Results 21 to 30 of about 1,605,385 (193)

A COMPARISON OF LIDAR REFLECTANCE AND RADIOMETRICALLY CALIBRATED HYPERSPECTRAL IMAGERY [PDF]

open access: yesThe 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
doaj   +1 more source

Restoration and Calibration of Tilting Hyperspectral Super-Resolution Image

open access: yesSensors, 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

Crops Fine Classification in Airborne Hyperspectral Imagery Based on Multi-Feature Fusion and Deep Learning

open access: yesRemote Sensing, 2021
Hyperspectral imagery has been widely used in precision agriculture due to its rich spectral characteristics. With the rapid development of remote sensing technology, the airborne hyperspectral imagery shows detailed spatial information and temporal ...
Lifei Wei   +7 more
doaj   +1 more source

Gudalur Spectral Target Detection (GST-D): A New Benchmark Dataset and Engineered Material Target Detection in Multi-Platform Remote Sensing Data

open access: yesRemote Sensing, 2020
Target detection in remote sensing imagery, mapping of sparsely distributed materials, has vital applications in defense security and surveillance, mineral exploration, agriculture, environmental monitoring, etc. The detection probability and the quality
Sudhanshu Shekhar Jha   +1 more
doaj   +1 more source

An Improved Atmospheric Correction Algorithm for Hyperspectral Remotely Sensed Imagery [PDF]

open access: yesIEEE Geoscience and Remote Sensing Letters, 2004
There is an increased trend toward quantitative estimation of land surface variables from hyperspectral remote sensing. One challenging issue is retrieving surface reflectance spectra from observed radiance through atmospheric correction, most methods for which are intended to correct water vapor and other absorbing gases.
Liang, Shunlin, Fang, Hongliang
openaire   +1 more source

LAND COVER CHANGE DETECTION BASED ON GENETICALLY FEATURE AELECTION AND IMAGE ALGEBRA USING HYPERION HYPERSPECTRAL IMAGERY [PDF]

open access: yesThe International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2015
The Earth has always been under the influence of population growth and human activities. This process causes the changes in land use. Thus, for optimal management of the use of resources, it is necessary to be aware of these changes.
S. T. Seydi, M. Hasanlou
doaj   +1 more source

Utilization of Hyperspectral Remote Sensing Imagery for Improving Burnt Area Mapping Accuracy [PDF]

open access: yesRemote Sensing, 2021
Wildfires pose a direct threat when occurring close to populated areas. Additionally, their significant carbon and climate feedbacks represent an indirect threat on a global, long-term scale. Monitoring and analyzing wildfires is therefore a crucial task to increase the understanding of interconnections between fire and ecosystems, in order to improve ...
Nolde, Michael   +2 more
openaire   +6 more sources

A Tool for Analysis of Spectral Indices for Remote Sensing of Vegetation and Crops Using Hyperspectral Images

open access: yesEntre Ciencia e Ingeniería, 2019
Food requirements in the world have increased, evidencing the necessity to improve standard techniques of agricultural production. To do so, one option is through technological elements like hyperspectral remote sensing of vegetation and crops.
David Ruiz Hidalgo   +2 more
doaj   +1 more source

Classification of Different Winter Wheat Cultivars on Hyperspectral UAV Imagery

open access: yesApplied Sciences, 2023
Crop phenotype observation techniques via UAV (unmanned aerial vehicle) are necessary to identify different winter wheat cultivars to better realize their future smart productions and satisfy the requirement of smart agriculture.
Xiaoxuan Lyu   +5 more
doaj   +1 more source

Shallow-Guided Transformer for Semantic Segmentation of Hyperspectral Remote Sensing Imagery

open access: yesRemote Sensing, 2023
Convolutional neural networks (CNNs) have achieved great progress in the classification of surface objects with hyperspectral data, but due to the limitations of convolutional operations, CNNs cannot effectively interact with contextual information. Transformer succeeds in solving this problem, and thus has been widely used to classify hyperspectral ...
Yuhan Chen   +4 more
openaire   +2 more sources

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