Search NASA⌕ Search

SEARCH · Search NASA

Results for “cropland”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Tracking cropland transitions: A comparative analysis of U.S. land cover change data

There are a growing number of land cover data available for the conterminous United States, supporting various applications ranging from biofuel regulatory decisions to habitat conservation assessments. These datasets vary in their source information, frequency of data collection and reporting, land class definitions, categorical detail, and spatial scale and time intervals of representation. These differences limit direct comparison, contribute to disagreements among studies, confuse stakeholders, and hamper our ability to confidently report key land cover trends in the U.S. Here we assess changes in cropland derived from the Land Change Monitoring, Assessment, and Projection (LCMAP) dataset from the U.S. Geological Survey and compare them with analyses of three established land cover datasets across the coterminous U.S. from 2008-2017: (1) the National Resources Inventory (NRI), (2) a dataset Lark et al. 2020 derived from the Cropland Data Layer (CDL), and (3) a dataset from Potapov et al. 2022. LCMAP reports more stable cropland and less stable noncropland in all comparisons, likely due to its more expansive definition of cropland which includes managed grasslands (pasture and hay). Despite these differences, net cropland expansion from all four datasets was comparable (5.18-6.33 million acres), although the geographic extent and type of conversion differed. LCMAP projected the largest cropland expansion in the southern Great Plains, whereas other datasets projected the largest expansion in the northwestern and central Midwest. Most of the pixel-level disagreements (86%) between LCMAP and Lark et al. 2020 were due to definitional differences among datasets, whereas the remainder (14%) were from a variety of causes. Cropland expansion in the LCMAP likely reflects conversions of more natural areas, whereas cropland expansion in other data sources also captures conversion of managed pasture to cropland. The particular research question considered (e.g., habitat versus soil carbon) should influence which data source is more appropriate.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Permafrost, Peatland, and Cropland Regions Are Key to Reconciling North American Carbon Sink Estimates

Persistent discrepancies between bottom-up, terrestrial biosphere models (TBMs), and top-down, atmospheric inversions, have made it difficult to quantify the magnitude of the North American terrestrial carbon sink. Previous studies have compared aggregated continent-scale estimates of carbon fluxes from TBMs and inversions for all of North America, but this provides limited insights into finer-scale mismatches that contribute to the overall discrepancies. Here we evaluate agreement between TBM and inversion carbon flux estimates at 1° × 1° resolution to provide more direct insights into where models disagree and what underlying factors drive discrepancies. We find that the additional carbon uptake estimated by inversions, in just 16% of the area of North America, is large enough to account for the discrepancy between TBMs and inversions across the whole continent. The majority of these differences occur in permafrost, peatland, and cropland regions. In these regions, we find a higher likelihood of potential biases in the weaker sink estimates from TBMs, suggesting that the stronger sink implied by inversions is more likely to be realistic. However, the current observational coverage is insufficient for fully assessing the causes of discrepancies or the magnitude of biases in either approach. Encouragingly, improved representation of agricultural processes in a TBM led to better agreement with inversions in croplands. Efforts to accurately model cropland dynamics will help improve agreement between TBMs and inversions. Overall, this work presents a clear path for reconciling the discrepancies between inversion and TBM estimates of the North American carbon sink that have persisted for two decades.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

A multi-objective optimization model for cropland design considering profit, biodiversity, and ecosystem services

More sustainable agricultural methods are needed to alleviate the decreases in biodiversity and ecosystem services that have occurred because of industrial agriculture. One such method is the inclusion of alternative crops into croplands that can support biodiversity, reduce erosion and chemical runoff, and sequester carbon in the soil. However, the question of where such crops should be planted to balance competing economic and environmental objectives remains open. To this end, we develop a mixed-integer quadratically constrained program to optimize the layout of a cropland considering economic, biodiversity, greenhouse gas emissions, and water quality objectives. We include spatially varying fertilization as a decision variable in addition to crop establishment location. We further include the effect of core area and edges between different crops on biodiversity. To demonstrate the applicability of the model, we apply it to an example field, showing how the optimal cropland design changes as a decision-maker prioritizes different objectives and as edges have different impacts on biodiversity.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

AmeriFlux FLUXNET-1F CR-Fsc Filadelfia sugar cane cropland

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site CR-Fsc Filadelfia sugar cane cropland. This is the FLUXNET version of the carbon flux data for the site CR-Fsc Filadelfia sugar cane cropland produced by applying the standard ONEFlux (1F) software. Site Description - The research site is located in a sugar cane cropland generally harvested in December. Sugarcane is irrigated(furrow irrigation) sporadically only during the dry season (January-April).Crop height varies from 0m to 4m.

Johnson, Mark [University of British Columbia]↗
DOE OSTI2026

AmeriFlux FLUXNET-1F US-VT1 Vermillion Tributary Paired Cropland – Site 1 (Corn/Soy; No Cover Crops)

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-VT1 Vermillion Tributary Paired Cropland – Site 1 (Corn/Soy; No Cover Crops). This is the FLUXNET version of the carbon flux data for the site US-VT1 Vermillion Tributary Paired Cropland – Site 1 (Corn/Soy; No Cover Crops) produced by applying the standard ONEFlux (1F) software. Site Description - US-VT1 is located on flat, actively managed farmland operated by working farmers, following a conventional no-till corn–soybean rotation in the U.S. Midwest. US-VT1 is one of two paired working farm sites on the same property; both are managed using similar conventional practices, with the key difference being that the paired site (US-VT2) incorporates cover crops into its rotation. This paired design enables direct site-to-site comparisons to assess the impacts of cover cropping on carbon, water, and energy fluxes.

Key, Kesondra [Indiana University - Bloomington]↗
DOE OSTI2026

AmeriFlux FLUXNET-1F US-VT2 Vermillion Tributary Paired Cropland – Site 2 (Corn/Soy; Cover Crops)

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-VT2 Vermillion Tributary Paired Cropland – Site 2 (Corn/Soy; Cover Crops). This is the FLUXNET version of the carbon flux data for the site US-VT2 Vermillion Tributary Paired Cropland – Site 2 (Corn/Soy; Cover Crops) produced by applying the standard ONEFlux (1F) software. Site Description - US-VT2 is located on flat, actively managed farmland operated by working farmers, following a conventional no-till corn–soybean rotation in the U.S. Midwest that uses cover crops. US-VT2 is one of two paired working farm sites on the same property; both are managed using similar conventional practices, with the key difference being that the paired site (US-VT1) does not incorporate cover crops into its rotation. This paired design enables direct site-to-site comparisons to assess the impacts of cover cropping on carbon, water, and energy fluxes.

Key, Kesondra [Indiana University - Bloomington]↗
DOE OSTI2026

AmeriFlux FLUXNET-1F US-SD1 Shatto Ditch Paired Cropland - Site 1 (Corn/Soy; No Cover Crops)

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-SD1 Shatto Ditch Paired Cropland - Site 1 (Corn/Soy; No Cover Crops). This is the FLUXNET version of the carbon flux data for the site US-SD1 Shatto Ditch Paired Cropland - Site 1 (Corn/Soy; No Cover Crops) produced by applying the standard ONEFlux (1F) software. Site Description - US-SD1, located on mostly flat terrain with some gentle hills, is an actively managed farmland operated by working farmers following a conventional no-till corn–soybean rotation in the U.S. Midwest. US-SD1 is one of two paired working farm sites which are relatively close by; both are managed using similar conventional practices with the key difference being that the paired site (US-SD2) incorporates cover crops into its rotation, along with minor differentiating terrain and soil type, where US-SD2 is located on a gently sloped site with more sandy soils. This paired design enables direct site-to-site comparisons to assess the impacts of cover cropping on carbon, water, and energy fluxes.

Key, Kesondra [Indiana University - Bloomington]↗
DOE OSTI2026

AmeriFlux FLUXNET-1F US-SD2 Shatto Ditch Paired Cropland - Site 2 (Corn/Soy; Cover Crops)

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-SD2 Shatto Ditch Paired Cropland - Site 2 (Corn/Soy; Cover Crops). This is the FLUXNET version of the carbon flux data for the site US-SD2 Shatto Ditch Paired Cropland - Site 2 (Corn/Soy; Cover Crops) produced by applying the standard ONEFlux (1F) software. Site Description - US-SD2, located on gently sloped terrain, is an actively managed farmland operated by working farmers following a conventional no-till corn–soybean rotation in the U.S. Midwest. US-SD2 is one of two paired working farm sites which are relatively close by; both are managed using similar conventional practices with the key difference being that the paired site (US-SD1) incorporates cover crops into its rotation, along with minor differentiating terrain and soil type, where US-SD1 is located on mostly flat terrain with some gentle hills. This paired design enables direct site-to-site comparisons to assess the impacts of cover cropping on carbon, water, and energy fluxes.

Key, Kesondra [Indiana University - Bloomington]↗
DOE OSTI2025

Combining organic amendments with enhanced rock weathering shifts soil carbon storage in croplands

Enhanced rock weathering (ERW) involves applying crushed silicate minerals to cropland soils to remove carbon dioxide and stabilize the global climate. If practiced widely, ERW has the potential to mitigate climate change and improve soil health and crop productivity. However, most ERW studies emphasize inorganic carbon (IC) chemistry, using model-based estimates and short-term mesocosms. Limited field data exist on how ERW interacts with organic amendments to affect organic carbon (C) cycling in soils. In a three-year field study in conventionally managed, irrigated maize fields, we monitored how key soil variables responded to crushed rock-alone, and in combination with compost and/or biochar. We measured weathering indicators (pH, major cations, and IC contents) and organic fractions, including particulate organic matter (POM), mineral-associated organic matter (MAOM), microbial biomass C, and water-extractable organic C. Rock-alone treatments increased weathering proxies (pH and IC) and showed an increasing trend in POM and MAOM, relative to control. In contrast, combining crushed rock with organic amendments resulted in lower soil organic C and nitrogen (N) concentrations (in both POM and MAOM) compared to organic amendments alone, though IC increased in the rock+compost treatment. Combining rock with both compost and biochar (compost/biochar) significantly lowered MAOM-N compared to compost/biochar alone. Overall, co-applying rock with organic inputs may promote weathering and C accrual but slow the accrual rate of organic C and N relative to organic amendments alone. Quantifying these trade-offs over multiple years and scales is critical to integrating ERW with existing soil health practices and climate mitigation strategies.

Biological and medical sciences↗
DOE OSTI2025

A multi model ensemble reveals net climate benefits from regenerative practices in US Midwest croplands

Process-based cropping systems models (CSMs) are key components of measurement, monitoring, reporting, and verification frameworks of carbon markets, but model-specific differences limit their applicability across diverse pedo-climatic conditions and agronomic practices. Multi-model ensemble (MME) provides an opportunity to better estimate changes in soil organic carbon (SOC) and nitrous oxide (N 2 O) emissions from agronomic practices at scale. We used an MME across 46 million hectares of US Midwest cropland at a resolution of 4-km 2 to assess the aggregate ability of different regenerative practices to sequester SOC and N 2 O emissions compared to their counterfactual dynamic baselines. MME was validated against long-term trials and compared to its constituent CSMs, showing greater accuracy and lower uncertainty. The results show that adopting no-till combined with cover crops increased SOC stocks by 0.36 ± 0.12 Mg ha -1 yr -1 , corresponding to a net regional SOC gain of 16.4 Tg C yr -1 compared to business-as-usual baselines. These benefits are halved when each management is practiced individually, and the SOC gains are only fully realized with low initial carbon stock. By including N 2 O emissions, we can assess the overall climate mitigation potential, specifically, the extent to which carbon sequestration can offset direct N 2 O emissions. The magnitude of this potential varies depending on management practices and geographic location with net climate benefits on average ranging from 0 to 3 Mg CO 2 -eq ha -1 yr -1 . High-resolution MME results allow for robust estimates of climate mitigation, reducing barriers to carbon market participation and supporting regenerative agriculture initiatives at scale.

carbon credits↗
DOE OSTI2026

Coupled machine learning–ecosystem ensemble models substantially improve predictions of nitrous oxide (N 2 O) fluxes from US croplands

Nitrous oxide (N 2 O) is a potent and persistent greenhouse gas, with rising atmospheric concentrations driven in part by inefficient use of synthetic nitrogen (N) fertilizers in agriculture. Predicting soil N 2 O emissions is challenging due to high spatial and temporal variability arising from complex soil biogeochemical processes. Process-based ecosystem models and standalone machine learning (ML) approaches without extensive site-specific calibration often miss high-emission episodes. Here, we show how an Ensemble Modeling System (EMS) based on outputs from an ensemble of ecosystem models coupled to an ensemble of ML models can improve predictions and understanding of N 2 O fluxes from US cropland. Trained and validated on ~12,000 N 2 O chamber measurements at 17 US Midwest sites (six crops, 35 management practices), the EMS accurately predicted daily fluxes of N 2 O at both training (R 2 = 0.84, RMSE = 16.4 g N ha −1 d −1 ) and held-out testing sites (R 2 = 0.84, RMSE = 6.2 g N ha −1 d −1 ). Analyses identified six dominant N 2 O drivers: soil organic carbon (SOC), NH 4 + , NO 3 - , water-filled pore space, temperature, and aboveground biomass production. Wet, warm soils produced large N 2 O peaks only with sufficient SOC and mineral N; in low-SOC soils, fluxes remained low. Incorporating these drivers into process-based models might significantly improve their predictive capacity. The EMS demonstrates a strong potential to predict N 2 O fluxes at unseen sites, enabling more reliable regional inventories, improved gap-filling where measurements are sparse, and enhanced understanding of mechanisms to advance targeted mitigation strategies in food, feed, and bioenergy crops.

AI↗
DOE OSTI2026

Estimating Fine-Resolution Shortwave Broadband Albedo of Croplands from Harmonized Landsat and Sentinel-2 Data

Altered surface albedo due to land-cover conversions and management is a significant driver of global climate change. Albedo can be directly measured at ground stations, and remote sensing data can be used to scale-up albedo values to regional and global levels. Some previous studies have retrieved fine-resolution (10–30 m) instantaneous albedo and coarse-resolution (500–1000 m) daily mean albedo from remote sensing data, but they all required the input of Moderate Resolution Imaging Spectroradiometer (MODIS) albedo information at 500-m resolution, and none have assembled both instantaneous and daily albedo based exclusively on fine-resolution satellite data. Here, to address this issue, we compiled 387 instantaneous and 346 daily albedo records using field net radiometer measurements from the bioenergy croplands at the W. K. Kellogg Biological Station in southwest Michigan. We then connected these albedo records with a suite of variables derived from harmonized Landsat and Sentinel-2 data through two machine learning algorithms (random forest regression and extreme gradient boosting) to retrieve clear-sky instantaneous and daily shortwave broadband albedo. The performance statistics indicate reasonable accuracy of model results [root-mean-square error (RMSE)] around or below 0.03 except for snow-covered surfaces), suggesting that the retrieval of both instantaneous and daily albedo based exclusively on fine-resolution satellite data is promising. To facilitate the use of fine-resolution albedo products at the global level, future efforts need to include more albedo records of diverse surface cover types, as well as to accurately model daily albedo for cloudy days to address the “clear-sky bias.”

Harmonized Landsat and Sentinel-2↗
DOE OSTI2025

AmeriFlux US-VT1 Vermillion Tributary Paired Cropland – Site 1 (Corn/Soy; No Cover Crops)

This is the AmeriFlux version of the carbon flux data for the site US-VT1 Vermillion Tributary Paired Cropland – Site 1 (Corn/Soy; No Cover Crops). Site Description - US-VT1 is located on flat, actively managed farmland operated by working farmers, following a conventional no-till corn–soybean rotation in the U.S. Midwest. US-VT1 is one of two paired working farm sites on the same property; both are managed using similar conventional practices, with the key difference being that the paired site (US-VT2) incorporates cover crops into its rotation. This paired design enables direct site-to-site comparisons to assess the impacts of cover cropping on carbon, water, and energy fluxes.

Key, Kesondra [Indiana University - Bloomington]↗
DOE OSTI2025

AmeriFlux US-VT2 Vermillion Tributary Paired Cropland – Site 2 (Corn/Soy; Cover Crops)

This is the AmeriFlux version of the carbon flux data for the site US-VT2 Vermillion Tributary Paired Cropland – Site 2 (Corn/Soy; Cover Crops). Site Description - US-VT2 is located on flat, actively managed farmland operated by working farmers, following a conventional no-till corn–soybean rotation in the U.S. Midwest that uses cover crops. US-VT2 is one of two paired working farm sites on the same property; both are managed using similar conventional practices, with the key difference being that the paired site (US-VT1) does not incorporate cover crops into its rotation. This paired design enables direct site-to-site comparisons to assess the impacts of cover cropping on carbon, water, and energy fluxes.

Key, Kesondra [Indiana University - Bloomington]↗
DOE OSTI2026

AmeriFlux US-SD1 Shatto Ditch Paired Cropland - Site 1 (Corn/Soy; No Cover Crops)

This is the AmeriFlux version of the carbon flux data for the site US-SD1 Shatto Ditch Paired Cropland - Site 1 (Corn/Soy; No Cover Crops). Site Description - US-SD1, located on mostly flat terrain with some gentle hills, is an actively managed farmland operated by working farmers following a conventional no-till corn–soybean rotation in the U.S. Midwest. US-SD1 is one of two paired working farm sites which are relatively close by; both are managed using similar conventional practices with the key difference being that the paired site (US-SD2) incorporates cover crops into its rotation, along with minor differentiating terrain and soil type, where US-SD2 is located on a gently sloped site with more sandy soils. This paired design enables direct site-to-site comparisons to assess the impacts of cover cropping on carbon, water, and energy fluxes.

Key, Kesondra [Indiana University - Bloomington]↗
DOE OSTI2026

AmeriFlux US-SD2 Shatto Ditch Paired Cropland - Site 2 (Corn/Soy; Cover Crops)

This is the AmeriFlux version of the carbon flux data for the site US-SD2 Shatto Ditch Paired Cropland - Site 2 (Corn/Soy; Cover Crops). Site Description - US-SD2, located on gently sloped terrain, is an actively managed farmland operated by working farmers following a conventional no-till corn–soybean rotation in the U.S. Midwest. US-SD2 is one of two paired working farm sites which are relatively close by; both are managed using similar conventional practices with the key difference being that the paired site (US-SD1) incorporates cover crops into its rotation, along with minor differentiating terrain and soil type, where US-SD1 is located on mostly flat terrain with some gentle hills. This paired design enables direct site-to-site comparisons to assess the impacts of cover cropping on carbon, water, and energy fluxes.

Key, Kesondra [Indiana University - Bloomington]↗
DOE OSTI2026

Data from: Coupled machine learning-ecosystem ensemble models substantially improve predictions of nitrous oxide (N 2 O) fluxes from US croplands

Nitrous oxide (N₂O) is a potent and persistent greenhouse gas, with rising atmospheric concentrations driven in part by inefficient use of synthetic nitrogen (N) fertilizers in agriculture. Predicting soil N₂O emissions is challenging due to high spatial and temporal variability arising from complex soil biogeochemical processes. Process-based ecosystem models and standalone machine learning (ML) approaches without extensive site-specific calibration often miss high emission episodes. Here, we show how an Ensemble Modeling System (EMS) based on outputs from an ensemble of ecosystem models coupled to an ensemble of ML models can improve predictions and understanding of N2O fluxes from US cropland. Trained and validated on approximately 12,000 N2O chamber measurements at 17 U.S. Midwest sites (six crops, 35 management practices), the EMS accurately predicted daily fluxes of N2O at both training (R² = 0.84, RMSE = 16.4 g N ha⁻¹ d⁻¹) and held-out testing sites (R² = 0.84, RMSE = 6.2 g N ha⁻¹ d⁻¹). Analyses identified six dominant N₂O drivers: soil organic carbon (SOC), NH₄⁺, NO₃⁻, water-filled pore space (WFPS), soil temperature, and biomass production. Wet, warm soils produced large N₂O peaks only with sufficient SOC and mineral N; in low-SOC soils, fluxes remained low. Incorporating these drivers into process-based models might significantly improve their predictive capacity. The EMS demonstrates a strong potential to predict N₂O fluxes at unseen sites, enabling more reliable regional inventories, improved gap-filling where measurements are sparse, and enhanced understanding of mechanisms to advance targeted mitigation strategies in food, feed, and bioenergy crops.

agricultural sciences↗
DOE OSTI2025

Land conversion to energy crops for sustainable aviation fuel production reduces greenhouse gas emissions in the United States

Energy crops will be critical for scaling up production of Sustainable Aviation Fuel in the United States and reducing greenhouse gas emissions. Here we examine the economic incentives for the extent and type of land conversion needed to scale up fuel production from a mix of cellulosic feedstocks and quantify its greenhouse gas intensity. We show that even with the availability of marginal non-cropland, there will be incentives for converting cropland to produce energy crops as the price of sustainable aviation fuel increases. But contrary to expectations, we find that scaling up fuel production by converting more cropland and more non-cropland from existing uses to energy crops lowers its net greenhouse gas intensity, due to high soil carbon sequestration rate of energy crops, even after considering land use change emissions. The potential savings in emissions are larger than the foregone soil carbon accumulation benefits from keeping that land in current uses.

54 ENVIRONMENTAL SCIENCES↗