[PDF][PDF] Applications of Machine Learning and Remote Sensing in Soil and Water Conservation
The application of machine learning (ML) and remote sensing (RS) in soil and water
conservation has become a powerful tool. As analytical tools continue to advance, the …
conservation has become a powerful tool. As analytical tools continue to advance, the …
[HTML][HTML] Explainable machine learning-based fractional vegetation cover inversion and performance optimization–a case study of an alpine grassland on the Qinghai …
X Li, J Chen, Z Chen, Y Lan, M Ling, Q Huang, H Li… - Ecological …, 2024 - Elsevier
Abstract Fractional Vegetation Cover (FVC) serves as a crucial indicator in ecological
sustainability and climate change monitoring. While machine learning is the primary method …
sustainability and climate change monitoring. While machine learning is the primary method …
IRIME: Mitigating exploitation-exploration imbalance in RIME optimization for feature selection
J Huang, Y Chen, AA Heidari, L Liu, H Chen, G Liang - Iscience, 2024 - cell.com
Rime optimization algorithm (RIME) encounters issues such as an imbalance between
exploitation and exploration, susceptibility to local optima, and low convergence accuracy …
exploitation and exploration, susceptibility to local optima, and low convergence accuracy …
[HTML][HTML] Application of Getis-Ord Correlation Index (Gi) for Burned Area Detection Improvement in Mediterranean Ecosystems (Southern Italy and Sardinia) Using …
This study collects the results obtained using the Getis-Ord local spatial autocorrelation
index (Gi) with the aim of improving the classification of burned area detection maps …
index (Gi) with the aim of improving the classification of burned area detection maps …
[HTML][HTML] Underutilized Feature Extraction Methods for Burn Severity Mapping: A Comprehensive Evaluation
L Nguyen Van, G Lee - Remote Sensing, 2024 - mdpi.com
Wildfires increasingly threaten ecosystems and infrastructure, making accurate burn severity
mapping (BSM) essential for effective disaster response and environmental management …
mapping (BSM) essential for effective disaster response and environmental management …
[HTML][HTML] Segmentation of Any Fire Event (SAFE): A Rapid and High-Precision Approach for Burned Area Extraction Using Sentinel-2 Imagery
S Liu, Y Xue, H Chen, Y Chen, T Zhan - Remote Sensing, 2024 - mdpi.com
The timely and accurate monitoring of wildfires and other sudden natural disasters is crucial
for safeguarding the safety of residents and their property. Satellite imagery for wildfire …
for safeguarding the safety of residents and their property. Satellite imagery for wildfire …
Global Lightning-Ignited Wildfires Prediction and Climate Change Projections based on Explainable Machine Learning Models
Wildfires pose a significant natural disaster risk to populations and contribute to accelerated
climate change. As wildfires are also affected by climate change, extreme wildfires are …
climate change. As wildfires are also affected by climate change, extreme wildfires are …