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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
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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
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Impervious Surface Information Extraction Based on Hyperspectral Remote Sensing Imagery [PDF]
Remote Sensing, 2017 The retrieval of impervious surface information is a hot topic in remote sensing. However, researches on impervious surface retrieval from hyperspectral remote sensing imagery are rare. This paper illustrates a case study of information extraction from urban impervious surfaces based on hyperspectral remote sensing imagery that is intended to improve ...
Fei Tang, Hanqiu Xu
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Remote Sensing, 2019 The precise classification of crop types is an important basis of agricultural monitoring and crop protection. With the rapid development of unmanned aerial vehicle (UAV) technology, UAV-borne hyperspectral remote sensing imagery with high spatial ...
Lifei Wei +6 more
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Non-Local Sparse Unmixing for Hyperspectral Remote Sensing Imagery
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2014 Sparse unmixing is a promising approach that acts as a semi-supervised unmixing strategy by assuming that the observed image signatures can be expressed in the form of linear combinations of a number of pure spectral signatures that are known in advance.
Ruyi Feng +2 more
exaly +3 more sources
Nonlocal Total Variation Subpixel Mapping for Hyperspectral Remote Sensing Imagery [PDF]
Remote Sensing, 2016 Subpixel mapping is a method of enhancing the spatial resolution of images, which involves dividing a mixed pixel into subpixels and assigning each subpixel to a definite land-cover class. Traditionally, subpixel mapping is based on the assumption of spatial dependence, and the spatial correlation information among pixels and subpixels is considered in
Ruyi Feng +2 more
exaly +4 more sources
Applied Sciences, 2022 Weeds are found on every cropland across the world. Weeds compete for light, water, and nutrients with attractive plants, introduce illnesses or viruses, and attract harmful insects and pests, resulting in yield loss. New weed detection technologies have
Nursyazyla Sulaiman +5 more
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Transparency Estimation of Narrow Rivers by UAV-Borne Hyperspectral Remote Sensing Imagery
IEEE Access, 2020 Urban rivers are often narrow, and general remote sensing data cannot meet the needs of water quality monitoring. In the process of monitoring of river water quality by remote sensing, the spectral and spatial dimension of satellite-borne images cannot ...
Lifei Wei +6 more
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Remote Sensing, 2019 The fine classification of crops is critical for food security and agricultural management. There are many different species of crops, some of which have similar spectral curves.
Lifei Wei +5 more
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Global and Local Real-Time Anomaly Detectors for Hyperspectral Remote Sensing Imagery [PDF]
Remote Sensing, 2015 Anomaly detection has received considerable interest for hyperspectral data exploitation due to its high spectral resolution. A well-known algorithm for hyperspectral anomaly detection is the RX detector. A number of variations have been studied since then, including global and local versions for different type of anomalies.
Yulei Wang, Bin Qi, Chunhui Zhao
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