Journal Issue: Seoul, South Korea
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2015-20-09
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Volume Introduction Letter
Raghavan, Venkatesh
This Conference Proceedings is a collection of outstanding papers submitted to the Academic Program of the International Conference for Free and Open Source Software for Geospatial (FOSS4G), 14th to 19th September 2015 in Seoul, South Korea.
FOSS4G 2015 Full Conference Proceedings (papers)
Shin, Sanghee
This Conference Proceedings is a collection of outstanding papers submitted to the Academic Program of the International Conference for Free and Open Source Software for Geospatial (FOSS4G), 14th to 19th September 2015 in Seoul, South Korea.
Solar Energy Resource Assessment Using R.SUN In GRASS GIS And Site Suitability Analysis Using AHP For Groundmounted Solar Photovoltaic (PV) Farm In The Central Luzon Region (Region 3), Philippines
Pintor, Ben Hur; Sola, Eula Fae; Teves, Justine; Inocencio, Loureal Camille; Ang, Ma. Rosario Concepcion
In the study, the solar energy resource in the Central Luzon Region (Region 3), Philippines was determined using r.sun – a topography-based solar radiation model implemented in GRASS GIS – and suitable sites for the installation of ground-mounted solar photovoltaic (PV) farms were identified using the Analytic Hierarchy Process (AHP) to determine the weights of different physical, environmental, socio-economic, risk, and constraint criteria. For the resource assessment, the inputs to r.sun used in the study consisted of freely available data that include: an SRTM (90m resolution) Digital Elevation Model (DEM) and monthly average Linke turbidity coefficients available from the SoDA (Solar Radiation Database) webservice (www.soda-is.com). Daily solar radiation data from eight (8) measuring stations throughout the region were gathered. Readings from six (6) stations were used to interpolate monthly clear-sky index rasters while the readings from the remaining two (2) stations were used to validate the modelled monthly average Global Horizontal Irradiation (GHI) computed by r.sun. For the site suitability analysis, different criteria rasters were created and combined using weighted overlay to generate a suitability map for ground-mounted solar PV farms in the region. From the results, the monthly average GHI in the region computed by r.sun ranged from 3706.8 Wh/m2 - day in December to 6021.0 Wh/m2 -day in May with an annual average GHI of 4727.12 Wh/m2 -day indicating a good amount of resource potential. High GHI values were observed for the summer months of March to May (Mean: 5640.26 Wh/m2 -day) while the cold and rainy season ranging from July to December showed relatively lower values (Mean: 4298.98 Wh/m2 -day). The Mean Absolute Error (MAE) and Mean Absolute Percentage Error (MAPE) between the measured and modelled GHI were 352.88 Wh/m2 -day and 8.53%, respectively, with the lowest error in March (73.94 Wh/m2 -day, 1.44%) and the highest in August (844.01 Wh/m2 -day, 21.65%). In fact, the model performed well for the months of January to June (MAE: 192.18 Wh/m2 -day, MAPE: 3.83%) and slightly poorer for July to December (MAE: 512.824 Wh/m2 -day, MAPE: 13.22%). For further study, other data sources and inputs can be looked into to improve the accuracy of the resource assessment and site suitability analysis. Aside from this, the use of more solar radiation recording stations for validation is preferred in order to better validate the results of r.sun and its applicability for solar energy resource assessment in the Philippines.
Leightweight Urban Computation Interchange (LUCI) System
Treyer, Lukas; Klein, Bernhard; König, Reinhard; Meixner, Christine
In this paper we introduce LUCI, a Leightweight Urban Calculation Interchange system, designed to bring the advantages of calculation and content co-ordination system to small planning and design groups by the means of an open source middle-ware.The middle-ware focuses on problems typical to urban planning and therefore features a geo-data repository as well as a job runtime administration, to coordinate simulation models and its multiple views.The described system architecture is accompanied by two exemplary use cases, that have been used to test and further develop our concepts and implementations.
CROWD-2-CLOUD – Remote Sensing Land Cover Verification With Crowd-Sourcing Data
Ahmed, Moataz; Huynh, Dai; Wickramasinghe, Darshana; Vu, Tuong-Thuy
Nowadays, advanced remote sensing technologies provide huge amount of Earth Observation (EO) data timely. Growing quickly in terms of size and structure, EO data require a new way of handling and processing as it is considered big data. Cloud-computing platform proved to be a reliable and scalable platform that suits various user demands in remote sensing data processing. To verify the ambiguity of information derived solely from remote sensing, ground data is vital. The only way to keep pace with big remote sensing data is to exploit the crowdsourced data, which has been recently proposed elsewhere. In this study, we developed a prototype of an integrated location based service on top of cloud computing platform to detect land cover features and engage the crowd of volunteers during training and verification process. Relying on open-source tools, the proposed system provides location-based data collection and satellite image classification. The prototype was tested over the rapid on-going landscape surrounding the University of Nottingham, Malaysia campus. More advanced functions will be developed and a full system will be deployed and tested in further study.