Assessing land surface temperature in urban areas using open-source geospatial tools
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Number of Parts | 351 | |
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License | CC Attribution 3.0 Unported: You are free to use, adapt and copy, distribute and transmit the work or content in adapted or unchanged form for any legal purpose as long as the work is attributed to the author in the manner specified by the author or licensor. | |
Identifiers | 10.5446/68945 (DOI) | |
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Production Year | 2022 |
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00:00
Open sourceNeuroinformatikGrass (card game)Presentation of a groupCompilation albumComputer animation
00:16
Ultraviolet photoelectron spectroscopyPoint cloudPressure volume diagramTemporal logicPoint cloudPrice indexIntermediate languageWärmestrahlungTemporal logicSurfaceMeasurementComputer animation
00:53
Mathematical modelVector spaceBoltzmann constantGrass (card game)CoefficientHeat transferDigital signalSurfaceNichtlineares GleichungssystemRaster graphicsParameter (computer programming)Mathematical modelUltraviolet photoelectron spectroscopyScripting languageCalculationUniform convergenceoutputFaculty (division)FingerprintDigital photographySource codeOpen setCondition numberMathematical modelMaterialization (paranormal)Normal distributionVector spaceGrass (card game)CalculationModule (mathematics)Observational studyoutputParameter (computer programming)Flow separationHorizonMeasurementRevision controlLevel (video gaming)MereologyRaster graphicsCASE <Informatik>Different (Kate Ryan album)Sampling (statistics)Procedural programmingResultantBuildingScripting languageAreaRight angleMathematical modelMultiplication signComputer animation
Transcript: English(auto-generated)
00:00
And good morning to everybody here and online. In this short, brief presentation, I'd like to talk about new tools for computation of land surface temperature in a grass GIS. Land surface temperature, or LST,
00:21
is considered quite a reliable indicator for urban heat island phenomenon. And LST is usually measured using satellite or airborne thermal sensors. The problem is that these sensors have quite a rough spatial and temporal resolution.
00:43
And sometimes even clouds can pose an obstacle to sense or measure this data. So we developed a new tool for calculation to calculate LST in grass GIS using physical principles.
01:02
And it is implemented in grass GIS as RLST for raster data and the V.LST for vector 3D city models. This model is quite simple. It uses several input parameters.
01:22
One of them, or the most important, is solar irradiance. That is calculated also in grass GIS using r.sun. This module is part of the standard distribution of grass. And also, v.sun solar radiation model,
01:41
there is full 3D solar radiation model that is not part of the standard distribution of grass. So in this picture, you can see the 2D version of LST calculation or model that is calculated for urban data.
02:01
And here, I want to show you examples how LST can be calculated for 3D city model. So you can see here on the left, autofone map of our study area, sample of 3D city model. And the procedure is quite simple,
02:21
because first, you need to calculate solar irradiance using v.sun in this case. And then using v.LST script, you can calculate LST values. So this is solar radiation map.
02:40
These are three time horizons. On the upper left side is at 7 o'clock in the morning. Then there is noon. And on the lower right, there is evening at 17 or 5 PM.
03:04
So you can see that for buildings, you have different values of solar irradiance that are directly translated to land surface temperature. So the result is here. So you can see that some buildings in the morning
03:22
have more higher temperature on facades than on roofs. During the noon, you can see on the lower left picture that roofs have more, are hotter. And evening is the opposite of the morning's situation.
03:44
So using this model, you can calculate LST. Then you can take some preventing or mitigating measures to mitigate urban heat island phenomenon to use maybe roofs with the lower albedo or higher albedo.
04:03
Or you can use different materials to decrease temperature of the building materials. So thank you very much. If you are interested in this topic, you can find here three papers. The first one is published within this conference.
04:22
And the next two have been already published in scientific journals. Thank you very much.