[HTML][HTML] A review on deep learning in UAV remote sensing
Abstract Deep Neural Networks (DNNs) learn representation from data with an impressive
capability, and brought important breakthroughs for processing images, time-series, natural …
capability, and brought important breakthroughs for processing images, time-series, natural …
A systematic review on advancements in remote sensing for assessing and monitoring land use and land cover changes impacts on surface water resources in semi …
This study aimed to provide a systematic overview of the progress made in utilizing remote
sensing for assessing the impacts of land use and land cover (LULC) changes on water …
sensing for assessing the impacts of land use and land cover (LULC) changes on water …
Vision transformers for remote sensing image classification
In this paper, we propose a remote-sensing scene-classification method based on vision
transformers. These types of networks, which are now recognized as state-of-the-art models …
transformers. These types of networks, which are now recognized as state-of-the-art models …
Assessment of land use land cover changes and future predictions using CA-ANN simulation for selangor, Malaysia
Land use land cover (LULC) has altered dramatically because of anthropogenic activities,
particularly in places where climate change and population growth are severe. The …
particularly in places where climate change and population growth are severe. The …
Fire‐Net: A Deep Learning Framework for Active Forest Fire Detection
Forest conservation is crucial for the maintenance of a healthy and thriving ecosystem. The
field of remote sensing (RS) has been integral with the wide adoption of computer vision and …
field of remote sensing (RS) has been integral with the wide adoption of computer vision and …
Spatiotemporal variation in land use land cover in the response to local climate change using multispectral remote sensing data
Climate change is likely to have serious social, economic, and environmental impacts on
farmers whose subsistence depends on nature. Land Use Land Cover (LULC) changes …
farmers whose subsistence depends on nature. Land Use Land Cover (LULC) changes …
Land use and land cover classification with hyperspectral data: A comprehensive review of methods, challenges and future directions
Recently, many efforts have been concentrated on land use land cover (LULC) classification
due to rapid urbanization, environmental pollution, agriculture drought, frequent floods, and …
due to rapid urbanization, environmental pollution, agriculture drought, frequent floods, and …
Land change modeler and CA-Markov chain analysis for land use land cover change using satellite data of Peshawar, Pakistan
Urbanization is a global phenomenon that caused many regions worldwide to face dramatic
Land Use Land Cover (LULC) changes associated with urban sprawl and significant …
Land Use Land Cover (LULC) changes associated with urban sprawl and significant …
Object detection and image segmentation with deep learning on Earth observation data: A review—Part II: Applications
In Earth observation (EO), large-scale land-surface dynamics are traditionally analyzed by
investigating aggregated classes. The increase in data with a very high spatial resolution …
investigating aggregated classes. The increase in data with a very high spatial resolution …
Sensors, features, and machine learning for oil spill detection and monitoring: A review
Remote sensing technologies and machine learning (ML) algorithms play an increasingly
important role in accurate detection and monitoring of oil spill slicks, assisting scientists in …
important role in accurate detection and monitoring of oil spill slicks, assisting scientists in …