[HTML][HTML] A review on deep learning in UAV remote sensing

LP Osco, JM Junior, APM Ramos… - International Journal of …, 2021 - Elsevier
Abstract Deep Neural Networks (DNNs) learn representation from data with an impressive
capability, and brought important breakthroughs for processing images, time-series, natural …

A review of machine learning applications in wildfire science and management

P Jain, SCP Coogan, SG Subramanian… - Environmental …, 2020 - cdnsciencepub.com
Artificial intelligence has been applied in wildfire science and management since the 1990s,
with early applications including neural networks and expert systems. Since then, the field …

Convolutional neural network (CNN) with metaheuristic optimization algorithms for landslide susceptibility map** in Icheon, South Korea

WL Hakim, F Rezaie, AS Nur, M Panahi… - Journal of environmental …, 2022 - Elsevier
Landslides are a geological hazard that can pose a serious threat to human health and the
environment of highlands or mountain slopes. Landslide susceptibility map** is an …

[HTML][HTML] Predicting flood susceptibility using LSTM neural networks

Z Fang, Y Wang, L Peng, H Hong - Journal of Hydrology, 2021 - Elsevier
Identifying floods and producing flood susceptibility maps are crucial steps for decision-
makers to prevent and manage disasters. Plenty of studies have used machine learning …

Spatial prediction of groundwater potential map** based on convolutional neural network (CNN) and support vector regression (SVR)

M Panahi, N Sadhasivam, HR Pourghasemi… - Journal of …, 2020 - Elsevier
Freshwater shortages have become much more common globally in recent years. Water
resources that are naturally available beneath the surface are capable of reversing this …

Potential for artificial intelligence (AI) and machine learning (ML) applications in biodiversity conservation, managing forests, and related services in India

KN Shivaprakash, N Swami, S Mysorekar, R Arora… - Sustainability, 2022 - mdpi.com
The recent advancement in data science coupled with the revolution in digital and satellite
technology has improved the potential for artificial intelligence (AI) applications in the …
Y Wang, Z Fang, M Wang, L Peng, H Hong - Computers & Geosciences, 2020 - Elsevier
This paper aims to use recurrent neural networks (RNNs) to perform landslide susceptibility
map** in Yongxin County, China. The two main contributions of this study are summarized …
Save Cite Cited by 243 K Ullah, Y Wang, Z Fang, L Wang, M Rahman - Geoscience Frontiers, 2022 - Elsevier
Multi-hazard susceptibility prediction is an important component of disasters risk
management plan. An effective multi-hazard risk mitigation strategy includes assessing …

Performance evaluation of machine learning methods for forest fire modeling and prediction

BT Pham, A Jaafari, M Avand, N Al-Ansari, T Dinh Du… - Symmetry, 2020 - mdpi.com
Predicting and map** fire susceptibility is a top research priority in fire-prone forests
worldwide. This study evaluates the abilities of the Bayes Network (BN), Naïve Bayes (NB) …