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Preprocessing eo-1 hyperion hyperspectral data to support the application of agricultural indexes
2003
IEEE Transactions on Geoscience and Remote Sensing
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His areas of interest have included scene and image modeling, BRDF modeling, hyperspectral data analysis, applications, technology transfer, and commercialization of remote sensing. ...
Applications include coastal zone and inland waters, water resources applications, land surface temperature for applications to soil moisture, and water balance estimation. ...
Dunn (NSW Department of Agriculture ) for their real-time differential GPS unit, J. Angus (CSIRO) for the SPAD meter, D. Graetz (CSIRO) for field equipment. Particular acknowledgment is due to J. ...
doi:10.1109/tgrs.2003.813206
fatcat:p3c3h2tdtneg3g56rkl5pkbrve
EO-1 Hyperion Reflectance Time Series at Calibration and Validation Sites: Stability and Sensitivity to Seasonal Dynamics
2013
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
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This study evaluated Earth Observing 1 (EO-1) Hyperion reflectance time series at established calibration sites to assess the instrument stability and suitability for monitoring vegetation functional parameters ...
Using three vegetated sites instrumented with eddy covariance towers, the Hyperion reflectance time series were evaluated for their ability to determine important variables of ecosystem function. ...
Data Collections and Processing 1) EO-1 Hyperion Time Series Collection: The Hyperion image collection in the 2001-2011 timeframe over the study sites is comprised of more than 350 images with varying ...
doi:10.1109/jstars.2013.2246139
fatcat:5deemcu2fvaxtl6hj2si6w4fsa
Accuracies Achieved in Classifying Five Leading World Crop Types and their Growth Stages Using Optimal Earth Observing-1 Hyperion Hyperspectral Narrowbands on Google Earth Engine
2018
Remote Sensing
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The study was conducted in seven agroecological zones of the United States using 99 Earth Observing-1 (EO-1) Hyperion hyperspectral images from 2008–2015 at 30 m resolution. ...
This resulted in the establishment of 30 optimal hyperspectral narrowbands (OHNBs) for the study of agricultural crops. The rest of the 242 Hyperion HNBs were redundant, uncalibrated, or noisy. ...
Additionally, we thank the internal reviewers at the USGS for providing feedback that has much strengthened the manuscript. ...
doi:10.3390/rs10122027
fatcat:errtobjcunbhpeuwdgwveysxca
Tracking the Seasonal Dynamics of Boreal Forest Photosynthesis Using EO-1 Hyperion Reflectance: Sensitivity to Structural and Illumination Effects
2016
IEEE Transactions on Geoscience and Remote Sensing
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To better understand the connection between the two structural levels, we used four narrowband vegetation indices (VIs) derived from Hyperion imagery to track the seasonal dynamics of boreal forest stands ...
Linking canopy-level spectral reflectance to leaf-level processes for monitoring forest seasonal physiology using satellite images is hindered by view and illumination effects and variations in canopy ...
The Hyperion EO-1 data were available courtesy of the U.S. Geological Survey. ...
doi:10.1109/tgrs.2016.2554466
fatcat:pzozokvkx5dtrkehzxauky5j7m
Detection of chlorophyll and leaf area index dynamics from sub-weekly hyperspectral imagery
2016
Remote Sensing for Agriculture, Ecosystems, and Hydrology XVIII
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In this study, a dense timeseries of images were acquired from the Earth Observing-1 (EO-1) Hyperion sensor over an intensive farming area in the center of Saudi Arabia. ...
The study advocates the benefits associated with the availability of optimum spectral and temporal resolution spaceborne observations for agricultural management purposes. ...
ACKNOWLEDGEMENTS Research reported in this publication was supported by the King Abdullah University of Science and Technology (KAUST). ...
doi:10.1117/12.2241345
fatcat:txcr6i4uurfwtfmibybjdzrqqq
Remote sensing of crop residue cover and soil tillage intensity
2006
Soil & Tillage Research
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Landsat Thematic Mapper (TM) and EO-1 Hyperion imaging spectrometer data were acquired over agricultural fields in central Iowa in May and June 2004. ...
Coefficients of determination (r 2 ) for crop residue cover as a function of CAI were 0.85 for the May and 0.77 for the June Hyperion data. ...
Our objectives were: (1) to evaluate several spectral indices for estimating crop residue cover using the Landsat TM and Hyperion imaging spectrometer data over an agricultural region and (2) to classify ...
doi:10.1016/j.still.2005.11.013
fatcat:oqohj6de4jdjdphao4fxtnzlgq
Remote Sensing Applications in Sugarcane Cultivation: A Review
2021
Remote Sensing
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Those difficulties relate mainly to the often (i) time consuming pre-processing of optical time series to cope with atmospheric perturbations and cloud coverage, (ii) the still important lack of analysis-ready-data ...
1981 to 2020, (ii) discussed key strengths and weaknesses of remote sensing approaches in the sugarcane context, and (iii) described the challenges and opportunities for future earth observation (EO)- ...
Conflicts of Interest: The authors declare no conflict of interest. ...
doi:10.3390/rs13204040
fatcat:dfpsctv7yzgjzogww7u56hejt4
Survey of Hyperspectral Earth Observation Applications from Space in the Sentinel-2 Context
2018
Remote Sensing
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Hyperion (EO-1 platform) was first launched in 2000 and recorded data with a 30-m GSD and 400-2500 nm as the spectral range ( Figure 1 ). ...
, sensor cost, data volume and associated data processing cost and time [10] . ...
[110] estimated an SNR of 90:1 for the VIS range, 60:1 for the 1000-1600-nm bands and 35:1 for the 2000-2400-nm bands. Kruse et al. ...
doi:10.3390/rs10020157
fatcat:r3pktecntjbahc5htc53d5ende
Twenty five years of remote sensing in precision agriculture: Key advances and remaining knowledge gaps
2013
Biosystems Engineering
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At present there is considerable interest in collecting remote sensing data at multiple times in order to conduct near real time soil, crop and pest management. ...
A variety of spectral indices now exist for various precision agriculture applications, rather than a focus on only normalised difference vegetation indices. ...
The assistance of Mr. Tyler Nigon in preparing figures is acknowledged. ...
doi:10.1016/j.biosystemseng.2012.08.009
fatcat:ccfqjayitfeodi2yfqylo5w4yy
Networking technologies enable advances in Earth Science
2004
Computer Networks
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A combination of satellite, wireless, and terrestrial networking provided geologists at a remote field site with interactive access to supercomputer facilities at two NASA centers, thus enabling them to ...
A combination of satellite, wireless, and terrestrial networking provided geologists at a remote field site with interactive access to supercomputer facilities at two NASA centers, thus enabling them to ...
The Ground Truthing experiment was funded by the Computing, Networking and Information Systems (CNIS) Project of the NASA Computing, Information and Communications Technology (CICT) Program. ...
doi:10.1016/j.comnet.2004.06.015
fatcat:ghldu4w2azgq5f7swdyjwdy53m
Recent Advances of Hyperspectral Imaging Technology and Applications in Agriculture
2020
Remote Sensing
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Meanwhile, the acquisition, processing, and analysis of hyperspectral imagery still remain a challenging research topic (e.g., large data volume, high data dimensionality, and complex information analysis ...
Recommendations for future hyperspectral imaging research for precision agriculture are also presented. ...
More sensor specifications of EO-1 Hyperion are given in Table 2 . ...
doi:10.3390/rs12162659
fatcat:bfoe3xuja5b27b7wuu5ak7tdpq
Seasonal variations in phenology and productivity of a tropical dry deciduous forest from MODIS and Hyperion
2015
Agricultural and Forest Meteorology
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Hyperion EVI resampled at multiple resolutions (30 m; 60 m; 120 m; 250 m; 500 m) maintained synchrony with variations in the phenological events of canopy. ...
Given the patchy landscape and moisturedriven seasonal cycle of phenology and GPP, spatial resolutions of better than 250 m and narrowband spectral features like Hyperion are necessary for monitoring phenology ...
NJ, MS, NSR are thankful for the financial assistance by NRDMS, DST, New Delhi (NRDMS/11/1669/10/Pr: 3). ...
doi:10.1016/j.agrformet.2015.08.246
fatcat:zg5zj443djg77picmkoinug3xi
Estimating spatial variations in soil organic carbon using satellite hyperspectral data and map algebra
2011
International Journal of Remote Sensing
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The grant title is 'Virtual Watershed: Agricultural Landscape Evolution in an Adaptive Management Context'. ...
Any opinions, findings, conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation. ...
The results for several patches are added together to yield an estimate for a region (Post et al. 2001) . ...
doi:10.1080/01431161.2010.494637
fatcat:gpxsorbxgbdljevfj36qknlxra
D6.1 Conceptual framework for remote sensing-based CH monitoring
2020
Zenodo
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For this communication, appropriate metadata for the RS-MMS products will be created and an appropriate web cataloguing service for geospatial data (GeoNetwork) will be used. ...
The deliverable is intended for public use, and it will particularly be helpful for the partners involved in the design of the HYPERION platform. ...
et al., 2017, carried out harmonic analysis on seven years of ENVISAT ASAR data and identified floods by looking at anomalies in the time series. ...
doi:10.5281/zenodo.6352008
fatcat:nul4udvk35hupazeullordefxa
A new approach to image fusion based on cokriging
2005
2005 7th International Conference on Information Fusion
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The fusion of ALI with Hyperion data is studied using PCA and wavelet-based fusion. ...
We consider the image fusion problem involving remotely sensed data. We introduce cokriging as a method to perform fusion. We investigate the advantages of fusing Hyperion with ALI. ...
Our image/data fusion problem is then considered as an interpolation problem where we want to estimate frequencies at missing data points for data with low spatial resolution, or re-estimate or come up ...
doi:10.1109/icif.2005.1591912
fatcat:kgk5nwi32fgehkxq7snhgdh7bi
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