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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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
NASA NTRS2018

Intercomparison of MODIS AQUA and VIIRS I-Band Fires and Emissions in an Agricultural Landscape - Implications for Air Pollution Research

Quantifying emissions from crop residue burning is crucial as it is a significant source of air pollution. In this study, we first compared the fire products from two different sensors, the Visible Infrared Imaging Radiometer Suite (VIIRS) 375 m active fire product (VNP14IMG) and Moderate Resolution Imaging Spectroradiometer (MODIS) 1 km fire product (MCD14ML) in an agricultural landscape, Punjab, India. We then performed an intercomparison of three different approaches for estimating total particulate matter (TPM) emissions which includes the fire radiative power (FRP) based approach using VIIRS and MODIS data, the Global Fire Emissions Database (GFED) burnt area emissions and a bottom-up emissions approach involving agricultural census data. Results revealed that VIIRS detected fires were higher by a factor of 4.8 compared to MODIS Aqua and Terra sensors. Further, VIIRS detected fires were higher by a factor of 6.5 than Aqua. The mean monthly MODIS Aqua FRP was found to be higher than the VIIRS FRP; however, the sum of FRP from VIIRS was higher than MODIS data due to the large number of fires detected by the VIIRS. Besides, the VIIRS sum of FRP was 2.5 times more than the MODIS sum of FRP. MODIS and VIIRS monthly FRP data were found to be strongly correlated (r2 = 0.98). The bottom-up approach suggested TPM emissions in the range of 88.19-91.19 Gg compared to 42.0-61.71 Gg, 42.59-58.75 Gg and 93.98-111.72 Gg using the GFED, MODIS FRP, and VIIRS FRP based approaches, respectively. Of the different approaches, VIIRS FRP TPM emissions were highest. Since VIIRS data are only available since 2012 compared to MODIS Aqua data which have been available since May 2002, a prediction model combining MODIS and VIIRS FRP was derived to obtain potential TPM emissions from 2003-2016. The results suggested a range of 2.56-63.66 (Gg) TPM emissions per month, with the highest crop residue emissions during November of each year. Our results on TPM emissions for seasonality matched the ground-based data from the literature. As a mitigation option, stringent policy measures are recommended to curtail agricultural residue burning in the study area.

Global Fire Emissions Database (GFED)↗
NASA NTRS2017

Mapping Threats to Agriculture in East Africa: Performance of MODIS Derived LST for Frost Identification in Kenya's Tea Plantations

Increased prevalence of weather related hazards in eastern Africa including drought, floods, hail and frost threatening agricultural productivity. Kenya is heavily dependent on agriculture for economic growth (FAO 2013); (1) Agriculture contributed 23.5% and 21.5% of GDP in 2009 and 2010 respectively, (2) Employment to half a million households of smallholders and 150,000 on large tea estates. Tea growing in Kenya depends on stability of the weather; (1) Weather is unpredictable, (2) Frost has contributed 30% of tea leaf losses, (3) Drought has contributed 14-30%, (4) The losses are experienced between January and march - frost and dry season.

remote sensing↗
NASA NTRS2019

Evaluating the Operational Application of SMAP for Global Agricultural Drought Monitoring

Over the past two decades, remote sensing has made possible the routine global monitoring of surface soil moisture. Regionalagricultural drought monitoring is one of the most logicalapplication areas for such monitoring. However, remote sensing alone provides soil moisture information for only the top few centimetersof the soil profile, while agricultural drought monitoring requires knowledge of the amount of water present in the entireroot zone. The assimilation of remotely sensed soil moisture productsinto continuous soil water balance models provides a way ofaddressing this shortcoming. Here, we describe the assimilationof NASA's soil moisture active passive (SMAP) surface soil moisture data into the United States Department of Agriculture Foreign Agricultural Service (USDA FAS) Palmer model and assess the impactof SMAP on USDA FAS drought monitoring capabilities. Theassimilation of SMAP is specifically designed to enhance the model skill and the USDA FAS drought capabilities by correcting for randomerrors inherent in its rainfall forcing data. The performanceof this SMAP-based assimilation system is evaluated using two approaches.At global scale, the accuracy of the system is assessed by examining the lagged correlation agreement between soil moistureand the normalized difference vegetation index (NDVI). Additional regional-scale evaluation using in situ-based soil moisture estimatesis carried out at seven of the SMAP core Cal/Val sites located in theUSA. Both types of analysis demonstrate the value of assimilating SMAP into the USDA FAS Palmer model and its potential to enhance operational USDA FAS root-zone soil moisture information.

Mladenova, Iliana E.↗
NASA NTRS2020

A Multi-Modal Approach for Monitoring Changes in Agriculture in the Mekong River Delta

Smallholder farms in South East Asia are characterized by small irregular field patterns, dense cloud cover and haze which limits our ability to observe changes in agriculture land-use. Very-high resolution (VHR, < 5 m) Earth observing (EO) satellites have grown into constellations with global repeat coverage that can support multiple observations within a growing season. Here we present a multi-modal approach to map and monitor changes in agriculture at the field scale in the Mekong River Delta with VHR optical imagery from Worldview-1, 2 and 3, and synthetic aperture radar (SAR) from Sentinel-1. Our approach leverages the benefits of SAR and VHR imagery with geographic object-based image analysis (GEOBIA) in a high-end computing environment to rapidly map the distribution and size of agriculture fields that are not observable at moderate resolution (> 30 m) in regions with dense persistent cloud cover and haze from biomass burning.

Christopher S R Neigh↗
NASA NTRS2021

Midwest Food Security & Agriculture II: Leveraging NASA Earth Observations to Analyze and Display Crop Phenology Data and Weather Conditions to Support Expansion of Small Grain Crops in the Midwest

Agriculture in the Midwest is dominated by monoculture systems that strip the soil of nutrients, decrease yields, and worsen water quality. Crop diversification and cultivating small grains is economically and ecologically advantageous, but limited in practice due to a lack of data about small-grain crop performance as well as monoculture-favoring insurance coverage, economic incentives, and sociocultural traditions. Practical Farmers of Iowa (PFI) strives to create more sustainable agriculture and supports Midwestern farmers in adding small grains into their crop rotations. The DEVELOP team partnered with the USDA Agricultural Research Service and the USA National Phenology Network to assist PFI in applying NASA Earth observation data to track small-grain crop performance. This project developed a Google Earth Engine user interface that enables PFI farmers to compare satellite-assessed vegetation production and climatic conditions of their farm with other PFI farmers. The team assessed the crop performance through Normalized Difference Vegetation Index (NDVI) values derived from Landsat 7 Enhanced Thematic Mapper Plus (ETM+) and Landsat 8 Operational Land Imager (OLI). Additionally, the team created a regression model to analyze the predictive properties of vegetation indices and crop yield, ultimately establishing a relationship with mean NDVI from the early growing season. PFI farmers can utilize these products to make informed decisions about their crop production as well as advocate for more expansive insurance policies to protect small-grain crops.

Sophie Barrowman↗
NASA NTRS2022

Midwest Water Resources II: Evaluating Evapotranspiration with NASA Earth Observations and In Situ Observations to Understand Water Balance in Midwest Agriculture

Seasonal water variability in the midwestern United States extensively affects the agricultural community, as it impacts irrigation schedules, growing seasons, and overall ecosystem function. Evapotranspiration (ET) is a critical climatic variable in the water cycle and is used to evaluate spatiotemporal trends in drought and flood conditions. The NASA DEVELOP team partnered with the United States Department of Agriculture (USDA) Midwest Climate Hub, the Minnesota Department of Agriculture, the Illinois State Water Survey, and Michigan State University to compare remotely sensed ET products with in situ observations from January 2001 through December 2020. Remotely sensed actual ET (aET) data were sourced from NASA’s Terra Moderate Resolution Imaging Spectroradiometer (MODIS), and reference ET (refET) data were derived from the Gridded Surface Meteorological (gridMET) dataset. For in situ comparison, aET data were downloaded from the AmeriFlux database while refET data were collected from the Illinois Climate Network and Michigan State University’s Enviro-weather database. For a holistic assessment of ET, this project generated comparisons between remotely sensed and in situ observations, calculated descriptive statistics for validation between refET datasets, and spatially produced statistical validation maps regarding in situ sites. The temporal and spatial gaps of AmeriFlux data limited aET analysis. This comparative assessment of ET products across the Midwest can be used by project partners to assess regional water trends and guide future land management decisions.

Addison Pletcher↗
NASA NTRS2023

Measurement Report :Emission Factors of NH3 and NHx for Wildfires and Agricultural Fires in the United States

During the 2019 Fire Influence on Regional to Global Environments and Air Quality (FIREX-AQ) study, the NASA DC-8 carried out in situ chemical measurements in smoke plumes emitted from wildfires and agricultural fires in the contiguous United States. The DC-8 payload included a modified proton-transfer-reaction time-of-flight mass spectrometer (PTR-ToF-MS) for the fast measurement of gaseous ammonia (NH 3 ) and a high-resolution time-of-flight aerosol mass spectrometer (AMS) for the fast measurement of submicron particulate ammonium (NH 4 + ). We herein report data collected in smoke plumes emitted from 6 wildfires in the Western United States, 2 prescribed grassland fires in the Central United States, 1 prescribed forest fire in the Southern United States, and 66 small agricultural fires in the Southeastern United States. Smoke plumes contained double to triple digit ppb levels of NH 3 . In the wildfire plumes, a significant fraction of NH 3 had already been converted to NH 4 + at the time of sampling (≥2 h after emission). Substantial amounts of NH 4 + were also detected in freshly emitted smoke from corn and rice field fires. We herein present a comprehensive set of emission factors of NH 3 and NH x , with NH x = NH 3 + NH 4 + . Average NH 3 and NH x emission factors for wildfires in the Western United States were 1.86±0.75 g kg −1 and 2.47±0.80 g kg −1 of fuel burned, respectively. Average NH 3 and NH x emission factors for agricultural fires in the Southeastern United States were 0.89±0.58 and 1.74±0.92 g kg −1 , respectively. Our data show no clear inverse correlation between modified combustion efficiency (MCE) and NH 3 emissions. The observed NH 3 emissions were significantly higher than measured in previous laboratory experiments in the FIREX FireLab 2016 study.

Laura Tomsche↗
NASA NTRS2015

AgMIP's Transdisciplinary Agricultural Systems Approach to Regional Integrated Assessment of Climate Impacts, Vulnerability, and Adaptation

This chapter describes methods developed by the Agricultural Model Intercomparison and Improvement Project (AgMIP) to implement a transdisciplinary, systems-based approach for regional-scale (local to national) integrated assessment of agricultural systems under future climate, biophysical, and socio-economic conditions. These methods were used by the AgMIP regional research teams in Sub-Saharan Africa and South Asia to implement the analyses reported in their respective chapters of this book. Additional technical details are provided in Appendix 1.The principal goal that motivates AgMIP's regional integrated assessment (RIA) methodology is to provide scientifically rigorous information needed to support improved decision-making by various stakeholders, ranging from local to national and international non-governmental and governmental organizations.

agriculture↗
NASA NTRS2015

Growing Food for Space and Earth: NASA's Contributions to Vertical Agriculture

Beginning in the 1980s with NASA's Controlled Ecological Life Support System (CELSS) Program and later the 1990s and early 2000s with the Advanced Life Support Project, NASA conducted extensive testing with crops in controlled environment conditions. One series of tests conducted at Kennedy Space Center used a large chamber with vertically stacked shelves to support hydroponic growing trays, with a bank of electric lamps above each shelf. This is essentially the same approach that has become popular for use in so-called vertical agriculture systems, which attempts to optimize plant production in a fixed volume. Some of the findings and commonalities of NASA's work during this period and how it overlaps with current interests in vertical agriculture will be presented in the talk.

Controlled Environment Agriculture↗
NASA NTRS2015

The Agricultural Model Intercomparison and Improvement Project (AgMIP) Town Hall

AgMIP (www.agmip.org) is an international community of climate, crop, livestock, economics, and IT experts working to further the development and application of multi-model, multi-scale, multi-disciplinary agricultural models that can inform policy and decision makers around the world. This meeting will engage the AGU community by providing a brief overview of AgMIP, in particular its new plans for a Coordinated Global and Regional Assessment of climate change impacts on agriculture and food security for AR6. This Town Hall will help identify opportunities for participants to become involved in AgMIP and its 30+ activities.

farm crops↗
NASA NTRSDate not supplied

Calculator for Agricultural Water Use Fractions in California

Improved quantification of agricultural water use efficiency is a primary focus of California's Water Conservation Act. The California Department of Water Resources (CDWR), after extensive stakeholder consultation, has published methods and indicators to help identify opportunities for improved efficiency of irrigation management at various spatial scales. Additional 2017 legislation directs water suppliers to quantify water use efficiency using the CDWR metrics to support preparation of agricultural water management plans. The IrriQuest calculator derives the Crop Consumptive Use Fraction (CCUF), a foundational metric relating seasonal crop evapotranspiration (ET) to total applied water. Satellite normalized difference vegetation index (NDVI) data are used to develop fractional canopy cover timeseries. Additional key inputs include daily reference ET, irrigation volume, irrigation method, precipitation, soil texture and crop type. IrriQuest estimates of seasonal crop ET show less than 10% mean absolute error compared to ground-based measurements of several annual and perennial crops monitored by sensor deployment in commercial fields. Two additional indicators build on CCUF. The Agronomic Water Use Fraction adds consideration of water applied for beneficial purposes such as pre-plant soil preparation, soil salinity management, and climate control. Total Water Use Fraction additionally accounts for water applied for environmental purposes such as maintenance of wetland and riparian habitat. A convenient on-line portal is under development for CCUF estimation and a standalone spreadsheet is available for computation of all three use fractions.

Calculator↗
NASA NTRS2020

Fusion Approach for Remotely-Sensed Mapping of Agriculture (FARMA): A Scalable Open Source Method for Land Cover Monitoring Using Data Fusion

The increasing availability of very-high resolution (VHR; <2 m) imagery has the potential to enable agricultural monitoring at increased resolution and cadence, particularly when used in combination with widely available moderate-resolution imagery. However, scaling limitations exist at the regional level due to big data volumes and processing constraints. Here, we demonstrate the Fusion Approach for Remotely-Sensed Mapping of Agriculture (FARMA), using a suite of open source software capable of efficiently characterizing time-series field-scale statistics across large geographical areas at VHR resolution. We provide distinct implementation examples in Vietnam and Senegal to demonstrate the approach using WorldView VHR optical, Sentinel-1 Synthetic Aperture Radar, and Sentinel-2 and Sentinel-3 optical imagery. This distributed software is open source and entirely scalable, enabling large area mapping even with modest computing power. FARMA provides the ability to extract and monitor sub-hectare fields with multisensor raster signals, which previously could only be achieved at scale with large computational resources. Implementing FARMA could enhance predictive yield models by delineating boundaries and tracking productivity of smallholder fields, enabling more precise food security observations in low and lower-middle income countries.

fusion↗
NASA NTRS1970

A semi-operational agricultural inventory using small scale aerial photography

The feasibility of performing inventories of agricultural resources using very small scale aerial or space photography was studied. The results were encouraging on two counts: (1) The very practical problems of an operational survey are being faced and solutions are being found. (2) It seems that a fully operational agricultural inventory using space photography is not beyond the scope of present technology.

Draeger, W. C.↗
NASA NTRS1971

The Use of Small Scale Aerial Photography in a Regional Agricultural Survey

The feasibility of performing inventories of agricultural resources using very small scale aerial or space photography has been investigated. Results to date are encouraging on two counts: (1) the questions posed initially are being answered, and (2) it would seem that a fully operational agricultural inventory using very small scale photography is not beyond the scope of present technology. The biggest problems to be faced in establishing a functional inventory system are those concerning logistics and data handling.

Draeger, W. C.↗
NASA NTRS1973

The results of an agricultural analysis of the ERTS-1 MSS data at the Johnson Space Center

The initial analysis of the ERTS-1 multispectral scanner (MSS) data at the Johnson Space Center (JSC), Houston, Texas is discussed. The primary data set utilized was the scene over Monterey Bay, California, on July 25, 1972, NASA ERTS ID No. 1002-18134. It was submitted to both computerized and image interpretative processing. An area in the San Joaquin Valley was submitted to an intensive evaluation of the ability of the data to (1) discriminate between crop types and (2) to provide a reasonably accurate area measurement of agricultural features of interest. The results indicate that the ERTS-1 MSS data is capable of providing the identifications and area extent of agricultural lands and field crop types.

Bizzell, R. M.↗
NASA NTRS1973

Agricultural applications of ERTS-1 data

In an attempt to evaluate the usefulness of ERTS imagery for the production of land use stratifications as a preliminary step in the crop inventory process, all land within San Joaquin County was delineated into broad land use and crop category classes based on their appearance on the ERTS-1 Color composite image. The stratification of the agricultural land use categories proved to be a relatively simple task, taking each of three interpreters approximately 30 minutes to complete. The three interpretations were quite similar requiring only minor revisions to produce a consensus stratification. A total of 13 different agricultural strata were recognized, differing both in general field size and relative proportions of crop types and degree of irrigation. Upon comparing these interpretations, it was concluded that nearly all boundaries were truly representative of differing cropping practices. In a number of cases, the stratifications agreed almost exactly with soil type boundaries as drawn by earlier soils surveys.

Draeger, W. C.↗
NASA NTRS1973

Mapping of agricultural land use from ERTS-1 digital data

A study area was selected in Lancaster and Lebanon Counties, two of the major agricultural counties in Pennsylvania. This area was delineated on positive transparencies on MSS data collected on October 11, 1972 (1080-15185). Channel seven was used to delineate general land forms, drainage patterns, water and urban areas. Channel five was used to delineate highway networks. These identifiable features were useful aids for locating areas on the computer output. Computer generated maps were used to delineate broad land use categories, such as forest land, agricultural land, urban areas and water. These digital maps have a scale of approximately 1:24,000 thereby allowing direct comparison with U.S.G.S. 7.5 minute quadrangle sheets. Aircraft data were used as a form of ground truth useful for the delineation of land use patterns.

Wilson, A. D.↗
NASA NTRS1973

Impact of nowcasting on the production and processing of agricultural crops

The value was studied of improved weather information and weather forecasting to farmers, growers, and agricultural processing industries in the United States. The study was undertaken to identify the production and processing operations that could be improved with accurate and timely information on changing weather patterns. Estimates were then made of the potential savings that could be realized with accurate information about the prevailing weather and short term forecasts for up to 12 hours. This weather information has been termed nowcasting. The growing, marketing, and processing operations of the twenty most valuable crops in the United States were studied to determine those operations that are sensitive to short-term weather forecasting. Agricultural extension specialists, research scientists, growers, and representatives of processing industries were consulted and interviewed. The value of the crops included in this survey and their production levels are given. The total value for crops surveyed exceeds 24 billion dollars and represents more than 92 percent of total U.S. crop value.

Dancer, W. S.↗