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All sources NASA NTRS DOE OSTI

DOE OSTI2024

From Text to Maps: LLM-Driven Extraction and Geotagging of Epidemiological Data

Epidemiological datasets are essential for public health analysis and decision-making, yet they remain scarce and often difficult to compile due to inconsistent data formats, language barriers, and evolving political boundaries. Traditional methods of creating such datasets involve extensive manual effort and are prone to errors in accurate location extraction. To address these challenges, we propose utilizing large language models (LLMs) to automate the extraction and geotagging of epidemiological data from textual documents. Our approach significantly reduces the manual effort required, limiting human intervention to validating a subset of records against text snippets and verifying the geotagging reasoning, as opposed to reviewing multiple entire documents manually to extract, clean, and geotag. Additionally, the LLMs identify information often overlooked by human annotators, further enhancing the dataset’s completeness. Our findings demonstrate that LLMs can be effectively used to semi-automate the extraction and geotagging of epidemiological data, offering several key advantages: (1) comprehensive information extraction with minimal risk of missing critical details; (2) minimal human intervention; (3) higher-resolution data with more precise geotagging; and (4) significantly reduced resource demands compared to traditional methods.

Harrod, Karly↗

DOE OSTI2026

A Public Data Set of Auto-Generated Geotagged PV Site Equipment, Generated via Deep Learning

In this research, we present a data set over 100 photovoltaic (PV) sites in TX, which have been automatically geotagged via a fully autonomous deep learning (DL) pipeline. Specifically, locations of inverters, tracker/fixed tilt rows, batteries, and substations are labeled algorithmically. To ensure high data quality, all systems have been reviewed manually and any deep learning errors have been corrected. This public data set, as well as the open-sourced pipeline used to generate it, is valuable for site planning, modelling, and insurance purposes. Given time and resources, we hope to extend the data set to additional states/regions in the US.

14 SOLAR ENERGY↗

NASA NTRS2009

Flashline Mars Arctic Research Station (FMARS) 2009 Expedition Crew Perspectives

The Flashline Mars Arctic Research Station (FMARS), located on the rim of the Haughton Crater on Devon Island in the Canadian Arctic, is a simulated Mars habitat that provides operational constraints similar to those which will be faced by future human explorers on Mars. In July 2009, a six-member crew inhabited the isolated habitation module and conducted the twelfth FMARS mission. The crew members conducted frequent EVA operations wearing mock space suits to conduct field experiments under realistic Mars-like conditions. Their scientific campaign spanned a wide range of disciplines and included many firsts for Mars analog research. Among these are the first use of a Class IV medical laser during a Mars simulation, helping to relieve crew stress injuries during the mission. Also employed for the first time in a Mars simulation at FMARS, a UAV (Unmanned Aerial Vehicle) was used by the space-suited explorers, aiding them in their search for mineral resources. Sites identified by the UAV were then visited by geologists who conducted physical geologic sampling. For the first time, explorers in spacesuits deployed passive seismic equipment to monitor earthquake activity and characterize the planet's interior. They also conducted the first geophysical electromagnetic survey as analog Mars pioneers to search for water and characterize geological features under the surface. The crew collected hydrated minerals and attempted to produce drinkable water from the rocks. A variety of equipment was field tested as well, including new cameras that automatically geotag photos, data-recording GPS units, a tele-presence rover (operated from Florida), as well as MIT-developed mission planning software. As plans develop to return to the Moon and go on to Mars, analog facilities like FMARS can provide significant benefit to NASA and other organizations as they prepare for robust human space exploration. The authors will present preliminary results from these studies as well as their perspectives on topics including human factors, logistics, EVA operations, and the use of social media throughout the mission.

Cusack, Stacy↗

NASA NTRS2009

Use of Web 2.0 Technologies for Public Outreach on a Simulated Mars Mission

Recent advances in social media and internet communications have revolutionized the ways people interact and disseminate information. Astronauts are already taking advantage of these tools by blogging and tweeting from space, and almost all NASA missions now have presences on the major social networking sites. One priotity for future human explorers on Mars will be communicating their experiences to the people back on Earth. During July 2009, a 6-member crew of volunteers carried out a simulated Mars mission at the Flashline Mars Arctic Research Station (FMARS). The Mars Society built the mock Mars habitat in 2000-01 to help develop key knowledge and inspire the public for human Mars exploration. It is located on Devon island about 1600 km from the North Pole within the Arctic Circle. The structure is situated on the rim of Haughton Crater in an environment geologically and biologically analogous to Mars. Living in a habitat, conducting EVAs wearing spacesuits, and observing communication delays with "Earth,"the crew endured restrictions similar to those that will be faced by future human Mars explorers. Throughout the expedition, crewmembers posted daily blog entries, reports, photos, videos, and updates to their website and social media outlets Twitter, Facebook, YouTube, and Picasa Web Albums. During the sixteen EVAs of thier field science research campaign, FMARS crewmembers collected GPS track information and took geotagged photos using GPS-enabled cameras. They combined their traverse GPS tracks with photo location information into KML/KMZ files that website visitors can view in Google Earth.

Ferrone, Kristine↗

NASA NTRS2015

Dissemination of Earth Remote Sensing Data for Use in the NOAA/NWS Damage Assessment Toolkit

The National Weather Service has developed the Damage Assessment Toolkit (DAT), an application for smartphones and tablets that allows for the collection, geolocation, and aggregation of various damage indicators that are collected during storm surveys. The DAT supports the often labor‐intensive process where meteorologists venture into the storm‐affected area, allowing them to acquire geotagged photos of the observed damage while also assigning estimated EF‐scale categories based upon their observations. Once the data are collected, the DAT infrastructure aggregates the observations into a server that allows other meteorologists to perform quality control and other analysis steps before completing their survey and making the resulting data available to the public. In addition to in‐person observations, Earth remote sensing from operational, polar-orbiting satellites can support the damage assessment process by identifying portions of damage tracks that may be missed due to road limitations, access to private property, or time constraints. Products resulting from change detection techniques can identify damage to vegetation and the land surface, aiding in the survey process. In addition, higher resolution commercial imagery can corroborate ground‐based surveys by examining higher‐resolution commercial imagery. As part of an ongoing collaboration, NASA and NOAA are working to integrate near real‐time Earth remote sensing observations into the NOAA/NWS Damage Assessment Toolkit. This presentation will highlight recent developments in a streamlined approach for disseminating Earth remote sensing data via web mapping services and a new menu interface that has been integrated within the DAT. A review of current and future products will be provided, including products derived from MODIS and VIIRS for preliminary track identification, along with conduits for higher‐resolution Landsat, ASTER, and commercial imagery as they become available. In addition to tornado damage assessments, the team is also investigating the use of near real‐time imagery for identifying hail damage to vegetation, which also results in large swaths of damage, particularly in the central United States during the peak growing season months of June, July, and August. This presentation will present an overview of recent activities, challenges and successes, best practices, and opportunities for future work and collaboration

Molthan, Andrew↗

NASA NTRSDate not supplied

Assessing Alaskan boreal forest landcover affected by climate-wildfire interactions from ground truth surveys and NASA airborne remote sensing

Alaska’s boreal forest is facing unprecedented challenges under rapid climate warming (increasingly severe fires, droughts, pest/disease outbreaks) that may destabilize its function as a global carbon sink. Forests near Fairbanks may be especially vulnerable, impacting air quality and ecosystem services. We combined GT (ground truthing) with Airborne Visible InfraRed Imaging Spectrometer (AVIRIS-NG) images collected by the NASA Arctic-Boreal Vulnerability Experiment (ABoVE) program (2017-2019) to assess landcover change at five recently burned sites (2001-2019) of different fire severities and moisture regimes within 30 miles of Fairbanks. GT included tree seedling counts, understory % cover and >50% leaf canopy color assessment. 36 circular plots (1/30 ha radius) including 6 moderate to severely burned plots were selected across sites. 31 additional sites including 12 burned sites were geotagged in photos. AVIRIS images were processed from 29 spectral bands selected to identify changes in chlorophyll and water content. Images were segmented into natural boundaries (polygons) using ENVI 5.5 software. A spectral library of 8 AVIRIS bands with high between-class/low within-class variation was used in two random forest models to predict vegetation classes (model 1: 12 classes, model 2: 14 classes) in each AVIRIS scene, using 20% of the data as training data. Model 2 classified 20% more polygons overall, but only 42% of GT/geotagged polygons were correctly classified by both models. More forest sites were correctly classified (63%) than open vegetation (32%) or post-fire sites (46%). 50% of aspen forest and post-fire polygons were misclassified as shrubland. GT revealed that post-fire plots supported 134,000 (± 48,000) tree seedlings and saplings ha-1 (0.2 - 4 m height, 64% deciduous) versus 2500 (± 2100) shrubs ha-1 (1-6 m height). > 50% canopy browning was observed in conifer forest (8 plots) with no signs of insect infestation. Canopy herbivory > 50% (leaf miner, leaf beetle) and moose herbivory of tree bark was seen across aspen sites. Our study suggests: 1) low canopy vegetation presents challenges for improved landcover classification, and 2) aspen forest should be differentiated in vegetation maps which would aid in tracking herbivory.

Alaska↗

NASA NTRSDate not supplied

Monocular Horizon Navigation

The Artemis program advances towards operations on the lunar surface, where precise surface localization is a driving need for safety and science. Using the observable horizon as an image landmark allows for estimating the photographer’s position. This work analyzes the application of Perspective-n-Point (PnP) algorithms to this lunar localization problem. Batch simulations using lunar topography display the accuracy and drawbacks of these methods. Monte Carlo techniques show the pipeline’s solutions as measurements provided to a navigation filter. When filtered, these solutions have position errors of 50 meters or better, which is similar to or better than the performance of other methods of surface localization.

optical navigation↗