Regional evaporation estimates from flux tower and MODIS satellite data

2007 ◽  
Vol 106 (3) ◽  
pp. 285-304 ◽  
Author(s):  
Helen A. Cleugh ◽  
Ray Leuning ◽  
Qiaozhen Mu ◽  
Steven W. Running
Keyword(s):  
Satellite Data ◽  
Flux Tower

scholarly journals COMS-Based Retrieval of Daily Actual Evapotranspiration over Korea

2017 ◽  
Vol 2017 ◽  
pp. 1-16 ◽  
Author(s):  
Na-Yeon Park ◽  
Jae-Dong Jang ◽  
Youngmi Kim ◽  
Eun-Ha Sohn ◽  
Mi-Lim Ou ◽  
...  
Keyword(s):  
Satellite Data ◽  
Land Surface ◽  
Mixed Forest ◽  
Data Communication ◽  
Surface Characteristics ◽  
Semiempirical Method ◽  
Rice Paddy ◽  
Flux Tower ◽  
Polar Orbiting Satellite ◽  
Meteorological Satellite

Evapotranspiration (ET) from the land surface is an important hydrometeorological factor in the exchange of energy between the atmosphere and land surface. The accurate quantification for management of water resources and understanding of climate change are crucial, requiring continuous temporal and spatial monitoring. The objective of this study is to apply and estimate daily actual ET using semiempirical method, B-method, which is based on surface energy balance over heterogeneous area, Korea. To estimate daily ET, we used geostationary meteorological satellite data (Communication, Ocean and Meteorological Satellite, COMS) and polar-orbiting satellite data (Système Pour ľObservation de la Terre, SPOT). Estimated daily ET using only satellite data was relatively accurate and reflects land surface characteristics. It had high periodicity and spatial resolution over a wide area on clear-sky days. The daily ET was overestimated by about 1 mm/day at the two flux tower measurements sites, but the simulated seasonal variation and pattern were in good agreement with flux tower measurements. In the mixed forest, the root-mean-square error (RMSE) was 0.94 mm/day and the bias was 1.05 mm/day, while, in the rice paddy, RMSE was 1.12 mm/day and bias was 1.21 mm/day.

Generation of DEM and Ortho-image from High Resolution Stereo Satellite Data for a selected part of Southeast Bangladesh

2011 ◽  
Vol 4 (1) ◽  
pp. 500-502
Author(s):  
Md. Fazlul Haque ◽  
◽  
Md. Mostafizur Rahman Akhand ◽  
Dr. Dewan Abdul Quadir
Keyword(s):  
High Resolution ◽  
Satellite Data

Distributed access and search for the satellite data of remote sensing

2007 ◽  
Vol 13 (1s) ◽  
pp. 80-85
Author(s):  
E.B. Kudashev ◽  
◽  
A.N. Filonov ◽  
Keyword(s):  
Remote Sensing ◽  
Satellite Data

Delay-throughput tradeoff in satellite data relay networks with prioritized user satellites

2020 ◽  
Vol 17 (11) ◽  
pp. 219-230
Author(s):  
Yan Zhu ◽  
Min Sheng ◽  
Jiandong Li ◽  
Di Zhou
Keyword(s):  
Satellite Data ◽  
Relay Networks

Evaluation of Capacity of Salandi Reservoir Using Remote Sensing Data Along With Qgis Software

2018 ◽  
Vol 6 (8) ◽  
pp. 339
Author(s):  
Rupali Dhal ◽  
D. P. Satapathy
Keyword(s):  
Remote Sensing ◽  
Satellite Data ◽  
Remote Sensing Data ◽  
Project Work ◽  
Space Technology ◽  
Reservoir Water ◽  
Sediment Distribution ◽  
Sensing Data ◽  
Spread Area ◽  
Water Spread

The dynamic aspects of the reservoir which are water spread, suspended sediment distribution and concentration requires regular and periodical mapping and monitoring. Sedimentation in a reservoir affects the capacity of the reservoir by affecting both life and dead storages. The life of a reservoir depends on the rate of siltation. The various aspects and behavior of the reservoir sedimentation, like the process of sedimentation in the reservoir, sources of sediments, measures to check the sediment and limitations of space technology have been discussed in this report. Multi satellite remote sensing data provide information on elevation contours in the form of water spread area. Any reduction in reservoir water spread area at a specified elevation corresponding to the date of satellite data is an indication of sediment deposition. Thus the quality of sediment load that is settled down over a period of time can be determined by evaluating the change in the aerial spread of the reservoir at various elevations. Salandi reservoir project work was completed in 1982 and the same is taken as the year of first impounding. The original gross and live storages capacities were 565 MCM& 556.50 MCM respectively. In SRS CWC (2009), they found that live storage capacity of the Salandi reservoir is 518.61 MCM witnessing a loss of 37.89 MCM (i.e. 6.81%) in a period of 27 years.The data obtained through satellite enables us to study the aspects on various scales and at different stages. This report comprises of the use of satellite to obtain data for the years 2009-2013 through remote sensing in the sedimentation study of Salandi reservoir. After analysis of the satellite data in the present study(2017), it is found that live capacity of the reservoir of the Salandi reservoir in 2017 is 524.19MCM witnessing a loss of 32.31 MCM (i.e. 5.80%)in a period of 35 years. This accounts for live capacity loss of 0.16 % per annum since 1982. The trap efficiencies of this reservoir evaluated by using Brown’s, Brune’s and Gill’s methods are 94.03%, 98.01and 99.94% respectively. Thus, the average trap efficiency of the Salandi Reservoir is obtained as 97.32%.

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