AIMC Topic: Remote Sensing Technology

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Segmentation of plateau zokor mounds in alpine meadows from UAV images using an improved UNet network.

Scientific reports
Plateau zokor mounds, created by the burrowing activity of Plateau zokor, cause significant damage to crops, grasslands, and infrastructure, particularly in the alpine meadows of the Tibetan Plateau. Traditional field surveys are inefficient and labo...

From sample to sonde to Sentinel-2: insights from a multi-scale chlorophyll-a monitoring effort in the Hudson River, New York.

Environmental monitoring and assessment
Monitoring cyanobacteria and other nuisance phytoplankton in the Hudson River is of great interest given its societal and ecological importance. Satellite remote sensing provides a cost-effective method to monitor chlorophyll-a (chl-a), a common prox...

Building extraction from remote sensing imagery using SegFormer with post-processing optimization.

PloS one
Traditional methods for building extraction from remote sensing images rely on feature classification techniques, which often suffer from high usage thresholds, cumbersome data processing, slow recognition speeds, and poor adaptability. With the rapi...

A new approach improving koala habitat prediction using hyperspectral airborne imagery.

The Science of the total environment
Koala populations are declining primarily due to habitat loss, making large-scale habitat quality prediction essential for conservation. A first approach to defining koala habitat quality involves identifying the number of different 'koala' trees spe...

D2FLS-Net: Dual-Stage DEM-guided Fusion Transformer for landslide segmentation.

PloS one
Landslide segmentation from remote sensing imagery is crucial for rapid disaster assessment and risk mitigation. Owing to the pronounced heterogeneity of landslide scales and the subtle visual contrast between some landslide bodies and their backgrou...

Dataset of High-Resolution Aerial Images for Intertidal Macroalgae.

Scientific data
Macroalgae play a key role in the structure of benthic communities and provide essential ecological services; their responsiveness to stress positions them as indicators of ecosystem health. Traditional manual monitoring methods are resource-demandin...

A lightweight improved YOLOv8 method for intelligent detection of pine wilt disease.

Scientific reports
Pine wood nematode disease (PWD) is one of the most devastating forest diseases worldwide, often described as the "cancer" of pine trees due to its rapid and large-scale lethality. Early and accurate detection of infected trees is essential for inter...

A hybrid ACO-random forest optimization framework for scalable microalgae biomass estimation using multispectral imaging.

Environmental monitoring and assessment
Accurate estimation of algal biomass is essential for monitoring ecosystem productivity, managing aquaculture systems, and optimizing bioresource applications. However, traditional in situ methods are labor-intensive and spatially limited, while remo...

An Integrated Machine Learning and Remote Sensing Method for Predicting Cyanobacterial Blooms: A Case Study in China's lakes along a large-scale water diversion project.

Environmental management
Cyanobacterial blooms in lakes are a complex and challenging environmental issue worldwide. However, many existing studies on cyanobacterial bloom prediction were constrained by limited data availability, which poses significant challenges to the dev...

Four decades of satellite observations reveal climate-driven shifts and spatial heterogeneity in shallow lake Chlorophyll-a dynamics.

Water research
Shallow lakes worldwide face escalating pressures from eutrophication and climate change, yet comprehensive monitoring of Chlorophyll-a (Chl-a) spatiotemporal dynamics remains challenging due to the high costs and logistical constraints of traditiona...