AIMC Topic: Remote Sensing Technology
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Soil moisture mapping in Indian tropical islands with C-band SAR and artificial neural network models.
Environmental monitoring and assessment
Jun 17, 2025
This study aims at analyzing the patterns of soil moisture in the South Andaman district using an integrated approach that incorporates Sentinel-1A C-band synthetic aperture radar (SAR) data and other auxiliary data from Sentinel-2A and Landsat 8. A ...
Enhanced wheat yield prediction through integrated climate and satellite data using advanced AI techniques.
Scientific reports
May 24, 2025
Wheat plays a vital role in Pakistan's economy and food security, making accurate yield forecasting essential for planning and resource management. Traditional approaches-such as manual field surveys and remote sensing-have been widely used, but thei...
Remote sensing-based detection of brown spot needle blight: a comprehensive review, and future directions.
PeerJ
May 22, 2025
Pine forests are increasingly threatened by needle diseases, including Brown Spot Needle Blight (BSNB), caused by . BSNB leads to needle loss, reduced growth, significant tree mortality, and disruptions in global timber production. Due to its severit...
Modeling climate change impacts and predicting future vulnerability in the Mount Kenya forest ecosystem using remote sensing and machine learning.
Environmental monitoring and assessment
May 6, 2025
The Mount Kenya forest ecosystem (MKFE), a crucial biodiversity hotspot and one of Kenya's key water towers, is increasingly threatened by climate change, putting its ecological integrity and vital ecosystem services at risk. Understanding the intera...
Improved integrated framework for flooded crop damage and recovery assessment: A multi-source earth observation and participatory mapping in Hadejia, Nigeria.
Journal of environmental management
Apr 30, 2025
Flooding has increasingly significant adverse effects on global food security, and there is a lack of a framework to effectively integrate remote sensing with survey data for accurate damage and recovery assessment. Also, optical satellite images for...
Inversion of lake transparency using remote sensing and deep hybrid recurrent models.
Ecotoxicology and environmental safety
Apr 26, 2025
Utilizing computer technology and remote sensing data, the extraction of water-related features of lakes has become a hot topic in lake ecological research. Addressing challenges like the high optical complexity of lake water bodies, the inadequacy o...
Estimating soil cadmium concentration using multi-source UAV imagery and machine learning techniques.
Environmental monitoring and assessment
Apr 24, 2025
Urbanization and industrialization have led to widespread soil heavy metals contamination, posing significant risks to ecosystems and human health. Conventional methods for mapping heavy metal distribution, which rely on soil sampling followed by che...
Fine extraction of multi-crop planting area based on deep learning with Sentinel- 2 time-series data.
Environmental science and pollution research international
Apr 21, 2025
Accurate and timely access to the spatial distribution of crops is crucial for sustainable agricultural development and food security. However, extracting multi-crop areas based on high-resolution time-series data and deep learning still faces challe...
Maize yield estimation in Northeast China's black soil region using a deep learning model with attention mechanism and remote sensing.
Scientific reports
Apr 15, 2025
Accurate prediction of maize yields is crucial for effective crop management. In this paper, we propose a novel deep learning framework (CNNAtBiGRU) for estimating maize yield, which is applied to typical black soil areas in Northeast China. This fra...
Integrating Proximal and Remote Sensing with Machine Learning for Pasture Biomass Estimation.
Sensors (Basel, Switzerland)
Mar 22, 2025
This study tackles the challenge of accurately estimating pasture biomass by integrating proximal sensing, remote sensing, and machine learning techniques. Field measurements of vegetation height collected using the PaddockTrac ultrasonic sensor were...
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