AIMC Topic: Satellite Imagery
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Improved early-stage crop classification using a novel fusion-based machine learning approach with Sentinel-2A and Landsat 8-9 data.
Environmental monitoring and assessment
Aug 6, 2025
Crop classification during the early stages is challenging because of the striking similarity in spectral and texture features among various crops. To improve classification accuracy, this study proposes a novel fusion-based deep learning approach. T...
Mangrove species classification using a proposed ensemble U-Net model and Planet satellite imagery: A case study in Ngoc Hien district, Ca Mau province, Vietnam.
PloS one
Aug 6, 2025
Land cover and plant species identification using satellite images and deep learning approaches have recently been a widely addressed area of research. However, mangroves, a specific species that have significantly declined in quantity and quality wo...
The First Seasonal Green View Index Mapping Dataset across Chinese cities powered by deep learning.
Scientific data
Aug 5, 2025
Multi-temporal mapping of the Green View Index (GVI) is crucial for understanding how urban residents perceive seasonal changes in streetscape greenness. Compared to street view imagery (SVI), remote sensing data offers higher temporal frequency and ...
Prevalence, associated risk factors and satellite imagery analysis in predicting soil-transmitted helminth infection in Nakhon Si Thammarat Province, Thailand.
Scientific reports
Aug 4, 2025
Soil-transmitted helminth (STH) infections remain a significant public health concern in rural areas, often leading to nutritional and physical impairment, particularly in children. This study aimed to assess the prevalence and associated factors of ...
Advanced spatiotemporal downscaling of MODIS land surface temperature: utilizing Sentinel-1 and Sentinel-2 data with machine learning technique in Qazvin Province, Iran.
Environmental monitoring and assessment
Jul 23, 2025
This study presents a spatiotemporal downscaling framework for MODIS land surface temperature (LST) using Sentinel-1 and Sentinel-2 data with machine learning techniques on the Google Earth Engine (GEE) platform. Random Forest regression was applied ...
Modeling water quality in the brazilian semiarid region using remote sensing: support for water management.
Environmental monitoring and assessment
Jul 10, 2025
Water management in semi-arid regions faces challenges due to water scarcity and the need for continuous quality monitoring. This study evaluates the use of remote sensing to analyze a reservoir's water quality status in Brazil's semi-arid region to ...
Fusing satellite imagery and ground-based observations for PM air pollution modeling in Iran using a deep learning approach.
Scientific reports
Jul 1, 2025
With the rapid advancement of urbanization and industrialization in cities, air pollution has become one of the significant environmental challenges and issues in many countries. The concentration of particulate matter with an aerodynamic diameter of...
Unsupervised deep clustering of high-resolution satellite imagery reveals phenotypes of urban development in Sub-Saharan Africa.
The Science of the total environment
Jun 5, 2025
Sub-Saharan Africa and other developing regions have urbanized extensively, leading to complex urban features with varying presence and types of roads, buildings and vegetation. We use a novel hierarchical deep learning framework and high-resolution ...
Global dominance of seasonality in shaping lake-surface-extent dynamics.
Nature
May 28, 2025
Lakes are crucial for ecosystems, greenhouse gas emissions and water resources, yet their surface-extent dynamics, particularly seasonality, remain poorly understood at continental to global scales owing to limitations in satellite observations. Alth...
Satellite data to support air quality assessment and management.
Journal of the Air & Waste Management Association (1995)
May 28, 2025
Satellite data have long been recognized as valuable for air quality applications. These applications are in a stage of rapid growth: new geostationary satellites provide hourly or sub-hourly data; improvements in algorithms convert measured waveleng...
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