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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 721 records · Page 40
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

The influence of fire aerosols on surface climate and gross primary production in the Energy Exascale Earth System Model (E3SM)

Fire-emitted aerosols play an important role in influencing Earth’s climate, directly by scattering and absorbing radiation and indirectly by influencing cloud microphysics. The quantification of fire-aerosol interactions, however, remains challenging and subject to uncertainties in emissions, plume parameterizations, and aerosol properties. Here we optimized fire-associated aerosol emissions in the Energy Exascale Earth System Model (E3SM) using the Global Fire Emissions Database (GFED) and AERONET aerosol optical depth (AOD) observations during 1997-2016. Furthermore, we distributed fire emissions vertically using smoke plume heights from Multi-angle Imaging SpectroRadiometer (MISR) satellite observations. From the optimization, we estimate that global fires emit 45.5 Tg y -1 of primary particulate organic matter and 3.9 Tg y -1 of black carbon. We then performed two climate simulations with and without the optimized fire emissions. We find that fire aerosols significantly increase global AOD by 14 ± 7% and contribute to a reduction in net shortwave radiation at the surface (-2.3 ± 0.5 W m -2 ). Together, fire-induced direct and indirect aerosol effects cause annual mean global land surface air temperature to decrease by 0.17 ± 0.15°C, relative humidity to increase by 0.4 ± 0.3%, and diffuse light fraction to increase by 0.5 ± 0.3%. In response, GPP declines by 2.8 Pg C y -1 , as a result of large positive drivers (decreases in temperature and increases in humidity and diffuse light) nearly cancelling out large negative drivers (decreases shortwave radiation and soil moisture). Our analysis highlights the importance of fire aerosols in modifying surface climate and photosynthesis across the tropics.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

On the Generation of Weddell Sea Polynyas in a High-Resolution Earth System Model

Larger Weddell Sea polynyas (WSPs), differentiated in this study from the smaller Maud Rise Polynyas (MRPs), forming to the east of the prime meridian in the proximity of the Maud Rise seamount, have last been observed in the 1970s. We investigate WSPs that grow realistically out of MRPs in a high-resolution (HR) preindustrial simulation with the Energy Exascale Earth System Model version 0.1. The formation of MRPs requires HR to simulate the detailed flow around Maud Rise, while the realistic formation of WSPs requires a model to produce MRPs. Furthermore, WSPs tend to follow periods of a prolonged build-up of a heat reservoir at depth and weakly negative wind-stress curl in association with the core of the southern hemisphere westerlies at an anomalously northern position. While this scenario also leads to drier conditions over the central Weddell Sea, which some literature claims to be a necessary condition for the formation of WSPs, our model results indicate that open-ocean polynyas do not occur during periods of weakly negative wind-stress curl despite drier atmospheric conditions. Our study supports the hypothesis noted in earlier studies that a shift from a weakly negative to a strongly negative wind-stress curl over the Weddell Sea is a prerequisite for WSPs to form, together with a large heat reservoir at depth. However, the ultimate trigger is a pronounced MRP; whose associated convection creates high surface salinity anomalies that propagate westward with the flow of the Weddell Gyre. If large enough, these anomalies trigger the formation of a WSP and a pulse of newly formed Antarctic Bottom Water.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Hybridizing Machine Learning and Physically-based Earth System Models to Improve Prediction of Multivariate Extreme Events (AI Exploration of Wildland Fire Prediction)

Focal Areas: This project responds to two focal areas identified in the DOE Call for AI4ESP White Papers: 1) Predictive modeling through the use of artificial intelligence (AI) techniques, and 2) insights gleaned from complex data using explainable AI and big data analytics. Science Challenge: Large wildland fires (hereafter wildfires) appearing as high-impact compound climate extreme events are closely related to hydroclimate and water cycle extremes that modulate surface fuel supply and combustibility. These compound events have multivariate climatic features (e.g., temperature, precipitation, relative humidity, wind, lightning) and societal drivers (e.g., forest management, land use change, human caused ignitions). Meanwhile, they induce strong feedbacks to the coupled atmosphere, biosphere, and hydrosphere by perturbing regional and global radiation budget as well as ecological, biogeochemical, and water cycles across multiple spatiotemporal scales. The nonlinear interactions between these natural and anthropogenic components of the Earth system are too complex to be completely and adequately represented in today’s Earth system models (ESMs). The inherent stochastic nature of fire activity at all scales further increases the difficulty of its prediction using ESMs that are usually developed from deterministic equations and parameterizations. Besides, concurrence of long-term (decadal to interdecadal) global climate change and fire regime shifts overlapping with short-term (intraseasonal to interannual) variations of regional fire weather and burning activity confound predictability of these compound extreme events. We propose to address the above scientific challenges by using machine learning (ML)-based data-driven modeling techniques to integrate observations and physically-based ESMs’ simulations in a computationally efficient hybrid prediction system. This prediction system is supposed to characterize the wildfire’s sensitivity to climate and exogenous drivers at high resolution (~ 0.25°) on subseasonal to seasonal (S2S) timescales providing improved predictability and explainability. We will use the system to help identify: (1) What are the computational elements of a hybrid system needed to predict compound climate extreme events such as global wildfires? (2) What are the key drivers (either natural or anthropogenic) that modulate short-term variations of multivariate fire weather and burning activity over different regions? How can one take advantage of those driver-response relationships to improve the predictability of large wildfires on S2S time scales? (3) What are the underlying physical mechanisms and sources of improved predictability? Which ML techniques are optimal in revealing and adapting these mechanisms?

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Future Changes in Active and Inactive Atlantic Hurricane Seasons in the Energy Exascale Earth System Model

Abstract North Atlantic tropical cyclones (TCs) have considerable interannual variability, with La Niña and the positive phase of the Atlantic Meridional Mode (AMM) tending to drive active hurricane seasons, and El Niño and the negative AMM often driving inactive seasons. Here, we analyze how active and inactive Atlantic hurricane seasons may change in the future using the high resolution Energy Exascale Earth System Model (E3SM). We performed atmosphere‐only simulations forced by sea‐surface temperature patterns characteristic of La Niña and the positive AMM jointly, and El Niño and the negative AMM jointly, in historical and future climates. Projected Atlantic TCs become more frequent in the future by approximately 34% during El Niño and negative AMM and by 66% during La Niña and positive AMM, with a significant increase in the portion of intense TCs. Warmer SSTs increase TC potential intensity, with reduced wind shear and increased mid‐tropospheric humidity further supporting TC activity.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Projections of leaf area index in earth system models

The area of leaves in the plant canopy, measured as leaf area index (LAI), modulates key land–atmosphere interactions, including the exchange of energy, moisture, carbon dioxide (CO 2 ), and other trace gases and aerosols, and is therefore an essential variable in predicting terrestrial carbon, water, and energy fluxes. Here our goal is to characterize the LAI projections from the latest generation of earth system models (ESMs) for the Representative Concentration Pathway (RCP) 8.5 and RCP4.5 scenarios. On average, the models project increases in LAI in both RCP8.5 and RCP4.5 over most of the globe, but also show decreases in some parts of the tropics. Because of projected increases in variability, there are also more frequent periods of low LAI across broad regions of the tropics. Projections of LAI changes varied greatly among models: some models project very modest changes, while others project large changes, usually increases. Modeled LAI typically increases with modeled warming in the high latitudes, but often decreases with increasing local warming in the tropics. The models with the most skill in simulating current LAI in the tropics relative to satellite observations tend to project smaller increases in LAI in the tropics in the future compared to the average of all the models. Using LAI projections to identify regions that may be vulnerable to climate change presents a slightly different picture than using precipitation projections, suggesting LAI may be an additional useful tool for understanding climate change impacts. Going forward, users of LAI projections from the CMIP5 ESMs evaluated here should be aware that model outputs do not exhibit clear-cut relationships to vegetation carbon and precipitation. Lastly, our findings underscore the need for more attention to LAI projections, in terms of understanding the drivers of projected changes and improvements to model skill.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2008

Pharmacokinetics of Acetaminophen in Hind Limbs Unloaded Mice: A Model System Simulating the Effects of Low Gravity on Astronauts in Space

The pharmacokinetics (PK) of medications administered to astronauts could be altered by the conditions in Space. Low gravity and free floating (and associated hemodynamic changes) could affect the absorption, distribution, metabolism and excretion of the drugs. Knowledge of these alterations is essential for adjusting the dosage and the regimen of drug administration in astronauts. Acquiring of such knowledge has inherent difficulties due to limited opportunities for experimenting in Space. One of the approaches is to use model systems that simulate some of the Space conditions on Earth. In this study we used hind limbs unloaded mice (HLU) to investigate the possible changes in PK of acetaminophen, a widely used analgesic with high probability of use by astronauts. The HLU is recognized as an appropriate model for simulating the effects of low gravity on hemodynamic parameters. Mice were tail suspended (n = 24) for 24-96 hours prior to introduction of acetaminophen (150 - 300 mg/kg). The drug (in aqueous solution containing 10% ethyl alcohol by volume) was given orally by a gavage procedure and after the administration of acetaminophen mice were additionally suspended for 30 min, 1 and 2 hours. Control mice (n = 24) received the same dose of acetaminophen and were kept freely all the time. Blood specimens were obtained either from retroorbital venous sinuses or from heart. Acetaminophen concentration was measured in plasma by the fluorescent polarization immunoassay and the AxSYM analyzer (Abbott Laboratories). In control mice peak acetaminophen concentration was achieved at 30 min. By 1 hour the concentration decreased to less than 50% of the peak level and at 2 hours the drug was almost undetectable in the serum. HLU for 24 hours significantly altered the acetaminophen pharmacokinetic: at 30 min the acetaminophen concentrations were significantly (both statistically and medically significant) lower than in control mice. The concentrations also reduced less significantly after 1 and 2 hours. At 2 hours approximately 20% of the drug still remained in the circulation. After 96 hrs of HLU the changes in acetaminophen PK were less prominent. These data indicate that short term HLU causes significant changes in acetaminophen PK most likely associated with HUL-related hemodynamic changes. However, after 96 hour these changes diminished. This suggests hemodynamic adaptation to the HUL conditions that possibly occurs also in real space conditions.

Peterson, Amanda↗
DOE OSTI2022

Representing Global Soil Erosion and Sediment Flux in Earth System Models

Abstract Soil erosion produces enormous amounts of sediment, carbon, and nutrient fluxes from land to rivers, thus playing crucial roles in global biogeochemical cycles and food security. To predict soil erosion in the context of climate and land use changes, we explicitly parameterize cropland management actions (i.e., irrigation, conserved agriculture, and crop residue management) and geological factors (i.e., lithology and glacier) in the Energy Exascale Earth System Model (E3SM) soil erosion module. The erosion model is calibrated using a global‐scale regionalized parameter calibration method. The spatial variabilities of the modeled and the Revised Universal Soil Loss Equation (RUSLE) based benchmark soil erosion are consistent across vegetation, climate and soil properties. Compared with independent data, our model shows a bias reduction in 59% of the observations relative to the RUSLE‐based soil erosion, with 53% of the bias reduction exceeding 50%. This improvement is mainly due to a better representation of the topographic effect on soil erosion. Our results indicate that conserved agriculture practices have effectively reduced soil erosion in cropland by over 25% in the United States and Argentina. In contrast, irrigation has increased soil erosion in many Asian countries. For upland sediment flux, our model is consistent with the WBMsed benchmark data in inter‐basin variability but could be more skillful in simulating intra‐basin variability because it couples soil erosion and sediment flux explicitly. The developed model provides useful skills for more realistic predictions of soil erosion and river sediment dynamics under environmental changes.

58 GEOSCIENCES↗
DOE OSTI2021

Dataset and scripts for manuscript "Using Neural Network Ensembles to Separate Ocean Biogeochemical and Physical Drivers of Phytoplankton Biogeography in Earth System Models"

Please note: The title of this version contains an updated title for the manuscript compared to the previous version of this dataset. This is only due to title updates during the peer review process for the manuscript. The zip file contains the scripts, functions, and source files for the manuscript titled "Using Neural Network Ensembles to Separate Ocean Biogeochemical and Physical Drivers of Phytoplankton Biogeography in Earth System Models." The manuscript has been submitted for peer review. Please consult the README file for information on the specifications of the files. These files may occasionally be updated to add annotations to the scripts to make them more user friendly and to correct any errors.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRSDate not supplied

Coupled Aerosol-Chemistry Simulations of the January 2022 Eruptions of Hunga Tonga-Hunga Ha’apai in the NASA GEOS Earth System Model

The January 2022 eruptions of the underwater Hunga Tonga-Hunga Ha’apai volcano injected more than 100 Tg of water vapor and approximately 0.5 Tg of sulfur dioxide into the stratosphere. Injected materials reached as high as ~55 km in altitude, while the main plume from the eruption travelled west over Australia and the Indian Ocean between about 20 – 30 km altitude. We investigate the transport and the impact of the erupted materials in coupled aerosol-chemistry simulations performed with the NASA Goddard Earth Observing System (GEOS) Earth system model. A sulfur mechanism introduced into the Global Modeling Initiative (GMI) stratospheric-tropospheric chemistry package allows for an interactive simulation of the water vapor-chemistry impacts, and the large water vapor perturbation results in rapid conversion of sulfur dioxide to sulfate aerosol in our aerosol mechanism. We report on the results of a multi-year ensemble of simulations performed with this system that include a control ensemble (no eruption), a water vapor-only injection ensemble, and a water vapor and sulfur dioxide injection ensemble. Simulations of the near-field aerosol and chemistry transport are compared to available measurements from OMPS-LP, OMPS-NM, CALIOP, MLS, and other sensors. The extended impact of the volcanic materials on the stratospheric composition and chemistry over the next several years is further investigated in forecast simulations.

Peter Colarco↗
NASA NTRS2004

In-Space Chemical Propulsion System Model

Multiple, new technologies for chemical systems are becoming available and include high temperature rockets, very light propellant tanks and structures, new bipropellant and monopropellant options, lower mass propellant control components, and zero boil off subsystems. Such technologies offer promise of increasing the performance of in-space chemical propulsion for energetic space missions. A mass model for pressure-fed, Earth and space-storable, advanced chemical propulsion systems (ACPS) was developed in support of the NASA MSFC In-Space Propulsion Program. Data from flight systems and studies defined baseline system architectures and subsystems and analyses were formulated for parametric scaling relationships for all ACPS subsystems. The paper will first provide summary descriptions of the approaches used for the systems and the subsystems and then present selected analyses to illustrate use of the model for missions with characteristics of current interest.

Byers, David C.↗
NASA NTRS2004

In-Space Chemical Propulsion System Model

Multiple, new technologies for chemical systems are becoming available and include high temperature rockets, very light propellant tanks and structures, new bipropellant and monopropellant options, lower mass propellant control components, and zero boil off subsystems. Such technologies offer promise of increasing the performance of in-space chemical propulsion for energetic space missions. A mass model for pressure-fed, Earth and space-storable, advanced chemical propulsion systems (ACPS) was developed in support of the NASA MSFC In-Space Propulsion Program. Data from flight systems and studies defined baseline system architectures and subsystems and analyses were formulated for parametric scaling relationships for all ACPS subsystem. The paper will first provide summary descriptions of the approaches used for the systems and the subsystems and then present selected analyses to illustrate use of the model for missions with characteristics of current interest.

Byers, David C.↗
DOE OSTI2018

Attributing the Carbon Cycle Impacts of CMIP5 Historical and Future Land Use and Land Cover Change in the Community Earth System Model (CESM1)

Historical global land use and land cover change (LULCC) emissions of 160 PgC represent a third of all human CO 2 emissions from 1850 to 2010. Future land management decisions will have large impacts on the global carbon cycle, with scenarios ranging from continued deforestation and wood harvest to mitigation scenarios that reduce total emissions through afforestation and conversion to bioenergy. Here we present a systematic assessment of Community Earth System Model (CESM1) Coupled Model Intercomparison Project phase 5 (CMIP5) historic and projection simulations, with and without LULCC. For the historical period, CESM produced a Net LULCC flux of 123 PgC to the atmosphere, removing 130 PgC from ecosystems while increasing wood product pools by 7 PgC. Historical LULCC fluxes were equally divided between conversion and wood harvest fluxes. For the Representative Concentration Pathway (RCP) 4.5 afforestation scenario CESM produced a Net LULCC flux of 53 PgC to the atmosphere, removing 58 PgC out of the ecosystem and increasing wood product pools of 5 PgC. The afforestation offsets the Direct LULCC flux of 153 PgC with a negative Indirect LULCC flux of 94 PgC. For the RCP 8.5 high LULCC scenario, CESM produced a Net LULCC flux of 211 PgC, removing 227 PgC from ecosystems and increasing wood product pools of 15 PgC. The LULCC of the future RCP scenarios was dominated by wood harvest fluxes, which is a process that was not included in many of the CMIP5 models. The analysis framework also allowed the attribution of Indirect and Prior LULCC fluxes that offset the Direct LULCC fluxes in many cases.

58 GEOSCIENCES↗
DOE OSTI2024

Clusters of Regional Precipitation Seasonality Change in the Community Earth System Model, Version 2

Abstract The likely changes to precipitation seasonality with warming are both impactful and not well understood. This work aims to describe areas that experience similar changes to seasonal precipitation irrespective of the original underlying precipitation seasonality. We train a self-organizing map on the difference between the seasonal cycle of precipitation in the past and in a high-warming future climate as represented by the Community Earth System Model, version 2, to create regions with similar changes in precipitation seasonality. This method is applied separately over land and ocean surfaces because of the differing processes leading to precipitation over each. This method indicates that future changes in seasonal precipitation are most varied in the tropics because of a southward shift in the intertropical convergence zone. The seasonal shifts found over midlatitude oceans indicate a poleward shift in atmospheric river activity. We find a correspondence between certain land-based precipitation changes and Köppen climate classification. The seasonality of large-scale and convective precipitation is examined for each region. The relationship between the seasonal changes to precipitation and associated atmospheric processes is discussed. These processes include atmospheric rivers, the intertropical convergence zone, tropical cyclones, and monsoons.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Simulating Extreme Precipitation in the United States in the Energy Exascale Earth System Model: Investigating the Importance of Representing Convective Intensity versus Dynamic Structure (Final Report)

Weather events that produce extreme precipitation are associated with severe flooding and winds that result in thousands of deaths and billions of dollars in damages annually in the United States (U.S.). This project aims to improve understanding of the small- and large-scale processes that govern these events and improve our ability to project changes in these extreme events under the influences of natural variability and human activities. We focus on two promising directions in the development of the U.S. Department of Energy’s Energy Exascale Earth System Model (E3SM) to investigate the tradeoffs between resolving the convective-scale processes that control the intensity versus the intermediate-scale processes that control the dynamic structure of the most prominent extreme precipitation events that impact the U.S. throughout the year (i.e., mesoscale convective systems, tropical cyclones, and extratropical cyclone).

58 GEOSCIENCES↗
DOE OSTI2023

Investigating Future Arctic Sea Ice Loss and Near–Surface Wind Speed Changes Related to Surface Roughness Using the Community Earth System Model

The Arctic is undergoing a pronounced and rapid transformation in response to changing greenhouse gasses, including reduction in sea ice extent and thickness. There are also projected increases in near-surface Arctic wind. This study addresses how the winds trends may be driven by changing surface roughness and/or stability in different Arctic regions and seasons, something that has not yet been thoroughly investigated. We analyze 50 experiments from the Community Earth System Model Version 2 (CESM2) Large Ensemble and five experiments using CESM2 with an artificially decreased sea ice roughness to match that of the open ocean. We find that with a smoother surface there are higher mean wind speeds and slower mean ice speeds in the autumn, winter, and spring. The artificially reduced surface roughness also strongly impacts the wind speed trends in autumn and winter, and we find that atmospheric stability changes are also important contributors to driving wind trends in both experiments. In contrast to the clear impacts on winds, the sea ice mean state and trends are statistically indistinguishable, suggesting that near-surface winds are not major drivers of Arctic sea ice loss. Two major results of this work are: (a) the near-surface wind trends are driven by changes in both surface roughness and near-surface atmospheric stability that are themselves changing from sea ice loss, and (b) the sea ice mean state and trends are driven by the overall warming trend due to increasing greenhouse gas emissions and not significantly impacted by coupled feedbacks with the surface winds.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2022

History and Development of the USAF Agriculture Meteorology Modeling System and resulting USAF-NASA Strategic Partnership

The USAF Weather (AFW) supports a number of military and U.S. government agencies by providing authoritative weather analysis and forecast products for any location globally, including soil moisture analyses. The long history of supporting soil moisture products and partnering with other U.S. government agencies led to the partnering between the U.S. Air Force (USAF) and NASA Goddard Space Flight Center, resulting in a merger of those organizations’ modeling systems, collaborative development of the Land Information System (LIS), and operational fielding of the system within the USAF 557th Weather Wing [557 WW; formerly, Headquarters Air Force Weather Agency (HQ AFWA)]. In 2009, the USAF implemented the NASA LIS and later made it the primary software system to generate global soil hydrology and energy budget products. The implementation of LIS delivered a significant upgrade over the existing Land Data Assimilation System (LDAS) the USAF operated, the Agriculture Meteorology (AGRMET) system. Implementation enabled the rapid integration of new LDAS technology into USAF operations, and led to a long-term NASA–USAF partnership resulting in continued development, integration, and implementation of new LIS capabilities. This paper documents both the history of the USAF Weather organization capabilities enabling the generation of soil moisture and other land surface analysis products, and describes the USAF–NASA partnership leading to the development of the merged LIS-AGRMET system. The article also presents a successful example of a mutually beneficial partnership that has enabled cutting-edge land analysis capabilities at the USAF, while transitioning NASA software and satellite data into USAF operations.

John Eylander↗
DOE OSTI2018

Evaluating simplified chemical mechanisms within present-day simulations of the Community Earth System Model version 1.2 with CAM4 (CESM1.2 CAM-chem): MOZART-4 vs. Reduced Hydrocarbon vs. Super-Fast chemistry

Abstract. While state-of-the-art complex chemical mechanisms expand our understanding of atmospheric chemistry, their sheer size and computational requirements often limit simulations to short lengths or ensembles to only a few members. Here we present and compare three 25-year present-day offline simulations with chemical mechanisms of different levels of complexity using the Community Earth System Model (CESM) Version 1.2 CAM-chem (CAM4): the Model for Ozone and Related Chemical Tracers, version 4 (MOZART-4) mechanism, the Reduced Hydrocarbon mechanism, and the Super-Fast mechanism. We show that, for most regions and time periods, differences in simulated ozone chemistry between these three mechanisms are smaller than the model–observation differences themselves. The MOZART-4 mechanism and the Reduced Hydrocarbon are in close agreement in their representation of ozone throughout the troposphere during all time periods (annual, seasonal, and diurnal). While the Super-Fast mechanism tends to have higher simulated ozone variability and differs from the MOZART-4 mechanism over regions of high biogenic emissions, it is surprisingly capable of simulating ozone adequately given its simplicity. We explore the trade-offs between chemical mechanism complexity and computational cost by identifying regions where the simpler mechanisms are comparable to the MOZART-4 mechanism and regions where they are not. The Super-Fast mechanism is 3 times as fast as the MOZART-4 mechanism, which allows for longer simulations or ensembles with more members that may not be feasible with the MOZART-4 mechanism given limited computational resources.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1997

Environmental Assessment and Monitoring with ICAMS (Image Characterization and Modeling System) Using Multiscale Remote-Sensing Data

With the rapid increase in spatial data, especially in the NASA-EOS (Earth Observing System) era, it is necessary to develop efficient and innovative tools to handle and analyze these data so that environmental conditions can be assessed and monitored. A main difficulty facing geographers and environmental scientists in environmental assessment and measurement is that spatial analytical tools are not easily accessible. We have recently developed a remote sensing/GIS software module called Image Characterization and Modeling System (ICAMS) to provide specialized spatial analytical tools for the measurement and characterization of satellite and other forms of spatial data. ICAMS runs on both the Intergraph-MGE and Arc/info UNIX and Windows-NT platforms. The main techniques in ICAMS include fractal measurement methods, variogram analysis, spatial autocorrelation statistics, textural measures, aggregation techniques, normalized difference vegetation index (NDVI), and delineation of land/water and vegetated/non-vegetated boundaries. In this paper, we demonstrate the main applications of ICAMS on the Intergraph-MGE platform using Landsat Thematic Mapper images from the city of Lake Charles, Louisiana. While the utilities of ICAMS' spatial measurement methods (e.g., fractal indices) in assessing environmental conditions remain to be researched, making the software available to a wider scientific community can permit the techniques in ICAMS to be evaluated and used for a diversity of applications. The findings from these various studies should lead to improved algorithms and more reliable models for environmental assessment and monitoring.

Lam, N.↗