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Sample records for surface temperatures lst

  1. Determination of Land Surface Temperature (LST) and Potential ...

    African Journals Online (AJOL)

    Determination of Land Surface Temperature (LST) and Potential Urban Heat Island Effect in Parts of Lagos State using Satellite ... Changes in temperature appear to be closely related to concentrations of atmospheric carbon dioxide.

  2. Developing a synergy algorithm for land surface temperature: the SEN4LST project

    Science.gov (United States)

    Sobrino, Jose A.; Jimenez, Juan C.; Ghent, Darren J.

    2013-04-01

    Land surface Temperature (LST) is one of the key parameters in the physics of land-surface processes on regional and global scales, combining the results of all surface-atmosphere interactions and energy fluxes between the surface and the atmosphere. An adequate characterization of LST distribution and its temporal evolution requires measurements with detailed spatial and temporal frequencies. With the advent of the Sentinel 2 (S2) and 3 (S3) series of satellites a unique opportunity exists to go beyond the current state of the art of single instrument algorithms. The Synergistic Use of The Sentinel Missions For Estimating And Monitoring Land Surface Temperature (SEN4LST) project aims at developing techniques to fully utilize synergy between S2 and S3 instruments in order to improve LST retrievals. In the framework of the SEN4LST project, three LST retrieval algorithms were proposed using the thermal infrared bands of the Sea and Land Surface Temperature Retrieval (SLSTR) instrument on board the S3 platform: split-window (SW), dual-angle (DA) and a combined algorithm using both split-window and dual-angle techniques (SW-DA). One of the objectives of the project is to select the best algorithm to generate LST products from the synergy between S2/S3 instruments. In this sense, validation is a critical step in the selection process for the best performing candidate algorithm. A unique match-up database constructed at University of Leicester (UoL) of in situ observations from over twenty ground stations and corresponding brightness temperature (BT) and LST match-ups from multi-sensor overpasses is utilised for validating the candidate algorithms. Furthermore, their performance is also evaluated against the standard ESA LST product and the enhanced offline UoL LST product. In addition, a simulation dataset is constructed using 17 synthetic images of LST and the radiative transfer model MODTRAN carried under 66 different atmospheric conditions. Each candidate LST

  3. Inversion of Land Surface Temperature (LST Using Terra ASTER Data: A Comparison of Three Algorithms

    Directory of Open Access Journals (Sweden)

    Milton Isaya Ndossi

    2016-12-01

    Full Text Available Land Surface Temperature (LST is an important measurement in studies related to the Earth surface’s processes. The Advanced Space-borne Thermal Emission and Reflection Radiometer (ASTER instrument onboard the Terra spacecraft is the currently available Thermal Infrared (TIR imaging sensor with the highest spatial resolution. This study involves the comparison of LSTs inverted from the sensor using the Split Window Algorithm (SWA, the Single Channel Algorithm (SCA and the Planck function. This study has used the National Oceanic and Atmospheric Administration’s (NOAA data to model and compare the results from the three algorithms. The data from the sensor have been processed by the Python programming language in a free and open source software package (QGIS to enable users to make use of the algorithms. The study revealed that the three algorithms are suitable for LST inversion, whereby the Planck function showed the highest level of accuracy, the SWA had moderate level of accuracy and the SCA had the least accuracy. The algorithms produced results with Root Mean Square Errors (RMSE of 2.29 K, 3.77 K and 2.88 K for the Planck function, the SCA and SWA respectively.

  4. Estimating Understory Temperatures Using MODIS LST in Mixed Cordilleran Forests

    Directory of Open Access Journals (Sweden)

    David N. Laskin

    2016-08-01

    Full Text Available Satellite remote sensing provides a rapid and broad-scale means for monitoring vegetation phenology and its relationship with fluctuations in air temperature. Investigating the response of plant communities to climate change is needed to gain insight into the potentially detrimental effects on ecosystem processes. While many studies have used satellite-derived land surface temperature (LST as a proxy for air temperature, few studies have attempted to create and validate models of forest understory temperature (Tust, as it is obscured from these space-borne observations. This study worked to predict instantaneous values of Tust using daily Moderate Resolution Imaging Spectroradiometer (MODIS LST data over a 99,000 km2 study area located in the Rocky Mountains of western Alberta, Canada. Specifically, we aimed to identify the forest characteristics that improve estimates of Tust over using LST alone. Our top model predicted Tust to within a mean absolute error (MAE of 1.4 °C with an overall model fit of R2 = 0.89 over two growing seasons. Canopy closure and the LiDAR-derived standard deviation of canopy height metric were found to significantly improve estimations of Tust over MODIS LST alone. These findings demonstrate that canopy structure and forest stand-type function to differentiate understory air temperatures from ambient canopy temperature as seen by the sensor overhead.

  5. Determining the required accuracy of LST products for estimating surface energy fluxes

    Science.gov (United States)

    Pinheiro, A. C.; Reichle, R.; Sujay, K.; Arsenault, K.; Privette, J. L.; Yu, Y.

    2006-12-01

    Land Surface Temperature (LST) is an important parameter to assess the energy state of a surface. Synoptic satellite observations of LST must be used when attempting to estimate fluxes over large spatial scales. Due to the close coupling between LST, root level water availability, and mass and energy fluxes at the surface, LST is particularly useful over agricultural areas to help determine crop water demands and facilitate water management decisions (e.g., irrigation). Further, LST can be assimilated into land surface models to help improve estimates of latent and sensible heat fluxes. However, the accuracy of LST products and its impact on surface flux estimation is not well known. In this study, we quantify the uncertainty limits in LST products for accurately estimating latent heat fluxes over agricultural fields in the Rio Grande River basin of central New Mexico. We use the Community Land Model (CLM) within the Land Information Systems (LIS), and adopt an Ensemble Kalman Filter approach to assimilate the LST fields into the model. We evaluate the LST and assimilation performance against field measurements of evapotranspiration collected at two eddy-covariance towers in semi-arid cropland areas. Our results will help clarify sensor and LST product requirements for future remote sensing systems.

  6. ESA DUE GlobTemperature project: Infrared-based LST Product

    Science.gov (United States)

    Ermida, Sofia; Pires, Ana; Ghent, Darren; Trigo, Isabel; DaCamara, Carlos; Remedios, John

    2016-04-01

    One of the purposes of the GlobTemperature project is to provide a product of global Land Surface Temperature (LST) based on Geostationary Earth Orbit (GEO) and Low Earth polar Orbit (LEO) satellite data. The objective is to use existing LST products, which are obtained from different sensors/platforms, combining them into a harmonized product for a reference view angle. In a first approach, only infra-red based retrievals are considered, and LEO LSTs will be used as a common denominator among geostationary sensors. LST data is provided by a wide range of sensors to optimize spatial coverage, namely: (i) 2 LEO sensors - the Advanced Along Track Scanning Radiometer (AATSR) series of instruments on-board ESA's Envisat, and the Moderate Resolution Imaging Spectroradiometer (MODIS) on-board NASA's TERRA and AQUA; and (ii) 3 GEO sensors - the Spinning Enhanced Visible and Infrared Imager (SEVIRI) on-board EUMETSAT's Meteosat Second Generation (MSG), the Japanese Meteorological Imager (JAMI) on-board the Japanese Meteorological Association (JMA) Multifunction Transport SATellite (MTSAT-2), and NASA's Geostationary Operational Environmental Satellites (GOES). The merged LST product is generated in two steps: 1) calibration between each LEO and each GEO that consists in the removal of systematic differences (associated to sensor type and LST algorithms, including calibration, atmospheric and surface emissivity corrections, amongst others) represented by linear regressions; 2) angular correction that consists in bringing all LST data to reference (nadir) view. Angular effects on LST are estimated by means of a kernel model of the surface thermal emission, which describes the angular dependence of LST as function of viewing and illumination geometry. The model is adjusted to MODIS and SEVIRI/MSG LST estimates and validated against LST retrievals from those sensors obtained for other years (not used in the calibration). It is shown that the model leads to a reduction of LST

  7. Modelling the angular effects on satellite retrieved LST at global scale using a land surface classification

    Science.gov (United States)

    Ermida, Sofia; DaCamara, Carlos C.; Trigo, Isabel F.; Pires, Ana C.; Ghent, Darren

    2017-04-01

    Land Surface Temperature (LST) is a key climatological variable and a diagnostic parameter of land surface conditions. Remote sensing constitutes the most effective method to observe LST over large areas and on a regular basis. Although LST estimation from remote sensing instruments operating in the Infrared (IR) is widely used and has been performed for nearly 3 decades, there is still a list of open issues. One of these is the LST dependence on viewing and illumination geometry. This effect introduces significant discrepancies among LST estimations from different sensors, overlapping in space and time, that are not related to uncertainties in the methodologies or input data used. Furthermore, these directional effects deviate LST products from an ideally defined LST, which should represent to the ensemble of directional radiometric temperature of all surface elements within the FOV. Angular effects on LST are here conveniently estimated by means of a kernel model of the surface thermal emission, which describes the angular dependence of LST as a function of viewing and illumination geometry. The model is calibrated using LST data as provided by a wide range of sensors to optimize spatial coverage, namely: 1) a LEO sensor - the Moderate Resolution Imaging Spectroradiometer (MODIS) on-board NASA's TERRA and AQUA; and 2) 3 GEO sensors - the Spinning Enhanced Visible and Infrared Imager (SEVIRI) on-board EUMETSAT's Meteosat Second Generation (MSG), the Japanese Meteorological Imager (JAMI) on-board the Japanese Meteorological Association (JMA) Multifunction Transport SATellite (MTSAT-2), and NASA's Geostationary Operational Environmental Satellites (GOES). As shown in our previous feasibility studies the sampling of illumination and view angles has a high impact on the obtained model parameters. This impact may be mitigated when the sampling size is increased by aggregating pixels with similar surface conditions. Here we propose a methodology where land surface is

  8. Developing NASA's VIIRS LST and Emissivity EDRs using a physics based Temperature Emissivity Separation (TES) algorithm

    Science.gov (United States)

    Islam, T.; Hulley, G. C.; Malakar, N.; Hook, S. J.

    2015-12-01

    Land Surface Temperature and Emissivity (LST&E) data are acknowledged as critical Environmental Data Records (EDRs) by the NASA Earth Science Division. The current operational LST EDR for the recently launched Suomi National Polar-orbiting Partnership's (NPP) Visible Infrared Imaging Radiometer Suite (VIIRS) payload utilizes a split-window algorithm that relies on previously-generated fixed emissivity dependent coefficients and does not produce a dynamically varying and multi-spectral land surface emissivity product. Furthermore, this algorithm deviates from its MODIS counterpart (MOD11) resulting in a discontinuity in the MODIS/VIIRS LST time series. This study presents an alternative physics based algorithm for generation of the NASA VIIRS LST&E EDR in order to provide continuity with its MODIS counterpart algorithm (MOD21). The algorithm, known as temperature emissivity separation (TES) algorithm, uses a fast radiative transfer model - Radiative Transfer for (A)TOVS (RTTOV) in combination with an emissivity calibration model to isolate the surface radiance contribution retrieving temperature and emissivity. Further, a new water-vapor scaling (WVS) method is developed and implemented to improve the atmospheric correction process within the TES system. An independent assessment of the VIIRS LST&E outputs is performed against in situ LST measurements and laboratory measured emissivity spectra samples over dedicated validation sites in the Southwest USA. Emissivity retrievals are also validated with the latest ASTER Global Emissivity Database Version 4 (GEDv4). An overview and current status of the algorithm as well as the validation results will be discussed.

  9. Mapping air temperature using time series analysis of LST: the SINTESI approach

    NARCIS (Netherlands)

    Alfieri, S.M.; De Lorenzi, F.; Menenti, M.

    2013-01-01

    This paper presents a new procedure to map time series of air temperature (Ta) at fine spatial resolution using time series analysis of satellite-derived land surface temperature (LST) observations. The method assumes that air temperature is known at a single (reference) location such as in gridded

  10. Development of an Operational Calibration Methodology for the Landsat Thermal Data Archive and Initial Testing of the Atmospheric Compensation Component of a Land Surface Temperature (LST Product from the Archive

    Directory of Open Access Journals (Sweden)

    Monica Cook

    2014-11-01

    Full Text Available The Landsat program has been producing an archive of thermal imagery that spans the globe and covers 30 years of the thermal history of the planet at human scales (60–120 m. Most of that archive’s absolute radiometric calibration has been fixed through vicarious calibration techniques. These calibration ties to trusted values have often taken a year or more to gather sufficient data and, in some cases, it has been over a decade before calibration certainty has been established. With temperature being such a critical factor for all living systems and the ongoing concern over the impacts of climate change, NASA and the United States Geological Survey (USGS are leading efforts to provide timely and accurate temperature data from the Landsat thermal data archive. This paper discusses two closely related advances that are critical steps toward providing timely and reliable temperature image maps from Landsat. The first advance involves the development and testing of an autonomous procedure for gathering and performing initial screening of large amounts of vicarious calibration data. The second advance discussed in this paper is the per-pixel atmospheric compensation of the data to permit calculation of the emitted surface radiance (using ancillary sources of emissivity data and the corresponding land surface temperature (LST.

  11. Cross-satellite comparison of operational land surface temperature products derived from MODIS and ASTER data over bare soil surfaces

    Science.gov (United States)

    Duan, Si-Bo; Li, Zhao-Liang; Cheng, Jie; Leng, Pei

    2017-04-01

    The collection 6 (C6) MODIS land surface temperature (LST) product is publicly available for the user community. Compared to the collection 5 (C5) MODIS LST product, the C6 MODIS LST product has been refined over bare soil pixels. Assessing the accuracy of the C6 MODIS LST product will help to facilitate the use of the LST product in various applications. In this study, we present a cross-satellite comparison to evaluate the accuracy of the C6 MODIS LST product (MOD11_L2) over bare soil surfaces under various atmospheric and surface conditions using the ASTER LST product as a reference. For comparison, the C5 MODIS LST product was also used in the analysis. The absolute biases (0.2-1.5 K) of the differences between the C6 MODIS LST and ASTER LST over bare soil surfaces are approximately two times less than those (0.6-3.8 K) of the differences between the C5 MODIS LST and ASTER LST. Furthermore, the RMSEs (0.7-2.3 K) over bare soil surfaces for the C6 MODIS LST are significantly smaller than those (0.9-4.2 K) for the C5 MODIS LST. These results indicate that the accuracy of the C6 MODIS LST product is much better than that of the C5 MODIS LST product. We recommend that the user community employs the C6 MODIS LST product in their applications.

  12. estimation of land surface temperature of kaduna metropolis, nigeria

    African Journals Online (AJOL)

    Zaharaddeen et. al

    Understanding the spatial variation of Land Surface Temperature. (LST), will be ... positive correlation between mean of surface emissivity with date and ... deviation of 1.92 of LST and coefficient determinant R2 (0.46) show a ... (LST), as the prime and basic physical parameter of the earth's ..... thorough review of the paper.

  13. Intensity and Pattern of Land Surface Temperature in Hat Yai City, Thailand

    OpenAIRE

    Poonyanuch RUTHIRAKO; Rotchanatch DARNSAWASDI; Wichien CHATUPOTE

    2014-01-01

    Land Surface Temperature (LST) is an important factor in global climate. LST is governed by surface heat fluxes, which are affected by urbanization. In order to understand urban climate, LST needs to be examined. This study aimed to investigate the intensity and pattern of LST and examine the relationships between LST and the characteristics of urban land use, indices, and population density in Hat Yai City. Landsat 5TM images were used for interpretation of land use characteristics and deriv...

  14. Research on Earthquake Precursor in E-TEC: A Study on Land Surface Thermal Anomalies Using MODIS LST Product in Taiwan

    Science.gov (United States)

    Chang, W. Y.; Wu, M. C.

    2014-12-01

    Taiwan has been known as an excellent natural laboratory characterized by rapid active tectonic rate and high dense seismicity. The Eastern Taiwan Earthquake Research Center (E-TEC) is established on 2013/09/24 in National Dong Hwa University and collaborates with Central Weather Bureau (CWB), National Center for Research on Earthquake Engineering (NCREE), National Science and Technology Center for Disaster Reduction (NCDR), Institute of Earth Science of Academia Sinica (IES, AS) and other institutions (NCU, NTU, CCU) and aims to provide an integrated platform for researchers to conduct the new advances on earthquake precursors and early warning for seismic disaster prevention in the eastern Taiwan, as frequent temblors are most common in the East Taiwan rift valley. E-TEC intends to integrate the multi-disciplinary observations and is equipped with stations to monitor a wide array of factors of quake precursors, including seismicity, GPS, strain-meter, ground water, geochemistry, gravity, electromagnetic, ionospheric density, thermal infrared remote sensing, gamma radiation etc, and will maximize the value of the data for researches with the range of monitoring equipment that enable to predict where and when the next devastated earthquake will strike Taiwan and develop reliable earthquake prediction models. A preliminary study on earthquake precursor using monthly Moderate Resolution Imaging Spectroradiometer (MODIS) Land Surface Temperature (LST) data before 2013/03/27 Mw6.2 Nantou earthquake in Taiwan is presented. Using the statistical analysis, the result shows the peak of the anomalous LST that exceeds a standard deviation of LST appeared on 2013/03/09 and became less or none anomalies observed on 2013/03/16 before the main-shock, which is in consist with the phenomenon observed by other researchers. This preliminary experimental result shows that the thermal anomalies reveal the possibility to associate surface thermal phenomena before the strong earthquakes.

  15. Cloud tolerance of remote sensing technologies to measure land surface temperature

    Science.gov (United States)

    Conventional means to estimate land surface temperature (LST) from space relies on the thermal infrared (TIR) spectral window and is limited to cloud-free scenes. To also provide LST estimates during periods with clouds, a new method was developed to estimate LST based on passive microwave (MW) obse...

  16. MODIS Surface Temperatures for Cryosphere Studies (Invited)

    Science.gov (United States)

    Hall, D. K.; Comiso, J. C.; DiGirolamo, N. E.; Shuman, C. A.; Riggs, G. A.

    2013-12-01

    We have used Moderate-resolution Imaging Spectroradiometer (MODIS) land-surface temperature (LST) and ice-surface temperature (IST) products for several applications in studies of the cryosphere. A climate-quality climate data record (CDR) of the IST of the Greenland ice sheet has been developed and was one of the data sources used to monitor the extreme melt event covering nearly the entire Greenland ice sheet on 11 - 12 July 2012. The IST CDR is available online for users to employ in models, and to study temperature distributions and melt trends on the ice sheet. We continue to assess accuracy of the IST product through comparative analysis with air temperature data from the NOAA Logan temperature sensor at Summit Station, Greenland. We find a small offset between the air temperature and the IST with the IST being slightly lower which is consistent with findings of other studies. The LST data product has been applied in studies of snow melt in regions where snow is a significant water resource. We have used LST data in seasonally snow-covered areas such as the Wind River Range, Wyoming, to monitor the relationship between LST and seasonal streamflow. A close association between a sudden and sustained increase in LST and complete snowmelt, and between melt-season maximum LST and maximum daily streamflow has been documented. Use of LST and MODIS snow-cover and products in hydrological models increases the accuracy of the modeled prediction of runoff. The IST and LST products have also been applied to study of sea ice, e.g. extent and concentration, and lake ice, such as determining ice-out dates, and these efforts will also be described.

  17. Evaluation and Monitoring of Jpss Land Surface Temperature Data

    Science.gov (United States)

    Yu, Y.; Yu, P.; Liu, Y.; Csiszar, I. A.

    2016-12-01

    Land Surface Temperature (LST) is one of environmental data records (EDRs) produced operationally through the U.S. Joint Polar Satellite System (JPSS) mission. LST is an important parameter for understanding climate change, modeling the hydrological and biogeochemical cycles, and is a prime candidate for Numerical Weather Prediction (NWP) assimilation models. Recently, the international LST and Emissivity Working Ggroup (ILSTE-WG) is promoting to the inclusion of the LST as essential climate variable (ECV) in the Global Climate Observation System (GCOS) of the Word Meteorological Organization (WMO). At the Center for Satellite Applications and Research (STAR) of National Atmospheric and Oceanic Administration (NOAA), we, are as a science team, are responsible to for the science of JPSS LST production. In this work, we present our activities and accomplishments on the JPSS LST evaluation and monitoring since the launch of the first JPSS satellite, i.e. S-NPP, satellite. Beta version, provisional version, and validated stage 1 version of the S-NPP LST products which were announced in May 2013, July 2014, and March 2015, respectively. Evaluation of the LST products have been performed versus ground measurements and other polar-orbiting satellite LST data (e,g. MODIS LSTs); some results will be illustrated. A daily monitoring system of the JPSS LST production has been developed, which presents daily, weekly and monthly global LST maps and inter-comparison results on the STAR JPSS program website. Further, evaluation of the enterprise LST algorithm for JPSS mission which is in development at STAR currently are presented in this work. Finally, evaluation and monitoring plan of the LST production for the JPSS-1 satellite are also presented.

  18. eMODIS Global Land Surface Temperature Version 6

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — The EROS Moderate Resolution Imaging Spectroradiometer (eMODIS) Aqua Land Surface Temperature (LST) product is similar to the Land Processes Distributed Active...

  19. Satellite observations of surface temperature during the March 2015 total solar eclipse.

    Science.gov (United States)

    Good, Elizabeth

    2016-09-28

    The behaviour of remotely sensed land surface temperatures (LSTs) from the spinning-enhanced visible and infrared imager (SEVIRI) during the total solar eclipse of 20 March 2015 is analysed over Europe. LST is found to drop by up to several degrees Celcius during the eclipse, with the minimum LST occurring just after the eclipse mid-point (median=+1.5 min). The drop in LST is typically larger than the drop in near-surface air temperatures reported elsewhere, and correlates with solar obscuration (r=-0.47; larger obscuration = larger LST drop), eclipse duration (r=-0.62; longer duration = larger LST drop) and time (r=+0.37; earlier eclipse = larger LST drop). Locally, the LST drop is also correlated with vegetation (up to r=+0.6), with smaller LST drops occurring over more vegetated surfaces. The LSTs at locations near the coast and at higher elevation are also less affected by the eclipse. This study covers the largest area and uses the most observations of eclipse-induced surface temperature drops to date, and is the first full characterization of satellite LST during an eclipse (known to the author). The methods described could be applied to Geostationary Operational Environmental Satellite (GOES) LST data over North America during the August 2017 total solar eclipse.This article is part of the themed issue 'Atmospheric effects of solar eclipses stimulated by the 2015 UK eclipse'.

  20. Construction and Analysis of Long-Term Surface Temperature Dataset in Fujian Province

    Science.gov (United States)

    Li, W. E.; Wang, X. Q.; Su, H.

    2017-09-01

    Land surface temperature (LST) is a key parameter of land surface physical processes on global and regional scales, linking the heat fluxes and interactions between the ground and atmosphere. Based on MODIS 8-day LST products (MOD11A2) from the split-window algorithms, we constructed and obtained the monthly and annual LST dataset of Fujian Province from 2000 to 2015. Then, we analyzed the monthly and yearly time series LST data and further investigated the LST distribution and its evolution features. The average LST of Fujian Province reached the highest in July, while the lowest in January. The monthly and annual LST time series present a significantly periodic features (annual and interannual) from 2000 to 2015. The spatial distribution showed that the LST in North and West was lower than South and East in Fujian Province. With the rapid development and urbanization of the coastal area in Fujian Province, the LST in coastal urban region was significantly higher than that in mountainous rural region. The LST distributions might affected by the climate, topography and land cover types. The spatio-temporal distribution characteristics of LST could provide good references for the agricultural layout and environment monitoring in Fujian Province.

  1. Intensity and Pattern of Land Surface Temperature in Hat Yai City, Thailand

    Directory of Open Access Journals (Sweden)

    Poonyanuch RUTHIRAKO

    2014-07-01

    Full Text Available Land Surface Temperature (LST is an important factor in global climate. LST is governed by surface heat fluxes, which are affected by urbanization. In order to understand urban climate, LST needs to be examined. This study aimed to investigate the intensity and pattern of LST and examine the relationships between LST and the characteristics of urban land use, indices, and population density in Hat Yai City. Landsat 5TM images were used for interpretation of land use characteristics and derivation of LST, normalized difference built-up index (NDBI and normalized vegetation index (NDVI. The characteristics of land use were classified into 4 types: commercial/high density residential, medium density residential, minimum density residential and vegetation cover/park. The average maximum and minimum LST derived from Landsat 5TM were 25.9, 33.7 and 15.8 °C, respectively. The areas with high LST were located principally in central built-up areas, slightly northwest-southeast of the study area, including the commercial center and the newly expanded residential areas. The LST pattern was well related to land use types and population density. The relationship between LST and NDVI however portrayed negative correlation, while that between LST and NDBI highlighted a positive correlation. It is concluded that NDVI and NDBI can be used to evaluate the risk of Urban Heat Island (UHI and may help city managers better prepare for possible impacts of climate change.

  2. Spatial pattern of impervious surfaces and their impacts on land surface temperature in Beijing, China

    Institute of Scientific and Technical Information of China (English)

    XIAO Rong-bo; OUYANG Zhi-yun; ZHENG Hua; LI Wei-feng; SCHIENKE Erich W; WANG Xiao-ke

    2007-01-01

    Land surface temperature (LST), which is heavily influenced by urban surface structures, is a significant parameter in urban environmental analysis. This study examined the effect impervious surfaces (IS) spatial patterns have on LST in Beijing, China. A classification and regression tree model (CART) was adopted to estimate IS as a continuous variable using Landsat images from two seasons combined with QuickBird. LST was retrieved from the Landsat Thematic Mapper (TM) image to examine the relationships between IS and LST. The results revealed that CART was capable of consistently predicting LST with acceptable accuracy (correlation coefficient of 0.94 and the average error of 8.59%). Spatial patterns of IS exhibited changing gradients across the various urban-rural transects, with LST values showing a concentric shape that increased as you moved from the outskirts towards the downtown areas.Transect analysis also indicated that the changes in both IS and LST patterns were similar at various resolution levels, which suggests a distinct linear relationship between them. Results of correlation analysis further showed that IS tended to be positively correlated with LST, and that the correlation coefficients increased from 0.807 to 0.925 with increases in IS pixel size. The findings identified in this study provide a theoretical basis for improving urban planning efforts to lessen urban temperatures and thus dampen urban heat island effects.

  3. Terrain Segmentation of Egypt from Multi-Temporal Night LST Imagery and Elevation Data

    Directory of Open Access Journals (Sweden)

    Panagiotis Partsinevelos

    2010-09-01

    Full Text Available Monthly night averaged land surface temperature (LST MODIS imagery was analyzed throughout a year-period (2006, in an attempt to segment the terrain of Egypt into regions with different LST seasonal variability, and represent them parametrically. Regions with distinct spatial and temporal LST patterns were outlined using several clustering techniques capturing aspects of spatial, temporal and temperature homogeneity or differentiation. Segmentation was supplemented, taking into consideration elevation, morphological features and landcover information. The northern coastal region along the Mediterranean Sea occupied by lowland plain areas corresponds to the coolest clusters indicating a latitude/elevation dependency of seasonal LST variability. On the other hand, for the inland regions, elevation and terrain dissection plays a key role in LST seasonal variability, while an east to west variability of clusters’ spatial distribution is evident. Finally, elevation biased clustering revealed annual LST differences among the regions with the same physiographic/terrain characteristics. Thermal terrain segmentation outlined the temporal variation of LST during 2006, as well as the spatial distribution of LST zones.

  4. Daytime sensible heat flux estimation over heterogeneous surfaces using multitemporal land-surface temperature observations

    Science.gov (United States)

    Castellví, F.; Cammalleri, C.; Ciraolo, G.; Maltese, A.; Rossi, F.

    2016-05-01

    Equations based on surface renewal (SR) analysis to estimate the sensible heat flux (H) require as input the mean ramp amplitude and period observed in the ramp-like pattern of the air temperature measured at high frequency. A SR-based method to estimate sensible heat flux (HSR-LST) requiring only low-frequency measurements of the air temperature, horizontal mean wind speed, and land-surface temperature as input was derived and tested under unstable conditions over a heterogeneous canopy (olive grove). HSR-LST assumes that the mean ramp amplitude can be inferred from the difference between land-surface temperature and mean air temperature through a linear relationship and that the ramp frequency is related to a wind shear scale characteristic of the canopy flow. The land-surface temperature was retrieved by integrating in situ sensing measures of thermal infrared energy emitted by the surface. The performance of HSR-LST was analyzed against flux tower measurements collected at two heights (close to and well above the canopy top). Crucial parameters involved in HSR-LST, which define the above mentioned linear relationship, were explained using the canopy height and the land surface temperature observed at sunrise and sunset. Although the olive grove can behave as either an isothermal or anisothermal surface, HSR-LST performed close to H measured using the eddy covariance and the Bowen ratio energy balance methods. Root mean square differences between HSR-LST and measured H were of about 55 W m-2. Thus, by using multitemporal thermal acquisitions, HSR-LST appears to bypass inconsistency between land surface temperature and the mean aerodynamic temperature. The one-source bulk transfer formulation for estimating H performed reliable after calibration against the eddy covariance method. After calibration, the latter performed similar to the proposed SR-LST method.

  5. Land surface temperature retrieval from Landsat 8 data and validation with geosensor network

    Science.gov (United States)

    Tan, Kun; Liao, Zhihong; Du, Peijun; Wu, Lixin

    2017-03-01

    A method for the retrieval of land surface temperature (LST) from the two thermal bands of Landsat 8 data is proposed in this paper. The emissivities of vegetation, bare land, buildings, and water are estimated using different features of the wavelength ranges and spectral response functions. Based on the Planck function of the Thermal Infrared Sensor (TIRS) band 10 and band 11, the radiative transfer equation is rebuilt and the LST is obtained using the modified emissivity parameters. A sensitivity analysis for the LST retrieval is also conducted. The LST was retrieved from Landsat 8 data for the city of Zoucheng, Shandong Province, China, using the proposed algorithm, and the LST reference data were obtained at the same time from a geosensor network (GSN). A comparative analysis was conducted between the retrieved LST and the reference data from the GSN. The results showed that water had a higher LST error than the other land-cover types, of less than 1.2°C, and the LST errors for buildings and vegetation were less than 0.75°C. The difference between the retrieved LST and reference data was about 1°C on a clear day. These results confirm that the proposed algorithm is effective for the retrieval of LST from the Landsat 8 thermal bands, and a GSN is an effective way to validate and improve the performance of LST retrieval.

  6. Effect of emissivity uncertainty on surface temperature retrieval over urban areas: Investigations based on spectral libraries

    NARCIS (Netherlands)

    Chen, F.; Yang, S.; Su, Zhongbo; Wang, K.

    2016-01-01

    Land surface emissivity (LSE) is a prerequisite for retrieving land surface temperature (LST) through single channel methods. According to error model, a 0.01 (1%) uncertainty of LSE may result in a 0.5 K error in LST under a moderate condition, while an obvious error (approximately 1 K) is possible

  7. DISAGGREGATION OF GOES LAND SURFACE TEMPERATURES USING SURFACE EMISSIVITY

    Science.gov (United States)

    Accurate temporal and spatial estimation of land surface temperatures (LST) is important for modeling the hydrological cycle at field to global scales because LSTs can improve estimates of soil moisture and evapotranspiration. Using remote sensing satellites, accurate LSTs could be routine, but unfo...

  8. Validation of the modified Becker's split-window approach for retrieving land surface temperature from AVHRR

    Science.gov (United States)

    Quan, Weijun; Chen, Hongbin; Han, Xiuzhen; Ma, Zhiqiang

    2015-10-01

    To further verify the modified Becker's split-window approach for retrieving land surface temperature (LST) from long-term Advanced Very High Resolution Radiometer (AVHRR) data, a cross-validation and a radiance-based (R-based) validation are performed and examined in this paper. In the cross-validation, 3481 LST data pairs are extracted from the AVHRR LST product retrieved with the modified Becker's approach and compared with the Moderate Resolution Imaging Spectroradiometer (MODIS) LST product (MYD11A1) for the period 2002-2008, relative to the positions of 548 weather stations in China. The results show that in most cases, the AVHRR LST values are higher than the MYD11A1. When the AVHRR LSTs are adjusted with a linear regression, the values are close to the MYD11A1, showing a good linear relationship between the two datasets ( R 2 = 0.91). In the R-based validation, comparison is made between AVHRR LST retrieved from the modified Becker's approach and the inversed LST from the Moderate Resolution Transmittance Model (MODTRAN) consolidated with observed temperature and humidity profiles at four radiosonde stations. The results show that the retrieved AVHRR LST deviates from the MODTRAN inversed LST by-1.3 (-2.5) K when the total water vapor amount is less (larger) than 20 mm. This provides useful hints for further improvement of the LST retrieval algorithms' accuracy and consistency.

  9. Comparison of Bayesian Land Surface Temperature algorithm performance with Terra MODIS observations

    CERN Document Server

    Morgan, J A

    2009-01-01

    An approach to land surface temperature (LST) estimation that relies upon Bayesian inference has been validated against multiband infrared radiometric imagery from the Terra MODIS instrument. Bayesian LST estimators are shown to reproduce standard MODIS product LST values starting from a parsimoniously chosen (hence, uninformative) range of prior band emissivity knowledge. Two estimation methods have been tested. The first is the iterative contraction mapping of joint expectation values for LST and surface emissivity described in a previous paper. In the second method, the Bayesian algorithm is reformulated as a Maximum \\emph{A-Posteriori} (MAP) search for the maximum joint \\emph{a-posteriori} probability for LST, given observed sensor aperture radiances and \\emph{a-priori} probabilities for LST and emissivity. Two MODIS data granules each for daytime and nighttime were used for the comparison. The granules were chosen to be largely cloud-free, with limited vertical relief in those portions of the granules fo...

  10. Reconstruction of MODIS daily land surface temperature under clouds

    Science.gov (United States)

    Sun, L.; Gao, F.; Chen, Z.; Song, L.; Xie, D.

    2015-12-01

    Land surface temperature (LST), generally defined as the skin temperature of the Earth's surface, controls the process of evapotranspiration, surface energy balance, soil moisture change and climate change. Moderate Resolution Imaging Spectrometer (MODIS) is equipped with 1km resolution thermal sensor andcapable of observing the earth surface at least once per day.Thermal infrared bands cannot penetrate cloud, which means we cannot get consistency drought monitoring condition at one area. However, the cloudy-sky conditions represent more than half of the actual day-to-day weather around the global. In this study, we developed an LST filled model based on the assumption that under good weather condition, LST difference between two nearby pixels are similar among the closest 8 days. We used all the valid pixels covered by a 9*9 window to reconstruct the gap LST. Each valid pixel is assigned a weight which is determined by the spatial distance and the spectral similarity. This model is applied in the Middle-East of China including Gansu, Ningxia, Shaanxi province. The terrain is complicated in this area including plain and hill. The MODIS daily LST product (MOD11A3) from 2000 to 2004 is tested. Almost all the gap pixels are filled, and the terrain information is reconstructed well and smoothly. We masked two areas in order to validate the model, one located in the plain, another located in the hill. The correlation coefficient is greater than 0.8, even up to 0.92 in a few days. We also used ground measured day maximum and mean surface temperature to valid our model. Although both the temporal and spatial scale are different between ground measured temperature and MODIS LST, they agreed well in all the stations. This LST filled model is operational because it only needs LST and reflectance, and does not need other auxiliary information such as climate factors. We will apply this model to more regions in the future.

  11. Detection of land use and land cover change and land surface temperature in English Bazar urban centre

    Directory of Open Access Journals (Sweden)

    Swades Pal

    2017-06-01

    Full Text Available Present paper tends to capture the impact of land use land cover (LULC on land surface temperature (LST in English Bazar Municipality of Malda District using multi spectral and multi temporal satellite data. Seasonal and temporal LST is extracted in three phases e.g. in 1991, 2010 and 2014. Results show that LST increases 0.070 °C/year and 0.114 °C/year during winter and summer periods respectively and significant LST difference exist over different LULC units. Built up area retains maximum LST in all selected phases. Correlation coefficient among different deriving factors of LST with LST reveals that impervious land maximally control LST (r = 0.62 followed by water bodies and vegetation cover. Even a single land use unit like impervious land water body and vegetation also create differences in LST (R2 of NDBI vs. LST ranges from 0.47 to 0.607; NDVI vs. LST ranges from 0.441 to 0.62. LST is almost co linear with aerial temperature as indicated by significant correlation value (0.44604 for January and 0.658 for April 2014 at 0.01 level of significance and the temperature gap between them ranges from 3.5 °C to 6.5 °C. Such co linearity validates the LST models. The estimated temperature gap is also strongly controlled by LULC. As the LULC pattern is getting changed, its imprint is reflected on LST and air temperature. So, immediate thinking about new urbanism should be adopted, started and implement to arrest the rising temperature and effect of urban heat island.

  12. Understanding the effects of the impervious surfaces pattern on land surface temperature in an urban area

    Science.gov (United States)

    Nie, Qin; Xu, Jianhua

    2015-06-01

    It is well known that urban impervious surface (IS) has a warming effect on urban land surface temperature (LST). However, the influence of an IS's structure, components, and spatial distribution on LST has rarely been quantitatively studied within strictly urban areas. Using ETM+ remote sensing images from the downtown area of Shanghai, China in 2010, this study characterized and quantified the influence of the IS spatial pattern on LST by selecting the percent cover of each IS cover feature and ten configuration metrics. The IS fraction was estimated by linear spectral mixture analysis (LSMA), and LST was retrieved using a mono-window algorithm. The results indicate that high fraction IS cover features account for the majority of the study area. The high fraction IS cover features are widely distributed and concentrated in groups, which is similar with that of high temperature zones. Both the percent composition and the configuration of IS cover features greatly affect the magnitude of LST, but the percent composition is a more important factor in determining LST than the configuration of those features. The significances and effects of the given configuration variables on LST vary greatly among IS cover features.

  13. Estimating land-surface temperature under clouds using MSG/SEVIRI observations

    NARCIS (Netherlands)

    Lu, L.; Venus, V.; Skidmore, A.K.; Wang, T.; Luo, G.

    2011-01-01

    The retrieval of land-surface temperature (LST) from thermal infrared satellite sensor observations is known to suffer from cloud contamination. Hence few studies focus on LST retrieval under cloudy conditions. In this paper a temporal neighboring-pixel approach is presented that reconstructs the di

  14. Estimating land-surface temperature under clouds using MSG/SEVIRI observations

    NARCIS (Netherlands)

    Lu, L.; Venus, V.; Skidmore, A.K.; Wang, T.; Luo, G.

    2011-01-01

    The retrieval of land-surface temperature (LST) from thermal infrared satellite sensor observations is known to suffer from cloud contamination. Hence few studies focus on LST retrieval under cloudy conditions. In this paper a temporal neighboring-pixel approach is presented that reconstructs the

  15. Comparison of MODIS Land Surface Temperature and Air Temperature over the Continental USA Meteorological Stations

    Science.gov (United States)

    Zhang, Ping; Bounoua, Lahouari; Imhoff, Marc L.; Wolfe, Robert E.; Thome, Kurtis

    2014-01-01

    The National Land Cover Database (NLCD) Impervious Surface Area (ISA) and MODIS Land Surface Temperature (LST) are used in a spatial analysis to assess the surface-temperature-based urban heat island's (UHIS) signature on LST amplitude over the continental USA and to make comparisons to local air temperatures. Air-temperature-based UHIs (UHIA), calculated using the Global Historical Climatology Network (GHCN) daily air temperatures, are compared with UHIS for urban areas in different biomes during different seasons. NLCD ISA is used to define urban and rural temperatures and to stratify the sampling for LST and air temperatures. We find that the MODIS LST agrees well with observed air temperature during the nighttime, but tends to overestimate it during the daytime, especially during summer and in nonforested areas. The minimum air temperature analyses show that UHIs in forests have an average UHIA of 1 C during the summer. The UHIS, calculated from nighttime LST, has similar magnitude of 1-2 C. By contrast, the LSTs show a midday summer UHIS of 3-4 C for cities in forests, whereas the average summer UHIA calculated from maximum air temperature is close to 0 C. In addition, the LSTs and air temperatures difference between 2006 and 2011 are in agreement, albeit with different magnitude.

  16. A comparison of all-weather land surface temperature products

    Science.gov (United States)

    Martins, Joao; Trigo, Isabel F.; Ghilain, Nicolas; Goettche, Frank-M.; Ermida, Sofia; Olesen, Folke-S.; Gellens-Meulenberghs, Françoise; Arboleda, Alirio

    2017-04-01

    The Satellite Application Facility on Land Surface Analysis (LSA-SAF, http://landsaf.ipma.pt) has been providing land surface temperature (LST) estimates using SEVIRI/MSG on an operational basis since 2006. The LSA-SAF service has since been extended to provide a wide range of satellite-based quantities over land surfaces, such as emissivity, albedo, radiative fluxes, vegetation state, evapotranspiration, and fire-related variables. Being based on infra-red measurements, the SEVIRI/MSG LST product is limited to clear-sky pixels only. Several all-weather LST products have been proposed by the scientific community either based on microwave observations or using Soil-Vegetation-Atmosphere Transfer models to fill the gaps caused by clouds. The goal of this work is to provide a nearly gap-free operational all-weather LST product and compare these approaches. In order to estimate evapotranspiration and turbulent energy fluxes, the LSA-SAF solves the surface energy budget for each SEVIRI pixel, taking into account the physical and physiological processes occurring in vegetation canopies. This task is accomplished with an adapted SVAT model, which adopts some formulations and parameters of the Tiled ECMWF Scheme for Surface Exchanges over Land (TESSEL) model operated at the European Center for Medium-range Weather Forecasts (ECMWF), and using: 1) radiative inputs also derived by LSA-SAF, which includes surface albedo, down-welling fluxes and fire radiative power; 2) a land-surface characterization obtained by combining the ECOCLIMAP database with both LSA-SAF vegetation products and the H(ydrology)-SAF snow mask; 3) meteorological fields from ECMWF forecasts interpolated to SEVIRI pixels, and 4) soil moisture derived by the H-SAF and LST from LSA-SAF. A byproduct of the SVAT model is surface skin temperature, which is needed to close the surface energy balance. The model skin temperature corresponds to the radiative temperature of the interface between soil and atmosphere

  17. Cloud tolerance of remote-sensing technologies to measure land surface temperature

    Science.gov (United States)

    Holmes, Thomas R. H.; Hain, Christopher R.; Anderson, Martha C.; Crow, Wade T.

    2016-08-01

    Conventional methods to estimate land surface temperature (LST) from space rely on the thermal infrared (TIR) spectral window and is limited to cloud-free scenes. To also provide LST estimates during periods with clouds, a new method was developed to estimate LST based on passive-microwave (MW) observations. The MW-LST product is informed by six polar-orbiting satellites to create a global record with up to eight observations per day for each 0.25° resolution grid box. For days with sufficient observations, a continuous diurnal temperature cycle (DTC) was fitted. The main characteristics of the DTC were scaled to match those of a geostationary TIR-LST product.This paper tests the cloud tolerance of the MW-LST product. In particular, we demonstrate its stable performance with respect to flux tower observation sites (four in Europe and nine in the United States), over a range of cloudiness conditions up to heavily overcast skies. The results show that TIR-based LST has slightly better performance than MW-LST for clear-sky observations but suffers an increasing negative bias as cloud cover increases. This negative bias is caused by incomplete masking of cloud-covered areas within the TIR scene that affects many applications of TIR-LST. In contrast, for MW-LST we find no direct impact of clouds on its accuracy and bias. MW-LST can therefore be used to improve TIR cloud screening. Moreover, the ability to provide LST estimates for cloud-covered surfaces can help expand current clear-sky-only satellite retrieval products to all-weather applications.

  18. Evaluation of Land Surface Temperature Operationally Retrieved from Korean Geostationary Satellite (COMS Data

    Directory of Open Access Journals (Sweden)

    A-Ra Cho

    2013-08-01

    Full Text Available We evaluated the precision of land surface temperature (LST operationally retrieved from the Korean multipurpose geostationary satellite, Communication, Ocean and Meteorological Satellite (COMS. The split-window (SW-type retrieval algorithm was developed through radiative transfer model simulations under various atmospheric profiles, satellite zenith angles, surface emissivity values and surface lapse rate conditions using Moderate Resolution Atmospheric Transmission version 4 (MODTRAN4. The estimation capabilities of the COMS SW (CSW LST algorithm were evaluated for various impacting factors, and the retrieval accuracy of COMS LST data was evaluated with collocated Moderate Resolution Imaging Spectroradiometer (MODIS LST data. The surface emissivity values for two SW channels were generated using a vegetation cover method. The CSW algorithm estimated the LST distribution reasonably well (averaged bias = 0.00 K, Root Mean Square Error (RMSE = 1.41 K, correlation coefficient = 0.99; however, the estimation capabilities of the CSW algorithm were significantly impacted by large brightness temperature differences and surface lapse rates. The CSW algorithm reproduced spatiotemporal variations of LST comparing well to MODIS LST data, irrespective of what month or time of day the data were collected from. The one-year evaluation results with MODIS LST data showed that the annual mean bias, RMSE and correlation coefficient for the CSW algorithm were −1.009 K, 2.613 K and 0.988, respectively.

  19. Long-range cross-correlation between urban impervious surfaces and land surface temperatures

    Institute of Scientific and Technical Information of China (English)

    Qin NIE; Jianhua XU; Wang MAN

    2016-01-01

    The thermal effect of urban impervious surfaces (UIS) is a complex problem.It is thus necessary to study the relationship between UIS and land surface temperatures (LST) using complexity science theory and methods.This paper investigates the long-range cross-correlation between UIS and LST with detrended cross-correlation analysis and multifractal detrended cross-correlation analysis,utilizing data from downtown Shanghai,China.UIS estimates were obtained from linear spectral mixture analysis,and LST was retrieved through application of the mono-window algorithm,using Landsat Thematic Mapper and Enhanced Thematic Mapper Plus data for 1997-2010.These results highlight a positive long-range cross-correlation between UIS and LST across People's Square in Shanghai.LST has a long memory for a certain spatial range of UIS values,such that a large increment in UIS is likely to be followed by a large increment in LST.While the multifractal long-range cross-correlation between UIS and LST was observed over a longer time period in the W-E direction (2002-2010) than in the N-S (2007-2010),these observed correlations show a weakening during the study period as urbanization increased.

  20. Long-range cross-correlation between urban impervious surfaces and land surface temperatures

    Science.gov (United States)

    Nie, Qin; Xu, Jianhua; Man, Wang

    2016-03-01

    The thermal effect of urban impervious surfaces (UIS) is a complex problem. It is thus necessary to study the relationship between UIS and land surface temperatures (LST) using complexity science theory and methods. This paper investigates the long-range cross-correlation between UIS and LST with detrended cross-correlation analysis and multifractal detrended cross-correlation analysis, utilizing data from downtown Shanghai, China. UIS estimates were obtained from linear spectral mixture analysis, and LST was retrieved through application of the mono-window algorithm, using Landsat Thematic Mapper and Enhanced Thematic Mapper Plus data for 1997-2010. These results highlight a positive long-range cross-correlation between UIS and LST across People's Square in Shanghai. LST has a long memory for a certain spatial range of UIS values, such that a large increment in UIS is likely to be followed by a large increment in LST. While the multifractal long-range cross-correlation between UIS and LST was observed over a longer time period in the W-E direction (2002-2010) than in the N-S (2007-2010), these observed correlations show a weakening during the study period as urbanization increased.

  1. The Land Surface Temperature Synergistic Processor in BEAM: A Prototype towards Sentinel-3

    OpenAIRE

    Ruescas, Ana Belen; Danne, Olaf; Fomferra, Norman; Brockmann, Carsten

    2016-01-01

    Land Surface Temperature (LST) is one of the key parameters in the physics of land-surface processes on regional and global scales, combining the results of all surface-atmosphere interactions and energy fluxes between the surface and the atmosphere. With the advent of the European Space Agency (ESA) Sentinel 3 (S3) satellite, accurate LST retrieval methodologies are being developed by exploiting the synergy between the Ocean and Land Colour Instrument (OLCI) and the Sea and Land Surface Temp...

  2. The impact of built-up surfaces on land surface temperatures in Italian urban areas.

    Science.gov (United States)

    Morabito, Marco; Crisci, Alfonso; Messeri, Alessandro; Orlandini, Simone; Raschi, Antonio; Maracchi, Giampiero; Munafò, Michele

    2016-05-01

    Urban areas are characterized by the very high degree of soil sealing and continuous built-up areas: Italy is one of the European countries with the highest artificial land cover rate, which causes a substantial spatial variation in the land surface temperature (LST), modifying the urban microclimate and contributing to the urban heat island effect. Nevertheless, quantitative data regarding the contribution of different densities of built-up surfaces in determining urban spatial LST changes is currently lacking in Italy. This study, which aimed to provide clear and quantitative city-specific information on annual and seasonal spatial LST modifications resulting from increased urban built-up coverage, was conducted generally throughout the whole year, and specifically in two different periods (cool/cold and warm/hot periods). Four cities (Milan, Rome, Bologna and Florence) were included in the study. The LST layer and the built-up-surface indicator were obtained via use of MODIS remote sensing data products (1km) and a very high-resolution map (5m) of built-up surfaces recently developed by the Italian National Institute for Environmental Protection and Research. The relationships between the dependent (mean daily, daytime and nighttime LST values) and independent (built-up surfaces) variables were investigated through linear regression analyses, and comprehensive built-up-surface-related LST maps were also developed. Statistically significant linear relationships (pcities studied, with a higher impact during the warm/hot period than in the cool/cold ones. Daytime and nighttime LST slope patterns depend on the city size and relative urban morphology. If implemented in the existing city plan, the urban maps of built-up-surface-related LST developed in this study might be able to support more sustainable urban land management practices by identifying the critical areas (Hot-Spots) that would benefit most from mitigation actions by local authorities, land-use decision

  3. Spatial-temporal variation of the land surface temperature field and present-day tectonic activity

    Directory of Open Access Journals (Sweden)

    Jin Ma

    2010-10-01

    Full Text Available This study attempts to acquire information on tectonic activity in western China from land surface temperature (LST field data. On the basis of the established relationship between heat and strain, we analyzed the LST distribution in western China using the satellite data product MODIS/Terra. Our results show that: 1. There are departures from annual changes of LST in some areas, and that these changes are associated with the activity of some active tectonic zones. 2. When annual-change background values caused by climate factors are removed, the long-period component (LSTLOW of temperature residual (ΔT of the LST is able to serve as an indicator for tectonic activity. We have found that a major earthquake can produce different effects on the LST fields of surrounding areas. These effects are characterized by both rises and drops in temperature. For example, there was a noteworthy temperature decline associated with the Sumatran M9 earthquake of 2004 in the Bayan Har-Songpan block of central Tibetan Plateau. 3. On the other hand, the LST field of a single area may respond differently to major shocks occurring in different areas in the regions surrounding China. For instance, the Kunlun M 8.1 event made the LST on the Longmen Mountains fault zone increase, whereas the Zaisan Lake M 7.9 quake of 2003, and the Sumatran M 9 event of 2004, caused decreases in the same area’s LST. 4. The variations of land surface temperature (LST over time are different in different tectonic areas. These phenomena may provide clues for the study of tectonic deformation processes. On the basis of these phenomena, we use a combination of temperature data obtained at varied depths, regional seismicity and strain results obtained with GPS measurements, to test the information related to tectonic activity derived from variations of the LST field, and discuss its implications to the creation of models of regional tectonic deformation.

  4. Remote Sensing Based Analysis of the Role of Land Use/Land Cover on Surface Temperature and Temporal Changes in Temperature; a Case Study of Ajmer District, Rajasthan

    Science.gov (United States)

    Hussain, A.; Bhalla, P.; Palria, S.

    2014-12-01

    An attempt has been made in this research to analyze temporal variations in surface temperature in Ajmer District Rajasthan. The research is carried out to assess the relationship between the land surface temperatures (LST) and land cover (LC) changes both in quantitative and qualitative ways in Ajmer District area using Landsat TM/ETM+ data over the period 1989 to 2013.in this period we used three temporal TM/ETM data 1989, 2001 and 2013. Remote sensing of Land surface temperature (LST) has traditionally used the Normalized Difference Vegetation Index (NDVI) as the indicator of vegetation abundance to estimate the land surface temperature (LST)-vegetation relationship. Unsupervised classification methods have been taken to prepare the LC map. LST is derived from the thermal band of Landsat TM/ETM+ using the calibration of spectral radiance and emissivity correction of remote sensing. NDVI is derived from the NIR & RED Band using image enhancement technique (Indices). Arc-GIS have been utilized for data visualization. This procedure allowed analyzing whether LULC classes match LST classes. However, the results of such overlaying are hard to interpret. LST and LULC maps of these areas give the understanding on how the classes and corresponding LST have changed from one date to the other. Another option is to collect statistical data. it was impossible to calculate linear regression between LULC map and LST map. A solution to that matter is to use Normalized Vegetation Index (NDVI) instead of LULC classification result.

  5. AATSR Land Surface Temperature Product Validation Using Ground Measurements in China and Implications for SLSTR

    Science.gov (United States)

    Zhou, Ji; Zmuda, Andy; Desnos, Yves-Louis; Ma, Jin

    2016-08-01

    Land surface temperature (LST) is one of the most important parameters at the interface between the earth's surface and the atmosphere. It acts as a sensitive indicator of climate change and is an essential input parameter for land surface models. Because of the intense variability at different spatial and temporal scales, satellite remote sensing provides the sole opportunity to acquire LSTs over large regions. Validation of the LST products is an necessary step before their applications conducted by scientific community and it is essential for the developers to improve the LST products.

  6. Characterization of urban heat island effects over Asian megacities with hourly LST maps derived from Japanese geostationary satellite data

    Science.gov (United States)

    Oyoshi, K.; Tamura, M.

    2009-12-01

    Asian countries are expected to continue economic growth with high rate and urban structure can be transformed dramatically. Urbanization and increase in anthropogenic energy consumption cause urban heat island effect. And, Heat island effect increases cooling cost in summer and induces health problem such as heat stroke. Remotely sensed data can be powerful tool to characterize urban area and measure urban thermal conditions, because it is able to capture spatio-temporal variations in urban environments. Japanese geostationary meteorological satellite, MTSAT which covers east Asia and the western Pacific region from 140 degrees East above the equator was launched in February 2005. MTSAT provides hourly visible and thermal infrared image, and hourly Land Surface Temperature (LST) can be retrieved. Therefore, compared to polar orbiting satellites such as MODIS or AVHRR, MTSAT is expected to characterize urban thermal conditions in much detailed temporal scale. In this study, in order to evaluate thermal conditions over Asian megacities with MTSAT data, we investigated methodology for monitoring urban LST with satellite data and characterize thermal conditions by using hourly LST data. Firstly, LST were retrieved from MTSAT thermal infrared data with split-window algorithm, and it was confirmed that MTSAT is able to capture hourly spatio-temporal changes and detect urban heat island effects. Then, we constructed LST database of Asian megacities and the database was open to public on the WWW (http://eiserv.uee.kyoto-u.ac.jp/MTSAT/LST/index_e.php). Finally, by using developed LST database, characteristics of hourly temperature changes of Asian megacities were compared and categorized. And it is found that these characteristics were depend on urban structure of each city. Near-real time land surface temperature (LST) monitoring system on the WWW. Latest LST images of Asian megacities are displayed on the top page.

  7. MODIS/TERRA MOD11A2 Land Surface Temperature & Emissivity 8-Day L3 Global 1km

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — The MODIS/Terra Land Surface Temperature and Emissivity (LST/E) products provide per-pixel temperature and emissivity values in a sequence of swath-based to...

  8. MODIS/TERRA MOD11_L2 Land Surface Temperature and Emissivity 5-Minute L2 Swath 1 km

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — The MODIS/Terra Land Surface Temperature and Emissivity (LST/E) products provide per-pixel temperature and emissivity values in a sequence of swath-based to...

  9. MODIS/TERRA MOD11A2 Land Surface Temperature & Emissivity 8-Day L3 Global 1km Version 6

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — The MODIS/Aqua Land Surface Temperature and Emissivity (LST/E) products provide per-pixel temperature and emissivity values in a sequence of swath-based global...

  10. MODIS/COMBINED MOD11A1 Land Surface Temperature and Emissivity Daily L3 Global 1 km Grid SIN

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — The MODIS/Terra Land Surface Temperature and Emissivity (LST/E) products provide per-pixel temperature and emissivity values in a sequence of swath-based to...

  11. IDENTIFYING THE LOCAL SURFACE URBAN HEAT ISLAND THROUGH THE MORPHOLOGY OF THE LAND SURFACE TEMPERATURE

    Directory of Open Access Journals (Sweden)

    J. Wang

    2016-06-01

    Full Text Available Current characterization of the Land Surface Temperature (LST at city scale insufficiently supports efficient mitigations and adaptations of the Surface Urban Heat Island (SUHI at local scale. This research intends to delineate the LST variation at local scale where mitigations and adaptations are more feasible. At the local scale, the research helps to identify the local SUHI (LSUHI at different levels. The concept complies with the planning and design conventions that urban problems are treated with respect to hierarchies or priorities. Technically, the MODerate-resolution Imaging Spectroradiometer satellite image products are used. The continuous and smooth latent LST is first recovered from the raw images. The Multi-Scale Shape Index (MSSI is then applied to the latent LST to extract morphological indicators. The local scale variation of the LST is quantified by the indicators such that the LSUHI can be identified morphologically. The results are promising. It can potentially be extended to investigate the temporal dynamics of the LST and LSUHI. This research serves to the application of remote sensing, pattern analysis, urban microclimate study, and urban planning at least at 2 levels: (1 it extends the understanding of the SUHI to the local scale, and (2 the characterization at local scale facilitates problem identification and support mitigations and adaptations more efficiently.

  12. Spatial Modeling of Urban Vegetation and Land Surface Temperature: A Case Study of Beijing

    Directory of Open Access Journals (Sweden)

    Chudong Huang

    2015-07-01

    Full Text Available The coupling relationship between urban vegetation and land surface temperature (LST has been heatedly debated in a variety of environmental studies. This paper studies the urban vegetation information and LST by utilizing a series of remote sensing imagery covering the period from 1990 to 2007. Their coupling relationship is analyzed, in order to provide the basis for ecological planning and environment protection. The results show that the normalized difference vegetation index (NDVI, urban vegetation abundance (UVA and urban forest abundance (UFA are negatively correlated with LST, which means that both urban vegetation and urban forest are capable in decreasing LST. The apparent influence of urban vegetation and urban forest on LST varies with the spatial resolution of the imagery, and peaks at the resolutions ranging from 90 m to 120 m.

  13. Reconstructing daily clear-sky land surface temperature for cloudy regions from MODIS data

    Science.gov (United States)

    Sun, Liang; Chen, Zhongxin; Gao, Feng; Anderson, Martha; Song, Lisheng; Wang, Limin; Hu, Bo; Yang, Yun

    2017-08-01

    Land surface temperature (LST) is a critical parameter in environmental studies and resource management. The MODIS LST data product has been widely used in various studies, such as drought monitoring, evapotranspiration mapping, soil moisture estimation and forest fire detection. However, cloud contamination affects thermal band observations and will lead to inconsistent LST results. In this study, we present a new Remotely Sensed DAily land Surface Temperature reconstruction (RSDAST) model that recovers clear sky LST for pixels covered by cloud using only clear-sky neighboring pixels from nearby dates. The reconstructed LST was validated using the original LST pixels. Model shows high accuracy for reconstructing one masked pixel with R2 of 0.995, bias of -0.02 K and RMSE of 0.51 K. Extended spatial reconstruction results show a better accuracy for flat areas with R2 of 0.72‒0.89, bias of -0.02-0.21 K, and RMSE of 0.92-1.16 K, and for mountain areas with R2 of 0.81-0.89, bias of -0.35-1.52 K, and RMSE of 1.42‒2.24 K. The reconstructed areas show spatial and temporal patterns that are consistent with the clear neighbor areas. In the reconstructed LST and NDVI triangle feature space which is controlled by soil moisture, LST values distributed reasonably and correspond well to the real soil moisture conditions. Our approach shows great potential for reconstructing clear sky LST under cloudy conditions and provides consistent daily LST which are critical for daily drought monitoring.

  14. Interannual Variation of the Surface Temperature of Tropical Forests from Satellite Observations

    Directory of Open Access Journals (Sweden)

    Huilin Gao

    2016-01-01

    Full Text Available Land surface temperatures (LSTs within tropical forests contribute to climate variations. However, observational data are very limited in such regions. This study used passive microwave remote sensing data from the Special Sensor Microwave/Imager (SSM/I and the Special Sensor Microwave Imager Sounder (SSMIS, providing observations under all weather conditions, to investigate the LST over the Amazon and Congo rainforests. The SSM/I and SSMIS data were collected from 1996 to 2012. The morning and afternoon observations from passive microwave remote sensing facilitate the investigation of the interannual changes of LST anomalies on a diurnal basis. As a result of the variability of cloud cover and the corresponding reduction of solar radiation, the afternoon LST anomalies tend to vary more than the morning LST anomalies. The dominant spatial and temporal patterns for interseasonal variations of the LST anomalies over the tropical rainforest were analyzed. The impacts of droughts and El Niños on this LST were also investigated. Differences between early morning and late afternoon LST anomalies were identified by the remote sensing product, with the morning LST anomalies controlled by humidity (according to comparisons with the National Centers for Environmental Prediction (NCEP reanalysis data.

  15. Improvements of a COMS Land Surface Temperature Retrieval Algorithm Based on the Temperature Lapse Rate and Water Vapor/Aerosol Effect

    Directory of Open Access Journals (Sweden)

    A-Ra Cho

    2015-02-01

    Full Text Available The National Meteorological Satellite Center in Korea retrieves land surface temperature (LST by applying the split-window LST algorithm (CSW_v1.0 to Communication, Ocean, and Meteorological Satellite (COMS data. Considerable errors were detected under conditions of high water vapor content or temperature lapse rates during validation with Moderate Resolution Imaging Spectroradiometer (MODIS LST because of the too simplified LST algorithm. In this study, six types of LST retrieval equations (CSW_v2.0 were developed to upgrade the CSW_v1.0. These methods were developed by classifying “dry,” “normal,” and “wet” cases for day and night and considering the relative sizes of brightness temperature difference (BTD values. Similar to CSW_v1.0, the LST retrieved by CSW_v2.0 had a correlation coefficient of 0.99 with the prescribed LST and a slightly larger bias of −0.03 K from 0.00K; the root mean square error (RMSE improved from 1.41 K to 1.39 K. In general, CSW_v2.0 improved the retrieval accuracy compared to CSW_v1.0, especially when the lapse rate was high (mid-day and dawn and the water vapor content was high. The spatial distributions of LST retrieved by CSW_v2.0 were found to be similar to the MODIS LST independently of the season, day/night, and geographic locations. The validation using one year’s MODIS LST data showed that CSW_v2.0 improved the retrieval accuracy of LST in terms of correlations (from 0.988 to 0.989, bias (from −1.009 K to 0.292 K, and RMSEs (from 2.613 K to 2.237 K.

  16. Validation of Satellite-Derived Land Surface Temperature Products - Methods and Good Practice

    Science.gov (United States)

    Guillevic, P. C.; Hulley, G. C.; Hook, S. J.; Biard, J.; Ghent, D.

    2014-12-01

    Land Surface Temperature (LST) is a key variable for surface water and energy budget calculations that can be obtained globally and operationally from satellite observations. LST is used for many applications, including weather forecasting, short-term climate prediction, extreme weather monitoring, and irrigation and water resource management. In order to maximize the usefulness of LST for research and studies it is necessary to know the uncertainty in the LST measurement. Multiple validation methods and activities are necessary to assess LST compliance with the quality specifications of operational users. This work presents four different validation methods that have been widely used to determine the uncertainties in LST products derived from satellite measurements. 1) The temperature based validation method involves comparisons with ground-based measurements of LST. The method is strongly limited by the number and quality of available field stations. 2) Scene-based comparisons involve comparing a new satellite LST product with a heritage LST product. This method is not an absolute validation and satellite LST inter-comparisons alone do not provide an independent validation measurement. 3) The radiance-based validation method does not require ground-based measurements and is usually used for large scale validation effort or for LST products with coarser spatial resolution (> 1km). 4) Time series comparisons are used to detect problems that can occur during the instrument's life, e.g. calibration drift, or unrealistic outliers due to cloud coverage. This study enumerates the sources of errors associated with each method. The four different approaches are complementary and provide different levels of information about the quality of the retrieved LST. The challenges in retrieving the LST from satellite measurements are discussed using results obtained for MODIS and VIIRS. This work contributes to the objective of the Land Product Validation (LPV) sub-group of the

  17. Spatial validation of large scale land surface models against monthly land surface temperature patterns using innovative performance metrics.

    Science.gov (United States)

    Koch, Julian; Siemann, Amanda; Stisen, Simon; Sheffield, Justin

    2016-04-01

    Land surface models (LSMs) are a key tool to enhance process understanding and to provide predictions of the terrestrial hydrosphere and its atmospheric coupling. Distributed LSMs predict hydrological states and fluxes, such as land surface temperature (LST) or actual evapotranspiration (aET), at each grid cell. LST observations are widely available through satellite remote sensing platforms that enable comprehensive spatial validations of LSMs. In spite of the availability of LST data, most validation studies rely on simple cell to cell comparisons and thus do not regard true spatial pattern information. This study features two innovative spatial performance metrics, namely EOF- and connectivity-analysis, to validate predicted LST patterns by three LSMs (Mosaic, Noah, VIC) over the contiguous USA. The LST validation dataset is derived from global High-Resolution-Infrared-Radiometric-Sounder (HIRS) retrievals for a 30 year period. The metrics are bias insensitive, which is an important feature in order to truly validate spatial patterns. The EOF analysis evaluates the spatial variability and pattern seasonality, and attests better performance to VIC in the warm months and to Mosaic and Noah in the cold months. Further, more than 75% of the LST variability can be captured by a single pattern that is strongly driven by air temperature. The connectivity analysis assesses the homogeneity and smoothness of patterns. The LSMs are most reliable at predicting cold LST patterns in the warm months and vice versa. Lastly, the coupling between aET and LST is investigated at flux tower sites and compared against LSMs to explain the identified LST shortcomings.

  18. Modelling the Relationship Between Land Surface Temperature and Landscape Patterns of Land Use Land Cover Classification Using Multi Linear Regression Models

    Science.gov (United States)

    Bernales, A. M.; Antolihao, J. A.; Samonte, C.; Campomanes, F.; Rojas, R. J.; dela Serna, A. M.; Silapan, J.

    2016-06-01

    The threat of the ailments related to urbanization like heat stress is very prevalent. There are a lot of things that can be done to lessen the effect of urbanization to the surface temperature of the area like using green roofs or planting trees in the area. So land use really matters in both increasing and decreasing surface temperature. It is known that there is a relationship between land use land cover (LULC) and land surface temperature (LST). Quantifying this relationship in terms of a mathematical model is very important so as to provide a way to predict LST based on the LULC alone. This study aims to examine the relationship between LST and LULC as well as to create a model that can predict LST using class-level spatial metrics from LULC. LST was derived from a Landsat 8 image and LULC classification was derived from LiDAR and Orthophoto datasets. Class-level spatial metrics were created in FRAGSTATS with the LULC and LST as inputs and these metrics were analysed using a statistical framework. Multi linear regression was done to create models that would predict LST for each class and it was found that the spatial metric "Effective mesh size" was a top predictor for LST in 6 out of 7 classes. The model created can still be refined by adding a temporal aspect by analysing the LST of another farming period (for rural areas) and looking for common predictors between LSTs of these two different farming periods.

  19. Geostatistical Solutions for Downscaling Remotely Sensed Land Surface Temperature

    Science.gov (United States)

    Wang, Q.; Rodriguez-Galiano, V.; Atkinson, P. M.

    2017-09-01

    Remotely sensed land surface temperature (LST) downscaling is an important issue in remote sensing. Geostatistical methods have shown their applicability in downscaling multi/hyperspectral images. In this paper, four geostatistical solutions, including regression kriging (RK), downscaling cokriging (DSCK), kriging with external drift (KED) and area-to-point regression kriging (ATPRK), are applied for downscaling remotely sensed LST. Their differences are analyzed theoretically and the performances are compared experimentally using a Landsat 7 ETM+ dataset. They are also compared to the classical TsHARP method.

  20. Land Surface Temperature Retrieval from Landsat 8 TIRS - A Case Study of Istanbul.

    Science.gov (United States)

    Bektas Balcik, Filiz; Mujgan Ergene, Emine

    2016-04-01

    Land Surface Temperature (LST) is considered as one of the important parameter to determine negative human population influences like rapid urbanization, destruction of vegetated area, unplanned industrialization, climate change from local to global scale on earth surface. On February 11, 2013 Landsat 8 OLI was launched with two thermal infrared bands that is between 10.60-12.51μm. This innovation on thermal sensors of Landsat 8 TIRS provide a good opportunity to calculate LST using different algorithms such as Split Window Algorithm (SW) and Mono Window Algorithm (MW) with the same TIRS bands. In this study, 21 October 2014 dated Landsat 8 OLI data was used to determine LST of Istanbul using mono window and split window algorithm. The population of the Istanbul was 3 million in the 1970s, 7.4 million in the 1990s, and around 13 million currently. As a result of rapid population growth and unplanned urban expansion in Istanbul, dramatic land cover changes have occurred especially within the past 65 years. Because of this reason it has huge importance to determine LST distribution of the city for sustainable management. Meteorological data used in the study include near- surface temperature and relative-humidity from 15 meteorological stations in Istanbul for the same date and hour of the Landsat 8 OLI sensor image provided (October 21, 10:30AM). The mean near-surface air temperature gathered from meteorological stations was used to verify the final retrieved LST results. The correlation coefficient between LST and the meteorological station derived near-surface temperature was calculated for accuracy verification. To determine the impact of urban components on LST, Index based built up index calculated using remote sensing data. The regression analysis was performed on the relationship between built-up land and LST using various regression models. The derived results were compared to eximine the ability of the selected algorithms.

  1. Near–surface air temperature and snow skin temperature comparison from CREST-SAFE station data with MODIS land surface temperature data

    Directory of Open Access Journals (Sweden)

    C. L. Pérez Díaz

    2015-08-01

    Full Text Available Land Surface Temperature (LST is a key variable (commonly studied to understand the hydrological cycle that helps drive the energy balance and water exchange between the Earth's surface and its atmosphere. One observable constituent of much importance in the land surface water balance model is snow. Snow cover plays a critical role in the regional to global scale hydrological cycle because rain-on-snow with warm air temperatures accelerates rapid snow-melt, which is responsible for the majority of the spring floods. Accurate information on near-surface air temperature (T-air and snow skin temperature (T-skin helps us comprehend the energy and water balances in the Earth's hydrological cycle. T-skin is critical in estimating latent and sensible heat fluxes over snow covered areas because incoming and outgoing radiation fluxes from the snow mass and the air temperature above make it different from the average snowpack temperature. This study investigates the correlation between MODerate resolution Imaging Spectroradiometer (MODIS LST data and observed T-air and T-skin data from NOAA-CREST-Snow Analysis and Field Experiment (CREST-SAFE for the winters of 2013 and 2014. LST satellite validation is imperative because high-latitude regions are significantly affected by climate warming and there is a need to aid existing meteorological station networks with the spatially continuous measurements provided by satellites. Results indicate that near-surface air temperature correlates better than snow skin temperature with MODIS LST data. Additional findings show that there is a negative trend demonstrating that the air minus snow skin temperature difference is inversely proportional to cloud cover. To a lesser extent, it will be examined whether the surface properties at the site are representative for the LST properties within the instrument field of view.

  2. Near-surface air temperature and snow skin temperature comparison from CREST-SAFE station data with MODIS land surface temperature data

    Science.gov (United States)

    Pérez Díaz, C. L.; Lakhankar, T.; Romanov, P.; Muñoz, J.; Khanbilvardi, R.; Yu, Y.

    2015-08-01

    Land Surface Temperature (LST) is a key variable (commonly studied to understand the hydrological cycle) that helps drive the energy balance and water exchange between the Earth's surface and its atmosphere. One observable constituent of much importance in the land surface water balance model is snow. Snow cover plays a critical role in the regional to global scale hydrological cycle because rain-on-snow with warm air temperatures accelerates rapid snow-melt, which is responsible for the majority of the spring floods. Accurate information on near-surface air temperature (T-air) and snow skin temperature (T-skin) helps us comprehend the energy and water balances in the Earth's hydrological cycle. T-skin is critical in estimating latent and sensible heat fluxes over snow covered areas because incoming and outgoing radiation fluxes from the snow mass and the air temperature above make it different from the average snowpack temperature. This study investigates the correlation between MODerate resolution Imaging Spectroradiometer (MODIS) LST data and observed T-air and T-skin data from NOAA-CREST-Snow Analysis and Field Experiment (CREST-SAFE) for the winters of 2013 and 2014. LST satellite validation is imperative because high-latitude regions are significantly affected by climate warming and there is a need to aid existing meteorological station networks with the spatially continuous measurements provided by satellites. Results indicate that near-surface air temperature correlates better than snow skin temperature with MODIS LST data. Additional findings show that there is a negative trend demonstrating that the air minus snow skin temperature difference is inversely proportional to cloud cover. To a lesser extent, it will be examined whether the surface properties at the site are representative for the LST properties within the instrument field of view.

  3. Estimating Temperature Fields from MODIS Land Surface Temperature and Air Temperature Observations in a Sub-Arctic Alpine Environment

    Directory of Open Access Journals (Sweden)

    Scott N. Williamson

    2014-01-01

    Full Text Available Spatially continuous satellite infrared temperature measurements are essential for understanding the consequences and drivers of change, at local and regional scales, especially in northern and alpine environments dominated by a complex cryosphere where in situ observations are scarce. We describe two methods for producing daily temperature fields using MODIS “clear-sky” day-time Land Surface Temperatures (LST. The Interpolated Curve Mean Daily Surface Temperature (ICM method, interpolates single daytime Terra LST values to daily means using the coincident diurnal air temperature curves. The second method calculates daily mean LST from daily maximum and minimum LST (MMM values from MODIS Aqua and Terra. These ICM and MMM models were compared to daily mean air temperatures recorded between April and October at seven locations in southwest Yukon, Canada, covering characteristic alpine land cover types (tundra, barren, glacier at elevations between 1,408 m and 2,319 m. Both methods for producing mean daily surface temperatures have advantages and disadvantages. ICM signals are strongly correlated with air temperature (R2 = 0.72 to 0.86, but have relatively large variability (RMSE = 4.09 to 4.90 K, while MMM values had a stronger correlation to air temperature (R2 = 0.90 and smaller variability (RMSE = 2.67 K. Finally, when comparing 8-day LST averages, aggregated from the MMM method, to air temperature, we found a high correlation (R2 = 0.84 with less variability (RMSE = 1.54 K. Where the trend was less steep and the y-intercept increased by 1.6 °C compared to the daily correlations. This effect is likely a consequence of LST temperature averages being differentially affected by cloud cover over warm and cold surfaces. We conclude that satellite infrared skin temperature (e.g., MODIS LST, which is often aggregated into multi-day composites to mitigate data reductions caused by cloud cover, changes in its relationship to air temperature

  4. Effects of spatial pattern of green space on land surface temperature: implications for sustainable urban planning and climate change adaptation

    Science.gov (United States)

    Maimaitiyiming, M.; Ghulam, A.

    2013-12-01

    The urban heat island (UHI) refers to the phenomenon of higher atmospheric and surface temperatures occurring in urban areas than in the surrounding rural areas. Numerous studies have shown that increased percent cover of green space (PLAND) can significantly decrease land surface temperatures (LST). Fewer studies, however, have investigated the effects of configuration of green space on LST. This paper aims at to fill this gap using oasis city Aksu in northwestern China as a case study. PLAND along with two configuration metrics are used to measure the composition and configuration of green space. The metrics are calculated by moving window method based on a green space map derived from Landsat Thematic Mapper (TM) imagery, and LST data are retrieved from Landsat TM thermal band. Normalized mutual information measure is employed to investigate the relationship between LST and the spatial pattern of green space. The results show that while the PLAND is the most important variable that elicits LST dynamics, spatial configuration of green space also has significant effect on LST. In addition, the variance of LST is largely explained by both composition and configuration of green space. Results from this study can expand our understanding of the relationship between LST and vegetation, and provide insights for sustainable urban planning and management under changing climate.

  5. Global Assessment of Land Surface Temperature From Geostationary Satellites and Model Estimates

    Science.gov (United States)

    Reichle, Rolf H.; Liu, Q.; Minnis, P.; daSilva, A. M., Jr.; Palikonda, R.; Yost, C. R.

    2012-01-01

    Land surface (or 'skin') temperature (LST) lies at the heart of the surface energy balance and is a key variable in weather and climate models. In this research we compare two global and independent data sets: (i) LST retrievals from five geostationary satellites generated at the NASA Langley Research Center (LaRC) and (ii) LST estimates from the quasi-operational NASA GEOS-5 global modeling and assimilation system. The objective is to thoroughly understand both data sets and their systematic differences in preparation for the assimilation of the LaRC LST retrievals into GEOS-5. As expected, mean differences (MD) and root-mean-square differences (RMSD) between modeled and retrieved LST vary tremendously by region and time of day. Typical (absolute) MD values range from 1-3 K in Northern Hemisphere mid-latitude regions to near 10 K in regions where modeled clouds are unrealistic, for example in north-eastern Argentina, Uruguay, Paraguay, and southern Brazil. Typically, model estimates of LST are higher than satellite retrievals during the night and lower during the day. RMSD values range from 1-3 K during the night to 2-5 K during the day, but are larger over the 50-120 W longitude band where the LST retrievals are derived from the FY2E platform

  6. A Prototype Algorithm for Land Surface Temperature Retrieval from Sentinel-3 Mission

    Science.gov (United States)

    Sobrino, Jose A.; Jimenez-Munoz, Juan C.; Soria, Guillem; Brockmann, Carsten; Ruescas, Ana; Danne, Olaf; North, Peter; Phillipe, Pierre; Berger, Michel; Merchant, Chris; Ghent, Darren; Remedios, John

    2015-12-01

    In this work we present a prototype algorithm to retrieve Land Surface Temperature (LST) from OLCI and SLSTR instruments on board Sentinel-3 platform, which was developed in the framework of the SEN4LST project. For this purpose, data acquired with the ENVISAT MERIS and AATSR instruments are used as a benchmark. The objective is to improve the LST standard product (level 2) currently derived from the single AATSR instrument taking advantages of the improved characteristics of the future OLCI and SLSTR instruments. Hence, the high spectral resolution of OLCI instrument and the dual-view and thermal bands available in the SLSTR instruments have the potential to improve the characterization of the atmosphere and therefore to improve the atmospheric correction and cloud mask. Bands in the solar domain available in both instruments allow the retrieval of the surface emissivity, being a key input to the LST algorithm. Pairs of MERIS/AATSR are processed over different sites and validated with in situ measurements using the LST processor included in the BEAM software. Results showed that the proposed LST algorithm improves LST retrievals of the standard level-2 product.

  7. Estimating Daily Maximum and Minimum Land Air Surface Temperature Using MODIS Land Surface Temperature Data and Ground Truth Data in Northern Vietnam

    Directory of Open Access Journals (Sweden)

    Phan Thanh Noi

    2016-12-01

    Full Text Available This study aims to evaluate quantitatively the land surface temperature (LST derived from MODIS (Moderate Resolution Imaging Spectroradiometer MOD11A1 and MYD11A1 Collection 5 products for daily land air surface temperature (Ta estimation over a mountainous region in northern Vietnam. The main objective is to estimate maximum and minimum Ta (Ta-max and Ta-min using both TERRA and AQUA MODIS LST products (daytime and nighttime and auxiliary data, solving the discontinuity problem of ground measurements. There exist no studies about Vietnam that have integrated both TERRA and AQUA LST of daytime and nighttime for Ta estimation (using four MODIS LST datasets. In addition, to find out which variables are the most effective to describe the differences between LST and Ta, we have tested several popular methods, such as: the Pearson correlation coefficient, stepwise, Bayesian information criterion (BIC, adjusted R-squared and the principal component analysis (PCA of 14 variables (including: LST products (four variables, NDVI, elevation, latitude, longitude, day length in hours, Julian day and four variables of the view zenith angle, and then, we applied nine models for Ta-max estimation and nine models for Ta-min estimation. The results showed that the differences between MODIS LST and ground truth temperature derived from 15 climate stations are time and regional topography dependent. The best results for Ta-max and Ta-min estimation were achieved when we combined both LST daytime and nighttime of TERRA and AQUA and data from the topography analysis.

  8. Land surface temperature shaped by urban fractions in megacity region

    Science.gov (United States)

    Zhang, Xiaoxuan; Hu, Yonghong; Jia, Gensuo; Hou, Meiting; Fan, Yanguo; Sun, Zhongchang; Zhu, Yuxiang

    2017-02-01

    Large areas of cropland and natural vegetation have been replaced by impervious surfaces during the recent rapid urbanization in China, which has resulted in intensified urban heat island effects and modified local or regional warming trends. However, it is unclear how urban expansion contributes to local temperature change. In this study, we investigated the relationship between land surface temperature (LST) change and the increase of urban land signals. The megacity of Tianjin was chosen for the case study because it is representative of the urbanization process in northern China. A combined analysis of LST and urban land information was conducted based on an urban-rural transect derived from Landsat 8 Thermal Infrared Sensor (TIRS), Terra Moderate Resolution Imaging Spectrometer (MODIS), and QuickBird images. The results indicated that the density of urban land signals has intensified within a 1-km2 grid in the urban center with an impervious land fraction >60 %. However, the construction on urban land is quite different with low-/mid-rise buildings outnumbering high-rise buildings in the urban-rural transect. Based on a statistical moving window analysis, positive correlation ( R 2 > 0.9) is found between LST and urban land signals. Surface temperature change (ΔLST) increases by 0.062 °C, which was probably caused by the 1 % increase of urbanized land (ΔIF) in this case region.

  9. A study of the coupling relationship between concrete surface temperature and concrete surface emissivity in natural conditions.

    Science.gov (United States)

    Tang, Lin-Ling; Chen, Xiao-Ling; Wang, Jia-Ning; Zhao, Hong-Mei; Huang, Qi-Ting

    2014-07-01

    Land surface emissivity (LSE) has already been recognized as a crucial parameter for the determination of land surface temperature (LST). There is an ill-posed problem for the retrieval of LST and LSE. And laboratory-based emissivity is measured in natural constant conditions, which is limited in the application in thermal remote sensing. To solve the above problems, the coupling of LST and LSE is explored to eliminate temperature effects and improve the accuracy of LES. And then, the estimation accuracy of LST from passive remote sensing images will be improved. For different land surface materials, the coupling of land surface emissivity and land surface temperature is various. This paper focuses on studying concrete surface that is one of the typical man-made materials in urban. First the experiments of measuring concrete surface emissivity and concrete surface temperature in natural conditions are arranged reasonably and the suitable data are selected under ideal atmosphere conductions. Then to improve the determination accuracy of concrete surface emissivity, the algorithm worked on the computer of Fourier Transform Infrared Spectroradiometer (FTIR) has been improved by the most adapted temperature and emissivity separation algorithm. Finally the coupling of concrete surface temperature and concrete surface emissivity is analyzed and the coupling model of concrete surface temperature and concrete surface emissivity is established. The results show that there is a highest correlation coefficient between the second derivative of emissivity spectra and concrete surface temperature, and the correlation coefficient is -0.925 1. The best coupling model is the stepwise regression model, whose determination coefficient (R2) is 0.886. The determination coefficient (R2) is 0.905 and the root mean squares error (RMSE) is 0.292 1 in the validation of the model. The coupling model of concrete surface temperature and concrete surface emissivity under natural conditions

  10. Retrieval of Land Surface Temperature over the Heihe River Basin Using HJ-1B Thermal Infrared Data

    Directory of Open Access Journals (Sweden)

    Xiaoying Ouyang

    2014-12-01

    Full Text Available The reliable estimation of spatially distributed Land Surface Temperature (LST is useful for monitoring regional land surface heat fluxes. A single-channel method is developed to derive the LST over the Heihe River Basin in China using data from the infrared sensor (IRS onboard the Chinese “Environmental and Disaster Monitoring and Forecasting with a Small Satellite Constellation” (HJ-1B for short for one of the satellites, with ancillary water vapor information from Moderate Resolution Imaging Spectroradiometer (MODIS products (MOD05 and in situ automatic sun tracking photometer CE318 data for the first time. In situ LST data for the period from mid-June to mid-September 2012 were acquired from automatic meteorological stations (AMS that are part of Heihe Watershed Allied Telemetry Experimental Research (HiWATER project. MOD05-based LST and CE318-based LST are compared with in situ measurements at 16 AMS sites with land cover types of vegetable, maize and orchards. The results show that the use of the MOD05 product could achieve a comparable accuracy in LST retrieval with that achieved using the CE318 data. The largest difference between the MOD05-based LST and CE318-based LST is 0.84 K throughout the study period over the Heihe River Basin. The standard deviation (STD, root mean square error (RMSE, and correlation coefficient (R of HJ-1B/IRS vs. the in situ measurements are 2.45 K, 2.78 K, and 0.67, respectively, whereas those for the MODIS 1 km LST product vs. the in situ measurements are 4.07 K, 2.98 K, and 0.79, respectively. The spatial pattern of the HJ-1B/LST over the study area in the Heihe River Basin generally agreed well with the MODIS 1 km LST product and contained more detailed spatial textures.

  11. MODIS/TERRA MOD11C3 Land Surface Temperature and Emissivity Monthly L3 Global 0.05Deg CMG

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — The MODIS/Terra Land Surface Temperature and Emissivity (LST/E) products provide per-pixel temperature and emissivity values in a sequence of swath-based to...

  12. MODIS/Aqua MYD11_L2 Land Surface Temperature and Emissivity 5-Minute L2 Swath 1 km Version 6

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — The MODIS/Aqua Land Surface Temperature and Emissivity (LST/E) products provide per-pixel temperature and emissivity values in a sequence of swath-based global...

  13. MODIS/Aqua MYD11C2 Land Surface Temperature/Emissivity 8-Day L3 Global 0.05Deg CMG Version 6

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — The MODIS/Aqua Land Surface Temperature and Emissivity (LST/E) products provide per-pixel temperature and emissivity values in a sequence of swath-based global...

  14. MODIS/TERRA MOD11C2 Land Surface Temperature/Emissivity 8-Day L3 Global 0.05Deg CMG Version 6

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — The MODIS/Aqua Land Surface Temperature and Emissivity (LST/E) products provide per-pixel temperature and emissivity values in a sequence of swath-based global...

  15. MODIS/TERRA MOD11B3 Land Surface Temperature and Emissivity Daily L3 Global 5 km Grid SIN Version 6

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — The MODIS/Aqua Land Surface Temperature and Emissivity (LST/E) products provide per-pixel temperature and emissivity values in a sequence of swath-based global...

  16. MODIS/Aqua MYD11A2 Land Surface Temperature & Emissivity 8-Day L3 Global 1km Gird SIN Version 6

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — The MODIS/Aqua Land Surface Temperature and Emissivity (LST/E) products provide per-pixel temperature and emissivity values in a sequence of swath-based global...

  17. MODIS/Aqua MYD11C3 Land Surface Temperature/Emissivity Monthly L3 Global 0.05Deg CMG Version 6

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — The MODIS/Aqua Land Surface Temperature and Emissivity (LST/E) products provide per-pixel temperature and emissivity values in a sequence of swath-based global...

  18. MODIS/TERRA MOD11B2 Land Surface Temperature and Emissivity Daily L3 Global 5 km Grid SIN Version 6

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — The MODIS/Aqua Land Surface Temperature and Emissivity (LST/E) products provide per-pixel temperature and emissivity values in a sequence of swath-based global...

  19. MODIS/TERRA MOD11_L2 Land Surface Temperature and Emissivity 5-Minute L2 Swath 1 km Version 6

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — The MODIS/Aqua Land Surface Temperature and Emissivity (LST/E) products provide per-pixel temperature and emissivity values in a sequence of swath-based global...

  20. MODIS/Aqua MYD11C1 Land Surface Temperature and Emissivity Daily L3 Global 0.05Deg CMG Version 6

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — The MODIS/Aqua Land Surface Temperature and Emissivity (LST/E) products provide per-pixel temperature and emissivity values in a sequence of swath-based global...

  1. MODIS/TERRA MOD11C1 Land Surface Temperature and Emissivity Daily L3 Global 0.05Deg CMG Version 6

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — The MODIS/Aqua Land Surface Temperature and Emissivity (LST/E) products provide per-pixel temperature and emissivity values in a sequence of swath-based global...

  2. MODIS/Aqua MYD11A1 Land Surface Temperature and Emissivity Daily L3 Global 1 km Grid SIN Version 6

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — The MODIS/Aqua Land Surface Temperature and Emissivity (LST/E) products provide per-pixel temperature and emissivity values in a sequence of swath-based global...

  3. MODIS/TERRA MOD11C3 Land Surface Temperature and Emissivity Monthly L3 Global 0.05Deg CMG Version 6

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — The MODIS/Aqua Land Surface Temperature and Emissivity (LST/E) products provide per-pixel temperature and emissivity values in a sequence of swath-based global...

  4. MODIS/COMBINED MOD11A1 Land Surface Temperature and Emissivity Daily L3 Global 1 km Grid SIN Version 6

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — The MODIS/Aqua Land Surface Temperature and Emissivity (LST/E) products provide per-pixel temperature and emissivity values in a sequence of swath-based global...

  5. MODIS/TERRA MOD11B1 Land Surface Temperature and Emissivity Daily L3 Global 5 km Grid SIN Version 6

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — The MODIS/Aqua Land Surface Temperature and Emissivity (LST/E) products provide per-pixel temperature and emissivity values in a sequence of swath-based global...

  6. MODIS/Aqua MYD11B1 Land Surface Temperature and Emissivity Daily L3 Global 5 km Grid SIN Version 6

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — The MODIS/Aqua Land Surface Temperature and Emissivity (LST/E) products provide per-pixel temperature and emissivity values in a sequence of swath-based global...

  7. MODIS/TERRA MYD11B3 Land Surface Temperature and Emissivity Daily L3 Global 5 km Grid SIN Version 6

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — The MODIS/Aqua Land Surface Temperature and Emissivity (LST/E) products provide per-pixel temperature and emissivity values in a sequence of swath-based global...

  8. MODIS/TERRA MYD11B2 Land Surface Temperature and Emissivity Daily L3 Global 5 km Grid SIN Version 6

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — The MODIS/Aqua Land Surface Temperature and Emissivity (LST/E) products provide per-pixel temperature and emissivity values in a sequence of swath-based global...

  9. Evaluation of MODIS Land Surface Temperature with In Situ Snow Surface Temperature from CREST-SAFE

    Science.gov (United States)

    Perez Diaz, C. L.; Lakhankar, T.; Romanov, P.; Munoz, J.; Khanbilvardi, R.; Yu, Y.

    2016-12-01

    This paper presents the procedure and results of a temperature-based validation approach for the Moderate Resolution Imaging Spectroradiometer (MODIS) Land Surface Temperature (LST) product provided by the National Aeronautics and Space Administration (NASA) Terra and Aqua Earth Observing System satellites using in situ LST observations recorded at the Cooperative Remote Sensing Science and Technology Center - Snow Analysis and Field Experiment (CREST-SAFE) during the years of 2013 (January-April) and 2014 (February-April). A total of 314 day and night clear-sky thermal images, acquired by the Terra and Aqua satellites, were processed and compared to ground-truth data from CREST-SAFE with a frequency of one measurement every 3 min. Additionally, this investigation incorporated supplementary analyses using meteorological CREST-SAFE in situ variables (i.e. wind speed, cloud cover, incoming solar radiation) to study their effects on in situ snow surface temperature (T-skin) and T-air. Furthermore, a single pixel (1km2) and several spatially averaged pixels were used for satellite LST validation by increasing the MODIS window size to 5x5, 9x9, and 25x25 windows for comparison. Several trends in the MODIS LST data were observed, including the underestimation of daytime values and nighttime values. Results indicate that, although all the data sets (Terra and Aqua, diurnal and nocturnal) showed high correlation with ground measurements, day values yielded slightly higher accuracy ( 1°C), both suggesting that MODIS LST retrievals are reliable for similar land cover classes and atmospheric conditions. Results from the CREST-SAFE in situ variables' analyses indicate that T-air is commonly higher than T-skin, and that a lack of cloud cover results in: lower T-skin and higher T-air minus T-skin difference (T-diff). Additionally, the study revealed that T-diff is inversely proportional to cloud cover, wind speed, and incoming solar radiation. Increasing the MODIS window size

  10. Analyzing land surface temperature variations during Fogo Island (Cape Verde) 2014-2015 eruption with Landsat 8 images

    Science.gov (United States)

    Vieira, D.; Teodoro, A.; Gomes, A.

    2016-10-01

    Land Surface Temperature (LST) is an important parameter related to land surface processes that changes continuously through time. Assessing its dynamics during a volcanic eruption has both environmental and socio-economical interest. Lava flows and other volcanic materials produced and deposited throughout an eruption transform the landscape, contributing to its heterogeneity and altering LST measurements. This paper aims to assess variations of satellite-derived LST and to detect patterns during the latest Fogo Island (Cape Verde) eruption, extending from November 2014 through February 2015. LST data was obtained through four processed Landsat 8 images, focused on the caldera where Pico do Fogo volcano sits. QGIS' plugin Semi-Automatic Classification was used in order to apply atmospheric corrections and radiometric calibrations. The algorithm used to retrieve LST values is a single-channel method, in which emissivity values are known. The absence of in situ measurements is compensated by the use of MODIS sensor-derived LST data, used to compare with Landsat retrieved measurements. LST data analysis shows as expected that the highest LST values are located inside the caldera. High temperature values were also founded on the south-facing flank of the caldera. Although spatial patterns observed on the retrieved data remained roughly the same during the time period considered, temperature values changed throughout the area and over time, as it was also expected. LST values followed the eruption dynamic experiencing a growth followed by a decline. Moreover, it seems possible to recognize areas affected by lava flows of previous eruptions, due to well-defined LST spatial patterns.

  11. Estimation of Land Surface Temperature through Blending MODIS and AMSR-E Data with the Bayesian Maximum Entropy Method

    Directory of Open Access Journals (Sweden)

    Xiaokang Kou

    2016-01-01

    Full Text Available Land surface temperature (LST plays a major role in the study of surface energy balances. Remote sensing techniques provide ways to monitor LST at large scales. However, due to atmospheric influences, significant missing data exist in LST products retrieved from satellite thermal infrared (TIR remotely sensed data. Although passive microwaves (PMWs are able to overcome these atmospheric influences while estimating LST, the data are constrained by low spatial resolution. In this study, to obtain complete and high-quality LST data, the Bayesian Maximum Entropy (BME method was introduced to merge 0.01° and 0.25° LSTs inversed from MODIS and AMSR-E data, respectively. The result showed that the missing LSTs in cloudy pixels were filled completely, and the availability of merged LSTs reaches 100%. Because the depths of LST and soil temperature measurements are different, before validating the merged LST, the station measurements were calibrated with an empirical equation between MODIS LST and 0~5 cm soil temperatures. The results showed that the accuracy of merged LSTs increased with the increasing quantity of utilized data, and as the availability of utilized data increased from 25.2% to 91.4%, the RMSEs of the merged data decreased from 4.53 °C to 2.31 °C. In addition, compared with the filling gap method in which MODIS LST gaps were filled with AMSR-E LST directly, the merged LSTs from the BME method showed better spatial continuity. The different penetration depths of TIR and PMWs may influence fusion performance and still require further studies.

  12. Quantification of the Scale Effect in Downscaling Remotely Sensed Land Surface Temperature

    Directory of Open Access Journals (Sweden)

    Ji Zhou

    2016-11-01

    Full Text Available Most current statistical models for downscaling the remotely sensed land surface temperature (LST are based on the assumption of the scale-invariant LST-descriptors relationship, which is being debated and requires an in-depth examination. Additionally, research on downscaling LST to high or very high resolutions (~10 m is still rare. Here, a simple analytical model was developed to quantify the scale effect in downscaling the LST from a medium resolution (~100 m to high resolutions. The model was verified in the Zhangye oasis and Beijing city. Examinations of the simulation datasets that were generated based on airborne and space station LSTs demonstrate that the developed model can predict the scale effect in LST downscaling; the scale effect exists in both of these two study areas. The model was further applied to 12 ASTER images in the Zhangye oasis during a complete crop growing season and one Landsat-8 TIRS image in Beijing city in the summer. The results demonstrate that the scale effect is intrinsically caused by the varying probability distribution of the LST and its descriptors at the native and target resolutions. The scale effect depends on the values of the descriptors, the phenology, and the ratio of the native resolution to the target resolution. Removing the scale effect would not necessarily improve the accuracy of the downscaled LST.

  13. Quantifying the influences of various ecological factors on land surface temperature of urban forests.

    Science.gov (United States)

    Ren, Yin; Deng, Lu-Ying; Zuo, Shu-Di; Song, Xiao-Dong; Liao, Yi-Lan; Xu, Cheng-Dong; Chen, Qi; Hua, Li-Zhong; Li, Zheng-Wei

    2016-09-01

    Identifying factors that influence the land surface temperature (LST) of urban forests can help improve simulations and predictions of spatial patterns of urban cool islands. This requires a quantitative analytical method that combines spatial statistical analysis with multi-source observational data. The purpose of this study was to reveal how human activities and ecological factors jointly influence LST in clustering regions (hot or cool spots) of urban forests. Using Xiamen City, China from 1996 to 2006 as a case study, we explored the interactions between human activities and ecological factors, as well as their influences on urban forest LST. Population density was selected as a proxy for human activity. We integrated multi-source data (forest inventory, digital elevation models (DEM), population, and remote sensing imagery) to develop a database on a unified urban scale. The driving mechanism of urban forest LST was revealed through a combination of multi-source spatial data and spatial statistical analysis of clustering regions. The results showed that the main factors contributing to urban forest LST were dominant tree species and elevation. The interactions between human activity and specific ecological factors linearly or nonlinearly increased LST in urban forests. Strong interactions between elevation and dominant species were generally observed and were prevalent in either hot or cold spots areas in different years. In conclusion, quantitative studies based on spatial statistics and GeogDetector models should be conducted in urban areas to reveal interactions between human activities, ecological factors, and LST.

  14. On the sensitivity of Land Surface Temperature estimates in arid irrigated lands using MODTRAN

    KAUST Repository

    Rosas, Jorge

    2015-11-29

    Land surface temperature (LST) derived from thermal infrared (TIR) satellite data has been reliably used as a remote indicator of evapotranspiration (ET) and surface moisture status. However, in order to retrieve the ET with an accuracy approaching 10%, LST should be retrieved to within 1 ◦C or better, disregarding other elements of uncertainty. The removal of atmospheric effects is key towards achieving a precise estimation of LST and it requires detailed information on water vapor. The Thermal Infrared Sensor (TIRS) onboard Landsat 8 captures data in two long wave thermal bands with 100-meter resolution. However, the US Geological Survey has reported a calibration problem of TIRS bands caused by stray light, resulting in a higher bias in one of its two bands (4% in band 11, 2% in band 10). Therefore, split-window algorithms for the estimation of LST might not be reliable. Our work will focus on the impact of using different atmospheric profiles (e.g. weather prediction models, satellite) for the estimation of LST derived from MODTRAN by using one of the TIRS bands onboard Landsat 8 (band 10). Sites with in-situ measurements of LST are used as evaluation sources. Comparisons between the measured LST and LST derived based on different atmospheric profile inputs to MODTRAN are carried out from 2 Landsat-overpass days (DOY 153 and 160 2015). Preliminary results show a mean absolute error of around 3 ◦C between in-situ and estimated LST over two different crops (alfalfa and carrot) and bare soil.

  15. Land Surface Temperature Retrieval in Wetlands Using Normalized Difference Vegetation Index-Emissivity Estimation and ASTER Emissivity Product

    Science.gov (United States)

    Muro, Javier; Heinmann, Sascha; Strauch, Adrian; Menz, Gunter

    2016-08-01

    Land Surface Temperature (LST) has the potential to act as a continuous indicator of the ecological status of wetlands. Accurate emissivity values are required in order to calculate precise LST. We test two emissivity retrieval methods and their influence on LST calculated from a Landsat 7 image of a highly dynamic wetland in Southern Spain. LST calculated using NDVI (Normalized Difference Vegetation Index) threshold estimations and the ASTER emissivity product are compared. The results show differences of around 0-1 K for most land covers, and up to 3 K for areas of bare soil when Landsat and ASTER images have the same acquisition date. Tests using Landsat and ASTER images from different seasons do not show greater differences between both LSTs. This has important implications for automated LST retrieval methods, such as the one planed by the USGS using Landsat and ASTER emissivity products.

  16. Using Microwave Observations to Estimate Land Surface Temperature during Cloudy Conditions

    Science.gov (United States)

    Holmes, T. R.; Crow, W. T.; Hain, C.; Anderson, M. C.

    2014-12-01

    Land surface temperature (LST), a key ingredient for physically-based retrieval algorithms of hydrological states and fluxes, remains a poorly constrained parameter for global scale studies. The main two observational methods to remotely measure T are based on thermal infrared (TIR) observations and passive microwave observations (MW). TIR is the most commonly used approach and the method of choice to provide standard LST products for various satellite missions. MW-based LST retrievals on the other hand are not as widely adopted for land applications; currently their principle use is in soil moisture retrieval algorithms. MW and TIR technologies present two highly complementary and independent means of measuring LST. MW observations have a high tolerance to clouds but a low spatial resolution, and TIR has a high spatial resolution with temporal sampling restricted to clear skies. The nature of the temperature at the very surface layer of the land makes it difficult to combine temperature estimates between different methods. The skin temperature is characterized by a strong diurnal cycle that is dependant in timing and amplitude on the exact sensing depth and thermal properties of the vegetation. This paper builds on recent progress in characterizing the main structural components of the DTC that explain differences in TIR and MW estimates of LST. Spatial patterns in DTC timing (phase lag with solar noon) and DTC amplitude have been calculated for TIR, MW and compared to weather prediction estimates. Based on these comparisons MW LST can be matched to the TIR record. This paper will compare in situ measurements of LST with satellite estimates from (downscaled) TIR and (reconciled) MW products. By contrasting the validation results of clear sky days with those of cloudy days the expected tolerance to clouds of the MW observations will be tested. The goal of this study is to determine the weather conditions in which MW can supplement the TIR LST record.

  17. The Land Surface Temperature Synergistic Processor in BEAM: A Prototype towards Sentinel-3

    CERN Document Server

    Ruescas, Ana Belen; Fomferra, Norman; Brockmann, Carsten

    2016-01-01

    Land Surface Temperature (LST) is one of the key parameters in the physics of land-surface processes on regional and global scales, combining the results of all surface-atmosphere interactions and energy fluxes between the surface and the atmosphere. With the advent of the European Space Agency (ESA) Sentinel 3 (S3) satellite, accurate LST retrieval methodologies are being developed by exploiting the synergy between the Ocean and Land Colour Instrument (OLCI) and the Sea and Land Surface Temperature Radiometer (SLSTR). In this paper we explain the implementation in the Basic ENVISAT Toolbox for (A)ATSR and MERIS (BEAM) and the use of one LST algorithm developed in the framework of the Synergistic Use of The Sentinel Missions For Estimating And Monitoring Land Surface Temperature (SEN4LST) project. The LST algorithm is based on the split-window technique with an explicit dependence on the surface emissivity. Performance of the methodology is assessed by using MEdium Resolution Imaging Spectrometer/Advanced Alo...

  18. Afforestation in China cools local land surface temperature.

    Science.gov (United States)

    Peng, Shu-Shi; Piao, Shilong; Zeng, Zhenzhong; Ciais, Philippe; Zhou, Liming; Li, Laurent Z X; Myneni, Ranga B; Yin, Yi; Zeng, Hui

    2014-02-25

    China has the largest afforested area in the world (∼62 million hectares in 2008), and these forests are carbon sinks. The climatic effect of these new forests depends on how radiant and turbulent energy fluxes over these plantations modify surface temperature. For instance, a lower albedo may cause warming, which negates the climatic benefits of carbon sequestration. Here, we used satellite measurements of land surface temperature (LST) from planted forests and adjacent grasslands or croplands in China to understand how afforestation affects LST. Afforestation is found to decrease daytime LST by about 1.1 ± 0.5 °C (mean ± 1 SD) and to increase nighttime LST by about 0.2 ± 0.5 °C, on average. The observed daytime cooling is a result of increased evapotranspiration. The nighttime warming is found to increase with latitude and decrease with average rainfall. Afforestation in dry regions therefore leads to net warming, as daytime cooling is offset by nighttime warming. Thus, it is necessary to carefully consider where to plant trees to realize potential climatic benefits in future afforestation projects.

  19. Analysis of the Relationship between Land Surface Temperature and Wildfire Severity in a Series of Landsat Images

    Directory of Open Access Journals (Sweden)

    Lidia Vlassova

    2014-06-01

    Full Text Available The paper assesses spatio-temporal patterns of land surface temperature (LST and fire severity in the Las Hurdes wildfire of Pinus pinaster forest, which occurred in July 2009, in Extremadura (Spain, from a time series of fifteen Landsat 5 TM images corresponding to 27 post-fire months. The differenced Normalized Burn Ratio (dNBR was used to evaluate burn severity. The mono-window algorithm was applied to estimate LST from the Landsat thermal band. The burned zones underwent a significant increase in LST after fire. Statistically significant differences have been detected between the LST within regions of burn severity categories. More substantial changes in LST are observed in zones of greater fire severity, which can be explained by the lower emissivity of combustion products found in the burned area and changes in the energy balance related to vegetation removal. As time progresses over the 27 months after fire, LST differences decrease due to vegetation regeneration. The differences in LST and Normalized Difference Vegetation Index (NDVI values between burn severity categories in each image are highly correlated (r = 0.84. Spatial patterns of severity and post-fire LST obtained from Landsat time series enable an evaluation of the relationship between these variables to predict the natural dynamics of burned areas.

  20. Statistical analysis of land surface temperature-vegetation indexes relationship through thermal remote sensing.

    Science.gov (United States)

    Kumar, Deepak; Shekhar, Sulochana

    2015-11-01

    Vegetation coverage has a significant influence on the land surface temperature (LST) distribution. In the field of urban heat islands (UHIs) based on remote sensing, vegetation indexes are widely used to estimate the LST-vegetation relationship. This paper devises two objectives. The first analyzes the correlation between vegetation parameters/indicators and LST. The subsequent computes the occurrence of vegetation parameter, which defines the distribution of LST (for quantitative analysis of urban heat island) in Kalaburagi (formerly Gulbarga) City. However, estimation work has been done on the valuation of the relationship between different vegetation indexes and LST. In addition to the correlation between LST and the normalized difference vegetation index (NDVI), the normalized difference build-up index (NDBI) is attempted to explore the impacts of the green land to the build-up land on the urban heat island by calculating the evaluation index of sub-urban areas. The results indicated that the effect of urban heat island in Kalaburagi city is mainly located in the sub-urban areas or Rurban area especially in the South-Eastern and North-Western part of the city. The correlation between LST and NDVI, indicates the negative correlation. The NDVI suggests that the green land can weaken the effect on urban heat island, while we perceived the positive correlation between LST and NDBI, which infers that the built-up land can strengthen the effect of urban heat island in our case study. Although satellite data (e.g., Landsat TM thermal bands data) has been applied to test the distribution of urban heat islands, but the method still needs to be refined with in situ measurements of LST in future studies.

  1. Impacts of Land Use and Cover Change on Land Surface Temperature in the Zhujiang Delta

    Institute of Scientific and Technical Information of China (English)

    QIAN Le-Xiang; CUI Hai-Sha; CHANG Jie

    2006-01-01

    Remote sensing and geographic information systems (GIS) technologies were used to detect land use/cover changes(LUCC) and to assess their impacts on land surface temperature (LST) in the Zhujiang Delta. Multi-temporal Landsat TM and Landsat ETM+ data were employed to identify patterns of LUCC as well as to quantify urban expansion and the associated decrease of vegetation cover. The thermal infrared bands of the data were used to retrieve LST. The results revealed a strong and uneven urban growth, which caused LST to raise 4.56 ℃ in the newly urbanized part of the study area. Overall, remote sensing and CIS technologies were effective approaches for monitoring and analyzing urban growth patterns and evaluating their impacts on LST.

  2. Potential association of dengue hemorrhagic fever incidence and remote senses land surface temperature, Thailand, 1998.

    Science.gov (United States)

    Nitatpattana, Narong; Singhasivanon, Pratap; Kiyoshi, Honda; Andrianasolo, Haja; Yoksan, Sutee; Gonzalez, Jean-Paul; Barbazan, Philippe

    2007-05-01

    A pilot study was designed to analyze a potential association between dengue hemorrhagic fever (DHF) incidence and, temperature computed by satellite. DHF is a mosquito transmitted disease, and water vapor and humidity are known to have a positive effect on mosquito life by increasing survival time and shortening the development cycle. Among other available satellite data, Land Surface Temperature (LST) was chosen as an indicator that combined radiated earth temperature and atmospheric water vapor concentration. Monthly DHF incidence was recorded by province during the 1998 epidemic and obtained as a weekly combined report available from the National Ministry of Public Health. Conversely, LST was calculated using remotely sensed data obtained from thermal infrared sensors of NOAA satellites and computed on a provincial scale. Out of nine selected study provinces, five (58.3%) exhibited an LST with a significant positive correlation with rainfall (p < 0.05). In four out of nineteen surveyed provinces (21.3%), LST showed a significant positive correlation with DHF incidence (p < 0.05). Positive association between LST and DHF incidence was significantly correlated in 75% of the cases during non-epidemic months, while no correlation was found during epidemic months. Non-climatic factors are supposed to be at the origin of this discrepancy between seasonality in climate (LST) and DHF incidence during epidemics.

  3. Inter-Comparison of In-Situ Sensors for Land Surface Temperature Measurements

    Science.gov (United States)

    Krishnan, P.; Kochendorfer, J.; Meyers, T. P.; Guillevic, P. C.; Hook, S. J.

    2014-12-01

    Land Surface Temperature (LST) is a key variable in the determination of land surface processes from local to global scales. It has been identified as one of the most important environmental data records and is widely used in meteorological, climatological, hydrological, ecological, biophysical, and biochemical studies. Despite its importance, accurate in-situ measurements of LST are not yet available for the whole globe and are not routinely conducted at weather stations along with standard meteorological observations, with few exceptions including NOAA's United States Climate Reference Network. Even though satellite radiometric measurements of LST are a powerful tool, there are still large uncertainties associated with the retrieval of remotely sensed LST measurements. To improve confidence in the methods, algorithms, and parameters used to derive remotely sensed LST, validation of satellite data using high-quality ground-based measurements is required. With the objective of improving the quality of in situ measurements of LST and to evaluate the quantitative uncertainties in the ground-based measurements, intensive experiments were conducted at NOAA/ATDD in Oak ridge, TN from September 2013 to 2014. During the study period, multiple measurements of land surface skin temperature were made using infra-red temperature sensors - including the JPL radiometer, two models of Apogee infrared radiometers, and thermocouples embedded in the ground surface. In addition, aspirated air temperature and four-band net radiation measurements were also made. Overall the in situ LST measurements from the different sensors were in good agreement with each other, with a correlation coefficient of ~1 and root mean square error of <1 oC.

  4. Developing a confidence metric for the Landsat land surface temperature product

    Science.gov (United States)

    Laraby, Kelly G.; Schott, John R.; Raqueno, Nina

    2016-05-01

    Land Surface Temperature (LST) is an important Earth system data record that is useful to fields such as change detection, climate research, environmental monitoring, and smaller scale applications such as agriculture. Certain Earth-observing satellites can be used to derive this metric, and it would be extremely useful if such imagery could be used to develop a global product. Through the support of the National Aeronautics and Space Administration (NASA) and the United States Geological Survey (USGS), a LST product for the Landsat series of satellites has been developed. Currently, it has been validated for scenes in North America, with plans to expand to a trusted global product. For ideal atmospheric conditions (e.g. stable atmosphere with no clouds nearby), the LST product underestimates the surface temperature by an average of 0.26 K. When clouds are directly above or near the pixel of interest, however, errors can extend to several Kelvin. As the product approaches public release, our major goal is to develop a quality metric that will provide the user with a per-pixel map of estimated LST errors. There are several sources of error that are involved in the LST calculation process, but performing standard error propagation is a difficult task due to the complexity of the atmospheric propagation component. To circumvent this difficulty, we propose to utilize the relationship between cloud proximity and the error seen in the LST process to help develop a quality metric. This method involves calculating the distance to the nearest cloud from a pixel of interest in a scene, and recording the LST error at that location. Performing this calculation for hundreds of scenes allows us to observe the average LST error for different ranges of distances to the nearest cloud. This paper describes this process in full, and presents results for a large set of Landsat scenes.

  5. Estimation and Modelling of Land Surface Temperature Using Landsat 7 ETM+ Images and Fuzzy System Techniques

    Science.gov (United States)

    Bisht, K.; Dodamani, S. S.

    2016-12-01

    Modelling of Land Surface Temperature is essential for short term and long term management of environmental studies and management activities of the Earth's resources. The objective of this research is to estimate and model Land Surface Temperatures (LST). For this purpose, Landsat 7 ETM+ images period from 2007 to 2012 were used for retrieving LST and processed through MATLAB software using Mamdani fuzzy inference systems (MFIS), which includes pre-monsoon and post-monsoon LST in the fuzzy model. The Mangalore City of Karnataka state, India has been taken for this research work. Fuzzy model inputs are considered as the pre-monsoon and post-monsoon retrieved temperatures and LST was chosen as output. In order to develop a fuzzy model for LST, seven fuzzy subsets, nineteen rules and one output are considered for the estimation of weekly mean air temperature. These are very low (VL), low (L), medium low (ML), medium (M), medium high (MH), high (H) and very high (VH). The TVX (Surface Temperature Vegetation Index) and the empirical method have provided estimated LST. The study showed that the Fuzzy model M4/7-19-1 (model 4, 7 fuzzy sets, 19 rules and 1 output) which developed over Mangalore City has provided more accurate outcomes than other models (M1, M2, M3, M5). The result of this research was evaluated according to statistical rules. The best correlation coefficient (R) and root mean squared error (RMSE) between estimated and measured values for pre-monsoon and post-monsoon LST found to be 0.966 - 1.607 K and 0.963- 1.623 respectively.

  6. Uncertainty Estimates of NASA Satellite LST over the Greenland and Antarctic Plateau: 2003-2015

    Science.gov (United States)

    Knuteson, R.; Borbas, E. E.; Burgess, G.

    2015-12-01

    Jin and Dickinson (2010) identify three reasons why LST has not been adopted as a climate variable. Paraphrasing the authors, the three roadblocks for use of satellite LST products in climate studies are; 1) unknown accuracy (What are surface emissivity and atmospheric correction uncertainties?)2) spatial scale ambiguity (Are satellite footprints too large to be physically meaningful?)3) lack of consistency over decadal time scales (How far backward/forward can we go in time?). These issues apply particularly to the cryosphere where the lack of surface measurement sites make the proper use of satellite observations critical for monitoring climate change. This paper will address each of these three issues but with a focus on the high and dry Greenland and Antarctic plateaus and the contrast in trends between the two. Recent comparisons of MODIS LST products with AIRS version 6 LST products show large differences over Greenland (Lee et al. 2014). In this paper we take the logical next step of creating a bottoms up uncertainty budget for a new synergistic AIRS/MODIS LST product for ice and snow conditions. This new product will address the issue of unknown accuracy by providing a local LST uncertainty along with each estimate of surface temperature. The combination of the high spatial resolution of the MODIS and the high spectral resolution of the AIRS observations of radiance allow the combination of the two sensors to provide information with lower uncertainty than what is possible from the current separate operational products. The issue of surface emissivity and atmospheric correction uncertainties will be addressed explicitly using spectrally resolved models that cover the infrared region. The issue of spatial scale ambiguity is overcome by creating a classification of the results based on the spatial homogenity of surface temperatures. The issue of lack of consistency over long time scales is addressed by demonstrating an algorithm using collocated NASA MODIS

  7. Derivation and evaluation of land surface temperature from the geostationary operational environmental satellite series

    Science.gov (United States)

    Fang, Li

    The Geostationary Operational Environmental Satellites (GOES) have been continuously monitoring the earth surface since 1970, providing valuable and intensive data from a very broad range of wavelengths, day and night. The National Oceanic and Atmospheric Administration's (NOAA's) National Environmental Satellite, Data, and Information Service (NESDIS) is currently operating GOES-15 and GOES-13. The design of the GOES series is now heading to the 4 th generation. GOES-R, as a representative of the new generation of the GOES series, is scheduled to be launched in 2015 with higher spatial and temporal resolution images and full-time soundings. These frequent observations provided by GOES Image make them attractive for deriving information on the diurnal land surface temperature (LST) cycle and diurnal temperature range (DTR). These parameters are of great value for research on the Earth's diurnal variability and climate change. Accurate derivation of satellite-based LSTs from thermal infrared data has long been an interesting and challenging research area. To better support the research on climate change, the generation of consistent GOES LST products for both GOES-East and GOES-West from operational dataset as well as historical archive is in great demand. The derivation of GOES LST products and the evaluation of proposed retrieval methods are two major objectives of this study. Literature relevant to satellite-based LST retrieval techniques was reviewed. Specifically, the evolution of two LST algorithm families and LST retrieval methods for geostationary satellites were summarized in this dissertation. Literature relevant to the evaluation of satellite-based LSTs was also reviewed. All the existing methods are a valuable reference to develop the GOES LST product. The primary objective of this dissertation is the development of models for deriving consistent GOES LSTs with high spatial and high temporal coverage. Proper LST retrieval algorithms were studied

  8. Analysing the Effects of Different Land Cover Types on Land Surface Temperature Using Satellite Data

    Science.gov (United States)

    Şekertekin, A.; Kutoglu, Ş. H.; Kaya, S.; Marangoz, A. M.

    2015-12-01

    Monitoring Land Surface Temperature (LST) via remote sensing images is one of the most important contributions to climatology. LST is an important parameter governing the energy balance on the Earth and it also helps us to understand the behavior of urban heat islands. There are lots of algorithms to obtain LST by remote sensing techniques. The most commonly used algorithms are split-window algorithm, temperature/emissivity separation method, mono-window algorithm and single channel method. In this research, mono window algorithm was implemented to Landsat 5 TM image acquired on 28.08.2011. Besides, meteorological data such as humidity and temperature are used in the algorithm. Moreover, high resolution Geoeye-1 and Worldview-2 images acquired on 29.08.2011 and 12.07.2013 respectively were used to investigate the relationships between LST and land cover type. As a result of the analyses, area with vegetation cover has approximately 5 ºC lower temperatures than the city center and arid land., LST values change about 10 ºC in the city center because of different surface properties such as reinforced concrete construction, green zones and sandbank. The temperature around some places in thermal power plant region (ÇATES and ZETES) Çatalağzı, is about 5 ºC higher than city center. Sandbank and agricultural areas have highest temperature due to the land cover structure.

  9. ANALYSING THE EFFECTS OF DIFFERENT LAND COVER TYPES ON LAND SURFACE TEMPERATURE USING SATELLITE DATA

    Directory of Open Access Journals (Sweden)

    A. Şekertekin

    2015-12-01

    Full Text Available Monitoring Land Surface Temperature (LST via remote sensing images is one of the most important contributions to climatology. LST is an important parameter governing the energy balance on the Earth and it also helps us to understand the behavior of urban heat islands. There are lots of algorithms to obtain LST by remote sensing techniques. The most commonly used algorithms are split-window algorithm, temperature/emissivity separation method, mono-window algorithm and single channel method. In this research, mono window algorithm was implemented to Landsat 5 TM image acquired on 28.08.2011. Besides, meteorological data such as humidity and temperature are used in the algorithm. Moreover, high resolution Geoeye-1 and Worldview-2 images acquired on 29.08.2011 and 12.07.2013 respectively were used to investigate the relationships between LST and land cover type. As a result of the analyses, area with vegetation cover has approximately 5 ºC lower temperatures than the city center and arid land., LST values change about 10 ºC in the city center because of different surface properties such as reinforced concrete construction, green zones and sandbank. The temperature around some places in thermal power plant region (ÇATES and ZETES Çatalağzı, is about 5 ºC higher than city center. Sandbank and agricultural areas have highest temperature due to the land cover structure.

  10. Estimation of Land Surface Temperature under Cloudy Skies Using Combined Diurnal Solar Radiation and Surface Temperature Evolution

    Directory of Open Access Journals (Sweden)

    Xiaoyu Zhang

    2015-01-01

    Full Text Available Land surface temperature (LST is a key parameter in the interaction of the land-atmosphere system. However, clouds affect the retrieval of LST data from thermal-infrared remote sensing data. Thus, it is important to determine a method for estimating LSTs at times when the sky is overcast. Based on a one-dimensional heat transfer equation and on the evolution of daily temperatures and net shortwave solar radiation (NSSR, a new method for estimating LSTs under cloudy skies (Tcloud from diurnal NSSR and surface temperatures is proposed. Validation is performed against in situ measurements that were obtained at the ChangWu ecosystem experimental station in China. The results show that the root-mean-square error (RMSE between the actual and estimated LSTs is as large as 1.23 K for cloudy data. A sensitivity analysis to the errors in the estimated LST under clear skies (Tclear and in the estimated NSSR reveals that the RMSE of the obtained Tcloud is less than 1.5 K after adding a 0.5 K bias to the actual Tclear and 10 percent NSSR errors to the actual NSSR. Tcloud is estimated by the proposed method using Tclear and NSSR products of MSG-SEVIRI for southern Europe. The results indicate that the new algorithm is practical for retrieving the LST under cloudy sky conditions, although some uncertainty exists. Notably, the approach can only be used during the daytime due to the assumption of the variation in LST caused by variations in insolation. Further, if there are less than six Tclear observations on any given day, the method cannot be used.

  11. Implications of atmospheric conditions for analysis of surface temperature variability derived from landscape-scale thermography

    Science.gov (United States)

    Hammerle, Albin; Meier, Fred; Heinl, Michael; Egger, Angelika; Leitinger, Georg

    2016-08-01

    Thermal infrared (TIR) cameras perfectly bridge the gap between (i) on-site measurements of land surface temperature (LST) providing high temporal resolution at the cost of low spatial coverage and (ii) remotely sensed data from satellites that provide high spatial coverage at relatively low spatio-temporal resolution. While LST data from satellite (LSTsat) and airborne platforms are routinely corrected for atmospheric effects, such corrections are barely applied for LST from ground-based TIR imagery (using TIR cameras; LSTcam). We show the consequences of neglecting atmospheric effects on LSTcam of different vegetated surfaces at landscape scale. We compare LST measured from different platforms, focusing on the comparison of LST data from on-site radiometry (LSTosr) and LSTcam using a commercially available TIR camera in the region of Bozen/Bolzano (Italy). Given a digital elevation model and measured vertical air temperature profiles, we developed a multiple linear regression model to correct LSTcam data for atmospheric influences. We could show the distinct effect of atmospheric conditions and related radiative processes along the measurement path on LSTcam, proving the necessity to correct LSTcam data on landscape scale, despite their relatively low measurement distances compared to remotely sensed data. Corrected LSTcam data revealed the dampening effect of the atmosphere, especially at high temperature differences between the atmosphere and the vegetated surface. Not correcting for these effects leads to erroneous LST estimates, in particular to an underestimation of the heterogeneity in LST, both in time and space. In the most pronounced case, we found a temperature range extension of almost 10 K.

  12. Implications of atmospheric conditions for analysis of surface temperature variability derived from landscape-scale thermography.

    Science.gov (United States)

    Hammerle, Albin; Meier, Fred; Heinl, Michael; Egger, Angelika; Leitinger, Georg

    2017-04-01

    Thermal infrared (TIR) cameras perfectly bridge the gap between (i) on-site measurements of land surface temperature (LST) providing high temporal resolution at the cost of low spatial coverage and (ii) remotely sensed data from satellites that provide high spatial coverage at relatively low spatio-temporal resolution. While LST data from satellite (LSTsat) and airborne platforms are routinely corrected for atmospheric effects, such corrections are barely applied for LST from ground-based TIR imagery (using TIR cameras; LSTcam). We show the consequences of neglecting atmospheric effects on LSTcam of different vegetated surfaces at landscape scale. We compare LST measured from different platforms, focusing on the comparison of LST data from on-site radiometry (LSTosr) and LSTcam using a commercially available TIR camera in the region of Bozen/Bolzano (Italy). Given a digital elevation model and measured vertical air temperature profiles, we developed a multiple linear regression model to correct LSTcam data for atmospheric influences. We could show the distinct effect of atmospheric conditions and related radiative processes along the measurement path on LSTcam, proving the necessity to correct LSTcam data on landscape scale, despite their relatively low measurement distances compared to remotely sensed data. Corrected LSTcam data revealed the dampening effect of the atmosphere, especially at high temperature differences between the atmosphere and the vegetated surface. Not correcting for these effects leads to erroneous LST estimates, in particular to an underestimation of the heterogeneity in LST, both in time and space. In the most pronounced case, we found a temperature range extension of almost 10 K.

  13. Trends of urban surface temperature and heat island characteristics in the Mediterranean

    Science.gov (United States)

    Benas, Nikolaos; Chrysoulakis, Nektarios; Cartalis, Constantinos

    2016-09-01

    Urban air temperature studies usually focus on the urban canopy heat island phenomenon, whereby the city center experiences higher near surface air temperatures compared to its surrounding non-urban areas. The Land Surface Temperature (LST) is used instead of urban air temperature to identify the Surface Urban Heat Island (SUHI). In this study, the nighttime LST and SUHI characteristics and trends in the seventeen largest Mediterranean cities were investigated, by analyzing satellite observations for the period 2001-2012. SUHI averages and trends were based on an innovative approach of comparing urban pixels to randomly selected non-urban pixels, which carries the potential to better standardize satellite-derived SUHI estimations. A positive trend for both LST and SUHI for the majority of the examined cities was documented. Furthermore, a 0.1 °C decade-1 increase in urban LST corresponded to an increase in SUHI by about 0.04 °C decade-1. A longitudinal differentiation was found in the urban LST trends, with higher positive values appearing in the eastern Mediterranean. Examination of urban infrastructure and development factors during the same period revealed correlations with SUHI trends, which can be used to explain differences among cities. However, the majority of the cities examined show considerably increased trends in terms of the enhancement of SUHI. These findings are considered important so as to promote sustainable urbanization, as well as to support the development of heat island adaptation and mitigation plans in the Mediterranean.

  14. A Physically Constrained Calibration Database for Land Surface Temperature Using Infrared Retrieval Algorithms

    Directory of Open Access Journals (Sweden)

    João P. A. Martins

    2016-09-01

    Full Text Available Land surface temperature (LST is routinely retrieved from remote sensing instruments using semi-empirical relationships between top of atmosphere (TOA radiances and LST, using ancillary data such as total column water vapor or emissivity. These algorithms are calibrated using a set of forward radiative transfer simulations that return the TOA radiances given the LST and the thermodynamic profiles. The simulations are done in order to cover a wide range of surface and atmospheric conditions and viewing geometries. This study analyzes calibration strategies while considering some of the most critical factors that need to be taken into account when building a calibration dataset, covering the full dynamic range of relevant variables. A sensitivity analysis of split-windows and single channel algorithms revealed that selecting a set of atmospheric profiles that spans the full range of surface temperatures and total column water vapor combinations that are physically possible seems beneficial for the quality of the regression model. However, the calibration is extremely sensitive to the low-level structure of the atmosphere, indicating that the presence of atmospheric boundary layer features such as temperature inversions or strong vertical gradients of thermodynamic properties may affect LST retrievals in a non-trivial way. This article describes the criteria established in the EUMETSAT Land Surface Analysis—Satellite Application Facility to calibrate its LST algorithms, applied both for current and forthcoming sensors.

  15. Towards a protocol for validating satellite-based Land Surface Temperature: Application to AATSR data

    Science.gov (United States)

    Ghent, Darren; Schneider, Philipp; Remedios, John

    2013-04-01

    Land surface temperature (LST) retrieval accuracy can be challenging as a result of emissivity variability and atmospheric effects. Surface emissivities can be highly variable owing to the heterogeneity of the land; a problem which is amplified in regions of high topographic variance or for larger viewing angles. Atmospheric effects caused by the presence of aerosols and by water vapour absorption can give a bias to the underlying LST. Combined, atmospheric effects and emissivity variability can result in retrieval errors of several degrees. If though these are appropriately handled satellite-derived LST products can be used to improve our ability to monitor and to understand land surface and climate change processes, such as desertification, urbanization, deforestation and land/atmosphere coupling. Here we present validation of an improved LST data record from the Advanced Along-Track Scanning Radiometer (AATSR) and illustrate the improvements in accuracy and precision compared with the standard ESA LST product. Validation is a critical part of developing any satellite product, although over the land heterogeneity ensures this is a challenging undertaking. A substantial amount of previous effort has gone into the area of structuring and standardizing calibration and validation approaches within the field of Earth Observation. However, no unified approach for accomplishing this for LST has yet to be practised by the LST community. Recent work has attempted to address this situation with the development of a protocol for validating LST (Schneider et al., 2012) under the auspices of ESA and the support of the wider LST community. We report here on a first application of this protocol to satellite LST data. The approach can briefly be summarised thus: in situ validation is performed where ground-based observations are available - being predominantly homogeneous sites; heterogeneous pixels are validated by way of established radiometric-based techniques (Wan and Li

  16. A novel interpolation method for MODIS land surface temperature data on the Tibetan Plateau

    Science.gov (United States)

    Yu, Wenjun; Wu, Tonghua; Nan, Zhuotong; Zhao, Lin; Wang, Zhiwei

    2014-11-01

    MODIS satellites provide continuous global observations on land surface temperature. It is more important in data-sparse area, such as on the Tibetan Plateau (TP) with very few meteorological stations. Images with severe data missing or poor quality pixels were often found in MODIS LST products, which mostly were caused by the influences of clouds. The traditional geo-statistic methods, including ordinary Kriging and inverse distance weighted (IDW) methods, cannot well interpolate missing-data pixels for a large area. Assuming that the changes of LST at one location would be similar with that at the locations with similar features, a novel method was proposed to interpolate the missing-data pixels by making use of other pixels with the most similar features. MODIS/Terra LST covering TP in 2005 were used as experimental data, and pixels with cloud coverage, average emissivity error greater than 0.04, and average LST error greater than 2K were identified as missing-data pixels. The images with less than 10% missing-data pixels were selected as reference images, in which the missing-data pixels were interpolated with IDW. Distances for different land surface features in images, such as DEM, slope, NDVI and LST, from the interpolating pixel to the other pixels with known LST were calculated. Similar pixels are identified as the distances less than a given threshold. Relationship of LST for those similar pixels was regressed, and was applied to estimate LSTs for the missing pixels. Compared with IDW and Kriging, the proposed method could interpolate the MODIS LST much better on the Tibetan Plateau.

  17. Multi-Temporal Evaluation of Soil Moisture and Land Surface Temperature Dynamics Using in Situ and Satellite Observations

    Directory of Open Access Journals (Sweden)

    Miriam Pablos

    2016-07-01

    Full Text Available Soil moisture (SM is an important component of the Earth’s surface water balance and by extension the energy balance, regulating the land surface temperature (LST and evapotranspiration (ET. Nowadays, there are two missions dedicated to monitoring the Earth’s surface SM using L-band radiometers: ESA’s Soil Moisture and Ocean Salinity (SMOS and NASA’s Soil Moisture Active Passive (SMAP. LST is remotely sensed using thermal infrared (TIR sensors on-board satellites, such as NASA’s Terra/Aqua MODIS or ESA & EUMETSAT’s MSG SEVIRI. This study provides an assessment of SM and LST dynamics at daily and seasonal scales, using 4 years (2011–2014 of in situ and satellite observations over the central part of the river Duero basin in Spain. Specifically, the agreement of instantaneous SM with a variety of LST-derived parameters is analyzed to better understand the fundamental link of the SM–LST relationship through ET and thermal inertia. Ground-based SM and LST measurements from the REMEDHUS network are compared to SMOS SM and MODIS LST spaceborne observations. ET is obtained from the HidroMORE regional hydrological model. At the daily scale, a strong anticorrelation is observed between in situ SM and maximum LST (R ≈ − 0.6 to −0.8, and between SMOS SM and MODIS LST Terra/Aqua day (R ≈ − 0.7. At the seasonal scale, results show a stronger anticorrelation in autumn, spring and summer (in situ R ≈ − 0.5 to −0.7; satellite R ≈ − 0.4 to −0.7 indicating SM–LST coupling, than in winter (in situ R ≈ +0.3; satellite R ≈ − 0.3 indicating SM–LST decoupling. These different behaviors evidence changes from water-limited to energy-limited moisture flux across seasons, which are confirmed by the observed ET evolution. In water-limited periods, SM is extracted from the soil through ET until critical SM is reached. A method to estimate the soil critical SM is proposed. For REMEDHUS, the critical SM is estimated to be ∼0

  18. Effect of land cover and green space on land surface temperature of a fast growing economic region in Malaysia

    Science.gov (United States)

    Sheikhi, A.; Kanniah, K. D.; Ho, C. H.

    2015-10-01

    Green space must be increased in the development of new cities as green space can moderate temperature in the cities. In this study we estimated the land surface temperature (LST) and established relationships between LST and land cover and various vegetation and urban surface indices in the Iskandar Malaysia (IM) region. IM is one of the emerging economic gateways of Malaysia, and is envisaged to transform into a metropolis by 2025. This change may cause increased temperature in IM and therefore we conducted a study by using Landsat 5 image covering the study region (2,217 km2) to estimate LST, classify different land covers and calculate spectral indices. Results show that urban surface had highest LST (24.49 °C) and the lowest temperature was recorded in, forest, rubber and water bodies ( 20.69 to 21.02°C). Oil palm plantations showed intermediate mean LST values with 21.65 °C. We further investigated the relationship between vegetation and build up densities with temperature. We extracted 1000 collocated pure pixels of Normalized Difference Vegetation Index (NDVI), Normalized Difference Water Index (NDWI), Normalized Difference Built-up Index (NDBI), Urban Index (UI) and LST in the study area. Results show a strong and significant negative correlation with (R2= -0.74 and -0.79) respectively between NDVI, NDWI and LST . Meanwhile a strong positive correlation (R2=0.8 and 0.86) exists between NDBI, UI and LST. These results show the importance of increasing green cover in urban environment to combat any adverse effects of climate change.

  19. A radiance-based method for estimating uncertainties in the Atmospheric Infrared Sounder (AIRS) land surface temperature product

    Science.gov (United States)

    Hulley, Glynn C.; Hook, Simon J.

    2012-10-01

    Land Surface Temperature (LST) has been identified by NASA and other international organizations as an important Earth System Data Record (ESDR). An ESDR is defined as a long-term, well calibrated and validated data set. Identifying uncertainties in LST products with coarse spatial resolutions (>10 km) such as those from hyperspectral infrared sounders is notoriously difficult due to the challenges of making reliable in situ measurements representative of the spatial scales of the output products. In this study we utilize a Radiance-based (R-based) LST method for estimating uncertainties in the Atmospheric Infrared Sounder (AIRS) v5 LST product. The R-based method provides estimates of the true LST using a radiative closure simulation without the need for in situ measurements, and requires input air temperature, relative humidity profiles and emissivity data. The R-based method was employed at three validation sites over the Namib Desert, Gran Desierto, and Redwood National Park for all AIRS observations from 2002 to 2010. Results showed daytime LST root-mean square errors (RMSE) of 2-3 K at the Namib and Desierto sites, and 1.5 K at the Redwood site. Nighttime LST RMSEs at the two desert sites were a factor of two less when compared to daytime results. Positive daytime LST biases were found at each site due to an underestimation of the daytime AIRS v5 longwave spectral emissivity, while the reverse occurred at nighttime. In the AIRS v6 product (release 2012), LST biases and RMSEs will be reduced significantly due to improved methodologies for the surface retrieval and emissivity first guess.

  20. Comparing and Combining Remotely Sensed Land Surface Temperature Products for Improved Hydrological Applications

    Directory of Open Access Journals (Sweden)

    Robert M. Parinussa

    2016-02-01

    Full Text Available Land surface temperature (LST is an important variable that provides a valuable connection between the energy and water budget and is strongly linked to land surface hydrology. Space-borne remote sensing provides a consistent means for regularly observing LST using thermal infrared (TIR and passive microwave observations each with unique strengths and weaknesses. The spatial resolution of TIR based LST observations is around 1 km, a major advantage when compared to passive microwave observations (around 10 km. However, a major advantage of passive microwaves is their cloud penetrating capability making them all-weather sensors whereas TIR observations are routinely masked under the presence of clouds and aerosols. In this study, a relatively simple combination approach that benefits from the cloud penetrating capacity of passive microwave sensors was proposed. In the first step, TIR and passive microwave LST products were compared over Australia for both anomalies and raw timeseries. A very high agreement was shown over the vast majority of the country with R2 typically ranging from 0.50 to 0.75 for the anomalies and from 0.80 to 1.00 for the raw timeseries. Then, the scalability of the passive microwave based LST product was examined and a pixel based merging approach through linear scaling was proposed. The individual and merged LST products were further compared against independent LST from the re-analysis model outputs. This comparison revealed that the TIR based LST product agrees best with the re-analysis data (R2 0.26 for anomalies and R2 0.76 for raw data, followed by the passive microwave LST product (R2 0.16 for anomalies and R2 0.66 for raw data and the combined LST product (R2 0.18 for anomalies and R2 0.62 for raw data. It should be noted that the drop in performance comes with an increased revisit frequency of approximately 20% compared to the revised frequency of the TIR alone. Additionally, this comparison against re

  1. Using Landsat, MODIS, and a Biophysical Model to Evaluate LST in Urban Centers

    Directory of Open Access Journals (Sweden)

    Mohammad Z. Al-Hamdan

    2016-11-01

    Full Text Available In this paper, we assessed and compared land surface temperature (LST in urban centers using data from Landsat, MODIS, and the Simple Biosphere model (SiB2. We also evaluated the sensitivity of the model’s LST to different land cover types, fractions (percentages, and emissivities compared to reference points derived from Landsat thermal data. This was demonstrated in three climatologically- and morphologically-different cities of Atlanta, GA, New York, NY, and Washington, DC. Our results showed that in these cities SiB2 was sensitive to both the emissivity and the land cover type and fraction, but much more sensitive to the latter. The practical implications of these results are rather significant since they imply that the SiB2 model can be used to run different scenarios for evaluating urban heat island (UHI mitigation strategies. This study also showed that using detailed emissivities per land cover type and fractions from Landsat-derived data caused a convergence of the model results towards the Landsat-derived LST for most of the studied cases. This study also showed that SiB2 LSTs are closer in magnitude to Landsat-derived LSTs than MODIS-derived LSTs. It is important, however, to emphasize that both Landsat and MODIS LSTs are not direct observations and, as such, do not represent a ground truth. More studies will be needed to compare these results to in situ LST data and provide further validation.

  2. Effect of land use/cover change on land surface temperatures - The Nile Delta, Egypt

    Science.gov (United States)

    Hereher, Mohamed E.

    2017-02-01

    In this study remote sensing techniques were employed to investigate the impact of land use/cover change on land surface temperatures (LST) for a highly dynamic landscape, i.e. the Nile Delta. Land use change was determined from analyzing a 15 years of bi-monthly normalized difference vegetation index (NDVI) dataset acquired from the Moderate Resolution Imaging Spectroradiometer (MODIS) Terra satellite along with a synchronized 13 years of bi-monthly LST dataset retrieved from MODIS Aqua satellite. Time series analysis for NDVI and LST data was carried out at selected locations experiencing land use change. Mean LST change was determined for each location before and after the land use change. Results indicate that NDVI composite data for 15 years proved sufficient for delineating land use change. Significant spatial changes include the transformation from agriculture to urban land, which increased the LST by 1.7 °C during the 13 years and the transformation of bare land to agriculture, which decreased the LST by 0.52 °C for the same period. Due to the explosive population growth in the Nile Delta, urban encroachment upon agricultural land could, hence, promote a prolonged regional warming by modifying the micro-climate and other climate-related phenomena.

  3. Heat waves measured with MODIS land surface temperature data predict changes in avian community structure

    Science.gov (United States)

    Thomas P. Albright; Anna M. Pidgeon; Chadwick D. Rittenhouse; Murray K. Clayton; Curtis H. Flather; Patrick D. Culbert; Volker C. Radeloff

    2011-01-01

    Heat waves are expected to become more frequent and severe as climate changes, with unknown consequences for biodiversity. We sought to identify ecologically-relevant broad-scale indicators of heat waves based on MODIS land surface temperature (LST) and interpolated air temperature data and assess their associations with avian community structure. Specifically, we...

  4. Comparison of Satellite-Derived and In-Situ Observations of Ice and Snow Surface Temperatures over Greenland

    Science.gov (United States)

    Hall, Dorothy K.; Box, Jason E.; Casey, Kimberly A.; Hook, Simon J.; Shuman, Christopher A.; Steffen, Konrad

    2008-01-01

    The most practical way to get a spatially broad and continuous measurements of the surface temperature in the data-sparse cryosphere is by satellite remote sensing. The uncertainties in satellite-derived LSTs must be understood to develop internally-consistent decade-scale land-surface temperature (LST) records needed for climate studies. In this work we assess satellite-derived "clear-sky" LST products from the Moderate Resolution Imaging Spectroradiometer (MODIS) and the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), and LSTs derived from the Enhanced Thematic Mapper Plus (ETM+) over snow and ice on Greenland. When possible, we compare satellite-derived LSTs with in-situ air-temperature observations from Greenland Climate Network (GC-Net) automatic-weather stations (AWS). We find that MODIS, ASTER and ETM+ provide reliable and consistent LSTs under clear-sky conditions and relatively-flat terrain over snow and ice targets over a range of temperatures from -40 to 0 C. The satellite-derived LSTs agree within a relative RMS uncertainty of approx.0.5 C. The good agreement among the LSTs derived from the various satellite instruments is especially notable since different spectral channels and different retrieval algorithms are used to calculate LST from the raw satellite data. The AWS record in-situ data at a "point" while the satellite instruments record data over an area varying in size from: 57 X 57 m (ETM+), 90 X 90 m (ASTER), or to 1 X 1 km (MODIS). Surface topography and other factors contribute to variability of LST within a pixel, thus the AWS measurements may not be representative of the LST of the pixel. Without more information on the local spatial patterns of LST, the AWS LST cannot be considered valid ground truth for the satellite measurements, with RMS uncertainty approx.2 C. Despite the relatively large AWS-derived uncertainty, we find LST data are characterized by high accuracy but have uncertain absolute precision.

  5. A framework for global diurnally-resolved observations of Land Surface Temperature

    Science.gov (United States)

    Ghent, Darren; Remedios, John

    2014-05-01

    Land surface temperature (LST) is the radiative skin temperature of the land, and is one of the key parameters in the physics of land-surface processes on regional and global scales. Being a key boundary condition in land surface models, which determine the surface to atmosphere fluxes of heat, water and carbon; thus influencing cloud cover, precipitation and atmospheric chemistry predictions within Global models, the requirement for global diurnal observations of LST is well founded. Earth Observation satellites offer an opportunity to obtain global coverage of LST, with the appropriate exploitation of data from multiple instruments providing a capacity to resolve the diurnal cycle on a global scale. Here we present a framework for the production of global, diurnally resolved, data sets for LST which is a key request from users of LST data. We will show how the sampling of both geostationary and low earth orbit data sets could conceptually be employed to build combined, multi-sensor, pole-to-pole data sets. Although global averages already exist for individual instruments and merging of geostationary based LST is already being addressed operationally (Freitas, et al., 2013), there are still a number of important challenges to overcome. In this presentation, we will consider three of the issues still open in LST remote sensing: 1) the consistency amongst retrievals; 2) the clear-sky bias and its quantification; and 3) merging methods and the propagation of uncertainties. For example, the combined use of both geostationary earth orbit (GEO) and low earth orbit (LEO) data, and both infra-red and microwave data are relatively unexplored but are necessary to make the most progress. Hence this study will suggest what is state-of-the-art and how considerable advances can be made, accounting also for recent improvements in techniques and data quality. The GlobTemperature initiative under the Data User Element of ESA's 4th Earth Observation Envelope Programme (2013

  6. A protocol for validating Land Surface Temperature from Sentinel-3

    Science.gov (United States)

    Ghent, D.

    2015-12-01

    One of the main objectives of the Sentinel-3 mission is to measure sea- and land-surface temperature with high-end accuracy and reliability in support of environmental and climate monitoring in an operational context. Calibration and validation are thus key criteria for operationalization within the framework of the Sentinel-3 Mission Performance Centre (S3MPC).Land surface temperature (LST) has a long heritage of satellite observations which have facilitated our understanding of land surface and climate change processes, such as desertification, urbanization, deforestation and land/atmosphere coupling. These observations have been acquired from a variety of satellite instruments on platforms in both low-earth orbit and in geostationary orbit. Retrieval accuracy can be a challenge though; surface emissivities can be highly variable owing to the heterogeneity of the land, and atmospheric effects caused by the presence of aerosols and by water vapour absorption can give a bias to the underlying LST. As such, a rigorous validation is critical in order to assess the quality of the data and the associated uncertainties. The Sentinel-3 Cal-Val Plan for evaluating the level-2 SL_2_LST product builds on an established validation protocol for satellite-based LST. This set of guidelines provides a standardized framework for structuring LST validation activities, and is rapidly gaining international recognition. The protocol introduces a four-pronged approach which can be summarised thus: i) in situ validation where ground-based observations are available; ii) radiance-based validation over sites that are homogeneous in emissivity; iii) intercomparison with retrievals from other satellite sensors; iv) time-series analysis to identify artefacts on an interannual time-scale. This multi-dimensional approach is a necessary requirement for assessing the performance of the LST algorithm for SLSTR which is designed around biome-based coefficients, thus emphasizing the importance of

  7. Modelling Angular Dependencies in Land Surface Temperatures From the SEVIRI Instrument onboard the Geostationary Meteosat Second Generation Satellites

    DEFF Research Database (Denmark)

    Rasmussen, Mads Olander; Pinheiro, AC; Proud, Simon Richard

    2010-01-01

    Satellite-based estimates of land surface temperature (LST) are widely applied as an input to models. A model output is often very sensitive to error in the input data, and high-quality inputs are therefore essential. One of the main sources of errors in LST estimates is the dependence on vegetat......Satellite-based estimates of land surface temperature (LST) are widely applied as an input to models. A model output is often very sensitive to error in the input data, and high-quality inputs are therefore essential. One of the main sources of errors in LST estimates is the dependence...... on vegetation structure and viewing and illumination geometry. Despite this, these effects are not considered in current operational LST products from neither polar-orbiting nor geostationary satellites. In this paper, we simulate the angular dependence that can be expected when estimating LST with the viewing...... by different land covers. The results show that the sun-target-sensor geometry plays a significant role in the estimated temperature, with variations strictly due to the angular configuration of more than ±3°C in some cases. On the continental scale, the average error is small except in hot-spot conditions...

  8. Comparing Methods for Land Surface Temperature Retrieval over Heterogeneous Land Cover Using Landsat-5 TM Thermal Infrared Data

    Science.gov (United States)

    Windahl, E.; de Beurs, K.

    2014-12-01

    Among other applications, remotely sensed land surface temperature (LST) has become critical for monitoring the surface urban heat island (SUHI) effect in cities across the world. While daily MODIS thermal infrared data is invaluable for examining changes in LST over time, the large 1 km spatial resolution makes studying the spatial patterns of LST in a heterogeneous urban environment difficult. The 120 m spatial resolution of Landsat 4-5 TM, as well the archive of data stretching back to 1982, make Landsat 4-5 TM sensors valuable resources for thermal data, especially in urban areas. However, the difficulty accurately correcting for atmospheric effects with only one thermal band, as well as the necessity for a priori knowledge of land surface emissivity (LSE), mean it is underutilized. Research to determine best practices for deriving LST from Landsat TM data given homogenous, usually vegetated land cover is relatively extensive; however, the accuracy of these methods given heterogeneous land cover is less well known, especially given Land Surface Emissivity (LSE) calculations that often rely heavily on NDVI. In order to determine the best methodology for measuring LST across heterogeneous land cover in the central United States, this study derives LST from Landsat 5 TM band 6 for Oklahoma City and the surrounding countryside on a fall and a spring date using three different methods: no atmospheric correction, the radiative transfer equation, and the mono-window algorithm. With all three methods, the common NDVI-based approach for estimating LSE is used; a fourth LST calculation with no atmospheric correction and an assumed emissivity of one is therefore included as contrast. Using regression analysis, these four LST measurements are compared to air temperatures recorded concurrently by approximately 40 Oklahoma Mesonet stations across the study area, and results are broken down by land cover type to explore potential biases or variations in accuracy.

  9. Letter to the EditorRetrieval of land surface temperature from combined AVHRR data

    Directory of Open Access Journals (Sweden)

    H. Fischer

    Full Text Available Accurate retrievals of land surface temperature (LST from space are of high interest for studies of land surface processes. Here, an operationally applicable method to retrieve LST from NOAA/AVHRR data is proposed, which combines a split-window technique (SWT for atmospheric correction with a Normalised Difference Vegetation Index threshold method for the retrieval of land surface emissivity. Preliminary results of LST retrievals with this "combined method" are in good agreement with ground truth measurements for bare soil and wheat crops. The results are also compared with results from the same SWT but using emissivities from laboratory measurements.Key words. Meteorology and atmospheric dynamics (radiation processes; instruments and techniques – Radio science (remote sensing

  10. Innovative approach to retrieve land surface emissivity and land surface temperature in areas of highly dynamic emissivity changes by using thermal infrared data

    Science.gov (United States)

    Heinemann, Sascha; Muro, Javier; Burkart, Andreas; Schultz, Johannes; Thonfeld, Frank; Menz, Gunter

    2016-04-01

    The land surface temperature (LST) is an extremely significant parameter in order to understand the processes of energetic interactions between the Earth's surface and the atmosphere. This knowledge is significant for various environmental research questions, particularly with regard to climate change. The current challenge is to reduce the higher deviations during daytime especially for bare areas with a maximum of 5.7 Kelvin. These temperature differences are time and vegetation cover dependent. This study shows an innovative approach to retrieve land surface emissivity (LSE) and LST by using thermal infrared (TIR) data from satellite sensors, such as SEVIRI and AATSR. So far there are no methods to derive LSE/LST particularly in areas of highly dynamic emissivity changes. Therefore especially for regions with large surface temperature amplitude in the diurnal cycle such as bare and uneven soil surfaces but also for regions with seasonal changes in vegetation cover including various surface areas such as grassland, mixed forests or agricultural land different methods were investigated to identify the most appropriate one. The LSE is retrieved by using the day/night Temperature-Independent Spectral Indices (TISI) method, while the Generalised Split-Window (GSW) method is used to retrieve the LST. Nevertheless different GSW algorithms show that equal LSEs lead to large LST differences. For bare surfaces during daytime the difference is about 6 Kelvin. Additionally LSE is also measured using a NDVI-based threshold method (NDVITHM) to distinguish between soil, dense vegetation cover and pixel composed of soil and vegetation. The data used for this analysis were derived from MODIS TIR. The analysis is implemented with IDL and an intercomparison is performed to determine the most effective methods. To compensate temperature differences between derived and ground truth data appropriate correction terms, by comparing derived LSE/LST data with ground-based measurements

  11. Determining Land Surface Temperature Relations with Land Use-Land Cover and Air Pollution

    Science.gov (United States)

    Kahya, Ceyhan; Bektas Balcik, Filiz; Burak Oztaner, Yasar; Guney, Burcu

    2016-04-01

    Rapid population growth in conjunction with unplanned urbanization, expansion, and encroachment into the limited agricultural fields and green areas have negative impacts on vegetated areas. Land Surface Temperature (LST), Urban Heat Islands (UHI) and air pollution are the most important environmental problems that the extensive part of the world suffers from. The main objective of this research is to investigate the relationship between LST, air pollution and Land Use-Land Cover (LULC) in Istanbul, using Landsat 8 OLI satellite image. Mono-window algorithm is used to compute LST from Landsat 8 TIR data. In order to determine the air pollution, in-situ measurements of particulate matter (PM10) of the same day as the Landsat 8 OLI satellite image are obtained. The results of this data are interpolated using the Inverse Distance Weighted (IDW) method and LULC categories of Istanbul were determined by using remote sensing indices. Error matrix was created for accuracy assessment. The relationship between LST, air pollution and LULC categories are determined by using regression analysis method. Keywords: Land Surface Temperature (LST), air pollution, Land Use-Land Cover (LULC), Istanbul

  12. A Useful Tool for Atmospheric Correction and Surface Temperature Estimation of Landsat Infrared Thermal Data

    Science.gov (United States)

    Rivalland, Vincent; Tardy, Benjamin; Huc, Mireille; Hagolle, Olivier; Marcq, Sébastien; Boulet, Gilles

    2016-04-01

    Land Surface temperature (LST) is a critical variable for studying the energy and water budgets at the Earth surface, and is a key component of many aspects of climate research and services. The Landsat program jointly carried out by NASA and USGS has been providing thermal infrared data for 40 years, but no associated LST product has been yet routinely proposed to community. To derive LST values, radiances measured at sensor-level need to be corrected for the atmospheric absorption, the atmospheric emission and the surface emissivity effect. Until now, existing LST products have been generated with multi channel methods such as the Temperature/Emissivity Separation (TES) adapted to ASTER data or the generalized split-window algorithm adapted to MODIS multispectral data. Those approaches are ill-adapted to the Landsat mono-window data specificity. The atmospheric correction methodology usually used for Landsat data requires detailed information about the state of the atmosphere. This information may be obtained from radio-sounding or model atmospheric reanalysis and is supplied to a radiative transfer model in order to estimate atmospheric parameters for a given coordinate. In this work, we present a new automatic tool dedicated to Landsat thermal data correction which improves the common atmospheric correction methodology by introducing the spatial dimension in the process. The python tool developed during this study, named LANDARTs for LANDsat Automatic Retrieval of surface Temperature, is fully automatic and provides atmospheric corrections for a whole Landsat tile. Vertical atmospheric conditions are downloaded from the ERA Interim dataset from ECMWF meteorological organization which provides them at 0.125 degrees resolution, at a global scale and with a 6-hour-time step. The atmospheric correction parameters are estimated on the atmospheric grid using the commercial software MODTRAN, then interpolated to 30m resolution. We detail the processing steps

  13. Urban Surface Temperature Time Series Estimation at the Local Scale by Spatial-Spectral Unmixing of Satellite Observations

    Directory of Open Access Journals (Sweden)

    Zina Mitraka

    2015-04-01

    Full Text Available The study of urban climate requires frequent and accurate monitoring of land surface temperature (LST, at the local scale. Since currently, no space-borne sensor provides frequent thermal infrared imagery at high spatial resolution, the scientific community has focused on synergistic methods for retrieving LST that can be suitable for urban studies. Synergistic methods that combine the spatial structure of visible and near-infrared observations with the more frequent, but low-resolution surface temperature patterns derived by thermal infrared imagery provide excellent means for obtaining frequent LST estimates at the local scale in cities. In this study, a new approach based on spatial-spectral unmixing techniques was developed for improving the spatial resolution of thermal infrared observations and the subsequent LST estimation. The method was applied to an urban area in Crete, Greece, for the time period of one year. The results were evaluated against independent high-resolution LST datasets and found to be very promising, with RMSE less than 2 K in all cases. The developed approach has therefore a high potential to be operationally used in the near future, exploiting the Copernicus Sentinel (2 and 3 observations, to provide high spatio-temporal resolution LST estimates in cities.

  14. A New Global Climatology of Annual Land Surface Temperature

    Directory of Open Access Journals (Sweden)

    Benjamin Bechtel

    2015-03-01

    Full Text Available Land surface temperature (LST is an important parameter in various fields including hydrology, climatology, and geophysics. Its derivation by thermal infrared remote sensing has long tradition but despite substantial progress there remain limited data availability and challenges like emissivity estimation, atmospheric correction, and cloud contamination. The annual temperature cycle (ATC is a promising approach to ease some of them. The basic idea to fit a model to the ATC and derive annual cycle parameters (ACP has been proposed before but so far not been tested on larger scale. In this study, a new global climatology of annual LST based on daily 1 km MODIS/Terra observations was processed and evaluated. The derived global parameters were robust and free of missing data due to clouds. They allow estimating LST patterns under largely cloud-free conditions at different scales for every day of year and further deliver a measure for its accuracy respectively variability. The parameters generally showed low redundancy and mostly reflected real surface conditions. Important influencing factors included climate, land cover, vegetation phenology, anthropogenic effects, and geology which enable numerous potential applications. The datasets will be available at the CliSAP Integrated Climate Data Center pending additional processing.

  15. Derivation of Land Surface Temperature for Landsat-8 TIRS Using a Split Window Algorithm

    Directory of Open Access Journals (Sweden)

    Offer Rozenstein

    2014-03-01

    Full Text Available Land surface temperature (LST is one of the most important variables measured by satellite remote sensing. Public domain data are available from the newly operational Landsat-8 Thermal Infrared Sensor (TIRS. This paper presents an adjustment of the split window algorithm (SWA for TIRS that uses atmospheric transmittance and land surface emissivity (LSE as inputs. Various alternatives for estimating these SWA inputs are reviewed, and a sensitivity analysis of the SWA to misestimating the input parameters is performed. The accuracy of the current development was assessed using simulated Modtran data. The root mean square error (RMSE of the simulated LST was calculated as 0.93 °C. This SWA development is leading to progress in the determination of LST by Landsat-8 TIRS.

  16. MODELLING THE RELATIONSHIP BETWEEN LAND SURFACE TEMPERATURE AND LANDSCAPE PATTERNS OF LAND USE LAND COVER CLASSIFICATION USING MULTI LINEAR REGRESSION MODELS

    Directory of Open Access Journals (Sweden)

    A. M. Bernales

    2016-06-01

    Full Text Available The threat of the ailments related to urbanization like heat stress is very prevalent. There are a lot of things that can be done to lessen the effect of urbanization to the surface temperature of the area like using green roofs or planting trees in the area. So land use really matters in both increasing and decreasing surface temperature. It is known that there is a relationship between land use land cover (LULC and land surface temperature (LST. Quantifying this relationship in terms of a mathematical model is very important so as to provide a way to predict LST based on the LULC alone. This study aims to examine the relationship between LST and LULC as well as to create a model that can predict LST using class-level spatial metrics from LULC. LST was derived from a Landsat 8 image and LULC classification was derived from LiDAR and Orthophoto datasets. Class-level spatial metrics were created in FRAGSTATS with the LULC and LST as inputs and these metrics were analysed using a statistical framework. Multi linear regression was done to create models that would predict LST for each class and it was found that the spatial metric “Effective mesh size” was a top predictor for LST in 6 out of 7 classes. The model created can still be refined by adding a temporal aspect by analysing the LST of another farming period (for rural areas and looking for common predictors between LSTs of these two different farming periods.

  17. Using microwave observations to estimate land surface temperature during cloudy conditions

    Science.gov (United States)

    Land surface temperature (LST), a key ingredient for physically-based retrieval algorithms of hydrological states and fluxes, remains a poorly constrained parameter for global scale studies. The main two observational methods to remotely measure T are based on thermal infrared (TIR) observations and...

  18. Use of satellite land surface temperatures in the EUSTACE global surface air temperature analysis

    Science.gov (United States)

    Ghent, D.; Good, E.; Rayner, N. A.

    2015-12-01

    EUSTACE (EU Surface Temperatures for All Corners of Earth) is a Horizon2020 project that will produce a spatially complete, near-surface air temperature (NSAT) analysis for the globe for every day since 1850. The analysis will be based on both satellite and in situ surface temperature observations over land, sea, ice and lakes, which will be combined using state-of-the-art statistical methods. The use of satellite data will enable the EUSTACE analysis to offer improved estimates of NSAT in regions that are poorly observed in situ, compared with existing in-situ based analyses. This presentation illustrates how satellite land surface temperature (LST) data - sourced from the European Space Agency (ESA) Data User Element (DUE) GlobTemperature project - will be used in EUSTACE. Satellite LSTs represent the temperature of the Earth's skin, which can differ from the corresponding NSAT by several degrees or more, particularly during the hottest part of the day. Therefore the first challenge is to develop an approach to estimate global NSAT from satellite observations. Two methods will be trialled in EUSTACE, both of which are summarised here: an established empirical regression-based approach for predicting NSAT from satellite data, and a new method whereby NSAT is calculated from LST and other parameters using a physics-based model. The second challenge is in estimating the uncertainties for the satellite NSAT estimates, which will determine how these data are used in the final blended satellite-in situ analysis. This is also important as a key component of EUSTACE is in delivering accurate uncertainty information to users. An overview of the methods to estimate the satellite NSATs is also included in this presentation.

  19. Diurnal and Seasonal Variation of Clear-Sky Land Surface Temperature of Several Representative Land Surface Types in China Retrieved by GMS-5

    Institute of Scientific and Technical Information of China (English)

    WANG Minyan; Lu Daren

    2006-01-01

    The retrieved results in this paper by GMS-5/VISSR thermal infrared data with single time/dual channel Split-Window Algorithm reveal the characteristics of diurnal and seasonal variation of clear-sky land surface temperature (LST) of several representative land surface types in China, including Tarim Basin, QinghaiTibetan Plateau, Hunshandake Sands, North China Plain, and South China. The seasonal variation of clear-sky LST in above areas varies distinctly for the different surface albedo, soil water content, and the extent of influence by solar radiation. The monthly average diurnal ranges of LST have two peaks and two valleys in one year. The characteristics of LST in most land of East Asia and that of sea surface temperature (SST) in the south of Taiwan Strait and the Yellow Sea are also analyzed as comparison. Tarim Basin and Hunshandake Sands have not only considerable LST diurnal cycle but also remarkable seasonal variation.In 2000, the maximum monthly average diurnal ranges of LST in both areas are over 30 K, and the annual range in Hunshadake Sands reaches 58.50 K. Seasonal variation of LST in the Qinghai-Tibetan Plateau is less than those in East Asia, Tarim Basin, and Hunshandake Sands. However, the maximum diurnal range exists in this area. The yearly average diurnal range is 28.05 K in the Qinghai-Tibetan Plateau in 2000. The characteristics of diurnal, seasonal, and annual variation from 1998 to 2000 are also shown in this research.All the results will be valuable to the research of climate change, radiation balance, and estimation for the change of land surface types.

  20. Moderate Resolution Imaging Spectroradiometer (MODIS) MOD21 Land Surface Temperature and Emissivity Algorithm Theoretical Basis Document

    Science.gov (United States)

    Hulley, G.; Malakar, N.; Hughes, T.; Islam, T.; Hook, S.

    2016-01-01

    This document outlines the theory and methodology for generating the Moderate Resolution Imaging Spectroradiometer (MODIS) Level-2 daily daytime and nighttime 1-km land surface temperature (LST) and emissivity product using the Temperature Emissivity Separation (TES) algorithm. The MODIS-TES (MOD21_L2) product, will include the LST and emissivity for three MODIS thermal infrared (TIR) bands 29, 31, and 32, and will be generated for data from the NASA-EOS AM and PM platforms. This is version 1.0 of the ATBD and the goal is maintain a 'living' version of this document with changes made when necessary. The current standard baseline MODIS LST products (MOD11*) are derived from the generalized split-window (SW) algorithm (Wan and Dozier 1996), which produces a 1-km LST product and two classification-based emissivities for bands 31 and 32; and a physics-based day/night algorithm (Wan and Li 1997), which produces a 5-km (C4) and 6-km (C5) LST product and emissivity for seven MODIS bands: 20, 22, 23, 29, 31-33.

  1. High spatial resolution Land Surface Temperature estimation over urban areas with uncertainty indices

    Science.gov (United States)

    Mitraka, Zina; Lazzarini, Michele; Doxani, Georgia; Del Frate, Fabio; Ghedira, Hosni

    2014-05-01

    Land Surface Temperature (LST) is a key variable for studying land surface processes and interactions with the atmosphere and it is listed in the Earth System Data Records (ESDRs) identified by international organizations like Global Climate Observing System. It is a valuable source of information for a range of topics in earth sciences and essential for urban climatology studies. Detailed, frequent and accurate LST mapping may support various urban applications, like the monitoring of urban heat island. Currently, no spaceborne instruments provide frequent thermal imagery at high spatial resolution, thus there is a need for synergistic algorithms that combine different kinds of data for LST retrieval. Moreover, knowing the confidence level of any satellite-derived product is highly important to the users, especially when referred to the urban environment, which is extremely heterogenic. The developed method employs spatial-spectral unmixing techniques for improving the spatial resolution of thermal measurements, combines spectral library information for emissivity estimation and applies a split-window algorithm to estimate LST with an uncertainty estimation inserted in the final product. A synergistic algorithm that utilizes the spatial information provided by visible and near-infrared measurements with more frequent low resolution thermal measurements provides excellent means for high spatial resolution LST estimation. Given the low spatial resolution of thermal infrared sensors, the measured radiation is a combination of radiances of different surface types. High spatial resolution information is used to quantify the different surface types in each pixel and then the measured radiance of each pixel is decomposed. The several difficulties in retrieving LST from space measurements, mainly related to the temperature-emissivity coupling and the atmospheric contribution to the thermal measurements, and the measurements themselves, introduce uncertainties in the final

  2. Reducing the Discrepancy Between ASTER and MODIS Land Surface Temperature Products

    Directory of Open Access Journals (Sweden)

    Changqing Ke

    2007-12-01

    Full Text Available Human-induced global warming has significantly increased the importance ofsatellite monitoring of land surface temperature (LST on a global scale. The MODerate-resolution Imaging Spectroradiometer (MODIS provides a 1-km resolution LST productwith almost daily coverage of the Earth, invaluable to both local and global change studies.The Advanced Spaceborne Thermal Emission Reflection Radiometer (ASTER provides aLST product with a high spatial resolution of 90-m and a 16-day recurrent cycle,simultaneously acquired at the same height and nadir view as MODIS. ASTER andMODIS are complementary in resolution, offering a unique opportunity for scale-relatedstudies. ASTER and MODIS LST have been widely used but the errors in LST were mostlydisregarded. Correction of ASTER-to-MODIS LST discrepancies is essential for studiesreliant upon the joint use of these sensors. In this study, we compared three correctionapproaches: the Wan et al.’s approach, the refined Wan et al.’s approach, and thegeneralized split window (GSW algorithm based approach. The Wan et al.’s approachcorrects the MODIS 1-km LST using MODIS 5-km LST. The refined approach modifiesthe Wan et al.’s approach through incorporating ASTER emissivity and MODIS 5-km data.The GSW algorithm approach does not use MODIS 5-km but only ASTER emissivity data. We examined the case over a semi-arid terrain area for the part of the Loess Plateau of China. All the approaches reduced the ASTER-to-MODIS LST discrepancy effectively. With terrain correction, the original ASTER-to-MODIS LST difference reduced from 2.7±1.28 K to -0.1±1.87 K for the Wan et al.’s approach, 0.2±1.57 K for the refined approach, and 0.1±1.33 K for the GSW algorithm based approach. Among all the approaches, the GSW algorithm based approach performed best in terms of mean, standard deviation, root mean square root, and correlation coefficient.

  3. Status of Land Surface Temperature Product Development at NOAA/NESDIS/STAR for JPSS and GOES-R Missions

    Science.gov (United States)

    Yu, Yunyue; Liu, yuling; yu, peng; Casiszar, Ivan; Zhou, Lihang

    2016-04-01

    Land surface temperature (LST) is of fundamental importance to many aspects of the geosciences, e.g., net radiation budget at the Earth surface, monitoring state of crops and vegetation, as well as an important indicator of both the greenhouse effect and the physics of land-surface processes at local through global scales. Satellite LST measurements provide unique data sources for regional and global coverage in fairly good temporal, spatial resolution and time span. Therefore, LST is one of baseline products in both JPSS and GOES-R satellite missions. The Center for SaTellite Applications and Research (STAR) of NOAA/NESDIS is responsible for developing high quality LST products for a variety of satellite missions including JPSS and GOES-R. The JPSS LST data, which is produced for each swath of observations, has reached its beta, provisional and validated stage 1 status in October 2013, May 2014, and December 2015, respectively. A routine validation and monitoring toolkit has been developed and its results are available through a public web site. Our validation results against the U.S. SURFRAD ground stations show that uncertainty of the VIIRS LST is less than 2.35K (vs. the JPSS mission requirement of 2.5K). Improvement of the JPSS LST product is on-going, which counts surface emissive variation explicitly in retrieval algorithm. Further, a gridded daily global LST product will be available by end of 2016. In terms of the GOES-R LST product, we have evaluated the retrieval algorithm using SEVIRI and AHI data as proxies. The evaluation results show that the accuracy of GOES-R LST is expected to be less than 2.30K (GOES-R mission requirement). The validation toolkit developed for JPSS mission will be extended and applicable for the GOES-R mission as well. A detailed Readiness, Implementation and Management Plan (RIMP) of GOES-R LST beta and provisional validation has been developed for the GOES-R launch that is scheduled in October 2016.

  4. Estimating surface turbulent heat fluxes from land surface temperature and soil moisture observations using the particle batch smoother

    Science.gov (United States)

    Lu, Yang; Dong, Jianzhi; Steele-Dunne, Susan C.; van de Giesen, Nick

    2016-11-01

    Surface heat fluxes interact with the overlying atmosphere and play a crucial role in meteorology, hydrology, and climate change studies, but in situ observations are costly and difficult. It has been demonstrated that surface heat fluxes can be estimated from assimilation of land surface temperature (LST). One approach is to estimate a neutral bulk heat transfer coefficient (CHN) to scale the sum of turbulent heat fluxes, and an evaporative fraction (EF) that represents the partitioning between fluxes. Here the newly developed particle batch smoother (PBS) is implemented. The PBS makes no assumptions about the prior distributions and is therefore well-suited for non-Gaussian processes. It is also particularly advantageous for parameter estimation by tracking the entire prior distribution of parameters using Monte Carlo sampling. To improve the flux estimation on wet or densely vegetated surfaces, a simple soil moisture scheme is introduced to further constrain EF, and soil moisture observations are assimilated simultaneously. This methodology is implemented with the FIFE 1987 and 1988 data sets. Validation against observed fluxes indicates that assimilating LST using the PBS significantly improves the flux estimates at both daily and half-hourly timescales. When soil moisture is assimilated, the estimated EFs become more accurate, particularly when the surface heat flux partitioning is energy-limited. The feasibility of extending the methodology to use remote sensing observations is tested by limiting the number of LST observations. Results show that flux estimates are greatly improved after assimilating soil moisture, particularly when LST observations are sparse.

  5. Estimation of Daily Air Temperature Based on MODIS Land Surface Temperature Products over the Corn Belt in the US

    Directory of Open Access Journals (Sweden)

    Linglin Zeng

    2015-01-01

    Full Text Available Air temperature (Ta is a key input in a wide range of agroclimatic applications. Moderate Resolution Imaging Spectroradiometer (MODIS Ts (Land Surface Temperature (LST products are widely used to estimate daily Ta. However, only daytime LST (Ts-day or nighttime LST (Ts-night data have been used to estimate Tmax/Tmin (daily maximum or minimum air temperature, respectively. The relationship between Tmax and Ts-night, and the one between Tmin and Ts-day has not been studied. In this study, both the ability of Ts-night data to estimate Tmax and the ability of Ts-day data to estimate Tmin were tested and studied in the Corn Belt during the growing season (May–September from 2008 to 2012, using MODIS daily LST products from both Terra and Aqua. The results show that using Ts-night for estimating Tmax could result in a higher accuracy than using Ts-day for a similar estimate. Combining Ts-day and Ts-night, the estimation of Tmax was improved by 0.19–1.85, 0.37–1.12 and 0.26–0.93 °C for crops, deciduous forest and developed areas, respectively, when compared with using only Ts-day or Ts-night data. The main factors influencing the Ta estimation errors spatially and temporally were analyzed and discussed, such as satellite overpassing time, air masses, irrigation, etc.

  6. Comparison of two split-window methods for retrieving land surface temperature from MODIS data

    Indian Academy of Sciences (India)

    Shaohua Zhao; Qiming Qin; Yonghui Yang; Yujiu Xiong; Guoyu Qiu

    2009-08-01

    Land surface temperature (LST) is a key parameter in environment and earth science study, especially for monitoring drought. The objective of this work is a comparison of two split-window methods: Mao method and Sobrino method, for retrieving LST using MODIS (Moderate-resolution Imaging Spectroradiometer) data in North China Plain. The results show that the max, min and mean errors of Mao method are 1.33K, 1.54K and 0.13K lower than the standard LST product respectively; while those of Sobrino method are 0.73K, 1.46K and 1.50K higher than the standard respectively. Validation of the two methods using LST product based on weather stations shows a good agreement between the standard and Sobrino method, with RMSE of 1.17K, whereas RMSE of Mao method is 1.85K. Finally, the study introduces the Sobmao method, which is based on Sobrino method but simplifies the estimation of atmospheric water vapour content using Mao method. The Sobmao method has almost the same accuracy with Sobrino method. With high accuracy and simplification of water vapour content estimation, the Sobmao method is recommendable in LST inversion for good application in Ningxia region, the northwest China, with mean error of 0.33K and the RMSE value of 0.91K.

  7. Time series decomposition of remotely sensed land surface temperature and investigation of trends and seasonal variations in surface urban heat islands

    Science.gov (United States)

    Quan, Jinling; Zhan, Wenfeng; Chen, Yunhao; Wang, Mengjie; Wang, Jinfei

    2016-03-01

    Previous time series methods have difficulties in simultaneous characterization of seasonal, gradual, and abrupt changes of remotely sensed land surface temperature (LST). This study proposed a model to decompose LST time series into trend, seasonal, and noise components. The trend component indicates long-term climate change and land development and is described as a piecewise linear function with iterative breakpoint detection. The seasonal component illustrates annual insolation variations and is modeled as a sinusoidal function on the detrended data. This model is able to separate the seasonal variation in LST from the long-term (including gradual and abrupt) change. Model application to nighttime Moderate Resolution Imaging Spectroradiometer (MODIS)/LST time series during 2000-2012 over Beijing yielded an overall root-mean-square error of 1.62 K between the combination of the decomposed trend and seasonal components and the actual MODIS/LSTs. LST decreased (~ -0.086 K/yr, p sixth ring roads. The decreasing trend was stronger over croplands than over urban lands (p < 0.05), resulting in an increasing trend in surface urban heat island intensity (SUHII, 0.022 ± 0.006 K/yr). This was mainly attributed to the trends in urban-rural differences in rainfall and albedo. The SUHII demonstrated a concave seasonal variation primarily due to the seasonal variations of urban-rural differences in temperature cooling rate (related to canyon structure, vegetation, and soil moisture) and surface heat dissipation (affected by humidity and wind).

  8. Downscaling MODIS Land Surface Temperature for Urban Public Health Applications

    Science.gov (United States)

    Al-Hamdan, M. Z.; Crosson, W. L.; Estes, M. G., Jr.; Estes, S. M.; Quattrochi, D. A.; Johnson, D.

    2013-12-01

    This study is part of a project funded by the NASA Applied Sciences Public Health Program, which focuses on Earth science applications of remote sensing data for enhancing public health decision-making. Heat related death is currently the number one weather-related killer in the United States. Mortality from these events is expected to increase as a function of climate change. This activity sought to augment current Heat Watch/Warning Systems (HWWS) with NASA remotely sensed data, and models used in conjunction with socioeconomic and heat-related mortality data. The current HWWS do not take into account intra-urban spatial variations in risk assessment. The purpose of this effort is to evaluate a potential method to improve spatial delineation of risk from extreme heat events in urban environments by integrating sociodemographic risk factors with land surface temperature (LST) estimates derived from thermal remote sensing data. In order to further improve the assessment of intra-urban variations in risk from extreme heat, we developed and evaluated a number of spatial statistical techniques for downscaling the 1-km daily MODerate-resolution Imaging Spectroradiometer (MODIS) LST data to 60 m using Landsat-derived LST data, which have finer spatial but coarser temporal resolution than MODIS. We will present these techniques, which have been demonstrated and validated for Phoenix, AZ using data from the summers of 2000-2006.

  9. Downscaling MODIS Land Surface Temperature for Urban Public Health Applications

    Science.gov (United States)

    Al-Hamdan, Mohammad; Crosson, William; Estes, Maurice, Jr.; Estes, Sue; Quattrochi, Dale; Johnson, Daniel

    2013-01-01

    This study is part of a project funded by the NASA Applied Sciences Public Health Program, which focuses on Earth science applications of remote sensing data for enhancing public health decision-making. Heat related death is currently the number one weather-related killer in the United States. Mortality from these events is expected to increase as a function of climate change. This activity sought to augment current Heat Watch/Warning Systems (HWWS) with NASA remotely sensed data, and models used in conjunction with socioeconomic and heatrelated mortality data. The current HWWS do not take into account intra-urban spatial variation in risk assessment. The purpose of this effort is to evaluate a potential method to improve spatial delineation of risk from extreme heat events in urban environments by integrating sociodemographic risk factors with estimates of land surface temperature (LST) derived from thermal remote sensing data. In order to further improve the consideration of intra-urban variations in risk from extreme heat, we also developed and evaluated a number of spatial statistical techniques for downscaling the 1-km daily MODerate-resolution Imaging Spectroradiometer (MODIS) LST data to 60 m using Landsat-derived LST data, which have finer spatial but coarser temporal resolution than MODIS. In this paper, we will present these techniques, which have been demonstrated and validated for Phoenix, AZ using data from the summers of 2000-2006.

  10. The Utility of Remotely-Sensed Land Surface Temperature from Multiple Platforms For Testing Distributed Hydrologic Models over Complex Terrain

    Science.gov (United States)

    Xiang, T.; Vivoni, E. R.; Gochis, D. J.

    2011-12-01

    Land surface temperature (LST) is a key parameter in watershed energy and water budgets that is relatively unexplored as a validation metric for distributed hydrologic models. Ground-based or remotely-sensed LST datasets can provide insights into a model's ability in reproducing water and energy fluxes across a large range of terrain, vegetation, soil and meteorological conditions. As a result, spatiotemporal LST observations can serve as a strong constraint for distributed simulations and can augment other available in-situ data. LST fields are particular useful in mountainous areas where temperature varies with terrain properties and time-variable surface conditions. In this study, we collect and process remotely-sensed fields from several satellite platforms - Landsat 5/7, MODIS and ASTER - to capture spatiotemporal LST dynamics at multiple resolutions and with frequent repeat visits. We focus our analysis of these fields over the Sierra Los Locos basin (~100 km2) in Sonora, Mexico, for a period encompassing the Soil Moisture Experiment in 2004 and the North American Monsoon Experiment (SMEX04-NAME). Satellite observations are verified using a limited set of ground data from manual sampling at 30 locations and continuous measurements at 2 sites. First, we utilize the remotely-sensed fields to understand the summer seasonal evolution of LST in the basin in response to the arrival of summer storms and the vigorous ecosystem greening organized along elevation bands. Then, we utilize the ground and remote-sensing datasets to test the distributed predictions of the TIN-based Real-time Integrated Basin Simulator (tRIBS) under conditions accounting static and dynamic vegetation patterns. Basin-averaged and distributed comparisons are carried out for two different terrain products (INEGI aerial photogrammetry and ASTER stereo processing) used to derive the distributed model domain. Results from the comparisons are discussed in light of the utility of remotely-sensed LST

  11. Assessment of post-fire changes in land surface temperature and surface albedo, and their relation with fire-burn severity using multitemporal MODIS imagery

    OpenAIRE

    Veraverbeke, Sander; Verstraeten, Willem W.; Lhermitte, Stefaan; Van De Kerchove, Ruben; Goossens, Rudi

    2012-01-01

    This study evaluates the effects of the large 2007 Peloponnese (Greece) wildfires on changes in broadband surface albedo (a), daytime land surface temperature (LSTd) and night-time LST (LSTn) using a 2-year post-fire time series of Moderate Resolution Imaging Spectroradiometer satellite data. In addition, it assesses the potential of remotely sensed a and LST as indicators for fire-burn severity. Immediately after the fire event, mean a dropped up to 0.039 (standard deviation = 0.012) (P < 0....

  12. Algorithm Development for Land Surface Temperature Retrieval: Application to Chinese Gaofen-5 Data

    Directory of Open Access Journals (Sweden)

    Yuanyuan Chen

    2017-02-01

    Full Text Available Land surface temperature (LST is a key variable in the study of the energy exchange between the land surface and the atmosphere. Among the different methods proposed to estimate LST, the quadratic split-window (SW method has achieved considerable popularity. This method works well when the emissivities are high in both channels. Unfortunately, it performs poorly for low land surface emissivities (LSEs. To solve this problem, assuming that the LSE is known, the constant in the quadratic SW method was calculated by maintaining the other coefficients the same as those obtained for the black body condition. This procedure permits transfer of the emissivity effect to the constant. The result demonstrated that the constant was influenced by both atmospheric water vapour content (W and atmospheric temperature (T0 in the bottom layer. To parameterize the constant, an exponential approximation between W and T0 was used. A LST retrieval algorithm was proposed. The error for the proposed algorithm was RMSE = 0.70 K. Sensitivity analysis results showed that under the consideration of NEΔT = 0.2 K, 20% uncertainty in W and 1% uncertainties in the channel mean emissivity and the channel emissivity difference, the RMSE was 1.29 K. Compared with AST 08 product, the proposed algorithm underestimated LST by about 0.8 K for both study areas when ASTER L1B data was used as a proxy of Gaofen-5 (GF-5 satellite data. The GF-5 satellite is scheduled to be launched in 2017.

  13. Assessment of Methods for Land Surface Temperature Retrieval from Landsat-5 TM Images Applicable to Multiscale Tree-Grass Ecosystem Modeling

    Directory of Open Access Journals (Sweden)

    Lidia Vlassova

    2014-05-01

    Full Text Available Land Surface Temperature (LST is one of the key inputs for Soil-Vegetation-Atmosphere transfer modeling in terrestrial ecosystems. In the frame of BIOSPEC (Linking spectral information at different spatial scales with biophysical parameters of Mediterranean vegetation in the context of global change and FLUXPEC (Monitoring changes in water and carbon fluxes from remote and proximal sensing in Mediterranean “dehesa” ecosystem projects LST retrieved from Landsat data is required to integrate ground-based observations of energy, water, and carbon fluxes with multi-scale remotely-sensed data and assess water and carbon balance in ecologically fragile heterogeneous ecosystem of Mediterranean wooded grassland (dehesa. Thus, three methods based on the Radiative Transfer Equation were used to extract LST from a series of 2009–2011 Landsat-5 TM images to assess the applicability for temperature input generation to a Landsat-MODIS LST integration. When compared to surface temperatures simulated using MODerate resolution atmospheric TRANsmission 5 (MODTRAN 5 with atmospheric profiles inputs (LSTref, values from Single-Channel (SC algorithm are the closest (root-mean-square deviation (RMSD = 0.50 °C; procedure based on the online Radiative Transfer Equation Atmospheric Correction Parameters Calculator (RTE-ACPC shows RMSD = 0.85 °C; Mono-Window algorithm (MW presents the highest RMSD (2.34 °C with systematical LST underestimation (bias = 1.81 °C. Differences between Landsat-retrieved LST and MODIS LST are in the range of 2 to 4 °C and can be explained mainly by differences in observation geometry, emissivity, and time mismatch between Landsat and MODIS overpasses. There is a seasonal bias in Landsat-MODIS LST differences due to greater variations in surface emissivity and thermal contrasts between landcover components.

  14. Retrieving Land Surface Temperature and Emissivity from Multispectral and Hyperspectral Thermal Infrared Instruments

    Science.gov (United States)

    Hook, Simon; Hulley, Glynn; Nicholson, Kerry

    2017-04-01

    Land Surface Temperature and Emissivity (LST&E) data are critical variables for studying a variety of Earth surface processes and surface-atmosphere interactions such as evapotranspiration, surface energy balance and water vapor retrievals. LST&E have been identified as an important Earth System Data Record (ESDR) by NASA and many other international organizations Accurate knowledge of the LST&E is a key requirement for many energy balance models to estimate important surface biophysical variables such as evapotranspiration and plant-available soil moisture. LST&E products are currently generated from sensors in low earth orbit (LEO) such as the NASA Moderate Resolution Imaging Spectroradiometer (MODIS) instruments on the Terra and Aqua satellites as well as from sensors in geostationary Earth orbit (GEO) such as the Geostationary Operational Environmental Satellites (GOES) and airborne sensors such as the Hyperspectral Thermal Emission Spectrometer (HyTES). LST&E products are generated with varying accuracies depending on the input data, including ancillary data such as atmospheric water vapor, as well as algorithmic approaches. NASA has identified the need to develop long-term, consistent, and calibrated data and products that are valid across multiple missions and satellite sensors. We will discuss the different approaches that can be used to retrieve surface temperature and emissivity from multispectral and hyperspectral thermal infrared sensors using examples from a variety of different sensors such as those mentioned, and planned new sensors like the ECOsystem Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS) and the Hyperspectral Infrared Imager (HyspIRI). We will also discuss a project underway at NASA to develop a single unified product from some the individual sensor products and assess the errors associated with the product.

  15. AATSR land surface temperature product algorithm verification over a WATERMED site

    Science.gov (United States)

    Noyes, E. J.; Sòria, G.; Sobrino, J. A.; Remedios, J. J.; Llewellyn-Jones, D. T.; Corlett, G. K.

    A new operational Land Surface Temperature (LST) product generated from data acquired by the Advanced Along-Track Scanning Radiometer (AATSR) provides the opportunity to measure LST on a global scale with a spatial resolution of 1 km2. The target accuracy of the product, which utilises nadir data from the AATSR thermal channels at 11 and 12 μm, is 2.5 K for daytime retrievals and 1.0 K at night. We present the results of an experiment where the performance of the algorithm has been assessed for one daytime and one night time overpass occurring over the WATERMED field site near Marrakech, Morocco, on 05 March 2003. Top of atmosphere (TOA) brightness temperatures (BTs) are simulated for 12 pixels from each overpass using a radiative transfer model, with the LST product and independent emissivity values and atmospheric data as inputs. We have estimated the error in the LST product over this biome for this set of conditions by applying the operational AATSR LST retrieval algorithm to the modelled BTs and comparing the results with the original AATSR LSTs input into the model. An average bias of -1.00 K (standard deviation 0.07 K) for the daytime data, and -1.74 K (standard deviation 0.02 K) for the night time data is obtained, which indicates that the algorithm is yielding an LST that is too cold under these conditions. While these results are within specification for daytime retrievals, this suggests that the target accuracy of 1.0 K at night is not being met within this biome.

  16. Evaluation of Land Surface Temperature Retrieval from FY-3B/VIRR Data in an Arid Area of Northwestern China

    Directory of Open Access Journals (Sweden)

    Jinxiong Jiang

    2015-05-01

    Full Text Available This paper uses the refined Generalized Split-Window (GSW algorithm to derive the land surface temperature (LST from the data acquired by the Visible and Infrared Radiometer on FengYun 3B (FY-3B/VIRR. The coefficients in the GSW algorithm corresponding to a series of overlapping ranges for the mean emissivity, the atmospheric Water Vapor Content (WVC, and the LST are derived using a statistical regression method from the numerical values simulated with an accurate atmospheric radiative transfer model MODTRAN 4 over a wide range of atmospheric and surface conditions. The GSW algorithm is applied to retrieve LST from FY-3B/VIRR data in an arid area in northwestern China. Three emissivity databases are used to evaluate the accuracy of different emissivity databases for LST retrieval, including the ASTER Global Emissivity Database (ASTER_GED at a 1-km spatial resolution (AG1km, an average of twelve ASTER emissivity data in the 2012 summer and emissivity spectra extracted from spectral libraries. The LSTs retrieved from the three emissivity databases are evaluated with ground-measured LST at four barren surface sites from June 2012 to December 2013 collected during the HiWATER field campaign. The results indicate that using emissivity extracted from ASTER_GED can achieve the highest accuracy with an average bias of 1.26 and −0.04 K and an average root mean square error (RMSE of 2.69 and 1.38 K for the four sites during daytime and nighttime, respectively. This result indicates that ASTER_GED is a useful emissivity database for generating global LST products from different thermal infrared data and that using FY-3B/VIRR data can produce reliable LST products for other research areas.

  17. Air temperature field distribution estimations over a Chinese mega-city using MODIS land surface temperature data: the case of Shanghai

    Science.gov (United States)

    Ma, Weichun; Zhou, Liguo; Zhang, Hao; Zhang, Yan; Dai, Xiaoyan

    2016-03-01

    The capability of obtaining spatially distributed air temperature data from remote sensing measurements is an improvement for many environmental applications focused on urban heat island, carbon emissions, climate change, etc. This paper is based on the MODIS/Terra and Aqua data utilized to study the effect of the urban atmospheric heat island in Shanghai, China. The correlation between retrieved MODIS land surface temperature (LST) and air temperature measured at local weather stations was initially studied at different temporal and spatial scales. Secondly, the air temperature data with spatial resolutions of 250 m and 1 km were estimated from MODIS LST data and in-situ measured air temperature. The results showed that there is a slightly higher correlation between air temperature and MODIS LST at a 250m resolution in spring and autumn on an annual scale than observed at a 1 km resolution. Although the distribution pattern of the air temperature thermal field varies in different seasons, the urban heat island (UHI) in Shanghai is characterized by a distribution pattern of multiple centers, with the central urban area as the primary center and the built-up regions in each district as the subcenters. This study demonstrates the potential not only for estimating the distribution of the air temperature thermal field from MODIS LST with 250 m resolution in spring and autumn in Shanghai, but also for providing scientific and effective methods for monitoring and studying UHI effect in a Chinese mega-city such as Shanghai.

  18. Land Surface Temperature Retrieval from Landsat 8 TIRS—Comparison between Radiative Transfer Equation-Based Method, Split Window Algorithm and Single Channel Method

    Directory of Open Access Journals (Sweden)

    Xiaolei Yu

    2014-10-01

    Full Text Available Accurate inversion of land surface geo/biophysical variables from remote sensing data for earth observation applications is an essential and challenging topic for the global change research. Land surface temperature (LST is one of the key parameters in the physics of earth surface processes from local to global scales. The importance of LST is being increasingly recognized and there is a strong interest in developing methodologies to measure LST from the space. Landsat 8 Thermal Infrared Sensor (TIRS is the newest thermal infrared sensor for the Landsat project, providing two adjacent thermal bands, which has a great benefit for the LST inversion. In this paper, we compared three different approaches for LST inversion from TIRS, including the radiative transfer equation-based method, the split-window algorithm and the single channel method. Four selected energy balance monitoring sites from the Surface Radiation Budget Network (SURFRAD were used for validation, combining with the MODIS 8 day emissivity product. For the investigated sites and scenes, results show that the LST inverted from the radiative transfer equation-based method using band 10 has the highest accuracy with RMSE lower than 1 K, while the SW algorithm has moderate accuracy and the SC method has the lowest accuracy.

  19. Study of land surface temperature and spectral emissivity using multi-sensor satellite data

    Indian Academy of Sciences (India)

    P K Srivastava; T J Majumdar; Amit K Bhattacharya

    2010-02-01

    In this study, an attempt has been made to estimate land surface temperatures (LST) and spectral emissivities over a hard rock terrain using multi-sensor satellite data. The study area, of about 6000 km2, is a part of Singhbhum–Orissa craton situated in the eastern part of India. TIR data from ASTER, MODIS and Landsat ETM+ have been used in the present study. Telatemp Model AG-42D Portable Infrared Thermometer was used for ground measurements to validate the results derived from satellite (MODIS/ASTER) data. LSTs derived using Landsat ETM+ data of two different dates have been compared with the satellite data (ASTER and MODIS) of those two dates. Various techniques, viz., temperature and emissivity separation (TES) algorithm, gray body adjustment approach in TES algorithm, Split-Window algorithms and Single Channel algorithm along with NDVI based emissivity approach have been used. LSTs derived from bands 31 and 32 of MODIS data using Split-Window algorithms with higher viewing angle (50°) (LST1 and LST2) are found to have closer agreement with ground temperature measurements (ground LST) over waterbody, Dalma forest and Simlipal forest, than that derived from ASTER data (TES with AST 13). However, over agriculture land, there is some uncertainty and difference between the measured and the estimated LSTs for both validation dates for all the derived LSTs. LST obtained using Single Channel algorithm with NDVI based emissivity method in channel 13 of ASTER data has yielded closer agreement with ground measurements recorded over vegetation and mixed lands of low spectral contrast. LST results obtained with TIR band 6 of Landsat ETM+ using Single Channel algorithm show close agreement over Dalma forest, Simlipal forest and waterbody with LSTs obtained using MODIS and ASTER data for a different date. Comparison of LSTs shows good agreement with ground measurements in thermally homogeneous area. However, results in agriculture area with less homogeneity show

  20. Contrasting effects of urbanization and agriculture on surface temperature in eastern China

    Science.gov (United States)

    Zhou, Decheng; Li, Dan; Sun, Ge; Zhang, Liangxia; Liu, Yongqiang; Hao, Lu

    2016-08-01

    The combined effect of urbanization and agriculture, two most pervasive land use activities, on the surface climate remains poorly understood. Using Moderate Resolution Imaging Spectroradiometer data over 2010-2015 and forests as reference, we showed that urbanization warmed the land surface temperature (LST), especially during the daytime and in growing seasons (maximized at 5.0 ± 2.0°C in May), whereas agriculture (dominated by double-cropping system) cooled the LST in two growing seasons during the daytime and all the months but July during the nighttime in Jiangsu Province, eastern China. Collectively, they had insignificant effects on the LST during the day (-0.01°C) and cooled the LST by -0.6°C at night. We also found large geographic variations associated with their thermal effects, indicated by a warming tendency southward. These spatiotemporal patterns depend strongly on vegetation activity, evapotranspiration, surface albedo, and the background climate. Our results emphasize the great potential of agriculture in offsetting the heating effects caused by rapid urbanization in China.

  1. Downscaling of Aircraft-, Landsat-, and MODIS-based Land Surface Temperature Images with Support Vector Machines

    Science.gov (United States)

    Ha, W.; Gowda, P. H.; Oommen, T.; Howell, T. A.; Hernandez, J. E.

    2010-12-01

    High spatial resolution Land Surface Temperature (LST) images are required to estimate evapotranspiration (ET) at a field scale for irrigation scheduling purposes. Satellite sensors such as Landsat 5 Thematic Mapper (TM) and Moderate Resolution Imaging Spectroradiometer (MODIS) can offer images at several spectral bandwidths including visible, near-infrared (NIR), shortwave-infrared, and thermal-infrared (TIR). The TIR images usually have coarser spatial resolutions than those from non-thermal infrared bands. Due to this technical constraint of the satellite sensors on these platforms, image downscaling has been proposed in the field of ET remote sensing. This paper explores the potential of the Support Vector Machines (SVM) to perform downscaling of LST images derived from aircraft (4 m spatial resolution), TM (120 m), and MODIS (1000 m) using normalized difference vegetation index images derived from simultaneously acquired high resolution visible and NIR data (1 m for aircraft, 30 m for TM, and 250 m for MODIS). The SVM is a new generation machine learning algorithm that has found a wide application in the field of pattern recognition and time series analysis. The SVM would be ideally suited for downscaling problems due to its generalization ability in capturing non-linear regression relationship between the predictand and the multiple predictors. Remote sensing data acquired over the Texas High Plains during the 2008 summer growing season will be used in this study. Accuracy assessment of the downscaled 1, 30, and 250 m LST images will be made by comparing them with LST data measured with infrared thermometers at a small spatial scale, upscaled 30 m aircraft-based LST images, and upscaled 250 m TM-based LST images, respectively.

  2. A One-Source Approach for Estimating Land Surface Heat Fluxes Using Remotely Sensed Land Surface Temperature

    Directory of Open Access Journals (Sweden)

    Yongmin Yang

    2017-01-01

    Full Text Available The partitioning of available energy between sensible heat and latent heat is important for precise water resources planning and management in the context of global climate change. Land surface temperature (LST is a key variable in energy balance process and remotely sensed LST is widely used for estimating surface heat fluxes at regional scale. However, the inequality between LST and aerodynamic surface temperature (Taero poses a great challenge for regional heat fluxes estimation in one-source energy balance models. To address this issue, we proposed a One-Source Model for Land (OSML to estimate regional surface heat fluxes without requirements for empirical extra resistance, roughness parameterization and wind velocity. The proposed OSML employs both conceptual VFC/LST trapezoid model and the electrical analog formula of sensible heat flux (H to analytically estimate the radiometric-convective resistance (rae via a quartic equation. To evaluate the performance of OSML, the model was applied to the Soil Moisture-Atmosphere Coupling Experiment (SMACEX in United States and the Multi-Scale Observation Experiment on Evapotranspiration (MUSOEXE in China, using remotely sensed retrievals as auxiliary data sets at regional scale. Validated against tower-based surface fluxes observations, the root mean square deviation (RMSD of H and latent heat flux (LE from OSML are 34.5 W/m2 and 46.5 W/m2 at SMACEX site and 50.1 W/m2 and 67.0 W/m2 at MUSOEXE site. The performance of OSML is very comparable to other published studies. In addition, the proposed OSML model demonstrates similar skills of predicting surface heat fluxes in comparison to SEBS (Surface Energy Balance System. Since OSML does not require specification of aerodynamic surface characteristics, roughness parameterization and meteorological conditions with high spatial variation such as wind speed, this proposed method shows high potential for routinely acquisition of latent heat flux estimation

  3. An operational method for the disaggregation of land surface temperature to estimate actual evapotranspiration in the arid region of Chile

    Science.gov (United States)

    Olivera-Guerra, L.; Mattar, C.; Merlin, O.; Durán-Alarcón, C.; Santamaría-Artigas, A.; Fuster, R.

    2017-06-01

    Monitoring evapotranspiration in arid and semi-arid environments plays a key role in water irrigation scheduling for water use efficiency. This work presents an operational method for evapotranspiration retrievals based on disaggregated Land Surface Temperature (LST). The retrieved LSTs from Landsat-8 and MODIS data were merged in order to provide an 8-day composite LST product at 100 × 100 m resolution. The method was tested in the arid region of Copiapó, Chile using data from years 2013-2014 and validated using data from years 2015-2016. In-situ measurements from agrometeorological stations such as air temperature and potential evapotranspiration (ET0) estimated at the location were used in the ET estimation method. The disaggregation method was developed by taking into account (1) the spatial relationship between Landsat-8 and MODIS LST, (2) the spatial relationship between LST and the Normalized Difference Vegetation Index (NDVI) at high spatial resolution (Landsat-8), and (3) the temporal variations along the year of both relationships aforementioned. The comparison between disaggregated LST at 100 m resolution and in situ LST measurements presents a coefficient of determination (r2), in average, equal to 0.70 and a RMSE equal to 3.6 K. The disaggregated LST was used in an operational model to estimate the actual evapotranspiration (ETa). The ETa shows good results in terms of seasonal variations and in comparison to the evapotranspiration estimated by using crop coefficients (kc). The comparison between remotely sensed and in situ ETa presents an overall r2 close to 0.67 and a RMSE equal to 0.6 mm day-1 for both crops. These results are important for further improvements in water use sustainability in the Copiapó valley, which is currently affected by high water demand.

  4. Developing first time-series of land surface temperature from AATSR with uncertainty estimates

    Science.gov (United States)

    Ghent, Darren; Remedios, John

    2013-04-01

    Land surface temperature (LST) is the radiative skin temperature of the land, and is one of the key parameters in the physics of land-surface processes on regional and global scales. Earth Observation satellites provide the opportunity to obtain global coverage of LST approximately every 3 days or less. One such source of satellite retrieved LST has been the Advanced Along-Track Scanning Radiometer (AATSR); with LST retrieval being implemented in the AATSR Instrument Processing Facility in March 2004. Here we present first regional and global time-series of LST data from AATSR with estimates of uncertainty. Mean changes in temperature over the last decade will be discussed along with regional patterns. Although time-series across all three ATSR missions have previously been constructed (Kogler et al., 2012), the use of low resolution auxiliary data in the retrieval algorithm and non-optimal cloud masking resulted in time-series artefacts. As such, considerable ESA supported development has been carried out on the AATSR data to address these concerns. This includes the integration of high resolution auxiliary data into the retrieval algorithm and subsequent generation of coefficients and tuning parameters, plus the development of an improved cloud mask based on the simulation of clear sky conditions from radiance transfer modelling (Ghent et al., in prep.). Any inference on this LST record is though of limited value without the accompaniment of an uncertainty estimate; wherein the Joint Committee for Guides in Metrology quote an uncertainty as "a parameter associated with the result of a measurement that characterizes the dispersion of the values that could reasonably be attributed to the measurand that is the value of the particular quantity to be measured". Furthermore, pixel level uncertainty fields are a mandatory requirement in the on-going preparation of the LST product for the upcoming Sea and Land Surface Temperature (SLSTR) instrument on-board Sentinel-3

  5. Maximizing the Use of Satellite Thermal Infrared Data for Advancing Land Surface Temperature Analysis

    Science.gov (United States)

    Weng, Q.; Fu, P.; Gao, F.

    2014-12-01

    Land surface temperature (LST) is a crucial parameter in investigating environmental, ecological processes and climate change at various scales, and is also valuable in the studies of evapotranspiration, soil moisture conditions, surface energy balance, and urban heat islands. These studies require thermal infrared (TIR) images at both high temporal and spatial resolution to retrieve LST. However, currently, no single satellite sensors can deliver TIR data at both high temporal and spatial resolution. Thus, various algorithms/models have been developed to enhance the spatial or the temporal resolution of TIR data, but rare of those can enhance both spatial and temporal details. This paper presents a new data fusion algorithm for producing Landsat-like LST data by blending daily MODIS and periodic Landsat TM datasets. The original Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM) was improved and modified for predicting thermal radiance and LST data by considering annual temperature cycle (ATC) and urban thermal landscape heterogeneity. The technique of linear spectral mixture analysis was employed to relate the Landsat radiance with the MODIS one, so that the temporal changes in radiance can be incorporated in the fusion model. This paper details the theoretical basis and the implementation procedures of the proposed data fusion algorithm, Spatio-temporal Adaptive Data Fusion Algorithm for Temperature mapping (SADFAT). A case study was conducted that predicted LSTs of five dates in 2005 from July to October in Los Angeles County, California. The results indicate that the prediction accuracy for the whole study area ranged from 1.3 K to 2 K. Like existing spatio-temporal data fusion models, the SADFAT method has a limitation in predicting LST changes that were not recorded in the MODIS and/or Landsat pixels due to the model assumption.

  6. Simulating Land Cover Changes and Their Impacts on Land Surface Temperature in Dhaka, Bangladesh

    Directory of Open Access Journals (Sweden)

    Bayes Ahmed

    2013-11-01

    Full Text Available Despite research that has been conducted elsewhere, little is known, to-date, about land cover dynamics and their impacts on land surface temperature (LST in fast growing mega cities of developing countries. Landsat satellite images of 1989, 1999, and 2009 of Dhaka Metropolitan (DMP area were used for analysis. This study first identified patterns of land cover changes between the periods and investigated their impacts on LST; second, applied artificial neural network to simulate land cover changes for 2019 and 2029; and finally, estimated their impacts on LST in respective periods. Simulation results show that if the current trend continues, 56% and 87% of the DMP area will likely to experience temperatures in the range of greater than or equal to 30 °C in 2019 and 2029, respectively. The findings possess a major challenge for urban planners working in similar contexts. However, the technique presented in this paper would help them to quantify the impacts of different scenarios (e.g., vegetation loss to accommodate urban growth on LST and consequently to devise appropriate policy measures.

  7. Detection of Terrestrial Ecosystem Disturbances Using Aqua/MODIS Land Surface Temperature and Enhanced Vegetation Index

    Science.gov (United States)

    Mildrexler, D. J.; Zhao, M.; Running, S. W.

    2011-12-01

    Global information on the timing, location and magnitude of large-scale ecosystem disturbance events is needed to reduce significant uncertainty in the global carbon cycle. The MODIS Global Disturbance Index (MGDI) algorithm is designed for systematic, global, disturbance mapping using Aqua/MODIS Land Surface Temperature (LST) and Enhanced Vegetation Index (EVI) data. The MGDI uses annual maximum composite LST data to detect fundamental changes in land-surface energy partitioning, while avoiding the high natural variability associated with tracking LST at daily, weekly, or seasonal time frames. LST and EVI respond to different biophysical processes and coupling these variables together into a ratio results in a dynamic approach that measures both the energy exchange consequence and the vegetation density changes resulting from disturbance. This robust radiometric relationship is revisited for each individual pixel every year resulting in a consistent methodology that can be generalized globally to provide 1-km resolution information about the effects of major disturbance on woody ecosystems and has been validated across North America. We have now applied the full Aqua/MODIS dataset through 2010 to the MGDI algorithm across woody ecosystems globally and continue to validate the MGDI results by comparison with confirmed, historical disturbance events such as wildfire, hurricanes, insect epidemics, ice storms, and droughts.

  8. An enhanced single-channel algorithm for retrieving land surface temperature from Landsat series data

    Science.gov (United States)

    Wang, Mengmeng; Zhang, Zhaoming; He, Guojin; Wang, Guizhou; Long, Tengfei; Peng, Yan

    2016-10-01

    Land surface temperature (LST) is a critical parameter in the physics of Earth surface processes and is required for many applications related to ecology and environment. Landsat series satellites have provided more than 30 years of thermal information at medium spatial resolution. This paper proposes an enhanced single-channel algorithm (SCen) for retrieving LST from Landsat series data (Landsat 4 to Landsat 8). The SCen algorithm includes three atmospheric functions (AFs), and the latitude and acquisition month of Landsat image were added to the AF models to improve LST retrieval. Performance of the SCen algorithm was assessed with both simulated and in situ data, and accuracy of three single-channel algorithms (including the monowindow algorithm developed by Qin et al., SCQin, and the generalized single-channel algorithm developed by Jiménez-Muñoz and Sobrino, SCJ&S) were compared. The accuracy assessments with simulated data had root-mean-square deviations (RMSDs) for the SCen, SCJ&S, and SCQin algorithms of 1.363 K, 1.858 K, and 2.509 K, respectively. Validation with in situ data showed RMSDs for the SCen and SCJ&S algorithms of 1.04 K and 1.49 K, respectively. It was concluded that the SCen algorithm is very operational, has good precision, and can be used to develop an LST product for Landsat series data.

  9. Air Temperature estimation from Land Surface temperature and solar Radiation parameters

    Science.gov (United States)

    Lazzarini, Michele; Eissa, Yehia; Marpu, Prashanth; Ghedira, Hosni

    2013-04-01

    Air Temperature (AirT) is a fundamental parameter in a wide range of applications such as climate change studies, weather forecast, energy balance modeling, efficiency of Photovoltaic (PV) solar cells, etc. Air temperature data are generally obtained through regular measurements from meteorological stations. The distribution of these stations is normally sparse, so the spatial pattern of this parameter cannot be accurately estimated by interpolation methods. This work investigated the relationship between Air Temperature measured at meteorological stations and spatially contiguous measurements derived from Remote Sensing techniques, such as Land Surface Temperature (LST) maps, emissivity maps and shortwave radiation maps with the aim of creating a continuous map of AirT. For LST and emissivity, MSG-SEVIRI LST product from Land Surface Analysis Satellite Applications Facility (LSA-SAF) has been used. For shortwave radiation maps, an Artificial Neural Networks ensemble model has been developed and previously tested to create continuous maps from Global Horizontal Irradiance (GHI) point measurements, utilizing six thermal channels of MSG-SEVIRI. The testing sites corresponded to three meteorological stations located in the United Arab Emirates (UAE), where in situ measurements of Air Temperature were available. From the starting parameters, energy fluxes and net radiation have been calculated, in order to have information on the incoming and outgoing long-wave radiation and the incoming short-wave radiation. The preliminary analysis (day and Night measurements, cloud free) showed a strong negative correlation (0.92) between Outgoing long-wave radiation - GHI and LST- AirT, with a RMSE of 1.84 K in the AirT estimation from the initial parameters. Regression coefficients have been determined and tested on all the ground stations. The analysis also demonstrated the predominant impact of the incoming short-wave radiation in the AirT hourly variation, while the incoming

  10. Effects of urban impervious surfaces on land surface temperatures: Spatial scale dependence, temporal variations, and bioclimatic modulation

    Science.gov (United States)

    Ma, Qun; Wu, Jianguo; He, Chunyang

    2016-04-01

    Quantifying the relationship between urban impervious surfaces (UIS) and land surface temperatures (LST) is important for understanding and mitigating the environmental impacts of urban heat islands in human-dominated landscapes. The main goal of this study was to examine how the UIS-LST relationship changes with spatial scales, seasonal and diurnal variations, and bioclimatic context in mainland China. We took a hierarchical approach that explicitly considered three spatial scales: the ecoregion, urban cluster, and urban core. Remote sensing data and regression methods were used. Our results showed that, in general, UIS and LST were positively correlated in summer and winter nighttime, but negatively in winter daytime. The strength of correlation increased from broad to fine scales. For example, the mean R2 for winter nights was 3 times higher at the urban core scale than at the ecoregion scale. The relationship showed large seasonal and diurnal variations: generally stronger in summer than in winter and stronger in nighttime than in daytime. At the urban core scale, for instance, the mean R2 was 2.2 times higher in summer daytime than in winter daytime, and 3.1 times higher in winter nighttime than in winter daytime. Vegetation and climate modified the relationship during summer daytime on the ecoregion scale. In conclusion, UIS has substantial influences on LST, and these effects vary greatly with spatial scales, diurnal/seasonal cycles, and bioclimatic context. Our study reveals several trends on the scale multiplicity, temporal variations, and context dependence of the UIS-LST relationship, which deserve further examination. Importantly, high mean R2 values with large variations on the local urban scale suggest that a great potential exists for mitigating urban heat island effects via urban landscape planning.

  11. Effects of landscape composition and pattern on land surface temperature: An urban heat island study in the megacities of Southeast Asia.

    Science.gov (United States)

    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.

  12. An Improved Mono-Window Algorithm for Land Surface Temperature Retrieval from Landsat 8 Thermal Infrared Sensor Data

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    Fei Wang

    2015-04-01

    Full Text Available The successful launch of the Landsat 8 satellite with two thermal infrared bands on February 11, 2013, for continuous Earth observation provided another opportunity for remote sensing of land surface temperature (LST. However, calibration notices issued by the United States Geological Survey (USGS indicated that data from the Landsat 8 Thermal Infrared Sensor (TIRS Band 11 have large uncertainty and suggested using TIRS Band 10 data as a single spectral band for LST estimation. In this study, we presented an improved mono-window (IMW algorithm for LST retrieval from the Landsat 8 TIRS Band 10 data. Three essential parameters (ground emissivity, atmospheric transmittance and effective mean atmospheric temperature were required for the IMW algorithm to retrieve LST. A new method was proposed to estimate the parameter of effective mean atmospheric temperature from local meteorological data. The other two essential parameters could be both estimated through the so-called land cover approach. Sensitivity analysis conducted for the IMW algorithm revealed that the possible error in estimating the required atmospheric water vapor content has the most significant impact on the probable LST estimation error. Under moderate errors in both water vapor content and ground emissivity, the algorithm had an accuracy of ~1.4 K for LST retrieval. Validation of the IMW algorithm using the simulated datasets for various situations indicated that the LST difference between the retrieved and the simulated ones was 0.67 K on average, with an RMSE of 0.43 K. Comparison of our IMW algorithm with the single-channel (SC algorithm for three main atmosphere profiles indicated that the average error and RMSE of the IMW algorithm were −0.05 K and 0.84 K, respectively, which were less than the −2.86 K and 1.05 K of the SC algorithm. Application of the IMW algorithm to Nanjing and its vicinity in east China resulted in a reasonable LST estimation for the region. Spatial

  13. Prediction of high spatio-temporal resolution land surface temperature under cloudy conditions using microwave vegetation index and ANN

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    Shwetha, H. R.; Kumar, D. Nagesh

    2016-07-01

    Land Surface Temperature (LST) with high spatio-temporal resolution is in demand for hydrology, climate change, ecology, urban climate and environmental studies, etc. Moderate Resolution Imaging Spectroradiometer (MODIS) is one of the most commonly used sensors owing to its high spatial and temporal availability over the globe, but is incapable of providing LST data under cloudy conditions, resulting in gaps in the data. In contrast, microwave measurements have a capability to penetrate under clouds. The current study proposes a methodology by exploring this property to predict high spatio-temporal resolution LST under cloudy conditions during daytime and nighttime without employing in-situ LST measurements. To achieve this, Artificial Neural Networks (ANNs) based models are employed for different land cover classes, utilizing Microwave Polarization Difference Index (MPDI) at finer resolution with ancillary data. MPDI was derived using resampled (from 0.25° to 1 km) brightness temperatures (Tb) at 36.5 GHz channel of dual polarization from Advance Microwave Scanning Radiometer (AMSR)-Earth Observing System and AMSR2 sensors. The proposed methodology is tested over Cauvery basin in India and the performance of the model is quantitatively evaluated through performance measures such as correlation coefficient (r), Nash Sutcliffe Efficiency (NSE) and Root Mean Square Error (RMSE). Results revealed that during daytime, AMSR-E(AMSR2) derived LST under clear sky conditions corresponds well with MODIS LST resulting in values of r ranging from 0.76(0.78) to 0.90(0.96), RMSE from 1.76(1.86) K to 4.34(4.00) K and NSE from 0.58(0.61) to 0.81(0.90) for different land cover classes. During nighttime, r values ranged from 0.76(0.56) to 0.87(0.90), RMSE from 1.71(1.70) K to 2.43(2.12) K and NSE from 0.43(0.28) to 0.80(0.81) for different land cover classes. RMSE values found between predicted LST and MODIS LST during daytime under clear sky conditions were within acceptable

  14. TOWARD CALIBRATED MODULAR WIRELESS SYSTEM BASED AD HOC SENSORS FOR IN SITU LAND SURFACE TEMPERATURE MEASUREMENTS AS SUPPORT TO SATELLITE REMOTE SENSING

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    ASAAD CHAHBOUN

    2011-06-01

    Full Text Available This paper presents a new method for in situ Land Surface Temperature (LST measurements' campaigns for satellite algorithms validations. The proposed method based on Wireless Sensor Network (WSN is constituted by modules of node arrays. Each of which is constituted by 25 smart nodes scattered throughout a target field. Every node represents a Thermal Infra Red (TIR radiation sensor and keeps a minimum size while ensuring the functions of communication, sensing, and processing. This Wireless-LST (Wi-LST system is convenient to beinstalled on a field pointing to any type of targets (e.g. bare soil, grass, water, etc.. Ad hoc topology is adopted among the TIR nodes with multi-hop mesh routing protocol for communication, acquisition data are transmitted to the client tier wirelessly. Using these emergent technologies, we propose a practical method for Wi-LSTsystem calibration. TIR sensor (i.e. OSM101 from OMEGA society measures temperature, which is conditioned and amplified by an AD595 within a precision of 0.1 °C. Assessed LST is transmitted over thedeveloped ad hoc WSN modules (i.e. MICA2DOT from CROSSBOW society, and collected at in situ base station (i.e. PANASONIC CF19 laptop using an integrated database. LST is evaluated with a polynomialalgorithm structure as part of developed software. Finally, the comparison of the mean values of LST(Wi-LST in each site with the Moderate Resolution Imaging Spectro-radiometer (MODIS sensor, obtained from the daily LST product (MOD11C1 developed by the MODIS-NASA Science Team, on board TERRA satellite during the campaign period is provided.

  15. MEaSUREs Land Surface Temperature from GOES Satellites

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    Pinker, Rachel T.; Chen, Wen; Ma, Yingtao; Islam, Tanvir; Borbas, Eva; Hain, Chris; Hulley, Glynn; Hook, Simon

    2017-04-01

    Information on Land Surface Temperature (LST) can be generated from observations made from satellites in low Earth orbit (LEO) such as MODIS and ASTER and by sensors in geostationary Earth orbit (GEO) such as GOES. Under a project titled: "A Unified and Coherent Land Surface Temperature and Emissivity Earth System Data Record for Earth Science" led by Jet Propulsion Laboratory, an effort is underway to develop long term consistent information from both such systems. In this presentation we will describe an effort to derive LST information from GOES satellites. Results will be presented from two approaches: 1) based on regression developed from a wide range of simulations using MODTRAN, SeeBor Version 5.0 global atmospheric profiles and the CAMEL (Combined ASTER and MODIS Emissivity for Land) product based on the standard University of Wisconsin 5 km emissivity values (UWIREMIS) and the ASTER Global Emissivity Database (GED) product; 2) RTTOV radiative transfer model driven with MERRA-2 reanalysis fields. We will present results of evaluation of these two methods against various products, such as MOD11, and ground observations for the five year period of (2004-2008).

  16. Mapping Land Surface Temperature and Land Cover to Detect Urban Heat Island Effect: A Case Study of Tarkwa, South West Ghana

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    Michael Soakodan Aduah

    2012-01-01

    Full Text Available Urban Heat Island (UHI effect controls internal climates of buildings and affects energy use and comfort of urban dwellers. The objective of this study was to detect UHI from Land Surface Temperature (LST and to investigate whether land cover has any influence on UHI in Tarkwa, South West Ghana using satellite remote sensing techniques. A Landsat 7 ETM+ image, DEM and meteorological data were used to generate a land cover map with the maximum likelihood classification algorithm whiles LST was modeled with the Landsat Plank’s curve. Validation of the LST map was achieved by comparing it with air temperature measured at the UMaT meteorological station. The mean modeled LST of 298.60 Kelvin compared well with the mean observed air temperature of 298.30 Kelvin. Furthermore, LST ranged between 289 and 305 Kelvin while urban areas and bare soils had higher LSTs than vegetated areas implying that higher NDVI areas are associated with lower temperatures. Hence, LST maps produced indicated the existence of UHI effect in the Tarkwa area. From the study it is evident that impervious and non-evaporative surfaces have high LSTs due to absence of vegetation. Therefore, uncontrolled land cover changes may intensify the UHI effect. The study has proven that remote sensing can be used in operational mapping of LST for climate studies, vegetation monitoring and detecting UHIs in the humid regions of Ghana. This confirms the important role Earth observation and geoinformation technology can play in environmental monitoring and management as global climate and land cover changes.

  17. Calibration of the Distributed Hydrological Model mHM using Satellite derived Land Surface Temperature

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    Zink, M.; Samaniego, L. E.; Cuntz, M.

    2012-12-01

    A combined investigation of the water and energy balance in hydrologic models can lead to a more accurate estimation of hydrological fluxes and state variables, such as evapotranspiration and soil moisture. Hydrologic models are usually calibrated against discharge measurements, and thus are only trained on information of few points within a catchment. This procedure does not take into account any spatio-temporal variability of fluxes or state variables. Satellite data are a useful source of information to account for this spatial distributions. The objective of this study is to calibrate the distributed hydrological model mHM with satellite derived Land Surface Temperature (LST) fields provided by the Land Surface Analysis - Satellite Application Facility (LSA-SAF). LST is preferred to other satellite products such as soil moisture or evapotranspiration due to its higher precision. LST is obtained by solving the energy balance by assuming that the soil heat flux and the storage term are negligible on a daily time step. The evapotranspiration is determined by closing the water balance in mHM. The net radiation is calculated by using the incoming short- and longwave radiation, albedo and emissivity data provided by LSA-SAF. The Multiscale Parameter Regionalization technique (MPR, Samaniego et al. 2010) is used to determine the aerodynamic resistance among other parameters. The optimization is performed within the time period 2008-2010 using three objective functions that consider 1) only discharge, 2) only LST, and 3) a combination of both. The proposed method is applied to seven major German river basins: Danube, Ems, Main, Mulde, Neckar, Saale, and Weser. The annual coefficient of correlation between LSA-SAF incoming shortwave radiation and 28 meteorological stations operated by the German Weather Service (DWD) is 0.94 (RMSE = 29 W m-2) in 2009. LSA-SAF incoming longwave radiation could be further evaluated at two eddy covariance stations with a very similar

  18. Towards a protocol for validating satellite-based Land Surface Temperature: Theoretical considerations

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    Schneider, Philipp; Ghent, Darren J.; Corlett, Gary C.; Prata, Fred; Remedios, John J.

    2013-04-01

    Land Surface Temperature (LST) and emissivity are important parameters for environmental monitoring and earth system modelling. LST has been observed from space for several decades using a wide variety of satellite instruments with different characteristics, including both platforms in low-earth orbit and in geostationary orbit. This includes for example the series of Advanced Very High Resolution Radiometers (AVHRR) delivering a continuous thermal infrared (TIR) data stream since the early 1980s, the series of Along-Track Scanning Radiometers (ATSR) providing TIR data since 1991, and the Moderate Resolution Imaging Spectroradiometer (MODIS) instruments onboard NASA's Terra and Aqua platforms, providing data since the year 2000. In addition, the Spinning Enhanced Visible and Infrared Imager (SEVIRI) onboard of the geostationary Meteosat satellites is now providing LST at unprecedented sub-hour frequency. The data record provided by such instruments is extremely valuable for a wide variety of applications, including climate change, land/atmosphere feedbacks, fire monitoring, modelling, land cover change, geology, crop- and water management. All of these applications, however, require a rigorous validation of the data in order to assess the product quality and the associated uncertainty. Here we report on recent work towards developing a protocol for validation of satellite-based Land Surface Temperature products. Four main validation categories are distinguished within the protocol: A) Comparison with in situ observations, B) Radiance-based validation, C) Inter-comparison with similar LST products, and D) Time-series analysis. Each category is further subdivided into several quality classes, which approximately reflect the validation accuracy that can be achieved by the different approaches, as well as the complexity involved with each method. Advice on best practices is given for methodology common to all categories. For each validation category, recommendations

  19. Towards reducing the cloud-induced sampling biases in MODIS LST data: a case study from Greenland

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    Karami, M.; Hansen, B. U.

    2016-12-01

    Satellite-driven Land Surface Temperature (LST) datasets are essential for characterizing climate change impacts on terrestrial ecosystems, as well as a wide range of surface-atmosphere studies. In the past one and a half decade, NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) has provided the scientific community with LST estimates on a global scale with reasonable spatial resolution and revisit time. However, the use of MODIS LST for climate studies is complicated by the simple fact that the observations can only be made under clear-sky conditions. In regions with frequent overcast skies, this can result in the calculated climatic variables deviating from the actual surface conditions. In the present study, we propose and validate a framework based on model-driven downwelling radiation data from ERA-Interim and instantenous LST observations from both MODIS Terra and Aqua, in order to minimize the clear-sky sampling bias. The framework is validated on a cloud-affected MODIS scene covering parts of Greenland (h15v02), and by incorporating in-situ data from a number of monitoring stations in the area. The results indicate that the proposed method is able to increase the number of daily LST estimates by a factor of 2.07 and reduce the skewnewss of monthly distribution of the successful estimates by a factor of 0.22. Considering that these improvements are achieved mainly through introducing data from partially overcast days, the estimated climatic variables show better agreement with the ground truth. The overall accuracy of the model in estimating in-situ mean daily LST remained satisfactory even after incoprporating the daily downweling radiation from ERA-interim (RMSE=0.41 °K, R-squared=0.992). Nonetheless, since technical constraints are expected to continue limiting the use of high temporal resolution satellites in high latitudes, more research is required to quantify and deal with various types of cloud-induced biases present in the data from

  20. Trends in ERS and Envisat (A)ATSR Global Land Surface Temperature Data Since 1991

    Science.gov (United States)

    Kogler, Christian; Pinnock, Simon; Arino, Olivier; Casadio, Stefano; Corlett, Gary; Prata, Fred; Bras, Teresa

    2010-12-01

    Land surface temperature (LST) is a key parameter in the physical study of atmosphere-land interactions as well as for global warming and climate change monitoring on a longer timescale. The main tool to obtain LST as such a key parameter at global scale with different spatial and temporal resolutions is remote sensing. To retrieve highly accurate LSTs, measured radiances at the sensor have to be corrected for emissivity, atmospheric effects and contaminating clouds. This study is based on LST data provided by the Along-Track Scanning Radiometer (ATSR) and the Advanced ATSR (AATSR) on board the three ESA satellites ERS-1, ERS-2 and ENVISAT. The analysis covers data from August 1991 up to December 2009 and contains detailed investigations on global as well as on regional scale with a temporal resolution of one month, outlining problems and restrictions within the time series due to cloud contamination and failing cloud detection tests. It is demonstrated that trends, for cooling as well as for warming, rather show trends in cloud contamination, than real trends in LST.

  1. Relating trends in land surface-air temperature difference to soil moisture and evapotranspiration

    Science.gov (United States)

    Veal, Karen; Taylor, Chris; Gallego-Elvira, Belen; Ghent, Darren; Harris, Phil; Remedios, John

    2016-04-01

    Soil water is central to both physical and biogeochemical processes within the Earth System. Drying of soils leads to evapotranspiration (ET) becoming limited or "water-stressed" and is accompanied by rises in land surface temperature (LST), land surface-air temperature difference (delta T), and sensible heat flux. Climate models predict sizable changes to the global water cycle but there is variation between models in the time scale of ET decay during dry spells. The e-stress project is developing novel satellite-derived diagnostics to assess the ability of Earth System Models (ESMs) to capture behaviour that is due to soil moisture controls on ET. Satellite records of LST now extend 15 years or more. MODIS Terra LST is available from 2000 to the present and the Along-Track Scanning Radiometer (ATSR) LST record runs from 1995 to 2012. This paper presents results from an investigation into the variability and trends in delta T during the MODIS Terra mission. We use MODIS Terra and MODIS Aqua LST and ESA GlobTemperature ATSR LST with 2m air temperatures from reanalyses to calculate trends in delta T and "water-stressed" area. We investigate the variability of delta T in relation to soil moisture (ESA CCI Passive Daily Soil Moisture), vegetation (MODIS Monthly Normalized Difference Vegetation Index) and precipitation (TRMM Multi-satellite Monthly Precipitation) and compare the temporal and spatial variability of delta T with model evaporation data (GLEAM). Delta T anomalies show significant negative correlations with soil moisture, in different seasons, in several regions across the planet. Global mean delta T anomaly is small (magnitude mostly less than 0.2 K) between July 2002 and July 2008 and decreases to a minimum in early 2010. The reduction in delta T anomaly coincides with an increase in soil moisture anomaly and NDVI anomaly suggesting an increase in evapotranspiration and latent heat flux with reduced sensible heat flux. In conclusion there have been

  2. A Software Tool for Atmospheric Correction and Surface Temperature Estimation of Landsat Infrared Thermal Data

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    Benjamin Tardy

    2016-08-01

    Full Text Available Land surface temperature (LST is an important variable involved in the Earth’s surface energy and water budgets and a key component in many aspects of environmental research. The Landsat program, jointly carried out by NASA and the USGS, has been recording thermal infrared data for the past 40 years. Nevertheless, LST data products for Landsat remain unavailable. The atmospheric correction (AC method commonly used for mono-window Landsat thermal data requires detailed information concerning the vertical structure (temperature, pressure and the composition (water vapor, ozone of the atmosphere. For a given coordinate, this information is generally obtained through either radio-sounding or atmospheric model simulations and is passed to the radiative transfer model (RTM to estimate the local atmospheric correction parameters. Although this approach yields accurate LST data, results are relevant only near this given coordinate. To meet the scientific community’s demand for high-resolution LST maps, we developed a new software tool dedicated to processing Landsat thermal data. The proposed tool improves on the commonly-used AC algorithm by incorporating spatial variations occurring in the Earth’s atmosphere composition. The ERA-Interim dataset (ECMWFmeteorological organization was used to retrieve vertical atmospheric conditions, which are available at a global scale with a resolution of 0.125 degrees and a temporal resolution of 6 h. A temporal and spatial linear interpolation of meteorological variables was performed to match the acquisition dates and coordinates of the Landsat images. The atmospheric correction parameters were then estimated on the basis of this reconstructed atmospheric grid using the commercial RTMsoftware MODTRAN. The needed surface emissivity was derived from the common vegetation index NDVI, obtained from the red and near-infrared (NIR bands of the same Landsat image. This permitted an estimation of LST for the entire

  3. Evaluation of ESTARFM based algorithm for generating land surface temperature products by fusing ASTER and MODIS data during the HiWATER-MUSOEXE

    Science.gov (United States)

    Land surface temperature (LST) is an important parameter that is highly responsive to surface energy fluxes and has become valuable to many disciplines. However, it is difficult to acquire satellite LSTs with both high spatial and temporal resolutions due to tradeoffs between them. Thus, various alg...

  4. Surface Temperature Data Analysis

    Science.gov (United States)

    Hansen, James; Ruedy, Reto

    2012-01-01

    Small global mean temperature changes may have significant to disastrous consequences for the Earth's climate if they persist for an extended period. Obtaining global means from local weather reports is hampered by the uneven spatial distribution of the reliably reporting weather stations. Methods had to be developed that minimize as far as possible the impact of that situation. This software is a method of combining temperature data of individual stations to obtain a global mean trend, overcoming/estimating the uncertainty introduced by the spatial and temporal gaps in the available data. Useful estimates were obtained by the introduction of a special grid, subdividing the Earth's surface into 8,000 equal-area boxes, using the existing data to create virtual stations at the center of each of these boxes, and combining temperature anomalies (after assessing the radius of high correlation) rather than temperatures.

  5. Land Surface Temperature in Łódź Obtained from Landsat 5TM

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    Jędruszkiewicz, Joanna; Zieliński, Mariusz

    2012-01-01

    The main aim of this paper is to present the spatial differentiation of Land Surface Temperature LST in Łódź based on Landsat 5 Thematic Mapper (L5TM) images. Analysis was performed for all L5TM images from 2011, with clear sky over Łódź. Land surface temperature (LST) play an important role in determination of weather conditions in boundary layer of atmosphere, especially connected with convection. Environmental satellites from Landsat series delivers the high resolution images of Earth's surface and according to the estimations made on the ground of it are precise. LST depends widely on surface emissivity. In this paper the emissivity was estimated from MODIS sensor as well as NDVI index, then both method were compared. The processed images allowed to determine the warmest and the coldest areas in the administrative boundaries of Łódź. The highest LST values has been found in industrial areas and the in the heart of the city. However, there are some places lying in city outskirts, where the LST values are as high, for instance Lodz Airport. On the contrary the lowest LST values occur mostly in terrains covered with vegetation i.e. forests or city parks. Głównym celem tego opracowania było oszacowanie temperatury powierzchni Ziemi w Łodzi, na podstawie obrazów satelitarnych pochodzących z satelity Landsat 5 Thematic Mapper (L5TM). Analizę wykonane dla obrazów wszystkich dostępnych obrazów z 2011 roku, na których zachmurzenie nie wystąpiło nad obszarem Łodzi. Temperatura powierzchni Ziemi odgrywa istotną rolę w kształtowaniu warunków pogodowych w warstwie granicznej, szczególnie związanych z konwekcją. Satelity środowiskowe z serii Landsat dostarczają obrazów w dużej rozdzielczości, dzięki czemu pozwalają na stosunkowo dokładne oszacowanie tego parametru. Wielkość temperatury w dużym stopniu zależy od emisyjności danej powierzchni. W niniejszym opracowaniu porównano temperaturę powierzchniową obliczoną dla emisyjno

  6. Characterizing the relationship between land use land cover change and land surface temperature

    Science.gov (United States)

    Tran, Duy X.; Pla, Filiberto; Latorre-Carmona, Pedro; Myint, Soe W.; Caetano, Mario; Kieu, Hoan V.

    2017-02-01

    Exploring changes in land use land cover (LULC) to understand the urban heat island (UHI) effect is valuable for both communities and local governments in cities in developing countries, where urbanization and industrialization often take place rapidly but where coherent planning and control policies have not been applied. This work aims at determining and analyzing the relationship between LULC change and land surface temperature (LST) patterns in the context of urbanization. We first explore the relationship between LST and vegetation, man-made features, and cropland using normalized vegetation, and built-up indices within each LULC type. Afterwards, we assess the impacts of LULC change and urbanization in UHI using hot spot analysis (Getis-Ord Gi∗ statistics) and urban landscape analysis. Finally, we propose a model applying non-parametric regression to estimate future urban climate patterns using predicted land cover and land use change. Results from this work provide an effective methodology for UHI characterization, showing that (a) LST depends on a nonlinear way of LULC types; (b) hotspot analysis using Getis Ord Gi∗ statistics allows to analyze the LST pattern change through time; (c) UHI is influenced by both urban landscape and urban development type; (d) LST pattern forecast and UHI effect examination can be done by the proposed model using nonlinear regression and simulated LULC change scenarios. We chose an inner city area of Hanoi as a case-study, a small and flat plain area where LULC change is significant due to urbanization and industrialization. The methodology presented in this paper can be broadly applied in other cities which exhibit a similar dynamic growth. Our findings can represent an useful tool for policy makers and the community awareness by providing a scientific basis for sustainable urban planning and management.

  7. The Role of Vegetation in Mitigating Urban Land Surface Temperatures: A Case Study of Munich, Germany during the Warm Season

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    Sadroddin Alavipanah

    2015-04-01

    Full Text Available The Urban Heat Island (UHI is the phenomenon of altered increased temperatures in urban areas compared to their rural surroundings. UHIs grow and intensify under extreme hot periods, such as during heat waves, which can affect human health and also increase the demand for energy for cooling. This study applies remote sensing and land use/land cover (LULC data to assess the cooling effect of varying urban vegetation cover, especially during extreme warm periods, in the city of Munich, Germany. To compute the relationship between Land Surface Temperature (LST and Land Use Land Cover (LULC, MODIS eight-day interval LST data for the months of June, July and August from 2002 to 2012 and the Corine Land Cover (CLC database were used. Due to similarities in the behavior of surface temperature of different CLCs, some classes were reclassified and combined to form two major, rather simplified, homogenized classes: one of built-up area and one of urban vegetation. The homogenized map was merged with the MODIS eight-day interval LST data to compute the relationship between them. The results revealed that (i the cooling effect accrued from urban vegetation tended to be non-linear; and (ii a remarkable and stronger cooling effect in terms of LST was identified in regions where the proportion of vegetation cover was between seventy and almost eighty percent per square kilometer. The results also demonstrated that LST within urban vegetation was affected by the temperature of the surrounding built-up and that during the well-known European 2003 heat wave, suburb areas were cooler from the core of the urbanized region. This study concluded that the optimum green space for obtaining the lowest temperature is a non-linear trend. This could support urban planning strategies to facilitate appropriate applications to mitigate heat-stress in urban area.

  8. Linking Satellite Derived Land Surface Temperature with Cholera: A Case Study for South Sudan

    Science.gov (United States)

    Aldaach, H. S. V.; Jutla, A.; Akanda, A. S.; Colwell, R. R.

    2014-12-01

    A sudden onset of cholera in South Sudan, in April 2014 in Northern Bari in Juba town resulted in more than 400 cholera cases after four weeks of initial outbreak with a case of fatality rate of CFR 5.4%. The total number of reported cholera cases for the period of April to July, 2014 were 5,141 including 114 deaths. With the limited efficacy of cholera vaccines, it is necessary to develop mechanisms to predict cholera occurrence and thereafter devise intervention strategies for mitigating impacts of the disease. Hydroclimatic processes, primarily precipitation and air temperature are related to epidemic and episodic outbreak of cholera. However, due to coarse resolution of both datasets, it is not possible to precisely locate the geographical location of disease. Here, using Land Surface Temperature (LST) from MODIS sensors, we have developed an algorithm to identify regions susceptible for cholera. Conditions for occurrence of cholera were detectable at least one month in advance in South Sudan and were statistically sensitive to hydroclimatic anomalies of land surface and air temperature, and precipitation. Our results indicate significant spatial and temporal averaging required to infer usable information from LST over South Sudan. Preliminary results that geographically location of cholera outbreak was identifiable within 1km resolution of the LST data.

  9. Neighborhood Landscape Spatial Patterns and Land Surface Temperature: An Empirical Study on Single-Family Residential Areas in Austin, Texas.

    Science.gov (United States)

    Kim, Jun-Hyun; Gu, Donghwan; Sohn, Wonmin; Kil, Sung-Ho; Kim, Hwanyong; Lee, Dong-Kun

    2016-09-02

    Rapid urbanization has accelerated land use and land cover changes, and generated the urban heat island effect (UHI). Previous studies have reported positive effects of neighborhood landscapes on mitigating urban surface temperatures. However, the influence of neighborhood landscape spatial patterns on enhancing cooling effects has not yet been fully investigated. The main objective of this study was to assess the relationships between neighborhood landscape spatial patterns and land surface temperatures (LST) by using multi-regression models considering spatial autocorrelation issues. To measure the influence of neighborhood landscape spatial patterns on LST, this study analyzed neighborhood environments of 15,862 single-family houses in Austin, Texas, USA. Using aerial photos, geographic information systems (GIS), and remote sensing, FRAGSTATS was employed to calculate values of several landscape indices used to measure neighborhood landscape spatial patterns. After controlling for the spatial autocorrelation effect, results showed that larger and better-connected landscape spatial patterns were positively correlated with lower LST values in neighborhoods, while more fragmented and isolated neighborhood landscape patterns were negatively related to the reduction of LST.

  10. Neighborhood Landscape Spatial Patterns and Land Surface Temperature: An Empirical Study on Single-Family Residential Areas in Austin, Texas

    Directory of Open Access Journals (Sweden)

    Jun-Hyun Kim

    2016-09-01

    Full Text Available Rapid urbanization has accelerated land use and land cover changes, and generated the urban heat island effect (UHI. Previous studies have reported positive effects of neighborhood landscapes on mitigating urban surface temperatures. However, the influence of neighborhood landscape spatial patterns on enhancing cooling effects has not yet been fully investigated. The main objective of this study was to assess the relationships between neighborhood landscape spatial patterns and land surface temperatures (LST by using multi-regression models considering spatial autocorrelation issues. To measure the influence of neighborhood landscape spatial patterns on LST, this study analyzed neighborhood environments of 15,862 single-family houses in Austin, Texas, USA. Using aerial photos, geographic information systems (GIS, and remote sensing, FRAGSTATS was employed to calculate values of several landscape indices used to measure neighborhood landscape spatial patterns. After controlling for the spatial autocorrelation effect, results showed that larger and better-connected landscape spatial patterns were positively correlated with lower LST values in neighborhoods, while more fragmented and isolated neighborhood landscape patterns were negatively related to the reduction of LST.

  11. Estimation of Land Surface Temperature for the Quantitative Analysis of Land Cover of Lower Areas of Sindh to Assess the Impacts of Climate Variability

    Science.gov (United States)

    Qaisar, Maha

    2016-07-01

    Due to the present land use practices and climate variability, drastic shifts in regional climate and land covers are easily seen and their future reduction and gain are too well predicted. Therefore, there is an increasing need for data on land-cover changes at narrow and broad spatial scales. In this study, a remote sensing-based technique for land-cover-change analysis is applied to the lower Sindh areas for the last decade. Landsat satellite products were analyzed on an alternate yearly basis, from 1990 to 2016. Then Land-cover-change magnitudes were measured and mapped for alternate years. Land Surface Temperature (LST) is one of the critical elements in the natural phenomena of surface energy and water balance at local and global extent. However, LST was computed by using Landsat thermal bands via brightness temperature and a vegetation index. Normalized difference vegetation index (NDVI) was interpreted and maps were achieved. LST reflected NDVI patterns with complexity of vegetation patterns. Along with this, Object Based Image Analysis (OBIA) was done for classifying 5 major classes of water, vegetation, urban, marshy lands and barren lands with significant map layouts. Pakistan Meteorological Department provided the climate data in which rainfall, temperature and air temperature are included. Once the LST and OBIA are performed, overlay analysis was done to correlate the results of LST with OBIA and LST with meteorological data to ascertain the changes in land covers due to increasing centigrade of LST. However, satellite derived LST was also correlated with climate data for environmental analysis and to estimate Land Surface Temperature for assessing the inverse impacts of climate variability. This study's results demonstrate the land-cover changes in Lower Areas of Sindh including the Indus Delta mostly involve variations in land-cover conditions due to inter-annual climatic variability and temporary shifts in seasonality. However it is too concluded

  12. The WATERMED field experiment: validation of the AATSR LST product with in situ measurements

    Science.gov (United States)

    Noyes, E.; Soria, G.; Sobrino, J.; Remedios, J.; Llewellyn-Jones, D.; Corlett, G.

    The Advanced Along-Track Scanning Radiometer (AATSR) onboard ESA's Envisat Satellite, is the third in a series of a precision radiometers designed to measure Sea Surface Temperature (SST) with accuracies of better than ± 0.3 K (within 1-sigma limit). Since its launch in March 2001, a prototype AATSR Land Surface Temperature (LST) product has been produced for validation purposes only, with the product becoming operational from mid-2004. The (A)ATSR instrument design is unique in that it has both a nadir- and a forward-view, allowing the Earth's surface to be viewed along two different atmospheric path lengths, thus enabling an improved atmospheric correction to be made when retrieving surface temperature. It also uses an innovative and exceptionally stable on-board calibration system for its infrared channels, which, together with actively cooled detectors, gives extremely high radiometric sensitivity and precision. In this presentation, results from a comparison of the prototype LST product with ground-based measurements obtained at the WATERMED (WATer use Efficiency in natural vegetation and agricultural areas by Remote sensing in the MEDiterranean basin) field site near Marrakech, Morocco, are presented. The comparison shows that the AATSR has a positive bias of + 1.5 K, with a standard deviation of 0.7 K, indicating that the product is operating within the target specification (± 2.5 K) over the WATERMED field site. However, several anomalous validation points were observed during the analysis and we will discuss possible reasons for the occurrence of these data, including their coincidence with the presence of an Envisat blanking pulse (indicating the presence of a radar pulse at the time of AATSR pixel integration). Further investigation into this matter is required as previous investigations have always indicated that the presence of a payload radar pulse does not have any effect on (A)ATSR data quality.

  13. Analysis of multi-temporal landsat satellite images for monitoring land surface temperature of municipal solid waste disposal sites.

    Science.gov (United States)

    Yan, Wai Yeung; Mahendrarajah, Prathees; Shaker, Ahmed; Faisal, Kamil; Luong, Robin; Al-Ahmad, Mohamed

    2014-12-01

    This studypresents a remote sensing application of using time series Landsat satellite images for monitoring the Trail Road and Nepean municipal solid waste (MSW) disposal sites in Ottawa, Ontario, Canada. Currently, the Trail Road landfill is in operation; however, during the 1960s and 1980s, the city relied heavily on the Nepean landfill. More than 400 Landsat satellite images were acquired from the US Geological Survey (USGS) data archive between 1984 and 2011. Atmospheric correction was conducted on the Landsat images in order to derive the landfill sites' land surface temperature (LST). The findings unveil that the average LST of the landfill was always higher than the immediate surrounding vegetation and air temperature by 4 to 10 °C and 5 to 11.5 °C, respectively. During the summer, higher differences of LST between the landfill and its immediate surrounding vegetation were apparent, while minima were mostly found in fall. Furthermore, there was no significant temperature difference between the Nepean landfill (closed) and the Trail Road landfill (active) from 1984 to 2007. Nevertheless, the LST of the Trail Road landfill was much higher than the Nepean by 15 to 20 °C after 2007. This is mainly due to the construction and dumping activities (which were found to be active within the past few years) associated with the expansion of the Trail Road landfill. The study demonstrates that the use of the Landsat data archive can provide additional and viable information for the aid of MSW disposal site monitoring.

  14. Assessing the Impacts of Urbanization-Associated Land Use/Cover Change on Land Surface Temperature and Surface Moisture: A Case Study in the Midwestern United States

    Directory of Open Access Journals (Sweden)

    Yitong Jiang

    2015-04-01

    Full Text Available Urbanization-associated land use and land cover (LULC changes lead to modifications of surface microclimatic and hydrological conditions, including the formation of urban heat islands and changes in surface runoff pattern. The goal of the paper is to investigate the changes of biophysical variables due to urbanization induced LULC changes in Indianapolis, USA, from 2001 to 2006. The biophysical parameters analyzed included Land Surface Temperature (LST, fractional vegetation cover, Normalized Difference Water Index (NDWI, impervious fractions evaporative fraction, and soil moisture. Land cover classification and changes and impervious fractions were obtained from the National Land Cover Database of 2001 and 2006. The Temperature-Vegetation Index (TVX space was created to analyze how these satellite-derived biophysical parameters change during urbanization. The results showed that the general trend of pixel migration in response to the LULC changes was from the areas of low temperature, dense vegetation cover, and high surface moisture conditions to the areas of high temperature, sparse vegetation cover, and low surface moisture condition in the TVX space. Analyses of the T-soil moisture and T-NDWI spaces revealed similar changed patterns. The rate of change in LST, vegetation cover, and moisture varied with LULC type and percent imperviousness. Compared to conversion from cultivated to residential land, the change from forest to commercial land altered LST and moisture more intensively. Compared to the area changed from cultivated to residential, the area changed from forest to commercial altered 48% more in fractional vegetation cover, 71% more in LST, and 15% more in soil moisture Soil moisture and NDWI were both tested as measures of surface moisture in the urban areas. NDWI was proven to be a useful measure of vegetation liquid water and was more sensitive to the land cover changes comparing to soil moisture. From a change forest to

  15. Disaggregation of remotely sensed land surface temperature: A new dynamic methodology

    Science.gov (United States)

    Zhan, Wenfeng; Huang, Fan; Quan, Jinling; Zhu, Xiaolin; Gao, Lun; Zhou, Ji; Ju, Weimin

    2016-09-01

    The trade-off between the spatial and temporal resolutions of satellite-derived land surface temperature (LST) gives birth to disaggregation of LST (DLST). However, the concurrent enhancement of the spatiotemporal resolutions of LST remains difficult, and many studies disregard the conservation of thermal radiance between predisaggregated and postdisaggregated LSTs. Here we propose a new dynamic methodology to enhance concurrently the spatiotemporal resolutions of satellite-derived LSTs. This methodology conducts DLST by the controlling parameters of the temperature cycle models, i.e., the diurnal temperature cycle (DTC) model and annual temperature cycle (ATC) model, rather than directly by the LST. To achieve the conservation of thermal radiance between predisaggregated and postdisaggregated LSTs, herein we incorporate a modulation procedure that adds temporal thermal details to coarse resolution LSTs rather than straightforwardly transforms fine-resolution scaling factors into LSTs. Indirect validations at the same resolution show that the mean absolute error (MAE) between the predicted and reference LSTs is around 1.0 K during a DTC; the associated MAE is around 2.0 K during an ATC, but this relatively lower accuracy is due more to the uncertainty of the ATC model. The upscaling validations indicate that the MAE is around 1.0 K and the normalized mean absolute error is around 0.3. Comparisons between the DTC- and ATC-based DLST illustrate that the former retains a higher accuracy, but the latter holds a higher flexibility on days when background low-resolution LSTs are unavailable. This methodology alters the static DLST into a dynamic way, and it is able to provide temporally continuous fine-resolution LSTs; it will also promote the design of DLST methods for the generation of high-quality LSTs.

  16. Use of remotely sensed land surface temperature as a proxy for air temperatures at high elevations: Findings from a 5000 m elevational transect across Kilimanjaro

    Science.gov (United States)

    Pepin, N. C.; Maeda, E. E.; Williams, R.

    2016-09-01

    High elevations are thought to be warming more rapidly than lower elevations, but there is a lack of air temperature observations in high mountains. This study compares instantaneous values of land surface temperature (10:30/22:30 and 01:30/13:30 local solar time) as measured by Moderate Resolution Imaging Spectroradiometer MOD11A2/MYD11A2 at 1 km resolution from the Terra and Aqua platforms, respectively, with equivalent screen-level air temperatures (in the same pixel). We use a transect of 22 in situ weather stations across Kilimanjaro ranging in elevation from 990 to 5803 m, one of the biggest elevational ranges in the world. There are substantial differences between LST and Tair, sometimes up to 20°C. During the day/night land surface temperature tends to be higher/lower than Tair. LST-Tair differences (ΔT) show large variance, particularly during the daytime, and tend to increase with elevation, particularly on the NE slope which faces the morning Sun. Differences are larger in the dry seasons (JF and JJAS) and reduce in cloudy seasons. Healthier vegetation (as measured by normalized difference vegetation index) and increased humidity lead to reduced daytime surface heating above air temperature and lower ΔT, but these relationships weaken with elevation. At high elevations transient snow cover cools LST more than Tair. The predictability of ΔT therefore reduces. It will therefore be challenging to use satellite data at high elevations as a proxy for in situ air temperatures in climate change assessments, especially for daytime Tmax. ΔT is smaller and more consistent at night, so it will be easier to use LST to monitor changes in Tmin.

  17. Temperature-based and radiance-based validations of the V5 MODIS land surface temperature product

    Science.gov (United States)

    Coll, CéSar; Wan, Zhengming; Galve, Joan M.

    2009-10-01

    The V5 level 2 land surface temperature (LST) product of the Moderate Resolution Imaging Spectroradiometer (MODIS) was validated over homogeneous rice fields in Valencia, Spain, and the Hainich forest in Germany. For the Valencia site, ground LST measurements were compared with the MOD11_L2 product in the conventional temperature-based (T-based) method. We also applied the alternative radiance-based (R-based) method, with in situ LSTs calculated from brightness temperatures in band 31 through radiative transfer simulations using temperature and water vapor profiles and surface emissivity data. At the Valencia site, profiles were obtained from local radiosonde measurements and from National Centers for Environmental Prediction (NCEP) data. The R-based method was applied at the Hainich site using radiosonde profiles from a nearby sounding station and NCEP profiles. The T-based validation showed average bias (MODIS minus ground) of -0.3 K, standard deviation of 0.6 K and root mean square error (RMSE) of ±0.7 K. For the R-based method, the quality of the atmospheric profiles was assessed through the difference δ(T31-T32) between the actual MODIS and the profile-based calculated brightness temperature difference in bands 31 and 32. For the cases where -0.3 K studied. The good performance of the R-based method opens the possibility for a more complete validation including heterogeneous surfaces where the T-based method is not feasible.

  18. Assessment of methods for land surface temperature retrieval from Landsat-5 TM images applicable to multiscale tree-grass ecosystem modeling

    DEFF Research Database (Denmark)

    Vlassova, Lidia; Perez-Cabello, Fernando; Nieto Solana, Hector;

    2014-01-01

    Land Surface Temperature (LST) is one of the key inputs for Soil-Vegetation-Atmosphere transfer modeling in terrestrial ecosystems. In the frame of BIOSPEC (Linking spectral information at different spatial scales with biophysical parameters of Mediterranean vegetation in the context of global ch...

  19. Assessment of methods for land surface temperature retrieval from Landsat-5 TM images applicable to multiscale tree-grass ecosystem modeling

    DEFF Research Database (Denmark)

    Vlassova, Lidia; Perez-Cabello, Fernando; Nieto Solana, Hector;

    2014-01-01

    Land Surface Temperature (LST) is one of the key inputs for Soil-Vegetation-Atmosphere transfer modeling in terrestrial ecosystems. In the frame of BIOSPEC (Linking spectral information at different spatial scales with biophysical parameters of Mediterranean vegetation in the context of global...

  20. Satellite Observations of Wind Farm Impacts on Nocturnal Land Surface Temperature in Iowa

    Directory of Open Access Journals (Sweden)

    Ronald A. Harris

    2014-12-01

    Full Text Available Wind farms (WFs are believed to have an impact on lower boundary layer meteorology. A recent study examined satellite-measured land surface temperature data (LST and found a local nighttime warming effect attributable to a group of four large WFs in Texas. This study furthers their work by investigating the impacts of five individual WFs in Iowa, where the land surface properties and climate conditions are different from those in Texas. Two methods are used to assess WF impacts: first, compare the spatial coupling between the LST changes (after turbine construction versus before and the geographic layouts of the WFs; second, quantify the LST difference between the WFs and their immediate surroundings (non-WF areas. Each WF shows an irrefutable nighttime warming signal relative to the surrounding areas after their turbines were installed, and these warming signals are generally coupled with the geographic layouts of the wind turbines, especially in summer. This study provides further observational evidence that WFs can cause surface warming at nighttime, and that such a signal can be detected by satellite-based sensors.

  1. A Practical Split-Window Algorithm for Retrieving Land Surface Temperature from Landsat-8 Data and a Case Study of an Urban Area in China

    Directory of Open Access Journals (Sweden)

    Meijun Jin

    2015-04-01

    Full Text Available This paper proposes a practical split-window algorithm (SWA for retrieving land surface temperature (LST from Landsat-8 Thermal Infrared Sensor (TIRS data. This SWA has a universal applicability and a set of parameters that can be applied when retrieving LSTs year-round. The atmospheric transmittance and the land surface emissivity (LSE, the essential SWA input parameters, of the Landsat-8 TIRS data are determined in this paper. We also analysed the error sensitivity of these SWA input parameters. The accuracy evaluation of the proposed SWA in this paper was conducted using the software MODTRAN 4.0. The root mean square error (RMSE of the simulated LST using the mid-latitude summer atmospheric profile is 0.51 K, improving on the result of 0.93 K from Rozenstein (2014. Among the 90 simulated data points, the maximum absolute error is 0.99 °C, and the minimum absolute error is 0.02 °C. Under the Tropical model and 1976 US standard atmospheric conditions, the RMSE of the LST errors are 0.70 K and 0.63 K, respectively. The accuracy results indicate that the SWA provides an LST retrieval method that features not only high accuracy but also a certain universality. Additionally, the SWA was applied to retrieve the LST of an urban area using two Landsat-8 images. The SWA presented in this paper should promote the application of Landsat-8 data in the study of environmental evolution.

  2. GODAE, SFCOBS - Surface Temperature Observations

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — GODAE, SFCOBS - Surface Temperature Observations: Ship, fixed/drifting buoy, and CMAN in-situ surface temperature. Global Telecommunication System (GTS) Data. The...

  3. Validation of Land Surface Temperature products in arid climate regions with permanent in-situ measurements

    Science.gov (United States)

    Goettsche, F.; Olesen, F.; Trigo, I.; Hulley, G. C.

    2013-12-01

    Land Surface Temperature (LST) is operationally obtained from several space-borne sensors, e.g. from the Spinning Enhanced Visible and Infrared Imager (SEVIRI) onboard Meteosat Second Generation (MSG) by the Land Surface Analysis - Satellite Application Facility (LSA-SAF) and from the Moderate Resolution Imaging Spectroradiometer (MODIS) on EOS-Terra by the MODIS Land Team. The relative accuracy of LST products can be assessed by cross-validating different products. Alternatively, the so-called 'radiance based validation' can be used to compare satellite-retrieved LST with results from radiative transfer models: however, this requires precise a priori knowledge of land surface emissivity (LSE) and atmospheric conditions. Ultimately, in-situ measurements (';ground truth') are needed for validating satellite LST&E products. Therefore, the LST product derived by LSA-SAF is validated with independent in-situ measurements (';temperature based validation') at permanent validation stations located in different climate regions on the SEVIRI disk. In-situ validation is largely complicated by the spatial scale mismatch between satellite sensors and ground based sensors, i.e. areas observed by ground radiometers usually cover about 10 m2, whereas satellite measurements in the thermal infrared typically cover between 1 km2 and 100 km2. Furthermore, an accurate characterization of the surface is critical for all validation approaches, but particularly over arid regions, as shown by in-situ measurements revealing that LSE products can be wrong by more than 3% [1]. The permanent stations near Gobabeb (Namibia; hyper-arid desert climate) and Dahra (Senegal; hot-arid steppe-prairie climate) are two of KIT's four dedicated LST validation stations. Gobabeb station is located on vast and flat gravel plains (several 100 km2), which are mainly covered by coarse gravel, sand, and desiccated grass. The gravel plains are highly homogeneous in space and time, which makes them ideal for

  4. Effect of impervious surface area and vegetation changes on mean ...

    African Journals Online (AJOL)

    adeniyi adeyemi

    1 Department of Geography, Geoinformatics and Meteorology, University of Pretoria, .... temperature image to Land Surface Temperature (LST) using the equation ..... For example, the study presented the extent of formation urban heat island ...

  5. Parametrization of Land Surface Temperature Fields with Optical and Microwave Remote Sensing in Brazil's Atlantic Forest

    Science.gov (United States)

    McDonald, K. C.; Khan, A.; Carnaval, A. C.

    2016-12-01

    Brazil is home to two of the largest and most biodiverse ecosystems in the world, primarily encompassed in forests and wetlands. A main region of interest in this project is Brazil's Atlantic Forest (AF). Although this forest is only a fraction of the size of the Amazon rainforest, it harbors significant biological richness, making it one of the world's major hotspots for biodiversity. The AF is located on the East to Southeast region of Brazil, bordering the Atlantic Ocean. As luscious and biologically rich as this region is, the area covered by the Atlantic Forest has been diminishing over past decades, mainly due to human influences and effects of climate change. We examine 1 km resolution Land Surface Temperature (LST) data from NASA's Moderate-resolution Imaging Spectroradiometer (MODIS) combined with 25 km resolution radiometric temperature derived from NASA's Advanced Microwave Scanning Radiometer on EOS (AMSR-E) to develop a capability employing both in combination to assess LST. Since AMSR-E is a microwave remote sensing instrument, products derived from its measurements are minimally effected by cloud cover. On the other hand, MODIS data are heavily influenced by cloud cover. We employ a statistical downscaling technique to the coarse-resolution AMSR-E datasets to enhance its spatial resolution to match that of MODIS. Our approach employs 16-day composite MODIS LST data in combination with synergistic ASMR-E radiometric brightness temperature data to develop a combined, downscaled dataset. Our goal is to use this integrated LST retrieval with complementary in situ station data to examine associated influences on regional biodiversity

  6. Air temperature field distribution estimations over a Chinese mega-city using MODIS land surface temperature data: the case of Shanghai

    Institute of Scientific and Technical Information of China (English)

    Weichun MA; Liguo ZHOU; Hao ZHANG; Yan ZHANG; Xiaoyan DAI

    2016-01-01

    The capability of obtaining spatially distributed air temperature data from remote sensing measurements is an improvement for many environmental applications focused on urban heat island,carbon emissions,climate change,etc.This paper is based on the MODIS/Terra and Aqua data utilized to study the effect of the urban atmospheric heat island in Shanghai,China.The correlation between retrieved MODIS land surface temperature (LST) and air temperature measured at local weather stations was initially studied at different temporal and spatial scales.Secondly,the air temperature data with spatial resolutions of 250 m and 1 km were estimated from MODIS LST data and in-situ measured air temperature.The results showed that there is a slightly higher correlation between air temperature and MODIS LST at a 250 m resolution in spring and autumn on an annual scale than observed at a 1 km resolution.Although the distribution pattern of the air temperature thermal field varies in different seasons,the urban heat island (UHI) in Shanghai is characterized by a distribution pattern of multiple centers,with the central urban area as the primary center and the built-up regions in each district as the subcenters.This study demonstrates the potential not only for estimating the distribution of the air temperature thermal field from MODIS LST with 250 m resolution in spring and autumn in Shanghai,but also for providing scientific and effective methods for monitoring and studying UHI effect in a Chinese mega-city such as Shanghai.

  7. Land Surface Temperature retrieval from Sentinel 2 and 3 Missions: a conceptual framework

    Science.gov (United States)

    Sobrino, J. A.; Jimenez-Muñoz, J. C.; Ruescas, A.; Brockmann, C.; Heckel, A.; North, P. R. J.; Remedios, J. J.; Darren, G.; Merchant, C.; Berger, M.; Soria, G.; Danne, O.

    2012-04-01

    Land Surface Temperature (LST) is one of the key parameters in the physics of land-surface processes on regional and global scales, combining the results of all the surface-atmosphere interactions and energy fluxes between the surface and the atmosphere. Because of the strong heterogeneity in land surface characteristics such as vegetation, topography and soil physical properties, LST changes rapidly in space as well as in time. An adequate characterization of LST distribution and its temporal evolution, therefore, requires measurements with detailed spatial and temporal frequencies. With the advent of the ESA's Sentinel 2 and 3 series of satellites a unique opportunity exists to go beyond the current state of the art of single instrument algorithms. In this work we explore the synergistic use of future MSI instrument on board Sentinel-2 platform and OLCI/SLSTR instruments on board Sentinel-3 platform in order to improve LST products currently derived from the single AATSR instrument on board the ENVISAT satellite. For this purpose, the high spatial resolution data from Sentinel2/MSI will be used for a good characterization of the land surface sub-pixel heterogeneity, in particular for a precise parameterization of surface emissivity using a land cover map and spectral mixture techniques. On the other hand, the high spectral resolution of OLCI instrument, suitable for a better characterization of the atmosphere, along with the dual-view available in the SLTSR instrument, will allow a better atmospheric correction through improved aerosol/water vapor content retrievals and the implementation of novel cloud screening procedures. Effective emissivity and atmospheric corrections will allow accurate LST retrievals using the SLTSR thermal bands by developing a synergistic split-window/dual-angle algorithm. ENVISAT MERIS and AATSR instruments and different high spatial resolution data (Landsat/TM, Proba/CHRIS, Terra/ASTER) will be used as a benchmark for the future OLCI

  8. A Case Study of Land-Surface-Temperature Impact from Large-Scale Deployment of Wind Farms in China from Guazhou

    Directory of Open Access Journals (Sweden)

    Rui Chang

    2016-09-01

    Full Text Available The wind industry in China has experienced a rapid expansion of capacity after 2009, especially in northwestern China, where the China’s first 10 GW-level wind power project is located. Based on the analysis from Moderate Resolution Imaging Spectroradiometer (MODIS land surface temperature (LST data for period of 2005–2012, the potential LST impacts from the large-scale wind farms in northwestern China’s Guazhou are investigated in this paper. It shows the noticeable nighttime warming trends on LST over the wind farm areas relative to the nearby non-wind-farm regions in Guazhou and that the nighttime LST warming is strongest in summer (0.51 °C/8 years, followed by autumn (0.48 °C/8 years and weakest in winter (0.38 °C/8 years with no warming trend observed in spring. Meanwhile, the quantitative comparison results firstly indicate that the nighttime LST warming from wind farm areas are less than those from the urban areas in this work.

  9. Effect of emissivity uncertainty on surface temperature retrieval over urban areas: Investigations based on spectral libraries

    Science.gov (United States)

    Chen, Feng; Yang, Song; Su, Z.; Wang, Kai

    2016-04-01

    Land surface emissivity (LSE) is a prerequisite for retrieving land surface temperature (LST) through single channel methods. According to error model, a 0.01 (1%) uncertainty of LSE may result in a 0.5 K error in LST under a moderate condition, while an obvious error (approximately 1 K) is possible under a warmer and less humid situation. Significant emissivity variations are presented among the anthropogenic materials in three spectral libraries, which raise a critical question that whether urban LSE can be estimated accurately to meet the needs for LST retrieval. Methods widely used for urban LSE estimation are investigated, including the classification-based method, the spectral-index based method, and the linear spectral mixture model (LSMM). Results indicate that the classification-based method may not be effectively applicable for urban LSE estimation, due mainly to the insignificant relation between the short-wave multispectral reflectance and the long-wave thermal emissivity shown by the spectra. Compared with the classification-based method, the LSMM shows relatively more accurate predictions, whereas, the performance of the LSMM largely depends on the determination of endmembers. Obvious uncertainties in LSE estimation likely appear if endmembers are determined improperly. Increasing the spectra for endmembers is a practical and beneficial means for LSMM when there is not a priori knowledge, which emphasizes the necessity of building a comprehensive spectral library of urban materials. Furthermore, the LST retrieval from a single channel of Landsat 8 is more challenging as compared with the retrieval from the channels of its predecessors-Landsat 4/5/7.

  10. Spatial Downscaling Research of Satellite Land Surface Temperature Based on Spectral Normalization Index

    Directory of Open Access Journals (Sweden)

    LI Xiaojun

    2017-03-01

    Full Text Available Aiming at the problem that the spatial and temporal resolution of land surface temperature (LST have the contradiction with each other, a new downscaling model was put forward, based on the TsHARP(an algorithm for sharpening thermal imagery downscaling method, this research makes improvements by selecting the better correlation of spectral index(normalized difference vegetation index, NDVI; normalized difference build-up index, NDBI; modified normalized difference water index, MNDWI; enhanced bare soil index, EBSI with LST, i.e., replaces the original NDVI with new spectral index according to the different surface land-cover types, to assess the accuracy of each downscaling method based on qualitative and quantitative analysis with synchronous Landsat 8 TIRS LST data. The results show that both models could effectively enhance the spatial resolution while simultaneously preserving the characteristics and spatial distribution of the original 1 km MODIS LST image, and also eliminate the “mosaic” effect in the original 1 km image, both models were proved to be effective and applicable in our study area; global scale analysis shows that the new model (RMSE:1.635℃ is better than the TsHARP method (RMSE:2.736℃ in terms of the spatial variability and accuracy of the results; the different land-cover types of downscaling statistical analysis shows that the TsHARP method has poor downscaling results in the low vegetation coverage area, especially for the bare land and building-up area(|MBE|>3℃, the new model has obvious advantages in the description of the low vegetation coverage area. Seasonal analysis shows that the downscaling results of two models in summer and autumn are superior to those in spring and winter, the new model downscaling results are better than the TsHARP method in the four seasons, in which the spring and winter downscaling improvement is better than summer and autumn.

  11. Landcover Change, Land Surface Temperature, Surface Albedo and Topography in the Plateau Region of North-Central Nigeria

    Directory of Open Access Journals (Sweden)

    Shakirudeen Odunuga

    2015-04-01

    Full Text Available This study assessed the change in some environmental parameters in the Plateau region of North-Central Nigeria (Barakinladi, Jos, and Kafachan environs using the nexus of landcover change, land surface temperature, surface albedo, and topography. The study employed both remote sensing and statistical techniques for the period between 1986 and 2014 to analyze the dynamics between and within these environmental variables. In Barakinladi, the built up landcover change is highest (increasing from 39.53% to 47.59% between 1986 and 2014; LST ranges from 19.09 °C to 38.59 °C in 1986 and from 22.68 °C and 41.68 °C in 2014; and the albedo ranges between 0.014 and 0.154 in 1986 and 0.017 and 0.248 in 2014. In Jos, the built-up landcover occupied 34.26% in 1986 and 36.67% in 2014; LST values range between 20.83 °C and 41.33 °C in 1986 and between 21.61 °C and 42.64 °C in 2014; and the albedo ranges between 0.003 and 0.211 in 1986 and 0.15 and 0.237 in 2014. In Kafachan area, the built up landcover occupied 32.95% in 1986 and 39.01% in 2014. Urbanization and agricultural activities, including animal grazing, were responsible for the gradual loss in vegetation and increasing average LST and albedo. The results also revealed that changing landcover and topography have a relationship with surface albedo and land surface temperature, thereby impacting significantly on ecosystem services delivered by the natural system.

  12. Cloud clearing techniques over land for land surface temperature retrieval from the Advanced Along Track Scanning Radiometer

    OpenAIRE

    Bulgin, C.E.; H. Sembhi; D. Ghent; Remedios, J.J.; Merchant, Christopher

    2014-01-01

    We present five new cloud detection algorithms over land based on dynamic threshold or Bayesian techniques, applicable to the Advanced Along Track Scanning Radiometer (AATSR) instrument and compare these with the standard threshold based SADIST cloud detection scheme. We use a manually classified dataset as a reference to assess algorithm performance and quantify the impact of each cloud detection scheme on land surface temperature (LST) retrieval. The use of probabilistic Bayesian cloud dete...

  13. Geothermal Heat Flux Assessment Using Remote Sensing Land Surface Temperature and Simulated Data. Case Studies at the Kenyan Rift and Yellowstone Geothermal Areas

    Science.gov (United States)

    Romaguera, M.; Vaughan, R. G.; Ettema, J.; Izquierdo-Verdiguier, E.; Hecker, C.; van der Meer, F. D.

    2015-12-01

    In this work we propose an innovative approach to assess the geothermal heat flux anomalies in the regions of the Kenyan Rift and the Yellowstone geothermal areas. The method is based on the land surface temperature (LST) differences obtained between remote sensing data and land surface model simulations. The hypothesis is that the model simulations do not account for the subsurface geothermal heat source in the formulation. Remote sensing of surface emitted radiances is able to detect at least the radiative portion of the geothermal signal that is not in the models. Two methods were proposed to assess the geothermal component of LST (LSTgt) based on the aforementioned hypothesis: a physical model and a data mining approach. The LST datasets were taken from the Land Surface Analysis Satellite Application Facilities products over Africa and the Copernicus Programme for North America, at a spatial resolution of 3-5 km. These correspond to Meteosat Second Generation and Geostationary Operational Environmental Satellite system satellites data respectively. The Weather Research and Forecasting model was used to simulate LST based on atmospheric and surface characteristics using the Noah land surface model. The analysis was carried out for a period of two months by using nighttime acquisitions. Higher spatial resolution images from the Advanced Spaceborne Thermal Emission and Reflection Radiometer data were also used on the Kenyan area to produce similar outputs employing existing methods. The comparison of the results from both methods and areas illustrated the potential of the data and methodologies for geothermal applications.

  14. GISS Surface Temperature Analysis

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The GISTEMP dataset is a global 2x2 gridded temperature anomaly dataset. Temperature data is updated around the middle of every month using current data files from...

  15. Using dual temperature difference two source energy balance model and MODIS data to estimate surface energy fluxes at regional scales in northern latitudes

    Science.gov (United States)

    Guzinski, R.; Anderson, M.; Kustas, W.; Nieto, H.; Sandholt, I.

    2012-04-01

    A Two Source Energy Balance (TSEB) thermal-based modeling scheme has previously been used to successfully estimate surface latent and sensible heat fluxes at regional to continental scales with the help of satellite surface radiometric temperature observations. The Dual Temperature Difference (DTD) model introduced a simple methodology to address the sensitivity of the thermal-based energy balance models to the absolute measurement of land surface temperature (LST), which when derived with the help of satellites can have errors of several degrees. The original DTD model formulation required an early morning LST observation (1 hour after local sunrise) when fluxes were minimal followed by another LST observations later in the morning or afternoon and so was limited in use to data provided by geostationary satellites having high temporal resolution. This, however, made it unsuitable for areas at higher latitudes, such as northern Eurasia and northern North America. In this poster we present a number of modifications to the DTD model which allows it to exploit the day and night LST observations by the MODIS sensor aboard the Terra and Aqua polar orbiting satellites. Firstly, we look at whether taking the first LST observation around the time of Aqua's night overpass, when fluxes are small but not insignificant, would greatly affect the accuracy of the model. Secondly, we consider the issues directly related to using the MODIS sensor to measure the LST. This includes different view zenith angles of the day and night LST observations, the two observations possibly coming from the two different satellites and the accuracy of the instrument itself. We also evaluate two approaches for estimating αPT, the Priestley-Taylor parameter used in the TSEB modeling scheme to estimate heat fluxes of the vegetation canopy, to improve the performance of the model in coniferous and deciduous forests. The first approach estimates αPT based on tree height, while the second uses

  16. Evaluation of ASTER-Like Daily Land Surface Temperature by Fusing ASTER and MODIS Data during the HiWATER-MUSOEXE

    Directory of Open Access Journals (Sweden)

    Guijun Yang

    2016-01-01

    Full Text Available Land surface temperature (LST is an important parameter that is highly responsive to surface energy fluxes and has become valuable to many disciplines. However, it is difficult to acquire satellite LSTs with both high spatial and temporal resolutions due to tradeoffs between them. Thus, various algorithms/models have been developed to enhance the spatial or the temporal resolution of thermal infrared (TIR data or LST, but rarely both. The Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM is the widely-used data fusion algorithm for Landsat and MODIS imagery to produce Landsat-like surface reflectance. In order to extend the STARFM application over heterogeneous areas, an enhanced STARFM (ESTARFM approach was proposed by introducing a conversion coefficient and the spectral unmixing theory. The aim of this study is to conduct a comprehensive evaluation of the ESTARFM algorithm for generating ASTER-like daily LST by three approaches: simulated data, ground measurements and remote sensing products, respectively. The datasets of LST ground measurements, MODIS, and ASTER images were collected in an arid region of Northwest China during the first thematic HiWATER-Multi-Scale Observation Experiment on Evapotranspiration (MUSOEXE over heterogeneous land surfaces in 2012 from May to September. Firstly, the results of the simulation test indicated that ESTARFM could accurately predict background with temperature variations, even coordinating with small ground objects and linear ground objects. Secondly, four temporal ASTER and MODIS data fusion LSTs (i.e., predicted ASTER-like LST products were highly consistent with ASTER LST products. Here, the four correlation coefficients were greater than 0.92, root mean square error (RMSE reached about 2 K and mean absolute error (MAE ranged from 1.32 K to 1.73 K. Finally, the results of the ground measurement validation indicated that the overall accuracy was high (R2 = 0.92, RMSE = 0.77 K, and the

  17. Greenland ice sheet surface temperature, melt and mass loss: 2000-06

    Science.gov (United States)

    Hall, D.K.; Williams, R.S.; Luthcke, S.B.; DiGirolamo, N.E.

    2008-01-01

    A daily time series of 'clear-sky' surface temperature has been compiled of the Greenland ice sheet (GIS) using 1 km resolution moderate-resolution imaging spectroradiometer (MODIS) land-surface temperature (LST) maps from 2000 to 2006. We also used mass-concentration data from the Gravity Recovery and Climate Experiment (GRACE) to study mass change in relationship to surface melt from 2003 to 2006. The mean LST of the GIS increased during the study period by ???0.27??Ca-1. The increase was especially notable in the northern half of the ice sheet during the winter months. Melt-season length and timing were also studied in each of the six major drainage basins. Rapid (meltwater is flowing rapidly to the base of the ice sheet, causing acceleration of outlet glaciers, thus highlighting the metastability of parts of the GIS and the vulnerability of the ice sheet to air-temperature increases. If air temperatures continue to rise over Greenland, increased surface melt will play a large role in ice-sheet mass loss.

  18. Climate Variability in Coastal Ecosystems - Use of MODIS Land Surface and Sea Surface Temperature Observations

    Science.gov (United States)

    Chintalapati, S.; Lakshmi, V.

    2007-12-01

    The intertidal zone, with its complex blend of marine and terrestrial environments, is one of the intensively studied ecosystems, in understanding the effects of climate change on species abundance and distribution. As climatic conditions change, the geographic limits of the intertidal species will likely move towards more tolerable coastal conditions. Traditionally, understanding climate change effects through species physiologic response have involved use of in situ measurements and thermal engineering models. But these approaches are constrained by their data intensive requirements and may not be suitable for predicting change patterns relevant to large scale species distributions. Satellite remote sensing provides an alternate approach, given the regular global coverage at moderate spatial resolutions. The present study uses six years of land surface temperature (LST) and sea surface temperature (SST) data from MODIS/Terra instrument along various coastlines around the globe - East and West Coast US, Southern Africa, Northern Japan and New Zealand. Apart from the dominant annual cycle in LST and SST, the other seasonal cycles vary from dominant semi-annual cycles in lower latitudes to 1.5 and 2 year cycles at higher latitudes. The monthly anomalies show strong spatial structure at lower latitudes when compared to higher latitudes, with the exception of US east coast, where the spatial structure extended almost along the whole coastline, indicating strong regulation from the Gulf Stream. The patterns along different coast lines are consistent with the atmospheric and ocean circulation patterns existing at those regions. These results suggest that the climatology at the coastal regions can be adequately represented using satellite-based temperature data, thus enabling further research in understanding the effects of climate change on species abundance and distribution at larger scales.

  19. Impacts of urban and industrial development on Arctic land surface temperature in Lower Yenisei River Region.

    Science.gov (United States)

    Li, Z.; Shiklomanov, N. I.

    2015-12-01

    Urbanization and industrial development have significant impacts on arctic climate that in turn controls settlement patterns and socio-economic processes. In this study we have analyzed the anthropogenic influences on regional land surface temperature of Lower Yenisei River Region of the Russia Arctic. The study area covers two consecutive Landsat scenes and includes three major cities: Norilsk, Igarka and Dudingka. Norilsk industrial region is the largest producer of nickel and palladium in the world, and Igarka and Dudingka are important ports for shipping. We constructed a spatio-temporal interpolated temperature model by including 1km MODIS LST, field-measured climate, Modern Era Retrospective-analysis for Research and Applications (MERRA), DEM, Landsat NDVI and Landsat Land Cover. Those fore-mentioned spatial data have various resolution and coverage in both time and space. We analyzed their relationships and created a monthly spatio-temporal interpolated surface temperature model at 1km resolution from 1980 to 2010. The temperature model then was used to examine the characteristic seasonal LST signatures, related to several representative assemblages of Arctic urban and industrial infrastructure in order to quantify anthropogenic influence on regional surface temperature.

  20. A Study of Spatial Soil Moisture Estimation Using a Multiple Linear Regression Model and MODIS Land Surface Temperature Data Corrected by Conditional Merging

    Directory of Open Access Journals (Sweden)

    Chunggil Jung

    2017-08-01

    Full Text Available This study attempts to estimate spatial soil moisture in South Korea (99,000 km2 from January 2013 to December 2015 using a multiple linear regression (MLR model and the Terra moderate-resolution imaging spectroradiometer (MODIS land surface temperature (LST and normalized distribution vegetation index (NDVI data. The MODIS NDVI was used to reflect vegetation variations. Observed precipitation was measured using the automatic weather stations (AWSs of the Korea Meteorological Administration (KMA, and soil moisture data were recorded at 58 stations operated by various institutions. Prior to MLR analysis, satellite LST data were corrected by applying the conditional merging (CM technique and observed LST data from 71 KMA stations. The coefficient of determination (R2 of the original LST and observed LST was 0.71, and the R2 of corrected LST and observed LST was 0.95 for 3 selected LST stations. The R2 values of all corrected LSTs were greater than 0.83 for total 71 LST stations. The regression coefficients of the MLR model were estimated seasonally considering the five-day antecedent precipitation. The p-values of all the regression coefficients were less than 0.05, and the R2 values were between 0.28 and 0.67. The reason for R2 values less than 0.5 is that the soil classification at each observation site was not completely accurate. Additionally, the observations at most of the soil moisture monitoring stations used in this study started in December 2014, and the soil moisture measurements did not stabilize. Notably, R2 and root mean square error (RMSE in winter were poor, as reflected by the many missing values, and uncertainty existed in observations due to freezing and mechanical errors in the soil. Thus, the prediction accuracy is low in winter due to the difficulty of establishing an appropriate regression model. Specifically, the estimated map of the soil moisture index (SMI can be used to better understand the severity of droughts with the

  1. The Land Surface Temperature Impact to Land Cover Types

    Science.gov (United States)

    Ibrahim, I.; Abu Samah, A.; Fauzi, R.; Noor, N. M.

    2016-06-01

    Land cover type is an important signature that is usually used to understand the interaction between the ground surfaces with the local temperature. Various land cover types such as high density built up areas, vegetation, bare land and water bodies are areas where heat signature are measured using remote sensing image. The aim of this study is to analyse the impact of land surface temperature on land cover types. The objectives are 1) to analyse the mean temperature for each land cover types and 2) to analyse the relationship of temperature variation within land cover types: built up area, green area, forest, water bodies and bare land. The method used in this research was supervised classification for land cover map and mono window algorithm for land surface temperature (LST) extraction. The statistical analysis of post hoc Tukey test was used on an image captured on five available images. A pixel-based change detection was applied to the temperature and land cover images. The result of post hoc Tukey test for the images showed that these land cover types: built up-green, built up-forest, built up-water bodies have caused significant difference in the temperature variation. However, built up-bare land did not show significant impact at p<0.05. These findings show that green areas appears to have a lower temperature difference, which is between 2° to 3° Celsius compared to urban areas. The findings also show that the average temperature and the built up percentage has a moderate correlation with R2 = 0.53. The environmental implications of these interactions can provide some insights for future land use planning in the region.

  2. Temperature dependence of surface nanobubbles

    NARCIS (Netherlands)

    Berkelaar, R.P.; Seddon, James Richard Thorley; Zandvliet, Henricus J.W.; Lohse, Detlef

    2012-01-01

    The temperature dependence of nanobubbles was investigated experimentally using atomic force microscopy. By scanning the same area of the surface at temperatures from 51 °C to 25 °C it was possible to track geometrical changes of individual nanobubbles as the temperature was decreased.

  3. Modeling directional effects in land surface temperature derived from geostationary satellite data

    DEFF Research Database (Denmark)

    Rasmussen, Mads Olander

    This PhD-thesis investigates the directional effects in land surface temperature (LST) estimates from the SEVIRI sensor onboard the Meteosat Second Generation (MSG) satellites. The directional effects are caused by the land surface structure (i.e. tree size and shape) interacting with the changing...... sun-target-sensor geometry. The directional effects occur because the different surface components, e.g. tree canopies and bare soil surfaces, will in many cases have significantly different temperatures. Depending on the viewing angle, different fractions of each of the components will be viewed......; shaded and sunlit canopy and background, respectively. Given data on vegetation structure and density, the model estimates the fractions of the four components as well as the directional composite temperature in the view of a sensor, given the illumination and viewing geometry. The modeling results show...

  4. A comparison of radiometric correction techniques in the evaluation of the relationship between LST and NDVI in Landsat imagery.

    Science.gov (United States)

    Tan, Kok Chooi; Lim, Hwee San; Matjafri, Mohd Zubir; Abdullah, Khiruddin

    2012-06-01

    Atmospheric corrections for multi-temporal optical satellite images are necessary, especially in change detection analyses, such as normalized difference vegetation index (NDVI) rationing. Abrupt change detection analysis using remote-sensing techniques requires radiometric congruity and atmospheric correction to monitor terrestrial surfaces over time. Two atmospheric correction methods were used for this study: relative radiometric normalization and the simplified method for atmospheric correction (SMAC) in the solar spectrum. A multi-temporal data set consisting of two sets of Landsat images from the period between 1991 and 2002 of Penang Island, Malaysia, was used to compare NDVI maps, which were generated using the proposed atmospheric correction methods. Land surface temperature (LST) was retrieved using ATCOR3_T in PCI Geomatica 10.1 image processing software. Linear regression analysis was utilized to analyze the relationship between NDVI and LST. This study reveals that both of the proposed atmospheric correction methods yielded high accuracy through examination of the linear correlation coefficients. To check for the accuracy of the equation obtained through linear regression analysis for every single satellite image, 20 points were randomly chosen. The results showed that the SMAC method yielded a constant value (in terms of error) to predict the NDVI value from linear regression analysis-derived equation. The errors (average) from both proposed atmospheric correction methods were less than 10%.

  5. Global clear-sky surface skin temperature from multiple satellites using a single-channel algorithm with angular anisotropy corrections

    Science.gov (United States)

    Scarino, Benjamin R.; Minnis, Patrick; Chee, Thad; Bedka, Kristopher M.; Yost, Christopher R.; Palikonda, Rabindra

    2017-01-01

    Surface skin temperature (Ts) is an important parameter for characterizing the energy exchange at the ground/water-atmosphere interface. The Satellite ClOud and Radiation Property retrieval System (SatCORPS) employs a single-channel thermal-infrared (TIR) method to retrieve Ts over clear-sky land and ocean surfaces from data taken by geostationary Earth orbit (GEO) and low Earth orbit (LEO) satellite imagers. GEO satellites can provide somewhat continuous estimates of Ts over the diurnal cycle in non-polar regions, while polar Ts retrievals from LEO imagers, such as the Advanced Very High Resolution Radiometer (AVHRR), can complement the GEO measurements. The combined global coverage of remotely sensed Ts, along with accompanying cloud and surface radiation parameters, produced in near-realtime and from historical satellite data, should be beneficial for both weather and climate applications. For example, near-realtime hourly Ts observations can be assimilated in high-temporal-resolution numerical weather prediction models and historical observations can be used for validation or assimilation of climate models. Key drawbacks to the utility of TIR-derived Ts data include the limitation to clear-sky conditions, the reliance on a particular set of analyses/reanalyses necessary for atmospheric corrections, and the dependence on viewing and illumination angles. Therefore, Ts validation with established references is essential, as is proper evaluation of Ts sensitivity to atmospheric correction source.This article presents improvements on the NASA Langley GEO satellite and AVHRR TIR-based Ts product that is derived using a single-channel technique. The resulting clear-sky skin temperature values are validated with surface references and independent satellite products. Furthermore, an empirically adjusted theoretical model of satellite land surface temperature (LST) angular anisotropy is tested to improve satellite LST retrievals. Application of the anisotropic correction

  6. Global Clear-Sky Surface Skin Temperature from Multiple Satellites Using a Single-Channel Algorithm with Angular Anisotropy Corrections

    Science.gov (United States)

    Scarino, Benjamin R.; Minnis, Patrick; Chee, Thad; Bedka, Kristopher M.; Yost, Christopher R.; Palikonda, Rabindra

    2017-01-01

    Surface skin temperature (T(sub s)) is an important parameter for characterizing the energy exchange at the ground/water-atmosphere interface. The Satellite ClOud and Radiation Property retrieval System (SatCORPS) employs a single-channel thermal-infrared (TIR) method to retrieve T(sub s) over clear-sky land and ocean surfaces from data taken by geostationary Earth orbit (GEO) and low Earth orbit (LEO) satellite imagers. GEO satellites can provide somewhat continuous estimates of T(sub s) over the diurnal cycle in non-polar regions, while polar T(sub s) retrievals from LEO imagers, such as the Advanced Very High Resolution Radiometer (AVHRR), can complement the GEO measurements. The combined global coverage of remotely sensed T(sub s), along with accompanying cloud and surface radiation parameters, produced in near-realtime and from historical satellite data, should be beneficial for both weather and climate applications. For example, near-realtime hourly T(sub s) observations can be assimilated in high-temporal-resolution numerical weather prediction models and historical observations can be used for validation or assimilation of climate models. Key drawbacks to the utility of TIR-derived T(sub s) data include the limitation to clear-sky conditions, the reliance on a particular set of analyses/reanalyses necessary for atmospheric corrections, and the dependence on viewing and illumination angles. Therefore, T(sub s) validation with established references is essential, as is proper evaluation of T(sub s) sensitivity to atmospheric correction source. This article presents improvements on the NASA Langley GEO satellite and AVHRR TIR-based T(sub s) product that is derived using a single-channel technique. The resulting clear-sky skin temperature values are validated with surface references and independent satellite products. Furthermore, an empirically adjusted theoretical model of satellite land surface temperature (LST) angular anisotropy is tested to improve

  7. Can Reconstructed Land Surface Temperature Data from Space Predict a West Nile Virus Outbreak?

    Science.gov (United States)

    Andreo, V.; Metz, M.; Neteler, M.; Rosà, R.; Marcantonio, M.; Billinis, C.; Rizzoli, A.; Papa, A.

    2017-07-01

    Temperature is one of the main drivers of ecological processes. The availability of temporally and spatially continuous temperature time series is crucial in different research and application fields, such as epidemiology and control of zoonotic diseases. In 2010, several West Nile virus (WNV) outbreaks in humans were observed in Europe, with the largest number of cases recorded in Greece. Human cases continued to occur for four more years. The occurrence of the 2010's outbreak in Greece has been related to positive anomalies in temperature. Currently available remote sensing time series might provide the temporal and spatial coverage needed to assess this kind of hypothesis. However, the main problem with remotely sensed temperature are the gaps caused by cloud cover. With the objective of testing the former hypothesis, we reconstructed daily MODIS Land Surface Temperature (LST) data and derived several indices that are known or hypothesized to be related to mosquito populations, WNV transmission or risk of disease since they might constitute proxies for favoring or limiting conditions. We present the first results of the comparisons of time series of LST-derived indices among locations with WNV human cases and municipalities with and without reported WNV infection in Greece between 2010 and 2014.

  8. Analysis of Spatial-Temporal Variation of Land Surface Temperature, Vegetation and Snow Cover in Lar National Park of Iran

    Science.gov (United States)

    Arekhi, M.

    2016-10-01

    Changes in land surface reflectance measured by remote sensing data can be useful in climate change studies. This study attempts to analyze the spatial-temporal extent change of vegetation greenness, Land Surface Temperature (LST), and Normalized Difference Snow Index (NDSI) in late spring at the Lar National Park of Iran using Landsat data. Vegetation indices (VIs), LST, and NDSI maps were calculated for each date (1985, 1994, 2010, and 2015). All VIs have shown an increasing trend from 1985 to 2015 which depicted increase of vegetation. Spectral reflectance of all bands is declining from 1985 to 2015 except in near-infrared (NIR) bands. High reflectance in NIR bands is due to increased vegetation greenness. The reduction was seen in the visible bands that show increased vegetation photosynthetic activity. In the short-wave infrared bands (SWIR) were observed reduced trend from 1985 to 2015 which is indicate increased vegetation. Also, in the mid-wave infrared (MWIR) bands were observed a declining trend which is the result of decreasing soil fraction from 1985 to 2015. LST has increased from 23.27 °C in 1985 to 27.45 °C in 2015. Snow patches were decreased over the study period. In conclusion, VIs and surface reflectance bands are considered the main tool to display vegetation change. Also, high VIs values showed healthy and dense vegetation. The results of our study will provide valuable information in preliminary climate change studies.

  9. ANALYSIS OF SPATIAL-TEMPORAL VARIATION OF LAND SURFACE TEMPERATURE, VEGETATION AND SNOW COVER IN LAR NATIONAL PARK OF IRAN

    Directory of Open Access Journals (Sweden)

    M. Arekhi

    2016-10-01

    Full Text Available Changes in land surface reflectance measured by remote sensing data can be useful in climate change studies. This study attempts to analyze the spatial-temporal extent change of vegetation greenness, Land Surface Temperature (LST, and Normalized Difference Snow Index (NDSI in late spring at the Lar National Park of Iran using Landsat data. Vegetation indices (VIs, LST, and NDSI maps were calculated for each date (1985, 1994, 2010, and 2015. All VIs have shown an increasing trend from 1985 to 2015 which depicted increase of vegetation. Spectral reflectance of all bands is declining from 1985 to 2015 except in near-infrared (NIR bands. High reflectance in NIR bands is due to increased vegetation greenness. The reduction was seen in the visible bands that show increased vegetation photosynthetic activity. In the short-wave infrared bands (SWIR were observed reduced trend from 1985 to 2015 which is indicate increased vegetation. Also, in the mid-wave infrared (MWIR bands were observed a declining trend which is the result of decreasing soil fraction from 1985 to 2015. LST has increased from 23.27 °C in 1985 to 27.45 °C in 2015. Snow patches were decreased over the study period. In conclusion, VIs and surface reflectance bands are considered the main tool to display vegetation change. Also, high VIs values showed healthy and dense vegetation. The results of our study will provide valuable information in preliminary climate change studies.

  10. Daytime Land Surface Temperature Extraction from MODIS Thermal Infrared Data under Cirrus Clouds

    Directory of Open Access Journals (Sweden)

    Xiwei Fan

    2015-04-01

    Full Text Available Simulated data showed that cirrus clouds could lead to a maximum land surface temperature (LST retrieval error of 11.0 K when using the generalized split-window (GSW algorithm with a cirrus optical depth (COD at 0.55 μm of 0.4 and in nadir view. A correction term in the COD linear function was added to the GSW algorithm to extend the GSW algorithm to cirrus cloudy conditions. The COD was acquired by a look up table of the isolated cirrus bidirectional reflectance at 0.55 μm. Additionally, the slope k of the linear function was expressed as a multiple linear model of the top of the atmospheric brightness temperatures of MODIS channels 31–34 and as the difference between split-window channel emissivities. The simulated data showed that the LST error could be reduced from 11.0 to 2.2 K. The sensitivity analysis indicated that the total errors from all the uncertainties of input parameters, extension algorithm accuracy, and GSW algorithm accuracy were less than 2.5 K in nadir view. Finally, the Great Lakes surface water temperatures measured by buoys showed that the retrieval accuracy of the GSW algorithm was improved by at least 1.5 K using the proposed extension algorithm for cirrus skies.

  11. Land Surface Temperature- Comparing Data from Polar Orbiting and Geostationary Satellites

    Science.gov (United States)

    Comyn-Platt, E.; Remedios, J. J.; Good, E. J.; Ghent, D.; Saunders, R.

    2012-04-01

    Land Surface Temperature (LST) is a vital parameter in Earth climate science, driving long-wave radiation exchanges that control the surface energy budget and carbon fluxes, which are important factors in Numerical Weather Prediction (NWP) and the monitoring of climate change. Satellites offer a convenient way to observe LST consistently and regularly over large areas. A comparison between LST retrieved from a Geostationary Instrument, the Spinning Enhanced Visible and InfraRed Imager (SEVIRI), and a Polar Orbiting Instrument, the Advanced Along Track Scanning Radiometer (AATSR) is presented. Both sensors offer differing benefits. AATSR offers superior precision and spatial resolution with global coverage but given its sun-synchronous platform only observes at two local times, ~10am and ~10pm. SEVIRI provides the high-temporal resolution (every 15 minutes) required for observing diurnal variability of surface temperatures but given its geostationary platform has a poorer resolution, 3km at nadir, which declines at higher latitudes. A number of retrieval methods are applied to the raw satellite data: First order coefficient based algorithms provided on an operational basis by the LandSAF (for SEVIRI) and the University of Leicester (for AATSR); Second order coefficient based algorithms put forward by the University of Valencia; and an optimal estimation method using the 1DVar software provided by the NWP SAF. Optimal estimation is an iterative technique based upon inverse theory, thus is very useful for expanding into data assimilation systems. The retrievals are assessed and compared on both a fine scale using in-situ data from recognised validation sites and on a broad scale using two 100x100 regions such that biases can be better understood. Overall, the importance of LST lies in monitoring daily temperature extremes, e.g. for estimating permafrost thawing depth or risk of crop damage due to frost, hence the ideal dataset would use a combination of observations

  12. Assessing the radiative impacts of precipitating clouds on winter surface air temperatures and land surface properties in general circulation models using observations

    Science.gov (United States)

    Li, J.-L. F.; Lee, Wei-Liang; Wang, Yi-Hui; Richardson, Mark; Yu, Jia-Yuh; Suhas, E.; Fetzer, Eric; Lo, Min-Hui; Yue, Qing

    2016-10-01

    Using CloudSat-CALIPSO ice water, cloud fraction, and radiation; Clouds and the Earth's Radiant Energy System (CERES) radiation; and long-term station-measured surface air temperature (SAT), we identified a substantial underestimation of the total ice water path, total cloud fraction, land surface radiative flux, land surface temperature (LST), and SAT during Northern Hemisphere winter in Coupled Model Intercomparison Project Phase 5 (CMIP5) models. We perform sensitivity experiments with the National Center for Atmospheric Research (NCAR) Community Earth System Model version 1 (CESM1) in fully coupled modes to identify processes driving these biases. We found that biases in land surface properties are associated with the exclusion of downwelling longwave heating from precipitating ice during Northern Hemisphere winter. The land surface temperature biases introduced by the exclusion of precipitating ice radiative effects in CESM1 and CMIP5 both spatially correlate with winter biases over Eurasia and North America. The underestimated precipitating ice radiative effect leads to colder LST, associated surface energy-budget adjustments, and cooler SAT. This bias also shifts regional soil moisture state from liquid to frozen, increases snow cover, and depresses evapotranspiration (ET) and total leaf area index in Northern Hemisphere winter. The inclusion of the precipitating ice radiative effects largely reduces the model biases of surface radiative fluxes (more than 15 W m-2), SAT (up to 2-4 K), and snow cover and ET (25-30%), compared with those without snow-radiative effects.

  13. Advancing of Land Surface Temperature Retrieval Using Extreme Learning Machine and Spatio-Temporal Adaptive Data Fusion Algorithm

    Directory of Open Access Journals (Sweden)

    Yang Bai

    2015-04-01

    Full Text Available As a critical variable to characterize the biophysical processes in ecological environment, and as a key indicator in the surface energy balance, evapotranspiration and urban heat islands, Land Surface Temperature (LST retrieved from Thermal Infra-Red (TIR images at both high temporal and spatial resolution is in urgent need. However, due to the limitations of the existing satellite sensors, there is no earth observation which can obtain TIR at detailed spatial- and temporal-resolution simultaneously. Thus, several attempts of image fusion by blending the TIR data from high temporal resolution sensor with data from high spatial resolution sensor have been studied. This paper presents a novel data fusion method by integrating image fusion and spatio-temporal fusion techniques, for deriving LST datasets at 30 m spatial resolution from daily MODIS image and Landsat ETM+ images. The Landsat ETM+ TIR data were firstly enhanced based on extreme learning machine (ELM algorithm using neural network regression model, from 60 m to 30 m resolution. Then, the MODIS LST and enhanced Landsat ETM+ TIR data were fused by Spatio-temporal Adaptive Data Fusion Algorithm for Temperature mapping (SADFAT in order to derive high resolution synthetic data. The synthetic images were evaluated for both testing and simulated satellite images. The average difference (AD and absolute average difference (AAD are smaller than 1.7 K, where the correlation coefficient (CC and root-mean-square error (RMSE are 0.755 and 1.824, respectively, showing that the proposed method enhances the spatial resolution of the predicted LST images and preserves the spectral information at the same time.

  14. 利用MATLAB实现FY-3/MERSI地表温度反演及专题制图%Utilization of MATLAB to Realize LST Retrieval and Thematic Mapping from FY-3/MERSI Data

    Institute of Scientific and Technical Information of China (English)

    杨何群; 尹球; 周红妹; 葛伟强

    2012-01-01

    Currently, application - oriented researches on the data of Medium Resolution Spectral Imager (MERSI) , which is on board China ' s new generation polar orbit meteorological satellite FY - 3 , are very insufficient, due to the reason that the data as a new source have been delivered only since 2008. With the normal operation of FY - 3 satellite system, it is necessary to develop an operational module for FY - 3/MERSI regional land surface temperature (LST) retrieval and its post - processing, since LST is required for a wide variety of scientific studies but FY - 3/MERSI' s operational LST products have not yet been provided by National Satellite Meteorological Center (NSMC ). Rased on an analysis of FY - 3/MERSI LI data' s HDF5 format and its channel characteristics, the authors selected the generalized single - channel algorithm developed by Jimenez - Munoz & Sobrino to directly realize the LST retrieval at 250 m spatial resolution with MATLAR programming and the thematic mapping of LST derivative products. This paper describes the parametric processes of LST retrieval algorithm in detail, which include radiometric calibration, cloud detection, estimation of two intermediate parameters - surface emissivity and atmospheric water vapor, and calculation of thermal indexes from LST. On these bases, an automatic flowchart for FY - 3/MERSI LST retrieval and thematic mapping was established. Experimental results of this flowchart applied in Shanghai thermal environmental monitoring show that it can process FY - 3/MERSI LI data in a fast, real - time and automatic way, thus suitable for operational products producing and sharing, with the saving of human resources. It is also proved that FY - 3/MERSI data and various forms of LST products can reveal the spatial pattern of Shanghai thermal field and the urban heat island effect more finely and intuitively.%我国新型自主研发的风云三号卫星MERSI(FY-3/MERSI)数据目前多见于试验研究,国家卫星气象

  15. Agriculture pest and disease risk maps considering MSG satellite data and land surface temperature

    Science.gov (United States)

    Marques da Silva, J. R.; Damásio, C. V.; Sousa, A. M. O.; Bugalho, L.; Pessanha, L.; Quaresma, P.

    2015-06-01

    Pest risk maps for agricultural use are usually constructed from data obtained from in-situ meteorological weather stations, which are relatively sparsely distributed and are often quite expensive to install and difficult to maintain. This leads to the creation of maps with relatively low spatial resolution, which are very much dependent on interpolation methodologies. Considering that agricultural applications typically require a more detailed scale analysis than has traditionally been available, remote sensing technology can offer better monitoring at increasing spatial and temporal resolutions, thereby, improving pest management results and reducing costs. This article uses ground temperature, or land surface temperature (LST), data distributed by EUMETSAT/LSASAF (with a spatial resolution of 3 × 3 km (nadir resolution) and a revisiting time of 15 min) to generate one of the most commonly used parameters in pest modeling and monitoring: "thermal integral over air temperature (accumulated degree-days)". The results show a clear association between the accumulated LST values over a threshold and the accumulated values computed from meteorological stations over the same threshold (specific to a particular tomato pest). The results are very promising and enable the production of risk maps for agricultural pests with a degree of spatial and temporal detail that is difficult to achieve using in-situ meteorological stations.

  16. Estimation of Diurnal Cycle of Land Surface Temperature at High Temporal and Spatial Resolution from Clear-Sky MODIS Data

    Directory of Open Access Journals (Sweden)

    Si-Bo Duan

    2014-04-01

    Full Text Available The diurnal cycle of land surface temperature (LST is an important element of the climate system. Geostationary satellites can provide the diurnal cycle of LST with low spatial resolution and incomplete global coverage, which limits its applications in some studies. In this study, we propose a method to estimate the diurnal cycle of LST at high temporal and spatial resolution from clear-sky MODIS data. This method was evaluated using the MSG-SEVIRI-derived LSTs. The results indicate that this method fits the diurnal cycle of LST well, with root mean square error (RMSE values less than 1 K for most pixels. Because MODIS provides at most four observations per day at a given location, this method was further evaluated using only four MSG-SEVIRI-derived LSTs corresponding to the MODIS overpass times (10:30, 13:30, 22:30, and 01:30 local solar time. The results show that the RMSE values using only four MSG-SEVIRI-derived LSTs are approximately two times larger than those using all LSTs. The spatial distribution of the modeled LSTs at the MODIS pixel scale is presented from 07:00 to 05:00 local solar time of the next day with an increment of 2 hours. The diurnal cycle of the modeled LSTs describes the temporal evolution of the LSTs at the MODIS pixel scale.

  17. Land surface thermal characterization of Asian-pacific region with Japanese geostationary satellite

    Science.gov (United States)

    Oyoshi, K.; Tamura, M.

    2010-12-01

    Land Surface Temperature (LST) is a significant indicator of energy balance at the Earth's surface. It is required for a wide variety of climate, hydrological, ecological, and biogeochemical studies. Although LST is highly variable both temporally and spatially, it is impossible for polar-orbiting satellite to detect hourly changes in LST, because the satellite is able to only collect data of the same area at most twice a day. On the other hand, geostationary satellite is able to collect hourly data and has a possibility to monitor hourly changes in LST, therefore hourly measurements of geostationary satellite enables us to characterize detailed thermal conditions of the Earth's surface and improve our understanding of the surface energy balance. Multi-functional Transport Satellite (MTSAT) is a Japanese geostationary satellite launched in 2005 and covers Asia-Pacific region. MTSAT provides hourly data with 5 bands including two thermal infrared (TIR) bands in the 10.5-12.5 micron region. In this research, we have developed a methodology to retrieve hourly LST from thermal infrared data of MTSAT. We applied Generalized Split-window (GSW) equation to estimate LST from TIR data. First, the brightness temperatures measured at sensor on MTSAT was simulated by radiative transfer code (MODTRAN), and the numerical coefficients of GSW equation were optimized based on the simulation results with non-linear minimization algorithm. The standard deviation of derived GSW equation was less than or equal to 1.09K in the case of viewing zenith angle lower than 40 degree and 1.73K in 60 degree. Then, spatial distributions of LST have been mapped optimized GSW equation with brightness temperatures of MTSAT IR1 and IR2 and emissivity map from MODIS product. Finally, these maps were validated with MODIS LST product (MOD11A1) over four Asian-pacific regions such as Bangkok, Tokyo, UlanBator and Jakarta , It is found that RMSE of these regions were 4.57K, 2.22K, 2.71K and 3.92K

  18. The new single-channel approaches for retrieving land surface temperature and the preliminary results

    Science.gov (United States)

    Chen, Feng; Yang, Song; Liu, Lin; Zhao, Xiaofeng

    2014-11-01

    Two satellites named HJ-1A and HJ-1B were launched on 6 September 2008, which are intended for environment and disaster monitoring and forecasting. The infrared scanner (IRS) onboard HJ-1B has one thermal infrared band. Currently, for sensors with one thermal band (e.g. Landsat TM/ETM+ and HJ-1B), several empirical algorithms have been developed to estimate land surface temperature (LST). However, surface emissivity and atmospheric parameters which are not readily accessible to general users are required for these empirical methods. To resolve this problem, particularly for HJ-1B, new retrieval methodology is desired. According to proper assumptions, two approaches were proposed, which included the single-channel method based on temporal and spatial information (MTSC) and the image based single-channel method (IBSC). The newly developed methods are mainly for estimating LST accurately from one thermal band, even without any accurate information related to the atmospheric parameters and land surface emissivity. In this paper, we introduce and give preliminary assessments on the new approaches. Assessments generally show good agreement between the HJ-1B retrieved results and the MODIS references. Especially, over sea and water areas the biases were less than 1K while the root mean square errors were about 1K for both MTSC and IBSC methods. As expected, the MTSC method did superiorly to the IBSC method, owning to spatiotemporal information is incorporated into the MTSC method, although more experiments and comparisons should be conducted further.

  19. 新疆焉耆盆地地表温度时空分布对 LUCC 的响应%Spatiotemporal response of land surface temperature to land use/cover change in Yanqi Basin, Xinjiang

    Institute of Scientific and Technical Information of China (English)

    热伊莱·卡得尔; 玉素甫江·如素力; 高倩; 阿迪来·乌甫; 姜红

    2016-01-01

    biodiversity, local climate, hydrologic processes, and so forth. The land surface temperature (LST) is the radiative skin temperature of ground. It depends on the albedo, the vegetation cover and the soil moisture. In most cases, LST is a mixture of vegetation and bare soil temperatures. In turn, the LST influences the partition of energy between ground and vegetation, and determines the surface air temperature. In recent decades, geographical information systems and remote sensing techniques are widely employed to investigate the impact of land-use/cover change on land surface temperature. Understanding the interconnection of biological and climatic processes is essential for predicting the effects of climate change on the biosphere. Spatiotemporal distribution of LST is a critical factor of environmental change, and is the driving forces of the land surface processes. Study on the spatiotemporal response of LST to LUCC is an important scientific issue under the circumstances of anthropogenic pressure increasing rapidly. In the paper, characteristics of spatiotemporal distribution of LST and its response to LUCC are studied by LST data retrieved by methods of mono-window algorithm and single-channel from Landsat data of the year 2000, 2009, 2011 and 2015, observed metrological data and field sampling data in Yanqi Basin, Xinjiang, China. Results demonstrated that: 1) LST was classified as high LST, medium LST and low LST. The decreasing ratio of high LST area from the greatest to the least took place in the year of 2000, 2009 and 2015, respectively; the decreasing ratio of low LST area from the greatest to the least took place in the year of 2009, 2000 and 2015, respectively; 2) the distribution of LST had different spatial patters obviously. High LST distributed in deserts and Gobi between mountain and basin, and it had a circular pattern around the Bosten Lake. Low LST distributed in water, wetlands and oasis area; 3) the amplitude of LST change was different depending on

  20. The surface temperature of Europa

    CERN Document Server

    Ashkenazy, Yosef

    2016-01-01

    Previous estimates of the surface temperature of Jupiter's moon, Europa, neglected the effect of the eccentricity of Jupiter's orbit around the Sun, the effect of the eclipse of Europa (i.e., the relative time that Europa is within the shadow of Jupiter), and the effect of Europa's internal heating. Here we estimate the surface temperature of Europa, when Europa's obliquity, eclipse and internal heating, as well as the eccentricity of Jupiter, are all taken into account. For a typical internal heating rate of 0.05 W/m$^2$ (corresponding to an ice thickness of about 10 kms), the equator, pole, and global mean surface temperatures are 101.7 K, 45.26 K, and 94.75 K, respectively. We found that the temperature at the high latitudes is significantly affected by the internal heating. We also studied the effect of the internal heating on the mean thickness of Europa's icy shell and conclude that the polar region temperature can be used to constrain the internal heating and the depth of the ice. Our approach and form...

  1. Using dry spell dynamics of land surface temperature to evaluate large-scale model representation of soil moisture control on evapotranspiration

    Science.gov (United States)

    Taylor, Christopher M.; Harris, Philip P.; Gallego-Elvira, Belen; Folwell, Sonja S.

    2017-04-01

    The soil moisture control on the partition of land surface fluxes between sensible and latent heat is a key aspect of land surface models used within numerical weather prediction and climate models. As soils dry out, evapotranspiration (ET) decreases, and the excess energy is used to warm the atmosphere. Poor simulations of this dynamic process can affect predictions of mean, and in particular, extreme air temperatures, and can introduce substantial biases into projections of climate change at regional scales. The lack of reliable observations of fluxes and root zone soil moisture at spatial scales that atmospheric models use (typically from 1 to several hundred kilometres), coupled with spatial variability in vegetation and soil properties, makes it difficult to evaluate the flux partitioning at the model grid box scale. To overcome this problem, we have developed techniques to use Land Surface Temperature (LST) to evaluate models. As soils dry out, LST rises, so it can be used under certain circumstances as a proxy for the partition between sensible and latent heat. Moreover, long time series of reliable LST observations under clear skies are available globally at resolutions of the order of 1km. Models can exhibit large biases in seasonal mean LST for various reasons, including poor description of aerodynamic coupling, uncertainties in vegetation mapping, and errors in down-welling radiation. Rather than compare long-term average LST values with models, we focus on the dynamics of LST during dry spells, when negligible rain falls, and the soil moisture store is drying out. The rate of warming of the land surface, or, more precisely, its warming rate relative to the atmosphere, emphasises the impact of changes in soil moisture control on the surface energy balance. Here we show the application of this approach to model evaluation, with examples at continental and global scales. We can compare the behaviour of both fully-coupled land-atmosphere models, and land

  2. Diurnal and Seasonal Variation of Surface Urban Cool and Heat Islands in the Semi-Arid City of Erbil, Iraq

    OpenAIRE

    Azad Rasul; Heiko Balzter; Claire Smith

    2016-01-01

    The influence of land surface temperature (LST) makes the near-surface layer of the troposphere a key driver of urban climate. This paper assesses the temporal formation of the daytime Surface Urban Cool Island (SUCI) and night-time Surface Urban Heat Island (SUHI) effect in Erbil, Iraq, situated in a semi-arid climate region. LST retrievals from the Moderate Resolution Imaging Spectroradiometer (MODIS) Aqua and Terra and MODIS Normalized Difference Vegetation Index (NDVI) from January 2003 t...

  3. [Monitoring of farmland drought based on LST-LAI spectral feature space].

    Science.gov (United States)

    Sui, Xin-Xin; Qin, Qi-Ming; Dong, Heng; Wang, Jin-Liang; Meng, Qing-Ye; Liu, Ming-Chao

    2013-01-01

    Farmland drought has the characteristics of wide range and seriously affecting on agricultural production, so real-time dynamic monitored has been a challenging problem. By using MODIS land products, and constructing the spectral space of LST and LAI, the temperature LAI drought index (TLDI) was put forward and validated using ground-measured 0-10 cm averaged soil moisture of Ningxia farmland. The results show that the coefficient of determination (R2) of both them varies from 0.43 to 0.86. Compared to TVDI, the TLDI has higher accuracy for farmland moisture monitoring, and solves the saturation of NDVI during the late development phases of the crop. Furthermore, directly using MODIS land products LST and LAI and avoiding the complicated process of using the original MODIS data provide a new technical process to the regular operation of farmland drought monitoring.

  4. Albedo and land surface temperature shift in hydrocarbon seepage potential area, case study in Miri Sarawak Malaysia

    Science.gov (United States)

    Suherman, A.; Rahman, M. Z. A.; Busu, I.

    2014-02-01

    The presence of hydrocarbon seepage is generally associated with rock or mineral alteration product exposures, and changes of soil properties which manifest with bare development and stress vegetation. This alters the surface thermodynamic properties, changes the energy balance related to the surface reflection, absorption and emission, and leads to shift in albedo and LST. Those phenomena may provide a guide for seepage detection which can be recognized inexpensively by remote sensing method. District of Miri is used for study area. Available topographic maps of Miri and LANDSAT ETM+ were used for boundary construction and determination albedo and LST. Three land use classification methods, namely fixed, supervised and NDVI base classifications were employed for this study. By the intensive land use classification and corresponding statistical comparison was found a clearly shift on albedo and land surface temperature between internal and external seepage potential area. The shift shows a regular pattern related to vegetation density or NDVI value. In the low vegetation density or low NDVI value, albedo of internal area turned to lower value than external area. Conversely in the high vegetation density or high NDVI value, albedo of internal area turned to higher value than external area. Land surface temperature of internal seepage potential was generally shifted to higher value than external area in all of land use classes. In dense vegetation area tend to shift the temperature more than poor vegetation area.

  5. Monitoring snow melt characteristics on the Greenland ice sheet using a new MODIS land surface temperature and emissivity product (MOD21)

    Science.gov (United States)

    Hulley, G. C.; Hall, D. K.; Hook, S. J.

    2013-12-01

    Land Surface Temperature (LST) and emissivity are sensitive energy-balance parameters that control melt and energy exchange between the surface and the atmosphere. MODIS LST is currently used to monitor melt zones on glaciers and can be used for glacier or ice sheet mass balance calculations. Much attention has been paid recently to the warming of the Arctic in the context of global warming, with a focus on the Greenland ice sheet because of its importance with sea-level rise. Various researchers have shown a steady decline in the extent of the Northern Hemisphere sea ice, both the total extent and the extent of the perennial or multiyear ice. Surface melt characteristics over the Greenland ice sheet have been traditionally monitored using the MODIS LST and albedo products (e.g. MOD11 and MOD10A1). Far fewer studies have used thermal emissivity data to monitor surface melt characteristics due to the lack of suitable data. In theory, longwave emissivity combined with LST information should give a more direct measure of snow melt characteristics since the emissivity is an intrinsic property of the surface, whereas the albedo is dependent on other factors such as solar zenith angle, and shadowing effects. Currently no standard emissivity product exists that can dynamically retrieve changes in longwave emissivity consistently over long time periods. This problem has been addressed with the new MOD21 product, which uses the ASTER TES algorithm to dynamically retrieve LST and spectral emissivity (bands 29, 31, 32) at 1-km resolution. In this study we show that using a new proposed index termed the snow emissivity difference index (SEDI) derived from the MOD21 longwave emissivity product, combined with the LST, will improve our understanding of snow melt and freezeup dynamics on ice sheets such as Greenland. The results also suggest that synergistic use of both thermal-based and albedo data will help to improve our understanding of snow melt dynamics on glaciers and ice

  6. Comparison of Satellite-Derived Land Surface Temperature and Air Temperature from Meteorological Stations on the Pan-Arctic Scale

    Directory of Open Access Journals (Sweden)

    Christiane Schmullius

    2013-05-01

    Full Text Available Satellite-based temperature measurements are an important indicator for global climate change studies over large areas. Records from Moderate Resolution Imaging Spectroradiometer (MODIS, Advanced Very High Resolution Radiometer (AVHRR and (Advanced Along Track Scanning Radiometer ((AATSR are providing long-term time series information. Assessing the quality of remote sensing-based temperature measurements provides feedback to the climate modeling community and other users by identifying agreements and discrepancies when compared to temperature records from meteorological stations. This paper presents a comparison of state-of-the-art remote sensing-based land surface temperature data with air temperature measurements from meteorological stations on a pan-arctic scale (north of 60° latitude. Within this study, we compared land surface temperature products from (AATSR, MODIS and AVHRR with an in situ air temperature (Tair database provided by the National Climate Data Center (NCDC. Despite analyzing the whole acquisition time period of each land surface temperature product, we focused on the inter-annual variability comparing land surface temperature (LST and air temperature for the overlapping time period of the remote sensing data (2000–2005. In addition, land cover information was included in the evaluation approach by using GLC2000. MODIS has been identified as having the highest agreement in comparison to air temperature records. The time series of (AATSR is highly variable, whereas inconsistencies in land surface temperature data from AVHRR have been found.

  7. Estimation of Land Surface Temperature from 1-km AVHRR data

    Science.gov (United States)

    Frey, Corinne

    2016-04-01

    In order to re-process DLRs 1km AVHRR data archive to different geophysical and descriptive parameters of the land surface and the atmosphere, a series of scientific data processors are being developed in the framework of the TIMELINE project. The archive of DLR ranges back to the 80ies. One of the data processors is SurfTemp, which processes L2 LST and emissivity datasets from AVHRR L1b data. The development of the data processor included the selection of statistical procedures suitable for time series processing, including four mono-window and six split window algorithms. For almost all of these algorithms, new constants were generated, which better account for different atmospheric and geometric acquisition situations. The selection of optimal algorithms for SurfTemp is based on a round robin approach, in which the selected mono-window and split window algorithms are tested on the basis of a large number of TOA radiance/LST pairs, which were generated using a radiative transfer model and the SeeBorV5 profile database. The original LSTs are thereby compared to the LSTs derived from the TOA radiances using the mono- and split window algorithms. The algorithm comparison includes measures of precision, as well as the sensitivity of a method to the accuracy of its input data. The results of the round robin are presented, as well as the implementation of selected algorithms into SurfTemp. Further, first cross-validation results between the AVHRR LST and MODIS LST are shown.

  8. Evaluating the use of sharpened land surface temperature for daily evapotranspiration estimation over irrigated crops in arid lands

    KAUST Repository

    Rosas, Jorge

    2014-12-01

    Satellite remote sensing provides data on land surface characteristics, useful for mapping land surface energy fluxes and evapotranspiration (ET). Land-surface temperature (LST) derived from thermal infrared (TIR) satellite data has been reliably used as a remote indicator of ET and surface moisture status. However, TIR imagery usually operates at a coarser resolution than that of shortwave sensors on the same satellite platform, making it sometimes unsuitable for monitoring of field-scale crop conditions. This study applies the data mining sharpener (DMS; Gao et al., 2012) technique to data from the Moderate Resolution Imaging Spectroradiometer (MODIS), which sharpens the 1 km thermal data down to the resolution of the optical data (250-500 m) based on functional LST and reflectance relationships established using a flexible regression tree approach. The DMS approach adopted here has been enhanced/refined for application over irrigated farming areas located in harsh desert environments in Saudi Arabia. The sharpened LST data is input to an integrated modeling system that uses the Atmosphere-Land Exchange Inverse (ALEXI) model and associated flux disaggregation scheme (DisALEXI) in conjunction with model reanalysis data and remotely sensed data from polar orbiting (MODIS) and geostationary (MSG; Meteosat Second Generation) satellite platforms to facilitate daily estimates of evapotranspiration. Results are evaluated against available flux tower observations over irrigated maize near Riyadh in Saudi Arabia. Successful monitoring of field-scale changes in surface fluxes are of importance towards an efficient water use in areas where fresh water resources are scarce and poorly monitored. Gao, F.; Kustas, W.P.; Anderson, M.C. A Data Mining Approach for Sharpening Thermal Satellite Imagery over Land. Remote Sens. 2012, 4, 3287-3319.

  9. Assessment of Mono- and Split-Window Approaches for Time Series Processing of LST from AVHRR—A TIMELINE Round Robin

    Directory of Open Access Journals (Sweden)

    Corinne Myrtha Frey

    2017-01-01

    Full Text Available Processing of land surface temperature from long time series of AVHRR (Advanced Very High Resolution Radiometer requires stable algorithms, which are well characterized in terms of accuracy, precision and sensitivity. This assessment presents a comparison of four mono-window (Price 1983, Qin et al., 2001, Jiménez-Muñoz and Sobrino 2003, linear approach and six split-window algorithms (Price 1984, Becker and Li 1990, Ulivieri et al., 1994, Wan and Dozier 1996, Yu 2008, Jiménez-Muñoz and Sobrino 2008 to estimate LST from top of atmosphere brightness temperatures, emissivity and columnar water vapour. Where possible, new coefficients were estimated matching the spectral response curves of the different AVHRR sensors of the past and present. The consideration of unique spectral response curves is necessary to avoid artificial anomalies and wrong trends when processing time series data. Using simulated data on the base of a large atmospheric profile database covering many different states of the atmosphere, biomes and geographical regions, it was assessed (a to what accuracy and precision LST can be estimated using before mentioned algorithms and (b how sensitive the algorithms are to errors in their input variables. It was found, that the split-window algorithms performed almost equally well, differences were found mainly in their sensitivity to input bands, resulting in the Becker and Li 1990 and Price 1984 split-window algorithm to perform best. Amongst the mono-window algorithms, larger deviations occurred in terms of accuracy, precision and sensitivity. The Qin et al., 2001 algorithm was found to be the best performing mono-window algorithm. A short comparison of the application of the Becker and Li 1990 coefficients to AVHRR with the MODIS LST product confirmed the approach to be physically sound.

  10. Satellite-derived NDVI, LST, and climatic factors driving the distribution and abundance of Anopheles mosquitoes in a former malarious area in northwest Argentina.

    Science.gov (United States)

    Dantur Juri, María Julia; Estallo, Elizabet; Almirón, Walter; Santana, Mirta; Sartor, Paolo; Lamfri, Mario; Zaidenberg, Mario

    2015-06-01

    Distribution and abundance of disease vectors are directly related to climatic conditions and environmental changes. Remote sensing data have been used for monitoring environmental conditions influencing spatial patterns of vector-borne diseases. The aim of this study was to analyze the effect of the Normalized Difference Vegetation Index (NDVI) and Land Surface Temperature (LST) obtained from the Moderate Resolution Imaging Spectroradiometer (MODIS), and climatic factors (temperature, humidity, wind velocity, and accumulated rainfall) on the distribution and abundance of Anopheles species in northwestern Argentina using Poisson regression analyses. Samples were collected from December, 2001 to December, 2005 at three localities, Aguas Blancas, El Oculto and San Ramón de la Nueva Orán. We collected 11,206 adult Anopheles species, with the major abundance observed at El Oculto (59.11%), followed by Aguas Blancas (22.10%) and San Ramón de la Nueva Orán (18.79%). Anopheles pseudopunctipennis was the most abundant species at El Oculto, Anopheles argyritarsis predominated in Aguas Blancas, and Anopheles strodei in San Ramón de la Nueva Orán. Samples were collected throughout the sampling period, with the highest peaks during the spring seasons. LST and mean temperature appear to be the most important variables determining the distribution patterns and major abundance of An. pseudopunctipennis and An. argyritarsis within malarious areas. © 2015 The Society for Vector Ecology.

  11. Modeling of mean radiant temperature based on comparison of airborne remote sensing data with surface measured data

    Science.gov (United States)

    Chen, Yu-Cheng; Chen, Chih-Yu; Matzarakis, Andreas; Liu, Jin-King; Lin, Tzu-Ping

    2016-06-01

    Assessment of outdoor thermal comfort is becoming increasingly important due to the urban heat island effect, which strongly affects the urban thermal environment. The mean radiant temperature (Tmrt) quantifies the effect of the radiation environment on humans, but it can only be estimated based on influencing parameters and factors. Knowledge of Tmrt is important for quantifying the heat load on human beings, especially during heat waves. This study estimates Tmrt using several methods, which are based on climatic data from a traditional weather station, microscale ground surface measurements, land surface temperature (LST) and light detection and ranging (LIDAR) data measured using airborne devices. Analytical results reveal that the best means of estimating Tmrt combines information about LST and surface elevation information with meteorological data from the closest weather station. The application in this method can eliminate the inconvenience of executing a wide range ground surface measurement, the insufficient resolution of satellite data and the incomplete data of current urban built environments. This method can be used to map a whole city to identify hot spots, and can be contributed to understanding human biometeorological conditions quickly and accurately.

  12. How can we use MODIS land surface temperature to validate long-term urban model simulations?

    Science.gov (United States)

    Hu, Leiqiu; Brunsell, Nathaniel A.; Monaghan, Andrew J.; Barlage, Michael; Wilhelmi, Olga V.

    2014-03-01

    High spatial resolution urban climate modeling is essential for understanding urban climatology and predicting the human health impacts under climate change. Satellite thermal remote-sensing data are potential observational sources for urban climate model validation with comparable spatial scales, temporal consistency, broad coverage, and long-term archives. However, sensor view angle, cloud distribution, and cloud-contaminated pixels can confound comparisons between satellite land surface temperature (LST) and modeled surface radiometric temperature. The impacts of sensor view angles on urban LST values are investigated and addressed. Three methods to minimize the confounding factors of clouds are proposed and evaluated using 10years of Moderate Resolution Imaging Spectroradiometer (MODIS) data and simulations from the High-Resolution Land Data Assimilation System (HRLDAS) over Greater Houston, Texas, U.S. For the satellite cloud mask (SCM) method, prior to comparison, the cloud mask for each MODIS scene is applied to its concurrent HRLDAS simulation. For the max/min temperature (MMT) method, the 50 warmest days and coolest nights for each data set are selected and compared to avoid cloud impacts. For the high clear-sky fraction (HCF) method, only those MODIS scenes that have a high percentage of clear-sky pixels are compared. The SCM method is recommended for validation of long-term simulations because it provides the largest sample size as well as temporal consistency with the simulations. The MMT method is best for comparison at the extremes. And the HCF method gives the best absolute temperature comparison due to the spatial and temporal consistency between simulations and observations.

  13. Variational assimilation of land surface temperature observations for enhanced river flow predictions

    Science.gov (United States)

    Ercolani, Giulia; Castelli, Fabio

    2016-04-01

    Data assimilation (DA) has the potential of improving hydrologic forecasts. However, many issues arise in case it is employed for spatially distributed hydrologic models that describes processes in various compartments: large dimensionality of the inverse problem, layers governed by different equations, non-linear and discontinuous model structure, complex topology of domains such as surface drainage and river network.On the other hand, integrated models offer the possibility of improving prediction of specific states by exploiting observations of quantities belonging to other compartments. In terms of forecasting river discharges, and hence for their enhancement, soil moisture is a key variable, since it determines the partitioning of rainfall into infiltration and surface runoff. However, soil moisture measurements are affected by issues that could prevent a successful DA and an actual improvement of discharge predictions.In-situ measurements suffer a dramatic spatial scarcity, while observations from satellite are barely accurate and provide spatial information only at a very coarse scale (around 40 km).Hydrologic models that explicitly represent land surface processes of coupled water and energy balance provide a valid alternative to direct DA of soil moisture.They gives the possibility of inferring soil moisture states through DA of remotely sensed Land Surface Temperature (LST), whose measurements are more accurate and with a higher spatial resolution in respect to those of soil moisture. In this work we present the assimilation of LST data in a hydrologic model (Mobidic) that is part of the operational forecasting chain for the Arno river, central Italy, with the aim of improving flood predictions. Mobidic is a raster based, continuous in time and distributed in space hydrologic model, with coupled mass and energy balance at the surface and coupled groundwater and surface hydrology. The variational approach is adopted for DA, since it requires less

  14. Examining the impact of urban biophysical composition and neighboring environment on surface urban heat island effect

    Science.gov (United States)

    Song, Yang; Wu, Changshan

    2016-01-01

    Due to atmospheric and surface modifications associated with urbanization, surface urban heat island (SUHI) effects have been considered essential in examining urban ecological environments. With remote sensing technologies, numerous land cover type related variables, including spectral indices and land cover fractions, have been applied to estimate land surface temperature (LST), thereby further examining SUHI. This study begins with the reexamination of the commonly used indicators of LST using Landsat Enhanced Thematic Mapper Plus (ETM+) and Landsat Thematic Mapper (TM) images which cover four counties of Wisconsin, United States. Origin of the large variation of LST found in urban areas is then investigated by discriminating soil and impervious surfaces. Except land cover types, neighboring environment is another key factor which may affect LST in urban areas. Thus, a neighboring effect considered method is proposed at the end of the study to better understand the relationship between impervious surfaces fraction (%ISA) and LST by taking the influence of neighboring environment into account. Results indicate that spectral indices have better performance in predicting LST than land cover fractions do within the study area. However, the result remains arguable due to the complexity and uncertainty of spectral mixture analysis. Impervious surfaces are found responsible for the large variation of LST in urban areas, which indicates that impervious surfaces should not be simply considered as a single land cover type has stable negative correlation with LST. Moreover, a better relationship is found between %ISA and LST when neighboring effect is considered, when compared to the traditional method which ignores the neighboring effect.

  15. Sensitivity of Satellite-Based Skin Temperature to Different Surface Emissivity and NWP Reanalysis Sources Demonstrated Using a Single-Channel, Viewing-Angle-Corrected Retrieval Algorithm

    Science.gov (United States)

    Scarino, B. R.; Minnis, P.; Yost, C. R.; Chee, T.; Palikonda, R.

    2015-12-01

    Single-channel algorithms for satellite thermal-infrared- (TIR-) derived land and sea surface skin temperature (LST and SST) are advantageous in that they can be easily applied to a variety of satellite sensors. They can also accommodate decade-spanning instrument series, particularly for periods when split-window capabilities are not available. However, the benefit of one unified retrieval methodology for all sensors comes at the cost of critical sensitivity to surface emissivity (ɛs) and atmospheric transmittance estimation. It has been demonstrated that as little as 0.01 variance in ɛs can amount to more than a 0.5-K adjustment in retrieved LST values. Atmospheric transmittance requires calculations that employ vertical profiles of temperature and humidity from numerical weather prediction (NWP) models. Selection of a given NWP model can significantly affect LST and SST agreement relative to their respective validation sources. Thus, it is necessary to understand the accuracies of the retrievals for various NWP models to ensure the best LST/SST retrievals. The sensitivities of the single-channel retrievals to surface emittance and NWP profiles are investigated using NASA Langley historic land and ocean clear-sky skin temperature (Ts) values derived from high-resolution 11-μm TIR brightness temperature measured from geostationary satellites (GEOSat) and Advanced Very High Resolution Radiometers (AVHRR). It is shown that mean GEOSat-derived, anisotropy-corrected LST can vary by up to ±0.8 K depending on whether CERES or MODIS ɛs sources are used. Furthermore, the use of either NOAA Global Forecast System (GFS) or NASA Goddard Modern-Era Retrospective Analysis for Research and Applications (MERRA) for the radiative transfer model initial atmospheric state can account for more than 0.5-K variation in mean Ts. The results are compared to measurements from the Surface Radiation Budget Network (SURFRAD), an Atmospheric Radiation Measurement (ARM) Program ground

  16. Extended Reconstructed Sea Surface Temperature (ERSST)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Extended Reconstructed Sea Surface Temperature (ERSST) dataset is a global monthly sea surface temperature analysis derived from the International Comprehensive...

  17. NOAA Global Surface Temperature (NOAAGlobalTemp)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The NOAA Global Surface Temperature Dataset (NOAAGlobalTemp) is a merged land–ocean surface temperature analysis (formerly known as MLOST) (link is external). It is...

  18. Simulation and validation of land surface temperature algorithms for MODIS and AATSR data

    Directory of Open Access Journals (Sweden)

    J. M. Galve

    2007-01-01

    Full Text Available A database of global, cloud-free, atmospheric radiosounding profiles was compiled with the aim of simulating radiometric measurements from satellite-borne sensors in the thermal infrared. The objective of the simulation was to use Terra/Moderate Resolution Imaging Spectroradiometer (MODIS and Envisat/Advanced Along Track Scanning Radiometer (AATSR data to generate split-window (SW and dual-angle (DA algorithms for the retrieval of land surface temperature (LST. The database contains 382 radiosounding profiles acquired from land surfaces, with an almost uniform distribution of precipitable water between 0 and 5.5 cm. Radiative transfer calculations were performed with the MODTRAN 4 code for six different viewing angles between 0 and 65º. The resulting radiance spectra were integrated with the response filter functions of MODIS bands 31 and 32 and AATSR channels at 11 and 12 μm. Using the simulation database, SW algorithms adapted for MODIS and AATSR data, and DA algorithms for AATSR data were developed. Both types of algorithms are quadratic in the brightness temperature difference, and depend explicitly on the land surface emissivity. These SW and DA algorithms were validated with actual ground measurements of LST collected concurrently with MODIS and AATSR observations in a large, flat and thermally homogeneous area of rice crops located close to the city of Valencia, Spain. The results were not bias and had a standard deviation of around ± 0.5 K for SW algorithms at the nadir of both sensors; the SW algorithm used in the forward view resulted in a bias of 0.5 K and a standard deviation of ± 0.8 K. The least accurate results were obtained in the DA algorithms with a bias close to -2.0 K and a standard deviation of almost ± 1.0 K.

  19. Spatial assessment of land surface temperature and land use/land cover in Langkawi Island

    Science.gov (United States)

    Abu Bakar, Suzana Binti; Pradhan, Biswajeet; Salihu Lay, Usman; Abdullahi, Saleh

    2016-06-01

    This study investigates the relationship between Land Surface Temperature and Land Use/Land Cover in Langkawi Island by using Normalized Difference Vegetation Index (NDVI), Normalized Difference Build-Up Index (NDBI) and Modified Normalized Difference Water Index (MNDWI) qualitatively by using Landsat 7 ETM+ and Landsat 8 (OLI/TIRS) over the period 2002 and 2015. Pixel-based classifiers Maximum Likelihood (MLC) and Support Vector Machine (SVM), has been performed to prepare the Land Use/ Land Cover map (LU/LC) and the result shows that Support Vector Machine (SVM) achieved maximum accuracy with 90% and 90.46% compared to Maximum Likelihood (MLC) classifier with 86.62% and 86.98% respectively. The result revealed that as the impervious surface (built-up /roads) increases, the surface temperature of the area increased. However, land surface temperature decreased in the vegetated areas. Based from the linear regression between LST and NDVI, NDBI and MNDWI, these indices can be used as an indicator to monitor the impact of Land Use/Land Cover on Land Surface Temperature.

  20. Estimation and Validation of Land Surface Temperatures from Chinese Second-Generation Polar-Orbit FY-3A VIRR Data

    Directory of Open Access Journals (Sweden)

    Bo-Hui Tang

    2015-03-01

    Full Text Available This work estimated and validated the land surface temperature (LST from thermal-infrared Channels 4 (10.8 µm and 5 (12.0 µm of the Visible and Infrared Radiometer (VIRR onboard the second-generation Chinese polar-orbiting FengYun-3A (FY-3A meteorological satellite. The LST, mean emissivity and atmospheric water vapor content (WVC were divided into several tractable sub-ranges with little overlap to improve the fitting accuracy. The experimental results showed that the root mean square errors (RMSEs were proportional to the viewing zenith angles (VZAs and WVC. The RMSEs were below 1.0 K for VZA sub-ranges less than 30° or for VZA sub-ranges less than 60° and WVC less than 3.5 g/cm2, provided that the land surface emissivities were known. A preliminary validation using independently simulated data showed that the estimated LSTs were quite consistent with the actual inputs, with a maximum RMSE below 1 K for all VZAs. An inter-comparison using the Moderate Resolution Imaging Spectroradiometer (MODIS-derived LST product MOD11_L2 showed that the minimum RMSE was 1.68 K for grass, and the maximum RMSE was 3.59 K for barren or sparsely vegetated surfaces. In situ measurements at the Hailar field site in northeastern China from October, 2013, to September, 2014, were used to validate the proposed method. The result showed that the RMSE between the LSTs calculated from the ground measurements and derived from the VIRR data was 1.82 K.

  1. The impact of climatic and non-climatic factors on land surface temperature in southwestern Romania

    Science.gov (United States)

    Roşca, Cristina Florina; Harpa, Gabriela Victoria; Croitoru, Adina-Eliza; Herbel, Ioana; Imbroane, Alexandru Mircea; Burada, Doina Cristina

    2016-09-01

    Land surface temperature is one of the most important parameters related to global warming. It depends mainly on soil type, discontinuous vegetation cover, or lack of precipitation. The main purpose of this paper is to investigate the relationship between high LST, synoptic conditions and air masses trajectories, vegetation cover, and soil type in one of the driest region in Romania. In order to calculate the land surface temperature and normalized difference vegetation index, five satellite images of LANDSAT missions 5 and 7, covering a period of 26 years (1986-2011), were selected, all of them collected in the month of June. The areas with low vegetation density were derived from normalized difference vegetation index, while soil types have been extracted from Corine Land Cover database. HYSPLIT application was employed to identify the air masses origin based on their backward trajectories for each of the five study cases. Pearson, logarithmic, and quadratic correlations were used to detect the relationships between land surface temperature and observed ground temperatures, as well as between land surface temperature and normalized difference vegetation index. The most important findings are: strong correlation between land surface temperature derived from satellite images and maximum ground temperature recorded in a weather station located in the area, as well as between areas with land surface temperature equal to or higher than 40.0 °C and those with lack of vegetation; the sandy soils are the most prone to high land surface temperature and lack of vegetation, followed by the chernozems and brown soils; extremely severe drought events may occur in the region.

  2. Diurnal and Seasonal Variation of Surface Urban Cool and Heat Islands in the Semi-Arid City of Erbil, Iraq

    Directory of Open Access Journals (Sweden)

    Azad Rasul

    2016-09-01

    Full Text Available The influence of land surface temperature (LST makes the near-surface layer of the troposphere a key driver of urban climate. This paper assesses the temporal formation of the daytime Surface Urban Cool Island (SUCI and night-time Surface Urban Heat Island (SUHI effect in Erbil, Iraq, situated in a semi-arid climate region. LST retrievals from the Moderate Resolution Imaging Spectroradiometer (MODIS Aqua and Terra and MODIS Normalized Difference Vegetation Index (NDVI from January 2003 to December 2014 are analysed. The relationships of LST with NDVI and the Normalized Multi-band Drought Index (NMDI are investigated in order to assess the influence of vegetation and moisture on the observed patterns of LST and the SUCI/SUHI. The results indicate that during the daytime, in summer, autumn and winter, densely built-up areas had lower LST acting as a SUCI compared to the non-urbanised area around the city. In contrast, at night-time, Erbil experienced higher LST and demonstrated a significant SUHI effect. The relationship between LST and NDVI is affected by seasonality and is strongly inverted during spring (r2 = 0.73; p < 0.01. Contrary to previous studies of semi-arid cities, a SUCI was detected, not only in the morning, but also during the afternoon.

  3. Genetic and bibliographic information: LST1 [GenLibi

    Lifescience Database Archive (English)

    Full Text Available LST1 leukocyte specific transcript 1 human Myocardial Infarction (MeSH) Cardiovascular Diseases... (C14) > Heart Diseases (C14.280) > Myocardial Ischemia (C14.280.647) > Myocardial Infarction (C...14.280.647.500) Cardiovascular Diseases (C14) > Vascular Diseases (C14.907) > Myocardial Ischemia (C14.907.585) > Myocardial Infarction (C14.907.585.500) 03A0779575 ...

  4. The Pacific sea surface temperature

    Energy Technology Data Exchange (ETDEWEB)

    Douglass, David H., E-mail: douglass@pas.rochester.edu [Department of Physics and Astronomy, University of Rochester, Rochester, NY 14627-0171 (United States)

    2011-12-05

    The Pacific sea surface temperature data contains two components: N{sub L}, a signal that exhibits the familiar El Niño/La Niña phenomenon and N{sub H}, a signal of one-year period. Analysis reveals: (1) The existence of an annual solar forcing F{sub S}; (2) N{sub H} is phase locked directly to F{sub S} while N{sub L} is frequently phase locked to the 2nd or 3rd subharmonic of F{sub S}. At least ten distinct subharmonic time segments of N{sub L} since 1870 are found. The beginning or end dates of these segments have a near one-to-one correspondence with the abrupt climate changes previously reported. Limited predictability is possible. -- Highlights: ► El Niño/La Niña consists of 2 components phase-locked to annual solar cycle. ► The first component N{sub L} is the familiar El Niño/La Niña effect. ► The second N{sub H} component has a period of 1 cycle/year. ► N{sub L} can be phase-locked to 2nd or 3rd subharmonic of annual cycle. ► Ends of phase-locked segments correspond to abrupt previously reported climate changes.

  5. Monitoring of the ground surface temperature and the active layer in NorthEastern Canadian permafrost areas using remote sensing data assimilated in a climate land surface scheme.

    Science.gov (United States)

    Marchand, N.; Royer, A.; Krinner, G.; Roy, A.

    2014-12-01

    Projected future warming is particularly strong in the Northern high latitudes where increases of temperatures are up to 2 to 6 °C. Permafrost is present on 25 % of the northern hemisphere lands and contain high quantities of « frozen » carbon, estimated at 1400 Gt (40 % of the global terrestrial carbon). The aim of this study is to improve our understanding of the climate evolution in arctic areas, and more specifically of land areas covered by snow. The objective is to describe the ground temperature year round including under snow cover, and to analyse the active layer thickness evolution in relation to the climate variability. We use satellite data (fusion of MODIS land surface temperature « LST » and microwave AMSR-E brightness temperature « Tb ») assimilated in the Canadian Land Surface Scheme (CLASS) of the Canadian climate model coupled with a simple radiative transfer model (HUT). This approach benefits from the advantages of each of the data type in order to complete two objectives : 1- build a solid methodology for retrieving the ground temperature, with and without snow cover, in taïga and tundra areas ; 2 - from those retrieved ground temperatures, derive the summer melt duration and the active layer depth. We describe the coupling of the models and the methodology that adjusts the meteorological input parameters of the CLASS model (mainly air temperature and precipitations derived from the NARR database) in order to minimise the simulated LST and Tb ouputs in comparison with satellite measurements. Using ground-based meteorological data as validation references in NorthEastern Canadian tundra, the results show that the proposed approach improves the soil temperatures estimates when using the MODIS LST and Tb at 10 and 19 GHz to constrain the model in comparison with the model outputs without satellite data. Error analysis is discussed for the summer period (2.5 - 4 K) and for the snow covered winter period (2 - 3.5 K). Further steps are

  6. Prediction of Turbulent Heat Fluxes by Assimilation of Remotely Sensed Land Surface Temperature and Soil Moisture Data into an Ensemble-Based Data Assimilation Framework

    Science.gov (United States)

    Xu, T.; Bateni, S. M.; Liu, S.

    2015-12-01

    Accurate estimation of turbulent heat fluxes is important for water resources planning and management, irrigation scheduling, and weather forecast. Land surface models (LSMs) can be used to simulate turbulent heat fluxes over large-scale domains. However, the application of LSMs is hindered due to the high uncertainty in model parameters and state variables. In this study, a dual-pass ensemble-based data assimilation (DA) approach is developed to estimate turbulent heat fluxes. Initially, the common land model (CoLM) is used as the LSM (open-loop), and thereafter the ensemble Kalman filter is employed to optimize the CoLM parameters and variables. The first pass of the DA scheme optimizes vegetation parameters of CoLM (which are related to the leaf stomatal conductance) on a weekly-basis by assimilating the MODIS land surface temperature (LST) data. The second pass optimizes the soil moisture state of CoLM on a daily-basis by assimilating soil moisture observations from Cosmic-ray instrument. The ultimate goal is to improve turbulent heat fluxes estimates from CoLM by optimizing its vegetation parameters and soil moisture state via assimilation of LST and soil moisture data into the proposed DA system. The DA approach is tested over a wet and densely vegetated site, called Daman in northwest of China. Results indicate that the CoLM (open-loop) model typically underestimates latent heat flux and overestimates sensible heat flux. By assimilation of LST in the first pass, the turbulent heat fluxes are improved compared to those of the open-loop. These fluxes become even more accurate by assimilation of soil moisture in the second pass of the DA approach. These findings illustrate that the introduced DA approach can successfully extract information in LST and soil moisture data to optimize the CoLM parameters and states and improve the turbulent heat fluxes estimates.

  7. A physics-based statistical algorithm for retrieving land surface temperature from AMSR-E passive microwave data

    Institute of Scientific and Technical Information of China (English)

    MAO KeBiao; SHI JianCheng; LI ZhaoLiang; QIN ZhiHao; LI ManChun; XU Bin

    2007-01-01

    AMSR-E and MODIS are two EOS (Earth Observing System) instruments on board the Aqua satellite. A regression analysis between the brightness of all AMSR-E bands and the MODIS land surface temperature product indicated that the 89 GHz vertical polarization is the best single band to retrieve land surface temperature. According to simulation analysis with AIEM, the difference of different frequencies can eliminate the influence of water in soil and atmosphere, and also the surface roughness partly. The analysis results indicate that the radiation mechanism of surface covered snow is different from others. In order to retrieve land surface temperature more accurately, the land surface should be at least classified into three types: water covered surface, snow covered surface, and non-water and non-snow covered land surface. In order to improve the practicality and accuracy of the algorithm, we built different equations for different ranges of temperature. The average land surface temperature error is about 2-3℃ relative to the MODIS LST product.

  8. A physics-based statistical algorithm for retrieving land surface temperature from AMSR-E passive microwave data

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    AMSR-E and MODIS are two EOS (Earth Observing System) instruments on board the Aqua satellite. A regression analysis between the brightness of all AMSR-E bands and the MODIS land surface tem-perature product indicated that the 89 GHz vertical polarization is the best single band to retrieve land surface temperature. According to simulation analysis with AIEM,the difference of different frequen-cies can eliminate the influence of water in soil and atmosphere,and also the surface roughness partly. The analysis results indicate that the radiation mechanism of surface covered snow is different from others. In order to retrieve land surface temperature more accurately,the land surface should be at least classified into three types:water covered surface,snow covered surface,and non-water and non-snow covered land surface. In order to improve the practicality and accuracy of the algorithm,we built different equations for different ranges of temperature. The average land surface temperature er-ror is about 2―3℃ relative to the MODIS LST product.

  9. Purification and characterization of organic solvent-stable lipase from organic solvent-tolerant Pseudomonas aeruginosa LST-03.

    Science.gov (United States)

    Ogino, H; Nakagawa, S; Shinya, K; Muto, T; Fujimura, N; Yasuda, M; Ishikawa, H

    2000-01-01

    An organic solvent-stable lipase (LST-03 lipase) secreted into the culture broth of the organic solvent-tolerant Pseudomonas aeruginosa LST-03 was purified by ion-exchange and hydrophobic interaction chromatography in the presence of 2-propanol. The purified enzyme was homogeneous as determined by SDS-PAGE. The molecular mass of the lipase was estimated to be 27.1 kDa by SDS-PAGE and 36 kDa by gel filtration. The optimum pH and temperature were 6.0 and 37 degrees C. LST-03 lipase was stable at pH 5-8 and below 40 degrees C. Its hydrolytic activity was highest against tricaproin (C6), methyl octanoate (C8), and coconut oil respectively among the triacylglycerols, fatty acid methyl esters, and natural oils investigated. The enzyme cleaved not only the 1,3-positioned ester bonds, but also the 2-positioned ester bond of triolein. It exhibited high levels of activity in the presence of n-decane, n-octane, DMSO, and DMF as well as in the absence of an organic solvent. In addition, LST-03 lipase was stabler in the presence of n-decane, ethyleneglycol, DMSO, n-octane, n-heptane, isooctane, and cyclohexane than in the absence of an organic solvent.

  10. Surface temperature measurements of diamond

    CSIR Research Space (South Africa)

    Masina, BN

    2006-07-01

    Full Text Available ) and the waist position (z0) 3. TEMPERATURE MEASUREMENTS There are many methods to measure the temperature of a body. Here we used a thermocou- ple and a pyrometer, while future plans involve emission spectroscopy. A thermocouple is a temperature... sensor that consists of two wires con- nected together made from different metals, which produces an electrical voltage that is dependant on tem- perature. A Newport electronic thermocou- ple was used to meas- ured temperature. It can measure...

  11. 同化MODIS温度产品估算地表水热通量%Estimation of sensible and latent heat flux by assimilating MODIS LST products

    Institute of Scientific and Technical Information of China (English)

    徐同仁; 刘绍民; 秦军; 梁顺林

    2009-01-01

    In this paper, a land surface temperature data assimilation scheme is developed based on Ensemble Kalman Filter (EnKF) and Common Land Model version 1.0 (CLM), which is mainly used to improve the estimation of the sensible and latent heat fluxes by assimilating MODIS land surface temperature (LST) products. Leaf area index (LAI) is also updated dynamically by MODIS LAI products. In this study, the relationship between the MODIS LST and the CLM surface temperature is determined and taken as the observation operator of the assimilation scheme. Meanwhile, the MODIS LST is compared with the ground-measured surface temperature, and the Root Mean Square Error (RMSE) is taken as the observation error. The scheme is tested and validated based on measurements in three observation stations (Blackhill, Bondville and Brookings) of Ameriflux. Results indicate that data assimilation method improves the estimation of surface temperature and sensible heat flux. The RMSE of sensible heat flux reduced from 81.5W·m~(-2) to 58.4W·m~(-2) at the Blackhill site, from 47.0W·m~(-2) to 31.8W·m~(-2) at the Bondville site, from 46.5W·m~(-2) to 45.1W·m~(-2) at the Brookings site. The RMSE of latent heat fluxes reduced from 88.6W·m~(-2) to 57.7W·m~(-2) at the Bondville site, from 53.4W·m~(-2) to 47.2W·m~(-2) at the Blackhill site. In addition, it is a practical way to improve the estimation of sensible and latent heat flux by assimilating MODIS LST into land surface model.%基于集合卡尔曼滤波和通用陆面模型(CLM 1.0)发展了一个地表温度的同化系统.这个系统同化了MODIS温度产品,并将MODIS的叶面积指数引入CLM模型中,主要用于改进地表水热通量的估算精度.将CLM输出的地表温度与MODIS地表温度建立关系,并作为同化系统的观测算子.将MODIS地表温度与实测地表温度进行了比较,将其均方差(Root Mean Square Error,RMSE)作为观测误差.选取3个美国通量网站点(Blackhill、 Bondville

  12. Assessing the Impacts of the 2009/2010 Drought on Vegetation Indices, Normalized Difference Water Index, and Land Surface Temperature in Southwestern China

    Directory of Open Access Journals (Sweden)

    Xiaoqiang Zhang

    2017-01-01

    Full Text Available Droughts are projected to increase in severity and frequency on both regional and global scales. Despite the increasing occurrence and intensity of the 2009/2010 drought in southwestern China, the impacts of drought on vegetation in this region remain unclear. We examined the impacts of the 2009/2010 drought in southwestern China on vegetation by calculating the standardized anomalies of Normalized Difference Vegetation Index (NDVI, Enhanced Vegetation Index (EVI, Normalized Difference Water Index (NDWI, and Land Surface Temperature (LST. The standardized anomalies of NDVI, EVI, and NDWI exhibited positively skewed frequency distributions, while the standardized anomalies of LST exhibited a negatively skewed frequency distribution. These results implied that the NDVI, EVI, and NDWI declined, while LST increased in the 2009/2010 drought-stricken vegetated areas during the drought period. The responses of vegetation to the 2009/2010 drought differed substantially among biomes. Savannas, croplands, and mixed forests were more vulnerable to the 2009/2010 drought than deciduous forest and grasslands, while evergreen forest was resistant to the 2009/2010 drought in southwestern China. We concluded that the 2009/2010 drought had negative impacts on vegetation in southwestern China. The resulting assessment on the impacts of drought assists in evaluating and mitigating its adverse effects in southwestern China.

  13. Modelling global fresh surface water temperature

    NARCIS (Netherlands)

    Beek, L.P.H. van; Eikelboom, T.; Vliet, M.T.H. van; Bierkens, M.F.P.

    2011-01-01

    Temperature directly determines a range of water physical properties including vapour pressure, surface tension, density and viscosity, and the solubility of oxygen and other gases. Indirectly water temperature acts as a strong control on fresh water biogeochemistry, influencing sediment

  14. Modelling global fresh surface water temperature

    NARCIS (Netherlands)

    Beek, L.P.H. van; Eikelboom, T.; Vliet, M.T.H. van; Bierkens, M.F.P.

    2011-01-01

    Temperature directly determines a range of water physical properties including vapour pressure, surface tension, density and viscosity, and the solubility of oxygen and other gases. Indirectly water temperature acts as a strong control on fresh water biogeochemistry, influencing sediment concentrati

  15. Modeling directional effects in land surface temperature derived from geostationary satellite data

    DEFF Research Database (Denmark)

    Rasmussen, Mads Olander

    varying magnitude and sign on both diurnal and seasonal scales, which will have implications if using LST products in downstream applications like hydrological or soil vegetation atmosphere transfer (SVAT) models. The directional effects will cause uncertainties in LST estimates that are different...... in terms of timing than the uncertainties in data from polar orbiting sensors, which will cause discrepancies between measurements from the two types of sensors. An assessment of the performance of current LST algorithms from MSG SEVIRI for semi-arid West Africa was carried out, using data from two field...... the illumination geometry changes both over the course of the day and with the seasons. In the present study, the directional effects are assessed at different scales using a modeling approach. The model applied, the Modified Geometry Projection (MGP) model, represents the surface as a composite of four components...

  16. Generalized Split-Window Algorithm for Estimate of Land Surface Temperature from Chinese Geostationary FengYun Meteorological Satellite (FY-2C Data

    Directory of Open Access Journals (Sweden)

    Jun Xia

    2008-02-01

    Full Text Available On the basis of the radiative transfer theory, this paper addressed the estimate ofLand Surface Temperature (LST from the Chinese first operational geostationarymeteorological satellite-FengYun-2C (FY-2C data in two thermal infrared channels (IR1,10.3-11.3 μ m and IR2, 11.5-12.5 μ m , using the Generalized Split-Window (GSWalgorithm proposed by Wan and Dozier (1996. The coefficients in the GSW algorithmcorresponding to a series of overlapping ranging of the mean emissivity, the atmosphericWater Vapor Content (WVC, and the LST were derived using a statistical regressionmethod from the numerical values simulated with an accurate atmospheric radiativetransfer model MODTRAN 4 over a wide range of atmospheric and surface conditions.The simulation analysis showed that the LST could be estimated by the GSW algorithmwith the Root Mean Square Error (RMSE less than 1 K for the sub-ranges with theViewing Zenith Angle (VZA less than 30° or for the sub-rangs with VZA less than 60°and the atmospheric WVC less than 3.5 g/cm2 provided that the Land Surface Emissivities(LSEs are known. In order to determine the range for the optimum coefficients of theGSW algorithm, the LSEs could be derived from the data in MODIS channels 31 and 32 provided by MODIS/Terra LST product MOD11B1, or be estimated either according tothe land surface classification or using the method proposed by Jiang et al. (2006; and theWVC could be obtained from MODIS total precipitable water product MOD05, or beretrieved using Li et al.’ method (2003. The sensitivity and error analyses in term of theuncertainty of the LSE and WVC as well as the instrumental noise were performed. Inaddition, in order to compare the different formulations of the split-window algorithms,several recently proposed split-window algorithms were used to estimate the LST with thesame simulated FY-2C data. The result of the intercomparsion showed that most of thealgorithms give

  17. A Preliminary View on the Estimation of Land Surface Temperature Under Cloud Cover from Thermal Remote Sensing Data%热红外遥感图像中云覆盖像元地表温度估算初论

    Institute of Scientific and Technical Information of China (English)

    周义; 覃志豪; 包刚

    2013-01-01

    Land surface temperature (LST) is a very important parameter controlling the energy and water balance between atmosphere and land surface. Since it is difficult to obtain such information from ground-based measurements, it appears to be very attractive by using satellite thermal infrared measurements to estimate LST since it can be used for estimating surface temperature at global or local scale. Moreover, the estimation of LST by using satellite remote sensing data is feasible. Cloud cover is a major obstacle to thermal infrared remote sensing applications and remote sensing quantitative retrieval of land surface temperature. Furthermore, cloud frequently exists in most time and covers roughly half the surface of the Earth even if the sky is clear. This is the case especially in some regions of high latitudes in the north hemisphere, e.g. the tropics are covered by cloud for about 60% of the time. Therefore, the influence of clouds on LST deserves more discussion and how to estimate LST of pixels covered by cloud on thermal remotely sensed imagery is one of the cutting-edge research problems. In this article, based on the theory of surface energy balance (SEB), three methods, which are spatial interpretation adjustment method, the adjustment method by correlations between LST and Vegetation Indices (VIs) and improved surface energy balance method, have been put forward for the estimation of LST when the sky is cloudy. Moreover, the lowland effect of LST spatial distribution under cloud cover and the method for the calculation of its intensity (denoted as SE) were also discussed. Generally speaking, when SE equals to 1, it means that SE reaches its maximum due to thick cloud cover .While SE equals to 0, it means that there is no lowland effect in clear sky. SE is strongly affected by the cloud and surface conditions. That is to say, SE is influenced greatly by cloud properties such as the time it appears and lasts, its shape, thickness and height and surface

  18. Role of surface temperature in fluorocarbon plasma-surface interactions

    Energy Technology Data Exchange (ETDEWEB)

    Nelson, Caleb T.; Overzet, Lawrence J.; Goeckner, Matthew J. [Department of Electrical Engineering, University of Texas at Dallas, PO Box 830688, Richardson, TX 75083 (United States)

    2012-07-15

    This article examines plasma-surface reaction channels and the effect of surface temperature on the magnitude of those channels. Neutral species CF{sub 4}, C{sub 2}F{sub 6}, and C{sub 3}F{sub 8} are produced on surfaces. The magnitude of the production channel increases with surface temperature for all species, but favors higher mass species as the temperature is elevated. Additionally, the production rate of CF{sub 2} increases by a factor of 5 as the surface temperature is raised from 25 Degree-Sign C to 200 Degree-Sign C. Fluorine density, on the other hand, does not change as a function of either surface temperature or position outside of the plasma glow. This indicates that fluorine addition in the gas-phase is not a dominant reaction. Heating reactors can result in higher densities of depositing radical species, resulting in increased deposition rates on cooled substrates. Finally, the sticking probability of the depositing free radical species does not change as a function of surface temperature. Instead, the surface temperature acts together with an etchant species (possibly fluorine) to elevate desorption rates on that surface at temperatures lower than those required for unassisted thermal desorption.

  19. Assessment of land surface temperature and heat fluxes over Delhi using remote sensing data.

    Science.gov (United States)

    Chakraborty, Surya Deb; Kant, Yogesh; Mitra, Debashis

    2015-01-15

    Surface energy processes has an essential role in urban weather, climate and hydrosphere cycles, as well in urban heat redistribution. The research was undertaken to analyze the potential of Landsat and MODIS data in retrieving biophysical parameters in estimating land surface temperature & heat fluxes diurnally in summer and winter seasons of years 2000 and 2010 and understanding its effect on anthropogenic heat disturbance over Delhi and surrounding region. Results show that during years 2000-2010, settlement and industrial area increased from 5.66 to 11.74% and 4.92 to 11.87% respectively which in turn has direct effect on land surface temperature (LST) and heat fluxes including anthropogenic heat flux. Based on the energy balance model for land surface, a method to estimate the increase in anthropogenic heat flux (Has) has been proposed. The settlement and industrial areas has higher amounts of energy consumed and has high values of Has in all seasons. The comparison of satellite derived LST with that of field measured values show that Landsat estimated values are in close agreement within error of ±2 °C than MODIS with an error of ±3 °C. It was observed that, during 2000 and 2010, the average change in surface temperature using Landsat over settlement & industrial areas of both seasons is 1.4 °C & for MODIS data is 3.7 °C. The seasonal average change in anthropogenic heat flux (Has) estimated using Landsat & MODIS is up by around 38 W/m(2) and 62 W/m(2) respectively while higher change is observed over settlement and concrete structures. The study reveals that the dynamic range of Has values has increased in the 10 year period due to the strong anthropogenic influence over the area. The study showed that anthropogenic heat flux is an indicator of the strength of urban heat island effect, and can be used to quantify the magnitude of the urban heat island effect.

  20. A Temperature and Emissivity Separation Algorithm for Landsat-8 Thermal Infrared Sensor Data

    Directory of Open Access Journals (Sweden)

    Songhan Wang

    2015-08-01

    Full Text Available On-board the Landsat-8 satellite, the Thermal Infrared Sensor (TIRS, which has two adjacent thermal channels centered roughly at 10.9 and 12.0 μm, has a great benefit for the land surface temperature (LST retrieval. The single-channel algorithm (SC and split-window algorithm (SW have been applied to retrieve the LST from TIRS data, which need the land surface emissivity (LSE as prior knowledge. Due to the big challenge of determining the LSE, this study develops a temperature and emissivity separation algorithm which can simultaneously retrieve the LST and LSE. Based on the laboratory emissivity spectrum data, the minimum-maximum emissivity difference module (MMD module for TIRS data is developed. Then, an emissivity log difference method (ELD method is developed to maintain the emissivity spectrum shape in the iterative process, which is based on the modified Wien’s approximation. Simulation results show that the root-mean-square-errors (RMSEs are below 0.7 K for the LST and below 0.015 for the LSE. Based on the SURFRAD ground measurements, further evaluation demonstrates that the average absolute error of the LST is about 1.7 K, which indicated that the algorithm is capable of retrieving the LST and LSE simultaneously from TIRS data with fairly good results.

  1. Gravity increased by lunar surface temperature

    Science.gov (United States)

    Keene, James

    2013-04-01

    Quantitatively large effects of lunar surface temperature on apparent gravitational force measured by lunar laser ranging (LLR) and lunar perigee may challenge widely accepted theories of gravity. LLR data grouped by days from full moon shows the moon is about 5 percent closer to earth at full moon compared to 8 days before or after full moon. In a second, related result, moon perigees were least distant in days closer to full moon. Moon phase was used as proxy independent variable for lunar surface temperature. The results support the prediction by binary mechanics that gravitational force increases with object surface temperature.

  2. Sea Surface Temperature Average_SST_Master

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Sea surface temperature collected via satellite imagery from http://www.esrl.noaa.gov/psd/data/gridded/data.noaa.ersst.html and averaged for each region using ArcGIS...

  3. OW NOAA GOES Sea-Surface Temperature

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The dataset contains satellite-derived sea-surface temperature measurements collected by means of the Geostationary Orbiting Environmental Satellite. The data is...

  4. evaluation of land surface temperature parameterization ...

    African Journals Online (AJOL)

    user

    1 DEPARTMENT OF PHYSICS, ADEYEMI COLLEGE OF EDUCATION, ONDO, ... Surface temperature (Ts) is vital to the study of land-atmosphere interactions and climate variabilities. .... value = 0.167 m3m-3), and very low for dry days (mean.

  5. Monthly Near-Surface Air Temperature Averages

    Data.gov (United States)

    National Aeronautics and Space Administration — Global surface temperatures in 2010 tied 2005 as the warmest on record. The International Satellite Cloud Climatology Project (ISCCP) was established in 1982 as part...

  6. Sea Surface Temperature (14 KM North America)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Product shows local sea surface temperatures (degrees C). It is a composite gridded-image derived from 8-km resolution SST Observations. It is generated every 48...

  7. Analysed foundation sea surface temperature, global

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The through-cloud capabilities of microwave radiometers provide a valuable picture of global sea surface temperature (SST). To utilize this, scientists at Remote...

  8. Using Landsat Thematic Mapper (TM) sensor to detect change in land surface temperature in relation to land use change in Yazd, Iran

    Science.gov (United States)

    Zareie, Sajad; Khosravi, Hassan; Nasiri, Abouzar; Dastorani, Mostafa

    2016-11-01

    Land surface temperature (LST) is one of the key parameters in the physics of land surface processes from local to global scales, and it is one of the indicators of environmental quality. Evaluation of the surface temperature distribution and its relation to existing land use types are very important to the investigation of the urban microclimate. In arid and semi-arid regions, understanding the role of land use changes in the formation of urban heat islands is necessary for urban planning to control or reduce surface temperature. The internal factors and environmental conditions of Yazd city have important roles in the formation of special thermal conditions in Iran. In this paper, we used the temperature-emissivity separation (TES) algorithm for LST retrieving from the TIRS (Thermal Infrared Sensor) data of the Landsat Thematic Mapper (TM). The root mean square error (RMSE) and coefficient of determination (R2) were used for validation of retrieved LST values. The RMSE of 0.9 and 0.87 °C and R2 of 0.98 and 0.99 were obtained for the 1998 and 2009 images, respectively. Land use types for the city of Yazd were identified and relationships between land use types, land surface temperature and normalized difference vegetation index (NDVI) were analyzed. The Kappa coefficient and overall accuracy were calculated for accuracy assessment of land use classification. The Kappa coefficient values are 0.96 and 0.95 and the overall accuracy values are 0.97 and 0.95 for the 1998 and 2009 classified images, respectively. The results showed an increase of 1.45 °C in the average surface temperature. The results of this study showed that optical and thermal remote sensing methodologies can be used to research urban environmental parameters. Finally, it was found that special thermal conditions in Yazd were formed by land use changes. Increasing the area of asphalt roads, residential, commercial and industrial land use types and decreasing the area of the parks, green spaces and

  9. Urban aerosol effects on surface insolation and surface temperature

    Science.gov (United States)

    Jin, M.; Burian, S. J.; Remer, L. A.; Shepherd, M. J.

    2007-12-01

    Urban aerosol particulates may play a fundamental role in urban microclimates and city-generated mesoscale circulations via its effects on energy balance of the surface. Key questions that need to be addressed include: (1) How do these particles affect the amount of solar energy reaching the surface and resulting surface temperature? (2) Is the effect the same in all cities? and (3) How does it vary from city to city? Using NASA AERONET in-situ observations, a radiative transfer model, and a regional climate mode (MM5), we assess aerosol effects on surface insolation and surf ace temperature for dense urban-polluted regions. Two big cities, one in a developing country (Beijing, P.R. China) and another in developed country (New York City, USA), are selected for inter-comparison. The study reveals that aerosol effects on surface temperature depends largely on aerosols' optical and chemical properties as well as atmosphere and land surface conditions, such as humidity and land cover. Therefore, the actual magnitudes of aerosol effects differ from city to city. Aerosol measurements from AERONET show both average and extreme cases for aerosol impacts on surface insolation. In general, aerosols reduce surface insolation by 30Wm-2. Nevertheless, in extreme cases, such reduction can exceed 100 Wm-2. Consequently, this reduces surface skin temperature 2-10C in an urban environment.

  10. Modeling of global surface air temperature

    Science.gov (United States)

    Gusakova, M. A.; Karlin, L. N.

    2012-04-01

    A model to assess a number of factors, such as total solar irradiance, albedo, greenhouse gases and water vapor, affecting climate change has been developed on the basis of Earth's radiation balance principle. To develop the model solar energy transformation in the atmosphere was investigated. It's a common knowledge, that part of the incoming radiation is reflected into space from the atmosphere, land and water surfaces, and another part is absorbed by the Earth's surface. Some part of outdoing terrestrial radiation is retained in the atmosphere by greenhouse gases (carbon dioxide, methane, nitrous oxide) and water vapor. Making use of the regression analysis a correlation between concentration of greenhouse gases, water vapor and global surface air temperature was obtained which, it is turn, made it possible to develop the proposed model. The model showed that even smallest fluctuations of total solar irradiance intensify both positive and negative feedback which give rise to considerable changes in global surface air temperature. The model was used both to reconstruct the global surface air temperature for the 1981-2005 period and to predict global surface air temperature until 2030. The reconstructions of global surface air temperature for 1981-2005 showed the models validity. The model makes it possible to assess contribution of the factors listed above in climate change.

  11. Attenuating the surface Urban Heat Island within the Local Thermal Zones through land surface modification.

    Science.gov (United States)

    Wang, Jiong; Ouyang, Wanlu

    2017-02-01

    Inefficient mitigation of excessive heat is attributed to the discrepancy between the scope of climate research and conventional planning practice. This study approaches this problem at both domains. Generally, the study, on one hand, claims that the climate research of the temperature phenomenon should be at local scale, where implementation of planning and design strategies can be more feasible. On the other hand, the study suggests that the land surface factors should be organized into zones or patches, which conforms to the urban planning and design manner. Thus in each zone, the land surface composition of those excessively hot places can be compared to the zonal standard. The comparison gives guidance to the modification of the land surface factors at the target places. Specifically, this study concerns the Land Surface Temperature (LST) in Wuhan, China. The land surface is classified into Local Thermal Zones (LTZ). The specifications of temperature sensitive land surface factors are relative homogeneous in each zone and so is the variation of the LST. By extending the city scale analysis of Urban Heat Island into local scale, the Local Surface Urban Heat Islands (LSUHIs) are extracted. Those places in each zone that constantly maintain as LSUHI and exceed the homogenous LST variation are considered as target places or hotspots with higher mitigation or adaptation priority. The operation is equivalent to attenuate the abnormal LST variation in each zone. The framework is practical in the form of prioritization and zoning, and mitigation strategies are essentially operated locally.

  12. Impact of impervious surface on urban heat island in Wuhan, China

    Science.gov (United States)

    Cao, Liqin; Li, Pingxiang; Zhang, Liangpei

    2008-12-01

    Impervious surfaces (IS), as one of the most important land cover types and characteristic of urban/suburban1 environments, are known to effect urban surface temperatures by altering the sensible and latent heat fluxes. This study examined the effect IS spatial patterns have on land surface temperature (LST) in Wuhan, China. LST were retrieved from the corrected TIR band (10.4~12.5μm) of Landsat images using Single-Channel method. IS distribution, together with vegetation and soil distribution, was estimated through a fully constrained linear spectral mixture model. Four endmembers, vegetation, soil, low albedo, and high albedo were selected to model heterogeneous urban land cover. Impervious surface fraction was estimated by analyzing low and high albedo endmembers. Correlation analyses were conducted to investigate the changing relationship of LST with impervious surface. The result indicated there was a strongly positive relationship (r2>0.85) between LST and percent impervious surface for all seasons, which suggested the variations in LST could be accounted for very well by percent impervious surface.

  13. International Surface Temperature Initiative (ISTI) Global Land Surface Temperature Databank - Stage 2 Monthly

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The global land surface temperature databank contains monthly timescale mean, max, and min temperature for approximately 40,000 stations globally. It was developed...

  14. International Surface Temperature Initiative (ISTI) Global Land Surface Temperature Databank - Stage 2 Daily

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The global land surface temperature databank contains monthly timescale mean, max, and min temperature for approximately 40,000 stations globally. It was developed...

  15. International Surface Temperature Initiative (ISTI) Global Land Surface Temperature Databank - Stage 3 Monthly

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Global Land Surface Temperature Databank contains monthly timescale mean, maximum, and minimum temperature for approximately 40,000 stations globally. It was...

  16. International Surface Temperature Initiative (ISTI) Global Land Surface Temperature Databank - Stage 1 Daily

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The global land surface temperature databank contains monthly timescale mean, max, and min temperature for approximately 40,000 stations globally. It was developed...

  17. International Surface Temperature Initiative (ISTI) Global Land Surface Temperature Databank - Stage 1 Monthly

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The global land surface temperature databank contains monthly timescale mean, max, and min temperature for approximately 40,000 stations globally. It was developed...

  18. Amino Acids Stimulate TORC1 through Lst4-Lst7, a GTPase-Activating Protein Complex for the Rag Family GTPase Gtr2

    Directory of Open Access Journals (Sweden)

    Marie-Pierre Péli-Gulli

    2015-10-01

    Full Text Available Rag GTPases assemble into heterodimeric complexes consisting of RagA or RagB and RagC or RagD in higher eukaryotes, or Gtr1 and Gtr2 in yeast, to relay amino acid signals toward the growth-regulating target of rapamycin complex 1 (TORC1. The TORC1-stimulating state of Rag GTPase heterodimers, containing GTP- and GDP-loaded RagA/B/Gtr1 and RagC/D/Gtr2, respectively, is maintained in part by the FNIP-Folliculin RagC/D GAP complex in mammalian cells. Here, we report the existence of a similar Lst4-Lst7 complex in yeast that functions as a GAP for Gtr2 and that clusters at the vacuolar membrane in amino acid-starved cells. Refeeding of amino acids, such as glutamine, stimulated the Lst4-Lst7 complex to transiently bind and act on Gtr2, thereby entailing TORC1 activation and Lst4-Lst7 dispersal from the vacuolar membrane. Given the remarkable functional conservation of the RagC/D/Gtr2 GAP complexes, our findings could be relevant for understanding the glutamine addiction of mTORC1-dependent cancers.

  19. Frost Monitoring and Forecasting Using MODIS Land Surface Temperature Data and a Numerical Weather Prediction Model Forecasts for Eastern Africa

    Science.gov (United States)

    Kabuchanga, Eric; Flores, Africa; Malaso, Susan; Mungai, John; Sakwa, Vincent; Shaka, Ayub; Limaye, Ashutosh

    2014-01-01

    Frost is a major challenge across Eastern Africa, severely impacting agricultural farms. Frost damages have wide ranging economic implications on tea and coffee farms, which represent a major economic sector. Early monitoring and forecasting will enable farmers to take preventive actions to minimize the losses. Although clearly important, timely information on when to protect crops from freezing is relatively limited. MODIS Land Surface Temperature (LST) data, derived from NASA's Terra and Aqua satellites, and 72-hr weather forecasts from the Kenya Meteorological Service's operational Weather Research Forecast model are enabling the Regional Center for Mapping of Resources for Development (RCMRD) and the Tea Research Foundation of Kenya to provide timely information to farmers in the region. This presentation will highlight an ongoing collaboration among the Kenya Meteorological Service, RCMRD, and the Tea Research Foundation of Kenya to identify frost events and provide farmers with potential frost forecasts in Eastern Africa.

  20. Calibration of surface temperature on rocky exoplanets

    Science.gov (United States)

    Kashyap Jagadeesh, Madhu

    2016-07-01

    Study of exoplanets and the search for life elsewhere has been a very fascinating area in recent years. Presently, lots of efforts have been channelled in this direction in the form of space exploration and the ultimate search for the habitable planet. One of the parametric methods to analyse the data available from the missions such as Kepler, CoRoT, etc, is the Earth Similarity Index (ESI), defined as a number between zero (no similarity) and one (identical to Earth), introduced to assess the Earth likeness of exoplanets. A multi-parameter ESI scale depends on the radius, density, escape velocity and surface temperature of exoplanets. Our objective is to establish how exactly the individual parameters, entering the interior ESI and surface ESI, are contributing to the global ESI, using the graphical analysis. Presently, the surface temperature estimates are following a correction factor of 30 K, based on the Earth's green-house effect. The main objective of this work in calculations of the global ESI using the HabCat data is to introduce a new method to better estimate the surface temperature of exoplanets, from theoretical formula with fixed albedo factor and emissivity (Earth values). From the graphical analysis of the known data for the Solar System objects, we established the calibration relation between surface and equilibrium temperatures for the Solar System objects. Using extrapolation we found that the power function is the closest description of the trend to attain surface temperature. From this we conclude that the correction term becomes very effective way to calculate the accurate value of the surface temperature, for further analysis with our graphical methodology.

  1. Integrative inversion of land surface component temperature

    Institute of Scientific and Technical Information of China (English)

    FAN Wenjie; XU Xiru

    2005-01-01

    In this paper, the row winter wheat was selected as the example to study the component temperature inversion method of land surface target in detail. The result showed that the structural pattern of row crop can affect the inversion precision of component temperature evidently. Choosing appropriate structural pattern of row crop can improve the inversion precision significantly. The iterative method combining inverse matrix was a stable method that was fit for inversing component temperature of land surface target. The result of simulation and field experiment showed that the integrative method could remarkably improve the inversion accuracy of the lighted soil surface temperature and the top layer canopy temperature, and enhance inversion stability of components temperature. Just two parameters were sufficient for accurate atmospheric correction of multi-angle and multi-spectral thermal infrared data: atmospheric transmittance and the atmospheric upwelling radiance. If the atmospheric parameters and component temperature can be inversed synchronously, the really and truly accurate atmospheric correction can be achieved. The validation using ATSRII data showed that the method was useful.

  2. LST data management and mission operations concept. [pointing control optimization for maximum data

    Science.gov (United States)

    Walker, R.; Hudson, F.; Murphy, L.

    1977-01-01

    A candidate design concept for an LST ground facility is described. The design objectives were to use NASA institutional hardware, software and facilities wherever practical, and to maximize efficiency of telescope use. The pointing control performance requirements of LST are summarized, and the major data interfaces of the candidate ground system are diagrammed.

  3. Use of Land Surface Temperature Observations in a Two-Source Energy Balance Model Towards Improved Monitoring of Evapotranspiration and Drought

    Science.gov (United States)

    Hain, C.; Anderson, M. C.; Otkin, J.; Semmens, K. A.; Zhan, X.; Fang, L.; Li, Z.

    2014-12-01

    As the world's water resources come under increasing tension due to the dual stressors of climate change and population growth, accurate knowledge of water consumption through evapotranspiration (ET) over a range in spatial scales will be critical in developing adaptation strategies. However, direct validation of ET models is challenging due to lack of available observations that are sufficiently representative at the model grid scale (10-100 km). Prognostic land-surface models require accurate information about observed precipitation, soil moisture storage, groundwater, and artificial controls on water supply (e.g., irrigation, dams, etc.) to reliably link rainfall to evaporative fluxes. In contrast, diagnostic estimates of ET can be generated, with no prior knowledge of the surface moisture state, by energy balance models using thermal-infrared remote sensing of land-surface temperature (LST) as a boundary condition. One such method, the Atmosphere Land Exchange Inverse (ALEXI) model provides estimates of surface energy fluxes through the use of mid-morning change in LST and radiation inputs. The LST inputs carry valuable proxy information regarding soil moisture and its effect on soil evaporation and canopy transpiration. Additionally, the Evaporative Stress Index (ESI) representing anomalies in the ratio of actual-to-potential ET has shown to be a reliable indicator of drought. ESI maps over the continental US show good correspondence with standard drought metrics and with patterns of precipitation, but can be generated at significantly higher spatial resolution due to a limited reliance on ground observations. Furthermore, ESI is a measure of actual stress rather than potential for stress, and has physical relevance to projected crop development. Because precipitation is not used in construction of the ESI, it provides an independent assessment of drought conditions and has particular utility for real-time monitoring in regions with sparse rainfall data or

  4. Temperature limit values for gripping cold surfaces

    NARCIS (Netherlands)

    Malchaire, J.; Geng, Q.; Den Hartog, E.; Havenith, G.; Holmer, I.; Piette, A.; Powell, S.L.; Rintamäki, H.; Rissanen, S.

    2002-01-01

    Objectives. At the request of the European Commission and in the framework of the European Machinery Directive, research was conducted jointly in five different laboratories to develop specifications for surface temperature limit values for the gripping and handling of cold items. Methods. Four

  5. Temperature limit values for gripping cold surfaces

    NARCIS (Netherlands)

    Malchaire, J.; Geng, Q.; Den Hartog, E.; Havenith, G.; Holmer, I.; Piette, A.; Powell, S.L.; Rintamäki, H.; Rissanen, S.

    2002-01-01

    Objectives. At the request of the European Commission and in the framework of the European Machinery Directive, research was conducted jointly in five different laboratories to develop specifications for surface temperature limit values for the gripping and handling of cold items. Methods. Four hund

  6. Surface temperature excess in heterogeneous catalysis

    NARCIS (Netherlands)

    Zhu, L.

    2005-01-01

    In this dissertation we study the surface temperature excess in heterogeneous catalysis. For heterogeneous reactions, such as gas-solid catalytic reactions, the reactions take place at the interfaces between the two phases: the gas and the solid catalyst. Large amount of reaction heats are released

  7. Surface temperature excess in heterogeneous catalysis

    NARCIS (Netherlands)

    Zhu, L.

    2005-01-01

    In this dissertation we study the surface temperature excess in heterogeneous catalysis. For heterogeneous reactions, such as gas-solid catalytic reactions, the reactions take place at the interfaces between the two phases: the gas and the solid catalyst. Large amount of reaction heats are released

  8. Trend patterns in global sea surface temperature

    DEFF Research Database (Denmark)

    Barbosa, S.M.; Andersen, Ole Baltazar

    2009-01-01

    Isolating long-term trend in sea surface temperature (SST) from El Nino southern oscillation (ENSO) variability is fundamental for climate studies. In the present study, trend-empirical orthogonal function (EOF) analysis, a robust space-time method for extracting trend patterns, is applied...

  9. Advancing the retrievals of surface emissivity by modelling the spatial distribution of temperature in the thermal hyperspectral scene

    Science.gov (United States)

    Shimoni, M.; Haelterman, R.; Lodewyckx, P.

    2016-05-01

    Land Surface Temperature (LST) and Land Surface Emissivity (LSE) are commonly retrieved from thermal hyperspectral imaging. However, their retrieval is not a straightforward procedure because the mathematical problem is ill-posed. This procedure becomes more challenging in an urban area where the spatial distribution of temperature varies substantially in space and time. For assessing the influence of several spatial variances on the deviation of the temperature in the scene, a statistical model is created. The model was tested using several images from various times in the day and was validated using in-situ measurements. The results highlight the importance of the geometry of the scene and its setting relative to the position of the sun during day time. It also shows that when the position of the sun is in zenith, the main contribution to the thermal distribution in the scene is the thermal capacity of the landcover materials. In this paper we propose a new Temperature and Emissivity Separation (TES) method which integrates 3D surface and landcover information from LIDAR and VNIR hyperspectral imaging data in an attempt to improve the TES procedure for a thermal hyperspectral scene. The experimental results prove the high accuracy of the proposed method in comparison to another conventional TES model.

  10. Estimation of daily minimum land surface air temperature using MODIS data in southern Iran

    Science.gov (United States)

    Didari, Shohreh; Norouzi, Hamidreza; Zand-Parsa, Shahrokh; Khanbilvardi, Reza

    2016-10-01

    Land surface air temperature (LSAT) is a key variable in agricultural, climatological, hydrological, and environmental studies. Many of their processes are affected by LSAT at about 5 cm from the ground surface (LSAT5cm). Most of the previous studies tried to find statistical models to estimate LSAT at 2 m height (LSAT2m) which is considered as a standardized height, and there is not enough study for LSAT5cm estimation models. Accurate measurements of LSAT5cm are generally acquired from meteorological stations, which are sparse in remote areas. Nonetheless, remote sensing data by providing rather extensive spatial coverage can complement the spatiotemporal shortcomings of meteorological stations. The main objective of this study was to find a statistical model from the previous day to accurately estimate spatial daily minimum LSAT5cm, which is very important in agricultural frost, in Fars province in southern Iran. Land surface temperature (LST) data were obtained using the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard Aqua and Terra satellites at daytime and nighttime periods with normalized difference vegetation index (NDVI) data. These data along with geometric temperature and elevation information were used in a stepwise linear model to estimate minimum LSAT5cm during 2003-2011. The results revealed that utilization of MODIS Aqua nighttime data of previous day provides the most applicable and accurate model. According to the validation results, the accuracy of the proposed model was suitable during 2012 (root mean square difference (RMSD) = 3.07 °C, {R}_{adj}^2 = 87 %). The model underestimated (overestimated) high (low) minimum LSAT5cm. The accuracy of estimation in the winter time was found to be lower than the other seasons (RMSD = 3.55 °C), and in summer and winter, the errors were larger than in the remaining seasons.

  11. Status of the Sea & Land Surface Temperature Radiometer (SLSTR) for the Sentinel 3 GMES Mission

    Science.gov (United States)

    Coppo, Peter; Cosi, Massimo; Engel, Wolfgang; Nieke, Jens; Smith, Dave; Bianchi, Stephane

    2010-10-01

    The Sea & Land Surface Temperature Radiometer (SLSTR) is a high accuracy infrared radiometer selected as optical payload for the Sentinel 3 component of the GMES mission, to provide climatological data continuity respect to the previous ERS and ESA Envisat missions, that embarked respectively the ATSR, ATSR-2 and AATSR payloads. The instrument design follows the dual view concept of the ATSR series with some notable improvements. An increased swath width in both nadir and oblique views (1400 and 740 km) provides measurements at global coverage of Sea and Land Surface Temperature (SST/LST) with daily revisit times, which is useful for climate and meteorology (1 Km spatial resolution). Improved day-time cloud screening and other atmospheric products will be possible from the increased spatial resolution (0.5 Km) of the VIS and SWIR channels and additional SWIR channels at 1.375μm and 2.25μm. Two additional channels using dedicated detector and electronics elements are also included for high temperature events monitoring (1 km spatial resolution). The two Earth viewing swaths are generated using two telescopes and scan mirrors that are optically combined by means of a switching mirror at the entrance of a common Focal Plane Assembly. The eleven spectral channels (3 VIS, 3 SWIR, 2 MWIR, 3 TIR) are split within the FPA using a series of dichroics. The SWIR, MWIR and TIR optics/detectors are cooled down to 80 K with an active cryocooler, while the VIS detectors work at a stabilised uncooled temperature. The paper highlights the technical and programmatic status of the project, which is now in phase C.

  12. Surface defects and temperature on atomic friction

    Energy Technology Data Exchange (ETDEWEB)

    Fajardo, O Y; Mazo, J J, E-mail: yovany@unizar.es [Departamento de Fisica de la Materia Condensada and Instituto de Ciencia de Materiales de Aragon, CSIC-Universidad de Zaragoza, 50009 Zaragoza (Spain)

    2011-09-07

    We present a theoretical study of the effect of surface defects on atomic friction in the stick-slip dynamical regime of a minimalistic model. We focus on how the presence of defects and temperature change the average properties of the system. We have identified two main mechanisms which modify the mean friction force of the system when defects are considered. As expected, defects change the potential profile locally and thus affect the friction force. But the presence of defects also changes the probability distribution function of the tip slip length and thus the mean friction force. We corroborated both effects for different values of temperature, external load, dragging velocity and damping. We also show a comparison of the effects of surface defects and surface disorder on the dynamics of the system. (paper)

  13. Surface temperature distribution in broiler houses

    Directory of Open Access Journals (Sweden)

    MS Baracho

    2011-09-01

    Full Text Available In the Brazilian meat production scenario broiler production is the most dynamic segment. Despite of the knowledge generated in the poultry production chain, there are still important gaps on Brazilian rearing conditions as housing is different from other countries. This research study aimed at analyzing the variation in bird skin surface as function of heat distribution inside broiler houses. A broiler house was virtually divided into nine sectors and measurements were made during the first four weeks of the grow-out in a commercial broiler farm in the region of Rio Claro, São Paulo, Brazil. Rearing ambient temperature and relative humidity, as well as light intensity and air velocity, were recorded in the geometric center of each virtual sector to evaluate the homogeneity of these parameters. Broiler surface temperatures were recorded using infrared thermography. Differences both in surface temperature (Ts and dry bulb temperature (DBT were significant (p<0.05 as a function of week of rearing. Ts was different between the first and fourth weeks (p<0.05 in both flocks. Results showed important variations in rearing environment parameters (temperature and relative humidity and in skin surface temperature as a function of week and house sector. Air velocity data were outside the limits in the first and third weeks in several sectors. Average light intensity values presented low variation relative to week and house sector. The obtained values were outside the recommended ranges, indicating that broilers suffered thermal distress. This study points out the need to record rearing environment data in order to provide better environmental control during broiler grow-out.

  14. Geomagnetic effects on the average surface temperature

    Science.gov (United States)

    Ballatore, P.

    Several results have previously shown as the solar activity can be related to the cloudiness and the surface solar radiation intensity (Svensmark and Friis-Christensen, J. Atmos. Sol. Terr. Phys., 59, 1225, 1997; Veretenenkoand Pudovkin, J. Atmos. Sol. Terr. Phys., 61, 521, 1999). Here, the possible relationships between the averaged surface temperature and the solar wind parameters or geomagnetic activity indices are investigated. The temperature data used are the monthly SST maps (generated at RAL and available from the related ESRIN/ESA database) that represent the averaged surface temperature with a spatial resolution of 0.5°x0.5° and cover the entire globe. The interplanetary data and the geomagnetic data are from the USA National Space Science Data Center. The time interval considered is 1995-2000. Specifically, possible associations and/or correlations of the average temperature with the interplanetary magnetic field Bz component and with the Kp index are considered and differentiated taking into account separate geographic and geomagnetic planetary regions.

  15. Decomposing Person and Occasion-Specific Effects: An Extension of Latent State-Trait (LSI) Theory to Hierarchical LST Models

    Science.gov (United States)

    Schermelleh-Engel, Karin; Keith, Nina; Moosbrugger, Helfried; Hodapp, Volker

    2004-01-01

    An extension of latent state-trait (LST) theory to hierarchical LST models is presented. In hierarchical LST models, the covariances between 2 or more latent traits are explained by a general 3rd-order factor, and the covariances between latent state residuals pertaining to different traits measured on the same measurement occasion are explained…

  16. Use of Landsat land surface temperature and vegetation indices for monitoring drought in the Salt Lake Basin Area, Turkey.

    Science.gov (United States)

    Orhan, Osman; Ekercin, Semih; Dadaser-Celik, Filiz

    2014-01-01

    The main purpose of this paper is to investigate multitemporal land surface temperature (LST) changes by using satellite remote sensing data. The study included a real-time field work performed during the overpass of Landsat-5 satellite on 21/08/2011 over Salt Lake, Turkey. Normalized vegetation index (NDVI), vegetation condition index (VCI), and temperature vegetation index (TVX) were used for evaluating drought impact over the region between 1984 and 2011. In the image processing step, geometric and radiometric correction procedures were conducted to make satellite remote sensing data comparable with in situ measurements carried out using thermal infrared thermometer supported by hand-held GPS. The results showed that real-time ground and satellite remote sensing data were in good agreement with correlation coefficient (R2) values of 0.90. The remotely sensed and treated satellite images and resulting thematic indices maps showed that dramatic land surface temperature changes occurred (about 2°C) in the Salt Lake Basin area during the 28-year period (1984-2011). Analysis of air temperature data also showed increases at a rate of 1.5-2°C during the same period. Intensification of irrigated agriculture particularly in the southern basin was also detected. The use of water supplies, especially groundwater, should be controlled considering particularly summer drought impacts on the basin.

  17. Use of Landsat Land Surface Temperature and Vegetation Indices for Monitoring Drought in the Salt Lake Basin Area, Turkey

    Directory of Open Access Journals (Sweden)

    Osman Orhan

    2014-01-01

    Full Text Available The main purpose of this paper is to investigate multitemporal land surface temperature (LST changes by using satellite remote sensing data. The study included a real-time field work performed during the overpass of Landsat-5 satellite on 21/08/2011 over Salt Lake, Turkey. Normalized vegetation index (NDVI, vegetation condition index (VCI, and temperature vegetation index (TVX were used for evaluating drought impact over the region between 1984 and 2011. In the image processing step, geometric and radiometric correction procedures were conducted to make satellite remote sensing data comparable with in situ measurements carried out using thermal infrared thermometer supported by hand-held GPS. The results showed that real-time ground and satellite remote sensing data were in good agreement with correlation coefficient (R2 values of 0.90. The remotely sensed and treated satellite images and resulting thematic indices maps showed that dramatic land surface temperature changes occurred (about 2∘C in the Salt Lake Basin area during the 28-year period (1984–2011. Analysis of air temperature data also showed increases at a rate of 1.5–2∘C during the same period. Intensification of irrigated agriculture particularly in the southern basin was also detected. The use of water supplies, especially groundwater, should be controlled considering particularly summer drought impacts on the basin.

  18. Assessment of surface dryness due to deforestation using satellite-based temperature-vegetation dryness index (TVDI) in Rondônia, Amazon

    Science.gov (United States)

    Ryu, J. H.; Cho, J.

    2016-12-01

    The Rondônia is the most deforested region in the Amazon due to human activities such as forest lumbering for the several decades. The deforestation affects to water cycle because evapotranspiration was reduced, and then soil moisture and precipitation will be changed. In this study, we assess surface dryness using satellite-based data such as moderate resolution imaging spectroradiometer (MODIS) land surface temperature (LST), normalized difference vegetation index (NDVI), albedo, TRMM Multi-sensor Precipitation Analysis (TMPA) precipitation from 2002 to 2014, and Global Ozone Monitoring Experiment-2 (GOME-2) sun-induced fluorescence (SIF) from 2007 to 2014. Temperature-vegetation dryness index (TVDI) was calculated using LST and NDVI to evaluate surface dryness during dry season (June-July). TVDI relatively represents the surface dryness on specific area and period. Forest, deforesting and deforested regions were selected in the Rondônia to assess the relative changes on surface dryness occurred from human activity. The relative TVDI (rTVDI) at deforesting region increased because of deforestation, it means that surface in deforesting region became more dryness. We also found that to assess the impact of deforestation using satellite-based precipitation and vegetation conditions such as NDVI and sun-induced fluorescence (SIF) is possible. The relative NDVI (rNDVI) and SIF decreased when TVDI increased, and two variables (rTVDI-rNDVI, rTVDI-SIF) had linear correlation. Thesis results can be helpful to comprehend impact of deforestation in Amazon, and to validate simulations of deforestation from hydrological models.

  19. Experimental study of UTM-LST generic half model transport aircraft

    Science.gov (United States)

    Ujang, M. I.; Mat, S.; Perumal, K.; Mohd. Nasir, M. N.

    2016-10-01

    This paper presents the experimental results from the investigation carried out at the UTM Low Speed wind tunnel facility (UTM-LST) on a half model generic transport aircraft at several configurations of primary control surfaces (flap, aileron and elevator). The objective is to measure the aerodynamic forces and moments due to the configuration changes. The study is carried out at two different speeds of 26.1 m/s and 43.1 m/s at corresponding Reynolds number of 1 × 106 and 2 × 106, respectively. Angle of attack of the model is varied between -2o to 20o. For the flaps, the deflection applied is 0o, 5o and 10o. Meanwhile, for aileron and elevator, the deflection applied is between -10o and 10o. The results show the differences in aerodynamic characteristics of the aircraft at different control surfaces configurations. The results obtained indicate that a laminar separation bubble developed on the surface of the wing at lower angles of attack and show that the separation process is delayed when the Reynolds number is increased.

  20. Validation of the MODIS "Clear-Sky" Surface Temperature of the Greenland Ice Sheet

    Science.gov (United States)

    Hall, Dorothy K.; Koenig, L. S.; DiGirolamo, N. E.; Comiso, J.; Shuman, C. A.

    2011-01-01

    . We use the MODIS ice-surface temperature (IST) algorithm. Validation of the CDR consists of several facets: 1) comparisons between the Terra and Aqua IST maps; 2) comparisons between ISTs and in-situ measurements; 3) comparisons between ISTs and AWS data; and 4) comparisons of ISTs with surface temperatures derived from other satellite instruments such as the Thermal Emission and Reflection Radiometer. In this work, we focus on 1) and 2) above. First we provide comparisons between Terra and Aqua swath-based ISTs at approximately 14:00 Local Solar Time, reprojected to 12.5 km polar stereographic cells. Results show good correspondence when Terra and Aqua data were acquired within 2 hrs of each other. For example, for a cell centered over Summit Camp (72.58 N, 38.5 W), the average agreement between Terra and Aqua ISTs is 0.74 K (February 2003), 0.47 K (April 2003), 0.7 K (August 2003) and 0.96 K (October 2003) with the Terra ISTs being generally lower than the Aqua ISTs. More precise comparisons will be calculated using pixel data at the swath level, and correspondence between Terra and Aqua IST is expected to be closer. (Because of cloud cover and other considerations, only a few common cloud-free swaths are typically available for each month for comparison.) Additionally, previous work comparing land-surface temperatures (LSTs) from the standard MODIS LST product and in-situ surface-temperature data at Summit Camp on the Greenland Ice Sheet show that Terra MODIS LSTs are about 3 K lower than in-situ temperatures at Summit Camp, during the winter of 2008-09. This work will be repeated using both Terra and Aqua IST pixel data (in place of LST data). In conclusion, we demonstrate that the uncertainties in the CDR will be well characterized as we work through the various facets of its validation.

  1. Inter-Seasonal Dynamics of Vegetation Cover and Surface Temperature Distribution: a Case Study of Ondo State, Nigeria

    Science.gov (United States)

    Ibitolu, H. A.; Ogunjobi, K. O.

    2016-06-01

    This study employs Landsat ETM+ satellite imagery to access the inter-seasonal variations of Surface Temperature and Vegetation cover in Ondo State in 2013. Also, air temperature data for year 2013 acquired from 3 synoptic meteorological stations across the state were analyzed. The Single-channel Algorithm was used to extract the surface temperature maps from the digital number embedded within the individual pixel. To understand the spatio-temporal distribution of LST and vegetation across the various landuse types, 200 sample points were randomly chosen, so that each land-use covers 40 points. Imagery for the raining season where unavailable because of the intense cloud cover. Result showed that the lowest air temperature of 20.9°C was in January, while the highest air temperature of 34°C occurred in January and March. There was a significant shift in the vegetation greenness over Ondo State, as average NDVI tend to increase from a weak positive value (0.189) to a moderate value (0.419). The LULC map revealed that vegetation cover occupied the largest area (65%) followed by Built-up (26%), Swampy land (4%), Rock outcrop (3%) and water bodies (2%). The surface temperature maps revealed that January has the lowest temperature of 10°C experienced in the coastal riverine areas of Ilaje and Igbokoda, while the highest temperature of 39°C observed in September is experienced on the rocky grounds. The study also showed the existence of pockets of Urban Heat Islands (UHI) that are well scattered all over the state. This finding proves the capability and reliability of Satellite remote sensing for environmental studies.

  2. A novel gene, lstC, of Listeria monocytogenes is implicated in high salt tolerance.

    Science.gov (United States)

    Burall, Laurel S; Simpson, Alexandra C; Chou, Luoth; Laksanalamai, Pongpan; Datta, Atin R

    2015-06-01

    Listeria monocytogenes, causative agent of human listeriosis, has been isolated from a wide variety of foods including deli meats, soft cheeses, cantaloupes, sprouts and canned mushrooms. Standard control measures for restricting microbial growth such as refrigeration and high salt are often inadequate as L. monocytogenes grows quite well in these environments. In an effort to better understand the genetic and physiological basis by which L. monocytogenes circumvents these controls, a transposon library of L. monocytogenes was screened for changes in their ability to grow in 7% NaCl and/ or at 5 °C. This work identified a transposon insertion upstream of an operon, here named lstABC, that led to a reduction in growth in 7% NaCl. In-frame deletion studies identified lstC which codes for a GNAT-acetyltransferase being responsible for the phenotype. Transcriptomic and RT-PCR analyses identified nine genes that were upregulated in the presence of high salt in the ΔlstC mutant. Further analysis of lstC and the genes affected by ΔlstC is needed to understand LstC's role in salt tolerance. Published by Elsevier Ltd.

  3. Optimized AVHRR land surface temperature downscaling method for local scale observations: case study for the coastal area of the Gulf of Gdańsk

    Directory of Open Access Journals (Sweden)

    Chybicki Andrzej

    2017-09-01

    Full Text Available Satellite imaging systems have known limitations regarding their spatial and temporal resolution. The approaches based on subpixel mapping of the Earth’s environment, which rely on combining the data retrieved from sensors of higher temporal and lower spatial resolution with the data characterized by lower temporal but higher spatial resolution, are of considerable interest. The paper presents the downscaling process of the land surface temperature (LST derived from low resolution imagery acquired by the Advanced Very High Resolution Radiometer (AVHRR, using the inverse technique. The effective emissivity derived from another data source is used as a quantity describing thermal properties of the terrain in higher resolution, and allows the downsampling of low spatial resolution LST images. The authors propose an optimized downscaling method formulated as the inverse problem and show that the proposed approach yields better results than the use of other downsampling methods. The proposed method aims to find estimation of high spatial resolution LST data by minimizing the global error of the downscaling. In particular, for the investigated region of the Gulf of Gdansk, the RMSE between the AVHRR image downscaled by the proposed method and the Landsat 8 LST reference image was 2.255°C with correlation coefficient R equal to 0.828 and Bias = 0.557°C. For comparison, using the PBIM method, it was obtained RMSE = 2.832°C, R = 0.775 and Bias = 0.997°C for the same satellite scene. It also has been shown that the obtained results are also good in local scale and can be used for areas much smaller than the entire satellite imagery scene, depicting diverse biophysical conditions. Specifically, for the analyzed set of small sub-datasets of the whole scene, the obtained RSME between the downscaled and reference image was smaller, by approx. 0.53°C on average, in the case of applying the proposed method than in the case of using the PBIM method.

  4. The international surface temperature initiative's global land surface databank

    Science.gov (United States)

    Lawrimore, J. H.; Rennie, J.; Gambi de Almeida, W.; Christy, J.; Flannery, M.; Gleason, B.; Klein-Tank, A.; Mhanda, A.; Ishihara, K.; Lister, D.; Menne, M. J.; Razuvaev, V.; Renom, M.; Rusticucci, M.; Tandy, J.; Thorne, P. W.; Worley, S.

    2013-09-01

    The International Surface Temperature Initiative (ISTI) consists of an end-to-end process for land surface air temperature analyses. The foundation is the establishment of a global land surface Databank. This builds upon the groundbreaking efforts of scientists in the 1980s and 1990s. While using many of their principles, a primary aim is to improve aspects including data provenance, version control, openness and transparency, temporal and spatial coverage, and improved methods for merging disparate sources. The initial focus is on daily and monthly timescales. A Databank Working Group is focused on establishing Stage-0 (original observation forms) through Stage-3 data (merged dataset without quality control). More than 35 sources of data have already been added and efforts have now turned to development of the initial version of the merged dataset. Methods have been established for ensuring to the extent possible the provenance of all data from the point of observation through all intermediate steps to final archive and access. Databank submission procedures were designed to make the process of contributing data as easy as possible. All data are provided openly and without charge. We encourage the use of these data and feedback from interested users.

  5. Low Temperature Surface Carburization of Stainless Steels

    Energy Technology Data Exchange (ETDEWEB)

    Collins, Sunniva R; Heuer, Arthur H; Sikka, Vinod K

    2007-12-07

    Low-temperature colossal supersaturation (LTCSS) is a novel surface hardening method for carburization of austenitic stainless steels (SS) without the precipitation of carbides. The formation of carbides is kinetically suppressed, enabling extremely high or colossal carbon supersaturation. As a result, surface carbon concentrations in excess of 12 at. % are routinely achieved. This treatment increases the surface hardness by a factor of four to five, improving resistance to wear, corrosion, and fatigue, with significant retained ductility. LTCSS is a diffusional surface hardening process that provides a uniform and conformal hardened gradient surface with no risk of delamination or peeling. The treatment retains the austenitic phase and is completely non-magnetic. In addition, because parts are treated at low temperature, they do not distort or change dimensions. During this treatment, carbon diffusion proceeds into the metal at temperatures that constrain substitutional diffusion or mobility between the metal alloy elements. Though immobilized and unable to assemble to form carbides, chromium and similar alloying elements nonetheless draw enormous amounts of carbon into their interstitial spaces. The carbon in the interstitial spaces of the alloy crystals makes the surface harder than ever achieved before by more conventional heat treating or diffusion process. The carbon solid solution manifests a Vickers hardness often exceeding 1000 HV (equivalent to 70 HRC). This project objective was to extend the LTCSS treatment to other austenitic alloys, and to quantify improvements in fatigue, corrosion, and wear resistance. Highlights from the research include the following: • Extension of the applicability of the LTCSS process to a broad range of austenitic and duplex grades of steels • Demonstration of LTCSS ability for a variety of different component shapes and sizes • Detailed microstructural characterization of LTCSS-treated samples of 316L and other alloys

  6. The surface temperature of free evaporating drops

    Science.gov (United States)

    Borodulin, V. Y.; Letushko, V. N.; Nizovtsev, M. I.; Sterlyagov, A. N.

    2016-10-01

    Complex experimental and theoretical investigation of heat and mass transfer processes was performed at evaporation of free liquid drops. For theoretical calculation the emission-diffusion model was proposed. This allowed taking into account the characteristics of evaporation of small droplets, for which heat and mass transfer processes are not described in the conventional diffusion model. The calculation results of evaporation of droplets of different sizes were compared using two models: the conventional diffusion and emission-diffusion models. To verify the proposed physical model, the evaporation of droplets suspended on a polypropylene fiber was experimentally investigated. The form of droplets in the evaporation process was determined using microphotographing. The temperature was measured on the surfaces of evaporating drops using infrared thermography. The experimental results have showed good agreement with the numerical data for the time of evaporation and the temperature of evaporating drops.

  7. Low temperature surface conductivity of hydrogenated diamond

    Energy Technology Data Exchange (ETDEWEB)

    Sauerer, C.; Ertl, F.; Nebel, C.E.; Stutzmann, M. [Technische Univ. Muenchen, Garching (Germany). Walter-Schottky-Inst. fuer Physikalische Grundlagen der Halbleiterelektronik; Bergonzo, P. [LIST(CEA-Recherche Technology)/DIMIR/SIAR/Saclay, Gif-sur-Yvette (France); Williams, O.A.; Jackman, R.A. [University Coll., London (United Kingdom). Dept. of Electrical and Electronic Engineering

    2001-07-23

    Conductivity and Hall experiments are performed on hydrogenated poly-CVD, atomically flat homoepitaxially grown Ib and natural type IIa diamond layers in the regime 0.34 to 400 K. For all experiments hole transport is detected with sheet resistivities at room temperature in the range 10{sup 4} to 10{sup 5} {omega}/{radical}. We introduce a transport model where a disorder induced tail of localized states traps holes at very low temperatures (T < 70 K). The characteristic energy of the tail is in the range of 6 meV. Towards higher temperatures (T > 70 K) the hole density is approximately constant and the hole mobility {mu} is increasing two orders of magnitude. In the regime 70 K < T < 200 K, {mu} is exponentially activated with 22 meV, above it follows a {proportional_to}T{sup 3/2} law. The activation energy of the hole density at T < 70 K is governed by the energy gap between holes trapped in the tail and the mobility edge which they can propagate. In the temperature regime T < 25 K an increasing hole mobility is detected which is attributed to transport in delocalized states at the surface. (orig.)

  8. Combination of Well-Logging Temperature and Thermal Remote Sensing for Characterization of Geothermal Resources in Hokkaido, Northern Japan

    Directory of Open Access Journals (Sweden)

    Bingwei Tian

    2015-03-01

    Full Text Available Geothermal resources have become an increasingly important source of renewable energy for electrical power generation worldwide. Combined Three Dimension (3D Subsurface Temperature (SST and Land Surface Temperature (LST measurements are essential for accurate assessment of geothermal resources. In this study, subsurface and surface temperature distributions were combined using a dataset comprised of well logs and Thermal Infrared Remote sensing (TIR images from Hokkaido island, northern Japan. Using 28,476 temperature data points from 433 boreholes sites and a method of Kriging with External Drift or trend (KED, SST distribution model from depths of 100 to 1500 m was produced. Regional LST was estimated from 13 scenes of Landsat 8 images. Resultant SST ranged from around 50 °C to 300 °C at a depth of 1500 m. Most of western and part of the eastern Hokkaido are characterized by high temperature gradients, while low temperatures were found in the central region. Higher temperatures in shallower crust imply the western region and part of the eastern region have high geothermal potential. Moreover, several LST zones considered to have high geothermal potential were identified upon clarification of the underground heat distribution according to 3D SST. LST in these zones showed the anomalies, 3 to 9 °C higher than the surrounding areas. These results demonstrate that our combination of TIR and 3D temperature modeling using well logging and geostatistics is an efficient and promising approach to geothermal resource exploration.

  9. Improving Soil Moisture and Temperature Profile and Surface Turbulent Fluxes Estimations in Irrigated Field by Assimilating Multi-source Data into Land Surface Model

    Science.gov (United States)

    Chen, Weijing; Huang, Chunlin; Shen, Huanfeng; Wang, Weizhen

    2016-04-01

    located in an artificial oasis in the semi-arid region of northwestern China. Land surface temperature (LST) and soil volumetric water content (SVW) at first layer measured at Daman station are taken as observations in the framework of data assimilation. The study demonstrates the feasibility of ESIL in improving the soil moisture and temperature profile under unknown irrigation. ESIL promotes the coefficient correlation with in-situ measurements for soil moisture and temperature at first layer from 0.3421 and 0.7027 (ensemble simulation) to 0.8767 and 0.8304 meanwhile all the RMSE of soil moisture and temperature in deeper layers dramatically decrease more than 40 percent in different degree. To verify the reliability of ESIL in practical application, thereby promoting the utilization of satellite data, we test ESIL with varying observation internal interval and standard deviation. As a consequence, ESIL shows stabilized and promising effectiveness in soil moisture and soil temperature estimation.

  10. Satellite Sensed Skin Sea Surface Temperature

    Science.gov (United States)

    Donlon, Craig

    1997-01-01

    Quantitative predictions of spatial and temporal changes the global climate rely heavily on the use of computer models. Unfortunately, such models cannot provide the basis for climate prediction because key physical processes are inadequately treated. Consequently, fine tuning procedures are often used to optimize the fit between model output and observational data and the validation of climate models using observations is essential if model based predictions of climate change are to be treated with any degree of confidence. Satellite Sea Surface Temperature (SST) observations provide high spatial and temporal resolution data which is extremely well suited to the initialization, definition of boundary conditions and, validation of climate models. In the case of coupled ocean-atmosphere models, the SST (or more correctly the 'Skin' SST (SSST)) is a fundamental diagnostic variable to consider in the validation process. Daily global SST maps derived from satellite sensors also provide adequate data for the detection of global patterns of change which, unlike any other SST data set, repeatedly extend into the southern hemisphere extra-tropical regions. Such data are essential to the success of the spatial 'fingerprint' technique, which seeks to establish a north-south asymmetry where warming is suppressed in the high latitude Southern Ocean. Some estimates suggest that there is a greater than 80% chance of directly detecting significant change (97.5 % confidence level) after 10-12 years of consistent global observations of mean sea surface temperature. However, these latter statements should be qualified with the assumption that a negligible drift in the observing system exists and that biases between individual instruments required to derive a long term data set are small. Given that current estimates for the magnitude of global warming of 0.015 K yr(sup -1) - 0.025 K yr(sup -1), satellite SST data sets need to be both accurate and stable if such a warming trend is to

  11. Extended Reconstructed Sea Surface Temperature (ERSST), Version 4

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Extended Reconstructed Sea Surface Temperature (ERSST) dataset is a global monthly sea surface temperature analysis on a 2x2 degree grid derived from the...

  12. NOAA Global Surface Temperature Dataset, Version 4.0

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The NOAA Global Surface Temperature Dataset (NOAAGlobalTemp) is derived from two independent analyses: the Extended Reconstructed Sea Surface Temperature (ERSST)...

  13. HTPro: Low-temperature Surface Hardening of Stainless Steel

    DEFF Research Database (Denmark)

    Christiansen, Thomas Lundin; Somers, Marcel A. J.

    2013-01-01

    Low-temperature surface hardening of stainless steel provides the required performance properties without affecting corrosion resistance.......Low-temperature surface hardening of stainless steel provides the required performance properties without affecting corrosion resistance....

  14. Merged Land and Ocean Surface Temperature, Version 3.5

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The historical Merged Land-Ocean Surface Temperature Analysis (MLOST) is derived from two independent analyses, an Extended Reconstructed Sea Surface Temperature...

  15. Middle Pliocene sea surface temperature variability

    Science.gov (United States)

    Dowsett, H.J.; Chandler, M.A.; Cronin, T. M.; Dwyer, G.S.

    2005-01-01

    Estimates of sea surface temperature (SST) based upon foraminifer, diatom, and ostracod assemblages from ocean cores reveal a warm phase of the Pliocene between about 3.3 and 3.0 Ma. Pollen records and plant megafossils, although not as well dated, show evidence for a warmer climate at about the same time. Increased greenhouse forcing and altered ocean heat transport are the leading candidates for the underlying cause of Pliocene global warmth. Despite being a period of global warmth, this interval encompasses considerable variability. Two new SST reconstructions are presented that are designed to provide a climatological error bar for warm peak phases of the Pliocene and to document the spatial distribution and magnitude of SST variability within the mid-Pliocene warm period. These data suggest long-term stability of low-latitude SST and document greater variability in regions of maximum warming. Copyright 2005 by the American Geophysical Union.

  16. Impact of Atlantic sea surface temperatures on the warmest global surface air temperature of 1998

    Science.gov (United States)

    Lu, Riyu

    2005-03-01

    The year 1998 is the warmest year in the record of instrumental measurements. In this study, an atmospheric general circulation model is used to investigate the role of sea surface temperatures (SSTs) in this warmth, with a focus on the role of the Atlantic Ocean. The model forced with the observed global SSTs captures the main features of land surface air temperature anomalies in 1998. A sensitivity experiment shows that in comparison with the global SST anomalies, the Atlantic SST anomalies can explain 35% of the global mean surface air temperature (GMAT) anomaly, and 57% of the land surface air temperature anomaly in 1998. The mechanisms through which the Atlantic Ocean influences the GMAT are likely different from season to season. Possible detailed mechanisms involve the impact of SST anomalies on local convection in the tropical Atlantic region, the consequent excitation of a Rossby wave response that propagates into the North Atlantic and the Eurasian continent in winter and spring, and the consequent changes in tropical Walker circulation in summer and autumn that induce changes in convection over the tropical Pacific. This in turn affects climate in Asia and Australia. The important role of the Atlantic Ocean suggests that attention should be paid not only to the tropical Pacific Ocean, but also to the tropical Atlantic Ocean in understanding the GMAT variability and its predictability.

  17. Low Temperature Surface Carburization of Stainless Steels

    Energy Technology Data Exchange (ETDEWEB)

    Collins, Sunniva R; Heuer, Arthur H; Sikka, Vinod K

    2007-12-07

    Low-temperature colossal supersaturation (LTCSS) is a novel surface hardening method for carburization of austenitic stainless steels (SS) without the precipitation of carbides. The formation of carbides is kinetically suppressed, enabling extremely high or colossal carbon supersaturation. As a result, surface carbon concentrations in excess of 12 at. % are routinely achieved. This treatment increases the surface hardness by a factor of four to five, improving resistance to wear, corrosion, and fatigue, with significant retained ductility. LTCSS is a diffusional surface hardening process that provides a uniform and conformal hardened gradient surface with no risk of delamination or peeling. The treatment retains the austenitic phase and is completely non-magnetic. In addition, because parts are treated at low temperature, they do not distort or change dimensions. During this treatment, carbon diffusion proceeds into the metal at temperatures that constrain substitutional diffusion or mobility between the metal alloy elements. Though immobilized and unable to assemble to form carbides, chromium and similar alloying elements nonetheless draw enormous amounts of carbon into their interstitial spaces. The carbon in the interstitial spaces of the alloy crystals makes the surface harder than ever achieved before by more conventional heat treating or diffusion process. The carbon solid solution manifests a Vickers hardness often exceeding 1000 HV (equivalent to 70 HRC). This project objective was to extend the LTCSS treatment to other austenitic alloys, and to quantify improvements in fatigue, corrosion, and wear resistance. Highlights from the research include the following: • Extension of the applicability of the LTCSS process to a broad range of austenitic and duplex grades of steels • Demonstration of LTCSS ability for a variety of different component shapes and sizes • Detailed microstructural characterization of LTCSS-treated samples of 316L and other alloys

  18. Turbulent Flow past High Temperature Surfaces

    Science.gov (United States)

    Mehmedagic, Igbal; Thangam, Siva; Carlucci, Pasquale; Buckley, Liam; Carlucci, Donald

    2014-11-01

    Flow over high-temperature surfaces subject to wall heating is analyzed with applications to projectile design. In this study, computations are performed using an anisotropic Reynolds-stress model to study flow past surfaces that are subject to radiative flux. The model utilizes a phenomenological treatment of the energy spectrum and diffusivities of momentum and heat to include the effects of wall heat transfer and radiative exchange. The radiative transport is modeled using Eddington approximation including the weighted effect of nongrayness of the fluid. The time-averaged equations of motion and energy are solved using the modeled form of transport equations for the turbulence kinetic energy and the scalar form of turbulence dissipation with an efficient finite-volume algorithm. The model is applied for available test cases to validate its predictive capabilities for capturing the effects of wall heat transfer. Computational results are compared with experimental data available in the literature. Applications involving the design of projectiles are summarized. Funded in part by U.S. Army, ARDEC.

  19. Aggregation and Disaggregation Techniques Applied on Remotely Sensed Data to Obtain Optimum Resolution for Surface Energy Fluxes Estimation

    Science.gov (United States)

    Agam, N.; Kustas, W. P.; Li, F.; Anderson, M. C.

    2006-05-01

    Continuous monitoring of surface energy fluxes provides an important tool for precision agriculture management. It is, therefore, desirable to obtain these fluxes at agricultural field size (length scale ~ 10-100 m). To date, land surface temperature (LST), a fundamental input required for flux computations, is usually available at a nominal resolution of 1 km, which disables field-scale monitoring. Disaggregating LST data into field-scale sub-pixels was found to be possible, with deterioration in temperature accuracy as sub-pixel size is reduced. In contrast to LST, land use and fractional vegetation cover (LU and FC, additional key inputs) are available at high spatial resolution (e.g., 30 m). Aggregation of LU and FC to meet the lower resolution LST data introduces errors when aggregating to larger pixel sizes. The objective of this research is to find the optimum resolution that will minimize the errors due to aggregation of LU/FC and disaggregation of LST data, to provide continuous estimates of field scale surface energy fluxes. Data were used from the 2002 Soil Moisture-Atmosphere Coupling Experiment (SMACEX02) conducted over the upper Midwest corn and soybean production region of Iowa. Three dates during the period of rapid crops growth (June 23, July 1, and July 8) for which Landsat TM images are available were analyzed. The original pixels were aggregated to form 960 m pixels (to mimic thermal data currently available from MODIS) and were then disaggregated following the procedure suggested by Kustas et al. (2003)* to form 60, 120, and 240 m sub-pixels. LU and FC were obtained at 30 m resolution and then aggregated to 60, 120, 240, and 960 m. The Two-Source-Model was run at each of the resolutions using the pertinent inputs. The model output at 60 m resolution, using the original LST data was considered the base line, to which all other outputs were compared. For comparing the flux results at the lower resolutions, the 60 m flux output was aggregated. The

  20. Automatic estimation of lake ice cover and lake surface temperature using ENVISAT MERIS and AATSR

    Science.gov (United States)

    Rudjord, Ø.; Due Trier, Ø.; Solberg, R.

    2012-04-01

    Lake ice plays an important role in the understanding of the processes of cold region freshwater. On northern latitudes lakes form a major part of atmospheric and hydrologic systems, and a proper understanding of the water and energy budget of lakes is necessary to be able to forecast weather, climate and river flows. We will here present two algorithms for automatic estimation of lake ice cover and lake surface temperature using optical and thermal data, well suited for evaluating large time series of data. The method for estimating the lake surface temperature (LST) from measurements of thermal radiation is based on the well-known algorithm developed by Key (1997). We make use of the thermal (11μm and 12 μm) bands of the Advanced Along Track Scanning Radiometer (AATSR) sensor on board ENVISAT. AATSR consists of two identical sensors, one pointing towards nadir and one pointing slightly forward. Both sensors are used for temperature retrieval. For estimating lake ice cover (LIC) we make use of the Medium Resolution Imaging Spectrometer (MERIS) sensor, also carried by ENVISAT. The method for estimating the lake ice cover is based on linear spectral unmixing, allowing estimation of endmember contribution at sub-pixel resolution. Open water, snow and ice all have distinct spectra, which makes them well suited for spectral unmixing methods. The ice cover within a pixel is based on the estimated presence of ice and snow on the lake surface. Both algorithms are integrated in a common software framework, with geo-correction, mosaicking and mask generation. Simultaneous AATSR images are used for cloud detection for both products. Since the spectral unmixing algorithm is sensitive to spectral variation, atmospheric correction is applied to the MERIS data. For this purpose we use the SMAC processor in the BEAM software. Both algorithms are compared to in situ point measurements. Additionally, visual interpretation of MERIS image data is done for further evaluation of the

  1. Sea and land surface temperatures, ocean heat content, Earth's energy imbalance and net radiative forcing over the last decade

    Science.gov (United States)

    Dieng, Habib B.; Cazenave, Anny; Meyssignac, Benoit; Schuckmann, Karina

    2016-04-01

    The Earth's global mean surface temperature (GMST) has increased less rapidly since the early 2000s than during the previous decades. Here we investigate the regional distribution of the reported temperature slowdown, focusing on the 2003-2014 decade of most complete global datasets. We find that both land surface temperature (LST) and sea surface temperature (SST) have increased at a rate significantly lower than over the previous decades with small regional differences. While confirming cooling of eastern tropical Pacific during the last decade, our results show that the reduced rate of change is a global phenomenon. We further evaluate the time derivative of full-depth ocean heat content to determine the planetary energy imbalance based on three different approaches: in situ measurements, ocean reanalysis and an indirect measure through the global sea level budget. For the 2003-2014 time span, it is estimated to 0.5 +/- 0.06 Wm-2, 0.64 +/- 0.04 Wm-2, and 0.6 +/- 0.07 Wm-2, respectively for the 3 approaches. We constrain the ocean heat uptake rates using the EBAF energy imbalance time series from the CERES/TOA project and find significant agreement at interannual scales. Finally, we compute the net radiative forcing of the last decade, considering the radiative feedback from observed GMST and the 3 different rates of the total ocean heat content. We obtain values of 1.6 +/- 0.19 Wm-2, 1.75 +/- 0.17 Wm-2, and 1.70 +/- 0.19 Wm-2, respectively over 2003-2014. We find no evidence of decrease in the net radiative forcing in the recent years, but rather increase compared to the previous decades.

  2. Using Machine learning method to estimate Air Temperature from MODIS over Berlin

    Science.gov (United States)

    Marzban, F.; Preusker, R.; Sodoudi, S.; Taheri, H.; Allahbakhshi, M.

    2015-12-01

    Land Surface Temperature (LST) is defined as the temperature of the interface between the Earth's surface and its atmosphere and thus it is a critical variable to understand land-atmosphere interactions and a key parameter in meteorological and hydrological studies, which is involved in energy fluxes. Air temperature (Tair) is one of the most important input variables in different spatially distributed hydrological, ecological models. The estimation of near surface air temperature is useful for a wide range of applications. Some applications from traffic or energy management, require Tair data in high spatial and temporal resolution at two meters height above the ground (T2m), sometimes in near-real-time. Thus, a parameterization based on boundary layer physical principles was developed that determines the air temperature from remote sensing data (MODIS). Tair is commonly obtained from synoptic measurements in weather stations. However, the derivation of near surface air temperature from the LST derived from satellite is far from straight forward. T2m is not driven directly by the sun, but indirectly by LST, thus T2m can be parameterized from the LST and other variables such as Albedo, NDVI, Water vapor and etc. Most of the previous studies have focused on estimating T2m based on simple and advanced statistical approaches, Temperature-Vegetation index and energy-balance approaches but the main objective of this research is to explore the relationships between T2m and LST in Berlin by using Artificial intelligence method with the aim of studying key variables to allow us establishing suitable techniques to obtain Tair from satellite Products and ground data. Secondly, an attempt was explored to identify an individual mix of attributes that reveals a particular pattern to better understanding variation of T2m during day and nighttime over the different area of Berlin. For this reason, a three layer Feedforward neural networks is considered with LMA algorithm

  3. Monitoring temperature and pressure over surfaces using sensitive paints

    Science.gov (United States)

    Guerrero-Viramontes, J. Ascención; Moreno Hernández, David; Mendoza Santoyo, Fernando; Morán Loza, José Miguel; García Arreola, Alicia

    2007-03-01

    Two techniques for monitoring temperature and pressure variations over surfaces using sensitive paints are presented. The analysis is done by the acquisition of a set of images of the surface under analysis. The surface is painted by a paint called Pressure Sensitive Paint (PSP) for pressure measurements and Temperature Sensitive Paints (TSP) for temperature measurements. These kinds of paints are deposited over the surface under analysis. The recent experimental advances in calibration process are presented in this paper.

  4. Estimation of sea surface temperature (SST) using marine seismic data

    Digital Repository Service at National Institute of Oceanography (India)

    Sinha, S.K.; Dewangan, P.; Sain, K.

    .g. Wu et al. [1999]). However, due to the skin effect, sea surface temperatures as measured by satellites can be very different from temperatures a few centimeters below the sea surface (i.e. in-situ temperatures) [Emery et al., 1994]. Therefore...

  5. Noncontact Monitoring of Surface Temperature Distribution by Laser Ultrasound Scanning

    Science.gov (United States)

    Yamada, Hiroyuki; Kosugi, Akira; Ihara, Ikuo

    2011-07-01

    A laser ultrasound scanning method for measuring a surface temperature distribution of a heated material is presented. An experiment using an aluminum plate heated up to 120 °C is carried out to verify the feasibility of the proposed method. A series of one-dimensional surface acoustic wave (SAW) measurements within an area of a square on the aluminum surface are performed by scanning a pulsed laser for generating SAW using a galvanometer system, where the SAWs are detected at a fixed location on the surface. An inverse analysis is then applied to SAW data to determine the surface temperature distribution in a certain direction. The two-dimensional distribution of the surface temperature in the square is constructed by combining the one-dimensional surface temperature distributions obtained within the square. The surface temperature distributions obtained by the proposed method almost agrees with those obtained using an infrared radiation camera.

  6. Examination of elevation dependency in observed and projected temperature change in the Upper Indus Basin and Western Himalaya

    Science.gov (United States)

    Fowler, H. J.; Forsythe, N. D.; Blenkinsop, S.; Archer, D.; Hardy, A.; Janes, T.; Jones, R. G.; Holderness, T.

    2013-12-01

    We present results of two distinct, complementary analyses to assess evidence of elevation dependency in temperature change in the UIB (Karakoram, Eastern Hindu Kush) and wider WH. The first analysis component examines historical remotely-sensed land surface temperature (LST) from the second and third generation of the Advanced Very High Resolution Radiometer (AVHRR/2, AVHRR/3) instrument flown on NOAA satellite platforms since the mid-1980s through present day. The high spatial resolution (AVHRR instrument enables precise consideration of the relationship between estimated LST and surface topography. The LST data product was developed as part of initiative to produce continuous time-series for key remotely sensed spatial products (LST, snow covered area, cloud cover, NDVI) extending as far back into the historical record as feasible. Context for the AVHRR LST data product is provided by results of bias assessment and validation procedures against both available local observations, both manned and automatic weather stations. Local observations provide meaningful validation and bias assessment of the vertical gradients found in the AVHRR LST as the elevation range from the lowest manned meteorological station (at 1460m asl) to the highest automatic weather station (4733m asl) covers much of the key range yielding runoff from seasonal snowmelt. Furthermore the common available record period of these stations (1995 to 2007) enables assessment not only of the AVHRR LST but also performance comparisons with the more recent MODIS LST data product. A range of spatial aggregations (from minor tributary catchments to primary basin headwaters) is performed to assess regional homogeneity and identify potential latitudinal or longitudinal gradients in elevation dependency. The second analysis component investigates elevation dependency, including its uncertainty, in projected temperature change trajectories in the downscaling of a seventeen member Global Climate Model (GCM

  7. Technique for the estimation of surface temperatures from embedded temperature sensing for rapid, high energy surface deposition.

    Energy Technology Data Exchange (ETDEWEB)

    Watkins, Tyson R.; Schunk, Peter Randall; Roberts, Scott Alan

    2014-07-01

    Temperature histories on the surface of a body that has been subjected to a rapid, highenergy surface deposition process can be di cult to determine, especially if it is impossible to directly observe the surface or attach a temperature sensor to it. In this report, we explore two methods for estimating the temperature history of the surface through the use of a sensor embedded within the body very near to the surface. First, the maximum sensor temperature is directly correlated with the peak surface temperature. However, it is observed that the sensor data is both delayed in time and greatly attenuated in magnitude, making this approach unfeasible. Secondly, we propose an algorithm that involves tting the solution to a one-dimensional instantaneous energy solution problem to both the sensor data and to the results of a one-dimensional CVFEM code. This algorithm is shown to be able to estimate the surface temperature 20 C.

  8. Prediction of lake surface temperature using the air2water model: guidelines, challenges, and future perspectives

    Directory of Open Access Journals (Sweden)

    Sebastiano Piccolroaz

    2016-04-01

    Full Text Available Water temperature plays a primary role in controlling a wide range of physical, geochemical and ecological processes in lakes, with considerable influences on lake water quality and ecosystem functioning. Being able to reliably predict water temperature is therefore a desired goal, which stimulated the development of models of different type and complexity, ranging from simple regression-based models to more sophisticated process-based numerical models. However, both types of models suffer of some limitations: the first are not able to address some fundamental physical processes as e.g., thermal stratification, while the latter generally require a large amount of data in input, which are not always available. In this work, lake surface temperature is simulated by means of air2water, a hybrid physically-based/statistical model, which is able to provide a robust, predictive understanding of LST dynamics knowing air temperature only. This model showed performances that are comparable with those obtained by using process based models (a root mean square error on the order of 1°C, at daily scale, while retaining the simplicity and parsimony of regression-based models, thus making it a good candidate for long-term applications.The aim of the present work is to provide the reader with useful and practical guidelines for proper use of the air2water model and for critical analysis of results. Two case studies have been selected for the analysis: Lake Superior and Lake Erie. These are clear and emblematic examples of a deep and a shallow temperate lake characterized by markedly different thermal responses to external forcing, thus are ideal for making the results of the analysis the most general and comprehensive. Particular attention is paid to assessing the influence of missing data on model performance, and to evaluating when an observed time series is sufficiently informative for proper model calibration or, conversely, data are too scarce thus

  9. Research on the Contribution of Urban Land Surface Moisture to the Alleviation Effect of Urban Land Surface Heat Based on Landsat 8 Data

    Directory of Open Access Journals (Sweden)

    Yu Zhang

    2015-08-01

    Full Text Available This paper presents a new assessment method for alleviating urban heat island (UHI effects by using an urban land surface moisture (ULSM index. With the aid of Landsat 8 OLI/TIRS data, the land surface temperature (LST was retrieved by a mono-window algorithm, and ULSM was extracted by tasselled cap transformation. Polynomial regression and buffer analysis were used to analyze the effects of ULSM on the LST, and the alleviation effect of ULSM was compared with three vegetation indices, GVI, SAVI, and FVC, by using the methods of grey relational analysis and Taylor skill calculation. The results indicate that when the ULSM value is greater than the value of an extreme point, the LST declines with the increasing ULSM value. Areas with a high ULSM value have an obvious reducing effect on the temperature of their surrounding areas within 150 m. Grey relational degrees and Taylor skill scores between ULSM and the LST are 0.8765 and 0.9378, respectively, which are higher than the results for the three vegetation indices GVI, SAVI, and FVC. The reducing effect of the ULSM index on environmental temperatures is significant, and ULSM can be considered to be a new and more effective index to estimate UHI alleviation effects for urban areas.

  10. Temperature dependent droplet impact dynamics on flat and textured surfaces

    Energy Technology Data Exchange (ETDEWEB)

    Azar Alizadeh; Vaibhav Bahadur; Sheng Zhong; Wen Shang; Ri Li; James Ruud; Masako Yamada; Liehi Ge; Ali Dhinojwala; Manohar S Sohal (047160)

    2012-03-01

    Droplet impact dynamics determines the performance of surfaces used in many applications such as anti-icing, condensation, boiling and heat transfer. We study impact dynamics of water droplets on surfaces with chemistry/texture ranging from hydrophilic to superhydrophobic and across a temperature range spanning below freezing to near boiling conditions. Droplet retraction shows very strong temperature dependence especially for hydrophilic surfaces; it is seen that lower substrate temperatures lead to lesser retraction. Physics-based analyses show that the increased viscosity associated with lower temperatures can explain the decreased retraction. The present findings serve to guide further studies of dynamic fluid-structure interaction at various temperatures.

  11. Using a thermal-based two source energy balance model with time-differencing to estimate surface energy fluxes with day-night MODIS observations

    DEFF Research Database (Denmark)

    Guzinski, Radoslaw; Anderson, M.C.; Kustas, W.P.;

    2013-01-01

    measurement as input, the approach reduces model sensitivity to errors in absolute temperature retrieval. The original formulation of the DTD required an early morning LST observation (approximately 1 h after sunrise) when surface fluxes are minimal, limiting application to data provided by geostationary...

  12. Estimation of Surface Heat Flux and Surface Temperature during Inverse Heat Conduction under Varying Spray Parameters and Sample Initial Temperature

    Directory of Open Access Journals (Sweden)

    Muhammad Aamir

    2014-01-01

    Full Text Available An experimental study was carried out to investigate the effects of inlet pressure, sample thickness, initial sample temperature, and temperature sensor location on the surface heat flux, surface temperature, and surface ultrafast cooling rate using stainless steel samples of diameter 27 mm and thickness (mm 8.5, 13, 17.5, and 22, respectively. Inlet pressure was varied from 0.2 MPa to 1.8 MPa, while sample initial temperature varied from 600°C to 900°C. Beck’s sequential function specification method was utilized to estimate surface heat flux and surface temperature. Inlet pressure has a positive effect on surface heat flux (SHF within a critical value of pressure. Thickness of the sample affects the maximum achieved SHF negatively. Surface heat flux as high as 0.4024 MW/m2 was estimated for a thickness of 8.5 mm. Insulation effects of vapor film become apparent in the sample initial temperature range of 900°C causing reduction in surface heat flux and cooling rate of the sample. A sensor location near to quenched surface is found to be a better choice to visualize the effects of spray parameters on surface heat flux and surface temperature. Cooling rate showed a profound increase for an inlet pressure of 0.8 MPa.

  13. Estimation of surface heat flux and surface temperature during inverse heat conduction under varying spray parameters and sample initial temperature.

    Science.gov (United States)

    Aamir, Muhammad; Liao, Qiang; Zhu, Xun; Aqeel-ur-Rehman; Wang, Hong; Zubair, Muhammad

    2014-01-01

    An experimental study was carried out to investigate the effects of inlet pressure, sample thickness, initial sample temperature, and temperature sensor location on the surface heat flux, surface temperature, and surface ultrafast cooling rate using stainless steel samples of diameter 27 mm and thickness (mm) 8.5, 13, 17.5, and 22, respectively. Inlet pressure was varied from 0.2 MPa to 1.8 MPa, while sample initial temperature varied from 600°C to 900°C. Beck's sequential function specification method was utilized to estimate surface heat flux and surface temperature. Inlet pressure has a positive effect on surface heat flux (SHF) within a critical value of pressure. Thickness of the sample affects the maximum achieved SHF negatively. Surface heat flux as high as 0.4024 MW/m(2) was estimated for a thickness of 8.5 mm. Insulation effects of vapor film become apparent in the sample initial temperature range of 900°C causing reduction in surface heat flux and cooling rate of the sample. A sensor location near to quenched surface is found to be a better choice to visualize the effects of spray parameters on surface heat flux and surface temperature. Cooling rate showed a profound increase for an inlet pressure of 0.8 MPa.

  14. Monitoring the Surface Heat Island (shi) Effects of Industrial Enterprises

    Science.gov (United States)

    Şekertekin, A.; Kutoglu, Ş. H.; Kaya, S.; Marangoz, A. M.

    2016-06-01

    The aim of this study is to present the effects of industrial enterprises on Land Surface Temperature (LST) and to retrieve Surface Heat Island (SHI) maps of these regions. SHI is one of the types of Urban Heat Island (UHI) and as the urban areas grow in a city, UHI effect becomes bigger. The city centre of Zonguldak was chosen as study area and Landsat 5 satellite data were used as materials. Zonguldak has important industrial enterprises like thermal power plants and iron and steel plant. ERDEMIR is the biggest iron and steel plant in Turkey and it is one of the biggest ones in Europe, as well. There are three operating thermal power plants in the region namely CATES, ZETES1 and ZETES2. In order to investigate these industrial regions, Landsat 5 satellite data were processed using mono-window algorithm to retrieve LST and they were acquired on 11.09.1987, 18.09.2007 and 29.09.2011, respectively. The obtained results revealed that from 1987 to 2011, spatial and temporal variability in LST in industrial enterprises became higher than the surroundings. Besides, the sizes of SHIs in 2011 are bigger than the ones in 1987. For the countries and governments, having industrial enterprises is crucial for the development and it is also important to present the community better conditions in life. Thus, decision makers should consider mitigating the effects of these regions on LST.

  15. MONITORING THE SURFACE HEAT ISLAND (SHI EFFECTS OF INDUSTRIAL ENTERPRISES

    Directory of Open Access Journals (Sweden)

    A. Şekertekin

    2016-06-01

    Full Text Available The aim of this study is to present the effects of industrial enterprises on Land Surface Temperature (LST and to retrieve Surface Heat Island (SHI maps of these regions. SHI is one of the types of Urban Heat Island (UHI and as the urban areas grow in a city, UHI effect becomes bigger. The city centre of Zonguldak was chosen as study area and Landsat 5 satellite data were used as materials. Zonguldak has important industrial enterprises like thermal power plants and iron and steel plant. ERDEMIR is the biggest iron and steel plant in Turkey and it is one of the biggest ones in Europe, as well. There are three operating thermal power plants in the region namely CATES, ZETES1 and ZETES2. In order to investigate these industrial regions, Landsat 5 satellite data were processed using mono-window algorithm to retrieve LST and they were acquired on 11.09.1987, 18.09.2007 and 29.09.2011, respectively. The obtained results revealed that from 1987 to 2011, spatial and temporal variability in LST in industrial enterprises became higher than the surroundings. Besides, the sizes of SHIs in 2011 are bigger than the ones in 1987. For the countries and governments, having industrial enterprises is crucial for the development and it is also important to present the community better conditions in life. Thus, decision makers should consider mitigating the effects of these regions on LST.

  16. Predicting monsoon rainfall and pressure indices from sea surface temperature

    Digital Repository Service at National Institute of Oceanography (India)

    Sadhuram, Y.

    The relationship between the sea surface temperature (SST) in the Indian Ocean and monsoon rainfall has been examined by using 21 years data set (1967-87) of MOHSST.6 (Met. Office Historical Sea Surface Temperature data set, obtained from U.K. Met...

  17. Metal surface temperature induced by moving laser beams

    NARCIS (Netherlands)

    Römer, G.R.B.E.; Meijer, J.

    1995-01-01

    Whenever a metal is irradiated with a laser beam, electromagnetic energy is transformed into heat in a thin surface layer. The maximum surface temperature is the most important quantity which determines the processing result. Expressions for this maximum temperature are provided by the literature fo

  18. Recent trends in sea surface temperature off Mexico

    NARCIS (Netherlands)

    Lluch-Cota, S.E.; Tripp-Valdéz, M.; Lluch-Cota, D.B.; Lluch-Belda, D.; Verbesselt, J.; Herrera-Cervantes, H.; Bautista-Romero, J.

    2013-01-01

    Changes in global mean sea surface temperature may have potential negative implications for natural and socioeconomic systems; however, measurements to predict trends in different regions have been limited and sometimes contradictory. In this study, an assessment of sea surface temperature change si

  19. Recent trends in sea surface temperature off Mexico

    NARCIS (Netherlands)

    Lluch-Cota, S.E.; Tripp-Valdéz, M.; Lluch-Cota, D.B.; Lluch-Belda, D.; Verbesselt, J.; Herrera-Cervantes, H.; Bautista-Romero, J.

    2013-01-01

    Changes in global mean sea surface temperature may have potential negative implications for natural and socioeconomic systems; however, measurements to predict trends in different regions have been limited and sometimes contradictory. In this study, an assessment of sea surface temperature change

  20. Reintroducing radiometric surface temperature into the Penman-Monteith formulation

    DEFF Research Database (Denmark)

    Mallick, Kaniska; Bøgh, Eva; Trebs, Ivonne;

    2015-01-01

    Here we demonstrate a novel method to physically integrate radiometric surface temperature (TR) into the Penman-Monteith (PM) formulation for estimating the terrestrial sensible and latent heat fluxes (H and λE) in the framework of a modified Surface Temperature Initiated Closure (STIC). It combi...

  1. Interferometric measurements of sea surface temperature and emissivity

    Science.gov (United States)

    Fiedler, Lars; Bakan, Stephan

    1997-09-01

    A new multispectral method to derive sea surface emissivity and temperature by using interferometer measurements of the near surface upwelling radiation in the infrared window region is presented. As reflected sky radiation adds substantial spectral variability to the otherwise spectrally smooth surface radiation, an appropriate estimate of surface emissivity allows the measured upwelling radiation to be corrected for the reflected sky component. The remaining radiation, together with the estimated surface emissivity, yields an estimate of the sea surface temperature. Measurements from an ocean pier in the Baltic Sea in October 1995 indicate an accuracy of about 0.1 K for the sea surface temperature thus derived. A strong sea surface skin effect of about 0.6 K is found in that particular case.

  2. Age-surface temperature estimation model: When will oil palm plantation reach the same surface temperature as natural forest?

    Science.gov (United States)

    Rushayati, S. B.; Hermawan, R.; Meilani, R.

    2017-01-01

    Oil palm plantation has often been accused as the cause of global warming. However, along with its growth, it would be able to decrease surface temperature. The question is ‘when will the plantation be able to reach the same surface temperature as natural forest’. This research aimed to estimate the age of oil palm plantation that create similar surface temperature to those in natural forest (land cover before the opening and planting of oil palm). The method used in this research was spatial analysis of land cover and surface temperature distribution. Based on the spatial analysis of surface temperature, five points was randomly taken from each planting age (age 1 15 years). Linear regression was then employed in the analysis. The linear regression formula between surface temperature and age of oil palm plantation was Y = 26.002 – 0.1237X. Surface temperature will decrease as much as 0.1237 ° C with one year age growth oil palm. Surface temperature that was similar to the initial temperature, when the land cover was natural forest (23.04 °C), was estimated to occur when the oil palm plantation reach the age 24 year.

  3. Evaluation of MODIS Land products for air temperature estimations in Colombia

    Directory of Open Access Journals (Sweden)

    Ricardo Castro-Díaz

    2013-08-01

    Full Text Available The moderate resolution imaging spectroradiometer (MODIS land-surface temperature/emissivity (LST product is often used for studies in meteorology due to its ability for near realtime evaluations. Colombia, as a country requires a prospective management for its productive ecosystems, but currently does not have sufficient spatially-distributed field data for air temperature at 2-m above the ground. The traditional validation of MODIS products includes field campaigns for calibrating and measuring differences between the satellite sensor and radiometers. For this research, the LST data on the ground was compared with climatologic stations using multiple regression techniques for improving the accuracy of the LST from MODIS, using MOD09GA , MOD17A2, MOD15A2, MOD13A2 as ancillary parameters (explanatory variables in the final model. The ground measurements were obtained in the Caribbean zone and the Casanare and Valle del Cauca departments in Colombia, using agroclimatic stations in the first dry season of 2007 and daily MODIS data. Enhanced vegetation index, fraction of photosynthetically active radiation, and net photosynthesis were included in the final model for explaining the vegetation as a key parameter for air temperature. Finally, two factors were proposed for LST estimation: sensor zenith angle and solar zenith angle due to the reflectance of the vegetation and sensitivity of the sensor

  4. Evolutionary conservation of TORC1 components, TOR, Raptor, and LST8, between rice and yeast.

    Science.gov (United States)

    Maegawa, Kentaro; Takii, Rumi; Ushimaru, Takashi; Kozaki, Akiko

    2015-10-01

    Target of rapamycin (TOR) is a conserved eukaryotic serine/threonine kinase that functions as a central controller of cell growth. TOR protein is structurally defined by the presence several conserved domains such as the HEAT repeat, focal adhesion target (FAT), FKBP12/rapamycin binding (FRB), kinase, and FATC domains starting from the N-terminus. In most eukaryotes, TOR forms two distinct physical and functional complexes, which are termed as TOR complex 1 (TORC1) and TORC2. However, plants contain only TORC1 components, i.e., TOR, Raptor, and LST8. In this study, we analyzed the gene structure and functions of TORC components in rice to understand the properties of the TOR complex in plants. Comparison of the locations of introns in these genes among rice and other eukaryotes showed that they were well conserved among plants except for Chlamydomonas. Moreover, the intron positions in the coding sequence of human Raptor and LST8 were closer to those of plants than of fly or nematode. Complementation tests of rice TOR (OsTOR) components in yeast showed that although OsTOR did not complement yeast tor mutants, chimeric TOR, which consisted of the HEAT repeat and FAT domain from yeast and other regions from rice, rescued the tor mutants, indicating that the HEAT repeat and FAT domains are important for species-specific signaling. OsRaptor perfectly complemented a kog1 (yeast Raptor homolog) mutant, and OsLST8 partially complemented an lst8 mutant. Together, these data suggest the importance of the N-terminal region of the TOR, HEAT, and FAT domains for functional diversification of the TOR complex.

  5. Land Surface Temperature Retrieval from Landsat-8 Data using Split-window Algorithm and Its Application on the Study of Urban Heat Island Effect%基于Landsat-8数据和劈窗算法的地表温度反演及城市热岛效应研究

    Institute of Scientific and Technical Information of China (English)

    宋挺; 段峥; 刘军志; 严飞; 黄君; 吴蔚

    2014-01-01

    Land Surface Temperature (LST)is an important parameter of surface energy balance components.With the rapid devel-opment of satellite remote sensing technology,satellite remote sensing has become an important approach to retrieving LST over large areas.Various satellite-based retrieval algorithms have been proposed,and the Split-Window algorithm has been proved to be a high precision algorithms.In this study,the LST of Wuxi was retrieved from Landsat-8 data with the SW algorithm.The retrieved LST data were further compared with both simultaneous ground measured temperature data and the MODIS LST product.Results showed that the retrieved LST had good accuracy with errors of less than 1 K.Furthermore,the Thermal Field Variance Composite Index computed from the retrieved LST data was used to analyze the spatial distribution of urban heat island.The urban heat island effect was quantified,and the effects of different land cover types on the heat island were also investigated.%陆地表面温度(Land Surface Temperature,LST)是地表能量平衡组分中的一个重要参数。随着卫星遥感技术的快速发展,遥感反演成为获取区域 LST的一个重要手段。目前已有学者提出多种基于遥感数据反演 LST的算法,其中劈窗算法被证明是一种精度较高的算法。基于 Landsat-8卫星30 m空间分辨率的陆地成像仪(OLI)数据和100 m分辨率的热红外传感器(TIRS)数据,采用劈窗算法计算了无锡地区的 LST,并采用地面实测水温数据和同步的 MODIS 温度产品对 Land-sat-8的计算结果进行了验证和对比分析。结果表明:基于 Landsat-8数据和劈窗算法获取的 LST精度较高,误差<1 K。在计算的 LST结果基础上,进一步提取了热场变异指数来分析城市热岛空间分布特征,给出了城市热岛效应的定量化描述,并就不同地表覆盖类型对热岛效应的影响进行了分析。

  6. Estimation of minimum surface temperature at stage ll (Short Communication

    Directory of Open Access Journals (Sweden)

    A. P. Dimri

    2001-04-01

    Full Text Available Forecasting minimum surface temperature at a station, Stage II, located in mountainous region requires information on the meteorological fields. An attempt has been made to develop a statistical model for forecasting minimum temperature at ground level using previous years' data. Surface data were collected at StageII (longitude 73 oB, latitude 34 oN, and altitude 2650 m. Atmospheric variables are influenced by complex orography and surface features to a great extent. In the present study, statistical relationship between atmosphere parameters and minimum temperature at the site has been established. Multivariate linear regression analysis has been used to establish the relationship to predict the minimum surface temperature for the following day. A comparison between the observed and the calculated forecast minimum temperature has been made. Most of the cases are well predicted (multiple correlation coefficient of 0.94.

  7. North American regional climate reconstruction from ground surface temperature histories

    Science.gov (United States)

    Jaume-Santero, Fernando; Pickler, Carolyne; Beltrami, Hugo; Mareschal, Jean-Claude

    2016-12-01

    Within the framework of the PAGES NAm2k project, 510 North American borehole temperature-depth profiles were analyzed to infer recent climate changes. To facilitate comparisons and to study the same time period, the profiles were truncated at 300 m. Ground surface temperature histories for the last 500 years were obtained for a model describing temperature changes at the surface for several climate-differentiated regions in North America. The evaluation of the model is done by inversion of temperature perturbations using singular value decomposition and its solutions are assessed using a Monte Carlo approach. The results within 95 % confidence interval suggest a warming between 1.0 and 2.5 K during the last two centuries. A regional analysis, composed of mean temperature changes over the last 500 years and geographical maps of ground surface temperatures, show that all regions experienced warming, but this warming is not spatially uniform and is more marked in northern regions.

  8. Ground-based measurement of surface temperature and thermal emissivity

    Science.gov (United States)

    Owe, M.; Van De Griend, A. A.

    1994-01-01

    Motorized cable systems for transporting infrared thermometers have been used successfully during several international field campaigns. Systems may be configured with as many as four thermal sensors up to 9 m above the surface, and traverse a 30 m transect. Ground and canopy temperatures are important for solving the surface energy balance. The spatial variability of surface temperature is often great, so that averaged point measurements result in highly inaccurate areal estimates. The cable systems are ideal for quantifying both temporal and spatial variabilities. Thermal emissivity is also necessary for deriving the absolute physical temperature, and measurements may be made with a portable measuring box.

  9. Effect of milling temperatures on surface area, surface energy and cohesion of pharmaceutical powders.

    Science.gov (United States)

    Shah, Umang V; Wang, Zihua; Olusanmi, Dolapo; Narang, Ajit S; Hussain, Munir A; Tobyn, Michael J; Heng, Jerry Y Y

    2015-11-10

    Particle bulk and surface properties are influenced by the powder processing routes. This study demonstrates the effect of milling temperatures on the particle surface properties, particularly surface energy and surface area, and ultimately on powder cohesion. An active pharmaceutical ingredient (API) of industrial relevance (brivanib alaninate, BA) was used to demonstrate the effect of two different, but most commonly used milling temperatures (cryogenic vs. ambient). The surface energy of powders milled at both cryogenic and room temperatures increased with increasing milling cycles. The increase in surface energy could be related to the generation of surface amorphous regions. Cohesion for both cryogenic and room temperature milled powders was measured and found to increase with increasing milling cycles. For cryogenic milling, BA had a surface area ∼ 5× higher than the one obtained at room temperature. This was due to the brittle nature of this compound at cryogenic temperature. By decoupling average contributions of surface area and surface energy on cohesion by salinization post-milling, the average contribution of surface energy on cohesion for powders milled at room temperature was 83% and 55% at cryogenic temperature.

  10. Study on retrieval model of land surface temperature in Jinghe watershed in arid region%干旱区精河流域地表温度的模型反演研究

    Institute of Scientific and Technical Information of China (English)

    王明霞; 毋兆鹏

    2014-01-01

    Based on Landsat ETM+ image data in Jinghe watershed oasis ,both methods of mono-window algorithm and single-channel algorithm were adopted to retrieve land surface temperature (LST ) in the study area ,and the compari-son between the retrieved results and MODIS temperature products (MODIS LST ) was made .The results showed :(1 ) The retrieved results from these two algorithms were similar each other in overall trend ,and the mean temperature differ-ence of the whole study area was about 2k .(2) The retrieval accuracy could be improved effectively by using modified soil-adjusted vegetation index (MSAVI ) instead of normalized differential vegetation index (NDVI ) to compute land sur-face emissivity ,and the retrieval accuracy of single-window algorithm was higher than that of single-channel algorithm . The correlation coefficients between the retrieved data of these two algorithms and MODIS LST were 0 .925 and 0 .8651 , respectively .(3) In the urban areas ,the correlation coefficient between the retrieved data of single-channel algorithm and MSAVI was 0 .8136 ,being higher than that of mono-window algorithm .Therefore ,the method of single-channel al-gorithm was more suitable for the retrieval research of LST in urban areas in large scale .%以精河流域绿洲为研究区,使用Landsat ETM+数据,采用单窗算法和普适性单通道算法对研究区地表温度进行反演,并将这两种算法的反演结果与研究区MODIS温度产品(MODIS LST )进行比较。结果表明:(1)单窗算法和普适性单通道算法反演的结果总体趋势比较接近,研究区整体的平均温度相差约2k;(2)采用改进型土壤调整植被指数(MSAVI )代替归一植被指数(NDVI )计算地表比辐射率可有效提高反演精度,并且同等条件下单窗算法的反演精度高于普适性单通道算法,两种算法的反演结果与MODIS LST的相关系数分别是0.9255和0.8651;(3)在城镇区域,普适

  11. TEMPERATURE CONTROL CIRCUIT FOR SURFACE ACOUSTIC WAVE (SAW RESONATORS

    Directory of Open Access Journals (Sweden)

    Zainab Mohamad Ashari

    2011-10-01

    Full Text Available Surface Acoustic Wave (SAW resonators are key components in oscillators, frequency synthesizers and transceivers. One of the drawbacks of SAW resonators are that its piezoelectric substrates are highly sensitive to ambient temperature resulting in performance degradation. This work propose a simple circuit design which stabalizes the temperature of the SAW resonator, making it independet of temperature change. This circuit is based on the oven control method which elevates the temperature of the resonator to a high temperature, making it tolerant to minor changes in ambient temperature.This circuit consist of a temperature sensor, heaters and a comparator which turn the heater on or off depending on the ambient temperature. Several SAW resonator were tested using this circuit. Experimental results indicate the temperature coefficient of frequency (TCF decreases from maximum of 130.44/°C to a minimum of -1.11/°C. 

  12. Mapping the body surface temperature of cattle by infrared thermography.

    Science.gov (United States)

    Salles, Marcia Saladini Vieira; da Silva, Suelen Corrêa; Salles, Fernando André; Roma, Luiz Carlos; El Faro, Lenira; Bustos Mac Lean, Priscilla Ayleen; Lins de Oliveira, Celso Eduardo; Martello, Luciane Silva

    2016-12-01

    Infrared thermography (IRT) is an alternative non-invasive method that has been studied as a tool for identifying many physiological and pathological processes related to changes in body temperature. The objective of the present study was to evaluate the body surface temperature of Jersey dairy cattle in a thermoneutral environment in order to contribute to the determination of a body surface temperature pattern for animals of this breed in a situation of thermal comfort. Twenty-four Jersey heifers were used over a period of 35 days at APTA Brazil. Measurements were performed on all animals, starting with the physiological parameters. Body surface temperature was measured by IRT collecting images in different body regions: left and right eye area, right and left eye, caudal left foreleg, cranial left foreleg, right and left flank, and forehead. High correlations were observed between temperature and humidity index (THI) and right flank, left flank and forehead temperatures (0.85, 0.81, and 0.81, respectively). The IRT variables that exhibited the five highest correlation coefficients in principal component 1 were, in decreasing order: forehead (0.90), right flank (0.87), left flank (0.84), marker 1 caudal left foreleg (0.83), marker 2 caudal left foreleg (0.74). The THI showed a high correlation coefficient (0.88) and moderate to low correlations were observed for the physiological variables rectal temperature (0.43), and respiratory frequency (0.42). The thermal profile obtained indicates a surface temperature pattern for each region studied in a situation of thermal comfort and may contribute to studies investigating body surface temperature. Among the body regions studied, IRT forehead temperature showed the highest association with rectal temperature, and forehead and right and left flank temperatures are strongly associated with THI and may be adopted in future studies on thermoregulation and body heat production.

  13. 2002 Average Monthly Sea Surface Temperature for California

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The NOAA/ NASA AVHRR Oceans Pathfinder sea surface temperature data are derived from the 5-channel Advanced Very High Resolution Radiometers (AVHRR) on board the...

  14. 2003 Average Monthly Sea Surface Temperature for California

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The NOAA/ NASA AVHRR Oceans Pathfinder sea surface temperature data are derived from the 5-channel Advanced Very High Resolution Radiometers (AVHRR) on board the...

  15. Sea surface temperature anomalies in the Arabian Sea

    Digital Repository Service at National Institute of Oceanography (India)

    RameshKumar, M.R.

    . Further analysis has shown that the sea surface anomalies are well correlated to the anomalies of air temperature and latent heat flux values; whereas they are least correlated to the anomalies of wind stress and net radiation values, except over...

  16. An Estimation of Land Surface Temperatures from Landsat ETM+ ...

    African Journals Online (AJOL)

    Dr-Adeline

    2 National Authority for Remote Sensing and Space Sciences, Cairo, Egypt. 3University of ... Keywords: Urban growth, urban heat Island, land surface temperatures, satellite remote sensing .... observed target includes green vegetation or not.

  17. Global 1-km Sea Surface Temperature (G1SST)

    Data.gov (United States)

    National Aeronautics and Space Administration — JPL OurOcean Portal: A daily, global Sea Surface Temperature (SST) data set is produced at 1-km (also known as ultra-high resolution) by the JPL ROMS (Regional Ocean...

  18. COBE-SST2 Sea Surface Temperature and Ice

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — A new sea surface temperature (SST) analysis on a centennial time scale is presented. The dataset starts in 1850 with monthly 1x1 means and is periodically updated....

  19. Surface layer temperature inversion in the Arabian Sea during winter

    Digital Repository Service at National Institute of Oceanography (India)

    Pankajakshan, T.; Ghosh, A.K.

    Surface layer temperature inversion in the south eastern Arabian Sea, during winter has been studied using Bathythermograph data collected from 1132 stations. It is found that the inversion in this area is a stable seasonal feature...

  20. Seasonal Sea Surface Temperature Averages, 1985-2001 - Direct Download

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — This data set consists of four images showing seasonal sea surface temperature (SST) averages for the entire earth. Data for the years 1985-2001 are averaged to...

  1. 1996 Average Monthly Sea Surface Temperature for California

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The NOAA/ NASA AVHRR Oceans Pathfinder sea surface temperature data are derived from the 5-channel Advanced Very High Resolution Radiometers (AVHRR) on board the...

  2. 2000 Average Monthly Sea Surface Temperature for California

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The NOAA/ NASA AVHRR Oceans Pathfinder sea surface temperature data are derived from the 5-channel Advanced Very High Resolution Radiometers (AVHRR) on board the...

  3. OW NOAA Pathfinder/GAC Sea-Surface Temperature

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The dataset contains satellite-derived sea-surface temperature measurements collected by means of the Advanced Very High Resolution Radiometer - Global Area Coverage...

  4. OW NOAA AVHRR-GAC Sea-Surface Temperature

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The dataset contains satellite-derived sea-surface temperature measurements collected by means of the Advanced Very High Resolution Radiometer - Global Area Coverage...

  5. NOAA High-Resolution Sea Surface Temperature (SST) Analysis Products

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This archive covers two high resolution sea surface temperature (SST) analysis products developed using an optimum interpolation (OI) technique. The analyses have a...

  6. Tropical sea surface temperatures and the earth's orbital eccentricity cycles

    Digital Repository Service at National Institute of Oceanography (India)

    Gupta, S.M.; Fernandes, A.A.; Mohan, R.

    The tropical oceanic warm pools are climatologically important regions because their sea surface temperatures (SSTs) are positively related to atmospheric greenhouse effect and the cumulonimbus-cirrus cloud anvil. Such a warm pool is also present...

  7. Temperature Distribution Measurement of The Wing Surface under Icing Conditions

    Science.gov (United States)

    Isokawa, Hiroshi; Miyazaki, Takeshi; Kimura, Shigeo; Sakaue, Hirotaka; Morita, Katsuaki; Japan Aerospace Exploration Agency Collaboration; Univ of Notre Dame Collaboration; Kanagawa Institute of Technology Collaboration; Univ of Electro-(UEC) Team, Comm

    2016-11-01

    De- or anti-icing system of an aircraft is necessary for a safe flight operation. Icing is a phenomenon which is caused by a collision of supercooled water frozen to an object. For the in-flight icing, it may cause a change in the wing cross section that causes stall, and in the worst case, the aircraft would fall. Therefore it is important to know the surface temperature of the wing for de- or anti-icing system. In aerospace field, temperature-sensitive paint (TSP) has been widely used for obtaining the surface temperature distribution on a testing article. The luminescent image from the TSP can be related to the temperature distribution. (TSP measurement system) In icing wind tunnel, we measured the surface temperature distribution of the wing model using the TSP measurement system. The effect of icing conditions on the TSP measurement system is discussed.

  8. High temperature photoelectron emission and surface photovoltage in semiconducting diamond

    Science.gov (United States)

    Williams, G. T.; Cooil, S. P.; Roberts, O. R.; Evans, S.; Langstaff, D. P.; Evans, D. A.

    2014-08-01

    A non-equilibrium photovoltage is generated in semiconducting diamond at above-ambient temperatures during x-ray and UV illumination that is sensitive to surface conductivity. The H-termination of a moderately doped p-type diamond (111) surface sustains a surface photovoltage up to 700 K, while the clean (2 × 1) reconstructed surface is not as severely affected. The flat-band C 1s binding energy is determined from 300 K measurement to be 283.87 eV. The true value for the H-terminated surface, determined from high temperature measurement, is (285.2 ± 0.1) eV, corresponding to a valence band maximum lying 1.6 eV below the Fermi level. This is similar to that of the reconstructed (2 × 1) surface, although this surface shows a wider spread of binding energy between 285.2 and 285.4 eV. Photovoltage quantification and correction are enabled by real-time photoelectron spectroscopy applied during annealing cycles between 300 K and 1200 K. A model is presented that accounts for the measured surface photovoltage in terms of a temperature-dependent resistance. A large, high-temperature photovoltage that is sensitive to surface conductivity and photon flux suggests a new way to use moderately B-doped diamond in voltage-based sensing devices.

  9. Temperature Compensation of Surface Acoustic Waves on Berlinite

    Science.gov (United States)

    Searle, David Michael Marshall

    The surface acoustic wave properties of Berlinite (a-AlPO4) have been investigated theoretically and experimentally, for a variety of crystallographic orientations, to evaluate its possible use as a substrate material for temperature compensated surface acoustic wave devices. A computer program has been developed to calculate the surface wave properties of a material from its elastic, piezoelectric, dielectric and lattice constants and their temperature derivatives. The program calculates the temperature coefficient of delay, the velocity of the surface wave, the direction of power flow and a measure of the electro-mechanical coupling. These calculations have been performed for a large number of orientations using a modified form of the data given by Chang and Barsch for Berlinite and predict several new temperature compensated directions. Experimental measurements have been made of the frequency-temperature response of a surface acoustic wave oscillator on an 80° X axis boule cut which show it to be temperature compensated in qualitative agreement with the theoretical predictions. This orientation shows a cubic frequency-temperature dependence instead of the expected parabolic response. Measurements of the electro-mechanical coupling coefficient k gave a value lower than predicted. Similar measurements on a Y cut plate gave a value which is approximately twice that of ST cut quartz, but again lower than predicted. The surface wave velocity on both these cuts was measured to be slightly higher than predicted by the computer program. Experimental measurements of the lattice parameters a and c are also presented for a range of temperatures from 25°C to just above the alpha-beta transition at 584°C. These results are compared with the values obtained by Chang and Barsch. The results of this work indicate that Berlinite should become a useful substrate material for the construction of temperature compensated surface acoustic wave devices.

  10. SURFACE TEMPERATURES ON TITAN DURING NORTHERN WINTER AND SPRING

    Energy Technology Data Exchange (ETDEWEB)

    Jennings, D. E.; Cottini, V.; Nixon, C. A.; Achterberg, R. K.; Flasar, F. M.; Kunde, V. G.; Romani, P. N.; Samuelson, R. E. [Goddard Space Flight Center, Greenbelt, MD 20771 (United States); Mamoutkine, A. [ADNET Systems, Inc., Bethesda, MD 20817 (United States); Gorius, N. J. P. [The Catholic University of America, Washington, DC 20064 (United States); Coustenis, A. [Laboratoire d’Etudes Spatiales et d’Instrumentation en Astrophysique (LESIA), Observatoire de Paris, CNRS, UPMC Univ. Paris 06, Univ. Paris-Diderot, 5, place Jules Janssen, F-92195 Meudon Cedex (France); Tokano, T., E-mail: donald.e.jennings@nasa.gov [Universität zu Köln, Albertus-Magnus-Platz, D-50923 Köln (Germany)

    2016-01-01

    Meridional brightness temperatures were measured on the surface of Titan during the 2004–2014 portion of the Cassini mission by the Composite Infrared Spectrometer. Temperatures mapped from pole to pole during five two-year periods show a marked seasonal dependence. The surface temperature near the south pole over this time decreased by 2 K from 91.7 ± 0.3 to 89.7 ± 0.5 K while at the north pole the temperature increased by 1 K from 90.7 ± 0.5 to 91.5 ± 0.2 K. The latitude of maximum temperature moved from 19 S to 16 N, tracking the sub-solar latitude. As the latitude changed, the maximum temperature remained constant at 93.65 ± 0.15 K. In 2010 our temperatures repeated the north–south symmetry seen by Voyager one Titan year earlier in 1980. Early in the mission, temperatures at all latitudes had agreed with GCM predictions, but by 2014 temperatures in the north were lower than modeled by 1 K. The temperature rise in the north may be delayed by cooling of sea surfaces and moist ground brought on by seasonal methane precipitation and evaporation.

  11. Temperature dependence of surface enhanced Raman scattering on C70

    Institute of Scientific and Technical Information of China (English)

    GAO Ying; Zhang Zhenlong; DU Yinxiao; DONG Hua; MO Yujun

    2005-01-01

    The temperature dependence of surface enhanced Raman scattering of the C70 molecule is reported.The Raman scattering of C70 molecules adsorbed on the surface of a silver mirror was measured at different temperatures. The experimental results indicate that the relative intensities of the Raman features vary with the temperature of the sample. When the temperature decreases from room temperature to 0℃, the relative intensities of certain Raman bands decrease abruptly. If we take the strongest band 1565cm-1 as a standard value 100, the greatest decrease approaches to 43%. However, with the further decrease in the temperature these relative intensities increase and resume the value at room temperature. And such a temperature dependence is reversible. Our results show that the adsorption state of the C70 molecules on the silver surface around 0℃changes greatly with the temperature, resulting in a decrease in relative intensities for some main Raman features of C70molecule. When the temperature is lower than 0℃, the adsorption state changes continually and more slowly. Synchronously, eight new Raman featu res, which have not ever been reported in literature, are observed in our experiment and this enriches the basic information of the vibrational modes for C70 molecule.

  12. Sea Surface Temperature from EUMETSAT Including Sentinel-3 SLSTR

    Science.gov (United States)

    O'Carroll, Anne; Bonekamp, Hans; Montagner, Francois; Santacesaria, Vincenzo; Tomazic, Igor

    2015-12-01

    The paper gives an overview of sea surface temperature (SST) activities at EUMETSAT including information on SST planned from the Sea and Land Surface Temperature Radiometer (SLSTR). Operational oceanography activities within the Marine Applications group at EUMETSAT continue with a focus on SST, sea surface winds, sea-ice products, radiative fluxes, significant wave height and sea surface topography. These are achieved through the mandatory, optional and third-party programmes, and for some products with the EUMETSAT Ocean and Sea-Ice Satellite Application Facility (OSI SAF). Progress towards products from sea-ice surface temperature, ocean colour products, turbidity and aerosol optical depth over water continue. Information on oceanography products from EUMETSAT can be found through the product navigator (http://navigator.eumetsat.int). EUMETSAT have been collaborating with ESA for a number of years on the development of SST for SLSTR.

  13. A model of the ground surface temperature for micrometeorological analysis

    Science.gov (United States)

    Leaf, Julian S.; Erell, Evyatar

    2017-07-01

    Micrometeorological models at various scales require ground surface temperature, which may not always be measured in sufficient spatial or temporal detail. There is thus a need for a model that can calculate the surface temperature using only widely available weather data, thermal properties of the ground, and surface properties. The vegetated/permeable surface energy balance (VP-SEB) model introduced here requires no a priori knowledge of soil temperature or moisture at any depth. It combines a two-layer characterization of the soil column following the heat conservation law with a sinusoidal function to estimate deep soil temperature, and a simplified procedure for calculating moisture content. A physically based solution is used for each of the energy balance components allowing VP-SEB to be highly portable. VP-SEB was tested using field data measuring bare loess desert soil in dry weather and following rain events. Modeled hourly surface temperature correlated well with the measured data (r 2 = 0.95 for a whole year), with a root-mean-square error of 2.77 K. The model was used to generate input for a pedestrian thermal comfort study using the Index of Thermal Stress (ITS). The simulation shows that the thermal stress on a pedestrian standing in the sun on a fully paved surface, which may be over 500 W on a warm summer day, may be as much as 100 W lower on a grass surface exposed to the same meteorological conditions.

  14. Determination of temperature of moving surface by sensitivity analysis

    CERN Document Server

    Farhanieh, B

    2002-01-01

    In this paper sensitivity analysis in inverse problem solutions is employed to estimate the temperature of a moving surface. Moving finite element method is used for spatial discretization. Time derivatives are approximated using Crank-Nicklson method. The accuracy of the solution is assessed by simulation method. The convergence domain is investigated for the determination of the temperature of a solid fuel.

  15. A new interpolation method for Antarctic surface temperature

    Institute of Scientific and Technical Information of China (English)

    Yetang Wang; Shugui Hou

    2009-01-01

    We propose a new methodology for the spatial interpolation of annual mean temperature into a regular grid with a geographic resolution of 0.01° for Antarctica by applying a recent compilation of the Antarctic temperature data.A multiple linear regression model of the dependence of temperature on some geographic parameters (i.e.,latitude,longitude,and elevation) is proposed empirically,and the kriging method is used to determine the spatial distribution of regional and local deviations from the temperature calculated from the multiple linear regression model.The modeled value and residual grids are combined to derive a high-resolution map of surface air temperature.The performance of our new methodology is superior to a variety of benchmark methods (e.g.,inverse distance weighting,kriging,and spline methods) via cross-validation techniques.Our simulation resembles well with those distinct spatial features of surface temperature,such as the decrease in annual mean surface temperature with increasing latitude and the distance away from the coast line;and it also reveals the complex topographic effects on the spatial distribution of surface temperature.

  16. Analysis of Anomaly in Land Surface Temperature Using MODIS Products

    Science.gov (United States)

    Yorozu, K.; Kodama, T.; Kim, S.; Tachikawa, Y.; Shiiba, M.

    2011-12-01

    Atmosphere-land surface interaction plays a dominant role on the hydrologic cycle. Atmospheric phenomena cause variation of land surface state and land surface state can affect on atmosphereic conditions. Widely-known article related in atmospheric-land interaction was published by Koster et al. in 2004. The context of this article is that seasonal anomaly in soil moisture or soil surface temperature can affect summer precipitation generation and other atmospheric processes especially in middle North America, Sahel and south Asia. From not only above example but other previous research works, it is assumed that anomaly of surface state has a key factor. To investigate atmospheric-land surface interaction, it is necessary to analyze anomaly field in land surface state. In this study, soil surface temperature should be focused because it can be globally and continuously observed by satellite launched sensor. To land surface temperature product, MOD11C1 and MYD11C1 products which are kinds of MODIS products are applied. Both of them have 0.05 degree spatial resolution and daily temporal resolution. The difference of them is launched satellite, MOD11C1 is Terra and MYD11C1 is Aqua. MOD11C1 covers the latter of 2000 to present and MYD11C1 covers the early 2002 to present. There are unrealistic values on provided products even if daily product was already calibrated or corrected. For pre-analyzing, daily data is aggregated into 8-days data to remove irregular values for stable analysis. It was found that there are spatial and temporal distribution of 10-years average and standard deviation for each 8-days term. In order to point out extreme anomaly in land surface temperature, standard score for each 8-days term is applied. From the analysis of standard score, it is found there are large anomaly in land surface temperature around north China plain in early April 2005 and around Bangladesh in early May 2009.

  17. Radar Backscatter Across the Gulf Stream Sea Surface Temperature Front

    Science.gov (United States)

    Nghiem, S. V.; Li, F. K.; Walsh, E. J.; Lou, S. H.

    1998-01-01

    Ocean backscatter signatures were measured by the Jet Propulsion Laboratory airborne NUSCAT K(sub u)-band scatterometer across the Gulf Stream sea surface temperature front. The measurements were made during the Surface Wave Dynamics Experiment (SWADE) off the coast of Virginia and Maryland in the winter of 1991.

  18. ESTIMATION OF PV MODULE SURFACE TEMPERATURE USING ARTIFICIAL NEURAL NETWORKS

    Directory of Open Access Journals (Sweden)

    Can Coskun

    2016-12-01

    Full Text Available This study aimed to use the artificial neural network (ANN method to estimate the surface temperature of a photovoltaic (PV panel. Using the experimentally obtained PV data, the accuracy of the ANN model was evaluated. To train the artificial neural network (ANN, outer temperature solar radiation and wind speed values were inputs and surface temperature was an output. The ANN was used to estimate PV panel surface temperature. Using the Levenberg-Marquardt (LM algorithm the feed forward artificial neural network was trained. Two back propagation type ANN algorithms were used and their performance was compared with the estimate from the LM algorithm. To train the artificial neural network, experimental data were used for two thirds with the remaining third used for testing. Additionally scaled conjugate gradient (SCG back propagation and resilient back propagation (RB type ANN algorithms were used for comparison with the LM algorithm. The performances of these three types of artificial neural network were compared and mean error rates of between 0.005962 and 0.012177% were obtained. The best estimate was produced by the LM algorithm. Estimation of PV surface temperature with artificial neural networks provides better results than conventional correlation methods. This study showed that artificial neural networks may be effectively used to estimate PV surface temperature.

  19. Mathematical model of the metal mould surface temperature optimization

    Energy Technology Data Exchange (ETDEWEB)

    Mlynek, Jaroslav, E-mail: jaroslav.mlynek@tul.cz; Knobloch, Roman, E-mail: roman.knobloch@tul.cz [Department of Mathematics, FP Technical University of Liberec, Studentska 2, 461 17 Liberec, The Czech Republic (Czech Republic); Srb, Radek, E-mail: radek.srb@tul.cz [Institute of Mechatronics and Computer Engineering Technical University of Liberec, Studentska 2, 461 17 Liberec, The Czech Republic (Czech Republic)

    2015-11-30

    The article is focused on the problem of generating a uniform temperature field on the inner surface of shell metal moulds. Such moulds are used e.g. in the automotive industry for artificial leather production. To produce artificial leather with uniform surface structure and colour shade the temperature on the inner surface of the mould has to be as homogeneous as possible. The heating of the mould is realized by infrared heaters located above the outer mould surface. The conceived mathematical model allows us to optimize the locations of infrared heaters over the mould, so that approximately uniform heat radiation intensity is generated. A version of differential evolution algorithm programmed in Matlab development environment was created by the authors for the optimization process. For temperate calculations software system ANSYS was used. A practical example of optimization of heaters locations and calculation of the temperature of the mould is included at the end of the article.

  20. Remote Sensing of the Surface Urban Heat Island and Land Architecture in Phoenix, Arizona: Combined Effects of Land Composition and Configuration and Cadastral-Demographic-Economic Factors

    Science.gov (United States)

    Middel, A. C.; LI, X.

    2015-12-01

    This study seeks to determine the role of land architecture—the composition and configuration of land cover—as well as cadastral-demographic-economic factors on land surface temperature (LST) and the surface urban heat island (SUHI) effect of Phoenix, Arizona. It employs 1 m National Agricultural Imagery Program data of land-cover with 120 m Landsat-derived land surface temperature decomposed to 30m, a new measure of configuration, the normalized moment of inertia, and U.S. Census data to address the question for two randomly selected samples comprising 523 and 545 residential neighborhoods (census blocks) in the city. The results indicate that, contrary to most other studies, land configuration maintains as strong a role in LST as does land composition. In addition, land architecture combined with cadastral, demographic and economic data, captures a significant amount of explained variance in LST. The results indicate that attention to land architecture in the development of or reshaping of neighborhoods may ameliorate the summer extremes in LST.

  1. Influence of Annealing Temperature on CZTS Thin Film Surface Properties

    Science.gov (United States)

    Feng, Wenmei; Han, Junfeng; Ge, Jun; Peng, Xianglin; Liu, Yunong; Jian, Yu; Yuan, Lin; Xiong, Xiaolu; Cha, Limei; Liao, Cheng

    2017-01-01

    In this work, copper zinc tin sulfide (CZTS) films were deposited by direct current sputtering and the samples were annealed in different oven-set temperatures and atmosphere (Ar and H2S). The surface evolution was investigated carefully by using scanning electron microscopy (SEM), Raman spectroscopy and x-ray photoelectron spectroscopy. The surface of the as-sputtered precursor contained little Cu and large amounts of Zn and Sn. The metallic precursor was continuous and compact without pinholes or cracks. With the increase of the temperature from room temperature to 250°C, Cu atoms diffused to the film surface to form Cu1- x S and covered other compounds. Some small platelets were smaller than 500 nm spreading randomly in the holes of the film surfaces. When the temperature reached 350°C, Zn and Sn atoms began to diffuse to the surface and react with S or Cu1- x S. At 400°C, SEM showed the melting of large particles and small particles with a size from 100 nm to 200 nm in the background of the film surface. Excess Zn segregated towards the surface regions and formed ZnS phase on the surface. In addition, the signal of sodium in the CZTS surface was observed above 400°C. At 600°C, a large amount of regular structures with clear edges and corners were observed in the film surface in SEM images. A clear recrystallized process on the surface was assumed from those observations.

  2. Climate Change Signal Analysis for Northeast Asian Surface Temperature

    Institute of Scientific and Technical Information of China (English)

    Jeong-Hyeong LEE; Byungsoo KIM; Keon-Tae SOHN; Won-Tae KOWN; Seung-Ki MIN

    2005-01-01

    Climate change detection, attribution, and prediction were studied for the surface temperature in the Northeast Asian region using NCEP/NCAR reanalysis data and three coupled-model simulations from ECHAM4/OPYC3, HadCM3, and CCCma GCMs (Canadian Centre for Climate Modeling and Analysis general circulation model). The Bayesian fingerprint approach was used to perform the detection and attribution test for the anthropogenic climate change signal associated with changes in anthropogenic carbon dioxide (CO2) and sulfate aerosol (SO42-) concentrations for the Northeast Asian temperature. It was shown that there was a weak anthropogenic climate change signal in the Northeast Asian temperature change. The relative contribution of CO2 and SOl- effects to total temperature change in Northeast Asia was quantified from ECHAM4/OPYC3 and CCCma GCM simulations using analysis of variance. For the observed temperature change for the period of 1959-1998, the CO2 effect contributed 10%-21% of the total variance and the direct cooling effect of SO42- played a less important role (0% 7%) than the CO2effect. The prediction of surface temperature change was estimated from the second CO2+SO24- scenario run of ECHAM4/OPYC3 which has the least error in the simulation of the present-day temperature field near the Korean Peninsula. The result shows that the area-mean surface temperature near the Korean Peninsula will increase by about 1.1° by the 2040s relative to the 1990s.

  3. Remotely sensed surface temperature variation of an inland saline lake over the central Qinghai-Tibet Plateau

    Science.gov (United States)

    Ke, Linghong; Song, Chunqiao

    2014-12-01

    Research on surface water temperature (SWT) variations in large lakes over the Qinghai-Tibet Plateau (QTP) has been limited by lack of in situ measurements. By taking advantage of the increased availability of remotely sensed observations, this study investigated SWT variation of Siling Co in central QTP by processing complete MODIS Land surface temperature (LST) images over the lake covering from 2001 to 2013. The temporal (diurnal, intra-annul and inter-annul) variations of Siling Co SWT as well as the spatial patterns were analyzed. The results show that on average from late December to mid-April the lake is in a mixing state of water and ice and drastic diurnal temperature differences occur, especially along the shallow shoreline areas. The extent of spatial variations in monthly SWT ranges from 1.25 °C to 3.5 °C, and particularly large at nighttime and in winter months. The spatial patterns of annual average SWT were likely impacted by the cooling effect of river inflow from the west and east side of the lake. The annual cycle of spatial pattern of SWT is characterized by seasonal reversions between the shallow littoral regions and deep parts due to different heat capacity. Compared to the deep regions, the littoral shallow shoreline areas warms up quickly in spring and summer, and cool down drastically in autumn and winter, showing large diurnal and seasonal variation amplitudes of SWT. Two cold belt zones in the western and eastern side of the lake and warm patches along the southwestern and northeastern shorelines are shaped by the combined effects of the lakebed topography and river runoff. Overall, the lake-averaged SWT increased at a rate of 0.26 °C/decade during 2001-2013. Faster increase of temperature was found at nighttime (0.34 °C/decade) and in winter and spring, consistent with the asymmetric warming pattern over land areas reported in prior studies. The rate of temperature increase over Siling Co is remarkably lower than that over Bangoin

  4. Fiber-Optic Surface Temperature Sensor Based on Modal Interference

    Directory of Open Access Journals (Sweden)

    Frédéric Musin

    2016-07-01

    Full Text Available Spatially-integrated surface temperature sensing is highly useful when it comes to controlling processes, detecting hazardous conditions or monitoring the health and safety of equipment and people. Fiber-optic sensing based on modal interference has shown great sensitivity to temperature variation, by means of cost-effective image-processing of few-mode interference patterns. New developments in the field of sensor configuration, as described in this paper, include an innovative cooling and heating phase discrimination functionality and more precise measurements, based entirely on the image processing of interference patterns. The proposed technique was applied to the measurement of the integrated surface temperature of a hollow cylinder and compared with a conventional measurement system, consisting of an infrared camera and precision temperature probe. As a result, the optical technique is in line with the reference system. Compared with conventional surface temperature probes, the optical technique has the following advantages: low heat capacity temperature measurement errors, easier spatial deployment, and replacement of multiple angle infrared camera shooting and the continuous monitoring of surfaces that are not visually accessible.

  5. Assessment of broiler surface temperature variation when exposed to different air temperatures

    Directory of Open Access Journals (Sweden)

    GR Nascimento

    2011-12-01

    Full Text Available This study was conducted to determine the effect of the air temperature variation on the mean surface temperature (MST of 7- to 35-day-old broiler chickens using infrared thermometry to estimate MST, and to study surface temperature variation of the wings, head, legs, back and comb as affected by air temperature and broiler age. One hundred Cobb® broilers were used in the experiment. Starting on day 7, 10 birds were weekly selected at random, housed in an environmental chamber and reared under three distinct temperatures (18, 25 and 32 ºC to record their thermal profile using an infrared thermal camera. The recorded images were processed to estimate MST by selecting the whole area of the bird within the picture and comparing it with the values obtained using selected equations in literature, and to record the surface temperatures of the body parts. The MST estimated by infrared images were not statistically different (p > 0.05 from the values obtained by the equations. MST values significantly increased (p < 0.05 when the air temperature increased, but were not affected by bird age. However, age influenced the difference between MST and air temperature, which was highest on day 14. The technique of infrared thermal image analysis was useful to estimate the mean surface temperature of broiler chickens.

  6. Subsurface Emission Effects in AMSR-E Measurements: Implications for Land Surface Microwave Emissivity Retrieval

    Science.gov (United States)

    Galantowicz, John F.; Moncet, Jean-Luc; Liang, Pan; Lipton, Alan E.; Uymin, Gennady; Prigent, Catherine; Grassotti, Christopher

    2011-01-01

    An analysis of land surface microwave emission time series shows that the characteristic diurnal signature associated with subsurface emission in sandy deserts carry over to arid and semi-arid region worldwide. Prior work found that diurnal variation of Special Sensor Microwave/Imager (SSM/I) brightness temperatures in deserts was small relative to International Satellite Cloud Climatology Project land surface temperature (LST) variation and that the difference varied with surface type and was largest in sand sea regions. Here we find more widespread subsurface emission effects in Advanced Microwave Scanning Radiometer-EOS (AMSR-E) measurements. The AMSR-E orbit has equator crossing times near 01:30 and 13 :30 local time, resulting in sampling when near-surface temperature gradients are likely to be large and amplifying the influence of emission depth on effective emitting temperature relative to other factors. AMSR-E measurements are also temporally coincident with Moderate Resolution Imaging Spectroradiometer (MODIS) LST measurements, eliminating time lag as a source of LST uncertainty and reducing LST errors due to undetected clouds. This paper presents monthly global emissivity and emission depth index retrievals for 2003 at 11, 19, 37, and 89 GHz from AMSR-E, MODIS, and SSM/I time series data. Retrieval model fit error, stability, self-consistency, and land surface modeling results provide evidence for the validity of the subsurface emission hypothesis and the retrieval approach. An analysis of emission depth index, emissivity, precipitation, and vegetation index seasonal trends in northern and southern Africa suggests that changes in the emission depth index may be tied to changes in land surface moisture and vegetation conditions

  7. Investigating the effect of surface water - groundwater interactions on stream temperature using Distributed temperature sensing and instream temperature model

    DEFF Research Database (Denmark)

    Karthikeyan, Matheswaran; Blemmer, Morten; Mortensen, Julie Flor;

    2011-01-01

    Surface water–groundwater interactions at the stream interface influences, and at times controls the stream temperature, a critical water property driving biogeochemical processes. This study investigates the effects of these interactions on temperature of Stream Elverdamsåen in Denmark using...... the Distributed Temperature Sensing (DTS) system and instream temperature modelling. Locations of surface water–groundwater interactions were identified from the temperature data collected over a 2-km stream reach using a DTS system with 1-m spatial and 5-min temporal resolution. The stream under consideration...... exhibits three distinct thermal regimes within a 2 km reach length due to two major interactions. An energy balance model is used to simulate the instream temperature and to quantify the effect of these interactions on the stream temperature. This research demonstrates the effect of reach level small scale...

  8. Uncertainties and shortcomings of ground surface temperature histories derived from inversion of temperature logs

    OpenAIRE

    Hartmann, Andreas; Rath, Volker

    2008-01-01

    Analysing borehole temperature data in terms of ground surface history can add useful information to reconstructions of past climates. Therefore, a rigorous assessment of uncertainties and error sources is a necessary prerequisite for the meaningful interpretation of such ground surface temperature histories. This study analyses the most prominent sources of uncertainty. The diffusive nature of the process makes the inversion relatively robust against incomplete knowledge of the thermal diffu...

  9. Relationship between Surface Urban Heat Island intensity and sensible heat flux retrieved from meteorological parameters observed by road weather stations in urban area

    Science.gov (United States)

    Gawuć, Lech

    2017-04-01

    Urban Heat Island (UHI) is a direct consequence of altered energy balance in urban areas (Oke 1982). There has been a significant effort put into an understanding of air temperature variability in urban areas and underlying mechanisms (Arnfield 2003, Grimmond 2006, Stewart 2011, Barlow 2014). However, studies that are concerned on surface temperature are less frequent. Therefore, Voogt & Oke (2003) proposed term "Surface Urban Heat Island (SUHI)", which is analogical to UHI and it is defined as a difference in land surface temperature (LST) between urban and rural areas. SUHI is a phenomenon that is not only concerned with high spatial variability, but also with high temporal variability (Weng and Fu 2014). In spite of the fact that satellite remote sensing techniques give a full spatial pattern over a vast area, such measurements are strictly limited to cloudless conditions during a satellite overpass (Sobrino et al., 2012). This significantly reduces the availability and applicability of satellite LST observations, especially over areas and seasons with high cloudiness occurrence. Also, the surface temperature is influenced by synoptic conditions (e.g., wind and humidity) (Gawuc & Struzewska 2016). Hence, utilising single observations is not sufficient to obtain a full image of spatiotemporal variability of urban LST and SUHI intensity (Gawuc & Struzewska 2016). One of the possible solutions would be a utilisation of time-series of LST data, which could be useful to monitor the UHI growth of individual cities and thus, to reveal the impact of urbanisation on local climate (Tran et al., 2006). The relationship between UHI and synoptic conditions have been summarised by Arnfield (2003). However, similar analyses conducted for urban LST and SUHI are lacking. We will present analyses of the relationship between time series of remotely-sensed LST and SUHI intensity and in-situ meteorological observations collected by road weather stations network, namely: road surface

  10. Improved in-situ methods for determining land surface emissivity

    Science.gov (United States)

    Göttsche, Frank; Olesen, Folke; Hulley, Glynn

    2014-05-01

    The accurate validation of LST satellite products, such as the operational LST retrieved by the Land Surface Analysis - Satellite Application Facility (LSA-SAF), requires accurate knowledge of emissivity for the areas observed by the ground radiometers as well as for the area observed by the satellite sensor. Especially over arid regions, the relatively high uncertainty in land surface emissivity (LSE) limits the accuracy with which land surface temperature (LST) can be retrieved from thermal infrared (TIR) radiance measurements. LSE uncertainty affects LST obtained from satellite measurements and in-situ radiance measurements alike. Furthermore, direct comparisons between satellite sensors and ground based sensors are complicated by spatial scale mismatch: ground radiometers usually observe some 10 m2, whereas satellite sensors typically observe between 1 km2 and 100 km2. Therefore, validation sites have to be carefully selected and need to be characterised on the scale of the ground radiometer as well as on the scale of the satellite pixel. The permanent stations near Gobabeb (Namibia; hyper-arid desert climate) and Dahra (Senegal; hot-arid steppe-prairie climate) are two of KIT's four dedicated LST validation stations. Gobabeb station is located on vast and flat gravel plains (several 100 km2), which are mainly covered by coarse gravel, sand, and desiccated grass. The gravel plains are highly homogeneous in space and time, which makes them ideal for validating a broad range of satellite-derived products. Dahra station is located in so called 'tiger bush' and is covered by strongly seasonal grass (95%) and sparse, evergreen trees (dominantly acacia trees) with a background of reddish sand. The strong seasonality is caused by a pronounced rainy season, during which LST retrieval is highly challenging. Outside the rainy season, both sites have relatively large fractions of bare ground and desiccated vegetation: therefore, they are particularly prone to be

  11. High-Temperature Surface-Acoustic-Wave Transducer

    Science.gov (United States)

    Zhao, Xiaoliang; Tittmann, Bernhard R.

    2010-01-01

    Aircraft-engine rotating equipment usually operates at high temperature and stress. Non-invasive inspection of microcracks in those components poses a challenge for the non-destructive evaluation community. A low-profile ultrasonic guided wave sensor can detect cracks in situ. The key feature of the sensor is that it should withstand high temperatures and excite strong surface wave energy to inspect surface/subsurface cracks. As far as the innovators know at the time of this reporting, there is no existing sensor that is mounted to the rotor disks for crack inspection; the most often used technology includes fluorescent penetrant inspection or eddy-current probes for disassembled part inspection. An efficient, high-temperature, low-profile surface acoustic wave transducer design has been identified and tested for nondestructive evaluation of structures or materials. The development is a Sol-Gel bismuth titanate-based surface-acoustic-wave (SAW) sensor that can generate efficient surface acoustic waves for crack inspection. The produced sensor is very thin (submillimeter), and can generate surface waves up to 540 C. Finite element analysis of the SAW transducer design was performed to predict the sensor behavior, and experimental studies confirmed the results. One major uniqueness of the Sol-Gel bismuth titanate SAW sensor is that it is easy to implement to structures of various shapes. With a spray coating process, the sensor can be applied to surfaces of large curvatures. Second, the sensor is very thin (as a coating) and has very minimal effect on airflow or rotating equipment imbalance. Third, it can withstand temperatures up to 530 C, which is very useful for engine applications where high temperature is an issue.

  12. Investigation of surface properties of high temperature nitrided titanium alloys

    Directory of Open Access Journals (Sweden)

    E. Koyuncu

    2009-12-01

    Full Text Available Purpose: The purpose of paper is to investigate surface properties of high temperature nitrided titanium alloys.Design/methodology/approach: In this study, surface modification of Ti6Al4V titanium alloy was made at various temperatures by plasma nitriding process. Plasma nitriding treatment was performed in 80% N2-20% H2 gas mixture, for treatment times of 2-15 h at the temperatures of 700-1000°C. Surface properties of plasma nitrided Ti6Al4V alloy were examined by metallographic inspection, X-Ray diffraction and Vickers hardness.Findings: Two layers were determined by optic inspection on the samples that were called the compound and diffusion layers. Compound layer contain TiN and Ti2N nitrides, XRD results support in this formations. Maximum hardness was obtained at 10h treatment time and 1000°C treatment temperature. Micro hardness tests showed that hardness properties of the nitrided samples depend on treatment time and temperature.Practical implications: Titanium and its alloys have very attractive properties for many industries. But using of titanium and its alloys is of very low in mechanical engineering applications because of poor tribological properties.Originality/value: The nitriding of titanium alloy surfaces using plasma processes has already reached the industrial application stage in the biomedical field.

  13. Surface Intermediates on Metal Electrodes at High Temperature

    DEFF Research Database (Denmark)

    Zachau-Christiansen, Birgit; Jacobsen, Torben; Bay, Lasse

    1997-01-01

    The mechanisms widely suggested for the O2-reduc-tion or H2-oxidation SOFC reactions involve inter-mediate O/H species adsorbed on the electrode surface. The presence of these intermediates is investigated by linear sweep voltammetry. In airat moderate temperatures (500øC) Pt in contact with YSZ ...... is covered with adsorbed oxygen which vanishes at high temperature (1000øC). On Ni (YSZ) a specific layer of NiO is observed abovethe equilibrium potential while no surface species can identified at SOFC anode conditions....

  14. Determination of sea surface temperatures from microwave and IR data

    Science.gov (United States)

    Rangaswamy, S.; Grover, J.

    1982-01-01

    Microwave measurements from the Nimbus 7 SMMR were used to derive the atmospheric precipitable water, which was then used to obtain the atmospheric correction for use with AVHRR thermal IR measurements to obtain sea surface temperature (SST). The resulting SST's were compared with the NOAA operational sea surface temperature measurements, and the two sets of measurements were found to be in reasonable agreement. The average residuals between the two sets of measurements was 0.15 K with the NOAA operational SST's being slightly greater.

  15. Surface intermediates on metal electrodes at high temperatures

    DEFF Research Database (Denmark)

    Zachau-Christiansen, Birgit; Jacobsen, Torben; Bay, Lasse;

    1998-01-01

    in contact with YSZ is covered with adsorbed oxygen which vanishes at high temperature (1000 degrees C). On Ni (YSZ) a specific layer of NiO is observed above the equilibrium potential while no surface species involving hydrogen can be identified at SOFC anode conditions. (C) 1998 Published by Elsevier......The mechanisms widely conceived for the O(2)-reduction or H(2)-oxidation reactions in SOFC's involve intermediate O/H species adsorbed on the electrode surface. The presence of these intermediates is investigated by linear sweep voltammetry. In air at moderate temperatures (500 degrees C) Pt...

  16. Surface air temperature variability in global climate models

    CERN Document Server

    Davy, Richard

    2012-01-01

    New results from the Coupled Model Inter-comparison Project phase 5 (CMIP5) and multiple global reanalysis datasets are used to investigate the relationship between the mean and standard deviation in the surface air temperature. A combination of a land-sea mask and orographic filter were used to investigate the geographic region with the strongest correlation and in all cases this was found to be for low-lying over-land locations. This result is consistent with the expectation that differences in the effective heat capacity of the atmosphere are an important factor in determining the surface air temperature response to forcing.

  17. Study on morning land surface temperature retrieval of Sanjiang Plain using clear sky MODIS data%MODIS数据反演三江平原晴空上午陆表温度比较研究

    Institute of Scientific and Technical Information of China (English)

    孔繁艳

    2012-01-01

    三江平原大面积开垦后区域水热平衡发生变化,晴空上午陆表增温状况在开垦后和未开垦区域之间周年变化表现不同.选择2006~2009年55个时次67个Terra卫星上午降轨MODIS L1B数据集,在黑龙江南岸乌苏里江西岸开垦后农田、黑龙江北岸乌苏里江东岸俄罗斯境内未开垦平坦荒原各选择200个地面数据点,比较分析开垦和未开垦区晴空上午陆表温度(Land surface temperature,LST).结果表明,与未开垦荒原比较,开垦后区域LST年变化表现为两谷一峰:春季解冻后未开垦区有大量枯萎植物覆盖,开垦后区域裸土为主,表现为温度谷;5月下旬至7月中下旬,未开垦区植物大量生长,开垦区农田前期多为裸土或植株矮小,表现为一个很强的温度峰;7月末至8月末农田作物茂密生长,表现为另一个温度谷;9月以后至次年4月份大部分时间为冻土或被冰雪覆盖,开垦区和未开垦区LST差异不明显.%Water and heat balance of Sanjiang Plain has been changed after large area of reclamation. The increasing land surface temperature (LST) in morning of clear sky conditions performs an annual variation between cultivated and uncultivated land. 200 pairs of the sample data points distributed on the south bank of the Heilong River and the west bank of the Wusuli River in China and on the north bank of the Heilong River and the east bank of the Wusuli River in Russian were selected from reclaimed and unreclaimed lands respectively. 67 Terra Satellite descending orbit MODIS L1B granules from 55 days were used in this study. The results indicate that compared with the uncultivated wild land, LST annual variation of the cultivated area exhibits two valleys and one peak that are as follows: The first temperature valley appears after thawing in spring, when uncultivated area were covered with wilted plants while cultivated area are mostly bare land; From late May to mid/late July is a strong

  18. Observing the Agulhas Current with sea surface temperature and altimetry data: challenges and perspectives

    CSIR Research Space (South Africa)

    Krug, Marjolaine, J

    2014-06-01

    Full Text Available -Red Sea Surface Temperature datasets still suffer from inadequate cloud masking algorithms, particularly in regions of strong temperature gradient. Despite both Sea Surface Height and Sea Surface Temperature observations being severely compromised...

  19. New indexing and surface temperature analysis of exoplanets

    CERN Document Server

    Kashyap, J M; Safonova, M

    2016-01-01

    Study of exoplanets is the holy grail of present research in planetary sciences and astrobiology. Analysis of huge planetary data from space missions such as CoRoT and Kepler is directed ultimately at finding a planet similar to Earth\\-the Earth's twin, and answering the question of potential exo-habitability. The Earth Similarity Index (ESI) is a first step in this quest, ranging from 1 (Earth) to 0 (totally dissimilar to Earth). It was defined for the four physical parameters of a planet: radius, density, escape velocity and surface temperature. The ESI is further sub-divided into interior ESI (geometrical mean of radius and density) and surface ESI (geometrical mean of escape velocity and surface temperature). The challenge here is to determine which exoplanet parameter(s) is important in finding this similarity; how exactly the individual parameters entering the interior ESI and surface ESI are contributing to the global ESI. Since the surface temperature entering surface ESI is a non-observable quantity,...

  20. INVESTIGATION OF SURFACE TEMPERATURE IN HIGH-EFFICIENCY DEEP GRINDING

    Institute of Scientific and Technical Information of China (English)

    Zhao Henghua; Cai Guangqi; Jin Tan

    2005-01-01

    A new thermal model with triangular heat flux distribution is given in high-efficiency deep grinding. The mathematical expressions are driven to calculate the surface temperature. The transient behavior of the maximum temperature on contact area is investigated in different grinding conditions with a J-type thermocouple. The maximum contact temperatures measured in different conditions are found to be between 1 000 ℃ and 1 500 ℃ in burn-out conditions. The experiment results show good agreement with the new thermal model.

  1. The Remote Sensing of Surface Radiative Temperature over Barbados.

    Science.gov (United States)

    remote sensing of surface radiative temperature over Barbados was undertaken using a PRT-5 attached to a light aircraft. Traverses across the centre of the island, over the rugged east coast area, and the urban area of Bridgetown were undertaken at different times of day and night in the last week of June and the first week of December, 1969. These traverses show that surface variations in long-wave radiation emission lie within plus or minus 5% of the observations over grass at a representative site. The quick response of the surface to sunset and sunrise was

  2. Enzyme surface rigidity tunes the temperature dependence of catalytic rates.

    Science.gov (United States)

    Isaksen, Geir Villy; Åqvist, Johan; Brandsdal, Bjørn Olav

    2016-07-12

    The structural origin of enzyme adaptation to low temperature, allowing efficient catalysis of chemical reactions even near the freezing point of water, remains a fundamental puzzle in biocatalysis. A remarkable universal fingerprint shared by all cold-active enzymes is a reduction of the activation enthalpy accompanied by a more negative entropy, which alleviates the exponential decrease in chemical reaction rates caused by lowering of the temperature. Herein, we explore the role of protein surface mobility in determining this enthalpy-entropy balance. The effects of modifying surface rigidity in cold- and warm-active trypsins are demonstrated here by calculation of high-precision Arrhenius plots and thermodynamic activation parameters for the peptide hydrolysis reaction, using extensive computer simulations. The protein surface flexibility is systematically varied by applying positional restraints, causing the remarkable effect of turning the cold-active trypsin into a variant with mesophilic characteristics without changing the amino acid sequence. Furthermore, we show that just restraining a key surface loop causes the same effect as a point mutation in that loop between the cold- and warm-active trypsin. Importantly, changes in the activation enthalpy-entropy balance of up to 10 kcal/mol are almost perfectly balanced at room temperature, whereas they yield significantly higher rates at low temperatures for the cold-adapted enzyme.

  3. Temperature limit values for touching cold surfaces with the fingertip

    NARCIS (Netherlands)

    Geng, Q.; Holme, I.; Hartog, E.A. den; Havenith, G.; Jay, O.; Malchaires, J.; Piette, A.; Rintama, H.; Rissanen, S.

    2006-01-01

    Objectives: At the request of the European Commission and in the framework of the European Machinery Directive, research was performed in five different laboratories to develop specifications for surface temperature limit values for the short-term accidental touching of the fingertip with cold

  4. Temperature limit values for touching cold surfaces with the fingertip

    NARCIS (Netherlands)

    Geng, Q.; Holme, I.; Hartog, E.A. den; Havenith, G.; Jay, O.; Malchaires, J.; Piette, A.; Rintama, H.; Rissanen, S.

    2006-01-01

    Objectives: At the request of the European Commission and in the framework of the European Machinery Directive, research was performed in five different laboratories to develop specifications for surface temperature limit values for the short-term accidental touching of the fingertip with cold surfa

  5. Climate Prediction Center (CPC) Global Land Surface Air Temperature Analysis

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — A station observation-based global land monthly mean surface air temperature dataset at 0.5 x 0.5 latitude-longitude resolution for the period from 1948 to the...

  6. Quantifying and specifying the solar influence on terrestrial surface temperature

    NARCIS (Netherlands)

    de Jager, C.; Duhau, S.; van Geel, B.

    2010-01-01

    This investigation is a follow-up of a paper in which we showed that both major magnetic components of the solar dynamo, viz. the toroidal and the poloidal ones, are correlated with average terrestrial surface temperatures. Here, we quantify, improve and specify that result and search for their caus

  7. A physically based model of global freshwater surface temperature

    NARCIS (Netherlands)

    Beek, van L.P.H.; Eikelboom, T.; Vliet, van M.T.H.; Bierkens, M.F.P.

    2012-01-01

    Temperature determines a range of physical properties of water and exerts a strong control on surface water biogeochemistry. Thus, in freshwater ecosystems the thermal regime directly affects the geographical distribution of aquatic species through their growth and metabolism and indirectly through

  8. Climate Prediction Center (CPC) Global Land Surface Air Temperature Analysis

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — A station observation-based global land monthly mean surface air temperature dataset at 0.5 0.5 latitude-longitude resolution for the period from 1948 to the present...

  9. Processes of India's offshore summer intraseasonal sea surface temperature variability

    Digital Repository Service at National Institute of Oceanography (India)

    Kurian, N.; Lengaigne, M.; Gopalakrishna, V.V.; Vialard, J.; Pous, S.; Peter, A-C.; Durand; Naik, Shweta

    ., vol.63; 2013; 329-346 Processes of India’s offshore summer intraseasonal sea surface temperature variability K. Nisha1, M. Lengaigne1,2, V.V. Gopalakrishna,1 J. Vialard2, S. Pous2, A.-C. Peter2, F. Durand3, S.Naik1 1. NIO, CSIR, Goa, India 2...

  10. A physically based model of global freshwater surface temperature

    NARCIS (Netherlands)

    Beek, van L.P.H.; Eikelboom, T.; Vliet, van M.T.H.; Bierkens, M.F.P.

    2012-01-01

    Temperature determines a range of physical properties of water and exerts a strong control on surface water biogeochemistry. Thus, in freshwater ecosystems the thermal regime directly affects the geographical distribution of aquatic species through their growth and metabolism and indirectly through

  11. Surface temperature maps for II Peg during 1999-2002

    CERN Document Server

    Lindborg, M; Tuominen, I; Hackman, T; Ilyin, I; Piskunov, N

    2009-01-01

    The active RS CVn star II Peg has been spectroscopically monitored for almost 18 years with the SOFIN spectrograph at NOT, La Palma, Spain. In this paper we present five new surface temperature maps of the object for the years 1999 (two maps), 2001 (one map) and 2002 (two maps).

  12. A Microring Temperature Sensor Based on the Surface Plasmon Wave

    Directory of Open Access Journals (Sweden)

    Wenchao Li

    2015-01-01

    Full Text Available A structure of microring sensor suitable for temperature measurement based on the surface plasmon wave is put forward in this paper. The sensor uses surface plasmon multilayer waveguiding structure in the vertical direction and U-shaped microring structure in the horizontal direction and utilizes SOI as the thermal material. The transfer function derivation of the structure of surface plasmon microring sensor is according to the transfer matrix method. While the change of refractive index of Si is caused by the change of ambient temperature, the effective refractive index of the multilayer waveguiding structure is changed, resulting in the drifting of the sensor output spectrum. This paper focuses on the transmission characteristics of multilayer waveguide structure and the impact on the output spectrum caused by refractive index changes in temperature parts. According to the calculation and simulation, the transmission performance of the structure is stable and the sensitivity is good. The resonance wavelength shift can reach 0.007 μm when the temperature is increased by 100 k and FSR can reach about 60 nm. This structure achieves a high sensitivity in the temperature sense taking into account a wide range of filter frequency selections, providing a theoretical basis for the preparation of microoptics.

  13. Modeling the surface temperature of Earth-like planets

    CERN Document Server

    Vladilo, G; Murante, G; Filippi, L; Provenzale, A

    2015-01-01

    We introduce a novel Earth-like planet surface temperature model (ESTM) for habitability studies based on the spatial-temporal distribution of planetary surface temperatures. The ESTM adopts a surface Energy Balance Model complemented by: radiative-convective atmospheric column calculations, a set of physically-based parameterizations of meridional transport, and descriptions of surface and cloud properties more refined than in standard EBMs. The parameterization is valid for rotating terrestrial planets with shallow atmospheres and moderate values of axis obliquity (epsilon >= 45^o). Comparison with a 3D model of atmospheric dynamics from the literature shows that the equator-to-pole temperature differences predicted by the two models agree within ~5K when the rotation rate, insolation, surface pressure and planet radius are varied in the intervals 0.5 <= Omega/Omega_o <= 2, 0.75 <= S/S_o <= 1.25, 0.3 <= p/(1 bar) <= 10, and 0.5 <= R/R_o <= 2, respectively. The ESTM has an extremely l...

  14. Modeling Apple Surface Temperature Dynamics Based on Weather Data

    Directory of Open Access Journals (Sweden)

    Lei Li

    2014-10-01

    Full Text Available The exposure of fruit surfaces to direct sunlight during the summer months can result in sunburn damage. Losses due to sunburn damage are a major economic problem when marketing fresh apples. The objective of this study was to develop and validate a model for simulating fruit surface temperature (FST dynamics based on energy balance and measured weather data. A series of weather data (air temperature, humidity, solar radiation, and wind speed was recorded for seven hours between 11:00–18:00 for two months at fifteen minute intervals. To validate the model, the FSTs of “Fuji” apples were monitored using an infrared camera in a natural orchard environment. The FST dynamics were measured using a series of thermal images. For the apples that were completely exposed to the sun, the RMSE of the model for estimating FST was less than 2.0 °C. A sensitivity analysis of the emissivity of the apple surface and the conductance of the fruit surface to water vapour showed that accurate estimations of the apple surface emissivity were important for the model. The validation results showed that the model was capable of accurately describing the thermal performances of apples under different solar radiation intensities. Thus, this model could be used to more accurately estimate the FST relative to estimates that only consider the air temperature. In addition, this model provides useful information for sunburn protection management.

  15. A model of the tropical Pacific sea surface temperature climatology

    Science.gov (United States)

    Seager, Richard; Zebiak, Stephen E.; Cane, Mark A.

    1988-01-01

    A model for the climatological mean sea surface temperature (SST) of the tropical Pacific Ocean is developed. The upper ocean response is computed using a time dependent, linear, reduced gravity model, with the addition of a constant depth frictional surface layer. The full three-dimensional temperature equation and a surface heat flux parameterization that requires specification of only wind speed and total cloud cover are used to evaluate the SST. Specification of atmospheric parameters, such as air temperature and humidity, over which the ocean has direct influence, is avoided. The model simulates the major features of the observed tropical Pacific SST. The seasonal evolution of these features is generally captured by the model. Analysis of the results demonstrates the control the ocean has over the surface heat flux from ocean to atmosphere and the crucial role that dynamics play in determining the mean SST in the equatorial Pacific. The sensitivity of the model to perturbations in the surface heat flux, cloud cover specification, diffusivity, and mixed layer depth is discussed.

  16. Temperature maps measurements on 3D surfaces with infrared thermography

    Energy Technology Data Exchange (ETDEWEB)

    Cardone, Gennaro; Ianiro, Andrea [University of Naples Federico II, Department of Aerospace Engineering (DIAS), Naples (Italy); Ioio, Gennaro dello [University of Cambridge, BP Institute for Multiphase Flow, Cambridge, England (United Kingdom); Passaro, Andrea [Alta SpA, Ospedaletto, PI (Italy)

    2012-02-15

    The use of the infrared camera as a temperature transducer in wind tunnel applications is convenient and widespread. Nevertheless, the infrared data are available in the form of 2D images while the observed surfaces are often not planar and the reconstruction of temperature maps over them is a critical task. In this work, after recalling the principles of IR thermography, a methodology to rebuild temperature maps on the surfaces of 3D object is proposed. In particular, an optical calibration is applied to the IR camera by means of a novel target plate with control points. The proposed procedure takes also into account the directional emissivity by estimating the viewing angle. All the needed steps are described and analyzed. The advantages given by the proposed method are shown with an experiment in a hypersonic wind tunnel. (orig.)

  17. A Surface Temperature Initiated Closure (STIC) for surface energy balance fluxes

    DEFF Research Database (Denmark)

    Mallick, Kaniska; Jarvis, Andrew J.; Boegh, Eva;

    2014-01-01

    of four state equations. Taking advantage of the psychrometric relationship between temperature and vapor pressure, the present method also estimates the near surface moisture availability (M) from TS, air temperature (TA) and relative humidity (RH), thereby being capable of decomposing λ...

  18. Characterizing Greenland ice sheet surface mass balance via assimilation of spaceborne surface temperature, albedo, and passive microwave data into a physically-based model

    Science.gov (United States)

    Navari, M.; Bateni, S.; Margulis, S. A.; Alexander, P. M.; Tedesco, M.

    2012-12-01

    The Greenland ice sheet (GrIS) has been the focus of climate studies due to its significant impact on sea level rise and Arctic climate. Accurate estimates of space-time maps of surface mass balance (SMB) components including precipitation, runoff, and evaporation over the GrIS would contribute to understanding the cause of its recent unprecedented changes (e.g., increase in melt amount and duration, thickening of ice sheet interior, and thinning at the margins) and forecasting its changes in the future. In situ measurement of the SMB components across the GrIS is difficult and costly, and thus there are only a limited number of sparse measurements. Remote sensing retrievals are capable of providing some estimates of SMB terms and/or SMB indicators (i.e. melt onset), but generally provide an incomplete picture of the SMB. Additional efforts have focused on the use of regional climate models coupled to surface models in an effort to obtain spatially and temporally continuous estimates of the SMB. However, these estimates are prone to model errors and are generally unconstrained by the remote sensing record. To overcome these uncertainties and consequently improve estimates of the GrIS SMB, an ensemble data assimilation approach is developed for characterizing the SMB and its uncertainty. The EnBS consists of two steps: forecast and update. In the forecast step, an unconditional estimate of SMB using the MAR regional climate model and an ensemble implementation of the CROCUS snow is obtained that includes appropriate uncertainty in key SMB forcings. In the update step, the estimate is conditioned on remotely sensed land surface temperature (LST), albedo, and passive microwave (1.4, 6.9, 18.7, 36.5, and 89 GHz) measurements to provide a posterior estimate of the GrIS SMB components. The end result is an estimate that benefits from the regional atmospheric and snow models, but is also constrained by remote sensing data streams. The assimilation approach is tested for

  19. 利用NDVI估算云覆盖地区的植被表面温度研究%Study on Estimation of Vegetation Surface Temperature in Cloudy Region by NDVI

    Institute of Scientific and Technical Information of China (English)

    刘梅; 覃志豪; 涂丽丽; 张军

    2011-01-01

    Drought monitoring and other practical applications all need to obtain comprehensive spatial distribution of LST,but cloud cover is a major barrier of this process.We attempt to study the method of estimating vegetation surface temperature of cloudy areas in the remote sensing images by the relationship between changes of LST and ground vegetation.Because of the vegetation transpiration,the density of vegetation has a great effect on changes of spatial distribution of LST.This effect not only exists in cloudless areas,but also can be applied to the cloudy areas.Therefore,we first analyzed the relationship between LST and NDVI in cloudless areas which were nearby cloudy areas and established the equation;Then we used the feature that NDVI was stable within a short time to acquire NDVI value of cloudy areas.At last,we estimated the LST of cloudy areas according to the relationship between the NDVI and LST.We applied this method to Landsat ETM+ images of Liaocheng city in Shandong province.The results show that,when the cloudy area is within or equal to 2 000 pixels(about 1.72 km2),the mean absolute error(MAE) of LST in cloudy area which estimated through NDVI is little than 0.7 ℃,the RMS is1.2 ℃.In order to verify its practicality,we also applied the method to TM images of Bengbu in Anhui province,when cloudy area is within 300 pixels,the MAE is less than 0.1 ℃.Hence,it can be argued that when the range of cloudy area is not very large,using NDVI to estimate the LST of cloudy area has certain feasibility.%干旱监测等实际应用都需要全面掌握地表温度(LST)的空间分布,而云覆盖是这种应用的重要阻碍。试图根据地表温度变化与地表植被之间的相互关系,研究遥感影像中云覆盖区域植被表面温度的估算方法。由于植被的蒸腾作用,植被茂密程度对其表面温度的空间分布有较大影响。这种影响不仅在晴朗无云区域存在,同样适用于云覆盖区域。因此,

  20. Designing high-temperature steels via surface science and thermodynamics

    Science.gov (United States)

    Gross, Cameron T.; Jiang, Zilin; Mathai, Allan; Chung, Yip-Wah

    2016-06-01

    Electricity in many countries such as the US and China is produced by burning fossil fuels in steam-turbine-driven power plants. The efficiency of these power plants can be improved by increasing the operating temperature of the steam generator. In this work, we adopted a combined surface science and computational thermodynamics approach to the design of high-temperature, corrosion-resistant steels for this application. The result is a low-carbon ferritic steel with nanosized transition metal monocarbide precipitates that are thermally stable, as verified by atom probe tomography. High-temperature Vickers hardness measurements demonstrated that these steels maintain their strength for extended periods at 700 °C. We hypothesize that the improved strength of these steels is derived from the semi-coherent interfaces of these thermally stable, nanosized precipitates exerting drag forces on impinging dislocations, thus maintaining strength at elevated temperatures.

  1. Surface layer temperature inversion in the Bay of Bengal

    Science.gov (United States)

    Thadathil, Pankajakshan; Gopalakrishna, V. V.; Muraleedharan, P. M.; Reddy, G. V.; Araligidad, Nilesh; Shenoy, Shrikant

    2002-10-01

    Surface layer temperature inversion occurring in the Bay of Bengal has been addressed. Hydrographic data archived in the Indian Oceanographic Data Center are used to understand various aspects of the temperature inversion of surface layer in the Bay of Bengal, such as occurrence time, characteristics, stability, inter-annual variability and generating mechanisms. Spatially organized temperature inversion occurs in the coastal waters of the western and northeastern Bay during winter (November-February). Although the inversion in the northeastern Bay is sustained until February (with remnants seen even in March), in the western Bay it becomes less organized in January and almost disappears by February. Inversion is confined to the fresh water induced seasonal halocline of the surface layer. Inversions of large temperature difference (of the order of 1.6-2.4°C) and thin layer thickness (10-20 m) are located adjacent to major fresh water inputs from the Ganges, Brahmaputra, Irrawaddy, Krishna and Godavari rivers. The inversion is stable with a mean stability of 3600×10 -8 m -1. Inter-annual variability of the inversion is significantly high and it is caused by the inter-annual variability of fresh water flux and surface cooling in the northern Bay. Fresh water flux leads the occurrence process in association with surface heat flux and advection. The leading role of fresh water flux is understood from the observation that the two occurrence regions of inversion (the western and northeastern Bay) have proximity to the two low salinity (with values about 28-29‰) zones. In the western Bay, the East India Coastal Current brings less saline and cold water from the head of the Bay to the south-west Bay, where it advects over warm, saline water, promoting temperature inversion in this region in association with the surface heat loss. For inversion occurring in the northeastern Bay (where the surface water gains heat from atmosphere), surface advection of the less saline

  2. New Measurements from Old Boreholes: A Look at Interaction Between Surface Air Temperature and Ground Surface Temperature

    Science.gov (United States)

    Heinle, S. M.; Gosnold, W. D.

    2007-12-01

    We recently logged new field measurements of several boreholes throughout the Midwest, including North Dakota, South Dakota, and Nebraska. We then compared these new measurements against measurements previously obtained. Our comparisons included inverse modeling of past and recent measurements as well as climate modeling based on past surface air temperatures obtained from the weather stations. The data show a good correlation between climate warming in the last century and ground surface warming. Of particular importance is that cooling of air temperatures beginning in the mid 1990s reflects in the ground surface temperatures. The boreholes included in the study consist of three boreholes located in north central North Dakota, including two deeper than 200 meters. Two boreholes in the southwestern part of South Dakota, and two from southeastern South Dakota, all approximately 180 meters deep. Also included, were two boreholes (135 meters and over 200 meters deep) located in southwestern Nebraska, and two boreholes in the panhandle of Nebraska, each over 100 meters deep. We obtained historical surface air temperature from climate stations located near the boreholes, both from the United States Historical Climatology Network and from the Western Regional Climate Center.

  3. Surface emissivity and temperature retrieval for a hyperspectral sensor

    Energy Technology Data Exchange (ETDEWEB)

    Borel, C.C.

    1998-12-01

    With the growing use of hyper-spectral imagers, e.g., AVIRIS in the visible and short-wave infrared there is hope of using such instruments in the mid-wave and thermal IR (TIR) some day. The author believes that this will enable him to get around using the present temperature-emissivity separation algorithms using methods which take advantage of the many channels available in hyper-spectral imagers. A simple fact used in coming up with a novel algorithm is that a typical surface emissivity spectrum are rather smooth compared to spectral features introduced by the atmosphere. Thus, a iterative solution technique can be devised which retrieves emissivity spectra based on spectral smoothness. To make the emissivities realistic, atmospheric parameters are varied using approximations, look-up tables derived from a radiative transfer code and spectral libraries. One such iterative algorithm solves the radiative transfer equation for the radiance at the sensor for the unknown emissivity and uses the blackbody temperature computed in an atmospheric window to get a guess for the unknown surface temperature. By varying the surface temperature over a small range a series of emissivity spectra are calculated. The one with the smoothest characteristic is chosen. The algorithm was tested on synthetic data using MODTRAN and the Salisbury emissivity database.

  4. Sea-surface temperature and salinity mapping from remote microwave radiometric measurements of brightness temperature

    Science.gov (United States)

    Hans-Juergen, C. B.; Kendall, B. M.; Fedors, J. C.

    1977-01-01

    A technique to measure remotely sea surface temperature and salinity was demonstrated with a dual frequency microwave radiometer system. Accuracies in temperature of 1 C and in salinity of part thousand for salinity greater than 5 parts per thousand were attained after correcting for the influence of extraterrestrial background radiation, atmospheric radiation and attenuation, sea-surface roughness, and antenna beamwidth. The radiometers, operating at 1.43 and 2.65 GHz, comprise a third-generation system using null balancing and feedback noise injection. Flight measurements from an aircraft at an altitude of 1.4 km over the lower Chesapeake Bay and coastal areas of the Atlantic Ocean resulted in contour maps of sea-surface temperature and salinity with a spatial resolution of 0.5 km.

  5. Ultraviolet surface plasmon-mediated low temperature hydrazine decomposition

    Energy Technology Data Exchange (ETDEWEB)

    Peng, Siying; Sheldon, Matthew T.; Atwater, Harry A. [Thomas J. Watson Laboratories of Applied Physics, California Institute of Technology, Pasadena, California 91125 (United States); Liu, Wei-Guang; Jaramillo-Botero, Andres; Goddard, William Andrew [Materials and Process Simulation Center, California Institute of Technology, Pasadena, California 91125 (United States)

    2015-01-12

    Conventional methods require elevated temperatures in order to dissociate high-energy nitrogen bonds in precursor molecules such as ammonia or hydrazine used for nitride film growth. We report enhanced photodissociation of surface-absorbed hydrazine (N{sub 2}H{sub 4}) molecules at low temperature by using ultraviolet surface plasmons to concentrate the exciting radiation. Plasmonic nanostructured aluminum substrates were designed to provide resonant near field concentration at λ = 248 nm (5 eV), corresponding to the maximum optical cross section for hydrogen abstraction from N{sub 2}H{sub 4}. We employed nanoimprint lithography to fabricate 1 mm × 1 mm arrays of the resonant plasmonic structures, and ultraviolet reflectance spectroscopy confirmed resonant extinction at 248 nm. Hydrazine was cryogenically adsorbed to the plasmonic substrate in a low-pressure ambient, and 5 eV surface plasmons were resonantly excited using a pulsed KrF laser. Mass spectrometry was used to characterize the photodissociation products and indicated a 6.2× overall enhancement in photodissociation yield for hydrazine adsorbed on plasmonic substrates compared with control substrates. The ultraviolet surface plasmon enhanced photodissociation demonstrated here may provide a valuable method to generate reactive precursors for deposition of nitride thin film materials at low temperatures.

  6. The dependence of surface temperature on IGBTs load and ambient temperature

    Science.gov (United States)

    Alexander, Čaja; Marek, Patsch

    2015-05-01

    Currently, older power electronics and electrotechnics are improvement and at the same time developing new and more efficient devices. These devices produce in their activities a significant part of the heat which, if not effectively drained, causing damage to these elements. In this case, it is important to develop new and more efficient cooling system. The most widespread of modern methods of cooling is the cooling by heat pipe. This contribution is aimed at cooling the insulated-gate bipolar transistor (IGBT) elements by loop heat pipe (LHP). IGBTs are very prone to damage due to high temperatures, and therefore is the important that the surface temperature was below 100°C. It was therefore created a model that examined what impact of surface temperature on the IGBT element and heat removal at different load and constant ambient temperature.

  7. The dependence of surface temperature on IGBTs load and ambient temperature

    Directory of Open Access Journals (Sweden)

    Alexander Čaja

    2015-01-01

    Full Text Available Currently, older power electronics and electrotechnics are improvement and at the same time developing new and more efficient devices. These devices produce in their activities a significant part of the heat which, if not effectively drained, causing damage to these elements. In this case, it is important to develop new and more efficient cooling system. The most widespread of modern methods of cooling is the cooling by heat pipe. This contribution is aimed at cooling the insulated-gate bipolar transistor (IGBT elements by loop heat pipe (LHP. IGBTs are very prone to damage due to high temperatures, and therefore is the important that the surface temperature was below 100°C. It was therefore created a model that examined what impact of surface temperature on the IGBT element and heat removal at different load and constant ambient temperature.

  8. Piglets’ Surface Temperature Change at Different Weights at Birth

    Science.gov (United States)

    Caldara, Fabiana Ribeiro; dos Santos, Luan Sousa; Machado, Sivanilza Teixeira; Moi, Marta; de Alencar Nääs, Irenilza; Foppa, Luciana; Garcia, Rodrigo Garófallo; de Kássia Silva dos Santos, Rita

    2014-01-01

    The study was carried out in order to verify the effects of piglets’ weight at birth on their surface temperature change (ST) after birth, and its relationship with ingestion time of colostrum. Piglets from four different sows were weighed at birth and divided into a totally randomized design with three treatments according to birth weight (PBW): T1 - less than 1.00 kg, T2 - 1.00 to 1.39 kg, and T3 - higher than or equal to 1.40 kg. The time spent for the first colostrum ingestion was recorded (TFS). Images of piglets’ surface by thermal imaging camera were recorded at birth (STB) and 15, 30, 45, 60, and 120 min after birth. The air temperature and relative humidity were recorded every 30 min and the indexes of temperature and humidity (THI) were calculated. A ST drop after 15 min from birth was observed, increasing again after sixty minutes. Positive correlations were found between the PBW and the ST at 30 and 45 min after birth. The PBW was negatively correlated with the TFS. The THI showed high negative correlations (−0.824 and −0.815) with STB and after 15 min from birth. The piglet’s surface temperature at birth was positively correlated with temperature thereof to 15 min, influencing therefore the temperatures in the interval of 45 to 120 min. The birth weight contributes significantly to postnatal hypothermia and consequently to the time it takes for piglets ingest colostrum, requiring special attention to those of low birth weight. PMID:25049971

  9. Piglets' surface temperature change at different weights at birth.

    Science.gov (United States)

    Caldara, Fabiana Ribeiro; Dos Santos, Luan Sousa; Machado, Sivanilza Teixeira; Moi, Marta; de Alencar Nääs, Irenilza; Foppa, Luciana; Garcia, Rodrigo Garófallo; de Kássia Silva Dos Santos, Rita

    2014-03-01

    The study was carried out in order to verify the effects of piglets' weight at birth on their surface temperature change (ST) after birth, and its relationship with ingestion time of colostrum. Piglets from four different sows were weighed at birth and divided into a totally randomized design with three treatments according to birth weight (PBW): T1 - less than 1.00 kg, T2 - 1.00 to 1.39 kg, and T3 - higher than or equal to 1.40 kg. The time spent for the first colostrum ingestion was recorded (TFS). Images of piglets' surface by thermal imaging camera were recorded at birth (STB) and 15, 30, 45, 60, and 120 min after birth. The air temperature and relative humidity were recorded every 30 min and the indexes of temperature and humidity (THI) were calculated. A ST drop after 15 min from birth was observed, increasing again after sixty minutes. Positive correlations were found between the PBW and the ST at 30 and 45 min after birth. The PBW was negatively correlated with the TFS. The THI showed high negative correlations (-0.824 and -0.815) with STB and after 15 min from birth. The piglet's surface temperature at birth was positively correlated with temperature thereof to 15 min, influencing therefore the temperatures in the interval of 45 to 120 min. The birth weight contributes significantly to postnatal hypothermia and consequently to the time it takes for piglets ingest colostrum, requiring special attention to those of low birth weight.

  10. Piglets’ Surface Temperature Change at Different Weights at Birth

    Directory of Open Access Journals (Sweden)

    Fabiana Ribeiro Caldara

    2014-03-01

    Full Text Available The study was carried out in order to verify the effects of piglets’ weight at birth on their surface temperature change (ST after birth, and its relationship with ingestion time of colostrum. Piglets from four different sows were weighed at birth and divided into a totally randomized design with three treatments according to birth weight (PBW: T1 - less than 1.00 kg, T2 - 1.00 to 1.39 kg, and T3 - higher than or equal to 1.40 kg. The time spent for the first colostrum ingestion was recorded (TFS. Images of piglets’ surface by thermal imaging camera were recorded at birth (STB and 15, 30, 45, 60, and 120 min after birth. The air temperature and relative humidity were recorded every 30 min and the indexes of temperature and humidity (THI were calculated. A ST drop after 15 min from birth was observed, increasing again after sixty minutes. Positive correlations were found between the PBW and the ST at 30 and 45 min after birth. The PBW was negatively correlated with the TFS. The THI showed high negative correlations (−0.824 and −0.815 with STB and after 15 min from birth. The piglet’s surface temperature at birth was positively correlated with temperature thereof to 15 min, influencing therefore the temperatures in the interval of 45 to 120 min. The birth weight contributes significantly to postnatal hypothermia and consequently to the time it takes for piglets ingest colostrum, requiring special attention to those of low birth weight.

  11. A Quasi-Global Approach to Improve Day-Time Satellite Surface Soil Moisture Anomalies through the Land Surface Temperature Input

    Directory of Open Access Journals (Sweden)

    Robert M. Parinussa

    2016-10-01

    the radiative transfer was varied by imposing a bias on an existing regression. These scenarios were evaluated through the Rvalue technique, resulting in optimal bias values on top of this regression. In a next step, these optimal bias values were incorporated in order to re-calibrate the existing linear regression, resulting in a quasi-global uniform LST relation for day-time observations. In a final step, day-time soil moisture retrievals using the re-calibrated land surface temperature relation were again validated through the Rvalue technique. Results indicate an average increasing Rvalue of 16.5%, which indicates a better performance obtained through the re-calibration. This number was confirmed through an independent Triple Collocation verification over the same domain, demonstrating an average root mean square error reduction of 15.3%. Furthermore, a comparison against an extensive in situ database (679 stations also indicates a generally higher quality for the re-calibrated dataset. Besides the improved day-time dataset, this study furthermore provides insights on the relative quality of soil moisture retrieved from AMSR-E’s day- and night-time observations.

  12. Temperature-dependent photoluminescence of surface-engineered silicon nanocrystals

    Science.gov (United States)

    Mitra, Somak; Švrček, Vladimir; Macias-Montero, Manual; Velusamy, Tamilselvan; Mariotti, Davide

    2016-01-01

    In this work we report on temperature-dependent photoluminescence measurements (15–300 K), which have allowed probing radiative transitions and understanding of the appearance of various transitions. We further demonstrate that transitions associated with oxide in SiNCs show characteristic vibronic peaks that vary with surface characteristics. In particular we study differences and similarities between silicon nanocrystals (SiNCs) derived from porous silicon and SiNCs that were surface-treated using a radio-frequency (RF) microplasma system. PMID:27296771

  13. Biological control of surface temperature in the Arabian Sea

    Science.gov (United States)

    Sathyendranath, Shubha; Gouveia, Albert D.; Shetye, Satish R.; Ravindran, P.; Platt, Trevor

    1991-01-01

    In the Arabian Sea, the southwest monsoon promotes seasonal upwelling of deep water, which supplies nutrients to the surface layer and leads to a marked increase in phytoplankton growth. Remotely sensed data on ocean color are used here to show that the resulting distribution of phytoplankton exerts a controlling influence on the seasonal evolution of sea surface temperature. This results in a corresponding modification of ocean-atmosphere heat exchange on regional and seasonal scales. It is shown that this biological mechanism may provide an important regulating influence on ocean-atmosphere interactions.

  14. Calibration plan for the sea and land surface temperature radiometer

    Science.gov (United States)

    Smith, David L.; Nightingale, Tim J.; Mortimer, Hugh; Middleton, Kevin; Edeson, Ruben; Cox, Caroline V.; Mutlow, Chris T.; Maddison, Brian J.

    2013-10-01

    The Sea and Land Surface Temperature Radiometer (SLSTR) to be flown on ESA's Sentinel-3 mission is a multichannel scanning radiometer that will continue the 21-year datasets of the Along Track Scanning Radiometer (ATSR) series. As its name implies, measurements from SLSTR will be used to retrieve global sea surface temperatures to an uncertainty of SLSTR instrument, infrared calibration sources and alignment equipment. The calibration rig has been commissioned and results of these tests will be presented. Finally the authors will present the planning for the on-orbit monitoring and calibration activities to ensure that calibration is maintained. These activities include vicarious calibration techniques that have been developed through previous missions, and the deployment of ship-borne radiometers.

  15. A surface acoustic wave ICP sensor with good temperature stability.

    Science.gov (United States)

    Zhang, Bing; Hu, Hong; Ye, Aipeng; Zhang, Peng

    2017-07-20

    Intracranial pressure (ICP) monitoring is very important for assessing and monitoring hydrocephalus, head trauma and hypertension patients, which could lead to elevated ICP or even devastating neurological damage. The mortality rate due to these diseases could be reduced through ICP monitoring, because precautions can be taken against the brain damage. This paper presents a surface acoustic wave (SAW) pressure sensor to realize ICP monitoring, which is capable of wireless and passive transmission with antenna attached. In order to improve the temperature stability of the sensor, two methods were adopted. First, the ST cut quartz was chosen as the sensor substrate due to its good temperature stability. Then, a differential temperature compensation method was proposed to reduce the effects of temperature. Two resonators were designed based on coupling of mode (COM) theory and the prototype was fabricated and verified using a system established for testing pressure and temperature. The experiment result shows that the sensor has a linearity of 2.63% and hysteresis of 1.77%. The temperature stability of the sensor has been greatly improved by using the differential compensation method, which validates the effectiveness of the proposed method.

  16. A New Estimate of the Earth's Land Surface Temperature History

    Science.gov (United States)

    Muller, R. A.; Curry, J. A.; Groom, D.; Jacobsen, B.; Perlmutter, S.; Rohde, R. A.; Rosenfeld, A.; Wickham, C.; Wurtele, J.

    2011-12-01

    The Berkeley Earth Surface Temperature team has re-evaluated the world's atmospheric land surface temperature record using a linear least-squares method that allow the use of all the digitized records back to 1800, including short records that had been excluded by prior groups. We use the Kriging method to estimate an optimal weighting of stations to give a world average based on uniform weighting of the land surface. We have assembled a record of the available data by merging 1.6 billion temperature reports from 16 pre-existing data archives; this data base will be made available for public use. The former Global Historic Climatology Network (GHCN) monthly data base shows a sudden drop in the number of stations reporting monthly records from 1980 to the present; we avoid this drop by calculating monthly averages from the daily records. By using all the data, we reduce the effects of potential data selection bias. We make an independent estimate of the urban heat island effect by calculating the world land temperature trends based on stations chosen to be far from urban sites. We calculate the effect of poor station quality, as documented in the US by the team led by Anthony Watts by estimating the temperature trends based solely on the stations ranked good (1,2 or 1,2,3 in the NOAA ranking scheme). We avoid issues of homogenization bias by using raw data; at times when the records are discontinuous (e.g. due to station moves) we break the record into smaller segments and analyze those, rather than attempt to correct the discontinuity. We estimate the uncertainties in the final results using the jackknife procedure developed by J. Tukey. We calculate spatial uncertainties by measuring the effects of geographical exclusion on recent data that have good world coverage. The results we obtain are compared to those published by the groups at NOAA, NASA-GISS, and Hadley-CRU in the UK.

  17. Effect of floor surface temperature on blood flow and skin temperature in the foot.

    Science.gov (United States)

    Song, G-S

    2008-12-01

    A total of 16 healthy college students participated as subjects to elucidate the hypothesis that blood flow and skin temperature in foot are affected by the floor surface temperature. The floor surface temperature was controlled by varying the temperature of water (tw) flowing underneath the floor, and it ranged from tw 15 to 40 degrees C at 5 degrees C intervals. The blood flow rate was measured in the dorsal right toe, and skin temperatures were measured for 60 min at 8 points: the neck, right scapular, left hand, right shin, left bottom of the toe, right instep, left finger, and rectum. The blood flow rate in the foot tissue was increased until the foot skin temperature warmed up to 34 degrees C (P = 0.000). The final skin temperatures on the bottom of the toe were 19.4 +/- 2.44 degrees C for tw 15 degrees C, 22.4 +/- 2.45 degrees C for tw 20 degrees C, 24.8 +/- 2.80 degrees C for tw 25 degrees C, 27.7 +/- 2.13 degrees C for tw 30 degrees C, 30.6 +/- 2.06 degrees C for tw 35 degrees C, 33.2 +/- 1.45 degrees C for tw 40 degrees C, 34.2 +/- 1.55 degrees C for tw 45 degrees C, and 35.2 +/- 1.65 degrees C for tw 50 degrees C. Considering blood flow and comfort, the partial floor heating system is suggested and the recommended floor surface temperature range is 27-33 degrees C. A warm floor surface can serve to satisfy occupants when the ambient temperature maintained at 20 degrees C which represents an energy conscious temperature. A warm floor can induce high blood perfusion in the feet and consequently improve an occupant's health by treating many vascular-related disorders. Even in a well-insulated residential building, a partially heated floor system could prevent overheating while providing surface warmth.

  18. Actual evaporation estimation from infrared measurement of soil surface temperature

    Directory of Open Access Journals (Sweden)

    Davide Pognant

    2013-09-01

    Full Text Available Within the hydrological cycle, actual evaporation represents the second most important process in terms of volumes of water transported, second only to the precipitation phenomena. Several methods for the estimation of the Ea were proposed by researchers in scientific literature, but the estimation of the Ea from potential evapotranspiration often requires the knowledge of hard-to-find parameters (e.g.: vegetation morphology, vegetation cover, interception of rainfall by the canopy, evaporation from the canopy surface and uptake of water by plant roots and many existing database are characterized by missing or incomplete information that leads to a rough estimation of the actual evaporation amount. Starting from the above considerations, the aim of this study is to develop and validate a method for the estimation of the Ea based on two steps: i the potential evaporation estimation by using the meteorological data (i.e. Penman-Monteith; ii application of a correction factor based on the infrared soil surface temperature measurements. The dataset used in this study were collected during two measurement campaigns conducted both in a plain testing site (Grugliasco, Italy, and in a mountain South-East facing slope (Cogne, Italy. During those periods, hourly measurement of air temperature, wind speed, infrared surface temperature, soil heat flux, and soil water content were collected. Results from the dataset collected in the two testing sites show a good agreement between the proposed method and reference methods used for the Ea estimation.

  19. High temperature surface degradation of III-V nitrides

    Energy Technology Data Exchange (ETDEWEB)

    Vartuli, C.B.; Pearton, S.J.; Abernathy, C.R.; MacKenzie, J.D.; Lambers, E.S. [Univ. of Florida, Gainesville, FL (United States). Dept. of Materials Science and Engineering; Zolper, J.C. [Sandia National Labs., Albuquerque, NM (United States)

    1996-05-01

    The surface stoichiometry, surface morphology and electrical conductivity of AlN, GaN, InN, InGaN and InAlN was examined at rapid thermal annealing temperatures up to 1,150 C. The sheet resistance of the AlN dropped steadily with annealing, but the surface showed signs of roughening only above 1,000 C. Auger Electronic Spectroscopy (AES) analysis showed little change in the surface stoichiometry even at 1,150 C. GaN root mean square (RMS) surface roughness showed an overall improvement with annealing, but the surface became pitted at 1,000 C, at which point the sheet resistance also dropped by several orders of magnitude, and AES confirmed a loss of N from the surface. The InN surface had roughened considerably even at 650 C, and scanning electron microscopy (SEM) showed significant degradation. In contrast to the binary nitrides the sheet resistance of InAlN was found to increase by {approximately} 10{sup 2} from the as grown value after annealing at 800 C and then remain constant up to 1,000 C, while that of InGaN increased rapidly above 700 C. The RMS roughness increased above 800 C and 700 C respectively for InAlN and InGaN samples. In droplets began to form on the surface at 900 C for InAlN and at 800 C for InGaN, and then evaporate at 1,000 C leaving pits. AES analysis showed a decrease in the N concentration in the top 500 {angstrom} of the sample for annealing {ge} 800 C in both materials.

  20. Cloning and expression of gene, and activation of an organic solvent-stable lipase from Pseudomonas aeruginosa LST-03.

    Science.gov (United States)

    Ogino, Hiroyasu; Katou, Yoshikazu; Akagi, Rieko; Mimitsuka, Takashi; Hiroshima, Shinichi; Gemba, Yuichi; Doukyu, Noriyuki; Yasuda, Masahiro; Ishimi, Kosaku; Ishikawa, Haruo

    2007-11-01

    Organic solvent-tolerant Pseudomonas aeruginosa LST-03 secretes an organic solvent-stable lipase, LST-03 lipase. The gene of the LST-03 lipase (Lip9) and the gene of the lipase-specific foldase (Lif9) were cloned and expressed in Escherichia coli. In the cloned 2.6 kbps DNA fragment, two open reading frames, Lip9 consisting of 933 nucleotides which encoded 311 amino acids and Lif9 consisting of 1,020 nucleotides which encoded 340 amino acids, were found. The overexpression of the lipase gene (lip9) was achieved when T7 promoter was used and the signal peptide of the lipase was deleted. The expressed amount of the lipase was greatly increased and overexpressed lipase formed inclusion body in E. coli cell. The collected inclusion body of the lipase from the cell was easily solubilized by urea and activated by using lipase-specific foldase of which 52 or 58 amino acids of N-terminal were deleted. Especially, the N-terminal methionine of the lipase of which the signal peptide was deleted was released in E. coli and the amino acid sequence was in agreement with that of the originally-produced lipase by P. aeruginosa LST-03. Furthermore, the overexpressed and solubilized lipase of which the signal peptide was deleted was more effectively activated by lipase-specific foldase.

  1. Surface Tensions and Their Variations with Temperature and Impurities

    Science.gov (United States)

    Hardy, S. C.; Fine, J.

    1985-01-01

    The surface tensions in this work were determined using the sessile drop technique. This method is based on a comparison of the profile of a liquid drop with the profile calculated by solving the Young-Laplace equation. The comparison can be made in several ways; the traditional Bashforth-Adams procedure was used in conjunction with recently calculated drop shape tables which virtually eliminate interpolation errors. Although previous study has found little difference in measurements with pure and oxygen doped silicon, there is other evidence suggesting that oxygen in dilute concentrations severely depresses the surface tension of silicon. The surface tension of liquid silicon in purified argon atmospheres was measured. A temperature coefficient near -0.28 mJ/square meters K was found. The experiments show a high sensitivity of the surface tension to what is believed are low concentrations of oxygen. Thus one cannot rule out some effect of low levels of oxygen in the results. However, the highest surface tension values obtained in conditions which minimized the residual oxygen pressure are in good agreement with a previous measurement in pure hydrogen. Therefore, depression of the surface tension by oxygen is insignificant in these measurements.

  2. Decadal trends in Red Sea maximum surface temperature

    KAUST Repository

    Chaidez, Veronica

    2017-08-09

    Ocean warming is a major consequence of climate change, with the surface of the ocean having warmed by 0.11 °C decade-1 over the last 50 years and is estimated to continue to warm by an additional 0.6 - 2.0 °C before the end of the century1. However, there is considerable variability in the rates experienced by different ocean regions, so understanding regional trends is important to inform on possible stresses for marine organisms, particularly in warm seas where organisms may be already operating in the high end of their thermal tolerance. Although the Red Sea is one of the warmest ecosystems on earth, its historical warming trends and thermal evolution remain largely understudied. We characterized the Red Sea\\'s thermal regimes at the basin scale, with a focus on the spatial distribution and changes over time of sea surface temperature maxima, using remotely sensed sea surface temperature data from 1982 - 2015. The overall rate of warming for the Red Sea is 0.17 ± 0.07 °C decade-1, while the northern Red Sea is warming between 0.40 and 0.45 °C decade-1, all exceeding the global rate. Our findings show that the Red Sea is fast warming, which may in the future challenge its organisms and communities.

  3. Using Canopy Temperature to Infer Hydrologic Processes in Floodplain Forests

    Science.gov (United States)

    Lemon, M. G.; Allen, S. T.; Keim, R.; Edwards, B. L.; King, S. L.

    2015-12-01

    Decreased water availability due to hydrologic modifications, groundwater withdrawal, and climate change threaten the hydrological architecture of floodplain forests globally. The relative contributions of different sources of water (e.g., precipitation, surface flooding, and groundwater) to soil moisture on floodplains is poorly constrained, so identification of areas of water stress within a floodplain can provide valuable information about floodplain hydrology. Canopy temperature is a useful indicator of moisture stress and has long been used in agricultural and natural landscapes. Accordingly, thermal infrared (TIR) remote sensing data (spatial resolution of 1 km) from NASA's MODIS sensor was used to examine patterns of spatiotemporal variation in water stress in two floodplain forests over 12 growing seasons. On the upper Sabine River floodplain, Texas, increasing rainfall-derived soil moisture corresponded with increased heterogeneity of LST but there was weak association between river stage and heterogeneity. On the lower White River floodplain, Arkansas, distinct differences in LST between two reaches were observed during low flow years, while little relationship was observed between LST spatial variability and rainfall-derived soil moisture on either reach. The differences in hydrological control on these floodplain ecosystems have important ramifications for varying resilience to climate change and water resource management.

  4. Temperature-mediated transition from Dyakonov-Tamm surface waves to surface-plasmon-polariton waves

    Science.gov (United States)

    Chiadini, Francesco; Fiumara, Vincenzo; Mackay, Tom G.; Scaglione, Antonio; Lakhtakia, Akhlesh

    2017-08-01

    The effect of changing the temperature on the propagation of electromagnetic surface waves (ESWs), guided by the planar interface of a homogeneous isotropic temperature-sensitive material (namely, InSb) and a temperature-insensitive structurally chiral material (SCM) was numerically investigated in the terahertz frequency regime. As the temperature rises, InSb transforms from a dissipative dielectric material to a dissipative plasmonic material. Correspondingly, the ESWs transmute from Dyakonov-Tamm surface waves into surface-plasmon-polariton waves. The effects of the temperature change are clearly observed in the phase speeds, propagation distances, angular existence domains, multiplicity, and spatial profiles of energy flow of the ESWs. Remarkably large propagation distances can be achieved; in such instances the energy of an ESW is confined almost entirely within the SCM. For certain propagation directions, simultaneous excitation of two ESWs with (i) the same phase speeds but different propagation distances or (ii) the same propagation distances but different phase speeds are also indicated by our results.

  5. Gaia FGK Benchmark Stars: Effective temperatures and surface gravities

    CERN Document Server

    Heiter, U; Gustafsson, B; Korn, A J; Soubiran, C; Thévenin, F

    2015-01-01

    Large Galactic stellar surveys and new generations of stellar atmosphere models and spectral line formation computations need to be subjected to careful calibration and validation and to benchmark tests. We focus on cool stars and aim at establishing a sample of 34 Gaia FGK Benchmark Stars with a range of different metallicities. The goal was to determine the effective temperature and the surface gravity independently from spectroscopy and atmospheric models as far as possible. Fundamental determinations of Teff and logg were obtained in a systematic way from a compilation of angular diameter measurements and bolometric fluxes, and from a homogeneous mass determination based on stellar evolution models. The derived parameters were compared to recent spectroscopic and photometric determinations and to gravity estimates based on seismic data. Most of the adopted diameter measurements have formal uncertainties around 1%, which translate into uncertainties in effective temperature of 0.5%. The measurements of bol...

  6. Global Surface Temperature Response Explained by Multibox Energy Balance Models

    Science.gov (United States)

    Fredriksen, H. B.; Rypdal, M.

    2016-12-01

    We formulate a multibox energy balance model, from which global temperature evolution can be described by convolving a linear response function and a forcing record. We estimate parameters in the response function from instrumental data and historic forcing, such that our model can produce a response to both deterministic forcing and stochastic weather forcing consistent with observations. Furthermore, if we make separate boxes for upper oc