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At least 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Data Driven Commercial Building Energy Code Compliance and Technology Inventory for New York City

Building Performance Standards (BPS) are gaining national traction. A BPS will require new processes in the design, construction, and operation of buildings that take the occupants into account and enable predictive analysis to ensure compliance with current and future GHG emissions caps. In New York City, most buildings over 25,000 square feet will be regulated by a BPS starting in 2024, regardless of whether it is new construction permitted under current energy codes or an existing building. This research is one of the first to begin the evaluation of a long-term series of building policies in the context of an open data ecosystem, in cooperation with city agencies. Existing building policies enacted in NYC have ranged from building energy benchmarking and labeling to energy audits to the regulation of GHG emission in buildings. Through the development of a dataset related to building technologies and energy consumption, this project can help to evaluate if meaningful conclusions can be drawn for the data that has been largely self-reported in compliance with city regulations. This project will also provide lessons learned from a deep dive into these types of datasets to provide best practices for municipalities or states seeking to embark on policies like those enacted in NYC. In addition, a Building Automation System (BAS) Stretch Standard of Care (SSOC) for owners, designers, and building operators will enable the measurement and predictive analysis of energy consumption and GHG emissions at the plant, system, or component level, in anticipation of regulated GHG limits on buildings based on energy use. The SSOC is expected to be suitable for use on a national level. The primary feature of an SSOC is a standardized format for a set of BAS points that can be used to control and to gather data from individual plants, systems, or components that are related to building energy consumption. This project examined how measurements compare to prescriptive or simulation-based energy code targets, finding little correlation between predictive 8760-hour energy modeling and actual energy consumption for a small sample (n=27) of buildings constructed after 2015. Other analysis found that, while large multifamily housing (MFH) buildings showed a general trend similar to predicted reductions in energy use from the implementation of model commercial energy codes, this trend was not evident in the office, K-12 school, and hotel use groups in NYC. No upward or downward trends in energy consumption were found when buildings were grouped by size. Energy audit data were analyzed and it appears that there is bias by audit company on measures recommended to clients. Further research should be performed to cross-analyze this with other attributes, such as building size, vintage, and number of stories. Analysis found that for 281 buildings that were permitted and completed after 2015 and had submitted benchmarking data in 2022, between 81% and 96% (by use group) were found to be in compliance with the 2024 to 2029 NYC BPS emission caps, and between 55% and 89% were in compliance with the 2030-2034 caps. This work is beneficial to the public in helping policymakers and building stakeholders better understand the wide-ranging implications of a BPS.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
NASA NTRS1983

Wildland inventory and resource modeling for Douglas and Carson City Counties, Nevada, using LANDSAT and digital terrain data

The potential of using LANDSAT satellite imagery to map and inventory pinyon-juniper desert forest types in Douglas and Carson City Counties, Nevada was demonstrated. Specific map and statistical products produced include land cover, mechanical operations capability, big game winter range habitat, fire hazard, and forest harvestability. The Nevada Division of Forestry determined that LANDSAT can produce a reliable and low-cost resource data. Added benefits become apparent when the data are linked to a geographical information system (GIS) containing existing ownership, planning, elevation, slope, and aspect information.

Brass, J. A.↗
DOE OSTI2021

Fossil fuel CO 2 emissions over metropolitan areas from space: A multi-model analysis of OCO-2 data over Lahore, Pakistan

Urban areas, where gathering more than 55% of the global population, alone contributed to more than 70% of anthropogenic fossil fuel carbon dioxide (CO 2ff ) emissions. Accurate quantification of CO 2ff emissions from urban areas is of great importance to the formulation of global warming mitigation policies to achieve carbon neutrality by 2050. Satellite-based inversion techniques are unique among “top-down” approaches, potentially allowing us to track CO 2ff emission changes over cities globally. However, its accuracy is still limited by incomplete background information, cloud blockages, aerosol contaminations, and uncertainties in models and emission inventories used as prior. To evaluate the current potential of space-based quantification techniques, we present the first attempt to monitor long-term changes in CO 2ff emissions based on the OCO-2 satellite measurements of column-averaged dry-air mole fractions of CO 2 (X CO2 ) over a fast-growing Asian metropolitan area: Lahore, Pakistan. We first examined the OCO-2 data availability at global scale. About 17% of OCO-2 soundings are marked as high-quality soundings by quality flags over the global 70 most populated cities over the period 2014-2019. Cloud blockage and aerosol contamination are the two main causes of data loss. As an attempt to recover additional soundings, we evaluated the effectiveness of OCO-2 quality flags at the city level by comparing three flux quantification methods (WRF-Chem, X-STILT, and flux cross-sectional integration method), all based on the Open-Data Inventory for Anthropogenic Carbon dioxide (ODIAC) product. The satellite/bottom-up emissions (OCO-2/ODIAC) ratios of the high-quality tracks better converged across the three methods compared to the all-data tracks with reduced uncertainties in emissions. Thus, OCO-2 quality flags are useful filters of low-quality OCO-2 retrievals at local scales, although originally designed for global-scale studies. All three methods consistently suggested that the ratio medians are greater than 1, which implies that the ODIAC slightly underestimated the CO2ff emissions over Lahore. Additionally, our estimation of the a posteriori CO2ff emission trend was about 734 kt C/year (i.e., an annual 6.7% increase). 10,000 Monte Carlo simulations of the Mann-Kendall upward trend test showed that less than 10% prior uncertainty for 8 tracks (or less than 20% prior uncertainty for 25 tracks) is required to achieve a greater-than-50% trend significant possibility at a 95% confidence level. It implies that the trend is driven by the prior and not due to the assimilation of OCO-2 retrievals. The key to improving the role of satellite data in CO 2 emission trend detection lies in collecting more frequent high-quality tracks near metropolitan areas to achieve significant constraints from X CO2 retrievals.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS1976

Applications of feature selection

The use of satellite-acquired (LANDSAT) multispectral scanner (MSS) data to conduct an inventory of some crop of economic interest such as wheat over a large geographical area is considered in relation to the development of accurate and efficient algorithms for data classification. The dimension of the measurement space and the computational load for a classification algorithm is increased by the use of multitemporal measurements. Feature selection/combination techniques used to reduce the dimensionality of the problem are described.

Guseman, L. F., Jr.↗
DOE OSTI2020

Characterization of the β-Phrase Region of the SAS Compressor Bed 1 Material (LANA10)

Isotherm data have been acquired and analyzed on the SAS Compressor Bed 1 material in order to define a method to set the initial bed Q/M value when freshly filled after inventory. β-phase data from eleven protium and two deuterium isotherms have been combined to determine a method for calculating the bed Q/M value given a β-phase equilibrium pressure at temperature. This method is a two-step method; first, the plateau pressure is calculated based on the isotope used and the temperature of the bed, and second, the measured equilibrium pressure is divided by the computed plateau pressure to obtain the reduced pressure, which is then inserted into the β-phase equation to calculate the bed’s Q/M value. Error sources and effects are discussed, with the conclusion that the ‘true’ reduced isotherm has been determined in the β-phase which will allow virgin bed inventory to be determined to ~3-4% accuracy.

36 MATERIALS SCIENCE↗
NASA NTRS1990

Space Data for Crop Management

CROPIX, Inc., formed in 1984 by Frank Lamb, president of the Eastern Oregon Farming Company, monitors primarily potato crops in a 20,000 square mile area of northern Oregon and central Washington. Potatoes are a high value specialty crop that can be more profitable to the farmer if he has advance knowledge of market conditions, knows when to harvest, and when to take it to market. By processing and collecting data collected by the NASA-developed Landsat Earth Resources survey satellites, Lamb is able to provide accurate information on crop acreage and conditions on a more timely basis than the routine estimates by the USDA. CROPIX uses Landsat data to make acreage estimates of crops, and to calculate a field-by-field vegetative index number. CROPIX then distributes to its customers a booklet containing color-coded maps, an inventory of crops, plus data and graphs on crop conditions and other valuable information.

Source record↗
NASA NTRS2018

Fire Analysis of the Thomas Fire in California Using NASA Data in a GIS

NASA's Earth Observing System Data Information System (EOSDIS) manages Earth Observation satellites and the Distributed Active Archive Centers (DAACs), where the data is stored and processed. This poster presents the use of satellite data from NASA's inventory that have the potential for use in identification and analysis of forest fire risk and subsequent after-effects within a geographic information system (GIS). The challenge is that Earth Observation data is complicated. There is plenty of data available, however, the science teams have had a "top-down" approach: define what it is you are trying to study -select a set of satellite(s) and sensor(s), and drill down for the data.

Worldview↗
NASA NTRS1980

Landsat for practical forest type mapping - A test case

Computer classified Landsat maps are compared with a recent conventional inventory of forest lands in northern Maine. Over the 196,000 hectare area mapped, estimates of the areas of softwood, mixed wood and hardwood forest obtained by a supervised classification of the Landsat data and a standard inventory based on aerial photointerpretation, probability proportional to prediction, field sampling and a standard forest measurement program are found to agree to within 5%. The cost of the Landsat maps is estimated to be $0.065/hectare. It is concluded that satellite techniques are worth developing for forest inventories, although they are not yet refined enough to be incorporated into current practical inventories.

Bryant, E.↗
NASA NTRS1973

ERTS data user investigation to develop a multistage forest sampling inventory system

The author has identified the following significant results. A system to provide precision annotation of predetermined forest inventory sampling units on the ERTS-1 MSS images was developed. In addition, an annotation system for high altitude U2 photographs was completed. MSS bulk image accuracy is good enough to allow the use of one square mile sampling units. IMANCO image analyzer interpretation work for small scale images demonstrated the need for much additional analyses. Continuing image interpretation work for the next reporting period is concentrated on manual image interpretation work as well as digital interpretation system development using the computer compatible tapes.

Langley, P. G.↗
NASA NTRS1973

ERTS data user investigation to develop a multistage forest sampling inventory system

The author has identified the following significant results. A unique digital timber volume estimation system was developed for use with the MSS CCT tapes. The system was tested on a 64-square mile area in Northern California's Trinity Alps. The outcome of a systematic experiment, in which several possible combinations of bands 5 and 7 and a contrast measure were tried, showed that an estimated gain in precision of 50% can be obtained in a multistage sampling design. The difference between bands 5 and 7 proved to be of special importance for the estimation of biomass in the form of timber volume. In addition, an interpretation model for high flight U2 photographs was developed. A maximum multiple correlation coefficient of 0.74 was obtained for the regression model, explaining 55% of the variation in timber volume as estimated from aerial photos and ground measurments. An interpretation model for MSS color composites is in the testing stage.

Langley, P. G.↗
NASA NTRS1986

Calculations of cosmogenic nuclide production rates in the Earth's atmosphere and their inventories

The production rates of cosmogenic isotopes in the Earth's atmosphere and their resulting terrestrial abundances have been calculated, taking into account both geomagnetic and solar-modulatory effects. The local interstellar flux was assumed to be that of Garcia-Munoz, et al. Solar modulation was accounted for using the heliocentric potential model and expressed in terms of the Deep River neutron monitor count rates. The geomagnetic field was presented by vertical cutoffs calculated by Shea and Smart and the non-vertical cutoffs calculated using ANGRI. The local interstellar particle flux was first modulated using the heliocentric potential field. The modulated cosmic-ray fluxes reaching the earth's orbit then interacted with the geomagnetic field as though it were a high-pass filter. The interaction of the cosmic radiation with the Earth's atmosphere was calculated utilizing the Bolztmann transport equation. Spallation cross sections for isotope production were calculated using the formalism of Silberberg and Tsao and other cross sections were taken from standard sources. Inventories were calculated by accounting from the variation in solar modulation and geomagnetic field strength with time. Results for many isotope, including C-14, Be-7 and Be-10 are in generally good agreement with existing data. The C-14 inventory, for instance, amounts to 1.75/sq cm(e)/s, in excellent agreement with direct estimates.

Obrien, K.↗
NASA NTRS1990

Space Shuttle Orbiter logistics - Managing in a dynamic environment

The importance and methods of monitoring logistics vital signs, logistics data sources and acquisition, and converting data into useful management information are presented. With the launch and landing site for the Shuttle Orbiter project at the Kennedy Space Center now totally responsible for its own supportability posture, it is imperative that logistics resource requirements and management be continually monitored and reassessed. Detailed graphs and data concerning various aspects of logistics activities including objectives, inventory operating levels, customer environment, and data sources are provided. Finally, some lessons learned from the Shuttle Orbiter project and logistics options which should be considered by other space programs are discussed.

Renfroe, Michael B.↗
NASA NTRS2003

The Aura Mission and Its Application to Climate and Air Quality

NASA's Aura satellite is scheduled to launch in the second quarter of 2004 into a polar orbit. The Aura mission is designed to collect data to address three high priority environmental science questions: (1) Is the ozone layer recovering as expected? (2) What are the sources and processes that control tropospheric pollutants? And (3) what is the quantitative impact of constituents on climate change? Aura will answer these questions by globally measuring a comprehensive set of trace gases and aerosols in the troposphere and stratosphere. Aura data will also have applications for monitoring and predicting climate and air quality parameters. Aura s observations will continue the TOMS ozone trend record and provide an assessment as to whether the Montreal Protocol is achieving its objective. Aura will measure gases and aerosols in the upper troposphere and lower stratosphere that contribute to climate forcing. These data will be of sufficient coverage, vertical resolution, and accuracy to help constrain climate models. In addition, Aura observations of tropospheric ozone and its precursors will have regional as well as intercontinental coverage, which could improve emission inventories. Near real time data will tested for local air quality forecasts in collaboration with the US's Environmental Protection UV-B forecasts from Aura ozone and cloud cover data. An overview of Aura s instruments, data products, validation, and examples of data applications will be presented.

Hilsenrath, Ernest↗
NASA NTRS1983

A summary of the history of the development of automated remote sensing for agricultural applications

The research conducted in the United States for the past 20 years with the objective of developing automated satellite remote sensing for monitoring the earth's major food crops is reviewed. The highlights of this research include a National Academy of Science study on the applicability of remote sensing monitoring given impetus by the introduction in the mid-1960's of the first airborne multispectral scanner (MSS); design simulations for the first earth resource satellite in 1969; and the use of the airborne MSS in the Corn Blight Watch, the first large application of remote sensing in agriculture, in 1970. Other programs discussed include the CITAR research project in 1972 which established the feasibility of automating digital classification to process high volumes of Landsat MSS data; the Large Area Crop Inventory Experiment (LACIE) in 1974-78, which demonstrated automated processing of Landsat MSS data in estimating wheat crop production on a global basis; and AgRISTARS, a program designed to address the technical issues defined by LACIE.

Macdonald, R. B.↗
NASA NTRS2020

Critical land change information enhances the understanding of carbon balance in the United States

Large‐scale terrestrial carbon (C) estimating studies using methods such as atmospheric inversion, biogeochemical modeling, and field inventories have produced different results. The goal of this study was to integrate fine‐scale processes including land use and land cover change into a large‐scale ecosystem framework. We analyzed the terrestrial C budget of the conterminous United States from 1971 to 2015 at 1‐km resolution using an enhanced dynamic global vegetation model and comprehensive land cover change data. Effects of atmospheric CO2 fertilization, nitrogen deposition, climate, wildland fire, harvest, and land use/land cover change (LUCC) were considered. We estimate annual C losses from cropland harvest, forest clearcut and thinning, fire, and LUCC were 436.8, 117.9, 10.5, and 10.4 TgC/year, respectively. C stored in ecosystems increased from 119,494 to 127,157 TgC between 1971 and 2015, indicating a mean annual net C sink of 170.3 TgC/year. Although ecosystem net primary production increased by approximately 12.3 TgC/year, most of it was offset by increased C loss from harvest and natural disturbance and increased ecosystem respiration related to forest aging. As a result, the strength of the overall ecosystem C sink did not increase over time. Our modeled results indicate the conterminous US C sink was about 30% smaller than previous modeling studies, but converged more closely with inventory data.

carbon sequestration↗
NASA NTRS2007

Using High Frequency Passive Microwave, A-train, and TRMM Data to Evaluate Hydrometer Structure in the NASA GEOS-5 Data Assimilation System

Validating water vapor and prognostic condensate in global models remains a challenging research task. Model parameterizations are still subject to a large number of tunable parameters; furthermore, accurate and representative in situ observations are very sparse, and satellite observations historically have significant quantitative uncertainties. Progress on improving cloud / hydrometeor fields in models stands to benefit greatly from the growing inventory ofA-Train data sets. ill the present study we are using a variety of complementary satellite retrievals of hydrometeors to examine condensate produced by the emerging NASA Modem Era Retrospective Analysis for Research and Applications, MERRA, and its associated atmospheric general circulation model GEOS5. Cloud and precipitation are generated by both grid-scale prognostic equations and by the Relaxed Arakawa-Schubert (RAS) diagnostic convective parameterization. The high frequency channels (89 to 183.3 GHz) from AMSU-B and MRS on NOAA polar orbiting satellites are being used to evaluate the climatology and variability of precipitating ice from tropical convective anvils. Vertical hydrometeor structure from the Tropical Rainfall Measuring Mission (TRMM) and CloudSat radars are used to develop statistics on vertical hydrometeor structure in order to better interpret the extensive high frequency passive microwave climatology. Cloud liquid and ice water path data retrieved from the Moderate Resolution Imaging Spectroradiometer, MODIS, are used to investigate relationships between upper level cloudiness and tropical deep convective anvils. Together these data are used to evaluate cloud / ice water path, gross aspects of vertical hydrometeor structure, and the relationship between cloud extent and surface precipitation that the MERRA reanalysis must capture.

Robertson, Franklin↗
DOE OSTI2021

Assessing the Consistency of Estimated Ground Cover Fractions between the BLM AIM Method and Optical Remote Sensing Method

Since 2012, Argonne National Laboratory (Argonne) has supported the Bureau of Land Management (BLM) in developing remote sensing methodologies for long-term environmental monitoring of Palo Verde Mesa in eastern Riverside County, California, including methods for: detailed mapping of ephemeral streams, estimating fractional cover of desert-land surface components (e.g., trees, shrubs, litters, and bare ground), evaluating erosion risk or land stability, and characterizing vegetation alliances using spatial structure and geostatistical approaches. These studies showed the promise of remote sensing for monitoring changes in desert landscapes by providing information that would be difficult to obtain through field surveys. During this time the BLM has also worked to establish long-term monitoring protocols and compiled field-observation data collected using standardized protocols from the Assessment, Inventory, and Monitoring (AIM) strategy. The AIM data can be compared to data derived from remote sensing methods to evaluate their relative operational utility in monitoring landscape change. If ground cover estimated using remotely sensed imagery is comparable to AIM ground cover estimates, then remote sensing can be used to monitor whether any land cover change in desert landscapes may be related to solar energy development. Therefore, the goal of this study was to determine the consistency in ground cover estimates between AIM data and those derived from publicly- available remotely sensed imagery, such as that available through the U.S. Department of Agriculture, National Agricultural Imagery Program (NAIP), to examine feasibility of a remote sensing method for complementing AIM monitoring. Based on the image analysis in this study, we also provide recommendations for how small unmanned aerial system (sUAS) data may be used to complement BLM’s AIM data and NAIP imagery for future vegetation monitoring. The ground cover types we originally planned to investigate were trees, shrubs, and bare ground. However, the small sample size and a limited range of cover fraction of trees and shrubs in the AIM dataset (e.g., 33 samples with a maximum shrub cover of 18%, 14 samples with a maximum tree cover of 17%) did not allow for performing a meaningful evaluation for the remote sensing approach. Therefore, we conducted the study focusing on bare ground, foliar, and rock cover, all of which are indicators reported in the AIM remote sensing dataset.

47 OTHER INSTRUMENTATION↗