TRMM Multi-Satellite Precipitation Analysis (TMPA 3B42RT. The evaluation of the satellite precipitation products focuses on the skill of depicting the geometric features of the localized precipitation areas. Seasonal variability of the performances of these products against the ground observations is investigated through the examples of warm and cold seasons. It is found that PERSIANN is capable of depicting the orientation of the localized precipitation areas in both seasons. CMORPH has the ability to capture the sizes of the localized precipitation areas and performs the best in the overall assessment for both seasons. 3B42RT is capable of depicting the location of the precipitation areas for both seasons. In addition, all of the products perform better on capturing the sizes and centroids of precipitation areas in the warm season than in the cold season, while they perform better on depicting the intersection area and orientation in the cold season than in the warm season. These products are more skillful on correctly detecting the localized precipitation areas against the observations in the warm season than in the cold season.

Development of methods for inferring cloud thickness and cloud-base height from satellite radiance data

Science.gov (United States)

Smith, William L., Jr.; Minnis, Patrick; Alvarez, Joseph M.; Uttal, Taneil; Intrieri, Janet M.; Ackerman, Thomas P.; Clothiaux, Eugene

1993-01-01

Cloud-top height is a major factor determining the outgoing longwave flux at the top of the atmosphere. The downwelling radiation from the cloud strongly affects the cooling rate within the atmosphere and the longwave radiation incident at the surface. Thus, determination of cloud-base temperature is important for proper calculation of fluxes below the cloud. Cloud-base altitude is also an important factor in aircraft operations. Cloud-top height or temperature can be derived in a straightforward manner using satellite-based infrared data. Cloud-base temperature, however, is not observable from the satellite, but is related to the height, phase, and optical depth of the cloud in addition to other variables. This study uses surface and satellite data taken during the First ISCCP Regional Experiment (FIRE) Phase-2 Intensive Field Observation (IFO) period (13 Nov. - 7 Dec. 1991, to improve techniques for deriving cloud-base height from conventional satellite data.

Supervised Classification Performance of Multispectral Images

OpenAIRE

Perumal, K.; Bhaskaran, R.

2010-01-01

Nowadays government and private agencies use remote sensing imagery for a wide range of applications from military applications to farm development. The images may be a panchromatic, multispectral, hyperspectral or even ultraspectral of terra bytes. Remote sensing image classification is one amongst the most significant application worlds for remote sensing. A few number of image classification algorithms have proved good precision in classifying remote sensing data. But, of late, due to the ...

DebriSat - A Planned Laboratory-Based Satellite Impact Experiment for Breakup Fragment Characterizations

Science.gov (United States)

Liou, Jer-Chyi; Clark, S.; Fitz-Coy, N.; Huynh, T.; Opiela, J.; Polk, M.; Roebuck, B.; Rushing, R.; Sorge, M.; Werremeyer, M.

2013-01-01

The goal of the DebriSat project is to characterize fragments generated by a hypervelocity collision involving a modern satellite in low Earth orbit (LEO). The DebriSat project will update and expand upon the information obtained in the 1992 Satellite Orbital Debris Characterization Impact Test (SOCIT), which characterized the breakup of a 1960 s US Navy Transit satellite. There are three phases to this project: the design and fabrication of DebriSat - an engineering model representing a modern, 60-cm/50-kg class LEO satellite; conduction of a laboratory-based hypervelocity impact to catastrophically break up the satellite; and characterization of the properties of breakup fragments down to 2 mm in size. The data obtained, including fragment size, area-to-mass ratio, density, shape, material composition, optical properties, and radar cross-section distributions, will be used to supplement the DoD s and NASA s satellite breakup models to better describe the breakup outcome of a modern satellite.

Precise Multi-Spectral Dermatological Imaging

DEFF Research Database (Denmark)

Gomez, David Delgado; Carstensen, Jens Michael; Ersbøll, Bjarne Kjær

2004-01-01

In this work, an integrated imaging system to obtain accurate and reproducible multi-spectral dermatological images is proposed. The system is made up of an integrating sphere, light emitting diodes and a generic monochromatic camera. The system can collect up to 10 different spectral bands....... These spectral bands vary from ultraviolet to near infrared. The welldefined and diffuse illumination of the optically closed scene aims to avoid shadows and specular reflections. Furthermore, the system has been developed to guarantee the reproducibility of the collected images. This allows for comparative...

Multispectral fingerprinting for improved in vivo cell dynamics analysis

Directory of Open Access Journals (Sweden)

Cooper Cameron HJ

2010-09-01

Full Text Available Abstract Background Tracing cell dynamics in the embryo becomes tremendously difficult when cell trajectories cross in space and time and tissue density obscure individual cell borders. Here, we used the chick neural crest (NC as a model to test multicolor cell labeling and multispectral confocal imaging strategies to overcome these roadblocks. Results We found that multicolor nuclear cell labeling and multispectral imaging led to improved resolution of in vivo NC cell identification by providing a unique spectral identity for each cell. NC cell spectral identity allowed for more accurate cell tracking and was consistent during short term time-lapse imaging sessions. Computer model simulations predicted significantly better object counting for increasing cell densities in 3-color compared to 1-color nuclear cell labeling. To better resolve cell contacts, we show that a combination of 2-color membrane and 1-color nuclear cell labeling dramatically improved the semi-automated analysis of NC cell interactions, yet preserved the ability to track cell movements. We also found channel versus lambda scanning of multicolor labeled embryos significantly reduced the time and effort of image acquisition and analysis of large 3D volume data sets. Conclusions Our results reveal that multicolor cell labeling and multispectral imaging provide a cellular fingerprint that may uniquely determine a cell's position within the embryo. Together, these methods offer a spectral toolbox to resolve in vivo cell dynamics in unprecedented detail.

Multispectral Imaging of Meat Quality - Color and Texture

DEFF Research Database (Denmark)

Trinderup, Camilla Himmelstrup

transformations to the CIELAB color space, the common color space within food science. The results show that meat color assessment with a multispectral imaging is a great alternative to the traditional colorimeter, i.e. the vision system meets some of the limitations that the colorimeter possesses. To mention one...

Development of a PC-based ground support system for a small satellite instrument

Science.gov (United States)

Deschambault, Robert L.; Gregory, Philip R.; Spenler, Stephen; Whalen, Brian A.

1993-11-01

The importance of effective ground support for the remote control and data retrieval of a satellite instrument cannot be understated. Problems with ground support may include the need to base personnel at a ground tracking station for extended periods, and the delay between the instrument observation and the processing of the data by the science team. Flexible solutions to such problems in the case of small satellite systems are provided by using low-cost, powerful personal computers and off-the-shelf software for data acquisition and processing, and by using Internet as a communication pathway to enable scientists to view and manipulate satellite data in real time at any ground location. The personal computer based ground support system is illustrated for the case of the cold plasma analyzer flown on the Freja satellite. Commercial software was used as building blocks for writing the ground support equipment software. Several levels of hardware support, including unit tests and development, functional tests, and integration were provided by portable and desktop personal computers. Satellite stations in Saskatchewan and Sweden were linked to the science team via phone lines and Internet, which provided remote control through a central point. These successful strategies will be used on future small satellite space programs.

A proposed architecture for a satellite-based mobile communications network - The lowest three layers

Science.gov (United States)

Yan, T. Y.; Naderi, F. M.

1986-01-01

Architecture for a commercial mobile satellite network is proposed. The mobile satellite system (MSS) is composed of a network management center, mobile terminals, base stations, and gateways; the functions of each component are described. The satellite is a 'bent pipe' that performs frequency translations, and it has multiple UHF beams. The development of the MSS design based on the seven-layer open system interconnection model is examined. Consideration is given to the functions of the physical, data link, and network layers and the integrated adaptive mobile access protocol.

Automatic Hotspot and Sun Glint Detection in UAV Multispectral Images.

Science.gov (United States)

Ortega-Terol, Damian; Hernandez-Lopez, David; Ballesteros, Rocio; Gonzalez-Aguilera, Diego

2017-10-15

Last advances in sensors, photogrammetry and computer vision have led to high-automation levels of 3D reconstruction processes for generating dense models and multispectral orthoimages from Unmanned Aerial Vehicle (UAV) images. However, these cartographic products are sometimes blurred and degraded due to sun reflection effects which reduce the image contrast and colour fidelity in photogrammetry and the quality of radiometric values in remote sensing applications. This paper proposes an automatic approach for detecting sun reflections problems (hotspot and sun glint) in multispectral images acquired with an Unmanned Aerial Vehicle (UAV), based on a photogrammetric strategy included in a flight planning and control software developed by the authors. In particular, two main consequences are derived from the approach developed: (i) different areas of the images can be excluded since they contain sun reflection problems; (ii) the cartographic products obtained (e.g., digital terrain model, orthoimages) and the agronomical parameters computed (e.g., normalized vegetation index-NVDI) are improved since radiometric defects in pixels are not considered. Finally, an accuracy assessment was performed in order to analyse the error in the detection process, getting errors around 10 pixels for a ground sample distance (GSD) of 5 cm which is perfectly valid for agricultural applications. This error confirms that the precision in the detection of sun reflections can be guaranteed using this approach and the current low-cost UAV technology.

Advances In Global Aerosol Modeling Applications Through Assimilation of Satellite-Based Lidar Measurements

Science.gov (United States)

Campbell, James; Hyer, Edward; Zhang, Jianglong; Reid, Jeffrey; Westphal, Douglas; Xian, Peng; Vaughan, Mark

2010-05-01

Modeling the instantaneous three-dimensional aerosol field and its downwind transport represents an endeavor with many practical benefits foreseeable to air quality, aviation, military and science agencies. The recent proliferation of multi-spectral active and passive satellite-based instruments measuring aerosol physical properties has served as an opportunity to develop and refine the techniques necessary to make such numerical modeling applications possible. Spurred by high-resolution global mapping of aerosol source regions, and combined with novel multivariate data assimilation techniques designed to consider these new data streams, operational forecasts of visibility and aerosol optical depths are now available in near real-time1. Active satellite-based aerosol profiling, accomplished using lidar instruments, represents a critical element for accurate analysis and transport modeling. Aerosol source functions, alone, can be limited in representing the macrophysical structure of injection scenarios within a model. Two-dimensional variational (2D-VAR; x, y) assimilation of aerosol optical depth from passive satellite observations significantly improves the analysis of the initial state. However, this procedure can not fully compensate for any potential vertical redistribution of mass required at the innovation step. The expense of an inaccurate vertical analysis of aerosol structure is corresponding errors downwind, since trajectory paths within successive forecast runs will likely diverge with height. In this paper, the application of a newly-designed system for 3D-VAR (x,y,z) assimilation of vertical aerosol extinction profiles derived from elastic-scattering lidar measurements is described [Campbell et al., 2009]. Performance is evaluated for use with the U. S. Navy Aerosol Analysis and Prediction System (NAAPS) by assimilating NASA/CNES satellite-borne Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) 0.532 μm measurements [Winker et al., 2009

Satellite single-axis attitude determination based on Automatic Dependent Surveillance - Broadcast signals

Science.gov (United States)

Zhou, Kaixing; Sun, Xiucong; Huang, Hai; Wang, Xinsheng; Ren, Guangwei

2017-10-01

The space-based Automatic Dependent Surveillance - Broadcast (ADS-B) is a new technology for air traffic management. The satellite equipped with spaceborne ADS-B system receives the broadcast signals from aircraft and transfers the message to ground stations, so as to extend the coverage area of terrestrial-based ADS-B. In this work, a novel satellite single-axis attitude determination solution based on the ADS-B receiving system is proposed. This solution utilizes the signal-to-noise ratio (SNR) measurement of the broadcast signals from aircraft to determine the boresight orientation of the ADS-B receiving antenna fixed on the satellite. The basic principle of this solution is described. The feasibility study of this new attitude determination solution is implemented, including the link budget and the access analysis. On this basis, the nonlinear least squares estimation based on the Levenberg-Marquardt method is applied to estimate the single-axis orientation. A full digital simulation has been carried out to verify the effectiveness and performance of this solution. Finally, the corresponding results are processed and presented minutely.

Initial Radiometric Characteristics of KOMPSAT-3A Multispectral Imagery Using the 6S Radiative Transfer Model, Well-Known Radiometric Tarps, and MFRSR Measurements

Directory of Open Access Journals (Sweden)

Jong-Min Yeom

2017-02-01

Full Text Available On-orbit radiometric characterization of the multispectral (MS imagery of the Korea Aerospace Research Institute (KARI’s Korea Multi-Purpose Satellite-3A (KOMPSAT-3A, which was launched on 25 March 2015, was conducted to provide quantitative radiometric information about KOMPSAT-3A. During the in-orbit test (IOT, vicarious radiometric calibration of KOMPSAT-3A was performed using the Second Simulation of a Satellite Signal in the Solar Spectrum (6S radiative transfer model. The characteristics of radiometric tarps, the atmospheric optical depth from multi-filter rotating shadowband radiometer (MFRSR measurements, and sun–sensor–geometry were carefully considered, in order to calculate the exact top of atmosphere (TOA radiance received by KOMPSAT-3A MS bands. In addition, the bidirectional reflectance distribution function (BRDF behaviors of the radiometric tarps were measured in the laboratory with a two-dimensional hyperspectral gonioradiometer, to compensate for the geometry discrepancy between the satellite and the ASD FieldSpec® 3 spectroradiometer. The match-up datasets between the TOA radiance and the digital number (DN from KOMPSAT-3A were used to determine DN-to-radiance conversion factors, based on linear least squares fitting for two field campaigns. The final results showed that the R2 values between the observed and simulated radiances for the blue, green, red, and near-infrared (NIR bands, are greater than 0.998. An approximate error budget analysis for the vicarious calibration of KOMPSAT-3A showed an error of less than 6.8%. When applying the laboratory-based BRDF correction to the case of higher viewing zenith angle geometry, the gain ratio was improved, particularly for the blue (1.3% and green (1.2% bands, which exhibit high sensitivity to the BRDF of radiometric tarps during the backward-scattering phase. The calculated gain ratio between the first and second campaigns showed a less than 5% discrepancy, indicating that

Satellite-based emission constraint for nitrogen oxides: Capability and uncertainty

Science.gov (United States)

Lin, J.; McElroy, M. B.; Boersma, F.; Nielsen, C.; Zhao, Y.; Lei, Y.; Liu, Y.; Zhang, Q.; Liu, Z.; Liu, H.; Mao, J.; Zhuang, G.; Roozendael, M.; Martin, R.; Wang, P.; Spurr, R. J.; Sneep, M.; Stammes, P.; Clemer, K.; Irie, H.

2013-12-01

Vertical column densities (VCDs) of tropospheric nitrogen dioxide (NO2) retrieved from satellite remote sensing have been employed widely to constrain emissions of nitrogen oxides (NOx). A major strength of satellite-based emission constraint is analysis of emission trends and variability, while a crucial limitation is errors both in satellite NO2 data and in model simulations relating NOx emissions to NO2 columns. Through a series of studies, we have explored these aspects over China. We separate anthropogenic from natural sources of NOx by exploiting their different seasonality. We infer trends of NOx emissions in recent years and effects of a variety of socioeconomic events at different spatiotemporal scales including the general economic growth, global financial crisis, Chinese New Year, and Beijing Olympics. We further investigate the impact of growing NOx emissions on particulate matter (PM) pollution in China. As part of recent developments, we identify and correct errors in both satellite NO2 retrieval and model simulation that ultimately affect NOx emission constraint. We improve the treatments of aerosol optical effects, clouds and surface reflectance in the NO2 retrieval process, using as reference ground-based MAX-DOAS measurements to evaluate the improved retrieval results. We analyze the sensitivity of simulated NO2 to errors in the model representation of major meteorological and chemical processes with a subsequent correction of model bias. Future studies will implement these improvements to re-constrain NOx emissions.

SAMIRA - SAtellite based Monitoring Initiative for Regional Air quality

Science.gov (United States)

Schneider, Philipp; Stebel, Kerstin; Ajtai, Nicolae; Diamandi, Andrei; Horalek, Jan; Nicolae, Doina; Stachlewska, Iwona; Zehner, Claus

2016-04-01

Here, we present a new ESA-funded project entitled Satellite based Monitoring Initiative for Regional Air quality (SAMIRA), which aims at improving regional and local air quality monitoring through synergetic use of data from present and upcoming satellites, traditionally used in situ air quality monitoring networks and output from chemical transport models. Through collaborative efforts in four countries, namely Romania, Poland, the Czech Republic and Norway, all with existing air quality problems, SAMIRA intends to support the involved institutions and associated users in their national monitoring and reporting mandates as well as to generate novel research in this area. Despite considerable improvements in the past decades, Europe is still far from achieving levels of air quality that do not pose unacceptable hazards to humans and the environment. Main concerns in Europe are exceedances of particulate matter (PM), ground-level ozone, benzo(a)pyrene (BaP) and nitrogen dioxide (NO2). While overall sulfur dioxide (SO2) emissions have decreased in recent years, regional concentrations can still be high in some areas. The objectives of SAMIRA are to improve algorithms for the retrieval of hourly aerosol optical depth (AOD) maps from SEVIRI, and to develop robust methods for deriving column- and near-surface PM maps for the study area by combining satellite AOD with information from regional models. The benefit to existing monitoring networks (in situ, models, satellite) by combining these datasets using data fusion methods will be tested for satellite-based NO2, SO2, and PM/AOD. Furthermore, SAMIRA will test and apply techniques for downscaling air quality-related EO products to a spatial resolution that is more in line with what is generally required for studying urban and regional scale air quality. This will be demonstrated for a set of study sites that include the capitals of the four countries and the highly polluted areas along the border of Poland and the

Recovery of Forest Canopy Parameters by Inversion of Multispectral LiDAR Data

Directory of Open Access Journals (Sweden)

Andrew Wallace

2012-02-01

Full Text Available We describe the use of Bayesian inference techniques, notably Markov chain Monte Carlo (MCMC and reversible jump MCMC (RJMCMC methods, to recover forest structural and biochemical parameters from multispectral LiDAR (Light Detection and Ranging data. We use a variable dimension, multi-layered model to represent a forest canopy or tree, and discuss the recovery of structure and depth profiles that relate to photochemical properties. We first demonstrate how simple vegetation indices such as the Normalized Differential Vegetation Index (NDVI, which relates to canopy biomass and light absorption, and Photochemical Reflectance Index (PRI which is a measure of vegetation light use efficiency, can be measured from multispectral data. We further describe and demonstrate our layered approach on single wavelength real data, and on simulated multispectral data derived from real, rather than simulated, data sets. This evaluation shows successful recovery of a subset of parameters, as the complete recovery problem is ill-posed with the available data. We conclude that the approach has promise, and suggest future developments to address the current difficulties in parameter inversion.

Soil moisture extremes drive tree canopy death in 2011 Texas drought: multispectral (Landsat, NAIP) and L-band passive microwave remote sensing (SMOS-IC)

Science.gov (United States)

Swenson, J. J.; Schwantes, A. M.; Johnson, D. M.; Domec, J. C.; Wigneron, J. P.

2017-12-01

Climate change is bringing more frequent and intense droughts that are causing broad scale tree mortality events. Detecting regional drought stress is now more frequently monitored with passive microwave satellite sensing of soil moisture (SM) and vegetation water status (through the vegetation optical depth (VOD) index), that can be validated with in-situ measurements of soil moisture or corroborated with satellite multispectral indices of greenness. The detection of canopy death however marks the passing of a definitive physiological threshold. We compare soil moisture from the L-band SMOS-IC passive microwave product (2010-20176) to an accurate and detailed (30-m spatial resolution) map of canopy loss across the US state of Texas during the record breaking 2011 drought. The SMOS-IC product (25 km) is a new and simpler product of soil moisture and VOD that has been shown to be more accurate than past SMOS products and it is independent of ancillary data. Canopy loss was mapped from Landsat imagery trained with 186, 41 km2 subplots of classified National Agriculture Inventory Program color infrared aerial imagery recorded before and after the drought. Bringing these two datasets of disparate spatial resolution together and averaging them across the state, we find that areas with at least 25% tree cover that experienced the most canopy loss (highest quartile) had lower soil moisture compared to areas with less canopy loss in 2011. These areas with the most loss, experienced up to 9 weeks of the growing season at stress as well as the effects of topography, soil, and climate. Having more information on plant hydraulic limits would lend itself to modeling and prediction of die offs based on satellite tracked SM.

Observing System Simulations for Small Satellite Formations Estimating Bidirectional Reflectance

Science.gov (United States)

Nag, Sreeja; Gatebe, Charles K.; de Weck, Olivier

2015-01-01

The bidirectional reflectance distribution function (BRDF) gives the reflectance of a target as a function of illumination geometry and viewing geometry, hence carries information about the anisotropy of the surface. BRDF is needed in remote sensing for the correction of view and illumination angle effects (for example in image standardization and mosaicing), for deriving albedo, for land cover classification, for cloud detection, for atmospheric correction, and other applications. However, current spaceborne instruments provide sparse angular sampling of BRDF and airborne instruments are limited in the spatial and temporal coverage. To fill the gaps in angular coverage within spatial, spectral and temporal requirements, we propose a new measurement technique: Use of small satellites in formation flight, each satellite with a VNIR (visible and near infrared) imaging spectrometer, to make multi-spectral, near-simultaneous measurements of every ground spot in the swath at multiple angles. This paper describes an observing system simulation experiment (OSSE) to evaluate the proposed concept and select the optimal formation architecture that minimizes BRDF uncertainties. The variables of the OSSE are identified; number of satellites, measurement spread in the view zenith and relative azimuth with respect to solar plane, solar zenith angle, BRDF models and wavelength of reflection. Analyzing the sensitivity of BRDF estimation errors to the variables allow simplification of the OSSE, to enable its use to rapidly evaluate formation architectures. A 6-satellite formation is shown to produce lower BRDF estimation errors, purely in terms of angular sampling as evaluated by the OSSE, than a single spacecraft with 9 forward-aft sensors. We demonstrate the ability to use OSSEs to design small satellite formations as complements to flagship mission data. The formations can fill angular sampling gaps and enable better BRDF products than currently possible.

Observing system simulations for small satellite formations estimating bidirectional reflectance

Science.gov (United States)

Nag, Sreeja; Gatebe, Charles K.; Weck, Olivier de

2015-12-01

The bidirectional reflectance distribution function (BRDF) gives the reflectance of a target as a function of illumination geometry and viewing geometry, hence carries information about the anisotropy of the surface. BRDF is needed in remote sensing for the correction of view and illumination angle effects (for example in image standardization and mosaicing), for deriving albedo, for land cover classification, for cloud detection, for atmospheric correction, and other applications. However, current spaceborne instruments provide sparse angular sampling of BRDF and airborne instruments are limited in the spatial and temporal coverage. To fill the gaps in angular coverage within spatial, spectral and temporal requirements, we propose a new measurement technique: use of small satellites in formation flight, each satellite with a VNIR (visible and near infrared) imaging spectrometer, to make multi-spectral, near-simultaneous measurements of every ground spot in the swath at multiple angles. This paper describes an observing system simulation experiment (OSSE) to evaluate the proposed concept and select the optimal formation architecture that minimizes BRDF uncertainties. The variables of the OSSE are identified; number of satellites, measurement spread in the view zenith and relative azimuth with respect to solar plane, solar zenith angle, BRDF models and wavelength of reflection. Analyzing the sensitivity of BRDF estimation errors to the variables allow simplification of the OSSE, to enable its use to rapidly evaluate formation architectures. A 6-satellite formation is shown to produce lower BRDF estimation errors, purely in terms of angular sampling as evaluated by the OSSE, than a single spacecraft with 9 forward-aft sensors. We demonstrate the ability to use OSSEs to design small satellite formations as complements to flagship mission data. The formations can fill angular sampling gaps and enable better BRDF products than currently possible.

Identification of High-Variation Fields based on Open Satellite Imagery

DEFF Research Database (Denmark)

Jeppesen, Jacob Høxbroe; Jacobsen, Rune Hylsberg; Nyholm Jørgensen, Rasmus

2017-01-01

. The categorization is based on vegetation indices derived from Sentinel-2 satellite imagery. A case study on 7678 winter wheat fields is presented, which employs open data and open source software to analyze the satellite imagery. Furthermore, the method can be automated to deliver categorizations at every update......This paper proposes a simple method for categorizing fields on a regional level, with respect to intra-field variations. It aims to identify fields where the potential benefits of applying precision agricultural practices are highest from an economic and environmental perspective...

Multispectral imaging system based on laser-induced fluorescence for security applications

Science.gov (United States)

Caneve, L.; Colao, F.; Del Franco, M.; Palucci, A.; Pistilli, M.; Spizzichino, V.

2016-10-01

The development of portable sensors for fast screening of crime scenes is required to reduce the number of evidences useful to be collected, optimizing time and resources. Laser based spectroscopic techniques are good candidates to this scope due to their capability to operate in field, in remote and rapid way. In this work, the prototype of a multispectral imaging LIF (Laser Induced Fluorescence) system able to detect evidence of different materials on large very crowded and confusing areas at distances up to some tens of meters will be presented. Data collected as both 2D fluorescence images and LIF spectra are suitable to the identification and the localization of the materials of interest. A reduced scan time, preserving at the same time the accuracy of the results, has been taken into account as a main requirement in the system design. An excimer laser with high energy and repetition rate coupled to a gated high sensitivity ICCD assures very good performances for this purpose. Effort has been devoted to speed up the data processing. The system has been tested in outdoor and indoor real scenarios and some results will be reported. Evidence of the plastics polypropylene (PP) and polyethilene (PE) and polyester have been identified and their localization on the examined scenes has been highlighted through the data processing. By suitable emission bands, the instrument can be used for the rapid detection of other material classes (i.e. textiles, woods, varnishes). The activities of this work have been supported by the EU-FP7 FORLAB project (Forensic Laboratory for in-situ evidence analysis in a post blast scenario).

DebriSat - A Planned Laboratory-Based Satellite Impact Experiment for Breakup Fragment Characterization

Science.gov (United States)

Liou, J.-C.; Fitz-Coy, N.; Werremeyer, M.; Huynh, T.; Voelker, M.; Opiela, J.

2012-01-01

DebriSat is a planned laboratory ]based satellite hypervelocity impact experiment. The goal of the project is to characterize the orbital debris that would be generated by a hypervelocity collision involving a modern satellite in low Earth orbit (LEO). The DebriSat project will update and expand upon the information obtained in the 1992 Satellite Orbital Debris Characterization Impact Test (SOCIT), which characterized the breakup of a 1960 's US Navy Transit satellite. There are three phases to this project: the design and fabrication of an engineering model representing a modern, 50-cm/50-kg class LEO satellite known as DebriSat; conduction of a laboratory-based hypervelocity impact to catastrophically break up the satellite; and characterization of the properties of breakup fragments down to 2 mm in size. The data obtained, including fragment size, area ]to ]mass ratio, density, shape, material composition, optical properties, and radar cross ]section distributions, will be used to supplement the DoD fs and NASA fs satellite breakup models to better describe the breakup outcome of a modern satellite. Updated breakup models will improve mission planning, environmental models, and event response. The DebriSat project is sponsored by the Air Force fs Space and Missile Systems Center and the NASA Orbital Debris Program Office. The design and fabrication of DebriSat is led by University of Florida with subject matter experts f support from The Aerospace Corporation. The major milestones of the project include the complete fabrication of DebriSat by September 2013, the hypervelocity impact of DebriSat at the Air Force fs Arnold Engineering Development Complex in early 2014, and fragment characterization and data analyses in late 2014.