Effects of Spectral Band Differences between Landsat 8 Operational Land Imager (OLI) and Sentinel 2A Multispectral Instrument (MSI)

NASA Astrophysics Data System (ADS)

Micijevic, E.; Haque, M. O.

2015-12-01

In satellite remote sensing, Landsat sensors are recognized for providing well calibrated satellite images for over four decades. This image data set provides an important contribution to detection and temporal analysis of land changes. Landsat 8 (L8), the latest satellite of the Landsat series, was designed to continue its legacy as well as to embrace advanced technology and satisfy the demand of the broader scientific community. Sentinel 2A (S2A), a European satellite launched in June 2015, is designed to keep data continuity of Landsat and SPOT like satellites. The S2A MSI sensor is equipped with spectral bands similar to L8 OLI and includes some additional ones. Compared to L8 OLI, green and near infrared MSI bands have narrower bandwidths, whereas coastal-aerosol (CA) and cirrus have larger bandwidths. The blue and red MSI bands cover higher wavelengths than the matching OLI bands. Although the spectral band differences are not large, their combination with the spectral signature of a studied target can largely affect the Top Of Atmosphere (TOA) reflectance seen by the sensors. This study investigates the effect of spectral band differences between S2A MSI and L8 OLI sensors. The differences in spectral bands between sensors can be assessed by calculating Spectral Band Adjustment Factors (SBAF). For radiometric calibration purposes, the SBAFs for the calibration test site are used to bring the two sensors to the same radiometric scale. However, the SBAFs are target dependent and different sensors calibrated to the same radiometric scale will (correctly!) measure different reflectance for the same target. Thus, when multiple sensors are used to study a given target, the sensor responses need to be adjusted using SBAFs specific to that target. Comparison of the SBAFs for S2A MSI and L8 OLI based on various vegetation spectral profiles revealed variations in radiometric responses as high as 15%. Depending on target under study, these differences could be even

Radiometric Comparison between Sentinel 2A (S2A) Multispectral Imager (MSI) and Landsat 8 (L8) Operational Land Imager (OLI)

NASA Astrophysics Data System (ADS)

Micijevic, E.; Haque, M. O.

2016-12-01

With its forty-four year continuous data record, the Landsat image archive provides an invaluable source of information for essential climate variables, global land change studies and a variety of other applications. The latest in the series, Landsat 8, carries the Operational Land Imager (OLI), the sensor with an improved design compared to its predecessors, but with similar radiometric, spatial and spectral characteristics, to provide image data continuity. Sentinel 2A (S2A), launched in June 2015, carries the Multispectral Imager (MSI) that has a number of bands with spectral and radiometric characteristics similar to L8 OLI. As such, it offers an opportunity to augment the Landsat data record through increased frequency of acquisitions, when combined with OLI. In this study, we compared Top-of-Atmosphere (TOA) reflectance of matching spectral bands in MSI and OLI products. Comparison between S2A MSI and L8 OLI sensors was performed using image data acquired near simultaneously primarily over Pseudo Invariant Calibration Site (PICS) Libya 4, but also over other calibration test sites. Spectral differences between the two sensors were accounted for using their spectral filter profiles and a spectral signature of the site derived from EO1 Hyperion hyperspectral imagery. Temporal stability was also assessed through temporal trending of Top-of-Atmosphere (TOA) reflectance measured by the two sensors over PICS. The performed analysis suggests good agreement between the two sensors, within 5% for the costal aerosol band and better than 3% for other matching bands. It is important to note that whenever data from different sensors are used together in a study, the special attention need to be paid to the spectral band differences between the sensors because the necessary spectral difference adjustment is target dependent and may vary a lot from target to target.

Hot Spot Detection System Using Landsat 8/OLI Data

NASA Astrophysics Data System (ADS)

Kato, S.; Nakamura, R.; Oda, A.; Iijima, A.; Kouyama, T.; Iwata, T.

2015-12-01

We developed a simple algorithm and a Web-based visualizing system to detect hot spots using Landsat 8 OLI multispectral data as one of the applications of the real-time processing of Landsat 8 data. An empirical equation and radiometric and reflective thresholds were derived to detect hot spots using the OLI data at band 5 (0.865 μm) and band 7 (2.200 μm) based on the increase in spectral radiance at shortwave infrared (SWIR) region due to the emission from objects with high surface temperature. We surveyed typical patterns of surface spectra using the ASTER spectral library to delineate a threshold to distinguish hot spots from background surfaces. To adjust the empirical coefficients of our detection algorithm, we visually inspected the detected hot spots using 6593 Landsat 8 scenes, which cover eastern part of East Asia, taken from January 1, 2014 to December 31, 2014, displayed on a dedicated Web GIS system. Eventually we determined threshold equations which can theoretically detect hot spots at temperatures above 230 °C over isothermal pixels and hot spots as small as 1 m2 at temperatures of 1000 °C as the lowest temperature and the smallest subpixel coverage, respectively, for daytime scenes. The algorithm detected hot spots including wildfires, volcanos, open burnings and factories. 30-m spatial resolution of Landsat 8 enabled to detect wild fires and open burnings accompanied by clearer shapes of fire front lines than MODIS and VIIRS fire products. Although the 16-day revisit cycle of Landsat 8 is too long to effectively find unexpected wildfire or outbreak of eruption, the revisit cycle is enough to monitor temporally stable heat sources, such as continually erupting volcanos and factories. False detection was found over building rooftops, which have relatively smooth surfaces at longer wavelengths, when specular reflection occurred at the satellite overpass.

Imaging Spectroscopy Enables Novel Applications and Continuity with the Landsat Record to Sustain Legacy Applications: An Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) and Landsat 8 OLI Case Study

NASA Astrophysics Data System (ADS)

Stavros, E. N.; Seidel, F.; Cable, M. L.; Green, R. O.; Freeman, A.

2017-12-01

While, imaging spectrometers offer additional information that provide value added products for applications that are otherwise underserved, there is need to demonstrate their ability to augment the multi-spectral (e.g., Landsat) optical record by both providing more frequent temporal revisit and lengthening the existing record. Here we test the hypothesis that imaging spectroscopic optical data is compatible with multi-spectral data to within ±5% radiometric accuracy, as desirable to continue the long-term Landsat data record. We use a coincident Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) flight with over-passing Operational Land Imager (OLI) data on Landsat 8 to document a procedure for simulating OLI multi-spectral bands from AVIRIS, evaluate influencing factors on the observed radiance, and assess AVIRIS radiometric accuracy compared to OLI. The procedure for simulating OLI data includes spectral convolution, accounting for atmospheric effects introduced by different sensor altitude and viewing geometries, and spatial resampling. After accounting for these influences, we expect the remaining differences between the simulated and the real OLI data result from differences in sensor calibration, surface bi-directional reflectance, from the different viewing geometries, and spatial sampling. The median radiometric percent difference for each band in the data used range from 0.6% to 8.3%. After bias-correction to minimize potential calibration discrepancies, we find no more than 1.2% radiometric percent difference for any OLI band. This analysis therefore successfully demonstrates that imaging spectrometer data can not only address novel applications, but also contribute to the Landsat-type or other multi-spectral data records to sustain legacy applications.

Assessing the potential of Landsat 8 OLI for retrieving salinity in the hypersaline Arabian Gulf

NASA Astrophysics Data System (ADS)

Zhao, Jun; Temimi, Marouane

2016-04-01

The Arabian Gulf, located in an arid region in the Middle East, has high salinity that can exceed 43 practical salinity units (psu) due to its special conditions, such as high evaporation, low precipitation, and desalination discharge. In this study, a regional algorithm was developed to retrieve salinity using in situ measurements conducted between June 2013 and November 2014 along the western coast of Abu Dhabi, United Arab Emirates (UAE). A multivariate linear regression model using the visible bands of Operational Land Imager (OLI) was proposed and indicated good performance with a determination coefficient (R2) of 0.7. The algorithm was then applied to an OLI scene, which revealed the spatial distribution of salinity over the study area. The findings are favorable for better interpretation of the complex water mass exchange between the Arabian Gulf and the Sea of Oman through the Strait of Hormuz, validating salinity from numerical models, studying the effects of anthropogenic activities and climate change on ecosystem in the hypersaline Arabian Gulf, etc.

Evaluating the capability of Landsat 8 OLI and SPOT 6 for discriminating invasive alien species in the African Savanna landscape

NASA Astrophysics Data System (ADS)

Kganyago, Mahlatse; Odindi, John; Adjorlolo, Clement; Mhangara, Paidamoyo

2018-05-01

Globally, there is paucity of accurate information on the spatial distribution and patch sizes of Invasive Alien Plants (IAPs) species. Such information is needed to aid optimisation of control mechanisms to prevent further spread of IAPs and minimize their impacts. Recent studies have shown the capability of very high spatial (<1 m) and spectral resolution (<10 nm) data for discriminating vegetation species. However, very high spatial resolution may introduce significant intra-species spectral variability and result in reduced mapping accuracy, while higher spectral resolution data are commonly limited to smaller areas, are costly and computationally expensive. Alternatively, medium and high spatial resolution data are available at low or no cost and have limitedly been evaluated for their potential in determining invasion patterns relevant for invasion ecology and aiding effective IAPs management. In this study medium and high resolution datasets from Landsat Operational Land Imager (OLI) and SPOT 6 sensors respectively, were evaluated for mapping the distribution and patch sizes of IAP, Parthenium hysterophorus in the savannah landscapes of KwaZulu-Natal, South Africa. Support Vector Machines (SVM) classifier was used for classification of both datasets. Results indicated that SPOT 6 had a higher overall accuracy (86%) than OLI (83%) in mapping P. hysterophorus. The study found larger distributions and patch sizes in OLI than in SPOT 6 as a result of possible P. hysterophorus expansion due to temporal differences between images and coarser pixels were insufficient to delineate gaps inside larger patches. On the other hand, SPOT 6 showed better capabilities of delineating gaps and boundaries of patches, hence had better estimates of distribution and patch sizes. Overall, the study showed that OLI may be suitable for mapping well-established patches for the purpose of large scale monitoring, while SPOT 6 can be used for mapping small patches and prioritising them

Radiometric Cross-Calibration of GAOFEN-1 Wfv Cameras with LANDSAT-8 Oli and Modis Sensors Based on Radiation and Geometry Matching

NASA Astrophysics Data System (ADS)

Li, J.; Wu, Z.; Wei, X.; Zhang, Y.; Feng, F.; Guo, F.

2018-04-01

Cross-calibration has the advantages of high precision, low resource requirements and simple implementation. It has been widely used in recent years. The four wide-field-of-view (WFV) cameras on-board Gaofen-1 satellite provide high spatial resolution and wide combined coverage (4 × 200 km) without onboard calibration. In this paper, the four-band radiometric cross-calibration coefficients of WFV1 camera were obtained based on radiation and geometry matching taking Landsat 8 OLI (Operational Land Imager) sensor as reference. Scale Invariant Feature Transform (SIFT) feature detection method and distance and included angle weighting method were introduced to correct misregistration of WFV-OLI image pair. The radiative transfer model was used to eliminate difference between OLI sensor and WFV1 camera through the spectral match factor (SMF). The near-infrared band of WFV1 camera encompasses water vapor absorption bands, thus a Look Up Table (LUT) for SMF varies from water vapor amount is established to estimate the water vapor effects. The surface synchronization experiment was designed to verify the reliability of the cross-calibration coefficients, which seem to perform better than the official coefficients claimed by the China Centre for Resources Satellite Data and Application (CCRSDA).

A cloud shadow detection method combined with cloud height iteration and spectral analysis for Landsat 8 OLI data

NASA Astrophysics Data System (ADS)

Sun, Lin; Liu, Xinyan; Yang, Yikun; Chen, TingTing; Wang, Quan; Zhou, Xueying

2018-04-01

Although enhanced over prior Landsat instruments, Landsat 8 OLI can obtain very high cloud detection precisions, but for the detection of cloud shadows, it still faces great challenges. Geometry-based cloud shadow detection methods are considered the most effective and are being improved constantly. The Function of Mask (Fmask) cloud shadow detection method is one of the most representative geometry-based methods that has been used for cloud shadow detection with Landsat 8 OLI. However, the Fmask method estimates cloud height employing fixed temperature rates, which are highly uncertain, and errors of large area cloud shadow detection can be caused by errors in estimations of cloud height. This article improves the geometry-based cloud shadow detection method for Landsat OLI from the following two aspects. (1) Cloud height no longer depends on the brightness temperature of the thermal infrared band but uses a possible dynamic range from 200 m to 12,000 m. In this case, cloud shadow is not a specific location but a possible range. Further analysis was carried out in the possible range based on the spectrum to determine cloud shadow location. This effectively avoids the cloud shadow leakage caused by the error in the height determination of a cloud. (2) Object-based and pixel spectral analyses are combined to detect cloud shadows, which can realize cloud shadow detection from two aspects of target scale and pixel scale. Based on the analysis of the spectral differences between the cloud shadow and typical ground objects, the best cloud shadow detection bands of Landsat 8 OLI were determined. The combined use of spectrum and shape can effectively improve the detection precision of cloud shadows produced by thin clouds. Several cloud shadow detection experiments were carried out, and the results were verified by the results of artificial recognition. The results of these experiments indicated that this method can identify cloud shadows in different regions with correct

Monitoring water quality in a hypereutrophic reservoir using Landsat ETM+ and OLI sensors: how transferable are the water quality algorithms?

PubMed

Deutsch, Eliza S; Alameddine, Ibrahim; El-Fadel, Mutasem

2018-02-15

The launch of the Landsat 8 in February 2013 extended the life of the Landsat program to over 40 years, increasing the value of using Landsat to monitor long-term changes in the water quality of small lakes and reservoirs, particularly in poorly monitored freshwater systems. Landsat-based water quality hindcasting often incorporate several Landsat sensors in an effort to increase the temporal range of observations; yet the transferability of water quality algorithms across sensors remains poorly examined. In this study, several empirical algorithms were developed to quantify chlorophyll-a, total suspended matter (TSM), and Secchi disk depth (SDD) from surface reflectance measured by Landsat 7 ETM+ and Landsat 8 OLI sensors. Sensor-specific multiple linear regression models were developed by correlating in situ water quality measurements collected from a semi-arid eutrophic reservoir with band ratios from Landsat ETM+ and OLI sensors, along with ancillary data (water temperature and seasonality) representing ecological patterns in algae growth. Overall, ETM+-based models outperformed (adjusted R 2 chlorophyll-a = 0.70, TSM = 0.81, SDD = 0.81) their OLI counterparts (adjusted R 2 chlorophyll-a = 0.50, TSM = 0.58, SDD = 0.63). Inter-sensor differences were most apparent for algorithms utilizing the Blue spectral band. The inclusion of water temperature and seasonality improved the power of TSM and SDD models.

Comparison of hyperspectral transformation accuracies of multispectral Landsat TM, ETM+, OLI and EO-1 ALI images for detecting minerals in a geothermal prospect area

NASA Astrophysics Data System (ADS)

Hoang, Nguyen Tien; Koike, Katsuaki

2018-03-01

Hyperspectral remote sensing generally provides more detailed spectral information and greater accuracy than multispectral remote sensing for identification of surface materials. However, there have been no hyperspectral imagers that cover the entire Earth surface. This lack points to a need for producing pseudo-hyperspectral imagery by hyperspectral transformation from multispectral images. We have recently developed such a method, a Pseudo-Hyperspectral Image Transformation Algorithm (PHITA), which transforms Landsat 7 ETM+ images into pseudo-EO-1 Hyperion images using multiple linear regression models of ETM+ and Hyperion band reflectance data. This study extends the PHITA to transform TM, OLI, and EO-1 ALI sensor images into pseudo-Hyperion images. By choosing a part of the Fish Lake Valley geothermal prospect area in the western United States for study, the pseudo-Hyperion images produced from the TM, ETM+, OLI, and ALI images by PHITA were confirmed to be applicable to mineral mapping. Using a reference map as the truth, three main minerals (muscovite and chlorite mixture, opal, and calcite) were identified with high overall accuracies from the pseudo-images (> 95% and > 42% for excluding and including unclassified pixels, respectively). The highest accuracy was obtained from the ALI image, followed by ETM+, TM, and OLI images in descending order. The TM, OLI, and ALI images can be alternatives to ETM+ imagery for the hyperspectral transformation that aids the production of pseudo-Hyperion images for areas without high-quality ETM+ images because of scan line corrector failure, and for long-term global monitoring of land surfaces.

River plumes investigation using Sentinel-2A MSI and Landsat-8 OLI data

NASA Astrophysics Data System (ADS)

Lavrova, Olga Yu.; Soloviev, Dmitry M.; Strochkov, Mikhail A.; Bocharova, Tatiana Y.; Kashnitsky, Alexandr V.

2016-10-01

We present the results of using Sentinel-2A Multispectral Imager Instrument (MSI/S2) and Landsat-8 Operational Land Imager (OLI/L8) data to monitor river plumes in the eastern Black Sea and from the Rhône River in the Mediterranean Sea. The focus is on exploring the possibility to investigate hydrodynamic processes associated with river outflows, in particular internal waves (IWs). Submesoscale IWs having wavelengths less than 50 m and generated by unstable sharp front of a river plume were revealed and their parameters were assessed. A map of surface manifestation of IW trains in the Gulf of Lions was created based on MSI/S2 images. There are different mechanisms of IW generation in river outflow zones, they are determined by a number of parameters including river discharge, bottom topography and presence of tidal currents or inertial period IWs in the shelf zone. A new phenomenon manifested as a chain of quasi circles was discovered. Inertial water motions were suggested as its prime cause, however, this hypothesis is yet to be investigated. An analysis of OLI/L8 and MSI/S2 data enabled us to consider in detail river debouchment streams. For the first time a wave pattern of such stream in the eastern Black Sea was observed in conditions of foehn winds. Usually, foehn winds are distinctly manifested in radar images. A joint analysis of quasi simultaneous ocean color MSI/S2 and Sentinel-1A SAR images demonstrated how water stream wave-like signatures differ from those of foehn winds.

Improving the frequency of high spatial resolution leaf area index maps using Landsat OLI and Sentinel-2 MSI

NASA Astrophysics Data System (ADS)

Li, S.; Ganguly, S.; Dungan, J. L.; Zhang, G.; Ju, J.; Claverie, M.

2015-12-01

The European Space Agency's Sentinel-2 mission successfully launched the first of two satellites in June, 2015. Sentinel 2A's MSI instrument is now providing optical data similar to Landsat 8's OLI imagery and, with its global repeat of 10 days, has the potential to increase the availability of 30m resolution high level products such as leaf area index (LAI). Prior to the launch of S-2A, we simulated MSI imagery using EO-1 Hyperion data and estimated green LAI using an algorithm based on canopy spectral invariants theory. Comparison of the resulting LAI maps resulting from the simulated MSI and corresponding maps derived from OLI data showed a RMSE of 0.1875. Uncertainty bounds on actual MSI data promise to be narrower because of the superior signal-to-noise ratio of MSI. A workflow for the production of LAI and other high level products including data ingest, BRDF correction, cloud masking and atmospheric correction is being developed using the NASA Earth Exchange (NEX) and will improve the capability to examine seasonal changes in canopy LAI.

Lithological mapping using Landsat 8 OLI and Terra ASTER multispectral data in the Bas Drâa inlier, Moroccan Anti Atlas

NASA Astrophysics Data System (ADS)

Adiri, Zakaria; Harti, Abderrazak El; Jellouli, Amine; Maacha, Lhou; Bachaoui, El Mostafa

2016-01-01

Lithological mapping is a fundamental step in various mineral prospecting studies because it forms the basis of the interpretation and validation of retrieved results. Therefore, this study exploited the multispectral Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) and Landsat 8 Operational Land Imager (OLI) data in order to map lithological units in the Bas Drâa inlier, at the Moroccan Anti Atlas. This task was completed by using principal component analysis (PCA), band ratios (BR), and support vector machine (SVM) classification. Overall accuracy and the kappa coefficient of SVM based on ground truth in addition to the results of PCA and BR show an excellent correlation with the existing geological map of the study area. Consequently, the methodology proposed demonstrates a high potential of ASTER and Landsat 8 OLI data in lithological units discrimination.

Ground-based radiometric calibration of the Landsat 8 Operational Land Imager (OLI) using in situ techniques

NASA Astrophysics Data System (ADS)

Czapla-Myers, J.

2013-12-01

Landsat 8 was successfully launched from Vandenberg Air Force Base in California on 11 February 2013, and was placed into the orbit previously occupied by Landsat 5. Landsat 8 is the latest platform in the 40-year history of the Landsat series of satellites, and it contains two instruments that operate in the solar-reflective and the thermal infrared regimes. The Operational Land Imager (OLI) is a pushbroom sensor that contains eight multispectral bands ranging from 400-2300 nm, and one panchromatic band. The spatial resolution of the multispectral bands is 30 m, which is similar to previous Landsat sensors, and the panchromatic band has a 15-m spatial resolution, which is also similar to previous Landsat sensors. The 12-bit radiometric resolution of OLI improves upon the 8-bit resolution of the Enhanced Thematic Mapper Plus (ETM+) onboard Landsat 7. An important requirement for the Landsat program is the long-term radiometric continuity of its sensors. Ground-based vicarious techniques have been used for over 20 years to determine the absolute radiometric calibration of sensors that encompass a wide variety of spectral and spatial characteristics. This work presents the early radiometric calibration results of Landsat 8 OLI that were obtained using the traditional reflectance-based approach. University of Arizona personnel used five sites in Arizona, California, and Nevada to collect ground-based data. In addition, a unique set of in situ data were collected in March 2013, when Landsat 7 and Landsat 8 were observing the same site within minutes of each other. The tandem overfly schedule occurred while Landsat 8 was shifting to the WRS-2 orbital grid, and lasted only a few days. The ground-based data also include results obtained using the University of Arizona's Radiometric Calibration Test Site (RadCaTS), which is an automated suite of instruments located at Railroad Valley, Nevada. The results presented in this work include a comparison to the L1T at

Mapping paddy rice planting area in rice-wetland coexistent areas through analysis of Landsat 8 OLI and MODIS images

PubMed Central

Zhou, Yuting; Xiao, Xiangming; Qin, Yuanwei; Dong, Jinwei; Zhang, Geli; Kou, Weili; Jin, Cui; Wang, Jie; Li, Xiangping

2016-01-01

Accurate and up-to-date information on the spatial distribution of paddy rice fields is necessary for the studies of trace gas emissions, water source management, and food security. The phenology-based paddy rice mapping algorithm, which identifies the unique flooding stage of paddy rice, has been widely used. However, identification and mapping of paddy rice in rice-wetland coexistent areas is still a challenging task. In this study, we found that the flooding/transplanting periods of paddy rice and natural wetlands were different. The natural wetlands flood earlier and have a shorter duration than paddy rice in the Panjin Plain, a temperate region in China. We used this asynchronous flooding stage to extract the paddy rice planting area from the rice-wetland coexistent area. MODIS Land Surface Temperature (LST) data was used to derive the temperature-defined plant growing season. Landsat 8 OLI imagery was used to detect the flooding signal and then paddy rice was extracted using the difference in flooding stages between paddy rice and natural wetlands. The resultant paddy rice map was evaluated with in-situ ground-truth data and Google Earth images. The estimated overall accuracy and Kappa coefficient were 95% and 0.90, respectively. The spatial pattern of OLI-derived paddy rice map agrees well with the paddy rice layer from the National Land Cover Dataset from 2010 (NLCD-2010). The differences between RiceLandsat and RiceNLCD are in the range of ±20% for most 1-km grid cell. The results of this study demonstrate the potential of the phenology-based paddy rice mapping algorithm, via integrating MODIS and Landsat 8 OLI images, to map paddy rice fields in complex landscapes of paddy rice and natural wetland in the temperate region. PMID:27688742

Mapping paddy rice planting area in rice-wetland coexistent areas through analysis of Landsat 8 OLI and MODIS images.

PubMed

Zhou, Yuting; Xiao, Xiangming; Qin, Yuanwei; Dong, Jinwei; Zhang, Geli; Kou, Weili; Jin, Cui; Wang, Jie; Li, Xiangping

2016-04-01

Accurate and up-to-date information on the spatial distribution of paddy rice fields is necessary for the studies of trace gas emissions, water source management, and food security. The phenology-based paddy rice mapping algorithm, which identifies the unique flooding stage of paddy rice, has been widely used. However, identification and mapping of paddy rice in rice-wetland coexistent areas is still a challenging task. In this study, we found that the flooding/transplanting periods of paddy rice and natural wetlands were different. The natural wetlands flood earlier and have a shorter duration than paddy rice in the Panjin Plain, a temperate region in China. We used this asynchronous flooding stage to extract the paddy rice planting area from the rice-wetland coexistent area. MODIS Land Surface Temperature (LST) data was used to derive the temperature-defined plant growing season. Landsat 8 OLI imagery was used to detect the flooding signal and then paddy rice was extracted using the difference in flooding stages between paddy rice and natural wetlands. The resultant paddy rice map was evaluated with in-situ ground-truth data and Google Earth images. The estimated overall accuracy and Kappa coefficient were 95% and 0.90, respectively. The spatial pattern of OLI-derived paddy rice map agrees well with the paddy rice layer from the National Land Cover Dataset from 2010 (NLCD-2010). The differences between Rice Landsat and Rice NLCD are in the range of ±20% for most 1-km grid cell. The results of this study demonstrate the potential of the phenology-based paddy rice mapping algorithm, via integrating MODIS and Landsat 8 OLI images, to map paddy rice fields in complex landscapes of paddy rice and natural wetland in the temperate region.

A multicharge ion source (Supernanogan) for the OLIS facility at ISAC/TRIUMF.

PubMed

Jayamanna, K; Wight, G; Gallop, D; Dube, R; Jovicic, V; Laforge, C; Marchetto, M; Leross, M; Louie, D; Laplante, R; Laxdal, R; McDonald, M; Wiebe, G J; Wang, V; Yan, F

2010-02-01

The Off-Line Ion Source (OLIS) [K. Jayamanna, D. Yuan, T. Kuo, M. MacDonald, P. Schmor, and G. Dutto, Rev. Sci. Instrum. 67, 1061 (1996); K. Jayamanna, Rev. Sci. Instrum. 79, 02711 (2008)] facility consists of a high voltage terminal containing a microwave cusp ion source, either a surface ion source or a hybrid surface-arc discharge ion source [K. Jayamanna and C. Vockenhuber, Rev. Sci. Instrum. 79, 02C712 (2008)], and an electrostatic switch that allows the selection of any one of the sources without mechanical intervention. These sources provide a variety of +1 beams up to mass 30 for Isotope Separator and ACcelerator (ISAC) [R. E. Laxdal, Nucl. Instrum. Methods Phys. Res. B 204, 400 (2003)] experiments, commissioning the accelerators, setting up the radioactive experiments, and for tuning the beam lines. The radio frequency quadrupole (RFQ) [M. Marchetto, Z. T. Ang, K. Jayamanna, R. E. Laxdal, A. Mitra, and V. Zvyagintsev, Eur. Phys. J. Spec. Top. 150, 241 (2005)] injector accelerator is a constant velocity machine designed to accept only 2 keV/u and the source extraction energy is limited to 60 kV. Further stripping is then needed downstream of the RFQ to inject the beam into the drift tube linac [M. Marchetto, Z. T. Ang, K. Jayamanna, R. E. Laxdal, A. Mitra, and V. Zvyagintsev, Eur. Phys. J. Spec. Top. 150, 241 (2005)] accelerator that requires A/q up to 6. Base on this constraints a multicharge ion source capable to deliver beams above mass 30 with A/q up to 6 was needed in order to reach full capability of the ISAC facility. A Supernanogan [C. Bieth et al., Nucleonika 48, S93 (2003)] multicharge ion source was then purchased from Pantechnik and was installed in the OLIS terminal. Commissioning and performance of the Supernanogan with some results such as emittance dependence of the charge states as well as charge state efficiencies are presented.

Detection flying aircraft from Landsat 8 OLI data

NASA Astrophysics Data System (ADS)

Zhao, F.; Xia, L.; Kylling, A.; Li, R. Q.; Shang, H.; Xu, Ming

2018-07-01

Monitoring flying aircraft from satellite data is important for evaluating the climate impact caused by the global aviation industry. However, due to the small size of aircraft and the complex surface types, it is almost impossible to identify aircraft from satellite data with moderate resolution, e.g. 30 m. In this study, the 1.38 μm water vapor absorption channel, often used for cirrus cloud or ash detection, is for the first time used to monitor flying aircraft from Landsat 8 data. The basic theory behind the detection of flying aircraft is that in the 1.38 μm channel most of the background reflectance between the ground and the aircraft is masked due to the strong water vapor absorption, while the signal of the flying aircraft will be attenuated less due to the low water vapor content between the satellite and the aircraft. A new composition of the Laplacian and Sobel operators for segmenting aircraft and other features were used to identify the flying aircraft. The Landsat 8 Operational Land Imager (OLI) 2.1 μm channel was used to make the method succeed under low vapor content. The accuracy assessment based on 65 Landsat 8 images indicated that the percentage of leakage is 3.18% and the percentage of false alarm is 0.532%.

The Landsat Data Continuity Mission Operational Land Imager (OLI) Radiometric Calibration

NASA Technical Reports Server (NTRS)

Markham, Brian L.; Dabney, Philip W.; Murphy-Morris, Jeanine E.; Knight, Edward J.; Kvaran, Geir; Barsi, Julia A.

2010-01-01

The Operational Land Imager (OLI) on the Landsat Data Continuity Mission (LDCM) has a comprehensive radiometric characterization and calibration program beginning with the instrument design, and extending through integration and test, on-orbit operations and science data processing. Key instrument design features for radiometric calibration include dual solar diffusers and multi-lamped on-board calibrators. The radiometric calibration transfer procedure from NIST standards has multiple checks on the radiometric scale throughout the process and uses a heliostat as part of the transfer to orbit of the radiometric calibration. On-orbit lunar imaging will be used to track the instruments stability and side slither maneuvers will be used in addition to the solar diffuser to flat field across the thousands of detectors per band. A Calibration Validation Team is continuously involved in the process from design to operations. This team uses an Image Assessment System (IAS), part of the ground system to characterize and calibrate the on-orbit data.

Cross calibration of GF-1 satellite wide field of view sensor with Landsat 8 OLI and HJ-1A HSI

NASA Astrophysics Data System (ADS)

Liu, Li; Gao, Hailiang; Pan, Zhiqiang; Gu, Xingfa; Han, Qijin; Zhang, Xuewen

2018-01-01

This paper focuses on cross calibrating the GaoFen (GF-1) satellite wide field of view (WFV) sensor using the Landsat 8 Operational Land Imager (OLI) and HuanJing-1A (HJ-1A) hyperspectral imager (HSI) as reference sensors. Two methods are proposed to calculate the spectral band adjustment factor (SBAF). One is based on the HJ-1A HSI image and the other is based on ground-measured reflectance. However, the HSI image and ground-measured reflectance were measured at different dates, as the WFV and OLI imagers passed overhead. Three groups of regions of interest (ROIs) were chosen for cross calibration, based on different selection criteria. Cross-calibration gains with nonzero and zero offsets were both calculated. The results confirmed that the gains with zero offset were better, as they were more consistent over different groups of ROIs and SBAF calculation methods. The uncertainty of this cross calibration was analyzed, and the influence of SBAF was calculated based on different HSI images and ground reflectance spectra. The results showed that the uncertainty of SBAF was <3% for bands 1 to 3. Two other large uncertainties in this cross calibration were variation of atmosphere and low ground reflectance.

Modified Optimization Water Index (mowi) for LANDSAT-8 Oli/tirs

NASA Astrophysics Data System (ADS)

Moradi, M.; Sahebi, M.; Shokri, M.

2017-09-01

Water is one of the most important resources that essential need for human life. Due to population growth and increasing need of human to water, proper management of water resources will be one of the serious challenges of next decades. Remote sensing data is the best way to the management of water resources due time and cost effectiveness over a greater range of temporal and spatial scales. Between many kinds of satellite data, from SAR to optic or from high resolution to low resolution, Landsat imagery is more interesting data for water detection and management of earth surface water. Landsat8 OLI/TIRS is the newest version of Landsat satellite series. In this paper, we investigated the full spectral potential of Landsat8 for water detection. It is developed many kinds of methods for this purpose that index based methods have some advantages than other methods. Pervious indices just use a limited number of spectral band. In this paper, Modified Optimization Water Index (MOWI) defined by consideration of a linear combination of bands that each coefficient of bands calculated by particle swarm algorithm. The result shows that modified optimization water index (MOWI) has a proper performance on different condition like cloud, cloud shadow and mountain shadow.

Field-based rice classification in Wuhua county through integration of multi-temporal Sentinel-1A and Landsat-8 OLI data

NASA Astrophysics Data System (ADS)

Yang, Huijin; Pan, Bin; Wu, Wenfu; Tai, Jianhao

2018-07-01

Rice is one of the most important cereals in the world. With the change of agricultural land, it is urgently necessary to update information about rice planting areas. This study aims to map rice planting areas with a field-based approach through the integration of multi-temporal Sentinel-1A and Landsat-8 OLI data in Wuhua County of South China where has many basins and mountains. This paper, using multi-temporal SAR and optical images, proposes a methodology for the identification of rice-planting areas. This methodology mainly consists of SSM applied to time series SAR images for the calculation of a similarity measure, image segmentation process applied to the pan-sharpened optical image for the searching of homogenous objects, and the integration of SAR and optical data for the elimination of some speckles. The study compares the per-pixel approach with the per-field approach and the results show that the highest accuracy (91.38%) based on the field-based approach is 1.18% slightly higher than that based on the pixel-based approach for VH polarization, which is brought by eliminating speckle noise through comparing the rice maps of these two approaches. Therefore, the integration of Sentinel-1A and Landsat-8 OLI images with a field-based approach has great potential for mapping rice or other crops' areas.

Mapping Soil Salinity/Sodicity by using Landsat OLI Imagery and PLSR Algorithm over Semiarid West Jilin Province, China

PubMed Central

Liu, Mingyue; Du, Baojia; Zhang, Bai

2018-01-01

Soil salinity and sodicity can significantly reduce the value and the productivity of affected lands, posing degradation, and threats to sustainable development of natural resources on earth. This research attempted to map soil salinity/sodicity via disentangling the relationships between Landsat 8 Operational Land Imager (OLI) imagery and in-situ measurements (EC, pH) over the west Jilin of China. We established the retrieval models for soil salinity and sodicity using Partial Least Square Regression (PLSR). Spatial distribution of the soils that were subjected to hybridized salinity and sodicity (HSS) was obtained by overlay analysis using maps of soil salinity and sodicity in geographical information system (GIS) environment. We analyzed the severity and occurring sizes of soil salinity, sodicity, and HSS with regard to specified soil types and land cover. Results indicated that the models’ accuracy was improved by combining the reflectance bands and spectral indices that were mathematically transformed. Therefore, our results stipulated that the OLI imagery and PLSR method applied to mapping soil salinity and sodicity in the region. The mapping results revealed that the areas of soil salinity, sodicity, and HSS were 1.61 × 106 hm2, 1.46 × 106 hm2, and 1.36 × 106 hm2, respectively. Also, the occurring area of moderate and intensive sodicity was larger than that of salinity. This research may underpin efficiently mapping regional salinity/sodicity occurrences, understanding the linkages between spectral reflectance and ground measurements of soil salinity and sodicity, and provide tools for soil salinity monitoring and the sustainable utilization of land resources. PMID:29614727

Application of Landsat 8 OLI Image and Empirical Model for Water Trophic Status Identification of Riam Kanan Reservoir, Banjar, South Kalimantan

NASA Astrophysics Data System (ADS)

Saputra, A. N.; Danoedoro, P.; Kamal, M.

2017-12-01

Remote sensing has a potential for observing, mapping and monitoring the quality of lake water. Riam Kanan is a reservoir which has a water resource from Riam Kanan River with the area width of its watershed about 1043 km2. The accumulation of nutrient in this reservoir simultaneously deteriorates the condition of waters, which can cause an increasingly growth of harm micro algae or Harmful Algal Blooms (HABs). This research applied Carlson’s trophic status index (CTSI) at Riam Kanan Reservoir using Landsat-8 OLI satellite image. The Landsat 8 OLI image was recorded on 14 August 2016 and was used in this research based on its surface reflectance values. The result of correlation test shows that band 3 of the image as coefficient of chlorophyll-a parameter, channel 2 as coefficient of phosphate, and band ratio of SDT as coefficient of SDT. Based on the result of modelling using CTSI, the majority scale of CTSI score at Riam Kanan Reservoir is between 60 to70 in medium eutrophic class. The class of medium eutrophic at Riam Kanan Reservoir potentially emerges the threat both of the improvement of water fertility and the reduction of water quality. Improvement of the fertility is apprehensive since it can trigger an explosion of micro algae which will endanger the ecological condition at the area of Riam Kanan Reservoir.

Quantifying biomass consumption and carbon release from the California Rim fire by integrating airborne LiDAR and Landsat OLI data.

PubMed

Garcia, Mariano; Saatchi, Sassan; Casas, Angeles; Koltunov, Alexander; Ustin, Susan; Ramirez, Carlos; Garcia-Gutierrez, Jorge; Balzter, Heiko

2017-02-01

Quantifying biomass consumption and carbon release is critical to understanding the role of fires in the carbon cycle and air quality. We present a methodology to estimate the biomass consumed and the carbon released by the California Rim fire by integrating postfire airborne LiDAR and multitemporal Landsat Operational Land Imager (OLI) imagery. First, a support vector regression (SVR) model was trained to estimate the aboveground biomass (AGB) from LiDAR-derived metrics over the unburned area. The selected model estimated AGB with an R 2 of 0.82 and RMSE of 59.98 Mg/ha. Second, LiDAR-based biomass estimates were extrapolated to the entire area before and after the fire, using Landsat OLI reflectance bands, Normalized Difference Infrared Index, and the elevation derived from LiDAR data. The extrapolation was performed using SVR models that resulted in R 2 of 0.73 and 0.79 and RMSE of 87.18 (Mg/ha) and 75.43 (Mg/ha) for the postfire and prefire images, respectively. After removing bias from the AGB extrapolations using a linear relationship between estimated and observed values, we estimated the biomass consumption from postfire LiDAR and prefire Landsat maps to be 6.58 ± 0.03 Tg (10 12  g), which translate into 12.06 ± 0.06 Tg CO2 e released to the atmosphere, equivalent to the annual emissions of 2.57 million cars.

Quantifying biomass consumption and carbon release from the California Rim fire by integrating airborne LiDAR and Landsat OLI data

PubMed Central

Saatchi, Sassan; Casas, Angeles; Koltunov, Alexander; Ustin, Susan; Ramirez, Carlos; Garcia‐Gutierrez, Jorge; Balzter, Heiko

2017-01-01

Abstract Quantifying biomass consumption and carbon release is critical to understanding the role of fires in the carbon cycle and air quality. We present a methodology to estimate the biomass consumed and the carbon released by the California Rim fire by integrating postfire airborne LiDAR and multitemporal Landsat Operational Land Imager (OLI) imagery. First, a support vector regression (SVR) model was trained to estimate the aboveground biomass (AGB) from LiDAR‐derived metrics over the unburned area. The selected model estimated AGB with an R 2 of 0.82 and RMSE of 59.98 Mg/ha. Second, LiDAR‐based biomass estimates were extrapolated to the entire area before and after the fire, using Landsat OLI reflectance bands, Normalized Difference Infrared Index, and the elevation derived from LiDAR data. The extrapolation was performed using SVR models that resulted in R 2 of 0.73 and 0.79 and RMSE of 87.18 (Mg/ha) and 75.43 (Mg/ha) for the postfire and prefire images, respectively. After removing bias from the AGB extrapolations using a linear relationship between estimated and observed values, we estimated the biomass consumption from postfire LiDAR and prefire Landsat maps to be 6.58 ± 0.03 Tg (1012 g), which translate into 12.06 ± 0.06 Tg CO2e released to the atmosphere, equivalent to the annual emissions of 2.57 million cars. PMID:28405539

Estimation of Chlorophyll-a Concentration and the Trophic State of the Barra Bonita Hydroelectric Reservoir Using OLI/Landsat-8 Images

PubMed Central

Watanabe, Fernanda Sayuri Yoshino; Alcântara, Enner; Rodrigues, Thanan Walesza Pequeno; Imai, Nilton Nobuhiro; Barbosa, Cláudio Clemente Faria; Rotta, Luiz Henrique da Silva

2015-01-01

Reservoirs are artificial environments built by humans, and the impacts of these environments are not completely known. Retention time and high nutrient availability in the water increases the eutrophic level. Eutrophication is directly correlated to primary productivity by phytoplankton. These organisms have an important role in the environment. However, high concentrations of determined species can lead to public health problems. Species of cyanobacteria produce toxins that in determined concentrations can cause serious diseases in the liver and nervous system, which could lead to death. Phytoplankton has photoactive pigments that can be used to identify these toxins. Thus, remote sensing data is a viable alternative for mapping these pigments, and consequently, the trophic. Chlorophyll-a (Chl-a) is present in all phytoplankton species. Therefore, the aim of this work was to evaluate the performance of images of the sensor Operational Land Imager (OLI) onboard the Landsat-8 satellite in determining Chl-a concentrations and estimating the trophic level in a tropical reservoir. Empirical models were fitted using data from two field surveys conducted in May and October 2014 (Austral Autumn and Austral Spring, respectively). Models were applied in a temporal series of OLI images from May 2013 to October 2014. The estimated Chl-a concentration was used to classify the trophic level from a trophic state index that adopted the concentration of this pigment-like parameter. The models of Chl-a concentration showed reasonable results, but their performance was likely impaired by the atmospheric correction. Consequently, the trophic level classification also did not obtain better results. PMID:26322489

The Aplication of Landsat 8 OLI for Total Suspended Solid (TSS) Mapping in Gajahmungkur Reservoir Wonogiri Regency 2016

NASA Astrophysics Data System (ADS)

Yanti, Apriwida; Susilo, Bowo; Wicaksono, Pramaditya

2016-11-01

Gajahmungkur reservoir is administratively located in Wonogiri Regency, Central Java, with the main function as a flood control in the upstream of Bengawan Solo River. Other functions of the reservoir are as hydroelectric power plant (PLTA), water supply, irrigation, fisheries and tourism. Economic utilization of the reservoir is estimated until 100 years, but it is begun to be threatened by the silting of the reservoir. Eroded materials entering water body will be suspended and accumulated. Suspended Material or TSS (Total Suspended Solid) will increase the turbidity of water, which can affect the quality of water and silting the reservoir. Remote sensing technology can be used to determine the spatial distribution of TSS. The purposes of this study were to 1) utilize and compare the accuracy of single band Landsat 8 OLI for mapping the spatial distribution of TSS and 2) estimate the TSS on Gajahmungkur reservoir surface waters up to the depth of 30 cm. The method used for modelling the TSS spatial distribution is the empirical modelling that integrates image pixel values and field data using correlation analysis and regression analysis. The data used in the empirical modelling are single band of visible, NIR, and SWIR of Landsat 8 OLI, which was acquired on 8 May 2016, and field-measured TSS values based on the field data collection conducted on 12 April 2016. The results revealed that mapping the distribution and the estimated value of TSS in Reservoir Gajahmungkur can be performed more accurately using band 4 (red band). The determinant coefficient between TSS field and TSS value of image using band 4 is 0.5431. The Standard Error (SE) of the predicted TSS value is 16.16 mg/L. The results also showed that the estimated total TSS of May 2016 according to band 4 is 1.087,56 tons. The average estimation of TSS value in up to the depth of 30 cm is 61.61 mg/L. The highest TSS distribution is in the northern parts, which was dominated by eroded materials from Keduang

On the Corrosion Performance of Monel 400 in Molten LiCl-Li2O-Li at 923 K

NASA Astrophysics Data System (ADS)

Phillips, William; Merwin, Augustus; Chidambaram, Dev

2018-06-01

The corrosion resistance of a Ni-Cu alloy, Monel 400, in molten LiCl-Li2O-Li at 923 K (650 °C) was investigated. Exposure testing of Monel 400 samples submerged in molten LiCl-2 wt pct Li2O solutions with Li concentrations between zero and 1 wt pct was performed at 923 K (650°C) for 20 hours. Post exposure surface analysis was performed using X-ray diffraction, scanning electron microscopy, energy dispersive X-ray spectroscopy, optical microscopy, micro-Vickers hardness testing, and X-ray photoelectron spectroscopy, while inductively coupled plasma optical emission spectroscopy was used to quantify the rate of material leaching. The extent of material degradation was observed to be strongly correlated to the concentration of metallic Li in the molten LiCl-Li2O system.

Spatiotemporal Built-up Land Density Mapping Using Various Spectral Indices in Landsat-7 ETM+ and Landsat-8 OLI/TIRS (Case Study: Surakarta City)

NASA Astrophysics Data System (ADS)

Risky, Yanuar S.; Aulia, Yogi H.; Widayani, Prima

2017-12-01

Spectral indices variations support for rapid and accurate extracting information such as built-up density. However, the exact determination of spectral waves for built-up density extraction is lacking. This study explains and compares the capabilities of 5 variations of spectral indices in spatiotemporal built-up density mapping using Landsat-7 ETM+ and Landsat-8 OLI/TIRS in Surakarta City on 2002 and 2015. The spectral indices variations used are 3 mid-infrared (MIR) based indices such as the Normalized Difference Built-up Index (NDBI), Urban Index (UI) and Built-up and 2 visible based indices such as VrNIR-BI (visible red) and VgNIR-BI (visible green). Linear regression statistics between ground value samples from Google Earth image in 2002 and 2015 and spectral indices for determining built-up land density. Ground value used amounted to 27 samples for model and 7 samples for accuracy test. The classification of built-up density mapping is divided into 9 classes: unclassified, 0-12.5%, 12.5-25%, 25-37.5%, 37.5-50%, 50-62.5%, 62.5-75%, 75-87.5% and 87.5-100 %. Accuracy of built-up land density mapping in 2002 and 2015 using VrNIR-BI (81,823% and 73.235%), VgNIR-BI (78.934% and 69.028%), NDBI (34.870% and 74.365%), UI (43.273% and 64.398%) and Built-up (59.755% and 72.664%). Based all spectral indices, Surakarta City on 2000-2015 has increased of built-up land density. VgNIR-BI has better capabilities for built-up land density mapping on Landsat-7 ETM + and Landsat-8 OLI/TIRS.

Quantitative extraction of the bedrock exposure rate based on unmanned aerial vehicle data and Landsat-8 OLI image in a karst environment

NASA Astrophysics Data System (ADS)

Wang, Hongyan; Li, Qiangzi; Du, Xin; Zhao, Longcai

2017-12-01

In the karst regions of southwest China, rocky desertification is one of the most serious problems in land degradation. The bedrock exposure rate is an important index to assess the degree of rocky desertification in karst regions. Because of the inherent merits of macro-scale, frequency, efficiency, and synthesis, remote sensing is a promising method to monitor and assess karst rocky desertification on a large scale. However, actual measurement of the bedrock exposure rate is difficult and existing remote-sensing methods cannot directly be exploited to extract the bedrock exposure rate owing to the high complexity and heterogeneity of karst environments. Therefore, using unmanned aerial vehicle (UAV) and Landsat-8 Operational Land Imager (OLI) data for Xingren County, Guizhou Province, quantitative extraction of the bedrock exposure rate based on multi-scale remote-sensing data was developed. Firstly, we used an object-oriented method to carry out accurate classification of UAVimages. From the results of rock extraction, the bedrock exposure rate was calculated at the 30 m grid scale. Parts of the calculated samples were used as training data; other data were used for model validation. Secondly, in each grid the band reflectivity of Landsat-8 OLI data was extracted and a variety of rock and vegetation indexes (e.g., NDVI and SAVI) were calculated. Finally, a network model was established to extract the bedrock exposure rate. The correlation coefficient of the network model was 0.855, that of the validation model was 0.677 and the root mean square error of the validation model was 0.073. This method is valuable for wide-scale estimation of bedrock exposure rate in karst environments. Using the quantitative inversion model, a distribution map of the bedrock exposure rate in Xingren County was obtained.

Mapping paddy rice planting area in cold temperate climate region through analysis of time series Landsat 8 (OLI), Landsat 7 (ETM+) and MODIS imagery

NASA Astrophysics Data System (ADS)

Qin, Yuanwei; Xiao, Xiangming; Dong, Jinwei; Zhou, Yuting; Zhu, Zhe; Zhang, Geli; Du, Guoming; Jin, Cui; Kou, Weili; Wang, Jie; Li, Xiangping

2015-07-01

Accurate and timely rice paddy field maps with a fine spatial resolution would greatly improve our understanding of the effects of paddy rice agriculture on greenhouse gases emissions, food and water security, and human health. Rice paddy field maps were developed using optical images with high temporal resolution and coarse spatial resolution (e.g., Moderate Resolution Imaging Spectroradiometer (MODIS)) or low temporal resolution and high spatial resolution (e.g., Landsat TM/ETM+). In the past, the accuracy and efficiency for rice paddy field mapping at fine spatial resolutions were limited by the poor data availability and image-based algorithms. In this paper, time series MODIS and Landsat ETM+/OLI images, and the pixel- and phenology-based algorithm are used to map paddy rice planting area. The unique physical features of rice paddy fields during the flooding/open-canopy period are captured with the dynamics of vegetation indices, which are then used to identify rice paddy fields. The algorithm is tested in the Sanjiang Plain (path/row 114/27) in China in 2013. The overall accuracy of the resulted map of paddy rice planting area generated by both Landsat ETM+ and OLI is 97.3%, when evaluated with areas of interest (AOIs) derived from geo-referenced field photos. The paddy rice planting area map also agrees reasonably well with the official statistics at the level of state farms (R2 = 0.94). These results demonstrate that the combination of fine spatial resolution images and the phenology-based algorithm can provide a simple, robust, and automated approach to map the distribution of paddy rice agriculture in a year.

Mapping paddy rice planting area in cold temperate climate region through analysis of time series Landsat 8 (OLI), Landsat 7 (ETM+) and MODIS imagery.

PubMed

Qin, Yuanwei; Xiao, Xiangming; Dong, Jinwei; Zhou, Yuting; Zhu, Zhe; Zhang, Geli; Du, Guoming; Jin, Cui; Kou, Weili; Wang, Jie; Li, Xiangping

2015-07-01

Accurate and timely rice paddy field maps with a fine spatial resolution would greatly improve our understanding of the effects of paddy rice agriculture on greenhouse gases emissions, food and water security, and human health. Rice paddy field maps were developed using optical images with high temporal resolution and coarse spatial resolution (e.g., Moderate Resolution Imaging Spectroradiometer (MODIS)) or low temporal resolution and high spatial resolution (e.g., Landsat TM/ETM+). In the past, the accuracy and efficiency for rice paddy field mapping at fine spatial resolutions were limited by the poor data availability and image-based algorithms. In this paper, time series MODIS and Landsat ETM+/OLI images, and the pixel- and phenology-based algorithm are used to map paddy rice planting area. The unique physical features of rice paddy fields during the flooding/open-canopy period are captured with the dynamics of vegetation indices, which are then used to identify rice paddy fields. The algorithm is tested in the Sanjiang Plain (path/row 114/27) in China in 2013. The overall accuracy of the resulted map of paddy rice planting area generated by both Landsat ETM+ and OLI is 97.3%, when evaluated with areas of interest (AOIs) derived from geo-referenced field photos. The paddy rice planting area map also agrees reasonably well with the official statistics at the level of state farms ( R 2 = 0.94). These results demonstrate that the combination of fine spatial resolution images and the phenology-based algorithm can provide a simple, robust, and automated approach to map the distribution of paddy rice agriculture in a year.

Mapping of the Seagrass Cover Along the Mediterranean Coast of Turkey Using Landsat 8 Oli Images

NASA Astrophysics Data System (ADS)

Bakirman, T.; Gumusay, M. U.; Tuney, I.

2016-06-01

Benthic habitat is defined as ecological environment where marine animals, plants and other organisms live in. Benthic habitat mapping is defined as plotting the distribution and extent of habitats to create a map with complete coverage of the seabed showing distinct boundaries separating adjacent habitats or the use of spatially continuous environmental data sets to represent and predict biological patterns on the seafloor. Seagrass is an essential endemic marine species that prevents coast erosion and regulates carbon dioxide absorption in both undersea and atmosphere. Fishing, mining, pollution and other human activities cause serious damage to seabed ecosystems and reduce benthic biodiversity. According to the latest studies, only 5-10% of the seafloor is mapped, therefore it is not possible to manage resources effectively, protect ecologically important areas. In this study, it is aimed to map seagrass cover using Landsat 8 OLI images in the northern part of Mediterranean coast of Turkey. After pre-processing (e.g. radiometric, atmospheric, water depth correction) of Landsat images, coverage maps are produced with supervised classification using in-situ data which are underwater photos and videos. Result maps and accuracy assessment are presented and discussed.

Examining spectral properties of Landsat 8 OLI for predicting above-ground carbon of Labanan Forest, Berau

NASA Astrophysics Data System (ADS)

Suhardiman, A.; Tampubolon, B. A.; Sumaryono, M.

2018-04-01

Many studies revealed significant correlation between satellite image properties and forest data attributes such as stand volume, biomass or carbon stock. However, further study is still relevant due to advancement of remote sensing technology as well as improvement on methods of data analysis. In this study, the properties of three vegetation indices derived from Landsat 8 OLI were tested upon above-ground carbon stock data from 50 circular sample plots (30-meter radius) from ground survey in PT. Inhutani I forest concession in Labanan, Berau, East Kalimantan. Correlation analysis using Pearson method exhibited a promising results when the coefficient of correlation (r-value) was higher than 0.5. Further regression analysis was carried out to develop mathematical model describing the correlation between sample plots data and vegetation index image using various mathematical models.Power and exponential model were demonstrated a good result for all vegetation indices. In order to choose the most adequate mathematical model for predicting Above-ground Carbon (AGC), the Bayesian Information Criterion (BIC) was applied. The lowest BIC value (i.e. -376.41) shown by Transformed Vegetation Index (TVI) indicates this formula, AGC = 9.608*TVI21.54, is the best predictor of AGC of study area.

Forest Disturbance Analysis with LANDSAT-8 Oli Data Related to a Parametric Wind Field: a Case Study for Typhoon Rammasun (201409)

NASA Astrophysics Data System (ADS)

Tan, C.; Fang, W.

2018-04-01

Forest disturbance induced by tropical cyclone often has significant and profound effects on the structure and function of forest ecosystem. Detection and analysis of post-disaster forest disturbance based on remote sensing technology has been widely applied. At present, it is necessary to conduct further quantitative analysis of the magnitude of forest disturbance with the intensity of typhoon. In this study, taking the case of super typhoon Rammasun (201409), we analysed the sensitivity of four common used remote sensing indices and explored the relationship between remote sensing index and corresponding wind speeds based on pre-and post- Landsat-8 OLI (Operational Land Imager) images and a parameterized wind field model. The results proved that NBR is the most sensitive index for the detection of forest disturbance induced by Typhoon Rammasun and the variation of NBR has a significant linear dependence relation with the simulated 3-second gust wind speed.

Multi-Feature Classification of Multi-Sensor Satellite Imagery Based on Dual-Polarimetric Sentinel-1A, Landsat-8 OLI, and Hyperion Images for Urban Land-Cover Classification.

PubMed

Zhou, Tao; Li, Zhaofu; Pan, Jianjun

2018-01-27

This paper focuses on evaluating the ability and contribution of using backscatter intensity, texture, coherence, and color features extracted from Sentinel-1A data for urban land cover classification and comparing different multi-sensor land cover mapping methods to improve classification accuracy. Both Landsat-8 OLI and Hyperion images were also acquired, in combination with Sentinel-1A data, to explore the potential of different multi-sensor urban land cover mapping methods to improve classification accuracy. The classification was performed using a random forest (RF) method. The results showed that the optimal window size of the combination of all texture features was 9 × 9, and the optimal window size was different for each individual texture feature. For the four different feature types, the texture features contributed the most to the classification, followed by the coherence and backscatter intensity features; and the color features had the least impact on the urban land cover classification. Satisfactory classification results can be obtained using only the combination of texture and coherence features, with an overall accuracy up to 91.55% and a kappa coefficient up to 0.8935, respectively. Among all combinations of Sentinel-1A-derived features, the combination of the four features had the best classification result. Multi-sensor urban land cover mapping obtained higher classification accuracy. The combination of Sentinel-1A and Hyperion data achieved higher classification accuracy compared to the combination of Sentinel-1A and Landsat-8 OLI images, with an overall accuracy of up to 99.12% and a kappa coefficient up to 0.9889. When Sentinel-1A data was added to Hyperion images, the overall accuracy and kappa coefficient were increased by 4.01% and 0.0519, respectively.

Multi-Feature Classification of Multi-Sensor Satellite Imagery Based on Dual-Polarimetric Sentinel-1A, Landsat-8 OLI, and Hyperion Images for Urban Land-Cover Classification

PubMed Central

Pan, Jianjun

2018-01-01

This paper focuses on evaluating the ability and contribution of using backscatter intensity, texture, coherence, and color features extracted from Sentinel-1A data for urban land cover classification and comparing different multi-sensor land cover mapping methods to improve classification accuracy. Both Landsat-8 OLI and Hyperion images were also acquired, in combination with Sentinel-1A data, to explore the potential of different multi-sensor urban land cover mapping methods to improve classification accuracy. The classification was performed using a random forest (RF) method. The results showed that the optimal window size of the combination of all texture features was 9 × 9, and the optimal window size was different for each individual texture feature. For the four different feature types, the texture features contributed the most to the classification, followed by the coherence and backscatter intensity features; and the color features had the least impact on the urban land cover classification. Satisfactory classification results can be obtained using only the combination of texture and coherence features, with an overall accuracy up to 91.55% and a kappa coefficient up to 0.8935, respectively. Among all combinations of Sentinel-1A-derived features, the combination of the four features had the best classification result. Multi-sensor urban land cover mapping obtained higher classification accuracy. The combination of Sentinel-1A and Hyperion data achieved higher classification accuracy compared to the combination of Sentinel-1A and Landsat-8 OLI images, with an overall accuracy of up to 99.12% and a kappa coefficient up to 0.9889. When Sentinel-1A data was added to Hyperion images, the overall accuracy and kappa coefficient were increased by 4.01% and 0.0519, respectively. PMID:29382073

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.

Performance evaluation of object based greenhouse detection from Sentinel-2 MSI and Landsat 8 OLI data: A case study from Almería (Spain)

NASA Astrophysics Data System (ADS)

Novelli, Antonio; Aguilar, Manuel A.; Nemmaoui, Abderrahim; Aguilar, Fernando J.; Tarantino, Eufemia

2016-10-01

This paper shows the first comparison between data from Sentinel-2 (S2) Multi Spectral Instrument (MSI) and Landsat 8 (L8) Operational Land Imager (OLI) headed up to greenhouse detection. Two closely related in time scenes, one for each sensor, were classified by using Object Based Image Analysis and Random Forest (RF). The RF input consisted of several object-based features computed from spectral bands and including mean values, spectral indices and textural features. S2 and L8 data comparisons were also extended using a common segmentation dataset extracted form VHR World-View 2 (WV2) imagery to test differences only due to their specific spectral contribution. The best band combinations to perform segmentation were found through a modified version of the Euclidian Distance 2 index. Four different RF classifications schemes were considered achieving 89.1%, 91.3%, 90.9% and 93.4% as the best overall accuracies respectively, evaluated over the whole study area.

A comparison of two adaptive multivariate analysis methods (PLSR and ANN) for winter wheat yield forecasting using Landsat-8 OLI images

NASA Astrophysics Data System (ADS)

Chen, Pengfei; Jing, Qi

2017-02-01

An assumption that the non-linear method is more reasonable than the linear method when canopy reflectance is used to establish the yield prediction model was proposed and tested in this study. For this purpose, partial least squares regression (PLSR) and artificial neural networks (ANN), represented linear and non-linear analysis method, were applied and compared for wheat yield prediction. Multi-period Landsat-8 OLI images were collected at two different wheat growth stages, and a field campaign was conducted to obtain grain yields at selected sampling sites in 2014. The field data were divided into a calibration database and a testing database. Using calibration data, a cross-validation concept was introduced for the PLSR and ANN model construction to prevent over-fitting. All models were tested using the test data. The ANN yield-prediction model produced R2, RMSE and RMSE% values of 0.61, 979 kg ha-1, and 10.38%, respectively, in the testing phase, performing better than the PLSR yield-prediction model, which produced R2, RMSE, and RMSE% values of 0.39, 1211 kg ha-1, and 12.84%, respectively. Non-linear method was suggested as a better method for yield prediction.

Amino acid substitutions in subunit 9 of the mitochondrial ATPase complex of Saccharomyces cerevisiae. Sequence analysis of a series of revertants of an oli1 mit- mutant carrying an amino acid substitution in the hydrophilic loop of subunit 9.

PubMed

Willson, T A; Nagley, P

1987-09-01

This work concerns a biochemical genetic study of subunit 9 of the mitochondrial ATPase complex of Saccharomyces cerevisiae. Subunit 9, encoded by the mitochondrial oli1 gene, contains a hydrophilic loop connecting two transmembrane stems. In one particular oli1 mit- mutant 2422, the substitution of a positively charged amino acid in this loop (Arg39----Met) renders the ATPase complex non-functional. A series of 20 revertants, selected for their ability to grow on nonfermentable substrates, has been isolated from mutant 2422. The results of DNA sequence analysis of the oli1 gene in each revertant have led to the recognition of three groups of revertants. Class I revertants have undergone a same-site reversion event: the mutant Met39 is replaced either by arginine (as in wild-type) or lysine. Class II revertants maintain the mutant Met39 residue, but have undergone a second-site reversion event (Asn35----Lys). Two revertants showing an oligomycin-resistant phenotype carry this same second-site reversion in the loop region together with a further amino acid substitution in either of the two membrane-spanning segments of subunit 9 (either Gly23----Ser or Leu53----Phe). Class III revertants contain subunit 9 with the original mutant 2422 sequence, and additionally carry a recessive nuclear suppressor, demonstrated to represent a single gene. The results on the revertants in classes I and II indicate that there is a strict requirement for a positively charged residue in the hydrophilic loop close to the boundary of the lipid bilayer. The precise location of this positive charge is less stringent; in functional ATPase complexes it can be found at either residue 39 or 35. This charged residue is possibly required to interact with some other component of the mitochondrial ATPase complex. These findings, together with hydropathy plots of subunit 9 polypeptides from normal, mutant and revertant strains, led to the conclusion that the hydrophilic loop in normal subunit 9

Evaluation of automatic cloud removal method for high elevation areas in Landsat 8 OLI images to improve environmental indexes computation

NASA Astrophysics Data System (ADS)

Alvarez, César I.; Teodoro, Ana; Tierra, Alfonso

2017-10-01

Thin clouds in the optical remote sensing data are frequent and in most of the cases don't allow to have a pure surface data in order to calculate some indexes as Normalized Difference Vegetation Index (NDVI). This paper aims to evaluate the Automatic Cloud Removal Method (ACRM) algorithm over a high elevation city like Quito (Ecuador), with an altitude of 2800 meters above sea level, where the clouds are presented all the year. The ACRM is an algorithm that considers a linear regression between each Landsat 8 OLI band and the Cirrus band using the slope obtained with the linear regression established. This algorithm was employed without any reference image or mask to try to remove the clouds. The results of the application of the ACRM algorithm over Quito didn't show a good performance. Therefore, was considered improving this algorithm using a different slope value data (ACMR Improved). After, the NDVI computation was compared with a reference NDVI MODIS data (MOD13Q1). The ACMR Improved algorithm had a successful result when compared with the original ACRM algorithm. In the future, this Improved ACRM algorithm needs to be tested in different regions of the world with different conditions to evaluate if the algorithm works successfully for all conditions.

Multiscale object-based drought monitoring and comparison in rainfed and irrigated agriculture from Landsat 8 OLI imagery

NASA Astrophysics Data System (ADS)

Ozelkan, Emre; Chen, Gang; Ustundag, Burak Berk

2016-02-01

Drought is a rapidly rising environmental issue that can cause hardly repaired or unrepaired damages to the nature and socio-economy. This is especially true for a region that features arid/semi-arid climate, including the Turkey's most important agricultural district - Southeast Anatolia. In this area, we examined the uncertainties of applying Landsat 8 Operational Land Imager (OLI) NDVI data to estimate meteorological drought - Standardized Precipitation Index (SPI) - measured from 31 in-situ agro-meteorological monitoring stations during spring and summer of 2013 and 2014. Our analysis was designed to address two important, yet under-examined questions: (i) how does the co-existence of rainfed and irrigated agriculture affect remote sensing drought monitoring in an arid/semi-arid region? (ii) What is the role of spatial scale in drought monitoring using a GEOBIA (geographic object-based image analysis) framework? Results show that spatial scale exerted a higher impact on drought monitoring especially in the drier year 2013, during which small scales were found to outperform large scales in general. In addition, consideration of irrigated and rainfed areas separately ensured a better performance in drought analysis. Compared to the positive correlations between SPI and NDVI over the rainfed areas, negative correlations were determined over the irrigated agricultural areas. Finally, the time lag effect was evident in the study, i.e., strong correlations between spring SPI and summer NDVI in both 2013 and 2014. This reflects the fact that spring watering is crucial for the growth and yield of the major crops (i.e., winter wheat, barley and lentil) cultivated in the region.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Identifying Distribution of Chlorophyll-a Concentration Using Landsat 8 OLI on Marine Waters Area of Cirebon

NASA Astrophysics Data System (ADS)

Buditama, Gilang; Damayanti, Astrid; Giok Pin, Tjiong

2017-12-01

Phytoplankton is a microscopic plant that has a function to produces oxygen and organic substances. It also plays a role as a main producer in the food chain of a marine ecosystem. Chlorophyll-a is a colour pigment most common in phytoplankton species, so that the concentration level of chlorophyll-a can be used as an indicator of the abundance of phytoplankton cells, and as a reference for predicting organic potency in the aquatic area. This research discusses about the spatial and temporal distribution of chlorophyll-a and its correlation with salinity and total suspended solid (TSS), in the seawaters of Cirebon, West Java. The goal of this research is to be a source of information for fishermen, and other stakeholders whose related subjects in the field of marine and fisheries to predict fertile water regions and can also be used as an indicator in discovering potential areas to catch pelagic fish in Cirebon seawaters. Chlorophyll-a concentration, salinity, and TSS are identified using remote sensing data such as Landsat-8 OLI multi temporal images according to dry and wet month parameters in the 2014-2015. The results of the processed image are then validated between in-situ measurements in the field and remote sensing imagery at the same time. This research utilizes descriptive analysis, and statistics with spatial approach. The results of the research show that temporally, chlorophyll-a levels have a tendency to be higher in wet months compared to dry months, while chlorophyll-a is higher in areas near the coastline compared to open sea areas. The distribution of chlorophyll-a concentration is affected by salinity and TSS distribution, where salinity has the negative relationship and TSS has the positive relationship with chlorophyll-a distribution.

Effect of RE (Nd3+, Sm3+) oxide on structural, optical properties of Na2O-Li2O-ZnO-B2O3 glass system

NASA Astrophysics Data System (ADS)

Hivrekar, Mahesh M.; Bhoyar, D. N.; Mande, V. K.; Dhole, V. V.; Solunke, M. B.; Jadhav, K. M.

2018-05-01

Zinc borate glass activated with rare earth oxide (Nd2O3, Sm2O3) of Na2O-Li2O-ZnO-B2O3 quaternary system has been prepared successfully by melt quenching method. The nucleation and growth of RE oxide were controlled temperature range 950-1000° C and rapid cooling at room temperature. The physical, structural and optical properties were characterized by using X-ray diffraction (XRD), SEM, Ultraviolet-visible spectroscopy (UV-Vis). XRD and SEM studies confirmed the amorphous nature, surface morphology of prepared zinc borate glass. The physical parameters like density, molar volume, molar mass of Nd3+, Sm3+ doped borate glass are summarized in the present article. The optical absorption spectra along with tauc's plot are presented. The optical energy band gap increases due to the addition of rare earth oxide confirming the role of network modifier.

A robust Multi-Band Water Index (MBWI) for automated extraction of surface water from Landsat 8 OLI imagery

NASA Astrophysics Data System (ADS)

Wang, Xiaobiao; Xie, Shunping; Zhang, Xueliang; Chen, Cheng; Guo, Hao; Du, Jinkang; Duan, Zheng

2018-06-01

Surface water is vital resources for terrestrial life, while the rapid development of urbanization results in diverse changes in sizes, amounts, and quality of surface water. To accurately extract surface water from remote sensing imagery is very important for water environment conservations and water resource management. In this study, a new Multi-Band Water Index (MBWI) for Landsat 8 Operational Land Imager (OLI) images is proposed by maximizing the spectral difference between water and non-water surfaces using pure pixels. Based on the MBWI map, the K-means cluster method is applied to automatically extract surface water. The performance of MBWI is validated and compared with six widely used water indices in 29 sites of China. Results show that our proposed MBWI performs best with the highest accuracy in 26 out of the 29 test sites. Compared with other water indices, the MBWI results in lower mean water total errors by a range of 9.31%-25.99%, and higher mean overall accuracies and kappa coefficients by 0.87%-3.73% and 0.06-0.18, respectively. It is also demonstrated for MBWI in terms of robustly discriminating surface water from confused backgrounds that are usually sources of surface water extraction errors, e.g., mountainous shadows and dark built-up areas. In addition, the new index is validated to be able to mitigate the seasonal and daily influences resulting from the variations of the solar condition. MBWI holds the potential to be a useful surface water extraction technology for water resource studies and applications.

Estimating soil organic and aboveground woody carbon stock in a protected dry Miombo ecosystem, Zimbabwe: Landsat 8 OLI data applications

NASA Astrophysics Data System (ADS)

Dube, Timothy; Muchena, Richard; Masocha, Mhosisi; Shoko, Cletah

2018-06-01

Accurate and reliable soil organic carbon stock estimation is critical in understanding forest role to regional carbon cycles. So far, the total carbon pool in dry Miombo ecosystems is often under-estimated. In that regard this study sought to model the relationship between the aboveground woody carbon pool and the soil carbon pool, using both ground-based and remote sensing methods. To achieve this objective, the Ratio Vegetation Index (RVI), Normalized Difference Vegetation Index (NDVI), and the Soil Adjusted Vegetation Index (SAVI) computed from the newly launched Landsat 8 OLI satellite data were used. Correlation and regression analysis were used to relate Soil Organic Carbon (S.O.C), aboveground woody carbon and remotely sensed vegetation indices. Results showed a soil organic carbon in the upper soil layer (0-15 cm) was positively correlated with aboveground woody carbon and this relationship was significant (r = 0.678; P < 0.05) aboveground carbon. However, there were no significant correlations (r = -0.11, P > 0.05) between SOC in the deeper soil layer (15-30 cm) and aboveground woody carbon. These findings imply that (relationship between aboveground woody carbon and S.O.C) aboveground woody carbon stocks can be used as a proxy to estimate S.O.C in the top soil layer (0-15 cm) in dry Miombo ecosystems. Overall, these findings underscore the potential and significance of remote sensing data in understanding savanna ecosystems contribution to the global carbon cycle.

Fluctuating snow line altitudes in the Hunza basin (Karakoram) using Landsat OLI imagery

NASA Astrophysics Data System (ADS)

Racoviteanu, Adina; Rittger, Karl; Brodzik, Mary J.; Painter, Thomas H.; Armstrong, Richard

2016-04-01

Snowline altitudes (SLAs) on glacier surfaces are needed for separating snow and ice as input for melt models. When measured at the end of the ablation season, SLAs are used for inferring stable-state glacier equilibrium line altitudes (ELAs). Direct measurements of snowlines are rarely possible particularly in remote, high altitude glacierized terrain, but remote sensing data can be used to separate these snow and ice surfaces. Snow lines are commonly visible on optical satellite images acquired at the end of the ablation season if the images are contrasted enough, and are manually digitized on screen using various satellite band combinations for visual interpretation, which is a time-consuming, subjective process. Here we use Landsat OLI imagery at 30 m resolution to estimate glacier SLAs for a subset of the Hunza basin in the Upper Indus in the Karakoram. Clean glacier ice surfaces are delineated using a standardized semi-automated band ratio algorithm with image segmentation. Within the glacier surface, snow and ice are separated using supervised classification schemes based on regions of interest, and glacier SLAs are extracted on the basis of these areas. SLAs are compared with estimates from a new automated method that relies on fractional snow covered area rather than on band ratio algorithms for delineating clean glacier ice surfaces, and on grain size (instead of supervised classification) for separating snow from glacier ice on the glacier surface. The two methods produce comparable snow/ice outputs. The fSCA-derived glacierized areas are slightly larger than the band ratio estimates. Some of the additional area is the result of better detection in shadows from spectral mixture analysis (true positive) while the rest is shallow water, which is spectrally similar to snow/ice (false positive). On the glacier surface, a thresholding the snow grain size image (grain size > 500μm) results in similar glacier ice areas derived from the supervised

Early spring post-fire snow albedo dynamics in high latitude boreal forests using Landsat-8 OLI data

PubMed Central

Wang, Zhuosen; Erb, Angela M.; Schaaf, Crystal B.; Sun, Qingsong; Liu, Yan; Yang, Yun; Shuai, Yanmin; Casey, Kimberly A.; Román, Miguel O.

2018-01-01

Taking advantage of the improved radiometric resolution of Landsat-8 OLI which, unlike previous Landsat sensors, does not saturate over snow, the progress of fire recovery progress at the landscape scale (< 100m) is examined. High quality Landsat-8 albedo retrievals can now capture the true reflective and layered character of snow cover over a full range of land surface conditions and vegetation densities. This new capability particularly improves the assessment of post-fire vegetation dynamics across low- to high- burn severity gradients in Arctic and boreal regions in the early spring, when the albedos during recovery show the greatest variation. We use 30 m resolution Landsat-8 surface reflectances with concurrent coarser resolution (500m) MODIS high quality full inversion surface Bidirectional Reflectance Distribution Functions (BRDF) products to produce higher resolution values of surface albedo. The high resolution full expression shortwave blue sky albedo product performs well with an overall RMSE of 0.0267 between tower and satellite measures under both snow-free and snow-covered conditions. While the importance of post-fire albedo recovery can be discerned from the MODIS albedo product at regional and global scales, our study addresses the particular importance of early spring post-fire albedo recovery at the landscape scale by considering the significant spatial heterogeneity of burn severity, and the impact of snow on the early spring albedo of various vegetation recovery types. We found that variations in early spring albedo within a single MODIS gridded pixel can be larger than 0.6. Since the frequency and severity of wildfires in Arctic and boreal systems is expected to increase in the coming decades, the dynamics of albedo in response to these rapid surface changes will increasingly impact the energy balance and contribute to other climate processes and physical feedback mechanisms. Surface radiation products derived from Landsat-8 data will thus

Early Spring Post-Fire Snow Albedo Dynamics in High Latitude Boreal Forests Using Landsat-8 OLI Data

NASA Technical Reports Server (NTRS)

Wang, Zhuosen; Erb, Angela M.; Schaaf, Crystal B.; Sun, Qingsong; Liu, Yan; Yang, Yun; Shuai, Yanmin; Casey, Kimberly A.; Roman, Miguel O.

2016-01-01

Taking advantage of the improved radiometric resolution of Landsat-8 OLI which, unlike previous Landsat sensors, does not saturate over snow, the progress of fire recovery progress at the landscape scale (less than 100 m) is examined. High quality Landsat-8 albedo retrievals can now capture the true reflective and layered character of snow cover over a full range of land surface conditions and vegetation densities. This new capability particularly improves the assessment of post-fire vegetation dynamics across low- to high-burn severity gradients in Arctic and boreal regions in the early spring, when the albedos during recovery show the greatest variation. We use 30 m resolution Landsat-8 surface reflectances with concurrent coarser resolution (500 m) MODIS high quality full inversion surface Bidirectional Reflectance Distribution Functions (BRDF) products to produce higher resolution values of surface albedo. The high resolution full expression shortwave blue sky albedo product performs well with an overall RMSE of 0.0267 between tower and satellite measures under both snow-free and snow-covered conditions. While the importance of post-fire albedo recovery can be discerned from the MODIS albedo product at regional and global scales, our study addresses the particular importance of early spring post-fire albedo recovery at the landscape scale by considering the significant spatial heterogeneity of burn severity, and the impact of snow on the early spring albedo of various vegetation recovery types. We found that variations in early spring albedo within a single MODIS gridded pixel can be larger than 0.6. Since the frequency and severity of wildfires in Arctic and boreal systems is expected to increase in the coming decades, the dynamics of albedo in response to these rapid surface changes will increasingly impact the energy balance and contribute to other climate processes and physical feedback mechanisms. Surface radiation products derived from Landsat-8 data will

Early spring post-fire snow albedo dynamics in high latitude boreal forests using Landsat-8 OLI data.

PubMed

Wang, Zhuosen; Erb, Angela M; Schaaf, Crystal B; Sun, Qingsong; Liu, Yan; Yang, Yun; Shuai, Yanmin; Casey, Kimberly A; Román, Miguel O

2016-11-01

Taking advantage of the improved radiometric resolution of Landsat-8 OLI which, unlike previous Landsat sensors, does not saturate over snow, the progress of fire recovery progress at the landscape scale (< 100m) is examined. High quality Landsat-8 albedo retrievals can now capture the true reflective and layered character of snow cover over a full range of land surface conditions and vegetation densities. This new capability particularly improves the assessment of post-fire vegetation dynamics across low- to high- burn severity gradients in Arctic and boreal regions in the early spring, when the albedos during recovery show the greatest variation. We use 30 m resolution Landsat-8 surface reflectances with concurrent coarser resolution (500m) MODIS high quality full inversion surface Bidirectional Reflectance Distribution Functions (BRDF) products to produce higher resolution values of surface albedo. The high resolution full expression shortwave blue sky albedo product performs well with an overall RMSE of 0.0267 between tower and satellite measures under both snow-free and snow-covered conditions. While the importance of post-fire albedo recovery can be discerned from the MODIS albedo product at regional and global scales, our study addresses the particular importance of early spring post-fire albedo recovery at the landscape scale by considering the significant spatial heterogeneity of burn severity, and the impact of snow on the early spring albedo of various vegetation recovery types. We found that variations in early spring albedo within a single MODIS gridded pixel can be larger than 0.6. Since the frequency and severity of wildfires in Arctic and boreal systems is expected to increase in the coming decades, the dynamics of albedo in response to these rapid surface changes will increasingly impact the energy balance and contribute to other climate processes and physical feedback mechanisms. Surface radiation products derived from Landsat-8 data will thus

Ability of LANDSAT-8 Oli Derived Texture Metrics in Estimating Aboveground Carbon Stocks of Coppice Oak Forests

NASA Astrophysics Data System (ADS)

Safari, A.; Sohrabi, H.

2016-06-01

The role of forests as a reservoir for carbon has prompted the need for timely and reliable estimation of aboveground carbon stocks. Since measurement of aboveground carbon stocks of forests is a destructive, costly and time-consuming activity, aerial and satellite remote sensing techniques have gained many attentions in this field. Despite the fact that using aerial data for predicting aboveground carbon stocks has been proved as a highly accurate method, there are challenges related to high acquisition costs, small area coverage, and limited availability of these data. These challenges are more critical for non-commercial forests located in low-income countries. Landsat program provides repetitive acquisition of high-resolution multispectral data, which are freely available. The aim of this study was to assess the potential of multispectral Landsat 8 Operational Land Imager (OLI) derived texture metrics in quantifying aboveground carbon stocks of coppice Oak forests in Zagros Mountains, Iran. We used four different window sizes (3×3, 5×5, 7×7, and 9×9), and four different offsets ([0,1], [1,1], [1,0], and [1,-1]) to derive nine texture metrics (angular second moment, contrast, correlation, dissimilar, entropy, homogeneity, inverse difference, mean, and variance) from four bands (blue, green, red, and infrared). Totally, 124 sample plots in two different forests were measured and carbon was calculated using species-specific allometric models. Stepwise regression analysis was applied to estimate biomass from derived metrics. Results showed that, in general, larger size of window for deriving texture metrics resulted models with better fitting parameters. In addition, the correlation of the spectral bands for deriving texture metrics in regression models was ranked as b4>b3>b2>b5. The best offset was [1,-1]. Amongst the different metrics, mean and entropy were entered in most of the regression models. Overall, different models based on derived texture metrics

Waterbodies Extraction from LANDSAT8-OLI Imagery Using Awater Indexs-Guied Stochastic Fully-Connected Conditional Random Field Model and the Support Vector Machine

NASA Astrophysics Data System (ADS)

Wang, X.; Xu, L.

2018-04-01

One of the most important applications of remote sensing classification is water extraction. The water index (WI) based on Landsat images is one of the most common ways to distinguish water bodies from other land surface features. But conventional WI methods take into account spectral information only form a limited number of bands, and therefore the accuracy of those WI methods may be constrained in some areas which are covered with snow/ice, clouds, etc. An accurate and robust water extraction method is the key to the study at present. The support vector machine (SVM) using all bands spectral information can reduce for these classification error to some extent. Nevertheless, SVM which barely considers spatial information is relatively sensitive to noise in local regions. Conditional random field (CRF) which considers both spatial information and spectral information has proven to be able to compensate for these limitations. Hence, in this paper, we develop a systematic water extraction method by taking advantage of the complementarity between the SVM and a water index-guided stochastic fully-connected conditional random field (SVM-WIGSFCRF) to address the above issues. In addition, we comprehensively evaluate the reliability and accuracy of the proposed method using Landsat-8 operational land imager (OLI) images of one test site. We assess the method's performance by calculating the following accuracy metrics: Omission Errors (OE) and Commission Errors (CE); Kappa coefficient (KP) and Total Error (TE). Experimental results show that the new method can improve target detection accuracy under complex and changeable environments.

Analysis of Relationship Between Urban Heat Island Effect and Land Use/cover Type Using Landsat 7 ETM+ and Landsat 8 Oli Images

NASA Astrophysics Data System (ADS)

Aslan, N.; Koc-San, D.

2016-06-01

The main objectives of this study are (i) to calculate Land Surface Temperature (LST) from Landsat imageries, (ii) to determine the UHI effects from Landsat 7 ETM+ (June 5, 2001) and Landsat 8 OLI (June 17, 2014) imageries, (iii) to examine the relationship between LST and different Land Use/Land Cover (LU/LC) types for the years 2001 and 2014. The study is implemented in the central districts of Antalya. Initially, the brightness temperatures are retrieved and the LST values are calculated from Landsat thermal images. Then, the LU/LC maps are created from Landsat pan-sharpened images using Random Forest (RF) classifier. Normalized Difference Vegetation Index (NDVI) image, ASTER Global Digital Elevation Model (GDEM) and DMSP_OLS nighttime lights data are used as auxiliary data during the classification procedure. Finally, UHI effect is determined and the LST values are compared with LU/LC classes. The overall accuracies of RF classification results were computed higher than 88 % for both Landsat images. During 13-year time interval, it was observed that the urban and industrial areas were increased significantly. Maximum LST values were detected for dry agriculture, urban, and bareland classes, while minimum LST values were detected for vegetation and irrigated agriculture classes. The UHI effect was computed as 5.6 °C for 2001 and 6.8 °C for 2014. The validity of the study results were assessed using MODIS/Terra LST and Emissivity data and it was found that there are high correlation between Landsat LST and MODIS LST data (r2 = 0.7 and r2 = 0.9 for 2001 and 2014, respectively).

The Landsat Data Continuity Mission Operational Land Imager: Radiometric Performance

NASA Technical Reports Server (NTRS)

Markham, Brian; Dabney, Philip; Pedelty, Jeffrey

2011-01-01

The Operational Land Imager (OLI) is one of two instruments to fly on the Landsat Data Continuity Mission (LDCM), which is scheduled to launch in December 2012 to become the 8th in the series of Landsat satellites. The OLI images in the solar reflective part of the spectrum, with bands similar to bands 1-5, 7 and the panchromatic band on the Landsat-7 ETM+ instrument. In addition, it has a 20 nm bandpass spectral band at 443 nm for coastal and aerosol studies and a 30 nm band at 1375 nm to aid in cirrus cloud detection. Like ETM+, spatial resolution is 30 m in the all but the panchromatic band, which is 15 meters. OLI is a pushbroom radiometer with approximately 6000 detectors per 30 meter band as opposed to the 16 detectors per band on the whiskbroom ETM+. Data are quantized to 12 bits on OLI as opposed to 8 bits on ETM+ to take advantage of the improved signal to noise ratio provided by the pushbroom design. The saturation radiances are higher on OLI than ETM+ to effectively eliminate saturation issues over bright Earth targets. OLI includes dual solar diffusers for on-orbit absolute and relative (detector to detector) radiometric calibration. Additionally, OLI has 3 sets of on-board lamps that illuminate the OLI focal plane through the full optical system, providing additional checks on the OLI's response[l]. OLI has been designed and built by Ball Aerospace & Technology Corp. (BATC) and is currently undergoing testing and calibration in preparation for delivery in Spring 2011. Final pre-launch performance results should be available in time for presentation at the conference. Preliminary results will be presented below. These results are based on the performance of the Engineering Development Unit (EDU) that was radiometrically tested at the integrated instrument level in 2010 and assembly level measurements made on the flight unit. Signal-to-Noise (SNR) performance: One of the advantages of a pushbroom system is the increased dwell time of the detectors

Automatic Sub-Pixel Co-Registration of LandSat-8 OLI and Sentinel-2A MSI Images Using Phase Correlation and Machine Learning Based Mapping

NASA Technical Reports Server (NTRS)

Skakun, Sergii; Roger, Jean-Claude; Vermote, Eric F.; Masek, Jeffrey G.; Justice, Christopher O.

2017-01-01

This study investigates misregistration issues between Landsat-8/OLI and Sentinel-2A/MSI at 30 m resolution, and between multi-temporal Sentinel-2A images at 10 m resolution using a phase correlation approach and multiple transformation functions. Co-registration of 45 Landsat-8 to Sentinel-2A pairs and 37 Sentinel-2A to Sentinel-2A pairs were analyzed. Phase correlation proved to be a robust approach that allowed us to identify hundreds and thousands of control points on images acquired more than 100 days apart. Overall, misregistration of up to 1.6 pixels at 30 m resolution between Landsat-8 and Sentinel-2A images, and 1.2 pixels and 2.8 pixels at 10 m resolution between multi-temporal Sentinel-2A images from the same and different orbits, respectively, were observed. The non-linear Random Forest regression used for constructing the mapping function showed best results in terms of root mean square error (RMSE), yielding an average RMSE error of 0.07+/-0.02 pixels at 30 m resolution, and 0.09+/-0.05 and 0.15+/-0.06 pixels at 10 m resolution for the same and adjacent Sentinel-2A orbits, respectively, for multiple tiles and multiple conditions. A simpler 1st order polynomial function (affine transformation) yielded RMSE of 0.08+/-0.02 pixels at 30 m resolution and 0.12+/-0.06 (same Sentinel-2A orbits) and 0.20+/-0.09 (adjacent orbits) pixels at 10 m resolution.

Object-based Forest Fire Analysis for Pedrógão Grande Fire Using Landsat 8 OLI and Sentinel-2A Imagery

NASA Astrophysics Data System (ADS)

Tonbul, H.; Kavzoglu, T.

2017-12-01

Forest fires are among the most important natural disasters with the damage to the natural habitat and human-life. Mapping damaged forest fires is crucial for assessing ecological effects caused by fire, monitoring land cover changes and modeling atmospheric and climatic effects of fire. In this context, satellite data provides a great advantage to users by providing a rapid process of detecting burning areas and determining the severity of fire damage. Especially, Mediterranean ecosystems countries sets the suitable conditions for the forest fires. In this study, the determination of burnt areas of forest fire in Pedrógão Grande region of Portugal occurred in June 2017 was carried out using Landsat 8 OLI and Sentinel-2A satellite images. The Pedrógão Grande fire was one of the largest fires in Portugal, more than 60 people was killed and thousands of hectares were ravaged. In this study, four pairs of pre-fire and post-fire top of atmosphere (TOA) and atmospherically corrected images were utilized. The red and near infrared (NIR) spectral bands of pre-fire and post-fire images were stacked and multiresolution segmentation algorithm was applied. In the segmentation processes, the image objects were generated with estimated optimum homogeneity criteria. Using eCognition software, rule sets have been created to distinguish unburned areas from burned areas. In constructing the rule sets, NDVI threshold values were determined pre- and post-fire and areas where vegetation loss was detected using the NDVI difference image. The results showed that both satellite images yielded successful results for burned area discrimination with a very high degree of consistency in terms of spatial overlap and total burned area (over 93%). Object based image analysis (OBIA) was found highly effective in delineation of burnt areas.

Antisense Oligodeoxynucleotide Inhibition of HIV Gene Expression

DTIC Science & Technology

1989-03-20

synthesis using trimethoxybenzyl side chain protection for Gln, the highly efficient benzotriazolyloxy tris(dimethylamino) phosphonium hexafluorophosphate ...0 - P - 0 -0 - O - - OH + Li OLi OLi OLi R 0 Fig. 11. Fai.t atom bombardment ma.ss spectroscopy of the lithium salt of 5’-trityl-CUAA, sputtered from

Optical properties of nanocrystalline potassium lithium niobate in the glass system (100-x) TeO2-x(1.5K2O-Li2O-2.5Nb2O5).

PubMed

Ahamad, M Niyaz; Varma, K B R

2009-08-01

Optically clear glasses of various compositions in the system (100-x) TeO2-x(1.5K2O-Li2O-2.5Nb2O5) (2 < or = x < or = 12, in molar ratio) were prepared by the melt-quenching technique. The glassy nature of the as-quenched samples was established via differential scanning calorimetry (DSC). The amorphous and the crystalline nature of the as-quenched and heat-treated samples were confirmed by the X-ray powder diffraction and transmission electron microscopic (TEM) studies. Transparent glasses comprising potassium lithium niobate (K3Li2Nb5O15) microcrystallites on the surface and nanocrystallites within the glass were obtained by controlled heat-treatment of the as-quenched glasses just above the glass transition temperature (T(g)). The optical transmission spectra of these glasses and glass-crystal composites of various compositions were recorded in the 200-2500 nm wavelength range. Various optical parameters such as optical band gap, Urbach energy, refractive index were determined. Second order optical non-linearity was established in the heat-treated samples by employing the Maker-Fringe method.

OLIGOCELLULA1/HIGH EXPRESSION OF OSMOTICALLY RESPONSIVE GENES15 Promotes Cell Proliferation With HISTONE DEACETYLASE9 and POWERDRESS During Leaf Development in Arabidopsis thaliana

PubMed Central

Suzuki, Marina; Shinozuka, Nanae; Hirakata, Tomohiro; Nakata, Miyuki T.; Demura, Taku; Tsukaya, Hirokazu; Horiguchi, Gorou

2018-01-01

Organ size regulation is dependent on the precise spatial and temporal regulation of cell proliferation and cell expansion. A number of transcription factors have been identified that play a key role in the determination of aerial lateral organ size, but their functional relationship to various chromatin modifiers has not been well understood. To understand how leaf size is regulated, we previously isolated the oligocellula1 (oli1) mutant of Arabidopsis thaliana that develops smaller first leaves than the wild type (WT) mainly due to a reduction in the cell number. In this study, we further characterized oli1 leaf phenotypes and identified the OLI1 gene as well as interaction partners of OLI1. Detailed characterizations of leaf development suggested that the cell proliferation rate in oli1 leaf primordia is lower than that in the WT. In addition, oli1 was associated with a slight delay of the progression from the juvenile to adult phases of leaf traits. A classical map-based approach demonstrated that OLI1 is identical to HIGH EXPRESSION OF OSMOTICALLY RESPONSIVE GENES15 (HOS15). HOS15/OLI1 encodes a homolog of human transducin β-like protein1 (TBL1). TBL1 forms a transcriptional repression complex with the histone deacetylase (HDAC) HDAC3 and either nuclear receptor co-repressor (N-CoR) or silencing mediator for retinoic acid and thyroid receptor (SMRT). We found that mutations in HISTONE DEACETYLASE9 (HDA9) and a switching-defective protein 3, adaptor 2, N-CoR, and transcription factor IIIB-domain protein gene, POWERDRESS (PWR), showed a small-leaf phenotype similar to oli1. In addition, hda9 and pwr did not further enhance the oli1 small-leaf phenotype, suggesting that these three genes act in the same pathway. Yeast two-hybrid assays suggested physical interactions, wherein PWR probably bridges HOS15/OLI1 and HDA9. Earlier studies suggested the roles of HOS15, HDA9, and PWR in transcriptional repression. Consistently, transcriptome analyses showed several

Snow fraction products evaluation with Landsat-8/OLI data and its spatial scale effects over the Tibetan Plateau

NASA Astrophysics Data System (ADS)

Jiang, L.

2016-12-01

Snow cover is one of important elements in the water supply of large populations, especially in those downstream from mountainous watershed. The cryosphere process in the Tibetan Plateau is paid much attention due to rapid change of snow amount and cover extent. Snow mapping from MODIS has been increased attention in the study of climate change and hydrology. But the lack of intensive validation of different snow mapping methods especially at Tibetan Plateau hinders its application. In this work, we examined three MODIS snow products, including standard MODIS fractional snow product (MOD10A1) (Kaufman et al., 2002; Salomonson & Appel, 2004, 2006), two other fractional snow product, MODSCAG (Painter et al., 2009) and MOD_MESMA (Shi, 2012). Both these two methods are based on spectral mixture analysis. The difference between MODISCAG and MOD_MESMA was the endmember selection. For MODSCAG product, snow spectral endmembers of varying grain size was obtained both from a radiative transfer model and spectra of vegetation, rock and soil collected in the field and laboratory. MOD_MESMA was obtained from automated endmember extraction method using linear spectral mixture analysis. Its endmembers are selected in each image to enhance the computational efficiency of MESMA (Multiple Endmember Spectral Analysis). Landsat-8 Operatinal Land Imager (OLI) data from 2013-2015 was used to evaluate the performance of these three snow fraction products in Tibetan Plateau. The effect of land cover types including forest, grass and bare soil was analyzed to evaluate three products. In addition, the effects of relatively flat surface in internal plateau and high mountain areas of Himalaya were also evaluated on the impact of these snow fraction products. From our comparison, MODSCAG and MOD10A1 overestimated snow cover, while MOD_MESMA underestimated snow cover. And RMSE of MOD_MESMA at each land cover type including forest, grass and mountain area decreased with the spatial resolution

The Landsat Data Continuity Mission Operational Land Imager: Pre-Launch Performance

NASA Technical Reports Server (NTRS)

Markham, Brian L.; Knight, Edward J.; Canova, Brent; Donley, Eric; Kvaran, Geir; Lee, Kenton

2011-01-01

The Operational Land Imager(OLI) will be the main instrument on Landsat-8 when it launches in 2012. OLI represents a generational change from heritage Landsat instruments in its design but must maintain data continuity with the 30+ year Landsat data archive. As a result, OLI has undergone a stringent calibration and characterization campaign to ensure its characteristics are understood and consistent with past instruments. This paper presents an overview of the OLI design, its major differences from previous Landsat instruments, and a summary of its expected performance.

Evaluating Radiometric Sensitivity of LandSat 8 Over Coastal-Inland Waters

NASA Technical Reports Server (NTRS)

Pahlevan, Nima; Wei, Jian-Wei; Shaaf, Crystal B.; Schott, John R.

2014-01-01

The operational Land Imager (OLI) aboard Landsat 8 was launched in February 2013 to continue the Landsat's mission of monitoring earth resources at relatively high spatial resolution. Compared to Landsat heritage sensors, OLI has an additional 443-nm band (termed coastal/aerosol (CA) band), which extends its potential for mapping/monitoring water quality in coastal/inland waters. In addition, OLI's pushbroom design allows for longer integration time and, as a result, higher signal-to-noise ratio (SNR). Using a series of radiative transfer simulations, we provide insights into the radiometric sensitivity of OLI when studying coastal/inland waters. This will address how the changes in water constituents manifest at top-of-atmosphere (TOA) and whether the changes are resolvable at TOA (focal plane) relative to OLI's overall noise.

Landsat 9: Status and Plans

NASA Technical Reports Server (NTRS)

Markham, Brian L.; Jenstrom, Del; Masek, Jeffrey G.; Dabney, Phil; Pedelty, Jeffrey A.; Barsi, Julia A.; Montanaro, Matthew

2016-01-01

The Landsat 9 mission, currently under development and proceeding towards a targeted launch in late 2020, will be very similar to the Landsat 8 mission, launched in 2013. Like Landsat 8, Landsat 9 is a joint effort between NASA and USGS with two sensors, the Operational Land Imager 2 (OLI-2), essentially a copy of the OLI on Landsat 8 and the Thermal Infrared Sensor 2 (TIRS-2), very similar to the TIRS on Landsat 8. The OLI-2, like OLI, provides 14-bit image data, though for Landsat 9, all 14 bits will be retained and transmitted to the ground. The focal plane modules to be used for OLI-2 were flight spares for OLI and are currently being retested by Ball Aerospace. Results indicate radiometric performance comparable to OLI. The TIRS was a class C instrument, with a 3-year design lifetime, and therefore had limited redundancy. TIRS-2 will be a class B instrument, with a 5-year design lifetime, like OLI (and OLI-2), necessitating design changes to increase redundancy. The stray light and Scene Select Mechanism (SSM) encoder problems observed on orbit with TIRS have also instigated a few design changes to TIRS-2. Stray light analysis and testing have indicated that additional baffles in the TIRS-2 optical system will suppress the out-of-field response. The SSM encoder problems have not been definitively traced to a route cause, though conductive anodic filament growth in the circuit boards is suspected. Improved designs for the encoder are being considered for TIRS-2. The spare Focal Plane Array (FPA) from TIRS is planned for use in TIRS-2; FPA spectral and radiometric performance testing is scheduled for September of this year at NASA's Goddard Space Flight Center.

Process optimization for the preparation of oligomycin-loaded folate-conjugated chitosan nanoparticles as a tumor-targeted drug delivery system using a two-level factorial design method.

PubMed

Zu, Yuangang; Zhao, Qi; Zhao, Xiuhua; Zu, Shuchong; Meng, Li

2011-01-01

Oligomycin-A (Oli-A), an anticancer drug, was loaded to the folate (FA)-conjugated chitosan as a tumor-targeted drug delivery system for the purpose of overcoming the nonspecific targeting characteristics and the hydrophobicity of the compound. The two-level factorial design (2-LFD) was applied to modeling the preparation process, which was composed of five independent variables, namely FA-conjugated chitosan (FA-CS) concentration, Oli-A concentration, sodium tripolyphosphate (TPP) concentration, the mass ratio of FA-CS to TPP, and crosslinking time. The mean particle size (MPS) and the drug loading rate (DLR) of the resulting Oli-loaded FA-CS nanoparticles (FA-Oli-CSNPs) were used as response variables. The interactive effects of the five independent variables on the response variables were studied. The characteristics of the nanoparticles, such as amount of FA conjugation, drug entrapment rate (DER), DLR, surface morphology, and release kinetics properties in vitro were investigated. The FA-Oli-CSNPs with MPS of 182.6 nm, DER of 17.3%, DLR of 58.5%, and zeta potential (ZP) of 24.6 mV were obtained under optimum conditions. The amount of FA conjugation was 45.9 mg/g chitosan. The FA-Oli-CSNPs showed sustained-release characteristics for 576 hours in vitro. The results indicated that FA-Oli-CSNPs obtained as a targeted drug delivery system could be effective in the therapy of leukemia in the future.

Landsat 8 thermal infrared sensor geometric characterization and calibration

USGS Publications Warehouse

Storey, James C.; Choate, Michael J.; Moe, Donald

2014-01-01

The Landsat 8 spacecraft was launched on 11 February 2013 carrying two imaging payloads: the Operational Land Imager (OLI) and the Thermal Infrared Sensor (TIRS). The TIRS instrument employs a refractive telescope design that is opaque to visible wavelengths making prelaunch geometric characterization challenging. TIRS geometric calibration thus relied heavily on on-orbit measurements. Since the two Landsat 8 payloads are complementary and generate combined Level 1 data products, the TIRS geometric performance requirements emphasize the co-alignment of the OLI and TIRS instrument fields of view and the registration of the OLI reflective bands to the TIRS long-wave infrared emissive bands. The TIRS on-orbit calibration procedures include measuring the TIRS-to-OLI alignment, refining the alignment of the three TIRS sensor chips, and ensuring the alignment of the two TIRS spectral bands. The two key TIRS performance metrics are the OLI reflective to TIRS emissive band registration accuracy, and the registration accuracy between the TIRS thermal bands. The on-orbit calibration campaign conducted during the commissioning period provided an accurate TIRS geometric model that enabled TIRS Level 1 data to meet all geometric accuracy requirements. Seasonal variations in TIRS-to-OLI alignment have led to several small calibration parameter adjustments since commissioning.

From Landsat through SLI: Ball Aerospace Instrument Architecture for Earth Surface Monitoring

NASA Astrophysics Data System (ADS)

Wamsley, P. R.; Gilmore, A. S.; Malone, K. J.; Kampe, T. U.; Good, W. S.

2017-12-01

The Landsat legacy spans more than forty years of moderate resolution, multi-spectral imaging of the Earth's surface. Applications for Landsat data include global environmental change, disaster planning and recovery, crop and natural resource management, and glaciology. In recent years, coastal water science has been greatly enhanced by the outstanding on-orbit performance of Landsat 8. Ball Aerospace designed and built the Operational Land Imager (OLI) instrument on Landsat 8, and is in the process of building OLI 2 for Landsat 9. Both of these instruments have the same design however improved performance is expected from OLI 2 due to greater image bit depth (14 bit on OLI 2 vs 12 bit on OLI). Ball Aerospace is currently working on two novel instrument architectures applicable to Sustainable Land Imaging for Landsat 10 and beyond. With increased budget constraints probable for future missions, technological improvements must be included in future instrument architectures to enable increased capabilities at lower cost. Ball presents the instrument architectures and associated capabilities enabling new science in past, current, and future Landsat missions.

Landsat-8 Operational Land Imager On-Orbit Radiometric Calibration

NASA Technical Reports Server (NTRS)

Markham, Brian L.; Barsi, Julia A.

2017-01-01

The Operational Land Imager (OLI), the VIS/NIR/SWIR sensor on the Landsat-8 has been successfully acquiring Earth Imagery for more than four years. The OLI incorporates two on-board radiometric calibration systems, one diffuser based and one lamp based, each with multiple sources. For each system one source is treated as primary and used frequently and the other source(s) are used less frequently to assist in tracking any degradation in the primary sources. In addition, via a spacecraft maneuver, the OLI instrument views the moon once a lunar cycle (approx. 29 days). The integrated lunar irradiances from these acquisitions are compared to the output of a lunar irradiance model. The results from all these techniques, combined with cross calibrations with other sensors and ground based vicarious measurements are used to monitor the OLI's stability and correct for any changes observed. To date, the various techniques have other detected significant changes in the shortest wavelength OLI band centered at 443 nm and these are currently being adjusted in the operational processing.

Landsat 8 Remote Sensing Reflectance (Rrs) Products: Evaluations, Intercomparisons, and Enhancements

NASA Technical Reports Server (NTRS)

Pahlevan, Nima; Schott, John R.; Franz, Bryan A.; Zibordi, Giuseppe; Markham, Brian; Bailey, Sean; Schaaf, Crystal B.; Ondrusek, Michael; Greb, Steven; Strait, Christopher M.

2017-01-01

The Operational Land Imager (OLI) onboard Landsat-8 is generating high-quality aquatic science products, the most critical of which is the remote sensing reflectance (Rrs), defined as the ratio of water-leaving radiance to the total downwelling irradiance just above water. The quality of the Rrs products has not, however, been extensively assessed. This manuscript provides a comprehensive evaluation of Level-1B, i.e., top of atmosphere reflectance, and Rrs products available from OLI imagery under near-ideal atmospheric conditions in moderately turbid waters. The procedure includes a) evaluations of the Rrs products at sites included in the Ocean Color component of the Aerosol Robotic Network (AERONET-OC), b) intercomparisons and cross-calibrations against other ocean color products, and c) optimizations of vicarious calibration gains across the entire OLI observing swath. Results indicate that the near-infrared and shortwave infrared (NIR-SWIR) band combinations yield the most robust and stable Rrs retrievals in moderately turbid waters. Intercomparisons against products derived from the Visible Infrared Imaging Radiometer Suite (VIIRS) and the Moderate Resolution Imaging Spectroradiometer onboard the Aqua platform (MODISA) indicate slight across-track non-uniformities (<1%) associated with OLI scenes in the blue bands. In both product domains (TOA and Rrs), on average, the OLI products were found larger in radiometric responses in the blue channels. Following the implementation of updated vicarious calibration gains and accounting for across-track non-uniformities, matchup analyses using independent in-situ validation data confirmed improvements in Rrs products. These findings further support high-fidelity OLI-derived aquatic science products in terms of both demonstrating a robust atmospheric correction method and providing consistent products across OLI's imaging swath.

Li2O (LiOLi)

NASA Astrophysics Data System (ADS)

Guelachvili, G.

This document is part of Subvolume B `Linear Triatomic Molecules', Part 9, of Volume 20 `Molecular Constants mostly from Infrared Spectroscopy' of Landolt-Börnstein Group II `Molecules and Radicals'.

Evaluating the utility of the medium-spatial resolution Landsat 8 multispectral sensor in quantifying aboveground biomass in uMgeni catchment, South Africa

NASA Astrophysics Data System (ADS)

Dube, Timothy; Mutanga, Onisimo

2015-03-01

Aboveground biomass estimation is critical in understanding forest contribution to regional carbon cycles. Despite the successful application of high spatial and spectral resolution sensors in aboveground biomass (AGB) estimation, there are challenges related to high acquisition costs, small area coverage, multicollinearity and limited availability. These challenges hamper the successful regional scale AGB quantification. The aim of this study was to assess the utility of the newly-launched medium-resolution multispectral Landsat 8 Operational Land Imager (OLI) dataset with a large swath width, in quantifying AGB in a forest plantation. We applied different sets of spectral analysis (test I: spectral bands; test II: spectral vegetation indices and test III: spectral bands + spectral vegetation indices) in testing the utility of Landsat 8 OLI using two non-parametric algorithms: stochastic gradient boosting and the random forest ensembles. The results of the study show that the medium-resolution multispectral Landsat 8 OLI dataset provides better AGB estimates for Eucalyptus dunii, Eucalyptus grandis and Pinus taeda especially when using the extracted spectral information together with the derived spectral vegetation indices. We also noted that incorporating the optimal subset of the most important selected medium-resolution multispectral Landsat 8 OLI bands improved AGB accuracies. We compared medium-resolution multispectral Landsat 8 OLI AGB estimates with Landsat 7 ETM + estimates and the latter yielded lower estimation accuracies. Overall, this study demonstrates the invaluable potential and strength of applying the relatively affordable and readily available newly-launched medium-resolution Landsat 8 OLI dataset, with a large swath width (185-km) in precisely estimating AGB. This strength of the Landsat OLI dataset is crucial especially in sub-Saharan Africa where high-resolution remote sensing data availability remains a challenge.

Enriching the hydrogen storage capacity of carbon nanotube doped with polylithiated molecules

NASA Astrophysics Data System (ADS)

Panigrahi, P.; Naqvi, S. R.; Hankel, M.; Ahuja, R.; Hussain, T.

2018-06-01

In a quest to find optimum materials for efficient storage of clean energy, we have performed first principles calculations to study the structural and energy storage properties of one-dimensional carbon nanotubes (CNTs) functionalized with polylithiated molecules (PLMs). Van der Waals corrected calculations disclosed that various PLMs like CLi, CLi2, CLi3, OLi, OLi2, OLi3, bind strongly to CNTs even at high doping concentrations ensuring a uniform distribution of dopants without forming clusters. Bader charge analysis reveals that each Li in all the PLMs attains a partial positive charge and transform into Li+ cations. This situation allows multiple H2 molecules adsorbed with each Li+ through the polarization of incident H2 molecules via electrostatic and van der Waals type of interaction. With a maximum doping concentration, that is 3CLi2/3CLi3 and 3OLi2/3OLi3 a maximum of 36 H2 molecules could be adsorbed that corresponds to a reasonably high H2 storage capacity with the adsorption energies in the range of -0.33 to -0.15 eV/H2. This suits the ambient condition applications.

Assembly of the mitochondrial membrane system: mutations in the pho2 locus of the mitochondrial genome of Saccharomyces cerevisiae.

PubMed

Coruzzi, G; Trembath, M K; Tzagoloff, A

1978-12-01

Two mutants of Saccharomyces cerevisiae which show a loss of mitochondrial rutamycin-sensitive ATPase activity are described. Although phenotypically similar to mutants of the mitochondrial locus pho1 [F. Foury and A. Tzagoloff (1976) Eur. J. Biochem. 68, 113-119], these mutants define a second ATPase locus on the mitochondrial DNA (designated pho2), which is genetically unlinked to pho1. Analysis of recombination in crosses involving multiple antibiotic resistance markers indicates that the locus is in the segment of the genome between ery1 and oli2, very close to oli1. In fact it is proposed that the oli1 and pho2 mutations are in the same gene. Supporting evidence for this proposal includes: 1. The analysis of marker retention in petite mutants shows that the oli1 and pho2 loci were either retained or lost together in all cases. 2. Recombination frequencies of 0.05% or less are observed in crosses between the oli1 and pho2 loci. 3. When rho+ revertants are isolated from the pho2 mutants they frequently are oligomycin resistant. 4. pho2 mutants have an altered subunit 9 of the ATPase complex.

Landsat 8 operational land imager on-orbit geometric calibration and performance

USGS Publications Warehouse

Storey, James C.; Choate, Michael J.; Lee, Kenton

2014-01-01

The Landsat 8 spacecraft was launched on 11 February 2013 carrying the Operational Land Imager (OLI) payload for moderate resolution imaging in the visible, near infrared (NIR), and short-wave infrared (SWIR) spectral bands. During the 90-day commissioning period following launch, several on-orbit geometric calibration activities were performed to refine the prelaunch calibration parameters. The results of these calibration activities were subsequently used to measure geometric performance characteristics in order to verify the OLI geometric requirements. Three types of geometric calibrations were performed including: (1) updating the OLI-to-spacecraft alignment knowledge; (2) refining the alignment of the sub-images from the multiple OLI sensor chips; and (3) refining the alignment of the OLI spectral bands. The aspects of geometric performance that were measured and verified included: (1) geolocation accuracy with terrain correction, but without ground control (L1Gt); (2) Level 1 product accuracy with terrain correction and ground control (L1T); (3) band-to-band registration accuracy; and (4) multi-temporal image-to-image registration accuracy. Using the results of the on-orbit calibration update, all aspects of geometric performance were shown to meet or exceed system requirements.

Development of the Landsat Data Continuity Mission Cloud Cover Assessment Algorithms

USGS Publications Warehouse

Scaramuzza, Pat; Bouchard, M.A.; Dwyer, John L.

2012-01-01

The upcoming launch of the Operational Land Imager (OLI) will start the next era of the Landsat program. However, the Automated Cloud-Cover Assessment (CCA) (ACCA) algorithm used on Landsat 7 requires a thermal band and is thus not suited for OLI. There will be a thermal instrument on the Landsat Data Continuity Mission (LDCM)-the Thermal Infrared Sensor-which may not be available during all OLI collections. This illustrates a need for CCA for LDCM in the absence of thermal data. To research possibilities for full-resolution OLI cloud assessment, a global data set of 207 Landsat 7 scenes with manually generated cloud masks was created. It was used to evaluate the ACCA algorithm, showing that the algorithm correctly classified 79.9% of a standard test subset of 3.95 109 pixels. The data set was also used to develop and validate two successor algorithms for use with OLI data-one derived from an off-the-shelf machine learning package and one based on ACCA but enhanced by a simple neural network. These comprehensive CCA algorithms were shown to correctly classify pixels as cloudy or clear 88.5% and 89.7% of the time, respectively.

Monitoring algal blooms in drinking water reservoirs using the Landsat-8 Operational Land Imager

EPA Science Inventory

In this study, we demonstrated that the Landsat-8 Operational Land Imager (OLI) sensor is a powerful tool that can provide periodic and system-wide information on the condition of drinking water reservoirs. The OLI is a multispectral radiometer (30 m spatial resolution) that allo...

Analysis of seasonal variation in urban heat island effect for West Mediterranean Region of Turkey using Landsat 8 OLI/TIRS data

NASA Astrophysics Data System (ADS)

Aslan, Nagihan; KOC-SAN, Dilek

2016-07-01

Technological developments are accelerating day by day in 21st century which has brought social and economic developments. Besides, the word population is increasing rapidly and the majority of population lives in city center. Large and crowded cities, industrial areas and shopping centers are being built for providing human needs and wishes. For these purposes, natural resources are destroyed and urban climate is affected. The temperatures of urban areas can be warmer than the rural areas and differences in temperature between urban and surrounding rural areas were defined as Urban Heat Island (UHI). The objectives of this study are (i) to calculate Land Surface Temperatures (LST) for urban and vegetation areas in the selected cities, (ii) to determine the UHI effects and its change between seasons, (iii) to examine the relationship between city size and UHI effect magnitude. In this study, Landsat 8 OLI/TIRS imageries for winter (23 December 2013), summer (17 June 2014) and autumn (7 October 2014) seasons were used. The Antalya, Burdur and Isparta provinces that are placed in West Mediterranean Region of Turkey were selected as study areas. These three provinces have different characteristics. Antalya is the fifth biggest city of Turkey and its population growth is quite high. In addition, the summer population of this city increases severely, because of its tourism potential. On the other hand, Isparta and Burdur are relatively small cities when compared to Antalya with respect to population and urban area. In this study, firstly, the brightness temperatures and LST values are calculated from Landsat 8 thermal images. Secondly, urban areas are identified by an approach that combines emissivity image, Defense Meteorological Satellite Program - Operational Linescan System (DMSP/OLS) nighttime lights data and ASTER Global Digital Elevation Model (GDEM). In addition, the vegetation areas are defined by using emissivity image. Finally, the UHI effect is determined

Farm Management in Organic and Conventional Dairy Production Systems Based on Pasture in Southern Brazil and Its Consequences on Production and Milk Quality

PubMed Central

Kuhnen, Shirley; Stibuski, Rudinei Butka; Honorato, Luciana Aparecida; Pinheiro Machado Filho, Luiz Carlos

2015-01-01

Simple Summary This study provides the characteristics of the conventional high input (C-HI), conventional low input (C-LI), and organic low input (O-LI) pasture-based production systems used in Southern Brazil, and its consequences on production and milk quality. C-HI farms had larger farms and herds, annual pasture with higher inputs and milk yield, whereas O-LI had smaller farms and herds, perennial pastures with lowest input and milk yields; C-LI was in between. O-LI farms may contribute to eco-system services, but low milk yield is a major concern. Hygienic and microbiological milk quality was poor for all farms and needs to be improved. Abstract Pasture-based dairy production is used widely on family dairy farms in Southern Brazil. This study investigates conventional high input (C-HI), conventional low input (C-LI), and organic low input (O-LI) pasture-based systems and their effects on quantity and quality of the milk produced. We conducted technical site visits and interviews monthly over one year on 24 family farms (n = 8 per type). C-HI farms had the greatest total area (28.9 ha), greatest percentage of area with annual pasture (38.7%), largest number of lactating animals (26.2) and greatest milk yield per cow (22.8 kg·day−1). O-LI farms had the largest perennial pasture area (52.3%), with the greatest botanical richness during all seasons. Area of perennial pasture was positively correlated with number of species consumed by the animals (R2 = 0.74). Milk from O-LI farms had higher levels of fat and total solids only during the winter. Hygienic and microbiological quality of the milk was poor for all farms and need to be improved. C-HI farms had high milk yield related to high input, C-LI had intermediate characteristics and O-LI utilized a year round perennial pasture as a strategy to diminish the use of supplements in animal diets, which is an important aspect in ensuring production sustainability. PMID:26479369

The mitochondrial COB region in yeast codes for apocytochrome b and is mosaic.

PubMed

Haid, A; Schweyen, R J; Bechmann, H; Kaudewitz, F; Solioz, M; Schatz, G

1979-03-01

Mitochondrial mutants of Saccharomyces cerevisiae defective in cytochrome b were analyzed genetically and biochemically in order to elucidate the role of the mitochondrial genetic system in the biosynthesis of this cytochrome. The mutants mapped between OLI1 and OLI2 on mitochondrial DNA in a region called COB. A fine structure map of the COB region was constructed by rho- deletion mapping and recombination analysis. The combined genetic and biochemical data indicate that the COB region is mosaic and contains at least five distinct clusters of mutants, A-E, with A being closest to OLI2 and E being closest to OLI1. Clusters A, C and E are probably coding regions for apocytochrome b, whereas clusters B and D seem to be involved in as yet unknown functions. These conclusions rest on the following evidence. 1. Most mutants in clusters A, C and E have specifically lost cytochrome b. Many of them accumulate smaller mitochondrial translation products; some of these were identified as fragments of apocytochrome b by proteolytic fingerprinting. The molecular weight of these fragments depends on the map position of the mutant, increasing in the direction OLI2 leads to OLI1. The mutant closest to OLI1 accumulates an apocytochrome b which is slightly larger than that of wild type. 2. A mutant in cluster C exhibits a spectral absorption band of cytochrome b that is shifted 1.5 nm to the red. 3. Mutants in clusters B and D are pleiotropic. A majority of them are conditional and lack the absorption bands of both cytochrome b and cytochrome aa3; these mutants also fail to accumulate apocytochrome b and subunit I of cytochrome c oxidase and instead form a large number of abnormal translation products whose nature is unknown. 4. Zygotic complementation tests reveal at least two complementation groups: The first group includes all mutants in cluster B and the second group includes mutants in clusters (A + C + D + E).

Exploring Capabilities of SENTINEL-2 for Vegetation Mapping Using Random Forest

NASA Astrophysics Data System (ADS)

Saini, R.; Ghosh, S. K.

2018-04-01

Accurate vegetation mapping is essential for monitoring crop and sustainable agricultural practice. This study aims to explore the capabilities of Sentinel-2 data over Landsat-8 Operational Land Imager (OLI) data for vegetation mapping. Two combination of Sentinel-2 dataset have been considered, first combination is 4-band dataset at 10m resolution which consists of NIR, R, G and B bands, while second combination is generated by stacking 4 bands having 10 m resolution along with other six sharpened bands using Gram-Schmidt algorithm. For Landsat-8 OLI dataset, six multispectral bands have been pan-sharpened to have a spatial resolution of 15 m using Gram-Schmidt algorithm. Random Forest (RF) and Maximum Likelihood classifier (MLC) have been selected for classification of images. It is found that, overall accuracy achieved by RF for 4-band, 10-band dataset of Sentinel-2 and Landsat-8 OLI are 88.38 %, 90.05 % and 86.68 % respectively. While, MLC give an overall accuracy of 85.12 %, 87.14 % and 83.56 % for 4-band, 10-band Sentinel and Landsat-8 OLI respectively. Results shown that 10-band Sentinel-2 dataset gives highest accuracy and shows a rise of 3.37 % for RF and 3.58 % for MLC compared to Landsat-8 OLI. However, all the classes show significant improvement in accuracy but a major rise in accuracy is observed for Sugarcane, Wheat and Fodder for Sentinel 10-band imagery. This study substantiates the fact that Sentinel-2 data can be utilized for mapping of vegetation with a good degree of accuracy when compared to Landsat-8 OLI specifically when objective is to map a sub class of vegetation.

Differential Fee: From Conceptualisation to Implementation.

ERIC Educational Resources Information Center

Ng, Todd C. Y.; Wong, Andrew L. S.

A differential fee policy was adopted at the Open Learning Institute (OLI) of Hong Kong after a process of conceptualization, planning, proposal, approval and implementation. Under the differential fee policy different tuition rates were charged for different courses. The differential fee policy was conceptualized at OLI based on economics,…

Targeting Hydrothermal Alterations Utilizing LANDSAT-8 Andaster Data in Shahr-E Iran

NASA Astrophysics Data System (ADS)

Safari, M.; Pour, A. B.; Maghsoudi, A.; Hashim, M.

2017-10-01

Shahr-e-Babak tract of the Kerman metalogenic belt is one of the most potential segments of Urumieh-Dokhtar (Sahand-Bazman) magmatic arc. This area encompasses several porphyry copper deposits in exploration, development and exploitation hierarchy. The aim of this study is to map hydrothermal alterations caused by early Cenozoic magmatic intrusions in Shahr-e-Babak area. To this purpose, mineral mapping methods including band combinations, ratios and multiplications as well as PCA and MNF data space transforms in SWIR and VNIR for both ASTER and OLI sensors. Alteration zones according to spectral signatures of each type of alteration mineral assemblages such as argillic, phyllic and propylitic are successfully mapped. For enhancing the target areas false color composites and HSI-RGB color space transform are performed on developed band combinations. Previous studies have proven the robust application of ASTER in geology and mineral exploration; nonetheless, the results of this investigation prove applicability of OLI sensor from landsat-8 for alteration mapping. According to the results, evidently OLI sensor data can accurately map alteration zones. Additionally, the 12-bit quantization of OLI data is its privilege over 8-bit data of ASTER in VNIR and SWIR, thus OLI high quality results, which makes it easy to distinguish targets with enhanced color contrast between the altered and unaltered rocks.

Evaluation of multi-resolution satellite sensors for assessing water quality and bottom depth of Lake Garda.

PubMed

Giardino, Claudia; Bresciani, Mariano; Cazzaniga, Ilaria; Schenk, Karin; Rieger, Patrizia; Braga, Federica; Matta, Erica; Brando, Vittorio E

2014-12-15

In this study we evaluate the capabilities of three satellite sensors for assessing water composition and bottom depth in Lake Garda, Italy. A consistent physics-based processing chain was applied to Moderate Resolution Imaging Spectroradiometer (MODIS), Landsat-8 Operational Land Imager (OLI) and RapidEye. Images gathered on 10 June 2014 were corrected for the atmospheric effects with the 6SV code. The computed remote sensing reflectance (Rrs) from MODIS and OLI were converted into water quality parameters by adopting a spectral inversion procedure based on a bio-optical model calibrated with optical properties of the lake. The same spectral inversion procedure was applied to RapidEye and to OLI data to map bottom depth. In situ measurements of Rrs and of concentrations of water quality parameters collected in five locations were used to evaluate the models. The bottom depth maps from OLI and RapidEye showed similar gradients up to 7 m (r = 0.72). The results indicate that: (1) the spatial and radiometric resolutions of OLI enabled mapping water constituents and bottom properties; (2) MODIS was appropriate for assessing water quality in the pelagic areas at a coarser spatial resolution; and (3) RapidEye had the capability to retrieve bottom depth at high spatial resolution. Future work should evaluate the performance of the three sensors in different bio-optical conditions.

Landsat Data Continuity Mission Calibration and Validation

NASA Technical Reports Server (NTRS)

Markham, Brian L.; Dabney, Philip W.; Storey, James C.; Morfitt, Ron; Knight, Ed; Kvaran, Geir; Lee, Kenton

2008-01-01

The primary payload for the Landsat Data Continuity Mission (LDCM) is the Operational Land Imager (OLI), being built by Ball Aerospace and Technologies, under contract to NASA. The OLI has spectral bands similar to the Landsat-7 ETM+, minus the thermal band and with two new bands, a 443 nm band and 1375 nm cirrus detection band. On-board calibration systems include two solar diffusers (routine and pristine), a shutter and three sets of internal lamps (routine, backup and pristine). Being a pushbroom opposed to a whiskbroom design of ETM+, the system poses new challenges for characterization and calibration, chief among them being the large focal plane with 75000+ detectors. A comprehensive characterization and calibration plan is in place for the instrument and the data throughout the mission including Ball, NASA and the United States Geological Survey, which will take over operations of LDCM after on-orbit commissioning. Driving radiometric calibration requirements for OLI data include radiance calibration to 5% uncertainty (1 q); reflectance calibration to 3% uncertainty (1 q) and relative (detector-to-detector) calibration to 0.5% (J (r). Driving geometric calibration requirements for OLI include bandto- band registration of 4.5 meters (90% confidence), absolute geodetic accuracy of 65 meters (90% CE) and relative geodetic accuracy of 25 meters (90% CE). Key spectral, spatial and radiometric characterization of the OLI will occur in thermal vacuum at Ball Aerospace. During commissioning the OLI will be characterized and calibrated using celestial (sun, moon, stars) sources and terrestrial sources. The USGS EROS ground processing system will incorporate an image assessment system similar to Landsat-7 for characterization and calibration. This system will have the added benefit that characterization data will be extracted as part of the normal image data processing, so that the characterization data available will be significantly larger than for Landsat-7 ETM+.

Fold or hold: experimental evolution in vitro

PubMed Central

Collins, S; Rambaut, A; Bridgett, S J

2013-01-01

We introduce a system for experimental evolution consisting of populations of short oligonucleotides (Oli populations) evolving in a modified quantitative polymerase chain reaction (qPCR). It is tractable at the genetic, genomic, phenotypic and fitness levels. The Oli system uses DNA hairpins designed to form structures that self-prime under defined conditions. Selection acts on the phenotype of self-priming, after which differences in fitness are amplified and quantified using qPCR. We outline the methodological and bioinformatics tools for the Oli system here and demonstrate that it can be used as a conventional experimental evolution model system by test-driving it in an experiment investigating adaptive evolution under different rates of environmental change. PMID:24003997

From School-Culture-to-Family-Culture: Reflections on Four Generations of a Deweyan Education in Hawai'i

ERIC Educational Resources Information Center

Makaiau, Amber Strong

2015-01-01

In 1918, the author's great great aunt, Sophie Judd Cooke founded a small progressive school in Honolulu. Her brother Henry named it Hanahau'oli School, which means joyful work school. In this essay the author's mother, Linda Summers Strong and the author reflect on the impact of Hanahau'oli School's Deweyan approach to education on the…

Hanahau'oli School: Theory Meets Practice

ERIC Educational Resources Information Center

Peters, Robert

2015-01-01

Progressive schools, by their very nature, need to respond to changing societal conditions. Within that context, learning guided by the teachings of John Dewey will not only make the progressive tradition sustainable but also make it increasingly relevant in a future that will increasingly make demands on students to possess the knowledge to…

Immunohistochemical localization of c-fos in the nuclei of the medulla oblongata in relation to asphyxia.

PubMed

Nogami, M; Takatsu, A; Endo, N; Ishiyama, I

1999-01-01

The immediately early gene product c-fos is known to be induced in neurons under noxious stimuli. Therefore, the immunohistochemistry of c-fos expression in human brains might offer information on the localization of stimulated neurons. In this study, the immunohistochemical localization of c-fos was studied in the neurons of the hypoglossal nucleus (XII), the dorsal motor nucleus of the vagal nerve (X), the nucleus solitarius (Sol), the accessory cuneate nucleus (Cun), the spinal trigeminal nucleus (V) and the inferior olive (Oli) of the human medulla oblongata from forensic autopsy cases. The neurons in the X nucleus showed the highest percentage of positive reactions for c-fos, followed in descending order by the Cun, V, Oli, XII and Sol. The c-fos immunoreactivity in the Cun and X was statistically significantly higher than in the Sol, XII and Oli. Although neurons in the Sol are known to be involved in respiration, there was no statistically significant difference in the c-fos immunoreactivity in the neurons in the Sol between asphyxia and non-asphyxia cases. On the other hand, the percentage of neurons positive for the c-fos immunoreactivity was statistically significantly higher in the Oli of asphyxia cases than of non-asphyxia cases. Our results indicate the difference in the immunoreactivity of c-fos among the nuclei of the human medulla oblongata and that the c-fos immunoreactivity in the Oli might assist the diagnosis of asphyxia.

Blends of POSS-PEO(n=4)(8) and high molecular weight poly(ethylene oxide) as solid polymer electrolytes for lithium batteries.

PubMed

Zhang, Hanjun; Kulkarni, Sunil; Wunder, Stephanie L

2007-04-12

Solid polymer electrolyte blends were prepared with POSS-PEO(n=4)8 (3K), poly(ethylene oxide) (PEO(600K)), and LiClO4 at different salt concentrations (O/Li = 8/1, 12/1, and 16/1). POSS-PEO(n=4)8/LiClO4 is amorphous at all O/Li investigated, whereas PEO(600K) is amorphous only for O/Li = 8/1 and semicrystalline for O/Li = 12/1 and 16/1. The tendency of PEO(600K) to crystallize limited the amount of POSS-PEO(n=4)(8) that could be incorporated into the blends, so that the greatest incorporation of POSS-PEO(n=4)(8) occurred for O/Li = 8/1. Blends of POSS-PEO(n=4)(8)/PEO(600K)/LiClO4 (O/Li = 8/1 and 12/1) microphase separated into two amorphous phases, a low T(g) phase of composition 85% POSS-PEO(n=4)(8)/15% PEO(600K) and a high T(g) phase of composition 29% POSS-PEO(n=4)(8)/71% PEO(600K). For O/Li = 16/1, the blends contained crystalline (pure PEO(600K)), and two amorphous phases, one rich in POSS-PEO(n=4)(8) and one rich in PEO(600K). Microphase, rather than macrophase separation was believed to occur as a result of Li(+)/ether oxygen cross-link sites. The conductivity of the blends depended on their composition. As expected, crystallinity decreased the conductivity of the blends. For the amorphous blends, when the low T(g) (80/20) phase was the continuous phase, the conductivity was intermediate between that of pure PEO(600K) and POSS-PEO(n=4)(8). When the high T(g) (70/30, 50/50, 30/70, and 20/80) phase was the continuous phase, the conductivity of the blend and PEO(600K) were identical, and lower than that for the POSS-PEO(n=4)(8) over the whole temperature range (10-90 degrees C). This suggests that the motions of the POSS-PEO(n=4)(8) were slowed down by the dynamics of the long chain PEO(600K) and that the minor, low Tg phase was not interconnected and thus did not contribute to enhanced conductivity. At temperatures above T(m) of PEO(600K), addition of the POSS-PEO(n=4)(8) did not result in conductivity improvement. The highest RT conductivity, 8 x 10(-6) S

Landsat Data Continuity Mission

NASA Technical Reports Server (NTRS)

Markham, Brian; Irons, James; Dabney, Philip

2011-01-01

The Landsat Data Continuity Mission (LDCM) is currently under development and is on schedule to launch the 8th satellite in the Landsat series in December of 2012. LDCM is a joint project between the National Aeronautics and Space Administration (NASA) and the United States Geological Survey (USGS). NASA is responsible for developing and launching the flight hardware and on-orbit commissioning and USGS is responsible for developing the ground system and operating the system onorbit after commissioning. Key components of the flight hardware are the Operational Land Imager (OLI), nearing completion by Ball Aerospace & Technologies Corp in Boulder, CO, the Thermal Infrared Sensor (TIRS), being built by NASA's Goddard Space Flight Center and the spacecraft, undergoing integration at Orbital Sciences Corp in Gilbert, Arizona. The launch vehicle will be an Atlas-5 with launch services provided by NASA's Kennedy Space Center. Key ground systems elements are the Mission Operations Element, being developed by the Hammers Corporation, and the Collection Activity Planning Element, Ground Network Element, and Data Processing and Archive System, being developed internally by the USGS Earth Resources Observations and Science (EROS) Center. The primary measurement goal of LDCM is to continue the global coverage of moderate spatial resolution imagery providing continuity with the existing Landsat record. The science goal for this imagery is to monitor land use and land cover, particularly as it relates to global climate change. Together the OLI and TIRS instruments on LDCM replace the ETM+ instrument on Landsat-7 with significant enhancements. The OLI is a pushbroom design instrument where the scanning mechanism of the ETM+ is effectively replaced by a long line of detectors. The OLI has 9 spectral bands with similar spatial resolution to ETM+: 7 of them similar to the reflective spectral bands on ETM+ and two new bands. The two new bands cover (1) the shorter wavelength blue part

Installation Summaries From the FY 2001 Survey of Threatened and Endangered Species on Army Lands

DTIC Science & Technology

2002-08-01

lepard frog Amphibian PT Rhinichthys cobitis Loach minnow Fish T Sarracenia oreophilia Green pitcher-plant Plant E Sarracenia rubra alabamensis...Alabama canebrake pitcher-plant Plant E Sarracenia rubra spp. Jonesii Moutain sweet pitcher-plant Plant E Schiedea adamantis Ma`oli`oli Plant E...Isotria medeoloides Small whorled pogonia Onsite T Plant No Sarracenia oreophilia Green pitcher-plant Onsite E Plant No A-11 MACOM

Spatiotemporal monitoring of soil salinization in irrigated Tadla Plain (Morocco) using satellite spectral indices

NASA Astrophysics Data System (ADS)

El Harti, Abderrazak; Lhissou, Rachid; Chokmani, Karem; Ouzemou, Jamal-eddine; Hassouna, Mohamed; Bachaoui, El Mostafa; El Ghmari, Abderrahmene

2016-08-01

Soil salinization is major environmental issue in irrigated agricultural production. Conventional methods for salinization monitoring are time and money consuming and limited by the high spatiotemporal variability of this phenomenon. This work aims to propose a spatiotemporal monitoring method of soil salinization in the Tadla plain in central Morocco using spectral indices derived from Thematic Mapper (TM) and Operational Land Imager (OLI) data. Six Landsat TM/OLI satellite images acquired during 13 years period (2000-2013) coupled with in-situ electrical conductivity (EC) measurements were used to develop the proposed method. After radiometric and atmospheric correction of TM/OLI images, a new soil salinity index (OLI-SI) is proposed for soil EC estimation. Validation shows that this index allowed a satisfactory EC estimation in the Tadla irrigated perimeter with coefficient of determination R2 varying from 0.55 to 0.77 and a Root Mean Square Error (RMSE) ranging between 1.02 dS/m and 2.35 dS/m. The times-series of salinity maps produced over the Tadla plain using the proposed method show that salinity is decreasing in intensity and progressively increasing in spatial extent, over the 2000-2013 period. This trend resulted in a decrease in agricultural activities in the southwestern part of the perimeter, located in the hydraulic downstream.

Next-generation pushbroom filter radiometers for remote sensing

NASA Astrophysics Data System (ADS)

Tarde, Richard W.; Dittman, Michael G.; Kvaran, Geir E.

2012-09-01

Individual focal plane size, yield, and quality continue to improve, as does the technology required to combine these into large tiled formats. As a result, next-generation pushbroom imagers are replacing traditional scanning technologies in remote sensing applications. Pushbroom architecture has inherently better radiometric sensitivity and significantly reduced payload mass, power, and volume than previous generation scanning technologies. However, the architecture creates challenges achieving the required radiometric accuracy performance. Achieving good radiometric accuracy, including image spectral and spatial uniformity, requires creative optical design, high quality focal planes and filters, careful consideration of on-board calibration sources, and state-of-the-art ground test facilities. Ball Aerospace built the Landsat Data Continuity Mission (LDCM) next-generation Operational Landsat Imager (OLI) payload. Scheduled to launch in 2013, OLI provides imagery consistent with the historical Landsat spectral, spatial, radiometric, and geometric data record and completes the generational technology upgrade from the Enhanced Thematic Mapper (ETM+) whiskbroom technology to modern pushbroom technology afforded by advanced focal planes. We explain how Ball's capabilities allowed producing the innovative next-generational OLI pushbroom filter radiometer that meets challenging radiometric accuracy or calibration requirements. OLI will improve the multi-decadal land surface observation dataset dating back to the 1972 launch of ERTS-1 or Landsat 1.

Assembly of the mitochondrial membrane system. XVIII. Genetic loci on mitochondrial DNA involved in cytochrome b biosynthesis.

PubMed

Tzagoloff, A; Foury, F; Akai, A

1976-11-24

1. Fourteen cytoplasmic mutants of Saccharomyces cerevisiae with a specific deficiency of cytochrome b have been studied. The mutations have been shown to occur in two separate genetic loci, COB 1 and COB 2. These loci can be distinguished by mit- X mit- crosses. Pairwise crosses of cytochrome b mutants belonging to different loci yield 4-6% wild type recombinants corresponding to recombinational frequencies of 8-12%. In intra-locus crosses, the recombinational frequencies range from 1% to less than 0.01%. The two loci can also be distinguished by mit- X rho- crosses. Twenty rho- testers have been isolated of which ten preferentially restore mutations in COB 1 and ten others in COB 2. 2. The COB 1 and COB 2 loci have been localized on mitochondrial DNA between the two antibiotic resistance loci OLI 1 and OLI 2 in the order OLI 2-COB 2-COB 1-OLI 1. The results of mit- X mit- and mit- X rho- crosses have also been used to map the cytochrome b mutations relative to each other. The maps obtained by the two independent methods are in good agreement. 3. Mutations in COB 1 have been found to be linked to the OLI1 locus in some but not in other strains of S. cervisiae. This evidence suggests that there may be a spacer region between the two loci whose length varies from strain to strain. 4. Two mutations in COB 2 have been found to cause a loss of a mitochondrial translation product corresponding to the cytochrome b apoprotein. Instead of the wild type protein the mutants have a new low-molecular weight product which is probably a fragment of cytochrome b. The fact that the mutations revert suggests that they are nonsense mutations in the structural gene of cytochrome b.

Operational Land Imager relative radiometric calibration

NASA Astrophysics Data System (ADS)

Barsi, Julia A.; Markham, Brian L.

2015-09-01

The Operational Land Imager (OLI), on board the Landsat-8 satellite, is a pushbroom sensor with nearly 7000 detectors per band, divided between 14 separate modules. While rigorously characterized prior to launch, the shear number of individual detectors presents a challenge to maintaining the on-orbit relative calibration, such that stripes, bands and other artifacts are minimized in the final image products. On-orbit relative calibration of the OLI is primarily monitored and corrected by observing an on-board primary solar diffuser panel. The panel is the most uniform target available to the OLI, though as observed but the OLI, it has a slope across the field of view due to view angle effects. Just after launch, parameters were derived using the solar diffuser data, to correct for the angular effects across the 14 modules. The residual discontinuities between arrays and the detector-to-detector uniformity continue to be monitored on a weekly basis. The observed variations in the responses to the diffuser panel since launch are thought to be due to real instrument changes. Since launch, the Coastal/Aerosol (CA) and Blue bands have shown the most variation in relative calibration of the VNIR bands, with as much as 0.14% change (3-sigma) between consecutive relative gain estimates. The other VNIR bands (Green, Red and NIR) initially had detectors showing a slow drift of about 0.2% per year, though this stopped after an instrument power cycle about seven months after launch. The SWIR bands also exhibit variability between collects (0.11% 3-sigma) but the larger changes have been where individual detectors' responses change suddenly by as much as 1.5%. The mechanisms behind these changes are not well understood but in order to minimize impact to the users, the OLI relative calibration is updated on a quarterly basis in order to capture changes over time.

Radiometric calibration updates to the Landsat collection

USGS Publications Warehouse

Micijevic, Esad; Haque, Md. Obaidul; Mishra, Nischal

2016-01-01

The Landsat Project is planning to implement a new collection management strategy for Landsat products generated at the U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center. The goal of the initiative is to identify a collection of consistently geolocated and radiometrically calibrated images across the entire Landsat archive that is readily suitable for time-series analyses. In order to perform an accurate land change analysis, the data from all Landsat sensors must be on the same radiometric scale. Landsat 7 Enhanced Thematic Mapper Plus (ETM+) is calibrated to a radiance standard and all previous sensors are cross-calibrated to its radiometric scale. Landsat 8 Operational Land Imager (OLI) is calibrated to both radiance and reflectance standards independently. The Landsat 8 OLI reflectance calibration is considered to be most accurate. To improve radiometric calibration accuracy of historical data, Landsat 1-7 sensors also need to be cross-calibrated to the OLI reflectance scale. Results of that effort, as well as other calibration updates including the absolute and relative radiometric calibration and saturated pixel replacement for Landsat 8 OLI and absolute calibration for Landsat 4 and 5 Thematic Mappers (TM), will be implemented into Landsat products during the archive reprocessing campaign planned within the new collection management strategy. This paper reports on the planned radiometric calibration updates to the solar reflective bands of the new Landsat collection.

Estimating wetland vegetation abundance from Landsat-8 operational land imager imagery: a comparison between linear spectral mixture analysis and multinomial logit modeling methods

NASA Astrophysics Data System (ADS)

Zhang, Min; Gong, Zhaoning; Zhao, Wenji; Pu, Ruiliang; Liu, Ke

2016-01-01

Mapping vegetation abundance by using remote sensing data is an efficient means for detecting changes of an eco-environment. With Landsat-8 operational land imager (OLI) imagery acquired on July 31, 2013, both linear spectral mixture analysis (LSMA) and multinomial logit model (MNLM) methods were applied to estimate and assess the vegetation abundance in the Wild Duck Lake Wetland in Beijing, China. To improve mapping vegetation abundance and increase the number of endmembers in spectral mixture analysis, normalized difference vegetation index was extracted from OLI imagery along with the seven reflective bands of OLI data for estimating the vegetation abundance. Five endmembers were selected, which include terrestrial plants, aquatic plants, bare soil, high albedo, and low albedo. The vegetation abundance mapping results from Landsat OLI data were finally evaluated by utilizing a WorldView-2 multispectral imagery. Similar spatial patterns of vegetation abundance produced by both fully constrained LSMA algorithm and MNLM methods were observed: higher vegetation abundance levels were distributed in agricultural and riparian areas while lower levels in urban/built-up areas. The experimental results also indicate that the MNLM model outperformed the LSMA algorithm with smaller root mean square error (0.0152 versus 0.0252) and higher coefficient of determination (0.7856 versus 0.7214) as the MNLM model could handle the nonlinear reflection phenomenon better than the LSMA with mixed pixels.

Enhancing moderate-resolution ocean color products over coastal/inland waters (Conference Presentation)

NASA Astrophysics Data System (ADS)

Pahlevan, Nima; Schott, John R.; Zibordi, Giuseppe

2016-10-01

With the successful launch of Landsat-8 in 2013 followed by a very recent launch of Sentinel-2A, we are entering a new area where frequent moderate resolution water quality products over coastal/inland waters will be available to scientists and operational agencies. Although designed for land observations, the Operational Land Imager (OLI) has proven to provide high-fidelity products in these aquatic systems where coarse-resolution ocean color imagers fail to provide valid observations. High-quality, multi-scale ocean color products can give insights into the biogeochemical/physical processes from the upstream in watersheds, into near-shore regions, and further out in ocean basins. In this research, we describe a robust cross-calibration approach, which facilitates seamless ocean color products at multi scales. The top-of-atmosphere (TOA) OLI imagery is cross-calibrated against near-simultaneous MODIS and VIIRS ocean color observations in high-latitude regions. This allows for not only examining the overall relative performance of OLI but also for characterizing non-uniformity (i.e., banding) across its swath. The uncertainty of this approach is, on average, found to be less than 0.5% in the blue channels. The adjustments made for OLI TOA reflectance products are then validated against in-situ measurements of remote sensing reflectance collected in research cruises or at the AERONET-OC.

Earth-observing satellite intercomparison using the Radiometric Calibration Test Site at Railroad Valley

NASA Astrophysics Data System (ADS)

Czapla-Myers, Jeffrey; McCorkel, Joel; Anderson, Nikolaus; Biggar, Stuart

2018-01-01

This paper describes the current ground-based calibration results of Landsat 7 Enhanced Thematic Mapper Plus (ETM+), Landsat 8 Operational Land Imager (OLI), Terra and Aqua Moderate Resolution Imaging Spectroradiometer (MODIS), Suomi National Polar orbiting Partnership Visible Infrared Imaging Radiometer Suite (VIIRS), and Sentinel-2A Multispectral Instrument (MSI), using an automated suite of instruments located at Railroad Valley, Nevada, USA. The period of this study is 2012 to 2016 for MODIS, VIIRS, and ETM+, 2013 to 2016 for OLI, and 2015 to 2016 for MSI. The current results show that all sensors agree with the Radiometric Calibration Test Site (RadCaTS) to within ±5% in the solar-reflective regime, except for one band on VIIRS that is within ±6%. In the case of ETM+ and OLI, the agreement is within ±3%, and, in the case of MODIS, the agreement is within ±3.5%. MSI agrees with RadCaTS to within ±4.5% in all applicable bands.

Confocal micrographs: automated segmentation and quantitative shape analysis of neuronal cells treated with ostreolysin A/pleurotolysin B pore-forming complex.

PubMed

Kopanja, Lazar; Kovacevic, Zorana; Tadic, Marin; Žužek, Monika Cecilija; Vrecl, Milka; Frangež, Robert

2018-04-23

Detailed shape analysis of cells is important to better understand the physiological mechanisms of toxins and determine their effects on cell morphology. This study aimed to develop a procedure for accurate morphological analysis of cell shape and use it as a tool to estimate toxin activity. With the aim of optimizing the method of cell morphology analysis, we determined the influence of ostreolysin A and pleurotolysin B complex (OlyA/PlyB) on the morphology of murine neuronal NG108-15 cells. A computational method was introduced and successfully applied to quantify morphological attributes of the NG108-15 cell line before and after 30 and 60 min exposure to OlyA/PlyB using confocal microscopy. The modified circularity measure [Formula: see text] for shape analysis was applied, which defines the degree to which the shape of the neuron differs from a perfect circle. It enables better detection of small changes in the shape of cells, making the outcome easily detectable numerically. Additionally, we analyzed the influence of OlyA/PlyB on the cell area, allowing us to detect the cells with blebs. This is important because the formation of plasma membrane protrusions such as blebs often reflects cell injury that leads to necrotic cell death. In summary, we offer a novel analytical method of neuronal cell shape analysis and its correlation with the toxic effects of the pore-forming OlyA/PlyB toxin in situ.

Automated Sargassum Detection for Landsat Imagery

NASA Astrophysics Data System (ADS)

McCarthy, S.; Gallegos, S. C.; Armstrong, D.

2016-02-01

We implemented a system to automatically detect Sargassum, a floating seaweed, in 30-meter LANDSAT-8 Operational Land Imager (OLI) imagery. Our algorithm for Sargassum detection is an extended form of Hu's approach to derive a floating algae index (FAI) [1]. Hu's algorithm was developed for Moderate Resolution Imaging Spectroradiometer (MODIS) data, but we extended it for use with the OLI bands centered at 655, 865, and 1609 nm, which are comparable to the MODIS bands located at 645, 859, and 1640 nm. We also developed a high resolution true color product to mask cloud pixels in the OLI scene by applying a threshold to top of the atmosphere (TOA) radiances in the red (655 nm), green (561 nm), and blue (443 nm) wavelengths, as well as a method for removing false positive identifications of Sargassum in the imagery. Hu's algorithm derives a FAI for each Sargassum identified pixel. Our algorithm is currently set to only flag the presence of Sargassum in an OLI pixel by classifying any pixel with a FAI > 0.0 as Sargassum. Additionally, our system geo-locates the flagged Sargassum pixels identified in the OLI imagery into the U.S. Navy Global HYCOM model grid. One element of the model grid covers an area 0.125 degrees of latitude by 0.125 degrees of longitude. To resolve the differences in spatial coverage between Landsat and HYCOM, a scheme was developed to calculate the percentage of pixels flagged within the grid element and if above a threshold, it will be flagged as Sargassum. This work is a part of a larger system, sponsored by NASA/Applied Science and Technology Project at J.C. Stennis Space Center, to forecast when and where Sargassum will land on shore. The focus area of this work is currently the Texas coast. Plans call for extending our efforts into the Caribbean. References: [1] Hu, Chuanmin. A novel ocean color index to detect floating algae in the global oceans. Remote Sensing of Environment 113 (2009) 2118-2129.

Evaluating the performance of the newly-launched Landsat 8 sensor in detecting and mapping the spatial configuration of water hyacinth (Eichhornia crassipes) in inland lakes, Zimbabwe

NASA Astrophysics Data System (ADS)

Dube, Timothy; Mutanga, Onisimo; Sibanda, Mbulisi; Bangamwabo, Victor; Shoko, Cletah

2017-08-01

The remote sensing of freshwater resources is increasingly becoming important, due to increased patterns of water use and the current or projected impacts of climate change and the rapid invasion by lethal water weeds. This study therefore sought to explore the potential of the recently-launched Landsat 8 OLI/TIRS sensor in mapping invasive species in inland lakes. Specifically, the study compares the performance of the newly-launched Landsat 8 sensor, with more advanced sensor design and image acquisition approach to the traditional Landsat-7 ETM+ in detecting and mapping the water hyacinth (Eichhornia crassipes) invasive species across Lake Chivero, in Zimbabwe. The analysis of variance test was used to identify windows of spectral separability between water hyacinth and other land cover types. The results showed that portions of the visible (B3), NIR (B4), as well as the shortwave bands (Band 8, 9 and 10) of both Landsat 8 OLI and Landsat 7 ETM, exhibited windows of separability between water hyacinth and other land cover types. It was also observed that on the use of Landsat 8 OLI produced high overall classification accuracy of 72%, when compared Landsat 7 ETM, which yielded lower accuracy of 57%. Water hyacinth had optimal accuracies (i.e. 92%), when compared to other land cover types, based on Landsat 8 OLI data. However, when using Landsat 7 ETM data, classification accuracies of water hyacinth were relatively lower (i.e. 67%), when compared to other land cover types (i.e. water with accuracy of 100%). Spectral curves of the old, intermediate and the young water hyacinth in Lake Chivero based on: (a) Landsat 8 OLI, and (b) Landsat 7 ETM were derived. Overall, the findings of this study underscores the relevance of the new generation multispectral sensors in providing primary data-source required for mapping the spatial distribution, and even configuration of water weeds at lower or no cost over time and space.

Imager-to-Radiometer In-flight Cross Calibration: RSP Radiometric Comparison with Airborne and Satellite Sensors

NASA Technical Reports Server (NTRS)

McCorkel, Joel; Cairns, Brian; Wasilewski, Andrzej

2016-01-01

This work develops a method to compare the radiometric calibration between a radiometer and imagers hosted on aircraft and satellites. The radiometer is the airborne Research Scanning Polarimeter (RSP), which takes multi-angle, photo-polarimetric measurements in several spectral channels. The RSP measurements used in this work were coincident with measurements made by the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS), which was on the same aircraft. These airborne measurements were also coincident with an overpass of the Landsat 8 Operational Land Imager (OLI). First we compare the RSP and OLI radiance measurements to AVIRIS since the spectral response of the multispectral instruments can be used to synthesize a spectrally equivalent signal from the imaging spectrometer data. We then explore a method that uses AVIRIS as a transfer between RSP and OLI to show that radiometric traceability of a satellite-based imager can be used to calibrate a radiometer despite differences in spectral channel sensitivities. This calibration transfer shows agreement within the uncertainty of both the various instruments for most spectral channels.

[Effects of vacuum sealing drainage combined with irrigation of oxygen loaded fluid on chronic wounds in diabetic patients].

PubMed

Zhang, Meiguang; Li, Zhiqing; Wang, Jiahan; Wu, Qi; Wen, Huangding

2014-04-01

To evaluate the therapeutic effects of VSD combined with irrigation of oxygen loaded fluid on chronic wounds in diabetic patients. Twenty-six diabetic patients hospitalized in Nanfang Hospital of Southern Medical University from September 2010 to June 2013, with chronic ulcers on lower extremities conforming to the inclusive criteria, were divided into group VSD (n = 8), VSD + irrigation control group (VSD + IC, n = 9), VSD + oxygen loaded fluid irrigation group (VSD OLI, n = 9) according to the random number table. After gross observation was conducted and wound secretion was sent for bacterial culturing right after admission, debridement was performed. During the debridement, granulation tissue of wound center was harvested for determination of the activity of lactate dehydrogenase (LDH) and succinate dehydrogenase (SDH) with ELISA. After debridement, the patients in group VSD were treated with VSD (negative pressure from -30 to -25 kPa, the same below); the patients in group VSD + IC were treated with VSD combining irrigation of normal saline; the patients in group VSD + OLI were treated with VSD combining normal saline loaded with oxygen (flow of 1 L/min ) irrigation. Drainage tube blockage was recorded and its incidence rate was recorded during the treatment. On post treatment day (PTD) 7, tissue exudates were collected and analyzed with blood gas analyzer for determining the partial pressure of oxygen of the exudate. After the VSD was terminated, bacterial culture was conducted as before, and the bacterial clearance rate was calculated. After the calculation of granulation tissue coverage rate, the granulation tissue in the center of the wound was harvested for histopathological observation with HE staining; morphological characteristics and density of mitochondria were observed with transmission electron microscopy; the activity of LDH and SDH was estimated as before; microvascular density (MVD) was counted after CD31 antibody immunohistochemical staining

Emission analysis of Tb3+ -and Sm3+ -ion-doped (Li2 O/Na2 O/K2 O) and (Li2 O + Na2 O/Li2 O + K2 O/K2 O + Na2 O)-modified borosilicate glasses.

PubMed

Naveen Kumar Reddy, B; Sailaja, S; Thyagarajan, K; Jho, Young Dahl; Sudhakar Reddy, B

2018-05-01

Four series of borosilicate glasses modified by alkali oxides and doped with Tb 3+ and Sm 3+ ions were prepared using the conventional melt quenching technique, with the chemical composition 74.5B 2 O 3 + 10SiO 2 + 5MgO + R + 0.5(Tb 2 O 3 /Sm 2 O 3 ) [where R = 10(Li 2 O /Na 2 O/K 2 O) for series A and C, and R = 5(Li 2 O + Na 2 O/Li 2 O + K 2 O/K 2 O + Na 2 O) for series B and D]. The X-ray diffraction (XRD) patterns of all the prepared glasses indicate their amorphous nature. The spectroscopic properties of the prepared glasses were studied by optical absorption analysis, photoluminescence excitation (PLE) and photoluminescence (PL) analysis. A green emission corresponding to the 5 D 4 → 7 F 5 (543 nm) transition of the Tb 3+ ions was registered under excitation at 379 nm for series A and B glasses. The emission spectra of the Sm 3+ ions with the series C and D glasses showed strong reddish-orange emission at 600 nm ( 4 G 5/2 → 6 H 7/2 ) with an excitation wavelength λ exci = 404 nm ( 6 H 5/2 → 4 F 7/2 ). Furthermore, the change in the luminescence intensity with the addition of an alkali oxide and combinations of these alkali oxides to borosilicate glasses doped with Tb 3+ and Sm 3+ ions was studied to optimize the potential alkali-oxide-modified borosilicate glass. Copyright © 2017 John Wiley & Sons, Ltd.

Acting Administrator Lightfoot Visits Ball Aerospace

NASA Image and Video Library

2017-04-06

Leanne Presley, Operational Land Imager-2 (OLI-2) program manager at Ball Aerospace, left, speaks with acting NASA Deputy Administrator Lesa Roe, center, and acting NASA Administrator Robert Lightfoot in front of a thermal vacuum chamber used to test satellite optics, Thursday, April 6, 2017 during a visit to Ball Aerospace in Boulder, Colo. The Operation Land Imager-2 (OLI-2) is being build for Landsat 9, a collaboration between NASA and the U.S. Geological Survey that will continue the Landsat Program's 40-year data record of monitoring the Earth's landscapes from space. Photo Credit: (NASA/Joel Kowsky)

On-orbit performance of the Landsat 8 Operational Land Imager

USGS Publications Warehouse

Micijevic, Esad; Vanderwerff, Kelly; Scaramuzza, Pat; Morfitt, Ron; Barsi, Julia A.; Levy, Raviv

2014-01-01

The Landsat 8 satellite was launched on February 11, 2013, to systematically collect multispectral images for detection and quantitative analysis of changes on the Earth’s surface. The collected data are stored at the U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center and continue the longest archive of medium resolution Earth images. There are two imaging instruments onboard the satellite: the Operational Land Imager (OLI) and the Thermal InfraRed Sensor (TIRS). This paper summarizes radiometric performance of the OLI including the bias stability, the system noise, saturation and other artifacts observed in its data during the first 1.5 years on orbit. Detector noise levels remain low and Signal-To-Noise Ratio high, largely exceeding the requirements. Impulse noise and saturation are present in imagery, but have negligible effect on Landsat 8 products. Oversaturation happens occasionally, but the affected detectors quickly restore their nominal responsivity. Overall, the OLI performs very well on orbit and provides high quality products to the user community. © (2014) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.

Characterization of Landsat-7 to Landsat-8 Reflective Wavelength and Normalized Difference Vegetation Index Continuity

NASA Technical Reports Server (NTRS)

Roy, D. P.; Kovalskyy, V.; Zhang, H. K.; Vermote, E. F.; Yan, L.; Kumar, S. S.; Egorov, A.

2016-01-01

At over 40 years, the Landsat satellites provide the longest temporal record of space-based land surface observations, and the successful 2013 launch of the Landsat-8 is continuing this legacy. Ideally, the Landsat data record should be consistent over the Landsat sensor series. The Landsat-8 Operational Land Imager (OLI) has improved calibration, signal to noise characteristics, higher 12-bit radiometric resolution, and spectrally narrower wavebands than the previous Landsat-7 Enhanced Thematic Mapper (ETM+). Reflective wavelength differences between the two Landsat sensors depend also on the surface reflectance and atmospheric state which are difficult to model comprehensively. The orbit and sensing geometries of the Landsat- 8 OLI and Landsat-7 ETM+ provide swath edge overlapping paths sensed only one day apart. The overlap regions are sensed in alternating backscatter and forward scattering orientations so Landsat bi-directional reflectance effects are evident but approximately balanced between the two sensors when large amounts of time series data are considered. Taking advantage of this configuration a total of 59 million 30m corresponding sensor observations extracted from 6,317 Landsat-7 ETM+ and Landsat-8 OLI images acquired over three winter and three summer months for all the conterminous United States (CONUS) are compared. Results considering different stages of cloud and saturation filtering, and filtering to reduce one day surface state differences, demonstrate the importance of appropriate per-pixel data screening. Top of atmosphere (TOA) and atmospherically corrected surface reflectance for the spectrally corresponding visible, near infrared and shortwave infrared bands, and derived normalized difference vegetation index (NDVI), are compared and their differences quantified. On average the OLI TOA reflectance is greater than the ETM+ TOA reflectance for all bands, with greatest differences in the near-infrared (NIR) and the shortwave infrared bands

Evaluation of forest fires in Portugal Mainland during 2016 summer considering different satellite datasets

NASA Astrophysics Data System (ADS)

Teodoro, A. C.; Amaral, A.

2017-10-01

Portugal is one of the most affected countries in Europe by forest fires. Every year in the summer, hundreds of hectares burn, destroying goods and forests at an alarming rate. The objective of this work was to analyze the forest areas burned in Portugal in 2016 (summer) using different satellite data with different spatial resolution (Sentinel-2A MSI and Landsat 8 OLI) in two affected areas. Data from spring from 2016 and 2017 were chosen (pre-fire event and post-fire event) in order to maximize the Normalized Difference Vegetation Index (NDVI) values. The QGIS software's plugin - Semi- Automatic Classification Plugin- which allowed to obtain NDVI values for the Landsat 8 OLI and Sentinel- 2A was used. The results showed that the NDVI decreased considerably in Arouca and Vila Nova de Cerveira after de fire event, meaning a marked drop in vegetation level. In Sintra municipality this change was not verified because non forest fire was registered in this area during the study period. The results from the Sentinel-2A and Landsat 8 OLI data analysis are in agreement, however the Sentinel-2A satellite gives results more accurate than Landsat-8 OLI since it has best spatial resolution. This study could help the experts to understand both the causes and consequences of spatial variability of post-fire effects. Other vegetation spectral indices related with fire and burnt areas could also be calculated in order to discriminate burnt areas. Added to the best spatial resolution of Sentinel-2A (10 m), the temporal resolution of Sentinel- 2A (10 days) was increased with the launch of the twin Sentinel-2B (very recently) and therefore the frequency of the combined constellation revisit will be 5 days. However, for historical studies, the Landsat program remains the best option.

Monitoring algal blooms in drinking water reservoirs using the Landsat-8 Operational Land Imager

USGS Publications Warehouse

Keith, Darryl; Rover, Jennifer; Green, Jason; Zalewsky, Brian; Charpentier, Mike; Hursby, Glen; Bishop, Joseph

2018-01-01

In this study, we demonstrated that the Landsat-8 Operational Land Imager (OLI) sensor is a powerful tool that can provide periodic and system-wide information on the condition of drinking water reservoirs. The OLI is a multispectral radiometer (30 m spatial resolution) that allows ecosystem observations at spatial and temporal scales that allow the environmental community and water managers another means to monitor changes in water quality not feasible with field-based monitoring. Using the provisional Land Surface Reflectance product and field-collected chlorophyll-a (chl-a) concentrations from drinking water monitoring programs in North Carolina and Rhode Island, we compared five established approaches for estimating chl-aconcentrations using spectral data. We found that using the three band reflectance approach with a combination of OLI spectral bands 1, 3, and 5 produced the most promising results for accurately estimating chl-a concentrations in lakes (R2 value of 0.66; root mean square error value of 8.9 µg l−1). Using this model, we forecast the spatial and temporal variability of chl-a for Jordan Lake, a recreational and drinking water source in piedmont North Carolina and several small ponds that supply drinking water in southeastern Rhode Island.

The Sentinel-2 MSI Can Increase the Temporal Resolution of 30m Satellite-Derived LAI Estimates

NASA Astrophysics Data System (ADS)

Dungan, J. L.; Li, S.; Ganguly, S.; Wang, W.; Nemani, R. R.; Ju, J.; Claverie, M.; Masek, J. G.

2016-12-01

The successful launch of the European Space Agency (ESA) Sentinel-2A (S2-A) on 23 June 2015 with its MultiSpectral Instrument (MSI) provides an important means to augment Earth-observation capabilities following the legacy of Landsat. After the three-month satellite commissioning campaign, the MSI onboard S-2A is performing very well (ESA, 2015). By 3 December 2015, the sensor data records have achieved provisional maturity status and have been accessed in level-1C Top-Of-Atmosphere (TOA) reflectance by the remote sensing community worldwide. Near-nadir observations by the MSI onboard S-2A and the Operational Land Imager (OLI) onboard Landsat 8 were collected during Simultaneous Nadir Overpasses as well as nearly coincident overpasses. This paper presents a processing chain using harmonized S-2A MSI and Landsat 8 OLI sensors to obtain increased temporal resolution in Leaf Area Index (LAI) estimates using the red-edge band B8A of MSI to replace the NIR band B08. Results demonstrate that LAI estimates from the MSI and OLI are comparable, and, given sufficient preprocessing for atmospheric correction and geometric rectification, can be used interchangeably to improve the frequency with which low LAI canopies can be monitored.

Potential Long-Term Records of Surface Albedo at Fine Spatiotemporal Resolution from Landsat/Sentinle-2A Surface Reflectance and MODIS/VIIRS BRDF

NASA Astrophysics Data System (ADS)

Li, Z.; Schaaf, C.; Shuai, Y.; Liu, Y.; Sun, Q.; Erb, A.; Wang, Z.

2016-12-01

The land surface albedo products at fine spatial resolutions are generated by coupling surface reflectance (SR) from Landsat (30 m) or Sentinel-2A (20 m) with concurrent surface anisotropy information (the Bidirectional Reflectance Distribution Function - BRDF) at coarser spatial resolutions from sequential multi-angular observations by the Moderate Resolution Imaging Spectroradiometer (MODIS) or its successor, the Visible Infrared Imaging Radiometer Suite (VIIRS). We assess the comparability of four types of fine-resolution albedo products (black-sky and white-sky albedos over the shortwave broad band) generated by coupling, (1) Landsat-8 Optical Land Imager (OLI) SR with MODIS BRDF; (2) OLI SR with VIIRS BRDF; (3) Sentinel-2A MultiSpectral Instrument (MSI) SR with MODIS BRDF; and (4) MSI SR with VIIRS BRDF. We evaluate the accuracy of these four types of fine-resolution albedo products using ground tower measurements of surface albedo over six SURFace RADiation Network (SURFRAD) sites in the United States. For comparison with the ground measurements, we estimate the actual (blue-sky) albedo values at the six sites by using the satellite-based retrievals of black-sky and white-sky albedos and taking into account the proportion of direct and diffuse solar radiation from the ground measurements at the sites. The coupling of the OLI and MSI SR with MODIS BRDF has already been shown to provide accurate fine-resolution albedo values. With demonstration of a high agreement in BRDF products from MODIS and VIIRS, we expect to see consistency between all four types of fine-resolution albedo products. This assurance of consistency between the couplings of both OLI and MSI with both MODIS and VIIRS guarantees the production of long-term records of surface albedo at fine spatial resolutions and an increased temporal resolution. Such products will be critical in studying land surface changes and associated surface energy balance over the dynamic and heterogeneous landscapes

Impact of Spatial Sampling on Continuity of MODIS-VIIRS Land Surface Reflectance Products: A Simulation Approach

NASA Technical Reports Server (NTRS)

Pahlevan, Nima; Sarkar, Sudipta; Devadiga, Sadashiva; Wolfe, Robert E.; Roman, Miguel; Vermote, Eric; Lin, Guoqing; Xiong, Xiaoxiong

2016-01-01

With the increasing need to construct long-term climate-quality data records to understand, monitor, and predict climate variability and change, it is vital to continue systematic satellite measurements along with the development of new technology for more quantitative and accurate observations. The Suomi National Polar-orbiting Partnership mission provides continuity in monitoring the Earths surface and its atmosphere in a similar fashion as the heritage MODIS instruments onboard the National Aeronautics and Space Administrations Terra and Aqua satellites. In this paper, we aim at quantifying the consistency of Aqua MODIS and Suomi-NPP Visible Infrared Imaging Radiometer Suite (VIIRS) Land Surface Reflectance (LSR) and NDVI products as related to their inherent spatial sampling characteristics. To avoid interferences from sources of measurement and/or processing errors other than spatial sampling, including calibration, atmospheric correction, and the effects of the bidirectional reflectance distribution function, the MODIS and VIIRSLSR products were simulated using the Landsat-8s Operational Land Imager (OLI) LSR products. The simulations were performed using the instruments point spread functions on a daily basis for various OLI scenes over a 16-day orbit cycle. It was found that the daily mean differences due to discrepancies in spatial sampling remain below 0.0015 (1) in absolute surface reflectance at subgranule scale (i.e., OLI scene size).We also found that the MODISVIIRS product intercomparisons appear to be minimally impacted when differences in the corresponding view zenith angles (VZAs) are within the range of -15deg to -35deg (VZA(sub v) - VZA(sub m)), where VIIRS and MODIS footprints resemble in size. In general, depending on the spatial heterogeneity of the OLI scene contents, per-grid-cell differences can reach up to 20.Further spatial analysis of the simulated NDVI and LSR products revealed that, depending on the user accuracy requirements for

Continuous Calibration Improvement in Solar Reflective Bands: Landsat 5 Through Landsat 8

NASA Technical Reports Server (NTRS)

Mishra, Nischal; Helder, Dennis; Barsi, Julia; Markham, Brian

2016-01-01

Launched in February 2013, the Operational Land Imager (OLI) on-board Landsat 8 continues to perform exceedingly well and provides high science quality data globally. Several design enhancements have been made in the OLI instrument relative to prior Landsat instruments: pushbroom imaging which provides substantially improved Signal-to-Noise Ratio (SNR), spectral bandpasses refinement to avoid atmospheric absorption features, 12 bit data resolution to provide a larger dynamic range that limits the saturation level, a set of well-designed onboard calibrators to monitor the stability of the sensor. Some of these changes such as refinements in spectral bandpasses compared to earlier Landsats and well-designed on-board calibrator have a direct impact on the improved radiometric calibration performance of the instrument from both the stability of the response and the ability to track the changes. The on-board calibrator lamps and diffusers indicate that the instrument drift is generally less than 0.1% per year across the bands. The refined bandpasses of the OLI indicate that temporal uncertainty of better than 0.5% is possible when the instrument is trended over vicarious targets such as Pseudo Invariant Calibration Sites (PICS), a level of precision that was never achieved with the earlier Landsat instruments. The stability measurements indicated by on-board calibrators and PICS agree much better compared to the earlier Landsats, which is very encouraging and bodes well for the future Landsat missions too.

CONTINUOUS CALIBRATION IMPROVEMENT: LANDSAT 5 THROUGH LANDSAT 8

PubMed Central

Mishra, Nischal; Helder, Dennis; Barsi, Julia; Markham, Brian

2018-01-01

Launched in February 2013, the Operational Land Imager (OLI) on-board Landsat 8 continues to perform exceedingly well and provides high science quality data globally. Several design enhancements have been made in the OLI instrument relative to prior Landsat instruments: pushbroom imaging which provides substantially improved Signal-to-Noise Ratio (SNR), spectral bandpasses refinement to avoid atmospheric absorption features, 12 bit data resolution to provide a larger dynamic range that limits the saturation level, a set of well-designed onboard calibrators to monitor the stability of the sensor. Some of these changes such as refinements in spectral bandpasses compared to earlier Landsats and well-designed on-board calibrator have a direct impact on the improved radiometric calibration performance of the instrument from both the stability of the response and the ability to track the changes. The on-board calibrator lamps and diffusers indicate that the instrument drift is generally less than 0.1% per year across the bands. The refined bandpasses of the OLI indicate that temporal uncertainty of better than 0.5% is possible when the instrument is trended over vicarious targets such as Pseudo Invariant Calibration Sites (PICS), a level of precision that was never achieved with the earlier Landsat instruments. The stability measurements indicated by on-board calibrators and PICS agree much better compared to the earlier Landsats, which is very encouraging and bodes well for the future Landsat missions too. PMID:29449747

Regulatory off-gas analysis from the evaporation of Hanford simulated waste spiked with organic compounds.

PubMed

Saito, Hiroshi H; Calloway, T Bond; Ferrara, Daro M; Choi, Alexander S; White, Thomas L; Gibson, Luther V; Burdette, Mark A

2004-10-01

After strontium/transuranics removal by precipitation followed by cesium/technetium removal by ion exchange, the remaining low-activity waste in the Hanford River Protection Project Waste Treatment Plant is to be concentrated by evaporation before being mixed with glass formers and vitrified. To provide a technical basis to permit the waste treatment facility, a relatively organic-rich Hanford Tank 241-AN-107 waste simulant was spiked with 14 target volatile, semi-volatile, and pesticide compounds and evaporated under vacuum in a bench-scale natural circulation evaporator fitted with an industrial stack off-gas sampler at the Savannah River National Laboratory. An evaporator material balance for the target organics was calculated by combining liquid stream mass and analytical data with off-gas emissions estimates obtained using U.S. Environmental Protection Agency (EPA) SW-846 Methods. Volatile and light semi-volatile organic compounds (<220 degrees C BP, >1 mm Hg vapor pressure) in the waste simulant were found to largely exit through the condenser vent, while heavier semi-volatiles and pesticides generally remain in the evaporator concentrate. An OLI Environmental Simulation Program (licensed by OLI Systems, Inc.) evaporator model successfully predicted operating conditions and the experimental distribution of the fed target organics exiting in the concentrate, condensate, and off-gas streams, with the exception of a few semi-volatile and pesticide compounds. Comparison with Henry's Law predictions suggests the OLI Environmental Simulation Program model is constrained by available literature data.

U.S. EPA, Pesticide Product Label, BEST BBC 12-E EMULSIFIABLE LIQUID, 01/12/1968

EPA Pesticide Factsheets

2011-04-14

... plar,7"":) 1 q'J ;-,I'r Ol.I',' (OTTON, p~EPl/\\~~~ T ~!"~'i!I~~\\.. i)()SrPLANT. PiNEAPPLES: [11'(0(1"\\1' ~'~Lr'~ I.~ .. T ,~,l ~-'lt~~~1:~~'~j ?OSTPLP.,Nf. ...

The Evolution of Landsat Data Systems and Science Products

NASA Astrophysics Data System (ADS)

Dwyer, J. L.

2011-12-01

The series of Landsat satellite missions have collected observations of the Earth's surface since 1972, resulting in the richest archive of remotely sensed data covering the global land masses at scales from which natural and human-induced changes can be distinguished. This observational record will continue to be extended with the launch of the Landsat Data Continuity Mission, or Landsat 8, in December of 2012 carrying the Operational Land Imager (OLI) and Thermal Infrared Sensor (TIRS) instruments. The data streams from these instruments will be significantly enhanced yet compatible with data acquired by heritage Landsat instruments. The radiometry and geometry of the OLI and TIRS data will be calibrated and combined into single, multi-band Level-1 terrain-corrected image products. Coefficients will be included in the product metadata to convert OLI to at-sensor radiance or reflectance and to convert TIRS data to at-aperture radiances. A quality assurance band will contain pixel-based information regarding the presences or clouds, shadows, and terrain occlusion. The raw data as well as the Level-1 products will be stored online and made freely accessible through web coverage services. Rescaled Level-1 OLI and TIRS images will be made available via web mapping services to enable inventory searches and for ready use in geospatial applications. The architecture of the Landsat science data processing systems is scalable to accommodate additional processing and storage nodes in response to archive growth and increased demands on processing and distribution. The data collected by the various Landsat instruments have been inter-calibrated to enable the generation of higher level science data products that are of consistent quality through time and from which geophysical and biophysical parameters of the land surface can be derived for use in process models and decision support systems. Data access and delivery services have evolved in response to increasing demand for

Terrestrial Applications of the Thermal Infrared Sensor, TIRS

NASA Technical Reports Server (NTRS)

Smith, Ramsey L.; Thome, Kurtis; Richardson, Cathleen; Irons, James; Reuter, Dennis

2009-01-01

Landsat satellites have acquired single-band thermal images since 1978. The next satellile in the heritage, Landsat Data Continuity Mission (LDCM), is scheduled to launch in December 2012. LDCM will contain the Operational Land Imager (OLI) and the Thermal Infrared Sensor (TIRS), where TIRS operates in concert with, but independently of OLI. This paper will provide an overview of the remote sensing instrument TIRS. The T1RS instrument was designed at National Aeronautics and Space Administration's (NASA) Goddard Space Flight Center (GSFC) where it will be fabricated and calibrated as well. Protecting the integrity of the Scientific Data that will be collected from TIRS played a strong role in definition of the calibration test equipment and procedures used for the optical, radiometric, and spatial calibration. The data that will be produced from LCDM will continue to be used world wide for environment monitoring and resource management.

Radiometric characterization of Landsat Collection 1 products

USGS Publications Warehouse

Micijevic, Esad; Haque, Md. Obaidul; Mishra, Nischal

2017-01-01

Landsat data in the U.S. Geological Survey (USGS) archive are being reprocessed to generate a tiered collection of consistently geolocated and radiometrically calibrated products that are suitable for time series analyses. With the implementation of the collection management, no major updates will be made to calibration of the Landsat sensors within a collection. Only calibration parameters needed to maintain the established calibration trends without an effect on derived environmental records will be regularly updated, while all other changes will be deferred to a new collection. This first collection, Collection 1, incorporates various radiometric calibration updates to all Landsat sensors including absolute and relative gains for Landsat 8 Operational Land Imager (OLI), stray light correction for Landsat 8 Thermal Infrared Sensor (TIRS), absolute gains for Landsat 4 and 5 Thematic Mappers (TM), recalibration of Landsat 1-5 Multispectral Scanners (MSS) to ensure radiometric consistency among different formats of archived MSS data, and a transfer of Landsat 8 OLI reflectance based calibration to all previous Landsat sensors. While all OLI/TIRS, ETM+ and majority of TM data have already been reprocessed to Collection 1, a completion of MSS and remaining TM data reprocessing is expected by the end of this year. It is important to note that, although still available for download from the USGS web pages, the products generated using the Pre-Collection processing do not benefit from the latest radiometric calibration updates. In this paper, we are assessing radiometry of solar reflective bands in Landsat Collection 1 products through analysis of trends in on-board calibrator and pseudo invariant site (PICS) responses.

Bias estimation for the Landsat 8 operational land imager

USGS Publications Warehouse

Morfitt, Ron; Vanderwerff, Kelly

2011-01-01

The Operational Land Imager (OLI) is a pushbroom sensor that will be a part of the Landsat Data Continuity Mission (LDCM). This instrument is the latest in the line of Landsat imagers, and will continue to expand the archive of calibrated earth imagery. An important step in producing a calibrated image from instrument data is accurately accounting for the bias of the imaging detectors. Bias variability is one factor that contributes to error in bias estimation for OLI. Typically, the bias is simply estimated by averaging dark data on a per-detector basis. However, data acquired during OLI pre-launch testing exhibited bias variation that correlated well with the variation in concurrently collected data from a special set of detectors on the focal plane. These detectors are sensitive to certain electronic effects but not directly to incoming electromagnetic radiation. A method of using data from these special detectors to estimate the bias of the imaging detectors was developed, but found not to be beneficial at typical radiance levels as the detectors respond slightly when the focal plane is illuminated. In addition to bias variability, a systematic bias error is introduced by the truncation performed by the spacecraft of the 14-bit instrument data to 12-bit integers. This systematic error can be estimated and removed on average, but the per pixel quantization error remains. This paper describes the variability of the bias, the effectiveness of a new approach to estimate and compensate for it, as well as the errors due to truncation and how they are reduced.

Detection of Green up Phenomenon in Amazon Forests Using Spaceborne Solar-induced Fluorescence

NASA Astrophysics Data System (ADS)

Chen, S.; Chen, X.; Chen, J.; Cao, X.

2016-12-01

The role of Amazon forests in the global carbon budget still remains uncertain. The critical issue is whether tropical forest productivity is more limited by sunlight or rainfall. Recent studies using satellite data have challenged the paradigm of light-limited net primary production in Amazon forests and enhanced forest growth during drought conditions because of the adding effects of variations in sun-sensor geometry. To reducing uncertainties in knowing the sensitivity of Amazon rainforests to dry season droughts, we evaluated a newly emerging satellite retrieval, solar-induced fluorescence (SIF) of chlorophyll for the seasonal green-up phenomenon, providing for the first time a direct measurement related to vegetation photosynthetic activity as well as unaffected by sun-sensor geometry. Moreover, NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) products (the enhanced vegetation index (EVI) and leaf area index (LAI)) and Landsat Operational Land Imager (OLI) data are also compared to evaluate this phenomenon. Here we show that the green up of Amazon forests in the study area around manas site did show in SIF of chlorophyll data in 2015 drought resulted from seasonal changes. The EVI has more apparent green up phenomenon than the NDVI data both in MODIS and OLI data, suggesting that the EVI can better reflect near-infrared (NIR) and LAI information of vegetation. The OLI data is less influenced by variations caused by bidirectional reflectance effect. In addition, SIF of chlorophyll data shows well correlation relationship with the EVI, LAI and NDVI, suggesting that the SIF of chlorophyll data present well quality to capture the characteristics of the phenology of vegetation.

Radiometric characterization of Landsat Collection 1 products

NASA Astrophysics Data System (ADS)

Micijevic, Esad; Haque, Md. Obaidul; Mishra, Nischal

2017-09-01

Landsat data in the U.S. Geological Survey (USGS) archive are being reprocessed to generate a tiered collection of consistently geolocated and radiometrically calibrated products that are suitable for time series analyses. With the implementation of the collection management, no major updates will be made to calibration of the Landsat sensors within a collection. Only calibration parameters needed to maintain the established calibration trends without an effect on derived environmental records will be regularly updated, while all other changes will be deferred to a new collection. This first collection, Collection 1, incorporates various radiometric calibration updates to all Landsat sensors including absolute and relative gains for Landsat 8 Operational Land Imager (OLI), stray light correction for Landsat 8 Thermal Infrared Sensor (TIRS), absolute gains for Landsat 4 and 5 Thematic Mappers (TM), recalibration of Landsat 1-5 Multispectral Scanners (MSS) to ensure radiometric consistency among different formats of archived MSS data, and a transfer of Landsat 8 OLI reflectance based calibration to all previous Landsat sensors. While all OLI/TIRS, ETM+ and majority of TM data have already been reprocessed to Collection 1, a completion of MSS and remaining TM data reprocessing is expected by the end of this year. It is important to note that, although still available for download from the USGS web pages, the products generated using the Pre-Collection processing do not benefit from the latest radiometric calibration updates. In this paper, we are assessing radiometry of solar reflective bands in Landsat Collection 1 products through analysis of trends in on-board calibrator and pseudo invariant site (PICS) responses.

Attitudes Affecting Online Learning Implementation in Higher Education Institutions

ERIC Educational Resources Information Center

Mitchell, Betty; Geva-May, Iris

2009-01-01

This study explores attitudes towards and affecting online learning implementation (OLI). In recent years there has been greater acceptance of online learning (OL) by institutional decision-makers, as evidenced by higher levels of institutional involvement; nevertheless, the increase in faculty acceptance lags behind. This gap affects the…

Landsat 8 and ICESat-2: Performance and potential synergies for quantifying dryland ecosystem vegetation cover and biomass

USGS Publications Warehouse

Glenn, Nancy F.; Neuenschwander, Amy; Vierling, Lee A.; Spaete, Lucas; Li, Aihua; Shinneman, Douglas; Pilliod, David S.; Arkle, Robert; McIlroy, Susan

2016-01-01

To estimate the potential synergies of OLI and ICESat-2 we used simulated ICESat-2 photon data to predict vegetation structure. In a shrubland environment with a vegetation mean height of 1 m and mean vegetation cover of 33%, vegetation photons are able to explain nearly 50% of the variance in vegetation height. These results, and those from a comparison site, suggest that a lower detection threshold of ICESat-2 may be in the range of 30% canopy cover and roughly 1 m height in comparable dryland environments and these detection thresholds could be used to combine future ICESat-2 photon data with OLI spectral data for improved vegetation structure. Overall, the synergistic use of Landsat 8 and ICESat-2 may improve estimates of above-ground biomass and carbon storage in drylands that meet these minimum thresholds, increasing our ability to monitor drylands for fuel loading and the potential to sequester carbon.

Detecting Water Bodies in LANDSAT8 Oli Image Using Deep Learning

NASA Astrophysics Data System (ADS)

Jiang, W.; He, G.; Long, T.; Ni, Y.

2018-04-01

Water body identifying is critical to climate change, water resources, ecosystem service and hydrological cycle. Multi-layer perceptron(MLP) is the popular and classic method under deep learning framework to detect target and classify image. Therefore, this study adopts this method to identify the water body of Landsat8. To compare the performance of classification, the maximum likelihood and water index are employed for each study area. The classification results are evaluated from accuracy indices and local comparison. Evaluation result shows that multi-layer perceptron(MLP) can achieve better performance than the other two methods. Moreover, the thin water also can be clearly identified by the multi-layer perceptron. The proposed method has the application potential in mapping global scale surface water with multi-source medium-high resolution satellite data.

Evaluating MODIS snow products for modelling snowmelt runoff: case study of the Rio Grande headwaters

USDA-ARS?s Scientific Manuscript database

Snow-covered area (SCA) is a key variable in the Snowmelt-Runoff Model (SRM). Landsat Thematic Mapper (TM) or Operational Land Imager (OLI) provide remotely sensed data at an appropriate spatial resolution for mapping SCA in small headwater basins, but the temporal resolution of the data is low and ...

The next Landsat satellite; the Landsat Data Continuity Mission

USGS Publications Warehouse

Irons, James R.; Dwyer, John L.; Barsi, Julia A.

2012-01-01

The National Aeronautics and Space Administration (NASA) and the Department of Interior United States Geological Survey (USGS) are developing the successor mission to Landsat 7 that is currently known as the Landsat Data Continuity Mission (LDCM). NASA is responsible for building and launching the LDCM satellite observatory. USGS is building the ground system and will assume responsibility for satellite operations and for collecting, archiving, and distributing data following launch. The observatory will consist of a spacecraft in low-Earth orbit with a two-sensor payload. One sensor, the Operational Land Imager (OLI), will collect image data for nine shortwave spectral bands over a 185 km swath with a 30 m spatial resolution for all bands except a 15 m panchromatic band. The other instrument, the Thermal Infrared Sensor (TIRS), will collect image data for two thermal bands with a 100 m resolution over a 185 km swath. Both sensors offer technical advancements over earlier Landsat instruments. OLI and TIRS will coincidently collect data and the observatory will transmit the data to the ground system where it will be archived, processed to Level 1 data products containing well calibrated and co-registered OLI and TIRS data, and made available for free distribution to the general public. The LDCM development is on schedule for a December 2012 launch. The USGS intends to rename the satellite "Landsat 8" following launch. By either name a successful mission will fulfill a mandate for Landsat data continuity. The mission will extend the almost 40-year Landsat data archive with images sufficiently consistent with data from the earlier missions to allow long-term studies of regional and global land cover change.

Influence of temperature and the role of chromium on the kinetics of sulfidation of 310 stainless steel

NASA Technical Reports Server (NTRS)

Rao, D. B.; Nelson, H. G.

1977-01-01

The sulfidation of 310 stainless steel was studied over the temperature range from 910 K to 1285 K. By adjusting the ratio of hydrogen sulfide, variations in sulfur potential were obtained. The effect of temperature on sulfidation was determined at three different sulfur potentials: 39/sqNm, 0.014/sqNm, and 0.00015/sqNm. All sulfide scales contained one or two surface layers in addition to a subscale. The second outer layer (OL-II), furthest from the alloy, contained primarily Fe-Ni-S. The first outer layer (OL-I), nearest the subscale, contained FE-Cr-S. The subscale consisted of sulfide inclusions in the metal matrix. At a given temperature and sulfur potential, the weight gain data obeyed the parabolic rate law after an initial transient period. The parabolic rate constants obtained at the sulfur potential of 39/sqNm did not show a break when the logarithm of the rate constant was plotted as a function of the inverse of absolute temperature. Sulfidation carried out at sulfur potentials below 0.02/sqNm, however, did show a break at 1145 K, which is termed as the transition temperature. This break was found to be associated with the changes which had occurred in the Fe:Cr ratio of OL-I. Below the transition temperature the activation energy was found to be approximately 125 kj/mole. Above the transition temperature the rate of sulfidation decreased with temperature but dependent on the Fe:Cr ratio in the iron-chromium-sulfide layers of the OL-I. A reaction mechanism consistent with the experimental results has been proposed.

Quality assessment of the Harmonized Landsat and Sentinel-2 (HLS) data set

NASA Astrophysics Data System (ADS)

Masek, J. G.; Claverie, M.; Ju, J.; Vermote, E.

2017-12-01

The Harmonized Landsat and Sentinel-2 (HLS) project is a NASA initiative aiming to produce a compatible surface reflectance (SR) data set from a virtual constellation consisting of the US Landsat-8 and the European Sentinel-2 satellites. The creation of such a long-term surface reflectance data record requires the development and implementation of Quality assessment (QA) methods to evaluate the quality of the product. QA is built as an integral part of the HLS production chain. The QA includes three components: (i) the comparison of the HLS data with MODIS data, (ii) an analysis of the geometric accuracy of the Landsat-8 OLI and Sentinel-2 MSI Level-1 products, and (iii) an evaluation of the temporal consistency of the HLS products.The methodology of the cross-comparison of the HLS product with MODIS products was introduced by Claverie et al. (2015, RSE, vol. 169). It consists in comparing HLS SR (L30 products for Landsat-8 and S30 products for Sentinel-2) with MODIS SR (MOD09CMG), after adjustment of sun-view geometry and bandpass differences. The overall uncertainties and biases between MODIS and HLS SR do not exceed, depending on the band (excluding blue bands), 9% and 3%, respectively. No significant spatial or temporal patterns were identified. The most important source of uncertainty comes from the cloud detection omission on the MSI data.The HLS and Level-1 products geometric accuracy was assessed and improved using the automated registration and orthorectification package, AROP (Gao et al., 2009, SPIE JARS, vol. 3). The use of AROP reduces the geometric co-registration error in Level-1 products by about 40% and 60% during HLS processing of OLI and MSI, respectively. The final CE-90 are 6.2 m and 18.8 m, for HLS MSI (computed with 10m pixels) and OLI (30 m pixels), respectively.Finally, the time series (TS) smoothness of the data set was analyzed by computing the time series noise (Vermote et al., 2009, TGRS, vol. 47). We showed that major issue is related

JPRS Report, East Europe.

DTIC Science & Technology

1990-02-05

Jersey, Philadelphia, Chicago, and to Ismet Abdulahu, Hasan Ramadani , and Haljimi Mrati Canada, to organize receptions and parties for Yugoslav had fled...by (rhetorical) attack. When they did He com h course o studie at tecelopoeit-not avethe ourge-te oly nes n Eropeto ign He completed the course of

The Open Learning Initiative: New Directions for Higher Education.

ERIC Educational Resources Information Center

King, Bruce

This paper describes the Australian Open Learning Initiative (OLI), a program to facilitate access to postsecondary education. The program will provide off-campus or distance education courses for which there is evident high demand. Program features include an independent brokering agency, coordination by a university or group of universities,…

Identification of stand age in rubber plantations using time series Landsat and PALSAR-2 data

NASA Astrophysics Data System (ADS)

Chen, B.; Wu, Z.; Xiao, X.; Li, X.; Ma, J.; Lan, G.; Yang, C.; Xie, G.; Dong, J.; Qin, Y.

2016-12-01

Stand age of rubber plantation is vital for optimal plantation management such as fertilization, prediction of latex yield and timber production. It is also an important variable for biomass estimation and determining the distribution of carbon pools and fluxes in rubber plantation ecosystem. Benefit from the traits of large coverage, high speed, and low-cost, satellite remote sensing techniques have been serviced as a major approach to map acreage and stand age of forest and plantations. Despite a number of studies working on acreage and stand age mapping, the stand age information of rubber plantation is still poorly available at regional scale. In this study, the 25-m cloud-free Phased Array type L-band Synthetic Aperture Radar 2 (PALSAR-2) mosaic product, together with the 30-m time series images of Landsat 7 Enhanced Thematic Mapper Plus (ETM+) and Landsat 8 Operational Land Imager (OLI), were used to map stand age of rubber plantation in China under Google Earth Engine computing platform. Rubber plantation in 2015 were first identified by structural information in PALSAR-2 and phenological and spectral signatures (deciduous, rapid change of canopies during rubber defoliation and foliation periods, and dense canopy in growing season) that derived from time series Landsat ETM+/OLI images. Based on the resultant rubber plantation map, we then successfully identified the stand age of rubber plantation using land cover transfer information during rubber seeding cultivation period, specifically, by yearly composited Land Surface Water Index (LSWI) of Landsat TM/ETM+/OLI images since 1985. The estimated stand age has very high accuracy with Root Square Mean Error (RMSE) less than 2 years. The resultant rubber stand age information are likely to be useful for sustainable plantation management and ecological assessment, and the methodology can be extendable for applications in other regions.

Next Generation Landsat Products Delivered Using Virtual Globes and OGC Standard Services

NASA Astrophysics Data System (ADS)

Neiers, M.; Dwyer, J.; Neiers, S.

2008-12-01

The Landsat Data Continuity Mission (LDCM) is the next in the series of Landsat satellite missions and is tasked with the objective of delivering data acquired by the Operational Land Imager (OLI). The OLI instrument will provide data continuity to over 30 years of global multispectral data collected by the Landsat series of satellites. The U.S. Geological Survey Earth Resources Observation and Science (USGS EROS) Center has responsibility for the development and operation of the LDCM ground system. One of the mission objectives of the LDCM is to distribute OLI data products electronically over the Internet to the general public on a nondiscriminatory basis and at no cost. To ensure the user community and general public can easily access LDCM data from multiple clients, the User Portal Element (UPE) of the LDCM ground system will use OGC standards and services such as Keyhole Markup Language (KML), Web Map Service (WMS), Web Coverage Service (WCS), and Geographic encoding of Really Simple Syndication (GeoRSS) feeds for both access to and delivery of LDCM products. The USGS has developed and tested the capabilities of several successful UPE prototypes for delivery of Landsat metadata, full resolution browse, and orthorectified (L1T) products from clients such as Google Earth, Google Maps, ESRI ArcGIS Explorer, and Microsoft's Virtual Earth. Prototyping efforts included the following services: using virtual globes to search the historical Landsat archive by dynamic generation of KML; notification of and access to new Landsat acquisitions and L1T downloads from GeoRSS feeds; Google indexing of KML files containing links to full resolution browse and data downloads; WMS delivery of reduced resolution browse, full resolution browse, and cloud mask overlays; and custom data downloads using WCS clients. These various prototypes will be demonstrated and LDCM service implementation plans will be discussed during this session.

Comparison of Landsat-8 and Sentinel-2A reflectance and normalized difference vegetation index

NASA Astrophysics Data System (ADS)

Zhang, H.; Roy, D. P.; Yan, L.; Li, Z.; Huang, H.

2017-12-01

The moderate spatial resolution satellite data from the polar-orbiting Landsat-8 (launched 2013) and Sentinel-2A (launched 2015) sensors provide 10 m to 30 m multi-spectral global coverage with a better than 5-day revisit. Although a national laboratory traceable cross-calibration comparison of the Landsat-8 Operational Land Imager (OLI) and the Sentinel-2A MultiSpectral Instrument (MSI) was undertaken pre-launch, there are a number of other sensor differences, notably due to spectral, spatial and angular differences. To examine these in a comprehensive way, Landsat-8 and Sentinel-2A data for approximately 20° × 10° of southern Africa acquired in the summer (January to March) and winter (July to September) of 2016 were compared. Only Landsat-8 and Sentinel-2A observations acquired within one-day apart were considered. The sensor data were registered and then each orbit projected into 30 m fixed global Web Enabled Landsat Data (GWELD) tiles defined in the MODIS sinusoidal equal area projection. Only corresponding sensor observations of each 30 m tile pixel that were flagged as cloud and snow-free, unsaturated, and that had no significant change in their one day separation, were compared. Both the Landsat-8 and Sentinel-2A data were atmospherically corrected using the Landsat Surface Reflectance Code (LaSRC) and were also corrected to nadir BRDF adjusted reflectance (NBAR). Top of atmosphere and surface reflectance for the spectrally corresponding visible, near infrared and shortwave infrared OLI and MSI bands, and derived normalized difference vegetation index (NDVI), were compared and their differences quantified using regression analyses. The resulting statistical transformations may be used to improve the consistency between the Landsat-8 OLI and Sentinel-2A MSI data. The importance and sensitivity of the results to correct filtering, atmospheric correction and adjustment to NBAR is demonstrated.

Knowledge-based decision tree approach for mapping spatial distribution of rice crop using C-band synthetic aperture radar-derived information

NASA Astrophysics Data System (ADS)

Mishra, Varun Narayan; Prasad, Rajendra; Kumar, Pradeep; Srivastava, Prashant K.; Rai, Praveen Kumar

2017-10-01

Updated and accurate information of rice-growing areas is vital for food security and investigating the environmental impact of rice ecosystems. The intent of this work is to explore the feasibility of dual-polarimetric C-band Radar Imaging Satellite-1 (RISAT-1) data in delineating rice crop fields from other land cover features. A two polarization combination of RISAT-1 backscatter, namely ratio (HH/HV) and difference (HH-HV), significantly enhanced the backscatter difference between rice and nonrice categories. With these inputs, a QUEST decision tree (DT) classifier is successfully employed to extract the spatial distribution of rice crop areas. The results showed the optimal polarization combination to be HH along with HH/HV and HH-HV for rice crop mapping with an accuracy of 88.57%. Results were further compared with a Landsat-8 operational land imager (OLI) optical sensor-derived rice crop map. Spatial agreement of almost 90% was achieved between outputs produced from Landsat-8 OLI and RISAT-1 data. The simplicity of the approach used in this work may serve as an effective tool for rice crop mapping.

Future of Land Remote Sensing: What is Needed

NASA Technical Reports Server (NTRS)

Goward, Samuel N.

2007-01-01

A viewgraph presentation describing the future of land remote sensing and the new technologies needed for clear views of the Earth is shown. The contents include: 1) Viewing the Earth; 2) Multi-Imagery; 3) May Missions and Sensors; 4) What is Needed; 5) Things to Think About; 6) Global Land Remote Sensing in Landsat 7 Era; 7) Seasonality; 8) Cloud Contamination; 9) NRC Decadal Study; 10) Atmospheric Attenuation; 11) Geo-Registration; 12) Orthorectification Required; 13) Band Registration with OLI; and 14) Things to Do. A viewgraph presentation describing the future of land remote sensing and the new technologies needed for clear views of the Earth is shown. The contents include: 1) Viewing the Earth; 2) Multi-Imagery; 3) May Missions and Sensors; 4) What is Needed; 5) Things to Think About; 6) Global Land Remote Sensing in Landsat 7 Era; 7) Seasonality; 8) Cloud Contamination; 9) NRC Decadal Study; 10) Atmospheric Attenuation; 11) Geo-Registration; 12) Orthorectification Required; 13) Band Registration with OLI; and 14) Things to Do.

Optimization of an organic yogurt based on sensorial, nutritional, and functional perspectives.

PubMed

Karnopp, Ariadne Roberto; Oliveira, Katherine Guimarães; de Andrade, Eriel Forville; Postingher, Bruna Mara; Granato, Daniel

2017-10-15

The effects of purple grape juice (PGJ), grape skin flour (GSF), and oligofructose (OLI) on proximate composition, total phenolic content (TPC), antioxidant activity (AA), sensory, physicochemical, and textural properties of yogurts were analyzed using response surface methodology. Multiple regression models were proposed and results showed that PGJ increased the viscosity, AA, and TPC, while GSF increased the ash and total fiber contents of yogurts. GSF and OLI increased the hardness and consistency. A simultaneous optimization was performed to maximize TPC, ash and fibers contents, and sensory acceptance: a yogurt containing 1.7% GSF and 8.0% PGJ had a high fiber (5.60±0.13%) and ash (0.76±0.02%) contents, TPC (28.32±2.10mg GAE/100g), AA toward DPPH (57.85±1.36mg AAE/100g), and total reducing capacity (28.86±5.19mg QE/100g). The optimized yogurt had 79% acceptability index, indicating the use of PGJ and GSF is a feasible alternative to increase the functional properties of yogurts. Copyright © 2017 Elsevier Ltd. All rights reserved.

East Peak Fire Burn Scar, Colorado [annotated

NASA Image and Video Library

2017-12-08

On June 22, 2013, the Operational Land Imager (OLI) on Landsat 8 captured this false-color image of the East Peak fire burning in southern Colorado near Trinidad. Burned areas appear dark red, while actively burning areas look orange. Dark green areas are forests; light green areas are grasslands. Lightning ignited the blaze on June 19, 2013. By June 25, it had burned nearly 13,500 acres (5,500 hectares). NASA Earth Observatory image by Jesse Allen and Robert Simmon, using Landsat data from the U.S. Geological Survey. Caption by Adam Voiland. Instrument: Landsat 8 - OLI More images from this event: 1.usa.gov/14DesQC Credit: NASA Earth Observatory NASA image use policy. NASA Goddard Space Flight Center enables NASA’s mission through four scientific endeavors: Earth Science, Heliophysics, Solar System Exploration, and Astrophysics. Goddard plays a leading role in NASA’s accomplishments by contributing compelling scientific knowledge to advance the Agency’s mission. Follow us on Twitter Like us on Facebook Find us on Instagram

East Peak Fire Burn Scar, Colorado [high res

NASA Image and Video Library

2017-12-08

On June 22, 2013, the Operational Land Imager (OLI) on Landsat 8 captured this false-color image of the East Peak fire burning in southern Colorado near Trinidad. Burned areas appear dark red, while actively burning areas look orange. Dark green areas are forests; light green areas are grasslands. Lightning ignited the blaze on June 19, 2013. By June 25, it had burned nearly 13,500 acres (5,500 hectares). NASA Earth Observatory image by Jesse Allen and Robert Simmon, using Landsat data from the U.S. Geological Survey. Caption by Adam Voiland. Instrument: Landsat 8 - OLI More images from this event: 1.usa.gov/14DesQC Credit: NASA Earth Observatory NASA image use policy. NASA Goddard Space Flight Center enables NASA’s mission through four scientific endeavors: Earth Science, Heliophysics, Solar System Exploration, and Astrophysics. Goddard plays a leading role in NASA’s accomplishments by contributing compelling scientific knowledge to advance the Agency’s mission. Follow us on Twitter Like us on Facebook Find us on Instagram

Data Quality Evaluation and Application Potential Analysis of TIANGONG-2 Wide-Band Imaging Spectrometer

NASA Astrophysics Data System (ADS)

Qin, B.; Li, L.; Li, S.

2018-04-01

Tiangong-2 is the first space laboratory in China, which launched in September 15, 2016. Wide-band Imaging Spectrometer is a medium resolution multispectral imager on Tiangong-2. In this paper, the authors introduced the indexes and parameters of Wideband Imaging Spectrometer, and made an objective evaluation about the data quality of Wide-band Imaging Spectrometer in radiation quality, image sharpness and information content, and compared the data quality evaluation results with that of Landsat-8. Although the data quality of Wide-band Imager Spectrometer has a certain disparity with Landsat-8 OLI data in terms of signal to noise ratio, clarity and entropy. Compared with OLI, Wide-band Imager Spectrometer has more bands, narrower bandwidth and wider swath, which make it a useful remote sensing data source in classification and identification of large and medium scale ground objects. In the future, Wide-band Imaging Spectrometer data will be widely applied in land cover classification, ecological environment assessment, marine and coastal zone monitoring, crop identification and classification, and other related areas.

Cost Improvement Analysis

DTIC Science & Technology

1986-06-01

Cc) Ul y Cli U;ra ISO or.) . ............ t cc fl .9 it it ý I oli CC) I it cli L3 I HIM .......... 114 t4l t.r IM...Burroughz Cost AFIT/LSQ AV785-6280 Curve Programs Prof. Jeff Daneman Z-100 Cost Curve ASD/ACCR AV785- 8583 Programs Capt Arthur Mills * *- PROGRAMS CONCEPT

Grounding Lines Detecting Using LANDSAT8 Oli and CRYOSAT-2 Data Fusion

NASA Astrophysics Data System (ADS)

Li, F.; Guo, Y.; Zhang, Y.; Zhang, S.

2018-04-01

The grounding zone is the region where ice transitions from grounded ice sheet to freely floating ice shelf, grounding lines are actually more of a zone, typically over several kilometers. The mass loss from Antarctica is strongly linked to changes in the ice shelves and their grounding lines, since the variation in the grounding line can result in very rapid changes in glacier and ice-shelf behavior. Based on remote sensing observations, five global Antarctic grounding line products have been released internationally, including MOA, ASAID, ICESat, MEaSUREs, and Synthesized grounding lines. However, the five products could not provide the annual grounding line products of the whole Antarctic, even some products have stopped updating, which limits the time series analysis of Antarctic material balance to a certain extent. Besides, the accurate of single remote-sensing data based grounding line products is far from satisficed. Therefore, we use algorithms to extract grounding lines with SAR and Cryosat-2 data respectively, and combine the results of two kinds of grounding lines to obtain new products, we obtain a mature grounding line extraction algorithm process, so that we can realize the extraction of grounding line of the Antarctic each year in the future. The comparison between fusion results and the MOA product results indicate that there is a maximum deviation of 188.67 meters between the MOA product and the fusion result.

Time Series Reconstruction of Surface Flow Velocity on Marine-terminating Outlet Glaciers

NASA Astrophysics Data System (ADS)

Jeong, Seongsu

The flow velocity of glacier and its fluctuation are valuable data to study the contribution of sea level rise of ice sheet by understanding its dynamic structure. Repeat-image feature tracking (RIFT) is a platform-independent, feature tracking-based velocity measurement methodology effective for building a time series of velocity maps from optical images. However, limited availability of perfectly-conditioned images motivated to improve robustness of the algorithm. With this background, we developed an improved RIFT algorithm based on multiple-image multiple-chip algorithm presented in Ahn and Howat (2011). The test results affirm improvement in the new RIFT algorithm in avoiding outlier, and the analysis of the multiple matching results clarified that each individual matching results worked in complementary manner to deduce the correct displacements. LANDSAT 8 is a new satellite in LANDSAT program that has begun its operation since 2013. The improved radiometric performance of OLI aboard the satellite is expected to enable better velocity mapping results than ETM+ aboard LANDSAT 7. However, it was not yet well studied that in what cases the new will sensor will be beneficial, and how much the improvement will be obtained. We carried out a simulation-based comparison between ETM+ and OLI and confirmed OLI outperforms ETM+ especially in low contrast conditions, especially in polar night, translucent cloud covers, and bright upglacier with less texture. We have identified a rift on ice shelf of Pine island glacier located in western Antarctic ice sheet. Unlike the previous events, the evolution of the current started from the center of the ice shelf. In order to analyze this unique event, we utilized the improved RIFT algorithm to its OLI images to retrieve time series of velocity maps. We discovered from the analyses that the part of ice shelf below the rift is changing its speed, and shifting of splashing crevasses on shear margin is migrating to the center of the

U.S. EPA, Pesticide Product Label, PRENTOX METHOXYCHLOR 50W, 10/06/1982

EPA Pesticide Factsheets

2011-04-14

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Burlington IAP, Vermont. Revised Uniform Summary of Surface Weather Observations (RUSSWO). Parts A-F.

DTIC Science & Technology

1981-12-23

34~ ~ ~ ~ ~ ~ ~ ~ ~~ ~A .... . ... .. . .. ... ... . . .. . .. ........ . . . . . . .. ’_L ’,AL CLIŘATOLOGY FRANCH 7AC SURFACE WINDS S A T,-.ŕ SERVICM/MAC...72 C USAP ETAC 0-1-5n (a.. A) ..vWW... 1394""S "IS FOOD ~~ ADS 00OLI *L ,AL CLIMATOLOGY BRANCH uSAFETAC CEILING VERSUS VISIBILITY A7. EATHER SERVICE/MAC

Landsat-8: Status and on-orbit performance

USGS Publications Warehouse

Markham, Brian L; Barsi, Julia A.; Morfitt, Ron; Choate, Michael J.; Montanaro, Matthew; Arvidson, Terry; Irons, James R.

2015-01-01

Landsat 8 and its two Earth imaging sensors, the Operational Land Imager (OLI) and Thermal Infrared Sensor (TIRS) have been operating on-orbit for 2 ½ years. Landsat 8 has been acquiring substantially more images than initially planned, typically around 700 scenes per day versus a 400 scenes per day requirement, acquiring nearly all land scenes. Both the TIRS and OLI instruments are exceeding their SNR requirements by at least a factor of 2 and are very stable, degrading by at most 1% in responsivity over the mission to date. Both instruments have 100% operable detectors covering their cross track field of view using the redundant detectors as necessary. The geometric performance is excellent, meeting or exceeding all performance requirements. One anomaly occurred with the TIRS Scene Select Mirror (SSM) encoder that affected its operation, though by switching to the side B electronics, this was fully recovered. The one challenge is with the TIRS stray light, which affects the flat fielding and absolute calibration of the TIRS data. The error introduced is smaller in TIRS band 10. Band 11 should not currently be used in science applications.

Geospatial approach towards enumerative analysis of suspended sediment concentration for Ganges-Brahmaputra Bay

NASA Astrophysics Data System (ADS)

Pandey, Palak; Kunte, Pravin D.

2016-10-01

This study presents an easy, modular, user-friendly, and flexible software package for processing of Landsat 7 ETM and Landsat 8 OLI-TIRS data for estimating suspended particulate matter concentrations in the coastal waters. This package includes 1) algorithm developed using freely downloadable SCILAB package, 2) ERDAS Models for iterative processing of Landsat images and 3) ArcMAP tool for plotting and map making. Utilizing SCILAB package, a module is written for geometric corrections, radiometric corrections and obtaining normalized water-leaving reflectance by incorporating Landsat 8 OLI-TIRS and Landsat 7 ETM+ data. Using ERDAS models, a sequence of modules are developed for iterative processing of Landsat images and estimating suspended particulate matter concentrations. Processed images are used for preparing suspended sediment concentration maps. The applicability of this software package is demonstrated by estimating and plotting seasonal suspended sediment concentration maps off the Bengal delta. The software is flexible enough to accommodate other remotely sensed data like Ocean Color monitor (OCM) data, Indian Remote Sensing data (IRS), MODIS data etc. by replacing a few parameters in the algorithm, for estimating suspended sediment concentration in coastal waters.

A Multiscale Mapping Assessment of Lake Champlain Cyanobacterial Harmful Algal Blooms

PubMed Central

Torbick, Nathan; Corbiere, Megan

2015-01-01

Lake Champlain has bays undergoing chronic cyanobacterial harmful algal blooms that pose a public health threat. Monitoring and assessment tools need to be developed to support risk decision making and to gain a thorough understanding of bloom scales and intensities. In this research application, Landsat 8 Operational Land Imager (OLI), Rapid Eye, and Proba Compact High Resolution Imaging Spectrometer (CHRIS) images were obtained while a corresponding field campaign collected in situ measurements of water quality. Models including empirical band ratio regressions were applied to map chlorophyll-a and phycocyanin concentrations; all sensors performed well with R2 and root-mean-square error (RMSE) ranging from 0.76 to 0.88 and 0.42 to 1.51, respectively. The outcomes showed spatial patterns across the lake with problematic bays having phycocyanin concentrations >25 µg/L. An alert status metric tuned to the current monitoring protocol was generated using modeled water quality to illustrate how the remote sensing tools can inform a public health monitoring system. Among the sensors utilized in this study, Landsat 8 OLI holds the most promise for providing exposure information across a wide area given the resolutions, systematic observation strategy and free cost. PMID:26389930

VUV/XUV measurements of impurity emission in plasmas with liquid lithium surfaces on LTX [VUV/XUV measurements of low recycling plasmas with liquid lithium surfaces on LTX

DOE PAGES

Tritz, Kevin; Bell, Ronald E.; Beiersdorfer, Peter; ...

2014-11-12

The VUV/XUV spectrum has been measured on the Lithium Tokamak eXperiment (LTX) using a transmission grating imaging spectrometer (TGIS) coupled to a direct-detection x-ray charge-coupled device camera. TGIS data show significant changes in the ratios between the lithium and oxygen impurity line emission during discharges with varying lithium wall conditions. Lithium coatings that have been passivated by lengthy exposure to significant levels of impurities contribute to a large O/Li ratio measured during LTX plasma discharges. Furthermore, previous results have indicated that a passivated lithium film on the plasma facing components will function as a stronger impurity source when in themore » form of a hot liquid layer compared to a solid lithium layer. However, recent TGIS measurements of plasma discharges in LTX with hot stainless steel boundary shells and a fresh liquid lithium coating show lower O/Li impurity line ratios when compared to discharges with a solid lithium film on cool shells. In conclusion, these new measurements help elucidate the somewhat contradictory results of the effects of solid and liquid lithium on plasma confinement observed in previous experiments.« less

Shape-from-shading using Landsat 8 and airborne laser altimetry over ice sheets: toward new regional DEMs of Greenland and Antarctica

NASA Astrophysics Data System (ADS)

Moussavi, M. S.; Scambos, T.; Haran, T. M.; Klinger, M. J.; Abdalati, W.

2015-12-01

We investigate the capability of Landsat 8's Operational Land Imager (OLI) instrument to quantify subtle ice sheet topography of Greenland and Antarctica. We use photoclinometry, or 'shape-from-shading', a method of deriving surface topography from local variations in image brightness due to varying surface slope. Photoclinomeetry is applicable over ice sheet areas with highly uniform albedo such as regions covered by recent snowfall. OLI imagery is available from both ascending and descending passes near the summer solstice period for both ice sheets. This provides two views of the surface features from two distinct solar azimuth illumination directions. Airborne laser altimetry data from the Airborne Topographic Mapper (ATM) instrument (flying on the Operation Ice Bridge program) are used to quantitatively convert the image brightness variations of surface undulations to surface slope. To validate the new DEM products, we use additional laser altimetry profiles collected over independent sites from Ice Bridge and ICESat, and high-resolution WorldView-2 DEMs. The photoclinometry-derived DEM products will be useful for studying surface elevation changes, enhancing bedrock elevation maps through inversion of surface topography, and inferring local variations in snow accumulation rates.

A comparison of different radiative transfer model inversion methods for canopy water content retrieval

NASA Astrophysics Data System (ADS)

Boren, E. J.; Boschetti, L.; Johnson, D.

2016-12-01

With near-future droughts predicted to become both more frequent and more intense (Allen et al. 2015, Diffenbaugh et al. 2015), the estimation of satellite-derived vegetation water content would benefit a wide range of environmental applications including agricultural, vegetation, and fire risk monitoring. No vegetation water content thematic product is currently available (Yebra et al. 2013), but the successful launch of the Landsat 8 OLI and Sentinel 2A satellites, and the forthcoming Sentinel 2B, provide the opportunity for monitoring biophysical variables at a scale (10-30m) and temporal resolution (5 days) needed by most applications. Radiative transfer models (RTM) use a set of biophysical parameters to produce an estimated spectral response and - when used in inverse mode - provide a way to use satellite spectral data to estimate vegetation biophysical parameters, including water content (Zarco-Tejada et al. 2003). Using the coupled leaf and canopy level model PROSAIL5, and Landsat 8 OLI and Sentinel 2A MSI optical satellite data, the present research compares the results of three model inversion techniques: iterative optimization (OPT), look-up table (LUT), and artificial neural network (ANN) training. Ancillary biophysical data, needed for constraining the inversion process, were collected from various crop species grown in a controlled setting and under different water stress conditions. The measurements included fresh weight, dry weight, leaf area, and spectral leaf transmittance and reflectance in the 350-2500 nm range. Plot-level data, collected coincidently with satellite overpasses during three summer field campaigns in northern Idaho (2014 to 2016), are used to evaluate the results of the model inversion. Field measurements included fresh weight, dry weight, leaf area index, plant height, and top of canopy reflectance in the 350-2500 nm range. The results of the model inversion intercomparison exercised are used to characterize the uncertainties of

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Retrieval of Spatio-temporal Evaporation by Integrating Landsat OLI Optical and Thermal Data

NASA Astrophysics Data System (ADS)

Wandera, L. N.; Tol, C. V. D.; Mallick, K.; Bayat, B.; Verbeiren, B.; van Griensven, A.; Verhoef, W.; Suliga, J.; Barrios, J. M.; Chormański, J.; Kleniewska, M.

2017-12-01

Soil-Vegetation-Atmosphere (SVAT) Transfer Models are capable of providing continuous predictions of evapotranspiration (ET). However, providing these models with reliable spatio-temporal information of vegetation and soil properties remains challenging. Thus, combining optical and thermal satellite information might assists to overcome this challenge when using SVAT models. In this study, using a radiative transfer model of solar and sky radiation (RTMo), we simulate Landsat 8 reflectance bands (2-7). We then apply a numerical optimization approach to invert the model and retrieve the corresponding canopy attributes leaf chlorophyll content (Cab), leaf water content (Cw), leaf dry matter content (Cdm), leaf brown material (Cs), Leaf Area Index (LAI) and the leaf angle distribution function in the canopy at overpass time. The retrievals are then directly used as inputs into our SVAT model of choice, Soil Canopy Observations of Photochemistry and Energy Fluxes (SCOPE). Using a model for transfer of thermal radiation emitted by vegetation and soil (RTMt), we proceed to simulate Landsat radiance for the corresponding reflectance data using a lookup table (LUT). These variables were then used to develop a crop factor (Kc) map. A reference ET was generated and applied to the Kc map to obtain actual ET. We proceeded to interpolate the ET between the image acquisition dates to have a complete time series. The retrieval maps for the specific variables captured seasonal variability patterns for the respective variables. The generated KC map showed similar trend with the LAI maps. There was an underestimation of actual ET when the simulation was not constrained to the thermal information. The interpolation of ET between acquisition image dates reflected the seasonal trends. Key Word: SVAT, optical, thermal, remote sensing, evapotranspiration

Waterborne Commerce of the United States, Calendar Year 1980. Part 5. National Summaries.

DTIC Science & Technology

1982-09-01

elsewhere classified 2915 Residual fuel oil 2021 Dairy products, except dried silk and cream 2916 Lubricating olis and greae 2022 Dried milk and cres...136,29 63994 ..3 4 1 6 4--------------------- 2022 DRIED MILK miD CREAM .---------- 184.069 2 01 ...4 390 1.132--------------------- 2631 RIlM ANo S...2021 DAIRY PRODUCTS, NEC ----------------------------------------------------------------- 1,49 136.24 14.300 2022 DM11) MILK AND0 CREAM

National Dam Safety Program. Lake Muskoday Dam (Inventory Number N.Y. 341) Delaware River Basin, Sullivan County, New York. Phase I Inspection Report,

DTIC Science & Technology

1981-09-14

DACW-51-81-C-0006 . PERFORMING ORGANIZATION NAME AND ADDRESS 10. PROGRAM ELEMENT PROJECT. TASK AREA & WORK UNIT NUMBERS ~ Flaherty-Giauara Associates...olie It neceary and Idontily b block number) Dam Safety National Dam Safety Program Visual Inspection Lake Muskoday Dam Hydrology, Structural Stability...DELAWARE RIVER BASIN LAKE MUSKODAY DAM SULLIVAN COUNTY, NEW YORK INVENTORY No.NY341 PHASE I INSPECTION REPORT NATIONAL DAM SAFETY PROGRAM J T C NEW YORK

A Commensal Gone Bad: Complete Genome Sequence of the Prototypical Enterotoxigenic Escherichia coli Strain H10407

DTIC Science & Technology

2010-11-01

and Escherichia ferguso- . TABLE 2. General characteristics of the plasm ids from ETEC strains H10407 and E1392/75 Value in E. c·oli: Characteristic...0352). consetved proteins with unknown func- tions (CDSs 0673 to 0678), a flavoprotein electron transfer system (CDSs 1730 to 1734), the colanic...mediating diarrhea are not chromosomally encoded. indicating that the essential virulence factors are encoded on the plasm ids (61 ). Potentia l

Machine vision systems using machine learning for industrial product inspection

NASA Astrophysics Data System (ADS)

Lu, Yi; Chen, Tie Q.; Chen, Jie; Zhang, Jian; Tisler, Anthony

2002-02-01

Machine vision inspection requires efficient processing time and accurate results. In this paper, we present a machine vision inspection architecture, SMV (Smart Machine Vision). SMV decomposes a machine vision inspection problem into two stages, Learning Inspection Features (LIF), and On-Line Inspection (OLI). The LIF is designed to learn visual inspection features from design data and/or from inspection products. During the OLI stage, the inspection system uses the knowledge learnt by the LIF component to inspect the visual features of products. In this paper we will present two machine vision inspection systems developed under the SMV architecture for two different types of products, Printed Circuit Board (PCB) and Vacuum Florescent Displaying (VFD) boards. In the VFD board inspection system, the LIF component learns inspection features from a VFD board and its displaying patterns. In the PCB board inspection system, the LIF learns the inspection features from the CAD file of a PCB board. In both systems, the LIF component also incorporates interactive learning to make the inspection system more powerful and efficient. The VFD system has been deployed successfully in three different manufacturing companies and the PCB inspection system is the process of being deployed in a manufacturing plant.

Oligodendroglial p130Cas Is a Target of Fyn Kinase Involved in Process Formation, Cell Migration and Survival

PubMed Central

Gonsior, Constantin; Binamé, Fabien; Frühbeis, Carsten; Bauer, Nina M.; Hoch-Kraft, Peter; Luhmann, Heiko J.; Trotter, Jacqueline; White, Robin

2014-01-01

Oligodendrocytes are the myelinating glial cells of the central nervous system. In the course of brain development, oligodendrocyte precursor cells migrate, scan the environment and differentiate into mature oligodendrocytes with multiple cellular processes which recognize and ensheath neuronal axons. During differentiation, oligodendrocytes undergo dramatic morphological changes requiring cytoskeletal rearrangements which need to be tightly regulated. The non-receptor tyrosine kinase Fyn plays a central role in oligodendrocyte differentiation and myelination. In order to improve our understanding of the role of oligodendroglial Fyn kinase, we have identified Fyn targets in these cells. Purification and mass-spectrometric analysis of tyrosine-phosphorylated proteins in response to overexpressed active Fyn in the oligodendrocyte precursor cell line Oli-neu, yielded the adaptor molecule p130Cas. We analyzed the function of this Fyn target in oligodendroglial cells and observed that reduction of p130Cas levels by siRNA affects process outgrowth, the thickness of cellular processes and migration behavior of Oli-neu cells. Furthermore, long term p130Cas reduction results in decreased cell numbers as a result of increased apoptosis in cultured primary oligodendrocytes. Our data contribute to understanding the molecular events taking place during oligodendrocyte migration and morphological differentiation and have implications for myelin formation. PMID:24586768

Remote Sensing-Based Quantification of the Impact of Flash Flooding on the Rice Production: A Case Study over Northeastern Bangladesh

PubMed Central

Rahaman, Khan Rubayet; Kok, Aaron; Hassan, Quazi K.

2017-01-01

The northeastern region of Bangladesh often experiences flash flooding during the pre-harvesting period of the boro rice crop, which is the major cereal crop in the country. In this study, our objective was to delineate the impact of the 2017 flash flood (that initiated on 27 March 2017) on boro rice using multi-temporal Landsat-8 OLI and MODIS data. Initially, we opted to use Landsat-8 OLI data for mapping the damages; however, during and after the flooding event the acquisition of cloud free images were challenging. Thus, we used this data to map the cultivated boro rice acreage considering the planting to mature stages of the crop. Also, in order to map the extent of the damaged boro area, we utilized MODIS data as their 16-day composites provided cloud free information. Our results indicated that both the cultivated and damaged boro area estimates based on satellite data had strong relationships while compared to the ground-based estimates (i.e., r2 values approximately 0.92 for both cases, and RMSE of 18,374 and 9380 ha for cultivated and damaged areas, respectively). Finally, we believe that our study would be critical for planning and ensuring food security for the country. PMID:29036896

Remote Sensing-Based Quantification of the Impact of Flash Flooding on the Rice Production: A Case Study over Northeastern Bangladesh.

PubMed

Ahmed, M Razu; Rahaman, Khan Rubayet; Kok, Aaron; Hassan, Quazi K

2017-10-14

The northeastern region of Bangladesh often experiences flash flooding during the pre-harvesting period of the boro rice crop, which is the major cereal crop in the country. In this study, our objective was to delineate the impact of the 2017 flash flood (that initiated on 27 March 2017) on boro rice using multi-temporal Landsat-8 OLI and MODIS data. Initially, we opted to use Landsat-8 OLI data for mapping the damages; however, during and after the flooding event the acquisition of cloud free images were challenging. Thus, we used this data to map the cultivated boro rice acreage considering the planting to mature stages of the crop. Also, in order to map the extent of the damaged boro area, we utilized MODIS data as their 16-day composites provided cloud free information. Our results indicated that both the cultivated and damaged boro area estimates based on satellite data had strong relationships while compared to the ground-based estimates (i.e., r ² values approximately 0.92 for both cases, and RMSE of 18,374 and 9380 ha for cultivated and damaged areas, respectively). Finally, we believe that our study would be critical for planning and ensuring food security for the country.

IWO JIMA Campaign - Special Action Report

DTIC Science & Technology

1946-01-01

John L. Hurd, (337386), USMCR. Private First Class Samuel J. IMfl, (480055) USMICR. Private First Class Harlan E. Fa?_oj, (3212 43),USMC. Pharmacist Mate...USNR. Pharmacist Mateo Third Class Frank T. Austin, (826-24-99), USmN. Private First Class Eu-cno J. Cousin, (517406),US1ICR. Private First Class...Field Artillery Group consists of a medical officer (Lieut.Comdr.) and four Hospital corpsman (olie Chief Pharmacist ’iatc, and three Pharmacist

A Study of Computer Center Management

DTIC Science & Technology

1988-06-01

the United States and the rest of the western world and do not take into consideration the various economic and culture factors in developing countries...Mortagy, Thesis Advisor John B Isett, Second Reader David R. Whipple -airman Department of . .&;-sation Science mes M.mgen, Act ng Dean of nm_ Jon and oli...take into consideration the various economic and culture factors in developing countries. This thesis seeks to present a number of new techniques in

Integrating age in the detection and mapping of incongruous patches in coffee (Coffea arabica) plantations using multi-temporal Landsat 8 NDVI anomalies

NASA Astrophysics Data System (ADS)

Chemura, Abel; Mutanga, Onisimo; Dube, Timothy

2017-05-01

The development of cost-effective, reliable and easy to implement crop condition monitoring methods is urgently required for perennial tree crops such as coffee (Coffea arabica), as they are grown over large areas and represent long term and higher levels of investment. These monitoring methods are useful in identifying farm areas that experience poor crop growth, pest infestation, diseases outbreaks and/or to monitor response to management interventions. This study compares field level coffee mean NDVI and LSWI anomalies and age-adjusted coffee mean NDVI and LSWI anomalies in identifying and mapping incongruous patches across perennial coffee plantations. To achieve this objective, we first derived deviation of coffee pixels from the global coffee mean NDVI and LSWI values of nine sequential Landsat 8 OLI image scenes. We then evaluated the influence of coffee age class (young, mature and old) on Landsat-scale NDVI and LSWI values using a one-way ANOVA and since results showed significant differences, we adjusted NDVI and LSWI anomalies for age-class. We then used the cumulative inverse distribution function (α ≤ 0.05) to identify fields and within field areas with excessive deviation of NDVI and LSWI from the global and the age-expected mean for each of the Landsat 8 OLI scene dates spanning three seasons. Results from accuracy assessment indicated that it was possible to separate incongruous and healthy patches using these anomalies and that using NDVI performed better than using LSWI for both global and age-adjusted mean anomalies. Using the age-adjusted anomalies performed better in separating incongruous and healthy patches than using the global mean for both NDVI (Overall accuracy = 80.9% and 68.1% respectively) and for LSWI (Overall accuracy = 68.1% and 48.9% respectively). When applied to other Landsat 8 OLI scenes, the results showed that the proportions of coffee fields that were modelled incongruent decreased with time for the young age category and

Understanding the spatial distribution of eroded areas in the former rural homelands of South Africa: Comparative evidence from two new non-commercial multispectral sensors

NASA Astrophysics Data System (ADS)

Sepuru, Terrence Koena; Dube, Timothy

2018-07-01

In this study, we determine the most suitable multispectral sensor that can accurately detect and map eroded areas from other land cover types in Sekhukhune rural district, Limpopo Province, South Africa. Specifically, the study tested the ability of multi-date (wet and dry season) Landsat 8 OLI and Sentinel-2 MSI images in detecting and mapping eroded areas. The implementation was done, using a robust non-parametric classification ensemble: Discriminant Analysis (DA). Three sets of analysis were applied (Analysis 1: Spectral bands as independent dataset; Analysis 2: Spectral vegetation indices as independent and Analysis 3: Combined spectral bands and spectral vegetation indices). Overall classification accuracies ranging between 80% to 81.90% for MSI and 75.71%-80.95% for OLI were derived for the wet and dry season, respectively. The integration of spectral bands and spectral vegetation indices showed that Sentinel-2 (OA = 83, 81%), slightly performed better than Landsat 8, with 82, 86%. The use of bands and vegetation indices as independent dataset resulted in slightly weaker results for both sensors. Sentinel-2 MSI bands located in the NIR (0.785-0.900 μm), red edge (0.698-0.785 μm) and SWIR (1.565-2.280 μm) regions were selected as the most optimal for discriminating degraded soils from other land cover types. However, for Landsat 8OLI, only the SWIR (1.560-2.300 μm), NIR (0.845-0.885 μm) region were selected as the best regions. Of the eighteen spectral vegetation indices computed, NDVI and SAVI and SAVI and Global Environmental Monitoring Index (GEMI) were ranked selected as the most suitable for detecting and mapping soil erosion. Additionally, SRTM DEM derived information illustrates that for both sensors eroded areas occur on sites that are 600 m and 900 m of altitude with similar trends observed in both dry and wet season maps. Findings of this work emphasize the importance of free and readily available new generation sensors in continuous landscape

Chlorophyll-a retrieval in the Philippine waters

NASA Astrophysics Data System (ADS)

Perez, G. J. P.; Leonardo, E. M.; Felix, M. J.

2017-12-01

Satellite-based monitoring of chlorophyll-a (Chl-a) concentration has been widely used for estimating plankton biomass, detecting harmful algal blooms, predicting pelagic fish abundance, and water quality assessment. Chl-a concentrations at 1 km spatial resolution can be retrieved from MODIS onboard Aqua and Terra satellites. However, with this resolution, MODIS has scarce Chl-a retrieval in coastal and inland waters, which are relevant for archipelagic countries such as the Philippines. These gaps on Chl-a retrieval can be filled by sensors with higher spatial resolution, such as the OLI of Landsat 8. In this study, assessment of Chl-a concentration derived from MODIS/Aqua and OLI/Landsat 8 imageries across the open, coastal and inland waters of the Philippines was done. Validation activities were conducted at eight different sites around the Philippines for the period October 2016 to April 2017. Water samples filtered on the field were processed in the laboratory for Chl-a extraction. In situ remote sensing reflectance was derived from radiometric measurements and ancillary information, such as bathymetry and turbidity, were also measured. Correlation between in situ and satellite-derived Chl-a concentration using the blue-green ratio yielded relatively high R2 values of 0.51 to 0.90. This is despite an observed overestimation for both MODIS and OLI-derived values, especially in turbid and coastal waters. The overestimation of Chl-a may be attributed to inaccuracies in i) remote sensing reflectance (Rrs) retrieval and/or ii) empirical model used in calculating Chl-a concentration. However, a good 1:1 correspondence between the satellite and in situ maximum Rrs band ratio was established. This implies that the overestimation is largely due to the inaccuracies from the default coefficients used in the empirical model. New coefficients were then derived from the correlation analysis of both in situ-measured Chl-a concentration and maximum Rrs band ratio. This

Preliminary Analysis of the Performance of the Landsat 8/OLI Land Surface Reflectance Product

NASA Technical Reports Server (NTRS)

Vermote, Eric; Justice, Chris; Claverie, Martin; Franch, Belen

2016-01-01

The surface reflectance, i.e., satellite derived top of atmosphere (TOA) reflectance corrected for the temporally, spatially and spectrally varying scattering and absorbing effects of atmospheric gases and aerosols, is needed to monitor the land surface reliably. For this reason, the surface reflectance, and not TOA reflectance, is used to generate the greater majority of global land products, for example, from the Moderate Resolution Imaging Spectroradiometer (MODIS) and Visible Infrared Imaging Radiometer Suite (VIIRS) sensors. Even if atmospheric effects are minimized by sensor design, atmospheric effects are still challenging to correct. In particular, the strong impact of aerosols in the visible and near infrared spectral range can be difficult to correct, because they can be highly discrete in space and time (e.g., smoke plumes) and because of the complex scattering and absorbing properties of aerosols that vary spectrally and with aerosol size, shape, chemistry and density.

Fort Meade, Baltimore, Maryland. Revised Uniform Summary of Surface Weather Observations (RUSSWO).

DTIC Science & Technology

1972-01-03

1 1___.o .2 TOTAL NUMBER OF OBSERVATIONS 82 5 USAFETAC ’oRA 0-8 5 (OL.I) PALvious [ DION $ OF TIS IORM ARE OBSOLETE)UL 64 .- -, . - ; I ’~~ ~ - - -*’V...i ]’ 059 .q -a.. i) 1 ./.,C4 I Eel celin v~ues ndnenen ofv’.ibii~vundr ci~u-,n- igh " , 4 . nea4>O 1 Fo ins,_ne, fo~a he able ’"A- ,s..n > 150 fet

Equilibrium studies of oxalate and aluminum containing solutions

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

Hay, M. S.; King, W. D.; Peters, T. B.

2015-11-01

The Savannah River National Laboratory (SRNL) was tasked to develop data on the solubility and conditions leading to precipitation of sodium oxalate, sodium nitrate, Bayerite (a polymorph of gibbsite, Al(OH) 3), and sodium aluminosilicate solids recently found in the Modular Caustic Side Solvent Extraction Unit (MCU). The data generated will be used to improve the OLI Systems thermodynamic database for these compounds allowing better prediction of solids formation by the modeling software in the future.

Analysis of the Cost of Late Contractor Delivery

DTIC Science & Technology

1987-09-01

9.99 10.99 90.91 O.OO 19.M 0.00 •459.90 TM9.99 •030.14 ■909.49 9949.99 9M1.09 •931.90 B0O4.97 103M .71 49M.T9 O.119399 o.oooooo...UAWUSDNC FMPMCUOO SYSIQIMPUT ■fmum ttCONOUMtN RSFNO10 OLY RH KX£Wt RtQUESI ADOHNTO KSPOND 11 Center, little effort is expended working a late

Describing the spatio-temporal variability of vines and soil by satellite-based spectral indices: A case study in Apulia (South Italy)

NASA Astrophysics Data System (ADS)

Borgogno-Mondino, E.; Novello, V.; Lessio, A.; de Palma, L.

2018-06-01

A time series of Landsat 8 OLI (L8 OLI) multispectral images acquired between May 2013 and February 2016 were used to investigate vigour, vine and soil water content in a vineyard of Moscato Reale (syn. Moscato Bianco) sited in the Castel del Monte DOCG area. Normalized Difference Vegetation Index (NDVI) and Normalized Difference Water Index (NDWI) were calculated and compared with vine midday stem water potential (ΨMDstem) and soil volume water content (VWC), to calibrate estimation models. Estimation models were calibrated using already existing ground observation datasets from previous ordinary vineyard management operations: ΨMDstem was measured at two different locations in vineyard at 6 different dates in summer 2014; VWC was continuously measured from June to October 2014 and from January to September 2015. Results showed that: a) vine stem water potential can be locally estimated with an accuracy ranging from ±0.046 (high vigour vines) to ±0.127 (low vigour vines) MPa; b) soil volume water content can be locally estimated with an accuracy of about ±1.7%. Medium resolution satellite imagery proved, therefore, to be effective, at vineyard level, to describe vigour, vine and soil water status and their seasonality. This is an important issue to focus on since, as Landsat 8 images are free, the entire process is economic enough to be consistent with cost and incoming of the farming system.

Utilizing NASA Earth Observations to Assess Impacts of Hurricanes Andrew and Irma on Mangrove Forests in Biscayne Bay National Park, FL

NASA Astrophysics Data System (ADS)

Kumar, A.; Weber, S.; Remillard, C.; Escobar Pardo, M. L.; Hashemi Tonekaboni, N.; Cameron, C.; Linton, S.; Rickless, D.; Rivero, R.; Madden, M.

2017-12-01

Extreme weather events, such as hurricanes, pose major threats to coastal communities around the globe. However, mangrove forests along coastlines act as barriers and subdue the impacts associated with these catastrophic events. The Biscayne Bay National Park mangrove forest located near the city of Miami Beach was recently affected by the category four hurricane Irma in September of 2017. This study analyzed the impact of Hurricane Irma on Biscayne Bay National Park mangroves. Several remote sensing datasets including Landsat 8 Operational Land Imager (OLI), Sentinel 2-Multi Spectral Imager (MSI), PlanetScope, and aerial imagery were utilized to assess pre-and post-hurricane conditions. The high-resolution aerial imagery and PlanetScope data were used to map damaged areas within the national park. Additionally, Landsat 8 OLI and Sentinel-2 MSI data were utilized to estimate changes in biophysical parameters, including gross primary productivity (GPP), before and after Hurricane Irma. This project also examined damages associated with Hurricane Andrew (1992) using historical Landsat 5 Thematic Mapper (TM) data. These results were compared to GPP estimates following Hurricane Irma and suggested that Hurricane Andrew's impact was greater than that of Irma in Biscayne Bay National Park. The results of this study will help to enhance the mangrove health monitoring and shoreline management programs led by officials at the City of Miami Beach Public Works Department.

Landsat 8 on-orbit characterization and calibration system

USGS Publications Warehouse

Micijevic, Esad; Morfitt, Ron; Choate, Michael J.

2011-01-01

The Landsat Data Continuity Mission (LDCM) is planning to launch the Landsat 8 satellite in December 2012, which continues an uninterrupted record of consistently calibrated globally acquired multispectral images of the Earth started in 1972. The satellite will carry two imaging sensors: the Operational Land Imager (OLI) and the Thermal Infrared Sensor (TIRS). The OLI will provide visible, near-infrared and short-wave infrared data in nine spectral bands while the TIRS will acquire thermal infrared data in two bands. Both sensors have a pushbroom design and consequently, each has a large number of detectors to be characterized. Image and calibration data downlinked from the satellite will be processed by the U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center using the Landsat 8 Image Assessment System (IAS), a component of the Ground System. In addition to extracting statistics from all Earth images acquired, the IAS will process and trend results from analysis of special calibration acquisitions, such as solar diffuser, lunar, shutter, night, lamp and blackbody data, and preselected calibration sites. The trended data will be systematically processed and analyzed, and calibration and characterization parameters will be updated using both automatic and customized manual tools. This paper describes the analysis tools and the system developed to monitor and characterize on-orbit performance and calibrate the Landsat 8 sensors and image data products.

The Thermal Infrared Sensor on the Landsat Data Continuity Mission

NASA Technical Reports Server (NTRS)

Reuter, Dennis; Richardson, Cathy; Irons, James; Allen, Rick; Anderson, Martha; Budinoff, Jason; Casto, Gordon; Coltharp, Craig; Finneran, Paul; Forsbacka, Betsy;

A Landsat-based model for retrieving total suspended solids concentration of estuaries and coasts in China

NASA Astrophysics Data System (ADS)

Wang, Chongyang; Chen, Shuisen; Li, Dan; Wang, Danni; Liu, Wei; Yang, Ji

2017-11-01

Retrieving total suspended solids (TSS) concentration accurately is essential for sustainable management of estuaries and coasts, which plays a key role in the interaction between hydrosphere, pedosphere and atmosphere. Although many TSS retrieval models have been published, the general inversion method that is applicable to different field conditions is still under research. In order to obtain a TSS remote sensing model that is suitable for estimating TSS concentrations with wide range in estuaries and coasts by Landsat imagery, after reviewing a number of Landsat-based TSS retrieval models and improving a comparatively better one among them, this study developed a quadratic model using the ratio of logarithmic transformation of red band and near-infrared band and logarithmic transformation of TSS concentration (QRLTSS) based on 119 in situ samples collected in 2006-2013 from five regions of China. It was found that the QRLTSS model works well and shows a satisfactory performance. The QRLTSS model based on Landsat TM (Thematic Mapper), ETM+ (Enhanced Thematic Mapper Plus) and OLI (Operational Land Imager) sensors explained about 72 % of the TSS concentration variation (TSS: 4.3-577.2 mg L-1, N = 84, P value < 0.001) and had an acceptable validation accuracy (TSS: 4.5-474 mg L-1, root mean squared error (RMSE) ≤ 25 mg L-1, N = 35). In addition, a threshold method of red-band reflectance (OLI: 0.032, ETM+ and TM: 0.031) was proposed to solve the two-valued issue of the QRLTSS model and to retrieve TSS concentration from Landsat imagery. After a 6S model-based atmospheric correction of Landsat OLI and ETM+ imagery, the TSS concentrations of three regions (Moyangjiang River estuary, Pearl River estuary and Hanjiang River estuary) in Guangdong Province in China were mapped by the QRLTSS model. The results indicated that TSS concentrations in the three estuaries showed large variation ranging from 0.295 to 370.4 mg L-1. Meanwhile we found that TSS concentrations

Summary of Research Activities, Academic Departments, 1979-1980.

DTIC Science & Technology

1980-10-01

AD-AO99 373 NAVAL ACADEMY ANNAP’OLIS RD / , SUMM4ARY OF RE ARCH ACTIVITIES . ACADEMIC DEPARTMENTS. 1 .q79-jRO..ET-rf , ,OCT 60 W L NEFLITN UNCLASSIF...IED USNA-AR-6 NL llnnnm mmnlm 1 mum li lllMENl l llsllol I I I I SUMMARY OF RESEARCH ACTIVITIES 1979 - 1980 I COMPILED AND EDITED BY PROFESSOR WILSON L...policy of the Naval Academy to provide and maintain an environment in which research activities that contribute to the professional growth of the

Automatic Co-Registration of Multi-Temporal Landsat-8/OLI and Sentinel-2A/MSI Images

NASA Technical Reports Server (NTRS)

Skakun, S.; Roger, J.-C.; Vermote, E.; Justice, C.; Masek, J.

2017-01-01

Many applications in climate change and environmental and agricultural monitoring rely heavily on the exploitation of multi-temporal satellite imagery. Combined use of freely available Landsat-8 and Sentinel-2 images can offer high temporal frequency of about 1 image every 3-5 days globally.

Data-driven simulations of the Landsat Data Continuity Mission (LDCM) platform

NASA Astrophysics Data System (ADS)

Gerace, Aaron; Gartley, Mike; Schott, John; Raqueño, Nina; Raqueño, Rolando

2011-06-01

The Operational Land Imager (OLI) and Thermal Infrared Sensor (TIRS) are two new sensors being developed by the Landsat Data Continuity Mission (LDCM) that will extend over 35 years of archived Landsat data. In a departure from the whiskbroom design used by all previous generations of Landsat, the LDCM system will employ a pushbroom technology. Although the newly adopted modular array, pushbroom architecture has several advantages over the previous whiskbroom design, registration of the multi-spectral data products is a concern. In this paper, the Digital Imaging and Remote Sensing Image Generation (DIRSIG) tool was used to simulate an LDCM collection, which gives the team access to data that would not otherwise be available prior to launch. The DIRSIG model was used to simulate the two-instrument LDCM payload in order to study the geometric and radiometric impacts of the sensor design on the proposed processing chain. The Lake Tahoe area located in eastern California was chosen for this work because of its dramatic change in elevation, which was ideal for studying the geometric effects of the new Landsat sensor design. Multi-modal datasets were used to create the Lake Tahoe site model for use in DIRSIG. National Elevation Dataset (NED) data were used to create the digital elevation map (DEM) required by DIRSIG, QuickBird data were used to identify different material classes in the scene, and ASTER and Hyperion spectral data were used to assign radiometric properties to those classes. In order to model a realistic Landsat orbit in these simulations, orbital parameters were obtained from a Landsat 7 two-line element set and propagated with the SGP4 orbital position model. Line-of-sight vectors defining how the individual detector elements of the OLI and TIRS instruments project through the optics were measured and provided by NASA. Additionally, the relative spectral response functions for the 9 bands of OLI and the 2 bands of TIRS were measured and provided by NASA

Using multi-date satellite imagery to monitor invasive grass species distribution in post-wildfire landscapes: An iterative, adaptable approach that employs open-source data and software

USGS Publications Warehouse

West, Amanda M.; Evangelista, Paul H.; Jarnevich, Catherine S.; Kumar, Sunil; Swallow, Aaron; Luizza, Matthew; Chignell, Steve

2017-01-01

Among the most pressing concerns of land managers in post-wildfire landscapes are the establishment and spread of invasive species. Land managers need accurate maps of invasive species cover for targeted management post-disturbance that are easily transferable across space and time. In this study, we sought to develop an iterative, replicable methodology based on limited invasive species occurrence data, freely available remotely sensed data, and open source software to predict the distribution of Bromus tectorum (cheatgrass) in a post-wildfire landscape. We developed four species distribution models using eight spectral indices derived from five months of Landsat 8 Operational Land Imager (OLI) data in 2014. These months corresponded to both cheatgrass growing period and time of field data collection in the study area. The four models were improved using an iterative approach in which a threshold for cover was established, and all models had high sensitivity values when tested on an independent dataset. We also quantified the area at highest risk for invasion in future seasons given 2014 distribution, topographic covariates, and seed dispersal limitations. These models demonstrate the effectiveness of using derived multi-date spectral indices as proxies for species occurrence on the landscape, the importance of selecting thresholds for invasive species cover to evaluate ecological risk in species distribution models, and the applicability of Landsat 8 OLI and the Software for Assisted Habitat Modeling for targeted invasive species management.

Plasticity of the myelination genomic fabric.

PubMed

Iacobas, Sanda; Thomas, Neil M; Iacobas, Dumitru A

2012-03-01

This study aimed to quantify the influence of the astrocyte proximity on myelination genomic fabric (MYE) of oligodendrocytes, defined as the most interconnected and stably expressed gene web responsible for myelination. Such quantitation is important to evaluate whether astrocyte signaling may contribute to demyelination when impaired and remyelination when properly restored. For this, we compared changes in the gene expression profiles of immortalized precursor oligodendrocytes (Oli-neu), stimulated to differentiate by the proximity of nontouching astrocytes or treatment with db-cAMP. In a previous paper, we reported that the astrocyte proximity upregulated or turned-on a large number of myelination genes and substantially enriched the Ca(2+)-signaling and cytokine receptor regulatory networks of MYE in Oli-neu cells. Here, we introduce the "transcriptomic distance" to evaluate fabric remodeling and "pair-wise relevance" to identify the most influential gene pairs. Together with the prominence gene analysis used to select and rank the fabric genes, these novel analytical tools provide a comprehensively quantitative view of the physio/pathological transformations of the transcriptomic programs of myelinating cells. Applied to our data, the analyses revealed not only that the astrocyte neighborhood is a substantially more powerful regulator of myelination than the differentiating treatment but also the molecular mechanisms of the two differentiating paradigms are different. By inducing a profound remodeling of MYE and regulatory transcriptomic networks, the astrocyte-oligodendrocyte intercommunication may be considered as a major player in both pathophysiology and therapy of neurodegenerative diseases related to myelination.

Assessing Landslide Characteristics and Developing a Landslide Potential Hazard Map in Rwanda and Uganda Using NASA Earth Observations

NASA Astrophysics Data System (ADS)

Sinclair, L.; Conner, P.; le Roux, J.; Finley, T.

2015-12-01

The International Emergency Disasters Database indicates that a total of 482 people have been killed and another 27,530 have been affected by landslides in Rwanda and Uganda, although the actual numbers are thought to be much higher. Data for individual countries are poorly tracked, but hotspots for devastating landslides occur throughout Rwanda and Uganda due to the local topography and soil type, intense rainfall events, and deforestation. In spite of this, there has been little research in this region that utilizes satellite imagery to estimate areas susceptible to landslides. This project utilized Landsat 8 Operational Land Imager (OLI) data and Google Earth to identify landslides that occurred within the study area. These landslides were then added to SERVIR's Global Landslide Catalog (GLC). Next, Landsat 8 OLI, the Tropical Rainfall Measuring Mission (TRMM), the Global Precipitation Measurement (GPM), and Shuttle Radar Topography Mission Version 2 (SRTM V2) data were used to create a Landslide Susceptibility Map. This was combined with population data from the Socioeconomic Data and Applications Center (SEDAC) to create a Landslide Hazard map. A preliminary assessment of the relative performance of GPM and TRMM in identifying landslide conditions was also performed. The additions to the GLC, the Landslide Susceptibility Map, the Landslide Hazard Map, and the preliminary assessment of satellite rainfall performance will be used by SERVIR and the Regional Centre for Mapping of Resources for Development (RCMRD) for disaster risk management, land use planning, and determining landslide conditions and moisture thresholds.

Utilization of municipal wastewater for cooling in thermoelectric power plants

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

Safari, Iman; Walker, Michael E.; Hsieh, Ming-Kai

2013-09-01

A process simulation model has been developed using Aspen Plus® with the OLI (OLI System, Inc.) water chemistry model to predict water quality in the recirculating cooling loop utilizing secondary- and tertiary-treated municipal wastewater as the source of makeup water. Simulation results were compared with pilot-scale experimental data on makeup water alkalinity, loop pH, and ammonia evaporation. The effects of various parameters including makeup water quality, salt formation, NH 3 and CO 2 evaporation mass transfer coefficients, heat load, and operating temperatures were investigated. The results indicate that, although the simulation model can capture the general trends in the loopmore » pH, experimental data on the rates of salt precipitation in the system are needed for more accurate prediction of the loop pH. It was also found that stripping of ammonia and carbon dioxide in the cooling tower can influence the cooling loop pH significantly. The effects of the NH 3 mass transfer coefficient on cooling loop pH appear to be more significant at lower values (e.g., k NH3 < 4×10 -3 m/s) when the makeup water alkalinity is low (e.g., <90 mg/L as CaCO 3). The effect of the CO2 mass transfer coefficient was found to be significant only at lower alkalinity values (e.g., k CO2<4×10 -6 m/s).« less

An Overview of the Landsat Data Continuity Mission

NASA Technical Reports Server (NTRS)

Irons, James R.; Dwyer, John L.

2010-01-01

The advent of the Landsat Data Continuity Mission (LDCM), currently with a launch readiness date of December, 2012, will see evolutionary changes in the Landsat data products available from the U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center. The USGS initiated a revolution in 2009 when EROS began distributing Landsat data products at no cost to requestors in contrast to the past practice of charging the cost of fulfilling a request; that is, charging $600 per Landsat scene. To implement this drastic change, EROS terminated data processing options for requestors and began to produce all data products using a consistent processing recipe. EROS plans to continue this practice for the LDCM and will required new algorithms to process data from the LDCM sensors. All previous Landsat satellites flew multispectral scanners to collect image data of the global land surface. Additionally, Landsats 4, 5, and 7 flew sensors that acquired imagery for both reflective spectral bands and a single thermal band. In contrast, the LDCM will carry two pushbroom sensors; the Operational Land Imager (OLI) for reflective spectral bands and the Thermal InfraRed Sensor (TIRS) for two thermal bands. EROS is developing the ground data processing system that will both calibrate and correct the data from the thousands of detectors employed by the pushbroom sensors and that will also combine the data from the two sensors to create a single data product with registered data for all of the OLI and TIRS bands.

Using multi-date satellite imagery to monitor invasive grass species distribution in post-wildfire landscapes: An iterative, adaptable approach that employs open-source data and software

NASA Astrophysics Data System (ADS)

West, Amanda M.; Evangelista, Paul H.; Jarnevich, Catherine S.; Kumar, Sunil; Swallow, Aaron; Luizza, Matthew W.; Chignell, Stephen M.

2017-07-01

Among the most pressing concerns of land managers in post-wildfire landscapes are the establishment and spread of invasive species. Land managers need accurate maps of invasive species cover for targeted management post-disturbance that are easily transferable across space and time. In this study, we sought to develop an iterative, replicable methodology based on limited invasive species occurrence data, freely available remotely sensed data, and open source software to predict the distribution of Bromus tectorum (cheatgrass) in a post-wildfire landscape. We developed four species distribution models using eight spectral indices derived from five months of Landsat 8 Operational Land Imager (OLI) data in 2014. These months corresponded to both cheatgrass growing period and time of field data collection in the study area. The four models were improved using an iterative approach in which a threshold for cover was established, and all models had high sensitivity values when tested on an independent dataset. We also quantified the area at highest risk for invasion in future seasons given 2014 distribution, topographic covariates, and seed dispersal limitations. These models demonstrate the effectiveness of using derived multi-date spectral indices as proxies for species occurrence on the landscape, the importance of selecting thresholds for invasive species cover to evaluate ecological risk in species distribution models, and the applicability of Landsat 8 OLI and the Software for Assisted Habitat Modeling for targeted invasive species management.

Nonempirical electron-correlation calculations on ALi/sub k/ and Ali/sub k+1//sup +/ clusters formed with elements from the second and third periods

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

Mebel', A.M.; Klimenko, N.M.; Charkin, O.P.

Several basic sets have been used (from 3-21 G/sub A//asterisk/ to DZHD + P/sub A/) with electron correlation in the Meller-Plesset MP3 approximation in nonempirical calculations on ALi/sub k+1//sup +/ and ALi/sub K+1//sup +/ lithium clusters (CLi/sub 2/, CLi/sub 3//sup +/, NLi/sub 3/, NLi/sub 4//sup +/, OLi/sub 2/, OLi/sub 3//sup +/, etc.) formed with elements from the second and third periods in the lowest singlet states. A study has been made on the effects of the approximation on the results. Several reference systems are used to show that the SCF/3-21G/sub A//asterisk/ approximation describes the lithide geometry satisfactorily, while MP3/DZHD +more » P/sub A/ gives a satisfactory description of the affinity of Ali/sub k/ for Li/sup +/. These approximations have been taken as optimal for calculations on the other compounds. The Li/sup +/ affinities are highest for NLi/sub 3/ and PLi/sub 3/ (90 and 84 kcal correspondingly) and decrease as A varies along the subgroups from the second to the third and the lower sp periods, as well as when A varies in each period from the middle to the start or end. The affinities of the analogous compounds for Na/sup +/ are less by 5-10 kcal than those for Li/sup +/. The values are compared with the proton affinities for the related hydrides AK/sub k/.« less

Boston Community Information System User’s Manual (Version 8.17).

DTIC Science & Technology

1987-10-01

I) health risk Kt* . ( 0) mit or "massachusetts institute" ( 29) harvard (category: not sports) % 2) aids (4) (category: news) (priority: urgent...Mlove ;lerwird orne hlie (or summary) hiIt - t. woe Cock on.? lin u(r summiary) cift! tie neAd line (or summary) T ~Soto c the pruViOLis Imfe (or...summary) I jshift k;_ use(d in orii :nct~on witi I and j has the same effect as using the numeric;lock key. Tht s i - (f thi; f-2at01 sec!he w ruen to

Statistical relative gain calculation for Landsat 8

NASA Astrophysics Data System (ADS)

Anderson, Cody; Helder, Dennis L.; Jeno, Drake

2017-09-01

The Landsat 8 Operational Land Imager (OLI) is an optical multispectral push-broom sensor with a focal plane consisting of over 7000 detectors per spectral band. Each of the individual imaging detectors contributes one column of pixels to an image. Any difference in the response between neighboring detectors may result in a visible stripe or band in the imagery. An accurate estimate of each detector's relative gain is needed to account for any differences between detector responses. This paper describes a procedure for estimating relative gains which uses normally acquired Earth viewing statistics.

Kwajalein, Marshall Island, Bucholz. Revised Uniform Summary of Surface Weather Observations (RUSSWO). Parts A-F

DTIC Science & Technology

1973-06-08

J 107!> FOM1210 WS jUI. 64 O,|S,5 lOLI ) PA ls[IVIO S O010 F$0 THIS lORM A01 00S00)i| A .-.-- - -’* q t if DATA PROCESSING BRANCH EXTREME VALUES...1 994] 94.9 99.4 So 960 99~ loli 99,v 99, Y 99,’ Z919, 9, 9 0:9 9,0 99,0 9 , 00 , ¢,010 9.1,{0 400o 96.5 9,1 99,Z 99&4 . ,9 99, 71 eo . 9 ,9 4 le * A 9

Statistical relative gain calculation for Landsat 8

USGS Publications Warehouse

Anderson (CTR), Cody; Helder, Dennis; Jeno (CTR), Drake

2017-01-01

The Landsat 8 Operational Land Imager (OLI) is an optical multispectral push-broom sensor with a focal plane consisting of over 7000 detectors per spectral band. Each of the individual imaging detectors contributes one column of pixels to an image. Any difference in the response between neighboring detectors may result in a visible stripe or band in the imagery. An accurate estimate of each detector’s relative gain is needed to account for any differences between detector responses. This paper describes a procedure for estimating relative gains which uses normally acquired Earth viewing statistics.

Satellite image based methods for fuels maps updating

NASA Astrophysics Data System (ADS)

Alonso-Benito, Alfonso; Hernandez-Leal, Pedro A.; Arbelo, Manuel; Gonzalez-Calvo, Alejandro; Moreno-Ruiz, Jose A.; Garcia-Lazaro, Jose R.

2016-10-01

Regular updating of fuels maps is important for forest fire management. Nevertheless complex and time consuming field work is usually necessary for this purpose, which prevents a more frequent update. That is why the assessment of the usefulness of satellite data and the development of remote sensing techniques that enable the automatic updating of these maps, is of vital interest. In this work, we have tested the use of the spectral bands of OLI (Operational Land Imager) sensor on board Landsat 8 satellite, for updating the fuels map of El Hierro Island (Spain). From previously digitized map, a set of 200 reference plots for different fuel types was created. A 50% of the plots were randomly used as a training set and the rest were considered for validation. Six supervised and 2 unsupervised classification methods were applied, considering two levels of detail. A first level with only 5 classes (Meadow, Brushwood, Undergrowth canopy cover >50%, Undergrowth canopy cover <15%, and Xeric formations), and the second one containing 19 fuel types. The level 1 classification methods yielded an overall accuracy ranging from 44% for Parellelepided to an 84% for Maximun Likelihood. Meanwhile, level 2 results showed at best, an unacceptable overall accuracy of 34%, which prevents the use of this data for such a detailed characterization. Anyway it has been demonstrated that in some conditions, images of medium spatial resolution, like Landsat 8-OLI, could be a valid tool for an automatic upgrade of fuels maps, minimizing costs and complementing traditional methodologies.

N-acetylaspartate (NAA) and N-acetylaspartylglutamate (NAAG) promote growth and inhibit differentiation of glioma stem-like cells.

PubMed

Long, Patrick M; Moffett, John R; Namboodiri, Aryan M A; Viapiano, Mariano S; Lawler, Sean E; Jaworski, Diane M

2013-09-06

Metabolic reprogramming is a pathological feature of cancer and a driver of tumor cell transformation. N-Acetylaspartate (NAA) is one of the most abundant amino acid derivatives in the brain and serves as a source of metabolic acetate for oligodendrocyte myelination and protein/histone acetylation or a precursor for the synthesis of the neurotransmitter N-acetylaspartylglutamate (NAAG). NAA and NAAG as well as aspartoacylase (ASPA), the enzyme responsible for NAA degradation, are significantly reduced in glioma tumors, suggesting a possible role for decreased acetate metabolism in tumorigenesis. This study sought to examine the effects of NAA and NAAG on primary tumor-derived glioma stem-like cells (GSCs) from oligodendroglioma as well as proneural and mesenchymal glioblastoma, relative to oligodendrocyte progenitor cells (Oli-Neu). Although the NAA dicarboxylate transporter NaDC3 is primarily thought to be expressed by astrocytes, all cell lines expressed NaDC3 and, thus, are capable of NAA up-take. Treatment with NAA or NAAG significantly increased GSC growth and suppressed differentiation of Oli-Neu cells and proneural GSCs. Interestingly, ASPA was expressed in both the cytosol and nuclei of GSCs and exhibited greatest nuclear immunoreactivity in differentiation-resistant GSCs. Both NAA and NAAG elicited the expression of a novel immunoreactive ASPA species in select GSC nuclei, suggesting differential ASPA regulation in response to these metabolites. Therefore, this study highlights a potential role for nuclear ASPA expression in GSC malignancy and suggests that the use of NAA or NAAG is not an appropriate therapeutic approach to increase acetate bioavailability in glioma. Thus, an alternative acetate source is required.

Research on Remote Sensing Image Classification Based on Feature Level Fusion

NASA Astrophysics Data System (ADS)

Yuan, L.; Zhu, G.

2018-04-01

Remote sensing image classification, as an important direction of remote sensing image processing and application, has been widely studied. However, in the process of existing classification algorithms, there still exists the phenomenon of misclassification and missing points, which leads to the final classification accuracy is not high. In this paper, we selected Sentinel-1A and Landsat8 OLI images as data sources, and propose a classification method based on feature level fusion. Compare three kind of feature level fusion algorithms (i.e., Gram-Schmidt spectral sharpening, Principal Component Analysis transform and Brovey transform), and then select the best fused image for the classification experimental. In the classification process, we choose four kinds of image classification algorithms (i.e. Minimum distance, Mahalanobis distance, Support Vector Machine and ISODATA) to do contrast experiment. We use overall classification precision and Kappa coefficient as the classification accuracy evaluation criteria, and the four classification results of fused image are analysed. The experimental results show that the fusion effect of Gram-Schmidt spectral sharpening is better than other methods. In four kinds of classification algorithms, the fused image has the best applicability to Support Vector Machine classification, the overall classification precision is 94.01 % and the Kappa coefficients is 0.91. The fused image with Sentinel-1A and Landsat8 OLI is not only have more spatial information and spectral texture characteristics, but also enhances the distinguishing features of the images. The proposed method is beneficial to improve the accuracy and stability of remote sensing image classification.

Genetic Biodiversity of Italian Olives (Olea europaea) Germplasm Analyzed by SSR Markers

PubMed Central

Vendramin, Giuseppe Giovanni; Chiappetta, Adriana

2014-01-01

The olive is an important fruit species cultivated for oil and table olives in Italy and the Mediterranean basin. The conservation of cultivated plants in ex situ collections is essential for the optimal management and use of their genetic resources. The largest ex situ olive germplasm collection consists of approximately 500 Italian olive varieties and corresponding to 85% of the total Italian olive germplasm is maintained at the Consiglio per la Ricerca e sperimentazione per l'Agricoltura, Centro di Ricerca per l'Olivicoltura e l'Industria Olearia (CRA-OLI), in Italy. In this work, eleven preselected nuclear microsatellite markers were used to assess genetic diversity, population structure, and gene flows with the aim of assembling a core collection. The dendrogram obtained utilizing the unweighted pair group method highlights the presence of homonymy and synonymy in olive tree datasets analyzed in this study. 439 different unique genotype profiles were obtained with this combination of 11 loci nSSR, representing 89.8% of the varieties analyzed. The remaining 10.2% comprises different variety pairs in which both accessions are genetically indistinguishable. Clustering analysis performed using BAPS software detected seven groups in Italian olive germplasm and gene flows were determined among identified clusters. We proposed an Italian core collection of 23 olive varieties capturing all detected alleles at microsatellites. The information collected in this study regarding the CRA-OLI ex situ collection can be used for breeding programs, for germplasm conservation, and for optimizing a strategy for the management of olive gene pools. PMID:24723801

Utilizing NASA Earth Observations to Assess Landslide Characteristics and Devlelop Susceptibility and Exposure Maps in Malawi

NASA Astrophysics Data System (ADS)

Klug, M.; Cissell, J.; Grossman, M.

2017-12-01

Malawi has become increasingly prone to landslides in the past few decades. This can be attributed to the terrain, types of soil and vegetation, increased human interference, and heavy flooding after long periods of drought. In addition to the floods and droughts, landslides cause extra stress to farmlands, thus exacerbating the current food security crisis in the country. It can be difficult to pinpoint just how many people are affected by landslides in Malawi because landslides often occur in rural areas or are grouped with other disasters, such as floods or earthquakes. This project created a Landslide Susceptibility Map to assess landslide-prone areas in Malawi using variables such as slope, distance to roads, distance to streams, soil type, and precipitation. These variables were derived using imagery from Landsat 8 Operational Land Imager (OLI), Shuttle Radar Topography Mission Version 3 (SRTM-v3), Global Precipitation Measurement (GPM), and Tropical Rainfall Measuring Mission (TRMM) satellites. Furthermore, this project created a Landslide Exposure Map to estimate how much of the local population lives in susceptible areas by intersecting population data with the Landslide Susceptibility Map. Additionally, an assessment of GPM and TRMM precipitation measurements was generated to better understand the reliability of both measurements for landslide monitoring. Finally, this project updated NASA SERVIR's Global Landslide Catalog (GLC) for Malawi by using WorldView data from Google Earth and Landsat 8 OLI. These end products were used by NASA SERVIR and the Regional Centre for Mapping of Resources for Development (RCMRD) for aiding in disaster management throughout Malawi.

Features of electronic structure of hypovalent lithides ALi/sub k/ and ALi/sub k+1//sup +/

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

Klimenko, N.M.; Mebel', A.M.; Charkin, O.P.

The features of the chemical bonding and the behavior of the original energies of the lithides ALi/sub k/ and ALi/sub K+1//sup +/ have been analyzed on the basis of nonempirical calculations in the MP3/(DZHD + P/sub A/) approximation. It has been found that the new A-Li bond appearing upon the addition of Li/sup +/ to Ali/sub k/ is formed with the participation of only the p/sub A/ AO's from the atom A. In contrast to the case of the hydrides AK/sub k/ and the fluorides AF/sub k/, in the case of the lithides ALi/sub k/ and ALi/sub k+1//sup +/, themore » lone pair of the atom A consists of its almost pure s/sub A/ AO, which maintains its spherical shape, is not active stereochemically, and practically does not participate in the bonding. The lithides ALi/sub k/ and Ali/sub k+1//sup +/ (such as CLi/sub 2/, Cli/sub 3//sup +/, NLi/sub 3/, NLi/sub 4//sup +/, OLi/sub 2/, OLi/sub 3//sup +/, Fli, Fli/sub 2//sup +/, etc.) may be classified as hypovalent compounds, in which the number of valence AO's of the atom A participating in the bonding is smaller than the number of atoms of Li directly bonded to the atom A. The bonding in them is delocalized over all the atoms comparing the molecule, and the two-center approach and Gillespie's rules are, in principle, not suitable.« less

Retrieval of suspended sediment concentrations using Landsat-8 OLI satellite images in the Orinoco River (Venezuela)

NASA Astrophysics Data System (ADS)

Yepez, Santiago; Laraque, Alain; Martinez, Jean-Michel; De Sa, Jose; Carrera, Juan Manuel; Castellanos, Bartolo; Gallay, Marjorie; Lopez, Jose L.

2018-01-01

In this study, 81 Landsat-8 scenes acquired from 2013 to 2015 were used to estimate the suspended sediment concentration (SSC) in the Orinoco River at its main hydrological station at Ciudad Bolivar, Venezuela. This gauging station monitors an upstream area corresponding to 89% of the total catchment area where the mean discharge is of 33,000 m3·s-1. SSC spatial and temporal variabilities were analyzed in relation to the hydrological cycle and to local geomorphological characteristics of the river mainstream. Three types of atmospheric correction models were evaluated to correct the Landsat-8 images: DOS, FLAASH, and L8SR. Surface reflectance was compared with monthly water sampling to calibrate a SSC retrieval model using a bootstrapping resampling. A regression model based on surface reflectance at the Near-Infrared wavelengths showed the best performance: R2 = 0.92 (N = 27) for the whole range of SSC (18 to 203 mg·l-1) measured at this station during the studied period. The method offers a simple new approach to estimate the SSC along the lower Orinoco River and demonstrates the feasibility and reliability of remote sensing images to map the spatiotemporal variability in sediment transport over large rivers.

Brookville Lake, Greater Miami River Basin, Indiana Embankment Criteria and Performance Report.

DTIC Science & Technology

1982-09-01

a , 23* I 60321 02.y2.0 PP 4 o# lv16 -7 60.. OLI � 303 0 Pazo STAW... C..DONCREw AT20 -P P-~k PAfTE ,of of DAN~ 00 23 o 2-so Is~ 21o031T...1963- A . . . A2 T esaasif4 IA SECURITY CLASSIFICATION OF THIS PAGE (t1hm, De Enterom REPORT DOCUMENTATION PAGE BFRE D OM u O os 1. REPORT NUMBER 2. GOVT...Approved for public release; distribution unlimited. 17. DISTRIBUTION STATEMENT (*ofib* t -robtuicf in S ock "’. f ’-ffi-ont fiw Ripof)I A 2 9 IS

Reduction of nitrogen oxides (NOx) by superalkalis

NASA Astrophysics Data System (ADS)

Srivastava, Ambrish Kumar

2018-03-01

NOx are major air pollutants, having negative impact on environment and consequently, human health. We propose here the single-electron reduction of NOx (x = 1, 2) using superalkalis. We study the interaction of NOx with FLi2, OLi3 and NLi4 superalkalis using density functional and single-point CCSD(T) calculations, which lead to stable superalkali-NOx ionic complexes with negatively charged NOx. This clearly reveals that the NOx can successfully be reduced to NOx- anion due to electron transfer from superalkalis. It has been also noticed that the size of superalkalis plays a crucial in the single-electron reduction of NOx.

The Next Landsat Satellite: The Landsat Data Continuity Mission

NASA Technical Reports Server (NTRS)

Rons, James R.; Dwyer, John L.; Barsi, Julia A.

2012-01-01

The Landsat program is one of the longest running satellite programs for Earth observations from space. The program was initiated by the launch of Landsat 1 in 1972. Since then a series of six more Landsat satellites were launched and at least one of those satellites has been in operations at all times to continuously collect images of the global land surface. The Department of Interior (DOI) U.S. Geological Survey (USGS) preserves data collected by all of the Landsat satellites at their Earth Resources Observation and Science (EROS) Center in Sioux Falls, South Dakota. This 40-year data archive provides an unmatched record of the Earth's land surface that has undergone dramatic changes in recent decades due to the increasing pressure of a growing population and advancing technologies. EROS provides the ability for anyone to search the archive and order digital Landsat images over the internet for free. The Landsat data are a public resource for observing, characterizing, monitoring, trending, and predicting land use change over time providing an invaluable tool for those addressing the profound consequences of those changes to society. The most recent launch of a Landsat satellite occurred in 1999 when Landsat 7 was placed in orbit. While Landsat 7 remains in operation, the National Aeronautics and Space Administration (NASA) and the DOI/ USGS are building its successor satellite system currently called the Landsat Data Continuity Mission (LDCM). NASA has the lead for building and launching the satellite that will carry two Earth-viewing instruments, the Operational Land Imager (OLI) and the Thermal Infrared Sensor (TIRS). The OLI will take images that measure the amount of sunlight reflected by the land surface at nine wavelengths of light with three of those wavelengths beyond the range of human vision. T1RS will collect coincident images that measure light emitted by the land surface as a function of surface temperature at two longer wavelengths well beyond the

LITERATURE REVIEW ON IMPACT OF GLYCOLATE ON THE 2H EVAPORATOR AND THE EFFLUENT TREATMENT FACILITY

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

Adu-Wusu, K.

2012-05-10

Glycolic acid (GA) is being studied as an alternate reductant in the Defense Waste Processing Facility (DWPF) feed preparation process. It will either be a total or partial replacement for the formic acid that is currently used. A literature review has been conducted on the impact of glycolate on two post-DWPF downstream systems - the 2H Evaporator system and the Effluent Treatment Facility (ETF). The DWPF recycle stream serves as a portion of the feed to the 2H Evaporator. Glycolate enters the evaporator system from the glycolate in the recycle stream. The overhead (i.e., condensed phase) from the 2H Evaporatormore » serves as a portion of the feed to the ETF. The literature search revealed that virtually no impact is anticipated for the 2H Evaporator. Glycolate may help reduce scale formation in the evaporator due to its high complexing ability. The drawback of the solubilizing ability is the potential impact on the criticality analysis of the 2H Evaporator system. It is recommended that at least a theoretical evaluation to confirm the finding that no self-propagating violent reactions with nitrate/nitrites will occur should be performed. Similarly, identification of sources of ignition relevant to glycolate and/or update of the composite flammability analysis to reflect the effects from the glycolate additions for the 2H Evaporator system are in order. An evaluation of the 2H Evaporator criticality analysis is also needed. A determination of the amount or fraction of the glycolate in the evaporator overhead is critical to more accurately assess its impact on the ETF. Hence, use of predictive models like OLI Environmental Simulation Package Software (OLI/ESP) and/or testing are recommended for the determination of the glycolate concentration in the overhead. The impact on the ETF depends on the concentration of glycolate in the ETF feed. The impact is classified as minor for feed glycolate concentrations {le} 33 mg/L or 0.44 mM. The ETF unit operations that

Tradeoffs between vigor and yield for crops grown under different management systems

NASA Astrophysics Data System (ADS)

Simic Milas, Anita; Keller Vincent, Robert; Romanko, Matthew; Feitl, Melina; Rupasinghe, Prabha

2016-04-01

Remote sensing can provide an effective means for rapid and non-destructive monitoring of crop status and biochemistry. Monitoring pattern of traditional vigor algorithms generated from Landsat 8 OLI satellite data represents a robust method that can be widely used to differentiate the status of crops, as well as to monitor nutrient uptake functionality of differently treated seeds grown under different managements. This study considers 24 factorial parcels of winter wheat in 2013, corn in 2014, and soybeans in 2015, grown under four different types of agricultural management. The parcels are located at the Kellogg Biological Station, Long-Term Ecological Research site in the State of Michigan USA. At maturity, the organic crops exhibit significantly higher vigor and significantly lower yield than conventionally managed crops under different treatments. While organic crops invest in their metabolism at the expense of their yield, the conventional crops manage to increase their yield at the expense of their vigor. Landsat 8 OLI is capable of 1) differentiating the biochemical status of crops under different treatments at maturity, and 2) monitoring the tradeoff between crop yield and vigor that can be controlled by the seed treatments and proper conventional applications, with the ultimate goal of increasing food yield and food availability, and 3) distinguishing between organic and conventionally treated crops. Timing, quantity and types of herbicide applications have a great impact on early and pre-harvest vigor, maturity and yield of conventionally treated crops. Satellite monitoring using Landsat 8 is an optimal tool for coordinating agricultural applications, soil practices and genetic coding of the crop to produce higher yield as well as have early crop maturity, desirable in northern climates.

N-Acetylaspartate (NAA) and N-Acetylaspartylglutamate (NAAG) Promote Growth and Inhibit Differentiation of Glioma Stem-like Cells*

PubMed Central

Long, Patrick M.; Moffett, John R.; Namboodiri, Aryan M. A.; Viapiano, Mariano S.; Lawler, Sean E.; Jaworski, Diane M.

2013-01-01

Metabolic reprogramming is a pathological feature of cancer and a driver of tumor cell transformation. N-Acetylaspartate (NAA) is one of the most abundant amino acid derivatives in the brain and serves as a source of metabolic acetate for oligodendrocyte myelination and protein/histone acetylation or a precursor for the synthesis of the neurotransmitter N-acetylaspartylglutamate (NAAG). NAA and NAAG as well as aspartoacylase (ASPA), the enzyme responsible for NAA degradation, are significantly reduced in glioma tumors, suggesting a possible role for decreased acetate metabolism in tumorigenesis. This study sought to examine the effects of NAA and NAAG on primary tumor-derived glioma stem-like cells (GSCs) from oligodendroglioma as well as proneural and mesenchymal glioblastoma, relative to oligodendrocyte progenitor cells (Oli-Neu). Although the NAA dicarboxylate transporter NaDC3 is primarily thought to be expressed by astrocytes, all cell lines expressed NaDC3 and, thus, are capable of NAA up-take. Treatment with NAA or NAAG significantly increased GSC growth and suppressed differentiation of Oli-Neu cells and proneural GSCs. Interestingly, ASPA was expressed in both the cytosol and nuclei of GSCs and exhibited greatest nuclear immunoreactivity in differentiation-resistant GSCs. Both NAA and NAAG elicited the expression of a novel immunoreactive ASPA species in select GSC nuclei, suggesting differential ASPA regulation in response to these metabolites. Therefore, this study highlights a potential role for nuclear ASPA expression in GSC malignancy and suggests that the use of NAA or NAAG is not an appropriate therapeutic approach to increase acetate bioavailability in glioma. Thus, an alternative acetate source is required. PMID:23884408

Assessing groundwater accessibility in the Kharga Basin, Egypt: A remote sensing approach

NASA Astrophysics Data System (ADS)

Parks, Shawna; Byrnes, Jeffrey; Abdelsalam, Mohamed G.; Laó Dávila, Daniel A.; Atekwana, Estella A.; Atya, Magdy A.

2017-12-01

We used multi-map analysis of remote sensing and ancillary data to identify potentially accessible sites for groundwater resources in the Kharga Basin in the Western Desert of Egypt. This basin is dominated by Cretaceous sandstone formations and extends within the Nubian Sandstone Aquifer. It is dissected by N-S and E-W trending faults, possibly acting as conduits for upward migration of groundwater. Analysis of paleo-drainage using Digital Elevation Model (DEM) generated from the Shuttle Radar Topography Mission (SRTM) data shows that the Kharga was a closed basin that might have been the site of a paleo-lake. Lake water recharged the Nubian Sandstone Aquifer during the wetter Holocene time. We generated the following layers for the multi-map analysis: (1) Fracture density map from the interpretation of Landsat Operational Land Imager (OLI), SRTM DEM, and RADARSAT data. (2) Thermal Inertia (TI) map (for moisture content imaging) from the Moderate Resolution Imaging Spectroradiometer (MODIS) data. (3) Hydraulic conductivity map from mapping lithological units using the Landsat OLI and previously published data. (4) Aquifer thickness map from previously published data. We quantitatively ranked the Kharga Basin by considering that regions of high fracture density, high TI, thicker aquifer, and high hydraulic conductivity have higher potential for groundwater accessibility. Our analysis shows that part of the southern Kharga Basin is suitable for groundwater extraction. This region is where N-S and E-W trending faults intersect, has relatively high TI and it is underlain by thick aquifer. However, the suitability of this region for groundwater use will be reduced significantly when considering the changes in land suitability and economic depth to groundwater extraction in the next 50 years.

Spatio-temporal pattern of eco-environmental parameters in Jharia coalfield, India

NASA Astrophysics Data System (ADS)

Saini, V.; Gupta, R. P.; Arora, M. K.

2015-10-01

Jharia coal-field holds unequivocal importance in the Indian context as it is the only source of prime coking coal in the country. The coalfield is also known for its infamous coal mine fires which have been burning since last more than a century. Haphazard mining over a century has led to eco-environmental changes to a large extent such as changes in vegetation distribution and widespread development of surface and subsurface fires. This article includes the spatiotemporal study of remote sensing derived eco-environmental parameters like vegetation index (NDVI), tasseled cap transformation (TCT) and temperature distribution in fire areas. In order to have an estimate of the temporal variations of NDVI over the years, a study has been carried out on two subsets of the Jharia coalfield using Landsat images of 1972 (MSS), 1992 (TM), 1999 (ETM+) and 2013 (OLI). To assess the changes in brightness and greenness over the year s, difference images have been calculated using the 1992 (TM) and 2013 (OLI) images. Radiance images derived from thermal bands have been used to calculate at-sensor brightness temperature over a 23 year period from 1991 to 2013. It has been observed that during the years 1972 to 2013, moderate to dense vegetation has decreased drastically due to the intense mining going on in the area. TCT images show the areas that have undergone changes in both brightness and greenness from 1992 to 2013. Surface temperature data obtained shows a constant increase from 1991 to 2013 apparently due to coal fires. The utility of remote sensing data in such EIA studies has been emphasized.

Carbon sequestration associated to the land-use and land-cover changes in the forestry sector in Southern Brazil

NASA Astrophysics Data System (ADS)

Ronquim, Carlos C.; Silva, Ramon F. B.; de Figueiredo, Eduardo B.; Bordonal, Ricardo O.; de C. Teixeira, Antônio H.; Cochasrk, Thomas C. D.; Leivas, Janice F.

2016-10-01

We studied the Paraíba do Sul river watershed, São Paulo state (PSWSP), Southeastern Brazil, in order to assess the land use and cover (LULC) and their implications to the amount of carbon (C) stored in the forest cover between the years 1985 and 2015. The region covers an area of 1,395,975 ha. We used images made by the Operational Land Imager (OLI) sensor (OLI/Landsat-8) to produce mappings, and image segmentation techniques to produce vectors with homogeneous characteristics. The training samples and the samples used for classification and validation were collected from the segmented image. To quantify the C stocked in aboveground live biomass (AGLB), we used an indirect method and applied literature-based reference values. The recovery of 205,690 ha of a secondary Native Forest (NF) after 1985 sequestered 9.7 Tg (Teragram) of C. Considering the whole NF area (455,232 ha), the amount of C accumulated along the whole watershed was 35.5 Tg, and the whole Eucalyptus crop (EU) area (113,600 ha) sequestered 4.4 Tg of C. Thus, the total amount of C sequestered in the whole watershed (NF + EU) was 39.9 Tg of C or 145.6 Tg of CO2, and the NF areas were responsible for the largest C stock at the watershed (89%). Therefore, the increase of the NF cover contributes positively to the reduction of CO2 concentration in the atmosphere, and Reducing Emissions from Deforestation and Forest Degradation (REDD+) may become one of the most promising compensation mechanisms for the farmers who increased forest cover at their farms.

Combination of Landsat and Sentinel-2 MSI data for initial assessing of burn severity

NASA Astrophysics Data System (ADS)

Quintano, C.; Fernández-Manso, A.; Fernández-Manso, O.

2018-02-01

Nowadays Earth observation satellites, in particular Landsat, provide a valuable help to forest managers in post-fire operations; being the base of post-fire damage maps that enable to analyze fire impacts and to develop vegetation recovery plans. Sentinel-2A MultiSpectral Instrument (MSI) records data in similar spectral wavelengths that Landsat 8 Operational Land Imager (OLI), and has higher spatial and temporal resolutions. This work compares two types of satellite-based maps for evaluating fire damage in a large wildfire (around 8000 ha) located in Sierra de Gata (central-western Spain) on 6-11 August 2015. 1) burn severity maps based exclusively on Landsat data; specifically, on differenced Normalized Burn Ratio (dNBR) and on its relative versions (Relative dNBR, RdNBR, and Relativized Burn Ratio, RBR) and 2) burn severity maps based on the same indexes but combining pre-fire data from Landsat 8 OLI with post-fire data from Sentinel-2A MSI data. Combination of both Landsat and Sentinel-2 data might reduce the time elapsed since forest fire to the availability of an initial fire damage map. Interpretation of ortho-photograph Pléiades 1 B data (1:10,000) provided us the ground reference data to measure the accuracy of both burn severity maps. Results showed that Landsat based burn severity maps presented an adequate assessment of the damage grade (κ statistic = 0.80) and its spatial distribution in wildfire emergency response. Further using both Landsat and Sentinel-2 MSI data the accuracy of burn severity maps, though slightly lower (κ statistic = 0.70) showed an adequate level for be used by forest managers.

Tarawa to Okinawa: The Evolution of Amphibious Operations in the Pacific during World War II

DTIC Science & Technology

2010-04-06

successfully tested at Los Alamos, New Mexico. Tinian-based B-29 drops atomic bomb on Hiroshima. Tinian-based B-29 drops atomic bomb on Nagasaki. Russia...I< URO SHiM.\\ ~KAM!Y MothiiiOIO WAN tlTSUGEN SHIM!\\ Yli>:ABI SHIMA• ·~ i hMA,. SHIMA SHIIIIA :;nu~l·;;. U··be u’" OliO ru · ~Kil. SHlMA<:?r..EA MA...J .. _ ... ··j"··· JAPANESE DEFENSIVE OISPOS1TIONS 1 APRIL 1945 I - ~ .’!1 -4 lCXX 00 c?Sl29 tCORPS RES) lO ( [8Jr XX (Z17

Selection and Evaluation of a Real Time Monitoring System for the Bigeye Bomb Fill/Close Production Facility. Phase 2

DTIC Science & Technology

1989-06-01

and ZIP Code ) 10 SOURCE OF FUNDING NU MBERS I O KUI PROGRAM PRO ECCT TASKWOKUI E L E M E N T N O . N O .I 1 2 0 N O A 5 A C C E S S I O N N OlI I1 TITLE... source of by-products formation. Generating Data for Mathematical Modeling of Real Vapor Phase Reaction Systems (tremendously speeds multi -level, multi ...SMCC-RI1 6c AD RS(Ciry,. State, and ZIP Code ) SCRRI 7b. ADDRESS (City, State, and ZIP Code ) IA!hrueýýt Proving Ground, MD 21010-54213 a.NMOFFUNI.DNG

Implementation of Sentinel-2 Data in the M4Land System for the Generation of Continuous Information Products in Agriculture

NASA Astrophysics Data System (ADS)

Klug, P.; Schlenz, F.; Hank, T.; Migdall, S.; Weiß, I.; Danner, M.; Bach, H.; Mauser, W.

2016-08-01

The analysis system developed in the frame of the M4Land project (Model based, Multi-temporal, Multi scale and Multi sensorial retrieval of continuous land management information) has proven its capabilities of classifying crop type and creating products on the intensity of agricultural production using optical remote sensing data from Landsat and RapidEye. In this study, Sentinel-2 data is used for the first time together with Landsat 7 ETM+ and 8 OLI data within the M4Land analysis system to derive continuously crop type and the agricultural intensity of fields in an area north of Munich, Germany and the year 2015.

Estimation of carbon emission from peatland fires using Landsat-8 OLI imagery in Siak District, Riau Province

NASA Astrophysics Data System (ADS)

Aisyah Fadhillah Hafni, Dinda; Syaufina, Lailan; Puspaningsih, Nining; Prasasti, Indah

2018-05-01

The study was conducted in three land cover conditions (secondary peat forest, shrub land, and palm plantation) that were burned in the Siak District, Riau Province, Indonesia year 2015. Measurement and calculation carbon emission from soil and vegetation of peatland should be done accurately to be implemented on climate change mitigation or greenhouse gases mitigation. The objective of the study was to estimate the carbon emission caused peatland fires in the Siak District, Riau Province, Indonesia year 2015. Estimated carbon emissions were performed using visual method and digital method. The visual method was a method that uses on-screen digitization assisted by hotspot data, the presence of smoke, and fire suppression data. The digital method was a method that uses the Normalized Burn Ratio (NBR) index. The estimated carbon emissions were calculated using the equation that was developed from IPCC 2006 in Verified Carbon Standard 2015. The results showed that the estimation of carbon emissions from fires from above the peat soil surface were higher than the carbon emissions from the peat soil. Carbon emissions above the peat soil surface of 1376.51 ton C/ha were obtained by visual method while 3984.33 ton C/ha were obtained by digital method. Peatland carbon emissions of 6.6 x 10-4 ton C/ha were obtained by visual method, whereas 2.84 x 10-3 ton C/ha was obtained by digital method. Visual method and digital method using remote sensing must be combined and developed in order to carbon emission values will be more accurate.

Impact of the spatial resolution of satellite remote sensing sensors in the quantification of total suspended sediment concentration: A case study in turbid waters of Northern Western Australia.

PubMed

Dorji, Passang; Fearns, Peter

2017-01-01

The impact of anthropogenic activities on coastal waters is a cause of concern because such activities add to the total suspended sediment (TSS) budget of the coastal waters, which have negative impacts on the coastal ecosystem. Satellite remote sensing provides a powerful tool in monitoring TSS concentration at high spatiotemporal resolution, but coastal managers should be mindful that the satellite-derived TSS concentrations are dependent on the satellite sensor's radiometric properties, atmospheric correction approaches, the spatial resolution and the limitations of specific TSS algorithms. In this study, we investigated the impact of different spatial resolutions of satellite sensor on the quantification of TSS concentration in coastal waters of northern Western Australia. We quantified the TSS product derived from MODerate resolution Imaging Spectroradiometer (MODIS)-Aqua, Landsat-8 Operational Land Image (OLI), and WorldView-2 (WV2) at native spatial resolutions of 250 m, 30 m and 2 m respectively and coarser spatial resolution (resampled up to 5 km) to quantify the impact of spatial resolution on the derived TSS product in different turbidity conditions. The results from the study show that in the waters of high turbidity and high spatial variability, the high spatial resolution WV2 sensor reported TSS concentration as high as 160 mg L-1 while the low spatial resolution MODIS-Aqua reported a maximum TSS concentration of 23.6 mg L-1. Degrading the spatial resolution of each satellite sensor for highly spatially variable turbid waters led to variability in the TSS concentrations of 114.46%, 304.68% and 38.2% for WV2, Landsat-8 OLI and MODIS-Aqua respectively. The implications of this work are particularly relevant in the situation of compliance monitoring where operations may be required to restrict TSS concentrations to a pre-defined limit.

Seasonal discrimination of C3 and C4 grasses functional types: An evaluation of the prospects of varying spectral configurations of new generation sensors

NASA Astrophysics Data System (ADS)

Shoko, Cletah; Mutanga, Onisimo

2017-10-01

The present study assessed the potential of varying spectral configuration of Landsat 8 Operational Land Imager (OLI), Sentinel 2 MultiSpectal Instrument (MSI) and Worldview 2 sensors in the seasonal discrimination of Festuca costata (C3) and Themeda Triandra (C4) grass species in the Drakensberg, South Africa. This was achieved by resampling hyperspectral measurements to the spectral windows corresponding to the three sensors at two distinct seasonal periods (summer peak and end of winter), using the Discriminant Analysis (DA) classification ensemble. In summer, standard bands of the Worldview 2 produced the highest overall classification accuracy (98.61%), followed by Sentinel 2 (97.52%), whereas the Landsat 8 spectral configuration was the least performer, using vegetation indices (95.83%). In winter, Sentinel 2 spectral bands produced the highest accuracy (96.18%) for the two species, followed by Worldview 2 (94.44%) and Landsat 8 yielded the least (91.67%) accuracy. Results also showed that maximum separability between C3 and C4 grasses was in summer, while at the end of winter considerable overlaps were noted, especially when using the spectral settings of the Landsat 8 OLI and Sentinel 2 shortwave infrared bands. Test of significance in species reflectance further confirmed that in summer, there were significant differences (P < 0.05), whereas in winter, most of the spectral windows of all sensors yielded insignificant differences (P > 0.05) between the two species. In this regard, the peak summer period presents a promising opportunity for the spectral discrimination of C3 and C4 grass species functional types, than the end of winter, when using multispectral sensors. Results from this study highlight the influence of seasonality on discrimination and therefore provide the basis for the successful discrimination and mapping of C3 and C4 grass species.

In silico studies to explore the mutagenic ability of 5-halo/oxy/li-oxy-uracil bases with guanine of DNA base pairs.

PubMed

Jana, Kalyanashis; Ganguly, Bishwajit

2014-10-16

DNA nucleobases are reactive in nature and undergo modifications by deamination, oxidation, alkylation, or hydrolysis processes. Many such modified bases are susceptible to mutagenesis when formed in cellular DNA. The mutagenesis can occur by mispairing with DNA nucleobases by a DNA polymerase during replication. We have performed a study of mispairing of DNA bases with unnatural bases computationally. 5-Halo uracils have been studied as mispairs in mutagenesis; however, the reports on their different forms are scarce in the literature. The stability of mispairs with keto form, enol form, and ionized form of 5-halo-uracil has been computed with the M06-2X/6-31+G** level of theory. The enol form of 5-halo-uracil showed remarkable stability toward DNA mispair compared to the corresponding keto and ionized forms. (F)U-G mispair showed the highest stability in the series and (Halo)(U(enol/ionized)-G mispair interactions energies are more stable than the natural G-C basepair of DNA. To enhance the stability of DNA mispairs, we have introduced the hydroxyl group in the place of halogen atoms, which provides additional hydrogen-bonding interactions in the system while forming the 5-membered ring. The study has been further extended with lithiated 5-hydroxymethyl-uracil to stabilize the DNA mispair. (CH2OLi)U(ionized)-G mispair has shown the highest stability (ΔG = -32.4 kcal/mol) with multi O-Li interactions. AIM (atoms in molecules) and EDA (energy decomposition analysis) analysis has been performed to examine the nature of noncovalent interactions in such mispairs. EDA analysis has shown that electrostatic energy mainly contributes toward the interaction energy of mispairs. The higher stability achieved in these studied mispairs can play a pivotal role in the mutagenesis and can help to attain the mutation for many desired biological processes.

Validation of VIIRS Land Surface Phenology using Field Observations, PhenoCam Imagery, and Landsat data

NASA Astrophysics Data System (ADS)

Zhang, X.; Jayavelu, S.; Wang, J.; Henebry, G. M.; Gray, J. M.; Friedl, M. A.; Liu, Y.; Schaaf, C.; Shuai, A.

2016-12-01

A large number of land surface phenology (LSP) products have been produced from various detection algorithms applied to coarse resolution satellite datasets across regional to global scales. However, validation of the resulting LSP products is very challenging because in-situ observations at comparable spatiotemporal scales are generally not available. This research focuses on efforts to evaluate and validate the global 500m LSP product produced from Visible Infrared Imaging Radiometer Suite (VIIRS) NBAR time series for 2013 and 2014. Specifically, we used three different datasets to evaluate six VIIRS LSP metrics of greenup onset, mid-point of greenup phase, maturity onset, senescence onset, mid-point of senescence phase, and dormancy onset. First, we obtained the field observations from the USA National Phenology Network that has gathered extensive phenological data on individual species. Although it is inappropriate to compare these data directly with the LSP footprints, this large and spatially distributed dataset allows us to evaluate the overall quality of VIIRS LSP results. Second, we gathered PhenoCam imagery from 164 sites, which was used to extract the daily green chromatic coordinate (GCC) and vegetation contrast index (VCI)values. Utilizing these PhenoCam time series, the phenological events were quantified using a hybrid piecewise logistic models for each site. Third, we detected the phenological timing at the landscape scale (30m) from surface reflectance simulated by fusing MODIS data and Landsat 8 OLI observations in an agricultural area (in the central USA) and from overlap zones of OLI scenes in semiarid areas (California and Tibetan Plateau). The phenological timing from these three datasets was used to compare with VIIRS LSP data. Preliminary results show that the VIIRS LSP are generally comparable with phenological data from the USA-NPN, PhenoCam, and Landsat data, with differences arising in specific phenological events and land cover types.

Animal performance and meat characteristics in steers reared in intensive conditions fed with different vegetable oils.

PubMed

Castro, T; Cabezas, A; De la Fuente, J; Isabel, B; Manso, T; Jimeno, V

2016-03-01

Enhancing the quality of beef meat is an important goal in terms of improving both the nutritional value for the consumer and the commercial value for producers. The aim of this work was to study the effects of different vegetable oil supplements on growth performance, carcass quality and meat quality in beef steers reared under intensive conditions. A total of 240 Blonde D' Aquitaine steers (average BW=293.7±38.88 kg) were grouped into 24 batches (10 steers/batch) and were randomly assigned to one of the three dietary treatments (eight batches per treatment), each supplemented with either 4% hydrogenated palm oil (PALM) or fatty acids (FAs) from olive oil (OLI) or soybean oil (SOY). No differences in growth performance or carcass quality were observed. For the meat quality analysis, a steer was randomly selected from each batch and the 6th rib on the left half of the carcass was dissected. PALM meat had the highest percentage of 16:0 (P<0.05) and the lowest n-6/n-3 polyunsaturated fatty acids (PUFA) ratio (P<0.05), OLI had the highest content of t11-18:1 (P<0.01) and c9,t11-18:2 (P<0.05) and SOY showed the lowest value of monounsaturated fatty acids (MUFA) (P<0.001), the highest percentage of PUFA (P<0.01) and a lower index of atherogenicity (P=0.07) than PALM. No significant differences in the sensory characteristics of the meat were noted. However, the results of the principal component analysis of meat characteristics enabled meat from those steers that consumed fatty acids from olive oil to be differentiated from that of steers that consumed soybean oil.

Joint Use of Sentinel-1 and Landsat-8 data for Burned Areas Mapping: the Case of the Sardinia Island, Italy

NASA Astrophysics Data System (ADS)

Pepe, Antonio; Azar, Ramin; Calò, Fabiana; Stroppiana, Daniela; Brivio, Pietro Alessandro; Imperatore, Pasquale

2016-04-01

Fires widely affect Mediterranean regions, causing severe threats to human lives and damages to natural environments. The socio-economic impacts of fires on the affected local communities are significant, indeed, the activation of prevention measures and the extinguishment of fires and reclamation of the pre-fire conditions are very expensive. Moreover, fires have also global impacts: they affect global warming and climate changes due to gas and aerosol emissions to atmosphere. In such a context, fire scars mapping and monitoring are fundamental tasks for a sustainable management of natural resources and for the prevention/mitigation of fire risk. With this respect, remotely sensed data offer the opportunity for a regional-up-to-global scale monitoring of areas prone to fires, on a cost-effective and regular basis. In this work, the potential of a joint use of Sentinel-1A (C-band) Synthetic Aperture Radar (SAR) and Landsat-8 Operational Land Imager (OLI) data for detecting burned areas is investigated. The experimental analyses are conducted by focusing on Sardinia Island, which is one of the Italian regions most affected by fire events during summer. Our analysis shows that the capability of monitoring burned areas in the Mediterranean environment can be improved by exploiting information embedded in OLI multispectral bands in conjunction with multi-temporal dual-polarized SAR data. Indeed, limitations experienced in analyses based on the use of only optical data (e.g., cloud cover, spectral overlap/confusion of burned areas with dark soils, water surfaces and shaded regions) may be overcome by using SAR data, owing to the insensitiveness to sunlight-illumination conditions and the cloud-penetrating capability of microwave radiation. Results prove the effectiveness of an integrated approach based on the combination of optical and microwave imagery for the monitoring and mapping of burned areas in vegetated regions.

The Sargassum Early Advisory System (SEAS)

NASA Astrophysics Data System (ADS)

Armstrong, D.; Gallegos, S. C.

2016-02-01

The Sargassum Early Advisory System (SEAS) web-app was designed to automatically detect Sargassum at sea, forecast movement of the seaweed, and alert users of potential landings. Inspired to help address the economic hardships caused by large landings of Sargassum, the web app automates and enhances the manual tasks conducted by the SEAS group of Texas A&M University at Galveston. The SEAS web app is a modular, mobile-friendly tool that automates the entire workflow from data acquisition to user management. The modules include: 1) an Imagery Retrieval Module to automatically download Landsat-8 Operational Land Imagery (OLI) from the United States Geological Survey (USGS), 2) a Processing Module for automatic detection of Sargassum in the OLI imagery, and subsequent mapping of theses patches in the HYCOM grid, producing maps that show Sargassum clusters; 3) a Forecasting engine fed by the HYbrid Coordinate Ocean Model (HYCOM) model currents and winds from weather buoys; and 4) a mobile phone optimized geospatial user interface. The user can view the last known position of Sargassum clusters, trajectory and location projections for the next 24, 72 and 168 hrs. Users can also subscribe to alerts generated for particular areas. Currently, the SEAS web app produces advisories for Texas beaches. The forecasted Sargassum landing locations are validated by reports from Texas beach managers. However, the SEAS web app was designed to easily expand to other areas, and future plans call for extending the SEAS web app to Mexico and the Caribbean islands. The SEAS web app development is led by NASA, with participation by ASRC Federal/Computer Science Corporation, and the Naval Research Laboratory, all at Stennis Space Center, and Texas A&M University at Galveston.

Monitoring terrestrial dissolved organic carbon export at land-water interfaces using remote sensing

NASA Astrophysics Data System (ADS)

Yu, Q.; Li, J.; Tian, Y. Q.

2017-12-01

Carbon flux from land to oceans and lakes is a crucial component of carbon cycling. However, this lateral carbon flow at land-water interface is often neglected in the terrestrial carbon cycle budget, mainly because observations of the carbon dynamics are very limited. Monitoring CDOM/DOC dynamics using remote sensing and assessing DOC export from land to water remains a challenge. Current CDOM retrieval algorithms in the field of ocean color are not simply applicable to inland aquatic ecosystems since they were developed for coarse resolution ocean-viewing imagery and less complex water types in open-sea. We developed a new semi-analytical algorithm, called SBOP (Shallow water Bio-Optical Properties algorithm) to adapt to shallow inland waters. SBOP was first developed and calibrated based on in situ hyperspectral radiometer data. Then we applied it to the Landsat-8 OLI images and evaluated the effectiveness of the multispectral images on inversion of CDOM absorption based on our field sampling at the Saginaw Bay in the Lake Huron. The algorithm performances (RMSE = 0.17 and R2 = 0.87 in the Saginaw Bay; R2 = 0.80 in the northeastern US lakes) is promising and we conclude the CDOM absorption can be derived from Landsat-8 OLI image in both optically deep and optically shallow waters with high accuracy. Our method addressed challenges on employing appropriate atmospheric correction, determining bottom reflectance influence for shallow waters, and improving for bio-optical properties retrieval, as well as adapting to both hyperspectral and the multispectral remote sensing imagery. Over 100 Landsat-8 images in Lake Huron, northeastern US lakes, and the Arctic major rivers were processed to understand the CDOM spatio-temporal dynamics and its associated driving factors.

Exploiting the capabilities of the Sentinel-2 multi spectral instrument for predicting growing stock volume in forest ecosystems

NASA Astrophysics Data System (ADS)

Mura, Matteo; Bottalico, Francesca; Giannetti, Francesca; Bertani, Remo; Giannini, Raffaello; Mancini, Marco; Orlandini, Simone; Travaglini, Davide; Chirici, Gherardo

2018-04-01

The spatial prediction of growing stock volume is one of the most frequent application of remote sensing for supporting the sustainable management of forest ecosystems. For such a purpose data from active or passive sensors are used as predictor variables in combination with measures taken in the field in sampling plots. The Sentinel-2 (S2) satellites are equipped with a Multi Spectral Instrument (MSI) capable of acquiring 13 bands in the visible and infrared domains with a spatial resolution varying between 10 and 60 m. The present study aimed at evaluating the performance of the S2-MSI imagery for estimating the growing stock volume of forest ecosystems. To do so we used 240 plots measured in two study areas in Italy. The imputation was carried out with eight k-Nearest Neighbours (k-NN) methods available in the open source YaImpute R package. In order to evaluate the S2-MSI performance we repeated the experimental protocol also with two other sets of images acquired by two well-known satellites equipped with multi spectral instruments: Landsat 8 OLI and RapidEye scanner. We found that S2 worked better than Landsat in 37.5% of the cases and in 62.5% of the cases better than RapidEye. In one study area the best performance was obtained with Landsat OLI (RMSD = 6.84%) and in the other with S2 (RMSD = 22.94%), both with the k-NN system based on a distance matrix calculated with the Random Forest algorithm. The results confirmed that S2 images are suitable for predicting growing stock volume obtaining good performances (average RMSD for both the test areas of less than 19%).

Impact of the spatial resolution of satellite remote sensing sensors in the quantification of total suspended sediment concentration: A case study in turbid waters of Northern Western Australia

PubMed Central

Fearns, Peter

2017-01-01

The impact of anthropogenic activities on coastal waters is a cause of concern because such activities add to the total suspended sediment (TSS) budget of the coastal waters, which have negative impacts on the coastal ecosystem. Satellite remote sensing provides a powerful tool in monitoring TSS concentration at high spatiotemporal resolution, but coastal managers should be mindful that the satellite-derived TSS concentrations are dependent on the satellite sensor’s radiometric properties, atmospheric correction approaches, the spatial resolution and the limitations of specific TSS algorithms. In this study, we investigated the impact of different spatial resolutions of satellite sensor on the quantification of TSS concentration in coastal waters of northern Western Australia. We quantified the TSS product derived from MODerate resolution Imaging Spectroradiometer (MODIS)-Aqua, Landsat-8 Operational Land Image (OLI), and WorldView-2 (WV2) at native spatial resolutions of 250 m, 30 m and 2 m respectively and coarser spatial resolution (resampled up to 5 km) to quantify the impact of spatial resolution on the derived TSS product in different turbidity conditions. The results from the study show that in the waters of high turbidity and high spatial variability, the high spatial resolution WV2 sensor reported TSS concentration as high as 160 mg L-1 while the low spatial resolution MODIS-Aqua reported a maximum TSS concentration of 23.6 mg L-1. Degrading the spatial resolution of each satellite sensor for highly spatially variable turbid waters led to variability in the TSS concentrations of 114.46%, 304.68% and 38.2% for WV2, Landsat-8 OLI and MODIS-Aqua respectively. The implications of this work are particularly relevant in the situation of compliance monitoring where operations may be required to restrict TSS concentrations to a pre-defined limit. PMID:28380059

Cerium-Hydride Secondary Building Units in a Porous Metal–Organic Framework for Catalytic Hydroboration and Hydrophosphination

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

Ji, Pengfei; Sawano, Takahiro; Lin, Zekai

2016-11-16

We report the stepwise, quantitative transformation of CeIV6(μ3-O)4(μ3-OH)4(OH)6(OH2)6 nodes in a new Ce-BTC (BTC = trimesic acid) metal–organic framework (MOF) into the first CeIII6(μ3-O)4(μ3-OLi)4(H)6(THF)6Li6 metal-hydride nodes that effectively catalyze hydroboration and hydrophosphination reactions. CeH-BTC displays low steric hindrance and electron density compared to homogeneous organolanthanide catalysts, which likely accounts for the unique 1,4-regioselectivity for the hydroboration of pyridine derivatives. MOF nodes can thus be directly transformed into novel single-site solid catalysts without homogeneous counterparts for sustainable chemical synthesis.

Tokyo IAP, Honshu, Japan. Revised Uniform Summary of Surface Weather Observations (RUSSWO). Parts A-F

DTIC Science & Technology

1974-03-24

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Estimation of both optical and nonoptical surface water quality parameters using Landsat 8 OLI imagery and statistical techniques

NASA Astrophysics Data System (ADS)

Sharaf El Din, Essam; Zhang, Yun

2017-10-01

Traditional surface water quality assessment is costly, labor intensive, and time consuming; however, remote sensing has the potential to assess surface water quality because of its spatiotemporal consistency. Therefore, estimating concentrations of surface water quality parameters (SWQPs) from satellite imagery is essential. Remote sensing estimation of nonoptical SWQPs, such as chemical oxygen demand (COD), biochemical oxygen demand (BOD), and dissolved oxygen (DO), has not yet been performed because they are less likely to affect signals measured by satellite sensors. However, concentrations of nonoptical variables may be correlated with optical variables, such as turbidity and total suspended sediments, which do affect the reflected radiation. In this context, an indirect relationship between satellite multispectral data and COD, BOD, and DO can be assumed. Therefore, this research attempts to develop an integrated Landsat 8 band ratios and stepwise regression to estimate concentrations of both optical and nonoptical SWQPs. Compared with previous studies, a significant correlation between Landsat 8 surface reflectance and concentrations of SWQPs was achieved and the obtained coefficient of determination (R2)>0.85. These findings demonstrated the possibility of using our technique to develop models to estimate concentrations of SWQPs and to generate spatiotemporal maps of SWQPs from Landsat 8 imagery.

Normalized difference vegetation index (ndvi) analysis for land cover types using landsat 8 oli in besitang watershed, Indonesia

NASA Astrophysics Data System (ADS)

Zaitunah, A.; Samsuri; Ahmad, A. G.; Safitri, R. A.

2018-03-01

Watershed is an ecosystem area confined by topography and has function as a catcher, storage, and supplier of water, sediments, pollutants and nutrients in the river system and exit through a single outlet. Various activities around watershed areas of Besitang have changed the land cover and vegetation index (NDVI) that exist in the region. In order to detect changes in land cover and NDVI quickly and accurately, we used remote sensing technology and geographic information systems (GIS). The study aimed to assess changes in land cover and vegetation density (NDVI) between 2005 and 2015, as well as obtaining the density of vegetation (NDVI) on each of the land cover of 2005 and 2015. The research showed the extensive of forest area of 949.65 Ha and a decline of mangrove forest area covering an area of 2,884.06 Ha. The highest vegetation density reduced 39,714.58 Ha, and rather dense increased 24,410.72 Ha between 2005 and 2015. The land cover that have the highest NDVI value range with very dense vegetation density class is the primary dry forest (0.804 to 0.876), followed by secondary dry forest (0.737 to 0.804) for 2015. In 2015 the land cover has NDVI value range the primary dry forest (0.513 to 0.57), then secondary dry forest (0.456 to 0.513) with dense vegetation density class

Calibration of the Thermal Infrared Sensor on the Landsat Data Continuity Mission

NASA Technical Reports Server (NTRS)

Thome, K; Reuter, D.; Lunsford, D.; Montanaro, M.; Smith, J.; Tesfaye, Z.; Wenny, B.

2011-01-01

The Landsat series of satellites provides the longest running continuous data set of moderate-spatial-resolution imagery beginning with the launch of Landsat 1 in 1972 and continuing with the 1999 launch of Landsat 7 and current operation of Landsats 5 and 7. The Landsat Data Continuity Mission (LDCM) will continue this program into a fourth decade providing data that are keys to understanding changes in land-use changes and resource management. LDCM consists of a two-sensor platform comprised of the Operational Land Imager (OLI) and Thermal Infrared Sensors (TIRS). A description of the applications and design of the TIRS instrument is given as well as the plans for calibration and characterization. Included are early results from preflight calibration and a description of the inflight validation.

Barra da Tijuca, Rio de Janeiro, from Space

NASA Image and Video Library

2017-12-08

While gymnasts leap, cyclists pedal and divers twirl for Olympic gold in Rio de Janeiro, Brazil, several NASA Earth Observing satellites catch glimpses of the city and its surroundings from space. This image shows how Rio Olympic Park appeared to the Operational Land Imager (OLI), a sensor on Landsat 8, last September as the city prepared for the 2016 Summer Olympic Games. Image credit: Landsat 8/NASA Earth Observatory NASA image use policy. NASA Goddard Space Flight Center enables NASA’s mission through four scientific endeavors: Earth Science, Heliophysics, Solar System Exploration, and Astrophysics. Goddard plays a leading role in NASA’s accomplishments by contributing compelling scientific knowledge to advance the Agency’s mission. Follow us on Twitter Like us on Facebook Find us on Instagram

Airsickness During Naval Flight Officer Training: Advanced Squadron VT86-RIO (New Syllabus).

DTIC Science & Technology

1981-09-01

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Tracking surface and subsurface lakes on the Greenland Ice Sheet using Sentinel-1 SAR and Landsat-8 OLI imagery

NASA Astrophysics Data System (ADS)

Miles, Katie; Willis, Ian; Benedek, Corinne; Williamson, Andrew; Tedesco, Marco

2017-04-01

Supraglacial lakes (SGLs) on the Greenland Ice Sheet (GrIS) are an important component of the ice sheet's mass balance and hydrology, with their drainage affecting ice dynamics. This study uses imagery from the recently launched Sentinel-1A Synthetic Aperture Radar (SAR) to investigate SGLs in West Greenland. SAR can image through cloud and in darkness, overcoming some of the limitations of commonly used optical sensors. A semi automated algorithm is developed to detect surface lakes from Sentinel images during the 2015 summer. It generally detects water in all locations where a Landsat-8 NDWI classification (with a relatively high threshold value) detects water. A combined set of images from Landsat-8 and Sentinel-1 is used to track lake behaviour at a comparable temporal resolution to that which is possible with MODIS, but at a higher spatial resolution. A fully automated lake drainage detection algorithm is used to investigate both rapid and slow drainages for both small and large lakes through the summer. Our combined Landsat-Sentinel dataset, with a temporal resolution of three days, could track smaller lakes (mean 0.089 km2) than are resolvable in MODIS (minimum 0.125 km2). Small lake drainage events (lakes smaller than can be detected using MODIS) were found to occur at lower elevations ( 200 m) and slightly earlier in the melt season than larger events, as were slow lake drainage events compared to rapid events. The Sentinel imagery allows the analysis to be extended manually into the early winter to calculate the dates and elevations of lake freeze-through more precisely than is possible with optical imagery (mean 30 August, 1270 m mean elevation). Finally, the Sentinel imagery allows subsurface lakes (which are invisible to optical sensors) to be detected, and, for the first time, their dates of appearance and freeze-through to be calculated (mean 9 August and 7 October, respectively). These subsurface lakes occur at higher elevations than the surface lakes detected in this study (1593 m mean elevation). Sentinel imagery therefore provides great potential for tracking melting, water movement and freezing within the firn zone of the GrIS.

Evaluation and time series analysis of mountain snow from MODIS and VIIRS fractional snow cover products

NASA Astrophysics Data System (ADS)

Bormann, K.; Rittger, K.; Painter, T. H.

2016-12-01

The continuation of large-scale snow cover records into the future is crucial for monitoring the impacts of global pressures such as climate change and weather variability on the cryosphere. With daily MODIS records since 2000 from a now ageing MODIS constellation (Terra & Aqua) and daily VIIRS records since 2012 from the Suomi-NPP platform, the consistency of information between the two optical sensors must be understood. First, we evaluated snow cover maps derived from both MODIS and VIIRS retrievals with coincident cloud-free Landsat 8 OLI maps across a range of locations. We found that both MODIS and VIIRS snow cover maps show similar errors when evaluated with Landsat OLI retrievals. Preliminary results also show a general agreement in regional snowline between the two sensors that is maintained during the spring snowline retreat where the proportion of mixed pixels is increased. The agreement between sensors supports the future use of VIIRS snow cover maps to continue the long-term record beyond the lifetime of MODIS. Second, we use snowline elevation to quantify large scale snow cover variability and to monitor potential changes in the rain/snow transition zone where climate change pressures may be enhanced. Despite the large inter-annual variability that is often observed in snow metrics, we expect that over the 16-year time series we will see a rise in seasonal elevation of the snowline and consequently an increasing rain/snow transition boundary in mountain environments. These results form the basis for global snowline elevation monitoring using optical remote sensing data and highlight regional differences in snowline elevation dynamics. The long-term variability in observed snowline elevation provides a recent climatology of mountain snowpack across several regions that will likely to be of interest to those interested in climate change impacts in mountain environments. This work will also be of interest to existing users of MODSCAG and VIIRSCAG snow

Multi-stage approach to estimate forest biomass in degraded area by fire and selective logging

NASA Astrophysics Data System (ADS)

Santos, E. G.; Shimabukuro, Y. E.; Arai, E.; Duarte, V.; Jorge, A.; Gasparini, K.

2017-12-01

The Amazon forest has been the target of several threats throughout the years. Anthropogenic disturbances in the region can significantly alter this environment, affecting directly the dynamics and structure of tropical forests. Monitoring these threats of forest degradation across the Amazon is of paramount to understand the impacts of disturbances in the tropics. With the advance of new technologies such as Light Detection and Ranging (LiDAR) the quantification and development of methodologies to monitor forest degradation in the Amazon is possible and may bring considerable contributions to this topic. The objective of this study was to use remote sensing data to assess and estimate the aboveground biomass (AGB) across different levels of degradation (fire and selective logging) using multi-stage approach between airborne LiDAR and orbital image. The study area is in the northern part of the state of Mato Grosso, Brazil. It is predominantly characterized by agricultural land and remnants of the Amazon Forest intact and degraded by either anthropic or natural reasons (selective logging and/or fire). More specifically, the study area corresponds to path/row 226/69 of OLI/Landsat 8 image. With a forest mask generated from the multi-resolution segmentation, agriculture and forest areas, forest biomass was calculated from LiDAR data and correlated with texture images, vegetation indices and fraction images by Linear Spectral Unmixing of OLI/Landsat 8 image and extrapolated to the entire scene 226/69 and validated with field inventories. The results showed that there is a moderate to strong correlation between forest biomass and texture data, vegetation indices and fraction images. With that, it is possible to extract biomass information and create maps using optical data, specifically by combining vegetation indices, which contain forest greening information with texture data that contains forest structure information. Then it was possible to extrapolate the biomass

Examining the strength of the newly-launched Sentinel 2 MSI sensor in detecting and discriminating subtle differences between C3 and C4 grass species

NASA Astrophysics Data System (ADS)

Shoko, C.; Mutanga, O.

2017-07-01

C3 and C4 grass species discrimination has increasingly become relevant in understanding their response to environmental changes and to monitor their integrity in providing goods and services. While remotely-sensed data provide robust, cost-effective and repeatable monitoring tools for C3 and C4 grasses, this has been largely limited by the scarcity of sensors with better earth imaging characteristics. The recent launch of the advanced Sentinel 2 MultiSpectral Instrument (MSI) presents a new prospect for discriminating C3 and C4 grasses. The present study tested the potential of Sentinel 2, characterized by refined spatial resolution and more unique spectral bands in discriminating between Festuca (C3) and Themeda (C4) grasses. To evaluate the performance of Sentinel 2 MSI; spectral bands, vegetation indices and spectral bands plus indices were used. Findings from Sentinel 2 were compared with those derived from the widely-used Worldview 2 commercial sensor and the Landsat 8 Operational Land Imager (OLI). Overall classification accuracies have shown that Sentinel 2 bands have potential (90.36%), than indices (85.54%) and combined variables (88.61%). The results were comparable to Worldview 2 sensor, which produced slightly higher accuracies using spectral bands (95.69%), indices (86.02%) and combined variables (87.09%), and better than Landsat 8 OLI spectral bands (75.26%), indices (82.79%) and combined variables (86.02%). Sentinel 2 bands produced lower errors of commission and omission (between 4.76 and 14.63%), comparable to Worldview 2 (between 1.96 and 7.14%), than Landsat 8 (between 18.18 and 30.61%), when classifying the two species. The classification accuracy from Sentinel 2 also did not differ significantly (z = 1.34) from Worldview 2, using standard bands; it was significantly (z > 1.96) different using indices and combined variables, whereas when compared to Landsat 8, Sentinel 2 accuracies were significantly different (z > 1.96) using all variables

Msh1p counteracts oxidative lesion-induced instability of mtDNA and stimulates mitochondrial recombination in Saccharomyces cerevisiae.

PubMed

Kaniak, Aneta; Dzierzbicki, Piotr; Rogowska, Agata T; Malc, Ewa; Fikus, Marta; Ciesla, Zygmunt

2009-03-01

The proximity of the mitochondrial genome to the respiratory chain, a major source of ROS (radical oxygen species), makes mtDNA more vulnerable to oxidative damage than nuclear DNA. Mitochondrial BER (base excision repair) is generally considered to be the main pathway involved in the prevention of oxidative lesion-induced mutations in mtDNA. However, we previously demonstrated that the increased frequency of mitochondrial Oli(r) mutants in an ogg1Delta strain, lacking the activity of a crucial mtBER glycosylase, is reduced in the presence of plasmids encoding Msh1p, the mitochondrial homologue of the bacterial mismatch protein MutS. This finding suggested that Msh1p might be involved in the prevention of mitochondrial mutagenesis induced by oxidative stress. Here we show that a double mutant carrying the msh1-R813W allele, encoding a variant of the protein defective in the ATP hydrolysis activity, combined with deletion of SOD2, encoding the mitochondrial superoxide dismutase, displays a synergistic effect on the frequency of Oli(r) mutants, indicating that Msh1p prevents generation of oxidative lesion-induced mitochondrial mutations. We also show that double mutants carrying the msh1-R813W allele, combined with deletion of either OGG1 or APN1, the latter resulting in deficiency of the Apn1 endonuclease, exhibit a synergistic effect on the frequency of respiration-defective mutants having gross rearrangements of the mitochondrial genome. This suggests that Msh1p, Ogg1p and Apn1p play overlapping functions in maintaining the stability of mtDNA. In addition, we demonstrate, using a novel ARG8(m) recombination assay, that a surplus of Msh1p results in enhanced mitochondrial recombination. Interestingly, the mutant forms of the protein, msh1p-R813W and msh1p-G776D, fail to stimulate recombination. We postulate that the Msh1p-enhanced homologous recombination may play an important role in the prevention of oxidative lesion-induced rearrangements of the mitochondrial

Multi-resource data-based research on remote sensing monitoring over the green tide in the Yellow Sea

NASA Astrophysics Data System (ADS)

Gao, Zhiqiang; Xu, Fuxiang; Song, Debin; Zheng, Xiangyu; Chen, Maosi

2017-09-01

This paper conducted dynamic monitoring over the green tide (large green alga—Ulva prolifera) occurred in the Yellow Sea in 2014 to 2016 by the use of multi-source remote sensing data, including GF-1 WFV, HJ-1A/1B CCD, CBERS-04 WFI, Landsat-7 ETM+ and Landsta-8 OLI, and by the combination of VB-FAH (index of Virtual-Baseline Floating macroAlgae Height) with manual assisted interpretation based on remote sensing and geographic information system technologies. The result shows that unmanned aerial vehicle (UAV) and shipborne platform could accurately monitor the distribution of Ulva prolifera in small spaces, and therefore provide validation data for the result of remote sensing monitoring over Ulva prolifera. The result of this research can provide effective information support for the prevention and control of Ulva prolifera.

Solutions Network Formulation Report. The Potential Contribution of the Landsat Data Continuity Mission to the Mississippi Coastal Improvements Project

NASA Technical Reports Server (NTRS)

Hilbert, Kent; Anderson, Daniel; Lewis, David

2007-01-01

The 2005 hurricane season - especially Hurricane Katrina - left the Mississippi Gulf Coast devastated. In its efforts to assist in coastal re-building efforts, the U.S. Congress passed the Defense Appropriation Act of 2006. This legislation directed the Secretary of the Army, via the USACE, to generate reports discussing possible projects that would improve the State of Mississippi?s coastal region. These projects are referred to as the MsCIP. Data collected via the LDCM OLI could be used to evaluate the success of projects that result from the MsCIP by monitoring regional coastal changes associated with such projects. This Candidate Solution is in alignment with the Coastal Management, Water Management, and Disaster Management National Applications and will benefit society by improving the post-Hurricane Katrina Mississippi Gulf Coast.

Effect of additive on Zeta potential and particle size of nickel nanoparticles

NASA Astrophysics Data System (ADS)

Sharma, Vikash; Tarachand, Chotia, Chandrabhan; Okram, G. S.

2017-05-01

Nickel nanoparticles (NPs) were prepared by thermal decomposition method using Oleylamine (OLY) as a solvent and Trioctylphosphine (TOP) as a surfactant. We have investigated the effect of pH and addition of Ethylenediamine tetraacetic acid (EDTA) on the stability and particle size of Ni NPs using zeta potential and particle size analyser. Coating of the surfactants on the surface of Ni NPs was confirmed by Fourier transform infrared (FTIR) spectroscopy. Autotitration study of zeta potential of these NPs in ethanol by dynamic light scattering (DLS) at different pH values confirmed an isoelectric point (IEP) at pH = 3.64 in ethanol and pH = 3.04 after addition of EDTA in ethanol. It was observed that addition of EDTA in nanosuspension enhances stability of Ni-NPs significantly.

A Study of Land Surface Temperature Retrieval and Thermal Environment Distribution Based on Landsat-8 in Jinan City

NASA Astrophysics Data System (ADS)

Dong, Fang; Chen, Jian; Yang, Fan

2018-01-01

Based on the medium resolution Landsat 8 OLI/TIRS, the temperature distribution in four seasons of urban area in Jinan City was obtained by using atmospheric correction method for the retrieval of land surface temperature. Quantitative analysis of the spatio-temporal distribution characteristics, development trend of urban thermal environment, the seasonal variation and the relationship between surface temperature and normalized difference vegetation index (NDVI) was studied. The results show that the distribution of high temperature areas is concentrated in Jinan, and there is a tendency to expand from east to west, revealing a negative correlation between land surface temperature distribution and NDVI. So as to provide theoretical references and scientific basis of improving the ecological environment of Jinan City, strengthening scientific planning and making overall plan addressing climate change.

Spatiotemporal Change Detection Using Landsat Imagery: the Case Study of Karacabey Flooded Forest, Bursa, Turkey

NASA Astrophysics Data System (ADS)

Akay, A. E.; Gencal, B.; Taş, İ.

2017-11-01

This short paper aims to detect spatiotemporal detection of land use/land cover change within Karacabey Flooded Forest region. Change detection analysis applied to Landsat 5 TM images representing July 2000 and a Landsat 8 OLI representing June 2017. Various image processing tools were implemented using ERDAS 9.2, ArcGIS 10.4.1, and ENVI programs to conduct spatiotemporal change detection over these two images such as band selection, corrections, subset, classification, recoding, accuracy assessment, and change detection analysis. Image classification revealed that there are five significant land use/land cover types, including forest, flooded forest, swamp, water, and other lands (i.e. agriculture, sand, roads, settlement, and open areas). The results indicated that there was increase in flooded forest, water, and other lands, while the cover of forest and swamp decreased.

Towards monitoring surface and subsurface lakes on the Greenland Ice Sheet using Sentinel-1 SAR and Landsat-8 OLI imagery

NASA Astrophysics Data System (ADS)

Miles, Katie E.; Willis, Ian C.; Benedek, Corinne L.; Williamson, Andrew G.; Tedesco, Marco

2017-07-01

Supraglacial lakes are an important component of the Greenland Ice Sheet’s mass balance and hydrology, with their drainage affecting ice dynamics. This study uses imagery from the recently launched Sentinel-1A Synthetic Aperture Radar (SAR) satellite to investigate supraglacial lakes in West Greenland. A semi-automated algorithm is developed to detect surface lakes from Sentinel-1 images during the 2015 summer. A combined Landsat-8 and Sentinel-1 dataset, which has a comparable temporal resolution to MODIS (3 days versus daily) but a higher spatial resolution (25-40 m versus 250-500 m), is then used together with a fully-automated lake drainage detection algorithm. Rapid (< 4 days) and slow (> 4 days) drainages are investigated for both small (< 0.125 km2, the minimum size detectable by MODIS) and large (≥ 0.125 km2) lakes through the summer. Drainage events of small lakes occur at lower elevations (mean 159 m), and slightly earlier (mean 4.5 days) in the melt season than those of large lakes. The analysis is extended manually into the early winter to calculate the dates and elevations of lake freeze-through more precisely than is possible with optical imagery (mean 30 August; 1270 m mean elevation). Finally, the Sentinel-1 imagery is used to detect subsurface lakes and, for the first time, their dates of appearance and freeze-through (mean 9 August and 7 October, respectively). These subsurface lakes occur at higher elevations than the surface lakes detected in this study (mean 1593 m and 1185 m, respectively). Sentinel-1 imagery therefore provides great potential for tracking melting, water movement and freezing within both the firn zone and ablation area of the Greenland Ice Sheet.

Spatio-Temporal Assessment of Margalla Hills Forest by Using Landsat Imagery for Year 2000 and 2018

NASA Astrophysics Data System (ADS)

Batool, R.; Javaid, K.

2018-04-01

Environmental imbalance due to human activities has shown serious threat to ecosystem and produced negative impacts. The main goal of this study is to identify, monitor and classify temporal changes of forest cover, build up and open spaces in Margalla Hills National Park, Islamabad. Geographic Information Sciences (GISc) and Remote Sensing (RS) techniques has been used for the assessment of analysis. LANDSAT-7 Enhanced Thematic Mapper (ETM+) and LANDSAT-8 Operational Land Imager (OLI) were utilized for obtaining data of year 2000 and 2018. Temporal changes were evaluated after applying supervised classification and discrimination was analyzed by Per-Pixel based change detection. Results depicts forest cover decrease from 87 % to 74 % whereas build up has increased from 5 % to 7 % over the span. Consequences also justify the presence of open land in study area that has been increased from 2 % to 7 % respectively.

Cloud detection algorithm comparison and validation for operational Landsat data products

USGS Publications Warehouse

Foga, Steven Curtis; Scaramuzza, Pat; Guo, Song; Zhu, Zhe; Dilley, Ronald; Beckmann, Tim; Schmidt, Gail L.; Dwyer, John L.; Hughes, MJ; Laue, Brady

2017-01-01

Clouds are a pervasive and unavoidable issue in satellite-borne optical imagery. Accurate, well-documented, and automated cloud detection algorithms are necessary to effectively leverage large collections of remotely sensed data. The Landsat project is uniquely suited for comparative validation of cloud assessment algorithms because the modular architecture of the Landsat ground system allows for quick evaluation of new code, and because Landsat has the most comprehensive manual truth masks of any current satellite data archive. Currently, the Landsat Level-1 Product Generation System (LPGS) uses separate algorithms for determining clouds, cirrus clouds, and snow and/or ice probability on a per-pixel basis. With more bands onboard the Landsat 8 Operational Land Imager (OLI)/Thermal Infrared Sensor (TIRS) satellite, and a greater number of cloud masking algorithms, the U.S. Geological Survey (USGS) is replacing the current cloud masking workflow with a more robust algorithm that is capable of working across multiple Landsat sensors with minimal modification. Because of the inherent error from stray light and intermittent data availability of TIRS, these algorithms need to operate both with and without thermal data. In this study, we created a workflow to evaluate cloud and cloud shadow masking algorithms using cloud validation masks manually derived from both Landsat 7 Enhanced Thematic Mapper Plus (ETM +) and Landsat 8 OLI/TIRS data. We created a new validation dataset consisting of 96 Landsat 8 scenes, representing different biomes and proportions of cloud cover. We evaluated algorithm performance by overall accuracy, omission error, and commission error for both cloud and cloud shadow. We found that CFMask, C code based on the Function of Mask (Fmask) algorithm, and its confidence bands have the best overall accuracy among the many algorithms tested using our validation data. The Artificial Thermal-Automated Cloud Cover Algorithm (AT-ACCA) is the most accurate

Fall Harvest in Kazakhstan

NASA Image and Video Library

2017-12-08

September 22, the autumnal equinox, marks the beginning of fall in the Northern Hemisphere, but the fall harvest begins early in the harsh continental climate of eastern Kazakhstan. By September 9, 2013, when the Operational Land Imager (OLI) on the Landsat 8 satellite acquired this image, several fields were already harvested and bare. Others were dark green with pasture grasses or ripening crops. The fields fill the contours of the land, running long and narrow down mountain valleys and spreading in large squares over the plains. Agriculture is an important segment of the economy in Kazakhstan: the country’s dry climate is ideal for producing high quality wheat for export. However, 61 percent of the country’s agricultural land is pasture for livestock. The area shown in this image, far eastern Kazakhstan near the Chinese border, is a minor wheat-growing region and may also produce sunflowers, barley, and other food crops. An artifact of Soviet-era collective farms, most of the farms in Kazakhstan are large, covering more than 5,000 hectares (12,500 acres). Some of the larger fields in the image reflect the big business side of agriculture. However, family farms and small agriculture businesses account for 35 percent of the country’s agricultural production, and some of these are visible as well, particularly in the uneven hills and mountains. Nearly all agriculture in Kazakhstan is rain fed. Farmers in this region have designed their fields to take advantage of rain flowing down hills, allowing the natural shape of the land to channel water to crops. The effect is a mosaic of green and tan with tones matching the natural vegetation in the mountains to the north. NASA Earth Observatory image by Jesse Allen using Landsat data from the U.S. Geological Survey. Caption by Holli Riebeek. Instrument: Landsat 8 - OLI More info: 1.usa.gov/16IZ047 NASA image use policy. NASA Goddard Space Flight Center enables NASA’s mission through four scientific endeavors: Earth

A Harmonized Landsat-Sentinel-2 Surface Reflectance product: a resource for Agricultural Monitoring

NASA Astrophysics Data System (ADS)

Masek, J. G.; Claverie, M.; Ju, J.; Vermote, E.; Justice, C. O.

2015-12-01

The combination of Landsat and Sentinel-2 data offers a unique opportunity to observe globally the land every 2-3 days at medium (<30m) spatial resolution. The Harmonized Landsat-Sentinel-2 (HLS) project is a NASA initiative aiming to produce surface reflectance data from Landsat and Sentinel-2 missions and to deliver them to the community in a combined, seamless form. The HLS will be beneficial for global agricultural monitoring applications that require medium spatial resolution and weekly or more frequent observations. In particular, the provided opportunity to track crop phenology at the scale of individual fields will support detailed mapping of crop type and type-specific vegetation conditions. To create a compatible set of radiometric measurements, the HLS product relies on rigorous pre- and post-launch cross-calibration (Landsat-8 OLI and Sentinel-2 MSI) activities. The processing chain includes the following components: atmospheric correction, cloud/shadow masking, nadir BRDF-adjustment, spectral-adjustment, regridding, and temporal composite. The atmospheric correction and cloud masking is based on the OLI atmospheric correction developed at NASA-GSFC and has been adapted to the MSI data. The BRDF-adjustment is based on a disaggregation technique using MODIS-based BRDF coefficients. The technique has been evaluated using the multi-angular acquisition from the SPOT 4 and 5 (Take5) experiments. The spectral-adjustment relies on a linear regression that has been calibrated and evaluated using synthetic data and surface reflectance processed from a large number of hyperspectral EO-1 Hyperion scenes. Finally, significant effort is placed on product validation and evaluation. The delivered data set will include surface reflectance products at different levels: Using the native gridding, i.e. UTM, 30m for Landsat-8, and UTM, 10-20m for Sentinel-2 Using a common global gridding (Sinusoidal, 30m) Temporal composite (Sinusoidal, 30m, 5-day) During the first year of

Development of a regional bio-optical model for water quality assessment in the US Virgin Islands

NASA Astrophysics Data System (ADS)

Kerrigan, Kristi Lisa

Previous research in the US Virgin Islands (USVI) has demonstrated that land-based sources of pollution associated with watershed development and climate change are local and global factors causing coral reef degradation. A good indicator that can be used to assess stress on these environments is the water quality. Conventional assessment methods based on in situ measurements are timely and costly. Satellite remote sensing techniques offer better spatial coverage and temporal resolution to accurately characterize the dynamic nature of water quality parameters by applying bio-optical models. Chlorophyll-a, suspended sediments (TSM), and colored-dissolved organic matter are color-producing agents (CPAs) that define the water quality and can be measured remotely. However, the interference of multiple optically active constituents that characterize the water column as well as reflectance from the bottom poses a challenge in shallow coastal environments in USVI. In this study, field and laboratory based data were collected from sites on St. Thomas and St. John to characterize the CPAs and bottom reflectance of substrates. Results indicate that the optical properties of these waters are a function of multiple CPAs with chlorophyll-a values ranging from 0.10 to 2.35 microg/L and TSM values from 8.97 to 15.7 mg/L. These data were combined with in situ hyperspectral radiometric and Landsat OLI satellite data to develop a regionally tiered model that can predict CPA concentrations using traditional band ratio and multivariate approaches. Band ratio models for the hyperspectral dataset (R2 = 0.35; RMSE = 0.10 microg/L) and Landsat OLI dataset (R2 = 0.35; RMSE = 0.12 microg/L) indicated promising accuracy. However, a stronger model was developed using a multivariate, partial least squares regression to identify wavelengths that are more sensitive to chlorophyll-a (R2 = 0.62, RMSE = 0.08 microg/L) and TSM (R2 = 0.55). This approach takes advantage of the full spectrum of

Uncertainties in Coastal Ocean Color Products: Impacts of Spatial Sampling

NASA Technical Reports Server (NTRS)

Pahlevan, Nima; Sarkar, Sudipta; Franz, Bryan A.

2016-01-01

With increasing demands for ocean color (OC) products with improved accuracy and well characterized, per-retrieval uncertainty budgets, it is vital to decompose overall estimated errors into their primary components. Amongst various contributing elements (e.g., instrument calibration, atmospheric correction, inversion algorithms) in the uncertainty of an OC observation, less attention has been paid to uncertainties associated with spatial sampling. In this paper, we simulate MODIS (aboard both Aqua and Terra) and VIIRS OC products using 30 m resolution OC products derived from the Operational Land Imager (OLI) aboard Landsat-8, to examine impacts of spatial sampling on both cross-sensor product intercomparisons and in-situ validations of R(sub rs) products in coastal waters. Various OLI OC products representing different productivity levels and in-water spatial features were scanned for one full orbital-repeat cycle of each ocean color satellite. While some view-angle dependent differences in simulated Aqua-MODIS and VIIRS were observed, the average uncertainties (absolute) in product intercomparisons (due to differences in spatial sampling) at regional scales are found to be 1.8%, 1.9%, 2.4%, 4.3%, 2.7%, 1.8%, and 4% for the R(sub rs)(443), R(sub rs)(482), R(sub rs)(561), R(sub rs)(655), Chla, K(sub d)(482), and b(sub bp)(655) products, respectively. It is also found that, depending on in-water spatial variability and the sensor's footprint size, the errors for an in-situ validation station in coastal areas can reach as high as +/- 18%. We conclude that a) expected biases induced by the spatial sampling in product intercomparisons are mitigated when products are averaged over at least 7 km × 7 km areas, b) VIIRS observations, with improved consistency in cross-track spatial sampling, yield more precise calibration/validation statistics than that of MODIS, and c) use of a single pixel centered on in-situ coastal stations provides an optimal sampling size for

Estimation of Aboveground Biomass Change for Tropical Deciduous Forest in Bago Yoma, Myanmar between year 2000 and 2014 using Landsat Images and Ground Measurements

NASA Astrophysics Data System (ADS)

Kim, H. S.; Wynn, K. Z.; Ryu, Y.

2015-12-01

Even with recently increased awareness of the environmental conservation, the degradation of tropical forests are still one of the major sources of global carbon emission. Especially in Myanmar, the pressure to develop natural forest is growing rapidly after the change from socialism to capitalism in 2010. As the initial step of the forest conservation, the aboveground biomass(AGB) of South Zarmani Reserved Forest in Bago Yoma region were estimated using Landsat 8 OLI after the evaluation with 100 sample plot measurements. Multiple linear regression (MLR) model of band values and their principal component analysis (PCA) model were developed to estimate the AGB using the spectral reflectance from Landsat images and elevation as the input variables. The MLR model had r2 = 0.43, RMSE = 60.2 tons/ha, relative RMSE = 70.1%, Bias = -9.1 tons/ha, Bias (%) = -10.6%, and p < 0.0001, while the PCA model showed r2 = 0.45, RMSE = 55.1 tons/ha, relative RMSE = 64.1%, Bias = -8.3 tons/ha, Bias (%) = -9.7%, and p < 0.0001. The AGB maps of the study area were generated based on both MLR and PCA models. The estimated mean AGB values were 74.74±22.3 tons/ha and 73.04±17.6 tons/ha and the total AGB of the study area are about 5.7 and 5.6 million tons from MLR and PCA, respectively. Then, Landsat 7 ETM+ image acquired on 2000 was also used to compare the changing of AGB between year 2000 and 2014. The estimated mean AGB value generated from the Landsat 7 ETM+ image was 78.9±16.9 tons/ha, which is substantially decreased about 7.5% compared to year 2014. The reduction of AGB increased with closeness to village, however AGB in distant areas showed steady increases. In conclusion, we were able to generate solid regression models from Landsat 8 OLI image after ground truth and two regression models gave us very similar AGB estimation (less than 2%) of the study area. We were also able to estimate the changing of AGB from year 2000 to 2014 of South Zarmani Reserved Forest, Bago Yoma

A Note on the Temporary Misregistration of Landsat-8 Operational Land Imager (OLI) and Sentinel-2 Multi Spectral Instrument (MSI) Imagery

NASA Technical Reports Server (NTRS)

Storey, James; Roy, David P.; Masek, Jeffrey; Gascon, Ferran; Dwyer, John; Choate, Michael

2016-01-01

The Landsat-8 and Sentinel-2 sensors provide multi-spectral image data with similar spectral and spatial characteristics that together provide improved temporal coverage globally. Both systems are designed to register Level 1 products to a reference image framework, however, the Landsat-8 framework, based upon the Global Land Survey images, contains residual geolocation errors leading to an expected sensor-to-sensor misregistration of 38 m (2sigma). These misalignments vary geographically but should be stable for a given area. The Landsat framework will be readjusted for consistency with the Sentinel-2 Global Reference Image, with completion expected in 2018. In the interim, users can measure Landsat-to-Sentinel tie points to quantify the misalignment in their area of interest and if appropriate to reproject the data to better alignment.

A note on the temporary misregistration of Landsat-8 Operational Land Imager (OLI) and Sentinel-2 Multi Spectral Instrument (MSI) imagery

USGS Publications Warehouse

Storey, James C.; Roy, David P.; Masek, Jeffrey; Gascon, Ferran; Dwyer, John L.; Choate, Michael J.

2016-01-01

The Landsat-8 and Sentinel-2 sensors provide multi-spectral image data with similar spectral and spatial characteristics that together provide improved temporal coverage globally. Both systems are designed to register Level 1 products to a reference image framework, however, the Landsat-8 framework, based upon the Global Land Survey images, contains residual geolocation errors leading to an expected sensor-to-sensor misregistration of 38 m (2σ). These misalignments vary geographically but should be stable for a given area. The Landsat framework will be readjusted for consistency with the Sentinel-2 Global Reference Image, with completion expected in 2018. In the interim, users can measure Landsat-to-Sentinel tie points to quantify the misalignment in their area of interest and if appropriate to reproject the data to better alignment.

Mapping paddy rice planting area in wheat-rice double-cropped areas through integration of Landsat-8 OLI, MODIS, and PALSAR images.

PubMed

Wang, Jie; Xiao, Xiangming; Qin, Yuanwei; Dong, Jinwei; Zhang, Geli; Kou, Weili; Jin, Cui; Zhou, Yuting; Zhang, Yao

2015-05-12

As farmland systems vary over space and time (season and year), accurate and updated maps of paddy rice are needed for studies of food security and environmental problems. We selected a wheat-rice double-cropped area from fragmented landscapes along the rural-urban complex (Jiangsu Province, China) and explored the potential utility of integrating time series optical images (Landsat-8, MODIS) and radar images (PALSAR) in mapping paddy rice planting areas. We first identified several main types of non-cropland land cover and then identified paddy rice fields by selecting pixels that were inundated only during paddy rice flooding periods. These key temporal windows were determined based on MODIS Land Surface Temperature and vegetation indices. The resultant paddy rice map was evaluated using regions of interest (ROIs) drawn from multiple high-resolution images, Google Earth, and in-situ cropland photos. The estimated overall accuracy and Kappa coefficient were 89.8% and 0.79, respectively. In comparison with the National Land Cover Data (China) from 2010, the resultant map better detected changes in the paddy rice fields and revealed more details about their distribution. These results demonstrate the efficacy of using images from multiple sources to generate paddy rice maps for two-crop rotation systems.

Remote Sensing Extraction of Stopes and Tailings Ponds in AN Ultra-Low Iron Mining Area

NASA Astrophysics Data System (ADS)

Ma, B.; Chen, Y.; Li, X.; Wu, L.

2018-04-01

With the development of economy, global demand for steel has accelerated since 2000, and thus mining activities of iron ore have become intensive accordingly. An ultra-low-grade iron has been extracted by open-pit mining and processed massively since 2001 in Kuancheng County, Hebei Province. There are large-scale stopes and tailings ponds in this area. It is important to extract their spatial distribution information for environmental protection and disaster prevention. A remote sensing method of extracting stopes and tailings ponds is studied based on spectral characteristics by use of Landsat 8 OLI imagery and ground spectral data. The overall accuracy of extraction is 95.06 %. In addition, tailings ponds are distinguished from stopes based on thermal characteristics by use of temperature image. The results could provide decision support for environmental protection, disaster prevention, and ecological restoration in the ultra-low-grade iron ore mining area.

Ft Nelson, Muskwa Apt, British Columbia, Canada. Revised Uniform Summary of Surface Weather Observations (RUSSWO). Parts A-F.

DTIC Science & Technology

1972-01-17

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Informatics and computational method for inundation and land use study in Arctic Sea eastern Siberia, Russia

NASA Astrophysics Data System (ADS)

Boori, Mukesh Singh; Choudhary, Komal; Kupriyanov, Alexander; Sugimoto, Atsuko

2016-11-01

Eastern Siberia, Russia is physically and socio-economically vulnerable to accelerated Arctic sea level rise due to low topography, high ecological value, harsh climatic conditions, erosion and flooding of coastal area and destruction of harbor constructions and natural coastal hazards. A 1 to 10m inundation land loss scenarios for surface water and sea level rise (SLR) were developed using digital elevation models of study site topography through remote sensing and GIS techniques by ASTER GDEM and Landsat OLI data. Results indicate that 10.82% (8072.70km2) and 29.73% (22181.19km2) of the area will be lost by flooding at minimum and maximum inundation levels, respectively. The most severely impacted sectors are expected to be the vegetation, wetland and the natural ecosystem. Improved understanding of the extent and response of SLR will help in preparing for mitigation and adaptation.

Software Process Modeling and Execution within Virtual Environments

DTIC Science & Technology

1997-08-01

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Liquid Crystalline Thermosets from Ester, Ester-imide, and Ester-amide Oligomers

NASA Technical Reports Server (NTRS)

Dingemans, Theodorus J. (Inventor); Weiser, Erik S. (Inventor); St. Clair, Terry L. (Inventor)

2009-01-01

Main chain thermotropic liquid crystal esters, ester-imides, and ester-amides were prepared from AA, BB, and AB type monomeric materials and end-capped with phenylacetylene, phenylmaleimide, or nadimide reactive end-groups. The end-capped liquid crystal oligomers are thermotropic and have, preferably, molecular weights in the range of approximately 1000-15,000 grams per mole. The end-capped liquid crystaloligomers have broad liquid crystalline melting ranges and exhibit high melt stability and very low melt viscosities at accessible temperatures. The end-capped liquid crystal oli-gomers are stable forup to an hour in the melt phase. They are highly processable by a variety of melt process shape forming and blending techniques. Once processed and shaped, the end-capped liquid crystal oigomers were heated to further polymerize and form liquid crystalline thermosets (LCT). The fully cured products are rubbers above their glass transition temperatures.

Surface Energy Balance System (SEBS) Handbook

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

Cook, D. R.

2016-01-01

A Surface Energy Balance System (SEBS) has been installed collocated with each deployed Eddy Correlation Flux Measurement System (ECOR) at the Atmospheric Radiation Measurement (ARM) Climate Research Facility’s Southern Great Plains (SGP) site, North Slope of Alaska (NSA) site, first ARM Mobile Facility (AMF1), second ARM Mobile Facility (AMF2), and third ARM Mobile Facility (AMF3) at Oliktok Point (OLI). A SEBS was also deployed with the Tropical Western Pacific (TWP) site, before it was decommissioned. Data from these sites, including the retired TWP, are available in the ARM Data Archive. The SEBS consists of upwelling and downwelling solar and infraredmore » radiometers within one net radiometer, a wetness sensor, and soil measurements. The SEBS measurements allow the comparison of ECOR sensible and latent heat fluxes with the energy balance determined from the SEBS and provide information on wetting of the sensors for data quality purposes.« less

Design, Synthesis and Evaluation of Ribose-modified Anilinopyrimidine Derivatives as EGFR Tyrosine Kinase Inhibitors

NASA Astrophysics Data System (ADS)

Hu, Xiuqin; Wang, Disha; Tong, Yi; Tong, Linjiang; Wang, Xia; Zhu, Lili; Xie, Hua; Li, Shiliang; Yang, You; Xu, Yufang

2017-11-01

The synthesis of a series of ribose-modified anilinopyrimidine derivatives was efficiently achieved by utilizing DBU or tBuOLi-promoted coupling of ribosyl alcohols with 2,4,5-trichloropyrimidine as key step. Preliminary biological evaluation of this type of compounds as new EGFR tyrosine kinase inhibitors for combating EGFR L858R/T790M mutant associated with drug resistance in the treatment of non-small cell lung cancer revealed that 3-N-acryloyl-5-O-anilinopyrimidine ribose derivative 1a possessed potent and specific inhibitory activity against EGFR L858R/T790M over WT EGFR. Based upon molecular docking studies of the binding mode between compound 1a and EGFR, the distance between the Michael receptor and the pyrimidine scaffold is considered as an important factor for the inhibitory potency and future design of selective EGFR tyrosine kinase inhibitors against EGFR L858R/T790M mutants.

Fuzzy ontologies for semantic interpretation of remotely sensed images

NASA Astrophysics Data System (ADS)

Djerriri, Khelifa; Malki, Mimoun

2015-10-01

Object-based image classification consists in the assignment of object that share similar attributes to object categories. To perform such a task the remote sensing expert uses its personal knowledge, which is rarely formalized. Ontologies have been proposed as solution to represent domain knowledge agreed by domain experts in a formal and machine readable language. Classical ontology languages are not appropriate to deal with imprecision or vagueness in knowledge. Fortunately, Description Logics for the semantic web has been enhanced by various approaches to handle such knowledge. This paper presents the extension of the traditional ontology-based interpretation with fuzzy ontology of main land-cover classes in Landsat8-OLI scenes (vegetation, built-up areas, water bodies, shadow, clouds, forests) objects. A good classification of image objects was obtained and the results highlight the potential of the method to be replicated over time and space in the perspective of transferability of the procedure.

An overview of in-orbit radiometric calibration of typical satellite sensors

NASA Astrophysics Data System (ADS)

Zhou, G. Q.; Li, C. Y.; Yue, T.; Jiang, L. J.; Liu, N.; Sun, Y.; Li, M. Y.

2015-06-01

This paper reviews the development of in-orbit radiometric calibration methods in the past 40 years. It summarizes the development of in-orbit radiometric calibration technology of typical satellite sensors in the visible/near-infrared bands and the thermal infrared band. Focuses on the visible/near-infrared bands radiometric calibration method including: Lamp calibration and solar radiationbased calibration. Summarizes the calibration technology of Landsat series satellite sensors including MSS, TM, ETM+, OLI, TIRS; SPOT series satellite sensors including HRV, HRS. In addition to the above sensors, there are also summarizing ALI which was equipped on EO-1, IRMSS which was equipped on CBERS series satellite. Comparing the in-orbit radiometric calibration technology of different periods but the same type satellite sensors analyzes the similarities and differences of calibration technology. Meanwhile summarizes the in-orbit radiometric calibration technology in the same periods but different country satellite sensors advantages and disadvantages of calibration technology.

MO/DSD online information server and global information repository access

NASA Technical Reports Server (NTRS)

Nguyen, Diem; Ghaffarian, Kam; Hogie, Keith; Mackey, William

1994-01-01

Often in the past, standards and new technology information have been available only in hardcopy form, with reproduction and mailing costs proving rather significant. In light of NASA's current budget constraints and in the interest of efficient communications, the Mission Operations and Data Systems Directorate (MO&DSD) New Technology and Data Standards Office recognizes the need for an online information server (OLIS). This server would allow: (1) dissemination of standards and new technology information throughout the Directorate more quickly and economically; (2) online browsing and retrieval of documents that have been published for and by MO&DSD; and (3) searching for current and past study activities on related topics within NASA before issuing a task. This paper explores a variety of available information servers and searching tools, their current capabilities and limitations, and the application of these tools to MO&DSD. Most importantly, the discussion focuses on the way this concept could be easily applied toward improving dissemination of standards and new technologies and improving documentation processes.

Social vulnerability to heat in Greater Atlanta, USA: spatial pattern of heat, NDVI, socioeconomics and household composition

NASA Astrophysics Data System (ADS)

Sim, Sunhui

2017-10-01

The purpose of the article is evaluating spatial patterns of social vulnerability to heat in Greater Atlanta in 2015. The social vulnerability to heat is an index of socioeconomic status, household composition, land surface temperature and normalized differential vegetation index (NDVI). Land surface temperature and NDVI were derived from the red, NIR and thermal infrared (TIR) of a Landsat OLI/TIRS images collected on September 14, 2015. The research focus is on the variation of heat vulnerability in Greater Atlanta. The study found that heat vulnerability is highly clustered spatially, resulting in "hot spots" and "cool spots". The results show significant health disparities. The hotspots of social vulnerability to heat occurred in neighborhoods with lower socioeconomic status as measured by low education, low income and more poverty, greater proportion of elderly people and young children. The findings of this study are important for identifying clusters of heat vulnerability and the relationships with social factors. These significant results provide a basis for heat intervention services.

Lava and Snow on Klyuchevskaya Volcano [detail

NASA Image and Video Library

2017-12-08

This false-color (shortwave infrared, near infrared, green) satellite image reveals an active lava flow on the western slopes of Klyuchevskaya Volcano. Klyuchevskaya is one of several active volcanoes on the Kamchatka Peninsula in far eastern Russia. The lava flow itself is bright red. Snow on Klyuchevskaya and nearby mountains is cyan, while bare ground and volcanic debris is gray or brown. Vegetation is green. The image was collected by Landsat 8 on September 9, 2013. NASA Earth Observatory image by Jesse Allen and Robert Simmon, using Instrument: Landsat 8 - OLI More info: 1.usa.gov/1evspH7 NASA image use policy. NASA Goddard Space Flight Center enables NASA’s mission through four scientific endeavors: Earth Science, Heliophysics, Solar System Exploration, and Astrophysics. Goddard plays a leading role in NASA’s accomplishments by contributing compelling scientific knowledge to advance the Agency’s mission. Follow us on Twitter Like us on Facebook Find us on Instagram

Effect of functionalization of boron nitride flakes by main group metal clusters on their optoelectronic properties

NASA Astrophysics Data System (ADS)

Chakraborty, Debdutta; Chattaraj, Pratim Kumar

2017-10-01

The possibility of functionalizing boron nitride flakes (BNFs) with some selected main group metal clusters, viz. OLi4, NLi5, CLi6, BLI7 and Al12Be, has been analyzed with the aid of density functional theory (DFT) based computations. Thermochemical as well as energetic considerations suggest that all the metal clusters interact with the BNF moiety in a favorable fashion. As a result of functionalization, the static (first) hyperpolarizability (β ) values of the metal cluster supported BNF moieties increase quite significantly as compared to that in the case of pristine BNF. Time dependent DFT analysis reveals that the metal clusters can lower the transition energies associated with the dominant electronic transitions quite significantly thereby enabling the metal cluster supported BNF moieties to exhibit significant non-linear optical activity. Moreover, the studied systems demonstrate broad band absorption capability spanning the UV-visible as well as infra-red domains. Energy decomposition analysis reveals that the electrostatic interactions principally stabilize the metal cluster supported BNF moieties.

Effect of functionalization of boron nitride flakes by main group metal clusters on their optoelectronic properties.

PubMed

Chakraborty, Debdutta; Chattaraj, Pratim Kumar

2017-10-25

The possibility of functionalizing boron nitride flakes (BNFs) with some selected main group metal clusters, viz. OLi 4 , NLi 5 , CLi 6 , BLI 7 and Al 12 Be, has been analyzed with the aid of density functional theory (DFT) based computations. Thermochemical as well as energetic considerations suggest that all the metal clusters interact with the BNF moiety in a favorable fashion. As a result of functionalization, the static (first) hyperpolarizability ([Formula: see text]) values of the metal cluster supported BNF moieties increase quite significantly as compared to that in the case of pristine BNF. Time dependent DFT analysis reveals that the metal clusters can lower the transition energies associated with the dominant electronic transitions quite significantly thereby enabling the metal cluster supported BNF moieties to exhibit significant non-linear optical activity. Moreover, the studied systems demonstrate broad band absorption capability spanning the UV-visible as well as infra-red domains. Energy decomposition analysis reveals that the electrostatic interactions principally stabilize the metal cluster supported BNF moieties.

Lava and Snow on Klyuchevskaya Volcano [high res

NASA Image and Video Library

2013-09-20

IDL TIFF file This false-color (shortwave infrared, near infrared, green) satellite image reveals an active lava flow on the western slopes of Klyuchevskaya Volcano. Klyuchevskaya is one of several active volcanoes on the Kamchatka Peninsula in far eastern Russia. The lava flow itself is bright red. Snow on Klyuchevskaya and nearby mountains is cyan, while bare ground and volcanic debris is gray or brown. Vegetation is green. The image was collected by Landsat 8 on September 9, 2013. NASA Earth Observatory image by Jesse Allen and Robert Simmon, using Instrument: Landsat 8 - OLI More info: 1.usa.gov/1evspH7 NASA image use policy. NASA Goddard Space Flight Center enables NASA’s mission through four scientific endeavors: Earth Science, Heliophysics, Solar System Exploration, and Astrophysics. Goddard plays a leading role in NASA’s accomplishments by contributing compelling scientific knowledge to advance the Agency’s mission. Follow us on Twitter Like us on Facebook Find us on Instagram

Air Force Procedure for Predicting Aircraft Noise Around Airbases: Airbase Operations Program (BASEOPS) Description

DTIC Science & Technology

1990-01-01

B720B/JT3D-3 JCOM 2 JT3D 9 51 52 53 54 55 0 0 12 DC850 DC-8-50/JT3D-3 JCOM 2 JT3D 10 56 57 58 59 60 61 0 13 DC860 DC-8- 60 /JT30-7 JCOM 2 JT3D 11 62 63 64...B707-320B/JT30-7QN JCOM 3 JT3DQ 8 38 39 40 41 42 43 44 17 DCBQN DC-8- 60 /JT30-70N JCOM 3 JT3DQ 10 62 63 64 65 66 67 68 18 CONCRD CONCORDE/OLY593 JCOM...8 0LY593 14 83 83 83 83 84 84 0 19 DC1010 DC-10-10/CF6- 60 JCOM 11 CF660 15 85 86 87 88 89 90 0 20 DC1030 DC-10-30/CF6-50C2 JCOM 11 CF660 58 203 204

Spatial Analysis to Determine Paddy Field Changes in Indonesia: A Case Study in Suburban Areas of Jakarta

NASA Astrophysics Data System (ADS)

Putri Utami, Nadia; Ahamed, Tofael

2018-05-01

Karawang, a suburban area of Greater Jakarta, is known as the second largest rice-producing region in West Java, Indonesia. However, expansion of urban sprawl and industrial area from Greater Jakarta have created rapid agricultural land use/cover changes, especially paddy field, in Karawang. This study analyzed the land use/cover changes of paddy field from 2000 to 2016. Landsat 4-5 TM and Landsat 8 OLI/TIRS images were acquired from USGS Earth Explorer, UTM zone 48 south. Satellite image pre-processing, ground truth data collection, supervised maximum likelihood classifications, and Post-Classification Comparison (PCC) were performed in ArcGIS 10.3®. It was observed between 2000 and 2016, urban area increased 4.46% (8530 ha) from initial area of 10,004 ha. Meanwhile paddy field decreased 3.18% (6091 ha) from initial area of 115,720 ha. The spatial analysis showed that paddy field in the fringe of urban area are more susceptible for changes.

Image enhancements of Landsat 8 (OLI) and SAR data for preliminary landslide identification and mapping applied to the central region of Kenya

NASA Astrophysics Data System (ADS)

Mwaniki, M. W.; Kuria, D. N.; Boitt, M. K.; Ngigi, T. G.

2017-04-01

Image enhancements lead to improved performance and increased accuracy of feature extraction, recognition, identification, classification and hence change detection. This increases the utility of remote sensing to suit environmental applications and aid disaster monitoring of geohazards involving large areas. The main aim of this study was to compare the effect of image enhancement applied to synthetic aperture radar (SAR) data and Landsat 8 imagery in landslide identification and mapping. The methodology involved pre-processing Landsat 8 imagery, image co-registration, despeckling of the SAR data, after which Landsat 8 imagery was enhanced by Principal and Independent Component Analysis (PCA and ICA), a spectral index involving bands 7 and 4, and using a False Colour Composite (FCC) with the components bearing the most geologic information. The SAR data were processed using textural and edge filters, and computation of SAR incoherence. The enhanced spatial, textural and edge information from the SAR data was incorporated to the spectral information from Landsat 8 imagery during the knowledge based classification. The methodology was tested in the central highlands of Kenya, characterized by rugged terrain and frequent rainfall induced landslides. The results showed that the SAR data complemented Landsat 8 data which had enriched spectral information afforded by the FCC with enhanced geologic information. The SAR classification depicted landslides along the ridges and lineaments, important information lacking in the Landsat 8 image classification. The success of landslide identification and classification was attributed to the enhanced geologic features by spectral, textural and roughness properties.

Deriving a global land surface albedo product from Landsat MSS, TM, ETM+, and OLI data based on the unified direct estimation approach

USDA-ARS?s Scientific Manuscript database

Surface albedo is widely used in climate and environment applications as an important parameter for controlling the surface energy budget. There is an increasing need for fine resolution (< 100 m) albedo data for use in small scale applications and for validating coarse-resolution datasets; however,...

Timber production assessment of a plantation forest: An integrated framework with field-based inventory, multi-source remote sensing data and forest management history

NASA Astrophysics Data System (ADS)

Gao, Tian; Zhu, Jiaojun; Deng, Songqiu; Zheng, Xiao; Zhang, Jinxin; Shang, Guiduo; Huang, Liyan

2016-10-01

Timber production is the purpose for managing plantation forests, and its spatial and quantitative information is critical for advising management strategies. Previous studies have focused on growing stock volume (GSV), which represents the current potential of timber production, yet few studies have investigated historical process-harvested timber. This resulted in a gap in a synthetical ecosystem service assessment of timber production. In this paper, we established a Management Process-based Timber production (MPT) framework to integrate the current GSV and the harvested timber derived from historical logging regimes, trying to synthetically assess timber production for a historical period. In the MPT framework, age-class and current GSV determine the times of historical thinning and the corresponding harvested timber, by using a ;space-for-time; substitution. The total timber production can be estimated by the historical harvested timber in each thinning and the current GSV. To test this MPT framework, an empirical study on a larch plantation (LP) with area of 43,946 ha was conducted in North China for a period from 1962 to 2010. Field-based inventory data was integrated with ALOS PALSAR (Advanced Land-Observing Satellite Phased Array L-band Synthetic Aperture Radar) and Landsat-8 OLI (Operational Land Imager) data for estimating the age-class and current GSV of LP. The random forest model with PALSAR backscatter intensity channels and OLI bands as input predictive variables yielded an accuracy of 67.9% with a Kappa coefficient of 0.59 for age-class classification. The regression model using PALSAR data produced a root mean square error (RMSE) of 36.5 m3 ha-1. The total timber production of LP was estimated to be 7.27 × 106 m3, with 4.87 × 106 m3 in current GSV and 2.40 × 106 m3 in harvested timber through historical thinning. The historical process-harvested timber accounts to 33.0% of the total timber production, which component has been neglected in the

Mile Marker 28 Fire

NASA Image and Video Library

2017-12-08

Eight major wildfires burned through forests and grasslands in the Pacific Northwest in late-July 2013, threatening homes and forcing road closings and evacuations. Many parts of Washington and Oregon faced extreme fire threats, as strong thunderstorms lined up to hit parched forests and grasslands with lightning. On July 28, 2013, the Operational Land Imager (OLI) on Landsat 8 captured these images of the Mile Marker 28 fire in the Simcoe Mountains northeast of Goldendale, Washington. Smoke blew east toward Kennewick, Pasco, and Richland. The lower image shows a closer view of smoke billowing up from the most active part of the fire. Ignited on July 24, 2013, the fire charred more than 22,000 acres (8,900 hectares) by July 30, when more than 1,000 firefighters achieved 40 percent containment. The blaze forced the evacuation of dozens of homes and the closure of US Highway 97. Through July 25, 450 wildfires had burned 10,220 acres (4,136 hectares) in Washington, while Oregon saw 603 fires that burned 63,135 acres (25,549 hectares). In all, 2.3 million acres burned across the United States by late-July, below the national average. Over the past ten years, an average of 4.2 million acres had burned in the United States by the end of each July. While coastal and western Washington receive heavy rain throughout the year, the rain shadow caused by the Cascades leaves central Washington quite dry. The mountains force moist air from the Pacific to rise, causing it to cool and condense into rain or snow on the windward side of the Cascades. So little moisture is left by the time air passes over the Cascades, that the area around Mile Marker 28 typically receives just 8 inches (20 centimeters) of precipitation per year. NASA Earth Observatory image by Jesse Allen and Robert Simmon, using Landsat data from the U.S. Geological Survey. Caption by Adam Voiland Instrument: Landsat 8 - OLI More info: earthobservatory.nasa.gov/IOTD/view.php?id=81738 Credit: NASA Earth Observatory

Operational calibration and validation of landsat data continuity mission (LDCM) sensors using the image assessment system (IAS)

USGS Publications Warehouse

Micijevic, Esad; Morfitt, Ron

2010-01-01

Systematic characterization and calibration of the Landsat sensors and the assessment of image data quality are performed using the Image Assessment System (IAS). The IAS was first introduced as an element of the Landsat 7 (L7) Enhanced Thematic Mapper Plus (ETM+) ground segment and recently extended to Landsat 4 (L4) and 5 (L5) Thematic Mappers (TM) and Multispectral Sensors (MSS) on-board the Landsat 1-5 satellites. In preparation for the Landsat Data Continuity Mission (LDCM), the IAS was developed for the Earth Observer 1 (EO-1) Advanced Land Imager (ALI) with a capability to assess pushbroom sensors. This paper describes the LDCM version of the IAS and how it relates to unique calibration and validation attributes of its on-board imaging sensors. The LDCM IAS system will have to handle a significantly larger number of detectors and the associated database than the previous IAS versions. An additional challenge is that the LDCM IAS must handle data from two sensors, as the LDCM products will combine the Operational Land Imager (OLI) and Thermal Infrared Sensor (TIRS) spectral bands.

Identification of ex-sand mining area using optical and SAR imagery

NASA Astrophysics Data System (ADS)

Indriasari, Novie; Kusratmoko, Eko; Indra, Tito Latif; Julzarika, Atriyon

2018-05-01

Open mining activities in Sumedang Regency has been operated since 1984 impacted to degradation of environment due to large area of ex-mining. Therefore, identification of ex-mining area which generally been used for sand mining is crucial and important to detect and monitor recent environmental degradation impacted from the ex-mining activities. In this research, identification ex-sand mining area using optical and SAR data in Sumedang Regency will be discussed. We use Landsat 5 TM acquisition date August 01, 2009 and Landsat 8 OLI acquired on June 24, 2016 to identify location of sand mining area, processed using Tasselled Cap Trasformation (TCT), while the landform deformation approached using ALOS PALSAR in 2009 and ALOS PALSAR 2 in 2016 processed using SAR interferometry (InSAR) method. The results show that TCT and InSAR method can can be used to identify the areas of ex-sand mining clearly. In 2016 the total area of ex-mining were 352.92 Ha. The land deformation show that during 7 years period since 2009 has impacted to the deformation at 7 meters.

Application of Unmanned Aerial Systems in Spatial Downscaling of Landsat VIR imageries of Agricultural Fields

NASA Astrophysics Data System (ADS)

Torres, A.; Hassan Esfahani, L.; Ebtehaj, A.; McKee, M.

2016-12-01

While coarse space-time resolution of satellite observations in visible to near infrared (VIR) is a serious limiting factor for applications in precision agriculture, high resolution remotes sensing observation by the Unmanned Aerial Systems (UAS) systems are also site-specific and still practically restrictive for widespread applications in precision agriculture. We present a modern spatial downscaling approach that relies on new sparse approximation techniques. The downscaling approach learns from a large set of coincident low- and high-resolution satellite and UAS observations to effectively downscale the satellite imageries in VIR bands. We focus on field experiments using the AggieAirTM platform and Landsat 7 ETM+ and Landsat 8 OLI observations obtained in an intensive field campaign in 2013 over an agriculture field in Scipio, Utah. The results show that the downscaling methods can effectively increase the resolution of Landsat VIR imageries by the order of 2 to 4 from 30 m to 15 and 7.5 m, respectively. Specifically, on average, the downscaling method reduces the root mean squared errors up to 26%, considering bias corrected AggieAir imageries as the reference.

The use of cartographic modeling to assess the impacts of coastal flooding: a case study of Port Said Governorate, Egypt.

PubMed

Abou Samra, Rasha M

2017-09-01

Low-set coastal areas are expected to aggravate inundation on account of sea level rise (SLR). The present study is planned to appraise the impacts of coastal flooding in Port Said city, Egypt by using remote sensing, GIS, and cartographic modeling techniques. To accomplish this scope, Landsat 8-OLI image dated 2016 and SRTM 1Arc-Second Digital Elevation Model (DEM) data were used. Landsat image was classified into seven land use and land cover (LULC) classes by using remote sensing and GIS's software. Different inundation scenarios 1.0, 2.0, and 3.0-m coastal elevation were used to figure the influence of SLR on the study area. Estimation of potential losses under SLR was made by overlaying the expected scenarios on land use. The inundation areas under the expected SLR scenarios of 1.0, 2.0, and 3.0 m were estimated at 827.49, 1072.67, and 1179.41 km 2 , respectively. In conclusion, this study demonstrated that expected coastal flooding scenarios will lead up to serious impacts on LULC classes and coastal features in the study area.

Modeling of glycine solubility in aqueous HCl-MgCl2 system and its application in phase transition of glycine by changing media and supersaturation

NASA Astrophysics Data System (ADS)

Ansari, Ziaul Haque; Zeng, Yan; Zhang, Yan; Demopoulos, George P.; Li, Zhibao

2017-06-01

The solubility of glycine in HCl and HCl-MgCl2 solutions was measured from 283.15 to 343.15 K and found to increase with temperature and increase linearly with the concentration of HCl. The MSE model integrated in the OLI platform was modified by regressing the experimental and literature solubility data through the adjustment of the middle-range interaction parameters. After parameterization, the model can accurately calculate the solubility with the average absolute deviation lower than 3.5% and thus be able to predict supersaturation of glycine. Crystallization of different polymorphs of glycine in water, HCl, NaOH, MgCl2, and HCl-MgCl2 aqueous solutions was performed. The effects of medium, temperature, supersaturation, and time on the crystallization were investigated. It was found that only in the HCl solution the formation of single α-glycine phase was achieved under all the investigated temperature and holding time. α-glycine or its mixture with γ-glycine or C4H18N2O4·HCl was produced in systems other than HCl solution depending on the conditions.

Data on spatiotemporal urban sprawl of Dire Dawa City, Eastern Ethiopia.

PubMed

Taffa, Chaltu; Mekonen, Teferi; Mulugeta, Messay; Tesfaye, Bechaye

2017-06-01

The data presented in this paper shows the spatiotemporal expansion of Dire Dawa City (eastern Ethiopia) and the ensuing land use land cover changes in its peri-urban areas between 1985 and 2015. The data were generated from satellite images of Thematic Mapper (TM), Enhanced Thematic Mapper-Plus (ETM+) and OLI (Operational Land Image) with path/raw value of 166/053 by using Arc GIS 10.1 software. The precision of the images was verified by geolocation data collected from ground control points by using Geographic Positioning System (GPS) receiver. Four LULC classes (built up area, vegetation, barren land and farmland) with their respective spatiotemporal dimensions were clearly identified in the analysis. Built up area had shown an overall annual increment of 15.8% (82 ha per year) from 517 ha in 1985 to 2976 ha in 2015. Expansion took place in all directions but it was more pronounced along the main road towards other nearby towns, recently established business/service areas and the Industrial Park. Barren land, farmland and vegetation areas showed speedy decline over the years.

Rocky Mountain National Park

NASA Image and Video Library

2017-12-08

Colorado’s Rocky Mountain National Park presents a very different landscape in summertime than in wintertime. Snow retreats and gives way to blooms of wildflowers, even at high elevations. Roads and trails become accessible, allowing visitors easier access to the rugged mountain trails and vistas. The diversity of the park’s landscape is visible in this image, acquired on September 20, 2014, with the Operational Land Imager (OLI) on the Landsat 8 satellite. Except for a few patches, seasonal snow is mostly gone. Even the “Never Summer Mountains”—a range along the park’s northwest border known to receive snow any time of year—appears to be temporarily snow-free. Read more: go.nasa.gov/29Rmz4Y Credit: NASA/Landsat8 NASA image use policy. NASA Goddard Space Flight Center enables NASA’s mission through four scientific endeavors: Earth Science, Heliophysics, Solar System Exploration, and Astrophysics. Goddard plays a leading role in NASA’s accomplishments by contributing compelling scientific knowledge to advance the Agency’s mission. Follow us on Twitter Like us on Facebook Find us on Instagram

Analyzing the Impacts of Land Use Land Change on Near Shore Coastal Habitat

NASA Astrophysics Data System (ADS)

Lehman, R. D.; Ta, E.; Boyle, C.; Alwood, B.

2017-12-01

The natural beauty of the United States Virgin Islands (USVI) has continued to attract visitors and residents, which overtime has increased human development and impact. The resulting land use change increases sediment loads and the flow of pollutants into surrounding nearshore environments such as coral reefs, mangroves, and seagrass beds. Compounded with regional climate-related processes such as rising ocean temperatures and acidification, future land-use change poses a formidable threat to coral reefs and other susceptible marine environments. Without a healthy environment, the USVI economy also becomes endangered because it is mainly supported by tourism and recreation. Using Google Earth Engine, we created a tool to composite yearly Landsat 5 TM, Landsat 8 OLI/TIRS and Sentinel-2 MSI images identify changes from 1985 to present day. Using these land cover change maps we then analyzed trends at a watershed scale using hydrological data. We found there is a spatial relationship between development intensity and the health of coral reefs. Our work supports the existing knowledge of the link between land use and coastal ecosystem health.

Big Blast at Sakurajima Volcano, Japan

NASA Image and Video Library

2013-08-27

Although Japan’s Sakura-jima volcano is one of the most active in the world, it rarely makes headlines. One or two small explosions typically occur every few days, with effects no greater than a light dusting of ash on the surrounding cities. On August 18, 2013, a large eruption sent ash 20,000 feet (6,000 meters) above Kagoshima Bay, breaking the established pattern. It was possibly the largest eruption ever from the Showa Crater, which formed in 1946. NASA Earth Observatory images by Jesse Allen and Robert Simmon, using Landsat 8 data from the USGS Earth Explorer. Caption by Robert Simmon. Instrument: Landsat 8 - OLI More details: 1.usa.gov/19WQpBQ NASA image use policy. NASA Goddard Space Flight Center enables NASA’s mission through four scientific endeavors: Earth Science, Heliophysics, Solar System Exploration, and Astrophysics. Goddard plays a leading role in NASA’s accomplishments by contributing compelling scientific knowledge to advance the Agency’s mission. Follow us on Twitter Like us on Facebook Find us on Instagram

Big Blast at Sakurajima Volcano, Japan [annotated

NASA Image and Video Library

2013-08-27

Although Japan’s Sakura-jima volcano is one of the most active in the world, it rarely makes headlines. One or two small explosions typically occur every few days, with effects no greater than a light dusting of ash on the surrounding cities. On August 18, 2013, a large eruption sent ash 20,000 feet (6,000 meters) above Kagoshima Bay, breaking the established pattern. It was possibly the largest eruption ever from the Showa Crater, which formed in 1946. NASA Earth Observatory images by Jesse Allen and Robert Simmon, using Landsat 8 data from the USGS Earth Explorer. Caption by Robert Simmon. Instrument: Landsat 8 - OLI More details: 1.usa.gov/19WQpBQ NASA image use policy. NASA Goddard Space Flight Center enables NASA’s mission through four scientific endeavors: Earth Science, Heliophysics, Solar System Exploration, and Astrophysics. Goddard plays a leading role in NASA’s accomplishments by contributing compelling scientific knowledge to advance the Agency’s mission. Follow us on Twitter Like us on Facebook Find us on Instagram

Simulation of Image Performance Characteristics of the Landsat Data Continuity Mission (LDCM) Thermal Infrared Sensor (TIRS)

NASA Technical Reports Server (NTRS)

Schott, John; Gerace, Aaron; Brown, Scott; Gartley, Michael; Montanaro, Matthew; Reuter, Dennis C.

2012-01-01

The next Landsat satellite, which is scheduled for launch in early 2013, will carry two instruments: the Operational Land Imager (OLI) and the Thermal Infrared Sensor (TIRS). Significant design changes over previous Landsat instruments have been made to these sensors to potentially enhance the quality of Landsat image data. TIRS, which is the focus of this study, is a dual-band instrument that uses a push-broom style architecture to collect data. To help understand the impact of design trades during instrument build, an effort was initiated to model TIRS imagery. The Digital Imaging and Remote Sensing Image Generation (DIRSIG) tool was used to produce synthetic "on-orbit" TIRS data with detailed radiometric, geometric, and digital image characteristics. This work presents several studies that used DIRSIG simulated TIRS data to test the impact of engineering performance data on image quality in an effort to determine if the image data meet specifications or, in the event that they do not, to determine if the resulting image data are still acceptable.

TRPM2, calcium and neurodegenerative diseases

PubMed Central

Xie, Yu-Feng; MacDonald, John F; Jackson, Michael F

2010-01-01

NMDA receptor overactivation triggers intracellular Ca2+ dysregulation, which has long been thought to be critical for initiating excitotoxic cell death cascades associated with stroke and neurodegenerative disease. The inability of NMDA receptor antagonists to afford neuroprotection in clinical stroke trials has led to a re-evaluation of excitotoxic models of cell death and has focused research efforts towards identifying additional Ca2+ influx pathways. Recent studies indicate that TRPM2, a member of the TRPM subfamily of Ca2+-permeant, non-selective cation channel, plays an important role in mediating cellular responses to a wide range of stimuli that, under certain situations, can induce cell death. These include reactive oxygen and nitrogen species, tumour necrosis factor as well as soluble oli-gomers of amyloid beta. However, the molecular basis of TRPM2 channel involvement in these processes is not fully understood. In this review, we summarize recent studies about the regulation of TRPM2, its interaction with calcium and the possible implications for neurodegenerative diseases. PMID:21383889

Characterization of LANDSAT Panels Using the NIST BRDF Scale from 1100 nm to 2500 nm

NASA Technical Reports Server (NTRS)

Markham, Brian; Tsai, Benjamin K.; Allen, David W.; Cooksey, Catherine; Yoon, Howard; Hanssen, Leonard; Zeng, Jinan; Fulton, Linda; Biggar, Stuart; Markham, Brian

2010-01-01

Many earth observing sensors depend on white diffuse reflectance standards to derive scales of radiance traceable to the St Despite the large number of Earth observing sensors that operate in the reflective solar region of the spectrum, there has been no direct method to provide NIST traceable BRDF measurements out to 2500 rim. Recent developments in detector technology have allowed the NIST reflectance measurement facility to expand the operating range to cover the 250 nm to 2500 nm range. The facility has been modified with and additional detector using a cooled extended range indium gallium arsenide (Extended InGaAs) detector. Measurements were made for two PTFE white diffuse reflectance standards over the 1100 nm to 2500 nm region at a 0' incident and 45' observation angle. These two panels will be used to support the OLI calibration activities. An independent means of verification was established using a NIST radiance transfer facility based on spectral irradiance, radiance standards and a diffuse reflectance plaque. An analysis on the results and associated uncertainties will be discussed.

Long-Term Remote Monitoring of Three Typical Lake Area Variations in the Northwest China Over the Past 40 Years

NASA Astrophysics Data System (ADS)

Liu, Y.; Lu, Y.; Li, Y.; Yue, H.

2018-04-01

water resources management and sustainable development strategy, but also provide reference for assessing the impact of climate change and human activities. This paper selects three inland lakes in Northwest China, using Landsat MSS/TM/ETM+/OLI data from 1970 to 2015, Normalized Difference Water Index (NDWI) and Modified Normalized Difference Water Index (MNDWI) were used to extract lake area and analysed the dynamic trends. Meteorological station rainfall, evaporation and other meteorological data of the lakes were used to analyse reasons for the area change. The results showed that area of Hongjiannao Lake in the past 40 a was reduced, the groundwater impoundment and underground coal mining are the main cause of area reduction; the area of Bosten Lake in recent 40 a showed a decreasing trend after the first increase, the area was mainly affected by the surface runoff and snowmelt; the area of Qinghai Lake in the past 40 a shows a trend of decreasing first and then increasing, the change of its area is mainly affected by regional precipitation and the inflow.

The Combination of Uav Survey and Landsat Imagery for Monitoring of Crop Vigor in Precision Agriculture

NASA Astrophysics Data System (ADS)

Lukas, V.; Novák, J.; Neudert, L.; Svobodova, I.; Rodriguez-Moreno, F.; Edrees, M.; Kren, J.

2016-06-01

Mapping of the with-in field variability of crop vigor has a long tradition with a success rate ranging from medium to high depending on the local conditions of the study. Information about the development of agronomical relevant crop parameters, such as above-ground biomass and crop nutritional status, provides high reliability for yield estimation and recommendation for variable rate application of fertilizers. The aim of this study was to utilize unmanned and satellite multispectral imaging for estimation of basic crop parameters during the growing season. The experimental part of work was carried out in 2014 at the winter wheat field with an area of 69 ha located in the South Moravia region of the Czech Republic. An UAV imaging was done in April 2014 using Sensefly eBee, which was equipped by visible and near infrared (red edge) multispectral cameras. For ground truth calibration the spectral signatures were measured on 20 sites using portable spectroradiometer ASD Handheld 2 and simultaneously plant samples were taken at BBCH 32 (April 2014) and BBCH 59 (Mai 2014) for estimation of above-ground biomass and nitrogen content. The UAV survey was later extended by selected cloud-free Landsat 8 OLI satellite imagery, downloaded from USGS web application Earth Explorer. After standard pre-processing procedures, a set of vegetation indices was calculated from remotely and ground sensed data. As the next step, a correlation analysis was computed among crop vigor parameters and vegetation indices. Both, amount of above-ground biomass and nitrogen content were highly correlated (r > 0.85) with ground spectrometric measurement by ASD Handheld 2 in BBCH 32, especially for narrow band vegetation indices (e.g. Red Edge Inflection Point). UAV and Landsat broadband vegetation indices varied in range of r = 0.5 - 0.7, highest values of the correlation coefficients were obtained for crop biomass by using GNDVI. In all cases results from BBCH 59 vegetation stage showed lower

Can Satellite Remote Sensing be Applied in Geological Mapping in Tropics?

NASA Astrophysics Data System (ADS)

Magiera, Janusz

2018-03-01

Remote sensing (RS) techniques are based on spectral data registered by RS scanners as energy reflected from the Earth's surface or emitted by it. In "geological" RS the reflectance (or emittence) should come from rock or sediment. The problem in tropical and subtropical areas is a dense vegetation. Spectral response from the rocks and sediments is gathered only from the gaps among the trees and shrubs. Images of high resolution are appreciated here, therefore. New generation of satellites and scanners (Digital Globe WV2, WV3 and WV4) yield imagery of spatial resolution of 2 m and up to 16 spectral bands (WV3). Images acquired by Landsat (TM, ETM+, OLI) and Sentinel 2 have good spectral resolution too (6-12 bands in visible and infrared) and, despite lower spatial resolution (10-60 m of pixel size) are useful in extracting lithological information too. Lithological RS map may reveal good precision (down to a single rock or outcrop of a meter size). Supplemented with the analysis of Digital Elevation Model and high resolution ortophotomaps (Google Maps, Bing etc.) allows for quick and cheap mapping of unsurveyed areas.

Spatial temporal analysis of urban heat hazard in Tangerang City

NASA Astrophysics Data System (ADS)

Wibowo, Adi; Kuswantoro; Ardiansyah; Rustanto, Andry; Putut Ash Shidiq, Iqbal

2016-11-01

Urban heat is a natural phenomenon which might caused by human activities. The human activities were represented by various types of land-use such as urban and non-urban area. The aim of this study is to identify the urban heat behavior in Tangerang City as it might threats the urban environment. This study used three types of remote sensing data namely, Landsat TM, Landsat ETM+ and Landsat OLI-TIRS, to capture the urban heat behavior and to analysis the urban heat signature of Tangerang City in 2001, 2012, 2013, 2014, 2015 and 2016. The result showed that urban heat signature change dynamically each month based on the sun radiation. The urban heat island covered only small part of Tangerang City in 2001, but it was significantly increased and reached 50% of the area in 2012. Based on the result on urban heat signature, the threshold for threatening condition is 30 oC which recognized from land surface temperature (LST). The effective temperature (ET) index explains that condition as warm, uncomfortable, increase stress due to sweating and blood flow and may causing cardiovascular disorder.

Surge of Hispar Glacier, Pakistan, between 2013 and 2017 detected from remote sensing observations

NASA Astrophysics Data System (ADS)

Rashid, Irfan; Abdullah, Tariq; Glasser, Neil F.; Naz, Heena; Romshoo, Shakil Ahmad

2018-02-01

This study analyses the behaviour of an actively surging glacier, Hispar, in Pakistan using remote sensing methods. We used 15 m panchromatic band of Landsat 8 OLI from 2013 to 2017 to assess the changes in glacier velocity, glacier geomorphology and supraglacial water bodies. For the velocity estimation, correlation image analysis (CIAS) was used, which is based on normalized cross-correlation (NCC) of satellite data. On-screen digitization was employed to quantify changes in the glacier geomorphology and dynamics of supraglacial water bodies on the glacier. Our velocity estimates indicate that the upper part of the glacier is presently undergoing an active surge which not only affects the debris distribution but also impacts the development of supraglacial water bodies. Velocities in the actively surging part of the main glacier trunk and its three tributaries reach up to 900 m yr- 1. The surge of Hispar also impacts the distribution of supraglacial debris causing folding of the medial moraines features present on the glacier surface. Changes in the number and size of supraglacial lakes and ponds were also observed during the observation period from 2013 to 2017.

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

NASA Astrophysics Data System (ADS)

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

2018-05-01

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

Utilizing NASA Earth Observations to detect factors contributing to hypoxic events in the southern Gulf of Mexico

NASA Astrophysics Data System (ADS)

Chapman, R.; Johansen, A.; Mitchell, Å. R.; Caraballo Álvarez, I. O.; Taggart, M.; Smith, B.

2015-12-01

Monitoring and analyzing harmful algal blooms (HABs) and hypoxic events in the southern coastal areas of the Gulf of Mexico (GoM) is important for watershed management and mitigation of environmental degradation. This study uncovered trends and dynamic characteristics of chlorophyll-a (Chl) concentration, sea surface temperature (SST), colored dissolved organic matter index (CDOM), and photosynthetically available radiation (PAR); as evident in 8-day standard mapped image (SMI) products from the MODIS instrument on the Aqua platform from 2002-2015 using Clark Labs TerrSet Earth Trends Modeler (ETM). Predicted dissolved oxygen images were classified using a Multi-Layer Perceptron regression approach with in-situ data from the northern GoM. Additionally, sediment and nutrient loading values of the Grijalva-Usumacinta watershed were modeled using the ArcGIS Soil and Water Assessment Tool (SWAT). Lastly, A Turbidity Index was generated using Landsat 8 Operational Land Imager (OLI) scenes for 2014-2015. Results, tools, and products will assist local environmental and health authorities in revising water quality standards and mitigating the impacts of future HABs and hypoxic events in the region. This project uses NASA's earth observations as a viable alternative to studying a region with no in-situ data.

a Semi-Empirical Topographic Correction Model for Multi-Source Satellite Images

NASA Astrophysics Data System (ADS)

Xiao, Sa; Tian, Xinpeng; Liu, Qiang; Wen, Jianguang; Ma, Yushuang; Song, Zhenwei

2018-04-01

Topographic correction of surface reflectance in rugged terrain areas is the prerequisite for the quantitative application of remote sensing in mountainous areas. Physics-based radiative transfer model can be applied to correct the topographic effect and accurately retrieve the reflectance of the slope surface from high quality satellite image such as Landsat8 OLI. However, as more and more images data available from various of sensors, some times we can not get the accurate sensor calibration parameters and atmosphere conditions which are needed in the physics-based topographic correction model. This paper proposed a semi-empirical atmosphere and topographic corrction model for muti-source satellite images without accurate calibration parameters.Based on this model we can get the topographic corrected surface reflectance from DN data, and we tested and verified this model with image data from Chinese satellite HJ and GF. The result shows that the correlation factor was reduced almost 85 % for near infrared bands and the classification overall accuracy of classification increased 14 % after correction for HJ. The reflectance difference of slope face the sun and face away the sun have reduced after correction.

Ultra-portable field transfer radiometer for vicarious calibration of earth imaging sensors

NASA Astrophysics Data System (ADS)

Thome, Kurtis; Wenny, Brian; Anderson, Nikolaus; McCorkel, Joel; Czapla-Myers, Jeffrey; Biggar, Stuart

2018-06-01

A small portable transfer radiometer has been developed as part of an effort to ensure the quality of upwelling radiance from test sites used for vicarious calibration in the solar reflective. The test sites are used to predict top-of-atmosphere reflectance relying on ground-based measurements of the atmosphere and surface. The portable transfer radiometer is designed for one-person operation for on-site field calibration of instrumentation used to determine ground-leaving radiance. The current work describes the detector- and source-based radiometric calibration of the transfer radiometer highlighting the expected accuracy and SI-traceability. The results indicate differences between the detector-based and source-based results greater than the combined uncertainties of the approaches. Results from recent field deployments of the transfer radiometer using a solar radiation based calibration agree with the source-based laboratory calibration within the combined uncertainties of the methods. The detector-based results show a significant difference to the solar-based calibration. The source-based calibration is used as the basis for a radiance-based calibration of the Landsat-8 Operational Land Imager that agrees with the OLI calibration to within the uncertainties of the methods.

Nucleation kinetics of MgCl2-ethanol adduct for the supported Ziegler-Natta catalysts with a thermodynamic approach

NASA Astrophysics Data System (ADS)

Ansari, Ziaul Haque; Zeng, Yan; Demopoulos, George P.; Li, Zhibao

2018-07-01

MgCl2-ethanol adducts play a key role in the synthesis of supported Ziegler-Natta catalysts. The morphology of the MgCl2-ethanol adducts, which is controlled by their crystallization process, can determine the structure and thus the property of the polyolefin products. Here we study the nucleation kinetics of MgCl2-ethanol adducts by measuring the metastable zone width (MSZW) and induction time at different temperatures. Supersaturation ratios used in induction time measurements were predicted by the Mixed Solvent Electrolyte (MSE) model embedded in OLI System. Nývlt‧s approach was applied to determine MSZW. By the induction time measurement, the effect of temperature, and supersaturation were studied. It was found that induction time decreases as either temperature or supersaturation increases. The measured MSZW and induction time are used to estimate the nucleation kinetics of the system, and thereby distinguishing between the homogeneous and heterogeneous mechanisms. The interfacial tension and other related nucleation parameters were calculated from the induction time data. XRD and TGA indicate that the MgCl2-ethanol adduct has the stoichiometry of MgCl2·6C2H5OH.

Study of microstructural characterization and ionic conductivity of a chemical-covalent polyether-siloxane hybrid doped with LiClO4.

PubMed

Liang, Wuu-Jyh; Chen, Ying-Pin; Wu, Chien-Pang; Kuo, Ping-Lin

2005-12-29

The chemical-covalent polyether-siloxane hybrids (EDS) doped with various amounts of LiClO4 salt were characterized by FT-IR, DSC, TGA, and solid-state NMR spectra as well as impedance measurements. These observations indicate that different types of complexes by the interactions of Li+ and ClO4- ions are formed within the hybrid host, and the formation of transient cross-links between Li+ ions and ether oxygens results in the increase in T(g) of polyether segments and the decrease in thermal stability of hybrid electrolyte. Initially a cation complexation dominated by the oxirane-cleaved cross-link site and PEO block is present, and after the salt-doped level of O/Li+ = 20, the complexation through the PPO block becomes more prominent. Moreover, a significant degree of ionic association is examined in the polymer-salt complexes at higher salt uptakes. A VTF-like temperature dependence of ionic conductivity is observed in all of the investigated salt concentrations, implying that the diffusion of charge carrier is assisted by the segmental motions of the polymer chains. The behavior of ion transport in these hybrid electrolytes is further correlated with the interactions between ions and polymer host.

Towards decadal soil salinity mapping using Landsat time series data

NASA Astrophysics Data System (ADS)

Fan, Xingwang; Weng, Yongling; Tao, Jinmei

2016-10-01

Salinization is one of the major soil problems around the world. However, decadal variation in soil salinization has not yet been extensively reported. This study exploited thirty years (1985-2015) of Landsat sensor data, including Landsat-4/5 TM (Thematic Mapper), Landsat-7 ETM+ (Enhanced Thematic Mapper Plus) and Landsat-8 OLI (Operational Land Imager), for monitoring soil salinity of the Yellow River Delta, China. The data were initially corrected for atmospheric effects, and then matched the spectral bands of EO-1 (Earth Observing One) ALI (Advanced Land Imager). Subsequently, soil salinity maps were derived with a previously developed PLSR (Partial Least Square Regression) model. On intra-annual scale, the retrievals showed that soil salinity increased in February, stabilized in March, and decreased in April. On inter-annual scale, soil salinity decreased within 1985-2000 (-0.74 g kg-1/10a, p < 0.001), and increased within 2000-2015 (0.79 g kg-1/10a, p < 0.001). Our study presents a new perspective for use of multiple Landsat data in soil salinity retrieval, and further the understanding of soil salinization development over the Yellow River Delta.

The QWIP Focal Plane Assembly for NASA's Landsat Data Continuity Mission

NASA Technical Reports Server (NTRS)

Jhabvala, M.; Reuter, D.; Choi, K.; Sundaram, M.; Jhabvala, C.; La, A.; Waczynski, A.; Bundas, J.

2011-01-01

The Thermal Infrared Sensor (TIRS) is a QWIP based instrument intended to supplement the Operational Land Imager (OLI) for the Landsat Data Continuity Mission (LDCM). The TIRS instrument is a dual channel far infrared imager with the two bands centered at 10.8 m and 12.0 m. The focal plane assembly (FPA) consists of three 640x512 GaAs Quantum Well Infrared Photodetector (QWIP) arrays precisely mounted to a silicon carrier substrate that is mounted on an invar baseplate. The two spectral bands are defined by bandpass filters mounted in close proximity to the detector surfaces. The focal plane operating temperature is 43K. The QWIP arrays are hybridized to Indigo ISC9803 readout integrated circuits (ROICs). Two varieties of QWIP detector arrays are being developed for this project, a corrugated surface structure QWIP and a grating surface structure QWIP. This paper will describe the TIRS system noise equivalent temperature difference sensitivity as it affects the QWIP focal plane performance requirements: spectral response, dark current, conversion efficiency, read noise, temperature stability, pixel uniformity, optical crosstalk and pixel yield. Additional mechanical constraints as well as qualification through Technology Readiness Level 6 (TRL 6) will also be discussed.

Land cover changes induced by the great east Japan earthquake in 2011

NASA Astrophysics Data System (ADS)

Ishihara, Mitsunori; Tadono, Takeo

2017-03-01

The east Japan earthquake that occurred on March 11, 2011 was a big natural disaster, comprising the large earthquake shock, tsunami, and Fukushima Daiichi Nuclear Power Plant (FDNPP) accident. These disasters caused changes in the land use and land cover (LULC) in Japan’s Tohoku district. While the LULC map created before the disaster is available, as yet there is no precise LULC map of the district after the disaster. In this study, we created a precise LULC map for the years 2013-2015 post-disaster with 30-m spatial resolution using the Landsat-8 with the Operational Land Imager (OLI) to evaluate the changes in LULC induced by the disaster. Our results indicate many changes in areas categorized as rice paddies primarily into grass categories along the coast damaged by the tsunami and in the evacuation zone around the FDNPP. Since there is a possibility of future LULC changes according to the change of the evacuation zone and implementation of reconstruction and revitalization efforts, we recommend continual monitoring of the changes in LULC by the use of satellite data in order to evaluate the long-term effects of the disaster.

Land cover changes induced by the great east Japan earthquake in 2011.

PubMed

Ishihara, Mitsunori; Tadono, Takeo

2017-03-31

The east Japan earthquake that occurred on March 11, 2011 was a big natural disaster, comprising the large earthquake shock, tsunami, and Fukushima Daiichi Nuclear Power Plant (FDNPP) accident. These disasters caused changes in the land use and land cover (LULC) in Japan's Tohoku district. While the LULC map created before the disaster is available, as yet there is no precise LULC map of the district after the disaster. In this study, we created a precise LULC map for the years 2013-2015 post-disaster with 30-m spatial resolution using the Landsat-8 with the Operational Land Imager (OLI) to evaluate the changes in LULC induced by the disaster. Our results indicate many changes in areas categorized as rice paddies primarily into grass categories along the coast damaged by the tsunami and in the evacuation zone around the FDNPP. Since there is a possibility of future LULC changes according to the change of the evacuation zone and implementation of reconstruction and revitalization efforts, we recommend continual monitoring of the changes in LULC by the use of satellite data in order to evaluate the long-term effects of the disaster.

Biscayne National Park

NASA Image and Video Library

2017-12-08

On February 25, 2016, the Operational Land Imager (OLI) on the Landsat 8 satellite acquired this natural-color image of Biscayne National Park. The park encompasses the northernmost Florida Keys, starting from Miami to just north of Key Largo. The keys run like a spine through the center of the park, with Biscayne Bay to the west and the Atlantic Ocean to the east. The water-covered areas span more than 660 square kilometers (250 square miles) of the park, making it the largest marine park in the U.S. National Park System. Biscayne protects the longest stretch of mangrove forest on the U.S. East Coast, and one of the most extensive stretches of coral reef in the world. Read more: go.nasa.gov/1SWs1a3 Credit: NASA/Landsat8 NASA image use policy. NASA Goddard Space Flight Center enables NASA’s mission through four scientific endeavors: Earth Science, Heliophysics, Solar System Exploration, and Astrophysics. Goddard plays a leading role in NASA’s accomplishments by contributing compelling scientific knowledge to advance the Agency’s mission. Follow us on Twitter Like us on Facebook Find us on Instagram

Assessing the role of climate and resource management on groundwater dependent ecosystem changes in arid environments with the Landsat archive

USGS Publications Warehouse

Huntington, Justin; McGwire, Kenneth C.; Morton, Charles; Snyder, Keirith A.; Peterson, Sarah; Erickson, Tyler; Niswonger, Richard G.; Carroll, Rosemary W.H.; Smith, Guy; Allen, Richard

2016-01-01

Groundwater dependent ecosystems (GDEs) rely on near-surface groundwater. These systems are receiving more attention with rising air temperature, prolonged drought, and where groundwater pumping captures natural groundwater discharge for anthropogenic use. Phreatophyte shrublands, meadows, and riparian areas are GDEs that provide critical habitat for many sensitive species, especially in arid and semi-arid environments. While GDEs are vital for ecosystem services and function, their long-term (i.e. ~ 30 years) spatial and temporal variability is poorly understood with respect to local and regional scale climate, groundwater, and rangeland management. In this work, we compute time series of NDVI derived from sensors of the Landsat TM, ETM +, and OLI lineage for assessing GDEs in a variety of land and water management contexts. Changes in vegetation vigor based on climate, groundwater availability, and land management in arid landscapes are detectable with Landsat. However, the effective quantification of these ecosystem changes can be undermined if changes in spectral bandwidths between different Landsat sensors introduce biases in derived vegetation indices, and if climate, and land and water management histories are not well understood. The objective of this work is to 1) use the Landsat 8 under-fly dataset to quantify differences in spectral reflectance and NDVI between Landsat 7 ETM + and Landsat 8 OLI for a range of vegetation communities in arid and semiarid regions of the southwestern United States, and 2) demonstrate the value of 30-year historical vegetation index and climate datasets for assessing GDEs. Specific study areas were chosen to represent a range of GDEs and environmental conditions important for three scenarios: baseline monitoring of vegetation and climate, riparian restoration, and groundwater level changes. Google's Earth Engine cloud computing and environmental monitoring platform is used to rapidly access and analyze the Landsat archive

The QWIP Focal Plane Assembly for NASA's Landsat Data Continuity Mission

NASA Technical Reports Server (NTRS)

Jhabvala, M; Choi, K.; Reuter, D.; Sundaram, M.; Jhabvala, C; La, Anh; Waczynski, Augustyn; Bundas, Jason

2010-01-01

The Thermal Infrared Sensor (TIRS) is a QWIP based instrument intended to supplement the Operational Land Imager (OLI) for the Landsat Data Continuity Mission (LDCM). The TIRS instrument is a dual channel far infrared imager with the two bands centered at 10.8[mu]m and 12.0[mu]m. The focal plane assembly (FPA) consists of three 640x512 GaAs Quantum Well Infrared Photodetector (QWIP) arrays precisely mounted to a silicon carrier substrate that is mounted on an invar baseplate. The two spectral bands are defined by bandpass filters mounted in close proximity to the detector surfaces. The focal plane operating temperature is 43K. The QWIP arrays are hybridized to Indigo ISC9803 readout integrated circuits (ROICs). Two varieties of QWIP detector arrays are being developed for this project, a corrugated surface structure QWIP and a grating surface structure QWIP. This paper will describe the TIRS system noise equivalent temperature difference sensitivity as it affects the QWIP focal plane performance requirements: spectral response, dark current, conversion efficiency, read noise, temperature stability, pixel uniformity, optical crosstalk and pixel yield. Additional mechanical constraints as well as qualification through Technology Readiness Level 6 (TRL 6) will also be discussed.

A one year Landsat 8 conterminous United States study of spatial and temporal patterns of cirrus and non-cirrus clouds and implications for the long term Landsat archive.

NASA Astrophysics Data System (ADS)

Kovalskyy, V.; Roy, D. P.

2014-12-01

The successful February 2013 launch of the Landsat 8 satellite is continuing the 40+ year legacy of the Landsat mission. The payload includes the Operational Land Imager (OLI) that has a new 1370 mm band designed to monitor cirrus clouds and the Thermal Infrared Sensor (TIRS) that together provide 30m low, medium and high confidence cloud detections and 30m low and high confidence cirrus cloud detections. A year of Landsat 8 data over the Conterminous United States (CONUS), composed of 11,296 acquisitions, was analyzed comparing the spatial and temporal incidence of these cloud and cirrus states. This revealed (i) 36.5% of observations were detected with high confidence cloud with spatio-temporal patterns similar to those observed by previous Landsat 7 cloud analyses, (ii) 29.2% were high confidence cirrus, (iii) 20.9% were both high confidence cloud and high confidence cirrus, (iv) 8.3% were detected as high confidence cirrus but not as high confidence cloud. The results illustrate the value of the cirrus band for improved Landsat 8 terrestrial monitoring but imply that the historical CONUS Landsat archive has a similar 8% of undetected cirrus contaminated pixels. The implications for long term Landsat time series records, including the global Web Enabled Landsat Data (WELD) product record, are discussed.

Multi-scale investigation of shrub encroachment in southern Africa

NASA Astrophysics Data System (ADS)

Aplin, Paul; Marston, Christopher; Wilkinson, David; Field, Richard; O'Regan, Hannah

2016-04-01

There is growing speculation that savannah environments throughout Africa have been subject to shrub encroachment in recent years, whereby grassland is lost to woody vegetation cover. Changes in the relative proportions of grassland and woodland are important in the context of conservation of savannah systems, with implications for faunal distributions, environmental management and tourism. Here, we focus on southern Kruger National Park, South Africa, and investigate whether or not shrub encroachment has occurred over the last decade and a half. We use a multi-scale approach, examining the complementarity of medium (e.g. Landsat TM and OLI) and fine (e.g. QuickBird and WorldView-2) spatial resolution satellite sensor imagery, supported by intensive field survey in 2002 and 2014. We employ semi-automated land cover classification, involving a hybrid unsupervised clustering approach with manual class grouping and checking, followed by change detection post-classification comparison analysis. The results show that shrub encroachment is indeed occurring, a finding evidenced through three fine resolution replicate images plus medium resolution imagery. The results also demonstrate the complementarity of medium and fine resolution imagery, though some thematic information must be sacrificed to maintain high medium resolution classification accuracy. Finally, the findings have broader implications for issues such as vegetation seasonality, spatial transferability and management practices.

The Impact of Urbanization to Forest Degradation in Metropolitan Semarang: A Preliminary Study

NASA Astrophysics Data System (ADS)

Sejati, A. W.; Buchori, I.; Rudiarto, I.

2018-02-01

This paper aims to examine the relationship of urbanization and the consequences of environmental impacts, especially the availability of forests. The analysis used remote sensing data ie Landsat 7 ETM (1990), Landsat 7 ETM (2000), and Landsat 8 OLI (2015). Analysis of forest availability used green vegetation cover parameters with NDVI techniques, while urbanization was measured by looking at the built-up area growth with NDBI techniques. The detection result in 1990 area of urban area was 74.85 km2, in 2000 was 130.83 km2, and in 2015 was 292.74 km2. Given the overall size of the metropolitan area of Semarang (932.14 km2), the proportion of the built up area in 2015 was 31% with an average of 6% per year change in 1990-2000 and 8.2% per year in 2000-2015. Urbanization in this region is characterized by forest conversion into residential and industrial buildings. With increasing area and built-up density, NDBI is found to be proportionately increasing, while NDVI decrease is significant. The results show that NDBI-NDVI correlation is negative (-0.99). It is very important for policy makers to formulate land use control policies in Metropolitan Semarang particularly in responding to the issue of forest conversion.

Estimating plant area index for monitoring crop growth dynamics using Landsat-8 and RapidEye images

NASA Astrophysics Data System (ADS)

Shang, Jiali; Liu, Jiangui; Huffman, Ted; Qian, Budong; Pattey, Elizabeth; Wang, Jinfei; Zhao, Ting; Geng, Xiaoyuan; Kroetsch, David; Dong, Taifeng; Lantz, Nicholas

2014-01-01

This study investigates the use of two different optical sensors, the multispectral imager (MSI) onboard the RapidEye satellites and the operational land imager (OLI) onboard the Landsat-8 for mapping within-field variability of crop growth conditions and tracking the seasonal growth dynamics. The study was carried out in southern Ontario, Canada, during the 2013 growing season for three annual crops, corn, soybeans, and winter wheat. Plant area index (PAI) was measured at different growth stages using digital hemispherical photography at two corn fields, two winter wheat fields, and two soybean fields. Comparison between several conventional vegetation indices derived from concurrently acquired image data by the two sensors showed a good agreement. The two-band enhanced vegetation index (EVI2) and the normalized difference vegetation index (NDVI) were derived from the surface reflectance of the two sensors. The study showed that EVI2 was more resistant to saturation at high biomass range than NDVI. A linear relationship could be used for crop green effective PAI estimation from EVI2, with a coefficient of determination (R2) of 0.85 and root-mean-square error of 0.53. The estimated multitemporal product of green PAI was found to be able to capture the seasonal dynamics of the three crops.

Decadal changes in the land use/land cover and shoreline along the coastal districts of southern Gujarat, India.

PubMed

Misra, A; Balaji, R

2015-07-01

The coastal zone along the districts of Surat, Navsari, and Valsad in southern Gujarat, India, is reported to be facing serious environmental challenges in the form of shoreline erosion, wetland loss, and man-made encroachments. This study assesses the decadal land use/ land cover (LULC) changes in these three districts for the years 1990, 2001, and 2014 using satellite datasets of Landsat TM, ETM, and OLI. The LULC changes are identified by using band ratios as a pre-classification step, followed by implementation of hybrid classification (a combination of supervised and unsupervised classification). An accuracy assessment is carried out for each dataset, and the overall accuracy ranges from 90 to 95%. It is observed that the spatial extents of aquaculture, urban built-up, and barren classes have appreciated over time, whereas the coverage of mudflats has depreciated due to rapid urbanization. The changes in the shoreline of these districts have also been analyzed for the same years, and significant changes are found in the form of shoreline erosion. The LULC maps prepared as well as the shoreline change analysis done for this study area will enable the local decision makers to adopt better land-use planning and shoreline protection measures, which will further aid in sustainable future developments in this region.

Monitoring Jakobshavn Glacier using Sequential Landsat Images

NASA Astrophysics Data System (ADS)

Jian, Z.; Zhuoqi, C.; Cheng, X.

2016-12-01

Jakobshavn Glacier is the fastest (19 m per day) and one of the most active glaciers around the world. Discharging more than 35km3 of ice every year, its mass loss surpasses anyone else outside the Antarctic. From Landsat 8 OLI Images on August 14, 2015, we find a huge iceberg about 5 km2 calved from resulting in the front shrinking for 1060.8m. NSIDC ice velocity data and weather station data on Jakobshavn glacier are used to analyze the cause of calving. On one hand, upstream glacier push forward the Jakobshavn glacier westward continually, many cracks were formed over the glacier surface. Surface melting water flow into the interior of glaciers to accelerate calving. On the other hand with the gradually rising temperature, the bottom of glaciers accelerate ablation. When glaciers move into the ocean and the thin bottom can not provide strong enough support, calving occurs. Before this incident, we trace sequential Landsat data during 1986 to 2015. In 2010, it had another large-scale calving. We draw from our data that Jakobshavn retreated intensely in the past 30 years although in the last 10 years it appears more stable. The speed of glacier shrinking during 1996 to 2006 is three times as fast as past 10 years.

Object-based land-use/land-cover change detection using Landsat imagery: a case study of Ardabil, Namin, and Nir counties in northwest Iran.

PubMed

Aslami, Farnoosh; Ghorbani, Ardavan

2018-06-03

In this study, land-use/land-cover (LULC) change in the Ardabil, Namin, and Nir counties, in the Ardabil province in the northwest of Iran, was detected using an object-based method. Landsat images including Thematic Mapper (TM), Landsat Enhanced Thematic Mapper Plus (ETM + ), and Operational Land Imager (OLI) were used. Preprocessing methods, including geometric and radiometric correction, and topographic normalization were performed. Image processing was conducted according to object-based image analysis using the nearest neighbor algorithm. An accuracy assessment was conducted using overall accuracy and Kappa statistics. Results show that maps obtained from images for 1987, 2002, and 2013 had an overall accuracy of 91.76, 91.06, and 93.00%, and a Kappa coefficient of 0.90, 0.83, and 0.91, respectively. Change detection between 1987 and 2013 shows that most of the rangelands (97,156.6 ha) have been converted to dry farming; moreover, residential and other urban land uses have also increased. The largest change in land use has occurred for irrigated farming, rangelands, and dry farming, of which approximately 3539.8, 3086.9, and 2271.9 ha, respectively, have given way to urban land use for each of the studied years.

Earth Observing-1 Extended Mission

USGS Publications Warehouse

,

2005-01-01

Since November 2000, the National Aeronautics and Space Administration (NASA) Earth Observing-1 (EO-1) mission has demonstrated the capabilities of a dozen spacecraft sensor and communication innovations. Onboard the EO-1 spacecraft are two land remote sensing instruments. The Advanced Land Imager (ALI) acquires data in spectral bands and at resolutions similar to Landsat. The Hyperion instrument, which is the first civilian spaceborne hyperspectral imager, acquires data in 220 10-nanometer bands covering the visible, near, and shortwave-infrared bands. The initial one-year technology demonstration phase of the mission included a detailed comparison of ALI with the Landsat Enhanced Thematic Mapper Plus (ETM+) instrument. Specifications for the Operational Land Imager (OLI), the planned successor to ETM+, were formulated in part from performance characteristics of ALI. Recognizing the remarkable performance of the satellite's instruments and the exceptional value of the data, the U.S. Geological Survey (USGS) and NASA agreed in December 2001 to share responsibility for operating EO-1. The extended mission continues, on a cost-reimbursable basis, as long as customer sales fully recover flight and ground operations costs. As of May 2005, more than 17,800 scenes from each instrument have been acquired, indexed, archived, and made available to the public.

Targeted Deletion of the Antisilencer/Enhancer (ASE) Element from Intron 1 of the Myelin Proteolipid Protein Gene (Plp1) in Mouse Reveals that the Element Is Dispensable for Plp1 Expression in Brain during Development and Remyelination

PubMed Central

Pereira, Glauber B.; Meng, Fanxue; Kockara, Neriman T.; Yang, Baoli; Wight, Patricia A.

2012-01-01

Myelin proteolipid protein gene (Plp1) expression is temporally regulated in brain, which peaks during the active myelination period of CNS development. Previous studies with Plp1-lacZ transgenic mice demonstrated that (mouse) Plp1 intron 1 DNA is required for high levels of expression in oligodendrocytes. Deletion-transfection analysis revealed the intron contains a single positive regulatory element operative in the N20.1 oligodendroglial cell line, which was named ASE (antisilencer/enhancer) based on its functional properties in these cells. To investigate the role of the ASE in vivo, the element was deleted from the native gene in mouse using a Cre/lox strategy. While removal of the ASE from Plp1-lacZ constructs profoundly decreased expression in transfected oligodendroglial cell lines (N20.1 and Oli-neu), the element was dispensable to achieve normal levels of Plp1 gene expression in mouse during development (except perhaps at postnatal day 15) and throughout the remyelination period following cuprizone-induced (acute) demyelination. Thus, it is possible that the ASE is nonfunctional in vivo, or that loss of the ASE from the native gene in mouse can be compensated for by the presence of other regulatory elements within the Plp1 gene. PMID:23157328

Targeted deletion of the antisilencer/enhancer (ASE) element from intron 1 of the myelin proteolipid protein gene (Plp1) in mouse reveals that the element is dispensable for Plp1 expression in brain during development and remyelination.

PubMed

Pereira, Glauber B; Meng, Fanxue; Kockara, Neriman T; Yang, Baoli; Wight, Patricia A

2013-02-01

Myelin proteolipid protein gene (Plp1) expression is temporally regulated in brain, which peaks during the active myelination period of CNS development. Previous studies with Plp1-lacZ transgenic mice demonstrated that (mouse) Plp1 intron 1 DNA is required for high levels of expression in oligodendrocytes. Deletion-transfection analysis revealed the intron contains a single positive regulatory element operative in the N20.1 oligodendroglial cell line, which was named ASE (antisilencer/enhancer) based on its functional properties in these cells. To investigate the role of the ASE in vivo, the element was deleted from the native gene in mouse using a Cre/lox strategy. Although removal of the ASE from Plp1-lacZ constructs profoundly decreased expression in transfected oligodendroglial cell lines (N20.1 and Oli-neu), the element was dispensable to achieve normal levels of Plp1 gene expression in mouse during development (except perhaps at postnatal day 15) and throughout the remyelination period following cuprizone-induced (acute) demyelination. Thus, it is possible that the ASE is non-functional in vivo, or that loss of the ASE from the native gene in mouse can be compensated for by the presence of other regulatory elements within the Plp1 gene. © 2012 International Society for Neurochemistry.

Landsat Data Continuity Mission, now Landsat-8: six months on-orbit

USGS Publications Warehouse

Markham, Brian L.; Storey, James C.; Irons, James R.

2013-01-01

The Landsat Data Continuity Mission (LDCM) with two pushbroom Earth-imaging sensors, the Operational Land Imager (OLI) and the Thermal InfraRed Sensor (TIRS), was launched on February 11, 2013. Its on-orbit check out period or commissioning phase lasted about 90 days. During this phase the spacecraft and its instruments were activated, operationally tested and their performance verified. In addition, during this period, the spacecraft was temporarily placed in an intermediary orbit where it drifted relative to the Landsat-7 spacecraft, providing near simultaneous imaging for about 3 days, allowing data comparison and cross calibration. After this tandem-imaging period, LDCM was raised to its final altitude and placed in the position formerly occupied by Landsat-5, i.e., 8 days out of phase with Landsat-7, with about a 10:10 AM equatorial crossing time. At the end of commissioning, the satellite was transferred to the United States Geological Survey (USGS), officially renamed Landsat-8 and declared operational. Data were made available to the public beginning May 31, 2013. The performance of the satellite and two instruments has generally been excellent as evidenced in the quality of the distributed data products. © (2013) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.

Optical tool for salinity detection by remote sensing spectroscopy: application on Oran watershed, Algeria

NASA Astrophysics Data System (ADS)

Abdellatif, Dehni; Mourad, Lounis

2017-07-01

Soil salinity is a complex problem that affects groundwater aquifers and agricultural lands in the semiarid regions. Remote sensing and spectroscopy database systems provide accuracy for salinity autodetection and dynamical delineation. Salinity detection techniques using polychromatic wavebands by field geocomputation and experimental data are time consuming and expensive. This paper presents an automated spectral detection and identification of salt minerals using a monochromatic waveband concept from multispectral bands-Landsat 8 Operational Land Imager (OLI) and Thermal InfraRed Sensor (TIRS) and spectroscopy United States Geological Survey database. For detecting mineral salts related to electrolytes, such as electronical and vibrational transitions, an integrated approach of salinity detection related to the optical monochromatic concept has been addressed. The purpose of this paper is to discriminate waveband intrinsic spectral similarity using the Beer-Lambert and Van 't Hoff laws for spectral curve extraction such as transmittance, reflectance, absorbance, land surface temperature, molar concentration, and osmotic pressure. These parameters are primordial for hydrodynamic salinity modeling and continuity identification using chemical and physical approaches. The established regression fitted models have been addressed for salt spectroscopy validation for suitable calibration and validation. Furthermore, our analytical tool is conducted for better decision interface using spectral salinity detection and identification in the Oran watershed, Algeria.

Tracing Crop Nitrogen Dynamics on the Field-Scale by Combining Multisensoral EO Data with an Integrated Process Model- A Validation Experiment for Cereals in Southern Germany

NASA Astrophysics Data System (ADS)

Hank, Tobias B.; Bach, Heike; Danner, Martin; Hodrius, Martina; Mauser, Wolfram

2016-08-01

Nitrogen, being the basic element for the construction of plant proteins and pigments, is one of the most important production factors for agricultural cultivation. High resolution and near real-time information on nitrogen status in the soil thus is of highest interest for economically and ecologically optimized fertilizer planning and application. Unfortunately, nitrogen storage in the soil column cannot be directly observed with Earth Observation (EO) instruments. Advanced EO supported process modelling approaches therefore must be applied that allow tracing the spatiotemporal dynamics of nitrogen transformation, translocation and transport in the soil and in the canopy. Before these models can be applied as decision support tools for smart farming, they must be carefully parameterized and validated. This study applies an advanced land surface process model (PROMET) to selected winter cereal fields in Southern Germany and correlates the model outputs to destructively sampled nitrogen data from the growing season of 2015 (17 sampling dates, 8 sample locations). The spatial parametrization of the process model thereby is supported by assimilating eight satellite images (5 times Landsat 8 OLI and 3 times RapidEye). It was found that the model is capable of realistically tracing the temporal and spatial dynamics of aboveground nitrogen uptake and allocation (R2 = 0.84, RMSE 31.3 kg ha-1).

Study of Burn Scar Extraction Automatically Based on Level Set Method using Remote Sensing Data

PubMed Central

Liu, Yang; Dai, Qin; Liu, JianBo; Liu, ShiBin; Yang, Jin

2014-01-01

Burn scar extraction using remote sensing data is an efficient way to precisely evaluate burn area and measure vegetation recovery. Traditional burn scar extraction methodologies have no well effect on burn scar image with blurred and irregular edges. To address these issues, this paper proposes an automatic method to extract burn scar based on Level Set Method (LSM). This method utilizes the advantages of the different features in remote sensing images, as well as considers the practical needs of extracting the burn scar rapidly and automatically. This approach integrates Change Vector Analysis (CVA), Normalized Difference Vegetation Index (NDVI) and the Normalized Burn Ratio (NBR) to obtain difference image and modifies conventional Level Set Method Chan-Vese (C-V) model with a new initial curve which results from a binary image applying K-means method on fitting errors of two near-infrared band images. Landsat 5 TM and Landsat 8 OLI data sets are used to validate the proposed method. Comparison with conventional C-V model, OSTU algorithm, Fuzzy C-mean (FCM) algorithm are made to show that the proposed approach can extract the outline curve of fire burn scar effectively and exactly. The method has higher extraction accuracy and less algorithm complexity than that of the conventional C-V model. PMID:24503563

DWPF RECYCLE EVAPORATOR FLOWSHEET EVALUATION (U)

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

Stone, M

2005-04-30

stream must be pumpable to the DWPF SRAT vessel and should not precipitate solids to avoid fouling the evaporator vessel and heat transfer coils. The evaporation process must not generate excessive foam and must have a high Decontamination Factor (DF) for many species in the evaporator feed to allow the condensate to be transferred to the ETP. An initial scoping study was completed in 2001 to evaluate the feasibility of the evaporator which concluded that the concentration objectives could be met. This initial study was based on initial estimates of recycle concentration and was based solely on OLI modeling of the evaporation process. The Savannah River National Laboratory (SRNL) has completed additional studies using simulated recycle streams and OLI{reg_sign} simulations. Based on this work, the proposed flowsheet for the recycle evaporator was evaluated for feasibility, evaporator design considerations, and impact on the DWPF process. This work was in accordance with guidance from DWPF-E and was performed in accordance with the Technical Task and Quality Assurance Plan.« less

Hyperspectral Features of Oil-Polluted Sea Ice and the Response to the Contamination Area Fraction

PubMed Central

Li, Ying; Liu, Chengyu; Xie, Feng

2018-01-01

Researchers have studied oil spills in open waters using remote sensors, but few have focused on extracting reflectance features of oil pollution on sea ice. An experiment was conducted on natural sea ice in Bohai Bay, China, to obtain the spectral reflectance of oil-contaminated sea ice. The spectral absorption index (SAI), spectral peak height (SPH), and wavelet detail coefficient (DWT d5) were calculated using stepwise multiple linear regression. The reflectances of some false targets were measured and analysed. The simulated false targets were sediment, iron ore fines, coal dust, and the melt pool. The measured reflectances were resampled using five common sensors (GF-2, Landsat8-OLI, Sentinel3-OLCI, MODIS, and AVIRIS). Some significant spectral features could discriminate between oil-polluted and clean sea ice. The indices correlated well with the oil area fractions. All of the adjusted R2 values exceeded 0.9. The SPH model1, based on spectral features at 507–670 and 1627–1746 nm, displayed the best fitting. The resampled data indicated that these multi-spectral and hyper-spectral sensors could be used to detect crude oil on the sea ice if the effect of noise and spatial resolution are neglected. The spectral features and their identified changes may provide reference on sensor design and band selection. PMID:29342945

Regional Mapping of Plantation Extent Using Multisensor Imagery

NASA Astrophysics Data System (ADS)

Torbick, N.; Ledoux, L.; Hagen, S.; Salas, W.

2016-12-01

Industrial forest plantations are expanding rapidly across the tropics and monitoring extent is critical for understanding environmental and socioeconomic impacts. In this study, new, multisensor imagery were evaluated and integrated to extract the strengths of each sensor for mapping plantation extent at regional scales. Three distinctly different landscapes with multiple plantation types were chosen to consider scalability and transferability. These were Tanintharyi, Myanmar, West Kalimantan, Indonesia, and southern Ghana. Landsat-8 Operational Land Imager (OLI), Phased Array L-band Synthetic Aperture Radar-2 (PALSAR-2), and Sentinel-1A images were fused within a Classification and Regression Tree (CART) framework using random forest and high-resolution surveys. Multi-criteria evaluations showed both L-and C-band gamma nought γ° backscatter decibel (dB), Landsat reflectance ρλ, and texture indices were useful for distinguishing oil palm and rubber plantations from other land types. The classification approach identified 750,822 ha or 23% of the Taninathryi, Myanmar, and 216,086 ha or 25% of western West Kalimantan as plantation with very high cross validation accuracy. The mapping approach was scalable and transferred well across the different geographies and plantation types. As archives for Sentinel-1, Landsat-8, and PALSAR-2 continue to grow, mapping plantation extent and dynamics at moderate resolution over large regions should be feasible.

Recent forest cover changes (2002-2015) in the Southern Carpathians: A case study of the Iezer Mountains, Romania.

PubMed

Mihai, Bogdan; Săvulescu, Ionuț; Rujoiu-Mare, Marina; Nistor, Constantin

2017-12-01

The paper explores the dynamics of the forest cover change in the Iezer Mountains, part of Southern Carpathians, in the context of the forest ownership recovery and deforestation processes, combined with the effects of biotic and abiotic disturbances. The aim of the study is to map and evaluate the typology and the spatial extension of changes in the montane forest cover between 700 and 2462m a.s.l., sampling all the representative Carpathian ecosystems, from the European beech zone up to the spruce-fir zone and the subalpine-alpine pastures. The methodology uses a change detection analysis of satellite imagery with Landsat ETM+/OLI and Sentinel-2 MSI data. The workflow started with a complete calibration of multispectral data from 2002, before the massive forest restitution to private owners, after the Law 247/2005 empowerment, and 2015, the intensification of deforestation process. For the data classification, a Maximum Likelihood supervised classification algorithm was utilized. The forest change map was developed after combining the classifications in a unitary formula using image difference. The principal outcome of the research identifies the type of forest cover change using a quantitative formula. This information can be integrated in the future decision-making strategies for forest stand management and sustainable development. Copyright © 2017 Elsevier B.V. All rights reserved.

Total fecal microbiota transplantation alleviates high-fat diet-induced steatohepatitis in mice via beneficial regulation of gut microbiota.

PubMed

Zhou, Da; Pan, Qin; Shen, Feng; Cao, Hai-Xia; Ding, Wen-Jin; Chen, Yuan-Wen; Fan, Jian-Gao

2017-05-08

Non-alcoholic steatohepatitis (NASH) is an epidemic metabolic disease with limited therapeutic strategies. Cumulative data support the pivotal role of gut microbiota in NASH. Here, we investigated the hypothesis regarding whether fecal microbiota transplantation (FMT) is effective in attenuating high-fat diet (HFD)-induced steatohepatitis in mice. Mice were randomized into control, HFD and HFD + FMT groups. After an 8-week HFD, FMT treatment was initiated and carried out for 8 weeks. The gut microbiota structure, butyrate concentrations of the cecal content, liver pathology and intrahepatic lipid and cytokines were examined. Our results showed that after FMT, the gut microbiota disturbance was corrected in HFD-fed mice with elevated abundances of the beneficial bacteria Christensenellaceae and Lactobacillus. FMT also increased butyrate concentrations of the cecal content and the intestinal tight junction protein ZO-1, resulting in relief of endotoxima in HFD-fed mice. Steatohepatitis was alleviated after FMT, as indicated by a significant decrease in intrahepatic lipid accumulation (reduced Oli-red staining, decreased intrahepatic triglyceride and cholesterol), intrahepatic pro-inflammatory cytokines, and the NAS score. Accordingly, intrahepatic IFN-γ and IL-17 were decreased, but Foxp3, IL-4 and IL-22 were increased after FMT intervention. These data indicate that FMT attenuated HFD-induced steatohepatitis in mice via a beneficial effect on the gut microbiota.

GC13I-0860: An Assessment of Surface Water Detection Methods for the Tahoua Region, Niger

NASA Technical Reports Server (NTRS)

Herndon, Kelsey E.; Muench, Rebekke; Cherrington, Emil; Griffin, Robert

2017-01-01

The recent release of several global surface water datasets derived from remotely sensed data has allowed for unprecedented analysis of the earth's hydrologic processes at a global scale. However, some of these datasets fail to identify important sources of surface water, especially small ponds, in the Sahel, an arid region of Africa that forms a border zone between the Sahara Desert to the north, and the savannah to the south. These ponds may seem insignificant in the context of wider, global-scale hydrologic processes, but smaller sources of water are important for local and regional hydrologic assessments. Particularly, these smaller water bodies are significant sources of hydration and irrigation for nomadic pastoralists and smallholder farmers throughout the Sahel. For this study, several methods of identifying surface water from Landsat 8 OLI, Sentinel 1 SAR, Sentinel 2 MSI, and Planet Dove data were compared to determine the most effective means of delineating these features in the Tahoua Region of Niger. The Automated Water Extraction Index (AWEInsh) had the best performance when validated against very high resolution Digital Globe imagery, with an overall accuracy of 98.6%. This study reiterates the importance of region-specific algorithms and suggests that the AWEInsh method may be the best for delineating surface water in the Sahelian ecozone, likely due to the nature of the exposed geology and lack of dense green vegetation.

Multi-source remotely sensed data fusion for improving land cover classification

NASA Astrophysics Data System (ADS)

Chen, Bin; Huang, Bo; Xu, Bing

2017-02-01

Although many advances have been made in past decades, land cover classification of fine-resolution remotely sensed (RS) data integrating multiple temporal, angular, and spectral features remains limited, and the contribution of different RS features to land cover classification accuracy remains uncertain. We proposed to improve land cover classification accuracy by integrating multi-source RS features through data fusion. We further investigated the effect of different RS features on classification performance. The results of fusing Landsat-8 Operational Land Imager (OLI) data with Moderate Resolution Imaging Spectroradiometer (MODIS), China Environment 1A series (HJ-1A), and Advanced Spaceborne Thermal Emission and Reflection (ASTER) digital elevation model (DEM) data, showed that the fused data integrating temporal, spectral, angular, and topographic features achieved better land cover classification accuracy than the original RS data. Compared with the topographic feature, the temporal and angular features extracted from the fused data played more important roles in classification performance, especially those temporal features containing abundant vegetation growth information, which markedly increased the overall classification accuracy. In addition, the multispectral and hyperspectral fusion successfully discriminated detailed forest types. Our study provides a straightforward strategy for hierarchical land cover classification by making full use of available RS data. All of these methods and findings could be useful for land cover classification at both regional and global scales.

Genome sequence analyses of two isolates from the recent Escherichia coli outbreak in Germany reveal the emergence of a new pathotype: Entero-Aggregative-Haemorrhagic Escherichia coli (EAHEC).

PubMed

Brzuszkiewicz, Elzbieta; Thürmer, Andrea; Schuldes, Jörg; Leimbach, Andreas; Liesegang, Heiko; Meyer, Frauke-Dorothee; Boelter, Jürgen; Petersen, Heiko; Gottschalk, Gerhard; Daniel, Rolf

2011-12-01

The genome sequences of two Escherichia coli O104:H4 strains derived from two different patients of the 2011 German E. coli outbreak were determined. The two analyzed strains were designated E. coli GOS1 and GOS2 (German outbreak strain). Both isolates comprise one chromosome of approximately 5.31 Mbp and two putative plasmids. Comparisons of the 5,217 (GOS1) and 5,224 (GOS2) predicted protein-encoding genes with various E. coli strains, and a multilocus sequence typing analysis revealed that the isolates were most similar to the entero-aggregative E. coli (EAEC) strain 55989. In addition, one of the putative plasmids of the outbreak strain is similar to pAA-type plasmids of EAEC strains, which contain aggregative adhesion fimbrial operons. The second putative plasmid harbors genes for extended-spectrum β-lactamases. This type of plasmid is widely distributed in pathogenic E. coli strains. A significant difference of the E. coli GOS1 and GOS2 genomes to those of EAEC strains is the presence of a prophage encoding the Shiga toxin, which is characteristic for enterohemorrhagic E. coli (EHEC) strains. The unique combination of genomic features of the German outbreak strain, containing characteristics from pathotypes EAEC and EHEC, suggested that it represents a new pathotype Entero-Aggregative-Haemorrhagic E scherichia c oli (EAHEC).

Evaluation of SEBS, SEBAL, and METRIC models in estimation of the evaporation from the freshwater lakes (Case study: Amirkabir dam, Iran)

NASA Astrophysics Data System (ADS)

Zamani Losgedaragh, Saeideh; Rahimzadegan, Majid

2018-06-01

Evapotranspiration (ET) estimation is of great importance due to its key role in water resource management. Surface energy modeling tools such as Surface Energy Balance Algorithm for Land (SEBAL), Mapping Evapotranspiration with Internalized Calibration (METRIC), and the Surface Energy Balance System (SEBS) can estimate the amount of evapotranspiration for every pixel of the satellite images. The main objective of this research is evaporation investigation from the freshwater bodies using SEBAL, METRIC, and SEBS. For this purpose, the Amirkabir dam reservoir and its nearby agricultural lands in a semi-arid climate were selected and studied from 2011 to 2017 as the study area. The implementations of this study were accomplished on 16 satellite images of Landsat TM5 and OLI. Then, SEBAL, METRIC, and SEBS were implemented on the selected images. Moreover, the corresponding pan evaporate measurements on the reservoir bank were considered as the ground truth data. Regarding to the results, SEBAL is not a reliable method to evaluate freshwater evaporation with the coefficient of determination (R2) of 0.36 and the Root Mean Square Error (RMSE) of 5.1 mm. On the other hand, METRIC with RMSE and R2 of 0.57 and 2.02 mm and SEBS with RMSE and R2 of 0.93 and 0.62 demonstrated a relatively good performance.

Google Earth Engine derived areal extents to infer elevation variation of lakes and reservoirs

NASA Astrophysics Data System (ADS)

Nguy-Robertson, Anthony; May, Jack; Dartevelle, Sebastien; Griffin, Sean; Miller, Justin; Tetrault, Robert; Birkett, Charon; Lucero, Eileen; Russo, Tess; Zentner, Matthew

2017-04-01

Monitoring water supplies is important for identifying potential national security issues before they begin. As a means to estimate lake and reservoir storage for sites without reliable water stage data, this study defines correlations between water body levels from hypsometry curves based on in situ gauge station and altimeter data (i.e. TOPEX/Poseidon, Jason series) and sensor areal extents observed in historic multispectral (i.e. MODIS and Landsat TM/ETM+/OLI) imagery. Water levels measured using in situ observations and altimeters, when in situ data were unavailable, were used to estimate the relationship between water elevation and surface area for 18 sites globally. Altimeters were generally more accurate (RMSE: 0.40 - 0.49 m) for estimating in situ lake elevations from Iraq and Afghanistan than the modeled elevation data using multispectral sensor areal extents: Landsat (RMSE: 0.25 - 1.5 m) and MODIS (RMSE 0.53 - 3.0 m). Correlations between altimeter data and Landsat imagery processed with Google Earth Engine confirmed similar relationships exists for a broader range of lakes without reported in situ data across the globe (RMSE: 0.24 - 1.6 m). Thus, while altimetry is still preferred to an areal extent model, lake surface area derived with Google Earth Engine can be used as a reasonable proxy for lake storage, expanding the number of observable lakes beyond the current constellation of altimeters and in situ gauges.

Simulations Meet Experiment to Reveal New Insights into DNA Intrinsic Mechanics

PubMed Central

Ben Imeddourene, Akli; Elbahnsi, Ahmad; Guéroult, Marc; Oguey, Christophe; Foloppe, Nicolas; Hartmann, Brigitte

2015-01-01

The accurate prediction of the structure and dynamics of DNA remains a major challenge in computational biology due to the dearth of precise experimental information on DNA free in solution and limitations in the DNA force-fields underpinning the simulations. A new generation of force-fields has been developed to better represent the sequence-dependent B-DNA intrinsic mechanics, in particular with respect to the BI ↔ BII backbone equilibrium, which is essential to understand the B-DNA properties. Here, the performance of MD simulations with the newly updated force-fields Parmbsc0εζOLI and CHARMM36 was tested against a large ensemble of recent NMR data collected on four DNA dodecamers involved in nucleosome positioning. We find impressive progress towards a coherent, realistic representation of B-DNA in solution, despite residual shortcomings. This improved representation allows new and deeper interpretation of the experimental observables, including regarding the behavior of facing phosphate groups in complementary dinucleotides, and their modulation by the sequence. It also provides the opportunity to extensively revisit and refine the coupling between backbone states and inter base pair parameters, which emerges as a common theme across all the complementary dinucleotides. In sum, the global agreement between simulations and experiment reveals new aspects of intrinsic DNA mechanics, a key component of DNA-protein recognition. PMID:26657165

Detecting the Spatio-temporal Distribution of Soil Salinity and Its Relationship to Crop Growth in a Large-scale Arid Irrigation District Based on Sampling Experiment and Remote Sensing

NASA Astrophysics Data System (ADS)

Ren, D.; Huang, G., Sr.; Xu, X.; Huang, Q., Sr.; Xiong, Y.

2016-12-01

Soil salinity analysis on a regional scale is of great significance for protecting agriculture production and maintaining eco-environmental health in arid and semi-arid irrigated areas. In this study, the Hetao Irrigation District (Hetao) in Inner Mongolia Autonomous Region, with suffering long-term soil salinization problems, was selected as the case study area. Field sampling experiments and investigations related to soil salt contents, crop growth and yields were carried out across the whole area, during April to August in 2015. Soil salinity characteristics in space and time were systematically analyzed for Hetao as well as the corresponding impacts on crops. Remotely sensed map of soil salinity distribution for surface soil was also derived based on the Landsat OLI data with a 30 m resolution. The results elaborated the temporal and spatial dynamics of soil salinity and the relationships with irrigation, groundwater depth and crop water consumption in Hetao. In addition, the strong spatial variability of salinization was clearly presented by the remotely sensed map of soil salinity. Further, the relationship between soil salinity and crop growth was analyzed, and then the impact degrees of soil salinization on cropping pattern, leaf area index, plant height and crop yield were preliminarily revealed. Overall, this study can provide very useful information for salinization control and guide the future agricultural production and soil-water management for the arid irrigation districts analogous to Hetao.

Organic superalkalis with closed-shell structure and aromaticity

NASA Astrophysics Data System (ADS)

Srivastava, Ambrish Kumar

2018-06-01

Benzene (C6H6) and polycyclic hydrocarbons such as naphthalene (C10H8), anthracene (C14H10) and coronene (C24H12) are well known aromatic organic compounds. We study the substitution of Li replacing all H-atoms in these hydrocarbons using density functional method. The vertical ionisation energy of such lithiated species, i.e. C6Li6, C10Li8, C14Li10 and C24Li12 ranges 4.24-4.50 eV, which is lower than the ionisation energy (IE) of Li atom. Thus, these species may behave as superalkalis due to their lower IE than alkali metal. However, these lithiated species possess planar and closed-shell structure, unlike typical superalkalis. Furthermore, all Li-substituted species are aromatic although their degree of aromaticity is reduced as compared to corresponding hydrocarbon analogues. We have further explored the structure of C6Li6 as star-like, unlike its inorganic analogue B3N3Li6, which appears as fan-like structure. We have also demonstrated that the interaction of C6Li6 with a superhalogen (such as BF4) is similar to that of a typical superalkali (such as OLi3). This may further suggest that the proposed lithiated species may form a new class of closed-shell organic superalkalis with aromaticity.

An Assessment of Surface Water Detection Algorithms for the Tahoua Region, Niger

NASA Astrophysics Data System (ADS)

Herndon, K. E.; Muench, R.; Cherrington, E. A.; Griffin, R.

2017-12-01

The recent release of several global surface water datasets derived from remotely sensed data has allowed for unprecedented analysis of the earth's hydrologic processes at a global scale. However, some of these datasets fail to identify important sources of surface water, especially small ponds, in the Sahel, an arid region of Africa that forms a border zone between the Sahara Desert to the north, and the savannah to the south. These ponds may seem insignificant in the context of wider, global-scale hydrologic processes, but smaller sources of water are important for local and regional assessments. Particularly, these smaller water bodies are significant sources of hydration and irrigation for nomadic pastoralists and smallholder farmers throughout the Sahel. For this study, several methods of identifying surface water from Landsat 8 OLI and Sentinel 1 SAR data were compared to determine the most effective means of delineating these features in the Tahoua Region of Niger. The Modified Normalized Difference Water Index (MNDWI) had the best performance when validated against very high resolution World View 3 imagery, with an overall accuracy of 99.48%. This study reiterates the importance of region-specific algorithms and suggests that the MNDWI method may be the best for delineating surface water in the Sahelian ecozone, likely due to the nature of the exposed geology and lack of dense green vegetation.

Coloring the Sea Around the Pribilof Islands

NASA Image and Video Library

2017-12-08

The Operational Land Imager (OLI) on Landsat 8 captured this view of a phytoplankton bloom near Alaska’s Pribilof Islands on Sept. 22, 2014. The Pribilofs are surrounded by nutrient-rich waters in the Bering Sea. The milky green and light blue shading of the water indicates the presence of vast populations of microscopic phytoplankton—mostly coccolithophores, which have calcite scales that appear white in satellite images. Such phytoplankton form the foundation of a tremendously productive habitat for fish and birds. Blooms in the Bering Sea increase significantly in springtime, after winter ice cover retreats and nutrients and freshened water are abundant near the ocean surface. Phytoplankton populations plummet in summertime as the water warms, surface nutrients are depleted by blooms, and the plant-like organisms are depleted by grazing fish, zooplankton, and other marine life. By autumn, storms can stir nutrients back to the surface and cooler waters make better bloom conditions. More information: earthobservatory.nasa.gov/IOTD/view.php?id=85043&eocn... Image Credit: NASA/Landsat 8 NASA image use policy. NASA Goddard Space Flight Center enables NASA’s mission through four scientific endeavors: Earth Science, Heliophysics, Solar System Exploration, and Astrophysics. Goddard plays a leading role in NASA’s accomplishments by contributing compelling scientific knowledge to advance the Agency’s mission. Follow us on Twitter Like us on Facebook Find us on Instagram

Soil salinity mapping and hydrological drought indices assessment in arid environments based on remote sensing techniques

NASA Astrophysics Data System (ADS)

Elhag, Mohamed; Bahrawi, Jarbou A.

2017-03-01

Vegetation indices are mostly described as crop water derivatives. The normalized difference vegetation index (NDVI) is one of the oldest remote sensing applications that is widely used to evaluate crop vigor directly and crop water relationships indirectly. Recently, several NDVI derivatives were exclusively used to assess crop water relationships. Four hydrological drought indices are examined in the current research study. The water supply vegetation index (WSVI), the soil-adjusted vegetation index (SAVI), the moisture stress index (MSI) and the normalized difference infrared index (NDII) are implemented in the current study as an indirect tool to map the effect of different soil salinity levels on crop water stress in arid environments. In arid environments, such as Saudi Arabia, water resources are under pressure, especially groundwater levels. Groundwater wells are rapidly depleted due to the heavy abstraction of the reserved water. Heavy abstractions of groundwater, which exceed crop water requirements in most of the cases, are powered by high evaporation rates in the designated study area because of the long days of extremely hot summer. Landsat 8 OLI data were extensively used in the current research to obtain several vegetation indices in response to soil salinity in Wadi ad-Dawasir. Principal component analyses (PCA) and artificial neural network (ANN) analyses are complementary tools used to understand the regression pattern of the hydrological drought indices in the designated study area.

Effects of an extreme flood on river morphology (case study: Karoon River, Iran)

NASA Astrophysics Data System (ADS)

Yousefi, Saleh; Mirzaee, Somayeh; Keesstra, Saskia; Surian, Nicola; Pourghasemi, Hamid Reza; Zakizadeh, Hamid Reza; Tabibian, Sahar

2018-03-01

An extreme flood occurred on 14 April 2016 in the Karoon River, Iran. The occurred flood discharge was the highest discharge recorded over the last 60 years in the Karoon River. Using the OLI Landsat images taken on 8 April 2016 (before the flood) and 24 April 2016 (after the flood) the geomorphic effects were detected in different land cover types within the 155-km-long study reach. The results show that the flood significantly affected the channel width and the main effect was high mobilization of channel sediments and severe bank erosion in the meandering reaches. According to field surveys, the flood occupied the channel corridor and even the floodplain parts. However, the channel pattern was not significantly altered, although the results show that the average channel width increased from 192 to 256 m. Statistical results indicate a significant change for active channel width and sinuosity index at 99% confidence level for both indexes. The flood-induced morphological changes varied significantly for different land cover types along the Karoon River. Specifically, the channel has widened less in residential areas than in other land cover types because of the occurrence of bank protection structures. However, the value of bank retreat in residential and protected sides of the Karoon River is more than what we expected during the study of extreme flood.

Quantifying the Uncertainty in High Spatial and Temporal Resolution Synthetic Land Surface Reflectance at Pixel Level Using Ground-Based Measurements

NASA Astrophysics Data System (ADS)

Kong, J.; Ryu, Y.

2017-12-01

Algorithms for fusing high temporal frequency and high spatial resolution satellite images are widely used to develop dense time-series land surface observations. While many studies have revealed that the synthesized frequent high spatial resolution images could be successfully applied in vegetation mapping and monitoring, validation and correction of fused images have not been focused than its importance. To evaluate the precision of fused image in pixel level, in-situ reflectance measurements which could account for the pixel-level heterogeneity are necessary. In this study, the synthetic images of land surface reflectance were predicted by the coarse high-frequency images acquired from MODIS and high spatial resolution images from Landsat-8 OLI using the Flexible Spatiotemporal Data Fusion (FSDAF). Ground-based reflectance was measured by JAZ Spectrometer (Ocean Optics, Dunedin, FL, USA) on rice paddy during five main growth stages in Cheorwon-gun, Republic of Korea, where the landscape heterogeneity changes through the growing season. After analyzing the spatial heterogeneity and seasonal variation of land surface reflectance based on the ground measurements, the uncertainties of the fused images were quantified at pixel level. Finally, this relationship was applied to correct the fused reflectance images and build the seasonal time series of rice paddy surface reflectance. This dataset could be significant for rice planting area extraction, phenological stages detection, and variables estimation.

Kinetic Induction of Oat Shoot Pulvinus Invertase mRNA by Gravistimulation and Partial cDNA Cloning by the Polymerase Chain Reaction

NASA Technical Reports Server (NTRS)

Wu, Liu-Lai; Song, Il; Karuppiah, Nadarajah; Kaufman, Peter B.

1993-01-01

An asymmetric (top vs. bottom halves of pulvini) induction of invertase mRNA by gravistimulation was analyzed in oat shoot pulvini. Total RNA and poly(A)(+) RNA, isolated from oat pulvini, and two oli-gonucleotide primers, corresponding to two conserved amino acid sequences (NDPNG and WECPD) found in invertase from other species, were used for the polymerase chain reaction (PCR). A partial length cDNA (550 bp) was obtained and characterized. A 62% nucleotide sequence homology and 58% deduced amino acid sequence homology, as compared to beta-fructosidase of carrot cell wall, was found. Northern blot analysis showed that there was an obviously transient induction of invertase mRNA by gravistimulation in the oat pulvinus system. The mRNA was rapidly induced to a maximum level at 1 hour after gravistimulation treatment and gradually decreased afterwards. The mRNA level in the bottom half of the oat pulvinus was significantly higher than that in the top half of the pulvinus tissue. The kinetic induction of invertase mRNA was consistent with the transient accumulation of invertase activity during the graviresponse of the pulvinus. This indicates that the expression of the invertase gene(s) could be regulated by gravistimulation at the transcriptional level. Southern blot analysis showed that there were two to three genomic DNA fragments which hybridized with the partial-length invertase cDNA.

Application of pH-sensitive magnetic nanoparticles microgel as a sorbent for the preconcentration of phenoxy acid herbicides in water samples.

PubMed

Tabani, Hadi; Khodaei, Kamal; Bide, Yasamin; Zare, Farzaneh Dorabadi; Mirzaei, Saeed; Fakhari, Ali Reza

2015-08-14

Introducing new sorbents is an interesting and debatable issue in the field of sample preparation. In this study, for the first time, a pH-sensitive magnetic nanoparticles microgel, Fe3O4-SiO2-oly(4-vinylpyridine), was introduced as a new sorbent. The operating mechanism of this sorbent is based on changing the pH value of the sample and consequently the structure of this pH-sensitive microgel is changed. So that, at pH 6.0 the microgel was ready to accept and load the analytes (partial swelling), and when the pH was increased to 8.0, the microgel was closed and analytes were trapped inside the sorbent (deswelling). At pH 2.0 the microgel was opened and the analytes were released from the microgel (swelling). As the adsorption and desorption mechanism is based on changing the pH and only aqueous medium is used as the effluent solvent, this method is introduced as a green extraction method. The use of this microgel resulted in excellent figures of merit. The limits of quantitation and detection for herbicides were obtained within the range of 10-30 and 3-10 ng mL(-1), respectively. Finally, the proposed method was successfully applied to determine the concentration of phenoxy acid herbicides as hazardous materials in water samples. Copyright © 2015 Elsevier B.V. All rights reserved.

Insoluble Coatings for Stirling Engine Heat Pipe Condenser Surfaces

NASA Technical Reports Server (NTRS)

Dussinger, Peter M.; Lindemuth, James E.

1997-01-01

The principal objective of this Phase 2 SBIR program was to develop and demonstrate a practically insoluble coating for nickel-based superalloys for Stirling engine heat pipe applications. Specific technical objectives of the program were: (1) Determine the solubility corrosion rates for Nickel 200, Inconel 718, and Udimet 72OLI in a simulated Stirling engine heat pipe environment, (2) Develop coating processes and techniques for capillary groove and screen wick structures, (3) Evaluate the durability and solubility corrosion rates for capillary groove and screen wick structures coated with an insoluble coating in cylindrical heat pipes operating under Stirling engine conditions, and (4) Design and fabricate a coated full-scale, partial segment of the current Stirling engine heat pipe for the Stirling Space Power Convertor program. The work effort successfully demonstrated a two-step nickel aluminide coating process for groove wick structures and interior wall surfaces in contact with liquid metals; demonstrated a one-step nickel aluminide coating process for nickel screen wick structures; and developed and demonstrated a two-step aluminum-to-nickel aluminide coating process for nickel screen wick structures. In addition, the full-scale, partial segment was fabricated and the interior surfaces and wick structures were coated. The heat pipe was charged with sodium, processed, and scheduled to be life tested for up to ten years as a Phase 3 effort.

Image Mining in Remote Sensing for Coastal Wetlands Mapping: from Pixel Based to Object Based Approach

NASA Astrophysics Data System (ADS)

Farda, N. M.; Danoedoro, P.; Hartono; Harjoko, A.

2016-11-01

The availably of remote sensing image data is numerous now, and with a large amount of data it makes “knowledge gap” in extraction of selected information, especially coastal wetlands. Coastal wetlands provide ecosystem services essential to people and the environment. The aim of this research is to extract coastal wetlands information from satellite data using pixel based and object based image mining approach. Landsat MSS, Landsat 5 TM, Landsat 7 ETM+, and Landsat 8 OLI images located in Segara Anakan lagoon are selected to represent data at various multi temporal images. The input for image mining are visible and near infrared bands, PCA band, invers PCA bands, mean shift segmentation bands, bare soil index, vegetation index, wetness index, elevation from SRTM and ASTER GDEM, and GLCM (Harralick) or variability texture. There is three methods were applied to extract coastal wetlands using image mining: pixel based - Decision Tree C4.5, pixel based - Back Propagation Neural Network, and object based - Mean Shift segmentation and Decision Tree C4.5. The results show that remote sensing image mining can be used to map coastal wetlands ecosystem. Decision Tree C4.5 can be mapped with highest accuracy (0.75 overall kappa). The availability of remote sensing image mining for mapping coastal wetlands is very important to provide better understanding about their spatiotemporal coastal wetlands dynamics distribution.

Selection of vegetation indices for mapping the sugarcane condition around the oil and gas field of North West Java Basin, Indonesia

NASA Astrophysics Data System (ADS)

Muji Susantoro, Tri; Wikantika, Ketut; Saepuloh, Asep; Handoyo Harsolumakso, Agus

2018-05-01

Selection of vegetation indices in plant mapping is needed to provide the best information of plant conditions. The methods used in this research are the standard deviation and the linear regression. This research tried to determine the vegetation indices used for mapping the sugarcane conditions around oil and gas fields. The data used in this study is Landsat 8 OLI/TIRS. The standard deviation analysis on the 23 vegetation indices with 27 samples has resulted in the six highest standard deviations of vegetation indices, termed as GRVI, SR, NLI, SIPI, GEMI and LAI. The standard deviation values are 0.47; 0.43; 0.30; 0.17; 0.16 and 0.13. Regression correlation analysis on the 23 vegetation indices with 280 samples has resulted in the six vegetation indices, termed as NDVI, ENDVI, GDVI, VARI, LAI and SIPI. This was performed based on regression correlation with the lowest value R2 than 0,8. The combined analysis of the standard deviation and the regression correlation has obtained the five vegetation indices, termed as NDVI, ENDVI, GDVI, LAI and SIPI. The results of the analysis of both methods show that a combination of two methods needs to be done to produce a good analysis of sugarcane conditions. It has been clarified through field surveys and showed good results for the prediction of microseepages.

Subtype Coastline Determination in Urban Coast Based on Multiscale Features: a Case Study in Tianjin, China

NASA Astrophysics Data System (ADS)

Song, Y.; Ai, Y.; Zhu, H.

2018-04-01

In urban coast, coastline is a direct factor to reflect human activities. It is of crucial importance to the understanding of urban growth, resource development and ecological environment. Due to complexity and uncertainty in this type of coast, it is difficult to detect accurate coastline position and determine the subtypes of the coastline. In this paper, we present a multiscale feature-based subtype coastline determination (MFBSCD) method to extract coastline and determine the subtypes. In this method, uncertainty-considering coastline detection (UCCD) method is proposed to separate water and land for more accurate coastline position. The MFBSCD method can well integrate scale-invariant features of coastline in geometry and spatial structure to determine coastline in subtype scale, and can make subtypes verify with each other during processing to ensure the accuracy of final results. It was applied to Landsat Thematic Mapper (TM) and Operational Land Imager (OLI) images of Tianjin, China, and the accuracy of the extracted coastlines was assessed with the manually delineated coastline. The mean ME (misclassification error) and mean LM (Line Matching) are 0.0012 and 24.54 m respectively. The method provides an inexpensive and automated means of coastline mapping with subtype scale in coastal city sectors with intense human interference, which can be significant for coast resource management and evaluation of urban development.

Characterization and Spectral Monitoring of Coffee Lands in Brazil

NASA Astrophysics Data System (ADS)

Alves, H. M. R.; Volpato, M. M. L.; Vieira, T. G. C.; Maciel, D. A.; Gonçalves, T. G.; Dantas, M. F.

2016-06-01

In Brazil, coffee production has great economic and social importance. Despite this fact, there is still a shortage of information regarding its spatial distribution, crop management and environment. The aim of this study was to carry out spectral monitoring of coffee lands and to characterize their environments using geotechnologies. Coffee fields with contiguous areas over 0.01 km2 within a 488.5 km2 region in the south of Minas Gerais state were selected for the study. Spectral data from the sensors OLI/Landsat 8 and the Shuttle Radar Topography Mission from 2014 to 2015 were obtained, as well as information on production areas, surface temperature, vegetation indexes, altitude and slope, were gathered and analyzed. The results indicate that there is great variation in the NDVI and NDWI values, with means ranging from 0.21 to 0.91 (NDVI) and 0.108 to 0.543 (NDWI). The altitude ranged from 803 to 1150 m, and the surface temperature from 20.9°C to 27.6°C. The altitude and the surface temperature distribution patterns were correlated with the vegetation indexes. The slope classes were very homogeneous, predominantly with declivities between 8 to 20 %, characterized as wavy relief. This study made possible the characterization and monitoring of coffee lands and its results may be instrumental in decision-making processes related to coffee management.

Assessing heat fluxes and water quality trends in subalpine lakes from EO

NASA Astrophysics Data System (ADS)

Cazzaniga, Ilaria; Giardino, Claudia; Bresciani, Mariano; Elli, Chiara; Valerio, Giulia; Pilotti, Marco

2017-04-01

Lakes play a fundamental role in providing ecosystem services such as water supplying, hydrological regulation, climate change mitigation, touristic recreation (Schallenberg et al., 2013). Preserving and improving of quality of lakes waters, which is a function of either both natural and human influences, is therefore an important action to be considered. Remote Sensing techniques are spreading as useful instrument for lakes, by integrating classical in situ limnological measurements to frequent and synoptic monitoring capabilities. Within this study, Earth Observation data are exploited for understanding the temporal changes of water quality parameters over a decade, as well as for measuring the surface energy fluxes in recent years in deep clear lakes in the European subalpine ecoregion. According to Pareth et al. (2016), subalpine lakes are showing a clear response to climate change with an increase of 0.017 °C /year of lake surface temperature, whilst the human activities contribute to produce a large impact (agriculture, recreation, industry, fishing and drinking) on these lakes. The investigation is focused on Lake Iseo, which has shown a significant deterioration of water quality conditions since the seventies, and on Lake Garda, the largest Italian lake where EO data have been widely used for many purposes and applications (Giardino et al., 2014). Available ENVISAT-MERIS (2002-2012) and Landsat-8-OLI (2013-on going) imagery has been exploited to produce chlorophyll-a (chl-a) concentration maps, while Landsat-8-TIRS imagery has been used for estimating lake surface temperatures. MERIS images were processed through a neural network (namely the C2R processor, Doerffer et al., 2007), to correct the atmospheric effects and to retrieve water constituents concentration in optically complex deep waters. With regard to L8's images, some atmospheric correctors (e.g. ACOLITE and 6SV) were tested and validated to indentify, for each of the two lakes, the more accurate

Application and Comparison of the MODIS-Derived Enhanced Vegetation Index to VIIRS, Landsat 5 TM and Landsat 8 OLI Platforms: A Case Study in the Arid Colorado River Delta, Mexico.

PubMed

Jarchow, Christopher J; Didan, Kamel; Barreto-Muñoz, Armando; Nagler, Pamela L; Glenn, Edward P

2018-05-13

The Enhanced Vegetation Index (EVI) is a key Earth science parameter used to assess vegetation, originally developed and calibrated for the Moderate Resolution Imaging Spectroradiometer (MODIS) aboard the Terra and Aqua satellites. With the impending decommissioning of the MODIS sensors by the year 2020/2022, alternative platforms will need to be used to estimate EVI. We compared Landsat 5 (2000⁻2011), 8 (2013⁻2016) and the Visible Infrared Imaging Radiometer Suite (VIIRS; 2013⁻2016) to MODIS EVI (2000⁻2016) over a 420,083-ha area of the arid lower Colorado River Delta in Mexico. Over large areas with mixed land cover or agricultural fields, we found high correspondence between Landsat and MODIS EVI (R² = 0.93 for the entire area studied and 0.97 for agricultural fields), but the relationship was weak over bare soil (R² = 0.27) and riparian vegetation (R² = 0.48). The correlation between MODIS and Landsat EVI was higher over large, homogeneous areas and was generally lower in narrow riparian areas. VIIRS and MODIS EVI were highly similar (R² = 0.99 for the entire area studied) and did not show the same decrease in performance in smaller, narrower regions as Landsat. Landsat and VIIRS provide EVI estimates of similar quality and characteristics to MODIS, but scale, seasonality and land cover type(s) should be considered before implementing Landsat EVI in a particular area.

Application and Comparison of the MODIS-Derived Enhanced Vegetation Index to VIIRS, Landsat 5 TM and Landsat 8 OLI Platforms: A Case Study in the Arid Colorado River Delta, Mexico

PubMed Central

Jarchow, Christopher J.; Didan, Kamel; Barreto-Muñoz, Armando; Glenn, Edward P.

2018-01-01

The Enhanced Vegetation Index (EVI) is a key Earth science parameter used to assess vegetation, originally developed and calibrated for the Moderate Resolution Imaging Spectroradiometer (MODIS) aboard the Terra and Aqua satellites. With the impending decommissioning of the MODIS sensors by the year 2020/2022, alternative platforms will need to be used to estimate EVI. We compared Landsat 5 (2000–2011), 8 (2013–2016) and the Visible Infrared Imaging Radiometer Suite (VIIRS; 2013–2016) to MODIS EVI (2000–2016) over a 420,083-ha area of the arid lower Colorado River Delta in Mexico. Over large areas with mixed land cover or agricultural fields, we found high correspondence between Landsat and MODIS EVI (R2 = 0.93 for the entire area studied and 0.97 for agricultural fields), but the relationship was weak over bare soil (R2 = 0.27) and riparian vegetation (R2 = 0.48). The correlation between MODIS and Landsat EVI was higher over large, homogeneous areas and was generally lower in narrow riparian areas. VIIRS and MODIS EVI were highly similar (R2 = 0.99 for the entire area studied) and did not show the same decrease in performance in smaller, narrower regions as Landsat. Landsat and VIIRS provide EVI estimates of similar quality and characteristics to MODIS, but scale, seasonality and land cover type(s) should be considered before implementing Landsat EVI in a particular area. PMID:29757265

PI2GIS: processing image to geographical information systems, a learning tool for QGIS

NASA Astrophysics Data System (ADS)

Correia, R.; Teodoro, A.; Duarte, L.

2017-10-01

To perform an accurate interpretation of remote sensing images, it is necessary to extract information using different image processing techniques. Nowadays, it became usual to use image processing plugins to add new capabilities/functionalities integrated in Geographical Information System (GIS) software. The aim of this work was to develop an open source application to automatically process and classify remote sensing images from a set of satellite input data. The application was integrated in a GIS software (QGIS), automating several image processing steps. The use of QGIS for this purpose is justified since it is easy and quick to develop new plugins, using Python language. This plugin is inspired in the Semi-Automatic Classification Plugin (SCP) developed by Luca Congedo. SCP allows the supervised classification of remote sensing images, the calculation of vegetation indices such as NDVI (Normalized Difference Vegetation Index) and EVI (Enhanced Vegetation Index) and other image processing operations. When analysing SCP, it was realized that a set of operations, that are very useful in teaching classes of remote sensing and image processing tasks, were lacking, such as the visualization of histograms, the application of filters, different image corrections, unsupervised classification and several environmental indices computation. The new set of operations included in the PI2GIS plugin can be divided into three groups: pre-processing, processing, and classification procedures. The application was tested consider an image from Landsat 8 OLI from a North area of Portugal.

Spatial complexities in aboveground carbon stocks of a semi-arid mangrove community: A remote sensing height-biomass-carbon approach

NASA Astrophysics Data System (ADS)

Hickey, S. M.; Callow, N. J.; Phinn, S.; Lovelock, C. E.; Duarte, C. M.

2018-01-01

Mangroves are integral to ecosystem services provided by the coastal zone, in particular carbon (C) sequestration and storage. Allometric relationships linking mangrove height to estimated biomass and C stocks have been developed from field sampling, while various forms of remote sensing has been used to map vegetation height and biomass. Here we combine both these approaches to investigate spatial patterns in living biomass of mangrove forests in a small area of mangrove in north-west Australia. This study used LiDAR data and Landsat 8 OLI (Operational Land Imager) with allometric equations to derive mangrove height, biomass, and C stock estimates. We estimated the study site, Mangrove Bay, a semi-arid site in north-western Australia, contained 70 Mg ha-1 biomass and 45 Mg C ha-1 organic C, with total stocks of 2417 Mg biomass and 778 Mg organic C. Using spatial statistics to identify the scale of clustering of mangrove pixels, we found that living biomass and C stock declined with increasing distance from hydrological features (creek entrance: 0-150 m; y = -0.00041x + 0.9613, R2 = 0.96; 150-770 m; y = -0.0008x + 1.6808, R2 = 0.73; lagoon: y = -0.0041x + 3.7943, R2 = 0.78). Our results illustrate a set pattern of living C distribution within the mangrove forest, and then highlight the role hydrologic features play in determining C stock distribution in the arid zone.

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.

Study on the decomposition mechanism of alkyl carbonate on lithium metal by pyrolysis-gas chromatography-mass spectroscopy

NASA Astrophysics Data System (ADS)

Mogi, Ryo; Inaba, Minoru; Iriyama, Yasutoshi; Abe, Takeshi; Ogumi, Zempachi

The surface films formed on deposited lithium in electrolyte solutions based on ethylene carbonate (EC), diethyl carbonate (DEC), and dimethyl carbonate (DMC) were analyzed by pyrolysis-gas chromatography-mass spectroscopy (Py-GC-MS). In 1 M LiClO 4/EC, the main component of the surface film was easily hydrolyzed to give ethylene glycol after exposure to air, and hence was considered to have a chemical structure of ROCH 2CH 2OR', of which OR and OR' are OLi or OCO 2Li. Ethylene oxide, acetaldehyde, and 1,4-dioxane were detected in decomposition products, and they were considered to have been formed by pyrolysis of ROCH 2CH 2OR' in the pyrolyzer. The presence of ethanol in decomposition products confirmed that ring cleavage at the CH 2O bonds of EC occurs by one electron reduction. In addition, the presence of methanol implied the cleavage of the CC bond of EC upon reduction. From the surface films formed in 1 M LiClO 4/DEC and /DMC, ethanol and methanol, respectively, were detected, which suggested that corresponding lithium alkoxides and/or lithium alkyl carbonates were the main components. In 1 M LiClO 4/EC+DEC (1:1), EC dominantly decomposed to form the surface film. The surface film formed in 1 M LiPF 6/EC+DEC (1:1) contained a much smaller amount of organic compounds.

Change Detection Analysis of Costal Habitat Using Remote Sensing Technologies in the Western Arabian Gulf (Saudi Arabian Coast) over a Thirty-Year Period.

NASA Astrophysics Data System (ADS)

El-Askary, H. M.; Idris, N.; Johnson, S. H.; Qurban, M. A. B.

2014-12-01

Many factors can severely affect the growth and abundance of the marine ecosystems. For example, due to anthropogenic and natural forces, benthic habitats including but not limited to mangroves, sea grass, salt marshes, macro algae, and coral reefs have been experiencing high levels of declination. Furthermore, aerosols and their propellants are suspected contributors to marine habitat degradation. Although several studies reveal that the Arabian Gulf habitats have suffered deleterious impacts after the Gulf War and the following six month off-shore oil spill, limited research exists to track the changes in benthic habitats over the past three decades using remote sensing. Document changes in costal habitats over the past thirty years were better observed with the use of multispectral remote sensors such as Landsat-5, Landsat-7, and Landsat8 (OLI). Change detection analysis was performed on the three Landsat images (Landsat-5 for the 1987 image, Landsat-7 for the 2000, and Landsat-8 for the 2013 image). The images were then modified, masked off from open water and land. An unsupervised classification was performed which cluster similar classes together. The supervised classification displayed the seven following classes: coral reefs, macro algae, sea grass, salt marshes, mangroves, water, and land. Compared to 1987 image to 2000 scene, there was a noticeable increase in the extensiveness of salt marsh and macro algae habitats. However, a significant decrease in salt marsh habitats were apparent in the 2013 scene.

Radiometric Cross-calibration of KOMPSAT-3A with Landsat-8

NASA Astrophysics Data System (ADS)

Shin, D. Y.; Ahn, H. Y.; Lee, S. G.; Choi, C. U.; Kim, J. S.

2016-06-01

In this study, Cross calibration was conducted at the Libya 4 PICS site on 2015 using Landsat-8 and KOMPSAT-3A. Ideally a cross calibration should be calculated for each individual scene pair because on any given date the TOA spectral profile is influenced by sun and satellite view geometry and the atmospheric conditions. However, using the near-simultaneous images minimizes this effect because the sensors are viewing the same atmosphere. For the cross calibration, the calibration coefficient was calculated by comparing the at sensor spectral radiance for the same location calculated using the Landsat-8 calibration parameters in metadata and the DN of KOMPSAT-3A for the regions of interest (ROI). Cross calibration can be conducted because the satellite sensors used for overpass have a similar bandwidth. However, not all satellites have the same color filter transmittance and sensor reactivity, even though the purpose is to observe the visible bands. Therefore, the differences in the RSR should be corrected. For the cross-calibration, a calibration coefficient was calculated using the TOA radiance and KOMPSAT-3 DN of the Landsat-8 OLI overpassed at the Libya 4 Site, As a result, the accuracy of the calibration coefficient at the site was assumed to be ± 1.0%. In terms of the results, the radiometric calibration coefficients suggested here are thought to be useful for maintaining the optical quality of the KOMPSAT-3A.

Toward global crop type mapping using a hybrid machine learning approach and multi-sensor imagery

NASA Astrophysics Data System (ADS)

Wang, S.; Le Bras, S.; Azzari, G.; Lobell, D. B.

2017-12-01

Current global scale datasets on agricultural land use do not have sufficient spatial or temporal resolution to meet the needs of many applications. The recent rapid increase in public availability of fine- to moderate-resolution satellite imagery from Landsat OLI and Copernicus Sentinel-2 provides a unique opportunity to improve agricultural land use datasets. This project leverages these new satellite data streams, existing census data, and a novel training approach to develop global, annual maps that indicate the presence of (i) cropland and (ii) specific crops at a 20m resolution. Our machine learning methodology consists of two steps. The first is a supervised classifier trained with explicitly labelled data to distinguish between crop and non-crop pixels, creating a binary mask. For ground truth, we use labels collected by previous mapping efforts (e.g. IIASA's crowdsourced data (Fritz et al. 2015) and AFSIS's geosurvey data) in combination with new data collected manually. The crop pixels output by the binary mask are input to the second step: a semi-supervised clustering algorithm to resolve different crop types and generate a crop type map. We do not use field-level information on crop type to train the algorithm, making this approach scalable spatially and temporally. We instead incorporate size constraints on clusters based on aggregated agricultural land use statistics and other, more generalizable domain knowledge. We employ field-level data from the U.S., Southern Europe, and Eastern Africa to validate crop-to-cluster assignments.

Quantum-Well Infrared Photodetector (QWIP) Focal Plane Assembly

NASA Technical Reports Server (NTRS)

Jhabvala, Murzy; Jhabvala, Christine A.; Ewin, Audrey J.; Hess, Larry A.; Hartmann, Thomas M.; La, Anh T.

2012-01-01

A paper describes the Thermal Infrared Sensor (TIRS), a QWIP-based instrument intended to supplement the Operational Land Imager (OLI) for the Landsat Data Continuity Mission (LDCM). The TIRS instrument is a far-infrared imager operating in the pushbroom mode with two IR channels: 10.8 and 12 microns. The focal plane will contain three 640x512 QWIP arrays mounted on a silicon substrate. The silicon substrate is a custom-fabricated carrier board with a single layer of aluminum interconnects. The general fabrication process starts with a 4-in. (approx.10-cm) diameter silicon wafer. The wafer is oxidized, a single substrate contact is etched, and aluminum is deposited, patterned, and alloyed. This technology development is aimed at incorporating three large-format infrared detecting arrays based on GaAs QWIP technology onto a common focal plane with precision alignment of all three arrays. This focal plane must survive the rigors of flight qualification and operate at a temperature of 43 K (-230 C) for five years while orbiting the Earth. The challenges presented include ensuring thermal compatibility among all the components, designing and building a compact, somewhat modular system and ensuring alignment to very tight levels. The multi-array focal plane integrated onto a single silicon substrate is a new application of both QWIP array development and silicon wafer scale integration. The Invar-based assembly has been tested to ensure thermal reliability.

Analyzing spatial and temporal trends in Aboveground Biomass within the Acadian New England Forests using the complete Landsat Archive

NASA Astrophysics Data System (ADS)

Kilbride, J. B.; Fraver, S.; Ayrey, E.; Weiskittel, A.; Braaten, J.; Hughes, J. M.; Hayes, D. J.

2017-12-01

Forests within the New England states and Canadian Maritime provinces, here described as the Acadian New England (ANE) forests, have undergone substantial disturbances due to insect, fire, and anthropogenic factors. Through repeated satellite observations captures by USGS's Landsat program, 45 years of disturbance information can be incorporated into modeling efforts to better understand the spatial and temporal trends in forest above ground biomass (AGB). Using Google's Earth Engine, annual mosaics were developed for the ANE study area and then disturbance and recovery metrics were developed using the temporal segmentation algorithm VeRDET. Normalization procedures were developed to incorporate the Landsat Multispectral Scanner (MSS, 1972 - 1985) data alongside the modern era of Landsat Thematic Mapper (TM, 1984-2013), Enhanced Thematic Mapper plus (ETM+, 1999 - present), and Operational Land Imager (OLI, 2013- present) data products. This has enabled the creation of a dataset with an unprecedented spatial and temporal view of forest landscape change. Model training was performed using was the Forest Inventory Analysis (FIA) and New Brunswick Permanent Sample Plot data datasets. Modeling was performed using parametric techniques such as mixed effects models and non-parametric techniques such as k-NN imputation and generalized boosted regression. We compare the biomass estimate and model accuracy to other inventory and modeling studies produced within this study area. The spatial and temporal patterns of stock changes are analyzed against resource policy, land ownership changes, and forest management.

Thin Ice Area Extraction in the Seasonal Sea Ice Zones of the Northern Hemisphere Using Modis Data

NASA Astrophysics Data System (ADS)

Hayashi, K.; Naoki, K.; Cho, K.

2018-04-01

Sea ice has an important role of reflecting the solar radiation back into space. However, once the sea ice area melts, the area starts to absorb the solar radiation which accelerates the global warming. This means that the trend of global warming is likely to be enhanced in sea ice areas. In this study, the authors have developed a method to extract thin ice area using reflectance data of MODIS onboard Terra and Aqua satellites of NASA. The reflectance of thin sea ice in the visible region is rather low. Moreover, since the surface of thin sea ice is likely to be wet, the reflectance of thin sea ice in the near infrared region is much lower than that of visible region. Considering these characteristics, the authors have developed a method to extract thin sea ice areas by using the reflectance data of MODIS (NASA MYD09 product, 2017) derived from MODIS L1B. By using the scatter plots of the reflectance of Band 1 (620 nm-670 nm) and Band 2 (841 nm-876 nm)) of MODIS, equations for extracting thin ice area were derived. By using those equations, most of the thin ice areas which could be recognized from MODIS images were well extracted in the seasonal sea ice zones in the Northern Hemisphere, namely the Sea of Okhotsk, the Bering Sea and the Gulf of Saint Lawrence. For some limited areas, Landsat-8 OLI images were also used for validation.

Characterization of Truncated Tumor-Associated NADH Oxidase (ttNOX)

NASA Technical Reports Server (NTRS)

Karr, Laurel J.; Malone, Christine C.; Burk, Melissa; Moore, Blake P.; Achari, Aniruddha; Curreri, Peter A. (Technical Monitor)

2002-01-01

Bacterial, plant and animal cells possess novel surface proteins that exhibit both NADH oxidation (NOX) or hydroquinone and protein disulfide-thiol interchange. These enzymatic activities alternate to yield oscillating patterns wjth period lengths of approximately 24 minutes. The catalytic period of NOX proteins are temperature compensated and gravity responsive. We report the cloning, expression and characterization of truncated tumor-associated NADH oxidase (ttNOX), in which the membrane spanning region has been deleted. The cDNA (originated from HeLa cells) was cloned into pET-34b and pET-14b (Novagen) vectors for E. coli expression. Optimized expression and purification protocols yielded greater than 300mg per liter of culture with greater than 95% purity. Circular dichroism data was collected from a 2.7mg/ml solution in a 0.1mm cuvette with variable scanning using an Olis RSM CD spectrophotometer. The ellipticity values were scanned from 190 to 260nm. The spectra recorded have characteristics for alpha proteins with band maxima at 216nm and a possible shoulder at 212nm at 12OC and 250 C. Protein crystal screens are in progress and, to date, only small crystals have been observed. The regular periodic oscillatory change in the ttNOX protein is indicative of a possible time-keeping functional role. A single protein possessing alternating catalytic activities, with a potential biological clock function, is unprecedented and structural determination is paramount to understanding this role.

Multi-temporal analysis of land surface temperature in highly urbanized districts

NASA Astrophysics Data System (ADS)

Kaya, S.; Celik, B.; Sertel, E.; Bayram, B.; Seker, D. Z.

2017-12-01

Istanbul is one of the largest cities around the world with population over 15 million and it has 39 districts. Due to high immigration rate after the 1980s, parallel to the urbanization rapid population increase has occurred in some of these districts. Thus, a significant increase in land surface temperature were monitored and this subject became one of the most popular subject of different researches. Natural landscapes transformed into residential areas with impervious surfaces that causes rise in land surface temperatures which is one of the component of urban heat islands. This study focuses on determining the land use/land cover changes and land surface temperature in highly urbanized districts for last 32 years and examining the relationship between these two parameters using multi-temporal optical and thermal remotely sensed data. In this study, Landsat5 Thematic Mapper and Landsat8 OLI/TIR imagery with acquisition dates June 1984 and June 2016 were used. In order to assess the land use/cover change between 1984 and 2016, Vegetation Impervious Surface-soil (V-I-S) model is used. Each end-member spectra are extracted from ASTER spectral library. Additionally, V-I-S model, NDVI, NDBI and NDBaI indices have been derived for further investigation of land cover changes. The results of the study, presented that in the last 32 years, the amount of impervious surfaces substantially increased along with land surface temperatures.

U.S. Geological Survey distribution of European Space Agency's Sentinel-2 data

USGS Publications Warehouse

Pieschke, Renee L.

2017-03-31

A partnership established between the European Space Agency (ESA) and the U.S. Geological Survey (USGS) allows for USGS storage and redistribution of images acquired by the MultiSpectral Instrument (MSI) on the European Union's Sentinel-2 satellite mission. The MSI data are acquired from a pair of satellites, Sentinel-2A and Sentinel-2B, which are part of a larger set of ESA missions focusing on different aspects of Earth observation. The primary purpose of the Sentinel-2 series is to collect multispectral imagery over the Earth’s land surfaces, large islands, and inland and coastal waters. Sentinel-2A was launched in 2015 and Sentinel-2B launched in 2017.The collaborative effort between ESA and USGS provides for public access and redistribution of global acquisitions of Sentinel-2 data at no cost, which allows users to download the MSI imagery from USGS access systems such as Earth- Explorer, in addition to the ESA Sentinels Scientific Data Hub. The MSI sensor acquires 13 spectral bands that are highly complementary to data acquired by the USGS Landsat 8 Operational Land Imager (OLI) and Landsat 7 Enhanced Thematic Mapper Plus (ETM+). The product options from USGS include a Full-Resolution Browse (FRB) image product generated by USGS, along with a 100-kilometer (km) by 100-km tile-based Level-1C top-of-atmosphere (TOA) reflectance product that is very similar (but not identical) to the currently (2017) distributed ESA Level 1C product.

Comparison modeling for alpine vegetation distribution in an arid area.

PubMed

Zhou, Jihua; Lai, Liming; Guan, Tianyu; Cai, Wetao; Gao, Nannan; Zhang, Xiaolong; Yang, Dawen; Cong, Zhentao; Zheng, Yuanrun

2016-07-01

Mapping and modeling vegetation distribution are fundamental topics in vegetation ecology. With the rise of powerful new statistical techniques and GIS tools, the development of predictive vegetation distribution models has increased rapidly. However, modeling alpine vegetation with high accuracy in arid areas is still a challenge because of the complexity and heterogeneity of the environment. Here, we used a set of 70 variables from ASTER GDEM, WorldClim, and Landsat-8 OLI (land surface albedo and spectral vegetation indices) data with decision tree (DT), maximum likelihood classification (MLC), and random forest (RF) models to discriminate the eight vegetation groups and 19 vegetation formations in the upper reaches of the Heihe River Basin in the Qilian Mountains, northwest China. The combination of variables clearly discriminated vegetation groups but failed to discriminate vegetation formations. Different variable combinations performed differently in each type of model, but the most consistently important parameter in alpine vegetation modeling was elevation. The best RF model was more accurate for vegetation modeling compared with the DT and MLC models for this alpine region, with an overall accuracy of 75 % and a kappa coefficient of 0.64 verified against field point data and an overall accuracy of 65 % and a kappa of 0.52 verified against vegetation map data. The accuracy of regional vegetation modeling differed depending on the variable combinations and models, resulting in different classifications for specific vegetation groups.

Automated Mapping of Flood Events in the Mississippi River Basin Utilizing NASA Earth Observations

NASA Technical Reports Server (NTRS)

Bartkovich, Mercedes; Baldwin-Zook, Helen Blue; Cruz, Dashiell; McVey, Nicholas; Ploetz, Chris; Callaway, Olivia

2017-01-01

The Mississippi River Basin is the fourth largest drainage basin in the world, and is susceptible to multi-level flood events caused by heavy precipitation, snow melt, and changes in water table levels. Conducting flood analysis during periods of disaster is a challenging endeavor for NASA's Short-term Prediction Research and Transition Center (SPoRT), Federal Emergency Management Agency (FEMA), and the U.S. Geological Survey's Hazards Data Distribution Systems (USGS HDDS) due to heavily-involved research and lack of manpower. During this project, an automated script was generated that performs high-level flood analysis to relieve the workload for end-users. The script incorporated Landsat 8 Operational Land Imager (OLI) tiles and utilized computer-learning techniques to generate accurate water extent maps. The script referenced the Moderate Resolution Imaging Spectroradiometer (MODIS) land-water mask to isolate areas of flood induced waters. These areas were overlaid onto the National Land Cover Database's (NLCD) land cover data, the Oak Ridge National Laboratory's LandScan data, and Homeland Infrastructure Foundation-Level Data (HIFLD) to determine the classification of areas impacted and the population density affected by flooding. The automated algorithm was initially tested on the September 2016 flood event that occurred in Upper Mississippi River Basin, and was then further tested on multiple flood events within the Mississippi River Basin. This script allows end users to create their own flood probability and impact maps for disaster mitigation and recovery efforts.

Remote sensing estimation of terrestrially derived colored dissolved organic matterinput to the Arctic Ocean

NASA Astrophysics Data System (ADS)

Li, J.; Yu, Q.; Tian, Y. Q.

2017-12-01

The DOC flux from land to the Arctic Ocean has remarkable implication on the carbon cycle, biogeochemical & ecological processes in the Arctic. This lateral carbon flux is required to be monitored with high spatial & temporal resolution. However, the current studies in the Arctic regions were obstructed by the factors of the low spatial coverages. The remote sensing could provide an alternative bio-optical approach to field sampling for DOC dynamics monitoring through the observation of the colored dissolved organic matter (CDOM). The DOC and CDOM were found highly correlated based on the analysis of the field sampling data from the Arctic-GRO. These provide the solid foundation of the remote sensing observation. In this study, six major Arctic Rivers (Yukon, Kolyma, Lena, Mackenzie, Ob', Yenisey) were selected to derive the CDOM dynamics along four years. Our newly developed SBOP algorithm was applied to the large Landsat-8 OLI image data (nearly 100 images) for getting the high spatial resolution results. The SBOP algorithm is the first approach developing for the Shallow Water Bio-optical properties estimation. The CDOM absorption derived from the satellite images were verified with the field sampling results with high accuracy (R2 = 0.87). The distinct CDOM dynamics were found in different Rivers. The CDOM absorptions were found highly related to the hydrological activities and the terrestrially environmental dynamics. Our study helps to build the reliable system for studying the carbon cycle at Arctic regions.

The pan-sharpening of satellite and UAV imagery for agricultural applications

NASA Astrophysics Data System (ADS)

Jenerowicz, Agnieszka; Woroszkiewicz, Malgorzata

2016-10-01

Remote sensing techniques are widely used in many different areas of interest, i.e. urban studies, environmental studies, agriculture, etc., due to fact that they provide rapid, accurate and information over large areas with optimal time, spatial and spectral resolutions. Agricultural management is one of the most common application of remote sensing methods nowadays. Monitoring of agricultural sites and creating information regarding spatial distribution and characteristics of crops are important tasks to provide data for precision agriculture, crop management and registries of agricultural lands. For monitoring of cultivated areas many different types of remote sensing data can be used- most popular are multispectral satellites imagery. Such data allow for generating land use and land cover maps, based on various methods of image processing and remote sensing methods. This paper presents fusion of satellite and unnamed aerial vehicle (UAV) imagery for agricultural applications, especially for distinguishing crop types. Authors in their article presented chosen data fusion methods for satellite images and data obtained from low altitudes. Moreover the authors described pan- sharpening approaches and applied chosen pan- sharpening methods for multiresolution image fusion of satellite and UAV imagery. For such purpose, satellite images from Landsat- 8 OLI sensor and data collected within various UAV flights (with mounted RGB camera) were used. In this article, the authors not only had shown the potential of fusion of satellite and UAV images, but also presented the application of pan- sharpening in crop identification and management.

Urban dust in the Guanzhong Basin of China, part I: A regional distribution of dust sources retrieved using satellite data.

PubMed

Long, Xin; Li, Nan; Tie, Xuexi; Cao, Junji; Zhao, Shuyu; Huang, Rujin; Zhao, Mudan; Li, Guohui; Feng, Tian

2016-01-15

Urban dust pollution has been becoming an outstanding environmental problem due to rapid urbanization in China. However, it is very difficult to construct an urban dust inventory, owing to its small horizontal scale and strong temporal/spatial variability. With the analysis of visual interpretation, maximum likelihood classification, extrapolation and spatial overlaying, we quantified dust source distributions of urban constructions, barrens and croplands in the Guanzhong Basin using various satellite data, including VHR (0.5m), Lansat-8 OLI (30 m) and MCD12Q1 (500 m). The croplands were the dominant dust sources, accounting for 40% (17,913 km(2)) of the study area in summer and 36% (17,913 km(2)) in winter, followed by barrens, accounting for 5% in summer and 10% in winter. Moreover, the total constructions were 126 km(2), including 84% of active and 16% inactive. In addition, 59% of the constructions aggregated on the only megacity of the study area, Xi'an. With high accuracy exceeding 88%, the proposed satellite-data based method is feasible and valuable to quantify distributions of dust sources. This study provides a new perspective to evaluate regional urban dust, which is seldom quantified and reported. In a companied paper (Part-2 of the study), the detailed distribution of the urban dust sources is applied in a dynamical/aerosol model (WRF-Dust) to assess the effect of dust sources on aerosol pollution. Copyright © 2015 Elsevier B.V. All rights reserved.

Change in the Extent of Baffin Island's Penny Ice Cap in Response to Regional Warming, 1969 - 2014

NASA Astrophysics Data System (ADS)

Cox, M. C.; Cormier, H. M.; Gardner, A. S.

2014-12-01

Glaciers are retreating globally in response to warmer atmospheric temperatures, adding large volumes of melt water to the world's oceans. The largest glacierized region and present-day contributor to sea level rise outside of the massive ice sheets is the Canadian Arctic. Recent work has shown that the glaciers of the southern Canadian Arctic (Baffin and Bylot Island) have experienced accelerated rates of ice loss in recent decades, but little is known regarding the spatial and temporal variations in rates of loss. For this study we examine in detail changes in the extent of the Penny Ice Cap (a proxy for ice loss) between 1969 and 2014 to better understand the climatic drivers of the recently observed accelerated rates of ice loss on Baffin Island. To do this, we reconstruct the extent of the ice cap for the year 1969 from historical maps and for the years 1985, 1995, 2010, and 2014 from Landsat 5 TM and Landsat 8 OLI imagery. We use 2009 SPOT HRS imagery and a novel extent comparison algorithm to assess the accuracy of glacier extents derived from Landsat imagery. Regional temperature and precipitation records were used to explain the spatial pattern of change. Due to large variation in elevations, hypsometry was also investigated as a contributor to differences in rates of change across the ice cap. Preliminary results show overall retreat throughout the ice cap but with regional differences in area and length change on either side of the Ice Cap divide.

Acadia National Park

NASA Image and Video Library

2017-12-08

Acadia National Park is one of the most visited parks in America, drawing more than 2.5 million visitors per year to the craggy, jagged coast of Maine. The park is celebrating its 100th anniversary in 2016. On September 6, 2015, the Operational Land Imager (OLI) on the Landsat 8 satellite acquired these images of Acadia National Park and its surroundings. Mountains and hills roll right up to the Atlantic Ocean in this rocky landscape carved by glaciers at the end of the last Ice Age. Since the beginning of the 20th Century, the park has been pieced together by donations and acquisitions of once-private lands, and it is still growing. Of the park’s 47,000 acres, more than 12,000 are privately owned lands under conservation agreements, while the rest is held by the National Park Service. Mount Desert Island is the focal point of the park, which also includes lands around a former naval base (Schoodic Peninsula), Isle au Haut, and several smaller islands. Read more: go.nasa.gov/2adyd8J Credit: NASA/Landsat8 NASA image use policy. NASA Goddard Space Flight Center enables NASA’s mission through four scientific endeavors: Earth Science, Heliophysics, Solar System Exploration, and Astrophysics. Goddard plays a leading role in NASA’s accomplishments by contributing compelling scientific knowledge to advance the Agency’s mission. Follow us on Twitter Like us on Facebook Find us on Instagram

Recent glacier mass balance and area changes in the Kangri Karpo Mountains from DEMs and glacier inventories

NASA Astrophysics Data System (ADS)

Wu, Kunpeng; Liu, Shiyin; Jiang, Zongli; Xu, Junli; Wei, Junfeng; Guo, Wanqin

2018-01-01

Due to the influence of the Indian monsoon, the Kangri Karpo Mountains in the south-east of the Tibetan Plateau is in the most humid and one of the most important and concentrated regions containing maritime (temperate) glaciers. Glacier mass loss in the Kangri Karpo is an important contributor to global mean sea level rise, and changes run-off distribution, increasing the risk of glacial-lake outburst floods (GLOFs). Because of its inaccessibility and high labour costs, information about the Kangri Karpo glaciers is still limited. Using geodetic methods based on digital elevation models (DEMs) derived from 1980 topographic maps from the Shuttle Radar Topography Mission (SRTM) (2000) and from TerraSAR-X/TanDEM-X (2014), this study has determined glacier elevation changes. Glacier area and length changes between 1980 and 2015 were derived from topographical maps and Landsat TM/ETM+/OLI images. Results show that the Kangri Karpo contained 1166 glaciers with an area of 2048.50 ± 48.65 km2 in 2015. Ice cover diminished by 679.51 ± 59.49 km2 (24.9 ± 2.2 %) or 0.71 ± 0.06 % a-1 from 1980 to 2015, although nine glaciers advanced. A glacierized area of 788.28 km2, derived from DEM differencing, experienced a mean mass loss of 0.46 ± 0.08 m w.e. a-1 from 1980 to 2014. Shrinkage and mass loss accelerated significantly from 2000 to 2015 compared to 1980-2000, consistent with a warming climate.

Bridging Epidemiology and Remote Sensing: A Case Study of Dengue Fever and Land Use and Land Cover Change in Roatán, Honduras

NASA Astrophysics Data System (ADS)

Tuholske, C.; Brooks, T.

2015-12-01

Dengue fever is one of the fastest spreading infectious diseases in Latin America and the Caribbean. As part of a yearlong epidemiological study of dengue, this paper takes the first step to model the relationship between the urban/built environment and incidents of dengue fever in Roatán, Honduras. Roatán has experienced an 80-fold increase in annual tourists since the 1990s, with over 1.2 million people now visiting the island yearly. In tandem, the Caribbean island's population has exploded from fewer than 13,000 people in the 1970s to over 100,000 people today. Using broadband remote sensed satellite imagery, this paper maps and measures how this massive influx of tourists and population has altered the island's landscape. Results from a decision tree classifying technique applied to a Landsat 5 Thematic Mapper (TM) image from 1985 and Landsat 8 Operational Land Imager (OLI) image from 2014 suggest a rapid pace of urbanization; built and impervious surface has increased over 300% in the last 30 years. Emerging research suggests, similar to other mosquito-borne diseases, a correlation between built environment and risk to dengue because of the increase in stagnate water that serve as disease-host reservoirs. This remote sensing analysis will be integrated with georeferenced household level data of cases of dengue collected during a year-long cross-sectional study of dengue patients in Roatán. The result will be to model the relationship between dengue fever and urban/built environment.

Landsat Detection of the Effects of Hurricane Sandy on New Jersey Coastal Marshes

NASA Astrophysics Data System (ADS)

Riter, A.; Kearney, M.; Mo, Y.

2015-12-01

Hurricane Sandy, an extremely large (1611 km in diameter) and destructive extratropical storm, made landfall near Brigantine, New Jersey on October 29, 2012. We used twenty Landsat Thematic Mapper data sets collected between 1984 and 2011 and four Landsat Operational Land Imager data sets collected between 2013 and 2015 to examine the effect of Sandy on the New Jersey Atlantic coastal marshes between Sandy Hook and Cape May. Landsat data was unavailable between the 2011 failure of Landsat TM and the launch of Landsat OLI in April of 2013. Preliminary results suggest that most of the New Jersey marshes were relatively stable with some interannual variation between 1984 and 2005. Between 2006 and 2015, marsh area generally declined, with the greatest decline occurring in the small discontinuous marshes north of Barnegat Light. The marshes which were closest to where Sandy made landfall seem to have sustained less damage than the marshes north of Barnegat Light. The marshes west of the lagoon bar systems between Seaside Heights and Sandy Hook, that bore the brunt of Sandy's storm surge (from 1.5 to 2.6 meters) and the greatest wave action (Blake et al, 2013), display an increase in pond area within the marshes. As stated above, recent increases in pond size and area as well as the overall decline in marsh coverage began before Hurricane Sandy. This suggests that the even the most at-risk marshes were not as affected by Sandy's storm surge and waves as the barrier islands.

Dynamics Change of Vegetated Lands in A Highway Corridor during 37 Years (Case study of Jagorawi Toll Road, Jakarta-Bogor)

NASA Astrophysics Data System (ADS)

Perdana, B. P.; Setiawan, Y.; Prasetyo, L. B.

2018-02-01

Recently, a highway development is required as a liaison between regions to support the economic development of the regions. Even the availability of highways give positive impacts, it also has negative impacts, especially related to the changes of vegetated lands. This study aims to determine the change of vegetation coverage in Jagorawi corridor Jakarta-Bogor during 37 years, and to analyze landscape patterns in the corridor based on distance factor from Jakarta to Bogor. In this study, we used a long-series of Landsat images taken by Landsat 2 MSS (1978), Landsat 5 TM (1988, 1995, and 2005) and Landsat 8 OLI/TIRS (2015). Analysis of landscape metrics was conducted through patch analysis approach to determine the change of landscape patterns in the Jagorawi corridor Jakarta-Bogor. Several parameters of landscape metrics used are Number of Patches (NumP), Mean Patch Size (MPS), Mean Shape Index (MSI), and Edge Density (ED). These parameters can be used to provide information of structural elements of landscape, composition and spatial distribution in the corridor. The results indicated that vegetation coverage in the Jagorawi corridor Jakarta-Bogor decreased about 48% for 35 years. Moreover, NumP value increased and decreasing of MPS value as a means of higher fragmentation level occurs with patch size become smaller. Meanwhile, The increase in ED parameters indicates that vegetated land is damaged annually. MSI parameter shows a decrease in every year which means land degradation on vegetated land. This indicates that the declining value of MSI will have an impact on land degradation.

Carpathian mountain forest vegetation and its responses to climate stressors

NASA Astrophysics Data System (ADS)

Zoran, Maria A.; Savastru, Roxana S.; Savastru, Dan M.; Tautan, Marina N.; Baschir, Laurentiu V.; Dida, Adrian I.

2017-10-01

Due to anthropogenic and climatic changes, Carpathian Mountains forests in Romania experience environmental degradation. As a result of global climate change, there is growing evidence that some of the most severe weather events could become more frequent in Romania over the next 50 to 100 years. In the case of Carpathian mountain forests, winter storms and heat waves are considered key climate risks, particularly in prealpine and alpine areas. Effects of climate extremes on forests can have both short-term and long-term implications for standing biomass, tree health and species composition. The preservation and enhancement of mountain forest vegetation cover in natural, semi-natural forestry ecosystems is an essential factor in sustaining environmental health and averting natural hazards. This paper aims to: (i) describe observed trends and scenarios for summer heat waves, windstorms and heavy precipitation, based on results from satellite time series NOAA AVHRR, MODIS Terra/Aqua and Landsat TM/ETM+/OLI NDVI and LAI data recorded during 2000-2016 period correlated with meteorological parameters, regional climate models, and other downscaling procedures, and (ii) discuss potential impacts of climate changes and extreme events on Carpathian mountain forest system in Romania. The response of forest land cover vegetation in Carpathian Mountains, Romania to climatic factors varies in different seasons of the years, the diverse vegetation feedbacks to climate changes being related to different vegetation characteristics and meteorological conditions. Based on integrated analysis of satellite and field data was concluded that forest ecosystem functions are responsible of the relationships between mountain specific vegetation and climate.

A New Identity for Denali

NASA Image and Video Library

2017-12-08

Physically, not too much has changed on Denali, North America’s highest peak. What did change in 2015 is how people describe and measure Alaska’s majestic mountain. On August 30, 2015, U.S. Secretary of the Interior Sally Jewell announced that the mountain’s official name would be Denali, not Mount McKinley. Restoration of the traditional Koyukon Athabascan name of Denali, which means “the tall one,” resolved a request by former Alaska Gov. Jay Hammond that dates back to 1975. But the mountain’s name was not the only change. On September 2, its elevation was also revised. The U.S. Geological Survey announced that Denali’s summit had a new, official elevation of 20,310 feet (6,190 meters)—10 feet shorter than surveyors had determined in the 1950s. The mountain has not shrunk. Instead, technology has improved. The images on this page offer two views of Denali as observed on June 15, 2015, by the Operational Land Imager (OLI) on Landsat 8. The natural-color Landsat 8 images were draped over an ASTER-derived Global Digital Elevation Model, which helps show the topography of the area. Read more: 1.usa.gov/1QbmOFP NASA image use policy. NASA Goddard Space Flight Center enables NASA’s mission through four scientific endeavors: Earth Science, Heliophysics, Solar System Exploration, and Astrophysics. Goddard plays a leading role in NASA’s accomplishments by contributing compelling scientific knowledge to advance the Agency’s mission. Follow us on Twitter Like us on Facebook Find us on Instagram

A long-term perspective on deforestation rates in the Brazilian Amazon

NASA Astrophysics Data System (ADS)

Velasco Gomez, M. D.; Beuchle, R.; Shimabukuro, Y.; Grecchi, R.; Simonetti, D.; Eva, H. D.; Achard, F.

2015-04-01

Monitoring tropical forest cover is central to biodiversity preservation, terrestrial carbon stocks, essential ecosystem and climate functions, and ultimately, sustainable economic development. The Amazon forest is the Earth's largest rainforest, and despite intensive studies on current deforestation rates, relatively little is known as to how these compare to historic (pre 1985) deforestation rates. We quantified land cover change between 1975 and 2014 in the so-called Arc of Deforestation of the Brazilian Amazon, covering the southern stretch of the Amazon forest and part of the Cerrado biome. We applied a consistent method that made use of data from Landsat sensors: Multispectral Scanner (MSS), Thematic Mapper (TM), Enhanced Thematic Mapper Plus (ETM+) and Operational Land Imager (OLI). We acquired suitable images from the US Geological Survey (USGS) for five epochs: 1975, 1990, 2000, 2010, and 2014. We then performed land cover analysis for each epoch using a systematic sample of 156 sites, each one covering 10 km x 10 km, located at the confluence point of integer degree latitudes and longitudes. An object-based classification of the images was performed with five land cover classes: tree cover, tree cover mosaic, other wooded land, other land cover, and water. The automatic classification results were corrected by visual interpretation, and, when available, by comparison with higher resolution imagery. Our results show a decrease of forest cover of 24.2% in the last 40 years in the Brazilian Arc of Deforestation, with an average yearly net forest cover change rate of -0.71% for the 39 years considered.

Monitoring Changes of Ecosystem Services Supply and Demand Pattern in Central and Southern Liaoning Urban Agglomerations, China Using Landsat Images

NASA Astrophysics Data System (ADS)

Li, B.; Huang, F.; Chang, S.; Qi, H.; Zhai, H.

2018-04-01

Indentifying the spatio-temporal patterns of ecosystem services supply and demand and the driving forces is of great significance to the regional ecological security and sustainable socio-economic development. Due to long term and high-intensity development, the ecological environment in central and southern Liaoning urban agglomerations has been greatly destroyed thereafter has restricted sustainable development in this region. Based on Landsat ETM and OLI images, land use of this urban agglomeration in 2005, 2010 and 2015 was extracted. The integrative index of multiple-ecosystem services (IMES) was used to quantify the supply (IMESs), demand (IMESd) and balance (IMESb) of multiple-ecosystem services, The spatial patterns of ecosystem services and its dynamics for the period of 2005-2015 were revealed. The multiple regression and stepwise regression analysis were used to explore relationships between ecosystem services and socioeconomic factors. The results showed that the IMESs of the region increased by 2.93 %, whereas IMESd dropped 38 %. The undersupplied area was reduced to 2. The IMESs and IMESb were mainly negatively correlated with gross domestic product (GDP), population density, foreign investment and industrial output, while GDP per capita and the number of teachers had significant positive impacts on ecosystem services supply. The positive correlation between IMESd and GDP, population density and foreign investment were found. The ecosystem services models were established. Supply and balance of multiple-ecosystem services were positively correlated with population density, but the demand was the opposite. The results can provide some reference value for the coordinately economic and ecological development in the study area.

Using Remote Sensing to Determine the Spatial Scales of Estuaries

NASA Astrophysics Data System (ADS)

Davis, C. O.; Tufillaro, N.; Nahorniak, J.

2016-02-01

One challenge facing Earth system science is to understand and quantify the complexity of rivers, estuaries, and coastal zone regions. Earlier studies using data from airborne hyperspectral imagers (Bissett et al., 2004, Davis et al., 2007) demonstrated from a very limited data set that the spatial scales of the coastal ocean could be resolved with spatial sampling of 100 m Ground Sample Distance (GSD) or better. To develop a much larger data set (Aurin et al., 2013) used MODIS 250 m data for a wide range of coastal regions. Their conclusion was that farther offshore 500 m GSD was adequate to resolve large river plume features while nearshore regions (a few kilometers from the coast) needed higher spatial resolution data not available from MODIS. Building on our airborne experience, the Hyperspectral Imager for the Coastal Ocean (HICO, Lucke et al., 2011) was designed to provide hyperspectral data for the coastal ocean at 100 m GSD. HICO operated on the International Space Station for 5 years and collected over 10,000 scenes of the coastal ocean and other regions around the world. Here we analyze HICO data from an example set of major river delta regions to assess the spatial scales of variability in those systems. In one system, the San Francisco Bay and Delta, we also analyze Landsat 8 OLI data at 30 m and 15 m to validate the 100 m GSD sampling scale for the Bay and assess spatial sampling needed as you move up river.

Partial pedigree analysis of the segregation of yeast mitochondrial genes during vegetative reproduction.

PubMed

Waxman, M F; Birk, C W

1982-08-01

A three-factor cross of Saccharomyces cerevisiae involving the cap1, ery1, and oli1 loci was done, with partial pedigree analyses of 117 zygotes. First, second, and third buds were removed and the genotypes of their diploid progeny determined, along with those of the residual zygote mother cell. Results were analyzed in terms of frequencies of individual alleles and of recombinant genotypes in the dividing cells. There is a gradual increase in the frequency of homoplasmic cells and in gene frequency variance during these three generations, as would result from stochastic partitioning of mtDNA molecules between mother and bud, probably coupled with random drift of gene frequencies in interphase cells. These phenomena are more pronounced for buds than for mothers, suggesting that buds receive a smaller sample of molecules. End buds are more likely to be homoplasmic and have a lower frequency of recombinant genotypes than do central buds; an end bud is particularly enriched in alleles contributed by the parent that formed that end of the zygote. Zygotes with first central buds produce clones with a higher recombination frequency than do those with first end buds. These results confirm previous studies and suggest that mixing of parental genotypes occurs first in the center of the zygote. If segregation were strictly random, the number of segregating units would have to be much smaller than the number of mtDNA molecules in the zygote. On the other hand, there is no evidence for a region of the molecule ("attachment point") which segregates deterministically.

The Orphan G Protein-coupled Receptor GPR17 Negatively Regulates Oligodendrocyte Differentiation via Gαi/o and Its Downstream Effector Molecules.

PubMed

Simon, Katharina; Hennen, Stephanie; Merten, Nicole; Blättermann, Stefanie; Gillard, Michel; Kostenis, Evi; Gomeza, Jesus

2016-01-08

Recent studies have recognized G protein-coupled receptors as important regulators of oligodendrocyte development. GPR17, in particular, is an orphan G protein-coupled receptor that has been identified as oligodendroglial maturation inhibitor because its stimulation arrests primary mouse oligodendrocytes at a less differentiated stage. However, the intracellular signaling effectors transducing its activation remain poorly understood. Here, we use Oli-neu cells, an immortalized cell line derived from primary murine oligodendrocytes, and primary rat oligodendrocyte cultures as model systems to identify molecular targets that link cell surface GPR17 to oligodendrocyte maturation blockade. We demonstrate that stimulation of GPR17 by the small molecule agonist MDL29,951 (2-carboxy-4,6-dichloro-1H-indole-3-propionic acid) decreases myelin basic protein expression levels mainly by triggering the Gαi/o signaling pathway, which in turn leads to reduced activity of the downstream cascade adenylyl cyclase-cAMP-PKA-cAMP response element-binding protein (CREB). In addition, we show that GPR17 activation also diminishes myelin basic protein abundance by lessening stimulation of the exchange protein directly activated by cAMP (EPAC), thus uncovering a previously unrecognized role for EPAC to regulate oligodendrocyte differentiation. Together, our data establish PKA and EPAC as key downstream effectors of GPR17 that inhibit oligodendrocyte maturation. We envisage that treatments augmenting PKA and/or EPAC activity represent a beneficial approach for therapeutic enhancement of remyelination in those demyelinating diseases where GPR17 is highly expressed, such as multiple sclerosis. © 2016 by The American Society for Biochemistry and Molecular Biology, Inc.

Competition between agricultural, urban, and sand-mining areas at the Paraíba do Sul basin in southeastern Brazil

NASA Astrophysics Data System (ADS)

Ronquim, Carlos C.; Cordeiro, Guilherme P. L.; Amorim, Mariana de; de C. Teixeira, Antônio H.; Leivas, Janice F.; Galdino, Sergio

2017-10-01

This work was performed in the Paraíba do Sul basin, within the limits of the São Paulo state, southeastern Brazil, in order to assess the dynamics of the land-use and land-cover changes at the Paraíba do Sul river's floodplains between 1985 and 2016. We focused on investigating the development of agricultural areas used for the production of wetland rice and of areas featuring artificial lakes produced by sand mining. We mapped the land cover in 1985 using images made by the Landsat 5 satellite's Moderate Resolution Imaging Spectroradiometer (MODIS) and Thematic Mapper (TM) sensors, which were segmented to produce vectors featuring homogeneous characteristics, and which were classified by means of visual interpretation. Similarly, we applied the maximum likelihood classification and used spectral curve inserts and adjustments to study and analyze the same area using a Landsat 8's Operational Land Imager (OLI) image made in 2016. Our results show significant reduction of areas used for rice crops, and increase in areas featuring sandmining pits. The rice crop areas decreased approximately 43% from 24,131.4 ha in 1985 to 13,789.8 ha in 2016. Over this 30-year period, the area covered by sand-mining lakes increased from 615 ha to 3,876 ha (+ 630%), and the number of lakes increased from 54 to 316. Sand mining and urbanization are the main factors causing the reduction in wetland rice areas. The absence of environmental management actions at the basin interferes with the rice production, which depends on the Paraíba do Sul river's floodplains.

Validation of EO-1 Hyperion and Advanced Land Imager Using the Radiometric Calibration Test Site at Railroad Valley, Nevada

NASA Technical Reports Server (NTRS)

Czapla-Myers, Jeffrey; Ong, Lawrence; Thome, Kurtis; McCorkel, Joel

2015-01-01

The Earth-Observing One (EO-1) satellite was launched in 2000. Radiometric calibration of Hyperion and the Advanced Land Imager (ALI) has been performed throughout the mission lifetime using various techniques that include ground-based vicarious calibration, pseudo-invariant calibration sites, and also the moon. The EO-1 mission is nearing its useful lifetime, and this work seeks to validate the radiometric calibration of Hyperion and ALI from 2013 until the satellite is decommissioned. Hyperion and ALI have been routinely collecting data at the automated Radiometric Calibration Test Site [RadCaTS/Railroad Valley (RRV)] since launch. In support of this study, the frequency of the acquisitions at RadCaTS has been significantly increased since 2013, which provides an opportunity to analyze the radiometric stability and accuracy during the final stages of the EO-1 mission. The analysis of Hyperion and ALI is performed using a suite of ground instrumentation that measures the atmosphere and surface throughout the day. The final product is an estimate of the top-of-atmosphere (TOA) spectral radiance, which is compared to Hyperion and ALI radiances. The results show that Hyperion agrees with the RadCaTS predictions to within 5% in the visible and near-infrared (VNIR) and to within 10% in the shortwave infrared (SWIR). The 2013-2014 ALI results show agreement to within 6% in the VNIR and 7.5% in the SWIR bands. A cross comparison between ALI and the Operational Land Imager (OLI) using RadCaTS as a transfer source shows agreement of 3%-6% during the period of 2013-2014.

Integrating satellite remote sensing data and field data to predict rangeland structural indicators at the continental scale

NASA Astrophysics Data System (ADS)

Zhang, J.; Okin, G.

2016-12-01

Rangelands provide a variety of important ecosystem goods and services across drylands globally. They are also the most important emitters of dust across the globe. Field data collection based on points does not represent spatially continuous information about surface variables and, given the vast size of the world's rangelands, cannot cover even a small fraction of their area. Remote sensing is potentially a labor- and time-saving method to observe important rangeland vegetation variables at both temporal and spatial scales. Information on vegetation cover, bare gap size, and plant height provide key rangeland vegetation variables in arid and semiarid rangelands, in part because they strongly impact dust emission and determine wildlife habitat characteristics. This study reports on relationships between remote sensing in the reflected solar spectrum and field measures related to these three variables, and shows how these relationships can be extended to produce spatially and temporally continuous datasets coupled with quantitative estimates of error. Field data for this study included over 3,800 Assessment, Inventory, and Monitoring (AIM) measurements on Bureau of Land Management (BLM) lands throughout the western US. Remote sensing data were derived from MODIS nadir BRDF-adjusted reflectance (NBAR) and Landsat 8 OLI surface reflectance. Normalized bare gap size, total foliar cover, herbaceous cover and herbaceous height exhibit the greatest predictability from remote sensing variables with physically-reasonable relationships between remote sensing variables and field measures. Data fields produced using these relationships across the western US exhibit good agreement with independent high-resolution imagery.

The YJR127C/ZMS1 gene product is involved in glycerol-based respiratory growth of the yeast Saccharomyces cerevisiae.

PubMed

Lu, Lin; Roberts, George G; Oszust, Cynthia; Hudson, Alan P

2005-10-01

A putative yeast mitochondrial upstream activating sequence (UAS) was used in a one-hybrid screening procedure that identified the YJR127C ORF on chromosome X. This gene was previously designated ZMS1 and is listed as a transcription factor on the SGD website. Real time RT-PCR assays showed that expression of YJR127C/ZMS1 was glucose-repressible, and a deletion mutant for the gene showed a growth defect on glycerol-based but not on glucose- or ethanol-based medium. Real time RT-PCR analyses identified severely attenuated transcript levels from GUT1 and GUT2 to be the source of that growth defect, the products of GUT1 and GUT2 are required for glycerol utilization. mRNA levels from a large group of mitochondria- and respiration-related nuclear genes also were shown to be attenuated in the deletion mutant. Importantly, transcript levels from the mitochondrial OLI1 gene, which has an associated organellar UAS, were attenuated in the DeltaYJR127C mutant during glycerol-based growth, but those from COX3 (OXI2), which lacks an associated mitochondrial UAS, were not. Transcriptome analysis of the glycerol-grown deletion mutant showed that genes in several metabolic and other categories are affected by loss of this gene product, including protein transport, signal transduction, and others. Thus, the product of YJR127C/ZMS1 is involved in transcriptional control for genes in both cellular genetic compartments, many of which specify products required for glycerol-based growth, respiration, and other functions.

Describing River Plume Interactions in the Northern Adriatic Sea Using High Resolution Satellite Turbidity And Sea Surface Temperature Observations

NASA Astrophysics Data System (ADS)

Brando, V. E.; Braga, F.; Zaggia, L.; Carniel, S.

2016-02-01

Sea surface temperature (SST) and turbidity (T) derived from Landsat-8 (L8) imagery were used to characterize river plumes in the Northern Adriatic Sea (NAS). Sea surface salinity (SSS) from an operational coupled ocean-wave model supported the interpretation of the plumes interaction with the receiving waters and among them. In this study we used L8 OLI and TIRS imagery of 19 November 2014 capturing a significant freshwater inflow into the NAS for mapping both T and SST at 30 meters resolution. Sharp fronts in T and SST delimited each single river plume. The isotherms and turbidity isolines coupling varied among the plumes due to differences in particle loads and surface temperatures in the discharged waters. Overall, there was a good agreement of the SSS, T, and SST fields at the mesoscale delineation of the major river plumes. Landsat-8 30m resolution enabled the identification of smaller plume structures and the description at small scale and sub-mesoscale of the plume dynamical regions for all plume structures, as well as their interactions in the NAS. Although this study presents data captured with a sensor having a revisiting time of 16 days, we expect that with the recent launch of ESA's Sentinel 2A and the forthcoming launch of Sentinel 2B the temporal resolution will increase reaching almost the 1-3 days revisit time normally associated with Ocean Colour Radiometry (OCR). Combined with their radiometric resolution similar to OCR missions, these developments will thus offer an opportunity to also describe the temporal evolution of plume structures at the sub-mesoscale.

Tuning of Thermal Stability in Layered Li(NixMnyCoz)O2.

PubMed

Zheng, Jiaxin; Liu, Tongchao; Hu, Zongxiang; Wei, Yi; Song, Xiaohe; Ren, Yang; Wang, Weidong; Rao, Mumin; Lin, Yuan; Chen, Zonghai; Lu, Jun; Wang, Chongmin; Amine, Khalil; Pan, Feng

2016-10-12

Understanding and further designing new layered Li(Ni x Mn y Co z )O 2 (NMC) (x + y + z = 1) materials with optimized thermal stability is important to rechargeable Li batteries (LIBs) for electrical vehicles (EV). Using ab initio calculations combined with experiments, we clarified how the thermal stability of NMC materials can be tuned by the most unstable oxygen, which is determined by the local coordination structure unit (LCSU) of oxygen (TM(Ni, Mn, Co) 3 -O-Li 3-x' ): each O atom bonds with three transition metals (TM) from the TM-layer and three to zero Li from fully discharged to charged states from the Li-layer. Under this model, how the lithium content, valence states of Ni, contents of Ni, Mn, and Co, and Ni/Li disorder to tune the thermal stability of NMC materials by affecting the sites, content, and the release temperature of the most unstable oxygen is proposed. The synergistic effect between Li vacancies and raised valence state of Ni during delithiation process can aggravate instability of oxygen, and oxygen coordinated with more nickel (especially with high valence state) in LSCU becomes more unstable at a fixed delithiation state. The Ni/Li mixing would decrease the thermal stability of the "Ni═Mn" group NMC materials but benefit the thermal stability of "Ni-rich" group, because the Ni in the Li layer would form 180° Ni-O-Ni super exchange chains in "Ni-rich" NMC materials. Mn and Co doping can tune the initial valence state of Ni, local coordination environment of oxygen, and the Ni/Li disorder, thus to tune the thermal stability directly.

Inland-coastal water interaction: Remote sensing application for shallow-water quality and algal blooms modeling

NASA Astrophysics Data System (ADS)

Melesse, Assefa; Hajigholizadeh, Mohammad; Blakey, Tara

2017-04-01

In this study, Landsat 8 and Sea-Viewing Wide Field-of-View Sensor (SeaWIFS) sensors were used to model the spatiotemporal changes of four water quality parameters: Landsat 8 (turbidity, chlorophyll-a (chl-a), total phosphate, and total nitrogen) and Sea-Viewing Wide Field-of-View Sensor (SeaWIFS) (algal blooms). The study was conducted in Florda bay, south Florida and model outputs were compared with in-situ observed data. The Landsat 8 based study found that, the predictive models to estimate chl-a and turbidity concentrations, developed through the use of stepwise multiple linear regression (MLR), gave high coefficients of determination in dry season (wet season) (R2 = 0.86(0.66) for chl-a and R2 = 0.84(0.63) for turbidity). Total phosphate and TN were estimated using best-fit multiple linear regression models as a function of Landsat TM and OLI,127 and ground data and showed a high coefficient of determination in dry season (wet season) (R2 = 0.74(0.69) for total phosphate and R2 = 0.82(0.82) for TN). Similarly, the ability of SeaWIFS for chl-a retrieval from optically shallow coastal waters by applying algorithms specific to the pixels' benthic class was evaluated. Benthic class was determined through satellite image-based classification methods. It was found that benthic class based chl-a modeling algorithm was better than the existing regionally-tuned approach. Evaluation of the residuals indicated the potential for further improvement to chl-a estimation through finer characterization of benthic environments. Key words: Landsat, SeaWIFS, water quality, Florida bay, Chl-a, turbidity

Spatiotemporal Change Detection in Forest Cover Dynamics Along Landslide Susceptible Region of Karakoram Highway, Pakistan

NASA Astrophysics Data System (ADS)

Rashid, Barira; Iqbal, Javed

2018-04-01

Forest Cover dynamics and its understanding is essential for a country's social, environmental, and political engagements. This research provides a methodical approach for the assessment of forest cover along Karakoram Highway. It has great ecological and economic significance because it's a part of China-Pakistan Economic Corridor. Landsat 4, 5 TM, Landsat 7 ETM and Landsat 8 OLI imagery for the years 1990, 2000, 2010 and 2016 respectively were subjected to supervised classification in ArcMap 10.5 to identify forest change. The study area was categorized into five major land use land cover classes i.e., Forest, vegetation, urban, open land and snow cover. Results from post classification forest cover change maps illustrated notable decrease of almost 26 % forest cover over the time period of 26 years. The accuracy assessment revealed the kappa coefficients 083, 0.78, 0.77 and 0.85, respectively. Major reason for this change is an observed replacement of native forest cover with urban areas (12.5 %) and vegetation (18.6 %) However, there is no significant change in the reserved forests along the study area that contributes only 2.97 % of the total forest cover. The extensive forest degradation and risk prone topography of the region has increased the environmental risk of landslides. Hence, effective policies and forest management is needed to protect not only the environmental and aesthetic benefits of the forest cover but also to manage the disaster risks. Apart from the forest assessment, this research gives an insight of land cover dynamics, along with causes and consequences, thereby showing the forest degradation hotspots.

A novel cross-satellite based assessment of the spatio-temporal development of a cyanobacterial harmful algal bloom

NASA Astrophysics Data System (ADS)

Page, Benjamin P.; Kumar, Abhishek; Mishra, Deepak R.

2018-04-01

As the frequency of cyanobacterial harmful algal blooms (CyanoHABs) become more common in recreational lakes and water supply reservoirs, demand for rapid detection and temporal monitoring will be imminent for effective management. The goal of this study was to demonstrate a novel and potentially operational cross-satellite based protocol for synoptic monitoring of rapidly evolving and increasingly common CyanoHABs in inland waters. The analysis involved a novel way to cross-calibrate a chlorophyll-a (Chl-a) detection model for the Landsat-8 OLI sensor from the relationship between the normalized difference chlorophyll index and the floating algal index derived from Sentinel-2A on a coinciding overpass date during the summer CyanoHAB bloom in Utah Lake. This aided in the construction of a time-series phenology of the Utah Lake CyanoHAB event. Spatio-temporal cyanobacterial density maps from both Sentinel-2A and Landsat-8 sensors revealed that the bloom started in the first week of July 2016 (July 3rd, mean cell count: 9163 cells/mL), reached peak in mid-July (July 15th, mean cell count: 108176 cells/mL), and reduced in August (August 24th, mean cell count: 9145 cells/mL). Analysis of physical and meteorological factors suggested a complex interaction between landscape processes (high surface runoff), climatic conditions (high temperature, high rainfall followed by negligible rainfall, stable wind), and water quality (low water level, high Chl-a) which created a supportive environment for triggering these blooms in Utah Lake. This cross satellite-based monitoring methods can be a great tool for regular monitoring and will reduce the budget cost for monitoring and predicting CyanoHABs in large lakes.

Requirements, Science, and Measurements for Landsat 10 and Beyond: Perspectives from the Landsat Science Team

NASA Astrophysics Data System (ADS)

Crawford, C. J.; Masek, J. G.; Roy, D. P.; Woodcock, C. E.; Wulder, M. A.

2017-12-01

The U.S. Geological Survey (USGS) and NASA are currently prioritizing requirements and investing in technology options for a "Landsat 10 and beyond" mission concept as part of the Sustainable Land Imaging (SLI) architecture. Following the successful February 2013 launch of the Landsat 8, the Operational Land Imager (OLI) and Thermal Infrared Sensor (TIRS) have now added over 1 million images to the USGS Landsat archive. The USGS and NASA support and co-lead a Landsat Science Team made up largely of university and government experts to offer independent insight and guidance of program activities and directions. The rapid development of Landsat 9 reflects, in part, strong input from the 2012-2017 USGS Landsat Science Team (LST). During the last two years of the LST's tenure, individual LST members and within LST team working groups have made significant contributions to Landsat 10 and beyond's science traceability and future requirements justification. Central to this input, has been an effort to identify a trade space for enhanced measurement capabilities that maintains mission continuity with eight prior multispectral instruments, and will extend the Landsat Earth observation record beyond 55+ years with an approximate launch date of 2027. The trade space is framed by four fundamental principles in remote sensing theory and practice: (1) temporal resolution, (2) spatial resolution, (3) radiometric resolution, and (4) spectral coverage and resolution. The goal of this communication is to provide a synopsis of past and present 2012-2017 LST contributions to Landsat 10 and beyond measurement science and application priorities. A particular focus will be to document the links between new science and societal benefit areas with potential technical enhancements to the Landsat mission.

Volcanic Plumes Tower over Mount Etna

NASA Image and Video Library

2013-11-06

Twin volcanic plumes—one of ash, one of gas—rose from Sicily’ Mount Etna on the morning of October 26, 2013. L’Istituto Nazionale di Geofisica e Vulcanologia (INGV) Osservatorio Etneo (National Institute of Geophysics and Volcanology Etna Observatory) reported that Etna was experiencing its first paroxysm in six months. Multiple eruption columns are common at Etna, a result of complex plumbing within the volcano. The Northeast Crater, one of several on Etna’s summit, was emitting the ash column, while the New Southeast Crater was simultaneously venting mostly gas. This natural-color image collected by Landsat 8 shows the view from space at 11:38 a.m. local time. The towering, gas-rich plume cast a dark shadow over the lower, ash-rich plume and Etna’s northwestern flank. Relatively fresh lava flows (less than a century or so old) are dark gray; vegetation is green; and the tile-roofed buildings of Bronte and Biancavilla lend the towns an ochre hue. NASA Earth Observatory image by Jesse Allen and Robert Simmon, using Landsat data from the USGS Earth Explorer. Photograph ©2013, Boris Behncke. Caption by Robert Simmon with contributions from Boris Behncke. Instrument: Landsat 8 - OLI More info: 1.usa.gov/1cEcOFi Credit: NASA Earth Observatory NASA image use policy. NASA Goddard Space Flight Center enables NASA’s mission through four scientific endeavors: Earth Science, Heliophysics, Solar System Exploration, and Astrophysics. Goddard plays a leading role in NASA’s accomplishments by contributing compelling scientific knowledge to advance the Agency’s mission. Follow us on Twitter Like us on Facebook Find us on Instagram

Volcanic Plumes Tower over Mount Etna [annotated

NASA Image and Video Library

2013-11-06

Twin volcanic plumes—one of ash, one of gas—rose from Sicily’ Mount Etna on the morning of October 26, 2013. L’Istituto Nazionale di Geofisica e Vulcanologia (INGV) Osservatorio Etneo (National Institute of Geophysics and Volcanology Etna Observatory) reported that Etna was experiencing its first paroxysm in six months. Multiple eruption columns are common at Etna, a result of complex plumbing within the volcano. The Northeast Crater, one of several on Etna’s summit, was emitting the ash column, while the New Southeast Crater was simultaneously venting mostly gas. This natural-color image collected by Landsat 8 shows the view from space at 11:38 a.m. local time. The towering, gas-rich plume cast a dark shadow over the lower, ash-rich plume and Etna’s northwestern flank. Relatively fresh lava flows (less than a century or so old) are dark gray; vegetation is green; and the tile-roofed buildings of Bronte and Biancavilla lend the towns an ochre hue. NASA Earth Observatory image by Jesse Allen and Robert Simmon, using Landsat data from the USGS Earth Explorer. Photograph ©2013, Boris Behncke. Caption by Robert Simmon with contributions from Boris Behncke. Instrument: Landsat 8 - OLI More info: 1.usa.gov/1cEcOFi Credit: NASA Earth Observatory NASA image use policy. NASA Goddard Space Flight Center enables NASA’s mission through four scientific endeavors: Earth Science, Heliophysics, Solar System Exploration, and Astrophysics. Goddard plays a leading role in NASA’s accomplishments by contributing compelling scientific knowledge to advance the Agency’s mission. Follow us on Twitter Like us on Facebook Find us on Instagram

Remote Sensing Analysis of Temperature and Suspended Sediment Concentration in Ayeyarwady River in Myanmar

NASA Astrophysics Data System (ADS)

Thanda Ko, Nyein; Rutten, Martine

2017-04-01

Detailed spatial coverage of water quality parameters are crucial to better manage rivers. However, collection of water quality parameters is both time consuming and costly for large rivers. This study demonstrates that Operational Land Image (OLI) Sensor on board of Landsat 8 can be successfully applied for the detection of spatial patterns of water temperature as well as suspended sediment concentration (SSC) using the Ayeyarwady river, Myanmar as a case study. Water temperature estimation was obtained from the brightness thermal Band 10 by using the Split-Window algorithm. The study finds that there is a close agreement between the remote sensing temperature and in-situ temperature with relative error in the range from 4.5% to 8.2%. The sediment load of Ayeyarwady river is ranked as the third-largest sediment load among the world's rivers but there is very little known about this important parameter, due to a lack of adequate gauge data. The single band reflectance of Landsat image (Band 5) seems a good indicator for the estimation of SSC with relative error in the range of less than 10% but the developed empirical formula by the power relation with the only seven ground reference points is uncertain to apply for the entire river basin. It is to note that an important constraint for the sediment analysis is the availability of spatial and temporal ground reference data. Future studies should also focus on the improvement of ground reference data points to become more reliable, because most of the river in Asia, especially in Myanmar, don't have readily available continuous ground sediment data points due to lack of measurement gauge stations through the river.

Myanmar Ecological Forecasting: Utilizing NASA Earth Observations to Monitor, Map, and Analyze Mangrove Forests in Myanmar for Enhanced Conservation

NASA Technical Reports Server (NTRS)

Weber, Samuel J.; Keddell, Louis; Kemal, Mohammed

2014-01-01

Mangroves supply many essential environmental amenities, such as preventing soil erosion, filtering water pollution, and protecting shorelines from harmful waves, floods, storms and winds. The Mangroves in Myanmar not only provide citizens with a food source, but they also offer firewood, charcoal, and construction materials. The depletion of mangroves is threatening more than the biodiversity however; Myanmar's fiscal livelihood is also in harm's way. Mangroves are valued at $100,000 to $277,000 per square kilometer and if managed in a sustainable fashion, can infuse constant income to the emerging Myanmarese economy. This study analyzed three coastline regions, the Ayeyarwady Delta, Rakhine and Tanintharyi, and mapped the spatial extent of mangrove forest during the dry season in 2000 and 2013. The classifications were derived from Landsat 7 Enhanced Thematic Mapper Plus (ETM+) and Landsat 8 Operation Land Imager (OLI) imagery, as well as the Terra Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) digital elevation model information. This data was atmospherically corrected, mosaicked, masked and classified in ENVI, followed by ArcGIS to perform raster calculations and create final products. Forest degradation collected from 2000 to 2013 was later used to forecast the density and health of Mangroves in the year 2030. These results were subsequently presented to project partners Dr. Peter Leimgruber and Ellen Aiken at the Smithsonian Conservation Biology Institute in Front Royal, VA. After the presentation of the project to the partners, these organizations formally passed on to the Myanmar Ministry of Environment, Conservation and Forestry for policy makers and forest managers to utilize in order to protect the Myanmar mangrove ecosystem while sustaining a healthy economy.

Enhancing Pre- and Post-Wildfire Vegetation Recovery and Understanding Feedbacks of Cheatgrass invasion Using NASA Earth Observations

NASA Astrophysics Data System (ADS)

Olsen, N.; Counts, A.; Quistorff, C.; Ohr, C. A.; Toner, C.

2017-12-01

Increasing wildfire frequency and severity has emphasized the importance of post-wildfire recovery efforts in southern Idaho's sagebrush ecosystems. These changing fire regimes favor invasive grass species while hindering native sagebrush habitat regeneration, causing a positive feedback cycle of invasive growth - wildfires - invasive growth. Due to this undesirable process and anthropogenic influences, the sagebrush ecosystem is one of the most endangered in the US. In this project the NASA DEVELOP group of Pocatello, Idaho partnered with the Bureau of Land Management, Idaho Department of Fish and Game, and the US Department of Agriculture to characterize ecosystem recovery following the Crystal (2006), Henry Creek (2016), Jefferson (2010), and Soda (2015) wildfires. Determining vegetation cover heterogeneity and density can be time consuming and the factors affecting ecosystem recovery can be complex. In addition, restoration success is difficult to determine as vegetation composition is not often known prior to wildfire events and monitoring vegetation composition after restoration efforts can be resource intensive. These wildfires temporal monitoring consisted of 2001 to 2017 using NASA Earth observations such as Landsat 5 Thermal Mapper (TM), Landsat 8 Operational Land Imager (OLI), Terra Moderate Resolution Imaging Spectroradiometer (MODIS), and Shuttle Radar Topography Mission (SRTM) to determine the most significant factors of wildfire recovery and the influence targeted grazing could have for recovery. In addition, this project will include monitoring of invasive species propagation and whether spatial patterns or extents of the wildfire contribute to propagation. Understanding the key variables that made reseeding and natural recovery work in some areas, assessing why they failed in others, and identifying factors that made non-native propagation ideal are important issues for land managers in this region.

Triacetin-based acetate supplementation as a chemotherapeutic adjuvant therapy in glioma.

PubMed

Tsen, Andrew R; Long, Patrick M; Driscoll, Heather E; Davies, Matthew T; Teasdale, Benjamin A; Penar, Paul L; Pendlebury, William W; Spees, Jeffrey L; Lawler, Sean E; Viapiano, Mariano S; Jaworski, Diane M

2014-03-15

Cancer is associated with epigenetic (i.e., histone hypoacetylation) and metabolic (i.e., aerobic glycolysis) alterations. Levels of N-acetyl-L-aspartate (NAA), the primary storage form of acetate in the brain, and aspartoacylase (ASPA), the enzyme responsible for NAA catalysis to generate acetate, are reduced in glioma; yet, few studies have investigated acetate as a potential therapeutic agent. This preclinical study sought to test the efficacy of the food additive Triacetin (glyceryl triacetate, GTA) as a novel therapy to increase acetate bioavailability in glioma cells. The growth-inhibitory effects of GTA, compared to the histone deacetylase inhibitor Vorinostat (SAHA), were assessed in established human glioma cell lines (HOG and Hs683 oligodendroglioma, U87 and U251 glioblastoma) and primary tumor-derived glioma stem-like cells (GSCs), relative to an oligodendrocyte progenitor line (Oli-Neu), normal astrocytes, and neural stem cells (NSCs) in vitro. GTA was also tested as a chemotherapeutic adjuvant with temozolomide (TMZ) in orthotopically grafted GSCs. GTA-induced cytostatic growth arrest in vitro comparable to Vorinostat, but, unlike Vorinostat, GTA did not alter astrocyte growth and promoted NSC expansion. GTA alone increased survival of mice engrafted with glioblastoma GSCs and potentiated TMZ to extend survival longer than TMZ alone. GTA was most effective on GSCs with a mesenchymal cell phenotype. Given that GTA has been chronically administered safely to infants with Canavan disease, a leukodystrophy due to ASPA mutation, GTA-mediated acetate supplementation may provide a novel, safe chemotherapeutic adjuvant to reduce the growth of glioma tumors, most notably the more rapidly proliferating, glycolytic and hypoacetylated mesenchymal glioma tumors. © 2013 UICC.

A Method of Mapping Burned Area Using Chinese FengYun-3 MERSI Satellite Data

NASA Astrophysics Data System (ADS)

Shan, T.

2017-12-01

Wildfire is a naturally reoccurring global phenomenon which has environmental and ecological consequences such as effects on the global carbon budget, changes to the global carbon cycle and disruption to ecosystem succession. The information of burned area is significant for post disaster assessment, ecosystems protection and restoration. The Medium Resolution Spectral Imager (MERSI) onboard FENGYUN-3C (FY-3C) has shown good ability for fire detection and monitoring but lacks recognition among researchers. In this study, an automated burned area mapping algorithm was proposed based on FY-3C MERSI data. The algorithm is generally divided into two phases: 1) selection of training pixels based on 1000-m resolution MERSI data, which offers more spectral information through the use of more vegetation indices; and 2) classification: first the region growing method is applied to 1000-m MERSI data to calculate the core burned area and then the same classification method is applied to the 250-m MERSI data set by using the core burned area as a seed to obtain results at a finer spatial resolution. An evaluation of the performance of the algorithm was carried out at two study sites in America and Canada. The accuracy assessment and validation were made by comparing our results with reference results derived from Landsat OLI data. The result has a high kappa coefficient and the lower commission error, indicating that this algorithm can improve the burned area mapping accuracy at the two study sites. It may then be possible to use MERSI and other data to fill the gaps in the imaging of burned areas in the future.

The urban heat island in Rio de Janeiro, Brazil, in the last 30 years using remote sensing data

NASA Astrophysics Data System (ADS)

Peres, Leonardo de Faria; Lucena, Andrews José de; Rotunno Filho, Otto Corrêa; França, José Ricardo de Almeida

2018-02-01

The aim of this work is to study urban heat island (UHI) in Metropolitan Area of Rio de Janeiro (MARJ) based on the analysis of land-surface temperature (LST) and land-use patterns retrieved from Landsat-5/Thematic Mapper (TM), Landsat-7/Enhanced Thematic Mapper Plus (ETM+) and Landsat-8/Operational Land Imager (OLI) and Thermal Infrared Sensors (TIRS) data covering a 32-year period between 1984 and 2015. LST temporal evolution is assessed by comparing the average LST composites for 1984-1999 and 2000-2015 where the parametric Student t-test was conducted at 5% significance level to map the pixels where LST for the more recent period is statistically significantly greater than the previous one. The non-parametric Mann-Whitney-Wilcoxon rank sum test has also confirmed at the same 5% significance level that the more recent period (2000-2015) has higher LST values. UHI intensity between ;urban; and ;rural/urban low density; (;vegetation;) areas for 1984-1999 and 2000-2015 was established and confirmed by both parametric and non-parametric tests at 1% significance level as 3.3 °C (5.1 °C) and 4.4 °C (7.1 °C), respectively. LST has statistically significantly (p-value < 0.01) increased over time in two of three land cover classes (;urban; and ;urban low density;), respectively by 1.9 °C and 0.9 °C, except in ;vegetation; class. A spatial analysis was also performed to identify the urban pixels within MARJ where UHI is more intense by subtracting the LST of these pixels from the LST mean value of ;vegetation; land-use class.

Estimating Forest Aboveground Biomass by Combining Optical and SAR Data: A Case Study in Genhe, Inner Mongolia, China

PubMed Central

Shao, Zhenfeng; Zhang, Linjing

2016-01-01

Estimation of forest aboveground biomass is critical for regional carbon policies and sustainable forest management. Passive optical remote sensing and active microwave remote sensing both play an important role in the monitoring of forest biomass. However, optical spectral reflectance is saturated in relatively dense vegetation areas, and microwave backscattering is significantly influenced by the underlying soil when the vegetation coverage is low. Both of these conditions decrease the estimation accuracy of forest biomass. A new optical and microwave integrated vegetation index (VI) was proposed based on observations from both field experiments and satellite (Landsat 8 Operational Land Imager (OLI) and RADARSAT-2) data. According to the difference in interaction between the multispectral reflectance and microwave backscattering signatures with biomass, the combined VI (COVI) was designed using the weighted optical optimized soil-adjusted vegetation index (OSAVI) and microwave horizontally transmitted and vertically received signal (HV) to overcome the disadvantages of both data types. The performance of the COVI was evaluated by comparison with those of the sole optical data, Synthetic Aperture Radar (SAR) data, and the simple combination of independent optical and SAR variables. The most accurate performance was obtained by the models based on the COVI and optical and microwave optimal variables excluding OSAVI and HV, in combination with a random forest algorithm and the largest number of reference samples. The results also revealed that the predictive accuracy depended highly on the statistical method and the number of sample units. The validation indicated that this integrated method of determining the new VI is a good synergistic way to combine both optical and microwave information for the accurate estimation of forest biomass. PMID:27338378

Genetic analysis of hispanic individuals with cystic fibrosis

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

Grebe, T.A.; Doane, W.W.; Norman, R.A.

1994-03-01

The authors have performed molecular genetic analysis of Hispanic individuals with cystic fibrosis (CF) in the southwestern United States. Of 129 CF chromosomes analyzed, oly 46% (59/129) carry [Delta]F508. The G542X mutation was found on 5% (7/129) of CF chromosomes. The 3849+10kbC[yields]T mutation, detected primarily in Ashkenazi Jews, was present on 2% (3/129). R1162X and R334W, mutations identified in Spain and Italy, each occurred on 1.6% (2/129) of CF chromosomes. W1282X and R553X were each detected once. G551D and N1303K were not found. Overall, screening for 22 or more mutations resulted in detection of only 58% of CF transmembrane conductancemore » regulator gene mutations among Hispanic individuals. Analysis of KM19/XV2c haplotypes revealed an unusual distribution. Although the majority of [Delta]508 mutations are on chromosomes of B haplotypes, the other CF mutations are on A and C haplotypes at higher-than-expected frequencies. These genetic analysis demonstrate significant differences between Hispanic individuals with CF and those of the general North American population. Assessment of carrier/affected risk in Hispanic CF individuals cannot, therefore, be based on the mutation frequencies found through studies of the general population but must be adjusted to better reflect the genetic makeup of this ethnic group. Further studies are necessary to identify the causative mutation(s) in this population and to better delineate genotype/phenotype correlations. These will enable counselors to provide more accurate genetic counseling. 22 refs., 2 tabs.« less

Tuning of Thermal Stability in Layered Li(Ni x Mn y Co z )O 2

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

Zheng, Jiaxin; Liu, Tongchao; Hu, Zongxiang

2016-09-19

Understanding and further designing new layered Li(Ni xMn yCo z)O 2 (NMC) (x + y + z = 1) materials with optimized thermal stability is important to rechargeable Li batteries (LIBs) for electrical vehicles (EV). Using ab initio calculations combined with experiments, we clarified how the thermal stability of NMC materials can be tuned by the most unstable oxygen, which is determined by the local coordination structure unit (LCSU) of oxygen (TM(Ni, Mn, Co) 3-O-Li 3-x'): each O atom bonds with three transition metals (TM) from the TM-layer and three to zero Li from fully discharged to charged states frommore » the Li-layer. Under this model, how the lithium content, valence states of Ni, contents of Ni, Mn, and Co, and Ni/Li disorder to tune the thermal stability of NMC materials by affecting the sites, content, and the release temperature of the most unstable oxygen is proposed. The synergistic effect between Li vacancies and raised valence state of Ni during delithiation process can aggravate instability of oxygen, and oxygen coordinated with more nickel (especially with high valence state) in LSCU becomes more unstable at a fixed delithiation state. The Ni/Li mixing would decrease the thermal stability of the “NiMn” group NMC materials but benefit the thermal stability of “Ni-rich” group, because the Ni in the Li layer would form 180° Ni-O-Ni super exchange chains in “Ni-rich” NMC materials. Mn and Co doping can tune the initial valence state of Ni, local coordination environment of oxygen, and the Ni/Li disorder, thus to tune the thermal stability directly.« less

Greenup and evapotranspiration following the Minute 319 pulse flow to Mexico: An analysis using Landsat 8 Normalized Difference Vegetation Index (NDVI) data

USGS Publications Warehouse

Jarchow, Christopher J.; Nagler, Pamela L.; Glenn, Edward P.

2017-01-01

In the southwestern U.S., many riparian ecosystems have been altered by dams, water diversions, and other anthropogenic activities. This is particularly true of the Colorado River, where numerous dams and agricultural diversions have affected this water course, especially south of the U.S.–Mexico border. In the spring of 2014, 130 million cubic meters of water was released to the lower Colorado River Delta in Mexico. To understand the impact of this pulse flow release on vegetation in the delta’s riparian corridor, we analyzed a modified form of Landsat 8 Operational Land Imager (OLI) Normalized Difference Vegetation Index (NDVI*) data. We assessed greenup during the growing period and estimated actual evapotranspiration (ETa) for the period prior to (yr. 2013) and following (i.e., yr. 2014 and 2015) the pulse flow. We found a significant increase in NDVI* from 2013 to 2014 (P < 0.05) and a decrease from 2014 to 2015; however, 2015 levels were still significantly higher than in 2013. ETa was also higher in 2014 vs. 2013, with an estimated 74.5 million cubic meters in 2013 and 88.9 in 2014. The most intense greening occurred in the zone of inundation but also extended into the non-flooded part of the riparian zone, indicating replenishment of groundwater. These findings suggest the peak response by vegetation to the flow lasted about one year, followed by a decrease in NDVI*. As a long term solution to the declining condition of vegetation, additional pulse releases are likely needed for restoration and survival of riparian plant communities in the Colorado River Delta.

Implication of relationship between natural impacts and land use/land cover (LULC) changes of urban area in Mongolia

NASA Astrophysics Data System (ADS)

Gantumur, Byambakhuu; Wu, Falin; Zhao, Yan; Vandansambuu, Battsengel; Dalaibaatar, Enkhjargal; Itiritiphan, Fareda; Shaimurat, Dauryenbyek

2017-10-01

Urban growth can profoundly alter the urban landscape structure, ecosystem processes, and local climates. Timely and accurate information on the status and trends of urban ecosystems is critical to develop strategies for sustainable development and to improve the urban residential environment and living quality. Ulaanbaatar city was urbanized very rapidly caused by herders and farmers, many of them migrating from rural places, have played a big role in this urban expansion (sprawl). Today, 1.3 million residents for about 40% of total population are living in the Ulaanbaatar region. Those human activities influenced stronger to green environments. Therefore, the aim of this study is determined to change detection of land use/land cover (LULC) and estimating their areas for the trend of future by remote sensing and statistical methods. The implications of analysis were provided by change detection methods of LULC, remote sensing spectral indices including normalized difference vegetation index (NDVI), normalized difference water index (NDWI) and normalized difference built-up index (NDBI). In addition, it can relate to urban heat island (UHI) provided by Land surface temperature (LST) with local climate issues. Statistical methods for image processing used to define relations between those spectral indices and change detection images and regression analysis for time series trend in future. Remote sensing data are used by Landsat (TM/ETM+/OLI) satellite images over the period between 1990 and 2016 by 5 years. The advantages of this study are very useful remote sensing approaches with statistical analysis and important to detecting changes of LULC. The experimental results show that the LULC changes can image on the present and after few years and determined relations between impacts of environmental conditions.

[Characteristics of temporal-spatial differentiation in landscape pattern vulnerability in Nansihu Lake wetland, China.

PubMed

Liang, Jia Xin; Li, Xin Ju

2018-02-01

With remote sensing images from 1985, 2000 Lantsat 5 TM and 2015 Lantsat 8 OLI as data sources, we tried to select the suitable research scale and examine the temporal-spatial diffe-rentiation with such scale in the Nansihu Lake wetland by using landscape pattern vulnerability index constructed by sensitivity index and adaptability index, and combined with space statistics such as semivariogram and spatial autocorrelation. The results showed that 1 km × 1 km equidistant grid was the suitable research scale, which could eliminate the influence of spatial heterogeneity induced by random factors. From 1985 to 2015, the landscape pattern vulnerability in the Nansihu Lake wetland deteriorated gradually. The high-risk area of landscape pattern vulnerability dramatically expanded with time. The spatial heterogeneity of landscape pattern vulnerability increased, and the influence of non-structural factors on landscape pattern vulnerability strengthened. Spatial variability affected by spatial autocorrelation slightly weakened. Landscape pattern vulnerability had strong general spatial positive correlation, with the significant form of spatial agglomeration. The positive spatial autocorrelation continued to increase and the phenomenon of spatial concentration was more and more obvious over time. The local autocorrelation mainly based on high-high accumulation zone and low-low accumulation zone had stronger spatial autocorrelation among neighboring space units. The high-high accumulation areas showed the strongest level of significance, and the significant level of low-low accumulation zone increased with time. Natural factors, such as temperature and precipitation, affected water-level and landscape distribution, and thus changed the landscape patterns vulnerability of Nansihu Lake wetland. The dominant driver for the deterioration of landscape patterns vulnerability was human activities, including social economy activity and policy system.

Semi-Automatic Normalization of Multitemporal Remote Images Based on Vegetative Pseudo-Invariant Features

PubMed Central

Garcia-Torres, Luis; Caballero-Novella, Juan J.; Gómez-Candón, David; De-Castro, Ana Isabel

2014-01-01

A procedure to achieve the semi-automatic relative image normalization of multitemporal remote images of an agricultural scene called ARIN was developed using the following procedures: 1) defining the same parcel of selected vegetative pseudo-invariant features (VPIFs) in each multitemporal image; 2) extracting data concerning the VPIF spectral bands from each image; 3) calculating the correction factors (CFs) for each image band to fit each image band to the average value of the image series; and 4) obtaining the normalized images by linear transformation of each original image band through the corresponding CF. ARIN software was developed to semi-automatically perform the ARIN procedure. We have validated ARIN using seven GeoEye-1 satellite images taken over the same location in Southern Spain from early April to October 2010 at an interval of approximately 3 to 4 weeks. The following three VPIFs were chosen: citrus orchards (CIT), olive orchards (OLI) and poplar groves (POP). In the ARIN-normalized images, the range, standard deviation (s. d.) and root mean square error (RMSE) of the spectral bands and vegetation indices were considerably reduced compared to the original images, regardless of the VPIF or the combination of VPIFs selected for normalization, which demonstrates the method’s efficacy. The correlation coefficients between the CFs among VPIFs for any spectral band (and all bands overall) were calculated to be at least 0.85 and were significant at P = 0.95, indicating that the normalization procedure was comparably performed regardless of the VPIF chosen. ARIN method was designed only for agricultural and forestry landscapes where VPIFs can be identified. PMID:24604031

Acetate supplementation induces growth arrest of NG2/PDGFRα-positive oligodendroglioma-derived tumor-initiating cells.

PubMed

Long, Patrick M; Tighe, Scott W; Driscoll, Heather E; Moffett, John R; Namboodiri, Aryan M A; Viapiano, Mariano S; Lawler, Sean E; Jaworski, Diane M

2013-01-01

Cancer is associated with globally hypoacetylated chromatin and considerable attention has recently been focused on epigenetic therapies. N-acetyl-L-aspartate (NAA), the primary storage form of acetate in the brain, and aspartoacylase (ASPA), the enzyme responsible for NAA catalysis to generate acetate and ultimately acetyl-Coenzyme A for histone acetylation, are reduced in oligodendroglioma. The short chain triglyceride glyceryl triacetate (GTA), which increases histone acetylation and inhibits histone deacetylase expression, has been safely used for acetate supplementation in Canavan disease, a leukodystrophy due to ASPA mutation. We demonstrate that GTA induces cytostatic G0 growth arrest of oligodendroglioma-derived cells in vitro, without affecting normal cells. Sodium acetate, at doses comparable to that generated by complete GTA catalysis, but not glycerol also promoted growth arrest, whereas long chain triglycerides promoted cell growth. To begin to elucidate its mechanism of action, the effects of GTA on ASPA and acetyl-CoA synthetase protein levels and differentiation of established human oligodendroglioma cells (HOG and Hs683) and primary tumor-derived oligodendroglioma cells that exhibit some features of cancer stem cells (grade II OG33 and grade III OG35) relative to an oligodendrocyte progenitor line (Oli-Neu) were examined. The nuclear localization of ASPA and acetyl-CoA synthetase-1 in untreated cells was regulated during the cell cycle. GTA-mediated growth arrest was not associated with apoptosis or differentiation, but increased expression of acetylated proteins. Thus, GTA-mediated acetate supplementation may provide a safe, novel epigenetic therapy to reduce the growth of oligodendroglioma cells without affecting normal neural stem or oligodendrocyte progenitor cell proliferation or differentiation.

Triacetin-based acetate supplementation as a chemotherapeutic adjuvant therapy in glioma

PubMed Central

Tsen, Andrew R.; Long, Patrick M.; Driscoll, Heather E.; Davies, Matthew T.; Teasdale, Benjamin A.; Penar, Paul L.; Pendlebury, William W.; Spees, Jeffrey L.; Lawler, Sean E.; Viapiano, Mariano S.; Jaworski, Diane M.

2013-01-01

Cancer is associated with epigenetic (i.e., histone hypoacetylation) and metabolic (i.e., aerobic glycolysis) alterations. Levels of N-acetyl-L-aspartate (NAA), the primary storage form of acetate in the brain, and aspartoacylase (ASPA), the enzyme responsible for NAA catalysis to generate acetate, are reduced in glioma; yet, few studies have investigated acetate as a potential therapeutic agent. This preclinical study sought to test the efficacy of the food additive Triacetin (glyceryl triacetate, GTA) as a novel therapy to increase acetate bioavailability in glioma cells. The growth-inhibitory effects of GTA, compared to the histone deacetylase inhibitor Vorinostat (SAHA), were assessed in established human glioma cell lines (HOG and Hs683 oligodendroglioma, U87 and U251 glioblastoma) and primary tumor-derived glioma stem-like cells (GSCs), relative to an oligodendrocyte progenitor line (Oli-Neu), normal astrocytes, and neural stem cells (NSCs) in vitro. GTA was also tested as a chemotherapeutic adjuvant with temozolomide (TMZ) in orthotopically grafted GSCs. GTA induced cytostatic growth arrest in vitro comparable to Vorinostat, but, unlike Vorinostat, GTA did not alter astrocyte growth and promoted NSC expansion. GTA alone increased survival of mice engrafted with glioblastoma GSCs and potentiated TMZ to extend survival longer than TMZ alone. GTA was most effective on GSCs with a mesenchymal cell phenotype. Given that GTA has been chronically administered safely to infants with Canavan disease, a leukodystrophy due to ASPA mutation, GTA-mediated acetate supplementation may provide a novel, safe chemotherapeutic adjuvant to reduce the growth of glioma tumors, most notably the more rapidly proliferating, glycolytic, and hypoacetylated mesenchymal glioma tumors. PMID:23996800

Acetate Supplementation Induces Growth Arrest of NG2/PDGFRα-Positive Oligodendroglioma-Derived Tumor-Initiating Cells

PubMed Central

Long, Patrick M.; Tighe, Scott W.; Driscoll, Heather E.; Moffett, John R.; Namboodiri, Aryan M. A.; Viapiano, Mariano S.; Lawler, Sean E.; Jaworski, Diane M.

2013-01-01

Cancer is associated with globally hypoacetylated chromatin and considerable attention has recently been focused on epigenetic therapies. N-acetyl-L-aspartate (NAA), the primary storage form of acetate in the brain, and aspartoacylase (ASPA), the enzyme responsible for NAA catalysis to generate acetate and ultimately acetyl-Coenzyme A for histone acetylation, are reduced in oligodendroglioma. The short chain triglyceride glyceryl triacetate (GTA), which increases histone acetylation and inhibits histone deacetylase expression, has been safely used for acetate supplementation in Canavan disease, a leukodystrophy due to ASPA mutation. We demonstrate that GTA induces cytostatic G0 growth arrest of oligodendroglioma-derived cells in vitro, without affecting normal cells. Sodium acetate, at doses comparable to that generated by complete GTA catalysis, but not glycerol also promoted growth arrest, whereas long chain triglycerides promoted cell growth. To begin to elucidate its mechanism of action, the effects of GTA on ASPA and acetyl-CoA synthetase protein levels and differentiation of established human oligodendroglioma cells (HOG and Hs683) and primary tumor-derived oligodendroglioma cells that exhibit some features of cancer stem cells (grade II OG33 and grade III OG35) relative to an oligodendrocyte progenitor line (Oli-Neu) were examined. The nuclear localization of ASPA and acetyl-CoA synthetase-1 in untreated cells was regulated during the cell cycle. GTA-mediated growth arrest was not associated with apoptosis or differentiation, but increased expression of acetylated proteins. Thus, GTA-mediated acetate supplementation may provide a safe, novel epigenetic therapy to reduce the growth of oligodendroglioma cells without affecting normal neural stem or oligodendrocyte progenitor cell proliferation or differentiation. PMID:24278309

Accuracy of land use change detection using support vector machine and maximum likelihood techniques for open-cast coal mining areas.

PubMed

Karan, Shivesh Kishore; Samadder, Sukha Ranjan

2016-08-01

One objective of the present study was to evaluate the performance of support vector machine (SVM)-based image classification technique with the maximum likelihood classification (MLC) technique for a rapidly changing landscape of an open-cast mine. The other objective was to assess the change in land use pattern due to coal mining from 2006 to 2016. Assessing the change in land use pattern accurately is important for the development and monitoring of coalfields in conjunction with sustainable development. For the present study, Landsat 5 Thematic Mapper (TM) data of 2006 and Landsat 8 Operational Land Imager (OLI)/Thermal Infrared Sensor (TIRS) data of 2016 of a part of Jharia Coalfield, Dhanbad, India, were used. The SVM classification technique provided greater overall classification accuracy when compared to the MLC technique in classifying heterogeneous landscape with limited training dataset. SVM exceeded MLC in handling a difficult challenge of classifying features having near similar reflectance on the mean signature plot, an improvement of over 11 % was observed in classification of built-up area, and an improvement of 24 % was observed in classification of surface water using SVM; similarly, the SVM technique improved the overall land use classification accuracy by almost 6 and 3 % for Landsat 5 and Landsat 8 images, respectively. Results indicated that land degradation increased significantly from 2006 to 2016 in the study area. This study will help in quantifying the changes and can also serve as a basis for further decision support system studies aiding a variety of purposes such as planning and management of mines and environmental impact assessment.

Estimation the Amount of Oil Palm Trees Production Using Remote Sensing Technique

NASA Astrophysics Data System (ADS)

Fitrianto, A. C.; Tokimatsu, K.; Sufwandika, M.

2017-12-01

Currently, fossil fuels were used as the main source of power supply to generate energy including electricity. Depletion in the amount of fossil fuels has been causing the increasing price of crude petroleum and the demand for alternative energy which is renewable and environment-friendly and it is defined from vegetable oils such palm oil, rapeseed and soybean. Indonesia known as the big palm oil producer which is the largest agricultural industry with total harvested oil palm area which is estimated grew until 8.9 million ha in 2015. On the other hand, lack of information about the age of oil palm trees and changes also their spatial distribution is mainly problem for energy planning. This research conducted to estimate fresh fruit bunch (FFB) of oil palm and their distribution using remote sensing technique. Cimulang oil palm plantation was choose as study area. First step, estimated the age of oil palm trees based on their canopy density as the result from Landsat 8 OLI analysis and classified into five class. From this result, we correlated oil palm age with their average FFB production per six months and classified into seed (0-3 years, 0kg), young (4-8 years, 68.77kg), teen (9-14 years, 109.08kg), and mature (14-25 years, 73.91kg). The result from satellite image analysis shows if Cimulang plantation area consist of teen old oil palm trees that it is covers around 81.5% of that area, followed by mature oil palm trees with 18.5% or corresponding to 100 hectares and have total production of FFB every six months around 7,974,787.24 kg.

Multi-temporal Land Use Mapping of Coastal Wetlands Area using Machine Learning in Google Earth Engine

NASA Astrophysics Data System (ADS)

Farda, N. M.

2017-12-01

Coastal wetlands provide ecosystem services essential to people and the environment. Changes in coastal wetlands, especially on land use, are important to monitor by utilizing multi-temporal imagery. The Google Earth Engine (GEE) provides many machine learning algorithms (10 algorithms) that are very useful for extracting land use from imagery. The research objective is to explore machine learning in Google Earth Engine and its accuracy for multi-temporal land use mapping of coastal wetland area. Landsat 3 MSS (1978), Landsat 5 TM (1991), Landsat 7 ETM+ (2001), and Landsat 8 OLI (2014) images located in Segara Anakan lagoon are selected to represent multi temporal images. The input for machine learning are visible and near infrared bands, PCA band, invers PCA bands, bare soil index, vegetation index, wetness index, elevation from ASTER GDEM, and GLCM (Harralick) texture, and also polygon samples in 140 locations. There are 10 machine learning algorithms applied to extract coastal wetlands land use from Landsat imagery. The algorithms are Fast Naive Bayes, CART (Classification and Regression Tree), Random Forests, GMO Max Entropy, Perceptron (Multi Class Perceptron), Winnow, Voting SVM, Margin SVM, Pegasos (Primal Estimated sub-GrAdient SOlver for Svm), IKPamir (Intersection Kernel Passive Aggressive Method for Information Retrieval, SVM). Machine learning in Google Earth Engine are very helpful in multi-temporal land use mapping, the highest accuracy for land use mapping of coastal wetland is CART with 96.98 % Overall Accuracy using K-Fold Cross Validation (K = 10). GEE is particularly useful for multi-temporal land use mapping with ready used image and classification algorithms, and also very challenging for other applications.

Vegetation role in controlling the ecoenvironmental conditions for sustainable urban environments: a comparison of Beijing and Islamabad

NASA Astrophysics Data System (ADS)

Naeem, Shahid; Cao, Chunxiang; Waqar, Mirza Muhammad; Wei, Chen; Acharya, Bipin Kumar

2018-01-01

The rapid increase in urbanization due to population growth leads to the degradation of vegetation in major cities. This study investigated the spatial patterns of the ecoenvironmental conditions of inhabitants of two distinct Asian capital cities, Beijing of China and Islamabad of Pakistan, by utilizing Earth observation data products. The significance of urban vegetation for the cooling effect was studied in local climate zones, i.e., urban, suburban, and rural areas within 1-km2 quantiles. Landsat-8 (OLI) and Gaofen-1 satellite imagery were used to assess vegetation cover and land surface temperature, while population datasets were used to evaluate environmental impact. Comparatively, a higher cooling effect of vegetation presence was observed in rural and suburban zones of Beijing as compared to Islamabad, while the urban zone of Islamabad was found comparatively cooler than Beijing's urban zone. The urban thermal field variance index calculated from satellite imagery was ranked into the ecological evaluation index. The worst ecoenvironmental conditions were found in urban zones of both cities where the fraction of vegetation is very low. Meanwhile, this condition is more serious in Beijing, as more than 90% of the total population is living under the worst ecoenvironment conditions, while only 7% of the population is enjoying comfortable conditions. Ecoenvironmental conditions of Islamabad are comparatively better than Beijing where ˜61% of the total population live under the worst ecoenvironmental conditions, and ˜24% are living under good conditions. Thus, Islamabad at this early growth stage can learn from Beijing's ecoenvironmental conditions to improve the quality of living by controlling the associated factors in the future.

Potentials and limitations of remote fire monitoring in protected areas.

PubMed

Dos Santos, João Flávio Costa; Romeiro, Joyce Machado Nunes; de Assis, José Batuíra; Torres, Fillipe Tamiozzo Pereira; Gleriani, José Marinaldo

2018-03-01

Protected areas (PAs) play an important role in maintaining the biodiversity and ecological processes of the site. One of the greatest challenges for the PA management in several biomes in the world is wildfires. The objective of this work was to evaluate the potentialities and limitations of the use of data obtained by orbital remote sensing in the monitoring fire occurrence in PAs. Fire Occurrence Records (FORs) were analyzed in Serra do Brigadeiro State Park, Minas Gerais, Brazil, from 2007 to 2015, using photo interpreted data from TM, ETM + and OLI sensors of the Landsat series and the Hot Spot Database (HSD) from the Brazilian Institute of Space Research - INPE. It was also observed the time of permanence of the scar left by fire on the landscape, through the multitemporal analysis of the behavior of NDVI (Normalized Difference Vegetation Index) and NBR (Normalized Burn Ratio) indexes, before and after the occurrence. The greatest limitation found for the orbital remote monitoring was the presence of clouds in the passage of the sensor in dates close to the occurrence of the fires. The burned area identified by photo interpretation was 54.9% less than the area contained in the FOR. Although the HSD reported fire occurrences in the buffer zone (up to 10km from the Park), no FORs were found at a distance greater than 1100m from the boundaries of the PA. As the main potential of remote sensing, the possibility of identifying burned areas throughout the park and surroundings is highlighted, with low costs and greater accuracy. Copyright © 2017 Elsevier B.V. All rights reserved.

Satellite infrared imagery for thermal plume contamination monitoring in coastal ecosystem of Cernavoda NPP

NASA Astrophysics Data System (ADS)

Zoran, M. A.; Zoran, Liviu Florin V.; Dida, Adrian I.

2017-10-01

Satellite remote sensing is an important tool for spatio-temporal analysis and surveillance of NPP environment, thermal heat waste of waters being a major concern in many coastal ecosystems involving nuclear power plants. As a test case the adopted methodology was applied for 700x2 MW Cernavoda nuclear power plant (NPP) located in the South-Eastern part of Romania, which discharges warm water affecting coastal ecology. The thermal plume signatures in the NPP hydrological system have been investigated based on TIR (Thermal Infrared) spectral bands of NOAA AVHRR, Landsat TM/ETM+/OLI, and MODIS Terra/Aqua time series satellite data during 1990-2016 period. If NOAA AVHRR data proved the general pattern and extension of the thermal plume signature in Danube river and Black Sea coastal areas, Landsat TM/ETM and MODIS data used for WST (Water Surface Temperature) change detection, mapping and monitoring provided enhanced information about the plume shape, dimension and direction of dispersion in these waters. Thermal discharge from two nuclear reactors cooling is dissipated as waste heat in Danube-Black -Sea Channel and Danube River. From time-series analysis of satellite data during period 1990-2016 was found that during the winter season thermal plume was localized to an area of a few km of NPP, and the mean temperature difference between the plume and non-plume areas was about 1.7 oC. During summer and fall, derived mean temperature difference between the plume and non-plume areas was of about 1.3°C and thermal plume area was extended up to 5- 10 km far along Danube Black Sea Channel.

Understanding the relationship between vegetation phenology and productivity across key dryland ecosystem types through the integration of PhenoCam, satellite, and eddy covariance data

NASA Astrophysics Data System (ADS)

Yan, D.; Scott, R. L.; Moore, D. J.; Biederman, J. A.; Smith, W. K.

2017-12-01

Land surface phenology (LSP) - defined as remotely sensed seasonal variations in vegetation greenness - is intrinsically linked to seasonal carbon uptake, and is thus commonly used as a proxy for vegetation productivity (gross primary productivity; GPP). Yet, the relationship between LSP and GPP remains uncertain, particularly for understudied dryland ecosystems characterized by relatively large spatial and temporal variability. Here, we explored the relationship between LSP and the phenology of GPP for three dominant dryland ecosystem types, and we evaluated how these relationships change as a function of spatial and temporal scale. We focused on three long-term dryland eddy covariance flux tower sites: Walnut Gulch Lucky Hills Shrubland (WHS), Walnut Gulch Kendall Grassland (WKG), and Santa Rita Mesquite (SRM). We analyzed daily canopy-level, 16-day 30m, and 8-day 500m time series of greenness indices from PhenoCam, Landsat 7 ETM+/Landsat 8 OLI, and MODIS, respectively. We first quantified the impact of spatial scale by temporally resampling canopy-level PhenoCam, 30m Landsat, and 500m MODIS to 16-day intervals and then comparing against flux tower GPP estimates. We next quantified the impact of temporal scale by spatially resampling daily PhenoCam, 16-day Landsat, and 8-day MODIS to 500m time series and then comparing against flux tower GPP estimates. We find evidence of critical periods of decoupling between LSP and the phenology of GPP that vary according to the spatial and temporal scale, and as a function of ecosystem type. Our results provide key insight into dryland LSP and GPP dynamics that can be used in future efforts to improve ecosystem process models and satellite-based vegetation productivity algorithms.

One-dimensional nanostructured materials for lithium-ion battery and supercapacitor electrodes

NASA Astrophysics Data System (ADS)

Chan, Candace Kay

cycling performance of the SiNWs in different electrolytes, with various surface modifications and coatings, and other experimental parameters were evaluated. The electrochemical reaction of GeNWs with lithium resulted in capacities of ˜1000 mAh/g for tens of cycles. The GeNWs were also observed to become amorphous after the first charge. Interestingly, very large irreversible capacities were observed in the GeNWs, indicating surface instabilities or reactivity with the electrolyte. To passivate the surface, a thin layer of amorphous Si was used to coat the GeNWs and make Ge-Si coreshell nanowires. This passivation helped to reduce the irreversibly capacity loss and gave reversible capacities typical for the GeNWs. Two positive electrode materials for Li-ion batteries were synthesized in nano-morphologies and characterized. Transformation of layered structured V2O5 nanoribbons into the fully lithiated o-Li 3V2O5 phase was found to depend not only on the width but also the thickness of the nanoribbons. For the first time, complete delithiation of o-Li3V2O5 back to the single-crystalline, pristine V2O5 nanoribbon was observed, indicating a 30% higher energy density. Nanostructured BiOCl, a conversion material, was also synthesized and characterized for its Li insertion properties. Networks of silver nanowires (AgNWs) and single-walled carbon nanotubes (SWNTs) were explored as highly conducting, high surface area, and printable materials for flexible, light-weight supercapacitors. Use of the solution-processible AgNWs and SWNTs, as well as a polymer electrolyte, facilitated the fabrication of an entirely printable device on plastic substrates. The devices showed promising results for high energy and power density supercapacitors, with energy and power densities reaching 24 Wh/kg and 42 kW/kg for the AgNW/SWNT composite.

Detecting moisture status of pecan orchards and the potential of remotely-sensed surface reflectance data

NASA Astrophysics Data System (ADS)

Othman, Yahia Abdelrahman

Demand for New Mexico's limited water resources coupled with periodic drought has increased the need to schedule irrigation of pecan orchards based on tree water status. The overall goal of this research was to develop advanced tree water status sensing techniques to optimize irrigation scheduling of pecan orchards. To achieve this goal, I conducted three studies in the La Mancha and Leyendecker orchards, both mature pecan orchards located in the Mesilla Valley, New Mexico. In the first study, I screened leaf-level physiological changes that occurred during cyclic irrigation to determine parameters that best represented changes in plant moisture status. Then, I linked plant physiological changes to remotely-sensed surface reflectance data derived from Landsat Thematic Mapper (TM) and Enhanced Thematic Mapper (ETM+). In the second study, I assessed the impact of water deficits that developed during the flood irrigation dry-down cycles on photosynthesis (A) and gas exchange and established preliminary water deficit thresholds of midday stem water potential (Psi smd) critical to A and gas exchange of pecans. In a third study, I investigated whether hyperspectral data obtained from a handheld spectroradiometer and multispectral remotely-sensed data derived from Landsat 7 ETM+ and Landsat 8 Operational Land Imager (OLI) could detect moisture status in pecans during cyclic flood irrigations. I conducted the first study simultaneously in both orchards. Leaf-level physiological responses and remotely-sensed surface reflectance data were collected from trees that were either well watered or in water deficit. Midday stem water potential was the best leaf-level physiological response to detect moisture status in pecans. Multiple linear regression between Psismd and vegetation indices revealed a significant relationship (R 2 = 0.54) in both orchards. Accordingly, I concluded that remotely-sensed multispectral data form Landsat TMETM+ holds promise for detecting the moisture

Modelling Biophysical Parameters of Maize Using Landsat 8 Time Series

NASA Astrophysics Data System (ADS)

Dahms, Thorsten; Seissiger, Sylvia; Conrad, Christopher; Borg, Erik

2016-06-01

Open and free access to multi-frequent high-resolution data (e.g. Sentinel - 2) will fortify agricultural applications based on satellite data. The temporal and spatial resolution of these remote sensing datasets directly affects the applicability of remote sensing methods, for instance a robust retrieving of biophysical parameters over the entire growing season with very high geometric resolution. In this study we use machine learning methods to predict biophysical parameters, namely the fraction of absorbed photosynthetic radiation (FPAR), the leaf area index (LAI) and the chlorophyll content, from high resolution remote sensing. 30 Landsat 8 OLI scenes were available in our study region in Mecklenburg-Western Pomerania, Germany. In-situ data were weekly to bi-weekly collected on 18 maize plots throughout the summer season 2015. The study aims at an optimized prediction of biophysical parameters and the identification of the best explaining spectral bands and vegetation indices. For this purpose, we used the entire in-situ dataset from 24.03.2015 to 15.10.2015. Random forest and conditional inference forests were used because of their explicit strong exploratory and predictive character. Variable importance measures allowed for analysing the relation between the biophysical parameters with respect to the spectral response, and the performance of the two approaches over the plant stock evolvement. Classical random forest regression outreached the performance of conditional inference forests, in particular when modelling the biophysical parameters over the entire growing period. For example, modelling biophysical parameters of maize for the entire vegetation period using random forests yielded: FPAR: R² = 0.85; RMSE = 0.11; LAI: R² = 0.64; RMSE = 0.9 and chlorophyll content (SPAD): R² = 0.80; RMSE=4.9. Our results demonstrate the great potential in using machine-learning methods for the interpretation of long-term multi-frequent remote sensing datasets to model

Multifunctional glial support by Semper cells in the Drosophila retina

PubMed Central

Charlton-Perkins, Mark A.

2017-01-01

Glial cells play structural and functional roles central to the formation, activity and integrity of neurons throughout the nervous system. In the retina of vertebrates, the high energetic demand of photoreceptors is sustained in part by Müller glia, an intrinsic, atypical radial glia with features common to many glial subtypes. Accessory and support glial cells also exist in invertebrates, but which cells play this function in the insect retina is largely undefined. Using cell-restricted transcriptome analysis, here we show that the ommatidial cone cells (aka Semper cells) in the Drosophila compound eye are enriched for glial regulators and effectors, including signature characteristics of the vertebrate visual system. In addition, cone cell-targeted gene knockdowns demonstrate that such glia-associated factors are required to support the structural and functional integrity of neighboring photoreceptors. Specifically, we show that distinct support functions (neuronal activity, structural integrity and sustained neurotransmission) can be genetically separated in cone cells by down-regulating transcription factors associated with vertebrate gliogenesis (pros/Prox1, Pax2/5/8, and Oli/Olig1,2, respectively). Further, we find that specific factors critical for glial function in other species are also critical in cone cells to support Drosophila photoreceptor activity. These include ion-transport proteins (Na/K+-ATPase, Eaat1, and Kir4.1-related channels) and metabolic homeostatic factors (dLDH and Glut1). These data define genetically distinct glial signatures in cone/Semper cells that regulate their structural, functional and homeostatic interactions with photoreceptor neurons in the compound eye of Drosophila. In addition to providing a new high-throughput model to study neuron-glia interactions, the fly eye will further help elucidate glial conserved "support networks" between invertebrates and vertebrates. PMID:28562601

An improved active contour model for glacial lake extraction

NASA Astrophysics Data System (ADS)

Zhao, H.; Chen, F.; Zhang, M.

2017-12-01

Active contour model is a widely used method in visual tracking and image segmentation. Under the driven of objective function, the initial curve defined in active contour model will evolve to a stable condition - a desired result in given image. As a typical region-based active contour model, C-V model has a good effect on weak boundaries detection and anti noise ability which shows great potential in glacial lake extraction. Glacial lake is a sensitive indicator for reflecting global climate change, therefore accurate delineate glacial lake boundaries is essential to evaluate hydrologic environment and living environment. However, the current method in glacial lake extraction mainly contains water index method and recognition classification method are diffcult to directly applied in large scale glacial lake extraction due to the diversity of glacial lakes and masses impacted factors in the image, such as image noise, shadows, snow and ice, etc. Regarding the abovementioned advantanges of C-V model and diffcults in glacial lake extraction, we introduce the signed pressure force function to improve the C-V model for adapting to processing of glacial lake extraction. To inspect the effect of glacial lake extraction results, three typical glacial lake development sites were selected, include Altai mountains, Centre Himalayas, South-eastern Tibet, and Landsat8 OLI imagery was conducted as experiment data source, Google earth imagery as reference data for varifying the results. The experiment consequence suggests that improved active contour model we proposed can effectively discriminate the glacial lakes from complex backgound with a higher Kappa Coefficient - 0.895, especially in some small glacial lakes which belongs to weak information in the image. Our finding provide a new approach to improved accuracy under the condition of large proportion of small glacial lakes and the possibility for automated glacial lake mapping in large-scale area.

Effects of Fine-Scale Landscape Variability on Satellite-Derived Land Surface Temperature Products Over Sparse Vegetation Canopies

NASA Astrophysics Data System (ADS)

Powell, R. L.; Goulden, M.; Peterson, S.; Roberts, D. A.; Still, C. J.

2015-12-01

Temperature is a primary environmental control on biological systems and processes at a range of spatial and temporal scales, from controlling biochemical processes such as photosynthesis to influencing continental-scale species distribution. The Landsat satellite series provides a long record (since the mid-1980s) of relatively high spatial resolution thermal infrared (TIR) imagery, from which we derive land surface temperature (LST) grids. Here, we investigate fine spatial resolution factors that influence Landsat-derived LST over a spectrally and spatially heterogeneous landscape. We focus on paired sites (inside/outside a 1994 fire scar) within a pinyon-juniper scrubland in Southern California. The sites have nearly identical micro-meteorology and vegetation species composition, but distinctly different vegetation abundance and structure. The tower at the unburned site includes a number of in-situ imaging tools to quantify vegetation properties, including a thermal camera on a pan-tilt mount, allowing hourly characterization of landscape component temperatures (e.g., sunlit canopy, bare soil, leaf litter). We use these in-situ measurements to assess the impact of fine-scale landscape heterogeneity on estimates of LST, including sensitivity to (i) the relative abundance of component materials, (ii) directional effects due to solar and viewing geometry, (iii) duration of sunlit exposure for each compositional type, and (iv) air temperature. To scale these properties to Landsat spatial resolution (~100-m), we characterize the sub-pixel composition of landscape components (in addition to shade) by applying spectral mixture analysis (SMA) to the Landsat Operational Land Imager (OLI) spectral bands and test the sensitivity of the relationships established with the in-situ data at this coarser scale. The effects of vegetation abundance and cover height versus other controls on satellite-derived estimates of LST will be assessed by comparing estimates at the burned vs

Remote sensing applications for estimating changes on crop evapotranspiration of the most water intensive crops, due to climate change in Cyprus

NASA Astrophysics Data System (ADS)

Papadavid, G.; Neocleous, D.; Stylianou, A.; Markou, M.; Kountios, G.; Hadjimitsis, D.

2016-08-01

Water allocation to crops, and especially to the most water intensive ones, has always been of great importance in agricultural process. Deficit or excess water irrigation quantities could create either crop health related problems or water over-consumption situation which lead to stored water reduction and toxic material depletion to deeper ground layers, respectively. In this context, and under the current conditions, where Cyprus is facing effects of climate changes, purpose of this study is basically to estimate the needed crop water requirements of the past (1995-2004) and the corresponding ones of the present (2005-2015) in order to test if there were any significant changes regarding the crop water requirements of the most water intensive trees in Cyprus. Mediterranean region has been identified as the region that will suffer the most from climate change. Thus the paper refers to effects of climate changes on crop evapotranspiration (ETc) using remotely sensed data from Landsat TM/ ETM+ / OLI employing a sound methodology used worldwide, the Surface Energy Balance Algorithm for Land (SEBAL). Though the general feeling is that of changes on climate will consequently affect ETc, the results have indicated that there is no significant effect of climate change on crop evapotranspiration, despite the fact that some climatic factors have changed. Applying Student's T-test, the mean values for the most water intensive trees in Cyprus of the 1994-2004 decade have shown no statistical difference from the mean values of 2005-2015 decade's for all the cases, concluding that the climate change taking place the last decades in Cyprus have either not affected the crop evapotranspiration or the crops have manage to adapt into the new environmental conditions through time.

Preliminary determination of geothermal working area based on Thermal Infrared and Synthetic Aperture Radar (SAR) remote sensing

NASA Astrophysics Data System (ADS)

Agoes Nugroho, Indra; Kurniawahidayati, Beta; Syahputra Mulyana, Reza; Saepuloh, Asep

2017-12-01

Remote sensing is one of the methods for geothermal exploration. This method can be used to map the geological structures, manifestations, and predict the geothermal potential area. The results from remote sensing were used as guidance for the next step exploration. Analysis of target in remote sensing is an efficient method to delineate geothermal surface manifestation without direct contact to the object. The study took a place in District Merangin, Jambi Province, Indonesia. The area was selected due to existing of Merangin volcanic complex composed by Mounts Sumbing and Hulunilo with surface geothermal manifestations presented by hot springs and hot pools. The location of surface manifestations could be related with local and regional structures of Great Sumatra Fault. The methods used in this study were included identification of volcanic products, lineament extraction, and lineament density quantification. The objective of this study is to delineate the potential zones for sitting the geothermal working site based on Thermal Infrared and Synthetic Aperture Radar (SAR) sensors. The lineament-related to geological structures, was aimed for high lineament density, is using ALOS - PALSAR (Advanced Land Observing Satellite - The Phased Array type L-band Synthetic Aperture Radar) level 1.1. The Normalized Difference Vegetation Index (NDVI) analysis was used to predict the vegetation condition using Landsat 8 OLI-TIRS (The Operational Land Imager - Thermal Infrared Sensor). The brightness temperature was extracted from TIR band to estimate the surface temperature. Geothermal working area identified based on index overlay method from extracted parameter of remote sensing data was located at the western part of study area (Graho Nyabu area). This location was identified because of the existence of high surface temperature about 30°C, high lineament density about 4 - 4.5 km/km2 and low NDVI values less than 0.3.

Monitoring Phenology of Coastal Marshes in Louisiana using the Landsat Archive

NASA Astrophysics Data System (ADS)

Mo, Y.; Kearney, M.

2016-12-01

Coastal marshes are important sinks for blue carbon—carbon sequestered by coastal and marine ecosystems. Remote sensing phenology of the marshes is a good indicator for their ability to sequester carbon, which, however, is seldom addressed in the literature. This study aims to better understand phenology of coastal marshes in Louisiana using NDVI derived from a compilation the Landsat TM, ETM+, and OLI archive (30 m resolution) since 1984 to present. The environmental variables (i.e. annual temperature, sea level, and atmospheric CO2 concentration) of the study area all increased significantly overtime, showing that the study area is subject to climate change. However, marsh phenological parameters, including its peak NDVI, show no significant trend over time. This finding contrasts with the reported increase in summer photosynthetic activity of vegetation in the Northern Hemisphere, which is attributed to the increase in global temperature and atmospheric CO2 concentration. Such differences might be due to marsh physiological characteristics and the local environmental alterations. Coastal marshes in Louisiana contain many C4 species. The C4 photosynthesis pathway is less responsive to atmospheric CO2 concentration compared to the C3 photosynthesis. Coastal marshes thus respond to the elevated atmospheric CO2 differently compared to other ecosystems at middle to higher latitudes in the Northern Hemisphere. Another possible reason is that, while benefiting from the increased atmospheric CO2, coastal marshes are also undergoing significant stresses caused by sea level rise (e.g. submergence, and storm-induced floods and surges), which can offset the positive effects resulted from the increased temperature and atmospheric CO2 on photosynthesis. Our results suggest that coastal marshes might respond to climate change much differently from other ecosystems, but further investigation is required in order to better protect the ecosystem and its carbon storage under the

Drought Impacts on Agricultural Production and Land Fallowing in California's Central Valley in 2015

NASA Technical Reports Server (NTRS)

Rosevelt, Carolyn; Melton, Forrest S.; Johnson, Lee; Guzman, Alberto; Verdin, James P.; Thenkabail, Prasad S.; Mueller, Rick; Jones, Jeanine; Willis, Patrick

2016-01-01

The ongoing drought in California substantially reduced surface water supplies for millions of acres of irrigated farmland in California's Central Valley. Rapid assessment of drought impacts on agricultural production can aid water managers in assessing mitigation options, and guide decision making with respect to mitigation of drought impacts. Satellite remote sensing offers an efficient way to provide quantitative assessments of drought impacts on agricultural production and increases in fallow acreage associated with reductions in water supply. A key advantage of satellite-based assessments is that they can provide a measure of land fallowing that is consistent across both space and time. We describe an approach for monthly and seasonal mapping of uncultivated agricultural acreage developed as part of a joint effort by USGS, USDA, NASA, and the California Department of Water Resources to provide timely assessments of land fallowing during drought events. This effort has used the Central Valley of California as a pilot region for development and testing of an operational approach. To provide quantitative measures of uncultivated agricultural acreage from satellite data early in the season, we developed a decision tree algorithm and applied it to time-series data from Landsat TM (Thematic Mapper), ETM+ (Enhanced Thematic Mapper Plus), OLI (Operational Land Imager), and MODIS (Moderate Resolution Imaging Spectroradiometer). Our effort has been focused on development of indicators of drought impacts in the March-August timeframe based on measures of crop development patterns relative to a reference period with average or above average rainfall. To assess the accuracy of the algorithms, monthly ground validation surveys were conducted across 650 fields from March-September in 2014 and 2015. We present the algorithm along with updated results from the accuracy assessment, and data and maps of land fallowing in the Central Valley in 2015.

Optimizing spatial and temporal constraints for cropland canopy water content retrieval through coupled radiative transfer model inversion

NASA Astrophysics Data System (ADS)

Boren, E. J.; Boschetti, L.; Johnson, D.

2017-12-01

Water plays a critical role in all plant physiological processes, including transpiration, photosynthesis, nutrient transportation, and maintenance of proper plant cell functions. Deficits in water content cause drought-induced stress conditions, such as constrained plant growth and cellular metabolism, while overabundance of water cause anoxic conditions which limit plant physiological processes and promote disease. Vegetation water content maps can provide agricultural producers key knowledge for improving production capacity and resiliency in agricultural systems while facilitating the ability to pinpoint, monitor, and resolve water scarcity issues. Radiative transfer model (RTM) inversion has been successfully applied to remotely sensed data to retrieve biophysical and canopy parameter estimates, including water content. The successful launch of the Landsat 8 Operational Land Imager (OLI) in 2012, Sentinel 2A Multispectral Instrument (MSI) in 2015, followed by Sentinel 2B in 2017, the systematic acquisition schedule and free data distribution policy provide the opportunity for water content estimation at a spatial and temporal scale that can meet the demands of potential operational users: combined, these polar-orbiting systems provide 10 m to 30 m multi-spectral global coverage up to every 3 days. The goal of the present research is to prototype the generation of a cropland canopy water content product, obtained from the newly developed Landsat 8 and Sentinel 2 atmospherically corrected HLS product, through the inversion of the leaf and canopy model PROSAIL5B. We assess the impact of a novel spatial and temporal stratification, where some parameters of the model are constrained by crop type and phenological phase, based on ancillary biophysical data, collected from various crop species grown in a controlled setting and under different water stress conditions. Canopy-level data, collected coincidently with satellite overpasses during four summer field campaigns

Harmonized Landsat/Sentinel-2 Reflectance Products for Land Monitoring (Invited)

NASA Technical Reports Server (NTRS)

Masek, Jeffrey G.; Dungan, Jennifer L.; Ju, Junchang; Roger, Jean-Claude; Claverie, Martin P.; Skakun, Sergii; Vermote, Eric; Justice, Christopher Owen

2017-01-01

Many land applications require more frequent observations than can be obtained from a single 'Landsat class'� sensor. Agricultural monitoring, inland water quality assessment, stand-scale phenology, and numerous other applications all require near-daily imagery at better than 1ha resolution. Thus the land science community has begun expressing a desire for a '30-meter MODIS' global monitoring capability. One cost-effective way to achieve this goal is via merging data from multiple, international observatories into a single virtual constellation. The Harmonized Landsat/Sentinel-2 (HLS) project has been working to generate a seamless surface reflectance product by combining observations from USGS/NASA Landsat-8 and ESA Sentinel-2. Harmonization in this context requires a series of radiometric and geometric transforms to create a single surface reflectance time series agnostic to sensor origin. Radiometric corrections include a common atmospheric correction using the Landsat-8 LaSRC/6S approach, a simple BRDF adjustment to constant solar and nadir view angle, and spectral bandpass adjustments to fit the Landsat-8 OLI reference. Data are then resampled to a consistent 30m UTM grid, using the Sentinel-2 global tile system. Cloud and shadow masking are also implemented. Quality assurance (QA) involves comparison of the output 30m HLS products with near-simultaneous MODIS nadir-adjusted observations. Prototoype HLS products have been processed for approximately 7% of the global land area using the NASA Earth Exchange (NEX) compute environment at NASA Ames, and can be downloaded from the HLS web site (https://hls.gsfc.nasa.gov). A wall-to-wall North America data set is being prepared for 2018. This talk will review the objectives and status of the HLS project, and illustrate applications of high-density optical time series data for agriculture and ecology. We also discuss lessons learned from HLS in the general context of implementing virtual constellations.

Harmonized Landsat/Sentinel-2 Reflectance Products for Land Monitoring

NASA Astrophysics Data System (ADS)

Masek, J. G.; Ju, J.; Claverie, M.; Vermote, E.; Dungan, J. L.; Roger, J. C.; Skakun, S.; Justice, C. O.

2017-12-01

Many land applications require more frequent observations than can be obtained from a single "Landsat class" sensor. Agricultural monitoring, inland water quality assessment, stand-scale phenology, and numerous other applications all require near-daily imagery at better than 1ha resolution. Thus the land science community has begun expressing a desire for a "30-meter MODIS" global monitoring capability. One cost-effective way to achieve this goal is via merging data from multiple, international observatories into a single virtual constellation. The Harmonized Landsat/Sentinel-2 (HLS) project has been working to generate a seamless surface reflectance product by combining observations from USGS/NASA Landsat-8 and ESA Sentinel-2. Harmonization in this context requires a series of radiometric and geometric transforms to create a single surface reflectance time series agnostic to sensor origin. Radiometric corrections include a common atmospheric correction using the Landsat-8 LaSRC/6S approach, a simple BRDF adjustment to constant solar and nadir view angle, and spectral bandpass adjustments to fit the Landsat-8 OLI reference. Data are then resampled to a consistent 30m UTM grid, using the Sentinel-2 global tile system. Cloud and shadow masking are also implemented. Quality assurance (QA) involves comparison of the output 30m HLS products with near-simultaneous MODIS nadir-adjusted observations. Prototoype HLS products have been processed for 7% of the global land area using the NASA Earth Exchange (NEX) compute environment at NASA Ames, and can be downloaded from the HLS web site (https://hls.gsfc.nasa.gov). A wall-to-wall North America data set is being prepared for 2018.This talk will review the objectives and status of the HLS project, and illustrate applications of high-density optical time series data for agriculture and ecology. We also discuss lessons learned from HLS in the general context of implementing virtual constellations.

Changes of Vegetation Distribution in the East Dongting Lake After the Operation of the Three Gorges Dam, China.

PubMed

Hu, Jia-Yu; Xie, Yong-Hong; Tang, Yue; Li, Feng; Zou, Ye-Ai

2018-01-01

Water regime is regarded as the primary factor influencing the vegetation distribution in natural wetland ecosystems. However, the effect of water regime change induced by large-scale hydraulic engineering on vegetation distribution is still unclear. In this study, multi-temporal TM/ETM+/OLI images and hydrological data from 1995 to 2015 were used to elucidate how the change in water regime influenced the vegetation distribution in the East Dongting Lake (EDTL), especially after the operation of the Three Gorges Dam (TGD) in 2003. Using unsupervised and supervised classification methods, three types of land cover were identified in the study area: Water and Mudflat, Grass, and Reed and Forest. Results showed that the total vegetation area in EDTL increased by approximately 78 km 2 during 1995-2015. The areas of Reed and Forest and Grass exhibited a contrasting trend, dramatic increase in Reed and Forest but sharp decrease in Grass, particularly after the operation of TGD. The lowest distribution elevations of Grass and Reed and Forest decreased by 0.61 and 0.52 m, respectively. As a result of water level variation, submergence duration increased at 20-21 m and 28 m elevations (1-13 days), but significantly decreased at 22-27 m and 29-30 m elevations (-3 to -31 days). The submergence duration of Grass and Reed and Forest was 246 and 177 days, respectively. This study indicated that wetland vegetation pattern significantly changed after the operation of TGD, mainly as a result of changes in submergence condition. Submergence duration might be an effective indicator to predict the shift of vegetation distribution in EDTL, and which could provide scientific guidance for vegetation restoration and wetland management in this lake.

A new approach for the estimation of phytoplankton cell counts associated with algal blooms.

PubMed

Nazeer, Majid; Wong, Man Sing; Nichol, Janet Elizabeth

2017-07-15

This study proposes a method for estimating phytoplankton cell counts associated with an algal bloom, using satellite images coincident with in situ and meteorological parameters. Satellite images from Landsat Thematic Mapper (TM), Enhanced Thematic Mapper Plus (ETM+), Operational Land Imager (OLI) and HJ-1 A/B Charge Couple Device (CCD) sensors were integrated with the meteorological observations to provide an estimate of phytoplankton cell counts. All images were atmospherically corrected using the Second Simulation of the Satellite Signal in the Solar Spectrum (6S) atmospheric correction method with a possible error of 1.2%, 2.6%, 1.4% and 2.3% for blue (450-520nm), green (520-600nm), red (630-690nm) and near infrared (NIR 760-900nm) wavelengths, respectively. Results showed that the developed Artificial Neural Network (ANN) model yields a correlation coefficient (R) of 0.95 with the in situ validation data with Sum of Squared Error (SSE) of 0.34cell/ml, Mean Relative Error (MRE) of 0.154cells/ml and a bias of -504.87. The integration of the meteorological parameters with remote sensing observations provided a promising estimation of the algal scum as compared to previous studies. The applicability of the ANN model was tested over Hong Kong as well as over Lake Kasumigaura, Japan and Lake Okeechobee, Florida USA, where algal blooms were also reported. Further, a 40-year (1975-2014) red tide occurrence map was developed and revealed that the eastern and southern waters of Hong Kong are more vulnerable to red tides. Over the 40 years, 66% of red tide incidents were associated with the Dinoflagellates group, while the remainder were associated with the Diatom group (14%) and several other minor groups (20%). The developed technology can be applied to other similar environments in an efficient and cost-saving manner. Copyright © 2017 Elsevier B.V. All rights reserved.

Combining Quantitative Genetic Footprinting and Trait Enrichment Analysis to Identify Fitness Determinants of a Bacterial Pathogen

PubMed Central

Wiles, Travis J.; Norton, J. Paul; Russell, Colin W.; Dalley, Brian K.; Fischer, Kael F.; Mulvey, Matthew A.

2013-01-01

Strains of Extraintestinal Pathogenic Escherichia c oli (ExPEC) exhibit an array of virulence strategies and are a major cause of urinary tract infections, sepsis and meningitis. Efforts to understand ExPEC pathogenesis are challenged by the high degree of genetic and phenotypic variation that exists among isolates. Determining which virulence traits are widespread and which are strain-specific will greatly benefit the design of more effective therapies. Towards this goal, we utilized a quantitative genetic footprinting technique known as transposon insertion sequencing (Tn-seq) in conjunction with comparative pathogenomics to functionally dissect the genetic repertoire of a reference ExPEC isolate. Using Tn-seq and high-throughput zebrafish infection models, we tracked changes in the abundance of ExPEC variants within saturated transposon mutant libraries following selection within distinct host niches. Nine hundred and seventy bacterial genes (18% of the genome) were found to promote pathogen fitness in either a niche-dependent or independent manner. To identify genes with the highest therapeutic and diagnostic potential, a novel Trait Enrichment Analysis (TEA) algorithm was developed to ascertain the phylogenetic distribution of candidate genes. TEA revealed that a significant portion of the 970 genes identified by Tn-seq have homologues more often contained within the genomes of ExPEC and other known pathogens, which, as suggested by the first axiom of molecular Koch's postulates, is considered to be a key feature of true virulence determinants. Three of these Tn-seq-derived pathogen-associated genes—a transcriptional repressor, a putative metalloendopeptidase toxin and a hypothetical DNA binding protein—were deleted and shown to independently affect ExPEC fitness in zebrafish and mouse models of infection. Together, the approaches and observations reported herein provide a resource for future pathogenomics-based research and highlight the diversity of

Utilizing NASA Earth Observations to Model Volcanic Hazard Risk Levels in Areas Surrounding the Copahue Volcano in the Andes Mountains

NASA Astrophysics Data System (ADS)

Keith, A. M.; Weigel, A. M.; Rivas, J.

2014-12-01

Copahue is a stratovolcano located along the rim of the Caviahue Caldera near the Chile-Argentina border in the Andes Mountain Range. There are several small towns located in proximity of the volcano with the two largest being Banos Copahue and Caviahue. During its eruptive history, it has produced numerous lava flows, pyroclastic flows, ash deposits, and lahars. This isolated region has steep topography and little vegetation, rendering it poorly monitored. The need to model volcanic hazard risk has been reinforced by recent volcanic activity that intermittently released several ash plumes from December 2012 through May 2013. Exposure to volcanic ash is currently the main threat for the surrounding populations as the volcano becomes more active. The goal of this project was to study Copahue and determine areas that have the highest potential of being affected in the event of an eruption. Remote sensing techniques were used to examine and identify volcanic activity and areas vulnerable to experiencing volcanic hazards including volcanic ash, SO2 gas, lava flow, pyroclastic density currents and lahars. Landsat 7 Enhanced Thematic Mapper Plus (ETM+), Landsat 8 Operational Land Imager (OLI), EO-1 Advanced Land Imager (ALI), Terra Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), Shuttle Radar Topography Mission (SRTM), ISS ISERV Pathfinder, and Aura Ozone Monitoring Instrument (OMI) products were used to analyze volcanic hazards. These datasets were used to create a historic lava flow map of the Copahue volcano by identifying historic lava flows, tephra, and lahars both visually and spectrally. Additionally, a volcanic risk and hazard map for the surrounding area was created by modeling the possible extent of ash fallout, lahars, lava flow, and pyroclastic density currents (PDC) for future eruptions. These model results were then used to identify areas that should be prioritized for disaster relief and evacuation orders.

Fire Regime and Land Abandonment in European Russia: Case Study of Smolensk Oblast

NASA Astrophysics Data System (ADS)

Krylov, A.; McCarty, J. L.; Potapov, P.; Turubanova, S.; Prishchepov, A. V.; Manisha, A.; Romanenkov, V.; Rukhovitch, D.; Koroleva, P.; Hansen, M.

2014-12-01

Fires in anthropogenically-dominated landscapes are generally attributed to ecosystem management, agriculture, and policy drivers. In European Russia, fire mainly occurring on agricultural lands, wetlands, and abandoned lands. In the agricultural practice in Russia prescribed fires are believed to increase pasture and hay productivity, suppress trees and shrub expansion, and reduce fire hazards, with fire frequency fire dependent on land use and agricultural practices. The large-scale socio-economic transition since the fall of the Soviet Union has led to changes in land use and land management, including land abandonment and changing agricultural practices. In June 2014, an extensive field campaign was completed in the Smolensk Oblast, located approximately two hundred kilometers west of Moscow on the border with Belarus. Our field sampling was based on circa 1985 Landsat-based forest cover map (Potapov et al., 2014). Points were randomly selected from the non-forested class of the 1985 classification, prior to the collapse of the Soviet Union. Of total field collects, 55% points were sampled on land in either early or late stage of abandonment, 15% from actively cropped fields, and 30% from hay or pasture. Fire frequency was calculated for the 108 field points using 1 km Moderate Resolution Imaging Spectroradiometer (MODIS) active fire data for years 2000-2014. Also we calculated percent of points burned in spring 2014 using 30 m Landsat 8 Operational Land Imager (OLI) data to derive burn scars. Actively cropped fields had lowest burn frequency while abandoned lands - early and late stage abandonment - had highest frequency. Fire frequency was significantly higher on wet soils than dry soils, with no relationship between fire frequency and tree canopy cover. We hypothesize, higher fire frequency on abandoned lands was likely due to greater fuel loads and because of traditional belief in rural Russia that fire is efficient way to suppress tree and shrub expansion.

Geospatial Analysis of Wetlands Degradation in Makurdi, Nigeria

NASA Astrophysics Data System (ADS)

Anule, P.; Ujoh, F.

2017-09-01

Globally, the amount of wetlands have being on the decline due to the fragile nature of these ecosystems and unplanned land consumption practices. This has created pressure on suitable land for cultivation in most developing countries where most of the growing food demand originates. Previous studies revealed that wetlands and agricultural landuse dominated the landscape of Makurdi. However, the trend is changing in recent times. Makurdi has undergone tremendous transformation in its landuse/landcover due to rapid urbanization since 1976 when it became the capital city of Benue State. To estimate the land cover change in Makurdi, Landsat ETM, ETM+ and OLI satellite data for 1996, 2006 and 2016, respectively were utilised. The study adapted the Kappa index for assessing accuracy of the land use/cover maps generated from the analysis to improve the accuracy of results. An accuracy level of 80 to 91 % was achieved. The results reveal an overall significant increase in built-up area and other land uses at the expense of wetlands from 26.3 % in 1996 to 18.1 % in 2016. Further analysis includes the land consumption rate (LCR) and land absorption coefficient (LAC) which reveals the role of population expansion in the recorded levels of wetland losses recorded in this study. The study projects a further decline of wetland cover by 33.15 km2 (or by 22.57 %) in 2026 if steps are not instituted to control the rate of decline. Suggestions are made to align with and incorporate into policy the strategic need to adopt the provisions of the SDGs at local levels if we intend to avert the massive failure recorded by the now rested MDGs.

Effects of landscape composition and pattern on land surface temperature: An urban heat island study in the megacities of Southeast Asia.

PubMed

Estoque, Ronald C; Murayama, Yuji; Myint, Soe W

2017-01-15

Due to its adverse impacts on urban ecological environment and the overall livability of cities, the urban heat island (UHI) phenomenon has become a major research focus in various interrelated fields, including urban climatology, urban ecology, urban planning, and urban geography. This study sought to examine the relationship between land surface temperature (LST) and the abundance and spatial pattern of impervious surface and green space in the metropolitan areas of Bangkok (Thailand), Jakarta (Indonesia), and Manila (Philippines). Landsat-8 OLI/TIRS data and various geospatial approaches, including urban-rural gradient, multiresolution grid-based, and spatial metrics-based techniques, were used to facilitate the analysis. We found a significant strong correlation between mean LST and the density of impervious surface (positive) and green space (negative) along the urban-rural gradients of the three cities, depicting a typical UHI profile. The correlation of impervious surface density with mean LST tends to increase in larger grids, whereas the correlation of green space density with mean LST tends to increase in smaller grids, indicating a stronger influence of impervious surface and green space on the variability of LST in larger and smaller areas, respectively. The size, shape complexity, and aggregation of the patches of impervious surface and green space also had significant relationships with mean LST, though aggregation had the most consistent strong correlation. On average, the mean LST of impervious surface is about 3°C higher than that of green space, highlighting the important role of green spaces in mitigating UHI effects, an important urban ecosystem service. We recommend that the density and spatial pattern of urban impervious surfaces and green spaces be considered in landscape and urban planning so that urban areas and cities can have healthier and more comfortable living urban environments. Copyright © 2016 Elsevier B.V. All rights reserved.

Land cover changes assessment using object-based image analysis in the Binah River watershed (Togo and Benin)

NASA Astrophysics Data System (ADS)

Badjana, Hèou Maléki; Helmschrot, Jörg; Selsam, Peter; Wala, Kpérkouma; Flügel, Wolfgang-Albert; Afouda, Abel; Akpagana, Koffi

2015-10-01

In this study, land cover changes between 1972 and 2013 were investigated in the Binah River watershed (North of Togo and Benin) using remote sensing and geographic information system technologies. Multitemporal satellite images—Landsat MSS (1972), TM (1987), and OLI-TIRS (2013)—were processed using object-based image analysis and post-classification comparison methods including landscape metrics and changes trajectories analysis. Land cover maps referring to five main land cover classes, namely, agricultural land, forest land, savannah, settlements, and water bodies, were produced for each acquisition date. The overall accuracies were 76.64% (1972), 83.52% (1987), and 88.84% (2013) with respective Kappa statistics of 0.69, 0.78, and 0.86. The assessment of the spatiotemporal pattern of land cover changes indicates that savannah, the main vegetation type, has undergone the most dominant change, decreasing from 67% of the basin area in 1972 to 56% in 1987 and 33% in 2013. At the same time, agricultural land has significantly increased from 15% in 1972 to 24% in 1987 and 43% in 2013, while some proportions of agricultural land were converted to savannah relating to fallow agriculture. In total, more than 55% of the landscape experienced changes between 1972 and 2013. These changes are primarily due to human activities and population growth. In addition, agricultural activities significantly contributed to the increase in the number of patches, degree of division, and splitting index of forest and savannah vegetations and the decrease in their effective mesh sizes. These results indicate further fragmentation of forest and savannah vegetations between 1972 and 2013. Further research is needed to quantitatively evaluate the influences of individual factors of human activities and to separate these from the impacts of climate change-driven disturbances.

The Greek National Observatory of Forest Fires (NOFFi)

NASA Astrophysics Data System (ADS)

Tompoulidou, Maria; Stefanidou, Alexandra; Grigoriadis, Dionysios; Dragozi, Eleni; Stavrakoudis, Dimitris; Gitas, Ioannis Z.

2016-08-01

Efficient forest fire management is a key element for alleviating the catastrophic impacts of wildfires. Overall, the effective response to fire events necessitates adequate planning and preparedness before the start of the fire season, as well as quantifying the environmental impacts in case of wildfires. Moreover, the estimation of fire danger provides crucial information required for the optimal allocation and distribution of the available resources. The Greek National Observatory of Forest Fires (NOFFi)—established by the Greek Forestry Service in collaboration with the Laboratory of Forest Management and Remote Sensing of the Aristotle University of Thessaloniki and the International Balkan Center—aims to develop a series of modern products and services for supporting the efficient forest fire prevention management in Greece and the Balkan region, as well as to stimulate the development of transnational fire prevention and impacts mitigation policies. More specifically, NOFFi provides three main fire-related products and services: a) a remote sensing-based fuel type mapping methodology, b) a semi-automatic burned area mapping service, and c) a dynamically updatable fire danger index providing mid- to long-term predictions. The fuel type mapping methodology was developed and applied across the country, following an object-oriented approach and using Landsat 8 OLI satellite imagery. The results showcase the effectiveness of the generated methodology in obtaining highly accurate fuel type maps on a national level. The burned area mapping methodology was developed as a semi-automatic object-based classification process, carefully crafted to minimize user interaction and, hence, be easily applicable on a near real-time operational level as well as for mapping historical events. NOFFi's products can be visualized through the interactive Fire Forest portal, which allows the involvement and awareness of the relevant stakeholders via the Public Participation GIS

a Map Mash-Up Application: Investigation the Temporal Effects of Climate Change on Salt Lake Basin

NASA Astrophysics Data System (ADS)

Kirtiloglu, O. S.; Orhan, O.; Ekercin, S.

2016-06-01

The main purpose of this paper is to investigate climate change effects that have been occurred at the beginning of the twenty-first century at the Konya Closed Basin (KCB) located in the semi-arid central Anatolian region of Turkey and particularly in Salt Lake region where many major wetlands located in and situated in KCB and to share the analysis results online in a Web Geographical Information System (GIS) environment. 71 Landsat 5-TM, 7-ETM+ and 8-OLI images and meteorological data obtained from 10 meteorological stations have been used at the scope of this work. 56 of Landsat images have been used for extraction of Salt Lake surface area through multi-temporal Landsat imagery collected from 2000 to 2014 in Salt lake basin. 15 of Landsat images have been used to make thematic maps of Normalised Difference Vegetation Index (NDVI) in KCB, and 10 meteorological stations data has been used to generate the Standardized Precipitation Index (SPI), which was used in drought studies. For the purpose of visualizing and sharing the results, a Web GIS-like environment has been established by using Google Maps and its useful data storage and manipulating product Fusion Tables which are all Google's free of charge Web service elements. The infrastructure of web application includes HTML5, CSS3, JavaScript, Google Maps API V3 and Google Fusion Tables API technologies. These technologies make it possible to make effective "Map Mash-Ups" involving an embedded Google Map in a Web page, storing the spatial or tabular data in Fusion Tables and add this data as a map layer on embedded map. The analysing process and map mash-up application have been discussed in detail as the main sections of this paper.

Glacier changes in the Ravi basin, North-Western Himalaya (India) during the last four decades (1971-2010/13)

NASA Astrophysics Data System (ADS)

Chand, Pritam; Sharma, Milap Chand

2015-12-01

A glacier inventory of the Ravi basin, north-western Himalaya has been generated for the year 2002 using Landsat ETM + and ASTER Global DEM (GDEM V2) as the baseline data for the change analysis. The Ravi basin consists of 285 glaciers (> 0.02 km2) covering an area of 164.5 ± 7.5 km2, including 71 debris-covered glaciers with an area of 36.1 ± 2.1 km2 (22% of total glacierized area) in 2002. Change analysis based on Corona KH-4B (1971), Worldview (2010) and Landsat 8 OLI/TRIS (2013) images was restricted to a subset of 157 glaciers (covering an area of 121.4 ± 5.4 km2 in 2002) due to cloud cover. Glacier area decreased from 125.8 ± 1.9 km2 (1971) to 119.9 ± 4.8 km2 (2010/13), a loss of 4.7 ± 4.1% or 0.1 ± 0.1% a- 1. The glacier recession rate has decreased, to a minimum for the recent decades (2002-2010/13). The debris-covered glacier area increased by 19.2 ± 2.2% (0.5 ± 0.05% a- 1) in the Ravi basin. However, there were significant variation in its sub-basins i.e. in Budhil and Upper Ravi sub-basin, where the debris-covered area increased by 28.6 ± 3.1% (0.7 ± 0.1% a- 1) and 14 ± 1.6% (0.3 ± 0.04% a- 1), respectively, between 1971 and 2010/13. Field investigation of selected glaciers (2010-2014) supports glacier recession trend from remote sensing data. Glacier retreat rates in the Ravi basin were lower than previously reported for selected glaciers in the similar basin and other basins (e.g. Chenab, Beas, Parbati, Baspa and Tirungkhad) of the Himachal Himalaya.

Hyperspectral observation of anthropogenic and biogenic pollution in coastal zone

NASA Astrophysics Data System (ADS)

Lavrova, Olga; Loupian, Evgeny; Mityagina, Marina; Uvarov, Ivan

The work presents results of anthropogenic and biogenic pollution detection in coastal zones of the Black and Caspian Seas based on satellite hyperspetral data provided by the Hyperion and HICO instruments. Techniques developed on the basis of the analysis of spectral characteristics calculated in special points were employed to address the following problems: (a) assessment of the blooming intensity of cyanobacteria and their distribution in bays of western Crimea and discrimination between anthropogenic pollutant discharge events and algae bloom; (b) detection of anthropogenic pollution in Crimean lakes utilized as industrial liquid discharge reservoirs; (c) detection of oil pollution in areas of shelf oil production in the Caspian Sea. Information values of different spectral bands and their composites were estimated in connection with the retrieval of the main sea water components: phytoplankton, suspended matter and colored organic matter, and also various anthropogenic pollutants, including oil. Software tools for thematic hyperspectral data processing in application to the investigation of sea coastal zones and internal water bodies were developed on the basis of the See the Sea geoportal created by the Space Research Institute RAS. The geoportal is focused on the study of processes in the world ocean with the emphasis on the advantages of satellite systems of observation. The tools that were introduced into the portal allow joint analysis of quasi-simultaneous satellite data, in particular data from the Hyperion, HICO, OLI Landsat-8, ETM Landsat-7 and TM Landsat-5 instruments. Results of analysis attempts combining data from different sensors are discussed. Their strong and weak points are highlighted. The study was completed with partial financial support from The Russian Foundation for Basic Research grants # 14-05-00520-a and 13-07-12017.

Geodiametris: an integrated geoinformatic approach for monitoring land pollution from the disposal of olive oil mill wastes

NASA Astrophysics Data System (ADS)

Alexakis, Dimitrios D.; Sarris, Apostolos; Papadopoulos, Nikos; Soupios, Pantelis; Doula, Maria; Cavvadias, Victor

2014-08-01

The olive-oil industry is one of the most important sectors of agricultural production in Greece, which is the third in olive-oil production country worldwide. Olive oil mill wastes (OOMW) constitute a major factor in pollution in olivegrowing regions and an important problem to be solved for the agricultural industry. The olive-oil mill wastes are normally deposited at tanks, or directly in the soil or even on adjacent torrents, rivers and lakes posing a high risk to the environmental pollution and the community health. GEODIAMETRIS project aspires to develop integrated geoinformatic methodologies for performing monitoring of land pollution from the disposal of OOMW in the island of Crete -Greece. These methodologies integrate GPS surveys, satellite remote sensing and risk assessment analysis in GIS environment, application of in situ and laboratory geophysical methodologies as well as soil and water physicochemical analysis. Concerning project's preliminary results, all the operating OOMW areas located in Crete have been already registered through extensive GPS field campaigns. Their spatial and attribute information has been stored in an integrated GIS database and an overall OOMW spectral signature database has been constructed through the analysis of multi-temporal Landsat-8 OLI satellite images. In addition, a specific OOMW area located in Alikianos village (Chania-Crete) has been selected as one of the main case study areas. Various geophysical methodologies, such as Electrical Resistivity Tomography, Induced Polarization, multifrequency electromagnetic, Self Potential measurements and Ground Penetrating Radar have been already implemented. Soil as well as liquid samples have been collected for performing physico-chemical analysis. The preliminary results have already contributed to the gradual development of an integrated environmental monitoring tool for studying and understanding environmental degradation from the disposal of OOMW.

Absolute Calibration of Optical Satellite Sensors Using Libya 4 Pseudo Invariant Calibration Site

NASA Technical Reports Server (NTRS)

Mishra, Nischal; Helder, Dennis; Angal, Amit; Choi, Jason; Xiong, Xiaoxiong

2014-01-01

The objective of this paper is to report the improvements in an empirical absolute calibration model developed at South Dakota State University using Libya 4 (+28.55 deg, +23.39 deg) pseudo invariant calibration site (PICS). The approach was based on use of the Terra MODIS as the radiometer to develop an absolute calibration model for the spectral channels covered by this instrument from visible to shortwave infrared. Earth Observing One (EO-1) Hyperion, with a spectral resolution of 10 nm, was used to extend the model to cover visible and near-infrared regions. A simple Bidirectional Reflectance Distribution function (BRDF) model was generated using Terra Moderate Resolution Imaging Spectroradiometer (MODIS) observations over Libya 4 and the resulting model was validated with nadir data acquired from satellite sensors such as Aqua MODIS and Landsat 7 (L7) Enhanced Thematic Mapper (ETM+). The improvements in the absolute calibration model to account for the BRDF due to off-nadir measurements and annual variations in the atmosphere are summarized. BRDF models due to off-nadir viewing angles have been derived using the measurements from EO-1 Hyperion. In addition to L7 ETM+, measurements from other sensors such as Aqua MODIS, UK-2 Disaster Monitoring Constellation (DMC), ENVISAT Medium Resolution Imaging Spectrometer (MERIS) and Operational Land Imager (OLI) onboard Landsat 8 (L8), which was launched in February 2013, were employed to validate the model. These satellite sensors differ in terms of the width of their spectral bandpasses, overpass time, off-nadir-viewing capabilities, spatial resolution and temporal revisit time, etc. The results demonstrate that the proposed empirical calibration model has accuracy of the order of 3% with an uncertainty of about 2% for the sensors used in the study.

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

NASA Astrophysics Data System (ADS)

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

2017-10-01

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

Understanding the directed ortho lithiation of (R)-Ph₂P(=NCO₂Me)NHCH(Me)Ph. NMR spectroscopic and computational study of the structure of the N-lithiated species.

PubMed

Casimiro, M; García-López, J; Iglesias, M J; López-Ortiz, F

2014-10-14

A multinuclear magnetic resonance ((1)H, (7)Li, (13)C, (15)N, (31)P) and DFT computational study at the M06-2X(SMD,THF)/6-311+G(d,p)//B3LYP/6-31G(d) level of the structure of a N-lithiated phosphinimidic amide (R)-Ph2P(=NCO2Me)NHCH(Me)Ph 13 has been performed. In THF solution it exists as an equilibrium mixture of monomers and dimers. The monomers consist of a six-membered ring formed by coordination of the lithium atom with the deprotonated nitrogen and the oxygen atom of the carbonyl group. This coordination mode is in contrast to the standard N,N-chelation observed in N-lithiated N,N'-bis(trimethylsilyl)phosphinimidic amides. The calculations showed that the metallacycle adopts a twist-boat conformation and that the lithium atom is in a tetrahedral environment involving O,N-chelation by the ligand and coordination to two/one THF molecules in the monomer/dimer. Dimerization takes place through O-Li bridges. For all species two series of isomers have been identified, which originated by restricted rotation of the methoxy group and ring inversion. The twist-boat conformational interconversion seems to be operating for explaining the pattern of signals observed in the (7)Li and (31)P NMR spectra. The structure found for the most stable dimer is analogous to the molecular structure reported for a related C(α)-lithiated phosphazene 20. The structural study revealed that the chiral side-arm of the N-lithiated species is oriented to the outer face of the pro-S P-phenyl ring, which shows one ortho-proton very close to the nitrogen atom of the carbamate moiety. In this conformation, proton abstraction by a base is highly favoured, in agreement with the experimental results.

Phenology Analysis of Forest Vegetation to Environmental Variables during - and Post-Monsoon Seasons in Western Himalayan Region of India

NASA Astrophysics Data System (ADS)

Khare, S.; Latifi, H.; Ghosh, K.

2016-06-01

To assess the phenological changes in Moist Deciduous Forest (MDF) of western Himalayan region of India, we carried out NDVI time series analysis from 2013 to 2015 using Landsat 8 OLI data. We used the vegetation index differencing method to calculate the change in NDVI (NDVIchange) during pre and post monsoon seasons and these changes were used to assess the phenological behaviour of MDF by taking the effect of a set of environmental variables into account. To understand the effect of environmental variables on change in phenology, we designed a linear regression analysis with sample-based NDVIchange values as the response variable and elevation aspect, and Land Surface Temperature (LST) as explanatory variables. The Landsat-8 derived phenology transition stages were validated by calculating the phenology variation from Nov 2008 to April 2009 using Landsat-7 which has the same spatial resolution as Landsat-8. The Landsat-7 derived NDVI trajectories were plotted in accordance with MODIS derived phenology stages (from Nov 2008 to April 2009) of MDF. Results indicate that the Landsat -8 derived NDVI trajectories describing the phenology variation of MDF during spring, monsoon autumn and winter seasons agreed closely with Landsat-7 and MODIS derived phenology transition from Nov 2008 to April 2009. Furthermore, statistical analysis showed statistically significant correlations (p < 0.05) amongst the environmental variables and the NDVIchange between full greenness and maximum frequency stage of Onset of Greenness (OG) activity.. The major change in NDVI was observed in medium (600 to 650 m) and maximum (650 to 750 m) elevation areas. The change in LST showed also to be highly influential. The results of this study can be used for large scale monitoring of difficult-to-reach mountainous forests, with additional implications in biodiversity assessment. By means of a sufficient amount of available cloud-free imagery, detailed phenological trends across mountainous

Estimating of Soil Texture Using Landsat Imagery: a Case Study in Thatta Tehsil, Sindh

NASA Astrophysics Data System (ADS)

Khalil, Zahid

2016-07-01

Soil texture is considered as an important environment factor for agricultural growth. It is the most essential part for soil classification in large scale. Today the precise soil information in large scale is of great demand from various stakeholders including soil scientists, environmental managers, land use planners and traditional agricultural users. With the increasing demand of soil properties in fine scale spatial resolution made the traditional laboratory methods inadequate. In addition the costs of soil analysis with precision agriculture systems are more expensive than traditional methods. In this regard, the application of geo-spatial techniques can be used as an alternative for examining soil analysis. This study aims to examine the ability of Geo-spatial techniques in identifying the spatial patterns of soil attributes in fine scale. Around 28 samples of soil were collected from the different areas of Thatta Tehsil, Sindh, Pakistan for analyzing soil texture. An Ordinary Least Square (OLS) regression analysis was used to relate the reflectance values of Landsat8 OLI imagery with the soil variables. The analysis showed there was a significant relationship (p<0.05) of band 2 and 5 with silt% (R2 = 0.52), and band 4 and 6 with clay% (R2 =0.40). The equation derived from OLS analysis was then used for the whole study area for deriving soil attributes. The USDA textural classification triangle was implementing for the derivation of soil texture map in GIS environment. The outcome revealed that the 'sandy loam' was in great quantity followed by loam, sandy clay loam and clay loam. The outcome shows that the Geo-spatial techniques could be used efficiently for mapping soil texture of a larger area in fine scale. This technology helped in decreasing cost, time and increase detailed information by reducing field work to a considerable level.

Landsat-based trend analysis of lake dynamics across northern permafrost regions

USGS Publications Warehouse

Nitze, Ingmar; Grosse, Guido; Jones, Benjamin M.; Arp, Christopher D.; Ulrich, Mathias; Federov, Alexander; Veremeeva, Alexandra

2017-01-01

Lakes are a ubiquitous landscape feature in northern permafrost regions. They have a strong impact on carbon, energy and water fluxes and can be quite responsive to climate change. The monitoring of lake change in northern high latitudes, at a sufficiently accurate spatial and temporal resolution, is crucial for understanding the underlying processes driving lake change. To date, lake change studies in permafrost regions were based on a variety of different sources, image acquisition periods and single snapshots, and localized analysis, which hinders the comparison of different regions. Here we present, a methodology based on machine-learning based classification of robust trends of multi-spectral indices of Landsat data (TM,ETM+, OLI) and object-based lake detection, to analyze and compare the individual, local and regional lake dynamics of four different study sites (Alaska North Slope, Western Alaska, Central Yakutia, Kolyma Lowland) in the northern permafrost zone from 1999 to 2014. Regional patterns of lake area change on the Alaska North Slope (-0.69%), Western Alaska (-2.82%), and Kolyma Lowland (-0.51%) largely include increases due to thermokarst lake expansion, but more dominant lake area losses due to catastrophic lake drainage events. In contrast, Central Yakutia showed a remarkable increase in lake area of 48.48%, likely resulting from warmer and wetter climate conditions over the latter half of the study period. Within all study regions, variability in lake dynamics was associated with differences in permafrost characteristics, landscape position (i.e. upland vs. lowland), and surface geology. With the global availability of Landsat data and a consistent methodology for processing the input data derived from robust trends of multi-spectral indices, we demonstrate a transferability, scalability and consistency of lake change analysis within the northern permafrost region.

Assessing biomass of diverse coastal marsh ecosystems using statistical and machine learning models

NASA Astrophysics Data System (ADS)

Mo, Yu; Kearney, Michael S.; Riter, J. C. Alexis; Zhao, Feng; Tilley, David R.

2018-06-01

The importance and vulnerability of coastal marshes necessitate effective ways to closely monitor them. Optical remote sensing is a powerful tool for this task, yet its application to diverse coastal marsh ecosystems consisting of different marsh types is limited. This study samples spectral and biophysical data from freshwater, intermediate, brackish, and saline marshes in Louisiana, and develops statistical and machine learning models to assess the marshes' biomass with combined ground, airborne, and spaceborne remote sensing data. It is found that linear models derived from NDVI and EVI are most favorable for assessing Leaf Area Index (LAI) using multispectral data (R2 = 0.7 and 0.67, respectively), and the random forest models are most useful in retrieving LAI and Aboveground Green Biomass (AGB) using hyperspectral data (R2 = 0.91 and 0.84, respectively). It is also found that marsh type and plant species significantly impact the linear model development (P < .05 in both cases). Sensors with coarser spatial resolution yield lower LAI values because the fine water networks are not detected and mixed into the vegetation pixels. The Landsat OLI-derived map shows the LAI of coastal mashes in Louisiana mostly ranges from 0 to 5.0, and is highest for freshwater marshes and for marshes in the Atchafalaya Bay delta. The CASI-derived maps show that LAI of saline marshes at Bay Batiste typically ranges from 0.9 to 1.5, and the AGB is mostly less than 900 g/m2. This study provides solutions for assessing the biomass of Louisiana's coastal marshes using various optical remote sensing techniques, and highlights the impacts of the marshes' species composition on the model development and the sensors' spatial resolution on biomass mapping, thereby providing useful tools for monitoring the biomass of coastal marshes in Louisiana and diverse coastal marsh ecosystems elsewhere.

Drought Impacts on Agricultural Production and Land Fallowing in California's Central Valley in 2015

NASA Astrophysics Data System (ADS)

Rosevelt, C.; Melton, F. S.; Johnson, L.; Guzman, A.; Verdin, J. P.; Thenkabail, P. S.; Mueller, R.; Jones, J.; Willis, P.

2015-12-01

The ongoing drought in California substantially reduced surface water supplies for millions of acres of irrigated farmland in California's Central Valley. Rapid assessment of drought impacts on agricultural production can aid water managers in assessing mitigation options, and guide decision making with respect to mitigation of drought impacts. Satellite remote sensing offers an efficient way to provide quantitative assessments of drought impacts on agricultural production and increases in fallow acreage associated with reductions in water supply. A key advantage of satellite-based assessments is that they can provide a measure of land fallowing that is consistent across both space and time. We describe an approach for monthly and seasonal mapping of uncultivated agricultural acreage developed as part of a joint effort by USGS, USDA, NASA, and the California Department of Water Resources to provide timely assessments of land fallowing during drought events. This effort has used the Central Valley of California as a pilot region for development and testing of an operational approach. To provide quantitative measures of uncultivated agricultural acreage from satellite data early in the season, we developed a decision tree algorithm and applied it to timeseries of data from Landsat TM, ETM+, OLI, and MODIS. Our effort has been focused on development of indicators of drought impacts in the March - August timeframe based on measures of crop development patterns relative to a reference period with average or above average rainfall. To assess the accuracy of the algorithms, monthly ground validation surveys were conducted across 650 fields from March - September in 2014 and 2015. We present the algorithm along with updated results from the accuracy assessment, and data and maps of land fallowing in the Central Valley in 2015.

Mapping Drought Impacts on Agricultural Production in California's Central Valley

NASA Astrophysics Data System (ADS)

Melton, F. S.; Guzman, A.; Johnson, L.; Rosevelt, C.; Verdin, J. P.; Dwyer, J. L.; Mueller, R.; Zakzeski, A.; Thenkabail, P. S.; Wallace, C.; Jones, J.; Windell, S.; Urness, J.; Teaby, A.; Hamblin, D.; Post, K. M.; Nemani, R. R.

2014-12-01

The ongoing drought in California has substantially reduced surface water supplies for millions of acres of irrigated farmland in California's Central Valley. Rapid assessment of drought impacts on agricultural production can aid water managers in assessing mitigation options, and guide decision making with respect to requests for local water transfers, county drought disaster designations, and allocation of emergency funds to mitigate drought impacts. Satellite remote sensing offers an efficient way to provide quantitative assessments of drought impacts on agricultural production and increases in idle acreage associated with reductions in water supply. A key advantage of satellite-based assessments is that they can provide a measure of land fallowing that is consistent across both space and time. We describe an approach for monthly and seasonal mapping of uncultivated agricultural acreage developed as part of a joint effort by USGS, USDA, NASA, and the California Department of Water Resources to provide timely assessments of land fallowing during drought events. This effort has used the Central Valley of California as a pilot region for development and testing of an operational approach. To provide quantitative measures of uncultivated agricultural acreage from satellite data early in the season, we developed a decision tree algorithm and applied it to timeseries of data from Landsat TM, ETM+, OLI, and MODIS. Our effort has been focused on development of indicators of drought impacts in the March - August timeframe based on measures of crop development patterns relative to a reference period with average or above average rainfall. To assess the accuracy of the algorithms, monthly ground validation surveys were conducted across 640 fields from March - September, 2014. We present the algorithm along with updated results from the accuracy assessment, and discuss potential applications to other regions.

Using NASA Earth Observing Satellites and Statistical Model Analysis to Monitor Vegetation and Habitat Rehabilitation in Southwest Virginia's Reclaimed Mine Lands

NASA Astrophysics Data System (ADS)

Tate, Z.; Dusenge, D.; Elliot, T. S.; Hafashimana, P.; Medley, S.; Porter, R. P.; Rajappan, R.; Rodriguez, P.; Spangler, J.; Swaminathan, R. S.; VanGundy, R. D.

2014-12-01

The majority of the population in southwest Virginia depends economically on coal mining. In 2011, coal mining generated $2,000,000 in tax revenue to Wise County alone. However, surface mining completely removes land cover and leaves the land exposed to erosion. The destruction of the forest cover directly impacts local species, as some are displaced and others perish in the mining process. Even though surface mining has a negative impact on the environment, land reclamation efforts are in place to either restore mined areas to their natural vegetated state or to transform these areas for economic purposes. This project aimed to monitor the progress of land reclamation and the effect on the return of local species. By incorporating NASA Earth observations, such as Landsat 8 Operational Land Imager (OLI) and Landsat 5 Thematic Mapper (TM), re-vegetation process in reclamation sites was estimated through a Time series analysis using the Normalized Difference Vegetation Index (NDVI). A continuous source of cloud free images was accomplished by utilizing the Spatial and Temporal Adaptive Reflectance Fusion Model (STAR-FM). This model developed synthetic Landsat imagery by integrating the high-frequency temporal information from Terra/Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) and high-resolution spatial information from Landsat sensors In addition, the Maximum Entropy Modeling (MaxENT), an eco-niche model was used to estimate the adaptation of animal species to the newly formed habitats. By combining factors such as land type, precipitation from Tropical Rainfall Measuring Mission (TRMM), and slope from Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), the MaxENT model produced a statistical analysis on the probability of species habitat. Altogether, the project compiled the ecological information which can be used to identify suitable habitats for local species in reclaimed mined areas.

Changes of Vegetation Distribution in the East Dongting Lake After the Operation of the Three Gorges Dam, China

PubMed Central

Hu, Jia-Yu; Xie, Yong-Hong; Tang, Yue; Li, Feng; Zou, Ye-Ai

2018-01-01

Water regime is regarded as the primary factor influencing the vegetation distribution in natural wetland ecosystems. However, the effect of water regime change induced by large-scale hydraulic engineering on vegetation distribution is still unclear. In this study, multi-temporal TM/ETM+/OLI images and hydrological data from 1995 to 2015 were used to elucidate how the change in water regime influenced the vegetation distribution in the East Dongting Lake (EDTL), especially after the operation of the Three Gorges Dam (TGD) in 2003. Using unsupervised and supervised classification methods, three types of land cover were identified in the study area: Water and Mudflat, Grass, and Reed and Forest. Results showed that the total vegetation area in EDTL increased by approximately 78 km2 during 1995–2015. The areas of Reed and Forest and Grass exhibited a contrasting trend, dramatic increase in Reed and Forest but sharp decrease in Grass, particularly after the operation of TGD. The lowest distribution elevations of Grass and Reed and Forest decreased by 0.61 and 0.52 m, respectively. As a result of water level variation, submergence duration increased at 20–21 m and 28 m elevations (1–13 days), but significantly decreased at 22–27 m and 29–30 m elevations (-3 to -31 days). The submergence duration of Grass and Reed and Forest was 246 and 177 days, respectively. This study indicated that wetland vegetation pattern significantly changed after the operation of TGD, mainly as a result of changes in submergence condition. Submergence duration might be an effective indicator to predict the shift of vegetation distribution in EDTL, and which could provide scientific guidance for vegetation restoration and wetland management in this lake. PMID:29765388

Change detection using Landsat images and an analysis of the linkages between the change and property tax values in the Istanbul Province of Turkey.

PubMed

Canaz, Sibel; Aliefendioğlu, Yeşim; Tanrıvermiş, Harun

2017-09-15

In this study, the Istanbul Province was monitored using Landsat 5 TM, MSS, Landsat 7 ETM+, and Landsat 8 OLI imagery from the years 1986, 2000, 2009, 2011, 2013, and 2015 in order to assess land cover changes in the province. The aim of the study was to classify manmade structures, land, green, and water areas, and to observe the changes in the province using satellite images. After classification, the images were compared in selected years to observe land cover. Moreover, these changes were correlated with the property tax values of Istanbul by years. The findings of the study showed that manmade structure areas increased while vegetation areas decreased due to rapid population growth, urbanization, and industrial and commercial development in Istanbul. These changes also explain the transformation of land from rural and natural areas to residential use, and serve as a tool with which to assess land value increments. Land value capturing is critical for the analysis of the linkages between the changes in land cover, and for assessing land transformation and urban growth. Due to inadequate market data, real estate tax values were used to analyze the linkages between detection changes, land cover, and taxation. In fact, the declared tax values of land owners are generally lower than the actual market values and therefore it is not possible to transfer the value increasing of land in urban areas by using property taxation from the owner to local and central governments. The research results also show that the integration of remote sensing results with real estate market data give us to determine the tax base values of real estate more realistically. Copyright © 2017 Elsevier Ltd. All rights reserved.

Carbon dioxide solubility in aqueous solutions of sodium chloride at geological conditions: Experimental results at 323.15, 373.15, and 423.15 K and 150 bar and modeling up to 573.15 K and 2000 bar

NASA Astrophysics Data System (ADS)

Zhao, Haining; Fedkin, Mark V.; Dilmore, Robert M.; Lvov, Serguei N.

2015-01-01

A new experimental system was designed to measure the solubility of CO2 at pressures and temperatures (150 bar, 323.15-423.15 K) relevant to geologic CO2 sequestration. At 150 bar, new CO2 solubility data in the aqueous phase were obtained at 323.15, 373.15, and 423.15 K from 0 to 6 mol kg-1 NaCl(aq) for the CO2-NaCl-H2O system. A γ - φ (activity coefficient - fugacity coefficient) type thermodynamic model is presented for the calculation of both the solubility of CO2 in the aqueous phase and the solubility of H2O in the CO2-rich phase for the CO2-NaCl-H2O system. Validation of the model calculations against literature data and other models (MZLL2013, AD2010, SP2010, DS2006, and OLI) show that the proposed model is capable of predicting the solubility of CO2 in the aqueous phase for the CO2-H2O and CO2-NaCl-H2O systems with a high degree of accuracy (AAD <3.9%) at temperatures from 273.15 to 573.15 K and pressures up to 2000 bar. A comparison of modeling results with experimental values revealed a pressure-bounded "transition zone" in which the CO2 solubility decreases to a minimum then increases as the temperature increases. CO2 solubility is not a monotonic function of temperature in the transition zone but outside of that transition zone, the CO2 solubility is decrease or increase monotonically in response to increased temperature. A link of web-based CO2 solubility computational tool can be provided by sending a message to Haining Zhao at hzz5047@gmail.com.

Using remotely-sensed multispectral imagery to build age models for alluvial fan surfaces

NASA Astrophysics Data System (ADS)

D'Arcy, Mitch; Mason, Philippa J.; Roda Boluda, Duna C.; Whittaker, Alexander C.; Lewis, James

2016-04-01

Accurate exposure age models are essential for much geomorphological field research, and generally depend on laboratory analyses such as radiocarbon, cosmogenic nuclide, or luminescence techniques. These approaches continue to revolutionise geomorphology, however they cannot be deployed remotely or in situ in the field. Therefore other methods are still needed for producing preliminary age models, performing relative dating of surfaces, or selecting sampling sites for the laboratory analyses above. With the widespread availability of detailed multispectral imagery, a promising approach is to use remotely-sensed data to discriminate surfaces with different ages. Here, we use new Landsat 8 Operational Land Imager (OLI) multispectral imagery to characterise the reflectance of 35 alluvial fan surfaces in the semi-arid Owens Valley, California. Alluvial fans are useful landforms to date, as they are widely used to study the effects of tectonics, climate and sediment transport processes on source-to-sink sedimentation. Our target fan surfaces have all been mapped in detail in the field, and have well-constrained exposure ages ranging from modern to ~ 125 ka measured using a high density of 10Be cosmogenic nuclide samples. Despite all having similar granitic compositions, the spectral properties of these surfaces vary systematically with their exposure ages. Older surfaces demonstrate a predictable shift in reflectance across the visible and short-wave infrared spectrum. Simple calculations, such as the brightness ratios of different wavelengths, generate sensitive power law relationships with exposure age that depend on post-depositional alteration processes affecting these surfaces. We investigate what these processes might be in this dryland location, and evaluate the potential for using remotely-sensed multispectral imagery for developing surface age models. The ability to remotely sense relative exposure ages has useful implications for preliminary mapping, selecting

Study on the Characteristics and Impacts of the Spatial-temporal Urban Sprawl in Chinese Coastal Cities using Ocelet

NASA Astrophysics Data System (ADS)

Li, M.; Lo Seen, D.; Zhang, Z.

2015-12-01

The urban population is expected to rise 67% in developing countries and 86% in developed regions by 2050. As the most populous country in the world, China has been experiencing a remarkable urbanization process since the initialization of the reform and opening-up policies in the late 1970s. During the past several decades, the coastal zone undergone the highest urbanization and motst rapid economic development in China. Accurately understanding the characteristics of the spatial-temporal urban sprawl is helpful for urban planning on optimal land use in the future. Ocelet is an interactive visual interpretation and dynamic coding method that has been designed for studying issues related to space, time and multiple scales that are raised when dynamic landscapes are modelled. Using Ocelet, we aim to study the characteristics of the spatial-temporal urban sprawl in thirteen major Chinese coastal cities and how urban sprawl affects the surrounding land changes. Landsat MSS/TM/ETM/OLI, the China-Brazil Earth Resources Satellite (CBERS) and Chinese HJ-1A data are adopted to acquire urban built-up areas and their dynamic changes from 1979 to 2013. The results show that the urban built-up area increased gradually from 1979 to 2002 (~105 km²/yr), then accelerated about four times from 2002 to 2010 (~396 km²/yr) in thirteen major Chinese coastal cities. Although the expansion slowed down since 2010, the urban built-up area still increased at a fairly high rate (~210 km²/yr) from 2010 to 2013. The urban sprawl speed and pattern in each coastal city has also been analyzed, and has been grouped in three costal zones geographically. As a result of urban sprawl, large areas of arable land, rural settlements and forests were lost in these coastal cities. The lost non-urban land types and areas are different in the three costal zones and quantified respectively.

The Use of High-Resolution Pléiades Images to Extract Volcanic-Cloud Top Heights and Plume Elevation Models: examples on Mount Etna (Italy) and Mount Ontake (Japan)

NASA Astrophysics Data System (ADS)

de Michele, Marcello; Raucoules, Daniel; Corradini, Stefano; Merucci, Luca; spinetti, claudia

2017-04-01

Accurate and spatially-detailed knowledge of Volcanic Cloud Top Height (VCTH) and velocity is crucial in volcanology. As an example, the ash/gas dispersion in the atmosphere, their impact and lifetime around the globe, greatly depends on the injection altitude. The VCTH is critical for ash dispersion modelling and air traffic security. Furthermore, the volcanic plume height during explosive volcanism is the primary parameter for estimating mass eruption rate. Satellite remote sensing offers a comprehensive and safe way to estimate VCTH. Recently, it has been shown that high spatial resolution optical imagery from Landsat-8 OLI sensor can be used to extract Volcanic Cloud Top Height with a precision of 250 meters and an accuracy or 300m (de Michele et al., 2016). This method allows to extract a Plume Elevation Model (PEM) by jointly measuring the parallax between two optical bands acquired with a time lag varying from 0.1 to 2.5 seconds depending on the bands chosen and the sensors employed. The measure of the parallax is biased because the volcanic cloud is moving between the two images acquisitions, even if the time lag is short. The precision of our measurements is enhanced by compensating the parallax by measuring the velocity of the volcanic cloud in the perpendicular-to-epipolar direction (which is height independent) and correcting the initial parallax measurement. In this study, we push this methodology forward. We apply it to the very high spatial resolution Pleiades data (1m pixel spacing) provided by the French Space Agency (CNES). We apply the method on Mount Etna, during the 05 September 2015 eruptive episode and on Mount Ontake eruption occurring on 30 September 2014. We are able to extract VCTH as a PEM with high spatial resolution and improved precision. Since Pléiades has an improved revisit time (1day), our method has potential for routine monitoring of volcanic plumes in clear sky conditions and when the VCTH is higher than meteo clouds.

Landsat Data Continuity Mission (LDCM) space to ground mission data architecture

USGS Publications Warehouse

Nelson, Jack L.; Ames, J.A.; Williams, J.; Patschke, R.; Mott, C.; Joseph, J.; Garon, H.; Mah, G.

2012-01-01

The Landsat Data Continuity Mission (LDCM) is a scientific endeavor to extend the longest continuous multi-spectral imaging record of Earth's land surface. The observatory consists of a spacecraft bus integrated with two imaging instruments; the Operational Land Imager (OLI), built by Ball Aerospace & Technologies Corporation in Boulder, Colorado, and the Thermal Infrared Sensor (TIRS), an in-house instrument built at the Goddard Space Flight Center (GSFC). Both instruments are integrated aboard a fine-pointing, fully redundant, spacecraft bus built by Orbital Sciences Corporation, Gilbert, Arizona. The mission is scheduled for launch in January 2013. This paper will describe the innovative end-to-end approach for efficiently managing high volumes of simultaneous realtime and playback of image and ancillary data from the instruments to the reception at the United States Geological Survey's (USGS) Landsat Ground Network (LGN) and International Cooperator (IC) ground stations. The core enabling capability lies within the spacecraft Command and Data Handling (C&DH) system and Radio Frequency (RF) communications system implementation. Each of these systems uniquely contribute to the efficient processing of high speed image data (up to 265Mbps) from each instrument, and provide virtually error free data delivery to the ground. Onboard methods include a combination of lossless data compression, Consultative Committee for Space Data Systems (CCSDS) data formatting, a file-based/managed Solid State Recorder (SSR), and Low Density Parity Check (LDPC) forward error correction. The 440 Mbps wideband X-Band downlink uses Class 1 CCSDS File Delivery Protocol (CFDP), and an earth coverage antenna to deliver an average of 400 scenes per day to a combination of LGN and IC ground stations. This paper will also describe the integrated capabilities and processes at the LGN ground stations for data reception using adaptive filtering, and the mission operations approach fro- the LDCM

Seaweed Farms in South Korea [detail

NASA Image and Video Library

2015-04-30

The dark squares that make up the checkerboard pattern in this image are fields of a sort—fields of seaweed. Along the south coast of South Korea, seaweed is often grown on ropes, which are held near the surface with buoys. This technique ensures that the seaweed stays close enough to the surface to get enough light during high tide but doesn’t scrape against the bottom during low tide. The Operational Land Imager (OLI) on Landsat 8 acquired this image of seaweed cultivation in the shallow waters around Sisan Island on January 31, 2014. Home to a thriving aquaculture industry, the south coast of South Korea produces about 90 percent of the country’s seaweed crop. The waters around Sisan are not the only place where aquaculture is common. View the large image to see how ubiquitous seaweed aquaculture is along the coast in Jeollanam-do, the southernmost province on the Korean peninsula. Two main types of seaweed are cultivated in South Korea: Undaria (known as miyeok in Korean, wakame in Japanese) and Pyropia (gim in Korean, nori in Japanese). Both types are used generously in traditional Korean, Japanese, and Chinese food. Since 1970, farmed seaweed production has increased by approximately 8 percent per year. Today, about 90 percent of all the seaweed that humans consume globally is farmed. That may be good for the environment. In comparison to other types of food production, seaweed farming has a light environmental footprint because it does not require fresh water or fertilizer. NASA Earth Observatory image by Jesse Allen, using Landsat data from the U.S. Geological Survey. Caption by Adam Voiland. Credit: NASA Earth Observatory NASA image use policy. NASA Goddard Space Flight Center enables NASA’s mission through four scientific endeavors: Earth Science, Heliophysics, Solar System Exploration, and Astrophysics. Goddard plays a leading role in NASA’s accomplishments by contributing compelling scientific knowledge to advance the Agency’s mission

Seaweed Farms in South Korea

NASA Image and Video Library

2015-04-30

The dark squares that make up the checkerboard pattern in this image are fields of a sort—fields of seaweed. Along the south coast of South Korea, seaweed is often grown on ropes, which are held near the surface with buoys. This technique ensures that the seaweed stays close enough to the surface to get enough light during high tide but doesn’t scrape against the bottom during low tide. The Operational Land Imager (OLI) on Landsat 8 acquired this image of seaweed cultivation in the shallow waters around Sisan Island on January 31, 2014. Home to a thriving aquaculture industry, the south coast of South Korea produces about 90 percent of the country’s seaweed crop. The waters around Sisan are not the only place where aquaculture is common. View the large image to see how ubiquitous seaweed aquaculture is along the coast in Jeollanam-do, the southernmost province on the Korean peninsula. Two main types of seaweed are cultivated in South Korea: Undaria (known as miyeok in Korean, wakame in Japanese) and Pyropia (gim in Korean, nori in Japanese). Both types are used generously in traditional Korean, Japanese, and Chinese food. Since 1970, farmed seaweed production has increased by approximately 8 percent per year. Today, about 90 percent of all the seaweed that humans consume globally is farmed. That may be good for the environment. In comparison to other types of food production, seaweed farming has a light environmental footprint because it does not require fresh water or fertilizer. NASA Earth Observatory image by Jesse Allen, using Landsat data from the U.S. Geological Survey. Caption by Adam Voiland. Credit: NASA Earth Observatory NASA image use policy. NASA Goddard Space Flight Center enables NASA’s mission through four scientific endeavors: Earth Science, Heliophysics, Solar System Exploration, and Astrophysics. Goddard plays a leading role in NASA’s accomplishments by contributing compelling scientific knowledge to advance the Agency’s mission

Assessing Land Management Changes and Population Dynamics in Central Burkina Faso in Response to Climate Change.

NASA Astrophysics Data System (ADS)

Kabore Bontogho, P. E.; Boubacar, I.; Afouda, A.; Joerg, H.

2015-12-01

Assessing landscape and population's dynamics at watershed level contribute to address anthropogenic aspect of climate change issue owing to the close link between LULC and climate changes. The objective of this study is to explore the dependencies of population to land management changes in Massili basin (2612 km²) located in central Burkina Faso. A set of three satellite scenes was acquired for the years 1990 (Landsat 7 ETM), 2002 (Landsat 7 ETM+) and 2013 (Landsat 8 OLI/TIRS) from the Global Land Cover Facility's (GLCF) website. Census data were provided by the National institute of statistics and demographic (INSD). The satellites images were classified using object-oriented classification method which was supported by historic maps and field data. Those were collected in order to allow for class definition, verification and accuracy assessments. Based on the developed land use maps, change analysis was carried out using post classification comparison in GIS. Finally, derived land use changes were compared with census data in order to explore links between population dynamics and the land use changes. It was found in 1990 that Massili watershed LULC was dominated by Tree/shrub savannah (69%, 1802.28 km2 ), Farm/Fallow was representing 22%, Gallery forest (4%), Settlement (3%), Barre soil (1%), Water bodies (1%). In 2002, the major landscape was Farm (54%). Tree/Shrub savannas were reduced to 36% while the Gallery Forest was decreased to1% of the basin area. The situation has also slightly changed in 2013 with an increase of the area devoted to farm/fallow and settlement at a rate of 3% and Gallery forest has increased to 4%. The changes in land use are in agreement with a notable increase in population. The analysis of census data showed that the number of inhabitants increased from 338 inhabitants per km2 in 1990 to 1150 inhabitants per km2 in 2013. As shown by statistical analysis (Kendall correlation tau=0.9), there is a close relation between both dynamics.

Litho-structural analysis of eastern part of Ilesha schist belt, Southwestern Nigeria

NASA Astrophysics Data System (ADS)

Fagbohun, Babatunde Joseph; Adeoti, Blessing; Aladejana, Olabanji Odunayo

2017-09-01

The Ilesha schist belt is an excellent example of high strain shear belt within basement complex of southwestern Nigeria which is part of the larger West African Shield. The Ilesha schist belt is characterised by metasediment-metavolcanic, migmatite-gneiss and older granite rocks and the occurrence of a Shear zone which has been traced to and correlated with the central Hoggar Neoproterozoic shear zone as part of the Trans-Saharan Belt. Although the area is interesting in terms of geologic-tectonic setting, however, detailed geological assessment and structural interpretation of features in this area is lacking due accessibility problem. For these reasons we applied principal component analysis (PCA) and band ratio (BR) techniques on Landsat 8 OLI data for lithological discrimination while for structural interpretation, filtering techniques of edge enhancement and edge detection was applied on digital elevation model (DEM) acquired by shuttle radar topographic mission (SRTM) sensor. The PCA outperform BR for discrimination between quartzite and granite which are the most exposed rock units in the area. For structural interpretation, DEM was used to generate shaded relief model and edge maps which enable detailed structural interpretation. Geologic fieldwork was further conducted to validate structures and units identified from image processing. Based image interpretation, three deformation events were identified. The first event (D1) which is majorly a ductile deformation produced foliations and folds whose axial planes trend in NNE-SSW. The second event (D2) resulted in reactivation and rotation of the D1 structures particularly the folds in the NE-SW. The third event (D3) produced a transgressive deformation starting with the ductile deformation resulting in the development of sigmoidal structures oriented in NE-SW to E-W direction and the brittle deformation occurring at later stages producing fractures oriented in the E-W to NE-SW directions. These results have

Quantifying seasonal velocity at Khumbu Glacier, Nepal

NASA Astrophysics Data System (ADS)

Miles, E.; Quincey, D. J.; Miles, K.; Hubbard, B. P.; Rowan, A. V.

2017-12-01

While the low-gradient debris-covered tongues of many Himalayan glaciers exhibit low surface velocities, quantifying ice flow and its variation through time remains a key challenge for studies aimed at determining the long-term evolution of these glaciers. Recent work has suggested that glaciers in the Everest region of Nepal may show seasonal variability in surface velocity, with ice flow peaking during the summer as monsoon precipitation provides hydrological inputs and thus drives changes in subglacial drainage efficiency. However, satellite and aerial observations of glacier velocity during the monsoon are greatly limited due to cloud cover. Those that do exist do not span the period over which the most dynamic changes occur, and consequently short-term (i.e. daily) changes in flow, as well as the evolution of ice dynamics through the monsoon period, remain poorly understood. In this study, we combine field and remote (satellite image) observations to create a multi-temporal, 3D synthesis of ice deformation rates at Khumbu Glacier, Nepal, focused on the 2017 monsoon period. We first determine net annual and seasonal surface displacements for the whole glacier based on Landsat-8 (OLI) panchromatic data (15m) processed with ImGRAFT. We integrate inclinometer observations from three boreholes drilled by the EverDrill project to determine cumulative deformation at depth, providing a 3D perspective and enabling us to assess the role of basal sliding at each site. We additionally analyze high-frequency on-glacier L1 GNSS data from three sites to characterize variability within surface deformation at sub-seasonal timescales. Finally, each dataset is validated against repeat-dGPS observations at gridded points in the vicinity of the boreholes and GNSS dataloggers. These datasets complement one another to infer thermal regime across the debris-covered ablation area of the glacier, and emphasize the seasonal and spatial variability of ice deformation for glaciers in High

Mountain glaciers darkening: geochemical characterizazion of cryoconites and their radiative impact on the Vadret da Morteratsch (Swiss Alps)

NASA Astrophysics Data System (ADS)

Di Mauro, Biagio; Baccolo, Giovanni; Garzonio, Roberto; Piazzalunga, Andrea; Massabò, Dario; Colombo, Roberto

2016-04-01

Mountain glaciers represent an important source of fresh water across the globe. It is well known that these reservoirs are seriously threatened by global climate change, and a widespread reduction of glacier extension has been observed in recent years. Surface processes that promote ice melting are driven both by air temperature/precipitation and surface albedo. This latter is mainly influenced by the growth of snow grains and by the impurities content (such as mineral dust, soot, ash etc.). The origin of these light-absorbing impurities can be local or distal, and often, as a consequence of melting processes, they can aggregate on the glacier tongue, forming characteristics cryoconites, that decrease ice albedo and hence promote the melting. In this contribution, we coupled satellite images (EO1 - Hyperion and Landsat 8 - OLI) and ground hyperspectral data (ASD field spectrometer) for characterizing ice and snow surface reflectance of the Vadret da Morteratsch glacier (Swiss Alps). On the glacier ablation zone, we sampled ice, snow, surface dust and cryoconite material. To evaluate the possible impact of anthropogenic and natural emissions on cryoconites formation, we determined their geochemical composition (through the Neutron Activation Analysis, NAA) and the concentration of Black Carbon (BC), Organic Carbon (OC), Elemental Carbon (EC) and Levoglucosan. From satellite data, we computed the Snow Darkening Index (SDI), which is non-linearly correlated with dust content in snow. Results showed that, during 2015 summer season, ice albedo in the ablation zone reached very low values of about 0.1-0.2. The darkening of the glacier can be attributed to the impact of surface dust (from lateral moraine and Saharan desert) and cryoconites, coupled with grain growth driven by the extremely warm 2015 summer. The geochemical characterization of non-ice material contained in the cryoconites can provide important information regarding their source and the possible impact of

Effects of olive and fish oil Ca soaps in ewe diets on milk fat and muscle and subcutaneous tissue fatty-acid profiles of suckling lambs.

PubMed

Gallardo, B; Gómez-Cortés, P; Mantecón, A R; Juárez, M; Manso, T; de la Fuente, M A

2014-07-01

Enhancing healthy fatty acids (FAs) in ewe milk fat and suckling lamb tissues is an important objective in terms of improving the nutritional value of these foods for the consumer. The present study examined the effects of feeding-protected lipid supplements rich in unsaturated FAs on the lipid composition of ewe milk, and subsequently in the muscle and subcutaneous adipose tissues of lambs suckling such milk. Thirty-six pregnant Churra ewes with their new-born lambs were assigned to one of three experimental diets (forage/concentrate ratio 50 : 50), each supplemented with either 3% Ca soap FAs of palm (Control), olive (OLI) or fish (FO) oil. The lambs were nourished exclusively by suckling for the whole experimental period. When the lambs reached 11 kg BW, they were slaughtered and samples were taken from the Longissimus dorsi and subcutaneous fat depots. Although milk production was not affected by lipid supplementation, the FO diet decreased fat content (P0.05) and other trans-FAs between Control and FO treatments would indicate that FO treatment does not alter rumen biohydrogenation pathways under the assayed conditions. Changes in dam milk FA composition induced differences in the FA profiles of meat and fat depots of lambs, preferentially incorporated polyunsaturated FAs into the muscle rather than storing them in the adipose tissue. In the intramuscular fat of the FO treatment, all the n-3 FAs reached their highest concentrations: 0.97 (18:3 n-3), 2.72 (20:5 n-3), 2.21 (22:5 n-3) and 1.53% (22:6 n-3). In addition, not only did FO intramuscular fat have the most cis-9, trans-11 18:2 (1.66%) and trans-11 18:1 (3.75%), but also the lowest n-6/n-3 ratio (1.80) and saturated FA content were not affected. Therefore, FO exhibited the best FA profile from a nutritional point of view.

Satellite Derived Seafloor Bathymetry and Habitat Mapping on a Shallow Carbonate Platform: Campeche Bank, México.

NASA Astrophysics Data System (ADS)

Garza-Perez, J. R.; Rankey, E. C.; Rodriguez-Vázquez, R. A.; Naranjo-Garcia, M. J.

2017-12-01

Extensive and consistent high-resolution seafloor mapping is a difficult task involving important financial resources, intensive field work and careful planning; thus there is a paucity of this type of mapping products both in spatial distribution and through time. Remote sensed imagery has supported continuous mapping efforts elsewhere, but extensive seafloor mapping, even in shallow regions keeps being elusive. Challenges to this effort include cloud cover, surface sun-glint, and water turbidity caused by sediment resuspension and primary productivity. Nevertheless, using high-quality satellite imagery (Landsat-8 OLI -30x30m/pixel- and GeoEye-1 -2x2m/pixel) and rigorous pre-processing (atmospheric correction, de-glinting and water-column light extinction compensation), resulting data contribute towards the advancement of seafloor mapping. The Yucatan Peninsula in México is a carbonate ramp devoid of significant orographic features and surface water bodies. Its submerged portion is the Campeche Bank, gently sloping towards the Gulf of Mexico. The bottom features several distinct blankets composed by medium-fine sediment (dominated by pelecypods, gastropods, foraminifera, lithoclasts, calcareous peloids and algal nodules, Halimeda plaques and coralline algae fragments), and a reef unit with several bank-type coral reefs. Outside the coral reefs, biotic cover down to 20 m deep is dominated by macroalgae (red, brown, green), coralline and filamentous algae with sharp seasonal changes in abundance, from almost nil during north-winds (Oct. - Jan.) to high during dry (Feb.- May) and rainy seasons (Jun. - Sept.), with changes of dominance by algae groups between dry and rainy seasons. This bloom is favored by increases in sunlight and nutrients carried by the Caribbean current upwelling washing the Campeche Bank. Beyond 20 m depth, sandy plains dominate the seascape. Corals, octocorals, sponges and tunicates are spatially restricted to bottoms with thin layers of

On the added value of WUDAPT for Urban Climate Modelling

NASA Astrophysics Data System (ADS)

Brousse, Oscar; Martilli, Alberto; Mills, Gerald; Bechtel, Benjamin; Hammerberg, Kris; Demuzere, Matthias; Wouters, Hendrik; Van Lipzig, Nicole; Ren, Chao; Feddema, Johannes J.; Masson, Valéry; Ching, Jason

2017-04-01

Over half of the planet's population now live in cities and is expected to grow up to 65% by 2050 (United Nations, 2014), most of whom will actually occupy new emerging cities of the global South. Cities' impact on climate is known to be a key driver of environmental change (IPCC, 2014) and has been studied for decades now (Howard, 1875). Still very little is known about our cities' structure around the world, preventing urban climate simulations to be done and hence guidance to be provided for mitigation. Assessing the need to bridge the urban knowledge gap for urban climate modelling perspectives, the World Urban Database and Access Portal Tool - WUDAPT - project (Ching et al., 2015; Mills et al., 2015) developed an innovative technique to map cities globally rapidly and freely. The framework established by Bechtel and Daneke (2012) derives Local Climate Zones (Stewart and Oke, 2012) city maps out of LANDSAT 8 OLI-TIRS imagery (Bechtel et al., 2015) through a supervised classification by a Random Forest Classification algorithm (Breiman, 2001). The first attempt to implement Local Climate Zones (LCZ) out of the WUDAPT product within a major climate model was carried out by Brousse et al. (2016) over Madrid, Spain. This study proved the applicability of LCZs as an enhanced urban parameterization within the WRF model (Chen et al. 2011) employing the urban canopy model BEP-BEM (Martilli, 2002; Salamanca et al., 2010), using the averaged values of the morphological and physical parameters' ranges proposed by Stewart and Oke (2012). Other studies have now used the Local Climate Zones for urban climate modelling purposes (Alexander et al., 2016; Wouters et al. 2016; Hammerberg et al., 2017; Brousse et al., 2017) and demonstrated the added value of the WUDAPT dataset. As urban data accessibility is one of the major challenge for simulations in emerging countries, this presentation will show results of simulations using LCZs and the capacity of the WUDAPT framework to be

Bacterial colonization of the implant-abutment interface of conical connection with an internal octagon: an in vitro study using real-time PCR.

PubMed

Baj, A; Beltramini, G A; Bolzoni, A; Cura, F; Palmieri, A; Scarano, A; Ottria, L; Giannì, A B

2017-01-01

Bacterial leakage at the implant-abutment connection of a two-piece implant system is considered the main cause of peri-implantitis. Prevention of bacterial leakage at the implant-abutment connection is mandatory for reducing inflammation process around implant neck and achieving bone stability. Micro-cavities at implant-abutment connection level can favour bacterial leakage, even in modern two-piece implant systems. The conical connection with an internal octagon (CCIO) is considered to be more stable mechanically and allows a more tight link between implant and abutment. As P. gingivalis and T. forsythia penetration might have clinical relevance, it was the purpose of this investigation to evaluate molecular leakage of these two bacteria in a new two-implant system with an internal conical implant-abutment connection with internal octagon (Shiner XT, FMD Falappa Medical Devices S.p.A. Rome, Italy). To verify the ability of the implant in protecting the internal space from the external environment, the passage of genetically modified Escherichia c oli across implant-abutment interface was evaluated. Four Shiner XT implants (FMD, Falappa Medical Devices®, Rome, Italy) were immerged in a bacterial culture for 24 h and bacteria amount was measured inside implant-abutment interface with Real-time PCR. Bacteria were detected inside all studied implants, with a median percentage of 6% for P. gingivalis and 5% for T. forsythia. Other comparable studies about the tightness of the tested implant system reported similar results. The gap size at the implant-abutment connection of CCIOs was measured by other authors discovering a gap size of 1–2μm of the AstraTech system and of 4μm for the Ankylos system. Bacterial leakage along implant-abutment connection of cylindrical and tapered implants, Shiner XT, (FMD Falappa Medical Devices S.p.A. Rome, Italy) showed better results compared to other implants. Additional studies are needed to explore the relationship in terms of

Uncertainty analysis of moderate- versus coarse-scale satellite fire products for quantifying agricultural burning: Implications for Air Quality in European Russia, Belarus, and Lithuania

NASA Astrophysics Data System (ADS)

McCarty, J. L.; Krylov, A.; Prishchepov, A. V.; Banach, D. M.; Potapov, P.; Tyukavina, A.; Rukhovitch, D.; Koroleva, P.; Turubanova, S.; Romanenkov, V.

2015-12-01

Cropland and pasture burning are common agricultural management practices that negatively impact air quality at a local and regional scale, including contributing to short-lived climate pollutants (SLCPs). This research focuses on both cropland and pasture burning in European Russia, Lithuania, and Belarus. Burned area and fire detections were derived from 500 m and 1 km Moderate Resolution Imaging Spectroradiometer (MODIS), 30 m Landsat 7 Enhanced Thematic Mapper Plus (ETM+), and Landsat 8 Operational Land Imager (OLI) data. Carbon, particulate matter, volatile organic carbon (VOCs), and harmful air pollutants (HAPs) emissions were then calculated using MODIS and Landsat-based estimates of fire and land-cover and land-use. Agricultural burning in Belarus, Lithuania, and European Russia showed a strong and consistent seasonal geographic pattern from 2002 to 2012, with the majority of fire detections occurring in March - June and smaller peak in July and August. Over this 11-year period, there was a decrease in both cropland and pasture burning throughout this region. For Smolensk Oblast, a Russian administrative region with comparable agro-environmental conditions to Belarus and Lithuania, a detailed analysis of Landsat-based burned area estimations for croplands and pastures and field data collected in summer 2014 showed that the agricultural burning area can be up to 10 times higher than the 1 km MODIS active fire estimates. In general, European Russia is the main source of agricultural burning emissions compared to Lithuania and Belarus. On average, all cropland burning in European Russia as detected by the MCD45A1 MODIS Burned Area Product emitted 17.66 Gg of PM10 while annual burning of pasture in Smolensk Oblast, Russia as detected by Landsat burn scars emitted 494.85 Gg of PM10, a 96% difference. This highlights that quantifying the contribution of pasture burning and burned area versus cropland burning in agricultural regions is important for accurately

The impact of heat waves on surface urban heat island and local economy in Cluj-Napoca city, Romania

NASA Astrophysics Data System (ADS)

Herbel, Ioana; Croitoru, Adina-Eliza; Rus, Adina Viorica; Roşca, Cristina Florina; Harpa, Gabriela Victoria; Ciupertea, Antoniu-Flavius; Rus, Ionuţ

2017-07-01

The association between heat waves and the urban heat island effect can increase the impact on environment and society inducing biophysical hazards. Heat stress and their associated public health problems are among the most frequent. This paper explores the heat waves impact on surface urban heat island and on the local economy loss during three heat periods in Cluj-Napoca city in the summer of 2015. The heat wave events were identified based on daily maximum temperature, and they were divided into three classes considering the intensity threshold: moderate heat waves (daily maximum temperature exceeding the 90th percentile), severe heat waves (daily maximum temperature over the 95th percentile), and extremely severe heat waves (daily maximum temperature exceeding the 98th percentile). The minimum length of an event was of minimum three consecutive days. The surface urban heat island was detected based on land surface temperature derived from Landsat 8 thermal infrared data, while the economic impact was estimated based on data on work force structure and work productivity in Cluj-Napoca derived from the data released by Eurostat, National Bank of Romania, and National Institute of Statistics. The results indicate that the intensity and spatial extension of surface urban heat island could be governed by the magnitude of the heat wave event, but due to the low number of satellite images available, we should consider this information only as preliminary results. Thermal infrared remote sensing has proven to be a very efficient method to study surface urban heat island, due to the fact that the synoptic conditions associated with heat wave events usually favor cloud free image. The resolution of the OLI_TIRS sensor provided good results for a mid-extension city, but the low revisiting time is still a drawback. The potential economic loss was calculated for the working days during heat waves and the estimated loss reached more than 2.5 mil. EUR for each heat wave day

Secondary structure and dynamics study of the intrinsically disordered silica-mineralizing peptide P 5 S 3 during silicic acid condensation and silica decondensation

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

Zerfaß, Christian; Buchko, Garry W.; Shaw, Wendy J.

The silica forming repeat R5 of sil1 from Cylindrotheca fusiformis was the blueprint for the design of P5S3, a 50-residue peptide which can be produced in large amounts by recombinant bacterial expression. It contains five protein kinase A target sites and is highly cationic due to 10 lysine and 10 arginine residues. In the presence of supersaturated ortho silicic acid P5S3 strongly enhances silica-formation whereas it retards the dissolution of amorphous silica (SiO2) at globally undersaturated concentrations. The secondary structure of P5S3 during these different functions was studied by circular dichroism (CD), complemented by nuclear magnetic resonance (NMR) studies ofmore » the peptide in the absence of silicate. The NMR studies of dual-labeled (13C, 15N) P5S3 revealed a disordered structure at pH 2.8 and 4.5. Within the pH range of 4.5 to 9.5, the CD data verified the disordered secondary structure but also suggested the presence of some polyproline II character in the absence of silicic acid. Upon silicic acid polymerization and during dissolution of preformed silica, the CD spectrum of P5S3 indicated partial transition into an α-helical conformation which was transient during silica-dissolution. Consequently, the secondary structural changes observed for P5S3 correlate with the presence of oli-gomeric/polymeric silicic acid, presumably due to P5S3-silicic acid interactions. These interactions appear, at least in part, ionic in nature since dodecylsulfate micelles, which are negatively charged, cause similar conformational shifts to P5S3 in the absence of silica while ß-D-dodecyl maltoside micelles, which are neutral, do not. Thus, P5S3 influences both the condensation of silicic acid into silica and its decondensation back to silicic acid. Moreover, the dynamics of these pro-cesses may be indirectly monitored by following structural changes to P5S3 with CD spectroscopy.« less

Effect of nicotinamide on amino acids content in bone collagen depending on biological availability of vitamins in diabetic rats.

PubMed

Guzyk, M M; Sergiichuk, Iu T; Dyakun, K O; Yanitska, L V; Kuchmerovska, T M

2014-01-01

Connective tissue is highly susceptible to imbalances induced by diabetes. Diabetes-related osteopenia, decreased bone strength etc. may be associated with altered metabolism of various collagens: Although it is assumed that alterations in collagen amino acids (AA) may strongly affect protein properties andphysiological functions, however, very limited evidences are present at the moment regarding AA composition of bone type I collagen and its relevance to abnormal availability of vitamins which are necessary for collagen synthesis in diabetes. We have tested whether nicotinamide (NAm) can influence type Icollagen formation and AA composition as well as vitamins availability in diabetes. After 4 weeks of STZ-induced diabetes (60 mg/ kg) male Wistar rats were injected for 2 weeks with/without NAm (200 mg/kg b. w). Acid extraction of type I collagen from the bones was performed with following stepwise salting out. The content of type I collagen after its acid extraction from the bones was estimated by the amounts of hydroxyproline. Amino acids were assayed by cation exchange chromatography Diabetes-associated changes in AA composition of type I collagen mainly affect those amino acids which are known to be involved in helix formation and cross-linking of the molecules. Diabetes was found to significantly reduce bone collagen contents of o-Pro, Gly, Ala, o-Lys and Pro, whereas Lys, His, Arg, Glu, Thr, Leu, Phe contents were elevated (P < 0.05). NAm treatment was able to partially normalise AA contents. In diabetes, blood serum and hepatic vitamin C and B3 contents were shown to be significantly lowered, whereas a-tocopherol was slightly increased compared with control (P < 0.05). Restoration of circulatory and liver vitamin C and B3 was observed. The data demonstrate the close relationship between the diabetes-associated decrease in type I collagen deposition, altered amino acids metabolism and impaired availability of vitamins, which are necessary for collagen

Applications of NASA Earth Observation Imagery in Google Earth Engine to Estimate Glacier Trends and Water Availability in Chile's Aconcagua Watershed

NASA Astrophysics Data System (ADS)

Webb, M. J.; Babis, B.; Deland, S.; McGurk, G.

2017-12-01

The Aconcagua basin of Central Chile, just north of the capital city of Santiago, is characterized by the glaciated Andes to the east, which supply meltwater runoff to the lower fertile river valleys. Known for the production of fruit and vegetable crops, the region is experiencing stressed hydrologic resources as a result of anomalous climate conditions and anthropogenic water consumption. Traditionally, the wet and cool winter months account for 80 percent of Aconcagua's total annual precipitation, while dry and warm conditions prevail during the summer months. Consequently, the basin depends on seasonal glacial accumulation to provide water storage for the dry season when up to 67 percent of water is derived from glacial runoff. Overall, 70 percent of regional water is consumed by agricultural practices, specifically the fruit and vegetable farming that thrives in Aconcagua's Mediterranean-type climate. Globally, weather intensification and the rising zero-degree isotherm are poised to threaten the stability and longevity of glacial water resources. In recent years, Chile has experienced periods of prolonged drought as well as glacier shrinkage. The Aconcagua basin is especially vulnerable to these changes as a consequence of its agricultural economies and reliance on sub-tropical glaciers for water resources. Aconcagua is among the top three regions contributing to Chile's gross domestic product (GDP). Furthermore, in 2011 the Chilean government announced plans to increase the national land under irrigation by 57 percent by 2022. In partnership with the Chilean Ministry of Agriculture, the objective of this research was to integrate NASA Earth observations in conjunction with in situ river discharge measurements into Google Earth Engine to enhance regional understanding of current and future climate conditions in Chile. The remotely-sensed datasets included Landsat TM/OLI derived glacial extent, Terra MODIS snow cover and surface temperature, and Aqua AMSR

A cost effective and operational methodology for wall to wall Above Ground Biomass (AGB) and carbon stocks estimation and mapping: Nepal REDD+

NASA Astrophysics Data System (ADS)

Gilani, H., Sr.; Ganguly, S.; Zhang, G.; Koju, U. A.; Murthy, M. S. R.; Nemani, R. R.; Manandhar, U.; Thapa, G. J.

2015-12-01

Nepal is a landlocked country with 39% forest cover of the total land area (147,181 km2). Under the Forest Carbon Partnership Facility (FCPF) and implemented by the World Bank (WB), Nepal chosen as one of four countries best suitable for results-based payment system for Reducing Emissions from Deforestation and Forest Degradation (REDD and REDD+) scheme. At the national level Landsat based, from 1990 to 2000 the forest area has declined by 2%, i.e. by 1467 km2, whereas from 2000 to 2010 it has declined only by 0.12% i.e. 176 km2. A cost effective monitoring and evaluation system for REDD+ requires a balanced approach of remote sensing and ground measurements. This paper provides, for Nepal a cost effective and operational 30 m Above Ground Biomass (AGB) estimation and mapping methodology using freely available satellite data integrated with field inventory. Leaf Area Index (LAI) generated based on propose methodology by Ganguly et al. (2012) using Landsat-8 the OLI cloud free images. To generate tree canopy height map, a density scatter graph between the Geoscience Laser Altimeter System (GLAS) on the Ice, Cloud, and Land Elevation Satellite (ICESat) estimated maximum height and Landsat LAI nearest to the center coordinates of the GLAS shots show a moderate but significant exponential correlation (31.211*LAI0.4593, R2= 0.33, RMSE=13.25 m). From the field well distributed circular (750m2 and 500m2), 1124 field plots (0.001% representation of forest cover) measured which were used for estimation AGB (ton/ha) using Sharma et al. (1990) proposed equations for all tree species of Nepal. A satisfactory linear relationship (AGB = 8.7018*Hmax-101.24, R2=0.67, RMSE=7.2 ton/ha) achieved between maximum canopy height (Hmax) and AGB (ton/ha). This cost effective and operational methodology is replicable, over 5-10 years with minimum ground samples through integration of satellite images. Developed AGB used to produce optimum fuel wood scenarios using population and road

A New Technique For Quantifying Effusive Volcanic Activity at Tolbachik Volcano Using Multiple Remote Sensing Platforms

NASA Astrophysics Data System (ADS)

McAlpin, D. B.; Meyer, F. J.; Dehn, J.; Webley, P. W.

2016-12-01

In 1976, "The Great Tolbachik Fissure Eruption," became the largest basaltic eruption in the recorded history of the Kamchatka Peninsula. In November 2012, after thirty-six years of quiescence, Tolbachik again erupted, and continued for nine months until its end in August, 2013. Observers of the 2012-13 eruption reported a mostly effusive eruption from two main fissures, long, rapidly moving lava flows, and ash clouds of up to 6 km. Initial estimates of effusive activity reported an approximate volume of 0.52 km³ over an area of more than 35 km². In this analysis, we provide updated effusion estimates for the Tolbachik eruption, determined by thermal data acquired by the Advanced Very High Resolution Radiometer (AVHRR) satellites. Each of the four AVHRR satellites carries a broad-band, five channel sensor that acquires data in the visible and infrared portions of the electromagnetic spectrum, with each satellite completing 14 daily Earth orbits. A critical component to the volume estimates is a determination of fissure size and the area of lava flow at different times during the eruption. For this purpose, we acquired optical satellite images obtained from three orbiting platforms: the Advanced Land Imager (ALI),) aboard the Earth Observer-1 (EO-1) satellite, the Operational Land Imager (OLI) aboard Landsat 8, and the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) aboard NASA's Terra satellite. From these multiple platforms, lava flow maps were prepared from repeat acquisitions over the course of the eruption. Periodic lava flow measurements clarify effusion rates as instantaneous discharge rates, mean effusion rates over time, and an overall effusion rate over the entire eruption. Given the natural limitations of effusion estimates derived from thermal data, our results are compared to effusion estimates derived by DEM differencing to evaluate accuracy. This analysis is a true multi-sensor technique that affords a method to rapidly

Spatially detailed retrievals of spring phenology from single-season high-resolution image time series

NASA Astrophysics Data System (ADS)

Vrieling, Anton; Skidmore, Andrew K.; Wang, Tiejun; Meroni, Michele; Ens, Bruno J.; Oosterbeek, Kees; O'Connor, Brian; Darvishzadeh, Roshanak; Heurich, Marco; Shepherd, Anita; Paganini, Marc

2017-07-01

Vegetation indices derived from satellite image time series have been extensively used to estimate the timing of phenological events like season onset. Medium spatial resolution (≥250 m) satellite sensors with daily revisit capability are typically employed for this purpose. In recent years, phenology is being retrieved at higher resolution (≤30 m) in response to increasing availability of high-resolution satellite data. To overcome the reduced acquisition frequency of such data, previous attempts involved fusion between high- and medium-resolution data, or combinations of multi-year acquisitions in a single phenological reconstruction. The objectives of this study are to demonstrate that phenological parameters can now be retrieved from single-season high-resolution time series, and to compare these retrievals against those derived from multi-year high-resolution and single-season medium-resolution satellite data. The study focuses on the island of Schiermonnikoog, the Netherlands, which comprises a highly-dynamic saltmarsh, dune vegetation, and agricultural land. Combining NDVI series derived from atmospherically-corrected images from RapidEye (5 m-resolution) and the SPOT5 Take5 experiment (10m-resolution) acquired between March and August 2015, phenological parameters were estimated using a function fitting approach. We then compared results with phenology retrieved from four years of 30 m Landsat 8 OLI data, and single-year 100 m Proba-V and 250 m MODIS temporal composites of the same period. Retrieved phenological parameters from combined RapidEye/SPOT5 displayed spatially consistent results and a large spatial variability, providing complementary information to existing vegetation community maps. Retrievals that combined four years of Landsat observations into a single synthetic year were affected by the inclusion of years with warmer spring temperatures, whereas adjustment of the average phenology to 2015 observations was only feasible for a few pixels

Evolution and hazard analysis of high-mountain lakes in the Cordillera Vilcabamba (Southern Peru) from 1991 to 2014

NASA Astrophysics Data System (ADS)

Guardamino, Lucía; Drenkhan, Fabian

2015-04-01

In recent decades, glaciers in high-mountain regions have experienced unprecedented glacier retreat since the Little Ice Age (LIA). This development triggers the formation and growth of glacier lakes, which in combination with changes in glacier parameters might produce more frequent conditions for the occurrence of disasters, such as Glacier Lake Outburst Floods (GLOF). Facing such a scenario, the analysis of changing lake characteristics and identification of new glacier lakes are imperative in order to identify and reduce potential hazards and mitigate or prevent future disasters for adjacent human settlements. In this study, we present a multi-temporal analysis with Landsat TM 5 and OLI 8 images between 1991 and 2014 in the Cordillera Vilcabamba region (Southern Peru), a remote area with difficult access and climate and glaciological in-situ data scarcity. A semi-automatic model was developed using the band ratios Normalized Difference Snow Index (NDSI) and Normalized Difference Water Index (NDWI) in order to identify glacier and lake area changes. Results corroborate a strong glacier area reduction of about 51% from 1991 (200.3 km²) to 2014 (98.4 km²). At the same time, the number of lakes (total lake surface) has increased at an accelerated rate, from 0.77% (0.48%) in 1991 to 2.31% (2.49%) in 2014. In a multiple criteria analysis to identify potential hazards, 90 out of a total of 329 lakes in 2014 have been selected for further monitoring. Additionally, 29 population centers have been identified as highly exposed to lake related hazards from which 25 indicate a distance less than 1 km to an upstream lake and four are situated in a channel of potential debris flow. In these areas human risks are particularly high in view of a low HDI below Peru's average and hence pronounced vulnerability. We suggest more future research on measurements and monitoring of glacier and lake characteristics in these remote high-mountain regions, which include comprehensive risk

Landscape effects of wildfire on permafrost distribution in interior Alaska derived from remote sensing

USGS Publications Warehouse

Brown, Dana R. N.; Jorgenson, M. Torre; Kielland, Knut; Verbyla, David L.; Prakash, Anupma; Koch, Joshua C.

2016-01-01

Climate change coupled with an intensifying wildfire regime is becoming an important driver of permafrost loss and ecosystem change in the northern boreal forest. There is a growing need to understand the effects of fire on the spatial distribution of permafrost and its associated ecological consequences. We focus on the effects of fire a decade after disturbance in a rocky upland landscape in the interior Alaskan boreal forest. Our main objectives were to (1) map near-surface permafrost distribution and drainage classes and (2) analyze the controls over landscape-scale patterns of post-fire permafrost degradation. Relationships among remote sensing variables and field-based data on soil properties (temperature, moisture, organic layer thickness) and vegetation (plant community composition) were analyzed using correlation, regression, and ordination analyses. The remote sensing data we considered included spectral indices from optical datasets (Landsat 7 Enhanced Thematic Mapper Plus (ETM+) and Landsat 8 Operational Land Imager (OLI)), the principal components of a time series of radar backscatter (Advanced Land Observing Satellite—Phased Array type L-band Synthetic Aperture Radar (ALOS-PALSAR)), and topographic variables from a Light Detection and Ranging (LiDAR)-derived digital elevation model (DEM). We found strong empirical relationships between the normalized difference infrared index (NDII) and post-fire vegetation, soil moisture, and soil temperature, enabling us to indirectly map permafrost status and drainage class using regression-based models. The thickness of the insulating surface organic layer after fire, a measure of burn severity, was an important control over the extent of permafrost degradation. According to our classifications, 90% of the area considered to have experienced high severity burn (using the difference normalized burn ratio (dNBR)) lacked permafrost after fire. Permafrost thaw, in turn, likely increased drainage and resulted in

Preliminary study of near surface detections at geothermal field using optic and SAR imageries

NASA Astrophysics Data System (ADS)

Kurniawahidayati, Beta; Agoes Nugroho, Indra; Syahputra Mulyana, Reza; Saepuloh, Asep

2017-12-01

Current remote sensing technologies shows that surface manifestation of geothermal system could be detected with optical and SAR remote sensing, but to assess target beneath near the surface layer with the surficial method needs a further study. This study conducts a preliminary result using Optic and SAR remote sensing imagery to detect near surface geothermal manifestation at and around Mt. Papandayan, West Java, Indonesia. The data used in this study were Landsat-8 OLI/TIRS for delineating geothermal manifestation prospect area and an Advanced Land Observing Satellite(ALOS) Phased Array type L-band Synthetic Aperture Radar (PALSAR) level 1.1 for extracting lineaments and their density. An assumption was raised that the lineaments correlated with near surface structures due to long L-band wavelength about 23.6 cm. Near surface manifestation prospect area are delineated using visual comparison between Landsat 8 RGB True Colour Composite band 4,3,2 (TCC), False Colour Composite band 5,6,7 (FCC), and lineament density map of ALOS PALSAR. Visual properties of ground object were distinguished from interaction of the electromagnetic radiation and object whether it reflect, scatter, absorb, or and emit electromagnetic radiation based on characteristic of their molecular composition and their macroscopic scale and geometry. TCC and FCC composite bands produced 6 and 7 surface manifestation zones according to its visual classification, respectively. Classified images were then compared to a Normalized Different Vegetation Index (NDVI) to obtain the influence of vegetation at the ground surface to the image. Geothermal area were classified based on vegetation index from NDVI. TCC image is more sensitive to the vegetation than FCC image. The later composite produced a better result for identifying visually geothermal manifestation showed by detail-detected zones. According to lineament density analysis high density area located on the peak of Papandayan overlaid with zone 1

Development of Thermal Infrared Sensor to Supplement Operational Land Imager

NASA Technical Reports Server (NTRS)

Shu, Peter; Waczynski, Augustyn; Kan, Emily; Wen, Yiting; Rosenberry, Robert

2012-01-01

The thermal infrared sensor (TIRS) is a quantum well infrared photodetector (QWIP)-based instrument intended to supplement the Operational Land Imager (OLI) for the Landsat Data Continuity Mission (LDCM). The TIRS instrument is a far-infrared imager operating in the pushbroom mode with two IR channels: 10.8 and 12 m. The focal plane will contain three 640 512 QWIP arrays mounted onto a silicon substrate. The readout integrated circuit (ROIC) addresses each pixel on the QWIP arrays and reads out the pixel value (signal). The ROIC is controlled by the focal plane electronics (FPE) by means of clock signals and bias voltage value. The means of how the FPE is designed to control and interact with the TIRS focal plane assembly (FPA) is the basis for this work. The technology developed under the FPE is for the TIRS focal plane assembly (FPA). The FPE must interact with the FPA to command and control the FPA, extract analog signals from the FPA, and then convert the analog signals to digital format and send them via a serial link (USB) to a computer. The FPE accomplishes the described functions by converting electrical power from generic power supplies to the required bias power that is needed by the FPA. The FPE also generates digital clocking signals and shifts the typical transistor-to-transistor logic (TTL) to }5 V required by the FPA. The FPE also uses an application- specific integrated circuit (ASIC) named System Image, Digitizing, Enhancing, Controlling, And Retrieving (SIDECAR) from Teledyne Corp. to generate the clocking patterns commanded by the user. The uniqueness of the FPE for TIRS lies in that the TIRS FPA has three QWIP detector arrays, and all three detector arrays must be in synchronization while in operation. This is to avoid data skewing while observing Earth flying in space. The observing scenario may be customized by uploading new control software to the SIDECAR.

Malaspina Glacier, Alaska

NASA Image and Video Library

2017-12-08

The ice of a piedmont glacier spills from a steep valley onto a relatively flat plain, where it spreads out unconstrained like pancake batter. Elephant Foot Glacier in northeastern Greenland is an excellent example; it is particularly noted for its symmetry. But the largest piedmont glacier in North America (and possibly the world) is Malaspina in southeastern Alaska. On September 24, 2014, the Operational Land Imager (OLI) on Landsat 8 acquired this image of Malaspina Glacier. The main source of ice comes from Seward Glacier, located at the top-center of this image. The Agassiz and Libbey glaciers are visible on the left side, and the Hayden and Marvine glaciers are on the right. The brown lines on the ice are moraines—areas where soil, rock, and other debris have been scraped up by the glacier and deposited at its sides. Where two glaciers flow together, the moraines merge to form a medial moraine. Glaciers that flow at a steady speed tend to have moraines that are relatively straight. But what causes the dizzying pattern of curves, zigzags, and loops of Malaspina’s moraines? Glaciers in this area of Alaska periodically “surge,”meaning they lurch forward quickly for one to several years. As a result of this irregular flow, the moraines at the edges and between glaciers can become folded, compressed, and sheared to form the characteristic loops seen on Malaspina. For instance, a surge in 1986 displaced moraines on the east side of Malaspina by as much as 5 kilometers (3 miles). NASA Earth Observatory image by Jesse Allen, using Landsat data from the U.S. Geological Survey. Caption by Kathryn Hansen. Credit: NASA Earth Observatory NASA image use policy. NASA Goddard Space Flight Center enables NASA’s mission through four scientific endeavors: Earth Science, Heliophysics, Solar System Exploration, and Astrophysics. Goddard plays a leading role in NASA’s accomplishments by contributing compelling scientific knowledge to advance the Agency’s mission

High resolution stream water quality assessment in the Vancouver, British Columbia region: a citizen science study.

PubMed

Shupe, Scott M

2017-12-15

Changing land cover and climate regimes modify water quantity and quality in natural stream systems. In regions undergoing rapid change, it is difficult to effectively monitor and quantify these impacts at local to regional scales. In Vancouver, British Columbia, one of the most rapidly urbanizing areas in Canada, 750 measurements were taken from a total of 81 unique sampling sites representing 49 streams located in urban, forest, and agricultural-dominant watersheds at a frequency of up to 12 times per year between 2013 and 2016. Dissolved nitrate (NO 3 -N) and phosphate (PO 4 -P) concentrations, turbidity, water temperature, pH and conductivity were measured by citizen scientists in addition to observations of hydrology, vegetation, land use, and visible stream impacts. Land cover was mapped at a 15-m resolution using Landsat 8 OLI imagery and used to determine dominant land cover for each watershed in which a sample was recorded. Regional, seasonal, and catchment-type trends in measurements were determined using statistical analyses. The relationships of nutrients to land cover varied seasonally and on a catchment-type basis. Nitrate showed seasonal highs in winter and lows in summer, though phosphate had less seasonal variation. Overall, nitrate concentrations were positively associated to agriculture and deciduous forest and negatively associated with coniferous forest. In contrast, phosphate concentrations were positively associated with agricultural, deciduous forest, and disturbed land cover and negatively associated with urban land cover. Both urban and agricultural land cover were significantly associated with an increase in water conductivity. Increased forest land cover was associated with better water quality, including lower turbidity, conductivity, and water temperature. This study showed the importance of high resolution sampling in understanding seasonal and spatial dynamics of stream water quality, made possible with the large number of

Adjustment of prior constraints for an improved crop monitoring with the Earth Observation Land Data Assimilation System (EO-LDAS)

NASA Astrophysics Data System (ADS)

Truckenbrodt, Sina C.; Gómez-Dans, José; Stelmaszczuk-Górska, Martyna A.; Chernetskiy, Maxim; Schmullius, Christiane C.

2017-04-01

Throughout the past decades various satellite sensors have been launched that record reflectance in the optical domain and facilitate comprehensive monitoring of the vegetation-covered land surface from space. The interaction of photons with the canopy, leaves and soil that determines the spectrum of reflected sunlight can be simulated with radiative transfer models (RTMs). The inversion of RTMs permits the derivation of state variables such as leaf area index (LAI) and leaf chlorophyll content from top-of-canopy reflectance. Space-borne data are, however, insufficient for an unambiguous derivation of state variables and additional constraints are required to resolve this ill-posed problem. Data assimilation techniques permit the conflation of various information with due allowance for associated uncertainties. The Earth Observation Land Data Assimilation System (EO-LDAS) integrates RTMs into a dynamic process model that describes the temporal evolution of state variables. In addition, prior information is included to further constrain the inversion and enhance the state variable derivation. In previous studies on EO-LDAS, prior information was represented by temporally constant values for all investigated state variables, while information about their phenological evolution was neglected. Here, we examine to what extent the implementation of prior information reflecting the phenological variability improves the performance of EO-LDAS with respect to the monitoring of crops on the agricultural Gebesee test site (Central Germany). Various routines for the generation of prior information are tested. This involves the usage of data on state variables that was acquired in previous years as well as the application of phenological models. The performance of EO-LDAS with the newly implemented prior information is tested based on medium resolution satellite imagery (e.g., RapidEye REIS, Sentinel-2 MSI, Landsat-7 ETM+ and Landsat-8 OLI). The predicted state variables are

Classifying land cover from an object-oriented approach - applied to LANDSAT 8 at the regional scale of the Lake Tana Basin (Ethiopia)

NASA Astrophysics Data System (ADS)

Lemma, Hanibal; Frankl, Amaury; Poesen, Jean; Adgo, Enyew; Nyssen, Jan

2017-04-01

Object-oriented image classification has been gaining prominence in the field of remote sensing and provides a valid alternative to the 'traditional' pixel based methods. Recent studies have proven the superiority of the object-based approach. So far, object-oriented land cover classifications have been applied either at limited spatial coverages (ranging 2 to 1091 km2) or by using very high resolution (0.5-16 m) imageries. The main aim of this study is to drive land cover information for large area from Landsat 8 OLI surface reflectance using the Estimation of Scale Parameter (ESP) tool and the object oriented software eCognition. The available land cover map of Lake Tana Basin (Ethiopia) is about 20 years old with a courser spatial scale (1:250,000) and has limited use for environmental modelling and monitoring studies. Up-to-date and basin wide land cover maps are essential to overcome haphazard natural resources management, land degradation and reduced agricultural production. Indeed, object-oriented approach involves image segmentation prior to classification, i.e. adjacent similar pixels are aggregated into segments as long as the heterogeneity in the spectral and spatial domains is minimized. For each segmented object, different attributes (spectral, textural and shape) were calculated and used for in subsequent classification analysis. Moreover, the commonly used error matrix is employed to determine the quality of the land cover map. As a result, the multiresolution segmentation (with parameters of scale=30, shape=0.3 and Compactness=0.7) produces highly homogeneous image objects as it is observed in different sample locations in google earth. Out of the 15,089 km2 area of the basin, cultivated land is dominant (69%) followed by water bodies (21%), grassland (4.8%), forest (3.7%) and shrubs (1.1%). Wetlands, artificial surfaces and bare land cover only about 1% of the basin. The overall classification accuracy is 80% with a Kappa coefficient of 0.75. With

Updating the New Zealand Glacier Inventory

NASA Astrophysics Data System (ADS)

Baumann, S. C.; Anderson, B.; Mackintosh, A.; Lorrey, A.; Chinn, T.; Collier, C.; Rack, W.; Purdie, H.

2017-12-01

The last complete glacier inventory of New Zealand dates from the year 1978 (North Island 1988) and was manually constructed from oblique aerial photographs and geodetic maps (Chinn 2001). The inventory has been partly updated by Gjermundsen et al. (2011) for the year 2002 (40% of total area) and by Sirguey & More (2010) for the year 2009 (32% of total area), both using ASTER satellite imagery. We used Landsat 8 OLI/TIRS satellite data from February/March 2016 to map the total glaciated area. Clean and debris-covered ice were mapped semi-automatically. The band ratio approach was used for clean ice (ratio: red/SWIR). We mapped debris-covered ice using a supervised classification (maximum likelihood). Manual post processing was necessary due to misclassifications (e.g. lakes, clouds) or mapping in shadowed areas. It was also necessary to manually combine the clean and debris-covered parts into single glaciers. Additional input data for the post processing were Sentinel 2 images from the same time period, orthophotos from Land Information New Zealand (resolution: 0.75 m, date: Nov 2014), and the 1978/88 outlines from the GLIMS database (http://www.glims.org/). As the Sentinel 2 data were more heavily cloud covered compared to the Landsat 8 images, they were only used for post processing and not for the classification itself. Initial results show that New Zealand glaciers covered an area of about 1050 km² in 2016, a reduction of 16% since 1978. Approximately 17% of glacier area was covered in surface debris. The glaciers in the central Southern Alps around Mt Cook reduced in area by 24%. Glaciers in the North Island of New Zealand reduced by 71% since 1988, and only 2 km² of ice cover remained in 2016. Chinn, TJH (2001). "Distribution of the glacial water resources of New Zealand." Journal of Hydrology (NZ) 40(2): 139-187 Gjermundsen, EF, Mathieu, R, Kääb, A, Chinn, TJH, Fitzharris, B & Hagen, JO (2011). "Assessment of multispectral glacier mapping methods and