Floodplain analysis with high spatial resolution remote sensing satellite data

Author(s):  
J.R. Richardson ◽  
L. Peyton ◽  
A.C. Correa ◽  
C.H. Davis ◽  
S. Kong ◽  
...  
2019 ◽  
Vol 75 ◽  
pp. 01006
Author(s):  
Evgenii A. Maltsev ◽  
Yuri A. Maglinets ◽  
Gennady M. Tsibulskii

This work describes the technology to identify firebreak plowing objects of agriculture fields based on the satellite data of the Earth Remote Sensing within the medium and high spatial resolution. The technology uses a model of the firebreak plowing object, vegetation indexes and spatial relations between objects.


Author(s):  
A.R. As-syakur ◽  
T. Osawa ◽  
IW.S. Adnyana

Remote sensing data with high spatial resolution is very useful to provideinformation about Gross Primary Production (GPP) especially over spatial coverage in theurban area. Most models of ecosystem carbon exchange based on remote sensing data usedlight use efficiency (LUE) model. The aim of this research was to analyze the distributionof annual GPP urban area of Denpasar. Two main satellite data used in this study wereALOS/AVNIR-2 and Aster satellite data. Result showed that annual value of GPP usingALOS/AVNIR-2 varied from 0.130 gC m-2 yr-1 to 2586.181 gC m-2 yr-1. Meanwhile, usingAster the value varied from 0.144 gC m-2 yr-1 to 2595.264 gC m-2 yr-1. The annual value ofGPP ALOS was lower than the value of Aster, because ALOS have high spatial resolutionand smaller interval of spectral resolution compared to Aster. Different land use couldeffect the value of GPP, because the different land use has different vegetation type,distribution, and different photosynthetic pathway type. The high spatial resolution of theremote sensing data is crucial to discriminate different land cover types in urban region.With heterogeneous land cover surface, maximum value of GPP using ALOS/AVNIR-2was smaller than that of Aster, however, the annual mean of GPP value usingALOS/AVNIR-2 was higher than that of Aster.


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