scholarly journals Phytoplankton photosynthetic parameters off Baja California: A tool to estimate primary production with remote sensing data

2017 ◽  
Vol 43 (3) ◽  
pp. 157-172 ◽  
Author(s):  
Ramón Sosa-Ávalos
Keyword(s):  
Remote Sensing ◽  
Primary Production ◽  
Baja California ◽  
Remote Sensing Data ◽  
Photosynthetic Parameters ◽  
Sensing Data

scholarly journals Aplikasi Penghitungan Gross Primary Production dari Data Penginderaan Jauh

2016 ◽  
pp. 31
Author(s):  
Komang Gede Kurniadi ◽  
I Putu Agung Bayupati ◽  
I Dewa Nyoman Nurweda Putra
Keyword(s):  
Remote Sensing ◽  
Primary Production ◽  
Gross Primary Production ◽  
Satellite Image ◽  
Remote Sensing Data ◽  
Landsat 8 ◽  
Automatic Data ◽  
Sensing Data ◽  
Metadata File ◽  
Production Calculation

Calculation of Gross Primary Production that utilize remote sensing data is can be done on commercial remote sensing software by manual method. The commercial remote sensing software does not provides a specific feature that allow the user to do the Gross Primary Production calculation. This research is aimed to to build a remote sensing software that can be specifically used to do the Gross Primary Production calculation for Denpasar area. This software accepts remote sensing data as an input, such as satellite image from Landsat 8 OLI and TIRS and metadata file. The formulas and supporting data that required on the Gross Primary Production calculation are implemented on software in order to make an automatic image processing software. There also some additional feature on this software such as automatic data parsing from metadata file, cropping, masking and zoom that could help user to do the Gross Primary Production calculation. The developed software is able to produce information such as Gross Primary Production  value that depicted by a figure with color segmentation, area of the segments and mean, minimum and maximum value of the Gross Primary Production.  

Estimation of primary production of subhumid rangelands from remote sensing data

2000 ◽  
Vol 3 (2) ◽  
pp. 189-195 ◽  
Author(s):  
José M. Paruelo ◽  
Martín Oesterheld ◽  
Carlos M. Di Bella ◽  
Martín Arzadum ◽  
Juan Lafontaine ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Primary Production ◽  
Remote Sensing Data ◽  
Sensing Data

scholarly journals ESTIMATION OF GROSS PRIMARY PRODUCTION USING SATELLITE DATA AND GIS IN URBAN AREA, DENPASAR

2011 ◽  
Vol 7 (1) ◽  
Author(s):  
A.R. As-syakur ◽  
T. Osawa ◽  
IW.S. Adnyana
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Land Cover ◽  
Primary Production ◽  
Spatial Resolution ◽  
Satellite Data ◽  
High Spatial Resolution ◽  
Gross Primary Production ◽  
Remote Sensing Data ◽  
Sensing Data

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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