Next-generation forest change mapping across the United States: the landscape change monitoring system (LCMS)

Treesearch

Sean P. Healey; Warren B. Cohen; Yang Zhiqiang; Ken Brewer; Evan Brooks; Noel Gorelick; Mathew Gregory; Alexander Hernandez; Chengquan Huang; Joseph Hughes; Robert Kennedy; Thomas Loveland; Kevin Megown; Gretchen Moisen; Todd Schroeder; Brian Schwind; Stephen Stehman; Daniel Steinwand; James Vogelmann; Curtis Woodcock; Limin Yang; Zhe Zhu

2015-01-01

Forest change information is critical in forest planning, ecosystem modeling, and in updating forest condition maps. The Landsat satellite platform has provided consistent observations of the world’s ecosystems since 1972. A number of innovative change detection algorithms have been developed to use the Landsat archive to identify and characterize forest change. The...

Detecting spatial regimes in ecosystems | Science Inventory ...

EPA Pesticide Factsheets

Research on early warning indicators has generally focused on assessing temporal transitions with limited application of these methods to detecting spatial regimes. Traditional spatial boundary detection procedures that result in ecoregion maps are typically based on ecological potential (i.e. potential vegetation), and often fail to account for ongoing changes due to stressors such as land use change and climate change and their effects on plant and animal communities. We use Fisher information, an information theory based method, on both terrestrial and aquatic animal data (US Breeding Bird Survey and marine zooplankton) to identify ecological boundaries, and compare our results to traditional early warning indicators, conventional ecoregion maps, and multivariate analysis such as nMDS (non-metric Multidimensional Scaling) and cluster analysis. We successfully detect spatial regimes and transitions in both terrestrial and aquatic systems using Fisher information. Furthermore, Fisher information provided explicit spatial information about community change that is absent from other multivariate approaches. Our results suggest that defining spatial regimes based on animal communities may better reflect ecological reality than do traditional ecoregion maps, especially in our current era of rapid and unpredictable ecological change. Use an information theory based method to identify ecological boundaries and compare our results to traditional early warning

Support Vector Machines for Multitemporal and Multisensor Change Detection in a Mining Area

NASA Astrophysics Data System (ADS)

Hecheltjen, Antje; Waske, Bjorn; Thonfeld, Frank; Braun, Matthias; Menz, Gunter

2010-12-01

Long-term change detection often implies the challenge of incorporating multitemporal data from different sensors. Most of the conventional change detection algorithms are designed for bi-temporal datasets from the same sensors detecting only the existence of changes. The labeling of change areas remains a difficult task. To overcome such drawbacks, much attention has been given lately to algorithms arising from machine learning, such as Support Vector Machines (SVMs). While SVMs have been applied successfully for land cover classifications, the exploitation of this approach for change detection is still in its infancy. Few studies have already proven the applicability of SVMs for bi- and multitemporal change detection using data from one sensor only. In this paper we demonstrate the application of SVM for multitemporal and -sensor change detection. Our study site covers lignite open pit mining areas in the German state North Rhine-Westphalia. The dataset consists of bi-temporal Landsat data and multi-temporal ERS SAR data covering two time slots (2001 and 2009). The SVM is conducted using the IDL program imageSVM. Change is deduced from one time slot to the next resulting in two change maps. In contrast to change detection, which is based on post-classification comparison, change detection is seen here as a specific classification problem. Thus, changes are directly classified from a layer-stack of the two years. To reduce the number of change classes, we created a change mask using the magnitude of Change Vector Analysis (CVA). Training data were selected for different change classes (e.g. forest to mining or mining to agriculture) as well as for the no-change classes (e.g. agriculture). Subsequently, they were divided in two independent sets for training the SVMs and accuracy assessment, respectively. Our study shows the applicability of SVMs to classify changes via SVMs. The proposed method yielded a change map of reclaimed and active mines. The use of ERS SAR data, however, did not add to the accuracy compared to Landsat data only. A great advantage compared to other change detection approaches are the labeled change maps, which are a direct output of the methodology. Our approach also overcomes the drawback of post-classification comparison, namely the propagation of classification inaccuracies.

Applicability Assessment of Uavsar Data in Wetland Monitoring: a Case Study of Louisiana Wetland

NASA Astrophysics Data System (ADS)

Zhao, J.; Niu, Y.; Lu, Z.; Yang, J.; Li, P.; Liu, W.

2018-04-01

Wetlands are highly productive and support a wide variety of ecosystem goods and services. Monitoring wetland is essential and potential. Because of the repeat-pass nature of satellite orbit and airborne, time-series of remote sensing data can be obtained to monitor wetland. UAVSAR is a NASA L-band synthetic aperture radar (SAR) sensor compact pod-mounted polarimetric instrument for interferometric repeat-track observations. Moreover, UAVSAR images can accurately map crustal deformations associated with natural hazards, such as volcanoes and earthquakes. And its polarization agility facilitates terrain and land-use classification and change detection. In this paper, the multi-temporal UAVSAR data are applied for monitoring the wetland change. Using the multi-temporal polarimetric SAR (PolSAR) data, the change detection maps are obtained by unsupervised and supervised method. And the coherence is extracted from the interfometric SAR (InSAR) data to verify the accuracy of change detection map. The experimental results show that the multi-temporal UAVSAR data is fit for wetland monitor.

Rapid Landslide Mapping by Means of Post-Event Polarimetric SAR Imagery

NASA Astrophysics Data System (ADS)

Plank, Simon; Martinis, Sandro; Twele, Andre

2016-08-01

Rapid mapping of landslides, quickly providing information about the extent of the affected area and type and grade of damage, is crucial to enable fast crisis response. Reviewing the literature shows that most synthetic aperture radar (SAR) data-based landslide mapping procedures use change detection techniques. However, the required very high resolution (VHR) pre-event SAR imagery, acquired shortly before the landslide event, is commonly not available. Due to limitations in onboard disk space and downlink transmission rates modern VHR SAR missions do not systematically cover the entire world. We present a fast and robust procedure for mapping of landslides, based on change detection between freely available and systematically acquired pre-event optical and post-event polarimetric SAR data.

A Deep Convolutional Coupling Network for Change Detection Based on Heterogeneous Optical and Radar Images.

PubMed

Liu, Jia; Gong, Maoguo; Qin, Kai; Zhang, Puzhao

2018-03-01

We propose an unsupervised deep convolutional coupling network for change detection based on two heterogeneous images acquired by optical sensors and radars on different dates. Most existing change detection methods are based on homogeneous images. Due to the complementary properties of optical and radar sensors, there is an increasing interest in change detection based on heterogeneous images. The proposed network is symmetric with each side consisting of one convolutional layer and several coupling layers. The two input images connected with the two sides of the network, respectively, are transformed into a feature space where their feature representations become more consistent. In this feature space, the different map is calculated, which then leads to the ultimate detection map by applying a thresholding algorithm. The network parameters are learned by optimizing a coupling function. The learning process is unsupervised, which is different from most existing change detection methods based on heterogeneous images. Experimental results on both homogenous and heterogeneous images demonstrate the promising performance of the proposed network compared with several existing approaches.

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

NASA Astrophysics Data System (ADS)

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

2017-06-01

During the last 20 years, airborne laser scanning (ALS), often combined with passive multispectral information from aerial images, has shown its high feasibility for automated mapping processes. The main benefits have been achieved in the mapping of elevated objects such as buildings and trees. Recently, the first multispectral airborne laser scanners have been launched, and active multispectral information is for the first time available for 3D ALS point clouds from a single sensor. This article discusses the potential of this new technology in map updating, especially in automated object-based land cover classification and change detection in a suburban area. For our study, Optech Titan multispectral ALS data over a suburban area in Finland were acquired. Results from an object-based random forests analysis suggest that the multispectral ALS data are very useful for land cover classification, considering both elevated classes and ground-level classes. The overall accuracy of the land cover classification results with six classes was 96% compared with validation points. The classes under study included building, tree, asphalt, gravel, rocky area and low vegetation. Compared to classification of single-channel data, the main improvements were achieved for ground-level classes. According to feature importance analyses, multispectral intensity features based on several channels were more useful than those based on one channel. Automatic change detection for buildings and roads was also demonstrated by utilising the new multispectral ALS data in combination with old map vectors. In change detection of buildings, an old digital surface model (DSM) based on single-channel ALS data was also used. Overall, our analyses suggest that the new data have high potential for further increasing the automation level in mapping. Unlike passive aerial imaging commonly used in mapping, the multispectral ALS technology is independent of external illumination conditions, and there are no shadows on intensity images produced from the data. These are significant advantages in developing automated classification and change detection procedures.

Land use mapping and modelling for the Phoenix Quadrangle

NASA Technical Reports Server (NTRS)

Place, J. L. (Principal Investigator)

1973-01-01

The author has identified the following significant results. The land use of the Phoenix Quadrangle in Arizona had been mapped previously from aerial photographs and recorded in a computer data bank. During the ERTS-1 experiment, changes in land use were detected using only the ERTS-1 images. The I2S color additive viewer was used as the principal image enhancement tool, operated in a multispectral mode. Hard copy color composite images of the best multiband combinations from ERTS-1 were made by photographic and diazo processes. The I2S viewer was also used to enhance changes between successive images by quick flip techniques or by registering with different color filters. More recently, a Bausch and Lomb zoom transferscope has been used for the same purpose. Improved interpretation of land use change resulted, and a map of changes within the Phoenix Quadrangle was compiled. The first level of a proposed standard land use classification system was sucessfully used. ERTS-1 underflight photography was used to check the accuracy of the ERTS-1 image interpretation. It was found that the total areas of change detected in the photos were comparable with the total areas of change detected in the ERTS-1 images.

Spatially-Aware Temporal Anomaly Mapping of Gamma Spectra

NASA Astrophysics Data System (ADS)

Reinhart, Alex; Athey, Alex; Biegalski, Steven

2014-06-01

For security, environmental, and regulatory purposes it is useful to continuously monitor wide areas for unexpected changes in radioactivity. We report on a temporal anomaly detection algorithm which uses mobile detectors to build a spatial map of background spectra, allowing sensitive detection of any anomalies through many days or months of monitoring. We adapt previously-developed anomaly detection methods, which compare spectral shape rather than count rate, to function with limited background data, allowing sensitive detection of small changes in spectral shape from day to day. To demonstrate this technique we collected daily observations over the period of six weeks on a 0.33 square mile research campus and performed source injection simulations.

Feasibility of Multispectral Airborne Laser Scanning for Land Cover Classification, Road Mapping and Map Updating

NASA Astrophysics Data System (ADS)

Matikainen, L.; Karila, K.; Hyyppä, J.; Puttonen, E.; Litkey, P.; Ahokas, E.

2017-10-01

This article summarises our first results and experiences on the use of multispectral airborne laser scanner (ALS) data. Optech Titan multispectral ALS data over a large suburban area in Finland were acquired on three different dates in 2015-2016. We investigated the feasibility of the data from the first date for land cover classification and road mapping. Object-based analyses with segmentation and random forests classification were used. The potential of the data for change detection of buildings and roads was also demonstrated. The overall accuracy of land cover classification results with six classes was 96 % compared with validation points. The data also showed high potential for road detection, road surface classification and change detection. The multispectral intensity information appeared to be very important for automated classifications. Compared to passive aerial images, the intensity images have interesting advantages, such as the lack of shadows. Currently, we focus on analyses and applications with the multitemporal multispectral data. Important questions include, for example, the potential and challenges of the multitemporal data for change detection.

Enhancement of snow cover change detection with sparse representation and dictionary learning

NASA Astrophysics Data System (ADS)

Varade, D.; Dikshit, O.

2014-11-01

Sparse representation and decoding is often used for denoising images and compression of images with respect to inherent features. In this paper, we adopt a methodology incorporating sparse representation of a snow cover change map using the K-SVD trained dictionary and sparse decoding to enhance the change map. The pixels often falsely characterized as "changes" are eliminated using this approach. The preliminary change map was generated using differenced NDSI or S3 maps in case of Resourcesat-2 and Landsat 8 OLI imagery respectively. These maps are extracted into patches for compressed sensing using Discrete Cosine Transform (DCT) to generate an initial dictionary which is trained by the K-SVD approach. The trained dictionary is used for sparse coding of the change map using the Orthogonal Matching Pursuit (OMP) algorithm. The reconstructed change map incorporates a greater degree of smoothing and represents the features (snow cover changes) with better accuracy. The enhanced change map is segmented using kmeans to discriminate between the changed and non-changed pixels. The segmented enhanced change map is compared, firstly with the difference of Support Vector Machine (SVM) classified NDSI maps and secondly with a reference data generated as a mask by visual interpretation of the two input images. The methodology is evaluated using multi-spectral datasets from Resourcesat-2 and Landsat-8. The k-hat statistic is computed to determine the accuracy of the proposed approach.

Unsupervised Multi-Scale Change Detection from SAR Imagery for Monitoring Natural and Anthropogenic Disasters

NASA Astrophysics Data System (ADS)

Ajadi, Olaniyi A.

Radar remote sensing can play a critical role in operational monitoring of natural and anthropogenic disasters. Despite its all-weather capabilities, and its high performance in mapping, and monitoring of change, the application of radar remote sensing in operational monitoring activities has been limited. This has largely been due to: (1) the historically high costs associated with obtaining radar data; (2) slow data processing, and delivery procedures; and (3) the limited temporal sampling that was provided by spaceborne radar-based satellites. Recent advances in the capabilities of spaceborne Synthetic Aperture Radar (SAR) sensors have developed an environment that now allows for SAR to make significant contributions to disaster monitoring. New SAR processing strategies that can take full advantage of these new sensor capabilities are currently being developed. Hence, with this PhD dissertation, I aim to: (i) investigate unsupervised change detection techniques that can reliably extract signatures from time series of SAR images, and provide the necessary flexibility for application to a variety of natural, and anthropogenic hazard situations; (ii) investigate effective methods to reduce the effects of speckle and other noise on change detection performance; (iii) automate change detection algorithms using probabilistic Bayesian inferencing; and (iv) ensure that the developed technology is applicable to current, and future SAR sensors to maximize temporal sampling of a hazardous event. This is achieved by developing new algorithms that rely on image amplitude information only, the sole image parameter that is available for every single SAR acquisition.. The motivation and implementation of the change detection concept are described in detail in Chapter 3. In the same chapter, I demonstrated the technique's performance using synthetic data as well as a real-data application to map wildfire progression. I applied Radiometric Terrain Correction (RTC) to the data to increase the sampling frequency, while the developed multiscale-driven approach reliably identified changes embedded in largely stationary background scenes. With this technique, I was able to identify the extent of burn scars with high accuracy. I further applied the application of the change detection technology to oil spill mapping. The analysis highlights that the approach described in Chapter 3 can be applied to this drastically different change detection problem with only little modification. While the core of the change detection technique remained unchanged, I made modifications to the pre-processing step to enable change detection from scenes of continuously varying background. I introduced the Lipschitz regularity (LR) transformation as a technique to normalize the typically dynamic ocean surface, facilitating high performance oil spill detection independent of environmental conditions during image acquisition. For instance, I showed that LR processing reduces the sensitivity of change detection performance to variations in surface winds, which is a known limitation in oil spill detection from SAR. Finally, I applied the change detection technique to aufeis flood mapping along the Sagavanirktok River. Due to the complex nature of aufeis flooded areas, I substituted the resolution-preserving speckle filter used in Chapter 3 with curvelet filters. In addition to validating the performance of the change detection results, I also provide evidence of the wealth of information that can be extracted about aufeis flooding events once a time series of change detection information was extracted from SAR imagery. A summary of the developed change detection techniques is conducted and suggested future work is presented in Chapter 6.

Identification of irrigated crop types from ERTS-1 density contour maps and color infrared aerial photography. [Wyoming

NASA Technical Reports Server (NTRS)

Marrs, R. W.; Evans, M. A.

1974-01-01

The author has identified the following significant results. The crop types of a Great Plains study area were mapped from color infrared aerial photography. Each field was positively identified from field checks in the area. Enlarged (50x) density contour maps were constructed from three ERTS-1 images taken in the summer of 1973. The map interpreted from the aerial photography was compared to the density contour maps and the accuracy of the ERTS-1 density contour map interpretations were determined. Changes in the vegetation during the growing season and harvest periods were detectable on the ERTS-1 imagery. Density contouring aids in the detection of such charges.

Using NIR spatial illumination for detection and mapping chromophore changes during cerebral edema

NASA Astrophysics Data System (ADS)

Abookasis, David; Mathews, Marlon S.; Owen, Christopher M.; Binder, Devin K.; Linskey, Mark E.; Frostig, Ron D.; Tromberg, Bruce J.

2008-02-01

We used spatially modulated near-infrared (NIR) light to detect and map chromophore changes during cerebral edema in the rat neocortex. Cerebral edema was induced by intraperitoneal injections of free water (35% of body weight). Intracranial pressure (ICP) was measured with an optical fiber based Fabry-Perot interferometer sensor inserted into the parenchyma of the right frontal lobe during water administration. Increase in ICP from a baseline value of 10 cm-water to 145 cm-water was observed. Following induction of cerebral edema, there was a 26+/-1.7% increase in tissue concentration of deoxyhemoglobin and a 47+/-4.7%, 17+/-3% and 37+/-3.7% decrease in oxyhemoglobin, total hemoglobin concentration and cerebral tissue oxygen saturation levels, respectively. To the best of our knowledge, this is the first report describing the use of NIR spatial modulation of light for detecting and mapping changes in tissue concentrations of physiologic chromophores over time in response to cerebral edema.

Techniques for automatic large scale change analysis of temporal multispectral imagery

NASA Astrophysics Data System (ADS)

Mercovich, Ryan A.

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

A statistical method (cross-validation) for bone loss region detection after spaceflight

PubMed Central

Zhao, Qian; Li, Wenjun; Li, Caixia; Chu, Philip W.; Kornak, John; Lang, Thomas F.

2010-01-01

Astronauts experience bone loss after the long spaceflight missions. Identifying specific regions that undergo the greatest losses (e.g. the proximal femur) could reveal information about the processes of bone loss in disuse and disease. Methods for detecting such regions, however, remains an open problem. This paper focuses on statistical methods to detect such regions. We perform statistical parametric mapping to get t-maps of changes in images, and propose a new cross-validation method to select an optimum suprathreshold for forming clusters of pixels. Once these candidate clusters are formed, we use permutation testing of longitudinal labels to derive significant changes. PMID:20632144

Detection of changes in semi-natural grasslands by cross correlation analysis with WorldView-2 images and new Landsat 8 data.

PubMed

Tarantino, Cristina; Adamo, Maria; Lucas, Richard; Blonda, Palma

2016-03-15

Focusing on a Mediterranean Natura 2000 site in Italy, the effectiveness of the cross correlation analysis (CCA) technique for quantifying change in the area of semi-natural grasslands at different spatial resolutions (grain) was evaluated. In a fine scale analysis (2 m), inputs to the CCA were a) a semi-natural grasslands layer extracted from an existing validated land cover/land use (LC/LU) map (1:5000, time T 1 ) and b) a more recent single date very high resolution (VHR) WorldView-2 image (time T 2 ), with T 2  > T 1 . The changes identified through the CCA were compared against those detected by applying a traditional post-classification comparison (PCC) technique to the same reference T 1 map and an updated T 2 map obtained by a knowledge driven classification of four multi-seasonal Worldview-2 input images. Specific changes observed were those associated with agricultural intensification and fires. The study concluded that prior knowledge (spectral class signatures, awareness of local agricultural practices and pressures) was needed for the selection of the most appropriate image (in terms of seasonality) to be acquired at T 2 . CCA was also applied to the comparison of the existing T 1 map with recent high resolution (HR) Landsat 8 OLS images. The areas of change detected at VHR and HR were broadly similar with larger error values in HR change images.

Real-time change and damage detection of landslides and other earth movements threatening public infrastructure.

DOT National Transportation Integrated Search

2012-03-01

construction and maintenance. Repeat surveys using terrestrial laser scanning (TLS, ground-based LiDAR) enable rapid 3D data acquisition to map, see, analyze, and understand the processes generating such problems. Previously, change detection and ana...

Assessment of the relative sensitivity of milk ELISA for detection of Mycobacterium avium ssp. paratuberculosis infectious dairy cows.

PubMed

Laurin, Emilie L; Sanchez, Javier; Chaffer, Marcelo; McKenna, Shawn L B; Keefe, Greg P

2017-01-01

Milk ELISA are commonly used for detection of Mycobacterium avium ssp. paratuberculosis (MAP) antibodies in dairy cows, due to low cost and quick processing for large numbers of samples. However, low sensitivity and variations from host and environmental factors can impede detection of MAP antibodies at early disease stages. The objectives of our study were to assess the sensitivity of milk ELISA in comparison with fecal tests and to evaluate how detectable antibody concentrations in milk vary with changes in fecal shedding of MAP, cow age, cow parity, days in milk, and time of year. To compare the sensitivity of a commercial milk ELISA with solid and broth fecal culture and with fecal real-time PCR, a longitudinal study was performed for the identification of MAP-infectious animals as determined by prior fecal testing for MAP shedding. In addition, associations between variation in milk MAP ELISA score and changes in fecal MAP shedding, host age, days in milk, and season were evaluated. Monthly milk and fecal samples were collected over 1 yr from 46 cows that were previously shedding MAP in their feces. Sensitivity of milk ELISA was 29.9% (95% CI: 24.8 to 35.1%), compared with 46.7% (40.7 to 52.7%) for fecal solid culture, 55.0% (49.3 to 60.7%) for fecal broth culture, and 78.4% (73.3 to 83.1%) for fecal direct real-time PCR. The effect of stage of lactation could not be separated from the effect of season, with increased milk ELISA scores at greater days in milk in winter. However, unpredictable monthly variations in results were observed among the 3 assays for individual cow testing, which highlights the importance of identifying patterns in pathogen and antibody detection over time in MAP-positive herds. Copyright © 2017 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Assessment of Data Fusion Algorithms for Earth Observation Change Detection Processes.

PubMed

Molina, Iñigo; Martinez, Estibaliz; Morillo, Carmen; Velasco, Jesus; Jara, Alvaro

2016-09-30

In this work a parametric multi-sensor Bayesian data fusion approach and a Support Vector Machine (SVM) are used for a Change Detection problem. For this purpose two sets of SPOT5-PAN images have been used, which are in turn used for Change Detection Indices (CDIs) calculation. For minimizing radiometric differences, a methodology based on zonal "invariant features" is suggested. The choice of one or the other CDI for a change detection process is a subjective task as each CDI is probably more or less sensitive to certain types of changes. Likewise, this idea might be employed to create and improve a "change map", which can be accomplished by means of the CDI's informational content. For this purpose, information metrics such as the Shannon Entropy and "Specific Information" have been used to weight the changes and no-changes categories contained in a certain CDI and thus introduced in the Bayesian information fusion algorithm. Furthermore, the parameters of the probability density functions (pdf's) that best fit the involved categories have also been estimated. Conversely, these considerations are not necessary for mapping procedures based on the discriminant functions of a SVM. This work has confirmed the capabilities of probabilistic information fusion procedure under these circumstances.

Detection and mapping of QTL for temperature tolerance and body size in Chinook salmon (Oncorhynchus tshawytscha) using genotyping by sequencing

PubMed Central

Everett, Meredith V; Seeb, James E

2014-01-01

Understanding how organisms interact with their environments is increasingly important for conservation efforts in many species, especially in light of highly anticipated climate changes. One method for understanding this relationship is to use genetic maps and QTL mapping to detect genomic regions linked to phenotypic traits of importance for adaptation. We used high-throughput genotyping by sequencing (GBS) to both detect and map thousands of SNPs in haploid Chinook salmon (Oncorhynchus tshawytscha). We next applied this map to detect QTL related to temperature tolerance and body size in families of diploid Chinook salmon. Using these techniques, we mapped 3534 SNPs in 34 linkage groups which is consistent with the haploid chromosome number for Chinook salmon. We successfully detected three QTL for temperature tolerance and one QTL for body size at the experiment-wide level, as well as additional QTL significant at the chromosome-wide level. The use of haploids coupled with GBS provides a robust pathway to rapidly develop genomic resources in nonmodel organisms; these QTL represent preliminary progress toward linking traits of conservation interest to regions in the Chinook salmon genome. PMID:24822082

Using Bi-Seasonal WorldView-2 Multi-Spectral Data and Supervised Random Forest Classification to Map Coastal Plant Communities in Everglades National Park.

PubMed

Wendelberger, Kristie S; Gann, Daniel; Richards, Jennifer H

2018-03-09

Coastal plant communities are being transformed or lost because of sea level rise (SLR) and land-use change. In conjunction with SLR, the Florida Everglades ecosystem has undergone large-scale drainage and restoration, altering coastal vegetation throughout south Florida. To understand how coastal plant communities are changing over time, accurate mapping techniques are needed that can define plant communities at a fine-enough resolution to detect fine-scale changes. We explored using bi-seasonal versus single-season WorldView-2 satellite data to map three mangrove and four adjacent plant communities, including the buttonwood/glycophyte community that harbors the federally-endangered plant Chromolaena frustrata . Bi-seasonal data were more effective than single-season to differentiate all communities of interest. Bi-seasonal data combined with Light Detection and Ranging (LiDAR) elevation data were used to map coastal plant communities of a coastal stretch within Everglades National Park (ENP). Overall map accuracy was 86%. Black and red mangroves were the dominant communities and covered 50% of the study site. All the remaining communities had ≤10% cover, including the buttonwood/glycophyte community. ENP harbors 21 rare coastal species threatened by SLR. The spatially explicit, quantitative data provided by our map provides a fine-scale baseline for monitoring future change in these species' habitats. Our results also offer a method to monitor vegetation change in other threatened habitats.

Using Bi-Seasonal WorldView-2 Multi-Spectral Data and Supervised Random Forest Classification to Map Coastal Plant Communities in Everglades National Park

PubMed Central

Richards, Jennifer H.

2018-01-01

Coastal plant communities are being transformed or lost because of sea level rise (SLR) and land-use change. In conjunction with SLR, the Florida Everglades ecosystem has undergone large-scale drainage and restoration, altering coastal vegetation throughout south Florida. To understand how coastal plant communities are changing over time, accurate mapping techniques are needed that can define plant communities at a fine-enough resolution to detect fine-scale changes. We explored using bi-seasonal versus single-season WorldView-2 satellite data to map three mangrove and four adjacent plant communities, including the buttonwood/glycophyte community that harbors the federally-endangered plant Chromolaena frustrata. Bi-seasonal data were more effective than single-season to differentiate all communities of interest. Bi-seasonal data combined with Light Detection and Ranging (LiDAR) elevation data were used to map coastal plant communities of a coastal stretch within Everglades National Park (ENP). Overall map accuracy was 86%. Black and red mangroves were the dominant communities and covered 50% of the study site. All the remaining communities had ≤10% cover, including the buttonwood/glycophyte community. ENP harbors 21 rare coastal species threatened by SLR. The spatially explicit, quantitative data provided by our map provides a fine-scale baseline for monitoring future change in these species’ habitats. Our results also offer a method to monitor vegetation change in other threatened habitats. PMID:29522476

Urban change detection procedures using Landsat digital data

NASA Technical Reports Server (NTRS)

Jensen, J. R.; Toll, D. L.

1982-01-01

Landsat multispectral scanner data was applied to an urban change detection problem in Denver, CO. A dichotomous key yielding ten stages of residential development at the urban fringe was developed. This heuristic model allowed one to identify certain stages of development which are difficult to detect when performing digital change detection using Landsat data. The stages of development were evaluated in terms of their spectral and derived textural characteristics. Landsat band 5 (0.6-0.7 micron) and texture data produced change detection maps which were approximately 81 percent accurate. Results indicated that the stage of development and the spectral/textural features affect the change in the spectral values used for change detection. These preliminary findings will hopefully prove valuable for improved change detection at the urban fringe.

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

NASA Technical Reports Server (NTRS)

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.

Association of medial meniscal extrusion with medial tibial osteophyte distance detected by T2 mapping MRI in patients with early-stage knee osteoarthritis.

PubMed

Hada, Shinnosuke; Ishijima, Muneaki; Kaneko, Haruka; Kinoshita, Mayuko; Liu, Lizu; Sadatsuki, Ryo; Futami, Ippei; Yusup, Anwajan; Takamura, Tomohiro; Arita, Hitoshi; Shiozawa, Jun; Aoki, Takako; Takazawa, Yuji; Ikeda, Hiroshi; Aoki, Shigeki; Kurosawa, Hisashi; Okada, Yasunori; Kaneko, Kazuo

2017-09-12

Medial meniscal extrusion (MME) is associated with progression of medial knee osteoarthritis (OA), but no or little information is available for relationships between MME and osteophytes, which are found in cartilage and bone parts. Because of the limitation in detectability of the cartilage part of osteophytes by radiography or conventional magnetic resonance imaging (MRI), the rate of development and size of osteophytes appear to have been underestimated. Because T2 mapping MRI may enable us to evaluate the cartilage part of osteophytes, we aimed to examine the association between MME and OA-related changes, including osteophytes, by using conventional and T2 mapping MRI. Patients with early-stage knee OA (n = 50) were examined. MRI-detected OA-related changes, in addition to MME, were evaluated according to the Whole-Organ Magnetic Resonance Imaging Score. T2 values of the medial meniscus and osteophytes were measured on T2 mapping images. Osteophytes surgically removed from patients with end-stage knee OA were histologically analyzed and compared with findings derived by radiography and MRI. Medial side osteophytes were detected by T2 mapping MRI in 98% of patients with early-stage knee OA, although the detection rate was 48% by conventional MRI and 40% by radiography. Among the OA-related changes, medial tibial osteophyte distance was most closely associated with MME, as determined by multiple logistic regression analysis, in the patients with early-stage knee OA (β = 0.711, p < 0.001). T2 values of the medial meniscus were directly correlated with MME in patients with early-stage knee OA, who showed ≥ 3 mm of MME (r = 0.58, p = 0.003). The accuracy of osteophyte evaluation by T2 mapping MRI was confirmed by histological analysis of the osteophytes removed from patients with end-stage knee OA. Our study demonstrates that medial tibial osteophyte evaluated by T2 mapping MRI is frequently observed in the patients with early-stage knee OA, showing close association with MME, and that MME is positively correlated with the meniscal degeneration.

From Google Maps to a fine-grained catalog of street trees

NASA Astrophysics Data System (ADS)

Branson, Steve; Wegner, Jan Dirk; Hall, David; Lang, Nico; Schindler, Konrad; Perona, Pietro

2018-01-01

Up-to-date catalogs of the urban tree population are of importance for municipalities to monitor and improve quality of life in cities. Despite much research on automation of tree mapping, mainly relying on dedicated airborne LiDAR or hyperspectral campaigns, tree detection and species recognition is still mostly done manually in practice. We present a fully automated tree detection and species recognition pipeline that can process thousands of trees within a few hours using publicly available aerial and street view images of Google MapsTM. These data provide rich information from different viewpoints and at different scales from global tree shapes to bark textures. Our work-flow is built around a supervised classification that automatically learns the most discriminative features from thousands of trees and corresponding, publicly available tree inventory data. In addition, we introduce a change tracker that recognizes changes of individual trees at city-scale, which is essential to keep an urban tree inventory up-to-date. The system takes street-level images of the same tree location at two different times and classifies the type of change (e.g., tree has been removed). Drawing on recent advances in computer vision and machine learning, we apply convolutional neural networks (CNN) for all classification tasks. We propose the following pipeline: download all available panoramas and overhead images of an area of interest, detect trees per image and combine multi-view detections in a probabilistic framework, adding prior knowledge; recognize fine-grained species of detected trees. In a later, separate module, track trees over time, detect significant changes and classify the type of change. We believe this is the first work to exploit publicly available image data for city-scale street tree detection, species recognition and change tracking, exhaustively over several square kilometers, respectively many thousands of trees. Experiments in the city of Pasadena, California, USA show that we can detect >70% of the street trees, assign correct species to >80% for 40 different species, and correctly detect and classify changes in >90% of the cases.

Using remote sensing and GIS to detect and monitor land use and land cover change in Dhaka Metropolitan of Bangladesh during 1960-2005.

PubMed

Dewan, Ashraf M; Yamaguchi, Yasushi

2009-03-01

This paper illustrates the result of land use/cover change in Dhaka Metropolitan of Bangladesh using topographic maps and multi-temporal remotely sensed data from 1960 to 2005. The Maximum likelihood supervised classification technique was used to extract information from satellite data, and post-classification change detection method was employed to detect and monitor land use/cover change. Derived land use/cover maps were further validated by using high resolution images such as SPOT, IRS, IKONOS and field data. The overall accuracy of land cover change maps, generated from Landsat and IRS-1D data, ranged from 85% to 90%. The analysis indicated that the urban expansion of Dhaka Metropolitan resulted in the considerable reduction of wetlands, cultivated land, vegetation and water bodies. The maps showed that between 1960 and 2005 built-up areas increased approximately 15,924 ha, while agricultural land decreased 7,614 ha, vegetation decreased 2,336 ha, wetland/lowland decreased 6,385 ha, and water bodies decreased about 864 ha. The amount of urban land increased from 11% (in 1960) to 344% in 2005. Similarly, the growth of landfill/bare soils category was about 256% in the same period. Much of the city's rapid growth in population has been accommodated in informal settlements with little attempt being made to limit the risk of environmental impairments. The study quantified the patterns of land use/cover change for the last 45 years for Dhaka Metropolitan that forms valuable resources for urban planners and decision makers to devise sustainable land use and environmental planning.

Perspectives of Maine Forest Cover Change from Landsat Imagery and Forest Inventory Analysis (FIA)

Treesearch

Steven Sader; Michael Hoppus; Jacob Metzler; Suming Jin

2005-01-01

A forest change detection map was developed to document forest gains and losses during the decade of the 1990s. The effectiveness of the Landsat imagery and methods for detecting Maine forest cover change are indicated by the good accuracy assessment results: forest-no change, forest loss, and forest gain accuracy were 90, 88, and 92% respectively, and the good...

Detecting Landscape Change: The View from Above

ERIC Educational Resources Information Center

Porter, Jess

2008-01-01

This article will demonstrate an approach for discovering and assessing local landscape change through the use of remotely sensed images. A brief introduction to remotely sensed imagery is followed by a discussion of relevant ways to introduce this technology into the college science classroom. The Map Detective activity demonstrates the…

Whole-genome resequencing: changing the paradigms of SNP detection, molecular mapping and gene discovery

USDA-ARS?s Scientific Manuscript database

The next generation sequencing (NGS) technologies have opened a wealth of opportunities for plant breeding and genomics research, and changed the paradigms of marker detection, genotyping, and gene discovery. Abundant genomic resources have been generated using a whole genome resequencing (WGR) str...

Land use mapping and change detection using ERTS imagery in Montgomery County, Alabama

NASA Technical Reports Server (NTRS)

Wilms, R. P.

1973-01-01

The feasibility of using remotely sensed data from ERTS-1 for mapping land use and detecting land use change was investigated. Land use information was gathered from 1964 air photo mosaics and from 1972 ERTS data. The 1964 data provided the basis for comparison with ERTS-1 imagery. From this comparison, urban sprawl was quite evident for the city of Montgomery. A significant trend from forestland to agricultural was also discovered. The development of main traffic arteries between 1964 and 1972 was a vital factor in the development of some of the urban centers. Even though certain problems in interpreting and correlating land use data from ERTS imagery were encountered, it has been demonstrated that remotely sensed data from ERTS is useful for inventorying land use and detecting land use change.

Specifications for updating USGS land use and land cover maps

USGS Publications Warehouse

Milazzo, Valerie A.

1983-01-01

To meet the increasing demands for up-to-date land use and land cover information, a primary goal of the U.S. Geological Survey's (USGS) national land use and land cover mapping program is to provide for periodic updating of maps and data in a timely and uniform manner. The technical specifications for updating existing USGS land use and land cover maps that are presented here cover both the interpretive aspects of detecting and identifying land use and land cover changes and the cartographic aspects of mapping and presenting the change data in conventional map format. They provide the map compiler with the procedures and techniques necessary to then use these change data to update existing land use and land cover maps in a manner that is both standardized and repeatable. Included are specifications for the acquisition of remotely sensed source materials, selection of compilation map bases, handling of data base corrections, editing and quality control operations, generation of map update products for USGS open file, and the reproduction and distribution of open file materials. These specifications are planned to become part of the National Mapping Division's Technical Instructions.

A joint estimation detection of Glaucoma progression in 3D spectral domain optical coherence tomography optic nerve head images

NASA Astrophysics Data System (ADS)

Belghith, Akram; Bowd, Christopher; Weinreb, Robert N.; Zangwill, Linda M.

2014-03-01

Glaucoma is an ocular disease characterized by distinctive changes in the optic nerve head (ONH) and visual field. Glaucoma can strike without symptoms and causes blindness if it remains without treatment. Therefore, early disease detection is important so that treatment can be initiated and blindness prevented. In this context, important advances in technology for non-invasive imaging of the eye have been made providing quantitative tools to measure structural changes in ONH topography, an essential element for glaucoma detection and monitoring. 3D spectral domain optical coherence tomography (SD-OCT), an optical imaging technique, has been commonly used to discriminate glaucomatous from healthy subjects. In this paper, we present a new framework for detection of glaucoma progression using 3D SD-OCT images. In contrast to previous works that the retinal nerve fiber layer (RNFL) thickness measurement provided by commercially available spectral-domain optical coherence tomograph, we consider the whole 3D volume for change detection. To integrate a priori knowledge and in particular the spatial voxel dependency in the change detection map, we propose the use of the Markov Random Field to handle a such dependency. To accommodate the presence of false positive detection, the estimated change detection map is then used to classify a 3D SDOCT image into the "non-progressing" and "progressing" glaucoma classes, based on a fuzzy logic classifier. We compared the diagnostic performance of the proposed framework to existing methods of progression detection.

A joint estimation detection of Glaucoma progression in 3D spectral domain optical coherence tomography optic nerve head images.

PubMed

Belghith, Akram; Bowd, Christopher; Weinreb, Robert N; Zangwill, Linda M

2014-03-18

Glaucoma is an ocular disease characterized by distinctive changes in the optic nerve head (ONH) and visual field. Glaucoma can strike without symptoms and causes blindness if it remains without treatment. Therefore, early disease detection is important so that treatment can be initiated and blindness prevented. In this context, important advances in technology for non-invasive imaging of the eye have been made providing quantitative tools to measure structural changes in ONH topography, an essential element for glaucoma detection and monitoring. 3D spectral domain optical coherence tomography (SD-OCT), an optical imaging technique, has been commonly used to discriminate glaucomatous from healthy subjects. In this paper, we present a new framework for detection of glaucoma progression using 3D SD-OCT images. In contrast to previous works that the retinal nerve fiber layer (RNFL) thickness measurement provided by commercially available spectral-domain optical coherence tomograph, we consider the whole 3D volume for change detection. To integrate a priori knowledge and in particular the spatial voxel dependency in the change detection map, we propose the use of the Markov Random Field to handle a such dependency. To accommodate the presence of false positive detection, the estimated change detection map is then used to classify a 3D SDOCT image into the "non-progressing" and "progressing" glaucoma classes, based on a fuzzy logic classifier. We compared the diagnostic performance of the proposed framework to existing methods of progression detection.

Quantitative Susceptibility Mapping after Sports-Related Concussion.

PubMed

Koch, K M; Meier, T B; Karr, R; Nencka, A S; Muftuler, L T; McCrea, M

2018-06-07

Quantitative susceptibility mapping using MR imaging can assess changes in brain tissue structure and composition. This report presents preliminary results demonstrating changes in tissue magnetic susceptibility after sports-related concussion. Longitudinal quantitative susceptibility mapping metrics were produced from imaging data acquired from cohorts of concussed and control football athletes. One hundred thirty-six quantitative susceptibility mapping datasets were analyzed across 3 separate visits (24 hours after injury, 8 days postinjury, and 6 months postinjury). Longitudinal quantitative susceptibility mapping group analyses were performed on stability-thresholded brain tissue compartments and selected subregions. Clinical concussion metrics were also measured longitudinally in both cohorts and compared with the measured quantitative susceptibility mapping. Statistically significant increases in white matter susceptibility were identified in the concussed athlete group during the acute (24 hour) and subacute (day 8) period. These effects were most prominent at the 8-day visit but recovered and showed no significant difference from controls at the 6-month visit. The subcortical gray matter showed no statistically significant group differences. Observed susceptibility changes after concussion appeared to outlast self-reported clinical recovery metrics at a group level. At an individual subject level, susceptibility increases within the white matter showed statistically significant correlations with return-to-play durations. The results of this preliminary investigation suggest that sports-related concussion can induce physiologic changes to brain tissue that can be detected using MR imaging-based magnetic susceptibility estimates. In group analyses, the observed tissue changes appear to persist beyond those detected on clinical outcome assessments and were associated with return-to-play duration after sports-related concussion. © 2018 by American Journal of Neuroradiology.

Mapping Sub-Antarctic Cushion Plants Using Random Forests to Combine Very High Resolution Satellite Imagery and Terrain Modelling

PubMed Central

Bricher, Phillippa K.; Lucieer, Arko; Shaw, Justine; Terauds, Aleks; Bergstrom, Dana M.

2013-01-01

Monitoring changes in the distribution and density of plant species often requires accurate and high-resolution baseline maps of those species. Detecting such change at the landscape scale is often problematic, particularly in remote areas. We examine a new technique to improve accuracy and objectivity in mapping vegetation, combining species distribution modelling and satellite image classification on a remote sub-Antarctic island. In this study, we combine spectral data from very high resolution WorldView-2 satellite imagery and terrain variables from a high resolution digital elevation model to improve mapping accuracy, in both pixel- and object-based classifications. Random forest classification was used to explore the effectiveness of these approaches on mapping the distribution of the critically endangered cushion plant Azorella macquariensis Orchard (Apiaceae) on sub-Antarctic Macquarie Island. Both pixel- and object-based classifications of the distribution of Azorella achieved very high overall validation accuracies (91.6–96.3%, κ = 0.849–0.924). Both two-class and three-class classifications were able to accurately and consistently identify the areas where Azorella was absent, indicating that these maps provide a suitable baseline for monitoring expected change in the distribution of the cushion plants. Detecting such change is critical given the threats this species is currently facing under altering environmental conditions. The method presented here has applications to monitoring a range of species, particularly in remote and isolated environments. PMID:23940805

Aerial detection surveys in the United States

Treesearch

E. W. Johnson; D. Wittwer

2006-01-01

Aerial detection surveys, also known as aerial sketchmapping, is a remote sensing technique of observing forest change events from an aircraft and documenting them manually onto a map. Data from aerial surveys have become an important component of the Forest Health Monitoring, a national program designed to determine the status, changes, and trends in indicators of...

Investigation of Raman chemical imaging for detection of Lycopene changes in tomatoes during postharvest ripening

USDA-ARS?s Scientific Manuscript database

Lycopene is a major carotenoid in tomatoes and detecting changes in lycopene content can be used to monitor the ripening of tomatoes. Raman chemical imaging is a new technique that shows promise for mapping constituents of interest in complex food matrices. In this study, a benchtop point-scanning...

Anomaly Detection for Beam Loss Maps in the Large Hadron Collider

NASA Astrophysics Data System (ADS)

Valentino, Gianluca; Bruce, Roderik; Redaelli, Stefano; Rossi, Roberto; Theodoropoulos, Panagiotis; Jaster-Merz, Sonja

2017-07-01

In the LHC, beam loss maps are used to validate collimator settings for cleaning and machine protection. This is done by monitoring the loss distribution in the ring during infrequent controlled loss map campaigns, as well as in standard operation. Due to the complexity of the system, consisting of more than 50 collimators per beam, it is difficult to identify small changes in the collimation hierarchy, which may be due to setting errors or beam orbit drifts with such methods. A technique based on Principal Component Analysis and Local Outlier Factor is presented to detect anomalies in the loss maps and therefore provide an automatic check of the collimation hierarchy.

a Method of Time-Series Change Detection Using Full Polsar Images from Different Sensors

NASA Astrophysics Data System (ADS)

Liu, W.; Yang, J.; Zhao, J.; Shi, H.; Yang, L.

2018-04-01

Most of the existing change detection methods using full polarimetric synthetic aperture radar (PolSAR) are limited to detecting change between two points in time. In this paper, a novel method was proposed to detect the change based on time-series data from different sensors. Firstly, the overall difference image of a time-series PolSAR was calculated by ominous statistic test. Secondly, difference images between any two images in different times ware acquired by Rj statistic test. Generalized Gaussian mixture model (GGMM) was used to obtain time-series change detection maps in the last step for the proposed method. To verify the effectiveness of the proposed method, we carried out the experiment of change detection by using the time-series PolSAR images acquired by Radarsat-2 and Gaofen-3 over the city of Wuhan, in China. Results show that the proposed method can detect the time-series change from different sensors.

ERS-2 SAR and IRS-1C LISS III data fusion: A PCA approach to improve remote sensing based geological interpretation

NASA Astrophysics Data System (ADS)

Pal, S. K.; Majumdar, T. J.; Bhattacharya, Amit K.

Fusion of optical and synthetic aperture radar data has been attempted in the present study for mapping of various lithologic units over a part of the Singhbhum Shear Zone (SSZ) and its surroundings. ERS-2 SAR data over the study area has been enhanced using Fast Fourier Transformation (FFT) based filtering approach, and also using Frost filtering technique. Both the enhanced SAR imagery have been then separately fused with histogram equalized IRS-1C LISS III image using Principal Component Analysis (PCA) technique. Later, Feature-oriented Principal Components Selection (FPCS) technique has been applied to generate False Color Composite (FCC) images, from which corresponding geological maps have been prepared. Finally, GIS techniques have been successfully used for change detection analysis in the lithological interpretation between the published geological map and the fusion based geological maps. In general, there is good agreement between these maps over a large portion of the study area. Based on the change detection studies, few areas could be identified which need attention for further detailed ground-based geological studies.

Adjusting the specificity of an engine map based on the sensitivity of an engine control parameter relative to a performance variable

DOEpatents

Jiang, Li; Lee, Donghoon; Yilmaz, Hakan; Stefanopoulou, Anna

2014-10-28

Methods and systems for engine control optimization are provided. A first and a second operating condition of a vehicle engine are detected. An initial value is identified for a first and a second engine control parameter corresponding to a combination of the detected operating conditions according to a first and a second engine map look-up table. The initial values for the engine control parameters are adjusted based on a detected engine performance variable to cause the engine performance variable to approach a target value. A first and a second sensitivity of the engine performance variable are determined in response to changes in the engine control parameters. The first engine map look-up table is adjusted when the first sensitivity is greater than a threshold, and the second engine map look-up table is adjusted when the second sensitivity is greater than a threshold.

Mapping Changes and Damages in Areas of Conflict: From Archive C-Band SAR Data to New HR X-Band Imagery, Towards the Sentinels

NASA Astrophysics Data System (ADS)

Tapete, Deodato; Cigna, Francesca; Donoghue, Daniel N. M.; Philip, Graham

2015-05-01

On the turn of radar space science with the recent launch of Sentinel-1A, we investigate how to better exploit the opportunities offered by large C-band SAR archives and increasing datasets of HR to VHR X-band data, to map changes and damages in urban and rural areas affected by conflicts. We implement a dual approach coupling multi-interferogram processing and amplitude change detection, to assess the impact of the recent civil war on the city of Homs, Western Syria, and the surrounding semi-arid landscape. More than 280,000 coherent pixels are retrieved from Small BAseline Subset (SBAS) processing of the 8year-long ENVISAT ASAR IS2 archive, to quantify land subsidence due to pre-war water abstraction in rural areas. Damages in Homs are detected by analysing the changes of SAR backscattering (σ0), comparing 3m-resolution StripMap TerraSAR-X pairs from 2009 to 2014. Pre-war alteration is differentiated from war-related damages via operator-driven interpretation of the σ0 patterns.

Detecting changes in student teachers' conceptions of teaching science to adolescent English language learners

NASA Astrophysics Data System (ADS)

Pomeroy, Jonathon Richard

2000-10-01

This research study investigated the changes that occurred in six student teachers' conceptions of teaching science to adolescent English language learners over the duration of their participation in a one-year, graduate level, science teacher education program. Cases were created for each of the student teachers based on their concept maps, writing samples, interviews, lesson plans, informal interviews with cooperating teachers, and observation notes collected on biweekly visitations. The cases were divided into three dyads each consisting of two student teachers with similar preprogram and student teaching experiences. Cross case analysis revealed the existence of seven themes related to teaching science to adolescent English language learners. Further analysis suggested that student teachers that worked with experienced cooperating teachers and who had achieved a sense of autonomy over their student teaching demonstrated broad and sophisticated growth across all seven themes. Student teachers who had not achieved a sense of autonomy, demonstrated growth in two to three themes. Student teachers who demonstrated broad and sophisticated growth were able to clearly articulate their conceptions of teaching science to English language learners where as those who demonstrated limited growth were not. This research establishes the use of concept maps as a tool for detecting changes in student teachers' conceptions of teaching science to adolescent English language learners as well as the sensitivity of concept maps to detect the types of changes historically detected by writing samples and interviews. Recommendations based on the implications from are included.

Artificial-epitope mapping for CK-MB assay.

PubMed

Tai, Dar-Fu; Ho, Yi-Fang; Wu, Cheng-Hsin; Lin, Tzu-Chieh; Lu, Kuo-Hao; Lin, Kun-Shian

2011-06-07

A quantitative method using artificial antibody to detect creatine kinases was developed. Linear epitope sequences were selected based on an artificial-epitope mapping strategy. Nine different MIPs corresponding to the selected peptides were then fabricated on QCM chips. The subtle conformational changes were also recognized by these chips.

Web Based Rapid Mapping of Disaster Areas using Satellite Images, Web Processing Service, Web Mapping Service, Frequency Based Change Detection Algorithm and J-iView

NASA Astrophysics Data System (ADS)

Bandibas, J. C.; Takarada, S.

2013-12-01

Timely identification of areas affected by natural disasters is very important for a successful rescue and effective emergency relief efforts. This research focuses on the development of a cost effective and efficient system of identifying areas affected by natural disasters, and the efficient distribution of the information. The developed system is composed of 3 modules which are the Web Processing Service (WPS), Web Map Service (WMS) and the user interface provided by J-iView (fig. 1). WPS is an online system that provides computation, storage and data access services. In this study, the WPS module provides online access of the software implementing the developed frequency based change detection algorithm for the identification of areas affected by natural disasters. It also sends requests to WMS servers to get the remotely sensed data to be used in the computation. WMS is a standard protocol that provides a simple HTTP interface for requesting geo-registered map images from one or more geospatial databases. In this research, the WMS component provides remote access of the satellite images which are used as inputs for land cover change detection. The user interface in this system is provided by J-iView, which is an online mapping system developed at the Geological Survey of Japan (GSJ). The 3 modules are seamlessly integrated into a single package using J-iView, which could rapidly generate a map of disaster areas that is instantaneously viewable online. The developed system was tested using ASTER images covering the areas damaged by the March 11, 2011 tsunami in northeastern Japan. The developed system efficiently generated a map showing areas devastated by the tsunami. Based on the initial results of the study, the developed system proved to be a useful tool for emergency workers to quickly identify areas affected by natural disasters.

Land use mapping and modelling for the Phoenix Quadrangle

NASA Technical Reports Server (NTRS)

Place, J. L. (Principal Investigator)

1973-01-01

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

Change in land use in the Phoenix (1:250,000) Quadrangle, Arizona between 1970 and 1973: ERTS as an aid in a nationwide program for mapping general land use. [Phoenix Quadrangle, Arizona

NASA Technical Reports Server (NTRS)

Place, J. L.

1974-01-01

Changes in land use between 1970 and 1973 in the Phoenix (1:250,000 scale) Quadrangle in Arizona have been mapped using only the images from ERTS-1, tending to verify the utility of a standard land use classification system proposed for use with ERTS images. Types of changes detected have been: (1) new residential development of former cropland and rangeland; (2) new cropland from the desert; and (3) new reservoir fill-up. The seasonal changing of vegetation patterns in ERTS has complemented air photos in delimiting the boundaries of some land use types. ERTS images, in combination with other sources of information, can assist in mapping the generalized land use of the fifty states by the standard 1:250,000 quadrangles. Several states are already working cooperatively in this type of mapping.

USGS lidar science strategy—Mapping the technology to the science

USGS Publications Warehouse

Stoker, Jason M.; Brock, John C.; Soulard, Christopher E.; Ries, Kernell G.; Sugarbaker, Larry J.; Newton, Wesley E.; Haggerty, Patricia K.; Lee, Kathy E.; Young, John A.

2016-01-11

The U.S. Geological Survey (USGS) utilizes light detection and ranging (lidar) and enabling technologies to support many science research activities. Lidar-derived metrics and products have become a fundamental input to complex hydrologic and hydraulic models, flood inundation models, fault detection and geologic mapping, topographic and land-surface mapping, landslide and volcano hazards mapping and monitoring, forest canopy and habitat characterization, coastal and fluvial erosion mapping, and a host of other research and operational activities. This report documents the types of lidar being used by the USGS, discusses how lidar technology facilitates the achievement of individual mission area goals within the USGS, and offers recommendations and suggested changes in direction in terms of how a mission area could direct work using lidar as it relates to the mission area goals that have already been established.

Vegetation mapping from ERTS imagery of the Okavango Delta. [Botswana

NASA Technical Reports Server (NTRS)

Willamson, D. T.

1974-01-01

The Okavango is Botswana's major water resource. The present study has been specifically directed at mapping vegetation types within the delta and generally concerned with finding what information of value to plant and animal ecologists could be extracted from the imagery. To date it has been found that. (1) It is possible to map broad vegetation types from the imagery. (2) Imagery of the delta records the state of the system in a manner which will facilitate long-term studies of plant succession. (3) Phenological events can be detected. (4) The imagery can be used to detect and map wild fires. This will be useful in determining the role of fire in the ecology of the region. Using the imagery it is thus possible to map existing vegetation and monitor both short and long-term changes.

Baroreflex dysfunction in sick newborns makes heart rate an unreliable surrogate for blood pressure changes.

PubMed

Govindan, Rathinaswamy B; Al-Shargabi, Tareq; Massaro, An N; Metzler, Marina; Andescavage, Nickie N; Joshi, Radhika; Dave, Rhiya; du Plessis, Adre

2016-06-01

Cerebral pressure passivity (CPP) in sick newborns can be detected by evaluating coupling between mean arterial pressure (MAP) and cerebral blood flow measured by near infra-red spectroscopy hemoglobin difference (HbD). However, continuous MAP monitoring requires invasive catheterization with its inherent risks. We tested whether heart rate (HR) could serve as a reliable surrogate for MAP in the detection of CPP in sick newborns. Continuous measurements of MAP, HR, and HbD were made and partitioned into 10-min epochs. Spectral coherence (COH) was computed between MAP and HbD (COHMAP-HbD) to detect CPP, between HR and HbD (COHHR-HbD) for comparison, and between MAP and HR (COHMAP-HR) to quantify baroreflex function (BRF). The agreement between COHMAP-HbD and COHHR-HbD was assessed using ROC analysis. We found poor agreement between COHMAP-HbD and COHHR-HbD in left hemisphere (area under the ROC curve (AUC) 0.68) and right hemisphere (AUC 0.71). Baroreflex failure (COHMAP-HR not significant) was present in 79% of epochs. Confining comparison to epochs with intact BRF showed an AUC of 0.85 for both hemispheres. In these sick newborns, HR was an unreliable surrogate for MAP required for the detection of CPP. This is likely due to the prevalence of BRF failure in these infants.

Probabilistic change mapping from airborne LiDAR for post-disaster damage assessment

NASA Astrophysics Data System (ADS)

Jalobeanu, A.; Runyon, S. C.; Kruse, F. A.

2013-12-01

When both pre- and post-event LiDAR point clouds are available, change detection can be performed to identify areas that were most affected by a disaster event, and to obtain a map of quantitative changes in terms of height differences. In the case of earthquakes in built-up areas for instance, first responders can use a LiDAR change map to help prioritize search and recovery efforts. The main challenge consists of producing reliable change maps, robust to collection conditions, free of processing artifacts (due for instance to triangulation or gridding), and taking into account the various sources of uncertainty. Indeed, datasets acquired within a few years interval are often of different point density (sometimes an order of magnitude higher for recent data), different acquisition geometries, and very likely suffer from georeferencing errors and geometric discrepancies. All these differences might not be important for producing maps from each dataset separately, but they are crucial when performing change detection. We have developed a novel technique for the estimation of uncertainty maps from the LiDAR point clouds, using Bayesian inference, treating all variables as random. The main principle is to grid all points on a common grid before attempting any comparison, as working directly with point clouds is cumbersome and time consuming. A non-parametric approach based on local linear regression was implemented, assuming a locally linear model for the surface. This enabled us to derive error bars on gridded elevations, and then elevation differences. In this way, a map of statistically significant changes could be computed - whereas a deterministic approach would not allow testing of the significance of differences between the two datasets. This approach allowed us to take into account not only the observation noise (due to ranging, position and attitude errors) but also the intrinsic roughness of the observed surfaces occurring when scanning vegetation. As only elevation differences above a predefined noise level are accounted for (according to a specified confidence interval related to the allowable false alarm rate) the change detection is robust to all these sources of noise. To first validate the approach, we built small-scale models and scanned them using a terrestrial laser scanner to establish 'ground truth'. Changes were manually applied to the models then new scans were performed and analyzed. Additionally, two airborne datasets of the Monterey Peninsula, California, were processed and analyzed. The first one was acquired during 2010 (with relatively low point density, 1-3 pts/m2), and the second one was acquired during 2012 (with up to 30 pts/m2). To perform the comparison, a new point cloud registration technique was developed and the data were registered to a common 1 m grid. The goal was to correct systematic shifts due to GPS and INS errors, and focus on the actual height differences regardless of the absolute planimetric accuracy of the datasets. Though no major disaster event occurred between the two acquisition dates, sparse changes were detected and interpreted mostly as construction and natural landscape evolution.

A Spectral Mapping Signature for the Rapid Ohia Death (ROD) Pathogen in Hawaiian Forests

USDA-ARS?s Scientific Manuscript database

Pathogenic invasions are a major disruptive source of change in both agricultural and natural ecosystems. In forests, fungal pathogens can kill habitat-generating plant species such as canopy trees, but methods for remote detection, mapping and monitoring of such outbreaks are poorly developed. Cera...

Using adversary text to detect adversary phase changes.

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

Speed, Ann Elizabeth; Doser, Adele Beatrice; Warrender, Christina E.

2009-05-01

The purpose of this work was to help develop a research roadmap and small proof ofconcept for addressing key problems and gaps from the perspective of using text analysis methods as a primary tool for detecting when a group is undergoing a phase change. Self- rganizing map (SOM) techniques were used to analyze text data obtained from the tworld-wide web. Statistical studies indicate that it may be possible to predict phase changes, as well as detect whether or not an example of writing can be attributed to a group of interest.

Repeated mapping of cortical language sites by preoperative navigated transcranial magnetic stimulation compared to repeated intraoperative DCS mapping in awake craniotomy

PubMed Central

2014-01-01

Background Repetitive navigated transcranial magnetic stimulation (rTMS) was recently described for mapping of human language areas. However, its capability of detecting language plasticity in brain tumor patients was not proven up to now. Thus, this study was designed to evaluate such data in order to compare rTMS language mapping to language mapping during repeated awake surgery during follow-up in patients suffering from language-eloquent gliomas. Methods Three right-handed patients with left-sided gliomas (2 opercular glioblastomas, 1 astrocytoma WHO grade III of the angular gyrus) underwent preoperative language mapping by rTMS as well as intraoperative language mapping provided via direct cortical stimulation (DCS) for initial as well as for repeated Resection 7, 10, and 15 months later. Results Overall, preoperative rTMS was able to elicit clear language errors in all mappings. A good correlation between initial rTMS and DCS results was observed. As a consequence of brain plasticity, initial DCS and rTMS findings only corresponded with the results obtained during the second examination in one out of three patients thus suggesting changes of language organization in two of our three patients. Conclusions This report points out the usefulness but also the limitations of preoperative rTMS language mapping to detect plastic changes in language function or for long-term follow-up prior to DCS even in recurrent gliomas. However, DCS still has to be regarded as gold standard. PMID:24479694

Correlation-based perfusion mapping using time-resolved MR angiography: A feasibility study for patients with suspicions of steno-occlusive craniocervical arteries.

PubMed

Nam, Yoonho; Jang, Jinhee; Park, Sonya Youngju; Choi, Hyun Seok; Jung, So-Lyung; Ahn, Kook-Jin; Kim, Bum-Soo

2018-05-22

To explore the feasibility of using correlation-based time-delay (CTD) maps produced from time-resolved MR angiography (TRMRA) to diagnose perfusion abnormalities in patients suspected to have steno-occlusive lesions in the craniocervical arteries. Twenty-seven patients who were suspected to have steno-occlusive lesions in the craniocervical arteries underwent both TRMRA and brain single-photon emission computed tomography (SPECT). TRMRA was performed on the supra-aortic area after intravenous injection of a 0.03 mmol/kg gadolinium-based contrast agent. Time-to-peak (TTP) maps and CTD maps of the brain were automatically generated from TRMRA data, and their quality was assessed. Detection of perfusion abnormalities was compared between CTD maps and the time-series maximal intensity projection (MIP) images from TRMRA and TTP maps. Correlation coefficients between quantitative changes in SPECT and parametric maps for the abnormal perfusion areas were calculated. The CTD maps were of significantly superior quality than TTP maps (p < 0.01). For perfusion abnormality detection, CTD maps (kappa 0.84, 95% confidence interval [CI] 0.67-1.00) showed better agreement with SPECT than TTP maps (0.66, 0.46-0.85). For perfusion deficit detection, CTD maps showed higher accuracy (85.2%, 95% CI 66.3-95.8) than MIP images (66.7%, 46-83.5), with marginal significance (p = 0.07). In abnormal perfusion areas, correlation coefficients between SPECT and CTD (r = 0.74, 95% CI 0.34-0.91) were higher than those between SPECT and TTP (r = 0.66, 0.20-0.88). CTD maps generated from TRMRA were of high quality and offered good diagnostic performance for detecting perfusion abnormalities associated with steno-occlusive arterial lesions in the craniocervical area. • Generation of perfusion parametric maps from time-resolved MR angiography is clinically useful. • Correlation-based delay maps can be used to detect perfusion abnormalities associated with steno-occlusive craniocervical arteries. • Estimation of correlation-based delay is robust for low signal-to-noise 4D MR data.

Automatic spatiotemporal matching of detected pleural thickenings

NASA Astrophysics Data System (ADS)

Chaisaowong, Kraisorn; Keller, Simon Kai; Kraus, Thomas

2014-01-01

Pleural thickenings can be found in asbestos exposed patient's lung. Non-invasive diagnosis including CT imaging can detect aggressive malignant pleural mesothelioma in its early stage. In order to create a quantitative documentation of automatic detected pleural thickenings over time, the differences in volume and thickness of the detected thickenings have to be calculated. Physicians usually estimate the change of each thickening via visual comparison which provides neither quantitative nor qualitative measures. In this work, automatic spatiotemporal matching techniques of the detected pleural thickenings at two points of time based on the semi-automatic registration have been developed, implemented, and tested so that the same thickening can be compared fully automatically. As result, the application of the mapping technique using the principal components analysis turns out to be advantageous than the feature-based mapping using centroid and mean Hounsfield Units of each thickening, since the resulting sensitivity was improved to 98.46% from 42.19%, while the accuracy of feature-based mapping is only slightly higher (84.38% to 76.19%).

Mapping DNA Methylation with High Throughput Nanopore Sequencing

PubMed Central

Rand, Arthur C.; Jain, Miten; Eizenga, Jordan M.; Musselman-Brown, Audrey; Olsen, Hugh E.; Akeson, Mark

2017-01-01

Chemical modifications to DNA regulate its biological function. We present a framework for mapping methylation to cytosine and adenosine with the Oxford Nanopore Technologies MinION using its ionic current signal. We map three cytosine variants and two adenine variants. The results show that our model is sensitive enough to detect changes in genomic DNA methylation levels as a function of growth phase in E. coli. PMID:28218897

Focal Cortical Dysplasia (FCD) lesion analysis with complex diffusion approach.

PubMed

Rajan, Jeny; Kannan, K; Kesavadas, C; Thomas, Bejoy

2009-10-01

Identification of Focal Cortical Dysplasia (FCD) can be difficult due to the subtle MRI changes. Though sequences like FLAIR (fluid attenuated inversion recovery) can detect a large majority of these lesions, there are smaller lesions without signal changes that can easily go unnoticed by the naked eye. The aim of this study is to improve the visibility of focal cortical dysplasia lesions in the T1 weighted brain MRI images. In the proposed method, we used a complex diffusion based approach for calculating the FCD affected areas. Based on the diffused image and thickness map, a complex map is created. From this complex map; FCD areas can be easily identified. MRI brains of 48 subjects selected by neuroradiologists were given to computer scientists who developed the complex map for identifying the cortical dysplasia. The scientists were blinded to the MRI interpretation result of the neuroradiologist. The FCD could be identified in all the patients in whom surgery was done, however three patients had false positive lesions. More lesions were identified in patients in whom surgery was not performed and lesions were seen in few of the controls. These were considered as false positive. This computer aided detection technique using complex diffusion approach can help detect focal cortical dysplasia in patients with epilepsy.

UAS close range remote sensing for mapping coastal environments

NASA Astrophysics Data System (ADS)

Papakonstantinou, Apostolos; Topouzelis, Kostantinos; Doukari, Michaela

2017-09-01

Coastline change and marine litter concentration in shoreline zones are two different emerging problems indicating the vulnerability as well as the quality of a coastal environment. Both problems present spatiotemporal changes due to weather and anthropogenic factors. Traditionally spatiotemporal changes in coastal environments are monitored using high-resolution satellite images and manned surveys. The last years, Unmanned Aerial Systems (UAS) are used as additional tool for monitoring environmental phenomena in sensitive coastal areas. In this study, two different case studies for mapping emerging coastal phenomena i.e. coastline changes and marine litter in Lesvos island, are presented. Both phenomena have increasing interest among scientists monitoring sensitive coastal areas. This paper outlines the integration of UAS for data acquisition and Structure from Motion (SfM) pipeline for the visualization of selected coastal areas in the Aegean Sea. The followed UAS-SfM methodology produces very detailed orthophoto maps. This high resolution spatial information is used for mapping and detecting primarily, marine litter on coastal and underwater zones and secondly, coastline changes and coastal erosion. More specific the produced orthophoto maps analyzed through GIS and with the use of the appropriate cartographic techniques the objective environmental parameters were mapped. Results showed that UAS-SfM pipeline produces geoinformation with high accuracy and spatial resolution that helps scientists to map with confidence environmental changes that take place in shoreline zones.

fMRI brain mapping during motion capture and FES induced motor tasks: signal to noise ratio assessment.

PubMed

Gandolla, Marta; Ferrante, Simona; Casellato, Claudia; Ferrigno, Giancarlo; Molteni, Franco; Martegani, Alberto; Frattini, Tiziano; Pedrocchi, Alessandra

2011-10-01

Functional Electrical Stimulation (FES) is a well known clinical rehabilitation procedure, however the neural mechanisms that underlie this treatment at Central Nervous System (CNS) level are still not completely understood. Functional magnetic resonance imaging (fMRI) is a suitable tool to investigate effects of rehabilitative treatments on brain plasticity. Moreover, monitoring the effective executed movement is needed to correctly interpret activation maps, most of all in neurological patients where required motor tasks could be only partially accomplished. The proposed experimental set-up includes a 1.5 T fMRI scanner, a motion capture system to acquire kinematic data, and an electro-stimulation device. The introduction of metallic devices and of stimulation current in the MRI room could affect fMRI acquisitions so as to prevent a reliable activation maps analysis. What we are interested in is that the Blood Oxygenation Level Dependent (BOLD) signal, marker of neural activity, could be detected within a given experimental condition and set-up. In this paper we assess temporal Signal to Noise Ratio (SNR) as image quality index. BOLD signal change is about 1-2% as revealed by a 1.5 T scanner. This work demonstrates that, with this innovative set-up, in the main cortical sensorimotor regions 1% BOLD signal change can be detected at least in the 93% of the sub-volumes, and almost 100% of the sub-volumes are suitable for 2% signal change detection. The integrated experimental set-up will therefore allows to detect FES induced movements fMRI maps simultaneously with kinematic acquisitions so as to investigate FES-based rehabilitation treatments contribution at CNS level. Copyright © 2011 IPEM. Published by Elsevier Ltd. All rights reserved.

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

NASA Astrophysics Data System (ADS)

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

2017-04-01

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

Integration of Landsat TM and SPOT HRG Images for Vegetation Change Detection in the Brazilian Amazon

PubMed Central

Lu, Dengsheng; Batistella, Mateus; Moran, Emilio

2009-01-01

Traditional change detection approaches have been proven to be difficult in detecting vegetation changes in the moist tropical regions with multitemporal images. This paper explores the integration of Landsat Thematic Mapper (TM) and SPOT High Resolution Geometric (HRG) instrument data for vegetation change detection in the Brazilian Amazon. A principal component analysis was used to integrate TM and HRG panchromatic data. Vegetation change/non-change was detected with the image differencing approach based on the TM and HRG fused image and the corresponding TM image. A rule-based approach was used to classify the TM and HRG multispectral images into thematic maps with three coarse land-cover classes: forest, non-forest vegetation, and non-vegetation lands. A hybrid approach combining image differencing and post-classification comparison was used to detect vegetation change trajectories. This research indicates promising vegetation change techniques, especially for vegetation gain and loss, even if very limited reference data are available. PMID:19789721

Subtracting the sequence bias from partially digested MNase-seq data reveals a general contribution of TFIIS to nucleosome positioning.

PubMed

Gutiérrez, Gabriel; Millán-Zambrano, Gonzalo; Medina, Daniel A; Jordán-Pla, Antonio; Pérez-Ortín, José E; Peñate, Xenia; Chávez, Sebastián

2017-12-07

TFIIS stimulates RNA cleavage by RNA polymerase II and promotes the resolution of backtracking events. TFIIS acts in the chromatin context, but its contribution to the chromatin landscape has not yet been investigated. Co-transcriptional chromatin alterations include subtle changes in nucleosome positioning, like those expected to be elicited by TFIIS, which are elusive to detect. The most popular method to map nucleosomes involves intensive chromatin digestion by micrococcal nuclease (MNase). Maps based on these exhaustively digested samples miss any MNase-sensitive nucleosomes caused by transcription. In contrast, partial digestion approaches preserve such nucleosomes, but introduce noise due to MNase sequence preferences. A systematic way of correcting this bias for massively parallel sequencing experiments is still missing. To investigate the contribution of TFIIS to the chromatin landscape, we developed a refined nucleosome-mapping method in Saccharomyces cerevisiae. Based on partial MNase digestion and a sequence-bias correction derived from naked DNA cleavage, the refined method efficiently mapped nucleosomes in promoter regions rich in MNase-sensitive structures. The naked DNA correction was also important for mapping gene body nucleosomes, particularly in those genes whose core promoters contain a canonical TATA element. With this improved method, we analyzed the global nucleosomal changes caused by lack of TFIIS. We detected a general increase in nucleosomal fuzziness and more restricted changes in nucleosome occupancy, which concentrated in some gene categories. The TATA-containing genes were preferentially associated with decreased occupancy in gene bodies, whereas the TATA-like genes did so with increased fuzziness. The detected chromatin alterations correlated with functional defects in nascent transcription, as revealed by genomic run-on experiments. The combination of partial MNase digestion and naked DNA correction of the sequence bias is a precise nucleosomal mapping method that does not exclude MNase-sensitive nucleosomes. This method is useful for detecting subtle alterations in nucleosome positioning produced by lack of TFIIS. Their analysis revealed that TFIIS generally contributed to nucleosome positioning in both gene promoters and bodies. The independent effect of lack of TFIIS on nucleosome occupancy and fuzziness supports the existence of alternative chromatin dynamics during transcription elongation.

Color is processed less efficiently than orientation in change detection but more efficiently in visual search.

PubMed

Huang, Liqiang

2015-05-01

Basic visual features (e.g., color, orientation) are assumed to be processed in the same general way across different visual tasks. Here, a significant deviation from this assumption was predicted on the basis of the analysis of stimulus spatial structure, as characterized by the Boolean-map notion. If a task requires memorizing the orientations of a set of bars, then the map consisting of those bars can be readily used to hold the overall structure in memory and will thus be especially useful. If the task requires visual search for a target, then the map, which contains only an overall structure, will be of little use. Supporting these predictions, the present study demonstrated that in comparison to stimulus colors, bar orientations were processed more efficiently in change-detection tasks but less efficiently in visual search tasks (Cohen's d = 4.24). In addition to offering support for the role of the Boolean map in conscious access, the present work also throws doubts on the generality of processing visual features. © The Author(s) 2015.

Differential screening and mass mapping of proteins from premalignant and cancer cell lines using nonporous reversed-phase HPLC coupled with mass spectrometric analysis.

PubMed

Chong, B E; Hamler, R L; Lubman, D M; Ethier, S P; Rosenspire, A J; Miller, F R

2001-03-15

Nonporous (NPS) RP-HPLC has been used to rapidly separate proteins from whole cell lysates of human breast cell lines. The nonporous separation involves the use of hard-sphere silica beads of 1.5-microm diameter coated with C18, which can be used to separate proteins ranging from 5 to 90 kDa. Using only 30-40 microg of total protein, the protein molecular weights are detectable on-line using an ESI-oaTOF MS. Of hundreds of proteins detected in this mass range, approxinately 75-80 are more highly expressed. The molecular weight profiles can be displayed as a mass map analogous to a virtual "1-D gel" and differentially expressed proteins can be compared by image analysis. The separated proteins can also be detected by UV absorption and differentially expressed proteins quantified. The eluting proteins can be collected in the liquid phase and the molecular weight and peptide maps determined by MALDI-TOF MS for identification. It is demonstrated that the expressed protein profiles change during neoplastic progression and that many oncoproteins are readily detected. It is also shown that the response of premalignant cancer cells to estradiol can be rapidly screened by this method, demonstrating significant changes in response to an external agent. Ultimately, the proteins can be studied by peptide mapping to search for posttranslational modifications of the oncoproteins accompanying progression.

A Practical and Automated Approach to Large Area Forest Disturbance Mapping with Remote Sensing

PubMed Central

Ozdogan, Mutlu

2014-01-01

In this paper, I describe a set of procedures that automate forest disturbance mapping using a pair of Landsat images. The approach is built on the traditional pair-wise change detection method, but is designed to extract training data without user interaction and uses a robust classification algorithm capable of handling incorrectly labeled training data. The steps in this procedure include: i) creating masks for water, non-forested areas, clouds, and cloud shadows; ii) identifying training pixels whose value is above or below a threshold defined by the number of standard deviations from the mean value of the histograms generated from local windows in the short-wave infrared (SWIR) difference image; iii) filtering the original training data through a number of classification algorithms using an n-fold cross validation to eliminate mislabeled training samples; and finally, iv) mapping forest disturbance using a supervised classification algorithm. When applied to 17 Landsat footprints across the U.S. at five-year intervals between 1985 and 2010, the proposed approach produced forest disturbance maps with 80 to 95% overall accuracy, comparable to those obtained from traditional approaches to forest change detection. The primary sources of mis-classification errors included inaccurate identification of forests (errors of commission), issues related to the land/water mask, and clouds and cloud shadows missed during image screening. The approach requires images from the peak growing season, at least for the deciduous forest sites, and cannot readily distinguish forest harvest from natural disturbances or other types of land cover change. The accuracy of detecting forest disturbance diminishes with the number of years between the images that make up the image pair. Nevertheless, the relatively high accuracies, little or no user input needed for processing, speed of map production, and simplicity of the approach make the new method especially practical for forest cover change analysis over very large regions. PMID:24717283

A practical and automated approach to large area forest disturbance mapping with remote sensing.

PubMed

Ozdogan, Mutlu

2014-01-01

In this paper, I describe a set of procedures that automate forest disturbance mapping using a pair of Landsat images. The approach is built on the traditional pair-wise change detection method, but is designed to extract training data without user interaction and uses a robust classification algorithm capable of handling incorrectly labeled training data. The steps in this procedure include: i) creating masks for water, non-forested areas, clouds, and cloud shadows; ii) identifying training pixels whose value is above or below a threshold defined by the number of standard deviations from the mean value of the histograms generated from local windows in the short-wave infrared (SWIR) difference image; iii) filtering the original training data through a number of classification algorithms using an n-fold cross validation to eliminate mislabeled training samples; and finally, iv) mapping forest disturbance using a supervised classification algorithm. When applied to 17 Landsat footprints across the U.S. at five-year intervals between 1985 and 2010, the proposed approach produced forest disturbance maps with 80 to 95% overall accuracy, comparable to those obtained from traditional approaches to forest change detection. The primary sources of mis-classification errors included inaccurate identification of forests (errors of commission), issues related to the land/water mask, and clouds and cloud shadows missed during image screening. The approach requires images from the peak growing season, at least for the deciduous forest sites, and cannot readily distinguish forest harvest from natural disturbances or other types of land cover change. The accuracy of detecting forest disturbance diminishes with the number of years between the images that make up the image pair. Nevertheless, the relatively high accuracies, little or no user input needed for processing, speed of map production, and simplicity of the approach make the new method especially practical for forest cover change analysis over very large regions.

Land cover mapping after the tsunami event over Nanggroe Aceh Darussalam (NAD) province, Indonesia

NASA Astrophysics Data System (ADS)

Lim, H. S.; MatJafri, M. Z.; Abdullah, K.; Alias, A. N.; Mohd. Saleh, N.; Wong, C. J.; Surbakti, M. S.

2008-03-01

Remote sensing offers an important means of detecting and analyzing temporal changes occurring in our landscape. This research used remote sensing to quantify land use/land cover changes at the Nanggroe Aceh Darussalam (Nad) province, Indonesia on a regional scale. The objective of this paper is to assess the changed produced from the analysis of Landsat TM data. A Landsat TM image was used to develop land cover classification map for the 27 March 2005. Four supervised classifications techniques (Maximum Likelihood, Minimum Distance-to- Mean, Parallelepiped and Parallelepiped with Maximum Likelihood Classifier Tiebreaker classifier) were performed to the satellite image. Training sites and accuracy assessment were needed for supervised classification techniques. The training sites were established using polygons based on the colour image. High detection accuracy (>80%) and overall Kappa (>0.80) were achieved by the Parallelepiped with Maximum Likelihood Classifier Tiebreaker classifier in this study. This preliminary study has produced a promising result. This indicates that land cover mapping can be carried out using remote sensing classification method of the satellite digital imagery.

Upgraded airborne scanner for commercial remote sensing

NASA Astrophysics Data System (ADS)

Chang, Sheng-Huei; Rubin, Tod D.

1994-06-01

Traditional commercial remote sensing has focused on the geologic market, with primary focus on mineral identification and mapping in the visible through short-wave infrared spectral regions (0.4 to 2.4 microns). Commercial remote sensing users now demand airborne scanning capabilities spanning the entire wavelength range from ultraviolet through thermal infrared (0.3 to 12 microns). This spectral range enables detection, identification, and mapping of objects and liquids on the earth's surface and gases in the air. Applications requiring this range of wavelengths include detection and mapping of oil spills, soil and water contamination, stressed vegetation, and renewable and non-renewable natural resources, and also change detection, natural hazard mitigation, emergency response, agricultural management, and urban planning. GER has designed and built a configurable scanner that acquires high resolution images in 63 selected wave bands in this broad wavelength range.

Potential for Monitoring Snow Cover in Boreal Forests by Combining MODIS Snow Cover and AMSR-E SWE Maps

NASA Technical Reports Server (NTRS)

Riggs, George A.; Hall, Dorothy K.; Foster, James L.

2009-01-01

Monitoring of snow cover extent and snow water equivalent (SWE) in boreal forests is important for determining the amount of potential runoff and beginning date of snowmelt. The great expanse of the boreal forest necessitates the use of satellite measurements to monitor snow cover. Snow cover in the boreal forest can be mapped with either the Moderate Resolution Imaging Spectroradiometer (MODIS) or the Advanced Microwave Scanning Radiometer for EOS (AMSR-E) microwave instrument. The extent of snow cover is estimated from the MODIS data and SWE is estimated from the AMSR-E. Environmental limitations affect both sensors in different ways to limit their ability to detect snow in some situations. Forest density, snow wetness, and snow depth are factors that limit the effectiveness of both sensors for snow detection. Cloud cover is a significant hindrance to monitoring snow cover extent Using MODIS but is not a hindrance to the use of the AMSR-E. These limitations could be mitigated by combining MODIS and AMSR-E data to allow for improved interpretation of snow cover extent and SWE on a daily basis and provide temporal continuity of snow mapping across the boreal forest regions in Canada. The purpose of this study is to investigate if temporal monitoring of snow cover using a combination of MODIS and AMSR-E data could yield a better interpretation of changing snow cover conditions. The MODIS snow mapping algorithm is based on snow detection using the Normalized Difference Snow Index (NDSI) and the Normalized Difference Vegetation Index (NDVI) to enhance snow detection in dense vegetation. (Other spectral threshold tests are also used to map snow using MODIS.) Snow cover under a forest canopy may have an effect on the NDVI thus we use the NDVI in snow detection. A MODIS snow fraction product is also generated but not used in this study. In this study the NDSI and NDVI components of the snow mapping algorithm were calculated and analyzed to determine how they changed through the seasons. A blended snow product, the Air Force Weather Agency and NASA (ANSA) snow algorithm and product has recently been developed. The ANSA algorithm blends the MODIS snow cover and AMSR-E SWE products into a single snow product that has been shown to improve the performance of snow cover mapping. In this study components of the ANSA snow algorithm are used along with additional MODIS data to monitor daily changes in snow cover over the period of 1 February to 30 June 2008.

The Application of Remote Sensing Data to GIS Studies of Land Use, Land Cover, and Vegetation Mapping in the State of Hawaii

NASA Technical Reports Server (NTRS)

Hogan, Christine A.

1996-01-01

A land cover-vegetation map with a base classification system for remote sensing use in a tropical island environment was produced of the island of Hawaii for the State of Hawaii to evaluate whether or not useful land cover information can be derived from Landsat TM data. In addition, an island-wide change detection mosaic combining a previously created 1977 MSS land classification with the TM-based classification was produced. In order to reach the goal of transferring remote sensing technology to State of Hawaii personnel, a pilot project was conducted while training State of Hawaii personnel in remote sensing technology and classification systems. Spectral characteristics of young island land cover types were compared to determine if there are differences in vegetation types on lava, vegetation types on soils, and barren lava from soils, and if they can be detected remotely, based on differences in pigments detecting plant physiognomic type, health, stress at senescence, heat, moisture level, and biomass. Geographic information systems (GIS) and global positioning systems (GPS) were used to assist in image rectification and classification. GIS was also used to produce large-format color output maps. An interactive GIS program was written to provide on-line access to scanned photos taken at field sites. The pilot project found Landsat TM to be a credible source of land cover information for geologically young islands, and TM data bands are effective in detecting spectral characteristics of different land cover types through remote sensing. Large agriculture field patterns were resolved and mapped successfully from wildland vegetation, but small agriculture field patterns were not. Additional processing was required to work with the four TM scenes from two separate orbits which span three years, including El Nino and drought dates. Results of the project emphasized the need for further land cover and land use processing and research. Change in vegetation composition was noted in the change detection image.

Recognizing lexical and semantic change patterns in evolving life science ontologies to inform mapping adaptation.

PubMed

Dos Reis, Julio Cesar; Dinh, Duy; Da Silveira, Marcos; Pruski, Cédric; Reynaud-Delaître, Chantal

2015-03-01

Mappings established between life science ontologies require significant efforts to maintain them up to date due to the size and frequent evolution of these ontologies. In consequence, automatic methods for applying modifications on mappings are highly demanded. The accuracy of such methods relies on the available description about the evolution of ontologies, especially regarding concepts involved in mappings. However, from one ontology version to another, a further understanding of ontology changes relevant for supporting mapping adaptation is typically lacking. This research work defines a set of change patterns at the level of concept attributes, and proposes original methods to automatically recognize instances of these patterns based on the similarity between attributes denoting the evolving concepts. This investigation evaluates the benefits of the proposed methods and the influence of the recognized change patterns to select the strategies for mapping adaptation. The summary of the findings is as follows: (1) the Precision (>60%) and Recall (>35%) achieved by comparing manually identified change patterns with the automatic ones; (2) a set of potential impact of recognized change patterns on the way mappings is adapted. We found that the detected correlations cover ∼66% of the mapping adaptation actions with a positive impact; and (3) the influence of the similarity coefficient calculated between concept attributes on the performance of the recognition algorithms. The experimental evaluations conducted with real life science ontologies showed the effectiveness of our approach to accurately characterize ontology evolution at the level of concept attributes. This investigation confirmed the relevance of the proposed change patterns to support decisions on mapping adaptation. Copyright © 2014 Elsevier B.V. All rights reserved.

Generating Impact Maps from Automatically Detected Bomb Craters in Aerial Wartime Images Using Marked Point Processes

NASA Astrophysics Data System (ADS)

Kruse, Christian; Rottensteiner, Franz; Hoberg, Thorsten; Ziems, Marcel; Rebke, Julia; Heipke, Christian

2018-04-01

The aftermath of wartime attacks is often felt long after the war ended, as numerous unexploded bombs may still exist in the ground. Typically, such areas are documented in so-called impact maps which are based on the detection of bomb craters. This paper proposes a method for the automatic detection of bomb craters in aerial wartime images that were taken during the Second World War. The object model for the bomb craters is represented by ellipses. A probabilistic approach based on marked point processes determines the most likely configuration of objects within the scene. Adding and removing new objects to and from the current configuration, respectively, changing their positions and modifying the ellipse parameters randomly creates new object configurations. Each configuration is evaluated using an energy function. High gradient magnitudes along the border of the ellipse are favored and overlapping ellipses are penalized. Reversible Jump Markov Chain Monte Carlo sampling in combination with simulated annealing provides the global energy optimum, which describes the conformance with a predefined model. For generating the impact map a probability map is defined which is created from the automatic detections via kernel density estimation. By setting a threshold, areas around the detections are classified as contaminated or uncontaminated sites, respectively. Our results show the general potential of the method for the automatic detection of bomb craters and its automated generation of an impact map in a heterogeneous image stock.

Object-based change detection method using refined Markov random field

NASA Astrophysics Data System (ADS)

Peng, Daifeng; Zhang, Yongjun

2017-01-01

In order to fully consider the local spatial constraints between neighboring objects in object-based change detection (OBCD), an OBCD approach is presented by introducing a refined Markov random field (MRF). First, two periods of images are stacked and segmented to produce image objects. Second, object spectral and textual histogram features are extracted and G-statistic is implemented to measure the distance among different histogram distributions. Meanwhile, object heterogeneity is calculated by combining spectral and textual histogram distance using adaptive weight. Third, an expectation-maximization algorithm is applied for determining the change category of each object and the initial change map is then generated. Finally, a refined change map is produced by employing the proposed refined object-based MRF method. Three experiments were conducted and compared with some state-of-the-art unsupervised OBCD methods to evaluate the effectiveness of the proposed method. Experimental results demonstrate that the proposed method obtains the highest accuracy among the methods used in this paper, which confirms its validness and effectiveness in OBCD.

Selective 4D modelling framework for spatial-temporal land information management system

NASA Astrophysics Data System (ADS)

Doulamis, Anastasios; Soile, Sofia; Doulamis, Nikolaos; Chrisouli, Christina; Grammalidis, Nikos; Dimitropoulos, Kosmas; Manesis, Charalambos; Potsiou, Chryssy; Ioannidis, Charalabos

2015-06-01

This paper introduces a predictive (selective) 4D modelling framework where only the spatial 3D differences are modelled at the forthcoming time instances, while regions of no significant spatial-temporal alterations remain intact. To accomplish this, initially spatial-temporal analysis is applied between 3D digital models captured at different time instances. So, the creation of dynamic change history maps is made. Change history maps indicate spatial probabilities of regions needed further 3D modelling at forthcoming instances. Thus, change history maps are good examples for a predictive assessment, that is, to localize surfaces within the objects where a high accuracy reconstruction process needs to be activated at the forthcoming time instances. The proposed 4D Land Information Management System (LIMS) is implemented using open interoperable standards based on the CityGML framework. CityGML allows the description of the semantic metadata information and the rights of the land resources. Visualization aspects are also supported to allow easy manipulation, interaction and representation of the 4D LIMS digital parcels and the respective semantic information. The open source 3DCityDB incorporating a PostgreSQL geo-database is used to manage and manipulate 3D data and their semantics. An application is made to detect the change through time of a 3D block of plots in an urban area of Athens, Greece. Starting with an accurate 3D model of the buildings in 1983, a change history map is created using automated dense image matching on aerial photos of 2010. For both time instances meshes are created and through their comparison the changes are detected.

High-throughput interpretation of gene structure changes in human and nonhuman resequencing data, using ACE

USDA-ARS?s Scientific Manuscript database

We describe a suite of software tools for identifying possible functional changes in gene structure that may result from sequence variants. ACE (“Assessing Changes to Exons”) converts phased genotype calls to a collection of explicit haplotype sequences, maps transcript annotations onto them, detect...

Applications of space technology to developing nations

NASA Technical Reports Server (NTRS)

Freden, S. C.

1976-01-01

The use of imagery from the Landsat spacecraft for the monitoring and management of natural resources in developing countries is discussed. The Landsat imagery can be used to make cartographic maps at scales of 1:250,000 which meet the US National Map Accuracy Standards, providing a means of map updating to correct for river meanders or changing shorelines. The Landsat data can also be used in defining and measuring agricultural areas, identifying pest breeding areas, and monitoring irrigation practices and crop performance. Total volume estimates can be obtained in many cases for surface bodies of water, and subsurface water supplies can be detected from changes in vegetation in some instances.

Evaluation of a PCR assay on overgrown environmental samples cultured for Mycobacterium avium subsp. paratuberculosis.

PubMed

Arango-Sabogal, Juan C; Labrecque, Olivia; Paré, Julie; Fairbrother, Julie-Hélène; Roy, Jean-Philippe; Wellemans, Vincent; Fecteau, Gilles

2016-11-01

Culture of Mycobacterium avium subsp. paratuberculosis (MAP) is the definitive antemortem test method for paratuberculosis. Microbial overgrowth is a challenge for MAP culture, as it complicates, delays, and increases the cost of the process. Additionally, herd status determination is impeded when noninterpretable (NI) results are obtained. The performance of PCR is comparable to fecal culture, thus it may be a complementary detection tool to classify NI samples. Our study aimed to determine if MAP DNA can be identified by PCR performed on NI environmental samples and to evaluate the performance of PCR before and after the culture of these samples in liquid media. A total of 154 environmental samples (62 NI, 62 negative, and 30 positive) were analyzed by PCR before being incubated in an automated system. Growth was confirmed by acid-fast bacilli stain and then the same PCR method was again applied on incubated samples, regardless of culture and stain results. Change in MAP DNA after incubation was assessed by converting the PCR quantification cycle (Cq) values into fold change using the 2 -ΔCq method (ΔCq = Cq after culture - Cq before culture). A total of 1.6% (standard error [SE] = 1.6) of the NI environmental samples had detectable MAP DNA. The PCR had a significantly better performance when applied after culture than before culture (p = 0.004). After culture, a 66-fold change (SE = 17.1) in MAP DNA was observed on average. Performing a PCR on NI samples improves MAP culturing. The PCR method used in our study is a reliable and consistent method to classify NI environmental samples. © 2016 The Author(s).

Detecting spatio-temporal changes in agricultural land use in Heilongjiang province, China using MODIS time-series data and a random forest regression model

NASA Astrophysics Data System (ADS)

Hu, Q.; Friedl, M. A.; Wu, W.

2017-12-01

Accurate and timely information regarding the spatial distribution of crop types and their changes is essential for acreage surveys, yield estimation, water management, and agricultural production decision-making. In recent years, increasing population, dietary shifts and climate change have driven drastic changes in China's agricultural land use. However, no maps are currently available that document the spatial and temporal patterns of these agricultural land use changes. Because of its short revisit period, rich spectral bands and global coverage, MODIS time series data has been shown to have great potential for detecting the seasonal dynamics of different crop types. However, its inherently coarse spatial resolution limits the accuracy with which crops can be identified from MODIS in regions with small fields or complex agricultural landscapes. To evaluate this more carefully and specifically understand the strengths and weaknesses of MODIS data for crop-type mapping, we used MODIS time-series imagery to map the sub-pixel fractional crop area for four major crop types (rice, corn, soybean and wheat) at 500-m spatial resolution for Heilongjiang province, one of the most important grain-production regions in China where recent agricultural land use change has been rapid and pronounced. To do this, a random forest regression (RF-g) model was constructed to estimate the percentage of each sub-pixel crop type in 2006, 2011 and 2016. Crop type maps generated through expert visual interpretation of high spatial resolution images (i.e., Landsat and SPOT data) were used to calibrate the regression model. Five different time series of vegetation indices (155 features) derived from different spectral channels of MODIS land surface reflectance (MOD09A1) data were used as candidate features for the RF-g model. An out-of-bag strategy and backward elimination approach was applied to select the optimal spectra-temporal feature subset for each crop type. The resulting crop maps were assessed in two ways: (1) wall-to-wall pixel comparison with corresponding high spatial resolution reference maps; and (2) county-level comparison with census data. Based on these derived maps, changes in crop type, total area, and spatial patterns of change in Heilongjiang province during 2006-2016 were analyzed.

Urban and regional land use analysis: CARETS and Census Cities experiment package

NASA Technical Reports Server (NTRS)

Alexander, R. H. (Principal Investigator); Milazzo, V. A.

1973-01-01

The author has identified the following significant results. Areas of post 1970 and 1972 land use changes were identified solely from the Skylab imagery from comparisons with 1970 land use maps. Most land use changes identified involved transition from agriculture to single family residential land use. The second most prominent changes identified from the Skylab imagery were areas presently under construction. Post 1970 changes from Skylab were compared with the 1972 changes noted from the high altitude photographs. A good correlation existed between the change polygons mapped from Skylab and those mapped from the 1972 high altitude aerial photos. In addition, there were a number of instances where additional built-up land use not noted in the 1972 aerial photo as being developed were identified on the Skylab imagery. While these cases have not been documented by field observation, by correlating these areas with the appearance of similar land use areas whose identity has been determined, we can safely say that we have been able to map further occurrences of land use change beyond existing high altitude photo coverage from the Skylab imagery. It was concluded that Skylab data can be used to detect areas of land use change within an urban setting.

The uses of ERTS-1 imagery in the analysis of landscape change. [agriculture, strip mining forests, urban-suburban growth, and flooding in Tennessee, Kentucky, Mississippi, and Alabama

NASA Technical Reports Server (NTRS)

Rehder, J. B. (Principal Investigator)

1974-01-01

The author has identified the following significant results. The analysis of strip mining from ERTS-1 data has resulted in the mapping of landscape changes for the Cumberland Plateau Test Site. Several mapping experiments utilizing ERTS-1 data have been established for the mapping of state-wide land use regions. The first incorporates 12 frames of ERTS-1 imagery for the generalized thematic mapping of forest cover for the state of Tennessee. In another mapping effort, 14 ERTS-1 images have been analyzed for plowed ground signatures to produce a map of agricultural regions for Tennessee, Kentucky, and the northern portions of Mississippi and Alabama. Generalized urban land use categories and transportation networks have been determined from ERTS-1 imagery for the Knoxville Test Site. Finally, through the analysis of ERTS-1 imagery, short-lived phenomena such as the 1973 spring floods on the Mississippi River in western Tennessee, have been detected, monitored, and mapped.

Temporal variation in spectral detection thresholds of substrate and vegetation in AVIRIS images

NASA Technical Reports Server (NTRS)

Sabol, Donald E., Jr.; Roberts, Dar A.; Smith, Milton O.; Adams, John B.

1992-01-01

The ability to map changes over large surface areas over time is one of the advantages in using remote sensing as a monitoring tool. Temporal changes in the surface may be gradual, making them difficult to detect in the short-term, and because they commonly occur at the subpixel scale, they may be difficult to detect in the long-term as well. Also, subtle changes may be real or merely an artifact of image noise. It is, therefore, necessary to understand the factors that limit the detection of surface materials in evaluating temporal data. The spectral detectability of vegetation and soil in the 1990 July and October Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) data of Jasper Ridge, CA was evaluated and compared.

Collection efficiency and acceptance maps of electron detectors for understanding signal detection on modern scanning electron microscopy.

PubMed

Agemura, Toshihide; Sekiguchi, Takashi

2018-02-01

Collection efficiency and acceptance maps of typical detectors in modern scanning electron microscopes (SEMs) were investigated. Secondary and backscattered electron trajectories from a specimen to through-the-lens and under-the-lens detectors placed on an electron optical axis and an Everhart-Thornley detector mounted on a specimen chamber were simulated three-dimensionally. The acceptance maps were drawn as the relationship between the energy and angle of collected electrons under different working distances. The collection efficiency considering the detector sensitivity was also estimated for the various working distances. These data indicated that the acceptance maps and collection efficiency are keys to understand the detection mechanism and image contrast for each detector in the modern SEMs. Furthermore, the working distance is the dominant parameter because electron trajectories are drastically changed with the working distance.

Illumination Invariant Change Detection (iicd): from Earth to Mars

NASA Astrophysics Data System (ADS)

Wan, X.; Liu, J.; Qin, M.; Li, S. Y.

2018-04-01

Multi-temporal Earth Observation and Mars orbital imagery data with frequent repeat coverage provide great capability for planetary surface change detection. When comparing two images taken at different times of day or in different seasons for change detection, the variation of topographic shades and shadows caused by the change of sunlight angle can be so significant that it overwhelms the real object and environmental changes, making automatic detection unreliable. An effective change detection algorithm therefore has to be robust to the illumination variation. This paper presents our research on developing and testing an Illumination Invariant Change Detection (IICD) method based on the robustness of phase correlation (PC) to the variation of solar illumination for image matching. The IICD is based on two key functions: i) initial change detection based on a saliency map derived from pixel-wise dense PC matching and ii) change quantization which combines change type identification, motion estimation and precise appearance change identification. Experiment using multi-temporal Landsat 7 ETM+ satellite images, Rapid eye satellite images and Mars HiRiSE images demonstrate that our frequency based image matching method can reach sub-pixel accuracy and thus the proposed IICD method can effectively detect and precisely segment large scale change such as landslide as well as small object change such as Mars rover, under daily and seasonal sunlight changes.

ERTS-1 imagery interpretation techniques in the Tennessee Valley. [land use and soil mapping

NASA Technical Reports Server (NTRS)

Bodenheimer, R. E. (Principal Investigator)

1974-01-01

The author has identified the following significant results. The feasibility of delineating major soil associations and land uses through computerized analyses is discussed. Useful and potential applications in detecting landscape change and land use mapping are described. Recommendations for improving the data processing effort in a multidisciplinary program are presented.

High-resolution forest carbon stocks and emissions in the Amazon

Treesearch

G. P. Asner; George V. N. Powell; Joseph Mascaro; David E. Knapp; John K. Clark; James Jacobson; Ty Kennedy-Bowdoin; Aravindh Balaji; Guayana Paez-Acosta; Eloy Victoria; Laura Secada; Michael Valqui; R. Flint. Hughes

2010-01-01

Efforts to mitigate climate change through the Reduced Emissions from Deforestation and Degradation (REDD) depend on mapping and monitoring of tropical forest carbon stocks and emissions over large geographic areas. With a new integrated use of satellite imaging, airborne light detection and ranging, and field plots, we mapped aboveground carbon stocks and emissions at...

Saliency predicts change detection in pictures of natural scenes.

PubMed

Wright, Michael J

2005-01-01

It has been proposed that the visual system encodes the salience of objects in the visual field in an explicit two-dimensional map that guides visual selective attention. Experiments were conducted to determine whether salience measurements applied to regions of pictures of outdoor scenes could predict the detection of changes in those regions. To obtain a quantitative measure of change detection, observers located changes in pairs of colour pictures presented across an interstimulus interval (ISI). Salience measurements were then obtained from different observers for image change regions using three independent methods, and all were positively correlated with change detection. Factor analysis extracted a single saliency factor that accounted for 62% of the variance contained in the four measures. Finally, estimates of the magnitude of the image change in each picture pair were obtained, using nine separate visual filters representing low-level vision features (luminance, colour, spatial frequency, orientation, edge density). None of the feature outputs was significantly associated with change detection or saliency. On the other hand it was shown that high-level (structural) properties of the changed region were related to saliency and to change detection: objects were more salient than shadows and more detectable when changed.

Detection thresholds for gaps, overlaps, and no-gap-no-overlaps.

PubMed

Heldner, Mattias

2011-07-01

Detection thresholds for gaps and overlaps, that is acoustic and perceived silences and stretches of overlapping speech in speaker changes, were determined. Subliminal gaps and overlaps were categorized as no-gap-no-overlaps. The established gap and overlap detection thresholds both corresponded to the duration of a long vowel, or about 120 ms. These detection thresholds are valuable for mapping the perceptual speaker change categories gaps, overlaps, and no-gap-no-overlaps into the acoustic domain. Furthermore, the detection thresholds allow generation and understanding of gaps, overlaps, and no-gap-no-overlaps in human-like spoken dialogue systems. © 2011 Acoustical Society of America

Comparison of four machine learning methods for object-oriented change detection in high-resolution satellite imagery

NASA Astrophysics Data System (ADS)

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-resolution satellite imagery, Random Forest (RF), Support Vector Machine (SVM), Deep belief network (DBN), and Adaboost models were established to verify the possibility of different machine learning applications in change detection. In order to compare detection accuracy of four machine learning Method, we applied these four machine learning methods for two high-resolution images. The results shows that SVM has higher overall accuracy at small samples compared to RF, Adaboost, and DBN for binary and from-to change detection. With the increase in the number of samples, RF has higher overall accuracy compared to Adaboost, SVM and DBN.

Analysis of elevation changes detected from multi-temporal LiDAR surveys in forested landslide terrain in western Oregon

USGS Publications Warehouse

Burns, W.J.; Coe, J.A.; Kaya, B.S.; Ma, Liwang

2010-01-01

We examined elevation changes detected from two successive sets of Light Detection and Ranging (LiDAR) data in the northern Coast Range of Oregon. The first set of LiDAR data was acquired during leafon conditions and the second set during leaf-off conditions. We were able to successfully identify and map active landslides using a differential digital elevation model (DEM) created from the two LiDAR data sets, but this required the use of thresholds (0.50 and 0.75 m) to remove noise from the differential elevation data, visual pattern recognition of landslideinduced elevation changes, and supplemental QuickBird satellite imagery. After mapping, we field-verified 88 percent of the landslides that we had mapped with high confidence, but we could not detect active landslides with elevation changes of less than 0.50 m. Volumetric calculations showed that a total of about 18,100 m3 of material was missing from landslide areas, probably as a result of systematic negative elevation errors in the differential DEM and as a result of removal of material by erosion and transport. We also examined the accuracies of 285 leaf-off LiDAR elevations at four landslide sites using Global Positioning System and total station surveys. A comparison of LiDAR and survey data indicated an overall root mean square error of 0.50 m, a maximum error of 2.21 m, and a systematic error of 0.09 m. LiDAR ground-point densities were lowest in areas with young conifer forests and deciduous vegetation, which resulted in extensive interpolations of elevations in the leaf-on, bare-earth DEM. For optimal use of multi-temporal LiDAR data in forested areas, we recommend that all data sets be flown during leaf-off seasons.

Evaluation of Renal Oxygenation Level Changes after Water Loading Using Susceptibility-Weighted Imaging and T2* Mapping.

PubMed

Ding, Jiule; Xing, Wei; Wu, Dongmei; Chen, Jie; Pan, Liang; Sun, Jun; Xing, Shijun; Dai, Yongming

2015-01-01

To assess the feasibility of susceptibility-weighted imaging (SWI) while monitoring changes in renal oxygenation level after water loading. Thirty-two volunteers (age, 28.0 ± 2.2 years) were enrolled in this study. SWI and multi-echo gradient echo sequence-based T2(*) mapping were used to cover the kidney before and after water loading. Cortical and medullary parameters were measured using small regions of interest, and their relative changes due to water loading were calculated based on baseline and post-water loading data. An intraclass correlation coefficient analysis was used to assess inter-observer reliability of each parameter. A receiver operating characteristic curve analysis was conducted to compare the performance of the two methods for detecting renal oxygenation changes due to water loading. Both medullary phase and medullary T2(*) values increased after water loading (p < 0.001), although poor correlations were found between the phase changes and the T2(*) changes (p > 0.05). Interobserver reliability was excellent for the T2(*) values, good for SWI cortical phase values, and moderate for the SWI medullary phase values. The area under receiver operating characteristic curve of the SWI medullary phase values was 0.85 and was not different from the medullary T2(*) value (0.84). Susceptibility-weighted imaging enabled monitoring changes in the oxygenation level in the medulla after water loading, and may allow comparable feasibility to detect renal oxygenation level changes due to water loading compared with that of T2(*) mapping.

Change detection over Sokolov open-pit mining area, Czech Republic, using multi-temporal HyMAP data (2009-2010)

NASA Astrophysics Data System (ADS)

Adar, S.; Notesco, G.; Brook, A.; Livne, I.; Rojik, P.; Kopacková, V.; Zelenkova, K.; Misurec, J.; Bourguignon, A.; Chevrel, S.; Ehrler, C.; Fisher, C.; Hanus, J.; Shkolnisky, Y.; Ben Dor, E.

2011-11-01

Two HyMap images acquired over the same lignite open-pit mining site in Sokolov, Czech Republic, during the summers of 2009 and 2010 (12 months apart), were investigated in this study. The site selected for this research is one of three test sites (the others being in South Africa and Kyrgyzstan) within the framework of the EO-MINERS FP7 Project (http://www.eo-miners.eu). The goal of EO-MINERS is to "integrate new and existing Earth Observation tools to improve best practice in mining activities and to reduce the mining related environmental and societal footprint". Accordingly, the main objective of the current study was to develop hyperspectral-based means for the detection of small spectral changes and to relate these changes to possible degradation or reclamation indicators of the area under investigation. To ensure significant detection of small spectral changes, the temporal domain was investigated along with careful generation of reflectance information. Thus, intensive spectroradiometric ground measurements were carried out to ensure calibration and validation aspects during both overflights. The performance of these corrections was assessed using the Quality Indicators setup developed under a different FP7 project-EUFAR (http://www.eufar.net), which helped select the highest quality data for further work. This approach allows direct distinction of the real information from noise. The reflectance images were used as input for the application of spectral-based change-detection algorithms and indices to account for small and reliable changes. The related algorithms were then developed and applied on a pixel-by-pixel basis to map spectral changes over the space of a year. Using field spectroscopy and ground truth measurements on both overpass dates, it was possible to explain the results and allocate spatial kinetic processes of the environmental changes during the time elapsed between the flights. It was found, for instance, that significant spectral changes are capable of revealing mineral processes, vegetation status and soil formation long before these are apparent to the naked eye. Further study is being conducted under the above initiative to extend this approach to other mining areas worldwide and to improve the robustness of the developed algorithm.

Automated Processing of 2-D Gel Electrophoretograms of Genomic DNA for Hunting Pathogenic DNA Molecular Changes.

PubMed

Takahashi; Nakazawa; Watanabe; Konagaya

1999-01-01

We have developed the automated processing algorithms for 2-dimensional (2-D) electrophoretograms of genomic DNA based on RLGS (Restriction Landmark Genomic Scanning) method, which scans the restriction enzyme recognition sites as the landmark and maps them onto a 2-D electrophoresis gel. Our powerful processing algorithms realize the automated spot recognition from RLGS electrophoretograms and the automated comparison of a huge number of such images. In the final stage of the automated processing, a master spot pattern, on which all the spots in the RLGS images are mapped at once, can be obtained. The spot pattern variations which seemed to be specific to the pathogenic DNA molecular changes can be easily detected by simply looking over the master spot pattern. When we applied our algorithms to the analysis of 33 RLGS images derived from human colon tissues, we successfully detected several colon tumor specific spot pattern changes.

Pre-seizure state identified by diffuse optical tomography

PubMed Central

Zhang, Tao; Zhou, Junli; Jiang, Ruixin; Yang, Hao; Carney, Paul R.; Jiang, Huabei

2014-01-01

In epilepsy it has been challenging to detect early changes in brain activity that occurs prior to seizure onset and to map their origin and evolution for possible intervention. Here we demonstrate using a rat model of generalized epilepsy that diffuse optical tomography (DOT) provides a unique functional neuroimaging modality for noninvasively and continuously tracking such brain activities with high spatiotemporal resolution. We detected early hemodynamic responses with heterogeneous patterns, along with intracranial electroencephalogram gamma power changes, several minutes preceding the electroencephalographic seizure onset, supporting the presence of a “pre-seizure” state. We also observed the decoupling between local hemodynamic and neural activities. We found widespread hemodynamic changes evolving from local regions of the bilateral cortex and thalamus to the entire brain, indicating that the onset of generalized seizures may originate locally rather than diffusely. Together, these findings suggest DOT represents a powerful tool for mapping early seizure onset and propagation pathways. PMID:24445927

Insight From the Statistics of Nothing: Estimating Limits of Change Detection Using Inferred No-Change Areas in DEM Difference Maps and Application to Landslide Hazard Studies

NASA Astrophysics Data System (ADS)

Haneberg, W. C.

2017-12-01

Remote characterization of new landslides or areas of ongoing movement using differences in high resolution digital elevation models (DEMs) created through time, for example before and after major rains or earthquakes, is an attractive proposition. In the case of large catastrophic landslides, changes may be apparent enough that simple subtraction suffices. In other cases, statistical noise can obscure landslide signatures and place practical limits on detection. In ideal cases on land, GPS surveys of representative areas at the time of DEM creation can quantify the inherent errors. In less-than-ideal terrestrial cases and virtually all submarine cases, it may be impractical or impossible to independently estimate the DEM errors. Examining DEM difference statistics for areas reasonably inferred to have no change, however, can provide insight into the limits of detectability. Data from inferred no-change areas of airborne LiDAR DEM difference maps of the 2014 Oso, Washington landslide and landslide-prone colluvium slopes along the Ohio River valley in northern Kentucky, show that DEM difference maps can have non-zero mean and slope dependent error components consistent with published studies of DEM errors. Statistical thresholds derived from DEM difference error and slope data can help to distinguish between DEM differences that are likely real—and which may indicate landsliding—from those that are likely spurious or irrelevant. This presentation describes and compares two different approaches, one based upon a heuristic assumption about the proportion of the study area likely covered by new landslides and another based upon the amount of change necessary to ensure difference at a specified level of probability.

A comparison of change detection methods using multispectral scanner data

USGS Publications Warehouse

Seevers, Paul M.; Jones, Brenda K.; Qiu, Zhicheng; Liu, Yutong

1994-01-01

Change detection methods were investigated as a cooperative activity between the U.S. Geological Survey and the National Bureau of Surveying and Mapping, People's Republic of China. Subtraction of band 2, band 3, normalized difference vegetation index, and tasseled cap bands 1 and 2 data from two multispectral scanner images were tested using two sites in the United States and one in the People's Republic of China. A new statistical method also was tested. Band 2 subtraction gives the best results for detecting change from vegetative cover to urban development. The statistical method identifies areas that have changed and uses a fast classification algorithm to classify the original data of the changed areas by land cover type present for each image date.

Normalizing Landsat and ASTER Data Using MODIS Data Products for Forest Change Detection

NASA Technical Reports Server (NTRS)

Gao, Feng; Masek, Jeffrey G.; Wolfe, Robert E.; Tan, Bin

2010-01-01

Monitoring forest cover and its changes are a major application for optical remote sensing. In this paper, we present an approach to integrate Landsat, ASTER and MODIS data for forest change detection. Moderate resolution (10-100m) images (e.g. Landsat and ASTER) acquired from different seasons and times are normalized to one "standard" date using MODIS data products as reference. The normalized data are then used to compute forest disturbance index for forest change detection. Comparing to the results from original data, forest disturbance index from the normalized images is more consistent spatially and temporally. This work demonstrates an effective approach for mapping forest change over a large area from multiple moderate resolution sensors on various acquisition dates.

Use of remote sensing for land use policy formulation

NASA Technical Reports Server (NTRS)

1983-01-01

Multispectral scanning, infrared imagery, thematic mapping, and spectroradiometry from LANDSAT, GOES, and ground based instruments are being used to determine conifer distribution, maximum and minimum temperatures, topography, and crop diseases in Michigan's lower Peninsula. Image interpretation and automatic digital processing information from LANDSAT data are employed to classify and map the coniferous forests. Radiant temperature data from GOES were compared to temperature readings from the climatological station network. Digital data from LANDSAT is being used to develop techniques for detecting, monitoring, and modeling land surface change. Improved reflectance signatures through spectroradiometry aided in the detection of viral diseases in blueberry fields and vineyards. Soil survey maps from aerial reconnaissance are included as well as information on education, conferences, and awards.

ALOS PALSAR Applications in the Tropics and Subtropics: Characterisation, Mapping and Detecting Change in Forests and Coastal Wetlands

NASA Astrophysics Data System (ADS)

Lucas, Richard; Carreiras, Joao; Proisy, Christophe; Buniting, Peter

2008-11-01

Research undertaken as part of the Japanese Space Exploration Agency (JAXA) Principal Investigator (PI) and Kyoto and Carbon (K&C) programs has focused on the regional characterization (growth stage as a function of biomass and structure) and mapping of forests across northern Australia and mangroves (including wetlands) in selected tropical regions (northern Australia, Belize, French Guiana and Brazil) using Advanced Land Observing Satellite (ALOS) Phased Array L-band SAR (PALSAR) data, either singularly or in conjunction with other remote sensing (e.g., optical) data. Comparison against existing baseline datasets has allowed these data to be used for detecting change in these tropical and subtropical regions. Regional products (e.g., forest growth stage, mangrove/wetland extent and change) generated from the K&C dual polarimetric strip data are anticipated to benefit conservation of these ecosystems and allow better assessments of carbon stocks and changes in these as a function of natural and anthropogenic drivers, thereby supporting key international conventions.

Uav-Based 3d Urban Environment Monitoring

NASA Astrophysics Data System (ADS)

Boonpook, Wuttichai; Tan, Yumin; Liu, Huaqing; Zhao, Binbin; He, Lingfeng

2018-04-01

Unmanned Aerial Vehicle (UAV) based remote sensing can be used to make three-dimensions (3D) mapping with great flexibility, besides the ability to provide high resolution images. In this paper we propose a quick-change detection method on UAV images by combining altitude from Digital Surface Model (DSM) and texture analysis from images. Cases of UAV images with and without georeferencing are both considered. Research results show that the accuracy of change detection can be enhanced with georeferencing procedure, and the accuracy and precision of change detection on UAV images which are collected both vertically and obliquely but without georeferencing also have a good performance.

Composite Interval Mapping Based on Lattice Design for Error Control May Increase Power of Quantitative Trait Locus Detection.

PubMed

He, Jianbo; Li, Jijie; Huang, Zhongwen; Zhao, Tuanjie; Xing, Guangnan; Gai, Junyi; Guan, Rongzhan

2015-01-01

Experimental error control is very important in quantitative trait locus (QTL) mapping. Although numerous statistical methods have been developed for QTL mapping, a QTL detection model based on an appropriate experimental design that emphasizes error control has not been developed. Lattice design is very suitable for experiments with large sample sizes, which is usually required for accurate mapping of quantitative traits. However, the lack of a QTL mapping method based on lattice design dictates that the arithmetic mean or adjusted mean of each line of observations in the lattice design had to be used as a response variable, resulting in low QTL detection power. As an improvement, we developed a QTL mapping method termed composite interval mapping based on lattice design (CIMLD). In the lattice design, experimental errors are decomposed into random errors and block-within-replication errors. Four levels of block-within-replication errors were simulated to show the power of QTL detection under different error controls. The simulation results showed that the arithmetic mean method, which is equivalent to a method under random complete block design (RCBD), was very sensitive to the size of the block variance and with the increase of block variance, the power of QTL detection decreased from 51.3% to 9.4%. In contrast to the RCBD method, the power of CIMLD and the adjusted mean method did not change for different block variances. The CIMLD method showed 1.2- to 7.6-fold higher power of QTL detection than the arithmetic or adjusted mean methods. Our proposed method was applied to real soybean (Glycine max) data as an example and 10 QTLs for biomass were identified that explained 65.87% of the phenotypic variation, while only three and two QTLs were identified by arithmetic and adjusted mean methods, respectively.

Applications of remote sensor data by state and Federal user agencies in Arizona

NASA Technical Reports Server (NTRS)

Schumann, H. H.

1972-01-01

The use of NASA high altitude aerial photography of south eastern Arizona to develop a natural resources information system for Federal lands is discussed. The data are to be used by local, State, and Federal agencies in connection with geologic mapping projects, water resources investigations, and land use studies to determine the alignment of a proposed major aqueduct. In addition, the data are used to confirm land ownership boundaries, detect changes in land use, and legislative reappointment mapping. Other applications include mapping vegetive cover, evaluation of changes in wildlife habitat, location of deer kills, and as a base for recording telemetry data from radio-collared big game animals.

Renal sympathetic nerve activity measured by norepinephrine spillover rate in response to changes in blood pressure in conscious rabbits.

PubMed

Sano, N; Way, D; McGrath, B P

1989-04-01

1. Renal sympathetic nerve activity (RSNA) in response to changes in mean arterial pressure (MAP) was examined by measuring renal norepinephrine (NE) spillover rate in conscious rabbits. 2. A chronic renal vein catheter was implanted for sampling renal venous blood without stress in conscious animals. 3. RSNA estimated by renal NE spillover rate significantly increased in response to moderate falls in MAP produced by sodium nitroprusside (SNP) infusion and decreased in response to moderate rises in MAP produced by phenylephrine (PE) infusion. 4. The NE spillover method is sufficiently sensitive to detect responses of RSNA to physiological stimuli in conscious rabbits.

A targeted change-detection procedure by combining change vector analysis and post-classification approach

NASA Astrophysics Data System (ADS)

Ye, Su; Chen, Dongmei; Yu, Jie

2016-04-01

In remote sensing, conventional supervised change-detection methods usually require effective training data for multiple change types. This paper introduces a more flexible and efficient procedure that seeks to identify only the changes that users are interested in, here after referred to as "targeted change detection". Based on a one-class classifier "Support Vector Domain Description (SVDD)", a novel algorithm named "Three-layer SVDD Fusion (TLSF)" is developed specially for targeted change detection. The proposed algorithm combines one-class classification generated from change vector maps, as well as before- and after-change images in order to get a more reliable detecting result. In addition, this paper introduces a detailed workflow for implementing this algorithm. This workflow has been applied to two case studies with different practical monitoring objectives: urban expansion and forest fire assessment. The experiment results of these two case studies show that the overall accuracy of our proposed algorithm is superior (Kappa statistics are 86.3% and 87.8% for Case 1 and 2, respectively), compared to applying SVDD to change vector analysis and post-classification comparison.

Urban forest topographical mapping using UAV LIDAR

NASA Astrophysics Data System (ADS)

Putut Ash Shidiq, Iqbal; Wibowo, Adi; Kusratmoko, Eko; Indratmoko, Satria; Ardhianto, Ronni; Prasetyo Nugroho, Budi

2017-12-01

Topographical data is highly needed by many parties, such as government institution, mining companies and agricultural sectors. It is not just about the precision, the acquisition time and data processing are also carefully considered. In relation with forest management, a high accuracy topographic map is necessary for planning, close monitoring and evaluating forest changes. One of the solution to quickly and precisely mapped topography is using remote sensing system. In this study, we test high-resolution data using Light Detection and Ranging (LiDAR) collected from unmanned aerial vehicles (UAV) to map topography and differentiate vegetation classes based on height in urban forest area of University of Indonesia (UI). The semi-automatic and manual classifications were applied to divide point clouds into two main classes, namely ground and vegetation. There were 15,806,380 point clouds obtained during the post-process, in which 2.39% of it were detected as ground.

ASTER VNIR 15 years growth to the standard imaging radiometer in remote sensing

NASA Astrophysics Data System (ADS)

Hiramatsu, Masaru; Inada, Hitomi; Kikuchi, Masakuni; Sakuma, Fumihiro

2015-10-01

The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Visible and Near Infrared Radiometer (VNIR) is the remote sensing equipment which has 3 spectral bands and one along-track stereoscopic band radiometer. ASTER VNIR's planned long life design (more than 5 years) is successfully achieved. ASTER VNIR has been imaging the World-wide Earth surface multiband images and the Global Digital Elevation Model (GDEM). VNIR data create detailed world-wide maps and change-detection of the earth surface as utilization transitions and topographical changes. ASTER VNIR's geometric resolution is 15 meters; it is the highest spatial resolution instrument on NASA's Terra spacecraft. Then, ASTER VNIR was planned for the geometrical basis map makers in Terra instruments. After 15-years VNIR growth to the standard map-maker for space remote-sensing. This paper presents VNIR's feature items during 15-year operation as change-detection images , DEM and calibration result. VNIR observed the World-wide Earth images for biological, climatological, geological, and hydrological study, those successful work shows a way on space remote sensing instruments. Still more, VNIR 15 years observation data trend and onboard calibration trend data show several guide or support to follow-on instruments.

A method for age-matched OCT angiography deviation mapping in the assessment of disease- related changes to the radial peripapillary capillaries.

PubMed

Pinhas, Alexander; Linderman, Rachel; Mo, Shelley; Krawitz, Brian D; Geyman, Lawrence S; Carroll, Joseph; Rosen, Richard B; Chui, Toco Y

2018-01-01

To present a method for age-matched deviation mapping in the assessment of disease-related changes to the radial peripapillary capillaries (RPCs). We reviewed 4.5x4.5mm en face peripapillary OCT-A scans of 133 healthy control eyes (133 subjects, mean 41.5 yrs, range 11-82 yrs) and 4 eyes with distinct retinal pathologies, obtained using spectral-domain optical coherence tomography angiography. Statistical analysis was performed to evaluate the impact of age on RPC perfusion densities. RPC density group mean and standard deviation maps were generated for each decade of life. Deviation maps were created for the diseased eyes based on these maps. Large peripapillary vessel (LPV; noncapillary vessel) perfusion density was also studied for impact of age. Average healthy RPC density was 42.5±1.47%. ANOVA and pairwise Tukey-Kramer tests showed that RPC density in the ≥60yr group was significantly lower compared to RPC density in all younger decades of life (p<0.01). Average healthy LPV density was 21.5±3.07%. Linear regression models indicated that LPV density decreased with age, however ANOVA and pairwise Tukey-Kramer tests did not reach statistical significance. Deviation mapping enabled us to quantitatively and visually elucidate the significance of RPC density changes in disease. It is important to consider changes that occur with aging when analyzing RPC and LPV density changes in disease. RPC density, coupled with age-matched deviation mapping techniques, represents a potentially clinically useful method in detecting changes to peripapillary perfusion in disease.

Eccentricity mapping of the human visual cortex to evaluate temporal dynamics of functional T1ρ mapping.

PubMed

Heo, Hye-Young; Wemmie, John A; Johnson, Casey P; Thedens, Daniel R; Magnotta, Vincent A

2015-07-01

Recent experiments suggest that T1 relaxation in the rotating frame (T(1ρ)) is sensitive to metabolism and can detect localized activity-dependent changes in the human visual cortex. Current functional magnetic resonance imaging (fMRI) methods have poor temporal resolution due to delays in the hemodynamic response resulting from neurovascular coupling. Because T(1ρ) is sensitive to factors that can be derived from tissue metabolism, such as pH and glucose concentration via proton exchange, we hypothesized that activity-evoked T(1ρ) changes in visual cortex may occur before the hemodynamic response measured by blood oxygenation level-dependent (BOLD) and arterial spin labeling (ASL) contrast. To test this hypothesis, functional imaging was performed using T(1ρ), BOLD, and ASL in human participants viewing an expanding ring stimulus. We calculated eccentricity phase maps across the occipital cortex for each functional signal and compared the temporal dynamics of T(1ρ) versus BOLD and ASL. The results suggest that T(1ρ) changes precede changes in the two blood flow-dependent measures. These observations indicate that T(1ρ) detects a signal distinct from traditional fMRI contrast methods. In addition, these findings support previous evidence that T(1ρ) is sensitive to factors other than blood flow, volume, or oxygenation. Furthermore, they suggest that tissue metabolism may be driving activity-evoked T(1ρ) changes.

Locating and characterizing a crack in concrete with diffuse ultrasound: A four-point bending test.

PubMed

Larose, Eric; Obermann, Anne; Digulescu, Angela; Planès, Thomas; Chaix, Jean-Francois; Mazerolle, Frédéric; Moreau, Gautier

2015-07-01

This paper describes an original imaging technique, named Locadiff, that benefits from the diffuse effect of ultrasound waves in concrete to detect and locate mechanical changes associated with the opening of pre-existing cracks, and/or to the development of diffuse damage at the tip of the crack. After giving a brief overview of the theoretical model to describe the decorrelation of diffuse waveforms induced by a local change, the article introduces the inversion procedure that produces the three dimensional maps of density of changes. These maps are interpreted in terms of mechanical changes, fracture opening, and damage development. In addition, each fracture is characterized by its effective scattering cross section.

Towards developing Kentucky's landscape change maps

USGS Publications Warehouse

Zourarakis, D.P.; Lambert, S.C.; Palmer, M.

2003-01-01

The Kentucky Landscape Snapshot Project, a NASA-funded project, was established to provide a first baseline land cover/land use map for Kentucky. Through this endeavor, change detection will be institutionalized, thus aiding in decision-making at the local, state, and federal planning levels. 2002 Landsat 7 imaginery was classified following and Anderson Level III scheme, providing an enhancement over the 1992 USGS National Land Cover Data Set. Also as part of the deliverables, imperviousness and canopy closure layers were produced with the aid of IKONOS high resolution, multispectral imagery.

Making LULUCF matrix of Korea by Approach 2&3

NASA Astrophysics Data System (ADS)

Hwang, J.; Jang, R.; Seong, M.; Yim, J.; Jeon, S. W.

2017-12-01

To establish and implement policies in response to climate change, it is very important to identify domestic greenhouse gas emission sources and sinks, and accurately calculate emissions and removals from each source and sink. The IPCC Guideline requires the establishment of six sectors of energy, industrial processes, solvents and other product use, agriculture, Land-Use Change and Forestry (LULUCF) and waste in estimating GHG inventories. LULUCF is divided into 6 categories according to land use, purpose, and type, and then it calculates greenhouse gas emission/absorption amount due to artificial activities according to each land use category and greenhouse gas emission/absorption amount according to land use change. The IPCC Guideline provides three approaches to how to create a LULUCF discipline matrix. According to the IPCC Guidelines, it is a principle to divide into the land use that is maintained and the land use area changed to other lands. However, Korea currently uses Approach 1, which is based on statistical data, it is difficult to detect changed area. Therefore, in this study, we are going to do a preliminary work for constructing the LULUCF matrix at Approach 2 & 3 level. NFI data, GIS, and RS data were used to build the matrix of Approach 2 method by Sampling method. For used for Approach 3, we analyzed the four thematic maps - Cadastral Map, Land Cover Map, Forest Type Map, and Biotope Map - representing land cover and utilization in terms of legal, property, quantitative and qualitative aspects. There is a difference between these maps because their purpose, resolution, timing and spatial range are different. Comparing these maps is important because it can help for decide map which is suitable for constructing the LULUCF matrix.Keywords: LULUCF, GIS/RS, IPCC Guideline, Approach 2&3, Thematic Maps

Using Land Surface Phenology as the Basis for a National Early Warning System for Forest Disturbances

NASA Astrophysics Data System (ADS)

Hargrove, W. W.; Spruce, J.; Norman, S. P.; Hoffman, F. M.

2011-12-01

The National Early Warning System (EWS) provides an 8-day coast-to-coast snapshot of potentially disturbed forests across the U.S.. A prototype system has produced national maps of potential forest disturbances every eight days since January 2010, identifying locations that may require further investigation. Through phenology, the system shows both early and delayed vegetation development and detects all types of unexpected forest disturbances, including insects, disease, wildfires, frost and ice damage, tornadoes, hurricanes, blowdowns, harvest, urbanization, landslides, drought, flood, and climate change. The USDA Forest Service Eastern Forest Environmental Threat Assessment Center is collaborating with NASA Stennis Space Center and the Western Wildland Environmental Threat Assessment Center to develop the tool. The EWS uses differences in phenological responses between an expectation based on historical data and a current view to strategically identify potential forest disturbances and direct attention to locations where forest behavior seems unusual. Disturbance maps are available via the Forest Change Assessment Viewer (FCAV) (http://ews.forestthreats.org/gis), which allows resource managers and other users to see the most current national disturbance maps as soon as they are available. Phenology-based detections show not only vegetation disturbances in the classical sense, but all departures from normal seasonal vegetation behavior. In 2010, the EWS detected a repeated late-frost event at high elevations in North Carolina, USA, that resulted in delayed seasonal development, contrasting with an early spring development at lower elevations, all within close geographic proximity. Throughout 2011, there was a high degree of correspondence between the National Climatic Data Center's North American Drought Monitor maps and EWS maps of phenological drought disturbance in forests. Urban forests showed earlier and more severe phenological drought disturbance than surrounding non-urban forests. An EWS news page (http://www.geobabbble.org/~hnw/EWSNews) highlights disturbances the system has detected during the 2011 season. Unsupervised statistical multivariate clustering of smoothed phenology data every 8 days over an 11-year period produces a detailed map of national vegetation types, including major disturbances. Examining the constancy of these phenological classifications at a particular location from year to year produces a national map showing the persistence of vegetation, regardless of vegetation type. Using spectral unmixing methods, national maps of evergreen decline can be produced which are a composite of insect, disease, and anthropogenic factors causing chronic decline in these forests, including hemlock wooly adelgid, mountain pine beetle, wildfire, tree harvest, and urbanization. Because phenology shows vegetation responses, all disturbance and recovery events detected by the EWS are viewed through the lens of the vegetation.

Forest land cover change (1975-2000) in the Greater Border Lakes region

Treesearch

Peter T. Wolter; Brian R. Sturtevant; Brian R. Miranda; Sue M. Lietz; Phillip A. Townsend; John Pastor

2012-01-01

This document and accompanying maps describe land cover classifications and change detection for a 13.8 million ha landscape straddling the border between Minnesota, and Ontario, Canada (greater Border Lakes Region). Land cover classifications focus on discerning Anderson Level II forest and nonforest cover to track spatiotemporal changes in forest cover. Multi-...

Automatic Detection of Changes on Mars Surface from High-Resolution Orbital Images

NASA Astrophysics Data System (ADS)

Sidiropoulos, Panagiotis; Muller, Jan-Peter

2017-04-01

Over the last 40 years Mars has been extensively mapped by several NASA and ESA orbital missions, generating a large image dataset comprised of approximately 500,000 high-resolution images (of <100m resolution). The overall area mapped from orbital imagery is approximately 6 times the overall surface of Mars [1]. The multi-temporal coverage of Martian surface allows a visual inspection of the surface to identify dynamic phenomena, i.e. surface features that change over time, such as slope streaks [2], recurring slope lineae [3], new impact craters [4], etc. However, visual inspection for change detection is a limited approach, since it requires extensive use of human resources, which is very difficult to achieve when dealing with a rapidly increasing volume of data. Although citizen science can be employed for training and verification it is unsuitable for planetwide systematic change detection. In this work, we introduce a novel approach in planetary image change detection, which involves a batch-mode automatic change detection pipeline that identifies regions that have changed. This is tested in anger, on tens of thousands of high-resolution images over the MC11 quadrangle [5], acquired by CTX, HRSC, THEMIS-VIS and MOC-NA instruments [1]. We will present results which indicate a substantial level of activity in this region of Mars, including instances of dynamic natural phenomena that haven't been cataloged in the planetary science literature before. We will demonstrate the potential and usefulness of such an automatic approach in planetary science change detection. Acknowledgments: The research leading to these results has received funding from the STFC "MSSL Consolidated Grant" ST/K000977/1 and partial support from the European Union's Seventh Framework Programme (FP7/2007-2013) under iMars grant agreement n° 607379. References: [1] P. Sidiropoulos and J. - P. Muller (2015) On the status of orbital high-resolution repeat imaging of Mars for the observation of dynamic surface processes. Planetary and Space Science, 117: 207-222. [2] O. Aharonson, et al. (2003) Slope streak formation and dust deposition rates on Mars. Journal of Geophysical Research: Planets, 108(E12):5138 [3] A. McEwen, et al. (2011) Seasonal flows on warm martian slopes. Science, 333 (6043): 740-743. [4] S. Byrne, et al. (2009) Distribution of mid-latitude ground ice on mars from new impact craters. Science, 325(5948):1674-1676. [5] K. Gwinner, et al (2016) The High Resolution Stereo Camera (HRSC) of Mars Express and its approach to science analysis and mapping for Mars and its satellites. Planetary and Space Science, 126: 93-138.

A comparative study evaluating the efficacy of IS_MAP04 with IS900 and IS_MAP02 as a new diagnostic target for the detection of Mycobacterium avium subspecies paratuberculosis from bovine faeces.

PubMed

de Kruijf, Marcel; Govender, Rodney; Yearsley, Dermot; Coffey, Aidan; O'Mahony, Jim

2017-05-01

The aim of this study was to investigate the efficacy of IS_MAP04 as a potential new diagnostic quantitative PCR (qPCR) target for the detection of Mycobacterium avium subspecies paratuberculosis from bovine faeces. IS_MAP04 primers were designed and tested negative against non-MAP strains. The detection limit of IS_MAP04 qPCR was evaluated on different MAP K-10 DNA concentrations and on faecal samples spiked with different MAP K-10 cell dilutions. A collection of 106 faecal samples was analysed and the efficacy of IS_MAP04 was statistically compared with IS900 and IS_MAP02. The detection limits observed for IS_MAP04 and IS900 on MAP DNA was 34 fg and 3.4 fg respectively. The detection limit of MAP from inoculated faecal samples was 10 2 CFU/g for both IS_MAP04 and IS900 targets and a detection limit of 10 2 CFU/g was also achieved with a TaqMan qPCR targeting IS_MAP04. The efficacy of IS_MAP04 to detect positive MAP faecal samples was 83.0% compared to 85.8% and 83.9% for IS900 and IS_MAP02 respectively. Strong kappa agreements were observed between IS_MAP04 and IS900 (κ=0.892) and between IS_MAP04 and IS_MAP02 (κ=0.897). As a new molecular target, IS_MAP04 showed that the detection limit was comparable to IS900 to detect MAP from inoculated faecal material. The MAP detection efficacy of IS_MAP04 from naturally infected faecal samples proved to be relatively comparable to IS_MAP02, but yielded efficacy results slightly less than IS900. Moreover, IS_MAP04 could be of significant value when used in duplex or multiplex qPCR assays. Copyright © 2017 Elsevier B.V. All rights reserved.

Parallel changes in serum proteins and diffusion tensor imaging in methamphetamine-associated psychosis.

PubMed

Breen, Michael S; Uhlmann, Anne; Ozcan, Sureyya; Chan, Man; Pinto, Dalila; Bahn, Sabine; Stein, Dan J

2017-03-02

Methamphetamine-associated psychosis (MAP) involves widespread neurocognitive and molecular deficits, however accurate diagnosis remains challenging. Integrating relationships between biological markers, brain imaging and clinical parameters may provide an improved mechanistic understanding of MAP, that could in turn drive the development of better diagnostics and treatment approaches. We applied selected reaction monitoring (SRM)-based proteomics, profiling 43 proteins in serum previously implicated in the etiology of major psychiatric disorders, and integrated these data with diffusion tensor imaging (DTI) and psychometric measurements from patients diagnosed with MAP (N = 12), methamphetamine dependence without psychosis (MA; N = 14) and healthy controls (N = 16). Protein analysis identified changes in APOC2 and APOH, which differed significantly in MAP compared to MA and controls. DTI analysis indicated widespread increases in mean diffusivity and radial diffusivity delineating extensive loss of white matter integrity and axon demyelination in MAP. Upon integration, several co-linear relationships between serum proteins and DTI measures reported in healthy controls were disrupted in MA and MAP groups; these involved areas of the brain critical for memory and social emotional processing. These findings suggest that serum proteomics and DTI are sensitive measures for detecting pathophysiological changes in MAP and describe a potential diagnostic fingerprint of the disorder.

Change detection for synthetic aperture radar images based on pattern and intensity distinctiveness analysis

NASA Astrophysics Data System (ADS)

Wang, Xiao; Gao, Feng; Dong, Junyu; Qi, Qiang

2018-04-01

Synthetic aperture radar (SAR) image is independent on atmospheric conditions, and it is the ideal image source for change detection. Existing methods directly analysis all the regions in the speckle noise contaminated difference image. The performance of these methods is easily affected by small noisy regions. In this paper, we proposed a novel change detection framework for saliency-guided change detection based on pattern and intensity distinctiveness analysis. The saliency analysis step can remove small noisy regions, and therefore makes the proposed method more robust to the speckle noise. In the proposed method, the log-ratio operator is first utilized to obtain a difference image (DI). Then, the saliency detection method based on pattern and intensity distinctiveness analysis is utilized to obtain the changed region candidates. Finally, principal component analysis and k-means clustering are employed to analysis pixels in the changed region candidates. Thus, the final change map can be obtained by classifying these pixels into changed or unchanged class. The experiment results on two real SAR images datasets have demonstrated the effectiveness of the proposed method.

Improved Snow Mapping Accuracy with Revised MODIS Snow Algorithm

NASA Technical Reports Server (NTRS)

Riggs, George; Hall, Dorothy K.

2012-01-01

The MODIS snow cover products have been used in over 225 published studies. From those reports, and our ongoing analysis, we have learned about the accuracy and errors in the snow products. Revisions have been made in the algorithms to improve the accuracy of snow cover detection in Collection 6 (C6), the next processing/reprocessing of the MODIS data archive planned to start in September 2012. Our objective in the C6 revision of the MODIS snow-cover algorithms and products is to maximize the capability to detect snow cover while minimizing snow detection errors of commission and omission. While the basic snow detection algorithm will not change, new screens will be applied to alleviate snow detection commission and omission errors, and only the fractional snow cover (FSC) will be output (the binary snow cover area (SCA) map will no longer be included).

Unsupervised Change Detection for Geological and Ecological Monitoring via Remote Sensing: Application on a Volcanic Area

NASA Astrophysics Data System (ADS)

Falco, N.; Pedersen, G. B. M.; Vilmunandardóttir, O. K.; Belart, J. M. M. C.; Sigurmundsson, F. S.; Benediktsson, J. A.

2016-12-01

The project "Environmental Mapping and Monitoring of Iceland by Remote Sensing (EMMIRS)" aims at providing fast and reliable mapping and monitoring techniques on a big spatial scale with a high temporal resolution of the Icelandic landscape. Such mapping and monitoring will be crucial to both mitigate and understand the scale of processes and their often complex interlinked feedback mechanisms.In the EMMIRS project, the Hekla volcano area is one of the main sites under study, where the volcanic eruptions, extreme weather and human activities had an extensive impact on the landscape degradation. The development of innovative remote sensing approaches to compute earth observation variables as automatically as possible is one of the main tasks of the EMMIRS project. Furthermore, a temporal remote sensing archive is created and composed by images acquired by different sensors (Landsat, RapidEye, ASTER and SPOT5). Moreover, historical aerial stereo photos allowed decadal reconstruction of the landscape by reconstruction of digital elevation models. Here, we propose a novel architecture for automatic unsupervised change detection analysis able to ingest multi-source data in order to detect landscape changes in the Hekla area. The change detection analysis is based on multi-scale analysis, which allows the identification of changes at different level of abstraction, from pixel-level to region-level. For this purpose, operators defined in mathematical morphology framework are implemented to model the contextual information, represented by the neighbour system of a pixel, allowing the identification of changes related to both geometrical and spectral domains. Automatic radiometric normalization strategy is also implemented as pre-processing step, aiming at minimizing the effect of different acquisition conditions. The proposed architecture is tested on multi-temporal data sets acquired over different time periods coinciding with the last three eruptions (1980-1981, 1991, 2000) occurred on Hekla volcano. The results reveal emplacement of new lava flows and the initial vegetation succession, providing insightful information on the evolving of vegetation in such environment. Shadow and snow patch changes are resolved in post-processing by exploiting the available spectral information.

Remote sensing techniques for conservation and management of natural vegetation ecosystems

NASA Technical Reports Server (NTRS)

Parada, N. D. J. (Principal Investigator); Verdesio, J. J.; Dossantos, J. R.

1981-01-01

The importance of using remote sensing techniques, in the visible and near-infrared ranges, for mapping, inventory, conservation and management of natural ecosystems is discussed. Some examples realized in Brazil or other countries are given to evaluate the products from orbital platform (MSS and RBV imagery of LANDSAT) and aerial level (photography) for ecosystems study. The maximum quantitative and qualitative information which can be obtained from each sensor, at different level, are discussed. Based on the developed experiments it is concluded that the remote sensing technique is a useful tool in mapping vegetation units, estimating biomass, forecasting and evaluation of fire damage, disease detection, deforestation mapping and change detection in land-use. In addition, remote sensing techniques can be used in controling implantation and planning natural/artificial regeneration.

Urban Land Cover/use Change Detection Using High Resolution SPOT 5 and SPOT 6 Images and Urban Atlas Nomenclature

NASA Astrophysics Data System (ADS)

Akay, S. S.; Sertel, E.

2016-06-01

Urban land cover/use changes like urbanization and urban sprawl have been impacting the urban ecosystems significantly therefore determination of urban land cover/use changes is an important task to understand trends and status of urban ecosystems, to support urban planning and to aid decision-making for urban-based projects. High resolution satellite images could be used to accurately, periodically and quickly map urban land cover/use and their changes by time. This paper aims to determine urban land cover/use changes in Gaziantep city centre between 2010 and 2105 using object based images analysis and high resolution SPOT 5 and SPOT 6 images. 2.5 m SPOT 5 image obtained in 5th of June 2010 and 1.5 m SPOT 6 image obtained in 7th of July 2015 were used in this research to precisely determine land changes in five-year period. In addition to satellite images, various ancillary data namely Normalized Difference Vegetation Index (NDVI), Difference Water Index (NDWI) maps, cadastral maps, OpenStreetMaps, road maps and Land Cover maps, were integrated into the classification process to produce high accuracy urban land cover/use maps for these two years. Both images were geometrically corrected to fulfil the 1/10,000 scale geometric accuracy. Decision tree based object oriented classification was applied to identify twenty different urban land cover/use classes defined in European Urban Atlas project. Not only satellite images and satellite image-derived indices but also different thematic maps were integrated into decision tree analysis to create rule sets for accurate mapping of each class. Rule sets of each satellite image for the object based classification involves spectral, spatial and geometric parameter to automatically produce urban map of the city centre region. Total area of each class per related year and their changes in five-year period were determined and change trend in terms of class transformation were presented. Classification accuracy assessment was conducted by creating a confusion matrix to illustrate the thematic accuracy of each class.

Detection of early seizures by diffuse optical tomography

NASA Astrophysics Data System (ADS)

Zhang, Tao; Hajihashemi, M. Reza; Zhou, Junli; Carney, Paul R.; Jiang, Huabei

2015-03-01

In epilepsy it has been challenging to detect early changes in brain activity that occurs prior to seizure onset and to map their origin and evolution for possible intervention. Besides, preclinical seizure experiments need to be conducted in awake animals with images reconstructed and displayed in real-time. We demonstrate using a rat model of generalized epilepsy that diffuse optical tomography (DOT) provides a unique functional neuroimaging modality for noninvasively and continuously tracking brain activities with high spatiotemporal resolution. We developed methods to conduct seizure experiments in fully awake rats using a subject-specific helmet and a restraining mechanism. For the first time, we detected early hemodynamic responses with heterogeneous patterns several minutes preceding the electroencephalographic seizure onset, supporting the presence of a "pre-seizure" state both in anesthetized and awake rats. Using a novel time-series analysis of scattering images, we show that the analysis of scattered diffuse light is a sensitive and reliable modality for detecting changes in neural activity associated with generalized seizure. We found widespread hemodynamic changes evolving from local regions of the bilateral cortex and thalamus to the entire brain, indicating that the onset of generalized seizures may originate locally rather than diffusely. Together, these findings suggest DOT represents a powerful tool for mapping early seizure onset and propagation pathways.

Environmental mapping and monitoring of Iceland by remote sensing (EMMIRS)

NASA Astrophysics Data System (ADS)

Pedersen, Gro B. M.; Vilmundardóttir, Olga K.; Falco, Nicola; Sigurmundsson, Friðþór S.; Rustowicz, Rose; Belart, Joaquin M.-C.; Gísladóttir, Gudrun; Benediktsson, Jón A.

2016-04-01

Iceland is exposed to rapid and dynamic landscape changes caused by natural processes and man-made activities, which impact and challenge the country. Fast and reliable mapping and monitoring techniques are needed on a big spatial scale. However, currently there is lack of operational advanced information processing techniques, which are needed for end-users to incorporate remote sensing (RS) data from multiple data sources. Hence, the full potential of the recent RS data explosion is not being fully exploited. The project Environmental Mapping and Monitoring of Iceland by Remote Sensing (EMMIRS) bridges the gap between advanced information processing capabilities and end-user mapping of the Icelandic environment. This is done by a multidisciplinary assessment of two selected remote sensing super sites, Hekla and Öræfajökull, which encompass many of the rapid natural and man-made landscape changes that Iceland is exposed to. An open-access benchmark repository of the two remote sensing supersites is under construction, providing high-resolution LIDAR topography and hyperspectral data for land-cover and landform classification. Furthermore, a multi-temporal and multi-source archive stretching back to 1945 allows a decadal evaluation of landscape and ecological changes for the two remote sensing super sites by the development of automated change detection techniques. The development of innovative pattern recognition and machine learning-based approaches to image classification and change detection is one of the main tasks of the EMMIRS project, aiming to extract and compute earth observation variables as automatically as possible. Ground reference data collected through a field campaign will be used to validate the implemented methods, which outputs are then inferred with geological and vegetation models. Here, preliminary results of an automatic land-cover classification based on hyperspectral image analysis are reported. Furthermore, the EMMIRS project investigates the complex landscape dynamics between geological and ecological processes. This is done through cross-correlation of mapping results and implementation of modelling techniques that simulate geological and ecological processes in order to extrapolate the landscape evolution

Monitoring forest dynamics with multi-scale and time series imagery.

PubMed

Huang, Chunbo; Zhou, Zhixiang; Wang, Di; Dian, Yuanyong

2016-05-01

To learn the forest dynamics and evaluate the ecosystem services of forest effectively, a timely acquisition of spatial and quantitative information of forestland is very necessary. Here, a new method was proposed for mapping forest cover changes by combining multi-scale satellite remote-sensing imagery with time series data. Using time series Normalized Difference Vegetation Index products derived from the Moderate Resolution Imaging Spectroradiometer images (MODIS-NDVI) and Landsat Thematic Mapper/Enhanced Thematic Mapper Plus (TM/ETM+) images as data source, a hierarchy stepwise analysis from coarse scale to fine scale was developed for detecting the forest change area. At the coarse scale, MODIS-NDVI data with 1-km resolution were used to detect the changes in land cover types and a land cover change map was constructed using NDVI values at vegetation growing seasons. At the fine scale, based on the results at the coarse scale, Landsat TM/ETM+ data with 30-m resolution were used to precisely detect the forest change location and forest change trend by analyzing time series forest vegetation indices (IFZ). The method was tested using the data for Hubei Province, China. The MODIS-NDVI data from 2001 to 2012 were used to detect the land cover changes, and the overall accuracy was 94.02 % at the coarse scale. At the fine scale, the available TM/ETM+ images at vegetation growing seasons between 2001 and 2012 were used to locate and verify forest changes in the Three Gorges Reservoir Area, and the overall accuracy was 94.53 %. The accuracy of the two layer hierarchical monitoring results indicated that the multi-scale monitoring method is feasible and reliable.

Detection of magnetic field intensity gradient by homing pigeons (Columba livia) in a novel "virtual magnetic map" conditioning paradigm.

PubMed

Mora, Cordula V; Bingman, Verner P

2013-01-01

It has long been thought that birds may use the Earth's magnetic field not only as a compass for direction finding, but that it could also provide spatial information for position determination analogous to a map during navigation. Since magnetic field intensity varies systematically with latitude and theoretically could also provide longitudinal information during position determination, birds using a magnetic map should be able to discriminate magnetic field intensity cues in the laboratory. Here we demonstrate a novel behavioural paradigm requiring homing pigeons to identify the direction of a magnetic field intensity gradient in a "virtual magnetic map" during a spatial conditioning task. Not only were the pigeons able to detect the direction of the intensity gradient, but they were even able to discriminate upward versus downward movement on the gradient by differentiating between increasing and decreasing intensity values. Furthermore, the pigeons typically spent more than half of the 15 second sampling period in front of the feeder associated with the rewarded gradient direction indicating that they required only several seconds to make the correct choice. Our results therefore demonstrate for the first time that pigeons not only can detect the presence and absence of magnetic anomalies, as previous studies had shown, but are even able to detect and respond to changes in magnetic field intensity alone, including the directionality of such changes, in the context of spatial orientation within an experimental arena. This opens up the possibility for systematic and detailed studies of how pigeons could use magnetic intensity cues during position determination as well as how intensity is perceived and where it is processed in the brain.

7 Tesla Magnetic Resonance Imaging to Detect Cortical Pathology in Multiple Sclerosis

PubMed Central

van Gelderen, Peter; Merkle, Hellmuth; Chen, Christina; Lassmann, Hans; Duyn, Jeff H.; Bagnato, Francesca

2014-01-01

Background Neocortical lesions (NLs) are an important pathological component of multiple sclerosis (MS), but their visualization by magnetic resonance imaging (MRI) remains challenging. Objectives We aimed at assessing the sensitivity of multi echo gradient echo (ME-GRE) T2 *-weighted MRI at 7.0 Tesla in depicting NLs compared to myelin and iron staining. Methods Samples from two MS patients were imaged post mortem using a whole body 7T MRI scanner with a 24-channel receive-only array. Isotropic 200 micron resolution images with varying T2 * weighting were reconstructed from the ME-GRE data and converted into R2 * maps. Immunohistochemical staining for myelin (proteolipid protein, PLP) and diaminobenzidine-enhanced Turnbull blue staining for iron were performed. Results Prospective and retrospective sensitivities of MRI for the detection of NLs were 48% and 67% respectively. We observed MRI maps detecting only a small portion of 20 subpial NLs extending over large cortical areas on PLP stainings. No MRI signal changes suggestive of iron accumulation in NLs were observed. Conversely, R2 * maps indicated iron loss in NLs, which was confirmed by histological quantification. Conclusions High-resolution post mortem imaging using R2 * and magnitude maps permits detection of focal NLs. However, disclosing extensive subpial demyelination with MRI remains challenging. PMID:25303286

Mapping Land Cover and Land Use Changes in the Congo Basin Forests with Optical Satellite Remote Sensing: a Pilot Project Exploring Methodologies that Improve Spatial Resolution and Map Accuracy

NASA Astrophysics Data System (ADS)

Molinario, G.; Baraldi, A.; Altstatt, A. L.; Nackoney, J.

2011-12-01

The University of Maryland has been a USAID Central Africa Rregional Program for the Environment (CARPE) cross-cutting partner for many years, providing remote sensing derived information on forest cover and forest cover changes in support of CARPE's objectives of diminishing forest degradation, loss and biodiversity loss as a result of poor or inexistent land use planning strategies. Together with South Dakota State University, Congo Basin-wide maps have been provided that map forest cover loss at a maximum of 60m resolution, using Landsat imagery and higher resolution imagery for algorithm training and validation. However, to better meet the needs within the CARPE Landscapes, which call for higher resolution, more accurate land cover change maps, UMD has been exploring the use of the SIAM automatic spectral -rule classifier together with pan-sharpened Landsat data (15m resolution) and Very High Resolution imagery from various sources. The pilot project is being developed in collaboration with the African Wildlife Foundation in the Maringa Lopori Wamba CARPE Landscape. If successful in the future this methodology will make the creation of high resolution change maps faster and easier, making it accessible to other entities in the Congo Basin that need accurate land cover and land use change maps in order, for example, to create sustainable land use plans, conserve biodiversity and resources and prepare Reducing Emissions from forest Degradation and Deforestation (REDD) Measurement, Reporting and Verification (MRV) projects. The paper describes the need for higher resolution land cover change maps that focus on forest change dynamics such as the cycling between primary forests, secondary forest, agriculture and other expanding and intensifying land uses in the Maringa Lopori Wamba CARPE Landscape in the Equateur Province of the Democratic Republic of Congo. The Methodology uses the SIAM remote sensing imagery automatic spectral rule classifier, together with pan-sharpened Landsat imagery with 15m resolution and Very High Resolution imagery from different sensors, obtained from the Department of Defense database that was recently opened to NASA and its Earth Observation partners. Particular emphasis is placed on the detection of agricultural fields and their expansion in primary forests or intensification in secondary forests and fallow fields, as this is the primary driver of deforestation in this area. Fields in this area area also of very small size and irregular shapes, often partly obscured by neighboring forest canopy, hence the technical challenge of correctly detecting them and tracking them through time. Finally, the potential for use of this methodology in other regions where information on land cover changes is needed for land use sustainability planning, is also addressed.

Change detection from synthetic aperture radar images based on neighborhood-based ratio and extreme learning machine

NASA Astrophysics Data System (ADS)

Gao, Feng; Dong, Junyu; Li, Bo; Xu, Qizhi; Xie, Cui

2016-10-01

Change detection is of high practical value to hazard assessment, crop growth monitoring, and urban sprawl detection. A synthetic aperture radar (SAR) image is the ideal information source for performing change detection since it is independent of atmospheric and sunlight conditions. Existing SAR image change detection methods usually generate a difference image (DI) first and use clustering methods to classify the pixels of DI into changed class and unchanged class. Some useful information may get lost in the DI generation process. This paper proposed an SAR image change detection method based on neighborhood-based ratio (NR) and extreme learning machine (ELM). NR operator is utilized for obtaining some interested pixels that have high probability of being changed or unchanged. Then, image patches centered at these pixels are generated, and ELM is employed to train a model by using these patches. Finally, pixels in both original SAR images are classified by the pretrained ELM model. The preclassification result and the ELM classification result are combined to form the final change map. The experimental results obtained on three real SAR image datasets and one simulated dataset show that the proposed method is robust to speckle noise and is effective to detect change information among multitemporal SAR images.

Automated Plantation Mapping in Indonesia Using Remote Sensing Data

NASA Astrophysics Data System (ADS)

Karpatne, A.; Jia, X.; Khandelwal, A.; Kumar, V.

2017-12-01

Plantation mapping is critical for understanding and addressing deforestation, a key driver of climate change and ecosystem degradation. Unfortunately, most plantation maps are limited to small areas for specific years because they rely on visual inspection of imagery. In this work, we propose a data-driven approach which automatically generates yearly plantation maps for large regions using MODIS multi-spectral data. While traditional machine learning algorithms face manifold challenges in this task, e.g. imperfect training labels, spatio-temporal data heterogeneity, noisy and high-dimensional data, lack of evaluation data, etc., we introduce a novel deep learning-based framework that combines existing imperfect plantation products as training labels and models the spatio-temporal relationships of land covers. We also explores the post-processing steps based on Hidden Markov Model that further improve the detection accuracy. Then we conduct extensive evaluation of the generated plantation maps. Specifically, by randomly sampling and comparing with high-resolution Digital Globe imagery, we demonstrate that the generated plantation maps achieve both high precision and high recall. When compared with existing plantation mapping products, our detection can avoid both false positives and false negatives. Finally, we utilize the generated plantation maps in analyzing the relationship between forest fires and growth of plantations, which assists in better understanding the cause of deforestation in Indonesia.

Comparison of Tasseled Cap-based Landsat data structures for use in forest disturbance detection.

Treesearch

Sean P. Healey; Warren B. Cohen; Yang Zhiqiang; Olga N. Krankina

2005-01-01

Landsat satellite data has become ubiquitous in regional-scale forest disturbance detection. The Tasseled Cap (TC) transformation for Landsat data has been used in several disturbance-mapping projects because of its ability to highlight relevant vegetation changes. We used an automated composite analysis procedure to test four multi-date variants of the TC...

Mixing geometric and radiometric features for change classification

NASA Astrophysics Data System (ADS)

Fournier, Alexandre; Descombes, Xavier; Zerubia, Josiane

2008-02-01

Most basic change detection algorithms use a pixel-based approach. Whereas such approach is quite well defined for monitoring important area changes (such as urban growth monitoring) in low resolution images, an object based approach seems more relevant when the change detection is specifically aimed toward targets (such as small buildings and vehicles). In this paper, we present an approach that mixes radiometric and geometric features to qualify the changed zones. The goal is to establish bounds (appearance, disappearance, substitution ...) between the detected changes and the underlying objects. We proceed by first clustering the change map (containing each pixel bitemporal radiosity) in different classes using the entropy-kmeans algorithm. Assuming that most man-made objects have a polygonal shape, a polygonal approximation algorithm is then used in order to characterize the resulting zone shapes. Hence allowing us to refine the primary rough classification, by integrating the polygon orientations in the state space. Tests are currently conducted on Quickbird data.

Ladar imaging detection of salient map based on PWVD and Rényi entropy

NASA Astrophysics Data System (ADS)

Xu, Yuannan; Zhao, Yuan; Deng, Rong; Dong, Yanbing

2013-10-01

Spatial-frequency information of a given image can be extracted by associating the grey-level spatial data with one of the well-known spatial/spatial-frequency distributions. The Wigner-Ville distribution (WVD) has a good characteristic that the images can be represented in spatial/spatial-frequency domains. For intensity and range images of ladar, through the pseudo Wigner-Ville distribution (PWVD) using one or two dimension window, the statistical property of Rényi entropy is studied. We also analyzed the change of Rényi entropy's statistical property in the ladar intensity and range images when the man-made objects appear. From this foundation, a novel method for generating saliency map based on PWVD and Rényi entropy is proposed. After that, target detection is completed when the saliency map is segmented using a simple and convenient threshold method. For the ladar intensity and range images, experimental results show the proposed method can effectively detect the military vehicles from complex earth background with low false alarm.

Mapping the Recent US Hurricanes Triggered Flood Events in Near Real Time

NASA Astrophysics Data System (ADS)

Shen, X.; Lazin, R.; Anagnostou, E. N.; Wanik, D. W.; Brakenridge, G. R.

2017-12-01

Synthetic Aperture Radar (SAR) observations is the only reliable remote sensing data source to map flood inundation during severe weather events. Unfortunately, since state-of-art data processing algorithms cannot meet the automation and quality standard of a near-real-time (NRT) system, quality controlled inundation mapping by SAR currently depends heavily on manual processing, which limits our capability to quickly issue flood inundation maps at global scale. Specifically, most SAR-based inundation mapping algorithms are not fully automated, while those that are automated exhibit severe over- and/or under-detection errors that limit their potential. These detection errors are primarily caused by the strong overlap among the SAR backscattering probability density functions (PDF) of different land cover types. In this study, we tested a newly developed NRT SAR-based inundation mapping system, named Radar Produced Inundation Diary (RAPID), using Sentinel-1 dual polarized SAR data over recent flood events caused by Hurricanes Harvey, Irma, and Maria (2017). The system consists of 1) self-optimized multi-threshold classification, 2) over-detection removal using land-cover information and change detection, 3) under-detection compensation, and 4) machine-learning based correction. Algorithm details are introduced in another poster, H53J-1603. Good agreements were obtained by comparing the result from RAPID with visual interpretation of SAR images and manual processing from Dartmouth Flood Observatory (DFO) (See Figure 1). Specifically, the over- and under-detections that is typically noted in automated methods is significantly reduced to negligible levels. This performance indicates that RAPID can address the automation and accuracy issues of current state-of-art algorithms and has the potential to apply operationally on a number of satellite SAR missions, such as SWOT, ALOS, Sentinel etc. RAPID data can support many applications such as rapid assessment of damage losses and disaster alleviation/rescue at global scale.

Operational monitoring of land-cover change using multitemporal remote sensing data

NASA Astrophysics Data System (ADS)

Rogan, John

2005-11-01

Land-cover change, manifested as either land-cover modification and/or conversion, can occur at all spatial scales, and changes at local scales can have profound, cumulative impacts at broader scales. The implication of operational land-cover monitoring is that researchers have access to a continuous stream of remote sensing data, with the long term goal of providing for consistent and repetitive mapping. Effective large area monitoring of land-cover (i.e., >1000 km2) can only be accomplished by using remotely sensed images as an indirect data source in land-cover change mapping and as a source for land-cover change model projections. Large area monitoring programs face several challenges: (1) choice of appropriate classification scheme/map legend over large, topographically and phenologically diverse areas; (2) issues concerning data consistency and map accuracy (i.e., calibration and validation); (3) very large data volumes; (4) time consuming data processing and interpretation. Therefore, this dissertation research broadly addresses these challenges in the context of examining state-of-the-art image pre-processing, spectral enhancement, classification, and accuracy assessment techniques to assist the California Land-cover Mapping and Monitoring Program (LCMMP). The results of this dissertation revealed that spatially varying haze can be effectively corrected from Landsat data for the purposes of change detection. The Multitemporal Spectral Mixture Analysis (MSMA) spectral enhancement technique produced more accurate land-cover maps than those derived from the Multitemporal Kauth Thomas (MKT) transformation in northern and southern California study areas. A comparison of machine learning classifiers showed that Fuzzy ARTMAP outperformed two classification tree algorithms, based on map accuracy and algorithm robustness. Variation in spatial data error (positional and thematic) was explored in relation to environmental variables using geostatistical interpolation techniques. Finally, the land-cover modification maps generated for three time intervals (1985--1990--1996--2000), with nine change-classes revealed important variations in land-cover gain and loss between northern and southern California study areas.

New mapping techniques help assess the health of Hawaii's coral reefs

USGS Publications Warehouse

Field, M.E.; Chavez, P.S.; Evans, K.R.; Cochran, S.A.

2001-01-01

The U.S. Geological Survey (USGS) is working closely with academic institutions and state and Federal agencies to assess the factors that affect the health of Hawaii's and our Nation's coral reefs. In order to establish a basis from which scientists can objectively detect changes in reef health, the USGS and its cooperators are applying many new techniques to the mapping and monitoring of coral reefs in Hawaii.

Early detection of sporadic pancreatic cancer: strategic map for innovation--a white paper.

PubMed

Kenner, Barbara J; Chari, Suresh T; Cleeter, Deborah F; Go, Vay Liang W

2015-07-01

Innovation leading to significant advances in research and subsequent translation to clinical practice is urgently necessary in early detection of sporadic pancreatic cancer. Addressing this need, the Early Detection of Sporadic Pancreatic Cancer Summit Conference was conducted by Kenner Family Research Fund in conjunction with the 2014 American Pancreatic Association and Japan Pancreas Society Meeting. International interdisciplinary scientific representatives engaged in strategic facilitated conversations based on distinct areas of inquiry: Case for Early Detection: Definitions, Detection, Survival, and Challenges; Biomarkers for Early Detection; Imaging; and Collaborative Studies. Ideas generated from the summit have led to the development of a Strategic Map for Innovation built upon 3 components: formation of an international collaborative effort, design of an actionable strategic plan, and implementation of operational standards, research priorities, and first-phase initiatives. Through invested and committed efforts of leading researchers and institutions, philanthropic partners, government agencies, and supportive business entities, this endeavor will change the future of the field and consequently the survival rate of those diagnosed with pancreatic cancer.

Updating National Topographic Data Base Using Change Detection Methods

NASA Astrophysics Data System (ADS)

Keinan, E.; Felus, Y. A.; Tal, Y.; Zilberstien, O.; Elihai, Y.

2016-06-01

The traditional method for updating a topographic database on a national scale is a complex process that requires human resources, time and the development of specialized procedures. In many National Mapping and Cadaster Agencies (NMCA), the updating cycle takes a few years. Today, the reality is dynamic and the changes occur every day, therefore, the users expect that the existing database will portray the current reality. Global mapping projects which are based on community volunteers, such as OSM, update their database every day based on crowdsourcing. In order to fulfil user's requirements for rapid updating, a new methodology that maps major interest areas while preserving associated decoding information, should be developed. Until recently, automated processes did not yield satisfactory results, and a typically process included comparing images from different periods. The success rates in identifying the objects were low, and most were accompanied by a high percentage of false alarms. As a result, the automatic process required significant editorial work that made it uneconomical. In the recent years, the development of technologies in mapping, advancement in image processing algorithms and computer vision, together with the development of digital aerial cameras with NIR band and Very High Resolution satellites, allow the implementation of a cost effective automated process. The automatic process is based on high-resolution Digital Surface Model analysis, Multi Spectral (MS) classification, MS segmentation, object analysis and shape forming algorithms. This article reviews the results of a novel change detection methodology as a first step for updating NTDB in the Survey of Israel.

Airborne Remote Sensing

NASA Technical Reports Server (NTRS)

1992-01-01

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

Vegetation mapping and stress detection in the Santa Monica Mountains, California

NASA Technical Reports Server (NTRS)

Price, Curtis V.; Westman, Walter E.

1987-01-01

Thematic Mapper (TM) simulator data have been used to map coastal sage scrub in the mountains near Los Angeles by means of supervised classification. Changes in TM band radiances and band ratios are examined along an east-west gradient in ozone pollution loads. While the changes noted are interpretable in terms of ozone- and temperature-induced premature leaf drop, and consequent exposure of a dry, grassy understory, TM band and band ratio reflectances are influenced by a variety of independent factors which require that pollution stress interpretations be conducted in the context of the greatest possible ecological system comprehension.

On improving IED object detection by exploiting scene geometry using stereo processing

NASA Astrophysics Data System (ADS)

van de Wouw, Dennis W. J. M.; Dubbelman, Gijs; de With, Peter H. N.

2015-03-01

Detecting changes in the environment with respect to an earlier data acquisition is important for several applications, such as finding Improvised Explosive Devices (IEDs). We explore and evaluate the benefit of depth sensing in the context of automatic change detection, where an existing monocular system is extended with a second camera in a fixed stereo setup. We then propose an alternative frame registration that exploits scene geometry, in particular the ground plane. Furthermore, change characterization is applied to localized depth maps to distinguish between 3D physical changes and shadows, which solves one of the main challenges of a monocular system. The proposed system is evaluated on real-world acquisitions, containing geo-tagged test objects of 18 18 9 cm up to a distance of 60 meters. The proposed extensions lead to a significant reduction of the false-alarm rate by a factor of 3, while simultaneously improving the detection score with 5%.

Multiple pedestrian detection using IR LED stereo camera

NASA Astrophysics Data System (ADS)

Ling, Bo; Zeifman, Michael I.; Gibson, David R. P.

2007-09-01

As part of the U.S. Department of Transportations Intelligent Vehicle Initiative (IVI) program, the Federal Highway Administration (FHWA) is conducting R&D in vehicle safety and driver information systems. There is an increasing number of applications where pedestrian monitoring is of high importance. Visionbased pedestrian detection in outdoor scenes is still an open challenge. People dress in very different colors that sometimes blend with the background, wear hats or carry bags, and stand, walk and change directions unpredictably. The background is various, containing buildings, moving or parked cars, bicycles, street signs, signals, etc. Furthermore, existing pedestrian detection systems perform only during daytime, making it impossible to detect pedestrians at night. Under FHWA funding, we are developing a multi-pedestrian detection system using IR LED stereo camera. This system, without using any templates, detects the pedestrians through statistical pattern recognition utilizing 3D features extracted from the disparity map. A new IR LED stereo camera is being developed, which can help detect pedestrians during daytime and night time. Using the image differencing and denoising, we have also developed new methods to estimate the disparity map of pedestrians in near real time. Our system will have a hardware interface with the traffic controller through wireless communication. Once pedestrians are detected, traffic signals at the street intersections will change phases to alert the drivers of approaching vehicles. The initial test results using images collected at a street intersection show that our system can detect pedestrians in near real time.

Detecting Surface Changes from an Underground Explosion in Granite Using Unmanned Aerial System Photogrammetry

DOE PAGES

Schultz-Fellenz, Emily S.; Coppersmith, Ryan T.; Sussman, Aviva J.; ...

2017-08-19

Efficient detection and high-fidelity quantification of surface changes resulting from underground activities are important national and global security efforts. In this investigation, a team performed field-based topographic characterization by gathering high-quality photographs at very low altitudes from an unmanned aerial system (UAS)-borne camera platform. The data collection occurred shortly before and after a controlled underground chemical explosion as part of the United States Department of Energy’s Source Physics Experiments (SPE-5) series. The high-resolution overlapping photographs were used to create 3D photogrammetric models of the site, which then served to map changes in the landscape down to 1-cm-scale. Separate models weremore » created for two areas, herein referred to as the test table grid region and the nearfield grid region. The test table grid includes the region within ~40 m from surface ground zero, with photographs collected at a flight altitude of 8.5 m above ground level (AGL). The near-field grid area covered a broader area, 90–130 m from surface ground zero, and collected at a flight altitude of 22 m AGL. The photographs, processed using Agisoft Photoscan® in conjunction with 125 surveyed ground control point targets, yielded a 6-mm pixel-size digital elevation model (DEM) for the test table grid region. This provided the ≤3 cm resolution in the topographic data to map in fine detail a suite of features related to the underground explosion: uplift, subsidence, surface fractures, and morphological change detection. The near-field grid region data collection resulted in a 2-cm pixel-size DEM, enabling mapping of a broader range of features related to the explosion, including: uplift and subsidence, rock fall, and slope sloughing. This study represents one of the first works to constrain, both temporally and spatially, explosion-related surface damage using a UAS photogrammetric platform; these data will help to advance the science of underground explosion detection.« less

Detecting Surface Changes from an Underground Explosion in Granite Using Unmanned Aerial System Photogrammetry

NASA Astrophysics Data System (ADS)

Schultz-Fellenz, Emily S.; Coppersmith, Ryan T.; Sussman, Aviva J.; Swanson, Erika M.; Cooley, James A.

2017-08-01

Efficient detection and high-fidelity quantification of surface changes resulting from underground activities are important national and global security efforts. In this investigation, a team performed field-based topographic characterization by gathering high-quality photographs at very low altitudes from an unmanned aerial system (UAS)-borne camera platform. The data collection occurred shortly before and after a controlled underground chemical explosion as part of the United States Department of Energy's Source Physics Experiments (SPE-5) series. The high-resolution overlapping photographs were used to create 3D photogrammetric models of the site, which then served to map changes in the landscape down to 1-cm-scale. Separate models were created for two areas, herein referred to as the test table grid region and the nearfield grid region. The test table grid includes the region within 40 m from surface ground zero, with photographs collected at a flight altitude of 8.5 m above ground level (AGL). The near-field grid area covered a broader area, 90-130 m from surface ground zero, and collected at a flight altitude of 22 m AGL. The photographs, processed using Agisoft Photoscan® in conjunction with 125 surveyed ground control point targets, yielded a 6-mm pixel-size digital elevation model (DEM) for the test table grid region. This provided the ≤3 cm resolution in the topographic data to map in fine detail a suite of features related to the underground explosion: uplift, subsidence, surface fractures, and morphological change detection. The near-field grid region data collection resulted in a 2-cm pixel-size DEM, enabling mapping of a broader range of features related to the explosion, including: uplift and subsidence, rock fall, and slope sloughing. This study represents one of the first works to constrain, both temporally and spatially, explosion-related surface damage using a UAS photogrammetric platform; these data will help to advance the science of underground explosion detection.

Detecting Surface Changes from an Underground Explosion in Granite Using Unmanned Aerial System Photogrammetry

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

Schultz-Fellenz, Emily S.; Coppersmith, Ryan T.; Sussman, Aviva J.

Efficient detection and high-fidelity quantification of surface changes resulting from underground activities are important national and global security efforts. In this investigation, a team performed field-based topographic characterization by gathering high-quality photographs at very low altitudes from an unmanned aerial system (UAS)-borne camera platform. The data collection occurred shortly before and after a controlled underground chemical explosion as part of the United States Department of Energy’s Source Physics Experiments (SPE-5) series. The high-resolution overlapping photographs were used to create 3D photogrammetric models of the site, which then served to map changes in the landscape down to 1-cm-scale. Separate models weremore » created for two areas, herein referred to as the test table grid region and the nearfield grid region. The test table grid includes the region within ~40 m from surface ground zero, with photographs collected at a flight altitude of 8.5 m above ground level (AGL). The near-field grid area covered a broader area, 90–130 m from surface ground zero, and collected at a flight altitude of 22 m AGL. The photographs, processed using Agisoft Photoscan® in conjunction with 125 surveyed ground control point targets, yielded a 6-mm pixel-size digital elevation model (DEM) for the test table grid region. This provided the ≤3 cm resolution in the topographic data to map in fine detail a suite of features related to the underground explosion: uplift, subsidence, surface fractures, and morphological change detection. The near-field grid region data collection resulted in a 2-cm pixel-size DEM, enabling mapping of a broader range of features related to the explosion, including: uplift and subsidence, rock fall, and slope sloughing. This study represents one of the first works to constrain, both temporally and spatially, explosion-related surface damage using a UAS photogrammetric platform; these data will help to advance the science of underground explosion detection.« less

Applying the metro map to software development management

NASA Astrophysics Data System (ADS)

Aguirregoitia, Amaia; Dolado, J. Javier; Presedo, Concepción

2010-01-01

This paper presents MetroMap, a new graphical representation model for controlling and managing the software development process. Metromap uses metaphors and visual representation techniques to explore several key indicators in order to support problem detection and resolution. The resulting visualization addresses diverse management tasks, such as tracking of deviations from the plan, analysis of patterns of failure detection and correction, overall assessment of change management policies, and estimation of product quality. The proposed visualization uses a metaphor with a metro map along with various interactive techniques to represent information concerning the software development process and to deal efficiently with multivariate visual queries. Finally, the paper shows the implementation of the tool in JavaFX with data of a real project and the results of testing the tool with the aforementioned data and users attempting several information retrieval tasks. The conclusion shows the results of analyzing user response time and efficiency using the MetroMap visualization system. The utility of the tool was positively evaluated.

Wet Snow Mapping in Southern Ontario with Sentinel-1A Observations

NASA Astrophysics Data System (ADS)

Chen, H.; Kelly, R. E. J.

2017-12-01

Wet snow is defined as snow with liquid water present in an ice-water mix. It is can be an indicator for the onset of the snowmelt period. Knowledge about the extent of wet snow area can be of great importance for the monitoring of seasonal snowmelt runoff with climate-induced changes in snowmelt duration having implications for operational hydrological and ecological applications. Spaceborne microwave remote sensing has been used to observe seasonal snow under all-weather conditions. Active microwave observations of snow at C-band are sensitive to wet snow due to the high dielectric contrast with non-wet snow surfaces and synthetic aperture radar (SAR) is now openly available to identify and map the wet snow areas globally at relatively fine spatial resolutions ( 100m). In this study, a semi-automated workflow is developed from the change detection method of Nagler et al. (2016) using multi-temporal Sentinel-1A (S1A) dual-polarization observations of Southern Ontario. Weather station data and visible-infrared satellite observations are used to refine the wet snow area estimates. Wet snow information from National Operational Hydrologic Remote Sensing Center (NOHRSC) is used to compare with the S1A estimates. A time series of wet snow maps shows the variations in backscatter from wet snow on a pixel basis. Different land cover types in Southern Ontario are assessed with respect to their impacts on wet snow estimates. While forests and complex land surfaces can impact the ability to map wet snow, the approach taken is robust and illustrates the strong sensitivity of the approach to wet snow backscattering characteristics. The results indicate the feasibility of the change detection method on non-mountainous large areas and address the usefulness of Sentinel-1A data for wet snow mapping.

3D change detection at street level using mobile laser scanning point clouds and terrestrial images

NASA Astrophysics Data System (ADS)

Qin, Rongjun; Gruen, Armin

2014-04-01

Automatic change detection and geo-database updating in the urban environment are difficult tasks. There has been much research on detecting changes with satellite and aerial images, but studies have rarely been performed at the street level, which is complex in its 3D geometry. Contemporary geo-databases include 3D street-level objects, which demand frequent data updating. Terrestrial images provides rich texture information for change detection, but the change detection with terrestrial images from different epochs sometimes faces problems with illumination changes, perspective distortions and unreliable 3D geometry caused by the lack of performance of automatic image matchers, while mobile laser scanning (MLS) data acquired from different epochs provides accurate 3D geometry for change detection, but is very expensive for periodical acquisition. This paper proposes a new method for change detection at street level by using combination of MLS point clouds and terrestrial images: the accurate but expensive MLS data acquired from an early epoch serves as the reference, and terrestrial images or photogrammetric images captured from an image-based mobile mapping system (MMS) at a later epoch are used to detect the geometrical changes between different epochs. The method will automatically mark the possible changes in each view, which provides a cost-efficient method for frequent data updating. The methodology is divided into several steps. In the first step, the point clouds are recorded by the MLS system and processed, with data cleaned and classified by semi-automatic means. In the second step, terrestrial images or mobile mapping images at a later epoch are taken and registered to the point cloud, and then point clouds are projected on each image by a weighted window based z-buffering method for view dependent 2D triangulation. In the next step, stereo pairs of the terrestrial images are rectified and re-projected between each other to check the geometrical consistency between point clouds and stereo images. Finally, an over-segmentation based graph cut optimization is carried out, taking into account the color, depth and class information to compute the changed area in the image space. The proposed method is invariant to light changes, robust to small co-registration errors between images and point clouds, and can be applied straightforwardly to 3D polyhedral models. This method can be used for 3D street data updating, city infrastructure management and damage monitoring in complex urban scenes.

Environmental monitoring and assessment of landscape dynamics in southern coast of the Caspian Sea through intensity analysis and imprecise land-use data.

PubMed

Hasani, Mohammad; Sakieh, Yousef; Dezhkam, Sadeq; Ardakani, Tahereh; Salmanmahiny, Abdolrassoul

2017-04-01

A hierarchical intensity analysis of land-use change is applied to evaluate the dynamics of a coupled urban coastal system in Rasht County, Iran. Temporal land-use layers of 1987, 1999, and 2011 are employed, while spatial accuracy metrics are only available for 2011 data (overall accuracy of 94%). The errors in 1987 and 1999 layers are unknown, which can influence the accuracy of temporal change information. Such data were employed to examine the size and the type of errors that could justify deviations from uniform change intensities. Accordingly, errors comprising 3.31 and 7.47% of 1999 and 2011 maps, respectively, could explain all differences from uniform gains and errors including 5.21 and 1.81% of 1987 and 1999 maps, respectively, could explain all deviations from uniform losses. Additional historical information is also applied for uncertainty assessment and to separate probable map errors from actual land-use changes. In this regard, historical processes in Rasht County can explain different types of transition that are either consistent or inconsistent to known processes. The intensity analysis assisted in identification of systematic transitions and detection of competitive categories, which cannot be investigated through conventional change detection methods. Based on results, built-up area is the most active gaining category in the area and wetland category with less areal extent is more sensitive to intense land-use change processes. Uncertainty assessment results also indicated that there are no considerable classification errors in temporal land-use data and these imprecise layers can reliably provide implications for informed decision making.

Multiscale-Driven approach to detecting change in Synthetic Aperture Radar (SAR) imagery

NASA Astrophysics Data System (ADS)

Gens, R.; Hogenson, K.; Ajadi, O. A.; Meyer, F. J.; Myers, A.; Logan, T. A.; Arnoult, K., Jr.

2017-12-01

Detecting changes between Synthetic Aperture Radar (SAR) images can be a useful but challenging exercise. SAR with its all-weather capabilities can be an important resource in identifying and estimating the expanse of events such as flooding, river ice breakup, earthquake damage, oil spills, and forest growth, as it can overcome shortcomings of optical methods related to cloud cover. However, detecting change in SAR imagery can be impeded by many factors including speckle, complex scattering responses, low temporal sampling, and difficulty delineating boundaries. In this presentation we use a change detection method based on a multiscale-driven approach. By using information at different resolution levels, we attempt to obtain more accurate change detection maps in both heterogeneous and homogeneous regions. Integrated within the processing flow are processes that 1) improve classification performance by combining Expectation-Maximization algorithms with mathematical morphology, 2) achieve high accuracy in preserving boundaries using measurement level fusion techniques, and 3) combine modern non-local filtering and 2D-discrete stationary wavelet transform to provide robustness against noise. This multiscale-driven approach to change detection has recently been incorporated into the Alaska Satellite Facility (ASF) Hybrid Pluggable Processing Pipeline (HyP3) using radiometrically terrain corrected SAR images. Examples primarily from natural hazards are presented to illustrate the capabilities and limitations of the change detection method.

An Unsupervised Change Detection Method Using Time-Series of PolSAR Images from Radarsat-2 and GaoFen-3.

PubMed

Liu, Wensong; Yang, Jie; Zhao, Jinqi; Shi, Hongtao; Yang, Le

2018-02-12

The traditional unsupervised change detection methods based on the pixel level can only detect the changes between two different times with same sensor, and the results are easily affected by speckle noise. In this paper, a novel method is proposed to detect change based on time-series data from different sensors. Firstly, the overall difference image of the time-series PolSAR is calculated by omnibus test statistics, and difference images between any two images in different times are acquired by R j test statistics. Secondly, the difference images are segmented with a Generalized Statistical Region Merging (GSRM) algorithm which can suppress the effect of speckle noise. Generalized Gaussian Mixture Model (GGMM) is then used to obtain the time-series change detection maps in the final step of the proposed method. To verify the effectiveness of the proposed method, we carried out the experiment of change detection using time-series PolSAR images acquired by Radarsat-2 and Gaofen-3 over the city of Wuhan, in China. Results show that the proposed method can not only detect the time-series change from different sensors, but it can also better suppress the influence of speckle noise and improve the overall accuracy and Kappa coefficient.

Large area robust identification of snow cover from multitemporal COSMO-SkyMed images

NASA Astrophysics Data System (ADS)

Pettinato, S.; Santi, E.; Paloscia, S.; Aiazzi, B.; Baronti, S.; Palchetti, E.; Garzelli, A.

2015-10-01

This paper investigates the ability of the Information Theoretic Snow Detection Algorithm (ITSDA) in detecting changes due to snow cover between summer and winter seasons on large area images acquired by COSMO-SkyMed constellation. ITSDA is a method for change detection in multitemporal SAR images, which has been recently applied by the authors to a subset of Cosmo-SkyMed data. The proposed technique is based on a nonparametric approach in the framework of Shannon's information theory, and in particular it features the conditional probability of the local means between the two images taken at different times. Such an unsupervised approach does not require any preliminary despeckling procedure to be performed before the calculation of the change map. In the case of a low quantity of anomalous changes in relatively small-size images, a mean shift procedure can be utilized for refining the map. However, in the present investigation, the changes to be identified are pervasive in large size images. Consequently, for computational issues, the mean shift refinement has been omitted in the present work. However, a simplified implementation of mean shift procedure to save time will be possibly considered in future submissions. In any case, the present version of ITSDA method preserve its characteristics of flexibility and sensibility to backscattering changes, thanks to the possibility of setting up the number of quantization levels in the estimation of the conditional probability between the amplitude values at the two acquisition dates.

Change Detection via Selective Guided Contrasting Filters

NASA Astrophysics Data System (ADS)

Vizilter, Y. V.; Rubis, A. Y.; Zheltov, S. Y.

2017-05-01

Change detection scheme based on guided contrasting was previously proposed. Guided contrasting filter takes two images (test and sample) as input and forms the output as filtered version of test image. Such filter preserves the similar details and smooths the non-similar details of test image with respect to sample image. Due to this the difference between test image and its filtered version (difference map) could be a basis for robust change detection. Guided contrasting is performed in two steps: at the first step some smoothing operator (SO) is applied for elimination of test image details; at the second step all matched details are restored with local contrast proportional to the value of some local similarity coefficient (LSC). The guided contrasting filter was proposed based on local average smoothing as SO and local linear correlation as LSC. In this paper we propose and implement new set of selective guided contrasting filters based on different combinations of various SO and thresholded LSC. Linear average and Gaussian smoothing, nonlinear median filtering, morphological opening and closing are considered as SO. Local linear correlation coefficient, morphological correlation coefficient (MCC), mutual information, mean square MCC and geometrical correlation coefficients are applied as LSC. Thresholding of LSC allows operating with non-normalized LSC and enhancing the selective properties of guided contrasting filters: details are either totally recovered or not recovered at all after the smoothing. These different guided contrasting filters are tested as a part of previously proposed change detection pipeline, which contains following stages: guided contrasting filtering on image pyramid, calculation of difference map, binarization, extraction of change proposals and testing change proposals using local MCC. Experiments on real and simulated image bases demonstrate the applicability of all proposed selective guided contrasting filters. All implemented filters provide the robustness relative to weak geometrical discrepancy of compared images. Selective guided contrasting based on morphological opening/closing and thresholded morphological correlation demonstrates the best change detection result.

ForWarn: A Cross-Cutting Forest Resource Management and Decision Support System Providing the Capacity to Identify and Track Forest Disturbances Nationally

NASA Astrophysics Data System (ADS)

Hargrove, W. W.; Spruce, J.; Norman, S.; Christie, W.; Hoffman, F. M.

2012-12-01

The Eastern Forest Environmental Threat Assessment Center and Western Wildland Environmental Assessment Center of the USDA Forest Service have collaborated with NASA Stennis Space Center to develop ForWarn, a forest monitoring tool that uses MODIS satellite imagery to produce weekly snapshots of vegetation conditions across the lower 48 United States. Forest and natural resource managers can use ForWarn to rapidly detect, identify, and respond to unexpected changes in the nation's forests caused by insects, diseases, wildfires, severe weather, or other natural or human-caused events. ForWarn detects most types of forest disturbances, including insects, disease, wildfires, frost and ice damage, tornadoes, hurricanes, blowdowns, harvest, urbanization, and landslides. It also detects drought, flood, and temperature effects, and shows early and delayed seasonal vegetation development. Operating continuously since January 2010, results show ForWarn to be a robust and highly capable tool for detecting changes in forest conditions. ForWarn is the first national-scale system of its kind based on remote sensing developed specifically for forest disturbances. It has operated as a prototype since January 2010 and has provided useful information about the location and extent of disturbances detected during the 2011 growing season, including tornadoes, wildfires, and extreme drought. The ForWarn system had an official unveiling and rollout in March 2012, initiated by a joint NASA and USDA press release. The ForWarn home page has had 2,632 unique visitors since rollout in March 2012, with 39% returning visits. ForWarn was used to map tornado scars from the historic April 27, 2011 tornado outbreak, and detected timber damage within more than a dozen tornado tracks across northern Mississippi, Alabama, and Georgia. ForWarn is the result of an ongoing, substantive cooperation among four different government agencies: USDA, NASA, USGS, and DOE. Disturbance maps are available on the web through the ForWarn Change Assessment Viewer at http://forwarn.forestthreats.org/fcav. No user id or password is required, and there is no cost. The Assessment Viewer operates within any popular web browser using nearly any type of computer. It lets users pan, zoom, and scroll around within ForWarn maps, and also contains an up-to-date library of co-registered, near real-time ancillary maps from diverse sources that allows users to assess the nature of particular forest disturbances and ascribe their most-likely causes. Users can check the current week's U.S. Drought Monitor, USGS VegDRI maps, FHM Historical Aerial Disturbance Surveys, MODIS Cumulative Current Year Fire Detections, and many others. A "Share this map" feature lets users save the current map view and extent into a web URL, so that users can easily share what they are looking at inside the Assessment Viewer with others via an email, a document, or a web page. The ForWarn Rapid National Assessment Team examined more than 60 ForWarn forest disturbance events in 2011-2012, and issued over 30 alerts. We hope to automate forest disturbance alerts and supply them through various subscription services. Forest owners and managers would only be alerted to disturbances occurring near their own forest resources.

Utilization of ERTS-1 data in the Houston area

NASA Technical Reports Server (NTRS)

Erb, R. B. (Principal Investigator)

1973-01-01

The author has identified the following significant results. Using clustering techniques, several large lakes in Texas have been accurately delineated in computer printout graymaps. It was also found that small bodies of water (one to two acres in size) could be detected by searching for small reflectance values in the infrared data. A graymap printout of a lake described a shore outline that was not consistent with available maps. Field examination revealed that the actual level of the lake was below that for which the map was drawn. The current lake configuration agrees in shape and relative size with the ERTS-1 data printout. Water turbidity causes reflectance changes which are detectable in ERTS-1 band 7 data. A comparison has been made of the Monterey Bay, California area using 1971 aerial color infrared photography and a 1972 ERTS-1 band 7 infrared image. This comparison revealed that some event has occurred to impound a significant amount of water in the area since the infrared photography was taken. Data values in the ERTS-1 infrared image exhibit detectable changes in brightness at inflow points, where high turbidity would be present. Researchers had not expected to detect water turbidity patterns in band 7 (800 to 1100 nanometers).

Surface plasmon holographic microscopy for near-field refractive index detection and thin film mapping

NASA Astrophysics Data System (ADS)

Zhao, Jianlin; Zhang, Jiwei; Dai, Siqing; Di, Jianglei; Xi, Teli

2018-02-01

Surface plasmon microscopy (SPM) is widely applied for label-free detection of changes of refractive index and concentration, as well as mapping thin films in near field. Traditionally, the SPM systems are based on the detection of light intensity or phase changes. Here, we present two kinds of surface plasmon holographic microscopy (SPHM) systems for amplitude- and phase-contrast imaging simultaneously. Through recording off-axis holograms and numerical reconstruction, the complex amplitude distributions of surface plasmon resonance (SPR) images can be obtained. According to the Fresnel's formula, in a prism/ gold/ dielectric structure, the reflection phase shift is uniquely decided by refractive index of the dielectric. By measuring the phase shift difference of the reflected light exploiting prism-coupling SPHM system based on common-path interference configuration, monitoring tiny refractive index variation and imaging biological tissue are performed. Furthermore, to characterize the thin film thickness in near field, we employ a four-layer SPR model in which the third film layer is within the evanescent field. The complex reflection coefficient, including the reflectivity and reflection phase shift, is uniquely decided by the film thickness. By measuring the complex amplitude distributions of the SPR images exploiting objective-coupling SPHM system based on common-path interference configuration, the thickness distributions of thin films are mapped with sub-nanometer resolution theoretically. Owing to its high temporal stability, the recommended SPHMs show great potentials for monitoring tiny refractive index variations, imaging biological tissues and mapping thin films in near field with dynamic, nondestructive and full-field measurement capabilities in chemistry, biomedicine field, etc.

Event-related functional MRI: Past, present, and future

PubMed Central

Rosen, Bruce R.; Buckner, Randy L.; Dale, Anders M.

1998-01-01

The past two decades have seen an enormous growth in the field of human brain mapping. Investigators have extensively exploited techniques such as positron emission tomography and MRI to map patterns of brain activity based on changes in cerebral hemodynamics. However, until recently, most studies have investigated equilibrium changes in blood flow measured over time periods upward of 1 min. The advent of high-speed MRI methods, capable of imaging the entire brain with a temporal resolution of a few seconds, allows for brain mapping based on more transient aspects of the hemodynamic response. Today it is now possible to map changes in cerebrovascular parameters essentially in real time, conferring the ability to observe changes in brain state that occur over time periods of seconds. Furthermore, because robust hemodynamic alterations are detectable after neuronal stimuli lasting only a few tens of milliseconds, a new class of task paradigms designed to measure regional responses to single sensory or cognitive events can now be studied. Such “event related” functional MRI should provide for fundamentally new ways to interrogate brain function, and allow for the direct comparison and ultimately integration of data acquired by using more traditional behavioral and electrophysiological methods. PMID:9448240

The Effect of Local Orientation Change on the Detection of Contours Defined by Constant Curvature: Psychophysics and Image Statistics.

PubMed

Khuu, Sieu K; Cham, Joey; Hayes, Anthony

2016-01-01

In the present study, we investigated the detection of contours defined by constant curvature and the statistics of curved contours in natural scenes. In Experiment 1, we examined the degree to which human sensitivity to contours is affected by changing the curvature angle and disrupting contour curvature continuity by varying the orientation of end elements. We find that (1) changing the angle of contour curvature decreased detection performance, while (2) end elements oriented in the direction (i.e., clockwise) of curvature facilitated contour detection regardless of the curvature angle of the contour. In Experiment 2 we further established that the relative effect of end-element orientation on contour detection was not only dependent on their orientation (collinear or cocircular), but also their spatial separation from the contour, and whether the contour shape was curved or not (i.e., C-shaped or S-shaped). Increasing the spatial separation of end-elements reduced contour detection performance regardless of their orientation or the contour shape. However, at small separations, cocircular end-elements facilitated the detection of C-shaped contours, but not S-shaped contours. The opposite result was observed for collinear end-elements, which improved the detection of S- shaped, but not C-shaped contours. These dissociative results confirmed that the visual system specifically codes contour curvature, but the association of contour elements occurs locally. Finally, we undertook an analysis of natural images that mapped contours with a constant angular change and determined the frequency of occurrence of end elements with different orientations. Analogous to our behavioral data, this image analysis revealed that the mapped end elements of constantly curved contours are likely to be oriented clockwise to the angle of curvature. Our findings indicate that the visual system is selectively sensitive to contours defined by constant curvature and that this might reflect the properties of curved contours in natural images.

Where to restore ecological connectivity? Detecting barriers and quantifying restoration benefits.

PubMed

McRae, Brad H; Hall, Sonia A; Beier, Paul; Theobald, David M

2012-01-01

Landscape connectivity is crucial for many ecological processes, including dispersal, gene flow, demographic rescue, and movement in response to climate change. As a result, governmental and non-governmental organizations are focusing efforts to map and conserve areas that facilitate movement to maintain population connectivity and promote climate adaptation. In contrast, little focus has been placed on identifying barriers-landscape features which impede movement between ecologically important areas-where restoration could most improve connectivity. Yet knowing where barriers most strongly reduce connectivity can complement traditional analyses aimed at mapping best movement routes. We introduce a novel method to detect important barriers and provide example applications. Our method uses GIS neighborhood analyses in conjunction with effective distance analyses to detect barriers that, if removed, would significantly improve connectivity. Applicable in least-cost, circuit-theoretic, and simulation modeling frameworks, the method detects both complete (impermeable) barriers and those that impede but do not completely block movement. Barrier mapping complements corridor mapping by broadening the range of connectivity conservation alternatives available to practitioners. The method can help practitioners move beyond maintaining currently important areas to restoring and enhancing connectivity through active barrier removal. It can inform decisions on trade-offs between restoration and protection; for example, purchasing an intact corridor may be substantially more costly than restoring a barrier that blocks an alternative corridor. And it extends the concept of centrality to barriers, highlighting areas that most diminish connectivity across broad networks. Identifying which modeled barriers have the greatest impact can also help prioritize error checking of land cover data and collection of field data to improve connectivity maps. Barrier detection provides a different way to view the landscape, broadening thinking about connectivity and fragmentation while increasing conservation options.

Where to Restore Ecological Connectivity? Detecting Barriers and Quantifying Restoration Benefits

PubMed Central

McRae, Brad H.; Hall, Sonia A.; Beier, Paul; Theobald, David M.

2012-01-01

Landscape connectivity is crucial for many ecological processes, including dispersal, gene flow, demographic rescue, and movement in response to climate change. As a result, governmental and non-governmental organizations are focusing efforts to map and conserve areas that facilitate movement to maintain population connectivity and promote climate adaptation. In contrast, little focus has been placed on identifying barriers—landscape features which impede movement between ecologically important areas—where restoration could most improve connectivity. Yet knowing where barriers most strongly reduce connectivity can complement traditional analyses aimed at mapping best movement routes. We introduce a novel method to detect important barriers and provide example applications. Our method uses GIS neighborhood analyses in conjunction with effective distance analyses to detect barriers that, if removed, would significantly improve connectivity. Applicable in least-cost, circuit-theoretic, and simulation modeling frameworks, the method detects both complete (impermeable) barriers and those that impede but do not completely block movement. Barrier mapping complements corridor mapping by broadening the range of connectivity conservation alternatives available to practitioners. The method can help practitioners move beyond maintaining currently important areas to restoring and enhancing connectivity through active barrier removal. It can inform decisions on trade-offs between restoration and protection; for example, purchasing an intact corridor may be substantially more costly than restoring a barrier that blocks an alternative corridor. And it extends the concept of centrality to barriers, highlighting areas that most diminish connectivity across broad networks. Identifying which modeled barriers have the greatest impact can also help prioritize error checking of land cover data and collection of field data to improve connectivity maps. Barrier detection provides a different way to view the landscape, broadening thinking about connectivity and fragmentation while increasing conservation options. PMID:23300719

California nearshore processes - ERTS 1. [coastal currents and sediments

NASA Technical Reports Server (NTRS)

Steller, D. D.; Pirie, D. M.

1974-01-01

The detectability of many nearshore processes from ERTS is made possible due to the suspended sediment present in the coastal waters. From viewing and analyzing the California coastal imagery collected during the last year and a half, the overall current patterns and their changes have become evident. It is now possible to map monthly and seasonal changes that occur throughout the year. The original objectives of detecting currents, sediment transport, estuaries and river discharge have now been expanded to include the use of ERTS information in operational problems of the U.S. Army Corps of Engineers. This incorporates the detected nearshore features into planning and organizing shore protection facilities.

Colony mapping: A new technique for monitoring crevice-nesting seabirds

USGS Publications Warehouse

Renner, H.M.; Renner, M.; Reynolds, J.H.; Harping, A.M.A.; Jones, I.L.; Irons, D.B.; Byrd, G.V.

2006-01-01

Monitoring populations of auklets and other crevice-nesting seabirds remains problematic, although numerous methods have been attempted since the mid-1960s. Anecdotal evidence suggests several large auklet colonies have recently decreased in both abundance and extent, concurrently with vegetation encroachment and succession. Quantifying changes in the geographical extent of auklet colonies may be a useful alternative to monitoring population size directly. We propose a standardized method for colony mapping using a randomized systematic grid survey with two components: a simple presence/absence survey and an auklet evidence density survey. A quantitative auklet evidence density index was derived from the frequency of droppings and feathers. This new method was used to map the colony on St. George Island in the southeastern Bering Sea and results were compared to previous colony mapping efforts. Auklet presence was detected in 62 of 201 grid cells (each grid cell = 2500 m2) by sampling a randomly placed 16 m2 plot in each cell; estimated colony area = 155 000 m2. The auklet evidence density index varied by two orders of magnitude across the colony and was strongly correlated with means of replicated counts of birds socializing on the colony surface. Quantitatively mapping all large auklet colonies is logistically feasible using this method and would provide an important baseline for monitoring colony status. Regularly monitoring select colonies using this method may be the best means of detecting changes in distribution and population size of crevice-nesting seabirds. ?? The Cooper Ornithological Society 2006.

Role of interoceptive accuracy in topographical changes in emotion-induced bodily sensations

PubMed Central

Jung, Won-Mo; Ryu, Yeonhee; Lee, Ye-Seul; Wallraven, Christian; Chae, Younbyoung

2017-01-01

The emotion-associated bodily sensation map is composed of a specific topographical distribution of bodily sensations to categorical emotions. The present study investigated whether or not interoceptive accuracy was associated with topographical changes in this map following emotion-induced bodily sensations. This study included 31 participants who observed short video clips containing emotional stimuli and then reported their sensations on the body map. Interoceptive accuracy was evaluated with a heartbeat detection task and the spatial patterns of bodily sensations to specific emotions, including anger, fear, disgust, happiness, sadness, and neutral, were visualized using Statistical Parametric Mapping (SPM) analyses. Distinct patterns of bodily sensations were identified for different emotional states. In addition, positive correlations were found between the magnitude of sensation in emotion-specific regions and interoceptive accuracy across individuals. A greater degree of interoceptive accuracy was associated with more specific topographical changes after emotional stimuli. These results suggest that the awareness of one’s internal bodily states might play a crucial role as a required messenger of sensory information during the affective process. PMID:28877218

Semi-automatic mapping of cultural heritage from airborne laser scanning using deep learning

NASA Astrophysics Data System (ADS)

Due Trier, Øivind; Salberg, Arnt-Børre; Holger Pilø, Lars; Tonning, Christer; Marius Johansen, Hans; Aarsten, Dagrun

2016-04-01

This paper proposes to use deep learning to improve semi-automatic mapping of cultural heritage from airborne laser scanning (ALS) data. Automatic detection methods, based on traditional pattern recognition, have been applied in a number of cultural heritage mapping projects in Norway for the past five years. Automatic detection of pits and heaps have been combined with visual interpretation of the ALS data for the mapping of deer hunting systems, iron production sites, grave mounds and charcoal kilns. However, the performance of the automatic detection methods varies substantially between ALS datasets. For the mapping of deer hunting systems on flat gravel and sand sediment deposits, the automatic detection results were almost perfect. However, some false detections appeared in the terrain outside of the sediment deposits. These could be explained by other pit-like landscape features, like parts of river courses, spaces between boulders, and modern terrain modifications. However, these were easy to spot during visual interpretation, and the number of missed individual pitfall traps was still low. For the mapping of grave mounds, the automatic method produced a large number of false detections, reducing the usefulness of the semi-automatic approach. The mound structure is a very common natural terrain feature, and the grave mounds are less distinct in shape than the pitfall traps. Still, applying automatic mound detection on an entire municipality did lead to a new discovery of an Iron Age grave field with more than 15 individual mounds. Automatic mound detection also proved to be useful for a detailed re-mapping of Norway's largest Iron Age grave yard, which contains almost 1000 individual graves. Combined pit and mound detection has been applied to the mapping of more than 1000 charcoal kilns that were used by an iron work 350-200 years ago. The majority of charcoal kilns were indirectly detected as either pits on the circumference, a central mound, or both. However, kilns with a flat interior and a shallow ditch along the circumference were often missed by the automatic detection method. The successfulness of automatic detection seems to depend on two factors: (1) the density of ALS ground hits on the cultural heritage structures being sought, and (2) to what extent these structures stand out from natural terrain structures. The first factor may, to some extent, be improved by using a higher number of ALS pulses per square meter. The second factor is difficult to change, and also highlights another challenge: how to make a general automatic method that is applicable in all types of terrain within a country. The mixed experience with traditional pattern recognition for semi-automatic mapping of cultural heritage led us to consider deep learning as an alternative approach. The main principle is that a general feature detector has been trained on a large image database. The feature detector is then tailored to a specific task by using a modest number of images of true and false examples of the features being sought. Results of using deep learning are compared with previous results using traditional pattern recognition.

Applying time series Landsat data for vegetation change analysis in the Florida Everglades Water Conservation Area 2A during 1996-2016

NASA Astrophysics Data System (ADS)

Zhang, Caiyun; Smith, Molly; Lv, Jie; Fang, Chaoyang

2017-05-01

Mapping plant communities and documenting their changes is critical to the on-going Florida Everglades restoration project. In this study, a framework was designed to map dominant vegetation communities and inventory their changes in the Florida Everglades Water Conservation Area 2A (WCA-2A) using time series Landsat images spanning 1996-2016. The object-based change analysis technique was combined in the framework. A hybrid pixel/object-based change detection approach was developed to effectively collect training samples for historical images with sparse reference data. An object-based quantification approach was also developed to assess the expansion/reduction of a specific class such as cattail (an invasive species in the Everglades) from the object-based classifications of two dates of imagery. The study confirmed the results in the literature that cattail was largely expanded during 1996-2007. It also revealed that cattail expansion was constrained after 2007. Application of time series Landsat data is valuable to document vegetation changes for the WCA-2A impoundment. The digital techniques developed will benefit global wetland mapping and change analysis in general, and the Florida Everglades WCA-2A in particular.

Semantic Segmentation and Unregistered Building Detection from Uav Images Using a Deconvolutional Network

NASA Astrophysics Data System (ADS)

Ham, S.; Oh, Y.; Choi, K.; Lee, I.

2018-05-01

Detecting unregistered buildings from aerial images is an important task for urban management such as inspection of illegal buildings in green belt or update of GIS database. Moreover, the data acquisition platform of photogrammetry is evolving from manned aircraft to UAVs (Unmanned Aerial Vehicles). However, it is very costly and time-consuming to detect unregistered buildings from UAV images since the interpretation of aerial images still relies on manual efforts. To overcome this problem, we propose a system which automatically detects unregistered buildings from UAV images based on deep learning methods. Specifically, we train a deconvolutional network with publicly opened geospatial data, semantically segment a given UAV image into a building probability map and compare the building map with existing GIS data. Through this procedure, we could detect unregistered buildings from UAV images automatically and efficiently. We expect that the proposed system can be applied for various urban management tasks such as monitoring illegal buildings or illegal land-use change.

Rapid multislice T1 mapping of mouse myocardium: Application to quantification of manganese uptake in α-Dystrobrevin knockout mice.

PubMed

Jiang, Kai; Li, Wen; Li, Wei; Jiao, Sen; Castel, Laurie; Van Wagoner, David R; Yu, Xin

2015-11-01

The aim of this study was to develop a rapid, multislice cardiac T1 mapping method in mice and to apply the method to quantify manganese (Mn(2+)) uptake in a mouse model with altered Ca(2+) channel activity. An electrocardiography-triggered multislice saturation-recovery Look-Locker method was developed and validated both in vitro and in vivo. A two-dose study was performed to investigate the kinetics of T1 shortening, Mn(2+) relaxivity in myocardium, and the impact of Mn(2+) on cardiac function. The sensitivity of Mn(2+)-enhanced MRI in detecting subtle changes in altered Ca(2+) channel activity was evaluated in a mouse model with α-dystrobrevin knockout. Validation studies showed strong agreement between the current method and an established method. High Mn(2+) dose led to significantly accelerated T1 shortening. Heart rate decreased during Mn(2+) infusion, while ejection ratio increased slightly at the end of imaging protocol. No statistical difference in cardiac function was detected between the two dose groups. Mice with α-dystrobrevin knockout showed enhanced Mn(2+) uptake in vivo. In vitro patch-clamp study showed increased Ca(2+) channel activity. The saturation recovery method provides rapid T1 mapping in mouse hearts, which allowed sensitive detection of subtle changes in Mn(2+) uptake in α-dystrobrevin knockout mice. © 2014 Wiley Periodicals, Inc.

PSE-HMM: genome-wide CNV detection from NGS data using an HMM with Position-Specific Emission probabilities.

PubMed

Malekpour, Seyed Amir; Pezeshk, Hamid; Sadeghi, Mehdi

2016-11-03

Copy Number Variation (CNV) is envisaged to be a major source of large structural variations in the human genome. In recent years, many studies apply Next Generation Sequencing (NGS) data for the CNV detection. However, still there is a necessity to invent more accurate computational tools. In this study, mate pair NGS data are used for the CNV detection in a Hidden Markov Model (HMM). The proposed HMM has position specific emission probabilities, i.e. a Gaussian mixture distribution. Each component in the Gaussian mixture distribution captures a different type of aberration that is observed in the mate pairs, after being mapped to the reference genome. These aberrations may include any increase (decrease) in the insertion size or change in the direction of mate pairs that are mapped to the reference genome. This HMM with Position-Specific Emission probabilities (PSE-HMM) is utilized for the genome-wide detection of deletions and tandem duplications. The performance of PSE-HMM is evaluated on a simulated dataset and also on a real data of a Yoruban HapMap individual, NA18507. PSE-HMM is effective in taking observation dependencies into account and reaches a high accuracy in detecting genome-wide CNVs. MATLAB programs are available at http://bs.ipm.ir/softwares/PSE-HMM/ .

Satellite Earth observation data to identify anthropogenic pressures in selected protected areas

NASA Astrophysics Data System (ADS)

Nagendra, Harini; Mairota, Paola; Marangi, Carmela; Lucas, Richard; Dimopoulos, Panayotis; Honrado, João Pradinho; Niphadkar, Madhura; Mücher, Caspar A.; Tomaselli, Valeria; Panitsa, Maria; Tarantino, Cristina; Manakos, Ioannis; Blonda, Palma

2015-05-01

Protected areas are experiencing increased levels of human pressure. To enable appropriate conservation action, it is critical to map and monitor changes in the type and extent of land cover/use and habitat classes, which can be related to human pressures over time. Satellite Earth observation (EO) data and techniques offer the opportunity to detect such changes. Yet association with field information and expert interpretation by ecologists is required to interpret, qualify and link these changes to human pressure. There is thus an urgent need to harmonize the technical background of experts in the field of EO data analysis with the terminology of ecologists, protected area management authorities and policy makers in order to provide meaningful, context-specific value-added EO products. This paper builds on the DPSIR framework, providing a terminology to relate the concepts of state, pressures, and drivers with the application of EO analysis. The type of pressure can be inferred through the detection of changes in state (i.e. changes in land cover and/or habitat type and/or condition). Four broad categories of changes in state are identified, i.e. land cover/habitat conversion, land cover/habitat modification, habitat fragmentation and changes in landscape connectivity, and changes in plant community structure. These categories of change in state can be mapped through EO analyses, with the goal of using expert judgement to relate changes in state to causal direct anthropogenic pressures. Drawing on expert knowledge, a set of protected areas located in diverse socio-ecological contexts and subject to a variety of pressures are analysed to (a) link the four categories of changes in state of land cover/habitats to the drivers (anthropogenic pressure), as relevant to specific target land cover and habitat classes; (b) identify (for pressure mapping) the most appropriate spatial and temporal EO data sources as well as interpretations from ecologists and field data useful in connection with EO data analysis. We provide detailed examples for two protected areas, demonstrating the use of EO data for detection of land cover/habitat change, coupled with expert interpretation to relate such change to specific anthropogenic pressures. We conclude with a discussion of the limitations and feasibility of using EO data and techniques to identify anthropogenic pressures, suggesting additional research efforts required in this direction.

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

NASA Astrophysics Data System (ADS)

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

2015-12-01

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

Applications of ERTS-1 data to landscape change in eastern Tennessee

NASA Technical Reports Server (NTRS)

Rehder, J. B. (Principal Investigator)

1973-01-01

The author has identified the following significant results. The analysis of landscape change in eastern Tennessee from ERTS-1 data is being derived from three avenues of experimentation and analysis: (1) a multi-stage sampling procedure utilizing ground and aircraft imagery for ground truth and control; (2) a densitometric and computer analytical experiment for the analysis of gray tone signatures and comparisons for landscape change detection and monitoring; and (3) an ERTS image enhancement procedure for the detection and analysis of photomorphic regions. Significant results include: maps of strip mining changes and forest inventory, watershed identification and delimitation, and agricultural regions derived from spring plowing patterns appearing on the ERTS-1 imagery.

MIP-MAP: High-Throughput Mapping of Caenorhabditis elegans Temperature-Sensitive Mutants via Molecular Inversion Probes.

PubMed

Mok, Calvin A; Au, Vinci; Thompson, Owen A; Edgley, Mark L; Gevirtzman, Louis; Yochem, John; Lowry, Joshua; Memar, Nadin; Wallenfang, Matthew R; Rasoloson, Dominique; Bowerman, Bruce; Schnabel, Ralf; Seydoux, Geraldine; Moerman, Donald G; Waterston, Robert H

2017-10-01

Mutants remain a powerful means for dissecting gene function in model organisms such as Caenorhabditis elegans Massively parallel sequencing has simplified the detection of variants after mutagenesis but determining precisely which change is responsible for phenotypic perturbation remains a key step. Genetic mapping paradigms in C . elegans rely on bulk segregant populations produced by crosses with the problematic Hawaiian wild isolate and an excess of redundant information from whole-genome sequencing (WGS). To increase the repertoire of available mutants and to simplify identification of the causal change, we performed WGS on 173 temperature-sensitive (TS) lethal mutants and devised a novel mapping method. The mapping method uses molecular inversion probes (MIP-MAP) in a targeted sequencing approach to genetic mapping, and replaces the Hawaiian strain with a Million Mutation Project strain with high genomic and phenotypic similarity to the laboratory wild-type strain N2 We validated MIP-MAP on a subset of the TS mutants using a competitive selection approach to produce TS candidate mapping intervals with a mean size < 3 Mb. MIP-MAP successfully uses a non-Hawaiian mapping strain and multiplexed libraries are sequenced at a fraction of the cost of WGS mapping approaches. Our mapping results suggest that the collection of TS mutants contains a diverse library of TS alleles for genes essential to development and reproduction. MIP-MAP is a robust method to genetically map mutations in both viable and essential genes and should be adaptable to other organisms. It may also simplify tracking of individual genotypes within population mixtures. Copyright © 2017 by the Genetics Society of America.

MIP-MAP: High-Throughput Mapping of Caenorhabditis elegans Temperature-Sensitive Mutants via Molecular Inversion Probes

PubMed Central

Mok, Calvin A.; Au, Vinci; Thompson, Owen A.; Edgley, Mark L.; Gevirtzman, Louis; Yochem, John; Lowry, Joshua; Memar, Nadin; Wallenfang, Matthew R.; Rasoloson, Dominique; Bowerman, Bruce; Schnabel, Ralf; Seydoux, Geraldine; Moerman, Donald G.; Waterston, Robert H.

2017-01-01

Mutants remain a powerful means for dissecting gene function in model organisms such as Caenorhabditis elegans. Massively parallel sequencing has simplified the detection of variants after mutagenesis but determining precisely which change is responsible for phenotypic perturbation remains a key step. Genetic mapping paradigms in C. elegans rely on bulk segregant populations produced by crosses with the problematic Hawaiian wild isolate and an excess of redundant information from whole-genome sequencing (WGS). To increase the repertoire of available mutants and to simplify identification of the causal change, we performed WGS on 173 temperature-sensitive (TS) lethal mutants and devised a novel mapping method. The mapping method uses molecular inversion probes (MIP-MAP) in a targeted sequencing approach to genetic mapping, and replaces the Hawaiian strain with a Million Mutation Project strain with high genomic and phenotypic similarity to the laboratory wild-type strain N2. We validated MIP-MAP on a subset of the TS mutants using a competitive selection approach to produce TS candidate mapping intervals with a mean size < 3 Mb. MIP-MAP successfully uses a non-Hawaiian mapping strain and multiplexed libraries are sequenced at a fraction of the cost of WGS mapping approaches. Our mapping results suggest that the collection of TS mutants contains a diverse library of TS alleles for genes essential to development and reproduction. MIP-MAP is a robust method to genetically map mutations in both viable and essential genes and should be adaptable to other organisms. It may also simplify tracking of individual genotypes within population mixtures. PMID:28827289

Developing New Coastal Forest Restoration Products Based on Landsat, ASTER, and MODIS Data

NASA Technical Reports Server (NTRS)

Spruce, Joseph P.; Graham, William; Smoot, James

2009-01-01

This paper discusses an ongoing effort to develop new geospatial information products for aiding coastal forest restoration and conservation efforts in coastal Louisiana and Mississippi. This project employs Landsat, Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), and Moderate Resolution Imaging Spectroradiometer (MODIS) satellite data in conjunction with airborne elevation data to compute coastal forest cover type maps and change detection products. Improved forest mapping products are needed to aid coastal forest restoration and management efforts of State and Federal agencies in the Northern Gulf of Mexico (NGOM) region. In particular, such products may aid coastal forest land acquisition and conservation easement procurements. This region's forests are often disturbed and subjected to multiple biotic and abiotic threats, including subsidence, salt water intrusion, hurricanes, sea-level rise, insect-induced defoliation and mortality, altered hydrology, wildfire, and conversion to non-forest land use. In some cases, such forest disturbance has led to forest loss or loss of regeneration capacity. In response, a case study was conducted to assess and demonstrate the potential of satellite remote sensing products for improving forest type maps and for assessing forest change over the last 25 years. Change detection products are needed for assessing risks for specific priority coastal forest types, such as live oak and baldcypress-dominated forest. Preliminary results indicate Landsat time series data are capable of generating the needed forest type and change detection products. Useful classifications were obtained using 2 strategies: 1) general forest classification based on use of 3 seasons of Landsat data from the same year; and 2) classification of specific forest types of concern using a single date of Landsat data in which a given targeted type is spectrally distinct compared to adjacent forested cover. When available, ASTER data was useful as a complement to Landsat data. Elevation data helped to define areas in which targeted forest types occur, such as live oak forests on natural levees. MODIS Normalized Difference Vegetation Index time series data aided visual assessments of coastal forest damage and recovery from hurricanes. Landsat change detection products enabled change to be identified at the stand level and at 10- year intervals with the earliest date preceding available change detection products from the National Oceanic and Atmospheric Administration and from the U.S. Geological Survey. Additional work is being done in collaboration with State and Federal agency partners in a follow-on NASA ROSES project to refine and validate these new, promising products. The products from the ROSES project will be available for aiding NGOM coastal forest restoration and conservation.

Building Change Detection from LIDAR Point Cloud Data Based on Connected Component Analysis

NASA Astrophysics Data System (ADS)

Awrangjeb, M.; Fraser, C. S.; Lu, G.

2015-08-01

Building data are one of the important data types in a topographic database. Building change detection after a period of time is necessary for many applications, such as identification of informal settlements. Based on the detected changes, the database has to be updated to ensure its usefulness. This paper proposes an improved building detection technique, which is a prerequisite for many building change detection techniques. The improved technique examines the gap between neighbouring buildings in the building mask in order to avoid under segmentation errors. Then, a new building change detection technique from LIDAR point cloud data is proposed. Buildings which are totally new or demolished are directly added to the change detection output. However, for demolished or extended building parts, a connected component analysis algorithm is applied and for each connected component its area, width and height are estimated in order to ascertain if it can be considered as a demolished or new building part. Finally, a graphical user interface (GUI) has been developed to update detected changes to the existing building map. Experimental results show that the improved building detection technique can offer not only higher performance in terms of completeness and correctness, but also a lower number of undersegmentation errors as compared to its original counterpart. The proposed change detection technique produces no omission errors and thus it can be exploited for enhanced automated building information updating within a topographic database. Using the developed GUI, the user can quickly examine each suggested change and indicate his/her decision with a minimum number of mouse clicks.

Determination of chromophore distribution in skin by spectral imaging

NASA Astrophysics Data System (ADS)

Saknite, Inga; Lange, Marta; Jakovels, Dainis; Spigulis, Janis

2012-10-01

Possibilities to determine chromophore distribution in skin by spectral imaging were explored. Simple RGB sensor devices were used for image acquisition. Totally 200 images of 40 different bruises of 20 people were obtained in order to map chromophores bilirubin and haemoglobin. Possibilities to detect water in vitro and in vivo were estimated by using silicon photodetectors and narrow band LEDs. The results show that it is possible to obtain bilirubin and haemoglobin distribution maps and observe changes of chromophore parameter values over time by using a simple RGB imaging device. Water in vitro was detected by using differences in absorption at 450 nm and 950 nm, and 650 nm and 950 nm.

GEOS-3 ocean current investigation using radar altimeter profiling. [Gulf Stream surface topography

NASA Technical Reports Server (NTRS)

Leitao, C. D.; Huang, N. E.; Parra, C. G.

1978-01-01

Both quasi-stationary and dynamic departures from the marine geoid were successfully detected using altitude measurements from the GEOS-3 radar altimeter. The quasi-stationary departures are observed either as elevation changes in single pass profiles across the Gulf Stream or at the crowding of contour lines at the western and northern areas of topographic maps generated using altimeter data spanning one month or longer. Dynamic features such as current meandering and spawned eddies can be monitored by comparing monthly mean maps. Comparison of altimeter inferred eddies with IR detected thermal rings indicates agreement of the two techniques. Estimates of current velocity are made using derived slope estimates in conjunction with the geostrophic equation.

Geographic Information Technologies as an outreach activity in geo-scientific education

NASA Astrophysics Data System (ADS)

Maman, Shimrit; Isaacson, Sivan; Blumberg, Dan G.

2016-04-01

In recent years, a decline in the rates of examinees in the academic track that were entitled to an enhanced matriculation certificate in scientific-technological education was reported in Israel. To confront this problem the Earth and Planetary Image Facility (EPIF) at Ben-Gurion University of the Negev fosters interdisciplinary exploration through educational programs that make use of the facility and its equipment and enable the empowerment of the community by understanding and appreciating science and technology. This is achieved by using Geographic Information Technologies (GIT) such as remote sensing and Geographical Information Systems (GIS) for geo-physical sciences in activities that combine theoretical background with hands-on activities. Monitoring Earth from space by satellites, digital atlases and virtual-based positioning applications are examples for fusion of spatial information (geographic) and technology that the activity is based on. GIT opens a new chapter and a recent history of Cartography starting from the collection of spatial data to its presentation and analysis. GIS have replaced the use of classical atlas books and offer a variety of Web-based applications that provide maps and display up-to-date imagery. The purpose of this workshop is to expose teachers and students to GITs which are applicable in every classroom. The activity imparts free geographic information systems that exist in cyberspace and accessible to single users as the Israeli national GIS and Google earth, which are based on a spatial data and long term local and global satellite imagery coverage. In this paper, our "Think global-Map Local" activity is presented. The activity uses GIS and change detection technologies as means to encourage students to explore environmental issues both around the globe and close to their surroundings. The students detect changes by comparing multi temporal images of a chosen site and learn how to map the alterations and produce change detection maps with simple and user friendly tools. The activity is offered both for students and supervised projects for teachers and youth.

Building perceptual color maps for visualizing interval data

NASA Astrophysics Data System (ADS)

Kalvin, Alan D.; Rogowitz, Bernice E.; Pelah, Adar; Cohen, Aron

2000-06-01

In visualization, a 'color map' maps a range of data values onto a scale of colors. However, unless a color map is e carefully constructed, visual artifacts can be produced. This problem has stimulated considerable interest in creating perceptually based color maps, that is, color maps where equal steps in data value are perceived as equal steps in the color map [Robertson (1988); Pizer (1981); Green (1992); Lefkowitz and Herman, 1992)]. In Rogowitz and Treinish, (1996, 1998) and in Bergman, Treinish and Rogowitz, (1995), we demonstrated that color maps based on luminance or saturation could be good candidates for satisfying this requirement. This work is based on the seminal work of S.S. Stevens (1966), who measured the perceived magnitude of different magnitudes of physical stimuli. He found that for many physical scales, including luminance (cd/m2) and saturation (the 'redness' of a long-wavelength light source), equal ratios in stimulus value produced equal ratios in perceptual magnitude. He interpreted this as indicating that there exists in human cognition a common scale for representing magnitude, and we scale the effects of different physical stimuli to this internal scale. In Rogowitz, Kalvin, Pelahb and Cohen (1999), we used a psychophysical technique to test this hypothesis as it applies to the creation of perceptually uniform color maps. We constructed color maps as trajectories through three-color spaces, a common computer graphics standard (uncalibrated HSV), a common perceptually-based engineering standard for creating visual stimuli (L*a*b*), and a space commonly used in the graphic arts (Munsell). For each space, we created color scales that varied linearly in hue, saturation, or luminance and measured the detectability of increments in hue, saturation or luminance for each of these color scales. We measured the amplitude of the just-detectable Gaussian increments at 20 different values along the range of each color map. For all three color spaces, we found that luminance-based color maps provided the most perceptually- uniform representations of the data. The just-detectable increment was constant at all points in the color map, with the exception of the lowest-luminance values, where a larger increment was required. The saturation-based color maps provided less sensitivity than the luminance-based color maps, requiring much larger increments for detection. For the hue- based color maps, the size of the increment required for detection varied across the range. For example, for the standard 'rainbow' color map (uncalibrated HSV, hue-varying map), a step in the 'green' region required an increment 16 times the size of the increment required in the 'cyan' part of the range. That is, the rainbow color map would not successfully represent changes in the data in the 'green' region of this color map. In this paper, we extend this research by studying the detectability of spatially-modulated Gabor targets based on these hue, saturation and luminance scales. Since, in visualization, the user is called upon to detect and identify patterns that vary in their spatial characteristics, it is important to study how different types of color maps represent data with varying spatial properties. To do so, we measured modulation thresholds for low-(0.2 c/deg) and high-spatial frequency (4.0 c/deg) Gabor patches and compared them with the Gaussian results. As before, we measured increment thresholds for hue, saturation, and luminance modulations. These color scales were constructed as trajectories along the three perceptual dimensions of color (hue, saturation, and luminance) in two color spaces, uncalibrated HSV and calibrated L*a*b. This allowed us to study how the three perceptual dimensions represent magnitude information for test patterns varying in spatial frequency. This design also allowed us to test the hypothesis that the luminance channel best carries high-spatial frequency information while the saturation channel best represents low spatial-frequency information (Mullen 1985; DeValois and DeValois 1988).

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

Musgrove, Cameron H.; West, James C.

Missing samples within synthetic aperture radar data result in image distortions. For coherent data products, such as coherent change detection and interferometric processing, the image distortion can be devastating to these second order products, resulting in missed detections and inaccurate height maps. Earlier approaches to repair the coherent data products focus upon reconstructing the missing data samples. This study demonstrates that reconstruction is not necessary to restore the quality of the coherent data products.

Use of remote sensing for land use policy formulation

NASA Technical Reports Server (NTRS)

1982-01-01

Research projects described include: (1) identifying coniferous forest types in Michigan using LANDSAT imagery; (2) investigating synoptic temperature patterns in Michigan as determined via GOES and HCMM thermal imagery; (3) land surface change detection using satellite data and a geographic data base; (4) determining soil map unit composition by electronic scanning densitometry; and (5) delimiting areas of virus infection in vineyards and blueberry fields in southwestern and western Michigan. Contractual activities involve important farmlands inventory, changes in aquatic vegetation in Saginaw Bay, digitized soil association map of Michigan, and aerial photography for hybrid-poplar research. On-going projects are also being conducted in Jamaica, Honduras, the Dominican Republic and Kenya.

Diffuse ultrasound monitoring of stress and damage development on a 15-ton concrete beam.

PubMed

Zhang, Yuxiang; Planès, Thomas; Larose, Eric; Obermann, Anne; Rospars, Claude; Moreau, Gautier

2016-04-01

This paper describes the use of an ultrasonic imaging technique (Locadiff) for the Non-Destructive Testing & Evaluation of a concrete structure. By combining coda wave interferometry and a sensitivity kernel for diffuse waves, Locadiff can monitor the elastic and structural properties of a heterogeneous material with a high sensitivity, and can map changes of these properties over time when a perturbation occurs in the bulk of the material. The applicability of the technique to life-size concrete structures is demonstrated through the monitoring of a 15-ton reinforced concrete beam subject to a four-point bending test causing cracking. The experimental results show that Locadiff achieved to (1) detect and locate the cracking zones in the core of the concrete beam at an early stage by mapping the changes in the concrete's micro-structure; (2) monitor the internal stress level in both temporal and spatial domains by mapping the variation in velocity caused by the acousto-elastic effect. The mechanical behavior of the concrete structure is also studied using conventional techniques such as acoustic emission, vibrating wire extensometers, and digital image correlation. The performances of the Locadiff technique in the detection of early stage cracking are assessed and discussed.

Land use and land cover (LULC) of the Republic of the Maldives: first national map and LULC change analysis using remote-sensing data.

PubMed

Fallati, Luca; Savini, Alessandra; Sterlacchini, Simone; Galli, Paolo

2017-08-01

The Maldives islands in recent decades have experienced dramatic land-use change. Uninhabited islands were turned into new resort islands; evergreen tropical forests were cut, to be replaced by fields and new built-up areas. All these changes happened without a proper monitoring and urban planning strategy from the Maldivian government due to the lack of national land-use and land-cover (LULC) data. This study aimed to realize the first land-use map of the entire Maldives archipelago and to detect land-use and land-cover change (LULCC) using high-resolution satellite images and socioeconomic data. Due to the peculiar geographic and environmental features of the archipelago, the land-use map was obtained by visual interpretation and manual digitization of land-use patches. The images used, dated 2011, were obtained from Digital Globe's WorldView 1 and WorldView 2 satellites. Nine land-use classes and 18 subclasses were identified and mapped. During a field survey, ground control points were collected to test the geographic and thematic accuracy of the land-use map. The final product's overall accuracy was 85%. Once the accuracy of the map had been checked, LULCC maps were created using images from the early 2000s derived from Google Earth historical imagery. Post-classification comparison of the classified maps showed that growth of built-up and agricultural areas resulted in decreases in forest land and shrubland. The LULCC maps also revealed an increase in land reclamation inside lagoons near inhabited islands, resulting in environmental impacts on fragile reef habitat. The LULC map of the Republic of the Maldives produced in this study can be used by government authorities to make sustainable land-use planning decisions and to provide better management of land use and land cover.

Feature learning and change feature classification based on deep learning for ternary change detection in SAR images

NASA Astrophysics Data System (ADS)

Gong, Maoguo; Yang, Hailun; Zhang, Puzhao

2017-07-01

Ternary change detection aims to detect changes and group the changes into positive change and negative change. It is of great significance in the joint interpretation of spatial-temporal synthetic aperture radar images. In this study, sparse autoencoder, convolutional neural networks (CNN) and unsupervised clustering are combined to solve ternary change detection problem without any supervison. Firstly, sparse autoencoder is used to transform log-ratio difference image into a suitable feature space for extracting key changes and suppressing outliers and noise. And then the learned features are clustered into three classes, which are taken as the pseudo labels for training a CNN model as change feature classifier. The reliable training samples for CNN are selected from the feature maps learned by sparse autoencoder with certain selection rules. Having training samples and the corresponding pseudo labels, the CNN model can be trained by using back propagation with stochastic gradient descent. During its training procedure, CNN is driven to learn the concept of change, and more powerful model is established to distinguish different types of changes. Unlike the traditional methods, the proposed framework integrates the merits of sparse autoencoder and CNN to learn more robust difference representations and the concept of change for ternary change detection. Experimental results on real datasets validate the effectiveness and superiority of the proposed framework.

Long-term development of the Czech landscape studied on the basis of old topographic maps

NASA Astrophysics Data System (ADS)

Skokanová, H.; Havlíček, M.

2009-04-01

The paper deals with long-term land use changes in the Czech Republic with the help of old topographic maps. Departments of Landscape Ecology and GIS Applications from the Silva Tarouca Research Institute for Landscape and Ornamental Gardening, v.v.i. study these changes mainly in the research project MSM 6293359101 Research into sources and indicators of biodiversity in cultural landscape in the context of its fragmentation dynamics, the subpart Quantitative analysis of the dynamics of the Czech landscape development. In this paper, the authors concentrate mainly on map sources, which were acquired for the purpose of the project and also introduce partial results. Maps, which are the sources for the analyses, are following: maps from 2nd Austrian military survey in the scale 1:28 800 (created for the territory of the Czech Republic in the period 1836-1852), maps from 3rd Austrian military survey in the scale 1:25 000 (created for the Czech Republic in the period 1876-1880), Czechoslovak military topographic maps in the scale 1:25 000 from 1950s and 1990s, and Czech topographic base maps in the scale 1:10 000 from 2002-2006. It is necessary to complete maps of the 2nd and 3rd Austrian military survey thanks to their incompleteness, mainly along state borders. Also maps from 1nd Austrian military survey in the scale 1:28 800 (created for the Czech Republic in the period 1764-1783) are available; however, their usage for the accurate analyses in the GIS environment is restricted by their poor cartographic accuracy. Apart of the above mentioned maps, there has been progress in collecting maps from the interwar and war period (revised maps of the 3rd Austrian military survey maps, maps of the provisional military survey from 1923-1933, maps of definitive military survey from 1934-1938 and maps from survey of Moravian part of the Protectorate of Bohemia and Moravia, so called Messtischblätter from 1939-1945). Maps from five periods are manually vectorised in the GIS environment. When vectorizing maps, nine land use categories are distinguished according to the methodology created at the author's workplace. Only areas larger than 0.8 ha are vectorized with regard to the output scale of the project (1:200 000), which includes the whole territory of the republic. The so far vectorized areas are shown in the overview maps. The main analyses lay in overlaying vectorized maps and in calculation of the number of land use changes for the whole researched period. These then show stable areas, i.e. areas where no change in land use occurred, and dynamic areas with one or more changes. Also types of the land use changes both among individual maps and for the whole period can be detected.

Damage Proxy Map from InSAR Coherence Applied to February 2011 M6.3 Christchurch Earthquake, 2011 M9.0 Tohoku-oki Earthquake, and 2011 Kirishima Volcano Eruption

NASA Astrophysics Data System (ADS)

Yun, S.; Agram, P. S.; Fielding, E. J.; Simons, M.; Webb, F.; Tanaka, A.; Lundgren, P.; Owen, S. E.; Rosen, P. A.; Hensley, S.

2011-12-01

Under ARIA (Advanced Rapid Imaging and Analysis) project at JPL and Caltech, we developed a prototype algorithm to detect surface property change caused by natural or man-made damage using InSAR coherence change. The algorithm was tested on building demolition and construction sites in downtown Pasadena, California. The developed algorithm performed significantly better, producing 150 % higher signal-to-noise ratio, than a standard coherence change detection method. We applied the algorithm to February 2011 M6.3 Christchurch earthquake in New Zealand, 2011 M9.0 Tohoku-oki earthquake in Japan, and 2011 Kirishima volcano eruption in Kyushu, Japan, using ALOS PALSAR data. In Christchurch area we detected three different types of damage: liquefaction, building collapse, and landslide. The detected liquefaction damage is extensive in the eastern suburbs of Christchurch, showing Bexley as one of the most significantly affected areas as was reported in the media. Some places show sharp boundaries of liquefaction damage, indicating different type of ground materials that might have been formed by the meandering Avon River in the past. Well reported damaged buildings such as Christchurch Cathedral, Canterbury TV building, Pyne Gould building, and Cathedral of the Blessed Sacrament were detected by the algorithm. A landslide in Redcliffs was also clearly detected. These detected damage sites were confirmed with Google earth images provided by GeoEye. Larger-scale damage pattern also agrees well with the ground truth damage assessment map indicated with polygonal zones of 3 different damage levels, compiled by the government of New Zealand. The damage proxy map of Sendai area in Japan shows man-made structure damage due to the tsunami caused by the M9.0 Tohoku-oki earthquake. Long temporal baseline (~2.7 years) and volume scattering caused significant decorrelation in the farmlands and bush forest along the coastline. The 2011 Kirishima volcano eruption caused a lot of ash fall deposit in the southeast from the volcano. The detected ash fall damage area exactly matches the in-situ measurements implemented through fieldwork by Geological Survey of Japan. With 99-percentile threshold for damage detection, the periphery of the detected damage area aligns with a contour line of 100 kg/m2 ash deposit, equivalent to 10 cm of depth assuming a density of 1000 kg/m3 for the ash layer. With growing number of InSAR missions, rapidly produced accurate damage assessment maps will help save people, assisting effective prioritization of rescue operations at early stage of response, and significantly improve timely situational awareness for emergency management and national / international assessment and response for recovery planning. Results of this study will also inform the design of future InSAR missions including the proposed DESDynI.

Influence of Stress Connected with Moving to a New Farm on Potentially MAP-Infected Mouflons.

PubMed

Pribylova-Dziedzinska, Radka; Slana, Iva; Lamka, Jiri; Pavlik, Ivo

2014-01-01

There is no European legislation concerning paratuberculosis that requires that imported animals be kept in quarantine and commonly they are directly released into areas with other animals. In this study, detection of latent infection of paratuberculosis in healthy mouflons previously diagnosed as paratuberculosis-free, but originating from a real time quantitative PCR- (qPCR-) positive herd, occurred after their transport to a new farm. During a twelve-day quarantine period, all mouflons irregularly shed Mycobacterium avium subsp. paratuberculosis (MAP) in faeces, and in a small number of cases also in milk. After the animals were released from quarantine, MAP was detected for a further two days, after which, testing was negative, except in one case. Therefore, the stress connected with transport, novel environment, dietary change, or limited area with high density of animals might have contributed to the induction of paratuberculosis and the shedding of MAP from the animals, previously diagnosed as MAP-negative. According to these results, the keeping of imported animals in quarantine and their examination for MAP presence not only before the transport but also afterwards should be recommended. The designation of a particular area of a farm as a quarantine enclosure could help to mitigate the impact of stress caused by a confined space with a high density of animals.

A service relation model for web-based land cover change detection

NASA Astrophysics Data System (ADS)

Xing, Huaqiao; Chen, Jun; Wu, Hao; Zhang, Jun; Li, Songnian; Liu, Boyu

2017-10-01

Change detection with remotely sensed imagery is a critical step in land cover monitoring and updating. Although a variety of algorithms or models have been developed, none of them can be universal for all cases. The selection of appropriate algorithms and construction of processing workflows depend largely on the expertise of experts about the "algorithm-data" relations among change detection algorithms and the imagery data used. This paper presents a service relation model for land cover change detection by integrating the experts' knowledge about the "algorithm-data" relations into the web-based geo-processing. The "algorithm-data" relations are mapped into a set of web service relations with the analysis of functional and non-functional service semantics. These service relations are further classified into three different levels, i.e., interface, behavior and execution levels. A service relation model is then established using the Object and Relation Diagram (ORD) approach to represent the multi-granularity services and their relations for change detection. A set of semantic matching rules are built and used for deriving on-demand change detection service chains from the service relation model. A web-based prototype system is developed in .NET development environment, which encapsulates nine change detection and pre-processing algorithms and represents their service relations as an ORD. Three test areas from Shandong and Hebei provinces, China with different imagery conditions are selected for online change detection experiments, and the results indicate that on-demand service chains can be generated according to different users' demands.

Detection and mapping of delays in early cortical folding derived from in utero MRI

NASA Astrophysics Data System (ADS)

Habas, Piotr A.; Rajagopalan, Vidya; Scott, Julia A.; Kim, Kio; Roosta, Ahmad; Rousseau, Francois; Barkovich, A. James; Glenn, Orit A.; Studholme, Colin

2011-03-01

Understanding human brain development in utero and detecting cortical abnormalities related to specific clinical conditions is an important area of research. In this paper, we describe and evaluate methodology for detection and mapping of delays in early cortical folding from population-based studies of fetal brain anatomies imaged in utero. We use a general linear modeling framework to describe spatiotemporal changes in curvature of the developing brain and explore the ability to detect and localize delays in cortical folding in the presence of uncertainty in estimation of the fetal age. We apply permutation testing to examine which regions of the brain surface provide the most statistical power to detect a given folding delay at a given developmental stage. The presented methodology is evaluated using MR scans of fetuses with normal brain development and gestational ages ranging from 20.57 to 27.86 weeks. This period is critical in early cortical folding and the formation of the primary and secondary sulci. Finally, we demonstrate a clinical application of the framework for detection and localization of folding delays in fetuses with isolated mild ventriculomegaly.

Cooperative multisensor system for real-time face detection and tracking in uncontrolled conditions

NASA Astrophysics Data System (ADS)

Marchesotti, Luca; Piva, Stefano; Turolla, Andrea; Minetti, Deborah; Regazzoni, Carlo S.

2005-03-01

The presented work describes an innovative architecture for multi-sensor distributed video surveillance applications. The aim of the system is to track moving objects in outdoor environments with a cooperative strategy exploiting two video cameras. The system also exhibits the capacity of focusing its attention on the faces of detected pedestrians collecting snapshot frames of face images, by segmenting and tracking them over time at different resolution. The system is designed to employ two video cameras in a cooperative client/server structure: the first camera monitors the entire area of interest and detects the moving objects using change detection techniques. The detected objects are tracked over time and their position is indicated on a map representing the monitored area. The objects" coordinates are sent to the server sensor in order to point its zooming optics towards the moving object. The second camera tracks the objects at high resolution. As well as the client camera, this sensor is calibrated and the position of the object detected on the image plane reference system is translated in its coordinates referred to the same area map. In the map common reference system, data fusion techniques are applied to achieve a more precise and robust estimation of the objects" track and to perform face detection and tracking. The work novelties and strength reside in the cooperative multi-sensor approach, in the high resolution long distance tracking and in the automatic collection of biometric data such as a person face clip for recognition purposes.

Application of EREP imagery to fracture-related mine safety hazards and environmental problems in mining. [Indiana

NASA Technical Reports Server (NTRS)

Wier, C. E.; Wobber, F. J.; Amato, R. V.; Russell, O. R. (Principal Investigator)

1974-01-01

The author has identified the following significant results. All Skylab 2 imagery received to date has been analyzed manually and data related to fracture analysis and mined land inventories has been summarized on map-overlays. A comparison of the relative utility of the Skylab image products for fracture detection, soil tone/vegetation contrast mapping, and mined land mapping has been completed. Numerous fracture traces were detected on both color and black and white transparencies. Unique fracture trace data which will contribute to the investigator's mining hazards analysis were noted on the EREP imagery; these data could not be detected on ERTS-1 imagery or high altitude aircraft color infrared photography. Stream segments controlled by fractures or joint systems could be identified in more detail than with ERTS-1 imagery of comparable scale. ERTS-1 mine hazards products will be modified to demonstrate the value of this additional data. Skylab images were used successfully to update a mined land map of Indiana made in 1972. Changes in mined area as small as two acres can be identified. As the Energy Crisis increases the demand for coal, such demonstrations of the application of Skylab data to coal resources will take on new importance.

Mapping gullies, dunes, lava fields, and landslides via surface roughness

NASA Astrophysics Data System (ADS)

Korzeniowska, Karolina; Pfeifer, Norbert; Landtwing, Stephan

2018-01-01

Gully erosion is a widespread and significant process involved in soil and land degradation. Mapping gullies helps to quantify past, and anticipate future, soil losses. Digital terrain models offer promising data for automatically detecting and mapping gullies especially in vegetated areas, although methods vary widely measures of local terrain roughness are the most varied and debated among these methods. Rarely do studies test the performance of roughness metrics for mapping gullies, limiting their applicability to small training areas. To this end, we systematically explored how local terrain roughness derived from high-resolution Light Detection And Ranging (LiDAR) data can aid in the unsupervised detection of gullies over a large area. We also tested expanding this method for other landforms diagnostic of similarly abrupt land-surface changes, including lava fields, dunes, and landslides, as well as investigating the influence of different roughness thresholds, resolutions of kernels, and input data resolution, and comparing our method with previously published roughness algorithms. Our results show that total curvature is a suitable metric for recognising analysed gullies and lava fields from LiDAR data, with comparable success to that of more sophisticated roughness metrics. Tested dunes or landslides remain difficult to distinguish from the surrounding landscape, partly because they are not easily defined in terms of their topographic signature.

Fusion of Remote Sensing Methods, UAV Photogrammetry and LiDAR Scanning products for monitoring fluvial dynamics

NASA Astrophysics Data System (ADS)

Lendzioch, Theodora; Langhammer, Jakub; Hartvich, Filip

2015-04-01

Fusion of remote sensing data is a common and rapidly developing discipline, which combines data from multiple sources with different spatial and spectral resolution, from satellite sensors, aircraft and ground platforms. Fusion data contains more detailed information than each of the source and enhances the interpretation performance and accuracy of the source data and produces a high-quality visualisation of the final data. Especially, in fluvial geomorphology it is essential to get valuable images in sub-meter resolution to obtain high quality 2D and 3D information for a detailed identification, extraction and description of channel features of different river regimes and to perform a rapid mapping of changes in river topography. In order to design, test and evaluate a new approach for detection of river morphology, we combine different research techniques from remote sensing products to drone-based photogrammetry and LiDAR products (aerial LiDAR Scanner and TLS). Topographic information (e.g. changes in river channel morphology, surface roughness, evaluation of floodplain inundation, mapping gravel bars and slope characteristics) will be extracted either from one single layer or from combined layers in accordance to detect fluvial topographic changes before and after flood events. Besides statistical approaches for predictive geomorphological mapping and the determination of errors and uncertainties of the data, we will also provide 3D modelling of small fluvial features.

Optimal combinations of acute phase proteins for detecting infectious disease in pigs.

PubMed

Heegaard, Peter M H; Stockmarr, Anders; Piñeiro, Matilde; Carpintero, Rakel; Lampreave, Fermin; Campbell, Fiona M; Eckersall, P David; Toussaint, Mathilda J M; Gruys, Erik; Sorensen, Nanna Skall

2011-03-17

The acute phase protein (APP) response is an early systemic sign of disease, detected as substantial changes in APP serum concentrations and most disease states involving inflammatory reactions give rise to APP responses. To obtain a detailed picture of the general utility of porcine APPs to detect any disease with an inflammatory component seven porcine APPs were analysed in serum sampled at regular intervals in six different experimental challenge groups of pigs, including three bacterial (Actinobacillus pleuropneumoniae, Streptococcus suis, Mycoplasma hyosynoviae), one parasitic (Toxoplasma gondii) and one viral (porcine respiratory and reproductive syndrome virus) infection and one aseptic inflammation. Immunochemical analyses of seven APPs, four positive (C-reactive protein (CRP), haptoglobin (Hp), pig major acute phase protein (pigMAP) and serum amyloid A (SAA)) and three negative (albumin, transthyretin, and apolipoprotein A1 (apoA1)) were performed in the more than 400 serum samples constituting the serum panel. This was followed by advanced statistical treatment of the data using a multi-step procedure which included defining cut-off values and calculating detection probabilities for single APPs and for APP combinations. Combinations of APPs allowed the detection of disease more sensitively than any individual APP and the best three-protein combinations were CRP, apoA1, pigMAP and CRP, apoA1, Hp, respectively, closely followed by the two-protein combinations CRP, pigMAP and apoA1, pigMAP, respectively. For the practical use of such combinations, methodology is described for establishing individual APP threshold values, above which, for any APP in the combination, ongoing infection/inflammation is indicated.

Nanotechnology Approaches to Studying Epigenetic Changes in Cancer

NASA Astrophysics Data System (ADS)

Riehn, Robert

2011-03-01

Placing polyelectrolytes into confined geometries has a profound effect on their molecular configuration. For instance, placing long DNA molecules into channels with a cross-section of about 100 nm 2 stretches them out to about 70% of their contour length. We are using this effect to map epigenetic changes on single DNA and chromatin strands. This mapping on single molecules becomes central in the study of the heterogeneity of cell population in cancer, since rapid change of epigenetic makeup, propagated through rare cancer stem cells, is a hallmark of its progression. We demonstrate the basic building blocks for the single-molecule epigenetic analysis of genomic sized DNA. In particular, we have achieved the mapping of methylated regions in DNA with heterogeneous 5-methyl cytosine modification using a specific fluorescent marker. We further show that chromatin with an intact histone structure can be stretched similar to DNA, and that the epigenetic state of histone tails can be detected using fluorescent antibodies.

Central Atlantic regional ecological test site: A prototype regional environmental information system

NASA Technical Reports Server (NTRS)

Alexander, R. H. (Principal Investigator)

1972-01-01

The author has identified the following significant results. Preliminary analysis of the capabilities of ERTS-1 data in land use mapping and change detection has revealed that Level 1 land use mapping can be performed and that in some cases land use changes can be identified. Land use interpretation was accomplished with the aid of a film projection viewer and the I2S additive color viewer. By varying the filters and illumination of each spectral band it was possible to better distinguish urban areas and transportation routes. Also it enabled the toning down of signatures such as cropland and forests which on many color infrared composite photographs were washed out with strong red tints. It appears that ERTS-1 imagery is useful not only for Level 1 mapping at scales of 1:250,000 or smaller, but also for monitoring agricultural changes and locating areas of construction, when such land uses approach an area of approximately two hectares.

Evaluate ERTS imagery for mapping and detection of changes of snowcover on land and on glaciers

NASA Technical Reports Server (NTRS)

Meier, M. F. (Principal Investigator)

1973-01-01

The author has identified the following significant results. The area of snow cover on land was determined from ERTS-1 imagery. Snow cover in specific drainage basins was measured with the Stanford Research Institute console by electronically superimposing basin outlines on imagery, with video density slicing to measure areas. Snow covered area and snowline altitudes were also determined by enlarging ERTS-1 imagery 1:250,000 and using a transparent map overlay. Under very favorable conditions, snowline altitude was determined to an accuracy of about 60 m. Ability to map snow cover or to determine snowline altitude depends primarily on cloud cover and vegetation and secondarily on slope, terrain roughness, sun angle, radiometric fidelity, and amount of spectral information available. Glacier accumulation area ratios were determined from ERTS-1 imagery. Also, subtle flow structures, undetected on aerial photographs, were visible. Surging glaciers were identified, and the changes resulting from the surge of a large glacier were measured as were changes in tidal glacier termini.

A study and evaluation of image analysis techniques applied to remotely sensed data

NASA Technical Reports Server (NTRS)

Atkinson, R. J.; Dasarathy, B. V.; Lybanon, M.; Ramapriyan, H. K.

1976-01-01

An analysis of phenomena causing nonlinearities in the transformation from Landsat multispectral scanner coordinates to ground coordinates is presented. Experimental results comparing rms errors at ground control points indicated a slight improvement when a nonlinear (8-parameter) transformation was used instead of an affine (6-parameter) transformation. Using a preliminary ground truth map of a test site in Alabama covering the Mobile Bay area and six Landsat images of the same scene, several classification methods were assessed. A methodology was developed for automatic change detection using classification/cluster maps. A coding scheme was employed for generation of change depiction maps indicating specific types of changes. Inter- and intraseasonal data of the Mobile Bay test area were compared to illustrate the method. A beginning was made in the study of data compression by applying a Karhunen-Loeve transform technique to a small section of the test data set. The second part of the report provides a formal documentation of the several programs developed for the analysis and assessments presented.

Thermal mapping of Hawaiian volcanoes with ASTER satellite data

USGS Publications Warehouse

Patrick, Matthew R.; Witzke, Coral-Nadine

2011-01-01

Thermal mapping of volcanoes is important to determine baseline thermal behavior in order to judge future thermal activity that may precede an eruption. We used cloud-free kinetic temperature images from the ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer) sensor obtained between 2000 and 2010 to produce thermal maps for all five subaerial volcanoes in Hawai‘i that have had eruptions in the Holocene (Kīlauea, Mauna Loa, Hualālai, Mauna Kea, and Haleakalā). We stacked the images to provide time-averaged thermal maps, as well as to analyze temperature trends through time. Thermal areas are conspicuous at the summits and rift zones of Kīlauea and Mauna Loa, and the summit calderas of these volcanoes contain obvious arcuate, concentric linear thermal areas that probably result from channeling of rising gas along buried, historical intracaldera scarps. The only significant change in thermal activity noted in the study period is the opening of the Halema‘uma‘u vent at Kīlauea's summit in 2008. Several small thermal anomalies are coincident with pit craters on Hualālai. We suspect that these simply result from the sheltered nature of the depression, but closer inspection is warranted to determine if genuine thermal activity exists in the craters. Thermal areas were not detected on Haleakalā or Mauna Kea. The main limitation of the study is the large pixel size (90 m) of the ASTER images, which reduces our ability to detect subtle changes or to identify small, low-temperature thermal activity. This study, therefore, is meant to characterize the broad, large-scale thermal features on these volcanoes. Future work should study these thermal areas with thermal cameras and thermocouples, which have a greater ability to detect small, low-temperature thermal features.

Detecting of forest afforestation and deforestation in Hainan Jianfengling Forest Park (China) using yearly Landsat time-series images

NASA Astrophysics Data System (ADS)

Jiao, Quanjun; Zhang, Xiao; Sun, Qi

2018-03-01

The availability of dense time series of Landsat images pro-vides a great chance to reconstruct forest disturbance and change history with high temporal resolution, medium spatial resolution and long period. This proposal aims to apply forest change detection method in Hainan Jianfengling Forest Park using yearly Landsat time-series images. A simple detection method from the dense time series Landsat NDVI images will be used to reconstruct forest change history (afforestation and deforestation). The mapping result showed a large decrease occurred in the extent of closed forest from 1980s to 1990s. From the beginning of the 21st century, we found an increase in forest areas with the implementation of forestry measures such as the prohibition of cutting and sealing in our study area. Our findings provide an effective approach for quickly detecting forest changes in tropical original forest, especially for afforestation and deforestation, and a comprehensive analysis tool for forest resource protection.

In Vivo Volatile Organic Compound Signatures of Mycobacterium avium subsp. paratuberculosis

PubMed Central

Bergmann, Andreas; Trefz, Phillip; Fischer, Sina; Klepik, Klaus; Walter, Gudrun; Steffens, Markus; Ziller, Mario; Schubert, Jochen K.; Reinhold, Petra; Köhler, Heike; Miekisch, Wolfram

2015-01-01

Mycobacterium avium ssp. paratuberculosis (MAP) is the causative agent of a chronic enteric disease of ruminants. Available diagnostic tests are complex and slow. In vitro, volatile organic compound (VOC) patterns emitted from MAP cultures mirrored bacterial growth and enabled distinction of different strains. This study was intended to determine VOCs in vivo in the controlled setting of an animal model. VOCs were pre-concentrated from breath and feces of 42 goats (16 controls and 26 MAP-inoculated animals) by means of needle trap microextraction (breath) and solid phase microextraction (feces) and analyzed by gas chromatography/ mass spectrometry. Analyses were performed 18, 29, 33, 41 and 48 weeks after inoculation. MAP-specific antibodies and MAP-specific interferon-γ-response were determined from blood. Identities of all marker-VOCs were confirmed through analysis of pure reference substances. Based on detection limits in the high pptV and linear ranges of two orders of magnitude more than 100 VOCs could be detected in breath and in headspace over feces. Twenty eight substances differed between inoculated and non-inoculated animals. Although patterns of most prominent substances such as furans, oxygenated substances and hydrocarbons changed in the course of infection, differences between inoculated and non-inoculated animals remained detectable at any time for 16 substances in feces and 3 VOCs in breath. Differences of VOC concentrations over feces reflected presence of MAP bacteria. Differences in VOC profiles from breath were linked to the host response in terms of interferon-γ-response. In a perspective in vivo analysis of VOCs may help to overcome limitations of established tests. PMID:25915653

Toward a National Early Warning System for Forest Disturbances Using Remotely Sensed Land-Surface Phenology

NASA Astrophysics Data System (ADS)

Hargrove, W. W.; Spruce, J.

2010-12-01

A prototype National Early Warning System (EWS) for Forest Disturbances was established in 2010 by producing national maps showing potential forest disturbance across the conterminous United States at 231m resolution every 8 days. Each map is based on Land-Surface Phenology (LSP), calculated using temporally smoothed MODIS MOD13 imagery obtained over the preceding 24-day analysis window. Potential disturbance maps are generated by comparing a spatially and temporally specific historical expectation of normal NDVI "greenness" with NDVI "greenness" from a series of current satellite views. Three different disturbance products are produced using differing lengths of historical baseline periods to calculate the expected normal greenness. The short-term baseline products show only disturbances newer than one year ago, while the intermediate baseline products show disturbances since the prior three years, and the long-term baseline products show all disturbances over the MODIS historical period. A Forest Change Assessment Viewer website, http://ews.forestthreats.org/NPDE/NPDE.html, showcases the three most recent national disturbance maps in full spatial context. Although 2010 was a wet el Nino year without major forest problems, disturbances in 2010 in MI, NY, CO and LA will be highlighted. Forest disturbances caused by wildfire, hurricanes, tornadoes, hail, ice storms, and defoliating insects, including fall cankerworms, forest tent caterpillars, gypsy moths, baldcypress leafrollers and winter moths were successfully detected during the 2009 and 2010 field seasons. The EWS was used in 2010 to detect and alert Forest Health Monitoring (FHM) Aerial Disturbance Survey personnel to an otherwise-unknown outbreak of forest tent caterpillar and baldcypress leafroller in the Atchafalaya and Pearl River regions of southern Louisiana. A local FHM Program Coordinator verified these EWS-detected outbreaks. Many defoliator-induced disturbances were ephemeral, and were followed by recovery in LSP, presumably due to refoliation. 2009 Vegetation Disturbances mapped as percent change in max NDVI from June 10 - July 27 2000-2008

Multichannel optical mapping: investigation of depth information

NASA Astrophysics Data System (ADS)

Sase, Ichiro; Eda, Hideo; Seiyama, Akitoshi; Tanabe, Hiroki C.; Takatsuki, Akira; Yanagida, Toshio

2001-06-01

Near infrared (NIR) light has become a powerful tool for non-invasive imaging of human brain activity. Many systems have been developed to capture the changes in regional brain blood flow and hemoglobin oxygenation, which occur in the human cortex in response to neural activity. We have developed a multi-channel reflectance imaging system, which can be used as a `mapping device' and also as a `multi-channel spectrophotometer'. In the present study, we visualized changes in the hemodynamics of the human occipital region in multiple ways. (1) Stimulating left and right primary visual cortex independently by showing sector shaped checkerboards sequentially over the contralateral visual field, resulted in corresponding changes in the hemodynamics observed by `mapping' measurement. (2) Simultaneous measurement of functional-MRI and NIR (changes in total hemoglobin) during visual stimulation showed good spatial and temporal correlation with each other. (3) Placing multiple channels densely over the occipital region demonstrated spatial patterns more precisely, and depth information was also acquired by placing each pair of illumination and detection fibers at various distances. These results indicate that optical method can provide data for 3D analysis of human brain functions.

Detection limit of intragenic deletions with targeted array comparative genomic hybridization

PubMed Central

2013-01-01

Background Pathogenic mutations range from single nucleotide changes to deletions or duplications that encompass a single exon to several genes. The use of gene-centric high-density array comparative genomic hybridization (aCGH) has revolutionized the detection of intragenic copy number variations. We implemented an exon-centric design of high-resolution aCGH to detect single- and multi-exon deletions and duplications in a large set of genes using the OGT 60 K and 180 K arrays. Here we describe the molecular characterization and breakpoint mapping of deletions at the smaller end of the detectable range in several genes using aCGH. Results The method initially implemented to detect single to multiple exon deletions, was able to detect deletions much smaller than anticipated. The selected deletions we describe vary in size, ranging from over 2 kb to as small as 12 base pairs. The smallest of these deletions are only detectable after careful manual review during data analysis. Suspected deletions smaller than the detection size for which the method was optimized, were rigorously followed up and confirmed with PCR-based investigations to uncover the true detection size limit of intragenic deletions with this technology. False-positive deletion calls often demonstrated single nucleotide changes or an insertion causing lower hybridization of probes demonstrating the sensitivity of aCGH. Conclusions With optimizing aCGH design and careful review process, aCGH can uncover intragenic deletions as small as dozen bases. These data provide insight that will help optimize probe coverage in array design and illustrate the true assay sensitivity. Mapping of the breakpoints confirms smaller deletions and contributes to the understanding of the mechanism behind these events. Our knowledge of the mutation spectra of several genes can be expected to change as previously unrecognized intragenic deletions are uncovered. PMID:24304607

Use of satellite imagery for wildland resource evaluation in the Great Basin

NASA Technical Reports Server (NTRS)

Tueller, P. T. (Principal Investigator)

1973-01-01

The author has identified the following significant results. Most major vegetation types of Nevada have been mapped with success. The completed set of mosaic overlays will be more accurate and detailed than previous maps compiled by various State and Federal agencies due to the excellent vantage point that ERTS-1 data affords. This new vegetation type map will greatly aid resource agencies in their daily work. Such information as suitable grazing areas, wildlife habitat, forage production, and approximate wildland production potentials can be inferred from such a map. There has been some success in detecting vegetational changes with the use of ERTS-1 MSS imagery, but exposure differences have somewhat confounded the results. Future plans include work to solve this problem.

Land-based lidar mapping: a new surveying technique to shed light on rapid topographic change

USGS Publications Warehouse

Collins, Brian D.; Kayen, Robert

2006-01-01

The rate of natural change in such dynamic environments as rivers and coastlines can sometimes overwhelm the monitoring capacity of conventional surveying methods. In response to this limitation, U.S. Geological Survey (USGS) scientists are pioneering new applications of light detection and ranging (lidar), a laser-based scanning technology that promises to greatly increase our ability to track rapid topographic changes and manage their impact on affected communities.

Landsat Based Woody Vegetation Loss Detection in Queensland, Australia Using the Google Earth Engine

NASA Astrophysics Data System (ADS)

Johansen, K.; Phinn, S. R.; Taylor, M.

2014-12-01

Land clearing detection and woody Foliage Projective Cover (FPC) monitoring at the state and national level in Australia has mainly been undertaken by state governments and the Terrestrial Ecosystem Research Network (TERN) because of the considerable expense, expertise, sustained duration of activities and staffing levels needed. Only recently have services become available, providing low budget, generalized access to change detection tools suited to this task. The objective of this research was to examine if a globally available service, Google Earth Engine Beta, could be used to predict woody vegetation loss with accuracies approaching the methods used by TERN and the government of the state of Queensland, Australia. Two change detection approaches were investigated using Landsat Thematic Mapper time series and the Google Earth Engine Application Programming Interface: (1) CART and Random Forest classifiers; and (2) a normalized time series of Foliage Projective Cover (FPC) and NDVI combined with a spectral index. The CART and Random Forest classifiers produced high user's and producer's mapping accuracies of clearing (77-92% and 54-77%, respectively) when detecting change within epochs for which training data were available, but extrapolation to epochs without training data reduced the mapping accuracies. The use of FPC and NDVI time series provided a more robust approach for calculation of a clearing probability, as it did not rely on training data but instead on the difference of the normalized FPC / NDVI mean and standard deviation of a single year at the change point in relation to the remaining time series. However, the FPC and NDVI time series approach represented a trade-off between user's and producer's accuracies. Both change detection approaches explored in this research were sensitive to ephemeral greening and drying of the landscape. However, the developed normalized FPC and NDVI time series approach can be tuned to provide automated alerts for large woody vegetation clearing events by selecting suitable thresholds to identify very likely clearing. This research provides a comprehensive foundation to build further capacity to use globally accessible, free, online image datasets and processing tools to accurately detect woody vegetation clearing in an automated and rapid manner.

Change detection on LOD 2 building models with very high resolution spaceborne stereo imagery

NASA Astrophysics Data System (ADS)

Qin, Rongjun

2014-10-01

Due to the fast development of the urban environment, the need for efficient maintenance and updating of 3D building models is ever increasing. Change detection is an essential step to spot the changed area for data (map/3D models) updating and urban monitoring. Traditional methods based on 2D images are no longer suitable for change detection in building scale, owing to the increased spectral variability of the building roofs and larger perspective distortion of the very high resolution (VHR) imagery. Change detection in 3D is increasingly being investigated using airborne laser scanning data or matched Digital Surface Models (DSM), but rare study has been conducted regarding to change detection on 3D city models with VHR images, which is more informative but meanwhile more complicated. This is due to the fact that the 3D models are abstracted geometric representation of the urban reality, while the VHR images record everything. In this paper, a novel method is proposed to detect changes directly on LOD (Level of Detail) 2 building models with VHR spaceborne stereo images from a different date, with particular focus on addressing the special characteristics of the 3D models. In the first step, the 3D building models are projected onto a raster grid, encoded with building object, terrain object, and planar faces. The DSM is extracted from the stereo imagery by hierarchical semi-global matching (SGM). In the second step, a multi-channel change indicator is extracted between the 3D models and stereo images, considering the inherent geometric consistency (IGC), height difference, and texture similarity for each planar face. Each channel of the indicator is then clustered with the Self-organizing Map (SOM), with "change", "non-change" and "uncertain change" status labeled through a voting strategy. The "uncertain changes" are then determined with a Markov Random Field (MRF) analysis considering the geometric relationship between faces. In the third step, buildings are extracted combining the multispectral images and the DSM by morphological operators, and the new buildings are determined by excluding the verified unchanged buildings from the second step. Both the synthetic experiment with Worldview-2 stereo imagery and the real experiment with IKONOS stereo imagery are carried out to demonstrate the effectiveness of the proposed method. It is shown that the proposed method can be applied as an effective way to monitoring the building changes, as well as updating 3D models from one epoch to the other.

Calibration and validation of the relative differenced Normalized Burn Ratio (RdNBR) to three measures of fire severity in the Sierra Nevada and Klamath Mountains, California, USA

Treesearch

Jay D. Miller; Eric E. Knapp; Carl H. Key; Carl N. Skinner; Clint J. Isbell; R. Max Creasy; Joseph W. Sherlock

2009-01-01

Multispectral satellite data have become a common tool used in the mapping of wildland fire effects. Fire severity, defined as the degree to which a site has been altered, is often the variable mapped. The Normalized Burn Ratio (NBR) used in an absolute difference change detection protocol (dNBR), has become the remote sensing method of choice for US Federal land...

Friction Stir Weld Inspection Through Conductivity Imaging Using Shaped Field MWM(Registered Trademark) - Arrays

NASA Technical Reports Server (NTRS)

Goldfine, Neil; Grundy, David; Zilberstein, Vladimir; Kinchen, David G.; McCool, Alex (Technical Monitor)

2002-01-01

Friction Stir Welds (FSW) of Al 2195-T8 and Al 2219-T8, provided by Lockheed Martin Michoud Operations, were inspected for lack-of-penetration (LOP) defects using a custom designed MWM-Array, a multi-element eddy-current sensor. MWM (registered trademark) electrical conductivity mapping demonstrated high sensitivity to LOP as small as 0.75 mm (0.03 in.), as confirmed by metallographic data that characterized the extent of LOP defects. High sensitivity and high spatial resolution was achieved via a 37-element custom designed MWM-Array allowing LOP detection using the normalized longitudinal component of the MWM measured conductivity. This permitted both LOP detection and correlation of MWM conductivity features with the LOP defect size, as changes in conductivity were apparently associated with metallurgical features within the near-surface layer of the LOP defect zone. MWM conductivity mapping reveals information similar to macro-etching as the MWM-Array is sensitive to small changes in conductivity due to changes in microstructure associated with material thermal processing, in this case welding. The electrical conductivity measured on the root side of FSWs varies across the weld due to microstructural differences introduced by the FSW process, as well as those caused by planar flaws. Weld metal, i.e., dynamically recrystallized zone (DXZ), thermomechanically affected zone (TMZ), heat-affected zone (HAZ), and parent metal (PM) are all evident in the conductivity maps. While prior efforts had met with limited success for NDE (Nondestructive Evaluation) of dissimilar alloy, Al2219 to Al2195 FSW, the new custom designed multi-element MWM-Array achieved detection of all LOP defects even in dissimilar metal welds.

An FP7 "Space" project: Aphorism "Advanced PRocedures for volcanic and Seismic Monitoring"

NASA Astrophysics Data System (ADS)

Di Iorio, A., Sr.; Stramondo, S.; Bignami, C.; Corradini, S.; Merucci, L.

2014-12-01

APHORISM project proposes the development and testing of two new methods to combine Earth Observation satellite data from different sensors, and ground data. The aim is to demonstrate that this two types of data, appropriately managed and integrated, can provide new improved GMES products useful for seismic and volcanic crisis management. The first method, APE - A Priori information for Earthquake damage mapping, concerns the generation of maps to address the detection and estimate of damage caused by a seism. The use of satellite data to investigate earthquake damages is not an innovative issue. We can find a wide literature and projects concerning such issue, but usually the approach is only based on change detection techniques and classifications algorithms. The novelty of APE relies on the exploitation of a priori information derived by InSAR time series to measure surface movements, shake maps obtained from seismological data, and vulnerability information. This a priori information is then integrated with change detection map to improve accuracy and to limit false alarms. The second method deals with volcanic crisis management. The method, MACE - Multi-platform volcanic Ash Cloud Estimation, concerns the exploitation of GEO (Geosynchronous Earth Orbit) sensor platform, LEO (Low Earth Orbit) satellite sensors and ground measures to improve the ash detection and retrieval and to characterize the volcanic ash clouds. The basic idea of MACE consists of an improvement of volcanic ash retrievals at the space-time scale by using both the LEO and GEO estimations and in-situ data. Indeed the standard ash thermal infrared retrieval is integrated with data coming from a wider spectral range from visible to microwave. The ash detection is also extended in case of cloudy atmosphere or steam plumes. APE and MACE methods have been defined in order to provide products oriented toward the next ESA Sentinels satellite missions.The project is funded under the European Union FP7 program and the Kick-Off meeting has been held at INGV premises in Rome on 18th December 2013.

Improving the extraction of crisis information in the context of flood, fire, and landslide rapid mapping using SAR and optical remote sensing data

NASA Astrophysics Data System (ADS)

Martinis, Sandro; Clandillon, Stephen; Twele, André; Huber, Claire; Plank, Simon; Maxant, Jérôme; Cao, Wenxi; Caspard, Mathilde; May, Stéphane

2016-04-01

Optical and radar satellite remote sensing have proven to provide essential crisis information in case of natural disasters, humanitarian relief activities and civil security issues in a growing number of cases through mechanisms such as the Copernicus Emergency Management Service (EMS) of the European Commission or the International Charter 'Space and Major Disasters'. The aforementioned programs and initiatives make use of satellite-based rapid mapping services aimed at delivering reliable and accurate crisis information after natural hazards. Although these services are increasingly operational, they need to be continuously updated and improved through research and development (R&D) activities. The principal objective of ASAPTERRA (Advancing SAR and Optical Methods for Rapid Mapping), the ESA-funded R&D project being described here, is to improve, automate and, hence, speed-up geo-information extraction procedures in the context of natural hazards response. This is performed through the development, implementation, testing and validation of novel image processing methods using optical and Synthetic Aperture Radar (SAR) data. The methods are mainly developed based on data of the German radar satellites TerraSAR-X and TanDEM-X, the French satellite missions Pléiades-1A/1B as well as the ESA missions Sentinel-1/2 with the aim to better characterize the potential and limitations of these sensors and their synergy. The resulting algorithms and techniques are evaluated in real case applications during rapid mapping activities. The project is focussed on three types of natural hazards: floods, landslides and fires. Within this presentation an overview of the main methodological developments in each topic is given and demonstrated in selected test areas. The following developments are presented in the context of flood mapping: a fully automated Sentinel-1 based processing chain for detecting open flood surfaces, a method for the improved detection of flooded vegetation in Sentinel-1data using Entropy/Alpha decomposition, unsupervised Wishart Classification, and object-based post-classification as well as semi-automatic approaches for extracting inundated areas and flood traces in rural and urban areas from VHR and HR optical imagery using machine learning techniques. Methodological developments related to fires are the implementation of fast and robust methods for mapping burnt scars using change detection procedures using SAR (Sentinel-1, TerraSAR-X) and HR optical (e.g. SPOT, Sentinel-2) data as well as the extraction of 3D surface and volume change information from Pléiades stereo-pairs. In the context of landslides, fast and transferable change detection procedures based on SAR (TerraSAR-X) and optical (SPOT) data as well methods for extracting the extent of landslides only based on polarimetric VHR SAR (TerraSAR-X) data are presented.

Mapping northern Atlantic coastal marshlands, Maryland-Virginia, using ERTS imagery

NASA Technical Reports Server (NTRS)

Anderson, R. R. (Principal Investigator); Carter, V. L.; Mcginness, J. W., Jr.

1973-01-01

The author has identified the following significant results. ERTS-1 data provides repetitive synoptic coverage for DC 00000 of wetland ecology, detection of change, and mapping or inventory of wetland boundaries and plant communities. ERTS-1 positive transparencies of Atlantic Coastal wetlands were enlarged to different scales and mapped using a variety of methods. Results of analysis indicate: (1) mapping of wetland boundaries and vegetative communities from imagery at a scale of 1:1,000,000 is impractical because small details are difficult to illustrate; (2) mapping to a scale of 1:250,000 is practical for defining land-water interface, upper wetland boundary, gross vegetative communities, and spoil disposal/dredge and fill operations; (3) 1:125,000 enlargements provide additional information on transition zones, smaller plant communities, and drainage or mosquito ditching. Overlays may be made directly from prints.

US Topo Maps 2014: Program updates and research

USGS Publications Warehouse

Fishburn, Kristin A.

2014-01-01

The U. S. Geological Survey (USGS) US Topo map program is now in year two of its second three-year update cycle. Since the program was launched in 2009, the product and the production system tools and processes have undergone enhancements that have made the US Topo maps a popular success story. Research and development continues with structural and content product enhancements, streamlined and more fully automated workflows, and the evaluation of a GIS-friendly US Topo GIS Packet. In addition, change detection methodologies are under evaluation to further streamline product maintenance and minimize resource expenditures for production in the future. The US Topo map program will continue to evolve in the years to come, providing traditional map users and Geographic Information System (GIS) analysts alike with a convenient, freely available product incorporating nationally consistent data that are quality assured to high standards.

With or without spikes: localization of focal epileptic activity by simultaneous electroencephalography and functional magnetic resonance imaging

PubMed Central

Grouiller, Frédéric; Thornton, Rachel C.; Groening, Kristina; Spinelli, Laurent; Duncan, John S.; Schaller, Karl; Siniatchkin, Michael; Lemieux, Louis; Seeck, Margitta; Michel, Christoph M.

2011-01-01

In patients with medically refractory focal epilepsy who are candidates for epilepsy surgery, concordant non-invasive neuroimaging data are useful to guide invasive electroencephalographic recordings or surgical resection. Simultaneous electroencephalography and functional magnetic resonance imaging recordings can reveal regions of haemodynamic fluctuations related to epileptic activity and help localize its generators. However, many of these studies (40–70%) remain inconclusive, principally due to the absence of interictal epileptiform discharges during simultaneous recordings, or lack of haemodynamic changes correlated to interictal epileptiform discharges. We investigated whether the presence of epilepsy-specific voltage maps on scalp electroencephalography correlated with haemodynamic changes and could help localize the epileptic focus. In 23 patients with focal epilepsy, we built epilepsy-specific electroencephalographic voltage maps using averaged interictal epileptiform discharges recorded during long-term clinical monitoring outside the scanner and computed the correlation of this map with the electroencephalographic recordings in the scanner for each time frame. The time course of this correlation coefficient was used as a regressor for functional magnetic resonance imaging analysis to map haemodynamic changes related to these epilepsy-specific maps (topography-related haemodynamic changes). The method was first validated in five patients with significant haemodynamic changes correlated to interictal epileptiform discharges on conventional analysis. We then applied the method to 18 patients who had inconclusive simultaneous electroencephalography and functional magnetic resonance imaging studies due to the absence of interictal epileptiform discharges or absence of significant correlated haemodynamic changes. The concordance of the results with subsequent intracranial electroencephalography and/or resection area in patients who were seizure free after surgery was assessed. In the validation group, haemodynamic changes correlated to voltage maps were similar to those obtained with conventional analysis in 5/5 patients. In 14/18 patients (78%) with previously inconclusive studies, scalp maps related to epileptic activity had haemodynamic correlates even when no interictal epileptiform discharges were detected during simultaneous recordings. Haemodynamic changes correlated to voltage maps were spatially concordant with intracranial electroencephalography or with the resection area. We found better concordance in patients with lateral temporal and extratemporal neocortical epilepsy compared to medial/polar temporal lobe epilepsy, probably due to the fact that electroencephalographic voltage maps specific to lateral temporal and extratemporal epileptic activity are more dissimilar to maps of physiological activity. Our approach significantly increases the yield of simultaneous electroencephalography and functional magnetic resonance imaging to localize the epileptic focus non-invasively, allowing better targeting for surgical resection or implantation of intracranial electrode arrays. PMID:21752790

Application of Geologic Mapping Techniques and Autonomous Feature Detection to Future Exploration of Europa

NASA Astrophysics Data System (ADS)

Bunte, M. K.; Tanaka, K. L.; Doggett, T.; Figueredo, P. H.; Lin, Y.; Greeley, R.; Saripalli, S.; Bell, J. F.

2013-12-01

Europa's extremely young surface age, evidence for extensive resurfacing, and indications of a sub-surface ocean elevate its astrobiological potential for habitable environments and make it a compelling focus for study. Knowledge of the global distribution and timing of Europan geologic units is a key step in understanding the history of the satellite and for identifying areas relevant for exploration. I have produced a 1:15M scale global geologic map of Europa which represents a proportionate distribution of four unit types and associated features: plains, linea, chaos, and crater materials. Mapping techniques differ somewhat from other planetary maps but do provide a method to establish stratigraphic markers and to illustrate the surface history through four periods of formation as a function of framework lineament cross-cutting relationships. Correlations of observed features on Europa with Earth analogs enforce a multi-process theory for formation rather than the typical reliance on the principle of parsimony. Lenticulae and microchaos are genetically similar and most likely form by diapirism. Platy and blocky chaos units, endmembers of archetypical chaos, are best explained by brine mobilization. Ridges account for the majority of lineaments and may form by a number of methods indicative of local conditions; most form by either tidal pumping or shear heating. The variety of morphologies exhibited by bands indicates that multiple formation mechanisms apply once fracturing of the brittle surface over a ductile subsurface is initiated. Mapping results support the interpretation that Europa's shell has thickened over time resulting in changes in the style and intensity of deformation. Mapping serves as an index for change detection and classification, aids in pre-encounter targeting, and supports the selection of potential landing sites. Highest priority target areas are those which indicate geophysical activity by the presence of volcanic plumes, outgassing, or disrupted surface morphologies. Areas of high interest include lineaments and chaos margins. The limitations on detecting activity at these locations are approximated by studying similar observed conditions on other bodies. By adapting machine learning and data mining techniques to signatures of plumes and morphology, I have demonstrated autonomous rule-based detection of known features using edge-detection and supervised classification methods. These methods successfully detect ≤94% of known volcanic plumes or jets at Io, Enceladus, and comets. They also allow recognition of multiple feature types. Applying these results to conditions expected for Europa enables a prediction of the potential for detection of similar features and enables recommendations for mission concepts to increase the science return and efficiency of future missions to observe Europa. This post-Galileo view of Europa provides a synthesis of the overall history of this unique icy satellite and will be a useful frame of reference for future exploration of the jovian system and other potentially active outer solar system bodies.

Smartphone-Based Mobile Detection Platform for Molecular Diagnostics and Spatiotemporal Disease Mapping.

PubMed

Song, Jinzhao; Pandian, Vikram; Mauk, Michael G; Bau, Haim H; Cherry, Sara; Tisi, Laurence C; Liu, Changchun

2018-04-03

Rapid and quantitative molecular diagnostics in the field, at home, and at remote clinics is essential for evidence-based disease management, control, and prevention. Conventional molecular diagnostics requires extensive sample preparation, relatively sophisticated instruments, and trained personnel, restricting its use to centralized laboratories. To overcome these limitations, we designed a simple, inexpensive, hand-held, smartphone-based mobile detection platform, dubbed "smart-connected cup" (SCC), for rapid, connected, and quantitative molecular diagnostics. Our platform combines bioluminescent assay in real-time and loop-mediated isothermal amplification (BART-LAMP) technology with smartphone-based detection, eliminating the need for an excitation source and optical filters that are essential in fluorescent-based detection. The incubation heating for the isothermal amplification is provided, electricity-free, with an exothermic chemical reaction, and incubation temperature is regulated with a phase change material. A custom Android App was developed for bioluminescent signal monitoring and analysis, target quantification, data sharing, and spatiotemporal mapping of disease. SCC's utility is demonstrated by quantitative detection of Zika virus (ZIKV) in urine and saliva and HIV in blood within 45 min. We demonstrate SCC's connectivity for disease spatiotemporal mapping with a custom-designed website. Such a smart- and connected-diagnostic system does not require any lab facilities and is suitable for use at home, in the field, in the clinic, and particularly in resource-limited settings in the context of Internet of Medical Things (IoMT).

ForWarn Forest Disturbance Change Detection System Provides a Weekly Snapshot of US Forest Conditions to Aid Forest Managers

NASA Astrophysics Data System (ADS)

Hargrove, W. W.; Spruce, J.; Kumar, J.; Hoffman, F. M.

2012-12-01

The Eastern Forest Environmental Threat Assessment Center and Western Wildland Environmental Assessment Center of the USDA Forest Service have collaborated with NASA Stennis Space Center to develop ForWarn, a forest monitoring tool that uses MODIS satellite imagery to produce weekly snapshots of vegetation conditions across the lower 48 United States. Forest and natural resource managers can use ForWarn to rapidly detect, identify, and respond to unexpected changes in the nation's forests caused by insects, diseases, wildfires, severe weather, or other natural or human-caused events. ForWarn detects most types of forest disturbances, including insects, disease, wildfires, frost and ice damage, tornadoes, hurricanes, blowdowns, harvest, urbanization, and landslides. It also detects drought, flood, and temperature effects, and shows early and delayed seasonal vegetation development. Operating continuously since January 2010, results show ForWarn to be a robust and highly capable tool for detecting changes in forest conditions. To help forest and natural resource managers rapidly detect, identify, and respond to unexpected changes in the nation's forests, ForWarn produces sets of national maps showing potential forest disturbances at 231m resolution every 8 days, and posts the results to the web for examination. ForWarn compares current greenness with the "normal," historically seen greenness that would be expected for healthy vegetation for a specific location and time of the year, and then identifies areas appearing less green than expected to provide a strategic national overview of potential forest disturbances that can be used to direct ground and aircraft efforts. In addition to forests, ForWarn also tracks potential disturbances in rangeland vegetation and agriculural crops. ForWarn is the first national-scale system of its kind based on remote sensing developed specifically for forest disturbances. The ForWarn system had an official unveiling and rollout in March 2012, initiated by a joint NASA and USDA press release, and followed by a series of training webinars. Almost 60 early-adopter state and federal forest managers attended at least one of the ForWarn rollout webinars. The ForWarn home page has had 2,632 unique visitors since rollout in March 2012, with 39% returning visits. ForWarn was used to map tornado scars from the historic April 27, 2011 tornado outbreak, and detected timber damage within more than a dozen tornado tracks across northern Mississippi, Alabama, and Georgia. ForWarn is the result of an ongoing, substantive cooperation among four different government agencies: USDA, NASA, USGS, and DOE. Disturbance maps are available on the web through the ForWarn Change Assessment Viewer at http://forwarn.forestthreats.org/fcav.

Unveiling topographical changes using LiDAR mapping capability: case study of Belaga in Sarawak, East-Malaysia

NASA Astrophysics Data System (ADS)

Ganendra, T. R.; Khan, N. M.; Razak, W. J.; Kouame, Y.; Mobarakeh, E. T.

2016-06-01

The use of Light Detection and Ranging (LiDAR) remote sensing technology to scan and map landscapes has proven to be one of the most popular techniques to accurately map topography. Thus, LiDAR technology is the ultimate method of unveiling the surface feature under dense vegetation, and, this paper intends to emphasize the diverse techniques that can be utilized to elucidate topographical changes over the study area, using multi-temporal airborne full waveform LiDAR datasets collected in 2012 and 2014. Full waveform LiDAR data offers access to an almost unlimited number of returns per shot, which enables the user to explore in detail topographical changes, such as vegetation growth measurement. The study also found out topography changes at the study area due to earthwork activities contributing to soil consolidation, soil erosion and runoff, requiring cautious monitoring. The implications of this study not only concurs with numerous investigations undertaken by prominent researchers to improve decision making, but also corroborates once again that investigations employing multi-temporal LiDAR data to unveil topography changes in vegetated terrains, produce more detailed and accurate results than most other remote sensing data.

In Vivo Confocal Intrinsic Optical Signal Identification of Localized Retinal Dysfunction

PubMed Central

Zhang, Qiu-Xiang; Lu, Rong-Wen; Curcio, Christine A.; Yao, Xin-Cheng

2012-01-01

Purpose. The purposes of this study were to investigate the physiological mechanism of stimulus-evoked fast intrinsic optical signals (IOSs) recorded in dynamic confocal imaging of the retina, and to demonstrate the feasibility of in vivo confocal IOS mapping of localized retinal dysfunctions. Methods. A rapid line-scan confocal ophthalmoscope was constructed to achieve in vivo confocal IOS imaging of frog (Rana pipiens) retinas at cellular resolution. In order to investigate the physiological mechanism of confocal IOS, comparative IOS and electroretinography (ERG) measurements were made using normal frog eyes activated by variable-intensity stimuli. A dynamic spatiotemporal filtering algorithm was developed to reject the contamination of hemodynamic changes on fast IOS recording. Laser-injured frog eyes were employed to test the potential of confocal IOS mapping of localized retinal dysfunctions. Results. Comparative IOS and ERG experiments revealed a close correlation between the confocal IOS and retinal ERG, particularly the ERG a-wave, which has been widely used to evaluate photoreceptor function. IOS imaging of laser-injured frog eyes indicated that the confocal IOS could unambiguously detect localized (30 μm) functional lesions in the retina before a morphological abnormality is detectable. Conclusions. The confocal IOS predominantly results from retinal photoreceptors, and can be used to map localized photoreceptor lesion in laser-injured frog eyes. We anticipate that confocal IOS imaging can provide applications in early detection of age-related macular degeneration, retinitis pigmentosa, and other retinal diseases that can cause pathological changes in the photoreceptors. PMID:23150616

Active and Passive Remote Sensing Data Time Series for Flood Detection and Surface Water Mapping

NASA Astrophysics Data System (ADS)

Bioresita, Filsa; Puissant, Anne; Stumpf, André; Malet, Jean-Philippe

2017-04-01

As a consequence of environmental changes surface waters are undergoing changes in time and space. A better knowledge of the spatial and temporal distribution of surface waters resources becomes essential to support sustainable policies and development activities. Especially because surface waters, are not only a vital sweet water resource, but can also pose hazards to human settlements and infrastructures through flooding. Floods are a highly frequent disaster in the world and can caused huge material losses. Detecting and mapping their spatial distribution is fundamental to ascertain damages and for relief efforts. Spaceborne Synthetic Aperture Radar (SAR) is an effective way to monitor surface waters bodies over large areas since it provides excellent temporal coverage and, all-weather day-and-night imaging capabilities. However, emergent vegetation, trees, wind or flow turbulence can increase radar back-scatter returns and pose problems for the delineation of inundated areas. In such areas, passive remote sensing data can be used to identify vegetated areas and support the interpretation of SAR data. The availability of new Earth Observation products, for example Sentinel-1 (active) and Sentinel-2 (passive) imageries, with both high spatial and temporal resolution, have the potential to facilitate flood detection and monitoring of surface waters changes which are very dynamic in space and time. In this context, the research consists of two parts. In the first part, the objective is to propose generic and reproducible methodologies for the analysis of Sentinel-1 time series data for floods detection and surface waters mapping. The processing chain comprises a series of pre-processing steps and the statistical modeling of the pixel value distribution to produce probabilistic maps for the presence of surface waters. Images pre-processing for all Sentinel-1 images comprise the reduction SAR effect like orbit errors, speckle noise, and geometric effects. A modified Split Based Approach (MSBA) is used in order to focus on surface water areas automatically and facilitate the estimation of class models for water and non-water areas. A Finite Mixture Model is employed as the underlying statistical model to produce probabilistic maps. Subsequently, bilateral filtering is applied to take into account spatial neighborhood relationships in the generation of final map. The elimination of shadows effect is performed in a post-processing step. The processing chain is tested on three case studies. The first case is a flood event in central Ireland, the second case is located in Yorkshire county / Great Britain, and the third test case covers a recent flood event in northern Italy. The tests showed that the modified SBA step and the Finite Mixture Models can be applied for the automatic surface water detection in a variety of test cases. An evaluation again Copernicus products derived from very-high resolution imagery was performed, and showed a high overall accuracy and F-measure of the obtained maps. This evaluation also showed that the use of probability maps and bilateral filtering improved the accuracy of classification results significantly. Based on this quantitative evaluation, it is concluded that the processing chain can be applied for flood mapping from Sentinel-1 data. To estimate robust statistical distributions the method requires sufficient surface waters areas in the observed zone and sufficient contrast between surface waters and other land use classes. Ongoing research addresses the fusion of Sentinel-1 and passive remote sensing data (e.g. Sentinel-2) in order to reduce the current shortcomings in the developed processing chain. In this work, fusion is performed at the feature level to better account for the difference image properties of SAR and optical sensors. Further, the processing chain is currently being optimized in terms of calculation time for a further integration as a flood mapping service on the A2S (Alsace Aval Sentinel) high-performance computing infrastructure of University of Strasbourg.

US LAND-COVER MONITORING AND DETECTION OF CHANGES IN SCALE AND CONTEXT OF FOREST

EPA Science Inventory

Disparate land-cover mapping programs, previously focused solely on mission-oriented goals, have organized themselves as the Multi-Resolution Land Characteristics (MRLC) Consortium with a unified goal of producing land-cover nationwide at routine intervals. Under MRLC, United Sta...

Census cities experiment in urban change detection

NASA Technical Reports Server (NTRS)

Wray, J. R. (Principal Investigator)

1973-01-01

The author has identified the following significant results. Work continues on mapping of 1970 urban land use from 1970 census contemporaneous aircraft photography. In addition, change detection analysis from 1972 aircraft photography is underway for several urban test sites. Land use maps, mosaics, and census overlays for the two largest urban test sites are nearing publication readiness. Preliminary examinations of ERTS-1 imagery of San Francisco Bay have been conducted which show that tracts of land of more than 10 acres in size which are undergoing development in an urban setting can be identified. In addition, each spectral band is being evaluated as to its utility for urban analyses. It has been found that MSS infrared band 7 helps to differentiate intra-urban land use details not found in other MSS bands or in the RBV coverage of the same scene. Good quality false CIR composites have been generated from 9 x 9 inch positive MSS bands using the Diazo process.

Object-Based Classification and Change Detection of Hokkaido, Japan

NASA Astrophysics Data System (ADS)

Park, J. G.; Harada, I.; Kwak, Y.

2016-06-01

Topography and geology are factors to characterize the distribution of natural vegetation. Topographic contour is particularly influential on the living conditions of plants such as soil moisture, sunlight, and windiness. Vegetation associations having similar characteristics are present in locations having similar topographic conditions unless natural disturbances such as landslides and forest fires or artificial disturbances such as deforestation and man-made plantation bring about changes in such conditions. We developed a vegetation map of Japan using an object-based segmentation approach with topographic information (elevation, slope, slope direction) that is closely related to the distribution of vegetation. The results found that the object-based classification is more effective to produce a vegetation map than the pixel-based classification.

Spotlight-Mode Synthetic Aperture Radar Processing for High-Resolution Lunar Mapping

NASA Technical Reports Server (NTRS)

Harcke, Leif; Weintraub, Lawrence; Yun, Sang-Ho; Dickinson, Richard; Gurrola, Eric; Hensley, Scott; Marechal, Nicholas

2010-01-01

During the 2008-2009 year, the Goldstone Solar System Radar was upgraded to support radar mapping of the lunar poles at 4 m resolution. The finer resolution of the new system and the accompanying migration through resolution cells called for spotlight, rather than delay-Doppler, imaging techniques. A new pre-processing system supports fast-time Doppler removal and motion compensation to a point. Two spotlight imaging techniques which compensate for phase errors due to i) out of focus-plane motion of the radar and ii) local topography, have been implemented and tested. One is based on the polar format algorithm followed by a unique autofocus technique, the other is a full bistatic time-domain backprojection technique. The processing system yields imagery of the specified resolution. Products enabled by this new system include topographic mapping through radar interferometry, and change detection techniques (amplitude and coherent change) for geolocation of the NASA LCROSS mission impact site.

Evaluation of the initial thematic output from a continuous change-detection algorithm for use in automated operational land-change mapping by the U.S. Geological Survey

USGS Publications Warehouse

Pengra, Bruce; Gallant, Alisa L.; Zhu, Zhe; Dahal, Devendra

2016-01-01

The U.S. Geological Survey (USGS) has begun the development of operational, 30-m resolution annual thematic land cover data to meet the needs of a variety of land cover data users. The Continuous Change Detection and Classification (CCDC) algorithm is being evaluated as the likely methodology following early trials. Data for training and testing of CCDC thematic maps have been provided by the USGS Land Cover Trends (LC Trends) project, which offers sample-based, manually classified thematic land cover data at 2755 probabilistically located sample blocks across the conterminous United States. These samples represent a high quality, well distributed source of data to train the Random Forest classifier invoked by CCDC. We evaluated the suitability of LC Trends data to train the classifier by assessing the agreement of annual land cover maps output from CCDC with output from the LC Trends project within 14 Landsat path/row locations across the conterminous United States. We used a small subset of circa 2000 data from the LC Trends project to train the classifier, reserving the remaining Trends data from 2000, and incorporating LC Trends data from 1992, to evaluate measures of agreement across time, space, and thematic classes, and to characterize disagreement. Overall agreement ranged from 75% to 98% across the path/rows, and results were largely consistent across time. Land cover types that were well represented in the training data tended to have higher rates of agreement between LC Trends and CCDC outputs. Characteristics of disagreement are being used to improve the use of LC Trends data as a continued source of training information for operational production of annual land cover maps.

Facilitating the exploitation of ERTS-1 imagery using snow enhancement techniques. [geological fault maps of Massachusetts and Connecticut

NASA Technical Reports Server (NTRS)

Wobber, F. J. (Principal Investigator); Martin, K. R.; Amato, R. V.; Leshendok, T.

1973-01-01

The author has identified the following significant results. The applications of ERTS-1 imagery for geological fracture mapping regardless of season has been repeatedly confirmed. The enhancement provided by a differential cover of snow increases the number and length of fracture-lineaments which can be detected with ERTS-1 data and accelerates the fracture mapping process for a variety of practical applications. The geological mapping benefits of the program will be realized in geographic areas where data are most needed - complex glaciated terrain and areas of deep residual soils. ERTS-1 derived fracture-lineament maps which provide detail well in excess of existing geological maps are not available in the Massachusetts-Connecticut area. The large quantity of new data provided by ERTS-1 may accelerate and improve field mapping now in progress in the area. Numerous other user groups have requested data on the techniques. This represents a major change in operating philosophy for groups who to data judged that snow obscured geological detail.

A Multi-Index Integrated Change detection method for updating the National Land Cover Database

USGS Publications Warehouse

Jin, Suming; Yang, Limin; Xian, George Z.; Danielson, Patrick; Homer, Collin G.

2010-01-01

Land cover change is typically captured by comparing two or more dates of imagery and associating spectral change with true thematic change. A new change detection method, Multi-Index Integrated Change (MIIC), has been developed to capture a full range of land cover disturbance patterns for updating the National Land Cover Database (NLCD). Specific indices typically specialize in identifying only certain types of disturbances; for example, the Normalized Burn Ratio (NBR) has been widely used for monitoring fire disturbance. Recognizing the potential complementary nature of multiple indices, we integrated four indices into one model to more accurately detect true change between two NLCD time periods. The four indices are NBR, Normalized Difference Vegetation Index (NDVI), Change Vector (CV), and a newly developed index called the Relative Change Vector (RCV). The model is designed to provide both change location and change direction (e.g. biomass increase or biomass decrease). The integrated change model has been tested on five image pairs from different regions exhibiting a variety of disturbance types. Compared with a simple change vector method, MIIC can better capture the desired change without introducing additional commission errors. The model is particularly accurate at detecting forest disturbances, such as forest harvest, forest fire, and forest regeneration. Agreement between the initial change map areas derived from MIIC and the retained final land cover type change areas will be showcased from the pilot test sites.

Short Diffusion Time Diffusion-Weighted Imaging With Oscillating Gradient Preparation as an Early Magnetic Resonance Imaging Biomarker for Radiation Therapy Response Monitoring in Glioblastoma: A Preclinical Feasibility Study.

PubMed

Bongers, Andre; Hau, Eric; Shen, Han

2018-01-04

To investigate a novel alternative diffusion-weighted imaging (DWI) approach using oscillating gradients preparation (OGSE) to obtain much shorter effective diffusion times (Δ eff ) for tumor response monitoring by apparent diffusion coefficient (ADC) mapping in a glioblastoma mouse model. Twenty-four BALB/c nude mice inoculated with U87 glioblastoma cells were randomized into a control group and an irradiation group, which underwent a 15-day fractioned radiation therapy (RT) course with 2 Gy/d. Therapy response was assessed by mapping of ADCs at 6 time points using an in-house implementation of a cos-OGSE DWI sequence with Δ eff  = 1.25 ms and compared with a standard pulsed gradient DWI protocol (PGSE) with typical clinical diffusion time Δ eff  = 18 ms. Longitudinal ADC changes in tumor and contralateral white matter (WM) were statistically assessed using repeated-measures analysis of variance and post hoc (Sidak) testing. On short Δ eff OGSE maps tumor ADC was generally 30%-50% higher than in surrounding WM. Areas correlated well with histology. Tumor identification was generally more difficult on PGSE maps owing to nonsignificant WM/tumor contrast. During RT, OGSE maps also showed significant tumor ADC increase (approximately 15%) in response to radiation, consistently seen after 14-Gy RT dose. The clinical reference (PGSE) showed lower sensitivity to radiation changes, and no significant response across the radiation group and time course could be detected. Our short Δ eff DWI method using OGSE better reflected histologically defined tumor areas and enabled more consistent and earlier detection of microstructural radiation changes than conventional methods. Oscillating gradients preparation offers significant potential as a robust microstructural RT response biomarker, potentially helping to shift important therapy decisions to earlier stages in the RT time course. Copyright © 2018 Elsevier Inc. All rights reserved.

Assessment of land cover changes in Lampedusa Island (Italy) using Landsat TM and OLI data

NASA Astrophysics Data System (ADS)

Mei, Alessandro; Manzo, Ciro; Fontinovo, Giuliano; Bassani, Cristiana; Allegrini, Alessia; Petracchini, Francesco

2016-10-01

The Lampedusa Island displays important socio-economic criticalities related to an intensive touristic activity, which implies an increase in electricity consumption and waste production. An adequate island conversion to a more environmental, sustainable community needs to be faced by the local Management Plans establishment. For this purpose, several thematic datasets have to be produced and evaluated. Socio-economic and bio-ecological components as well as land cover/use assessment are some of the main topics to be managed within the Decision Support Systems. Considering the lack of Land Cover (LC) and vegetation change detection maps in Lampedusa Island (Italy), this paper focuses on the retrieval of these topics by remote sensing techniques. The analysis was carried out by Landsat 5 TM and Landsat 8 OLI multispectral images from 1984 to 2014 in order to obtain spatial and temporal information of changes occurred in the island. Firstly, imagery was co-registered and atmospherically corrected; secondly, it was then classified for land cover and vegetation distribution analysis with the use of QGIS and Saga GIS open source softwares. The Maximum Likelihood Classifier (MLC) was used for LC maps production, while the Normalized Difference Vegetation Index (NDVI) was used for vegetation examination and distribution. Topographic maps, historical aerial photos, ortophotos and field data are merged in the GIS for accuracy assessment. Finally, change detection of MLC and NDVI are provided respectively by Post-Classification Comparison (PCC) and Image Differencing (ID). The provided information, combined with local socio-economic parameters, is essential for the improvement of environmental sustainability of anthropogenic activities in Lampedusa.

Predicting impact of multi-paths on phase change in map-based vehicular ad hoc networks

NASA Astrophysics Data System (ADS)

Rahmes, Mark; Lemieux, George; Sonnenberg, Jerome; Chester, David B.

2014-05-01

Dynamic Spectrum Access, which through its ability to adapt the operating frequency of a radio, is widely believed to be a solution to the limited spectrum problem. Mobile Ad Hoc Networks (MANETs) can extend high capacity mobile communications over large areas where fixed and tethered-mobile systems are not available. In one use case with high potential impact cognitive radio employs spectrum sensing to facilitate identification of allocated frequencies not currently accessed by their primary users. Primary users own the rights to radiate at a specific frequency and geographic location, secondary users opportunistically attempt to radiate at a specific frequency when the primary user is not using it. We quantify optimal signal detection in map based cognitive radio networks with multiple rapidly varying phase changes and multiple orthogonal signals. Doppler shift occurs due to reflection, scattering, and rapid vehicle movement. Path propagation as well as vehicle movement produces either constructive or destructive interference with the incident wave. Our signal detection algorithms can assist the Doppler spread compensation algorithm by deciding how many phase changes in signals are present in a selected band of interest. Additionally we can populate a spatial radio environment map (REM) database with known information that can be leveraged in an ad hoc network to facilitate Dynamic Spectrum Access. We show how topography can help predict the impact of multi-paths on phase change, as well as about the prediction from dense traffic areas. Utilization of high resolution geospatial data layers in RF propagation analysis is directly applicable.

Evaluate ERTS imagery for mapping and detection of changes of snowcover on land and on glaciers

NASA Technical Reports Server (NTRS)

Meier, M. F. (Principal Investigator)

1973-01-01

The author has identified the following significant results. A possibly more accurate method to determine snowcover area change has been tried; snowcover area change over periods of an ERTS-1 cycle are very useful in determining energy balances over regional areas and to determine snow depth as a function of altitude. Also since shadow and cloud cover areas are highlighted this method may be a step toward more complete machine processing.

Census Cities experiment in urban change detection. [mapping of land use changes in San Francisco, Washington D.C., Phoenix, Tucson, Boston, New Haven, Cedar Rapids, and Pontiac

NASA Technical Reports Server (NTRS)

Wray, J. R. (Principal Investigator); Milazzo, V. A.

1974-01-01

The author has identified the following significant results. Mapping of 1970 and 1972 land use from high-flight photography has been completed for all test sites: San Francisco, Washington, Phoenix, Tucson, Boston, New Haven, Cedar Rapids, and Pontiac. Area analysis of 1970 and 1972 land use has been completed for each of the mandatory urban areas. All 44 sections of the 1970 land use maps of the San Francisco test site have been officially released through USGS Open File at 1:62,500. Five thousand copies of the Washington one-sheet color 1970 land use map, census tract map, and point line identification map are being printed by USGS Publication Division. ERTS-1 imagery for each of the eight test sites is being received and analyzed. Color infrared photo enlargements at 1:100,000 of ERTS-1 MSS images of Phoenix taken on October 16, 1972 and May 2, 1973 are being analyzed to determine to what level land use and land use changes can be identified and to what extent the ERTS-1 imagery can be used in updating the 1970 aircraft photo-derived land use data base. Work is proceeding on the analysis of ERTS-1 imagery by computer manipulation of ERTS-1 MSS data in digital format. ERTS-1 CCT maps at 1:24,000 are being analyzed for two dates over Washington and Phoenix. Anniversary tape sets have been received at Purdue LARS for some additional urban test sites.

Multiscale remote sensing analysis to monitor riparian and upland semiarid vegetation

NASA Astrophysics Data System (ADS)

Nguyen, Uyen

The health of natural vegetation communities is of concern due to observed changes in the climatic-hydrological regime and land cover changes particularly in arid and semiarid regions. Monitoring vegetation at multi temporal and spatial scales can be the most informative approach for detecting change and inferring causal agents of change and remediation strategies. Riparian communities are tightly linked to annual stream hydrology, ground water elevations and sediment transport. These processes are subject to varying magnitudes of disturbance overtime and are candidates for multi-scale monitoring. My first research objective focused on the response of vegetation in the Upper San Pedro River, Arizona, to reduced base flows and climate change. I addressed the correlation between riparian vegetation and hydro-climate variables during the last three decades in one of the remaining undammed rivers in the southwestern U.S. Its riparian forest is threatened by the diminishing base flows, attributed by different studies either to increases in evapotranspiration (ET) due to conversion of grasslands to mesquite shrublands in the adjacent uplands, or to increased regional groundwater pumping to serve growing populations in surrounding urban areas and or to some interactions of those causes. Landsat 5 imagery was acquired for pre- monsoon period, when riparian trees had leafed out but before the arrival of summer monsoon rains in July. The result has showed Normalized Difference Vegetation Index (NDVI) values from both Landsat and Moderate Resolution Imaging Spectrometer (MODIS) had significant decreases which positively correlated to river flows, which decreased over the study period, and negatively correlated with air temperatures, which have increased by about 1.4°C from 1904 to the present. The predictions from other studies that decreased river flows could negatively impact the riparian forest were supported by this study. The pre-monsoon Normalized Different Vegetation Index (NDVI) average values in the adjacent uplands also decreased over thirty years and were correlated with the previous year's annual precipitation. Hence an increase in ET in the uplands did not appear to be responsible for the decrease in river flows in this study, leaving increased regional groundwater pumping as a feasible alternative explanation for decreased flows and deterioration of the riparian forest. The second research objective was to develop a new method of classification using very high-resolution aerial photo to map riparian vegetation at the species level in the Colorado River Ecosystem, Grand Canyon area, Arizona. Ground surveys have showed an obvious trend in which non-native saltcedar (Tamarix spp.) has replaced native vegetation over time. Our goal was to develop a quantitative mapping procedure to detect changes in vegetation as the ecosystem continues to respond to hydrological and climate changes. Vegetation mapping for the Colorado River Ecosystem needed an updated database map of the area covered by riparian vegetation and an indicator of species composition in the river corridor. The objective of this research was to generate a new riparian vegetation map at species level using a supervised image classification technique for the purpose of patch and landscape change detection. A new classification approach using multispectral images allowed us to successfully identify and map riparian species coverage the over whole Colorado River Ecosystem, Grand Canyon area. The new map was an improvement over the initial 2002 map since it reduced fragmentation from mixed riparian vegetation areas. The most dominant tree species in the study areas is saltcedar (Tamarix spp.). The overall accuracy is 93.48% and the kappa coefficient is 0.88. The reference initial inventory map was created using 2002 images to compare and detect changes through 2009. The third objective of my research focused on using multiplatform of remote sensing and ground calibration to estimate the effects of vegetation, land use patterns and water cycles. Climate change, hydrological and human uses are also leading to riparian, upland, grassland and crop vegetation changes at a variety of temporal and spatial scales, particularly in the arid and semi arid ecosystems, which are more sensitive to changes in water availability than humid ecosystems. The objectives of these studies from the last three articles were to evaluate the effect of water balance on vegetation indices in different plant communities based on relevant spatial and temporal scales. The new methodology of estimating water requirements using remote sensing data and ground calibration with flux tower data has been successfully tested at a variety sites, a sparse desert shrub environment as well as mixed riparian and cropland systems and upland vegetation in the arid and semi-arid regions. The main finding form these studies is that vegetation-index methods have to be calibrated with ground data for each new ecosystem but once calibrated they can accurately scale ET over wide areas and long time spans.

Space moving target detection using time domain feature

NASA Astrophysics Data System (ADS)

Wang, Min; Chen, Jin-yong; Gao, Feng; Zhao, Jin-yu

2018-01-01

The traditional space target detection methods mainly use the spatial characteristics of the star map to detect the targets, which can not make full use of the time domain information. This paper presents a new space moving target detection method based on time domain features. We firstly construct the time spectral data of star map, then analyze the time domain features of the main objects (target, stars and the background) in star maps, finally detect the moving targets using single pulse feature of the time domain signal. The real star map target detection experimental results show that the proposed method can effectively detect the trajectory of moving targets in the star map sequence, and the detection probability achieves 99% when the false alarm rate is about 8×10-5, which outperforms those of compared algorithms.

Mitigating Effects of Missing Data for SAR Coherent Images

DOE PAGES

Musgrove, Cameron H.; West, James C.

2017-01-01

Missing samples within synthetic aperture radar data result in image distortions. For coherent data products, such as coherent change detection and interferometric processing, the image distortion can be devastating to these second order products, resulting in missed detections and inaccurate height maps. Earlier approaches to repair the coherent data products focus upon reconstructing the missing data samples. This study demonstrates that reconstruction is not necessary to restore the quality of the coherent data products.

Evaluate ERTS imagery for mapping and detection of changes of snowcover on land and on glaciers. [Washington, Alaska, British Columbia, and U.S.S.R.

NASA Technical Reports Server (NTRS)

Meier, M. F. (Principal Investigator)

1973-01-01

The author has identified the following significant results. The standard error of measurement of snow covered areas in major drainage basins in the Cascade Range, Washington, using single measurements of ERTS-1 images, was found to range from 11% to 7% during a typical melt season, but was as high as 32% in midwinter. Many dangerous glacier situations in Alaska, Yukon, and British Columbia were observed on ERTS-1 imagery. Glacier dammed lakes in Alaska are being monitored by ERTS-1. Embayments in tidal glaciers show changes detectable by ERTS-1. Surges of Russell and Tweedsmuir Glaciers, now in progress, are clearly visible. The Tweedsmuir surge is likely to dam the large Alsek River by mid-November, producing major floods down-river next summer. An ERTS-1 image of the Pamir Mountains, Tadjik S.S.R., shows the surging Medvezhii (Bear) Glacier just after its surge of early summer which dammed the Abdukagor Valley creating a huge lake and later a flood in the populous Vanch River Valley. A map was compiled from an ERTS-1 image of the Lowell Glacier after its recent surge, compared with an earlier map compiled from pain-stakingly compiled from a mosaic of many aerial photographs, in a total elapsed time of 1.5 hours. This demonstrates the value of ERTS-1 for rapid mapping of large features.

Evaluation of Water Retention in Lumbar Intervertebral Disks Before and After Exercise Stress With T2 Mapping.

PubMed

Chokan, Kou; Murakami, Hideki; Endo, Hirooki; Mimata, Yoshikuni; Yamabe, Daisuke; Tsukimura, Itsuko; Oikawa, Ryosuke; Doita, Minoru

2016-04-01

T2 mapping was used to quantify moisture content of the lumbar spinal disk nucleus pulposus (NP) and annulus fibrosus before and after exercise stress, and after rest, to evaluate the intervertebral disk function. To clarify water retention in intervertebral disks of the lumbar vertebrae by performing magnetic resonance imaging before and after exercise stress and quantitatively measuring changes in moisture content of intervertebral disks with T2 mapping. To date, a few case studies describe functional evaluation of articular cartilage with T2 mapping; however, T2 mapping to the functional evaluation of intervertebral disks has rarely been applied. Using T2 mapping might help detect changes in the moisture content of intervertebral disks, including articular cartilage, before and after exercise stress, thus enabling the evaluation of changes in water retention shock absorber function. Subjects, comprising 40 healthy individuals (males: 26, females: 14), underwent magnetic resonance imaging T2 mapping before and after exercise stress and after rest. Image J image analysis software was then used to set regions of interest in the obtained images of the anterior annulus fibrosus, posterior annulus fibrosus, and NP. T2 values were measured and compared according to upper vertebrae position and degeneration grade. T2 values significantly decreased in the NP after exercise stress and significantly increased after rest. According to upper vertebrae position, in all of the upper vertebrae positions, T2 values for the NP significantly decreased after exercise stress and significantly increased after rest. According to the degeneration grade, in the NP of grade 1 and 2 cases, T2 values significantly decreased after exercise stress and significantly increased after rest. T2 mapping could be used to not only diagnose the degree of degeneration but also evaluate intervertebral disk function. 3.

Transcriptome and Allele Specificity Associated with a 3BL Locus for Fusarium Crown Rot Resistance in Bread Wheat

PubMed Central

Ma, Jian; Stiller, Jiri; Zhao, Qiang; Feng, Qi; Cavanagh, Colin; Wang, Penghao; Gardiner, Donald; Choulet, Frédéric; Feuillet, Catherine; Zheng, You-Liang; Wei, Yuming; Yan, Guijun; Han, Bin; Manners, John M.; Liu, Chunji

2014-01-01

Fusarium pathogens cause two major diseases in cereals, Fusarium crown rot (FCR) and head blight (FHB). A large-effect locus conferring resistance to FCR disease was previously located to chromosome arm 3BL (designated as Qcrs-3B) and several independent sets of near isogenic lines (NILs) have been developed for this locus. In this study, five sets of the NILs were used to examine transcriptional changes associated with the Qcrs-3B locus and to identify genes linked to the resistance locus as a step towards the isolation of the causative gene(s). Of the differentially expressed genes (DEGs) detected between the NILs, 12.7% was located on the single chromosome 3B. Of the expressed genes containing SNP (SNP-EGs) detected, 23.5% was mapped to this chromosome. Several of the DEGs and SNP-EGs are known to be involved in host-pathogen interactions, and a large number of the DEGs were among those detected for FHB in previous studies. Of the DEGs detected, 22 were mapped in the Qcrs-3B interval and they included eight which were detected in the resistant isolines only. The enrichment of DEG, and not necessarily those containing SNPs between the resistant and susceptible isolines, around the Qcrs-3B locus is suggestive of local regulation of this region by the resistance allele. Functions for 13 of these DEGs are known. Of the SNP-EGs, 28 were mapped in the Qcrs-3B interval and biological functions for 16 of them are known. These results provide insights into responses regulated by the 3BL locus and identify a tractable number of target genes for fine mapping and functional testing to identify the causative gene(s) at this QTL. PMID:25405461

Comparison of point counts and territory mapping for detecting effects of forest management on songbirds

USGS Publications Warehouse

Newell, Felicity L.; Sheehan, James; Wood, Petra Bohall; Rodewald, Amanda D.; Buehler, David A.; Keyser, Patrick D.; Larkin, Jeffrey L.; Beachy, Tiffany A.; Bakermans, Marja H.; Boves, Than J.; Evans, Andrea; George, Gregory A.; McDermott, Molly E.; Perkins, Kelly A.; White, Matthew; Wigley, T. Bently

2013-01-01

Point counts are commonly used to assess changes in bird abundance, including analytical approaches such as distance sampling that estimate density. Point-count methods have come under increasing scrutiny because effects of detection probability and field error are difficult to quantify. For seven forest songbirds, we compared fixed-radii counts (50 m and 100 m) and density estimates obtained from distance sampling to known numbers of birds determined by territory mapping. We applied point-count analytic approaches to a typical forest management question and compared results to those obtained by territory mapping. We used a before–after control impact (BACI) analysis with a data set collected across seven study areas in the central Appalachians from 2006 to 2010. Using a 50-m fixed radius, variance in error was at least 1.5 times that of the other methods, whereas a 100-m fixed radius underestimated actual density by >3 territories per 10 ha for the most abundant species. Distance sampling improved accuracy and precision compared to fixed-radius counts, although estimates were affected by birds counted outside 10-ha units. In the BACI analysis, territory mapping detected an overall treatment effect for five of the seven species, and effects were generally consistent each year. In contrast, all point-count methods failed to detect two treatment effects due to variance and error in annual estimates. Overall, our results highlight the need for adequate sample sizes to reduce variance, and skilled observers to reduce the level of error in point-count data. Ultimately, the advantages and disadvantages of different survey methods should be considered in the context of overall study design and objectives, allowing for trade-offs among effort, accuracy, and power to detect treatment effects.

The Feasibility Evaluation of Land Use Change Detection Using GAOFEN-3 Data

NASA Astrophysics Data System (ADS)

Huang, G.; Sun, Y.; Zhao, Z.

2018-04-01

GaoFen-3 (GF-3) satellite, is the first C band and multi-polarimetric Synthetic Aperture Radar (SAR) satellite in China. In order to explore the feasibility of GF-3 satellite in remote sensing interpretation and land-use remote sensing change detection, taking Guangzhou, China as a study area, the full polarimetric image of GF-3 satellite with 8 m resolution of two temporal as the data source. Firstly, the image is pre-processed by orthorectification, image registration and mosaic, and the land-use remote sensing digital orthophoto map (DOM) in 2017 is made according to the each county. Then the classification analysis and judgment of ground objects on the image are carried out by means of ArcGIS combining with the auxiliary data and using artificial visual interpretation, to determine the area of changes and the category of change objects. According to the unified change information extraction principle to extract change areas. Finally, the change detection results are compared with 3 m resolution TerraSAR-X data and 2 m resolution multi-spectral image, and the accuracy is evaluated. Experimental results show that the accuracy of the GF-3 data is over 75 % in detecting the change of ground objects, and the detection capability of new filling soil is better than that of TerraSAR-X data, verify the detection and monitoring capability of GF-3 data to the change information extraction, also, it shows that GF-3 can provide effective data support for the remote sensing detection of land resources.

Mapping the Extent and Magnitude of Severe Flooding Induced by Hurricanes Harvey, Irma, and Maria with Sentinel-1 SAR and InSAR Observations

NASA Astrophysics Data System (ADS)

Zhang, B.; Koirala, R.; Oliver-Cabrera, T.; Wdowinski, S.; Osmanoglu, B.

2017-12-01

Hurricanes can cause winds, rainfall and storm surge, all of which could result in flooding. Between August and September 2017, Hurricanes Harvey, Irma and Maria made landfall over Texas, Florida and Puerto Rico causing destruction and damages. Flood mapping is important for water management and to estimate risks and property damage. Though water gauges are able to monitor water levels, they are normally distributed sparsely. To map flooding products of these extreme events, we use Synthetic Aperture Radar (SAR) observations acquired by the European satellite constellation Sentinel-1. We obtained two acquisitions from before each flooding event, a single acquisition during the hurricane, and two after each event, a total of five acquisitions. We use both amplitude and phase observations to map extent and magnitude of flooding respectively. To map flooding extents, we use amplitude images from before, after and if possible during the hurricane pass. A calibration is used to convert the image raw data to backscatter coefficient, termed sigma nought. We generate a composite of the two image layers using red and green bands to show the change of sigma nought between acquisitions, which directly reflects the extent of flooding. Because inundation can result with either an increase or decrease of sigma nought values depending on the surface scattering characteristics, we map flooded areas in location where sigma nought changes were above a detection threshold. To study magnitude of flooding we study Interferometric Synthetic Aperture Radar (InSAR) phase changes. Changes in the water level can be detected by the radar when the signal is reflected away from water surface and bounces again by another object (e.g. trees and/or buildings) known as double bounce phase. To generate meaningful interferograms, we compare phase information with the nearest water gauge records to verify our results. Preliminary results show that the three hurricanes caused flooding condition over wide area including both rural and urban areas. The flooding in Everglades National Park in Florida following hurricane Irma covered area 1087.35 km2. Flooding in Puerto Rico main island was limited to low flat areas covering 287.84 km2. Preliminary results of the InSAR analysis shows that flooding magnitude reached in some location level of 1 m.

Mapping Secondary Forest Succession on Abandoned Agricultural Land in the Polish Carpathians

NASA Astrophysics Data System (ADS)

Kolecka, N.; Kozak, J.; Kaim, D.; Dobosz, M.; Ginzler, Ch.; Psomas, A.

2016-06-01

Land abandonment and secondary forest succession have played a significant role in land cover changes and forest cover increase in mountain areas in Europe over the past several decades. Land abandonment can be easily observed in the field over small areas, but it is difficult to map over the large areas, e.g., with remote sensing, due to its subtle and spatially dispersed character. Our previous paper presented how the LiDAR (Light Detection and Ranging) and topographic data were used to detect secondary forest succession on abandoned land in one commune located in the Polish Carpathians by means of object-based image analysis (OBIA) and GIS (Kolecka et al., 2015). This paper proposes how the method can be applied to efficiently map secondary forest succession over the entire Polish Carpathians, incorporating spatial sampling strategy supported by various ancillary data. Here we discuss the methods of spatial sampling, its limitations and results in the context of future secondary forest succession modelling.

High resolution regional soil carbon mapping in Madagascar : towards easy to update maps

NASA Astrophysics Data System (ADS)

Grinand, Clovis; Dessay, Nadine; Razafimbelo, Tantely; Razakamanarivo, Herintsitoaina; Albrecht, Alain; Vaudry, Romuald; Tiberghien, Matthieu; Rasamoelina, Maminiaina; Bernoux, Martial

2013-04-01

The soil organic carbon plays an important role in climate change regulation through carbon emissions and sequestration due to land use changes, notably tropical deforestation. Monitoring soil carbon emissions from shifting-cultivation requires to evaluate the amount of carbon stored at plot scale with a sufficient level of accuracy to be able to detect changes. The objective of this work was to map soil carbon stocks (30 cm and 100 cm depths) for different land use at regional scale using high resolution satellite dataset. The Andohahela National Parc and its surroundings (South-Est Madagascar) - a region with the largest deforestation rate in the country - was selected as a pilot area for the development of the methodology. A three steps approach was set up: (i) carbon inventory using mid infra-red spectroscopy and stock calculation, (ii) spatial data processing and (iii) modeling and mapping. Soil spectroscopy was successfully used for measuring organic carbon in this region. The results show that Random Forest was the inference model that produced the best estimates on calibration and validation datasets. By using a simple and robust method, we estimated uncertainty levels of of 35% and 43% for 30-cm and 100-cm carbon maps respectively. The approach developed in this study was based on open data and open source software that can be easily replicated to other regions and for other time periods using updated satellite images.

Gastrointestinal Impedance Spectroscopy to Detect Hypoperfusion During Hemorrhage.

PubMed

Bloch, Andreas; Kohler, Andreas; Posthaus, Horst; Berger, David; Santos, Laura; Jakob, Stephan; Takala, Jukka; Haenggi, Matthias

2017-08-01

Changes in tissue impedance (Ω) have been proposed as early signs of impaired tissue perfusion. We hypothesized that hemorrhage may induce early changes in alimentary tract tissue impedance and that these can be detected by impedance spectroscopy. We evaluated impedance spectroscopy in an acute hemorrhage model in pigs. Twenty anesthetized pigs were randomized to stepwise hemorrhage to mean arterial blood pressure (MAP) targets of 60 mm Hg, 50 mm Hg, 45 mm Hg, and 40 mm Hg, followed by retransfusion in two steps, or control (n = 10 each). In the end, 500 mL of enteral nutrition was administered in both groups. Ω in four sites (sublingually, esophagus, stomach, proximal jejunum) and cardiac output (Qtot thermodilution), superior mesenteric artery blood flow (QSMA; Doppler ultrasound), and jejunal mucosal blood flow (LDF; laser Doppler) were measured. The bleeding (total volume 838 ± 185 mL; mean ± SD) resulted in progressive hypotension (actual MAP 65 ± 3 mm Hg, 59 ± 4 mm Hg, 55 ± 5 mm Hg, and 46 ± 6 mm Hg) and decrease in Qtot, QSMA, and mucosal LDF. Bleeding did not change Ω in any of the monitoring sites. Retransfusion restored the blood flows to at least baseline levels, again without change in Ω. Enteral nutrition did not alter Ω or any of the blood flows.Five animals (three in the hemorrhage group, two in the control group) had histologically proven acute gastric focal necrosis at the site of It transducer. Gastrointestinal impedance spectroscopy does not detect early changes in tissue perfusion during progressive hemorrhage or retransfusion. Ω spectroscopy is unlikely to provide any additional information of hypovolemia-induced early changes in gastrointestinal perfusion.

Comparing automated classification and digitization approaches to detect change in eelgrass bed extent during restoration of a large river delta

USGS Publications Warehouse

Davenport, Anna Elizabeth; Davis, Jerry D.; Woo, Isa; Grossman, Eric; Barham, Jesse B.; Ellings, Christopher S.; Takekawa, John Y.

2017-01-01

Native eelgrass (Zostera marina) is an important contributor to ecosystem services that supplies cover for juvenile fish, supports a variety of invertebrate prey resources for fish and waterbirds, provides substrate for herring roe consumed by numerous fish and birds, helps stabilize sediment, and sequesters organic carbon. Seagrasses are in decline globally, and monitoring changes in their growth and extent is increasingly valuable to determine impacts from large-scale estuarine restoration and inform blue carbon mapping initiatives. Thus, we examined the efficacy of two remote sensing mapping methods with high-resolution (0.5 m pixel size) color near infrared imagery with ground validation to assess change following major tidal marsh restoration. Automated classification of false color aerial imagery and digitized polygons documented a slight decline in eelgrass area directly after restoration followed by an increase two years later. Classification of sparse and low to medium density eelgrass was confounded in areas with algal cover, however large dense patches of eelgrass were well delineated. Automated classification of aerial imagery from unsupervised and supervised methods provided reasonable accuracies of 73% and hand-digitizing polygons from the same imagery yielded similar results. Visual clues for hand digitizing from the high-resolution imagery provided as reliable a map of dense eelgrass extent as automated image classification. We found that automated classification had no advantages over manual digitization particularly because of the limitations of detecting eelgrass with only three bands of imagery and near infrared.

(Semi-)Automated landform mapping of the alpine valley Gradental (Austria) based on LiDAR data

NASA Astrophysics Data System (ADS)

Strasser, T.; Eisank, C.

2012-04-01

Alpine valleys are typically characterised as complex, hierarchical structured systems with rapid landform changes. Detection of landform changes can be supported by automated geomorphological mapping. Especially, the analysis over short time scales require a method for standardised, unbiased geomorphological map reproduction, which is delivered by automated mapping techniques. In general, digital geomorphological mapping is a challenging task, since knowledge about landforms with respect to their natural boundaries as well as their hierarchical and scaling relationships, has to be integrated in an objective way. A combination of very-high spatial resolution data (VHSR) such as LiDAR and new methods like object based image analysis (OBIA) allow for a more standardised production of geomorphological maps. In OBIA the processing units are spatially configured objects that are created by multi-scale segmentation. Therefore, not only spectral information can be used for assigning the objects to geomorphological classes, but also spatial and topological properties can be exploited. In this study we focus on the detection of landforms, especially bedrock sediment deposits (alluvion, debris cone, talus, moraine, rockglacier), as well as glaciers. The study site Gradental [N 46°58'29.1"/ E 12°48'53.8"] is located in the Schobergruppe (Austria, Carinthia) and is characterised by heterogenic geology conditions and high process activity. The area is difficult to access and dominated by steep slopes, thus hindering a fast and detailed geomorphological field mapping. Landforms are identified using aerial and terrestrial LiDAR data (1 m spatial resolution). These DEMs are analysed by an object based hierarchical approach, which is structured in three main steps. The first step is to define occurring landforms by basic land surface parameters (LSPs), topology and hierarchy relations. Based on those definitions a semantic model is created. Secondly, a multi-scale segmentation is performed on a three-band LSP that integrates slope, aspect and plan curvature, which expresses the driving forces of geomorphological processes. In the third step, the generated multi-level object structures are classified in order to produce the geomorphological map. The classification rules are derived from the semantic model. Due to landform type-specific scale dependencies of LSPs, the values of LSPs used in the classification are calculated in a multi-scale manner by constantly enlarging the size of the moving window. In addition, object form properties (density, compactness, rectangular fit) are utilised as additional information for landform characterisation. Validation of classification is performed by intersecting a visually interpreted reference map with the classification output map and calculating accuracy matrices. Validation shows an overall accuracy of 78.25 % and a Kappa of 0.65. The natural borders of landforms can be easily detected by the use of slope, aspect and plan curvature. This study illustrates the potential of OBIA for a more standardised and automated mapping of surface units (landforms, landcover). Therefore, the presented methodology features a prospective automated geomorphological mapping approach for alpine regions.

Assessment of Data Fusion Algorithms for Earth Observation Change Detection Processes

PubMed Central

Molina, Iñigo; Martinez, Estibaliz; Morillo, Carmen; Velasco, Jesus; Jara, Alvaro

2016-01-01

In this work a parametric multi-sensor Bayesian data fusion approach and a Support Vector Machine (SVM) are used for a Change Detection problem. For this purpose two sets of SPOT5-PAN images have been used, which are in turn used for Change Detection Indices (CDIs) calculation. For minimizing radiometric differences, a methodology based on zonal “invariant features” is suggested. The choice of one or the other CDI for a change detection process is a subjective task as each CDI is probably more or less sensitive to certain types of changes. Likewise, this idea might be employed to create and improve a “change map”, which can be accomplished by means of the CDI’s informational content. For this purpose, information metrics such as the Shannon Entropy and “Specific Information” have been used to weight the changes and no-changes categories contained in a certain CDI and thus introduced in the Bayesian information fusion algorithm. Furthermore, the parameters of the probability density functions (pdf’s) that best fit the involved categories have also been estimated. Conversely, these considerations are not necessary for mapping procedures based on the discriminant functions of a SVM. This work has confirmed the capabilities of probabilistic information fusion procedure under these circumstances. PMID:27706048

Sensitive and specific detection of viable Mycobacterium avium subsp. paratuberculosis in raw milk by the peptide-mediated magnetic separation-phage assay.

PubMed

Foddai, A C G; Grant, I R

2017-05-01

To validate an optimized peptide-mediated magnetic separation (PMS)-phage assay for detection of viable Mycobacterium avium subsp. paratuberculosis (MAP) in milk. Inclusivity, specificity and limit of detection 50% (LOD 50 ) of the optimized PMS-phage assay were assessed. Plaques were obtained for all 43 MAP strains tested. Of 12 other Mycobacterium sp. tested, only Mycobacterium bovis BCG produced small numbers of plaques. LOD 50 of the PMS-phage assay was 0·93 MAP cells per 50 ml milk, which was better than both PMS-qPCR and PMS-culture. When individual milks (n = 146) and bulk tank milk (BTM, n = 22) obtained from Johne's affected herds were tested by the PMS-phage assay, viable MAP were detected in 31 (21·2%) of 146 individual milks and 13 (59·1%) of 22 BTM, with MAP numbers detected ranging from 6-948 plaque-forming-units per 50 ml milk. PMS-qPCR and PMS-MGIT culture proved to be less sensitive tests than the PMS-phage assay. The optimized PMS-phage assay is the most sensitive and specific method available for the detection of viable MAP in milk. Further work is needed to streamline the PMS-phage assay, because the assay's multistep format currently makes it unsuitable for adoption by the dairy industry as a screening test. The inclusivity (ability to detect all MAP strains), specificity (ability to detect only MAP) and detection sensitivity (ability to detect low numbers of MAP) of the optimized PMS-phage assay have been comprehensively demonstrated for the first time. © 2017 The Society for Applied Microbiology.

Monitoring watersheds and streams

Treesearch

Robert R. Ziemer

1998-01-01

Regulations increasingly require monitoring to detect changes caused by land management activities. Successful monitoring requires that objectives be clearly stated. Once objectives are clearly identified, it is important to map out all of the components and links that might affect the issues of concern. For each issue and each component that affects that issue, there...

A Critique of Patch-Based Landscape Indicators for Detection of Temporal Change in Fragmentation

EPA Science Inventory

Since O’Neill et al. (1988), analysis of landscape indicators based on measurements from land-cover maps has been a core area of research in landscape ecology. Landscape indicator research has focused on development of new measurements, statistical properties, and indictor behav...

Ice sheet topography by satellite altimetry

USGS Publications Warehouse

Brooks, R.L.; Campbell, W.J.; Ramseier, R.O.; Stanley, H.R.; Zwally, H.J.

1978-01-01

The surface elevation of the southern Greenland ice sheet and surface features of the ice flow are obtained from the radar altimeter on the GEOS 3 satellite. The achieved accuracy in surface elevation is ???2 m. As changes in surface elevation are indicative of changes in ice volume, the mass balance of the present ice sheets could be determined by repetitive mapping of the surface elevation and the surface could be monitored to detect surging or significant changes in ice flow. ?? 1978 Nature Publishing Group.

Fast Drawing of Traffic Sign Using Mobile Mapping System

NASA Astrophysics Data System (ADS)

Yao, Q.; Tan, B.; Huang, Y.

2016-06-01

Traffic sign provides road users with the specified instruction and information to enhance traffic safety. Automatic detection of traffic sign is important for navigation, autonomous driving, transportation asset management, etc. With the advance of laser and imaging sensors, Mobile Mapping System (MMS) becomes widely used in transportation agencies to map the transportation infrastructure. Although many algorithms of traffic sign detection are developed in the literature, they are still a tradeoff between the detection speed and accuracy, especially for the large-scale mobile mapping of both the rural and urban roads. This paper is motivated to efficiently survey traffic signs while mapping the road network and the roadside landscape. Inspired by the manual delineation of traffic sign, a drawing strategy is proposed to quickly approximate the boundary of traffic sign. Both the shape and color prior of the traffic sign are simultaneously involved during the drawing process. The most common speed-limit sign circle and the statistic color model of traffic sign are studied in this paper. Anchor points of traffic sign edge are located with the local maxima of color and gradient difference. Starting with the anchor points, contour of traffic sign is drawn smartly along the most significant direction of color and intensity consistency. The drawing process is also constrained by the curvature feature of the traffic sign circle. The drawing of linear growth is discarded immediately if it fails to form an arc over some steps. The Kalman filter principle is adopted to predict the temporal context of traffic sign. Based on the estimated point,we can predict and double check the traffic sign in consecutive frames.The event probability of having a traffic sign over the consecutive observations is compared with the null hypothesis of no perceptible traffic sign. The temporally salient traffic sign is then detected statistically and automatically as the rare event of having a traffic sign.The proposed algorithm is tested with a diverse set of images that are taken inWuhan, China with theMMS ofWuhan University. Experimental results demonstrate that the proposed algorithm can detect traffic signs at the rate of over 80% in around 10 milliseconds. It is promising for the large-scale traffic sign survey and change detection using the mobile mapping system.

Detection of seagrass beds in Khunk Graben Bay, Thailand, using ALOS AVNI2 image

NASA Astrophysics Data System (ADS)

Komatsu, Teruhisa; Noiraksar, Thidarat; Sakamoto, Shingo X.; Sawayama, Shuhei; Miyamoto, Hiroomi; Phauk, Sophany; Thongdee, Pornthep; Jualaong, Suthep; Nishida, Shuhei

2012-11-01

Coastal habitats having high productivity provide numerous ecological services such as foods, protection from strong waves through buffering effect, fixation of CO2 through photosynthesis, fostering biodiversity etc. However, increasing human impacts and climate change decrease or degrade coastal habitats. ASEAN region is developing most rapidly in the world. In the developing region, it is necessary to grasp present spatial distributions of habitats as a baseline data with standardized mapping methods. Remote sensing is one of the most effective methods for mapping. Japan Aerospace Exploration Agency (JAXA) provides non-commercial satellite images with ultra-high spatial resolution optical sensors (10 m), AVNIR2, similar to LANDSAT TM. Using ALOS AVNIR2 images it may be possible to make habitat map in the region. In Thailand, shrimp ponds cause degradation of coastal ecosystem through cutting mangroves and eutrophicated discharge from ponds. We examined capability of remote sesing with ALOS AVNIR2 to map seagrass beds in Khung Kraben Bay, Chanthaburi Province, Thailand, surrounded by shrimp ponds. We analyzed ALOS AVNIR2 taken on 25 January 2008. Ground truth survey was conducted in October 2010 using side scan sonar and scuba diving. The survey revealed that there were broad seagrass beds consisting of Enhalus acroides. We used a decision tree to detect seagrass beds in the bay with quite turbid seawater coupled with Depth-Invariant Index proposed by Lyzenga (1985) and bottom reflectances. We could succeed to detect seagrass beds. Thus it is concluded that ALOS AVNIR2 is practical to map seagrass beds in this region.

Earthquake Damage Assessment over Port-au-Prince (Haiti) by Fusing Optical and SAR Data

NASA Astrophysics Data System (ADS)

Romaniello, V.; Piscini, A.; Bignami, C.; Anniballe, R.; Pierdicca, N.; Stramondo, S.

2016-08-01

This work proposes methodologies aiming at evaluating the sensitivity of optical and SAR change features obtained from satellite images with respect to the damage grade. The proposed methods are derived from the literature ([1], [2], [3], [4]) and the main novelty concerns the estimation of these change features at object scale.The test case is the Mw 7.0 earthquake that hit Haiti on January 12, 2010.The analysis of change detection indicators is based on ground truth information collected during a post- earthquake survey. We have generated the damage map of Port-au-Prince by considering a set of polygons extracted from the open source Open Street Map geo- database. The resulting damage map was calculated in terms of collapse ratio [5].We selected some features having a good sensitivity with damage at object scale [6]: the Normalised Difference Index, the Kullback-Libler Divergence, the Mutual Information and the Intensity Correlation Difference.The Naive Bayes and the Support Vector Machine classifiers were used to evaluate the goodness of these features. The classification results demonstrate that the simultaneous use of several change features from EO observations can improve the damage estimation at object scale.

Glacier Changes in the Nanga Parbat Region, NW Himalaya: A longitudinal study over 160 years (1856-2016)

NASA Astrophysics Data System (ADS)

Nüsser, Marcus; Schmidt, Susanne

2017-04-01

Against the background of the prominent Himalayan glacier debate of the past decade, global concerns were raised about the severe consequences of detected and expected changes in the South Asian cryosphere. Due to the lack of historical glaciological data in the Himalayan region, studies of glacier changes over long time periods are rare. The present study seeks to analyze and quantify glacier changes in the Nanga Parbat region between 1856 and 2016. Due to the steep topography and great vertical span, the debris-covered glaciers of the mountain massif are largely fed by avalanches of different size. This impact of snow and ice re-distribution by avalanches is often neglected in glacier mass-balances. Therefore, an integrated approach was used to investigate the glacier changes and the impact of avalanches. This approach includes (1) a re-photographic survey with images from several expeditions between 1934 and 2010, (2) mapping during own field surveys between 1992 and 2010, as well as (3) the analyses of remote sensing data (Corona, QuickBird, KompSat, Landsat, etc. and DEM) and (4) historical topographic maps. The re-photographic survey allows for direct comparisons and illustrates glacier changes over a span of seventy years. Changes of glacier lengths were quantified by using remote sensing data and the topographic map of 1934. In order to calculate glacier surface changes, a digital elevation model (DEM) with a spatial resolution of 30 x 30 m2 was derived from the digitized contour lines of the topographic map from 1934 and compared to SRTM-DEM (30 x 30 m2) and ALOS-DSM. Based on remote sensing time-series, avalanche deposits on glaciers were mapped in order to identify their magnitude and frequencies. To calculate the potential glacier catchment, area of steep rock walls and the ratio between accumulation and ablation zones were calculated for each glacier basin. Our field based investigations show that the glaciers in the Rupal Valley are characterized by small retreating rates since 1856, when Adolph Schlagintweit mapped them for the first time; others such as the Raikot Glacier on the northern side of the Nanga Parbat are fluctuating since 1934.

LANDSAT data for coastal zone management. [New Jersey

NASA Technical Reports Server (NTRS)

Mckenzie, S.

1981-01-01

The lack of adequate, current data on land and water surface conditions in New Jersey led to the search for better data collections and analysis techniques. Four-channel MSS data of Cape May County and access to the OSER computer interpretation system were provided by NASA. The spectral resolution of the data was tested and a surface cover map was produced by going through the steps of supervised classification. Topics covered include classification; change detection and improvement of spectral and spatial resolution; merging LANDSAT and map data; and potential applications for New Jersey.

First experience with Remote Sensing methods and selected sensors in the monitoring of mining areas - a case study of the Belchatow open cast mine

NASA Astrophysics Data System (ADS)

Wajs, Jaroslaw

2018-01-01

The paper presents satellite imagery from active SENTINEL-1A and passive SENTINEL-2A/2B sensors for their application in the monitoring of mining areas focused on detecting land changes. Multispectral scenes of SENTINEL-2A/2B have allowed for detecting changes in land-cover near the region of interest (ROI), i.e. the Szczercow dumping site in the Belchatow open cast lignite mine, central Poland, Europe. Scenes from SENTINEL-1A/1B satellite have also been used in the research. Processing of the SLC signal enabled creating a return intensity map in VV polarization. The obtained SAR scene was reclassified and shows a strong return signal from the dumping site and the open pit. This fact may be used in detection and monitoring of changes occurring within the analysed engineering objects.

Short communication: Passive shedding of Mycobacterium avium ssp. paratuberculosis in commercial dairy goats in Brazil.

PubMed

Schwarz, D G G; Lima, M C; Barros, M; Valente, F L; Scatamburlo, T M; Rosado, N; Oliveira, C T S A M; Oliveira, L L; Moreira, M A S

2017-10-01

Goat farming is a low-cost alternative to dairy production in developing countries. In Brazil, goat production has increased in recent years due in part to the implementation of programs encouraging this activity. Mycobacterium avium ssp. paratuberculosis (MAP) is the causative agent of paratuberculosis, a disease that causes chronic granulomatous enteritis in ruminants, but MAP transmission dynamics are still poorly understood in goats. In a previously published study of our research group, 10 dairy goat farms (467 animals) from Minas Gerais state were analyzed for MAP detection; 2 fecal cultures and 11 milk samples tested positive for MAP by conventional PCR and were confirmed by sequencing. Because no clinical signs were observed over 1 yr of monitoring, we hypothesized that these MAP-positive goats could be passive shedders. Thus, in the present study, 4 positive goats (4/13) from the previous study were purchased and feces and milk samples were collected for evaluation (twice, with an interval of 3 mo between tests) by culture of MAP, IS900 PCR, or both. All analyses were negative for MAP. At the last time point, blood samples were collected for ELISA, the animals were killed, and tissues collected for tissue culture and histopathology. At necropsy, no macroscopic lesions related to paratuberculosis were observed. Similarly, no histological changes were observed and MAP in samples stained by Ziehl-Neelsen was not detected. These animals were characterized as potential passive shedders with upward contamination of the teat canal by MAP. This is the first report of the passive shedding phenomenon in goats in Brazil and it highlights the importance of identifying these animals for control programs and to ensure the quality of dairy products. Copyright © 2017 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

QSL Squasher: A Fast Quasi-separatrix Layer Map Calculator

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

Tassev, Svetlin; Savcheva, Antonia, E-mail: svetlin.tassev@cfa.harvard.edu

Quasi-Separatrix Layers (QSLs) are a useful proxy for the locations where current sheets can develop in the solar corona, and give valuable information about the connectivity in complicated magnetic field configurations. However, calculating QSL maps, even for two-dimensional slices through three-dimensional models of coronal magnetic fields, is a non-trivial task, as it usually involves tracing out millions of magnetic field lines with immense precision. Thus, extending QSL calculations to three dimensions has rarely been done until now. In order to address this challenge, we present QSL Squasher—a public, open-source code, which is optimized for calculating QSL maps in both twomore » and three dimensions on graphics processing units. The code achieves large processing speeds for three reasons, each of which results in an order-of-magnitude speed-up. (1) The code is parallelized using OpenCL. (2) The precision requirements for the QSL calculation are drastically reduced by using perturbation theory. (3) A new boundary detection criterion between quasi-connectivity domains is used, which quickly identifies possible QSL locations that need to be finely sampled by the code. That boundary detection criterion relies on finding the locations of abrupt field-line length changes, which we do by introducing a new Field-line Length Edge (FLEDGE) map. We find FLEDGE maps useful on their own as a quick-and-dirty substitute for QSL maps. QSL Squasher allows construction of high-resolution 3D FLEDGE maps in a matter of minutes, which is two orders of magnitude faster than calculating the corresponding 3D QSL maps. We include a sample of calculations done using QSL Squasher to demonstrate its capabilities as a QSL calculator, as well as to compare QSL and FLEDGE maps.« less

QSL Squasher: A Fast Quasi-separatrix Layer Map Calculator

NASA Astrophysics Data System (ADS)

Tassev, Svetlin; Savcheva, Antonia

2017-05-01

Quasi-Separatrix Layers (QSLs) are a useful proxy for the locations where current sheets can develop in the solar corona, and give valuable information about the connectivity in complicated magnetic field configurations. However, calculating QSL maps, even for two-dimensional slices through three-dimensional models of coronal magnetic fields, is a non-trivial task, as it usually involves tracing out millions of magnetic field lines with immense precision. Thus, extending QSL calculations to three dimensions has rarely been done until now. In order to address this challenge, we present QSL Squasher—a public, open-source code, which is optimized for calculating QSL maps in both two and three dimensions on graphics processing units. The code achieves large processing speeds for three reasons, each of which results in an order-of-magnitude speed-up. (1) The code is parallelized using OpenCL. (2) The precision requirements for the QSL calculation are drastically reduced by using perturbation theory. (3) A new boundary detection criterion between quasi-connectivity domains is used, which quickly identifies possible QSL locations that need to be finely sampled by the code. That boundary detection criterion relies on finding the locations of abrupt field-line length changes, which we do by introducing a new Field-line Length Edge (FLEDGE) map. We find FLEDGE maps useful on their own as a quick-and-dirty substitute for QSL maps. QSL Squasher allows construction of high-resolution 3D FLEDGE maps in a matter of minutes, which is two orders of magnitude faster than calculating the corresponding 3D QSL maps. We include a sample of calculations done using QSL Squasher to demonstrate its capabilities as a QSL calculator, as well as to compare QSL and FLEDGE maps.

Detection and Identification of the Vibrational Markers for the Quantification of Methionine Oxidation in Therapeutic Proteins.

PubMed

Balakrishnan, Gurusamy; Barnett, Gregory V; Kar, Sambit R; Das, Tapan K

2018-05-17

Methionine oxidation is a major degradation pathway in therapeutic proteins which can impact the structure and function of proteins as well as risk to drug product quality. Detecting Met oxidation in proteins by peptide mapping followed by liquid chromatography with mass spectrometry (LC-MS) is the industry standard but is also labor intensive and susceptible to artifacts. In this work, vibrational difference spectroscopy in combination with 18 O isotopic shift enabled us to demonstrate the application of Raman and FTIR techniques for the detection and quantification of Met oxidation in various therapeutic proteins, including mAbs, fusion proteins, and antibody drug conjugate. Vibrational markers of Met oxidation products, such as sulfoxide and sulfone, corresponding to S═O and C-S═O stretching frequencies were unequivocally identified based 18 O isotoptic shifts. The intensity of the isolated νC-S Raman band at 702 cm -1 was successfully applied to quantify the average Met oxidation level in multiple proteins. These results are further corroborated by oxidation levels measured by tryptic peptide mapping, and thus the confirmed Met oxidation levels derived from Raman and mass spectrometry are indeed consistent with each other. Thus, we demonstrate the broader application of vibrational spectroscopy to detect the subtle spectral changes associated with various chemical or physical degradation of proteins, including Met oxidation as well as higher order structural changes.

Saliency detection using mutual consistency-guided spatial cues combination

NASA Astrophysics Data System (ADS)

Wang, Xin; Ning, Chen; Xu, Lizhong

2015-09-01

Saliency detection has received extensive interests due to its remarkable contribution to wide computer vision and pattern recognition applications. However, most existing computational models are designed for detecting saliency in visible images or videos. When applied to infrared images, they may suffer from limitations in saliency detection accuracy and robustness. In this paper, we propose a novel algorithm to detect visual saliency in infrared images by mutual consistency-guided spatial cues combination. First, based on the luminance contrast and contour characteristics of infrared images, two effective saliency maps, i.e., the luminance contrast saliency map and contour saliency map are constructed, respectively. Afterwards, an adaptive combination scheme guided by mutual consistency is exploited to integrate these two maps to generate the spatial saliency map. This idea is motivated by the observation that different maps are actually related to each other and the fusion scheme should present a logically consistent view of these maps. Finally, an enhancement technique is adopted to incorporate spatial saliency maps at various scales into a unified multi-scale framework to improve the reliability of the final saliency map. Comprehensive evaluations on real-life infrared images and comparisons with many state-of-the-art saliency models demonstrate the effectiveness and superiority of the proposed method for saliency detection in infrared images.

Mycobacterium avium subspecies paratuberculosis in bioaerosols after depopulation and cleaning of two cattle barns.

PubMed

Eisenberg, S; Nielen, M; Hoeboer, J; Bouman, M; Heederik, D; Koets, A

2011-06-04

Settled dust samples were collected on a commercial dairy farm in the Netherlands with a high prevalence of Mycobacterium avium subspecies paratuberculosis (MAP) (barn A) and on a Dutch experimental cattle farm (barn B) stocked with cattle confirmed to be MAP shedders. Barns were sampled while animals were present, after both barns were destocked and cleaned by cold high-pressure cleaning, and after being kept empty for two weeks (barn A) or after additional disinfection (barn B). MAP DNA was detected by IS900 real-time PCR and viable MAP were detected by liquid culture. MAP DNA was detected in 78 per cent of samples from barn A and 86 per cent of samples from barn B collected while animals were still present. Viable MAP was detected in six of nine samples from barn A and in three of seven samples from barn B. After cold high-pressure cleaning, viable MAP could be detected in only two samples from each barn. After leaving barn A empty for two weeks, and following additional disinfection of barn B, no viable MAP could be detected in any settled dust sample.

Geodynamics and temporal variations in the gravity field

NASA Technical Reports Server (NTRS)

Mcadoo, D. C.; Wagner, C. A.

1989-01-01

Just as the Earth's surface deforms tectonically, so too does the gravity field evolve with time. Now that precise geodesy is yielding observations of these deformations it is important that concomitant, temporal changes in the gravity field be monitored. Although these temporal changes are minute they are observable: changes in the J2 component of the gravity field were inferred from satellite (LAGEOS) tracking data; changes in other components of the gravity field would likely be detected by Geopotential Research Mission (GRM), a proposed but unapproved NASA gravity field mission. Satellite gradiometers were also proposed for high-precision gravity field mapping. Using simple models of geodynamic processes such as viscous postglacial rebound of the solid Earth, great subduction zone earthquakes and seasonal glacial mass fluctuations, we predict temporal changes in gravity gradients at spacecraft altitudes. It was found that these proposed gravity gradient satellite missions should have sensitivities equal to or better than 10(exp -4) E in order to reliably detect these changes. It was also found that satellite altimetry yields little promise of useful detection of time variations in gravity.

Change in land use in the Phoenix (1:250,000) Quadrangle, Arizona between 1970 and 1972: Successful use of proposed land use classification system

NASA Technical Reports Server (NTRS)

Place, J. L.

1973-01-01

Changes in land use in the Phoenix (1:250,000 scale) Quadrangle in Arizona have been mapped using only the images from ERTS-1, tending to verify the utility of a land use classification system proposed for use with ERTS images. The period of change investigated was from November 1970 to late summer or early fall, 1972. Seasonal changes also were studied using successive ERTS images. Types of equipment used to aid interpretation included a color additive viewer, a twenty-power magnifier, a density slicer, and a diazo copy machine for making ERTS color composites in hard copy. Types of changes detected have been: (1) cropland or rangeland developed for new residential areas; (2) rangeland converted to new cropland; and (3) possibly new areas of industrial or commercial development. A map of land use previously compiled from air photos was updated in this manner.

Continuous Change Detection and Classification (CCDC) of Land Cover Using All Available Landsat Data

NASA Astrophysics Data System (ADS)

Zhu, Z.; Woodcock, C. E.

2012-12-01

A new algorithm for Continuous Change Detection and Classification (CCDC) of land cover using all available Landsat data is developed. This new algorithm is capable of detecting many kinds of land cover change as new images are collected and at the same time provide land cover maps for any given time. To better identify land cover change, a two step cloud, cloud shadow, and snow masking algorithm is used for eliminating "noisy" observations. Next, a time series model that has components of seasonality, trend, and break estimates the surface reflectance and temperature. The time series model is updated continuously with newly acquired observations. Due to the high variability in spectral response for different kinds of land cover change, the CCDC algorithm uses a data-driven threshold derived from all seven Landsat bands. When the difference between observed and predicted exceeds the thresholds three consecutive times, a pixel is identified as land cover change. Land cover classification is done after change detection. Coefficients from the time series models and the Root Mean Square Error (RMSE) from model fitting are used as classification inputs for the Random Forest Classifier (RFC). We applied this new algorithm for one Landsat scene (Path 12 Row 31) that includes all of Rhode Island as well as much of Eastern Massachusetts and parts of Connecticut. A total of 532 Landsat images acquired between 1982 and 2011 were processed. During this period, 619,924 pixels were detected to change once (91% of total changed pixels) and 60,199 pixels were detected to change twice (8% of total changed pixels). The most frequent land cover change category is from mixed forest to low density residential which occupies more than 8% of total land cover change pixels.

A landsat data tiling and compositing approach optimized for change detection in the conterminous United States

USGS Publications Warehouse

Nelson, Kurtis; Steinwand, Daniel R.

2015-01-01

Annual disturbance maps are produced by the LANDFIRE program across the conterminous United States (CONUS). Existing LANDFIRE disturbance data from 1999 to 2010 are available and current efforts will produce disturbance data through 2012. A tiling and compositing approach was developed to produce bi-annual images optimized for change detection. A tiled grid of 10,000 × 10,000 30 m pixels was defined for CONUS and adjusted to consolidate smaller tiles along national borders, resulting in 98 non-overlapping tiles. Data from Landsat-5,-7, and -8 were re-projected to the tile extents, masked to remove clouds, shadows, water, and snow/ice, then composited using a cosine similarity approach. The resultant images were used in a change detection algorithm to determine areas of vegetation change. This approach enabled more efficient processing compared to using single Landsat scenes, by taking advantage of overlap between adjacent paths, and allowed an automated system to be developed for the entire process.

Change Detection of Remote Sensing Images by Dt-Cwt and Mrf

NASA Astrophysics Data System (ADS)

Ouyang, S.; Fan, K.; Wang, H.; Wang, Z.

2017-05-01

Aiming at the significant loss of high frequency information during reducing noise and the pixel independence in change detection of multi-scale remote sensing image, an unsupervised algorithm is proposed based on the combination between Dual-tree Complex Wavelet Transform (DT-CWT) and Markov random Field (MRF) model. This method first performs multi-scale decomposition for the difference image by the DT-CWT and extracts the change characteristics in high-frequency regions by using a MRF-based segmentation algorithm. Then our method estimates the final maximum a posterior (MAP) according to the segmentation algorithm of iterative condition model (ICM) based on fuzzy c-means(FCM) after reconstructing the high-frequency and low-frequency sub-bands of each layer respectively. Finally, the method fuses the above segmentation results of each layer by using the fusion rule proposed to obtain the mask of the final change detection result. The results of experiment prove that the method proposed is of a higher precision and of predominant robustness properties.

Multi-parametric monitoring and assessment of high-intensity focused ultrasound (HIFU) boiling by harmonic motion imaging for focused ultrasound (HMIFU): an ex vivo feasibility study

NASA Astrophysics Data System (ADS)

Hou, Gary Y.; Marquet, Fabrice; Wang, Shutao; Konofagou, Elisa E.

2014-03-01

Harmonic motion imaging for focused ultrasound (HMIFU) is a recently developed high-intensity focused ultrasound (HIFU) treatment monitoring method with feasibilities demonstrated in vitro and in vivo. Here, a multi-parametric study is performed to investigate both elastic and acoustics-independent viscoelastic tissue changes using the Harmonic Motion Imaging (HMI) displacement, axial compressive strain and change in relative phase shift during high energy HIFU treatment with tissue boiling. Forty three (n = 43) thermal lesions were formed in ex vivo canine liver specimens (n = 28). Two-dimensional (2D) transverse HMI displacement maps were also obtained before and after lesion formation. The same method was repeated in 10 s, 20 s and 30 s HIFU durations at three different acoustic powers of 8, 10, and 11 W, which were selected and verified as treatment parameters capable of inducing boiling using both thermocouple and passive cavitation detection (PCD) measurements. Although a steady decrease in the displacement, compressive strain, and relative change in the focal phase shift (Δϕ) were obtained in numerous cases, indicating an overall increase in relative stiffness, the study outcomes also showed that during boiling, a reverse lesion-to-background displacement contrast was detected, indicating potential change in tissue absorption, geometrical change and/or, mechanical gelatification or pulverization. Following treatment, corresponding 2D HMI displacement images of the thermal lesions also mapped consistent discrepancy in the lesion-to-background displacement contrast. Despite the expectedly chaotic changes in acoustic properties with boiling, the relative change in phase shift showed a consistent decrease, indicating its robustness to monitor biomechanical properties independent of the acoustic property changes throughout the HIFU treatment. In addition, the 2D HMI displacement images confirmed and indicated the increase in the thermal lesion size with treatment duration, which was validated against pathology. In conclusion, multi-parametric HMIFU was shown capable of monitoring and mapping tissue viscoelastic response changes during and after HIFU boiling, some of which were independent of the acoustic parameter changes.

Multi-parametric monitoring and assessment of High Intensity Focused Ultrasound (HIFU) boiling by Harmonic Motion Imaging for Focused Ultrasound (HMIFU): An ex vivo feasibility study

PubMed Central

Hou, Gary Y.; Marquet, Fabrice; Wang, Shutao; Konofagou, Elisa E.

2014-01-01

Harmonic Motion Imaging for Focused Ultrasound (HMIFU) is a recently developed high-intensity focused ultrasound (HIFU) treatment monitoring method with feasibilities demonstrated in vitro and in vivo. Here, a multi-parametric study is performed to investigate both elastic and acoustics-independent viscoelastic tissue changes using the Harmonic Motion Imaging (HMI) displacement, axial compressive strain and change in relative phase-shift during high energy HIFU treatment with tissue boiling. Forty three (n=43) thermal lesions were formed in ex vivo canine liver specimens (n=28). Two dimensional (2D) transverse HMI displacement maps were also obtained before and after lesion formation. The same method was repeated in 10-s, 20-s and 30-s HIFU durations at three different acoustic powers of 8, 10, and 11W, which were selected and verified as treatment parameters capable of inducing boiling using both thermocouple and Passive Cavitation Detection (PCD) measurements. Although a steady decrease in the displacement, compressive strain, and relative change in the focal phase shift (Δφ) were obtained in numerous cases, indicating an overall increase in relative stiffness, the study outcomes also showed that during boiling, a reverse lesion-to-background displacement contrast was detected, indicating potential change in tissue absorption, geometrical change and/or, mechanical gelatification or pulverization. Following treatment, corresponding 2D HMI displacement images of the thermal lesions also mapped consistent discrepancy in the lesion-to-background displacement contrast. Despite unpredictable changes in acoustic properties with boiling, the relative change in phase shift showed a consistent decrease, indicating its robustness to monitor biomechanical properties independent of the acoustic property change throughout the HIFU treatment. In addition, the 2D HMI displacement images confirmed and indicated the increase in the thermal lesion size with treatment duration, which was validated against pathology. In conclusion, multi-parametric HMIFU was shown capable of monitoring and mapping tissue viscoelastic response changes during and after HIFU boiling, some of which were independent of the acoustic parameter changes. PMID:24556974

Multi-parametric monitoring and assessment of high-intensity focused ultrasound (HIFU) boiling by harmonic motion imaging for focused ultrasound (HMIFU): an ex vivo feasibility study.

PubMed

Hou, Gary Y; Marquet, Fabrice; Wang, Shutao; Konofagou, Elisa E

2014-03-07

Harmonic motion imaging for focused ultrasound (HMIFU) is a recently developed high-intensity focused ultrasound (HIFU) treatment monitoring method with feasibilities demonstrated in vitro and in vivo. Here, a multi-parametric study is performed to investigate both elastic and acoustics-independent viscoelastic tissue changes using the Harmonic Motion Imaging (HMI) displacement, axial compressive strain and change in relative phase shift during high energy HIFU treatment with tissue boiling. Forty three (n = 43) thermal lesions were formed in ex vivo canine liver specimens (n = 28). Two-dimensional (2D) transverse HMI displacement maps were also obtained before and after lesion formation. The same method was repeated in 10 s, 20 s and 30 s HIFU durations at three different acoustic powers of 8, 10, and 11 W, which were selected and verified as treatment parameters capable of inducing boiling using both thermocouple and passive cavitation detection (PCD) measurements. Although a steady decrease in the displacement, compressive strain, and relative change in the focal phase shift (Δϕ) were obtained in numerous cases, indicating an overall increase in relative stiffness, the study outcomes also showed that during boiling, a reverse lesion-to-background displacement contrast was detected, indicating potential change in tissue absorption, geometrical change and/or, mechanical gelatification or pulverization. Following treatment, corresponding 2D HMI displacement images of the thermal lesions also mapped consistent discrepancy in the lesion-to-background displacement contrast. Despite the expectedly chaotic changes in acoustic properties with boiling, the relative change in phase shift showed a consistent decrease, indicating its robustness to monitor biomechanical properties independent of the acoustic property changes throughout the HIFU treatment. In addition, the 2D HMI displacement images confirmed and indicated the increase in the thermal lesion size with treatment duration, which was validated against pathology. In conclusion, multi-parametric HMIFU was shown capable of monitoring and mapping tissue viscoelastic response changes during and after HIFU boiling, some of which were independent of the acoustic parameter changes.

A new automatic synthetic aperture radar-based flood mapping application hosted on the European Space Agency's Grid Processing of Demand Fast Access to Imagery environment

NASA Astrophysics Data System (ADS)

Matgen, Patrick; Giustarini, Laura; Hostache, Renaud

2012-10-01

This paper introduces an automatic flood mapping application that is hosted on the Grid Processing on Demand (GPOD) Fast Access to Imagery (Faire) environment of the European Space Agency. The main objective of the online application is to deliver operationally flooded areas using both recent and historical acquisitions of SAR data. Having as a short-term target the flooding-related exploitation of data generated by the upcoming ESA SENTINEL-1 SAR mission, the flood mapping application consists of two building blocks: i) a set of query tools for selecting the "crisis image" and the optimal corresponding "reference image" from the G-POD archive and ii) an algorithm for extracting flooded areas via change detection using the previously selected "crisis image" and "reference image". Stakeholders in flood management and service providers are able to log onto the flood mapping application to get support for the retrieval, from the rolling archive, of the most appropriate reference image. Potential users will also be able to apply the implemented flood delineation algorithm. The latter combines histogram thresholding, region growing and change detection as an approach enabling the automatic, objective and reliable flood extent extraction from SAR images. Both algorithms are computationally efficient and operate with minimum data requirements. The case study of the high magnitude flooding event that occurred in July 2007 on the Severn River, UK, and that was observed with a moderateresolution SAR sensor as well as airborne photography highlights the performance of the proposed online application. The flood mapping application on G-POD can be used sporadically, i.e. whenever a major flood event occurs and there is a demand for SAR-based flood extent maps. In the long term, a potential extension of the application could consist in systematically extracting flooded areas from all SAR images acquired on a daily, weekly or monthly basis.

Automatically Detecting Failures in Natural Language Processing Tools for Online Community Text.

PubMed

Park, Albert; Hartzler, Andrea L; Huh, Jina; McDonald, David W; Pratt, Wanda

2015-08-31

The prevalence and value of patient-generated health text are increasing, but processing such text remains problematic. Although existing biomedical natural language processing (NLP) tools are appealing, most were developed to process clinician- or researcher-generated text, such as clinical notes or journal articles. In addition to being constructed for different types of text, other challenges of using existing NLP include constantly changing technologies, source vocabularies, and characteristics of text. These continuously evolving challenges warrant the need for applying low-cost systematic assessment. However, the primarily accepted evaluation method in NLP, manual annotation, requires tremendous effort and time. The primary objective of this study is to explore an alternative approach-using low-cost, automated methods to detect failures (eg, incorrect boundaries, missed terms, mismapped concepts) when processing patient-generated text with existing biomedical NLP tools. We first characterize common failures that NLP tools can make in processing online community text. We then demonstrate the feasibility of our automated approach in detecting these common failures using one of the most popular biomedical NLP tools, MetaMap. Using 9657 posts from an online cancer community, we explored our automated failure detection approach in two steps: (1) to characterize the failure types, we first manually reviewed MetaMap's commonly occurring failures, grouped the inaccurate mappings into failure types, and then identified causes of the failures through iterative rounds of manual review using open coding, and (2) to automatically detect these failure types, we then explored combinations of existing NLP techniques and dictionary-based matching for each failure cause. Finally, we manually evaluated the automatically detected failures. From our manual review, we characterized three types of failure: (1) boundary failures, (2) missed term failures, and (3) word ambiguity failures. Within these three failure types, we discovered 12 causes of inaccurate mappings of concepts. We used automated methods to detect almost half of 383,572 MetaMap's mappings as problematic. Word sense ambiguity failure was the most widely occurring, comprising 82.22% of failures. Boundary failure was the second most frequent, amounting to 15.90% of failures, while missed term failures were the least common, making up 1.88% of failures. The automated failure detection achieved precision, recall, accuracy, and F1 score of 83.00%, 92.57%, 88.17%, and 87.52%, respectively. We illustrate the challenges of processing patient-generated online health community text and characterize failures of NLP tools on this patient-generated health text, demonstrating the feasibility of our low-cost approach to automatically detect those failures. Our approach shows the potential for scalable and effective solutions to automatically assess the constantly evolving NLP tools and source vocabularies to process patient-generated text.

A Hopfield neural network for image change detection.

PubMed

Pajares, Gonzalo

2006-09-01

This paper outlines an optimization relaxation approach based on the analog Hopfield neural network (HNN) for solving the image change detection problem between two images. A difference image is obtained by subtracting pixel by pixel both images. The network topology is built so that each pixel in the difference image is a node in the network. Each node is characterized by its state, which determines if a pixel has changed. An energy function is derived, so that the network converges to stable states. The analog Hopfield's model allows each node to take on analog state values. Unlike most widely used approaches, where binary labels (changed/unchanged) are assigned to each pixel, the analog property provides the strength of the change. The main contribution of this paper is reflected in the customization of the analog Hopfield neural network to derive an automatic image change detection approach. When a pixel is being processed, some existing image change detection procedures consider only interpixel relations on its neighborhood. The main drawback of such approaches is the labeling of this pixel as changed or unchanged according to the information supplied by its neighbors, where its own information is ignored. The Hopfield model overcomes this drawback and for each pixel allows a tradeoff between the influence of its neighborhood and its own criterion. This is mapped under the energy function to be minimized. The performance of the proposed method is illustrated by comparative analysis against some existing image change detection methods.

Interoperable cross-domain semantic and geospatial framework for automatic change detection

NASA Astrophysics Data System (ADS)

Kuo, Chiao-Ling; Hong, Jung-Hong

2016-01-01

With the increasingly diverse types of geospatial data established over the last few decades, semantic interoperability in integrated applications has attracted much interest in the field of Geographic Information System (GIS). This paper proposes a new strategy and framework to process cross-domain geodata at the semantic level. This framework leverages the semantic equivalence of concepts between domains through bridge ontology and facilitates the integrated use of different domain data, which has been long considered as an essential superiority of GIS, but is impeded by the lack of understanding about the semantics implicitly hidden in the data. We choose the task of change detection to demonstrate how the introduction of ontology concept can effectively make the integration possible. We analyze the common properties of geodata and change detection factors, then construct rules and summarize possible change scenario for making final decisions. The use of topographic map data to detect changes in land use shows promising success, as far as the improvement of efficiency and level of automation is concerned. We believe the ontology-oriented approach will enable a new way for data integration across different domains from the perspective of semantic interoperability, and even open a new dimensionality for the future GIS.

Wetland Classification for Black Duck Habitat Management Using Combined Polarimetric RADARSAT 2 and SPOT Imagery

NASA Astrophysics Data System (ADS)

Zhang, W.; Hu, B.; Brown, G.

2018-04-01

The black duck population has decreased significantly due to loss of its breeding habitat. Wetlands are an important feature that relates to habitat management and requires monitoring. Synthetic Aperture Radar (SAR) systems are helpful to map the wetland as the microwave signals are sensitive to water content and can be used to map surface water extent, saturated soils, and flooded vegetation. In this study, RadarSat 2 Polarimetric data is employed to map surface water and track changes in extent over the years through image thresholding and reviewed different approaches of Polarimetric decompositions for detecting flooded vegetation. Also, object-based analysis associated with beaver activity is conducted with combined multispectral SPOT satellite imagery. Results show SAR data has proven ability to improve mapping open water areas and locate flooded vegetation areas.

Exploring the association of the Minnesota Department of Natural Resources' satellite-detected change with the Forest Inventory and Analysis system of observed removals and mortality

Treesearch

Dale D. Gormanson; Timothy J. Aunan; Mark H. Hansen; Michael Hoppus

2009-01-01

Since 2001, the Minnesota Department of Natural Resources (MN-DNR) has mapped forest change annually by comparison of Landsat satellite image pairs. Over the same timeframe, 1,761 U.S. Department of Agriculture, Forest Service, Forest Inventory and Analysis (FIA) plots in Minnesota have been remeasured on a 5-year cycle, providing field data on growth, removals, and...

Active Fire Mapping Program

MedlinePlus

Active Fire Mapping Program Current Large Incidents (Home) New Large Incidents Fire Detection Maps MODIS Satellite Imagery VIIRS Satellite Imagery Fire Detection GIS Data Fire Data in Google Earth ...

Decision-level fusion of SAR and IR sensor information for automatic target detection

NASA Astrophysics Data System (ADS)

Cho, Young-Rae; Yim, Sung-Hyuk; Cho, Hyun-Woong; Won, Jin-Ju; Song, Woo-Jin; Kim, So-Hyeon

2017-05-01

We propose a decision-level architecture that combines synthetic aperture radar (SAR) and an infrared (IR) sensor for automatic target detection. We present a new size-based feature, called target-silhouette to reduce the number of false alarms produced by the conventional target-detection algorithm. Boolean Map Visual Theory is used to combine a pair of SAR and IR images to generate the target-enhanced map. Then basic belief assignment is used to transform this map into a belief map. The detection results of sensors are combined to build the target-silhouette map. We integrate the fusion mass and the target-silhouette map on the decision level to exclude false alarms. The proposed algorithm is evaluated using a SAR and IR synthetic database generated by SE-WORKBENCH simulator, and compared with conventional algorithms. The proposed fusion scheme achieves higher detection rate and lower false alarm rate than the conventional algorithms.

Object-based change detection: dimension of damage in residential areas of Abu Suruj, Sudan

NASA Astrophysics Data System (ADS)

Demharter, Timo; Michel, Ulrich; Ehlers, Manfred; Reinartz, Peter

2011-11-01

Given the importance of Change Detection, especially in the field of crisis management, this paper discusses the advantage of object-based Change Detection. This project and the used methods give an opportunity to coordinate relief actions strategically. The principal objective of this project was to develop an algorithm which allows to detect rapidly damaged and destroyed buildings in the area of Abu Suruj. This Sudanese village is located in West-Darfur and has become the victim of civil war. The software eCognition Developer was used to per-form an object-based Change Detection on two panchromatic Quickbird 2 images from two different time slots. The first image shows the area before, the second image shows the area after the massacres in this region. Seeking a classification for the huts of the Sudanese town Abu Suruj was reached by first segmenting the huts and then classifying them on the basis of geo-metrical and brightness-related values. The huts were classified as "new", "destroyed" and "preserved" with the help of a automated algorithm. Finally the results were presented in the form of a map which displays the different conditions of the huts. The accuracy of the project is validated by an accuracy assessment resulting in an Overall Classification Accuracy of 90.50 percent. These change detection results allow aid organizations to provide quick and efficient help where it is needed the most.

Detecting agricultural to urban land use change from multi-temporal MSS digital data. [Salt Lake County, Utah

NASA Technical Reports Server (NTRS)

Ridd, M. K.; Merola, J. A.; Jaynes, R. A.

1983-01-01

Conversion of agricultural land to a variety of urban uses is a major problem along the Wasatch Front, Utah. Although LANDSAT MSS data is a relatively coarse tool for discriminating categories of change in urban-size plots, its availability prompts a thorough test of its power to detect change. The procedures being applied to a test area in Salt Lake County, Utah, where the land conversion problem is acute are presented. The identity of land uses before and after conversion was determined and digital procedures for doing so were compared. Several algorithms were compared, utilizing both raw data and preprocessed data. Verification of results involved high quality color infrared photography and field observation. Two data sets were digitally registered, specific change categories internally identified in the software, results tabulated by computer, and change maps printed at 1:24,000 scale.

Analysis of vegetation changes in Cidanau watershed, Indonesia

NASA Astrophysics Data System (ADS)

Khairiah, R. N.; Kunihiko, Y.; Prasetyo, L. B.; Setiawan, Y.

2018-05-01

Vegetation change detection is needed for conserve of quality and water cycle in Cidanau watershed. The NDVI was applied to quantify the vegetation changes of Cidanau watershed for three different years 1989, 2001, and 2015. Using NDVI we mapped the reflectance from chlorophyll and distinguished varying amounts of vegetation at the pixel level by index. In the present study, as a preliminary study, we proposed a vegetation change detection analysis based on the NDVI from 1989 through 2015. Multi-temporal satellite data i.e. Landsat imagery with 30 m spatial resolution are used in the present study. It is reported that agroforestry land exhibited the greatest reductions in highly dense vegetation class in 1989-2001 and also moderate vegetation class in 2001-2015. It’s mean that amount of vegetation present in agroforestry land is getting lower year by year.

Image denoising based on noise detection

NASA Astrophysics Data System (ADS)

Jiang, Yuanxiang; Yuan, Rui; Sun, Yuqiu; Tian, Jinwen

2018-03-01

Because of the noise points in the images, any operation of denoising would change the original information of non-noise pixel. A noise detection algorithm based on fractional calculus was proposed to denoise in this paper. Convolution of the image was made to gain direction gradient masks firstly. Then, the mean gray was calculated to obtain the gradient detection maps. Logical product was made to acquire noise position image next. Comparisons in the visual effect and evaluation parameters after processing, the results of experiment showed that the denoising algorithms based on noise were better than that of traditional methods in both subjective and objective aspects.

A Proteomics Analysis of the Effects of Chronic Hemiparetic Stroke on Troponin T Expression in Human Vastus Lateralis

PubMed Central

Rabek, Jeffrey P.; Hafer-Macko, Charlene E.; Amaning, James K.; DeFord, James H.; Dimayuga, Vincent L.; Madsen, Mark A.; Macko, Richard F.

2009-01-01

Stroke disability is attributed to upper motor neuron deficits resulting from ischemic brain injury. We have developed proteome maps of the Vastus lateralis to examine the effects of ischemic brain injury on paretic skeletal muscle myofilament proteins. Proteomics analyses from seven hemiparetic stroke patients have detected a decrease of three troponin T isoforms in the paretic muscle suggesting that myosin–actin interactions may be attenuated. We propose that ischemic brain injury may prevent troponin T participation in complex formation thereby affecting the protein interactions associated with excitation–contraction coupling. We have also detected a novel skeletal troponin T isoform that has a C-terminal variation. Our data suggest that the decreased slow troponin T isoform pools in the paretic limb may contribute to the gait deficit after stroke. The complexity of the neurological deficit on Vastus lateralis is suggested by the multiple changes in proteins detected by our proteomics mapping. PMID:19447848

Optical remote sensing for forest area estimation

Treesearch

Randolph H. Wynne; Richard G. Oderwald; Gregory A. Reams; John A. Scrivani

2000-01-01

The air photo dot-count method is now widely and successfully used for estimating operational forest area in the USDA Forest Inventory and Analysis (FIA) program. Possible alternatives that would provide for more frequent updates, spectral change detection, and maps of forest area include the AVHRR calibration center technique and various Landsat TM classification...

Kon-Tiki: Spatio-Temporal Maps for Socio-Economic Sustainability

ERIC Educational Resources Information Center

Ahamer, Gilbert

2014-01-01

Purpose: The overall purpose of this paper is to detect spatial, temporal, sectoral, thematic and other patterns or transitions in techno-socio-economic evolution that are likely to co-determine future development and allow the steering of it. The development of a "Global Change Data Base" (GCDB) promises a graphically and geographically…

Acetic acid-guided biopsies in Barrett’s surveillance for neoplasia detection versus non-targeted biopsies (Seattle protocol): A feasibility study for a randomized tandem endoscopy trial. The ABBA study

PubMed Central

Chedgy, Fergus; Fogg, Carole; Kandiah, Kesavan; Barr, Hugh; Higgins, Bernard; McCord, Mimi; Dewey, Ann; De Caestecker, John; Gadeke, Lisa; Stokes, Clive; Poller, David; Longcroft-Wheaton, Gaius; Bhandari, Pradeep

2018-01-01

Background and study aims  Barrett’s esophagus is a potentially pre-cancerous condition, affecting 375,000 people in the UK. Patients receive a 2-yearly endoscopy to detect cancerous changes, as early detection and treatment results in better outcomes. Current treatment requires random mapping biopsies along the length of Barrett’s, in addition to biopsy of visible abnormalities. As only 13 % of pre-cancerous changes appear as visible nodules or abnormalities, areas of dysplasia are often missed. Acetic acid chromoendoscopy (AAC) has been shown to improve detection of pre-cancerous and cancerous tissue in observational studies, but no randomized controlled trials (RCTs) have been performed to date. Patients and methods  A “tandem” endoscopy cross-over design. Participants will be randomized to endoscopy using mapping biopsies or AAC, in which dilute acetic acid is sprayed onto the surface of the esophagus, highlighting tissue through an whitening reaction and enhancing visibility of areas with cellular changes for biopsy. After 4 to 10 weeks, participants will undergo a repeat endoscopy, using the second method. Rates of recruitment and retention will be assessed, in addition to the estimated dysplasia detection rate, effectiveness of the endoscopist training program, and rates of adverse events (AEs). Qualitative interviews will explore participant and endoscopist acceptability of study design and delivery, and the acceptability of switching endoscopic techniques for Barrett's surveillance. Results  Endoscopists’ ability to diagnose dysplasia in Barrett’s esophagus can be improved. AAC may offer a simple, universally applicable, easily-acquired technique to improve detection, affording patients earlier diagnosis and treatment, reducing endoscopy time and pathology costs. The ABBA study will determine whether a crossover “tandem” endoscopy design is feasible and acceptable to patients and clinicians and gather outcome data to power a definitive trial. PMID:29340297

Evaluation of bioreactor-cultivated bone by magnetic resonance microscopy and FTIR microspectroscopy.

PubMed

Chesnick, Ingrid E; Avallone, Francis A; Leapman, Richard D; Landis, William J; Eidelman, Naomi; Potter, Kimberlee

2007-04-01

We present a three-dimensional mineralizing model based on a hollow fiber bioreactor (HFBR) inoculated with primary osteoblasts isolated from embryonic chick calvaria. Using non-invasive magnetic resonance microscopy (MRM), the growth and development of the mineralized tissue around the individual fibers were monitored over a period of 9 weeks. Spatial maps of the water proton MRM properties of the intact tissue, with 78 microm resolution, were used to determine changes in tissue composition with development. Unique changes in the mineral and collagen content of the tissue were detected with high specificity by proton density (PD) and magnetization transfer ratio (MTR) maps, respectively. At the end of the growth period, the presence of a bone-like tissue was verified by histology and the formation of poorly crystalline apatite was verified by selected area electron diffraction and electron probe X-ray microanalysis. FTIR microspectroscopy confirmed the heterogeneous nature of the bone-like tissue formed. FTIR-derived phosphate maps confirmed that those locations with the lowest PD values contained the most mineral, and FTIR-derived collagen maps confirmed that bright pixels on MTR maps corresponded to regions of high collagen content. In conclusion, the spatial mapping of tissue constituents by FTIR microspectroscopy corroborated the findings of non-invasive MRM measurements and supported the role of MRM in monitoring the bone formation process in vitro.

Evaluation of Bioreactor-Cultivated Bone by Magnetic Resonance Microscopy and FTIR Microspectroscopy

PubMed Central

Chesnick, Ingrid E.; Avallone, Frank; Leapman, Richard D.; Landis, William J.; Eidelman, Naomi; Potter, Kimberlee

2007-01-01

We present a three-dimensional mineralizing model based on a hollow fiber bioreactor (HFBR) inoculated with primary osteoblasts isolated from embryonic chick calvaria. Using non-invasive magnetic resonance microscopy (MRM), the growth and development of the mineralized tissue around the individual fibers were monitored over a period of nine weeks. Spatial maps of the water proton MRM properties of the intact tissue, with 78 μm resolution, were used to determine changes in tissue composition with development. Unique changes in the mineral and collagen content of the tissue were detected with high specificity by proton density (PD) and magnetization transfer ratio (MTR) maps, respectively. At the end of the growth period, the presence of a bone-like tissue was verified by histology and the formation of poorly crystalline apatite was verified by selected area electron diffraction and electron probe X-ray microanalysis. FTIR microspectroscopy confirmed the heterogeneous nature of the bone-like tissue formed. FTIR-derived phosphate maps confirmed that those locations with the lowest PD values contained the most mineral, and FTIR-derived collagen maps confirmed that bright pixels on MTR maps corresponded to regions of high collagen content. In conclusion, the spatial mapping of tissue constituents by FTIR microspectroscopy corroborated the findings of non-invasive MRM measurements and supported the role of MRM in monitoring the bone formation process in vitro. PMID:17174620

3D Vegetation Mapping Using UAVSAR, LVIS, and LIDAR Data Acquisition Methods

NASA Technical Reports Server (NTRS)

Calderon, Denice

2011-01-01

The overarching objective of this ongoing project is to assess the role of vegetation within climate change. Forests capture carbon, a green house gas, from the atmosphere. Thus, any change, whether, natural (e.g. growth, fire, death) or due to anthropogenic activity (e.g. logging, burning, urbanization) may have a significant impact on the Earth's carbon cycle. Through the use of Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) and NASA's Laser Vegetation Imaging Sensor (LVIS), which are airborne Light Detection and Ranging (LIDAR) remote sensing technologies, we gather data to estimate the amount of carbon contained in forests and how the content changes over time. UAVSAR and LVIS sensors were sent all over the world with the objective of mapping out terrain to gather tree canopy height and biomass data; This data is in turn used to correlate vegetation with the global carbon cycle around the world.

Modeling photo-bleaching kinetics to map local variations in rod rhodopsin density

NASA Astrophysics Data System (ADS)

Ehler, M.; Dobrosotskaya, J.; King, E. J.; Czaja, W.; Bonner, R. F.

2011-03-01

Localized rod photoreceptor and rhodopsin losses have been observed in post mortem histology both in normal aging and in age-related maculopathy. We propose to noninvasively map local rod rhodopsin density through analysis of the brightening of the underlying lipofuscin autofluorescence (LAF) in confocal scanning laser ophthalmoscopy (cSLO) imaging sequences starting in the dark adapted eye. The detected LAF increases as rhodopsin is bleached (time constant ~ 25sec) by the average retinal irradiance of the cSLO 488nm laser beam. We fit parameters of analytical expressions for the kinetics of rhodopsin bleaching that Lamb validated using electroretinogram recordings in human. By performing localized (~ 100μm) kinetic analysis, we create high resolution maps of the rhodopsin density. This new noninvasive imaging and analysis approach appears well-suited for measuring localized changes in the rod photoreceptors and correlating them at high spatial resolution with localized pathological changes of the retinal pigment epithelium (RPE) seen in steady-state LAF images.

EAARL Topography-Padre Island National Seashore

USGS Publications Warehouse

Brock, John C.; Wright, C. Wayne; Nayegandhi, Amar; Patterson, Matt; Wilson, Iris; Travers, Laurinda J.

2007-01-01

This Web site contains 116 Lidar-derived bare earth topography maps and GIS files for Padre Island National Seashore-Texas. These Lidar-derived topography maps were produced as a collaborative effort between the U.S. Geological Survey (USGS) Florida Integrated Science Center (FISC) St. Petersburg, Florida, the National Park Service (NPS) Gulf Coast Network, Inventory and Monitoring Program, and the National Aeronautics and Space Administration (NASA) Wallops Flight Facility. One objective of this research is to create techniques to survey coral reefs and barrier islands for the purposes of geomorphic change studies, habitat mapping, ecological monitoring, change detection, and event assessment. As part of this project, data from an innovative instrument under development at the NASA Wallops Flight Facility, the NASA Experimental Airborne Advanced Research Lidar (EAARL) are being used. This sensor has the potential to make significant contributions in this realm for measuring subaerial and submarine topography wthin cross-environment surveys. High spectral resolution, water-column correction, and low costs were found to be key factors in providing accurate and affordable imagery to costal resource managers.

High-resolution three-dimensional imaging with compress sensing

NASA Astrophysics Data System (ADS)

Wang, Jingyi; Ke, Jun

2016-10-01

LIDAR three-dimensional imaging technology have been used in many fields, such as military detection. However, LIDAR require extremely fast data acquisition speed. This makes the manufacture of detector array for LIDAR system is very difficult. To solve this problem, we consider using compress sensing which can greatly decrease the data acquisition and relax the requirement of a detection device. To use the compressive sensing idea, a spatial light modulator will be used to modulate the pulsed light source. Then a photodetector is used to receive the reflected light. A convex optimization problem is solved to reconstruct the 2D depth map of the object. To improve the resolution in transversal direction, we use multiframe image restoration technology. For each 2D piecewise-planar scene, we move the SLM half-pixel each time. Then the position where the modulated light illuminates will changed accordingly. We repeat moving the SLM to four different directions. Then we can get four low-resolution depth maps with different details of the same plane scene. If we use all of the measurements obtained by the subpixel movements, we can reconstruct a high-resolution depth map of the sense. A linear minimum-mean-square error algorithm is used for the reconstruction. By combining compress sensing and multiframe image restoration technology, we reduce the burden on data analyze and improve the efficiency of detection. More importantly, we obtain high-resolution depth maps of a 3D scene.

Infrared small target detection based on directional zero-crossing measure

NASA Astrophysics Data System (ADS)

Zhang, Xiangyue; Ding, Qinghai; Luo, Haibo; Hui, Bin; Chang, Zheng; Zhang, Junchao

2017-12-01

Infrared small target detection under complex background and low signal-to-clutter ratio (SCR) condition is of great significance to the development on precision guidance and infrared surveillance. In order to detect targets precisely and extract targets from intricate clutters effectively, a detection method based on zero-crossing saliency (ZCS) map is proposed. The original map is first decomposed into different first-order directional derivative (FODD) maps by using FODD filters. Then the ZCS map is obtained by fusing all directional zero-crossing points. At last, an adaptive threshold is adopted to segment targets from the ZCS map. Experimental results on a series of images show that our method is effective and robust for detection under complex backgrounds. Moreover, compared with other five state-of-the-art methods, our method achieves better performance in terms of detection rate, SCR gain and background suppression factor.

Changes in Women’s Facial Skin Color over the Ovulatory Cycle are Not Detectable by the Human Visual System

PubMed Central

Burriss, Robert P.; Troscianko, Jolyon; Lovell, P. George; Fulford, Anthony J. C.; Stevens, Martin; Quigley, Rachael; Payne, Jenny; Saxton, Tamsin K.; Rowland, Hannah M.

2015-01-01

Human ovulation is not advertised, as it is in several primate species, by conspicuous sexual swellings. However, there is increasing evidence that the attractiveness of women’s body odor, voice, and facial appearance peak during the fertile phase of their ovulatory cycle. Cycle effects on facial attractiveness may be underpinned by changes in facial skin color, but it is not clear if skin color varies cyclically in humans or if any changes are detectable. To test these questions we photographed women daily for at least one cycle. Changes in facial skin redness and luminance were then quantified by mapping the digital images to human long, medium, and shortwave visual receptors. We find cyclic variation in skin redness, but not luminance. Redness decreases rapidly after menstrual onset, increases in the days before ovulation, and remains high through the luteal phase. However, we also show that this variation is unlikely to be detectable by the human visual system. We conclude that changes in skin color are not responsible for the effects of the ovulatory cycle on women’s attractiveness. PMID:26134671

Changes in Women's Facial Skin Color over the Ovulatory Cycle are Not Detectable by the Human Visual System.

PubMed

Burriss, Robert P; Troscianko, Jolyon; Lovell, P George; Fulford, Anthony J C; Stevens, Martin; Quigley, Rachael; Payne, Jenny; Saxton, Tamsin K; Rowland, Hannah M

2015-01-01

Human ovulation is not advertised, as it is in several primate species, by conspicuous sexual swellings. However, there is increasing evidence that the attractiveness of women's body odor, voice, and facial appearance peak during the fertile phase of their ovulatory cycle. Cycle effects on facial attractiveness may be underpinned by changes in facial skin color, but it is not clear if skin color varies cyclically in humans or if any changes are detectable. To test these questions we photographed women daily for at least one cycle. Changes in facial skin redness and luminance were then quantified by mapping the digital images to human long, medium, and shortwave visual receptors. We find cyclic variation in skin redness, but not luminance. Redness decreases rapidly after menstrual onset, increases in the days before ovulation, and remains high through the luteal phase. However, we also show that this variation is unlikely to be detectable by the human visual system. We conclude that changes in skin color are not responsible for the effects of the ovulatory cycle on women's attractiveness.

Multisensor monitoring of deforestation in the Guinea Highlands of West Africa

NASA Technical Reports Server (NTRS)

Gilruth, Peter T.; Hutchinson, Charles F.

1990-01-01

Multiple remote sensing systems were used to assess deforestation in the Guinea Highlands (Fouta Djallon) of West Africa. Sensor systems included: (1) historical (1953) and current (1989) aerial mapping photography; (2) current large-scale, small format (35mm) aerial photography; (3) current aerial video imagery; and (4) historical (1973) and recent (1985) LANDSAT MSS. Photographic and video data were manually interpreted and incorporated in a vector-based geographic information system (GIS). LANDSAT data were digitally classified. General results showed an increase in permanent and shifting agriculture over the past 35 years. This finding is consistent with hypothesized strategies to increase agricultural production through a shortening of the fallow period in areas of shifting cultivation. However, results also show that the total area of both permanent and shifting agriculture had expanded at the expense of natural vegetation and an increase in erosion. Although sequential LANDSAT MSS cannot be used in this region to accurately map land over, the location, direction and magnitude of changes can be detected in relative terms. Historical and current aerial photography can be used to map agricultural land use changes with some accuracy. Video imagery is useful as ancillary data for mapping vegetation. The most prudent approach to mapping deforestation would incorporate a multistage approach based on these sensors.

Evidential analysis of difference images for change detection of multitemporal remote sensing images

NASA Astrophysics Data System (ADS)

Chen, Yin; Peng, Lijuan; Cremers, Armin B.

2018-03-01

In this article, we develop two methods for unsupervised change detection in multitemporal remote sensing images based on Dempster-Shafer's theory of evidence (DST). In most unsupervised change detection methods, the probability of difference image is assumed to be characterized by mixture models, whose parameters are estimated by the expectation maximization (EM) method. However, the main drawback of the EM method is that it does not consider spatial contextual information, which may entail rather noisy detection results with numerous spurious alarms. To remedy this, we firstly develop an evidence theory based EM method (EEM) which incorporates spatial contextual information in EM by iteratively fusing the belief assignments of neighboring pixels to the central pixel. Secondly, an evidential labeling method in the sense of maximizing a posteriori probability (MAP) is proposed in order to further enhance the detection result. It first uses the parameters estimated by EEM to initialize the class labels of a difference image. Then it iteratively fuses class conditional information and spatial contextual information, and updates labels and class parameters. Finally it converges to a fixed state which gives the detection result. A simulated image set and two real remote sensing data sets are used to evaluate the two evidential change detection methods. Experimental results show that the new evidential methods are comparable to other prevalent methods in terms of total error rate.

Comparison of Object-Based Image Analysis Approaches to Mapping New Buildings in Accra, Ghana Using Multi-Temporal QuickBird Satellite Imagery

PubMed Central

Tsai, Yu Hsin; Stow, Douglas; Weeks, John

2013-01-01

The goal of this study was to map and quantify the number of newly constructed buildings in Accra, Ghana between 2002 and 2010 based on high spatial resolution satellite image data. Two semi-automated feature detection approaches for detecting and mapping newly constructed buildings based on QuickBird very high spatial resolution satellite imagery were analyzed: (1) post-classification comparison; and (2) bi-temporal layerstack classification. Feature Analyst software based on a spatial contextual classifier and ENVI Feature Extraction that uses a true object-based image analysis approach of image segmentation and segment classification were evaluated. Final map products representing new building objects were compared and assessed for accuracy using two object-based accuracy measures, completeness and correctness. The bi-temporal layerstack method generated more accurate results compared to the post-classification comparison method due to less confusion with background objects. The spectral/spatial contextual approach (Feature Analyst) outperformed the true object-based feature delineation approach (ENVI Feature Extraction) due to its ability to more reliably delineate individual buildings of various sizes. Semi-automated, object-based detection followed by manual editing appears to be a reliable and efficient approach for detecting and enumerating new building objects. A bivariate regression analysis was performed using neighborhood-level estimates of new building density regressed on a census-derived measure of socio-economic status, yielding an inverse relationship with R2 = 0.31 (n = 27; p = 0.00). The primary utility of the new building delineation results is to support spatial analyses of land cover and land use and demographic change. PMID:24415810

Mapping slope movements in Alpine environments using TerraSAR-X interferometric methods

NASA Astrophysics Data System (ADS)

Barboux, Chloé; Strozzi, Tazio; Delaloye, Reynald; Wegmüller, Urs; Collet, Claude

2015-11-01

Mapping slope movements in Alpine environments is an increasingly important task in the context of climate change and natural hazard management. We propose the detection, mapping and inventorying of slope movements using different interferometric methods based on TerraSAR-X satellite images. Differential SAR interferograms (DInSAR), Persistent Scatterer Interferometry (PSI), Short-Baseline Interferometry (SBAS) and a semi-automated texture image analysis are presented and compared in order to determine their contribution for the automatic detection and mapping of slope movements of various velocity rates encountered in Alpine environments. Investigations are conducted in a study region of about 6 km × 6 km located in the Western Swiss Alps using a unique large data set of 140 DInSAR scenes computed from 51 summer TerraSAR-X (TSX) acquisitions from 2008 to 2012. We found that PSI is able to precisely detect only points moving with velocities below 3.5 cm/yr in the LOS, with a root mean squared error of about 0.58 cm/yr compared to DGPS records. SBAS employed with 11 days summer interferograms increases the range of detectable movements to rates up to 35 cm/yr in the LOS with a root mean squared error of 6.36 cm/yr, but inaccurate measurements due to phase unwrapping are already possible for velocity rates larger than 20 cm/year. With the semi-automated texture image analysis the rough estimation of the velocity rates over an outlined moving zone is accurate for rates of "cm/day", "dm/month" and "cm/month", but due to the decorrelation of yearly TSX interferograms this method fails for the observation of slow movements in the "cm/yr" range.

Distribution and stability of eelgrass beds at Izembek Lagoon, Alaska

USGS Publications Warehouse

Ward, David H.; Markon, Carl J.; Douglas, David C.

1997-01-01

Spatial change in eelgrass meadows, Zostera marina L., was assessed between 1978 and 1987 and between 1987 and 1995 at Izembek Lagoon, Alaska. Change in total extent was evaluated through a map to map comparison of data interpreted from a 1978 Landsat multi-spectral scanner image and 1987 black and white aerial photographs. A ground survey in 1995 was used to assess spatial change from 1987. Eelgrass beds were the predominant vegetation type in the lagoon, comprising 44-47% (15000-16000 ha) of the total area in 1978 and 1987. Izembek Lagoon contains the largest bed of seagrass along the Pacific Coast of North America and largest known single stand of eelgrass in the world. There was a high degree of overlap in the spatial distribution of eelgrass among years of change detection. The overall net change was a 6% gain between, 1978 and 1987 and a <1% gain between 1987 and 1995. The lack of significant change in eelgrass cover suggests that eelgrass meadows in Izembek Lagoon have been stable during the 17-year period of our study.

Elasticity mapping of murine abdominal organs in vivo using harmonic motion imaging (HMI)

NASA Astrophysics Data System (ADS)

Payen, Thomas; Palermo, Carmine F.; Sastra, Stephen A.; Chen, Hong; Han, Yang; Olive, Kenneth P.; Konofagou, Elisa E.

2016-08-01

Recently, ultrasonic imaging of soft tissue mechanics has been increasingly studied to image otherwise undetectable pathologies. However, many underlying mechanisms of tissue stiffening remain unknown, requiring small animal studies and adapted elasticity mapping techniques. Harmonic motion imaging (HMI) assesses tissue viscoelasticity by inducing localized oscillation from a periodic acoustic radiation force. The objective of this study was to evaluate the feasibility of HMI for in vivo elasticity mapping of abdominal organs in small animals. Pathological cases, i.e. chronic pancreatitis and pancreatic cancer, were also studied in vivo to assess the capability of HMI for detection of the change in mechanical properties. A 4.5 MHz focused ultrasound transducer (FUS) generated an amplitude-modulated beam resulting in 50 Hz harmonic tissue oscillations at its focus. Axial tissue displacement was estimated using 1D-cross-correlation of RF signals acquired with a 7.8 MHz diagnostic transducer confocally aligned with the FUS. In vitro results in canine liver and kidney showed the correlation between HMI displacement and Young’s moduli measured by rheometry compression testing. HMI was capable of providing reproducible elasticity maps of the mouse abdominal region in vivo allowing the identification of, from stiffest to softest, the murine kidney, pancreas, liver, and spleen. Finally, pancreata affected by pancreatitis and pancreatic cancer showed HMI displacements 1.7 and 2.2 times lower than in the control case, respectively, indicating higher stiffness. The HMI displacement amplitude was correlated with the extent of fibrosis as well as detecting the very onset of stiffening even before fibrosis could be detected on H&E. This work shows that HMI can produce reliable elasticity maps of mouse abdominal region in vivo, thus providing a potentially critical tool to assess pathologies affecting organ elasticity.

Elasticity mapping of murine abdominal organs in vivo using Harmonic Motion Imaging (HMI)

PubMed Central

Payen, Thomas; Palermo, Carmine F.; Sastra, Steve; Chen, Hong; Han, Yang; Olive, Kenneth P.; Konofagou, Elisa E.

2016-01-01

Recently, ultrasonic imaging of soft tissue mechanics has been increasingly studied to image otherwise undetectable pathologies. However, many underlying mechanisms of tissue stiffening remain unknown, requiring small animal studies and adapted elasticity mapping techniques. Harmonic motion imaging (HMI) assesses tissue viscoelasticity by inducing localized oscillation from a periodic acoustic radiation force. The objective of this study was to evaluate the feasibility of HMI for in vivo elasticity mapping of abdominal organs in small animals. Pathological cases, i.e. chronic pancreatitis and pancreatic cancer, were also studied in vivo to assess the capability of HMI for detection of the change in mechanical properties. A 4.5-MHz focused ultrasound transducer (FUS) generated an amplitude-modulated beam resulting in 50-Hz harmonic tissue oscillations at its focus. Axial tissue displacement was estimated using 1D-cross-correlation of RF signals acquired with a 7.8-MHz diagnostic transducer confocally aligned with the FUS. In vitro results in canine liver and kidney showed the correlation between HMI displacement and Young’s moduli measured by rheometry compression tests. HMI was able to provide reproducible elasticity maps of the mouse abdominal region in vivo allowing the identification of, from stiffest to softest, the murine kidney, pancreas, liver, and spleen. Finally, pancreata affected by pancreatitis and pancreatic cancer showed HMI displacements 1.7 and 2.2 times lower than in the control case, respectively, indicating higher stiffness. HMI displacement was correlated with the extent of fibrosis as well as detecting the very onset of stiffening even before fibrosis could be detected on H&E. This work shows that HMI can produce reliable elasticity maps of mouse abdominal region in vivo providing a crucial tool to understand pathologies affecting organ elasticity. PMID:27401609

Elasticity mapping of murine abdominal organs in vivo using harmonic motion imaging (HMI).

PubMed

Payen, Thomas; Palermo, Carmine F; Sastra, Stephen A; Chen, Hong; Han, Yang; Olive, Kenneth P; Konofagou, Elisa E

2016-08-07

Recently, ultrasonic imaging of soft tissue mechanics has been increasingly studied to image otherwise undetectable pathologies. However, many underlying mechanisms of tissue stiffening remain unknown, requiring small animal studies and adapted elasticity mapping techniques. Harmonic motion imaging (HMI) assesses tissue viscoelasticity by inducing localized oscillation from a periodic acoustic radiation force. The objective of this study was to evaluate the feasibility of HMI for in vivo elasticity mapping of abdominal organs in small animals. Pathological cases, i.e. chronic pancreatitis and pancreatic cancer, were also studied in vivo to assess the capability of HMI for detection of the change in mechanical properties. A 4.5 MHz focused ultrasound transducer (FUS) generated an amplitude-modulated beam resulting in 50 Hz harmonic tissue oscillations at its focus. Axial tissue displacement was estimated using 1D-cross-correlation of RF signals acquired with a 7.8 MHz diagnostic transducer confocally aligned with the FUS. In vitro results in canine liver and kidney showed the correlation between HMI displacement and Young's moduli measured by rheometry compression testing. HMI was capable of providing reproducible elasticity maps of the mouse abdominal region in vivo allowing the identification of, from stiffest to softest, the murine kidney, pancreas, liver, and spleen. Finally, pancreata affected by pancreatitis and pancreatic cancer showed HMI displacements 1.7 and 2.2 times lower than in the control case, respectively, indicating higher stiffness. The HMI displacement amplitude was correlated with the extent of fibrosis as well as detecting the very onset of stiffening even before fibrosis could be detected on H&E. This work shows that HMI can produce reliable elasticity maps of mouse abdominal region in vivo, thus providing a potentially critical tool to assess pathologies affecting organ elasticity.

Subclinical keratoconus detection by pattern analysis of corneal and epithelial thickness maps with optical coherence tomography

PubMed Central

Li, Yan; Chamberlain, Winston; Tan, Ou; Brass, Robert; Weiss, Jack L.; Huang, David

2016-01-01

PURPOSE To screen for subclinical keratoconus by analyzing corneal, epithelial, and stromal thickness map patterns with Fourier-domain optical coherence tomography (OCT). SETTING Four centers in the United States. DESIGN Cross-sectional observational study. METHODS Eyes of normal subjects, subclinical keratoconus eyes, and the topographically normal eye of a unilateral keratoconus patient were studied. Corneas were scanned using a 26 000 Hz Fourier-domain OCT system (RTVue). Normal subjects were divided into training and evaluation groups. Corneal, epithelial, and stromal thickness maps and derived diagnostic indices, including pattern standard deviation (PSD) variables and pachymetric map–based keratoconus risk scores were calculated from the OCT data. Area under the receiver operating characteristic curve (AUC) analysis was used to evaluate the diagnostic accuracy of the indices. RESULTS The study comprised 150 eyes of 83 normal subjects, 50 subclinical keratoconus eyes of 32 patients, and 1 topographically normal eye of a unilateral keratoconus patient. Subclinical keratoconus was characterized by inferotemporal thinning of the cornea, epithelium, and stroma. The PSD values for corneal (P < .001), epithelial (P < .001), and stromal (P = .049) thickness maps were all significantly higher in subclinical keratoconic eyes than in the normal group. The diagnostic accuracy was significantly higher for PSD variables (pachymetric PSD, AUC = 0.941; epithelial PSD, AUC = 0.985; stromal PSD, AUC = 0.924) than for the pachymetric map–based keratoconus risk score (AUC = 0.735). CONCLUSIONS High-resolution Fourier-domain OCT could map corneal, epithelial, and stromal thicknesses. Corneal and sublayer thickness changes in subclinical keratoconus could be detected with high accuracy using PSD variables. These new diagnostic variables might be useful in the detection of early keratoconus. PMID:27026454

Absence of rotational activity detected using 2-dimensional phase mapping in the corresponding 3-dimensional phase maps in human persistent atrial fibrillation.

PubMed

Pathik, Bhupesh; Kalman, Jonathan M; Walters, Tomos; Kuklik, Pawel; Zhao, Jichao; Madry, Andrew; Sanders, Prashanthan; Kistler, Peter M; Lee, Geoffrey

2018-02-01

Current phase mapping systems for atrial fibrillation create 2-dimensional (2D) maps. This process may affect the accurate detection of rotors. We developed a 3-dimensional (3D) phase mapping technique that uses the 3D locations of basket electrodes to project phase onto patient-specific left atrial 3D surface anatomy. We sought to determine whether rotors detected in 2D phase maps were present at the corresponding time segments and anatomical locations in 3D phase maps. One-minute left atrial atrial fibrillation recordings were obtained in 14 patients using the basket catheter and analyzed off-line. Using the same phase values, 2D and 3D phase maps were created. Analysis involved determining the dominant propagation patterns in 2D phase maps and evaluating the presence of rotors detected in 2D phase maps in the corresponding 3D phase maps. Using 2D phase mapping, the dominant propagation pattern was single wavefront (36.6%) followed by focal activation (34.0%), disorganized activity (23.7%), rotors (3.3%), and multiple wavefronts (2.4%). Ten transient rotors were observed in 9 of 14 patients (64%). The mean rotor duration was 1.1 ± 0.7 seconds. None of the 10 rotors observed in 2D phase maps were seen at the corresponding time segments and anatomical locations in 3D phase maps; 4 of 10 corresponded with single wavefronts in 3D phase maps, 2 of 10 with 2 simultaneous wavefronts, 1 of 10 with disorganized activity, and in 3 of 10 there was no coverage by the basket catheter at the corresponding 3D anatomical location. Rotors detected in 2D phase maps were not observed in the corresponding 3D phase maps. These findings may have implications for current systems that use 2D phase mapping. Copyright © 2017 Heart Rhythm Society. Published by Elsevier Inc. All rights reserved.

Evaluate ERTS imagery for mapping and detection of changes of snowcover on land and on glaciers. [Alaska and Washington

NASA Technical Reports Server (NTRS)

Meier, M. F. (Principal Investigator)

1973-01-01

The author has identified the following significant results. A new procedure to determine snowcovered areas has been devised. Aside from problems in heavily forested areas this method shows promise in predicting snowmelt runoff from mountain areas and will also assist in energy balance modeling of large snowfields. Snowcover results compare favorably with measurements made by high altitude aircraft photography. Changes in snowcover in areas as small as 3 x 5 km can be determined from ERTS-1 images by both optical and electronic methods. Snowcover changes determined by these two methods in the experimental South Cascade Glacier Basin were verified by field mapping. Image enahancement techniques on ERTS-1 images of large Alaskan glaciers (the Hubbard, Yentna, and Kahiltna) have given new insights into the large-scale structures and flow dynamics of these potentially hazardous glaciers. The Hubbard Glacier, in particular, is one which poses a threat to man and should be monitored for future changes.

[Morphological and functional cartilage imaging].

PubMed

Rehnitz, C; Weber, M-A

2014-06-01

Excellent morphological imaging of cartilage is now possible and allows the detection of subtle cartilage pathologies. Besides the standard 2D sequences, a multitude of 3D sequences are available for high-resolution cartilage imaging. The first part therefore deals with modern possibilities of morphological imaging. The second part deals with functional cartilage imaging with which it is possible to detect changes in cartilage composition and thus early osteoarthritis as well as to monitor biochemical changes after therapeutic interventions. Validated techniques such as delayed gadolinium-enhanced magnetic resonance imaging of cartilage (dGEMRIC) and T2 mapping as well the latest techniques, such as the glycosaminoglycan chemical exchange-dependent saturation transfer (gagCEST) technique will be discussed.

[Morphological and functional cartilage imaging].

PubMed

Rehnitz, C; Weber, M-A

2015-04-01

Excellent morphological imaging of cartilage is now possible and allows the detection of subtle cartilage pathologies. Besides the standard 2D sequences, a multitude of 3D sequences are available for high-resolution cartilage imaging. The first part therefore deals with modern possibilities of morphological imaging. The second part deals with functional cartilage imaging with which it is possible to detect changes in cartilage composition and thus early osteoarthritis as well as to monitor biochemical changes after therapeutic interventions. Validated techniques such as delayed gadolinium-enhanced magnetic resonance imaging of cartilage (dGEMRIC) and T2 mapping as well the latest techniques, such as the glycosaminoglycan chemical exchange-dependent saturation transfer (gagCEST) technique will be discussed.

Modeling of light distribution in the brain for topographical imaging

NASA Astrophysics Data System (ADS)

Okada, Eiji; Hayashi, Toshiyuki; Kawaguchi, Hiroshi

2004-07-01

Multi-channel optical imaging system can obtain a topographical distribution of the activated region in the brain cortex by a simple mapping algorithm. Near-infrared light is strongly scattered in the head and the volume of tissue that contributes to the change in the optical signal detected with source-detector pair on the head surface is broadly distributed in the brain. This scattering effect results in poor resolution and contrast in the topographic image of the brain activity. We report theoretical investigations on the spatial resolution of the topographic imaging of the brain activity. The head model for the theoretical study consists of five layers that imitate the scalp, skull, subarachnoid space, gray matter and white matter. The light propagation in the head model is predicted by Monte Carlo simulation to obtain the spatial sensitivity profile for a source-detector pair. The source-detector pairs are one dimensionally arranged on the surface of the model and the distance between the adjoining source-detector pairs are varied from 4 mm to 32 mm. The change in detected intensity caused by the absorption change is obtained by Monte Carlo simulation. The position of absorption change is reconstructed by the conventional mapping algorithm and the reconstruction algorithm using the spatial sensitivity profiles. We discuss the effective interval between the source-detector pairs and the choice of reconstruction algorithms to improve the topographic images of brain activity.

New NASA Maps Show Flooding Changes In Aftermath of Hurricane Harvey

NASA Image and Video Library

2017-09-13

Data from NASA's Soil Moisture Active Passive (SMAP) satellite have been used to create new surface flooding maps of Southeast Texas and the Tennessee Valley following Hurricane Harvey. The SMAP observations detect the proportional cover of surface water within the satellite sensor's field of view. This sequence of images shows changes in the extent of surface flooding from successive five-day SMAP observation composite images. Widespread flooding can be seen in the Houston metropolitan area on Aug. 27 following record rainfall from the Category 4 hurricane, which made landfall on Aug. 25th, 2017 (left image). Flood waters around Houston had substantially receded by Aug. 31 (middle image), while flooding had increased across Louisiana, eastern Arkansas, and western Tennessee as then Tropical Storm Harvey passed over the area. The far right image shows the change in flooded area between Aug. 27 and Aug. 31, with regions showing the most flooding recession depicted in yellow and orange shades and those where flooding had increased depicted in blue shades. The SMAP satellite has a low-frequency (L-band) microwave radiometer with enhanced capabilities for detecting surface water changes in nearly all weather conditions and under low-to-moderate vegetation cover. SMAP provides global coverage with one-to-three-day repeat sampling that is well suited for global monitoring of inland surface water cover dynamics. https://photojournal.jpl.nasa.gov/catalog/PIA21951

Drawing for Traffic Marking Using Bidirectional Gradient-Based Detection with MMS LIDAR Intensity

NASA Astrophysics Data System (ADS)

Takahashi, G.; Takeda, H.; Nakamura, K.

2016-06-01

Recently, the development of autonomous cars is accelerating on the integration of highly advanced artificial intelligence, which increases demand for a digital map with high accuracy. In particular, traffic markings are required to be precisely digitized since automatic driving utilizes them for position detection. To draw traffic markings, we benefit from Mobile Mapping Systems (MMS) equipped with high-density Laser imaging Detection and Ranging (LiDAR) scanners, which produces large amount of data efficiently with XYZ coordination along with reflectance intensity. Digitizing this data, on the other hand, conventionally has been dependent on human operation, which thus suffers from human errors, subjectivity errors, and low reproductivity. We have tackled this problem by means of automatic extraction of traffic marking, which partially accomplished to draw several traffic markings (G. Takahashi et al., 2014). The key idea of the method was extracting lines using the Hough transform strategically focused on changes in local reflection intensity along scan lines. However, it failed to extract traffic markings properly in a densely marked area, especially when local changing points are close each other. In this paper, we propose a bidirectional gradient-based detection method where local changing points are labelled with plus or minus group. Given that each label corresponds to the boundary between traffic markings and background, we can identify traffic markings explicitly, meaning traffic lines are differentiated correctly by the proposed method. As such, our automated method, a highly accurate and non-human-operator-dependent method using bidirectional gradient-based algorithm, can successfully extract traffic lines composed of complex shapes such as a cross walk, resulting in minimizing cost and obtaining highly accurate results.

Accuracy of remotely sensed data: Sampling and analysis procedures

NASA Technical Reports Server (NTRS)

Congalton, R. G.; Oderwald, R. G.; Mead, R. A.

1982-01-01

A review and update of the discrete multivariate analysis techniques used for accuracy assessment is given. A listing of the computer program written to implement these techniques is given. New work on evaluating accuracy assessment using Monte Carlo simulation with different sampling schemes is given. The results of matrices from the mapping effort of the San Juan National Forest is given. A method for estimating the sample size requirements for implementing the accuracy assessment procedures is given. A proposed method for determining the reliability of change detection between two maps of the same area produced at different times is given.

Bi-orthogonal Symbol Mapping and Detection in Optical CDMA Communication System

NASA Astrophysics Data System (ADS)

Liu, Maw-Yang

2017-12-01

In this paper, the bi-orthogonal symbol mapping and detection scheme is investigated in time-spreading wavelength-hopping optical CDMA communication system. The carrier-hopping prime code is exploited as signature sequence, whose put-of-phase autocorrelation is zero. Based on the orthogonality of carrier-hopping prime code, the equal weight orthogonal signaling scheme can be constructed, and the proposed scheme using bi-orthogonal symbol mapping and detection can be developed. The transmitted binary data bits are mapped into corresponding bi-orthogonal symbols, where the orthogonal matrix code and its complement are utilized. In the receiver, the received bi-orthogonal data symbol is fed into the maximum likelihood decoder for detection. Under such symbol mapping and detection, the proposed scheme can greatly enlarge the Euclidean distance; hence, the system performance can be drastically improved.

Mindfulness Meditation Improves Mood, Quality of Life, and Attention in Adults with Attention Deficit Hyperactivity Disorder

PubMed Central

2015-01-01

Objective. Adults with attention deficit hyperactivity disorder (ADHD) display affective problems and impaired attention. Mood in ADHD can be improved by mindful awareness practices (MAP), but results are mixed regarding the enhancement of attentional performance. Here we evaluated MAP-induced changes in quality of life (QoL), mood, and attention in adult ADHD patients and controls using more measures of attention than prior studies. Methods. Twenty-one ADHD patients and 8 healthy controls underwent 8 weekly MAP sessions; 22 similar patients and 9 controls did not undergo the intervention. Mood and QoL were assessed using validated questionnaires, and attention was evaluated using the Attentional Network Test (ANT) and the Conners Continuous Performance Test (CPT II), before and after intervention. Results. MAP enhanced sustained attention (ANT) and detectability (CPT II) and improved mood and QoL of patients and controls. Conclusion. MAP is a complementary intervention that improves affect and attention of adults with ADHD and controls. PMID:26137496

Mindfulness Meditation Improves Mood, Quality of Life, and Attention in Adults with Attention Deficit Hyperactivity Disorder.

PubMed

Bueno, Viviane Freire; Kozasa, Elisa H; da Silva, Maria Aparecida; Alves, Tânia Maria; Louzã, Mario Rodrigues; Pompéia, Sabine

2015-01-01

Adults with attention deficit hyperactivity disorder (ADHD) display affective problems and impaired attention. Mood in ADHD can be improved by mindful awareness practices (MAP), but results are mixed regarding the enhancement of attentional performance. Here we evaluated MAP-induced changes in quality of life (QoL), mood, and attention in adult ADHD patients and controls using more measures of attention than prior studies. Twenty-one ADHD patients and 8 healthy controls underwent 8 weekly MAP sessions; 22 similar patients and 9 controls did not undergo the intervention. Mood and QoL were assessed using validated questionnaires, and attention was evaluated using the Attentional Network Test (ANT) and the Conners Continuous Performance Test (CPT II), before and after intervention. MAP enhanced sustained attention (ANT) and detectability (CPT II) and improved mood and QoL of patients and controls. MAP is a complementary intervention that improves affect and attention of adults with ADHD and controls.

Impaired cerebral autoregulation and brain injury in newborns with hypoxic-ischemic encephalopathy treated with hypothermia.

PubMed

Massaro, An N; Govindan, R B; Vezina, Gilbert; Chang, Taeun; Andescavage, Nickie N; Wang, Yunfei; Al-Shargabi, Tareq; Metzler, Marina; Harris, Kari; du Plessis, Adre J

2015-08-01

Impaired cerebral autoregulation may contribute to secondary injury in newborns with hypoxic-ischemic encephalopathy (HIE). Continuous, noninvasive assessment of cerebral pressure autoregulation can be achieved with bedside near-infrared spectroscopy (NIRS) and systemic mean arterial blood pressure (MAP) monitoring. This study aimed to evaluate whether impaired cerebral autoregulation measured by NIRS-MAP monitoring during therapeutic hypothermia and rewarming relates to outcome in 36 newborns with HIE. Spectral coherence analysis between NIRS and MAP was used to quantify changes in the duration [pressure passivity index (PPI)] and magnitude (gain) of cerebral autoregulatory impairment. Higher PPI in both cerebral hemispheres and gain in the right hemisphere were associated with neonatal adverse outcomes [death or detectable brain injury by magnetic resonance imaging (MRI), P < 0.001]. NIRS-MAP monitoring of cerebral autoregulation can provide an ongoing physiological biomarker that may help direct care in perinatal brain injury. Copyright © 2015 the American Physiological Society.

Marsh canopy structure changes and the Deepwater Horizon oil spill

USGS Publications Warehouse

Ramsey, Elijah W.; Rangoonwala, Amina; Jones, Cathleen E.

2016-01-01

Marsh canopy structure was mapped yearly from 2009 to 2012 in the Barataria Bay, Louisiana coastal region that was impacted by the 2010 Deepwater Horizon (DWH) oil spill. Based on the previously demonstrated capability of NASA's UAVSAR polarimetric synthetic aperture radar (PolSAR) image data to map Spartina alterniflora marsh canopy structure, structure maps combining the leaf area index (LAI) and leaf angle distribution (LAD, orientation) were constructed for yearly intervals that were directly relatable to the 2010 LAI-LAD classification. The yearly LAI-LAD and LAI difference maps were used to investigate causes for the previously revealed dramatic change in marsh structure from prespill (2009) to postspill (2010, spill cessation), and the occurrence of structure features that exhibited abnormal spatial and temporal patterns. Water level and salinity records showed that freshwater releases used to keep the oil offshore did not cause the rapid growth from 2009 to 2010 in marsh surrounding the inner Bay. Photointerpretation of optical image data determined that interior marsh patches exhibiting rapid change were caused by burns and burn recovery, and that the pattern of 2010 to 2011 LAI decreases in backshore marsh and extending along some tidal channels into the interior marsh were not associated with burns. Instead, the majority of 2010 to 2011 shoreline features aligned with vectors displaying the severity of 2010 shoreline oiling from the DWH spill. Although the association is not conclusive of a causal oil impact, the coexistent pattern is a significant discovery. PolSAR marsh structure mapping provided a unique perspective of marsh biophysical status that enhanced detection of change and monitoring of trends important to management effectiveness.

Mapping asphalt pavement aging and condition using multiple endmember spectral mixture analysis in Beijing, China

NASA Astrophysics Data System (ADS)

Pan, Yifan; Zhang, Xianfeng; Tian, Jie; Jin, Xu; Luo, Lun; Yang, Ke

2017-01-01

Asphalt road reflectance spectra change as pavement ages. This provides the possibility for remote sensing to be used to monitor a change in asphalt pavement conditions. However, the relatively narrow geometry of roads and the relatively coarse spatial resolution of remotely sensed imagery result in mixtures between pavement and adjacent landcovers (e.g., vegetation, buildings, and soil), increasing uncertainties in spectral analysis. To overcome this problem, multiple endmember spectral mixture analysis (MESMA) was used to map the asphalt pavement condition using Worldview-2 satellite imagery in this study. Based on extensive field investigation and in situ measurements, aged asphalt pavements were categorized into four stages-preliminarily aged, moderately aged, heavily aged, and distressed. The spectral characteristics in the first three stages were further analyzed, and a MESMA unmixing analysis was conducted to map these three kinds of pavement conditions from the Worldview-2 image. The results showed that the road pavement conditions could be detected well and mapped with an overall accuracy of 81.71% and Kappa coefficient of 0.77. Finally, a quantitative assessment of the pavement conditions for each road segment in this study area was conducted to inform road maintenance management.

Differentiating therapy-induced leukoencephalopathy from unmyelinated white matter in children treated for acute lymphoblastic leukemia (ALL)

NASA Astrophysics Data System (ADS)

Reddick, Wilburn E.; Glass, John O.; Pui, Ching-Hon

2003-05-01

Reliably detecting subtle therapy-induced leukoencephalopathy in children treated for cancer is a challenging task due to its nearly identical MR properties and location with unmyelinated white matter. T1, T2, PD, and FLAIR images were collected for 44 children aged 1.7-18.7 (median 5.9) years near the start of therapy for ALL. The ICBM atlas and corresponding apriori maps were spatially normalized to each patient and resliced using SPM99 software. A combined imaging set consisting of MR images and WM, GM and CSF apriori maps were then analyzed with a Kohonen Self-Organizing Map. Vectors from hyperintense regions were compared to normal appearing genu vectors from the same patient. Analysis of the distributions of the differences, calculated on T2 and FLAIR images, revealed two distinct groups. The first large group, assumed normal unmyelinated white matter, consisted of 37 patients with changes in FLAIR ranging from 80 to 147 (mean 117-/+17) and T2 ranging from 92 to 217 (mean 144-/+28). The second group, assumed leukoencephalopathy, consisted of seven patients with changes in FLAIR ranging from 154 to 196 (mean 171-/+19) and T2 ranging from 190 to 287 (mean 216-/+33). A threshold was established for both FLAIR (change > 150) and T2 (change > 180).

Visualising phase change in a brushite-based calcium phosphate ceramic

PubMed Central

Bannerman, A.; Williams, R. L.; Cox, S. C.; Grover, L. M.

2016-01-01

The resorption of brushite-based bone cements has been shown to be highly unpredictable, with strong dependence on a number of conditions. One of the major factors is phase transformation, with change to more stable phases such as hydroxyapatite affecting the rate of resorption. Despite its importance, the analysis of phase transformation has been largely undertaken using methods that only detect crystalline composition and give no information on the spatial distribution of the phases. In this study confocal Raman microscopy was used to map cross-sections of brushite cylinders aged in Phosphate Buffered Saline, Foetal Bovine Serum, Dulbecco’s – Minimum Essential Medium (with and without serum). Image maps showed the importance of ageing medium on the phase composition throughout the ceramic structure. When aged without serum, there was dissolution of the brushite phase concomitant to the deposition of octacalcium phosphate (OCP) around the periphery of the sample. The deposition of OCP was detectable within five days and reduced the rate of brushite dissolution from the material. The use of serum, even at a concentration of 10vol% prevented phase transformation. This paper demonstrates the value of confocal Raman microscopy in monitoring phase change in biocements; it also demonstrates the problems with assessing material degradation in non-serum containing media. PMID:27604149

Visualising phase change in a brushite-based calcium phosphate ceramic

NASA Astrophysics Data System (ADS)

Bannerman, A.; Williams, R. L.; Cox, S. C.; Grover, L. M.

2016-09-01

The resorption of brushite-based bone cements has been shown to be highly unpredictable, with strong dependence on a number of conditions. One of the major factors is phase transformation, with change to more stable phases such as hydroxyapatite affecting the rate of resorption. Despite its importance, the analysis of phase transformation has been largely undertaken using methods that only detect crystalline composition and give no information on the spatial distribution of the phases. In this study confocal Raman microscopy was used to map cross-sections of brushite cylinders aged in Phosphate Buffered Saline, Foetal Bovine Serum, Dulbecco’s - Minimum Essential Medium (with and without serum). Image maps showed the importance of ageing medium on the phase composition throughout the ceramic structure. When aged without serum, there was dissolution of the brushite phase concomitant to the deposition of octacalcium phosphate (OCP) around the periphery of the sample. The deposition of OCP was detectable within five days and reduced the rate of brushite dissolution from the material. The use of serum, even at a concentration of 10vol% prevented phase transformation. This paper demonstrates the value of confocal Raman microscopy in monitoring phase change in biocements; it also demonstrates the problems with assessing material degradation in non-serum containing media.

Spotlight SAR interferometry for terrain elevation mapping and interferometric change detection

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

Eichel, P.H.; Ghiglia, D.C.; Jakowatz, C.V. Jr.

1996-02-01

In this report, we employ an approach quite different from any previous work; we show that a new methodology leads to a simpler and clearer understanding of the fundamental principles of SAR interferometry. This methodology also allows implementation of an important collection mode that has not been demonstrated to date. Specifically, we introduce the following six new concepts for the processing of interferometric SAR (INSAR) data: (1) processing using spotlight mode SAR imaging (allowing ultra-high resolution), as opposed to conventional strip-mapping techniques; (2) derivation of the collection geometry constraints required to avoid decorrelation effects in two-pass INSAR; (3) derivation ofmore » maximum likelihood estimators for phase difference and the change parameter employed in interferometric change detection (ICD); (4) processing for the two-pass case wherein the platform ground tracks make a large crossing angle; (5) a robust least-squares method for two-dimensional phase unwrapping formulated as a solution to Poisson`s equation, instead of using traditional path-following techniques; and (6) the existence of a simple linear scale factor that relates phase differences between two SAR images to terrain height. We show both theoretical analysis, as well as numerous examples that employ real SAR collections to demonstrate the innovations listed above.« less

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

PubMed

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

2017-09-01

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

Quantitative Mapping of Human Cartilage at 3.0T

PubMed Central

Wang, Ligong; Regatte, Ravinder R.

2014-01-01

Rationale and Objectives The objectives of this study were to measure the parallel changes of transverse relaxation times (T2), spin-lattice relaxation time in the rotating frame (T1ρ), and the delayed gadolinium-enhanced magnetic resonance imaging of cartilage (dGEMRIC)-T1 mapping of human knee cartilage in detecting cartilage degeneration at 3.0T. Materials and Methods Healthy volunteers (n = 10, mean age 35.6 years) and patients (n = 10, mean age 65 years) with early knee osteoarthritis (OA) were scanned at 3.0T MR using an 8-channel phased array knee coil (transmit–receive). Quantitative assessment of T2, T1ρ, and dGEMRIC-T1 values (global and regional) were correlated between asymptomatic subjects and patients with OA. Results The average T2 (39 ± 2 milliseconds [mean ± standard deviation] vs. 47 ± 6 milliseconds, P < .0007) and T1ρ (48 ± 3 vs. 62 ± 8 milliseconds, P < .0002) values were all markedly increased in all patients with OA when compared to healthy volunteers. The average dGEMRIC-T1 (1244 ± 134 vs. 643 ± 227 milliseconds, P < .000002) value was sharply decreased after intravenous administration of gadolinium contrast agent in all patients with OA. Conclusions The research results showed that all the T2, T1ρ, and dGEMRIC-T1 relaxation times varied with the cartilage degeneration. The dGEMRIC-T1 and T1ρ relaxation times seem to be more sensitive than T2 in detecting early cartilage degeneration. The preliminary study demonstrated that the early biochemical changes in knee osteoarthritic patients could be detected noninvasively in in vivo using T1ρ and dGEMRIC-T1 mapping. PMID:24594416

Multi-Temporal Multi-Sensor Analysis of Urbanization and Environmental/Climate Impact in China for Sustainable Urban Development

NASA Astrophysics Data System (ADS)

Ban, Yifang; Gong, Peng; Gamba, Paolo; Taubenbock, Hannes; Du, Peijun

2016-08-01

The overall objective of this research is to investigate multi-temporal, multi-scale, multi-sensor satellite data for analysis of urbanization and environmental/climate impact in China to support sustainable planning. Multi- temporal multi-scale SAR and optical data have been evaluated for urban information extraction using innovative methods and algorithms, including KTH- Pavia Urban Extractor, Pavia UEXT, and an "exclusion- inclusion" framework for urban extent extraction, and KTH-SEG, a novel object-based classification method for detailed urban land cover mapping. Various pixel- based and object-based change detection algorithms were also developed to extract urban changes. Several Chinese cities including Beijing, Shanghai and Guangzhou are selected as study areas. Spatio-temporal urbanization patterns and environmental impact at regional, metropolitan and city core were evaluated through ecosystem service, landscape metrics, spatial indices, and/or their combinations. The relationship between land surface temperature and land-cover classes was also analyzed.The urban extraction results showed that urban areas and small towns could be well extracted using multitemporal SAR data with the KTH-Pavia Urban Extractor and UEXT. The fusion of SAR data at multiple scales from multiple sensors was proven to improve urban extraction. For urban land cover mapping, the results show that the fusion of multitemporal SAR and optical data could produce detailed land cover maps with improved accuracy than that of SAR or optical data alone. Pixel-based and object-based change detection algorithms developed with the project were effective to extract urban changes. Comparing the urban land cover results from mulitemporal multisensor data, the environmental impact analysis indicates major losses for food supply, noise reduction, runoff mitigation, waste treatment and global climate regulation services through landscape structural changes in terms of decreases in service area, edge contamination and fragmentation. In terms ofclimate impact, the results indicate that land surface temperature can be related to land use/land cover classes.

Does MRI scan acceleration affect power to track brain change?

PubMed

Ching, Christopher R K; Hua, Xue; Hibar, Derrek P; Ward, Chadwick P; Gunter, Jeffrey L; Bernstein, Matt A; Jack, Clifford R; Weiner, Michael W; Thompson, Paul M

2015-01-01

The Alzheimer's Disease Neuroimaging Initiative recently implemented accelerated T1-weighted structural imaging to reduce scan times. Faster scans may reduce study costs and patient attrition by accommodating people who cannot tolerate long scan sessions. However, little is known about how scan acceleration affects the power to detect longitudinal brain change. Using tensor-based morphometry, no significant difference was detected in numerical summaries of atrophy rates from accelerated and nonaccelerated scans in subgroups of patients with Alzheimer's disease, early or late mild cognitive impairment, or healthy controls over a 6- and 12-month scan interval. Whole-brain voxelwise mapping analyses revealed some apparent regional differences in 6-month atrophy rates when comparing all subjects irrespective of diagnosis (n = 345). No such whole-brain difference was detected for the 12-month scan interval (n = 156). Effect sizes for structural brain changes were not detectably different in accelerated versus nonaccelerated data. Scan acceleration may influence brain measures but has minimal effects on tensor-based morphometry-derived atrophy measures, at least over the 6- and 12-month intervals examined here. Copyright © 2015 Elsevier Inc. All rights reserved.

GPU-BSM: A GPU-Based Tool to Map Bisulfite-Treated Reads

PubMed Central

Manconi, Andrea; Orro, Alessandro; Manca, Emanuele; Armano, Giuliano; Milanesi, Luciano

2014-01-01

Cytosine DNA methylation is an epigenetic mark implicated in several biological processes. Bisulfite treatment of DNA is acknowledged as the gold standard technique to study methylation. This technique introduces changes in the genomic DNA by converting cytosines to uracils while 5-methylcytosines remain nonreactive. During PCR amplification 5-methylcytosines are amplified as cytosine, whereas uracils and thymines as thymine. To detect the methylation levels, reads treated with the bisulfite must be aligned against a reference genome. Mapping these reads to a reference genome represents a significant computational challenge mainly due to the increased search space and the loss of information introduced by the treatment. To deal with this computational challenge we devised GPU-BSM, a tool based on modern Graphics Processing Units. Graphics Processing Units are hardware accelerators that are increasingly being used successfully to accelerate general-purpose scientific applications. GPU-BSM is a tool able to map bisulfite-treated reads from whole genome bisulfite sequencing and reduced representation bisulfite sequencing, and to estimate methylation levels, with the goal of detecting methylation. Due to the massive parallelization obtained by exploiting graphics cards, GPU-BSM aligns bisulfite-treated reads faster than other cutting-edge solutions, while outperforming most of them in terms of unique mapped reads. PMID:24842718

Mapping Neglected Swimming Pools from Satellite Data for Urban Vector Control

NASA Astrophysics Data System (ADS)

Barker, C. M.; Melton, F. S.; Reisen, W. K.

2010-12-01

Neglected swimming pools provide suitable breeding habit for mosquitoes, can contain thousands of mosquito larvae, and present both a significant nuisance and public health risk due to their inherent proximity to urban and suburban populations. The rapid increase and sustained rate of foreclosures in California associated with the recent recession presents a challenge for vector control districts seeking to identify, treat, and monitor neglected pools. Commercial high resolution satellite imagery offers some promise for mapping potential neglected pools, and for mapping pools for which routine maintenance has been reestablished. We present progress on unsupervised classification techniques for mapping both neglected pools and clean pools using high resolution commercial satellite data and discuss the potential uses and limitations of this data source in support of vector control efforts. An unsupervised classification scheme that utilizes image segmentation, band thresholds, and a change detection approach was implemented for sample regions in Coachella Valley, CA and the greater Los Angeles area. Comparison with field data collected by vector control personal was used to assess the accuracy of the estimates. The results suggest that the current system may provide some utility for early detection, or cost effective and time efficient annual monitoring, but additional work is required to address spectral and spatial limitations of current commercial satellite sensors for this purpose.

Evaluation of focal cartilage lesions of the knee using MRI T2 mapping and delayed Gadolinium Enhanced MRI of Cartilage (dGEMRIC).

PubMed

Årøen, Asbjørn; Brøgger, Helga; Røtterud, Jan Harald; Sivertsen, Einar Andreas; Engebretsen, Lars; Risberg, May Arna

2016-02-11

Assessment of degenerative changes of the cartilage is important in knee cartilage repair surgery. Magnetic Resonance Imaging (MRI) T2 mapping and delayed Gadolinium Enhanced MRI of Cartilage (dGEMRIC) are able to detect early degenerative changes. The hypothesis of the study was that cartilage surrounding a focal cartilage lesion in the knee does not possess degenerative changes. Twenty-eight consecutive patients included in a randomized controlled trial on cartilage repair were evaluated using MRI T2 mapping and dGEMRIC before cartilage treatment was initiated. Inclusion was based on disabling knee problems (Lysholm score of ≤ 75) due to an arthroscopically verified focal femoral condyle cartilage lesion. Furthermore, no major malalignments or knee ligament injuries were accepted. Mean patient age was 33 ± 9.6 years, and the mean duration of knee symptoms was 49 ± 60 months. The MRI T2 mapping and the dGEMRIC measurements were performed at three standardized regions of interest (ROIs) at the medial and lateral femoral condyle, avoiding the cartilage lesion The MRI T2 mapping of the cartilage did not demonstrate significant differences between condyles with or without cartilage lesions. The dGEMRIC results did not show significantly lower values of the affected condyle compared with the opposite condyle and the contra-lateral knee in any of the ROIs. The intraclass correlation coefficient (ICC) of the dGEMRIC readings was 0.882. The MRI T2 mapping and the dGEMRIC confirmed the arthroscopic findings that normal articular cartilage surrounded the cartilage lesion, reflecting normal variation in articular cartilage quality. NCT00885729 , registered April 17 2009.

Ion Trapping with Fast-Response Ion-Selective Microelectrodes Enhances Detection of Extracellular Ion Channel Gradients

PubMed Central

Messerli, Mark A.; Collis, Leon P.; Smith, Peter J.S.

2009-01-01

Previously, functional mapping of channels has been achieved by measuring the passage of net charge and of specific ions with electrophysiological and intracellular fluorescence imaging techniques. However, functional mapping of ion channels using extracellular ion-selective microelectrodes has distinct advantages over the former methods. We have developed this method through measurement of extracellular K+ gradients caused by efflux through Ca2+-activated K+ channels expressed in Chinese hamster ovary cells. We report that electrodes constructed with short columns of a mechanically stable K+-selective liquid membrane respond quickly and measure changes in local [K+] consistent with a diffusion model. When used in close proximity to the plasma membrane (<4 μm), the ISMs pose a barrier to simple diffusion, creating an ion trap. The ion trap amplifies the local change in [K+] without dramatically changing the rise or fall time of the [K+] profile. Measurement of extracellular K+ gradients from activated rSlo channels shows that rapid events, 10–55 ms, can be characterized. This method provides a noninvasive means for functional mapping of channel location and density as well as for characterizing the properties of ion channels in the plasma membrane. PMID:19217875

Land use mapping and modelling for the Phoenix Quadrangle

NASA Technical Reports Server (NTRS)

Place, J. L. (Principal Investigator)

1974-01-01

The author has identified the following significant results. Changes in the land use in the Phoenix (1:250,000 scale) Quadrangle in Arizona have been mapped using only the images from ERTS-1, tending to verify the utility of a land use classification system proposed for use with ERTS images. Seasonal changes were studied on successive ERTS-1 images, particularly large scale color composite transparencies for August, October, February, and May, and this seasonal variation aided delineation of land use boundaries. Types of equipment used to aid interpretation included color additive viewer, a twenty-power magnifier, a density slicer, and a diazo copy machine. A Zoom Transfer Scope was used for scale and photogrammetric adjustments. Types of changes detected have been: (1) cropland or rangeland developed as new residential areas; (2) rangeland converted to new cropland or to new reservoirs; and (3) possibly new activity by the mining industries. A map of land use previously compiled from air photos was updated in this manner. ERTS-1 images complemented air photos: the photos gave detail on a one-shot basis; the ERTS-1 images provided currency and revealed seasonal variation in vegetation which aided interpretation of land use.

Evaluating online data of water quality changes in a pilot drinking water distribution system with multivariate data exploration methods.

PubMed

Mustonen, Satu M; Tissari, Soile; Huikko, Laura; Kolehmainen, Mikko; Lehtola, Markku J; Hirvonen, Arja

2008-05-01

The distribution of drinking water generates soft deposits and biofilms in the pipelines of distribution systems. Disturbances in water distribution can detach these deposits and biofilms and thus deteriorate the water quality. We studied the effects of simulated pressure shocks on the water quality with online analysers. The study was conducted with copper and composite plastic pipelines in a pilot distribution system. The online data gathered during the study was evaluated with Self-Organising Map (SOM) and Sammon's mapping, which are useful methods in exploring large amounts of multivariate data. The objective was to test the usefulness of these methods in pinpointing the abnormal water quality changes in the online data. The pressure shocks increased temporarily the number of particles, turbidity and electrical conductivity. SOM and Sammon's mapping were able to separate these situations from the normal data and thus make those visible. Therefore these methods make it possible to detect abrupt changes in water quality and thus to react rapidly to any disturbances in the system. These methods are useful in developing alert systems and predictive applications connected to online monitoring.

Footprint Map Partitioning Using Airborne Laser Scanning Data

NASA Astrophysics Data System (ADS)

Xiong, B.; Oude Elberink, S.; Vosselman, G.

2016-06-01

Nowadays many cities and countries are creating their 3D building models for a better daily management and smarter decision making. The newly created 3D models are required to be consistent with existing 2D footprint maps. Thereby the 2D maps are usually combined with height data for the task of 3D reconstruction. Many buildings are often composed by parts that are discontinuous over height. Building parts can be reconstructed independently and combined into a complete building. Therefore, most of the state-of-the-art work on 3D building reconstruction first decomposes a footprint map into parts. However, those works usually change the footprint maps for easier partitioning and cannot detect building parts that are fully inside the footprint polygon. In order to solve those problems, we introduce two methodologies, one more dependent on height data, and the other one more dependent on footprints. We also experimentally evaluate the two methodologies and compare their advantages and disadvantages. The experiments use Airborne Laser Scanning (ALS) data and two vector maps, one with 1:10,000 scale and another one with 1:500 scale.

Rapid detection methods for viable Mycobacterium avium subspecies paratuberculosis in milk and cheese.

PubMed

Botsaris, George; Slana, Iva; Liapi, Maria; Dodd, Christine; Economides, Constantinos; Rees, Catherine; Pavlik, Ivo

2010-07-31

Mycobacterium avium subsp. paratuberculosis (MAP) may have a role in the development of Crohn's disease in humans via the consumption of contaminated milk and milk products. Detection of MAP from milk and dairy products has been reported from countries on the European continent, Argentina, the UK and Australia. In this study three different methods (quantitative real time PCR, combined phage IS900 PCR and conventional cultivation) were used to detect the presence of MAP in bulk tank milk (BTM) and cheese originating from sheep, goat and mixed milks from farms and products in Cyprus. During the first survey the presence of MAP was detected in 63 (28.6%) of cows' BTM samples by quantitative real time PCR. A second survey of BTM used a new combined phage IS900 PCR assay, and in this case MAP was detected in 50 (22.2%) samples showing a good level of agreement by both methods. None of the herds tested were known to be affected by Johne's disease and the presence of viable MAP was confirmed by conventional culture in only two cases of cows BTM. This suggests that either rapid method used is more sensitive than the conventional culture when testing raw milk samples for MAP. The two isolates recovered from BTM were identified by IS1311 PCR REA as cattle and sheep strains, respectively. In contrast when cheese samples were tested, MAP DNA was detected by quantitative real time PCR in seven (25.0%) samples (n=28). However no viable MAP was detected when either the combined phage IS900 PCR or conventional culture methods were used. Copyright 2010 Elsevier B.V. All rights reserved.

Detecting post-fire salvage logging with Landsat change maps and national fire survey data

Treesearch

Todd A. Schroeder; Michael A. Wulder; Sean P. Healey; Gretchen G. Moisen

2012-01-01

In Canadian boreal forests, wildfire is the predominant agent of natural disturbance often with millions of hectares burning annually. In addition to fire, nearly one quarter of Canada's boreal forest is also managed for industrial wood production. Post-fire logging (or salvage harvesting) is increasingly used to minimize economic losses from fire, notwithstanding...

Long-term fragmentation effects on the distribution and dynamics of canopy gaps in a tropical montane forest

Treesearch

Nicholas R. Vaughn; Gregory P. Asner; Christian P. Giardina

2015-01-01

Fragmentation alters forest canopy structure through various mechanisms, which in turn drive subsequent changes to biogeochemical processes and biological diversity. Using repeated airborne LiDAR (Light Detection and Ranging) mappings, we investigated the size distribution and dynamics of forest canopy gaps across a topical montane forest landscape in Hawaii naturally...

Hierarchical Kohonenen net for anomaly detection in network security.

PubMed

Sarasamma, Suseela T; Zhu, Qiuming A; Huff, Julie

2005-04-01

A novel multilevel hierarchical Kohonen Net (K-Map) for an intrusion detection system is presented. Each level of the hierarchical map is modeled as a simple winner-take-all K-Map. One significant advantage of this multilevel hierarchical K-Map is its computational efficiency. Unlike other statistical anomaly detection methods such as nearest neighbor approach, K-means clustering or probabilistic analysis that employ distance computation in the feature space to identify the outliers, our approach does not involve costly point-to-point computation in organizing the data into clusters. Another advantage is the reduced network size. We use the classification capability of the K-Map on selected dimensions of data set in detecting anomalies. Randomly selected subsets that contain both attacks and normal records from the KDD Cup 1999 benchmark data are used to train the hierarchical net. We use a confidence measure to label the clusters. Then we use the test set from the same KDD Cup 1999 benchmark to test the hierarchical net. We show that a hierarchical K-Map in which each layer operates on a small subset of the feature space is superior to a single-layer K-Map operating on the whole feature space in detecting a variety of attacks in terms of detection rate as well as false positive rate.

Ten Years of Vegetation Change in Northern California Marshlands Detected using Landsat Satellite Image Analysis

NASA Technical Reports Server (NTRS)

Potter, Christopher

2013-01-01

The Landsat Ecosystem Disturbance Adaptive Processing System (LEDAPS) methodology was applied to detected changes in perennial vegetation cover at marshland sites in Northern California reported to have undergone restoration between 1999 and 2009. Results showed extensive contiguous areas of restored marshland plant cover at 10 of the 14 sites selected. Gains in either woody shrub cover and/or from recovery of herbaceous cover that remains productive and evergreen on a year-round basis could be mapped out from the image results. However, LEDAPS may not be highly sensitive changes in wetlands that have been restored mainly with seasonal herbaceous cover (e.g., vernal pools), due to the ephemeral nature of the plant greenness signal. Based on this evaluation, the LEDAPS methodology would be capable of fulfilling a pressing need for consistent, continual, low-cost monitoring of changes in marshland ecosystems of the Pacific Flyway.

Monitoring Farmland Loss Caused by Urbanization in Beijing from Modis Time Series Using Hierarchical Hidden Markov Model

NASA Astrophysics Data System (ADS)

Yuan, Y.; Meng, Y.; Chen, Y. X.; Jiang, C.; Yue, A. Z.

2018-04-01

In this study, we proposed a method to map urban encroachment onto farmland using satellite image time series (SITS) based on the hierarchical hidden Markov model (HHMM). In this method, the farmland change process is decomposed into three hierarchical levels, i.e., the land cover level, the vegetation phenology level, and the SITS level. Then a three-level HHMM is constructed to model the multi-level semantic structure of farmland change process. Once the HHMM is established, a change from farmland to built-up could be detected by inferring the underlying state sequence that is most likely to generate the input time series. The performance of the method is evaluated on MODIS time series in Beijing. Results on both simulated and real datasets demonstrate that our method improves the change detection accuracy compared with the HMM-based method.

Automated kidney detection for 3D ultrasound using scan line searching

NASA Astrophysics Data System (ADS)

Noll, Matthias; Nadolny, Anne; Wesarg, Stefan

2016-04-01

Ultrasound (U/S) is a fast and non-expensive imaging modality that is used for the examination of various anatomical structures, e.g. the kidneys. One important task for automatic organ tracking or computer-aided diagnosis is the identification of the organ region. During this process the exact information about the transducer location and orientation is usually unavailable. This renders the implementation of such automatic methods exceedingly challenging. In this work we like to introduce a new automatic method for the detection of the kidney in 3D U/S images. This novel technique analyses the U/S image data along virtual scan lines. Here, characteristic texture changes when entering and leaving the symmetric tissue regions of the renal cortex are searched for. A subsequent feature accumulation along a second scan direction produces a 2D heat map of renal cortex candidates, from which the kidney location is extracted in two steps. First, the strongest candidate as well as its counterpart are extracted by heat map intensity ranking and renal cortex size analysis. This process exploits the heat map gap caused by the renal pelvis region. Substituting the renal pelvis detection with this combined cortex tissue feature increases the detection robustness. In contrast to model based methods that generate characteristic pattern matches, our method is simpler and therefore faster. An evaluation performed on 61 3D U/S data sets showed, that in 55 cases showing none or minor shadowing the kidney location could be correctly identified.

Quantified elasticity mapping of ocular tissue using acoustic radiation force optical coherence elastography (Conference Presentation)

NASA Astrophysics Data System (ADS)

Qu, Yueqiao; He, Youmin; Zhang, Yi; Ma, Teng; Zhu, Jiang; Miao, Yusi; Dai, Cuixia; Silverman, Ronald; Humayun, Mark S.; Zhou, Qifa; Chen, Zhongping

2017-02-01

Age-related macular degeneration and keratoconus are two ocular diseases occurring in the posterior and anterior eye, respectively. In both conditions, the mechanical elasticity of the respective tissues changes during the early onset of disease. It is necessary to detect these differences and treat the diseases in their early stages to provide proper treatment. Acoustic radiation force optical coherence elastography is a method of elasticity mapping using confocal ultrasound waves for excitation and Doppler optical coherence tomography for detection. We report on an ARF-OCE system that uses modulated compression wave based excitation signals, and detects the spatial and frequency responses of the tissue. First, all components of the system is synchronized and triggered such that the signal is consistent between frames. Next, phantom studies are performed to validate and calibrate the relationship between the resonance frequency and the Young's modulus. Then the frequency responses of the anterior and posterior eye are detected for porcine and rabbit eyes, and the results correlated to the elasticity. Finally, spatial elastograms are obtained for a porcine retina. Layer segmentation and analysis is performed and correlated to the histology of the retina, where five distinct layers are recognized. The elasticities of the tissue layers will be quantified according to the mean thickness and displacement response for the locations on the retina. This study is a stepping stone to future in-vivo animal studies, where the elastic modulus of the ocular tissue can be quantified and mapped out accordingly.

The Attentional Boost Effect: Transient increases in attention to one task enhance performance in a second task.

PubMed

Swallow, Khena M; Jiang, Yuhong V

2010-04-01

Recent work on event perception suggests that perceptual processing increases when events change. An important question is how such changes influence the way other information is processed, particularly during dual-task performance. In this study, participants monitored a long series of distractor items for an occasional target as they simultaneously encoded unrelated background scenes. The appearance of an occasional target could have two opposite effects on the secondary task: It could draw attention away from the second task, or, as a change in the ongoing event, it could improve secondary task performance. Results were consistent with the second possibility. Memory for scenes presented simultaneously with the targets was better than memory for scenes that preceded or followed the targets. This effect was observed when the primary detection task involved visual feature oddball detection, auditory oddball detection, and visual color-shape conjunction detection. It was eliminated when the detection task was omitted, and when it required an arbitrary response mapping. The appearance of occasional, task-relevant events appears to trigger a temporal orienting response that facilitates processing of concurrently attended information (Attentional Boost Effect). Copyright 2009 Elsevier B.V. All rights reserved.

The Attentional Boost Effect: Transient Increases in Attention to One Task Enhance Performance in a Second Task

PubMed Central

Swallow, Khena M.; Jiang, Yuhong V.

2009-01-01

Recent work on event perception suggests that perceptual processing increases when events change. An important question is how such changes influence the way other information is processed, particularly during dual-task performance. In this study, participants monitored a long series of distractor items for an occasional target as they simultaneously encoded unrelated background scenes. The appearance of an occasional target could have two opposite effects on the secondary task: It could draw attention away from the second task, or, as a change in the ongoing event, it could improve secondary task performance. Results were consistent with the second possibility. Memory for scenes presented simultaneously with the targets was better than memory for scenes that preceded or followed the targets. This effect was observed when the primary detection task involved visual feature oddball detection, auditory oddball detection, and visual color-shape conjunction detection. It was eliminated when the detection task was omitted, and when it required an arbitrary response mapping. The appearance of occasional, task-relevant events appears to trigger a temporal orienting response that facilitates processing of concurrently attended information (Attentional Boost Effect). PMID:20080232

Mycobacterium avium Subspecies paratuberculosis: Human Exposure through Environmental and Domestic Aerosols

PubMed Central

Rhodes, Glenn; Richardson, Hollian; Hermon-Taylor, John; Weightman, Andrew; Higham, Andrew; Pickup, Roger

2014-01-01

Mycobacterium avium subspecies paratuberculosis (Map) causes Johne’s disease in animals and is significantly associated with Crohn’s disease (CD) in humans. Our previous studies have shown Map to be present in U.K. rivers due to land deposition from chronic livestock infection and runoff driven by rainfall. The epidemiology of CD in Cardiff showed a significant association with the River Taff, in which Map can be detected on a regular basis. We have previously hypothesized that aerosols from the river might influence the epidemiology of CD. In this preliminary study, we detected Map by quantitative PCR in one of five aerosol samples collected above the River Taff. In addition, we examined domestic showers from different regions in the U.K. and detected Map in three out of 30 independent samples. In detecting Map in river aerosols and those from domestic showers, this is the first study to provide evidence that aerosols are an exposure route for Map to humans and may play a role in the epidemiology of CD. PMID:25438013

Impervious surfaces mapping using high resolution satellite imagery

NASA Astrophysics Data System (ADS)

Shirmeen, Tahmina

In recent years, impervious surfaces have emerged not only as an indicator of the degree of urbanization, but also as an indicator of environmental quality. As impervious surface area increases, storm water runoff increases in velocity, quantity, temperature and pollution load. Any of these attributes can contribute to the degradation of natural hydrology and water quality. Various image processing techniques have been used to identify the impervious surfaces, however, most of the existing impervious surface mapping tools used moderate resolution imagery. In this project, the potential of standard image processing techniques to generate impervious surface data for change detection analysis using high-resolution satellite imagery was evaluated. The city of Oxford, MS was selected as the study site for this project. Standard image processing techniques, including Normalized Difference Vegetation Index (NDVI), Principal Component Analysis (PCA), a combination of NDVI and PCA, and image classification algorithms, were used to generate impervious surfaces from multispectral IKONOS and QuickBird imagery acquired in both leaf-on and leaf-off conditions. Accuracy assessments were performed, using truth data generated by manual classification, with Kappa statistics and Zonal statistics to select the most appropriate image processing techniques for impervious surface mapping. The performance of selected image processing techniques was enhanced by incorporating Soil Brightness Index (SBI) and Greenness Index (GI) derived from Tasseled Cap Transformed (TCT) IKONOS and QuickBird imagery. A time series of impervious surfaces for the time frame between 2001 and 2007 was made using the refined image processing techniques to analyze the changes in IS in Oxford. It was found that NDVI and the combined NDVI--PCA methods are the most suitable image processing techniques for mapping impervious surfaces in leaf-off and leaf-on conditions respectively, using high resolution multispectral imagery. It was also found that IS data generated by these techniques can be refined by removing the conflicting dry soil patches using SBI and GI obtained from TCT of the same imagery used for IS data generation. The change detection analysis of the IS time series shows that Oxford experienced the major changes in IS from the year 2001 to 2004 and 2006 to 2007.

Novel 3D ultrasound image-based biomarkers based on a feature selection from a 2D standardized vessel wall thickness map: a tool for sensitive assessment of therapies for carotid atherosclerosis

NASA Astrophysics Data System (ADS)

Chiu, Bernard; Li, Bing; Chow, Tommy W. S.

2013-09-01

With the advent of new therapies and management strategies for carotid atherosclerosis, there is a parallel need for measurement tools or biomarkers to evaluate the efficacy of these new strategies. 3D ultrasound has been shown to provide reproducible measurements of plaque area/volume and vessel wall volume. However, since carotid atherosclerosis is a focal disease that predominantly occurs at bifurcations, biomarkers based on local plaque change may be more sensitive than global volumetric measurements in demonstrating efficacy of new therapies. The ultimate goal of this paper is to develop a biomarker that is based on the local distribution of vessel-wall-plus-plaque thickness change (VWT-Change) that has occurred during the course of a clinical study. To allow comparison between different treatment groups, the VWT-Change distribution of each subject must first be mapped to a standardized domain. In this study, we developed a technique to map the 3D VWT-Change distribution to a 2D standardized template. We then applied a feature selection technique to identify regions on the 2D standardized map on which subjects in different treatment groups exhibit greater difference in VWT-Change. The proposed algorithm was applied to analyse the VWT-Change of 20 subjects in a placebo-controlled study of the effect of atorvastatin (Lipitor). The average VWT-Change for each subject was computed (i) over all points in the 2D map and (ii) over feature points only. For the average computed over all points, 97 subjects per group would be required to detect an effect size of 25% that of atorvastatin in a six-month study. The sample size is reduced to 25 subjects if the average were computed over feature points only. The introduction of this sensitive quantification technique for carotid atherosclerosis progression/regression would allow many proof-of-principle studies to be performed before a more costly and longer study involving a larger population is held to confirm the treatment efficacy.

Detecting Small-Scale Topographic Changes and Relict Geomorphic Features on Barrier Islands Using SAR

NASA Technical Reports Server (NTRS)

Gibeaut, James C.; Crawford, Melba M.; Gutierrez, Roberto; Slatton, K. Clint; Neuenschwander, Amy L.; Ricard, Michael R.

1997-01-01

The shapes and elevations of barrier islands may change dramatically over a short period of time during a storm. Coastal scientists and engineers, however, are currently unable to measure these changes occurring over an entire barrier island at once. This three-year project, which is funded by NASA and jointly conducted by the Bureau of Economic Geology and the Center for Space Research at The University of Texas at Austin, is designed to overcome this problem by developing the use of interferometry from airborne synthetic aperture radar (AIRSAR) to measure coastal topography and to detect storm-induced changes in topography. Surrogate measures of topography observed in multiband, fully polarimetric AIRSAR (This type of data are now referred to as POLSAR data.) are also being investigated. Digital elevation models (DEM) of Galveston Island and Bolivar Peninsula, Texas obtained with Topographic SAR (TOPSAR) are compared with measurements by Global Positioning System (GPS) ground surveys and electronic total station surveys. In addition to topographic mapping, this project is evaluating the use of POLSAR to detect old features such as storm scarps, storm channels, former tidal inlets, and beach ridges that have been obscured by vegetation, erosion, deposition, and artificial filling. We have also expanded the work from the original proposal to include the mapping of coastal wetland vegetation and depositional environments. Methods developed during this project will provide coastal geologists with an unprecedented tool for monitoring and understanding barrier island systems. This understanding will improve overall coastal management policies and will help reduce the effects of natural and man-induced coastal hazards. This report summarizes our accomplishments during the second year of the study. Also included is a discussion of our planned activities for year 3 and a revised budget.

Land cover change monitoring within the east central Louisiana study site: A case for large area surveys with LANDSAT multispectral scanner data

NASA Technical Reports Server (NTRS)

Burns, G. S.

1983-01-01

Results established for four digital procedures developed for characterizing the radiometric changes between multidate LANDSAT spectral data sets into meaningful measures of land cover/use dynamics are documented. Each technique's performance was contrasted against digitized land use change maps, which were produced from contemporaneous, retrospective aerophoto coverage, in a cell by cell comparison over a one half by one degree area in east central Louisiana as a standard for comparison. The four techniques identify from 10.5 to 13.0% loss in area of forestland in a five year period; however, they differ more by how accurately this amount of change is distributed, the need for ancillary ground truth, and amount of usable information that is extractable. All require some method of digitally co-registering the two data sets. All are capable of providing tabular statistics as well as map products. Two are capable of detecting changes and identifying their locations. The other two, in addition to this, provide information to qualify land cover conditions at each end of the study interval.

Spatial early warning signals in a lake manipulation

USGS Publications Warehouse

Butitta, Vince L.; Carpenter, Stephen R.; Loken, Luke; Pace, Michael L.; Stanley, Emily H.

2017-01-01

Rapid changes in state have been documented for many of Earth's ecosystems. Despite a growing toolbox of methods for detecting declining resilience or early warning indicators (EWIs) of ecosystem transitions, these methods have rarely been evaluated in whole-ecosystem trials using reference ecosystems. In this study, we experimentally tested EWIs of cyanobacteria blooms based on changes in the spatial structure of a lake. We induced a cyanobacteria bloom by adding nutrients to an experimental lake and mapped fine-resolution spatial patterning of cyanobacteria using a mobile sensor platform. Prior to the bloom, we detected theoretically predicted spatial EWIs based on variance and spatial autocorrelation, as well as a new index based on the extreme values. Changes in EWIs were not discernible in an unenriched reference lake. Despite the fluid environment of a lake where spatial heterogeneity driven by biological processes may be overwhelmed by physical mixing, spatial EWIs detected an approaching bloom suggesting the utility of spatial metrics for signaling ecological thresholds.

Stereo-vision-based terrain mapping for off-road autonomous navigation

NASA Astrophysics Data System (ADS)

Rankin, Arturo L.; Huertas, Andres; Matthies, Larry H.

2009-05-01

Successful off-road autonomous navigation by an unmanned ground vehicle (UGV) requires reliable perception and representation of natural terrain. While perception algorithms are used to detect driving hazards, terrain mapping algorithms are used to represent the detected hazards in a world model a UGV can use to plan safe paths. There are two primary ways to detect driving hazards with perception sensors mounted to a UGV: binary obstacle detection and traversability cost analysis. Binary obstacle detectors label terrain as either traversable or non-traversable, whereas, traversability cost analysis assigns a cost to driving over a discrete patch of terrain. In uncluttered environments where the non-obstacle terrain is equally traversable, binary obstacle detection is sufficient. However, in cluttered environments, some form of traversability cost analysis is necessary. The Jet Propulsion Laboratory (JPL) has explored both approaches using stereo vision systems. A set of binary detectors has been implemented that detect positive obstacles, negative obstacles, tree trunks, tree lines, excessive slope, low overhangs, and water bodies. A compact terrain map is built from each frame of stereo images. The mapping algorithm labels cells that contain obstacles as nogo regions, and encodes terrain elevation, terrain classification, terrain roughness, traversability cost, and a confidence value. The single frame maps are merged into a world map where temporal filtering is applied. In previous papers, we have described our perception algorithms that perform binary obstacle detection. In this paper, we summarize the terrain mapping capabilities that JPL has implemented during several UGV programs over the last decade and discuss some challenges to building terrain maps with stereo range data.

Stereo Vision Based Terrain Mapping for Off-Road Autonomous Navigation

NASA Technical Reports Server (NTRS)

Rankin, Arturo L.; Huertas, Andres; Matthies, Larry H.

2009-01-01

Successful off-road autonomous navigation by an unmanned ground vehicle (UGV) requires reliable perception and representation of natural terrain. While perception algorithms are used to detect driving hazards, terrain mapping algorithms are used to represent the detected hazards in a world model a UGV can use to plan safe paths. There are two primary ways to detect driving hazards with perception sensors mounted to a UGV: binary obstacle detection and traversability cost analysis. Binary obstacle detectors label terrain as either traversable or non-traversable, whereas, traversability cost analysis assigns a cost to driving over a discrete patch of terrain. In uncluttered environments where the non-obstacle terrain is equally traversable, binary obstacle detection is sufficient. However, in cluttered environments, some form of traversability cost analysis is necessary. The Jet Propulsion Laboratory (JPL) has explored both approaches using stereo vision systems. A set of binary detectors has been implemented that detect positive obstacles, negative obstacles, tree trunks, tree lines, excessive slope, low overhangs, and water bodies. A compact terrain map is built from each frame of stereo images. The mapping algorithm labels cells that contain obstacles as no-go regions, and encodes terrain elevation, terrain classification, terrain roughness, traversability cost, and a confidence value. The single frame maps are merged into a world map where temporal filtering is applied. In previous papers, we have described our perception algorithms that perform binary obstacle detection. In this paper, we summarize the terrain mapping capabilities that JPL has implemented during several UGV programs over the last decade and discuss some challenges to building terrain maps with stereo range data.

Change and Anomaly Detection in Real-Time GPS Data

NASA Astrophysics Data System (ADS)

Granat, R.; Pierce, M.; Gao, X.; Bock, Y.

2008-12-01

The California Real-Time Network (CRTN) is currently generating real-time GPS position data at a rate of 1-2Hz at over 80 locations. The CRTN data presents the possibility of studying dynamical solid earth processes in a way that complements existing seismic networks. To realize this possibility we have developed a prototype system for detecting changes and anomalies in the real-time data. Through this system, we can can correlate changes in multiple stations in order to detect signals with geographical extent. Our approach involves developing a statistical model for each GPS station in the network, and then using those models to segment the time series into a number of discrete states described by the model. We use a hidden Markov model (HMM) to describe the behavior of each station; fitting the model to the data requires neither labeled training examples nor a priori information about the system. As such, HMMs are well suited to this problem domain, in which the data remains largely uncharacterized. There are two main components to our approach. The first is the model fitting algorithm, regularized deterministic annealing expectation- maximization (RDAEM), which provides robust, high-quality results. The second is a web service infrastructure that connects the data to the statistical modeling analysis and allows us to easily present the results of that analysis through a web portal interface. This web service approach facilitates the automatic updating of station models to keep pace with dynamical changes in the data. Our web portal interface is critical to the process of interpreting the data. A Google Maps interface allows users to visually interpret state changes not only on individual stations but across the entire network. Users can drill down from the map interface to inspect detailed results for individual stations, download the time series data, and inspect fitted models. Alternatively, users can use the web portal look at the evolution of changes on the network by moving backwards and forwards in time.

Documenting Liquefaction Failures Using Satellite Remote Sensing and Artificial Intelligence Algorithms

NASA Astrophysics Data System (ADS)

Oommen, T.; Baise, L. G.; Gens, R.; Prakash, A.; Gupta, R. P.

2009-12-01

Historically, earthquake induced liquefaction is known to have caused extensive damage around the world. Therefore, there is a compelling need to characterize and map liquefaction after a seismic event. Currently, after an earthquake event, field-based mapping of liquefaction is sporadic and limited due to inaccessibility, short life of the failures, difficulties in mapping large aerial extents, and lack of resources. We hypothesize that as liquefaction occurs in saturated granular soils due to an increase in pore pressure, the liquefaction related terrain changes should have an associated increase in soil moisture with respect to the surrounding non-liquefied regions. The increase in soil moisture affects the thermal emittance and, hence, change detection using pre- and post-event thermal infrared (TIR) imagery is suitable for identifying areas that have undergone post-earthquake liquefaction. Though change detection using TIR images gives the first indication of areas of liquefaction, the spatial resolution of TIR images is typically coarser than the resolution of corresponding visible, near-infrared (NIR), and shortwave infrared (SWIR) images. We hypothesize that liquefaction induced changes in the soil and associated surface effects cause textural and spectral changes in images acquired in the visible, NIR, and SWIR. Although these changes can be from various factors, a synergistic approach taking advantage of the thermal signature variation due to changing soil moisture condition, together with the spectral information from high resolution visible, NIR, and SWIR bands can help to narrow down the locations of post-event liquefaction for regional documentation. In this study, we analyze the applicability of combining various spectral bands from different satellites (Landsat, Terra-MISR, IRS-1C, and IRS-1D) for documenting liquefaction failures associated with the magnitude 7.6 earthquake that occurred in Bhuj, India, in 2001. We combine the various spectral bands by neighborhood correlation image analysis using an artificial intelligence algorithm called support vector machine to remotely identify and document liquefaction failures across a region; and assess the reliability and accuracy of the thermal remote sensing approach in documenting regional liquefaction failures. Finally, we present the applicability of the satellite data analyzed and appropriateness of a multisensor and multispectral approach for documenting liquefaction related failures.

Real-time method for establishing a detection map for a network of sensors

DOEpatents

Nguyen, Hung D; Koch, Mark W; Giron, Casey; Rondeau, Daniel M; Russell, John L

2012-09-11

A method for establishing a detection map of a dynamically configurable sensor network. This method determines an appropriate set of locations for a plurality of sensor units of a sensor network and establishes a detection map for the network of sensors while the network is being set up; the detection map includes the effects of the local terrain and individual sensor performance. Sensor performance is characterized during the placement of the sensor units, which enables dynamic adjustment or reconfiguration of the placement of individual elements of the sensor network during network set-up to accommodate variations in local terrain and individual sensor performance. The reconfiguration of the network during initial set-up to accommodate deviations from idealized individual sensor detection zones improves the effectiveness of the sensor network in detecting activities at a detection perimeter and can provide the desired sensor coverage of an area while minimizing unintentional gaps in coverage.

Development and validation of a triplex real-time PCR for rapid detection and specific identification of M. avium sub sp. paratuberculosis in faecal samples.

PubMed

Irenge, Léonid M; Walravens, Karl; Govaerts, Marc; Godfroid, Jacques; Rosseels, Valérie; Huygen, Kris; Gala, Jean-Luc

2009-04-14

A triplex real-time (TRT-PCR) assay was developed to ensure a rapid and reliable detection of Mycobacterium avium subsp. paratuberculosis (Map) in faecal samples and to allow routine detection of Map in farmed livestock and wildlife species. The TRT-PCR assay was designed using IS900, ISMAP02 and f57 molecular targets. Specificity of TRT-PCR was first confirmed on a panel of control mycobacterial Map and non-Map strains and on faecal samples from Map-negative cows (n=35) and from Map-positive cows (n=20). The TRT-PCR assay was compared to direct examination after Ziehl-Neelsen (ZN) staining and to culture on 197 faecal samples collected serially from five calves experimentally exposed to Map over a 3-year period during the sub-clinical phase of the disease. The data showed a good agreement between culture and TRT-PCR (kappa score=0.63), with the TRT-PCR limit of detection of 2.5 x 10(2)microorganisms/g of faeces spiked with Map. ZN agreement with TRT-PCR was not good (kappa=0.02). Sequence analysis of IS900 amplicons from three single IS900 positive samples confirmed the true Map positivity of the samples. Highly specific IS900 amplification suggests therefore that each single IS900 positive sample from experimentally exposed animals was a true Map-positive specimen. In this controlled experimental setting, the TRT-PCT was rapid, specific and displayed a very high sensitivity for Map detection in faecal samples compared to conventional methods.

Automated Change Detection for Synthetic Aperture Sonar

DTIC Science & Technology

2014-01-01

channels, respectively. The canonical coordinates of x and y are defined as u = FHR−1/2xx x v = GHR−1/2yy y where F and G are the mapping matrices...containing the left and right singular vectors of the coherence matrix C, respectively. The canonical coordinate vectors u and v share the diagonal cross...feature set. The coherent change information between canonical coordinates v and u can be calculated using the residual, v −Ku, owing to the fact that

Nanoplasmonic molecular ruler for nuclease activity and DNA footprinting

DOEpatents

Chen, Fanqing Frank; Liu, Gang L; Lee, Luke P

2013-10-29

This invention provides a nanoplasmonic molecular ruler, which can perform label-free and real-time monitoring of nucleic acid (e.g., DNA) length changes and perform nucleic acid footprinting. In various embodiments the ruler comprises a nucleic acid attached to a nanoparticle, such that changes in the nucleic acid length are detectable using surface plasmon resonance. The nanoplasmonic ruler provides a fast and convenient platform for mapping nucleic acid-protein interactions, for nuclease activity monitoring, and for other footprinting related methods.

xMAP Technology: Applications in Detection of Pathogens

PubMed Central

Reslova, Nikol; Michna, Veronika; Kasny, Martin; Mikel, Pavel; Kralik, Petr

2017-01-01

xMAP technology is applicable for high-throughput, multiplex and simultaneous detection of different analytes within a single complex sample. xMAP multiplex assays are currently available in various nucleic acid and immunoassay formats, enabling simultaneous detection and typing of pathogenic viruses, bacteria, parasites and fungi and also antigen or antibody interception. As an open architecture platform, the xMAP technology is beneficial to end users and therefore it is used in various pharmaceutical, clinical and research laboratories. The main aim of this review is to summarize the latest findings and applications in the field of pathogen detection using microsphere-based multiplex assays. PMID:28179899

The National Map - Orthoimagery

USGS Publications Warehouse

Mauck, James; Brown, Kim; Carswell, William J.

2009-01-01

Orthorectified digital aerial photographs and satellite images of 1-meter (m) pixel resolution or finer make up the orthoimagery component of The National Map. The process of orthorectification removes feature displacements and scale variations caused by terrain relief and sensor geometry. The result is a combination of the image characteristics of an aerial photograph or satellite image and the geometric qualities of a map. These attributes allow users to: *Measure distance *Calculate areas *Determine shapes of features *Calculate directions *Determine accurate coordinates *Determine land cover and use *Perform change detection *Update maps The standard digital orthoimage is a 1-m or finer resolution, natural color or color infra-red product. Most are now produced as GeoTIFFs and accompanied by a Federal Geographic Data Committee (FGDC)-compliant metadata file. The primary source for 1-m data is the National Agriculture Imagery Program (NAIP) leaf-on imagery. The U.S. Geological Survey (USGS) utilizes NAIP imagery as the image layer on its 'Digital- Map' - a new generation of USGS topographic maps (http://nationalmap.gov/digital_map). However, many Federal, State, and local governments and organizations require finer resolutions to meet a myriad of needs. Most of these images are leaf-off, natural-color products at resolutions of 1-foot (ft) or finer.

Probabilistic mapping of flood-induced backscatter changes in SAR time series

NASA Astrophysics Data System (ADS)

Schlaffer, Stefan; Chini, Marco; Giustarini, Laura; Matgen, Patrick

2017-04-01

The information content of flood extent maps can be increased considerably by including information on the uncertainty of the flood area delineation. This additional information can be of benefit in flood forecasting and monitoring. Furthermore, flood probability maps can be converted to binary maps showing flooded and non-flooded areas by applying a threshold probability value pF = 0.5. In this study, a probabilistic change detection approach for flood mapping based on synthetic aperture radar (SAR) time series is proposed. For this purpose, conditional probability density functions (PDFs) for land and open water surfaces were estimated from ENVISAT ASAR Wide Swath (WS) time series containing >600 images using a reference mask of permanent water bodies. A pixel-wise harmonic model was used to account for seasonality in backscatter from land areas caused by soil moisture and vegetation dynamics. The approach was evaluated for a large-scale flood event along the River Severn, United Kingdom. The retrieved flood probability maps were compared to a reference flood mask derived from high-resolution aerial imagery by means of reliability diagrams. The obtained performance measures indicate both high reliability and confidence although there was a slight under-estimation of the flood extent, which may in part be attributed to topographically induced radar shadows along the edges of the floodplain. Furthermore, the results highlight the importance of local incidence angle for the separability between flooded and non-flooded areas as specular reflection properties of open water surfaces increase with a more oblique viewing geometry.

Identifying Spatiotemporal Changes In Irrigated Area Across Southwestern Michigan, USA, Using Remote Sensing and Climate Data

NASA Astrophysics Data System (ADS)

Xu, T.; Deines, J. M.; Kendall, A. D.; Hyndman, D. W.

2017-12-01

Irrigation, which has become more common in humid regions, is the largest consumptive water use across the US and the globe. In southwestern Michigan, there has been a dramatic expansion in irrigation water use for row crops (primarily corn and soybean) in the past decade, mostly from groundwater pumping. The rapid expansion of irrigated row crops has potentially profound implications for terrestrial water balances, food production, and local to regional climate. Detailed maps of spatio-temporal changes in irrigation are essential to better understand irrigation impacts. However, accurate monitoring of irrigation area can be difficult in humid regions using remotely sensed methods due to the similarity in greenness between non-irrigated and irrigated areas in most years. Here, we use remote sensing to create annual, 30m-resolution maps of irrigated cropland by integrating Landsat and MODIS satellite products along with the PRISM climate dataset. From these data we developed spatial time series of vegetation and extreme weather indices, including novel indices we developed specifically to maximize detection of irrigation. Using these input data, machine learning classification was then performed over the region to identify irrigated crop area for each year. The resulting annual irrigation maps suggest that total irrigated area in southwestern Michigan increased by 160% from 2000 to 2017. The accuracy of the maps is assessed relative to maps created for an arid region using the same method. The maps can be integrated into hydrologic models to quantify irrigation impacts and support water resources management.

Change Detection Analysis in Urban and Suburban Areas Using Landsat Thematic Mapper data: Case of Huntsville, Alabama

NASA Technical Reports Server (NTRS)

Kuan, Dana; Fahsi, A.; Steinfeld S.; Coleman, T.

1998-01-01

Two Landsat Thematic Mapper (TM) images, from July 1984 and July 1992, were used to identify land use/cover changes in the urban and suburban fringe of the city of Huntsville, Alabama. Image difference was the technique used to quantify the change between the two dates. The eight-year period showed a 16% change, mainly from agricultural lands to urban areas generated by the settlement of industrial, commercial, and residential areas. Visual analysis of the change map (i.e., difference image) supported this phenomenon by showing that most changes were occurring in the vicinity of the major roads and highways across the city.

Lunar Prospector: a Preliminary Surface Remote Sensing Resource Assessment for the Moon

NASA Technical Reports Server (NTRS)

Mardon, A. A.

1992-01-01

The potential existence of lunar volatiles is a scientific discovery that could distinctly change the direction of pathways of inner solar system human expansion. With a dedicated germanium gamma ray spectrometer launched in the early 1990's, surface water concentrations of 0.7 percent could be detected immediately upon full lunar polar orbit operations. The expense of lunar base construction and operation would be dramatically reduced over a scenario with no lunar volatile resources. Global surface mineral distribution could be mapped out and integrated into a GIS database for lunar base site selection. Extensive surface lunar mapping would also result in the utilization of archived Apollo images. A variety of remote sensing systems and their parameters have been proposed for use in the detection of these lunar ice masses. The detection or nondetection of subsurface and surface ice masses in lunar polar crater floors could dramatically direct the development pathways that the human race might follow in its radiation from the Earth to habitable locales in the inner terran solar system. Potential sources of lunar volatiles are described. The use of remote sensing to detect lunar volatiles is addressed.

Monitoring Urban Land Cover/land Use Change in Algiers City Using Landsat Images (1987-2016)

NASA Astrophysics Data System (ADS)

Bouchachi, B.; Zhong, Y.

2017-09-01

Monitoring the Urban Land Cover/Land Use change detection is important as one of the main driving forces of environmental change because Urbanization is the biggest changes in form of Land, resulting in a decrease in cultivated areas. Using remote sensing ability to solve land resources problems. The purpose of this research is to map the urban areas at different times to monitor and predict possible urban changes, were studied the annual growth urban land during the last 29 years in Algiers City. Improving the productiveness of long-term training in land mapping, were have developed an approach by the following steps: 1) pre-processing for improvement of image characteristics; 2) extract training sample candidates based on the developed methods; and 3) Derive maps and analyzed of Algiers City on an annual basis from 1987 to 2016 using a Supervised Classifier Support Vector Machine (SVMs). Our result shows that the strategy of urban land followed in the region of Algiers City, developed areas mostly were extended to East, West, and South of Central Regions. The urban growth rate is linked with National Office of Statistics data. Future studies are required to understand the impact of urban rapid lands on social, economy and environmental sustainability, it will also close the gap in data of urbanism available, especially on the lack of reliable data, environmental and urban planning for each municipality in Algiers, develop experimental models to predict future land changes with statistically significant confidence.

Next generation of global land cover characterization, mapping, and monitoring

USGS Publications Warehouse

Giri, Chandra; Pengra, Bruce; Long, J.; Loveland, Thomas R.

2013-01-01

Land cover change is increasingly affecting the biophysics, biogeochemistry, and biogeography of the Earth's surface and the atmosphere, with far-reaching consequences to human well-being. However, our scientific understanding of the distribution and dynamics of land cover and land cover change (LCLCC) is limited. Previous global land cover assessments performed using coarse spatial resolution (300 m–1 km) satellite data did not provide enough thematic detail or change information for global change studies and for resource management. High resolution (∼30 m) land cover characterization and monitoring is needed that permits detection of land change at the scale of most human activity and offers the increased flexibility of environmental model parameterization needed for global change studies. However, there are a number of challenges to overcome before producing such data sets including unavailability of consistent global coverage of satellite data, sheer volume of data, unavailability of timely and accurate training and validation data, difficulties in preparing image mosaics, and high performance computing requirements. Integration of remote sensing and information technology is needed for process automation and high-performance computing needs. Recent developments in these areas have created an opportunity for operational high resolution land cover mapping, and monitoring of the world. Here, we report and discuss these advancements and opportunities in producing the next generations of global land cover characterization, mapping, and monitoring at 30-m spatial resolution primarily in the context of United States, Group on Earth Observations Global 30 m land cover initiative (UGLC).

Estimating Unbiased Land Cover Change Areas In The Colombian Amazon Using Landsat Time Series And Statistical Inference Methods

NASA Astrophysics Data System (ADS)

Arevalo, P. A.; Olofsson, P.; Woodcock, C. E.

2017-12-01

Unbiased estimation of the areas of conversion between land categories ("activity data") and their uncertainty is crucial for providing more robust calculations of carbon emissions to the atmosphere, as well as their removals. This is particularly important for the REDD+ mechanism of UNFCCC where an economic compensation is tied to the magnitude and direction of such fluxes. Dense time series of Landsat data and statistical protocols are becoming an integral part of forest monitoring efforts, but there are relatively few studies in the tropics focused on using these methods to advance operational MRV systems (Monitoring, Reporting and Verification). We present the results of a prototype methodology for continuous monitoring and unbiased estimation of activity data that is compliant with the IPCC Approach 3 for representation of land. We used a break detection algorithm (Continuous Change Detection and Classification, CCDC) to fit pixel-level temporal segments to time series of Landsat data in the Colombian Amazon. The segments were classified using a Random Forest classifier to obtain annual maps of land categories between 2001 and 2016. Using these maps, a biannual stratified sampling approach was implemented and unbiased stratified estimators constructed to calculate area estimates with confidence intervals for each of the stable and change classes. Our results provide evidence of a decrease in primary forest as a result of conversion to pastures, as well as increase in secondary forest as pastures are abandoned and the forest allowed to regenerate. Estimating areas of other land transitions proved challenging because of their very small mapped areas compared to stable classes like forest, which corresponds to almost 90% of the study area. Implications on remote sensing data processing, sample allocation and uncertainty reduction are also discussed.

Tropical land use land cover mapping in Pará (Brazil) using discriminative Markov random fields and multi-temporal TerraSAR-X data

NASA Astrophysics Data System (ADS)

Hagensieker, Ron; Roscher, Ribana; Rosentreter, Johannes; Jakimow, Benjamin; Waske, Björn

2017-12-01

Remote sensing satellite data offer the unique possibility to map land use land cover transformations by providing spatially explicit information. However, detection of short-term processes and land use patterns of high spatial-temporal variability is a challenging task. We present a novel framework using multi-temporal TerraSAR-X data and machine learning techniques, namely discriminative Markov random fields with spatio-temporal priors, and import vector machines, in order to advance the mapping of land cover characterized by short-term changes. Our study region covers a current deforestation frontier in the Brazilian state Pará with land cover dominated by primary forests, different types of pasture land and secondary vegetation, and land use dominated by short-term processes such as slash-and-burn activities. The data set comprises multi-temporal TerraSAR-X imagery acquired over the course of the 2014 dry season, as well as optical data (RapidEye, Landsat) for reference. Results show that land use land cover is reliably mapped, resulting in spatially adjusted overall accuracies of up to 79% in a five class setting, yet limitations for the differentiation of different pasture types remain. The proposed method is applicable on multi-temporal data sets, and constitutes a feasible approach to map land use land cover in regions that are affected by high-frequent temporal changes.

Oxygen-17 anomaly in soil nitrate: A new precipitation proxy for desert landscapes

NASA Astrophysics Data System (ADS)

Wang, Fan; Ge, Wensheng; Luo, Hao; Seo, Ji-Hye; Michalski, Greg

2016-03-01

The nitrogen cycle in desert soil ecosystems is particularly sensitive to changes in precipitation, even of relatively small magnitude and short duration, because it is already under water stress. This suggests that desert soils may have preserved past evidence of small variations in continental precipitation. We have measured nitrate (NO3-) concentrations in soils from the Atacama (Chile), Kumtag (China), Mojave (US), and Thar (India) deserts, and stable nitrogen and oxygen isotope (15N, 17O, and 18O) abundances of the soil NO3-. 17O anomalies (Δ17O), the deviations from the mass-independent isotopic fractionation, were detected in soil NO3- from almost all sites of these four deserts. There was a strong negative correlation between the mean annual precipitation (MAP) and soil NO3- Δ17O values (Δ

Crosscutting Airborne Remote Sensing Technologies for Oil and Gas and Earth Science Applications

NASA Technical Reports Server (NTRS)

Aubrey, A. D.; Frankenberg, C.; Green, R. O.; Eastwood, M. L.; Thompson, D. R.; Thorpe, A. K.

2015-01-01

Airborne imaging spectroscopy has evolved dramatically since the 1980s as a robust remote sensing technique used to generate 2-dimensional maps of surface properties over large spatial areas. Traditional applications for passive airborne imaging spectroscopy include interrogation of surface composition, such as mapping of vegetation diversity and surface geological composition. Two recent applications are particularly relevant to the needs of both the oil and gas as well as government sectors: quantification of surficial hydrocarbon thickness in aquatic environments and mapping atmospheric greenhouse gas components. These techniques provide valuable capabilities for petroleum seepage in addition to detection and quantification of fugitive emissions. New empirical data that provides insight into the source strength of anthropogenic methane will be reviewed, with particular emphasis on the evolving constraints enabled by new methane remote sensing techniques. Contemporary studies attribute high-strength point sources as significantly contributing to the national methane inventory and underscore the need for high performance remote sensing technologies that provide quantitative leak detection. Imaging sensors that map spatial distributions of methane anomalies provide effective techniques to detect, localize, and quantify fugitive leaks. Airborne remote sensing instruments provide the unique combination of high spatial resolution (<1 m) and large coverage required to directly attribute methane emissions to individual emission sources. This capability cannot currently be achieved using spaceborne sensors. In this study, results from recent NASA remote sensing field experiments focused on point-source leak detection, will be highlighted. This includes existing quantitative capabilities for oil and methane using state-of-the-art airborne remote sensing instruments. While these capabilities are of interest to NASA for assessment of environmental impact and global climate change, industry similarly seeks to detect and localize leaks of both oil and methane across operating fields. In some cases, higher sensitivities desired for upstream and downstream applications can only be provided by new airborne remote sensing instruments tailored specifically for a given application. There exists a unique opportunity for alignment of efforts between commercial and government sectors to advance the next generation of instruments to provide more sensitive leak detection capabilities, including those for quantitative source strength determination.

Ice Sheet Change Detection by Satellite Image Differencing

NASA Technical Reports Server (NTRS)

Bindschadler, Robert A.; Scambos, Ted A.; Choi, Hyeungu; Haran, Terry M.

2010-01-01

Differencing of digital satellite image pairs highlights subtle changes in near-identical scenes of Earth surfaces. Using the mathematical relationships relevant to photoclinometry, we examine the effectiveness of this method for the study of localized ice sheet surface topography changes using numerical experiments. We then test these results by differencing images of several regions in West Antarctica, including some where changes have previously been identified in altimeter profiles. The technique works well with coregistered images having low noise, high radiometric sensitivity, and near-identical solar illumination geometry. Clouds and frosts detract from resolving surface features. The ETM(plus) sensor on Landsat-7, ALI sensor on EO-1, and MODIS sensor on the Aqua and Terra satellite platforms all have potential for detecting localized topographic changes such as shifting dunes, surface inflation and deflation features associated with sub-glacial lake fill-drain events, or grounding line changes. Availability and frequency of MODIS images favor this sensor for wide application, and using it, we demonstrate both qualitative identification of changes in topography and quantitative mapping of slope and elevation changes.

Self-organizing map classifier for stressed speech recognition

NASA Astrophysics Data System (ADS)

Partila, Pavol; Tovarek, Jaromir; Voznak, Miroslav

2016-05-01

This paper presents a method for detecting speech under stress using Self-Organizing Maps. Most people who are exposed to stressful situations can not adequately respond to stimuli. Army, police, and fire department occupy the largest part of the environment that are typical of an increased number of stressful situations. The role of men in action is controlled by the control center. Control commands should be adapted to the psychological state of a man in action. It is known that the psychological changes of the human body are also reflected physiologically, which consequently means the stress effected speech. Therefore, it is clear that the speech stress recognizing system is required in the security forces. One of the possible classifiers, which are popular for its flexibility, is a self-organizing map. It is one type of the artificial neural networks. Flexibility means independence classifier on the character of the input data. This feature is suitable for speech processing. Human Stress can be seen as a kind of emotional state. Mel-frequency cepstral coefficients, LPC coefficients, and prosody features were selected for input data. These coefficients were selected for their sensitivity to emotional changes. The calculation of the parameters was performed on speech recordings, which can be divided into two classes, namely the stress state recordings and normal state recordings. The benefit of the experiment is a method using SOM classifier for stress speech detection. Results showed the advantage of this method, which is input data flexibility.

Mapping fire probability and severity in a Mediterranean area using different weather and fuel moisture scenarios

NASA Astrophysics Data System (ADS)

Arca, B.; Salis, M.; Bacciu, V.; Duce, P.; Pellizzaro, G.; Ventura, A.; Spano, D.

2009-04-01

Although in many countries lightning is the main cause of ignition, in the Mediterranean Basin the forest fires are predominantly ignited by arson, or by human negligence. The fire season peaks coincide with extreme weather conditions (mainly strong winds, hot temperatures, low atmospheric water vapour content) and high tourist presence. Many works reported that in the Mediterranean Basin the projected impacts of climate change will cause greater weather variability and extreme weather conditions, with drier and hotter summers and heat waves. At long-term scale, climate changes could affect the fuel load and the dead/live fuel ratio, and therefore could change the vegetation flammability. At short-time scale, the increase of extreme weather events could directly affect fuel water status, and it could increase large fire occurrence. In this context, detecting the areas characterized by both high probability of large fire occurrence and high fire severity could represent an important component of the fire management planning. In this work we compared several fire probability and severity maps (fire occurrence, rate of spread, fireline intensity, flame length) obtained for a study area located in North Sardinia, Italy, using FlamMap simulator (USDA Forest Service, Missoula). FlamMap computes the potential fire behaviour characteristics over a defined landscape for given weather, wind and fuel moisture data. Different weather and fuel moisture scenarios were tested to predict the potential impact of climate changes on fire parameters. The study area, characterized by a mosaic of urban areas, protected areas, and other areas subject to anthropogenic disturbances, is mainly composed by fire-prone Mediterranean maquis. The input themes needed to run FlamMap were input as grid of 10 meters; the wind data, obtained using a computational fluid-dynamic model, were inserted as gridded file, with a resolution of 50 m. The analysis revealed high fire probability and severity in most of the areas, and therefore a high potential danger. The FlamMap outputs and the derived fire probability maps can be used in decision support systems for fire spread and behaviour and for fire danger assessment with actual and future fire regimes.

Aircraft Detection in High-Resolution SAR Images Based on a Gradient Textural Saliency Map.

PubMed

Tan, Yihua; Li, Qingyun; Li, Yansheng; Tian, Jinwen

2015-09-11

This paper proposes a new automatic and adaptive aircraft target detection algorithm in high-resolution synthetic aperture radar (SAR) images of airport. The proposed method is based on gradient textural saliency map under the contextual cues of apron area. Firstly, the candidate regions with the possible existence of airport are detected from the apron area. Secondly, directional local gradient distribution detector is used to obtain a gradient textural saliency map in the favor of the candidate regions. In addition, the final targets will be detected by segmenting the saliency map using CFAR-type algorithm. The real high-resolution airborne SAR image data is used to verify the proposed algorithm. The results demonstrate that this algorithm can detect aircraft targets quickly and accurately, and decrease the false alarm rate.

Tracking changes of river morphology in Ayeyarwady River in Myanmar using earth observations and surface water mapping tool

NASA Astrophysics Data System (ADS)

Piman, T.; Schellekens, J.; Haag, A.; Donchyts, G.; Apirumanekul, C.; Hlaing, K. T.

2017-12-01

River morphology changes is one of the key issues in Ayeyarwady River in Myanmar which cause impacts on navigation, riverine habitats, agriculture lands, communities and livelihoods near the bank of the river. This study is aimed to track the changes in river morphology in the middle reach of Ayeyarwady River over last 30 years from 1984-2014 to improve understanding of riverbank dynamic, erosion and deposition procress. Earth observations including LandSat-7, LandSat-8, Digital Elevation Model from SRTM Plus and, ASTER-2 GoogleMap and Open Street Map were obtained for the study. GIS and remote sensing tools were used to analyze changes in river morphology while surface water mapping tool was applied to determine how the dynamic behaviour of the surface river and effect of river morphology changes. The tool consists of two components: (1) a Google Earth Engine (GEE) javascript or python application that performs image analysis and (2) a user-friendly site/app using Google's appspot.com that exposes the application to the users. The results of this study shown that the fluvial morphology in the middle reach of Ayeyarwady River is continuously changing under the influence of high water flows in particularly from extreme flood events and land use change from mining and deforestation. It was observed that some meandering sections of the riverbank were straightened, which results in the movement of sediment downstream and created new sections of meandering riverbank. Several large islands have formed due to the stabilization by vegetation and is enforced by sedimentation while many small bars were formed and migrated dynamically due to changes in water levels and flow velocity in the wet and dry seasons. The main channel was changed to secondary channel in some sections of the river. This results a constant shift of the navigation route. We also found that some villages were facing riverbank erosion which can force villagers to relocate. The study results demonstrated that the products from earth observations and the surface water mapping tool could detect dynamic changes of river morphology in the Ayeyarwady River. This information is useful to support navigation and riverbank protection planning and formulating mitigation measures for local communities that are affecting by riverbank erosion.

A new automatic SAR-based flood mapping application hosted on the European Space Agency's grid processing on demand fast access to imagery environment

NASA Astrophysics Data System (ADS)

Hostache, Renaud; Chini, Marco; Matgen, Patrick; Giustarini, Laura

2013-04-01

There is a clear need for developing innovative processing chains based on earth observation (EO) data to generate products supporting emergency response and flood management at a global scale. Here an automatic flood mapping application is introduced. The latter is currently hosted on the Grid Processing on Demand (G-POD) Fast Access to Imagery (Faire) environment of the European Space Agency. The main objective of the online application is to deliver flooded areas using both recent and historical acquisitions of SAR data in an operational framework. It is worth mentioning that the method can be applied to both medium and high resolution SAR images. The flood mapping application consists of two main blocks: 1) A set of query tools for selecting the "crisis image" and the optimal corresponding pre-flood "reference image" from the G-POD archive. 2) An algorithm for extracting flooded areas using the previously selected "crisis image" and "reference image". The proposed method is a hybrid methodology, which combines histogram thresholding, region growing and change detection as an approach enabling the automatic, objective and reliable flood extent extraction from SAR images. The method is based on the calibration of a statistical distribution of "open water" backscatter values inferred from SAR images of floods. Change detection with respect to a pre-flood reference image helps reducing over-detection of inundated areas. The algorithms are computationally efficient and operate with minimum data requirements, considering as input data a flood image and a reference image. Stakeholders in flood management and service providers are able to log onto the flood mapping application to get support for the retrieval, from the rolling archive, of the most appropriate pre-flood reference image. Potential users will also be able to apply the implemented flood delineation algorithm. Case studies of several recent high magnitude flooding events (e.g. July 2007 Severn River flood, UK and March 2010 Red River flood, US) observed by high-resolution SAR sensors as well as airborne photography highlight advantages and limitations of the online application. A mid-term target is the exploitation of ESA SENTINEL 1 SAR data streams. In the long term it is foreseen to develop a potential extension of the application for systematically extracting flooded areas from all SAR images acquired on a daily, weekly or monthly basis. On-going research activities investigate the usefulness of the method for mapping flood hazard at global scale using databases of historic SAR remote sensing-derived flood inundation maps.

An Anomalous Force on the Map Spacecraft

NASA Technical Reports Server (NTRS)

Starin, Scott R.; ODonnell, James R., Jr.; Ward, David K.; Wollack, Edward J.; Bay, P. Michael; Fink, Dale R.; Bauer, Frank (Technical Monitor)

2002-01-01

The Microwave Anisotropy Probe (MAP) orbits the second Earth-Sun libration point (L2)-about 1.5 million kilometers outside Earth's orbit-mapping cosmic microwave background radiation. To achieve orbit near L2 on a small fuel budget, the MAP spacecraft needed to swing past the Moon for a gravity assist. Timing the lunar swing-by required MAP to travel in three high-eccentricity phasing loops with critical maneuvers at a minimum of two, but nominally all three, of the perigee passes. On the approach to the first perigee maneuver, MAP telemetry showed a considerable change in system angular momentum that threatened to cause on-board Failure Detection and Correction (FDC) to abort the critical maneuver. Fortunately, the system momentum did not reach the FDC limit; however, the MAP team did develop a contingency strategy should a stronger anomaly occur before or during subsequent perigee maneuvers, Simultaneously, members of the MAP team developed and tested various hypotheses for the cause of the anomalous force. The final hypothesis was that water was outgassing from the thermal blanketing and freezing to the cold side of the solar shield. As radiation from Earth warmed the cold side of the spacecraft, the uneven sublimation of frozen water created a torque on the spacecraft.

Image processing for quantifying fracture orientation and length scale transitions during brittle deformation

NASA Astrophysics Data System (ADS)

Rizzo, R. E.; Healy, D.; Farrell, N. J.

2017-12-01

We have implemented a novel image processing tool, namely two-dimensional (2D) Morlet wavelet analysis, capable of detecting changes occurring in fracture patterns at different scales of observation, and able of recognising the dominant fracture orientations and the spatial configurations for progressively larger (or smaller) scale of analysis. Because of its inherited anisotropy, the Morlet wavelet is proved to be an excellent choice for detecting directional linear features, i.e. regions where the amplitude of the signal is regular along one direction and has sharp variation along the perpendicular direction. Performances of the Morlet wavelet are tested against the 'classic' Mexican hat wavelet, deploying a complex synthetic fracture network. When applied to a natural fracture network, formed triaxially (σ1>σ2=σ3) deforming a core sample of the Hopeman sandstone, the combination of 2D Morlet wavelet and wavelet coefficient maps allows for the detection of characteristic scale orientation and length transitions, associated with the shifts from distributed damage to the growth of localised macroscopic shear fracture. A complementary outcome arises from the wavelet coefficient maps produced by increasing the wavelet scale parameter. These maps can be used to chart the variations in the spatial distribution of the analysed entities, meaning that it is possible to retrieve information on the density of fracture patterns at specific length scales during deformation.

Risk maps for targeting exotic plant pest detection programs in the United States

Treesearch

R.D. Magarey; D.M. Borchert; J.S. Engle; M Garcia-Colunga; Frank H. Koch; et al

2011-01-01

In the United States, pest risk maps are used by the Cooperative Agricultural Pest Survey for spatial and temporal targeting of exotic plant pest detection programs. Methods are described to create standardized host distribution, climate and pathway risk maps for the top nationally ranked exotic pest targets. Two examples are provided to illustrate the risk mapping...

Determine utility of ERTS-1 to detect and monitor area strip mining and reclamation. [southeastern Ohio

NASA Technical Reports Server (NTRS)

Rogers, R. H. (Principal Investigator); Pettyjohn, W. A.

1975-01-01

The author has identified the following significant results. Computer techniques were applied to process ERTS tapes acquired over coal mining operations in southeastern Ohio on 21 August 1972 and 3 September 1973. ERTS products obtained included geometrically correct map overlays showing stripped earth, partially reclaimed earth, water, and natural vegetation. Computer-generated tables listing the area covered by each land-water category in square kilometers and acres were produced. By comparing these mapping products, the study demonstrates the capability of ERTS to monitor changes in the extent of stripping, success of reclamation, and the secondary effects of mining on the environment.

Detection of Mycobacterium avium subspecies paratuberculosis in tie-stall dairy herds using a standardized environmental sampling technique and targeted pooled samples.

PubMed

Arango-Sabogal, Juan C; Côté, Geneviève; Paré, Julie; Labrecque, Olivia; Roy, Jean-Philippe; Buczinski, Sébastien; Doré, Elizabeth; Fairbrother, Julie H; Bissonnette, Nathalie; Wellemans, Vincent; Fecteau, Gilles

2016-07-01

Mycobacterium avium ssp. paratuberculosis (MAP) is the etiologic agent of Johne's disease, a chronic contagious enteritis of ruminants that causes major economic losses. Several studies, most involving large free-stall herds, have found environmental sampling to be a suitable method for detecting MAP-infected herds. In eastern Canada, where small tie-stall herds are predominant, certain conditions and management practices may influence the survival and transmission of MAP and recovery (isolation). Our objective was to estimate the performance of a standardized environmental and targeted pooled sampling technique for the detection of MAP-infected tie-stall dairy herds. Twenty-four farms (19 MAP-infected and 5 non-infected) were enrolled, but only 20 were visited twice in the same year, to collect 7 environmental samples and 2 pooled samples (sick cows and cows with poor body condition). Concurrent individual sampling of all adult cows in the herds was also carried out. Isolation of MAP was achieved using the MGIT Para TB culture media and the BACTEC 960 detection system. Overall, MAP was isolated in 7% of the environmental cultures. The sensitivity of the environmental culture was 44% [95% confidence interval (CI): 20% to 70%] when combining results from 2 different herd visits and 32% (95% CI: 13% to 57%) when results from only 1 random herd visit were used. The best sampling strategy was to combine samples from the manure pit, gutter, sick cows, and cows with poor body condition. The standardized environmental sampling technique and the targeted pooled samples presented in this study is an alternative sampling strategy to costly individual cultures for detecting MAP-infected tie-stall dairies. Repeated samplings may improve the detection of MAP-infected herds.

Mapping local anisotropy axis for scattering media using backscattering Mueller matrix imaging

NASA Astrophysics Data System (ADS)

He, Honghui; Sun, Minghao; Zeng, Nan; Du, E.; Guo, Yihong; He, Yonghong; Ma, Hui

2014-03-01

Mueller matrix imaging techniques can be used to detect the micro-structure variations of superficial biological tissues, including the sizes and shapes of cells, the structures in cells, and the densities of the organelles. Many tissues contain anisotropic fibrous micro-structures, such as collagen fibers, elastin fibers, and muscle fibers. Changes of these fibrous structures are potentially good indicators for some pathological variations. In this paper, we propose a quantitative analysis technique based on Mueller matrix for mapping local anisotropy axis of scattering media. By conducting both experiments on silk sample and Monte Carlo simulation based on the sphere-cylinder scattering model (SCSM), we extract anisotropy axis parameters from different backscattering Mueller matrix elements. Moreover, we testify the possible applications of these parameters for biological tissues. The preliminary experimental results of human cancerous samples show that, these parameters are capable to map the local axis of fibers. Since many pathological changes including early stage cancers affect the well aligned structures for tissues, the experimental results indicate that these parameters can be used as potential tools in clinical applications for biomedical diagnosis purposes.

High-resolution forest carbon stocks and emissions in the Amazon.

PubMed

Asner, Gregory P; Powell, George V N; Mascaro, Joseph; Knapp, David E; Clark, John K; Jacobson, James; Kennedy-Bowdoin, Ty; Balaji, Aravindh; Paez-Acosta, Guayana; Victoria, Eloy; Secada, Laura; Valqui, Michael; Hughes, R Flint

2010-09-21

Efforts to mitigate climate change through the Reduced Emissions from Deforestation and Degradation (REDD) depend on mapping and monitoring of tropical forest carbon stocks and emissions over large geographic areas. With a new integrated use of satellite imaging, airborne light detection and ranging, and field plots, we mapped aboveground carbon stocks and emissions at 0.1-ha resolution over 4.3 million ha of the Peruvian Amazon, an area twice that of all forests in Costa Rica, to reveal the determinants of forest carbon density and to demonstrate the feasibility of mapping carbon emissions for REDD. We discovered previously unknown variation in carbon storage at multiple scales based on geologic substrate and forest type. From 1999 to 2009, emissions from land use totaled 1.1% of the standing carbon throughout the region. Forest degradation, such as from selective logging, increased regional carbon emissions by 47% over deforestation alone, and secondary regrowth provided an 18% offset against total gross emissions. Very high-resolution monitoring reduces uncertainty in carbon emissions for REDD programs while uncovering fundamental environmental controls on forest carbon storage and their interactions with land-use change.

Mapping Typha Domingensis in the Cienega de Santa Clara Using Satellite Images, Global Positioning System, and Spectrometry

USGS Publications Warehouse

Sanchez, Richard D.; Burnett, Earl E.; Croxen, Fred

2000-01-01

The Cienega de Santa Clara, Sonora, Mexico, a brackish wetland area created near the delta of the Colorado River from drainage effluent flowing from the United States since 1977, may undergo changes owing to the operation of the Yuma Desalting Plant in the United States. This has become the largest wetland in the delta region containing rare and endangered species, yet little is known about the environmental impact of these changes. The water quality of the marsh is of growing concern to the Bureau of Reclamation (BOR) which operates the Desalting Plant. Consequently, the BOR solicited the U.S. Geological Survey to investigate the limits and usefulness of satellite, global positioning system (GPS), and spectra data to map the Typha domingensis (cattail) of the Cienega de Santa Clara. Typha domingensis was selected by the BOR as the Cienega de Santa Clara indicator species to best predict the environmental effects of effl uent from the Yuma Desalting Plant. The successful base mapping of Typha domingensis will provide a viable tool for long-term monitoring and stress detection in the Cienega de Santa Clara.

EAARL Topography-Sagamore Hill National Historic Site

USGS Publications Warehouse

Brock, John C.; Wright, C. Wayne; Nayegandhi, Amar; Patterson, Matt; Travers, Laurinda J.

2007-01-01

This Web site contains lidar-derived bare earth (BE) and first return (FR) topography maps and GIS files for the Sagamore Hill National Historic Site. These lidar-derived topography maps were produced as a collaborative effort between the U.S. Geological Survey (USGS) Coastal and Marine Geology Program, FISC St. Petersburg, Florida, the National Park Service (NPS), Northeast Coastal and Barrier Network, Inventory and Monitoring Program, and the National Aeronautics and Space Administration (NASA) Wallops Flight Facility. One objective of this research is to create techniques to survey coral reefs and barrier islands for the purposes of geomorphic change studies, habitat mapping, ecological monitoring, change detection, and event assessment. As part of this project, data from an innovative instrument under development at the NASA Wallops Flight Facility, the NASA Experimental Airborne Advanced Research Lidar (EAARL) are being used. This sensor has the potential to make significant contributions in this realm for measuring subaerial and submarine topography wthin cross-environment surveys. High spectral resolution, water-column correction, and low costs were found to be key factors in providing accurate and affordable imagery to costal resource managers.

EAARL topography: Cape Cod National Seashore

USGS Publications Warehouse

Brock, John C.; Wright, C. Wayne; Patterson, Matt; Nayegandhi, Amar; Travers, Laurinda J.

2007-01-01

This Web site contains 90 Lidar-derived bare earth topography maps and GIS files for the Cape Cod National Seashore. These Lidar-derived topography maps were produced as a collaborative effort between the U.S. Geological Survey (USGS) Florida Integrated Science Center (FISC) St. Petersburg, Florida, the National Park Service (NPS), Northeast Coastal and Barrier Network, Inventory and Monitoring Program, and the National Aeronautics and Space Administration (NASA) Wallops Flight Facility. One objective of this research is to create techniques to survey coral reefs and barrier islands for the purposes of geomorphic change studies, habitat mapping, ecological monitoring, change detection, and event assessment. As part of this project, data from an innovative instrument under development at the NASA Wallops Flight Facility, the NASA Experimental Airborne Advanced Research Lidar (EAARL) are being used. This sensor has the potential to make significant contributions in this realm for measuring subaerial and submarine topography wthin cross-environment surveys. High spectral resolution, water-column correction, and low costs were found to be key factors in providing accurate and affordable imagery to coastal resource managers.

EAARL topography: Thomas Stone National Historic Site

USGS Publications Warehouse

Brock, John C.; Wright, C. Wayne; Patterson, Matt; Nayegandhi, Amar; Patterson, Judd

2007-01-01

This Web site contains Lidar-derived topography (first return and bare earth) maps and GIS files for Thomas Stone National Historic Site in Maryland. These Lidar-derived topography maps were produced as a collaborative effort between the U.S. Geological Survey (USGS) Coastal and Marine Geology Program, FISC St. Petersburg, the National Park Service (NPS) South Florida/Caribbean Network Inventory and Monitoring Program, and the National Aeronautics and Space Administration (NASA) Wallops Flight Facility. One objective of this research is to create techniques to survey coral reefs and barrier islands for the purposes of geomorphic change studies, habitat mapping, ecological monitoring, change detection, and event assessment. As part of this project, data from an innovative instrument under development at the NASA Wallops Flight Facility, the NASA Experimental Airborne Advanced Research Lidar (EAARL) are being used. This sensor has the potential to make significant contributions in this realm for measuring subaerial and submarine topography wthin cross-environment surveys. High spectral resolution, water-column correction, and low costs were found to be key factors in providing accurate and affordable imagery to costal resource managers.

EAARL topography: Gulf Islands National Seashore: Florida

USGS Publications Warehouse

Brock, John C.; Wright, C. Wayne; Nayegandhi, Amar; Patterson, Matt; Wilson, Iris; Travers, Laurinda J.

2007-01-01

This Web site contains 33 lidar-derived bare earth topography maps and GIS files for the Gulf Islands National Seashore-Florida. These lidar-derived topography maps were produced as a collaborative effort between the U.S. Geological Survey (USGS) Coastal and Marine Geology Program, FISC St. Petersburg, Florida, the National Park Service (NPS), Gulf Coast Network, Network Inventory and Monitoring Program, and the National Aeronautics and Space Administration (NASA) Wallops Flight Facility. One objective of this research is to create techniques to survey coral reefs and barrier islands for the purposes of geomorphic change studies, habitat mapping, ecological monitoring, change detection, and event assessment. As part of this project, data from an innovative instrument under development at the NASA Wallops Flight Facility, the NASA Experimental Airborne Advanced Research Lidar (EAARL) are being used. This sensor has the potential to make significant contributions in this realm for measuring subaerial and submarine topography wthin cross-environment surveys. High spectral resolution, water-column correction, and low costs were found to be key factors in providing accurate and affordable imagery to costal resource managers.

EAARL topography: Gulf Islands National Seashore: Mississippi

USGS Publications Warehouse

Brock, John C.; Wright, C. Wayne; Nayegandhi, Amar; Patterson, Matt; Wilson, Iris; Travers, Laurinda J.

2007-01-01

This Web site contains 30 lidar-derived bare earth topography maps and GIS files for the Gulf Islands National Seashore-Mississippi. These lidar-derived topography maps were produced as a collaborative effort between the U.S. Geological Survey (USGS) Coastal and Marine Geology Program, FISC St. Petersburg, Florida, the National Park Service (NPS) Gulf Coast Network, Inventory and Monitoring Program, and the National Aeronautics and Space Administration (NASA) Wallops Flight Facility. One objective of this research is to create techniques to survey coral reefs and barrier islands for the purposes of geomorphic change studies, habitat mapping, ecological monitoring, change detection, and event assessment. As part of this project, data from an innovative instrument under development at the NASA Wallops Flight Facility, the NASA Experimental Airborne Advanced Research Lidar (EAARL) are being used. This sensor has the potential to make significant contributions in this realm for measuring subaerial and submarine topography wthin cross-environment surveys. High spectral resolution, water-column correction, and low costs were found to be key factors in providing accurate and affordable imagery to costal resource managers.

EAARL submarine topography: Florida Keys National Marine Sanctuary

USGS Publications Warehouse

Brock, John C.; Wright, C. Wayne; Nayegandhi, Amar; Woolard, Jason; Patterson, Matt; Wilson, Iris; Travers, Laurinda J.

2007-01-01

This Web site contains 46 Lidar-derived submarine topography maps and GIS files for the Florida Keys National Marine Sanctuary. These Lidar-derived submarine topographic maps were produced as a collaborative effort between the U.S. Geological Survey (USGS) Coastal and Marine Geology Program, FISC St. Petersburg, Florida, the National Oceanic and Atmospheric Administration (NOAA), Remote Sensing Division, the National Park Service (NPS) South Florida/Caribbean Network Inventory and Monitoring Program, and the National Aeronautics and Space Administration (NASA) Wallops Flight Facility. One objective of this research is to create techniques to survey coral reefs and barrier islands for the purposes of geomorphic change studies, habitat mapping, ecological monitoring, change detection, and event assessment. As part of this project, data from an innovative instrument under development at the NASA Wallops Flight Facility, the NASA Experimental Airborne Advanced Research Lidar (EAARL) are being used. This sensor has the potential to make significant contributions in this realm for measuring subaerial and submarine topography within cross-environment surveys. High spectral resolution, water-column correction, and low costs were found to be key factors in providing accurate and affordable imagery to coastal resource managers.

EAARL Submarine Topography - Northern Florida Keys Reef Tract

USGS Publications Warehouse

Brock, John C.; Wright, C. Wayne; Nayegandhi, Amar; Patterson, Matt; Travers, Laurinda J.; Wilson, Iris

2007-01-01

This Web site contains 32 Lidar-derived bare earth topography maps and GIS files for the Northern Florida Keys Reef Tract. These lidar-derived submarine topographic maps were produced as a collaborative effort between the U.S. Geological Survey (USGS) Coastal and Marine Geology Program, FISC St. Petersburg, Florida, the National Park Service (NPS) South Florida/Caribbean Network Inventory and Monitoring Program, and the National Aeronautics and Space Administration (NASA) Wallops Flight Facility. One objective of this research is to create techniques to survey coral reefs and barrier islands for the purposes of geomorphic change studies, habitat mapping, ecological monitoring, change detection, and event assessment. As part of this project, data from an innovative instrument under development at the NASA Wallops Flight Facility, the NASA Experimental Airborne Advanced Research Lidar (EAARL) are being used. This sensor has the potential to make significant contributions in this realm for measuring subaerial and submarine topography wthin cross-environment surveys. High spectral resolution, water-column correction, and low costs were found to be key factors in providing accurate and affordable imagery to costal resource managers.

EAARL topography: Gateway National Recreation Area

USGS Publications Warehouse

Brock, John C.; Wright, C. Wayne; Patterson, Matt; Nayegandhi, Amar; Patterson, Judd

2007-01-01

This Web site contains Lidar-derived topography (bare earth) maps and GIS files for the Sandy Hook Unit within Gateway National Recreation Area in New Jersey. These Lidar-derived topography maps were produced as a collaborative effort between the U.S. Geological Survey (USGS) Coastal and Marine Geology Program, FISC St. Petersburg, the National Park Service (NPS) South Florida/Caribbean Network Inventory and Monitoring Program, and the National Aeronautics and Space Administration (NASA) Wallops Flight Facility. One objective of this research is to create techniques to survey coral reefs and barrier islands for the purposes of geomorphic change studies, habitat mapping, ecological monitoring, change detection, and event assessment. As part of this project, data from an innovative instrument under development at the NASA Wallops Flight Facility, the NASA Experimental Airborne Advanced Research Lidar (EAARL) are being used. This sensor has the potential to make significant contributions in this realm for measuring subaerial and submarine topography wthin cross-environment surveys. High spectral resolution, water-column correction, and low costs were found to be key factors in providing accurate and affordable imagery to costal resource managers.

EAARL topography: Assateague Island National Seashore

USGS Publications Warehouse

Brock, John C.; Wright, C. Wayne; Patterson, Matt; Nayegandhi, Amar; Travers, Laurinda J.

2007-01-01

This Web site contains 58 lidar-derived bare earth topography maps and GIS files for the Assateague Island National Seashore. These lidar-derived topography maps were produced as a collaborative effort between the U.S. Geological Survey (USGS) Coastal and Marine Geology Program, FISC St. Petersburg, Florida, the National Park Service (NPS) South Florida/Caribbean Network Inventory and Monitoring Program, and the National Aeronautics and Space Administration (NASA) Wallops Flight Facility. One objective of this research is to create techniques to survey coral reefs and barrier islands for the purposes of geomorphic change studies, habitat mapping, ecological monitoring, change detection, and event assessment. As part of this project, data from an innovative instrument under development at the NASA Wallops Flight Facility, the NASA Experimental Airborne Advanced Research Lidar (EAARL) are being used. This sensor has the potential to make significant contributions in this realm for measuring subaerial and submarine topography wthin cross-environment surveys. High spectral resolution, water-column correction, and low costs were found to be key factors in providing accurate and affordable imagery to costal resource managers.

EAARL topography: George Washington Birthplace National Monument

USGS Publications Warehouse

Brock, John C.; Wright, C. Wayne; Patterson, Matt; Nayegandhi, Amar; Patterson, Judd

2007-01-01

This Web site contains Lidar-derived topography (first return and bare earth) maps and GIS files for George Washington Birthplace National Monument in Virginia. These lidar-derived topography maps were produced as a collaborative effort between the U.S. Geological Survey (USGS) Coastal and Marine Geology Program, FISC St. Petersburg, the National Park Service (NPS), Northeast Coastal and Barrier Network, Inventory and Monitoring Program, and the National Aeronautics and Space Administration (NASA) Wallops Flight Facility. One objective of this research is to create techniques to survey coral reefs and barrier islands for the purposes of geomorphic change studies, habitat mapping, ecological monitoring, change detection, and event assessment. As part of this project, data from an innovative instrument under development at the NASA Wallops Flight Facility, the NASA Experimental Airborne Advanced Research Lidar (EAARL) are being used. This sensor has the potential to make significant contributions in this realm for measuring subaerial and submarine topography wthin cross-environment surveys. High spectral resolution, water-column correction, and low costs were found to be key factors in providing accurate and affordable imagery to coastal resource managers.

High-Resolution Mapping of Thermal History in Polymer Nanocomposites: Gold Nanorods as Microscale Temperature Sensors.

PubMed

Kennedy, W Joshua; Slinker, Keith A; Volk, Brent L; Koerner, Hilmar; Godar, Trenton J; Ehlert, Gregory J; Baur, Jeffery W

2015-12-23

A technique is reported for measuring and mapping the maximum internal temperature of a structural epoxy resin with high spatial resolution via the optically detected shape transformation of embedded gold nanorods (AuNRs). Spatially resolved absorption spectra of the nanocomposites are used to determine the frequencies of surface plasmon resonances. From these frequencies the AuNR aspect ratio is calculated using a new analytical approximation for the Mie-Gans scattering theory, which takes into account coincident changes in the local dielectric. Despite changes in the chemical environment, the calculated aspect ratio of the embedded nanorods is found to decrease over time to a steady-state value that depends linearly on the temperature over the range of 100-200 °C. Thus, the optical absorption can be used to determine the maximum temperature experienced at a particular location when exposure times exceed the temperature-dependent relaxation time. The usefulness of this approach is demonstrated by mapping the temperature of an internally heated structural epoxy resin with 10 μm lateral spatial resolution.

Evaluate ERTS imagery for mapping and detection of changes of snowcover on land and on glaciers

NASA Technical Reports Server (NTRS)

Meier, M. F. (Principal Investigator)

1972-01-01

The author has identified the following significant results. Preliminary results on the feasibility of mapping snow cover extent have been obtained from a limited number of ERTS-1 images of mountains in Alaska, British Columbia, and Washington. The snowline on land can be readily distinguished, except in heavy forest where such distinction appears to be virtually impossible. The snowline on very large glaciers can also be distinguished remarkably easily, leading to a convenient way to measure glacier accumulation area ratios or equilibrium line altitude. Monitoring of large surging glaciers appears to be possible, but only through observation of a change in area and/or medial moraine extent. Under certain conditions, ERTS-1 imagery appears to have high potential for mapping snow cover in mountainous areas. Distinction between snow and clouds appears to require use of the human eye, but in a cloud-free scene the snow cover is sufficiently distinct to allow use of automated techniques. This technique may prove very useful as an aid in the monitoring of the snowpack water resource and the prediction of summer snowmelt runoff volume.

An evaluation of the effectiveness of low-cost UAVs and structure from motion for geomorphic change detection

NASA Astrophysics Data System (ADS)

Cook, Kristen L.

2017-02-01

The measurement of topography and of topographic change is essential for the study of many geomorphic processes. In recent years, structure from motion (SfM) techniques applied to photographs taken by camera-equipped unmanned aerial vehicles (UAVs) has become a powerful new tool for the generation of high resolution topography. The variety of available UAV systems continues to increase rapidly, but it is not clear whether increased UAV sophistication translates into improved quality of the calculated topography. To evaluate the lower end of the UAV spectrum, a simple low cost UAV was deployed to calculate high resolution topography in the Daan River gorge in western Taiwan, a site with a complicated 3D morphology and a wide range of surface types, making it a challenging site for topographic measurement. Terrestrial lidar surveys were conducted in parallel with UAV surveys in both June and November 2014, enabling an assessment of the reliability of the UAV survey to detect geomorphic changes in the range of 30 cm to several meters. A further UAV survey was conducted in June 2015 in order to quantify changes resulting from the 2015 spring monsoon. To evaluate the accuracy of the UAV derived topography, it was compared to terrestrial lidar data collected during the same survey period using the cloud-to-cloud comparison algorithm M3C2. The UAV-generated point clouds match the lidar point clouds well, with RMS errors of 30-40 cm; however, the accuracy of the SfM point clouds depends strongly on the characteristics of the surface being considered, with vegetation, water, and small scale texture causing inaccuracies. The lidar and SfM data yield similar maps of change from June to November 2014, with the same areas of geomorphic change detected by both methods. The SfM-generated change map for November 2014 to June 2015 indicates that the 2015 spring monsoon caused erosion throughout the gorge and highlights the importance of event-driven erosion in the Daan River. The results suggest that even very basic UAVs can yield data suitable for measuring geomorphic change on the scale of a channel reach.

MO-FG-CAMPUS-TeP1-03: Pre-Treatment Surface Imaging Based Collision Detection

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

Wiant, D; Maurer, J; Liu, H

2016-06-15

Purpose: Modern radiotherapy increasingly employs large immobilization devices, gantry attachments, and couch rotations for treatments. All of which raise the risk of collisions between the patient and the gantry / couch. Collision detection is often achieved by manually checking each couch position in the treatment room and sometimes results in extraneous imaging if collisions are detected after image based setup has begun. In the interest of improving efficiency and avoiding extra imaging, we explore the use of a surface imaging based collision detection model. Methods: Surfaces acquired from AlignRT (VisionRT, London, UK) were transferred in wavefront format to a custommore » Matlab (Mathworks, Natick, MA) software package (CCHECK). Computed tomography (CT) scans acquired at the same time were sent to CCHECK in DICOM format. In CCHECK, binary maps of the surfaces were created and overlaid on the CT images based on the fixed relationship of the AlignRT and CT coordinate systems. Isocenters were added through a graphical user interface (GUI). CCHECK then compares the inputted surfaces to a model of the linear accelerator (linac) to check for collisions at defined gantry and couch positions. Note, CCHECK may be used with or without a CT. Results: The nominal surface image field of view is 650 mm × 900 mm, with variance based on patient position and size. The accuracy of collision detections is primarily based on the linac model and the surface mapping process. The current linac model and mapping process yield detection accuracies on the order of 5 mm, assuming no change in patient posture between surface acquisition and treatment. Conclusions: CCHECK provides a non-ionizing method to check for collisions without the patient in the treatment room. Collision detection accuracy may be improved with more robust linac modeling. Additional gantry attachments (e.g. conical collimators) can be easily added to the model.« less

Measuring land-use and land-cover change using the U.S. department of agriculture's cropland data layer: Cautions and recommendations

NASA Astrophysics Data System (ADS)

Lark, Tyler J.; Mueller, Richard M.; Johnson, David M.; Gibbs, Holly K.

2017-10-01

Monitoring agricultural land is important for understanding and managing food production, environmental conservation efforts, and climate change. The United States Department of Agriculture's Cropland Data Layer (CDL), an annual satellite imagery-derived land cover map, has been increasingly used for this application since complete coverage of the conterminous United States became available in 2008. However, the CDL is designed and produced with the intent of mapping annual land cover rather than tracking changes over time, and as a result certain precautions are needed in multi-year change analyses to minimize error and misapplication. We highlight scenarios that require special considerations, suggest solutions to key challenges, and propose a set of recommended good practices and general guidelines for CDL-based land change estimation. We also characterize a problematic issue of crop area underestimation bias within the CDL that needs to be accounted for and corrected when calculating changes to crop and cropland areas. When used appropriately and in conjunction with related information, the CDL is a valuable and effective tool for detecting diverse trends in agriculture. By explicitly discussing the methods and techniques for post-classification measurement of land-cover and land-use change using the CDL, we aim to further stimulate the discourse and continued development of suitable methodologies. Recommendations generated here are intended specifically for the CDL but may be broadly applicable to additional remotely-sensed land cover datasets including the National Land Cover Database (NLCD), Moderate Resolution Imaging Spectroradiometer (MODIS)-based land cover products, and other regional, national, and global land cover classification maps.

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

Ciuca, Razvan; Hernández, Oscar F., E-mail: razvan.ciuca@mail.mcgill.ca, E-mail: oscarh@physics.mcgill.ca

There exists various proposals to detect cosmic strings from Cosmic Microwave Background (CMB) or 21 cm temperature maps. Current proposals do not aim to find the location of strings on sky maps, all of these approaches can be thought of as a statistic on a sky map. We propose a Bayesian interpretation of cosmic string detection and within that framework, we derive a connection between estimates of cosmic string locations and cosmic string tension G μ. We use this Bayesian framework to develop a machine learning framework for detecting strings from sky maps and outline how to implement this frameworkmore » with neural networks. The neural network we trained was able to detect and locate cosmic strings on noiseless CMB temperature map down to a string tension of G μ=5 ×10{sup −9} and when analyzing a CMB temperature map that does not contain strings, the neural network gives a 0.95 probability that G μ≤2.3×10{sup −9}.« less

The Tölz Temporal Topography Study: mapping the visual field across the life span. Part I: the topography of light detection and temporal-information processing.

PubMed

Poggel, Dorothe A; Treutwein, Bernhard; Calmanti, Claudia; Strasburger, Hans

2012-08-01

Temporal performance parameters vary across the visual field. Their topographical distributions relative to each other and relative to basic visual performance measures and their relative change over the life span are unknown. Our goal was to characterize the topography and age-related change of temporal performance. We acquired visual field maps in 95 healthy participants (age: 10-90 years): perimetric thresholds, double-pulse resolution (DPR), reaction times (RTs), and letter contrast thresholds. DPR and perimetric thresholds increased with eccentricity and age; the periphery showed a more pronounced age-related increase than the center. RT increased only slightly and uniformly with eccentricity. It remained almost constant up to the age of 60, a marked change occurring only above 80. Overall, age was a poor predictor of functionality. Performance decline could be explained only in part by the aging of the retina and optic media. In Part II, we therefore examine higher visual and cognitive functions.

Development of a multiplex Luminex assay for detecting swine antibodies to structural and nonstructural proteins of foot-and-mouth disease virus in Taiwan.

PubMed

Chen, Tsu-Han; Lee, Fan; Lin, Yeou-Liang; Pan, Chu-Hsiang; Shih, Chia-Ni; Tseng, Chun-Hsien; Tsai, Hsiang-Jung

2016-04-01

Foot-and-mouth disease (FMD) and swine vesicular disease (SVD) are serious vesicular diseases that have devastated swine populations throughout the world. The aim of this study was to develop a multianalyte profiling (xMAP) Luminex assay for the differential detection of antibodies to the FMD virus of structural proteins (SP) and nonstructural proteins (NSP). After the xMAP was optimized, it detected antibodies to SP-VP1 and NSP-3ABC of the FMD virus in a single serum sample. These tests were also compared with 3ABC polypeptide blocking enzyme-linked immunosorbent assay (ELISA) and virus neutralization test (VNT) methods for the differential diagnosis and assessment of immune status, respectively. To detect SP antibodies in 661 sera from infected naïve pigs and vaccinated pigs, the diagnostic sensitivity (DSn) and diagnostic specificity (DSp) of the xMAP were 90.0-98.7% and 93.0-96.5%, respectively. To detect NSP antibodies, the DSn was 90% and the DSp ranged from 93.3% to 99.1%. The xMAP can detect the immune response to SP and NSP as early as 4 days postinfection and 8 days postinfection, respectively. Furthermore, the SP and NSP antibodies in all 15 vaccinated but unprotected pigs were detected by xMAP. A comparison of SP and NSP antibodies detected in the sera of the infected samples indicated that the results from the xMAP had a high positive correlation with results from the VNT and a 3ABC polypeptide blocking ELISA assay. However, simultaneous quantitation detected that xMAP had no relationship with the VNT. Furthermore, the specificity was 93.3-94.9% with 3ABC polypeptide blocking ELISA for the FMDV-NSP antibody. The results indicated that xMAP has the potential to detect antibodies to FMDV-SP-VP1 and NSP-3ABC and to distinguish FMDV-infected pigs from pigs infected with the swine vesicular disease virus. Copyright © 2014. Published by Elsevier B.V.

The Analysis of Object-Based Change Detection in Mining Area: a Case Study with Pingshuo Coal Mine

NASA Astrophysics Data System (ADS)

Zhang, M.; Zhou, W.; Li, Y.

2017-09-01

Accurate information on mining land use and land cover change are crucial for monitoring and environmental change studies. In this paper, RapidEye Remote Sensing Image (Map 2012) and SPOT7 Remote Sensing Image (Map 2015) in Pingshuo Mining Area are selected to monitor changes combined with object-based classification and change vector analysis method, we also used R in highresolution remote sensing image for mining land classification, and found the feasibility and the flexibility of open source software. The results show that (1) the classification of reclaimed mining land has higher precision, the overall accuracy and kappa coefficient of the classification of the change region map were 86.67 % and 89.44 %. It's obvious that object-based classification and change vector analysis which has a great significance to improve the monitoring accuracy can be used to monitor mining land, especially reclaiming mining land; (2) the vegetation area changed from 46 % to 40 % accounted for the proportion of the total area from 2012 to 2015, and most of them were transformed into the arable land. The sum of arable land and vegetation area increased from 51 % to 70 %; meanwhile, build-up land has a certain degree of increase, part of the water area was transformed into arable land, but the extent of the two changes is not obvious. The result illustrated the transformation of reclaimed mining area, at the same time, there is still some land convert to mining land, and it shows the mine is still operating, mining land use and land cover are the dynamic procedure.

Flood Extent Mapping for Namibia Using Change Detection and Thresholding with SAR

NASA Technical Reports Server (NTRS)

Long, Stephanie; Fatoyinbo, Temilola E.; Policelli, Frederick

2014-01-01

A new method for flood detection change detection and thresholding (CDAT) was used with synthetic aperture radar (SAR) imagery to delineate the extent of flooding for the Chobe floodplain in the Caprivi region of Namibia. This region experiences annual seasonal flooding and has seen a recent renewal of severe flooding after a long dry period in the 1990s. Flooding in this area has caused loss of life and livelihoods for the surrounding communities and has caught the attention of disaster relief agencies. There is a need for flood extent mapping techniques that can be used to process images quickly, providing near real-time flooding information to relief agencies. ENVISAT/ASAR and Radarsat-2 images were acquired for several flooding seasons from February 2008 to March 2013. The CDAT method was used to determine flooding from these images and includes the use of image subtraction, decision based classification with threshold values, and segmentation of SAR images. The total extent of flooding determined for 2009, 2011 and 2012 was about 542 km2, 720 km2, and 673 km2 respectively. Pixels determined to be flooded in vegetation were typically <0.5 % of the entire scene, with the exception of 2009 where the detection of flooding in vegetation was much greater (almost one third of the total flooded area). The time to maximum flooding for the 2013 flood season was determined to be about 27 days. Landsat water classification was used to compare the results from the new CDAT with SAR method; the results show good spatial agreement with Landsat scenes.

Spatio-Semantic Comparison of Large 3d City Models in Citygml Using a Graph Database

NASA Astrophysics Data System (ADS)

Nguyen, S. H.; Yao, Z.; Kolbe, T. H.

2017-10-01

A city may have multiple CityGML documents recorded at different times or surveyed by different users. To analyse the city's evolution over a given period of time, as well as to update or edit the city model without negating modifications made by other users, it is of utmost importance to first compare, detect and locate spatio-semantic changes between CityGML datasets. This is however difficult due to the fact that CityGML elements belong to a complex hierarchical structure containing multi-level deep associations, which can basically be considered as a graph. Moreover, CityGML allows multiple syntactic ways to define an object leading to syntactic ambiguities in the exchange format. Furthermore, CityGML is capable of including not only 3D urban objects' graphical appearances but also their semantic properties. Since to date, no known algorithm is capable of detecting spatio-semantic changes in CityGML documents, a frequent approach is to replace the older models completely with the newer ones, which not only costs computational resources, but also loses track of collaborative and chronological changes. Thus, this research proposes an approach capable of comparing two arbitrarily large-sized CityGML documents on both semantic and geometric level. Detected deviations are then attached to their respective sources and can easily be retrieved on demand. As a result, updating a 3D city model using this approach is much more efficient as only real changes are committed. To achieve this, the research employs a graph database as the main data structure for storing and processing CityGML datasets in three major steps: mapping, matching and updating. The mapping process transforms input CityGML documents into respective graph representations. The matching process compares these graphs and attaches edit operations on the fly. Found changes can then be executed using the Web Feature Service (WFS), the standard interface for updating geographical features across the web.

Relative impact of previous disturbance history on the likelihood of additional disturbance in the Northern United States Forest Service USFS Region

NASA Astrophysics Data System (ADS)

Hernandez, A. J.

2015-12-01

The Landsat archive is increasingly being used to detect trends in the occurrence of forest disturbance. Beyond information about the amount of area affected, forest managers need to know if and how disturbance regimes change. The National Forest System (NFS) has developed a comprehensive plan for carbon monitoring that requires a detailed temporal mapping of forest disturbances across 75 million hectares. A long-term annual time series that shows the timing, extent, and type of disturbance beginning in 1990 and ending in 2011 has been prepared for several USFS Regions, including the Northern Region. Our mapping starts with an automated detection of annual disturbances using a time series of historical Landsat imagery. Automated detections are meticulously inspected, corrected and labeled using various USFS ancillary datasets. The resulting maps of verified disturbance show the timing and types are fires, harvests, insect activity, disease, and abiotic (wind, drought, avalanche) damage. Also, the magnitude of each change event is modeled in terms of the proportion of canopy cover lost. The sequence of disturbances for every pixel since 1990 has been consistently mapped and is available across the entirety of NFS. Our datasets contain sufficient information to describe the frequency of stand replacement, as well as how often disturbance results in only a partial loss of canopy. This information provides empirical insight into how an initial disturbance may predispose a stand to further disturbance, and it also show a climatic signal in the occurrence of processes such as fire and insect epidemics. Thus, we have the information to model the likelihood of occurrence of certain disturbances after a given event (i.e. if we have a fire in the past what does that do to the likelihood of occurrence of insects in the future). Here, we explore if previous disturbance history is a reliable predictor of additional disturbance in the future and we present results of applying logistic regression to obtain predicted probabilities of occurrence of additional disturbance types. We describe responses in additional disturbance and prominent trends for each major forest type.

Dynamic Flood Vulnerability Mapping with Google Earth Engine

NASA Astrophysics Data System (ADS)

Tellman, B.; Kuhn, C.; Max, S. A.; Sullivan, J.

2015-12-01

Satellites capture the rate and character of environmental change from local to global levels, yet integrating these changes into flood exposure models can be cost or time prohibitive. We explore an approach to global flood modeling by leveraging satellite data with computing power in Google Earth Engine to dynamically map flood hazards. Our research harnesses satellite imagery in two main ways: first to generate a globally consistent flood inundation layer and second to dynamically model flood vulnerability. Accurate and relevant hazard maps rely on high quality observation data. Advances in publicly available spatial, spectral, and radar data together with cloud computing allow us to improve existing efforts to develop a comprehensive flood extent database to support model training and calibration. This talk will demonstrate the classification results of algorithms developed in Earth Engine designed to detect flood events by combining observations from MODIS, Landsat 8, and Sentinel-1. Our method to derive flood footprints increases the number, resolution, and precision of spatial observations for flood events both in the US, recorded in the NCDC (National Climatic Data Center) storm events database, and globally, as recorded events from the Colorado Flood Observatory database. This improved dataset can then be used to train machine learning models that relate spatial temporal flood observations to satellite derived spatial temporal predictor variables such as precipitation, antecedent soil moisture, and impervious surface. This modeling approach allows us to rapidly update models with each new flood observation, providing near real time vulnerability maps. We will share the water detection algorithms used with each satellite and discuss flood detection results with examples from Bihar, India and the state of New York. We will also demonstrate how these flood observations are used to train machine learning models and estimate flood exposure. The final stage of our comprehensive approach to flood vulnerability couples inundation extent with social data to determine which flood exposed communities have the greatest propensity for loss. Specifically, by linking model outputs to census derived social vulnerability estimates (Indian and US, respectively) to predict how many people are at risk.

Mapping the Critical Gestational Age at Birth that Alters Brain Development in Preterm-born Infants using Multi-Modal MRI

PubMed Central

Wu, Dan; Chang, Linda; Akazawa, Kentaro; Oishi, Kumiko; Skranes, Jon; Ernst, Thomas; Oishi, Kenichi

2017-01-01

Preterm birth adversely affects postnatal brain development. In order to investigate the critical gestational age at birth (GAB) that alters the developmental trajectory of gray and white matter structures in the brain, we investigated diffusion tensor and quantitative T2 mapping data in 43 term-born and 43 preterm-born infants. A novel multivariate linear model—the change point model, was applied to detect change points in fractional anisotropy, mean diffusivity, and T2 relaxation time. Change points captured the “critical” GAB value associated with a change in the linear relation between GAB and MRI measures. The analysis was performed in 126 regions across the whole brain using an atlas-based image quantification approach to investigate the spatial pattern of the critical GAB. Our results demonstrate that the critical GABs are region- and modality-specific, generally following a central-to-peripheral and bottom-to-top order of structural development. This study may offer unique insights into the postnatal neurological development associated with differential degrees of preterm birth. PMID:28111189

Mapping the critical gestational age at birth that alters brain development in preterm-born infants using multi-modal MRI.

PubMed

Wu, Dan; Chang, Linda; Akazawa, Kentaro; Oishi, Kumiko; Skranes, Jon; Ernst, Thomas; Oishi, Kenichi

2017-04-01

Preterm birth adversely affects postnatal brain development. In order to investigate the critical gestational age at birth (GAB) that alters the developmental trajectory of gray and white matter structures in the brain, we investigated diffusion tensor and quantitative T2 mapping data in 43 term-born and 43 preterm-born infants. A novel multivariate linear model-the change point model, was applied to detect change points in fractional anisotropy, mean diffusivity, and T2 relaxation time. Change points captured the "critical" GAB value associated with a change in the linear relation between GAB and MRI measures. The analysis was performed in 126 regions across the whole brain using an atlas-based image quantification approach to investigate the spatial pattern of the critical GAB. Our results demonstrate that the critical GABs are region- and modality-specific, generally following a central-to-peripheral and bottom-to-top order of structural development. This study may offer unique insights into the postnatal neurological development associated with differential degrees of preterm birth. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Detection of IMRT delivery errors based on a simple constancy check of transit dose by using an EPID

NASA Astrophysics Data System (ADS)

Baek, Tae Seong; Chung, Eun Ji; Son, Jaeman; Yoon, Myonggeun

2015-11-01

Beam delivery errors during intensity modulated radiotherapy (IMRT) were detected based on a simple constancy check of the transit dose by using an electronic portal imaging device (EPID). Twenty-one IMRT plans were selected from various treatment sites, and the transit doses during treatment were measured by using an EPID. Transit doses were measured 11 times for each course of treatment, and the constancy check was based on gamma index (3%/3 mm) comparisons between a reference dose map (the first measured transit dose) and test dose maps (the following ten measured dose maps). In a simulation using an anthropomorphic phantom, the average passing rate of the tested transit dose was 100% for three representative treatment sites (head & neck, chest, and pelvis), indicating that IMRT was highly constant for normal beam delivery. The average passing rate of the transit dose for 1224 IMRT fields from 21 actual patients was 97.6% ± 2.5%, with the lower rate possibly being due to inaccuracies of patient positioning or anatomic changes. An EPIDbased simple constancy check may provide information about IMRT beam delivery errors during treatment.

Autonomous Underwater Navigation and Optical Mapping in Unknown Natural Environments.

PubMed

Hernández, Juan David; Istenič, Klemen; Gracias, Nuno; Palomeras, Narcís; Campos, Ricard; Vidal, Eduard; García, Rafael; Carreras, Marc

2016-07-26

We present an approach for navigating in unknown environments while, simultaneously, gathering information for inspecting underwater structures using an autonomous underwater vehicle (AUV). To accomplish this, we first use our pipeline for mapping and planning collision-free paths online, which endows an AUV with the capability to autonomously acquire optical data in close proximity. With that information, we then propose a reconstruction pipeline to create a photo-realistic textured 3D model of the inspected area. These 3D models are also of particular interest to other fields of study in marine sciences, since they can serve as base maps for environmental monitoring, thus allowing change detection of biological communities and their environment over time. Finally, we evaluate our approach using the Sparus II, a torpedo-shaped AUV, conducting inspection missions in a challenging, real-world and natural scenario.

Interpretation of geographic patterns in simulated orbital television imagery of earth resources

NASA Technical Reports Server (NTRS)

Latham, J. P.; Cross, C. I.; Kuyper, W. H.; Witmer, R. E.

1972-01-01

In order to better determine the effects of the television imagery characteristics upon the interpretation of geographic patterns obtainable from orbital television sensors, and in order to better evaluate the influences of alternative sensor system parameters such as changes in orbital altitudes or scan line rates, a team of three professional interpreters independently mapped thematically the selected geographic phenomena that they could detect in orbital television imagery produced on a fourteen inch monitor and recorded photographically for analysis. Three thematic maps were compiled by each interpreter. The maps were: (1) transportation patterns; (2) other land use; and (3) physical regions. The results from the three interpreters are compared, agreements noted, and differences analyzed for cause such as disagreement on identification of phenomenon, visual acuity, differences in interpretation techniques, and differing professional backgrounds.

Autonomous Underwater Navigation and Optical Mapping in Unknown Natural Environments

PubMed Central

Hernández, Juan David; Istenič, Klemen; Gracias, Nuno; Palomeras, Narcís; Campos, Ricard; Vidal, Eduard; García, Rafael; Carreras, Marc

2016-01-01

We present an approach for navigating in unknown environments while, simultaneously, gathering information for inspecting underwater structures using an autonomous underwater vehicle (AUV). To accomplish this, we first use our pipeline for mapping and planning collision-free paths online, which endows an AUV with the capability to autonomously acquire optical data in close proximity. With that information, we then propose a reconstruction pipeline to create a photo-realistic textured 3D model of the inspected area. These 3D models are also of particular interest to other fields of study in marine sciences, since they can serve as base maps for environmental monitoring, thus allowing change detection of biological communities and their environment over time. Finally, we evaluate our approach using the Sparus II, a torpedo-shaped AUV, conducting inspection missions in a challenging, real-world and natural scenario. PMID:27472337

Monitoring the urban expansion of Athens using remote sensing and GIS techniques in the last 35 years

NASA Astrophysics Data System (ADS)

Nikolakopoulos, Konstantinos; Pavlopoulos, Kosmas; Chalkias, Christos; Manou, Dora

2005-10-01

During the last thirty-five years the capital of Greece has suffered from an enormous internal immigration. Its population has overpassed the five millions and today almost the half population of Greece is squeezed in Athens metropolitan area. Because of the significant increase of population, the urban expansion in the basin of Athens was also excessive and in some cases catastrophic. Buildings have covered all the free places, new roads have been constructed, the drainage networks have been covered or disappeared and a lot of changes have been occurred to the landforms. The construction of the new airport (Elefterios Venizelos) at the beginning of this decade created a new commercial and urban pole at the eastern part of Athens and the constructive activity has been moved to new areas around the airport. Our aim was to detect and map all the changes that occurred in the urban area, estimate the urban expansion rate and the human interferences in the natural landscape, using GIS and remote sensing techniques. We have used satellite images from three different periods (1973, 1992, 2002) and topographic maps of 1:25.000 scale. The spatial resolution of all the satellite images ranges from 5 to 10 meters and is it acceptable for the monitoring and mapping of the urban growth. Supervised classification and on screen digitizing methods have been used in order to map the changes. Finally the qualitative and quantitative results of this study are presented in this paper.

Atmospheric Correction of High-Spatial-Resolution Commercial Satellite Imagery Products Using MODIS Atmospheric Products

NASA Technical Reports Server (NTRS)

Pagnutti, Mary; Holekamp, Kara; Ryan, Robert E.; Vaughan, Ronald; Russell, Jeffrey A.; Prados, Don; Stanley, Thomas

2005-01-01

Remotely sensed ground reflectance is the basis for many inter-sensor interoperability or change detection techniques. Satellite inter-comparisons and accurate vegetation indices such as the Normalized Difference Vegetation Index, which is used to describe or to imply a wide variety of biophysical parameters and is defined in terms of near-infrared and redband reflectance, require the generation of accurate reflectance maps. This generation relies upon the removal of solar illumination, satellite geometry, and atmospheric effects and is generally referred to as atmospheric correction. Atmospheric correction of remotely sensed imagery to ground reflectance, however, has been widely applied to only a few systems. In this study, we atmospherically corrected commercially available, high spatial resolution IKONOS and QuickBird imagery using several methods to determine the accuracy of the resulting reflectance maps. We used extensive ground measurement datasets for nine IKONOS and QuickBird scenes acquired over a two-year period to establish reflectance map accuracies. A correction approach using atmospheric products derived from Moderate Resolution Imaging Spectrometer data created excellent reflectance maps and demonstrated a reliable, effective method for reflectance map generation.

Mapping the Sensitivity of the Public Emotion to the Movement of STOCK Market Value: a Case Study of Manhattan

NASA Astrophysics Data System (ADS)

Kang, Y.; Wang, J.; Wang, Y.; Angsuesser, S.; Fei, T.

2017-09-01

We examined whether emotion expressed by users in social media can be influenced by stock market index or can predict the fluctuation of the stock market index. We collected the emotion data by using face detection technology and emotion cognition services for photos uploaded to Flickr. Each face's emotion was described in 8 dimensions the location was also recorded. An emotion score index was defined based on the combination of all 8 dimensions of emotion calculated by principal component analysis. The correlation coefficients between the stock market values and emotion scores are significant (R > 0.59 with p < 0.01). Using Granger Causality analysis for cause and effect detection, we found that users' emotion is influenced by stock market value change. A multiple linear regression model was established (R-square = 0.76) to explore the potential factors that influence the emotion score. Finally, a sensitivity map was created to show sensitive areas where human emotion is easily affected by the stock market changes. We concluded that in Manhattan region: (1) there is an obvious relationship between human emotion and stock market fluctuation; (2) emotion change follows the movements of the stock market; (3) the Times Square and Broadway Theatre are the most sensitive regions in terms of public emotional reaction to the economy represented by stock value.

Aircraft Detection in High-Resolution SAR Images Based on a Gradient Textural Saliency Map

PubMed Central

Tan, Yihua; Li, Qingyun; Li, Yansheng; Tian, Jinwen

2015-01-01

This paper proposes a new automatic and adaptive aircraft target detection algorithm in high-resolution synthetic aperture radar (SAR) images of airport. The proposed method is based on gradient textural saliency map under the contextual cues of apron area. Firstly, the candidate regions with the possible existence of airport are detected from the apron area. Secondly, directional local gradient distribution detector is used to obtain a gradient textural saliency map in the favor of the candidate regions. In addition, the final targets will be detected by segmenting the saliency map using CFAR-type algorithm. The real high-resolution airborne SAR image data is used to verify the proposed algorithm. The results demonstrate that this algorithm can detect aircraft targets quickly and accurately, and decrease the false alarm rate. PMID:26378543

Radio Astronomers Develop New Technique for Studying Dark Energy

NASA Astrophysics Data System (ADS)

2010-07-01

Pioneering observations with the National Science Foundation's giant Robert C. Byrd Green Bank Telescope (GBT) have given astronomers a new tool for mapping large cosmic structures. The new tool promises to provide valuable clues about the nature of the mysterious "dark energy" believed to constitute nearly three-fourths of the mass and energy of the Universe. Dark energy is the label scientists have given to what is causing the Universe to expand at an accelerating rate. While the acceleration was discovered in 1998, its cause remains unknown. Physicists have advanced competing theories to explain the acceleration, and believe the best way to test those theories is to precisely measure large-scale cosmic structures. Sound waves in the matter-energy soup of the extremely early Universe are thought to have left detectable imprints on the large-scale distribution of galaxies in the Universe. The researchers developed a way to measure such imprints by observing the radio emission of hydrogen gas. Their technique, called intensity mapping, when applied to greater areas of the Universe, could reveal how such large-scale structure has changed over the last few billion years, giving insight into which theory of dark energy is the most accurate. "Our project mapped hydrogen gas to greater cosmic distances than ever before, and shows that the techniques we developed can be used to map huge volumes of the Universe in three dimensions and to test the competing theories of dark energy," said Tzu-Ching Chang, of the Academia Sinica in Taiwan and the University of Toronto. To get their results, the researchers used the GBT to study a region of sky that previously had been surveyed in detail in visible light by the Keck II telescope in Hawaii. This optical survey used spectroscopy to map the locations of thousands of galaxies in three dimensions. With the GBT, instead of looking for hydrogen gas in these individual, distant galaxies -- a daunting challenge beyond the technical capabilities of current instruments -- the team used their intensity-mapping technique to accumulate the radio waves emitted by the hydrogen gas in large volumes of space including many galaxies. "Since the early part of the 20th Century, astronomers have traced the expansion of the Universe by observing galaxies. Our new technique allows us to skip the galaxy-detection step and gather radio emissions from a thousand galaxies at a time, as well as all the dimly-glowing material between them," said Jeffrey Peterson, of Carnegie Mellon University. The astronomers also developed new techniques that removed both man-made radio interference and radio emission caused by more-nearby astronomical sources, leaving only the extremely faint radio waves coming from the very distant hydrogen gas. The result was a map of part of the "cosmic web" that correlated neatly with the structure shown by the earlier optical study. The team first proposed their intensity-mapping technique in 2008, and their GBT observations were the first test of the idea. "These observations detected more hydrogen gas than all the previously-detected hydrogen in the Universe, and at distances ten times farther than any radio wave-emitting hydrogen seen before," said Ue-Li Pen of the University of Toronto. "This is a demonstration of an important technique that has great promise for future studies of the evolution of large-scale structure in the Universe," said National Radio Astronomy Observatory Chief Scientist Chris Carilli, who was not part of the research team. In addition to Chang, Peterson, and Pen, the research team included Kevin Bandura of Carnegie Mellon University. The scientists reported their work in the July 22 issue of the scientific journal Nature.

Integrating Radarsat-2, Lidar, and Worldview-3 Imagery to maximize detection of forested inundation extent in the Delmarva Peninsula, USA

USGS Publications Warehouse

Vanderhoof, Melanie; Distler, Hayley; Mendiola, Di Ana; Lang, Megan

2017-01-01

Natural variability in surface-water extent and associated characteristics presents a challenge to gathering timely, accurate information, particularly in environments that are dominated by small and/or forested wetlands. This study mapped inundation extent across the Upper Choptank River Watershed on the Delmarva Peninsula, occurring within both Maryland and Delaware. We integrated six quad-polarized Radarsat-2 images, Worldview-3 imagery, and an enhanced topographic wetness index in a random forest model. Output maps were filtered using light detection and ranging (lidar)-derived depressions to maximize the accuracy of forested inundation extent. Overall accuracy within the integrated and filtered model was 94.3%, with 5.5% and 6.0% errors of omission and commission for inundation, respectively. Accuracy of inundation maps obtained using Radarsat-2 alone were likely detrimentally affected by less than ideal angles of incidence and recent precipitation, but were likely improved by targeting the period between snowmelt and leaf-out for imagery collection. Across the six Radarsat-2 dates, filtering inundation outputs by lidar-derived depressions slightly elevated errors of omission for water (+1.0%), but decreased errors of commission (−7.8%), resulting in an average increase of 5.4% in overall accuracy. Depressions were derived from lidar datasets collected under both dry and average wetness conditions. Although antecedent wetness conditions influenced the abundance and total area mapped as depression, the two versions of the depression datasets showed a similar ability to reduce error in the inundation maps. Accurate mapping of surface water is critical to predicting and monitoring the effect of human-induced change and interannual variability on water quantity and quality.

Automatic Rock Detection and Mapping from HiRISE Imagery

NASA Technical Reports Server (NTRS)

Huertas, Andres; Adams, Douglas S.; Cheng, Yang

2008-01-01

This system includes a C-code software program and a set of MATLAB software tools for statistical analysis and rock distribution mapping. The major functions include rock detection and rock detection validation. The rock detection code has been evolved into a production tool that can be used by engineers and geologists with minor training.

Investigation of the effects of construction and stage filling of reservoirs on the environment and ecology: Preproject baseline. [Missouri

NASA Technical Reports Server (NTRS)

Riggins, R. E. (Principal Investigator); Anderson, J. R.

1977-01-01

The author has identified the following significant results: (1) LANDSAT imagery can be used effectively as a baseline for detection of environmental change, resulting from construction of a major inland reservoir. (2) Forest cover can be observed adequately on two-band composite enlargements at a scale of 1:130,000. (3) Forest cover delineated on LANDSAT enlargements compares accurately with ground truth at a scale of 1:250,000. (4) A dual image mapping technique superimposing winter, summer, and spring scenes using the zoom transfer scope facilitates the determination. (5) The same technique can be used to detect changes in the project area, resulting from construction activities. (6) High altitude aircraft imagery can also be used to interpret changes in land use and forest type. (7) Construction operations can be more clearly detailed on the air photos than on LANDSAT imagery.

Detecting changes in the nutritional value and elemental composition of transgenic sorghum grain

NASA Astrophysics Data System (ADS)

Ndimba, R.; Grootboom, A. W.; Mehlo, L.; Mkhonza, N. L.; Kossmann, J.; Barnabas, A. D.; Mtshali, C.; Pineda-Vargas, C.

2015-11-01

We have previously demonstrated that poor digestibility in sorghum can be addressed by using RNA interference (RNAi) to suppress kafirin synthesis. The approach resulted in a twofold improvement in overall protein digestibility levels. In the present study, the effect of this targeted kafirin suppression on other grain quality parameters was investigated. Several significant changes in the proximate composition, amino acid profile and the bulk mineral content were detected. Importantly, the most limiting amino acid, lysine, was significantly increased in the transgenic grains by up to 39%; whilst mineral elements in the bulk, such as sulphur (S) and zinc (Zn) were reduced by up to 15.8% and 21% respectively. Elemental mapping of the grain tissue, using micro-PIXE, demonstrated a significant decrease in Zn (>75%), which was localised to the outer endosperm region, whilst TEM revealed important changes to the protein body morphology of the transgenic grains.

Mycobacterium avium ss. paratuberculosis Zoonosis – The Hundred Year War – Beyond Crohn’s Disease

PubMed Central

Sechi, Leonardo A.; Dow, Coad Thomas

2015-01-01

The factitive role of Mycobacterium avium ss. paratuberculosis (MAP) in Crohn’s disease has been debated for more than a century. The controversy is due to the fact that Crohn’s disease is so similar to a disease of MAP-infected ruminant animals, Johne’s disease; and, though MAP can be readily detected in the infected ruminants, it is much more difficult to detect in humans. Molecular techniques that can detect MAP in pathologic Crohn’s specimens as well as dedicated specialty labs successful in culturing MAP from Crohn’s patients have provided strong argument for MAP’s role in Crohn’s disease. Perhaps more incriminating for MAP as a zoonotic agent is the increasing number of diseases with which MAP has been related: Blau syndrome, type 1 diabetes, Hashimoto thyroiditis, and multiple sclerosis. In this article, we debate about genetic susceptibility to mycobacterial infection and human exposure to MAP; moreover, it suggests that molecular mimicry between protein epitopes of MAP and human proteins is a likely bridge between infection and these autoimmune disorders. PMID:25788897

Detection of Deforestation and Land Conversion in Rondonia, Brazil Using Change Detection Techniques

NASA Technical Reports Server (NTRS)

Guild, Liane S.; Cohen, Warren B,; Kauffman, J. Boone; Peterson, David L. (Technical Monitor)

2001-01-01

Fires associated with tropical deforestation, land conversion, and land use greatly contribute to emissions as well as the depletion of carbon and nutrient pools. The objective of this research was to compare change detection techniques for identifying deforestation and cattle pasture formation during a period of early colonization and agricultural expansion in the vicinity of Jamari, Rond6nia. Multi-date Landsat Thematic Mapper (TM) data between 1984 and 1992 was examined in a 94 370-ha area of active deforestation to map land cover change. The Tasseled Cap (TC) transformation was used to enhance the contrast between forest, cleared areas, and regrowth. TC images were stacked into a composite multi-date TC and used in a principal components (PC) transformation to identify change components. In addition, consecutive TC image pairs were differenced and stacked into a composite multi-date differenced image. A maximum likelihood classification of each image composite was compared for identification of land cover change. The multi-date TC composite classification had the best accuracy of 78.1% (kappa). By 1984, only 5% of the study area had been cleared, but by 1992, 11% of the area had been deforested, primarily for pasture and 7% lost due to hydroelectric dam flooding. Finally, discrimination of pasture versus cultivation was improved due to the ability to detect land under sustained clearing opened to land exhibiting regrowth with infrequent clearing.

Topography changes monitoring of small islands using camera drone

NASA Astrophysics Data System (ADS)

Bang, E.

2017-12-01

Drone aerial photogrammetry was conducted for monitoring topography changes of small islands in the east sea of Korea. Severe weather and sea wave is eroding the islands and sometimes cause landslide and falling rock. Due to rugged cliffs in all direction and bad accessibility, ground based survey methods are less efficient in monitoring topography changes of the whole area. Camera drones can provide digital images and movie in every corner of the islands, and drone aerial photogrammetry is powerful to get precise digital surface model (DSM) for a limited area. We have got a set of digital images to construct a textured 3D model of the project area every year since 2014. Flight height is in less than 100m from the top of those islands to get enough ground sampling distance (GSD). Most images were vertically captured with automatic flights, but we also flied drones around the islands with about 30°-45° camera angle for constructing 3D model better. Every digital image has geo-reference, but we set several ground control points (GCPs) on the islands and their coordinates were measured with RTK surveying methods to increase the absolute accuracy of the project. We constructed 3D textured model using photogrammetry tool, which generates 3D spatial information from digital images. From the polygonal model, we could get DSM with contour lines. Thematic maps such as hill shade relief map, aspect map and slope map were also processed. Those maps make us understand topography condition of the project area better. The purpose of this project is monitoring topography change of these small islands. Elevation difference map between DSMs of each year is constructed. There are two regions showing big negative difference value. By comparing constructed textured models and captured digital images around these regions, it is checked that a region have experienced real topography change. It is due to huge rock fall near the center of the east island. The size of fallen rock can be measured on the digital model exactly, which is about 13m*6m*2m (height*width*thickness). We believe that drone aerial photogrammetry can be an efficient topography changes detection method for a complicated terrain area.

Correlation between microbial flora, sensory changes and biogenic amines formation in fresh chicken meat stored aerobically or under modified atmosphere packaging at 4 degrees C: possible role of biogenic amines as spoilage indicators.

PubMed

Balamatsia, C C; Paleologos, E K; Kontominas, M G; Savvaidis, I N

2006-01-01

This study evaluated the formation of biogenic amines (BAs) in breast chicken meat during storage under aerobic and modified atmospheric packaging (MAP) conditions at 4 degrees C, the correlation of microbial and sensory changes in chicken meat with formation of BAs and the possible role of BAs as indicators of poultry meat spoilage. Poultry breast fillets were stored aerobically or under MAP (30%, CO(2), 70% N(2)) at 4 degrees C for up to 17 days. Quality evaluation was carried out using microbiological, chemical and sensory analyses. Total viable counts, Pseudomonads and Enterobacteriaceae, were in general higher for chicken samples packaged in air whereas lactic acid bacteria (LAB) and Enterobacteriaceae were among the dominant species for samples under MAP. Levels of putrescine and cadaverine increased linearly with storage time and were higher in aerobically stored chicken samples. Spermine and spermidine levels were also detected in both aerobically and MAP stored chicken meat. Levels of tyramine in both chicken samples stored aerobically and or under MAP were low (< 10 mg kg(-1)) whereas the formation of histamine was only observed after day 11 of storage when Enterobacteriaceae had reached a population of ca. 10(7) CFU g(-1). Based on sensory and microbiological analyses and also taking into account a biogenic amines index (BAI, sum of putrescine, cadaverine and tyramine), BAI values between 96 and 101 mg kg(-1) may be proposed as a quality index of MAP and aerobically-packaged fresh chicken meat. Spermine and spermidine decreased steadily throughout the entire storage period of chicken meat under aerobic and MAP packaging, and thus these two amines cannot be used as indicators of fresh chicken meat quality.

Detection of water bodies in Saline County, Kansas

NASA Technical Reports Server (NTRS)

Barr, B. G. (Principal Investigator)

1973-01-01

The author has identified the following significant results. A total of 2,272 water bodies were mapped in Saline County, Kansas in 1972 using ERTS-1 imagery. A topographic map of 1955 shows 1,056 water bodies in the county. The major increase took place in farm ponds. Preliminary comparison of image and maps indicates that water bodies larger than ten acres in area proved consistently detectable. Most water areas between four and ten acres are also detectable, although occasionally image context prevents detection. Water areas less than four acres in extent are sometimes detected, but the number varies greatly depending on image context and the individual interpretor.

Variations in soil N cycling and trace gas emissions in wet tropical forests.

PubMed

Holtgrieve, Gordon W; Jewett, Peter K; Matson, Pamela A

2006-01-01

We used a previously described precipitation gradient in a tropical montane ecosystem of Hawai'i to evaluate how changes in mean annual precipitation (MAP) affect the processes resulting in the loss of N via trace gases. We evaluated three Hawaiian forests ranging from 2200 to 4050 mm year-1 MAP with constant temperature, parent material, ecosystem age, and vegetation. In situ fluxes of N2O and NO, soil inorganic nitrogen pools (NH4+ and NO3-), net nitrification, and net mineralization were quantified four times over 2 years. In addition, we performed 15N-labeling experiments to partition sources of N2O between nitrification and denitrification, along with assays of nitrification potential and denitrification enzyme activity (DEA). Mean NO and N2O emissions were highest at the mesic end of the gradient (8.7+/-4.6 and 1.1+/-0.3 ng N cm-2 h-1, respectively) and total oxidized N emitted decreased with increased MAP. At the wettest site, mean trace gas fluxes were at or below detection limit (

Semantic Segmentation and Difference Extraction via Time Series Aerial Video Camera and its Application

NASA Astrophysics Data System (ADS)

Amit, S. N. K.; Saito, S.; Sasaki, S.; Kiyoki, Y.; Aoki, Y.

2015-04-01

Google earth with high-resolution imagery basically takes months to process new images before online updates. It is a time consuming and slow process especially for post-disaster application. The objective of this research is to develop a fast and effective method of updating maps by detecting local differences occurred over different time series; where only region with differences will be updated. In our system, aerial images from Massachusetts's road and building open datasets, Saitama district datasets are used as input images. Semantic segmentation is then applied to input images. Semantic segmentation is a pixel-wise classification of images by implementing deep neural network technique. Deep neural network technique is implemented due to being not only efficient in learning highly discriminative image features such as road, buildings etc., but also partially robust to incomplete and poorly registered target maps. Then, aerial images which contain semantic information are stored as database in 5D world map is set as ground truth images. This system is developed to visualise multimedia data in 5 dimensions; 3 dimensions as spatial dimensions, 1 dimension as temporal dimension, and 1 dimension as degenerated dimensions of semantic and colour combination dimension. Next, ground truth images chosen from database in 5D world map and a new aerial image with same spatial information but different time series are compared via difference extraction method. The map will only update where local changes had occurred. Hence, map updating will be cheaper, faster and more effective especially post-disaster application, by leaving unchanged region and only update changed region.

Robustness of risk maps and survey networks to knowledge gaps about a new invasive pest.

PubMed

Yemshanov, Denys; Koch, Frank H; Ben-Haim, Yakov; Smith, William D

2010-02-01

In pest risk assessment it is frequently necessary to make management decisions regarding emerging threats under severe uncertainty. Although risk maps provide useful decision support for invasive alien species, they rarely address knowledge gaps associated with the underlying risk model or how they may change the risk estimates. Failure to recognize uncertainty leads to risk-ignorant decisions and miscalculation of expected impacts as well as the costs required to minimize these impacts. Here we use the information gap concept to evaluate the robustness of risk maps to uncertainties in key assumptions about an invading organism. We generate risk maps with a spatial model of invasion that simulates potential entries of an invasive pest via international marine shipments, their spread through a landscape, and establishment on a susceptible host. In particular, we focus on the question of how much uncertainty in risk model assumptions can be tolerated before the risk map loses its value. We outline this approach with an example of a forest pest recently detected in North America, Sirex noctilio Fabricius. The results provide a spatial representation of the robustness of predictions of S. noctilio invasion risk to uncertainty and show major geographic hotspots where the consideration of uncertainty in model parameters may change management decisions about a new invasive pest. We then illustrate how the dependency between the extent of uncertainties and the degree of robustness of a risk map can be used to select a surveillance network design that is most robust to knowledge gaps about the pest.

Based on time and spatial-resolved SERS mapping strategies for detection of pesticides.

PubMed

Ma, Bingbing; Li, Pan; Yang, Liangbao; Liu, Jinhuai

2015-08-15

For the sensitive and convenient detection of pesticides, several sensing methods and materials have been widely explored. However, it is still a challenge to obtain sensitive, simple detection techniques for pesticides. Here, the simple and sensitive Time-resolved SERS mapping (T-SERS) and Spatial-resolved SERS mapping (S-SERS) are presented for detection of pesticides by using Au@Ag NPs as SERS substrate. The Time-resolved SERS mapping (T-SERS) is based on state translation nanoparticles from the wet state to the dry state to realize SERS measurements. During the SERS measurement, adhesive force drives the particles closer together and then average interparticle gap becomes smaller. Following, air then begins to intersperse into the liquid network and the particles are held together by adhesive forces at the solid-liquid-air interface. In the late stage of water evaporation, all particles are uniformly distributed. Thus, so called hotspots matrix that can hold hotspots between every two adjacent particles in efficient space with minimal polydispersity of particle size are achieved, accompanying the red-shift of surface plasmon peak and appearance of an optimal SPR resonated sharply with excitation wavelength. Here, we found that the T-SERS method exhibits the detection limits of 1-2 orders of magnitude higher than that of S-SERS. On the other hand, the T-SERS is very simple method with high detection sensitivity, better reproducibility (RSD=10.8%) and is beneficial to construction of a calibration curve in comparison with that of Spatial-resolved SERS mapping (S-SERS). Most importantly, as a result of its remarkable sensitivity, T-SERS mapping strategies have been applied to detection of several pesticides and the detect limit can down to 1nM for paraoxon, 0.5nM for sumithion. In short, T-SERS mapping measurement promises to open a market for SERS practical detection with prominent advantages. Copyright © 2015. Published by Elsevier B.V.

Detecting Non-Markovianity of Quantum Evolution via Spectra of Dynamical Maps.

PubMed

Chruściński, Dariusz; Macchiavello, Chiara; Maniscalco, Sabrina

2017-02-24

We provide an analysis on non-Markovian quantum evolution based on the spectral properties of dynamical maps. We introduce the dynamical analog of entanglement witness to detect non-Markovianity and we illustrate its behavior with several instructive examples. It is shown that for several important classes of dynamical maps the corresponding evolution of singular values and/or eigenvalues of the map provides a simple non-Markovianity witness.

Patterns of Progressive Ganglion Cell-Inner Plexiform Layer Thinning in Glaucoma Detected by OCT.

PubMed

Shin, Joong Won; Sung, Kyung Rim; Park, Sun-Won

2018-04-25

To investigate the spatial characteristics and patterns of progressive macular ganglion cell-inner plexiform layer (GCIPL) thinning in glaucomatous eyes assessed by OCT Guided Progression Analysis (GPA). Longitudinal, retrospective, observational study. Two hundred ninety-two eyes of 192 patients with primary open-angle glaucoma with a mean follow-up of 6.0 years (range, 3.2-8.1 years) were included. Macular GCIPL imaging and visual field (VF) examination were performed at 6-month intervals for 3 years or more. Progressive GCIPL thinning was evaluated by a Cirrus HD-OCT (Carl Zeiss Meditec, Dublin, CA) GPA device. Spatial characteristics of progressive GCIPL thinning were assessed by the GCIPL thickness change map. The pattern of progressive GCIPL thinning was evaluated by comparing the baseline GCIPL thickness deviation map and the final GCIPL thickness change map. Visual field progression was determined by Early Manifest Glaucoma Trial criteria and linear regression of the VF index. Spatial characteristics and patterns of progressive GCIPL thinning. Seventy-two eyes of 62 participants (24.7% [72/292]) showed progressive GCIPL thinning in the GCIPL thickness change map. Progressive GCIPL thinning was detected most frequently (25.0%) at 2.08 mm from the fovea, and it extended in an arcuate shape in the inferotemporal region (250°-339°). Compared with the baseline GCIPL defects, the progressive GCIPL thinning extended toward the fovea and optic disc. The most common pattern of progressive GCIPL thinning was widening of GCIPL defects (42 eyes [58.3%]), followed by deepening of GCIPL defects (19 eyes [26.4%]) and newly developed GCIPL defects (15 eyes [20.8%]). Visual field progression was accompanied by progressive GCIPL thinning in 41 of 72 eyes (56.9%). Progressive GCIPL thinning preceded (61.0% [25/41]) or occurred concomitantly with (21.9% [9/41]) VF progression. The use of OCT GPA maps offers an effective approach to evaluate the topographic patterns of progressive GCIPL thinning in glaucomatous eyes. Progression of GCIPL thinning occurred before apparent progression on standard automated perimetry in most glaucomatous eyes. Understanding specific patterns and sequences of macular damage may provide important insights in the monitoring of glaucomatous progression. Copyright © 2018 American Academy of Ophthalmology. Published by Elsevier Inc. All rights reserved.

Using estimates of natural variation to detect ecologically important change in forest spatial patterns: a case study, Cascade Range, eastern Washington.

Treesearch

Paul F. Hessburg; Bradley G. Smith; R. Brion Salter

1999-01-01

Using hierarchical clustering techniques, we grouped subwatersheds on the eastern slope of the Cascade Range in Washington State into ecological subregions by similarity of area in potential vegetation and climate attributes. We then built spatially continuous historical and current vegetation maps for 48 randomly selected subwatersheds from interpretations of 1938-49...

Monitoring strip mining and reclamation with LANDSAT data in Belmont County, Ohio

NASA Technical Reports Server (NTRS)

Witt, R. G.; Schaal, G. M.; Bly, B. G.

1983-01-01

The utility of LANDSAT digital data for mapping and monitoring surface mines in Belmont County, Ohio was investigated. Two data sets from 1976 and 1979 were processed to classify level 1 land covers and three strip mine categories in order to examine change over time and assess reclamation efforts. The two classifications were compared with aerial photographs. Results of the accuracy assessment show that both classifications are approximately 86 per cent correct, and that surface mine change detection (date-to-date comparison) is facilitated by the digital format of LANDSAT data.

Potential effects of climate change on the risk of accidents with poisonous species of the genus Tityus (Scorpiones, Buthidae) in Argentina.

PubMed

Martinez, Pablo Ariel; Andrade, Mayane Alves; Bidau, Claudio Juan

2018-06-01

The temporal pattern of co-occurrence of human beings and venomous species (scorpions, spiders, snakes) is changing. Thus, the temporal pattern of areas with risk of accidents with such species tends to become dynamic in time. We analyze the areas of occurrence of species of Tityus in Argentina and assess the impact of global climate change on their area of distribution by the construction of risk maps. Using data of occurrence of the species and climatic variables, we constructed models of species distribution (SMDs) under current and future climatic conditions. We also created maps that allow the detection of temporal shifts in the distribution patterns of each Tityus species. Finally, we developed risk maps for the analyzed species. Our results predict that climate change will have an impact on the distribution of Tityus species which will clearly expand to more southern latitudes, with the exception of T. argentinus. T. bahiensis, widely distributed in Brazil, showed a considerable increase of its potential area (ca. 37%) with future climate change. The species T. confluens and T. trivittatus that cause the highest number of accidents in Argentina are expected to show significant changes of their distributions in future scenarios. The former fact is worrying because Buenos Aires province is the more densely populated district in Argentina thus iable to become the most affected by T. trivittatus. These alterations of distributional patterns can lead to amplify the accident risk zones of venomous species, becoming an important subject of concern for public health policies. Copyright © 2018 Elsevier Ltd. All rights reserved.

A unified approach for debugging is-a structure and mappings in networked taxonomies

PubMed Central

2013-01-01

Background With the increased use of ontologies and ontology mappings in semantically-enabled applications such as ontology-based search and data integration, the issue of detecting and repairing defects in ontologies and ontology mappings has become increasingly important. These defects can lead to wrong or incomplete results for the applications. Results We propose a unified framework for debugging the is-a structure of and mappings between taxonomies, the most used kind of ontologies. We present theory and algorithms as well as an implemented system RepOSE, that supports a domain expert in detecting and repairing missing and wrong is-a relations and mappings. We also discuss two experiments performed by domain experts: an experiment on the Anatomy ontologies from the Ontology Alignment Evaluation Initiative, and a debugging session for the Swedish National Food Agency. Conclusions Semantically-enabled applications need high quality ontologies and ontology mappings. One key aspect is the detection and removal of defects in the ontologies and ontology mappings. Our system RepOSE provides an environment that supports domain experts to deal with this issue. We have shown the usefulness of the approach in two experiments by detecting and repairing circa 200 and 30 defects, respectively. PMID:23548155

Comparison of rapid diagnostic tests to detect Mycobacterium avium subsp. paratuberculosis disseminated infection in bovine liver.

PubMed

Zarei, Mehdi; Ghorbanpour, Masoud; Tajbakhsh, Samaneh; Mosavari, Nader

2017-08-01

Mycobacterium avium subsp. paratuberculosis (MAP) causes Johne's disease, a chronic enteritis in cattle and other domestic and wild ruminants. The presence of MAP in tissues other than intestines and associated lymph nodes, such as meat and liver, is a potential public health concern. In the present study, the relationship between the results of rapid diagnostic tests of the Johne's disease, such as serum ELISA, rectal scraping PCR, and acid-fast staining, and the presence of MAP in liver was evaluated. Blood, liver, and rectal scraping samples were collected from 200 slaughtered cattle with unknown Johne's disease status. ELISA was performed to determine the MAP antibody activity in the serum. Acid-fast staining was performed on rectal scraping samples, and PCR was performed on rectal scraping and liver samples. PCR-positive liver samples were used for mycobacterial culture. Overall, the results of this study demonstrated that MAP can be detected and cultured from liver of slaughtered cattle and rapid diagnostic tests of Johne's disease have limited value in detecting cattle with MAP infection in liver. These findings show that the presence of MAP in liver tissue may occur in cows with negative results for rapid diagnostic tests and vice versa. Hence, liver might represent another possible risk of human exposure to MAP. Given concerns about a potential zoonotic role for MAP, these results show the necessity to find new methods for detecting cattle with MAP disseminated infection.

Detection, mapping, and quantification of single walled carbon nanotubes in histological specimens with photoacoustic microscopy.

PubMed

Avti, Pramod K; Hu, Song; Favazza, Christopher; Mikos, Antonios G; Jansen, John A; Shroyer, Kenneth R; Wang, Lihong V; Sitharaman, Balaji

2012-01-01

In the present study, the efficacy of multi-scale photoacoustic microscopy (PAM) was investigated to detect, map, and quantify trace amounts [nanograms (ng) to micrograms (µg)] of SWCNTs in a variety of histological tissue specimens consisting of cancer and benign tissue biopsies (histological specimens from implanted tissue engineering scaffolds). Optical-resolution (OR) and acoustic-resolution (AR)--Photoacoustic microscopy (PAM) was employed to detect, map and quantify the SWCNTs in a variety of tissue histological specimens and compared with other optical techniques (bright-field optical microscopy, Raman microscopy, near infrared (NIR) fluorescence microscopy). Both optical-resolution and acoustic-resolution PAM, allow the detection and quantification of SWCNTs in histological specimens with scalable spatial resolution and depth penetration. The noise-equivalent detection sensitivity to SWCNTs in the specimens was calculated to be as low as ∼7 pg. Image processing analysis further allowed the mapping, distribution, and quantification of the SWCNTs in the histological sections. The results demonstrate the potential of PAM as a promising imaging technique to detect, map, and quantify SWCNTs in histological specimens, and could complement the capabilities of current optical and electron microscopy techniques in the analysis of histological specimens containing SWCNTs.

Evaluation of PMS-PCR technology for detection of Mycobacterium avium subsp. paratuberculosis directly from bovine fecal specimens.

PubMed

Salgado, M; Steuer, P; Troncoso, E; Collins, M T

2013-12-27

Mycobacterium avium subsp. paratuberculosis (MAP) causes paratuberculosis, or Johne's disease, in animals. Diagnosis of MAP infection is challenging because of the pathogen's fastidious in vitro growth requirements and low-level intermittent shedding in feces during the preclinical phase of the infection. Detection of these "low-shedders" is important for effective control of paratuberculosis as these animals serve as sources of infection for susceptible calves. Magnetic separation technology, used in combination with culture or molecular methods for the isolation and detection of pathogenic bacteria, enhances the analytical sensitivity and specificity of detection methods. The aim of the present study was to evaluate peptide-mediated magnetic separation (PMS) capture technology coupled with IS900 PCR using the Roche real-time PCR system (PMS-PCR), in comparison with fecal culture using BACTEC-MGIT 960 system, for detection of MAP in bovine fecal samples. Among the 351 fecal samples 74.9% (263/351) were PMS-PCR positive while only 12.3% (43/351) were MGIT culture-positive (p=0.0001). All 43 MGIT culture-positive samples were also positive by PMS-PCR. Mean PMS-PCR crossing-point (Cp) values for the 13 fecal samples with the highest number of MAP, based on time to detection, (26.3) were significantly lower than for the 17 fecal samples with <100 MAP per 2g feces (30.06) (p<0.05). PMS-PCR technology provided results in a shorter time and yielded a higher number of positive results than MGIT culture. Earlier and faster detection of animals shedding MAP by PMS-PCR should significantly strengthen control efforts for MAP-infected cattle herds by helping to limit infection transmission at earlier stages of the infection. Copyright © 2013 Elsevier B.V. All rights reserved.

Forest loss maps from regional satellite monitoring systematically underestimate deforestation in two rapidly changing parts of the Amazon

NASA Astrophysics Data System (ADS)

Milodowski, D. T.; Mitchard, E. T. A.; Williams, M.

2017-09-01

Accurate, consistent reporting of changing forest area, stratified by forest type, is required for all countries under their commitments to the Paris Agreement (UNFCCC 2015 Adoption of the Paris Agreement (Paris: UNFCCC)). Such change reporting may directly impact on payments through comparisons to national Reference (Emissions) Levels under the Reducing Emissions from Deforestation and forest Degradation (REDD+) framework. The emergence of global, satellite-based forest monitoring systems, including Global Forest Watch (GFW) and FORMA, have great potential in aiding this endeavour. However, the accuracy of these systems has been questioned and their uncertainties are poorly constrained, both in terms of the spatial extent of forest loss and timing of change. Here, using annual time series of 5 m optical imagery at two sites in the Brazilian Amazon, we demonstrate that GFW more accurately detects forest loss than the coarser-resolution FORMA or Brazil’s national-level PRODES product, though all underestimate the rate of loss. We conclude GFW provides robust indicators of forest loss, at least for larger-scale forest change, but under-predicts losses driven by small-scale disturbances (< 2 ha), even though these are much larger than its minimum mapping unit (0.09 ha).

Forest loss maps from regional satellite monitoring systematically underestimate deforestation in two rapidly changing parts of the Amazon

NASA Astrophysics Data System (ADS)

Milodowski, D. T.; Mitchard, E. T. A.; Williams, M.

2016-09-01

Accurate, consistent reporting of changing forest area, stratified by forest type, is required for all countries under their commitments to the Paris Agreement (UNFCCC 2015 Adoption of the Paris Agreement (Paris: UNFCCC)). Such change reporting may directly impact on payments through comparisons to national Reference (Emissions) Levels under the Reducing Emissions from Deforestation and forest Degradation (REDD+) framework. The emergence of global, satellite-based forest monitoring systems, including Global Forest Watch (GFW) and FORMA, have great potential in aiding this endeavour. However, the accuracy of these systems has been questioned and their uncertainties are poorly constrained, both in terms of the spatial extent of forest loss and timing of change. Here, using annual time series of 5 m optical imagery at two sites in the Brazilian Amazon, we demonstrate that GFW more accurately detects forest loss than the coarser-resolution FORMA or Brazil’s national-level PRODES product, though all underestimate the rate of loss. We conclude GFW provides robust indicators of forest loss, at least for larger-scale forest change, but under-predicts losses driven by small-scale disturbances (< 2 ha), even though these are much larger than its minimum mapping unit (0.09 ha).

Investigation of an Optimum Detection Scheme for a Star-Field Mapping System

NASA Technical Reports Server (NTRS)

Aldridge, M. D.; Credeur, L.

1970-01-01

An investigation was made to determine the optimum detection scheme for a star-field mapping system that uses coded detection resulting from starlight shining through specially arranged multiple slits of a reticle. The computer solution of equations derived from a theoretical model showed that the greatest probability of detection for a given star and background intensity occurred with the use of a single transparent slit. However, use of multiple slits improved the system's ability to reject the detection of undesirable lower intensity stars, but only by decreasing the probability of detection for lower intensity stars to be mapped. Also, it was found that the coding arrangement affected the root-mean-square star-position error and that detection is possible with error in the system's detected spin rate, though at a reduced probability.

Non-invasive Imaging based Detection and Mapping of Brain Oxidative Stress and its Correlation with Cognitive Functions

DTIC Science & Technology

2017-05-14

AFRL-AFOSR-JP-TR-2017-0052 Non-invasive Imaging based Detection and Mapping of Brain Oxidative Stress and its Correlation with Cognative Functions...invasive Imaging based Detection and Mapping of Brain Oxidative Stress and its Correlation with Cognative Functions 5a.  CONTRACT NUMBER 5b.  GRANT...SUPPLEMENTARY NOTES 14. ABSTRACT Brain stress level measurement (non-invasively) in quantitative term is very helpful to correlate with various

Non invasive Imaging based Detection and Mapping of Brain Oxidative Stress and its Correlation with Cognative Functions

DTIC Science & Technology

2017-05-14

AFRL-AFOSR-JP-TR-2017-0052 Non-invasive Imaging based Detection and Mapping of Brain Oxidative Stress and its Correlation with Cognative Functions...invasive Imaging based Detection and Mapping of Brain Oxidative Stress and its Correlation with Cognative Functions 5a.  CONTRACT NUMBER 5b.  GRANT...SUPPLEMENTARY NOTES 14. ABSTRACT Brain stress level measurement (non-invasively) in quantitative term is very helpful to correlate with various

Exponentially Weighted Moving Average Change Detection Around the Country (and the World)

NASA Astrophysics Data System (ADS)

Brooks, E.; Wynne, R. H.; Thomas, V. A.; Blinn, C. E.; Coulston, J.

2014-12-01

With continuous, freely available moderate-resolution imagery of the Earth's surface available, and with the promise of more imagery to come, change detection based on continuous process models continues to be a major area of research. One such method, exponentially weighted moving average change detection (EWMACD), is based on a mixture of harmonic regression (HR) and statistical quality control, a branch of statistics commonly used to detect aberrations in industrial and medical processes. By using HR to approximate per-pixel seasonal curves, the resulting residuals characterize information about the pixels which stands outside of the periodic structure imposed by HR. Under stable pixels, these residuals behave as might be expected, but in the presence of changes (growth, stress, removal), the residuals clearly show these changes when they are used as inputs into an EWMA chart. In prior work in Alabama, USA, EWMACD yielded an overall accuracy of 85% on a random sample of known thinned stands, in some cases detecting thinnings as sparse as 25% removal. It was also shown to correctly identify the timing of the thinning activity, typically within a single image date of the change. The net result of the algorithm was to produce date-by-date maps of afforestation and deforestation on a variable scale of severity. In other research, EWMACD has also been applied to detect land use and land cover changes in central Java, Indonesia, despite the heavy incidence of clouds and a monsoonal climate. Preliminary results show that EWMACD accurately identifies land use conversion (agricultural to residential, for example) and also identifies neighborhoods where the building density has increased, removing neighborhood vegetation. In both cases, initial results indicate the potential utility of EWMACD to detect both gross and subtle ecosystem disturbance, but further testing across a range of ecosystems and disturbances is clearly warranted.

Change detection of bitemporal multispectral images based on FCM and D-S theory

NASA Astrophysics Data System (ADS)

Shi, Aiye; Gao, Guirong; Shen, Shaohong

2016-12-01

In this paper, we propose a change detection method of bitemporal multispectral images based on the D-S theory and fuzzy c-means (FCM) algorithm. Firstly, the uncertainty and certainty regions are determined by thresholding method applied to the magnitudes of difference image (MDI) and spectral angle information (SAI) of bitemporal images. Secondly, the FCM algorithm is applied to the MDI and SAI in the uncertainty region, respectively. Then, the basic probability assignment (BPA) functions of changed and unchanged classes are obtained by the fuzzy membership values from the FCM algorithm. In addition, the optimal value of fuzzy exponent of FCM is adaptively determined by conflict degree between the MDI and SAI in uncertainty region. Finally, the D-S theory is applied to obtain the new fuzzy partition matrix for uncertainty region and further the change map is obtained. Experiments on bitemporal Landsat TM images and bitemporal SPOT images validate that the proposed method is effective.

Examining change detection approaches for tropical mangrove monitoring

USGS Publications Warehouse

Myint, Soe W.; Franklin, Janet; Buenemann, Michaela; Kim, Won; Giri, Chandra

2014-01-01

This study evaluated the effectiveness of different band combinations and classifiers (unsupervised, supervised, object-oriented nearest neighbor, and object-oriented decision rule) for quantifying mangrove forest change using multitemporal Landsat data. A discriminant analysis using spectra of different vegetation types determined that bands 2 (0.52 to 0.6 μm), 5 (1.55 to 1.75 μm), and 7 (2.08 to 2.35 μm) were the most effective bands for differentiating mangrove forests from surrounding land cover types. A ranking of thirty-six change maps, produced by comparing the classification accuracy of twelve change detection approaches, was used. The object-based Nearest Neighbor classifier produced the highest mean overall accuracy (84 percent) regardless of band combinations. The automated decision rule-based approach (mean overall accuracy of 88 percent) as well as a composite of bands 2, 5, and 7 used with the unsupervised classifier and the same composite or all band difference with the object-oriented Nearest Neighbor classifier were the most effective approaches.

Potassium map from Chang'E-2 constraints the impact of Crisium and Orientale basin on the Moon.

PubMed

Zhu, Meng-Hua; Chang, Jin; Ma, Tao; Ip, Wing-Huen; Fa, WenZhe; Wu, Jian; Cai, MingSheng; Gong, YiZhong; Hu, YiMing; Xu, AoAo; Tang, ZeSheng

2013-01-01

KREEP materials were thought to be last crystallized at the lunar crust and mantle boundary. Impact cratering and volcanism are mainly responsible for their distributions on the lunar surface. Therefore, observation of global KREEP materials and investigation of distributions in the areas of large basins are of critical importance to understand the geologic history of the Moon. Here we report the new global potassium distribution on the Moon detected by Chang'E-2 Gamma-ray Spectrometer. We found that our new measurements are in general agreement with previous observation. A new finding and an important difference is that relatively higher K abundances in the Mare Crisium and Mare Orientale than their surrounding rims were detected for the first time. In light of our observations in these two areas, we propose that Crisium and Orientale basin-forming impact events may have penetrated to the lower crust and excavate the deeper materials to the lunar surface.

Electromechanical wave imaging for noninvasive mapping of the 3D electrical activation sequence in canines and humans in vivo

PubMed Central

Konofagou, Elisa E.; Provost, Jean

2014-01-01

Cardiovascular diseases rank as America’s primary killer, claiming the lives of over 41% of more than 2.4 million Americans. One of the main reasons for this high death toll is the severe lack of effective imaging techniques for screening, early detection and localization of an abnormality detected on the electrocardiogram (ECG). The two most widely used imaging techniques in the clinic are CT angiography and echocardiography with limitations in speed of application and reliability, respectively. It has been established that the mechanical and electrical properties of the myocardium change dramatically as a result of ischemia, infarction or arrhythmia; both at their onset and after survival. Despite these findings, no imaging technique currently exists that is routinely used in the clinic and can provide reliable, non-invasive, quantitative mapping of the regional, mechanical and electrical function of the myocardium. Electromechanical Wave Imaging (EWI) is an ultrasound-based technique that utilizes the electromechanical coupling and its associated resulting strain to infer to the underlying electrical function of the myocardium. The methodology of EWI is first described and its fundamental performance is presented. Subsequent in vivo canine and human applications are provided that demonstrate the applicability of Electromechanical Wave Imaging in differentiating between sinus rhythm and induced pacing schemes as well as mapping arrhythmias. Preliminary validation with catheter mapping is also provided and transthoracic electromechanical mapping in all four chambers of the human heart is also presented demonstrating the potential of this novel methodology to noninvasively infer to both the normal and pathological electrical conduction of the heart. PMID:22284425

[Epizootic and epidemic manifestation of natural foci of tularemia in Moscow region (1965-2013)].

PubMed

Demidova, T N; Popov, V P; Polukhina, A N; Orlov, D S; Mescheryakova, I S; Mikhailova, T V

2015-01-01

Detection of contemporary features of tularemia focimanifestations, determination of territories of high epidemic risk in various landscape zones and creation of a map of foci territories of Moscow Region for isolation of tularemia infectious agent cultures and registered human morbidity for justified planning of prophylaxis measures. Report materials of epizootologic examinations of natural foci for 1965-2013, 156 maps of epidemiologic examination of cases of human infection with tularemia, results of studies of casting of predatory birds and dung of predatory mammals were used. Registered morbidity and isolation of tularemia infectious agent cultures from 1965 to date were applied to an electronic map of Moscow Region by sign method using modern. GIS-technologies (MapInfo 10.5 program). Electronic maps Ingit at 1:200,000 scale, as well as Google Earth program were used to search for base points. Analysis of morbidity has revealed structure change in human tularemia morbidity--an increase of the fraction of urban population and a decrease of the fraction of patients among rural inhabitants, unimmunized against this infection are mostly ill. The presence of DNA of tularemia causative agent in biological objects in the complex with serologic and bacteriological studies was shown to allow to detect flaccid epizootics even at low numbers of rodents. Cartographic reflection of registered morbidity and isolation of tularemia infectious agent cultures allowed to show territories with various degrees of epizootic activity and epidemic manifestation. Positive results of serologic and molecular-genetic studies of environmental objects gives evident on epizootic activity and constant risk of aggravation of epidemic situation for this infection.

Global Urban Mapping and Modeling for Sustainable Urban Development

NASA Astrophysics Data System (ADS)

Zhou, Y.; Li, X.; Asrar, G.; Yu, S.; Smith, S.; Eom, J.; Imhoff, M. L.

2016-12-01

In the past several decades, the world has experienced fast urbanization, and this trend is expected to continue for decades to come. Urbanization, one of the major land cover and land use changes (LCLUC), is becoming increasingly important in global environmental changes, such as urban heat island (UHI) growth and vegetation phenology change. Better scientific insights and effective decision-making unarguably require reliable science-based information on spatiotemporal changes in urban extent and their environmental impacts. In this study, we developed a globally consistent 20-year urban map series to evaluate the time-reactive nature of global urbanization from the nighttime lights remote sensing data, and projected future urban expansion in the 21st century by employing an integrated modeling framework (Zhou et al. 2014, Zhou et al. 2015). We then evaluated the impacts of urbanization on building energy use and vegetation phenology that affect both ecosystem services and human health. We extended the modeling capability of building energy use in the Global Change Assessment Model (GCAM) with consideration of UHI effects by coupling the remote sensing based urbanization modeling and explored the impact of UHI on building energy use. We also investigated the impact of urbanization on vegetation phenology by using an improved phenology detection algorithm. The derived spatiotemporal information on historical and potential future urbanization and its implications in building energy use and vegetation phenology will be of great value in sustainable urban design and development for building energy use and human health (e.g., pollen allergy), especially when considered together with other factors such as climate variability and change. Zhou, Y., S. J. Smith, C. D. Elvidge, K. Zhao, A. Thomson & M. Imhoff (2014) A cluster-based method to map urban area from DMSP/OLS nightlights. Remote Sensing of Environment, 147, 173-185. Zhou, Y., S. J. Smith, K. Zhao, M. Imhoff, A. Thomson, B. Bond-Lamberty, G. R. Asrar, X. Zhang, C. He & C. D. Elvidge (2015) A global map of urban extent from nightlights. Environmental Research Letters, 10, 054011.

Detection and mapping of illicit drugs and their metabolites in fingermarks by MALDI MS and compatibility with forensic techniques

NASA Astrophysics Data System (ADS)

Groeneveld, G.; de Puit, M.; Bleay, S.; Bradshaw, R.; Francese, S.

2015-06-01

Despite the proven capabilities of Matrix Assisted Laser Desorption Ionisation Mass Spectrometry (MALDI MS) in laboratory settings, research is still needed to integrate this technique into current forensic fingerprinting practice. Optimised protocols enabling the compatible application of MALDI to developed fingermarks will allow additional intelligence to be gathered around a suspect’s lifestyle and activities prior to the deposition of their fingermarks while committing a crime. The detection and mapping of illicit drugs and metabolites in latent fingermarks would provide intelligence that is beneficial for both police investigations and court cases. This study investigated MALDI MS detection and mapping capabilities for a large range of drugs of abuse and their metabolites in fingermarks; the detection and mapping of a mixture of these drugs in marks, with and without prior development with cyanoacrylate fuming or Vacuum Metal Deposition, was also examined. Our findings indicate the versatility of MALDI technology and its ability to retrieve chemical intelligence either by detecting the compounds investigated or by using their ion signals to reconstruct 2D maps of fingermark ridge details.

Region-Based Building Rooftop Extraction and Change Detection

NASA Astrophysics Data System (ADS)

Tian, J.; Metzlaff, L.; d'Angelo, P.; Reinartz, P.

2017-09-01

Automatic extraction of building changes is important for many applications like disaster monitoring and city planning. Although a lot of research work is available based on 2D as well as 3D data, an improvement in accuracy and efficiency is still needed. The introducing of digital surface models (DSMs) to building change detection has strongly improved the resulting accuracy. In this paper, a post-classification approach is proposed for building change detection using satellite stereo imagery. Firstly, DSMs are generated from satellite stereo imagery and further refined by using a segmentation result obtained from the Sobel gradients of the panchromatic image. Besides the refined DSMs, the panchromatic image and the pansharpened multispectral image are used as input features for mean-shift segmentation. The DSM is used to calculate the nDSM, out of which the initial building candidate regions are extracted. The candidate mask is further refined by morphological filtering and by excluding shadow regions. Following this, all segments that overlap with a building candidate region are determined. A building oriented segments merging procedure is introduced to generate a final building rooftop mask. As the last step, object based change detection is performed by directly comparing the building rooftops extracted from the pre- and after-event imagery and by fusing the change indicators with the roof-top region map. A quantitative and qualitative assessment of the proposed approach is provided by using WorldView-2 satellite data from Istanbul, Turkey.

Influence of delayed gadolinium enhanced MRI of cartilage (dGEMRIC) protocol on T2-mapping: is it possible to comprehensively assess knee cartilage composition in one post-contrast MR examination at 3 Tesla?

PubMed

Verschueren, J; van Tiel, J; Reijman, M; Bron, E E; Klein, S; Verhaar, J A N; Bierma-Zeinstra, S M A; Krestin, G P; Wielopolski, P A; Oei, E H G

2017-09-01

To evaluate the possibility of assessing knee cartilage with T2-mapping and delayed gadolinium enhanced magnetic resonance imaging (MRI) of cartilage (dGEMRIC) in one post-contrast MR examination at 3 Tesla (T). T2 mapping was performed in 10 healthy volunteers at baseline; directly after baseline; after 10 min of cycling; and after 90 min delay, and in 16 osteoarthritis patients before and after intravenous administration of a double dose gadolinium dimeglumine contrast agent, reflecting key dGEMRIC protocol elements. Differences in T2 relaxation times between each timepoint and baseline were calculated for 6 cartilage regions using paired t tests or Wilcoxon signed-rank tests and the smallest detectable change (SDC). After cycling, a significant change in T2 relaxation times was found in the lateral weight-bearing tibial plateau (+1.0 ms, P = 0.04). After 90 min delay, significant changes were found in the lateral weight-bearing femoral condyle (+1.2 ms, P = 0.03) and the lateral weight-bearing tibial plateau (+1.3 ms, P = 0.01). In these regions of interests (ROIs), absolute differences were small and lower than the corresponding SDCs. T2-mapping after contrast administration only showed statistically significantly lower T2 relaxation times in the medial posterior femoral condyle (-2.4 ms, P < 0.001) with a change exceeding the SDC. Because dGEMRIC protocol elements resulted in only small differences in T2 relaxation times that were not consistent and lower than the SDC in the majority of regions, our results suggest that T2-mapping and dGEMRIC can be performed reliably in a single imaging session to assess cartilage biochemical composition in knee osteoarthritis (OA) at 3 T. Copyright © 2017 Osteoarthritis Research Society International. Published by Elsevier Ltd. All rights reserved.

Remote sensing of impervious surface growth: A framework for quantifying urban expansion and re-densification mechanisms

NASA Astrophysics Data System (ADS)

Shahtahmassebi, Amir Reza; Song, Jie; Zheng, Qing; Blackburn, George Alan; Wang, Ke; Huang, Ling Yan; Pan, Yi; Moore, Nathan; Shahtahmassebi, Golnaz; Sadrabadi Haghighi, Reza; Deng, Jing Song

2016-04-01

A substantial body of literature has accumulated on the topic of using remotely sensed data to map impervious surfaces which are widely recognized as an important indicator of urbanization. However, the remote sensing of impervious surface growth has not been successfully addressed. This study proposes a new framework for deriving and summarizing urban expansion and re-densification using time series of impervious surface fractions (ISFs) derived from remotely sensed imagery. This approach integrates multiple endmember spectral mixture analysis (MESMA), analysis of regression residuals, spatial statistics (Getis_Ord) and urban growth theories; hence, the framework is abbreviated as MRGU. The performance of MRGU was compared with commonly used change detection techniques in order to evaluate the effectiveness of the approach. The results suggested that the ISF regression residuals were optimal for detecting impervious surface changes while Getis_Ord was effective for mapping hotspot regions in the regression residuals image. Moreover, the MRGU outputs agreed with the mechanisms proposed in several existing urban growth theories, but importantly the outputs enable the refinement of such models by explicitly accounting for the spatial distribution of both expansion and re-densification mechanisms. Based on Landsat data, the MRGU is somewhat restricted in its ability to measure re-densification in the urban core but this may be improved through the use of higher spatial resolution satellite imagery. The paper ends with an assessment of the present gaps in remote sensing of impervious surface growth and suggests some solutions. The application of impervious surface fractions in urban change detection is a stimulating new research idea which is driving future research with new models and algorithms.

Mapping the MRI voxel volume in which thermal noise matches physiological noise--implications for fMRI.

PubMed

Bodurka, J; Ye, F; Petridou, N; Murphy, K; Bandettini, P A

2007-01-15

This work addresses the choice of the imaging voxel volume in blood oxygen level dependent (BOLD) functional magnetic resonance imaging (fMRI). Noise of physiological origin that is present in the voxel time course is a prohibitive factor in the detection of small activation-induced BOLD signal changes. If the physiological noise contribution dominates over the temporal fluctuation contribution in the imaging voxel, further increases in the voxel signal-to-noise ratio (SNR) will have diminished corresponding increases in temporal signal-to-noise (TSNR), resulting in reduced corresponding increases in the ability to detect activation induced signal changes. On the other hand, if the thermal and system noise dominate (suggesting a relatively low SNR) further decreases in SNR can prohibit detection of activation-induced signal changes. Here we have proposed and called the "suggested" voxel volume for fMRI the volume where thermal plus system-related and physiological noise variances are equal. Based on this condition we have created maps of fMRI suggested voxel volume from our experimental data at 3T, since this value will spatially vary depending on the contribution of physiologic noise in each voxel. Based on our fast EPI segmentation technique we have found that for gray matter (GM), white matter (WM), and cerebral spinal fluid (CSF) brain compartments the mean suggested cubical voxel volume is: (1.8 mm)3, (2.1 mm)3 and (1.4 mm)3, respectively. Serendipitously, (1.8 mm)3 cubical voxel volume for GM approximately matches the cortical thickness, thus optimizing BOLD contrast by minimizing partial volume averaging. The introduced suggested fMRI voxel volume can be a useful parameter for choice of imaging volume for functional studies.

Automatic drawing for traffic marking with MMS LIDAR intensity

NASA Astrophysics Data System (ADS)

Takahashi, G.; Takeda, H.; Shimano, Y.

2014-05-01

Upgrading the database of CYBER JAPAN has been strategically promoted because the "Basic Act on Promotion of Utilization of Geographical Information", was enacted in May 2007. In particular, there is a high demand for road information that comprises a framework in this database. Therefore, road inventory mapping work has to be accurate and eliminate variation caused by individual human operators. Further, the large number of traffic markings that are periodically maintained and possibly changed require an efficient method for updating spatial data. Currently, we apply manual photogrammetry drawing for mapping traffic markings. However, this method is not sufficiently efficient in terms of the required productivity, and data variation can arise from individual operators. In contrast, Mobile Mapping Systems (MMS) and high-density Laser Imaging Detection and Ranging (LIDAR) scanners are rapidly gaining popularity. The aim in this study is to build an efficient method for automatically drawing traffic markings using MMS LIDAR data. The key idea in this method is extracting lines using a Hough transform strategically focused on changes in local reflection intensity along scan lines. However, also note that this method processes every traffic marking. In this paper, we discuss a highly accurate and non-human-operator-dependent method that applies the following steps: (1) Binarizing LIDAR points by intensity and extracting higher intensity points; (2) Generating a Triangulated Irregular Network (TIN) from higher intensity points; (3) Deleting arcs by length and generating outline polygons on the TIN; (4) Generating buffers from the outline polygons; (5) Extracting points from the buffers using the original LIDAR points; (6) Extracting local-intensity-changing points along scan lines using the extracted points; (7) Extracting lines from intensity-changing points through a Hough transform; and (8) Connecting lines to generate automated traffic marking mapping data.

Seep Detection using E/V Nautilus Integrated Seafloor Mapping and Remotely Operated Vehicles on the United States West Coast

NASA Astrophysics Data System (ADS)

Gee, L. J.; Raineault, N.; Kane, R.; Saunders, M.; Heffron, E.; Embley, R. W.; Merle, S. G.

2017-12-01

Exploration Vessel (E/V) Nautilus has been mapping the seafloor off the west coast of the United States, from Washington to California, for the past three years with a Kongsberg EM302 multibeam sonar. This system simultaneously collects bathymetry, seafloor and water column backscatter data, allowing an integrated approach to mapping to more completely characterize a region, and has identified over 1,000 seafloor seeps. Hydrographic multibeam sonars like the EM302 were designed for mapping the bathymetry. It is only in the last decade that major mapping projects included an integrated approach that utilizes the seabed and water column backscatter information in addition to the bathymetry. Nautilus mapping in the Eastern Pacific over the past three years has included a number of seep-specific expeditions, and utilized and adapted the preliminary mapping guidelines that have emerged from research. The likelihood of seep detection is affected by many factors: the environment: seabed geomorphology, surficial sediment, seep location/depth, regional oceanography and biology, the nature of the seeps themselves: size variation, varying flux, depth, and transience, the detection system: design of hydrographic multibeam sonars limits use for water column detection, the platform: variations in the vessel and operations such as noise, speed, and swath overlap. Nautilus integrated seafloor mapping provided multiple indicators of seep locations, but it remains difficult to assess the probability of seep detection. Even when seeps were detected, they have not always been located during ROV dives. However, the presence of associated features (methane hydrate and bacterial mats) serve as evidence of potential seep activity and reinforce the transient nature of the seeps. Not detecting a seep in the water column data does not necessarily indicate that there is not a seep at a given location, but with multiple passes over an area and by the use of other contextual data, an area may be classified as likely or unlikely to host seeps.

From Conventional Radiotracer Tc-99(m) with Blue Dye to Indocyanine Green Fluorescence: A Comparison of Methods Towards Optimization of Sentinel Lymph Node Mapping in Early Stage Cervical Cancer for a Laparoscopic Approach.

PubMed

Buda, Alessandro; Papadia, Andrea; Zapardiel, Ignacio; Vizza, Enrico; Ghezzi, Fabio; De Ponti, Elena; Lissoni, Andrea Alberto; Imboden, Sara; Diestro, Maria Dolores; Verri, Debora; Gasparri, Maria Luisa; Bussi, Beatrice; Di Martino, Giampaolo; de la Noval, Begoña Diaz; Mueller, Michael; Crivellaro, Cinzia

2016-09-01

The credibility of sentinel lymph node (SLN) mapping is becoming increasingly more established in cervical cancer. We aimed to assess the sensitivity of SLN biopsy in terms of detection rate and bilateral mapping in women with cervical cancer by comparing technetium-99 radiocolloid (Tc-99(m)) and blue dye (BD) versus fluorescence mapping with indocyanine green (ICG). Data of patients with cervical cancer stage 1A2 to 1B1 from 5 European institutions were retrospectively reviewed. All centers used a laparoscopic approach with the same intracervical dye injection. Detection rate and bilateral mapping of ICG were compared, respectively, with results obtained by standard Tc-99(m) with BD. Overall, 76 (53 %) of 144 of women underwent preoperative SLN mapping with radiotracer and intraoperative BD, whereas 68 of (47 %) 144 patients underwent mapping using intraoperative ICG. The detection rate of SLN mapping was 96 % and 100 % for Tc-99(m) with BD and ICG, respectively. Bilateral mapping was achieved in 98.5 % for ICG and 76.3 % for Tc-99(m) with BD; this difference was statistically significant (p < 0.0001). The fluorescence SLN mapping with ICG achieved a significantly higher detection rate and bilateral mapping compared to standard radiocolloid and BD technique in women with early stage cervical cancer. Nodal staging with an intracervical injection of ICG is accurate, safe, and reproducible in patients with cervical cancer. Before replacing lymphadenectomy completely, the additional value of fluorescence SLN mapping on both perioperative morbidity and survival should be explored and confirmed by ongoing controlled trials.

Use of LANDSAT-1 data for the detection and mapping of saline seeps in Montana

NASA Technical Reports Server (NTRS)

May, G. A. (Principal Investigator); Petersen, G. W.

1976-01-01

The author has identified the following significant results. April, May, and August are the best times to detect saline seeps. Specific times within these months would be dependent upon weather, phenology, and growth conditions. Saline seeps can be efficiently and accurately mapped, within resolution capabilities, from merged May and August LANDSAT 1 data. Seeps were mapped by detecting salt crusts in the spring and indicator plants in the fall. These indicator plants were kochia, inkweed, and foxtail barley. The total hectares of the mapped saline seeps were calculated and tabulated. Saline seeps less than two hectares in size or that have linear configurations less than 200 meters in width were not mapped using the LANDSAT 1 data. Saline seep signatures developed in the Coffee Creek test site were extended to map saline seeps located outside this area.

Comparison of prevalence estimation of Mycobacterium avium subsp. paratuberculosis infection by sampling slaughtered cattle with macroscopic lesions vs. systematic sampling.

PubMed

Elze, J; Liebler-Tenorio, E; Ziller, M; Köhler, H

2013-07-01

The objective of this study was to identify the most reliable approach for prevalence estimation of Mycobacterium avium ssp. paratuberculosis (MAP) infection in clinically healthy slaughtered cattle. Sampling of macroscopically suspect tissue was compared to systematic sampling. Specimens of ileum, jejunum, mesenteric and caecal lymph nodes were examined for MAP infection using bacterial microscopy, culture, histopathology and immunohistochemistry. MAP was found most frequently in caecal lymph nodes, but sampling more tissues optimized the detection rate. Examination by culture was most efficient while combination with histopathology increased the detection rate slightly. MAP was detected in 49/50 animals with macroscopic lesions representing 1.35% of the slaughtered cattle examined. Of 150 systematically sampled macroscopically non-suspect cows, 28.7% were infected with MAP. This indicates that the majority of MAP-positive cattle are slaughtered without evidence of macroscopic lesions and before clinical signs occur. For reliable prevalence estimation of MAP infection in slaughtered cattle, systematic random sampling is essential.

Who Died, Where? Quantification of Drought-Induced Tree Mortality in Texas

NASA Astrophysics Data System (ADS)

Schwantes, A.; Swenson, J. J.; Johnson, D. M.; Domec, J. C.; Jackson, R. B.

2014-12-01

During 2011, Texas experienced a severe drought that killed millions of trees across the state. Drought-induced tree mortality can have significant ecological impacts and is expected to increase with climate change. We identify methods to quantify tree mortality in central Texas by using remotely sensed images before and after the drought at multiple spatial resolutions. Fine-scale tree mortality maps were created by classifying 1-m orthophotos from the National Agriculture Imagery Program. These classifications showed a high correlation with field estimates of percent canopy loss (RMSE = 2%; R2=0.9), and were thus used to calibrate coarser scale 30-m Landsat imagery. Random Forest, a machine learning method, was applied to obtain sub-pixel estimates of tree mortality. Traditional per-pixel classification techniques can map mortality of whole stands of trees (e.g. fire). However, these methods are often inadequate in detecting subtle changes in land cover, such as those associated with drought-induced tree mortality, which is often a widespread but scattered disturbance. Our method is unique, because it is capable of mapping death of individual canopies within a pixel. These 30-m tree mortality maps were then used to identify ecological systems most impacted by the drought and edaphic factors that control spatial distributions of tree mortality across central Texas. Ground observations coupled with our remote sensing analyses revealed that the majority of the mortality was Juniperus ashei. From a physiological standpoint this is surprising, because J. ashei is a drought-resistant tree. However, over the last century, this species has recently encroached into many areas previously dominated by grassland. Also, J. ashei tends to occupy landscape positions with lower available water storage, which could explain its high mortality rate. Predominantly tree mortality occurred in dry landscape positions (e.g. areas dominated by shallow soils, a low compound topographic index, and a high heat index). As increases in extreme drought events are predicted to occur with climate change, it will become more important to establish methods capable of detecting associated drought-induced tree mortality, to recognize vulnerable ecological systems, and to identify edaphic factors that predispose trees to mortality.

Mapping of forest disturbance magnitudes across the US National Forest System

NASA Astrophysics Data System (ADS)

Hernandez, A. J.; Healey, S. P.; Ramsey, R. D.; McGinty, C.; Garrard, C.; Lu, N.; Huang, C.

2013-12-01

A precise record in conjunction with ongoing monitoring of carbon pools constitutes essentials inputs for the continuous modernization of an ever- dynamic science such as climate change. This is particularly important in forested ecosystems for which accurate field archives are available and can be used in combination with historic satellite imagery to obtain spatially explicit estimates of several indicators that can be used in the assessment of said carbon pools. Many forest disturbance processes limit storage of carbon in forested ecosystems and thereby reduce those systems' capacity to mitigate changes in the global climate system. A component of the US National Forest System's (NFS) comprehensive plan for carbon monitoring includes accounting for mapped disturbances, such as fires, harvests, and insect activity. A long-term time series of maps that show the timing, extent, type, and magnitude of disturbances going back to 1990 has been prepared for the United States Forest Service (USFS) Northern Region, and is currently under preparation for the rest of the NFS regions covering more than 75 million hectares. Our mapping approach starts with an automated initial detection of annual disturbances using imagery captured within the growing season from the Landsat archive. Through a meticulous process, the initial detections are then visually inspected, manually corrected and labeled using various USFS ancillary datasets and Google Earth high-resolution historic imagery. We prepared multitemporal models of percent canopy cover and live tree carbon (T/ha) that were calibrated with extensive (in excess of 2000 locations) field data from the US Forest Service Forest Inventory and Analysis program (FIA). The models were then applied to all the years of the radiometrically corrected and normalized Landsat time series in order to provide annual spatially explicit estimates of the magnitude of change in terms of these two attributes. Our results provide objective, widely interpretable estimates of per-year disturbance effects across large areas. Different stakeholders (scientists, managers, policymakers) should benefit from this broad survey of disturbance processes affecting US federal forests over the last 20 years.

Detection and assessment of flood susceptible irrigation networks in Licab, Nueva Ecija, Philippines using LiDAR DTM

NASA Astrophysics Data System (ADS)

Alberto, R. T.; Hernando, P. J. C.; Tagaca, R. C.; Celestino, A. B.; Palado, G. C.; Camaso, E. E.; Damian, G. B.

2017-09-01

Climate change has wide-ranging effects on the environment and socio-economic and related sectors which includes water resources, agriculture and food security, human health, terrestrial ecosystems, coastal zones and biodiversity. Farmers are under pressure to the changing weather and increasing unpredictable water supply. Because of rainfall deficiencies, artificial application of water has been made through irrigation. Irrigation is a basic determinant of agriculture because its inadequacies are the most powerful constraints on the increase of agricultural production. Irrigation networks are permanent and temporary conduits that supply water to agricultural areas from an irrigation source. Detection of irrigation networks using LiDAR DTM, and flood susceptible assessment of irrigation networks could give baseline information on the development and management of sustainable agriculture. Map Gully Depth (MGD) in Whitebox GAT was used to generate the potential irrigation networks. The extracted MGD was overlaid in ArcGIS as guide in the digitization of potential irrigation networks. A flood hazard map was also used to identify the flood susceptible irrigation networks in the study area. The study was assessed through field validation of points which were generated using random sampling method. Results of the study showed that most of the detected irrigation networks have low to moderate susceptibility to flooding while the rest have high susceptibility to flooding which is due to shifting weather. These irrigation networks may cause flood when it overflows that could also bring huge damage to rice and other agricultural areas.

Detection by voxel-wise statistical analysis of significant changes in regional cerebral glucose uptake in an APP/PS1 transgenic mouse model of Alzheimer's disease.

PubMed

Dubois, Albertine; Hérard, Anne-Sophie; Delatour, Benoît; Hantraye, Philippe; Bonvento, Gilles; Dhenain, Marc; Delzescaux, Thierry

2010-06-01

Biomarkers and technologies similar to those used in humans are essential for the follow-up of Alzheimer's disease (AD) animal models, particularly for the clarification of mechanisms and the screening and validation of new candidate treatments. In humans, changes in brain metabolism can be detected by 1-deoxy-2-[(18)F] fluoro-D-glucose PET (FDG-PET) and assessed in a user-independent manner with dedicated software, such as Statistical Parametric Mapping (SPM). FDG-PET can be carried out in small animals, but its resolution is low as compared to the size of rodent brain structures. In mouse models of AD, changes in cerebral glucose utilization are usually detected by [(14)C]-2-deoxyglucose (2DG) autoradiography, but this requires prior manual outlining of regions of interest (ROI) on selected sections. Here, we evaluate the feasibility of applying the SPM method to 3D autoradiographic data sets mapping brain metabolic activity in a transgenic mouse model of AD. We report the preliminary results obtained with 4 APP/PS1 (64+/-1 weeks) and 3 PS1 (65+/-2 weeks) mice. We also describe new procedures for the acquisition and use of "blockface" photographs and provide the first demonstration of their value for the 3D reconstruction and spatial normalization of post mortem mouse brain volumes. Despite this limited sample size, our results appear to be meaningful, consistent, and more comprehensive than findings from previously published studies based on conventional ROI-based methods. The establishment of statistical significance at the voxel level, rather than with a user-defined ROI, makes it possible to detect more reliably subtle differences in geometrically complex regions, such as the hippocampus. Our approach is generic and could be easily applied to other biomarkers and extended to other species and applications. Copyright 2010 Elsevier Inc. All rights reserved.

Optimizing selection of training and auxiliary data for operational land cover classification for the LCMAP initiative

NASA Astrophysics Data System (ADS)

Zhu, Zhe; Gallant, Alisa L.; Woodcock, Curtis E.; Pengra, Bruce; Olofsson, Pontus; Loveland, Thomas R.; Jin, Suming; Dahal, Devendra; Yang, Limin; Auch, Roger F.

2016-12-01

The U.S. Geological Survey's Land Change Monitoring, Assessment, and Projection (LCMAP) initiative is a new end-to-end capability to continuously track and characterize changes in land cover, use, and condition to better support research and applications relevant to resource management and environmental change. Among the LCMAP product suite are annual land cover maps that will be available to the public. This paper describes an approach to optimize the selection of training and auxiliary data for deriving the thematic land cover maps based on all available clear observations from Landsats 4-8. Training data were selected from map products of the U.S. Geological Survey's Land Cover Trends project. The Random Forest classifier was applied for different classification scenarios based on the Continuous Change Detection and Classification (CCDC) algorithm. We found that extracting training data proportionally to the occurrence of land cover classes was superior to an equal distribution of training data per class, and suggest using a total of 20,000 training pixels to classify an area about the size of a Landsat scene. The problem of unbalanced training data was alleviated by extracting a minimum of 600 training pixels and a maximum of 8000 training pixels per class. We additionally explored removing outliers contained within the training data based on their spectral and spatial criteria, but observed no significant improvement in classification results. We also tested the importance of different types of auxiliary data that were available for the conterminous United States, including: (a) five variables used by the National Land Cover Database, (b) three variables from the cloud screening "Function of mask" (Fmask) statistics, and (c) two variables from the change detection results of CCDC. We found that auxiliary variables such as a Digital Elevation Model and its derivatives (aspect, position index, and slope), potential wetland index, water probability, snow probability, and cloud probability improved the accuracy of land cover classification. Compared to the original strategy of the CCDC algorithm (500 pixels per class), the use of the optimal strategy improved the classification accuracies substantially (15-percentage point increase in overall accuracy and 4-percentage point increase in minimum accuracy).

The Regional Land Cover Monitoring System: Building regional capacity through innovative land cover mapping approaches

NASA Astrophysics Data System (ADS)

Saah, D.; Tenneson, K.; Hanh, Q. N.; Aekakkararungroj, A.; Aung, K. S.; Goldstein, J.; Cutter, P. G.; Maus, P.; Markert, K. N.; Anderson, E.; Ellenburg, W. L.; Ate, P.; Flores Cordova, A. I.; Vadrevu, K.; Potapov, P.; Phongsapan, K.; Chishtie, F.; Clinton, N.; Ganz, D.

2017-12-01

Earth observation and Geographic Information System (GIS) tools, products, and services are vital to support the environmental decision making by governmental institutions, non-governmental agencies, and the general public. At the heart of environmental decision making is the monitoring land cover and land use change (LCLUC) for land resource planning and for ecosystem services, including biodiversity conservation and resilience to climate change. A major challenge for monitoring LCLUC in developing regions, such as Southeast Asia, is inconsistent data products at inconsistent intervals that have different typologies across the region and are typically made in without stakeholder engagement or input. Here we present the Regional Land Cover Monitoring System (RLCMS), a novel land cover mapping effort for Southeast Asia, implemented by SERVIR-Mekong, a joint NASA-USAID initiative that brings Earth observations to improve environmental decision making in developing countries. The RLCMS focuses on mapping biophysical variables (e.g. canopy cover, tree height, or percent surface water) at an annual interval and in turn using those biophysical variables to develop land cover maps based on stakeholder definitions of land cover classes. This allows for flexible and consistent land cover classifications that can meet the needs of different institutions across the region. Another component of the RLCMS production is the stake-holder engagement through co-development. Institutions that directly benefit from this system have helped drive the development for regional needs leading to services for their specific uses. Examples of services for regional stakeholders include using the RLCMS to develop maps using the IPCC classification scheme for GHG emission reporting and developing custom annual maps as an input to hydrologic modeling/flood forecasting systems. In addition to the implementation of this system and the service stemming from the RLCMS in Southeast Asia, it is planned to replicate the methods presented at the SERVIR-Hindu Kush Himalaya hub serving South Asia. Enhancements to the system will include change detection methods, enhanced biophysical models, and delivery systems.

Developing and Delivering National-Scale Gridded Phenology Data Products

NASA Astrophysics Data System (ADS)

Marsh, L.; Crimmins, M.; Crimmins, T. M.; Gerst, K.; Rosemartin, A.; Switzer, J.; Weltzin, J. F.

2016-12-01

The USA National Phenology Network (USA-NPN; www.usanpn.org) is now producing and freely delivering daily maps and short-term forecasts of accumulated growing degree days and spring onset dates (based on the Extended Spring Indices) at fine spatial scale for the conterminous United States. These data products have utility for a wide range of natural resource planning and management applications, including scheduling invasive species and pest detection and control activities, determining planting dates, anticipating allergy outbreaks and planning agricultural harvest dates. Accumulated growing degree day (AGDD) maps were selected because accumulated temperature is a strong driver of phenological transitions in plants and animals, including leaf-out, flowering, fruit ripening and migration. The Extended Spring Indices (SI-x) are based on predictive climate models for lilac and honeysuckle leaf and bloom; they have been widely used to summarize changes in the timing of spring onset. The SI-x is used as a national indicator of climate change impacts by the US Global Change Research Program and the Environmental Protection Agency. The USA-NPN is a national-scale program that supports scientific advancement and decision-making by collecting, storing, and sharing phenology data and information. To best serve various audiences, the AGDD and SI-x gridded maps are available in various formats through a range of access tools, including the USA-NPN online visualization tool as well as industry standards compliant web services. We plan to expand the suite of gridded map products offered by the USA-NPN to include predictive maps of phenological transitions for additional plant and animal species at fine spatial and temporal resolution in the near future. USA-NPN invites you to use freely available daily and short-term forecast maps of accumulated growing degree days and spring onset dates at fine spatial scale for the conterminous United States.

The emerging role of lidar remote sensing in coastal research and resource management

USGS Publications Warehouse

Brock, J.C.; Purkis, S.J.

2009-01-01

Knowledge of coastal elevation is an essential requirement for resource management and scientific research. Recognizing the vast potential of lidar remote sensing in coastal studies, this Special Issue includes a collection of articles intended to represent the state-of-the-art for lidar investigations of nearshore submerged and emergent ecosystems, coastal morphodynamics, and hazards due to sea-level rise and severe storms. Some current applications for lidar remote sensing described in this Special Issue include bluegreen wavelength lidar used for submarine coastal benthic environments such as coral reef ecosystems, airborne lidar used for shoreline mapping and coastal change detection, and temporal waveform-resolving lidar used for vegetation mapping. ?? 2009 Coastal Education and Research Foundation.

Satellite monitoring of vegetation and geology in semi-arid environments. [Tanzania

NASA Technical Reports Server (NTRS)

Kihlblom, U.; Johansson, D. (Principal Investigator)

1980-01-01

The possibility of mapping various characteristics of the natural environment of Tanzania by various LANDSAT techniques was assessed. Interpretation and mapping were carried out using black and white as well as color infrared images on the scale of 1:250,000. The advantages of several computer techniques were also assessed, including contrast-stretched rationing, differential edge enhancement; supervised classification; multitemporal classification; and change detection. Results Show the most useful image for interpretation comes from band 5, with additional information being obtained from either band 6 or band 7. The advantages of using color infrared images for interpreting vegetation and geology are so great that black and white should be used only to supplement the colored images.

The emerging role of lidar remote sensing in coastal research and resource management

USGS Publications Warehouse

Brock, John C.; Purkis, Samuel J.

2009-01-01

Knowledge of coastal elevation is an essential requirement for resource management and scientific research. Recognizing the vast potential of lidar remote sensing in coastal studies, this Special Issue includes a collection of articles intended to represent the state-of-the-art for lidar investigations of nearshore submerged and emergent ecosystems, coastal morphodynamics, and hazards due to sea-level rise and severe storms. Some current applications for lidar remote sensing described in this Special Issue include bluegreen wavelength lidar used for submarine coastal benthic environments such as coral reef ecosystems, airborne lidar used for shoreline mapping and coastal change detection, and temporal waveform-resolving lidar used for vegetation mapping.

Provisional maps of thermal areas in Yellowstone National Park, based on satellite thermal infrared imaging and field observations

USGS Publications Warehouse

Vaughan, R. Greg; Heasler, Henry; Jaworowski, Cheryl; Lowenstern, Jacob B.; Keszthelyi, Laszlo P.

2014-01-01

Maps that define the current distribution of geothermally heated ground are useful toward setting a baseline for thermal activity to better detect and understand future anomalous hydrothermal and (or) volcanic activity. Monitoring changes in the dynamic thermal areas also supports decisions regarding the development of Yellowstone National Park infrastructure, preservation and protection of park resources, and ensuring visitor safety. Because of the challenges associated with field-based monitoring of a large, complex geothermal system that is spread out over a large and remote area, satellite-based thermal infrared images from the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) were used to map the location and spatial extent of active thermal areas, to generate thermal anomaly maps, and to quantify the radiative component of the total geothermal heat flux. ASTER thermal infrared data acquired during winter nights were used to minimize the contribution of solar heating of the surface. The ASTER thermal infrared mapping results were compared to maps of thermal areas based on field investigations and high-resolution aerial photos. Field validation of the ASTER thermal mapping is an ongoing task. The purpose of this report is to make available ASTER-based maps of Yellowstone’s thermal areas. We include an appendix containing the names and characteristics of Yellowstone’s thermal areas, georeferenced TIFF files containing ASTER thermal imagery, and several spatial data sets in Esri shapefile format.

A Technology Analysis to Support Acquisition of UAVs for Gulf Coalition Forces Operations

DTIC Science & Technology

2017-06-01

their selection of the most suitable and cost-effective unmanned aerial vehicles to support detection operations. This study uses Map Aware Non ...being detected by Gulf Coalition Forces and improved time to detect them, support the use of UAVs in detection missions. Computer experimentations and...aerial vehicles to support detection operations. We use Map Aware Non - Uniform Automata, an agent-based simulation software platform, for the

Tracking the mammary architectural features and detecting breast cancer with magnetic resonance diffusion tensor imaging.

PubMed

Nissan, Noam; Furman-Haran, Edna; Feinberg-Shapiro, Myra; Grobgeld, Dov; Eyal, Erez; Zehavi, Tania; Degani, Hadassa

2014-12-15

Breast cancer is the most common cause of cancer among women worldwide. Early detection of breast cancer has a critical role in improving the quality of life and survival of breast cancer patients. In this paper a new approach for the detection of breast cancer is described, based on tracking the mammary architectural elements using diffusion tensor imaging (DTI). The paper focuses on the scanning protocols and image processing algorithms and software that were designed to fit the diffusion properties of the mammary fibroglandular tissue and its changes during malignant transformation. The final output yields pixel by pixel vector maps that track the architecture of the entire mammary ductal glandular trees and parametric maps of the diffusion tensor coefficients and anisotropy indices. The efficiency of the method to detect breast cancer was tested by scanning women volunteers including 68 patients with breast cancer confirmed by histopathology findings. Regions with cancer cells exhibited a marked reduction in the diffusion coefficients and in the maximal anisotropy index as compared to the normal breast tissue, providing an intrinsic contrast for delineating the boundaries of malignant growth. Overall, the sensitivity of the DTI parameters to detect breast cancer was found to be high, particularly in dense breasts, and comparable to the current standard breast MRI method that requires injection of a contrast agent. Thus, this method offers a completely non-invasive, safe and sensitive tool for breast cancer detection.

The application of remote sensing for climate change adaptation in Sahel region

NASA Astrophysics Data System (ADS)

Deafalla, Taisser H. H.; Csaplovics, Elmar; El-Abbas, Mustafa M.

2014-10-01

In recent years, there is no doubt that global climate change (CC) has observable development impacts, which seriously threatens the ability of individuals and communities at all levels. During this process, the clear degradation in the situation of ecosystems has produced a global concern of the urgency to mitigate climate threats and related effects. Assessing the impacts and vulnerability of CC requires accurate, up-to-date and improved information. Coupled with the ready availability of historical remote sensing (RS) data, the reduction in data cost and increased resolution from satellite platforms, RS technology appears poised to make a great impact on planning agencies and providing better understanding the dynamics of the climate system, predict and mitigate the expected global changes and the effects on human civilization involved in mapping Land Use Land Cover (LU/LC) at a variety of spatial scales. This research was designed to study the impact of CC in conflict zones and potential flashpoints in Sudan namely Nuba Mountains, where the community in this area living in fragile and unstable conditions, which making them more vulnerable to the risk of violent conflict and CC effects. And to determine the factors that exacerbate vulnerability in the study area as well as to map and assess the LU/LC change during the period 1984 to 2011 covered the years (1999, 2002 and 2009). Multispectral satellite data (i.e. LANDSAT TM and TERRA ASTER) were used. Change detection techniques were applied to analyze the rate of changes, causal factors as well as the drivers of changes. Recent study showed the importance of spatial variables in tackling CC which promoted the use of maps made within a RS. In addition to provide an input for climate models; and thus plan adaptation strategies.

Fully reprocessed ERS-1 altimeter data from 1992 to 1995: Feasibility of the detection of long term sea level change

NASA Astrophysics Data System (ADS)

Anzenhofer, M.; Gruber, T.

1998-04-01

Global mean sea level observations are necessary to answer the urgent questions about climate changes and their impact on socio-economy. At GeoForschungsZentrum/Geman Processing and Archiving Facility ERS altimeter data is used to systematically generate geophysical products such as sea surface topography, high-resolution geoid and short- and long-period sea surface height models. On the basis of this experience, fully reprocessed ERS-1 altimeter data is used to generated a time series of monthly sea surface height models from April 1992 to April 1995. The reprocessing consists of improved satellite ephemerides, merging of Grenoble tidal model, and application of range corrections due to timing errors. With the new data set the TOPEX/POSEIDON prelaunch accuracy requirements are fulfilled. The 3-year time series is taken to estimate the rate of change of global mean sea level. A careful treatment of seasonal effects is considered. A masking of continents, sea ice, and suspect sea surface heights is chosen that is common for all sea surface height models. The obtained rate of change is compared to external results from tide gauge records and TOPEX/POSEIDON data. The relation of sea level changes and sea surface temperature variations is examined by means of global monthly sea surface temperature maps. Both global wind speed and wave height maps are investigated and correlated with sea surface heights and sea surface temperatures in order to find other indicators of climate variations. The obtained rate of changes of the various global maps is compared to an atmospheric CO2 anomaly record, which is highly correlated to El Niño events. The relatively short period of 3 years, however, does not allow definite conclusions with respect to possible long-term climate changes.

Development of a sensitive Luminex xMAP-based microsphere immunoassay for specific detection of Iris yellow spot virus.

PubMed

Yu, Cui; Yang, Cuiyun; Song, Shaoyi; Yu, Zixiang; Zhou, Xueping; Wu, Jianxiang

2018-04-04

Iris yellow spot virus (IYSV) is an Orthotospovirus that infects most Allium species. Very few approaches for specific detection of IYSV from infected plants are available to date. We report the development of a high-sensitive Luminex xMAP-based microsphere immunoassay (MIA) for specific detection of IYSV. The nucleocapsid (N) gene of IYSV was cloned and expressed in Escherichia coli to produce the His-tagged recombinant N protein. A panel of monoclonal antibodies (MAbs) against IYSV was generated by immunizing the mice with recombinant N protein. Five specific MAbs (16D9, 11C6, 7F4, 12C10, and 14H12) were identified and used for developing the Luminex xMAP-based MIA systems along with a polyclonal antibody against IYSV. Comparative analyses of their sensitivity and specificity in detecting IYSV from infected tobacco leaves identified 7F4 as the best-performed MAb in MIA. We then optimized the working conditions of Luminex xMAP-based MIA in specific detection of IYSV from infected tobacco leaves by using appropriate blocking buffer and proper concentration of biotin-labeled antibodies as well as the suitable ratio between the antibodies and the streptavidin R-phycoerythrin (SA-RPE). Under the optimized conditions the Luminex xMAP-based MIA was able to specifically detect IYSV with much higher sensitivity than conventional enzyme-linked immunosorbent assay (ELISA). Importantly, the Luminex xMAP-based MIA is time-saving and the whole procedure could be completed within 2.5 h. We generated five specific MAbs against IYSV and developed the Luminex xMAP-based MIA method for specific detection of IYSV in plants. This assay provides a sensitive, high-specific, easy to perform and likely cost-effective approach for IYSV detection from infected plants, implicating potential broad usefulness of MIA in plant virus diagnosis.