Tutorial: create an aptitude map with ArcMap, with and without fuzzy criteria (3)

In the previous article, Tutorial : create an aptitude map with ArcMap, with and without  fuzzy criteria (2) , we have started by preparing basic data ( criteria ) to build an aptitude map. Right now we will finish the work.

Ranking of the ground slopes with Spatial Analyst

To avoid steep slopes and look for areas where the construction ground is relatively flat, you must know the slope of the site to be searched. The Slope tool creates this type of map identifying for each cell the maximum rate of variation of the values of each cell relative to the neighbouring cells. To rank the map, use the Reclassification tool. Since it is better to locate the location on relatively flat terrain, set the 1 to sites with steep slopes and the value 10 to locations where the slope is more gentle. Then, classify the intermediate values linearly as shown in the following illustration.

We use the Reclassify tool from Spatial Analyst- toolbox> Sort.
Steps:

  • Open the Reclassification tool
  • As layer in entry indicate Slope
  • Accept the default value for the parameter reclassification field to use the Value field .
  • Click Sort
  • Set the Method to equal Interval (variable number) and the number of Classes out of 10.
  • Click
  • Click Reverse the news values.
    The inversion of values applies new higher values with values that represent a slope less steep, since these surfaces are more suitable for building.
  • Enter a name for the raster output parameter: PenteReclass
  • Click

The result is the following:

Given the fact that the slope is a direct data from the field, unlike the two previous criteria (distances to schools and recreation centres), the distribution is clearly less regular.

Ranking of areas nearby the recreational installations using the fuzzy Criterion tool

 

However, classify the slopes in 10 classes between 0 and 75 ° does not really make sense with respect to construction constraints.

It is already known that in construction the limits are expressed in % of the slope and not in angle. Between 0 and 15% we are in the classical construction. Between 15 and 30% we are obliged to use the construction on piles or in scale. Beyond 30%, even if technically still feasible, the costs become prohibitive.

In our case, then, we can consider a terrain totally suitable for the construction of a school a ground having a slope between 0 and 15% (0 to 8.5 °) and totally unfit if the slope is >30% (16.75 °).

 

The result is as follows:

Ranking of land use with Spatial Analyst

To rank the map representing the types of land use, use the Reclassification tool. Since it is better to build on certain types of land use due to cost you must determine how to rank the values. The classification of distance values or slope is a procedure that remains quite simple. You must determine whether short or long distances are preferable and whether the steep or gentle slopes are desirable, then classify the rest of the values linearly or specify a distance or a maximum slope to take into account . Here you must determine the most appropriate types of land use. This process is subjective because it depends on your study. The simplest way is to decide which is best and which is the least appropriate. Then, rank in order of preference the types of use of the remaining soil. You have to continue with this process until all types of use are classified. Land uses such as water type and wetlands have been excluded from the analysis because you cannot build on water and must follow certain restrictions for the construction on wetlands. The illustration below indicates the classification of land use types.

Agriculture -> agricultural lands->   10
Barren land -> arid lands->   6
Brush / transitional -> shrub / transition zone -> 5
Forest -> forest -> 4
Built up -> built -> 3
Water -> water body -> 0
Wetlands -> wetlands -> 0

  • Open reclassification tool (3)
  • Accept the default value for the reclassification Field parameter to use the field LANDUSE
  • Enter the values indicated for each type of occupation in the table
  • click OK

The result is as follows:

Ranking of zones according to land occupation with the   Criterion   text tool.

 

The use of the command Criterion text follows the same process, the result is equivalent.

If we use seven levels of satisfaction, we will assign the following values:

Agriculture -> agricultural lands ->   Excellent
Barren land -> arid lands-> Good
Brush / transitional -> shrub / transition zone ->   Way
Forest -> forest ->   Poor
Built up -> built -> Very bad
Water -> water body->   Excluded
Wetlands -> wetlands ->   Excluded  figura10

The result is as follows :

Well, we have finished with the preparation of different criteria that are needed to build the aptitude map.

In  the next article we will discuss how to cross these criteria for obtaining the final result .

 

 

Tutorial : create an aptitude map with ArcMap, with and without fuzzy criteria (2)

Let’s go back literally to the Spatial Analyst tutorial:
”   …

Creation of an aptitude map

The creation an aptitude map allows you to get an aptitude value for each location on the map.
Once you have created the necessary layers ( in this example , the layers are Slope , Distance to Recreational Facilities , Distance to Schools and Land Use) to your analysis, how do these  created layers combine to create a classified map of the potential surfaces to locate school   ? You must compare the values of classes among layers. To accomplish this task, a method involves assigning numerical values to the classes included in each layer of the map or to re classify them.

Each layer of the map is classified according its aptitude degree as location for the new school.. For example, you can assign a value to each class of each layer, according to a scale from 1 to 10, 10 being the best ranking. Continue reading “Tutorial : create an aptitude map with ArcMap, with and without fuzzy criteria (2)”

Tutorial: create an aptitude map with ArcMap, with and without fuzzy criteria (1)

An aptitude map is the answer to the question:   Where is the best location for a new resource?   The result you looking is a map representing all the possible sites (ranked from the most to the least likely) that would be suitable for the installation a new resource. This map is a classified aptitude map since it depicts a relative in the map, taking into consideration the criteria you enter in in your study.

We will follow the ArcGIS Spatial Analyst tutorial

http://help.arcgis.com/fr/arcgisdesktop/10.0/pdf/tutorial_spatial_analyst.pdf  

in parallel with

http://help.arcgis.com/en/arcgisdesktop/10.0/help/index.html#//00nt00000002000000 ): using the conventional tools based on the Boolean logic, and using the tools based on fuzzy criteria (fuzzy numbers). Therefore we can appreciate that what these tools, actually, bring along, and how this approach differs from the classic process. Continue reading “Tutorial: create an aptitude map with ArcMap, with and without fuzzy criteria (1)”

How to set up Eclipse to develop QGis scripts or plugins

Eclipse software is an Eclipse Foundation project, developed and organized into a set of software sub-projects, to develop an open source software production environment that is open-ended, universal and versatile, relying mainly on Java.

As one of the great success stories of Open Source, Eclipse has become a standard in the development software market, built in by leading software publishers as well as service companies.

You can develop a plugin for QGis with a simple text editor, but if you want to have a real development environment, allowing you to quickly debug your scripts, Eclipse is the best solution.
Where to start? Continue reading “How to set up Eclipse to develop QGis scripts or plugins”

How to integrate free marine and terrestrial weather forecasts into QGis

In the previous article we discussed how   How to integrate free marine and terrestrial weather forecasts into ArcGis .
In this article we will discuss how to integrate these data into a QGis project . We will use 8- day marine forecast data. These data is provided by the companies   NASCA   and   ACTIMAR , via their  products  enav-forecast . In addition to the software that uses these forecasts and allows for their consultation and analysis ( enav-viewer ,   enav-forecast ,   enav-forecast for iPhone ,   enav -Pilot ), these companies also provide access to data via a WFS connection. Continue reading “How to integrate free marine and terrestrial weather forecasts into QGis”

How to create an animation of marine forecasts with QGis

We have discussed in a previous article,   How to integrate free marine and terrestrial weather forecasts into QGis , how to access, download and format the global marine forecast data proposed by the companies NASCA and Actimar  . For further details, visit www.enav-forecast.fr .
Now, we will discuss how to make an animation using these data with QGis and its Time Manager.

Once daily data is saved as shape format on your computer and added to your map, you must apply the desired symbology:
click on the layer -> Properties -> Style -> Load Style

In the previous article we have put at your disposal 3 QGis symbology files for wind, waves and currents.
If you have not already, you can download by   clicking here . Continue reading “How to create an animation of marine forecasts with QGis”

Exploratory data analysis for geostatics: trend analysis

Following the article   Introduction to  Exploratory data analysis for geostatistics   we will discuss each of the available tools to perform the exploratory analysis of the spatial data. We have discussed the  histograms ,    QQ-Plots , and Voronoï maps . Now, it is the turn for the data trends.

Trend? What is it?

Firstly we have to know what we are looking for. Certainly, you are already familiar with the notion of trend in the temporal series (the trend of unemployment is decreasing or increasing, etc …).

The topic here is spatial data processing. Therefore the notion of trend is a little different since we do not have, a priori, the variable time to organize our points in a temporal series. Continue reading “Exploratory data analysis for geostatics: trend analysis”

Exploratory data analysis for geostatistics: Voronoi diagrams

Following the article   Introduction to exploratory data analysis for geostatistics   we will discuss all the available tools to carry out the exploratory analysis of spatialized data. We have discussed   the histograms ,    the QQ-Plots , and now we will address the Voronoi maps.

We must introduce a notion not yet introduced in the previous articles that concerns the extent or influence of a phenomenon. In geostatistics we can consider two types of extension for a phenomenon: GLOBAL or LOCAL extent. Continue reading “Exploratory data analysis for geostatistics: Voronoi diagrams”

Exploratory analysis of data for geostatistics: the QQ-plot

Following the article   Introduction to exploratory data analysis for geostatistics   we   will discuss each of the available tools to carry out the exploratory analysis of spatial data. We have already discussed  the histograms , and now we will address the QQ-Plots.

QQ-Plots (or Quantile-Quantile Diagrams) are graphs in which the quantiles of two distributions are plotted against each other. Continue reading “Exploratory analysis of data for geostatistics: the QQ-plot”

ArcHydro : 2- Preparing a corrected DTM for hydrology – Part 1

A  Digital Terrain Model is a representation of the elevations of a territory. Each cell (pixel) of this DTM contains a height value. According to the generation means used for the surface and the allocated size ofr the cells, the height assigned to each one is more or less close to the exact reality.

If you want to use the DTM for a 3D view of the territory (ith ArcScene, for example), you can use it as it is and without any special precaution. By cons, if you want to model the water flow on the surface of this territory, the first thing to do, and the most important is to correct and adapt it to this objective.

What you will be doing during this step will define the quality of the results obtained regarding the watersheds and the different hydrological calculations available. Continue reading “ArcHydro : 2- Preparing a corrected DTM for hydrology – Part 1”