AIMC Topic: Remote Sensing Technology

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Evaluating contaminated land and the environmental impact of oil spills in the Niger Delta region: a remote sensing-based approach.

Environmental monitoring and assessment
The Niger Delta region of Nigeria is a major oil-producing area which experiences frequent oil spills that severely impacts the local environment and communities. Effective environmental monitoring and management remain inadequate in this area due to...

Water resource assessment in data-scarce hydrological regions based on limited underwater survey points.

Environmental monitoring and assessment
Lake topography, which serves as a crucial basis for water resource monitoring, has been extensively applied in hydrological and geomorphological research. However, monitoring lake dynamics in data-scarce regions remains challenging due to the limite...

Multi-branch and multi-label tree species classification using deep learning for UAV aerial photography and Sentinel remote sensing images.

Scientific reports
The classification and identification of forest tree species is of great value in the study of species diversity and forest monitoring. With the development of emerging technologies, the combination of remote sensing images and deep learning methods ...

A meta-analysis of predictive accuracies and errors of biomass estimation models in Sub-Saharan Africa.

The Science of the total environment
Accurate biomass estimation is essential for forest monitoring, energy planning and carbon accounting in Sub-Saharan Africa (SSA), where destructive sampling is often impractical. Biomass estimation models (BEMs) offer scalable alternatives, but thei...

HWANet: A Haar Wavelet-based Attention Network for remote sensing object detection.

PloS one
Remote sensing object detection (RSOD) is highly challenging due to large variations in object scales. Existing deep learning-based methods still face limitations in addressing this challenge. Specifically, reliance on stride convolutions during down...

Ecological and carcinogenic risk assessment of potentially toxic elements in rangelands and croplands around Lake Junin (Peru): Integrating remote sensing, machine learning, and land cover segmentation.

The Science of the total environment
The Junín Lake basin, a critical high-altitude ecosystem in the central Peruvian Andes, faces severe contamination from potentially toxic elements (PTEs) driven by mining activities, agriculture, and urbanization. This study evaluates the spatial dis...

Aboveground biomass estimation using multimodal remote sensing observations and machine learning in mixed temperate forest.

Scientific reports
Plants sequester carbon in their aboveground components, making aboveground tree biomass a key metric for assessing forest carbon storage. Traditional methods of aboveground biomass (AGB) estimation via Forest Inventory and Analysis (FIA) plots lack ...

Detection of weeds in teff crops using deep learning and UAV imagery for precision herbicide application.

Scientific reports
In Ethiopia, Teff is a vital staple crop, yet its productivity is significantly challenges due to inefficient weed and fertilizer management, threatening food security. Traditional weed control methods rely on manual labor and the indiscriminate appl...

Assessment of plant diversity index in degraded desert grassland using UAV hyperspectral multimodal data and Encoder-CNN.

Scientific reports
The biodiversity function of the desert steppe ecosystem faces many challenges under the pressure of climate change and human activities. Accurate and efficient assessment of plant diversity is critical for guiding desert steppe restoration efforts. ...

EchoMamba: A new Mamba model for fast and efficient hyperspectral image classification.

PloS one
The classification of hyperspectral images (HSI) is an important foundation in the field of remote sensing. Mamba architectures based on state space model (SSM) have shown great potential in the field of HSI processing due to their powerful long-rang...