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View article: LandScan HD: a high-resolution gridded ambient population methodology for the world
LandScan HD: a high-resolution gridded ambient population methodology for the world Open
Unwarned population distributions accounting for routine human activities are needed to address many global human security challenges, including disasters, conflict, and infrastructure demand. LandScan High Definition (LSHD) supports this …
View article: LandScan HD: A High-Resolution Gridded Ambient Population Methodology for the World
LandScan HD: A High-Resolution Gridded Ambient Population Methodology for the World Open
Population datasets accounting for the full range of routine human activities are needed to address many global human security challenges, including disasters, conflict, and infrastructure demand. LandScan High Definition (HD) supports thi…
View article: OReole-FM: successes and challenges toward billion-parameter foundation models for high-resolution satellite imagery
OReole-FM: successes and challenges toward billion-parameter foundation models for high-resolution satellite imagery Open
While the pretraining of Foundation Models (FMs) for remote sensing (RS) imagery is on the rise, models remain restricted to a few hundred million parameters. Scaling models to billions of parameters has been shown to yield unprecedented b…
View article: Conditional Experts for Improved Building Damage Assessment Across Satellite Imagery View Angles
Conditional Experts for Improved Building Damage Assessment Across Satellite Imagery View Angles Open
Rapid building damage assessment (BDA) is vital in guiding disaster response missions and estimating population distribution across impacted areas. While commercial satellite imagery providers have enabled near-daily monitoring of the Eart…
View article: Towards Diverse and Representative Global Pretraining Datasets for Remote Sensing Foundation Models
Towards Diverse and Representative Global Pretraining Datasets for Remote Sensing Foundation Models Open
The design of a pretraining dataset is emerging as a critical component for the generality of foundation models. In the remote sensing realm, large volumes of imagery and benchmark datasets exist that can be leveraged to pretrain foundatio…
View article: Deep Learning Scene Classification Experiments in Automatic Detection of Slums on Planetscope Imagery
Deep Learning Scene Classification Experiments in Automatic Detection of Slums on Planetscope Imagery Open
Population growth is increasingly happening in slum settlements of the large urban centers in the Global South. The term "slum" encompasses a wide range of communities, located mostly in underserved areas, and often exhibiting distinct str…
View article: Introducing SpaceNet 9 - Cross-Modal Satellite Imagery Registration for Natural Disaster Responses
Introducing SpaceNet 9 - Cross-Modal Satellite Imagery Registration for Natural Disaster Responses Open
Computer vision algorithms are increasingly leveraged to accelerate geospatial analysis for disaster response and recovery. As the diversity of remote sensing imagery grows with optical, SAR, and other modalities, a perquisite for analytic…
View article: Pretraining Billion-Scale Geospatial Foundational Models on Frontier
Pretraining Billion-Scale Geospatial Foundational Models on Frontier Open
As AI workloads increase in scope, generalization capability becomes challenging for small task-specific models and their demand for large amounts of labeled training samples increases. On the contrary, Foundation Models (FMs) are trained …
View article: Pretraining Billion-scale Geospatial Foundational Models on Frontier
Pretraining Billion-scale Geospatial Foundational Models on Frontier Open
As AI workloads increase in scope, generalization capability becomes challenging for small task-specific models and their demand for large amounts of labeled training samples increases. On the contrary, Foundation Models (FMs) are trained …
View article: A five-year milestone: reflections on advances and limitations in GeoAI research
A five-year milestone: reflections on advances and limitations in GeoAI research Open
The Annual Meeting of the American Association of Geographers (AAG) in 2023 marked a five-year milestone since the first Geospatial Artificial Intelligence (GeoAI) Symposium was held at AAG in 2018. In the past five years, progress has bee…
View article: A Science Gateway for the Repeatable Analysis of Machine Learning Predicted Gravity Anomalies
A Science Gateway for the Repeatable Analysis of Machine Learning Predicted Gravity Anomalies Open
In recent years, deep learning has become an increasingly popular alternative for modeling in geoscience applications due to its scalability and efficiency. However, the interpretability, compute, data volume, and hyperparameter tuning req…
View article: DeepSpeed4Science Initiative: Enabling Large-Scale Scientific Discovery through Sophisticated AI System Technologies
DeepSpeed4Science Initiative: Enabling Large-Scale Scientific Discovery through Sophisticated AI System Technologies Open
In the upcoming decade, deep learning may revolutionize the natural sciences, enhancing our capacity to model and predict natural occurrences. This could herald a new era of scientific exploration, bringing significant advancements across …
View article: Towards Geospatial Knowledge Graph Infused Neuro-Symbolic AI for Remote Sensing Scene Understanding
Towards Geospatial Knowledge Graph Infused Neuro-Symbolic AI for Remote Sensing Scene Understanding Open
Deep learning has proven its effectiveness in numerous tasks for remote sensing scene understanding. However there is an increasing interest to explore fusion of domain-specific background information to the deep neural network to further …
View article: Towards Rapid Response Updates of Populations at Risk
Towards Rapid Response Updates of Populations at Risk Open
Understanding population at risks has been a focus of the LandScan program through its development of population estimates. With advancements in computer vision, deep learning technologies and access to High Performance Computing (HPC) and…
View article: Scaling Automatic Vector Data Alignment to Satellite Imagery
Scaling Automatic Vector Data Alignment to Satellite Imagery Open
Given the tremendous volume of accessible Earth Observation (EO) data, there is a need to develop scalable Geospatial Artificial Intelligence (GeoAI) solutions for time-sensitive applications. Scalability in this context refers to rapidly …
View article: An Agenda for Multimodal Foundation Models for Earth Observation
An Agenda for Multimodal Foundation Models for Earth Observation Open
Archives of remote sensing (RS) data are increasing swiftly as new sensing modalities with enhanced spatiotemporal resolution become operational. While promising new breakthroughs, the sheer volume of RS archives stretches the limits of hu…
View article: Computer Vision for Earth Observation—The First IEEE GRSS Image Analysis and Data Fusion School [Technical Committees]
Computer Vision for Earth Observation—The First IEEE GRSS Image Analysis and Data Fusion School [Technical Committees] Open
Provides society information that may include news, reviews or technical notes that should be of interest to practitioners and researchers.
View article: Analysis-Ready Data and FAIR-AI—Standardization of Research Collaboration and Transparency Across Earth-Observation Communities [Technical Committees]
Analysis-Ready Data and FAIR-AI—Standardization of Research Collaboration and Transparency Across Earth-Observation Communities [Technical Committees] Open
Provides society information that may include news, reviews or technical notes that should be of interest to practitioners and researchers.
View article: GeoAI at ACM SIGSPATIAL: The New Frontier of Geospatial Artificial Intelligence Research
GeoAI at ACM SIGSPATIAL: The New Frontier of Geospatial Artificial Intelligence Research Open
Geospatial Artificial Intelligence (GeoAI) is an interdisciplinary field enjoying tremendous adoption. However, the efficient design and implementation of GeoAI systems face many open challenges. This is mainly due to the lack of non-stand…
View article: Post-Invasion Damage Assessment: Ukraine’s Crop Storage Infrastructure
Post-Invasion Damage Assessment: Ukraine’s Crop Storage Infrastructure Open
The Yale School of Public Health's (YSPH) Humanitarian Research Lab (HRL), working in collaboration with Oak Ridge National Labs (ORNL), concludes with high confidence that approximately 21.5% of Ukraine’s estimated 57 million tonnes of cr…
View article: Model Assumptions and Data Characteristics: Impacts on Domain Adaptation in Building Segmentation
Model Assumptions and Data Characteristics: Impacts on Domain Adaptation in Building Segmentation Open
Studies on domain adaptation (DA) for remote sensing (RS) imagery analysis lack consistency in selection and description of evaluation scenarios. Without properly characterizing datasets, model assumptions, and evaluation scenarios, it is …
View article: 2021 GeoAI Workshop Report: The Trillion Pixel Challenge
2021 GeoAI Workshop Report: The Trillion Pixel Challenge Open
The convergence of geospatial big data with advancements from artificial intelligence, cloud infrastructure, and high-performance computing continues to revolutionize mapping and analysis of Earth's surface in unprecedented detail. Rapid i…
View article: FAIR Interfaces for Geospatial Scientific Data Searches
FAIR Interfaces for Geospatial Scientific Data Searches Open
Several factors must be considered in designing a highly accurate, reliable, scalable, and user-friendly geospatial data search interfaces. This paper examines four critical questions that ought to be considered during design phase: (1) Is…
View article: Proceedings of KDD 2020 Workshop on Data-driven Humanitarian Mapping: Harnessing Human-Machine Intelligence for High-Stake Public Policy and Resilience Planning.
Proceedings of KDD 2020 Workshop on Data-driven Humanitarian Mapping: Harnessing Human-Machine Intelligence for High-Stake Public Policy and Resilience Planning. Open
Humanitarian challenges, including natural disasters, food insecurity, climate change, racial and gender violence, environmental crises, the COVID-19 coronavirus pandemic, human rights violations, and forced displacements, disproportionate…
View article: The New Working Groups of the GRSS Technical Committee on Image Analysis and Data Fusion [Technical Committees]
The New Working Groups of the GRSS Technical Committee on Image Analysis and Data Fusion [Technical Committees] Open
Presents information on the GRSS echnical Committee on Image Analysis and Data Fusion.
View article: Proceedings of KDD 2021 Workshop on Data-driven Humanitarian Mapping: Harnessing Human-Machine Intelligence for High-Stake Public Policy and Resilience Planning
Proceedings of KDD 2021 Workshop on Data-driven Humanitarian Mapping: Harnessing Human-Machine Intelligence for High-Stake Public Policy and Resilience Planning Open
Humanitarian challenges, including natural disasters, food insecurity, climate change, racial and gender violence, environmental crises, the COVID-19 coronavirus pandemic, human rights violations, and forced displacements, disproportionate…
View article: Proceedings of KDD 2021 Workshop on Data-driven Humanitarian Mapping:\n Harnessing Human-Machine Intelligence for High-Stake Public Policy and\n Resilience Planning
Proceedings of KDD 2021 Workshop on Data-driven Humanitarian Mapping:\n Harnessing Human-Machine Intelligence for High-Stake Public Policy and\n Resilience Planning Open
Humanitarian challenges, including natural disasters, food insecurity,\nclimate change, racial and gender violence, environmental crises, the COVID-19\ncoronavirus pandemic, human rights violations, and forced displacements,\ndisproportion…
View article: AI-Driven Data Discovery to Improve Earth System Predictability
AI-Driven Data Discovery to Improve Earth System Predictability Open
Focal Area(s): (3) Insight gleaned from complex data (both observed and simulated) using AI, big data analytics, and other advanced methods, including explainable AI and physics- or knowledge-guided AI.
View article: Semi-automated Design of Artificial Intelligence Earth Systems Models
Semi-automated Design of Artificial Intelligence Earth Systems Models Open
Prediction and observation of water cycles at various scales involve not only patterns isolated in space and time, but also modeling of complex spatio-temporal relationships across multiple domains. For instance, evapotranspiration (ET) an…