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At least 109 records · Page 6

Characterization of LANDSAT-4 TM and MSS Image Quality for Interpretation of Agricultural and Forest Resources

Systematic analysis of both image and numeric data shows that the overall spectral, spatial, and radiometric quality of the TM data are excellent. Spectral variations in fallow fields are due to the vaiability in soil moisture and surface roughness resulting from the various stages of field preparation for small grains production. Spectrally, the addition of the first TM short wave infrared band (Band 5) significantly enhanced ability to discriminate different crop types. Bands 1, 5, and 6 contain saturated pixels due to high albedo effects, low moisture conditions, and high radiant temperatures of granite and dry, bare soil on south facing slopes, respectively. Spatially, the two fold decrease in interpixel distance and four fold decrease in area per pixel between the TM and MSS allow for improved discrimination of small fields, boundary conditions, road and stream networks in rough terrain, and small forest clearings resulting from various forest management practices.

Degloria, S. D.↗

Mechanisms of nitrogen retention in forest ecosystems - A field experiment

Intensive forest management led to elevated losses of nitrogen from a recently harvested loblolly pine plantation in North Carolina. Measurements of nitrogen-15 retention in the field demonstrated that microbial uptake of nitrogen during the decomposition of residual organic material was the most important process retaining nitrogen. Management practices that remove this material cause increased losses of nitrogen to aquatic ecosystems and the atmosphere.

Vitousek, P. M.↗

Remote sensing of the earth's surface; Proceedings of the Symposium 2, Topical Meeting, and Workshop I of the 27th COSPAR Plenary Meeting, Espoo, Finland, July 18-29, 1988

The present conference discusses topics in the spaceborne study of the earth's surface, crust, and lithosphere, recent results from SPOT and Landsat TM investigations, and microwave observations of snowpack and soil properties. Attention is given to airborne and satellite-borne gravimetry, stereoviewing from space, TM studies of volcanism and tectonism in central Mexico, remote sensing of volcanoes, the uses of SPOT in forest management, the tectonics of the central Andes, and the application of VLBI to crustal movement studies. Also discussed are Landsat TM band ratios for soil investigations, snow dielectric measurements, the microwave radiometry of snow, microwave signatures of bare soil, the estimation of Alpine snow properties from Landsat TM data, and an experimental study of vegetable canopy microwave emissions.

Salomonson, V. V.↗

A memory efficient user interface for CLIPS micro-computer applications

The goal of the Integrated Southern Pine Beetle Expert System (ISPBEX) is to provide expert level knowledge concerning treatment advice that is convenient and easy to use for Forest Service personnel. ISPBEX was developed in CLIPS and delivered on an IBM PC AT class micro-computer, operating with an MS/DOS operating system. This restricted the size of the run time system to 640K. In order to provide a robust expert system, with on-line explanation, help, and alternative actions menus, as well as features that allow the user to back up or execute 'what if' scenarios, a memory efficient menuing system was developed to interface with the CLIPS programs. By robust, we mean an expert system that (1) is user friendly, (2) provides reasonable solutions for a wide variety of domain specific problems, (3) explains why some solutions were suggested but others were not, and (4) provides technical information relating to the problem solution. Several advantages were gained by using this type of user interface (UI). First, by storing the menus on the hard disk (instead of main memory) during program execution, a more robust system could be implemented. Second, since the menus were built rapidly, development time was reduced. Third, the user may try a new scenario by backing up to any of the input screens and revising segments of the original input without having to retype all the information. And fourth, asserting facts from the menus provided for a dynamic and flexible fact base. This UI technology has been applied successfully in expert systems applications in forest management, agriculture, and manufacturing. This paper discusses the architecture of the UI system, human factors considerations, and the menu syntax design.

Sterle, Mark E.↗

Forestry Vehicle

Power Pack II provides an economical means of moving a power source into remote roadless forest areas. It was developed by Prof. Miles and his associates, working in cooperation with the University of California's Department of Forestry. The team combined its own design of an all-terrain vehicle with a suspension system based on the NASA load equalization technology. Result is an intermediate-sized unit which carries a power source and the powered tools to perform a variety of forest management tasks which cannot be done economically with current equipment. Power Pack II can traverse very rough terrain and climb a 60 degree slope; any one of the wheels can move easily over an obstacle larger than itself. Work is being done on a more advanced Power Pack III.

Source record↗

Communicating the Needs of Climate Change Policy Makers to Scientists

This chapter will describe the challenges that earth scientists face in developing science data products relevant to decision maker and policy needs, and will describe strategies that can improve the two-way communication between the scientist and the policy maker. Climate change policy and decision making happens at a variety of scales - from local government implementing solar homes policies to international negotiations through the United Nations Framework Convention on Climate Change. Scientists can work to provide data at these different scales, but if they are not aware of the needs of decision makers or understand what challenges the policy maker is facing, they are likely to be less successful in influencing policy makers as they wished. This is because the science questions they are addressing may be compelling, but not relevant to the challenges that are at the forefront of policy concerns. In this chapter we examine case studies of science-policy partnerships, and the strategies each partnership uses to engage the scientist at a variety of scales. We examine three case studies: the global Carbon Monitoring System pilot project developed by NASA, a forest biomass mapping effort for Silvacarbon project, and a forest canopy cover project being conducted for forest management in Maryland. In each of these case studies, relationships between scientists and policy makers were critical for ensuring the focus of the science as well as the success of the decision-making.

Brown, Molly E.↗

Airborne Lidar-Based Estimates of Tropical Forest Structure in Complex Terrain: Opportunities and Trade-Offs for REDD+

Background: Carbon stocks and fluxes in tropical forests remain large sources of uncertainty in the global carbon budget. Airborne lidar remote sensing is a powerful tool for estimating aboveground biomass, provided that lidar measurements penetrate dense forest vegetation to generate accurate estimates of surface topography and canopy heights. Tropical forest areas with complex topography present a challenge for lidar remote sensing. Results: We compared digital terrain models (DTM) derived from airborne lidar data from a mountainous region of the Atlantic Forest in Brazil to 35 ground control points measured with survey grade GNSS receivers. The terrain model generated from full-density (approx. 20 returns/sq m) data was highly accurate (mean signed error of 0.19 +/-0.97 m), while those derived from reduced-density datasets (8/sq m, 4/sq m, 2/sq m and 1/sq m) were increasingly less accurate. Canopy heights calculated from reduced-density lidar data declined as data density decreased due to the inability to accurately model the terrain surface. For lidar return densities below 4/sq m, the bias in height estimates translated into errors of 80-125 Mg/ha in predicted aboveground biomass. Conclusions: Given the growing emphasis on the use of airborne lidar for forest management, carbon monitoring, and conservation efforts, the results of this study highlight the importance of careful survey planning and consistent sampling for accurate quantification of aboveground biomass stocks and dynamics. Approaches that rely primarily on canopy height to estimate aboveground biomass are sensitive to DTM errors from variability in lidar sampling density.

Airborne lidar↗

Landsat at 45: How it Changed the Way We See the Earth

On October 24, 1946, more than 10 years before the launch of the first artificial satellite Sputnik, scientists at the White Sands Missile Range in New Mexico placed a camera on top of a captured German V-2 ballistic missile. As the rocket flew to an altitude of about 65 miles - just above the generally recognized border of outer space - the 35-millimeter motion picture camera snapped a frame every one and a half seconds. Minutes later, the missile came crashing back down and slammed into the ground at more than 340 mph, but the film survived and gave us our first glimpse of Earth from space. Earth Resources Technology Satellite aka Landsat It was images like those first grainy black and white pictures and later those taken by America's first astronauts in the 1960's that inspired the development of the Earth Resources Technology Satellite (ERTS). From the unique vantage point of space, we could now observe Earth using a variety of different instruments to monitor changes over time. The ERTS-1 satellite, wisely renamed Landsat-1, was launched aboard a Delta rocket on July 23, 1972, into a Sun-synchronous polar orbit at an altitude of about 560 miles. In this unique orbit, Landsat could observe the same point on the Earth every 18 days, always with the same solar illumination, allowing for precise monitoring of changes on the ground over time. Landsat-1, derived from the highly successful Nimbus weather satellites, carried two instruments that allowed it to take images not only in visible light but also in infrared, well-suited to track changes in vegetation over time. Designed to last only one year, Landsat-1 actually operated for nearly three years, by which time it had been joined in space by Landsat-2, a near identical copy of the original. Since then, ever more sophisticated instruments were flown aboard Landsat-3 through -8, with Landsat-9 planned for launch in 2020, acquiring millions of images of Earth over more than four decades. At first, images from Landsat were processed by NASA and hardcopies sold to users for a fee, a somewhat tedious process. Since 2008, images have been made available to all interested users by the US Geological Survey (USGS) at no cost via the Internet in near real time. So, how can Landsat help? In short, Landsat looks. And looks. And proves Yogi right. Space-based images from Landsat and other similar satellites offer a unique and critical capability to observe land use over time by providing repetitive observations of the Earth otherwise unavailable. The data provided by the images can be used by scientists and politicians to inform wise decisions in areas such as agriculture, climate, ecosystems and biodiversity, energy, forest management, human health, fire, natural disasters, urban growth and water management. This overview article doesn't allow for examples from each of these disciplines, but details can be found at the following website: https://landsat.gsfc.nasa.gov/how_landsat_helps/. One third of the US economy is influenced by climate, weather and natural hazards, providing strong economic incentives to sustain a healthy space-based Earth observation program. One example, however, may be illustrative of how Landsat and other space-based observations can be helpful in monitoring and documenting some effects of global climate change. It had been noted since the 1970's that permafrost in subarctic areas like Siberia was melting at an accelerating rate. It also became apparent that this led to the formation of hundreds of melt lakes and the liberation of large quantities of methane, a gas that in the short-term has more potent greenhouse effects than carbon dioxide. The methane turned the water in these lakes blue, making them easy to track over time by satellite. Additionally, the newly released methane has been carbon dated to tens of thousands of years ago, meaning that it had remained frozen since the last Ice Age and therefore hadn't been accounted for in models of the Earth's overall carbon balance. Release of sufficient methane by an increasingly warming climate could actually cause a positive feedback loop in global warming, melting more permafrost and releasing yet more methane. Further monitoring by Landsat and other platforms will reveal whether this process is reversible or whether we've passed the tipping point. In addition to the highly successful Landsat series of satellites, NASA and other agencies such as the National Oceanic and Atmospheric Administration (NOAA) operate a fleet of other Earth observing platforms, many with more specific research goals such as monitoring sea ice levels or atmospheric carbon content. Several instruments aboard the International Space Station also contribute to this overall effort to better understand short- and long-term changes to the Earth. Many of these missions are guided by the 2009 Decadal Survey published by the National Research Council of the National Academy of Sciences. Europe, Russia and China all see the value of space-based Earth observation by deploying their own fleet of satellites.

Uri, John↗

Satellite-Based Assessment of Grassland Conversion and Related Fire Disturbance in the Kenai Peninsula, Alaska

Spruce beetle-induced (Dendroctonus rufipennis (Kirby)) mortality on the Kenai Peninsula has been hypothesized by local ecologists to result in the conversion of forest to grassland and subsequent increased fire danger. This hypothesis stands in contrast to empirical studies in the continental US which suggested that beetle mortality has only a negligible effect on fire danger. In response, we conducted a study using Landsat data and modeling techniques to map land cover change in the Kenai Peninsula and to integrate change maps with other geospatial data to predictively map fire danger for the same region. We collected Landsat imagery to map land cover change at roughly five-year intervals following a severe, mid-1990s beetle infestation to the present. Landcover classification was performed at each time step and used to quantify grassland encroachment patterns over time. The maps of land cover change along with digital elevation models (DEMs),temperature, and historical fire data were used to map and assess wildfire danger across the study area. Results indicate the highest wildfire danger tended to occur in herbaceous and black spruce land cover types, suggesting that the relationship between spruce beetle damage and wildfire danger in costal Alaskan forested ecosystems differs from the relationship between the two in the forests of the coterminous United States. These change detection analyses and fire danger predictions provide the Kenai National Wildlife Refuge (KENWR) ecologists and other forest managers a better understanding of the extent and magnitude of grassland conversion and subsequent change in fire danger following the 1990s spruce beetle outbreak.

wildfire↗

Bhutan Water Resources III: Analyzing Forest Disturbances and Climate Data in Bhutan to Create a Tool for Assisting the Himalayan Environment Rhythm Observation and Evaluation Systems (HEROES) Project

Forest disturbances from bark beetle outbreaks are a major concern in Bhutan, known to cause extensive tree mortality to pine and spruce forests. The NASA DEVELOP team partnered with the Ugyen Wangchuck Institute of Conservation and Environmental Research (UWICER), the Bhutan Foundation, and the Karuna Foundation to assess forest changes for the districts of Bumthang and Haa from 2000 to 2018. The project used preprocessed meteorological data from the Climate Hazards Center Infrared Precipitation with Station (CHIRPS) and Famine Early Warning System Network Land Data Assimilation System (FLDAS), along with Landsat 5 Thematic Mapper (TM), Landsat 7 Enhanced Thematic Mapper plus (ETM+), and Landsat 8 Operational Land Imager (OLI) to assess apparent forest disturbance occurrences and observed climate trends. Shuttle Radar Topography Mission (SRTM) was used to resolve variations in elevation and slope for mountainous regions. Using the Google Earth Engine LandTrendr (LT) code algorithm, along with Landsat data, the team developed an app called Forest Disturbances Detection Toolbox (FDDT) to assess forest changes in Bhutan. The app includes climate variables for the focus districts, along with LT variables, which allows the end users to further examine the cause of disturbances. The team compared geocoordinates for known disturbances with LT disturbance detection products. Although additional work is needed in the future to validate the project end products from the FDDT, the tool will be provided to the project partners to aid forest management efforts in Bhutan.

Tashi Choden↗

Wildfire Adaptation in the Russian Arctic: A Systematic Policy Review

A scientific consensus acknowledges that climate change has increased wildfire activity in the Russian Arctic, a trend projected to continue in response to further warming. Regional governments across Russia have started to design and develop adaptation policies and plans (i.e. outputs) to this end. Our comprehensive understanding on the state of wildfire adaptation in policy is limited. In this article we systematically review policies and plans developed to adapt to wildfires in the Russian Arctic. Using systematic approaches, we identify 12 wildfire adaptation outputs adopted between 2008 and 2020. Our findings indicate that wildfire adaptation outputs are aimed at reducing the risk of wildfires and improve wildland fire response, implemented through legislative and regulatory mechanisms, developed at the regional level, adopted in response to national mandates, and mainstreamed into existing forest management policies. Although there is evidence of wildfire adaptation planning occurring in the Russian Arctic, we find that the nature and extent of wildfire adaptation outputs are not sufficient to address the seriousness and severity of climate change, with key shortcomings found in relation to the scientific, human, and management characteristics. We argue that expanding the profile of climate change research in the Russian Arctic and improving the dialogue among researchers, local and Indigenous peoples, and decision-makers are critical for providing useful recommendations for policy makers to accelerate wildfire adaptation in the Russian Arctic.

Wildfire↗

Los Angeles Urban Development Utilizing Nasa Earth Observations to Evaluate the Impact of Tree Coverage on Urban Heat Mitigation

In recent decades, Los Angeles, California has experienced an increase in summer temperatures that has intensified the urban heat island effect. The expansion of developed areas has contributed significantly to this phenomenon by trapping and reradiating heat, posing dangerous health risks to residents. To mitigate this problem, organizations including City Plants and the L.A.’s Office of City Forest Management have implemented initiatives to promote urban greening and tree planting, which help cool down vulnerable communities. In collaboration with these partners, NASA DEVELOP has undertaken a study to investigate the role of trees in urban environments and their effectiveness in reducing local urban heat islands.

Leyla Namazie↗

Los Angeles Urban Development: Utilizing NASA Earth Observations to Evaluate the Impact of Tree Coverage on Urban Heat Mitigation

Over the last several decades the city of Los Angeles, California, has been experiencing increased temperatures resulting from the urban heat island effect. This is largely due to the expansion of developed areas which allow for the trapping of heat, posing dangerous health risks. As a solution, many organizations have turned to urban greening and tree planting initiatives to help cool vulnerable communities. NASA DEVELOP has partnered with City Plants and the City of Los Angeles, Office of Forest Management to study the role of trees in urban environments and their relation to the mitigation of local urban heat islands. This team used NASA Earth observation data spanning from 2016 to 2022, including land surface temperature and Normalized Difference Vegetation Index (NDVI) data collected from Landsat 8 Thermal Infrared Sensor (TIRS) and International Space Station (ISS) ECOsystem Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS), respectively. Data from the National Agriculture Imagery Program (NAIP) were also used to obtain a supervised classification of tree canopy cover. Our analysis reveals a spatial and temporal connection between temperature and vegetation, suggesting that areas with more vegetation are less likely to suffer high summertime temperatures. Results also highlight the impacts of tree planting programs, such as the Vermont Corridor planting project, which increased tree canopy cover by up to 5% in the community between 2016 and 2022. These findings support the implementation of urban greening practices and inform residents and officials about how investing in trees will help mitigate increasing heat within Los Angeles.

Urban heat island↗

Assessing the Transferability of Statistical Predictive Models for Leaf Area Index Between Two Airborne Discrete Return LiDAR Sensor Designs Within Multiple Intensely Managed Loblolly Pine Forest Locations in the South-Eastern USA

Leaf area is an important forest structural variable which serves as the primary means of mass and energy exchange within vegetated ecosystems. The objective of the current study was to determine if leaf area index (LAI) could be estimated accurately and consistently in five intensively managed pine plantation forests using two multiple-return airborne LiDAR datasets. Field measurements of LAI were made using the LiCOR LAI2000 and LAI2200 instruments within 116 plots were established of varying size and within a variety of stand conditions (i.e. stand age, nutrient regime and stem density) in North Carolina and Virginia in 2008 and 2013. A number of common LiDAR return height and intensity distribution metrics were calculated (e.g. average return height), in addition to ten indices, with two additional variants, utilized in the surrounding literature which have been used to estimate LAI and fractional cover, were calculated from return heights and intensity, for each plot extent. Each of the indices was assessed for correlation with each other, and was used as independent variables in linear regression analysis with field LAI as the dependent variable. All LiDAR derived metrics were also entered into a forward stepwise linear regression. The results from each of the indices varied from an R2 of 0.33 (S.E. 0.87) to 0.89 (S.E. 0.36). Those indices calculated using ratios of all returns produced the strongest correlations, such as the Above and Below Ratio Index (ABRI) and Laser Penetration Index 1 (LPI1). The regression model produced from a combination of three metrics did not improve correlations greatly (R2 0.90; S.E. 0.35). The results indicate that LAI can be predicted over a range of intensively managed pine plantation forest environments accurately when using different LiDAR sensor designs. Those indices which incorporated counts of specific return numbers (e.g. first returns) or return intensity correlated poorly with field measurements. There were disparities between the number of different types of returns and intensity values when comparing the results from two LiDAR sensors, indicating that predictive models developed using such metrics are not transferable between datasets with different acquisition parameters. Each of the indices were significantly correlated with one another, with one exception (LAI proxy), in particular those indices calculated from all returns, which indicates similarities in information content for those indices. It can then be argued that LiDAR indices have reached a similar stage in development to those calculated from optical-spectral sensors, but which offer a number of advantages, such as the reduction or removal of saturation issues in areas of high biomass.

Sumnall, Matthew↗

Mapping Pine Plantations in the Southeastern U.S. Using Structural, Spectral, and Temporal Remote Sensing Data

The southeastern U.S. produces the most industrial roundwood in the U.S. each year, largely from commercial pine plantations. The extent of plantation forests and management dynamics can be difficult to ascertain from periodic forest inventories, yet short-rotation tree plantations also present challenges for remote sensing. Here, we integrated spectral, temporal, and structural information from airborne and satellite platforms to distinguish pine plantations from natural forests and evaluate the contribution from planted forests to regional forest coverin the southeastern U.S. Within flight lines from NASA Goddard's Lidar, Hyperspectral, and Thermal (G-LiHT) Airborne Imager, lidar metrics of forest structure had the highest overall accuracy for pine plantations among single-source classifications (90%), but the combination of spectral and temporal metrics from Landsat generated comparable accuracy (91%). Combined structural, temporal, and spectral information from G-LiHT and Landsat had the highest accuracy for plantations (92%) and natural forests (88%). At a regional scale, classifications using Landsat spectral and temporal metrics had between 74 and 82% mean class accuracy for plantations.Regionally, plantations accounted for 28% of forest cover in the southeastern U.S., a result similar to plot-based estimates, albeit with greater spatial detail. Regional maps of plantation forests differed from existing map products, including the National Land Cover Database. Combining plantation extent in 2011 with Landsat based forest change data identified strong regional gradients in plantation dynamics since 1985, with distinct spatial patterns of rotation age (east-west) and plantation expansion (interior). Our analysis demonstrates the potential to improve the characterization of dynamic land cover classes, including economically important timber plantations, by integrating diverse remote sensing datasets. Critically, multi-source remote sensing provides an approach to leverage periodic forest inventory data for annual monitoring of managed forest landscapes.

Fagan, M. E.↗

Remote sensing applications in agriculture and forestry. Applications of aerial photography and ERTS data to agricultural, forest and water resources management

Remote sensing techniques are being used in Minnesota to study: (1) forest disease detection and control; (2) water quality indicators; (3) forest vegetation classification and management; (4) detection of saline soils in the Red River Valley; (5) corn defoliation; and (6) alfalfa crop productivity. Results of progress, and plans for future work in these areas, are discussed.

Source record↗

Development of a statewide Landsat digital data base for forest insect damage assessment

A Joint Research Project (JRP) invlving NASA/Goddard Space Flight Center and the Pennsylvania Bureau of Forestry/Division of Forest Pest Management demonstrates the utility of Landsat data for assessing forest insect damage. A major effort within the project has been the creation of map-registered, statewide Landsat digital data base for Pennsylvania. The data base, developed and stored on computers at the Pennsylvania State University Computation Center, contains Landsat imagery, a Landsat-derived forest resource map, and digitized data layers depicting Forest Pest Management District boundaries and county boundaries. A data management front-end system was also developed to provide an interface between the various layers of information within the data base and image analysis software. This front-end system insures than an automated assessment of defoliation damage can be conducted and summarized by geographic area or jurisdiction of interest.

Williams, D. L.↗

Development of computer software to analyze entire LANDSAT scenes and to summarize classification results of variable-size polygons

The Forest Pest Management Division (FPMD) of the Pennsylvania Bureau of Forestry has the responsibility for conducting annual surveys of the State's forest lands to accurately detect, map, and appraise forest insect infestations. A standardized, timely, and cost-effective method of accurately surveying forests and their condition should enhance the probability of suppressing infestations. The repetitive and synoptic coverage provided by LANDSAT (formerly ERTS) makes such satellite-derived data potentially attractive as a survey medium for monitoring forest insect damage over large areas. Forest Pest Management Division personnel have expressed keen interest in LANDSAT data and have informally cooperated with NASA/Goddard Space Flight Center (GSFC) since 1976 in the development of techniques to facilitate their use. The results of this work indicate that it may be feasible to use LANDSAT digital data to conduct annual surveys of insect defoliation of hardwood forests.

Turner, B. J.↗