[HTML][HTML] A dual-branch weakly supervised learning based network for accurate mapping of woody vegetation from remote sensing images

Y Cheng, S Lan, X Fan, T Tjahjadi, S Jin… - International Journal of …, 2023 - Elsevier
Mapping woody vegetation from aerial images is an important task bluein environment
monitoring and management. A few studies have shown that semantic segmentation …

[HTML][HTML] Remotely sensed functional diversity and its association with productivity in a subtropical forest

Z Zheng, B Schmid, Y Zeng, MC Schuman… - Remote Sensing of …, 2023 - Elsevier
Functional diversity is a critical component driving ecosystem functioning. Spatially explicit
data of plant functional traits and diversity are essential for understanding biodiversity effects …

[HTML][HTML] Comparing Object-Based and Pixel-Based Machine Learning Models for Tree-Cutting Detection with PlanetScope Satellite Images: Exploring Model …

V Nasiri, P Hawryło, P Janiec, J Socha - International Journal of Applied …, 2023 - Elsevier
Despite utilizing various remote sensing datasets, precise tree-cutting detection remains
challenging due to spatial and spectral resolution constraints in satellite imagery, complex …

Evaluating the Potential of Sentinel-2 Time Series Imagery and Machine Learning for Tree Species Classification in a Mountainous Forest

P Liu, C Ren, Z Wang, M Jia, W Yu, H Ren, C Xia - Remote Sensing, 2024 - mdpi.com
Accurate and reliable information on tree species composition and distribution is crucial in
operational and sustainable forest management. Developing a high-precision tree species …

How do conservation policies, climate and socioeconomic changes impact Hyrcanian forests of northern Iran?

V Nasiri, HB Heidarlou, AA Alchin, F Moradi… - Ecological …, 2023 - Elsevier
Sustainable forest management (SFM) practices are required to conserve forest ecosystem
services. International agreements and national management plans have been developed …

Remote sensing applications for mapping large wildfires based on machine learning and time series in northwestern Portugal

SMB dos Santos, SG Duverger, A Bento-Gonçalves… - Fire, 2023 - mdpi.com
Mapping large wildfires (LW) is essential for environmental applications and enhances the
understanding of the dynamics of affected areas. Remote sensing techniques supported by …

[HTML][HTML] Application of Multi-Source Remote Sensing Data and Machine Learning for Surface Soil Moisture Mapping in Temperate Forests of Central Japan

K Win, T Sato, S Tsuyuki - Information, 2024 - mdpi.com
Surface soil moisture (SSM) is a key parameter for land surface hydrological processes. In
recent years, satellite remote sensing images have been widely used for SSM estimation …

[HTML][HTML] Geotechnical characterisation of coal spoil piles using high-resolution optical and multispectral data: A machine learning approach

S Thiruchittampalam, BP Banerjee, NF Glenn… - Engineering …, 2024 - Elsevier
Geotechnical characterisation of spoil piles has traditionally relied on the expertise of field
specialists, which can be both hazardous and time-consuming. Although unmanned aerial …

Airborne Hyperspectral Images and Machine Learning Algorithms for the Identification of Lupine Invasive Species in Natura 2000 Meadows

A Sabat-Tomala, E Raczko, B Zagajewski - Remote Sensing, 2024 - mdpi.com
The mapping of invasive plant species is essential for effective ecosystem control and
planning, especially in protected areas. One of the widespread invasive plants that threatens …

A Review: Tree Species Classification Based on Remote Sensing Data and Classic Deep Learning-Based Methods

L Zhong, Z Dai, P Fang, Y Cao, L Wang - Forests, 2024 - mdpi.com
Timely and accurate information on tree species is of great importance for the sustainable
management of natural resources, forest inventory, biodiversity detection, and carbon stock …