AIMC Topic: Satellite Imagery
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Review on sea water quality (SWQ) monitoring using satellite remote sensing techniques (SRST).
Marine pollution bulletin
Aug 1, 2025
Due to extensive anthropogenic activities in coastal areas and rivers connected to the seas, effective and timely monitoring the sea water quality (SWQ) is crucial for maintaining ecosystem health. SWQ monitoring involves examining the chemical, phys...
Brick Kiln Dataset for Pakistan's IGP Region Using AI.
Scientific data
May 20, 2025
Brick kilns are a major source of air pollution in Pakistan, with many operating without regulation. A key challenge in Pakistan and across the Indo-Gangetic Plain is the limited air quality monitoring and lack of transparent data on pollution source...
Geospatial artificial intelligence for detection and mapping of small water bodies in satellite imagery.
Environmental monitoring and assessment
May 16, 2025
Remote sensing (RS) data is extensively used in the observation and management of surface water and the detection of water bodies for studying ecological and hydrological processes. Small waterbodies are often neglected because of their tiny presence...
Landslide susceptibility mapping using an entropy index-based negative sample selection strategy: A case study of Luolong county.
PloS one
Jan 1, 2025
Landslides constitute a significant geological hazard in China, particularly in high-altitude regions like the Himalayas, where the challenging environmental conditions impede field surveys. This research utilizes the IOE model to refine non-landslid...
Automated cooling tower detection through deep learning for Legionnaires' disease outbreak investigations: a model development and validation study.
The Lancet. Digital health
Jul 1, 2024
BACKGROUND: Cooling towers containing Legionella spp are a high-risk source of Legionnaires' disease outbreaks. Manually locating cooling towers from aerial imagery during outbreak investigations requires expertise, is labour intensive, and can be pr...
Deep Learning-Based Assessment of Built Environment From Satellite Images and Cardiometabolic Disease Prevalence.
JAMA cardiology
Jun 1, 2024
IMPORTANCE: Built environment plays an important role in development of cardiovascular disease. Large scale, pragmatic evaluation of built environment has been limited owing to scarce data and inconsistent data quality.
Long-term monitoring chlorophyll-a concentration using HJ-1 A/B imagery and machine learning algorithms in typical lakes, a cold semi-arid region.
Optics express
Apr 22, 2024
Chlorophyll a (Chl-a) in lakes serves as an effective marker for assessing algal biomass and the nutritional level of lakes, and its observation is feasible through remote sensing methods. HJ-1 (Huanjing-1) satellite, deployed in 2008, incorporates a...
The new science of volcanoes harnesses AI, satellites and gas sensors to forecast eruptions.
Nature
May 1, 2020
Intelligence in injury prevention: artificial and otherwise.
Injury prevention : journal of the International Society for Child and Adolescent Injury Prevention
Feb 1, 2020
Satellite images and machine learning can identify remote communities to facilitate access to health services.
Journal of the American Medical Informatics Association : JAMIA
Aug 1, 2019
OBJECTIVE: Community health systems operating in remote areas require accurate information about where people live to efficiently provide services across large regions. We sought to determine whether a machine learning analyses of satellite imagery c...
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