Geospatial data and analysis fundamentals applied to renewable energies potential assessment
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1 Geospatial data and analysis fundamentals applied to renewable energies potential assessment
2 Network analysis: Do we go to Perugia by car?
3
4 Guideline Introduction renewable energy and Geospatial Technologies Geographic Information Systems (GIS) Geospatial data sources 2 on live exercises: Lab 1: Thematic map using Eurostat's Renewable energy primary production Lab 2: Location of optimum places for Photovoltaic Energy in VitoriaGasteiz
5 Introduction More than the 70% of the data has a spatial component The key word to Geospatial technology is Geography data that is in some way referenced to locations on the earth (adresses, latitud-longitude, etc) Geography is ordinary in the science field but also on the people day to day life (specially since 2005, when Google Maps is released) Renewable energy field also uses high amount of spatial data and geospatial analysis
6 A simple map to show statistical information
7 Annual global radiation on roofs on Miraflores de la Sierra (Madrid) (source: CIEMAT)
8 Wind Turbine visibility maps
9 Biomass estimation Hill, A.; Breschan, J.; Mandallaz, D. Accuracy Assessment of Timber Volume Maps Using Forest Inventory Data and LiDAR Canopy Height Models. Forests 2014, 5,
10 Actual potential of the geothermal technique in Europe (Source: EEERA)
11 Some academic definitions for Geographic Information Systems The common ground between information processing and the many fields using spatial analysis techniques. (Tomlinson, 1972) A powerful set of tools for collecting, storing, retrieving, transforming, and displaying spatial data from the real world. (Burroughs, 1986) A computerised database management system for the capture, storage, retrieval, analysis and display of spatial (locationally defined) data. (NCGIA, 1987) A decision support system involving the integration of spatially referenced data in a problem solving environment. (Cowen, 1988)
12 Spatial/Thematic component link Spatial Database Alfanumeric Database
13 What is a GIS for? make possible the automation of activities involving geographic data map production calculation of areas, distances, route lengths measurement of slope, aspect, viewshed logistics: route planning, vehicle tracking, traffic management by tieing data to maps, permits the communication of complex spatial patterns. provides answers to spatial queries (find potential areas where power lines are in a neighborhood of 500 metres ) perform complex spatial modelling (what if scenarios for transportation planning, disaster planning, resource management, utility design)
14 What is here?
15 Spatial Query: Municipalities in a proximity of 40 km from the closest nuclear power station
16 Network analysis: Do we go to Perugia by car?
17 Spatial patterns: London Cholera
18 Spatial patterns: Active Fires
19 Spatial modelling: Tsunami effects
20 Photovoltaic Suitability GIS model Source: Application of Airborne LiDAR Data and Geographic Information Systems (GIS) to Develop a Distributed Generation System for the Town of Normal, IL,AIMS Energy,3, ,173,183, :00:00.0,Jin H. Jo, Zachary Rose, Jamie Cross, Evan Daebel, Andrew Verderber, John C.Kostelnick,
21 Data models : examples
22 Raster data model A representation of the world as a surface divided into a regular grid of cells Raster models are useful for storing data that varies continuously, as in an aerial photograph, a satellite image, a surface of chemical concentrations, or an elevation surface.
23 Raster model: importance of the spatial resolution
24 Vector model A representation of the world using points, lines, and polygons. Vector models are useful for storing data that has discrete boundaries, such as country borders, land parcels, and streets. Primitive Spatial entity Representation Points Lines Polygons Victor Attributes
25 Raster vs Vectorial Raster + Developpers are very used to work with arrays and the programming languages support them very well + Simple analysis (pixel-based) + Continuous surfaces - High data volume Vector + Very adequate for output maps + Represent better discrete locations - Complex analysis
26 Geospatial data sources Discrete GNSS Total Station Digitalization Massive Photogrammetry Lidar Laser scanner and mobile mapping Remote sensing
27 Classic topography: Total Station
28 Global Navigation Satellite System (GPS, Glonass, Galileo) (Source:
29 Manual digitalization (heads down)
30 Screen-based digitalization (heads up)
31 Light Detection and Ranging (Lidar)
32 Lidar
33 Canopy height James R. Kellner, David B. Clark, and Michelle A. Hofton Canopy height and ground elevation in a mixedland-use lowland Neotropical rain forest landscape. Ecology 90:3274.
34 Digital Terrain Model (Source:
35 3D Laser scanner
36 Mobile mapping
37 Photogrammetry
38 Photogrammetry
39 Photogrammetry derived products
40 Remote Sensing Remote sensing is the acquisition of information about an object or phenomenon without making physical contact with the object
41 Resolution concept Spectral Spatial Reflectance Temporal Radiometric Wavelength
42 Temporal resolution vs Spatial Resolution
43 Global Vision Global Sea Surface Temperature
44 From local to global analysis scales
45 Systematic coberture
46 Spatially exhaustive adquisition Interpolated Satellite (Sanchez y Chuvieco, 2000)
47 Non human visible spectral areas (ASPRS: 2nd Ed., Colwell, 1983)
48 Solar Energy Irradiation
49 Wave height
50 Ocean wind speed
51 Land cover
52 Photovoltaic installation inspection
53 GIS software
54 GIS software
55 QGIS The leading open source GIS software GNU General public License It works under Windows, Linux, Unix, Mac OSX, and Android Not only QGIS SAGA GIS GRASS Orfeo Toolbox GDAL /ORG libraries
56
57 Laboratory 1: Renewable Energy Primary Production Map Supply, transformation and consumption of renewable energies annual data [nrg_107a] (Source: Eurostat) NUTS 13 1/1M shapefile (Source: Eurostat)
58 Laboratory 1: Renewable Energy Primary Production Map
59 Laboratory 1: Renewable Energy Primary Production Map
60 Laboratory 2: Building suitability for photovoltaic panel location Find the optimum buildings (good solar insolation > 1300 kw/m2/year -computed each 15 days- and slopes < 20º and installation areas > 10m2) Lidar derived Digital surface model Photogrammetry derived buildings vector layer
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