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Comparative Analysis of GF-1 WFV, ZY-3 MUX, and HJ-1 CCD Sensor Data for Grassland Monitoring Applications

Lei Wang, Ranran Yang, Qingjiu Tian, Yanjun Yang, Yang Zhou, Yuan Sun, Xiaofei Mi
2015 Remote Sensing  
Based on spectral field measurements, the characteristic differences of spectral response functions of the sensors were analyzed.  ...  In this study, we assessed the potential use of GF-1 WFV (Wild Field Camera), ZY-3 MUX (Multispectral camera), and HJ-1 CCD (Charge Coupled Device) sensor data for grassland monitoring by comparing spectral  ...  Effects of the Spectral Response Function on Band Reflectance In order to assess the effects of varying spectral response functions in the red and near-infrared bands for the different sensors, Equation  ... 
doi:10.3390/rs70202089 fatcat:xaspzsbxkza5xkbzeyo5dqjtwq

Comparison of the Vegetation Index of Reclamation Mining Areas Calculated by Multi-Source Remote Sensing Data

Jiameng Hu, Baoying Ye, Zhongke Bai, Jiawei Hui
2022 Land  
Results show that: (1) Landsat 8 and Sentinel-2 satellite have a high relevance for monitoring the vegetation, but the correlation between these two sensors and HJ is relatively low, (2) the correlation  ...  Comparing the correlation of multi-source sensors to monitor the vegetation in the mining areas can be helpful to determine the alternative supplement of sensors through conversion formulas, which are  ...  The spectral response function of the sensor ((a-c) are the spectral responses of Sentinel-2, Landsat 8, and HJ respectively).  ... 
doi:10.3390/land11030325 fatcat:luucclaowjechksxqsfouvxlny

Comparability of Red/Near-Infrared Reflectance and NDVI Based on the Spectral Response Function between MODIS and 30 Other Satellite Sensors Using Rice Canopy Spectra

Weijiao Huang, Jingfeng Huang, Xiuzhen Wang, Fumin Wang, Jingjing Shi
2013 Sensors  
The reflectance and NDVI data sets derived from different satellite sensor systems will not be directly comparable due to different spectral response functions (SRF), which has been recognized as one of  ...  The rice canopy reflectances were convoluted with the spectral response functions of various OPEN ACCESS Sensors 2013, 13 16024 satellite instruments to simulate sensor-specific reflectances in the red  ...  Acknowledgements We acknowledge Yanlin Tang, Qian Cheng, Junfeng Xu, Lei Zhu, Zhanyu Liu, Yuan Wang, Qiuxiang Yi, and Yan Jin for their contributions to the spectral measurements of the rice canopy.  ... 
doi:10.3390/s131216023 pmid:24287529 pmcid:PMC3892887 fatcat:qcmjcuwbqfdv7axlr3r3ddnj7y

Remote Sensing Techniques to assess Post-Fire Vegetation Recovery

Fernando Pérez-Cabello, Raquel Montorio, Daniel Borini Alves
2021 Current Opinion in Environmental Science & Health  
Compared to the extensive and labour-intensive field campaigns, remote sensing provides a time-and cost-effective tool to monitor post-fire vegetation recovery (PVR).  ...  Monitoring postfire recovery dynamics is crucial for evaluating resilience and securing the relevant information that will enhance management and support ecosystem restoration after fires.  ...  Environmental Sciences Institute (IUCA) of the University of Zaragoza, the research project HARMO-LS2 (UZCUD2020-HUM-02): "Harmonizacio ´n de ima ´genes Landsat/Sentinel-2 para el seguimiento de la dina ´mica vegetal  ... 
doi:10.1016/j.coesh.2021.100251 fatcat:hwncovmi3rcdzfgiaevtyhriny

Experimental Evaluation of Sentinel-2 Spectral Response Functions for NDVI Time-Series Continuity

Petra D'Odorico, Alemu Gonsamo, Alexander Damm, Michael E. Schaepman
2013 IEEE Transactions on Geoscience and Remote Sensing  
Variations in spectral response functions (SRFs) are among the major causes of differences in multisensor reflectances and products.  ...  (MODIS), and Medium Resolution Imaging Spectrometer (MERIS) relevant for vegetation monitoring.  ...  Verhoef for providing and supporting the use of SLC model. The authors would also like to thank A. Hüni and M. Jehle of the APEX team for the support.  ... 
doi:10.1109/tgrs.2012.2235447 fatcat:yff2zfsi55b2djsryrkuc3mpzq

Effects of spectral response function on surface reflectance and NDVI measured with moderate resolution satellite sensors

Alexander P Trishchenko, Josef Cihlar, Zhanqing Li
2002 Remote Sensing of Environment  
We report the results of a modeling study on the sensitivity of normalized difference vegetation index (NDVI) and surface reflectance to differences in instrument spectral response functions (SRF) for  ...  (MODIS), the Vegetation sensor (VGT), and the Global Imager (GLI).  ...  Hitchcock of CCRS for making PROBE-1 data available for this study. We acknowledge the use of spectral data from JPL ASTER spectral library (  ... 
doi:10.1016/s0034-4257(01)00328-5 fatcat:5ayhnsbr5vfynl5wlusx5dt72y

Angle Effect on Typical Optical Remote Sensing Indices in Vegetation Monitoring

Lingxiao Gu, Yanmin Shuai, Congying Shao, Donghui Xie, Qingling Zhang, Yaoming Li, Jian Yang
2021 Remote Sensing  
We adopted the ground multi-angle hyperspectrum, spectral response function (SRF) of Thematic Mapper (TM), Enhanced Thematic Mapper (ETM+), Operational Land Imager (OLI), Moderate-Resolution Imaging Spectroradiometer  ...  In addition, based on this work, indices with a suppressed potential of angle effect are recommended for vegetation monitoring or information retrieval to avoid unexpected effects.  ...  of the ground canopy and to Jialei Wang for his help in this research.  ... 
doi:10.3390/rs13091699 fatcat:5jnm5g6dnzg7hcuw34gazsvvcq

Intercalibration of vegetation indices from different sensor systems

Michael D Steven, Timothy J Malthus, Frédéric Baret, Hui Xu, Mark J Chopping
2003 Remote Sensing of Environment  
The reflected spectral radiances were convoluted with the spectral response functions of a range of satellite instruments to simulate their responses.  ...  This result offers improved opportunities for monitoring crops through the growing season and the prospects of better continuity of long-term monitoring of vegetation responses to environmental change.  ...  We are particularly indebted to numerous colleagues who helped with fieldwork in the UK, France and China and to the NERC Equipment Pool for Field Spectroscopy who provided instrumentation and valuable  ... 
doi:10.1016/j.rse.2003.08.010 fatcat:uucp7bum4bf6pfoljctzkehh3a

Using a Vegetation Index-Based Mixture Model to Estimate Fractional Vegetation Cover Products by Jointly Using Multiple Satellite Data: Method and Feasibility Analysis

Wanjuan Song, Tian Zhao, Xihan Mu, Bo Zhong, Jing Zhao, Guangjian Yan, Li Wang, Zheng Niu
2022 Forests  
Analyses of the spatial resolution and spectral response function differences for MODIS and other satellites including Landsat 8, Chinese GF 1, and ZY 3 predicted that (1) the effect of Vv and Vs downscaling  ...  However, data from different satellites have large differences in spatial resolution, spectral response function, and so on, making joint use difficult.  ...  Spectral Analysis for Multiple Satellite Sensors The spectral difference among MODIS, Landsat 8, ZY 3, and GF 1 were compared based on NDVI.  ... 
doi:10.3390/f13050691 doaj:be958fe95d5f4b87bfcda91a7b415fc7 fatcat:uv4rrizdqnel7bpzteqtrh7ody

Comparison of NDVIs from GOCI and MODIS Data towards Improved Assessment of Crop Temporal Dynamics in the Case of Paddy Rice

Jong-Min Yeom, Hyun-Ok Kim
2015 Remote Sensing  
In this study, ground spectral measurements from CROPSCAN were also compared with satellite-based vegetation products, despite their different index magnitude, according to systematic discrepancy, showing  ...  This paper describes a four-year testing period from 2010 to 2014, during which satellite images from the world's first Geostationary Ocean Color Imager (GOCI) were used for spectral analyses of paddy  ...  Acknowledgments We thank the Korea Institute of Ocean Science & Technology (KIOST) for providing GOCI data. Author Contributions All authors assisted in the analysis and editing of the paper.  ... 
doi:10.3390/rs70911326 fatcat:b7rumzogu5e2fmol6e5hulmhva

BAIS2: Burned Area Index for Sentinel-2

Federico Filipponi
2018 Proceedings (MDPI)  
New MSI sensor aboard Sentinel-2 satellites carries more spectral information 14 recorded in the red-edge spectral region, opening the way to the development of new indices for 15 burned area mapping.  ...  Accurate and rapid mapping of fire damaged areas is fundamental to support fire 8 management, account for environmental loss, define planning strategies and monitor the 9 restoration of vegetation.  ...  Estimating spectral separability of satellite derived parameters for burned areas mapping in the Calabria region by using SPOT-Vegetation data. Ecol.  ... 
doi:10.3390/ecrs-2-05177 fatcat:evijm7wdrbearkukw2k2yxo6uu

Roof materials identification based on pleiades spectral responses using supervised classification

Ayom Widipaminto, Yohanes Fridolin Hestrio, Yuvita Dian Safitri, Donna Monica, Dedi Irawadi, Rokhmatuloh Rokhmatuloh, Djoko Triyono, Erna Sri Adiningsih
2021 TELKOMNIKA (Telecommunication Computing Electronics and Control)  
Spectroscopy is a technique for obtaining spectrum or wavelengths at each position from various spatial data so that images can be recognized based on their respective spectral wavelengths.  ...  This classification is based on data from satellite image spectroscopy results with very high resolution.  ...  DI contributed to the recommendations for the use of data. R, DT, and ESA helped to review the paper and methodology.  ... 
doi:10.12928/telkomnika.v19i2.18155 fatcat:lalhsn5iqbhijbwwk65yhzh3su

A UAV-Based Sensor System for Measuring Land Surface Albedo: Tested over a Boreal Peatland Ecosystem

Francis Canisius, Shusen Wang, Holly Croft, Sylvain G. Leblanc, Hazen A.J. Russell, Jing Chen, Rong Wang
2019 Drones  
Further, total shortwave albedo was estimated from spectral measurements and compared with the satellite-derived albedo.  ...  A multiple sensor payload for a multi-rotor based UAV platform was developed and tested for measuring land surface albedo and spectral measurements at user-defined spatial, temporal, and spectral resolutions  ...  Acknowledgments: The authors gratefully acknowledge the support from the CCRS management team for this activity.  ... 
doi:10.3390/drones3010027 fatcat:yp66j6ehvbe4vg3nevwptovqgu

Review of Satellite Remote Sensing Use in Forest Health Studies~!2010-01-27~!2010-04-05~!2010-06-29~!

Junming Wang, Theodore W. Sammis, Vincent P. Gutschick, Mekonnen Gebremichael, Sam O. Dennis, Robert E. Harrison
2010 The Open Geography Journal  
Some additional satellite sensors, such as for high temperature estimates (as high as 1800 K) and sensors of narrow bands, are also needed.  ...  Satellite remote sensing has been used in forest health management as a method for vegetation mapping, fire fuel mapping, fire risk estimation, fire detection, post-fire severity mapping, insect infestation  ...  Scott Williams for his literature collection assistance.  ... 
doi:10.2174/1874923201003010028 fatcat:7b4lao5windcfdjucbop62oed4

Comparative Analysis of Chinese HJ-1 CCD, GF-1 WFV and ZY-3 MUX Sensor Data for Leaf Area Index Estimations for Maize

Jing Zhao, Jing Li, Qinhuo Liu, Hongyan Wang, Chen Chen, Baodong Xu, Shanlong Wu
2018 Remote Sensing  
Currently, the satellite data of Remote Sens. 2018, 10, 68 3 of 20 ZY-3 MUX, GF-1 WFV, and HJ-1 CCD have been applied for vegetation monitoring.  ...  Apart from several reflectance fluctuations, the reflectance trends were coincident, and the reflectance values of the red and near-infrared (NIR) bands were comparable among these sensors.  ...  The maximal NDVI difference among ZY-3 MUX, GF-1 WFV, and HJ-1 CCD in theory reached 2.62% due to the different sensor spectral response functions ( Figure 10) .  ... 
doi:10.3390/rs10010068 fatcat:7qg6vqxf3fhpzlabb5zsdkzoli
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