30 CFR 780.23 - Reclamation plan: Land use information.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 30 Mineral Resources 3 2011-07-01 2011-07-01 false Reclamation plan: Land use information. 780.23... INTERIOR SURFACE COAL MINING AND RECLAMATION OPERATIONS PERMITS AND COAL EXPLORATION SYSTEMS UNDER... PLAN § 780.23 Reclamation plan: Land use information. (a) The plan shall contain a statement of the...

Comparison of two perturbation methods to estimate the land surface modeling uncertainty

NASA Astrophysics Data System (ADS)

Su, H.; Houser, P.; Tian, Y.; Kumar, S.; Geiger, J.; Belvedere, D.

2007-12-01

In land surface modeling, it is almost impossible to simulate the land surface processes without any error because the earth system is highly complex and the physics of the land processes has not yet been understood sufficiently. In most cases, people want to know not only the model output but also the uncertainty in the modeling, to estimate how reliable the modeling is. Ensemble perturbation is an effective way to estimate the uncertainty in land surface modeling, since land surface models are highly nonlinear which makes the analytical approach not applicable in this estimation. The ideal perturbation noise is zero mean Gaussian distribution, however, this requirement can't be satisfied if the perturbed variables in land surface model have physical boundaries because part of the perturbation noises has to be removed to feed the land surface models properly. Two different perturbation methods are employed in our study to investigate their impact on quantifying land surface modeling uncertainty base on the Land Information System (LIS) framework developed by NASA/GSFC land team. One perturbation method is the built-in algorithm named "STATIC" in LIS version 5; the other is a new perturbation algorithm which was recently developed to minimize the overall bias in the perturbation by incorporating additional information from the whole time series for the perturbed variable. The statistical properties of the perturbation noise generated by the two different algorithms are investigated thoroughly by using a large ensemble size on a NASA supercomputer and then the corresponding uncertainty estimates based on the two perturbation methods are compared. Their further impacts on data assimilation are also discussed. Finally, an optimal perturbation method is suggested.

Documentation of programs used to determine a wetlands hydroperiod from model-simulated water-surface elevations

USGS Publications Warehouse

Sonenshein, R.S.

1996-01-01

A technique has been developed to determine a wetlands hydroperiod by comparing simulated water levels from a ground-water flow model and land- surface elevation data through a geographic information system. The simulated water levels are compared with the land-surface elevation data to determine the height of the water surface above or below land surface for the area of interest. Finally, the hydroperiod is determined for established time periods using criteria specified by the user. The program application requires the use of geographic information system software (ARC/INFO), including the TIN and GRID subsystems of the software. The application consists of an ANSI compatible C program to translate ground- water data output from the U.S. Geological Survey modular three-dimensional, finite-difference, ground-water flow model (MODFLOW) into a format that can be used as input for the geographic information system programs (AML's). The application uses ARC/INFO AML programs and ARC/INFO menu interface programs to create digital spatial data layers of the land surface and water surface and to determine the hydroperiod. The technique can be used to evaluate and manage wetlands hydrology.

Retrieval of land parameters by multi-sensor information using the Earth Observation Land Data Assimilation System

NASA Astrophysics Data System (ADS)

Chernetskiy, Maxim; Gobron, Nadine; Gomez-Dans, Jose; Disney, Mathias

2016-07-01

Upcoming satellite constellations will substantially increase the amount of Earth Observation (EO) data, and presents us with the challenge of consistently using all these available information to infer the state of the land surface, parameterised through Essential Climate Variables (ECVs). A promising approach to this problem is the use of physically based models that describe the processes that generate the images, using e.g. radiative transfer (RT) theory. However, these models need to be inverted to infer the land surface parameters from the observations, and there is often not enough information in the EO data to satisfactorily achieve this. Data assimilation (DA) approaches supplement the EO data with prior information in the form of models or prior parameter distributions, and have the potential for solving the inversion problem. These methods however are computationally expensive. In this study, we show the use of fast surrogate models of the RT codes (emulators) based on Gaussian Processes (Gomez-Dans et al, 2016) embedded with the Earth Observation Land Data Assimilation System (EO-LDAS) framework (Lewis et al 2012) in order to estimate the surface of the land surface from a heterogeneous set of optical observations. The study uses time series of moderate spatial resolution observations from MODIS (250 m), MERIS (300 m) and MISR (275 m) over one site to infer the temporal evolution of a number of land surface parameters (and associated uncertainties) related to vegetation: leaf area index (LAI), leaf chlorophyll content, etc. These parameter estimates are then used as input to an RT model (semidiscrete or PROSAIL, for example) to calculate fluxes such as broad band albedo or fAPAR. The study demonstrates that blending different sensors in a consistent way using physical models results in a rich and coherent set of land surface parameters retrieved, with quantified uncertainties. The use of RT models also allows for the consistent prediction of fluxes, with a simple mechanism for propagating the uncertainty in the land surface parameters to the flux estimates.

Impact of High Resolution Land-Use Data in Meteorology and Air Quality Modeling Systems

EPA Science Inventory

Accurate land use information is important in meteorology for land surface exchanges, in emission modeling for emission spatial allocation, and in air quality modeling for chemical surface fluxes. Currently, meteorology, emission, and air quality models often use outdated USGS Gl...

Validation and Verification of Operational Land Analysis Activities at the Air Force Weather Agency

NASA Technical Reports Server (NTRS)

Shaw, Michael; Kumar, Sujay V.; Peters-Lidard, Christa D.; Cetola, Jeffrey

2011-01-01

The NASA developed Land Information System (LIS) is the Air Force Weather Agency's (AFWA) operational Land Data Assimilation System (LDAS) combining real time precipitation observations and analyses, global forecast model data, vegetation, terrain, and soil parameters with the community Noah land surface model, along with other hydrology module options, to generate profile analyses of global soil moisture, soil temperature, and other important land surface characteristics. (1) A range of satellite data products and surface observations used to generate the land analysis products (2) Global, 1/4 deg spatial resolution (3) Model analysis generated at 3 hours

Optimization of Modeled Land-Atmosphere Exchanges of Water and Energy in an Isotopically-Enabled Land Surface Model by Bayesian Parameter Calibration

NASA Astrophysics Data System (ADS)

Wong, T. E.; Noone, D. C.; Kleiber, W.

2014-12-01

The single largest uncertainty in climate model energy balance is the surface latent heating over tropical land. Furthermore, the partitioning of the total latent heat flux into contributions from surface evaporation and plant transpiration is of great importance, but notoriously poorly constrained. Resolving these issues will require better exploiting information which lies at the interface between observations and advanced modeling tools, both of which are imperfect. There are remarkably few observations which can constrain these fluxes, placing strict requirements on developing statistical methods to maximize the use of limited information to best improve models. Previous work has demonstrated the power of incorporating stable water isotopes into land surface models for further constraining ecosystem processes. We present results from a stable water isotopically-enabled land surface model (iCLM4), including model experiments partitioning the latent heat flux into contributions from plant transpiration and surface evaporation. It is shown that the partitioning results are sensitive to the parameterization of kinetic fractionation used. We discuss and demonstrate an approach to calibrating select model parameters to observational data in a Bayesian estimation framework, requiring Markov Chain Monte Carlo sampling of the posterior distribution, which is shown to constrain uncertain parameters as well as inform relevant values for operational use. Finally, we discuss the application of the estimation scheme to iCLM4, including entropy as a measure of information content and specific challenges which arise in calibration models with a large number of parameters.

Towards the Consideration of Surface and Environment variables for a Microwave Precipitation Algorithm Over Land

NASA Astrophysics Data System (ADS)

Wang, N. Y.; You, Y.; Ferraro, R. R.; Guch, I.

2014-12-01

Microwave satellite remote sensing of precipitation over land is a challenging problem due to the highly variable land surface emissivity, which, if not properly accounted for, can be much greater than the precipitation signal itself, especially in light rain/snow conditions. Additionally, surfaces such as arid land, deserts and snow cover have brightness temperatures characteristics similar to precipitation Ongoing work by NASA's GPM microwave radiometer team is constructing databases for the GPROF algorithm through a variety of means, however, there is much uncertainty as to what is the optimal information needed for the wide array of sensors in the GPM constellation, including examination of regional conditions. The at-launch database focuses on stratification by emissivity class, surface temperature and total precipitable water (TPW). We'll perform sensitivity studies to determine the potential role of environmental factors such as land surface temperature, surface elevation, and relative humidity and storm morphology such as storm vertical structure, height, and ice thickness to improve precipitation estimation over land, including rain and snow. In other words, what information outside of the satellite radiances can help describe the background and subsequent departures from it that are active precipitating regions? It is likely that this information will be a function of the various precipitation regimes. Statistical methods such as Principal Component Analysis (PCA) will be utilized in this task. Databases from a variety of sources are being constructed. They include existing satellite microwave measurements of precipitating and non-precipitating conditions, ground radar precipitation rate estimates, surface emissivity climatology from satellites, surface temperature and TPW from NWP reanalysis. Results from the analysis of these databases with respect to the microwave precipitation sensitivity to the variety of environmental conditions in different climate regimes will be discussed.

High Performance Hydrometeorological Modeling, Land Data Assimilation and Parameter Estimation with the Land Information System at NASA/GSFC

NASA Astrophysics Data System (ADS)

Peters-Lidard, C. D.; Kumar, S. V.; Santanello, J. A.; Tian, Y.; Rodell, M.; Mocko, D.; Reichle, R.

2008-12-01

The Land Information System (LIS; http://lis.gsfc.nasa.gov; Kumar et al., 2006; Peters-Lidard et al., 2007) is a flexible land surface modeling framework that has been developed with the goal of integrating satellite- and ground-based observational data products and advanced land surface modeling techniques to produce optimal fields of land surface states and fluxes. The LIS software was the co-winner of NASA's 2005 Software of the Year award. LIS facilitates the integration of observations from Earth-observing systems and predictions and forecasts from Earth System and Earth science models into the decision-making processes of partnering agency and national organizations. Due to its flexible software design, LIS can serve both as a Problem Solving Environment (PSE) for hydrologic research to enable accurate global water and energy cycle predictions, and as a Decision Support System (DSS) to generate useful information for application areas including disaster management, water resources management, agricultural management, numerical weather prediction, air quality and military mobility assessment. LIS has evolved from two earlier efforts - North American Land Data Assimilation System (NLDAS; Mitchell et al. 2004) and Global Land Data Assimilation System (GLDAS; Rodell et al. 2004) that focused primarily on improving numerical weather prediction skills by improving the characterization of the land surface conditions. Both of these systems, now use specific configurations of the LIS software in their current implementations. LIS not only consolidates the capabilities of these two systems, but also enables a much larger variety of configurations with respect to horizontal spatial resolution, input datasets and choice of land surface model through 'plugins'. In addition to these capabilities, LIS has also been demonstrated for parameter estimation (Peters-Lidard et al., 2008; Santanello et al., 2007) and data assimilation (Kumar et al., 2008). Examples and case studies demonstrating the capabilities and impacts of LIS for hydrometeorological modeling, land data assimilation and parameter estimation will be presented.

Land Data Assimilation of Satellite-Based Soil Moisture Products Using the Land Information System Over the NLDAS Domain

NASA Technical Reports Server (NTRS)

Mocko, David M.; Kumar, S. V.; Peters-Lidard, C. D.; Tian, Y.

2011-01-01

This presentation will include results from data assimilation simulations using the NASA-developed Land Information System (LIS). Using the ensemble Kalman filter in LIS, two satellite-based soil moisture products from the AMSR-E instrument were assimilated, one a NASA-based product and the other from the Land Parameter Retrieval Model (LPRM). The domain and land-surface forcing data from these simulations were from the North American Land Data Assimilation System Phase-2, over the period 2002-2008. The Noah land-surface model, version 3.2, was used during the simulations. Changes to estimates of land surface states, such as soil moisture, as well as changes to simulated runoff/streamflow will be presented. Comparisons over the NLDAS domain will also be made to two global reference evapotranspiration (ET) products, one an interpolated product based on FLUXNET tower data and the other a satellite- based algorithm from the MODIS instrument. Results of an improvement metric show that assimilating the LPRM product improved simulated ET estimates while the NASA-based soil moisture product did not.

Land Surface Verification Toolkit (LVT) - A Generalized Framework for Land Surface Model Evaluation

NASA Technical Reports Server (NTRS)

Kumar, Sujay V.; Peters-Lidard, Christa D.; Santanello, Joseph; Harrison, Ken; Liu, Yuqiong; Shaw, Michael

2011-01-01

Model evaluation and verification are key in improving the usage and applicability of simulation models for real-world applications. In this article, the development and capabilities of a formal system for land surface model evaluation called the Land surface Verification Toolkit (LVT) is described. LVT is designed to provide an integrated environment for systematic land model evaluation and facilitates a range of verification approaches and analysis capabilities. LVT operates across multiple temporal and spatial scales and employs a large suite of in-situ, remotely sensed and other model and reanalysis datasets in their native formats. In addition to the traditional accuracy-based measures, LVT also includes uncertainty and ensemble diagnostics, information theory measures, spatial similarity metrics and scale decomposition techniques that provide novel ways for performing diagnostic model evaluations. Though LVT was originally designed to support the land surface modeling and data assimilation framework known as the Land Information System (LIS), it also supports hydrological data products from other, non-LIS environments. In addition, the analysis of diagnostics from various computational subsystems of LIS including data assimilation, optimization and uncertainty estimation are supported within LVT. Together, LIS and LVT provide a robust end-to-end environment for enabling the concepts of model data fusion for hydrological applications. The evolving capabilities of LVT framework are expected to facilitate rapid model evaluation efforts and aid the definition and refinement of formal evaluation procedures for the land surface modeling community.

Numerical evaluation of surface modifications at landing site due to spacecraft (soft) landing on the moon

NASA Astrophysics Data System (ADS)

Mishra, Sanjeev Kumar; Prasad, K. Durga

2018-07-01

Understanding surface modifications at landing site during spacecraft landing on planetary surfaces is important for planetary missions from scientific as well as engineering perspectives. An attempt has been made in this work to numerically investigate the disturbance caused to the lunar surface during soft landing. The variability of eject velocity of dust, eject mass flux rate, ejecta amount etc. has been studied. The effect of lander hovering time and hovering altitude on the extent of disturbance is also evaluated. The study thus carried out will help us in understanding the surface modifications during landing thereby making it easier to plan a descent trajectory that minimizes the extent of disturbance. The information about the extent of damage will also be helpful in interpreting the data obtained from experiments carried on the lunar surface in vicinity of the lander.

Internal Physical Features of a Land Surface Model Employing a Tangent Linear Model

NASA Technical Reports Server (NTRS)

Yang, Runhua; Cohn, Stephen E.; daSilva, Arlindo; Joiner, Joanna; Houser, Paul R.

1997-01-01

The Earth's land surface, including its biomass, is an integral part of the Earth's weather and climate system. Land surface heterogeneity, such as the type and amount of vegetative covering., has a profound effect on local weather variability and therefore on regional variations of the global climate. Surface conditions affect local weather and climate through a number of mechanisms. First, they determine the re-distribution of the net radiative energy received at the surface, through the atmosphere, from the sun. A certain fraction of this energy increases the surface ground temperature, another warms the near-surface atmosphere, and the rest evaporates surface water, which in turn creates clouds and causes precipitation. Second, they determine how much rainfall and snowmelt can be stored in the soil and how much instead runs off into waterways. Finally, surface conditions influence the near-surface concentration and distribution of greenhouse gases such as carbon dioxide. The processes through which these mechanisms interact with the atmosphere can be modeled mathematically, to within some degree of uncertainty, on the basis of underlying physical principles. Such a land surface model provides predictive capability for surface variables including ground temperature, surface humidity, and soil moisture and temperature. This information is important for agriculture and industry, as well as for addressing fundamental scientific questions concerning global and local climate change. In this study we apply a methodology known as tangent linear modeling to help us understand more deeply, the behavior of the Mosaic land surface model, a model that has been developed over the past several years at NASA/GSFC. This methodology allows us to examine, directly and quantitatively, the dependence of prediction errors in land surface variables upon different vegetation conditions. The work also highlights the importance of accurate soil moisture information. Although surface variables are predicted imperfectly due to inherent uncertainties in the modeling process, our study suggests how satellite observations can be combined with the model, through land surface data assimilation, to improve their prediction.

Land, Ocean and Ice sheet surface elevation retrieval from CALIPSO lidar measurements

NASA Astrophysics Data System (ADS)

Lu, X.; Hu, Y.

2013-12-01

Since launching in April 2006 the main objective of the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) mission has been studying the climate impact of clouds and aerosols in the atmosphere. However, CALIPSO also collects information about other components of the Earth's ecosystem, such as lands, oceans and polar ice sheets. The objective of this study is to propose a Super-Resolution Altimetry (SRA) technique to provide high resolution of land, ocean and polar ice sheet surface elevation from CALIPSO single shot lidar measurements (70 m spot size). The land surface results by the new technique agree with the United States Geological Survey (USGS) National Elevation Database (NED) high-resolution elevation maps, and the ice sheet surface results in the region of Greenland and Antarctic compare very well with the Ice, Cloud and land Elevation Satellite (ICESat) laser altimetry measurements. The comparisons suggest that the obtained CALIPSO surface elevation information by the new technique is accurate to within 1 m. The effects of error sources on the retrieved surface elevation are discussed. Based on the new technique, the preliminary data products of along-track topography retrieved from the CALIPSO lidar measurements is available to the altimetry community for evaluation.

High Resolution Land Surface Modeling with the next generation Land Data Assimilation Systems

NASA Astrophysics Data System (ADS)

Kumar, S. V.; Eylander, J.; Peters-Lidard, C.

2005-12-01

Knowledge of land surface processes is important to many real-world applications such as agricultural production, water resources management, and flood predication. The Air Force Weather Agency (AFWA) has provided the USDA and other customers global soil moisture and temperature data for the past 30 years using the agrometeorological data assimilation model (now called AGRMET), merging atmospheric data. Further, accurate initialization of land surface conditions has been shown to greatly influence and improve weather forecast model and seasonal-to-interannual climate predictions. The AFWA AGRMET model exploits real time precipitation observations and analyses, global forecast model and satellite data to generate global estimates of soil moisture, soil temperature and other land surface states at 48km spatial resolution. However, to truly address the land surface initialization and climate prediction problem, and to mitigate the errors introduced by the differences in spatial scales of models, representations of land surface conditions need to be developed at the same fine scales such as that of cloud resolving models. NASA's Goddard Space Flight Center has developed an offline land data assimilation system known as the Land Information System (LIS) capable of modeling land atmosphere interactions at spatial resolutions as fine as 1km. LIS provides a software architecture that integrates the use of the state of the art land surface models, data assimilation techniques, and high performance computing and data management tools. LIS also employs many high resolution surface parameters such as the NASA Earth Observing System (EOS)-era products. In this study we describe the development of a next generation high resolution land surface modeling and data assimilation system, combining the capabilities of LIS and AGRMET. We investigate the influence of high resolution land surface data and observations on the land surface conditions by comparing with the operational AGRMET outputs.

Advances in Land Data Assimilation at the NASA Goddard Space Flight Center

NASA Technical Reports Server (NTRS)

Reichle, Rolf

2009-01-01

Research in land surface data assimilation has grown rapidly over the last decade. In this presentation we provide a brief overview of key research contributions by the NASA Goddard Space Flight Center (GSFC). The GSFC contributions to land assimilation primarily include the continued development and application of the Land Information System (US) and the ensemble Kalman filter (EnKF). In particular, we have developed a method to generate perturbation fields that are correlated in space, time, and across variables and that permit the flexible modeling of errors in land surface models and observations, along with an adaptive filtering approach that estimates observation and model error input parameters. A percentile-based scaling method that addresses soil moisture biases in model and observational estimates opened the path to the successful application of land data assimilation to satellite retrievals of surface soil moisture. Assimilation of AMSR-E surface soil moisture retrievals into the NASA Catchment model provided superior surface and root zone assimilation products (when validated against in situ measurements and compared to the model estimates or satellite observations alone). The multi-model capabilities of US were used to investigate the role of subsurface physics in the assimilation of surface soil moisture observations. Results indicate that the potential of surface soil moisture assimilation to improve root zone information is higher when the surface to root zone coupling is stronger. Building on this experience, GSFC leads the development of the Level 4 Surface and Root-Zone Soil Moisture (L4_SM) product for the planned NASA Soil-Moisture-Active-Passive (SMAP) mission. A key milestone was the design and execution of an Observing System Simulation Experiment that quantified the contribution of soil moisture retrievals to land data assimilation products as a function of retrieval and land model skill and yielded an estimate of the error budget for the SMAP L4_SM product. Terrestrial water storage observations from GRACE satellite system were also successfully assimilated into the NASA Catchment model and provided improved estimates of groundwater variability when compared to the model estimates alone. Moreover, satellite-based land surface temperature (LST) observations from the ISCCP archive were assimilated using a bias estimation module that was specifically designed for LST assimilation. As with soil moisture, LST assimilation provides modest yet statistically significant improvements when compared to the model or satellite observations alone. To achieve the improvement, however, the LST assimilation algorithm must be adapted to the specific formulation of LST in the land model. An improved method for the assimilation of snow cover observations was also developed. Finally, the coupling of LIS to the mesoscale Weather Research and Forecasting (WRF) model enabled investigations into how the sensitivity of land-atmosphere interactions to the specific choice of planetary boundary layer scheme and land surface model varies across surface moisture regimes, and how it can be quantified and evaluated against observations. The on-going development and integration of land assimilation modules into the Land Information System will enable the use of GSFC software with a variety of land models and make it accessible to the research community.

Global Land Information System (GLIS)

USGS Publications Warehouse

,

1992-01-01

The Global Land Information System (GLIS) is an interactive computer system developed by the U.S. Geological Survey (USGS) for scientists seeking sources of information about the Earth's land surfaces. GLIS contains "metadata," that is, descriptive information about data sets. Through GLIS, scientists can evaluate data sets, determine their availability, and place online requests for products. GLIS is more, however, than a mere list of products. It offers online samples of earth science data that may be ordered through the system.

Application of Intel Many Integrated Core (MIC) accelerators to the Pleim-Xiu land surface scheme

NASA Astrophysics Data System (ADS)

Huang, Melin; Huang, Bormin; Huang, Allen H.

2015-10-01

The land-surface model (LSM) is one physics process in the weather research and forecast (WRF) model. The LSM includes atmospheric information from the surface layer scheme, radiative forcing from the radiation scheme, and precipitation forcing from the microphysics and convective schemes, together with internal information on the land's state variables and land-surface properties. The LSM is to provide heat and moisture fluxes over land points and sea-ice points. The Pleim-Xiu (PX) scheme is one LSM. The PX LSM features three pathways for moisture fluxes: evapotranspiration, soil evaporation, and evaporation from wet canopies. To accelerate the computation process of this scheme, we employ Intel Xeon Phi Many Integrated Core (MIC) Architecture as it is a multiprocessor computer structure with merits of efficient parallelization and vectorization essentials. Our results show that the MIC-based optimization of this scheme running on Xeon Phi coprocessor 7120P improves the performance by 2.3x and 11.7x as compared to the original code respectively running on one CPU socket (eight cores) and on one CPU core with Intel Xeon E5-2670.

Some environmental problems and their satellite monitoring. [anthropogenic modifications of earth surface

NASA Technical Reports Server (NTRS)

Otterman, J.

1975-01-01

Anthropogenic modification of the earth's surface is discussed in two problem areas: (1) land use changes and overgrazing, and how it affects albedo and land surface-atmosphere interactions, and (2) water and land surface pollution, especially oil slicks. A literature survey evidences the importance of these problems. The need for monitoring is stressed, and it is suggested that with some modifications to the sensors, ERTS (Landsat) series satellites can provide approximate monitoring information. The European Landsat receiving station in Italy will facilitate data collection for the tasks described.

Historical Landsat data comparisons: illustrations of land surface change

USGS Publications Warehouse

Cross, Matthew D.

1990-01-01

This booklet provides an overview of the Landsat program and shows the application of the data to monitor changes occurring on the surface of the Earth. To show changes that have taken place within the last 20 years or less, image pairs were constructed from the Landsat multispectral scanner (MSS) and thematic mapper (TM) sensors. Landsat MSS data provide a historical global record of the land surface from the early 1970's to present. Landsat TM data provide land surface information from the early 1980's to present.

Estimating the extent of impervious surfaces and turf grass across large regions

USGS Publications Warehouse

Claggett, Peter; Irani, Frederick M.; Thompson, Renee L.

2013-01-01

The ability of researchers to accurately assess the extent of impervious and pervious developed surfaces, e.g., turf grass, using land-cover data derived from Landsat satellite imagery in the Chesapeake Bay watershed is limited due to the resolution of the data and systematic discrepancies between developed land-cover classes, surface mines, forests, and farmlands. Estimates of impervious surface and turf grass area in the Mid-Atlantic, United States that were based on 2006 Landsat-derived land-cover data were substantially lower than estimates based on more authoritative and independent sources. New estimates of impervious surfaces and turf grass area derived using land-cover data combined with ancillary information on roads, housing units, surface mines, and sampled estimates of road width and residential impervious area were up to 57 and 45% higher than estimates based strictly on land-cover data. These new estimates closely approximate estimates derived from authoritative and independent sources in developed counties.

Impact of Land Model Calibration on Coupled Land-Atmosphere Prediction

NASA Technical Reports Server (NTRS)

Santanello, Joseph A., Jr.; Kumar, Sujay V.; Peters-Lidard, Christa D.; Harrison, Ken; Zhou, Shujia

2012-01-01

Land-atmosphere (L-A) interactions play a critical role in determining the diurnal evolution of both planetary boundary layer (PBL) and land surface heat and moisture budgets, as well as controlling feedbacks with clouds and precipitation that lead to the persistence of dry and wet regimes. Recent efforts to quantify the strength of L-A coupling in prediction models have produced diagnostics that integrate across both the land and PBL components of the system. In this study, we examine the impact of improved specification of land surface states, anomalies, and fluxes on coupled WRF forecasts during the summers of extreme dry and wet land surface conditions in the U.S. Southern Great Plains. The improved land initialization and surface flux parameterizations are obtained through calibration of the Noah land surface model using the new optimization and uncertainty estimation subsystem in NASA's Land Information System (LIS-OPT/UE). The impact of the calibration on the a) spinup of the land surface used as initial conditions, and b) the simulated heat and moisture states and fluxes of the coupled WRF simulations is then assessed. Changes in ambient weather and land-atmosphere coupling are evaluated along with measures of uncertainty propagation into the forecasts. In addition, the sensitivity of this approach to the period of calibration (dry, wet, average) is investigated. Results indicate that the offline calibration leads to systematic improvements in land-PBL fluxes and near-surface temperature and humidity, and in the process provide guidance on the questions of what, how, and when to calibrate land surface models for coupled model prediction.

Historical Landsat data comparisons: illustrations of the Earth's changing surface

USGS Publications Warehouse

,

1995-01-01

The U.S. Geological Survey's (USGS) EROS Data Center (EDC) has managed the Landsat data archive for more than two decades. This archive provides a rich collection of information about the Earth's land surface. Major changes to the surface of the planet can be detected, measured, and analyzed using Landsat data. The effects of desertification, deforestation, pollution, cataclysmic volcanic activity, and other natural and anthropogenic events can be examined using data acquired from the Landsat series of Earth-observing satellites. The information obtainable from the historical and current Landsat data play a key role in studying surface changes through time. This document provides an overview of the Landsat program and illustrates the application of the data to monitor changes occurring on the surface of the Earth. To reveal changes that have taken place within the past 20 years, pairs and triplicates of images were constructed from the Landsat multispectral scanner (MSS) and thematic mapper (TM) sensors. Landsat MSS data provide a historical record of the Earth's land surface from the early 1970's to the early 1990's. Landsat TM data provide land surface information from the early 1980's to the present.

Validation and Verification of Operational Land Analysis Activities at the Air Force Weather Agency

NASA Technical Reports Server (NTRS)

Shaw, Michael; Kumar, Sujay V.; Peters-Lidard, Christa D.; Cetola, Jeffrey

2012-01-01

The NASA developed Land Information System (LIS) is the Air Force Weather Agency's (AFWA) operational Land Data Assimilation System (LDAS) combining real time precipitation observations and analyses, global forecast model data, vegetation, terrain, and soil parameters with the community Noah land surface model, along with other hydrology module options, to generate profile analyses of global soil moisture, soil temperature, and other important land surface characteristics. (1) A range of satellite data products and surface observations used to generate the land analysis products (2) Global, 1/4 deg spatial resolution (3) Model analysis generated at 3 hours. AFWA recognizes the importance of operational benchmarking and uncertainty characterization for land surface modeling and is developing standard methods, software, and metrics to verify and/or validate LIS output products. To facilitate this and other needs for land analysis activities at AFWA, the Model Evaluation Toolkit (MET) -- a joint product of the National Center for Atmospheric Research Developmental Testbed Center (NCAR DTC), AFWA, and the user community -- and the Land surface Verification Toolkit (LVT), developed at the Goddard Space Flight Center (GSFC), have been adapted to operational benchmarking needs of AFWA's land characterization activities.

Expansion of the Real-Time SPoRT-Land Information System for NOAA/National Weather Service Situational Awareness and Local Modeling Applications

NASA Technical Reports Server (NTRS)

Case, Jonathan L; White, Kristopher D.

2014-01-01

The NASA Short-term Prediction Research and Transition (SPoRT) Center in Huntsville, AL is running a real-time configuration of the Noah land surface model (LSM) within the NASA Land Information System (LIS) framework (hereafter referred to as the "SPoRT-LIS"). Output from the real-time SPoRT-LIS is used for (1) initializing land surface variables for local modeling applications, and (2) displaying in decision support systems for situational awareness and drought monitoring at select NOAA/National Weather Service (NWS) partner offices. The experimental CONUS run incorporates hourly quantitative precipitation estimation (QPE) from the National Severe Storms Laboratory Multi- Radar Multi-Sensor (MRMS) which will be transitioned into operations at the National Centers for Environmental Prediction (NCEP) in Fall 2014.This paper describes the current and experimental SPoRT-LIS configurations, and documents some of the limitations still remaining through the advent of MRMS precipitation analyses in the SPoRT-LIS land surface model (LSM) simulations.

Global Precipitation Measurement, Validation, and Applications Integrated Hydrologic Validation to Improve Physical Precipitation Retrievals for GPM

NASA Technical Reports Server (NTRS)

Peters-Lidar, Christa D.; Tian, Yudong; Kenneth, Tian; Harrison, Kenneth; Kumar, Sujay

2011-01-01

Land surface modeling and data assimilation can provide dynamic land surface state variables necessary to support physical precipitation retrieval algorithms over land. It is well-known that surface emission, particularly over the range of frequencies to be included in the Global Precipitation Measurement Mission (GPM), is sensitive to land surface states, including soil properties, vegetation type and greenness, soil moisture, surface temperature, and snow cover, density, and grain size. In order to investigate the robustness of both the land surface model states and the microwave emissivity and forward radiative transfer models, we have undertaken a multi-site investigation as part of the NASA Precipitation Measurement Missions (PMM) Land Surface Characterization Working Group. Specifically, we will demonstrate the performance of the Land Information System (LIS; http://lis.gsfc.nasa.gov; Peters-Lidard et aI., 2007; Kumar et al., 2006) coupled to the Joint Center for Satellite Data Assimilation (JCSDA's) Community Radiative Transfer Model (CRTM; Weng, 2007; van Deist, 2009). The land surface is characterized by complex physical/chemical constituents and creates temporally and spatially heterogeneous surface properties in response to microwave radiation scattering. The uncertainties in surface microwave emission (both surface radiative temperature and emissivity) and very low polarization ratio are linked to difficulties in rainfall detection using low-frequency passive microwave sensors (e.g.,Kummerow et al. 2001). Therefore, addressing these issues is of utmost importance for the GPM mission. There are many approaches to parameterizing land surface emission and radiative transfer, some of which have been customized for snow (e.g., the Helsinki University of Technology or HUT radiative transfer model;) and soil moisture (e.g., the Land Surface Microwave Emission Model or LSMEM).

Analysis of Summertime Convective Initiation in Central Alabama Using the Land Information System

NASA Technical Reports Server (NTRS)

James, Robert S.; Case, Jonathan L.; Molthan, Andrew L.; Jedlovec, Gary J.

2011-01-01

During the summer months in the southeastern United States, convective initiation presents a frequent challenge to operational forecasters. Thunderstorm development has traditionally been referred to as random due to their disorganized, sporadic appearance and lack of atmospheric forcing. Horizontal variations in land surface characteristics such as soil moisture, soil type, land and vegetation cover could possibly be a focus mechanism for afternoon convection during the summer months. The NASA Land Information System (LIS) provides a stand-alone land surface modeling framework that incorporates these varying soil and vegetation properties, antecedent precipitation, and atmospheric forcing to represent the soil state at high resolution. The use of LIS as a diagnostic tool may help forecasters to identify boundaries in land surface characteristics that could correlate to favored regions of convection initiation. The NASA Shortterm Prediction Research and Transition (SPoRT) team has been collaborating with the National Weather Service Office in Birmingham, AL to help incorporate LIS products into their operational forecasting methods. This paper highlights selected convective case dates from summer 2009 when synoptic forcing was weak, and identifies any boundaries in land surface characteristics that may have contributed to convective initiation. The LIS output depicts the effects of increased sensible heat flux from urban areas on the development of convection, as well as convection along gradients in land surface characteristics and surface sensible and latent heat fluxes. These features may promote mesoscale circulations and/or feedback processes that can either enhance or inhibit convection. With this output previously unavailable to operational forecasters, LIS provides a new tool to forecasters in order to help eliminate the randomness of summertime convective initiation.

Understanding Mesoscale Land-Atmosphere Interactions in Arctic Region

NASA Astrophysics Data System (ADS)

Hong, X.; Wang, S.; Nachamkin, J. E.

2017-12-01

Land-atmosphere interactions in Arctic region are examined using the U.S. Navy Coupled Ocean/Atmosphere Mesoscale Prediction System (COAMPS©*) with the Noah Land Surface Model (LSM). Initial land surface variables in COAMPS are interpolated from the real-time NASA Land Information System (LIS). The model simulations are configured for three nest grids with 27-9-3 km horizontal resolutions. The simulation period is set for October 2015 with 12-h data assimilation update cycle and 24-h integration length. The results are compared with those simulated without using LSM and evaluated with observations from ONR Sea State R/V Sikuliaq cruise and the North Slope of Alaska (NSA). There are complex soil and vegetation types over the surface for simulation with LSM, compared to without LSM simulation. The results show substantial differences in surface heat fluxes between bulk surface scheme and LSM, which may have an important impact on the sea ice evolution over the Arctic region. Evaluations from station data show surface air temperature and relative humidity have smaller biases for simulation using LSM. Diurnal variation of land surface temperature, which is necessary for physical processes of land-atmosphere, is also better captured than without LSM.

The NASA-Goddard Multi-Scale Modeling Framework - Land Information System: Global Land/atmosphere Interaction with Resolved Convection

NASA Technical Reports Server (NTRS)

Mohr, Karen Irene; Tao, Wei-Kuo; Chern, Jiun-Dar; Kumar, Sujay V.; Peters-Lidard, Christa D.

2013-01-01

The present generation of general circulation models (GCM) use parameterized cumulus schemes and run at hydrostatic grid resolutions. To improve the representation of cloud-scale moist processes and landeatmosphere interactions, a global, Multi-scale Modeling Framework (MMF) coupled to the Land Information System (LIS) has been developed at NASA-Goddard Space Flight Center. The MMFeLIS has three components, a finite-volume (fv) GCM (Goddard Earth Observing System Ver. 4, GEOS-4), a 2D cloud-resolving model (Goddard Cumulus Ensemble, GCE), and the LIS, representing the large-scale atmospheric circulation, cloud processes, and land surface processes, respectively. The non-hydrostatic GCE model replaces the single-column cumulus parameterization of fvGCM. The model grid is composed of an array of fvGCM gridcells each with a series of embedded GCE models. A horizontal coupling strategy, GCE4fvGCM4Coupler4LIS, offered significant computational efficiency, with the scalability and I/O capabilities of LIS permitting landeatmosphere interactions at cloud-scale. Global simulations of 2007e2008 and comparisons to observations and reanalysis products were conducted. Using two different versions of the same land surface model but the same initial conditions, divergence in regional, synoptic-scale surface pressure patterns emerged within two weeks. The sensitivity of largescale circulations to land surface model physics revealed significant functional value to using a scalable, multi-model land surface modeling system in global weather and climate prediction.

30 CFR 745.10 - Information collection.

Code of Federal Regulations, 2013 CFR

2013-07-01

... Mineral Resources OFFICE OF SURFACE MINING RECLAMATION AND ENFORCEMENT, DEPARTMENT OF THE INTERIOR FEDERAL LANDS PROGRAM STATE-FEDERAL COOPERATIVE AGREEMENTS § 745.10 Information collection. (a) In accordance... Federal lands under certain conditions. States that desire to enter into cooperative agreements to do so...

30 CFR 745.10 - Information collection.

Code of Federal Regulations, 2010 CFR

2010-07-01

... Mineral Resources OFFICE OF SURFACE MINING RECLAMATION AND ENFORCEMENT, DEPARTMENT OF THE INTERIOR FEDERAL LANDS PROGRAM STATE-FEDERAL COOPERATIVE AGREEMENTS § 745.10 Information collection. (a) In accordance... Federal lands under certain conditions. States that desire to enter into cooperative agreements to do so...

75 FR 65625 - Agency Information Collection Activities; Proposed Collection; Comment Request; Hazardous Waste...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-10-26

... ICR are: Tank systems, Surface impoundments, Waste piles, Land treatment, Landfills, Incinerators..., Process vents, Equipment leaks, Containment buildings, Recovery/recycling. With each information...: Waste Piles 17 Subpart M: Land Treatment 0 Subpart N: Landfills 37 [[Page 65627

In Situ SIMS and IR Spectroscopy of Well-defined Surfaces Prepared by Soft Landing of Mass-selected Ions

PubMed Central

Johnson, Grant E.; Gunaratne, K. Don Dasitha; Laskin, Julia

2014-01-01

Soft landing of mass-selected ions onto surfaces is a powerful approach for the highly-controlled preparation of materials that are inaccessible using conventional synthesis techniques. Coupling soft landing with in situ characterization using secondary ion mass spectrometry (SIMS) and infrared reflection absorption spectroscopy (IRRAS) enables analysis of well-defined surfaces under clean vacuum conditions. The capabilities of three soft-landing instruments constructed in our laboratory are illustrated for the representative system of surface-bound organometallics prepared by soft landing of mass-selected ruthenium tris(bipyridine) dications, [Ru(bpy)3]2+ (bpy = bipyridine), onto carboxylic acid terminated self-assembled monolayer surfaces on gold (COOH-SAMs). In situ time-of-flight (TOF)-SIMS provides insight into the reactivity of the soft-landed ions. In addition, the kinetics of charge reduction, neutralization and desorption occurring on the COOH-SAM both during and after ion soft landing are studied using in situ Fourier transform ion cyclotron resonance (FT-ICR)-SIMS measurements. In situ IRRAS experiments provide insight into how the structure of organic ligands surrounding metal centers is perturbed through immobilization of organometallic ions on COOH-SAM surfaces by soft landing. Collectively, the three instruments provide complementary information about the chemical composition, reactivity and structure of well-defined species supported on surfaces. PMID:24961913

In Situ SIMS and IR Spectroscopy of Well-Defined Surfaces Prepared by Soft Landing of Mass-Selected Ions

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

Johnson, Grant E.; Gunaratne, Kalupathirannehelage Don D.; Laskin, Julia

2014-06-16

Soft landing of mass-selected ions onto surfaces is a powerful approach for the highly-controlled preparation of materials that are inaccessible using conventional synthesis techniques. Coupling soft landing with in situ characterization using secondary ion mass spectrometry (SIMS) and infrared reflection absorption spectroscopy (IRRAS) enables analysis of well-defined surfaces under clean vacuum conditions. The capabilities of three soft-landing instruments constructed in our laboratory are illustrated for the representative system of surface-bound organometallics prepared by soft landing of mass-selected ruthenium tris(bipyridine) dications, [Ru(bpy)3]2+, onto carboxylic acid terminated self-assembled monolayer surfaces on gold (COOH-SAMs). In situ time-of-flight (TOF)-SIMS provides insight into the reactivitymore » of the soft-landed ions. In addition, the kinetics of charge reduction, neutralization and desorption occurring on the COOH-SAM both during and after ion soft landing are studied using in situ Fourier transform ion cyclotron resonance (FT-ICR)-SIMS measurements. In situ IRRAS experiments provide insight into how the structure of organic ligands surrounding metal centers is perturbed through immobilization of organometallic ions on COOH-SAM surfaces by soft landing. Collectively, the three instruments provide complementary information about the chemical composition, reactivity and structure of well-defined species supported on surfaces.« less

Improved Land Use and Leaf Area Index Enhances WRF-3DVAR Satellite Radiance Assimilation: A Case Study Focusing on Rainfall Simulation in the Shule River Basin during July 2013

NASA Astrophysics Data System (ADS)

Yang, Junhua; Ji, Zhenming; Chen, Deliang; Kang, Shichang; Fu, Congshen; Duan, Keqin; Shen, Miaogen

2018-06-01

The application of satellite radiance assimilation can improve the simulation of precipitation by numerical weather prediction models. However, substantial quantities of satellite data, especially those derived from low-level (surface-sensitive) channels, are rejected for use because of the difficulty in realistically modeling land surface emissivity and energy budgets. Here, we used an improved land use and leaf area index (LAI) dataset in the WRF-3DVAR assimilation system to explore the benefit of using improved quality of land surface information to improve rainfall simulation for the Shule River Basin in the northeastern Tibetan Plateau as a case study. The results for July 2013 show that, for low-level channels (e.g., channel 3), the underestimation of brightness temperature in the original simulation was largely removed by more realistic land surface information. In addition, more satellite data could be utilized in the assimilation because the realistic land use and LAI data allowed more satellite radiance data to pass the deviation test and get used by the assimilation, which resulted in improved initial driving fields and better simulation in terms of temperature, relative humidity, vertical convection, and cumulative precipitation.

Translation of Land Surface Model Accuracy and Uncertainty into Coupled Land-Atmosphere Prediction

NASA Technical Reports Server (NTRS)

Santanello, Joseph A.; Kumar, Sujay; Peters-Lidard, Christa D.; Harrison, Kenneth W.; Zhou, Shuija

2012-01-01

Land-atmosphere (L-A) Interactions playa critical role in determining the diurnal evolution of both planetary boundary layer (PBL) and land surface heat and moisture budgets, as well as controlling feedbacks with clouds and precipitation that lead to the persistence of dry and wet regimes. Recent efforts to quantify the strength of L-A coupling in prediction models have produced diagnostics that integrate across both the land and PBL components of the system. In this study, we examine the impact of improved specification of land surface states, anomalies, and fluxes on coupled WRF forecasts during the summers of extreme dry (2006) and wet (2007) land surface conditions in the U.S. Southern Great Plains. The improved land initialization and surface flux parameterizations are obtained through the use of a new optimization and uncertainty estimation module in NASA's Land Information System (US-OPT/UE), whereby parameter sets are calibrated in the Noah land surface model and classified according to a land cover and soil type mapping of the observation sites to the full model domain. The impact of calibrated parameters on the a) spinup of the land surface used as initial conditions, and b) heat and moisture states and fluxes of the coupled WRF Simulations are then assessed in terms of ambient weather and land-atmosphere coupling along with measures of uncertainty propagation into the forecasts. In addition, the sensitivity of this approach to the period of calibration (dry, wet, average) is investigated. Finally, tradeoffs of computational tractability and scientific validity, and the potential for combining this approach with satellite remote sensing data are also discussed.

MEaSUREs Land Surface Temperature from GOES Satellites

NASA Astrophysics Data System (ADS)

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).

The characteristics and interpretability of land surface change and implications for project design

USGS Publications Warehouse

Sohl, Terry L.; Gallant, Alisa L.; Loveland, Thomas R.

2004-01-01

The need for comprehensive, accurate information on land-cover change has never been greater. While remotely sensed imagery affords the opportunity to provide information on land-cover change over large geographic expanses at a relatively low cost, the characteristics of land-surface change bring into question the suitability of many commonly used methodologies. Algorithm-based methodologies to detect change generally cannot provide the same level of accuracy as the analyses done by human interpreters. Results from the Land Cover Trends project, a cooperative venture that includes the U.S. Geological Survey, Environmental Protection Agency, and National Aeronautics and Space Administration, have shown that land-cover conversion is a relatively rare event, occurs locally in small patches, varies geographically and temporally, and is spectrally ambiguous. Based on these characteristics of change and the type of information required, manual interpretation was selected as the primary means of detecting change in the Land Cover Trends project. Mixtures of algorithm-based detection and manual interpretation may often prove to be the most feasible and appropriate design for change-detection applications. Serious examination of the expected characteristics and measurability of change must be considered during the design and implementation phase of any change analysis project.

Possibilities of Land Administration Domain Model (ladm) Implementation in Nigeria

NASA Astrophysics Data System (ADS)

Babalola, S. O.; Rahman, A. Abdul; Choon, L. T.; Van Oosterom, P. J. M.

2015-10-01

LADM covers essential information associated components of land administration and management including those over water and elements above and below the surface of the earth. LADM standard provides an abstract conceptual model with three packages and one sub-package. LADM defined terminology for a land administration system that allows a shared explanation of different formal customary or informal tenures. The standard provides the basis for national and regional profiles and enables the combination of land management information from different sources in a coherent manner. Given this, this paper started with the description of land and land administration in Nigeria. The pre-colonial, colonial and post-colonial era with organization structure was discussed. This discussion is important to present an understanding of the background of any improvement needed for the LADM implementation in Nigeria. The LADM, ISO 19152 and the packages of LADM was discussed, and the comparison of the different aspects of each package and classes were made with Nigerian land administration and the cadastral system. In the comparison made, it was discovered that the concept is similar to LADM packages in Nigerian land administration. Although, the terminology may not be the same in all cases. Having studied conceptualization and the application of LADM, as a model that has essential information associated with components of the land administration. Including those on the land, over water as well as elements above and below the surface of the earth and discovered that the standard is suitable for the country. The model can, therefore, be adopted into Nigerian land administration system by mapping in some of the concepts of LADM.

Utility of Thermal Infrared Satellite Data For Urban Landscapes

NASA Astrophysics Data System (ADS)

Xian, G.; Crane, M.; Granneman, B.

2006-12-01

Urban landscapes are comprised of a variety of surfaces that are characterized by contrasting radiative, thermal, aerodynamic, and moisture properties. These different surfaces possess diverse physical and thermal attributes that directly influence surface energy balance and our ability to determine surface characteristics in urban areas. Reflectance properties obtained from satellite imagery have proven useful for mapping urban land use and land cover change, as well as ecosystem health. Landsat reflectance bands are commonly used in regression tree models to generate linear equations that correspond to distinct land surface materials. However, urban land cover is generally a heterogeneous mix of bare soil, vegetation, rock, and anthropogenic impervious surfaces. Surface temperature obtained from satellite thermal infrared bands provides valuable information about surface biophysical properties and radiant thermal characteristics of land cover elements, especially for urban environments. This study demonstrates the improved characterization of land cover conditions for Seattle, Washington, and Las Vegas, Nevada, that were achieved by using both the reflectance and thermal bands of Landsat Enhanced Thematic Mapper Plus (ETM+) data. Including the thermal band in the image analysis increased the accuracy of discriminating cover types in heterogeneous landscapes with extreme contrasts, especially for mixed pixels at the urban interface.

Remote sensing of land surface phenology

USGS Publications Warehouse

Meier, G.A.; Brown, Jesslyn F.

2014-01-01

Remote sensing of land-surface phenology is an important method for studying the patterns of plant and animal growth cycles. Phenological events are sensitive to climate variation; therefore phenology data provide important baseline information documenting trends in ecology and detecting the impacts of climate change on multiple scales. The USGS Remote sensing of land surface phenology program produces annually, nine phenology indicator variables at 250 m and 1,000 m resolution for the contiguous U.S. The 12 year archive is available at http://phenology.cr.usgs.gov/index.php.

Estimates of Soil Moisture Using the Land Information System for Land Surface Water Storage: Case Study for the Western States Water Mission

NASA Astrophysics Data System (ADS)

Liu, P. W.; Famiglietti, J. S.; Levoe, S.; Reager, J. T., II; David, C. H.; Kumar, S.; Li, B.; Peters-Lidard, C. D.

2017-12-01

Soil moisture is one of the critical factors in terrestrial hydrology. Accurate soil moisture information improves estimation of terrestrial water storage and fluxes, that is essential for water resource management including sustainable groundwater pumping and agricultural irrigation practices. It is particularly important during dry periods when water stress is high. The Western States Water Mission (WSWM), a multiyear mission project of NASA's Jet Propulsion Laboratory, is operated to understand and estimate quantities of the water availability in the western United States by integrating observations and measurements from in-situ and remote sensing sensors, and hydrological models. WSWM data products have been used to assess and explore the adverse impacts of the California drought (2011-2016) and provide decision-makers information for water use planning. Although the observations are often more accurate, simulations using land surface models can provide water availability estimates at desired spatio-temporal scales. The Land Information System (LIS), developed by NASA's Goddard Space Flight Center, integrates developed land surface models and data processing and management tools, that enables to utilize the measurements and observations from various platforms as forcings in the high performance computing environment to forecast the hydrologic conditions. The goal of this study is to implement the LIS in the western United States for estimates of soil moisture. We will implement the NOAH-MP model at the 12km North America Land Data Assimilation System grid and compare to other land surface models included in the LIS. Findings will provide insight into the differences between model estimates and model physics. Outputs from a multi-model ensemble from LIS can also be used to enhance estimated reliability and provide quantification of uncertainty. We will compare the LIS-based soil moisture estimates to the SMAP enhanced 9 km soil moisture product to understand the mechanistic differences between the model and observation. These outcomes will contribute to the WSWM for providing robust products.

Oblique Photogrammetry and Usage on Land Administration

NASA Astrophysics Data System (ADS)

Kisa, A.; Ozmus, L.; Erkek, B.; Ates, H. B.; Bakici, S.

2013-08-01

Projects based on Geographic Information Systems (GIS) have started within the body of the General Directorate of Land Registry and Cadastre (GDLRC) by the Land Registry and Cadastre Information System (LRCIS) in the beginning of 2000s. LRCIS was followed by other projects which are Turkish National Geographic Information System (TNGIS), Continuously Operating GPS Reference Stations (CORS-TR), Geo Metadata Portal (GMP), Orthophoto Web Services, Completion of Initial Cadastre, Cadastre Renovation Project (CRP), 2B and Land Registry Achieve Information System (LRAIS). When examining the projects generated by GDLRC, it is realized that they include basic functions of land administration required for sustainable development. Sustainable development is obtained through effective land administration as is known. Nowadays, land use becomes more intense as a result of rapid population increase. The importance of land ownership has increased accordingly. At this point, the necessity of cadastre appears. In Turkey, cadastral registration is carried out by the detection of parcels. In other words, it is obtained through the division of land surface into 2D boundaries and mapping of them. However, existing land administration systems have begun to lose their efficiency while coping with rights, restrictions and responsibilities (RRRs) belonging to land which become more complicated day by day. Overlapping and interlocking constructions appear particularly in urban areas with dense housing and consequently, the problem of how to project these structures onto the surface in 2D cadastral systems has arisen. Herein, the necessity of 3D cadastre concept and 3D property data is confronted. In recent years, oblique photogrammetry, whose applications are gradually spreading, is used as an effective method for producing 3D data. In this study, applications of oblique photogrammetry and usability of oblique images as base for 3D Cadastre and Land Administration projects are examined.

Investigating Satellite Microwave observations of Precipitation in Different Climate Regimes

NASA Astrophysics Data System (ADS)

Wang, N.; Ferraro, R. R.

2013-12-01

Microwave satellite remote sensing of precipitation over land is a challenging problem due to the highly variable land surface emissivity, which, if not properly accounted for, can be much greater than the precipitation signal itself, especially in light rain/snow conditions. Additionally, surfaces such as arid land, deserts and snow cover have brightness temperature characteristics similar to precipitation Ongoing work by GPM microwave radiometer team is constructing databases through a variety of means, however, there is much uncertainty as to what is the optimal information needed for the wide array of sensors in the GPM constellation, including examination of regional conditions. The original data sets will focus on stratification by emissivity class, surface temperature and total perceptible water. We'll perform sensitivity studies to determine the potential role of ancillary data (e.g., land surface temperature, snow cover/water equivalent, etc.) to improve precipitation estimation over land in different climate regimes, including rain and snow. In other words, what information outside of the radiances can help describe the background and subsequent departures from it that are active precipitating regions? It is likely that this information will be a function of the various precipitation regimes. Statistical methods such as Principal Component Analysis (PCA) will be utilized in this task. Databases from a variety of sources are being constructed. They include existing satellite microwave measurements of precipitating and non-precipitating conditions, ground radar precipitation rate estimates, surface emissivity climatology from satellites, surface temperature and TPW from NWP reanalysis. Results from the analysis of these databases with respect to the microwave precipitation sensitivity to the variety of environmental conditions in different climate regimes will be discussed.

Apollo program soil mechanics experiment. [interaction of the lunar module with the lunar surface

NASA Technical Reports Server (NTRS)

Scott, R. F.

1975-01-01

The soil mechanics investigation was conducted to obtain information relating to the landing interaction of the lunar module (LM) with the lunar surface, and lunar soil erosion caused by the spacecraft engine exhaust. Results obtained by study of LM landing performance on each Apollo mission are summarized.

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

NASA Astrophysics Data System (ADS)

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

2010-12-01

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

On the predictability of land surface fluxes from meteorological variables

NASA Astrophysics Data System (ADS)

Haughton, Ned; Abramowitz, Gab; Pitman, Andy J.

2018-01-01

Previous research has shown that land surface models (LSMs) are performing poorly when compared with relatively simple empirical models over a wide range of metrics and environments. Atmospheric driving data appear to provide information about land surface fluxes that LSMs are not fully utilising. Here, we further quantify the information available in the meteorological forcing data that are used by LSMs for predicting land surface fluxes, by interrogating FLUXNET data, and extending the benchmarking methodology used in previous experiments. We show that substantial performance improvement is possible for empirical models using meteorological data alone, with no explicit vegetation or soil properties, thus setting lower bounds on a priori expectations on LSM performance. The process also identifies key meteorological variables that provide predictive power. We provide an ensemble of empirical benchmarks that are simple to reproduce and provide a range of behaviours and predictive performance, acting as a baseline benchmark set for future studies. We reanalyse previously published LSM simulations and show that there is more diversity between LSMs than previously indicated, although it remains unclear why LSMs are broadly performing so much worse than simple empirical models.

The Goddard Snow Radiance Assimilation Project: An Integrated Snow Radiance and Snow Physics Modeling Framework for Snow/cold Land Surface Modeling

NASA Technical Reports Server (NTRS)

Kim, E.; Tedesco, M.; Reichle, R.; Choudhury, B.; Peters-Lidard C.; Foster, J.; Hall, D.; Riggs, G.

2006-01-01

Microwave-based retrievals of snow parameters from satellite observations have a long heritage and have so far been generated primarily by regression-based empirical "inversion" methods based on snapshots in time. Direct assimilation of microwave radiance into physical land surface models can be used to avoid errors associated with such retrieval/inversion methods, instead utilizing more straightforward forward models and temporal information. This approach has been used for years for atmospheric parameters by the operational weather forecasting community with great success. Recent developments in forward radiative transfer modeling, physical land surface modeling, and land data assimilation are converging to allow the assembly of an integrated framework for snow/cold lands modeling and radiance assimilation. The objective of the Goddard snow radiance assimilation project is to develop such a framework and explore its capabilities. The key elements of this framework include: a forward radiative transfer model (FRTM) for snow, a snowpack physical model, a land surface water/energy cycle model, and a data assimilation scheme. In fact, multiple models are available for each element enabling optimization to match the needs of a particular study. Together these form a modular and flexible framework for self-consistent, physically-based remote sensing and water/energy cycle studies. In this paper we will describe the elements and the integration plan. All modules will operate within the framework of the Land Information System (LIS), a land surface modeling framework with data assimilation capabilities running on a parallel-node computing cluster. Capabilities for assimilation of snow retrieval products are already under development for LIS. We will describe plans to add radiance-based assimilation capabilities. Plans for validation activities using field measurements will also be discussed.

Spatial scaling of net primary productivity using subpixel landcover information

NASA Astrophysics Data System (ADS)

Chen, X. F.; Chen, Jing M.; Ju, Wei M.; Ren, L. L.

2008-10-01

Gridding the land surface into coarse homogeneous pixels may cause important biases on ecosystem model estimations of carbon budget components at local, regional and global scales. These biases result from overlooking subpixel variability of land surface characteristics. Vegetation heterogeneity is an important factor introducing biases in regional ecological modeling, especially when the modeling is made on large grids. This study suggests a simple algorithm that uses subpixel information on the spatial variability of land cover type to correct net primary productivity (NPP) estimates, made at coarse spatial resolutions where the land surface is considered as homogeneous within each pixel. The algorithm operates in such a way that NPP obtained from calculations made at coarse spatial resolutions are multiplied by simple functions that attempt to reproduce the effects of subpixel variability of land cover type on NPP. Its application to a carbon-hydrology coupled model(BEPS-TerrainLab model) estimates made at a 1-km resolution over a watershed (named Baohe River Basin) located in the southwestern part of Qinling Mountains, Shaanxi Province, China, improved estimates of average NPP as well as its spatial variability.

Microwave Brightness Of Land Surfaces From Outer Space

NASA Technical Reports Server (NTRS)

Kerr, Yann H.; Njoku, Eni G.

1991-01-01

Mathematical model approximates microwave radiation emitted by land surfaces traveling to microwave radiometer in outer space. Applied to measurements made by Scanning Multichannel Microwave Radiometer (SMMR). Developed for interpretation of microwave imagery of Earth to obtain distributions of various chemical, physical, and biological characteristics across its surface. Intended primarily for use in mapping moisture content of soil and fraction of Earth covered by vegetation. Advanced Very-High-Resolution Radiometer (AVHRR), provides additional information on vegetative cover, thereby making possible retrieval of soil-moisture values from SMMR measurements. Possible to monitor changes of land surface during intervals of 5 to 10 years, providing significant data for mathematical models of evolution of climate.

Impact of Calibrated Land Surface Model Parameters on the Accuracy and Uncertainty of Land-Atmosphere Coupling in WRF Simulations

NASA Technical Reports Server (NTRS)

Santanello, Joseph A., Jr.; Kumar, Sujay V.; Peters-Lidard, Christa D.; Harrison, Ken; Zhou, Shujia

2012-01-01

Land-atmosphere (L-A) interactions play a critical role in determining the diurnal evolution of both planetary boundary layer (PBL) and land surface temperature and moisture budgets, as well as controlling feedbacks with clouds and precipitation that lead to the persistence of dry and wet regimes. Recent efforts to quantify the strength of L-A coupling in prediction models have produced diagnostics that integrate across both the land and PBL components of the system. In this study, we examine the impact of improved specification of land surface states, anomalies, and fluxes on coupled WRF forecasts during the summers of extreme dry (2006) and wet (2007) land surface conditions in the U.S. Southern Great Plains. The improved land initialization and surface flux parameterizations are obtained through the use of a new optimization and uncertainty estimation module in NASA's Land Information System (LIS-OPT/UE), whereby parameter sets are calibrated in the Noah land surface model and classified according to a land cover and soil type mapping of the observation sites to the full model domain. The impact of calibrated parameters on the a) spinup of the land surface used as initial conditions, and b) heat and moisture states and fluxes of the coupled WRF simulations are then assessed in terms of ambient weather and land-atmosphere coupling along with measures of uncertainty propagation into the forecasts. In addition, the sensitivity of this approach to the period of calibration (dry, wet, average) is investigated. Finally, tradeoffs of computational tractability and scientific validity, and the potential for combining this approach with satellite remote sensing data are also discussed.

Generation of High Resolution Land Surface Parameters in the Community Land Model

NASA Astrophysics Data System (ADS)

Ke, Y.; Coleman, A. M.; Wigmosta, M. S.; Leung, L.; Huang, M.; Li, H.

2010-12-01

The Community Land Model (CLM) is the land surface model used for the Community Atmosphere Model (CAM) and the Community Climate System Model (CCSM). It examines the physical, chemical, and biological processes across a variety of spatial and temporal scales. Currently, efforts are being made to improve the spatial resolution of the CLM, in part, to represent finer scale hydrologic characteristics. Current land surface parameters of CLM4.0, in particular plant functional types (PFT) and leaf area index (LAI), are generated from MODIS and calculated at a 0.05 degree resolution. These MODIS-derived land surface parameters have also been aggregated to coarser resolutions (e.g., 0.5, 1.0 degrees). To evaluate the response of CLM across various spatial scales, higher spatial resolution land surface parameters need to be generated. In this study we examine the use of Landsat TM/ETM+ imagery and data fusion techniques for generating land surface parameters at a 1km resolution within the Pacific Northwest United States. . Land cover types and PFTs are classified based on Landsat multi-season spectral information, DEM, National Land Cover Database (NLCD) and the USDA-NASS Crop Data Layer (CDL). For each PFT, relationships between MOD15A2 high quality LAI values, Landsat-based vegetation indices, climate variables, terrain, and laser-altimeter derived vegetation height are used to generate monthly LAI values at a 30m resolution. The high-resolution PFT and LAI data are aggregated to create a 1km model grid resolution. An evaluation and comparison of CLM land surface response at both fine and moderate scale is presented.

Ocean, Land and Meteorology Studies Using Space-Based Lidar Measurements

NASA Technical Reports Server (NTRS)

Hu,Yongxiang

2009-01-01

CALIPSO's main mission objective is studying the climate impact of clouds and aerosols in the atmosphere. CALIPSO also collects information about other components of the Earth's ecosystem, such as oceans and land. This paper introduces the physics concepts and presents preliminary results for the valueadded CALIPSO Earth system science products. These include ocean surface wind speeds, column atmospheric optical depths, ocean subsurface backscatter, land surface elevations, atmospheric temperature profiles, and A-train data fusion products.

A Prototype Land Information Sensor Web: Design, Implementation and Implication for the SMAP Mission

NASA Astrophysics Data System (ADS)

Su, H.; Houser, P.; Tian, Y.; Geiger, J. K.; Kumar, S. V.; Gates, L.

2009-12-01

Land Surface Model (LSM) predictions are regular in time and space, but these predictions are influenced by errors in model structure, input variables, parameters and inadequate treatment of sub-grid scale spatial variability. Consequently, LSM predictions are significantly improved through observation constraints made in a data assimilation framework. Several multi-sensor satellites are currently operating which provide multiple global observations of the land surface, and its related near-atmospheric properties. However, these observations are not optimal for addressing current and future land surface environmental problems. To meet future earth system science challenges, NASA will develop constellations of smart satellites in sensor web configurations which provide timely on-demand data and analysis to users, and can be reconfigured based on the changing needs of science and available technology. A sensor web is more than a collection of satellite sensors. That means a sensor web is a system composed of multiple platforms interconnected by a communication network for the purpose of performing specific observations and processing data required to support specific science goals. Sensor webs can eclipse the value of disparate sensor components by reducing response time and increasing scientific value, especially when the two-way interaction between the model and the sensor web is enabled. The study of a prototype Land Information Sensor Web (LISW) is sponsored by NASA, trying to integrate the Land Information System (LIS) in a sensor web framework which allows for optimal 2-way information flow that enhances land surface modeling using sensor web observations, and in turn allows sensor web reconfiguration to minimize overall system uncertainty. This prototype is based on a simulated interactive sensor web, which is then used to exercise and optimize the sensor web modeling interfaces. The Land Information Sensor Web Service-Oriented Architecture (LISW-SOA) has been developed and it is the very first sensor web framework developed especially for the land surface studies. Synthetic experiments based on the LISW-SOA and the virtual sensor web provide a controlled environment in which to examine the end-to-end performance of the prototype, the impact of various sensor web design trade-offs and the eventual value of sensor webs for a particular prediction or decision support. In this paper, the design, implementation of the LISW-SOA and the implication for the Soil Moisture Active and Passive (SMAP) mission is presented. Particular attention is focused on examining the relationship between the economic investment on a sensor web (space and air borne, ground based) and the accuracy of the model predicted soil moisture, which can be achieved by using such sensor observations. The Study of Virtual Land Information Sensor Web (LISW) is expected to provide some necessary a priori knowledge for designing and deploying the next generation Global Earth Observing System of systems (GEOSS).

Spatially Complete Global Surface Albedos Derived from Terra/MODIS Data

NASA Technical Reports Server (NTRS)

King, Michael D.; Moody, Eric G.; Platnick, Steven; Schaaf, Crystal B.

2005-01-01

Spectral land surface albedo is an important parameter for describing the radiative properties of the Earth. Accordingly it reflects the consequences of natural and human interactions, such as anthropogenic, meteorological, and phenological effects, on global and local climatological trends. Consequently, albedos are integral parts in a variety of research areas, such as general circulation models (GCMs), energy balance studies, modeling of land use and land use change, and biophysical, oceanographic, and meteorological studies. Recent production of land surface anisotropy, diffuse bihemispherical (white-sky) albedo and direct beam directional hemispherical (black-sky) albedo from observations acquired by the MODIS instruments aboard NASA's Terra and &la satellite platforms have provided researchers with unprecedented spatial, spectral, and temporal information on the land surface's radiative characteristics. Cloud cover, which curtails retrievals, and the presence of ephemeral and seasonal snow limit the snow-free data to approximately half the global land surfaces on an annual equal-angle basis. This precludes the MOD43B3 albedo products from being used in some remote sensing and ground-based applications, &mate models, and global change research projects.

Global Land Data Assimilation System (GLDAS) Products, Services and Application from NASA Hydrology Data and Information Services Center (HDISC)

NASA Technical Reports Server (NTRS)

Fang, Hongliang; Beaudoing, Hiroko K.; Rodell, matthew; Teng, William L.; Vollmer, Bruce E.

2009-01-01

The Global Land Data Assimilation System (GLDAS) is generating a series of land surface state (e.g., soil moisture and surface temperature) and flux (e.g., evaporation and sensible heat flux) products simulated by four land surface models (CLM, Mosaic, Noah and VIC). These products are now accessible at the Hydrology Data and Information Services Center (HDISC), a component of the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC). Current data holdings include a set of 1.0 degree resolution data products from the four models, covering 1979 to the present; and a 0.25 degree data product from the Noah model, covering 2000 to the present. The products are in Gridded Binary (GRIB) format and can be accessed through a number of interfaces. Users can search the products through keywords and perform on-the-fly spatial and parameter subsetting and format conversion of selected data. More advanced visualization, access and analysis capabilities will be available in the future. The long term GLDAS data are used to develop climatology of water cycle components and to explore the teleconnections of droughts and pluvial.

Global Land Data Assimilation System (GLDAS) Products from NASA Hydrology Data and Information Services Center (HDISC)

NASA Technical Reports Server (NTRS)

Fang, Hongliang; Hrubiak, Patricia; Kato, Hiroko; Rodell, Matthew; Teng, William L.; Vollmer, Bruce E.

2008-01-01

The Global Land Data Assimilation System (GLDAS) is generating a series of land surface state (e.g., soil moisture and surface temperature) and flux (e.g., evaporation and sensible heat flux) products simulated by four land surface models (CLM, Mosaic, Noah and VIC). These products are now accessible at the Hydrology Data and Information Services Center (HDISC), a component of the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC). Current data holdings include a set of 1.0 degree resolution data products from the four models, covering 1979 to the present; and a 0.25 degree data product from the Noah model, covering 2000 to the present. The products are in Gridded Binary (GRIB) format and can be accessed through a number of interfaces. New data formats (e.g., netCDF), temporal averaging and spatial subsetting will be available in the future. The HDISC has the capability to support more hydrology data products and more advanced analysis tools. The goal is to develop HDISC as a data and services portal that supports weather and climate forecast, and water and energy cycle research.

Investigating habitat value to inform contaminant remediation options: approach

Treesearch

Rebecca A. Efroymson; Mark J. Peterson; Christopher J. Welsh; Daniel L. Druckenbrod; Michael G. Ryon; John G. Smith; William W. Hargrove; Neil R. Giffen; W. Kelly Roy; Harry D. Quarles

2008-01-01

Habitat valuation methods are most often developed and used to prioritize candidate lands for conservation. In this study the intent of habitat valuation was to inform the decision-making process for remediation of chemical contaminants on specific lands or surface water bodies. Methods were developed to summarize dimensions of habitat value for six representative...

Global observation-based diagnosis of soil moisture control on land surface flux partition

NASA Astrophysics Data System (ADS)

Gallego-Elvira, Belen; Taylor, Christopher M.; Harris, Phil P.; Ghent, Darren; Veal, Karen L.; Folwell, Sonja S.

2016-04-01

Soil moisture plays a central role in the partition of available energy at the land surface between sensible and latent heat flux to the atmosphere. As soils dry out, evapotranspiration becomes water-limited ("stressed"), and both land surface temperature (LST) and sensible heat flux rise as a result. This change in surface behaviour during dry spells directly affects critical processes in both the land and the atmosphere. Soil water deficits are often a precursor in heat waves, and they control where feedbacks on precipitation become significant. State-of-the-art global climate model (GCM) simulations for the Coupled Model Intercomparison Project Phase 5 (CMIP5) disagree on where and how strongly the surface energy budget is limited by soil moisture. Evaluation of GCM simulations at global scale is still a major challenge owing to the scarcity and uncertainty of observational datasets of land surface fluxes and soil moisture at the appropriate scale. Earth observation offers the potential to test how well GCM land schemes simulate hydrological controls on surface fluxes. In particular, satellite observations of LST provide indirect information about the surface energy partition at 1km resolution globally. Here, we present a potentially powerful methodology to evaluate soil moisture stress on surface fluxes within GCMs. Our diagnostic, Relative Warming Rate (RWR), is a measure of how rapidly the land warms relative to the overlying atmosphere during dry spells lasting at least 10 days. Under clear skies, this is a proxy for the change in sensible heat flux as soil dries out. We derived RWR from MODIS Terra and Aqua LST observations, meteorological re-analyses and satellite rainfall datasets. Globally we found that on average, the land warmed up during dry spells for 97% of the observed surface between 60S and 60N. For 73% of the area, the land warmed faster than the atmosphere (positive RWR), indicating water stressed conditions and increases in sensible heat flux. Higher RWRs were observed for shorter vegetation and bare soil compared to tall, deep-rooted vegetation due to differences in both aerodynamic and hydrological properties. The variation of RWR with antecedent rainfall provides information on which evaporation regime a particular region lies in climatologically. Different drying stages for a given antecedent rainfall can thus be observed depending on land cover type. For instance, our results suggest that forests in a continental climate remain unstressed during a 10 day dry spell provided the previous month saw at least 95 mm of rain. Conversely, RWR values indicate that under similar conditions regions of grass/crop cover are water-stressed.

Preliminary Study of Information Extraction of LANDSAT TM Data for a Suburban/regional Test Site

NASA Technical Reports Server (NTRS)

Toll, D. L.

1985-01-01

A substantial amount of spectral information is available from TM (as compared to MSS) data for a 14.25 square km area between Beltsville and Laurel, Maryland. Large buildings and street patterns were resolved in the TM imagery. While there was added information content in TM data for discriminating surburban/regional land cover, characteristics of MSS can improve land cover discrimination over TM when conventional classification procedures are used on digital data. The improved qualitization of TM is likely valuable in situations where there are spectral similarities between classes. The spatial resolution in TM decreased land cover discrimination as a result of increased within class variability. For many general digital evaluations, inclusion of four bands representing the four spectral regions can provide much useful land cover discrimination. Inclusion of TM 6 indicates an improvement in spectral class discrimination. Of primary spectral importance is the discrimination between water, vegetative surfaces, and impervious surfaces due to differences in thermal properties. Results from the principle component transformed data clearly indicates additional information content in TM over MSS.

Multi-Scale Hydrometeorological Modeling, Land Data Assimilation and Parameter Estimation with the Land Information System

NASA Technical Reports Server (NTRS)

Peters-Lidard, Christa D.

2011-01-01

The Land Information System (LIS; http://lis.gsfc.nasa.gov) is a flexible land surface modeling framework that has been developed with the goal of integrating satellite-and ground-based observational data products and advanced land surface modeling techniques to produce optimal fields of land surface states and fluxes. As such, LIS represents a step towards the next generation land component of an integrated Earth system model. In recognition of LIS object-oriented software design, use and impact in the land surface and hydrometeorological modeling community, the LIS software was selected as a co-winner of NASA?s 2005 Software of the Year award.LIS facilitates the integration of observations from Earth-observing systems and predictions and forecasts from Earth System and Earth science models into the decision-making processes of partnering agency and national organizations. Due to its flexible software design, LIS can serve both as a Problem Solving Environment (PSE) for hydrologic research to enable accurate global water and energy cycle predictions, and as a Decision Support System (DSS) to generate useful information for application areas including disaster management, water resources management, agricultural management, numerical weather prediction, air quality and military mobility assessment. LIS has e volved from two earlier efforts -- North American Land Data Assimilation System (NLDAS) and Global Land Data Assimilation System (GLDAS) that focused primarily on improving numerical weather prediction skills by improving the characterization of the land surface conditions. Both of GLDAS and NLDAS now use specific configurations of the LIS software in their current implementations.In addition, LIS was recently transitioned into operations at the US Air Force Weather Agency (AFWA) to ultimately replace their Agricultural Meteorology (AGRMET) system, and is also used routinely by NOAA's National Centers for Environmental Prediction (NCEP)/Environmental Modeling Center (EMC) for their land data assimilation systems to support weather and climate modeling. LIS not only consolidates the capabilities of these two systems, but also enables a much larger variety of configurations with respect to horizontal spatial resolution, input datasets and choice of land surface model through "plugins". LIS has been coupled to the Weather Research and Forecasting (WRF) model to support studies of land-atmosphere coupling be enabling ensembles of land surface states to be tested against multiple representations of the atmospheric boundary layer. LIS has also been demonstrated for parameter estimation, who showed that the use of sequential remotely sensed soil moisture products can be used to derive soil hydraulic and texture properties given a sufficient dynamic range in the soil moisture retrievals and accurate precipitation inputs.LIS has also recently been demonstrated for multi-model data assimilation using an Ensemble Kalman Filter for sequential assimilation of soil moisture, snow, and temperature.Ongoing work has demonstrated the value of bias correction as part of the filter, and also that of joint calibration and assimilation.Examples and case studies demonstrating the capabilities and impacts of LIS for hydrometeorological modeling, assimilation and parameter estimation will be presented as advancements towards the next generation of integrated observation and modeling systems

A prototype for automation of land-cover products from Landsat Surface Reflectance Data Records

NASA Astrophysics Data System (ADS)

Rover, J.; Goldhaber, M. B.; Steinwand, D.; Nelson, K.; Coan, M.; Wylie, B. K.; Dahal, D.; Wika, S.; Quenzer, R.

2014-12-01

Landsat data records of surface reflectance provide a three-decade history of land surface processes. Due to the vast number of these archived records, development of innovative approaches for automated data mining and information retrieval were necessary. Recently, we created a prototype utilizing open source software libraries for automatically generating annual Anderson Level 1 land cover maps and information products from data acquired by the Landsat Mission for the years 1984 to 2013. The automated prototype was applied to two target areas in northwestern and east-central North Dakota, USA. The approach required the National Land Cover Database (NLCD) and two user-input target acquisition year-days. The Landsat archive was mined for scenes acquired within a 100-day window surrounding these target dates, and then cloud-free pixels where chosen closest to the specified target acquisition dates. The selected pixels were then composited before completing an unsupervised classification using the NLCD. Pixels unchanged in pairs of the NLCD were used for training decision tree models in an iterative process refined with model confidence measures. The decision tree models were applied to the Landsat composites to generate a yearly land cover map and related information products. Results for the target areas captured changes associated with the recent expansion of oil shale production and agriculture driven by economics and policy, such as the increase in biofuel production and reduction in Conservation Reserve Program. Changes in agriculture, grasslands, and surface water reflect the local hydrological conditions that occurred during the 29-year span. Future enhancements considered for this prototype include a web-based client, ancillary spatial datasets, trends and clustering algorithms, and the forecasting of future land cover.

Reconstructed historical land cover and biophysical parameters for studies of land-atmosphere interactions within the eastern United States

USGS Publications Warehouse

Steyaert, Louis T.; Knox, R.G.

2008-01-01

Over the past 350 years, the eastern half of the United States experienced extensive land cover changes. These began with land clearing in the 1600s, continued with widespread deforestation, wetland drainage, and intensive land use by 1920, and then evolved to the present-day landscape of forest regrowth, intensive agriculture, urban expansion, and landscape fragmentation. Such changes alter biophysical properties that are key determinants of land-atmosphere interactions (water, energy, and carbon exchanges). To understand the potential implications of these land use transformations, we developed and analyzed 20-km land cover and biophysical parameter data sets for the eastern United States at 1650, 1850, 1920, and 1992 time slices. Our approach combined potential vegetation, county-level census data, soils data, resource statistics, a Landsat-derived land cover classification, and published historical information on land cover and land use. We reconstructed land use intensity maps for each time slice and characterized the land cover condition. We combined these land use data with a mutually consistent set of biophysical parameter classes, to characterize the historical diversity and distribution of land surface properties. Time series maps of land surface albedo, leaf area index, a deciduousness index, canopy height, surface roughness, and potential saturated soils in 1650, 1850, 1920, and 1992 illustrate the profound effects of land use change on biophysical properties of the land surface. Although much of the eastern forest has returned, the average biophysical parameters for recent landscapes remain markedly different from those of earlier periods. Understanding the consequences of these historical changes will require land-atmosphere interactions modeling experiments.

Towards an Improved Represenation of Reservoirs and Water Management in a Land Surface-Hydrology Model

NASA Astrophysics Data System (ADS)

Yassin, F.; Anis, M. R.; Razavi, S.; Wheater, H. S.

2017-12-01

Water management through reservoirs, diversions, and irrigation have significantly changed river flow regimes and basin-wide energy and water balance cycles. Failure to represent these effects limits the performance of land surface-hydrology models not only for streamflow prediction but also for the estimation of soil moisture, evapotranspiration, and feedbacks to the atmosphere. Despite recent research to improve the representation of water management in land surface models, there remains a need to develop improved modeling approaches that work in complex and highly regulated basins such as the 406,000 km2 Saskatchewan River Basin (SaskRB). A particular challenge for regional and global application is a lack of local information on reservoir operational management. To this end, we implemented a reservoir operation, water abstraction, and irrigation algorithm in the MESH land surface-hydrology model and tested it over the SaskRB. MESH is Environment Canada's Land Surface-hydrology modeling system that couples Canadian Land Surface Scheme (CLASS) with hydrological routing model. The implemented reservoir algorithm uses an inflow-outflow relationship that accounts for the physical characteristics of reservoirs (e.g., storage-area-elevation relationships) and includes simplified operational characteristics based on local information (e.g., monthly target volume and release under limited, normal, and flood storage zone). The irrigation algorithm uses the difference between actual and potential evapotranspiration to estimate irrigation water demand. This irrigation demand is supplied from the neighboring reservoirs/diversion in the river system. We calibrated the model enabled with the new reservoir and irrigation modules in a multi-objective optimization setting. Results showed that the reservoir and irrigation modules significantly improved the MESH model performance in generating streamflow and evapotranspiration across the SaskRB and that this our approach provides a basis for improved large scale hydrological modelling.

Land and atmosphere interactions using satellite remote sensing and a coupled mesoscale/land surface model

NASA Astrophysics Data System (ADS)

Hong, Seungbum

Land and atmosphere interactions have long been recognized for playing a key role in climate and weather modeling. However their quantification has been challenging due to the complex nature of the land surface amongst various other reasons. One of the difficult parts in the quantification is the effect of vegetation which are related to land surface processes such soil moisture variation and to atmospheric conditions such as radiation. This study addresses various relational investigations among vegetation properties such as Normalized Difference Vegetation Index (NDVI), Leaf Area Index (LAI), surface temperature (TSK), and vegetation water content (VegWC) derived from satellite sensors such as Moderate Resolution Imaging Spectroradiometer (MODIS) and EOS Advanced Microwave Scanning Radiometer (AMSR-E). The study provides general information about a physiological behavior of vegetation for various environmental conditions. Second, using a coupled mesoscale/land surface model, we examined the effects of vegetation and its relationship with soil moisture on the simulated land-atmospheric interactions through the model sensitivity tests. The Weather Research and Forecasting (WRF) model was selected for this study, and the Noah land surface model (Noah LSM) implemented in the WRF model was used for the model coupled system. This coupled model was tested through two parameterization methods for vegetation fraction using MODIS data and through model initialization of soil moisture from High Resolution Land Data Assimilation System (HRLDAS). Then, this study evaluates the model improvements for each simulation method.

Geographical Applications of Remote Sensing

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

Weng, Qihao; Zhou, Yuyu; Quattrochi, Dale

2013-02-28

Data and Information derived through Earth observation technology have been extensively used in geographic studies, such as in the areas of natural and human environments, resources, land use and land cover, human-environment interactions, and socioeconomic issues. Land-use and land-cover change (LULCC), affecting biodiversity, climate change, watershed hydrology, and other surface processes, is one of the most important research topics in geography.

Improved Modeling of Land-Atmosphere Interactions using a Coupled Version of WRF with the Land Information System

NASA Technical Reports Server (NTRS)

Case, Jonathan L.; LaCasse, Katherine M.; Santanello, Joseph A., Jr.; Lapenta, William M.; Petars-Lidard, Christa D.

2007-01-01

The exchange of energy and moisture between the Earth's surface and the atmospheric boundary layer plays a critical role in many hydrometeorological processes. Accurate and high-resolution representations of surface properties such as sea-surface temperature (SST), vegetation, soil temperature and moisture content, and ground fluxes are necessary to better understand the Earth-atmosphere interactions and improve numerical predictions of weather and climate phenomena. The NASA/NWS Short-term Prediction Research and Transition (SPORT) Center is currently investigating the potential benefits of assimilating high-resolution datasets derived from the NASA moderate resolution imaging spectroradiometer (MODIS) instruments using the Weather Research and Forecasting (WRF) model and the Goddard Space Flight Center Land Information System (LIS). The LIS is a software framework that integrates satellite and ground-based observational and modeled data along with multiple land surface models (LSMs) and advanced computing tools to accurately characterize land surface states and fluxes. The LIS can be run uncoupled to provide a high-resolution land surface initial condition, and can also be run in a coupled mode with WRF to integrate surface and soil quantities using any of the LSMs available in LIS. The LIS also includes the ability to optimize the initialization of surface and soil variables by tuning the spin-up time period and atmospheric forcing parameters, which cannot be done in the standard WRF. Among the datasets available from MODIS, a leaf-area index field and composite SST analysis are used to improve the lower boundary and initial conditions to the LIS/WRF coupled model over both land and water. Experiments will be conducted to measure the potential benefits from using the coupled LIS/WRF model over the Florida peninsula during May 2004. This month experienced relatively benign weather conditions, which will allow the experiments to focus on the local and mesoscale impacts of the high-resolution MODIS datasets and optimized soil and surface initial conditions. Follow-on experiments will examine the utility of such an optimized WRF configuration for more complex weather scenarios such as convective initiation. This paper will provide an overview of the experiment design and present preliminary results from selected cases in May 2004.

Exploring Remote Sensing Products Online with Giovanni for Studying Urbanization

NASA Technical Reports Server (NTRS)

Shen, Suhung; Leptoukh, Gregory G.; Gerasimov, Irina; Kempler, Steve

2012-01-01

Recently, a Large amount of MODIS land products at multi-spatial resolutions have been integrated into the online system, Giovanni, to support studies on land cover and land use changes focused on Northern Eurasia and Monsoon Asia regions. Giovanni (Goddard Interactive Online Visualization ANd aNalysis Infrastructure) is a Web-based application developed by the NASA Goddard Earth Sciences Data and Information Services Center (GES-DISC) providing a simple and intuitive way to visualize, analyze, and access Earth science remotely-sensed and modeled data. The customized Giovanni Web portals (Giovanni-NEESPI and Giovanni-MAIRS) are created to integrate land, atmospheric, cryospheric, and social products, that enable researchers to do quick exploration and basic analyses of land surface changes and their relationships to climate at global and regional scales. This presentation documents MODIS land surface products in Giovanni system. As examples, images and statistical analysis results on land surface and local climate changes associated with urbanization over Yangtze River Delta region, China, using data in Giovanni are shown.

Upscaling and Downscaling of Land Surface Fluxes with Surface Temperature

NASA Astrophysics Data System (ADS)

Kustas, W. P.; Anderson, M. C.; Hain, C.; Albertson, J. D.; Gao, F.; Yang, Y.

2015-12-01

Land surface temperature (LST) is a key surface boundary condition that is significantly correlated to surface flux partitioning between latent and sensible heat. The spatial and temporal variation in LST is driven by radiation, wind, vegetation cover and roughness as well as soil moisture status in the surface and root zone. Data from airborne and satellite-based platforms provide LST from ~10 km to sub meter resolutions. A land surface scheme called the Two-Source Energy Balance (TSEB) model has been incorporated into a multi-scale regional modeling system ALEXI (Atmosphere Land Exchange Inverse) and a disaggregation scheme (DisALEXI) using higher resolution LST. Results with this modeling system indicates that it can be applied over heterogeneous land surfaces and estimate reliable surface fluxes with minimal in situ information. Consequently, this modeling system allows for scaling energy fluxes from subfield to regional scales in regions with little ground data. In addition, the TSEB scheme has been incorporated into a large Eddy Simulation (LES) model for investigating dynamic interactions between variations in the land surface state reflected in the spatial pattern in LST and the lower atmospheric air properties affecting energy exchange. An overview of research results on scaling of fluxes and interactions with the lower atmosphere from the subfield level to regional scales using the TSEB, ALEX/DisALEX and the LES-TSEB approaches will be presented. Some unresolved issues in the use of LST at different spatial resolutions for estimating surface energy balance and upscaling fluxes, particularly evapotranspiration, will be discussed.

Land-surface initialisation improves seasonal climate prediction skill for maize yield forecast.

PubMed

Ceglar, Andrej; Toreti, Andrea; Prodhomme, Chloe; Zampieri, Matteo; Turco, Marco; Doblas-Reyes, Francisco J

2018-01-22

Seasonal crop yield forecasting represents an important source of information to maintain market stability, minimise socio-economic impacts of crop losses and guarantee humanitarian food assistance, while it fosters the use of climate information favouring adaptation strategies. As climate variability and extremes have significant influence on agricultural production, the early prediction of severe weather events and unfavourable conditions can contribute to the mitigation of adverse effects. Seasonal climate forecasts provide additional value for agricultural applications in several regions of the world. However, they currently play a very limited role in supporting agricultural decisions in Europe, mainly due to the poor skill of relevant surface variables. Here we show how a combined stress index (CSI), considering both drought and heat stress in summer, can predict maize yield in Europe and how land-surface initialised seasonal climate forecasts can be used to predict it. The CSI explains on average nearly 53% of the inter-annual maize yield variability under observed climate conditions and shows how concurrent heat stress and drought events have influenced recent yield anomalies. Seasonal climate forecast initialised with realistic land-surface achieves better (and marginally useful) skill in predicting the CSI than with climatological land-surface initialisation in south-eastern Europe, part of central Europe, France and Italy.

The Water Cycle from Space: Use of Satellite Data in Land Surface Hydrology and Water Resource Management

NASA Technical Reports Server (NTRS)

Laymon, Charles; Blankenship, Clay; Khan, Maudood; Limaye, Ashutosh; Hornbuckle, Brian; Rowlandson, Tracy

2010-01-01

This slide presentation reviews how our understanding of the water cycle is enhanced by our use of satellite data, and how this informs land surface hydrology and water resource management. It reviews how NASA's current and future satellite missions will provide Earth system data of unprecedented breadth, accuracy and utility for hydrologic analysis.

Detecting Changes of Thermal Environment over the Bohai Coastal Region by Spectral Change Vector Analysis

NASA Astrophysics Data System (ADS)

Hu, Y.; Jia, G.

2009-12-01

Change vector analysis (CVA) is an effective approach for detecting and characterizing land-cover change by comparing pairs of multi-spectral and multi-temporal datasets over certain area derived from various satellite platforms. NDVI is considered as an effective detector for biophysical changes due to its sensitivity to red and near infrared signals, while land surface temperature (LST) is considered as a valuable indicator for changes of ground thermal conditions. Here we try to apply CVA over satellite derived LST datasets to detect changes of land surface thermal properties parallel to climate change and anthropogenic influence in a city cluster since 2001. In this study, monthly land surface temperature datasets from 2001-2008 derived from MODIS collection 5 were used to examine change pattern of thermal environment over the Bohai coastal region by using spectral change vector analysis. The results from principle component analysis (PCA) for LST show that the PC 1-3 contain over 80% information on monthly variations and these PCA components represent the main processes of land thermal environment change over the study area. Time series of CVA magnitude combined with land cover information show that greatest change occurred in urban and heavily populated area, featured with expansion of urban heat island, while moderate change appeared in grassland area in the north. However few changes were observed over large plain area and forest area. Strong signals also are related to economy level and especially the events of surface cover change, such as emergence of railway and port. Two main processes were also noticed about the changes of thermal environment. First, weak signal was detected in mostly natural area influenced by interannual climate change in temperate broadleaf forest area. Second, land surface temperature changes were controlled by human activities as 1) moderate change of LST happened in grassland influenced by grazing and 2) urban heat island was intensifier in major cities, such as Beijing and Tianjin. Further, the continual drier climate combined with human actions over past fifties years have intensified land thermal pattern change and the continuation will be an important aspects to understand land surface processes and local climate change. Land surface temperature trends from 2000-2008 over the Bohai coastal region

Simulations of the general circulation of the Martian atmosphere. II - Seasonal pressure variations

NASA Technical Reports Server (NTRS)

Pollack, James B.; Haberle, Robert M.; Murphy, James R.; Schaeffer, James; Lee, Hilda

1993-01-01

The CO2 seasonal cycle of the Martian atmosphere and surface is simulated with a hybrid energy balance model that incorporates dynamical and radiation information from a large number of general circulation model runs. This information includes: heating due to atmospheric heat advection, the seasonally varying ratio of the surface pressure at the two Viking landing sites to the globally averaged pressure, the rate of CO2 condensation in the atmosphere, and solar heating of the atmosphere and surface. The predictions of the energy balance model are compared with the seasonal pressure variations measured at the two Viking landing sites and the springtime retreat of the seasonal polar cap boundaries. The following quantities are found to have a strong influence on the seasonal pressures at the Viking landing sites: albedo of the seasonal CO2 ice deposits, emissivity of this deposit, atmospheric heat advection, and the pressure ratio.

A Prototype Physical Database for Passive Microwave Retrievals of Precipitation over the US Southern Great Plains

NASA Technical Reports Server (NTRS)

Ringerud, S.; Kummerow, C. D.; Peters-Lidard, C. D.

2015-01-01

An accurate understanding of the instantaneous, dynamic land surface emissivity is necessary for a physically based, multi-channel passive microwave precipitation retrieval scheme over land. In an effort to assess the feasibility of the physical approach for land surfaces, a semi-empirical emissivity model is applied for calculation of the surface component in a test area of the US Southern Great Plains. A physical emissivity model, using land surface model data as input, is used to calculate emissivity at the 10GHz frequency, combining contributions from the underlying soil and vegetation layers, including the dielectric and roughness effects of each medium. An empirical technique is then applied, based upon a robust set of observed channel covariances, extending the emissivity calculations to all channels. For calculation of the hydrometeor contribution, reflectivity profiles from the Tropical Rainfall Measurement Mission Precipitation Radar (TRMM PR) are utilized along with coincident brightness temperatures (Tbs) from the TRMM Microwave Imager (TMI), and cloud-resolving model profiles. Ice profiles are modified to be consistent with the higher frequency microwave Tbs. Resulting modeled top of the atmosphere Tbs show correlations to observations of 0.9, biases of 1K or less, root-mean-square errors on the order of 5K, and improved agreement over the use of climatological emissivity values. The synthesis of these models and data sets leads to the creation of a simple prototype Tb database that includes both dynamic surface and atmospheric information physically consistent with the land surface model, emissivity model, and atmospheric information.

Visualization and Analysis of Multi-scale Land Surface Products via Giovanni Portals

NASA Technical Reports Server (NTRS)

Shen, Suhung; Kempler, Steven J.; Gerasimov, Irina V.

2013-01-01

Large volumes of MODIS land data products at multiple spatial resolutions have been integrated into the Giovanni online analysis system to support studies on land cover and land use changes,focused on the Northern Eurasia and Monsoon Asia regions through the LCLUC program. Giovanni (Goddard Interactive Online Visualization ANd aNalysis Infrastructure) is a Web-based application developed by the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC), providing a simple and intuitive way to visualize, analyze, and access Earth science remotely-sensed and modeled data.Customized Giovanni Web portals (Giovanni-NEESPI andGiovanni-MAIRS) have been created to integrate land, atmospheric,cryospheric, and societal products, enabling researchers to do quick exploration and basic analyses of land surface changes, and their relationships to climate, at global and regional scales. This presentation shows a sample Giovanni portal page, lists selected data products in the system, and illustrates potential analyses with imagesand time-series at global and regional scales, focusing on climatology and anomaly analysis. More information is available at the GES DISCMAIRS data support project portal: http:disc.sci.gsfc.nasa.govmairs.

Impact of Optimized land Surface Parameters on the Land-Atmosphere Coupling in WRF Simulations of Dry and Wet Extremes

NASA Technical Reports Server (NTRS)

Kumar, Sujay; Santanello, Joseph; Peters-Lidard, Christa; Harrison, Ken

2011-01-01

Land-atmosphere (L-A) interactions play a critical role in determining the diurnal evolution of both planetary boundary layer (PBL) and land surface temperature and moisture budgets, as well as controlling feedbacks with clouds and precipitation that lead to the persistence of dry and wet regimes. Recent efforts to quantify the strength of L-A coupling in prediction models have produced diagnostics that integrate across both the land and PBL components of the system. In this study, we examine the impact of improved specification of land surface states, anomalies, and fluxes on coupled WRF forecasts during the summers of extreme dry (2006) and wet (2007) conditions in the U.S. Southern Great Plains. The improved land initialization and surface flux parameterizations are obtained through the use of a new optimization and uncertainty module in NASA's Land Information System (LIS-OPT), whereby parameter sets are calibrated in the Noah land surface model and classified according to the land cover and soil type mapping of the observations and the full domain. The impact of the calibrated parameters on the a) spin up of land surface states used as initial conditions, and b) heat and moisture fluxes of the coupled (LIS-WRF) simulations are then assessed in terms of ambient weather, PBL budgets, and precipitation along with L-A coupling diagnostics. In addition, the sensitivity of this approach to the period of calibration (dry, wet, normal) is investigated. Finally, tradeoffs of computational tractability and scientific validity (e.g.,. relating to the representation of the spatial dependence of parameters) and the feasibility of calibrating to multiple observational datasets are also discussed.

Assessing ecological integrity using multiscale information from Bureau of Land Management Assessment and Monitoring Programs [Chapter 4

Treesearch

Sarah K. Carter; Natasha B. Carr; Curtis H. Flather; Erica Fleishman; Matthias Leu; Barry R. Noon; David J. A. Wood

2016-01-01

The Bureau of Land Management manages 246 million surface acres (100 million hectares) across the United States for multiple uses and sustained yield. Ensuring protection of ecological systems in the context of multiple, and often conflicting, resource uses and values is a challenge. Ecological integrity and land health are terms used by the Bureau of Land Management...

Integration of land use and land cover inventories for landscape management and planning in Italy.

PubMed

Sallustio, Lorenzo; Munafò, Michele; Riitano, Nicola; Lasserre, Bruno; Fattorini, Lorenzo; Marchetti, Marco

2016-01-01

There are both semantic and technical differences between land use (LU) and land cover (LC) measurements. In cartographic approaches, these differences are often neglected, giving rise to a hybrid classification. The aim of this paper is to provide a better understanding and characterization of the two classification schemes using a comparison that allows maximization of the informative power of both. The analysis was carried out in the Molise region (Central Italy) using sample information from the Italian Land Use Inventory (IUTI). The sampling points were classified with a visual interpretation of aerial photographs for both LU and LC in order to estimate surfaces and assess the changes that occurred between 2000 and 2012. The results underscore the polarization of land use and land cover changes resulting from the following: (a) recolonization of natural surfaces, (b) strong dynamisms between the LC classes in the natural and semi-natural domain and (c) urban sprawl on the lower hills and plains. Most of the observed transitions are attributable to decreases in croplands, natural grasslands and pastures, owing to agricultural abandonment. The results demonstrate that a comparison between LU and LC estimates and their changes provides an understanding of the causes of misalignment between the two criteria. Such information may be useful for planning policies in both natural and semi-natural contexts as well as in urban areas.

The Effect of Large Scale Climate Oscillations on the Land Surface Phenology of the Northern Polar Regions and Central Asia

NASA Astrophysics Data System (ADS)

de Beurs, K.; Henebry, G. M.; Owsley, B.; Sokolik, I. N.

2016-12-01

Land surface phenology metrics allow for the summarization of long image time series into a set of annual observations that describe the vegetated growing season. These metrics have been shown to respond to both large scale climatic and anthropogenic impacts. In this study we assemble a time series (2001 - 2014) of Moderate Resolution Imaging Spectroradiometer (MODIS) Nadir BRDF-Adjusted Reflectance data and land surface temperature data at 0.05º spatial resolution. We then derive land surface phenology metrics focusing on the peak of the growing season by fitting quadratic regression models using NDVI and Accumulated Growing Degree-Days (AGDD) derived from land surface temperature. We link the annual information on the peak timing, the thermal time to peak and the maximum of the growing season with five of the most important large scale climate oscillations: NAO, AO, PDO, PNA and ENSO. We demonstrate several significant correlations between the climate oscillations and the land surface phenology peak metrics for a range of different bioclimatic regions in both dryland Central Asia and the northern Polar Regions. We will then link the correlation results with trends derived by the seasonal Mann-Kendall trend detection method applied to several satellite derived vegetation and albedo datasets.

An Assessment of Land Surface and Lightning Characteristics Associated with Lightning-Initiated Wildfires

NASA Technical Reports Server (NTRS)

Coy, James; Schultz, Christopher J.; Case, Jonathan L.

2017-01-01

Can we use modeled information of the land surface and characteristics of lightning beyond flash occurrence to increase the identification and prediction of wildfires? Combine observed cloud-to-ground (CG) flashes with real-time land surface model output, and Compare data with areas where lightning did not start a wildfire to determine what land surface conditions and lightning characteristics were responsible for causing wildfires. Statistical differences between suspected fire-starters and non-fire-starters were peak-current dependent 0-10 cm Volumetric and Relative Soil Moisture comparisons were statistically dependent to at least the p = 0.05 independence level for both polarity flash types Suspected fire-starters typically occurred in areas of lower soil moisture than non-fire-starters. GVF value comparisons were only found to be statistically dependent for -CG flashes. However, random sampling of the -CG non-fire starter dataset revealed that this relationship may not always hold.

Assessing soil quality indicator under different land use and soil erosion using multivariate statistical techniques.

PubMed

Nosrati, Kazem

2013-04-01

Soil degradation associated with soil erosion and land use is a critical problem in Iran and there is little or insufficient scientific information in assessing soil quality indicator. In this study, factor analysis (FA) and discriminant analysis (DA) were used to identify the most sensitive indicators of soil quality for evaluating land use and soil erosion within the Hiv catchment in Iran and subsequently compare soil quality assessment using expert opinion based on soil surface factors (SSF) form of Bureau of Land Management (BLM) method. Therefore, 19 soil physical, chemical, and biochemical properties were measured from 56 different sampling sites covering three land use/soil erosion categories (rangeland/surface erosion, orchard/surface erosion, and rangeland/stream bank erosion). FA identified four factors that explained for 82 % of the variation in soil properties. Three factors showed significant differences among the three land use/soil erosion categories. The results indicated that based upon backward-mode DA, dehydrogenase, silt, and manganese allowed more than 80 % of the samples to be correctly assigned to their land use and erosional status. Canonical scores of discriminant functions were significantly correlated to the six soil surface indices derived of BLM method. Stepwise linear regression revealed that soil surface indices: soil movement, surface litter, pedestalling, and sum of SSF were also positively related to the dehydrogenase and silt. This suggests that dehydrogenase and silt are most sensitive to land use and soil erosion.

Venus - Venera 8 Landing Site in Navka Region

NASA Image and Video Library

1996-09-26

This image is a mosaic of 24 orbits of the Navka region of Venus. The image is centered at about 10 degrees south latitude and 335 degrees east longitude. The image is about 400 km (240 miles) across. 'Behepa 8' marks the approximate landing site of the Soviet Venera 8 lander, which took measurements at the surface of Venus in 1972. The Venera 8 lander measured granitic or continental-like materials at the landing site. Magellan data reveals the landing site to lie in a region of plains cut by tectonic ridges and troughs. Volcanic domes and flows are seen throughout the region. Studying the regional setting of the Venera landing sites is important in linking information about surface composition to surface morphology seen in radar images. Resolution of the Magellan data is about 120 meters (400 feet). http://photojournal.jpl.nasa.gov/catalog/PIA00460

New and Improved GLDAS Data Sets and Data Services at NASA GES DISC

NASA Technical Reports Server (NTRS)

Rui, Hualan; Beaudoing, Hiroko; Teng, William; Vollmer, Bruce; Rodell, Matthew; Lei, Guang-Dih

2012-01-01

The goal of a Land Data Assimilation System (LDAS) is to ingest satellite- and ground-based observational data products, using advanced land surface modeling and data assimilation techniques, in order to generate optimal fields of land surface states and fluxes data and, thereby, facilitate hydrology and climate modeling, research, and forecast. With the motivation of creating more climatologically consistent data sets, NASA GSFC's Hydrological Sciences Laboratory has generated more than 60 years (Jan. 1948-- Dec. 2008) of Global LDAS Version 2 (GLDAS-2) data, by using the Princeton Forcing Data Set and upgraded versions of Land Surface Models (LSMs). GLDAS data and data services are provided at NASA GES DISC Hydrology Data and Information Services Center (HDISC), in collaboration with HSL and LDAS.

Diagnosing hydrological limitations of a Land Surface Model: application of JULES to a deep-groundwater chalk basin

NASA Astrophysics Data System (ADS)

Le Vine, N.; Butler, A.; McIntyre, N.; Jackson, C.

2015-08-01

Land Surface Models (LSMs) are prospective starting points to develop a global hyper-resolution model of the terrestrial water, energy and biogeochemical cycles. However, there are some fundamental limitations of LSMs related to how meaningfully hydrological fluxes and stores are represented. A diagnostic approach to model evaluation is taken here that exploits hydrological expert knowledge to detect LSM inadequacies through consideration of the major behavioural functions of a hydrological system: overall water balance, vertical water redistribution in the unsaturated zone, temporal water redistribution and spatial water redistribution over the catchment's groundwater and surface water systems. Three types of information are utilised to improve the model's hydrology: (a) observations, (b) information about expected response from regionalised data, and (c) information from an independent physics-based model. The study considers the JULES (Joint UK Land Environmental Simulator) LSM applied to a deep-groundwater chalk catchment in the UK. The diagnosed hydrological limitations and the proposed ways to address them are indicative of the challenges faced while transitioning to a global high resolution model of the water cycle.

Diagnosing hydrological limitations of a land surface model: application of JULES to a deep-groundwater chalk basin

NASA Astrophysics Data System (ADS)

Le Vine, N.; Butler, A.; McIntyre, N.; Jackson, C.

2016-01-01

Land surface models (LSMs) are prospective starting points to develop a global hyper-resolution model of the terrestrial water, energy, and biogeochemical cycles. However, there are some fundamental limitations of LSMs related to how meaningfully hydrological fluxes and stores are represented. A diagnostic approach to model evaluation and improvement is taken here that exploits hydrological expert knowledge to detect LSM inadequacies through consideration of the major behavioural functions of a hydrological system: overall water balance, vertical water redistribution in the unsaturated zone, temporal water redistribution, and spatial water redistribution over the catchment's groundwater and surface-water systems. Three types of information are utilized to improve the model's hydrology: (a) observations, (b) information about expected response from regionalized data, and (c) information from an independent physics-based model. The study considers the JULES (Joint UK Land Environmental Simulator) LSM applied to a deep-groundwater chalk catchment in the UK. The diagnosed hydrological limitations and the proposed ways to address them are indicative of the challenges faced while transitioning to a global high resolution model of the water cycle.

Multi-Scale Hydrometeorological Modeling, Land Data Assimilation and Parameter Estimation with the Land Information System

NASA Technical Reports Server (NTRS)

Peters-Lidard, Christa D.; Kumar, Sujay V.; Santanello, Joseph A., Jr.; Reichle, Rolf H.

2009-01-01

The Land Information System (LIS; http://lis.gsfc.nasa.gov; Kumar et al., 2006; Peters- Lidard et al.,2007) is a flexible land surface modeling framework that has been developed with the goal of integrating satellite- and ground-based observational data products and advanced land surface modeling techniques to produce optimal fields of land surface states and fluxes. As such, LIS represents a step towards the next generation land component of an integrated Earth system model. In recognition of LIS object-oriented software design, use and impact in the land surface and hydrometeorological modeling community, the LIS software was selected ase co-winner of NASA's 2005 Software of the Year award. LIS facilitates the integration of observations from Earth-observing systems and predictions and forecasts from Earth System and Earth science models into the decision-making processes of partnering agency and national organizations. Due to its flexible software design, LIS can serve both as a Problem Solving Environment (PSE) for hydrologic research to enable accurate global water and energy cycle predictions, and as a Decision Support System (DSS) to generate useful information for application areas including disaster management, water resources management, agricultural management, numerical weather prediction, air quality and military mobility assessment. LIS has evolved from two earlier efforts North American Land Data Assimilation System (NLDAS; Mitchell et al. 2004) and Global Land Data Assimilation System (GLDAS; Rodell al. 2004) that focused primarily on improving numerical weather prediction skills by improving the characterization of the land surface conditions. Both of GLDAS and NLDAS now use specific configurations of the LIS software in their current implementations. In addition, LIS was recently transitioned into operations at the US Air Force Weather Agency (AFWA) to ultimately replace their Agricultural Meteorology (AGRMET) system, and is also used routinely by NOAA's National Centers for Environmental Prediction (NCEP)/Environmental Modeling Center (EMC) for their land data assimilation systems to support weather and climate modeling. LIS not only consolidates the capabilities of these two systems, but also enables a much larger variety of configurations with respect to horizontal spatial resolution, input datasets and choice of land surface model through "plugins,". As described in Kumar et al., 2007, and demonstrated in Case et al., 2008, and Santanello et al., 2009, LIS has been coupled to the Weather Research and Forecasting (WRF) model to support studies of land-atmosphere coupling the enabling ensembles of land surface states to be tested against multiple representations of the atmospheric boundary layer. LIS has also been demonstrated for parameter estimation as described in Peters-Lidard et al. (2008) and Santanello et al. (2007), who showed that the use of sequential remotely sensed soil moisture products can be used to derive soil hydraulic and texture properties given a sufficient dynamic range in the soil moisture retrievals and accurate precipitation inputs. LIS has also recently been demonstrated for multi-model data assimilation (Kumar et al., 2008) using an Ensemble Kalman Filter for sequential assimilation of soil moisture, snow, and temperature. Ongoing work has demonstrated the value of bias correction as part of the filter, and also that of joint calibration and assimilation. Examples and case studies demonstrating the capabilities and impacts of LIS for hydrometeoroogical modeling, assimilation and parameter estimation will be presented as advancements towards the next generation of integrated observation and modeling systems.

The EUSTACE project: delivering global, daily information on surface air temperature

NASA Astrophysics Data System (ADS)

Ghent, D.; Rayner, N. A.

2017-12-01

Day-to-day variations in surface air temperature affect society in many ways; however, daily surface air temperature measurements are not available everywhere. A global daily analysis cannot be achieved with measurements made in situ alone, so incorporation of satellite retrievals is needed. To achieve this, in the EUSTACE project (2015-2018, https://www.eustaceproject.eu) we have developed an understanding of the relationships between traditional (land and marine) surface air temperature measurements and retrievals of surface skin temperature from satellite measurements, i.e. Land Surface Temperature, Ice Surface Temperature, Sea Surface Temperature and Lake Surface Water Temperature. Here we discuss the science needed to produce a fully-global daily analysis (or ensemble of analyses) of surface air temperature on the centennial scale, integrating different ground-based and satellite-borne data types. Information contained in the satellite retrievals is used to create globally-complete fields in the past, using statistical models of how surface air temperature varies in a connected way from place to place. This includes developing new "Big Data" analysis methods as the data volumes involved are considerable. We will present recent progress along this road in the EUSTACE project, i.e.: • identifying inhomogeneities in daily surface air temperature measurement series from weather stations and correcting for these over Europe; • estimating surface air temperature over all surfaces of Earth from surface skin temperature retrievals; • using new statistical techniques to provide information on higher spatial and temporal scales than currently available, making optimum use of information in data-rich eras. Information will also be given on how interested users can become involved.

Diagnosing the Nature of Land-Atmosphere Coupling During the 2006-7 Dry/Wet Extremes in the U. S. Southern Great Plains

NASA Technical Reports Server (NTRS)

Santanello, Joseph A., Jr.; Peters-Lidard, Christa D.; Kumar, Sujay V.; Dong, Xiquan; Kennedy, Aaron D.

2011-01-01

The degree of coupling between the land surface and PBL in NWP models remains largely undiagnosed due to the complex interactions and feedbacks present across a range of scales. In this study, a framework for diagnosing local land-atmosphere coupling (LoCo) is presented using a coupled mesoscale model with observations during the summers of 2006/7 in the U.S. Southern Great Plains. Specifically, the Weather Research and Forecasting (WRF) model has been coupled to NASA's Land Information System (LIS), which enables a suite of PBL and land surface model (LSM) options along provides a flexible and high-resolution representation and initialization of land surface physics and states. This coupling is one component of a larger project to develop a NASA-Unified WRF (NU-WRF) system. A range of diagnostics exploring the feedbacks between soil moisture and precipitation are examined for the dry/wet extremes, along with the sensitivity of PBL-LSM coupling to perturbations in soil moisture.

Air transport pilots' information priorities for surface moving maps

DOT National Transportation Integrated Search

2003-10-13

The use of a surface map display for operations on or near the airport surface (taxi out, takeoff, final approach and landing, taxi in) is expected to enhance safety. There is a lack of research, however, detailing how the airport surface should be d...

Earth and space science - Oceans

NASA Technical Reports Server (NTRS)

Stewart, R. H.

1983-01-01

Satellite observations of the oceans are now being used to obtain new information about the oceanic geoid, currents, winds, tides and the interaction of the ocean with the atmosphere. In addition, satellites routinely relay information from the sea surface to laboratories on land, and determine the position of instruments drifting on the sea surface.

To the National Map and beyond

USGS Publications Warehouse

Kelmelis, J.

2003-01-01

Scientific understanding, technology, and social, economic, and environmental conditions have driven a rapidly changing demand for geographic information, both digital and analog. For more than a decade, the U.S. Geological Survey (USGS) has been developing innovative partnerships with other government agencies and private industry to produce and distribute geographic information efficiently; increase activities in remote sensing to ensure ongoing monitoring of the land surface; and develop new understanding of the causes and consequences of land surface change. These activities are now contributing to a more robust set of geographic information called The National Map (TNM). The National Map is designed to provide an up-to-date, seamless, horizontally and vertically integrated set of basic digital geographic data, a frequent monitoring of changes on the land surface, and an understanding of the condition of the Earth's surface and many of the processes that shape it. The USGS has reorganized its National Mapping Program into three programs to address the continuum of scientific activities-describing (mapping), monitoring, understanding, modeling, and predicting. The Cooperative Topographic Mapping Program focuses primarily on the mapping and revision aspects of TNM. The National Map also includes results from the Land Remote Sensing and Geographic Analysis and Monitoring Programs that provide continual updates, new insights, and analytical tools. The National Map is valuable as a framework for current research, management, and operational activities. It also provides a critical framework for the development of distributed, spatially enabled decision support systems.

Enhanced Deep Blue Aerosol Retrieval Algorithm: The Second Generation

NASA Technical Reports Server (NTRS)

Hsu, N. C.; Jeong, M.-J.; Bettenhausen, C.; Sayer, A. M.; Hansell, R.; Seftor, C. S.; Huang, J.; Tsay, S.-C.

2013-01-01

The aerosol products retrieved using the MODIS collection 5.1 Deep Blue algorithm have provided useful information about aerosol properties over bright-reflecting land surfaces, such as desert, semi-arid, and urban regions. However, many components of the C5.1 retrieval algorithm needed to be improved; for example, the use of a static surface database to estimate surface reflectances. This is particularly important over regions of mixed vegetated and non- vegetated surfaces, which may undergo strong seasonal changes in land cover. In order to address this issue, we develop a hybrid approach, which takes advantage of the combination of pre-calculated surface reflectance database and normalized difference vegetation index in determining the surface reflectance for aerosol retrievals. As a result, the spatial coverage of aerosol data generated by the enhanced Deep Blue algorithm has been extended from the arid and semi-arid regions to the entire land areas.

Computer-implemented land use classification with pattern recognition software and ERTS digital data. [Mississippi coastal plains

NASA Technical Reports Server (NTRS)

Joyce, A. T.

1974-01-01

Significant progress has been made in the classification of surface conditions (land uses) with computer-implemented techniques based on the use of ERTS digital data and pattern recognition software. The supervised technique presently used at the NASA Earth Resources Laboratory is based on maximum likelihood ratioing with a digital table look-up approach to classification. After classification, colors are assigned to the various surface conditions (land uses) classified, and the color-coded classification is film recorded on either positive or negative 9 1/2 in. film at the scale desired. Prints of the film strips are then mosaicked and photographed to produce a land use map in the format desired. Computer extraction of statistical information is performed to show the extent of each surface condition (land use) within any given land unit that can be identified in the image. Evaluations of the product indicate that classification accuracy is well within the limits for use by land resource managers and administrators. Classifications performed with digital data acquired during different seasons indicate that the combination of two or more classifications offer even better accuracy.

Rapid prototyping of soil moisture estimates using the NASA Land Information System

NASA Astrophysics Data System (ADS)

Anantharaj, V.; Mostovoy, G.; Li, B.; Peters-Lidard, C.; Houser, P.; Moorhead, R.; Kumar, S.

2007-12-01

The Land Information System (LIS), developed at the NASA Goddard Space Flight Center, is a functional Land Data Assimilation System (LDAS) that incorporates a suite of land models in an interoperable computational framework. LIS has been integrated into a computational Rapid Prototyping Capabilities (RPC) infrastructure. LIS consists of a core, a number of community land models, data servers, and visualization systems - integrated in a high-performance computing environment. The land surface models (LSM) in LIS incorporate surface and atmospheric parameters of temperature, snow/water, vegetation, albedo, soil conditions, topography, and radiation. Many of these parameters are available from in-situ observations, numerical model analysis, and from NASA, NOAA, and other remote sensing satellite platforms at various spatial and temporal resolutions. The computational resources, available to LIS via the RPC infrastructure, support e- Science experiments involving the global modeling of land-atmosphere studies at 1km spatial resolutions as well as regional studies at finer resolutions. The Noah Land Surface Model, available with-in the LIS is being used to rapidly prototype soil moisture estimates in order to evaluate the viability of other science applications for decision making purposes. For example, LIS has been used to further extend the utility of the USDA Soil Climate Analysis Network of in-situ soil moisture observations. In addition, LIS also supports data assimilation capabilities that are used to assimilate remotely sensed soil moisture retrievals from the AMSR-E instrument onboard the Aqua satellite. The rapid prototyping of soil moisture estimates using LIS and their applications will be illustrated during the presentation.

ERTS-1 Role in land management and planning in Minnesota

NASA Technical Reports Server (NTRS)

Sizer, J. E.; Brown, D. A.

1974-01-01

Research on applications of ERTS-1 imagery to land use has focused on evaluating the ability of ERTS-1 imagery to update and refine the detail of land use information in the Minnesota Land Management Information System. Work has been directed toward defining the capabilities of the ERTS-1 system to provide information about surface cover by identifying forest, water, and wetland resources; urban and agricultural development: and testing and evaluating data input and output procedures. As capabilities were developed, meetings were held with administrators and resource information users from various agencies of government to identify their information needs. A full scale systems test for several selected pilot areas in the state is nearly complete. Users have been identified for each test area and they have been instrumental in identifying data requirements and analysis needs for administrative purposes. Users have both rural and urban orientations and provide a basis for evaluation of the results.

Toward Improved Land Surface Initialization in Support of Regional WRF Forecasts at the Kenya Meteorological Service (KMS)

NASA Technical Reports Server (NTRS)

Case, Johnathan L.; Mungai, John; Sakwa, Vincent; Kabuchanga, Eric; Zavodsky, Bradley T.; Limaye, Ashutosh S.

2014-01-01

Flooding and drought are two key forecasting challenges for the Kenya Meteorological Service (KMS). Atmospheric processes leading to excessive precipitation and/or prolonged drought can be quite sensitive to the state of the land surface, which interacts with the planetary boundary layer (PBL) of the atmosphere providing a source of heat and moisture. The development and evolution of precipitation systems are affected by heat and moisture fluxes from the land surface, particularly within weakly-sheared environments such as in the tropics and sub-tropics. These heat and moisture fluxes during the day can be strongly influenced by land cover, vegetation, and soil moisture content. Therefore, it is important to represent the land surface state as accurately as possible in land surface and numerical weather prediction (NWP) models. Enhanced regional modeling capabilities have the potential to improve forecast guidance in support of daily operations and high-impact weather over eastern Africa. KMS currently runs a configuration of the Weather Research and Forecasting (WRF) NWP model in real time to support its daily forecasting operations, making use of the NOAA/National Weather Service (NWS) Science and Training Resource Center's Environmental Modeling System (EMS) to manage and produce the KMS-WRF runs on a regional grid over eastern Africa. Two organizations at the NASA Marshall Space Flight Center in Huntsville, AL, SERVIR and the Shortterm Prediction Research and Transition (SPoRT) Center, have established a working partnership with KMS for enhancing its regional modeling capabilities through new datasets and tools. To accomplish this goal, SPoRT and SERVIR is providing enhanced, experimental land surface initialization datasets and model verification capabilities to KMS as part of this collaboration. To produce a land-surface initialization more consistent with the resolution of the KMS-WRF runs, the NASA Land Information System (LIS) is run at a comparable resolution to provide real-time, daily soil initialization data in place of data interpolated from the National Centers for Environmental Prediction (NCEP) Global Forecast System (GFS) model soil moisture and temperature fields. Additionally, realtime green vegetation fraction (GVF) data from the Visible Infrared Imaging Radiometer Suite (VIIRS) on the Suomi National Polar-orbiting Partnership (Suomi- NPP) satellite will be incorporated into the KMS-WRF runs, once it becomes publicly available from the National Environmental Satellite Data and Information Service (NESDIS). Finally, model verification capabilities will be transitioned to KMS using the Model Evaluation Tools (MET; Brown et al. 2009) package in conjunction with a dynamic scripting package developed by SPoRT (Zavodsky et al. 2014), to help quantify possible improvements in simulated temperature, moisture and precipitation resulting from the experimental land surface initialization. Furthermore, the transition of these MET tools will enable KMS to monitor model forecast accuracy in near real time. This paper presents preliminary efforts to improve land surface model initialization over eastern Africa in support of operations at KMS. The remainder of this extended abstract is organized as follows: The collaborating organizations involved in the project are described in Section 2; background information on LIS and the configuration for eastern Africa is presented in Section 3; the WRF configuration used in this modeling experiment is described in Section 4; sample experimental WRF output with and without LIS initialization data are given in Section 5; a summary is given in Section 6 followed by acknowledgements and references.

Assessing the Effects of Irrigation on Land Surface Processes Utilizing CLM.PF in Los Angeles, California

NASA Astrophysics Data System (ADS)

Reyes, B.; Vahmani, P.; Hogue, T. S.; Maxwell, R. M.

2013-05-01

Irrigation can significantly alter land surface properties including increases in evapotranspiration (ET) and latent heat flux and a decrease in land surface temperatures that have a wide range of effects on the hydrologic cycle. However, most irrigation in land surface modeling studies has generally been limited to large-scale cropland applications while ignoring the, relatively, much smaller use of irrigation in urban areas. Although this assumption may be valid in global studies, as we seek to apply models at higher resolutions and at more local scales, irrigation in urban areas can become a key factor in land-atmosphere interactions. Landscape irrigation can account for large portions of residential urban water use, especially in semi-arid environments (e.g. ~50% in Los Angeles, CA). Previous modeling efforts in urbanized semi-arid regions have shown that disregarding irrigation leads to inaccurate representation of the energy budget. The current research models a 49.5-km2 (19.11-mi2) domain near downtown Los Angeles in the Ballona Creek watershed at a high spatial and temporal resolution using a coupled hydrologic (ParFlow) and land surface model (CLM). Our goals are to (1) provide a sensitivity analysis for urban irrigation parameters including sensitivity to total volume and timing of irrigation, (2) assess the effects of irrigation on varying land cover types on the energy budget, and (3) evaluate if residential water use data is useful in providing estimates for irrigation in land surface modeling. Observed values of land surface parameters from remote sensing products (Land Surface Temperature and ET), water use data from the Los Angeles Department of Water and Power (LADWP), and modeling results from an irrigated version of the NOAH-Urban Canopy Model are being used for comparison and evaluation. Our analysis provides critical information on the degree to which urban irrigation should be represented in high-resolution, semi-arid urban land surface modeling of the region. This research also yields robust upper-boundary conditions for further analysis and modeling in Los Angeles.

Global Land Surface Temperature From the Along-Track Scanning Radiometers

NASA Astrophysics Data System (ADS)

Ghent, D. J.; Corlett, G. K.; Göttsche, F.-M.; Remedios, J. J.

2017-11-01

The Leicester Along-Track Scanning Radiometer (ATSR) and Sea and Land Surface Temperature Radiometer (SLSTR) Processor for LAnd Surface Temperature (LASPLAST) provides global land surface temperature (LST) products from thermal infrared radiance data. In this paper, the state-of-the-art version of LASPLAST, as deployed in the GlobTemperature project, is described and applied to data from the Advanced Along-Track Scanning Radiometer (AATSR). The LASPLAST retrieval formulation for LST is a nadir-only, two-channel, split-window algorithm, based on biome classification, fractional vegetation, and across-track water vapor dependences. It incorporates globally robust retrieval coefficients derived using highly sampled atmosphere profiles. LASPLAST benefits from appropriate spatial resolution auxiliary information and a new probabilistic-based cloud flagging algorithm. For the first time for a satellite-derived LST product, pixel-level uncertainties characterized in terms of random, locally correlated, and systematic components are provided. The new GlobTemperature GT_ATS_2P Version 1.0 product has been validated for 1 year of AATSR data (2009) against in situ measurements acquired from "gold standard reference" stations: Gobabeb, Namibia, and Evora, Portugal; seven Surface Radiation Budget stations, and the Atmospheric Radiation Measurement station at Southern Great Plains. These data show average absolute biases for the GT_ATS_2P Version 1.0 product of 1.00 K in the daytime and 1.08 K in the nighttime. The improvements in data provenance including better accuracy, fully traceable retrieval coefficients, quantified uncertainty, and more detailed information in the new harmonized format of the GT_ATS_2P product will allow for more significant exploitation of the historical LST data record from the ATSRs and a valuable near-real-time service from the Sea and Land Surface Temperature Radiometers (SLSTRs).

Documentation of a digital spatial data base for hydrologic investigations, Broward County, Florida

USGS Publications Warehouse

Sonenshein, R.S.

1992-01-01

Geographic information systems have become an important tool in planning for the protection and development of natural resources, including ground water and surface water. A digital spatial data base consisting of 18 data layers that can be accessed by a geographic information system was developed for Broward County, Florida. Five computer programs, including one that can be used to create documentation files for each data layer and four that can be used to create data layers from data files not already in geographic information system format, were also developed. Four types of data layers have been developed. Data layers for manmade features include major roads, municipal boundaries, the public land-survey section grid, land use, and underground storage tank facilities. The data layer for topographic features consists of surveyed point land-surface elevations. Data layers for hydrologic features include surface-water and rainfall data-collection stations, surface-water bodies, water-control district boundaries, and water-management basins. Data layers for hydrogeologic features include soil associations, transmissivity polygons, hydrogeologic unit depths, and a finite-difference model grid for south-central Broward County. Each data layer is documented as to the extent of the features, number of features, scale, data sources, and a description of the attribute tables where applicable.

10 CFR 61.12 - Specific technical information.

Code of Federal Regulations, 2010 CFR

2010-01-01

... NUCLEAR REGULATORY COMMISSION (CONTINUED) LICENSING REQUIREMENTS FOR LAND DISPOSAL OF RADIOACTIVE WASTE... of the land disposal facility and the disposal units. For near-surface disposal, the description must...; structural stability of backfill, wastes, and covers; contact of wastes with standing water; disposal site...

10 CFR 61.12 - Specific technical information.

Code of Federal Regulations, 2014 CFR

2014-01-01

... NUCLEAR REGULATORY COMMISSION (CONTINUED) LICENSING REQUIREMENTS FOR LAND DISPOSAL OF RADIOACTIVE WASTE... of the land disposal facility and the disposal units. For near-surface disposal, the description must...; structural stability of backfill, wastes, and covers; contact of wastes with standing water; disposal site...

10 CFR 61.12 - Specific technical information.

Code of Federal Regulations, 2012 CFR

2012-01-01

... NUCLEAR REGULATORY COMMISSION (CONTINUED) LICENSING REQUIREMENTS FOR LAND DISPOSAL OF RADIOACTIVE WASTE... of the land disposal facility and the disposal units. For near-surface disposal, the description must...; structural stability of backfill, wastes, and covers; contact of wastes with standing water; disposal site...

10 CFR 61.12 - Specific technical information.

Code of Federal Regulations, 2013 CFR

2013-01-01

... NUCLEAR REGULATORY COMMISSION (CONTINUED) LICENSING REQUIREMENTS FOR LAND DISPOSAL OF RADIOACTIVE WASTE... of the land disposal facility and the disposal units. For near-surface disposal, the description must...; structural stability of backfill, wastes, and covers; contact of wastes with standing water; disposal site...

10 CFR 61.12 - Specific technical information.

Code of Federal Regulations, 2011 CFR

2011-01-01

... NUCLEAR REGULATORY COMMISSION (CONTINUED) LICENSING REQUIREMENTS FOR LAND DISPOSAL OF RADIOACTIVE WASTE... of the land disposal facility and the disposal units. For near-surface disposal, the description must...; structural stability of backfill, wastes, and covers; contact of wastes with standing water; disposal site...

Likelihood parameter estimation for calibrating a soil moisture using radar backscatter

USDA-ARS?s Scientific Manuscript database

Assimilating soil moisture information contained in synthetic aperture radar imagery into land surface model predictions can be done using a calibration, or parameter estimation, approach. The presence of speckle, however, necessitates aggregating backscatter measurements over large land areas in or...

The EUSTACE project: delivering global, daily information on surface air temperature

NASA Astrophysics Data System (ADS)

Rayner, Nick

2017-04-01

Day-to-day variations in surface air temperature affect society in many ways; however, daily surface air temperature measurements are not available everywhere. A global daily analysis cannot be achieved with measurements made in situ alone, so incorporation of satellite retrievals is needed. To achieve this, in the EUSTACE project (2015-June 2018, https://www.eustaceproject.eu) we are developing an understanding of the relationships between traditional (land and marine) surface air temperature measurements and retrievals of surface skin temperature from satellite measurements, i.e. Land Surface Temperature, Ice Surface Temperature, Sea Surface Temperature and Lake Surface Water Temperature. Here we discuss the science needed to produce a fully-global daily analysis (or ensemble of analyses) of surface air temperature on the centennial scale, integrating different ground-based and satellite-borne data types. Information contained in the satellite retrievals is used to create globally-complete fields in the past, using statistical models of how surface air temperature varies in a connected way from place to place. As the data volumes involved are considerable, such work needs to include development of new "Big Data" analysis methods. We will present recent progress along this road in the EUSTACE project: 1. providing new, consistent, multi-component estimates of uncertainty in surface skin temperature retrievals from satellites; 2. identifying inhomogeneities in daily surface air temperature measurement series from weather stations and correcting for these over Europe; 3. estimating surface air temperature over all surfaces of Earth from surface skin temperature retrievals; 4. using new statistical techniques to provide information on higher spatial and temporal scales than currently available, making optimum use of information in data-rich eras. Information will also be given on how interested users can become involved.

The EUSTACE project: delivering global, daily information on surface air temperature

NASA Astrophysics Data System (ADS)

Ghent, D.; Rayner, N. A.

2016-12-01

Day-to-day variations in surface air temperature affect society in many ways; however, daily surface air temperature measurements are not available everywhere. A global daily analysis cannot be achieved with measurements made in situ alone, so incorporation of satellite retrievals is needed. To achieve this, in the EUSTACE project (2015-June 2018, https://www.eustaceproject.eu) we are developing an understanding of the relationships between traditional (land and marine) surface air temperature measurements and retrievals of surface skin temperature from satellite measurements, i.e. Land Surface Temperature, Ice Surface Temperature, Sea Surface Temperature and Lake Surface Water Temperature. Here we discuss the science needed to produce a fully-global daily analysis (or ensemble of analyses) of surface air temperature on the centennial scale, integrating different ground-based and satellite-borne data types. Information contained in the satellite retrievals is used to create globally-complete fields in the past, using statistical models of how surface air temperature varies in a connected way from place to place. As the data volumes involved are considerable, such work needs to include development of new "Big Data" analysis methods. We will present recent progress along this road in the EUSTACE project, i.e.: • providing new, consistent, multi-component estimates of uncertainty in surface skin temperature retrievals from satellites; • identifying inhomogeneities in daily surface air temperature measurement series from weather stations and correcting for these over Europe; • estimating surface air temperature over all surfaces of Earth from surface skin temperature retrievals; • using new statistical techniques to provide information on higher spatial and temporal scales than currently available, making optimum use of information in data-rich eras. Information will also be given on how interested users can become involved.

Geographic analysis and monitoring at the United States Geological Survey

USGS Publications Warehouse

Findley, J.

2003-01-01

The Geographic Analysis and Monitoring (GAM) Program of the U.S. Geological Survey assesses the Nation's land surface at a variety of spatial and temporal scales to understand the rates, causes, and consequences of natural and human-induced processes and their interactions that affect the landscape over time. The program plays an important role in developing National Map tools and application. The GAM is a science and synthesis program that not only assesses the rates of changes to the Earth's land surface, but also provides reports on the status and trends of the Nation's land resources on a periodic basis, produces a land-use and land- cover database for the periodically updated map and data set-the Geographic Face of the Nation, and conducts research leading to improved understanding and knowledge about geographic processes. Scientific investigations provide comprehensive information needed to understand the environmental, resource, and economic consequences of landscape change. These analyses responds to the needs of resource managers and offers the American public baseline information to help them understand the dynamic nature of our national landscape and to anticipate the opportunities and consequences of our actions.

Linking land cover and water quality in New York City's water supply watersheds.

PubMed

Mehaffey, M H; Nash, M S; Wade, T G; Ebert, D W; Jones, K B; Rager, A

2005-08-01

The Catskill/Delaware reservoirs supply 90% of New York City's drinking water. The City has implemented a series of watershed protection measures, including land acquisition, aimed at preserving water quality in the Catskill/Delaware watersheds. The objective of this study was to examine how relationships between landscape and surface water measurements change between years. Thirty-two drainage areas delineated from surface water sample points (total nitrogen, total phosphorus, and fecal coliform bacteria concentrations) were used in step-wise regression analyses to test landscape and surface-water quality relationships. Two measurements of land use, percent agriculture and percent urban development, were positively related to water quality and consistently present in all regression models. Together these two land uses explained 25 to 75% of the regression model variation. However, the contribution of agriculture to water quality condition showed a decreasing trend with time as overall agricultural land cover decreased. Results from this study demonstrate that relationships between land cover and surface water concentrations of total nitrogen, total phosphorus, and fecal coliform bacteria counts over a large area can be evaluated using a relatively simple geographic information system method. Land managers may find this method useful for targeting resources in relation to a particular water quality concern, focusing best management efforts, and maximizing benefits to water quality with minimal costs.

[Study of the microwave emissivity characteristics over different land cover types].

PubMed

Zhang, Yong-Pan; Jiang, Ling-Mei; Qiu, Yu-Bao; Wu, Sheng-Li; Shi, Jian-Cheng; Zhang, Li-Xin

2010-06-01

The microwave emissivity over land is very important for describing the characteristics of the lands, and it is also a key factor for retrieving the parameters of land and atmosphere. Different land covers have their emission behavior as a function of structure, water content, and surface roughness. In the present study the global land surface emissivities were calculated using six month (June, 2003-August, 2003, Dec, 2003-Feb, 2004) AMSR-E L2A brightness temperature, MODIS land surface temperature and the layered atmosphere temperature, and humidity and pressure profiles data retrieved from MODIS/Aqua under clear sky conditions. With the information of IGBP land cover types, "pure" pixels were used, which are defined when the fraction cover of each land type is larger than 85%. Then, the emissivity of sixteen land covers at different frequencies, polarization and their seasonal variation were analyzed respectively. The results show that the emissivity of vegetation including forests, grasslands and croplands is higher than that over bare soil, and the polarization difference of vegetation is smaller than that of bare soil. In summer, the emissivity of vegetation is relatively stable because it is in bloom, therefore the authors can use it as its emissivity in our microwave emissivity database over different land cover types. Furthermore, snow cover can heavily impact the change in land cover emissivity, especially in winter.

National Satellite Land Remote Sensing Data Archive

USGS Publications Warehouse

Faundeen, John L.; Kelly, Francis P.; Holm, Thomas M.; Nolt, Jenna E.

2013-01-01

The National Satellite Land Remote Sensing Data Archive (NSLRSDA) resides at the U.S. Geological Survey's (USGS) Earth Resources Observation and Science (EROS) Center. Through the Land Remote Sensing Policy Act of 1992, the U.S. Congress directed the Department of the Interior (DOI) to establish a permanent Government archive containing satellite remote sensing data of the Earth's land surface and to make this data easily accessible and readily available. This unique DOI/USGS archive provides a comprehensive, permanent, and impartial observational record of the planet's land surface obtained throughout more than five decades of satellite remote sensing. Satellite-derived data and information products are primary sources used to detect and understand changes such as deforestation, desertification, agricultural crop vigor, water quality, invasive plant species, and certain natural hazards such as flood extent and wildfire scars.

A Method for Estimating the Direction of Gravitational Acceleration in the Active Phase of a Spacecraft Landing on the Martian Surface

NASA Astrophysics Data System (ADS)

Likhachev, V. N.; Fedotov, V. P.

2017-12-01

We know the spacecraft orientation before its touchdown on the Martian surface with an accuracy of 3-4°. The spacecraft control can result in a significant horizontal velocity at altitudes lower than 15 meters at the instant when the landing legs contact the surface when data from the radar location system terminates. An independent method for determining the gravity acceleration vector is presented in the paper. This method is implemented using information obtained from the gyro-inertial and radar instrumentation.

The CEOS-Land Surface Imaging Constellation Portal for GEOSS: A resource for land surface imaging system information and data access

USGS Publications Warehouse

Holm, Thomas; Gallo, Kevin P.; Bailey, Bryan

2010-01-01

The Committee on Earth Observation Satellites is an international group that coordinates civil space-borne observations of the Earth, and provides the space component of the Global Earth Observing System of Systems (GEOSS). The CEOS Virtual Constellations concept was implemented in an effort to engage and coordinate disparate Earth observing programs of CEOS member agencies and ultimately facilitate their contribution in supplying the space-based observations required to satisfy the requirements of the GEOSS. The CEOS initially established Study Teams for four prototype constellations that included precipitation, land surface imaging, ocean surface topography, and atmospheric composition. The basic mission of the Land Surface Imaging (LSI) Constellation [1] is to promote the efficient, effective, and comprehensive collection, distribution, and application of space-acquired image data of the global land surface, especially to meet societal needs of the global population, such as those addressed by the nine Group on Earth Observations (GEO) Societal Benefit Areas (SBAs) of agriculture, biodiversity, climate, disasters, ecosystems, energy, health, water, and weather. The LSI Constellation Portal is the result of an effort to address important goals within the LSI Constellation mission and provide resources to assist in planning for future space missions that might further contribute to meeting those goals.

Assimilation of SMOS Retrieved Soil Moisture into the Land Information System

NASA Technical Reports Server (NTRS)

Blankenship, Clay; Case, Jonathan; Zavodsky, Bradley; Jedlovec, Gary

2014-01-01

Soil moisture retrievals from the Soil Moisture and Ocean Salinity (SMOS) instrument are assimilated into the Noah land surface model (LSM) within the NASA Land Information System (LIS). Before assimilation, SMOS retrievals are bias-corrected to match the model climatological distribution using a Cumulative Distribution Function (CDF) matching approach. Data assimilation is done via the Ensemble Kalman Filter. The goal is to improve the representation of soil moisture within the LSM, and ultimately to improve numerical weather forecasts through better land surface initialization. We present a case study showing a large area of irrigation in the lower Mississippi River Valley, in an area with extensive rice agriculture. High soil moisture value in this region are observed by SMOS, but not captured in the forcing data. After assimilation, the model fields reflect the observed geographic patterns of soil moisture. Plans for a modeling experiment and operational use of the data are given. This work helps prepare for the assimilation of Soil Moisture Active/Passive (SMAP) retrievals in the near future.

Toward Improved Land Surface Initialization in Support of Regional WRF Forecasts at the Kenya Meteorological Department

NASA Technical Reports Server (NTRS)

Case. Jonathan; Mungai, John; Sakwa, Vincent; Kabuchanga, Eric; Zavodsky, Bradley T.; Limaye, Ashutosh S.

2014-01-01

Flooding and drought are two key forecasting challenges for the Kenya Meteorological Department (KMD). Atmospheric processes leading to excessive precipitation and/or prolonged drought can be quite sensitive to the state of the land surface, which interacts with the boundary layer of the atmosphere providing a source of heat and moisture. The development and evolution of precipitation systems are affected by heat and moisture fluxes from the land surface within weakly-sheared environments, such as in the tropics and sub-tropics. These heat and moisture fluxes during the day can be strongly influenced by land cover, vegetation, and soil moisture content. Therefore, it is important to represent the land surface state as accurately as possible in numerical weather prediction models. Enhanced regional modeling capabilities have the potential to improve forecast guidance in support of daily operations and high-end events over east Africa. KMD currently runs a configuration of the Weather Research and Forecasting (WRF) model in real time to support its daily forecasting operations, invoking the Nonhydrostatic Mesoscale Model (NMM) dynamical core. They make use of the National Oceanic and Atmospheric Administration / National Weather Service Science and Training Resource Center's Environmental Modeling System (EMS) to manage and produce the WRF-NMM model runs on a 7-km regional grid over eastern Africa. Two organizations at the National Aeronautics and Space Administration Marshall Space Flight Center in Huntsville, AL, SERVIR and the Short-term Prediction Research and Transition (SPoRT) Center, have established a working partnership with KMD for enhancing its regional modeling capabilities. To accomplish this goal, SPoRT and SERVIR will provide experimental land surface initialization datasets and model verification capabilities to KMD. To produce a land-surface initialization more consistent with the resolution of the KMD-WRF runs, the NASA Land Information System (LIS) will be run at a comparable resolution to provide real-time, daily soil initialization data in place of interpolated Global Forecast System soil moisture and temperature data. Additionally, real-time green vegetation fraction data from the Visible Infrared Imaging Radiometer Suite will be incorporated into the KMD-WRF runs, once it becomes publicly available from the National Environmental Satellite Data and Information Service. Finally, model verification capabilities will be transitioned to KMD using the Model Evaluation Tools (MET) package, in order to quantify possible improvements in simulated temperature, moisture and precipitation resulting from the experimental land surface initialization. The transition of these MET tools will enable KMD to monitor model forecast accuracy in near real time. This presentation will highlight preliminary verification results of WRF runs over east Africa using the LIS land surface initialization.

Hydrological Response to Land Cover Changes and Human Activities in Arid Regions Using a Geographic Information System and Remote Sensing

PubMed Central

Mahmoud, Shereif H.; Alazba, A. A.

2015-01-01

The hydrological response to land cover changes induced by human activities in arid regions has attracted increased research interest in recent decades. The study reported herein assessed the spatial and quantitative changes in surface runoff resulting from land cover change in the Al-Baha region of Saudi Arabia between 1990 and 2000 using an ArcGIS-surface runoff model and predicted land cover and surface runoff depth in 2030 using Markov chain analysis. Land cover maps for 1990 and 2000 were derived from satellite images using ArcGIS 10.1. The findings reveal a 26% decrease in forest and shrubland area, 28% increase in irrigated cropland, 1.5% increase in sparsely vegetated land and 0.5% increase in bare soil between 1990 and 2000. Overall, land cover changes resulted in a significant decrease in runoff depth values in most of the region. The decrease in surface runoff depth ranged from 25-106 mm/year in a 7020-km2 area, whereas the increase in such depth reached only 10 mm/year in a 243-km2 area. A maximum increase of 73 mm/year was seen in a limited area. The surface runoff depth decreased to the greatest extent in the central region of the study area due to the huge transition in land cover classes associated with the construction of 25 rainwater harvesting dams. The land cover prediction revealed a greater than twofold increase in irrigated cropland during the 2000-2030 period, whereas forest and shrubland are anticipated to occupy just 225 km2 of land area by 2030, a significant decrease from the 747 km2 they occupied in 2000. Overall, changes in land cover are predicted to result in an annual increase in irrigated cropland and dramatic decline in forest area in the study area over the next few decades. The increase in surface runoff depth is likely to have significant implications for irrigation activities. PMID:25923712

L-band Microwave Remote Sensing and Land Data Assimilation Improve the Representation of Prestorm Soil Moisture Conditions for Hydrologic Forecasting

NASA Technical Reports Server (NTRS)

Crow, W. T.; Chen, F.; Reichle, R. H.; Liu, Q.

2017-01-01

Recent advances in remote sensing and land data assimilation purport to improve the quality of antecedent soil moisture information available for operational hydrologic forecasting. We objectively validate this claim by calculating the strength of the relationship between storm-scale runoff ratio (i.e., total stream flow divided by total rainfall accumulation in depth units) and pre-storm surface soil moisture estimates from a range of surface soil moisture data products. Results demonstrate that both satellite-based, L-band microwave radiometry and the application of land data assimilation techniques have significantly improved the utility of surface soil moisture data sets for forecasting stream flow response to future rainfall events.

Soil Moisture or Groundwater?

NASA Astrophysics Data System (ADS)

Swenson, S. C.; Lawrence, D. M.

2017-12-01

Partitioning the vertically integrated water storage variations estimated from GRACE satellite data into the components of which it is comprised requires independent information. Land surface models, which simulate the transfer and storage of moisture and energy at the land surface, are often used to estimate water storage variability of snow, surface water, and soil moisture. To obtain an estimate of changes in groundwater, the estimates of these storage components are removed from GRACE data. Biases in the modeled water storage components are therefore present in the residual groundwater estimate. In this study, we examine how soil moisture variability, estimated using the Community Land Model (CLM), depends on the vertical structure of the model. We then explore the implications of this uncertainty in the context of estimating groundwater variations using GRACE data.

L-band microwave remote sensing and land data assimilation improve the representation of pre-storm soil moisture conditions for hydrologic forecasting.

PubMed

Crow, W T; Chen, F; Reichle, R H; Liu, Q

2017-06-16

Recent advances in remote sensing and land data assimilation purport to improve the quality of antecedent soil moisture information available for operational hydrologic forecasting. We objectively validate this claim by calculating the strength of the relationship between storm-scale runoff ratio (i.e., total stream flow divided by total rainfall accumulation in depth units) and pre-storm surface soil moisture estimates from a range of surface soil moisture data products. Results demonstrate that both satellite-based, L-band microwave radiometry and the application of land data assimilation techniques have significantly improved the utility of surface soil moisture data sets for forecasting stream flow response to future rainfall events.

L-band microwave remote sensing and land data assimilation improve the representation of pre-storm soil moisture conditions for hydrologic forecasting

PubMed Central

Crow, W.T.; Chen, F.; Reichle, R.H.; Liu, Q.

2018-01-01

Recent advances in remote sensing and land data assimilation purport to improve the quality of antecedent soil moisture information available for operational hydrologic forecasting. We objectively validate this claim by calculating the strength of the relationship between storm-scale runoff ratio (i.e., total stream flow divided by total rainfall accumulation in depth units) and pre-storm surface soil moisture estimates from a range of surface soil moisture data products. Results demonstrate that both satellite-based, L-band microwave radiometry and the application of land data assimilation techniques have significantly improved the utility of surface soil moisture data sets for forecasting stream flow response to future rainfall events. PMID:29657342

Overview of the Mars Exploration Rover Mission

NASA Astrophysics Data System (ADS)

Adler, M.

2002-12-01

The Mars Exploration Rover (MER) Project is an ambitious mission to land two highly capable rovers at different sites in the equatorial region of Mars. The two vehicles are launched separately in May through July of 2003. Mars surface operations begin on January 4, 2004 with the first landing, followed by the second landing three weeks later on January 25. The useful surface lifetime of each rover will be at least 90 sols. The science objectives of exploring multiple locations within each of two widely separated and scientifically distinct landing sites will be accomplished along with the demonstration of key surface exploration technologies for future missions. The two MER spacecraft are planned to be identical. The rovers are landed using the Mars Pathfinder approach of a heatshield and parachute to slow the vehicle relative to the atmosphere, solid rockets to slow the lander near the surface, and airbags to cushion the surface impacts. During entry, descent, and landing, the vehicles will transmit coded tones directly to Earth, and in the terminal descent phase will also transmit telemetry to the MGS orbiter to indicate progress through the critical events. Once the lander rolls to a stop, a tetrahedral structure opens to right the lander and to reveal the folded rover, which then deploys and later by command will roll off of the lander to begin its exploration. Each six-wheeled rover carries a suite of instruments to collect contextual information about the landing site using visible and thermal infrared remote sensing, and to collect in situ information on the composition, mineralogy, and texture of selected Martian soils and rocks using an arm-mounted microscopic imager, rock abrasion tool, and spectrometers. During their surface missions, the rovers will communicate with Earth directly through the Deep Space Network as well as indirectly through the Odyssey and MGS orbiters. The solar-powered rovers will be commanded in the morning of each Sol, with the results returned in the afternoon of that Sol guiding the plans for the following Sol. Between the command sessions, the rover will autonomously execute the requested activities, including as an example traverses of tens of meters using autonomous navigation and hazard avoidance.

Using semi-variogram analysis for providing spatially distributed information on soil surface condition for land surface modeling

NASA Astrophysics Data System (ADS)

Croft, Holly; Anderson, Karen; Kuhn, Nikolaus J.

2010-05-01

The ability to quantitatively and spatially assess soil surface roughness is important in geomorphology and land degradation studies. Soils can experience rapid structural degradation in response to land cover changes, resulting in increased susceptibility to erosion and a loss of Soil Organic Matter (SOM). Changes in soil surface condition can also alter sediment detachment, transport and deposition processes, infiltration rates and surface runoff characteristics. Deriving spatially distributed quantitative information on soil surface condition for inclusion in hydrological and soil erosion models is therefore paramount. However, due to the time and resources involved in using traditional field sampling techniques, there is a lack of spatially distributed information on soil surface condition. Laser techniques can provide data for a rapid three dimensional representation of the soil surface at a fine spatial resolution. This provides the ability to capture changes at the soil surface associated with aggregate breakdown, flow routing, erosion and sediment re-distribution. Semi-variogram analysis of the laser data can be used to represent spatial dependence within the dataset; providing information about the spatial character of soil surface structure. This experiment details the ability of semi-variogram analysis to spatially describe changes in soil surface condition. Soil for three soil types (silt, silt loam and silty clay) was sieved to produce aggregates between 1 mm and 16 mm in size and placed evenly in sample trays (25 x 20 x 2 cm). Soil samples for each soil type were exposed to five different durations of artificial rainfall, to produce progressively structurally degraded soil states. A calibrated laser profiling instrument was used to measure surface roughness over a central 10 x 10 cm plot of each soil state, at 2 mm sample spacing. The laser data were analysed within a geostatistical framework, where semi-variogram analysis quantitatively represented the change in soil surface structure during crusting. The laser data were also used to create digital surface models (DSM) of the soil states for visual comparison. This research has shown that aggregate breakdown and soil crusting can be shown quantitatively by a decrease in sill variance (silt soil: 11.67 (control) to 1.08 (after 90 mins rainfall)). Features present within semi-variograms were spatially linked to features at the soil surface, such as soil cracks, tillage lines and areas of deposition. Directional semi-variograms were used to provide a spatially orientated component, where the directional sill variance associated with a soil crack was shown to increase from 7.95 to 19.33. Periodicity within semi-variogram was also shown to quantify the spatial scale of soil cracking networks and potentially surface flowpaths; an average distance between soil cracks of 37 mm closely corresponded to the distance of 38 mm shown in the semi-variogram. The results provide a strong basis for the future retrieval of spatio-temporal variations in soil surface condition. Furthermore, the presence of process-based information on hydrological pathways within semi-variograms may work towards an inclusion of geostatisically-derived information in land surface models and the understanding of complex surface processes at different spatial scales.

Land Surface Phenology from MODIS: Characterization of the Collection 5 Global Land Cover Dynamics Product

NASA Technical Reports Server (NTRS)

Ganguly, Sangram; Friedl, Mark A.; Tan, Bin; Zhang, Xiaoyang; Verma, Manish

2010-01-01

Information related to land surface phenology is important for a variety of applications. For example, phenology is widely used as a diagnostic of ecosystem response to global change. In addition, phenology influences seasonal scale fluxes of water, energy, and carbon between the land surface and atmosphere. Increasingly, the importance of phenology for studies of habitat and biodiversity is also being recognized. While many data sets related to plant phenology have been collected at specific sites or in networks focused on individual plants or plant species, remote sensing provides the only way to observe and monitor phenology over large scales and at regular intervals. The MODIS Global Land Cover Dynamics Product was developed to support investigations that require regional to global scale information related to spatiotemporal dynamics in land surface phenology. Here we describe the Collection 5 version of this product, which represents a substantial refinement relative to the Collection 4 product. This new version provides information related to land surface phenology at higher spatial resolution than Collection 4 (500-m vs. 1-km), and is based on 8-day instead of 16-day input data. The paper presents a brief overview of the algorithm, followed by an assessment of the product. To this end, we present (1) a comparison of results from Collection 5 versus Collection 4 for selected MODIS tiles that span a range of climate and ecological conditions, (2) a characterization of interannual variation in Collections 4 and 5 data for North America from 2001 to 2006, and (3) a comparison of Collection 5 results against ground observations for two forest sites in the northeastern United States. Results show that the Collection 5 product is qualitatively similar to Collection 4. However, Collection 5 has fewer missing values outside of regions with persistent cloud cover and atmospheric aerosols. Interannual variability in Collection 5 is consistent with expected ranges of variance suggesting that the algorithm is reliable and robust, except in the tropics where some systematic differences are observed. Finally, comparisons with ground data suggest that the algorithm is performing well, but that end of season metrics associated with vegetation senescence and dormancy have higher uncertainties than start of season metrics.

30 CFR 877.10 - Information collection.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 30 Mineral Resources 3 2010-07-01 2010-07-01 false Information collection. 877.10 Section 877.10 Mineral Resources OFFICE OF SURFACE MINING RECLAMATION AND ENFORCEMENT, DEPARTMENT OF THE INTERIOR ABANDONED MINE LAND RECLAMATION RIGHTS OF ENTRY § 877.10 Information collection. The information collection...

30 CFR 955.10 - Information collection.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 30 Mineral Resources 3 2010-07-01 2010-07-01 false Information collection. 955.10 Section 955.10 Mineral Resources OFFICE OF SURFACE MINING RECLAMATION AND ENFORCEMENT, DEPARTMENT OF THE INTERIOR... FEDERAL PROGRAM STATES AND ON INDIAN LANDS § 955.10 Information collection. The information collection...

Diagnosing the Nature of Land-Atmosphere Coupling During the 2006-7 Dry/Wet Extremes in the U. S. Southern Great Plains

NASA Technical Reports Server (NTRS)

Santanello, Joseph A.; Peters-Lidard, Christa D.; Kennedy, Aaron D.; Kumar, Sujay; Dong, Xiquan

2011-01-01

Land-atmosphere (L-A) interactions play a critical role in determining the diurnal evolution of land surface and planetary boundary layer (PBL) temperature and moisture states and fluxes. In turn, these interactions regulate the strength of the connection between surface moisture and precipitation in a coupled system. To address deficiencies in numerical weather prediction and climate models due to improper treatment of L-A interactions, recent studies have focused on development of diagnostics to quantify the strength and accuracy of the land-PBL coupling at the process-level. In this study, a diagnosis of the nature and impacts of local land-atmosphere coupling (LoCo) during dry and wet extreme conditions is presented using a combination of models and observations during the summers of2006-7 in the U.S. Southern Great Plains. Specifically, the Weather Research and Forecasting (WRF) model has been coupled to NASA's Land Information System (LIS), which provides a flexible and high resolution representation and initialization of land surface physics and states. A range of diagnostics exploring the links and feedbacks between soil moisture and precipitation are examined for the dry/wet regimes of this region, along with the behavior and accuracy of different land-PBL scheme couplings under these conditions. Results demonstrate how LoCo diagnostics can be applied to coupled model components in the context of their integrated impacts on the process-chain connecting the land surface to the PBL and support of hydrological anomalies.

MODIS land data at the EROS data center DAAC

USGS Publications Warehouse

Jenkerson, Calli B.; Reed, B.C.

2001-01-01

The US Geological Survey's (USGS) Earth Resources Observation Systems (EROS) Data Center (EDC) in Sioux Falls, SD, USA, is the primary national archive for land processes data and one of the National Aeronautics and Space Administration's (NASA) Distributed Active Archive Centers (DAAC) for the Earth Observing System (EOS). One of EDC's functions as a DAAC is the archival and distribution of Moderate Resolution Spectroradiometer (MODIS) Land Data collected from the Earth Observing System (EOS) satellite Terra. More than 500,000 publicly available MODIS land data granules totaling 25 Terabytes (Tb) are currently stored in the EDC archive. This collection is managed, archived, and distributed by EOS Data and Information System (EOSDIS) Core System (ECS) at EDC. EDC User Services support the use of MODIS Land data, which include land surface reflectance/albedo, temperature/emissivity, vegetation characteristics, and land cover, by responding to user inquiries, constructing user information sites on the EDC web page, and presenting MODIS materials worldwide.

Detecting temporal change in land-surface altitude using robotic land-surveying techniques and geographic information system applications at an earthen dam site in Southern Westchester County, New York

USGS Publications Warehouse

Noll, Michael L.; Chu, Anthony

2017-08-14

In 2005, the U.S. Geological Survey began a cooperative study with New York City Department of Environmental Protection to characterize the local groundwater-flow system and identify potential sources of seeps on the southern embankment at the Hillview Reservoir in southern Westchester County, New York. Monthly site inspections at the reservoir indicated an approximately 90-square-foot depression in the land surface directly upslope from a seep that has episodically flowed since 2007. In July 2008, the U.S. Geological Survey surveyed the topography of land surface in this depression area by collecting high-accuracy (resolution less than 1 inch) measurements. A point of origin was established for the topographic survey by using differentially corrected positional data collected by a global navigation satellite system. Eleven points were surveyed along the edge of the depression area and at arbitrary locations within the depression area by using robotic land-surveying techniques. The points were surveyed again in March 2012 to evaluate temporal changes in land-surface altitude. Survey measurements of the depression area indicated that the land-surface altitude at 8 of the 11 points decreased beyond the accepted measurement uncertainty during the 44 months from July 2008 to March 2012. Two additional control points were established at stable locations along Hillview Avenue, which runs parallel to the embankment. These points were measured during the July 2008 survey and measured again during the March 2012 survey to evaluate the relative accuracy of the altitude measurements. The relative horizontal and vertical (altitude) accuracies of the 11 topographic measurements collected in March 2012 were ±0.098 and ±0.060 feet (ft), respectively. Changes in topography at 8 of the 11 points ranged from 0.09 to 0.63 ft and topography remained constant, or within the measurement uncertainty, for 3 of the 11 points.Two cross sections were constructed through the depression area by using land-surface altitude data that were interpolated from positional data collected during the two topographic surveys. Cross section A–A′ was approximately 8.5 ft long and consisted of three surveyed points that trended north to south across the depression. Land-surface altitude change decreased along the entire north-south trending cross section during the 44 months, and ranged from 0.2 to more than 0.6 ft. In general, greater land-surface altitude change was measured north of the midpoint as compared to south of the midpoint of the cross section. Cross section B–B′ was 18 ft long and consisted of six surveyed points that trended east to west across the depression. Land-surface altitude change generally decreased or remained constant along the east-west trending cross section during the 44 months and ranged from 0.0 to 0.3 ft. Volume change of the depression area was calculated by using a three-dimensional geographic information system utility that subtracts interpolated surfaces. The results indicated a net volume loss of approximately 38 ±5 cubic feet of material from the depression area during the 44 months.

Investigating the Impacts of Surface Temperature Anomalies due to Burned Area Albedo in Northern sub-Saharan Africa

NASA Astrophysics Data System (ADS)

Gabbert, T.; Matsui, T.; Capehart, W. J.; Ichoku, C. M.; Gatebe, C. K.

2015-12-01

The northern Sub-Saharan African region (NSSA) is an area of intense focus due to periodic severe droughts that have dire consequences on the growing population, which relies mostly on rain fed agriculture for its food supply. This region's weather and hydrologic cycle are very complex and are dependent on the West African Monsoon. Different regional processes affect the West African Monsoon cycle and variability. One of the areas of current investigation is the water cycle response to the variability of land surface characteristics. Land surface characteristics are often altered in NSSA due to agricultural practices, grazing, and the fires that occur during the dry season. To better understand the effects of biomass burning on the hydrologic cycle of the sub-Saharan environment, an interdisciplinary team sponsored by NASA is analyzing potential feedback mechanisms due to the fires. As part of this research, this study focuses on the effects of land surface changes, particularly albedo and skin temperature, that are influenced by biomass burning. Surface temperature anomalies can influence the initiation of convective rainfall and surface albedo is linked to the absorption of solar radiation. To capture the effects of fire perturbations on the land surface, NASA's Unified Weather and Research Forecasting (NU-WRF) model coupled with NASA's Land Information System (LIS) is being used to simulate burned area surface albedo inducing surface temperature anomalies and other potential effects to environmental processes. Preliminary sensitivity results suggest an altered surface radiation budget, regional warming of the surface temperature, slight increase in average rainfall, and a change in precipitation locations.

Spatially Complete Global Surface Albedos Derived from Terra/MODIS Data

NASA Technical Reports Server (NTRS)

King, Michael D.; Moody, Eric G.; Schaaf, Crystal B.; Platnick, Steven

2006-01-01

Spectral land surface albedo is an important parameter for describing the radiative properties of the Earth. Accordingly it reflects the consequences of natural and human interactions, such as anthropogenic, meteorological, and phenological effects, on global and local climatological trends. Consequently, albedos are integral parts in a variety of research areas, such as general circulation models (GCMs), energy balance studies, modeling of land use and land use change, and biophysical, oceanographic, and meteorological studies. , Over five years of land surface anisotropy, diffuse bihemispherical (white-sky) albedo and direct beam directional hemispherical (black-sky) albedo from observations acquired by the MODIS instruments aboard NASA s Terra and Aqua satellite platforms have provided researchers with unprecedented spatial, spectral, and temporal information on the land surface s radiative characteristics. However, roughly 30% of the global land surface, on an annual equal-angle basis, is obscured due to persistent and transient cloud cover, while another 207% is obscured due to ephemeral and seasonal snow effects. This precludes the MOD43B3 albedo products from being directly used in some remote sensing and ground-based applications, climate models, and global change research projects. To provide researchers with the requisite spatially complete global snow-free land surface albedo dataset, an ecosystem-dependent temporal interpolation technique was developed to fill missing or lower quality data and snow covered values from the official MOD43B3 dataset with geophysically realistic values. The method imposes pixel-level and local regional ecosystem-dependent phenological behavior onto retrieved pixel temporal data in such a way as to maintain pixel-level spatial and spectral detail and integrity. The phenological curves are derived from statistics based on the MODIS MOD12Q1 IGBP land cover classification product geolocated with the MOD43B3 data.

Sensitivity Analysis of the Land Surface Model NOAH-MP for Different Model Fluxes

NASA Astrophysics Data System (ADS)

Mai, Juliane; Thober, Stephan; Samaniego, Luis; Branch, Oliver; Wulfmeyer, Volker; Clark, Martyn; Attinger, Sabine; Kumar, Rohini; Cuntz, Matthias

2015-04-01

Land Surface Models (LSMs) use a plenitude of process descriptions to represent the carbon, energy and water cycles. They are highly complex and computationally expensive. Practitioners, however, are often only interested in specific outputs of the model such as latent heat or surface runoff. In model applications like parameter estimation, the most important parameters are then chosen by experience or expert knowledge. Hydrologists interested in surface runoff therefore chose mostly soil parameters while biogeochemists interested in carbon fluxes focus on vegetation parameters. However, this might lead to the omission of parameters that are important, for example, through strong interactions with the parameters chosen. It also happens during model development that some process descriptions contain fixed values, which are supposedly unimportant parameters. However, these hidden parameters remain normally undetected although they might be highly relevant during model calibration. Sensitivity analyses are used to identify informative model parameters for a specific model output. Standard methods for sensitivity analysis such as Sobol indexes require large amounts of model evaluations, specifically in case of many model parameters. We hence propose to first use a recently developed inexpensive sequential screening method based on Elementary Effects that has proven to identify the relevant informative parameters. This reduces the number parameters and therefore model evaluations for subsequent analyses such as sensitivity analysis or model calibration. In this study, we quantify parametric sensitivities of the land surface model NOAH-MP that is a state-of-the-art LSM and used at regional scale as the land surface scheme of the atmospheric Weather Research and Forecasting Model (WRF). NOAH-MP contains multiple process parameterizations yielding a considerable amount of parameters (˜ 100). Sensitivities for the three model outputs (a) surface runoff, (b) soil drainage and (c) latent heat are calculated on twelve Model Parameter Estimation Experiment (MOPEX) catchments ranging in size from 1020 to 4421 km2. This allows investigation of parametric sensitivities for distinct hydro-climatic characteristics, emphasizing different land-surface processes. The sequential screening identifies the most informative parameters of NOAH-MP for different model output variables. The number of parameters is reduced substantially for all of the three model outputs to approximately 25. The subsequent Sobol method quantifies the sensitivities of these informative parameters. The study demonstrates the existence of sensitive, important parameters in almost all parts of the model irrespective of the considered output. Soil parameters, e.g., are informative for all three output variables whereas plant parameters are not only informative for latent heat but also for soil drainage because soil drainage is strongly coupled to transpiration through the soil water balance. These results contrast to the choice of only soil parameters in hydrological studies and only plant parameters in biogeochemical ones. The sequential screening identified several important hidden parameters that carry large sensitivities and have hence to be included during model calibration.

Comparative Study of Lunar Roughness from Multi - Source Data

NASA Astrophysics Data System (ADS)

Lou, Y.; Kang, Z.

2017-07-01

The lunar terrain can show its collision and volcanic history. The lunar surface roughness can give a deep indication of the effects of lunar surface magma, sedimentation and uplift. This paper aims to get different information from the roughness through different data sources. Besides introducing the classical Root-mean-square height method and Morphological Surface Roughness (MSR) algorithm, this paper takes the area of the Jurassic mountain uplift in the Sinus Iridum and the Plato Crater area as experimental areas. And then make the comparison and contrast of the lunar roughness derived from LRO's DEM and CE-2 DOM. The experimental results show that the roughness obtained by the traditional roughness calculation method reflect the ups and downs of the topography, while the results obtained by morphological surface roughness algorithm show the smoothness of the lunar surface. So, we can first use the surface fluctuation situation derived from RMSH to select the landing area range which ensures the lands are gentle. Then the morphological results determine whether the landing area is suitable for the detector walking and observing. The results obtained at two different scales provide a more complete evaluation system for selecting the landing site of the lunar probe.

An analysis of urban thermal characteristics and associated land cover in Tampa Bay and Las Vegas using Landsat satellite data

USGS Publications Warehouse

Xian, George; Crane, Mike

2006-01-01

Remote sensing data from both Landsat 5 and Landsat 7 systems were utilized to assess urban area thermal characteristics in Tampa Bay watershed of west-central Florida, and the Las Vegas valley of southern Nevada. To quantitatively determine urban land use extents and development densities, sub-pixel impervious surface areas were mapped for both areas. The urban–rural boundaries and urban development densities were defined by selecting certain imperviousness threshold values and Landsat thermal bands were used to investigate urban surface thermal patterns. Analysis results suggest that urban surface thermal characteristics and patterns can be identified through qualitatively based urban land use and development density data. Results show the urban area of the Tampa Bay watershed has a daytime heating effect (heat-source), whereas the urban surface in Las Vegas has a daytime cooling effect (heat-sink). These thermal effects strongly correlated with urban development densities where higher percent imperviousness is usually associated with higher surface temperature. Using vegetation canopy coverage information, the spatial and temporal distributions of urban impervious surface and associated thermal characteristics are demonstrated to be very useful sources in quantifying urban land use, development intensity, and urban thermal patterns.

Diagnosing the Nature of Land-Atmosphere Coupling During the 2006-7 Dry/Wet Extremes in the U.S. Southern Great Plains

NASA Technical Reports Server (NTRS)

Santanello, Joseph A., Jr.; Peters-Lidard, Christa D.; Kumar, Sujay V.; Dong, Xiquan; Kennedy, Aaron D.

2011-01-01

Land-atmosphere interactions play a critical role in determining the. diurnal evolution of both planetary boundary layer (PBL) and land surface temperature and moisture states. The degree of coupling between the land surface and PBL in numerical weather prediction and climate models remains largely unexplored and undiagnosed due to the complex interactions and feedbacks present across a range of scales. Further, uncoupled systems or experiments (e.g., the Project for Intercomparison of Land Parameterization Schemes, PILPS) may lead to inaccurate water and energy cycle process understanding by neglecting feedback processes such as PBL-top entrainment. In this study, a framework for diagnosing local land-atmosphere coupling (LoCo) is presented using a coupled mesoscale model with a suite of PBL and land surface model (LSM) options along with observations during the summers of 200617 in the U.S. Southern Great Plains. Specifically, the Weather Research and Forecasting (WRF) model has been coupled to NASA's Land Information System (LIS), which provides a flexible and high-resolution representation and initialization of land surface physics and states. A range of diagnostics exploring the links and feedbacks between soil moisture and precipitation are examined for the dry/wet extremes of this region, along with the sensitivity of PBL-LSM coupling to perturbations in soil moisture. As such, this methodology provides a potential pathway to study factors controlling local land-atmosphere coupling (LoCo) using the LIS-WRF system, which is serving as a testbed for LoCo experiments to evaluate coupling diagnostics within the community.

Land and federal mineral ownership coverage for southern Wyoming

USGS Publications Warehouse

Biewick, L.H.; Mercier, T.J.; Saber, T.T.; Urbanowski, S.R.; Neasloney, Larry

1999-01-01

This Arc/Info coverage contains land status and Federal mineral ownership for approximately 37,800 square miles in southern Wyoming. The polygon coverage (which is also provided here as a shapefile) contains two attributes of ownership information for each polygon. One attribute indicates where the surface is State owned, privately owned, or, if Federally owned, which Federal agency manages the land surface. The other attribute indicates which minerals, if any, are owned by the Federal govenment. This coverage is based on land status and Federal mineral ownership data compiled by the U.S. Geological Survey (USGS) and the Wyoming State Bureau of Land Management (BLM) at a scale of 1:24,000. This coverage was compiled primarily to serve the USGS National Oil and Gas Resource Assessment and National Coal Resource Assessment Projects in the Northern Rocky Mountains/Great Plains Region.

Development of an Impervious-Surface Database for the Little Blackwater River Watershed, Dorchester County, Maryland

USGS Publications Warehouse

Milheim, Lesley E.; Jones, John W.; Barlow, Roger A.

2007-01-01

Many agricultural and forested areas in proximity to National Wildlife Refuges (NWR) are under increasing economic pressure for commercial or residential development. The upper portion of the Little Blackwater River watershed - a 27 square mile area within largely low-lying Dorchester County, Maryland, on the eastern shore of the Chesapeake Bay - is important to the U.S. Fish and Wildlife Service (USFWS) because it flows toward the Blackwater National Wildlife Refuge (BNWR), and developmental impacts of areas upstream from the BNWR are unknown. One of the primary concerns for the Refuge is how storm-water runoff may affect living resources downstream. The Egypt Road project (fig. 1), for which approximately 600 residential units have been approved, has the potential to markedly change the land use and land cover on the west bank of the Little Blackwater River. In an effort to limit anticipated impacts, the Maryland Department of Natural Resources (Maryland DNR) recently decided to purchase some of the lands previously slated for development. Local topography, a high water table (typically 1 foot or less below the land surface), and hydric soils present a challenge for the best management of storm-water flow from developed surfaces. A spatial data coordination group was formed by the Dorchester County Soil and Conservation District to collect data to aid decisionmakers in watershed management and on the possible impacts of development on this watershed. Determination of streamflow combined with land cover and impervious-surface baselines will allow linking of hydrologic and geologic factors that influence the land surface. This baseline information will help planners, refuge managers, and developers discuss issues and formulate best management practices to mitigate development impacts on the refuge. In consultation with the Eastern Region Geospatial Information Office, the dataset selected to be that baseline land cover source was the June-July 2005 National Agricultural Imagery Program (NAIP) 1-meter resolution orthoimagery of Maryland. This publicly available, statewide dataset provided imagery corresponding to the closest in time to the installation of a U.S. Geological Survey (USGS) Water Resources Discipline gaging station on the Little Blackwater River. It also captures land cover status just before major residential development occurs. This document describes the process used to create a database of impervious surfaces for the Little Blackwater watershed.

Mars Exploration Rovers Entry, Descent, and Landing Trajectory Analysis

NASA Technical Reports Server (NTRS)

Desai, Prasun N.; Knocke, Philip C.

2007-01-01

In this study we present a novel method of land surface classification using surface-reflected GPS signals in combination with digital imagery. Two GPS-derived classification features are merged with visible image data to create terrain-moisture (TM) classes, defined here as visibly identifiable terrain or landcover classes containing a surface/soil moisture component. As compared to using surface imagery alone, classification accuracy is significantly improved for a number of visible classes when adding the GPS-based signal features. Since the strength of the reflected GPS signal is proportional to the amount of moisture in the surface, use of these GPS features provides information about the surface that is not obtainable using visible wavelengths alone. Application areas include hydrology, precision agriculture, and wetlands mapping.

Analyses of Rock Size-Frequency Distributions and Morphometry of Modified Hawaiian Lava Flows: Implications for Future Martian Landing Sites

NASA Technical Reports Server (NTRS)

Craddock, Robert A.; Golombek, Matthew; Howard, Alan D.

2000-01-01

Both the size-frequency distribution and morphometry of rock populations emplaced by a variety of geologic processes in Hawaii indicate that such information may be useful in planning future landing sites on Mars and interpreting the surface geology.

Integrated Display System for Low Visibility Landing and Surface Operations

NASA Technical Reports Server (NTRS)

Beskenis, Sharon Otero; Green, David F., Jr.; Hyer, Paul V.; Johnson, Edward J., Jr.

1998-01-01

This report summarizes the software products and system architectures developed by Lockheed Martin in support of the Low Visibility Landing and Surface Operations (LVLASO) program at NASA Langley Research Center. It presents an overview of the technical aspects, capabilities, and system integration issues associated with an integrated display system (IDS) that collects, processes and presents information to an aircraft flight crew during all phases of landing, roll-out, turn-off, inbound taxi, outbound taxi and takeoff. Communications hardware, drivers, and software provide continuous real-time data at varying rates and from many different sources to the display programs for presentation on a head-down display (HDD) and/or a head-up display (HUD). An electronic moving map of the airport surface is implemented on the HDD which includes the taxi route assigned by air traffic control, a text messaging system, and surface traffic and runway status information. Typical HUD symbology for navigation and control of the aircraft is augmented to provide aircraft deceleration guidance after touchdown to a pilot selected exit and taxi guidance along the route assigned by ATC. HUD displays include scene-linked symbolic runways, runway exits and taxiways that are conformal with the actual locations on the airport surface. Display formats, system architectures, and the various IDS programs are discussed.

NASA Ames Celebrates Curiosity Rover's Landing on Mars (Reporter Package)

NASA Image and Video Library

2012-08-08

Nearly 7,000 people came to NASA Ames Research Center, Moffett Field, Calif., to watch the Mars Science Laboratory rover Curiosity land on Mars. A full day's worth of activities and discussions with local Mars experts informed attendees about the contributions NASA Ames made to the mission. The highlight of the event was the live NASA TV broadcast of MSL's entry, descent and landing on the Martian surface.

Climatological Downscaling and Evaluation of AGRMET Precipitation Analyses Over the Continental U.S.

NASA Astrophysics Data System (ADS)

Garcia, M.; Peters-Lidard, C. D.; Eylander, J. B.; Daly, C.; Tian, Y.; Zeng, J.

2007-05-01

The spatially distributed application of a land surface model (LSM) over a region of interest requires the application of similarly distributed precipitation fields that can be derived from various sources, including surface gauge networks, surface-based radar, and orbital platforms. The spatial variability of precipitation influences the spatial organization of soil temperature and moisture states and, consequently, the spatial variability of land- atmosphere fluxes. The accuracy of spatially-distributed precipitation fields can contribute significantly to the uncertainty of model-based hydrological states and fluxes at the land surface. Collaborations between the Air Force Weather Agency (AFWA), NASA, and Oregon State University have led to improvements in the processing of meteorological forcing inputs for the NASA-GSFC Land Information System (LIS; Kumar et al. 2006), a sophisticated framework for LSM operation and model coupling experiments. Efforts at AFWA toward the production of surface hydrometeorological products are currently in transition from the legacy Agricultural Meteorology modeling system (AGRMET) to use of the LIS framework and procedures. Recent enhancements to meteorological input processing for application to land surface models in LIS include the assimilation of climate-based information for the spatial interpolation and downscaling of precipitation fields. Climatological information included in the LIS-based downscaling procedure for North America is provided by a monthly high-resolution PRISM (Daly et al. 1994, 2002; Daly 2006) dataset based on a 30-year analysis period. The combination of these sources and methods attempts to address the strengths and weaknesses of available legacy products, objective interpolation methods, and the PRISM knowledge-based methodology. All of these efforts are oriented on an operational need for timely estimation of spatial precipitation fields at adequate spatial resolution for customer dissemination and near-real-time simulations in regions of interest. This work focuses on value added to the AGRMET precipitation product by the inclusion of high-quality climatological information on a monthly time scale. The AGRMET method uses microwave-based satellite precipitation estimates from various polar-orbiting platforms (NOAA POES and DMSP), infrared-based estimates from geostationary platforms (GOES, METEOSAT, etc.), related cloud analysis products, and surface gauge observations in a complex and hierarchical blending process. Results from processing of the legacy AGRMET precipitation products over the U.S. using LIS-based methods for downscaling, both with and without climatological factors, are evaluated against high-resolution monthly analyses using the PRISM knowledge- based method (Daly et al. 2002). It is demonstrated that the incorporation of climatological information in a downscaling procedure can significantly enhance the accuracy, and potential utility, of AFWA precipitation products for military and civilian customer applications.

Urban land-cover change detection through sub-pixel imperviousness mapping using remotely sensed data

USGS Publications Warehouse

Yang, Limin; Xian, George Z.; Klaver, Jacqueline M.; Deal, Brian

2003-01-01

We developed a Sub-pixel Imperviousness Change Detection (SICD) approach to detect urban land-cover changes using Landsat and high-resolution imagery. The sub-pixel percent imperviousness was mapped for two dates (09 March 1993 and 11 March 2001) over western Georgia using a regression tree algorithm. The accuracy of the predicted imperviousness was reasonable based on a comparison using independent reference data. The average absolute error between predicted and reference data was 16.4 percent for 1993 and 15.3 percent for 2001. The correlation coefficient (r) was 0.73 for 1993 and 0.78 for 2001, respectively. Areas with a significant increase (greater than 20 percent) in impervious surface from 1993 to 2001 were mostly related to known land-cover/land-use changes that occurred in this area, suggesting that the spatial change of an impervious surface is a useful indicator for identifying spatial extent, intensity, and, potentially, type of urban land-cover/land-use changes. Compared to other pixel-based change-detection methods (band differencing, rationing, change vector, post-classification), information on changes in sub-pixel percent imperviousness allow users to quantify and interpret urban land-cover/land-use changes based on their own definition. Such information is considered complementary to products generated using other change-detection methods. In addition, the procedure for mapping imperviousness is objective and repeatable, hence, can be used for monitoring urban land-cover/land-use change over a large geographic area. Potential applications and limitations of the products developed through this study in urban environmental studies are also discussed.

Development of a Land Use Database for the Little Blackwater Watershed, Dorchester County, Maryland

USGS Publications Warehouse

Milheim, Lesley E.; Jones, John W.; Barlow, Roger A.

2007-01-01

Many agricultural and forested areas in proximity to National Wildlife Refuges (NWR) are under increasing economic pressure to develop lands for commercial or residential development. The upper portion of the Little Blackwater River watershed - a 27 square mile area within largely low-lying Dorchester County, Maryland, on the eastern shore of the Chesapeake Bay - is important to the U.S. Fish and Wildlife Service (USFWS) because it flows toward the Blackwater National Wildlife Refuge (BNWR), and developmental impacts of areas upstream from the BNWR are unknown. One of the primary concerns for the refuge is how storm-water runoff may affect living resources downstream. The Egypt Road project (fig. 1), for which approximately 600 residential units have been approved, has the potential to markedly change the land use and land cover on the west bank of the Little Blackwater River. In an effort to limit anticipated impacts, the Maryland Department of Natural Resources (Maryland DNR) recently decided to purchase some of the lands previously slated for development. Local topography, a high water table (typically 1 foot or less below the land surface), and hydric soils present a challenge for the best management of storm-water flow from developed surfaces. A spatial data coordination group was formed by the Dorchester County Soil and Conservation District to collect data to aid decisionmakers in watershed management and on the possible impacts of development on this watershed. Determination of streamflow combined with land cover and impervious-surface baselines will allow linking of hydrologic and geologic factors that influence the land surface. This baseline information will help planners, refuge managers, and developers discuss issues and formulate best management practices to mitigate development impacts on the refuge. In consultation with the Eastern Region Geospatial Information Office, the dataset selected to be that baseline land cover source was the June-July 2005 National Agricultural Imagery Program (NAIP) 1-meter resolution orthoimagery of Maryland. This publicly available, statewide dataset provided imagery corresponding to the closest in time to the installation of a U.S. Geological Survey (USGS) Water Resources Discipline gaging station on the Little Blackwater River. It also captures land cover status just before major residential development occurs. This document describes the process used to create a land use database for the Little Blackwater watershed.

Modeling and Observational Framework for Diagnosing Local Land-Atmosphere Coupling on Diurnal Time Scales

NASA Technical Reports Server (NTRS)

Santanello, Joseph A., Jr.; Peters-Lidard, Christa D.; Kumar, Sujay V.; Alonge, Charles; Tao, Wei-Kuo

2009-01-01

Land-atmosphere interactions play a critical role in determining the diurnal evolution of both planetary boundary layer (PBL) and land surface temperature and moisture states. The degree of coupling between the land surface and PBL in numerical weather prediction and climate models remains largely unexplored and undiagnosed due to the complex interactions and feedbacks present across a range of scales. Further, uncoupled systems or experiments (e.g., the Project for Intercomparison of Land Parameterization Schemes, PILPS) may lead to inaccurate water and energy cycle process understanding by neglecting feedback processes such as PBL-top entrainment. In this study, a framework for diagnosing local land-atmosphere coupling is presented using a coupled mesoscale model with a suite of PBL and land surface model (LSM) options along with observations during field experiments in the U. S. Southern Great Plains. Specifically, the Weather Research and Forecasting (WRF) model has been coupled to the Land Information System (LIS), which provides a flexible and high-resolution representation and initialization of land surface physics and states. Within this framework, the coupling established by each pairing of the available PBL schemes in WRF with the LSMs in LIS is evaluated in terms of the diurnal temperature and humidity evolution in the mixed layer. The co-evolution of these variables and the convective PBL is sensitive to and, in fact, integrative of the dominant processes that govern the PBL budget, which are synthesized through the use of mixing diagrams. Results show how the sensitivity of land-atmosphere interactions to the specific choice of PBL scheme and LSM varies across surface moisture regimes and can be quantified and evaluated against observations. As such, this methodology provides a potential pathway to study factors controlling local land-atmosphere coupling (LoCo) using the LIS-WRF system, which will serve as a testbed for future experiments to evaluate coupling diagnostics within the community.

Classification of Land Cover and Land Use Based on Convolutional Neural Networks

NASA Astrophysics Data System (ADS)

Yang, Chun; Rottensteiner, Franz; Heipke, Christian

2018-04-01

Land cover describes the physical material of the earth's surface, whereas land use describes the socio-economic function of a piece of land. Land use information is typically collected in geospatial databases. As such databases become outdated quickly, an automatic update process is required. This paper presents a new approach to determine land cover and to classify land use objects based on convolutional neural networks (CNN). The input data are aerial images and derived data such as digital surface models. Firstly, we apply a CNN to determine the land cover for each pixel of the input image. We compare different CNN structures, all of them based on an encoder-decoder structure for obtaining dense class predictions. Secondly, we propose a new CNN-based methodology for the prediction of the land use label of objects from a geospatial database. In this context, we present a strategy for generating image patches of identical size from the input data, which are classified by a CNN. Again, we compare different CNN architectures. Our experiments show that an overall accuracy of up to 85.7 % and 77.4 % can be achieved for land cover and land use, respectively. The classification of land cover has a positive contribution to the classification of the land use classification.

Role of Subsurface Physics in the Assimilation of Surface Soil Moisture Observations

NASA Technical Reports Server (NTRS)

Reichle, R. H.

2010-01-01

Root zone soil moisture controls the land-atmosphere exchange of water and energy and exhibits memory that may be useful for climate prediction at monthly scales. Assimilation of satellite-based surface soil moisture observations into a land surface model is an effective way to estimate large-scale root zone soil moisture. The propagation of surface information into deeper soil layers depends on the model-specific representation of subsurface physics that is used in the assimilation system. In a suite of experiments we assimilate synthetic surface soil moisture observations into four different models (Catchment, Mosaic, Noah and CLM) using the Ensemble Kalman Filter. We demonstrate that identical twin experiments significantly overestimate the information that can be obtained from the assimilation of surface soil moisture observations. The second key result indicates that the potential of surface soil moisture assimilation to improve root zone information is higher when the surface to root zone coupling is stronger. Our experiments also suggest that (faced with unknown true subsurface physics) overestimating surface to root zone coupling in the assimilation system provides more robust skill improvements in the root zone compared with underestimating the coupling. When CLM is excluded from the analysis, the skill improvements from using models with different vertical coupling strengths are comparable for different subsurface truths. Finally, the skill improvements through assimilation were found to be sensitive to the regional climate and soil types.

Assessing the Utility of 3-km Land Information System Soil Moisture Data for Drought Monitoring and Hydrologic Applications

NASA Technical Reports Server (NTRS)

White, Kristopher D.; Case, Jonathan L.

2014-01-01

The NASA Short term Prediction Research and Transition (SPoRT) Center in Huntsville, AL has been running a real-time configuration of the Noah land surface model within the NASA Land Information System (LIS) since June 2010. The SPoRT LIS version is run as a stand-alone land surface model over a Southeast Continental U.S. domain with 3-km grid spacing. The LIS contains output variables including soil moisture and temperature at various depths, skin temperature, surface heat fluxes, storm surface runoff, and green vegetation fraction (GVF). The GVF represents another real-time SPoRT product, which is derived from the Moderate Resolution Imaging Spectroradiometer instrument aboard NASA's Aqua and Terra satellites. These data have demonstrated operational utility for drought monitoring and hydrologic applications at the National Weather Service (NWS) office in Huntsville, AL since early 2011. The most relevant data for these applications have proven to be the moisture availability (%) in the 0-10 cm and 0-200 cm layers, and the volumetric soil moisture (%) in the 0-10 cm layer. In an effort to better understand their applicability among locations with different terrain, soil and vegetation types, SPoRT is conducting the first formal assessment of these data at NWS offices in Houston, TX, Huntsville, AL and Raleigh, NC during summer 2014. The goal of this assessment is to evaluate the LIS output in the context of assessing flood risk and determining drought designations for the U.S. Drought Monitor. Forecasters will provide formal feedback via a survey question web portal, in addition to the NASA SPoRT blog. In this presentation, the SPoRT LIS and its applications at NWS offices will be presented, along with information about the summer assessment, including training module development and preliminary results.

Land and federal mineral ownership coverage for northwestern Colorado

USGS Publications Warehouse

Biewick, L.H.; Mercier, T.J.; Levitt, Pam; Deikman, Doug; Vlahos, Bob

1999-01-01

This Arc/Info coverage contains land status and Federal mineral ownership for approximately 26,800 square miles in northwestern Colorado. The polygon coverage (which is also provided here as a shapefile) contains two attributes of ownership information for each polygon. One attribute indicates where the surface is State owned, privately owned, or, if Federally owned, which Federal agency manages the land surface. The other attribute indicates which minerals, if any, are owned by the Federal govenment. This coverage is based on land status and Federal mineral ownership data compiled by the U.S. Geological Survey (USGS) and three Colorado State Bureau of Land Management (BLM) former district offices at a scale of 1:24,000. This coverage was compiled primarily to serve the USGS National Oil and Gas Resource Assessment Project in the Uinta-Piceance Basin Province and the USGS National Coal Resource Assessment Project in the Colorado Plateau.

Estimation of Key Parameters of the Coupled Energy and Water Model by Assimilating Land Surface Data

NASA Astrophysics Data System (ADS)

Abdolghafoorian, A.; Farhadi, L.

2017-12-01

Accurate estimation of land surface heat and moisture fluxes, as well as root zone soil moisture, is crucial in various hydrological, meteorological, and agricultural applications. Field measurements of these fluxes are costly and cannot be readily scaled to large areas relevant to weather and climate studies. Therefore, there is a need for techniques to make quantitative estimates of heat and moisture fluxes using land surface state observations that are widely available from remote sensing across a range of scale. In this work, we applies the variational data assimilation approach to estimate land surface fluxes and soil moisture profile from the implicit information contained Land Surface Temperature (LST) and Soil Moisture (SM) (hereafter the VDA model). The VDA model is focused on the estimation of three key parameters: 1- neutral bulk heat transfer coefficient (CHN), 2- evaporative fraction from soil and canopy (EF), and 3- saturated hydraulic conductivity (Ksat). CHN and EF regulate the partitioning of available energy between sensible and latent heat fluxes. Ksat is one of the main parameters used in determining infiltration, runoff, groundwater recharge, and in simulating hydrological processes. In this study, a system of coupled parsimonious energy and water model will constrain the estimation of three unknown parameters in the VDA model. The profile of SM (LST) at multiple depths is estimated using moisture diffusion (heat diffusion) equation. In this study, the uncertainties of retrieved unknown parameters and fluxes are estimated from the inverse of Hesian matrix of cost function which is computed using the Lagrangian methodology. Analysis of uncertainty provides valuable information about the accuracy of estimated parameters and their correlation and guide the formulation of a well-posed estimation problem. The results of proposed algorithm are validated with a series of experiments using a synthetic data set generated by the simultaneous heat and water (SHAW) model. In addition, the feasibility of extending this algorithm to use remote sensing observations that have low temporal resolution is examined by assimilating the limited number of land surface moisture and temperature observations.

Impact of Uncertainties in Meteorological Forcing Data and Land Surface Parameters on Global Estimates of Terrestrial Water Balance Components

NASA Astrophysics Data System (ADS)

Nasonova, O. N.; Gusev, Ye. M.; Kovalev, Ye. E.

2009-04-01

Global estimates of the components of terrestrial water balance depend on a technique of estimation and on the global observational data sets used for this purpose. Land surface modelling is an up-to-date and powerful tool for such estimates. However, the results of modelling are affected by the quality of both a model and input information (including meteorological forcing data and model parameters). The latter is based on available global data sets containing meteorological data, land-use information, and soil and vegetation characteristics. Now there are a lot of global data sets, which differ in spatial and temporal resolution, as well as in accuracy and reliability. Evidently, uncertainties in global data sets will influence the results of model simulations, but to which extent? The present work is an attempt to investigate this issue. The work is based on the land surface model SWAP (Soil Water - Atmosphere - Plants) and global 1-degree data sets on meteorological forcing data and the land surface parameters, provided within the framework of the Second Global Soil Wetness Project (GSWP-2). The 3-hourly near-surface meteorological data (for the period from 1 July 1982 to 31 December 1995) are based on reanalyses and gridded observational data used in the International Satellite Land-Surface Climatology Project (ISLSCP) Initiative II. Following the GSWP-2 strategy, we used a number of alternative global forcing data sets to perform different sensitivity experiments (with six alternative versions of precipitation, four versions of radiation, two pure reanalysis products and two fully hybridized products of meteorological data). To reveal the influence of model parameters on simulations, in addition to GSWP-2 parameter data sets, we produced two alternative global data sets with soil parameters on the basis of their relationships with the content of clay and sand in a soil. After this the sensitivity experiments with three different sets of parameters were performed. As a result, 16 variants of global annual estimates of water balance components were obtained. Application of alternative data sets on radiation, precipitation, and soil parameters allowed us to reveal the influence of uncertainties in input data on global estimates of water balance components.

Assimilation of SMOS (and SMAP) Retrieved Soil Moisture into the Land Information System

NASA Technical Reports Server (NTRS)

Blankenship, Clay; Zavodsky, Bradley; Case, Jonathan; Stano, Geoffrey

2016-01-01

Goal: Accurate, high-resolution (approx.3 km) soil moisture in near-real time. Situational awareness (drought assessment, flood and fire threat). Local modeling applications (to improve sfc-PBL exchanges) Method: Assimilate satellite soil moisture retrievals into a land surface model. Combines high-resolution geophysical model data with latest satellite observations.

ExoMars Entry, Descent, and Landing Science

NASA Astrophysics Data System (ADS)

Karatekin, Özgür; Forget, Francois; Withers, Paul; Colombatti, Giacomo; Aboudan, Alessio; Lewis, Stephen; Ferri, Francesca; Van Hove, Bart; Gerbal, Nicolas

2016-07-01

Schiaparelli, the Entry Demonstrator Module (EDM) of the ESA ExoMars Program will to land on Mars on 19th October 2016. The ExoMars Atmospheric Mars Entry and Landing Investigations and Analysis (AMELIA) team seeks to exploit the Entry Descent and Landing (EDL) engineering measurements of Schiaparelli for scientific investigations of Mars' atmosphere and surface. ExoMars offers a rare opportunity to perform an in situ investigation of the martian environment over a wide altitude range. There has been only 7 successfully landing on the surface of Mars, from the Viking probes in the 1970's to the Mars Science Laboratory (MSL) in 2012. ExoMars EDM is equipped with an instrumented heat shield like MSL. These novel flight sensors complement conventional accelerometer and gyroscope instrumentation, and provide additional information to reconstruct atmospheric conditions with. This abstract outlines general atmospheric reconstruction methodology using complementary set of sensors and in particular the use of surface pressure and radio data. In addition, we discuss the lessons learned from previous EDL and the plans for ExoMars AMELIA data analysis.

Land Surface Model Biases and their Impacts on the Assimilation of Snow-related Observations

NASA Astrophysics Data System (ADS)

Arsenault, K. R.; Kumar, S.; Hunter, S. M.; Aman, R.; Houser, P. R.; Toll, D.; Engman, T.; Nigro, J.

2007-12-01

Some recent snow modeling studies have employed a wide range of assimilation methods to incorporate snow cover or other snow-related observations into different hydrological or land surface models. These methods often include taking both model and observation biases into account throughout the model integration. This study focuses more on diagnosing the model biases and presenting their subsequent impacts on assimilating snow observations and modeled snowmelt processes. In this study, the land surface model, the Community Land Model (CLM), is used within the Land Information System (LIS) modeling framework to show how such biases impact the assimilation of MODIS snow cover observations. Alternative in-situ and satellite-based observations are used to help guide the CLM LSM in better predicting snowpack conditions and more realistic timing of snowmelt for a western US mountainous region. Also, MODIS snow cover observation biases will be discussed, and validation results will be provided. The issues faced with inserting or assimilating MODIS snow cover at moderate spatial resolutions (like 1km or less) will be addressed, and the impacts on CLM will be presented.

Surface and Atmospheric Contributions to Passive Microwave Brightness Temperatures

NASA Technical Reports Server (NTRS)

Jackson, Gail Skofronick; Johnson, Benjamin T.

2010-01-01

Physically-based passive microwave precipitation retrieval algorithms require a set of relationships between satellite observed brightness temperatures (TB) and the physical state of the underlying atmosphere and surface. These relationships are typically non-linear, such that inversions are ill-posed especially over variable land surfaces. In order to better understand these relationships, this work presents a theoretical analysis using brightness temperature weighting functions to quantify the percentage of the TB resulting from absorption/emission/reflection from the surface, absorption/emission/scattering by liquid and frozen hydrometeors in the cloud, the emission from atmospheric water vapor, and other contributors. The results are presented for frequencies from 10 to 874 GHz and for several individual precipitation profiles as well as for three cloud resolving model simulations of falling snow. As expected, low frequency channels (<89 GHz) respond to liquid hydrometeors and the surface, while the higher frequency channels become increasingly sensitive to ice hydrometeors and the water vapor sounding channels react to water vapor in the atmosphere. Low emissivity surfaces (water and snow-covered land) permit energy downwelling from clouds to be reflected at the surface thereby increasing the percentage of the TB resulting from the hydrometeors. The slant path at a 53deg viewing angle increases the hydrometeor contributions relative to nadir viewing channels and show sensitivity to surface polarization effects. The TB percentage information presented in this paper answers questions about the relative contributions to the brightness temperatures and provides a key piece of information required to develop and improve precipitation retrievals over land surfaces.

Diagnosing the Nature of Land-Atmosphere Coupling: A Case Study of Dry/Wet Extremes

NASA Technical Reports Server (NTRS)

Santanello, Joseph A., Jr.; Peters-Lidard, Christa; Kennedy, Aaron D.

2012-01-01

Land-atmosphere (L-A) interactions play a critical role in determining the diurnal evolution of land surface and planetary boundary layer (PBL) temperature and moisture states and fluxes. In turn, these interactions regulate the strength of the connection between surface moisture and precipitation in a coupled system. To address deficiencies in numerical weather prediction and climate models due to improper treatment of L-A interactions, recent studies have focused on development of diagnostics to quantify the strength and accuracy of the land-PBL coupling at the process-level. In this study, a diagnosis of the nature and impacts oflocalland-atmosphere coupling (LoCo) during dry and wet extreme conditions is presented using a combination of models and observations during the summers of2006-7 in the U.S. Southern Great Plains. Specifically, the Weather Research and Forecasting (WRF) model has been coupled to NASA's Land Information System (LIS), which provides a flexible and high-resolution representation and initialization of land surface physics and states. A range of diagnostics exploring the links and feedbacks between soil moisture and precipitation are examined for the dry/wet regimes of this region, along with the behavior and accuracy of different land-PBL scheme couplings under these conditions. In addition, we examine the impact of improved specification ofland surface states, anomalies, and fluxes that are obtained through the use of a hew optimization and uncertainty module in LIS, on the L-A coupling in WRF forecasts. Results demonstrate how LoCo diagnostics can be applied to coupled model components in the context of their integrated impacts on the process-chain connecting the land surface to the PBL and support of hydrological anomalies.

The Impact of Anthropogenic Land Cover Change on Continental River Flow

NASA Astrophysics Data System (ADS)

Sterling, S. M.; Ducharne, A.; Polcher, J.

2006-12-01

The 2003 World Water Forum highlighted a water crisis that forces over one billion people to drink contaminated water and leaves countless millions with insufficient supplies for agriculture industry. This crisis has spurred numerous recent calls for improved science and understanding of how we alter the water cycle. Here we investigate how this global water crisis is affected by human-caused land cover change. We examine the impact of the present extent of land cover change on the water cycle, in particular on evapotranspiration and streamflow, through numerical experiments with the ORCHIDEE land surface model. Using Geographic Information Systems, we characterise land cover change by assembling and modifying existing global-scale maps of land cover change. To see how the land cover change impacts river runoff streamflow, we input the maps into ORCHIDEE and run 50-year "potential vegetation" and "current land cover" simulations of the land surface and energy fluxes, forced by the 50-year NCC atmospheric forcing data set. We present global maps showing the "hotspot" areas with the largest change in ET and streamflow due to anthropogenic land cover change. The results of this project enhance scientific understanding of the nature of human impact on the global water cycle.

An Investigation of Land-Atmosphere Coupling from Local to Regional Scales

NASA Astrophysics Data System (ADS)

Brunsell, N. A.; Van Vleck, E.; Rahn, D. A.

2017-12-01

The exchanges of mass and energy between the surface and atmosphere have been shown to depend upon both local and regional climatic influences. However, the degree of control exerted by the land surface on the coupling metrics is not well understood. In particular, we lack an understanding of the relationship between the local microclimate of a site and the regional forces responsible for land-atmosphere coupling. To address this, we investigate a series of metrics calculated from eddy covariance data and ceilometer data, land surface modeling and remotely sensed observations in the central United States to diagnose these interactions and predict the change from one coupling regime (e.g. wet/dry coupling) to another state. The stability of the coupling is quantified using a Lyapunov exponent based methodology. Through the use of a wavelet information theoretic approach, we isolate the roles local energy partitioning, as well as the temperature and moisture gradients on controlling and changing the coupling regime. Taking a multi-scale observational approach, we first examine the relationship at the tower scale. Using land surface models, we quantify to what extent current models are capable of properly diagnosing the dynamics of the coupling regime. In particular, we focus on the role of the surface moisture and vegetation to initiate and maintain precipitation feedbacks. We extend this analysis to the regional scale by utilizing reanalysis and remotely sensed observations. Thus, we are able to quantify the changes in observed coupling patterns with linkages to local interactions to address the question of the local control that the surface exerts over the maintenance of land-atmosphere coupling.

National Centers for Environmental Prediction

Science.gov Websites

Processing Land Surface Software Engineering Hurricanes Model Information Documentation Performance Statistics Observational Data Processing Data Assimilation Monsoon Desk Model Transition Seminars Seminar Series Other Information Collaborators In-House Website Transition to Operations Presentations

Evaluating soil moisture constraints on surface fluxes in land surface models globally

NASA Astrophysics Data System (ADS)

Harris, Phil; Gallego-Elvira, Belen; Taylor, Christopher; Folwell, Sonja; Ghent, Darren; Veal, Karen; Hagemann, Stefan

2016-04-01

Soil moisture availability exerts a strong control over land evaporation in many regions. However, global climate models (GCMs) disagree on when and where evaporation is limited by soil moisture. Evaluation of the relevant modelled processes has suffered from a lack of reliable, global observations of land evaporation at the GCM grid box scale. Satellite observations of land surface temperature (LST) offer spatially extensive but indirect information about the surface energy partition and, under certain conditions, about soil moisture availability on evaporation. Specifically, as soil moisture decreases during rain-free dry spells, evaporation may become limited leading to increases in LST and sensible heat flux. We use MODIS Terra and Aqua observations of LST at 1 km from 2000 to 2012 to assess changes in the surface energy partition during dry spells lasting 10 days or longer. The clear-sky LST data are aggregated to a global 0.5° grid before being composited as a function dry spell day across many events in a particular region and season. These composites are then used to calculate a Relative Warming Rate (RWR) between the land surface and near-surface air. This RWR can diagnose the typical strength of short term changes in surface heat fluxes and, by extension, changes in soil moisture limitation on evaporation. Offline land surface model (LSM) simulations offer a relatively inexpensive way to evaluate the surface processes of GCMs. They have the benefits that multiple models, and versions of models, can be compared on a common grid and using unbiased forcing. Here, we use the RWR diagnostic to assess global, offline simulations of several LSMs (e.g., JULES and JSBACH) driven by the WATCH Forcing Data-ERA Interim. Both the observed RWR and the LSMs use the same 0.5° grid, which allows the observed clear-sky sampling inherent in the underlying MODIS LST to be applied to the model outputs directly. This approach avoids some of the difficulties in analysing free-running simulations in which land and atmosphere are coupled and, as such, it provides a flexible intermediate step in the assessment of surface processes in GCMs.

Updating representation of land surface-atmosphere feedbacks in airborne campaign modeling analysis

NASA Astrophysics Data System (ADS)

Huang, M.; Carmichael, G. R.; Crawford, J. H.; Chan, S.; Xu, X.; Fisher, J. A.

2017-12-01

An updated modeling system to support airborne field campaigns is being built at NASA Ames Pleiades, with focus on adjusting the representation of land surface-atmosphere feedbacks. The main updates, referring to previous experiences with ARCTAS-CARB and CalNex in the western US to study air pollution inflows, include: 1) migrating the WRF (Weather Research and Forecasting) coupled land surface model from Noah to improved/more complex models especially Noah-MP and Rapid Update Cycle; 2) enabling the WRF land initialization with suitably spun-up land model output; 3) incorporating satellite land cover, vegetation dynamics, and soil moisture data (i.e., assimilating Soil Moisture Active Passive data using the ensemble Kalman filter approach) into WRF. Examples are given of comparing the model fields with available aircraft observations during spring-summer 2016 field campaigns taken place at the eastern side of continents (KORUS-AQ in South Korea and ACT-America in the eastern US), the air pollution export regions. Under fair weather and stormy conditions, air pollution vertical distributions and column amounts, as well as the impact from land surface, are compared. These help identify challenges and opportunities for LEO/GEO satellite remote sensing and modeling of air quality in the northern hemisphere. Finally, we briefly show applications of this system on simulating Australian conditions, which would explore the needs for further development of the observing system in the southern hemisphere and inform the Clean Air and Urban Landscapes (https://www.nespurban.edu.au) modelers.

SMOS Soil Moisture Data Assimilation in the NASA Land Information System: Impact on LSM Initialization and NWP Forecasts

NASA Technical Reports Server (NTRS)

Blankenship, Clay; Case, Jonathan L.; Zavodsky, Bradley

2015-01-01

Land surface models are important components of numerical weather prediction (NWP) models, partitioning incoming energy into latent and sensitive heat fluxes that affect boundary layer growth and destabilization. During warm-season months, diurnal heating and convective initiation depend strongly on evapotranspiration and available boundary layer moisture, which are substantially affected by soil moisture content. Therefore, to properly simulate warm-season processes in NWP models, an accurate initialization of the land surface state is important for accurately depicting the exchange of heat and moisture between the surface and boundary layer. In this study, soil moisture retrievals from the Soil Moisture and Ocean Salinity (SMOS) satellite radiometer are assimilated into the Noah Land Surface Model via an Ensemble Kalman Filter embedded within the NASA Land Information System (LIS) software framework. The output from LIS-Noah is subsequently used to initialize runs of the Weather Research and Forecasting (WRF) NWP model. The impact of assimilating SMOS retrievals is assessed by initializing the WRF model with LIS-Noah output obtained with and without SMOS data assimilation. The southeastern United States is used as the domain for a preliminary case study. During the summer months, there is extensive irrigation in the lower Mississippi Valley for rice and other crops. The irrigation is not represented in the meteorological forcing used to drive the LIS-Noah integration, but the irrigated areas show up clearly in the SMOS soil moisture retrievals, resulting in a case with a large difference in initial soil moisture conditions. The impact of SMOS data assimilation on both Noah soil moisture fields and on short-term (0-48 hour) WRF weather forecasts will be presented.

WRF Simulation over the Eastern Africa by use of Land Surface Initialization

NASA Astrophysics Data System (ADS)

Sakwa, V. N.; Case, J.; Limaye, A. S.; Zavodsky, B.; Kabuchanga, E. S.; Mungai, J.

2014-12-01

The East Africa region experiences severe weather events associated with hazards of varying magnitude. It receives heavy precipitation which leads to wide spread flooding and lack of sufficient rainfall in some parts results into drought. Cases of flooding and drought are two key forecasting challenges for the Kenya Meteorological Service (KMS). The source of heat and moisture depends on the state of the land surface which interacts with the boundary layer of the atmosphere to produce excessive precipitation or lack of it that leads to severe drought. The development and evolution of precipitation systems are affected by heat and moisture fluxes from the land surface within weakly-sheared environments, such as in the tropics and sub-tropics. These heat and moisture fluxes during the day can be strongly influenced by land cover, vegetation, and soil moisture content. Therefore, it is important to represent the land surface state as accurately as possible in numerical weather prediction models. Improved modeling capabilities within the region have the potential to enhance forecast guidance in support of daily operations and high-impact weather over East Africa. KMS currently runs a configuration of the Weather Research and Forecasting (WRF) model in real time to support its daily forecasting operations, invoking the Non-hydrostatic Mesoscale Model (NMM) dynamical core. They make use of the National Oceanic and Atmospheric Administration / National Weather Service Science and Training Resource Center's Environmental Modeling System (EMS) to manage and produce the WRF-NMM model runs on a 7-km regional grid over Eastern Africa.SPoRT and SERVIR provide land surface initialization datasets and model verification tool. The NASA Land Information System (LIS) provide real-time, daily soil initialization data in place of interpolated Global Forecast System soil moisture and temperature data. Model verification is done using the Model Evaluation Tools (MET) package, in order to quantify possible improvements in simulated temperature, moisture and precipitation resulting from the experimental land surface initialization. These MET tools enable KMS to monitor model forecast accuracy in near real time. This study highlights verification results of WRF runs over East Africa using the LIS land surface initialization.

Modifying a dynamic global vegetation model for simulating large spatial scale land surface water balances

NASA Astrophysics Data System (ADS)

Tang, G.; Bartlein, P. J.

2012-08-01

Satellite-based data, such as vegetation type and fractional vegetation cover, are widely used in hydrologic models to prescribe the vegetation state in a study region. Dynamic global vegetation models (DGVM) simulate land surface hydrology. Incorporation of satellite-based data into a DGVM may enhance a model's ability to simulate land surface hydrology by reducing the task of model parameterization and providing distributed information on land characteristics. The objectives of this study are to (i) modify a DGVM for simulating land surface water balances; (ii) evaluate the modified model in simulating actual evapotranspiration (ET), soil moisture, and surface runoff at regional or watershed scales; and (iii) gain insight into the ability of both the original and modified model to simulate large spatial scale land surface hydrology. To achieve these objectives, we introduce the "LPJ-hydrology" (LH) model which incorporates satellite-based data into the Lund-Potsdam-Jena (LPJ) DGVM. To evaluate the model we ran LH using historical (1981-2006) climate data and satellite-based land covers at 2.5 arc-min grid cells for the conterminous US and for the entire world using coarser climate and land cover data. We evaluated the simulated ET, soil moisture, and surface runoff using a set of observed or simulated data at different spatial scales. Our results demonstrate that spatial patterns of LH-simulated annual ET and surface runoff are in accordance with previously published data for the US; LH-modeled monthly stream flow for 12 major rivers in the US was consistent with observed values respectively during the years 1981-2006 (R2 > 0.46, p < 0.01; Nash-Sutcliffe Coefficient > 0.52). The modeled mean annual discharges for 10 major rivers worldwide also agreed well (differences < 15%) with observed values for these rivers. Compared to a degree-day method for snowmelt computation, the addition of the solar radiation effect on snowmelt enabled LH to better simulate monthly stream flow in winter and early spring for rivers located at mid-to-high latitudes. In addition, LH-modeled monthly soil moisture for the state of Illinois (US) agreed well (R2 = 0.79, p < 0.01) with observed data for the years 1984-2001. Overall, this study justifies both the feasibility of incorporating satellite-based land covers into a DGVM and the reliability of LH to simulate land-surface water balances. To better estimate surface/river runoff at mid-to-high latitudes, we recommended that LPJ-DGVM considers the effects of solar radiation on snowmelt.

A Physically-Based Drought Product Using Thermal Remote Sensing of Evapotranspiration

USDA-ARS?s Scientific Manuscript database

Thermal infrared (TIR) remote sensing of land-surface temperature (LST) provides valuable information about the sub-surface moisture status. While empirical indices measuring anomalies in LST and vegetation amount (e.g., as quantified by the Normalized Difference Vegetation Index; NDVI) have demonst...

Bridging the Global Precipitation and Soil Moisture Active Passive Missions: Variability of Microwave Surface Emissivity from In situ and Remote Sensing Perspectives

NASA Astrophysics Data System (ADS)

Zheng, Y.; Kirstetter, P.; Hong, Y.; Turk, J.

2016-12-01

The overland precipitation retrievals from satellite passive microwave (PMW) sensors such as the Global Precipitation Mission (GPM) microwave imager (GMI) are impacted by the land surface emissivity. The estimation of PMW emissivity faces challenges because it is highly variable under the influence of surface properties such as soil moisture, surface roughness and vegetation. This study proposes an improved quantitative understanding of the relationship between the emissivity and surface parameters. Surface parameter information is obtained through (i) in-situ measurements from the International Soil Moisture Network and (ii) satellite measurements from the Soil Moisture Active and Passive mission (SMAP) which provides global scale soil moisture estimates. The variation of emissivity is quantified with soil moisture, surface temperature and vegetation at various frequencies/polarization and over different types of land surfaces to sheds light into the processes governing the emission of the land. This analysis is used to estimate the emissivity under rainy conditions. The framework built with in-situ measurements serves as a benchmark for satellite-based analyses, which paves a way toward global scale emissivity estimates using SMAP.

Preliminary Assessment of Mars Exploration Rover Landing Site Predictions

NASA Technical Reports Server (NTRS)

Golombek, M.; Grant, J.; Parker, T.; Crisp, J.; Squyres, S.; Carr, M.; Haldemann, A.; Arvidson, R.; Ehlmann, B.; Bell, J.

2004-01-01

Selection of the Mars Exploration Rover (MER) landing sites took place over a three year period in which engineering constraints were identified, 155 possible sites were downselected to the final two, surface environments and safety considerations were developed, and the potential science return at the sites was considered. Landing sites in Gusev crater and Meridiani Planum were selected because they appeared acceptably safe for MER landing and roving and had strong morphologic and mineralogical indicators of liquid water in their past and thus appeared capable of addressing the science objectives of the MER missions, which are to determine the aqueous, climatic, and geologic history of sites on Mars where conditions may have been favorable to the preservation of evidence of possible pre-biotic or biotic processes. Engineering constraints important to the selection included: latitude (10 N-15 S) for maximum solar power; elevation (<-1.3 km) for sufficient atmosphere to slow the lander; low horizontal winds, shear and turbulence in the last few kilometers to minimize horizontal velocity; low 10-m scale slopes to reduce airbag spinup and bounce; moderate rock abundance to reduce abrasion or stroke-out of the airbags; and a radar-reflective, load-bearing and trafficable surface safe for landing and roving that is not dominated by fine-grained dust. In selecting the MER landing sites these engineering constraints were addressed via comprehensive evaluation of surface and atmospheric characteristics from existing remote sensing data and models as well as targeted orbital information acquired from Mars Global Surveyor and Mars Odyssey. This evaluation resulted in a number of predictions of the surface characteristics of the sites, which are tested in this abstract. Relating remote sensing signatures to surface characteristics at landing sites allows these sites to be used as ground truth for the orbital data, is essential for selecting and validating landing sites for future missions, and is required for correctly interpreting the surfaces and materials globally present on Mars.

MOLA-Based Landing Site Characterization

NASA Technical Reports Server (NTRS)

Duxbury, T. C.; Ivanov, A. B.

2001-01-01

The Mars Global Surveyor (MGS) Mars Orbiter Laser Altimeter (MOLA) data provide the basis for site characterization and selection never before possible. The basic MOLA information includes absolute radii, elevation and 1 micrometer albedo with derived datasets including digital image models (DIM's illuminated elevation data), slopes maps and slope statistics and small scale surface roughness maps and statistics. These quantities are useful in downsizing potential sites from descent engineering constraints and landing/roving hazard and mobility assessments. Slope baselines at the few hundred meter level and surface roughness at the 10 meter level are possible. Additionally, the MOLA-derived Mars surface offers the possibility to precisely register and map project other instrument datasets (images, ultraviolet, infrared, radar, etc.) taken at different resolution, viewing and lighting geometry, building multiple layers of an information cube for site characterization and selection. Examples of direct MOLA data, data derived from MOLA and other instruments data registered to MOLA arc given for the Hematite area.

Monitoring the Global Soil Moisture Climatology Using GLDAS/LIS

NASA Astrophysics Data System (ADS)

Meng, J.; Mitchell, K.; Wei, H.; Gottschalck, J.

2006-05-01

Soil moisture plays a crucial role in the terrestrial water cycle through governing the process of partitioning precipitation among infiltration, runoff and evaporation. Accurate assessment of soil moisture and other land states, namely, soil temperature, snowpack, and vegetation, is critical in numerical environmental prediction systems because of their regulation of surface water and energy fluxes between the surface and atmosphere over a variety of spatial and temporal scales. The Global Land Data Assimilation System (GLDAS) is developed, jointly by NASA Goddard Space Flight Center (GSFC) and NOAA National Centers for Environmental Prediction (NCEP), to perform high-quality global land surface simulation using state-of-art land surface models and further minimizing the errors of simulation by constraining the models with observation- based precipitation, and satellite land data assimilation techniques. The GLDAS-based Land Information System (LIS) infrastructure has been installed on the NCEP supercomputer that serves the operational weather and climate prediction systems. In this experiment, the Noah land surface model is offline executed within the GLDAS/LIS infrastructure, driven by the NCEP Global Reanalysis-2 (GR2) and the CPC Merged Analysis of Precipitation (CMAP). We use the same Noah code that is coupled to the operational NCEP Global Forecast System (GFS) for weather prediction and test bed versions of the NCEP Climate Forecast System (CFS) for seasonal prediction. For assessment, it is crucial that this uncoupled GLDAS/Noah uses exactly the same Noah code (and soil and vegetation parameters therein), and executes with the same horizontal grid, landmask, terrain field, soil and vegetation types, seasonal cycle of green vegetation fraction and surface albedo as in the coupled GFS/Noah and CFS/Noah. This execution is for the 25-year period of 1980-2005, starting with a pre-execution 10-year spin-up. This 25-year GLDAS/Noah global land climatology will be used for both climate variability assessment and as a source of land initial conditions for ensemble CFS/Noah seasonal hindcast experiments. Finally, this GLDAS/Noah climatology will serve as the foundation for a global drought/flood monitoring system that includes near realtime daily updates of the global land states.

Microclimatic conditions in different land-use systems in Sumatra, Indonesia

NASA Astrophysics Data System (ADS)

Meijide, Ana; Tiralla, Nina; Sabajo, Clifton; Panferov, Oleg; Gunawan, Dodo; Knohl, Alexander

2015-04-01

Over the last decades, Indonesia has experienced an unprecedented transformation of the land surface through deforestation and conversion from forest to other land-uses such as oil palm and rubber plantations. These transformations are expected to affect not only biodiversity and carbon storage, but also the biophysical conditions of the land surface, i.e. air and surface temperature, surface albedo, air humidity, and soil moisture. There is, however, a lack of quantitative information characterizing these differences with a systematic experimental design. We report results from micrometeorological measurements in four different land-use types (forest, rubber plantation, jungle rubber, and oil palm plantation, n=4) in two different landscapes in Jambi Province in Sumatra/Indonesia as well as remote sensing data from Landsat. Preliminary results show differences on the average within-canopy air temperature, with lowest values in the forest (24.70°C ± 0.01°C) and highest in oil palm and rubber plantations (25.45°C ± 0.02°C and 25.55°C ± 0.01°C respectively). The temperature ranges also varied between different land uses, from 6.27°C in the forest and up to 9.40 °C in oil palm between the 5 and 95% percentile. Relative air humidity followed an inverse trend to air temperature, with rubber and oil palm plantations being on average 6.29 and 5.37 % drier than the forest. Soil temperature was up to 1°C warmer in oil palm than in forest plots, while soil moisture was more influenced by the soil type in the different landscapes than by the land uses. In conclusion, our data demonstrate that land transformation in Indonesia results in distinctly different microclimatic conditions across land-use types.

Land management effects on near-surface soil properties of southern U.S. coastal plain kandiudults.

Treesearch

M. Levi; J. Shaw; C. Wood; S. Herman; E. Carter; Y. Feng

2010-01-01

A comparative assessment of land management systems and relatively undisturbed ecosystems is useful for evaluating anthropogenic impacts on soil properties (Larson and Pierce, 1994). Such information is useful for the restoration and evaluation of C sequestration potential. Comparison of disturbed with natural ecosystems allows the measurement of soil properties...

Planetary landing-zone reconnaissance using ice-penetrating radar data: Concept validation in Antarctica

NASA Astrophysics Data System (ADS)

Grima, Cyril; Schroeder, Dustin M.; Blankenship, Donald D.; Young, Duncan A.

2014-11-01

The potential for a nadir-looking radar sounder to retrieve significant surface roughness/permittivity information valuable for planetary landing site selection is demonstrated using data from an airborne survey of the Thwaites Glacier Catchment, West Antarctica using the High Capability Airborne Radar Sounder (HiCARS). The statistical method introduced by Grima et al. (2012. Icarus 220, 84-99. http://dx.doi.org/10.1007/s11214-012-9916-y) for surface characterization is applied systematically along the survey flights. The coherent and incoherent components of the surface signal, along with an internally generated confidence factor, are extracted and mapped in order to show how a radar sounder can be used as both a reflectometer and a scatterometer to identify regions of low surface roughness compatible with a planetary lander. These signal components are used with a backscattering model to produce a landing risk assessment map by considering the following surface properties: Root mean square (RMS) heights, RMS slopes, roughness homogeneity/stationarity over the landing ellipse, and soil porosity. Comparing these radar-derived surface properties with simultaneously acquired nadir-looking imagery and laser-altimetry validates this method. The ability to assess all of these parameters with an ice penetrating radar expands the demonstrated capability of a principle instrument in icy planet satellite science to include statistical reconnaissance of the surface roughness to identify suitable sites for a follow-on lander mission.

Physical Properties of the MER and Beagle II Landing Sites on Mars

NASA Astrophysics Data System (ADS)

Jakosky, B. M.; Pelkey, S. M.; Mellon, M. T.; Putzig, N.; Martinez-Alonso, S.; Murphy, N.; Hynek, B.

2003-12-01

The ESA Beagle II and the NASA Mars Exploration Rover spacecraft are scheduled to land on the martian surface in December 2003 and January 2004, respectively. Mission operations and success depends on the physical properties of the surfaces on which they land. Surface structural characteristics such as the abundances of loose, unconsolidated fine material, of fine material that has been cemented into a duricrust, and of rocks affect the ability to safely land and to successfully sample and traverse the surface. Also, physical properties affect surface and atmospheric temperatures, which affect lander and rover functionality. We are in the process of analyzing surface temperature information for these sites, derived from MGS TES and Odyssey THEMIS daytime and nighttime measurements. Our approach is to: (i) remap thermal inertia using TES data at ~3-km resolution, to obtain the most complete coverage possible; (ii) interpret physical properties from TES coverage in conjunction with other remote-sensing data sets; (iii) map infrared brightness using daytime and nighttime THEMIS data at 100-m resolution, and do qualitative analysis of physical properties and processes; and (iv) derive thermal inertia from THEMIS nighttime data in conjunction with daytime albedo measurements derived from TES, THEMIS, and MOC observations. In addition, we will use measured temperatures and derived thermal inertia to predict surface temperatures for the periods of the missions.

An Inventory of Ohio's Land Use/Land Cover as Seen by Landsat

NASA Technical Reports Server (NTRS)

Schaal, Gary M.

1977-01-01

LANDSAT 2 (Land Satellite) was launched at Vandenburg, AFB, California on January 22, 1975. The satellite orbits the earth at an altitude of about 920 km (570 miles) and scans the earth's surface in a continuous track 185 km (115 miles) wide. LANDSAT 2 passes over the same spot every 18 days transmitting scanned data to receiving stations scattered around the globe. LANDSAT's continuously-scanning sensors provide useful information about the earth, one of the most important categories being land use. The statistics contained in the appendices of this report represent acreage and percentage of seven types of land cover in Ohio as seen by LANDSAT. The inventory represents a trial effort at determining the Sate's land cover by a method which is inexpensive, reliable, accurate and rapid. Given a successful method, the inventory and periodic updates could provide information to land use decision-makers and, over a period of time, would reveal patterns of land use change. Technical aspects of the project (process, methodology, and verification) are discussed in Schaal (1977) and Schmidt (1976).

Mapping the Distribution of Potential Land Drought in Batam Island Using the Integration of Remote Sensing and Geographic Information Systems (GIS)

NASA Astrophysics Data System (ADS)

Lubis, M. Z.; Taki, H. M.; Anurogo, W.; Pamungkas, D. S.; Wicaksono, P.; Aprilliyanti, T.

2017-12-01

Potential land drought mapping on Batam is needed to determine the distribution of areas that are very potential to the physical drought of the land. It is because the drought is always threatening on the long dry season. This research integrates remote sensing science with Geographic Information System (GIS). This research aims to map the distribution of land drought potential in Batam Island. The parameters used in this research are land use, Land Surface Temperature (LST), Potential dryness of land on the Batam island. The resulting map indicates the existence of five potential drought classes on the island of Batam. The area of very low drought potential is 2629.45 ha, mostly located in the Sungai Beduk sub-district. High drought potential with an area of 7081.39 ha is located in Sekupang sub-district. The distribution of very high land drought potential is in Batam city and Nongsa sub-district with area of 15600.12 ha. The coefficient of determination (R 2) is 0.6279. This indicates a strong positive relationship between field LST and modelled LST.

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

NASA Astrophysics Data System (ADS)

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

2018-04-01

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

Evaluating the Utility of Satellite Soil Moisture Retrievals over Irrigated Areas and the Ability of Land Data Assimilation Methods to Correct for Unmodeled Processes

NASA Technical Reports Server (NTRS)

Kumar, S. V.; Peters-Lidard, C. D.; Santanello, J. A.; Reichle, R. H.; Draper, C. S.; Koster, R. D.; Nearing, G.; Jasinski, M. F.

2015-01-01

Earth's land surface is characterized by tremendous natural heterogeneity and human-engineered modifications, both of which are challenging to represent in land surface models. Satellite remote sensing is often the most practical and effective method to observe the land surface over large geographical areas. Agricultural irrigation is an important human-induced modification to natural land surface processes, as it is pervasive across the world and because of its significant influence on the regional and global water budgets. In this article, irrigation is used as an example of a human-engineered, often unmodeled land surface process, and the utility of satellite soil moisture retrievals over irrigated areas in the continental US is examined. Such retrievals are based on passive or active microwave observations from the Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E), the Advanced Microwave Scanning Radiometer 2 (AMSR2), the Soil Moisture Ocean Salinity (SMOS) mission, WindSat and the Advanced Scatterometer (ASCAT). The analysis suggests that the skill of these retrievals for representing irrigation effects is mixed, with ASCAT-based products somewhat more skillful than SMOS and AMSR2 products. The article then examines the suitability of typical bias correction strategies in current land data assimilation systems when unmodeled processes dominate the bias between the model and the observations. Using a suite of synthetic experiments that includes bias correction strategies such as quantile mapping and trained forward modeling, it is demonstrated that the bias correction practices lead to the exclusion of the signals from unmodeled processes, if these processes are the major source of the biases. It is further shown that new methods are needed to preserve the observational information about unmodeled processes during data assimilation.

Simulating the Effects of Irrigation over the U.S. in a Land Surface Model Based on Satellite Derived Agricultural Data

NASA Technical Reports Server (NTRS)

Ozdogan, Mutlu; Rodell, Matthew; Beaudoing, Hiroko Kato; Toll, David L.

2009-01-01

A novel method is introduced for integrating satellite derived irrigation data and high-resolution crop type information into a land surface model (LSM). The objective is to improve the simulation of land surface states and fluxes through better representation of agricultural land use. Ultimately, this scheme could enable numerical weather prediction (NWP) models to capture land-atmosphere feedbacks in managed lands more accurately and thus improve forecast skill. Here we show that application of the new irrigation scheme over the continental US significantly influences the surface water and energy balances by modulating the partitioning of water between the surface and the atmosphere. In our experiment, irrigation caused a 12% increase in evapotranspiration (QLE) and an equivalent reduction in the sensible heat flux (QH) averaged over all irrigated areas in the continental US during the 2003 growing season. Local effects were more extreme: irrigation shifted more than 100 W/m from QH to QLE in many locations in California, eastern Idaho, southern Washington, and southern Colorado during peak crop growth. In these cases, the changes in ground heat flux (QG), net radiation (RNET), evapotranspiration (ET), runoff (R), and soil moisture (SM) were more than 3 W/m(sup 2), 20 W/m(sup 2), 5 mm/day, 0.3 mm/day, and 100 mm, respectively. These results are highly relevant to continental- to global-scale water and energy cycle studies that, to date, have struggled to quantify the effects of agricultural management practices such as irrigation. Based on the results presented here, we expect that better representation of managed lands will lead to improved weather and climate forecasting skill when the new irrigation scheme is incorporated into NWP models such as NOAA's Global Forecast System (GFS).

Transitioning Enhanced Land Surface Initialization and Model Verification Capabilities to the Kenya Meteorological Department (KMD)

NASA Technical Reports Server (NTRS)

Case, Jonathan L.; Mungai, John; Sakwa, Vincent; Zavodsky, Bradley T.; Srikishen, Jayanthi; Limaye, Ashutosh; Blankenship, Clay B.

2016-01-01

Flooding, severe weather, and drought are key forecasting challenges for the Kenya Meteorological Department (KMD), based in Nairobi, Kenya. Atmospheric processes leading to convection, excessive precipitation and/or prolonged drought can be strongly influenced by land cover, vegetation, and soil moisture content, especially during anomalous conditions and dry/wet seasonal transitions. It is thus important to represent accurately land surface state variables (green vegetation fraction, soil moisture, and soil temperature) in Numerical Weather Prediction (NWP) models. The NASA SERVIR and the Short-term Prediction Research and Transition (SPoRT) programs in Huntsville, AL have established a working partnership with KMD to enhance its regional modeling capabilities. SPoRT and SERVIR are providing experimental land surface initialization datasets and model verification capabilities for capacity building at KMD. To support its forecasting operations, KMD is running experimental configurations of the Weather Research and Forecasting (WRF; Skamarock et al. 2008) model on a 12-km/4-km nested regional domain over eastern Africa, incorporating the land surface datasets provided by NASA SPoRT and SERVIR. SPoRT, SERVIR, and KMD participated in two training sessions in March 2014 and June 2015 to foster the collaboration and use of unique land surface datasets and model verification capabilities. Enhanced regional modeling capabilities have the potential to improve guidance in support of daily operations and high-impact weather and climate outlooks over Eastern Africa. For enhanced land-surface initialization, the NASA Land Information System (LIS) is run over Eastern Africa at 3-km resolution, providing real-time land surface initialization data in place of interpolated global model soil moisture and temperature data available at coarser resolutions. Additionally, real-time green vegetation fraction (GVF) composites from the Suomi-NPP VIIRS instrument is being incorporated into the KMD-WRF runs, using the product generated by NOAA/NESDIS. Model verification capabilities are also being transitioned to KMD using NCAR's Model *Corresponding author address: Jonathan Case, ENSCO, Inc., 320 Sparkman Dr., Room 3008, Huntsville, AL, 35805. Email: Jonathan.Case-1@nasa.gov Evaluation Tools (MET; Brown et al. 2009) software in conjunction with a SPoRT-developed scripting package, in order to quantify and compare errors in simulated temperature, moisture and precipitation in the experimental WRF model simulations. This extended abstract and accompanying presentation summarizes the efforts and training done to date to support this unique regional modeling initiative at KMD. To honor the memory of Dr. Peter J. Lamb and his extensive efforts in bolstering weather and climate science and capacity-building in Africa, we offer this contribution to the special Peter J. Lamb symposium. The remainder of this extended abstract is organized as follows. The collaborating international organizations involved in the project are presented in Section 2. Background information on the unique land surface input datasets is presented in Section 3. The hands-on training sessions from March 2014 and June 2015 are described in Section 4. Sample experimental WRF output and verification from the June 2015 training are given in Section 5. A summary is given in Section 6, followed by Acknowledgements and References.

Heart Rhythm Monitoring in the Constellation Lunar and Launch/Landing EVA Suit: Recommendations from an Expert Panel

NASA Technical Reports Server (NTRS)

Scheuring, Richard A.; Hamilton, Doug; Jones, Jeffrey A.; Alexander, David

2009-01-01

There are currently several physiological monitoring requirements for EVA in the Human-Systems Interface Requirements (HSIR) document. There are questions as to whether the capability to monitor heart rhythm in the lunar surface space suit is a necessary capability for lunar surface operations. Similarly, there are questions as to whether the capability to monitor heart rhythm during a cabin depressurization scenario in the launch/landing space suit is necessary. This presentation seeks to inform space medicine personnel of recommendations made by an expert panel of cardiovascular medicine specialists regarding in-suit ECG heart rhythm monitoring requirements during lunar surface operations. After a review of demographic information and clinical cases and panel discussion, the panel recommended that ECG monitoring capability as a clinical tool was not essential in the lunar space suit; ECG monitoring was not essential in the launch/landing space suit for contingency scenarios; the current hear rate monitoring capability requirement for both launch/landing and lunar space suits should be maintained; lunar vehicles should be required to have ECG monitoring capability with a minimum of 5-lead ECG for IVA medical assessments; and, exercise stress testing for astronaut selection and retention should be changed from the current 85% maximum heart rate limit to maximal, exhaustive 'symptom-limited' testing to maximize diagnostic utility as a screening tool for evaluating the functional capacity of astronauts and their cardiovascular health.

Investigation of a long time series of CO2 from a tall tower using WRF-SPA

NASA Astrophysics Data System (ADS)

Smallman, Luke; Williams, Mathew; Moncrieff, John B.

2013-04-01

Atmospheric observations from tall towers are an important source of information about CO2 exchange at the regional scale. Here, we have used a forward running model, WRF-SPA, to generate a time series of CO2 at a tall tower for comparison with observations from Scotland over multiple years (2006-2008). We use this comparison to infer strength and distribution of sources and sinks of carbon and ecosystem process information at the seasonal scale. The specific aim of this research is to combine a high resolution (6 km) forward running meteorological model (WRF) with a modified version of a mechanistic ecosystem model (SPA). SPA provides surface fluxes calculated from coupled energy, hydrological and carbon cycles. This closely coupled representation of the biosphere provides realistic surface exchanges to drive mixing within the planetary boundary layer. The combined model is used to investigate the sources and sinks of CO2 and to explore which land surfaces contribute to a time series of hourly observations of atmospheric CO2 at a tall tower, Angus, Scotland. In addition to comparing the modelled CO2 time series to observations, modelled ecosystem specific (i.e. forest, cropland, grassland) CO2 tracers (e.g., assimilation and respiration) have been compared to the modelled land surface assimilation to investigate how representative tall tower observations are of land surface processes. WRF-SPA modelled CO2 time series compares well to observations (R2 = 0.67, rmse = 3.4 ppm, bias = 0.58 ppm). Through comparison of model-observation residuals, we have found evidence that non-cropped components of agricultural land (e.g., hedgerows and forest patches) likely contribute a significant and observable impact on regional carbon balance.

Muiti-Sensor Historical Climatology of Satellite-Derived Global Land Surface Moisture

NASA Technical Reports Server (NTRS)

Owe, Manfred; deJeu, Richard; Holmes, Thomas

2007-01-01

A historical climatology of continuous satellite derived global land surface soil moisture is being developed. The data set consists of surface soil moisture retrievals from observations of both historical and currently active satellite microwave sensors, including Nimbus-7 SMMR, DMSP SSM/I, TRMM TMI, and AQUA AMSR-E. The data sets span the period from November 1978 through the end of 2006. The soil moisture retrievals are made with the Land Parameter Retrieval Model, a physically-based model which was developed jointly by researchers from the above institutions. These data are significant in that they are the longest continuous data record of observational surface soil moisture at a global scale. Furthermore, while previous reports have intimated that higher frequency sensors such as on SSM/I are unable to provide meaningful information on soil moisture, our results indicate that these sensors do provide highly useful soil moisture data over significant parts of the globe, and especially in critical areas located within the Earth's many arid and semi-arid regions.

Application of aerial photography to water-related programs in Michigan

NASA Technical Reports Server (NTRS)

Enslin, W. R.; Hill-Rowley, R.; Tilmann, S. E.

1977-01-01

Aerial photography and information system technology were used to generate information required for the effective operation of three water-related programs in Michigan. Potential mosquito breeding sites were identified from specially acquired low altitude 70 mm color photography for the city of Lansing; the inventory identified 35% more surface water areas than indicated on existing field maps. A comprehensive inventory of surface water sources and potential access sites was prepared to assist fire departments in Antrim County with fire truck water-recharge operations. Remotely-sensed land cover/use data for Windsor Township, Eaton County, were integrated with other resource data into a computer-based information system for regional water quality studies. Eleven thematic maps focusing on landscape features affecting non-point water pollution and waste disposal were generated from analyses of a four-hectare grid-based data file containing land cover/use, soils, topographic and geologic (well-log) data.

Susceptibility of major aquifers to surface contamination - Holmes, Humphreys, Issaquena, Sharkey, Washington, and Yazoo Counties, Mississippi

USGS Publications Warehouse

Moreland, Richard S.; O'Hara, Charles G.

1994-01-01

A geographic information system was used to integrate digital spatial data sets describing geology, slope of the land surface, depth to water table, soil permeability, and land use/land cover to rate the relative susceptibility of unconfined parts of the Mississippi River alluvial, Cockfield, and Sparta aquifers in west-central Mississippi to contamination from surface sources. Areas were rated as having a very low, low, moderate, high, or very high susceptibility to contamination from surface sources. Less than 1 percent of the Mississippi River alluvial aquifer has a very high susceptibility to surface contamination, 35 percent has a high susceptibility, 62 percent has a moderate susceptibility, and 2 percent has a low suscepti- bility. About 43 percent of the Cockfield aquifer has a high susceptibility to surface contamination, 57 percent has a moderate susceptibility, and less than 1 percent has a low susceptibility. About 41 percent of the Sparta aquifer has a high suscepti- bility, and less than 1 percent has a low suscepti- bility, and 1 percent has a low susceptibility. For all three aquifers, less than 1 percent has a very low susceptibility to surface contamination.

Investigation of Seasonal Landscape Freeze/Thaw Cycles in Relation to Cloud Structure in the High Northern Latitudes

NASA Technical Reports Server (NTRS)

Smith, Cosmo

2011-01-01

The seasonal freezing and thawing of Earth's cryosphere (the portion of Earth's surface permanently or seasonally frozen) has an immense impact on Earth's climate as well as on its water, carbon and energy cycles. During the spring, snowmelt and the transition between frozen and non-frozen states lowers Earth's surface albedo. This change in albedo causes more solar radiation to be absorbed by the land surface, raising surface soil and air temperatures as much as 5 C within a few days. The transition of ice into liquid water not only raises the surface humidity, but also greatly affects the energy exchange between the land surface and the atmosphere as the phase change creates a latent energy dominated system. There is strong evidence to suggest that the thawing of the cryosphere during spring and refreezing during autumn is correlated to local atmospheric conditions such as cloud structure and frequency. Understanding the influence of land surface freeze/thaw cycles on atmospheric structure can help improve our understanding of links between seasonal land surface state and weather and climate, providing insight into associated changes in Earth's water, carbon, and energy cycles that are driven by climate change.Information on both the freeze/thaw states of Earth's land surface and cloud characteristics is derived from data sets collected by NOAA's Special Sensor Microwave/Imager (SSM/I), the Advanced Microwave Scanning Radiometer on NASA's Earth Observing System(AMSR-E), NASA's CloudSat, and NASA's SeaWinds-on-QuickSCAT Earth remote sensing satellite instruments. These instruments take advantage of the microwave spectrum to collect an ensemble of atmospheric and land surface data. Our analysis uses data from radars (active instruments which transmit a microwave signal toward Earth and measure the resultant backscatter) and radiometers (passive devices which measure Earth's natural microwave emission) to accurately characterize salient details on Earth's surface and atmospheric states. By comparing the cloud measurements and the surface freeze-thaw data sets, a correlation between the two phenomena can be developed.

Assessment of surface turbulent fluxes using geostationary satellite surface skin temperatures and a mixed layer planetary boundary layer scheme

NASA Technical Reports Server (NTRS)

Diak, George R.; Stewart, Tod R.

1989-01-01

A method is presented for evaluating the fluxes of sensible and latent heating at the land surface, using satellite-measured surface temperature changes in a composite surface layer-mixed layer representation of the planetary boundary layer. The basic prognostic model is tested by comparison with synoptic station information at sites where surface evaporation climatology is well known. The remote sensing version of the model, using satellite-measured surface temperature changes, is then used to quantify the sharp spatial gradient in surface heating/evaporation across the central United States. An error analysis indicates that perhaps five levels of evaporation are recognizable by these methods and that the chief cause of error is the interaction of errors in the measurement of surface temperature change with errors in the assigment of surface roughness character. Finally, two new potential methods for remote sensing of the land-surface energy balance are suggested which will relay on space-borne instrumentation planned for the 1990s.

Using Land Surface Phenology to Detect Land Use Change in the Northern Great Plains

NASA Astrophysics Data System (ADS)

Nguyen, L. H.; Henebry, G. M.

2017-12-01

The Northern Great Plains of the US have been undergoing many types of land cover / land use change over the past two decades, including expansion of irrigation, conversion of grassland to cropland, biofuels production, urbanization, and fossil fuel mining. Much of the literature on these changes has relied on post-classification change detection based on a limited number of observations per year. Here we demonstrate an approach to characterize land dynamics through land surface phenology (LSP) by synergistic use of image time series at two scales. Our study areas include regions of interest (ROIs) across the Northern Great Plains located within Landsat path overlap zones to boost the number of valid observations (free of clouds or snow) each year. We first compute accumulated growing degree-days (AGDD) from MODIS 8-day composites of land surface temperature (MOD11A2 and MYD11A2). Using Landsat Collection 1 surface reflectance-derived vegetation indices (NDVI, EVI), we then fit at each pixel a downward convex quadratic model linking the vegetation index to each year's progression of AGDD. This quadratic equation exhibits linearity in a mathematical sense; thus, the fitted models can be linearly mixed and unmixed using a set of LSP endmembers (defined by the fitted parameter coefficients of the quadratic model) that represent "pure" land cover types with distinct seasonal patterns found within the region, such as winter wheat, spring wheat, maize, soybean, sunflower, hay/pasture/grassland, developed/built-up, among others. Information about land cover corresponding to each endmember are provided by the NLCD (National Land Cover Dataset) and CDL (Cropland Data Layer). We use linear unmixing to estimate the likely proportion of each LSP endmember within particular areas stratified by latitude. By tracking the proportions over the 2001-2011 period, we can quantify various types of land transitions in the Northern Great Plains.

Analysis of landfills with historic airphotos

NASA Technical Reports Server (NTRS)

Erb, T. L.; Philipson, W. R.; Teng, W. L.; Liang, T.

1981-01-01

An investigation is conducted regarding the value of existing aerial photographs for waste management, including landfill monitoring. The value of historic aerial photographs for documenting landfill boundaries is shown in a graph in which the expansion of an active landfill is traced over a 40-year period. Historic aerial photographs can also be analyzed to obtain general or detailed land-use and land-cover information. In addition, the photographs provide information regarding other elements of the physical environment, including geology, soils, and surface and subsurface drainage. The value of historic photos is discussed, taking into account applications for inventory, assessing contamination/health hazards, planning corrective measures, planning waste collection and facilities, developing inactive landfills, and research concerning improved land-filling operations.

Operational marine products from Copernicus Sentinel-3 mission

NASA Astrophysics Data System (ADS)

Tomazic, Igor; Montagner, Francois; O'Carroll, Anne; Kwiatkowska, Ewa; Scharroo, Remko; Nogueira Loddo, Carolina; Martin-Puig, Cristina; Bonekamp, Hans; Lucas, Bruno; Dinardo, Salvatore; Dash, Prasanjit; Taberner, Malcolm; Coto Cabaleiro, Eva; Santacesaria, Vincenzo; Wilson, Hilary

2017-04-01

The first Copernicus Sentinel-3 satellite, Sentinel-3A, was launched in early 2016, with the mission to provide a consistent, long-term collection of marine and land data for operational analysis, forecasting and environmental and climate monitoring. The marine centre is part of the Sentinel-3 Payload Data Ground Segment, located at EUMETSAT. This centre together with the existing EUMETSAT facilities provides a routine centralised service for operational meteorology, oceanography, and other Sentinel-3 marine users as part of the European Commission's Copernicus programme. The EUMETSAT marine centre delivers operational Sea Surface Temperature, Ocean Colour and Sea Surface Topography data products based on the measurements from the Sea and Land Surface Temperature Radiometer (SLSTR), Ocean and Land Colour Instrument (OLCI) and Synthetic Aperture Radar Altimeter (SRAL), respectively, all aboard Sentinel-3. All products have been developed together with ESA and industry partners and EUMETSAT is responsible for the production, distribution, and future evolution of Level-2 marine products. We will give an overview of the scientific characteristics and algorithms of all marine Level-2 products, as well as instrument calibration and product validation results based on on-going Sentinel-3 Cal/Val activities. Information will be also provided about the current status of the product dissemination and the future evolutions that are envisaged. Also, we will provide information how to access Sentinel-3 data from EUMETSAT and where to look for further information.

Development of a ground hydrology model suitable for global climate modeling using soil morphology and vegetation cover, and an evaluation of remotely sensed information

NASA Technical Reports Server (NTRS)

Zobler, L.; Lewis, R.

1988-01-01

The long-term purpose was to contribute to scientific understanding of the role of the planet's land surfaces in modulating the flows of energy and matter which influence the climate, and to quantify and monitor human-induced changes to the land environment that may affect global climate. Highlights of the effort include the following: production of geo-coded, digitized World Soil Data file for use with the Goddard Institute for Space Studies (GISS) climate model; contribution to the development of a numerical physically-based model of ground hydrology; and assessment of the utility of remote sensing for providing data on hydrologically significant land surface variables.

The Use of Multi-Source Satellite and Geospatial Data to Study the Effect of Urbanization of Primary Productivity in the United States

NASA Technical Reports Server (NTRS)

Imhoff, M. L.; Tucker, C. J.; Lawrence, W. T.; Stutzer, D.; Rusin, Robert

2000-01-01

Data from two different satellites, a digital land cover map, and digital census data were analyzed and combined in a geographic information system to study the effect of urbanization on photosynthetic vegetation productivity in the United States. Results show that urbanization can have a measurable but variable impact on the primary productivity of the land surface. Annual productivity can be reduced by as much as 20 days in some areas, but in resource limited regions, photosynthetic production can be enhanced by human activity. Overall, urban development reduces the productivity of the land surface and those areas with the highest productivity are directly in the path of urban sprawl.

Linkages between Land Surface Phenology Metrics and Natural and Anthropogenic Events in Drylands (Invited)

NASA Astrophysics Data System (ADS)

de Beurs, K.; Brown, M. E.; Ahram, A.; Walker, J.; Henebry, G. M.

2013-12-01

Tracking vegetation dynamics across landscapes using remote sensing, or 'land surface phenology,' is a key mechanism that allows us to understand ecosystem changes. Land surface phenology models rely on vegetation information from remote sensing, such as the datasets derived from the Advanced Very High Resolution Radiometer (AVHRR), the newer MODIS sensors on Aqua and Terra, and sometimes the higher spatial resolution Landsat data. Vegetation index data can aid in the assessment of variables such as the start of season, growing season length and overall growing season productivity. In this talk we use Landsat, MODIS and AVHRR data and derive growing season metrics based on land surface phenology models that couple vegetation indices with satellite derived accumulated growing degreeday and evapotranspiration estimates. We calculate the timing and the height of the peak of the growing season and discuss the linkage of these land surface phenology metrics with natural and anthropogenic changes on the ground in dryland ecosystems. First we will discuss how the land surface phenology metrics link with annual and interannual price fluctuations in 229 markets distributed over Africa. Our results show that there is a significant correlation between the peak height of the growing season and price increases for markets in countries such as Nigeria, Somalia and Niger. We then demonstrate how land surface phenology metrics can improve models of post-conflict resolution in global drylands. We link the Uppsala Conflict Data Program's dataset of political, economic and social factors involved in civil war termination with an NDVI derived phenology metric and the Palmer Drought Severity Index (PDSI). An analysis of 89 individual conflicts in 42 dryland countries (totaling 892 individual country-years of data between 1982 and 2005) revealed that, even accounting for economic and political factors, countries that have higher NDVI growth following conflict have a lower risk of reverting to civil war. Finally, the patchy and heterogeneous arrangement of vegetation in dryland areas sometimes complicates the extraction of phenological signals using existing remote sensing data. We conclude by demonstrating how the phenological analysis of a range of dryland land cover classes benefits from the availability of synthetic images at Landsat spatial resolution and MODIS time intervals.

Evolving the Land Information System into a Cloud Computing Service

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

Houser, Paul R.

The Land Information System (LIS) was developed to use advanced flexible land surface modeling and data assimilation frameworks to integrate extremely large satellite- and ground-based observations with advanced land surface models to produce continuous high-resolution fields of land surface states and fluxes. The resulting fields are extremely useful for drought and flood assessment, agricultural planning, disaster management, weather and climate forecasting, water resources assessment, and the like. We envisioned transforming the LIS modeling system into a scientific cloud computing-aware web and data service that would allow clients to easily setup and configure for use in addressing large water management issues.more » The focus of this Phase 1 project was to determine the scientific, technical, commercial merit and feasibility of the proposed LIS-cloud innovations that are currently barriers to broad LIS applicability. We (a) quantified the barriers to broad LIS utility and commercialization (high performance computing, big data, user interface, and licensing issues); (b) designed the proposed LIS-cloud web service, model-data interface, database services, and user interfaces; (c) constructed a prototype LIS user interface including abstractions for simulation control, visualization, and data interaction, (d) used the prototype to conduct a market analysis and survey to determine potential market size and competition, (e) identified LIS software licensing and copyright limitations and developed solutions, and (f) developed a business plan for development and marketing of the LIS-cloud innovation. While some significant feasibility issues were found in the LIS licensing, overall a high degree of LIS-cloud technical feasibility was found.« less

A two-step framework for reconstructing remotely sensed land surface temperatures contaminated by cloud

NASA Astrophysics Data System (ADS)

Zeng, Chao; Long, Di; Shen, Huanfeng; Wu, Penghai; Cui, Yaokui; Hong, Yang

2018-07-01

Land surface temperature (LST) is one of the most important parameters in land surface processes. Although satellite-derived LST can provide valuable information, the value is often limited by cloud contamination. In this paper, a two-step satellite-derived LST reconstruction framework is proposed. First, a multi-temporal reconstruction algorithm is introduced to recover invalid LST values using multiple LST images with reference to corresponding remotely sensed vegetation index. Then, all cloud-contaminated areas are temporally filled with hypothetical clear-sky LST values. Second, a surface energy balance equation-based procedure is used to correct for the filled values. With shortwave irradiation data, the clear-sky LST is corrected to the real LST under cloudy conditions. A series of experiments have been performed to demonstrate the effectiveness of the developed approach. Quantitative evaluation results indicate that the proposed method can recover LST in different surface types with mean average errors in 3-6 K. The experiments also indicate that the time interval between the multi-temporal LST images has a greater impact on the results than the size of the contaminated area.

43 CFR 3273.12 - How will BLM review my site license application?

Code of Federal Regulations, 2011 CFR

2011-10-01

...) BUREAU OF LAND MANAGEMENT, DEPARTMENT OF THE INTERIOR MINERALS MANAGEMENT (3000) GEOTHERMAL RESOURCE... information. (b) If your site license is located on geothermal leases where the surface is managed by the... requested by the Federal Energy Regulatory Commission. (d) If another Federal agency manages the surface, we...

Mapping Daily Evapotranspiration at Field to Global Scales using Geostationary and Polar Orbiting Satellite Imagery

USDA-ARS?s Scientific Manuscript database

Thermal infrared (TIR) remote sensing of land-surface temperature (LST) provides valuable information about the sub-surface moisture status required for estimating evapotranspiration (ET) and detecting the onset and severity of drought. While empirical indices measuring anomalies in LST and vegetati...

GIS-based Landing-Site Analysis and Passive Decision Support

NASA Astrophysics Data System (ADS)

van Gasselt, Stephan; Nass, Andrea

2016-04-01

The increase of surface coverage and the availability and accessibility of planetary data allow researchers and engineers to remotely perform detailed studies on surface processes and properties, in particular on objects such as Mars and the Moon for which Terabytes of multi-temporal data at multiple spatial resolution levels have become available during the last 15 years. Orbiters, rovers and landers have been returning information and insights into the surface evolution of the terrestrial planets in unprecedented detail. While rover- and lander-based analyses are one major research aim to obtain ground truth, resource exploration or even potential establishment of bases using autonomous platforms are others and they require detailed investigation of settings in order to identify spots on the surface that are suitable for spacecraft to land and operate safely and over a long period of time. What has been done using hardcopy material in the past is today being carried by using either in-house developments or off-the-shelf spatial information system technology which allows to manage, integrate and analyse data as well as visualize and create user-defined reports for performing assessments. Usually, such analyses can be broken down (manually) by considering scientific wishes, engineering boundary conditions, potential hazards and various tertiary constraints. We here (1) review standard tasks of landing site analyses, (2) discuss issues inherently related to the analysis using integrated spatial analysis systems and (3) demonstrate a modular analysis framework for integration of data and for the evaluation of results from individual tasks in order to support decisions for landing-site selection.

Contributions of Precipitation and Soil Moisture Observations to the Skill of Soil Moisture Estimates in a Land Data Assimilation System

NASA Technical Reports Server (NTRS)

Reichle, Rolf H.; Liu, Qing; Bindlish, Rajat; Cosh, Michael H.; Crow, Wade T.; deJeu, Richard; DeLannoy, Gabrielle J. M.; Huffman, George J.; Jackson, Thomas J.

2011-01-01

The contributions of precipitation and soil moisture observations to the skill of soil moisture estimates from a land data assimilation system are assessed. Relative to baseline estimates from the Modern Era Retrospective-analysis for Research and Applications (MERRA), the study investigates soil moisture skill derived from (i) model forcing corrections based on large-scale, gauge- and satellite-based precipitation observations and (ii) assimilation of surface soil moisture retrievals from the Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E). Soil moisture skill is measured against in situ observations in the continental United States at 44 single-profile sites within the Soil Climate Analysis Network (SCAN) for which skillful AMSR-E retrievals are available and at four CalVal watersheds with high-quality distributed sensor networks that measure soil moisture at the scale of land model and satellite estimates. The average skill (in terms of the anomaly time series correlation coefficient R) of AMSR-E retrievals is R=0.39 versus SCAN and R=0.53 versus CalVal measurements. The skill of MERRA surface and root-zone soil moisture is R=0.42 and R=0.46, respectively, versus SCAN measurements, and MERRA surface moisture skill is R=0.56 versus CalVal measurements. Adding information from either precipitation observations or soil moisture retrievals increases surface soil moisture skill levels by IDDeltaR=0.06-0.08, and root zone soil moisture skill levels by DeltaR=0.05-0.07. Adding information from both sources increases surface soil moisture skill levels by DeltaR=0.13, and root zone soil moisture skill by DeltaR=0.11, demonstrating that precipitation corrections and assimilation of satellite soil moisture retrievals contribute similar and largely independent amounts of information.

Global Land Product Validation Protocols: An Initiative of the CEOS Working Group on Calibration and Validation to Evaluate Satellite-derived Essential Climate Variables

NASA Astrophysics Data System (ADS)

Guillevic, P. C.; Nickeson, J. E.; Roman, M. O.; camacho De Coca, F.; Wang, Z.; Schaepman-Strub, G.

2016-12-01

The Global Climate Observing System (GCOS) has specified the need to systematically produce and validate Essential Climate Variables (ECVs). The Committee on Earth Observation Satellites (CEOS) Working Group on Calibration and Validation (WGCV) and in particular its subgroup on Land Product Validation (LPV) is playing a key coordination role leveraging the international expertise required to address actions related to the validation of global land ECVs. The primary objective of the LPV subgroup is to set standards for validation methods and reporting in order to provide traceable and reliable uncertainty estimates for scientists and stakeholders. The Subgroup is comprised of 9 focus areas that encompass 10 land surface variables. The activities of each focus area are coordinated by two international co-leads and currently include leaf area index (LAI) and fraction of absorbed photosynthetically active radiation (FAPAR), vegetation phenology, surface albedo, fire disturbance, snow cover, land cover and land use change, soil moisture, land surface temperature (LST) and emissivity. Recent additions to the focus areas include vegetation indices and biomass. The development of best practice validation protocols is a core activity of CEOS LPV with the objective to standardize the evaluation of land surface products. LPV has identified four validation levels corresponding to increasing spatial and temporal representativeness of reference samples used to perform validation. Best practice validation protocols (1) provide the definition of variables, ancillary information and uncertainty metrics, (2) describe available data sources and methods to establish reference validation datasets with SI traceability, and (3) describe evaluation methods and reporting. An overview on validation best practice components will be presented based on the LAI and LST protocol efforts to date.

Interaction of Convective Organization and Monsoon Precipitation, Atmosphere, Surface and Sea (INCOMPASS)

NASA Astrophysics Data System (ADS)

Turner, Andrew; Bhat, Gs; Evans, Jonathan; Marsham, John; Martin, Gill; Parker, Douglas; Taylor, Chris; Bhattacharya, Bimal; Madan, Ranju; Mitra, Ashis; Mrudula, Gm; Muddu, Sekhar; Pattnaik, Sandeep; Rajagopal, En; Tripathi, Sachida

2015-04-01

The monsoon supplies the majority of water in South Asia, making understanding and predicting its rainfall vital for the growing population and economy. However, modelling and forecasting the monsoon from days to the season ahead is limited by large model errors that develop quickly, with significant inter-model differences pointing to errors in physical parametrizations such as convection, the boundary layer and land surface. These errors persist into climate projections and many of these errors persist even when increasing resolution. At the same time, a lack of detailed observations is preventing a more thorough understanding of monsoon circulation and its interaction with the land surface: a process governed by the boundary layer and convective cloud dynamics. The INCOMPASS project will support and develop modelling capability in Indo-UK monsoon research, including test development of a new Met Office Unified Model 100m-resolution domain over India. The first UK detachment of the FAAM research aircraft to India, in combination with an intensive ground-based observation campaign, will gather new observations of the surface, boundary layer structure and atmospheric profiles to go with detailed information on the timing of monsoon rainfall. Observations will be focused on transects in the northern plains of India (covering a range of surface types from irrigated to rain-fed agriculture, and wet to dry climatic zones) and across the Western Ghats and rain shadow in southern India (including transitions from land to ocean and across orography). A pilot observational campaign is planned for summer 2015, with the main field campaign to take place during spring/summer 2016. This project will advance our ability to forecast the monsoon, through a programme of measurements and modelling that aims to capture the key surface-atmosphere feedback processes in models. The observational analysis will allow a unique and unprecedented characterization of monsoon processes that will feed directly into model development at the UK Met Office and Indian NCMRWF, through model evaluation at a range of scales and leading to model improvement by working directly with parametrization developers. The project will institute a new long-term series of measurements of land surface fluxes, a particularly unconstrained observation for India, through eddy covariance flux towers. Combined with detailed land surface modelling using the Joint UK Land Environment Simulator (JULES) model, this will allow testing of land surface initialization in monsoon forecasts and improved land-atmosphere coupling.

Mapping and estimating land change between 2001 and 2013 in a heterogeneous landscape in West Africa: Loss of forestlands and capacity building opportunities

NASA Astrophysics Data System (ADS)

Badjana, Hèou Maléki; Olofsson, Pontus; Woodcock, Curtis E.; Helmschrot, Joerg; Wala, Kpérkouma; Akpagana, Koffi

2017-12-01

In West Africa, accurate classification of land cover and land change remains a big challenge due to the patchy and heterogeneous nature of the landscape. Limited data availability, human resources and technical capacities, further exacerbate the challenge. The result is a region that is among the more understudied areas in the world, which in turn has resulted in a lack of appropriate information required for sustainable natural resources management. The objective of this paper is to explore open source software and easy-to-implement approaches to mapping and estimation of land change that are transferrable to local institutions to increase capacity in the region, and to provide updated information on the regional land surface dynamics. To achieve these objectives, stable land cover and land change between 2001 and 2013 in the Kara River Basin in Togo and Benin were mapped by direct multitemporal classification of Landsat data by parameterization and evaluation of two machine-learning algorithms. Areas of land cover and change were estimated by application of an unbiased estimator to sample data following international guidelines. A prerequisite for all tools and methods was implementation in an open source environment, and adherence to international guidelines for reporting land surface activities. Findings include a recommendation of the Random Forests algorithm as implemented in Orfeo Toolbox, and a stratified estimation protocol - all executed in the QGIS graphical use interface. It was found that despite an estimated reforestation of 10,0727 ± 3480 ha (95% confidence interval), the combined rate of forest and savannah loss amounted to 56,271 ± 9405 ha (representing a 16% loss of the forestlands present in 2001), resulting in a rather sharp net loss of forestlands in the study area. These dynamics had not been estimated prior to this study, and the results will provide useful information for decision making pertaining to natural resources management, land management planning, and the implementation of the United Nations Collaborative Programme on Reducing Emissions from Deforestation and Forest Degradation in Developing Countries (UN-REDD).

Information-Theoretic Benchmarking of Land Surface Models

NASA Astrophysics Data System (ADS)

Nearing, Grey; Mocko, David; Kumar, Sujay; Peters-Lidard, Christa; Xia, Youlong

2016-04-01

Benchmarking is a type of model evaluation that compares model performance against a baseline metric that is derived, typically, from a different existing model. Statistical benchmarking was used to qualitatively show that land surface models do not fully utilize information in boundary conditions [1] several years before Gong et al [2] discovered the particular type of benchmark that makes it possible to *quantify* the amount of information lost by an incorrect or imperfect model structure. This theoretical development laid the foundation for a formal theory of model benchmarking [3]. We here extend that theory to separate uncertainty contributions from the three major components of dynamical systems models [4]: model structures, model parameters, and boundary conditions describe time-dependent details of each prediction scenario. The key to this new development is the use of large-sample [5] data sets that span multiple soil types, climates, and biomes, which allows us to segregate uncertainty due to parameters from the two other sources. The benefit of this approach for uncertainty quantification and segregation is that it does not rely on Bayesian priors (although it is strictly coherent with Bayes' theorem and with probability theory), and therefore the partitioning of uncertainty into different components is *not* dependent on any a priori assumptions. We apply this methodology to assess the information use efficiency of the four land surface models that comprise the North American Land Data Assimilation System (Noah, Mosaic, SAC-SMA, and VIC). Specifically, we looked at the ability of these models to estimate soil moisture and latent heat fluxes. We found that in the case of soil moisture, about 25% of net information loss was from boundary conditions, around 45% was from model parameters, and 30-40% was from the model structures. In the case of latent heat flux, boundary conditions contributed about 50% of net uncertainty, and model structures contributed about 40%. There was relatively little difference between the different models. 1. G. Abramowitz, R. Leuning, M. Clark, A. Pitman, Evaluating the performance of land surface models. Journal of Climate 21, (2008). 2. W. Gong, H. V. Gupta, D. Yang, K. Sricharan, A. O. Hero, Estimating Epistemic & Aleatory Uncertainties During Hydrologic Modeling: An Information Theoretic Approach. Water Resources Research 49, 2253-2273 (2013). 3. G. S. Nearing, H. V. Gupta, The quantity and quality of information in hydrologic models. Water Resources Research 51, 524-538 (2015). 4. H. V. Gupta, G. S. Nearing, Using models and data to learn: A systems theoretic perspective on the future of hydrological science. Water Resources Research 50(6), 5351-5359 (2014). 5. H. V. Gupta et al., Large-sample hydrology: a need to balance depth with breadth. Hydrology and Earth System Sciences Discussions 10, 9147-9189 (2013).

On the relationship between land surface infrared emissivity and soil moisture

NASA Astrophysics Data System (ADS)

Zhou, Daniel K.; Larar, Allen M.; Liu, Xu

2018-01-01

The relationship between surface infrared (IR) emissivity and soil moisture content has been investigated based on satellite measurements. Surface soil moisture content can be estimated by IR remote sensing, namely using the surface parameters of IR emissivity, temperature, vegetation coverage, and soil texture. It is possible to separate IR emissivity from other parameters affecting surface soil moisture estimation. The main objective of this paper is to examine the correlation between land surface IR emissivity and soil moisture. To this end, we have developed a simple yet effective scheme to estimate volumetric soil moisture (VSM) using IR land surface emissivity retrieved from satellite IR spectral radiance measurements, assuming those other parameters impacting the radiative transfer (e.g., temperature, vegetation coverage, and surface roughness) are known for an acceptable time and space reference location. This scheme is applied to a decade of global IR emissivity data retrieved from MetOp-A infrared atmospheric sounding interferometer measurements. The VSM estimated from these IR emissivity data (denoted as IR-VSM) is used to demonstrate its measurement-to-measurement variations. Representative 0.25-deg spatially-gridded monthly-mean IR-VSM global datasets are then assembled to compare with those routinely provided from satellite microwave (MW) multisensor measurements (denoted as MW-VSM), demonstrating VSM spatial variations as well as seasonal-cycles and interannual variability. Initial positive agreement is shown to exist between IR- and MW-VSM (i.e., R2 = 0.85). IR land surface emissivity contains surface water content information. So, when IR measurements are used to estimate soil moisture, this correlation produces results that correspond with those customarily achievable from MW measurements. A decade-long monthly-gridded emissivity atlas is used to estimate IR-VSM, to demonstrate its seasonal-cycle and interannual variation, which is spatially coherent and consistent with that from MW measurements, and, moreover, to achieve our objective of investigating the relationship between land surface IR emissivity and soil moisture.

São Paulo urban heat islands have a higher incidence of dengue than other urban areas.

PubMed

Araujo, Ricardo Vieira; Albertini, Marcos Roberto; Costa-da-Silva, André Luis; Suesdek, Lincoln; Franceschi, Nathália Cristina Soares; Bastos, Nancy Marçal; Katz, Gizelda; Cardoso, Vivian Ailt; Castro, Bronislawa Ciotek; Capurro, Margareth Lara; Allegro, Vera Lúcia Anacleto Cardoso

2015-01-01

Urban heat islands are characterized by high land surface temperature, low humidity, and poor vegetation, and considered to favor the transmission of the mosquito-borne dengue fever that is transmitted by the Aedes aegypti mosquito. We analyzed the recorded dengue incidence in Sao Paulo city, Brazil, in 2010-2011, in terms of multiple environmental and socioeconomic variables. Geographical information systems, thermal remote sensing images, and census data were used to classify city areas according to land surface temperature, vegetation cover, population density, socioeconomic status, and housing standards. Of the 7415 dengue cases, a majority (93.1%) mapped to areas with land surface temperature >28°C. The dengue incidence rate (cases per 100,000 inhabitants) was low (3.2 cases) in high vegetation cover areas, but high (72.3 cases) in low vegetation cover areas where the land surface temperature was 29±2°C. Interestingly, a multiple cluster analysis phenogram showed more dengue cases clustered in areas of land surface temperature >32°C, than in areas characterized as low socioeconomic zones, high population density areas, or slum-like areas. In laboratory experiments, A. aegypti mosquito larval development, blood feeding, and oviposition associated positively with temperatures of 28-32°C, indicating these temperatures to be favorable for dengue transmission. Thus, among all the variables studied, dengue incidence was most affected by the temperature. Copyright © 2014 Elsevier Editora Ltda. All rights reserved.

Estimating the spatial distribution of soil moisture based on Bayesian maximum entropy method with auxiliary data from remote sensing

NASA Astrophysics Data System (ADS)

Gao, Shengguo; Zhu, Zhongli; Liu, Shaomin; Jin, Rui; Yang, Guangchao; Tan, Lei

2014-10-01

Soil moisture (SM) plays a fundamental role in the land-atmosphere exchange process. Spatial estimation based on multi in situ (network) data is a critical way to understand the spatial structure and variation of land surface soil moisture. Theoretically, integrating densely sampled auxiliary data spatially correlated with soil moisture into the procedure of spatial estimation can improve its accuracy. In this study, we present a novel approach to estimate the spatial pattern of soil moisture by using the BME method based on wireless sensor network data and auxiliary information from ASTER (Terra) land surface temperature measurements. For comparison, three traditional geostatistic methods were also applied: ordinary kriging (OK), which used the wireless sensor network data only, regression kriging (RK) and ordinary co-kriging (Co-OK) which both integrated the ASTER land surface temperature as a covariate. In Co-OK, LST was linearly contained in the estimator, in RK, estimator is expressed as the sum of the regression estimate and the kriged estimate of the spatially correlated residual, but in BME, the ASTER land surface temperature was first retrieved as soil moisture based on the linear regression, then, the t-distributed prediction interval (PI) of soil moisture was estimated and used as soft data in probability form. The results indicate that all three methods provide reasonable estimations. Co-OK, RK and BME can provide a more accurate spatial estimation by integrating the auxiliary information Compared to OK. RK and BME shows more obvious improvement compared to Co-OK, and even BME can perform slightly better than RK. The inherent issue of spatial estimation (overestimation in the range of low values and underestimation in the range of high values) can also be further improved in both RK and BME. We can conclude that integrating auxiliary data into spatial estimation can indeed improve the accuracy, BME and RK take better advantage of the auxiliary information compared to Co-OK, and BME outperforms RK by integrating the auxiliary data in a probability form.

Estimating Evapotranspiration with Land Data Assimilation Systems

NASA Technical Reports Server (NTRS)

Peters-Lidard, C. D.; Kumar, S. V.; Mocko, D. M.; Tian, Y.

2011-01-01

Advancements in both land surface models (LSM) and land surface data assimilation, especially over the last decade, have substantially advanced the ability of land data assimilation systems (LDAS) to estimate evapotranspiration (ET). This article provides a historical perspective on international LSM intercomparison efforts and the development of LDAS systems, both of which have improved LSM ET skill. In addition, an assessment of ET estimates for current LDAS systems is provided along with current research that demonstrates improvement in LSM ET estimates due to assimilating satellite-based soil moisture products. Using the Ensemble Kalman Filter in the Land Information System, we assimilate both NASA and Land Parameter Retrieval Model (LPRM) soil moisture products into the Noah LSM Version 3.2 with the North American LDAS phase 2 (NLDAS-2) forcing to mimic the NLDAS-2 configuration. Through comparisons with two global reference ET products, one based on interpolated flux tower data and one from a new satellite ET algorithm, over the NLDAS2 domain, we demonstrate improvement in ET estimates only when assimilating the LPRM soil moisture product.

A Simple Downscaling Algorithm for Remotely Sensed Land Surface Temperature

NASA Astrophysics Data System (ADS)

Sandholt, I.; Nielsen, C.; Stisen, S.

2009-05-01

The method is illustrated using a combination of MODIS NDVI data with a spatial resolution of 250m and 3 Km Meteosat Second Generation SEVIRI LST data. Geostationary Earth Observation data carry a large potential for assessment of surface state variables. Not the least the European Meteosat Second Generation platform with its SEVIRI sensor is well suited for studies of the dynamics of land surfaces due to its high temporal frequency (15 minutes) and its red, Near Infrared (NIR) channels that provides vegetation indices, and its two split window channels in the thermal infrared for assessment of Land Surface Temperature (LST). For some applications the spatial resolution in geostationary data is too coarse. Due to the low statial resolution of 4.8 km at nadir for the SEVIRI sensor, a means of providing sub pixel information is sought for. By combining and properly scaling two types of satellite images, namely data from the MODIS sensor onboard the polar orbiting platforms TERRA and AQUA and the coarse resolution MSG-SEVIRI, we exploit the best from two worlds. The vegetation index/surface temperature space has been used in a vast number of studies for assessment of air temperature, soil moisture, dryness indices, evapotranspiration and for studies of land use change. In this paper, we present an improved method to derive a finer resolution Land Surface Temperature (LST). A new, deterministic scaling method has been applied, and is compared to existing deterministic downscaling methods based on LST and NDVI. We also compare our results from in situ measurements of LST from the Dahra test site in West Africa.

Building hydrologic information systems to promote climate resilience in the Blue Nile/Abay higlands

USDA-ARS?s Scientific Manuscript database

Climate adaptation requires information about climate and land-surface conditions – spatially distributed, and at scales of human influence (the field scale). This article describes a project aimed at combining meteorological data, satellite remote sensing, hydrologic modeling, and downscaled clima...

Development and Implementation of the DTOPLATS-MP land surface model over the Continental US at 30 meters

NASA Astrophysics Data System (ADS)

Chaney, N.; Wood, E. F.

2014-12-01

The increasing accessibility of high-resolution land data (< 100 m) and high performance computing allows improved parameterizations of subgrid hydrologic processes in macroscale land surface models. Continental scale fully distributed modeling at these spatial scales is possible; however, its practicality for operational use is still unknown due to uncertainties in input data, model parameters, and storage requirements. To address these concerns, we propose a modeling framework that provides the spatial detail of a fully distributed model yet maintains the benefits of a semi-distributed model. In this presentation we will introduce DTOPLATS-MP, a coupling between the NOAH-MP land surface model and the Dynamic TOPMODEL hydrologic model. This new model captures a catchment's spatial heterogeneity by clustering high-resolution land datasets (soil, topography, and land cover) into hundreds of hydrologic similar units (HSUs). A prior DEM analysis defines the connections between each HSU. At each time step, the 1D land surface model updates each HSU; the HSUs then interact laterally via the subsurface and surface. When compared to the fully distributed form of the model, this framework allows a significant decrease in computation and storage while providing most of the same information and enabling parameter transferability. As a proof of concept, we will show how this new modeling framework can be run over CONUS at a 30-meter spatial resolution. For each catchment in the WBD HUC-12 dataset, the model is run between 2002 and 2012 using available high-resolution continental scale land and meteorological datasets over CONUS (dSSURGO, NLCD, NED, and NCEP Stage IV). For each catchment, the model is run with 1000 model parameter sets obtained from a Latin hypercube sample. This exercise will illustrate the feasibility of running the model operationally at continental scales while accounting for model parameter uncertainty.

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

PubMed

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.

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

PubMed Central

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

2016-01-01

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. PMID:27598186

Relay Support for the Mars Science Laboratory Mission

NASA Technical Reports Server (NTRS)

Edwards, Charles D. Jr,; Bell, David J.; Gladden, Roy E.; Ilott, Peter A.; Jedrey, Thomas C.; Johnston, M. Daniel; Maxwell, Jennifer L.; Mendoza, Ricardo; McSmith, Gaylon W.; Potts, Christopher L.;

Expansion of the Real-time Sport-land Information System for NOAA / National Weather Service Situational Awareness and Local Modeling Applications

NASA Technical Reports Server (NTRS)

Case, Jonathan L.; White, Kristopher D.

2014-01-01

The NASA Short-term Prediction Research and Transition (SPoRT) Center in Huntsville, AL (Jedlovec 2013; Ralph et al. 2013; Merceret et al. 2013) is running a real-time configuration of the Noah land surface model (LSM) within the NASA Land Information System (LIS) framework (hereafter referred to as the "SPoRT-LIS"). Output from the real-time SPoRT-LIS is used for (1) initializing land surface variables for local modeling applications, and (2) displaying in decision support systems for situational awareness and drought monitoring at select NOAA/National Weather Service (NWS) partner offices. The SPoRT-LIS is currently run over a domain covering the southeastern half of the Continental United States (CONUS), with an additional experimental real-time run over the entire CONUS and surrounding portions of southern Canada and northern Mexico. The experimental CONUS run incorporates hourly quantitative precipitation estimation (QPE) from the National Severe Storms Laboratory Multi- Radar Multi-Sensor (MRMS) product (Zhang et al. 2011, 2014), which will be transitioned into operations at the National Centers for Environmental Prediction (NCEP) in Fall 2014. This paper describes the current and experimental SPoRT-LIS configurations, and documents some of the limitations still remaining through the advent of MRMS precipitation analyses in the SPoRT-LIS land surface model (LSM) simulations. Section 2 gives background information on the NASA LIS and describes the realtime SPoRT-LIS configurations being compared. Section 3 presents recent work done to develop a training module on situational awareness applications of real-time SPoRT-LIS output. Comparisons between output from the two SPoRT-LIS runs are shown in Section 4, including a documentation of issues encountered in using the MRMS precipitation dataset. A summary and future work in given in Section 5, followed by acknowledgements and references.

Improving land surface parameter retrieval by integrating plant traits priors in the MULTIPLY data assimilation platform

NASA Astrophysics Data System (ADS)

Corbin, A. E.; Timmermans, J.; Hauser, L.; Bodegom, P. V.; Soudzilovskaia, N. A.

2017-12-01

There is a growing demand for accurate land surface parameterization from remote sensing (RS) observations. This demand has not been satisfied, because most estimation schemes apply 1) a single-sensor single-scale approach, and 2) require specific key-variables to be `guessed'. This is because of the relevant observational information required to accurately retrieve parameters of interest. Consequently, many schemes assume specific variables to be constant or not present; subsequently leading to more uncertainty. In this aspect, the MULTIscale SENTINEL land surface information retrieval Platform (MULTIPLY) was created. MULTIPLY couples a variety of RS sources with Radiative Transfer Models (RTM) over varying spectral ranges using data-assimilation to estimate geophysical parameters. In addition, MULTIPLY also uses prior information about the land surface to constrain the retrieval problem. This research aims to improve the retrieval of plant biophysical parameters through the use of priors of biophysical parameters/plant traits. Of particular interest are traits (physical, morphological or chemical trait) affecting individual performance and fitness of species. Plant traits that are able to be retrieved via RS and with RTMs include traits such as leaf-pigments, leaf water, LAI, phenols, C/N, etc. In-situ data for plant traits that are retrievable via RS techniques were collected for a meta-analysis from databases such as TRY, Ecosis, and individual collaborators. Of particular interest are the following traits: chlorophyll, carotenoids, anthocyanins, phenols, leaf water, and LAI. ANOVA statistics were generated for each traits according to species, plant functional groups (such as evergreens, grasses, etc.), and the trait itself. Afterwards, traits were also compared using covariance matrices. Using these as priors, MULTIPLY was is used to retrieve several plant traits in two validation sites in the Netherlands (Speulderbos) and in Finland (Sodankylä). Initial comparisons show significant improved results over non-a priori based retrievals.

Characterizing Urban Volumetry Using LIDAR Data

NASA Astrophysics Data System (ADS)

Santos, T.; Rodrigues, A. M.; Tenedório, J. A.

2013-05-01

Urban indicators are efficient tools designed to simplify, quantify and communicate relevant information for land planners. Since urban data has a strong spatial representation, one can use geographical data as the basis for constructing information regarding urban environments. One important source of information about the land status is imagery collected through remote sensing. Afterwards, using digital image processing techniques, thematic detail can be extracted from those images and used to build urban indicators. Most common metrics are based on area (2D) measurements. These include indicators like impervious area per capita or surface occupied by green areas, having usually as primary source a spectral image obtained through a satellite or airborne camera. More recently, laser scanning data has become available for large-scale applications. Such sensors acquire altimetric information and are used to produce Digital Surface Models (DSM). In this context, LiDAR data available for the city is explored along with demographic information, and a framework to produce volumetric (3D) urban indexes is proposed, and measures like Built Volume per capita, Volumetric Density and Volumetric Homogeneity are computed.

Orientale and South Pole-Aitken basins on the Moon: Preliminary Galileo imaging results

NASA Technical Reports Server (NTRS)

Head, J.; Fischer, E.; Murchie, S.; Pieters, C.; Plutchak, J.; Sunshine, J.; Belton, M.; Carr, M.; Chapman, C.; Davies, M.

1991-01-01

During the Earth-Moon flyby the Galileo Solid State Imaging System obtained new information on the landscape and physical geology of the Moon. Multicolor Galileo images of the Moon reveal variations in color properties of the lunar surface. Using returned lunar samples as a key, the color differences can be interpreted in terms of variations in the mineral makeup of the lunar rocks and soil. The combined results of Apollo landings and multicolor images from Galileo allow extrapolation of surface composition to areas distant from the landing sites, including the far side invisible from Earth.

Land and federal mineral ownership coverage for the Uinta Basin, Wasatch Plateau and surrounding areas, northeastern Utah

USGS Publications Warehouse

Biewick, L.H.; Green, G.A.

1999-01-01

This Arc/Info coverage contains land status and Federal and State mineral ownership for approximately 25,900 square miles in northeastern Utah. The polygon coverage (which is also provided here as a shapefile) contains three attributes of ownership information for each polygon. One attribute indicates whether the surface is State owned, privately owned, consists of Tribal and Indian lands, or, if Federally owned, which Federal agency manages the land surface. Another attribute indicates where the Utah School and Institutional Trust Lands Administration (SITLA) maintains full or partial subsurface mineral rights. The third attribute indicates which energy minerals, if any, are owned by the Federal govenment. This coverage is based on land management status and Federal and State mineral ownership data compiled by the U.S. Geological Survey (USGS), the former U.S. Bureau of Mines (USBM), and the Utah School and Institutional Trust Lands Administration at a scale of 1:100,000. This coverage was compiled primarily to serve the USGS National Oil and Gas Resource Assessment Project in the Uinta-Piceance Basin Province and the USGS National Coal Resource Assessment Project in the Colorado Plateau.

"Detecting people"

NASA Astrophysics Data System (ADS)

Arneth, A.; Pugh, T.; Krause, A.; Bayer, A.; Lindeskog, M.

2015-12-01

Land-use change (LUC) is known to significantly affect biogeochemical cycles as well as surface energy partitioning - with important implications, ranging from understanding present-day measurements, to simulations of climate change and impacts on ecosystems, to assessments of the mitigation potential of land-based mitigation policies on ecosystems. When connecting observations of surface-atmosphere interactions and modelling at different scales, two important issues in this context are: legacy effects (e.g., to what degree and for how long does past LUC at a given location affect vegetation structure, CO2 fluxes and carbon pools), and sub-grid variability of the land-use change per se (e.g., whether bi-directional information about changes are taken into consideration). Both are important when bridging between scales (in time and in space) to enhance long-term observation networks. This contribution to the session will be very much from a process-based modelling perspective. Using a second generation dynamic global vegetation model we will show how different land-use histories impact vegetation and soil recovery (carbon pool-size, fluxes) differently, depending on the type of previous land-use, its length, and on the type of biome. We also study the difference between "gross" and "net" LUC accounting for simulated carbon cycling. Two important aspects, considering the session's objectives, are: 1) When establishing and developing observation networks, land-use history is key information for the interpretation of measured fluxes and needs to be collected and made available;, 2) Observation networks that "operate" solely in the natural science domain need to increasingly seek cooperation with socio-economic observations (such as land-use change, land management) in order to gain better understanding of coupled socio-ecological systems.

Using a spatially-distributed hydrologic biogeochemistry model to study the spatial variation of carbon processes in a Critical Zone Observatory

NASA Astrophysics Data System (ADS)

Shi, Y.; Eissenstat, D. M.; Davis, K. J.; He, Y.

2016-12-01

Forest carbon processes are affected by, among other factors, soil moisture, soil temperature, soil nutrients and solar radiation. Most of the current biogeochemical models are 1-D and represent one point in space. Therefore, they cannot resolve the topographically driven hill-slope land surface heterogeneity or the spatial pattern of nutrient availability. A spatially distributed forest ecosystem model, Flux-PIHM-BGC, has been developed by coupling a 1-D mechanistic biogeochemical model Biome-BGC (BBGC) with a spatially distributed land surface hydrologic model, Flux-PIHM. Flux-PIHM is a coupled physically based model, which incorporates a land-surface scheme into the Penn State Integrated Hydrologic Model (PIHM). The land surface scheme is adapted from the Noah land surface model. Flux-PIHM is able to represent the link between groundwater and the surface energy balance, as well as the land surface heterogeneities caused by topography. In the coupled Flux-PIHM-BGC model, each Flux-PIHM model grid couples a 1-D BBGC model, while soil nitrogen is transported among model grids via subsurface water flow. In each grid, Flux-PIHM provides BBGC with soil moisture, soil temperature, and solar radiation information, while BBGC provides Flux-PIHM with leaf area index. The coupled Flux-PIHM-BGC model has been implemented at the Susquehanna/Shale Hills critical zone observatory (SSHCZO). Model results suggest that the vegetation and soil carbon distribution is primarily constrained by nitorgen availability (affected by nitorgen transport via topographically driven subsurface flow), and also constrained by solar radiation and root zone soil moisture. The predicted vegetation and soil carbon distribution generally agrees with the macro pattern observed within the watershed. The coupled ecosystem-hydrologic model provides an important tool to study the impact of topography on watershed carbon processes, as well as the impact of climate change on water resources.

Apollo 17

NASA Technical Reports Server (NTRS)

Garrett, David

1972-01-01

This is the Press Kit that was given to the various media outlets that were interested in covering the Apollo 17 mission. It includes information about the moon, lunar science, concentrating on the planned mission. The kit includes information about the flight, and the trajectory, planned orbit insertion maneuvers, the extravehicular mission events, a comparison with the Apollo 16, a map of the lunar surface, and the surface activity, information about the Taurus-Littrow landing site, the planned science experiments, the power source for the experiment package and diagrams of some of the instrumentation that was used to perform the experiments.

Techniques for the Retrieval of Aerosol Properties Over Land and Ocean Using Multi-angle Imaging

NASA Technical Reports Server (NTRS)

Martonchik, John V.; Diner, David J.; Kahn, Ralph; Ackerman, Thomas P.; Verstraete, Michel M.; Pinty, Bernard; Gordon, Howard R.

1997-01-01

Aerosols are believed to play a direct role in the radiation budget of Earth but their net radiative effect is not well established, particularly on regional scales. Whether aerosols heat or cool a given location depends on their composition and column amount and also on the surface albedo, information that is not routinely available, especially over land.

ICLUS Tools and Datasets (Version 1.3 & 1.3.1) | Science ...

EPA Pesticide Factsheets

As a part of the Integrated Climate and Land Use Scenarios (ICLUS) project, this Geographic Information System (GIS) tool can be used to generate scenarios of housing-density changes and calculate impervious surface cover for the conterminous United States. The ICLUS User’s Guide accompanies the tool. This product distributes the population projections and creates land use data described in the 2009 EPA report

ICLUS Tools and Datasets (Version 1.3.2) | Science Inventory ...

EPA Pesticide Factsheets

As a part of the Integrated Climate and Land Use Scenarios (ICLUS) project, this Geographic Information System (GIS) tool can be used to generate scenarios of housing-density changes and calculate impervious surface cover for the conterminous United States. The ICLUS User’s Guide accompanies the tool. This product distributes the population projections and creates land use data described in the 2009 EPA report

Using Landsat imagery to detect, monitor, and project net landscape change

USGS Publications Warehouse

Reker, Ryan R.; Sohl, Terry L.; Gallant, Alisa L.

2015-01-01

Detailed landscape information is a necessary component to bird habitat conservation planning. The U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center has been providing information on the Earth’s surface for over 40 years via the continuous series of Landsat satellites. In addition to operating, processing, and disseminating satellite images, EROS is the home to nationwide and global landscape mapping, monitoring, and projection products, including:National Land Cover Database (NLCD) – the definitive land cover dataset for the U.S., with updates occurring at five-year intervals;Global Land Cover Monitoring – producing 30m resolution global land cover;LANDFIRE – Landscape Fire and Resource Management Planning Tools–EROS is a partner in this joint program between U.S. Department of Agriculture and Department of Interior that produces consistent, comprehensive, geospatial data and databases that describe vegetation, wildland fuel, and fire regimes across the U.S.;Land Cover Trends – a landscape monitoring and assessment effort to understand the rates, trends, causes, and consequences of contemporary U.S. land use and land cover change; andLand Use and Land Cover (LULC) Modeling – a project extending contemporary databases of landscape change forward and backward in time through moderate-resolution land cover projections.

Subsidence (2004-2009) in and near lakebeds of the Mojave River and Morongo groundwater basins, southwest Mojave Desert, California

USGS Publications Warehouse

Solt, Mike; Sneed, Michelle

2014-01-01

Subsidence, in the vicinity of dry lakebeds, within the Mojave River and Morongo groundwater basins of the southwest Mojave Desert has been measured by Interferometric Synthetic Aperture Radar (InSAR). The investigation has focused on determining the location, extent, and magnitude of changes in land-surface elevation. In addition, the relation of changes in land-surface elevation to changes in groundwater levels and lithology was explored. This report is the third in a series of reports investigating land-surface elevation changes in the Mojave and Morongo Groundwater Basins, California. The first report, U.S. Geological Survey (USGS) Water-Resources Investigations Report 03-4015 by Sneed and others (2003), describes historical subsidence and groundwater-level changes in the southwest Mojave Desert from 1969 to 1999. The second report, U.S. Geological Survey Water-Resources Investigations Report 07-5097, an online interactive report and map, by Sneed and Brandt (2007), describes subsidence and groundwater-level changes in the southwest Mojave Desert from 1999 to 2004. The purpose of this report is to document an updated assessment of subsidence in these lakebeds and selected neighboring areas from 2004 to 2009 as measured by InSAR methods. In addition, continuous Global Positioning System (GPS)(2005-10), groundwater level (1951-2010), and lithologic data, if available, were used to characterize compaction mechanisms in these areas. The USGS California Water Science Center’s interactive website for the Mojave River and Morongo groundwater basins was created to centralize information pertaining to land subsidence and water levels and to allow readers to access available data and related reports online. An interactive map of land subsidence and water levels in the Mojave River and Morongo groundwater basins displays InSAR interferograms, subsidence areas, subsidence contours, hydrographs, well information, and water-level contours. Background information, including a basic description of the mechanics of land subsidence and InSAR, as well as a description of the study area, is presented within the Mojave Water Resources Interactive Map and report.

An energy balance approach for mapping crop waterstress and yield impacts over the Czech Republic

USDA-ARS?s Scientific Manuscript database

There is a growing demand for timely, spatially distributed information regarding crop condition and water use to inform agricultural decision making and yield forecasting efforts. Remote sensing of land-surface temperature has proven valuable for mapping evapotranspiration (ET) and crop stress from...

Using machine learning to produce near surface soil moisture estimates from deeper in situ records at U.S. Climate Reference Network (USCRN) locations: Analysis and applications to AMSR-E satellite validation

USDA-ARS?s Scientific Manuscript database

Surface soil moisture is critical parameter for understanding the energy flux at the land atmosphere boundary. Weather modeling, climate prediction, and remote sensing validation are some of the applications for surface soil moisture information. The most common in situ measurement for these purpo...

Land cover mapping of North and Central America—Global Land Cover 2000

USGS Publications Warehouse

Latifovic, Rasim; Zhu, Zhi-Liang

2004-01-01

The Land Cover Map of North and Central America for the year 2000 (GLC 2000-NCA), prepared by NRCan/CCRS and USGS/EROS Data Centre (EDC) as a regional component of the Global Land Cover 2000 project, is the subject of this paper. A new mapping approach for transforming satellite observations acquired by the SPOT4/VGTETATION (VGT) sensor into land cover information is outlined. The procedure includes: (1) conversion of daily data into 10-day composite; (2) post-seasonal correction and refinement of apparent surface reflectance in 10-day composite images; and (3) extraction of land cover information from the composite images. The pre-processing and mosaicking techniques developed and used in this study proved to be very effective in removing cloud contamination, BRDF effects, and noise in Short Wave Infra-Red (SWIR). The GLC 2000-NCA land cover map is provided as a regional product with 28 land cover classes based on modified Federal Geographic Data Committee/Vegetation Classification Standard (FGDC NVCS) classification system, and as part of a global product with 22 land cover classes based on Land Cover Classification System (LCCS) of the Food and Agriculture Organisation. The map was compared on both areal and per-pixel bases over North and Central America to the International Geosphere–Biosphere Programme (IGBP) global land cover classification, the University of Maryland global land cover classification (UMd) and the Moderate Resolution Imaging Spectroradiometer (MODIS) Global land cover classification produced by Boston University (BU). There was good agreement (79%) on the spatial distribution and areal extent of forest between GLC 2000-NCA and the other maps, however, GLC 2000-NCA provides additional information on the spatial distribution of forest types. The GLC 2000-NCA map was produced at the continental level incorporating specific needs of the region.

Surface and Atmospheric Contributions to Passive Microwave Brightness Temperatures for Falling Snow Events

NASA Technical Reports Server (NTRS)

Skofronick-Jackson, Gail; Johnson, Benjamin T.

2011-01-01

Physically based passive microwave precipitation retrieval algorithms require a set of relationships between satellite -observed brightness temperatures (TBs) and the physical state of the underlying atmosphere and surface. These relationships are nonlinear, such that inversions are ill ]posed especially over variable land surfaces. In order to elucidate these relationships, this work presents a theoretical analysis using TB weighting functions to quantify the percentage influence of the TB resulting from absorption, emission, and/or reflection from the surface, as well as from frozen hydrometeors in clouds, from atmospheric water vapor, and from other contributors. The percentage analysis was also compared to Jacobians. The results are presented for frequencies from 10 to 874 GHz, for individual snow profiles, and for averages over three cloud-resolving model simulations of falling snow. The bulk structure (e.g., ice water path and cloud depth) of the underlying cloud scene was found to affect the resultant TB and percentages, producing different values for blizzard, lake effect, and synoptic snow events. The slant path at a 53 viewing angle increases the hydrometeor contributions relative to nadir viewing channels. Jacobians provide the magnitude and direction of change in the TB values due to a change in the underlying scene; however, the percentage analysis provides detailed information on how that change affected contributions to the TB from the surface, hydrometeors, and water vapor. The TB percentage information presented in this paper provides information about the relative contributions to the TB and supplies key pieces of information required to develop and improve precipitation retrievals over land surfaces.

Using NASA Earth Observing Satellites and Statistical Model Analysis to Monitor Vegetation and Habitat Rehabilitation in Southwest Virginia's Reclaimed Mine Lands

NASA Astrophysics Data System (ADS)

Tate, Z.; Dusenge, D.; Elliot, T. S.; Hafashimana, P.; Medley, S.; Porter, R. P.; Rajappan, R.; Rodriguez, P.; Spangler, J.; Swaminathan, R. S.; VanGundy, R. D.

2014-12-01

The majority of the population in southwest Virginia depends economically on coal mining. In 2011, coal mining generated $2,000,000 in tax revenue to Wise County alone. However, surface mining completely removes land cover and leaves the land exposed to erosion. The destruction of the forest cover directly impacts local species, as some are displaced and others perish in the mining process. Even though surface mining has a negative impact on the environment, land reclamation efforts are in place to either restore mined areas to their natural vegetated state or to transform these areas for economic purposes. This project aimed to monitor the progress of land reclamation and the effect on the return of local species. By incorporating NASA Earth observations, such as Landsat 8 Operational Land Imager (OLI) and Landsat 5 Thematic Mapper (TM), re-vegetation process in reclamation sites was estimated through a Time series analysis using the Normalized Difference Vegetation Index (NDVI). A continuous source of cloud free images was accomplished by utilizing the Spatial and Temporal Adaptive Reflectance Fusion Model (STAR-FM). This model developed synthetic Landsat imagery by integrating the high-frequency temporal information from Terra/Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) and high-resolution spatial information from Landsat sensors In addition, the Maximum Entropy Modeling (MaxENT), an eco-niche model was used to estimate the adaptation of animal species to the newly formed habitats. By combining factors such as land type, precipitation from Tropical Rainfall Measuring Mission (TRMM), and slope from Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), the MaxENT model produced a statistical analysis on the probability of species habitat. Altogether, the project compiled the ecological information which can be used to identify suitable habitats for local species in reclaimed mined areas.

Quantifying Arctic Terrestrial Environment Behaviors Using Geophysical, Point-Scale and Remote Sensing Data

NASA Astrophysics Data System (ADS)

Dafflon, B.; Hubbard, S. S.; Ulrich, C.; Peterson, J. E.; Wu, Y.; Wainwright, H. M.; Gangodagamage, C.; Kholodov, A. L.; Kneafsey, T. J.

2013-12-01

Improvement in parameterizing Arctic process-rich terrestrial models to simulate feedbacks to a changing climate requires advances in estimating the spatiotemporal variations in active layer and permafrost properties - in sufficiently high resolution yet over modeling-relevant scales. As part of the DOE Next-Generation Ecosystem Experiments (NGEE-Arctic), we are developing advanced strategies for imaging the subsurface and for investigating land and subsurface co-variability and dynamics. Our studies include acquisition and integration of various measurements, including point-based, surface-based geophysical, and remote sensing datasets These data have been collected during a series of campaigns at the NGEE Barrow, AK site along transects that traverse a range of hydrological and geomorphological conditions, including low- to high- centered polygons and drained thaw lake basins. In this study, we describe the use of galvanic-coupled electrical resistance tomography (ERT), capacitively-coupled resistivity (CCR) , permafrost cores, above-ground orthophotography, and digital elevation model (DEM) to (1) explore complementary nature and trade-offs between characterization resolution, spatial extent and accuracy of different datasets; (2) develop inversion approaches to quantify permafrost characteristics (such as ice content, ice wedge frequency, and presence of unfrozen deep layer) and (3) identify correspondences between permafrost and land surface properties (such as water inundation, topography, and vegetation). In terms of methods, we developed a 1D-based direct search approach to estimate electrical conductivity distribution while allowing exploration of multiple solutions and prior information in a flexible way. Application of the method to the Barrow datasets reveals the relative information content of each dataset for characterizing permafrost properties, which shows features variability from below one meter length scales to large trends over more than a kilometer. Further, we used Pole- and Kite-based low-altitude aerial photography with inferred DEM, as well as DEM from LiDAR dataset, to quantify land-surface properties and their co-variability with the subsurface properties. Comparison of the above- and below-ground characterization information indicate that while some permafrost characteristics correspond with changes in hydrogeomorphological expressions, others features show more complex linkages with landscape properties. Overall, our results indicate that remote sensing data, point-scale measurements and surface geophysical measurements enable the identification of regional zones having similar relations between subsurface and land surface properties. Identification of such zonation and associated permafrost-land surface properties can be used to guide investigations of carbon cycling processes and for model parameterization.

The environment of Titan, 1975

NASA Technical Reports Server (NTRS)

1976-01-01

Information regarding the physical characteristics of Titan and atmospheric models necessary to support design and mission planning of spacecraft that are to orbit Titan, enter its atmosphere or land on its surface is given.

An Evaluation of ALOS Data in Disaster Applications

NASA Astrophysics Data System (ADS)

Igarashi, Tamotsu; Igarashi, Tamotsu; Furuta, Ryoich; Ono, Makoto

ALOS is the advanced land observing satellite, providing image data from onboard sensors; PRISM, AVNIR-2 and PALSAR. PRISM is the sensor of panchromatic stereo, high resolution three-line-scanner to characterize the earth surface. The accuracy of position in image and height of Digital Surface Model (DSM) are high, therefore the geographic information extraction is improved in the field of disaster applications with providing images of disaster area. Especially pan-sharpened 3D image composed with PRISM and the four-band visible near-infrared radiometer AVNIR-2 data is expected to provide information to understand the geographic and topographic feature. PALSAR is the advanced multi-functional synthetic aperture radar (SAR) operated in L-band, appropriate for the use of land surface feature characterization. PALSAR has many improvements from JERS-1/SAR, such as high sensitivity, having high resolution, polarimetric and scan SAR observation modes. PALSAR is also applicable for SAR interferometry processing. This paper describes the evaluation of ALOS data characteristic from the view point of disaster applications, through some exercise applications.

Land cover characterization and land surface parameterization research

USGS Publications Warehouse

Steyaert, Louis T.; Loveland, Thomas R.; Parton, William J.

1997-01-01

The understanding of land surface processes and their parameterization in atmospheric, hydrologic, and ecosystem models has been a dominant research theme over the past decade. For example, many studies have demonstrated the key role of land cover characteristics as controlling factors in determining land surface processes, such as the exchange of water, energy, carbon, and trace gases between the land surface and the lower atmosphere. The requirements for multiresolution land cover characteristics data to support coupled-systems modeling have also been well documented, including the need for data on land cover type, land use, and many seasonally variable land cover characteristics, such as albedo, leaf area index, canopy conductance, surface roughness, and net primary productivity. Recently, the developers of land data have worked more closely with the land surface process modelers in these efforts.

Characterizing a New Surface-Based Shortwave Cloud Retrieval Technique, Based on Transmitted Radiance for Soil and Vegetated Surface Types

NASA Technical Reports Server (NTRS)

Coddington, Odele; Pilewskie, Peter; Schmidt, K. Sebastian; McBride, Patrick J.; Vukicevic, Tomislava

2013-01-01

This paper presents an approach using the GEneralized Nonlinear Retrieval Analysis (GENRA) tool and general inverse theory diagnostics including the maximum likelihood solution and the Shannon information content to investigate the performance of a new spectral technique for the retrieval of cloud optical properties from surface based transmittance measurements. The cumulative retrieval information over broad ranges in cloud optical thickness (tau), droplet effective radius (r(sub e)), and overhead sun angles is quantified under two conditions known to impact transmitted radiation; the variability in land surface albedo and atmospheric water vapor content. Our conclusions are: (1) the retrieved cloud properties are more sensitive to the natural variability in land surface albedo than to water vapor content; (2) the new spectral technique is more accurate (but still imprecise) than a standard approach, in particular for tau between 5 and 60 and r(sub e) less than approximately 20 nm; and (3) the retrieved cloud properties are dependent on sun angle for clouds of tau from 5 to 10 and r(sub e) less than 10 nm, with maximum sensitivity obtained for an overhead sun.

Managed Clearings: an Unaccounted Land-cover in Urbanizing Regions

NASA Astrophysics Data System (ADS)

Singh, K. K.; Madden, M.; Meentemeyer, R. K.

2016-12-01

Managed clearings (MC), such as lawns, public parks and grassy transportation medians, are a common and ecologically important land cover type in urbanizing regions, especially those characterized by sprawl. We hypothesize that MC is underrepresented in land cover classification schemes and data products such as NLCD (National Land Cover Database) data, which may impact environmental assessments and models of urban ecosystems. We visually interpreted and mapped fine scale land cover with special attention to MC using 2012 NAIP (National Agriculture Imagery Program) images and compared the output with NLCD data. Areas sampled were 50 randomly distributed 1*1km blocks of land in three cities of the Char-lanta mega-region (Atlanta, Charlotte, and Raleigh). We estimated the abundance of MC relative to other land cover types, and the proportion of land-cover types in NLCD data that are similar to MC. We also assessed if the designations of recreation, transportation, and utility in MC inform the problem differently than simply tallying MC as a whole. 610 ground points, collected using the Google Earth, were used to evaluate accuracy of NLCD data and visual interpretation for consistency. Overall accuracy of visual interpretation and NLCD data was 78% and 58%, respectively. NLCD data underestimated forest and MC by 14.4km2 and 6.4km2, respectively, while overestimated impervious surfaces by 10.2km2 compared to visual interpretation. MC was the second most dominant land cover after forest (40.5%) as it covered about 28% of the total area and about 13% higher than impervious surfaces. Results also suggested that recreation in MC constitutes up to 90% of area followed by transportation and utility. Due to the prevalence of MC in urbanizing regions, the addition of MC to the synthesis of land-cover data can help delineate realistic cover types and area proportions that could inform ecologic/hydrologic models, and allow for accurate prediction of ecological phenomena.

Land and water impacts of oil sands production in Alberta.

PubMed

Jordaan, Sarah M

2012-04-03

Expansion of oil sands development results not only in the release of greenhouse gas emissions, but also impacts land and water resources. Though less discussed internationally due to to their inherently local nature, land and water impacts can be severe. Research in key areas is needed to manage oil sands operations effectively; including improved monitoring of ground and surface water quality. The resulting information gap means that such impacts are not well understood. Improved analyses of oil sands products are required that compare land and water use with other transportation fuel pathways and use a regional perspective so local effects can be considered and mitigated.

Modeling Impact of Urbanization in US Cities Using Simple Biosphere Model SiB2

NASA Technical Reports Server (NTRS)

Zhang, Ping; Bounoua, Lahouari; Thome, Kurtis; Wolfe, Robert

2016-01-01

We combine Landsat- and the Moderate Resolution Imaging Spectroradiometer (MODIS)-based products, as well as climate drivers from Phase 2 of the North American Land Data Assimilation System (NLDAS-2) in a Simple Biosphere land surface model (SiB2) to assess the impact of urbanization in continental USA (excluding Alaska and Hawaii). More than 300 cities and their surrounding suburban and rural areas are defined in this study to characterize the impact of urbanization on surface climate including surface energy, carbon budget, and water balance. These analyses reveal an uneven impact of urbanization across the continent that should inform upon policy options for improving urban growth including heat mitigation and energy use, carbon sequestration and flood prevention.

Paired forested watershed experiments in the Piedmont of North Carolina

Treesearch

Johnny Boggs; Ge Sun; Steve McNulty

2016-01-01

Understanding how regional-specific water resources respond to disturbances can serve as useful information to land managers as they aim to set flow targets needed to maintain ecological integrity in surface...

The Effect of Subsurface Parameterizations on Modeled Flows in the Catchment Land Surface Model, Fortuna 2.5

NASA Astrophysics Data System (ADS)

Roningen, J. M.; Eylander, J. B.

2014-12-01

Groundwater use and management is subject to economic, legal, technical, and informational constraints and incentives at a variety of spatial and temporal scales. Planned and de facto management practices influenced by tax structures, legal frameworks, and agricultural and trade policies that vary at the country scale may have medium- and long-term effects on the ability of a region to support current and projected agricultural and industrial development. USACE is working to explore and develop global-scale, physically-based frameworks to serve as a baseline for hydrologic policy comparisons and consequence assessment, and such frameworks must include a reasonable representation of groundwater systems. To this end, we demonstrate the effects of different subsurface parameterizations, scaling, and meteorological forcings on surface and subsurface components of the Catchment Land Surface Model Fortuna v2.5 (Koster et al. 2000). We use the Land Information System 7 (Kumar et al. 2006) to process model runs using meteorological components of the Air Force Weather Agency's AGRMET forcing data from 2006 through 2011. Seasonal patterns and trends are examined in areas of the Upper Nile basin, northern China, and the Mississippi Valley. We also discuss the relevance of the model's representation of the catchment deficit with respect to local hydrogeologic structures.

In situ mineralogical-chemical analysis of Martian materials at landing/roving sites by active and passive remote sensing methods

NASA Technical Reports Server (NTRS)

Neukum, G.; Lehmann, F.; Regner, P.; Jaumann, R.

1988-01-01

Remote sensing of the Martian surface from the ground and from orbiting spacecraft has provided some first-order insight into the mineralogical-chemical composition and the weathering state of Martian surface materials. Much more detailed information can be gathered from performing such measurements in situ at the landing sites or from a rover in combination with analogous measurements from orbit. Measurements in the wavelength range of approximately 0.3 to 12.0 micrometers appear to be suitable to characterize much of the physical, mineralogical, petrological, and chemical properties of Martian surface materials and the weathering and other alteration processes that have acted on them. It is of particular importance to carry out measurements at the same time over a broad wavelength range since the reflectance signatures are caused by different effects and hence give different and complementing information. It appears particularly useful to employ a combination of active and passive methods because the use of active laser spectroscopy allows the obtaining of specific information on thermal infrared reflectance of surface materials. It seems to be evident that a spectrometric survey of Martian materials has to be focused on the analysis of altered and fresh mafic materials and rocks, water-bearing silicates, and possibly carbonates.

Improving Numerical Weather Predictions of Summertime Precipitation Over the Southeastern U.S. Through a High-Resolution Initialization of the Surface State

NASA Technical Reports Server (NTRS)

Case, Jonathan L.; Kumar, Sujay V.; Krikishen, Jayanthi; Jedlovec, Gary J.

2011-01-01

It is hypothesized that high-resolution, accurate representations of surface properties such as soil moisture and sea surface temperature are necessary to improve simulations of summertime pulse-type convective precipitation in high resolution models. This paper presents model verification results of a case study period from June-August 2008 over the Southeastern U.S. using the Weather Research and Forecasting numerical weather prediction model. Experimental simulations initialized with high-resolution land surface fields from the NASA Land Information System (LIS) and sea surface temperature (SST) derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) are compared to a set of control simulations initialized with interpolated fields from the National Centers for Environmental Prediction 12-km North American Mesoscale model. The LIS land surface and MODIS SSTs provide a more detailed surface initialization at a resolution comparable to the 4-km model grid spacing. Soil moisture from the LIS spin-up run is shown to respond better to the extreme rainfall of Tropical Storm Fay in August 2008 over the Florida peninsula. The LIS has slightly lower errors and higher anomaly correlations in the top soil layer, but exhibits a stronger dry bias in the root zone. The model sensitivity to the alternative surface initial conditions is examined for a sample case, showing that the LIS/MODIS data substantially impact surface and boundary layer properties.

Susceptibility of ground water to surface and shallow sources of contamination, Orange County, North Carolina

USGS Publications Warehouse

Terziotti, Silvia; Eimers, J.L.

1999-01-01

In 1998, the relative susceptibility of ground water in Orange County, North Carolina,to contamination from surface and shallow sources was evaluated. A geographic information system was used to build three county-wide layers--soil permeability, land use/land cover, and land-surface slope. The harmonic mean permeability of soil layers was used to estimate a location's capacity to transmit water through the soil. Values for each of these three factors were categorized and ranked from 1 to 10 according to relative potential for contamination. Each factor was weighted to reflect its relative potential contribution to ground-water contamination, then the factors were combined to create a relative susceptibility index. The relative susceptibility index was categorized to reflect lowest, low, moderate, high, and highest potential for ground-water contamination. The relative susceptibility index for about 12 percent of the area in Orange County was categorized as high or highest. The high and highest range areas have highly permeable soils, land cover or land-use activities that have a high contamination potential, and low to moderate slopes. Most of the county is within the moderate category of relative susceptibility to ground-water contamination. About 21 percent of the county is ranked as low or lowest relative susceptibility to ground-water contamination.

Morning Frost on Martian Surface

NASA Technical Reports Server (NTRS)

2008-01-01

A thin layer of water frost is visible on the ground around NASA's Phoenix Mars Lander in this image taken by the Surface Stereo Imager at 6 a.m. on Sol 79 (August 14, 2008), the 79th Martian day after landing. The frost begins to disappear shortly after 6 a.m. as the sun rises on the Phoenix landing site.

The sun was about 22 degrees above the horizon when the image was taken, enhancing the detail of the polygons, troughs and rocks around the landing site.

This view is looking east southeast with the lander's eastern solar panel visible in the bottom lefthand corner of the image. The rock in the foreground is informally named 'Quadlings' and the rock near center is informally called 'Winkies.'

This false color image has been enhanced to show color variations.

The Phoenix Mission is led by the University of Arizona, Tucson, on behalf of NASA. Project management of the mission is by NASA's Jet Propulsion Laboratory, Pasadena, Calif. Spacecraft development is by Lockheed Martin Space Systems, Denver.

Exploring the Influence of Topography on Belowground C Processes Using a Coupled Hydrologic-Biogeochemical Model

NASA Astrophysics Data System (ADS)

Shi, Y.; Davis, K. J.; Eissenstat, D. M.; Kaye, J. P.; Duffy, C.; Yu, X.; He, Y.

2014-12-01

Belowground carbon processes are affected by soil moisture and soil temperature, but current biogeochemical models are 1-D and cannot resolve topographically driven hill-slope soil moisture patterns, and cannot simulate the nonlinear effects of soil moisture on carbon processes. Coupling spatially-distributed physically-based hydrologic models with biogeochemical models may yield significant improvements in the representation of topographic influence on belowground C processes. We will couple the Flux-PIHM model to the Biome-BGC (BBGC) model. Flux-PIHM is a coupled physically-based land surface hydrologic model, which incorporates a land-surface scheme into the Penn State Integrated Hydrologic Model (PIHM). The land surface scheme is adapted from the Noah land surface model. Because PIHM is capable of simulating lateral water flow and deep groundwater, Flux-PIHM is able to represent the link between groundwater and the surface energy balance, as well as the land surface heterogeneities caused by topography. The coupled Flux-PIHM-BBGC model will be tested at the Susquehanna/Shale Hills critical zone observatory (SSHCZO). The abundant observations, including eddy covariance fluxes, soil moisture, groundwater level, sap flux, stream discharge, litterfall, leaf area index, above ground carbon stock, and soil carbon efflux, make SSHCZO an ideal test bed for the coupled model. In the coupled model, each Flux-PIHM model grid will couple a BBGC cell. Flux-PIHM will provide BBGC with soil moisture and soil temperature information, while BBGC provides Flux-PIHM with leaf area index. Preliminary results show that when Biome- BGC is driven by PIHM simulated soil moisture pattern, the simulated soil carbon is clearly impacted by topography.

Exploring a new method for the retrieval of urban thermophysical properties using thermal infrared remote sensing and deterministic modeling

NASA Astrophysics Data System (ADS)

De Ridder, K.; Bertrand, C.; Casanova, G.; Lefebvre, W.

2012-09-01

Increasingly, mesoscale meteorological and climate models are used to predict urban weather and climate. Yet, large uncertainties remain regarding values of some urban surface properties. In particular, information concerning urban values for thermal roughness length and thermal admittance is scarce. In this paper, we present a method to estimate values for thermal admittance in combination with an optimal scheme for thermal roughness length, based on METEOSAT-8/SEVIRI thermal infrared imagery in conjunction with a deterministic atmospheric model containing a simple urbanized land surface scheme. Given the spatial resolution of the SEVIRI sensor, the resulting parameter values are applicable at scales of the order of 5 km. As a study case we focused on the city of Paris, for the day of 29 June 2006. Land surface temperature was calculated from SEVIRI thermal radiances using a new split-window algorithm specifically designed to handle urban conditions, as described inAppendix A, including a correction for anisotropy effects. Land surface temperature was also calculated in an ensemble of simulations carried out with the ARPS mesoscale atmospheric model, combining different thermal roughness length parameterizations with a range of thermal admittance values. Particular care was taken to spatially match the simulated land surface temperature with the SEVIRI field of view, using the so-called point spread function of the latter. Using Bayesian inference, the best agreement between simulated and observed land surface temperature was obtained for the Zilitinkevich (1970) and Brutsaert (1975) thermal roughness length parameterizations, the latter with the coefficients obtained by Kanda et al. (2007). The retrieved thermal admittance values associated with either thermal roughness parameterization were, respectively, 1843 ± 108 J m-2 s-1/2 K-1 and 1926 ± 115 J m-2 s-1/2 K-1.

Distributed hydrological models to quantify ecosystem services and inform land use decisions in Europe

NASA Astrophysics Data System (ADS)

Wilebore, Beccy; Willis, Kathy

2016-04-01

Landcover conversion is one of the largest anthropogenic threats to ecological services globally; in the EU around 1500 ha of biodiverse land are lost every day to changes in infrastructure and urbanisation. This land conversion directly affects key ecosystem services that support natural infrastructure, including water flow regulation and the mitigation of flood risks. We assess the sensitivity of runoff production to landcover in the UK at a high spatial resolution, using a distributed hydrologic model in the regional land-surface model JULES (Joint UK Land Environment Simulator). This work, as part of the wider initiative 'NaturEtrade', will create a novel suite of easy-to-use tools and mechanisms to allow EU landowners to quickly map and assess the value of their land in providing key ecosystem services.

The Effect of Landing Surface on the Plantar Kinetics of Chinese Paratroopers Using Half-Squat Landing

PubMed Central

Li, Yi; Wu, Ji; Zheng, Chao; Huang, Rong Rong; Na, Yuhong; Yang, Fan; Wang, Zengshun; Wu, Di

2013-01-01

The objective of the study was to determine the effect of landing surface on plantar kinetics during a half-squat landing. Twenty male elite paratroopers with formal parachute landing training and over 2 years of parachute jumping experience were recruited. The subjects wore parachuting boots in which pressure sensing insoles were placed. Each subject was instructed to jump off a platform with a height of 60 cm, and land on either a hard or soft surface in a half-squat posture. Outcome measures were maximal plantar pressure, time to maximal plantar pressure (T-MPP), and pressure-time integral (PTI) upon landing on 10 plantar regions. Compared to a soft surface, hard surface produced higher maximal plantar pressure in the 1st to 4th metatarsal and mid-foot regions, but lower maximal plantar pressure in the 5th metatarsal region. Shorter T- MPP was found during hard surface landing in the 1st and 2nd metatarsal and medial rear foot. Landing on a hard surface landing resulted in a lower PTI than a soft surface in the 1stphalangeal region. For Chinese paratroopers, specific foot prosthesis should be designed to protect the1st to 4thmetatarsal region for hard surface landing, and the 1stphalangeal and 5thmetatarsal region for soft surface landing. Key Points Understanding plantar kinetics during the half-squat landing used by Chinese paratroopers can assist in the design of protective footwear. Compared to landing on a soft surface, a hard surface produced higher maximal plantar pressure in the 1st to 4th metatarsal and mid-foot regions, but lower maximal plantar pressure in the 5th metatarsal region. A shorter time to maximal plantar pressure was found during a hard surface landing in the 1st and 2nd metatarsals and medial rear foot. Landing on a hard surface resulted in a lower pressure-time integral than landing on a soft surface in the 1st phalangeal region. For Chinese paratroopers, specific foot prosthesis should be designed to protect the 1st to 4th metatarsal region for a hard surface landing, and the 1st phalangeal and 5th metatarsal region for a soft surface landing. PMID:24149145

Analysis of relationships between land surface temperature and land use changes in the Yellow River Delta

NASA Astrophysics Data System (ADS)

Ning, Jicai; Gao, Zhiqiang; Meng, Ran; Xu, Fuxiang; Gao, Meng

2018-06-01

This study analyzed land use and land cover changes and their impact on land surface temperature using Landsat 5 Thematic Mapper and Landsat 8 Operational Land Imager and Thermal Infrared Sensor imagery of the Yellow River Delta. Six Landsat images comprising two time series were used to calculate the land surface temperature and correlated vegetation indices. The Yellow River Delta area has expanded substantially because of the deposited sediment carried from upstream reaches of the river. Between 1986 and 2015, approximately 35% of the land use area of the Yellow River Delta has been transformed into salterns and aquaculture ponds. Overall, land use conversion has occurred primarily from poorly utilized land into highly utilized land. To analyze the variation of land surface temperature, a mono-window algorithm was applied to retrieve the regional land surface temperature. The results showed bilinear correlation between land surface temperature and the vegetation indices (i.e., Normalized Difference Vegetation Index, Adjusted-Normalized Vegetation Index, Soil-Adjusted Vegetation Index, and Modified Soil-Adjusted Vegetation Index). Generally, values of the vegetation indices greater than the inflection point mean the land surface temperature and the vegetation indices are correlated negatively, and vice versa. Land surface temperature in coastal areas is affected considerably by local seawater temperature and weather conditions.

MODIS Measures Total U.S. Leaf Area

NASA Technical Reports Server (NTRS)

2002-01-01

This composite image over the continental United States was produced with data acquired by the Moderate-resolution Imaging Spectroradiometer (MODIS) during the period March 24 - April 8, 2000. The image is a map of the density of the plant canopy covering the ground. It is the first in a series of images over the continental U.S. produced by the MODIS Land Discipline Group (refer to this site June 2 and 5 for the next two images in the series). The image is a MODIS data product called 'Leaf Area Index,' which is produced by radiometrically measuring the visible and near infrared energy reflected by vegetation. The Leaf Area Index provides information on the structure of plant canopy, showing how much surface area is covered by green foliage relative to total land surface area. In this image, dark green pixels indicate areas where more than 80 percent of the land surface is covered by green vegetation, light green pixels show where leaves cover about 10 to 50 percent of the land surface, and brown pixels show virtually no leaf coverage. The more leaf area a plant has, the more sunlight it can absorb for photosynthesis. Leaf Area Index is one of a new suite of measurements that scientists use to understand how the Earth's land surfaces are changing over time. Their goal is to use these measurements to refine computer models well enough to simulate how the land biosphere influences the natural cycles of water, carbon, and energy throughout the Earth system. This image is the first of its kind from the MODIS instrument, which launched in December 1999 aboard the Terra spacecraft. MODIS began acquiring scientific data on February 24, 2000, when it first opened its aperture door. The MODIS instrument and Terra spacecraft are both managed by NASA's Goddard Space Flight Center, Greenbelt, MD. Image courtesy Steven Running, MODIS Land Group Member, University of Montana

Relationships between aerodynamic roughness and land use and land cover in Baltimore, Maryland

USGS Publications Warehouse

Nicholas, F.W.; Lewis, J.E.

1980-01-01

Urbanization changes the radiative, thermal, hydrologic, and aerodynamic properties of the Earth's surface. Knowledge of these surface characteristics, therefore, is essential to urban climate analysis. Aerodynamic or surface roughness of urban areas is not well documented, however, because of practical constraints in measuring the wind profile in the presence of large buildings. Using an empirical method designed by Lettau, and an analysis of variance of surface roughness values calculated for 324 samples averaging 0.8 hectare (ha) of land use and land cover sample in Baltimore, Md., a strong statistical relation was found between aerodynamic roughness and urban land use and land cover types. Assessment of three land use and land cover systems indicates that some of these types have significantly different surface roughness characteristics. The tests further indicate that statistically significant differences exist in estimated surface roughness values when categories (classes) from different land use and land cover classification systems are used as surrogates. A Level III extension of the U.S. Geological Survey Level II land use and land cover classification system provided the most reliable results. An evaluation of the physical association between the aerodynamic properties of land use and land cover and the surface climate by numerical simulation of the surface energy balance indicates that changes in surface roughness within the range of values typical of the Level III categories induce important changes in the surface climate.

Estimating the social value of geologic map information: A regulatory application

USGS Publications Warehouse

Bernknopf, R.L.; Brookshire, D.S.; McKee, M.; Soller, D.R.

1997-01-01

People frequently regard the landscape as part of a static system. The mountains and rivers that cross the landscape, and the bedrock that supports the surface, change little during the course of a lifetime. Society can alter the geologic history of an area and, in so doing, affect the occurrence and impact of environmental hazards. For example, changes in land use can induce changes in erosion, sedimentation, and ground-water supply. As the environmental system is changed by both natural processes and human activities, the system's capacity to respond to additional stresses also changes. Information such as geologic maps describes the physical world and is critical for identifying solutions to land use and environmental issues. In this paper, a method is developed for estimating the economic value of applying geologic map information to siting a waste disposal facility. An improvement in geologic map information is shown to have a net positive value to society. Such maps enable planners to make superior land management decisions.

Surface knowledge and risks to landing and roving - The scale problem

NASA Technical Reports Server (NTRS)

Bourke, Roger D.

1991-01-01

The role of surface information in the performance of surface exploration missions is discussed. Accurate surface models based on direct measurements or inference are considered to be an important component in mission risk management. These models can be obtained using high resolution orbital photography or a combination of laser profiling, thermal inertia measurements, and/or radar. It is concluded that strategies for Martian exploration should use high confidence models to achieve maximum performance and low risk.

Predictive Measures of Locomotor Performance on an Unstable Walking Surface

NASA Technical Reports Server (NTRS)

Bloomberg, J. J.; Peters, B. T.; Mulavara, A. P.; Caldwell, E. E.; Batson, C. D.; De Dios, Y. E.; Gadd, N. E.; Goel, R.; Wood, S. J.; Cohen, H. S.;

Soil moisture status estimation over Three Gorges area with Landsat TM data based on temperature vegetation dryness index

NASA Astrophysics Data System (ADS)

Xu, Lina; Niu, Ruiqing; Li, Jiong; Dong, Yanfang

2011-12-01

Soil moisture is the important indicator of climate, hydrology, ecology, agriculture and other parameters of the land surface and atmospheric interface. Soil moisture plays an important role on the water and energy exchange at the land surface/atmosphere interface. Remote sensing can provide information on large area quickly and easily, so it is significant to do research on how to monitor soil moisture by remote sensing. This paper presents a method to assess soil moisture status using Landsat TM data over Three Gorges area in China based on TVDI. The potential of Temperature- Vegetation Dryness Index (TVDI) from Landsat TM data in assessing soil moisture was investigated in this region. After retrieving land surface temperature and vegetation index a TVDI model based on the features of Ts-NDVI space is established. And finally, soil moisture status is estimated according to TVDI. It shows that TVDI has the advantages of stability and high accuracy to estimating the soil moisture status.

Marbles for the Imagination

NASA Technical Reports Server (NTRS)

Shue, Jack

2004-01-01

The end-to-end test would verify the complex sequence of events from lander separation to landing. Due to the large distances involved and the significant delay time in sending a command and receiving verification, the lander needed to operate autonomously after it separated from the orbiter. It had to sense conditions, make decisions, and act accordingly. We were flying into a relatively unknown set of conditions-a Martian atmosphere of unknown pressure, density, and consistency to land on a surface of unknown altitude, and one which had an unknown bearing strength. In order to touch down safely on Mars the lander had to orient itself for descent and entry, modulate itself to maintain proper lift, pop a parachute, jettison its aeroshell, deploy landing legs and radar, ignite a terminal descent engine, and fly a given trajectory to the surface. Once on the surface, it would determine its orientation, raise the high-gain antenna, perform a sweep to locate Earth, and begin transmitting information. It was this complicated, autonomous sequence that the end-to-end test was to simulate.

Impact of high resolution land surface initialization in Indian summer monsoon simulation using a regional climate model

NASA Astrophysics Data System (ADS)

Unnikrishnan, C. K.; Rajeevan, M.; Rao, S. Vijaya Bhaskara

2016-06-01

The direct impact of high resolution land surface initialization on the forecast bias in a regional climate model in recent years over Indian summer monsoon region is investigated. Two sets of regional climate model simulations are performed, one with a coarse resolution land surface initial conditions and second one used a high resolution land surface data for initial condition. The results show that all monsoon years respond differently to the high resolution land surface initialization. The drought monsoon year 2009 and extended break periods were more sensitive to the high resolution land surface initialization. These results suggest that the drought monsoon year predictions can be improved with high resolution land surface initialization. Result also shows that there are differences in the response to the land surface initialization within the monsoon season. Case studies of heat wave and a monsoon depression simulation show that, the model biases were also improved with high resolution land surface initialization. These results show the need for a better land surface initialization strategy in high resolution regional models for monsoon forecasting.

LAnd surface remote sensing Products VAlidation System (LAPVAS) and its preliminary application

NASA Astrophysics Data System (ADS)

Lin, Xingwen; Wen, Jianguang; Tang, Yong; Ma, Mingguo; Dou, Baocheng; Wu, Xiaodan; Meng, Lumin

2014-11-01

The long term record of remote sensing product shows the land surface parameters with spatial and temporal change to support regional and global scientific research widely. Remote sensing product with different sensors and different algorithms is necessary to be validated to ensure the high quality remote sensing product. Investigation about the remote sensing product validation shows that it is a complex processing both the quality of in-situ data requirement and method of precision assessment. A comprehensive validation should be needed with long time series and multiple land surface types. So a system named as land surface remote sensing product is designed in this paper to assess the uncertainty information of the remote sensing products based on a amount of in situ data and the validation techniques. The designed validation system platform consists of three parts: Validation databases Precision analysis subsystem, Inter-external interface of system. These three parts are built by some essential service modules, such as Data-Read service modules, Data-Insert service modules, Data-Associated service modules, Precision-Analysis service modules, Scale-Change service modules and so on. To run the validation system platform, users could order these service modules and choreograph them by the user interactive and then compete the validation tasks of remote sensing products (such as LAI ,ALBEDO ,VI etc.) . Taking SOA-based architecture as the framework of this system. The benefit of this architecture is the good service modules which could be independent of any development environment by standards such as the Web-Service Description Language(WSDL). The standard language: C++ and java will used as the primary programming language to create service modules. One of the key land surface parameter, albedo, is selected as an example of the system application. It is illustrated that the LAPVAS has a good performance to implement the land surface remote sensing product validation.

Retrieval of an available water-based soil moisture proxy from thermal infrared remote sensing. Part I: Methodology and validation

USDA-ARS?s Scientific Manuscript database

A retrieval of soil moisture is proposed using surface flux estimates from satellite-based thermal infrared (TIR) imagery and the Atmosphere-Land-Exchange-Inversion (ALEXI) model. The ability of ALEXI to provide valuable information about the partitioning of the surface energy budget, which can be l...

Analyzing the effects of urban expansion on land surface temperature patterns by landscape metrics: a case study of Isfahan city, Iran.

PubMed

Madanian, Maliheh; Soffianian, Ali Reza; Koupai, Saeid Soltani; Pourmanafi, Saeid; Momeni, Mehdi

2018-03-03

Urban expansion can cause extensive changes in land use and land cover (LULC), leading to changes in temperature conditions. Land surface temperature (LST) is one of the key parameters that should be considered in the study of urban temperature conditions. The purpose of this study was, therefore, to investigate the effects of changes in LULC due to the expansion of the city of Isfahan on LST using landscape metrics. To this aim, two Landsat 5 and Landsat 8 images, which had been acquired, respectively, on August 2, 1985, and July 4, 2015, were used. The support vector machine method was then used to classify the images. The results showed that Isfahan city had been encountered with an increase of impervious surfaces; in fact, this class covered 15% of the total area in 1985, while this value had been increased to 30% in 2015. Then LST zoning maps were created, indicating that the bare land and impervious surfaces categories were dominant in high temperature zones, while in the zones where water was present or NDVI was high, LST was low. Then, the landscape metrics in each of the LST zones were analyzed in relation to the LULC changes, showing that LULC changes due to urban expansion changed such landscape properties as the percentage of landscape, patch density, large patch index, and aggregation index. This information could be beneficial for urban planners to monitor and manage changes in the LULC patterns.

Visualizing Airborne and Satellite Imagery

NASA Technical Reports Server (NTRS)

Bierwirth, Victoria A.

2011-01-01

Remote sensing is a process able to provide information about Earth to better understand Earth's processes and assist in monitoring Earth's resources. The Cloud Absorption Radiometer (CAR) is one remote sensing instrument dedicated to the cause of collecting data on anthropogenic influences on Earth as well as assisting scientists in understanding land-surface and atmospheric interactions. Landsat is a satellite program dedicated to collecting repetitive coverage of the continental Earth surfaces in seven regions of the electromagnetic spectrum. Combining these two aircraft and satellite remote sensing instruments will provide a detailed and comprehensive data collection able to provide influential information and improve predictions of changes in the future. This project acquired, interpreted, and created composite images from satellite data acquired from Landsat 4-5 Thematic Mapper (TM) and Landsat 7 Enhanced Thematic Mapper plus (ETM+). Landsat images were processed for areas covered by CAR during the Arctic Research of the Composition of the Troposphere from Aircraft and Satellites (ARCT AS), Cloud and Land Surface Interaction Campaign (CLASIC), Intercontinental Chemical Transport Experiment-Phase B (INTEXB), and Southern African Regional Science Initiative (SAFARI) 2000 missions. The acquisition of Landsat data will provide supplemental information to assist in visualizing and interpreting airborne and satellite imagery.

The SMAP Level 4 Surface and Root-zone Soil Moisture (L4_SM) Product

NASA Technical Reports Server (NTRS)

Reichle, Rolf; Crow, Wade; Koster, Randal; Kimball, John

2010-01-01

The Soil Moisture Active and Passive (SMAP) mission is being developed by NASA for launch in 2013 as one of four first-tier missions recommended by the U.S. National Research Council Committee on Earth Science and Applications from Space in 2007. The primary science objectives of SMAP are to enhance understanding of land surface controls on the water, energy and carbon cycles, and to determine their linkages. Moreover, the high resolution soil moisture mapping provided by SMAP has practical applications in weather and seasonal climate prediction, agriculture, human health, drought and flood decision support. In this paper we describe the assimilation of SMAP observations for the generation of the planned SMAP Level 4 Surface and Root-zone Soil Moisture (L4_SM) product. The SMAP mission makes simultaneous active (radar) and passive (radiometer) measurements in the 1.26-1.43 GHz range (L-band) from a sun-synchronous low-earth orbit. Measurements will be obtained across a 1000 km wide swath using conical scanning at a constant incidence angle (40 deg). The radar resolution varies from 1-3 km over the outer 70% of the swath to about 30 km near the center of the swath. The radiometer resolution is 40 km across the entire swath. The radiometer measurements will allow high-accuracy but coarse resolution (40 km) measurements. The radar measurements will add significantly higher resolution information. The radar is however very sensitive to surface roughness and vegetation structure. The combination of the two measurements allows optimal blending of the advantages of each instrument. SMAP directly observes only surface soil moisture (in the top 5 cm of the soil column). Several of the key applications targeted by SMAP, however, require knowledge of root zone soil moisture (approximately top 1 m of the soil column), which is not directly measured by SMAP. The foremost objective of the SMAP L4_SM product is to fill this gap and provide estimates of root zone soil moisture that are informed by and consistent with SMAP observations. Such estimates are obtained by merging SMAP observations with estimates from a land surface model in a soil moisture data assimilation system. The land surface model component of the assimilation system is driven with observations-based surface meteorological forcing data, including precipitation, which is the most important driver for soil moisture. The model also encapsulates knowledge of key land surface processes, including the vertical transfer of soil moisture between the surface and root zone reservoirs. Finally, the model interpolates and extrapolates SMAP observations in time and in space. The L4_SM product thus provides a comprehensive and consistent picture of land surface hydrological conditions based on SMAP observations and complementary information from a variety of sources. The assimilation algorithm considers the respective uncertainties of each component and yields a product that is superior to satellite or model data alone. Error estimates for the L4_SM product are generated as a by-product of the data assimilation system.

Estimation of Surface Air Temperature from MODIS 1km Resolution Land Surface Temperature Over Northern China

NASA Technical Reports Server (NTRS)

Shen, Suhung; Leptoukh, Gregory G.; Gerasimov, Irina

2010-01-01

Surface air temperature is a critical variable to describe the energy and water cycle of the Earth-atmosphere system and is a key input element for hydrology and land surface models. It is a very important variable in agricultural applications and climate change studies. This is a preliminary study to examine statistical relationships between ground meteorological station measured surface daily maximum/minimum air temperature and satellite remotely sensed land surface temperature from MODIS over the dry and semiarid regions of northern China. Studies were conducted for both MODIS-Terra and MODIS-Aqua by using year 2009 data. Results indicate that the relationships between surface air temperature and remotely sensed land surface temperature are statistically significant. The relationships between the maximum air temperature and daytime land surface temperature depends significantly on land surface types and vegetation index, but the minimum air temperature and nighttime land surface temperature has little dependence on the surface conditions. Based on linear regression relationship between surface air temperature and MODIS land surface temperature, surface maximum and minimum air temperatures are estimated from 1km MODIS land surface temperature under clear sky conditions. The statistical errors (sigma) of the estimated daily maximum (minimum) air temperature is about 3.8 C(3.7 C).

Remote sensing with spaceborne synthetic aperture imaging radars: A review

NASA Technical Reports Server (NTRS)

Cimino, J. B.; Elachi, C.

1983-01-01

A review is given of remote sensing with Spaceborne Synthetic Aperture Radars (SAR's). In 1978, a spaceborne SA was flown on the SEASAT satellite. It acquired high resulution images over many regions in North America and the North Pacific. The acquired data clearly demonstrate the capability of spaceborne SARs to: image and track polar ice floes; image ocean surface patterns including swells, internal waves, current boundaries, weather boundaries and vessels; and image land features which are used to acquire information about the surface geology and land cover. In 1981, another SAR was flown on the second shuttle flight. This Shuttle Imaging Radar (SIR-A) acquired land and ocean images over many areas around the world. The emphasis of the SIR-A experiment was mainly toward geologic mapping. Some of the key results of the SIR-A experiment are given.

Comparing SMAP to Macro-scale and Hyper-resolution Land Surface Models over Continental U. S.

NASA Astrophysics Data System (ADS)

Pan, Ming; Cai, Xitian; Chaney, Nathaniel; Wood, Eric

2016-04-01

SMAP sensors collect moisture information in top soil at the spatial resolution of ~40 km (radiometer) and ~1 to 3 km (radar, before its failure in July 2015). Such information is extremely valuable for understanding various terrestrial hydrologic processes and their implications on human life. At the same time, soil moisture is a joint consequence of numerous physical processes (precipitation, temperature, radiation, topography, crop/vegetation dynamics, soil properties, etc.) that happen at a wide range of scales from tens of kilometers down to tens of meters. Therefore, a full and thorough analysis/exploration of SMAP data products calls for investigations at multiple spatial scales - from regional, to catchment, and to field scales. Here we first compare the SMAP retrievals to the Variable Infiltration Capacity (VIC) macro-scale land surface model simulations over the continental U. S. region at 3 km resolution. The forcing inputs to the model are merged/downscaled from a suite of best available data products including the NLDAS-2 forcing, Stage IV and Stage II precipitation, GOES Surface and Insolation Products, and fine elevation data. The near real time VIC simulation is intended to provide a source of large scale comparisons at the active sensor resolution. Beyond the VIC model scale, we perform comparisons at 30 m resolution against the recently developed HydroBloks hyper-resolution land surface model over several densely gauged USDA experimental watersheds. Comparisons are also made against in-situ point-scale observations from various SMAP Cal/Val and field campaign sites.

A dataset mapping the potential biophysical effects of vegetation cover change

NASA Astrophysics Data System (ADS)

Duveiller, Gregory; Hooker, Josh; Cescatti, Alessandro

2018-02-01

Changing the vegetation cover of the Earth has impacts on the biophysical properties of the surface and ultimately on the local climate. Depending on the specific type of vegetation change and on the background climate, the resulting competing biophysical processes can have a net warming or cooling effect, which can further vary both spatially and seasonally. Due to uncertain climate impacts and the lack of robust observations, biophysical effects are not yet considered in land-based climate policies. Here we present a dataset based on satellite remote sensing observations that provides the potential changes i) of the full surface energy balance, ii) at global scale, and iii) for multiple vegetation transitions, as would now be required for the comprehensive evaluation of land based mitigation plans. We anticipate that this dataset will provide valuable information to benchmark Earth system models, to assess future scenarios of land cover change and to develop the monitoring, reporting and verification guidelines required for the implementation of mitigation plans that account for biophysical land processes.

A dataset mapping the potential biophysical effects of vegetation cover change

PubMed Central

Duveiller, Gregory; Hooker, Josh; Cescatti, Alessandro

2018-01-01

Changing the vegetation cover of the Earth has impacts on the biophysical properties of the surface and ultimately on the local climate. Depending on the specific type of vegetation change and on the background climate, the resulting competing biophysical processes can have a net warming or cooling effect, which can further vary both spatially and seasonally. Due to uncertain climate impacts and the lack of robust observations, biophysical effects are not yet considered in land-based climate policies. Here we present a dataset based on satellite remote sensing observations that provides the potential changes i) of the full surface energy balance, ii) at global scale, and iii) for multiple vegetation transitions, as would now be required for the comprehensive evaluation of land based mitigation plans. We anticipate that this dataset will provide valuable information to benchmark Earth system models, to assess future scenarios of land cover change and to develop the monitoring, reporting and verification guidelines required for the implementation of mitigation plans that account for biophysical land processes. PMID:29461538

Use of land surface remotely sensed satellite and airborne data for environmental exposure assessment in cancer research

USGS Publications Warehouse

Maxwell, S.K.; Meliker, J.R.; Goovaerts, P.

2010-01-01

In recent years, geographic information systems (GIS) have increasingly been used for reconstructing individual-level exposures to environmental contaminants in epidemiological research. Remotely sensed data can be useful in creating space-time models of environmental measures. The primary advantage of using remotely sensed data is that it allows for study at the local scale (e.g., residential level) without requiring expensive, time-consuming monitoring campaigns. The purpose of our study was to identify how land surface remotely sensed data are currently being used to study the relationship between cancer and environmental contaminants, focusing primarily on agricultural chemical exposure assessment applications. We present the results of a comprehensive literature review of epidemiological research where remotely sensed imagery or land cover maps derived from remotely sensed imagery were applied. We also discuss the strengths and limitations of the most commonly used imagery data (aerial photographs and Landsat satellite imagery) and land cover maps.

Land surface energy budget during dry spells: global CMIP5 AMIP simulations vs. satellite observations

NASA Astrophysics Data System (ADS)

Gallego-Elvira, Belen; Taylor, Christopher M.; Harris, Phil P.; Ghent, Darren; Folwell, Sonja S.

2015-04-01

During extended periods without rain (dry spells), the soil can dry out due to vegetation transpiration and soil evaporation. At some point in this drying cycle, land surface conditions change from energy-limited to water-limited evapotranspiration, and this is accompanied by an increase of the ground and overlying air temperatures. Regionally, the characteristics of this transition determine the influence of soil moisture on air temperature and rainfall. Global Climate Models (GCMs) disagree on where and how strongly the surface energy budget is limited by soil moisture. Flux tower observations are improving our understanding of these dry down processes, but typical heterogeneous landscapes are too sparsely sampled to ascertain a representative regional response. Alternatively, satellite observations of land surface temperature (LST) provide indirect information about the surface energy partition at 1km resolution globally. In our study, we analyse how well the dry spell dynamics of LST are represented by GCMs across the globe. We use a spatially and temporally aggregated diagnostic to describe the composite response of LST during surface dry down in rain-free periods in distinct climatic regions. The diagnostic is derived from daytime MODIS-Terra LST observations and bias-corrected meteorological re-analyses, and compared against the outputs of historical climate simulations of seven models running the CMIP5 AMIP experiment. Dry spell events are stratified by antecedent precipitation, land cover type and geographic regions to assess the sensitivity of surface warming rates to soil moisture levels at the onset of a dry spell for different surface and climatic zones. In a number of drought-prone hot spot regions, we find important differences in simulated dry spell behaviour, both between models, and compared to observations. These model biases are likely to compromise seasonal forecasts and future climate projections.

Spatially Complete Global Surface Albedos Derived from Terra/MODIS Data

NASA Technical Reports Server (NTRS)

King, Michael D.; Moody, Eric G.; Platnick, Steven; Schaaf, Crystal B.

2004-01-01

Spectral land surface albedo is an important parameter for describing the radiative properties of the Earth. Accordingly it reflects the consequences of natural and human interactions, such as anthropogenic, meteorological, and phenological effects, on global and local climatological trends. Consequently, albedos are integral parts in a variety of research areas, such as general circulation models (GCMs), energy balance studies, modeling of land use and land use change, and biophysical, oceanographic, and meteorological studies. Recent production of land surface anisotropy, diffuse bihemispherical (white-sky) albedo and direct beam directional hemispherical (black-sky) albedo from observations acquired by the MODIS instruments aboard NASA s Terra and Aqua satellite platforms have provided researchers with unprecedented spatial, spectral, and temporal information on the land surface's radiative characteristics. Cloud cover, which cutails retrievals, and the presence of ephemeral and seasonal snow limit the snow-free data to approximately half the global land surfaces on an annual equal-angle basis. This precludes the MOD43B3 albedo products from being used in some remote sensing and ground-based applications, climate models, and global change research projects. An ecosystem-dependent temporal interpolation technique is described that has been developed to fill missing or seasonally snow-covered data in the official MOD43B3 albedo product. The method imposes pixel-level and local regional ecosystem-dependent phenological behavior onto retrieved pixel temporal data in such a way as to maintain pixel-level spatial and spectral detail and integrity. The phenological curves are derived from statistics based on the MODIS MOD12Q1 IGBP land cover classification product geolocated with the MOD43B3 data. The resulting snow-free value-added products provide the scientific community with spatially and temporally complete global white- and black-sky surface albedo maps and statistics. These products are stored on 1'(approximately 10 km) and coarser resolution equal-angle grids, and are computed for the first seven MODIS wavelengths, ranging from 0.47 through 2.1 microns, and for three broadband wavelengths, 0.3-0.7,0.3-5.0 and 0.7-5.0 microns.

Study on Classification Accuracy Inspection of Land Cover Data Aided by Automatic Image Change Detection Technology

NASA Astrophysics Data System (ADS)

Xie, W.-J.; Zhang, L.; Chen, H.-P.; Zhou, J.; Mao, W.-J.

2018-04-01

The purpose of carrying out national geographic conditions monitoring is to obtain information of surface changes caused by human social and economic activities, so that the geographic information can be used to offer better services for the government, enterprise and public. Land cover data contains detailed geographic conditions information, thus has been listed as one of the important achievements in the national geographic conditions monitoring project. At present, the main issue of the production of the land cover data is about how to improve the classification accuracy. For the land cover data quality inspection and acceptance, classification accuracy is also an important check point. So far, the classification accuracy inspection is mainly based on human-computer interaction or manual inspection in the project, which are time consuming and laborious. By harnessing the automatic high-resolution remote sensing image change detection technology based on the ERDAS IMAGINE platform, this paper carried out the classification accuracy inspection test of land cover data in the project, and presented a corresponding technical route, which includes data pre-processing, change detection, result output and information extraction. The result of the quality inspection test shows the effectiveness of the technical route, which can meet the inspection needs for the two typical errors, that is, missing and incorrect update error, and effectively reduces the work intensity of human-computer interaction inspection for quality inspectors, and also provides a technical reference for the data production and quality control of the land cover data.

A Landscape Indicator Approach to the Identification and Articulation of the Ecological Consequences of Land Cover Change in the Chesapeake Bay Watershed, 1970-2000

USGS Publications Warehouse

Slonecker, Terrence

2008-01-01

The advancement of geographic science in the area of land surface status and trends and land cover change is at the core of the current geographic scientific research of the U.S. Geological Survey (USGS) (McMahon and others, 2005). Perhaps the least developed or articulated aspects of USGS land change science have been the identification and analysis of the ecological consequences of land cover change. Changes in land use and land cover significantly affect the ability of ecosystems to provide essential ecological goods and services, which, in turn, affect the economic, public health, and social benefits that these ecosystems provide. One of the great scientific challenges for geographic science is to understand and calibrate the effects of land use and land cover change and the complex interaction between human and biotic systems at a variety of natural, geographic, and political scales. Understanding the dynamics of land surface change requires an increased understanding of the complex nature of human-environmental systems and will require a suite of scientific tools that include traditional geographic data and analysis methods, such as remote sensing and geographic information systems (GIS), as well as innovative approaches to understanding the dynamics of complex systems. One such approach that has gained much recent scientific attention is the landscape indicator, or landscape assessment, approach, which has been developed with the emergence of the science of landscape ecology.

Satellite image simulations for model-supervised, dynamic retrieval of crop type and land use intensity

NASA Astrophysics Data System (ADS)

Bach, H.; Klug, P.; Ruf, T.; Migdall, S.; Schlenz, F.; Hank, T.; Mauser, W.

2015-04-01

To support food security, information products about the actual cropping area per crop type, the current status of agricultural production and estimated yields, as well as the sustainability of the agricultural management are necessary. Based on this information, well-targeted land management decisions can be made. Remote sensing is in a unique position to contribute to this task as it is globally available and provides a plethora of information about current crop status. M4Land is a comprehensive system in which a crop growth model (PROMET) and a reflectance model (SLC) are coupled in order to provide these information products by analyzing multi-temporal satellite images. SLC uses modelled surface state parameters from PROMET, such as leaf area index or phenology of different crops to simulate spatially distributed surface reflectance spectra. This is the basis for generating artificial satellite images considering sensor specific configurations (spectral bands, solar and observation geometries). Ensembles of model runs are used to represent different crop types, fertilization status, soil colour and soil moisture. By multi-temporal comparisons of simulated and real satellite images, the land cover/crop type can be classified in a dynamically, model-supervised way and without in-situ training data. The method is demonstrated in an agricultural test-site in Bavaria. Its transferability is studied by analysing PROMET model results for the rest of Germany. Especially the simulated phenological development can be verified on this scale in order to understand whether PROMET is able to adequately simulate spatial, as well as temporal (intra- and inter-season) crop growth conditions, a prerequisite for the model-supervised approach. This sophisticated new technology allows monitoring of management decisions on the field-level using high resolution optical data (presently RapidEye and Landsat). The M4Land analysis system is designed to integrate multi-mission data and is well suited for the use of Sentinel-2's continuous and manifold data stream.

Precipitation from the GPM Microwave Imager and Constellation Radiometers

NASA Astrophysics Data System (ADS)

Kummerow, Christian; Randel, David; Kirstetter, Pierre-Emmanuel; Kulie, Mark; Wang, Nai-Yu

2014-05-01

Satellite precipitation retrievals from microwave sensors are fundamentally underconstrained requiring either implicit or explicit a-priori information to constrain solutions. The radiometer algorithm designed for the GPM core and constellation satellites makes this a-priori information explicit in the form of a database of possible rain structures from the GPM core satellite and a Bayesian retrieval scheme. The a-priori database will eventually come from the GPM core satellite's combined radar/radiometer retrieval algorithm. That product is physically constrained to ensure radiometric consistency between the radars and radiometers and is thus ideally suited to create the a-priori databases for all radiometers in the GPM constellation. Until a robust product exists, however, the a-priori databases are being generated from the combination of existing sources over land and oceans. Over oceans, the Day-1 GPM radiometer algorithm uses the TRMM PR/TMI physically derived hydrometer profiles that are available from the tropics through sea surface temperatures of approximately 285K. For colder sea surface temperatures, the existing profiles are used with lower hydrometeor layers removed to correspond to colder conditions. While not ideal, the results appear to be reasonable placeholders until the full GPM database can be constructed. It is more difficult to construct physically consistent profiles over land due to ambiguities in surface emissivities as well as details of the ice scattering that dominates brightness temperature signatures over land. Over land, the a-priori databases have therefore been constructed by matching satellite overpasses to surface radar data derived from the WSR-88 network over the continental United States through the National Mosaic and Multi-Sensor QPE (NMQ) initiative. Databases are generated as a function of land type (4 categories of increasing vegetation cover as well as 4 categories of increasing snow depth), land surface temperature and total precipitable water. One year of coincident observations, generating 20 and 80 million database entries, depending upon the sensor, are used in the retrieval algorithm. The remaining areas such as sea ice and high latitude coastal zones are filled with a combination of CloudSat and AMSR-E plus MHS observations together with a model to create the equivalent databases for other radiometers in the constellation. The most noteworthy result from the Day-1 algorithm is the quality of the land products when compared to existing products. Unlike previous versions of land algorithms that depended upon complex screening routines to decide if pixels were precipitating or not, the current scheme is free of conditional rain statements and appears to produce rain rate with much greater fidelity than previous schemes. There results will be shown.

Tire-to-Surface Friction-Coefficient Measurements with a C-123B Airplane on Various Runway Surfaces

NASA Technical Reports Server (NTRS)

Sawyer, Richard H.; Kolnick, Joseph J.

1959-01-01

An investigation was conducted to obtain information on the tire-to-surface friction coefficients available in aircraft braking during the landing run. The tests were made with a C-123B airplane on both wet and dry concrete and bituminous pavements and on snow-covered and ice surfaces at speeds from 12 to 115 knots. Measurements were made of the maximum (incipient skidding) friction coefficient, the full-skidding (locked wheel) friction coefficient, and the wheel slip ratio during braking.

Terra Satellite

Atmospheric Science Data Center

2013-04-19

... new types of information for scientists studying Earth's climate, such as the partitioning of energy and carbon between the land surface ... types of atmospheric particles and clouds on climate. The change in reflection at different view angles affords the means to distinguish ...

47 CFR 1.1311 - Environmental information to be included in the environmental assessment (EA).

Code of Federal Regulations, 2010 CFR

2010-10-01

... facilities on any district, site, building, structure or object listed, or eligible for listing, in the... land utilized (e.g., deforestation, water diversion, wetland fill, or other extensive change of surface...

Watershed Characteristics and Land Management in the Nonpoint-Source Evaluation Monitoring Watersheds in Wisconsin

USGS Publications Warehouse

Rappold, K.F.; Wierl, J.A.; Amerson, F.U.

1997-01-01

In 1992, the Wisconsin Department of Natural Resources, in cooperation with the U.S. Geological Survey, began a land-use inventory to identify sources of contaminants and track the land-management changes for eight evaluation monitoring watersheds in Wisconsin. An important component of the land-use inventory has been developing descriptions and preliminary assessments for the eight watersheds. These descriptions establish a baseline for future data analysis. The watershed descriptions include sections on location, reference watersheds, climate, land use, soils and topography, and surface-water resources. The land-management descriptions include sections on objectives, sources of nonpoint contamination and goals of contaminant reduction, and implementation of best-management practices. This information was compiled primarily from the nonpoint-source control plans, county soil surveys, farm conservation plans, Federal and State agency data reports, and data collected through the land-use inventory.

Customer-oriented Data Formats and Services for Global Land Data Assimilation System (GLDAS) Products at the NASA GES DISC

NASA Astrophysics Data System (ADS)

Fang, H.; Kato, H.; Rodell, M.; Teng, W. L.; Vollmer, B. E.

2008-12-01

The Global Land Data Assimilation System (GLDAS) has been generating a series of land surface state (e.g., soil moisture and surface temperature) and flux (e.g., evaporation and sensible heat flux) products, simulated by four land surface models (CLM, Mosaic, Noah and VIC). These products are now accessible at the Hydrology Data and Information Services Center (HDISC), a component of the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC). Current GLDAS data hosted at HDISC include a set of 1.0° data products, covering 1979 to the present, from the four models and a 0.25° data product, covering 2000 to the present, from the Noah model. In addition to the basic anonymous ftp data downloading, users can avail themselves of several advanced data search and downloading services, such as Mirador and OPeNDAP. Mirador is a Google-based search tool that provides keywords searching, on-the-fly spatial and parameter subsetting of selected data. OPeNDAP (Open-source Project for a Network Data Access Protocol) enables remote OPeNDAP clients to access OPeNDAP served data regardless of local storage format. Additional data services to be available in the near future from HDISC include (1) on-the-fly converter of GLDAS to NetCDF and binary data formats; (2) temporal aggregation of GLDAS files; and (3) Giovanni, an online visualization and analysis tool that provides a simple way to visualize, analyze, and access vast amounts of data without having to download the data.

Assimilation of SMOS Retrieved Soil Moisture into the Land Information System

NASA Technical Reports Server (NTRS)

Blankenship, Clay B.; Case, Jonathan L.; Zavodsky, Bradley T.

2014-01-01

Soil moisture is a crucial variable for weather prediction because of its influence on evaporation and surface heat fluxes. It is also of critical importance for drought and flood monitoring and prediction and for public health applications such as monitoring vector-borne diseases. Land surface modeling benefits greatly from regular updates with soil moisture observations via data assimilation. Satellite remote sensing is the only practical observation type for this purpose in most areas due to its worldwide coverage. The newest operational satellite sensor for soil moisture is the Microwave Imaging Radiometer using Aperture Synthesis (MIRAS) instrument aboard the Soil Moisture and Ocean Salinity (SMOS) satellite. The NASA Short-term Prediction Research and Transition Center (SPoRT) has implemented the assimilation of SMOS soil moisture observations into the NASA Land Information System (LIS), an integrated modeling and data assimilation software platform. We present results from assimilating SMOS observations into the Noah 3.2 land surface model within LIS. The SMOS MIRAS is an L-band radiometer launched by the European Space Agency in 2009, from which we assimilate Level 2 retrievals [1] into LIS-Noah. The measurements are sensitive to soil moisture concentration in roughly the top 2.5 cm of soil. The retrievals have a target volumetric accuracy of 4% at a resolution of 35-50 km. Sensitivity is reduced where precipitation, snowcover, frozen soil, or dense vegetation is present. Due to the satellite's polar orbit, the instrument achieves global coverage twice daily at most mid- and low-latitude locations, with only small gaps between swaths.

Slope effects on shortwave radiation components and net radiation

NASA Technical Reports Server (NTRS)

Walter-Shea, Elizabeth A.; Blad, Blaine L.; Hays, Cynthia J.; Mesarch, Mark A.

1992-01-01

The main objective of the International Satellite Land Surface Climatology Project (ISLSCP) has been stated as 'the development of techniques that may be applied to satellite observations of the radiation reflected and emitted from the Earth to yield quantitative information concerning land surface climatological conditions.' The major field study, FIFE (the First ISLSCP Field Experiment), was conducted in 1978-89 to accomplish this objective. Four intensive field campaigns (IFC's) were carried out in 1987 and one in 1989. Factors contributing to observed reflected radiation from the FIFE site must be understood before the radiation observed by satellites can be used to quantify surface processes. Analysis since our last report has focused on slope effects on incoming and outgoing shortwave radiation and net radiation from data collected in 1989.

Northern Everglades, Florida, satellite image map

USGS Publications Warehouse

Thomas, Jean-Claude; Jones, John W.

2002-01-01

These satellite image maps are one product of the USGS Land Characteristics from Remote Sensing project, funded through the USGS Place-Based Studies Program with support from the Everglades National Park. The objective of this project is to develop and apply innovative remote sensing and geographic information system techniques to map the distribution of vegetation, vegetation characteristics, and related hydrologic variables through space and over time. The mapping and description of vegetation characteristics and their variations are necessary to accurately simulate surface hydrology and other surface processes in South Florida and to monitor land surface changes. As part of this research, data from many airborne and satellite imaging systems have been georeferenced and processed to facilitate data fusion and analysis. These image maps were created using image fusion techniques developed as part of this project.

How NASA Sees the Earth and Its Climate

NASA Technical Reports Server (NTRS)

BrowndeColstoun, Eric

2012-01-01

NASA Research Addresses Broad Questions: (1) How are global ecosystems changing? (2) What changes are occurring in global land cover and land use and what are their causes? (3) How is the Earth s surface being transformed and how can such information be used to predict future changes? (4) What are the consequences of land cover and land use change for the sustainability of ecosystems and economic productivity? NASA uses the view from above to monitor our changing home. Different satellites help us study the various systems of the Earth. No one system can do it all. NASA tools and science helps us to understand how the planet is changing and what the changes mean for us.

Land Surface Modeling and Data Assimilation to Support Physical Precipitation Retrievals for GPM

NASA Technical Reports Server (NTRS)

Peters-Lidard, Christa D.; Tian. Yudong; Kumar, Sujay; Geiger, James; Choudhury, Bhaskar

2010-01-01

Objective: The objective of this proposal is to provide a routine land surface modeling and data assimilation capability for GPM in order to provide global land surface states that are necessary to support physical precipitation retrieval algorithms over land. It is well-known that surface emission, particularly over the range of frequencies to be included in GPM, is sensitive to land surface states, including soil properties, vegetation type and greenness, soil moisture, surface temperature, and snow cover, density, and grain size. Therefore, providing a robust capability to routinely provide these critical land states is essential to support GPM-era physical retrieval algorithms over land.

Estimation of evapotranspiration for different land covers in a Brazilian semi-arid region: A case study of the Brígida River basin, Brazil

NASA Astrophysics Data System (ADS)

Santos, Celso Augusto Guimarães; Silva, Richarde Marques da; Silva, Alexandro Medeiros; Brasil Neto, Reginaldo Moura

2017-03-01

In this study, the Surface Energy Balance Algorithm for Land (SEBAL) was used to compute the surface albedo, vegetation indices (NDVI, SAVI and LAI), surface temperature, soil heat flux and evapotranspiration (ET) over two contrasting years (dry and wet) in the Brígida River basin, a semi-arid region of north-eastern Brazil. The actual ET was computed during satellite overpass and was integrated for 24 h on a pixel-by-pixel basis for the daily ET distribution. Due to the topographic effects, an attempt was also made to incorporate DEM information to estimate the net radiation. The land cover types identified in the watershed are cropland, bare land, dense canopy, grassland, and caatinga vegetation. In order to study the variation among the biophysical parameters and ET, two-way analysis of variance (ANOVA) was used. The ET calculated by SEBAL ranged between 2.46 and 6.87 mm/day for the dry year (1990) and 1.31 and 6.84 mm/day for the wet year (2009) for the river basin. The results showed that a reduction in vegetation cover is evident in the temporal and spatial analysis over the studied periods in the region and that these facts influence the values of the energy balance and ET. The results showed significant differences in the variables of land cover type and year at the probability level of 0.05 for all land cover types.

Calibration to improve forward model simulation of microwave emissivity at GPM frequencies over the U.S. Southern Great Plains

PubMed Central

Harrison, Kenneth W.; Tian, Yudong; Peters-Lidard, Christa D.; Ringerud, Sarah; Kumar, Sujay V.

2018-01-01

Better estimation of land surface microwave emissivity promises to improve over-land precipitation retrievals in the GPM era. Forward models of land microwave emissivity are available but have suffered from poor parameter specification and limited testing. Here, forward models are calibrated and the accompanying change in predictive power is evaluated. With inputs (e.g., soil moisture) from the Noah land surface model and applying MODIS LAI data, two microwave emissivity models are tested, the Community Radiative Transfer Model (CRTM) and Community Microwave Emission Model (CMEM). The calibration is conducted with the NASA Land Information System (LIS) parameter estimation subsystem using AMSR-E based emissivity retrievals for the calibration dataset. The extent of agreement between the modeled and retrieved estimates is evaluated using the AMSR-E retrievals for a separate 7-year validation period. Results indicate that calibration can significantly improve the agreement, simulating emissivity with an across-channel average root-mean-square-difference (RMSD) of about 0.013, or about 20% lower than if relying on daily estimates based on climatology. The results also indicate that calibration of the microwave emissivity model alone, as was done in prior studies, results in as much as 12% higher across-channel average RMSD, as compared to joint calibration of the land surface and microwave emissivity models. It remains as future work to assess the extent to which the improvements in emissivity estimation translate into improvements in precipitation retrieval accuracy. PMID:29795962

Digital data used to relate nutrient inputs to water quality in the Chesapeake Bay watershed

USGS Publications Warehouse

Brakebill, John W.; Preston, Stephen D.

1999-01-01

Digital data sets were compiled by the U. S. Geological Survey (USGS) and used as input for a collection of Spatially Referenced Regressions On Watershed attributes for the Chesapeake Bay region. These regressions relate streamwater loads to nutrient sources and the factors that affect the transport of these nutrients throughout the watershed. A digital segmented network based on watershed boundaries serves as the primary foundation for spatially referencing total nitrogen and total phosphorus source and land-surface characteristic data sets within a Geographic Information System. Digital data sets of atmospheric wet deposition of nitrate, point-source discharge locations, land cover, and agricultural sources such as fertilizer and manure were created and compiled from numerous sources and represent nitrogen and phosphorus inputs. Some land-surface characteristics representing factors that affect the transport of nutrients include land use, land cover, average annual precipitation and temperature, slope, and soil permeability. Nutrient input and land-surface characteristic data sets merged with the segmented watershed network provide the spatial detail by watershed segment required by the models. Nutrient stream loads were estimated for total nitrogen, total phosphorus, nitrate/nitrite, amonium, phosphate, and total suspended soilds at as many as 109 sites within the Chesapeake Bay watershed. The total nitrogen and total phosphorus load estimates are the dependent variables for the regressions and were used for model calibration. Other nutrient-load estimates may be used for calibration in future applications of the models.

Autumn olive (Elaeagnus umbellata) presence and proliferation on former surface coal mines in Eastern USA

USGS Publications Warehouse

Oliphant, Adam J.; Wynne, R.H.; Zipper, Carl E.; Ford, W. Mark; Donovan, P. F.; Li, Jing

2017-01-01

Invasive plants threaten native plant communities. Surface coal mines in the Appalachian Mountains are among the most disturbed landscapes in North America, but information about land cover characteristics of Appalachian mined lands is lacking. The invasive shrub autumn olive (Elaeagnus umbellata) occurs on these sites and interferes with ecosystem recovery by outcompeting native trees, thus inhibiting re-establishment of the native woody-plant community. We analyzed Landsat 8 satellite imagery to describe autumn olive’s distribution on post-mined lands in southwestern Virginia within the Appalachian coalfield. Eight images from April 2013 through January 2015 served as input data. Calibration and validation data obtained from high-resolution aerial imagery were used to develop a land cover classification model that identified areas where autumn olive was a primary component of land cover. Results indicate that autumn olive cover was sufficiently dense to enable detection on approximately 12.6 % of post-mined lands within the study area. The classified map had user’s and producer’s accuracies of 85.3 and 78.6 %, respectively, for the autumn olive coverage class. Overall accuracy was assessed in reference to an independent validation dataset at 96.8 %. Autumn olive was detected more frequently on mines disturbed prior to 2003, the last year of known plantings, than on lands disturbed by more recent mining. These results indicate that autumn olive growing on reclaimed coal mines in Virginia and elsewhere in eastern USA can be mapped using Landsat 8 Operational Land Imager imagery; and that autumn olive occurrence is a significant landscape vegetation feature on former surface coal mines in the southwestern Virginia segment of the Appalachian coalfield.

Spatial variability in airborne bacterial communities across land-use types and their relationship to the bacterial communities of potential source environments

PubMed Central

Bowers, Robert M; McLetchie, Shawna; Knight, Rob; Fierer, Noah

2011-01-01

Although bacteria are ubiquitous in the near-surface atmosphere and they can have important effects on human health, airborne bacteria have received relatively little attention and their spatial dynamics remain poorly understood. Owing to differences in meteorological conditions and the potential sources of airborne bacteria, we would expect the atmosphere over different land-use types to harbor distinct bacterial communities. To test this hypothesis, we sampled the near-surface atmosphere above three distinct land-use types (agricultural fields, suburban areas and forests) across northern Colorado, USA, sampling five sites per land-use type. Microbial abundances were stable across land-use types, with ∼105–106 bacterial cells per m3 of air, but the concentrations of biological ice nuclei, determined using a droplet freezing assay, were on average two and eight times higher in samples from agricultural areas than in the other two land-use types. Likewise, the composition of the airborne bacterial communities, assessed via bar-coded pyrosequencing, was significantly related to land-use type and these differences were likely driven by shifts in the sources of bacteria to the atmosphere across the land-uses, not local meteorological conditions. A meta-analysis of previously published data shows that atmospheric bacterial communities differ from those in potential source environments (leaf surfaces and soils), and we demonstrate that we may be able to use this information to determine the relative inputs of bacteria from these source environments to the atmosphere. This work furthers our understanding of bacterial diversity in the atmosphere, the terrestrial controls on this diversity and potential approaches for source tracking of airborne bacteria. PMID:21048802

Spatial-Temporal Variations of Water Quality and Its Relationship to Land Use and Land Cover in Beijing, China

PubMed Central

Chen, Xiang; Zhou, Weiqi; Pickett, Steward T. A.; Li, Weifeng; Han, Lijian

2016-01-01

Rapid urbanization with intense land use and land cover (LULC) change and explosive population growth has a great impact on water quality. The relationship between LULC characteristics and water quality provides important information for non-point sources (NPS) pollution management. In this study, we first quantified the spatial-temporal patterns of five water quality variables in four watersheds with different levels of urbanization in Beijing, China. We then examined the effects of LULC on water quality across different scales, using Pearson correlation analysis, redundancy analysis, and multiple regressions. The results showed that water quality was improved over the sampled years but with no significant difference (p > 0.05). However, water quality was significantly different among nonurban and both exurban and urban sites (p < 0.05). Forest land was positively correlated with water quality and affected water quality significantly (p < 0.05) within a 200 m buffer zone. Impervious surfaces, water, and crop land were negatively correlated with water quality. Crop land and impervious surfaces, however, affected water quality significantly (p < 0.05) for buffer sizes greater than 800 m. Grass land had different effects on water quality with the scales. The results provide important insights into the relationship between LULC and water quality, and thus for controlling NPS pollution in urban areas. PMID:27128934

Regulating services as measures of ecological resilience on DoD lands

USGS Publications Warehouse

Angermeier, Paul; Villamagna, Amy M.

2015-01-01

Knowledge of the capacity and flow of ecosystem services can help DoD land managers make decisions that enhance cost-effectiveness, minimize environmental damage, and maximize resources available for military missions. We demonstrated a methodology to quantify and map selected regulating services (RS), which helps land managers envision tradeoffs. Our objectives were to 1) estimate current capacity of and demand for selected RS within DoD lands, 2) examine the effects of future DoD land management and climate changes on the capacity and flow of these RS, and 3) project how land-use and climate changes in nearby lands affect future demand for RS. Our approach incorporates widely accepted models and equations, remote sensing, GIS analysis, and stakeholder involvement. Required data include land cover/use, soil type, precipitation, and air temperature. We integrated data into the a) Surface Curve Number Method and b) Revised Universal Soil Loss Equation to estimate capacity of sediment, nitrogen (N) and surface-water regulation. Capacities and flows of RS vary greatly across landscapes and are likely to vary as climate changes or development occurs. Analyses of RS capacity and flow can help managers and planners prioritize actions in the context of best management practices and compatible use buffers. Staff surveys indicated that our approach was informative and easy to use. Implementation may be most limited by on-installation personnel time.

Long-Term Effects of Changing Land Use Practices on Surface Water Quality in a Coastal River and Lagoonal Estuary

NASA Astrophysics Data System (ADS)

Rothenberger, Meghan B.; Burkholder, Joann M.; Brownie, Cavell

2009-09-01

The watershed of the Neuse River, a major tributary of the largest lagoonal estuary on the U.S. mainland, has sustained rapid growth of human and swine populations. This study integrated a decade of available land cover and water quality data to examine relationships between land use changes and surface water quality. Geographic Information Systems (GIS) analysis was used to characterize 26 subbasins throughout the watershed for changes in land use during 1992-2001, considering urban, agricultural (cropland, animal as pasture, and densities of confined animal feed operations [CAFOs]), forested, grassland, and wetland categories and numbers of wastewater treatment plants (WWTPs). GIS was also used together with longitudinal regression analysis to identify specific land use characteristics that influenced surface water quality. Total phosphorus concentrations were significantly higher during summer in subbasins with high densities of WWTPs and CAFOs. Nitrate was significantly higher during winter in subbasins with high numbers of WWTPs, and organic nitrogen was higher in subbasins with higher agricultural coverage, especially with high coverage of pastures fertilized with animal manure. Ammonium concentrations were elevated after high precipitation. Overall, wastewater discharges in the upper, increasingly urbanized Neuse basin and intensive swine agriculture in the lower basin have been the highest contributors of nitrogen and phosphorus to receiving surface waters. Although nonpoint sources have been emphasized in the eutrophication of rivers and estuaries such as the Neuse, point sources continue to be major nutrient contributors in watersheds sustaining increasing human population growth. The described correlation and regression analyses represent a rapid, reliable method to relate land use patterns to water quality, and they can be adapted to watersheds in any region.

Assessment of Irrigation Physics in a Land Surface Modeling Framework Using Non-Traditional and Human-Practice Datasets

NASA Technical Reports Server (NTRS)

Lawston, Patricia M.; Santanello, Joseph A.; Rodell, Matthew; Franz, Trenton E.

2017-01-01

Irrigation increases soil moisture, which in turn controls water and energy fluxes from the land surface to the10 planetary boundary layer and determines plant stress and productivity. Therefore, developing a realistic representation of irrigation is critical to understanding land-atmosphere interactions in agricultural areas. Irrigation parameterizations are becoming more common in land surface models and are growing in sophistication, but there is difficulty in assessing the realism of these schemes, due to limited observations (e.g., soil moisture, evapotranspiration) and scant reporting of irrigation timing and quantity. This study uses the Noah land surface model run at high resolution within NASAs Land15 Information System to assess the physics of a sprinkler irrigation simulation scheme and model sensitivity to choice of irrigation intensity and greenness fraction datasets over a small, high resolution domain in Nebraska. Differences between experiments are small at the interannual scale but become more apparent at seasonal and daily time scales. In addition, this study uses point and gridded soil moisture observations from fixed and roving Cosmic Ray Neutron Probes and co-located human practice data to evaluate the realism of irrigation amounts and soil moisture impacts simulated by the model. Results20 show that field-scale heterogeneity resulting from the individual actions of farmers is not captured by the model and the amount of irrigation applied by the model exceeds that applied at the two irrigated fields. However, the seasonal timing of irrigation and soil moisture contrasts between irrigated and non-irrigated areas are simulated well by the model. Overall, the results underscore the necessity of both high-quality meteorological forcing data and proper representation of irrigation foraccurate simulation of water and energy states and fluxes over cropland.

Extreme Maximum Land Surface Temperatures.

NASA Astrophysics Data System (ADS)

Garratt, J. R.

1992-09-01

There are numerous reports in the literature of observations of land surface temperatures. Some of these, almost all made in situ, reveal maximum values in the 50°-70°C range, with a few, made in desert regions, near 80°C. Consideration of a simplified form of the surface energy balance equation, utilizing likely upper values of absorbed shortwave flux (1000 W m2) and screen air temperature (55°C), that surface temperatures in the vicinity of 90°-100°C may occur for dry, darkish soils of low thermal conductivity (0.1-0.2 W m1 K1). Numerical simulations confirm this and suggest that temperature gradients in the first few centimeters of soil may reach 0.5°-1°C mm1 under these extreme conditions. The study bears upon the intrinsic interest of identifying extreme maximum temperatures and yields interesting information regarding the comfort zone of animals (including man).

Examining Environmental Gradients with satellite data in permafrost regions - the current state of the ESA GlobPermafrost initative

NASA Astrophysics Data System (ADS)

Grosse, G.; Bartsch, A.; Kääb, A.; Westermann, S.; Strozzi, T.; Wiesmann, A.; Duguay, C. R.; Seifert, F. M.; Obu, J.; Nitze, I.; Heim, B.; Haas, A.; Widhalm, B.

2017-12-01

Permafrost cannot be directly detected from space, but many surface features of permafrost terrains and typical periglacial landforms are observable with a variety of EO sensors ranging from very high to medium resolution at various wavelengths. In addition, landscape dynamics associated with permafrost changes and geophysical variables relevant for characterizing the state of permafrost, such as land surface temperature or freeze-thaw state can be observed with spaceborne Earth Observation. Suitable regions to examine environmental gradients across the Arctic have been defined in a community white paper (Bartsch et al. 2014, hdl:10013/epic.45648.d001). These transects have been revised and adjusted within the DUE GlobPermafrost initiative of the European Space Agency. The ESA DUE GlobPermafrost project develops, validates and implements Earth Observation (EO) products to support research communities and international organisations in their work on better understanding permafrost characteristics and dynamics. Prototype product cases will cover different aspects of permafrost by integrating in situ measurements of subsurface and surface properties, Earth Observation, and modelling to provide a better understanding of permafrost today. The project will extend local process and permafrost monitoring to broader spatial domains, support permafrost distribution modelling, and help to implement permafrost landscape and feature mapping in a GIS framework. It will also complement active layer and thermal observing networks. Both lowland (latitudinal) and mountain (altitudinal) permafrost issues are addressed. The status of the Permafrost Information System and first results will be presented. Prototypes of GlobPermafrost datasets include: Modelled mean annual ground temperature by use of land surface temperature and snow water equivalent from satellites Land surface characterization including shrub height, land cover and parameters related to surface roughness Trends from Landsat time-series over selected transects For selected sites: subsidence, ground fast lake ice, land surface features and rock glacier monitoring

A factorial assessment of the sensitivity of the BATS land-surface parameterization scheme. [BATS (Biosphere-Atmosphere Transfer Scheme)

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

Henderson-Sellers, A.

Land-surface schemes developed for incorporation into global climate models include parameterizations that are not yet fully validated and depend upon the specification of a large (20-50) number of ecological and soil parameters, the values of which are not yet well known. There are two methods of investigating the sensitivity of a land-surface scheme to prescribed values: simple one-at-a-time changes or factorial experiments. Factorial experiments offer information about interactions between parameters and are thus a more powerful tool. Here the results of a suite of factorial experiments are reported. These are designed (i) to illustrate the usefulness of this methodology andmore » (ii) to identify factors important to the performance of complex land-surface schemes. The Biosphere-Atmosphere Transfer Scheme (BATS) is used and its sensitivity is considered (a) to prescribed ecological and soil parameters and (b) to atmospheric forcing used in the off-line tests undertaken. Results indicate that the most important atmospheric forcings are mean monthly temperature and the interaction between mean monthly temperature and total monthly precipitation, although fractional cloudiness and other parameters are also important. The most important ecological parameters are vegetation roughness length, soil porosity, and a factor describing the sensitivity of the stomatal resistance of vegetation to the amount of photosynthetically active solar radiation and, to a lesser extent, soil and vegetation albedos. Two-factor interactions including vegetation roughness length are more important than many of the 23 specified single factors. The results of factorial sensitivity experiments such as these could form the basis for intercomparison of land-surface parameterization schemes and for field experiments and satellite-based observation programs aimed at improving evaluation of important parameters.« less

Model evaluation using a community benchmarking system for land surface models

NASA Astrophysics Data System (ADS)

Mu, M.; Hoffman, F. M.; Lawrence, D. M.; Riley, W. J.; Keppel-Aleks, G.; Kluzek, E. B.; Koven, C. D.; Randerson, J. T.

2014-12-01

Evaluation of atmosphere, ocean, sea ice, and land surface models is an important step in identifying deficiencies in Earth system models and developing improved estimates of future change. For the land surface and carbon cycle, the design of an open-source system has been an important objective of the International Land Model Benchmarking (ILAMB) project. Here we evaluated CMIP5 and CLM models using a benchmarking system that enables users to specify models, data sets, and scoring systems so that results can be tailored to specific model intercomparison projects. Our scoring system used information from four different aspects of global datasets, including climatological mean spatial patterns, seasonal cycle dynamics, interannual variability, and long-term trends. Variable-to-variable comparisons enable investigation of the mechanistic underpinnings of model behavior, and allow for some control of biases in model drivers. Graphics modules allow users to evaluate model performance at local, regional, and global scales. Use of modular structures makes it relatively easy for users to add new variables, diagnostic metrics, benchmarking datasets, or model simulations. Diagnostic results are automatically organized into HTML files, so users can conveniently share results with colleagues. We used this system to evaluate atmospheric carbon dioxide, burned area, global biomass and soil carbon stocks, net ecosystem exchange, gross primary production, ecosystem respiration, terrestrial water storage, evapotranspiration, and surface radiation from CMIP5 historical and ESM historical simulations. We found that the multi-model mean often performed better than many of the individual models for most variables. We plan to publicly release a stable version of the software during fall of 2014 that has land surface, carbon cycle, hydrology, radiation and energy cycle components.

A hybrid HDRF model of GOMS and SAIL: GOSAIL

NASA Astrophysics Data System (ADS)

Dou, B.; Wu, S.; Wen, J.

2016-12-01

Understanding the surface reflectance anisotropy is the key facet in interpreting the features of land surface from remotely sensed information, which describes the property of land surface to reflect the solar radiation directionally. Most reflectance anisotropy models assumed the nature surface was illuminated only by the direct solar radiation, while the diffuse skylight becomes dominant especially for the over cast sky conditions and high rugged terrain. Correcting the effect of diffuse skylight on the reflectance anisotropy to obtain the intrinsic directional reflectance of land surface is highly desirable for remote sensing applications. This paper developed a hybrid HDRF model of GOMS and SAIL called GOSAIL model for discrete canopies. The accurate area proportions of four scene components are calculated by the GOMS model and the spectral signatures of scene components are provided by the SAIL model. Both the single scattering contribution and the multiple scattering contributions within and between the canopy and background under the clear and diffuse illumination conditions are considered in the GOSAIL model. The HDRF simulated by the 3-D Discrete Anisotropic Radiative Transfer (DART) model and the HDRF measurements over the 100m×100m mature pine stand at the Järvselja, Estonia are used for validating and evaluating the performance of proposed GOSAIL model. The comparison results indicate the GOSAIL model can accurately reproducing the angular feature of discrete canopy for both the clear and overcast atmospheric conditions. The GOSAIL model is promising for the land surface biophysical parameters retrieval (e.g. albedo, leaf area index) over the heterogeneous terrain.

Assessment of MERRA-2 Land Surface Energy Flux Estimates

NASA Technical Reports Server (NTRS)

Draper, Clara; Reichle, Rolf; Koster, Randal

2017-01-01

In MERRA-2, observed precipitation is inserted in place of model-generated precipitation at the land surface. The use of observed precipitation was originally developed for MERRA-Land(a land-only replay of MERRA with model-generated precipitation replaced with observations).Previously shown that the land hydrology in MERRA-2 and MERRA-Land is better than MERRA. We test whether the improved land surface hydrology in MERRA-2 leads to the expected improvements in the land surface energy fluxes and 2 m air temperatures (T2m).

A Novel Optical Model for Remote Sensing of Near-Surface Soil Moisture

NASA Astrophysics Data System (ADS)

Babaeian, E.; Sadeghi, M.; Jones, S. B.; Tuller, M.

2016-12-01

Common triangle and trapezoid methods that are based on both optical and thermal remote sensing (RS) information have been widely applied in the past to estimate near-surface soil moisture from the soil temperature - vegetation index space (e.g., LST-NDVI). For most cases, this approach assumes a linear relationship between soil moisture and temperature. Though this linearity assumption yields reasonable moisture estimates, it is not always justified as evidenced by laboratory and field measurements. Furthermore, this approach requires optical as well as thermal RS data for definition of the land surface temperature (LST) - vegetation index space, therefore, it is not applicable to satellites that do not provide thermal output such as the ESA Sentinel-2. To overcome these limitations, we propose a novel trapezoid model that only relies on optical NIR and SWIR data. The new model was validated using Sentinel-2 and Landsat-8 data for the semiarid Walnut Gulch (AZ) and sub humid Little Washita (OK) watersheds that vastly differ in land use and surface cover and provide excellent ground-truth moisture information from extensive sensor networks. Preliminary results for 2015-2016 indicate significant potential of the new model with a RMSE smaller than 4% volumetric near-surface moisture content and also confirm the enhanced utility of the high spatially and temporally resolved Sentinel-2 data.

Comparison of Land Skin Temperature from a Land Model, Remote Sensing, and In-situ Measurement

NASA Technical Reports Server (NTRS)

Wang, Aihui; Barlage, Michael; Zeng, Xubin; Draper, Clara Sophie

2014-01-01

Land skin temperature (Ts) is an important parameter in the energy exchange between the land surface and atmosphere. Here hourly Ts from the Community Land Model Version 4.0, MODIS satellite observations, and in-situ observations in 2003 were compared. Compared with the in-situ observations over four semi-arid stations, both MODIS and modeled Ts show negative biases, but MODIS shows an overall better performance. Global distribution of differences between MODIS and modeled Ts shows diurnal, seasonal, and spatial variations. Over sparsely vegetated areas, the model Ts is generally lower than the MODIS observed Ts during the daytime, while the situation is opposite at nighttime. The revision of roughness length for heat and the constraint of minimum friction velocity from Zeng et al. [2012] bring the modeled Ts closer to MODIS during the day, and have little effect on Ts at night. Five factors contributing to the Ts differences between the model and MODIS are identified, including the difficulty in properly accounting for cloud cover information at the appropriate temporal and spatial resolutions, and uncertainties in surface energy balance computation, atmospheric forcing data, surface emissivity, and MODIS Ts data. These findings have implications for the cross-evaluation of modeled and remotely sensed Ts, as well as the data assimilation of Ts observations into Earth system models.

Estimating snow water equivalent from GPS vertical site-position observations in the western United States

PubMed Central

Ouellette, Karli J; de Linage, Caroline; Famiglietti, James S

2013-01-01

[1] Accurate estimation of the characteristics of the winter snowpack is crucial for prediction of available water supply, flooding, and climate feedbacks. Remote sensing of snow has been most successful for quantifying the spatial extent of the snowpack, although satellite estimation of snow water equivalent (SWE), fractional snow covered area, and snow depth is improving. Here we show that GPS observations of vertical land surface loading reveal seasonal responses of the land surface to the total weight of snow, providing information about the stored SWE. We demonstrate that the seasonal signal in Scripps Orbit and Permanent Array Center (SOPAC) GPS vertical land surface position time series at six locations in the western United States is driven by elastic loading of the crust by the snowpack. GPS observations of land surface deformation are then used to predict the water load as a function of time at each location of interest and compared for validation to nearby Snowpack Telemetry observations of SWE. Estimates of soil moisture are included in the analysis and result in considerable improvement in the prediction of SWE. Citation: Ouellette, K. J., C. de Linage, and J. S. Famiglietti (2013), Estimating snow water equivalent from GPS vertical site-position observations in the western United States, Water Resour. Res., 49, 2508–2518, doi:10.1002/wrcr.20173. PMID:24223442

Development and Deployment of Unmanned Aircraft Instrumentation for Measuring Quantities Related to Land Surface-Atmosphere Interactions

NASA Astrophysics Data System (ADS)

de Boer, G.; Lawrence, D.; Elston, J.; Argrow, B. M.; Palo, S. E.; Curry, N.; Finamore, W.; Mack, J.; LoDolce, G.; Schmid, B.; Long, C. N.; Bland, G.; Maslanik, J. A.; Gao, R. S.; Telg, H.; Semmer, S.; Maclean, G.; Ivey, M.; Hock, T. F.; Bartram, B.; Bendure, A.; Stachura, M.

2015-12-01

Use of unmanned aircraft systems (UAS) in evaluation of geophysical parameters is expanding at a rapid rate. Despite limitation imposed by necessary regulations related to operation of UAS in the federal airspace, several groups have developed and deployed a variety of UAS and the associated sensors to make measurements of the atmosphere, land surface, ocean and cryosphere. Included in this grouping is work completed at the University of Colorado - Boulder, which has an extended history of operating UAS and expanding their use in the earth sciences. Collaborative projects between the department of Aerospace Engineering, the Cooperative Institute for Research in Environmental Sciences (CIRES), the Research and Engineering Center for Unmanned Vehicles (RECUV), the National Oceanographic and Atmospheric Administration (NOAA) and National Centers for Atmospheric Research (NCAR) have resulted in deployment of UAS to a variety of environments, including the Arctic. In this presentation, I will give an overview of some recent efforts lead by the University of Colorado to develop and deploy a variety of UAS. Work presented will emphasize recent campaigns and instrument development and testing related to understanding the land-atmosphere interface. Specifically, information on systems established for evaluating surface radiation (including albedo), turbulent exchange of water vapor, heat and gasses, and aerosol processes will be presented, along with information on the use of terrestrial ecosystem sensing to provide critical measurments for the evaluation of lower atmospheric flux measurements.

Characterization and Spectral Monitoring of Coffee Lands in Brazil

NASA Astrophysics Data System (ADS)

Alves, H. M. R.; Volpato, M. M. L.; Vieira, T. G. C.; Maciel, D. A.; Gonçalves, T. G.; Dantas, M. F.

2016-06-01

In Brazil, coffee production has great economic and social importance. Despite this fact, there is still a shortage of information regarding its spatial distribution, crop management and environment. The aim of this study was to carry out spectral monitoring of coffee lands and to characterize their environments using geotechnologies. Coffee fields with contiguous areas over 0.01 km2 within a 488.5 km2 region in the south of Minas Gerais state were selected for the study. Spectral data from the sensors OLI/Landsat 8 and the Shuttle Radar Topography Mission from 2014 to 2015 were obtained, as well as information on production areas, surface temperature, vegetation indexes, altitude and slope, were gathered and analyzed. The results indicate that there is great variation in the NDVI and NDWI values, with means ranging from 0.21 to 0.91 (NDVI) and 0.108 to 0.543 (NDWI). The altitude ranged from 803 to 1150 m, and the surface temperature from 20.9°C to 27.6°C. The altitude and the surface temperature distribution patterns were correlated with the vegetation indexes. The slope classes were very homogeneous, predominantly with declivities between 8 to 20 %, characterized as wavy relief. This study made possible the characterization and monitoring of coffee lands and its results may be instrumental in decision-making processes related to coffee management.

DSCOVR_EPIC_L2_VESDR_01

Atmospheric Science Data Center

2018-06-28

... improving forecasting of near surface weather. DASF provides information critical to accounting for structural contributions to measurements ... derived products.   We also provide two ancillary science data products. They are  10 km SIN Grid Land Cover Type and  ...

Monitoring land use/land cover changes using CORINE land cover data: a case study of Silivri coastal zone in Metropolitan Istanbul.

PubMed

Yilmaz, Rüya

2010-06-01

The objective of the present study was to assess changes in land use/land cover patterns in the coastal town of Silivri, a part of greater Istanbul administratively. In the assessment, remotely sensed data, in the form of satellite images, and geographic information systems were used. Types of land use/land cover were designated as the percentage of the total area studied. Results calculated from the satellite data for land cover classification were compared successfully with the database Coordination of Information on the Environment (CORINE). This served as a reference to appraise the reliability of the study presented here. The CORINE Program was established by the European Commission to create a harmonized Geographical Information System on the state of the environment in the European Community. Unplanned urbanization is causing land use changes mainly in developing countries such as Turkey. This situation in Turkey is frequently observed in the city of Istanbul. There are only a few studies of land use-land cover changes which provide an integrated assessment of the biophysical and societal causes and consequences of environmental degradation in Istanbul. The research area comprised greater Silivri Town which is situated by the coast of Marmara Sea, and it is located approximately 60 km west of Istanbul. The city of Istanbul is one of the largest metropolises in Europe with ca. 15 million inhabitants. Additionally, greater Silivri is located near the terminal point of the state highway connecting Istanbul with Europe. Measuring of changes occurring in land use would help control future planning of settlements; hence, it is of importance for the Greater Silivri and Silivri Town. Following our evaluations, coastal zone of Silivri was classified into the land use groups of artificial surfaces agricultural areas and forests and seminatural areas with 47.1%, 12.66%, and 22.62%, respectively.

High-Resolution Specification of the Land and Ocean Surface for Improving Regional Mesoscale Model Predictions

NASA Technical Reports Server (NTRS)

Case, Jonathan L.; Lazarus, Steven M.; Splitt, Michael E.; Crosson, William L.; Lapenta, William M.; Jedlovec, Gary J.; Peters-Lidard, Christa D.

2008-01-01

The exchange of energy and moisture between the Earth's surface and the atmospheric boundary layer plays a critical role in many meteorological processes. High-resolution, accurate representations of surface properties such as sea-surface temperature (SST), soil temperature and moisture content, ground fluxes, and vegetation are necessary to better understand the Earth-atmosphere interactions and improve numerical predictions of sensible weather. The NASA Short-term Prediction Research and Transition (SPoRT) Center has been conducting separate studies to examine the impacts of high-resolution land-surface initialization data from the Goddard Space Flight Center Land Information System (LIS) on subsequent WRF forecasts, as well as the influence of initializing WRF with SST composites derived from the MODIS instrument. This current project addresses the combined impacts of using high-resolution lower boundary data over both land (LIS data) and water (MODIS SSTs) on the subsequent daily WRF forecasts over Florida during May 2004. For this experiment, the WRF model is configured to run on a nested domain with 9- km and 3-kin grid spacing, centered on the Florida peninsula and adjacent coastal waters of the Gulf of Mexico and Atlantic Ocean. A control configuration of WRF is established to take all initial condition data from the NCEP Eta model. Meanwhile, two WRF experimental runs are configured to use high-resolution initialization data from (1) LIS land-surface data only, and (2) a combination of LIS data and high-resolution MODIS SST composites. The experiment involves running 24-hour simulations of the control WRF configuration, the MS-initialized WRF, and the LIS+MODIS-initialized WRF daily for the entire month of May 2004. All atmospheric data for initial and boundary conditions for the Control, LIS, and LIS+MODIS runs come from the NCEP Eta model on a 40-km grid. Verification statistics are generated at land surface observation sites and buoys, and the impacts of the high-resolution lower boundary data on the development and evolution of mesoscale circulations such as sea and land breezes are examined, This paper will present the results of these WRF modeling experiments using LIS and MODIS lower boundary datasets over the Florida peninsula during May 2004.

Towards a satellite driven land surface model using SURFEX modelling platform Offline Data Assimilation: an assessment of the method over Europe and the Mediterranean basin

NASA Astrophysics Data System (ADS)

Albergel, Clément; Munier, Simon; Leroux, Delphine; Fairbairn, David; Dorigo, Wouter; Decharme, Bertrand; Calvet, Jean-Christophe

2017-04-01

Modelling platforms including Land Surface Models (LSMs), forced by gridded atmospheric variables and coupled to river routing models are necessary to increase our understanding of the terrestrial water cycle. These LSMs need to simulate biogeophysical variables like Surface and Root Zone Soil Moisture (SSM, RZSM), Leaf Area Index (LAI) in a way that is fully consistent with the representation of surface/energy fluxes and river discharge simulations. Global SSM and LAI products are now operationally available from spaceborne instruments and they can be used to constrain LSMs through Data Assimilation (DA) techniques. In this study, an offline data assimilation system implemented in Météo-France's modelling platform (SURFEX) is tested over Europe and the Mediterranean basin to increase prediction accuracy for land surface variables. The resulting Land Data Assimilation System (LDAS) makes use of a simplified Extended Kalman Filter (SEKF). It is able to ingests information from satellite derived (i) SSM from the latest version of the ESA Climate Change Initiative as well as (ii) LAI from the Copernicus GLS project to constrain the multilayer, CO2-responsive version of the Interactions Between Soil, Biosphere, and Atmosphere model (ISBA) coupled with Météo-France's version of the Total Runoff Integrating Pathways continental hydrological system (ISBA-CTRIP). ERA-Interim observations based atmospheric forcing with precipitations corrected from Global Precipitation Climatology Centre observations (GPCC) is used to force ISBA-CTRIP at a resolution of 0.5 degree over 2000-2015. The model sensitivity to the assimilated observations is presented and a set of statistical diagnostics used to evaluate the impact of assimilating SSM and LAI on different model biogeophysical variables are provided. It is demonstrated that the assimilation scheme works effectively. The SEKF is able to extract useful information from the data signal at the grid scale and distribute the RZSM and LAI increments throughout the model impacting soil moisture, terrestrial vegetation and water cycle, surface carbon and energy fluxes.

Using Remotely-Sensed Estimates of Soil Moisture to Infer Soil Texture and Hydraulic Properties across a Semi-arid Watershed

NASA Technical Reports Server (NTRS)

Santanello, Joseph A.; Peters-Lidard, Christa D.; Garcia, Matthew E.; Mocko, David M.; Tischler, Michael A.; Moran, M. Susan; Thoma, D. P.

2007-01-01

Near-surface soil moisture is a critical component of land surface energy and water balance studies encompassing a wide range of disciplines. However, the processes of infiltration, runoff, and evapotranspiration in the vadose zone of the soil are not easy to quantify or predict because of the difficulty in accurately representing soil texture and hydraulic properties in land surface models. This study approaches the problem of parameterizing soils from a unique perspective based on components originally developed for operational estimation of soil moisture for mobility assessments. Estimates of near-surface soil moisture derived from passive (L-band) microwave remote sensing were acquired on six dates during the Monsoon '90 experiment in southeastern Arizona, and used to calibrate hydraulic properties in an offline land surface model and infer information on the soil conditions of the region. Specifically, a robust parameter estimation tool (PEST) was used to calibrate the Noah land surface model and run at very high spatial resolution across the Walnut Gulch Experimental Watershed. Errors in simulated versus observed soil moisture were minimized by adjusting the soil texture, which in turn controls the hydraulic properties through the use of pedotransfer functions. By estimating a continuous range of widely applicable soil properties such as sand, silt, and clay percentages rather than applying rigid soil texture classes, lookup tables, or large parameter sets as in previous studies, the physical accuracy and consistency of the resulting soils could then be assessed. In addition, the sensitivity of this calibration method to the number and timing of microwave retrievals is determined in relation to the temporal patterns in precipitation and soil drying. The resultant soil properties were applied to an extended time period demonstrating the improvement in simulated soil moisture over that using default or county-level soil parameters. The methodology is also applied to an independent case at Walnut Gulch using a new soil moisture product from active (C-band) radar imagery with much lower spatial and temporal resolution. Overall, results demonstrate the potential to gain physically meaningful soils information using simple parameter estimation with few but appropriately timed remote sensing retrievals.

Updates of Land Surface and Air Quality Products in NASA MAIRS and NEESPI Data Portals

NASA Technical Reports Server (NTRS)

Shen, Suhung; Leptoukh, Gregory G.; Gerasimov, Irina

2010-01-01

Following successful support of the Northern Eurasia Earth Sciences Partner Initiative (NEESPI) project with NASA satellite remote sensing data, from Spring 2009 the NASA GES DISC (Goddard Earth Sciences Data and Information Services Center) has been working on collecting more satellite and model data to support the Monsoon Asia Integrated Regional Study (MAIRS) project. The established data management and service infrastructure developed for NEESPI has been used and improved for MAIRS support.Data search, subsetting, and download functions are available through a single system. A customized Giovanni system has been created for MAIRS.The Web-based on line data analysis and visualization system, Giovanni (Goddard Interactive Online Visualization ANd aNalysis Infrastructure) allows scientists to explore, quickly analyze, and download data easily without learning the original data structure and format. Giovanni MAIRS includes satellite observations from multiple sensors and model output from the NASA Global Land Data Assimilation System (GLDAS), and from the NASA atmospheric reanalysis project, MERRA. Currently, we are working on processing and integrating higher resolution land data in to Giovanni, such as vegetation index, land surface temperature, and active fire at 5km or 1km from the standard MODIS products. For data that are not archived at the GESDISC,a product metadata portal is under development to serve as a gateway for providing product level information and data access links, which include both satellite, model products and ground-based measurements information collected from MAIRS scientists.Due to the large overlap of geographic coverage and many similar scientific interests of NEESPI and MAIRS, these data and tools will serve both projects.

Surface-material maps of Viking landing sites on Mars

NASA Technical Reports Server (NTRS)

Moore, H. J.; Keller, J. M.

1991-01-01

Researchers mapped the surface materials at the Viking landing sites on Mars to gain a better understanding of the materials and rock populations at the sites and to provide information for future exploration. The maps extent to about 9 m in front of each lander and are about 15 m wide - an area comparable to the area of a pixel in high resolution Viking Orbiter images. The maps are divided into the near and far fields. Data for the near fields are from 1/10 scale maps, umpublished maps, and lander images. Data for the far fields are from 1/20 scale contour maps, contoured lander camera mosaics, and lander images. Rocks are located on these maps using stereometric measurements and the contour maps. Frequency size distribution of rocks and the responses of soil-like materials to erosion by engine exhausts during landings are discussed.

A Colorful Landing on Pluto

NASA Image and Video Library

2017-01-21

What would it be like to actually land on Pluto? This image is one of more than 100 images taken by NASA's New Horizons spacecraft over six weeks of approach and close flyby in the summer of 2015. A video offers a trip down onto the surface of Pluto -- starting with a distant view of Pluto and its largest moon, Charon -- and leading up to an eventual ride in for a "landing" on the shoreline of Pluto's informally named Sputnik Planitia. After a 9.5-year voyage covering more than three billion miles, New Horizons flew through the Pluto system on July 14, 2015, coming within 7,800 miles (12,500 kilometers) of Pluto. Carrying powerful telescopic cameras that could spot features smaller than a football field, New Horizons sent back hundreds of images of Pluto and its moons that show how dynamic and fascinating their surfaces are. Movies are available at http://photojournal.jpl.nasa.gov/catalog/PIA11709

The 3-D geological model around Chang'E-3 landing site based on lunar penetrating radar Channel 1 data

NASA Astrophysics Data System (ADS)

Yuan, Yuefeng; Zhu, Peimin; Zhao, Na; Xiao, Long; Garnero, Edward; Xiao, Zhiyong; Zhao, Jiannan; Qiao, Le

2017-07-01

High-frequency lunar penetrating radar (LPR) data from an instrument on the lunar rover Yutu, from the Chang'E-3 (CE-3) robotic lander, were used to build a three-dimensional (3-D) geological model of the lunar subsurface structure. The CE-3 landing site is in the northern Mare Imbrium. More than five significant reflection horizons are evident in the LPR profile, which we interpret as different period lava flow sequences deposited on the lunar surface. The most probable directions of these flows were inferred from layer depths, thicknesses, and other geological information. Moreover, the apparent Imbrian paleoregolith homogeneity in the profile supports the suggestion of a quiescent period of lunar surface evolution. Similar subsurface structures are found at the NASA Apollo landing sites, indicating that the cause and time of formation of the imaged phenomena may be similar between the two distant regions.

Advances in land modeling of KIAPS based on the Noah Land Surface Model

NASA Astrophysics Data System (ADS)

Koo, Myung-Seo; Baek, Sunghye; Seol, Kyung-Hee; Cho, Kyoungmi

2017-08-01

As of 2013, the Noah Land Surface Model (LSM) version 2.7.1 was implemented in a new global model being developed at the Korea Institute of Atmospheric Prediction Systems (KIAPS). This land surface scheme is further refined in two aspects, by adding new physical processes and by updating surface input parameters. Thus, the treatment of glacier land, sea ice, and snow cover are addressed more realistically. Inconsistencies in the amount of absorbed solar flux at ground level by the land surface and radiative processes are rectified. In addition, new parameters are available by using 1-km land cover data, which had usually not been possible at a global scale. Land surface albedo/emissivity climatology is newly created using Moderate-Resolution Imaging Spectroradiometer (MODIS) satellitebased data and adjusted parameterization. These updates have been applied to the KIAPS-developed model and generally provide a positive impact on near-surface weather forecasting.

Multispectral image fusion for detecting land mines

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

Clark, G.A.; Sengupta, S.K.; Aimonetti, W.D.

1995-04-01

This report details a system which fuses information contained in registered images from multiple sensors to reduce the effects of clutter and improve the ability to detect surface and buried land mines. The sensor suite currently consists of a camera that acquires images in six bands (400nm, 500nm, 600nm, 700nm, 800nm and 900nm). Past research has shown that it is extremely difficult to distinguish land mines from background clutter in images obtained from a single sensor. It is hypothesized, however, that information fused from a suite of various sensors is likely to provide better detection reliability, because the suite ofmore » sensors detects a variety of physical properties that are more separable in feature space. The materials surrounding the mines can include natural materials (soil, rocks, foliage, water, etc.) and some artifacts.« less

Global land cover mapping using Earth observation satellite data: Recent progresses and challenges

NASA Astrophysics Data System (ADS)

Ban, Yifang; Gong, Peng; Giri, Chandra

2015-05-01

Land cover is an important variable for many studies involving the Earth surface, such as climate, food security, hydrology, soil erosion, atmospheric quality, conservation biology, and plant functioning. Land cover not only changes with human caused land use changes, but also changes with nature. Therefore, the state of land cover is highly dynamic. In winter snow shields underneath various other land cover types in higher latitudes. Floods may persist for a long period in a year over low land areas in the tropical and subtropical regions. Forest maybe burnt or clear cut in a few days and changes to bare land. Within several months, the coverage of crops may vary from bare land to nearly 100% crops and then back to bare land following harvest. The highly dynamic nature of land cover creates a challenge in mapping and monitoring which remains to be adequately addressed. As economic globalization continues to intensify, there is an increasing trend of land cover/land use change, environmental pollution, land degradation, biodiversity loss at the global scale, timely and reliable information on global land cover and its changes is urgently needed to mitigate the negative impact of global environment change.

Revising Hydrology of a Land Surface Model

NASA Astrophysics Data System (ADS)

Le Vine, Nataliya; Butler, Adrian; McIntyre, Neil; Jackson, Christopher

2015-04-01

Land Surface Models (LSMs) are key elements in guiding adaptation to the changing water cycle and the starting points to develop a global hyper-resolution model of the terrestrial water, energy and biogeochemical cycles. However, before this potential is realised, there are some fundamental limitations of LSMs related to how meaningfully hydrological fluxes and stores are represented. An important limitation is the simplistic or non-existent representation of the deep subsurface in LSMs; and another is the lack of connection of LSM parameterisations to relevant hydrological information. In this context, the paper uses a case study of the JULES (Joint UK Land Environmental Simulator) LSM applied to the Kennet region in Southern England. The paper explores the assumptions behind JULES hydrology, adapts the model structure and optimises the coupling with the ZOOMQ3D regional groundwater model. The analysis illustrates how three types of information can be used to improve the model's hydrology: a) observations, b) regionalized information, and c) information from an independent physics-based model. It is found that: 1) coupling to the groundwater model allows realistic simulation of streamflows; 2) a simple dynamic lower boundary improves upon JULES' stationary unit gradient condition; 3) a 1D vertical flow in the unsaturated zone is sufficient; however there is benefit in introducing a simple dual soil moisture retention curve; 4) regionalized information can be used to describe soil spatial heterogeneity. It is concluded that relatively simple refinements to the hydrology of JULES and its parameterisation method can provide a substantial step forward in realising its potential as a high-resolution multi-purpose model.

Evaluation Of The MODIS-VIIRS Land Surface Reflectance Fundamental Climate Data Record.

NASA Astrophysics Data System (ADS)

Roger, J. C.; Vermote, E.; Skakun, S.; Murphy, E.; Holben, B. N.; Justice, C. O.

2016-12-01

The land surface reflectance is a fundamental climate data record at the basis of the derivation of other climate data records (Albedo, LAI/Fpar, Vegetation indices) and has been recognized as a key parameter in the understanding of the land-surface-climate processes. Here, we present the validation of the Land surface reflectance used for MODIS and VIIRS data. This methodology uses the 6SV Code and data from the AERONET network. The first part was to define a protocol to use the AERONET data. To correctly take into account the aerosol model, we used the aerosol microphysical properties provided by the AERONET network including size-distribution (%Cf, %Cc, rf, rc, σr, σc), complex refractive indices and sphericity. Over the 670 available AERONET sites, we selected 230 sites with sufficient data. To be useful for validation, the aerosol model should be readily available anytime, which is rarely the case. We then used regressions for each microphysical parameter using the aerosol optical thickness at 440nm and the Angström coefficient as parameters. Comparisons with the AERONET dataset give good APU (Accuracy-Precision-Uncertainties) for each parameter. The second part of the study relies on the theoretical land surface retrieval. We generated TOA synthetic data using aerosol models from AERONET and determined APU on the surface reflectance retrieval while applying the MODIS and VIRRS Atmospheric correction software. Over 250 AERONET sites, the global uncertainties are for MODIS band 1 (red) is always lower than 0.0015 (when surface reflectance is > 0.04). This very good result shows the validity of our reference. Then, we used this reference for validating the MODIS and VIIRS surface reflectance products. The overall accuracy clearly reaches specifications. Finally, we will present an error budget of the surface reflectance retrieval. Indeed, to better understand how to improve the methodology, we defined an exhaustive error budget. We included all inputs i.e. sensor, calibration, aerosol properties, atmospheric conditions… This latter work provides a lot of information, such as the aerosol optical thickness obviously drives the uncertainties of the retrieval, the absorption and the volume concentration of the fine aerosol mode have an important impact as well…

Water wells on St. Thomas, U.S. Virgin Islands

USGS Publications Warehouse

Steiger, J.I.; Kessler, Richard

1993-01-01

This report is a compilation of well-inventory data collected from December 1989 to December 1990 on St. Thomas, U.S. Virgin Islands from 367 wells. The report includes well locations on 1982, 7.5 minute series, USGS topographic maps, which are published to scale, and tables of selected well data. The report includes the following well information; well name, U.S. Geological Survey Ground Water Site Identification number, use of water, year well constructed, reported depth of well, measured depth of well, casing diameter, type of well finish and finish interval, land surface altitude of well, depth to water below land surface, date water level measured, and well yield. (USGS)

Laser pulse bidirectional reflectance from CALIPSO mission

NASA Astrophysics Data System (ADS)

Lu, Xiaomei; Hu, Yongxiang; Yang, Yuekui; Vaughan, Mark; Liu, Zhaoyan; Rodier, Sharon; Hunt, William; Powell, Kathy; Lucker, Patricia; Trepte, Charles

2018-06-01

This paper presents an innovative retrieval method that translates the CALIOP land surface laser pulse returns into the surface bidirectional reflectance. To better analyze the surface returns, the CALIOP receiver impulse response and the downlinked samples' distribution at 30 m vertical resolution are discussed. The saturated laser pulse magnitudes from snow and ice surfaces are recovered based on information extracted from the tail end of the surface signal. The retrieved snow surface bidirectional reflectance is compared with reflectance from both CALIOP cloud-covered regions and MODIS BRDF-albedo model parameters. In addition to the surface bidirectional reflectance, the column top-of-atmosphere bidirectional reflectances are calculated from the CALIOP lidar background data and compared with the bidirectional reflectances derived from WFC radiance measurements. The retrieved CALIOP surface bidirectional reflectance and column top-of-atmosphere bidirectional reflectance results provide unique information to complement existing MODIS standard data products and are expected to have valuable applications for modelers.

Integration of environmental simulation models with satellite remote sensing and geographic information systems technologies: case studies

USGS Publications Warehouse

Steyaert, Louis T.; Loveland, Thomas R.; Brown, Jesslyn F.; Reed, Bradley C.

1993-01-01

Environmental modelers are testing and evaluating a prototype land cover characteristics database for the conterminous United States developed by the EROS Data Center of the U.S. Geological Survey and the University of Nebraska Center for Advanced Land Management Information Technologies. This database was developed from multi temporal, 1-kilometer advanced very high resolution radiometer (AVHRR) data for 1990 and various ancillary data sets such as elevation, ecological regions, and selected climatic normals. Several case studies using this database were analyzed to illustrate the integration of satellite remote sensing and geographic information systems technologies with land-atmosphere interactions models at a variety of spatial and temporal scales. The case studies are representative of contemporary environmental simulation modeling at local to regional levels in global change research, land and water resource management, and environmental simulation modeling at local to regional levels in global change research, land and water resource management and environmental risk assessment. The case studies feature land surface parameterizations for atmospheric mesoscale and global climate models; biogenic-hydrocarbons emissions models; distributed parameter watershed and other hydrological models; and various ecological models such as ecosystem, dynamics, biogeochemical cycles, ecotone variability, and equilibrium vegetation models. The case studies demonstrate the important of multi temporal AVHRR data to develop to develop and maintain a flexible, near-realtime land cover characteristics database. Moreover, such a flexible database is needed to derive various vegetation classification schemes, to aggregate data for nested models, to develop remote sensing algorithms, and to provide data on dynamic landscape characteristics. The case studies illustrate how such a database supports research on spatial heterogeneity, land use, sensitivity analysis, and scaling issues involving regional extrapolations and parameterizations of dynamic land processes within simulation models.

The Generation of Near-Real Time Data Products for MODIS

NASA Astrophysics Data System (ADS)

Teague, M.; Schmaltz, J. E.; Ilavajhala, S.; Ye, G.; Masuoka, E.; Murphy, K. J.; Michael, K.

2010-12-01

The GSFC Terrestrial Information Systems Branch (614.5) operate the Land and Atmospheres Near-real-time Capability for EOS (LANCE-MODIS) system. Other LANCE elements include -AIRS, -MLS, -OMI, and -AMSR-E. LANCE-MODIS incorporates the former Rapid Response system and will, in early 2011, include the Fire Information for Resource Management System (FIRMS). The purpose of LANCE is to provide applications users with a variety of products on a near-real time basis. The LANCE-MODIS data products include Level 1 (L1), L2 fire, snow, sea ice, cloud mask/profiles, aerosols, clouds, land surface reflectance, land surface temperature, and L2G and L3 gridded, daily, land surface reflectance products. Data are available either by ftp access (pull) or by subscription (push) and the L1 and L2 data products are available within an average of 2.5 hours of the observation time. The use of ancillary data products input to the standard science algorithms has been modified in order to obtain these latencies. The resulting products have been approved for applications use by the MODIS Science Team. The http://lance.nasa.gov site provides registration information and extensive information concerning the MODIS data products and imagery including a comparison between the LANCE-MODIS and the standard science-quality products generated by the MODAPS system. The LANCE-MODIS system includes a variety of tools that enable users to manipulate the data products including: parameter, band, and geographic subsetting, re-projection, mosaicing, and generation of data in the GeoTIFF format. In most instances the data resulting from use of these tools has a latency of less than 3 hours. Access to these tools is available through a Web Coverage Service. A Google Earth/Web Mapping Service is available to access image products. LANCE-MODIS supports a wide variety of applications users in civilian, military, and foreign agencies as well as universities and the private sector. Examples of applications are: Flood Mapping, Famine relief, Food and Agriculture, Hazards and Disasters, and Weather.

Generating a Long-Term Land Data Record from the AVHRR and MODIS Instruments

NASA Technical Reports Server (NTRS)

Pedelty, Jeffrey; Devadiga, Sadashiva; Masuoka, Edward; Brown, Molly; Pinzon, Jorge; Tucker, Compton; Vermote, Eric; Prince, Stephen; Nagol, Jyotheshwar; Justice, Christopher;

Next generation of global land cover characterization, mapping, and monitoring

USGS Publications Warehouse

Giri, Chandra; Pengra, Bruce; Long, J.; Loveland, Thomas R.

2013-01-01

Land cover change is increasingly affecting the biophysics, biogeochemistry, and biogeography of the Earth's surface and the atmosphere, with far-reaching consequences to human well-being. However, our scientific understanding of the distribution and dynamics of land cover and land cover change (LCLCC) is limited. Previous global land cover assessments performed using coarse spatial resolution (300 m–1 km) satellite data did not provide enough thematic detail or change information for global change studies and for resource management. High resolution (∼30 m) land cover characterization and monitoring is needed that permits detection of land change at the scale of most human activity and offers the increased flexibility of environmental model parameterization needed for global change studies. However, there are a number of challenges to overcome before producing such data sets including unavailability of consistent global coverage of satellite data, sheer volume of data, unavailability of timely and accurate training and validation data, difficulties in preparing image mosaics, and high performance computing requirements. Integration of remote sensing and information technology is needed for process automation and high-performance computing needs. Recent developments in these areas have created an opportunity for operational high resolution land cover mapping, and monitoring of the world. Here, we report and discuss these advancements and opportunities in producing the next generations of global land cover characterization, mapping, and monitoring at 30-m spatial resolution primarily in the context of United States, Group on Earth Observations Global 30 m land cover initiative (UGLC).

Surface Landing Site Weather Analysis for NASA's Constellation Program

NASA Technical Reports Server (NTRS)

Altino, Karen M.; Burns, K. L.

2008-01-01

Weather information is an important asset for NASA's Constellation Program in developing the next generation space transportation system to fly to the International Space Station, the Moon and, eventually, to Mars. Weather conditions can affect vehicle safety and performance during multiple mission phases ranging from pre-launch ground processing of the Ares vehicles to landing and recovery operations, including all potential abort scenarios. Meteorological analysis is art important contributor, not only to the development and verification of system design requirements but also to mission planning and active ground operations. Of particular interest are the surface weather conditions at both nominal and abort landing sites for the manned Orion capsule. Weather parameters such as wind, rain, and fog all play critical roles in the safe landing of the vehicle and subsequent crew and vehicle recovery. The Marshall Space Flight Center (MSFC) Natural Environments Branch has been tasked by the Constellation Program with defining the natural environments at potential landing zones. This paper wiI1 describe the methodology used for data collection and quality control, detail the types of analyses performed, and provide a sample of the results that cab be obtained.

A Comparison of Methods for a Priori Bias Correction in Soil Moisture Data Assimilation

NASA Technical Reports Server (NTRS)

Kumar, Sujay V.; Reichle, Rolf H.; Harrison, Kenneth W.; Peters-Lidard, Christa D.; Yatheendradas, Soni; Santanello, Joseph A.

2011-01-01

Data assimilation is being increasingly used to merge remotely sensed land surface variables such as soil moisture, snow and skin temperature with estimates from land models. Its success, however, depends on unbiased model predictions and unbiased observations. Here, a suite of continental-scale, synthetic soil moisture assimilation experiments is used to compare two approaches that address typical biases in soil moisture prior to data assimilation: (i) parameter estimation to calibrate the land model to the climatology of the soil moisture observations, and (ii) scaling of the observations to the model s soil moisture climatology. To enable this research, an optimization infrastructure was added to the NASA Land Information System (LIS) that includes gradient-based optimization methods and global, heuristic search algorithms. The land model calibration eliminates the bias but does not necessarily result in more realistic model parameters. Nevertheless, the experiments confirm that model calibration yields assimilation estimates of surface and root zone soil moisture that are as skillful as those obtained through scaling of the observations to the model s climatology. Analysis of innovation diagnostics underlines the importance of addressing bias in soil moisture assimilation and confirms that both approaches adequately address the issue.

Responding to Harmful Algal Blooms in Wyoming and on Tribal Lands in EPA Region 8

EPA Pesticide Factsheets

The Harmful Algal Blooms – Special Sampling and Response Actions webpage contains information about Background on Harmful Algae in Surface Waters and What to Do if Your System Has Indicators of an Algal Bloom.

Impact of Land Surface Initialization Approach on Subseasonal Forecast Skill: a Regional Analysis in the Southern Hemisphere

NASA Technical Reports Server (NTRS)

Hirsch, Annette L.; Kala, Jatin; Pitman, Andy J.; Carouge, Claire; Evans, Jason P.; Haverd, Vanessa; Mocko, David

2014-01-01

The authors use a sophisticated coupled land-atmosphere modeling system for a Southern Hemisphere subdomain centered over southeastern Australia to evaluate differences in simulation skill from two different land surface initialization approaches. The first approach uses equilibrated land surface states obtained from offline simulations of the land surface model, and the second uses land surface states obtained from reanalyses. The authors find that land surface initialization using prior offline simulations contribute to relative gains in subseasonal forecast skill. In particular, relative gains in forecast skill for temperature of 10%-20% within the first 30 days of the forecast can be attributed to the land surface initialization method using offline states. For precipitation there is no distinct preference for the land surface initialization method, with limited gains in forecast skill irrespective of the lead time. The authors evaluated the asymmetry between maximum and minimum temperatures and found that maximum temperatures had the largest gains in relative forecast skill, exceeding 20% in some regions. These results were statistically significant at the 98% confidence level at up to 60 days into the forecast period. For minimum temperature, using reanalyses to initialize the land surface contributed to relative gains in forecast skill, reaching 40% in parts of the domain that were statistically significant at the 98% confidence level. The contrasting impact of the land surface initialization method between maximum and minimum temperature was associated with different soil moisture coupling mechanisms. Therefore, land surface initialization from prior offline simulations does improve predictability for temperature, particularly maximum temperature, but with less obvious improvements for precipitation and minimum temperature over southeastern Australia.

A Remote Sensing Approach for Urban Environmental Decision-Making: An Atlanta, Georgia Case Study

NASA Technical Reports Server (NTRS)

Quattrochi, Dale A.; Luvall, Jeffrey C.; Rickman, Douglas L.; Laymon, Charles A.; Estes, Maurice G., Jr.; Howell, Burgess F.; Arnold, James E. (Technical Monitor)

2002-01-01

Unquestionably, urbanization causes tremendous changes in land cover and land use, as well as impacting a host of environmental characteristics. For example, unlike natural surfaces, urban surfaces have very different thermal energy properties whereby they store solar energy throughout the day and continue to release it as heat well after sunset. This effect, known as the 'Urban Heat Island', serves as a catalyst for chemical reactions from vehicular exhaust and industrial activities leading to the deterioration in air quality, especially exacerbating the production of ground level ozone. 'Cool Community' strategies that utilize remote sensing data, are now being implemented as a way to reduce the impacts of the urban heat island and its subsequent environmental impacts. This presentation focuses on how remote sensing data have been used to provide descriptive and quantitative data for characterizing the Atlanta, Georgia metropolitan area - particularly for measuring surface energy fluxes, such as the thermal or "heat" energy that emanates from different land cover types across the Atlanta urban landscape. In turn, this information is useful for developing a better understanding of how the thermal characteristics of the city surface affect the urban heat island phenomena and, ultimately, air quality and other environmental parameters over the Atlanta metropolitan region. Additionally, this paper also provides insight on how remote sensing, with its synoptic approach, can be used to provide urban planners, local, state, and federal government officials, and other decision-makers, as well as the general public, with information to better manage urban areas as sustainable environments.

Benchmarking NLDAS-2 Soil Moisture and Evapotranspiration to Separate Uncertainty Contributions

NASA Technical Reports Server (NTRS)

Nearing, Grey S.; Mocko, David M.; Peters-Lidard, Christa D.; Kumar, Sujay V.; Xia, Youlong

2016-01-01

Model benchmarking allows us to separate uncertainty in model predictions caused 1 by model inputs from uncertainty due to model structural error. We extend this method with a large-sample approach (using data from multiple field sites) to measure prediction uncertainty caused by errors in (i) forcing data, (ii) model parameters, and (iii) model structure, and use it to compare the efficiency of soil moisture state and evapotranspiration flux predictions made by the four land surface models in the North American Land Data Assimilation System Phase 2 (NLDAS-2). Parameters dominated uncertainty in soil moisture estimates and forcing data dominated uncertainty in evapotranspiration estimates; however, the models themselves used only a fraction of the information available to them. This means that there is significant potential to improve all three components of the NLDAS-2 system. In particular, continued work toward refining the parameter maps and look-up tables, the forcing data measurement and processing, and also the land surface models themselves, has potential to result in improved estimates of surface mass and energy balances.

Dryland photoautotrophic soil surface communities endangered by global change

USGS Publications Warehouse

Rodriguez-Caballero, Emilio; Belnap, Jayne; Büdel, Burkhard; Crutzen, Paul J.; Andreae, Meinrat O.; Pöschl, Ulrich; Weber, Bettina

2018-01-01

Photoautotrophic surface communities forming biological soil crusts (biocrusts) are crucial for soil stability as well as water, nutrient and trace gas cycling at regional and global scales. Quantitative information on their global coverage and the environmental factors driving their distribution patterns, however, are not readily available. We use observations and environmental modelling to estimate the global distribution of biocrusts and their response to global change using future projected scenarios. We find that biocrusts currently covering approximately 12% of Earth’s terrestrial surface will decrease by about 25–40% within 65 years due to anthropogenically caused climate change and land-use intensification, responding far more drastically than vascular plants. Our results illustrate that current biocrust occurrence is mainly driven by a combination of precipitation, temperature and land management, and future changes are expected to be affected by land-use and climate change in similar proportion. The predicted loss of biocrusts may substantially reduce the microbial contribution to nitrogen cycling and enhance the emissions of soil dust, which affects the functioning of ecosystems as well as human health and should be considered in the modelling, mitigation and management of global change.

Dryland photoautotrophic soil surface communities endangered by global change

NASA Astrophysics Data System (ADS)

Rodriguez-Caballero, Emilio; Belnap, Jayne; Büdel, Burkhard; Crutzen, Paul J.; Andreae, Meinrat O.; Pöschl, Ulrich; Weber, Bettina

2018-03-01

Photoautotrophic surface communities forming biological soil crusts (biocrusts) are crucial for soil stability as well as water, nutrient and trace gas cycling at regional and global scales. Quantitative information on their global coverage and the environmental factors driving their distribution patterns, however, are not readily available. We use observations and environmental modelling to estimate the global distribution of biocrusts and their response to global change using future projected scenarios. We find that biocrusts currently covering approximately 12% of Earth's terrestrial surface will decrease by about 25-40% within 65 years due to anthropogenically caused climate change and land-use intensification, responding far more drastically than vascular plants. Our results illustrate that current biocrust occurrence is mainly driven by a combination of precipitation, temperature and land management, and future changes are expected to be affected by land-use and climate change in similar proportion. The predicted loss of biocrusts may substantially reduce the microbial contribution to nitrogen cycling and enhance the emissions of soil dust, which affects the functioning of ecosystems as well as human health and should be considered in the modelling, mitigation and management of global change.

Mars Sample Return without Landing on the Surface

NASA Technical Reports Server (NTRS)

Jurewicz, A. J. G.; Jones, Steven M.; Yen, A. S.

2000-01-01

Many in the science community want a Mars sample return in the near future, with the expectation that it will provide in-depth information, significantly beyond what we know from remote sensing, limited in-situ measurements, and work with Martian meteorites. Certainly, return of samples from the Moon resulted in major advances in our understanding of both the geologic history of our planetary satellite, and its relationship to Earth. Similar scientific insights would be expected from analyses of samples returned from Mars. Unfortunately, Mars-lander sample-return missions have been delayed, for the reason that NASA needs more time to review the complexities and risks associated with that type of mission. A traditional sample return entails a complex transfer-chain, including landing, collection, launch, rendezvous, and the return to Earth, as well as an evaluation of potential biological hazards involved with bringing pristine Martian organics to Earth. There are, however, means of returning scientifically-rich samples from Mars without landing on the surface. This paper discusses an approach for returning intact samples of surface dust, based on known instrument technology, without using an actual Martian lander.

Benchmarking NLDAS-2 Soil Moisture and Evapotranspiration to Separate Uncertainty Contributions

PubMed Central

Nearing, Grey S.; Mocko, David M.; Peters-Lidard, Christa D.; Kumar, Sujay V.; Xia, Youlong

2018-01-01

Model benchmarking allows us to separate uncertainty in model predictions caused by model inputs from uncertainty due to model structural error. We extend this method with a “large-sample” approach (using data from multiple field sites) to measure prediction uncertainty caused by errors in (i) forcing data, (ii) model parameters, and (iii) model structure, and use it to compare the efficiency of soil moisture state and evapotranspiration flux predictions made by the four land surface models in the North American Land Data Assimilation System Phase 2 (NLDAS-2). Parameters dominated uncertainty in soil moisture estimates and forcing data dominated uncertainty in evapotranspiration estimates; however, the models themselves used only a fraction of the information available to them. This means that there is significant potential to improve all three components of the NLDAS-2 system. In particular, continued work toward refining the parameter maps and look-up tables, the forcing data measurement and processing, and also the land surface models themselves, has potential to result in improved estimates of surface mass and energy balances. PMID:29697706

Benchmarking NLDAS-2 Soil Moisture and Evapotranspiration to Separate Uncertainty Contributions.

PubMed

Nearing, Grey S; Mocko, David M; Peters-Lidard, Christa D; Kumar, Sujay V; Xia, Youlong

2016-03-01

Model benchmarking allows us to separate uncertainty in model predictions caused by model inputs from uncertainty due to model structural error. We extend this method with a "large-sample" approach (using data from multiple field sites) to measure prediction uncertainty caused by errors in (i) forcing data, (ii) model parameters, and (iii) model structure, and use it to compare the efficiency of soil moisture state and evapotranspiration flux predictions made by the four land surface models in the North American Land Data Assimilation System Phase 2 (NLDAS-2). Parameters dominated uncertainty in soil moisture estimates and forcing data dominated uncertainty in evapotranspiration estimates; however, the models themselves used only a fraction of the information available to them. This means that there is significant potential to improve all three components of the NLDAS-2 system. In particular, continued work toward refining the parameter maps and look-up tables, the forcing data measurement and processing, and also the land surface models themselves, has potential to result in improved estimates of surface mass and energy balances.

South Florida Everglades: satellite image map

USGS Publications Warehouse

Jones, John W.; Thomas, Jean-Claude; Desmond, G.B.

2001-01-01

These satellite image maps are one product of the USGS Land Characteristics from Remote Sensing project, funded through the USGS Place-Based Studies Program (http://access.usgs.gov/) with support from the Everglades National Park (http://www.nps.gov/ever/). The objective of this project is to develop and apply innovative remote sensing and geographic information system techniques to map the distribution of vegetation, vegetation characteristics, and related hydrologic variables through space and over time. The mapping and description of vegetation characteristics and their variations are necessary to accurately simulate surface hydrology and other surface processes in South Florida and to monitor land surface changes. As part of this research, data from many airborne and satellite imaging systems have been georeferenced and processed to facilitate data fusion and analysis. These image maps were created using image fusion techniques developed as part of this project.

An Integrated High Resolution Hydrometeorological Modeling Testbed using LIS and WRF

NASA Technical Reports Server (NTRS)

Kumar, Sujay V.; Peters-Lidard, Christa D.; Eastman, Joseph L.; Tao, Wei-Kuo

2007-01-01

Scientists have made great strides in modeling physical processes that represent various weather and climate phenomena. Many modeling systems that represent the major earth system components (the atmosphere, land surface, and ocean) have been developed over the years. However, developing advanced Earth system applications that integrates these independently developed modeling systems have remained a daunting task due to limitations in computer hardware and software. Recently, efforts such as the Earth System Modeling Ramework (ESMF) and Assistance for Land Modeling Activities (ALMA) have focused on developing standards, guidelines, and computational support for coupling earth system model components. In this article, the development of a coupled land-atmosphere hydrometeorological modeling system that adopts these community interoperability standards, is described. The land component is represented by the Land Information System (LIS), developed by scientists at the NASA Goddard Space Flight Center. The Weather Research and Forecasting (WRF) model, a mesoscale numerical weather prediction system, is used as the atmospheric component. LIS includes several community land surface models that can be executed at spatial scales as fine as 1km. The data management capabilities in LIS enable the direct use of high resolution satellite and observation data for modeling. Similarly, WRF includes several parameterizations and schemes for modeling radiation, microphysics, PBL and other processes. Thus the integrated LIS-WRF system facilitates several multi-model studies of land-atmosphere coupling that can be used to advance earth system studies.

Application-ready expedited MODIS data for operational land surface monitoring of vegetation condition

USGS Publications Warehouse

Brown, Jesslyn; Howard, Daniel M.; Wylie, Bruce K.; Friesz, Aaron M.; Ji, Lei; Gacke, Carolyn

2015-01-01

Monitoring systems benefit from high temporal frequency image data collected from the Moderate Resolution Imaging Spectroradiometer (MODIS) system. Because of near-daily global coverage, MODIS data are beneficial to applications that require timely information about vegetation condition related to drought, flooding, or fire danger. Rapid satellite data streams in operational applications have clear benefits for monitoring vegetation, especially when information can be delivered as fast as changing surface conditions. An “expedited” processing system called “eMODIS” operated by the U.S. Geological Survey provides rapid MODIS surface reflectance data to operational applications in less than 24 h offering tailored, consistently-processed information products that complement standard MODIS products. We assessed eMODIS quality and consistency by comparing to standard MODIS data. Only land data with known high quality were analyzed in a central U.S. study area. When compared to standard MODIS (MOD/MYD09Q1), the eMODIS Normalized Difference Vegetation Index (NDVI) maintained a strong, significant relationship to standard MODIS NDVI, whether from morning (Terra) or afternoon (Aqua) orbits. The Aqua eMODIS data were more prone to noise than the Terra data, likely due to differences in the internal cloud mask used in MOD/MYD09Q1 or compositing rules. Post-processing temporal smoothing decreased noise in eMODIS data.

Boulder Distributions at Legacy Landing Sites: Assessing Regolith Production Rates and Landing Site Hazards

NASA Technical Reports Server (NTRS)

Watkins, R. N.; Jolliff, B. L.; Lawrence, S. J.; Hayne, P. O.; Ghent, R. R.

2017-01-01

Understanding how the distribution of boulders on the lunar surface changes over time is key to understanding small-scale erosion processes and the rate at which rocks become regolith. Boulders degrade over time, primarily as a result of micrometeorite bombardment so their residence time at the surface can inform the rate at which rocks become regolith or become buried within regolith. Because of the gradual degradation of exposed boulders, we expect that the boulder population around an impact crater will decrease as crater age increases. Boulder distributions around craters of varying ages are needed to understand regolith production rates, and Lunar Reconnaissance Orbiter Camera (LROC) Narrow Angle Camera (NAC) images provide one of the best tools for conducting these studies. Using NAC images to assess how the distribution of boulders varies as a function of crater age provides key constraints for boulder erosion processes. Boulders also represent a potential hazard that must be addressed in the planning of future lunar landings. A boulder under a landing leg can contribute to deck tilt, and boulders can damage spacecraft during landing. Using orbital data to characterize boulder populations at locations where landers have safely touched down (Apollo, Luna, Surveyor, Chang'e-3) provides validation for landed mission hazard avoidance planning. Additionally, counting boulders at legacy landing sites is useful because: 1) LROC has extensive coverage of these sites at high resolutions (approximately 0.5 meters per pixel). 2) Returned samples from craters at these sites have been radiometrically dated, allowing assessment of how boulder distributions vary as a function of crater age. 3) Surface photos at these sites can be used to correlate with remote sensing measurements.

A hydrologic network supporting spatially referenced regression modeling in the Chesapeake Bay watershed

USGS Publications Warehouse

Brakebill, J.W.; Preston, S.D.

2003-01-01

The U.S. Geological Survey has developed a methodology for statistically relating nutrient sources and land-surface characteristics to nutrient loads of streams. The methodology is referred to as SPAtially Referenced Regressions On Watershed attributes (SPARROW), and relates measured stream nutrient loads to nutrient sources using nonlinear statistical regression models. A spatially detailed digital hydrologic network of stream reaches, stream-reach characteristics such as mean streamflow, water velocity, reach length, and travel time, and their associated watersheds supports the regression models. This network serves as the primary framework for spatially referencing potential nutrient source information such as atmospheric deposition, septic systems, point-sources, land use, land cover, and agricultural sources and land-surface characteristics such as land use, land cover, average-annual precipitation and temperature, slope, and soil permeability. In the Chesapeake Bay watershed that covers parts of Delaware, Maryland, Pennsylvania, New York, Virginia, West Virginia, and Washington D.C., SPARROW was used to generate models estimating loads of total nitrogen and total phosphorus representing 1987 and 1992 land-surface conditions. The 1987 models used a hydrologic network derived from an enhanced version of the U.S. Environmental Protection Agency's digital River Reach File, and course resolution Digital Elevation Models (DEMs). A new hydrologic network was created to support the 1992 models by generating stream reaches representing surface-water pathways defined by flow direction and flow accumulation algorithms from higher resolution DEMs. On a reach-by-reach basis, stream reach characteristics essential to the modeling were transferred to the newly generated pathways or reaches from the enhanced River Reach File used to support the 1987 models. To complete the new network, watersheds for each reach were generated using the direction of surface-water flow derived from the DEMs. This network improves upon existing digital stream data by increasing the level of spatial detail and providing consistency between the reach locations and topography. The hydrologic network also aids in illustrating the spatial patterns of predicted nutrient loads and sources contributed locally to each stream, and the percentages of nutrient load that reach Chesapeake Bay.

Probabilistic Assessment of Soil Moisture using C-band Quad-polarized Remote Sensing Data from RISAT1

NASA Astrophysics Data System (ADS)

Pal, Manali; Suman, Mayank; Das, Sarit Kumar; Maity, Rajib

2017-04-01

Information on spatio-temporal distribution of surface Soil Moisture Content (SMC) is essential in several hydrological, meteorological and agricultural applications. There has been increasing importance of microwave active remote sensing data for large-scale estimation of surface SMC because of its ability to monitor spatial and temporal variation of surface SMC at regional, continental and global scale at a reasonably fine spatial and temporal resolution. The use of Synthetic Aperture Radar (SAR) is highly potential for catchment-scale applications due to high spatial resolution (˜10-20 m) both for vegetated and bare soil surface as well as because of its all-weather and day and night characteristics. However, one prime disadvantage of SAR is that their signal is subjective to SMC along with Land Use Land Cover (LULC) and surface roughness conditions, making the retrieval of SMC from SAR data an "ill-posed" problem. Moreover, the quantification of uncertainty due to inappropriate surface roughness characterization, soil texture, inversion techniques etc. even in the latest established retrieval methods, is little explored. This paper reports a recently developed method to estimate the surface SMC with probabilistic assessment of uncertainty associated with the estimation (Pal et al., 2016). Quad-polarized SAR data from Radar Imaging Satellite1 (RISAT1), launched in 2012 by Indian Space Research Organization (ISRO) and information on LULC regarding bareland and vegetated land (<30 cm height) are used in estimation using the potential of multivariate probabilistic assessment through copulas. The salient features of the study are: 1) development of a combined index to understand the role of all the quad-polarized backscattering coefficients and soil texture information in SMC estimation; 2) applicability of the model for different incidence angles using normalized incidence angle theory proposed by Zibri et al. (2005); and 3) assessment of uncertainty range of the estimated SMC. Supervised Principal Component Analysis (SPCA) is used for development of combined index and Frank copula is found to be the best-fit copula. The developed model is validated with the field soil moisture values over 334 monitoring points within the study area and used for development of a soil moisture map. While the performance is promising, the model is applicable only for bare and vegetated land. References: Pal, M., Maity, R., Suman, M., Das, S.K., Patel, P., and Srivastava, H.S., (2016). "Satellite-Based Probabilistic Assessment of Soil Moisture Using C-Band Quad-Polarized RISAT1 Data." IEEE Transactions on Geoscience and Remote Sensing, In Press, doi:10.1109/TGRS.2016.2623378. Zribi, M., Baghdadi, N., Holah, N., and Fafin, O., (2005)."New methodology for soil surface moisture estimation and its application to ENVISAT-ASAR multi-incidence data inversion." Remote Sensing of Environment, vol. 96, nos. 3-4, pp. 485-496.

Flood Extent Delineation by Thresholding Sentinel-1 SAR Imagery Based on Ancillary Land Cover Information

NASA Astrophysics Data System (ADS)

Liang, J.; Liu, D.

2017-12-01

Emergency responses to floods require timely information on water extents that can be produced by satellite-based remote sensing. As SAR image can be acquired in adverse illumination and weather conditions, it is particularly suitable for delineating water extent during a flood event. Thresholding SAR imagery is one of the most widely used approaches to delineate water extent. However, most studies apply only one threshold to separate water and dry land without considering the complexity and variability of different dry land surface types in an image. This paper proposes a new thresholding method for SAR image to delineate water from other different land cover types. A probability distribution of SAR backscatter intensity is fitted for each land cover type including water before a flood event and the intersection between two distributions is regarded as a threshold to classify the two. To extract water, a set of thresholds are applied to several pairs of land cover types—water and urban or water and forest. The subsets are merged to form the water distribution for the SAR image during or after the flooding. Experiments show that this land cover based thresholding approach outperformed the traditional single thresholding by about 5% to 15%. This method has great application potential with the broadly acceptance of the thresholding based methods and availability of land cover data, especially for heterogeneous regions.

Upper-soil moisture inter-comparison from SMOS's products and land surface models over the Iberian Peninsula

NASA Astrophysics Data System (ADS)

Polcher, Jan; Barella-Ortiz, Anaïs; Aires, Filipe; Balsamo, Gianpaolo; Gelati, Emiliano; Rodríguez-Fernández, Nemesio

2015-04-01

Soil moisture is a key state variable of the hydrological cycle. It conditions runoff, infiltration and evaporation over continental surfaces, and is key for forecasting droughts and floods. It plays thus an important role in surface-atmosphere interactions. Surface Soil Moisture (SSM) can be measured by in situ measurements, by satellite observations or modelled using land surface models. As a complementary tool, data assimilation can be used to combine both modelling and satellite observations. The work presented here is an inter-comparison of retrieved and modelled SSM data, for the 2010 - 2012 period, over the Iberian Peninsula. The region has been chosen because its vegetation cover is not very dense and includes strong contrasts in the rainfall regimes and thus a diversity of behaviours for SSM. Furthermore this semi-arid region is strongly dependent on a good management of its water resources. Satellite observations correspond to the Soil Moisture and Ocean Salinity (SMOS) retrievals: the L2 product from an optimal interpolation retrieval, and 3 other products using Neural Network retrievals with different input information: SMOS time indexes, purely SMOS data, or addition of the European Advanced Scaterometer (ASCAT) backscattering, and the Moderate-Resolution Imaging Spectrometer (MODIS) surface temperature information. The modelled soil moistures have been taken from the ORCHIDEE (ORganising Carbon and Hydrology In Dynamic EcosystEms) and the HTESSEL (Hydrology-Tiled ECMWF Scheme for Surface Exchanges over Land) land surface models. Both models are forced with the same atmospheric conditions (as part of the Earth2Observe FP7 project) over the period but they represent the surface soil moisture with very different degrees of complexity. ORCHIDEE has 5 levels in the top 5 centimetres of soil while in HTESSEL this variable is part of the top soil moisture level. The two types of SMOS retrievals are compared to the model outputs in their spatial and temporal characteristics. The comparison with the model helps to identify which retrieval configuration is most consistent with our understanding of surface soil moisture in this region. In particular we have determined how each of the soil moisture products is related to the spatio-temporal variations of rainfall. In large parts of the Iberian Peninsula the co-variance of remote sensed SSM and rainfall is consistent with that of the models. But for some regions questions are raised. The variability of SSM observed by SMOS in the North West of the Iberian Peninsula is similar to that of rainfall, at least this relation of SSM and rainfall is closer than suggested by the two models.

Assimilation of SMOS Retrievals in the Land Information System

NASA Technical Reports Server (NTRS)

Blankenship, Clay B.; Case, Jonathan L.; Zavodsky, Bradley T.; Crosson, William L.

2016-01-01

The Soil Moisture and Ocean Salinity (SMOS) satellite provides retrievals of soil moisture in the upper 5 cm with a 30-50 km resolution and a mission accuracy requirement of 0.04 cm(sub 3 cm(sub -3). These observations can be used to improve land surface model soil moisture states through data assimilation. In this paper, SMOS soil moisture retrievals are assimilated into the Noah land surface model via an Ensemble Kalman Filter within the NASA Land Information System. Bias correction is implemented using Cumulative Distribution Function (CDF) matching, with points aggregated by either land cover or soil type to reduce sampling error in generating the CDFs. An experiment was run for the warm season of 2011 to test SMOS data assimilation and to compare assimilation methods. Verification of soil moisture analyses in the 0-10 cm upper layer and root zone (0-1 m) was conducted using in situ measurements from several observing networks in the central and southeastern United States. This experiment showed that SMOS data assimilation significantly increased the anomaly correlation of Noah soil moisture with station measurements from 0.45 to 0.57 in the 0-10 cm layer. Time series at specific stations demonstrate the ability of SMOS DA to increase the dynamic range of soil moisture in a manner consistent with station measurements. Among the bias correction methods, the correction based on soil type performed best at bias reduction but also reduced correlations. The vegetation-based correction did not produce any significant differences compared to using a simple uniform correction curve.

Assimilation of SMOS Retrievals in the Land Information System

PubMed Central

Blankenship, Clay B.; Case, Jonathan L.; Zavodsky, Bradley T.; Crosson, William L.

2018-01-01

The Soil Moisture and Ocean Salinity (SMOS) satellite provides retrievals of soil moisture in the upper 5 cm with a 30-50 km resolution and a mission accuracy requirement of 0.04 cm3 cm−3. These observations can be used to improve land surface model soil moisture states through data assimilation. In this paper, SMOS soil moisture retrievals are assimilated into the Noah land surface model via an Ensemble Kalman Filter within the NASA Land Information System. Bias correction is implemented using Cumulative Distribution Function (CDF) matching, with points aggregated by either land cover or soil type to reduce sampling error in generating the CDFs. An experiment was run for the warm season of 2011 to test SMOS data assimilation and to compare assimilation methods. Verification of soil moisture analyses in the 0-10 cm upper layer and root zone (0-1 m) was conducted using in situ measurements from several observing networks in the central and southeastern United States. This experiment showed that SMOS data assimilation significantly increased the anomaly correlation of Noah soil moisture with station measurements from 0.45 to 0.57 in the 0-10 cm layer. Time series at specific stations demonstrate the ability of SMOS DA to increase the dynamic range of soil moisture in a manner consistent with station measurements. Among the bias correction methods, the correction based on soil type performed best at bias reduction but also reduced correlations. The vegetation-based correction did not produce any significant differences compared to using a simple uniform correction curve. PMID:29367795

Mapping Urban Ecosystem Services Using High Resolution Aerial Photography

NASA Astrophysics Data System (ADS)

Pilant, A. N.; Neale, A.; Wilhelm, D.

2010-12-01

Ecosystem services (ES) are the many life-sustaining benefits we receive from nature: e.g., clean air and water, food and fiber, cultural-aesthetic-recreational benefits, pollination and flood control. The ES concept is emerging as a means of integrating complex environmental and economic information to support informed environmental decision making. The US EPA is developing a web-based National Atlas of Ecosystem Services, with a component for urban ecosystems. Currently, the only wall-to-wall, national scale land cover data suitable for this analysis is the National Land Cover Data (NLCD) at 30 m spatial resolution with 5 and 10 year updates. However, aerial photography is acquired at higher spatial resolution (0.5-3 m) and more frequently (1-5 years, typically) for most urban areas. Land cover was mapped in Raleigh, NC using freely available USDA National Agricultural Imagery Program (NAIP) with 1 m ground sample distance to test the suitability of aerial photography for urban ES analysis. Automated feature extraction techniques were used to extract five land cover classes, and an accuracy assessment was performed using standard techniques. Results will be presented that demonstrate applications to mapping ES in urban environments: greenways, corridors, fragmentation, habitat, impervious surfaces, dark and light pavement (urban heat island). Automated feature extraction results mapped over NAIP color aerial photograph. At this scale, we can look at land cover and related ecosystem services at the 2-10 m scale. Small features such as individual trees and sidewalks are visible and mappable. Classified aerial photo of Downtown Raleigh NC Red: impervious surface Dark Green: trees Light Green: grass Tan: soil

The Urban Heat Island Impact in Consideration of Spatial Pattern of Urban Landscape and Structure

NASA Astrophysics Data System (ADS)

Kim, J.; Lee, D. K.; Jeong, W.; Sung, S.; Park, J.

2015-12-01

Preceding study has established a clear relationship between land surface temperature and area of land covers. However, only few studies have specifically examined the effects of spatial patterns of land covers and urban structure. To examine how much the local climate is affected by the spatial pattern in highly urbanized city, we investigated the correlation between land surface temperature and spatial patterns of land covers. In the analysis of correlation, we categorized urban structure to four different land uses: Apartment residential area, low rise residential area, industrial area and central business district. Through this study, we aims to examine the types of residential structure and land cover pattern for reducing urban heat island and sustainable development. Based on land surface temperature, we investigated the phenomenon of urban heat island through using the data of remote sensing. This study focused on Daegu in Korea. This city, one of the hottest city in Korea has basin form. We used high-resolution land cover data and land surface temperature by using Landsat8 satellite image to examine 100 randomly selected sample sites of 884.15km2 (1)In each land use, we quantified several landscape-levels and class-level landscape metrics for the sample study sites. (2)In addition, we measured the land surface temperature in 3 year hot summer seasons (July to September). Then, we investigated the pattern of land surface temperature for each land use through Ecognition package. (3)We deducted the Pearson correlation coefficients between land surface temperature and each landscape metrics. (4)We analyzed the variance among the four land uses. (5)Using linear regression, we determined land surface temperature model for each land use. (6)Through this analysis, we aims to examine the best pattern of land cover and artificial structure for reducing urban heat island effect in highly urbanized city. The results of linear regression showed that proportional land cover of grass, tree, water and impervious surfaces well explained the temperature in apartment residential areas. In contrast, the changes in the pattern of water, grass, tree and impervious surfaces were the best to determine the temperature in low rise residential area, central business district and industrial area.

Identification and delineation of areas flood hazard using high accuracy of DEM data

NASA Astrophysics Data System (ADS)

Riadi, B.; Barus, B.; Widiatmaka; Yanuar, M. J. P.; Pramudya, B.

2018-05-01

Flood incidents that often occur in Karawang regency need to be mitigated. These expectations exist on technologies that can predict, anticipate and reduce disaster risks. Flood modeling techniques using Digital Elevation Model (DEM) data can be applied in mitigation activities. High accuracy DEM data used in modeling, will result in better flooding flood models. The result of high accuracy DEM data processing will yield information about surface morphology which can be used to identify indication of flood hazard area. The purpose of this study was to identify and describe flood hazard areas by identifying wetland areas using DEM data and Landsat-8 images. TerraSAR-X high-resolution data is used to detect wetlands from landscapes, while land cover is identified by Landsat image data. The Topography Wetness Index (TWI) method is used to detect and identify wetland areas with basic DEM data, while for land cover analysis using Tasseled Cap Transformation (TCT) method. The result of TWI modeling yields information about potential land of flood. Overlay TWI map with land cover map that produces information that in Karawang regency the most vulnerable areas occur flooding in rice fields. The spatial accuracy of the flood hazard area in this study was 87%.

The Synergistic Use of NASA's A-Train Observations to Characterize the Planetary Boundary Layer and Enable Improved Understanding and Prediction of Land-Atmosphere Interactions

NASA Astrophysics Data System (ADS)

Zavodsky, B.; Santanello, J. A.; Friedl, M. A.; Susskind, J.; Palm, S. P.

2010-12-01

The planetary boundary layer (PBL) serves as a short-term memory of land-atmosphere (L-A) interactions through the diurnal integration of surface fluxes and subsequent evolution of PBL fluxes and states. Recent advances in satellite remote sensing offer the ability to monitor PBL and land surface properties at increasingly high spatial and temporal resolutions and, consequently, have the potential to provide valuable information on the terrestrial energy and water cycle across a range of scales. In this study, we evaluate the retrieval of PBL structure and temperature and moisture properties from measurements made by NASA's Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO), Moderate Resolution Imaging Spectroradiometer (MODIS) , and Atmospheric Infrared Sounder (AIRS) instruments aboard the 'A-Train' constellation. The global coverage of these sensors greatly improves upon the coarse network of synoptic radiosonde and intermittent satellite and ground remote sensing currently available, and combining the high vertical and spectral resolution of these sensors allows for PBL retrievals to be evaluated in the context of their relationship with the land surface. Results include an evaluation of CALIPSO, MODIS, and AIRS temperature and humidity retrievals using radiosonde data, focusing on how well PBL properties (e.g. PBL height, temperature, humidity, and stability) can be discerned from each sensor under a range of conditions. Overall, this research is timely in assessing the potential for merging complimentary information from independent sensors, and provides a unique opportunity to evaluate and apply NASA data to answer fundamental questions regarding observation, understanding, and prediction of L-A interactions and coupling.

Quantifying the Components of Impervious Surfaces

USGS Publications Warehouse

Tilley, Janet S.; Slonecker, E. Terrence

2006-01-01

This study's objectives were to (1) determine the relative contribution of impervious surface individual components by collecting digital information from high-resolution imagery, 1-meter or better; and to (2) determine which of the more advanced techniques, such as spectral unmixing or the application of coefficients to land use or land cover data, was the most suitable method that could be used by State and local governments as well as Federal agencies to efficiently measure the imperviousness in any given watershed or area of interest. The components of impervious surfaces, combined from all the watersheds and time periods from objective one were the following: buildings 29.2-percent, roads 28.3-percent, parking lots 24.6-percent; with the remaining three totaling 14-percent - driveways, sidewalks, and other, where other were any other features that were not contained within the first five. Results from objective two were spectral unmixing techniques will ultimately be the most efficient method of determining imperviousness, but are not yet accurate enough as it is critical to achieve accuracy better than 10-percent of the truth, of which the method is not consistently accomplishing as observed in this study. Of the three techniques in coefficient application tested, land use coefficient application was not practical, while if the last two methods, coefficients applied to land cover data, were merged, their end results could be to within 5-percent or better, of the truth. Until the spectral unmixing technique has been further refined, land cover coefficients should be used, which offer quick results, but not current as they were developed for the 1992 National Land Characteristics Data.

Estimating time and spatial distribution of snow water equivalent in the Hakusan area

NASA Astrophysics Data System (ADS)

Tanaka, K.; Matsui, Y.; Touge, Y.

2015-12-01

In the Sousei program, on-going Japanese research program for risk information on climate change, assessing the impact of climate change on water resources is attempted using the integrated water resources model which consists of land surface model, irrigation model, river routing model, reservoir operation model, and crop growth model. Due to climate change, reduction of snowfall amount, reduction of snow cover and change in snowmelt timing, change in river discharge are of increasing concern. So, the evaluation of snow water amount is crucial for assessing the impact of climate change on water resources in Japan. To validate the snow simulation of the land surface model, time and spatial distribution of the snow water equivalent was estimated using the observed surface meteorological data and RAP (Radar Analysis Precipitation) data. Target area is Hakusan. Hakusan means 'white mountain' in Japanese. Water balance of the Tedori River Dam catchment was checked with daily inflow data. Analyzed runoff was generally well for the period from 2010 to 2012. From the result for 2010-2011 winter, maximum snow water equivalent in the headwater area of the Tedori River dam reached more than 2000mm in early April. On the other hand, due to the underestimation of RAP data, analyzed runoff was under estimated from 2006 to 2009. This underestimation is probably not from the lack of land surface model, but from the quality of input precipitation data. In the original RAP, only the rain gauge data of JMA (Japan Meteorological Agency) were used in the analysis. Recently, other rain gauge data of MLIT (Ministry of Land, Infrastructure, Transport and Tourism) and local government have been added in the analysis. So, the quality of the RAP data especially in the mountain region has been greatly improved. "Reanalysis" of the RAP precipitation is strongly recommended using all the available off-line rain gauges information. High quality precipitation data will contribute to validate hydrological model, satellite based precipitation product, GCM output, etc.

Urban growth in American cities : glimpses of U.S. urbanization

USGS Publications Warehouse

Auch, Roger; Taylor, Janis; Acevedo, William

2004-01-01

The Earth's surface is changing rapidly. Changes are local, regional, national, and even global in scope. Some changes have natural causes, such as earthquakes or drought. Other changes, such as urban expansion, agricultural intensification, resource extraction, and water resources development, are examples of human-induced change that have significant impact upon people, the economy, and resources. The consequences that result from these changes are often dramatic and widespread (Buchanan, Acevedo, and Zirbes, 2002)It is the role of the U.S. Geological Survey (USGS) to provide useful and relevant scientific information both to the agencies within the Department of the Interior and to the Nation in general. In an effort to comply with this task, USGS scientists are assessing the status of, and the trends in, the Nation's land surface. This assessment provides useful information for regional and national land use decisionmaking. This knowledge can be used to deal with issues of significance to the Nation, such as quality-of-life, ecology of urban environments, ecosystem health, ecological integrity, water quality and quantity concerns, resource availability, vulnerability to natural hazards, safeguards to human health, air and land quality, and accessibility to scientific information. Results of these assessments can also be analyzed to reveal rates and trends in land use change. Results from urban growth studies provide a firm foundation for continuing research that explores the consequences of human modification of the landscape.The USGS seeks to illustrate and explain the spatial history of urban growth and corresponding land use change. Scientists are studying urban environments from a regional perspective and a time scale of decades to measure the changes that have occurred in order to help understand the impact of anticipated changes in the future.Within this booklet are pairs of images of selected urbanized regions from across the Nation. These image pairs illustrate the transformation that these areas have undergone over two decades. Specifically, they depict changes in the extent of urban land. Each change pair is composed of one image from the 1970s and one image from the 1990s. Accompanying each image pair is a brief historical geography of factors that helped facilitate major changes that have occurred since the founding of the main city and the consequences and challenges of regional urban growth. The goal of this publication is to provide an illustration of urban change that is easily understood by a broad audience.The images used throughout this booklet were generated from land cover data developed by the USGS. The data sources include the Geographic Information Retrieval and Analysis System (GIRAS) for the 1970s images and the National Land Cover Dataset (NLCD) for the 1990s images. GIRAS digital maps are based on photointerpretations completed in the mid-1970s. The NLCD is a land cover dataset for the conterminous United States based on 1992 Landsat thematic mapper (TM) satellite imagery and supplemental data (fig. 1a and fig. 1b). The USGS distributes both of these land use and land cover digital datasets.The images were developed by using a geographic information system (GIS). The GIRAS and NLCD datasets were used to identify urban land within each region. In the final images all urban areas are shown in red. A shaded-relief map of each region was used to display the topographic context of the red polygon coverage. For all of these images, urban land is defined as areas transformed into a built-up environment for human use. It includes residential areas, commercial and industrial developments, transportation features, and institutions.

Small baseline subsets approach of DInSAR for investigating land surface deformation along the high-speed railway

NASA Astrophysics Data System (ADS)

Rao, Xiong; Tang, Yunwei

2014-11-01

Land surface deformation evidently exists in a newly-built high-speed railway in the southeast of China. In this study, we utilize the Small BAseline Subsets (SBAS)-Differential Synthetic Aperture Radar Interferometry (DInSAR) technique to detect land surface deformation along the railway. In this work, 40 Cosmo-SkyMed satellite images were selected to analyze the spatial distribution and velocity of the deformation in study area. 88 pairs of image with high coherence were firstly chosen with an appropriate threshold. These images were used to deduce the deformation velocity map and the variation in time series. This result can provide information for orbit correctness and ground control point (GCP) selection in the following steps. Then, more pairs of image were selected to tighten the constraint in time dimension, and to improve the final result by decreasing the phase unwrapping error. 171 combinations of SAR pairs were ultimately selected. Reliable GCPs were re-selected according to the previously derived deformation velocity map. Orbital residuals error was rectified using these GCPs, and nonlinear deformation components were estimated. Therefore, a more accurate surface deformation velocity map was produced. Precise geodetic leveling work was implemented in the meantime. We compared the leveling result with the geocoding SBAS product using the nearest neighbour method. The mean error and standard deviation of the error were respectively 0.82 mm and 4.17 mm. This result demonstrates the effectiveness of DInSAR technique for monitoring land surface deformation, which can serve as a reliable decision for supporting highspeed railway project design, construction, operation and maintenance.

Sample Return in Preparation for Human Mission on the Surface of Mars

NASA Astrophysics Data System (ADS)

Yun, P.

2018-04-01

Returned samples of martian regolith will help the science community make an informed decision in choosing the final human landing site and develop a better human mission plan to meet science criteria and IRSU and civil engineering criteria.

Applications of space technology to water resources management

NASA Technical Reports Server (NTRS)

Salomonson, V. V.

1977-01-01

Space technology transfer is discussed in terms of applying visible and infrared remote sensing measurement to water resources management. Mapping and monitoring of snowcovered areas, hydrologic land use, and surface water areas are discussed, using information acquired from LANDSAT and NOAA satellite systems.

Mapping the Upper Subsurface of MARS Using Radar Polarimetry

NASA Technical Reports Server (NTRS)

Carter, L. M.; Rincon, R.; Berkoski, L.

2012-01-01

Future human exploration of Mars will require detailed knowledge of the surface and upper several meters of the subsurface in potential landing sites. Likewise, many of the Planetary Science Decadal Survey science goals, such as understanding the history of Mars climate change, determining how the surface was altered through processes like volcanism and fluvial activity, and locating regions that may have been hospitable to life in the past, would be significantly advanced through mapping of the upper meters of the surface. Synthetic aperture radar (SAR) is the only remote sensing technique capable of penetrating through meters of material and imaging buried surfaces at high (meters to tens-of-meters) spatial resolution. SAR is capable of mapping the boundaries of buried units and radar polarimetry can provide quantitative information about the roughness of surface and subsurface units, depth of burial of stratigraphic units, and density of materials. Orbital SAR systems can obtain broad coverage at a spatial scale relevant to human and robotic surface operations. A polarimetric SAR system would greatly increase the safety and utility of future landed systems including sample caching.

Mapping Multi-Cropped Land Use to Estimate Water Demand Using the California Pesticide Reporting Database

NASA Astrophysics Data System (ADS)

Henson, W.; Baillie, M. N.; Martin, D.

2017-12-01

Detailed and dynamic land-use data is one of the biggest data deficiencies facing food and water security issues. Better land-use data results in improved integrated hydrologic models that are needed to look at the feedback between land and water use, specifically for adequately representing changes and dynamics in rainfall-runoff, urban and agricultural water demands, and surface fluxes of water (e.g., evapotranspiration, runoff, and infiltration). Currently, land-use data typically are compiled from annual (e.g., Crop Scape) or multi-year composites if mapped at all. While this approach provides information about interannual land-use practices, it does not capture the dynamic changes in highly developed agricultural lands prevalent in California agriculture such as (1) dynamic land-use changes from high frequency multi-crop rotations and (2) uncertainty in sub-annual crop distribution, planting times, and cropped areas. California has collected spatially distributed data for agricultural pesticide use since 1974 through the California Pesticide Information Portal (CalPIP). A method leveraging the CalPIP database has been developed to provide vital information about dynamic agricultural land use (e.g., crop distribution and planting times) and water demand issues in Salinas Valley, California, along the central coast. This 7 billion dollar/year agricultural area produces up to 50% of U.S. lettuce and broccoli. Therefore, effective and sustainable water resource development in the area must balance the needs of this essential industry, other beneficial uses, and the environment. This new tool provides a way to provide more dynamic crop data in hydrologic models. While the current application focuses on the Salinas Valley, the methods are extensible to all of California and other states with similar pesticide reporting. The improvements in representing variability in crop patterns and associated water demands increase our understanding of land-use change and precision of hydrologic decision models. Ultimately, further refinement to the parcel level will completely capture the changing topology of agricultural land use.

Producing Information for Corine Database by Using Classification Method: a Case Study of Sazlidere Basin, Istanbul

NASA Astrophysics Data System (ADS)

Sarıyılmaz, F. B.; Musaoğlu, N.; Uluğtekin, N.

2017-11-01

The Sazlidere Basin is located on the European side of Istanbul within the borders of Arnavutkoy and Basaksehir districts. The total area of the basin, which is largely located within the province of Arnavutkoy, is approximately 177 km2. The Sazlidere Basin is faced with intense urbanization pressures and land use / cover change due to the Northern Marmara Motorway, 3rd airport and Channel Istanbul Projects, which are planned to be realized in the Arnavutkoy region. Due to the mentioned projects, intense land use /cover changes occur in the basin. In this study, 2000 and 2012 dated LANDSAT images were supervised classified based on CORINE Land Cover first level to determine the land use/cover classes. As a result, four information classes were identified. These classes are water bodies, forest and semi-natural areas, agricultural areas and artificial surfaces. Accuracy analysis of the images were performed following the classification process. The supervised classified images that have the smallest mapping units 0.09 ha and 0.64 ha were generalized to be compatible with the CORINE Land Cover data. The image pixels have been rearranged by using the thematic pixel aggregation method as the smallest mapping unit is 25 ha. These results were compared with CORINE Land Cover 2000 and CORINE Land Cover 2012, which were obtained by digitizing land cover and land use classes on satellite images. It has been determined that the compared results are compatible with each other in terms of quality and quantity.

Sensitivity of Land Surface Parameters on Thunderstorm Simulation through HRLDAS-WRF Coupling Mode

NASA Astrophysics Data System (ADS)

Kumar, Dinesh; Kumar, Krishan; Mohanty, U. C.; Kisore Osuri, Krishna

2016-07-01

Land surface characteristics play an important role in large scale, regional and mesoscale atmospheric process. Representation of land surface characteristics can be improved through coupling of mesoscale atmospheric models with land surface models. Mesoscale atmospheric models depend on Land Surface Models (LSM) to provide land surface variables such as fluxes of heat, moisture, and momentum for lower boundary layer evolution. Studies have shown that land surface properties such as soil moisture, soil temperature, soil roughness, vegetation cover, have considerable effect on lower boundary layer. Although, the necessity to initialize soil moisture accurately in NWP models is widely acknowledged, monitoring soil moisture at regional and global scale is a very tough task due to high spatial and temporal variability. As a result, the available observation network is unable to provide the required spatial and temporal data for the most part of the globe. Therefore, model for land surface initializations rely on updated land surface properties from LSM. The solution for NWP land-state initialization can be found by combining data assimilation techniques, satellite-derived soil data, and land surface models. Further, it requires an intermediate step to use observed rainfall, satellite derived surface insolation, and meteorological analyses to run an uncoupled (offline) integration of LSM, so that the evolution of modeled soil moisture can be forced by observed forcing conditions. Therefore, for accurate land-state initialization, high resolution land data assimilation system (HRLDAS) is used to provide the essential land surface parameters. Offline-coupling of HRLDAS-WRF has shown much improved results over Delhi, India for four thunder storm events. The evolution of land surface variables particularly soil moisture, soil temperature and surface fluxes have provided more realistic condition. Results have shown that most of domain part became wetter and warmer after assimilation of soil moisture and soil temperature at the initial condition which helped to improve the exchange fluxes at lower atmospheric level. Mixing ratio were increased along with elevated theta-e at lower level giving a signature of improvement in LDAS experiment leading to a suitable condition for convection. In the analysis, moisture convergence, mixing ratio and vertical velocities have improved significantly in terms of intensity and time lag. Surface variables like soil moisture, soil temperature, sensible heat flux and latent heat flux have progressed in a possible realistic pattern. Above discussion suggests that assimilation of soil moisture and soil temperature improves the overall simulations significantly.

Impacts of land cover transitions on surface temperature in China based on satellite observations

NASA Astrophysics Data System (ADS)

Zhang, Yuzhen; Liang, Shunlin

2018-02-01

China has experienced intense land use and land cover changes during the past several decades, which have exerted significant influences on climate change. Previous studies exploring related climatic effects have focused mainly on one or two specific land use changes, or have considered all land use and land cover change types together without distinguishing their individual impacts, and few have examined the physical processes of the mechanism through which land use changes affect surface temperature. However, in this study, we considered satellite-derived data of multiple land cover changes and transitions in China. The objective was to obtain observational evidence of the climatic effects of land cover transitions in China by exploring how they affect surface temperature and to what degree they influence it through the modification of biophysical processes, with an emphasis on changes in surface albedo and evapotranspiration (ET). To achieve this goal, we quantified the changes in albedo, ET, and surface temperature in the transition areas, examined their correlations with temperature change, and calculated the contributions of different land use transitions to surface temperature change via changes in albedo and ET. Results suggested that land cover transitions from cropland to urban land increased land surface temperature (LST) during both daytime and nighttime by 0.18 and 0.01 K, respectively. Conversely, the transition of forest to cropland tended to decrease surface temperature by 0.53 K during the day and by 0.07 K at night, mainly through changes in surface albedo. Decreases in both daytime and nighttime LST were observed over regions of grassland to forest transition, corresponding to average values of 0.44 and 0.20 K, respectively, predominantly controlled by changes in ET. These results highlight the necessity to consider the individual climatic effects of different land cover transitions or conversions in climate research studies. This short-term analysis of land cover transitions in China means our estimates should represent local temperature effects. Changes in ET and albedo explained <60% of the variation in LST change caused by land cover transitions; thus, additional factors that affect surface climate need consideration in future studies.

A lake-centric geospatial database to guide research and inform management decisions in an Arctic watershed in northern Alaska experiencing climate and land-use changes

USGS Publications Warehouse

Jones, Benjamin M.; Arp, Christopher D.; Whitman, Matthew S.; Nigro, Debora A.; Nitze, Ingmar; Beaver, John; Gadeke, Anne; Zuck, Callie; Liljedahl, Anna K.; Daanen, Ronald; Torvinen, Eric; Fritz, Stacey; Grosse, Guido

2017-01-01

Lakes are dominant and diverse landscape features in the Arctic, but conventional land cover classification schemes typically map them as a single uniform class. Here, we present a detailed lake-centric geospatial database for an Arctic watershed in northern Alaska. We developed a GIS dataset consisting of 4362 lakes that provides information on lake morphometry, hydrologic connectivity, surface area dynamics, surrounding terrestrial ecotypes, and other important conditions describing Arctic lakes. Analyzing the geospatial database relative to fish and bird survey data shows relations to lake depth and hydrologic connectivity, which are being used to guide research and aid in the management of aquatic resources in the National Petroleum Reserve in Alaska. Further development of similar geospatial databases is needed to better understand and plan for the impacts of ongoing climate and land-use changes occurring across lake-rich landscapes in the Arctic.

Impact of land use changes on hydrology of Mt. Kilimanjaro. The case of Lake Jipe catchment

NASA Astrophysics Data System (ADS)

Ngugi, Keziah; Ogindo, Harun; Ertsen, Maurits

2015-04-01

Mt. Kilimanjaro is an important water tower in Kenya and Tanzania. Land degradation and land use changes have contributed to dwindling surface water resources around Mt. Kilimanjaro. This study focuses on Lake Jipe catchment of about 451Km2 (Ndetei 2011) which is mainly drained by River Lumi, a tributary of river Pangani. River Lumi starts from Mt. Kilimanjaro and flows North east wards to cross the border from Tanzania to Kenya eventually flowing into Lake Jipe which is a trans-boundary lake. The main purpose of this study was to investigate historical land use changes and relate this to reduction in surface water resources. The study will propose measures that could restore the catchment thereby enhancing surface water resources feeding Lake Jipe. A survey was conducted to document community perspectives of historical land use changes. This information was corroborated using Landsat remote sensed images spanning the period 1985-2013 to determine changes in the land cover due to human activities on Lake Jipe Catchment. River Lumi flow data was obtained from Water Resources Management Authority and analyzed for flow trends. The dwindling extent of the Lake was obtained from the community's perspective survey and by Landsat images. Community survey and remote sensing indicated clearing of the forest on the mountain and conversion of the same to crop production fields; damming of river Lumi in Tanzania, conversion of bush land to crop production fields further downstream of river Lumi and irrigation. There is heavy infestation of the invasive species Prosopis juliflora which had aggressively colonized grazing land and blocked irrigation canals. Other land use changes include land fragmentation due to subdivision. Insecure land tenure was blamed for failure by farmers to develop soil and water conservation infrastructure. Available River gauging data showed a general decline in river flow. Heavy flooding occurred during rainy seasons. Towards Lake Jipe after the river gauging station, several springs discharge into river Lumi and the river becomes permanent. The community believes Lake Jipe is a dying lake and will be gone in the coming years unless interventions to save it are implemented. Most of river Lumi water was delivered directly into the lakes outlet, river Ruvu, thus by-passing Lake Jipe. This was due to siltation that blocked river Lumis mouth. Consequently, lake Jipes volume and surface area have reduced dramatically from over the years. Drying of Lake Jipe will affect a lot of people who depend on the lake and the ecosystem. Addressing the problems requires re-afforestation measures and soil and moisture conservation. The severe runoff need to be dammed especially on the Kenyan side to create artificial surface water resources. River Lumi should be trained to discharge into the lake. Land tenure security need to be improved as incentives for proper land utilization. New farming methods to increase land productivity will encourage farmers to practice soil and water conservation measure.

Estimating Global Impervious Surface based on Social-economic Data and Satellite Observations

NASA Astrophysics Data System (ADS)

Zeng, Z.; Zhang, K.; Xue, X.; Hong, Y.

2016-12-01

Impervious surface areas around the globe are expanding and significantly altering the surface energy balance, hydrology cycle and ecosystem services. Many studies have underlined the importance of impervious surface, r from hydrological modeling to contaminant transport monitoring and urban development estimation. Therefore accurate estimation of the global impervious surface is important for both physical and social sciences. Given the limited coverage of high spatial resolution imagery and ground survey, using satellite remote sensing and geospatial data to estimate global impervious areas is a practical approach. Based on the previous work of area-weighted imperviousness for north branch of the Chicago River provided by HDR, this study developed a method to determine the percentage of impervious surface using latest global land cover categories from multi-source satellite observations, population density and gross domestic product (GDP) data. Percent impervious surface at 30-meter resolution were mapped. We found that 1.33% of the CONUS (105,814 km2) and 0.475% of the land surface (640,370km2) are impervious surfaces. To test the utility and practicality of the proposed method, National Land Cover Database (NLCD) 2011 percent developed imperviousness for the conterminous United States was used to evaluate our results. The average difference between the derived imperviousness from our method and the NLCD data across CONUS is 1.14%, while difference between our results and the NLCD data are within ±1% over 81.63% of the CONUS. The distribution of global impervious surface map indicates that impervious surfaces are primarily concentrated in China, India, Japan, USA and Europe where are highly populated and/or developed. This study proposes a straightforward way of mapping global imperviousness, which can provide useful information for hydrologic modeling and other applications.

Functional Connectivity of Precipitation Networks in the Brazilian Rainforest-Savanna Transition Zone

NASA Astrophysics Data System (ADS)

Adera, S.; Larsen, L.; Levy, M. C.; Thompson, S. E.

2016-12-01

In the Brazilian rainforest-savanna transition zone, vegetation change has the potential to significantly affect precipitation patterns. Deforestation, in particular, can affect precipitation patterns by increasing land surface albedo, increasing aerosol loading to the atmosphere, changing land surface roughness, and reducing transpiration. Understanding land surface-precipitation couplings in this region is important not only for sustaining Amazon and Cerrado ecosystems, but also for cattle ranching and agriculture, hydropower generation, and drinking water management. Simulations suggest complex, scale-dependent interactions between precipitation and land cover. For example, the size and distribution of deforested patches has been found to affect precipitation patterns. We take an empirical approach to ask: (1) what are the dominant spatial and temporal length scales of precipitation coupling in the Brazilian rainforest-savanna transition zone? (2) How do these length scales change over time? (3) How does the connectivity of precipitation change over time? The answers to these questions will help address fundamental questions about the impacts of deforestation on precipitation. We use rain gauge data from 1100 rain gauges intermittently covering the period 1980 - 2013, a period of intensive land cover change in the region. The dominant spatial and temporal length scales of precipitation coupling are resolved using transfer entropy, a metric from information theory. Connectivity of the emergent network of couplings is quantified using network statistics. Analyses using transfer entropy and network statistics reveal the spatial and temporal interdependencies of rainfall events occurring in different parts of the study domain.

New Versions of MISR Aerosol and Land Surface Products Available

Atmospheric Science Data Center

2018-02-14

New Versions of MISR Aerosol and Land Surface Products Available Monday, February 12, ... the release of new versions of the MISR Level 2 (L2) Aerosol Product, the MISR L2 Land Surface Product, and the Level 3 (L3) Component Global Aerosol and Land Surface Products.   The new MISR L2 Aerosol Product ...

Large-Eddy Atmosphere-Land-Surface Modelling over Heterogeneous Surfaces: Model Development and Comparison with Measurements

NASA Astrophysics Data System (ADS)

Shao, Yaping; Liu, Shaofeng; Schween, Jan H.; Crewell, Susanne

2013-08-01

A model is developed for the large-eddy simulation (LES) of heterogeneous atmosphere and land-surface processes. This couples a LES model with a land-surface scheme. New developments are made to the land-surface scheme to ensure the adequate representation of atmosphere-land-surface transfers on the large-eddy scale. These include, (1) a multi-layer canopy scheme; (2) a method for flux estimates consistent with the large-eddy subgrid closure; and (3) an appropriate soil-layer configuration. The model is then applied to a heterogeneous region with 60-m horizontal resolution and the results are compared with ground-based and airborne measurements. The simulated sensible and latent heat fluxes are found to agree well with the eddy-correlation measurements. Good agreement is also found in the modelled and observed net radiation, ground heat flux, soil temperature and moisture. Based on the model results, we study the patterns of the sensible and latent heat fluxes, how such patterns come into existence, and how large eddies propagate and destroy land-surface signals in the atmosphere. Near the surface, the flux and land-use patterns are found to be closely correlated. In the lower boundary layer, small eddies bearing land-surface signals organize and develop into larger eddies, which carry the signals to considerably higher levels. As a result, the instantaneous flux patterns appear to be unrelated to the land-use patterns, but on average, the correlation between them is significant and persistent up to about 650 m. For a given land-surface type, the scatter of the fluxes amounts to several hundred W { m }^{-2}, due to (1) large-eddy randomness; (2) rapid large-eddy and surface feedback; and (3) local advection related to surface heterogeneity.

LUNAR SITE MAP (APOLLO XV) - MSC

NASA Image and Video Library

1971-07-16

S71-40085 (July 1971) --- An enlarged Lunar Orbiter photograph of the Apollo 15 landing area in the Hadley-Apennine region on the nearside of the moon. The overlay indicates the location of the numerous informally-named surface features. These names will facilitate understanding the verbal descriptions from the astronauts during their lunar surface extravehicular activity (EVA). This is an August 1967, Lunar Orbiter V photograph of Site 26.1.

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

NASA Astrophysics Data System (ADS)

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 significant delays in meteorological reporting. An initial analysis of a new prototype global ALEXI system using twice-daily observations of MODIS LST will be presented. The newly generated global ET and ESI datasets will be compared to other globally available ET and drought products during a multi-year evaluation period (2000-2013).

Towards a Near Real-Time Satellite-Based Flux Monitoring System for the MENA Region

NASA Astrophysics Data System (ADS)

Ershadi, A.; Houborg, R.; McCabe, M. F.; Anderson, M. C.; Hain, C.

2013-12-01

Satellite remote sensing has the potential to offer spatially and temporally distributed information on land surface characteristics, which may be used as inputs and constraints for estimating land surface fluxes of carbon, water and energy. Enhanced satellite-based monitoring systems for aiding local water resource assessments and agricultural management activities are particularly needed for the Middle East and North Africa (MENA) region. The MENA region is an area characterized by limited fresh water resources, an often inefficient use of these, and relatively poor in-situ monitoring as a result of sparse meteorological observations. To address these issues, an integrated modeling approach for near real-time monitoring of land surface states and fluxes at fine spatio-temporal scales over the MENA region is presented. This approach is based on synergistic application of multiple sensors and wavebands in the visible to shortwave infrared and thermal infrared (TIR) domain. The multi-scale flux mapping and monitoring system uses the Atmosphere-Land Exchange Inverse (ALEXI) model and associated flux disaggregation scheme (DisALEXI), and the Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM) in conjunction with model reanalysis data and multi-sensor remotely sensed data from polar orbiting (e.g. Landsat and MODerate resolution Imaging Spectroradiometer (MODIS)) and geostationary (MSG; Meteosat Second Generation) satellite platforms to facilitate time-continuous (i.e. daily) estimates of field-scale water, energy and carbon fluxes. Within this modeling system, TIR satellite data provide information about the sub-surface moisture status and plant stress, obviating the need for precipitation input and a detailed soil surface characterization (i.e. for prognostic modeling of soil transport processes). The STARFM fusion methodology blends aspects of high frequency (spatially coarse) and spatially fine resolution sensors and is applied directly to flux output fields to facilitate daily mapping of fluxes at sub-field scales. A complete processing infrastructure to automatically ingest and pre-process all required input data and to execute the integrated modeling system for near real-time agricultural monitoring purposes over targeted MENA sites is being developed, and initial results from this concerted effort will be discussed.

Soil-vegetation-atmosphere energy fluxes: Land Surface Temperature evaluation by Terra/MODIS satellite images

NASA Astrophysics Data System (ADS)

Telesca, V.; Copertino, V. A.; Scavone, G.; Pastore, V.; Dal Sasso, S.

2009-04-01

Most of the hydrological models are by now founded on field and satellite data integration. In fact, the use of remote sensing techniques supplies the frequent lack of field-measured variables and parameters required to apply evaluation models of the hydrological cycle components at a regional scale. These components are very sensitive to the climatic and surface features and conditions. Remote sensing represent a complementary contribution to in situ investigation methodologies, furnishing repeated and real time observations. Naturally, the interest of these techniques is tied up to the existence of a solid correlation among the greatness to evaluate and the remote sensing information obtainable from the images. In this context, satellite remote sensing has become a basic tool since it allows the regular monitoring of extensive areas. Different surface variables and parameters can be extracted from the combination of the multi-spectral information contained in a satellite image. Land Surface Temperature (LST) is a fundamental parameter to estimate most of the components of the hydrological cycle and the soil-atmosphere energy balance, such as the net radiation, the sensible heat flux and the actual evapotranspiration. Besides, LST maps can be used in models for the fire monitoring and prevention. The aim of this work is to realize, exploiting the contribution of the remote sensing, some Land Surface Temperature maps, applying different "Split Windows" algorithms and to compare them with the "Day/Night" LST/MODIS, to select the best algorithm to apply in a Two-Source Energy Balance model (STSEB). Integrated into a rainfall/runoff model, it can contribute to cope with problems of land management for the protection from natural hazards. In particular, the energy balance procedure will be included into a model for the ‘in continuous' simulation and the forecast of floods. Another important application of our model is tied up to the forecast of scenarios connected to drought problems. In this context, they can contribute to the planning and the realization of mitigation interventions for the desertification risk.

High-resolution mapping and modelling of surface albedo in Norwegian boreal forests: from remotely sensed data to predictions

NASA Astrophysics Data System (ADS)

Cherubini, Francesco; Hu, Xiangping; Vezhapparambu, Sajith; Stromman, Anders

2017-04-01

Surface albedo, a key parameter of the Earth's climate system, has high variability in space, time, and land cover and its parameterization is among the most important variables in climate models. The lack of extensive estimates for model improvement is one of the main limitations for accurately quantifying the influence of surface albedo changes on the planetary radiation balance. We use multi-year satellite retrievals of MODIS surface albedo (MCD43A3), high resolution land cover maps, and meteorological records to characterize albedo variations in Norway across latitude, seasons, land cover type, and topography. We then use this dataset to elaborate semi-empirical models to predict albedo values as a function of tree species, age, volume and climate variables like temperature and snow water equivalents (SWE). Given the complexity of the dataset and model formulation, we apply an innovative non-linear programming approach simultaneously coupled with linear un-mixing. The MODIS albedo products are at a resolution of about 500 m and 8 days. The land cover maps provide vegetation structure information on relative abundance of tree species, age, and biomass volumes at 16 m resolution (for both deciduous and coniferous species). Daily observations of meteorological information on air temperature and SWE are produced at 1 km resolution from interpolation of meteorological weather stations in Norway. These datasets have different resolution and projection, and are harmonized by identifying, for each MODIS pixel, the intersecting land cover polygons and the percentage area of the MODIS pixel represented by each land cover type. We then filter the subplots according to the following criteria: i) at least 96% of the total pixel area is covered by a single land cover class (either forest or cropland); ii) if forest area, at least 98% of the forest area is covered by spruce, deciduous or pine. Forested pixels are then categorized as spruce, deciduous, or pine dominant if the fraction of the respective tree species is greater than 75%. Results show averages of albedo estimates for forests and cropland depicting spatial (along a latitudinal gradient) and temporal (daily, monthly, and seasonal) variations across Norway. As the case study region is a country with heterogeneous topography, we also study the sensitivity of the albedo estimates to the slope and aspect of the terrain. The mathematical programming approach uses a variety of functional forms, constraints and variables, leading to many different model outputs. There are several models with relatively high performances, allowing for a flexibility in the model selection, with different model variants suitable for different situations. This approach produces albedo predictions at the same resolution of the land cover dataset (16 m, notably higher than the MODIS estimates), can incorporate changes in climate conditions, and is robust to cross-validation between different locations. By integrating satellite measurements and high-resolution vegetation maps, we can thus produce semi-empirical models that can predict albedo values for boreal forests using a variety of input variables representing climate and/or vegetation structure. Further research can explore the possible advantages of its implementation in land surface schemes over existing approaches.

The Potential of Time Series Based Earth Observation for the Monitoring of Large River Deltas

NASA Astrophysics Data System (ADS)

Kuenzer, C.; Leinenkugel, P.; Huth, J.; Ottinger, M.; Renaud, F.; Foufoula-Georgiou, E.; Vo Khac, T.; Trinh Thi, L.; Dech, S.; Koch, P.; Le Tissier, M.

2015-12-01

Although river deltas only contribute 5% to the overall land surface, nearly six hundred million people live in these complex social-ecological environments, which combine a variety of appealing locational advantages. In many countries deltas provide the major national contribution to agricultural and industrial production. At the same time these already very dynamic environments are exposed to a variety of threats, including the disturbance and replacement of valuable ecosystems, increasing water, soil, and air pollution, human induced land subsidence, sea level rise, as well upstream developments impacting water and sediment supplies. A constant monitoring of delta systems is thus of utmost relevance for understanding past and current land surface change and anticipating possible future developments. We present the potential of Earth Observation based analyses and derived novel information products that can play a key role in this context. Along with the current trend of opening up numerous satellite data archives go increasing capabilities to explore big data. Whereas in past decades remote sensing data were analysed based on the spectral-reflectance-defined 'finger print' of individual surfaces, we mainly exploit the 'temporal fingerprints' of our land surface in novel pathways of data analyses at differing spatial-, and temporally-dense scales. Following our results on an Earth Observation based characterization of large deltas globally, we present in depth results from the Mekong Delta in Vietnam, the Yellow River Delta in China, the Niger Delta in Nigeria, as well as additional deltas, focussing on the assessment of river delta flood and inundation dynamics, river delta coastline dynamics, delta morphology dynamics including the quantification of erosion and accretion processes, river delta land use change and trends, as well as the monitoring of compliance to environmental regulations.

The Ice, Cloud, and land Elevation Satellite (ICESat) Summary Mission Timeline and Performance Relative to Pre-Launch Mission Success Criteria

NASA Technical Reports Server (NTRS)

Webb, Charles E.; Zwally H. Jay; Abdalati, Waleed

2012-01-01

The Ice, Cloud and land Elevation Satellite (ICESat) mission was conceived, primarily, to quantify the spatial and temporal variations in the topography of the Greenland and Antarctic ice sheets. It carried on board the Geoscience Laser Altimeter System (GLAS), which measured the round-trip travel time of a laser pulse emitted from the satellite to the surface of the Earth and back. Each range derived from these measurements was combined with precise, concurrent orbit and pointing information to determine the location of the laser spot centroid on the Earth. By developing a time series of precise topographic maps for each ice sheet, changes in their surface elevations can be used to infer their mass balances.

Effects of rainfall patterns and land cover on the subsurface flow generation of sloping Ferralsols in southern China

PubMed Central

Yang, Jie; Tang, Chongjun; Chen, Lihua; Liu, Yaojun; Wang, Lingyun

2017-01-01

Rainfall patterns and land cover are two important factors that affect the runoff generation process. To determine the surface and subsurface flows associated with different rainfall patterns on sloping Ferralsols under different land cover types, observational data related to surface and subsurface flows from 5 m × 15 m plots were collected from 2010 to 2012. The experiment was conducted to assess three land cover types (grass, litter cover and bare land) in the Jiangxi Provincial Soil and Water Conservation Ecological Park. During the study period, 114 natural rainfall events produced subsurface flow and were divided into four groups using k-means clustering according to rainfall duration, rainfall depth and maximum 30-min rainfall intensity. The results showed that the total runoff and surface flow values were highest for bare land under all four rainfall patterns and lowest for the covered plots. However, covered plots generated higher subsurface flow values than bare land. Moreover, the surface and subsurface flows associated with the three land cover types differed significantly under different rainfall patterns. Rainfall patterns with low intensities and long durations created more subsurface flow in the grass and litter cover types, whereas rainfall patterns with high intensities and short durations resulted in greater surface flow over bare land. Rainfall pattern I had the highest surface and subsurface flow values for the grass cover and litter cover types. The highest surface flow value and lowest subsurface flow value for bare land occurred under rainfall pattern IV. Rainfall pattern II generated the highest subsurface flow value for bare land. Therefore, grass or litter cover are able to convert more surface flow into subsurface flow under different rainfall patterns. The rainfall patterns studied had greater effects on subsurface flow than on total runoff and surface flow for covered surfaces, as well as a greater effect on surface flows associated with bare land. PMID:28792507

Effect of water table dynamics on land surface hydrologic memory

NASA Astrophysics Data System (ADS)

Lo, Min-Hui; Famiglietti, James S.

2010-11-01

The representation of groundwater dynamics in land surface models has received considerable attention in recent years. Most studies have found that soil moisture increases after adding a groundwater component because of the additional supply of water to the root zone. However, the effect of groundwater on land surface hydrologic memory (persistence) has not been explored thoroughly. In this study we investigate the effect of water table dynamics on National Center for Atmospheric Research Community Land Model hydrologic simulations in terms of land surface hydrologic memory. Unlike soil water or evapotranspiration, results show that land surface hydrologic memory does not always increase after adding a groundwater component. In regions where the water table level is intermediate, land surface hydrologic memory can even decrease, which occurs when soil moisture and capillary rise from groundwater are not in phase with each other. Further, we explore the hypothesis that in addition to atmospheric forcing, groundwater variations may also play an important role in affecting land surface hydrologic memory. Analyses show that feedbacks of groundwater on land surface hydrologic memory can be positive, negative, or neutral, depending on water table dynamics. In regions where the water table is shallow, the damping process of soil moisture variations by groundwater is not significant, and soil moisture variations are mostly controlled by random noise from atmospheric forcing. In contrast, in regions where the water table is very deep, capillary fluxes from groundwater are small, having limited potential to affect soil moisture variations. Therefore, a positive feedback of groundwater to land surface hydrologic memory is observed in a transition zone between deep and shallow water tables, where capillary fluxes act as a buffer by reducing high-frequency soil moisture variations resulting in longer land surface hydrologic memory.

Effects of Topography-based Subgrid Structures on Land Surface Modeling

NASA Astrophysics Data System (ADS)

Tesfa, T. K.; Ruby, L.; Brunke, M.; Thornton, P. E.; Zeng, X.; Ghan, S. J.

2017-12-01

Topography has major control on land surface processes through its influence on atmospheric forcing, soil and vegetation properties, network topology and drainage area. Consequently, accurate climate and land surface simulations in mountainous regions cannot be achieved without considering the effects of topographic spatial heterogeneity. To test a computationally less expensive hyper-resolution land surface modeling approach, we developed topography-based landunits within a hierarchical subgrid spatial structure to improve representation of land surface processes in the ACME Land Model (ALM) with minimal increase in computational demand, while improving the ability to capture the spatial heterogeneity of atmospheric forcing and land cover influenced by topography. This study focuses on evaluation of the impacts of the new spatial structures on modeling land surface processes. As a first step, we compare ALM simulations with and without subgrid topography and driven by grid cell mean atmospheric forcing to isolate the impacts of the subgrid topography on the simulated land surface states and fluxes. Recognizing that subgrid topography also has important effects on atmospheric processes that control temperature, radiation, and precipitation, methods are being developed to downscale atmospheric forcings. Hence in the second step, the impacts of the subgrid topographic structure on land surface modeling will be evaluated by including spatial downscaling of the atmospheric forcings. Preliminary results on the atmospheric downscaling and the effects of the new spatial structures on the ALM simulations will be presented.

Rock Statistics at the Mars Pathfinder Landing Site, Roughness and Roving on Mars

NASA Technical Reports Server (NTRS)

Haldemann, A. F. C.; Bridges, N. T.; Anderson, R. C.; Golombek, M. P.

1999-01-01

Several rock counts have been carried out at the Mars Pathfinder landing site producing consistent statistics of rock coverage and size-frequency distributions. These rock statistics provide a primary element of "ground truth" for anchoring remote sensing information used to pick the Pathfinder, and future, landing sites. The observed rock population statistics should also be consistent with the emplacement and alteration processes postulated to govern the landing site landscape. The rock population databases can however be used in ways that go beyond the calculation of cumulative number and cumulative area distributions versus rock diameter and height. Since the spatial parameters measured to characterize each rock are determined with stereo image pairs, the rock database serves as a subset of the full landing site digital terrain model (DTM). Insofar as a rock count can be carried out in a speedier, albeit coarser, manner than the full DTM analysis, rock counting offers several operational and scientific products in the near term. Quantitative rock mapping adds further information to the geomorphic study of the landing site, and can also be used for rover traverse planning. Statistical analysis of the surface roughness using the rock count proxy DTM is sufficiently accurate when compared to the full DTM to compare with radar remote sensing roughness measures, and with rover traverse profiles.

Hydrological modeling of upper Indus Basin and assessment of deltaic ecology

USDA-ARS?s Scientific Manuscript database

Managing water resources is mostly required at watershed scale where the complex hydrology processes and interactions linking land surface, climatic factors and human activities can be studied. Geographical Information System based watershed model; Soil and Water Assessment Tool (SWAT) is applied f...

ICLUS Tools and Datasets (Version 1.3.2)

EPA Science Inventory

As a part of the Integrated Climate and Land Use Scenarios (ICLUS) project, this Geographic Information System (GIS) tool can be used to generate scenarios of housing-density changes and calculate impervious surface cover for the conterminous United States. The ICLUS User’s Guid...

Generating high temporal and spatial resolution thermal band imagery using robust sharpening approach

USDA-ARS?s Scientific Manuscript database

Thermal infrared band imagery provides key information for detecting wild fires, mapping land surface energy fluxes and evapotranspiration, monitoring urban heat fluxes and drought monitoring. Thermal infrared (TIR) imagery at fine resolution is required for field scale applications. However, therma...

Unmanned airborne thermal and mutilspectral imagery for estimating evapotranspiration in irrigated vineyards

USDA-ARS?s Scientific Manuscript database

Thermal-infrared remote sensing of land surface temperature (LST) provides valuable information for quantifying rootzone water availability, evapotranspiration (ET) and crop condition. This paper describes the most recent modifications applied to the robust but relatively simple LST-based energy bal...

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

NASA Technical Reports Server (NTRS)

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.

In-flight wind identification and soft landing control for autonomous unmanned powered parafoils

NASA Astrophysics Data System (ADS)

Luo, Shuzhen; Tan, Panlong; Sun, Qinglin; Wu, Wannan; Luo, Haowen; Chen, Zengqiang

2018-04-01

For autonomous unmanned powered parafoil, the ability to perform a final flare manoeuvre against the wind direction can allow a considerable reduction of horizontal and vertical velocities at impact, enabling a soft landing for a safe delivery of sensible loads; the lack of knowledge about the surface-layer winds will result in messing up terminal flare manoeuvre. Moreover, unknown or erroneous winds can also prevent the parafoil system from reaching the target area. To realize accurate trajectory tracking and terminal soft landing in the unknown wind environment, an efficient in-flight wind identification method merely using Global Positioning System (GPS) data and recursive least square method is proposed to online identify the variable wind information. Furthermore, a novel linear extended state observation filter is proposed to filter the groundspeed of the powered parafoil system calculated by the GPS information to provide a best estimation of the present wind during flight. Simulation experiments and real airdrop tests demonstrate the great ability of this method to in-flight identify the variable wind field, and it can benefit the powered parafoil system to fulfil accurate tracking control and a soft landing in the unknown wind field with high landing accuracy and strong wind-resistance ability.

A Landing Site for ExoMars 2016

NASA Image and Video Library

2015-11-27

This image from NASA Mars Reconnaissance Orbiter spacecraft is of a landing site that the flattest, safest place on Mars: part of Meridiani Planum, close to where the Opportunity rover landed. In March 2016, the European Space Agency in partnership with Roscosmos will launch the ExoMars Trace Gas Orbiter. This orbiter will also carry an Entry, Descent, and Landing Demonstration Module (EDM): a lander designed primarily to demonstrate the capability to land on Mars. The EDM will survive for only a few days, running on battery power, but will make a few environmental measurements. The landing site is the flattest, safest place on Mars: part of Meridiani Planum, close to where the Opportunity rover landed. This image shows what this terrain is like: very flat and featureless. A full-resolution sample reveals the major surface features: small craters and wind ripples. HiRISE has been imaging the landing site region in advance of the landing, and will re-image the site after landing to identify the major pieces of hardware: heat shield, backshell with parachute, and the lander itself. The distribution of these pieces will provide information about the entry, descent and landing. http://photojournal.jpl.nasa.gov/catalog/PIA20159

Analysis of Water and Energy Budgets and Trends Using the NLDAS Monthly Data Sets

NASA Technical Reports Server (NTRS)

Vollmer, Bruce E.; Rui, Hualan; Mocko, David M.; Teng, William L.; Lei, Guang-Dih

2012-01-01

The North American Land Data Assimilation System (NLDAS) is a collaborative project between NASA GSFC, NOAA, Princeton University, and the University of Washington. NLDAS has created surface meteorological forcing data sets using the best-available observations and reanalyses. The forcing data sets are used to drive four separate land-surface models (LSMs), Mosaic, Noah, VIC, and SAC, to produce data sets of soil moisture, snow, runoff, and surface fluxes. NLDAS hourly data, accessible from the NASA GES DISC Hydrology Data Holdings Portal, http://disc.sci.gsfc.nasa.gov/hydrology/data-holdings, are widely used by various user communities in modeling, research, and applications, such as drought and flood monitoring, watershed and water quality management, and case studies of extreme events. More information is available at http://ldas.gsfc.nasa.gov/. To further facilitate analysis of water and energy budgets and trends, NLDAS monthly data sets have been recently released by NASA GES DISC.

Hyperspectral Observations of Land Surfaces Using Ground-based, Airborne, and Satellite Sensors

NASA Astrophysics Data System (ADS)

Knuteson, R. O.; Best, F. A.; Revercomb, H. E.; Tobin, D. C.

2006-12-01

The University of Wisconsin-Madison Space Science and Engineering Center (UW-SSEC) has helped pioneer the use of high spectral resolution infrared spectrometers for application to atmospheric and surface remote sensing. This paper is focused on observations of land surface infrared emission from high spectral resolution measurements collected over the past 15 years using airborne, ground-based, and satellite platforms. The earliest data was collected by the High-resolution Interferometer Sounder (HIS), an instrument designed in the 1980s for operation on the NASA ER-2 high altitude aircraft. The HIS was replaced in the late 1990s by the Scanning-HIS instrument which has flown on the NASA ER-2, WB-57, DC-8, and Scaled Composites Proteus aircraft and continues to support field campaigns, such as those for EOS Terra, Aqua, and Aura validation. Since 1995 the UW-SSEC has fielded a ground-based Atmospheric Emitted Radiance Interferometer (AERI) in a research vehicle (the AERIBAGO) which has allowed for direct field measurements of land surface emission from a height of about 16 ft above the ground. Several ground-based and aircraft campaigns were conducted to survey the region surrounding the ARM Southern Great Plains site in north central Oklahoma. The ground- based AERIBAGO has also participated in surface emissivity campaigns in the Western U.S.. Since 2002, the NASA Atmospheric InfraRed Sounder (AIRS) has provided similar measurements from the Aqua platform in an afternoon sun-synchronous polar orbit. Ground-based and airborne observations are being used to validate the land surface products derived from the AIRS observations. These cal/val activities are in preparation for similar measurements anticipated from the operational Cross-track InfraRed Sounder (CrIS) on the NPOESS Preparatory Platform (NPP), expected to be launched in 2008. Moreover, high spectral infrared observations will soon be made by the Infrared Atmospheric Sounder Interferometer (IASI) on the European MetOp platform as well as a planned series of Chinese polar orbiting satellites. The detailed understanding of the land surface infrared emission is a crucial step in the effective utilization of these advanced sounder instruments for the extraction of atmospheric composition information (esp. water vapor vertical profile) over land, which is a key goal for numerical weather prediction data assimilation.

Remote Sensing of the Environmental Impacts of Utility-Scale Solar Energy Plants

NASA Astrophysics Data System (ADS)

Edalat, Mohammad Masih

Solar energy has many environmental benefits compared with fossil fuels but solar farming can have environmental impacts especially during construction and development. Thus, in order to enhance environmental sustainability, it is imperative to understand the environmental impacts of utility-scale solar energy (USSE) plants. During recent decades, remote sensing techniques and geographic information systems have become standard techniques in environmental applications. In this study, the environmental impacts of USSE plants are investigated by analyzing changes to land surface characteristics using remote sensing. The surface characteristics studied include land cover, land surface temperature, and hydrological response whereas changes are mapped by comparing pre-, syn-, and post- construction conditions. In order to study the effects of USSE facilities on land cover, the changes in the land cover are measured and analyzed inside and around two USSE facilities. The principal component analysis (PCA), minimum noise fraction (MNF), and spectral mixture analysis (SMA) of remote sensing images are used to estimate the subpixel fraction of four land surface endmembers: high-albedo, low-albedo, shadow, and vegetation. The results revealed that USSE plants do not significantly impact land cover outside the plant boundary. However, land-cover radiative characteristics within the plant area are significantly affected after construction. During the construction phase, site preparation practices including shrub removal and land grading increase high-albedo and decrease low-albedo fractions. The thermal effects of USSE facilities are studied by the time series analysis of remote sensing land surface temperature (LST). A statistical trend analysis of LST, with seasonal trends removed is performed with a particular consideration of panel shadowing by analyzing sun angles for different times of year. The results revealed that the LST outside the boundary of the solar plant does not change, whereas it significantly decreases inside the plant at 10 AM after the construction. The decrease in LST mainly occurred in winters due to lower sun's altitude, which casts longer shadows on the ground. In order to study the hydrological impacts of PV plants, pre- and post-installation hydrological response over single-axis technology is compared. A theoretical reasoning is developed to explain flows under the influence of PV panels. Moreover, a distributed parametric hydrologic model is used to estimate runoff before and after the construction of PV plants. The results revealed that peak flow, peak flow time, and runoff volume alter after panel installation. After panel installation, peak flow decreases and is observed to shift in time, which depends on orientation. Likewise, runoff volume increases irrespective of panel orientation. The increase in the tilt angle of panel results in decrease in the peak flow, peak flow time, and runoff. This study provides an insight into the environmental impacts of USSE development using remote sensing. The research demonstrates that USSE plants are environmentally sustainable due to minimal impact on land cover and surface temperature in their vicinity. In addition, this research explains the role of rainfall shadowing on hydrological behavior at USSE plants.

An Automated Algorithm for Producing Land Cover Information from Landsat Surface Reflectance Data Acquired Between 1984 and Present

NASA Astrophysics Data System (ADS)

Rover, J.; Goldhaber, M. B.; Holen, C.; Dittmeier, R.; Wika, S.; Steinwand, D.; Dahal, D.; Tolk, B.; Quenzer, R.; Nelson, K.; Wylie, B. K.; Coan, M.

2015-12-01

Multi-year land cover mapping from remotely sensed data poses challenges. Producing land cover products at spatial and temporal scales required for assessing longer-term trends in land cover change are typically a resource-limited process. A recently developed approach utilizes open source software libraries to automatically generate datasets, decision tree classifications, and data products while requiring minimal user interaction. Users are only required to supply coordinates for an area of interest, land cover from an existing source such as National Land Cover Database and percent slope from a digital terrain model for the same area of interest, two target acquisition year-day windows, and the years of interest between 1984 and present. The algorithm queries the Landsat archive for Landsat data intersecting the area and dates of interest. Cloud-free pixels meeting the user's criteria are mosaicked to create composite images for training the classifiers and applying the classifiers. Stratification of training data is determined by the user and redefined during an iterative process of reviewing classifiers and resulting predictions. The algorithm outputs include yearly land cover raster format data, graphics, and supporting databases for further analysis. Additional analytical tools are also incorporated into the automated land cover system and enable statistical analysis after data are generated. Applications tested include the impact of land cover change and water permanence. For example, land cover conversions in areas where shrubland and grassland were replaced by shale oil pads during hydrofracking of the Bakken Formation were quantified. Analytical analysis of spatial and temporal changes in surface water included identifying wetlands in the Prairie Pothole Region of North Dakota with potential connectivity to ground water, indicating subsurface permeability and geochemistry.

Estimating daily surface NO2 concentrations from satellite data - a case study over Hong Kong using land use regression models

NASA Astrophysics Data System (ADS)

Anand, Jasdeep S.; Monks, Paul S.

2017-07-01

Land use regression (LUR) models have been used in epidemiology to determine the fine-scale spatial variation in air pollutants such as nitrogen dioxide (NO2) in cities and larger regions. However, they are often limited in their temporal resolution, which may potentially be rectified by employing the synoptic coverage provided by satellite measurements. In this work a mixed-effects LUR model is developed to model daily surface NO2 concentrations over the Hong Kong SAR during the period 2005-2015. In situ measurements from the Hong Kong Air Quality Monitoring Network, along with tropospheric vertical column density (VCD) data from the OMI, GOME-2A, and SCIAMACHY satellite instruments were combined with fine-scale land use parameters to provide the spatiotemporal information necessary to predict daily surface concentrations. Cross-validation with the in situ data shows that the mixed-effects LUR model using OMI data has a high predictive power (adj. R2 = 0. 84), especially when compared with surface concentrations derived using the MACC-II reanalysis model dataset (adj. R2 = 0. 11). Time series analysis shows no statistically significant trend in NO2 concentrations during 2005-2015, despite a reported decline in NOx emissions. This study demonstrates the utility in combining satellite data with LUR models to derive daily maps of ambient surface NO2 for use in exposure studies.

A dynamic aerodynamic resistance approach to calculate high resolution sensible heat fluxes in urban areas

NASA Astrophysics Data System (ADS)

Crawford, Ben; Grimmond, Sue; Kent, Christoph; Gabey, Andrew; Ward, Helen; Sun, Ting; Morrison, William

2017-04-01

Remotely sensed data from satellites have potential to enable high-resolution, automated calculation of urban surface energy balance terms and inform decisions about urban adaptations to environmental change. However, aerodynamic resistance methods to estimate sensible heat flux (QH) in cities using satellite-derived observations of surface temperature are difficult in part due to spatial and temporal variability of the thermal aerodynamic resistance term (rah). In this work, we extend an empirical function to estimate rah using observational data from several cities with a broad range of surface vegetation land cover properties. We then use this function to calculate spatially and temporally variable rah in London based on high-resolution (100 m) land cover datasets and in situ meteorological observations. In order to calculate high-resolution QH based on satellite-observed land surface temperatures, we also develop and employ novel methods to i) apply source area-weighted averaging of surface and meteorological variables across the study spatial domain, ii) calculate spatially variable, high-resolution meteorological variables (wind speed, friction velocity, and Obukhov length), iii) incorporate spatially interpolated urban air temperatures from a distributed sensor network, and iv) apply a modified Monte Carlo approach to assess uncertainties with our results, methods, and input variables. Modeled QH using the aerodynamic resistance method is then compared to in situ observations in central London from a unique network of scintillometers and eddy-covariance measurements.

The concept of hydrologic landscapes

USGS Publications Warehouse

Winter, T.C.

2001-01-01

Hydrologic landscapes are multiples or variations of fundamental hydrologic landscape units. A fundamental hydrologic landscape unit is defined on the basis of land-surface form, geology, and climate. The basic land-surface form of a fundamental hydrologic landscape unit is an upland separated from a lowland by an intervening steeper slope. Fundamental hydrologic landscape units have a complete hydrologic system consisting of surface runoff, ground-water flow, and interaction with atmospheric water. By describing actual landscapes in terms of land-surface slope, hydraulic properties of soils and geologic framework, and the difference between precipitation and evapotranspiration, the hydrologic system of actual landscapes can be conceptualized in a uniform way. This conceptual framework can then be the foundation for design of studies and data networks, syntheses of information on local to national scales, and comparison of process research across small study units in a variety of settings. The Crow Wing River watershed in central Minnesota is used as an example of evaluating stream discharge in the context of hydrologic landscapes. Lake-research watersheds in Wisconsin, Minnesota, North Dakota, and Nebraska are used as an example of using the hydrologic-landscapes concept to evaluate the effect of ground water on the degree of mineralization and major-ion chemistry of lakes that lie within ground-water flow systems.

Terrestrial Ecosystems - Land Surface Forms of the Conterminous United States

USGS Publications Warehouse

Cress, Jill J.; Sayre, Roger G.; Comer, Patrick; Warner, Harumi

2009-01-01

As part of an effort to map terrestrial ecosystems, the U.S. Geological Survey has generated land surface form classes to be used in creating maps depicting standardized, terrestrial ecosystem models for the conterminous United States, using an ecosystems classification developed by NatureServe . A biophysical stratification approach, developed for South America and now being implemented globally, was used to model the ecosystem distributions. Since land surface forms strongly influence the differentiation and distribution of terrestrial ecosystems, they are one of the key input layers in this biophysical stratification. After extensive investigation into various land surface form mapping methodologies, the decision was made to use the methodology developed by the Missouri Resource Assessment Partnership (MoRAP). MoRAP made modifications to Hammond's land surface form classification, which allowed the use of 30-meter source data and a 1-km2 window for analyzing the data cell and its surrounding cells (neighborhood analysis). While Hammond's methodology was based on three topographic variables, slope, local relief, and profile type, MoRAP's methodology uses only slope and local relief. Using the MoRAP method, slope is classified as gently sloping when more than 50 percent of the area in a 1-km2 neighborhood has slope less than 8 percent, otherwise the area is considered moderately sloping. Local relief, which is the difference between the maximum and minimum elevation in a neighborhood, is classified into five groups: 0-15 m, 16-30 m, 31-90 m, 91-150 m, and >150 m. The land surface form classes are derived by combining slope and local relief to create eight landform classes: flat plains (gently sloping and local relief = 90 m), low hills (not gently sloping and local relief = 150 m). However, in the USGS application of the MoRAP methodology, an additional local relief group was used (> 400 m) to capture additional local topographic variation. As a result, low mountains were redefined as not gently sloping and 151 m 400 m. The final application of the MoRAP methodology was implemented using the USGS 30-meter National Elevation Dataset and an existing USGS slope dataset that had been derived by calculating the slope from the NED in Universal Transverse Mercator (UTM) coordinates in each UTM zone, and then combining all of the zones into a national dataset. This map shows a smoothed image of the nine land surface form classes based on MoRAP's methodology. Additional information about this map and any data developed for the ecosystems modeling of the conterminous United States is available online at http://rmgsc.cr.usgs.gov/ecosystems/.

Applications of NASA GSFC's Land Information System (LIS) for water resources management in Korea and East-Asia

NASA Astrophysics Data System (ADS)

Kang, D. H.; Hwang, E.; Jung, H. C.; Kim, E. J.; Peters-Lidard, C. D.; Kumar, S.; Chae, H.; Baeck, S. H.

2017-12-01

NASA has contributed to resolve global water issues by utilizing their long-term legacy of remote sensing technologies supported by a state of art software engineering. In this context, NASA Goddard Space Flight Center has developed a land surface model framework to monitor and predict water hazards such as flood and drought with the Land Information System (hereafter LIS) applied to North America and beyond it to include a global coverage. However, it is still challenging to apply the LIS to East-Asia where a rice-paddy agriculture is prevalent compared to other parts of the world, but retains a high population density in this region. Thus, this paper introduces recent efforts from the Korea Water Resources Corporation (K-water) in S. Korea to establish the LIS in East-Asia including Korea, aiming at producing surface hydrology datasets in Asia. One of the ultimate goals of this project is to manage the water hazards in Korea and to provide the water resources dataset in East-Asia by adapting the LIS with their abundantly available hydrometeorological observations to support the LIS applications. Preliminary results from initiating efforts since the beginning of 2017 between NASA and K-water are addressed in the paper to review the possible outcomes after this ongoing project to benefit both entities. Acknowledgements This research was supported by a grant (17AWMP-B079625-04) from Water Management Research Program sponsored by Ministry of Land, Infrastructure and Transport of Korean government.

Multicriteria analysis for sources of renewable energy using data from remote sensing

NASA Astrophysics Data System (ADS)

Matejicek, L.

2015-04-01

Renewable energy sources are major components of the strategy to reduce harmful emissions and to replace depleting fossil energy resources. Data from remote sensing can provide information for multicriteria analysis for sources of renewable energy. Advanced land cover quantification makes it possible to search for suitable sites. Multicriteria analysis, together with other data, is used to determine the energy potential and socially acceptability of suggested locations. The described case study is focused on an area of surface coal mines in the northwestern region of the Czech Republic, where the impacts of surface mining and reclamation constitute a dominant force in land cover changes. High resolution satellite images represent the main input datasets for identification of suitable sites. Solar mapping, wind predictions, the location of weirs in watersheds, road maps and demographic information complement the data from remote sensing for multicriteria analysis, which is implemented in a geographic information system (GIS). The input spatial datasets for multicriteria analysis in GIS are reclassified to a common scale and processed with raster algebra tools to identify suitable sites for sources of renewable energy. The selection of suitable sites is limited by the CORINE land cover database to mining and agricultural areas. The case study is focused on long term land cover changes in the 1985-2015 period. Multicriteria analysis based on CORINE data shows moderate changes in mapping of suitable sites for utilization of selected sources of renewable energy in 1990, 2000, 2006 and 2012. The results represent map layers showing the energy potential on a scale of a few preference classes (1-7), where the first class is linked to minimum preference and the last class to maximum preference. The attached histograms show the moderate variability of preference classes due to land cover changes caused by mining activities. The results also show a slight increase in the more preferred classes for utilization of sources of renewable energy due to an increase area of reclaimed sites. Using data from remote sensing, such as the multispectral images and the CORINE land cover datasets, can reduce the financial resources currently required for finding and assessing suitable areas.

Impact of land cover change on the environmental hydrology characteristics in Kelantan river basin, Malaysia

NASA Astrophysics Data System (ADS)

Saadatkhah, Nader; Mansor, Shattri; Khuzaimah, Zailani; Asmat, Arnis; Adnan, Noraizam; Adam, Siti Noradzah

2016-09-01

Changing the land cover/ land use has serious environmental impacts affecting the ecosystem in Malaysia. The impact of land cover changes on the environmental functions such as surface water, loss water, and soil moisture is considered in this paper on the Kelantan river basin. The study area at the east coast of the peninsular Malaysia has suffered significant land cover changes in the recent years. The current research tried to assess the impact of land cover changes in the study area focused on the surface water, loss water, and soil moisture from different land use classes and the potential impact of land cover changes on the ecosystem of Kelantan river basin. To simulate the impact of land cover changes on the environmental hydrology characteristics, a deterministic regional modeling were employed in this study based on five approaches, i.e. (1) Land cover classification based on Landsat images; (2) assessment of land cover changes during last three decades; (3) Calculation the rate of water Loss/ Infiltration; (4) Assessment of hydrological and mechanical effects of the land cover changes on the surface water; and (5) evaluation the impact of land cover changes on the ecosystem of the study area. Assessment of land cover impact on the environmental hydrology was computed with the improved transient rainfall infiltration and grid based regional model (Improved-TRIGRS) based on the transient infiltration, and subsequently changes in the surface water, due to precipitation events. The results showed the direct increased in surface water from development area, agricultural area, and grassland regions compared with surface water from other land covered areas in the study area. The urban areas or lower planting density areas tend to increase for surface water during the monsoon seasons, whereas the inter flow from forested and secondary jungle areas contributes to the normal surface water.

Land-Sea relationships of climate-related records: example of the Holocene in the eastern Canadian Arctic and Greenland

NASA Astrophysics Data System (ADS)

de Vernal, Anne; Fréchette, Bianca; Hillaire-Marcel, Claude

2017-04-01

Anne de Vernal, Bianca Fréchette, Claude Hillaire-Marcel Important progresses have been made to reconstruct climate and ocean changes through time. However, there is often a hiatus between the land-based climate reconstructions and paleoceanographical data. The reconstructed parameters are not the same (e.g. surface air temperature vs. sea-surface temperature). Moreover, the spatial (local to regional) and temporal dimensions (seasonal, annual to multi-decadal) of proxy-data are often inconsistent, thus preventing direct correlation of time series and often leading to uncertainties in multi-site, multi-proxy compilations. Here, we address the issue of land-sea relationships in the eastern Canadian Arctic-Baffin Bay-Labrador Sea-western Greenland based on the examination of different climate-related information from marine cores (dinocysts) collected nearshore vs. offshore, ice cores (isotopes), fjord and lake data (pollen). The combined information tends to indicate that "climate" changes are not easily neither adequately captured by temperature and temperature shifts. However, the seasonal contrast of temperatures seems to be a key parameter. Whereas it is often attenuated offshore, it is generally easy to reconstruct nearshore, where water stratification is usually stronger. The confrontation of data also shows a relationship between ice core data and sea-ice cover and/or sea-surface salinity, suggesting that air-sea exchanges in basins surrounding ice sheets play a significant role with respect to their isotopic composition. On the whole, combined onshore-offshore data consistently suggest a two-step shift towards optimal summer and winter conditions the circum Baffin Bay and northern Labrador Sea at 7.5 and 6 ka BP. These delayed optimal conditions seem to result from ice-meltwater discharges maintaining low salinity conditions in marine surface waters and thus a strong seasonality.

A land data assimilation system for sub-Saharan Africa food and water security applications

PubMed Central

McNally, Amy; Arsenault, Kristi; Kumar, Sujay; Shukla, Shraddhanand; Peterson, Pete; Wang, Shugong; Funk, Chris; Peters-Lidard, Christa D.; Verdin, James P.

2017-01-01

Seasonal agricultural drought monitoring systems, which rely on satellite remote sensing and land surface models (LSMs), are important for disaster risk reduction and famine early warning. These systems require the best available weather inputs, as well as a long-term historical record to contextualize current observations. This article introduces the Famine Early Warning Systems Network (FEWS NET) Land Data Assimilation System (FLDAS), a custom instance of the NASA Land Information System (LIS) framework. The FLDAS is routinely used to produce multi-model and multi-forcing estimates of hydro-climate states and fluxes over semi-arid, food insecure regions of Africa. These modeled data and derived products, like soil moisture percentiles and water availability, were designed and are currently used to complement FEWS NET’s operational remotely sensed rainfall, evapotranspiration, and vegetation observations. The 30+ years of monthly outputs from the FLDAS simulations are publicly available from the NASA Goddard Earth Science Data and Information Services Center (GES DISC) and recommended for use in hydroclimate studies, early warning applications, and by agro-meteorological scientists in Eastern, Southern, and Western Africa. PMID:28195575

A land data assimilation system for sub-Saharan Africa food and water security applications

USGS Publications Warehouse

McNally, Amy; Arsenault, Kristi; Kumar, Sujay; Shukla, Shraddhanand; Peterson, Pete; Wang, Shugong; Funk, Chris; Peters-Lidard, Christa; Verdin, James

2017-01-01

Seasonal agricultural drought monitoring systems, which rely on satellite remote sensing and land surface models (LSMs), are important for disaster risk reduction and famine early warning. These systems require the best available weather inputs, as well as a long-term historical record to contextualize current observations. This article introduces the Famine Early Warning Systems Network (FEWS NET) Land Data Assimilation System (FLDAS), a custom instance of the NASA Land Information System (LIS) framework. The FLDAS is routinely used to produce multi-model and multi-forcing estimates of hydro-climate states and fluxes over semi-arid, food insecure regions of Africa. These modeled data and derived products, like soil moisture percentiles and water availability, were designed and are currently used to complement FEWS NET’s operational remotely sensed rainfall, evapotranspiration, and vegetation observations. The 30+ years of monthly outputs from the FLDAS simulations are publicly available from the NASA Goddard Earth Science Data and Information Services Center (GES DISC) and recommended for use in hydroclimate studies, early warning applications, and by agro-meteorological scientists in Eastern, Southern, and Western Africa.

A land data assimilation system for sub-Saharan Africa food and water security applications.

PubMed

McNally, Amy; Arsenault, Kristi; Kumar, Sujay; Shukla, Shraddhanand; Peterson, Pete; Wang, Shugong; Funk, Chris; Peters-Lidard, Christa D; Verdin, James P

2017-02-14

Seasonal agricultural drought monitoring systems, which rely on satellite remote sensing and land surface models (LSMs), are important for disaster risk reduction and famine early warning. These systems require the best available weather inputs, as well as a long-term historical record to contextualize current observations. This article introduces the Famine Early Warning Systems Network (FEWS NET) Land Data Assimilation System (FLDAS), a custom instance of the NASA Land Information System (LIS) framework. The FLDAS is routinely used to produce multi-model and multi-forcing estimates of hydro-climate states and fluxes over semi-arid, food insecure regions of Africa. These modeled data and derived products, like soil moisture percentiles and water availability, were designed and are currently used to complement FEWS NET's operational remotely sensed rainfall, evapotranspiration, and vegetation observations. The 30+ years of monthly outputs from the FLDAS simulations are publicly available from the NASA Goddard Earth Science Data and Information Services Center (GES DISC) and recommended for use in hydroclimate studies, early warning applications, and by agro-meteorological scientists in Eastern, Southern, and Western Africa.

Data Descriptor: A Land Data Assimilation System for Sub-Saharan Africa Food and Water Security Applications

NASA Technical Reports Server (NTRS)

McNally, Amy; Arsenault, Krist; Kumar, Sujay; Shukla, Shraddhanand; Peter, Pete; Wang, Shugong; Funk, Chris; Peters-Lidard, Christa D.; Verdin, James

2017-01-01

Seasonal agricultural drought monitoring systems, which rely on satellite remote sensing and land surface models (LSMs), are important for disaster risk reduction and famine early warning. These systems require the best available weather inputs, as well as a long-term historical record to contextualize current observations. This article introduces the Famine Early Warning Systems Network (FEWS NET) Land Data Assimilation System (FLDAS), a custom instance of the NASA Land Information System (LIS) framework. The FLDAS is routinely used to produce multi-model and multi-forcing estimates of hydro-climate states and fluxes over semi-arid, food insecure regions of Africa. These modeled data and derived products, like soil moisture percentiles and water availability, were designed and are currently used to complement FEWSNETs operational remotely sensed rainfall, evapotranspiration, and vegetation observations. The 30+ years of monthly outputs from the FLDAS simulations are publicly available from the NASA Goddard Earth Science Data and Information Services Center (GES DISC) and recommended for use in hydroclimate studies, early warning applications, and by agro-meteorological scientists in Eastern, Southern, and Western Africa.

A land data assimilation system for sub-Saharan Africa food and water security applications

NASA Astrophysics Data System (ADS)

McNally, Amy; Arsenault, Kristi; Kumar, Sujay; Shukla, Shraddhanand; Peterson, Pete; Wang, Shugong; Funk, Chris; Peters-Lidard, Christa D.; Verdin, James P.

2017-02-01

Seasonal agricultural drought monitoring systems, which rely on satellite remote sensing and land surface models (LSMs), are important for disaster risk reduction and famine early warning. These systems require the best available weather inputs, as well as a long-term historical record to contextualize current observations. This article introduces the Famine Early Warning Systems Network (FEWS NET) Land Data Assimilation System (FLDAS), a custom instance of the NASA Land Information System (LIS) framework. The FLDAS is routinely used to produce multi-model and multi-forcing estimates of hydro-climate states and fluxes over semi-arid, food insecure regions of Africa. These modeled data and derived products, like soil moisture percentiles and water availability, were designed and are currently used to complement FEWS NET's operational remotely sensed rainfall, evapotranspiration, and vegetation observations. The 30+ years of monthly outputs from the FLDAS simulations are publicly available from the NASA Goddard Earth Science Data and Information Services Center (GES DISC) and recommended for use in hydroclimate studies, early warning applications, and by agro-meteorological scientists in Eastern, Southern, and Western Africa.

ICLUS Tools and Datasets (Version 1.3 & 1.3.1)

EPA Science Inventory

As a part of the Integrated Climate and Land Use Scenarios (ICLUS) project, this Geographic Information System (GIS) tool can be used to generate scenarios of housing-density changes and calculate impervious surface cover for the conterminous United States. The ICLUS User’s Guid...

Microbial Source Module (MSM): Documenting the Science and Software for Discovery, Evaluation, and Integration

EPA Science Inventory

The Microbial Source Module (MSM) estimates microbial loading rates to land surfaces from non-point sources, and to streams from point sources for each subwatershed within a watershed. A subwatershed, the smallest modeling unit, represents the common basis for information consume...

Impact of Soil Moisture Assimilation on Land Surface Model Spin-Up and Coupled LandAtmosphere Prediction

NASA Technical Reports Server (NTRS)

Santanello, Joseph A., Jr.; Kumar, Sujay V.; Peters-Lidard, Christa D.; Lawston, P.

2016-01-01

Advances in satellite monitoring of the terrestrial water cycle have led to a concerted effort to assimilate soil moisture observations from various platforms into offline land surface models (LSMs). One principal but still open question is that of the ability of land data assimilation (LDA) to improve LSM initial conditions for coupled short-term weather prediction. In this study, the impact of assimilating Advanced Microwave Scanning Radiometer for EOS (AMSR-E) soil moisture retrievals on coupled WRF Model forecasts is examined during the summers of dry (2006) and wet (2007) surface conditions in the southern Great Plains. LDA is carried out using NASAs Land Information System (LIS) and the Noah LSM through an ensemble Kalman filter (EnKF) approach. The impacts of LDA on the 1) soil moisture and soil temperature initial conditions for WRF, 2) land-atmosphere coupling characteristics, and 3) ambient weather of the coupled LIS-WRF simulations are then assessed. Results show that impacts of soil moisture LDA during the spin-up can significantly modify LSM states and fluxes, depending on regime and season. Results also indicate that the use of seasonal cumulative distribution functions (CDFs) is more advantageous compared to the traditional annual CDF bias correction strategies. LDA performs consistently regardless of atmospheric forcing applied, with greater improvements seen when using coarser, global forcing products. Downstream impacts on coupled simulations vary according to the strength of the LDA impact at the initialization, where significant modifications to the soil moisture flux- PBL-ambient weather process chain are observed. Overall, this study demonstrates potential for future, higher-resolution soil moisture assimilation applications in weather and climate research.

Reconstructing disturbance history for an intensively mined region by time-series analysis of Landsat imagery.

PubMed

Li, Jing; Zipper, Carl E; Donovan, Patricia F; Wynne, Randolph H; Oliphant, Adam J

2015-09-01

Surface mining disturbances have attracted attention globally due to extensive influence on topography, land use, ecosystems, and human populations in mineral-rich regions. We analyzed a time series of Landsat satellite imagery to produce a 28-year disturbance history for surface coal mining in a segment of eastern USA's central Appalachian coalfield, southwestern Virginia. The method was developed and applied as a three-step sequence: vegetation index selection, persistent vegetation identification, and mined-land delineation by year of disturbance. The overall classification accuracy and kappa coefficient were 0.9350 and 0.9252, respectively. Most surface coal mines were identified correctly by location and by time of initial disturbance. More than 8 % of southwestern Virginia's >4000-km(2) coalfield area was disturbed by surface coal mining over the 28-year period. Approximately 19.5 % of the Appalachian coalfield surface within the most intensively mined county (Wise County) has been disturbed by mining. Mining disturbances expanded steadily and progressively over the study period. Information generated can be applied to gain further insight concerning mining influences on ecosystems and other essential environmental features.

Integrated modelling of anthropogenic land-use and land-cover change on the global scale

NASA Astrophysics Data System (ADS)

Schaldach, R.; Koch, J.; Alcamo, J.

2009-04-01

In many cases land-use activities go hand in hand with substantial modifications of the physical and biological cover of the Earth's surface, resulting in direct effects on energy and matter fluxes between terrestrial ecosystems and the atmosphere. For instance, the conversion of forest to cropland is changing climate relevant surface parameters (e.g. albedo) as well as evapotranspiration processes and carbon flows. In turn, human land-use decisions are also influenced by environmental processes. Changing temperature and precipitation patterns for example are important determinants for location and intensity of agriculture. Due to these close linkages, processes of land-use and related land-cover change should be considered as important components in the construction of Earth System models. A major challenge in modelling land-use change on the global scale is the integration of socio-economic aspects and human decision making with environmental processes. One of the few global approaches that integrates functional components to represent both anthropogenic and environmental aspects of land-use change, is the LandSHIFT model. It simulates the spatial and temporal dynamics of the human land-use activities settlement, cultivation of food crops and grazing management, which compete for the available land resources. The rational of the model is to regionalize the demands for area intensive commodities (e.g. crop production) and services (e.g. space for housing) from the country-level to a global grid with the spatial resolution of 5 arc-minutes. The modelled land-use decisions within the agricultural sector are influenced by changing climate and the resulting effects on biomass productivity. Currently, this causal chain is modelled by integrating results from the process-based vegetation model LPJmL model for changing crop yields and net primary productivity of grazing land. Model output of LandSHIFT is a time series of grid maps with land-use/land-cover information that can serve as basis for further impact analysis. An exemplary simulation study with LandSHIFT is presented, based on scenario assumptions from the UNEP Global Environmental Outlook 4. Time horizon of the analysis is the year 2050. Changes of future food production on country level are computed by the agro-economy model IMPACT as a function of demography, economic development and global trade pattern. Together with scenario assumptions on climatic change and population growth, this data serves as model input to compute the changing land-use und land-cover. The continental and global scale model results are then analysed with respect to changes in the spatial pattern of natural vegetation as well as the resulting effects on evapotranspiration processes and land surface parameters. Furthermore, possible linkages of LandSHIFT to the different components of Earth System models (e.g. climate and natural vegetation) are discussed.

Constraining the JULES land-surface model for different land-use types using citizen-science generated hydrological data

NASA Astrophysics Data System (ADS)

Chou, H. K.; Ochoa-Tocachi, B. F.; Buytaert, W.

2017-12-01

Community land surface models such as JULES are increasingly used for hydrological assessment because of their state-of-the-art representation of land-surface processes. However, a major weakness of JULES and other land surface models is the limited number of land surface parameterizations that is available. Therefore, this study explores the use of data from a network of catchments under homogeneous land-use to generate parameter "libraries" to extent the land surface parameterizations of JULES. The network (called iMHEA) is part of a grassroots initiative to characterise the hydrological response of different Andean ecosystems, and collects data on streamflow, precipitation, and several weather variables at a high temporal resolution. The tropical Andes are a useful case study because of the complexity of meteorological and geographical conditions combined with extremely heterogeneous land-use that result in a wide range of hydrological responses. We then calibrated JULES for each land-use represented in the iMHEA dataset. For the individual land-use types, the results show improved simulations of streamflow when using the calibrated parameters with respect to default values. In particular, the partitioning between surface and subsurface flows can be improved. But also, on a regional scale, hydrological modelling was greatly benefitted from constraining parameters using such distributed citizen-science generated streamflow data. This study demonstrates the modelling and prediction on regional hydrology by integrating citizen science and land surface model. In the context of hydrological study, the limitation of data scarcity could be solved indeed by using this framework. Improved predictions of such impacts could be leveraged by catchment managers to guide watershed interventions, to evaluate their effectiveness, and to minimize risks.

Predicting risk of trace element pollution from municipal roads using site-specific soil samples and remotely sensed data.

PubMed

Reeves, Mari Kathryn; Perdue, Margaret; Munk, Lee Ann; Hagedorn, Birgit

2018-07-15

Studies of environmental processes exhibit spatial variation within data sets. The ability to derive predictions of risk from field data is a critical path forward in understanding the data and applying the information to land and resource management. Thanks to recent advances in predictive modeling, open source software, and computing, the power to do this is within grasp. This article provides an example of how we predicted relative trace element pollution risk from roads across a region by combining site specific trace element data in soils with regional land cover and planning information in a predictive model framework. In the Kenai Peninsula of Alaska, we sampled 36 sites (191 soil samples) adjacent to roads for trace elements. We then combined this site specific data with freely-available land cover and urban planning data to derive a predictive model of landscape scale environmental risk. We used six different model algorithms to analyze the dataset, comparing these in terms of their predictive abilities and the variables identified as important. Based on comparable predictive abilities (mean R 2 from 30 to 35% and mean root mean square error from 65 to 68%), we averaged all six model outputs to predict relative levels of trace element deposition in soils-given the road surface, traffic volume, sample distance from the road, land cover category, and impervious surface percentage. Mapped predictions of environmental risk from toxic trace element pollution can show land managers and transportation planners where to prioritize road renewal or maintenance by each road segment's relative environmental and human health risk. Published by Elsevier B.V.

The Martian Oasis Detector

NASA Astrophysics Data System (ADS)

Smith, P. H.; tomasko, M. G.; McEwen, A.; Rice, J.

2000-07-01

The next phase of unmanned Mars missions paves the way for astronauts to land on the surface of Mars. There are lessons to be learned from the unmanned precursor missions to the Moon and the Apollo lunar surface expeditions. These unmanned missions (Ranger, Lunar Orbiter, and Surveyor) provided the following valuable information, useful from both a scientific and engineering perspective, which was required to prepare the way for the manned exploration of the lunar surface: (1) high resolution imagery instrumental to Apollo landing site selection also tremendously advanced the state of Nearside and Farside regional geology; (2) demonstrated precision landing (less than two kilometers from target) and soft landing capability; (3) established that the surface had sufficient bearing strength to support a spacecraft; and (4) examination of the chemical composition and mechanical properties of the surface. The search for extinct or extant life on Mars will follow the water. However, geomorphic studies have shown that Mars has had liquid water on its surface throughout its geologic history. A cornucopia of potential landing sites with water histories (lakes, floodplains, oceans, deltas, hydrothermal regions) presently exist. How will we narrow down site selection and increase the likelihood of finding the signs of life? One way to do this is to identify 'Martian oases.' It is known that the Martian surface is often highly fractured and some areas have karst structures that support underground caves. Much of the water that formed the channels and valley networks is thought to be frozen underground. All that is needed to create the potential for liquid water is a near surface source of heat; recent lava flows and Martian meteorites attest to the potential for volcanic activity. If we can locate even one spot where fracturing, ice, and underground heat are co-located then we have the potential for an oasis. Such a discovery could truly excite the imaginations of both the public and Congress providing an attainable goal for both robotic and manned missions. The instrument required to detect an active oasis is a high spatial resolution (few tens of meters) Short Wavelength Infrared (SWIR) spectrometer coupled with a high resolution camera (five m/pixel). This combination creates too large a data volume to possibly return data for the entire Martian Surface; therefore it has been designed as one of the first in a new generation of 'smart' detectors, called the Mars Oasis Detector (MOD).

Estimating morning changes in land surface temperature from MODIS day/night land surface temperature: Applications for surface energy balance modeling

USDA-ARS?s Scientific Manuscript database

Observations of land surface temperature (LST) are crucial for the monitoring of surface energy fluxes from satellite. Methods that require high temporal resolution LST observations (e.g., from geostationary orbit) can be difficult to apply globally because several geostationary sensors are required...

A COUPLED LAND-SURFACE AND DRY DEPOSITION MODEL AND COMPARISON TO FIELD MEASUREMENTS OF SURFACE HEAT, MOISTURE, AND OZONE FLUXES

EPA Science Inventory

We have developed a coupled land-surface and dry deposition model for realistic treatment of surface fluxes of heat, moisture, and chemical dry deposition within a comprehensive air quality modeling system. A new land-surface model (LSM) with explicit treatment of soil moisture...

Analysis of passive microwave signatures over snow-covered mountainous area

NASA Astrophysics Data System (ADS)

Kim, R. S.; Durand, M. T.

2015-12-01

Accurate knowledge of snow distribution over mountainous area is critical for climate studies and the passive microwave(PM) measurements have been widely used and invested in order to obtain information about snowpack properties. Understanding and analyzing the signatures for the explicit inversion of the remote sensing data from land surfaces is required for successful using of passive microwave sensors but this task is often ambiguous due to the large variability of physical conditions and object types. In this paper, we discuss the pattern of measured brightness temperatures and emissivities at vertical and horizontal polarization over the frequency range of 10.7 to 89 GHz of land surfaces under various snow and vegetation conditions. The Multiband polarimetric Scanning Radiometer(PSR) imagery is used over NASA Cold Land Processes Field Experiment(CLPX) study area with ground-based measurements of snow depth and snow properties. Classification of snow under various conditions in mountainous area is implemented based on different patterns of microwave signatures.

NASA Satellite Captures Super Bowl Cities - Denver, CO

NASA Image and Video Library

2016-02-06

Landsat 7 image of Denver area acquired Nov 3, 2015. Landsat 7 is a U.S. satellite used to acquire remotely sensed images of the Earth's land surface and surrounding coastal regions. It is maintained by the Landsat 7 Project Science Office at the NASA Goddard Space Flight Center in Greenbelt, MD...Landsat satellites have been acquiring images of the Earth’s land surface since 1972. Currently there are more than 2 million Landsat images in the National Satellite Land Remote Sensing Data Archive. For more information visit: landsat.usgs.gov/..To learn more about the Landsat satellite go to:.landsat.gsfc.nasa.gov/ Credit: NASA/GSFC/Landsat 7 NASA image use policy. NASA Goddard Space Flight Center enables NASA’s mission through four scientific endeavors: Earth Science, Heliophysics, Solar System Exploration, and Astrophysics. Goddard plays a leading role in NASA’s accomplishments by contributing compelling scientific knowledge to advance the Agency’s mission. Follow us on Twitter Like us on Facebook Find us on Instagram

NASA Satellite Captures Super Bowl Cities - Santa Clara, CA

NASA Image and Video Library

2017-12-08

Landsat 7 image of the Santa Clara area acquired Nov 16, 2015. Landsat 7 is a U.S. satellite used to acquire remotely sensed images of the Earth's land surface and surrounding coastal regions. It is maintained by the Landsat 7 Project Science Office at the NASA Goddard Space Flight Center in Greenbelt, MD...Landsat satellites have been acquiring images of the Earth’s land surface since 1972. Currently there are more than 2 million Landsat images in the National Satellite Land Remote Sensing Data Archive. For more information visit: landsat.usgs.gov/..To learn more about the Landsat satellite go to:.landsat.gsfc.nasa.gov/ Credit: NASA/GSFC/Landsat 7 NASA image use policy. NASA Goddard Space Flight Center enables NASA’s mission through four scientific endeavors: Earth Science, Heliophysics, Solar System Exploration, and Astrophysics. Goddard plays a leading role in NASA’s accomplishments by contributing compelling scientific knowledge to advance the Agency’s mission. Follow us on Twitter Like us on Facebook Find us on Instagram

NASA Satellite Captures Super Bowl Cities - Boston/Providence [annotated

NASA Image and Video Library

2015-01-30

Landsat 7 image of Boston/Providence area acquired August 25, 2014. Landsat 7 is a U.S. satellite used to acquire remotely sensed images of the Earth's land surface and surrounding coastal regions. It is maintained by the Landsat 7 Project Science Office at the NASA Goddard Space Flight Center in Greenbelt, MD. Landsat satellites have been acquiring images of the Earth’s land surface since 1972. Currently there are more than 2 million Landsat images in the National Satellite Land Remote Sensing Data Archive. For more information visit: landsat.usgs.gov/..To learn more about the Landsat satellite go to:.landsat.gsfc.nasa.gov/ Credit: NASA/GSFC/Landsat 7 NASA image use policy. NASA Goddard Space Flight Center enables NASA’s mission through four scientific endeavors: Earth Science, Heliophysics, Solar System Exploration, and Astrophysics. Goddard plays a leading role in NASA’s accomplishments by contributing compelling scientific knowledge to advance the Agency’s mission. Follow us on Twitter Like us on Facebook Find us on Instagram

NASA Satellite Captures Super Bowl Cities - Seattle

NASA Image and Video Library

2015-01-30

Landsat 7 image of Seattle, Washington acquired August 23, 2014. Landsat 7 is a U.S. satellite used to acquire remotely sensed images of the Earth's land surface and surrounding coastal regions. It is maintained by the Landsat 7 Project Science Office at the NASA Goddard Space Flight Center in Greenbelt, MD. Landsat satellites have been acquiring images of the Earth’s land surface since 1972. Currently there are more than 2 million Landsat images in the National Satellite Land Remote Sensing Data Archive. For more information visit: landsat.usgs.gov/..To learn more about the Landsat satellite go to:.landsat.gsfc.nasa.gov/ Credit: NASA/GSFC/Landsat 7 NASA image use policy. NASA Goddard Space Flight Center enables NASA’s mission through four scientific endeavors: Earth Science, Heliophysics, Solar System Exploration, and Astrophysics. Goddard plays a leading role in NASA’s accomplishments by contributing compelling scientific knowledge to advance the Agency’s mission. Follow us on Twitter Like us on Facebook Find us on Instagram

NASA Satellite Captures Super Bowl Cities - Seattle [annotated

NASA Image and Video Library

2015-01-30

Landsat 7 image of Seattle, Washington acquired August 23, 2014. Landsat 7 is a U.S. satellite used to acquire remotely sensed images of the Earth's land surface and surrounding coastal regions. It is maintained by the Landsat 7 Project Science Office at the NASA Goddard Space Flight Center in Greenbelt, MD. Landsat satellites have been acquiring images of the Earth’s land surface since 1972. Currently there are more than 2 million Landsat images in the National Satellite Land Remote Sensing Data Archive. For more information visit: landsat.usgs.gov/..To learn more about the Landsat satellite go to:.landsat.gsfc.nasa.gov/ Credit: NASA/GSFC/Landsat 7 NASA image use policy. NASA Goddard Space Flight Center enables NASA’s mission through four scientific endeavors: Earth Science, Heliophysics, Solar System Exploration, and Astrophysics. Goddard plays a leading role in NASA’s accomplishments by contributing compelling scientific knowledge to advance the Agency’s mission. Follow us on Twitter Like us on Facebook Find us on Instagram

NASA Satellite Captures Super Bowl Cities - Phoenix

NASA Image and Video Library

2015-01-30

Landsat 7 image of Phoenix, Arizona acquired November 28, 2014. Landsat 7 is a U.S. satellite used to acquire remotely sensed images of the Earth's land surface and surrounding coastal regions. It is maintained by the Landsat 7 Project Science Office at the NASA Goddard Space Flight Center in Greenbelt, MD. Landsat satellites have been acquiring images of the Earth’s land surface since 1972. Currently there are more than 2 million Landsat images in the National Satellite Land Remote Sensing Data Archive. For more information visit: landsat.usgs.gov/..To learn more about the Landsat satellite go to:.landsat.gsfc.nasa.gov/ Credit: NASA/GSFC/Landsat 7 NASA image use policy. NASA Goddard Space Flight Center enables NASA’s mission through four scientific endeavors: Earth Science, Heliophysics, Solar System Exploration, and Astrophysics. Goddard plays a leading role in NASA’s accomplishments by contributing compelling scientific knowledge to advance the Agency’s mission. Follow us on Twitter Like us on Facebook Find us on Instagram

NASA Satellite Captures Super Bowl Cities - Boston/Providence

NASA Image and Video Library

2015-01-30

Landsat 7 image of Boston/Providence area acquired August 25, 2014. Landsat 7 is a U.S. satellite used to acquire remotely sensed images of the Earth's land surface and surrounding coastal regions. It is maintained by the Landsat 7 Project Science Office at the NASA Goddard Space Flight Center in Greenbelt, MD...Landsat satellites have been acquiring images of the Earth’s land surface since 1972. Currently there are more than 2 million Landsat images in the National Satellite Land Remote Sensing Data Archive. For more information visit: landsat.usgs.gov/..To learn more about the Landsat satellite go to:.landsat.gsfc.nasa.gov/ Credit: NASA/GSFC/Landsat 7 NASA image use policy. NASA Goddard Space Flight Center enables NASA’s mission through four scientific endeavors: Earth Science, Heliophysics, Solar System Exploration, and Astrophysics. Goddard plays a leading role in NASA’s accomplishments by contributing compelling scientific knowledge to advance the Agency’s mission. Follow us on Twitter Like us on Facebook Find us on Instagram

NASA Satellite Captures Super Bowl Cities - Phoenix [annotated

NASA Image and Video Library

2015-01-30

Landsat 7 image of Phoenix, Arizona acquired November 28, 2014. Landsat 7 is a U.S. satellite used to acquire remotely sensed images of the Earth's land surface and surrounding coastal regions. It is maintained by the Landsat 7 Project Science Office at the NASA Goddard Space Flight Center in Greenbelt, MD. Landsat satellites have been acquiring images of the Earth’s land surface since 1972. Currently there are more than 2 million Landsat images in the National Satellite Land Remote Sensing Data Archive. For more information visit: landsat.usgs.gov/..To learn more about the Landsat satellite go to:.landsat.gsfc.nasa.gov/ Credit: NASA/GSFC/Landsat 7 NASA image use policy. NASA Goddard Space Flight Center enables NASA’s mission through four scientific endeavors: Earth Science, Heliophysics, Solar System Exploration, and Astrophysics. Goddard plays a leading role in NASA’s accomplishments by contributing compelling scientific knowledge to advance the Agency’s mission. Follow us on Twitter Like us on Facebook Find us on Instagram

NASA Satellite Captures Super Bowl Cities - Charlotte, NC

NASA Image and Video Library

2016-02-06

Landsat 7 image of the Charlotte, NC area acquired Oct 18, 2015. Landsat 7 is a U.S. satellite used to acquire remotely sensed images of the Earth's land surface and surrounding coastal regions. It is maintained by the Landsat 7 Project Science Office at the NASA Goddard Space Flight Center in Greenbelt, MD...Landsat satellites have been acquiring images of the Earth’s land surface since 1972. Currently there are more than 2 million Landsat images in the National Satellite Land Remote Sensing Data Archive. For more information visit: landsat.usgs.gov/..To learn more about the Landsat satellite go to:.landsat.gsfc.nasa.gov/ Credit: NASA/GSFC/Landsat 7 NASA image use policy. NASA Goddard Space Flight Center enables NASA’s mission through four scientific endeavors: Earth Science, Heliophysics, Solar System Exploration, and Astrophysics. Goddard plays a leading role in NASA’s accomplishments by contributing compelling scientific knowledge to advance the Agency’s mission. Follow us on Twitter Like us on Facebook Find us on Instagram

The Impact of Soil Moisture Initialization On Seasonal Precipitation Forecasts

NASA Technical Reports Server (NTRS)

Koster, R. D.; Suarez, M. J.; Tyahla, L.; Houser, Paul (Technical Monitor)

2002-01-01

Some studies suggest that the proper initialization of soil moisture in a forecasting model may contribute significantly to the accurate prediction of seasonal precipitation, especially over mid-latitude continents. In order for the initialization to have any impact at all, however, two conditions must be satisfied: (1) the initial soil moisture anomaly must be "remembered" into the forecasted season, and (2) the atmosphere must respond in a predictable way to the soil moisture anomaly. In our previous studies, we identified the key land surface and atmospheric properties needed to satisfy each condition. Here, we tie these studies together with an analysis of an ensemble of seasonal forecasts. Initial soil moisture conditions for the forecasts are established by forcing the land surface model with realistic precipitation prior to the start of the forecast period. As expected, the impacts on forecasted precipitation (relative to an ensemble of runs that do not utilize soil moisture information) tend to be localized over the small fraction of the earth with all of the required land and atmosphere properties.

Insights on How NASA's Earth Observing System (EOS) Monitors Our World Environment

NASA Technical Reports Server (NTRS)

King, Michael D.

2000-01-01

The Earth Observing System (EOS) is a space-based observing system comprised of a series of satellite sensors by which scientists can monitor the Earth, a Data and Information System (EOSDIS) enabling researchers worldwide to access the satellite data, and an interdisciplinary science research program to interpret the satellite data. During this year, four EOS science missions were launched, representing observations of (1) total solar irradiance, (2) Earth radiation budget, (3) land cover and land use change, (4) ocean processes (vector wind, sea surface temperature, and ocean color), (5) atmospheric processes (aerosol and cloud properties, water vapor, and temperature and moisture profiles), and (6) tropospheric chemistry. In succeeding years many more satellites will be launched that will contribute immeasurably to our understanding of the Earth's environment. In this presentation I will describe how scientists are using EOS data to examine land use and natural hazards, environmental air quality, including dust storms over the world's deserts, cloud and radiation properties, sea surface temperature, and winds over the ocean.

Disentangling Climate and Land-use Impacts on Grassland Carbon and Water Fluxes

NASA Astrophysics Data System (ADS)

Brunsell, N. A.; Nippert, J. B.

2014-12-01

Regional climate and land cover interact in a complex, non-linear manner to alter the local cycling of mass and energy. It is often difficult to isolate the role of either mechanism on the resultant fluxes. Here, we attempt to isolate these mechanisms through the use of network of 4 Ameriflux eddy covariance towers installed over different land cover and land use classes along a pronounced rainfall gradient. The land cover types include: annually burned C4 grassland, a 4 year burn site experiencing woody encroachment, an abandoned agricultural field and a new perennial agricultural site. We investigated the impact of rainfall variability, drought, and heat waves on the water and carbon budgets using data analysis, remote sensing, and modeling approaches. In addition, we have established a network of mini-meteorological stations at the annually and 4-year burn sites to assess micro-scale variability within the footprints of the towers as a function of topographic position, soil depth and soil water availability. Through the use of a wavelet multiscale decomposition and information theory metrics, we have isolated the role of environmental factors (temperature, humidity, soil moisture, etc.) on the fluxes across the different sites. By applying a similar analysis to model output, we can assess the ability of land-surface models to recreate the observed sensitity. Results indicate the utility of a network of measurement systems used in conjunction with land surface modeling and time series analysis to assess differential impacts to similar regional scale climate forcings. Implications for the role of land cover class in regional and global scale modeling systems will also be discussed.

Climate and the equilibrium state of land surface hydrology parameterizations

NASA Technical Reports Server (NTRS)

Entekhabi, Dara; Eagleson, Peter S.

1991-01-01

For given climatic rates of precipitation and potential evaporation, the land surface hydrology parameterizations of atmospheric general circulation models will maintain soil-water storage conditions that balance the moisture input and output. The surface relative soil saturation for such climatic conditions serves as a measure of the land surface parameterization state under a given forcing. The equilibrium value of this variable for alternate parameterizations of land surface hydrology are determined as a function of climate and the sensitivity of the surface to shifts and changes in climatic forcing are estimated.

Sensitivity of the WRF model to the lower boundary in an extreme precipitation event - Madeira island case study

NASA Astrophysics Data System (ADS)

Teixeira, J. C.; Carvalho, A. C.; Carvalho, M. J.; Luna, T.; Rocha, A.

2014-08-01

The advances in satellite technology in recent years have made feasible the acquisition of high-resolution information on the Earth's surface. Examples of such information include elevation and land use, which have become more detailed. Including this information in numerical atmospheric models can improve their results in simulating lower boundary forced events, by providing detailed information on their characteristics. Consequently, this work aims to study the sensitivity of the weather research and forecast (WRF) model to different topography as well as land-use simulations in an extreme precipitation event. The test case focused on a topographically driven precipitation event over the island of Madeira, which triggered flash floods and mudslides in the southern parts of the island. Difference fields between simulations were computed, showing that the change in the data sets produced statistically significant changes to the flow, the planetary boundary layer structure and precipitation patterns. Moreover, model results show an improvement in model skill in the windward region for precipitation and in the leeward region for wind, in spite of the non-significant enhancement in the overall results with higher-resolution data sets of topography and land use.

Multi-temporal analysis of land surface temperature in highly urbanized districts

NASA Astrophysics Data System (ADS)

Kaya, S.; Celik, B.; Sertel, E.; Bayram, B.; Seker, D. Z.

2017-12-01

Istanbul is one of the largest cities around the world with population over 15 million and it has 39 districts. Due to high immigration rate after the 1980s, parallel to the urbanization rapid population increase has occurred in some of these districts. Thus, a significant increase in land surface temperature were monitored and this subject became one of the most popular subject of different researches. Natural landscapes transformed into residential areas with impervious surfaces that causes rise in land surface temperatures which is one of the component of urban heat islands. This study focuses on determining the land use/land cover changes and land surface temperature in highly urbanized districts for last 32 years and examining the relationship between these two parameters using multi-temporal optical and thermal remotely sensed data. In this study, Landsat5 Thematic Mapper and Landsat8 OLI/TIR imagery with acquisition dates June 1984 and June 2016 were used. In order to assess the land use/cover change between 1984 and 2016, Vegetation Impervious Surface-soil (V-I-S) model is used. Each end-member spectra are extracted from ASTER spectral library. Additionally, V-I-S model, NDVI, NDBI and NDBaI indices have been derived for further investigation of land cover changes. The results of the study, presented that in the last 32 years, the amount of impervious surfaces substantially increased along with land surface temperatures.

Earth Observing System: Information on NASA’s Incorporation of Existing Data Into EOSDIS

DTIC Science & Technology

1992-09-25

oceanography, and marine resources can be derived from this data set. The Landsat Pathfinder Project comprises three separate activities, two of which...contain informnation about atmospheric properties such as water vapor and rain rate, ocean surface properties such as surface wind speed, and land...Ferrari, Assignment Manager anagement and Elizabeth L. Johnston, Evaluator-in-Charge ,chnology Division, ashington, D.C. Page 11 GAO/ AMTEC -92-79 Earth

Distributed parameterization of complex terrain

NASA Astrophysics Data System (ADS)

Band, Lawrence E.

1991-03-01

This paper addresses the incorporation of high resolution topography, soils and vegetation information into the simulation of land surface processes in atmospheric circulation models (ACM). Recent work has concentrated on detailed representation of one-dimensional exchange processes, implicitly assuming surface homogeneity over the atmospheric grid cell. Two approaches that could be taken to incorporate heterogeneity are the integration of a surface model over distributed, discrete portions of the landscape, or over a distribution function of the model parameters. However, the computational burden and parameter intensive nature of current land surface models in ACM limits the number of independent model runs and parameterizations that are feasible to accomplish for operational purposes. Therefore, simplications in the representation of the vertical exchange processes may be necessary to incorporate the effects of landscape variability and horizontal divergence of energy and water. The strategy is then to trade off the detail and rigor of point exchange calculations for the ability to repeat those calculations over extensive, complex terrain. It is clear the parameterization process for this approach must be automated such that large spatial databases collected from remotely sensed images, digital terrain models and digital maps can be efficiently summarized and transformed into the appropriate parameter sets. Ideally, the landscape should be partitioned into surface units that maximize between unit variance while minimizing within unit variance, although it is recognized that some level of surface heterogeneity will be retained at all scales. Therefore, the geographic data processing necessary to automate the distributed parameterization should be able to estimate or predict parameter distributional information within each surface unit.

Land Surface Precipitation and Hydrology in MERRA-2

NASA Technical Reports Server (NTRS)

Reichle, R.; Koster, R.; Draper, C.; Liu, Q.; Girotto, M.; Mahanama, S.; De Lannoy, G.; Partyka, G.

2017-01-01

The Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2), provides global, 1-hourly estimates of land surface conditions for 1980-present at 50-km resolution. Outside of the high latitudes, MERRA-2 uses observations-based precipitation data products to correct the precipitation falling on the land surface. This paper describes the precipitation correction method and evaluates the MERRA-2 land surface precipitation and hydrology. Compared to monthly GPCPv2.2 observations, the corrected MERRA-2 precipitation (M2CORR) is better than the precipitation generated by the atmospheric models within the cyclingMERRA-2 system and the earlier MERRA reanalysis. Compared to 3-hourlyTRMM observations, the M2CORR diurnal cycle has better amplitude but less realistic phasing than MERRA-2 model-generated precipitation. Because correcting the precipitation within the coupled atmosphere-land modeling system allows the MERRA-2 near-surface air temperature and humidity to respond to the improved precipitation forcing, MERRA-2 provides more self-consistent surface meteorological data than were available from the earlier, offline MERRA-Land reanalysis. Overall, MERRA-2 land hydrology estimates are better than those of MERRA-Land and MERRA. A comparison against GRACE satellite observations of terrestrial water storage demonstrates clear improvements in MERRA-2 over MERRA in South America and Africa but also reflects known errors in the observations used to correct the MERRA-2 precipitation. The MERRA-2 and MERRA-Land surface and root zone soil moisture skill vs. in situ measurements is slightly higher than that of ERA-Interim Land and higher than that of MERRA (significantly for surface soil moisture). Snow amounts from MERRA-2 have lower bias and correlate better against reference data than do those of MERRA-Land and MERRA, with MERRA-2 skill roughly matching that of ERA-Interim Land. Seasonal anomaly R values against naturalized stream flow measurements in the United States are, on balance, highest for MERRA-2 and ERA-Interim Land, somewhat lower for MERRA-Land, and lower still for MERRA.

Utility of a Two-source Energy Balance Approach for Daily Mapping of Landsat-scale Fluxes Over Irrigated Agriculture in a Desert Environment

NASA Astrophysics Data System (ADS)

Houborg, R.; McCabe, M. F.; Rosas Aguilar, J.; Anderson, M. C.; Hain, C.

2014-12-01

The Middle East and North Africa (MENA) region is an area characterized by limited fresh water resources, an often inefficient use of these, and relatively poor in-situ monitoring as a result of sparse meteorological observations. Enhanced satellite-based monitoring systems are needed for aiding local water resource and agricultural management activities in these data poor arid environments. A multi-sensor and multi-scale land-surface flux monitoring capacity is being implemented over parts of MENA in order to provide meaningful decision support at relevant spatiotemporal scales. The integrated modeling system uses the Atmosphere-Land Exchange Inverse (ALEXI) model and associated flux disaggregation scheme (DisALEXI), and the Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM) in conjunction with model reanalysis data and remotely sensed data from polar orbiting (Landsat and MODIS; MODerate resolution Imaging Spectroradiometer) and geostationary (MSG; Meteosat Second Generation) satellite platforms to facilitate daily estimates of land surface fluxes down to sub-field scale (i.e. 30 m). Within this modeling system, thermal infrared satellite data provide information about the sub-surface moisture status and plant stress, obviating the need for precipitation input and error-prone soil surface characterizations. In this study, the integrated ALEXI-DisALEXI-STARFM framework is applied over an irrigated agricultural region in Saudi Arabia, and the daily estimates of Landsat scale water, energy and carbon fluxes are evaluated against available flux tower observations and other independent in-situ and satellite-based records. The study addresses the challenges associated with time-continuous sub-field scale mapping of land-surface fluxes in a harsh desert environment, and looks into the optimization of model descriptions and parameterizations and meteorological forcing and vegetation inputs for application over these regions.

Applications of the Atmosphere-Land Exchange Inverse (ALEXI) Model and Highlights of Current Projects

NASA Astrophysics Data System (ADS)

Hain, C.; Mecikalski, J. R.; Schultz, L. A.

2009-12-01

The Atmosphere-Land Exchange Inverse (ALEXI) model was developed as an auxiliary means for estimating surface fluxes over large regions primarily using remote-sensing data. The model is unique in that no information regarding antecedent precipitation or moisture storage capacity is required - the surface moisture status is deduced from a radiometric temperature change signal. ALEXI uses the available water fraction (fAW) as a proxy for soil moisture conditions. Combining fAW with ALEXI’s ability to provide valuable information about the partitioning of the surface energy budget, which can dictated largely by soil moisture conditions, accommodates the retrieval of an average fAW from the surface to the rooting depth of the active vegetation. Using this approach has many advantages over traditional energy flux and soil moisture measurements (towers with limited range and large monetary/personnel costs) or approximation methods (parametrization of the relationship between available water and soil moisture) in that data is available both spatially and temporal over a large, non-homogeneous, sometimes densely vegetated area. Being satellite based, the model can be run anywhere thermal infrared satellite information is available. The current ALEXI climatology dates back to March 2000 and covers the continental U.S. Examples of projects underway using the ALEXI soil moisture retrieval tools include the Southern Florida Water Management Project; NASA’s Project Nile, which proposes to acquire hydrological information for the water management in the Nile River basin; and a USDA pro ject to expand the ALEXI framework to include Europe and parts of northern Africa using data from the European geostationary satellites, specifically the Meteosat Second Generation (MSG) Series.

Maps showing water-level declines, land subsidence, and earth fissures in south-central Arizona

USGS Publications Warehouse

Laney, R.L.; Raymond, R.H.; Winikka, C.C.

1978-01-01

From 1915 to 1975, more than 109 million acre-feet of ground water was withdrawn from about 4,500 square miles in Pinal and Maricopa Counties in south-central Arizona. The volume of water withdrawn greatly exceeds the volume of natural recharge, and water levels have been declining since 1923. As a result of the water-level declines, the land surface has subsided, the alluvial deposits have been subjected to stress, and earth fissures have developed. Land subsidence and earth fissures have damaged public and private properties. Subsidence and fissures will continue to occur as long as ground water is being mined and water levels continue to decline. As urban development expands, land subsidence and earth fissures will have an increasing socioeconomic impact. Information on maps includes change in water levels, measurements of land subsidence, and location of earth fissures. A section showing land subsidence between Casa Grande and the Picacho Peak Interchange also is included. Scale 1:250,000. (Woodard-USGS)

Apollo Video Photogrammetry Estimation Of Plume Impingement Effects

NASA Technical Reports Server (NTRS)

Immer, Christopher; Lane, John; Metzger, Philip T.; Clements, Sandra

2008-01-01

The Constellation Project's planned return to the moon requires numerous landings at the same site. Since the top few centimeters are loosely packed regolith, plume impingement from the Lander ejects the granular material at high velocities. Much work is needed to understand the physics of plume impingement during landing in order to protect hardware surrounding the landing sites. While mostly qualitative in nature, the Apollo Lunar Module landing videos can provide a wealth of quantitative information using modem photogrammetry techniques. The authors have used the digitized videos to quantify plume impingement effects of the landing exhaust on the lunar surface. The dust ejection angle from the plume is estimated at 1-3 degrees. The lofted particle density is estimated at 10(exp 8)- 10(exp 13) particles per cubic meter. Additionally, evidence for ejection of large 10-15 cm sized objects and a dependence of ejection angle on thrust are presented. Further work is ongoing to continue quantitative analysis of the landing videos.

Surface Hydrology in Global River Basins in the Off-Line Land-Surface GEOS Assimilation (OLGA) System

NASA Technical Reports Server (NTRS)

Bosilovich, Michael G.; Yang, Runhua; Houser, Paul R.

1998-01-01

Land surface hydrology for the Off-line Land-surface GEOS Analysis (OLGA) system and Goddard Earth Observing System (GEOS-1) Data Assimilation System (DAS) has been examined using a river routing model. The GEOS-1 DAS land-surface parameterization is very simple, using an energy balance prediction of surface temperature and prescribed soil water. OLGA uses near-surface atmospheric data from the GEOS-1 DAS to drive a more comprehensive parameterization of the land-surface physics. The two global systems are evaluated using a global river routing model. The river routing model uses climatologic surface runoff from each system to simulate the river discharge from global river basins, which can be compared to climatologic river discharge. Due to the soil hydrology, the OLGA system shows a general improvement in the simulation of river discharge compared to the GEOS-1 DAS. Snowmelt processes included in OLGA also have a positive effect on the annual cycle of river discharge and source runoff. Preliminary tests of a coupled land-atmosphere model indicate improvements to the hydrologic cycle compared to the uncoupled system. The river routing model has provided a useful tool in the evaluation of the GCM hydrologic cycle, and has helped quantify the influence of the more advanced land surface model.

Study on the cloud detection of GOCI by using the simulated surface reflectance from BRDF-model for the land application and meteorological utilization

NASA Astrophysics Data System (ADS)

Kim, Hye-Won; Yeom, Jong-Min; Woo, Sun-Hee; Chae, Tae-Byeong

2016-04-01

COMS (Communication, Ocean, and Meteorological Satellite) was launched at French Guiana Kourou space center on 27 June 2010. Geostationary Ocean Color Imager (GOCI), which is the first ocean color geostationary satellite in the world for observing the ocean phenomena, is able to obtain the scientific data per an hour from 00UTC to 07UTC. Moreover, the spectral channels of GOCI would enable not only monitoring for the ocean, but for extracting the information of the land surface over the Korean Peninsula, Japan, and Eastern China. Since it is extremely important to utilize GOCI data accurately for the land application, cloud pixels over the surface have to be removed. Unfortunately, infra-red (IR) channels that can easily detect the water vapor with the cloud top temperature, are not included in the GOCI sensor. In this paper, the advanced cloud masking algorithm will be proposed with visible and near-IR (NIR) bands that are within GOCI bands. The main obstacle of cloud masking with GOCI is how to handle the high variable surface reflectance, which is mainly depending on the solar zenith angle. In this study, we use semi-empirical BRDF model to simulate the surface reflectance by using 16 day composite cloudy free image. When estimating the simulated surface reflectance, same geometry for GOCI observation was applied. The simulated surface reflectance is used to discriminate cloud areas especially for the thin cloud and shows more reasonable result than original threshold methods.

A Framework for Land Cover Classification Using Discrete Return LiDAR Data: Adopting Pseudo-Waveform and Hierarchical Segmentation

NASA Technical Reports Server (NTRS)

Jung, Jinha; Pasolli, Edoardo; Prasad, Saurabh; Tilton, James C.; Crawford, Melba M.

2014-01-01

Acquiring current, accurate land-use information is critical for monitoring and understanding the impact of anthropogenic activities on natural environments.Remote sensing technologies are of increasing importance because of their capability to acquire information for large areas in a timely manner, enabling decision makers to be more effective in complex environments. Although optical imagery has demonstrated to be successful for land cover classification, active sensors, such as light detection and ranging (LiDAR), have distinct capabilities that can be exploited to improve classification results. However, utilization of LiDAR data for land cover classification has not been fully exploited. Moreover, spatial-spectral classification has recently gained significant attention since classification accuracy can be improved by extracting additional information from the neighboring pixels. Although spatial information has been widely used for spectral data, less attention has been given to LiDARdata. In this work, a new framework for land cover classification using discrete return LiDAR data is proposed. Pseudo-waveforms are generated from the LiDAR data and processed by hierarchical segmentation. Spatial featuresare extracted in a region-based way using a new unsupervised strategy for multiple pruning of the segmentation hierarchy. The proposed framework is validated experimentally on a real dataset acquired in an urban area. Better classification results are exhibited by the proposed framework compared to the cases in which basic LiDAR products such as digital surface model and intensity image are used. Moreover, the proposed region-based feature extraction strategy results in improved classification accuracies in comparison with a more traditional window-based approach.

Estimating surface fluxes over middle and upper streams of the Heihe River Basin with ASTER imagery

NASA Astrophysics Data System (ADS)

Ma, W.; Ma, Y.; Hu, Z.; Su, Z.; Wang, J.; Ishikawa, H.

2011-05-01

Land surface heat fluxes are essential measures of the strengths of land-atmosphere interactions involving energy, heat and water. Correct parameterization of these fluxes in climate models is critical. Despite their importance, state-of-the-art observation techniques cannot provide representative areal averages of these fluxes comparable to the model grid. Alternative methods of estimation are thus required. These alternative approaches use (satellite) observables of the land surface conditions. In this study, the Surface Energy Balance System (SEBS) algorithm was evaluated in a cold and arid environment, using land surface parameters derived from Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) data. Field observations and estimates from SEBS were compared in terms of net radiation flux (Rn), soil heat flux (G0), sensible heat flux (H) and latent heat flux (λE) over a heterogeneous land surface. As a case study, this methodology was applied to the experimental area of the Watershed Allied Telemetry Experimental Research (WATER) project, located on the mid-to-upstream sections of the Heihe River in northwest China. ASTER data acquired between 3 May and 4 June 2008, under clear-sky conditions were used to determine the surface fluxes. Ground-based measurements of land surface heat fluxes were compared with values derived from the ASTER data. The results show that the derived surface variables and the land surface heat fluxes furnished by SEBS in different months over the study area are in good agreement with the observed land surface status under the limited cases (some cases looks poor results). So SEBS can be used to estimate turbulent heat fluxes with acceptable accuracy in areas where there is partial vegetation cover in exceptive conditions. It is very important to perform calculations using ground-based observational data for parameterization in SEBS in the future. Nevertheless, the remote-sensing results can provide improved explanations of land surface fluxes over varying land coverage at greater spatial scales.

Coal Fields and Federal Lands of the Conterminous United States

USGS Publications Warehouse

Biewick, Laura

1997-01-01

The map depicts the relationship of coal and public lands in the conterminous U. S. Multiple GIS layers are being created for the purpose of deriving estimates of how much coal is owned and administered by the Federal government. Federal coal areas have a profound effect on land-management decisions. Regulatory agencies attempt to balance energy development with alternative land-use and environmental concerns. A GIS database of Federal lands used in energy resource assessments is being developed by the U. S. Geological Survey (USGS) in cooperation with the U.S. Bureau of Land Management (BLM) to integrate information on status of public land, and minerals owned by the Federal government with geologic information on coal resources, other spatial data, coal quality characteristics, and coal availability for development. Using national-scale data we estimate that approximately 60 percent of the area underlain by coal-bearing rocks in the conterminous United States are under Federal surface. Coal produced from Federal leases has tripled from about 12 percent of the total U.S. production in 1976 to almost 34 percent in 1995 (Energy Information Administration website ftp://ftp.eia.doe.gov/pub/coal/cia_95_tables/t13p01.txt). The reason for this increase is demand for low-sulfur coal for use in power plants and the fact that large reserves of this low-sulfur coal are in the western interior U.S., where the Federal government owns the rights to most of the coal reserves. The map was created using Arc/Info 7.0.3 on a UNIX system. The HPGL2 plot file for this map is available from the USGS Energy Resource Surveys Team from http://energy.cr.usgs.gov:8080/energy/coal.html.

Advanced Land Surface Processes in the Coupled WRF/CMAQ with MODIS Input

EPA Science Inventory

Land surface modeling (LSM) is important in WRF/CMAQ for simulating the exchange of heat, moisture, momentum, trace atmospheric chemicals, and windblown dust between the land surface and the atmosphere.? Vegetation and soil treatments are crucial in LSM for surface energy budgets...

Land surface sensitivity of monsoon depressions formed over Bay of Bengal using improved high-resolution land state

NASA Astrophysics Data System (ADS)

Rajesh, P. V.; Pattnaik, S.; Mohanty, U. C.; Rai, D.; Baisya, H.; Pandey, P. C.

2017-12-01

Monsoon depressions (MDs) constitute a large fraction of the total rainfall during the Indian summer monsoon season. In this study, the impact of high-resolution land state is addressed by assessing the evolution of inland moving depressions formed over the Bay of Bengal using a mesoscale modeling system. Improved land state is generated using High Resolution Land Data Assimilation System employing Noah-MP land-surface model. Verification of soil moisture using Soil Moisture and Ocean Salinity (SMOS) and soil temperature using tower observations demonstrate promising results. Incorporating high-resolution land state yielded least root mean squared errors with higher correlation coefficient in the surface and mid tropospheric parameters. Rainfall forecasts reveal that simulations are spatially and quantitatively in accordance with observations and provide better skill scores. The improved land surface characteristics have brought about the realistic evolution of surface, mid-tropospheric parameters, vorticity and moist static energy that facilitates the accurate MDs dynamics in the model. Composite moisture budget analysis reveals that the surface evaporation is negligible compared to moisture flux convergence of water vapor, which supplies moisture into the MDs over land. The temporal relationship between rainfall and moisture convergence show high correlation, suggesting a realistic representation of land state help restructure the moisture inflow into the system through rainfall-moisture convergence feedback.

Biogenic CO2 fluxes, changes in surface albedo and biodiversity impacts from establishment of a miscanthus plantation.

PubMed

Jørgensen, Susanne V; Cherubini, Francesco; Michelsen, Ottar

2014-12-15

Depletion in oil resources and environmental concern related to the use of fossil fuels has increased the interest in using second generation biomass as alternative feedstock for fuels and materials. However, the land use and land use change for producing second generation (2G) biomass impacts the environment in various ways, of which not all are usually considered in life cycle assessment. This study assesses the biogenic CO2 fluxes, surface albedo changes and biodiversity impacts for 100 years after changing land use from forest or fallow land to miscanthus plantation in Wisconsin, US. Climate change impacts are addressed in terms of effective forcing, a mid-point indicator which can be used to compare impacts from biogenic CO2 fluxes and albedo changes. Biodiversity impacts are assessed through elaboration on two different existing approaches, to express the change in biodiversity impact from one human influenced state to another. Concerning the impacts from biogenic CO2 fluxes, in the case of conversion from a forest to a miscanthus plantation (case A) there is a contribution to global warming, whereas when a fallow land is converted (case B), there is a climate cooling. When the effects from albedo changes are included, both scenarios show a net cooling impact, which is more pronounced in case B. Both cases reduce biodiversity in the area where the miscanthus plantation is established, though most in case A. The results illustrate the relevance of these issues when considering environmental impacts of land use and land use change. The apparent trade-offs in terms of environmental impacts further highlight the importance of including these aspects in LCA of land use and land use changes, in order to enable informed decision making. Copyright © 2014 Elsevier Ltd. All rights reserved.

Utilization of satellite imagery by in-flight aircraft. [for weather information

NASA Technical Reports Server (NTRS)

Luers, J. K.

1976-01-01

Present and future utilization of satellite weather data by commercial aircraft while in flight was assessed. Weather information of interest to aviation that is available or will become available with future geostationary satellites includes the following: severe weather areas, jet stream location, weather observation at destination airport, fog areas, and vertical temperature profiles. Utilization of this information by in-flight aircraft is especially beneficial for flights over the oceans or over remote land areas where surface-based observations and communications are sparse and inadequate.

Short-Term Retrospective Land Data Assimilation Schemes

NASA Technical Reports Server (NTRS)

Houser, P. R.; Cosgrove, B. A.; Entin, J. K.; Lettenmaier, D.; ODonnell, G.; Mitchell, K.; Marshall, C.; Lohmann, D.; Schaake, J. C.; Duan, Q.;

The Value of GRACE Data in Improving, Assessing and Evaluating Land Surface and Climate Models

NASA Astrophysics Data System (ADS)

Yang, Z.

2011-12-01

I will review how the Gravity Recovery and Climate Experiment (GRACE) satellite measurements have improved land surface models that are developed for weather, climate, and hydrological studies. GRACE-derived terrestrial water storage (TWS) changes have been successfully used to assess and evaluate the improved representations of land-surface hydrological processes such as groundwater-soil moisture interaction, frozen soil and infiltration, and the topographic control on runoff production, as evident in the simulations from the latest Noah-MP, the Community Land Model, and the Community Climate System Model. GRACE data sets have made it possible to estimate key terrestrial water storage components (snow mass, surface water, groundwater or water table depth), biomass, and surface water fluxes (evapotranspiration, solid precipitation, melt of snow/ice). Many of the examples will draw from my Land, Environment and Atmosphere Dynamics group's work on land surface model developments, snow mass retrieval, and multi-sensor snow data assimilation using the ensemble Karman filter and the ensemble Karman smoother. Finally, I will briefly outline some future directions in using GRACE in land surface modeling.

Multisource Imaging of Seasonal Dynamics in Land Surface Phenology Using Harmonized Landsat and Sentinel-2 Data

NASA Astrophysics Data System (ADS)

Melaas, E. K.; Graesser, J.; Friedl, M. A.

2017-12-01

Land surface phenology, including the timing of phenophase transitions and the entire seasonal cycle of surface reflectance and vegetation indices, is important for a myriad of applications including monitoring the response of terrestrial ecosystems to climate variability and extreme events, and land cover mapping. While methods to monitor and map phenology from coarse spatial resolution instruments such as MODIS are now relatively mature, the spatial resolution of these instruments is inadequate where vegetation properties, land use, and land cover vary at spatial scales of tens of meters. To address this need, algorithms to map phenology at moderate spatial resolution (30 m) using data from Landsat have recently been developed. However, the 16-day repeat cycle of Landsat presents significant challenges in regions where changes are rapid or where cloud cover reduces the frequency of clear-sky views. The European Space Agency's Sentinel-2 satellites, which are designed to provide moderate spatial resolution data at 5-day revisit frequency near the equator and 3 day revisit frequency in the mid-latitudes, will alleviate this constraint in many parts of the world. Here, we use harmonized time series of data from Sentinel-2A and Landsat OLI (HLS) to quantify the timing of land surface phenology metrics across a sample of deciduous forest and grassland-dominated sites, and then compare these estimates with co-located in situ observations. The resulting phenology maps demonstrate the improved information related to landscape-scale features that can be estimated from HLS data relative to comparable metrics from coarse spatial resolution instruments. For example, our results based on HLS data reveal spatial patterns in phenological metrics related to topographic and land cover controls that are not resolved in MODIS data, and show good agreement with transition dates observed from in situ measurements. Our results also show systematic bias toward earlier timing of spring, which is caused by inadequate density of observations that will be mitigated once data from Sentinel-2B are available. Overall, our results highlight the potential for using moderate spatial resolution data from Landsat and Sentinel-2 for developing operational phenology algorithms and products in support of the science community.

Expansion of oil palm and other cash crops causes an increase of the land surface temperature in the Jambi province in Indonesia

NASA Astrophysics Data System (ADS)

Sabajo, Clifton R.; le Maire, Guerric; June, Tania; Meijide, Ana; Roupsard, Olivier; Knohl, Alexander

2017-10-01

Indonesia is currently one of the regions with the highest transformation rate of land surface worldwide related to the expansion of oil palm plantations and other cash crops replacing forests on large scales. Land cover changes, which modify land surface properties, have a direct effect on the land surface temperature (LST), a key driver for many ecological functions. Despite the large historic land transformation in Indonesia toward oil palm and other cash crops and governmental plans for future expansion, this is the first study so far to quantify the impacts of land transformation on the LST in Indonesia. We analyze LST from the thermal band of a Landsat image and produce a high-resolution surface temperature map (30 m) for the lowlands of the Jambi province in Sumatra (Indonesia), a region which suffered large land transformation towards oil palm and other cash crops over the past decades. The comparison of LST, albedo, normalized differenced vegetation index (NDVI) and evapotranspiration (ET) between seven different land cover types (forest, urban areas, clear-cut land, young and mature oil palm plantations, acacia and rubber plantations) shows that forests have lower surface temperatures than the other land cover types, indicating a local warming effect after forest conversion. LST differences were up to 10.1 ± 2.6 °C (mean ± SD) between forest and clear-cut land. The differences in surface temperatures are explained by an evaporative cooling effect, which offsets the albedo warming effect. Our analysis of the LST trend of the past 16 years based on MODIS data shows that the average daytime surface temperature in the Jambi province increased by 1.05 °C, which followed the trend of observed land cover changes and exceeded the effects of climate warming. This study provides evidence that the expansion of oil palm plantations and other cash crops leads to changes in biophysical variables, warming the land surface and thus enhancing the increase of the air temperature because of climate change.

Discrimination of unique biological communities in the Mississippi lignite belt

NASA Technical Reports Server (NTRS)

Miller, W. F. (Principal Investigator); Cutler, J. D.

1981-01-01

Small scale hardcopy LANDSAT prints were manually interpreted and color infrared aerial photography was obtained in an effort to identify and map large contiguous areas of old growth hardwood stands within Mississippi's lignite belt which do not exhibit signs of recent disturbance by agriculture, grazing, timber harvesting, fire, or any natural catastrophe, and which may, therefore, contain unique or historical ecological habitat types. An information system using land cover classes derived from digital LANDSAT data and containing information on geology, hydrology, soils, and cultural activities was developed. Using computer-assisted land cover classifications, all hardwood remnants in the study area which are subject to possible disturbance from surface mining were determined. Twelve rare plants were also identified by botanists.

Elevation maps of the San Francisco Bay region, California, a digital database

USGS Publications Warehouse

Graham, Scott E.; Pike, Richard J.

1998-01-01

PREFACE: Topography, the configuration of the land surface, plays a major role in various natural processes that have helped shape the ten-county San Francisco Bay region and continue to affect its development. Such processes include a dangerous type of landslide, the debris flow (Ellen and others, 1997) as well as other modes of slope failure that damage property but rarely threaten life directly?slumping, translational sliding, and earthflow (Wentworth and others, 1997). Different types of topographic information at both local and regional scales are helpful in assessing the likelihood of slope failure and the mapping the extent of its past activity, as well as addressing other issues in hazard mitigation and land-use policy. The most useful information is quantitative.

Use of remote sensing for land use policy formulation

NASA Technical Reports Server (NTRS)

1983-01-01

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

GIS-BASED MODELING OF THE LONG-TERM IMPACTS OF LAND-USE CHANGE ON SURFACE HYDROLOGY. (R825871)

EPA Science Inventory

The perspectives, information and conclusions conveyed in research project abstracts, progress reports, final reports, journal abstracts and journal publications convey the viewpoints of the principal investigator and may not represent the views and policies of ORD and EPA. Concl...

Urban Sustainability and Public Health: Throwing the Bath Water Out and Not the Baby

NASA Technical Reports Server (NTRS)

Quattrochi, Dale A.

2009-01-01

This slide presentation reviews the affect of urbanization on community health. It exams urbanization trends in the Atlanta metro area and includes information on impervious surfaces, air quality, mitigation strategies, spatial growth modeling, land use, public health surveillance and different data collection methods.

A thermal-based remote sensing modeling system for estimating evapotranspiration from field to global scales

USDA-ARS?s Scientific Manuscript database

Thermal-infrared remote sensing of land surface temperature provides valuable information for quantifying root-zone water availability, evapotranspiration (ET) and crop condition. This paper describes a robust but relatively simple thermal-based energy balance model that parameterizes the key soil/s...

78 FR 15040 - Renewal of Approved Information Collection

Federal Register 2010, 2011, 2012, 2013, 2014

2013-03-08

... authorized by the mining laws, and in obtaining financial guarantees for the reclamation of public lands. The... the General Mining Law (43 CFR subpart 3809). Forms: Form 3809-1, Surface Management Surety Bond; Form... whether operators and mining claimants are meeting their responsibility to prevent unnecessary or undue...

Development of a 3D Underground Cadastral System with Indoor Mapping for As-Built BIM: The Case Study of Gangnam Subway Station in Korea.

PubMed

Kim, Sangmin; Kim, Jeonghyun; Jung, Jaehoon; Heo, Joon

2015-12-09

The cadastral system provides land ownership information by registering and representing land boundaries on a map. The current cadastral system in Korea, however, focuses mainly on the management of 2D land-surface boundaries. It is not yet possible to provide efficient or reliable land administration, as this 2D system cannot support or manage land information on 3D properties (including architectures and civil infrastructures) for both above-ground and underground facilities. A geometrical model of the 3D parcel, therefore, is required for registration of 3D properties. This paper, considering the role of the cadastral system, proposes a framework for a 3D underground cadastral system that can register various types of 3D underground properties using indoor mapping for as-built Building Information Modeling (BIM). The implementation consists of four phases: (1) geometric modeling of a real underground infrastructure using terrestrial laser scanning data; (2) implementation of as-built BIM based on geometric modeling results; (3) accuracy assessment for created as-built BIM using reference points acquired by total station; and (4) creation of three types of 3D underground cadastral map to represent underground properties. The experimental results, based on indoor mapping for as-built BIM, show that the proposed framework for a 3D underground cadastral system is able to register the rights, responsibilities, and restrictions corresponding to the 3D underground properties. In this way, clearly identifying the underground physical situation enables more reliable and effective decision-making in all aspects of the national land administration system.

Surface Emissivity Retrieved with Satellite Ultraspectral IR Measurements for Monitoring Global Change

NASA Technical Reports Server (NTRS)

Zhou, Daniel K.; Larar, Allen M.; Liu, Xu; Smith, William L.; Schluessel, Peter

2009-01-01

Surface and atmospheric thermodynamic parameters retrieved with advanced ultraspectral remote sensors aboard Earth observing satellites are critical to general atmospheric and Earth science research, climate monitoring, and weather prediction. Ultraspectral resolution infrared radiance obtained from nadir observations provide atmospheric, surface, and cloud information. Presented here is the global surface IR emissivity retrieved from Infrared Atmospheric Sounding Interferometer (IASI) measurements under "clear-sky" conditions. Fast radiative transfer models, applied to the cloud-free (or clouded) atmosphere, are used for atmospheric profile and surface parameter (or cloud parameter) retrieval. The inversion scheme, dealing with cloudy as well as cloud-free radiances observed with ultraspectral infrared sounders, has been developed to simultaneously retrieve atmospheric thermodynamic and surface (or cloud microphysical) parameters. Rapidly produced surface emissivity is initially evaluated through quality control checks on the retrievals of other impacted atmospheric and surface parameters. Surface emissivity and surface skin temperature from the current and future operational satellites can and will reveal critical information on the Earth s ecosystem and land surface type properties, which can be utilized as part of long-term monitoring for the Earth s environment and global climate change.

Land surface phenology of Northeast China during 2000-2015: temporal changes and relationships with climate changes.

PubMed

Zhang, Yue; Li, Lin; Wang, Hongbin; Zhang, Yao; Wang, Naijia; Chen, Junpeng

2017-10-01

As an important crop growing area, Northeast China (NEC) plays a vital role in China's food security, which has been severely affected by climate change in recent years. Vegetation phenology in this region is sensitive to climate change, and currently, the relationship between the phenology of NEC and climate change remains unclear. In this study, we used a satellite-derived normalized difference vegetation index (NDVI) to obtain the temporal patterns of the land surface phenology in NEC from 2000 to 2015 and validated the results using ground phenology observations. We then explored the relationships among land surface phenology, temperature, precipitation, and sunshine hours for relevant periods. Our results showed that the NEC experienced great phenological changes in terms of spatial heterogeneity during 2000-2015. The spatial patterns of land surface phenology mainly changed with altitude and land cover type. In most regions of NEC, the start date of land surface phenology had advanced by approximately 1.0 days year -1 , and the length of land surface phenology had been prolonged by approximately 1.0 days year -1 except for the needle-leaf and cropland areas, due to the warm conditions. We found that a distinct inter-annual variation in land surface phenology related to climate variables, even if some areas presented non-significant trends. Land surface phenology was coupled with climate variables and distinct responses at different combinations of temperature, precipitation, sunshine hours, altitude, and anthropogenic influence. These findings suggest that remote sensing and our phenology extracting methods hold great potential for helping to understand how land surface phenology is sensitive to global climate change.

Environment of Mars, 1988

NASA Technical Reports Server (NTRS)

Kaplan, David I. (Compiler)

1988-01-01

A compilation of scientific knowledge about the planet Mars is provided. Information is divided into three categories: atmospheric data, surface data, and astrodynamic data. The discussion of atmospheric data includes the presentation of nine different models of the Mars atmosphere. Also discussed are Martian atmospheric constituents, winds, clouds, and solar irradiance. The great dust storms of Mars are presented. The section on Mars surface data provides an in-depth examination of the physical and chemical properties observed at the two Viking landing sites. Bulk densities, dielectric constants, and thermal inertias across the planet are then described and related back to those specific features found at the Viking landing sites. The astrodynamic materials provide the astronomical constants, time scales, and reference coordinate frames necessary to perform flightpath analysis, navigation design, and science observation design.

A Capable and Temporary Test Facility on a Shoestring Budget: The MSL Touchdown Test Facility

NASA Technical Reports Server (NTRS)

White, Christopher V.; Frankovich, John K.; Yates, Philip; Wells, George, Jr.; Robert, Losey

2008-01-01

The Mars Science Laboratory mission (MSL) has undertaken a developmental Touchdown Test Program that utilizes a full-scale rover vehicle and an overhead winch system to replicate the skycrane landing event. Landing surfaces consisting of flat and sloped granular media, planar, rigid surfaces, and various combinations of rocks and slopes were studied. Information gathered from these tests was vital for validating the rover analytical model, validating certain design or system behavior assumptions, and for exploring events and phenomenon that are either very difficult or too costly to model in a credible way. This paper describes this test program, with a focus on the creation of test facility, daily test operations, and some of the challenges faced and lessons learned along the way.

Land Cover and Topography Affect the Land Transformation Caused by Wind Facilities

PubMed Central

Diffendorfer, Jay E.; Compton, Roger W.

2014-01-01

Land transformation (ha of surface disturbance/MW) associated with wind facilities shows wide variation in its reported values. In addition, no studies have attempted to explain the variation across facilities. We digitized land transformation at 39 wind facilities using high resolution aerial imagery. We then modeled the effects of turbine size, configuration, land cover, and topography on the levels of land transformation at three spatial scales. The scales included strings (turbines with intervening roads only), sites (strings with roads connecting them, buried cables and other infrastructure), and entire facilities (sites and the roads or transmission lines connecting them to existing infrastructure). An information theoretic modeling approach indicated land cover and topography were well-supported variables affecting land transformation, but not turbine size or configuration. Tilled landscapes, despite larger distances between turbines, had lower average land transformation, while facilities in forested landscapes generally had the highest land transformation. At site and string scales, flat topographies had the lowest land transformation, while facilities on mesas had the largest. The results indicate the landscape in which the facilities are placed affects the levels of land transformation associated with wind energy. This creates opportunities for optimizing wind energy production while minimizing land cover change. In addition, the results indicate forecasting the impacts of wind energy on land transformation should include the geographic variables affecting land transformation reported here. PMID:24558449

Land cover and topography affect the land transformation caused by wind facilities

USGS Publications Warehouse

Diffendorfer, Jay E.; Compton, Roger W.

2014-01-01

Land transformation (ha of surface disturbance/MW) associated with wind facilities shows wide variation in its reported values. In addition, no studies have attempted to explain the variation across facilities. We digitized land transformation at 39 wind facilities using high resolution aerial imagery. We then modeled the effects of turbine size, configuration, land cover, and topography on the levels of land transformation at three spatial scales. The scales included strings (turbines with intervening roads only), sites (strings with roads connecting them, buried cables and other infrastructure), and entire facilities (sites and the roads or transmission lines connecting them to existing infrastructure). An information theoretic modeling approach indicated land cover and topography were well-supported variables affecting land transformation, but not turbine size or configuration. Tilled landscapes, despite larger distances between turbines, had lower average land transformation, while facilities in forested landscapes generally had the highest land transformation. At site and string scales, flat topographies had the lowest land transformation, while facilities on mesas had the largest. The results indicate the landscape in which the facilities are placed affects the levels of land transformation associated with wind energy. This creates opportunities for optimizing wind energy production while minimizing land cover change. In addition, the results indicate forecasting the impacts of wind energy on land transformation should include the geographic variables affecting land transformation reported here.

Evaluating relationships between urban land cover composition and evapotranspiration in semi-arid regions

NASA Astrophysics Data System (ADS)

Manago, K. F.; Hogue, T. S.; Litvak, E.; Pataki, D. E.

2016-12-01

California experienced its most severe drought on record in 2013 and 2014, forcing the governor to call for the first statewide reductions in urban water use. This led to numerous water conservation efforts including turf removal and restrictions on outdoor irrigation. The decrease in irrigation across the city of Los Angeles has had major effects on regional hydrologic fluxes. Previous studies have found that conservation efforts have decreased streamflow but little work has been done on the impact of reduced irrigation on Evapotranspiration (ET). ET is one of the most difficult variables to measure as a result of its heterogeneity both spatially and temporally; yet, it is imperative in characterizing energy and hydrologic processes and in aiding water management decisions. Estimating ET is further complicated in urban regions where land cover composition is extremely variable, even at small scales. Irrigated landscape and impervious surfaces are two of the most common land cover types associated with urbanization, but they have opposite effects on ET. While numerous studies have evaluated changes in ET caused by urbanization, they have all produced varying results. This is expected as changes to ET are highly dependent on land cover composition. In this study, we modeled the relationship between ET and urban land cover change in Los Angeles. We utilized empirical equations derived from in situ measurements to calculate tree and irrigated turfgrass ET and compared the results to estimates based on remote-sensing and California Irrigation Management Information System (CIMIS) network of weather stations. We found that unshaded turfgrass largely increased ET compared to impervious surfaces, which reveals lavish irrigation practices. Trees also increased ET, but they provided shade that decreased ET from turf grass. With much of the western United States facing drought and water supply uncertainty due to climate change, understanding and predicting how land cover impacts ET under various scenarios is imperative for informed water management and efficient conservation solutions.

Synergistic use of optical and InSAR data for urban impervious surface mapping: A case study in Hong Kong

USGS Publications Warehouse

Jiang, L.; Liao, M.; Lin, H.; Yang, L.

2009-01-01

A wide range of urban ecosystem studies, including urban hydrology, urban climate, land use planning and watershed resource management, require accurate and up‐to‐date geospatial data of urban impervious surfaces. In this study, the potential of the synergistic use of optical and InSAR data in urban impervious surface mapping at the sub‐pixel level was investigated. A case study in Hong Kong was conducted for this purpose by applying a classification and regression tree (CART) algorithm to SPOT 5 multispectral imagery and ERS‐2 SAR data. Validated by reference data derived from high‐resolution colour‐infrared (CIR) aerial photographs, our results show that the addition of InSAR feature information can improve the estimation of impervious surface percentage (ISP) in comparison with using SPOT imagery alone. The improvement is especially notable in separating urban impervious surface from the vacant land/bare ground, which has been a difficult task in ISP modelling with optical remote sensing data. In addition, the results demonstrate the potential to map urban impervious surface by using InSAR data alone. This allows frequent monitoring of world's cities located in cloud‐prone and rainy areas.

A Continental United States High Resolution NLCD Land Cover – MODIS Albedo Database to Examine Albedo and Land Cover Change Relationships

EPA Science Inventory

Surface albedo influences climate by affecting the amount of solar radiation that is reflected at the Earth’s surface, and surface albedo is, in turn, affected by land cover. General Circulation Models typically use modeled or prescribed albedo to assess the influence of land co...

CARETS: A prototype regional environmental information system. Volume 5: Interpretation, compilation and field verification procedures in the CARETS project

NASA Technical Reports Server (NTRS)

Alexander, R. H. (Principal Investigator); Deforth, P. W.; Fitzpatrick, K. A.; Lins, H. F., Jr.; Mcginty, H. K., III

1975-01-01

The author has identified the following significant results. Level 2 land use mapping from high altitude aircraft photography at a scale of 1:100,000 required production of a photomosaic mapping base for each of the 48, 50 x 50 km sheets, and the interpretation and coding of land use polygons on drafting film overlays. To enhance the value of the land use sheets, a series of overlays was compiled, showing cultural features, county boundaries and census tracts, surface geology, and drainage basins. In producing level 1 land use maps from LANDSAT imagery, at a scale of 1:250,000 drafting film was directly overlaid on LANDSAT color composite transparencies. Numerous areas of change were identified, but extensive areas of false changes were also noted.

Landing Characteristics of a Lenticular-Shaped Reentry Vehicle

NASA Technical Reports Server (NTRS)

Blanchard, Ulysse J.

1961-01-01

An experimental investigation was made of the landing characteristics of a 1/9-scale dynamic model of a lenticular-shaped reentry vehicle having extendible tail panels for control after reentry and for landing control (flare-out). The landing tests were made by catapulting a free model onto a hard-surface runway and onto water. A "belly-landing" technique in which the vehicle was caused to skid and rock on its curved undersurface (heat shield), converting sinking speed into angular energy, was investigated on a hard-surface runway. Landings were made in calm water and in waves both with and without auxiliary landing devices. Landing motions and acceleration data were obtained over a range of landing attitudes and initial sinking speeds during hard-surface landings and for several wave conditions during water landings. A few vertical landings (parachute letdown) were made in calm water. The hard-surface landing characteristics were good. Maximum landing accelerations on a hard surface were 5g and 18 radians per sq second over a range of landing conditions. Horizontal landings on water resulted in large violent rebounds and some diving in waves. Extreme attitude changes during rebound at initial impact made the attitude of subsequent impact random. Maximum accelerations for water landings were approximately 21g and 145 radians per sq second in waves 7 feet high. Various auxiliary water-landing devices produced no practical improvement in behavior. Reduction of horizontal speed and positive control of impact attitude did improve performance in calm water. During vertical landings in calm water maximum accelerations of 15g and 110 radians per sq second were measured for a contact attitude of -45 deg and a vertical velocity of 70 feet per second.

Real Time Land-Surface Hydrologic Modeling Over Continental US

NASA Technical Reports Server (NTRS)

Houser, Paul R.

1998-01-01

The land surface component of the hydrological cycle is fundamental to the overall functioning of the atmospheric and climate processes. Spatially and temporally variable rainfall and available energy, combined with land surface heterogeneity cause complex variations in all processes related to surface hydrology. The characterization of the spatial and temporal variability of water and energy cycles are critical to improve our understanding of land surface-atmosphere interaction and the impact of land surface processes on climate extremes. Because the accurate knowledge of these processes and their variability is important for climate predictions, most Numerical Weather Prediction (NWP) centers have incorporated land surface schemes in their models. However, errors in the NWP forcing accumulate in the surface and energy stores, leading to incorrect surface water and energy partitioning and related processes. This has motivated the NWP to impose ad hoc corrections to the land surface states to prevent this drift. A proposed methodology is to develop Land Data Assimilation schemes (LDAS), which are uncoupled models forced with observations, and not affected by NWP forcing biases. The proposed research is being implemented as a real time operation using an existing Surface Vegetation Atmosphere Transfer Scheme (SVATS) model at a 40 km degree resolution across the United States to evaluate these critical science questions. The model will be forced with real time output from numerical prediction models, satellite data, and radar precipitation measurements. Model parameters will be derived from the existing GIS vegetation and soil coverages. The model results will be aggregated to various scales to assess water and energy balances and these will be validated with various in-situ observations.

Bridging the Gap between Policy-Driven Land Use Changes and Regional Climate Projections

NASA Astrophysics Data System (ADS)

Berckmans, J.; Hamdi, R.; Dendoncker, N.; Ceulemans, R.

2017-12-01

Land use land cover changes (LULCC) can impact the regional climate by two mechanisms: biogeochemical and biogeophysical. The biogeochemical mechanism of the LULCC alters the chemical composition of the atmosphere by greenhouse gas emissions. The biogeophysical mechanism forces changes in the heat and moisture transfer between the land and the atmosphere. The different representations of the future LULCC under influence of the biogeochemical mechanism are included in the IPCC Radiative Concentration Pathways (RCPs). In contrast, the RCPs do not incorporate the biogeophysical effects. Although considerable research has been devoted to the biogeophysical effects of LULCC on climate, less attention has been paid to assessing the full (both biogeochemical and biogeophysical) LULCC impact on the regional climate in modeling studies. Due to the large variety of small changes in the landscape of Western Europe, the small scale climate impact by the LULCC has been achieved using high-resolution scenarios. The "ALARM" project that was governed by the European Commission generated LULCC data on a resolution of 250x250 m for three time steps: 2020, 2050 and 2080. The CNRM-CM5.1 global climate model has been downscaled to perform simulations with ALARO-SURFEX for the near-term future. Both climate changes and land cover changes have been assessed based on RCP and ALARM scenarios. The use of the land surface model SURFEX with its tiling approach allowed us to accurately represent the small scale changes in the landscape. The largest landscape changes contain the abandonment of agricultural land and the increase in forestry and urban areas. Our results show that the conversions from rural areas to urban areas and arable land to forest in Western Europe considerable affect the near-surface temperature and to a lesser extent the precipitation. These results are related to modifications demonstrated in the surface energy budget. The LULCC have a significant impact compared to the near-term future climate changes. They provide valuable information for landscape planning to mitigate and adapt to climate change. The strength of this study is the use of policy-driven LULCC data combined with an accurate representation of the land by the climate model.

Hydrologic connections between environmental and societal change at the Bonneville Salt Flats, Utah

NASA Astrophysics Data System (ADS)

Bowen, B. B.; Harman, C. J.; Kipnis, E. L.; Liu, T.; Bernau, J. A.; Horel, J.

2017-12-01

The Bonneville Salt Flats (BSF) is an ephemeral and valued salt pan in northwestern Utah where a century of land speed racing and potash mining have created a complex and intertwined social and hydrologic system. The character of BSF changes on daily, weekly, monthly, annual, and geologic time scales in response to fluctuations in water balance, solute flux, and groundwater flow which is impacted by both local meteorology and water management associated with potash mining. In addition, the texture of the salt surface is changed by land use including racing activities, which impacts water fluxes through the crust. Ongoing research is focused on characterizing physical changes in the BSF environment and attributing observed changes in the landscape to specific processes and drivers. Five years of field observations and sampling, analyses of satellite imagery dating back the 1980s, and geochemical analysis of surface brines have shown that spatiotemporal changes in surface water and fluctuations in the surface salt footprint are linked to both climate and land use. Climate data over the last 30 years are examined to identify annual patterns in surface water balance at BSF to identify annual and seasonal climate constraints on flooding, evaporation, and desiccation cycles. A new weather station installed in the Fall of 2016 in the middle of BSF allows for unprecedented analyses of halite surface dynamics. Spatiotemporally dispersed stable isotope analyses of BSF surface brine samples constrain brine sources and evolution. An understanding of the processes that change the surface composition and texture through time inform interpretation of subsurface saline deposits at BSF. The wide range of temporal and spatial scales of observation help to guide to best management practices of this iconic natural resource.

Highest Resolution Topography of 433 Eros and Implications for MUSES-C

NASA Technical Reports Server (NTRS)

Cheng, A. F.; Barnouin-Jha, O.

2003-01-01

The highest resolution observations of surface morphology and topography at asteroid 433 Eros were obtained by the Near Earth Asteroid Rendezvous (NEAR) Shoemaker spacecraft on 12 February 2001, as it landed within a ponded deposit on Eros. Coordinated observations were obtained by the imager and the laser rangefinder, at best image resolution of 1 cm/pixel and best topographic resolution of 0.4 m. The NEAR landing datasets provide unique information on rock size and height distributions and regolith processes. Rocks and soil can be distinguished photometrically, suggesting that bare rock is indeed exposed. The NEAR landing data are the only data at sufficient resolution to be relevant to hazard assessment on future landed missions to asteroids, such as the MUSES-C mission which will land on asteroid 25143 (1998 SF36) in order to obtain samples. In a typical region just outside the pond where NEAR landed, the areal coverage by resolved positive topographic features is 18%. At least one topographic feature in the vicinity of the NEAR landing site would have been hazardous for a spacecraft.

Assessment of Mars Exploration Rover Landing Site Predictions

NASA Astrophysics Data System (ADS)

Golombek, M. P.

2005-05-01

Comprehensive analyses of remote sensing data during the 3-year effort to select the Mars Exploration Rover landing sites at Gusev crater and Meridiani Planum correctly predicted the safe and trafficable surfaces explored by the two rovers. Gusev crater was predicted to be a relatively low relief surface that was comparably dusty, but less rocky than the Viking landing sites. Available data for Meridiani Planum indicated a very flat plain composed of basaltic sand to granules and hematite that would look completely unlike any of the existing landing sites with a dark, low albedo surface, little dust and very few rocks. Orbital thermal inertia measurements of 315 J m-2 s-0.5 K-1 at Gusev suggested surfaces dominated by duricrust to cemented soil-like materials or cohesionless sand or granules, which is consistent with observed soil characteristics and measured thermal inertias from the surface. THEMIS thermal inertias along the traverse at Gusev vary from 285 at the landing site to 330 around Bonneville rim and show systematic variations that can be related to the observed increase in rock abundance (5-30%). Meridiani has an orbital bulk inertia of ~200, similar to measured surface inertias that correspond to observed surfaces dominated by 0.2 mm sand size particles. Rock abundance derived from orbital thermal differencing techniques suggested that Meridiani Planum would have very low rock abundance, consistent with the rock free plain traversed by Opportunity. Spirit landed in an 8% orbital rock abundance pixel, consistent with the measured 7% of the surface covered by rocks >0.04 m diameter at the landing site, which is representative of the plains away from craters. The orbital albedo of the Spirit traverse varies from 0.19 to 0.30, consistent with surface measurements in and out of dust devil tracks. Opportunity is the first landing in a low albedo portion of Mars as seen from orbit, which is consistent with the dark, dust-free surface and measured albedos. The close correspondence between surface characteristics inferred from orbital remote sensing data and that found at the landing sites argues that future efforts to select safe landing sites will be successful. Linking the five landing sites to their remote sensing signatures suggests that they span most of the important, likely safe surfaces available for landing on Mars.

Land surface dynamics monitoring using microwave passive satellite sensors

NASA Astrophysics Data System (ADS)

Guijarro, Lizbeth Noemi

Soil moisture, surface temperature and vegetation are variables that play an important role in our environment. There is growing demand for accurate estimation of these geophysical parameters for the research of global climate models (GCMs), weather, hydrological and flooding models, and for the application to agricultural assessment, land cover change, and a wide variety of other uses that meet the needs for the study of our environment. The different studies covered in this dissertation evaluate the capabilities and limitations of microwave passive sensors to monitor land surface dynamics. The first study evaluates the 19 GHz channel of the SSM/I instrument with a radiative transfer model and in situ datasets from the Illinois stations and the Oklahoma Mesonet to retrieve land surface temperature and surface soil moisture. The surface temperatures were retrieved with an average error of 5 K and the soil moisture with an average error of 6%. The results show that the 19 GHz channel can be used to qualitatively predict the spatial and temporal variability of surface soil moisture and surface temperature at regional scales. In the second study, in situ observations were compared with sensor observations to evaluate aspects of low and high spatial resolution at multiple frequencies with data collected from the Southern Great Plains Experiment (SGP99). The results showed that the sensitivity to soil moisture at each frequency is a function of wavelength and amount of vegetation. The results confirmed that L-band is more optimal for soil moisture, but each sensor can provide soil moisture information if the vegetation water content is low. The spatial variability of the emissivities reveals that resolution suffers considerably at higher frequencies. The third study evaluates C- and X-bands of the AMSR-E instrument. In situ datasets from the Soil Moisture Experiments (SMEX03) in South Central Georgia were utilized to validate the AMSR-E soil moisture product and to derive surface soil moisture with a radiative transfer model. The soil moisture was retrieved with an average error of 2.7% at X-band and 6.7% at C-band. The AMSR-E demonstrated its ability to successfully infer soil moisture during the SMEX03 experiment.

The use of LiDAR-derived high-resolution DSM and intensity data to support modelling of urban flooding

NASA Astrophysics Data System (ADS)

Aktaruzzaman, Md.; Schmitt, Theo G.

2011-11-01

This paper addresses the issue of a detailed representation of an urban catchment in terms of hydraulic and hydrologic attributes. Modelling of urban flooding requires a detailed knowledge of urban surface characteristics. The advancement in spatial data acquisition technology such as airborne LiDAR (Light Detection and Ranging) has greatly facilitated the collection of high-resolution topographic information. While the use of the LiDAR-derived Digital Surface Model (DSM) has gained popularity over the last few years as input data for a flood simulation model, the use of LiDAR intensity data has remained largely unexplored in this regard. LiDAR intensity data are acquired along with elevation data during the data collection mission by an aircraft. The practice of using of just aerial images with RGB (Red, Green and Blue) wavebands is often incapable of identifying types of surface under the shadow. On the other hand, LiDAR intensity data can provide surface information independent of sunlight conditions. The focus of this study is the use of intensity data in combination with aerial images to accurately map pervious and impervious urban areas. This study presents an Object-Based Image Analysis (OBIA) framework for detecting urban land cover types, mainly pervious and impervious surfaces in order to improve the rainfall-runoff modelling. Finally, this study shows the application of highresolution DSM and land cover maps to flood simulation software in order to visualize the depth and extent of urban flooding phenomena.

[A review on research of land surface water and heat fluxes].

PubMed

Sun, Rui; Liu, Changming

2003-03-01

Many field experiments were done, and soil-vegetation-atmosphere transfer(SVAT) models were stablished to estimate land surface heat fluxes. In this paper, the processes of experimental research on land surface water and heat fluxes are reviewed, and three kinds of SVAT model(single layer model, two layer model and multi-layer model) are analyzed. Remote sensing data are widely used to estimate land surface heat fluxes. Based on remote sensing and energy balance equation, different models such as simplified model, single layer model, extra resistance model, crop water stress index model and two source resistance model are developed to estimate land surface heat fluxes and evapotranspiration. These models are also analyzed in this paper.

The Value of Forest and Pasture to Water Supply in Kona, HI

NASA Astrophysics Data System (ADS)

Brauman, K. A.; Daily, G. C.; Freyberg, D. L.

2007-12-01

By quantifying the supply and value of ecosystem services flowing from private land, we can provide a mechanism for sustaining ecosystem services by compensating landowners for their supply. In order for compensation to occur, however, both suppliers and users of ecosystem services require information about the way different land management scenarios will affect ecosystem service flows. This case study in Kona, HI, takes advantage of the direct link between upland water source areas and municipal drinking water users in Kailua-Kona to explore the value of one type of hydrologic service. By quantifying the difference in aquifer recharge under paired forest and pasture sites, we assess the impact of each land-cover type on the volume of water potentially available to municipal water users. We use a water balance approach - measuring rainfall interception and water use by plants, then calculating the balance to be aquifer recharge because of the absence of surface runoff. We aim to integrate these biophysical measurements with information, including costs of pumping, well construction, and land-cover maintenance, provided by the water utility and landowners to ascertain the value of forest and pasture to water supply. By determining the value to water users in Kailua-Kona of the increase or decrease in water quantity that would result from upland land-cover change, we aim both to protect drinking water quantity and to help landowners offset financial pressure to convert their land.

Improving sand and gravel utilization and land-use planning. - 3D-modelling gravel resources with geospatial data.

NASA Astrophysics Data System (ADS)

Rolstad Libach, Lars; Wolden, Knut; Dagestad, Atle; Eskil Larsen, Bjørn

2017-04-01

The Norwegian aggregate industry produces approximately 14 million tons of sand and gravel aggregates annually to a value of approximately 100 million Euros. Utilization of aggregates are often linked to land-use conflicts and complex environmental impacts at the extraction site. These topics are managed on a local municipal level in Norway. The Geological Survey of Norway has a database and a web map service with information about sand and gravel deposits with considerable volumes and an importance evaluation. Some of the deposits covers large areas where the land-use conflicts are high. To ease and improve land-use planning, safeguard other important resources like groundwater and sustainable utilization of sand and gravel resources - there is a need for more detailed information of already mapped important resources. Detailed 3D-models of gravel deposits is a tool for a better land-use- and resource management. By combining seismic, GPR and resistivity geophysical profile data, borehole data, quaternary maps and lidar surface data, it has been possible to make 3D-models of deposits and to further research the possibilities for distinguishing different qualities and volumes. Good datasets and a detailed resource map is a prerequisite to assess geological resources for planners, extractors and neighbours. Future challenges lies in use of, often old, geophysical data, and combining these. What kind of information is it possible to grasp from depth-data that actually argues for a more detailed delineation of resources?

Salinity monitoring in Western Australia using remotely sensed and other spatial data.

PubMed

Furby, Suzanne; Caccetta, Peter; Wallace, Jeremy

2010-01-01

The southwest of Western Australia is affected by dryland salinity that results in the loss of previously productive agricultural land, damage to buildings, roads, and other infrastructure, decline in pockets of remnant vegetation and biodiversity, and reduction in water quality. Accurate information on the location and rate of change of the extent of saline land over the region is required by resource managers. For the first time, comprehensive, spatially explicit maps of dryland salinity and its change over approximately 10 yr for the southwest agricultural region of Western Australia have been produced operationally in the 'Land Monitor' project. The methods rely on an integrated analysis of long-term sequences of Landsat TM satellite image data together with variables derived from digital elevation models (DEMs). Understanding of the physical process and surface expression of salinity provided by experts was used to guide the analyses. Ground data-the delineation of salt-affected land by field experts-was collected for training and validation. The results indicate that the land area currently affected by salinity in Western Australia's southwest is about 1 million hectares (in 1996) and the annual rate of increase is about 14,000 ha. This is a lesser extent than many previous estimates and lower rate of change than generally predicted from limited hydrological data. The results are widely distributed and publicly available. The key to providing accurate mapping and monitoring information was the incorporation of time series classification of a sequence of images over several years combined with landform information.

Does surface roughness dominate biophysical forcing of land use and land cover change in the eastern United States?

NASA Astrophysics Data System (ADS)

Burakowski, E. A.; Tawfik, A. B.; Ouimette, A.; Lepine, L. C.; Ollinger, S. V.; Bonan, G. B.; Zarzycki, C. M.; Novick, K. A.

2016-12-01

Changes in land use, land cover, or both promote changes in surface temperature that can amplify or dampen long-term trends driven by natural and anthropogenic climate change by modifying the surface energy budget, primarily through differences in albedo, evapotranspiration, and aerodynamic roughness. Recent advances in variable resolution global models provide the tools necessary to investigate local and global impacts of land use and land cover change by embedding a high-resolution grid over areas of interest in a seamless and computationally efficient manner. Here, we used two eddy covariance tower clusters in the Eastern US (University of New Hampshire UNH and Duke Forest) to validate simulation of surface energy fluxes and properties by the uncoupled Community Land Model (PTCLM4.5) and coupled land-atmosphere Variable-Resolution Community Earth System Model (VR-CESM1.3). Surface energy fluxes and properties are generally well captured by the models for grassland sites, however forested sites tend to underestimate latent heat and overestimate sensible heat flux. Surface roughness emerged as the dominant biophysical forcing factor affecting surface temperature in the eastern United States, generally leading to warmer nighttime temperatures and cooler daytime temperatures. However, the sign and magnitude of the roughness effect on surface temperature was highly sensitive to the calculation of aerodynamic resistance to heat transfer.

Relationship Between Landcover Pattern and Surface Net Radiation in AN Coastal City

NASA Astrophysics Data System (ADS)

Zhao, X.; Liu, L.; Liu, X.; Zhao, Y.

2016-06-01

Taking Xiamen city as the study area this research first retrieved surface net radiation using meteorological data and Landsat 5 TM images of the four seasons in the year 2009. Meanwhile the 65 different landscape metrics of each analysis unit were acquired using landscape analysis method. Then the most effective landscape metrics affecting surface net radiation were determined by correlation analysis, partial correlation analysis, stepwise regression method, etc. At both class and landscape levels, this paper comprehensively analyzed the temporal and spatial variations of the surface net radiation as well as the effects of land cover pattern on it in Xiamen from a multi-seasonal perspective. The results showed that the spatial composition of land cover pattern shows significant influence on surface net radiation while the spatial allocation of land cover pattern does not. The proportions of bare land and forest land are effective and important factors which affect the changes of surface net radiation all the year round. Moreover, the proportion of forest land is more capable for explaining surface net radiation than the proportion of bare land. So the proportion of forest land is the most important and continuously effective factor which affects and explains the cross-seasonal differences of surface net radiation. This study is helpful in exploring the formation and evolution mechanism of urban heat island. It also gave theoretical hints and realistic guidance for urban planning and sustainable development.

Analytical Retrieval of Global Land Surface Emissivity Maps at AMSR-E passive microwave frequencies

NASA Astrophysics Data System (ADS)

Norouzi, H.; Temimi, M.; Khanbilvardi, R.

2009-12-01

Land emissivity is a crucial boundary condition in Numerical Weather Prediction (NWP) modeling. Land emissivity is also a key indicator of land surface and subsurface properties. The objective of this study, supported by NOAA-NESDIS, is to develop global land emissivity maps using AMSR-E passive microwave measurements along with several ancillary data. The International Satellite Cloud Climatology Project (ISCCP) database has been used to obtain several inputs for the proposed approach such as land surface temperature, cloud mask and atmosphere profile. The Community Radiative Transfer Model (CRTM) has been used to estimate upwelling and downwelling atmospheric contributions. Although it is well known that correction of the atmospheric effect on brightness temperature is required at higher frequencies (over 19 GHz), our preliminary results have shown that a correction at 10.7 GHz is also necessary over specific areas. The proposed approach is based on three main steps. First, all necessary data have been collected and processed. Second, a global cloud free composite of AMSR-E data and corresponding ancillary images is created. Finally, monthly composting of emissivity maps has been performed. AMSR-E frequencies at 6.9, 10.7, 18.7, 36.5 and 89.0 GHz have been used to retrieve the emissivity. Water vapor information obtained from ISCCP (TOVS data) was used to calculate upwelling, downwelling temperatures and atmospheric transmission in order to assess the consistency of those derived from the CRTM model. The frequent land surface temperature (LST) determination (8 times a day) in the ISCCP database has allowed us to assess the diurnal cycle effect on emissivity retrieval. Differences in magnitude and phase between thermal temperature and low frequencies microwave brightness temperature have been noticed. These differences seem to vary in space and time. They also depend on soil texture and thermal inertia. The proposed methodology accounts for these factors and resultant differences in phase and magnitude between LST and microwave brightness temperature. Additional factors such as topography and vegetation cover are under investigation. In addition, the potential of extrapolating the obtained land emissivity maps to different window and sounding channels has been also investigated in this study. The extrapolation of obtained emissivities to different incident angles is also under investigation. Land emissivity maps have been developed at different AMSR-E frequencies. Obtained product has been validated and compared to global land use distribution. Moreover, global soil moisture AMSR-E product maps have been also used to assess to the spatial distribution of the emissivity. Moreover, obtained emissivity maps seem to be consistent with landuse/land cover maps. They also agree well with land emissivity maps obtained from the ISCCP database and developed using SSM/I observations (for frequencies over 19 GHz).

Using land-cover change as dynamic variables in surface-water and water-quality models

USGS Publications Warehouse

Karstensen, Krista A.; Warner, Kelly L.; Kuhn, Anne

2010-01-01

Land-cover data are typically used in hydrologic modeling to establish or describe land surface dynamics. This project is designed to demonstrate the use of land-cover change data in surface-water and water-quality models by incorporating land-cover as a variable condition. The project incorporates three different scenarios that vary hydrologically and geographically: 1) Agriculture in the Plains, 2) Loon habitat in New England, and 3) Forestry in the Ozarks.