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At least 145 records · Page 8

Global Carbon Budget 1800-2018 Loss of Additional Sink Capacity and Present Transient Difference

A dataset of two global carbon fluxes: the loss of additional sink capacity (LASC) and present versus transient difference (PTD). The loss of additional sink capacity is the loss of indirect anthropogenic sink capacity in land ecosystems caused by the loss of ecosystems that can increase carbon in response to changing environments, primarily forests. The present transient difference refers to the direct anthropogenic flux in land ecosystems (from land cover and land use change) and the difference in that flux when calculated assuming "present day" (actually more like 1980) ecosystem carbon stocks or when calculated assuming transient carbon stocks (i.e. caused by environmental change). In this dataset, the LASC and PTD fluxes were calculated using the TRENDY ensemble of Dynamic Global Vegetation Models (DGVMs; Sitch et al., 2024) following the methods described therein and in Obermeier et al. (2021). For further details see Obermeier et al. (2021), Friedlingstein et al. (2019), Sitch et al. (2024), and Walker et al. (2025). The dataset includes ensemble means and standard deviations for annual fluxes, fluxes cumulated annually over the whole time period, and cumulated since 1959. These data were originally collected to compare different approaches (DGVMs versus bookkeeping models) for estimating land use and land cover change (LULCC) emissions (Obermeier et al. 2021). More recently, and similarly, these data were used to harmonize the estimates of the direct and indirect anthropogenic fluxes in the global carbon cycle and to recalculate the global carbon budget (Walker et al., 2025).

54 ENVIRONMENTAL SCIENCES↗

Passive Acoustic Monitoring Provides Insights into Avian Use of Energycane Cropping Systems in Southern Florida

Birds are important indicators of ecosystem health and provide a range of benefits to society. It is important, therefore, to understand the impacts of agricultural land use changes on bird populations. The cultivation of energycane (EC)—a sugarcane hybrid—for biofuel production represents one form of agricultural land use change in southern Florida. We used passive acoustic monitoring (PAM) to examine bird community use of experimental EC fields and other agricultural land uses at two study sites in southern Florida. We deployed 16 acoustic recorders in different study plots and used the automatic species identifier BirdNET to identify 40 focal bird species. We found seasonal differences in daily avian species diversity and richness between EC experimental plots and reference agricultural fields (corn fields, orchards, pastureland), and between time periods (pre-planting, post-planting). Daily avian species diversity and richness were lower in the EC experimental plots during Fall and Winter months when plants reached maximum height (>400 cm in some areas). Despite seasonal differences in daily measures of species diversity and richness, we found no differences in cumulative species richness, suggesting that there may be little overall (season-long) effects of EC production. These findings could provide insight to avian seasonal habitat preferences and underscore the potential limitations of PAM in areas experiencing dynamic vegetation changes. More research is needed to better understand if utilization of EC cropping systems results in positive or negative effects on avian populations (e.g., foraging habitat quality, predator–prey dynamics, nest success).

BirdNET↗

Combining Satellite Data and Models to Assess the Impacts of Urbanization on the Continental US Surface Climate

Urbanization is one of the most important and long lasting forms of land transformation. Urbanization affects the surface climate in different ways: (1) by reduction of the vegetation fraction causing subsequent reduction in photosynthesis and plant s water transpiration, (2) by alternation of surface runoff and infiltration and their impacts on soil moisture and the water table, (3) by change in the surface albedo and surface energy partitioning, and (4) by transformation of the surface roughness length and modification of surface fluxes. Land cover and land use change maps including urban areas have been developed and will be used in a suite of land surface models of different complexity to assess the impacts of urbanization on the continental US surface climate. These maps and datasets based on a full range of available satellite data and ground observations will be used to characterize distant-past (pre-urban), recent-past (2001), present (2010), and near future (2020) land cover and land use changes. The main objective of the project is to assess the impacts of these land transformation on past, current and near-future climate and the potential feedbacks from these changes on the atmospheric, hydrologic, biological, and socio-economic properties beyond the immediate metropolitan regions of cities and their near suburbs. The WRF modeling system will be used to explore the nature and the magnitude of the two-way interactions between urban lands and the atmosphere and assess the overall regional dynamic effect of urban expansion on the northeastern US weather and climate

Bounoua, L.↗

A land use and environmental impact analysis of the Norfolk-Portsmouth SMSA

The feasibility of using remote sensing techniques for land use and environmental assessment in the Norfolk-Portsmouth area is discussed. Data cover the use of high altitude aircraft and satellite remote sensing data for: (1) identifying various heirarchial levels of land use, (2) monitoring land use changes for repetitive basis, (3) assessing the impact of competing land uses, and (4) identifying areas of potential environmental deterioration. High altitude aircraft photographs (scale 1:120,000) acquired in 1959, 1970, and 1972, plus Earth Resources Technology Satellite (ERTS-1) color composite images acquired in 1972 were used for the land use and environmental assessments. The high altitude aircraft photography, as expected, was successfully used to map Level 1, Level 2, as well as some urban Level 3 land use categories. However, the detail of land use analysis obtainable from the ERTS imagery exceeded the expectations for the U.S. Geological Survey's land use classification scheme. Study results are consistent with the initial investigation which determined Level 1 land use change to be 16.7 square km per year.

Mitchel, W. B.↗

Land-cover Change in the Caucasus Mountains Since 1987 Based on the Topographic Correction of Multi-temporal Landsat Composites

Mountainous regions are changing rapidly across the world due to both land-use change and climate change. Given the importance of mountainous regions for ecosystem services and endemic biodiversity, monitoring these changes is essential. Satellite data provide a great resource to map land-cover change in mountainous regions, however mapping is especially challenging there because topographic complexity affects reflectance. The so called ‘topographic effect’ has been successfully corrected for in case studies of small areas, but a comparison of large-area classifications and land-cover change analyses with and without topographic correction is missing. Here, we performed a long-term land-cover change assessment for a large mountainous region, i.e., the Caucasus Mountains with topographic correction. Our two goals were 1) to examine the effect of topographic correction on land-cover classification for a large mountainous region, and 2) to assess land-cover changes since 1987 across the Caucasus based on the full Landsat archive. Both the complex topography and the history of land-use changes, especially after the collapse of the Soviet Union in 1991, make the Caucasus Mountains an ideal study area to understand topographic effects on large-area land-cover mapping for the last three decades. First, we compared a non-topographically-corrected Landsat classification for 2015 with a classification that was topographically-corrected with an enhanced C-correction for the same year and assessed the accuracy of both. Second, we derived topographically-corrected Landsat classifications for six dates to assess changes in cropland and forest from 1987 to 2015, based on class probabilities and post-classification comparisons. In regard to our first goal, topographic correction improved the overall accuracy of the classification only by 2% (from 79 to 81%), but disagreement rates were as high as 100% in mountainous regions, especially among forest types. In regard to our second goal, we found that cropland loss was the most prevalent change process since 1987. Cropland loss was particularly widespread in Georgia and Armenia until 2000, and in Azerbaijan until 2005. The North Caucasus (the Russian Federation) had more stable cropland over time, most likely due to different land reforms after the collapse of the Soviet Union, and the prevalence of flat landscapes and very fertile soils, which make cultivation easier than in the South Caucasus. Rates of forest change throughout the Caucasus Mountains were surprisingly low, with forest loss and forest gain was most likely due to cropland abandonment and less grazing pressure. Our results highlight both the importance and the feasibility of topographic correction for accurate large-area land-cover classifications in steep terrain.

Large-area mapping↗

Comprehensive Analysis of Thirty Years of Land Change in Georgia: Forest Degradation, Land-Use Patterns, and Drivers

In this talk, we present results from a study, funded by the NASA Land-Cover and Land-Use Change program, of thirty years of environmental change in the country of Georgia. The country, a former Soviet Union Republic, has experienced more political, economic and social change in the last 30 years than most countries. But the environmental implications of these extreme events remain largely unknown – the region is understudied, no national forest inventory has been completed in 20 years, and previous research in the area conducted by the authors were not successful. The latter statement is because of forest degradation. After the collapse of the Soviet Union, much of the forestry infrastructure broke down and people resorted to chopping down individual trees. The result was in many parts of the country a reduction in forest biomass but not to the point of a change in land cover. This type of forest degradation, which was either gradual over decades or abrupt, could not be readily identified using the methods and data at our disposal at the time. In the recent study, we had full access to the Landsat archive in combination with computing power. By using monitoring methods that are based on time series analysis, we were able to capture and identify the gradual processes driven by small scale activities that are so characteristic of the post-Soviet Georgian landscape. We developed an approach (“CCDC-SMA”) that combines time series analysis and spectral mixture analysis running on Google Earth Engine for monitoring abrupt and gradual forest degradation. By using this approach, we found that forest degradation was significantly larger than the area estimate of deforestation; 3,541 ± 556 km2 (11% of the forest area in 1987) compared to 158 ± 98 km2 from 1987 to 2020. The prevailing narrative is that legal and illegal cutting of trees for fuelwood is primarily responsible for this process. Yet, since independence from the Soviet Union in 1991, the country has undergone rapid socioeconomic and institutional changes which have not been explored as drivers of forest change. To further our understanding of the underlying causes, we combined forest disturbance estimates, Georgian statistical data, and historical institutional change data to examine socioeconomic drivers of forest degradation. We found that higher winter temperature and drought were associated with higher degradation at the regional scale, while major institutional changes and drought were associated with higher forest degradation at the national level. Access to natural gas, the major energy alternative to fuelwood, had no significant association with degradation. Our results challenge the narrative that poverty and a lack of alternative energy infrastructure drive forest degradation and suggest that government policies banning household fuelwood cutting, including the new Forest Code of 2020, may not reduce forest degradation. Given these results, improved data on wood harvesting and more research on the commercial drivers of degradation and their links to economic and political reforms is needed to better inform forest policy in the region, especially given ongoing risks from climate change.

Pontus Olofsson↗

A Continental-Scale Estimate of Soil Organic Carbon Change at NEON Sites and Their Environmental and Edaphic Controls

Current carbon cycle models focus on the effects of climate and land-use change on primary productivity and microbial-mineral dependent carbon turnover in the topsoil, while less attention has been paid to vertical soil processes and soil-dependent response to land-use change along the profile. In this study, a spatial-temporal analysis was used to estimate soil organic carbon (SOC) change in topsoil/A horizon and subsoil/B horizon at National Ecological Observatory Network (NEON) sites, USA over 30 years. To separate the effects of land-use, environmental, and edaphic factors on SOC change, space-for-time substitution was used in combination with the Continuous Change Detection and Classification algorithm and Structural Equation Modeling. Results showed that (a) under natural vegetation, Spodosols and Inceptisols found in the eastern NEON sites had substantial topsoil SOC accumulation (+0.4 to +1.2 Mg C ha –1 year –1 ), while Inceptisols and Andisols in the west had a comparable magnitude of topsoil SOC loss (–0.5 to –1.8 Mg C ha –1 year –1 ); (b) Mollisols and Alfisols in the Central Plains sites were susceptible to significant SOC loss under farming and grazing; (c) Runoff/erosion and leaching potential, vertical translocation, and mineral sorption were the most important factors controlling SOC variation across the NEON sites. Our work could be used to parameterize ecosystem models simulating SOC change.

54 ENVIRONMENTAL SCIENCES↗

Calibration of the Thermal Infrared Sensor on the Landsat Data Continuity Mission

The Landsat series of satellites provides the longest running continuous data set of moderate-spatial-resolution imagery beginning with the launch of Landsat 1 in 1972 and continuing with the 1999 launch of Landsat 7 and current operation of Landsats 5 and 7. The Landsat Data Continuity Mission (LDCM) will continue this program into a fourth decade providing data that are keys to understanding changes in land-use changes and resource management. LDCM consists of a two-sensor platform comprised of the Operational Land Imager (OLI) and Thermal Infrared Sensors (TIRS). A description of the applications and design of the TIRS instrument is given as well as the plans for calibration and characterization. Included are early results from preflight calibration and a description of the inflight validation.

Thome, K↗

The International Summer School on Land Cover Change and Hydroclimate of the La Plata Basin

The La Plata Basin (LPB) in southern South America has been subject to land cover and land use changes (LCLUCs) since colonial times and with an accelerated rate in the last decades and over extensive areas. The work of Ameghino even suggested that there were relations between those land use changes and the frequency of droughts and floods in the region. Despite this early knowledge, not much is known of the potential impacts of LCLUC on the hydroclimate of the La Plata basin. Besides, over the last century much of the La Plata Basin has had a reported increase in precipitation and heavy rains, and these changes along with an increase in population growth - have resulted in more adverse effects from flooding. To draw attention to these issues, during two weeks in November 2009 the International Summer School on Land Cover Change and Hydroclimate of the La Plata Basin was organized at the grounds of the Itaip Hydropower Plant in Brazil. The school was the result of the combination of interests between the La Plata Basin Regional Hydroclimate Project, the Inter-American Institute for Global Change Research (IAI), and the International Hydroinformatics Center (IHC) in Itaip . LPB is an umbrella project endorsed by the Global Energy and Water Cycle Experiment (GEWEX) and the Climate Prediction and Variability (CLIVAR), both of the World Climate Research Programme (WCRP). LPB has made a priority to train young scientists and promote interdisciplinary collaborations in areas related to Climate, Hydrology, Ecology and Agriculture. The IAI, with a similar agenda, was a natural partner to develop this Summer School, which in turn benefited from Itaipu s interest in relating with the scientific community of neighboring countries. The choice of location (Itaip Technological Park) was made so that participants could relate research usually done at academic institutions to applications and operations at one of the largest hydropower plants in the world. The school was attended by 45 advanced graduate students and young scientists with different backgrounds from seven countries, including less technically advanced ones in the region..

Berbery, Ernesto Hugo↗

Using Earth Observations to Analyze Shoreline Changes and Understand the Effects of Sea Level Rise in Southern Puerto Rico

This summer, the Jobos Bay National Estuarine Research Reserve (JBNERR) partnered with NASA DEVELOP to evaluate water quality, mangrove forest extent, sea level rise, and land cover changes in Jobos Bay. DEVELOP is a national capacity building program that connects satellite data with early career scientists and decision makers. Through ten-week feasibility studies, DEVELOP partners with organizations that have the power to enact policy within their communities. Jobos Bay, in the southeast coast of Puerto Rico, has experienced intense hurricane seasons with increased seasonal storm surge, near-shore land use changes, and strong variations in precipitation and runoff. Through proposals, bi-weekly meetings, and frequent email communication, this cross-sector initiative provided valuable results for management decisions within the reserve. Using satellite observations to measure land use change, the team found that 17% of the reserve has shifted from land to water along the coast since 1997. Using Sentinel-2 the team was able to visualize turbidity, chlorophyll-a, and colored dissolved organic matter (CDOM) for Jobos Bay. While some large events such as Hurricane Maria were reflected in the turbidity analysis, chlorophyll-a and CDOM visualizations were limited by the influence of shallow-water bottom reflectance, particularly around reefs and within the Bay. The team also found that Jobos Bay lost 4.9 square kilometers of mangrove habitat over the past decade, calculated using Landsat 7 and 8 within Google Earth Engine. The results from this study will inform JBNERR and its community members on the regional impacts of sea level rise as well as serve as a baseline for future conservation efforts and research in the estuary.

Olivia Spencer↗

Land use mapping and modelling for the Phoenix Quadrangle

The author has identified the following significant results. Comparison of 9 x 9 MSS band images and color composites made from bands 4, 5, and 6 showing vegetated areas near Phoenix during the summer, fall, and winter seasons aided in definitely establishing that certain land areas were being used as agricultural land and not as rangeland. Agricultural land, which appeared to be fallow, idle, or not irrigated, often became more readily identifiable as agricultural land when comparing different images of identical land areas which have been affected by seasonal vegetation changes. Experimentation with the Bausch and Lomb Zoom Transferscope using MSS images of identical areas in the same spectral band from different time periods, with a quick flip method of alternately viewing the frame areas, enabled rapid detection of a major land use change from agricultural to urban use on the northwest fringe of the metropolitan Phoenix area. The best results in this case were obtained when comparing MSS band 5 images. Examination of MSS transparencies and color composites allowed further updating of a map of land use change in the Phoenix Quadrangle.

Place, J. L.↗

Monitoring the evolving land use patterns using remote sensing

The urbanization of Walnut Valley from 1953-71 prompted land use change from intensive von Thunen market-oriented patterns to extensive, disinvested, production-factor-minimized patterns. Shortrun, interim land use planning, has allowed agriculture to persist but only in the form of barley farming and grazing. Aerial photography used synoptically recorded six periods of land use change that bracketed dates before and after the freeway was announced and built. Interpretations of these changes help recognize potential conversions to urban uses which allow guidelines to be established that deal with rural-urban transition problems before they arise.

Goehring, D. R.↗

SERVIR: Cross-Comparison of Carbon Emission Estimates Based on Variable Land Use Land Cover Changes within SERVIR Focus Regions

Deforestation in the tropics contributes approximately one-fifth of the annual global greenhouse gas (GHG) emissions. In an effort to reduce GHG emissions, SERVIR - a joint USAID and NASA initiative - is currently implementing the SERVIR CArbon Pilot (S-CAP) activity. By developing a comprehensive CO2 tracking system in Google Earth Engine based on both remotely sensed data and in situ observations, S-CAP aims to build capacity within the SERVIR regional hubs to improve decision making and local monitoring efforts surrounding GHG emissions. The S-CAP estimations are being completed throughout 11 pilot countries within the SERVIR regions of Asia, Africa, and the Americas to integrate partner contributions and local input into the development process. These emission estimate calculations use country-level REDD+ FREL reported values, global remotely sensed data (e.g. Global Forest Watch) and regional datasets and are completed using the IPCC Guidelines for National Greenhouse Gas Inventories. From the S-CAP activity thus far, country CO2 estimations had varied differences, ranging from 56% to 197% between their lowest and highest estimates. The results from this study show that CO2 emission estimates can differ greatly depending on the land cover data sets used as well as the biomass values, and how a comprehensive database is essential in understanding the full range of impacts that land cover change has in these regions. Using this ensemble approach, SERVIR hubs can better select the most appropriate datasets available for estimating emissions.

Carbon Emission↗

Land use classification and change analysis using ERTS-1 imagery in CARETS

Land use detail in the CARETS area obtainable from ERTS exceeds the expectations of the Interagency Steering Committee and the USGS proposed standardized classification, which presents Level 1 categories for ERTS and Level 2 for high altitude aircraft data. Some Levels 2 and 3, in addition to Level 1, categories were identified on ERTS data. Significant land use changes totaling 39.2 sq km in the Norfolk-Portsmouth SMSA were identified and mapped at Level 2 detail using a combination of procedures employing ERTS and high altitude aircraft data.

Alexander, R. H.↗

Biodiversity loss reduces global terrestrial carbon storage

Natural ecosystems store large amounts of carbon globally, as organisms absorb carbon from the atmosphere to build large, long-lasting, or slow-decaying structures such as tree bark or root systems. An ecosystem’s carbon sequestration potential is tightly linked to its biological diversity. Yet when considering future projections, many carbon sequestration models fail to account for the role biodiversity plays in carbon storage. Here, we assess the consequences of plant biodiversity loss for carbon storage under multiple climate and land-use change scenarios. We link a macroecological model projecting changes in vascular plant richness under different scenarios with empirical data on relationships between biodiversity and biomass. We find that biodiversity declines from climate and land use change could lead to a global loss of between 7.44-103.14 PgC (global sustainability scenario) and 10.87-145.95 PgC (fossil-fueled development scenario). This indicates a self-reinforcing feedback loop, where higher levels of climate change lead to greater biodiversity loss, which in turn leads to greater carbon emissions and ultimately more climate change. Conversely, biodiversity conservation and restoration can help achieve climate change mitigation goals.

Biodiversity↗

How NASA Sees the Earth and Its Climate

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

BrowndeColstoun, Eric↗

Forest Carbon Emissions from Cropland Expansion in the Brazilian Cerrado Biome

Land use, land use change, and forestry accounted for two-thirds of Brazil's greenhouse gas emissions profile in 2005. Amazon deforestation has declined by more than 80% over the past decade, yet Brazil's forests extend beyond the Amazon biome. Rapid expansion of cropland in the neighboring Cerrado biome has the potential to undermine climate mitigation efforts if emissions from dry forest and woodland conversion negate some of the benefits of avoided Amazon deforestation. Here, we used satellite data on cropland expansion, forest cover, and vegetation carbon stocks to estimate annual gross forest carbon emissions from cropland expansion in the Cerrado biome. Nearly half of the Cerrado met Brazil's definition of forest cover in 2000 (greater than or equal to 0.5 ha with greater than or equal to 10% canopy cover). In areas of established crop production, conversion of both forest and non-forest Cerrado formations for cropland declined during 2003-2013. However, forest carbon emissions from cropland expansion increased over the past decade in Matopiba, a new frontier of agricultural production that includes portions of Maranhao, Tocantins, Piau­, and Bahia states. Gross carbon emissions from cropland expansion in the Cerrado averaged 16.28 Tg C yr (exp -1) between 2003 and 2013, with forest-to-cropland conversion accounting for 29% of emissions. The fraction of forest carbon emissions from Matopiba was much higher; between 2010-2013, large-scale cropland conversion in Matopiba contributed 45% of total Cerrado forest carbon emissions. Carbon emissions from Cerrado-tocropland transitions offset 5-7% of the avoided emissions from reduced Amazon deforestation rates during 2011-2013. Comprehensive national estimates of forest carbon fluxes, including all biomes, are critical to detect cross-biome leakage within countries and achieve climate mitigation targets to reduce emissions from land use, land use change, and forestry.

remote sensing↗