Using artificial intelligence and data fusion for environmental monitoring: A review and future perspectives
Analyzing satellite images and remote sensing (RS) data using artificial intelligence (AI)
tools and data fusion strategies has recently opened new perspectives for environmental …
tools and data fusion strategies has recently opened new perspectives for environmental …
Mapping local climate zones for cities: A large review
The local climate zone (LCZ) system provides a universal classification mechanism for
urban and natural landscapes and plays an increasingly important role in urban climate …
urban and natural landscapes and plays an increasingly important role in urban climate …
[HTML][HTML] A global map of Local Climate Zones to support earth system modelling and urban scale environmental science
There is a scientific consensus on the need for spatially detailed information on urban
landscapes at a global scale. These data can support a range of environmental services …
landscapes at a global scale. These data can support a range of environmental services …
Land use and land cover classification with hyperspectral data: A comprehensive review of methods, challenges and future directions
MA Moharram, DM Sundaram - Neurocomputing, 2023 - Elsevier
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 …
DKDFN: Domain knowledge-guided deep collaborative fusion network for multimodal unitemporal remote sensing land cover classification
Land use and land cover maps provide fundamental information that has been used in
different types of studies, ranging from public health to carbon cycling. However, the existing …
different types of studies, ranging from public health to carbon cycling. However, the existing …
[HTML][HTML] Comparing deep neural networks, ensemble classifiers, and support vector machine algorithms for object-based urban land use/land cover classification
With the advent of high-spatial resolution (HSR) satellite imagery, urban land use/land cover
(LULC) mapping has become one of the most popular applications in remote sensing. Due …
(LULC) mapping has become one of the most popular applications in remote sensing. Due …
[HTML][HTML] A review of landcover classification with very-high resolution remotely sensed optical images—Analysis unit, model scalability and transferability
As an important application in remote sensing, landcover classification remains one of the
most challenging tasks in very-high-resolution (VHR) image analysis. As the rapidly …
most challenging tasks in very-high-resolution (VHR) image analysis. As the rapidly …
Exploring multiscale object-based convolutional neural network (multi-OCNN) for remote sensing image classification at high spatial resolution
Abstract Convolutional Neural Network (CNN) has been increasingly used for land cover
mapping of remotely sensed imagery. However, large-area classification using traditional …
mapping of remotely sensed imagery. However, large-area classification using traditional …
Self-supervised SAR-optical data fusion of Sentinel-1/-2 images
Y Chen, L Bruzzone - IEEE Transactions on Geoscience and …, 2021 - ieeexplore.ieee.org
The effective combination of the complementary information provided by huge amount of
unlabeled multisensor data (eg, synthetic aperture radar (SAR) and optical images) is a …
unlabeled multisensor data (eg, synthetic aperture radar (SAR) and optical images) is a …
[HTML][HTML] Polarimetric imaging via deep learning: A review
Polarization can provide information largely uncorrelated with the spectrum and intensity.
Therefore, polarimetric imaging (PI) techniques have significant advantages in many fields …
Therefore, polarimetric imaging (PI) techniques have significant advantages in many fields …