The state of the art in deep learning applications, challenges, and future prospects: A comprehensive review of flood forecasting and management
Floods are a devastating natural calamity that may seriously harm both infrastructure and
people. Accurate flood forecasts and control are essential to lessen these effects and …
people. Accurate flood forecasts and control are essential to lessen these effects and …
A brief review of machine learning algorithms in forest fires science
Due to the harm forest fires cause to the environment and the economy as they occur more
frequently around the world, early fire prediction and detection are necessary. To anticipate …
frequently around the world, early fire prediction and detection are necessary. To anticipate …
[HTML][HTML] What is going on within google earth engine? A systematic review and meta-analysis
P Pérez-Cutillas, A Pérez-Navarro… - … Society and environment, 2023 - Elsevier
Abstract Google Earth Engine (GEE) is a geospatial processing platform based on geo-
information applications in the 'cloud'. This platform provides free access to huge volumes of …
information applications in the 'cloud'. This platform provides free access to huge volumes of …
A google earth engine algorithm to map phenological metrics in mountain areas worldwide with landsat collection and sentinel-2
Google Earth Engine has deeply changed the way in which Earth observation data are
processed, allowing the analysis of wide areas in a faster and more efficient way than ever …
processed, allowing the analysis of wide areas in a faster and more efficient way than ever …
Enhancing land cover mapping and monitoring: An interactive and explainable machine learning approach using Google Earth Engine
Artificial intelligence (AI) and machine learning (ML) have been applied to solve various
remote sensing problems. To fully leverage the power of AI and ML to tackle impactful …
remote sensing problems. To fully leverage the power of AI and ML to tackle impactful …
AI-enabled strategies for climate change adaptation: protecting communities, infrastructure, and businesses from the impacts of climate change
Climate change is one of the most pressing global challenges we face today. The impacts of
rising temperatures, sea levels, and extreme weather events are already being felt around …
rising temperatures, sea levels, and extreme weather events are already being felt around …
Machine learning algorithms for satellite image classification using Google Earth Engine and Landsat satellite data: Morocco case study
Earth observation data have proven to be a valuable resource of quantitative information
that is more consistent in time and space than traditional land-based surveys. Remote …
that is more consistent in time and space than traditional land-based surveys. Remote …
Synergistic use of earth observation driven techniques to support the implementation of water framework directive in europe: a review
The development of a sustainable water quality monitoring system at national scale remains
a big challenge until today, acting as a hindrance for the efficient implementation of the …
a big challenge until today, acting as a hindrance for the efficient implementation of the …
Coastal wetland vegetation classification using pixel-based, object-based and deep learning methods based on RGB-UAV
JY Zheng, YY Hao, YC Wang, SQ Zhou, WB Wu… - Land, 2022 - mdpi.com
The advancement of deep learning (DL) technology and Unmanned Aerial Vehicles (UAV)
remote sensing has made it feasible to monitor coastal wetlands efficiently and precisely …
remote sensing has made it feasible to monitor coastal wetlands efficiently and precisely …
Remote sensing of diverse urban environments: From the single city to multiple cities
Remote sensing of urban environments has unveiled a significant shift from single-city
investigations to the inclusion of multiple cities. Originated from the ideas of the Remote …
investigations to the inclusion of multiple cities. Originated from the ideas of the Remote …