Geospatial data and analysis fundamentals applied to renewable energies potential assessment

Network analysis: Do we go to Perugia by car?

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

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

A simple map to show statistical information

Annual global radiation on roofs on Miraflores de la Sierra (Madrid) (source: CIEMAT)

Wind Turbine visibility maps

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, 2253-2275.

Actual potential of the geothermal technique in Europe (Source: EEERA)

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)

Spatial/Thematic component link Spatial Database Alfanumeric Database

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)

What is here?

Spatial Query: Municipalities in a proximity of 40 km from the closest nuclear power station

Network analysis: Do we go to Perugia by car?

Spatial patterns: London Cholera 1854 https://www.ted.com/talks/steven_johnson_tours_the_ghost_map

Spatial patterns: Active Fires

Spatial modelling: Tsunami effects

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,3,2333-8334,173,183,2015-03-23 00:00:00.0,Jin H. Jo, Zachary Rose, Jamie Cross, Evan Daebel, Andrew Verderber, John C.Kostelnick,

Data models : examples

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.

Raster model: importance of the spatial resolution

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 Olaya @volayaf Attributes

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

Geospatial data sources Discrete GNSS Total Station Digitalization Massive Photogrammetry Lidar Laser scanner and mobile mapping Remote sensing

Classic topography: Total Station

Global Navigation Satellite System (GPS, Glonass, Galileo) (Source: www.academic.edu)

Manual digitalization (heads down)

Screen-based digitalization (heads up)

Light Detection and Ranging (Lidar)

Lidar

Canopy height James R. Kellner, David B. Clark, and Michelle A. Hofton. 2009. Canopy height and ground elevation in a mixedland-use lowland Neotropical rain forest landscape. Ecology 90:3274.

Digital Terrain Model (Source: www.toposys.com/)

3D Laser scanner

Mobile mapping

Photogrammetry

Photogrammetry derived products

Remote Sensing Remote sensing is the acquisition of information about an object or phenomenon without making physical contact with the object

Resolution concept Spectral Spatial 60.00 Reflectance 50.00 40.00 30.00 59.09 33.27 20.00 0.00 10.00 0.00 0.36 Temporal 0.45 0.54 0.63 0.72 0.80 0.89 0.98 1.16 1.42 Radiometric 1.67 1.91 2.15 2.40 Wavelength

Temporal resolution vs Spatial Resolution

Global Vision Global Sea Surface Temperature

From local to global analysis scales

Systematic coberture

Spatially exhaustive adquisition Interpolated Satellite (Sanchez y Chuvieco, 2000)

Non human visible spectral areas (ASPRS: 2nd Ed., Colwell, 1983)

Solar Energy Irradiation

Wave height

Ocean wind speed

Land cover

Photovoltaic installation inspection

GIS software Www.gisgeography.com

QGIS www.qgis.org 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 Www.gisgeography.com

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)

Laboratory 1: Renewable Energy Primary Production Map

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