Optical Remote Sensing
Geological Disaster Recognition on Optical Remote Sensing Images Using Deep Learning
... Phase 3. Feature extraction. Deep learning model is adopted to extract features out of the input optical remote sensing images. Usually, a deep learning model may consist of hidden layers, each of ...
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Automated detection of snow avalanche deposits: segmentation and classification of optical remote sensing imagery
... (VHR) optical remote sensing imagery has the potential to assist in the development of accurate, spatially widespread, detailed maps of zones prone to avalanches as well as to build up data bases of ...
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Deriving Primary Specifications of Optical Remote Sensing Satellite from user Requirements
... The table shows that the orbital time increases with altitude. It can be noted that many altitudes are suitable for a particular repeativity requirement. The inclination increases with the altitude to maintain sun ...
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PhenoFly Planning Tool: flight planning for high-resolution optical remote sensing with unmanned areal systems
... Unmanned areal systems (UAS) are increasingly used as platforms to monitor vegetation by means of optical remote sensing [1, 2]. Recent UAS and sensor technolo- gies allow ground sampling distances ...
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Utility of Microwave and Optical Remote Sensing in Oil Spill Detection in the Mangrove Region of Nigeria
... and optical remote sensing. The result proves that optical remote sensing has the potentials for detecting oil spill on the ...
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Interactive Analyses in Marine Fisheries using Passive Optical Remote Sensing Techniques
... Satellite remote sensing is emerging as a powerful tool in synoptic survey of natural ...of remote sensing methods to examine physical oceanography is becoming increasingly important within ...
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Evaluation of Machine Learning Algorithms for Lake Ice Classification from Optical Remote Sensing Data
... important when studying freeze-up at northern latitudes (Brown and Duguay, 2012). Moreover, traditional threshold-based approaches for cloud detection still face severe challenges over ice-covered areas in the Arctic and ...
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Model based traffic congestion detection in optical remote sensing imagery
... from optical satellites is still limited due to the not sufficiently high spatial resolution, but the detection of vehicle queues seems to be promising ...airborne optical remote sensing ...
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Applicability Study on the Optical Remote Sensing Techniques in a River
... cope with climate change, increase biodiversity and restore species, promoting the accumulation and development of scientific knowledge related to the river environment as a sustainable mid-term and long term task. In ...
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Integrating artificial neural network and classical methods for unsupervised classification of optical remote sensing data
... In those works one algorithm was used as a pre-stage to improve the classification results of another algorithm. That is, the final decision is made according to only one classifier’s decision. Methods involving a ...
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Object detection in optical remote sensing images based on weakly supervised learning and high-level feature learning
... of remote sensing technology has led to the explosive growth of satellite and aerial images in both quantity and ...large-scale optical satellite and aerial image ...
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An Optical Model for the Remote Sensing of Absorption Coefficients of Phytoplankton in Oceanic/Coastal Waters
... the Optical Remote Sensing Changes in the concentration and composition of the water constituents, due to biological, chemical or physical proc- esses, affect light penetration in the water and the ...
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Remote sensing of zooplankton swarms
... finmarchicus and other astaxanthin-rich zooplankton, even at the high abundances observed here. Although the recorded abundances of Calanus spp. are comparatively high, quantifying abundance in the surface layer around ...
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An overview of GNSS remote sensing
... atmospheric remote sensing using LEO satellites such as CHAllenging Minisatellite Payload (CHAMP), Gravity Recovery and Climate Experiment (GRACE) and Constellation Observing System for Meteorology, Iono- ...
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Biological Oceanography by Remote Sensing
... apparent optical properties (IOPs and ...in remote sensing, the important quantities are radiance, irradiance, upwelling (upward) and downwelling (downward) irra- diance, diffuse attenuation ...
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Spectral Imaging for Remote Sensing
... tive sensing concepts, includ- ing energy-efficient techniques for both line-of-sight and non- line-of-sight electro-optical communication and network- ...
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Application of Remote Sensing in Flood
... The advantage of using radar data over the optical data is its ability to penetrate cloud cover and also data acquisition during day and night. Water surfaces are generally smooth at radar wavelengths and can be ...
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Multi-Spectral Ship Detection using Optical, Hyperspectral, and Microwave SAR Remote Sensing for Sustainability of the Coastal Region
... on optical, hyperspectral, and microwave remote ...for optical, hyperspectral, and SAR images for comprehensive coastal management purposes toward perpetual sustainability in the ...
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Remote Sensing: Essentials and Applications
... Remote sensing has become a vital part of the space ...missions. Remote sensing offers services that are useful for ocean monitoring, to detect the harmful contents in environment, to forecast ...
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Image Classification in Remote Sensing
... There are various classification approaches that have been developed and widely used to produce land cover maps (Aplin, Atkinson 2004). They range in logic, from supervised to unsupervised; parametric to non- parametric ...
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