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NASA NTRS2000

Influence of the Biosphere on Precipitation: July 1995 Studies with the ARM-CART Data

Ensemble sets of simulation experiments were conducted with a single column model (SCM) using the Goddard GEOS II GCM physics containing a recent version of the Cumulus Scheme (McRAS) and a biosphere based land-fluxes scheme (SSiB). The study used the 18 July to 5 August 1995 ARM-CART (Atmospheric Radiation Measurement-Cloud Atmospheric Radiation Test-bed) data, which was collected at the ARM-CART site in the mid-western United States and analyzed for single column modeling (SCM) studies. The new findings affirm the earlier findings that the vegetation, which increases the solar energy absorption at the surface together with soil and soil-moisture dependent processes, which modulate the surface, fluxes (particularly evapotranspiration) together help to increase the local rainfall. In addition, the results also show that for the particular study period roughly 50% of the increased evaporation over the ARM-CART site would be converted into rainfall with the Column, while the remainder would be advected out to the large-scale. Notwithstanding the limitations of only one-way interaction (i.e., the large-scale influencing the regional physics and not vice versa), the current SCM simulations show a very robust relationship. The evaporation-precipitation relationship turns out to be independent of the soil types, and soil moisture; however, it is weakly dependent on the vegetation cover because of its surface-albedo effect. Clearly, these inferences are prone to weaknesses of the SCM physics, the assumptions of the large-scale being unaffected by gridscale (SCM-scale) changes in moist processes, and other limitations of the evaluation procedures.

Sud, Y. C.↗

NASA NTRS2021

Trends in Barrier Island Geomorphology Under Continuous Sea Level Rise: Padre Island from 1940-2020

Barrier islands serve an important role in shielding coastal areas from storm surges and wave erosion. Monitoring changes in a barrier island system helps determine the combined effect of sediment supply, aeolian sand transport, storms and sea level rise (SLR) on long-term island survival. Here we present and discuss changes to the southern end of Padre Island (TX),including a back-barrier active dune field, across 7 decades from 1941 - 2020. We have used aerial photos, satellite imagery, and field monitoring to map the decadal and seasonal geomorphological changes. We produced facies maps for each decade from 1970 to present, complemented with qualitative observations for 1941-1970, when aerial imagery was incomplete. We also used supervised classification to monitor monthly changes in the availability of sand for aeolian transport over a full seasonal cycle, to determine the role of the fluctuating water table on the sand budget of the active dune field. Results indicate that the southern end of Padre Island experienced significant change over the study period, transitioning from unvegetated dune fields and sand flats to expansive vegetated dunes, a tidal flat with microbial mats and a shrinking active dune field. Vegetated dunes, absent in 1970, now cover 14% of the study area. The active dune field shrunk from 12%coverage to 6%, with sand available for transport varying from 3% to 21% as the water table fluctuates throughout the year. The infrequently flooded back-island sand flat covering 40% of the study area has transitioned to a lower-lying tidal flat. Furthermore, extensive microbial mats and crusts have developed within the wind-tidal flat, in washover fans, and in low-lying interdune areas. All these early signs are consistent with a progressive drowning of the barrier island, an event we hypothesize was triggered by the sudden spread of vegetation along the back-beach dunes. Plant colonization then cut off sand supply from the beach to the back-barrier, and thus access to the primary source of sand to the system. Our findings highlight the contradictory role of vegetation in barrier islands, as they stabilize dunes and promote sand accretion at the back-beach, while also isolating the back-barrier from aeolian sediment sources, thus amplifying the effects of sea level rise in the absence of salt marshes and/or mangrove platforms.

K R Fisher↗

NASA NTRS2009

Developing New Coastal Forest Restoration Products Based on Landsat, ASTER, and MODIS Data

This paper discusses an ongoing effort to develop new geospatial information products for aiding coastal forest restoration and conservation efforts in coastal Louisiana and Mississippi. This project employs Landsat, Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), and Moderate Resolution Imaging Spectroradiometer (MODIS) satellite data in conjunction with airborne elevation data to compute coastal forest cover type maps and change detection products. Improved forest mapping products are needed to aid coastal forest restoration and management efforts of State and Federal agencies in the Northern Gulf of Mexico (NGOM) region. In particular, such products may aid coastal forest land acquisition and conservation easement procurements. This region's forests are often disturbed and subjected to multiple biotic and abiotic threats, including subsidence, salt water intrusion, hurricanes, sea-level rise, insect-induced defoliation and mortality, altered hydrology, wildfire, and conversion to non-forest land use. In some cases, such forest disturbance has led to forest loss or loss of regeneration capacity. In response, a case study was conducted to assess and demonstrate the potential of satellite remote sensing products for improving forest type maps and for assessing forest change over the last 25 years. Change detection products are needed for assessing risks for specific priority coastal forest types, such as live oak and baldcypress-dominated forest. Preliminary results indicate Landsat time series data are capable of generating the needed forest type and change detection products. Useful classifications were obtained using 2 strategies: 1) general forest classification based on use of 3 seasons of Landsat data from the same year; and 2) classification of specific forest types of concern using a single date of Landsat data in which a given targeted type is spectrally distinct compared to adjacent forested cover. When available, ASTER data was useful as a complement to Landsat data. Elevation data helped to define areas in which targeted forest types occur, such as live oak forests on natural levees. MODIS Normalized Difference Vegetation Index time series data aided visual assessments of coastal forest damage and recovery from hurricanes. Landsat change detection products enabled change to be identified at the stand level and at 10- year intervals with the earliest date preceding available change detection products from the National Oceanic and Atmospheric Administration and from the U.S. Geological Survey. Additional work is being done in collaboration with State and Federal agency partners in a follow-on NASA ROSES project to refine and validate these new, promising products. The products from the ROSES project will be available for aiding NGOM coastal forest restoration and conservation.

Spruce, Joseph P.↗

NASA NTRS2011

Online Time Series Analysis of Land Products over Asia Monsoon Region via Giovanni

Time series analysis is critical to the study of land cover/land use changes and climate. Time series studies at local-to-regional scales require higher spatial resolution, such as 1km or less, data. MODIS land products of 250m to 1km resolution enable such studies. However, such MODIS land data files are distributed in 10ox10o tiles, due to large data volumes. Conducting a time series study requires downloading all tiles that include the study area for the time period of interest, and mosaicking the tiles spatially. This can be an extremely time-consuming process. In support of the Monsoon Asia Integrated Regional Study (MAIRS) program, NASA GES DISC (Goddard Earth Sciences Data and Information Services Center) has processed MODIS land products at 1 km resolution over the Asia monsoon region (0o-60oN, 60o-150oE) with a common data structure and format. The processed data have been integrated into the Giovanni system (Goddard Interactive Online Visualization ANd aNalysis Infrastructure) that enables users to explore, analyze, and download data over an area and time period of interest easily. Currently, the following regional MODIS land products are available in Giovanni: 8-day 1km land surface temperature and active fire, monthly 1km vegetation index, and yearly 0.05o, 500m land cover types. More data will be added in the near future. By combining atmospheric and oceanic data products in the Giovanni system, it is possible to do further analyses of environmental and climate changes associated with the land, ocean, and atmosphere. This presentation demonstrates exploring land products in the Giovanni system with sample case scenarios.

Shen, Suhung↗

NASA NTRS1974

Automatic mapping of strip mine operations from spacecraft data

The author has identified the following significant results. Computer techniques were applied to process ERTS tapes acquired over coal mining operations in southeastern Ohio on 21 August 1972 and 3 September 1973. ERTS products obtained included geometrically-correct map overlays, at scales from 1:24,000 to 1:250,000, showing stripped earth, partially reclaimed earth, water, and natural vegetation. Computer-generated tables listing the area covered by each land-water category in square kilometers were also produced. By comparing these mapping products, the study demonstrates the capability of ERTS to monitor changes in the extent of stripping and reclamation. NASA C-130 photography acquired on 7 September 1973 when compared with the ERTS products generated from the 3 September 1973 tape established the categorization accuracy to be better than 90%. It is estimated that the stripping and reclamation maps and data were produced from the ERTS CCTs at a tenth of the cost of conventional techniques.

Rogers, R. H.↗

NASA NTRS2004

Autonomous Vegetation Cover Scene Classification of EO-1 Hyperion Hyperspectral Data

The Autonomous Sciencecraft Experiment (ASE) is a JPL-led, New Millennium Program mission containing new technology in the form of software to be flown on the Earth Observer-1 (EO-1) satellite in early 2004. This new technology will facilitate an artificially intelligent machine with autonomous science-driven capabilities. Among the ASE flight software is a set of onboard science algorithms designed for autonomous data processing, primarily based on change detection from observation to observation. Using the output from these algorithms, ASE has the ability to autonomously modify the EO-1 observation plan, retargeting itself for a more in-depth observation of a scientific event in progress. Furthermore, intelligent and selective information down-linking will maximize return of the most valuable scientific data. Among the algorithms developed for use on ASE is a Lava-Vegetation (L-V) detection algorithm. This algorithm can effectively identify the initial location and extent of lava and vegetation coverage based on spectral shape. Comparison of several different observations, all classified via this algorithm, can make change detection possible.

Lee, R. J.↗

DOE OSTI2025

Exploring Micro-Environmental Conditions of Urban Agrivoltaics: Advancing Sustainable Green Spaces and Agriculture in Temperate Cities

Agrivoltaics, the integrated land use combining renewable energy production and agriculture, can potentially address key challenges faced by urban communities, including limited access to vacant land, fresh produce, and electricity. However, urban agrivoltaics has rarely been considered a viable solution, primarily due to a lack of experimental systems demonstrating the functionality of urban food production or green spaces alongside solar energy production. To evaluate the potential of solar photovoltaics to help mitigate heat stress on urban agriculture and green spaces in a temperate climate, we examined the microclimatic changes introduced by an urban agrivoltaics system (UrAV) when combined with vegetable crops and turfgrass, respectively. Accordingly, we installed an experimental setup instrumented with environmental sensors to compare full-sun conditions with those of an agrivoltaics system designed for urban environments. We found minimal differences for both land cover types between the control and agrivoltaics sites in air and soil temperature. However, during periods of intensified summer heat, temperatures beneath the panels cooled due to reductions in wind speed and relative humidity, which impeded the movement of hot, moist air and reduced reference evapotranspiration. Further, soil moisture in UrAV was highly spatially heterogeneous, influenced by the layout of the photovoltaic panels and their support structure, which redistributed rainfall and controlled where solar radiation could penetrate and drive evapotranspiration. Overall, our results suggest that PV-induced environmental changes in temperate climates are compatible with cultivating turfgrass or appropriate crops. These findings can help planners and designers integrate agrivoltaics into community gardens, farms, and green spaces in temperate cities.

14 SOLAR ENERGY↗

NASA NTRS1975

Determine utility of ERTS-1 to detect and monitor area strip mining and reclamation

Rogers, R. H.↗

NASA NTRS1992

A toy terrestrial carbon flow model

A generalized carbon flow model for the major terrestrial ecosystems of the world is reported. The model is a simplification of the Century model and the Forest-Biogeochemical model. Topics covered include plant production, decomposition and nutrient cycling, biomes, the utility of the carbon flow model for predicting carbon dynamics under global change, and possible applications to state-and-transition models and environmentally driven global vegetation models.

Parton, William J.↗

NASA NTRSDate not supplied

Relating Land Cover Change to Runoff Distribution Using NASA Earth Observations in Riley County, Kansas

In recent years, Riley County, Kansas experienced high levels of flooding potentially due to changes in land use and impervious surface. To analyze the increase in floods and runoff patterns over time, this study contrasted two methods of curve number (CN) calculation, which estimated runoff from rainfall events, from 2006-2020. The conventional calculation method used a look-up table and tracked land use/land cover change. This method resulted in static tables from various inputs such as soil type, surface imperviousness, slope, and crop phenology to estimate runoff versus infiltration. These tables allowed for phenology specific curve numbers and accounted for various farming techniques but required many inputs and lacked flexibility to include seasonal variations in vegetation. In contrast, the dynamic method is a more modern and simple calculation employing normalized difference vegetation index (NDVI) data from Landsat 5, Landsat 7, and Landsat 8 satellites compiled over the rainy season each year to calculate curve numbers based off seasonal vegetation. This dynamic method allowed for more precise analysis of runoff variability because NDVI is a more accurate, real-time measurement for land cover and it could be calculated with greater temporal detail. The results will allow decision makers to make more informed decisions on resiliency strategies to address future flooding.

Trista Brophy↗

DOE OSTI2023

Global variations in critical drought thresholds that impact vegetation

ABSTRACT Identifying the thresholds of drought that, if crossed, suppress vegetation functioning is vital for accurate quantification of how land ecosystems respond to climate variability and change. We present a globally applicable framework to identify drought thresholds for vegetation responses to different levels of known soil-moisture deficits using four remotely sensed vegetation proxies spanning 2001–2018. The thresholds identified represent critical inflection points for changing vegetation responses from highly resistant to highly vulnerable in response to drought stress, and as a warning signal for substantial vegetation impacts. Drought thresholds varied geographically, with much lower percentiles of soil-moisture anomalies in vegetated areas covered by more forests, corresponding to a comparably stronger capacity to mitigate soil water deficit stress in forested ecosystems. Generally, those lower thresholds are detected in more humid climates. State-of-the-art land models, however, overestimated thresholds of soil moisture (i.e. overestimating drought impacts), especially in more humid areas with higher forest covers and arid areas with few forest covers. Based on climate model projections, we predict that the risk of vegetation damage will increase by the end of the twenty-first century in some hotspots like East Asia, Europe, Amazon, southern Australia and eastern and southern Africa. Our data-based results will inform projections on future drought impacts on terrestrial ecosystems and provide an effective tool for drought management.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1975

Snow survey and vegetation growth in high mountains (Swiss Alps) and additional ERTS investigations in Switzerland

The author has identified the following significant results. Two different methods, an analog and a digital one, have been developed for rapid and accurate mapping of the areal extent and changes in snow cover in high mountains. The quick-look method is based on individual visual control of each image using a photo quantizer which provides exact references for density slicing with high resolution lith-film. The digital snow classification system is based on discriminant analysis with the data of the four multispectral bands as variables and contains all preprocessing, feature extraction, and mapping steps for an operational application. Two different sets of sampling groups were established which apply to different conditions of snow cover. The first one serves for the normal situation with a uniform dry and new cover. The second one serves for situations with partly thawing and/or frozen snow.

Haefner, H.↗

NASA NTRS2001

Visions of Our Planet's Atmosphere, Land and Oceans Electronic-Theater 2001

The NASA/NOAA/AMS Electronic Theater presents Earth science observations and visualizations in a historical perspective. Fly in from outer space to Fredericton New Brunswick. Drop in on the Kennedy Space Center and Park City Utah, site of the 2002 Olympics using 1 m IKONOS "Spy Satellite" data. Go back to the early weather satellite images from the 1960s and see them contrasted with the latest US and International global satellite weather movies including hurricanes & tornadoes. See the latest spectacular images from NASA/NOAA and Canadian remote sensing missions like Terra GOES, TRMM, SeaWiFS, Landsat 7, and Radarsat that are visualized & explained. See how High Definition Television (HDTV) is revolutionizing the way we communicate science in cooperation with the American Museum of Natural History in NYC. See dust storms in Africa and smoke plumes from fires in Mexico. See visualizations featured on Newsweek, TIME, National Geographic, Popular Science covers & National & International Network TV. New visualization tools allow us to roam & zoom through massive global images eg Landsat tours of the US, Africa, & New Zealand showing desert and mountain geology as well as seasonal changes in vegetation. See animations of the polar ice packs and the motion of gigantic Antarctic Icebergs from SeaWinds data. Spectacular new visualizations of the global atmosphere & oceans are shown. See massive dust storms sweeping across Africa. See vortexes and currents in the global oceans that bring up the nutrients to feed tiny plankton and draw the fish, whales and fisherman. See the how the ocean blooms in response to these currents and El Nino/La Nina climate changes. The demonstration is interactively driven by a SGI Onyx II Graphics Supercomputer with four CPUs, 8 Gigabytes of RAM and Terabyte of disk. With multiple projectors on a giant screen. See the city lights, fishing fleets, gas flares and bio-mass burning of the Earth at night observed by the "night-vision" DMSP military satellite.

Hasler, A. F.↗

NASA NTRS2001

Electronic-Theater 2001: Visions of Our Planet's Atmosphere, Land and Oceans

The NASA/NOAA/AMS Electronic Theater presents Earth science observations and visualizations in a historical perspective. Fly in from outer space to Wisconsin, Madison and the Monona Terrace Center. Drop in on the Kennedy Space Center and Park City Utah, site of the 2002 Olympics using I m IKONOS "Spy Satellite" data. Go back to the early weather satellite images from the 1960s pioneered by UW. Scientists and see them contrasted with the latest US and International global satellite weather movies including hurricanes & tornadoes. See the latest spectacular images from NASA/NOAA remote sensing missions like Terra GOES, TRMM, SeaWiFS, Landsat 7 that are visualized & explained. See how High Definition Television (HDTV) is revolutionizing the way we communicate science in cooperation with the American Museum of Natural History in NYC. See dust storms in Africa and smoke plumes from fires in Mexico. See visualizations featured on Newsweek, TIME, National Geographic, Popular Science covers & National & International Network TV. New visualization tools allow us to roam & zoom through massive global images eg Landsat tours of the US, Africa, & New Zealand showing desert and mountain geology as well as seasonal changes in vegetation. See animations of the polar ice packs and the motion of gigantic Antarctic Icebergs from SeaWinds data. Spectacular new visualizations of the global atmosphere & oceans are shown. See massive dust storms sweeping across Africa. See vortices and currents in the global oceans that bring up the nutrients to feed tiny plankton and draw the fish, whales and fisherman. See the how the ocean blooms in response to these currents and El Nina/La Nina climate changes. The demonstration is interactively driven by a SGI Onyx 11 Graphics Supercomputer with four CPUs, 8 Gigabytes of RAM and Terabyte of disk. With five projectors on a giant IMAX sized 18 x 72 ft screen. See the city lights, fishing fleets, gas flares and bio-mass burning of the Earth at night observed by the "nightvision" DMSP military satellite.

Hasler, Authur↗

NASA NTRS2018

Modeling the Distribution and Type of High-Latitude Natural Wetlands for Methane Studies

High latitude (>50N) natural wetlands emit a substantial amount of methane to the atmosphere, and are located in a region of amplified warming. Northern hemisphere high latitudes are characterized by cold climates, extensive permafrost, poor drainage, short growing seasons, and slow decay rates. Under these conditions, organic carbon accumulates in the soil, sequestering CO2 from the atmosphere. Methanogens produce methane from this carbon reservoir, converting stored carbon into a powerful greenhouse gas. Methane emission from wetland ecosystems depends on vegetation type, climate characteristics (e.g, precipitation amount and seasonality, temperature, snow cover, etc.), and geophysical variables (e.g., permafrost, soil type, and landscape slope). To understand how wetland methane dynamics in this critical region will respond to climate change, we have to first understand how wetlands themselves will change and therefore, what the primary controllers of wetland distribution and type are. Understanding these relationships permits data-anchored, physically-based modeling of wetland distribution and type in other climate scenarios, such as paleoclimates or future climates, a necessary first step toward modeling wetland methane emissions in these scenarios. We investigate techniques and datasets for predicting the distribution and type of high latitude (>50N) natural wetlands from a suite of geophysical and climate predictors. Hierarchical clustering is used to derive an empirical methane-centric wetland model. The model is applied in a multistep process first to predict the distribution of wetlands from relevant geophysical parameters, and then, given the predicted wetland distribution, to classify the wetlands into methane-relevant types using an expanded suite of climate and biogeophysical variables. As the optimum set of predictor variables is not known a priori, the model is applied iteratively, and each simulation is evaluated with respect to observed high-latitude wetlands.

Romanski, Joy↗

DOE OSTI2023

Climate cooling benefits of cellulosic bioenergy crops from elevated albedo

Abstract Changes in land surface albedo can alter ecosystem energy balance and potentially influence climate. We examined the albedo of six bioenergy cropping systems in southwest Michigan USA: monocultures of energy sorghum ( Sorghum bicolor ), switchgrass ( Panicum virgatum L.), and giant miscanthus ( Miscanthus × giganteus) , and polycultures of native grasses, early successional vegetation, and restored prairie. Direct field measurements of surface albedo ( α s ) from May 2018 through December 2020 at half‐hourly intervals in each system quantified the magnitudes and seasonal differences in albedo (∆ α ) and albedo‐induced radiative forcing (RF ∆ α ). We used a nearby forest as a historical native cover type to estimate reference albedo and RF ∆ α change upon original land use conversion, and a continuous no‐till maize ( Zea mays L .) system as a contemporary reference to estimate change upon conversion from annual row crops. Annually, α s differed significantly ( p < 0.05) among crops in the order: early successional (0.288 ± 0.012SE) >> miscanthus (0.271 ± 0.009) ≈ energy sorghum (0.270 ± 0.010) ≥ switchgrass (0.265 ± 0.009) ≈ restored prairie (0.264 ± 0.012) > native grasses (0.259 ± 0.010) > maize (0.247 ± 0.010). Reference forest had the lowest annual α s (0.134 ± 0.003). Albedo differences among crops during the growing season were also statistically significant, with growing season α s in perennial crops and energy sorghum on average ~20% higher (0.206 ± 0.003) than in no‐till maize (0.184 ± 0.002). Average non‐growing season (NGS) α s (0.370 ± 0.020) was much higher than growing season α s (0.203 ± 0.003) but these NGS differences were not significant. Overall, the original conversion of reference forest and maize landscapes to perennials provided a cooling effect on the local climate (RF αMAIZE : −3.83 ± 1.00 W m −2 ; RF αFOREST : −16.75 ± 3.01 W m −2 ). Significant differences among cropping systems suggest an additional management intervention for maximizing the positive climate benefit of bioenergy crops, with cellulosic crops on average ~9.1% more reflective than no‐till maize, which itself was about twice as reflective as the reference forest.

Lei, Cheyenne↗

NASA NTRS1987

Digital image classification approach for estimating forest clearing and regrowth rates and trends

A technique is presented to monitor vegetation changes for a selected study area in Costa Rica. A normalized difference vegetation index was computed for three dates of Landsat satellite data and a modified parallelipiped classifier was employed to generate a multitemporal greenness image representing all three dates. A second-generation image was created by partitioning the intensity levels at each date into high, medium, and low and thereby reducing the number of classes to 21. A sampling technique was applied to describe forest and other land cover change occurring between time periods based on interpretation of aerial photography that closely matched the dates of satellite acquisition. Comparison of the Landsat-derived classes with the photo-interpreted sample areas can provide a basis for evaluating the satellite monitoring technique and the accuracy of estimating forest clearing and regrowth rates and trends.

Sader, Steven A.↗

DOE OSTI2023

Long-Term Changes in Concentration and Yield of Riverine Dissolved Silicon From the Poles to the Tropics

Riverine exports of silicon (Si) influence global carbon cycling through the growth of marine diatoms, which account for ~25% of global primary production. Climate change will likely alter river Si exports in biome-specific ways due to interacting shifts in chemical weathering rates, hydrologic connectivity, and metabolic processes in aquatic and terrestrial systems. Nonetheless, factors driving long-term changes in Si exports remain unexplored at local, regional, and global scales. We evaluated how concentrations and yields of dissolved Si (DSi) changed over the last several decades of rapid climate warming using long-term data sets from 60 rivers and streams spanning the globe (e.g., Antarctic, tropical, temperate, boreal, alpine, Arctic systems). We show that widespread changes in river DSi concentration and yield have occurred, with the most substantial shifts occurring in alpine and polar regions. The magnitude and direction of trends varied within and among biomes, were most strongly associated with differences in land cover, and were often independent of changes in river discharge. These findings indicate that there are likely diverse mechanisms driving change in river Si biogeochemistry that span the land-water interface, which may include glacial melt, changes in terrestrial vegetation, and river productivity. Finally, trends were often stronger in months outside of the growing season, particularly in temperate and boreal systems, demonstrating a potentially important role of shifting seasonality for the flux of Si from rivers. Our results have implications for the timing and magnitude of silica processing in rivers and its delivery to global oceans.

54 ENVIRONMENTAL SCIENCES↗