WorldWideScience

Sample records for spatial resolution satellite

  1. High Spatial Resolution Bidirectional Reflectance Retrieval Using Satellite Data

    Science.gov (United States)

    2010-12-01

    done on South African savanna vegetation, researchers found that a leaf, when intact displayed specular reflection, but when crushed more closely... community , low spatial resolution is defined as 30 m or greater, medium ranges from 4-30 m, and high resolution imagery is less than 4 m. Excellent...not require a high temporal resolution, as change occurs over a long period of time, whereas the intelligence community requires high temporal

  2. Spatial scales of pollution from variable resolution satellite imaging

    International Nuclear Information System (INIS)

    Chudnovsky, Alexandra A.; Kostinski, Alex; Lyapustin, Alexei; Koutrakis, Petros

    2013-01-01

    The Moderate Resolution Imaging Spectroradiometer (MODIS) provides daily global coverage, but the 10 km resolution of its aerosol optical depth (AOD) product is not adequate for studying spatial variability of aerosols in urban areas. Recently, a new Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm was developed for MODIS which provides AOD at 1 km resolution. Using MAIAC data, the relationship between MAIAC AOD and PM 2.5 as measured by the EPA ground monitoring stations was investigated at varying spatial scales. Our analysis suggested that the correlation between PM 2.5 and AOD decreased significantly as AOD resolution was degraded. This is so despite the intrinsic mismatch between PM 2.5 ground level measurements and AOD vertically integrated measurements. Furthermore, the fine resolution results indicated spatial variability in particle concentration at a sub-10 km scale. Finally, this spatial variability of AOD within the urban domain was shown to depend on PM 2.5 levels and wind speed. - Highlights: ► The correlation between PM 2.5 and AOD decreases as AOD resolution is degraded. ► High resolution MAIAC AOD 1 km retrieval can be used to investigate within-city PM 2.5 variability. ► Low pollution days exhibit higher spatial variability of AOD and PM 2.5 then moderate pollution days. ► AOD spatial variability within urban area is higher during the lower wind speed conditions. - The correlation between PM 2.5 and AOD decreases as AOD resolution is degraded. The new high-resolution MAIAC AOD retrieval has the potential to capture PM 2.5 variability at the intra-urban scale.

  3. Spatial scales of pollution from variable resolution satellite imaging.

    Science.gov (United States)

    Chudnovsky, Alexandra A; Kostinski, Alex; Lyapustin, Alexei; Koutrakis, Petros

    2013-01-01

    The Moderate Resolution Imaging Spectroradiometer (MODIS) provides daily global coverage, but the 10 km resolution of its aerosol optical depth (AOD) product is not adequate for studying spatial variability of aerosols in urban areas. Recently, a new Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm was developed for MODIS which provides AOD at 1 km resolution. Using MAIAC data, the relationship between MAIAC AOD and PM(2.5) as measured by the EPA ground monitoring stations was investigated at varying spatial scales. Our analysis suggested that the correlation between PM(2.5) and AOD decreased significantly as AOD resolution was degraded. This is so despite the intrinsic mismatch between PM(2.5) ground level measurements and AOD vertically integrated measurements. Furthermore, the fine resolution results indicated spatial variability in particle concentration at a sub-10 km scale. Finally, this spatial variability of AOD within the urban domain was shown to depend on PM(2.5) levels and wind speed. Copyright © 2012 Elsevier Ltd. All rights reserved.

  4. Spatial resolution enhancement of satellite image data using fusion approach

    Science.gov (United States)

    Lestiana, H.; Sukristiyanti

    2018-02-01

    Object identification using remote sensing data has a problem when the spatial resolution is not in accordance with the object. The fusion approach is one of methods to solve the problem, to improve the object recognition and to increase the objects information by combining data from multiple sensors. The application of fusion image can be used to estimate the environmental component that is needed to monitor in multiple views, such as evapotranspiration estimation, 3D ground-based characterisation, smart city application, urban environments, terrestrial mapping, and water vegetation. Based on fusion application method, the visible object in land area has been easily recognized using the method. The variety of object information in land area has increased the variation of environmental component estimation. The difficulties in recognizing the invisible object like Submarine Groundwater Discharge (SGD), especially in tropical area, might be decreased by the fusion method. The less variation of the object in the sea surface temperature is a challenge to be solved.

  5. ADVANCED EXTRACTION OF SPATIAL INFORMATION FROM HIGH RESOLUTION SATELLITE DATA

    Directory of Open Access Journals (Sweden)

    T. Pour

    2016-06-01

    Full Text Available In this paper authors processed five satellite image of five different Middle-European cities taken by five different sensors. The aim of the paper was to find methods and approaches leading to evaluation and spatial data extraction from areas of interest. For this reason, data were firstly pre-processed using image fusion, mosaicking and segmentation processes. Results going into the next step were two polygon layers; first one representing single objects and the second one representing city blocks. In the second step, polygon layers were classified and exported into Esri shapefile format. Classification was partly hierarchical expert based and partly based on the tool SEaTH used for separability distinction and thresholding. Final results along with visual previews were attached to the original thesis. Results are evaluated visually and statistically in the last part of the paper. In the discussion author described difficulties of working with data of large size, taken by different sensors and different also thematically.

  6. Effects of satellite image spatial aggregation and resolution on estimates of forest land area

    Science.gov (United States)

    M.D. Nelson; R.E. McRoberts; G.R. Holden; M.E. Bauer

    2009-01-01

    Satellite imagery is being used increasingly in association with national forest inventories (NFIs) to produce maps and enhance estimates of forest attributes. We simulated several image spatial resolutions within sparsely and heavily forested study areas to assess resolution effects on estimates of forest land area, independent of other sensor characteristics. We...

  7. 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.

  8. Classification of high resolution satellite images using spatial constraints-based fuzzy clustering

    Science.gov (United States)

    Singh, Pankaj Pratap; Garg, Rahul Dev

    2014-01-01

    A spatial constraints-based fuzzy clustering technique is introduced in the paper and the target application is classification of high resolution multispectral satellite images. This fuzzy-C-means (FCM) technique enhances the classification results with the help of a weighted membership function (Wmf). Initially, spatial fuzzy clustering (FC) is used to segment the targeted vegetation areas with the surrounding low vegetation areas, which include the information of spatial constraints (SCs). The performance of the FCM image segmentation is subject to appropriate initialization of Wmf and SC. It is able to evolve directly from the initial segmentation by spatial fuzzy clustering. The controlling parameters in fuzziness of the FCM approach, Wmf and SC, help to estimate the segmented road results, then the Stentiford thinning algorithm is used to estimate the road network from the classified results. Such improvements facilitate FCM method manipulation and lead to segmentation that is more robust. The results confirm its effectiveness for satellite image classification, which extracts useful information in suburban and urban areas. The proposed approach, spatial constraint-based fuzzy clustering with a weighted membership function (SCFCWmf), has been used to extract the information of healthy trees with vegetation and shadows showing elevated features in satellite images. The performance values of quality assessment parameters show a good degree of accuracy for segmented roads using the proposed hybrid SCFCWmf-MO (morphological operations) approach which also occluded nonroad parts.

  9. Medium Spatial Resolution Satellite Imagery to Estimate Gross Primary Production in an Urban Area

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    A. Rahman As-syakur

    2010-06-01

    Full Text Available Remote sensing data with medium spatial resolution can provide useful information about Gross Primary Production (GPP, especially on the scale of urban areas. Most models of ecosystem carbon exchange that are based on remote sensing use some form of the light use efficiency (LUE model. The aim of this work is to analyze the distribution of annual GPP in the urban area of Denpasar, Bali. Additional analysis using two types of satellite data (ALOS/AVNIR-2 and Aster addresses the impact of spatial resolution on the detection of various ecosystem processes in Denpasar. Annual GPP estimated using ALOS/AVNIR-2 varied from 0.13 gC m−2 yr−1 to 2,586.18 gC m−2 yr−1. Meanwhile, the Aster estimate varied from 0.14 gC m−2 yr−1 to 2,595.26 gC m−2 yr−1. GPP as measured by ALOS/AVNIR-2 was lower than that from Aster because ALOS/AVNIR-2 has medium spatial resolution and a smaller spectral range than Aster. Variations in land use may influence the measured value of GPP via differences in vegetation type, distribution, and photosynthetic pathway type. The medium spatial resolution of the remote sensing data is crucial for discriminating different land cover types in heterogeneous urban areas. Given the heterogeneity of land cover over Denpasar, ALOS/AVNIR-2 detects a smaller maximum value of GPP than Aster, but the annual mean GPP from ALOS/AVNIR-2 is higher than that from Aster. Based on comparisons with previous work, we find that ALOS/AVNIR-2 and Aster satellite data provided more accurate estimates of maximum GPP in Denpasar and in the tropical Kalimantan-Indonesia and Amazon forest than estimates derived from the MODIS GPP product (MOD17.

  10. Quantifying tree mortality in a mixed species woodland using multitemporal high spatial resolution satellite imagery

    Science.gov (United States)

    Garrity, Steven R.; Allen, Craig D.; Brumby, Steven P.; Gangodagamage, Chandana; McDowell, Nate G.; Cai, D. Michael

    2013-01-01

    Widespread tree mortality events have recently been observed in several biomes. To effectively quantify the severity and extent of these events, tools that allow for rapid assessment at the landscape scale are required. Past studies using high spatial resolution satellite imagery have primarily focused on detecting green, red, and gray tree canopies during and shortly after tree damage or mortality has occurred. However, detecting trees in various stages of death is not always possible due to limited availability of archived satellite imagery. Here we assess the capability of high spatial resolution satellite imagery for tree mortality detection in a southwestern U.S. mixed species woodland using archived satellite images acquired prior to mortality and well after dead trees had dropped their leaves. We developed a multistep classification approach that uses: supervised masking of non-tree image elements; bi-temporal (pre- and post-mortality) differencing of normalized difference vegetation index (NDVI) and red:green ratio (RGI); and unsupervised multivariate clustering of pixels into live and dead tree classes using a Gaussian mixture model. Classification accuracies were improved in a final step by tuning the rules of pixel classification using the posterior probabilities of class membership obtained from the Gaussian mixture model. Classifications were produced for two images acquired post-mortality with overall accuracies of 97.9% and 98.5%, respectively. Classified images were combined with land cover data to characterize the spatiotemporal characteristics of tree mortality across areas with differences in tree species composition. We found that 38% of tree crown area was lost during the drought period between 2002 and 2006. The majority of tree mortality during this period was concentrated in piñon-juniper (Pinus edulis-Juniperus monosperma) woodlands. An additional 20% of the tree canopy died or was removed between 2006 and 2011, primarily in areas

  11. Evaluation of the Chinese Fine Spatial Resolution Hyperspectral Satellite TianGong-1 in Urban Land-Cover Classification

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    Xueke Li

    2016-05-01

    Full Text Available The successful launch of the Chinese high spatial resolution hyperspectral satellite TianGong-1 (TG-1 opens up new possibilities for applications of remotely-sensed satellite imagery. One of the main goals of the TG-1 mission is to provide observations of surface attributes at local and landscape spatial scales to map urban land cover accurately using the hyperspectral technique. This study attempted to evaluate the TG-1 datasets for urban feature analysis, using existing data over Beijing, China, by comparing the TG-1 (with a spatial resolution of 10 m to EO-1 Hyperion (with a spatial resolution of 30 m. The spectral feature of TG-1 was first analyzed and, thus, finding out optimal hyperspectral wavebands useful for the discrimination of urban areas. Based on this, the pixel-based maximum likelihood classifier (PMLC, pixel-based support vector machine (PSVM, hybrid maximum likelihood classifier (HMLC, and hybrid support vector machine (HSVM were implemented, as well as compared in the application of mapping urban land cover types. The hybrid classifier approach, which integrates the pixel-based classifier and the object-based segmentation approach, was demonstrated as an effective alternative to the conventional pixel-based classifiers for processing the satellite hyperspectral data, especially the fine spatial resolution data. For TG-1 imagery, the pixel-based urban classification was obtained with an average overall accuracy of 89.1%, whereas the hybrid urban classification was obtained with an average overall accuracy of 91.8%. For Hyperion imagery, the pixel-based urban classification was obtained with an average overall accuracy of 85.9%, whereas the hybrid urban classification was obtained with an average overall accuracy of 86.7%. Overall, it can be concluded that the fine spatial resolution satellite hyperspectral data TG-1 is promising in delineating complex urban scenes, especially when using an appropriate classifier, such as the

  12. Estimating global and North American methane emissions with high spatial resolution using GOSAT satellite data

    Science.gov (United States)

    Turner, A. J.; Jacob, D. J.; Wecht, K. J.; Maasakkers, J. D.; Biraud, S. C.; Boesch, H.; Bowman, K. W.; Deutscher, N. M.; Dubey, M. K.; Griffith, D. W. T.; Hase, F.; Kuze, A.; Notholt, J.; Ohyama, H.; Parker, R.; Payne, V. H.; Sussmann, R.; Velazco, V. A.; Warneke, T.; Wennberg, P. O.; Wunch, D.

    2015-02-01

    We use 2009-2011 space-borne methane observations from the Greenhouse Gases Observing SATellite (GOSAT) to constrain global and North American inversions of methane emissions with 4° × 5° and up to 50 km × 50 km spatial resolution, respectively. The GOSAT data are first evaluated with atmospheric methane observations from surface networks (NOAA, TCCON) and aircraft (NOAA/DOE, HIPPO), using the GEOS-Chem chemical transport model as a platform to facilitate comparison of GOSAT with in situ data. This identifies a high-latitude bias between the GOSAT data and GEOS-Chem that we correct via quadratic regression. The surface and aircraft data are subsequently used for independent evaluation of the methane source inversions. Our global adjoint-based inversion yields a total methane source of 539 Tg a-1 and points to a large East Asian overestimate in the EDGARv4.2 inventory used as a prior. Results serve as dynamic boundary conditions for an analytical inversion of North American methane emissions using radial basis functions to achieve high resolution of large sources and provide full error characterization. We infer a US anthropogenic methane source of 40.2-42.7 Tg a-1, as compared to 24.9-27.0 Tg a-1 in the EDGAR and EPA bottom-up inventories, and 30.0-44.5 Tg a-1 in recent inverse studies. Our estimate is supported by independent surface and aircraft data and by previous inverse studies for California. We find that the emissions are highest in the South-Central US, the Central Valley of California, and Florida wetlands, large isolated point sources such as the US Four Corners also contribute. We attribute 29-44% of US anthropogenic methane emissions to livestock, 22-31% to oil/gas, 20% to landfills/waste water, and 11-15% to coal with an additional 9.0-10.1 Tg a-1 source from wetlands.

  13. Effects of daily, high spatial resolution a priori profiles of satellite-derived NOx emissions

    Science.gov (United States)

    Laughner, J.; Zare, A.; Cohen, R. C.

    2016-12-01

    The current generation of space-borne NO2 column observations provides a powerful method of constraining NOx emissions due to the spatial resolution and global coverage afforded by the Ozone Monitoring Instrument (OMI). The greater resolution available in next generation instruments such as TROPOMI and the capabilities of geosynchronous platforms TEMPO, Sentinel-4, and GEMS will provide even greater capabilities in this regard, but we must apply lessons learned from the current generation of retrieval algorithms to make the best use of these instruments. Here, we focus on the effect of the resolution of the a priori NO2 profiles used in the retrieval algorithms. We show that for an OMI retrieval, using daily high-resolution a priori profiles results in changes in the retrieved VCDs up to 40% when compared to a retrieval using monthly average profiles at the same resolution. Further, comparing a retrieval with daily high spatial resolution a priori profiles to a more standard one, we show that emissions derived increase by 100% when using the optimized retrieval.

  14. Estimation of Land Surface Energy Balance Using Satellite Data of Spatial Reduced Resolution

    Science.gov (United States)

    Vintila, Ruxandra; Radnea, Cristina; Savin, Elena; Poenaru, Violeta

    2010-12-01

    The paper presents preliminary results concerning the monitoring at national level of several geo-biophysical variables retrieved by remote sensing, in particular those related to drought or aridisation. The study, which is in progress, represents also an exercise for to the implementation of a Land Monitoring Core Service for Romania, according to the Kopernikus Program and in compliance with the INSPIRE Directive. The SEBS model has been used to retrieve land surface energy balance variables, such as turbulent heat fluxes, evaporative fraction and daily evaporation, based on three information types: (1) surface albedo, emissivity, temperature, fraction of vegetation cover (fCover), leaf area index (LAI) and vegetation height; (2) air pressure, temperature, humidity and wind speed at the planetary boundary layer (PBL) height; (3) downward solar radiation and downward longwave radiation. AATSR and MERIS archived reprocessed images have provided several types of information. Thus, surface albedo, emissivity, and land surface temperature have been retrieved from AATSR, while LAI and fCover have been estimated from MERIS. The vegetation height has been derived from CORINE Land Cover and PELCOM Land Use databases, while the meteorological information at the height of PBL have been estimated from the measurements provided by the national weather station network. Other sources of data used during this study have been the GETASSE30 digital elevation model with 30" spatial resolution, used for satellite image orthorectification, and the SIGSTAR-200 geographical information system of soil resources of Romania, used for water deficit characterisation. The study will continue by processing other AATSR and MERIS archived images, complemented by the validation of SEBS results with ground data collected on the most important biomes for Romania at various phenological stages, and the transformation of evaporation / evapotranspiration into a drought index using the soil texture

  15. 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.

  16. Bayesian Information Criterion Based Feature Filtering for the Fusion of Multiple Features in High-Spatial-Resolution Satellite Scene Classification

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    Da Lin

    2015-01-01

    Full Text Available This paper presents a novel classification method for high-spatial-resolution satellite scene classification introducing Bayesian information criterion (BIC-based feature filtering process to further eliminate opaque and redundant information between multiple features. Firstly, two diverse and complementary feature descriptors are extracted to characterize the satellite scene. Then, sparse canonical correlation analysis (SCCA with penalty function is employed to fuse the extracted feature descriptors and remove the ambiguities and redundancies between them simultaneously. After that, a two-phase Bayesian information criterion (BIC-based feature filtering process is designed to further filter out redundant information. In the first phase, we gradually impose a constraint via an iterative process to set a constraint on the loadings for averting sparse correlation descending below to a lower confidence limit of the approximated canonical correlation. In the second phase, Bayesian information criterion (BIC is utilized to conduct the feature filtering which sets the smallest loading in absolute value to zero in each iteration for all features. Lastly, a support vector machine with pyramid match kernel is applied to obtain the final result. Experimental results on high-spatial-resolution satellite scenes demonstrate that the suggested approach achieves satisfactory performance in classification accuracy.

  17. Processing of high spatial resolution information obtained from satellites of Resource-P series according to the level 1

    Science.gov (United States)

    Eremeev, V.; Kuznetcov, A.; Poshekhonov, V.; Presniakov, O.; Zenin, V.; Svetelkin, P.; Kochergin, A.

    2016-10-01

    The present paper has described main functioning principles of imagery instruments of high spatial resolution of Russian satellites "Resource-P". Processing of images obtained from these instruments according to the level 1 includes: relative radiometric correction, stitching of video data obtained from separate CCD-matrices, geometric matching of multitemporal multispectral images from optoelectronic converters (OEC), pansharpening, saving of results in distribution formats. Stages for acquisition of a high-precision model for the Earth surface imagery being a base of processing are considered. Descriptions of algorithms for realization of mentioned processing types, examples of their practical usage and also precise characteristics of outputs are described.

  18. Estimating babassu palm density using automatic palm tree detection with very high spatial resolution satellite images.

    Science.gov (United States)

    Dos Santos, Alessio Moreira; Mitja, Danielle; Delaître, Eric; Demagistri, Laurent; de Souza Miranda, Izildinha; Libourel, Thérèse; Petit, Michel

    2017-05-15

    High spatial resolution images as well as image processing and object detection algorithms are recent technologies that aid the study of biodiversity and commercial plantations of forest species. This paper seeks to contribute knowledge regarding the use of these technologies by studying randomly dispersed native palm tree. Here, we analyze the automatic detection of large circular crown (LCC) palm tree using a high spatial resolution panchromatic GeoEye image (0.50 m) taken on the area of a community of small agricultural farms in the Brazilian Amazon. We also propose auxiliary methods to estimate the density of the LCC palm tree Attalea speciosa (babassu) based on the detection results. We used the "Compt-palm" algorithm based on the detection of palm tree shadows in open areas via mathematical morphology techniques and the spatial information was validated using field methods (i.e. structural census and georeferencing). The algorithm recognized individuals in life stages 5 and 6, and the extraction percentage, branching factor and quality percentage factors were used to evaluate its performance. A principal components analysis showed that the structure of the studied species differs from other species. Approximately 96% of the babassu individuals in stage 6 were detected. These individuals had significantly smaller stipes than the undetected ones. In turn, 60% of the stage 5 babassu individuals were detected, showing significantly a different total height and a different number of leaves from the undetected ones. Our calculations regarding resource availability indicate that 6870 ha contained 25,015 adult babassu palm tree, with an annual potential productivity of 27.4 t of almond oil. The detection of LCC palm tree and the implementation of auxiliary field methods to estimate babassu density is an important first step to monitor this industry resource that is extremely important to the Brazilian economy and thousands of families over a large scale. Copyright

  19. Opportunities and challenges of applications of satellite-derived sun-induced fluorescence at relatively high spatial resolution.

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    Lu, Xinchen; Cheng, Xiao; Li, Xianglan; Tang, Jianwu

    2018-04-01

    Estimating gross primary production (GPP) regionally and globally remains challenging despite its primary role in driving ecosystem productivity and carbon cycling. Recently, satellite-derived sun-induced fluorescence (SIF) provides an alternative approach to investigate GPP from space. However, our ability to apply SIF to estimating GPP at large scales is still lacking, primarily because the SIF-GPP relationships at various spatial and temporal scales are not fully understood. The coarse spatial representativeness (around 0.5° or coarser) of previous satellite-derived SIF data makes it difficult to compare and validate with eddy covariance (EC) based GPP measurements. Orbiting Carbon Observatory-2 (OCO-2) has shown prospects in providing SIF at significantly improved spatial resolutions (around 1.3km by 2.25km) that are comparable to ground-based GPP measurements. However, OCO-2 operates at a 16-day revisiting schedule with a sparse spatial sampling strategy. We found that for most EC sites, the observations of OCO-2 passing through were extremely limited. The average number of successfully retrieved SIF by OCO-2 encompassing each site within a year was only 3.21 from 2015 to 2016. For an EC site with high companion OCO-2 coverages, we found a strong correlation between GPP and SIF. Despite challenges, the emerging high-spatial-resolution SIF data provide unprecedented opportunities to estimate GPP over time and space and its underlying mechanism. We recommend that to fully use the satellite-derived SIF data, a research agenda is critically needed to improve our understanding of the relationship between SIF and GPP across biomes, ecosystems, and even species. We advocate maintaining and upgrading current EC sites and adding ground-based SIF measurements to provide another scale of SIF observations. We also suggest constructions of new EC sites taking into consideration the scientific benefits that can be gained by locating sites within the belts within OCO-2 or

  20. Impact of spatial resolution on cirrus infrared satellite retrievals in the presence of cloud heterogeneity

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    Fauchez, T.; Platnick, S. E.; Meyer, K.; Zhang, Z.; Cornet, C.; Szczap, F.; Dubuisson, P.

    2015-12-01

    Cirrus clouds are an important part of the Earth radiation budget but an accurate assessment of their role remains highly uncertain. Cirrus optical properties such as Cloud Optical Thickness (COT) and ice crystal effective particle size are often retrieved with a combination of Visible/Near InfraRed (VNIR) and ShortWave-InfraRed (SWIR) reflectance channels. Alternatively, Thermal InfraRed (TIR) techniques, such as the Split Window Technique (SWT), have demonstrated better accuracy for thin cirrus effective radius retrievals with small effective radii. However, current global operational algorithms for both retrieval methods assume that cloudy pixels are horizontally homogeneous (Plane Parallel Approximation (PPA)) and independent (Independent Pixel Approximation (IPA)). The impact of these approximations on ice cloud retrievals needs to be understood and, as far as possible, corrected. Horizontal heterogeneity effects in the TIR spectrum are mainly dominated by the PPA bias that primarily depends on the COT subpixel heterogeneity; for solar reflectance channels, in addition to the PPA bias, the IPA can lead to significant retrieval errors due to a significant photon horizontal transport between cloudy columns, as well as brightening and shadowing effects that are more difficult to quantify. Furthermore TIR retrievals techniques have demonstrated better retrieval accuracy for thin cirrus having small effective radii over solar reflectance techniques. The TIR range is thus particularly relevant in order to characterize, as accurately as possible, thin cirrus clouds. Heterogeneity effects in the TIR are evaluated as a function of spatial resolution in order to estimate the optimal spatial resolution for TIR retrieval applications. These investigations are performed using a cirrus 3D cloud generator (3DCloud), a 3D radiative transfer code (3DMCPOL), and two retrieval algorithms, namely the operational MODIS retrieval algorithm (MOD06) and a research-level SWT algorithm.

  1. An Object-Based Image Analysis Approach for Detecting Penguin Guano in very High Spatial Resolution Satellite Images

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    Chandi Witharana

    2016-04-01

    Full Text Available The logistical challenges of Antarctic field work and the increasing availability of very high resolution commercial imagery have driven an interest in more efficient search and classification of remotely sensed imagery. This exploratory study employed geographic object-based analysis (GEOBIA methods to classify guano stains, indicative of chinstrap and Adélie penguin breeding areas, from very high spatial resolution (VHSR satellite imagery and closely examined the transferability of knowledge-based GEOBIA rules across different study sites focusing on the same semantic class. We systematically gauged the segmentation quality, classification accuracy, and the reproducibility of fuzzy rules. A master ruleset was developed based on one study site and it was re-tasked “without adaptation” and “with adaptation” on candidate image scenes comprising guano stains. Our results suggest that object-based methods incorporating the spectral, textural, spatial, and contextual characteristics of guano are capable of successfully detecting guano stains. Reapplication of the master ruleset on candidate scenes without modifications produced inferior classification results, while adapted rules produced comparable or superior results compared to the reference image. This work provides a road map to an operational “image-to-assessment pipeline” that will enable Antarctic wildlife researchers to seamlessly integrate VHSR imagery into on-demand penguin population census.

  2. Estimating Soil Moisture at High Spatial Resolution with Three Radiometric Satellite Products: A Study from a South-Eastern Australian Catchment

    Science.gov (United States)

    Senanayake, I. P.; Yeo, I. Y.; Tangdamrongsub, N.; Willgoose, G. R.; Hancock, G. R.; Wells, T.; Fang, B.; Lakshmi, V.

    2017-12-01

    Long-term soil moisture datasets at high spatial resolution are important in agricultural, hydrological, and climatic applications. The soil moisture estimates can be achieved using satellite remote sensing observations. However, the satellite soil moisture data are typically available at coarse spatial resolutions ( several tens of km), therefore require further downscaling. Different satellite soil moisture products have to be conjointly employed in developing a consistent time-series of high resolution soil moisture, while the discrepancies amongst different satellite retrievals need to be resolved. This study aims to downscale three different satellite soil moisture products, the Soil Moisture and Ocean Salinity (SMOS, 25 km), the Soil Moisture Active Passive (SMAP, 36 km) and the SMAP-Enhanced (9 km), and to conduct an inter-comparison of the downscaled results. The downscaling approach is developed based on the relationship between the diurnal temperature difference and the daily mean soil moisture content. The approach is applied to two sub-catchments (Krui and Merriwa River) of the Goulburn River catchment in the Upper Hunter region (NSW, Australia) to estimate soil moisture at 1 km resolution for 2015. The three coarse spatial resolution soil moisture products and their downscaled results will be validated with the in-situ observations obtained from the Scaling and Assimilation of Soil Moisture and Streamflow (SASMAS) network. The spatial and temporal patterns of the downscaled results will also be analysed. This study will provide the necessary insights for data selection and bias corrections to maintain the consistency of a long-term high resolution soil moisture dataset. The results will assist in developing a time-series of high resolution soil moisture data over the south-eastern Australia.

  3. Assimilation of satellite NO2 observations at high spatial resolution using OSSEs

    Science.gov (United States)

    Liu, Xueling; Mizzi, Arthur P.; Anderson, Jeffrey L.; Fung, Inez Y.; Cohen, Ronald C.

    2017-06-01

    Observations of trace gases from space-based instruments offer the opportunity to constrain chemical and weather forecast and reanalysis models using the tools of data assimilation. In this study, observing system simulation experiments (OSSEs) are performed to investigate the potential of high space- and time-resolution column measurements as constraints on urban NOx emissions. The regional chemistry-meteorology assimilation system where meteorology and chemical variables are simultaneously assimilated is comprised of a chemical transport model, WRF-Chem, the Data Assimilation Research Testbed, and a geostationary observation simulator. We design OSSEs to investigate the sensitivity of emission inversions to the accuracy and uncertainty of the wind analyses and the emission updating scheme. We describe the overall model framework and some initial experiments that point out the first steps toward an optimal configuration for improving our understanding of NOx emissions by combining space-based measurements and data assimilation. Among the findings we describe is the dependence of errors in the estimated NOx emissions on the wind forecast errors, showing that wind vectors with a RMSE below 1 m s-1 allow inference of NOx emissions with a RMSE of less than 30 mol/(km2 × h) at the 3 km scale of the model we use. We demonstrate that our inference of emissions is more accurate when we simultaneously update both NOx emissions and NOx concentrations instead of solely updating emissions. Furthermore, based on our analyses, we recommend carrying out meteorology assimilations to stabilize NO2 transport from the initial wind errors before starting the emission assimilation. We show that wind uncertainties (calculated as a spread around a mean wind) are not important for estimating NOx emissions when the wind uncertainties are reduced below 1.5 m s-1. Finally, we present results assessing the role of separate vs. simultaneous chemical and meteorological assimilation in a model

  4. High spatial resolution satellite observations for validation of MODIS land products: IKONOS observations acquired under the NASA scientific data purchase.

    Science.gov (United States)

    Jeffrey T. Morisette; Jaime E. Nickeson; Paul Davis; Yujie Wang; Yuhong Tian; Curtis E. Woodcock; Nikolay Shabanov; Matthew Hansen; Warren B. Cohen; Doug R. Oetter; Robert E. Kennedy

    2003-01-01

    Phase 1I of the Scientific Data Purchase (SDP) has provided NASA investigators access to data from four different satellite and airborne data sources. The Moderate Resolution Imaging Spectrometer (MODIS) land discipline team (MODLAND) sought to utilize these data in support of land product validation activities with a lbcus on tile EOS Land Validation Core Sites. These...

  5. Estimation and quantification of mangrove forest extent by using different spatial resolution satellite data for the sandspit area of Karachi coast

    International Nuclear Information System (INIS)

    Saeed, U.; Daud, A.; Ashraf, S.; Mahmood, A.

    2006-01-01

    Mangrove forest is an integral part of inter-tidal zone of the coastal environment extending throughout the tropics and subtropics of the world. In Pakistan, for the last thirty years, remote-sensing data has significantly been used for area estimation of mangrove forests. In the previous studies medium resolution satellite data have been used for the area estimation of mangrove forests that revealed some of the discrepancies in terms of recognition of the subtle variations of landcover features in the satellite imagery. Current study aims at the classification techniques employed for the area estimation using high and medium resolution satellite imageries. To study the effects of spatial resolution on classification results, three different satellite data were used, including Quickbird, TERRA and Landsat satellites. Thematic map derived from Quickbird data was comprised of maximum number of land cover classes with a definite zone of mangroves that extends from regeneration to mature canopies. Total estimated mangroves extent was 370 ha with 57.45, 125.9, 180.89, and 5.35 ha of tall, medium, small, and new recruitment mangrove plants respectively. While mangrove area estimations from thematic maps derived using TERRA and Landsat satellite data, showed a gradual increase in the mangrove extent from 390.95 ha to 417.92 ha. This increase in area is an indicative of the fact that some of the landcover classes may have been miss-classified and hence added to the area under mangrove forests. This study also showed that high-resolution satellite data could be used for identifying different height zones of mangrove forests, along with an accurate delineation of classes like salt bushes and algae, which could not be classified otherwise. (author)

  6. Geo-Parcel Based Crop Identification by Integrating High Spatial-Temporal Resolution Imagery from Multi-Source Satellite Data

    Directory of Open Access Journals (Sweden)

    Yingpin Yang

    2017-12-01

    Full Text Available Geo-parcel based crop identification plays an important role in precision agriculture. It meets the needs of refined farmland management. This study presents an improved identification procedure for geo-parcel based crop identification by combining fine-resolution images and multi-source medium-resolution images. GF-2 images with fine spatial resolution of 0.8 m provided agricultural farming plot boundaries, and GF-1 (16 m and Landsat 8 OLI data were used to transform the geo-parcel based enhanced vegetation index (EVI time-series. In this study, we propose a piecewise EVI time-series smoothing method to fit irregular time profiles, especially for crop rotation situations. Global EVI time-series were divided into several temporal segments, from which phenological metrics could be derived. This method was applied to Lixian, where crop rotation was the common practice of growing different types of crops, in the same plot, in sequenced seasons. After collection of phenological features and multi-temporal spectral information, Random Forest (RF was performed to classify crop types, and the overall accuracy was 93.27%. Moreover, an analysis of feature significance showed that phenological features were of greater importance for distinguishing agricultural land cover compared to temporal spectral information. The identification results indicated that the integration of high spatial-temporal resolution imagery is promising for geo-parcel based crop identification and that the newly proposed smoothing method is effective.

  7. Spatial downscaling algorithm of TRMM precipitation based on multiple high-resolution satellite data for Inner Mongolia, China

    Science.gov (United States)

    Duan, Limin; Fan, Keke; Li, Wei; Liu, Tingxi

    2017-12-01

    Daily precipitation data from 42 stations in Inner Mongolia, China for the 10 years period from 1 January 2001 to 31 December 2010 was utilized along with downscaled data from the Tropical Rainfall Measuring Mission (TRMM) with a spatial resolution of 0.25° × 0.25° for the same period based on the statistical relationships between the normalized difference vegetation index (NDVI), meteorological variables, and digital elevation models (https://en.wikipedia.org/wiki/Digital_elevation_model) (DEM) using the leave-one-out (LOO) cross validation method and multivariate step regression. The results indicate that (1) TRMM data can indeed be used to estimate annual precipitation in Inner Mongolia and there is a linear relationship between annual TRMM and observed precipitation; (2) there is a significant relationship between TRMM-based precipitation and predicted precipitation, with a spatial resolution of 0.50° × 0.50°; (3) NDVI and temperature are important factors influencing the downscaling of TRMM precipitation data for DEM and the slope is not the most significant factor affecting the downscaled TRMM data; and (4) the downscaled TRMM data reflects spatial patterns in annual precipitation reasonably well, showing less precipitation falling in west Inner Mongolia and more in the south and southeast. The new approach proposed here provides a useful alternative for evaluating spatial patterns in precipitation and can thus be applied to generate a more accurate precipitation dataset to support both irrigation management and the conservation of this fragile grassland ecosystem.

  8. Monitoring forest areas from continental to territorial levels using a sample of medium spatial resolution satellite imagery

    Science.gov (United States)

    Eva, Hugh; Carboni, Silvia; Achard, Frédéric; Stach, Nicolas; Durieux, Laurent; Faure, Jean-François; Mollicone, Danilo

    A global systematic sampling scheme has been developed by the UN FAO and the EC TREES project to estimate rates of deforestation at global or continental levels at intervals of 5 to 10 years. This global scheme can be intensified to produce results at the national level. In this paper, using surrogate observations, we compare the deforestation estimates derived from these two levels of sampling intensities (one, the global, for the Brazilian Amazon the other, national, for French Guiana) to estimates derived from the official inventories. We also report the precisions that are achieved due to sampling errors and, in the case of French Guiana, compare such precision with the official inventory precision. We extract nine sample data sets from the official wall-to-wall deforestation map derived from satellite interpretations produced for the Brazilian Amazon for the year 2002 to 2003. This global sampling scheme estimate gives 2.81 million ha of deforestation (mean from nine simulated replicates) with a standard error of 0.10 million ha. This compares with the full population estimate from the wall-to-wall interpretations of 2.73 million ha deforested, which is within one standard error of our sampling test estimate. The relative difference between the mean estimate from sampling approach and the full population estimate is 3.1%, and the standard error represents 4.0% of the full population estimate. This global sampling is then intensified to a territorial level with a case study over French Guiana to estimate deforestation between the years 1990 and 2006. For the historical reference period, 1990, Landsat-5 Thematic Mapper data were used. A coverage of SPOT-HRV imagery at 20 m × 20 m resolution acquired at the Cayenne receiving station in French Guiana was used for year 2006. Our estimates from the intensified global sampling scheme over French Guiana are compared with those produced by the national authority to report on deforestation rates under the Kyoto

  9. Analyzing the Variation of Building Density Using High Spatial Resolution Satellite Images: the Example of Shanghai City

    Directory of Open Access Journals (Sweden)

    Bo Sun

    2008-04-01

    Full Text Available Building density is an important issue in urban planning and land management. In the article, building coverage ratio (BCR and floor area ratio (FAR values extracted from high resolution satellite images were used to indicate buildings’ stretching on the surface and growth along the third dimension within areas of interest in Shanghai City, P.R. China. The results show that the variation of FAR is higher than that of BCR in the inner circle, and that the newer commercial centers have higher FAR and lower BCR values, while the traditional commercial areas have higher FAR and BCR ratios. By comparing different residential areas, it was found that the historical “Shikumen” areas and the old residential areas built before 1980s have higher BCR and lower FAR, while the new residential areas have higher FAR and lower BCR, except for the villa areas. These results suggest that both older building areas and villa areas use land resources in an inefficient way, and therefore better planning and management of urban land are needed for those fast economic growing regions.

  10. Towards high temporal and moderate spatial resolutions in the remote sensing retrieval of evapotranspiration by combining geostationary and polar orbit satellite data

    Science.gov (United States)

    Barrios, José Miguel; Ghilain, Nicolas; Arboleda, Alirio; Gellens-Meulenberghs, Françoise

    2014-05-01

    Evapotranspiration (ET) is the water flux going from the surface into the atmosphere as result of soil and surface water evaporation and plant transpiration. It constitutes a key component of the water cycle and its quantification is of crucial importance for a number of applications like water management, climatic modelling, agriculture monitoring and planning, etc. Estimating ET is not an easy task; specially if large areas are envisaged and various spatio-temporal patterns of ET are present as result of heterogeneity in land cover, land use and climatic conditions. In this respect, spaceborne remote sensing (RS) provides the only alternative to continuously measure surface parameters related to ET over large areas. The Royal Meteorological Institute (RMI) of Belgium, in the framework of EUMETSAT's "Land Surface Analysis-Satellite Application Facility" (LSA-SAF), has developed a model for the estimation of ET. The model is forced by RS data, numerical weather predictions and land cover information. The RS forcing is derived from measurements by the Spinning Enhanced Visible and Infrared Imager (SEVIRI) onboard the Meteosat Second Generation (MSG) satellite. This ET model is operational and delivers ET estimations over the whole field of view of the MSG satellite (Europe, Africa and Eastern South America) (http://landsaf.meteo.pt) every 30 minutes. The spatial resolution of MSG is 3 x 3 km at subsatellite point and about 4 x 5 km in continental Europe. The spatial resolution of this product may constrain its full exploitation as the interest of potential users (farmers and natural resources scientists) may lie on smaller spatial units. This study aimed at testing methodological alternatives to combine RS imagery (geostationary and polar orbit satellites) for the estimation of ET such that the spatial resolution of the final product is improved. In particular, the study consisted in the implementation of two approaches for combining the current ET estimations with

  11. Granulometric maps from high resolution satellite images:

    OpenAIRE

    Chopin, Franck; Mering, Catherine

    2002-01-01

    A new method of land cover mapping from satellite images using granulometric analysis is presented here. Discontinuous landscapes such as steppian bushes of semi arid regions and recently growing urban settlements are especially concerned by this study. Spatial organisations of the land cover are quantified by means of the size distribution analysis of the land cover units extracted from high resolution remotely sensed images. A granulometric map is built by automatic classification of every ...

  12. Assessing Wildfire Risk in Cultural Heritage Properties Using High Spatial and Temporal Resolution Satellite Imagery and Spatially Explicit Fire Simulations: The Case of Holy Mount Athos, Greece

    Directory of Open Access Journals (Sweden)

    Giorgos Mallinis

    2016-02-01

    Full Text Available Fire management implications and the design of conservation strategies on fire prone landscapes within the UNESCO World Heritage Properties require the application of wildfire risk assessment at landscape level. The objective of this study was to analyze the spatial variation of wildfire risk on Holy Mount Athos in Greece. Mt. Athos includes 20 monasteries and other structures that are threatened by increasing frequency of wildfires. Site-specific fuel models were created by measuring in the field several fuel parameters in representative natural fuel complexes, while the spatial extent of the fuel types was determined using a synergy of high-resolution imagery and high temporal information from medium spatial resolution imagery classified through object-based analysis and a machine learning classifier. The Minimum Travel Time (MTT algorithm, as it is embedded in FlamMap software, was applied in order to evaluate Burn Probability (BP, Conditional Flame Length (CFL, Fire Size (FS, and Source-Sink Ratio (SSR. The results revealed low burn probabilities for the monasteries; however, nine out of the 20 monasteries have high fire potential in terms of fire intensity, which means that if an ignition occurs, an intense fire is expected. The outputs of this study may be used for decision-making for short-term predictions of wildfire risk at an operational level, contributing to fire suppression and management of UNESCO World Heritage Properties.

  13. Monitoring mangrove forests after aquaculture abandonment using time series of very high spatial resolution satellite images: A case study from the Perancak estuary, Bali, Indonesia.

    Science.gov (United States)

    Proisy, Christophe; Viennois, Gaëlle; Sidik, Frida; Andayani, Ariani; Enright, James Anthony; Guitet, Stéphane; Gusmawati, Niken; Lemonnier, Hugues; Muthusankar, Gowrappan; Olagoke, Adewole; Prosperi, Juliana; Rahmania, Rinny; Ricout, Anaïs; Soulard, Benoit; Suhardjono

    2017-06-23

    Revegetation of abandoned aquaculture regions should be a priority for any integrated coastal zone management (ICZM). This paper examines the potential of a matchless time series of 20 very high spatial resolution (VHSR) optical satellite images acquired for mapping trends in the evolution of mangrove forests from 2001 to 2015 in an estuary fragmented into aquaculture ponds. Evolution of mangrove extent was quantified through robust multitemporal analysis based on supervised image classification. Results indicated that mangroves are expanding inside and outside ponds and over pond dykes. However, the yearly expansion rate of vegetation cover greatly varied between replanted ponds. Ground truthing showed that only Rhizophora species had been planted, whereas natural mangroves consist of Avicennia and Sonneratia species. In addition, the dense Rhizophora plantations present very low regeneration capabilities compared with natural mangroves. Time series of VHSR images provide comprehensive and intuitive level of information for the support of ICZM. Copyright © 2017 Elsevier Ltd. All rights reserved.

  14. Object-Based Mapping of Aboveground Biomass in Tropical Forests Using LiDAR and Very-High-Spatial-Resolution Satellite Data

    Directory of Open Access Journals (Sweden)

    Yasumasa Hirata

    2018-03-01

    Full Text Available Developing countries that intend to implement the United Nations REDD-plus (Reducing Emissions from Deforestation and forest Degradation, and the role of forest conservation, sustainable management of forests, and enhancement of forest carbon stocks framework and obtain economic incentives are required to estimate changes in forest carbon stocks based on the IPCC guidelines. In this study, we developed a method to support REDD-plus implementation by estimating tropical forest aboveground biomass (AGB by combining airborne LiDAR with very-high-spatial-resolution satellite data. We acquired QuickBird satellite images of Kampong Thom, Cambodia in 2011 and airborne LiDAR measurements in some parts of the same area. After haze reduction and atmospheric correction of the satellite data, we calibrated reflectance values from the mean reflectance of the objects (obtained by segmentation from areas of overlap between dates to reduce the effects of the observation angle and solar elevation. Then, we performed object-based classification using the satellite data (overall accuracy = 77.0%, versus 92.9% for distinguishing forest from non-forest land. We used a two-step method to estimate AGB and map it in a tropical environment in Cambodia. First, we created a multiple-regression model to estimate AGB from the LiDAR data and plotted field-surveyed AGB values against AGB values predicted by the LiDAR-based model (R2 = 0.90, RMSE = 38.7 Mg/ha, and calculated reflectance values in each band of the satellite data for the analyzed objects. Then, we created a multiple-regression model using AGB predicted by the LiDAR-based model as the dependent variable and the mean and standard deviation of the reflectance values in each band of the satellite data as the explanatory variables (R2 = 0.73, RMSE = 42.8 Mg/ha. We calculated AGB of all objects, divided the results into density classes, and mapped the resulting AGB distribution. Our results suggest that this approach

  15. Mapping the vegetation colonization on recent lava flows using spectral unmixing of moderate spatial resolution satellite images: Nyamuragira volcano, D. R. Congo

    Science.gov (United States)

    Li, Long; Kervyn, Matthieu; Canters, Frank

    2014-05-01

    In volcanic areas, vegetation colonizes recently erupted lava flows and expands over time. The fraction of vegetation is therefore likely to provide information on lava flows' age. Individual lava flows are usually not well resolved on satellite imagery due to the coarse spatial resolution: one pixel on the imagery is a mixture of mainly lava and vegetation. In order to solve the mixed pixel problem, many different methods have been proposed among which linear spectral unmixing is the most widely-used. It assumes that the reflectance of the mixed pixel is the sum of the reflectance of each pure end members multiplied by their proportion in the pixel. It has been frequently used in urban area studies, but no efforts have yet been made to apply it to volcanic areas. Here, we demonstrate the application of linear spectral unmixing for the lava flows of Nyamuragira volcano, in the Virunga Volcanic province. Nyamuragira is an active volcano, emitting over 30 lava flows in the last 100 years. The limited access to the volcano due to social unrest in D. R. Congo justifies the value of remote sensing techniques. This shield volcano is exposed to tropical climate and thus vegetation colonizes lava flows rapidly. An EO-1 ALI image (Advanced land imager mounted on Earth Observing -1 Satellite) acquired over Nyamuragira on January 3, 2012 at spatial resolution of 30 m was processed with minimum noise fraction transform and end member extraction, and spectrally unmixed by linear mixture modelling technique into two types of lava, and one or two types of vegetation. The three end member model is better in terms of the RMSE and the expected spatial distribution of end members. A 2 m resolution Pleiades image acquired on January 21, 2013 and partly overlapping with the ALI image was taken as the reference image for validation. It was first classified using a supervised pixel-based classification technique and then compared to the proportion image derived from the ALI image

  16. Remote sensing of atmospheric PM2.5 from high spatial resolution image of Chinese environmental satellite HJ-1/ CCD data

    International Nuclear Information System (INIS)

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

    2014-01-01

    Due to lack of the middle infrared wavelength, it is difficult to employ the classic dark target method to retrieve aerosol optical depth (AOD) from Chinese Environmental satellite HJ1-CCD data. Therefore, focusing on extracting weak information from mixed satellite signals of atmosphere and land surface, we developed the Multi-wavelength, Multi-sensor, Multi-day (3M) approach in order to utilize maximally the observation information, and with the consideration of a prior knowledge, e.g. the surface property changes quickly with location but slowly with time. We present the AOD retrieval algorithm based on HJ1-CCD blue and green bands, based on the look-up table approach constructed using 6S radiative transfer model to provide the simultaneous determination of AOD and the ground reflectance. The aerosol and particle size information obtained from ground-based sun-sky radiometer are then used to estimate PM 2.5 on the surface level, while air humidity and height of planetary boundary layer from reanalysis data are employed to improve the correlation between AOD and PM 2.5 . Validation of the retrieval results with different spatial resolutions (300, 500 and 1000 m), are also performed by comparison with ground-based measurements at three sites of North China regions

  17. How Attention Affects Spatial Resolution

    OpenAIRE

    Carrasco, Marisa; Barbot, Antoine

    2014-01-01

    We summarize and discuss a series of psychophysical studies on the effects of spatial covert attention on spatial resolution, our ability to discriminate fine patterns. Heightened resolution is beneficial in most, but not all, visual tasks. We show how endogenous attention (voluntary, goal driven) and exogenous attention (involuntary, stimulus driven) affect performance on a variety of tasks mediated by spatial resolution, such as visual search, crowding, acuity, and texture segmentation. Exo...

  18. Evaluation of TRMM Multi-satellite Precipitation Analysis (TMPA performance in the Central Andes region and its dependency on spatial and temporal resolution

    Directory of Open Access Journals (Sweden)

    M. L. M. Scheel

    2011-08-01

    Full Text Available Climate time series are of major importance for base line studies for climate change impact and adaptation projects. However, for instance, in mountain regions and in developing countries there exist significant gaps in ground based climate records in space and time. Specifically, in the Peruvian Andes spatially and temporally coherent precipitation information is a prerequisite for ongoing climate change adaptation projects in the fields of water resources, disasters and food security. The present work aims at evaluating the ability of Tropical Rainfall Measurement Mission (TRMM Multi-satellite Precipitation Analysis (TMPA to estimate precipitation rates at daily 0.25° × 0.25° scale in the Central Andes and the dependency of the estimate performance on changing spatial and temporal resolution. Comparison of the TMPA product with gauge measurements in the regions of Cuzco, Peru and La Paz, Bolivia were carried out and analysed statistically. Large biases are identified in both investigation areas in the estimation of daily precipitation amounts. The occurrence of strong precipitation events was well assessed, but their intensities were underestimated. TMPA estimates for La Paz show high false alarm ratio.

    The dependency of the TMPA estimate quality with changing resolution was analysed by comparisons of 1-, 7-, 15- and 30-day sums for Cuzco, Peru. The correlation of TMPA estimates with ground data increases strongly and almost linearly with temporal aggregation. The spatial aggregation to 0.5°, 0.75° and 1° grid box averaged precipitation and its comparison to gauge data of the same areas revealed no significant change in correlation coefficients and estimate performance.

    In order to profit from the TMPA combination product on a daily basis, a procedure to blend it with daily precipitation gauge measurements is proposed.

    Different sources of errors and uncertainties introduced by the sensors, sensor

  19. GRANULOMETRIC MAPS FROM HIGH RESOLUTION SATELLITE IMAGES

    Directory of Open Access Journals (Sweden)

    Catherine Mering

    2011-05-01

    Full Text Available A new method of land cover mapping from satellite images using granulometric analysis is presented here. Discontinuous landscapes such as steppian bushes of semi arid regions and recently growing urban settlements are especially concerned by this study. Spatial organisations of the land cover are quantified by means of the size distribution analysis of the land cover units extracted from high resolution remotely sensed images. A granulometric map is built by automatic classification of every pixel of the image according to the granulometric density inside a sliding neighbourhood. Granulometric mapping brings some advantages over traditional thematic mapping by remote sensing by focusing on fine spatial events and small changes in one peculiar category of the landscape.

  20. SEOSAT/INGENIO: a Spanish high-spatial-resolution optical mission

    Science.gov (United States)

    Marini, A.; Reina Barragan, F. J.; Crippa, G.; Harnisch, B.; Fuente, I.; Lopez, M.; Cabeza, I.; Zorita, D.

    2017-11-01

    SEOSAT/Ingenio (Spanish Earth Observation SATellite) is a high-spatial-resolution optical mission developed, together with PAZ (a synthetic aperture radar satellite), under the Spanish Earth Observation National Program for Satellites (PNOTS).

  1. Enhancing Spatial Resolution of Remotely Sensed Imagery Using Deep Learning

    Science.gov (United States)

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

    2017-12-01

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

  2. Spatial resolution in visual memory.

    Science.gov (United States)

    Ben-Shalom, Asaf; Ganel, Tzvi

    2015-04-01

    Representations in visual short-term memory are considered to contain relatively elaborated information on object structure. Conversely, representations in earlier stages of the visual hierarchy are thought to be dominated by a sensory-based, feed-forward buildup of information. In four experiments, we compared the spatial resolution of different object properties between two points in time along the processing hierarchy in visual short-term memory. Subjects were asked either to estimate the distance between objects or to estimate the size of one of the objects' features under two experimental conditions, of either a short or a long delay period between the presentation of the target stimulus and the probe. When different objects were referred to, similar spatial resolution was found for the two delay periods, suggesting that initial processing stages are sensitive to object-based properties. Conversely, superior resolution was found for the short, as compared with the long, delay when features were referred to. These findings suggest that initial representations in visual memory are hybrid in that they allow fine-grained resolution for object features alongside normal visual sensitivity to the segregation between objects. The findings are also discussed in reference to the distinction made in earlier studies between visual short-term memory and iconic memory.

  3. Consequences of kriging and land use regression for PM2.5 predictions in epidemiologic analyses: insights into spatial variability using high-resolution satellite data.

    Science.gov (United States)

    Alexeeff, Stacey E; Schwartz, Joel; Kloog, Itai; Chudnovsky, Alexandra; Koutrakis, Petros; Coull, Brent A

    2015-01-01

    Many epidemiological studies use predicted air pollution exposures as surrogates for true air pollution levels. These predicted exposures contain exposure measurement error, yet simulation studies have typically found negligible bias in resulting health effect estimates. However, previous studies typically assumed a statistical spatial model for air pollution exposure, which may be oversimplified. We address this shortcoming by assuming a realistic, complex exposure surface derived from fine-scale (1 km × 1 km) remote-sensing satellite data. Using simulation, we evaluate the accuracy of epidemiological health effect estimates in linear and logistic regression when using spatial air pollution predictions from kriging and land use regression models. We examined chronic (long-term) and acute (short-term) exposure to air pollution. Results varied substantially across different scenarios. Exposure models with low out-of-sample R(2) yielded severe biases in the health effect estimates of some models, ranging from 60% upward bias to 70% downward bias. One land use regression exposure model with >0.9 out-of-sample R(2) yielded upward biases up to 13% for acute health effect estimates. Almost all models drastically underestimated the SEs. Land use regression models performed better in chronic effect simulations. These results can help researchers when interpreting health effect estimates in these types of studies.

  4. Classification of high resolution satellite images

    OpenAIRE

    Karlsson, Anders

    2003-01-01

    In this thesis the Support Vector Machine (SVM)is applied on classification of high resolution satellite images. Sveral different measures for classification, including texture mesasures, 1st order statistics, and simple contextual information were evaluated. Additionnally, the image was segmented, using an enhanced watershed method, in order to improve the classification accuracy.

  5. Merging thermal and microwave satellite observations for a high-resolution soil moisture data product

    Science.gov (United States)

    Many societal applications of soil moisture data products require high spatial resolution and numerical accuracy. Current thermal geostationary satellite sensors (GOES Imager and GOES-R ABI) could produce 2-16km resolution soil moisture proxy data. Passive microwave satellite radiometers (e.g. AMSR...

  6. High spatial resolution radiation budget for Europe: derived from satellite data, validation of a regional model; Raeumlich hochaufgeloeste Strahlungsbilanz ueber Europa: Ableitung aus Satellitendaten, Validation eines regionalen Modells

    Energy Technology Data Exchange (ETDEWEB)

    Hollmann, R. [GKSS-Forschungszentrum Geesthacht GmbH (Germany). Inst. fuer Atmosphaerenphysik

    2000-07-01

    Since forty years instruments onboard satellites have been demonstrated their usefulness for many applications in the field of meteorology and oceanography. Several experiments, like ERBE, are dedicated to establish a climatology of the global Earth radiation budget at the top of the atmosphere. Now the focus has been changed to the regional scale, e.g. GEWEX with its regional sub-experiments like BALTEX. To obtain a regional radiation budget for Europe in the first part of the work the well calibrated measurements from ScaRaB (scanner for radiation budget) are used to derive a narrow-to-broadband conversion, which is applicable to the AVHRR (advanced very high resolution radiometer). It is shown, that the accuracy of the method is in the order of that from SCaRaB itself. In the second part of the work, results of REMO have been compared with measurements of ScaRaB and AVHRR for March 1994. The model reproduces the measurements overall well, but it is overestimating the cold areas and underestimating the warm areas in the longwave spectral domain. Similarly it is overestimating the dark areas and underestimating the bright areas in the solar spectral domain. (orig.)

  7. Continuous Field Vegetation Classification of a Sagebrush (Artemesia spp.) Dominated Ecosystem Using High Spatial-Resolution Multi-spectral Satellite Imagery

    Science.gov (United States)

    Buchert, M. P.; White, M.

    2006-12-01

    Global change scientists have grown increasingly interested over the past decade in continuous field vegetation mapping, whereby remotely sensed imagery is processed to yield a data product whose pixel values represent the percent of ground element land area covered by vegetative canopy. The continuous field approach offers distinct benefits over older discrete classification approaches, but current methods developed for production of global tree cover data sets are biased in favor of taller, denser vegetation and misrepresent percent cover of woody shrubs, the dominant vegetation throughout large reaches of North America's Intermountain West. The underperformance of current methods in accurately representing shrub cover is of significant interest to conservation biologists, as shrub-steppe ecosystems dominated by sagebrush (Artemesia spp.) are among the most threatened habitats in North America. We report on our efforts to generate percent-cover vegetation classifications for shrub, herbaceous, and bare land cover classes for study sites in northeastern Nevada and northeastern Utah, using 4m multi-spectral satellite imagery, a regression-tree classification method, and ground-collected reference data. Continuous field vegetation cover data are typically used as inputs to carbon cycling models, but we anticipate that at the fine grain of our dataset, such data will also be useful in ecological and conservation biological applications. In this vein, we demonstrate the applicability of high resolution shrub percent-cover data to habitat modeling efforts for threatened sage-obligate species.

  8. Deep Learning for Super-Resolution of Time Series Satellite Images

    Data.gov (United States)

    National Aeronautics and Space Administration — We propose to use deep learning techniques to enhance the spatial resolution of time series satellite images. This improvement, also called “super-resolution” is...

  9. Using High Spatial Resolution Digital Imagery

    National Research Council Canada - National Science Library

    Campbell, Michael V; Fischer, Robert L; Pangburn, Timothy; Hardenberg, Mark J

    2005-01-01

    This document is the culmination of over 3 years worth of applied research. The overall objective of this multi-year investigation was to assess the utility of high spatial resolution digital imagery to Corps civil works operations...

  10. Comparison of Satellite NO2 Observations with High Resolution Model Simulations over the Balkan Peninsula

    International Nuclear Information System (INIS)

    Zyrichidou, I.; Koukouli, M. E.; Balis, D. S.; Katragkou, E.; Poupkou, A.; Kioutsioukis, I.; Markakis, K.; Melas, D.; van der A., R.; Boersma, F. K.; Roozendael, M. van

    2010-01-01

    High resolution model estimations of tropospheric NO 2 column amounts from the Comprehensive Air Quality Model (CAMx) were simulated for the Balkan Peninsula and were compared with satellite data for a period of one year, in order to study the characteristics of the spatial and temporal variability of pollution in the area. The Balkan area is considered a crossroad of different pollution sources and therefore has been divided in urban, industrial and rural regions, aiming to investigate the consistency of satellite retrievals and model predictions at high spatial resolution. Satellite measurements of tropospheric NO 2 are available daily at 13:30 LT since 2004 from OMI/Aura with a resolution of 13x24 km. The anthropogenic emissions used in CAMx for the domain under study, was compiled employing bottom-up approaches (road transport sector, off-road machinery) as well as other national registries and international databases. High resolution GIS maps (road network, landuses, population) were also used in order to achieve high spatial resolution. In most of the cases the model reveals similar spatial patterns with the satellite data, while over certain areas discrepancies were found and investigated.

  11. Hurricane Satellite (HURSAT) from Advanced Very High Resolution Radiometer (AVHRR)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Huricane Satellite (HURSAT)-Advanced Very High Resolution Radiometer (AVHRR) is used to extend the HURSAT data set such that appling the Objective Dvorak technique...

  12. Improved wetland classification using eight-band high-resolution satellite imagery and a hybrid approach

    Science.gov (United States)

    Although remote sensing technology has long been used in wetland inventory and monitoring, the accuracy and detail level of derived wetland maps were limited or often unsatisfactory largely due to the relatively coarse spatial resolution of conventional satellite imagery. This re...

  13. Super-Resolution Reconstruction of High-Resolution Satellite ZY-3 TLC Images

    Science.gov (United States)

    Li, Lin; Wang, Wei; Luo, Heng; Ying, Shen

    2017-01-01

    Super-resolution (SR) image reconstruction is a technique used to recover a high-resolution image using the cumulative information provided by several low-resolution images. With the help of SR techniques, satellite remotely sensed images can be combined to achieve a higher-resolution image, which is especially useful for a two- or three-line camera satellite, e.g., the ZY-3 high-resolution Three Line Camera (TLC) satellite. In this paper, we introduce the application of the SR reconstruction method, including motion estimation and the robust super-resolution technique, to ZY-3 TLC images. The results show that SR reconstruction can significantly improve both the resolution and image quality of ZY-3 TLC images. PMID:28481287

  14. Super-Resolution Reconstruction of High-Resolution Satellite ZY-3 TLC Images

    Directory of Open Access Journals (Sweden)

    Lin Li

    2017-05-01

    Full Text Available Super-resolution (SR image reconstruction is a technique used to recover a high-resolution image using the cumulative information provided by several low-resolution images. With the help of SR techniques, satellite remotely sensed images can be combined to achieve a higher-resolution image, which is especially useful for a two- or three-line camera satellite, e.g., the ZY-3 high-resolution Three Line Camera (TLC satellite. In this paper, we introduce the application of the SR reconstruction method, including motion estimation and the robust super-resolution technique, to ZY-3 TLC images. The results show that SR reconstruction can significantly improve both the resolution and image quality of ZY-3 TLC images.

  15. Super-Resolution Reconstruction of High-Resolution Satellite ZY-3 TLC Images.

    Science.gov (United States)

    Li, Lin; Wang, Wei; Luo, Heng; Ying, Shen

    2017-05-07

    Super-resolution (SR) image reconstruction is a technique used to recover a high-resolution image using the cumulative information provided by several low-resolution images. With the help of SR techniques, satellite remotely sensed images can be combined to achieve a higher-resolution image, which is especially useful for a two- or three-line camera satellite, e.g., the ZY-3 high-resolution Three Line Camera (TLC) satellite. In this paper, we introduce the application of the SR reconstruction method, including motion estimation and the robust super-resolution technique, to ZY-3 TLC images. The results show that SR reconstruction can significantly improve both the resolution and image quality of ZY-3 TLC images.

  16. Is Spatial Resolution Critical in Urbanization Velocity Analysis? Investigations in the Pearl River Delta

    Directory of Open Access Journals (Sweden)

    Chunzhu Wei

    2017-01-01

    Full Text Available Grid-based urbanization velocity analysis of remote sensing imagery is used to measure urban growth rates. However, it remains unclear how critical the spatial resolution of the imagery is to such grid-based approaches. This research therefore investigated how urbanization velocity estimates respond to different spatial resolutions, as determined by the grid sizes used. Landsat satellite images of the Pearl River Delta (PRD in China from the years 2000, 2005, 2010 and 2015 were hierarchically aggregated using different grid sizes. Statistical analyses of urbanization velocity derived using different spatial resolutions (or grid sizes were used to investigate the relationships between socio-economic indicators and the velocity of urbanization for 27 large cities in PRD. The results revealed that those cities with above-average urbanization velocities remain unaffected by the spatial resolution (or grid-size, and the relationships between urbanization velocities and socio-economic indicators are independent of spatial resolution (or grid sizes used. Moreover, empirical variogram models, the local variance model, and the geographical variance model all indicated that coarse resolution version (480 m of Landsat images based on aggregated pixel yielded more appropriate results than the original fine resolution version (30 m, when identifying the characteristics of spatial autocorrelation and spatial structure variability of urbanization patterns and processes. The results conclude that the most appropriate spatial resolution for investigations into urbanization velocities is not always the highest resolution. The resulting patterns of urbanization velocities at different spatial resolutions can be used as a basis for studying the spatial heterogeneity of other datasets with variable spatial resolutions, especially for evaluating the capability of a multi-resolution dataset in reflecting spatial structure and spatial autocorrelation features in an

  17. Classification of High Spatial Resolution, Hyperspectral ...

    Science.gov (United States)

    EPA announced the availability of the final report,Classification of High Spatial Resolution, Hyperspectral Remote Sensing Imagery of the Little Miami River Watershed in Southwest Ohio, USA . This report and associated land use/land cover (LULC) coverage is the result of a collaborative effort among an interdisciplinary team of scientists with the U.S. Environmental Protection Agency's (U.S. EPA's) Office of Research and Development in Cincinnati, Ohio. A primary goal of this project is to enhance the use of geography and spatial analytic tools in risk assessment, and to improve the scientific basis for risk management decisions affecting drinking water and water quality. The land use/land cover classification is derived from 82 flight lines of Compact Airborne Spectrographic Imager (CASI) hyperspectral imagery acquired from July 24 through August 9, 2002 via fixed-wing aircraft.

  18. Optofluidic microscope with 3D spatial resolution

    DEFF Research Database (Denmark)

    Vig, Asger Laurberg; Marie, Rodolphe; Jensen, Eric

    2010-01-01

    This paper reports on-chip based optical detection with three-dimensional spatial resolution by integration of an optofluidic microscope (OFM) in a microfluidic pinched flow fractionation (PFF) separation device. This setup also enables on-chip particle image velocimetry (PIV). The position...... fluorescence microscope readout. The size separated microspheres are detected by OFM with an accuracy of ≤0.92μm. The position in the height of the channel and the velocity of the separated microspheres are detected with an accuracy of 1.4μm and 0.08 mm/s respectively. Throughout the measurements of the height...

  19. Spatial and decadal variations in satellite-based terrestrial ...

    Indian Academy of Sciences (India)

    Zhaolu Zhang

    2017-12-02

    s12040-017-0885-0. Spatial and decadal variations in satellite-based terrestrial evapotranspiration and drought over. Inner Mongolia Autonomous Region of China during 1982–2009. Zhaolu Zhang1, Hui Kang2, Yunjun Yao3,.

  20. Fuel type characterization based on coarse resolution MODIS satellite data

    Directory of Open Access Journals (Sweden)

    Lanorte A

    2007-01-01

    Full Text Available Fuel types is one of the most important factors that should be taken into consideration for computing spatial fire hazard and risk and simulating fire growth and intensity across a landscape. In the present study, forest fuel mapping is considered from a remote sensing perspective. The purpose is to delineate forest types by exploring the use of coarse resolution satellite remote sensing MODIS imagery. In order to ascertain how well MODIS data can provide an exhaustive classification of fuel properties a sample area characterized by mixed vegetation covers and complex topography was analysed. The study area is located in the South of Italy. Fieldwork fuel type recognitions, performed before, after and during the acquisition of remote sensing MODIS data, were used as ground-truth dataset to assess the obtained results. The method comprised the following three steps: (I adaptation of Prometheus fuel types for obtaining a standardization system useful for remotely sensed classification of fuel types and properties in the considered Mediterranean ecosystems; (II model construction for the spectral characterization and mapping of fuel types based on two different approach, maximum likelihood (ML classification algorithm and spectral Mixture Analysis (MTMF; (III accuracy assessment for the performance evaluation based on the comparison of MODIS-based results with ground-truth. Results from our analyses showed that the use of remotely sensed MODIS data provided a valuable characterization and mapping of fuel types being that the achieved classification accuracy was higher than 73% for ML classifier and higher than 83% for MTMF.

  1. Inverse modeling of pan-Arctic methane emissions at high spatial resolution: what can we learn from assimilating satellite retrievals and using different process-based wetland and lake biogeochemical models?

    Directory of Open Access Journals (Sweden)

    Z. Tan

    2016-10-01

    Full Text Available Understanding methane emissions from the Arctic, a fast-warming carbon reservoir, is important for projecting future changes in the global methane cycle. Here we optimized methane emissions from north of 60° N (pan-Arctic regions using a nested-grid high-resolution inverse model that assimilates both high-precision surface measurements and column-average SCanning Imaging Absorption spectroMeter for Atmospheric CHartogrphY (SCIAMACHY satellite retrievals of methane mole fraction. For the first time, methane emissions from lakes were integrated into an atmospheric transport and inversion estimate, together with prior wetland emissions estimated with six biogeochemical models. In our estimates, in 2005, global methane emissions were in the range of 496.4–511.5 Tg yr−1, and pan-Arctic methane emissions were in the range of 11.9–28.5 Tg yr−1. Methane emissions from pan-Arctic wetlands and lakes were 5.5–14.2 and 2.4–14.2 Tg yr−1, respectively. Methane emissions from Siberian wetlands and lakes are the largest and also have the largest uncertainty. Our results indicate that the uncertainty introduced by different wetland models could be much larger than the uncertainty of each inversion. We also show that assimilating satellite retrievals can reduce the uncertainty of the nested-grid inversions. The significance of lake emissions cannot be identified across the pan-Arctic by high-resolution inversions, but it is possible to identify high lake emissions from some specific regions. In contrast to global inversions, high-resolution nested-grid inversions perform better in estimating near-surface methane concentrations.

  2. Tamarisk Mapping and Monitoring Using High Resolution Satellite Imagery

    Science.gov (United States)

    Jason W. San Souci; John T. Doyle

    2006-01-01

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

  3. Analysis of urban decay from low resolution satellite remote sensing ...

    African Journals Online (AJOL)

    This paper analyzed the spatial and temporal pattern of urban decay in different parts of a traditional organic city through data extracted from satellite remote sensing images. It analyzed temporal differences in urban quality in the city using uniform parameter of urban blight measurement. It presented a classification scheme ...

  4. 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).

  5. Global High Resolution Sea Surface Flux Parameters From Multiple Satellites

    Science.gov (United States)

    Zhang, H.; Reynolds, R. W.; Shi, L.; Bates, J. J.

    2007-05-01

    Advances in understanding the coupled air-sea system and modeling of the ocean and atmosphere demand increasingly higher resolution data, such as air-sea fluxes of up to 3 hourly and every 50 km. These observational requirements can only be met by utilizing multiple satellite observations. Generation of such high resolution products from multiple-satellite and in-situ observations on an operational basis has been started at the U.S. National Oceanic and Atmospheric Administration (NOAA) National Climatic Data Center. Here we describe a few products that are directly related to the computation of turbulent air-sea fluxes. Sea surface wind speed has been observed from in-situ instruments and multiple satellites, with long-term observations ranging from one satellite in the mid 1987 to six or more satellites since mid 2002. A blended product with a global 0.25° grid and four snapshots per day has been produced for July 1987 to present, using a near Gaussian 3-D (x, y, t) interpolation to minimize aliases. Wind direction has been observed from fewer satellites, thus for the blended high resolution vector winds and wind stresses, the directions are taken from the NCEP Re-analysis 2 (operationally run near real time) for climate consistency. The widely used Reynolds Optimum Interpolation SST analysis has been improved with higher resolutions (daily and 0.25°). The improvements use both infrared and microwave satellite data that are bias-corrected by in- situ observations for the period 1985 to present. The new versions provide very significant improvements in terms of resolving ocean features such as the meandering of the Gulf Stream, the Aghulas Current, the equatorial jets and other fronts. The Ta and Qa retrievals are based on measurements from the AMSU sounder onboard the NOAA satellites. Ta retrieval uses AMSU-A data, while Qa retrieval uses both AMSU-A and AMSU-B observations. The retrieval algorithms are developed using the neural network approach. Training

  6. LUMINOUS SATELLITES OF EARLY-TYPE GALAXIES. I. SPATIAL DISTRIBUTION

    International Nuclear Information System (INIS)

    Nierenberg, A. M.; Auger, M. W.; Treu, T.; Marshall, P. J.; Fassnacht, C. D.

    2011-01-01

    We study the spatial distribution of faint satellites of intermediate redshift (0.1 s = 1.7 +0.9 -0.8 ) that is comparable to the number of Milky Way satellites with similar host-satellite contrast. The average projected radial profile of the satellite distribution is isothermal (γ p = -1.0 +0.3 -0.4 ), which is consistent with the observed central mass density profile of massive early-type galaxies. Furthermore, the satellite distribution is highly anisotropic (isotropy is ruled out at a >99.99% confidence level). Defining φ to be the offset between the major axis of the satellite spatial distribution and the major axis of the host light profile, we find a maximum posterior probability of φ = 0 and |φ| less than 42 0 at the 68% confidence level. The alignment of the satellite distribution with the light of the host is consistent with simulations, assuming that light traces mass for the host galaxy as observed for lens galaxies. The anisotropy of the satellite population enhances its ability to produce the flux ratio anomalies observed in gravitationally lensed quasars.

  7. Strengthening IAEA safeguards using high-resolution commercial satellite imagery

    International Nuclear Information System (INIS)

    Zhang Hui

    2001-01-01

    Full text: In May 1997, the IAEA Board of Governors adopted the Additional Safeguards Protocol to improve its ability to detect the undeclared production of fissile material. This new strengthened safeguards system has opened the door for the IAEA to use of all types of information, including the potential use of commercial satellite imagery. We have therefore been investigating the feasibility of strengthening IAEA safeguards using commercial satellite imagery. Based on our analysis on a number of one-meter resolution IKONOS satellite images of military nuclear production facilities at nuclear states including Russia, China, India, Pakistan and Israel, we found that the new high-resolution commercial satellite imagery would play a new and valuable role in strengthening IAEA safeguards. Since 1999, images with a resolution of one meter have been available commercially from Space Imaging's IKONOS satellite. One-meter images from other companies are expected to enter the market soon. Although still an order of magnitude less capable than military imaging satellites, the capabilities of these new high-resolution commercial satellites are good enough to detect and identify the major visible characteristics of nuclear production facilities and sites. Unlike the classified spy satellite photos limited to few countries, the commercial satellite imagery is commercially available to anyone who wants to purchase it. Therefore, the new commercial satellite open a new chance that each state, international organizations, and non-governmental groups could use the commercial images to play a more proactive role in monitoring the nuclear activities in related countries and verifying the compliance of non-proliferation agreements. This could help galvanize support for intensified efforts to slow the pace of nuclear proliferation. To produce fissile materials (plutonium and highly enriched uranium) for weapons, a country would operate dedicated plutonium-production reactors and the

  8. LUMINOUS SATELLITES. II. SPATIAL DISTRIBUTION, LUMINOSITY FUNCTION, AND COSMIC EVOLUTION

    Energy Technology Data Exchange (ETDEWEB)

    Nierenberg, A. M.; Treu, T. [Department of Physics, University of California, Santa Barbara, CA 93106 (United States); Auger, M. W. [Institute of Astronomy, University of Cambridge, Madingley Road, Cambridge CB30HA (United Kingdom); Marshall, P. J. [Department of Physics, University of Oxford, Keble Road, Oxford OX1 3RH (United Kingdom); Fassnacht, C. D. [Department of Physics, University of California, Davis, CA 95616 (United States); Busha, Michael T., E-mail: amn01@physics.ucsb.edu [Institute for Theoretical Physics, University of Zuerich, Zuerich (Switzerland)

    2012-06-20

    We infer the normalization and the radial and angular distributions of the number density of satellites of massive galaxies (log{sub 10}[M*{sub h}/M{sub Sun }] > 10.5) between redshifts 0.1 and 0.8 as a function of host stellar mass, redshift, morphology, and satellite luminosity. Exploiting the depth and resolution of the COSMOS Hubble Space Telescope images, we detect satellites up to 8 mag fainter than the host galaxies and as close as 0.3 (1.4) arcsec (kpc). Describing the number density profile of satellite galaxies to be a projected power law such that P(R){proportional_to}R{sup {gamma}{sub p}}, we find {gamma}{sub p} = -1.1 {+-} 0.3. We find no dependency of {gamma}{sub p} on host stellar mass, redshift, morphology, or satellite luminosity. Satellites of early-type hosts have angular distributions that are more flattened than the host light profile and are aligned with its major axis. No significant average alignment is detected for satellites of late-type hosts. The number of satellites within a fixed magnitude contrast from a host galaxy is dependent on its stellar mass, with more massive galaxies hosting significantly more satellites. Furthermore, high-mass late-type hosts have significantly fewer satellites than early-type galaxies of the same stellar mass, possibly indicating that they reside in more massive halos. No significant evolution in the number of satellites per host is detected. The cumulative luminosity function of satellites is qualitatively in good agreement with that predicted using SubHalo Abundance Matching techniques. However, there are significant residual discrepancies in the absolute normalization, suggesting that properties other than the host galaxy luminosity or stellar mass determine the number of satellites.

  9. A spatial Coherent Global Soil Moisture Product with Improved Temporal Resolution

    NARCIS (Netherlands)

    de Jeu, R.A.M.; Holmes, T.R.H.; Parinussa, R.M.; Owe, M.

    2014-01-01

    Global soil moisture products that are completely independent of any type of ancillary data and solely rely on satellite observations are presented. Additionally, we further develop an existing downscaling technique that enhances the spatial resolution of such products to approximately 11. km. These

  10. TESTFIELD TRENTO: GEOMETRIC EVALUATION OF VERY HIGH RESOLUTION SATELLITE IMAGERY

    Directory of Open Access Journals (Sweden)

    G. Agugiaro

    2012-07-01

    Full Text Available Today the use of spaceborne Very High Spatial Resolution (VHSR optical sensors for automatic 3D information extraction is increasing in the scientific and civil communities. The 3D Optical Metrology (3DOM Unit of the Bruno Kessler Foundation (FBK in Trento (Italy has collected stereo VHSR satellite imagery, as well as aerial and terrestrial data over Trento, with the aim to create a complete data collection with state-of-the-art datasets for investigations on image analysis, automatic digital surface model (DSM generation, 2D/3D feature extraction, city modelling and data fusion. The testfield region covers the city of Trento, characterised by very dense urban (historical centre, residential and industrial areas, and the surrounding hills and steep mountains (approximate height range 200-2100 m with cultivations, forests and bare soil. This paper reports the analysis conducted in FBK on the VHSR spaceborne imagery of Trento testfield for 3D information extraction. The data include two stereo-pairs acquired by WorldView-2 in August 2010 and by GeoEye-1 in September 2011 in panchromatic and multispectral mode, together with their original Rational Polynomial Coefficients (RPC, and the position and description of well distributed ground points. For reference and validation, a DSM from airborne LiDAR acquisition is used. The paper gives details on the project and the dataset characteristics. The results achieved by 3DOM on DSM extraction from WorldView-2 and GeoEye-1 stereo-pairs are shown and commented.

  11. Using High Spatial Resolution Digital Imagery

    National Research Council Canada - National Science Library

    Campbell, Michael V; Fischer, Robert L; Pangburn, Timothy; Hardenberg, Mark J

    2005-01-01

    .... The sources of remotely sensed data used in this research effort include digital airborne multispectral imaging technology, digital airborne hyperspectral imaging technology, and digital satellite multispectral images...

  12. The Pleiades System High Resolution Optical Satellite and its Performances

    Science.gov (United States)

    Boussarie, E.

    France is setting up a cooperative program with Italy as main partner, including other european cooperative countries, in order to develop a dual use system. This means that it intends to be used by civilian users, and by military ones, as well. It will deliver optical images (part of the system developed under french responsibility), and radar images (part of the system developed under italian responsibility). This paper aims at describing the optical satellite inside the overall system. The Pléiades optical high resolution system is based upon the use of a satellite featuring a set of newly european developed technologies. This paper reports the status of the satellite development. It describes the newly developed technologies, explains the system sizing philosophy, and describes the performances status.

  13. Automatic Matching of High Resolution Satellite Images Based on RFM

    Directory of Open Access Journals (Sweden)

    JI Shunping

    2016-02-01

    Full Text Available A matching method for high resolution satellite images based on RFM is presented.Firstly,the RFM parameters are used to predict the initial parallax of corresponding points and the prediction accuracy is analyzed.Secondly,the approximate epipolar equation is constructed based on projection tracking and its accuracy is analyzed.Thirdly,approximate 1D image matching is executed on pyramid images and least square matching on base images.At last RANSAC is imbedded to eliminate mis-matching points and matching results are obtained.Test results verified the method more robust and with higher matching rate,compared to 2D gray correlation method and the popular SIFT matching method,and the method preferably solved the question of high resolution satellite image matching with different stereo model,different time and large rotation images.

  14. High spatial resolution probes for neurobiology applications

    Science.gov (United States)

    Gunning, D. E.; Kenney, C. J.; Litke, A. M.; Mathieson, K.

    2009-06-01

    Position-sensitive biological neural networks, such as the brain and the retina, require position-sensitive detection methods to identify, map and study their behavior. Traditionally, planar microelectrodes have been employed to record the cell's electrical activity with device limitations arising from the electrode's 2-D nature. Described here is the development and characterization of an array of electrically conductive micro-needles aimed at addressing the limitations of planar electrodes. The capability of this array to penetrate neural tissue improves the electrode-cell electrical interface and allows more complicated 3-D networks of neurons, such as those found in brain slices, to be studied. State-of-the-art semiconductor fabrication techniques were used to etch and passivate conformally the metal coat and fill high aspect ratio holes in silicon. These are subsequently transformed into needles with conductive tips. This process has enabled the fabrication of arrays of unprecedented dimensions: 61 hexagonally close-packed electrodes, ˜200 μm tall with 60 μm spacing. Electroplating the tungsten tips with platinum ensure suitable impedance values (˜600 kΩ at 1 kHz) for the recording of neuronal signals. Without compromising spatial resolution of the neuronal recordings, this array adds a new and exciting dimension to the study of biological neural networks.

  15. Automatic Matching of High Resolution Satellite Images Based on RFM

    OpenAIRE

    JI Shunping; YUAN Xiuxiao

    2016-01-01

    A matching method for high resolution satellite images based on RFM is presented.Firstly,the RFM parameters are used to predict the initial parallax of corresponding points and the prediction accuracy is analyzed.Secondly,the approximate epipolar equation is constructed based on projection tracking and its accuracy is analyzed.Thirdly,approximate 1D image matching is executed on pyramid images and least square matching on base images.At last RANSAC is imbedded to eliminate mis-matching points...

  16. Mid-Season High-Resolution Satellite Imagery for Forecasting Site-Specific Corn Yield

    Directory of Open Access Journals (Sweden)

    Nahuel R. Peralta

    2016-10-01

    Full Text Available A timely and accurate crop yield forecast is crucial to make better decisions on crop management, marketing, and storage by assessing ahead and implementing based on expected crop performance. The objective of this study was to investigate the potential of high-resolution satellite imagery data collected at mid-growing season for identification of within-field variability and to forecast corn yield at different sites within a field. A test was conducted on yield monitor data and RapidEye satellite imagery obtained for 22 cornfields located in five different counties (Clay, Dickinson, Rice, Saline, and Washington of Kansas (total of 457 ha. Three basic tests were conducted on the data: (1 spatial dependence on each of the yield and vegetation indices (VIs using Moran’s I test; (2 model selection for the relationship between imagery data and actual yield using ordinary least square regression (OLS and spatial econometric (SPL models; and (3 model validation for yield forecasting purposes. Spatial autocorrelation analysis (Moran’s I test for both yield and VIs (red edge NDVI = NDVIre, normalized difference vegetation index = NDVIr, SRre = red-edge simple ratio, near infrared = NIR and green-NDVI = NDVIG was tested positive and statistically significant for most of the fields (p < 0.05, except for one. Inclusion of spatial adjustment to model improved the model fit on most fields as compared to OLS models, with the spatial adjustment coefficient significant for half of the fields studied. When selected models were used for prediction to validate dataset, a striking similarity (RMSE = 0.02 was obtained between predicted and observed yield within a field. Yield maps could assist implementing more effective site-specific management tools and could be utilized as a proxy of yield monitor data. In summary, high-resolution satellite imagery data can be reasonably used to forecast yield via utilization of models that include spatial adjustment to

  17. Restructuring of high-resolution satellite precipitation products for hydrological modeling

    Science.gov (United States)

    Chen, C. J.; Senarath, S. U. S.

    2014-12-01

    Most river basins of the world lack dense networks of precipitation gauges that produce high-quality precipitation data. In these basins, it is difficult to ensure systematic, unbiased hydrological modeling without relying on other sources of precipitation data. Although especially useful for data-scarce river basins, satellite-based precipitation still contains uncertainties that could propagate through hydrological modeling into simulated results, such as flow and stage. One of the main sources of uncertainty is the gridding process itself, typically associated with geo-statistical adjustments/calibrations founded on various interpolation schemes and ground-based measurements. Thus, the accuracy of a satellite precipitation product is inversely related to its resolution, both spatially and temporally. This also holds true for most gridded global/regional data sets. This study presents a method that integrates area-conservative regridding with fraction-redistribution to correct the satellite-based CMORPH data set (~8-km resolution and 30-minute time step) using rain-gauge-based APHRODITE (0.25 degree resolution and daily time step). This method can be broadly applied for refining any pairs of gridded data at different resolutions containing complementary information. Inter-comparison of modeled flow between the usage of the prior- and post-corrected CMORPH, APHRODITE, and gauge data is conducted spanning several orders of magnitude for catchments in Southeast Asia.

  18. Improving spatial resolution of confocal Raman microscopy by super-resolution image restoration.

    Science.gov (United States)

    Cui, Han; Zhao, Weiqian; Wang, Yun; Fan, Ying; Qiu, Lirong; Zhu, Ke

    2016-05-16

    A new super-resolution image restoration confocal Raman microscopy method (SRIR-RAMAN) is proposed for improving the spatial resolution of confocal Raman microscopy. This method can recover the lost high spatial frequency of the confocal Raman microscopy by using Poisson-MAP super-resolution imaging restoration, thereby improving the spatial resolution of confocal Raman microscopy and realizing its super-resolution imaging. Simulation analyses and experimental results indicate that the spatial resolution of SRIR-RAMAN can be improved by 65% to achieve 200 nm with the same confocal Raman microscopy system. This method can provide a new tool for high spatial resolution micro-probe structure detection in physical chemistry, materials science, biomedical science and other areas.

  19. A NEW OPTIMIZED RFM OF HIGH-RESOLUTION SATELLITE IMAGERY

    Directory of Open Access Journals (Sweden)

    C. Li

    2016-06-01

    Full Text Available Over-parameterization and over-correction are two of the major problems in the rational function model (RFM. A new approach of optimized RFM (ORFM is proposed in this paper. By synthesizing stepwise selection, orthogonal distance regression, and residual systematic error correction model, the proposed ORFM can solve the ill-posed problem and over-correction problem caused by constant term. The least square, orthogonal distance, and the ORFM are evaluated with control and check grids generated from satellite observation Terre (SPOT-5 high-resolution satellite data. Experimental results show that the accuracy of the proposed ORFM, with 37 essential RFM parameters, is more accurate than the other two methods, which contain 78 parameters, in cross-track and along-track plane. Moreover, the over-parameterization and over-correction problems have been efficiently alleviated by the proposed ORFM, so the stability of the estimated RFM parameters and its accuracy have been significantly improved.

  20. High-Resolution Imaging of Asteroids/Satellites with AO

    Science.gov (United States)

    Merline, William

    2012-02-01

    We propose to make high-resolution observations of asteroids using AO, to measure size, shape, and pole position (spin vectors), and/or to search for satellites. We have demonstrated that AO imaging allows determination of the pole/dimensions in 1 or 2 nights on a single target, rather than the years of observations with lightcurve inversion techniques that only yield poles and axial ratios, not true dimensions. Our new technique (KOALA) combines AO imaging with lightcurve and occultation data for optimum size/shape determinations. We request that LGS be available for faint targets, but using NGS AO, we will measure several large and intermediate asteroids that are favorably placed in spring/summer of 2012 for size/shape/pole. Accurately determining the volume from the often-irregular shape allows us to derive densities to much greater precision in cases where the mass is known, e.g., from the presence of a satellite. We will search several d! ozen asteroids for the presence of satellites, particularly in under-studied populations, particularly NEOs (we have recently achieved the first-ever optical image of an NEO binary [Merline et al. 2008b, IAUC 8977]). Satellites provide a real-life lab for testing collisional models. We will search for satellites around special objects at the request of lightcurve observers, and we will make a search for debris in the vicinity of Pluto, in support of the New Horizons mission. Our shape/size work requires observations over most of a full rotation period (typically several hours).

  1. Monitoring Termite-Mediated Ecosystem Processes Using Moderate and High Resolution Satellite Imagery

    Science.gov (United States)

    Lind, B. M.; Hanan, N. P.

    2016-12-01

    Termites are considered dominant decomposers and prominent ecosystem engineers in the global tropics and they build some of the largest and architecturally most complex non-human-made structures in the world. Termite mounds significantly alter soil texture, structure, and nutrients, and have major implications for local hydrological dynamics, vegetation characteristics, and biological diversity. An understanding of how these processes change across large scales has been limited by our ability to detect termite mounds at high spatial resolutions. Our research develops methods to detect large termite mounds in savannas across extensive geographic areas using moderate and high resolution satellite imagery. We also investigate the effect of termite mounds on vegetation productivity using Landsat-8 maximum composite NDVI data as a proxy for production. Large termite mounds in arid and semi-arid Senegal generate highly reflective `mound scars' with diameters ranging from 10 m at minimum to greater than 30 m. As Sentinel-2 has several bands with 10 m resolution and Landsat-8 has improved calibration, higher radiometric resolution, 15 m spatial resolution (pansharpened), and improved contrast between vegetated and bare surfaces compared to previous Landsat missions, we found that the largest and most influential mounds in the landscape can be detected. Because mounds as small as 4 m in diameter are easily detected in high resolution imagery we used these data to validate detection results and quantify omission errors for smaller mounds.

  2. Temporal and spatial assessments of minimum air temperature using satellite surface temperature measurements in Massachusetts, USA.

    Science.gov (United States)

    Kloog, Itai; Chudnovsky, Alexandra; Koutrakis, Petros; Schwartz, Joel

    2012-08-15

    Although meteorological stations provide accurate air temperature observations, their spatial coverage is limited and thus often insufficient for epidemiological studies. Satellite data expand spatial coverage, enhancing our ability to estimate near surface air temperature (Ta). However, the derivation of Ta from surface temperature (Ts) measured by satellites is far from being straightforward. In this study, we present a novel approach that incorporates land use regression, meteorological variables and spatial smoothing to first calibrate between Ts and Ta on a daily basis and then predict Ta for days when satellite Ts data were not available. We applied mixed regression models with daily random slopes to calibrate Moderate Resolution Imaging Spectroradiometer (MODIS) Ts data with monitored Ta measurements for 2003. Then, we used a generalized additive mixed model with spatial smoothing to estimate Ta in days with missing Ts. Out-of-sample tenfold cross-validation was used to quantify the accuracy of our predictions. Our model performance was excellent for both days with available Ts and days without Ts observations (mean out-of-sample R(2)=0.946 and R(2)=0.941 respectively). Furthermore, based on the high quality predictions we investigated the spatial patterns of Ta within the study domain as they relate to urban vs. non-urban land uses. Copyright © 2012 Elsevier B.V. All rights reserved.

  3. Scanning SQUID susceptometers with sub-micron spatial resolution

    Energy Technology Data Exchange (ETDEWEB)

    Kirtley, John R., E-mail: jkirtley@stanford.edu; Rosenberg, Aaron J.; Palmstrom, Johanna C.; Holland, Connor M.; Moler, Kathryn A. [Department of Applied Physics, Stanford University, Stanford, California 94305-4045 (United States); Paulius, Lisa [Department of Physics, Western Michigan University, Kalamazoo, Michigan 49008-5252 (United States); Spanton, Eric M. [Department of Physics, Stanford University, Stanford, California 94305-4045 (United States); Schiessl, Daniel [Attocube Systems AG, Königinstraße 11A, 80539 Munich (Germany); Jermain, Colin L.; Gibbons, Jonathan [Department of Physics, Cornell University, Cornell, Ithaca, New York 14853 (United States); Fung, Y.-K.K.; Gibson, Gerald W. [IBM Research Division, T. J. Watson Research Center, Yorktown Heights, New York 10598 (United States); Huber, Martin E. [Department of Physics, University of Colorado Denver, Denver, Colorado 80217-3364 (United States); Ralph, Daniel C. [Department of Physics, Cornell University, Cornell, Ithaca, New York 14853 (United States); Kavli Institute at Cornell, Ithaca, New York 14853 (United States); Ketchen, Mark B. [OcteVue, Hadley, Massachusetts 01035 (United States)

    2016-09-15

    Superconducting QUantum Interference Device (SQUID) microscopy has excellent magnetic field sensitivity, but suffers from modest spatial resolution when compared with other scanning probes. This spatial resolution is determined by both the size of the field sensitive area and the spacing between this area and the sample surface. In this paper we describe scanning SQUID susceptometers that achieve sub-micron spatial resolution while retaining a white noise floor flux sensitivity of ≈2μΦ{sub 0}/Hz{sup 1/2}. This high spatial resolution is accomplished by deep sub-micron feature sizes, well shielded pickup loops fabricated using a planarized process, and a deep etch step that minimizes the spacing between the sample surface and the SQUID pickup loop. We describe the design, modeling, fabrication, and testing of these sensors. Although sub-micron spatial resolution has been achieved previously in scanning SQUID sensors, our sensors not only achieve high spatial resolution but also have integrated modulation coils for flux feedback, integrated field coils for susceptibility measurements, and batch processing. They are therefore a generally applicable tool for imaging sample magnetization, currents, and susceptibilities with higher spatial resolution than previous susceptometers.

  4. Objective Tuning of Model Parameters in CAM5 Across Different Spatial Resolutions

    Science.gov (United States)

    Bulaevskaya, V.; Lucas, D. D.

    2014-12-01

    Parameterizations of physical processes in climate models are highly dependent on the spatial and temporal resolution and must be tuned for each resolution under consideration. At high spatial resolutions, objective methods for parameter tuning are computationally prohibitive. Our work has focused on calibrating parameters in the Community Atmosphere Model 5 (CAM5) for three spatial resolutions: 1, 2, and 4 degrees. Using perturbed-parameter ensembles and uncertainty quantification methodology, we have identified input parameters that minimize discrepancies of energy fluxes simulated by CAM5 across the three resolutions and with respect to satellite observations. We are also beginning to exploit the parameter-resolution relationships to objectively tune parameters in a high-resolution version of CAM5 by leveraging cheaper, low-resolution simulations and statistical models. We will present our approach to multi-resolution climate model parameter tuning, as well as the key findings. This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under contract DE-AC52-07NA27344 and was supported from the DOE Office of Science through the Scientific Discovery Through Advanced Computing (SciDAC) project on Multiscale Methods for Accurate, Efficient, and Scale-Aware Models of the Earth System.

  5. Effects of the Forecasting Methods, Precipitation Character, and Satellite Resolution on the Predictability of Short-Term Quantitative Precipitation Nowcasting (QPN from a Geostationary Satellite.

    Directory of Open Access Journals (Sweden)

    Yu Liu

    Full Text Available The prediction of the short-term quantitative precipitation nowcasting (QPN from consecutive gestational satellite images has important implications for hydro-meteorological modeling and forecasting. However, the systematic analysis of the predictability of QPN is limited. The objective of this study is to evaluate effects of the forecasting model, precipitation character, and satellite resolution on the predictability of QPN using images of a Chinese geostationary meteorological satellite Fengyun-2F (FY-2F which covered all intensive observation since its launch despite of only a total of approximately 10 days. In the first step, three methods were compared to evaluate the performance of the QPN methods: a pixel-based QPN using the maximum correlation method (PMC; the Horn-Schunck optical-flow scheme (PHS; and the Pyramid Lucas-Kanade Optical Flow method (PPLK, which is newly proposed here. Subsequently, the effect of the precipitation systems was indicated by 2338 imageries of 8 precipitation periods. Then, the resolution dependence was demonstrated by analyzing the QPN with six spatial resolutions (0.1atial, 0.3a, 0.4atial rand 0.6. The results show that the PPLK improves the predictability of QPN with better performance than the other comparison methods. The predictability of the QPN is significantly determined by the precipitation system, and a coarse spatial resolution of the satellite reduces the predictability of QPN.

  6. Effects of the Forecasting Methods, Precipitation Character, and Satellite Resolution on the Predictability of Short-Term Quantitative Precipitation Nowcasting (QPN) from a Geostationary Satellite.

    Science.gov (United States)

    Liu, Yu; Xi, Du-Gang; Li, Zhao-Liang; Ji, Wei

    2015-01-01

    The prediction of the short-term quantitative precipitation nowcasting (QPN) from consecutive gestational satellite images has important implications for hydro-meteorological modeling and forecasting. However, the systematic analysis of the predictability of QPN is limited. The objective of this study is to evaluate effects of the forecasting model, precipitation character, and satellite resolution on the predictability of QPN using images of a Chinese geostationary meteorological satellite Fengyun-2F (FY-2F) which covered all intensive observation since its launch despite of only a total of approximately 10 days. In the first step, three methods were compared to evaluate the performance of the QPN methods: a pixel-based QPN using the maximum correlation method (PMC); the Horn-Schunck optical-flow scheme (PHS); and the Pyramid Lucas-Kanade Optical Flow method (PPLK), which is newly proposed here. Subsequently, the effect of the precipitation systems was indicated by 2338 imageries of 8 precipitation periods. Then, the resolution dependence was demonstrated by analyzing the QPN with six spatial resolutions (0.1atial, 0.3a, 0.4atial rand 0.6). The results show that the PPLK improves the predictability of QPN with better performance than the other comparison methods. The predictability of the QPN is significantly determined by the precipitation system, and a coarse spatial resolution of the satellite reduces the predictability of QPN.

  7. The impact of spatial resolution on resolving spatial precipitation patterns in the Himalayas

    NARCIS (Netherlands)

    Bonekamp, P.N.J.; Collier, S.E.; Immerzeel, W.W.

    2017-01-01

    Frequently used gridded meteorological datasets poorly represent precipitation in the Himalaya due to their relatively low spatial resolution and the associated coarse representation of the complex topography. Dynamical downscaling using high-resolution atmospheric models may improve the accuracy

  8. A Feasibility Study of Sea Ice Motion and Deformation Measurements Using Multi-Sensor High-Resolution Optical Satellite Images

    Directory of Open Access Journals (Sweden)

    Chang-Uk Hyun

    2017-09-01

    Full Text Available Sea ice motion and deformation have generally been measured using low-resolution passive microwave or mid-resolution radar remote sensing datasets of daily (or few days intervals to monitor long-term trends over a wide polar area. This feasibility study presents an application of high-resolution optical images from operational satellites, which have become more available in polar regions, for sea ice motion and deformation measurements. The sea ice motion, i.e., Lagrangian vector, is measured by using a maximum cross-correlation (MCC technique and multi-temporal high-resolution images acquired on 14–15 August 2014 from multiple spaceborne sensors on board Korea Multi-Purpose Satellites (KOMPSATs with short acquisition time intervals. The sea ice motion extracted from the six image pairs of the spatial resolutions were resampled to 4 m and 15 m yields with vector length measurements of 57.7 m root mean square error (RMSE and −11.4 m bias and 60.7 m RMSE and −13.5 m bias, respectively, compared with buoy location records. The errors from both resolutions indicate more accurate measurements than from conventional sea ice motion datasets from passive microwave and radar data in ice and water mixed surface conditions. In the results of sea ice deformation caused by interaction of individual ice floes, while free drift patterns of ice floes were delineated from the 4 m spatial resolution images, the deformation was less revealing in the 15 m spatial resolution image pairs due to emphasized discretization uncertainty from coarser pixel sizes. The results demonstrate that using multi-temporal high-resolution optical satellite images enabled precise image block matching in the melting season, thus this approach could be used for expanding sea ice motion and deformation dataset, with an advantage of frequent image acquisition capability in multiple areas by means of many operational satellites.

  9. OMI NO2 column densities over North American urban cities: the effect of satellite footprint resolution

    Science.gov (United States)

    Kim, Hyun Cheol; Lee, Pius; Judd, Laura; Pan, Li; Lefer, Barry

    2016-03-01

    Nitrogen dioxide vertical column density (NO2 VCD) measurements via satellite are compared with a fine-scale regional chemistry transport model, using a new approach that considers varying satellite footprint sizes. Space-borne NO2 VCD measurement has been used as a proxy for surface nitrogen oxide (NOx) emission, especially for anthropogenic urban emission, so accurate comparison of satellite and modeled NO2 VCD is important in determining the future direction of NOx emission policy. The NASA Ozone Monitoring Instrument (OMI) NO2 VCD measurements, retrieved by the Royal Netherlands Meteorological Institute (KNMI), are compared with a 12 km Community Multi-scale Air Quality (CMAQ) simulation from the National Oceanic and Atmospheric Administration. We found that the OMI footprint-pixel sizes are too coarse to resolve urban NO2 plumes, resulting in a possible underestimation in the urban core and overestimation outside. In order to quantify this effect of resolution geometry, we have made two estimates. First, we constructed pseudo-OMI data using fine-scale outputs of the model simulation. Assuming the fine-scale model output is a true measurement, we then collected real OMI footprint coverages and performed conservative spatial regridding to generate a set of fake OMI pixels out of fine-scale model outputs. When compared to the original data, the pseudo-OMI data clearly showed smoothed signals over urban locations, resulting in roughly 20-30 % underestimation over major cities. Second, we further conducted conservative downscaling of OMI NO2 VCDs using spatial information from the fine-scale model to adjust the spatial distribution, and also applied averaging kernel (AK) information to adjust the vertical structure. Four-way comparisons were conducted between OMI with and without downscaling and CMAQ with and without AK information. Results show that OMI and CMAQ NO2 VCDs show the best agreement when both downscaling and AK methods are applied, with the correlation

  10. Spatial Resolution Assessment of the Telops Airborne TIR Imagery

    Science.gov (United States)

    Mousakhani, S.; Eslami, M.; Saadatseresht, M.

    2017-09-01

    Having a high spatial resolution of Thermal InfraRed (TIR) Sensors is a challenge in remote sensing applications. Airborne high spatial resolution TIR is a novel source of data that became available lately. Recent developments in spatial resolution of the TIR sensors have been an interesting topic for scientists. TIR sensors are very sensitive to the energies emitted from objects. Past researches have been shown that increasing the spatial resolution of an airborne image will decrease the spectral content of the data and will reduce the Signal to Noise Ratio (SNR). Therefore, in this paper a comprehensive assessment is adapted to estimate an appropriate spatial resolution of the TIR data (TELOPS TIR data), in consideration of the SNR. So, firstly, a low-pass filter is applied on TIR data and the achieved products fed to a classification method for analysing of the accuracy improvement. The obtained results show that, there is no significant change in classification accuracy by applying low-pass filter. Furthermore, estimation of the appropriate spatial resolution of the TIR data is evaluated for obtaining higher spectral content and SNR. For this purpose, different resolutions of the TIR data are created and fed to the maximum likelihood classification method separately. The results illustrated in the case of using images with ground pixel size four times greater than the original image, the classification accuracy is not reduced. Also, SNR and spectral contents are improved. But the corners sharpening is declined.

  11. Monitoring of oil pollution in the Arabian Gulf based on medium resolution satellite imagery

    Science.gov (United States)

    Zhao, J.; Ghedira, H.

    2013-12-01

    A large number of inland and offshore oil fields are located in the Arabian Gulf where about 25% of the world's oil is produced by the countries surrounding the Arabian Gulf region. Almost all of this oil production is shipped by sea worldwide through the Strait of Hormuz making the region vulnerable to environmental and ecological threats that might arise from accidental or intentional oil spills. Remote sensing technologies have the unique capability to detect and monitor oil pollutions over large temporal and spatial scales. Synoptic satellite imaging can date back to 1972 when Landsat-1 was launched. Landsat satellite missions provide long time series of imagery with a spatial resolution of 30 m. MODIS sensors onboard NASA's Terra and Aqua satellites provide a wide and frequent coverage at medium spatial resolution, i.e. 250 m and 500, twice a day. In this study, the capability of medium resolution MODIS and Landsat data in detecting and monitoring oil pollutions in the Arabian Gulf was tested. Oil spills and slicks show negative or positive contrasts in satellite derived RGB images compared with surrounding clean waters depending on the solar/viewing geometry, oil thickness and evolution, etc. Oil-contaminated areas show different spectral characteristics compared with surrounding waters. Rayleigh-corrected reflectance at the seven medium resolution bands of MODIS is lower in oil affected areas. This is caused by high light absorption of oil slicks. 30-m Landsat image indicated the occurrence of oil spill on May 26 2000 in the Arabian Gulf. The oil spill showed positive contrast and lower temperature than surrounding areas. Floating algae index (FAI) images are also used to detect oil pollution. Oil-contaminated areas were found to have lower FAI values. To track the movement of oil slicks found on October 21 2007, ocean circulations from a HYCOM model were examined and demonstrated that the oil slicks were advected toward the coastal areas of United Arab

  12. New device based on the super spatial resolution (SSR) method

    International Nuclear Information System (INIS)

    Soluri, A.; Atzeni, G.; Ucci, A.; Bellone, T.; Cusanno, F.; Rodilossi, G.; Massari, R.

    2013-01-01

    Recently it have been described that innovative methods, namely Super Spatial Resolution (SSR), can be used to improve the scintigraphic imaging. The aim of SSR techniques is the enhancement of the resolution of an imaging system, using information from several images. In this paper we describe a new experimental apparatus that could be used for molecular imaging and small animal imaging. In fact we present a new device, completely automated, that uses the SSR method and provides images with better spatial resolution in comparison to the original resolution. Preliminary small animal imaging studies confirm the feasibility of a very high resolution system in scintigraphic imaging and the possibility to have gamma cameras using the SSR method, to perform the applications on functional imaging. -- Highlights: • Super spatial resolution brings a high resolution image from scintigraphic images. • Resolution improvement depends on the signal to noise ratio of the original images. • The SSR shows significant improvement on spatial resolution in scintigraphic images. • The SSR method is potentially utilizable for all scintigraphic devices

  13. Scene Classification Using High Spatial Resolution Multispectral Data

    National Research Council Canada - National Science Library

    Garner, Jamada

    2002-01-01

    ...), High-spatial resolution (8-meter), 4-color MSI data from IKONOS provide a new tool for scene classification, The utility of these data are studied for the purpose of classifying the Elkhorn Slough and surrounding wetlands in central...

  14. A temperature-compensated high spatial resolution distributed strain sensor

    International Nuclear Information System (INIS)

    Belal, Mohammad; Cho, Yuh Tat; Ibsen, Morten; Newson, Trevor P

    2010-01-01

    We propose and demonstrate a scheme which utilizes the temperature dependence of spontaneous Raman scattering to provide temperature compensation for a high spatial resolution Brillouin frequency-based strain sensor

  15. Methods of photoelectrode characterization with high spatial and temporal resolution

    Energy Technology Data Exchange (ETDEWEB)

    Esposito, Daniel V. [Department of Chemical Engineering; Columbia University in the City of New York; New York; USA; National Institute of Standards and Technology; Baxter, Jason B. [Department of Chemical and Biological Engineering; Drexel University; Philadelphia; USA; John, Jimmy [Division of Chemistry and Chemical Engineering; California Institute of Technology; Pasadena; USA; Lewis, Nathan S. [Division of Chemistry and Chemical Engineering; California Institute of Technology; Pasadena; USA; Joint Center for Artificial Photosynthesis; Moffat, Thomas P. [National Institute of Standards and Technology; Gaithersburg; USA; Ogitsu, Tadashi [Quantum Simulations Group; Lawrence Livermore National Laboratory; Livermore; USA; O' Neil, Glen D. [Department of Chemical Engineering; Columbia University in the City of New York; New York; USA; Pham, Tuan Anh [Quantum Simulations Group; Lawrence Livermore National Laboratory; Livermore; USA; Talin, A. Alec [Sandia National Laboratories; Livermore; USA; Velazquez, Jesus M. [Division of Chemistry and Chemical Engineering; California Institute of Technology; Pasadena; USA; Joint Center for Artificial Photosynthesis; Wood, Brandon C. [Quantum Simulations Group; Lawrence Livermore National Laboratory; Livermore; USA

    2015-01-01

    This article reviews computational andin situexperimental tools capable of characterizing the properties and performance of photoelectrodes used for solar fuels production with high spatial and temporal resolution.

  16. Fusion of Pixel-based and Object-based Features for Road Centerline Extraction from High-resolution Satellite Imagery

    Directory of Open Access Journals (Sweden)

    CAO Yungang

    2016-10-01

    Full Text Available A novel approach for road centerline extraction from high spatial resolution satellite imagery is proposed by fusing both pixel-based and object-based features. Firstly, texture and shape features are extracted at the pixel level, and spectral features are extracted at the object level based on multi-scale image segmentation maps. Then, extracted multiple features are utilized in the fusion framework of Dempster-Shafer evidence theory to roughly identify the road network regions. Finally, an automatic noise removing algorithm combined with the tensor voting strategy is presented to accurately extract the road centerline. Experimental results using high-resolution satellite imageries with different scenes and spatial resolutions showed that the proposed approach compared favorably with the traditional methods, particularly in the aspect of eliminating the salt noise and conglutination phenomenon.

  17. Detection and Extraction of Roads from High Resolution Satellites Images with Dynamic Programming

    Science.gov (United States)

    Benzouai, Siham; Smara, Youcef

    2010-12-01

    The advent of satellite images allows now a regular and a fast digitizing and update of geographic data, especially roads which are very useful for Geographic Information Systems (GIS) applications such as transportation, urban pollution, geomarketing, etc. For this, several studies have been conducted to automate roads extraction in order to minimize the manual processes [4]. In this work, we are interested in roads extraction from satellite imagery with high spatial resolution (at best equal to 10 m). The method is semi automatic and follows a linear approach where road is considered as a linear object. As roads extraction is a pattern recognition problem, it is useful, above all, to characterize roads. After, we realize a pre-processing by applying an Infinite Size Edge Filter -ISEF- and processing method based on dynamic programming concept, in particular, Fishler algorithm designed by F*.

  18. Evaluating the influence of spatial resolutions of DEM on watershed ...

    Indian Academy of Sciences (India)

    Digital elevation model (DEM) of a watershed forms key basis for hydrologic modelling and its resolution plays a key role in accurate prediction of various hydrological processes. This study appraises the effect of different DEMs with varied spatial resolutions (namely TOPO 20 m, CARTO 30 m, ASTER 30 m, SRTM 90 m, ...

  19. Evaluating the influence of spatial resolutions of DEM on watershed ...

    Indian Academy of Sciences (India)

    Digital elevation model (DEM) of a watershed forms key basis for hydrologic modelling and its resolution plays a key role in accurate prediction of ... ies also investigated the effect of spatial resolution of input datasets on hydrological ... watersheds under different management practices. (Arnold et al. 1998). In the past ...

  20. High spatial resolution compressed sensing (HSPARSE) functional MRI.

    Science.gov (United States)

    Fang, Zhongnan; Van Le, Nguyen; Choy, ManKin; Lee, Jin Hyung

    2016-08-01

    To propose a novel compressed sensing (CS) high spatial resolution functional MRI (fMRI) method and demonstrate the advantages and limitations of using CS for high spatial resolution fMRI. A randomly undersampled variable density spiral trajectory enabling an acceleration factor of 5.3 was designed with a balanced steady state free precession sequence to achieve high spatial resolution data acquisition. A modified k-t SPARSE method was then implemented and applied with a strategy to optimize regularization parameters for consistent, high quality CS reconstruction. The proposed method improves spatial resolution by six-fold with 12 to 47% contrast-to-noise ratio (CNR), 33 to 117% F-value improvement and maintains the same temporal resolution. It also achieves high sensitivity of 69 to 99% compared the original ground-truth, small false positive rate of less than 0.05 and low hemodynamic response function distortion across a wide range of CNRs. The proposed method is robust to physiological noise and enables detection of layer-specific activities in vivo, which cannot be resolved using the highest spatial resolution Nyquist acquisition. The proposed method enables high spatial resolution fMRI that can resolve layer-specific brain activity and demonstrates the significant improvement that CS can bring to high spatial resolution fMRI. Magn Reson Med 76:440-455, 2016. © 2015 The Authors. Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine. This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made. © 2015 The Authors. Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine.

  1. Accuracy VS Performance: Finding the Sweet Spot in the Geospatial Resolution of Satellite Metadata

    Science.gov (United States)

    Baskin, W. E.; Mangosing, D. C.; Rinsland, P. L.

    2010-12-01

    NASA’s Atmospheric Science Data Center (ASDC) and the Cloud-Aerosol LIDAR and Infrared Pathfinder Satellite Observation (CALIPSO) team at the NASA Langley Research Center recently collaborated in the development of a new CALIPSO Search and Subset web application. The web application is comprised of three elements: (1) A PostGIS-enabled PostgreSQL database system, which is used to store temporal and geospatial metadata from CALIPSO’s LIDAR, Infrared, and Wide Field Camera datasets, (2) the SciFlo engine, which is a data flow engine that enables semantic, scientific data flow executions in a grid or clustered network computational environment, and (3) PHP-based web application that incorporates some Web 2.0 / AJAX technologies used in the web interface. The search portion of the web application leverages geodetic indexing and search capabilities that became available in the February 2010 release of PostGIS version1.5. This presentation highlights the lessons learned in experimenting with various geospatial resolutions of CALIPSO’s LIDAR sensor ground track metadata. Details of the various spatial resolutions, spatial database schema designs, spatial indexing strategies, and performance results will be discussed. The focus will be on illustrating our findings on the spatial resolutions for ground track metadata that optimized search time and search accuracy in the CALIPSO Search and Subset Application. The CALIPSO satellite provides new insight into the role that clouds and atmospheric aerosols (airborne particles) play in regulating Earth's weather, climate, and air quality. CALIPSO combines an active LIDAR instrument with passive infrared and visible imagers to probe the vertical structure and properties of thin clouds and aerosols over the globe. The CALIPSO satellite was launched on April 28, 2006 and is part of the A-train satellite constellation. The ASDC in Langley’s Science Directorate leads NASA’s program for the processing, archival and

  2. Mapping of CO2 at high spatiotemporal resolution using satellite observations: Global distributions from OCO-2

    Science.gov (United States)

    Hammerling, Dorit M.; Michalak, Anna M.; Kawa, S. Randolph

    2012-03-01

    [1] Satellite observations of CO2 offer new opportunities to improve our understanding of the global carbon cycle. Using such observations to infer global maps of atmospheric CO2 and their associated uncertainties can provide key information about the distribution and dynamic behavior of CO2, through comparison to atmospheric CO2 distributions predicted from biospheric, oceanic, or fossil fuel flux emissions estimates coupled with atmospheric transport models. Ideally, these maps should be at temporal resolutions that are short enough to represent and capture the synoptic dynamics of atmospheric CO2. This study presents a geostatistical method that accomplishes this goal. The method can extract information about the spatial covariance structure of the CO2 field from the available CO2 retrievals, yields full coverage (Level 3) maps at high spatial resolutions, and provides estimates of the uncertainties associated with these maps. The method does not require information about CO2 fluxes or atmospheric transport, such that the Level 3 maps are informed entirely by available retrievals. The approach is assessed by investigating its performance using synthetic OCO-2 data generated from the PCTM/GEOS-4/CASA-GFED model, for time periods ranging from 1 to 16 days and a target spatial resolution of 1° latitude × 1.25° longitude. Results show that global CO2 fields from OCO-2 observations can be predicted well at surprisingly high temporal resolutions. Even one-day Level 3 maps reproduce the large-scale features of the atmospheric CO2 distribution, and yield realistic uncertainty bounds. Temporal resolutions of two to four days result in the best performance for a wide range of investigated scenarios, providing maps at an order of magnitude higher temporal resolution relative to the monthly or seasonal Level 3 maps typically reported in the literature.

  3. High-Resolution Satellite Data Open for Government Research

    Science.gov (United States)

    Neigh, Christopher S. R.; Masek, Jeffrey G.; Nickeson, Jaime E.

    2013-01-01

    U.S. satellite commercial imagery (CI) with resolution less than 1 meter is a common geospatial reference used by the public through Web applications, mobile devices, and the news media. However, CI use in the scientific community has not kept pace, even though those who are performing U.S. government research have access to these data at no cost.Previously, studies using multiple CI acquisitions from IKONOS-2, Quickbird-2, GeoEye-1, WorldView-1, and WorldView-2 would have been cost prohibitive. Now, with near-global submeter coverage and online distribution, opportunities abound for future scientific studies. This archive is already quite extensive (examples are shown in Figure 1) and is being used in many novel applications.

  4. DETECTION OF BARCHAN DUNES IN HIGH RESOLUTION SATELLITE IMAGES

    Directory of Open Access Journals (Sweden)

    M. A. Azzaoui

    2016-06-01

    Full Text Available Barchan dunes are the fastest moving sand dunes in the desert. We developed a process to detect barchans dunes on High resolution satellite images. It consisted of three steps, we first enhanced the image using histogram equalization and noise reduction filters. Then, the second step proceeds to eliminate the parts of the image having a texture different from that of the barchans dunes. Using supervised learning, we tested a coarse to fine textural analysis based on Kolomogorov Smirnov test and Youden’s J-statistic on co-occurrence matrix. As an output we obtained a mask that we used in the next step to reduce the search area. In the third step we used a gliding window on the mask and check SURF features with SVM to get barchans dunes candidates. Detected barchans dunes were considered as the fusion of overlapping candidates. The results of this approach were very satisfying in processing time and precision.

  5. The impact of spatial resolution on resolving spatial precipitation patterns in the Himalayas

    OpenAIRE

    Bonekamp, P.N.J.; Collier, S.E.; Immerzeel, W.W.

    2017-01-01

    Frequently used gridded meteorological datasets poorly represent precipitation in the Himalaya due to their relatively low spatial resolution and the associated coarse representation of the complex topography. Dynamical downscaling using high-resolution atmospheric models may improve the accuracy and quality of the precipitation fields, as simulations at higher spatial resolution are more capable of resolving the interaction between the topography and the atmosphere. However, most physics par...

  6. Crop area estimation using high and medium resolution satellite imagery in areas with complex topography

    Science.gov (United States)

    Husak, G. J.; Marshall, M. T.; Michaelsen, J.; Pedreros, D.; Funk, C.; Galu, G.

    2008-07-01

    Reliable estimates of cropped area (CA) in developing countries with chronic food shortages are essential for emergency relief and the design of appropriate market-based food security programs. Satellite interpretation of CA is an effective alternative to extensive and costly field surveys, which fail to represent the spatial heterogeneity at the country-level. Bias-corrected, texture based classifications show little deviation from actual crop inventories, when estimates derived from aerial photographs or field measurements are used to remove systematic errors in medium resolution estimates. In this paper, we demonstrate a hybrid high-medium resolution technique for Central Ethiopia that combines spatially limited unbiased estimates from IKONOS images, with spatially extensive Landsat ETM+ interpretations, land-cover, and SRTM-based topography. Logistic regression is used to derive the probability of a location being crop. These individual points are then aggregated to produce regional estimates of CA. District-level analysis of Landsat based estimates showed CA totals which supported the estimates of the Bureau of Agriculture and Rural Development. Continued work will evaluate the technique in other parts of Africa, while segmentation algorithms will be evaluated, in order to automate classification of medium resolution imagery for routine CA estimation in the future.

  7. An Assessment of the Ability of Potential Satellite Instruments to Resolve Spatial and Temporal Variability of Atmospheric CO2

    Science.gov (United States)

    Andrews, A.; Bhartia, Pawan (Technical Monitor)

    2002-01-01

    Sufficiently precise satellite observations with adequate spatial and temporal resolution would substantially increase our knowledge of the atmospheric CO2 distribution and would undoubtedly lead to reduced uncertainty in estimates of the global carbon budget. An overview of possible strategies for measuring CO2 from space will be presented, including IR and nearby measurements, active sensors and broad band and narrow band passive sensors. The ability of potential satellite instruments with a variety of orbits, horizontal resolution and vertical weighting functions to capture the variation in atmospheric CO2 mixing ratios will be illustrated using a combination of surface data, aircraft data and model results.

  8. A Very High Spatial Resolution Detector for Small Animal PET

    International Nuclear Information System (INIS)

    Kanai Shah, M.S.

    2007-01-01

    Positron Emission Tomography (PET) is an in vivo analog of autoradiography and has the potential to become a powerful new tool in imaging biological processes in small laboratory animals. PET imaging of small animals can provide unique information that can help in advancement of human disease models as well as drug development. Clinical PET scanners used for human imaging are bulky, expensive and do not have adequate spatial resolution for small animal studies. Hence, dedicated, low cost instruments are required for conducting small animal studies with higher spatial resolution than what is currently achieved with clinical as well as dedicated small animal PET scanners. The goal of the proposed project is to investigate a new all solid-state detector design for small animal PET imaging. Exceptionally high spatial resolution, good timing resolution, and excellent energy resolution are expected from the proposed detector design. The Phase I project was aimed at demonstrating the feasibility of producing high performance solid-state detectors that provide high sensitivity, spatial resolution, and timing characteristics. Energy resolution characteristics of the new detector were also investigated. The goal of the Phase II project is to advance the promising solid-state detector technology for small animal PET and determine its full potential. Detectors modules will be built and characterized and finally, a bench-top small animal PET system will be assembled and evaluated

  9. 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.

  10. A high-resolution and observationally constrained OMI NO2 satellite retrieval

    Science.gov (United States)

    Goldberg, Daniel L.; Lamsal, Lok N.; Loughner, Christopher P.; Swartz, William H.; Lu, Zifeng; Streets, David G.

    2017-09-01

    This work presents a new high-resolution NO2 dataset derived from the NASA Ozone Monitoring Instrument (OMI) NO2 version 3.0 retrieval that can be used to estimate surface-level concentrations. The standard NASA product uses NO2 vertical profile shape factors from a 1.25° × 1° (˜ 110 km × 110 km) resolution Global Model Initiative (GMI) model simulation to calculate air mass factors, a critical value used to determine observed tropospheric NO2 vertical columns. To better estimate vertical profile shape factors, we use a high-resolution (1.33 km × 1.33 km) Community Multi-scale Air Quality (CMAQ) model simulation constrained by in situ aircraft observations to recalculate tropospheric air mass factors and tropospheric NO2 vertical columns during summertime in the eastern US. In this new product, OMI NO2 tropospheric columns increase by up to 160 % in city centers and decrease by 20-50 % in the rural areas outside of urban areas when compared to the operational NASA product. Our new product shows much better agreement with the Pandora NO2 and Airborne Compact Atmospheric Mapper (ACAM) NO2 spectrometer measurements acquired during the DISCOVER-AQ Maryland field campaign. Furthermore, the correlation between our satellite product and EPA NO2 monitors in urban areas has improved dramatically: r2 = 0.60 in the new product vs. r2 = 0.39 in the operational product, signifying that this new product is a better indicator of surface concentrations than the operational product. Our work emphasizes the need to use both high-resolution and high-fidelity models in order to recalculate satellite data in areas with large spatial heterogeneities in NOx emissions. Although the current work is focused on the eastern US, the methodology developed in this work can be applied to other world regions to produce high-quality region-specific NO2 satellite retrievals.

  11. ROI-ORIENTATED SENSOR CORRECTION BASED ON VIRTUAL STEADY REIMAGING MODEL FOR WIDE SWATH HIGH RESOLUTION OPTICAL SATELLITE IMAGERY

    Directory of Open Access Journals (Sweden)

    Y. Zhu

    2017-09-01

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

  12. Generating High-Temporal and Spatial Resolution TIR Image Data

    Science.gov (United States)

    Herrero-Huerta, M.; Lagüela, S.; Alfieri, S. M.; Menenti, M.

    2017-09-01

    Remote sensing imagery to monitor global biophysical dynamics requires the availability of thermal infrared data at high temporal and spatial resolution because of the rapid development of crops during the growing season and the fragmentation of most agricultural landscapes. Conversely, no single sensor meets these combined requirements. Data fusion approaches offer an alternative to exploit observations from multiple sensors, providing data sets with better properties. A novel spatio-temporal data fusion model based on constrained algorithms denoted as multisensor multiresolution technique (MMT) was developed and applied to generate TIR synthetic image data at both temporal and spatial high resolution. Firstly, an adaptive radiance model is applied based on spectral unmixing analysis of . TIR radiance data at TOA (top of atmosphere) collected by MODIS daily 1-km and Landsat - TIRS 16-day sampled at 30-m resolution are used to generate synthetic daily radiance images at TOA at 30-m spatial resolution. The next step consists of unmixing the 30 m (now lower resolution) images using the information about their pixel land-cover composition from co-registered images at higher spatial resolution. In our case study, TIR synthesized data were unmixed to the Sentinel 2 MSI with 10 m resolution. The constrained unmixing preserves all the available radiometric information of the 30 m images and involves the optimization of the number of land-cover classes and the size of the moving window for spatial unmixing. Results are still being evaluated, with particular attention for the quality of the data streams required to apply our approach.

  13. GENERATING HIGH-TEMPORAL AND SPATIAL RESOLUTION TIR IMAGE DATA

    Directory of Open Access Journals (Sweden)

    M. Herrero-Huerta

    2017-09-01

    Full Text Available Remote sensing imagery to monitor global biophysical dynamics requires the availability of thermal infrared data at high temporal and spatial resolution because of the rapid development of crops during the growing season and the fragmentation of most agricultural landscapes. Conversely, no single sensor meets these combined requirements. Data fusion approaches offer an alternative to exploit observations from multiple sensors, providing data sets with better properties. A novel spatio-temporal data fusion model based on constrained algorithms denoted as multisensor multiresolution technique (MMT was developed and applied to generate TIR synthetic image data at both temporal and spatial high resolution. Firstly, an adaptive radiance model is applied based on spectral unmixing analysis of . TIR radiance data at TOA (top of atmosphere collected by MODIS daily 1-km and Landsat – TIRS 16-day sampled at 30-m resolution are used to generate synthetic daily radiance images at TOA at 30-m spatial resolution. The next step consists of unmixing the 30 m (now lower resolution images using the information about their pixel land-cover composition from co-registered images at higher spatial resolution. In our case study, TIR synthesized data were unmixed to the Sentinel 2 MSI with 10 m resolution. The constrained unmixing preserves all the available radiometric information of the 30 m images and involves the optimization of the number of land-cover classes and the size of the moving window for spatial unmixing. Results are still being evaluated, with particular attention for the quality of the data streams required to apply our approach.

  14. Super-resolution post-processing for satellites with yaw-steering capability

    CSIR Research Space (South Africa)

    Van den Dool, R

    2012-10-01

    Full Text Available We describe a method for improving Earth observation satellite image resolution, for specific areas of interest where the sensor design resolution is insufficient. Our method may be used for satellites with yaw-steering capability, such as Nigeria...

  15. Improved Spatial Resolution For Reflection Mode Infrared Spectromicroscopy

    International Nuclear Information System (INIS)

    Bechtel, Hans A.; Martin, Michael C.; May, T.E.; Lerch, Philippe

    2009-01-01

    Standard commercial infrared microscopes operating in reflection mode use a mirror to direct the reflected light from the sample to the detector. This mirror blocks about half of the incident light, however, and thus degrades the spatial resolution by reducing the numerical aperture of the objective. Here, we replace the mirror with a 50% beamsplitter to allow full illumination of the objective and retain a way to direct the reflected light to the detector. The improved spatial resolution is demonstrated using a microscope coupled to a synchrotron source.

  16. Improved Spatial Resolution For Reflection Mode Infrared Spectromicroscopy

    International Nuclear Information System (INIS)

    Bechtel, Hans A.; Martin, Michael C.; May, T. E.; Lerch, Philippe

    2010-01-01

    Standard commercial infrared microscopes operating in reflection mode use a mirror to direct the reflected light from the sample to the detector. This mirror blocks about half of the incident light, however, and thus degrades the spatial resolution by reducing the numerical aperture of the objective. Here, we replace the mirror with a 50% beamsplitter to allow full illumination of the objective and retain a way to direct the reflected light to the detector. The improved spatial resolution is demonstrated using a microscope coupled to a synchrotron source.

  17. Spatial Resolution of the ECE for JET Typical Parameters

    Energy Technology Data Exchange (ETDEWEB)

    Tribaldos, V. [Ciemat. Madrid (Spain)

    2000-07-01

    The purpose of this report is to obtain estimations of the spatial resolution of the electron cyclotron emission (ECE) phenomena for the typical plasmas found in JET tokamak. The analysis of the spatial resolution of the ECE is based on the underlying physical process of emission and a working definition is presented and discussed. In making these estimations a typical JET pulse is being analysed taking into account the magnetic configuration, the density and temperature profiles, obtained with the EFIT code and from the LIDAR diagnostic. Ray tracing simulations are performed for a Maxwellian plasma taking into account the antenna pattern. (Author) 5 refs.

  18. Interactions of collimation, sampling and filtering on spect spatial resolution

    International Nuclear Information System (INIS)

    Tsui, B.M.W.; Jaszczak, R.J.

    1984-01-01

    The major factors which affect the spatial resolution of single-photon emission computer tomography (SPECT) include collimation, sampling and filtering. A theoretical formulation is presented to describe the relationship between these factors and their effects on the projection data. Numerical calculations were made using commercially available SPECT systems and imaging parameters. The results provide an important guide for proper selection of the collimator-detector design, the imaging and the reconstruction parameters to avoid unnecessary spatial resolution degradation and aliasing artifacts in the reconstructed image. In addition, the understanding will help in the fair evaluation of different SPECT systems under specific imaging conditions

  19. High spatial resolution CT image reconstruction using parallel computing

    International Nuclear Information System (INIS)

    Yin Yin; Liu Li; Sun Gongxing

    2003-01-01

    Using the PC cluster system with 16 dual CPU nodes, we accelerate the FBP and OR-OSEM reconstruction of high spatial resolution image (2048 x 2048). Based on the number of projections, we rewrite the reconstruction algorithms into parallel format and dispatch the tasks to each CPU. By parallel computing, the speedup factor is roughly equal to the number of CPUs, which can be up to about 25 times when 25 CPUs used. This technique is very suitable for real-time high spatial resolution CT image reconstruction. (authors)

  20. Studies on the drift properties and spatial resolution using a ...

    Indian Academy of Sciences (India)

    Spatial resolution is studied using right angle tracks, φ = 0 relative to the pad. The resolution is deduced from the geometric mean [5] of the sigma of the residuals of x-coordinate of the track of the middle two rows having 2.3 mm pad pitch and. 6.3 mm pad row pitch. The standard deviation from Gaussian fit of the residual.

  1. Use of UAS Remote Sensing Data (AggieAir) to Estimate Crop ET at High Spatial Resolution

    Science.gov (United States)

    ELarab, M.; Torres, A.; Nieto Solana, H.; Kustas, W. P.; Song, L.; Alfieri, J. G.; Prueger, J. H.; McKee, L.; Anderson, M. C.; Jensen, A.; McKee, M.; Alsina, M. M.

    2015-12-01

    Estimation of the spatial distribution of evapotranspiration (ET) based on remotely sensed imagery has become useful for managing water in irrigated agricultural at various spatial scales. Currently, data acquired by conventional satellites (Landsat, ASTER, etc.) lack the needed spatial resolution to capture variability of interest to support evapotranspiration estimates. In this study, an unmanned aerial system (UAS), called AggieAirTM, was used to acquire high-resolution imagery in the visual, near infrared (0.15m resolution) and thermal infrared spectra (0.6m resolution). AggieAir flew over two study sites in Utah and Central Valley of California. The imagery was used as input to a surface energy balance model based on the Mapping Evapotranspiration with Internalized Calibration (METRIC) modeling approach. The discussion will highlight the ET estimation methodologies and the implications of having high resolution ET maps.

  2. Spatial resolution influence on the identification of land cover classes in the Amazon environment

    Directory of Open Access Journals (Sweden)

    PONZONI FLÁVIO J.

    2002-01-01

    Full Text Available To evaluate the role played by the spatial resolution in distinguishing land cover classes in the Amazon region, different levels of spatial resolution (60, 100, 120, 200 and 250 meters were simulated from a Landsat_5 Thematic Mapper (TM image. Thematic maps were produced by visual interpretation from the original (30 x 30 meters and simulated set of images. The map legend included primary forest, old and young woody secondary succession, and non-forest. The results indicated that for the discrimination between primary forest and non-forest, spatial resolution did not have great influence for pixel size equal or lower than 200 meters. The contrary was verified for the identification of old and young woody secondary vegetation due to their occurrence in small polygons. To avoid significant changes in the calculated area of these land cover types, a spatial resolution better than 100 meters is required. This result is an indication that the use of the future Brazilian remote sensing satellite (SSR-1 for secondary succession identification may be unreliable, especially for latitudes between S10degrees and S15degrees where critical areas of deforestation are located and pixel size is expected to vary within the same scene from 100 meters (S10degrees to 200 meters (S15degrees.

  3. Comparison of different "along the track" high resolution satellite stereo-pair for DSM extraction

    Science.gov (United States)

    Nikolakopoulos, Konstantinos G.

    2013-10-01

    The possibility to create DEM from stereo pairs is based on the Pythagoras theorem and on the principles of photogrammetry that are applied to aerial photographs stereo pairs for the last seventy years. The application of these principles to digital satellite stereo data was inherent in the first satellite missions. During the last decades the satellite stereo-pairs were acquired across the track in different days (SPOT, ERS etc.). More recently the same-date along the track stereo-data acquisition seems to prevail (Terra ASTER, SPOT5 HRS, Cartosat, ALOS Prism) as it reduces the radiometric image variations (refractive effects, sun illumination, temporal changes) and thus increases the correlation success rate in any image matching.Two of the newest satellite sensors with stereo collection capability is Cartosat and ALOS Prism. Both of them acquire stereopairs along the track with a 2,5m spatial resolution covering areas of 30X30km. In this study we compare two different satellite stereo-pair collected along the track for DSM creation. The first one is created from a Cartosat stereopair and the second one from an ALOS PRISM triplet. The area of study is situated in Chalkidiki Peninsula, Greece. Both DEMs were created using the same ground control points collected with a Differential GPS. After a first control for random or systematic errors a statistical analysis was done. Points of certified elevation have been used to estimate the accuracy of these two DSMs. The elevation difference between the different DEMs was calculated. 2D RMSE, correlation and the percentile value were also computed and the results are presented.

  4. Modeling Surface Energy Fluxes over a Dehesa (Oak Savanna Ecosystem Using a Thermal Based Two Source Energy Balance Model (TSEB II—Integration of Remote Sensing Medium and Low Spatial Resolution Satellite Images

    Directory of Open Access Journals (Sweden)

    Ana Andreu

    2018-04-01

    Full Text Available Dehesas are highly valuable agro-forestry ecosystems, widely distributed over Mediterranean-type climate areas, which play a key role in rural development, basing their productivity on a sustainable use of multiple resources (crops, livestock, wildlife, etc.. The information derived from remote sensing based models addressing ecosystem water consumption, at different scales, can be used by institutions and private landowners to support management decisions. In this study, the Two-Source Energy Balance (TSEB model is analyzed over two Spanish dehesa areas integrating multiple satellites (MODIS and Landsat for estimating water use (ET, vegetation ground cover, leaf area and phenology. Instantaneous latent heat (LE values are derived on a regional scale and compared with eddy covariance tower (ECT measurements, yielding accurate results (RMSDMODIS Las Majadas 44 Wm−2, Santa Clotilde RMSDMODIS 47 Wm−2 and RMSDLandsat 64 Wm−2. Daily ET(mm is estimated using daily return interval of MODIS for both study sites and compared with the flux measurements of the ECTs, with RMSD of 1 mm day−1 over Las Majadas and 0.99 mm day−1 over Santa Clotilde. Distributed ET over Andalusian dehesa (15% of the region is successfully mapped using MODIS images, as an approach to monitor the ecosystem status and the vegetation water stress on a regular basis.

  5. The Impact of Spatial and Temporal Resolutions in Tropical Summer Rainfall Distribution: Preliminary Results

    Science.gov (United States)

    Liu, Q.; Chiu, L. S.; Hao, X.

    2017-10-01

    The abundance or lack of rainfall affects peoples' life and activities. As a major component of the global hydrological cycle (Chokngamwong & Chiu, 2007), accurate representations at various spatial and temporal scales are crucial for a lot of decision making processes. Climate models show a warmer and wetter climate due to increases of Greenhouse Gases (GHG). However, the models' resolutions are often too coarse to be directly applicable to local scales that are useful for mitigation purposes. Hence disaggregation (downscaling) procedures are needed to transfer the coarse scale products to higher spatial and temporal resolutions. The aim of this paper is to examine the changes in the statistical parameters of rainfall at various spatial and temporal resolutions. The TRMM Multi-satellite Precipitation Analysis (TMPA) at 0.25 degree, 3 hourly grid rainfall data for a summer is aggregated to 0.5,1.0, 2.0 and 2.5 degree and at 6, 12, 24 hourly, pentad (five days) and monthly resolutions. The probability distributions (PDF) and cumulative distribution functions(CDF) of rain amount at these resolutions are computed and modeled as a mixed distribution. Parameters of the PDFs are compared using the Kolmogrov-Smironov (KS) test, both for the mixed and the marginal distribution. These distributions are shown to be distinct. The marginal distributions are fitted with Lognormal and Gamma distributions and it is found that the Gamma distributions fit much better than the Lognormal.

  6. Selecting Appropriate Spatial Scale for Mapping Plastic-Mulched Farmland with Satellite Remote Sensing Imagery

    Directory of Open Access Journals (Sweden)

    Hasituya

    2017-03-01

    Full Text Available In recent years, the area of plastic-mulched farmland (PMF has undergone rapid growth and raised remarkable environmental problems. Therefore, mapping the PMF plays a crucial role in agricultural production, environmental protection and resource management. However, appropriate data selection criteria are currently lacking. Thus, this study was carried out in two main plastic-mulching practice regions, Jizhou and Guyuan, to look for an appropriate spatial scale for mapping PMF with remote sensing. The average local variance (ALV function was used to obtain the appropriate spatial scale for mapping PMF based on the GaoFen-1 (GF-1 satellite imagery. Afterwards, in order to validate the effectiveness of the selected method and to interpret the relationship between the appropriate spatial scale derived from the ALV and the spatial scale with the highest classification accuracy, we classified the imagery with varying spatial resolution by the Support Vector Machine (SVM algorithm using the spectral features, textural features and the combined spectral and textural features respectively. The results indicated that the appropriate spatial scales from the ALV lie between 8 m and 20 m for mapping the PMF both in Jizhou and Guyuan. However, there is a proportional relation: the spatial scale with the highest classification accuracy is at the 1/2 location of the appropriate spatial scale generated from the ALV in Jizhou and at the 2/3 location of the appropriate spatial scale generated from the ALV in Guyuan. Therefore, the ALV method for quantitatively selecting the appropriate spatial scale for mapping PMF with remote sensing imagery has theoretical and practical significance.

  7. Biomass estimation with high resolution satellite images: A case study of Quercus rotundifolia

    Science.gov (United States)

    Sousa, Adélia M. O.; Gonçalves, Ana Cristina; Mesquita, Paulo; Marques da Silva, José R.

    2015-03-01

    Forest biomass has had a growing importance in the world economy as a global strategic reserve, due to applications in bioenergy, bioproduct development and issues related to reducing greenhouse gas emissions. Current techniques used for forest inventory are usually time consuming and expensive. Thus, there is an urgent need to develop reliable, low cost methods that can be used for forest biomass estimation and monitoring. This study uses new techniques to process high spatial resolution satellite images (0.70 m) in order to assess and monitor forest biomass. Multi-resolution segmentation method and object oriented classification are used to obtain the area of tree canopy horizontal projection for Quercus rotundifolia. Forest inventory allows for calculation of tree and canopy horizontal projection and biomass, the latter with allometric functions. The two data sets are used to develop linear functions to assess above ground biomass, with crown horizontal projection as an independent variable. The functions for the cumulative values, both for inventory and satellite data, for a prediction error equal or smaller than the Portuguese national forest inventory (7%), correspond to stand areas of 0.5 ha, which include most of the Q.rotundifolia stands.

  8. Accessing High Spatial Resolution in Astronomy Using Interference Methods

    Science.gov (United States)

    Carbonel, Cyril; Grasset, Sébastien; Maysonnave, Jean

    2018-01-01

    In astronomy, methods such as direct imaging or interferometry-based techniques (Michelson stellar interferometry for example) are used for observations. A particular advantage of interferometry is that it permits greater spatial resolution compared to direct imaging with a single telescope, which is limited by diffraction owing to the aperture of…

  9. Passive Standoff Super Resolution Imaging using Spatial-Spectral Multiplexing

    Science.gov (United States)

    2017-08-14

    emission wavelength. Fig. 69. Measured results. (a) Channeled spectra . The spectra are illustrated from highest to lowest spatial frequency from top...1967).Photon Technologies International, “PTI Technical Notes: Lamp Emission Spectra ,” http://www.pti-nj.com/TechnicalNotes/Lamp- Emission -Spectra.pdf...Nonlinear Channeled Spectra ..................................................................... 29 2.4 Angular Resolution Analysis

  10. Spatial Resolution of a Wedge Shaped MSGC Module

    CERN Document Server

    Bachmann, Sebastian

    1997-01-01

    A banana shaped closed design MSGC detector module was tested together with silicon detectors and other MSGCs in a 100 GeV muon beam. Despite of an undesirable geometry of the test setup, a spatial resolution below 40 micron m was reached. The efficiency of the module, defined by track reconstruction, shows to be 95,6 percent

  11. Linear and nonlinear optical spectroscopy: Spectral, temporal and spatial resolution

    DEFF Research Database (Denmark)

    Hvam, Jørn Marcher

    1997-01-01

    Selected linear and nonlinear optical spectroscopies are being described with special emphasis on the possibility of obtaining simultaneous spectral, temporal and spatial resolution. The potential of various experimental techniques is being demonstrated by specific examples mostly taken from inve...... investigations of the electronic, and opto-electronic, properties of semiconductor nanostructures....

  12. Generating high-temporal and spatial resolution tir image data

    NARCIS (Netherlands)

    Herrero Huerta, M.; Lagüela, S.; Alfieri, S.M.; Menenti, M.; Lichti, D.; Weng, Q

    2017-01-01

    Remote sensing imagery to monitor global biophysical dynamics requires the availability of thermal infrared data at high temporal and spatial resolution because of the rapid development of crops during the growing season and the fragmentation of most agricultural landscapes. Conversely, no single

  13. Stars and planets at high spatial and spectral resolution

    NARCIS (Netherlands)

    Albrecht, Simon

    2008-01-01

    The work presented in this thesis involves the development of new instrumental techniques and analysing tools, combining high spectral resolution with high spatial information, with the aim to increase our understanding of the formation and evolution of stars and planets. First, a novel instrumental

  14. Automatic Near-Real-Time Image Processing Chain for Very High Resolution Optical Satellite Data

    Science.gov (United States)

    Ostir, K.; Cotar, K.; Marsetic, A.; Pehani, P.; Perse, M.; Zaksek, K.; Zaletelj, J.; Rodic, T.

    2015-04-01

    In response to the increasing need for automatic and fast satellite image processing SPACE-SI has developed and implemented a fully automatic image processing chain STORM that performs all processing steps from sensor-corrected optical images (level 1) to web-delivered map-ready images and products without operator's intervention. Initial development was tailored to high resolution RapidEye images, and all crucial and most challenging parts of the planned full processing chain were developed: module for automatic image orthorectification based on a physical sensor model and supported by the algorithm for automatic detection of ground control points (GCPs); atmospheric correction module, topographic corrections module that combines physical approach with Minnaert method and utilizing anisotropic illumination model; and modules for high level products generation. Various parts of the chain were implemented also for WorldView-2, THEOS, Pleiades, SPOT 6, Landsat 5-8, and PROBA-V. Support of full-frame sensor currently in development by SPACE-SI is in plan. The proposed paper focuses on the adaptation of the STORM processing chain to very high resolution multispectral images. The development concentrated on the sub-module for automatic detection of GCPs. The initially implemented two-step algorithm that worked only with rasterized vector roads and delivered GCPs with sub-pixel accuracy for the RapidEye images, was improved with the introduction of a third step: super-fine positioning of each GCP based on a reference raster chip. The added step exploits the high spatial resolution of the reference raster to improve the final matching results and to achieve pixel accuracy also on very high resolution optical satellite data.

  15. High spatial resolution diffusion tensor imaging and its applications

    CERN Document Server

    Wang, J J

    2002-01-01

    Introduction Magnetic Resonance Imaging is at present the only imaging technique available to measure diffusion of water and metabolites in humans. It provides vital insights to brain connectivity and has proved to be an important tool in diagnosis and therapy planning in many neurological diseases such as brain tumour, ischaemia and multiple sclerosis. This project focuses on the development of a high resolution diffusion tensor imaging technique. In this thesis, the basic theory of diffusion tensor MR Imaging is presented. The technical challenges encountered during development of these techniques will be discussed, with proposed solutions. New sequences with high spatial resolution have been developed and the results are compared with the standard technique more commonly used. Overview The project aims at the development of diffusion tensor imaging techniques with a high spatial resolution. Chapter 2 will describe the basic physics of MRI, the phenomenon of diffusion and the measurement of diffusion by MRI...

  16. Spatiotemporal estimation of air temperature patterns at the street level using high resolution satellite imagery.

    Science.gov (United States)

    Pelta, Ran; Chudnovsky, Alexandra A

    2017-02-01

    Although meteorological monitoring stations provide accurate measurements of Air Temperature (AT), their spatial coverage within a given region is limited and thus is often insufficient for exposure and epidemiological studies. In many applications, satellite imagery measures energy flux, which is spatially continuous, and calculates Brightness Temperature (BT) that used as an input parameter. Although both quantities (AT-BT) are physically related, the correlation between them is not straightforward, and varies daily due to parameters such as meteorological conditions, surface moisture, land use, satellite-surface geometry and others. In this paper we first investigate the relationship between AT and BT as measured by 39 meteorological stations in Israel during 1984-2015. Thereafter, we apply mixed regression models with daily random slopes to calibrate Landsat BT data with monitored AT measurements for the period 1984-2015. Results show that AT can be predicted with high accuracy by using BT with high spatial resolution. The model shows relatively high accuracy estimation of AT (R 2 =0.92, RMSE=1.58°C, slope=0.90). Incorporating meteorological parameters into the model generates better accuracy (R 2 =0.935) than the AT-BT model (R 2 =0.92). Furthermore, based on the relatively high model accuracy, we investigated the spatial patterns of AT within the study domain. In the latter we focused on July-August, as these two months are characterized by relativity stable synoptic conditions in the study area. In addition, a temporal change in AT during the last 30years was estimated and verified using available meteorological stations and two additional remote sensing platforms. Finally, the impact of different land coverage on AT were estimated, as an example of future application of the presented approach. Copyright © 2016 Elsevier B.V. All rights reserved.

  17. Remote Measurements of the Atmosphere with High Spatial Resolution

    Science.gov (United States)

    Weinman, J. A.; Marzano, F. S.; Mugnai, A.

    2009-09-01

    Global atmosphere-ocean models are now operating at 3.5 km resolution and mesoscale weather prediction models operating at 1.7 km resolution have been used for the analysis of hurricanes. One can expect that weather prediction models will operate at resolutions better than 5 km during the coming decade. Microwave sensors have contributed valuable information about rainfall and sea surface winds. The Precipitation Radar (PR) onboard the Tropical Rainfall Measuring Mission (TRMM) can address this need. However it may be nearing the end of its life, and its replacement by the Global Precipitation Measurement (GPM) mission is expected no earlier than 2013. Recently the four Italian Cosmo-SkyMed, and the German Terra-SAR X-band synthetic aperture radars (SAR’s) have displayed rain distributions with resolution better than 0.5 km. The Quickscat also now provides distributions of rainfall and sea surface winds with 2.5 km resolution. We will describe rainfall retrieval algorithms, show rainfall distributions retrieved from Terra-SAR, and discuss errors in those measurements. We will also describe multi-frequency radar measurements of sea surface winds and rainfall during hurricanes. Although most remotely sensed rainfall and wind data can be expected to be obtained from satellites, unmanned aerial vehicles (UAV’s) with one week cruising duration and ~180 kg payloads flying at 18 km height may become attractive platforms from which severe weather can be tracked with high resolution.

  18. Evolution of spatial resolution in breast CT at UC Davis

    Energy Technology Data Exchange (ETDEWEB)

    Gazi, Peymon M. [Department of Biomedical Engineering, University of California, Davis, One Shields Avenue, Davis, California 95616 (United States); Yang, Kai [Department of Radiological Sciences, University of Oklahoma Health Sciences Center, 940 N.E. 13th Street, Nicholson Tower, Oklahoma City, Oklahoma 73104 (United States); Burkett, George W.; Aminololama-Shakeri, Shadi [Department of Radiology, University of California, Davis Medical Center, 4860 Y Street, Suite 3100 Ellison Building, Sacramento, California 95817 (United States); Anthony Seibert, J.; Boone, John M., E-mail: john.boone@ucdmc.ucdavis.edu [Department of Biomedical Engineering, University of California, Davis, One Shields Avenue, Davis, California 95616 and Department of Radiology, University of California, Davis Medical Center, 4860 Y Street, Suite 3100 Ellison Building, Sacramento, California 95817 (United States)

    2015-04-15

    Purpose: Dedicated breast computed tomography (bCT) technology for the purpose of breast cancer screening has been a focus of research at UC Davis since the late 1990s. Previous studies have shown that improvement in spatial resolution characteristics of this modality correlates with greater microcalcification detection, a factor considered a potential limitation of bCT. The aim of this study is to improve spatial resolution as characterized by the modulation transfer function (MTF) via changes in the scanner hardware components and operational schema. Methods: Four prototypes of pendant-geometry, cone-beam breast CT scanners were designed and developed spanning three generations of design evolution. To improve the system MTF in each bCT generation, modifications were made to the imaging components (x-ray tube and flat-panel detector), system geometry (source-to-isocenter and detector distance), and image acquisition parameters (technique factors, number of projections, system synchronization scheme, and gantry rotational speed). Results: Characterization of different generations of bCT systems shows these modifications resulted in a 188% improvement of the limiting MTF properties from the first to second generation and an additional 110% from the second to third. The intrinsic resolution degradation in the azimuthal direction observed in the first generation was corrected by changing the acquisition from continuous to pulsed x-ray acquisition. Utilizing a high resolution detector in the third generation, along with modifications made in system geometry and scan protocol, resulted in a 125% improvement in limiting resolution. An additional 39% improvement was obtained by changing the detector binning mode from 2 × 2 to 1 × 1. Conclusions: These results underscore the advancement in spatial resolution characteristics of breast CT technology. The combined use of a pulsed x-ray system, higher resolution flat-panel detector and changing the scanner geometry and image

  19. Roads Data Conflation Using Update High Resolution Satellite Images

    Science.gov (United States)

    Abdollahi, A.; Riyahi Bakhtiari, H. R.

    2017-11-01

    Urbanization, industrialization and modernization are rapidly growing in developing countries. New industrial cities, with all the problems brought on by rapid population growth, need infrastructure to support the growth. This has led to the expansion and development of the road network. A great deal of road network data has made by using traditional methods in the past years. Over time, a large amount of descriptive information has assigned to these map data, but their geometric accuracy and precision is not appropriate to today's need. In this regard, the improvement of the geometric accuracy of road network data by preserving the descriptive data attributed to them and updating of the existing geo databases is necessary. Due to the size and extent of the country, updating the road network maps using traditional methods is time consuming and costly. Conversely, using remote sensing technology and geographic information systems can reduce costs, save time and increase accuracy and speed. With increasing the availability of high resolution satellite imagery and geospatial datasets there is an urgent need to combine geographic information from overlapping sources to retain accurate data, minimize redundancy, and reconcile data conflicts. In this research, an innovative method for a vector-to-imagery conflation by integrating several image-based and vector-based algorithms presented. The SVM method for image classification and Level Set method used to extract the road the different types of road intersections extracted from imagery using morphological operators. For matching the extracted points and to find the corresponding points, matching function which uses the nearest neighborhood method was applied. Finally, after identifying the matching points rubber-sheeting method used to align two datasets. Two residual and RMSE criteria used to evaluate accuracy. The results demonstrated excellent performance. The average root-mean-square error decreased from 11.8 to 4.1 m.

  20. High resolution satellite image indexing and retrieval using SURF features and bag of visual words

    Science.gov (United States)

    Bouteldja, Samia; Kourgli, Assia

    2017-03-01

    In this paper, we evaluate the performance of SURF descriptor for high resolution satellite imagery (HRSI) retrieval through a BoVW model on a land-use/land-cover (LULC) dataset. Local feature approaches such as SIFT and SURF descriptors can deal with a large variation of scale, rotation and illumination of the images, providing, therefore, a better discriminative power and retrieval efficiency than global features, especially for HRSI which contain a great range of objects and spatial patterns. Moreover, we combine SURF and color features to improve the retrieval accuracy, and we propose to learn a category-specific dictionary for each image category which results in a more discriminative image representation and boosts the image retrieval performance.

  1. Satellite-based high-resolution mapping of rainfall over southern Africa

    Science.gov (United States)

    Meyer, Hanna; Drönner, Johannes; Nauss, Thomas

    2017-06-01

    A spatially explicit mapping of rainfall is necessary for southern Africa for eco-climatological studies or nowcasting but accurate estimates are still a challenging task. This study presents a method to estimate hourly rainfall based on data from the Meteosat Second Generation (MSG) Spinning Enhanced Visible and Infrared Imager (SEVIRI). Rainfall measurements from about 350 weather stations from 2010-2014 served as ground truth for calibration and validation. SEVIRI and weather station data were used to train neural networks that allowed the estimation of rainfall area and rainfall quantities over all times of the day. The results revealed that 60 % of recorded rainfall events were correctly classified by the model (probability of detection, POD). However, the false alarm ratio (FAR) was high (0.80), leading to a Heidke skill score (HSS) of 0.18. Estimated hourly rainfall quantities were estimated with an average hourly correlation of ρ = 0. 33 and a root mean square error (RMSE) of 0.72. The correlation increased with temporal aggregation to 0.52 (daily), 0.67 (weekly) and 0.71 (monthly). The main weakness was the overestimation of rainfall events. The model results were compared to the Integrated Multi-satellitE Retrievals for GPM (IMERG) of the Global Precipitation Measurement (GPM) mission. Despite being a comparably simple approach, the presented MSG-based rainfall retrieval outperformed GPM IMERG in terms of rainfall area detection: GPM IMERG had a considerably lower POD. The HSS was not significantly different compared to the MSG-based retrieval due to a lower FAR of GPM IMERG. There were no further significant differences between the MSG-based retrieval and GPM IMERG in terms of correlation with the observed rainfall quantities. The MSG-based retrieval, however, provides rainfall in a higher spatial resolution. Though estimating rainfall from satellite data remains challenging, especially at high temporal resolutions, this study showed promising results

  2. Evaluation of High-Resolution Satellite Rainfall Estimates in Blue Nile River Basin, Ethiopia: A Hydrological Perspective

    Science.gov (United States)

    Bitew, Menberu Meles

    Accurate measurement of rainfall has paramount importance for the water-based economy of Ethiopia. However, the ground based rainfall measurement is limited to sparsely distributed rain gauges primarily located across the densely populated regions of the county. Due to their poor coverage these gauges hardly capture the spatially variable and topographically controlled rainfall of the region. The past two decades have opened a new chapter of global data acquisition from space using wide ranges of satellites including geostationary and polar orbiting satellites. The satellite-based rainfall estimate provides an opportunity to fill in the huge data voids of complex terrain regions in Ethiopia with less/no ground based measurements such as the Blue Nile River Basin. The satellite rainfall itself, on the other hand, is affected by uncertainties mainly resulting from large satellite sampling periods, indirect rainfall sensors and retrieval algorithms. The objective of this study is to evaluate accuracy of four widely used high-resolution satellite rainfall estimates for hydrological applications in the Blue Nile River Basin. These satellite rainfall estimates are available at high spatial (The evaluations were conducted in two-pronged approaches. In the first approach, the evaluation was conducted through comparison of the satellite rainfall estimates with independent measurement. The independent observations were obtained through deployment of dense rain gauges in Ethiopia highland within scales equivalent to satellite rainfall pixels and using existing historical measurements obtained from sparse rain gauges in the proximity of our study watersheds. In the second approach, observed streamflow was used as a way of evaluating accuracy of satellite rainfall estimates in several watersheds through multiple hydrological modeling frameworks. This approach was also used to evaluate the propagation of satellite rainfall errors to simulated streamflow as a function of

  3. Improving PET spatial resolution and detectability for prostate cancer imaging

    Science.gov (United States)

    Bal, H.; Guerin, L.; Casey, M. E.; Conti, M.; Eriksson, L.; Michel, C.; Fanti, S.; Pettinato, C.; Adler, S.; Choyke, P.

    2014-08-01

    Prostate cancer, one of the most common forms of cancer among men, can benefit from recent improvements in positron emission tomography (PET) technology. In particular, better spatial resolution, lower noise and higher detectability of small lesions could be greatly beneficial for early diagnosis and could provide a strong support for guiding biopsy and surgery. In this article, the impact of improved PET instrumentation with superior spatial resolution and high sensitivity are discussed, together with the latest development in PET technology: resolution recovery and time-of-flight reconstruction. Using simulated cancer lesions, inserted in clinical PET images obtained with conventional protocols, we show that visual identification of the lesions and detectability via numerical observers can already be improved using state of the art PET reconstruction methods. This was achieved using both resolution recovery and time-of-flight reconstruction, and a high resolution image with 2 mm pixel size. Channelized Hotelling numerical observers showed an increase in the area under the LROC curve from 0.52 to 0.58. In addition, a relationship between the simulated input activity and the area under the LROC curve showed that the minimum detectable activity was reduced by more than 23%.

  4. Improving PET spatial resolution and detectability for prostate cancer imaging

    International Nuclear Information System (INIS)

    Bal, H; Guerin, L; Casey, M E; Conti, M; Eriksson, L; Michel, C; Fanti, S; Pettinato, C; Adler, S; Choyke, P

    2014-01-01

    Prostate cancer, one of the most common forms of cancer among men, can benefit from recent improvements in positron emission tomography (PET) technology. In particular, better spatial resolution, lower noise and higher detectability of small lesions could be greatly beneficial for early diagnosis and could provide a strong support for guiding biopsy and surgery. In this article, the impact of improved PET instrumentation with superior spatial resolution and high sensitivity are discussed, together with the latest development in PET technology: resolution recovery and time-of-flight reconstruction. Using simulated cancer lesions, inserted in clinical PET images obtained with conventional protocols, we show that visual identification of the lesions and detectability via numerical observers can already be improved using state of the art PET reconstruction methods. This was achieved using both resolution recovery and time-of-flight reconstruction, and a high resolution image with 2 mm pixel size. Channelized Hotelling numerical observers showed an increase in the area under the LROC curve from 0.52 to 0.58. In addition, a relationship between the simulated input activity and the area under the LROC curve showed that the minimum detectable activity was reduced by more than 23%. (paper)

  5. Exposure Estimation from Multi-Resolution Optical Satellite Imagery for Seismic Risk Assessment

    Directory of Open Access Journals (Sweden)

    Jochen Zschau

    2012-05-01

    Full Text Available Given high urbanization rates and increasing spatio-temporal variability in many present-day cities, exposure information is often out-of-date, highly aggregated or spatially fragmented, increasing the uncertainties associated with seismic risk assessments. This work therefore aims at using space-based technologies to estimate, complement and extend exposure data at multiple scales, over large areas and at a comparatively low cost for the case of the city of Bishkek, Kyrgyzstan. At a neighborhood scale, an analysis of urban structures using medium-resolution optical satellite images is performed. Applying image classification and change-detection analysis to a time-series of Landsat images, the urban environment can be delineated into areas of relatively homogeneous urban structure types, which can provide a first estimate of an exposed building stock (e.g., approximate age of structures, composition and distribution of predominant building types. At a building-by-building scale, a more detailed analysis of the exposed building stock is carried out using a high-resolution Quickbird image. Furthermore, the multi-resolution datasets are combined with census data to disaggregate population statistics. The tools used within this study are being developed on a free- and open-source basis and aim at being transparent, usable and transferable.

  6. Demarcation of Prime Farmland Protection Areas around a Metropolis Based on High-Resolution Satellite Imagery.

    Science.gov (United States)

    Xia, Nan; Wang, YaJun; Xu, Hao; Sun, YueFan; Yuan, Yi; Cheng, Liang; Jiang, PengHui; Li, ManChun

    2016-12-21

    Prime farmland (PF) is defined as high-quality farmland and a prime farmland protection area (PFPA, including related roads, waters and facilities) is a region designated for the special protection of PF. However, rapid urbanization in China has led to a tremendous farmland loss and to the degradation of farmland quality. Based on remote sensing and geographic information system technology, this study developed a semiautomatic procedure for designating PFPAs using high-resolution satellite imagery (HRSI), which involved object-based image analysis, farmland composite evaluation, and spatial analysis. It was found that the HRSIs can provide elaborate land-use information, and the PFPA demarcation showed strong correlation with the farmland area and patch distance. For the benefit of spatial planning and management, different demarcation rules should be applied for suburban and exurban areas around a metropolis. Finally, the overall accuracy of HRSI classification was about 80% for the study area, and high-quality farmlands from evaluation results were selected as PFs. About 95% of the PFs were demarcated within the PFPAs. The results of this study will be useful for PFPA planning and the methods outlined could help in the automatic designation of PFPAs from the perspective of the spatial science.

  7. High spatial resolution Kelvin probe force microscopy with coaxial probes

    International Nuclear Information System (INIS)

    Brown, Keith A; Westervelt, Robert M; Satzinger, Kevin J

    2012-01-01

    Kelvin probe force microscopy (KPFM) is a widely used technique to measure the local contact potential difference (CPD) between an AFM probe and the sample surface via the electrostatic force. The spatial resolution of KPFM is intrinsically limited by the long range of the electrostatic interaction, which includes contributions from the macroscopic cantilever and the conical tip. Here, we present coaxial AFM probes in which the cantilever and cone are shielded by a conducting shell, confining the tip–sample electrostatic interaction to a small region near the end of the tip. We have developed a technique to measure the true CPD despite the presence of the shell electrode. We find that the behavior of these probes agrees with an electrostatic model of the force, and we observe a factor of five improvement in spatial resolution relative to unshielded probes. Our discussion centers on KPFM, but the field confinement offered by these probes may improve any variant of electrostatic force microscopy. (paper)

  8. Incoherent improvement of the spatial resolution in digital holography

    International Nuclear Information System (INIS)

    Garcia-Sucerquia, J.; Herrera-Ramirez, J.; Castaneda, R.

    2005-10-01

    We report on a technique for increasing the spatial resolution of digitally recorded and reconstructed holograms of macroscopic objects, via the reduction of the contrast of the speckle noise present in the coherent imaging techniques. The contrast of the speckle noise is reduced through the superposition on an intensity basis of digitally reconstructed holograms of the same static scene. The reconstruction of a very poor contrasted object illustrates the performance of the technique. (author)

  9. Spatial resolution of wedge shaped silicon microstrip detectors

    Science.gov (United States)

    Antičić, T.; Barnett, B.; Blumenfeld, B.; Chien, C.-Y.; Fisher, P.; Gougas, A.; Krizmanic, J.; Madansky, L.; Newman, D.; Orndorff, J.; Pevsner, A.; Spangler, J.

    1995-02-01

    Several wedge-shaped silicon microstrip detectors with pitches from 30 to 100 μm have been designed by our group and beam tested at the CERN SPS. We find the spatial resolution σ becomes larger at the rate of 0.21 μm per 1 μm increase in pitch, but the number of strips per cluster remains about the same as the pitch varies from 30 to 100 μm.

  10. Spatial resolution of wedge shaped silicon microstrip detectors

    International Nuclear Information System (INIS)

    Anticic, T.; Barnett, B.; Blumenfeld, B.; Chien, C.Y.; Fisher, P.; Gougas, A.; Krizmanic, J.; Madansky, L.; Newman, D.; Orndorff, J.; Pevsner, A.; Spangler, J.

    1995-01-01

    Several wedge-shaped silicon microstrip detectors with pitches from 30 to 100 μm have been designed by our group and beam tested at the CERN SPS. We find the spatial resolution σ becomes larger at the rate of 0.21 μm per 1 μm increase in pitch, but the number of strips per cluster remains about the same as the pitch varies from 30 to 100 μm. (orig.)

  11. Elevated-temperature luminescence measurements to improve spatial resolution

    Science.gov (United States)

    Pluska, Mariusz; Czerwinski, Andrzej

    2018-01-01

    Various branches of applied physics use luminescence based methods to investigate light-emitting specimens with high spatial resolution. A key problem is that luminescence signals lack all the advantages of high locality (i.e. of high spatial resolution) when structures with strong built-in electric field are measured. Such fields exist intentionally in most photonic structures, and occur unintentionally in many other materials. In this case, as a result of beam-induced current generation and its outflow, information that indicates irregularities, nonuniformities and inhomogeneities, such as defects, is lost. We show that to avoid nonlocality and enable truly local luminescence measurements, an elevated measurement temperature as high as 350 K (or even higher) is, perhaps surprisingly, advantageous. This is in contrast to a widely used approach, where cryogenic temperatures, or at least room temperature, are recommended. The elevated temperature of a specimen, together with the current outflow being limited by focused ion beam (FIB) milling, is shown to improve the spatial resolution of luminescence measurements greatly. All conclusions drawn using the example of cathodoluminescence are useful for other luminescence techniques.

  12. A Verification of Optical Depth Retrievals From High Resolution Satellite Imagery

    National Research Council Canada - National Science Library

    Evans, Jack R

    2007-01-01

    A new technique has been developed using high resolution satellite imagery to derive aerosol optical depths by measuring the difference of the radiances inside and outside of shaded regions Vincent (2006...

  13. Science with High Spatial Resolution Far-Infrared Data

    Science.gov (United States)

    Terebey, Susan (Editor); Mazzarella, Joseph M. (Editor)

    1994-01-01

    The goal of this workshop was to discuss new science and techniques relevant to high spatial resolution processing of far-infrared data, with particular focus on high resolution processing of IRAS data. Users of the maximum correlation method, maximum entropy, and other resolution enhancement algorithms applicable to far-infrared data gathered at the Infrared Processing and Analysis Center (IPAC) for two days in June 1993 to compare techniques and discuss new results. During a special session on the third day, interested astronomers were introduced to IRAS HIRES processing, which is IPAC's implementation of the maximum correlation method to the IRAS data. Topics discussed during the workshop included: (1) image reconstruction; (2) random noise; (3) imagery; (4) interacting galaxies; (5) spiral galaxies; (6) galactic dust and elliptical galaxies; (7) star formation in Seyfert galaxies; (8) wavelet analysis; and (9) supernova remnants.

  14. An Object-Oriented Classification Method on High Resolution Satellite Data

    National Research Council Canada - National Science Library

    Xiaoxia, Sun; Jixian, Zhang; Zhengjun, Liu

    2004-01-01

    .... Thereby only the spectral information is used for the classification. High spatial resolution sensors involves a general increase of spatial information and the accuracy of results may decrease on a per-pixel basis...

  15. EBSD spatial resolution for detecting sigma phase in steels

    Energy Technology Data Exchange (ETDEWEB)

    Bordín, S. Fernandez; Limandri, S. [Instituto de Física Enrique Gaviola, CONICET. M. Allende s/n, Ciudad Universitaria, 5000 Córdoba (Argentina); Ranalli, J.M. [Comisión Nacional de Energía Atómica, Av. Gral. Paz 1499, San Martín, 1650 Buenos Aires (Argentina); Castellano, G. [Instituto de Física Enrique Gaviola, CONICET. M. Allende s/n, Ciudad Universitaria, 5000 Córdoba (Argentina)

    2016-12-15

    The spatial resolution of the electron backscatter diffraction signal is explored by Monte Carlo simulation for the sigma phase in steel at a typical instrumental set-up. In order to estimate the active volume corresponding to the diffracted electrons, the fraction of the backscattered electrons contributing to the diffraction signal was inferred by extrapolating the Kikuchi pattern contrast measured by other authors, as a function of the diffracted electron energy. In the resulting estimation, the contribution of the intrinsic incident beam size and the software capability to deconvolve patterns were included. A strong influence of the beam size on the lateral resolution was observed, resulting in 20 nm for the aperture considered. For longitudinal and depth directions the resolutions obtained were 75 nm and 16 nm, respectively. The reliability of this last result is discussed in terms of the survey of the last large-angle deflection undergone by the backscattered electrons involved in the diffraction process. Bearing in mind the mean transversal resolution found, it was possible to detect small area grains of sigma phase by EBSD measurements, for a stabilized austenitic AISI 347 stainless steel under heat treatments, simulating post welding (40 h at 600 °C) and aging (284 h at 484 °C) effects—as usually occurring in nuclear reactor pressure vessels. - Highlights: • EBSD spatial resolution is studied by Monte Carlo simulation for σ-phase in steel. • The contribution of the intrinsic incident beam size was included. • A stabilized austenitic stainless steel under heat treatments was measured by EBSD. • With the transversal resolution found, small area σ-phase grains could be identified.

  16. High resolution satellite retrievals of NO2 and Aerosol Optical Depth for health impact studies on urban scales

    Science.gov (United States)

    Goldberg, D. L.; Lu, Z.; Lamsal, L. N.; Loughner, C.; Levy, R. C.; Gupta, P.; Zhang, Y.; Streets, D. G.

    2016-12-01

    Satellite measurements provide greater spatial coverage than any other observing platform. Despite this advantage, the horizontal resolution of operational products is often considered a major weakness when conducting health impact studies on urban scales. Improving the spatial resolution and accuracy of satellite data products may spur their use in the health and policy communities. This work presents a new high resolution nitrogen dioxide (NO2) dataset derived from the standard NASA Ozone Monitoring Instrument (OMI) NO2 v2.1 product. The standard product uses NO2 vertical profile shape factors from a 2.5° × 2° resolution NASA Global Model Initiative (GMI) model simulation to calculate air mass factors, a critical value used to determine tropospheric NO2 vertical columns. While GMI can provide global coverage and is extremely useful in an operational setting due to its quick runtime, the shape factors generated on a 2.5° × 2° grid are not representative of regions with large spatial heterogeneities, such as near major urban areas and large power plants. To better estimate vertical profile shape factors, we use regional air quality simulations to recalculate tropospheric air mass factors and tropospheric NO2 columns. Results show that retrievals using these new air mass factors capture the fine-scale gradients near urban areas and large point sources. We also use re-processed 10 km Aerosol Optical Depth (AOD) data from MODIS and regional model simulations to provide a first-order estimate of fine particulate matter (PM2.5) concentrations in urban areas. Although the current work focuses on urban areas in the eastern United States, the methodology developed in this work can be applied to other world regions to produce high-quality region-specific NO2 and PM2.5 satellite retrievals.

  17. Coastal and Inland Water Applications of High Resolution Optical Satellite Data from Landsat-8 and Sentinel-2

    Science.gov (United States)

    Vanhellemont, Q.

    2016-02-01

    Since the launch of Landsat-8 (L8) in 2013, a joint NASA/USGS programme, new applications of high resolution imagery for coastal and inland waters have become apparent. The optical imaging instrument on L8, the Operational Land Imager (OLI), is much improved compared to its predecessors on L5 and L7, especially with regards to SNR and digitization, and is therefore well suited for retrieving water reflectances and derived parameters such as turbidity and suspended sediment concentration. In June 2015, the European Space Agency (ESA) successfully launched a similar instrument, the MultiSpectral Imager (MSI), on board of Sentinel-2A (S2A). Imagery from both L8 and S2A are free of charge and publicly available (S2A starting at the end of 2015). Atmospheric correction schemes and processing software is under development in the EC-FP7 HIGHROC project. The spatial resolution of these instruments (10-60 m) is a great improvement over typical moderate resolution ocean colour sensors such as MODIS and MERIS (0.25 - 1 km). At higher resolution, many more lakes, rivers, ports and estuaries are spatially resolved, and can thus now be studied using satellite data, unlocking potential for mandatory monitoring e.g. under European Directives such as the Marine Strategy Framework Directive and the Water Framework Directive. We present new applications of these high resolution data, such as monitoring of offshore constructions, wind farms, sediment transport, dredging and dumping, shipping and fishing activities. The spatial variability at sub moderate resolution (0.25 - 1 km) scales can be assessed, as well as the impact of sub grid scale variability (including ships and platforms used for validation) on the moderate pixel retrieval. While the daily revisit time of the moderate resolution sensors is vastly superior to those of the high resolution satellites, at the equator respectively 16 and 10 days for L8 and S2A, the low revisit times can be partially mitigated by combining data

  18. Performance Evaluation of Three Different High Resolution Satellite Images in Semi-Automatic Urban Illegal Building Detection

    Science.gov (United States)

    Khalilimoghadama, N.; Delavar, M. R.; Hanachi, P.

    2017-09-01

    The problem of overcrowding of mega cities has been bolded in recent years. To meet the need of housing this increased population, which is of great importance in mega cities, a huge number of buildings are constructed annually. With the ever-increasing trend of building constructions, we are faced with the growing trend of building infractions and illegal buildings (IBs). Acquiring multi-temporal satellite images and using change detection techniques is one of the proper methods of IB monitoring. Using the type of satellite images with different spatial and spectral resolutions has always been an issue in efficient detection of the building changes. In this research, three bi-temporal high-resolution satellite images of IRS-P5, GeoEye-1 and QuickBird sensors acquired from the west of metropolitan area of Tehran, capital of Iran, in addition to city maps and municipality property database were used to detect the under construction buildings with improved performance and accuracy. Furthermore, determining the employed bi-temporal satellite images to provide better performance and accuracy in the case of IB detection is the other purpose of this research. The Kappa coefficients of 70 %, 64 %, and 68 % were obtained for producing change image maps using GeoEye-1, IRS-P5, and QuickBird satellite images, respectively. In addition, the overall accuracies of 100 %, 6 %, and 83 % were achieved for IB detection using the satellite images, respectively. These accuracies substantiate the fact that the GeoEye-1 satellite images had the best performance among the employed images in producing change image map and detecting the IBs.

  19. Spatial variability of soil moisture retrieved by SMOS satellite

    Science.gov (United States)

    Lukowski, Mateusz; Marczewski, Wojciech; Usowicz, Boguslaw; Rojek, Edyta; Slominski, Jan; Lipiec, Jerzy

    2015-04-01

    Standard statistical methods assume that the analysed variables are independent. Since the majority of the processes observed in the nature are continuous in space and time, this assumption introduces a significant limitation for understanding the examined phenomena. In classical approach, valuable information about the locations of examined observations is completely lost. However, there is a branch of statistics, called geostatistics, which is the study of random variables, but taking into account the space where they occur. A common example of so-called "regionalized variable" is soil moisture. Using in situ methods it is difficult to estimate soil moisture distribution because it is often significantly diversified. Thanks to the geostatistical methods, by employing semivariance analysis, it is possible to get the information about the nature of spatial dependences and their lengths. Since the Soil Moisture and Ocean Salinity mission launch in 2009, the estimation of soil moisture spatial distribution for regional up to continental scale started to be much easier. In this study, the SMOS L2 data for Central and Eastern Europe were examined. The statistical and geostatistical features of moisture distributions of this area were studied for selected natural soil phenomena for 2010-2014 including: freezing, thawing, rainfalls (wetting), drying and drought. Those soil water "states" were recognized employing ground data from the agro-meteorological network of ground-based stations SWEX and SMUDP2 data from SMOS. After pixel regularization, without any upscaling, the geostatistical methods were applied directly on Discrete Global Grid (15-km resolution) in ISEA 4H9 projection, on which SMOS observations are reported. Analysis of spatial distribution of SMOS soil moisture, carried out for each data set, in most cases did not show significant trends. It was therefore assumed that each of the examined distributions of soil moisture in the adopted scale satisfies

  20. Derivation of high spatial resolution albedo from UAV digital imagery: application over the Greenland Ice Sheet

    Science.gov (United States)

    Ryan, Jonathan C.; Hubbard, Alun; Box, Jason E.; Brough, Stephen; Cameron, Karen; Cook, Joseph M.; Cooper, Matthew; Doyle, Samuel H.; Edwards, Arwyn; Holt, Tom; Irvine-Fynn, Tristram; Jones, Christine; Pitcher, Lincoln H.; Rennermalm, Asa K.; Smith, Laurence C.; Stibal, Marek; Snooke, Neal

    2017-05-01

    Measurements of albedo are a prerequisite for modelling surface melt across the Earth's cryosphere, yet available satellite products are limited in spatial and/or temporal resolution. Here, we present a practical methodology to obtain centimetre resolution albedo products with accuracies of 5% using consumer-grade digital camera and unmanned aerial vehicle (UAV) technologies. Our method comprises a workflow for processing, correcting and calibrating raw digital images using a white reference target, and upward and downward shortwave radiation measurements from broadband silicon pyranometers. We demonstrate the method with a set of UAV sorties over the western, K-sector of the Greenland Ice Sheet. The resulting albedo product, UAV10A1, covers 280 km2, at a resolution of 20 cm per pixel and has a root-mean-square difference of 3.7% compared to MOD10A1 and 4.9% compared to ground-based broadband pyranometer measurements. By continuously measuring downward solar irradiance, the technique overcomes previous limitations due to variable illumination conditions during and between surveys over glaciated terrain. The current miniaturization of multispectral sensors and incorporation of upward facing radiation sensors on UAV packages means that this technique will likely become increasingly attractive in field studies and used in a wide range of applications for high temporal and spatial resolution surface mapping of debris, dust, cryoconite and bioalbedo and for directly constraining surface energy balance models.

  1. Validation of High Resolution IMERG Satellite Precipitation over the Global Oceans using OceanRAIN

    Science.gov (United States)

    Kucera, Paul; Klepp, Christian

    2017-04-01

    Precipitation is a key parameter of the essential climate variables in the Earth System that is a key variable in the global water cycle. Observations of precipitation over oceans is relatively sparse. Satellite observations over oceans is the only viable means of measuring the spatially distribution of precipitation. In an effort to improve global precipitation observations, the research community has developed a state of the art precipitation dataset as part of the NASA/JAXA Global Precipitation Measurement (GPM) program. The satellite gridded product that has been developed is called Integrated Multi-satelliE Retrievals for GPM (IMERG), which has a maximum spatial resolution of 0.1° x 0.1° and temporal 30 minute. Even with the advancements in retrievals, there is a need to quantify uncertainty of IMERG especially over oceans. To address this need, the OceanRAIN dataset has been used to create a comprehensive database to compare IMERG products. The OceanRAIN dataset was collected using an ODM-470 optical disdrometer that has been deployed on 12 research vessels worldwide with 6 long-term installations operating in all climatic regions, seasons and ocean basins. More than 5.5 million data samples have been collected on the OceanRAIN program. These data were matched to IMERG grids for the study period of 15 March 2014-31 January 2016. This evaluation produced over a 1000 matched pairs with precipitation observed at the surface. These matched pairs were used to evaluate the performance of IMERG for different latitudinal bands and precipitation regimes. The presentation will provide an overview of the study and summary of evaluation results.

  2. Introducing mapping standards in the quality assessment of buildings extracted from very high resolution satellite imagery

    Science.gov (United States)

    Freire, S.; Santos, T.; Navarro, A.; Soares, F.; Silva, J. D.; Afonso, N.; Fonseca, A.; Tenedório, J.

    2014-04-01

    Many municipal activities require updated large-scale maps that include both topographic and thematic information. For this purpose, the efficient use of very high spatial resolution (VHR) satellite imagery suggests the development of approaches that enable a timely discrimination, counting and delineation of urban elements according to legal technical specifications and quality standards. Therefore, the nature of this data source and expanding range of applications calls for objective methods and quantitative metrics to assess the quality of the extracted information which go beyond traditional thematic accuracy alone. The present work concerns the development and testing of a new approach for using technical mapping standards in the quality assessment of buildings automatically extracted from VHR satellite imagery. Feature extraction software was employed to map buildings present in a pansharpened QuickBird image of Lisbon. Quality assessment was exhaustive and involved comparisons of extracted features against a reference data set, introducing cartographic constraints from scales 1:1000, 1:5000, and 1:10,000. The spatial data quality elements subject to evaluation were: thematic (attribute) accuracy, completeness, and geometric quality assessed based on planimetric deviation from the reference map. Tests were developed and metrics analyzed considering thresholds and standards for the large mapping scales most frequently used by municipalities. Results show that values for completeness varied with mapping scales and were only slightly superior for scale 1:10,000. Concerning the geometric quality, a large percentage of extracted features met the strict topographic standards of planimetric deviation for scale 1:10,000, while no buildings were compliant with the specification for scale 1:1000.

  3. High spatial resolution soft-x-ray microscopy

    Energy Technology Data Exchange (ETDEWEB)

    Meyer-Ilse, W.; Medecki, H.; Brown, J.T. [Ernest Orlando Lawrence Berkeley National Lab., CA (United States)] [and others

    1997-04-01

    A new soft x-ray microscope (XM-1) with high spatial resolution has been constructed by the Center for X-ray Optics. It uses bending magnet radiation from beamline 6.1 at the Advanced Light Source, and is used in a variety of projects and applications in the life and physical sciences. Most of these projects are ongoing. The instrument uses zone plate lenses and achieves a resolution of 43 nm, measured over 10% to 90% intensity with a knife edge test sample. X-ray microscopy permits the imaging of relatively thick samples, up to 10 {mu}m thick, in water. XM-1 has an easy to use interface, that utilizes visible light microscopy to precisely position and focus the specimen. The authors describe applications of this device in the biological sciences, as well as in studying industrial applications including structured polymer samples.

  4. Neuromorphic model of magnocellular and parvocellular visual paths: spatial resolution

    International Nuclear Information System (INIS)

    Aguirre, Rolando C; Felice, Carmelo J; Colombo, Elisa M

    2007-01-01

    Physiological studies of the human retina show the existence of at least two visual information processing channels, the magnocellular and the parvocellular ones. Both have different spatial, temporal and chromatic features. This paper focuses on the different spatial resolution of these two channels. We propose a neuromorphic model, so that they match the retina's physiology. Considering the Deutsch and Deutsch model (1992), we propose two configurations (one for each visual channel) of the connection between the retina's different cell layers. The responses of the proposed model have similar behaviour to those of the visual cells: each channel has an optimum response corresponding to a given stimulus size which decreases for larger or smaller stimuli. This size is bigger for the magno path than for the parvo path and, in the end, both channels produce a magnifying of the borders of a stimulus

  5. Accessing High Spatial Resolution in Astronomy Using Interference Methods

    Science.gov (United States)

    Carbonel, Cyril; Grasset, Sébastien; Maysonnave, Jean

    2018-04-01

    In astronomy, methods such as direct imaging or interferometry-based techniques (Michelson stellar interferometry for example) are used for observations. A particular advantage of interferometry is that it permits greater spatial resolution compared to direct imaging with a single telescope, which is limited by diffraction owing to the aperture of the instrument as shown by Rueckner et al. in a lecture demonstration. The focus of this paper, addressed to teachers and/or students in high schools and universities, is to easily underline both an application of interferometry in astronomy and stress its interest for resolution. To this end very simple optical experiments are presented to explain all the concepts. We show how an interference pattern resulting from the combined signals of two telescopes allows us to measure the distance between two stars with a resolution beyond the diffraction limit. Finally this work emphasizes the breathtaking resolution obtained in state-of-the-art instruments such as the VLTi (Very Large Telescope interferometer).

  6. Using High-Resolution Satellite Aerosol Optical Depth To Estimate Daily PM2.5 Geographical Distribution in Mexico City.

    Science.gov (United States)

    Just, Allan C; Wright, Robert O; Schwartz, Joel; Coull, Brent A; Baccarelli, Andrea A; Tellez-Rojo, Martha María; Moody, Emily; Wang, Yujie; Lyapustin, Alexei; Kloog, Itai

    2015-07-21

    Recent advances in estimating fine particle (PM2.5) ambient concentrations use daily satellite measurements of aerosol optical depth (AOD) for spatially and temporally resolved exposure estimates. Mexico City is a dense megacity that differs from other previously modeled regions in several ways: it has bright land surfaces, a distinctive climatological cycle, and an elevated semi-enclosed air basin with a unique planetary boundary layer dynamic. We extend our previous satellite methodology to the Mexico City area, a region with higher PM2.5 than most U.S. and European urban areas. Using a novel 1 km resolution AOD product from the MODIS instrument, we constructed daily predictions across the greater Mexico City area for 2004-2014. We calibrated the association of AOD to PM2.5 daily using municipal ground monitors, land use, and meteorological features. Predictions used spatial and temporal smoothing to estimate AOD when satellite data were missing. Our model performed well, resulting in an out-of-sample cross-validation R(2) of 0.724. Cross-validated root-mean-squared prediction error (RMSPE) of the model was 5.55 μg/m(3). This novel model reconstructs long- and short-term spatially resolved exposure to PM2.5 for epidemiological studies in Mexico City.

  7. The Effect of Spatial and Spectral Resolution in Determining NDVI

    Science.gov (United States)

    Boelman, N. T.

    2003-12-01

    We explore the impact that varying spatial and spectral resolutions of several sensors (a field portable spectroradiometer, Landsat, MODIS and AVHRR) has in determining the average Normalized Difference Vegetation Index (NDVI) at Imnavait Creek, a small arctic tundra watershed located on the north slope of Alaska. We found that at the field-of-views (FOVs) of less than 20 m2 that were sampled, the average NDVI value for this watershed is 0.65, compared to 0.77 at FOVs equal to and greater than 20 m2. In addition, we found that at FOVs less than 20 m2, the average NDVI value calculated according to each of Landsat, MODIS and AVHRR band definitions (controlled by spectral resolution) was similar. However, at FOVs equal to and greater than 20 m2, the average NDVI value calculated according to AVHRR's broad-band definitions was significantly and consistently higher than that from both Landsat and MODIS's narrow-band NDVI values. We speculate that these differences in NDVI exist because high leaf-area-index vegetation communities associated with watertracks are commonly spaced between 10 and 20 m apart in arctic tundra landscapes and are often only included when spectral sampling is conducted at FOVs greater than tens of square meters. These results suggest that both spatial resolution alone and its interaction with spectral resolution have to be considered when interpreting commonly used global-scale NDVI datasets. This is because traditionally, the fundamental relationships established between NDVI and ecosystem parameters, such as CO2 fluxes, aboveground biomass and net primary productivity, have been established at scales less than 20 m2. Other ecosystems, such as landscapes with isolated tree islands in boreal forest-tundra ecotones, may exhibit similar scaling patterns that need to be considered when interpreting global-scale NDVI datasets.

  8. Very high resolution satellite data: New challenges in image analysis

    Digital Repository Service at National Institute of Oceanography (India)

    Sathe, P.V.; Muraleedharan, P.M.

    or other natural landscapes. Having very high resolution digital data over a landscape will however create new challenges in the field of atmospheric correction, ground registration, image processing and finally the image interpretation itself. Even...

  9. Assessment of burned areas in Mato Grosso State, Brazil, from a systematic sample of medium resolution satellite imagery

    OpenAIRE

    SHIMABUKURO YOSIO EDEMIR; BEUCHLE Rene'; GRECCHI ROSANA; SIMONETTI DARIO; ACHARD Frederic

    2014-01-01

    This paper presents a method for mapping and assessing burned areas at a regional scale, using a systematic sample of medium spatial resolution satellite images (Landsat). The State of Mato Grosso, located in the Brazilian Amazon region, comprising an area of pproximately 903,366 km², was selected for this study. 77 sample sites (20km × 20km in size) located at each full degree confluence of latitude and longitude were analyzed. The results showed that 52,663 km² or approximately 5.8% of the ...

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

    Science.gov (United States)

    Quattrochi, D. A.; Luvall, J. C.

    2006-12-01

    Although the study of the Urban Heat Island (UHI) effect dates back to the early 1800's when Luke Howard discovered London's heat island, it has only been with the advent of thermal remote sensing systems that the extent, characteristics, and impacts of the UHI have become to be understood. Analysis of the UHI effect is important because above all, this phenomenon can directly influence the health and welfare of urban residents. For example, in 1995, over 700 people died in Chicago due to heat-related causes. UHI's are characterized by increased temperature in comparison to rural areas and mortality rates during a heat wave increase exponentially with the maximum temperature, an effect that is exacerbated by the UHI. Aside from the direct impacts of the UHI on temperature, UHI's can produce secondary effects on local meteorology, including altering local wind patterns, increased development of clouds and fog, and increasing rates of precipitation either over, or downwind, of cities. Because of the extreme heterogeneity of the urban surface, in combination with the sprawl associated with urban growth, thermal infrared (TIR) remote sensing data have become of significant importance in understanding how land cover and land use characteristics affect the development and intensification of the UHI. TIR satellite data have been used extensively to analyze the surface temperature regimes of cities to help observe and measure the impacts of surface temperatures across the urban landscape. However, the spatial scales at which satellite TIR data are collected are for the most part, coarse, with the finest readily available TIR data collected by the Landsat ETM+ sensor at 60m spatial resolution. For many years, we have collected high spatial resolution (10m) data using an airborne multispectral TIR sensor over a number of cities across the United States. These high resolution data have been used to develop an understanding of how discrete surfaces across the urban environment

  11. Identifying Spatial Units of Human Occupation in the Brazilian Amazon Using Landsat and CBERS Multi-Resolution Imagery

    Directory of Open Access Journals (Sweden)

    Maria Isabel Sobral Escada

    2012-01-01

    Full Text Available Every spatial unit of human occupation is part of a network structuring an extensive process of urbanization in the Amazon territory. Multi-resolution remote sensing data were used to identify and map human presence and activities in the Sustainable Forest District of Cuiabá-Santarém highway (BR-163, west of Pará, Brazil. The limits of spatial units of human occupation were mapped based on digital classification of Landsat-TM5 (Thematic Mapper 5 image (30m spatial resolution. High-spatial-resolution CBERS-HRC (China-Brazil Earth Resources Satellite-High-Resolution Camera images (5 m merged with CBERS-CCD (Charge Coupled Device images (20 m were used to map spatial arrangements inside each populated unit, describing intra-urban characteristics. Fieldwork data validated and refined the classification maps that supported the categorization of the units. A total of 133 spatial units were individualized, comprising population centers as municipal seats, villages and communities, and units of human activities, such as sawmills, farmhouses, landing strips, etc. From the high-resolution analysis, 32 population centers were grouped in four categories, described according to their level of urbanization and spatial organization as: structured, recent, established and dependent on connectivity. This multi-resolution approach provided spatial information about the urbanization process and organization of the territory. It may be extended into other areas or be further used to devise a monitoring system, contributing to the discussion of public policy priorities for sustainable development in the Amazon.

  12. Structural and chemical analysis of materials with high spatial resolution

    International Nuclear Information System (INIS)

    Benthem, K. van; Kraemer, S.; Sigle, W.; Ruehle, M.

    2002-01-01

    An understanding of the correlation between microstructures and properties of materials require the characterization of the material on many different length scales. Often the properties depend primarily on the atomistics of defects, such as dislocations and interfaces. The different techniques of transmission electron microscopy allow the characterization of the structure and of the chemical composition of materials with high spatial resolution to the atomic level: high resolution transmission electron microscopy allows the determination of the position of the columns of atoms (ions) with high accuracy. The accuracy which can be achieved in these measurements depends not only on the instrumentation but also on the quality of the transmitted specimen and on the scattering power of the atoms (ions) present in the analyzed column. The chemical composition can be revealed from investigations by analytical microscopy which includes energy dispersive x-ray spectroscopy, mainly quantitatively applied for heavy elements, and electron energy-loss spectroscopy. Furthermore, the energy-loss near-edge structure of EELS data results in information on the local band structure of unoccupied states of the excited atoms and, therefore, on bonding. A quantitative evaluation of convergent beam electron diffraction results in information on the electron charge density distribution of the bulk (defect-free) material. The different techniques are described and applied to different problems in materials science. lt will be shown that nearly atomic resolution can be achieved in high resolution electron microscopy and in analytical electron microscopy. Recent developments in electron microscopy instrumentation will result in atomic resolution in the foreseeable future. (author)

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

    Directory of Open Access Journals (Sweden)

    Guizhou Wang

    2013-01-01

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

  14. Satellite-based high-resolution mapping of rainfall over southern Africa

    Directory of Open Access Journals (Sweden)

    H. Meyer

    2017-06-01

    Full Text Available A spatially explicit mapping of rainfall is necessary for southern Africa for eco-climatological studies or nowcasting but accurate estimates are still a challenging task. This study presents a method to estimate hourly rainfall based on data from the Meteosat Second Generation (MSG Spinning Enhanced Visible and Infrared Imager (SEVIRI. Rainfall measurements from about 350 weather stations from 2010–2014 served as ground truth for calibration and validation. SEVIRI and weather station data were used to train neural networks that allowed the estimation of rainfall area and rainfall quantities over all times of the day. The results revealed that 60 % of recorded rainfall events were correctly classified by the model (probability of detection, POD. However, the false alarm ratio (FAR was high (0.80, leading to a Heidke skill score (HSS of 0.18. Estimated hourly rainfall quantities were estimated with an average hourly correlation of ρ = 0. 33 and a root mean square error (RMSE of 0.72. The correlation increased with temporal aggregation to 0.52 (daily, 0.67 (weekly and 0.71 (monthly. The main weakness was the overestimation of rainfall events. The model results were compared to the Integrated Multi-satellitE Retrievals for GPM (IMERG of the Global Precipitation Measurement (GPM mission. Despite being a comparably simple approach, the presented MSG-based rainfall retrieval outperformed GPM IMERG in terms of rainfall area detection: GPM IMERG had a considerably lower POD. The HSS was not significantly different compared to the MSG-based retrieval due to a lower FAR of GPM IMERG. There were no further significant differences between the MSG-based retrieval and GPM IMERG in terms of correlation with the observed rainfall quantities. The MSG-based retrieval, however, provides rainfall in a higher spatial resolution. Though estimating rainfall from satellite data remains challenging, especially at high temporal resolutions, this study showed

  15. Benefits of optical clocks for high spatial resolution geopotential determination

    Science.gov (United States)

    Lion, G.; Panet, I.; Wolf, P.; Guerlin, C.; Bize, S.; Delva, P.

    2016-12-01

    Recent technological advances in optical atomic clocks are opening new perspectives for the direct determination of geopotential differences at the Earth's surface. To date, the best of them reach an accuracy of 10-18 in term of relative frequency shift, corresponding to a centimeter-level accuracy in geoid height. However, so far detailed quantitative estimates of the possible improvement in geoid determination when adding such clock measurements to existing gravity data are lacking. In this context, the present work aims at evaluating the contribution of this new kind of direct measurements in determining the geopotential at high spatial resolution. We consider the Alps-Mediterranean area, which comprises high reliefs and a land/sea transition, leading to variations of the gravitational field over a range of spatial scales. In such type of region, the scarcity of gravity data is an important limitation in deriving accurate high resolution geopotential models. First, we present our methodology to assess the contribution of clock data in the geopotential recovery, in combination with ground gravity measurements. We sample synthetic gravity and disturbing potential data from a spherical harmonics geopotential model, and a topography model, up to 10 km resolution; we also build a potential control grid. From the synthetic data, we estimate the disturbing potential by least-squares collocation. Finally, we assess the quality of the reconstructed potential by comparing it to that of the control grid. We show that adding only a few clock data reduces the reconstruction bias significantly and improves the standard deviation by a factor 3. We investigate the effect of the data coverage and data quality on these results, and discuss the trade-off between the measurement noise level and the number of data.

  16. Spatial Ensemble Postprocessing of Precipitation Forecasts Using High Resolution Analyses

    Science.gov (United States)

    Lang, Moritz N.; Schicker, Irene; Kann, Alexander; Wang, Yong

    2017-04-01

    Ensemble prediction systems are designed to account for errors or uncertainties in the initial and boundary conditions, imperfect parameterizations, etc. However, due to sampling errors and underestimation of the model errors, these ensemble forecasts tend to be underdispersive, and to lack both reliability and sharpness. To overcome such limitations, statistical postprocessing methods are commonly applied to these forecasts. In this study, a full-distributional spatial post-processing method is applied to short-range precipitation forecasts over Austria using Standardized Anomaly Model Output Statistics (SAMOS). Following Stauffer et al. (2016), observation and forecast fields are transformed into standardized anomalies by subtracting a site-specific climatological mean and dividing by the climatological standard deviation. Due to the need of fitting only a single regression model for the whole domain, the SAMOS framework provides a computationally inexpensive method to create operationally calibrated probabilistic forecasts for any arbitrary location or for all grid points in the domain simultaneously. Taking advantage of the INCA system (Integrated Nowcasting through Comprehensive Analysis), high resolution analyses are used for the computation of the observed climatology and for model training. The INCA system operationally combines station measurements and remote sensing data into real-time objective analysis fields at 1 km-horizontal resolution and 1 h-temporal resolution. The precipitation forecast used in this study is obtained from a limited area model ensemble prediction system also operated by ZAMG. The so called ALADIN-LAEF provides, by applying a multi-physics approach, a 17-member forecast at a horizontal resolution of 10.9 km and a temporal resolution of 1 hour. The performed SAMOS approach statistically combines the in-house developed high resolution analysis and ensemble prediction system. The station-based validation of 6 hour precipitation sums

  17. A new multiple spatial resolution estimate of the bedrock elevation of the Greenland ice sheet.

    Science.gov (United States)

    Griggs, Jennifer; Bamber, Jonathan; Plummer, Joel; Gogineni, Sivaprasad; Rignot, Eric

    2010-05-01

    Gridded bedrock elevation for the Greenland ice sheet has previously been determined with 5 km postings. The true resolution of the data set was, in places, however, considerably coarser than this due to the across-track spacing of flight lines. Errors were estimated to be on the order of a few percent in the centre of the ice sheet but increasing markedly in relative magnitude near the margins, where, for numerical modelling, accurate thickness is particularly critical. We use new airborne and satellite estimates of ice thickness and surface elevation to determine the bed topography for the whole of Greenland. In particular, the University of Kansas have in recent years, flown an airborne ice-penetrating radar system with close flightline spacing over several key outlet glacier systems. This allows us to produce a multi-resolution bedrock elevation dataset with the high spatial resolution needed for ice dynamic modelling over these key outlet glaciers and coarser resolution over the more sparsely sampled interior. Airborne ice thickness and elevation from CReSIS obtained between 1993 and 2009 are combined with JPL, DONNEES data covering the marginal areas along the south west coast from 2009. Data collected in the 1970's by the Technical University of Denmark were also used in interior areas with sparse coverage from other sources. Marginal elevation data from the ICESat laser altimeter were used to help constrain the ice thickness and bed topography close to the ice sheet margin where, typically, the terrestrial observations have poor sampling between flight tracks.

  18. Multi-resolution analysis of high density spatial and temporal cloud inhomogeneity fields from HOPE campaign

    Science.gov (United States)

    Lakshmi Madhavan, Bomidi; Deneke, Hartwig; Macke, Andreas

    2015-04-01

    Clouds are the most complex structures in both spatial and temporal scales of the Earth's atmosphere that effect the downward surface reaching fluxes and thus contribute to large uncertainty in the global radiation budget. Within the framework of High Definition Clouds and Precipitation for advancing Climate Prediction (HD(CP)2) Observational Prototype Experiment (HOPE), a high density network of 99 pyranometer stations was set up around Jülich, Germany (~ 10 × 12 km2 area) during April to July 2013 to capture the small-scale variability in cloud induced radiation fields at the surface. In this study, we perform multi-resolution analysis of the downward solar irradiance variability at the surface from the pyranometer network to investigate the dependence of temporal and spatial averaging scales on the variance and spatial correlation for different cloud regimes. Preliminary results indicate that correlation is strongly scale-dependent where as the variance is dependent on the length of averaging period. Implications of our findings will be useful for quantifying the effect of spatial collocation while validating the satellite inferred solar irradiance estimates, and also to explore the link between cloud structure and radiation. We will present the details of our analysis and results.

  19. Forming intermediate spatial resolution of microscopy images for continuous zooming on multi-resolution processing system

    Science.gov (United States)

    Putranto, Evan H. E.; Suzuki, Tomohiro; Usuki, Shin; Miura, Kenjiro T.

    2017-09-01

    Digital zooming especially on microscopy image has attempted to improve their quality of measurement into a better assessment. However, since the field of view of high-resolution image are not wide despite of the fact that high-resolution image has more information detail and low-resolution image has their merits which is bring a big picture of the whole structure, we need to observe the sample in any scale. This problem was been solved by developing dual-view of high and low images resolution1 but in a single interpolated images. The goal of this research is utilize multi-resolution images to develop smooth zooming magnification of microscopy image. In order to achieve smooth zooming magnification on different condition of the images, scheme process will be needed. First, we took a several spatial images of the same sample based on the different objective lens, author was used 4 objective lens which are 10×, 20×, 50× and 150× magnification. In this synthesize phase, we interpolate lower resolution image for synthesize purpose with the next higher resolution image of the sample. Second, continue to looking for the feature point of both images with SIFT feature point method until we synthesize both images. Third, author treat this synthesized image with discrete fourier transform (DFT) with low-pass filter as the same size with numerical aperture (NA) that was input on the first phase. Then the fourth phase is looping this processes until intermediate images are generated enough to be blend with pyramid blend method. In this article we also try to make a system that can arbitrarily generate intermediate image with hierarchical system.

  20. Detection of Local Anomalies in High Resolution Hyperspectral Imagery Using Geostatistical Filtering and Local Spatial Statistics

    Science.gov (United States)

    Goovaerts, P.; Jacquez, G. M.; Marcus, A. W.

    2004-12-01

    Spatial data are periodically collected and processed to monitor, analyze and interpret developments in our changing environment. Remote sensing is a modern way of data collecting and has seen an enormous growth since launching of modern satellites and development of airborne sensors. In particular, the recent availability of high spatial resolution hyperspectral imagery (spatial resolution of less than 5 meters and including data collected over 64 or more bands of electromagnetic radiation for each pixel offers a great potential to significantly enhance environmental mapping and our ability to model spatial systems. High spatial resolution imagery contains a remarkable quantity of information that could be used to analyze spatial breaks (boundaries), areas of similarity (clusters), and spatial autocorrelation (associations) across the landscape. This paper addresses the specific issue of soil disturbance detection, which could indicate the presence of land mines or recent movements of troop and heavy equipment. A challenge presented by soil detection is to retain the measurement of fine-scale features (i.e. mineral soil changes, organic content changes, vegetation disturbance related changes, aspect changes) while still covering proportionally large spatial areas. An additional difficulty is that no ground data might be available for the calibration of spectral signatures, and little might be known about the size of patches of disturbed soils to be detected. This paper describes a new technique for automatic target detection which capitalizes on both spatial and across spectral bands correlation, does not require any a priori information on the target spectral signature but does not allow discrimination between targets. This approach involves successively a multivariate statistical analysis (principal component analysis) of all spectral bands, a geostatistical filtering of noise and regional background in the first principal components using factorial kriging, and

  1. High-resolution satellite-based cloud-coupled estimates of total downwelling surface radiation for hydrologic modelling applications

    Directory of Open Access Journals (Sweden)

    B. A. Forman

    2009-07-01

    Full Text Available A relatively simple satellite-based radiation model yielding high-resolution (in space and time downwelling longwave and shortwave radiative fluxes at the Earth's surface is presented. The primary aim of the approach is to provide a basis for deriving physically consistent forcing fields for distributed hydrologic models using satellite-based remote sensing data. The physically-based downwelling radiation model utilises satellite inputs from both geostationary and polar-orbiting platforms and requires only satellite-based inputs except that of a climatological lookup table derived from a regional climate model. Comparison against ground-based measurements over a 14-month simulation period in the Southern Great Plains of the United States demonstrates the ability to reproduce radiative fluxes at a spatial resolution of 4 km and a temporal resolution of 1 h with good accuracy during all-sky conditions. For hourly fluxes, a mean difference of −2 W m−2 with a root mean square difference of 21 W m−2 was found for the longwave fluxes whereas a mean difference of −7 W m−2 with a root mean square difference of 29 W m−2 was found for the shortwave fluxes. Additionally, comparison against advanced downwelling longwave and solar insolation products during all-sky conditions showed comparable uncertainty in the longwave estimates and reduced uncertainty in the shortwave estimates. The relatively simple form of the model enables future usage in ensemble-based applications including data assimilation frameworks in order to explicitly account for input uncertainties while providing the potential for conditioning estimates from other readily available products derived from more sophisticated retrieval algorithms.

  2. MACSAT - A Mini-Satellite Approach to High Resolution Space Imaging

    OpenAIRE

    Kim, Byung-Jin; Park, Sungdong; Kim, Ee-Eul; Chang, Hyon-Sock; Park, Wonkyu; Seon, Jongho; Ismail, Maszlan; Ad-Rasheed, Ad-Aziz; Sabirin-Arshad, Ahmad

    2003-01-01

    To be launched in 2004, MACSAT is a 200kg satellite, designed to provide 2.5m ground sampling distance (GSD) resolution imagery on a near equatorial orbit (NEqO). The mission objective is to demonstrate the capability of a high-resolution remote sensing satellite system on a NEqO. Initi-ated by ATSB, the proprietary NEqO mission has advantages for monitoring the environment of equatorial regions of Malaysia with unique revisit characteristics from the baseline circular orbit of 7 degrees of i...

  3. OSIS: remote sensing code for estimating aerosol optical properties in urban areas from very high spatial resolution images.

    Science.gov (United States)

    Thomas, Colin; Briottet, Xavier; Santer, Richard

    2011-10-01

    The achievement of new satellite or airborne remote sensing instruments enables the more precise study of cities with metric spatial resolutions. For studies such as the radiative characterization of urban features, knowledge of the atmosphere and particularly of aerosols is required to perform first an atmospheric compensation of the remote sensing images. However, to our knowledge, no efficient aerosol characterization technique adapted both to urban areas and to very high spatial resolution images has yet been developed. The goal of this paper is so to present a new code to characterize aerosol optical properties, OSIS, adapted to urban remote sensing images of metric spatial resolution acquired in the visible and near-IR spectral domains. First, a new aerosol characterization method based on the observation of shadow/sun transitions is presented, offering the advantage to avoid the assessment of target reflectances. Its principle and the modeling of the signal used to solve the retrieval equation are then detailed. Finally, a sensitivity study of OSIS from synthetic images simulated by the radiative transfer code AMARTIS v2 is also presented. This study has shown an intrinsic precision of this tool of Δτ(a)=0.1.τ(a) ± (0.02 + 0.4.τ(a)) for retrieval of aerosol optical thicknesses. This study shows that OSIS is a powerful tool for aerosol characterization that has a precision similar to satellite products for the aerosol optical thicknesses retrieval and that can be applied to every very high spatial resolution instrument, multispectral or hyperspectral, airborne or satellite.

  4. Non Local Spatial and Angular Matching: Enabling higher spatial resolution diffusion MRI datasets through adaptive denoising.

    Science.gov (United States)

    St-Jean, Samuel; Coupé, Pierrick; Descoteaux, Maxime

    2016-08-01

    Diffusion magnetic resonance imaging (MRI) datasets suffer from low Signal-to-Noise Ratio (SNR), especially at high b-values. Acquiring data at high b-values contains relevant information and is now of great interest for microstructural and connectomics studies. High noise levels bias the measurements due to the non-Gaussian nature of the noise, which in turn can lead to a false and biased estimation of the diffusion parameters. Additionally, the usage of in-plane acceleration techniques during the acquisition leads to a spatially varying noise distribution, which depends on the parallel acceleration method implemented on the scanner. This paper proposes a novel diffusion MRI denoising technique that can be used on all existing data, without adding to the scanning time. We first apply a statistical framework to convert both stationary and non stationary Rician and non central Chi distributed noise to Gaussian distributed noise, effectively removing the bias. We then introduce a spatially and angular adaptive denoising technique, the Non Local Spatial and Angular Matching (NLSAM) algorithm. Each volume is first decomposed in small 4D overlapping patches, thus capturing the spatial and angular structure of the diffusion data, and a dictionary of atoms is learned on those patches. A local sparse decomposition is then found by bounding the reconstruction error with the local noise variance. We compare against three other state-of-the-art denoising methods and show quantitative local and connectivity results on a synthetic phantom and on an in-vivo high resolution dataset. Overall, our method restores perceptual information, removes the noise bias in common diffusion metrics, restores the extracted peaks coherence and improves reproducibility of tractography on the synthetic dataset. On the 1.2 mm high resolution in-vivo dataset, our denoising improves the visual quality of the data and reduces the number of spurious tracts when compared to the noisy acquisition. Our

  5. High spatial resolution spectroscopy of single semiconductor nanostructures

    Science.gov (United States)

    Harris, T. D.; Gershoni, D.; Pfeiffer, L.; Nirmal, M.; Trautman, J. K.; Macklin, J. J.

    1996-11-01

    Low-temperature near-field scanning optical microscopy is used for the first time in spectroscopic studies of single, nanometre dimension, cleaved edge overgrown quantum wires. A direct experimental comparison between a two-dimensional system and a single genuinely one-dimensional quantum wire system, inaccessible to conventional far-field optical spectroscopy, is enabled by the enhanced spatial resolution. We show that the photoluminescence of a single quantum wire is easily distinguished from that of the surrounding quantum well. Emission from localized centres is shown to dominate the photoluminescence from both wires and wells at low temperatures. A factor of three oscillator strength enhancement for these wires compared with the wells is concluded from the photoluminescence excitation data. We also report room-temperature spectroscopy and dynamics of single CdSe nanocrystals. Photochemistry, trap dynamics and spectroscopy are easily determined.

  6. Tactile Feedback Display with Spatial and Temporal Resolutions

    Science.gov (United States)

    Vishniakou, Siarhei; Lewis, Brian W.; Niu, Xiaofan; Kargar, Alireza; Sun, Ke; Kalajian, Michael; Park, Namseok; Yang, Muchuan; Jing, Yi; Brochu, Paul; Sun, Zhelin; Li, Chun; Nguyen, Truong; Pei, Qibing; Wang, Deli

    2013-08-01

    We report the electronic recording of the touch contact and pressure using an active matrix pressure sensor array made of transparent zinc oxide thin-film transistors and tactile feedback display using an array of diaphragm actuators made of an interpenetrating polymer elastomer network. Digital replay, editing and manipulation of the recorded touch events were demonstrated with both spatial and temporal resolutions. Analog reproduction of the force is also shown possible using the polymer actuators, despite of the high driving voltage. The ability to record, store, edit, and replay touch information adds an additional dimension to digital technologies and extends the capabilities of modern information exchange with the potential to revolutionize physical learning, social networking, e-commerce, robotics, gaming, medical and military applications.

  7. Improved Wetland Classification Using Eight-Band High Resolution Satellite Imagery and a Hybrid Approach

    Directory of Open Access Journals (Sweden)

    Charles R. Lane

    2014-12-01

    Full Text Available Although remote sensing technology has long been used in wetland inventory and monitoring, the accuracy and detail level of wetland maps derived with moderate resolution imagery and traditional techniques have been limited and often unsatisfactory. We explored and evaluated the utility of a newly launched high-resolution, eight-band satellite system (Worldview-2; WV2 for identifying and classifying freshwater deltaic wetland vegetation and aquatic habitats in the Selenga River Delta of Lake Baikal, Russia, using a hybrid approach and a novel application of Indicator Species Analysis (ISA. We achieved an overall classification accuracy of 86.5% (Kappa coefficient: 0.85 for 22 classes of aquatic and wetland habitats and found that additional metrics, such as the Normalized Difference Vegetation Index and image texture, were valuable for improving the overall classification accuracy and particularly for discriminating among certain habitat classes. Our analysis demonstrated that including WV2’s four spectral bands from parts of the spectrum less commonly used in remote sensing analyses, along with the more traditional bandwidths, contributed to the increase in the overall classification accuracy by ~4% overall, but with considerable increases in our ability to discriminate certain communities. The coastal band improved differentiating open water and aquatic (i.e., vegetated habitats, and the yellow, red-edge, and near-infrared 2 bands improved discrimination among different vegetated aquatic and terrestrial habitats. The use of ISA provided statistical rigor in developing associations between spectral classes and field-based data. Our analyses demonstrated the utility of a hybrid approach and the benefit of additional bands and metrics in providing the first spatially explicit mapping of a large and heterogeneous wetland system.

  8. High resolution earth observation satellites and services in the next decade a European perspective

    Science.gov (United States)

    Schreier, Gunter; Dech, Stefan

    2005-07-01

    Projects to use very high resolution optical satellite sensor data started in the late 90s and are believed to be the major driver for the commercialisation of earth observation. The global political security situation and updated legislative frameworks created new opportunities for high resolution, dual use satellite systems. In addition to new optical sensors, very high resolution synthetic aperture radars will become in the next few years an important component in the imaging satellite fleet. The paper will review the development in this domain so far, and give perspectives on future emerging markets and opportunities. With dual-use satellite initiatives and new political frameworks agreed between the European Commission and the European Space Agency (ESA), the European market becomes very attractive for both service suppliers and customers. The political focus on "Global Monitoring for Environment and Security" (GMES) and the "European Defence and Security Policy" drive and amplify this demand which ranges from low resolution climate monitoring to very high resolution reconnaissance tasks. In order to create an operational and sustainable GMES in Europe by 2007, the European infrastructure need to be adapted and extended. This includes the ESA SENTINEL and OXYGEN programmes, aiming for a fleet of earth observation satellites and an open and operational earth observation ground segment. The harmonisation of national and regional geographic information is driven by the European Commission's INSPIRE programme. The necessary satellite capacity to complement existing systems in the delivery of space based data required for GMES is currently under definition. Embedded in a market with global competition and in the global political framework of a Global Earth Observation System of Systems, European companies, agencies and research institutions are now contributing to this joint undertaking. The paper addresses the chances, risks and options for the future.

  9. Recent advances in the determination of a high spatial resolution geopotential model using chronometric geodesy

    Science.gov (United States)

    Lion, Guillaume; Guerlin, Christine; Bize, Sébastien; Wolf, Peter; Delva, Pacôme; Panet, Isabelle

    2016-04-01

    Current methods to determine the geopotential are mainly based on indirect approaches using gravimetric, gradiometric and topographic data. Satellite missions (GRACE, GOCE) have contributed significantly to improve the knowledge of the Earth's gravity field with a spatial resolution of about 90 km, but it is not enough to access, for example, to the geoid variation in hilly regions. While airborne and ground-based gravimeters provide the high resolution, the problem of these technics is that the accuracy is hampered by the heterogeneous coverage of gravity data (ground and offshore). Recent technological advances in atomic clocks are opening new perspectives in the determination of the geopotential. To date, the best of them reach a stability of 1.6×10-18 (NIST, RIKEN + Univ. Tokyo) in just 7 hours of integration, an accuracy of 2.0×10-18 (JILA). Using the relation of the relativistic gravitational redshift, this corresponds to a determination of geopotential differences at the 0.1 m²/s² level (or 1 cm in geoid height). In this context, the present work aims at evaluating the contribution of optical atomic clocks for the determination of the geopotential at high spatial resolution. To do that, we have studied a test area surrounding the Massif Central in the middle of southern of France. This region, consists in low mountain ranges and plateaus, is interesting because, the gravitational field strength varies greatly from place to place at high resolution due to the relief. Here, we present the synthetic tests methodology: generation of synthetic gravity and potential data, then estimation of the potential from these data using the least-squares collocation and assessment of the clocks contribution. We shall see how the coverage of the data points (realistic or not) can affect the results, and discuss how to quantify the trade-off between the noise level and the number of data points used.

  10. Extraction of Airport Features from High Resolution Satellite Imagery for Design and Risk Assessment

    Science.gov (United States)

    Robinson, Chris; Qiu, You-Liang; Jensen, John R.; Schill, Steven R.; Floyd, Mike

    2001-01-01

    The LPA Group, consisting of 17 offices located throughout the eastern and central United States is an architectural, engineering and planning firm specializing in the development of Airports, Roads and Bridges. The primary focus of this ARC project is concerned with assisting their aviation specialists who work in the areas of Airport Planning, Airfield Design, Landside Design, Terminal Building Planning and design, and various other construction services. The LPA Group wanted to test the utility of high-resolution commercial satellite imagery for the purpose of extracting airport elevation features in the glide path areas surrounding the Columbia Metropolitan Airport. By incorporating remote sensing techniques into their airport planning process, LPA wanted to investigate whether or not it is possible to save time and money while achieving the equivalent accuracy as traditional planning methods. The Affiliate Research Center (ARC) at the University of South Carolina investigated the use of remotely sensed imagery for the extraction of feature elevations in the glide path zone. A stereo pair of IKONOS panchromatic satellite images, which has a spatial resolution of 1 x 1 m, was used to determine elevations of aviation obstructions such as buildings, trees, towers and fence-lines. A validation dataset was provided by the LPA Group to assess the accuracy of the measurements derived from the IKONOS imagery. The initial goal of this project was to test the utility of IKONOS imagery in feature extraction using ERDAS Stereo Analyst. This goal was never achieved due to problems with ERDAS software support of the IKONOS sensor model and the unavailability of imperative sensor model information from Space Imaging. The obstacles encountered in this project pertaining to ERDAS Stereo Analyst and IKONOS imagery will be reviewed in more detail later in this report. As a result of the technical difficulties with Stereo Analyst, ERDAS OrthoBASE was used to derive aviation

  11. Design of the high resolution optical instrument for the Pleiades HR Earth observation satellites

    Science.gov (United States)

    Lamard, Jean-Luc; Gaudin-Delrieu, Catherine; Valentini, David; Renard, Christophe; Tournier, Thierry; Laherrere, Jean-Marc

    2017-11-01

    As part of its contribution to Earth observation from space, ALCATEL SPACE designed, built and tested the High Resolution cameras for the European intelligence satellites HELIOS I and II. Through these programmes, ALCATEL SPACE enjoys an international reputation. Its capability and experience in High Resolution instrumentation is recognised by the most customers. Coming after the SPOT program, it was decided to go ahead with the PLEIADES HR program. PLEIADES HR is the optical high resolution component 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. ALCATEL SPACE has been entrusted by CNES with the development of the high resolution camera of the Earth observation satellites PLEIADES HR. The first optical satellite of the PLEIADES HR constellation will be launched in mid-2008, the second will follow in 2009. To minimize the development costs, a mini satellite approach has been selected, leading to a compact concept for the camera design. The paper describes the design and performance budgets of this novel high resolution and large field of view optical instrument with emphasis on the technological features. This new generation of camera represents a breakthrough in comparison with the previous SPOT cameras owing to a significant step in on-ground resolution, which approaches the capabilities of aerial photography. Recent advances in detector technology, optical fabrication and electronics make it possible for the PLEIADES HR camera to achieve their image quality performance goals while staying within weight and size restrictions normally considered suitable only for much lower performance systems. This camera design delivers superior performance using an innovative low power, low mass, scalable architecture, which provides a versatile approach for a variety of imaging requirements and allows for a wide number of possibilities of accommodation with a mini-satellite

  12. Accuracy and impact of spatial aids based upon satellite enumeration to improve indoor residual spraying spatial coverage.

    Science.gov (United States)

    Bridges, Daniel J; Pollard, Derek; Winters, Anna M; Winters, Benjamin; Sikaala, Chadwick; Renn, Silvia; Larsen, David A

    2018-02-23

    Indoor residual spraying (IRS) is a key tool in the fight to control, eliminate and ultimately eradicate malaria. IRS protection is based on a communal effect such that an individual's protection primarily relies on the community-level coverage of IRS with limited protection being provided by household-level coverage. To ensure a communal effect is achieved through IRS, achieving high and uniform community-level coverage should be the ultimate priority of an IRS campaign. Ensuring high community-level coverage of IRS in malaria-endemic areas is challenging given the lack of information available about both the location and number of households needing IRS in any given area. A process termed 'mSpray' has been developed and implemented and involves use of satellite imagery for enumeration for planning IRS and a mobile application to guide IRS implementation. This study assessed (1) the accuracy of the satellite enumeration and (2) how various degrees of spatial aid provided through the mSpray process affected community-level IRS coverage during the 2015 spray campaign in Zambia. A 2-stage sampling process was applied to assess accuracy of satellite enumeration to determine number and location of sprayable structures. Results indicated an overall sensitivity of 94% for satellite enumeration compared to finding structures on the ground. After adjusting for structure size, roof, and wall type, households in Nchelenge District where all types of satellite-based spatial aids (paper-based maps plus use of the mobile mSpray application) were used were more likely to have received IRS than Kasama district where maps used were not based on satellite enumeration. The probability of a household being sprayed in Nchelenge district where tablet-based maps were used, did not differ statistically from that of a household in Samfya District, where detailed paper-based spatial aids based on satellite enumeration were provided. IRS coverage from the 2015 spray season benefited from

  13. Device for high spatial resolution chemical analysis of a sample and method of high spatial resolution chemical analysis

    Science.gov (United States)

    Van Berkel, Gary J.

    2015-10-06

    A system and method for analyzing a chemical composition of a specimen are described. The system can include at least one pin; a sampling device configured to contact a liquid with a specimen on the at least one pin to form a testing solution; and a stepper mechanism configured to move the at least one pin and the sampling device relative to one another. The system can also include an analytical instrument for determining a chemical composition of the specimen from the testing solution. In particular, the systems and methods described herein enable chemical analysis of specimens, such as tissue, to be evaluated in a manner that the spatial-resolution is limited by the size of the pins used to obtain tissue samples, not the size of the sampling device used to solubilize the samples coupled to the pins.

  14. Derivation of High Spatial Resolution Albedo from UAV Digital Imagery: Application over the Greenland Ice Sheet

    Directory of Open Access Journals (Sweden)

    Jonathan C. Ryan

    2017-05-01

    Full Text Available Measurements of albedo are a prerequisite for modeling surface melt across the Earth's cryosphere, yet available satellite products are limited in spatial and/or temporal resolution. Here, we present a practical methodology to obtain centimeter resolution albedo products with accuracies of ±5% using consumer-grade digital camera and unmanned aerial vehicle (UAV technologies. Our method comprises a workflow for processing, correcting and calibrating raw digital images using a white reference target, and upward and downward shortwave radiation measurements from broadband silicon pyranometers. We demonstrate the method with a set of UAV sorties over the western, K-sector of the Greenland Ice Sheet. The resulting albedo product, UAV10A1, covers 280 km2, at a resolution of 20 cm per pixel and has a root-mean-square difference of 3.7% compared to MOD10A1 and 4.9% compared to ground-based broadband pyranometer measurements. By continuously measuring downward solar irradiance, the technique overcomes previous limitations due to variable illumination conditions during and between surveys over glaciated terrain. The current miniaturization of multispectral sensors and incorporation of upward facing radiation sensors on UAV packages means that this technique could become increasingly common in field studies and used for a wide range of applications. These include the mapping of debris, dust, cryoconite and bioalbedo, and directly constraining surface energy balance models.

  15. Spatial and energy distributions of satellite-speed helium atoms reflected from satellite-type surfaces

    International Nuclear Information System (INIS)

    Liu, S.M.; Rodgers, W.E.; Knuth, E.L.

    1977-01-01

    Interactions of satellite-speed helium atoms (accelerated in an expansion from an arc-heated supersonic-molecular-beam source) with practical satellite surfaces have been investigated experimentally. The density and energy distributions of the scattered atoms were measured using a detection system developed for this study. This detection system includes (a) a target positioning mechanism, (b) a detector rotating mechanism, and (c) a mass spectrometer and/or a retarding-field energy analyzer. (Auth.)

  16. Multi Resolution Analysis (MRA of satellite images of oil spill disasters

    Directory of Open Access Journals (Sweden)

    Rashid Hussain

    2014-09-01

    Full Text Available Oil spill disasters monitoring and mitigation requires availability of state of the art applications and tools. Conventional technology gets benefit from latest trends and research in satellite imaginary. This research highlights multi-resolution wavelet analysis of satellite images of oil spill disasters. Multi-resolution analysis is one of the powerful techniques to analyze information content of images. This analysis enables us to have a scale-invariant interpretation of the image. At each resolution level, both smooth and detailed signals carry all the necessary information to reconstruct the smooth signal at the next level. The wavelet decomposition results in detail and approximate threshold coefficients. Multi resolution wavelet decomposition is used to analyze the image in both time and frequency domain. It provides better frequency resolution and poor time resolution for lower frequency; better time resolution and poor frequency resolution for higher frequency. This condition is fortunately suited for real applications; as signals have high frequency components for very short period of the interval and low frequency components for longer durations.

  17. Impact of spectral resolution of in situ ocean color radiometric data in satellite matchups analyses.

    Science.gov (United States)

    Zibordi, Giuseppe; Talone, Marco; Voss, Kenneth J; Johnson, B Carol

    2017-08-07

    The spectral resolution requirements for in situ remote sensing reflectanceR RS measurements aiming at supporting satellite ocean color validation and System Vicarious Calibration (SVC) were investigated. The study, conducted using sample hyperspectral R RS from different water types, focused on the visible spectral bands of the ocean land color imager (OLCI) and of the Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) satellite sensors. Allowing for a ±0.5% maximum difference between in situ and satellite derived R RS solely due to the spectral band characteristics of the in situ radiometer, a spectral resolution of 1 nm for SVC of PACE is needed in oligotrophic waters. Requirements decrease to 3 nm for SVC of OLCI. In the case of validation activities, which exhibit less stringent uncertainty requirements with respect to SVC, a maximum difference of ±1% between in situ and satellite derived data indicates the need for a spectral resolution of 3 nm for both OLCI and PACE in oligotrophic waters. Conversely, spectral resolutions of 6 nm for PACE and 9 nm for OLCI appear to satisfy validation activities in optically complex waters.

  18. Analysis of high resolution satellite digital data for land use studies ...

    African Journals Online (AJOL)

    High-resolution satellite data can give vital information about land cover, which can lead to better interpretation and classification of land resources. This study examined the relationship between Systeme Probatoire d'Observation de la Terre (SPOT) digital data and land use types in the derived savanna ecosystem of ...

  19. Super-Resolution for “Jilin-1” Satellite Video Imagery via a Convolutional Network

    Directory of Open Access Journals (Sweden)

    Aoran Xiao

    2018-04-01

    Full Text Available Super-resolution for satellite video attaches much significance to earth observation accuracy, and the special imaging and transmission conditions on the video satellite pose great challenges to this task. The existing deep convolutional neural-network-based methods require pre-processing or post-processing to be adapted to a high-resolution size or pixel format, leading to reduced performance and extra complexity. To this end, this paper proposes a five-layer end-to-end network structure without any pre-processing and post-processing, but imposes a reshape or deconvolution layer at the end of the network to retain the distribution of ground objects within the image. Meanwhile, we formulate a joint loss function by combining the output and high-dimensional features of a non-linear mapping network to precisely learn the desirable mapping relationship between low-resolution images and their high-resolution counterparts. Also, we use satellite video data itself as a training set, which favors consistency between training and testing images and promotes the method’s practicality. Experimental results on “Jilin-1” satellite video imagery show that this method demonstrates a superior performance in terms of both visual effects and measure metrics over competing methods.

  20. Super-Resolution for "Jilin-1" Satellite Video Imagery via a Convolutional Network.

    Science.gov (United States)

    Xiao, Aoran; Wang, Zhongyuan; Wang, Lei; Ren, Yexian

    2018-04-13

    Super-resolution for satellite video attaches much significance to earth observation accuracy, and the special imaging and transmission conditions on the video satellite pose great challenges to this task. The existing deep convolutional neural-network-based methods require pre-processing or post-processing to be adapted to a high-resolution size or pixel format, leading to reduced performance and extra complexity. To this end, this paper proposes a five-layer end-to-end network structure without any pre-processing and post-processing, but imposes a reshape or deconvolution layer at the end of the network to retain the distribution of ground objects within the image. Meanwhile, we formulate a joint loss function by combining the output and high-dimensional features of a non-linear mapping network to precisely learn the desirable mapping relationship between low-resolution images and their high-resolution counterparts. Also, we use satellite video data itself as a training set, which favors consistency between training and testing images and promotes the method's practicality. Experimental results on "Jilin-1" satellite video imagery show that this method demonstrates a superior performance in terms of both visual effects and measure metrics over competing methods.

  1. Role of light satellites in the high-resolution Earth observation domain

    Science.gov (United States)

    Fishman, Moshe

    1999-12-01

    Current 'classic' applications using and exploring space based earth imagery are exclusive, narrow niche tailored, expensive and hardly accessible. On the other side new, inexpensive and widely used 'consumable' applications will be only developed concurrently to the availability of appropriate imagery allowing that process. A part of these applications can be imagined today, like WWW based 'virtual tourism' or news media, but the history of technological, cultural and entertainment evolution teaches us that most of future applications are unpredictable -- they emerge together with the platforms enabling their appearance. The only thing, which can be ultimately stated, is that the definitive condition for such applications is the availability of the proper imagery platform providing low cost, high resolution, large area, quick response, simple accessibility and quick dissemination of the raw picture. This platform is a constellation of Earth Observation satellites. Up to 1995 the Space Based High Resolution Earth Observation Domain was dominated by heavy, super-expensive and very inflexible birds. The launch of Israeli OFEQ-3 Satellite by MBT Division of Israel Aircraft Industries (IAI) marked the entrance to new era of light, smart and cheap Low Earth Orbited Imaging satellites. The Earth Resource Observation System (EROS) initiated by West Indian Space, is based on OFEQ class Satellites design and it is capable to gather visual data of Earth Surface both at high resolution and large image capacity. The main attributes, derived from its compact design, low weight and sophisticated logic and which convert the EROS Satellite to valuable and productive system, are discussed. The major advantages of Light Satellites in High Resolution Earth Observation Domain are presented and WIS guidelines featuring the next generation of LEO Imaging Systems are included.

  2. Tree Species Classification By Multiseasonal High Resolution Satellite Data

    Science.gov (United States)

    Elatawneh, Alata; Wallner, Adelheid; Straub, Christoph; Schneider, Thomas; Knoke, Thomas

    2013-12-01

    Accurate forest tree species mapping is a fundamental issue for sustainable forest management and planning. Forest tree species mapping with the means of remote sensing data is still a topic to be investigated. The Bavaria state institute of forestry is investigating the potential of using digital aerial images for forest management purposes. However, using aerial images is still cost- and time-consuming, in addition to their acquisition restrictions. The new space-born sensor generations such as, RapidEye, with a very high temporal resolution, offering multiseasonal data have the potential to improve the forest tree species mapping. In this study, we investigated the potential of multiseasonal RapidEye data for mapping tree species in a Mid European forest in Southern Germany. The RapidEye data of level A3 were collected on ten different dates in the years 2009, 2010 and 2011. For data analysis, a model was developed, which combines the Spectral Angle Mapper technique with a 10-fold- cross-validation. The analysis succeeded to differentiate four tree species; Norway spruce (Picea abies L.), Silver Fir (Abies alba Mill.), European beech (Fagus sylvatica) and Maple (Acer pseudoplatanus). The model success was evaluated using digital aerial images acquired in the year 2009 and inventory point records from 2008/09 inventory. Model results of the multiseasonal RapidEye data analysis achieved an overall accuracy of 76%. However, the success of the model was evaluated only for all the identified species and not for the individual.

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

    Directory of Open Access Journals (Sweden)

    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.

  4. 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. PMID:24069206

  5. Global anthropogenic heat flux database with high spatial resolution

    Science.gov (United States)

    Dong, Y.; Varquez, A. C. G.; Kanda, M.

    2017-02-01

    This study developed a top-down method for estimating global anthropogenic heat emission (AHE), with a high spatial resolution of 30 arc-seconds and temporal resolution of 1 h. Annual average AHE was derived from human metabolic heating and primary energy consumption, which was further divided into three components based on consumer sector. The first and second components were heat loss and heat emissions from industrial sectors equally distributed throughout the country and populated areas, respectively. The third component comprised the sum of emissions from commercial, residential, and transportation sectors (CRT). Bulk AHE from the CRT was proportionally distributed using a global population dataset, with a radiance-calibrated nighttime lights adjustment. An empirical function to estimate monthly fluctuations of AHE based on gridded monthly temperatures was derived from various Japanese and American city measurements. Finally, an AHE database with a global coverage was constructed for the year 2013. Comparisons between our proposed AHE and other existing datasets revealed that the problem of overestimation of AHE intensity in previous top-down models was mitigated by the separation of energy consumption sectors; furthermore, the problem of AHE underestimation at central urban areas was solved by the nighttime lights adjustment. A strong agreement in the monthly profiles of AHE between our database and other bottom-up datasets further proved the validity of the current methodology. Investigations of AHE for the 29 largest urban agglomerations globally highlighted that the share of heat emissions from CRT sectors to the total AHE at the city level was 40-95%; whereas that of metabolic heating varied with the city's level of development by a range of 2-60%. A negative correlation between gross domestic product (GDP) and the share of metabolic heating to a city's total AHE was found. Globally, peak AHE values were found to occur between December and February, while

  6. Optimizing Spatial Resolution of Imagery for Urban Form Detection—The Cases of France and Vietnam

    Directory of Open Access Journals (Sweden)

    Christiane Weber

    2011-09-01

    Full Text Available The multitude of satellite data products available offers a large choice for urban studies. Urban space is known for its high heterogeneity in structure, shape and materials. To approach this heterogeneity, finding the optimal spatial resolution (OSR is needed for urban form detection from remote sensing imagery. By applying the local variance method to our datasets (pan-sharpened images, we can identify OSR at two levels of observation: individual urban elements and urban districts in two agglomerations in West Europe (Strasbourg, France and in Southeast Asia (Da Nang, Vietnam. The OSR corresponds to the minimal variance of largest number of spectral bands. We carry out three categories of interval values of spatial resolutions for identifying OSR: from 0.8 m to 3 m for isolated objects, from 6 m to 8 m for vegetation area and equal or higher than 20 m for urban district. At the urban district level, according to spatial patterns, form, size and material of elements, we propose the range of OSR between 30 m and 40 m for detecting administrative districts, new residential districts and residential discontinuous districts. The detection of industrial districts refers to a coarser OSR from 50 m to 60 m. The residential continuous dense districts effectively need a finer OSR of between 20 m and 30 m for their optimal identification. We also use fractal dimensions to identify the threshold of homogeneity/heterogeneity of urban structure at urban district level. It seems therefore that our approaches are robust and transferable to different urban contexts.

  7. Environmental monitoring of El Hierro Island submarine volcano, by combining low and high resolution satellite imagery

    Science.gov (United States)

    Eugenio, F.; Martin, J.; Marcello, J.; Fraile-Nuez, E.

    2014-06-01

    El Hierro Island, located at the Canary Islands Archipelago in the Atlantic coast of North Africa, has been rocked by thousands of tremors and earthquakes since July 2011. Finally, an underwater volcanic eruption started 300 m below sea level on October 10, 2011. Since then, regular multidisciplinary monitoring has been carried out in order to quantify the environmental impacts caused by the submarine eruption. Thanks to this natural tracer release, multisensorial satellite imagery obtained from MODIS and MERIS sensors have been processed to monitor the volcano activity and to provide information on the concentration of biological, chemical and physical marine parameters. Specifically, low resolution satellite estimations of optimal diffuse attenuation coefficient (Kd) and chlorophyll-a (Chl-a) concentration under these abnormal conditions have been assessed. These remote sensing data have played a fundamental role during field campaigns guiding the oceanographic vessel to the appropriate sampling areas. In addition, to analyze El Hierro submarine volcano area, WorldView-2 high resolution satellite spectral bands were atmospherically and deglinted processed prior to obtain a high-resolution optimal diffuse attenuation coefficient model. This novel algorithm was developed using a matchup data set with MERIS and MODIS data, in situ transmittances measurements and a seawater radiative transfer model. Multisensor and multitemporal imagery processed from satellite remote sensing sensors have demonstrated to be a powerful tool for monitoring the submarine volcanic activities, such as discolored seawater, floating material and volcanic plume, having shown the capabilities to improve the understanding of submarine volcanic processes.

  8. RELATIVE ORIENTATION AND MODIFIED PIECEWISE EPIPOLAR RESAMPLING FOR HIGH RESOLUTION SATELLITE IMAGES

    Directory of Open Access Journals (Sweden)

    K. Gong

    2017-05-01

    Full Text Available High resolution, optical satellite sensors are boosted to a new era in the last few years, because satellite stereo images at half meter or even 30cm resolution are available. Nowadays, high resolution satellite image data have been commonly used for Digital Surface Model (DSM generation and 3D reconstruction. It is common that the Rational Polynomial Coefficients (RPCs provided by the vendors have rough precision and there is no ground control information available to refine the RPCs. Therefore, we present two relative orientation methods by using corresponding image points only: the first method will use quasi ground control information, which is generated from the corresponding points and rough RPCs, for the bias-compensation model; the second method will estimate the relative pointing errors on the matching image and remove this error by an affine model. Both methods do not need ground control information and are applied for the entire image. To get very dense point clouds, the Semi-Global Matching (SGM method is an efficient tool. However, before accomplishing the matching process the epipolar constraints are required. In most conditions, satellite images have very large dimensions, contrary to the epipolar geometry generation and image resampling, which is usually carried out in small tiles. This paper also presents a modified piecewise epipolar resampling method for the entire image without tiling. The quality of the proposed relative orientation and epipolar resampling method are evaluated, and finally sub-pixel accuracy has been achieved in our work.

  9. Spatial and decadal variations in satellite-based terrestrial ...

    Indian Academy of Sciences (India)

    Home; Journals; Journal of Earth System Science; Volume 126; Issue 8. Spatial and decadal variations in ... Ayad M Fadhil Yuhu Zhang Kun Jia. Volume 126 Issue 8 December 2017 Article ID 119 ... of Kufa, Najaf 34003, Iraq. College of Resource Environment and Tourism, Capital Normal University, Beijing 100048, China.

  10. Towards breaking the spatial resolution barriers: An optical flow and super-resolution approach for sea ice motion estimation

    Science.gov (United States)

    Petrou, Zisis I.; Xian, Yang; Tian, YingLi

    2018-04-01

    Estimation of sea ice motion at fine scales is important for a number of regional and local level applications, including modeling of sea ice distribution, ocean-atmosphere and climate dynamics, as well as safe navigation and sea operations. In this study, we propose an optical flow and super-resolution approach to accurately estimate motion from remote sensing images at a higher spatial resolution than the original data. First, an external example learning-based super-resolution method is applied on the original images to generate higher resolution versions. Then, an optical flow approach is applied on the higher resolution images, identifying sparse correspondences and interpolating them to extract a dense motion vector field with continuous values and subpixel accuracies. Our proposed approach is successfully evaluated on passive microwave, optical, and Synthetic Aperture Radar data, proving appropriate for multi-sensor applications and different spatial resolutions. The approach estimates motion with similar or higher accuracy than the original data, while increasing the spatial resolution of up to eight times. In addition, the adopted optical flow component outperforms a state-of-the-art pattern matching method. Overall, the proposed approach results in accurate motion vectors with unprecedented spatial resolutions of up to 1.5 km for passive microwave data covering the entire Arctic and 20 m for radar data, and proves promising for numerous scientific and operational applications.

  11. Analysing the advantages of high temporal resolution geostationary MSG SEVIRI data compared to Polar Operational Environmental Satellite data for land surface monitoring in Africa

    Science.gov (United States)

    Fensholt, R.; Anyamba, A.; Huber, S.; Proud, S. R.; Tucker, C. J.; Small, J.; Pak, E.; Rasmussen, M. O.; Sandholt, I.; Shisanya, C.

    2011-10-01

    Since 1972, satellite remote sensing of the environment has been dominated by polar-orbiting sensors providing useful data for monitoring the earth's natural resources. However their observation and monitoring capacity are inhibited by daily to monthly looks for any given ground surface which often is obscured by frequent and persistent cloud cover creating large gaps in time series measurements. The launch of the Meteosat Second Generation (MSG) satellite into geostationary orbit has opened new opportunities for land surface monitoring. The Spinning Enhanced Visible and Infrared Imager (SEVIRI) instrument on-board MSG with an imaging capability every 15 min which is substantially greater than any temporal resolution that can be obtained from existing Polar Operational Environmental Satellite (POES) systems currently in use for environmental monitoring. Different areas of the African continent were affected by droughts and floods in 2008 caused by periods of abnormally low and high rainfall, respectively. Based on the effectiveness of monitoring these events from Earth Observation (EO) data the current analyses show that the new generation of geostationary remote sensing data can provide higher temporal resolution cloud-free (systems. SEVIRI MSG 5-day continental scale composites will enable rapid assessment of environmental conditions and improved early warning of disasters for the African continent such as flooding or droughts. The high temporal resolution geostationary data will complement existing higher spatial resolution polar-orbiting satellite data for various dynamic environmental and natural resource applications of terrestrial ecosystems.

  12. The high-resolution version of TM5-MP for optimized satellite retrievals: description and validation

    Science.gov (United States)

    Williams, Jason E.; Folkert Boersma, K.; Le Sager, Phillipe; Verstraeten, Willem W.

    2017-02-01

    We provide a comprehensive description of the high-resolution version of the TM5-MP global chemistry transport model, which is to be employed for deriving highly resolved vertical profiles of nitrogen dioxide (NO2), formaldehyde (CH2O), and sulfur dioxide (SO2) for use in satellite retrievals from platforms such as the Ozone Monitoring Instrument (OMI) and the Sentinel-5 Precursor, and the TROPOspheric Monitoring Instrument (tropOMI). Comparing simulations conducted at horizontal resolutions of 3° × 2° and 1° × 1° reveals differences of ±20 % exist in the global seasonal distribution of 222Rn, being larger near specific coastal locations and tropical oceans. For tropospheric ozone (O3), analysis of the chemical budget terms shows that the impact on globally integrated photolysis rates is rather low, in spite of the higher spatial variability of meteorological data fields from ERA-Interim at 1° × 1°. Surface concentrations of O3 in high-NOx regions decrease between 5 and 10 % at 1° × 1° due to a reduction in NOx recycling terms and an increase in the associated titration term of O3 by NO. At 1° × 1°, the net global stratosphere-troposphere exchange of O3 decreases by ˜ 7 %, with an associated shift in the hemispheric gradient. By comparing NO, NO2, HNO3 and peroxy-acetyl-nitrate (PAN) profiles against measurement composites, we show that TM5-MP captures the vertical distribution of NOx and long-lived NOx reservoirs at background locations, again with modest changes at 1° × 1°. Comparing monthly mean distributions in lightning NOx and applying ERA-Interim convective mass fluxes, we show that the vertical re-distribution of lightning NOx changes with enhanced release of NOx in the upper troposphere. We show that surface mixing ratios in both NO and NO2 are generally underestimated in both low- and high-NOx scenarios. For Europe, a negative bias exists for [NO] at the surface across the whole domain, with lower biases at 1° × 1° at only ˜ 20

  13. Predicting spatial variations of tree species richness in tropical forests from high-resolution remote sensing.

    Science.gov (United States)

    Fricker, Geoffrey A; Wolf, Jeffrey A; Saatchi, Sassan S; Gillespie, Thomas W

    2015-10-01

    There is an increasing interest in identifying theories, empirical data sets, and remote-sensing metrics that can quantify tropical forest alpha diversity at a landscape scale. Quantifying patterns of tree species richness in the field is time consuming, especially in regions with over 100 tree species/ha. We examine species richness in a 50-ha plot in Barro Colorado Island in Panama and test if biophysical measurements of canopy reflectance from high-resolution satellite imagery and detailed vertical forest structure and topography from light detection and ranging (lidar) are associated with species richness across four tree size classes (>1, 1-10, >10, and >20 cm dbh) and three spatial scales (1, 0.25, and 0.04 ha). We use the 2010 tree inventory, including 204,757 individuals belonging to 301 species of freestanding woody plants or 166 ± 1.5 species/ha (mean ± SE), to compare with remote-sensing data. All remote-sensing metrics became less correlated with species richness as spatial resolution decreased from 1.0 ha to 0.04 ha and tree size increased from 1 cm to 20 cm dbh. When all stems with dbh > 1 cm in 1-ha plots were compared to remote-sensing metrics, standard deviation in canopy reflectance explained 13% of the variance in species richness. The standard deviations of canopy height and the topographic wetness index (TWI) derived from lidar were the best metrics to explain the spatial variance in species richness (15% and 24%, respectively). Using multiple regression models, we made predictions of species richness across Barro Colorado Island (BCI) at the 1-ha spatial scale for different tree size classes. We predicted variation in tree species richness among all plants (adjusted r² = 0.35) and trees with dbh > 10 cm (adjusted r² = 0.25). However, the best model results were for understory trees and shrubs (dbh 1-10 cm) (adjusted r² = 0.52) that comprise the majority of species richness in tropical forests. Our results indicate that high-resolution

  14. Interactions of satellite-speed helium atoms with satellite-surfaces. 1. Spatial distributions of reflected helium atoms

    International Nuclear Information System (INIS)

    Liu, S.M.; Rodgers, W.E.; Knuth, E.L.

    1975-06-01

    Interactions of satellite-speed helium atoms with practical satellite surfaces were investigated experimentally, and spatial distributions of satellite-speed helium beams scattered from four different engineering surfaces were measured. The 7000-m/s helium beams were produced using an arc-heated supersonic molecular beam source. The test surfaces included cleaned 6061-T6 aluminum plate, anodized aluminum foil, white paint, and quartz surfaces. Both in-plane (in the plane containing the incident beam and the surface normal) and out-of-plane spatial distributions of reflected helium atoms were measured for six different incidence angles (0, 15, 30, 45, 60, and 75 deg from the surface normal). It was found that a large fraction of the incident helium atoms were scattered back in the vicinity of the incoming beam, particularly in the case of glancing incidence angles. This unexpected scattering feature results perhaps from the gross roughness of these test surfaces. This prominent backscattering could yield drag coefficients which are higher than for surfaces with either forward-lobed or diffusive (cosine) scattering patterns

  15. Improved Spatial Resolution in Thick, Fully-Depleted CCDs withEnhanced Red Sensitivity

    Energy Technology Data Exchange (ETDEWEB)

    Fairfield, Jessamyn A.; Groom, Donald E.; Bailey, Stephen J.; Bebek, Christopher J.; Holland, Stephen E.; Karcher, Armin; Kolbe,William F.; Lorenzon, Wolfgang; Roe, Natalie A.

    2006-03-09

    The point spread function (PSF) is an important measure of spatial resolution in CCDs for point-like objects, since it affects image quality and spectroscopic resolution. We present new data and theoretical developments for lateral charge diffusion in thick, fully-depleted charge-coupled devices (CCDs) developed at Lawrence Berkeley National Laboratory (LBNL). Because they can be over-depleted, the LBNL devices have no field-free region and diffusion is controlled through the application of an external bias voltage. We give results for a 3512 x 3512 format, 10.5 {micro}m pixel back-illuminated p-channel CCD developed for the SuperNova/Acceleration Probe (SNAP), a proposed satellite-based experiment designed to study dark energy. The PSF was measured at substrate bias voltages between 3 V and 115 V. At a bias voltage of 115 V, we measure an rms diffusion of 3.7 {+-} 0.2 {micro}m. Lateral charge diffusion in LBNL CCDs will meet the SNAP requirements.

  16. Comparative study between ultrahigh spatial frequency algorithm and high spatial frequency algorithm in high-resolution CT of the lungs

    International Nuclear Information System (INIS)

    Oh, Yu Whan; Kim, Jung Kyuk; Suh, Won Hyuck

    1994-01-01

    To date, the high spatial frequency algorithm (HSFA) which reduces image smoothing and increases spatial resolution has been used for the evaluation of parenchymal lung diseases in thin-section high-resolution CT. In this study, we compared the ultrahigh spatial frequency algorithm (UHSFA) with the high spatial frequency algorithm in the assessment of thin section images of the lung parenchyma. Three radiologists compared the UHSFA and HSFA on identical CT images in a line-pair resolution phantom, one lung specimen, 2 patients with normal lung and 18 patients with abnormal lung parenchyma. Scanning of a line-pair resolution phantom demonstrated no difference in resolution between two techniques but it showed that outer lines of the line pairs with maximal resolution looked thicker on UHSFA than those on HSFA. Lung parenchymal detail with UHSFA was judged equal or superior to HSFA in 95% of images. Lung parenchymal sharpness was improved with UHSFA in all images. Although UHSFA resulted in an increase in visible noise, observers did not found that image noise interfered with image interpretation. The visual CT attenuation of normal lung parenchyma is minimally increased in images with HSFA. The overall visual preference of the images reconstructed on UHSFA was considered equal to or greater than that of those reconstructed on HSFA in 78% of images. The ultrahigh spatial frequency algorithm improved the overall visual quality of the images in pulmonary parenchymal high-resolution CT

  17. Detector Motion Method to Increase Spatial Resolution in Photon-Counting Detectors

    Energy Technology Data Exchange (ETDEWEB)

    Lee, Daehee; Park, Kyeongjin; Lim, Kyung Taek; Cho, Gyuseong [Korea Advanced Institute of Science and Technology, Daejon (Korea, Republic of)

    2017-03-15

    Medical imaging requires high spatial resolution of an image to identify fine lesions. Photoncounting detectors in medical imaging have recently been rapidly replacing energy-integrating detectors due to the former's high spatial resolution, high efficiency and low noise. Spatial resolution in a photon counting image is determined by the pixel size. Therefore, the smaller the pixel size, the higher the spatial resolution that can be obtained in an image. However, detector redesigning is required to reduce pixel size, and an expensive fine process is required to integrate a signal processing unit with reduced pixel size. Furthermore, as the pixel size decreases, charge sharing severely deteriorates spatial resolution. To increase spatial resolution, we propose a detector motion method using a large pixel detector that is less affected by charge sharing. To verify the proposed method, we utilized a UNO-XRI photon-counting detector (1-mm CdTe, Timepix chip) at the maximum X-ray tube voltage of 80 kVp. A similar spatial resolution of a 55-μm-pixel image was achieved by application of the proposed method to a 110-μm-pixel detector with a higher signal-to-noise ratio. The proposed method could be a way to increase spatial resolution without a pixel redesign when pixels severely suffer from charge sharing as pixel size is reduced.

  18. Ionization statistics and diffusion: analytical estimate of their contribution to spatial resolution of drift chambers

    International Nuclear Information System (INIS)

    Tarnopolsky, G.J.

    1983-01-01

    The spatial resolution of a drift chamber often is the foremost design parameter. The calculation described here - a design tool - permits us to estimate the contributions of ionization statistics and diffusion to the spatial resolution when actually sampling the drift pulse waveform. Useful formulae are derived for the cylindrical and jet-chamber cell geometries

  19. Comparative analysis of time efficiency and spatial resolution between different EIT reconstruction algorithms

    International Nuclear Information System (INIS)

    Kacarska, Marija; Loskovska, Suzana

    2002-01-01

    In this paper comparative analysis between different EIT algorithms is presented. Analysis is made for spatial and temporal resolution of obtained images by several different algorithms. Discussions consider spatial resolution dependent on data acquisition method, too. Obtained results show that conventional applied-current EIT is more powerful compared to induced-current EIT. (Author)

  20. The use of satellite data for monitoring temporal and spatial patterns of fire: a comprehensive review

    Science.gov (United States)

    Lasaponara, R.

    2009-04-01

    Remotely sensed (RS) data can fruitfully support both research activities and operative monitoring of fire at different temporal and spatial scales with a synoptic view and cost effective technologies. "The contribution of remote sensing (RS) to forest fires may be grouped in three categories, according to the three phases of fire management: (i) risk estimation (before fire), (ii) detection (during fire) and (iii) assessment (after fire)" Chuvieco (2006). Relating each phase, wide research activities have been conducted over the years. (i) Risk estimation (before fire) has been mainly based on the use of RS data for (i) monitoring vegetation stress and assessing variations in vegetation moisture content, (ii) fuel type mapping, at different temporal and spatial scales from global, regional down to a local scale (using AVHRR, MODIS, TM, ASTER, Quickbird images and airborne hyperspectral and LIDAR data). Danger estimation has been mainly based on the use of AVHRR (onborad NOAA), MODIS (onboard TERRA and AQUA), VEGETATION (onboard SPOT) due to the technical characteristics (i.e. spectral, spatial and temporal resolution). Nevertheless microwave data have been also used for vegetation monitoring. (ii) Detection: identification of active fires, estimation of fire radiative energy and fire emission. AVHRR was one of the first satellite sensors used for setting up fire detection algorithms. The availbility of MODIS allowed us to obtain global fire products free downloaded from NASA web site. Sensors onboard geostationary satellite platforms, such as GOES, SEVIRI, have been used for fire detection, to obtain a high temporal resolution (at around 15 minutes) monitoring of active fires. (iii) Post fire damage assessment includes: burnt area mapping, fire emission, fire severity, vegetation recovery, fire resilience estimation, and, more recently, fire regime characterization. Chuvieco E. L. Giglio, C. Justice, 2008 Global charactrerization of fire activity: toward defining

  1. Using Low Resolution Satellite Imagery for Yield Prediction and Yield Anomaly Detection

    Directory of Open Access Journals (Sweden)

    Oscar Rojas

    2013-04-01

    Full Text Available Low resolution satellite imagery has been extensively used for crop monitoring and yield forecasting for over 30 years and plays an important role in a growing number of operational systems. The combination of their high temporal frequency with their extended geographical coverage generally associated with low costs per area unit makes these images a convenient choice at both national and regional scales. Several qualitative and quantitative approaches can be clearly distinguished, going from the use of low resolution satellite imagery as the main predictor of final crop yield to complex crop growth models where remote sensing-derived indicators play different roles, depending on the nature of the model and on the availability of data measured on the ground. Vegetation performance anomaly detection with low resolution images continues to be a fundamental component of early warning and drought monitoring systems at the regional scale. For applications at more detailed scales, the limitations created by the mixed nature of low resolution pixels are being progressively reduced by the higher resolution offered by new sensors, while the continuity of existing systems remains crucial for ensuring the availability of long time series as needed by the majority of the yield prediction methods used today.

  2. MODELING AND SIMULATION OF HIGH RESOLUTION OPTICAL REMOTE SENSING SATELLITE GEOMETRIC CHAIN

    Directory of Open Access Journals (Sweden)

    Z. Xia

    2018-04-01

    Full Text Available The high resolution satellite with the longer focal length and the larger aperture has been widely used in georeferencing of the observed scene in recent years. The consistent end to end model of high resolution remote sensing satellite geometric chain is presented, which consists of the scene, the three line array camera, the platform including attitude and position information, the time system and the processing algorithm. The integrated design of the camera and the star tracker is considered and the simulation method of the geolocation accuracy is put forward by introduce the new index of the angle between the camera and the star tracker. The model is validated by the geolocation accuracy simulation according to the test method of the ZY-3 satellite imagery rigorously. The simulation results show that the geolocation accuracy is within 25m, which is highly consistent with the test results. The geolocation accuracy can be improved about 7 m by the integrated design. The model combined with the simulation method is applicable to the geolocation accuracy estimate before the satellite launching.

  3. Using high resolution satellite multi-temporal interferometry for landslide hazard detection in tropical environments: the case of Haiti

    Science.gov (United States)

    Wasowski, Janusz; Nutricato, Raffaele; Nitti, Davide Oscar; Bovenga, Fabio; Chiaradia, Maria Teresa; Piard, Boby Emmanuel; Mondesir, Philemon

    2015-04-01

    Synthetic aperture radar (SAR) multi-temporal interferometry (MTI) is one of the most promising satellite-based remote sensing techniques for fostering new opportunities in landslide hazard detection and assessment. MTI is attractive because it can provide very precise quantitative information on slow slope displacements of the ground surface over huge areas with limited vegetation cover. Although MTI is a mature technique, we are only beginning to realize the benefits of the high-resolution imagery that is currently acquired by the new generation radar satellites (e.g., COSMO-SkyMed, TerraSAR-X). In this work we demonstrate the potential of high resolution X-band MTI for wide-area detection of slope instability hazards even in tropical environments that are typically very harsh (eg. coherence loss) for differential interferometry applications. This is done by presenting an example from the island of Haiti, a tropical region characterized by dense and rapidly growing vegetation, as well as by significant climatic variability (two rainy seasons) with intense precipitation events. Despite the unfavorable setting, MTI processing of nearly 100 COSMO-SkyMed (CSK) mages (2011-2013) resulted in the identification of numerous radar targets even in some rural (inhabited) areas thanks to the high resolution (3 m) of CSK radar imagery, the adoption of a patch wise processing SPINUA approach and the presence of many man-made structures dispersed in heavily vegetated terrain. In particular, the density of the targets resulted suitable for the detection of some deep-seated and shallower landslides, as well as localized, very slow slope deformations. The interpretation and widespread exploitation of high resolution MTI data was facilitated by Google EarthTM tools with the associated high resolution optical imagery. Furthermore, our reconnaissance in situ checks confirmed that MTI results provided useful information on landslides and marginally stable slopes that can represent a

  4. 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.

  5. NITESat: A High Resolution, Full-Color, Light Pollution Imaging Satellite Mission

    Directory of Open Access Journals (Sweden)

    Ken Walczak

    2017-06-01

    Full Text Available The NITESat (Night Imaging and Tracking Experiment Satellite mission is a 2U CubeSat satellite designed for nighttime Earth imaging to quantify and characterize light pollution across the Midwestern United States. It is accompanied and supported by an array of ground-based light pollution observing stations called GONet (Ground Observing Network. NITESat is a pilot mission testing the potential for a simple and inexpensive (<$500,000 satellite to deliver high-resolution, three-color regional data of artificial light at night. In addition, GONet will form the core of an educational outreach program by establishing an array of all-sky monitors covering the imaging region of the satellite with 20+ full sky light pollution citizen-operated stations. This will provide synchronized data coinciding with the NITESat overpasses as well as providing near continuous night sky quality monitoring. If the initial mission is a success, the potential exists to expand the program into a low cost constellation of satellites capable of delivering global coverage. NITESat is being designed, built and will be operated by the Far Horizons program at the Adler Planetarium in Chicago, Illinois. Far Horizons is a student and volunteer centered program offering hands-on engineering and scientific research opportunities for education.

  6. Charge-coupled devices for particle detection with high spatial resolution

    International Nuclear Information System (INIS)

    Farley, F.J.; Damerell, C.J.S.; Gillman, A.R.; Wickens, F.J.

    1980-10-01

    The results of a study of the possible application of a thin microelectronic device (the charge-coupled device) to high energy physics as particle detectors with good spatial resolution which can distinguish between tracks emerging from the primary vertex and those from secondary vertices due to the decay of short lived particles with higher flavours, are reported. Performance characteristics indicating the spatial resolution, particle discrimination, time resolution, readout time and lifetime of such detectors have been obtained. (U.K.)

  7. Very high resolution airborne imagery for characterising spatial and temporal thermal patterns of braided rivers

    Science.gov (United States)

    Wawrzyniak, V.; Piégay, H.; Allemand, P.; Grandjean, P.

    2011-12-01

    (44°44' N, 4°56' E) is characterized by a nivo-pluvial regime while the Drac Noir (44°40' N, 6°18' E) is a glacial river. Very high spatial resolution thermal images are needed because braided rivers have multiple, often narrow, channels. Satellite and aircraft TIR do not have fine enough spatial resolutions and consequently we used a drone, a helicopter and a paraglider to acquire sets of images. The three vector types were equipped with a thermal camera (7.5-14 μm) which can detect noise equivalent temperature differences of ±0.08°C. Based on flight and camera parameter, we collected thermal images with very high spatial resolution (10-30 cm). At the same time as the thermal acquisitions, visible images were recorded and in situ measurements of water temperatures, velocities and discharges were taken.

  8. SUPER RESOLUTION RECONSTRUCTION BASED ON ADAPTIVE DETAIL ENHANCEMENT FOR ZY-3 SATELLITE IMAGES

    Directory of Open Access Journals (Sweden)

    H. Zhu

    2016-06-01

    Full Text Available Super-resolution reconstruction of sequence remote sensing image is a technology which handles multiple low-resolution satellite remote sensing images with complementary information and obtains one or more high resolution images. The cores of the technology are high precision matching between images and high detail information extraction and fusion. In this paper puts forward a new image super resolution model frame which can adaptive multi-scale enhance the details of reconstructed image. First, the sequence images were decomposed into a detail layer containing the detail information and a smooth layer containing the large scale edge information by bilateral filter. Then, a texture detail enhancement function was constructed to promote the magnitude of the medium and small details. Next, the non-redundant information of the super reconstruction was obtained by differential processing of the detail layer, and the initial super resolution construction result was achieved by interpolating fusion of non-redundant information and the smooth layer. At last, the final reconstruction image was acquired by executing a local optimization model on the initial constructed image. Experiments on ZY-3 satellite images of same phase and different phase show that the proposed method can both improve the information entropy and the image details evaluation standard comparing with the interpolation method, traditional TV algorithm and MAP algorithm, which indicate that our method can obviously highlight image details and contains more ground texture information. A large number of experiment results reveal that the proposed method is robust and universal for different kinds of ZY-3 satellite images.

  9. 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

  10. High-spatial resolution numerical simulations of in-water radiative transfer processes

    Science.gov (United States)

    D'Alimonte, D.; Kajiyama, T.; Zibordi, G.

    2012-04-01

    Monte Carlo (MC) simulations of radiative processes allow for addressing optical radiometric problems strictly linked to complex geometries. Within such a context, MC simulations have been used to investigate uncertainties affecting in-water radiometric measurements performed with free-fall optical profilers commonly utilized for the vicarious calibration of space sensors or the validation of satellite ocean color primary products (e.g, the normalized water leaving radiance). Specifically, a MC code (henceforth called MOX) has been developed to simulate in-water and above-water radiometric fields with high spatial-resolution (up to 1 cm) over a 2-dimensional (2D) domain of tens of meters. This has been achieved by exploiting high performance computing (HPC) solutions (e.g., parallel programs and job-scheduling based on novel performance prediction and optimization schemes) to trace up to 10^12 photons. A dedicated study, focused on the simulation of in-water radiometric fields, has led to the generation of virtual optical profiles accounting for perturbations due to light focusing effect by sea-surface gravity and capillary waves at a spatial resolution comparable to that of actual measurements. Different from field experiments, which are often constrained by environmental factors like illumination conditions and sea-water optical properties, numerical simulations permits analyzing realistic cases whereas allowing for a free input parameter selection. MOX simulations have shown that uncertainties induced by focusing effects upon radiometric data products can be reduced by slowing the deployment speed of free-fall optical profilers, rather than increasing the sampling frequency (i.e., while keeping the same number of samples per depth unit). This result has confirmed the appropriateness of profiling techniques (i.e., multicasting) so far solely supported by a limited number of field measurements and has additionally suggested the possibility of investigating further

  11. 3D high resolution tracking of ice flow using mutli-temporal stereo satellite imagery, Franz Josef Glacier, New Zealand

    Science.gov (United States)

    Leprince, S.; Lin, J.; Ayoub, F.; Herman, F.; Avouac, J.

    2013-12-01

    We present the latest capabilities added to the Co-Registration of Optically Sensed Images and Correlation (COSI-Corr) software, which aim at analyzing time-series of stereoscopic imagery to document 3D variations of the ground surface. We review the processing chain and present the new and improved modules for satellite pushbroom imagery, in particular the N-image bundle block adjustment to jointly optimize the viewing geometry of multiple acquisitions, the improved multi-scale image matching based on Semi-Global Matching (SGM) to extract high resolution topography, and the triangulation of multi-temporal disparity maps to derive 3D ground motion. In particular, processes are optimized to run on a cluster computing environment. This new suite of algorithms is applied to the study of Worldview stereo imagery above the Franz Josef, Fox, and Tasman Glaciers, New Zealand, acquired on 01/30/2013, 02/09/2013, and 02/28/2013. We derive high resolution (1m post-spacing) maps of ice flow in three dimensions, where ice velocities of up to 4 m/day are recorded. Images were collected in early summer during a dry and sunny period, which followed two weeks of unsettled weather with several heavy rainfall events across the Southern Alps. The 3D tracking of ice flow highlights the surface response of the glaciers to changes in effective pressure at the ice-bedrock interface due to heavy rainfall, at an unprecedented spatial resolution.

  12. Multi-Scale Analysis of Very High Resolution Satellite Images Using Unsupervised Techniques

    Directory of Open Access Journals (Sweden)

    Jérémie Sublime

    2017-05-01

    Full Text Available This article is concerned with the use of unsupervised methods to process very high resolution satellite images with minimal or little human intervention. In a context where more and more complex and very high resolution satellite images are available, it has become increasingly difficult to propose learning sets for supervised algorithms to process such data and even more complicated to process them manually. Within this context, in this article we propose a fully unsupervised step by step method to process very high resolution images, making it possible to link clusters to the land cover classes of interest. For each step, we discuss the various challenges and state of the art algorithms to make the full process as efficient as possible. In particular, one of the main contributions of this article comes in the form of a multi-scale analysis clustering algorithm that we use during the processing of the image segments. Our proposed methods are tested on a very high resolution image (Pléiades of the urban area around the French city of Strasbourg and show relevant results at each step of the process.

  13. Ionosphere influence on success rate of GPS ambiguity resolution in a satellite formation flying

    Science.gov (United States)

    Baroni, Leandro

    2015-10-01

    Satellite formation flying is one of the most promising technologies for future space missions. The distribution of sensors and payloads among different satellites provides more redundancy, flexibility, improved communication coverage, among other advantages. One of the fundamental issues in spacecraft formation flying is precise position and velocity determination between satellites. For missions in low Earth orbits, GPS system can meet the precision requirement in relative positioning, since the satellite dynamics is modeled properly. The key for high accuracy GPS relative positioning is to resolve the ambiguities to their integer values. Ambiguities resolved successfully can improve the positioning accuracy to decimetre or even millimetre-level. So, integer carrier phase ambiguity resolution is often a prerequisite for high precision GPS positioning. The determination of relative position was made using an extended Kalman filter. The filter must take into account imperfections in dynamic modeling of perturbations affecting the orbital flight, and changes in solar activity that affects the GPS signal propagation, for mitigating these effects on relative positioning accuracy. Thus, this work aims to evaluate the impact of ionosphere variation, caused by changes in solar activity, in success rate of ambiguity resolution. Using the Ambiguity Dilution of Precision (ADOP) concept, the ambiguity success rate is analyzed and the expected precision of the ambiguity-fixed solution is calculated. Evaluations were performed using actual data from GRACE mission and analyzed for their performance in real scenarios. Analyses were conducted in different configurations of relative position and during different levels of solar activity. Results bring the impact of various disturbances and modeling of solar activity level on the success rate of ambiguity resolution.

  14. A Flexible Spatiotemporal Method for Fusing Satellite Images with Different Resolutions

    Science.gov (United States)

    Studies of land surface dynamics in heterogeneous landscapes often require remote sensing data with high acquisition frequency and high spatial resolution. However, no single sensor meets this requirement. This study presents a new spatiotemporal data fusion method, the Flexible Spatiotemporal DAta ...

  15. Systematic neighborhood observations at high spatial resolution: methodology and assessment of potential benefits.

    Directory of Open Access Journals (Sweden)

    Tammy C M Leonard

    Full Text Available There is a growing body of public health research documenting how characteristics of neighborhoods are associated with differences in the health status of residents. However, little is known about how the spatial resolution of neighborhood observational data or community audits affects the identification of neighborhood differences in health. We developed a systematic neighborhood observation instrument for collecting data at very high spatial resolution (we observe each parcel independently and used it to collect data in a low-income minority neighborhood in Dallas, TX. In addition, we collected data on the health status of individuals residing in this neighborhood. We then assessed the inter-rater reliability of the instrument and compared the costs and benefits of using data at this high spatial resolution. Our instrument provides a reliable and cost-effect method for collecting neighborhood observational data at high spatial resolution, which then allows researchers to explore the impact of varying geographic aggregations. Furthermore, these data facilitate a demonstration of the predictive accuracy of self-reported health status. We find that ordered logit models of health status using observational data at different spatial resolution produce different results. This implies a need to analyze the variation in correlative relationships at different geographic resolutions when there is no solid theoretical rational for choosing a particular resolution. We argue that neighborhood data at high spatial resolution greatly facilitates the evaluation of alternative geographic specifications in studies of neighborhood and health.

  16. The Relaxation Wall: Experimental Limits to Improving MPI Spatial Resolution by Increasing Nanoparticle Core size.

    Science.gov (United States)

    Tay, Zhi Wei; Hensley, Daniel W; Vreeland, Erika C; Zheng, Bo; Conolly, Steven M

    2017-06-01

    Magnetic Particle Imaging (MPI) is a promising new tracer modality with zero attenuation in tissue, high contrast and sensitivity, and an excellent safety profile. However, the spatial resolution of MPI is currently around 1 mm in small animal scanners. Especially considering tradeoffs when scaling up MPI scanning systems to human size, this resolution needs to be improved for clinical applications such as angiography and brain perfusion. One method to improve spatial resolution is to increase the magnetic core size of the superparamagnetic nanoparticle tracers. The Langevin model of superparamagnetism predicts a cubic improvement of spatial resolution with magnetic core diameter. However, prior work has shown that the finite temporal response, or magnetic relaxation, of the tracer increases with magnetic core diameter and eventually leads to blurring in the MPI image. Here we perform the first wide ranging study of 5 core sizes between 18-32 nm with experimental quantification of the spatial resolution of each. Our results show that increasing magnetic relaxation with core size eventually opposes the expected Langevin behavior, causing spatial resolution to stop improving after 25 nm. Different MPI excitation strategies were experimentally investigated to mitigate the effect of magnetic relaxation. The results show that magnetic relaxation could not be fully mitigated for the larger core sizes and the cubic resolution improvement predicted by the Langevin was not achieved. This suggests that magnetic relaxation is a significant and unsolved barrier to achieving the high spatial resolutions predicted by the Langevin model for large core size SPIOs.

  17. NOAA high resolution sea surface winds data from Synthetic Aperture Radar (SAR) on the Sentinel-1 satellites

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set consists of high resolution sea surface winds data produced from Synthetic Aperture Radar (SAR) on board Sentinel-1A and Sentinel-1B satellites. This...

  18. The performance of the new enhanced-resolution satellite passive microwave dataset applied for snow water equivalent estimation

    Science.gov (United States)

    Pan, J.; Durand, M. T.; Jiang, L.; Liu, D.

    2017-12-01

    The newly-processed NASA MEaSures Calibrated Enhanced-Resolution Brightness Temperature (CETB) reconstructed using antenna measurement response function (MRF) is considered to have significantly improved fine-resolution measurements with better georegistration for time-series observations and equivalent field of view (FOV) for frequencies with the same monomial spatial resolution. We are looking forward to its potential for the global snow observing purposes, and therefore aim to test its performance for characterizing snow properties, especially the snow water equivalent (SWE) in large areas. In this research, two candidate SWE algorithms will be tested in China for the years between 2005 to 2010 using the reprocessed TB from the Advanced Microwave Scanning Radiometer for EOS (AMSR-E), with the results to be evaluated using the daily snow depth measurements at over 700 national synoptic stations. One of the algorithms is the SWE retrieval algorithm used for the FengYun (FY) - 3 Microwave Radiation Imager. This algorithm uses the multi-channel TB to calculate SWE for three major snow regions in China, with the coefficients adapted for different land cover types. The second algorithm is the newly-established Bayesian Algorithm for SWE Estimation with Passive Microwave measurements (BASE-PM). This algorithm uses the physically-based snow radiative transfer model to find the histogram of most-likely snow property that matches the multi-frequency TB from 10.65 to 90 GHz. It provides a rough estimation of snow depth and grain size at the same time and showed a 30 mm SWE RMS error using the ground radiometer measurements at Sodankyla. This study will be the first attempt to test it spatially for satellite. The use of this algorithm benefits from the high resolution and the spatial consistency between frequencies embedded in the new dataset. This research will answer three questions. First, to what extent can CETB increase the heterogeneity in the mapped SWE? Second, will

  19. Spatial Mapping of NEO 2008 EV5 Using Small Satellite Formation Flying and Steresoscopic Technology

    Science.gov (United States)

    Gonzalez, Juan; Singh Derewa, Chrishma

    2016-10-01

    NASA is currently developing the first-ever robotic Asteroid Redirect Robotic Mission (ARRM) to the near-Earth asteroid 2008 EV5 with the objective to capture a multi-ton boulder from the asteroids surface and use its mass to redirect its parent into a CIS lunar orbit where astronauts will study its physical and chemical composition.A critical step towards achieving this mission is to effectively map the target asteroid, identify the candidate boulder for retrieval and characterize its critical parameters. Currently, ARRM utilizes a laser altimeter to characterize the height of the boulders and mapping for final autonomous control of the capture. The proposed Lava-Kusha mission provides the increased of stereoscopic imaging and mapping, not only the Earthward side of the asteroid which has been observed for possible landing sites, but mapping the whole asteroid. LKM will enhance the fidelity of the data collected by the laser altimeter and gather improved topographic data for future Orion missions to 2008 EV5 once in cis lunar space.LKM consists of two low cost small satellites (6U) as a part of the ARRM. They will launch with ARRM as an integrated part of the system. Once at the target, this formation of pathfinder satellites will image the mission critical boulder to ensure the system design can support its removal. LKM will conduct a series of flybys prior to ARRM's rendezvous. LKMs stereoscopic cameras will provide detailed surveys of the boulder's terrain and environment to ensure ARRM can operate safely, reach the location and interface with the boulder. The LKM attitude control and cold gas propulsion system will enable formation maintenance maneuvers for global mapping of asteroid 2008 EV5 at an altitude of 100 km to a high-spatial resolution imaging altitude of 5 km.LKM will demonstrate formation flying in deep space and the reliability of stereoscopic cameras to precisely identify a specific target and provide physical characterization of an asteroid. An

  20. Retrieving aerosol in a cloudy environment: aerosol product availability as a function of spatial resolution

    Directory of Open Access Journals (Sweden)

    L. A. Remer

    2012-07-01

    Full Text Available The challenge of using satellite observations to retrieve aerosol properties in a cloudy environment is to prevent contamination of the aerosol signal from clouds, while maintaining sufficient aerosol product yield to satisfy specific applications. We investigate aerosol retrieval availability at different instrument pixel resolutions using the standard MODIS aerosol cloud mask applied to MODIS data and supplemented with a new GOES-R cloud mask applied to GOES data for a domain covering North America and surrounding oceans. Aerosol product availability is not the same as the cloud free fraction and takes into account the techniques used in the MODIS algorithm to avoid clouds, reduce noise and maintain sufficient numbers of aerosol retrievals. The inherent spatial resolution of each instrument, 0.5×0.5 km for MODIS and 1×1 km for GOES, is systematically degraded to 1×1, 2×2, 1×4, 4×4 and 8×8 km resolutions and then analyzed as to how that degradation would affect the availability of an aerosol retrieval, assuming an aerosol product resolution at 8×8 km. The analysis is repeated, separately, for near-nadir pixels and those at larger view angles to investigate the effect of pixel growth at oblique angles on aerosol retrieval availability. The results show that as nominal pixel size increases, availability decreases until at 8×8 km 70% to 85% of the retrievals available at 0.5 km, nadir, have been lost. The effect at oblique angles is to further decrease availability over land but increase availability over ocean, because sun glint is found at near-nadir view angles. Finer resolution sensors (i.e., 1×1, 2×2 or even 1×4 km will retrieve aerosols in partly cloudy scenes significantly more often than sensors with nadir views of 4×4 km or coarser. Large differences in the results of the two cloud masks designed for MODIS aerosol and GOES cloud products strongly reinforce that cloud masks must be developed with specific purposes in mind and

  1. Inter-Comparison of High-Resolution Satellite Precipitation Products over Central Asia

    Directory of Open Access Journals (Sweden)

    Hao Guo

    2015-06-01

    Full Text Available This paper examines the spatial error structures of eight precipitation estimates derived from four different satellite retrieval algorithms including TRMM Multi-satellite Precipitation Analysis (TMPA, Climate Prediction Center morphing technique (CMORPH, Global Satellite Mapping of Precipitation (GSMaP and Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN. All the original satellite and bias-corrected products of each algorithm (3B42RTV7 and 3B42V7, CMORPH_RAW and CMORPH_CRT, GSMaP_MVK and GSMaP_Gauge, PERSIANN_RAW and PERSIANN_CDR are evaluated against ground-based Asian Precipitation-Highly Resolved Observational Data Integration Towards Evaluation of Water Resources (APHRODITE over Central Asia for the period of 2004 to 2006. The analyses show that all products except PERSIANN exhibit overestimation over Aral Sea and its surrounding areas. The bias-correction improves the quality of the original satellite TMPA products and GSMaP significantly but slightly in CMORPH and PERSIANN over Central Asia. 3B42RTV7 overestimates precipitation significantly with large Relative Bias (RB (128.17% while GSMaP_Gauge shows consistent high correlation coefficient (CC (>0.8 but RB fluctuates between −57.95% and 112.63%. The PERSIANN_CDR outperforms other products in winter with the highest CC (0.67. Both the satellite-only and gauge adjusted products have particularly poor performance in detecting rainfall events in terms of lower POD (less than 65%, CSI (less than 45% and relatively high FAR (more than 35%.

  2. SPATIAL AND TEMPORAL ANALYSIS OF SEA SURFACE SALINITY USING SATELLITE IMAGERY IN GULF OF MEXICO

    Directory of Open Access Journals (Sweden)

    S. Rajabi

    2017-09-01

    Full Text Available The recent development of satellite sea surface salinity (SSS observations has enabled us to analyse SSS variations with high spatiotemporal resolution. In this regards, The Level3-version4 data observed by Aquarius are used to examine the variability of SSS in Gulf of Mexico for the 2012-2014 time periods. The highest SSS value occurred in April 2013 with the value of 36.72 psu while the lowest value (35.91 psu was observed in July 2014. Based on the monthly distribution maps which will be demonstrated in the literature, it was observed that east part of the region has lower salinity values than the west part for all months mainly because of the currents which originate from low saline waters of the Caribbean Sea and furthermore the eastward currents like loop current. Also the minimum amounts of salinity occur in coastal waters where the river runoffs make fresh the high saline waters. Our next goal here is to study the patterns of sea surface temperature (SST, chlorophyll-a (CHLa and fresh water flux (FWF and examine the contributions of them to SSS variations. So by computing correlation coefficients, the values obtained for SST, FWF and CHLa are 0.7, 0.22 and 0.01 respectively which indicated high correlation of SST on SSS variations. Also by considering the spatial distribution based on the annual means, it found that there is a relationship between the SSS, SST, CHLa and the latitude in the study region which can be interpreted by developing a mathematical model.

  3. Evaluating the Impact of Spatial Resolution of Landsat Predictors on the Accuracy of Biomass Models for Large-area Estimation Across the Eastern USA

    Science.gov (United States)

    Deo, R. K.; Domke, G. M.; Russell, M.; Woodall, C. W.

    2017-12-01

    Landsat data have been widely used to support strategic forest inventory and management decisions despite the limited success of passive optical remote sensing for accurate estimation of aboveground biomass (AGB). The archive of publicly available Landsat data, available at 30-m spatial resolutions since 1984, has been a valuable resource for cost-effective large-area estimation of AGB to inform national requirements such as for the US national greenhouse gas inventory (NGHGI). In addition, other optical satellite data such as MODIS imagery of wider spatial coverage and higher temporal resolution are enriching the domain of spatial predictors for regional scale mapping of AGB. Because NGHGIs require national scale AGB information and there are tradeoffs in the prediction accuracy versus operational efficiency of Landsat, this study evaluated the impact of various resolutions of Landsat predictors on the accuracy of regional AGB models across three different sites in the eastern USA: Maine, Pennsylvania-New Jersey, and South Carolina. We used recent national forest inventory (NFI) data with numerous Landsat-derived predictors at ten different spatial resolutions ranging from 30 to 1000 m to understand the optimal spatial resolution of the optical data for enhanced spatial inventory of AGB for NGHGI reporting. Ten generic spatial models at different spatial resolutions were developed for all sites and large-area estimates were evaluated (i) at the county-level against the independent designed-based estimates via the US NFI Evalidator tool and (ii) within a large number of strips ( 1 km wide) predicted via LiDAR metrics at a high spatial resolution. The county-level estimates by the Evalidator and Landsat models were statistically equivalent and produced coefficients of determination (R2) above 0.85 that varied with sites and resolution of predictors. The mean and standard deviation of county-level estimates followed increasing and decreasing trends, respectively

  4. TRANSFER OF TECHNOLOGY FOR CADASTRAL MAPPING IN TAJIKISTAN USING HIGH RESOLUTION SATELLITE DATA

    Directory of Open Access Journals (Sweden)

    R. Kaczynski

    2012-07-01

    Full Text Available European Commission funded project entitled: "Support to the mapping and certification capacity of the Agency of Land Management, Geodesy and Cartography" in Tajikistan was run by FINNMAP FM-International and Human Dynamics from Nov. 2006 to June 2011. The Agency of Land Management, Geodesy and Cartography is the state agency responsible for development, implementation, monitoring and evaluation of state policies on land tenure and land management, including the on-going land reform and registration of land use rights. The specific objective was to support and strengthen the professional capacity of the "Fazo" Institute in the field of satellite geodesy, digital photogrammetry, advanced digital satellite image processing of high resolution satellite data and digital cartography. Lectures and on-the-job trainings for the personnel of "Fazo" and Agency in satellite geodesy, digital photogrammetry, cartography and the use of high resolution satellite data for cadastral mapping have been organized. Standards and Quality control system for all data and products have been elaborated and implemented in the production line. Technical expertise and trainings in geodesy, photogrammetry and satellite image processing to the World Bank project "Land Registration and Cadastre System for Sustainable Agriculture" has also been completed in Tajikistan. The new map projection was chosen and the new unclassified geodetic network has been established for all of the country in which all agricultural parcel boundaries are being mapped. IKONOS, QuickBird and WorldView1 panchromatic data have been used for orthophoto generation. Average accuracy of space triangulation of non-standard (long up to 90km satellite images of QuickBird Pan and IKONOS Pan on ICPs: RMSEx = 0.5m and RMSEy = 0.5m have been achieved. Accuracy of digital orthophoto map is RMSExy = 1.0m. More then two and half thousands of digital orthophoto map sheets in the scale of 1:5000 with pixel size 0.5m

  5. Influence of Regional Climate Model spatial resolution on wind climates

    Science.gov (United States)

    Pryor, S. C.; Barthelmie, R. J.; Nikulin, G.; Jones, C.

    2010-12-01

    Global and regional climate models are being run at increasingly fine horizontal and vertical resolution with the goal of increased skill. However, relatively few studies have quantified the change in modeled wind climates that derives from applying a Regional Climate Model (RCM) at varying resolutions, and the response to varying resolution may be highly non-linear since most models run in climate mode are hydrostatic. Thus, herein we examine the influence of grid-resolution on modelled wind speeds and gusts and derived extremes thereof over southern Scandinavia using output from the Rossby Centre (RCA3) RCM run at four different resolutions from 50 x 50 km to 6 x 6 km, and with two different vertical grid-spacings. Domain averaged fifty-year return period wind speeds and wind gusts derived using the method of moments approach to compute the Gumbel parameters, increase with resolution (Table 1), though the change is strongly mediated by the model grid-cell surface characteristics. Power spectra of the 3-hourly model time-step ‘instantaneous’ wind speeds and daily wind gusts at all four resolutions show clear peaks in the variance associated with bi-annual, annual, seasonal and synoptic frequencies. The variance associated with these peaks is enhanced with increased resolution, though not in a monotonic fashion, and is more marked in wind gusts than wind speeds. Relative to in situ observations, the model generally underestimates the variance, particularly associated with the synoptic time scale, even for the highest resolution simulations. There is some evidence to suggest that the change in the power spectra with horizontal resolution is less marked in the transition from 12.5 km to 6.25 km, than from 50 to 25 km, or 25 km to 12.5 km.Table 1. Domain averaged mean annual wind speed (U), 50-year return period extreme wind speed (U50yr) and wind gust (Gust50yr) (m/s) from the four RCA3 simulations at different resolution based on output from 1987-2008. The

  6. Scaling Properties of Arctic Sea Ice Deformation in a High‐Resolution Viscous‐Plastic Sea Ice Model and in Satellite Observations

    Science.gov (United States)

    Losch, Martin; Menemenlis, Dimitris

    2018-01-01

    Abstract Sea ice models with the traditional viscous‐plastic (VP) rheology and very small horizontal grid spacing can resolve leads and deformation rates localized along Linear Kinematic Features (LKF). In a 1 km pan‐Arctic sea ice‐ocean simulation, the small‐scale sea ice deformations are evaluated with a scaling analysis in relation to satellite observations of the Envisat Geophysical Processor System (EGPS) in the Central Arctic. A new coupled scaling analysis for data on Eulerian grids is used to determine the spatial and temporal scaling and the coupling between temporal and spatial scales. The spatial scaling of the modeled sea ice deformation implies multifractality. It is also coupled to temporal scales and varies realistically by region and season. The agreement of the spatial scaling with satellite observations challenges previous results with VP models at coarser resolution, which did not reproduce the observed scaling. The temporal scaling analysis shows that the VP model, as configured in this 1 km simulation, does not fully resolve the intermittency of sea ice deformation that is observed in satellite data.

  7. Scaling Properties of Arctic Sea Ice Deformation in a High-Resolution Viscous-Plastic Sea Ice Model and in Satellite Observations.

    Science.gov (United States)

    Hutter, Nils; Losch, Martin; Menemenlis, Dimitris

    2018-01-01

    Sea ice models with the traditional viscous-plastic (VP) rheology and very small horizontal grid spacing can resolve leads and deformation rates localized along Linear Kinematic Features (LKF). In a 1 km pan-Arctic sea ice-ocean simulation, the small-scale sea ice deformations are evaluated with a scaling analysis in relation to satellite observations of the Envisat Geophysical Processor System (EGPS) in the Central Arctic. A new coupled scaling analysis for data on Eulerian grids is used to determine the spatial and temporal scaling and the coupling between temporal and spatial scales. The spatial scaling of the modeled sea ice deformation implies multifractality. It is also coupled to temporal scales and varies realistically by region and season. The agreement of the spatial scaling with satellite observations challenges previous results with VP models at coarser resolution, which did not reproduce the observed scaling. The temporal scaling analysis shows that the VP model, as configured in this 1 km simulation, does not fully resolve the intermittency of sea ice deformation that is observed in satellite data.

  8. SACRA - a method for the estimation of global high-resolution crop calendars from a satellite-sensed NDVI

    Science.gov (United States)

    Kotsuki, S.; Tanaka, K.

    2015-11-01

    To date, many studies have performed numerical estimations of biomass production and agricultural water demand to understand the present and future supply-demand relationship. A crop calendar (CC), which defines the date or month when farmers sow and harvest crops, is an essential input for the numerical estimations. This study aims to present a new global data set, the SAtellite-derived CRop calendar for Agricultural simulations (SACRA), and to discuss advantages and disadvantages compared to existing census-based and model-derived products. We estimate global CC at a spatial resolution of 5 arcmin using satellite-sensed normalized difference vegetation index (NDVI) data, which corresponds to vegetation vitality and senescence on the land surface. Using the time series of the NDVI averaged from three consecutive years (2004-2006), sowing/harvesting dates are estimated for six crops (temperate-wheat, snow-wheat, maize, rice, soybean and cotton). We assume time series of the NDVI represent the phenology of one dominant crop and estimate CCs of the dominant crop in each grid. The dominant crops are determined using harvested areas based on census-based data. The cultivation period of SACRA is identified from the time series of the NDVI; therefore, SACRA considers current effects of human decisions and natural disasters. The difference between the estimated sowing dates and other existing products is less than 2 months (sowing in spring or fall) is a major source of error in global CC estimations.

  9. High-resolution land surface fluxes from satellite and reanalysis data (HOLAPS v1.0): evaluation and uncertainty assessment

    Science.gov (United States)

    Loew, Alexander; Peng, Jian; Borsche, Michael

    2016-07-01

    Surface water and energy fluxes are essential components of the Earth system. Surface latent heat fluxes provide major energy input to the atmosphere. Despite the importance of these fluxes, state-of-the-art data sets of surface energy and water fluxes largely differ. The present paper introduces a new framework for the estimation of surface energy and water fluxes at the land surface, which allows for temporally and spatially high-resolved flux estimates at the quasi-global scale (50° S, 50° N) (High resOlution Land Atmosphere Parameters from Space - HOLAPS v1.0). The framework makes use of existing long-term satellite and reanalysis data records and ensures internally consistent estimates of the surface radiation and water fluxes. The manuscript introduces the technical details of the developed framework and provides results of a comprehensive sensitivity and evaluation study. Overall the root mean square difference (RMSD) was found to be 51.2 (30.7) W m-2 for hourly (daily) latent heat flux, and 84 (38) W m-2 for sensible heat flux when compared against 48 FLUXNET stations worldwide. The largest uncertainties of latent heat flux and net radiation were found to result from uncertainties in the solar radiation flux obtained from satellite data products.

  10. Improved Spatial Resolution in Thick, Fully-Depleted CCDs with Enhanced Red Sensitivity

    International Nuclear Information System (INIS)

    Fairfield, Jessamyn A.

    2005-01-01

    The point spread function (PSF) is an important measure of spatial resolution in CCDs for point-like objects, since it can affect use in imaging and spectroscopic applications. We present new data and theoretical developments in the study of lateral charge diffusion in thick, fully-depleted charge-coupled devices (CCDs) developed at Lawrence Berkeley National Laboratory (LBNL). Because they are fully depleted, the LBNL devices have no field-free region, and diffusion can be controlled through the application of an external bias voltage. We give results for a 3512x3512 format, 10.5 ?m pixel back-illuminated p-channel CCD developed for the SuperNova/Acceleration Probe (SNAP), a proposed satellite-based experiment designed to study dark energy. The PSF was measured at substrate bias voltages between 3 V and 115 V. At a bias voltage of 115V, we measure an rms diffusion of 3.7 ± 0.2 (micro)m. Lateral charge diffusion in LBNL CCDs is thus expected to meet the SNAP requirements

  11. A method for examining temporal changes in cyanobacterial harmful algal bloom spatial extent using satellite remote sensing

    Science.gov (United States)

    Urquhart, Erin A.; Schaeffer, Blake A.; Stumpf, Richard P.; Loftin, Keith A.; Werdell, P. Jeremy

    2017-01-01

    Cyanobacterial harmful algal blooms (CyanoHAB) are thought to be increasing globally over the past few decades, but relatively little quantitative information is available about the spatial extent of blooms. Satellite remote sensing provides a potential technology for identifying cyanoHABs in multiple water bodies and across geo-political boundaries. An assessment method was developed using MEdium Resolution Imaging Spectrometer (MERIS) imagery to quantify cyanoHAB surface area extent, transferable to different spatial areas, in Florida, Ohio, and California for the test period of 2008 to 2012. Temporal assessment was used to evaluate changes in satellite resolvable inland waterbodies for each state of interest. To further assess cyanoHAB risk within the states, the World Health Organization’s (WHO) recreational guidance level thresholds were used to categorize surface area of cyanoHABs into three risk categories: low, moderate, and high-risk bloom area. Results showed that in Florida, the area of cyanoHABs increased largely due to observed increases in high-risk bloom area. California exhibited a slight decrease in cyanoHAB extent, primarily attributed to decreases in Northern California. In Ohio (excluding Lake Erie), little change in cyanoHAB surface area was observed. This study uses satellite remote sensing to quantify changes in inland cyanoHAB surface area across numerous water bodies within an entire state. The temporal assessment method developed here will be relevant into the future as it is transferable to the Ocean Land Colour Instrument (OLCI) on Sentinel-3A/3B missions.

  12. Spatial and temporal interpolation of satellite-based aerosol optical depth measurements over North America using B-splines

    Science.gov (United States)

    Pfister, Nicolas; O'Neill, Norman T.; Aube, Martin; Nguyen, Minh-Nghia; Bechamp-Laganiere, Xavier; Besnier, Albert; Corriveau, Louis; Gasse, Geremie; Levert, Etienne; Plante, Danick

    2005-08-01

    Satellite-based measurements of aerosol optical depth (AOD) over land are obtained from an inversion procedure applied to dense dark vegetation pixels of remotely sensed images. The limited number of pixels over which the inversion procedure can be applied leaves many areas with little or no AOD data. Moreover, satellite coverage by sensors such as MODIS yields only daily images of a given region with four sequential overpasses required to straddle mid-latitude North America. Ground based AOD data from AERONET sun photometers are available on a more continuous basis but only at approximately fifty locations throughout North America. The object of this work is to produce a complete and coherent mapping of AOD over North America with a spatial resolution of 0.1 degree and a frequency of three hours by interpolating MODIS satellite-based data together with available AERONET ground based measurements. Before being interpolated, the MODIS AOD data extracted from different passes are synchronized to the mapping time using analyzed wind fields from the Global Multiscale Model (Meteorological Service of Canada). This approach amounts to a trajectory type of simplified atmospheric dynamics correction method. The spatial interpolation is performed using a weighted least squares method applied to bicubic B-spline functions defined on a rectangular grid. The least squares method enables one to weight the data accordingly to the measurement errors while the B-splines properties of local support and C2 continuity offer a good approximation of AOD behaviour viewed as a function of time and space.

  13. AN ENHANCED ALGORITHM FOR AUTOMATIC RADIOMETRIC HARMONIZATION OF HIGH-RESOLUTION OPTICAL SATELLITE IMAGERY USING PSEUDOINVARIANT FEATURES AND LINEAR REGRESSION

    Directory of Open Access Journals (Sweden)

    M. Langheinrich

    2017-05-01

    Full Text Available The growing number of available optical remote sensing data providing large spatial and temporal coverage enables the coherent and gapless observation of the earth’s surface on the scale of whole countries or continents. To produce datasets of that size, individual satellite scenes have to be stitched together forming so-called mosaics. Here the problem arises that the different images feature varying radiometric properties depending on the momentary acquisition conditions. The interpretation of optical remote sensing data is to a great extent based on the analysis of the spectral composition of an observed surface reflection. Therefore the normalization of all images included in a large image mosaic is necessary to ensure consistent results concerning the application of procedures to the whole dataset. In this work an algorithm is described which enables the automated spectral harmonization of satellite images to a reference scene. As the stable and satisfying functionality of the proposed algorithm was already put to operational use to process a high number of SPOT-4/-5, IRS LISS-III and Landsat-5 scenes in the frame of the European Environment Agency's Copernicus/GMES Initial Operations (GIO High-Resolution Layer (HRL mapping of the HRL Forest for 20 Western, Central and (SouthEastern European countries, it is further evaluated on its reliability concerning the application to newer Sentinel-2 multispectral imaging products. The results show that the algorithm is comparably efficient for the processing of satellite image data from sources other than the sensor configurations it was originally designed for.

  14. Using high-resolution satellite imagery to assess populations of animals in the Antarctic

    Science.gov (United States)

    LaRue, Michelle Ann

    The Southern Ocean is one of the most rapidly-changing ecosystems on the planet due to the effects of climate change and commercial fishing for ecologically-important krill and fish. It is imperative that populations of indicator species, such as penguins and seals, be monitored at regional- to global scales to decouple the effects of climate and anthropogenic changes for appropriate ecosystem-based management of the Southern Ocean. Remotely monitoring populations through high-resolution satellite imagery is currently the only feasible way to gain information about population trends of penguins and seals in Antarctica. In my first chapter, I review the literature where high-resolution satellite imagery has been used to assess populations of animals in polar regions. Building on this literature, my second chapter focuses on estimating changes in abundance in the Weddell seal population in Erebus Bay. I found a strong correlation between ground and satellite counts, and this finding provides an alternate method for assessing populations of Weddell seals in areas where less is known about population status. My third chapter explores how size of the guano stain of Adelie penguins can be used to predict population size. Using high-resolution imagery and ground counts, I built a model to estimate the breeding population of Adelie penguins using a supervised classification to estimate guano size. These results suggest that the size of guano stain is an accurate predictor of population size, and can be applied to estimate remote Adelie penguin colonies. In my fourth chapter, I use air photos, satellite imagery, climate and mark-resight data to determine that climate change has positively impacted the population of Adelie penguins at Beaufort Island through a habitat release that ultimately affected the dynamics within the southern Ross Sea metapopulation. Finally, for my fifth chapter I combined the literature with observations from aerial surveys and satellite imagery to

  15. Assessing Building Vulnerability to Tsunami Hazards using Very High Resolution Satellite Imagery (Case : Cilacap, Indonesia)

    Science.gov (United States)

    Sumaryono, S.; Strunz, G.; Ludwig, R.; Post, J.; Zosseder, K.; Mück, M.

    2009-04-01

    The big tsunami disaster occurring on 26 December 2004 has destroyed many cities along the Indian Ocean rim and killed approximately 300,000 people and destroyed buildings and city infrastructures making it the deadliest tsunami as well as one of the deadliest natural disasters in recorded history. Furthermore, there are large numbers of world's cities located near coastal lines prone to tsunami hazard. Anticipation measures and disaster mitigation must be taken in order to minimize the negative impacts that may hit those living and built in the cities. The assessment of building vulnerability is an important measure in order to minimize disaster risks to the city. Measuring vulnerability for large number of buildings using conventional method is time consuming and costly. This paper offers a comprehensive framework in assessing building vulnerability by combining field assessment and remote sensing techniques. Field assessment was based on quantitative and qualitative building structural analysis and remote sensing technique was undertaken using object-oriented classification. Very high resolution satellite imagery (quickbird) and elevation data were employed in the remote sensing technique. Each building in the study area was classified automatically into 4 classes (Class A, B, C and Vertical Evacuation) based on their level of vulnerability to tsunami hazard using parameters extracted from remotely sensed data. This paper presents results from Cilacap City, South coast of Java, Indonesia. The research work was performed in the framework of the GITEWS project. The results show that remote sensing and GIS approaches are promising to be applied to measure building vulnerability to tsunami hazards. Outcomes of the research consist of : new concepts in assessing urban vulnerability to tsunami hazard, new algorithm for extracting information from very high resolution satellite images, map of building vulnerability and recommendations concerning to urban vulnerability

  16. Toward a High-Resolution Monitoring of Continental Surface Water Extent and Dynamics, at Global Scale: from GIEMS (Global Inundation Extent from Multi-Satellites) to SWOT (Surface Water Ocean Topography)

    Science.gov (United States)

    Prigent, Catherine; Lettenmaier, Dennis P.; Aires, Filipe; Papa, Fabrice

    2016-03-01

    Up to now, high-resolution mapping of surface water extent from satellites has only been available for a few regions, over limited time periods. The extension of the temporal and spatial coverage was difficult, due to the limitation of the remote sensing technique [e.g., the interaction of the radiation with vegetation or cloud for visible observations or the temporal sampling with the synthetic aperture radar (SAR)]. The advantages and the limitations of the various satellite techniques are reviewed. The need to have a global and consistent estimate of the water surfaces over long time periods triggered the development of a multi-satellite methodology to obtain consistent surface water all over the globe, regardless of the environments. The Global Inundation Extent from Multi-satellites (GIEMS) combines the complementary strengths of satellite observations from the visible to the microwave, to produce a low-resolution monthly dataset (0.25^circ × 0.25^circ) of surface water extent and dynamics. Downscaling algorithms are now developed and applied to GIEMS, using high-spatial-resolution information from visible, near-infrared, and synthetic aperture radar (SAR) satellite images, or from digital elevation models. Preliminary products are available down to 500-m spatial resolution. This work bridges the gaps and prepares for the future NASA/CNES Surface Water Ocean Topography (SWOT) mission to be launched in 2020. SWOT will delineate surface water extent estimates and their water storage with an unprecedented spatial resolution and accuracy, thanks to a SAR in an interferometry mode. When available, the SWOT data will be adopted to downscale GIEMS, to produce a long time series of water surfaces at global scale, consistent with the SWOT observations.

  17. Megapixel Longwave Infrared SLS FPAs for High Spatial Resolution Earth Observing Missions, Phase I

    Data.gov (United States)

    National Aeronautics and Space Administration — Earth observing missions like NASA's LANDSAT Data Continuity Mission - Thermal Infrared Sensor (LDCM-TIRS) require greater spatial resolution of the earth than the ~...

  18. Megapixel Longwave Infrared SLS FPAs for High Spatial Resolution Earth Observing Missions, Phase II

    Data.gov (United States)

    National Aeronautics and Space Administration — Earth observing missions like NASA's LANDSAT Data Continuity Mission - Thermal Infrared Sensor (LDCM-TIRS) require greater spatial resolution of the earth than the ~...

  19. Single-acquisition method for simultaneous determination of extrinsic gamma-camera sensitivity and spatial resolution

    Energy Technology Data Exchange (ETDEWEB)

    Santos, J.A.M. [Servico de Fisica Medica, Instituto Portugues de Oncologia Francisco Gentil do Porto, E.P.E., Rua Dr. Antonio Bernardino de Almeida, 4200-072 Porto (Portugal)], E-mail: a.miranda@portugalmail.pt; Sarmento, S. [Servico de Fisica Medica, Instituto Portugues de Oncologia Francisco Gentil do Porto, E.P.E., Rua Dr. Antonio Bernardino de Almeida, 4200-072 Porto (Portugal); Alves, P.; Torres, M.C. [Departamento de Fisica da Universidade do Porto, Rua do Campo Alegre 687, 4169-007 Porto (Portugal); Bastos, A.L. [Servico de Medicina Nuclear, Instituto Portugues de Oncologia Francisco Gentil do Porto, E.P.E., Rua Dr. Antonio Bernardino de Almeida, 4200-072 Porto (Portugal); Ponte, F. [Servico de Fisica Medica, Instituto Portugues de Oncologia Francisco Gentil do Porto, E.P.E., Rua Dr. Antonio Bernardino de Almeida, 4200-072 Porto (Portugal)

    2008-01-15

    A new method for measuring simultaneously both the extrinsic sensitivity and spatial resolution of a gamma-camera in a single planar acquisition was implemented. A dual-purpose phantom (SR phantom; sensitivity/resolution) was developed, tested and the results compared with other conventional methods used for separate determination of these two important image quality parameters. The SR phantom yielded reproducible and accurate results, allowing an immediate visual inspection of the spatial resolution as well as the quantitative determination of the contrast for six different spatial frequencies. It also proved to be useful in the estimation of the modulation transfer function (MTF) of the image formation collimator/detector system at six different frequencies and can be used to estimate the spatial resolution as function of the direction relative to the digital matrix of the detector.

  20. Impact of precipitation spatial resolution on the hydrological response of an integrated distributed water resources model

    DEFF Research Database (Denmark)

    Fu, Suhua; Sonnenborg, Torben; Jensen, Karsten Høgh

    2011-01-01

    Precipitation is a key input variable to hydrological models, and the spatial variability of the input is expected to impact the hydrological response predicted by a distributed model. In this study, the effect of spatial resolution of precipitation on runoff , recharge and groundwater head...... was analyzed in the Alergaarde catchment in Denmark. Six different precipitation spatial resolutions were used as inputs to a physically based, distributed hydrological model, the MIKE SHE model. The results showed that the resolution of precipitation input had no apparent effect on annual water balance...... of the total catchment and runoff discharge hydrograph at watershed outlet. On the other hand, groundwater recharge and groundwater head were both aff ected. The impact of the spatial resolution of precipitation input is reduced with increasing catchment size. The effect on stream discharge is relatively low...

  1. Fine Resolution Air Quality Monitoring from a Small Satellite: CHRIS/PROBA

    Directory of Open Access Journals (Sweden)

    Man Sing Wong

    2008-11-01

    Full Text Available Current remote sensing techniques fail to address the task of air quality monitoring over complex regions where multiple pollution sources produce high spatial variability. This is due to a lack of suitable satellite-sensor combinations and appropriate aerosol optical thickness (AOT retrieval algorithms. The new generation of small satellites, with their lower costs and greater flexibility has the potential to address this problem, with customised platform-sensor combinations dedicated to monitoring single complex regions or mega-cities. This paper demonstrates the ability of the European Space Agency’s small satellite sensor CHRIS/PROBA to provide reliable AOT estimates at a spatially detailed level over Hong Kong, using a modified version of the dense dark vegetation (DDV algorithm devised for MODIS. Since CHRIS has no middle-IR band such as the MODIS 2,100 nm band which is transparent to fine aerosols, the longest waveband of CHRIS, the 1,019 nm band was used to approximate surface reflectance, by the subtraction of an offset derived from synchronous field reflectance spectra. Aerosol reflectance in the blue and red bands was then obtained from the strong empirical relationship observed between the CHRIS 1,019 nm, and the blue and red bands respectively. AOT retrievals for three different dates were shown to be reliable, when compared with AERONET and Microtops II sunphotometers, and a Lidar, as well as air quality data at ground stations. The AOT images exhibited considerable spatial variability over the 11 x 11km image area and were able to indicate both local and long distance sources.

  2. The High Visible Resolution (HVR) instrument of the spot ground observation satellite

    Science.gov (United States)

    Otrio, G.

    1980-01-01

    Two identical high resolution cameras, capable of attaining a track width of 116 km in an almost vertical line of sight from the two 60 km images of each instrument, will be carried on the initial mission of the space observation of Earth satellite (SPOT). Specifications for the instrument, including the telescope and CCD devices are summarized. The present status of development is described including the optical characteristics, structure and thermal control, detector assembly, electronic equipment, and calibration. SPOT mission objectives include the developments relating to soil use, the exploration of EART Earth resources, the discrimination of plant species, and cartography.

  3. Evaluating the influence of spatial resolutions of DEM on watershed ...

    Indian Academy of Sciences (India)

    Application of effective models in hydrological studies is vital to understand the natural pro- cesses occurring at .... 200, 300, 500 and 1000 m) on the uncertainties of. SWAT-predicted runoff, sediment, nitrate nitrogen ... lyzing the uncertainties of SWAT outputs due to. DEM resolution on annual and monthly basis (Lin et al.

  4. Classification of semiurban landscapes from very high-resolution satellite images using a regionalized multiscale segmentation approach

    Science.gov (United States)

    Kavzoglu, Taskin; Erdemir, Merve Yildiz; Tonbul, Hasan

    2017-07-01

    In object-based image analysis, obtaining representative image objects is an important prerequisite for a successful image classification. The major threat is the issue of scale selection due to the complex spatial structure of landscapes portrayed as an image. This study proposes a two-stage approach to conduct regionalized multiscale segmentation. In the first stage, an initial high-level segmentation is applied through a "broadscale," and a set of image objects characterizing natural borders of the landscape features are extracted. Contiguous objects are then merged to create regions by considering their normalized difference vegetation index resemblance. In the second stage, optimal scale values are estimated for the extracted regions, and multiresolution segmentation is applied with these settings. Two satellite images with different spatial and spectral resolutions were utilized to test the effectiveness of the proposed approach and its transferability to different geographical sites. Results were compared to those of image-based single-scale segmentation and it was found that the proposed approach outperformed the single-scale segmentations. Using the proposed methodology, significant improvement in terms of segmentation quality and classification accuracy (up to 5%) was achieved. In addition, the highest classification accuracies were produced using fine-scale values.

  5. Monte Carlo simulation studies of spatial resolution in magnification mammography using the edge method

    Science.gov (United States)

    Koutalonis, M.; Delis, H.; Spyrou, G.; Costaridou, L.; Tzanakos, G.; Panayiotakis, G.

    2009-05-01

    Small sized focal spots are very essential when magnification is performed in mammography, as they represent the only way to reduce the geometrical unsharpness. The effect of focal spot size on spatial resolution in contact mammography or under magnification has been experimentally investigated but, due to construction limitations, only a small range of focal spot sizes has been studied. In this study, a Monte Carlo simulation model is utilized in order to examine the effect of a wide range of focal spots on spatial resolution under magnification conditions. A thick sharp edge consisted of lead was imaged under various conditions and the corresponding spatial resolution was calculated through the Modulation Transfer Function. Results demonstrate that increasing the degree of magnification from 1.0 to 2.0 induces degradation on spatial resolution which varies from 49% for a 0.04 mm focal spot to 53.2% for a 0.14 mm one. Larger focal spots cause higher degradation even for low magnification. Focal spots larger than 0.10 mm are considered appropriate only for low degrees of magnification according to the IAEA regulations that designate spatial resolution for mammography higher than 12 lp/mm. However, for high degrees of magnification the focal spot size should be even smaller. The construction of a microfocus of 0.04 mm would result in acceptable values of spatial resolution even for degrees of magnification up to 1.9.

  6. Monte Carlo simulation studies of spatial resolution in magnification mammography using the edge method

    Energy Technology Data Exchange (ETDEWEB)

    Koutalonis, M; Delis, H; Costaridou, L; Panayiotakis, G [University of Patras, Department of Medical Physics, 26500 Rio-Patras (Greece); Spyrou, G [Academy of Athens, Biomedical Research Foundation, 11527 Athens (Greece); Tzanakos, G [University of Athens, Department of Physics, 15771 Athens (Greece)], E-mail: mkoutalonis@med.upatras.gr

    2009-05-15

    Small sized focal spots are very essential when magnification is performed in mammography, as they represent the only way to reduce the geometrical unsharpness. The effect of focal spot size on spatial resolution in contact mammography or under magnification has been experimentally investigated but, due to construction limitations, only a small range of focal spot sizes has been studied. In this study, a Monte Carlo simulation model is utilized in order to examine the effect of a wide range of focal spots on spatial resolution under magnification conditions. A thick sharp edge consisted of lead was imaged under various conditions and the corresponding spatial resolution was calculated through the Modulation Transfer Function. Results demonstrate that increasing the degree of magnification from 1.0 to 2.0 induces degradation on spatial resolution which varies from 49% for a 0.04 mm focal spot to 53.2% for a 0.14 mm one. Larger focal spots cause higher degradation even for low magnification. Focal spots larger than 0.10 mm are considered appropriate only for low degrees of magnification according to the IAEA regulations that designate spatial resolution for mammography higher than 12 lp/mm. However, for high degrees of magnification the focal spot size should be even smaller. The construction of a microfocus of 0.04 mm would result in acceptable values of spatial resolution even for degrees of magnification up to 1.9.

  7. Fundamental x-ray interaction limits in diagnostic imaging detectors: spatial resolution.

    Science.gov (United States)

    Hajdok, G; Battista, J J; Cunningham, I A

    2008-07-01

    The practice of diagnostic x-ray imaging has been transformed with the emergence of digital detector technology. Although digital systems offer many practical advantages over conventional film-based systems, their spatial resolution performance can be a limitation. The authors present a Monte Carlo study to determine fundamental resolution limits caused by x-ray interactions in four converter materials: Amorphous silicon (a-Si), amorphous selenium, cesium iodide, and lead iodide. The "x-ray interaction" modulation transfer function (MTF) was determined for each material and compared in terms of the 50% MTF spatial frequency and Wagner's effective aperture for incident photon energies between 10 and 150 keV and various converter thicknesses. Several conclusions can be drawn from their Monte Carlo study. (i) In low-Z (a-Si) converters, reabsorption of Compton scatter x rays limits spatial resolution with a sharp MTF drop at very low spatial frequencies (x-ray interaction MTF. (iii) The spread of energy due to secondary electron (e.g., photoelectrons) transport is significant only at very high spatial frequencies. (iv) Unlike the spread of optical light in phosphors, the spread of absorbed energy from x-ray interactions does not significantly degrade spatial resolution as converter thickness is increased. (v) The effective aperture results reported here represent fundamental spatial resolution limits of the materials tested and serve as target benchmarks for the design and development of future digital x-ray detectors.

  8. Unlocking high spatial resolution in neutron imaging through an add-on fibre optics taper.

    Science.gov (United States)

    Morgano, M; Trtik, P; Meyer, M; Lehmann, E H; Hovind, J; Strobl, M

    2018-01-22

    The demand for high resolution neutron imaging has been steadily increasing over the past years. The number of facilities offering cutting edge resolution is however limited, due to (i) the design complexity of an optimized device able to reach a resolution in the order of ≈ 10 μm and (ii) limitations in available neutron flux. Here we propose a simple addition, based on a Fibre Optics Taper (FOT), that can be easily attached to an already existing scintillator-camera imaging detector in order to efficiently increase its spatial resolution and hence boost the capability of an instrument into high resolution applications.

  9. Spatial resolution is dependent on image content for SPECT with iterative reconstruction incorporating distance dependent resolution (DDR) correction.

    Science.gov (United States)

    Badger, Daniel; Barnden, Leighton

    2014-09-01

    The aim of this study is to determine the dependence of single photon emission computed tomography (SPECT) spatial resolution on the content of images for iterative reconstruction with distance dependent resolution (DDR) correction. An experiment was performed using a perturbation technique to measure change in resolution of line sources in simple and complex images with iterative reconstruction with increasing iteration. Projections of the line sources were reconstructed alone and again after the addition of projections of a uniform flood or a complex phantom. An alternative experiment used images of a realistic brain phantom and evaluated an effective spatial resolution by matching the images to the digital version of the phantom convolved with 3D Gaussian kernels. The experiments were performed using ordered subset expectation maximisation iterative reconstruction with and without the use of DDR correction. The results show a significant difference in reconstructed resolution between images of line sources depending on the content of the added image. The full width at half maximum of images of a line source reconstructed using DDR correction increased by 20-30 % when the added image was complex. Without DDR this difference was much smaller and disappeared with increasing iteration. Reported SPECT resolution should be taken as indicative only with regard to clinical imaging if the measurement is made using a point or line source alone and an iterative reconstruction algorithm is used.

  10. Quantifying Surface Water Dynamics at 30 Meter Spatial Resolution in the North American High Northern Latitudes 1991-2011

    Science.gov (United States)

    Carroll, Mark; Wooten, Margaret; DiMiceli, Charlene; Sohlberg, Robert; Kelly, Maureen

    2016-01-01

    The availability of a dense time series of satellite observations at moderate (30 m) spatial resolution is enabling unprecedented opportunities for understanding ecosystems around the world. A time series of data from Landsat was used to generate a series of three maps at decadal time step to show how surface water has changed from 1991 to 2011 in the high northern latitudes of North America. Previous attempts to characterize the change in surface water in this region have been limited in either spatial or temporal resolution, or both. This series of maps was generated for the NASA Arctic and Boreal Vulnerability Experiment (ABoVE), which began in fall 2015. These maps show a nominal extent of surface water by using multiple observations to make a single map for each time step. This increases the confidence that any detected changes are related to climate or ecosystem changes not simply caused by short duration weather events such as flood or drought. The methods and comparison to other contemporary maps of the region are presented here. Initial verification results indicate 96% producer accuracy and 54% user accuracy when compared to 2-m resolution World View-2 data. All water bodies that were omitted were one Landsat pixel or smaller, hence below detection limits of the instrument.

  11. Impacts of spatial resolution and representation of flow connectivity on large-scale simulation of floods

    Science.gov (United States)

    Mateo, Cherry May R.; Yamazaki, Dai; Kim, Hyungjun; Champathong, Adisorn; Vaze, Jai; Oki, Taikan

    2017-10-01

    Global-scale river models (GRMs) are core tools for providing consistent estimates of global flood hazard, especially in data-scarce regions. Due to former limitations in computational power and input datasets, most GRMs have been developed to use simplified representations of flow physics and run at coarse spatial resolutions. With increasing computational power and improved datasets, the application of GRMs to finer resolutions is becoming a reality. To support development in this direction, the suitability of GRMs for application to finer resolutions needs to be assessed. This study investigates the impacts of spatial resolution and flow connectivity representation on the predictive capability of a GRM, CaMa-Flood, in simulating the 2011 extreme flood in Thailand. Analyses show that when single downstream connectivity (SDC) is assumed, simulation results deteriorate with finer spatial resolution; Nash-Sutcliffe efficiency coefficients decreased by more than 50 % between simulation results at 10 km resolution and 1 km resolution. When multiple downstream connectivity (MDC) is represented, simulation results slightly improve with finer spatial resolution. The SDC simulations result in excessive backflows on very flat floodplains due to the restrictive flow directions at finer resolutions. MDC channels attenuated these effects by maintaining flow connectivity and flow capacity between floodplains in varying spatial resolutions. While a regional-scale flood was chosen as a test case, these findings should be universal and may have significant impacts on large- to global-scale simulations, especially in regions where mega deltas exist.These results demonstrate that a GRM can be used for higher resolution simulations of large-scale floods, provided that MDC in rivers and floodplains is adequately represented in the model structure.

  12. Impacts of spatial resolution and representation of flow connectivity on large-scale simulation of floods

    Directory of Open Access Journals (Sweden)

    C. M. R. Mateo

    2017-10-01

    Full Text Available Global-scale river models (GRMs are core tools for providing consistent estimates of global flood hazard, especially in data-scarce regions. Due to former limitations in computational power and input datasets, most GRMs have been developed to use simplified representations of flow physics and run at coarse spatial resolutions. With increasing computational power and improved datasets, the application of GRMs to finer resolutions is becoming a reality. To support development in this direction, the suitability of GRMs for application to finer resolutions needs to be assessed. This study investigates the impacts of spatial resolution and flow connectivity representation on the predictive capability of a GRM, CaMa-Flood, in simulating the 2011 extreme flood in Thailand. Analyses show that when single downstream connectivity (SDC is assumed, simulation results deteriorate with finer spatial resolution; Nash–Sutcliffe efficiency coefficients decreased by more than 50 % between simulation results at 10 km resolution and 1 km resolution. When multiple downstream connectivity (MDC is represented, simulation results slightly improve with finer spatial resolution. The SDC simulations result in excessive backflows on very flat floodplains due to the restrictive flow directions at finer resolutions. MDC channels attenuated these effects by maintaining flow connectivity and flow capacity between floodplains in varying spatial resolutions. While a regional-scale flood was chosen as a test case, these findings should be universal and may have significant impacts on large- to global-scale simulations, especially in regions where mega deltas exist.These results demonstrate that a GRM can be used for higher resolution simulations of large-scale floods, provided that MDC in rivers and floodplains is adequately represented in the model structure.

  13. Spatial resolution of the HRRT PET scanner using 3D-OSEM PSF reconstruction

    DEFF Research Database (Denmark)

    Olesen, Oline Vinter; Sibomana, Merence; Keller, Sune Høgild

    2009-01-01

    The spatial resolution of the Siemens High Resolution Research Tomograph (HRRT) dedicated brain PET scanner installed at Copenhagen University Hospital (Rigshospitalet) was measured using a point-source phantom with high statistics. Further, it was demonstrated how the newly developed 3D-OSEM PSF...

  14. Spatial covariance reconstructive (SCORE super-resolution fluorescence microscopy.

    Directory of Open Access Journals (Sweden)

    Yi Deng

    Full Text Available Super-resolution fluorescence microscopy has become a powerful tool to resolve structural information that is not accessible to traditional diffraction-limited imaging techniques such as confocal microscopy. Stochastic optical reconstruction microscopy (STORM and photoactivation localization microscopy (PALM are promising super-resolution techniques due to their relative ease of implementation and instrumentation on standard microscopes. However, the application of STORM is critically limited by its long sampling time. Several recent works have been focused on improving the STORM imaging speed by making use of the information from emitters with overlapping point spread functions (PSF. In this work, we present a fast and efficient algorithm that takes into account the blinking statistics of independent fluorescence emitters. We achieve sub-diffraction lateral resolution of 100 nm from 5 to 7 seconds of imaging. Our method is insensitive to background and can be applied to different types of fluorescence sources, including but not limited to the organic dyes and quantum dots that we demonstrate in this work.

  15. Spatial resolution of confocal XRF technique using capillary optics.

    Science.gov (United States)

    Dehlinger, Maël; Fauquet, Carole; Lavandier, Sebastien; Aumporn, Orawan; Jandard, Franck; Arkadiev, Vladimir; Bjeoumikhov, Aniouar; Tonneau, Didier

    2013-06-07

    XRF (X-ray fluorescence) is a powerful technique for elemental analysis with a high sensitivity. The resolution is presently limited by the size of the primary excitation X-ray beam. A test-bed for confocal-type XRF has been developed to estimate the ultimate lateral resolution which could be reached in chemical mapping using this technique. A polycapillary lens is used to tightly focus the primary X-ray beam of a low power rhodium X-ray source, while the fluorescence signal is collected by a SDD detector through a cylindrical monocapillary. This system was used to characterize the geometry of the fluorescent zone. Capillary radii ranging from 50 μm down to 5 μm were used to investigate the fluorescence signal maximum level This study allows to estimate the ultimate resolution which could be reached in-lab or on a synchrotron beamline. A new tool combining local XRF and scanning probe microscopy is finally proposed.

  16. Evaluation of high resolution global satellite precipitation products using daily raingauge data over the Upper Blue Nile Basin

    Science.gov (United States)

    Sahlu, Dejene; Moges, Semu; Anagnostou, Emmanouil; Nikolopoulos, Efthymios; Hailu, Dereje; Mei, Yiwen

    2017-04-01

    Water resources assessment, planning and management in Africa is often constrained by the lack of reliable spatio-temporal rainfall data. Satellite products are steadily growing and offering useful alternative datasets of rainfall globally. The aim of this paper is to examine the error characteristics of the main available global satellite precipitation products with the view of improving the reliability of wet season (June to September) and small rainy season rainfall datasets over the Upper Blue Nile Basin. The study utilized six satellite derived precipitation datasets at 0.25-deg spatial grid size and daily temporal resolution:1) the near real-time (3B42_RT) and gauge adjusted (3B42_V7) products of Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA), 2) gauge adjusted and unadjusted Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN) products and 3) the gauge adjusted and un-adjusted product of the National Oceanic and Atmospheric Administration (NOAA) Climate Prediction Center Morphing technique (CMORPH) over the period of 2000 to 2013.The error analysis utilized statistical techniques using bias ratio (Bias), correlation coefficient (CC) and root-mean-square-error (RMSE). Mean relative error (MRE), CC and RMSE metrics are further examined for six categories of 10th, 25th, 50th, 75th, 90thand 95th percentile rainfall thresholds. The skill of the satellite estimates is evaluated using categorical error metrics of missed rainfall volume fraction (MRV), falsely detected rainfall volume fraction (FRV), probability of detection (POD) and False Alarm Ratio (FAR). Results showed that six satellite based rainfall products underestimated wet season (June to September) gauge precipitation, with the exception of non-adjusted PERSIANN that overestimated the initial part of the rainy season (March to May). During the wet season, adjusted CMORPH has relatively better bias ratio (89

  17. Impact of climate change on river flooding assessed with different spatial model resolutions

    NARCIS (Netherlands)

    Booij, Martijn J.

    2005-01-01

    The impact of climate change on flooding in the river Meuse is assessed on a daily basis using spatially and temporally changed climate patterns and a hydrological model with three different spatial resolutions. This is achieved by selecting a hydrological modelling framework and implementing

  18. High-resolution sensing for precision agriculture: from Earth-observing satellites to unmanned aerial vehicles

    Science.gov (United States)

    McCabe, Matthew F.; Houborg, Rasmus; Lucieer, Arko

    2016-10-01

    With global population projected to approach 9 billion by 2050, it has been estimated that a 40% increase in cereal production will be required to satisfy the worlds growing nutritional demands. Any such increases in agricultural productivity are likely to occur within a system that has limited room for growth and in a world with a climate that is different from that of today. Fundamental to achieving food and water security, is the capacity to monitor the health and condition of agricultural systems. While space-agency based satellites have provided the backbone for earth observation over the last few decades, many developments in the field of high-resolution earth observation have been advanced by the commercial sector. These advances relate not just to technological developments in the use of unmanned aerial vehicles (UAVs), but also the advent of nano-satellite constellations that offer a radical shift in the way earth observations are now being retrieved. Such technologies present opportunities for improving our description of the water, energy and carbon cycles. Efforts towards developing new observational techniques and interpretative frameworks are required to provide the tools and information needed to improve the management and security of agricultural and related sectors. These developments are one of the surest ways to better manage, protect and preserve national food and water resources. Here we review the capabilities of recently deployed satellite systems and UAVs and examine their potential for application in precision agriculture.

  19. High-resolution sensing for precision agriculture: from Earth-observing satellites to unmanned aerial vehicles

    KAUST Repository

    McCabe, Matthew

    2016-10-25

    With global population projected to approach 9 billion by 2050, it has been estimated that a 40% increase in cereal production will be required to satisfy the worlds growing nutritional demands. Any such increases in agricultural productivity are likely to occur within a system that has limited room for growth and in a world with a climate that is different from that of today. Fundamental to achieving food and water security, is the capacity to monitor the health and condition of agricultural systems. While space-Agency based satellites have provided the backbone for earth observation over the last few decades, many developments in the field of high-resolution earth observation have been advanced by the commercial sector. These advances relate not just to technological developments in the use of unmanned aerial vehicles (UAVs), but also the advent of nano-satellite constellations that offer a radical shift in the way earth observations are now being retrieved. Such technologies present opportunities for improving our description of the water, energy and carbon cycles. Efforts towards developing new observational techniques and interpretative frameworks are required to provide the tools and information needed to improve the management and security of agricultural and related sectors. These developments are one of the surest ways to better manage, protect and preserve national food and water resources. Here we review the capabilities of recently deployed satellite systems and UAVs and examine their potential for application in precision agriculture.

  20. Estimating aboveground biomass in Avicennia marina plantation in Indian Sundarbans using high-resolution satellite data

    Science.gov (United States)

    Manna, Sudip; Nandy, Subrata; Chanda, Abhra; Akhand, Anirban; Hazra, Sugata; Dadhwal, Vinay Kumar

    2014-01-01

    Mangroves are active carbon sequesters playing a crucial role in coastal ecosystems. In the present study, aboveground biomass (AGB) was estimated in a 5-year-old Avicennia marina plantation (approximate area ≈190 ha) of Indian Sundarbans using high-resolution satellite data in order to assess its carbon sequestration potential. The reflectance values of each band of LISS IV satellite data and the vegetation indices, viz., normalized difference vegetation index (NDVI), optimized soil adjusted vegetation index (OSAVI), and transformed difference vegetation index (TDVI), derived from the satellite data, were correlated with the AGB. OSAVI showed the strongest positive linear relationship with the AGB and hence carbon content of the stand. OSAVI was found to predict the AGB to a great extent (r=0.72) as it is known to nullify the background soil reflectance effect added to vegetation reflectance. The total AGB of the entire plantation was estimated to be 236 metric tons having a carbon stock of 54.9 metric tons, sequestered within a time span of 5 years. Integration of this technique for monitoring and management of young mangrove plantations will give time and cost effective results.

  1. Merging high-resolution satellite-based precipitation fields and point-scale rain gauge measurements—A case study in Chile

    Science.gov (United States)

    Yang, Zhongwen; Hsu, Kuolin; Sorooshian, Soroosh; Xu, Xinyi; Braithwaite, Dan; Zhang, Yuan; Verbist, Koen M. J.

    2017-05-01

    With high spatial-temporal resolution, Satellite-based Precipitation Estimates (SPE) are becoming valuable alternative rainfall data for hydrologic and climatic studies but are subject to considerable uncertainty. Effective merging of SPE and ground-based gauge measurements may help to improve precipitation estimation in both better resolution and accuracy. In this study, a framework for merging satellite and gauge precipitation data is developed based on three steps, including SPE bias adjustment, gauge observation gridding, and data merging, with the objective to produce high-quality precipitation estimates. An inverse-root-mean-square-error weighting approach is proposed to combine the satellite and gauge estimates that are in advance adjusted and gridded, respectively. The model is applied and tested with the Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Cloud Classification System (PERSIANN-CCS) estimates (daily, 0.04° × 0.04°) over Chile, for the 6 year period of 2009-2014. Daily observations from about 90% of collected gauges over the study area are used for model calibration; the rest of the gauged data are regarded as ground "truth" for validation. Evaluation results indicate high effectiveness of the model in producing high-resolution-precision precipitation data. Compared to reference data, the merged data (daily) show correlation coefficients, probabilities of detection, root-mean-square errors, and absolute mean biases that were consistently improved from the original PERSIANN-CCS estimates. The cross-validation evidences that the framework is effective in providing high-quality estimates even over nongauged satellite pixels. The same method can be applied globally and is expected to produce precipitation products in near real time by integrating gauge observations with satellite estimates.

  2. Assessment of the Latest GPM-Era High-Resolution Satellite Precipitation Products by Comparison with Observation Gauge Data over the Chinese Mainland

    Directory of Open Access Journals (Sweden)

    Shaowei Ning

    2016-10-01

    Full Text Available The Global Precipitation Mission (GPM Core Observatory that was launched on 27 February 2014 ushered in a new era for estimating precipitation from satellites. Based on their high spatial–temporal resolution and near global coverage, satellite-based precipitation products have been applied in many research fields. The goal of this study was to quantitatively compare two of the latest GPM-era satellite precipitation products (GPM IMERG and GSMap-Gauge Ver. 6 with a network of 840 precipitation gauges over the Chinese mainland. Direct comparisons of satellite-based precipitation products with rain gauge observations over a 20 month period from April 2014 to November 2015 at 0.1° and daily/monthly resolutions showed the following results: Both of the products were capable of capturing the overall spatial pattern of the 20 month mean daily precipitation, which was characterized by a decreasing trend from the southeast to the northwest. GPM IMERG overestimated precipitation by approximately 0.09 mm/day while GSMap-Gauge Ver. 6 underestimated precipitation by −0.04 mm/day. The two satellite-based precipitation products performed better over wet southern regions than over dry northern regions. They also showed better performance in summer than in winter. In terms of mean error, root mean square error, correlation coefficient, and probability of detection, GSMap-Gauge was better able to estimate precipitation and had more stable quality results than GPM IMERG on both daily and monthly scales. GPM IMERG was more sensitive to conditions of no rain or light rainfall and demonstrated good capability of capturing the behavior of extreme precipitation events. Overall, the results revealed some limitations of these two latest satellite-based precipitation products when used over the Chinese mainland, helping to characterize some of the error features in these datasets for potential users.

  3. A fuzzy decision making system for building damage map creation using high resolution satellite imagery

    Science.gov (United States)

    Rastiveis, H.; Samadzadegan, F.; Reinartz, P.

    2013-02-01

    Recent studies have shown high resolution satellite imagery to be a powerful data source for post-earthquake damage assessment of buildings. Manual interpretation of these images, while being a reliable method for finding damaged buildings, is a subjective and time-consuming endeavor, rendering it unviable at times of emergency. The present research, proposes a new state-of-the-art method for automatic damage assessment of buildings using high resolution satellite imagery. In this method, at the first step a set of pre-processing algorithms are performed on the images. Then, extracting a candidate building from both pre- and post-event images, the intact roof part after an earthquake is found. Afterwards, by considering the shape and other structural properties of this roof part with its pre-event condition in a fuzzy inference system, the rate of damage for each candidate building is estimated. The results obtained from evaluation of this algorithm using QuickBird images of the December 2003 Bam, Iran, earthquake prove the ability of this method for post-earthquake damage assessment of buildings.

  4. Testing methods for using high-resolution satellite imagery to monitor polar bear abundance and distribution

    Science.gov (United States)

    LaRue, Michelle A.; Stapleton, Seth P.; Porter, Claire; Atkinson, Stephen N.; Atwood, Todd C.; Dyck, Markus; Lecomte, Nicolas

    2015-01-01

    High-resolution satellite imagery is a promising tool for providing coarse information about polar species abundance and distribution, but current applications are limited. With polar bears (Ursus maritimus), the technique has only proven effective on landscapes with little topographic relief that are devoid of snow and ice, and time-consuming manual review of imagery is required to identify bears. Here, we evaluated mechanisms to further develop methods for satellite imagery by examining data from Rowley Island, Canada. We attempted to automate and expedite detection via a supervised spectral classification and image differencing to expedite image review. We also assessed what proportion of a region should be sampled to obtain reliable estimates of density and abundance. Although the spectral signature of polar bears differed from nontarget objects, these differences were insufficient to yield useful results via a supervised classification process. Conversely, automated image differencing—or subtracting one image from another—correctly identified nearly 90% of polar bear locations. This technique, however, also yielded false positives, suggesting that manual review will still be required to confirm polar bear locations. On Rowley Island, bear distribution approximated a Poisson distribution across a range of plot sizes, and resampling suggests that sampling >50% of the site facilitates reliable estimation of density (CV in certain areas, but large-scale applications remain limited because of the challenges in automation and the limited environments in which the method can be effectively applied. Improvements in resolution may expand opportunities for its future uses.

  5. Airborne LIDAR and high resolution satellite data for rapid 3D feature extraction

    Science.gov (United States)

    Jawak, S. D.; Panditrao, S. N.; Luis, A. J.

    2014-11-01

    This work uses the canopy height model (CHM) based workflow for individual tree crown delineation and 3D feature extraction approach (Overwatch Geospatial's proprietary algorithm) for building feature delineation from high-density light detection and ranging (LiDAR) point cloud data in an urban environment and evaluates its accuracy by using very high-resolution panchromatic (PAN) (spatial) and 8-band (multispectral) WorldView-2 (WV-2) imagery. LiDAR point cloud data over San Francisco, California, USA, recorded in June 2010, was used to detect tree and building features by classifying point elevation values. The workflow employed includes resampling of LiDAR point cloud to generate a raster surface or digital terrain model (DTM), generation of a hill-shade image and an intensity image, extraction of digital surface model, generation of bare earth digital elevation model (DEM) and extraction of tree and building features. First, the optical WV-2 data and the LiDAR intensity image were co-registered using ground control points (GCPs). The WV-2 rational polynomial coefficients model (RPC) was executed in ERDAS Leica Photogrammetry Suite (LPS) using supplementary *.RPB file. In the second stage, ortho-rectification was carried out using ERDAS LPS by incorporating well-distributed GCPs. The root mean square error (RMSE) for the WV-2 was estimated to be 0.25 m by using more than 10 well-distributed GCPs. In the second stage, we generated the bare earth DEM from LiDAR point cloud data. In most of the cases, bare earth DEM does not represent true ground elevation. Hence, the model was edited to get the most accurate DEM/ DTM possible and normalized the LiDAR point cloud data based on DTM in order to reduce the effect of undulating terrain. We normalized the vegetation point cloud values by subtracting the ground points (DEM) from the LiDAR point cloud. A normalized digital surface model (nDSM) or CHM was calculated from the LiDAR data by subtracting the DEM from the DSM

  6. High-resolution CASSINI-VIMS mosaics of Titan and the icy Saturnian satellites

    Science.gov (United States)

    Jaumann, R.; Stephan, K.; Brown, R.H.; Buratti, B.J.; Clark, R.N.; McCord, T.B.; Coradini, A.; Capaccioni, F.; Filacchione, G.; Cerroni, P.; Baines, K.H.; Bellucci, G.; Bibring, J.-P.; Combes, M.; Cruikshank, D.P.; Drossart, P.; Formisano, V.; Langevin, Y.; Matson, D.L.; Nelson, R.M.; Nicholson, P.D.; Sicardy, B.; Sotin, Christophe; Soderbloom, L.A.; Griffith, C.; Matz, K.-D.; Roatsch, Th.; Scholten, F.; Porco, C.C.

    2006-01-01

    The Visual Infrared Mapping Spectrometer (VIMS) onboard the CASSINI spacecraft obtained new spectral data of the icy satellites of Saturn after its arrival at Saturn in June 2004. VIMS operates in a spectral range from 0.35 to 5.2 ??m, generating image cubes in which each pixel represents a spectrum consisting of 352 contiguous wavebands. As an imaging spectrometer VIMS combines the characteristics of both a spectrometer and an imaging instrument. This makes it possible to analyze the spectrum of each pixel separately and to map the spectral characteristics spatially, which is important to study the relationships between spectral information and geological and geomorphologic surface features. The spatial analysis of the spectral data requires the determination of the exact geographic position of each pixel on the specific surface and that all 352 spectral elements of each pixel show the same region of the target. We developed a method to reproject each pixel geometrically and to convert the spectral data into map projected image cubes. This method can also be applied to mosaic different VIMS observations. Based on these mosaics, maps of the spectral properties for each Saturnian satellite can be derived and attributed to geographic positions as well as to geological and geomorphologic surface features. These map-projected mosaics are the basis for all further investigations. ?? 2006 Elsevier Ltd. All rights reserved.

  7. Estimating burned area in Mato Grosso, Brazil, using an object-based classification method on a systematic sample of medium resolution satellite images

    OpenAIRE

    SHIMABUKURO YOSIO EDEMIR; MIETTINEN JUKKA ILMARI; BEUCHLE Rene'; GRECCHI ROSANA; SIMONETTI DARIO; ACHARD Frederic

    2015-01-01

    This paper presents a new approach for estimating burned areas at a regional scale, using a systematic sample of medium spatial resolution satellite images. This approach is based on a pan-tropical deforestation survey developed by the Joint Research Centre. We developed and tested our approach over Mato Grosso State, located in the Brazilian Legal Amazon region, with a total area of 903,366 km². We analyze Landsat-5 TM imagery over 77 sample sites (20 km × 20 km in size) located at each full...

  8. Poverty, health and satellite-derived vegetation indices: their inter-spatial relationship in West Africa

    Science.gov (United States)

    Sedda, Luigi; Tatem, Andrew J.; Morley, David W.; Atkinson, Peter M.; Wardrop, Nicola A.; Pezzulo, Carla; Sorichetta, Alessandro; Kuleszo, Joanna; Rogers, David J.

    2015-01-01

    Background Previous analyses have shown the individual correlations between poverty, health and satellite-derived vegetation indices such as the normalized difference vegetation index (NDVI). However, generally these analyses did not explore the statistical interconnections between poverty, health outcomes and NDVI. Methods In this research aspatial methods (principal component analysis) and spatial models (variography, factorial kriging and cokriging) were applied to investigate the correlations and spatial relationships between intensity of poverty, health (expressed as child mortality and undernutrition), and NDVI for a large area of West Africa. Results This research showed that the intensity of poverty (and hence child mortality and nutrition) varies inversely with NDVI. From the spatial point-of-view, similarities in the spatial variation of intensity of poverty and NDVI were found. Conclusions These results highlight the utility of satellite-based metrics for poverty models including health and ecological components and, in general for large scale analysis, estimation and optimisation of multidimensional poverty metrics. However, it also stresses the need for further studies on the causes of the association between NDVI, health and poverty. Once these relationships are confirmed and better understood, the presence of this ecological component in poverty metrics has the potential to facilitate the analysis of the impacts of climate change on the rural populations afflicted by poverty and child mortality. PMID:25733559

  9. Poverty, health and satellite-derived vegetation indices: their inter-spatial relationship in West Africa.

    Science.gov (United States)

    Sedda, Luigi; Tatem, Andrew J; Morley, David W; Atkinson, Peter M; Wardrop, Nicola A; Pezzulo, Carla; Sorichetta, Alessandro; Kuleszo, Joanna; Rogers, David J

    2015-03-01

    Previous analyses have shown the individual correlations between poverty, health and satellite-derived vegetation indices such as the normalized difference vegetation index (NDVI). However, generally these analyses did not explore the statistical interconnections between poverty, health outcomes and NDVI. In this research aspatial methods (principal component analysis) and spatial models (variography, factorial kriging and cokriging) were applied to investigate the correlations and spatial relationships between intensity of poverty, health (expressed as child mortality and undernutrition), and NDVI for a large area of West Africa. This research showed that the intensity of poverty (and hence child mortality and nutrition) varies inversely with NDVI. From the spatial point-of-view, similarities in the spatial variation of intensity of poverty and NDVI were found. These results highlight the utility of satellite-based metrics for poverty models including health and ecological components and, in general for large scale analysis, estimation and optimisation of multidimensional poverty metrics. However, it also stresses the need for further studies on the causes of the association between NDVI, health and poverty. Once these relationships are confirmed and better understood, the presence of this ecological component in poverty metrics has the potential to facilitate the analysis of the impacts of climate change on the rural populations afflicted by poverty and child mortality. © The Author 2015. Published by Oxford University Press on behalf of Royal Society of Tropical Medicine and Hygiene. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

  10. Landform classification using a sub-pixel spatial attraction model to increase spatial resolution of digital elevation model (DEM

    Directory of Open Access Journals (Sweden)

    Marzieh Mokarrama

    2018-04-01

    Full Text Available The purpose of the present study is preparing a landform classification by using digital elevation model (DEM which has a high spatial resolution. To reach the mentioned aim, a sub-pixel spatial attraction model was used as a novel method for preparing DEM with a high spatial resolution in the north of Darab, Fars province, Iran. The sub-pixel attraction models convert the pixel into sub-pixels based on the neighboring pixels fraction values, which can only be attracted by a central pixel. Based on this approach, a mere maximum of eight neighboring pixels can be selected for calculating of the attraction value. In the mentioned model, other pixels are supposed to be far from the central pixel to receive any attraction. In the present study by using a sub-pixel attraction model, the spatial resolution of a DEM was increased. The design of the algorithm is accomplished by using a DEM with a spatial resolution of 30 m (the Advanced Space borne Thermal Emission and Reflection Radiometer; (ASTER and a 90 m (the Shuttle Radar Topography Mission; (SRTM. In the attraction model, scale factors of (S = 2, S = 3, and S = 4 with two neighboring methods of touching (T = 1 and quadrant (T = 2 are applied to the DEMs by using MATLAB software. The algorithm is evaluated by taking the best advantages of 487 sample points, which are measured by surveyors. The spatial attraction model with scale factor of (S = 2 gives better results compared to those scale factors which are greater than 2. Besides, the touching neighborhood method is turned to be more accurate than the quadrant method. In fact, dividing each pixel into more than two sub-pixels decreases the accuracy of the resulted DEM. On the other hand, in these cases DEM, is itself in charge of increasing the value of root-mean-square error (RMSE and shows that attraction models could not be used for S which is greater than 2. Thus considering results, the proposed model is highly capable of

  11. A practical algorithm for the retrieval of floe size distribution of Arctic sea ice from high-resolution satellite Synthetic Aperture Radar imagery

    Directory of Open Access Journals (Sweden)

    Byongjun Hwang

    2017-07-01

    Full Text Available In this study, we present an algorithm for summer sea ice conditions that semi-automatically produces the floe size distribution of Arctic sea ice from high-resolution satellite Synthetic Aperture Radar data. Currently, floe size distribution data from satellite images are very rare in the literature, mainly due to the lack of a reliable algorithm to produce such data. Here, we developed the algorithm by combining various image analysis methods, including Kernel Graph Cuts, distance transformation and watershed transformation, and a rule-based boundary revalidation. The developed algorithm has been validated against the ground truth that was extracted manually with the aid of 1-m resolution visible satellite data. Comprehensive validation analysis has shown both perspectives and limitations. The algorithm tends to fail to detect small floes (mostly less than 100 m in mean caliper diameter compared to ground truth, which is mainly due to limitations in water-ice segmentation. Some variability in the power law exponent of floe size distribution is observed due to the effects of control parameters in the process of de-noising, Kernel Graph Cuts segmentation, thresholds for boundary revalidation and image resolution. Nonetheless, the algorithm, for floes larger than 100 m, has shown a reasonable agreement with ground truth under various selections of these control parameters. Considering that the coverage and spatial resolution of satellite Synthetic Aperture Radar data have increased significantly in recent years, the developed algorithm opens a new possibility to produce large volumes of floe size distribution data, which is essential for improving our understanding and prediction of the Arctic sea ice cover

  12. Local Optical Spectroscopies for Subnanometer Spatial Resolution Chemical Imaging

    Energy Technology Data Exchange (ETDEWEB)

    Weiss, Paul

    2014-01-20

    The evanescently coupled photon scanning tunneling microscopes (STMs) have special requirements in terms of stability and optical access. We have made substantial improvements to the stability, resolution, and noise floor of our custom-built visible-photon STM, and will translate these advances to our infrared instrument. Double vibration isolation of the STM base with a damping system achieved increased rigidity, giving high tunneling junction stability for long-duration and high-power illumination. Light frequency modulation with an optical chopper and phase-sensitive detection now enhance the signal-to-noise ratio of the tunneling junction during irradiation.

  13. Resolving mass flux at high spatial and temporal resolution using GRACE intersatellite measurements

    DEFF Research Database (Denmark)

    Rowlands, D. D.; Luthcke, S. B.; Klosko, S. M.

    2005-01-01

    The GRACE mission is designed to monitor mass flux on the Earth's surface at one month and high spatial resolution through the estimation of monthly gravity fields. Although this approach has been largely successful, information at submonthly time scales can be lost or even aliased through...... the estimation of static monthly parameters. Through an analysis of the GRACE data residuals, we show that the fundamental temporal and spatial resolution of the GRACE data is 10 days and 400 km. We present an approach similar in concept to altimetric methods that recovers submonthly mass flux at a high spatial...

  14. 3D-information fusion from very high resolution satellite sensors

    Science.gov (United States)

    Krauss, T.; d'Angelo, P.; Kuschk, G.; Tian, J.; Partovi, T.

    2015-04-01

    In this paper we show the pre-processing and potential for environmental applications of very high resolution (VHR) satellite stereo imagery like these from WorldView-2 or Pl'eiades with ground sampling distances (GSD) of half a metre to a metre. To process such data first a dense digital surface model (DSM) has to be generated. Afterwards from this a digital terrain model (DTM) representing the ground and a so called normalized digital elevation model (nDEM) representing off-ground objects are derived. Combining these elevation based data with a spectral classification allows detection and extraction of objects from the satellite scenes. Beside the object extraction also the DSM and DTM can directly be used for simulation and monitoring of environmental issues. Examples are the simulation of floodings, building-volume and people estimation, simulation of noise from roads, wave-propagation for cellphones, wind and light for estimating renewable energy sources, 3D change detection, earthquake preparedness and crisis relief, urban development and sprawl of informal settlements and much more. Also outside of urban areas volume information brings literally a new dimension to earth oberservation tasks like the volume estimations of forests and illegal logging, volume of (illegal) open pit mining activities, estimation of flooding or tsunami risks, dike planning, etc. In this paper we present the preprocessing from the original level-1 satellite data to digital surface models (DSMs), corresponding VHR ortho images and derived digital terrain models (DTMs). From these components we present how a monitoring and decision fusion based 3D change detection can be realized by using different acquisitions. The results are analyzed and assessed to derive quality parameters for the presented method. Finally the usability of 3D information fusion from VHR satellite imagery is discussed and evaluated.

  15. .A method for examining temporal changes in cyanobacterial harmful algal bloom spatial extent using satellite remote sensing

    Science.gov (United States)

    Cyanobacterial harmful algal blooms (CyanoHAB) are thought to be increasing globally over the past few decades, but relatively little quantitative information is available about the spatial extent of blooms. Satellite remote sensing provides a potential technology for identifying...

  16. A method for examining temporal changes in cyanobacterial harmful algal bloom spatial extent using satellite remote sensing (Harmful Algae)

    Science.gov (United States)

    Cyanobacterial harmful algal blooms (CyanoHAB) are thought to be increasing globally over the past few decades, but relatively little quantitative information is available about the spatial extent of blooms. Satellite remote sensing provides a potential technology for identifying...

  17. Angular difference feature extraction for urban scene classification using ZY-3 multi-angle high-resolution satellite imagery

    Science.gov (United States)

    Huang, Xin; Chen, Huijun; Gong, Jianya

    2018-01-01

    Spaceborne multi-angle images with a high-resolution are capable of simultaneously providing spatial details and three-dimensional (3D) information to support detailed and accurate classification of complex urban scenes. In recent years, satellite-derived digital surface models (DSMs) have been increasingly utilized to provide height information to complement spectral properties for urban classification. However, in such a way, the multi-angle information is not effectively exploited, which is mainly due to the errors and difficulties of the multi-view image matching and the inaccuracy of the generated DSM over complex and dense urban scenes. Therefore, it is still a challenging task to effectively exploit the available angular information from high-resolution multi-angle images. In this paper, we investigate the potential for classifying urban scenes based on local angular properties characterized from high-resolution ZY-3 multi-view images. Specifically, three categories of angular difference features (ADFs) are proposed to describe the angular information at three levels (i.e., pixel, feature, and label levels): (1) ADF-pixel: the angular information is directly extrapolated by pixel comparison between the multi-angle images; (2) ADF-feature: the angular differences are described in the feature domains by comparing the differences between the multi-angle spatial features (e.g., morphological attribute profiles (APs)). (3) ADF-label: label-level angular features are proposed based on a group of urban primitives (e.g., buildings and shadows), in order to describe the specific angular information related to the types of primitive classes. In addition, we utilize spatial-contextual information to refine the multi-level ADF features using superpixel segmentation, for the purpose of alleviating the effects of salt-and-pepper noise and representing the main angular characteristics within a local area. The experiments on ZY-3 multi-angle images confirm that the proposed

  18. Estimation of Orbital Neutron Detector Spatial Resolution by Systematic Shifting of Differential Topographic Masks

    Science.gov (United States)

    McClanahan, T. P.; Mitrofanov, I. G.; Boynton, W. V.; Chin, G.; Livengood, T.; Starr, R. D.; Evans, L. G.; Mazarico, E.; Smith, D. E.

    2012-01-01

    We present a method and preliminary results related to determining the spatial resolution of orbital neutron detectors using epithermal maps and differential topographic masks. Our technique is similar to coded aperture imaging methods for optimizing photonic signals in telescopes [I]. In that approach photon masks with known spatial patterns in a telescope aperature are used to systematically restrict incoming photons which minimizes interference and enhances photon signal to noise. Three orbital neutron detector systems with different stated spatial resolutions are evaluated. The differing spatial resolutions arise due different orbital altitudes and the use of neutron collimation techniques. 1) The uncollimated Lunar Prospector Neutron Spectrometer (LPNS) system has spatial resolution of 45km FWHM from approx. 30km altitude mission phase [2]. The Lunar Rennaissance Orbiter (LRO) Lunar Exploration Neutron Detector (LEND) with two detectors at 50km altitude evaluated here: 2) the collimated 10km FWHM spatial resolution detector CSETN and 3) LEND's collimated Sensor for Epithermal Neutrons (SETN). Thus providing two orbital altitudes to study factors of: uncollimated vs collimated and two average altitudes for their effect on fields-of-view.

  19. In-air ion beam analysis with high spatial resolution proton microbeam

    Energy Technology Data Exchange (ETDEWEB)

    Jakšić, M.; Chokheli, D.; Fazinić, S.; Grilj, V.; Skukan, N.; Sudić, I.; Tadić, T.; Antičić, T.

    2016-03-15

    One of the possible ways to maintain the micrometre spatial resolution while performing ion beam analysis in the air is to increase the energy of ions. In order to explore capabilities and limitations of this approach, we have tested a range of proton beam energies (2–6 MeV) using in-air STIM (Scanning Ion Transmission Microscopy) setup. Measurements of the spatial resolution dependence on proton energy have been compared with SRIM simulation and modelling of proton multiple scattering by different approaches. Results were used to select experimental conditions in which 1 micrometre spatial resolution could be obtained. High resolution in-air microbeam could be applied for IBIC (Ion Beam Induced Charge) tests of large detectors used in nuclear and high energy physics that otherwise cannot be tested in relatively small microbeam vacuum chambers.

  20. Super-resolution reconstruction to increase the spatial resolution of diffusion weighted images from orthogonal anisotropic acquisitions

    Science.gov (United States)

    Scherrer, Benoit; Gholipour, Ali; Warfield, Simon K.

    2012-01-01

    Diffusion-weighted imaging (DWI) enables non-invasive investigation and characterization of the white matter but suffers from a relatively poor spatial resolution. Increasing the spatial resolution in DWI is challenging with a single-shot EPI acquisition due to the decreased signal-to-noise ratio and T2* relaxation effect amplified with increased echo time. In this work we propose a super-resolution reconstruction (SRR) technique based on the acquisition of multiple anisotropic orthogonal DWI scans. DWI scans acquired in different planes are not typically closely aligned due to the geometric distortion introduced by magnetic susceptibility differences in each phase-encoding direction. We compensate each scan for geometric distortion by acquisition of a dual echo gradient echo field map, providing an estimate of the field inhomogeneity. We address the problem of patient motion by aligning the volumes in both space and q-space. The SRR is formulated as a maximum a posteriori problem. It relies on a volume acquisition model which describes how the acquired scans are observations of an unknown high-resolution image which we aim to recover. Our model enables the introduction of image priors that exploit spatial homogeneity and enables regularized solutions. We detail our SRR optimization procedure and report experiments including numerical simulations, synthetic SRR and real world SRR. In particular, we demonstrate that combining distortion compensation and SRR provides better results than acquisition of a single isotropic scan for the same acquisition duration time. Importantly, SRR enables DWI with resolution beyond the scanner hardware limitations. This work provides the first evidence that SRR, which employs conventional single shot EPI techniques, enables resolution enhancement in DWI, and may dramatically impact the role of DWI in both neuroscience and clinical applications. PMID:22770597

  1. Spatializing vineyard hydric status within heterogeneous Mediterranean watershed from high spatial resolution optical remote sensing.

    Science.gov (United States)

    Galleguillos, M.; Jacob, F.; Prevot, L.; Lagacherie, P.

    2009-04-01

    Land surface evapotranspiration is one of key hydrological inputs that determine hydric status within Mediterranean vineyards. Its knowledge in a spatially distributed manner is of interest for the monitoring of vine activity throughout the cultural cycle, and for the acquainting of hydrological modeling as upper boundary conditions. Due to vineyard landscape structures, mostly including small fields, the use of remote sensing has not been extensively investigated, apart from airborne observations. Spaceborne ASTER data, collected over the optical domain at high spatial resolution, are of strong interest for the mapping of vineyard hydric status in relation with surface and soil properties, provided vine thermal and hydric status are strongly linked. The objective of this study is to assess the performances of two spatialized approaches devoted to the mapping of instantaneous surface energy fluxes from optical remote sensing. Amongst the candidate methods to be foreseen for the mapping of vineyard water status from remote sensing, we consider two single layer methods characterized by their simplicities and feasibilities, in terms of implementation and input requirements. The first method is the Simplified Surface Energy Balance Index (S-SEBI, proposed by Roerink et al., 2000) and the second is the Water Deficit Index (WDI, designed by Moran et al., 1994). They differ by the way they use the spatial information captured over the solar and thermal domains, for the differentiating based retrieving of water status and evapotranspiration. First, the spatial information can be characterized through the temperature - vegetation index triangle that is controlled by soil moisture (WDI), or through the temperature - albedo diagram that is controlled by radiative and evaporative processes (S-SEBI). Second, evaporative extremes can be determined according to theoretical considerations and related formalisms (WDI), or assigned according to variabilities captured through thermal

  2. VAST PLANES OF SATELLITES IN A HIGH-RESOLUTION SIMULATION OF THE LOCAL GROUP: COMPARISON TO ANDROMEDA

    International Nuclear Information System (INIS)

    Gillet, N.; Ocvirk, P.; Aubert, D.; Knebe, A.; Yepes, G.; Libeskind, N.; Gottlöber, S.; Hoffman, Y.

    2015-01-01

    We search for vast planes of satellites (VPoS) in a high-resolution simulation of the Local Group performed by the CLUES project, which improves significantly the resolution of previous similar studies. We use a simple method for detecting planar configurations of satellites, and validate it on the known plane of M31. We implement a range of prescriptions for modeling the satellite populations, roughly reproducing the variety of recipes used in the literature, and investigate the occurrence and properties of planar structures in these populations. The structure of the simulated satellite systems is strongly non-random and contains planes of satellites, predominantly co-rotating, with, in some cases, sizes comparable to the plane observed in M31 by Ibata et al. However, the latter is slightly richer in satellites, slightly thinner, and has stronger co-rotation, which makes it stand out as overall more exceptional than the simulated planes, when compared to a random population. Although the simulated planes we find are generally dominated by one real structure forming its backbone, they are also partly fortuitous and are thus not kinematically coherent structures as a whole. Provided that the simulated and observed planes of satellites are indeed of the same nature, our results suggest that the VPoS of M31 is not a coherent disk and that one-third to one-half of its satellites must have large proper motions perpendicular to the plane

  3. Spatiotemporal prediction of fine particulate matter using high resolution satellite images in the southeastern U.S 2003–2011

    Science.gov (United States)

    Lee, Mihye; Kloog, Itai; Chudnovsky, Alexandra; Lyapustin, Alexei; Wang, Yujie; Melly, Steven; Coull, Brent; Koutrakis, Petros; Schwartz, Joel

    2016-01-01

    Numerous studies have demonstrated that fine particulate matter (PM2.5, particles smaller than 2.5 μm in aerodynamic diameter) is associated with adverse health outcomes. The use of ground monitoring stations of PM2.5 to assess personal exposure; however, induces measurement error. Land use regression provides spatially resolved predictions but land use terms do not vary temporally. Meanwhile, the advent of satellite-retrieved aerosol optical depth (AOD) products have made possible to predict the spatial and temporal patterns of PM2.5 exposures. In this paper, we used AOD data with other PM2.5 variables such as meteorological variables, land use regression, and spatial smoothing to predict daily concentrations of PM2.5 at a 1 km2 resolution of the southeastern United States including the seven states of Georgia, North Carolina, South Carolina, Alabama, Tennessee, Mississippi, and Florida for the years from 2003 through 2011. We divided the study area into 3 regions and applied separate mixed-effect models to calibrate AOD using ground PM2.5 measurements and other spatiotemporal predictors. Using 10-fold cross-validation, we obtained out of sample R2 values of 0.77, 0.81, and 0.70 with the square root of the mean squared prediction errors (RMSPE) of 2.89, 2.51, and 2.82 μg/m3 for regions 1, 2, and 3, respectively. The slopes of the relationships between predicted PM2.5 and held out measurements were approximately 1 indicating no bias between the observed and modeled PM2.5 concentrations. Predictions can be used in epidemiological studies investigating the effects of both acute and chronic exposures to PM2.5. Our model results will also extend the existing studies on PM2.5 which have mostly focused on urban areas due to the paucity of monitors in rural areas. PMID:26082149

  4. Downscaling of coarse resolution LAI products to achieve both high spatial and temporal resolution for regions of interest

    KAUST Repository

    Houborg, Rasmus

    2015-11-12

    This paper presents a flexible tool for spatio-temporal enhancement of coarse resolution leaf area index (LAI) products, which is readily adaptable to different land cover types, landscape heterogeneities and cloud cover conditions. The framework integrates a rule-based regression tree approach for estimating Landsat-scale LAI from existing 1 km resolution LAI products, and the Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM) to intelligently interpolate the downscaled LAI between Landsat acquisitions. Comparisons against in-situ records of LAI measured over corn and soybean highlights its utility for resolving sub-field LAI dynamics occurring over a range of plant development stages.

  5. On the assessment of spatial resolution of PET systems with iterative image reconstruction

    Science.gov (United States)

    Gong, Kuang; Cherry, Simon R.; Qi, Jinyi

    2016-03-01

    Spatial resolution is an important metric for performance characterization in PET systems. Measuring spatial resolution is straightforward with a linear reconstruction algorithm, such as filtered backprojection, and can be performed by reconstructing a point source scan and calculating the full-width-at-half-maximum (FWHM) along the principal directions. With the widespread adoption of iterative reconstruction methods, it is desirable to quantify the spatial resolution using an iterative reconstruction algorithm. However, the task can be difficult because the reconstruction algorithms are nonlinear and the non-negativity constraint can artificially enhance the apparent spatial resolution if a point source image is reconstructed without any background. Thus, it was recommended that a background should be added to the point source data before reconstruction for resolution measurement. However, there has been no detailed study on the effect of the point source contrast on the measured spatial resolution. Here we use point source scans from a preclinical PET scanner to investigate the relationship between measured spatial resolution and the point source contrast. We also evaluate whether the reconstruction of an isolated point source is predictive of the ability of the system to resolve two adjacent point sources. Our results indicate that when the point source contrast is below a certain threshold, the measured FWHM remains stable. Once the contrast is above the threshold, the measured FWHM monotonically decreases with increasing point source contrast. In addition, the measured FWHM also monotonically decreases with iteration number for maximum likelihood estimate. Therefore, when measuring system resolution with an iterative reconstruction algorithm, we recommend using a low-contrast point source and a fixed number of iterations.

  6. Species classification using Unmanned Aerial Vehicle (UAV)-acquired high spatial resolution imagery in a heterogeneous grassland

    Science.gov (United States)

    Lu, Bing; He, Yuhong

    2017-06-01

    Investigating spatio-temporal variations of species composition in grassland is an essential step in evaluating grassland health conditions, understanding the evolutionary processes of the local ecosystem, and developing grassland management strategies. Space-borne remote sensing images (e.g., MODIS, Landsat, and Quickbird) with spatial resolutions varying from less than 1 m to 500 m have been widely applied for vegetation species classification at spatial scales from community to regional levels. However, the spatial resolutions of these images are not fine enough to investigate grassland species composition, since grass species are generally small in size and highly mixed, and vegetation cover is greatly heterogeneous. Unmanned Aerial Vehicle (UAV) as an emerging remote sensing platform offers a unique ability to acquire imagery at very high spatial resolution (centimetres). Compared to satellites or airplanes, UAVs can be deployed quickly and repeatedly, and are less limited by weather conditions, facilitating advantageous temporal studies. In this study, we utilize an octocopter, on which we mounted a modified digital camera (with near-infrared (NIR), green, and blue bands), to investigate species composition in a tall grassland in Ontario, Canada. Seven flight missions were conducted during the growing season (April to December) in 2015 to detect seasonal variations, and four of them were selected in this study to investigate the spatio-temporal variations of species composition. To quantitatively compare images acquired at different times, we establish a processing flow of UAV-acquired imagery, focusing on imagery quality evaluation and radiometric correction. The corrected imagery is then applied to an object-based species classification. Maps of species distribution are subsequently used for a spatio-temporal change analysis. Results indicate that UAV-acquired imagery is an incomparable data source for studying fine-scale grassland species composition

  7. A dense camera network for cropland (CropInsight) - developing high spatiotemporal resolution crop Leaf Area Index (LAI) maps through network images and novel satellite data

    Science.gov (United States)

    Kimm, H.; Guan, K.; Luo, Y.; Peng, J.; Mascaro, J.; Peng, B.

    2017-12-01

    Monitoring crop growth conditions is of primary interest to crop yield forecasting, food production assessment, and risk management of individual farmers and agribusiness. Despite its importance, there are limited access to field level crop growth/condition information in the public domain. This scarcity of ground truth data also hampers the use of satellite remote sensing for crop monitoring due to the lack of validation. Here, we introduce a new camera network (CropInsight) to monitor crop phenology, growth, and conditions that are designed for the US Corn Belt landscape. Specifically, this network currently includes 40 sites (20 corn and 20 soybean fields) across southern half of the Champaign County, IL ( 800 km2). Its wide distribution and automatic operation enable the network to capture spatiotemporal variations of crop growth condition continuously at the regional scale. At each site, low-maintenance, and high-resolution RGB digital cameras are set up having a downward view from 4.5 m height to take continuous images. In this study, we will use these images and novel satellite data to construct daily LAI map of the Champaign County at 30 m spatial resolution. First, we will estimate LAI from the camera images and evaluate it using the LAI data collected from LAI-2200 (LI-COR, Lincoln, NE). Second, we will develop relationships between the camera-based LAI estimation and vegetation indices derived from a newly developed MODIS-Landsat fusion product (daily, 30 m resolution, RGB + NIR + SWIR bands) and the Planet Lab's high-resolution satellite data (daily, 5 meter, RGB). Finally, we will scale up the above relationships to generate high spatiotemporal resolution crop LAI map for the whole Champaign County. The proposed work has potentials to expand to other agro-ecosystems and to the broader US Corn Belt.

  8. THE IDEA IS TO USEMODIS IN CONJUNCTION WITH THE CURRENT LIMITED LANDSAT CAPABILITY, COMMERCIAL SATELLITES, ANDUNMANNED AERIAL VEHICLES (UAV), IN A MULTI-STAGE APPROACH TO MEET EPA INFORMATION NEEDS.REMOTE SENSING OVERVIEW: EPA CAPABILITIES, PRIORITY AGENCY APPLICATIONS, SENSOR/AIRCRAFT CAPABILITIES, COST CONSIDERATIONS, SPECTRAL AND SPATIAL RESOLUTIONS, AND TEMPORAL CONSIDERATIONS

    Science.gov (United States)

    EPA remote sensing capabilities include applied research for priority applications and technology support for operational assistance to clients across the Agency. The idea is to use MODIS in conjunction with the current limited Landsat capability, commercial satellites, and Unma...

  9. Spatial resolution of subsurface anthropogenic heat fluxes in cities

    Science.gov (United States)

    Benz, Susanne; Bayer, Peter; Menberg, Kathrin; Blum, Philipp

    2015-04-01

    Urban heat islands in the subsurface contain large quantities of energy in the form of elevated groundwater temperatures caused by anthropogenic heat fluxes (AHFS) into the subsurface. Hence, the objective of this study is to exemplarily quantify these AHFS and the generated thermal powers in two German cities, Karlsruhe and Cologne. A two-dimensional (2D) statistical analytical model of the vertical subsurface anthropogenic heat fluxes across the unsaturated zone was developed. The model consists of a so-called Local Monte Carlo approach that introduces a spatial representation of the following sources of AHFS: (1) elevated ground surface temperatures, (2) basements, (3) sewage systems, (4) sewage leakage, (5) subway tunnels, and (6) district heating networks. The results show that district heating networks induce the largest local AHFS with values larger than 60 W/m2 and one order of magnitude higher than the other evaluated heat sources. Only sewage pipes and basements reaching into the groundwater cause equally high heat fluxes, with maximal values of 40.37 W/m2 and 13.60 W/m2, respectively. While dominating locally, the district heating network is rather insignificant for the citywide energy budget in both urban subsurfaces. Heat from buildings (1.51 ± 1.36 PJ/a in Karlsruhe; 0.31 ± 0.14 PJ/a in Cologne) and elevated GST (0.34 ± 0.10 PJ/a in Karlsruhe; 0.42 ± 0.13 PJ/a in Cologne) are dominant contributors to the anthropogenic thermal power of the urban aquifer. In Karlsruhe, buildings are the source of 70% of the annual heat transported into the groundwater, which is mainly caused by basements reaching into the groundwater. A variance analysis confirms these findings: basement depth is the most influential factor to citywide thermal power in the studied cities with high groundwater levels. The spatial distribution of fluxes, however, is mostly influenced by the prevailing thermal gradient across the unsaturated zone. A relatively cold groundwater

  10. Measurement of spatial and density resolutions in x-ray nanocomputed tomography

    Science.gov (United States)

    Kawata, Y.; Kageyama, K.; Nakaya, Y.; Niki, N.; Umetani, K.; Yada, K.; Ohmatsu, H.; Eguchi, K.; Kaneko, M.; Moriyama, N.

    2009-02-01

    The latest generation of nano computed tomography (nano-CT) systems with sub-micrometer focus X-ray source is expected to yield non-invasive imaging of internal microstructure of objects with isotropic spatial resolution in the range of hundreds nanometers. Most recently commercial systems have become available for purchase. The quantitative characterization of the performance of nano-CT systems is important for evaluating the accuracy of size and density measurements of fine details in nano-CT images. The point spread function (PSF) and modulation transfer function (MTF) are calculated most commonly from the measurement of thin wire phantom for measuring the spatial resolution of clinical CT systems. However, a consistent method for describing the spatial resolution of nano-CT has not been utilized due to the requirement of a nanowire which is a wire of diameter of the order of tens of nanometers. This paper presents a method to characterize the spatial resolution in x/y-scan plane (transversal orientation) of nano-CT systems using a relatively large microwire in the PSF measurement. In this method, the MTF computed from the PSF is estimated on the basis of a two-Gaussian PSF model. Experimenting with microwire images with three different diameter sizes (3μm, 10μm, 30μm) obtained by the synchrotron radiation CT, we demonstrate the potential usefulness of the method for describing the spatial resolutions of nano-CT systems.

  11. High spatial and time resolutions with gas ionization detectors

    International Nuclear Information System (INIS)

    Pouthas, J.

    2001-09-01

    This document presents the principles and the characteristics of the gaseous ionisation detectors used in position and timing measurements. The first two parts recall the main notions (electron and ion motions, gaseous amplification, signal formation) and their applications to the proportional counter and the wire chamber. The explanation of the signal formation makes use of the Ramo theorem. The third part is devoted to the different types of wire chambers: drift or cathode strip chambers, TPC (time projection chamber). Some aspects on construction and ageing are also presented. Part 4 is on the detectors in which the multiplication is performed by a 'Parallel Plate' system (PPAC, Pestov counter). Special attention is paid to the RPCs (Resistive Plate Chambers) and their timing resolutions. Part 5 concentrates on 'Micro-pattern detectors' which use different kinds of microstructure for gaseous amplification. The new detectors MICROMEGAS, CAT (compteur a trous) and GEM (gas electron multiplier) and some of their applications are presented. The last part is a bibliography including some comments on the documents. (author)

  12. Progressive refining of spatial and temporal resolutions in a hydrological model: how far should we go?

    Science.gov (United States)

    de Lavenne, Alban; Ficchi, Andrea; Goullet, Julien

    2017-04-01

    Choosing a modelling resolution for an hydrological model is an important preliminary question. However, it is quite often arbitrary determined by the modeller experience according to the objective, the model capacity or the available measurements. The hydrological literature provides numerous studies which focus on the effect of refining either spatial resolution or (sometimes) temporal resolution in order to better catch hydrological response. In this study, we investigate the impact of changing simultaneously both resolutions on hydrological model performance. The idea is that these resolutions are linked and should be considered together. Thus, we look for the combination of spatial and temporal resolutions fitting at best each catchment behaviour and type of rainfall events. A large data set of 240 catchments scattered all around France is used, and in particular, we benefit from a high-resolution precipitation database (ANTILOPE, Météo-France) that describes hourly precipitation at 1 km2 resolution. Data were aggregated at different time steps (1h, 3h, 6h, 12h and 24h). Streamflow simulations are performed at these different time steps using the GR5 model in its lumped and semi-distributed version (GRSD, de Lavenne et al. (2016)), with a mesh grid of 500, 250, 100 and 50 km2. Ten different indices are used to describe spatio-temporal characteristics of rainfall events, in order to analyse in which contexts refined resolutions are needed to improve the performance of the model. These indices characterise the spatial variability, localisation, movement, intensity and temporal variability of rainfall events. In addition to some indices already reported in the hydrological literature, we propose some new indices like an indice usually applied in economics. This analysis at different time steps, events and catchments demonstrates the limits for some of them and allows to propose some corrections (Goullet J., 2016). Model performances are shown to be

  13. Mapping Impervious Surface Expansion using Medium-resolution Satellite Image Time Series: A Case Study in the Yangtze River Delta, China

    Science.gov (United States)

    Gao, Feng; DeColstoun, Eric Brown; Ma, Ronghua; Weng, Qihao; Masek, Jeffrey G.; Chen, Jin; Pan, Yaozhong; Song, Conghe

    2012-01-01

    Cities have been expanding rapidly worldwide, especially over the past few decades. Mapping the dynamic expansion of impervious surface in both space and time is essential for an improved understanding of the urbanization process, land-cover and land-use change, and their impacts on the environment. Landsat and other medium-resolution satellites provide the necessary spatial details and temporal frequency for mapping impervious surface expansion over the past four decades. Since the US Geological Survey opened the historical record of the Landsat image archive for free access in 2008, the decades-old bottleneck of data limitation has gone. Remote-sensing scientists are now rich with data, and the challenge is how to make best use of this precious resource. In this article, we develop an efficient algorithm to map the continuous expansion of impervious surface using a time series of four decades of medium-resolution satellite images. The algorithm is based on a supervised classification of the time-series image stack using a decision tree. Each imerpervious class represents urbanization starting in a different image. The algorithm also allows us to remove inconsistent training samples because impervious expansion is not reversible during the study period. The objective is to extract a time series of complete and consistent impervious surface maps from a corresponding times series of images collected from multiple sensors, and with a minimal amount of image preprocessing effort. The approach was tested in the lower Yangtze River Delta region, one of the fastest urban growth areas in China. Results from nearly four decades of medium-resolution satellite data from the Landsat Multispectral Scanner (MSS), Thematic Mapper (TM), Enhanced Thematic Mapper plus (ETM+) and China-Brazil Earth Resources Satellite (CBERS) show a consistent urbanization process that is consistent with economic development plans and policies. The time-series impervious spatial extent maps derived

  14. Anthropogenic heat flux: advisable spatial resolutions when input data are scarce

    Science.gov (United States)

    Gabey, A. M.; Grimmond, C. S. B.; Capel-Timms, I.

    2018-02-01

    Anthropogenic heat flux (QF) may be significant in cities, especially under low solar irradiance and at night. It is of interest to many practitioners including meteorologists, city planners and climatologists. QF estimates at fine temporal and spatial resolution can be derived from models that use varying amounts of empirical data. This study compares simple and detailed models in a European megacity (London) at 500 m spatial resolution. The simple model (LQF) uses spatially resolved population data and national energy statistics. The detailed model (GQF) additionally uses local energy, road network and workday population data. The Fractions Skill Score (FSS) and bias are used to rate the skill with which the simple model reproduces the spatial patterns and magnitudes of QF, and its sub-components, from the detailed model. LQF skill was consistently good across 90% of the city, away from the centre and major roads. The remaining 10% contained elevated emissions and "hot spots" representing 30-40% of the total city-wide energy. This structure was lost because it requires workday population, spatially resolved building energy consumption and/or road network data. Daily total building and traffic energy consumption estimates from national data were within ± 40% of local values. Progressively coarser spatial resolutions to 5 km improved skill for total QF, but important features (hot spots, transport network) were lost at all resolutions when residential population controlled spatial variations. The results demonstrate that simple QF models should be applied with conservative spatial resolution in cities that, like London, exhibit time-varying energy use patterns.

  15. Impact of spatial resolution on results of esophageal high-resolution manometry

    NARCIS (Netherlands)

    de Schepper, H. U.; Kessing, B. F.; Weijenborg, P. W.; Oors, J. M.; Smout, A. J. P. M.; Bredenoord, A. J.

    2014-01-01

    The Chicago classification for esophageal motility disorders was designed for a 36-channel manometry system with sensors spaced at 1 cm. However, many motility laboratories outside the USA use catheters with a lower resolution in the segments outside the esophagogastric junction. Our aim was to

  16. Detection of a weak meddy-like anomaly from high-resolution satellite SST maps

    Directory of Open Access Journals (Sweden)

    Mikhail Emelianov

    2012-09-01

    Full Text Available Despite the considerable impact of meddies on climate through the long-distance transport of properties, a consistent observation of meddy generation and propagation in the ocean is rather elusive. Meddies propagate at about 1000 m below the ocean surface, so satellite sensors are not able to detect them directly and finding them in the open ocean is more fortuitous than intentional. However, a consistent census of meddies and their paths is required in order to gain knowledge about their role in transporting properties such as heat and salt. In this paper we propose a new methodology for processing high-resolution sea surface temperature maps in order to detect meddy-like anomalies in the open ocean on a near-real-time basis. We present an example of detection, involving an atypical meddy-like anomaly that was confirmed as such by in situ measurements.

  17. Automatic Centerline Extraction of Coverd Roads by Surrounding Objects from High Resolution Satellite Images

    Science.gov (United States)

    Kamangir, H.; Momeni, M.; Satari, M.

    2017-09-01

    This paper presents an automatic method to extract road centerline networks from high and very high resolution satellite images. The present paper addresses the automated extraction roads covered with multiple natural and artificial objects such as trees, vehicles and either shadows of buildings or trees. In order to have a precise road extraction, this method implements three stages including: classification of images based on maximum likelihood algorithm to categorize images into interested classes, modification process on classified images by connected component and morphological operators to extract pixels of desired objects by removing undesirable pixels of each class, and finally line extraction based on RANSAC algorithm. In order to evaluate performance of the proposed method, the generated results are compared with ground truth road map as a reference. The evaluation performance of the proposed method using representative test images show completeness values ranging between 77% and 93%.

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

    Science.gov (United States)

    Corucci, Linda; Masini, Andrea; Cococcioni, Marco

    2011-01-01

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

  19. Luobei graphite mines surrounding ecological environment monitoring based on high-resolution satellite data

    Science.gov (United States)

    Zhang, Lifeng; Liu, Xiaosha; Wan, Huawei; Liu, Xiaoman

    2014-11-01

    Graphite is one of the important industrial mineral raw materials, but the high content of heavy metals in tailings may cause soil pollution and other regional ecological environmental problems. Luobei has already become the largest production base of graphite. To find out the ecological situation in the region, further ecological risk analysis has been carried out. Luobei graphite mine which is located in Yabdanhe basin has been selected as the study area, SVM classifiers method with the support of GF-1 Satellite remote sensing data has been used, which is the first high-resolution earth observation satellite in China. The surrounding ecological environment was monitored and its potential impact on the ecological environment was analyzed by GIS platform. The results showed that the Luobei graphite mine located Yadanhe basin covers an area of 499.65 km2, the main types of forest ecosystems ( 44.05% of the total basin area ), followed by agricultural area( 35.14% ), grass area( 15.52% ), residential area ( 4.34% ), mining area ( 0.64% ) and water area( 0.30% ). By confirming the classification results, the total accuracy is 91.61%, the Kappa coefficient is 0.8991. Overall, GF-1 Satellite data can obtain regional ecosystems quickly, and provide a better data support for regional ecological resource protection zone. For Luobei graphite mines area, farmland and residential areas within its watershed are most vulnerable to mining, the higher proportion of farmland in duck river basin. The regulatory tailings need to be strengthened in the process of graphite mining processing.

  20. Performance of High Resolution Satellite Rainfall Products over Data Scarce Parts of Eastern Ethiopia

    Directory of Open Access Journals (Sweden)

    Shimelis B. Gebere

    2015-09-01

    Full Text Available Accurate estimation of rainfall in mountainous areas is necessary for various water resource-related applications. Though rain gauges accurately measure rainfall, they are rarely found in mountainous regions and satellite rainfall data can be used as an alternative source over these regions. This study evaluated the performance of three high-resolution satellite rainfall products, the Tropical Rainfall Measuring Mission (TRMM 3B42, the Global Satellite Mapping of Precipitation (GSMaP_MVK+, and the Precipitation Estimation from Remotely-Sensed Information using Artificial Neural Networks (PERSIANN at daily, monthly, and seasonal time scales against rain gauge records over data-scarce parts of Eastern Ethiopia. TRMM 3B42 rain products show relatively better performance at the three time scales, while PERSIANN did much better than GSMaP. At the daily time scale, TRMM correctly detected 88% of the rainfall from the rain gauge. The correlation at the monthly time scale also revealed that the TRMM has captured the observed rainfall better than the other two. For Belg (short rain and Kiremt (long rain seasons, the TRMM did better than the others by far. However, during Bega (dry season, PERSIANN showed a relatively good estimate. At all-time scales, noticing the bias, TRMM tends to overestimate, while PERSIANN and GSMaP tend to underestimate the rainfall. The overall result suggests that monthly and seasonal TRMM rainfall performed better than daily rainfall. It has also been found that both GSMaP and PERSIANN performed better in relatively flat areas than mountainous areas. Before the practical use of TRMM, the RMSE value needs to be improved by considering the topography of the study area or adjusting the bias.

  1. Hi-Res scan mode in clinical MDCT systems: Experimental assessment of spatial resolution performance.

    Science.gov (United States)

    Cruz-Bastida, Juan P; Gomez-Cardona, Daniel; Li, Ke; Sun, Heyi; Hsieh, Jiang; Szczykutowicz, Timothy P; Chen, Guang-Hong

    2016-05-01

    The introduction of a High-Resolution (Hi-Res) scan mode and another associated option that combines Hi-Res mode with the so-called High Definition (HD) reconstruction kernels (referred to as a Hi-Res/HD mode in this paper) in some multi-detector CT (MDCT) systems offers new opportunities to increase spatial resolution for some clinical applications that demand high spatial resolution. The purpose of this work was to quantify the in-plane spatial resolution along both the radial direction and tangential direction for the Hi-Res and Hi-Res/HD scan modes at different off-center positions. A technique was introduced and validated to address the signal saturation problem encountered in the attempt to quantify spatial resolution for the Hi-Res and Hi-Res/HD scan modes. Using the proposed method, the modulation transfer functions (MTFs) of a 64-slice MDCT system (Discovery CT750 HD, GE Healthcare) equipped with both Hi-Res and Hi-Res/HD modes were measured using a metal bead at nine different off-centered positions (0-16 cm with a step size of 2 cm); at each position, both conventional scans and Hi-Res scans were performed. For each type of scan and position, 80 repeated acquisitions were performed to reduce noise induced uncertainties in the MTF measurements. A total of 15 reconstruction kernels, including eight conventional kernels and seven HD kernels, were used to reconstruct CT images of the bead. An ex vivo animal study consisting of a bone fracture model was performed to corroborate the MTF results, as the detection of this high-contrast and high frequency task is predominantly determined by spatial resolution. Images of this animal model generated by different scan modes and reconstruction kernels were qualitatively compared with the MTF results. At the centered position, the use of Hi-Res mode resulted in a slight improvement in the MTF; each HD kernel generated higher spatial resolution than its counterpart conventional kernel. However, the MTF along the

  2. Automatic Cloud Detection for Chinese High Resolution Remote Sensing Satellite Imagery

    Directory of Open Access Journals (Sweden)

    TAN Kai

    2016-05-01

    Full Text Available Cloud detection is always an arduous problem in satellite imagery processing, especially the thin cloud which has the similar spectral characteristics as ground surfacehas long been the obstacle of the production of imagery product. In this paper, an automatic cloud detection method for Chinese high resolution remote sensing satellite imagery is introduced to overcome this problem.Firstly, the image is transformed from RGB to HIS color space by an improved color transformation model. The basic cloud coverage figure is obtained by using the information of intensity and saturation,followed by getting the modified figure with the information of near-infrared band and hue. Methods of histogram equalization and bilateral filtering, combined with conditioned Otsu thresholding are adopted to generate texture information. Then the cloud seed figureis obtained by using texture information to eliminate the existed errors in the modified figure. Finally, cloud covered areas are accurately extracted by integration of intensity information from the HIS color space and cloud seed figure. Compared to the detection results of other automatic and interactive methods, the overall accuracy of our proposed method achieves nearly 10% improvement, and it is capable of improving the efficiency of cloud detection significantly.

  3. Rule-based land cover classification from very high-resolution satellite image with multiresolution segmentation

    Science.gov (United States)

    Haque, Md. Enamul; Al-Ramadan, Baqer; Johnson, Brian A.

    2016-07-01

    Multiresolution segmentation and rule-based classification techniques are used to classify objects from very high-resolution satellite images of urban areas. Custom rules are developed using different spectral, geometric, and textural features with five scale parameters, which exploit varying classification accuracy. Principal component analysis is used to select the most important features out of a total of 207 different features. In particular, seven different object types are considered for classification. The overall classification accuracy achieved for the rule-based method is 95.55% and 98.95% for seven and five classes, respectively. Other classifiers that are not using rules perform at 84.17% and 97.3% accuracy for seven and five classes, respectively. The results exploit coarse segmentation for higher scale parameter and fine segmentation for lower scale parameter. The major contribution of this research is the development of rule sets and the identification of major features for satellite image classification where the rule sets are transferable and the parameters are tunable for different types of imagery. Additionally, the individual objectwise classification and principal component analysis help to identify the required object from an arbitrary number of objects within images given ground truth data for the training.

  4. AUTOMATIC BLOCKED ROADS ASSESSMENT AFTER EARTHQUAKE USING HIGH RESOLUTION SATELLITE IMAGERY

    Directory of Open Access Journals (Sweden)

    H. Rastiveis

    2015-12-01

    Full Text Available In 2010, an earthquake in the city of Port-au-Prince, Haiti, happened quite by chance an accident and killed over 300000 people. According to historical data such an earthquake has not occurred in the area. Unpredictability of earthquakes has necessitated the need for comprehensive mitigation efforts to minimize deaths and injuries. Blocked roads, caused by debris of destroyed buildings, may increase the difficulty of rescue activities. In this case, a damage map, which specifies blocked and unblocked roads, can be definitely helpful for a rescue team. In this paper, a novel method for providing destruction map based on pre-event vector map and high resolution world view II satellite images after earthquake, is presented. For this purpose, firstly in pre-processing step, image quality improvement and co-coordination of image and map are performed. Then, after extraction of texture descriptor from the image after quake and SVM classification, different terrains are detected in the image. Finally, considering the classification results, specifically objects belong to “debris” class, damage analysis are performed to estimate the damage percentage. In this case, in addition to the area objects in the “debris” class their shape should also be counted. The aforementioned process are performed on all the roads in the road layer.In this research, pre-event digital vector map and post-event high resolution satellite image, acquired by Worldview-2, of the city of Port-au-Prince, Haiti's capital, were used to evaluate the proposed method. The algorithm was executed on 1200×800 m2 of the data set, including 60 roads, and all the roads were labelled correctly. The visual examination have authenticated the abilities of this method for damage assessment of urban roads network after an earthquake.

  5. Improvement of range spatial resolution of medical ultrasound imaging by element-domain signal processing

    Science.gov (United States)

    Hasegawa, Hideyuki

    2017-07-01

    The range spatial resolution is an important factor determining the image quality in ultrasonic imaging. The range spatial resolution in ultrasonic imaging depends on the ultrasonic pulse length, which is determined by the mechanical response of the piezoelectric element in an ultrasonic probe. To improve the range spatial resolution without replacing the transducer element, in the present study, methods based on maximum likelihood (ML) estimation and multiple signal classification (MUSIC) were proposed. The proposed methods were applied to echo signals received by individual transducer elements in an ultrasonic probe. The basic experimental results showed that the axial half maximum of the echo from a string phantom was improved from 0.21 mm (conventional method) to 0.086 mm (ML) and 0.094 mm (MUSIC).

  6. Effect of electrode density and measurement noise on the spatial resolution of cortical potential distribution.

    Science.gov (United States)

    Ryynänen, Outi R M; Hyttinen, Jari A K; Laarne, Päivi H; Malmivuo, Jaakko A

    2004-09-01

    The purpose of the present study was to examine the spatial resolution of electroencephalography (EEG) by means of inverse cortical EEG solution. The main interest was to study how the number of measurement electrodes and the amount of measurement noise affects the spatial resolution. A three-layer spherical head model was used to obtain the source-field relationship of cortical potentials and scalp EEG field. Singular value decomposition was used to evaluate the spatial resolution with various measurement noise estimates. The results suggest that as the measurement noise increases the advantage of dense electrode systems is decreased. With low realistic measurement noise, a more accurate inverse cortical potential distribution can be obtained with an electrode system where the distance between two electrodes is as small as 16 mm, corresponding to as many as 256 measurement electrodes. In clinical measurement environments, it is always beneficial to have at least 64 measurement electrodes.

  7. Real-time and quantitative isotropic spatial resolution susceptibility imaging for magnetic nanoparticles

    Science.gov (United States)

    Pi, Shiqiang; Liu, Wenzhong; Jiang, Tao

    2018-03-01

    The magnetic transparency of biological tissue allows the magnetic nanoparticle (MNP) to be a promising functional sensor and contrast agent. The complex susceptibility of MNPs, strongly influenced by particle concentration, excitation magnetic field and their surrounding microenvironment, provides significant implications for biomedical applications. Therefore, magnetic susceptibility imaging of high spatial resolution will give more detailed information during the process of MNP-aided diagnosis and therapy. In this study, we present a novel spatial magnetic susceptibility extraction method for MNPs under a gradient magnetic field, a low-frequency drive magnetic field, and a weak strength high-frequency magnetic field. Based on this novel method, a magnetic particle susceptibility imaging (MPSI) of millimeter-level spatial resolution (<3 mm) was achieved using our homemade imaging system. Corroborated by the experimental results, the MPSI shows real-time (1 s per frame acquisition) and quantitative abilities, and isotropic high resolution.

  8. Study on spatial resolution improvement of distributed temperature sensor system by linear fitting algorithm

    Science.gov (United States)

    Sun, Miao; Tang, Yuquan; Li, Jun; Yang, Shuang; Dong, Fengzhong

    2015-10-01

    Spatial resolution determines the minimum space unit that a distributed temperature sensor system can distinguish along the fiber thus it is an important parameter to evaluate the performance of the distributed temperature sensor system. A typical distributed temperature sensor system with a spatial resolution of 5m is built and an algorithm of linear fitting correction is proposed to realize temperature measurement of fiber length shorter than 5m accurately. With the method of linear fitting correction, the spatial resolution of the distributed temperature sensor system has been improved from 5m to 1m. The measured temperature of the DTS system is well calibrated by using linear fitting correction algorithm with a fiber length of 4m, 3m, 2m and 1m respectively. The maximum error of the corrective temperature is 2° for long term measurement.

  9. Identification of the potential gap areas for the developing green infrastructure in the Urban area using High resolution satellite Imagery

    Science.gov (United States)

    Kanaparthi, M. B.

    2017-12-01

    In India urban population is growing day by day which is causing air pollution less air quality finally leading to climate change and global warming. To mitigate the effect of the climate change we need to plant more trees in the urban area. The objective of this study is develop a plan to improve the urban Green Infrastructure (GI) to fight against the climate change and global warming. Improving GI is a challenging and difficult task in the urban areas because land unavailability of land, to overcome the problem greenways is a good the solution. Greenway is a linear open space developed along the rivers, canals, roads in the urban areas to form a network of green spaces. Roads are the most common structures in the urban area. The idea is to develop the greenways alongside the road to connecting the different green spaces. Tree crowns will act as culverts to connect the green spaces. This will require the spatial structure of the green space, distribution of trees along the roads and the gap areas along the road where more trees can be planted. This can be achieved with help of high resolution Satellite Imagery and the object extraction techniques. This study was carried in the city Bhimavaram which is located in state Andhra Pradesh. The final outcome of this study is potential gap areas for planting trees in the city.

  10. Bridging Ridge-to-Reef Patches: Seamless Classification of the Coast Using Very High Resolution Satellite

    Directory of Open Access Journals (Sweden)

    Serge Planes

    2013-07-01

    Full Text Available The structure and functioning of coral reef coastal zones are currently coping with an increasing variety of threats, thereby altering the coastal spatial patterns at an accelerated pace. Understanding and predicting the evolution of these highly valuable coastal ecosystems require reliable and frequent mapping and monitoring of both inhabited terrestrial and marine areas at the individual tree and coral colony spatial scale. The very high spatial resolution (VHR mapping that was recently spearheaded by WorldView-2 (WV2 sensor with 2 m and 0.5 m multispectral (MS and panchromatic (Pan bands has the potential to address this burning issue. The objective of this study was to classify nine terrestrial and twelve marine patch classes with respect to spatial resolution enhancement and coast integrity using eight bands of the WV2 sensor on a coastal zone of Moorea Island, French Polynesia. The contribution of the novel WV2 spectral bands towards classification accuracy at 2 m and 0.5 m were tested using traditional and innovative Pan-sharpening techniques. The land and water classes were examined both separately and combinedly. All spectral combinations that were built only with the novel WV2 bands systematically increased the overall classification accuracy of the standard four band classification. The overall best contribution was attributed to the coastal-red edge-near infrared (NIR 2 combination (Kappagain = 0.0287, which significantly increased the fleshy and encrusting algae (User’s Accuracygain = 18.18% class. However, the addition of the yellow-NIR2 combination dramatically impacted the hard coral/algae patches class (Producer’s Accuracyloss = −20.88%. Enhancement of the spatial resolution reduced the standard classification accuracy, depending on the Pan-sharpening technique. The proposed composite method (local maximum provided better overall results than the commonly used sensor method (systematic. However, the sensor technique

  11. High-Resolution Spatially Gridded Biomass Burning Emissions Inventory In Asia

    Science.gov (United States)

    Vadrevu, K. P.; Lau, W. K.; da Silva, A.; Justice, C. O.

    2012-12-01

    Biomass burning is long recognized an important source of greenhouse gas (GHG) emissions (CO2, CO, CH4, H2, CH3Cl, NO, HCN, CH3CN, COS, etc) and aerosols. In the Asian region, the current estimates of greenhouse gas emissions and aerosols from biomass burning are severely constrained by the lack of reliable statistics on fire distribution and frequency, and the lack of accurate estimates of area burned, fuel load, etc. As a part of NASA funded interdisciplinary research project entitled "Effects of biomass burning on water cycle and climate in the monsoon Asia", we initially developed a high resolution spatially gridded emissions inventory from the biomass burning for Indo-Ganges region and then extended the inventory to the entire Asia. Active fires from MODIS as well as high resolution LANDSAT data have been used to fine-tune the MODIS burnt area products for estimating the emissions. Locally based emission factors were used to refine the gaseous emissions. The resulting emissions data has been gridded at 5-minute intervals. We also compared our emission estimates with the other emission products such as Global Fire Assimilation System (GFAS), Quick fire emissions database (QFED) and Global Fire Emissions Database (GFED). Our results revealed significant vegetation fires from Myanmar, India, Indonesia, China, Laos, Thailand, Cambodia and Vietnam. These seven countries accounted for 92.4% of all vegetation fires in the Asian region. Satellite-based vegetation fire analysis showed the highest fire occurrence in the closed to open shrub land category, (19%) followed by closed to open, broadleaved evergreen-semi deciduous forest (16%), rain fed croplands (17%), post flooded or irrigated croplands (12%), mosaic cropland vegetation (11%), mosaic vegetation/cropland (10%). Emission contribution from agricultural fires was significant, however, showed discrepancies due to low confidence in burnt areas and lack of crop specific emission factors. Further, our results

  12. Research on the affect of differential-images technique to the resolution of infrared spatial camera

    Science.gov (United States)

    Jin, Guang; An, Yuan; Qi, Yingchun; Hu, Fusheng

    2007-12-01

    The optical system of infrared spatial camera adopts bigger relative aperture and bigger pixel size on focal plane element. These make the system have bulky volume and low resolution. The potential of the optical systems can not be exerted adequately. So, one method for improving resolution of infrared spatial camera based on multi-frame difference-images is introduced in the dissertation. The method uses more than one detectors to acquire several difference images, and then reconstructs a new high-resolution image from these images through the relationship of pixel grey value. The technique of difference-images that uses more than two detectors is researched, and it can improve the resolution 2.5 times in theory. The relationship of pixel grey value between low-resolution difference-images and high-resolution image is found by analyzing the energy of CCD sampling, a general relationship between the enhanced times of the resolution of the detected figure with differential method and the least count of CCD that will be used to detect figure is given. Based on the research of theory, the implementation process of utilizing difference-images technique to improve the resolution of the figure was simulated used Matlab software by taking a personality image as the object, and the software can output the result as an image. The result gotten from the works we have finished proves that the technique is available in high-resolution image reconstruction. The resolution of infrared spatial camera can be improved evidently when holding the size of optical structure or using big size detector by applying for difference image technique. So the technique has a high value in optical remote fields.

  13. Crowding in Visual Working Memory Reveals Its Spatial Resolution and the Nature of Its Representations.

    Science.gov (United States)

    Tamber-Rosenau, Benjamin J; Fintzi, Anat R; Marois, René

    2015-09-01

    Spatial resolution fundamentally limits any image representation. Although this limit has been extensively investigated for perceptual representations by assessing how neighboring flankers degrade the perception of a peripheral target with visual crowding, the corresponding limit for representations held in visual working memory (VWM) is unknown. In the present study, we evoked crowding in VWM and directly compared resolution in VWM and perception. Remarkably, the spatial resolution of VWM proved to be no worse than that of perception. However, mixture modeling of errors caused by crowding revealed the qualitatively distinct nature of these representations. Perceptual crowding errors arose from both increased imprecision in target representations and substitution of flankers for targets. By contrast, VWM crowding errors arose exclusively from substitutions, which suggests that VWM transforms analog perceptual representations into discrete items. Thus, although perception and VWM share a common resolution limit, exceeding this limit reveals distinct mechanisms for perceiving images and holding them in mind. © The Author(s) 2015.

  14. Temporal and Spatial Analysis of Precipitation in Guizhou Based on TRMM 3B42 Satellite Data

    Science.gov (United States)

    Wu, Jianfeng; Zhang, Fengtai; Cao, Guangjie; Li, Wei; Zhao, Xuemei

    2017-08-01

    Precipitation is an important part of the earth’s climate system. This article makes full use of the advantages of remote sensing images. In this paper, the TRMM 3B42 satellite precipitation from 1998 to 2013 is selected as the data source and Guizhou Province as the research area. The temporal and spatial distribution characteristics of precipitation in Guizhou Province are studied by linear trend estimation, linear regression analysis and ArcGIS spatial analysis. The conclusion as below: Precipitation shows a decreasing trend from southeast to northwest in Guizhou Province. From the seasonal scale, Precipitation is mainly concentrated in summer and the least precipitation in winter. Over the past 16 years, precipitation in Guizhou Province has shown a fluctuating change. Summer precipitation trend is more obvious. And winter precipitation is not obvious.

  15. Using very high resolution satellite images to identify coastal zone dynamics at North Western Black Sea

    Science.gov (United States)

    Florin Zoran, Liviu; Ionescu Golovanov, Carmen; Zoran, Maria

    2010-05-01

    The availability of updated information about the extension and characteristics of land cover is a crucial issue in the perspective of a correct landscape planning and management of marine coastal zones. Satellite remote sensing data can provide accurate information about land coverage at different scales and the recent availability of very high resolution images definitely improved the precision of coastal zone spatio-temporal changes. The Romanian North Western coastal and shelf zones of the Black Sea and Danube delta are a mosaic of complex, interacting ecosystems, rich natural resources and socio-economic activity. Dramatic changes in the Black Sea's ecosystem and resources are due to natural and anthropogenic causes (increase in the nutrient and pollutant load of rivers input, industrial and municipal wastewater pollution along the coast, and dumping on the open sea). A scientific management system for protection, conservation and restoration must be based on reliable information on bio-geophysical and geomorphologic processes, coastal erosion, sedimentation dynamics, mapping of macrophyte fields, water quality, and climatic change effects. Use of satellite images is of great help for coastal zone monitoring and environmental impact assessment. Synergetic use of in situ measurements with multisensors satellite data could provide a complex assessment of spatio-temporal changes. In this study was developed a method for extracting coastal zone features information as well as landcover dynamics from IKONOS, very high resolution images for North-Western Black Sea marine coastal zone. The main objective was obtaining reliable data about the spatio-temporal coastal zone changes in two study areas located in Constanta urban area and Danube Delta area. We used an object-oriented approach based on preliminary segmentation and classification of the resulting object. First of all, segmentation parameters were tested and selected comparing segmented polygons with

  16. PIV study of flow field in Rushton turbine stirred vessel influenced by spatial resolution

    Czech Academy of Sciences Publication Activity Database

    Kotek, M.; Jašíková, D.; Kysela, Bohuš; Šulc, R.; Kopecký, V.

    2017-01-01

    Roč. 2, č. 2017 (2017), s. 79-84 ISSN 2367-8992 R&D Projects: GA ČR GA16-20175S Grant - others:GA MŠk(CZ) LO1201 Institutional support: RVO:67985874 Keywords : mixing process * PIV measurement * spatial resolution Subject RIV: JP - Industrial Processing OBOR OECD: Fluids and plasma physics (including surface physics) http://www.iaras.org/iaras/ home /caijtam/piv-study-of-flow-field-in-rushton-turbine-stirred-vessel-influenced-by-spatial-resolution

  17. Prevalence of Pure Versus Mixed Snow Cover Pixels across Spatial Resolutions in Alpine Environments

    Directory of Open Access Journals (Sweden)

    David J. Selkowitz

    2014-12-01

    Full Text Available Remote sensing of snow-covered area (SCA can be binary (indicating the presence/absence of snow cover at each pixel or fractional (indicating the fraction of each pixel covered by snow. Fractional SCA mapping provides more information than binary SCA, but is more difficult to implement and may not be feasible with all types of remote sensing data. The utility of fractional SCA mapping relative to binary SCA mapping varies with the intended application as well as by spatial resolution, temporal resolution and period of interest, and climate. We quantified the frequency of occurrence of partially snow-covered (mixed pixels at spatial resolutions between 1 m and 500 m over five dates at two study areas in the western U.S., using 0.5 m binary SCA maps derived from high spatial resolution imagery aggregated to fractional SCA at coarser spatial resolutions. In addition, we used in situ monitoring to estimate the frequency of partially snow-covered conditions for the period September 2013–August 2014 at 10 60-m grid cell footprints at two study areas with continental snow climates. Results from the image analysis indicate that at 40 m, slightly above the nominal spatial resolution of Landsat, mixed pixels accounted for 25%–93% of total pixels, while at 500 m, the nominal spatial resolution of MODIS bands used for snow cover mapping, mixed pixels accounted for 67%–100% of total pixels. Mixed pixels occurred more commonly at the continental snow climate site than at the maritime snow climate site. The in situ data indicate that some snow cover was present between 186 and 303 days, and partial snow cover conditions occurred on 10%–98% of days with snow cover. Four sites remained partially snow-free throughout most of the winter and spring, while six sites were entirely snow covered throughout most or all of the winter and spring. Within 60 m grid cells, the late spring/summer transition from snow-covered to snow-free conditions lasted 17–56 days

  18. Resolution enhancement method for lensless in-line holographic microscope with spatially-extended light source.

    Science.gov (United States)

    Feng, Shaodong; Wu, Jigang

    2017-10-02

    We propose a resolution enhancement method for lensless in-line holographic microscope (LIHM) with spatially-extended light source, where the resolution is normally deteriorated by the insufficient spatial coherence of the illumination. In our LIHM setup, a light-emitting diode (LED), which was a spatially-extended light source, directly illuminated the sample, and the in-line hologram were recorded by a CMOS imaging sensor located behind the sample. In our holographic reconstruction process, the in-line hologram was first deconvoled with a properly resized image of the LED illumination area, and then back-propagated with scalar diffraction formula to reconstruct the sample image. We studied the hologram forming process and showed that the additional deconvolution process besides normal scalar diffraction reconstruction in LIHM can effectively enhance the imaging resolution. The resolution enhancements capability was calibrated by numerical simulations and imaging experiments with the U.S. air force target as the sample. We also used our LIHM to image the wing of a green lacewing to further demonstrate the capability of our methods for practical imaging applications. Our methods provide a way for LIHM to achieve satisfactory resolution with less stringent requirement for spatial coherence of the source and could reduce the cost for compact imaging system.

  19. Simulations of the temporal and spatial resolution for a compact time-resolved electron diffractometer

    Science.gov (United States)

    Robinson, Matthew S.; Lane, Paul D.; Wann, Derek A.

    2016-02-01

    A novel compact electron gun for use in time-resolved gas electron diffraction experiments has recently been designed and commissioned. In this paper we present and discuss the extensive simulations that were performed to underpin the design in terms of the spatial and temporal qualities of the pulsed electron beam created by the ionisation of a gold photocathode using a femtosecond laser. The response of the electron pulses to a solenoid lens used to focus the electron beam has also been studied. The simulated results show that focussing the electron beam affects the overall spatial and temporal resolution of the experiment in a variety of ways, and that factors that improve the resolution of one parameter can often have a negative effect on the other. A balance must, therefore, be achieved between spatial and temporal resolution. The optimal experimental time resolution for the apparatus is predicted to be 416 fs for studies of gas-phase species, while the predicted spatial resolution of better than 2 nm-1 compares well with traditional time-averaged electron diffraction set-ups.

  20. Coherent optical adaptive technique improves the spatial resolution of STED microscopy in thick samples

    Science.gov (United States)

    Yan, Wei; Yang, Yanlong; Tan, Yu; Chen, Xun; Li, Yang; Qu, Junle; Ye, Tong

    2018-01-01

    Stimulated emission depletion microscopy (STED) is one of far-field optical microscopy techniques that can provide sub-diffraction spatial resolution. The spatial resolution of the STED microscopy is determined by the specially engineered beam profile of the depletion beam and its power. However, the beam profile of the depletion beam may be distorted due to aberrations of optical systems and inhomogeneity of specimens’ optical properties, resulting in a compromised spatial resolution. The situation gets deteriorated when thick samples are imaged. In the worst case, the sever distortion of the depletion beam profile may cause complete loss of the super resolution effect no matter how much depletion power is applied to specimens. Previously several adaptive optics approaches have been explored to compensate aberrations of systems and specimens. However, it is hard to correct the complicated high-order optical aberrations of specimens. In this report, we demonstrate that the complicated distorted wavefront from a thick phantom sample can be measured by using the coherent optical adaptive technique (COAT). The full correction can effectively maintain and improve the spatial resolution in imaging thick samples. PMID:29400356

  1. Coherent optical adaptive technique improves the spatial resolution of STED microscopy in thick samples.

    Science.gov (United States)

    Yan, Wei; Yang, Yanlong; Tan, Yu; Chen, Xun; Li, Yang; Qu, Junle; Ye, Tong

    2017-06-01

    Stimulated emission depletion microscopy (STED) is one of far-field optical microscopy techniques that can provide sub-diffraction spatial resolution. The spatial resolution of the STED microscopy is determined by the specially engineered beam profile of the depletion beam and its power. However, the beam profile of the depletion beam may be distorted due to aberrations of optical systems and inhomogeneity of specimens' optical properties, resulting in a compromised spatial resolution. The situation gets deteriorated when thick samples are imaged. In the worst case, the sever distortion of the depletion beam profile may cause complete loss of the super resolution effect no matter how much depletion power is applied to specimens. Previously several adaptive optics approaches have been explored to compensate aberrations of systems and specimens. However, it is hard to correct the complicated high-order optical aberrations of specimens. In this report, we demonstrate that the complicated distorted wavefront from a thick phantom sample can be measured by using the coherent optical adaptive technique (COAT). The full correction can effectively maintain and improve the spatial resolution in imaging thick samples.

  2. The spatial structure of magnetospheric plasma disturbance estimated by using magnetic data obtained by SWARM satellites.

    Science.gov (United States)

    Yokoyama, Y.; Iyemori, T.; Aoyama, T.

    2017-12-01

    Field-aligned currents with various spatial scales flow into and out from high-latitude ionosphere. The magnetic fluctuations observed by LEO satellites along their orbits having period longer than a few seconds can be regarded as the manifestations of spatial structure of field aligned currents.This has been confirmed by using the initial orbital characteristics of 3 SWARM-satellites. From spectral analysis, we evaluated the spectral indices of these magnetic fluctuations and investigated their dependence on regions, such as magnetic latitude and MLT and so on. We found that the spectral indices take quite different values between the regions lower than the equatorward boundary of the auroral oval (around 63 degrees' in magnetic latitude) and the regions higher than that. On the other hands, we could not find the clear MLT dependence. In general, the FACs are believed to be generated in the magnetiospheric plasma sheet and boundary layer, and they flow along the field lines conserving their currents.The theory of FAC generation [e.g., Hasegawa and Sato ,1978] indicates that the FACs are strongly connected with magnetospheric plasma disturbances. Although the spectral indices above are these of spatial structures of the FACs over the ionosphere, by using the theoretical equation of FAC generation, we evaluate the spectral indices of magnetospheric plasma disturbance in FAC's generation regions. Furthermore, by projecting the area of fluctuations on the equatorial plane of magnetosphere (i.e. plasma sheet), we can estimate the spatial structure of magnetospheric plasma disturbance. In this presentation, we focus on the characteristics of disturbance in midnight region and discuss the relations to the substorm.

  3. Exploring the Spatial Resolution of the Photothermal Beam Deflection Technique in the Infrared Region

    CERN Document Server

    Seidel, Wolfgang

    2004-01-01

    In photothermal beam deflection spectroscopy (PTBD) generating and detection of thermal waves occur generally in the sub-millimeter length scale. Therefore, PTBD provides spatial information about the surface of the sample and permits imaging and/or microspectrometry. Recent results of PTBD experiments are presented with a high spatial resolution which is near the diffraction limit of the infrared pump beam (CLIO-FEL). We investigated germanium substrates showing restricted O+-doped regions with an infrared absorption line at a wavelength around 11.6 microns. The spatial resolution was obtained by strongly focusing the probe beam (i.e. a HeNe laser) on a sufficiently small spot. The strong divergence makes it necessary to refocus the probe beam in front of the position detector. The influence of the focusing elements on spatial resolution and signal-to-noise ratio is discussed. In future studies we expect an enhanced spatial resolution due to an extreme focusing of the probe beam leading to a highly sensitive...

  4. The effect of spatial resolution on water scarcity estimates in Australia

    Science.gov (United States)

    Gevaert, Anouk; Veldkamp, Ted; van Dijk, Albert; Ward, Philip

    2017-04-01

    Water scarcity is an important global issue with severe socio-economic consequences, and its occurrence is likely to increase in many regions due to population growth, economic development and climate change. This has prompted a number of global and regional studies to identify areas that are vulnerable to water scarcity and to determine how this vulnerability will change in the future. A drawback of these studies, however, is that they typically have coarse spatial resolutions. Here, we studied the effect of increasing the spatial resolution of water scarcity estimates in Australia, and the Murray-Darling Basin in particular. This was achieved by calculating the water stress index (WSI), an indicator showing the ratio of water use to water availability, at 0.5 and 0.05 degree resolution for the period 1990-2010. Monthly water availability data were based on outputs of the Australian Water Resources Assessment Landscape model (AWRA-L), which was run at both spatial resolutions and at a daily time scale. Water use information was obtained from a monthly 0.5 degree global dataset that distinguishes between water consumption for irrigation, livestock, industrial and domestic uses. The data were downscaled to 0.05 degree by dividing the sectoral water uses over the areas covered by relevant land use types using a high resolution ( 0.5km) land use dataset. The monthly WSIs at high and low resolution were then used to evaluate differences in the patterns of water scarcity frequency and intensity. In this way, we assess to what extent increasing the spatial resolution can improve the identification of vulnerable areas and thereby assist in the development of strategies to lower this vulnerability. The results of this study provide insight into the scalability of water scarcity estimates and the added value of high resolution water scarcity information in water resources management.

  5. Spatial Resolution Enhancement of Hyperspectral Images Using Spectral Unmixing and Bayesian Sparse Representation

    Directory of Open Access Journals (Sweden)

    Elham Kordi Ghasrodashti

    2017-05-01

    Full Text Available In this paper, a new method is presented for spatial resolution enhancement of hyperspectral images (HSI using spectral unmixing and a Bayesian sparse representation. The proposed method combines the high spectral resolution from the HSI with the high spatial resolution from a multispectral image (MSI of the same scene and high resolution images from unrelated scenes. The fusion method is based on a spectral unmixing procedure for which the endmember matrix and the abundance fractions are estimated from the HSI and MSI, respectively. A Bayesian formulation of this method leads to an ill-posed fusion problem. A sparse representation regularization term is added to convert it into a well-posed inverse problem. In the sparse representation, dictionaries are constructed from the MSI, high optical resolution images, synthetic aperture radar (SAR or combinations of them. The proposed algorithm is applied to real datasets and compared with state-of-the-art fusion algorithms based on spectral unmixing and sparse representation, respectively. The proposed method significantly increases the spatial resolution and decreases the spectral distortion efficiently.

  6. Automatic Geometric Processing for Very High Resolution Optical Satellite Data Based on Vector Roads and Orthophotos

    Directory of Open Access Journals (Sweden)

    Peter Pehani

    2016-04-01

    Full Text Available In response to the increasing need for fast satellite image processing SPACE-SI developed STORM—a fully automatic image processing chain that performs all processing steps from the input optical images to web-delivered map-ready products for various sensors. This paper focuses on the automatic geometric corrections module and its adaptation to very high resolution (VHR multispectral images. In the automatic ground control points (GCPs extraction sub-module a two-step algorithm that utilizes vector roads as a reference layer and delivers GCPs for high resolution RapidEye images with near pixel accuracy was initially implemented. Super-fine positioning of individual GCPs onto an aerial orthophoto was introduced for VHR images. The enhanced algorithm is capable of achieving accuracy of approximately 1.5 pixels on WorldView-2 data. In the case of RapidEye images the accuracies of the physical sensor model reach sub-pixel values at independent check points. When compared to the reference national aerial orthophoto the accuracies of WorldView-2 orthoimages automatically produced with the rational function model reach near-pixel values. On a heterogeneous set of 41 RapidEye images the rate of automatic processing reached 97.6%. Image processing times remained under one hour for standard-size images of both sensor types.

  7. Obtaining Accurate Change Detection Results from High-Resolution Satellite Sensors

    Science.gov (United States)

    Bryant, N.; Bunch, W.; Fretz, R.; Kim, P.; Logan, T.; Smyth, M.; Zobrist, A.

    2012-01-01

    Multi-date acquisitions of high-resolution imaging satellites (e.g. GeoEye and WorldView), can display local changes of current economic interest. However, their large data volume precludes effective manual analysis, requiring image co-registration followed by image-to-image change detection, preferably with minimal analyst attention. We have recently developed an automatic change detection procedure that minimizes false-positives. The processing steps include: (a) Conversion of both the pre- and post- images to reflectance values (this step is of critical importance when different sensors are involved); reflectance values can be either top-of-atmosphere units or have full aerosol optical depth calibration applied using bi-directional reflectance knowledge. (b) Panchromatic band image-to-image co-registration, using an orthorectified base reference image (e.g. Digital Orthophoto Quadrangle) and a digital elevation model; this step can be improved if a stereo-pair of images have been acquired on one of the image dates. (c) Pan-sharpening of the multispectral data to assure recognition of change objects at the highest resolution. (d) Characterization of multispectral data in the post-image ( i.e. the background) using unsupervised cluster analysis. (e) Band ratio selection in the post-image to separate surface materials of interest from the background. (f) Preparing a pre-to-post change image. (g) Identifying locations where change has occurred involving materials of interest.

  8. Damage Mapping of Powdery Mildew in Winter Wheat with High-Resolution Satellite Image

    Directory of Open Access Journals (Sweden)

    Lin Yuan

    2014-04-01

    Full Text Available Powdery mildew, caused by the fungus Blumeria graminis, is a major winter wheat disease in China. Accurate delineation of powdery mildew infestations is necessary for site-specific disease management. In this study, high-resolution multispectral imagery of a 25 km2 typical outbreak site in Shaanxi, China, taken by a newly-launched satellite, SPOT-6, was analyzed for mapping powdery mildew disease. Two regions with high representation were selected for conducting a field survey of powdery mildew. Three supervised classification methods—artificial neural network, mahalanobis distance, and maximum likelihood classifier—were implemented and compared for their performance on disease detection. The accuracy assessment showed that the ANN has the highest overall accuracy of 89%, following by MD and MLC with overall accuracies of 84% and 79%, respectively. These results indicated that the high-resolution multispectral imagery with proper classification techniques incorporated with the field investigation can be a useful tool for mapping powdery mildew in winter wheat.

  9. Global Monitoring of Terrestrial Chlorophyll Fluorescence from Moderate-spectral-resolution Near-infrared Satellite Measurements: Methodology, Simulations, and Application to GOME-2

    Science.gov (United States)

    Joiner, J.; Gaunter, L.; Lindstrot, R.; Voigt, M.; Vasilkov, A. P.; Middleton, E. M.; Huemmrich, K. F.; Yoshida, Y.; Frankenberg, C.

    2013-01-01

    Globally mapped terrestrial chlorophyll fluorescence retrievals are of high interest because they can provide information on the functional status of vegetation including light-use efficiency and global primary productivity that can be used for global carbon cycle modeling and agricultural applications. Previous satellite retrievals of fluorescence have relied solely upon the filling-in of solar Fraunhofer lines that are not significantly affected by atmospheric absorption. Although these measurements provide near-global coverage on a monthly basis, they suffer from relatively low precision and sparse spatial sampling. Here, we describe a new methodology to retrieve global far-red fluorescence information; we use hyperspectral data with a simplified radiative transfer model to disentangle the spectral signatures of three basic components: atmospheric absorption, surface reflectance, and fluorescence radiance. An empirically based principal component analysis approach is employed, primarily using cloudy data over ocean, to model and solve for the atmospheric absorption. Through detailed simulations, we demonstrate the feasibility of the approach and show that moderate-spectral-resolution measurements with a relatively high signal-to-noise ratio can be used to retrieve far-red fluorescence information with good precision and accuracy. The method is then applied to data from the Global Ozone Monitoring Instrument 2 (GOME-2). The GOME-2 fluorescence retrievals display similar spatial structure as compared with those from a simpler technique applied to the Greenhouse gases Observing SATellite (GOSAT). GOME-2 enables global mapping of far-red fluorescence with higher precision over smaller spatial and temporal scales than is possible with GOSAT. Near-global coverage is provided within a few days. We are able to show clearly for the first time physically plausible variations in fluorescence over the course of a single month at a spatial resolution of 0.5 deg × 0.5 deg

  10. High Resolution Aerosol Data from MODIS Satellite for Urban Air Quality Studies

    Science.gov (United States)

    Chudnovsky, A.; Lyapustin, A.; Wang, Y.; Tang, C.; Schwartz, J.; Koutrakis, P.

    2013-01-01

    The Moderate Resolution Imaging Spectroradiometer (MODIS) provides daily global coverage, but the 10 km resolution of its aerosol optical depth (AOD) product is not suitable for studying spatial variability of aerosols in urban areas. Recently, a new Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm was developed for MODIS which provides AOD at 1 km resolution. Using MAIAC data, the relationship between MAIAC AOD and PM(sub 2.5) as measured by the 27 EPA ground monitoring stations was investigated. These results were also compared to conventional MODIS 10 km AOD retrievals (MOD04) for the same days and locations. The coefficients of determination for MOD04 and for MAIAC are R(exp 2) =0.45 and 0.50 respectively, suggested that AOD is a reasonably good proxy for PM(sub 2.5) ground concentrations. Finally, we studied the relationship between PM(sub 2.5) and AOD at the intra-urban scale (10 km) in Boston. The fine resolution results indicated spatial variability in particle concentration at a sub-10 kilometer scale. A local analysis for the Boston area showed that the AOD-PM(sub 2.5) relationship does not depend on relative humidity and air temperatures below approximately 7 C. The correlation improves for temperatures above 7 - 16 C. We found no dependence on the boundary layer height except when the former was in the range 250-500 m. Finally, we apply a mixed effects model approach to MAIAC aerosol optical depth (AOD) retrievals from MODIS to predict PM(sub 2.5) concentrations within the greater Boston area. With this approach we can control for the inherent day-to-day variability in the AOD-PM(sub 2.5) relationship, which depends on time-varying parameters such as particle optical properties, vertical and diurnal concentration profiles and ground surface reflectance. Our results show that the model-predicted PM(sub 2.5) mass concentrations are highly correlated with the actual observations (out-of-sample R(exp 2) of 0.86). Therefore, adjustment

  11. Spatial resolution of tropical terrestrial CO2 fluxes inferred using space-borne column CO2 sampled in different earth orbits: the role of spatial error correlations

    Directory of Open Access Journals (Sweden)

    H. Bösch

    2011-09-01

    Full Text Available We use realistic numerical experiments to assess the sensitivity of 8-day CO2 flux estimates, inferred from space-borne short-wave infrared measurements of column-averaged CO2 dry air mixing ratio XCO2, to the choice of Earth observing orbit. We focus on three orbits: (1 a low-inclination circular orbit used by the NASA Tropical Rainfall Measuring Mission (TRMM; (2 a sun-synchronous orbit used by the Japanese Greenhouse Gases Observing SATellite (GOSAT and proposed for the NASA Orbiting Carbon Observatory (OCO-2 instrument; and (3 a precessing orbit used by the International Space Station (ISS. For each orbit, we assume an instrument based on the specification of the OCO-2; for GOSAT we use the relevant instrument specification. Sun-synchronous orbits offer near global coverage within a few days but have implications for the density of clear-sky measurements. The TRMM and ISS orbits intensively sample tropical latitudes, with sun-lit clear-sky measurements evenly distributed between a.m./p.m. For a specified spatial resolution for inferred fluxes, we show there is a critical number of measurements beyond which there is a disproportionately small decrease in flux uncertainty. We also show that including spatial correlations for measurements and model errors (of length 300 km reduces the effectiveness of high measurement density for flux estimation, as expected, and so should be considered when deciding sampling strategies. We show that cloud-free data from the TRMM orbit generally can improve the spatial resolution of CO2 fluxes achieved by OCO-2 over tropical South America, for example, from 950 km to 630 km, and that combining data from these low-inclination and sun-synchronous orbits have the potential to reduce this spatial length further. Decreasing the length of the error correlations to 50 km, reflecting anticipated future improvements to transport models, results in CO2 flux estimates on spatial scales that approach those observed by

  12. Estimation of the high-spatial-resolution variability in extreme wind speeds for forestry applications

    Science.gov (United States)

    Venäläinen, Ari; Laapas, Mikko; Pirinen, Pentti; Horttanainen, Matti; Hyvönen, Reijo; Lehtonen, Ilari; Junila, Päivi; Hou, Meiting; Peltola, Heli M.

    2017-07-01

    The bioeconomy has an increasing role to play in climate change mitigation and the sustainable development of national economies. In Finland, a forested country, over 50 % of the current bioeconomy relies on the sustainable management and utilization of forest resources. Wind storms are a major risk that forests are exposed to and high-spatial-resolution analysis of the most vulnerable locations can produce risk assessment of forest management planning. In this paper, we examine the feasibility of the wind multiplier approach for downscaling of maximum wind speed, using 20 m spatial resolution CORINE land-use dataset and high-resolution digital elevation data. A coarse spatial resolution estimate of the 10-year return level of maximum wind speed was obtained from the ERA-Interim reanalyzed data. Using a geospatial re-mapping technique the data were downscaled to 26 meteorological station locations to represent very diverse environments. Applying a comparison, we find that the downscaled 10-year return levels represent 66 % of the observed variation among the stations examined. In addition, the spatial variation in wind-multiplier-downscaled 10-year return level wind was compared with the WAsP model-simulated wind. The heterogeneous test area was situated in northern Finland, and it was found that the major features of the spatial variation were similar, but in some locations, there were relatively large differences. The results indicate that the wind multiplier method offers a pragmatic and computationally feasible tool for identifying at a high spatial resolution those locations with the highest forest wind damage risks. It can also be used to provide the necessary wind climate information for wind damage risk model calculations, thus making it possible to estimate the probability of predicted threshold wind speeds for wind damage and consequently the probability (and amount) of wind damage for certain forest stand configurations.

  13. Noise Removal with Maintained Spatial Resolution in Raman Images of Cells Exposed to Submicron Polystyrene Particles

    Directory of Open Access Journals (Sweden)

    Linnea Ahlinder

    2016-04-01

    Full Text Available The biodistribution of 300 nm polystyrene particles in A549 lung epithelial cells has been studied with confocal Raman spectroscopy. This is a label-free method in which particles and cells can be imaged without using dyes or fluorescent labels. The main drawback with Raman imaging is the comparatively low spatial resolution, which is aggravated in heterogeneous systems such as biological samples, which in addition often require long measurement times because of their weak Raman signal. Long measurement times may however induce laser-induced damage. In this study we use a super-resolution algorithm with Tikhonov regularization, intended to improve the image quality without demanding an increased number of collected pixels. Images of cells exposed to polystyrene particles have been acquired with two different step lengths, i.e., the distance between pixels, and compared to each other and to corresponding images treated with the super-resolution algorithm. It is shown that the resolution after application of super-resolution algorithms is not significantly improved compared to the theoretical limit for optical microscopy. However, to reduce noise and artefacts in the hyperspectral Raman images while maintaining the spatial resolution, we show that it is advantageous to use short mapping step lengths and super-resolution algorithms with appropriate regularization. The proposed methodology should be generally applicable for Raman imaging of biological samples and other photo-sensitive samples.

  14. Spatial variation and seasonal dynamics of leaf-area index in the arctic tundra-implications for linking ground observations and satellite images

    Science.gov (United States)

    Juutinen, Sari; Virtanen, Tarmo; Kondratyev, Vladimir; Laurila, Tuomas; Linkosalmi, Maiju; Mikola, Juha; Nyman, Johanna; Räsänen, Aleksi; Tuovinen, Juha-Pekka; Aurela, Mika

    2017-09-01

    Vegetation in the arctic tundra typically consists of a small-scale mosaic of plant communities, with species differing in growth forms, seasonality, and biogeochemical properties. Characterization of this variation is essential for understanding and modeling the functioning of the arctic tundra in global carbon cycling, as well as for evaluating the resolution requirements for remote sensing. Our objective was to quantify the seasonal development of the leaf-area index (LAI) and its variation among plant communities in the arctic tundra near Tiksi, coastal Siberia, consisting of graminoid, dwarf shrub, moss, and lichen vegetation. We measured the LAI in the field and used two very-high-spatial resolution multispectral satellite images (QuickBird and WorldView-2), acquired at different phenological stages, to predict landscape-scale patterns. We used the empirical relationships between the plant community-specific LAI and degree-day accumulation (0 °C threshold) and quantified the relationship between the LAI and satellite NDVI (normalized difference vegetation index). Due to the temporal difference between the field data and satellite images, the LAI was approximated for the imagery dates, using the empirical model. LAI explained variation in the NDVI values well (R 2 adj. 0.42-0.92). Of the plant functional types, the graminoid LAI showed the largest seasonal amplitudes and was the main cause of the varying spatial patterns of the NDVI and the related LAI between the two images. Our results illustrate how the short growing season, rapid development of the LAI, yearly climatic variation, and timing of the satellite data should be accounted for in matching imagery and field verification data in the Arctic region.

  15. PET investigation of a fluidized particle : spatial and temporal resolution and short term motion

    NARCIS (Netherlands)

    Hoffmann, AC; Dechsiri, C; van de Wiel, F; Dehling, HG

    The motion of a single particle in a fluidized bed has been followed with high temporal and spatial resolution using an ECAT EXACT HR+ PET camera. An account is given of the analysis of the output from the camera, and the calculation of the particle position. The particle position was determined

  16. Ground-state depletion for subdiffraction-limited spatial resolution in coherent anti-Stokes Raman

    NARCIS (Netherlands)

    Cleff, C.; Groß, P.; Fallnich, C.; Offerhaus, H. L.; Herek, J.; Kruse, K.; Beeker, W. P.; Lee, C. J.; Boller, K. J.

    2012-01-01

    We theoretically investigate ground-state depletion for subdiffraction-limited spatial resolution in coherent anti-Stokes Raman scattering (CARS) microscopy. We propose a scheme based on ground-state depopulation, which is achieved via a control laser light field incident prior to the CARS

  17. High Spatial Resolution Imaging of Endogenous Hydrogen Peroxide in Living Cells by Solid-State Fluorescence.

    Science.gov (United States)

    Lindberg, Eric; Winssinger, Nicolas

    2016-09-02

    Herein, we describe selective imaging of hydrogen peroxide using a precipitating dye conjugated to a boronic acid-based immolative linker. We achieved visualization of endogenous hydrogen peroxide in phagosomes by solid-state two-photon fluorescence imaging in living cells with exceptionally high spatial resolution. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  18. High spatial resolution three-dimensional mapping of vegetation spectral dynamics using computer vision

    Science.gov (United States)

    Jonathan P. Dandois; Erle C. Ellis

    2013-01-01

    High spatial resolution three-dimensional (3D) measurements of vegetation by remote sensing are advancing ecological research and environmental management. However, substantial economic and logistical costs limit this application, especially for observing phenological dynamics in ecosystem structure and spectral traits. Here we demonstrate a new aerial remote sensing...

  19. Improving spatial resolution of the light field microscope with Fourier ptychography

    Science.gov (United States)

    Tani, Yoshitake; Usuki, Shin; Miura, Kenjiro T.

    2017-09-01

    Light field microscope (LFM) is an optical microscope capable of obtaining images having large depth of field with different viewpoints. By using the parallax of these multi-view images, it is possible to reconstruct the 3D sample. However, the sampling interval of this multi-viewpoint image depends on the pitch interval of the microlens array, so the spatial resolution is low, and the accuracy of the 3D sample to be reconstructed is also low. Conventional research has a method of increasing the spatial resolution by subpixel-shifted multiple images. However, this method has problems such as the necessity of mechanical operation and high cost. Therefore, we propose applying Fourier ptychography to the LFM. Fourier ptychography is a technique to obtain high spatial resolution images by joining images obtained by irradiating samples from different angles using LED arrays in Fourier space. Fourier ptychography does not require mechanical scanning and is high throughput and low cost. In addition, Fourier ptycoography is possible to obtain phase information on a sample, and it is also possible to obtain a fine 3D sample. We propose a method to generate high spatial resolution multiview images using Fourier ptychography and reconstruct highly accurate 3D sample from those images. In this research, we experiment with the original LFM and verify the effect.

  20. The spatial resolution of the porcine multifocal electroretinogram for detection of laser-induced retinal lesions

    DEFF Research Database (Denmark)

    Kyhn, Maria Voss; Kiilgaard, Jens Folke; Scherfig, Erik

    2008-01-01

    This study aimed to investigate the spatial resolution of a porcine multifocal electroretinogram (mfERG) protocol by testing its ability to detect laser-induced retinal lesions. Furthermore, we wanted to describe time-dependent changes in implicit time and amplitude of the different mfERG peaks...

  1. Temporal and spatial resolution of rainfall measurements required for urban hydrology

    NARCIS (Netherlands)

    Berne, A.D.; Delrieu, G.; Creutin, J.D.; Obled, C.

    2004-01-01

    The objective of the paper is to provide recommendations on the temporal and spatial resolution of rainfall measurements required for urban hydrological applications, based on quantitative investigations of the space-time scales of urban catchments and rainfall. First the temporal rainfall-runoff

  2. Limits on the spatial resolution of monolithic scintillators read out by APD arrays

    NARCIS (Netherlands)

    van der Laan, D.J.J.; Maas, M.C.; Bruyndonckx, P.; Schaart, D.R.

    2012-01-01

    Cramér-Rao theory can be used to derive the lower bound on the spatial resolution achievable with position-sensitive scintillation detectors as a function of the detector geometry and the pertinent physical properties of the scintillator, the photosensor and the readout electronics. Knowledge of the

  3. Stimulated Emission Pumping Enablling Sub-Diffraction-Limited Spatial Resolution in CARS Microscopy

    NARCIS (Netherlands)

    Cleff, C.; Gross, P.; Fallnich, C.; Offerhaus, Herman L.; Herek, Jennifer Lynn; Kruse, K.; Beeker, W.P; Beeker, W.P.; Lee, Christopher James; Boller, Klaus J.; Dobner, S.

    2012-01-01

    Suppression of CARS signal generation is demonstrated by equalization of the ground and Raman states via a control state in a theoretical investigation. Using donut-shaped control light fields for population transfer results in sub-diffraction-limited spatial resolution CARS microscopy.

  4. Array diagnostics, spatial resolution, and filtering of undesired radiation with the 3D reconstruction algorithm

    DEFF Research Database (Denmark)

    Cappellin, C.; Pivnenko, Sergey; Jørgensen, E.

    2013-01-01

    This paper focuses on three important features of the 3D reconstruction algorithm of DIATOOL: the identification of array elements improper functioning and failure, the obtainable spatial resolution of the reconstructed fields and currents, and the filtering of undesired radiation and scattering...

  5. High spatial resolution X-ray and gamma ray imaging system using diffraction crystals

    Science.gov (United States)

    Smither, Robert K [Hinsdale, IL

    2011-05-17

    A method and a device for high spatial resolution imaging of a plurality of sources of x-ray and gamma-ray radiation are provided. The device comprises a plurality of arrays, with each array comprising a plurality of elements comprising a first collimator, a diffracting crystal, a second collimator, and a detector.

  6. Spatial and Temporal Analysis of Winter Fog Episodes over South Asia by exploiting ground-based and satellite observations

    Science.gov (United States)

    Fahim Khokhar, Muhammad; Yasmin, Naila; Zaib, Naila; Murtaza, Rabia; Noreen, Asma; Ishtiaq, Hira; Khayyam, Junaid; Panday, Arnico

    2016-04-01

    The South Asian region in general and the Indo-Gangetic Plains (IGP) in particular hold about 1/6th of the world's population and is considered as one of the major hotspots with increasing air pollution. Due to growing population and globalization, South Asia is experiencing high transformations in the urban and industrial sectors. Fog is one of the meteorological/environmental phenomena which can generate significant social and economic problems especially havoc to air and road traffic. Meteorological stations provide information about the fog episodes only on the basis of point observation. Continuous monitoring as well as a spatially coherent picture of fog distribution can only be possible through the use of satellite imagery. Current study focus on winter fog episodes over South Asian region using Moderate Resolution Image Spectrometer (MODIS) Level 2 Terra Product and other MODIS Aerosol Product in addition to ground-based sampling and AERONET measurements. MODIS Corrected Reflectance RGBs are used to analyse the spatial extent of fog over study area. MOD04 level 2 Collection 6 data is used to study aerosol load and distribution which are further characterised by using aerosol type land product of MODIS. In order to study the variation of ground based observations from satellite data MODIS, AERONET and high volume air Sampler were used. Main objective of this study was to explore the spatial extent of fog, its causes and to analyse the Aerosol Optical Depth (AOD) over South Asia with particular focus over Indo-Gangetic Plains (IGP). Current studies show a descent increase in AOD from past few decades over South Asia and is contributing to poor air quality in the region due to growing population, urbanization, and industrialization. Smoke and absorbing aerosol are major constituent of fog over South Asia. Furthermore, winter 2014-15 extended span of Fog was also observed over South Asia. A significant correlation between MODIS (AOD) and AERONET Station (AOD

  7. Cadastral Resurvey using High Resolution Satellite Ortho Image - challenges: A case study in Odisha, India

    Science.gov (United States)

    Parida, P. K.; Sanabada, M. K.; Tripathi, S.

    2014-11-01

    Advancements in satellite sensor technology enabling capturing of geometrically accurate images of earth's surface coupled with DGPS/ETS and GIS technology holds the capability of large scale mapping of land resources at cadastral level. High Resolution Satellite Images depict field bunds distinctly. Thus plot parcels are to be delineated from cloud free ortho-images and obscured/difficult areas are to be surveyed using DGPS and ETS. The vector datasets thus derived through RS/DGPS/ETS survey are to be integrated in GIS environment to generate the base cadastral vector datasets for further settlement/title confirmation activities. The objective of this paper is to illustrate the efficacy of a hybrid methodology employed in Pitambarpur Sasana village under Digapahandi Tahasil of Ganjam district, as a pilot project, particularly in Odisha scenario where the land parcel size is very small. One of the significant observations of the study is matching of Cadastral map area i.e. 315.454 Acres, the image map area i.e. 314.887 Acres and RoR area i.e. 313.815 Acre. It was revealed that 79 % of plots derived by high-tech survey method show acceptable level of accuracy despite the fact that the mode of area measurement by ground and automated method has significant variability. The variations are more in case of Government lands, Temple/Trust lands, Common Property Resources and plots near to river/nalas etc. The study indicates that the adopted technology can be extended to other districts and cadastral resurvey and updating work can be done for larger areas of the country using this methodology.

  8. Efficient high-rate satellite clock estimation for PPP ambiguity resolution using carrier-ranges.

    Science.gov (United States)

    Chen, Hua; Jiang, Weiping; Ge, Maorong; Wickert, Jens; Schuh, Harald

    2014-11-25

    In order to catch up the short-term clock variation of GNSS satellites, clock corrections must be estimated and updated at a high-rate for Precise Point Positioning (PPP). This estimation is already very time-consuming for the GPS constellation only as a great number of ambiguities need to be simultaneously estimated. However, on the one hand better estimates are expected by including more stations, and on the other hand satellites from different GNSS systems must be processed integratively for a reliable multi-GNSS positioning service. To alleviate the heavy computational burden, epoch-differenced observations are always employed where ambiguities are eliminated. As the epoch-differenced method can only derive temporal clock changes which have to be aligned to the absolute clocks but always in a rather complicated way, in this paper, an efficient method for high-rate clock estimation is proposed using the concept of "carrier-range" realized by means of PPP with integer ambiguity resolution. Processing procedures for both post- and real-time processing are developed, respectively. The experimental validation shows that the computation time could be reduced to about one sixth of that of the existing methods for post-processing and less than 1 s for processing a single epoch of a network with about 200 stations in real-time mode after all ambiguities are fixed. This confirms that the proposed processing strategy will enable the high-rate clock estimation for future multi-GNSS networks in post-processing and possibly also in real-time mode.

  9. SkySat-1: very high-resolution imagery from a small satellite

    Science.gov (United States)

    Murthy, Kiran; Shearn, Michael; Smiley, Byron D.; Chau, Alexandra H.; Levine, Josh; Robinson, M. Dirk

    2014-10-01

    This paper presents details of the SkySat-1 mission, which is the first microsatellite-class commercial earth- observation system to generate sub-meter resolution panchromatic imagery, in addition to sub-meter resolution 4-band pan-sharpened imagery. SkySat-1 was built and launched for an order of magnitude lower cost than similarly performing missions. The low-cost design enables the deployment of a large imaging constellation that can provide imagery with both high temporal resolution and high spatial resolution. One key enabler of the SkySat-1 mission was simplifying the spacecraft design and instead relying on ground- based image processing to achieve high-performance at the system level. The imaging instrument consists of a custom-designed high-quality optical telescope and commercially-available high frame rate CMOS image sen- sors. While each individually captured raw image frame shows moderate quality, ground-based image processing algorithms improve the raw data by combining data from multiple frames to boost image signal-to-noise ratio (SNR) and decrease the ground sample distance (GSD) in a process Skybox calls "digital TDI". Careful qual-ity assessment and tuning of the spacecraft, payload, and algorithms was necessary to generate high-quality panchromatic, multispectral, and pan-sharpened imagery. Furthermore, the framing sensor configuration en- abled the first commercial High-Definition full-frame rate panchromatic video to be captured from space, with approximately 1 meter ground sample distance. Details of the SkySat-1 imaging instrument and ground-based image processing system are presented, as well as an overview of the work involved with calibrating and validating the system. Examples of raw and processed imagery are shown, and the raw imagery is compared to pre-launch simulated imagery used to tune the image processing algorithms.

  10. Total porosity of carbonate reservoir rocks by X-ray microtomography in two different spatial resolutions

    International Nuclear Information System (INIS)

    Nagata, Rodrigo; Appoloni, Carlos R.; Marques, Leonardo C.; Fernandes, Celso P.

    2011-01-01

    Carbonate reservoir rocks contain more than 50% of world's petroleum. To know carbonate rocks' structural properties is quite important to petroleum extraction. One of their main structural properties is the total porosity, which shows the rock's capacity to stock petroleum. In recent years, the X-ray microtomography had been used to analyze the structural parameters of reservoir rocks. Such nondestructive technique generates images of the samples' internal structure, allowing the evaluation of its properties. The spatial resolution is a measurement parameter that indicates the smallest structure size observable in a sample. It is possible to measure one sample using two or more different spatial resolutions in order to evaluate the samples' pore scale. In this work, two samples of the same sort of carbonate rock were measured, and in each measurement a different spatial resolution (17 μm and 7 μm) was applied. The obtained results showed that with the better resolution it was possible to measure 8% more pores than with the poorer resolution. Such difference provides us with good expectations about such approach to study the pore scale of carbonate rocks. (author)

  11. Global spectroscopic survey of cloud thermodynamic phase at high spatial resolution, 2005-2015

    Science.gov (United States)

    Thompson, David R.; Kahn, Brian H.; Green, Robert O.; Chien, Steve A.; Middleton, Elizabeth M.; Tran, Daniel Q.

    2018-02-01

    The distribution of ice, liquid, and mixed phase clouds is important for Earth's planetary radiation budget, impacting cloud optical properties, evolution, and solar reflectivity. Most remote orbital thermodynamic phase measurements observe kilometer scales and are insensitive to mixed phases. This under-constrains important processes with outsize radiative forcing impact, such as spatial partitioning in mixed phase clouds. To date, the fine spatial structure of cloud phase has not been measured at global scales. Imaging spectroscopy of reflected solar energy from 1.4 to 1.8 µm can address this gap: it directly measures ice and water absorption, a robust indicator of cloud top thermodynamic phase, with spatial resolution of tens to hundreds of meters. We report the first such global high spatial resolution survey based on data from 2005 to 2015 acquired by the Hyperion imaging spectrometer onboard NASA's Earth Observer 1 (EO-1) spacecraft. Seasonal and latitudinal distributions corroborate observations by the Atmospheric Infrared Sounder (AIRS). For extratropical cloud systems, just 25 % of variance observed at GCM grid scales of 100 km was related to irreducible measurement error, while 75 % was explained by spatial correlations possible at finer resolutions.

  12. Retrieval of High-Resolution Atmospheric Particulate Matter Concentrations from Satellite-Based Aerosol Optical Thickness over the Pearl River Delta Area, China

    Directory of Open Access Journals (Sweden)

    Lili Li

    2015-06-01

    Full Text Available Satellite remote sensing offers an effective approach to estimate indicators of air quality on a large scale. It is critically significant for air quality monitoring in areas experiencing rapid urbanization and consequently severe air pollution, like the Pearl River Delta (PRD in China. This paper starts with examining ground observations of particulate matter (PM and the relationship between PM10 (particles smaller than 10 μm and aerosol optical thickness (AOT by analyzing observations on the sampling sites in the PRD. A linear regression (R2 = 0.51 is carried out using MODIS-derived 500 m-resolution AOT and PM10 concentration from monitoring stations. Data of atmospheric boundary layer (ABL height and relative humidity are used to make vertical and humidity corrections on AOT. Results after correction show higher correlations (R2 = 0.55 between extinction coefficient and PM10. However, coarse spatial resolution of meteorological data affects the smoothness of retrieved maps, which suggests high-resolution and accurate meteorological data are critical to increase retrieval accuracy of PM. Finally, the model provides the spatial distribution maps of instantaneous and yearly average PM10 over the PRD. It is proved that observed PM10 is more relevant to yearly mean AOT than instantaneous values.

  13. Using Spatial Reinforcement Learning to Build Forest Wildfire Dynamics Models From Satellite Images

    Directory of Open Access Journals (Sweden)

    Sriram Ganapathi Subramanian

    2018-04-01

    Full Text Available Machine learning algorithms have increased tremendously in power in recent years but have yet to be fully utilized in many ecology and sustainable resource management domains such as wildlife reserve design, forest fire management, and invasive species spread. One thing these domains have in common is that they contain dynamics that can be characterized as a spatially spreading process (SSP, which requires many parameters to be set precisely to model the dynamics, spread rates, and directional biases of the elements which are spreading. We present related work in artificial intelligence and machine learning for SSP sustainability domains including forest wildfire prediction. We then introduce a novel approach for learning in SSP domains using reinforcement learning (RL where fire is the agent at any cell in the landscape and the set of actions the fire can take from a location at any point in time includes spreading north, south, east, or west or not spreading. This approach inverts the usual RL setup since the dynamics of the corresponding Markov Decision Process (MDP is a known function for immediate wildfire spread. Meanwhile, we learn an agent policy for a predictive model of the dynamics of a complex spatial process. Rewards are provided for correctly classifying which cells are on fire or not compared with satellite and other related data. We examine the behavior of five RL algorithms on this problem: value iteration, policy iteration, Q-learning, Monte Carlo Tree Search, and Asynchronous Advantage Actor-Critic (A3C. We compare to a Gaussian process-based supervised learning approach and also discuss the relation of our approach to manually constructed, state-of-the-art methods from forest wildfire modeling. We validate our approach with satellite image data of two massive wildfire events in Northern Alberta, Canada; the Fort McMurray fire of 2016 and the Richardson fire of 2011. The results show that we can learn predictive, agent

  14. Spatiotemporal Prediction of Fine Particulate Matter Using High-Resolution Satellite Images in the Southeastern US 2003-2011

    Science.gov (United States)

    Lee, Mihye; Kloog, Itai; Chudnovsky, Alexandra; Lyapustin, Alexei; Wang, Yujie; Melly, Steven; Coull, Brent; Koutrakis, Petros; Schwartz, Joel

    2016-01-01

    Numerous studies have demonstrated that fine particulate matter (PM(sub 2.5), particles smaller than 2.5 micrometers in aerodynamic diameter) is associated with adverse health outcomes. The use of ground monitoring stations of PM(sub 2.5) to assess personal exposure, however, induces measurement error. Land-use regression provides spatially resolved predictions but land-use terms do not vary temporally. Meanwhile, the advent of satellite-retrieved aerosol optical depth (AOD) products have made possible to predict the spatial and temporal patterns of PM(sub 2.5) exposures. In this paper, we used AOD data with other PM(sub 2.5) variables, such as meteorological variables, land-use regression, and spatial smoothing to predict daily concentrations of PM(sub 2.5) at a 1 sq km resolution of the Southeastern United States including the seven states of Georgia, North Carolina, South Carolina, Alabama, Tennessee, Mississippi, and Florida for the years from 2003 to 2011. We divided the study area into three regions and applied separate mixed-effect models to calibrate AOD using ground PM(sub 2.5) measurements and other spatiotemporal predictors. Using 10-fold cross-validation, we obtained out of sample R2 values of 0.77, 0.81, and 0.70 with the square root of the mean squared prediction errors of 2.89, 2.51, and 2.82 cu micrograms for regions 1, 2, and 3, respectively. The slopes of the relationships between predicted PM2.5 and held out measurements were approximately 1 indicating no bias between the observed and modeled PM(sub 2.5) concentrations. Predictions can be used in epidemiological studies investigating the effects of both acute and chronic exposures to PM(sub 2.5). Our model results will also extend the existing studies on PM(sub 2.5) which have mostly focused on urban areas because of the paucity of monitors in rural areas.

  15. Space volcano observatory (SVO): a metric resolution system on-board a micro/mini-satellite

    Science.gov (United States)

    Briole, P.; Cerutti-Maori, G.; Kasser, M.

    2017-11-01

    1500 volcanoes on the Earth are potentially active, one third of them have been active during this century and about 70 are presently erupting. At the beginning of the third millenium, 10% of the world population will be living in areas directly threatened by volcanoes, without considering the effects of eruptions on climate or air-trafic for example. The understanding of volcanic eruptions, a major challenge in geoscience, demands continuous monitoring of active volcanoes. The only way to provide global, continuous, real time and all-weather information on volcanoes is to set up a Space Volcano Observatory closely connected to the ground observatories. Spaceborne observations are mandatory and implement the ground ones as well as airborne ones that can be implemented on a limited set of volcanoes. SVO goal is to monitor both the deformations and the changes in thermal radiance at optical wavelengths from high temperature surfaces of the active volcanic zones. For that, we propose to map at high resolution (1 to 1,5 m pixel size) the topography (stereoscopic observation) and the thermal anomalies (pixel-integrated temperatures above 450°C) of active volcanic areas in a size of 6 x 6 km to 12 x 12 km, large enough for monitoring most of the target features. A return time of 1 to 3 days will allow to get a monitoring useful for hazard mitigation. The paper will present the concept of the optical payload, compatible with a micro/mini satellite (mass in the range 100 - 400 kg), budget for the use of Proteus platform in the case of minisatellite approach will be given and also in the case of CNES microsat platform family. This kind of design could be used for other applications like high resolution imagery on a limited zone for military purpose, GIS, evolution cadaster…

  16. Exploring image data assimilation in the prospect of high-resolution satellite oceanic observations

    Science.gov (United States)

    Durán Moro, Marina; Brankart, Jean-Michel; Brasseur, Pierre; Verron, Jacques

    2017-07-01

    Satellite sensors increasingly provide high-resolution (HR) observations of the ocean. They supply observations of sea surface height (SSH) and of tracers of the dynamics such as sea surface salinity (SSS) and sea surface temperature (SST). In particular, the Surface Water Ocean Topography (SWOT) mission will provide measurements of the surface ocean topography at very high-resolution (HR) delivering unprecedented information on the meso-scale and submeso-scale dynamics. This study investigates the feasibility to use these measurements to reconstruct meso-scale features simulated by numerical models, in particular on the vertical dimension. A methodology to reconstruct three-dimensional (3D) multivariate meso-scale scenes is developed by using a HR numerical model of the Solomon Sea region. An inverse problem is defined in the framework of a twin experiment where synthetic observations are used. A true state is chosen among the 3D multivariate states which is considered as a reference state. In order to correct a first guess of this true state, a two-step analysis is carried out. A probability distribution of the first guess is defined and updated at each step of the analysis: (i) the first step applies the analysis scheme of a reduced-order Kalman filter to update the first guess probability distribution using SSH observation; (ii) the second step minimizes a cost function using observations of HR image structure and a new probability distribution is estimated. The analysis is extended to the vertical dimension using 3D multivariate empirical orthogonal functions (EOFs) and the probabilistic approach allows the update of the probability distribution through the two-step analysis. Experiments show that the proposed technique succeeds in correcting a multivariate state using meso-scale and submeso-scale information contained in HR SSH and image structure observations. It also demonstrates how the surface information can be used to reconstruct the ocean state below

  17. Using high-resolution satellite imagery to engage students in classroom experiences which meld research, the nature of science, and inquiry-based instruction

    Science.gov (United States)

    Pennycook, J.; LaRue, M.; Herried, B.; Morin, P. J.

    2013-12-01

    Recognizing the need to bridge the gap between scientific research and the classroom, we have developed an exciting activity which engages students in grades 5-12 using high-resolution satellite imagery to observe Weddell seal populations in Antarctica. Going beyond the scope of the textbook, students experience the challenge researchers face in counting and monitoring animal populations in the field. The activity is presented in a non-expert, non-technical exercise enriched for students, with background information, tutorials, and satellite imagery included. Teachers instruct their class in how to use satellite imagery analysis techniques to collect data on seal populations in the McMurdo Sound region of the Ross Sea, Antarctica. Students participate in this inquiry-based, open-ended exercise to evaluate changes in the seal population within and between seasons. The activity meets the New Generation Science Standards (NGSS) through inquiry-based, real-world application and supports seven Performance Expectations (PE) for grade 5-12. In addition, it offers students a glimpse into the work of a field biologist, promoting interest in entering the STEM career pipeline. As every new Antarctica season unfolds, new imagery will be uploaded to the website allowing each year of students to add their counts to a growing long-term dataset for the classroom. The activity files provide 1) a tutorial in how to use the images to count the populations, 2) background information about Weddell seals in the McMurdo Sound region of the Ross Sea for the students and the teachers, and 3) collections of satellite imagery for spatial and temporal analysis of population fluctuations. Teachers can find all activity files to conduct the activity, including student instructions, on the Polar Geospatial Center's website (http://z.umn.edu/seals). Satellite image, Big Razorback Island, Antarctica Weddell seals,Tent Island, Antarctica

  18. Spatial resolution requirements for traffic-related air pollutant exposure evaluations

    Science.gov (United States)

    Batterman, Stuart; Chambliss, Sarah; Isakov, Vlad

    2014-09-01

    Vehicle emissions represent one of the most important air pollution sources in most urban areas, and elevated concentrations of pollutants found near major roads have been associated with many adverse health impacts. To understand these impacts, exposure estimates should reflect the spatial and temporal patterns observed for traffic-related air pollutants. This paper evaluates the spatial resolution and zonal systems required to estimate accurately intraurban and near-road exposures of traffic-related air pollutants. The analyses use the detailed information assembled for a large (800 km2) area centered on Detroit, Michigan, USA. Concentrations of nitrogen oxides (NOx) due to vehicle emissions were estimated using hourly traffic volumes and speeds on 9700 links representing all but minor roads in the city, the MOVES2010 emission model, the RLINE dispersion model, local meteorological data, a temporal resolution of 1 h, and spatial resolution as low as 10 m. Model estimates were joined with the corresponding shape files to estimate residential exposures for 700,000 individuals at property parcel, census block, census tract, and ZIP code levels. We evaluate joining methods, the spatial resolution needed to meet specific error criteria, and the extent of exposure misclassification. To portray traffic-related air pollutant exposure, raster or inverse distance-weighted interpolations are superior to nearest neighbor approaches, and interpolations between receptors and points of interest should not exceed about 40 m near major roads, and 100 m at larger distances. For census tracts and ZIP codes, average exposures are overestimated since few individuals live very near major roads, the range of concentrations is compressed, most exposures are misclassified, and high concentrations near roads are entirely omitted. While smaller zones improve performance considerably, even block-level data can misclassify many individuals. To estimate exposures and impacts of traffic

  19. Comparison of the spatial resolution of source imaging techniques in high-density EEG and MEG.

    Science.gov (United States)

    Hedrich, T; Pellegrino, G; Kobayashi, E; Lina, J M; Grova, C

    2017-08-15

    The present study aims at evaluating and comparing electrical and magnetic distributed source imaging methods applied to high-density Electroencephalography (hdEEG) and Magnetoencephalography (MEG) data. We used resolution matrices to characterize spatial resolution properties of Minimum Norm Estimate (MNE), dynamic Statistical Parametric Mapping (dSPM), standardized Low-Resolution Electromagnetic Tomography (sLORETA) and coherent Maximum Entropy on the Mean (cMEM, an entropy-based technique). The resolution matrix provides information of the Point Spread Functions (PSF) and of the Crosstalk functions (CT), this latter being also called source leakage, as it reflects the influence of a source on its neighbors. The spatial resolution of the inverse operators was first evaluated theoretically and then with real data acquired using electrical median nerve stimulation on five healthy participants. We evaluated the Dipole Localization Error (DLE) and the Spatial Dispersion (SD) of each PSF and CT map. cMEM showed the smallest spatial spread (SD) for both PSF and CT maps, whereas localization errors (DLE) were similar for all methods. Whereas cMEM SD values were lower in MEG compared to hdEEG, the other methods slightly favored hdEEG over MEG. In real data, cMEM provided similar localization error and significantly less spatial spread than other methods for both MEG and hdEEG. Whereas both MEG and hdEEG provided very accurate localizations, all the source imaging methods actually performed better in MEG compared to hdEEG according to all evaluation metrics, probably due to the higher signal-to-noise ratio of the data in MEG. Our overall results show that all investigated methods provide similar localization errors, suggesting very accurate localization for both MEG and hdEEG when similar number of sensors are considered for both modalities. Intrinsic properties of source imaging methods as well as their behavior for well-controlled tasks, suggest an overall better

  20. Very high resolution Earth observation features for monitoring plant and animal community structure across multiple spatial scales in protected areas

    Science.gov (United States)

    Mairota, Paola; Cafarelli, Barbara; Labadessa, Rocco; Lovergine, Francesco; Tarantino, Cristina; Lucas, Richard M.; Nagendra, Harini; Didham, Raphael K.

    2015-05-01

    Monitoring the status and future trends in biodiversity can be prohibitively expensive using ground-based surveys. Consequently, significant effort is being invested in the use of satellite remote sensing to represent aspects of the proximate mechanisms (e.g., resource availability) that can be related to biodiversity surrogates (BS) such as species community descriptors. We explored the potential of very high resolution (VHR) satellite Earth observation (EO) features as proxies for habitat structural attributes that influence spatial variation in habitat quality and biodiversity change. In a semi-natural grassland mosaic of conservation concern in southern Italy, we employed a hierarchical nested sampling strategy to collect field and VHR-EO data across three spatial extent levels (landscape, patch and plot). Species incidence and abundance data were collected at the plot level for plant, insect and bird functional groups. Spectral and textural VHR-EO image features were derived from a Worldview-2 image. Three window sizes (grains) were tested for analysis and computation of textural features, guided by the perception limits of different organisms. The modelled relationships between VHR-EO features and BS responses differed across scales, suggesting that landscape, patch and plot levels are respectively most appropriate when dealing with birds, plants and insects. This research demonstrates the potential of VHR-EO for biodiversity mapping and habitat modelling, and highlights the importance of identifying the appropriate scale of analysis for specific taxonomic groups of interest. Further, textural features are important in the modelling of functional group-specific indices which represent BS in high conservation value habitat types, and provide a more direct link to species interaction networks and ecosystem functioning, than provided by traditional taxonomic diversity indices.

  1. Quality of Life Assessment Based on Spatial and Temporal Analysis of the Vegetation Area Derived from Satellite Images

    Directory of Open Access Journals (Sweden)

    MARIA IOANA VLAD

    2011-01-01

    Full Text Available The quality of life in urban areas is a function of many parameters among which, one highly important is the number and quality of green areas for people and wildlife to thrive. The quality of life is also a political concept often used to describe citizen satisfaction within different residential locations. Only in the last decades green areas have suffered a progressive decrease in quality, pointing out the ecological urban risk with a negative impact on the standard of living and population health status. This paper presents the evolution of green areas in the cities of South-Eastern Romania within the last 20 years and sets forth the current state of quality of life from the perspective of vegetation reference. By using state-of-the-art processing tools applied on high-resolution satellite images, we have derived knowledge about the spatial and temporal expansion of urbanized regions. Our semi-automatic technologies for analysis of remote sensing data such as Landsat 7 ETM+, correlated with statistical information inferred from urban charts, demonstrate a negative trend in the distribution of green areas within the analyzed cities, with long-term implications on multiple areas in our lives.

  2. A global high resolution mean sea surface from multi mission satellite altimetry

    DEFF Research Database (Denmark)

    Knudsen, Per

    1999-01-01

    Satellite altimetry from the GEOSAT and the ERS-1 geodetic missions provide altimeter data with a very dense coverage. Hence, the heights of the sea surface may be recovered very detailed. Satellite altimetry from the 35 days repeat cycle mission of the ERS satellites and, especially, from the 10...

  3. FULLY AUTOMATED GENERATION OF ACCURATE DIGITAL SURFACE MODELS WITH SUB-METER RESOLUTION FROM SATELLITE IMAGERY

    Directory of Open Access Journals (Sweden)

    J. Wohlfeil

    2012-07-01

    Full Text Available Modern pixel-wise image matching algorithms like Semi-Global Matching (SGM are able to compute high resolution digital surface models from airborne and spaceborne stereo imagery. Although image matching itself can be performed automatically, there are prerequisites, like high geometric accuracy, which are essential for ensuring the high quality of resulting surface models. Especially for line cameras, these prerequisites currently require laborious manual interaction using standard tools, which is a growing problem due to continually increasing demand for such surface models. The tedious work includes partly or fully manual selection of tie- and/or ground control points for ensuring the required accuracy of the relative orientation of images for stereo matching. It also includes masking of large water areas that seriously reduce the quality of the results. Furthermore, a good estimate of the depth range is required, since accurate estimates can seriously reduce the processing time for stereo matching. In this paper an approach is presented that allows performing all these steps fully automated. It includes very robust and precise tie point selection, enabling the accurate calculation of the images’ relative orientation via bundle adjustment. It is also shown how water masking and elevation range estimation can be performed automatically on the base of freely available SRTM data. Extensive tests with a large number of different satellite images from QuickBird and WorldView are presented as proof of the robustness and reliability of the proposed method.

  4. Advances In very high resolution satellite imagery analysis for Monitoring human settlements

    Energy Technology Data Exchange (ETDEWEB)

    Vatsavai, Raju [ORNL; Cheriyadat, Anil M [ORNL; Bhaduri, Budhendra L [ORNL

    2014-01-01

    The high rate of urbanization, political conflicts and ensuing internal displacement of population, and increased poverty in the 20th century has resulted in rapid increase of informal settlements. These unplanned, unauthorized, and/or unstructured homes, known as informal settlements, shantytowns, barrios, or slums, pose several challenges to the nations, as these settlements are often located in most hazardous regions and lack basic services. Though several World Bank and United Nations sponsored studies stress the importance of poverty maps in designing better policies and interventions, mapping slums of the world is a daunting and challenging task. In this paper, we summarize our ongoing research on settlement mapping through the utilization of Very high resolution (VHR) remote sensing imagery. Most existing approaches used to classify VHR images are single instance (or pixel-based) learning algorithms, which are inadequate for analyzing VHR imagery, as single pixels do not contain sufficient contextual information (see Figure 1). However, much needed spatial contextual information can be captured via feature extraction and/or through newer machine learning algorithms in order to extract complex spatial patterns that distinguish informal settlements from formal ones. In recent years, we made significant progress in advancing the state of art in both directions. This paper summarizes these results.

  5. Assessment of spatial distribution of soil heavy metals using ANN-GA, MSLR and satellite imagery.

    Science.gov (United States)

    Naderi, Arman; Delavar, Mohammad Amir; Kaboudin, Babak; Askari, Mohammad Sadegh

    2017-05-01

    This study aims to assess and compare heavy metal distribution models developed using stepwise multiple linear regression (MSLR) and neural network-genetic algorithm model (ANN-GA) based on satellite imagery. The source identification of heavy metals was also explored using local Moran index. Soil samples (n = 300) were collected based on a grid and pH, organic matter, clay, iron oxide contents cadmium (Cd), lead (Pb) and zinc (Zn) concentrations were determined for each sample. Visible/near-infrared reflectance (VNIR) within the electromagnetic ranges of satellite imagery was applied to estimate heavy metal concentrations in the soil using MSLR and ANN-GA models. The models were evaluated and ANN-GA model demonstrated higher accuracy, and the autocorrelation results showed higher significant clusters of heavy metals around the industrial zone. The higher concentration of Cd, Pb and Zn was noted under industrial lands and irrigation farming in comparison to barren and dryland farming. Accumulation of industrial wastes in roads and streams was identified as main sources of pollution, and the concentration of soil heavy metals was reduced by increasing the distance from these sources. In comparison to MLSR, ANN-GA provided a more accurate indirect assessment of heavy metal concentrations in highly polluted soils. The clustering analysis provided reliable information about the spatial distribution of soil heavy metals and their sources.

  6. Pseudofaults and associated seamounts in the conjugate Arabian and Eastern Somali basins, NW Indian Ocean - New constraints from high-resolution satellite-derived gravity data

    Science.gov (United States)

    Sreejith, K. M.; Chaubey, A. K.; Mishra, Akhil; Kumar, Shravan; Rajawat, A. S.

    2016-12-01

    Marine gravity data derived from satellite altimeters are effective tools in mapping fine-scale tectonic features of the ocean basins such as pseudofaults, fracture zones and seamounts, particularly when the ocean basins are carpeted with thick sediments. We use high-resolution satellite-generated gravity and seismic reflection data to map boundaries of pseudofaults and transferred crust related to the Paleocene spreading ridge propagation in the Arabian and its conjugate Eastern Somali basins. The study has provided refinement in the position of previously reported pseudofaults and their spatial extensions in the conjugate basins. It is observed that the transferred crustal block bounded by inner pseudofault and failed spreading ridge is characterized by a gravity low and rugged basement. The refined satellite gravity image of the Arabian Basin also revealed three seamounts in close proximity to the pseudofaults, which were not reported earlier. In the Eastern Somali Basin, seamounts are aligned along NE-SW direction forming ∼300 km long seamount chain. Admittance analysis and Flexural model studies indicated that the seamount chain is isostatically compensated locally with Effective Elastic Thickness (Te) of 3-4 km. Based on the present results and published plate tectonic models, we interpret that the seamounts in the Arabian Basin are formed by spreading ridge propagation and are associated with pseudofaults, whereas the seamount chain in the Eastern Somali Basin might have probably originated due to melting and upwelling of upper mantle heterogeneities in advance of migrating/propagating paleo Carlsberg Ridge.

  7. Improved spatial resolution of luminescence images acquired with a silicon line scanning camera

    Science.gov (United States)

    Teal, Anthony; Mitchell, Bernhard; Juhl, Mattias K.

    2018-04-01

    Luminescence imaging is currently being used to provide spatially resolved defect in high volume silicon solar cell production. One option to obtain the high throughput required for on the fly detection is the use a silicon line scan cameras. However, when using a silicon based camera, the spatial resolution is reduced as a result of the weakly absorbed light scattering within the camera's chip. This paper address this issue by applying deconvolution from a measured point spread function. This paper extends the methods for determining the point spread function of a silicon area camera to a line scan camera with charge transfer. The improvement in resolution is quantified in the Fourier domain and in spatial domain on an image of a multicrystalline silicon brick. It is found that light spreading beyond the active sensor area is significant in line scan sensors, but can be corrected for through normalization of the point spread function. The application of this method improves the raw data, allowing effective detection of the spatial resolution of defects in manufacturing.

  8. Study of the spatial resolution of low-material GEM tracking detectors

    Directory of Open Access Journals (Sweden)

    Kudryavtsev V.N.

    2018-01-01

    Full Text Available The spatial resolution of GEM based tracking detectors has been simulated and measured. The simulation includes the GEANT4 based transport of high energy electrons with careful accounting for atomic relaxation processes including emission of fluorescent photons and Auger electrons and custom post-processing, including accounting for diffusion, gas amplification fluctuations, the distribution of signals on readout electrodes, electronics noise and a particular algorithm of the final coordinate calculation (center of gravity. The simulation demonstrates that a minimum of the spatial resolution of about 10 μm can be achieved with strip pitches from 250 μm to 300 μm. For larger pitches the resolution is quickly degrading reaching 80-100 μm at a pitch of 500 μm. The spatial resolution of low-material triple-GEM detectors for the DEUTRON facility at the VEPP-3 storage ring is measured at the extracted beam facility of the VEPP-4M collider. The amount of material in these detectors is reduced by etching the copper of the GEMs electrodes and using a readout structure on a thin kapton foil rather than on a glass fibre plate. The exact amount of material in one DEUTRON detector is measured by studying multiple scattering of 100 MeV electrons in it. The result of these measurements is X/X0 = 2.4×10−3 corresponding to a thickness of the copper layers of the GEM foils of 3 μm. The spatial resolution of one DEUTRON detector is measured with 500 MeV electrons and the measured value is equal to 35 ± 1 μm for orthogonal tracks.

  9. Study of the spatial resolution of low-material GEM tracking detectors

    Science.gov (United States)

    Kudryavtsev, V. N.; Maltsev, T. V.; Shekhtman, L. I.

    2018-02-01

    The spatial resolution of GEM based tracking detectors has been simulated and measured. The simulation includes the GEANT4 based transport of high energy electrons with careful accounting for atomic relaxation processes including emission of fluorescent photons and Auger electrons and custom post-processing, including accounting for diffusion, gas amplification fluctuations, the distribution of signals on readout electrodes, electronics noise and a particular algorithm of the final coordinate calculation (center of gravity). The simulation demonstrates that a minimum of the spatial resolution of about 10 μm can be achieved with strip pitches from 250 μm to 300 μm. For larger pitches the resolution is quickly degrading reaching 80-100 μm at a pitch of 500 μm. The spatial resolution of low-material triple-GEM detectors for the DEUTRON facility at the VEPP-3 storage ring is measured at the extracted beam facility of the VEPP-4M collider. The amount of material in these detectors is reduced by etching the copper of the GEMs electrodes and using a readout structure on a thin kapton foil rather than on a glass fibre plate. The exact amount of material in one DEUTRON detector is measured by studying multiple scattering of 100 MeV electrons in it. The result of these measurements is X/X0 = 2.4×10-3 corresponding to a thickness of the copper layers of the GEM foils of 3 μm. The spatial resolution of one DEUTRON detector is measured with 500 MeV electrons and the measured value is equal to 35 ± 1 μm for orthogonal tracks.

  10. Monitoring of the Orbital Position of a Geostationary Satellite by the Spatially Separated Reception of Signals of Digital Satellite Television

    Directory of Open Access Journals (Sweden)

    Kaliuzny, M.P.

    2017-01-01

    Full Text Available The results of the determination of the geostationary satellite «Eutelsat-13B» orbital position obtained during 2015-2016 years using European stations’ network for reception of DVB-S signals from the satellite are presented. The network consists of five stations located in Ukraine and Latvia. The stations are equipped with a radio engineering complex developed by the RI «MAO». The measured parameter is a time difference of arrival (TDOA of the DVB-S signals to the stations of the network. The errors of TDOA determination and satellite coordinates, obtained using a numerical model of satellite motion, are equal ±2.6m and ±35m respectively. Software implementation of the numerical model is taken from the free space dynamics library OREKIT.

  11. A mixed-effects, spatially varying coefficients model with application to multi-resolution functional magnetic resonance imaging data.

    Science.gov (United States)

    Liu, Zhuqing; Bartsch, Andreas J; Berrocal, Veronica J; Johnson, Timothy D

    2018-01-01

    Spatial resolution plays an important role in functional magnetic resonance imaging studies as the signal-to-noise ratio increases linearly with voxel volume. In scientific studies, where functional magnetic resonance imaging is widely used, the standard spatial resolution typically used is relatively low which ensures a relatively high signal-to-noise ratio. However, for pre-surgical functional magnetic resonance imaging analysis, where spatial accuracy is paramount, high-resolution functional magnetic resonance imaging may play an important role with its greater spatial resolution. High spatial resolution comes at the cost of a smaller signal-to-noise ratio. This begs the question as to whether we can leverage the higher signal-to-noise ratio of a standard functional magnetic resonance imaging study with the greater spatial accuracy of a high-resolution functional magnetic resonance imaging study in a pre-operative patient. To answer this question, we propose to regress the statistic image from a high resolution scan onto the statistic image obtained from a standard resolution scan using a mixed-effects model with spatially varying coefficients. We evaluate our model via simulation studies and we compare its performance with a recently proposed model that operates at a single spatial resolution. We apply and compare the two models on data from a patient awaiting tumor resection. Both simulation study results and the real data analysis demonstrate that our newly proposed model indeed leverages the larger signal-to-noise ratio of the standard spatial resolution scan while maintaining the advantages of the high spatial resolution scan.

  12. High spatial resolution remote sensing imagery improves GPP predictions in disturbed, semi-arid woodlands

    Science.gov (United States)

    Krofcheck, D. J.; Eitel, J.; Vierling, L. A.; Schulthess, U.; Litvak, M. E.

    2012-12-01

    Climate across the globe is changing and consequently the productivity of terrestrial vegetation is changing with it. Gross primary productivity (GPP) is an integral part of the carbon cycle, yet challenging to measure everywhere, all the time. Efforts to estimate GPP in the context of climate change are becoming continually more salient of the need for models sensitive to the heterogeneous nature of drought and pest induced disturbance. Given the increased availability of high spatial resolution remotely sensed imagery, their use in ecosystem scale GPP estimation is becoming increasingly viable. We used a simple linear model with inputs derived from RapidEye time series data (5 meter spatial resolution) as compared to MODIS inputs (250 meter spatial resolution) to estimate GPP in intact and girdled PJ woodland to simulate drought and pest induced disturbance. An area equal to the MODIS pixels measured was aggregated using RapidEye data centered on the flux towers for comparison purposes. We generated four model runs, two using only MODIS or RapidEye spectral vegetation indices (VIs) and two using MODIS and RapidEye VIs combined at both the control and disturbed tower site. Our results suggest that for undisturbed regions, MODIS derived VIs perform better than the higher spatial resolution RapidEye VIs when a moisture sensitive index is incorporated into the model (RMSE of 17.51for MODIS vs. 22.71 for RapidEye). Modeling GPP in disturbed regions however benefits from the inclusion of high spatial resolution data (RMSE of 14.83 for MODIS vs. 14.70 for RapidEye). This discrepancy may have to do with the disparate scale of a MODIS pixel and the size of the tower fetch. Our results suggest that the best source of VI's for the modeling GPP in semi-arid woodlands depends on the level of disturbance in the landscape. Given that the rate and extent of drought and insect induced mortality events in terrestrial forests are projected to increase with our changing climate

  13. [A novel spatial modulation Fourier transform spectrometer with adjustable spectral resolution].

    Science.gov (United States)

    Lian, Yu-Sheng; Liao, Ning-Fang; Lü, Hang; Wu, Wen-Min; Dong, Zhi-Gang

    2014-11-01

    In the premise of fulfilling the application requirement, the adjustment of spectral resolution can improve efficiency of data acquisition, data processing and data saving. So, by adjusting the spectral resolution, the performance of spectrometer can be improved, and its application range can be extended. To avoid the problems of the fixed spectral resolution of classical Fourier transform spectrometer, a novel type of spatial modulation Fourier transform spectrometer with adjustable spectral resolution is proposed in this paper. The principle of the novel spectrometer and its interferometer is described. The general expressions of the optical path difference and the lateral shear are induced by a ray tracing procedure. The equivalent model of the novel interferometer is analyzed. Meanwhile, the principle of the adjustment of spectral resolution is analyzed. The result shows that the novel spectrometer has the merits of adjustable spectral resolution, high stability, easy assemblage and adjustment etc. This theoretical study will provide the theoretical basis for the design of the spectrometer with adjustable spectral resolution and expand the application range of Fourier transform spectrometer.

  14. High Cognitive Reserve is associated with a reduced age-related deficit in spatial conflict resolution.

    Directory of Open Access Journals (Sweden)

    Olga ePuccioni

    2012-12-01

    Full Text Available Several studies support the existence of a specific age-related difficulty in suppressing potentially distracting information. The aim of the present study is to investigate whether spatial conflict resolution is selectively affected by aging. The way aging affects individuals could be modulated by many factors determined by the socieconomic status: we investigated whether factors such as cognitive reserve (CR and years of education may play a compensatory role against age-related deficits in the spatial domain. A spatial Stroop task with no feature repetitions was administered to a sample of 17 non-demented older adults (69-79 years old and 18 younger controls (18-34 years old matched for gender and years of education. The two age groups were also administered with measures of intelligence and CR. The overall spatial Stroop effect did not differ according to age, neither for speed nor for accuracy. The two age groups equally showed sequential effects for congruent trials: reduced response times (RTs if another congruent trial preceded them, and accuracy at ceiling. For incongruent trials, older adults, but not younger controls, were influenced by congruency of trialn-1, since RTs increased with preceding congruent trials. Interestingly, such an age-related modulation negatively correlated with CR. These findings suggest that spatial conflict resolution in aging is predominantly affected by general slowing, rather than by a more specific deficit. However, a high level of CR seems to play a compensatory role for both factors.

  15. High cognitive reserve is associated with a reduced age-related deficit in spatial conflict resolution

    Science.gov (United States)

    Puccioni, Olga; Vallesi, Antonino

    2012-01-01

    Several studies support the existence of a specific age-related difficulty in suppressing potentially distracting information. The aim of the present study is to investigate whether spatial conflict resolution is selectively affected by aging. The way aging affects individuals could be modulated by many factors determined by the socieconomic status: we investigated whether factors such as cognitive reserve (CR) and years of education may play a compensatory role against age-related deficits in the spatial domain. A spatial Stroop task with no feature repetitions was administered to a sample of 17 non-demented older adults (69–79 years-old) and 18 younger controls (18–34 years-old) matched for gender and years of education. The two age groups were also administered with measures of intelligence and CR. The overall spatial Stroop effect did not differ according to age, neither for speed nor for accuracy. The two age groups equally showed sequential effects for congruent trials: reduced response times (RTs) if another congruent trial preceded them, and accuracy at ceiling. For incongruent trials, older adults, but not younger controls, were influenced by congruency of trialn−1, since RTs increased with preceding congruent trials. Interestingly, such an age-related modulation negatively correlated with CR. These findings suggest that spatial conflict resolution in aging is predominantly affected by general slowing, rather than by a more specific deficit. However, a high level of CR seems to play a compensatory role for both factors. PMID:23248595

  16. MISTiC Winds: A micro-satellite constellation approach to high resolution observations of the atmosphere using infrared sounding and 3D winds measurements

    Science.gov (United States)

    Maschhoff, K. R.; Polizotti, J. J.; Aumann, H. H.; Susskind, J.

    2016-09-01

    MISTiCTM Winds is an approach to improve short-term weather forecasting based on a miniature high resolution, wide field, thermal emission spectrometry instrument that will provide global tropospheric vertical profiles of atmospheric temperature and humidity at high (3-4 km) horizontal and vertical ( 1 km) spatial resolution. MISTiC's extraordinarily small size, payload mass of less than 15 kg, and minimal cooling requirements can be accommodated aboard a 27U-class CubeSat or an ESPA-Class micro-satellite. Low fabrication and launch costs enable a LEO sunsynchronous sounding constellation that would collectively provide frequent IR vertical profiles and vertically resolved atmospheric motion vector wind observations in the troposphere. These observations are highly complementary to present and emerging environmental observing systems, and would provide a combination of high vertical and horizontal resolution not provided by any other environmental observing system currently in operation. The spectral measurements that would be provided by MISTiC Winds are similar to those of NASA's AIRS that was built by BAE Systems and operates aboard the AQUA satellite. These new observations, when assimilated into high resolution numerical weather models, would revolutionize short-term and severe weather forecasting, save lives, and support key economic decisions in the energy, air transport, and agriculture arenas-at much lower cost than providing these observations from geostationary orbit. In addition, this observation capability would be a critical tool for the study of transport processes for water vapor, clouds, pollution, and aerosols. Key remaining technical risks are being reduced through laboratory and airborne testing under NASA's Instrument Incubator Program.

  17. MISTiC Winds, a Micro-Satellite Constellation Approach to High Resolution Observations of the Atmosphere using Infrared Sounding and 3D Winds Measurements

    Science.gov (United States)

    Maschhoff, K. R.; Polizotti, J. J.; Susskind, J.; Aumann, H. H.

    2015-12-01

    MISTiCTM Winds is an approach to improve short-term weather forecasting based on a miniature high resolution, wide field, thermal emission spectrometry instrument that will provide global tropospheric vertical profiles of atmospheric temperature and humidity at high (3-4 km) horizontal and vertical ( 1 km) spatial resolution. MISTiC's extraordinarily small size, payload mass of less than 15 kg, and minimal cooling requirements can be accommodated aboard a 27U-class CubeSat or an ESPA-Class micro-satellite. Low fabrication and launch costs enable a LEO sun-synchronous sounding constellation that would collectively provide frequent IR vertical profiles and vertically resolved atmospheric motion vector wind observations in the troposphere. These observations are highly complementary to present and emerging environmental observing systems, and would provide a combination of high vertical and horizontal resolution not provided by any other environmental observing system currently in operation. The spectral measurements that would be provided by MISTiC Winds are similar to those of NASA's Atmospheric Infrared Sounder that was built by BAE Systems and operates aboard the AQUA satellite. These new observations, when assimilated into high resolution numerical weather models, would revolutionize short-term and severe weather forecasting, save lives, and support key economic decisions in the energy, air transport, and agriculture arenas-at much lower cost than providing these observations from geostationary orbit. In addition, this observation capability would be a critical tool for the study of transport processes for water vapor, clouds, pollution, and aerosols. Key technical risks are being reduced through laboratory and airborne testing under NASA's Instrument Incubator Program.

  18. MISTiC Winds, a Micro-Satellite Constellation Approach to High Resolution Observations of the Atmosphere Using Infrared Sounding and 3D Winds Measurements

    Science.gov (United States)

    Maschhoff, K. R.; Polizotti, J. J.; Aumann, H. H.; Susskind, J.

    2016-01-01

    MISTiC(TM) Winds is an approach to improve short-term weather forecasting based on a miniature high resolution, wide field, thermal emission spectrometry instrument that will provide global tropospheric vertical profiles of atmospheric temperature and humidity at high (3-4 km) horizontal and vertical ( 1 km) spatial resolution. MISTiCs extraordinarily small size, payload mass of less than 15 kg, and minimal cooling requirements can be accommodated aboard a 27U-class CubeSat or an ESPA-Class micro-satellite. Low fabrication and launch costs enable a LEO sunsynchronous sounding constellation that would collectively provide frequent IR vertical profiles and vertically resolved atmospheric motion vector wind observations in the troposphere. These observations are highly complementary to present and emerging environmental observing systems, and would provide a combination of high vertical and horizontal resolution not provided by any other environmental observing system currently in operation. The spectral measurements that would be provided by MISTiC Winds are similar to those of NASA's AIRS that was built by BAE Systems and operates aboard the AQUA satellite. These new observations, when assimilated into high resolution numerical weather models, would revolutionize short-term and severe weather forecasting, save lives, and support key economic decisions in the energy, air transport, and agriculture arenasat much lower cost than providing these observations from geostationary orbit. In addition, this observation capability would be a critical tool for the study of transport processes for water vapor, clouds, pollution, and aerosols. Key remaining technical risks are being reduced through laboratory and airborne testing under NASA's Instrument Incubator Program.

  19. A versatile fluorescence lifetime imaging system for scanning large areas with high time and spatial resolution

    Science.gov (United States)

    Bernardo, César; Belsley, Michael; de Matos Gomes, Etelvina; Gonçalves, Hugo; Isakov, Dmitry; Liebold, Falk; Pereira, Eduardo; Pires, Vladimiro; Samantilleke, Anura; Vasilevskiy, Mikhail; Schellenberg, Peter

    2014-08-01

    We present a flexible fluorescence lifetime imaging device which can be employed to scan large sample areas with a spatial resolution adjustable from many micrometers down to sub-micrometers and a temporal resolution of 20 picoseconds. Several different applications of the system will be presented including protein microarrays analysis, the scanning of historical samples, evaluation of solar cell surfaces and nanocrystalline organic crystals embedded in electrospun polymeric nanofibers. Energy transfer processes within semiconductor quantum dot superstructures as well as between dye probes and graphene layers were also investigated.

  20. Efficient, High-Spatial Resolution Neutron Detector for Coded Aperture Imaging of ICF Targets

    Science.gov (United States)

    Lerche, R. A.; Ress, D.; Fisher, R. K.

    1996-11-01

    Imaging the burning core of an ICF target using fusion neutrons requires an efficient detector. Current systems use plastic scintillator arrays 10-cm thick. These limit detector spatial resolution to > 2 mm. We propose using a neutron-sensitive liquid-filled bubble chamber for recording coded aperture images. Each detected neutron forms only one bubble and the threshold energy for bubble formation can be selected. The bubble chamber can be made thick for efficiency, is insensitive to γ-ray background, and has a resolution bubble chamber detector should be significantly less than the equivalent plastic scintillator array with its associated readout system.

  1. Effects of sensor spatial resolution on cloud properties retrieved from imagery data

    Science.gov (United States)

    Coakley, J. A., Jr.

    1986-01-01

    Techniques being applied to test the sensitivity of the physical characteristics of clouds, as determined by remote sensing, to the spatial resolution of the scans are described. The sensitivity is being evaluated with an error assessment of data from the AVHRR instrument on Nimbus-7. A spatial coherence analysis is being applied to AVHRR data for a 250 sq km region in the Pacific off the Mexican coast. Errors in the derived cloud cover and radiances from which cloud-free regions and cloud-covered regions are being estimated on the basis of radiance values in pixel-sized areas.

  2. Evaluating the Value of High Spatial Resolution in National Capacity Expansion Models using ReEDS: Preprint

    Energy Technology Data Exchange (ETDEWEB)

    Krishnan, Venkat; Cole, Wesley

    2016-07-01

    Power sector capacity expansion models (CEMs) have a broad range of spatial resolutions. This paper uses the Regional Energy Deployment System (ReEDS) model, a long-term national scale electric sector CEM, to evaluate the value of high spatial resolution for CEMs. ReEDS models the United States with 134 load balancing areas (BAs) and captures the variability in existing generation parameters, future technology costs, performance, and resource availability using very high spatial resolution data, especially for wind and solar modeled at 356 resource regions. In this paper we perform planning studies at three different spatial resolutions--native resolution (134 BAs), state-level, and NERC region level--and evaluate how results change under different levels of spatial aggregation in terms of renewable capacity deployment and location, associated transmission builds, and system costs. The results are used to ascertain the value of high geographically resolved models in terms of their impact on relative competitiveness among renewable energy resources.

  3. Identification and classification of structural soil conservation measures based on very high resolution stereo satellite data.

    Science.gov (United States)

    Eckert, Sandra; Tesfay Ghebremicael, Selamawit; Hurni, Hans; Kohler, Thomas

    2017-05-15

    Land degradation affects large areas of land around the globe, with grave consequences for those living off the land. Major efforts are being made to implement soil and water conservation measures that counteract soil erosion and help secure vital ecosystem services. However, where and to what extent such measures have been implemented is often not well documented. Knowledge about this could help to identify areas where soil and water conservation measures are successfully supporting sustainable land management, as well as areas requiring urgent rehabilitation of conservation structures such as terraces and bunds. This study explores the potential of the latest satellite-based remote sensing technology for use in assessing and monitoring the extent of existing soil and water conservation structures. We used a set of very high resolution stereo Geoeye-1 satellite data, from which we derived a detailed digital surface model as well as a set of other spectral, terrain, texture, and filtered information layers. We developed and applied an object-based classification approach, working on two segmentation levels. On the coarser level, the aim was to delimit certain landscape zones. Information about these landscape zones is useful in distinguishing different types of soil and water conservation structures, as each zone contains certain specific types of structures. On the finer level, the goal was to extract and identify different types of linear soil and water conservation structures. The classification rules were based mainly on spectral, textural, shape, and topographic properties, and included object relationships. This approach enabled us to identify and separate from other classes the majority (78.5%) of terraces and bunds, as well as most hillside terraces (81.25%). Omission and commission errors are similar to those obtained by the few existing studies focusing on the same research objective but using different types of remotely sensed data. Based on our results

  4. A comprehensive biomass burning emission inventory with high spatial and temporal resolution in China

    Science.gov (United States)

    Zhou, Ying; Xing, Xiaofan; Lang, Jianlei; Chen, Dongsheng; Cheng, Shuiyuan; Wei, Lin; Wei, Xiao; Liu, Chao

    2017-02-01

    Biomass burning injects many different gases and aerosols into the atmosphere that could have a harmful effect on air quality, climate, and human health. In this study, a comprehensive biomass burning emission inventory including domestic and in-field straw burning, firewood burning, livestock excrement burning, and forest and grassland fires is presented, which was developed for mainland China in 2012 based on county-level activity data, satellite data, and updated source-specific emission factors (EFs). The emission inventory within a 1 × 1 km2 grid was generated using geographical information system (GIS) technology according to source-based spatial surrogates. A range of key information related to emission estimation (e.g. province-specific proportion of domestic and in-field straw burning, detailed firewood burning quantities, uneven temporal distribution coefficient) was obtained from field investigation, systematic combing of the latest research, and regression analysis of statistical data. The established emission inventory includes the major precursors of complex pollution, greenhouse gases, and heavy metal released from biomass burning. The results show that the emissions of SO2, NOx, PM10, PM2.5, NMVOC, NH3, CO, EC, OC, CO2, CH4, and Hg in 2012 are 336.8 Gg, 990.7 Gg, 3728.3 Gg, 3526.7 Gg, 3474.2 Gg, 401.2 Gg, 34 380.4 Gg, 369.7 Gg, 1189.5 Gg, 675 299.0 Gg, 2092.4 Gg, and 4.12 Mg, respectively. Domestic straw burning, in-field straw burning, and firewood burning are identified as the dominant biomass burning sources. The largest contributing source is different for various pollutants. Domestic straw burning is the largest source of biomass burning emissions for all the pollutants considered, except for NH3, EC (firewood), and NOx (in-field straw). Corn, rice, and wheat represent the major crop straws. The combined emission of these three straw types accounts for 80 % of the total straw-burned emissions for each specific pollutant mentioned in this study

  5. Atmospheric Moisture Budget and Spatial Resolution Dependence of Precipitation Extremes in Aquaplanet Simulations

    Energy Technology Data Exchange (ETDEWEB)

    Yang, Qing; Leung, Lai-Yung R.; Rauscher, Sara; Ringler, Todd; Taylor, Mark

    2014-05-01

    data aggregation effect in omega, thermodynamic changes become relatively significant in offsetting the effect of dynamics leading to reduce differences between the simulated and aggregated results. Compared to MPAS, the simulated stronger vertical motion with HOMME also results in larger resolution dependency. Compared to the simulation at fine resolution, the vertical motion during extremes is insufficiently resolved/parameterized at the coarser resolution even after accounting for the natural reduction in variability with coarser resolution, and this is more distinct in the simulation with HOMME. To reduce uncertainties in simulated precipitation extremes, future development in cloud parameterizations must address their sensitivity to spatial resolution as well as dynamical cores.

  6. 3D high spectral and spatial resolution imaging of ex vivo mouse brain

    International Nuclear Information System (INIS)

    Foxley, Sean; Karczmar, Gregory S.; Domowicz, Miriam; Schwartz, Nancy

    2015-01-01

    Purpose: Widely used MRI methods show brain morphology both in vivo and ex vivo at very high resolution. Many of these methods (e.g., T 2 * -weighted imaging, phase-sensitive imaging, or susceptibility-weighted imaging) are sensitive to local magnetic susceptibility gradients produced by subtle variations in tissue composition. However, the spectral resolution of commonly used methods is limited to maintain reasonable run-time combined with very high spatial resolution. Here, the authors report on data acquisition at increased spectral resolution, with 3-dimensional high spectral and spatial resolution MRI, in order to analyze subtle variations in water proton resonance frequency and lineshape that reflect local anatomy. The resulting information compliments previous studies based on T 2 * and resonance frequency. Methods: The proton free induction decay was sampled at high resolution and Fourier transformed to produce a high-resolution water spectrum for each image voxel in a 3D volume. Data were acquired using a multigradient echo pulse sequence (i.e., echo-planar spectroscopic imaging) with a spatial resolution of 50 × 50 × 70 μm 3 and spectral resolution of 3.5 Hz. Data were analyzed in the spectral domain, and images were produced from the various Fourier components of the water resonance. This allowed precise measurement of local variations in water resonance frequency and lineshape, at the expense of significantly increased run time (16–24 h). Results: High contrast T 2 * -weighted images were produced from the peak of the water resonance (peak height image), revealing a high degree of anatomical detail, specifically in the hippocampus and cerebellum. In images produced from Fourier components of the water resonance at −7.0 Hz from the peak, the contrast between deep white matter tracts and the surrounding tissue is the reverse of the contrast in water peak height images. This indicates the presence of a shoulder in the water resonance that is not

  7. 3D high spectral and spatial resolution imaging of ex vivo mouse brain

    Energy Technology Data Exchange (ETDEWEB)

    Foxley, Sean, E-mail: sean.foxley@ndcn.ox.ac.uk; Karczmar, Gregory S. [Department of Radiology, University of Chicago, Chicago, Illinois 60637 (United States); Domowicz, Miriam [Department of Pediatrics, University of Chicago, Chicago, Illinois 60637 (United States); Schwartz, Nancy [Department of Pediatrics, Department of Biochemistry and Molecular Biology, University of Chicago, Chicago, Illinois 60637 (United States)

    2015-03-15

    Purpose: Widely used MRI methods show brain morphology both in vivo and ex vivo at very high resolution. Many of these methods (e.g., T{sub 2}{sup *}-weighted imaging, phase-sensitive imaging, or susceptibility-weighted imaging) are sensitive to local magnetic susceptibility gradients produced by subtle variations in tissue composition. However, the spectral resolution of commonly used methods is limited to maintain reasonable run-time combined with very high spatial resolution. Here, the authors report on data acquisition at increased spectral resolution, with 3-dimensional high spectral and spatial resolution MRI, in order to analyze subtle variations in water proton resonance frequency and lineshape that reflect local anatomy. The resulting information compliments previous studies based on T{sub 2}{sup *} and resonance frequency. Methods: The proton free induction decay was sampled at high resolution and Fourier transformed to produce a high-resolution water spectrum for each image voxel in a 3D volume. Data were acquired using a multigradient echo pulse sequence (i.e., echo-planar spectroscopic imaging) with a spatial resolution of 50 × 50 × 70 μm{sup 3} and spectral resolution of 3.5 Hz. Data were analyzed in the spectral domain, and images were produced from the various Fourier components of the water resonance. This allowed precise measurement of local variations in water resonance frequency and lineshape, at the expense of significantly increased run time (16–24 h). Results: High contrast T{sub 2}{sup *}-weighted images were produced from the peak of the water resonance (peak height image), revealing a high degree of anatomical detail, specifically in the hippocampus and cerebellum. In images produced from Fourier components of the water resonance at −7.0 Hz from the peak, the contrast between deep white matter tracts and the surrounding tissue is the reverse of the contrast in water peak height images. This indicates the presence of a shoulder in

  8. Temporal and spatial air quality monitoring using internet protocol camera and LANSAT5 satellite image

    Science.gov (United States)

    Wong, C. J.; Lim, H. S.; MatJafri, M. Z.; Abdullah, K.; Chin, T. S.

    2009-05-01

    Atmospheric fine particles with diameter less than 10 micron (PM10) have already become a major public health concern in any part of the world. These particles can be breathed more deeply into the lungs to cause adverse health effects. In order to prevent long exposure to these harmful atmospheric particles, this motivates a growing interest in developing efficient methods of fine particles monitoring. In this study, we proposed that an internet protocol camera and LANDSAT5 satellite image be used to monitor the temporal and spatial air quality. We developed an algorithm to converts multispectral image pixel values acquired from digital images into quantitative values of the concentrations of PM10. This algorithm was developed based on the regression analysis of relationship between the measured reflectance and the reflected components from a surface material and the ambient air. The computed PM10 values were compared to other standard values measured by a DustTrak meter. The correlation results showed that the newly develop algorithm produced a high degree of accuracy as indicated by high correlation coefficient (R2) and low root-mean-square-error (RMS). This study indicates that the temporal and spatial development of air quality can be monitored by using internet protocol camera and LANDSAT5 images.

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

    Science.gov (United States)

    D.J. Hayes; W.B. Cohen

    2006-01-01

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

  10. Silicon microstrip detectors for digital mammography - evaluation and spatial resolution study

    CERN Document Server

    Mali, T; Mikuz, M

    2001-01-01

    Silicon microstrip detectors were used to build an experimental X-ray imaging setup. The detectors were used in an 'edge-on' geometry, with the photons hitting the detector from the side. Efficiencies up to 90% at 20 keV photon energy could be achieved. The system was tested using a standard mammographic phantom. Images of modeled microcalcifications with various diameters down to 200 mu m and images of modeled tumors were made. Spatial resolution of the system was studied on an X-ray test pattern with frequency of line-pairs between 1 and 10l p/mm. An appropriate scanning step combined with knowledge of the system's line spread function was used to deconvolve the measured image and increase the spatial resolution. In this way the effective pixel size was reduced as much as for a factor of approx 3.

  11. Matrix Sublimation/Recrystallization for Imaging Proteins by Mass Spectrometry at High Spatial Resolution

    Science.gov (United States)

    Yang, Junhai; Caprioli, Richard M.

    2011-01-01

    We have employed matrix deposition by sublimation for protein image analysis on tissue sections using a hydration/recrystallization process that produces high quality MALDI mass spectra and high spatial resolution ion images. We systematically investigated different washing protocols, the effect of tissue section thickness, the amount of sublimated matrix per unit area and different recrystallization conditions. The results show that an organic solvent rinse followed by ethanol/water rinses substantially increased sensitivity for the detection of proteins. Both the thickness of tissue section and amount of sinapinic acid sublimated per unit area have optimal ranges for maximal protein signal intensity. Ion images of mouse and rat brain sections at 50, 20 and 10 µm spatial resolution are presented and are correlated with H&E stained optical images. For targeted analysis, histology directed imaging can be performed using this protocol where MS analysis and H&E staining are performed on the same section. PMID:21639088

  12. Experimental Estimation of CLASP Spatial and Spectral Resolutions: Results of the Instrument's Optical Alignment

    Science.gov (United States)

    Giono, G.; Katsukawa, Y.; Ishikawa, R.; Narukage, N.; Bando, T.; Kano, R.; Suematsu, Y.; Winebarger, A.; Kobayashi, K.; Auchere, F.

    2015-01-01

    The Chromospheric Lyman-Alpha SpectroPolarimeter is a sounding rocket experiment design to measure for the first time the polarization signal of the Lyman-Alpha line (121.6nm), emitted in the solar upper-chromosphere and transition region. This instrument aims to detect the Hanle effect's signature hidden in the Ly-alpha polarization, as a tool to probe the chromospheric magnetic field. Hence, an unprecedented polarization accuracy is needed ((is) less than 10 (exp -3). Nevertheless, spatial and spectral resolutions are also crucial to observe chhromospheric feature such as spicules, and to have precise measurement of the Ly-alpha line core and wings. Hence, this poster will present how the telescope and the spectrograph were separately aligned, and their combined spatial and spectral resolutions.

  13. Effects of Electric Field Gradient on Sub-nanometer Spatial Resolution of Tip-enhanced Raman Spectroscopy

    OpenAIRE

    Meng, Lingyan; Yang, Zhilin; Chen, Jianing; Sun, Mengtao

    2014-01-01

    Tip-enhanced Raman spectroscopy (TERS) with sub-nanometer spatial resolution has been recently demonstrated experimentally. However, the physical mechanism underlying is still under discussion. Here, we theoretically investigate the electric field gradient of a coupled tip-substrate system. Our calculations suggest that the ultra-high spatial resolution of TERS can be partially attributed to the electric field gradient effect owning to its tighter spatial confinement and sensitivity to the in...

  14. Effects of high spatial and temporal resolution Earth observations on simulated hydrometeorological variables in a cropland (southwestern France

    Directory of Open Access Journals (Sweden)

    J. Etchanchu

    2017-11-01

    Full Text Available Agricultural landscapes are often constituted by a patchwork of crop fields whose seasonal evolution is dependent on specific crop rotation patterns and phenologies. This temporal and spatial heterogeneity affects surface hydrometeorological processes and must be taken into account in simulations of land surface and distributed hydrological models. The Sentinel-2 mission allows for the monitoring of land cover and vegetation dynamics at unprecedented spatial resolutions and revisit frequencies (20 m and 5 days, respectively that are fully compatible with such heterogeneous agricultural landscapes. Here, we evaluate the impact of Sentinel-2-like remote sensing data on the simulation of surface water and energy fluxes via the Interactions between the Surface Biosphere Atmosphere (ISBA land surface model included in the EXternalized SURface (SURFEX modeling platform. The study focuses on the effect of the leaf area index (LAI spatial and temporal variability on these fluxes. We compare the use of the LAI climatology from ECOCLIMAP-II, used by default in SURFEX-ISBA, and time series of LAI derived from the high-resolution Formosat-2 satellite data (8 m. The study area is an agricultural zone in southwestern France covering 576 km2 (24 km  ×  24 km. An innovative plot-scale approach is used, in which each computational unit has a homogeneous vegetation type. Evaluation of the simulations quality is done by comparing model outputs with in situ eddy covariance measurements of latent heat flux (LE. Our results show that the use of LAI derived from high-resolution remote sensing significantly improves simulated evapotranspiration with respect to ECOCLIMAP-II, especially when the surface is covered with summer crops. The comparison with in situ measurements shows an improvement of roughly 0.3 in the correlation coefficient and a decrease of around 30 % of the root mean square error (RMSE in the simulated evapotranspiration. This

  15. High-resolution mapping and spatial variability of soil organic carbon storage of permafrost-affected soils

    Science.gov (United States)

    Siewert, Matthias; Hugelius, Gustaf

    2017-04-01

    Permafrost-affected soils store large amounts of soil organic carbon (SOC). Mapping of this SOC provides a first order spatial input variable for research that relates carbon stored in permafrost regions to carbon cycle dynamics. High-resolution satellite imagery is becoming increasingly available even in circum-polar regions. The presented research highlights findings of high-resolution mapping efforts of SOC from five study areas in the northern circum-polar permafrost region. These study areas are located in Siberia (Kytalyk, Spasskaya Pad /Neleger, Lena delta), Northern Sweden (Abisko) and Northwestern Canada (Herschel Island). Our high spatial resolution analyses show how geomorphology has a strong influence on the distribution of SOC. This is organized at different spatial scales. Periglacial landforms and processes dictate local scale SOC distribution due to patterned ground. Such landforms are non-sorted circles and ice-wedge polygons of different age and scale. Palsas and peat plateaus are formed and can cover larger areas in Sub-Arctic environments. Study areas that have not been affected by Pleistocene glaciation feature ice-rich Yedoma sediments that dominate the local relief through thermokarst formation and create landscape scale macro environments that dictate the distribution of SOC. A general trend indicates higher SOC storage in Arctic tundra soils compared to forested Boreal or Sub-Arctic taiga soils. Yet, due to the shallower active layer depth in the Arctic, much of the SOC may be permanently frozen and thus not be available to ecosystem processes. Significantly more SOC is stored in soils compared to vegetation, indicating that vegetation growth and incorporation of the carbon into the plant phytomass alone will not be able to offset SOC released from permafrost. This contribution also addresses advances in thematic mapping methods and digital soil mapping of SOC in permafrost terrain. In particular machine-learning methods, such as support

  16. Assessing the Resolution Adaptability of the Zhang-McFarlane Cumulus Parameterization With Spatial and Temporal Averaging: RESOLUTION ADAPTABILITY OF ZM SCHEME

    Energy Technology Data Exchange (ETDEWEB)

    Yun, Yuxing [Atmospheric Sciences and Global Change Division, Pacific Northwest National Laboratory, Richland WA USA; State Key Laboratory of Severe Weather, Chinese Academy of Meteorological Sciences, Beijing China; Fan, Jiwen [Atmospheric Sciences and Global Change Division, Pacific Northwest National Laboratory, Richland WA USA; Xiao, Heng [Atmospheric Sciences and Global Change Division, Pacific Northwest National Laboratory, Richland WA USA; Zhang, Guang J. [Scripps Institution of Oceanography, University of California, San Diego CA USA; Ghan, Steven J. [Atmospheric Sciences and Global Change Division, Pacific Northwest National Laboratory, Richland WA USA; Xu, Kuan-Man [NASA Langley Research Center, Hampton VA USA; Ma, Po-Lun [Atmospheric Sciences and Global Change Division, Pacific Northwest National Laboratory, Richland WA USA; Gustafson, William I. [Atmospheric Sciences and Global Change Division, Pacific Northwest National Laboratory, Richland WA USA

    2017-11-01

    Realistic modeling of cumulus convection at fine model resolutions (a few to a few tens of km) is problematic since it requires the cumulus scheme to adapt to higher resolution than they were originally designed for (~100 km). To solve this problem, we implement the spatial averaging method proposed in Xiao et al. (2015) and also propose a temporal averaging method for the large-scale convective available potential energy (CAPE) tendency in the Zhang-McFarlane (ZM) cumulus parameterization. The resolution adaptability of the original ZM scheme, the scheme with spatial averaging, and the scheme with both spatial and temporal averaging at 4-32 km resolution is assessed using the Weather Research and Forecasting (WRF) model, by comparing with Cloud Resolving Model (CRM) results. We find that the original ZM scheme has very poor resolution adaptability, with sub-grid convective transport and precipitation increasing significantly as the resolution increases. The spatial averaging method improves the resolution adaptability of the ZM scheme and better conserves the total transport of moist static energy and total precipitation. With the temporal averaging method, the resolution adaptability of the scheme is further improved, with sub-grid convective precipitation becoming smaller than resolved precipitation for resolution higher than 8 km, which is consistent with the results from the CRM simulation. Both the spatial distribution and time series of precipitation are improved with the spatial and temporal averaging methods. The results may be helpful for developing resolution adaptability for other cumulus parameterizations that are based on quasi-equilibrium assumption.

  17. Study of spatial resolution of YAG:Ce cathodoluminescent imaging screens

    Czech Academy of Sciences Publication Activity Database

    Schauer, Petr; Bok, Jan

    2013-01-01

    Roč. 308, 1 August (2013), s. 68-73 ISSN 0168-583X R&D Projects: GA TA ČR TE01020118; GA ČR GAP102/10/1410; GA MŠk EE.2.3.20.0103 Institutional support: RVO:68081731 Keywords : Spatial resolution * Imaging screen * Electron microscope * Cathodoluminescence * YAG:Ce single crystal * Line spread function * Modulation transfer function Subject RIV: JA - Electronics ; Optoelectronics, Electrical Engineering Impact factor: 1.186, year: 2013

  18. Difet: Distributed Feature Extraction Tool for High Spatial Resolution Remote Sensing Images

    Science.gov (United States)

    Eken, S.; Aydın, E.; Sayar, A.

    2017-11-01

    In this paper, we propose distributed feature extraction tool from high spatial resolution remote sensing images. Tool is based on Apache Hadoop framework and Hadoop Image Processing Interface. Two corner detection (Harris and Shi-Tomasi) algorithms and five feature descriptors (SIFT, SURF, FAST, BRIEF, and ORB) are considered. Robustness of the tool in the task of feature extraction from LandSat-8 imageries are evaluated in terms of horizontal scalability.

  19. DIFET: DISTRIBUTED FEATURE EXTRACTION TOOL FOR HIGH SPATIAL RESOLUTION REMOTE SENSING IMAGES

    Directory of Open Access Journals (Sweden)

    S. Eken

    2017-11-01

    Full Text Available In this paper, we propose distributed feature extraction tool from high spatial resolution remote sensing images. Tool is based on Apache Hadoop framework and Hadoop Image Processing Interface. Two corner detection (Harris and Shi-Tomasi algorithms and five feature descriptors (SIFT, SURF, FAST, BRIEF, and ORB are considered. Robustness of the tool in the task of feature extraction from LandSat-8 imageries are evaluated in terms of horizontal scalability.

  20. Quantitative metrics for assessment of chemical image quality and spatial resolution.

    Science.gov (United States)

    Kertesz, Vilmos; Cahill, John F; Van Berkel, Gary J

    2016-04-15

    Currently objective/quantitative descriptions of the quality and spatial resolution of mass spectrometry derived chemical images are not standardized. Development of these standardized metrics is required to objectively describe the chemical imaging capabilities of existing and/or new mass spectrometry imaging technologies. Such metrics would allow unbiased judgment of intra-laboratory advancement and/or inter-laboratory comparison for these technologies if used together with standardized surfaces. Two image metrics, viz., "chemical image contrast" (ChemIC) based on signal-to-noise related statistical measures on chemical image pixels and "corrected resolving power factor" (cRPF) constructed from statistical analysis of mass-to-charge chronograms across features of interest in an image, were developed. These metrics, quantifying chemical image quality and spatial resolution, respectively, were used to evaluate chemical images of a model photoresist patterned surface collected using a laser ablation/liquid vortex capture mass spectrometry imaging system under different instrument operational parameters. The calculated ChemIC and cRPF metrics determined in an unbiased fashion the relative ranking of chemical image quality obtained with the laser ablation/liquid vortex capture mass spectrometry imaging system. These rankings were used to show that both chemical image contrast and spatial resolution deteriorated with increasing surface scan speed, increased lane spacing and decreasing size of surface features. ChemIC and cRPF, respectively, were developed and successfully applied for the objective description of chemical image quality and spatial resolution of chemical images collected from model surfaces using a laser ablation/liquid vortex capture mass spectrometry imaging system. Published in 2016. This article is a U.S. Government work and is in the public domain in the USA. Published in 2016. This article is a U.S. Government work and is in the public domain in

  1. High spatial and temporal resolution interrogation of fully distributed chirped fiber Bragg grating sensors

    OpenAIRE

    Ahmad, Eamonn J.; Wang, Chao; Feng, Dejun; Yan, Zhijun; Zhang, Lin

    2017-01-01

    A novel interrogation technique for fully distributed linearly chirped fiber Bragg grating (LCFBG) strain sensors with simultaneous high temporal and spatial resolution based on optical time-stretch frequency-domain reflectometry (OTS-FDR) is proposed and experimentally demonstrated. LCFBGs is a promising candidate for fully distributed sensors thanks to its longer grating length and broader reflection bandwidth compared to normal uniform FBGs. In the proposed system, two identical LCFBGs are...

  2. Echo planar perfusion imaging with high spatial and temporal resolution: methodology and clinical aspects

    International Nuclear Information System (INIS)

    Bitzer, M.; Klose, U.; Naegele, T.; Friese, S.; Kuntz, R.; Voigt, K.; Fetter, M.; Opitz, H.

    1999-01-01

    The purpose of the present study was to analyse specific advantages of calculated parameter images and their limitations using an optimized echo-planar imaging (EPI) technique with high spatial and temporal resolution. Dynamic susceptibility contrast magnetic resonance imaging (DSC-MRI) was performed in 12 patients with cerebrovascular disease and in 13 patients with brain tumours. For MR imaging of cerebral perfusion an EPI sequence was developed which provides a temporal resolution of 0.68 s for three slices with a 128 x 128 image matrix. To evaluate DSC-MRI, the following parameter images were calculated pixelwise: (1) Maximum signal reduction (MSR); (2) maximum signal difference (ΔSR); (3) time-to-peak (T p ); and (4) integral of signal-intensity-time curve until T p (S Int ). The MSR maps were superior in the detection of acute infarctions and ΔSR maps in the delineation of vasogenic brain oedema. The time-to-peak (T p ) maps seemed to be highly sensitive in the detection of poststenotic malperfused brain areas (sensitivity 90 %). Hyperperfused areas of brain tumours were detectable down to a diameter of 1 cm with high sensitivity (> 90 %). Distinct clinical and neuroradiological conditions revealed different suitabilities for the parameter images. The time-to-peak (T p ) maps may be an important advantage in the detection of poststenotic ''areas at risk'', due to an improved temporal resolution using an EPI technique. With regard to spatial resolution, a matrix size of 128 x 128 is sufficient for all clinical conditions. According to our results, a further increase in matrix size would not improve the spatial resolution in DSC-MRI, since the degree of the vascularization of lesions and the susceptibility effect itself seem to be the limiting factors. (orig.)

  3. Influence of Elevation Data Resolution on Spatial Prediction of Colluvial Soils in a Luvisol Region.

    Directory of Open Access Journals (Sweden)

    Vít Penížek

    Full Text Available The development of a soil cover is a dynamic process. Soil cover can be altered within a few decades, which requires updating of the legacy soil maps. Soil erosion is one of the most important processes quickly altering soil cover on agriculture land. Colluvial soils develop in concave parts of the landscape as a consequence of sedimentation of eroded material. Colluvial soils are recognised as important soil units because they are a vast sink of soil organic carbon. Terrain derivatives became an important tool in digital soil mapping and are among the most popular auxiliary data used for quantitative spatial prediction. Prediction success rates are often directly dependent on raster resolution. In our study, we tested how raster resolution (1, 2, 3, 5, 10, 20 and 30 meters influences spatial prediction of colluvial soils. Terrain derivatives (altitude, slope, plane curvature, topographic position index, LS factor and convergence index were calculated for the given raster resolutions. Four models were applied (boosted tree, neural network, random forest and Classification/Regression Tree to spatially predict the soil cover over a 77 ha large study plot. Models training and validation was based on 111 soil profiles surveyed on a regular sampling grid. Moreover, the predicted real extent and shape of the colluvial soil area was examined. In general, no clear trend in the accuracy prediction was found without the given raster resolution range. Higher maximum prediction accuracy for colluvial soil, compared to prediction accuracy of total soil cover of the study plot, can be explained by the choice of terrain derivatives that were best for Colluvial soils differentiation from other soil units. Regarding the character of the predicted Colluvial soils area, maps of 2 to 10 m resolution provided reasonable delineation of the colluvial soil as part of the cover over the study area.

  4. When does higher spatial resolution rainfall information improve streamflow simulation? An evaluation on 3620 flood events

    Science.gov (United States)

    Lobligeois, F.; Andréassian, V.; Perrin, C.; Tabary, P.; Loumagne, C.

    2013-10-01

    Precipitation is the key factor controlling the high-frequency hydrological response in catchments, and streamflow simulation is thus dependent on the way rainfall is represented in the hydrological model. A characteristic that distinguishes distributed from lumped models is the ability to explicitly represent the spatial variability of precipitation. Although the literature on this topic is abundant, the results are contrasted and sometimes contradictory. This paper investigates the impact of spatial rainfall on runoff generation to better understand the conditions where higher-resolution rainfall information improves streamflow simulations. In this study, we used the rainfall reanalysis developed by Météo-France over the whole French territory at 1 km and 1 h resolution over a 10 yr period. A hydrological model was applied in the lumped mode (a single spatial unit) and in the semi-distributed mode using three unit sizes of sub-catchments. The model was evaluated against observed streamflow data using split-sample tests on a large set of 181 French catchments representing a variety of size and climate conditions. The results were analyzed by catchment classes and types of rainfall events based on the spatial variability of precipitation. The evaluation clearly showed different behaviors. The lumped model performed as well as the semi-distributed model in western France where catchments are under oceanic climate conditions with quite spatially uniform precipitation fields. In contrast, higher resolution in precipitation inputs significantly improved the simulated streamflow dynamics and accuracy in southern France (Cévennes and Mediterranean regions) for catchments in which precipitation fields were identified to be highly variable in space. In all regions, natural variability allows for contradictory examples to be found, showing that analyzing a large number of events over varied catchments is warranted.

  5. When does higher spatial resolution rainfall information improve streamflow simulation? An evaluation using 3620 flood events

    Science.gov (United States)

    Lobligeois, F.; Andréassian, V.; Perrin, C.; Tabary, P.; Loumagne, C.

    2014-02-01

    Precipitation is the key factor controlling the high-frequency hydrological response in catchments, and streamflow simulation is thus dependent on the way rainfall is represented in a hydrological model. A characteristic that distinguishes distributed from lumped models is the ability to explicitly represent the spatial variability of precipitation. Although the literature on this topic is abundant, the results are contrasting and sometimes contradictory. This paper investigates the impact of spatial rainfall on runoff generation to better understand the conditions where higher-resolution rainfall information improves streamflow simulations. In this study, we used the rainfall reanalysis developed by Météo-France over the whole country of France at 1 km and 1 h resolution over a 10 yr period. A hydrological model was applied in the lumped mode (a single spatial unit) and in the semidistributed mode using three unit sizes of subcatchments. The model was evaluated against observed streamflow data using split-sample tests on a large set of French catchments (181) representing a variety of sizes and climate conditions. The results were analyzed by catchment classes and types of rainfall events based on the spatial variability of precipitation. The evaluation clearly showed different behaviors. The lumped model performed as well as the semidistributed model in western France, where catchments are under oceanic climate conditions with quite spatially uniform precipitation fields. By contrast, higher resolution in precipitation inputs significantly improved the simulated streamflow dynamics and accuracy in southern France (Cévennes and Mediterranean regions) for catchments in which precipitation fields were identified to be highly variable in space. In all regions, natural variability allows for contradictory examples to be found, showing that analyzing a large number of events over varied catchments is warranted.

  6. DEM GENERATION FROM HIGH RESOLUTION SATELLITE IMAGES THROUGH A NEW 3D LEAST SQUARES MATCHING ALGORITHM

    Directory of Open Access Journals (Sweden)

    T. Kim

    2012-09-01

    Full Text Available Automated generation of digital elevation models (DEMs from high resolution satellite images (HRSIs has been an active research topic for many years. However, stereo matching of HRSIs, in particular based on image-space search, is still difficult due to occlusions and building facades within them. Object-space matching schemes, proposed to overcome these problem, often are very time consuming and critical to the dimensions of voxels. In this paper, we tried a new least square matching (LSM algorithm that works in a 3D object space. The algorithm starts with an initial height value on one location of the object space. From this 3D point, the left and right image points are projected. The true height is calculated by iterative least squares estimation based on the grey level differences between the left and right patches centred on the projected left and right points. We tested the 3D LSM to the Worldview images over 'Terrassa Sud' provided by the ISPRS WG I/4. We also compared the performance of the 3D LSM with the correlation matching based on 2D image space and the correlation matching based on 3D object space. The accuracy of the DEM from each method was analysed against the ground truth. Test results showed that 3D LSM offers more accurate DEMs over the conventional matching algorithms. Results also showed that 3D LSM is sensitive to the accuracy of initial height value to start the estimation. We combined the 3D COM and 3D LSM for accurate and robust DEM generation from HRSIs. The major contribution of this paper is that we proposed and validated that LSM can be applied to object space and that the combination of 3D correlation and 3D LSM can be a good solution for automated DEM generation from HRSIs.

  7. High spatial resolution distributed fiber system for multi-parameter sensing based on modulated pulses.

    Science.gov (United States)

    Zhang, Jingdong; Zhu, Tao; Zhou, Huan; Huang, Shihong; Liu, Min; Huang, Wei

    2016-11-28

    We demonstrate a cost-effective distributed fiber sensing system for the multi-parameter detection of the vibration, the temperature, and the strain by integrating phase-sensitive optical time domain reflectometry (φ-OTDR) and Brillouin optical time domain reflectometry (B-OTDR). Taking advantage of the fast changing property of the vibration and the static properties of the temperature and the strain, both the width and intensity of the laser pulses are modulated and injected into the single-mode sensing fiber proportionally, so that three concerned parameters can be extracted simultaneously by only one photo-detector and one data acquisition channel. A data processing method based on Gaussian window short time Fourier transform (G-STFT) is capable of achieving high spatial resolution in B-OTDR. The experimental results show that up to 4.8kHz vibration sensing with 3m spatial resolution at 10km standard single-mode fiber can be realized, as well as the distributed temperature and stress profiles along the same fiber with 80cm spatial resolution.

  8. Hyperspectral Image Spatial Super-Resolution via 3D Full Convolutional Neural Network

    Directory of Open Access Journals (Sweden)

    Shaohui Mei

    2017-11-01

    Full Text Available Hyperspectral images are well-known for their fine spectral resolution to discriminate different materials. However, their spatial resolution is relatively low due to the trade-off in imaging sensor technologies, resulting in limitations in their applications. Inspired by recent achievements in convolutional neural network (CNN based super-resolution (SR for natural images, a novel three-dimensional full CNN (3D-FCNN is constructed for spatial SR of hyperspectral images in this paper. Specifically, 3D convolution is used to exploit both the spatial context of neighboring pixels and spectral correlation of neighboring bands, such that spectral distortion when directly applying traditional CNN based SR algorithms to hyperspectral images in band-wise manners is alleviated. Furthermore, a sensor-specific mode is designed for the proposed 3D-FCNN such that none of the samples from the target scene are required for training. Fine-tuning by a small number of training samples from the target scene can further improve the performance of such a sensor-specific method. Extensive experimental results on four benchmark datasets from two well-known hyperspectral sensors, namely hyperspectral digital imagery collection experiment (HYDICE and reflective optics system imaging spectrometer (ROSIS sensors, demonstrate that our proposed 3D-FCNN outperforms several existing SR methods by ensuring higher quality both in reconstruction and spectral fidelity.

  9. Mapping the layer count of few-layer hexagonal boron nitride at high lateral spatial resolutions

    Science.gov (United States)

    Mohsin, Ali; Cross, Nicholas G.; Liu, Lei; Watanabe, Kenji; Taniguchi, Takashi; Duscher, Gerd; Gu, Gong

    2018-01-01

    Layer count control and uniformity of two dimensional (2D) layered materials are critical to the investigation of their properties and to their electronic device applications, but methods to map 2D material layer count at nanometer-level lateral spatial resolutions have been lacking. Here, we demonstrate a method based on two complementary techniques widely available in transmission electron microscopes (TEMs) to map the layer count of multilayer hexagonal boron nitride (h-BN) films. The mass-thickness contrast in high-angle annular dark-field (HAADF) imaging in the scanning transmission electron microscope (STEM) mode allows for thickness determination in atomically clean regions with high spatial resolution (sub-nanometer), but is limited by surface contamination. To complement, another technique based on the boron K ionization edge in the electron energy loss spectroscopy spectrum (EELS) of h-BN is developed to quantify the layer count so that surface contamination does not cause an overestimate, albeit at a lower spatial resolution (nanometers). The two techniques agree remarkably well in atomically clean regions with discrepancies within  ±1 layer. For the first time, the layer count uniformity on the scale of nanometers is quantified for a 2D material. The methodology is applicable to layer count mapping of other 2D layered materials, paving the way toward the synthesis of multilayer 2D materials with homogeneous layer count.

  10. Study and design of a very high spatial resolution beta imaging system

    International Nuclear Information System (INIS)

    Donnard, J.

    2008-01-01

    The b autoradiography is a widely used technique in pharmacology or biological fields. It is able to locate in two dimensions molecules labeled with beta emitters. The development of a gaseous detector incorporating micro-mesh called PIM in the Subatech laboratory leads to the construction of a very high spatial resolution apparatus dedicated to b imaging. This device is devoted to small analysis surface of a half microscope slide in particular of 3 H or 14 C and the measured spatial resolution is 20 μm FWHM. The recent development of a new reconstruction method allows enlarging the field of investigation to high energy beta emitters such as 131 I, 18 F or 46 Sc. A new device with a large active area of 18*18 cm 2 has been built with a user friendly design. This allows to image simultaneously 10 microscope slides. Thanks to a multi-modality solution, it retains the good characteristics of spatial resolution obtained previously on a small surface. Moreover, different kinds of samples, like microscope slides or scotches can be analysed. The simulation and experimentation work achieved during this thesis led to an optimal disposition of the inner structure of the detector. These results and characterization show that the PIM structure has to be considered for a next generation of b-Imager. (author)

  11. Fourier transform infrared absorption spectroscopy characterization of gaseous atmospheric pressure plasmas with 2 mm spatial resolution

    Energy Technology Data Exchange (ETDEWEB)

    Laroche, G. [Laboratoire d' Ingenierie de Surface, Centre de Recherche sur les Materiaux Avances, Departement de genie des mines, de la metallurgie et des materiaux, Universite Laval, 1065, avenue de la Medecine, Quebec G1V 0A6 (Canada); Centre de recherche du CHUQ, Hopital St Francois d' Assise, 10, rue de l' Espinay, local E0-165, Quebec G1L 3L5 (Canada); Vallade, J. [Laboratoire Procedes, Materiaux et Energie Solaire, PROMES, CNRS, Technosud, Rambla de la Thermodynamique, F-66100 Perpignan (France); Agence de l' environnement et de la Ma Latin-Small-Letter-Dotless-I -carettrise de l' Energie, 20, avenue du Gresille, BP 90406, F-49004 Angers Cedex 01 (France); Bazinette, R.; Hernandez, E.; Hernandez, G.; Massines, F. [Laboratoire Procedes, Materiaux et Energie Solaire, PROMES, CNRS, Technosud, Rambla de la Thermodynamique, F-66100 Perpignan (France); Nijnatten, P. van [OMT Solutions bv, High Tech Campus 9, 5656AE Eindhoven (Netherlands)

    2012-10-15

    This paper describes an optical setup built to record Fourier transform infrared (FTIR) absorption spectra in an atmospheric pressure plasma with a spatial resolution of 2 mm. The overall system consisted of three basic parts: (1) optical components located within the FTIR sample compartment, making it possible to define the size of the infrared beam (2 mm Multiplication-Sign 2 mm over a path length of 50 mm) imaged at the site of the plasma by (2) an optical interface positioned between the spectrometer and the plasma reactor. Once through the plasma region, (3) a retro-reflector module, located behind the plasma reactor, redirected the infrared beam coincident to the incident path up to a 45 Degree-Sign beamsplitter to reflect the beam toward a narrow-band mercury-cadmium-telluride detector. The antireflective plasma-coating experiments performed with ammonia and silane demonstrated that it was possible to quantify 42 and 2 ppm of these species in argon, respectively. In the case of ammonia, this was approximately three times less than this gas concentration typically used in plasma coating experiments while the silane limit of quantification was 35 times lower. Moreover, 70% of the incoming infrared radiation was focused within a 2 mm width at the site of the plasma, in reasonable agreement with the expected spatial resolution. The possibility of reaching this spatial resolution thus enabled us to measure the gaseous precursor consumption as a function of their residence time in the plasma.

  12. Theoretical limit of spatial resolution in diffuse optical tomography using a perturbation model

    International Nuclear Information System (INIS)

    Konovalov, A B; Vlasov, V V

    2014-01-01

    We have assessed the limit of spatial resolution of timedomain diffuse optical tomography (DOT) based on a perturbation reconstruction model. From the viewpoint of the structure reconstruction accuracy, three different approaches to solving the inverse DOT problem are compared. The first approach involves reconstruction of diffuse tomograms from straight lines, the second – from average curvilinear trajectories of photons and the third – from total banana-shaped distributions of photon trajectories. In order to obtain estimates of resolution, we have derived analytical expressions for the point spread function and modulation transfer function, as well as have performed a numerical experiment on reconstruction of rectangular scattering objects with circular absorbing inhomogeneities. It is shown that in passing from reconstruction from straight lines to reconstruction using distributions of photon trajectories we can improve resolution by almost an order of magnitude and exceed the accuracy of reconstruction of multi-step algorithms used in DOT. (optical tomography)

  13. Beyond spicule dynamics: spicule and fibril spectroscopy at high spatial and temporal resolution

    Science.gov (United States)

    Mendes Domingos Pereira, T.; Rouppe van der Voort, L.

    2015-12-01

    Solar spicules are chromospheric fibrils observed at the solar limb. They are observed everywhere in the Sun, but their origin is not yet understood. Much of our understanding of spicules has been obtained through filtergram observations and/or focused on the dynamics of spicules. Spectroscopic studies have been usually limited by spatial extent/resolution, temporal resolution, or variable seeing. In this work we make use of a unique time series of imaging spectroscopy at high spatial and temporal resolution, obtained with the Swedish Solar Telescope under excellent seeing and coordinated with the IRIS mission. With these data we characterize the evolution of spectra along quiet Sun fibrils and spicules, and discuss what makes them visible in filtergrams and sets them apart from other chromospheric fibrils. With combined H-alpha and Ca II H high-resolution observations we also discuss how spicules appear in these two lines, a long standing issue that has been interpreted in conflicting ways. Finally, using the wide range of IRIS diagnostics we put together the spectral evolution of spicules through the chromosphere and transition region.

  14. DETECTION OF THE VELOCITY SHEAR EFFECT ON THE SPATIAL DISTRIBUTIONS OF THE GALACTIC SATELLITES IN ISOLATED SYSTEMS

    International Nuclear Information System (INIS)

    Lee, Jounghun; Choi, Yun-Young

    2015-01-01

    We report a detection of the effect of the large-scale velocity shear on the spatial distributions of the galactic satellites around the isolated hosts. Identifying the isolated galactic systems, each of which consists of a single host galaxy and its satellites, from the Seventh Data Release of the Sloan Digital Sky Survey and reconstructing linearly the velocity shear field in the local universe, we measure the alignments between the relative positions of the satellites from their isolated hosts and the principal axes of the local velocity shear tensors projected onto the plane of sky. We find a clear signal that the galactic satellites in isolated systems are located preferentially along the directions of the minor principal axes of the large-scale velocity shear field. Those galactic satellites that are spirals, are brighter, are located at distances larger than the projected virial radii of the hosts, and belong to the spiral hosts yield stronger alignment signals, which implies that the alignment strength depends on the formation and accretion epochs of the galactic satellites. It is also shown that the alignment strength is quite insensitive to the cosmic web environment, as well as the size and luminosity of the isolated hosts. Although this result is consistent with the numerical finding of Libeskind et al. based on an N-body experiment, owing to the very low significance of the observed signals, it remains inconclusive whether or not the velocity shear effect on the satellite distribution is truly universal

  15. Combining satellite data and appropriate objective functions for improved spatial pattern performance of a distributed hydrologic model

    Directory of Open Access Journals (Sweden)

    M. C. Demirel

    2018-02-01

    Full Text Available Satellite-based earth observations offer great opportunities to improve spatial model predictions by means of spatial-pattern-oriented model evaluations. In this study, observed spatial patterns of actual evapotranspiration (AET are utilised for spatial model calibration tailored to target the pattern performance of the model. The proposed calibration framework combines temporally aggregated observed spatial patterns with a new spatial performance metric and a flexible spatial parameterisation scheme. The mesoscale hydrologic model (mHM is used to simulate streamflow and AET and has been selected due to its soil parameter distribution approach based on pedo-transfer functions and the build in multi-scale parameter regionalisation. In addition two new spatial parameter distribution options have been incorporated in the model in order to increase the flexibility of root fraction coefficient and potential evapotranspiration correction parameterisations, based on soil type and vegetation density. These parameterisations are utilised as they are most relevant for simulated AET patterns from the hydrologic model. Due to the fundamental challenges encountered when evaluating spatial pattern performance using standard metrics, we developed a simple but highly discriminative spatial metric, i.e. one comprised of three easily interpretable components measuring co-location, variation and distribution of the spatial data. The study shows that with flexible spatial model parameterisation used in combination with the appropriate objective functions, the simulated spatial patterns of actual evapotranspiration become substantially more similar to the satellite-based estimates. Overall 26 parameters are identified for calibration through a sequential screening approach based on a combination of streamflow and spatial pattern metrics. The robustness of the calibrations is tested using an ensemble of nine calibrations based on different seed numbers using the

  16. Combining satellite data and appropriate objective functions for improved spatial pattern performance of a distributed hydrologic model

    Science.gov (United States)

    Demirel, Mehmet C.; Mai, Juliane; Mendiguren, Gorka; Koch, Julian; Samaniego, Luis; Stisen, Simon

    2018-02-01

    Satellite-based earth observations offer great opportunities to improve spatial model predictions by means of spatial-pattern-oriented model evaluations. In this study, observed spatial patterns of actual evapotranspiration (AET) are utilised for spatial model calibration tailored to target the pattern performance of the model. The proposed calibration framework combines temporally aggregated observed spatial patterns with a new spatial performance metric and a flexible spatial parameterisation scheme. The mesoscale hydrologic model (mHM) is used to simulate streamflow and AET and has been selected due to its soil parameter distribution approach based on pedo-transfer functions and the build in multi-scale parameter regionalisation. In addition two new spatial parameter distribution options have been incorporated in the model in order to increase the flexibility of root fraction coefficient and potential evapotranspiration correction parameterisations, based on soil type and vegetation density. These parameterisations are utilised as they are most relevant for simulated AET patterns from the hydrologic model. Due to the fundamental challenges encountered when evaluating spatial pattern performance using standard metrics, we developed a simple but highly discriminative spatial metric, i.e. one comprised of three easily interpretable components measuring co-location, variation and distribution of the spatial data. The study shows that with flexible spatial model parameterisation used in combination with the appropriate objective functions, the simulated spatial patterns of actual evapotranspiration become substantially more similar to the satellite-based estimates. Overall 26 parameters are identified for calibration through a sequential screening approach based on a combination of streamflow and spatial pattern metrics. The robustness of the calibrations is tested using an ensemble of nine calibrations based on different seed numbers using the shuffled complex

  17. Predicting bird phenology from space: satellite-derived vegetation green-up signal uncovers spatial variation in phenological synchrony between birds and their environment.

    Science.gov (United States)

    Cole, Ella F; Long, Peter R; Zelazowski, Przemyslaw; Szulkin, Marta; Sheldon, Ben C

    2015-11-01

    Population-level studies of how tit species (Parus spp.) track the changing phenology of their caterpillar food source have provided a model system allowing inference into how populations can adjust to changing climates, but are often limited because they implicitly assume all individuals experience similar environments. Ecologists are increasingly using satellite-derived data to quantify aspects of animals' environments, but so far studies examining phenology have generally done so at large spatial scales. Considering the scale at which individuals experience their environment is likely to be key if we are to understand the ecological and evolutionary processes acting on reproductive phenology within populations. Here, we use time series of satellite images, with a resolution of 240 m, to quantify spatial variation in vegetation green-up for a 385-ha mixed-deciduous woodland. Using data spanning 13 years, we demonstrate that annual population-level measures of the timing of peak abundance of winter moth larvae (Operophtera brumata) and the timing of egg laying in great tits (Parus major) and blue tits (Cyanistes caeruleus) is related to satellite-derived spring vegetation phenology. We go on to show that timing of local vegetation green-up significantly explained individual differences in tit reproductive phenology within the population, and that the degree of synchrony between bird and vegetation phenology showed marked spatial variation across the woodland. Areas of high oak tree (Quercus robur) and hazel (Corylus avellana) density showed the strongest match between remote-sensed vegetation phenology and reproductive phenology in both species. Marked within-population variation in the extent to which phenology of different trophic levels match suggests that more attention should be given to small-scale processes when exploring the causes and consequences of phenological matching. We discuss how use of remotely sensed data to study within-population variation

  18. Dynamics in mangroves assessed by high-resolution and multi-temporal satellite data: a case study in Zhanjiang Mangrove National Nature Reserve (ZMNNR, P. R. China

    Directory of Open Access Journals (Sweden)

    K. Leempoel

    2013-08-01

    Full Text Available Mangrove forests are declining across the globe, mainly because of human intervention, and therefore require an evaluation of their past and present status (e.g. areal extent, species-level distribution, etc. to implement better conservation and management strategies. In this paper, mangrove cover dynamics at Gaoqiao (P. R. China were assessed through time using 1967, 2000 and 2009 satellite imagery (sensors Corona KH-4B, Landsat ETM+, GeoEye-1 respectively. Firstly, multi-temporal analysis of satellite data was undertaken, and secondly biotic and abiotic differences were analysed between the different mangrove stands, assessed through a supervised classification of a high-resolution satellite image. A major decline in mangrove cover (−36% was observed between 1967 and 2009 due to rice cultivation and aquaculture practices. Moreover, dike construction has prevented mangroves from expanding landward. Although a small increase of mangrove area was observed between 2000 and 2009 (+24%, the ratio mangrove / aquaculture kept decreasing due to increased aquaculture at the expense of rice cultivation in the vicinity. From the land-use/cover map based on ground-truth data (5 × 5 m plot-based tree measurements (August–September, 2009 as well as spectral reflectance values (obtained from pansharpened GeoEye-1, both Bruguiera gymnorrhiza and small Aegiceras corniculatum are distinguishable at 73–100% accuracy, whereas tall A. corniculatum was correctly classified at only 53% due to its mixed vegetation stands with B. gymnorrhiza (overall classification accuracy: 85%. In the case of sediments, sand proportion was significantly different between the three mangrove classes. Overall, the advantage of very high resolution satellite images like GeoEye-1 (0.5 m for mangrove spatial heterogeneity assessment and/or species-level discrimination was well demonstrated, along with the complexity to provide a precise classification for non-dominant species (e

  19. Spatial resolution dependence on spectral frequency in human speech cortex electrocorticography

    Science.gov (United States)

    Muller, Leah; Hamilton, Liberty S.; Edwards, Erik; Bouchard, Kristofer E.; Chang, Edward F.

    2016-10-01

    Objective. Electrocorticography (ECoG) has become an important tool in human neuroscience and has tremendous potential for emerging applications in neural interface technology. Electrode array design parameters are outstanding issues for both research and clinical applications, and these parameters depend critically on the nature of the neural signals to be recorded. Here, we investigate the functional spatial resolution of neural signals recorded at the human cortical surface. We empirically derive spatial spread functions to quantify the shared neural activity for each frequency band of the electrocorticogram. Approach. Five subjects with high-density (4 mm center-to-center spacing) ECoG grid implants participated in speech perception and production tasks while neural activity was recorded from the speech cortex, including superior temporal gyrus, precentral gyrus, and postcentral gyrus. The cortical surface field potential was decomposed into traditional EEG frequency bands. Signal similarity between electrode pairs for each frequency band was quantified using a Pearson correlation coefficient. Main results. The correlation of neural activity between electrode pairs was inversely related to the distance between the electrodes; this relationship was used to quantify spatial falloff functions for cortical subdomains. As expected, lower frequencies remained correlated over larger distances than higher frequencies. However, both the envelope and phase of gamma and high gamma frequencies (30-150 Hz) are largely uncorrelated (<90%) at 4 mm, the smallest spacing of the high-density arrays. Thus, ECoG arrays smaller than 4 mm have significant promise for increasing signal resolution at high frequencies, whereas less additional gain is achieved for lower frequencies. Significance. Our findings quantitatively demonstrate the dependence of ECoG spatial resolution on the neural frequency of interest. We demonstrate that this relationship is consistent across patients and

  20. Integration of Ground and Multi-Resolution Satellite Data for Predicting the Water Balance of a Mediterranean Two-Layer Agro-Ecosystem

    Directory of Open Access Journals (Sweden)

    Piero Battista

    2016-09-01

    Full Text Available The estimation of site water budget is important in Mediterranean areas, where it represents a crucial factor affecting the quantity and quality of traditional crop production. This is particularly the case for spatially fragmented, multi-layer agricultural ecosystems such as olive groves, which are traditional cultivations of the Mediterranean basin. The current paper aims at demonstrating the effectiveness of spatialized meteorological data and remote sensing techniques to estimate the actual evapotranspiration (ETA and the soil water content (SWC of an olive orchard in Central Italy. The relatively small size of this orchard (about 0.1 ha and its two-layer structure (i.e., olive trees and grasses require the integration of remotely sensed data with different spatial and temporal resolutions (Terra-MODIS, Landsat 8-OLI and Ikonos. These data are used to drive a recently proposed water balance method (NDVI-Cws and predict ETA and then site SWC, which are assessed through comparison with sap flow and soil wetness measurements taken in 2013. The results obtained indicate the importance of integrating satellite imageries having different spatio-temporal properties in order to properly characterize the examined olive orchard. More generally, the experimental evidences support the possibility of using widely available remotely sensed and ancillary datasets for the operational estimation of ETA and SWC in olive tree cultivation systems.

  1. Identification and Quantification of Tree Species in Open Mixed Forests using High Resolution QuickBird Satellite Imagery

    Directory of Open Access Journals (Sweden)

    S Arockiaraj

    2015-12-01

    Full Text Available Present study deals with identification and quantification of tree species within an open mixed forest in parts of Ranchi district Jharkhand, India using high resolution QuickBird satellite data using image processing and GIS techniques. A high resolution QuickBird satellite image was used for shadow enhancement and tree crown area extraction. The First Principal Component of QuickBird satellite images was employed to enhance the shadowed area and subsequently shadow and non-shadow area were classified using ISODATA. The satellite image was used for crown area extraction with standard deviation of NDVI value and the crowns were classified into five classes using Maximum Likelihood supervised algorithm. Result shows that barring few limitation, the high resolution QuickBird image provides rapid and accurate results in terms of identification and quantification of tree species in conjugation with field verification and attained 88% of classification accuracy. It reduces the time required for obtaining inventory data in open mixed forest. Results also showed that total 5,522 trees of various species were present in the study area and dominated by Shorea robusta (80.48% followed by Ziziphus mauritiana (16.26%, unknown tree (1.81%, Ficus religiosa (0.98% and Mangifera indica (0.47%. The demography patterns of the locals mainly tribal (89.9% exhibited their direct as well as indirect dependency on mixed forests resources for their subsistence and livelihood. The study necessitate towards the effective implication of policies to raise the standard of living of tribal people in the region.

  2. Integrating Landsat-8, Sentinel-2, and nano-satellite data for deriving atmospherically corrected vegetation indices at enhanced spatio-temporal resolution

    Science.gov (United States)

    Houborg, Rasmus; McCabe, Matthew F.; Ershadi, Ali

    2017-04-01

    Flocks of nano-satellites are emerging as an economic resource for overcoming spatio-temporal constraints of conventional single-sensor satellite missions. Planet Labs operates an expanding constellation of currently more than 40 CubeSats (30x10x10 cm3), which will facilitate daily capture of broadband RGB and near-infrared (NIR) imagery for every location on earth at a 3-5 m ground sampling distance. However, data acquired by these miniaturized satellites lack rigorous radiometric corrections and radiance conversions and should be used in synergy with high quality imagery required by conventional large satellites such as Landsat-8 (L8) and Sentinel-2 (S2) in order to realize the full potential of this game changing observational resource. This study integrates L8, S2 and Planet data acquired over sites in Saudi Arabia and the state of California for deriving cross-sensor consistent and atmospherically corrected Vegetation Indices (VI) that may serve as important metrics for vegetation growth, health, and productivity. An automated framework, based on 6S and satellite retrieved atmospheric state and aerosol inputs, is first applied to L8 and S2 at-sensor radiances for the production of atmospherically corrected VIs. Scale-consistent Planet RGB and NIR imagery is then related to the corrected VI data using a selective, scene-specific, and computationally fast machine learning approach. The developed technique uses the closest pair of Planet and L8/S2 scenes in the training of the predictive VI models and accounts for changes in cover conditions over the acquisition timespan. Application of the models to full resolution Planet imagery results in cross-sensor consistent VI estimates at the scale and time of the nano-satellite acquisition. The utility of the approach for reproducing spatial features in L8 and S2 based indices based on Planet imagery is evaluated. The technique is generic, computationally efficient, and extendable and serves well for implementation

  3. Laser ablation isotope ratio mass spectrometry for enhanced sensitivity and spatial resolution in stable isotope analysis.

    Science.gov (United States)

    Moran, James J; Newburn, Matt K; Alexander, M Lizabeth; Sams, Robert L; Kelly, James F; Kreuzer, Helen W

    2011-05-15

    Stable isotope analysis permits the tracking of physical, chemical, and biological reactions and source materials at a wide variety of spatial scales. We present a laser ablation isotope ratio mass spectrometry (LA-IRMS) method that enables δ(13)C measurement of solid samples at 50 µm spatial resolution. The method does not require sample pre-treatment to physically separate spatial zones. We use laser ablation of solid samples followed by quantitative combustion of the ablated particulates to convert sample carbon into CO(2). Cryofocusing of the resulting CO(2) coupled with modulation in the carrier flow rate permits coherent peak introduction into an isotope ratio mass spectrometer, with only 65 ng carbon required per measurement. We conclusively demonstrate that the measured CO(2) is produced by combustion of laser-ablated aerosols from the sample surface. We measured δ(13)C for a series of solid compounds using laser ablation and traditional solid sample analysis techniques. Both techniques produced consistent isotopic results but the laser ablation method required over two orders of magnitude less sample. We demonstrated that LA-IRMS sensitivity coupled with its 50 µm spatial resolution could be used to measure δ(13) C values along a length of hair, making multiple sample measurements over distances corresponding to a single day's growth. This method will be highly valuable in cases where the δ(13)C analysis of small samples over prescribed spatial distances is required. Suitable applications include forensic analysis of hair samples, investigations of tightly woven microbial systems, and cases of surface analysis where there is a sharp delineation between different components of a sample. Copyright © 2011 John Wiley & Sons, Ltd.

  4. Sub-3mm spatial resolution from a large monolithic LaBr3 (Ce scintillator

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    Liprandi Silvia

    2017-09-01

    Full Text Available A Compton camera prototype for ion beam range monitoring via prompt (< 1 ns gamma detection in hadron therapy is being developed and characterized at the Medical Physics Department of LMU Munich. The system consists of a large (50x50x30 mm3 monolithic LaBr3(Ce scintillation crystal as absorber component to detect the multi-MeV Compton scattered photons, together with a stack of 6 double-sided silicon strip detectors (DSSSD acting as scatterer component. Key ingredient of the γ-source reconstruction is the determination of the γ-ray interaction position in the scintillator, which is read out by a 256-fold segmented multi-anode photomultiplier tube (PMT. From simulations an angular resolution of about 1.5o for the photon source reconstruction can be expected for the energy range around 3 – 5 MeV, provided that a spatial resolution of 3 mm can be reached in the absorbing scintillator [1]. Therefore, particular effort was dedicated to characterize this latter property as a function of the γ-ray energy. Intense, tightly collimated 137Cs and 60Co photon sources were used for 2D irradiation scans (step size 0.5 mm as prerequisite for studying the performance of the “k-Nearest-Neighbors” algorithm developed at TU Delft [2] (together with its variant ”Categorical Average Pattern”, CAP and extending its applicability into the energy range beyond the original 511 keV. In this paper we present our most recent interaction position analysis in the absorbing scintillator, leading to a considerably improved value for the spatial resolution: systematic studies were performed as a function of the k-NN parameters and the PMT segmentation. A trend of improving spatial resolution with increasing photon energy was confirmed, resulting in the realization of the presently optimum spatial resolution of 2.9(1 mm @1.3 MeV, thus reaching the design specifications of the Compton camera absorber. The specification goal was reached also for a reduced PMT

  5. High spatial resolution quantitative MR images: an experimental study of dedicated surface coils

    International Nuclear Information System (INIS)

    Gensanne, D; Josse, G; Lagarde, J M; Vincensini, D

    2006-01-01

    Measuring spin-spin relaxation times (T 2 ) by quantitative MR imaging represents a potentially efficient tool to evaluate the physicochemical properties of various media. However, noise in MR images is responsible for uncertainties in the determination of T 2 relaxation times, which limits the accuracy of parametric tissue analysis. The required signal-to-noise ratio (SNR) depends on the T 2 relaxation behaviour specific to each tissue. Thus, we have previously shown that keeping the uncertainty in T 2 measurements within a limit of 10% implies that SNR values be greater than 100 and 300 for mono- and biexponential T 2 relaxation behaviours, respectively. Noise reduction can be obtained either by increasing the voxel size (i.e., at the expense of spatial resolution) or by using high sensitivity dedicated surface coils (which allows us to increase SNR without deteriorating spatial resolution in an excessive manner). However, surface coil sensitivity is heterogeneous, i.e., it- and hence SNR-decreases with increasing depth, and the more so as the coil radius is smaller. The use of surface coils is therefore limited to the analysis of superficial structure such as the hypodermic tissue analysed here. The aim of this work was to determine the maximum limits of spatial resolution and depth compatible with reliable in vivo T 2 quantitative MR images using dedicated surface coils available on various clinical MR scanners. The average thickness of adipose tissue is around 15 mm, and the results obtained have shown that obtaining reliable biexponential relaxation analysis requires a minimum achievable voxel size of 13 mm 3 for a conventional volume birdcage coil and only of 1.7 mm 3 for the smallest available surface coil (23 mm in diameter). Further improvement in spatial resolution allowing us to detect low details in MR images without deteriorating parametric T 2 images can be obtained by image filtering. By using the non-linear selective blurring filter described in a

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

    Science.gov (United States)

    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.

  7. Assessing the Suitability of Future Multi- and Hyperspectral Satellite Systems for Mapping the Spatial Distribution of Norway Spruce Timber Volume

    Directory of Open Access Journals (Sweden)

    Sascha Nink

    2015-09-01

    Full Text Available The availability of accurate and timely information on timber volume is important for supporting operational forest management. One option is to combine statistical concepts (e.g., small area estimates with specifically designed terrestrial sampling strategies to provide estimations also on the level of administrative units such as forest districts. This may suffice for economic assessments, but still fails to provide spatially explicit information on the distribution of timber volume within these management units. This type of information, however, is needed for decision-makers to design and implement appropriate management operations. The German federal state of Rhineland-Palatinate is currently implementing an object-oriented database that will also allow the direct integration of Earth observation data products. This work analyzes the suitability of forthcoming multi- and hyperspectral satellite imaging systems for producing local distribution maps for timber volume of Norway spruce, one of the most economically important tree species. In combination with site-specific inventory data, fully processed hyperspectral data sets (HyMap were used to simulate datasets of the forthcoming EnMAP and Sentinel-2 systems to establish adequate models for estimating timber volume maps. The analysis included PLS regression and the k-NN method. Root Mean Square Errors between 21.6% and 26.5% were obtained, where k-NN performed slightly better than PLSR. It was concluded that the datasets of both simulated sensor systems fulfill accuracy requirements to support local forest management operations and could be used in synergy. Sentinel-2 can provide meaningful volume distribution maps in higher geometric resolution, while EnMAP, due to its hyperspectral coverage, can contribute complementary information, e.g., on biophysical conditions.

  8. Hydrological differentiation and spatial distribution of high altitude wetlands in a semi-arid Andean region derived from satellite data

    Science.gov (United States)

    Otto, M.; Scherer, D.; Richters, J.

    2011-05-01

    High Altitude Wetlands of the Andes (HAWA) belong to a unique type of wetland within the semi-arid high Andean region. Knowledge about HAWA has been derived mainly from studies at single sites within different parts of the Andes at only small time scales. On the one hand, HAWA depend on water provided by glacier streams, snow melt or precipitation. On the other hand, they are suspected to influence hydrology through water retention and vegetation growth altering stream flow velocity. We derived HAWA land cover from satellite data at regional scale and analysed changes in connection with precipitation over the last decade. Perennial and temporal HAWA subtypes can be distinguished by seasonal changes of photosynthetically active vegetation (PAV) indicating the perennial or temporal availability of water during the year. HAWA have been delineated within a region of 12 800 km2 situated in the Northwest of Lake Titicaca. The multi-temporal classification method used Normalized Differenced Vegetation Index (NDVI) and Normalized Differenced Infrared Index (NDII) data derived from two Landsat ETM+ scenes at the end of austral winter (September 2000) and at the end of austral summer (May 2001). The mapping result indicates an unexpected high abundance of HAWA covering about 800 km2 of the study region (6 %). Annual HAWA mapping was computed using NDVI 16-day composites of Moderate Resolution Imaging Spectroradiometer (MODIS). Analyses on the relation between HAWA and precipitation was based on monthly precipitation data of the Tropical Rain Measurement Mission (TRMM 3B43) and MODIS Eight Day Maximum Snow Extent data (MOD10A2) from 2000 to 2010. We found HAWA subtype specific dependencies on precipitation conditions. A strong relation exists between perennial HAWA and snow fall (r2: 0.82) in dry austral winter months (June to August) and between temporal HAWA and precipitation (r2: 0.75) during austral summer (March to May). Annual changes in spatial extend of perennial HAWA

  9. Estimates of changes of structural parameters of forest ecosystems in decoding high resolution satellite images

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    Yuri F. Rozhkov

    2016-05-01

    Full Text Available Aim of this study was to assess the possibility of using of the parameter of symmetry of pixel distribution in the forest condition monitoring. Multispectral satellite imagery and their fragments of high and medium resolution (Landsat TM/ЕТМ+, Aster, Spot, IRS, which have been made in 1995–2011, were processed in two stages. At the first stage, uncontrolled classification has been carried out using the method ISODATA (Iterative Self-Organizing Data Analysis Technigue. At the second stage, parameter of symmetry of pixel distribution was calculated. The results of classification were divided into two halves. Classes with lower optical density of the reflected light were concentrated in the upper half while classes with higher optical density of the reflected light were concentrated in the bottom half. The prospects for using the parameter symmetry of pixel distribution aim to assess the degree of forest disturbance after the fire impact was demonstrated. Disturbed forest areas a have larger sum of pixels in the bottom half of the classification results compared with the upper half. In contrast, undisturbed forest areas have a larger or equal sum of pixels in the upper half of the classification results compared with the bottom half. The prospects for using the parameter symmetry of pixel distribution in monitoring of seasonal changes of forest status were demonstrated. Comparison of two forest fragments with dominance of larch and Siberian pine showed that during the autumn months (September, October after needle fall and leaf fall, there is a sharp decrease of the parameter "symmetry of pixel distribution" within the fragment with dominance of larch due to the increase of the proportion of pixels with high optical density. Seasonal changes in the parameter of symmetry of pixels distribution were less pronounced for the forest fragment with dominance of Siberian pine. We considered the prospect to use the parameter of symmetry of pixel

  10. Nanoscale Spatial Organization of Prokaryotic Cells Studied by Super-Resolution Optical Microscopy

    Science.gov (United States)

    McEvoy, Andrea Lynn

    All cells spatially organize their interiors, and this arrangement is necessary for cell viability. Until recently, it was believed that only eukaryotic cells spatially segregate their components. However, it is becoming increasingly clear that bacteria also assemble their proteins into complex patterns. In eukaryotic cells, spatial organization arises from membrane bound organelles as well as motor transport proteins which can move cargos within the cell. To date, there are no known motor transport proteins in bacteria and most microbes lack membrane bound organelles, so it remains a mystery how bacterial spatial organization emerges. In hind-sight it is not surprising that bacteria also exhibit complex spatial organization considering much of what we have learned about the basic processes that take place in all cells, such as transcription and translation was first discovered in prokaryotic cells. Perhaps the fundamental principles that govern spatial organization in prokaryotic cells may be applicable in eukaryotic cells as well. In addition, bacteria are attractive model organism for spatial organization studies because they are genetically tractable, grow quickly and much biochemical and structural data is known about them. A powerful tool for observing spatial organization in cells is the fluorescence microscope. By specifically tagging a protein of interest with a fluorescent probe, it is possible to examine how proteins organize and dynamically assemble inside cells. A significant disadvantage of this technology is its spatial resolution (approximately 250 nm laterally and 500 nm axially). This limitation on resolution causes closely spaced proteins to look blurred making it difficult to observe the fine structure within the complexes. This resolution limit is especially problematic within small cells such as bacteria. With the recent invention of new optical microscopies, we now can surpass the existing limits of fluorescence imaging. In some cases, we can

  11. Comparison of four machine learning methods for object-oriented change detection in high-resolution satellite imagery

    Science.gov (United States)

    Bai, Ting; Sun, Kaimin; Deng, Shiquan; Chen, Yan

    2018-03-01

    High resolution image change detection is one of the key technologies of remote sensing application, which is of great significance for resource survey, environmental monitoring, fine agriculture, military mapping and battlefield environment detection. In this paper, for high-re