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At least 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Machine Learning Explainability and Transferability for Path Navigation

Deep neural networks are powerful tools for machine perception. Unfortunately their decisions are difficult to explain due to the complexity and size of the networks. Previously we have alleviated this issue by using the representational portion of a deep neural network and combining it with a k-nearest neighbor (KNN) classifier. Through inspection of the decisions made by the KNN, we can directly see the training data responsible for the decisions, allowing us to determine the quality of the overall decision and the quality of the representational layer of the deep NN. While the technique worked well, it requires tens of thousands of latent vectors to be stored for classification. In addition, it lacks the ability to show how parts of an image influence the classification decision. Here we address these issues by 1) Using a radial basis function network (RBFN) in place of the KNN allowing far fewer images to be used in deployment and 2) Using an auto encoder network for explainability. In addition to these techniques, we examine the effects of transfer learning to determine that results are robust. All results are tested on a domain where an unmanned aerial vehicle (UAV) navigates a forest trail through a single camera.

explainable machine learning↗
DOE OSTI2020

AmeriFlux US-xTR NEON Treehaven (TREE)

This is the AmeriFlux version of the carbon flux data for the site US-xTR NEON Treehaven (TREE). Site Description - Treehaven, situated between Rhinelander and Tomahawk, WI, is one of two relocatable sites located in NEON’s Great Lakes Domain. The Treehaven property spans 1400 acres and is owned and operated by the University of Wisconsin-Stevens Point (UWSP), College of Natural Resources. UWSP uses the property and conference center for summer field techniques courses but welcomes other educators, researchers, and the public to use and enjoy their forests, trails, and facility.

Network), NEON (National Ecological Observatory↗
DOE OSTI2023

AmeriFlux FLUXNET-1F US-xTR NEON Treehaven (TREE)

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-xTR NEON Treehaven (TREE). This is the FLUXNET version of the carbon flux data for the site US-xTR NEON Treehaven (TREE) produced by applying the standard ONEFlux (1F) software. Site Description - Treehaven, situated between Rhinelander and Tomahawk, WI, is one of two relocatable sites located in NEON’s Great Lakes Domain. The Treehaven property spans 1400 acres and is owned and operated by the University of Wisconsin-Stevens Point (UWSP), College of Natural Resources. UWSP uses the property and conference center for summer field techniques courses but welcomes other educators, researchers, and the public to use and enjoy their forests, trails, and facility.

Network), NEON (National Ecological Observatory↗
NASA NTRS2020

Improving Trust in Deep Neural Networks with Nearest Neighbors

Deep neural networks are used increasingly for perception and decision-making in UAVs. For example, they can be used to recognize objects from images and decide what actions the vehicle should take. While deep neural networks can perform very well at complex tasks, their decisions may be unintuitive to a human operator. When a human disagrees with a neural network prediction, due to the black box nature of deep neural networks, it can be unclear whether the system knows something the human does not or whether the system is malfunctioning. This uncertainty is problematic when it comes to ensuring safety. As a result, it is important to develop technologies for explaining neural network decisions for trust and safety. This paper explores a modification to the deep neural network classification layer to produce both a predicted label and an explanation to support its prediction. Specifically, at test time, we replace the final output layer of the neural network classifier by a k-nearest neighbor classifier. The nearest neighbor classifier produces 1) a predicted label through voting and 2) the nearest neighbors involved in the prediction, which represent the most similar examples from the training dataset. Because prediction and explanation are derived from the same underlying process, this approach guarantees that the explanations are always relevant to the predictions. We demonstrate the approach on a convolutional neural network for a UAV image classification task. We perform experiments using a forest trail image dataset and show empirically that the hybrid classifier can produce intuitive explanations without loss of predictive performance compared to the original neural network. We also show how the approach can be used to help identify potential issues in the network and training process.

Lee, Ritchie↗
DOE OSTI2023

Inspection Status Report of Site A/Plot M Report for 2023

The Site A/Plot M Decommissioned Reactor Site was inspected on June 6, 2023. Site A/Plot M is in the Palos Area Preserves, operated by the Forest Preserve District of Cook County. The site was found to be in good condition with negligible erosional concerns across the grass covered mound at Plot M. Landscaping timbers installed along the footpath of Plot M have been effective in reducing erosion down the eastern slope, thus, no additional timber steps are needed at this time. The bike trail, installed by Cook County Forest Preserve, located to the south and east of Plot M has helped to significantly reduce traffic at the site. The Site A and Plot M monuments were both replaced on May 1, 2021, and remain in good condition, despite a small amount of graffiti observed on both monuments at the time of the inspection. The 19 groundwater monitoring wells at Site A/Plot M were found to be secure and in good condition.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2020

Inspection Status Report of Site A/Plot M (Report for 2020)

The Site A/Plot M, Decommissioned Reactor Site was inspected on September 24, 2020. Site A/Plot M is located in the Palos Area Preserves, operated by the Forest Preserve District of Cook County. The site was found to be in good condition with minimal erosional concerns across the grass covered mound at Plot M. Landscaping timbers installed along the footpath north of Plot M is effective in reducing erosion down the hill. Erosion concerns at Plot M are being addressed by Argonne National Laboratory (ANL). The bike trail installed by Cook County Forest Preserve to the east of Plot M has helped reduce traffic at the site. The Plot M monument appears solid with no visible cracks. The Site A monument has several cracks present that will possibly widen over time. No cause for a follow up inspection was identified.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

AmeriFlux US-DUF Denver Urban Field Station

This is the AmeriFlux version of the carbon flux data for the site US-DUF Denver Urban Field Station. Site Description - This site was established on a 25m freestanding former radio tower at the Forest Service's Rocky Mountain Research Station headquarters in Fort Collins, CO. The tower is situated next to a parking lot and several one and two story buildings. To the north and west is the campus of Colorado State University, and to the north and east is low density residential development. To the south and east are a busy intersection and rapid transit bus line, and to the south is green space surrounding the City of Fort Collins' Spring Creek Trail.

Frank, John [US Forest Service, Rocky Mountain Res↗
NASA NTRS2012

Contrasting Patterns of Damage and Recovery in Logged Amazon Forests From Small Footprint LiDAR Data

Tropical forests ecosystems respond dynamically to climate variability and disturbances on time scales of minutes to millennia. To date, our knowledge of disturbance and recovery processes in tropical forests is derived almost exclusively from networks of forest inventory plots. These plots typically sample small areas (less than or equal to 1 ha) in conservation units that are protected from logging and fire. Amazon forests with frequent disturbances from human activity remain under-studied. Ongoing negotiations on REDD+ (Reducing Emissions from Deforestation and Forest Degradation plus enhancing forest carbon stocks) have placed additional emphasis on identifying degraded forests and quantifying changing carbon stocks in both degraded and intact tropical forests. We evaluated patterns of forest disturbance and recovery at four -1000 ha sites in the Brazilian Amazon using small footprint LiDAR data and coincident field measurements. Large area coverage with airborne LiDAR data in 2011-2012 included logged and unmanaged areas in Cotriguacu (Mato Grosso), Fiona do Jamari (Rondonia), and Floresta Estadual do Antimary (Acre), and unmanaged forest within Reserva Ducke (Amazonas). Logging infrastructure (skid trails, log decks, and roads) was identified using LiDAR returns from understory vegetation and validated based on field data. At each logged site, canopy gaps from logging activity and LiDAR metrics of canopy heights were used to quantify differences in forest structure between logged and unlogged areas. Contrasting patterns of harvesting operations and canopy damages at the three logged sites reflect different levels of pre-harvest planning (i.e., informal logging compared to state or national logging concessions), harvest intensity, and site conditions. Finally, we used multi-temporal LiDAR data from two sites, Reserva Ducke (2009, 2012) and Antimary (2010, 2011), to evaluate gap phase dynamics in unmanaged forest areas. The rates and patterns of canopy gap formation at these sites illustrate potential issues for separating logging damages from natural forest disturbances over longer time scales. Multi-temporal airborne LiDAR data and coincident field measurements provide complementary perspectives on disturbance and recovery processes in intact and degraded Amazon forests. Compared to forest inventory plots, the large size of each individual site permitted analyses of landscape-scale processes that would require extremely high investments to study using traditional forest inventory methods.

Morton, D. C.↗
NASA NTRS2016

Meteorite Falls and the Fragmentation of Meteorites

In order to understand the fragmentation of objects entering the atmosphere and why some produce more fragments than others, I have searched the Meteoritical Society database for meteorites greater than 20 kilograms that fell in the USA, China, and India. I also studied the video and film records of 21 fireballs that produced meteorites. A spreadsheet was prepared that noted smell, fireball, explosion, whistling, rumbling, the number of fragments, light, and impact sounds. Falls with large numbers of fragments were examined to look for common traits. These were: the Norton County aubrite, explosion and a flare greater than 100 fragments; the Forest City H5 chondrite explosion, a flare, a dust trail, 505 specimens; the Richardton H5 chondrite explosion and light, 71 specimens; the Juancheng H5 chondrite explosion, a rumbling, a flare, a dust trail,1000 specimens; the Tagish Lake C2 chondrite explosion, flare, dust trail, 500 specimens. I conclude that fragmentation is governed by the following: (1) Bigger meteors undergo more stress which results in more specimens; (2) Harder meteorites also require more force to break them up which will cause greater fragmentation; (3) Force and pressure are directly proportional during falls. General observations made were; (1) Meteorites produce fireballs sooner due to high friction; (2) Meteors tend to explode as well because of high stress; (3) Softer meteorites tend to cause dust trails; (4) Some falls produce light as they fall at high velocity. I am grateful to NASA Ames for this opportunity and Derek Sears, Katie Bryson, and Dan Ostrowski for discussions.

fragmentations↗
NASA NTRS2012

Evaluation of Algorithms for a Miles-in-Trail Decision Support Tool

Four machine learning algorithms were prototyped and evaluated for use in a proposed decision support tool that would assist air traffic managers as they set Miles-in-Trail restrictions. The tool would display probabilities that each possible Miles-in-Trail value should be used in a given situation. The algorithms were evaluated with an expected Miles-in-Trail cost that assumes traffic managers set restrictions based on the tool-suggested probabilities. Basic Support Vector Machine, random forest, and decision tree algorithms were evaluated, as was a softmax regression algorithm that was modified to explicitly reduce the expected Miles-in-Trail cost. The algorithms were evaluated with data from the summer of 2011 for air traffic flows bound to the Newark Liberty International Airport (EWR) over the ARD, PENNS, and SHAFF fixes. The algorithms were provided with 18 input features that describe the weather at EWR, the runway configuration at EWR, the scheduled traffic demand at EWR and the fixes, and other traffic management initiatives in place at EWR. Features describing other traffic management initiatives at EWR and the weather at EWR achieved relatively high information gain scores, indicating that they are the most useful for estimating Miles-in-Trail. In spite of a high variance or over-fitting problem, the decision tree algorithm achieved the lowest expected Miles-in-Trail costs when the algorithms were evaluated using 10-fold cross validation with the summer 2011 data for these air traffic flows.

Bloem, Michael↗
NASA NTRS1977

Volcanism of the Eastern Snake River Plain, Idaho: A comparative planetary geology-guidebook

The Planetary Geology Field Conference on the central Snake River Plain was conceived and developed to accomplish several objectives. Primarily, field conferences are sponsored by the National Aeronautics and Space Administration to draw attention to aspects of terrestrial geology that appear to be important in interpreting the origin and evolution of extraterrestrial planetary surfaces. Another aspect is to present results of recent research in a region. A final objective of this conference is to bring together investigators of diverse backgrounds who share a common interest in the Snake River Plain. The Snake River Plain appears to be similar in surface morphology to many volcanic regions on the Moon, Mars, and possibly Mercury. Therefore, the Snake River Plain, in combination with the relatively good state of preservation, the lack of forests or other heavy vegetation, and the good network of jeep trails, is an area nearly ideal for analog studies.

Greeley, R.↗
NASA NTRS2023

Coronado Ecological Conservation: Assessing Vegetation Change Due to Border Wall Construction and Shifting Social Trails

Species monitoring is essential for mitigating the impacts of plant invasion, such as radical changes in an area’s ecosystem, degraded soil health, increased wildfire severity, landslides, and increased flooding. For this project, NASA DEVELOP partnered with the National Park Service (NPS) to investigate invasive species in disturbed lands: specifically, areas affected by off-trail travel and U.S.-Mexico border construction activities. The team assessed how construction has impacted the distribution of Lehmann’s lovegrass and Russian thistle invasives throughout Coronado National Memorial, AZ from 1986-2022. Using data from Landsat 5 and 8, Sentinel-2, NAIP, and PlanetScope, the team computed NDVI, NDMI, MSAVI2, EVI, and Tasseled Cap Wetness, Brightness, and Greenness transformations as vegetation health indicators to input into various machine learning algorithms. To minimize noise, the team conducted Principal Component Analysis on vegetation indices and spectral bands before running k-means clustering and random forest classification algorithms. Between all datasets, the team found that the median area fully overtaken by invasive plants was 5.37% of the park’s total area in 2022. The NPS will use end products to help increase restoration efforts in disturbed areas with high concentrations of invasive plants, and this project can serve as a jumping off point for future invasive species monitoring. The NPS’s collection of ground data for 2022-2023, in conjunction with future data collection, will notably improve the accuracy of classification models, leading to more precise monitoring of invasive species spread over time.

Coronado National Memorial↗
NASA NTRS2015

Reforestation and Crop Land Conversion Impacts on Future Regional Air Quality in the Southeastern U.S.

Land in the southeastern U.S. is expected to change, e.g., given the potential demand to develop forest-to-fuel technologies or, conversely, cropification of current forests to increase food production. Possible future PM(sub 2.5) and O3 air quality for two land use/land cover change (LULCC) scenarios, reforestation and cropland conversion, are compared to a reference case scenario for the year 2050 using the Weather Research and Forecasting (WRF) and Community Multi-scale Air Quality (CMAQ) models. Changes in air quality driven by changes in climate, deposition and emissions relating to the LULCC are investigated. Reforestation in the Southeast tends to decrease the ambient O3mixing ratio while slightly increasing summertime PM(sub 2.5) in the Southeastern U.S. Results of a climate and deposition (CD) sensitivity simulation are provided for the two alternative LULCC scenarios to isolate the impact of changing climate and deposition on PM(sub 2.5) and O3 air quality. The sensitivity results indicate that deposition and emissions changes associated with reforestation impact O3 and PM(sub 2.5concentrations as much as, and in most cases more than, changes in meteorology. Conversion of forest to cropland in the Southeast, on the other hand, tends to increase O3and increase PM(sub 2.5) year-round. Cropland conversion leads to increased NOX emissions and increases in the 4th highest maximum daily 8-h O3(MDA8) of the year by up to 10 ppb despite the tendency for increased deposition and decreased temperature to reduce the MDA8 mixing ratio. The results of this study show that O3and aerosol concentrations are sensitive to reforestation and cropland conversion in the Southeast and these land use changes should be considered in air quality management plans. Further, they show the sensitivity of such calculations to land cover properties.

deposition↗
NASA NTRS1977

Sports and Recreation

Among a number of solar energy tests being jointly conducted by NASA's Lewis Research Center and the Energy Research and Development Administration are a sun-powered refrigerator and a back-pack mounted power supply for radios. Both use solar cells, spacecraft power sources which convert sun energy into electricity. The refrigerator, which has potential utility for outdoor campers, is in operation at a trail construction camp in Isle Royale National Park, a remote wilderness in Michigan's Lake Superior where electricity is available only at park headquarters. Trail maintenance crews working in the back country get food supplies only once weekly; with refrigeration they can enjoy a more varied and nutritious diet. Solar cells provide power to run the refrigerator and to charge its batteries for an alternate power supply when sun is not available. At the request of Znyo National Forest personnel NASA-Lewis also developed a back-pack system. The lightweight solar cell pack (on the pack strap in photo) charges batteries for portable two-way radios used by trailguards, who are on patrol for as much as two weeks at a time. Guards want continuous communication with the District Station, but battery capacity precludes such operation. With the solar cell power supply, guards can use their radios 24 hours a day.A lightweight, higher-capacity oxygen bottle-derived from rocket propellant tank technology-proved an important aid in the 1976 ascent to the summit of Mt. Everest by members of the. American Bicentennial Everest Expedition.

Source record↗
NASA NTRSDate not supplied

Coronado Ecological Conservation: Assessing Vegetation Change Due to Border Wall Construction and Shifting Social Trails

Species monitoring is essential in mitigating the impacts of plant invasion, such as radical changes in an area’s ecosystem, degraded soil health, increased wildfire severity, landslides, and increased flooding. NASA DEVELOP partnered with the National Park Service (NPS) to investigate invasive species in disturbed lands: specifically, areas affected by off-trail walking and US-Mexico border construction activities. The team assessed how construction has impacted the distribution of Lehmann’s lovegrass and Russian thistle invasives throughout Coronado National Memorial, AZ from 1986 to 2022. Using data from Landsat 5 and 8, Sentinel-2, the National Agriculture Imagery Program, and PlanetScope, the team computed vegetation indices including the Normalized Difference Vegetation Index, Normalized Difference Moisture Index, Modified Soil Adjusted Vegetation Index 2, Enhanced Vegetation Index, and Tasseled Cap Wetness, Brightness, and Greenness transformations as vegetation health indicators to input into various machine learning algorithms. To minimize noise, the team conducted Principal Component Analysis on the vegetation indices and spectral bands before running k-means++ clustering and random forest classification algorithms. Between all datasets, we found the median area fully overtaken by invasive plants was 5.37% of the park’s total area in 2022. The NPS will use the end products to help increase restoration efforts in disturbed areas with high concentrations of invasive plants. The NPS’s collection of ground data for 2022–2023, in conjunction with future data collection, will notably improve the accuracy of classification models, leading to more precise monitoring of invasive spread over time.

Carson Schuetze↗
NASA NTRS2013

Potential Impact of Land Use Change on Future Regional Climate in the Southeastern U.S.: Reforestation and Crop Land Conversion

The impact of future land use and land cover changes (LULCC) on regional and global climate is one of the most challenging aspects of understanding anthropogenic climate change. We study the impacts of LULCC on regional climate in the southeastern U.S. by downscaling the NASA Goddard Institute for Space Studies global climate model E to the regional scale using a spectral nudging technique with the Weather Research and Forecasting Model. Climate-relevant meteorological fields are compared for two southeastern U.S. LULCC scenarios to the current land use/cover for four seasons of the year 2050. In this work it is shown that reforestation of cropland in the southeastern U.S. tends to warm surface air by up to 0.5 K, while replacing forested land with cropland tends to cool the surface air by 0.5 K. Processes leading to this response are investigated and sensitivity analyses conducted. The sensitivity analysis shows that results are most sensitive to changes in albedo and the stomatal resistance. Evaporative cooling of croplands also plays an important role in regional climate. Implications of LULCC on air quality are discussed. Summertime warming associated with reforestation of croplands could increase the production of some secondary pollutants, while a higher boundary layer will decrease pollutant concentrations; wintertime warming may decrease emissions from biomass burning from wood stoves

Regional climate change↗
DOE OSTI2023

Range wide genetic differentiation in the bull kelp Nereocystis luetkeana with a seascape genetic focus on the Salish Sea

Introduction: In temperate regions, one of the most critical determinants of present range-wide genetic diversity was the Pleistocene climate oscillations, the most recent one created by the last glacial maximum (LGM). This study aimed to describe N. luetkeana genetic structure across its entire range (Alaska to California) and test different models of population connectivity within the Salish Sea. This region was colonized after the LGM and has been under increased disturbance in recent decades. Methods: We utilized microsatellite markers to study N. luetkeana genetic diversity at 53 sites across its range. Using higher sampling density in the Salish Sea, we employed a seascape genetics approach and tested isolation by hydrodynamic transport and environment models. Results: At the species distribution scale, we found four main groups of genetic co-ancestry, Alaska; Washington with Vancouver Island’s outer coast and Juan de Fuca Strait; Washington’s inner Salish Sea; and Oregon with California. The highest allelic richness (AR) levels were found in California, near the trailing range edge, although AR was also high in Alaska. The inner Salish Sea region had the poorest diversity across the species distribution. Nevertheless, a pattern of isolation by hydrodynamic transport and environment was supported in this region. Discussion: The levels of allelic, private allele richness and genetic differentiation suggest that during the LGM, bull kelp had both northern and southern glacial refugia in the Prince of Wales Island-Haida Gwaii region and Central California, respectively. Genetic diversity in Northern California sites seems resilient to recent disturbances, whereas the low levels of genetic diversity in the inner Salish Sea are concerning.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Climatology of Linear Mesoscale Convective System Morphology in the United States based on Random Forests Method

This study uses machine learning methods, specifically the random forest (RF), on a radar-based mesoscale convective system (MCS) tracking dataset to classify the five types of linear MCS morphology in the contiguous United States during the period 2004-2016. The algorithm is trained using radar- and satellite-derived spatial and morphological parameters, and reanalysis environmental information from 5-26yr manually identified nonlinear and five linear MCS modes. The algorithm is then used to automate the classification of linear MCSs over 8 years with high accuracy, providing a systematic, long-term climatology of linear MCSs. Results reveal that nearly 40% of MCSs are classified as linear MCSs, in which half of the linear events belong to the type of system having a leading convective line. The occurrence of linear MCSs shows large annual and seasonal variations. On average, 113 linear MCSs occur annually during the warm season (through March to October), with most of these events clustered from May through August in the central eastern Great Plains. MCS characteristics, including duration, propagation speed, orientation, and system cloud size, have large variability among the different linear modes. The systems having a trailing convective line and the systems having a back-building area of convection typically move more slowly and have higher precipitation rate, and thus have higher potential in producing extreme rainfall and flash flooding. Analysis of the environmental conditions associated with linear MCSs show that the storm-relative flow is of most importance in determining the organization mode of linear MCSs.

Cui, Wenjun↗