Subpixel temperature retrieval with multispectral sensors

Author(s):  
John J. Szymanski ◽  
Christoph C. Borel ◽  
Quincy O. Harberger ◽  
Pawel Smolarkiewicz ◽  
James P. Theiler
1999 ◽  
Author(s):  
John J. Szymanski ◽  
Christoph C. Borel ◽  
Quincy O. Harberger ◽  
Pawel Smolarkiewicz ◽  
James P. Theiler

2021 ◽  
Vol 13 (4) ◽  
pp. 830
Author(s):  
Adam R. Benjamin ◽  
Amr Abd-Elrahman ◽  
Lyn A. Gettys ◽  
Hartwig H. Hochmair ◽  
Kyle Thayer

This study investigates the use of unmanned aerial systems (UAS) mapping for monitoring the efficacy of invasive aquatic vegetation (AV) management on a floating-leaved AV species, Nymphoides cristata (CFH). The study site consists of 48 treatment plots (TPs). Based on six unique flights over two days at three different flight altitudes while using both a multispectral and RGB sensor, accuracy assessment of the final object-based image analysis (OBIA)-derived classified images yielded overall accuracies ranging from 89.6% to 95.4%. The multispectral sensor was significantly more accurate than the RGB sensor at measuring CFH areal coverage within each TP only with the highest multispectral, spatial resolution (2.7 cm/pix at 40 m altitude). When measuring response in the AV community area between the day of treatment and two weeks after treatment, there was no significant difference between the temporal area change from the reference datasets and the area changes derived from either the RGB or multispectral sensor. Thus, water resource managers need to weigh small gains in accuracy from using multispectral sensors against other operational considerations such as the additional processing time due to increased file sizes, higher financial costs for equipment procurements, and longer flight durations in the field when operating multispectral sensors.


2018 ◽  
Vol 7 (1) ◽  
pp. 1 ◽  
Author(s):  
John Odindi ◽  
Elhadi Adam ◽  
Elfatih M. Abdel-Rahman ◽  
Onisimo Mutanga

2017 ◽  
Vol 37 (4) ◽  
pp. 782-789 ◽  
Author(s):  
Heloisa B. Souza ◽  
Fabio H. R. Baio ◽  
Danilo C. Neves

2015 ◽  
Vol 2015 ◽  
pp. 1-16 ◽  
Author(s):  
Caixia Gao ◽  
Enyu Zhao ◽  
Chuanrong Li ◽  
Yonggang Qian ◽  
Lingling Ma ◽  
...  

The aim of this study is to evaluate the aerosol influence on LST retrieval with two algorithms (split-window (SW) method and a four-channel based method) using simulated data under typical conditions. The results show that the root mean square error (RMSE) decreases to approximately 2.3 K for SW method and 1.5 K for four channel based method when VZA = 60° and visibility = 3 km; an RMSE would be increased by approximately 1.0 K when visibility varies from 3 km to 23 km. Moreover, a detailed sensitivity analysis under a visibility of 3 km and 23 km is performed in terms of uncertainties of land surface emissivity (LSE), water vapor content (WVC), and instrument noise, respectively. It is noted that the four-channel based method is more sensitive to LSE than SW method, especially for dry atmosphere; LST error caused by a WVC uncertainty of 20% is within 1.5 K for SW method and within 0.8 K for four-channel based method; the instrument noise would introduce LST error with a maximum standard deviation of 0.5 K and 0.04 K for the four-channel based method and SW method, respectively.


2013 ◽  
Vol 785-786 ◽  
pp. 1333-1336
Author(s):  
Xiao Feng Yang ◽  
Xing Ping Wen

Land surface temperature (LST) is important factor in global climate change studies, radiation budgets estimating, city heat and others. In this paper, land surface temperature of Guangzhou metropolis was retrieved from two MODIS imageries obtained at night and during the day respectively. Firstly, pixel values were calibrated to spectral radiances according to parameters from header files. Then, the brightness temperature was calculated using Planck function. Finally, The brightness temperature retrieval maps were projected and output. Comparing two brightness temperature retrieval maps, it is concluded that the brightness temperature retrieval are more accurate at night than during the day. Comparing the profile line of brightness temperature from north to south, the brightness temperature increases from north to south. Temperature different from north to south is larger at night than during the day. The average temperature nears 18°C at night and the average temperature nears 26°C during the day, which is consistent with the surface temperature observed by automatic weather stations.


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