Some months ago, the Ciudad Real city council performed some maintenance and repair works on the Puerta the Toledo gate, one of the most iconic constructions in the city. This medieval construction was built in the 13th century, under the reign of Alfonso X.
During the Christmas break, I had the opportunity of have a walk around it and taking advantage of the solitude of New Year’s day, I took some pictures with my cellphone from the ground.
After processing the images with Agisoft Photoscan and cleaning the dense point cloud by means of CloudCompare, here you are some results. That was a sunny and clear day and I took the pictures in the afternoon, so there is an important difference between the north face (top left) and the south one (top right). Where are the clouds when one needs them?
Our latest work on HBIM, presented by my colleague Fred Bosché at the 35th International Symposium on Automation and Robotics in Construction (ISARC 2018), have received the best paper award.
The paper, titled “High Level-of-Detail BIM and Machine Learning for Automated Masonry Wall Defect Surveying”, was developed by our research team at Heriot-Watt University in collaboration with Historic Environment Scotland and can be found at the following link.
I hope you find it interesting!
Some weeks ago, and following the work of @ClimateLabBook, I produced a ‘warming stripes’ graph, illustrating the rise of temperature in Scotland in recent years.
Each stripe corresponds to a year, from 1910 on the left hand to 2017, and depicts variations in temperature. Intuitively, blue stripes show values under the average and red lines illustrate years with temperatures over the average. More saturated colours represent higher (or lower) temperatures, while shades of white correspond to temperature values close to the average.
A more complete graph can be produced if monthly average values of temperature are considered (instead of yearly figures). Following the same colour code used for the previous plot, a ‘warming patches’ map is created, illustrating for each particular month (e.g. January 2017) its variation of temperature with respect to historical records for that month (other Januaries).
The first line corresponds to January and the last one to December. And columns go from 1910 (left) to 2017.
The following map illustrates the proximity to coast of all the properties managed by Historic Environment Scotland. As can be seen, most of them obtained a score between 0,87 and 1, meaning that they can be directly (or indirectly) affected by their proximity to the sea.
In this post, a strategy to obtain the elevation of certain locations (i.e. buildings) is proposed.
First, a digital terrain model (DTM) is needed. In the example, the OS Terrain 50 has been used. This is a 50m gridded DTM, with 10m contours and spot heights, which is provided by the Ordnance Survey. In the next figure, the DTM for the Edinburgh area is shown.
Note that a ‘Merge‘ operation might be needed if the region of interest is covered by several DTMs.
After this operation, a Digital Elevation Model (DEM) is obtained after the DTM. This raster is created by means of the tool ‘Topo to Raster‘. In this example, an output cell size of 50m was used.
As illustrated in the DEM, the Arthur Seat, in Holyrood Park, is the highest area in Edinburgh. In the West part of the city, Hillwood Park is remarkable, as well as the Pentlands in the South.
Finally, elevations are extracted from the DEM for all the buildings/regions under study. In this case, the next figure shows the elevation of the properties managed by Historic Environment Scotland (HES) in Edinburgh, which have been extracted by means of ‘Extract multivalues to Points‘.
As usual in ArcGIS, different tools can deliver similar results. In this post, a map has been generated to show how to [quickly] filter features according to their position with respect to other elements.
There are several proximity tools that can be used to calculate distances between features. Some examples are: Near, Generate Near Table, Buffer or Multiple Ring Buffer.
In the following map, the distances from the attractions managed by Historic Environment Scotland (HES) to the John Muir Way have been calculated by means of Near. After that, the buildings have been filtered by attribute (distance), showing those in a range of [at most] 5 kms along this route.
This is a quick trick to personalise the symbols used to indicate the position of features in our maps in ArcGIS. Even if this is a simple operation, a nice visual effect can be obtained.
You just need to open the Symbol Selector > Edit Symbol.
In the menu Type, choose Picture Marker Symbol. Browse in your folders and choose the image you want to use as icon. Then, select the size and angle and click OK.
In the following map, I have applied this feature to display the properties managed by Historic Environment Scotland in Edinburgh and surronding area.
In this post, I will store [updated] links to different sources of GIS data. This collection may vary according to my works, but it will mainly contain data about EU, UK and Spain.
British Government’s data https://data.gov.uk/
Ordnance Survey Open Data https://www.ordnancesurvey.co.uk/
British Geological Survey. OpenGeoscience http://www.bgs.ac.uk
Scottish Spatial Data Infrastructure https://www.spatialdata.gov.scot
Scottish Natural Heritage https://gateway.snh.gov.uk/natural-spaces/
Edinburgh Council Open Data http://edinburghopendata.info/
Spanish Government Open Data http://datos.gob.es/es/catalogo
National Center for Geographic Information http://centrodedescargas.cnig.es/CentroDescargas/index.jsp
Junta de Castilla-La Mancha Open Data http://data-castillalamancha.opendata.arcgis.com/
Eurostat GISCO. Administrative boundaries, infrastructure and land cover http://ec.europa.eu/eurostat/web/gisco
UNESCO Institute for Statistics http://data.uis.unesco.org/
Global administrative areas http://www.gadm.org/
University of Pennsylvania international GIS database http://guides.library.upenn.edu/globalgis
Federal government’s open data site https://www.data.gov/open-gov/
Applying machine learning techniques to aerial photography.
The following map illustrates the use of agricultural land in the surroundings of the Parque Natural de las Lagunas de Ruidera, in Castilla-La Mancha, Spain.
Percentage of population with access to improved water source.