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ISBDD Model for Classification of Hyperspectral Remote Sensing Imagery. [PDF]
Sensors (Basel), 2018 The diverse density (DD) algorithm was proposed to handle the problem of low classification accuracy when training samples contain interference such as mixed pixels. The DD algorithm can learn a feature vector from training bags, which comprise instances (pixels).
Li N +6 more
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Potential Assessment of PRISMA Hyperspectral Imagery for Remote Sensing Applications
Remote Sensing, 2023 Hyperspectral imagery plays a vital role in precision agriculture, forestry, environment, and geological applications. Over the past decade, extensive research has been carried out in the field of hyperspectral remote sensing.
Riyaaz Uddien Shaik +2 more
doaj +2 more sources
Anomaly Detection from Hyperspectral Remote Sensing Imagery [PDF]
Geosciences, 2016 Hyperspectral remote sensing imagery contains much more information in the spectral domain than does multispectral imagery. The consecutive and abundant spectral signals provide a great potential for classification and anomaly detection.
Qiandong Guo, Ruiliang Pu, Jun Cheng
doaj +3 more sources
Research and application of UAV-based hyperspectral remote sensing for smart city construction
Cognitive Robotics, 2022 Hyperspectral remote sensing has been an important technical means to obtain more refined information and provide rich, accurate, and reasonable data for the quantitative analysis and delicacy management of a ''smart city''.
Boxiong Yang +6 more
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Data in Brief, 2023 Maintaining rich biodiversity and being a habitat and resource for humans, tropical forests are one of the most important global biomes. These forest ecosystems have been experiencing a host of unregulated anthropogenic activities including illegal ...
C.B. Rajesh +4 more
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HYPERSPECTRAL TRANSFORMATION FROM EO-1 ALI IMAGERY USING PSEUDO-HYPERSPECTRAL IMAGE SYNTHESIS ALGORITHM [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2016 Hyperspectral remote sensing is more effective than multispectral remote sensing in many application fields because of having hundreds of observation bands with high spectral resolution.
N. T. Hoang, N. T. Hoang, K. Koike
doaj +1 more source
Living up to the Hype of Hyperspectral Aquatic Remote Sensing: Science, Resources and Outlook
Frontiers in Environmental Science, 2021 Intensifying pressure on global aquatic resources and services due to population growth and climate change is inspiring new surveying technologies to provide science-based information in support of management and policy strategies.
Heidi M. Dierssen +6 more
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Remote Sensing, 2021 The chlorophyll-a (Chl-a) concentration of eutrophic lakes fluctuates significantly due to the disturbance of wind and anthropogenic activities on the water body. Consequently, estimation of the Chl-a concentration has become an immense challenge. Due to
Runfei Zhang +10 more
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A COMPARISON OF LIDAR REFLECTANCE AND RADIOMETRICALLY CALIBRATED HYPERSPECTRAL IMAGERY [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2016 In order to retrieve results comparable under different flight parameters and among different flight campaigns, passive remote sensing data such as hyperspectral imagery need to undergo a radiometric calibration.
A. Roncat +3 more
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Restoration and Calibration of Tilting Hyperspectral Super-Resolution Image
Sensors, 2020 Tilting sampling is a novel sampling mode for achieving a higher resolution of hyperspectral imagery. However, most studies on the tilting image have only focused on a single band, which loses the features of hyperspectral imagery.
Xizhen Zhang +4 more
doaj +1 more source