Results 21 to 30 of about 1,791 (210)

GeoAI: Where machine learning and big data converge in GIScience

Journal of Spatial Information Science, 2020
In this paper GeoAI is introduced as an emergent spatial analytical framework for data-intensive GIScience. As the new fuel of geospatial research, GeoAI leverages recent breakthroughs in machine learning and advanced computing to achieve scalable ...
Wenwen Li
doaj   +1 more source

Data Acquisition and Processing for GeoAI Models to Support Sustainable Agricultural Practices [PDF]

, 2020
There are growing opportunities to leverage new technologies and data sources to address global problems related to sustainability, climate change, and biodiversity loss.
Curry, Edward, García Pereira, Agustín, Ojo, Adegboyega, Porwol, Lukasz   +3 more
core   +3 more sources

GeoAI for Large-Scale Image Analysis and Machine Vision: Recent Progress of Artificial Intelligence in Geography

ISPRS International Journal of Geo-Information, 2022
GeoAI, or geospatial artificial intelligence, has become a trending topic and the frontier for spatial analytics in Geography. Although much progress has been made in exploring the integration of AI and Geography, there is yet no clear definition of ...
Wenwen Li, Chia-Yu Hsu
doaj   +1 more source

Pragmatic GeoAI: Geographic Information as Externalized Practice

KI - Künstliche Intelligenz, 2023
AbstractCurrent artificial intelligence (AI) approaches to handle geographic information (GI) reveal a fatal blindness for the information practices of exactly those sciences whose methodological agendas are taken over with earth-shattering speed. At the same time, there is an apparent inability to remove the human from the loop, despite repeated ...
Simon Scheider, Kai-Florian Richter
openaire   +4 more sources

GeoAI as Collaborative Effort

KI - Künstliche Intelligenz, 2023
Devis Tuia is an Associate Professor at Ecole Polytechnique Fédérale de Lausanne (EPFL), where he heads the Environmental Computational Science and Earth Observation (ECEO) laboratory. Devis is an expert in earth observation and remote sensing research, machine learning, and image processing.
Richter, Kai-Florian, Scheider, Simon, Tuia, Devis   +2 more
openaire   +3 more sources

Current topics and challenges in geoAI

KI - Künstliche Intelligenz, 2023
AbstractTaken literally, geoAI is the use of Artificial Intelligence methods and techniques in solving geo-spatial problems. Similar to AI more generally, geoAI has seen an influx of new (big) data sources and advanced machine learning techniques, but also a shift in the kind of problems under investigation.
Kai-Florian Richter, Simon Scheider
openaire   +3 more sources

A Machine Learning-Based Dynamic SST Index for Long-Lead Malaria Prediction in the Peruvian Amazon. [PDF]

Geohealth
Abstract Malaria imposes a major health burden in the Peruvian Amazon, and its early warning is essential for effective disease prevention. The tropical sea surface temperature (SST) variability, fundamentally shaping the global weather patterns, may also alter malaria transmission and potentially improve its long‐lead predictability. In this study, we
Pan M, Hu S, Janko MM, Zaitchik BF, Takahashi K, Lescano AG, Munayco CV, Pan WK.   +7 more
europepmc   +2 more sources

Emerging trends in geospatial artificial intelligence (geoAI): potential applications for environmental epidemiology

Environmental Health, 2018
Geospatial artificial intelligence (geoAI) is an emerging scientific discipline that combines innovations in spatial science, artificial intelligence methods in machine learning (e.g., deep learning), data mining, and high-performance computing to ...
Trang VoPham, Jaime E. Hart, Francine Laden, Yao-Yi Chiang   +3 more
doaj   +1 more source

SPATIAL MACHINE LEARNING FOR MONITORING TEA LEAVES AND CROP YIELD ESTIMATION USING SENTINEL-2 IMAGERY, (A Case of Gunung Mas Plantation, Bogor) [PDF]

, 2023
Indonesia's tea production and export volume have fluctuated with a downward trend in the last five years, partly due to the increasingly competitive world tea quality.
Manessa, Masita Dwi Mandini, Nuraeni, Dini   +1 more
core   +2 more sources

Short-Term Exposure to Fine Particulate Matter (PM_2.5), Cause Specific-Mortality, and High-Risk Populations: A Nationwide Time-Stratified Case-Crossover Study. [PDF]

Geohealth
Abstract Numerous studies have reported that short‐term exposure to fine particulate matter (PM2.5) is associated with mortality risk; however, results on high‐risk populations and regions have been mixed. This study performed a nationwide time‐stratified case‐crossover study to assess the association between short‐term PM2.5 and mortality in South ...
Ahn S, Oh J, Yun H, Min H, Kim Y, Kang C, An S, Kim A, Kwon D, Park J, Lee W.   +10 more
europepmc   +2 more sources