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Deep Learning Methods for Remote Sensing
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Remote sensing is a field where important physical characteristics of an area are exacted using emitted radiation generally captured by satellite cameras, sensors onboard aerial vehicles, etc. Captured data help researchers develop solutions to sense and detect various characteristics such as forest fires, flooding, changes in urban areas, crop diseases, soil moisture, etc. The recent impressive progress in artificial intelligence (AI) and deep learning has sparked innovations in technologies, algorithms, and approaches and led to results that were unachievable until recently in multiple areas, among them remote sensing. This book consists of sixteen peer-reviewed papers covering new advances in the use of AI for remote sensing.
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Keywords
- aerial images
- AGB
- alternating decision trees
- attention mechanism
- bivariate statistics
- change detection
- changes detection
- channel-separable ResNet
- chimney
- circularly fully convolutional networks
- complex Morlet wavelet
- convolutional networks
- convolutional neural networks
- cross-layer feature fusion
- cultivated land extraction
- deep learning
- deep learning neural network
- deep neural networks
- deep-learning
- disease classification
- DLNN
- DOA estimation
- ensemble learning
- ensemble model
- ensemble models
- Environmental science, engineering & technology
- Erosion
- extreme events
- Faster R-CNN
- feature extraction
- fire classification
- fire segmentation
- flash-flood potential index
- full convolutional network
- fully convolutional feature maps
- fully convolutional network
- fusion
- generative adversarial networks
- geohazard
- Geoinformatics
- geometry structure
- gully erosion susceptibility
- hazard map
- high resolution
- high resolution remote sensing image
- high spatial resolution images
- History of engineering & technology
- image enhancement
- image segmentation
- intelligent prediction
- Machine learning
- mask R-CNN
- meteorological parameters
- multi-scale context
- natural hazard
- network
- NSFs
- object-based
- off-grid
- optical sensors
- outdated building map
- particle swarm optimization
- power transmission lines
- prediction
- PSO
- radar modulation signal
- Rainfall
- Remote sensing
- remote sensing images
- remote sensing sensors
- rural settlements
- scattered vegetation
- space-frequency pseudo-spectrum
- Spatial Analysis
- spatial model
- super-resolution
- target detection
- Technology, engineering, agriculture
- Technology: general issues
- temperature field
- thermophysical parameters
- three-dimensional scene
- time–frequency analysis
- typhoon
- u-net
- UAV
- unmanned aerial vehicle (UAV)
- very high-resolution
- VHR images
- vibration dampers detection
- vision transformers
- wildfire detection
Links
DOI: 10.3390/books978-3-0365-4630-8Editions