Starting with Geoserver

We have discussed how to start with Postgresql / Postgis. Once you have
your database, the next most common need is to upload online the data.

Of course, there are many technical possibilities to do this. To keep
within the most standard, the WFS and WMS streams setting from Postgresql /
Postgis data is one of the most robust ways.

Therefore, we will now see how to start with Geoserver.

NOTE: The original article was written for
Geoserver version 2.8.
I updated it on 9/9/2016 to take into account the installation
changes for version 2.9.1.


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Cutting rasters using ArcGis How to cut rasters in ArcMap?

You could be
surprised
but,
actually, there are two ways to cut rasters in ArcMap.
The
classical technique is the
“raster clip” (“raster
cutting”) tool in ArcToolbox.
This has been the only procedure for a long time.
But
since version 10, you have at your disposal the “Image
Analysis” tool in the standard toolbar. This tool
contains
also
a way to cut out rasters and pictures.
The
main advantage of the images analysis toolbar is that you can
see
the final result before exporting it!

We will discuss both methods,
by cutting a part
of the orthophoto coastline of the IGN with the
municipalities’ boundaries of Pont-Aven.

First method: ArcToolbox: clip Raster tool

In ArcToolbox (Data
Management> Raster> Raster Processing> Clip), double-click the clip
tool.


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Start with PostgrSQL / Postgis -Introduction to pgAdmin3

Following a previous article ( Start with Postgres / Postgis ), we will discuss
an introduction to the administration of Postgres / postgis databases, the
loading of a shapefile and the connection and loading of the Postgis layer from
QGis.

An update of
this
article using
pgAdmin 4 is available by following this link.

The most convenient way for administrating PostgreSQL databases is to
use the pgAdmin3 graphic interface.

This tool is installed automatically when
PostgreSQL is installed. It can launched from the program bar:


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GIS and decision support (1): classifying with fuzzy numbers

Decision processes are based on information from very diverse source and
type. This information is used by the decision-makers to perform   choices,
i.e. to retain a certain number of entities and to exclude others.

Let’s discuss the following example:
An action must be performed on municipalities, but this action depends on: 1. the area of ​​the communes, between 2500 and 3000 hectares
2. the number of inhabitants of the municipality, between 2500 and 5000
The purpose of the operation is to perform a classification of objects (municipalities)
according to two criteria (population and area).


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GIS and decision support (2): the crossing of two fuzzy criteria

Let’s reconsider our example regarding the towns ranking
for the Finistère region according to the following two criteria: population
and area.

How to rank entities according to a single criterion

To establish the fuzzy number allowing the
classification of the towns according a single criterion, we rely on our assessment
of two qualities: the complete satisfaction of the criterion (1) or the complete
dissatisfaction (0).

By accomplishing this task, we have generated a complete
series of intermediate values, between 0 and 1. Working with numbers is not
easy but, above all, it is not natural. Let’s say that a town meets the 0.356
surface criterions and that the town surface is rather unsatisfactory, it does
not affect the classification process but it sure does the operator.


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GIS and decision support (3): a tool to create fuzzy criteria with ArcMap

In the two previous articles ( GIS
and decision support (2): the crossing of two
fuzzy criteria
, and GIS
and decision support (1): ranking with fuzzy numbers
), we have discussed examples for using fuzzy
logic to process geographic information .
It is time to get your hands dirty. This is why we put, here, at your
disposal an ArcGIS command to create a fuzzy criterion.
 

In a second stage (the next
article) we will discuss how to perform the
aggregation of two fuzzy criteria with another command, which we will put at
your disposal as well.

As
we have seen in the examples discussed in previous articles, the first step to
process the information as fuzzy is to transform the values of a classic attribute into a fuzzy number:


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GIS and decision support (4): a tool for aggregating fuzzy criteria with ArcMap

In this article we will discuss how to cross two fuzzy attributes, with
a command that we put at your disposal. The “Flexible Aggregation”
command allows the aggregation of two fuzzy criteria.
The interface offers three questions to the user to define the desired
aggregation formula. Then, the tool proceeds to the union or intersection of
the two criteria by producing a new data layer. This layer contains the data of
the two input layers plus one field with the result of the calculated
aggregation.
It is essential to create the fuzzy criteria before proceeding with their
aggregation.
In the case of non-numeric criteria, a manual transformation has to be executed
by the user to match numeric codes to the text attributes.


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GIS and decision support (7): a tool to create fuzzy qualitative criteria with ArcMap

In a previous article, GIS and Decision Support (3): A tool for creating fuzzy
criteria with ArcMap
, we have seen a tool for transforming numeric
attribute into a soft attribute (fuzzy number).
In this article we will discuss and put at your disposal the last one that
makes it possible to create a soft attribute (fuzzy number) starting from a
text attribute containing a classification of the entities.
 

The tool is composed of a command, “Text criterion”,
that makes it possible to transform a textual criterion into a fuzzy number.
The original criterion is a text field of a layer of a feature class. The
contents of this field include classified values ​​that will be transformed
into another field, numeric, but with values ​​within the range 0-1. This
transformation takes place to match the values ​​of the origin field with a
degree of satisfaction of the field, criterion: 1 corresponds to a total
satisfaction, 0 to a total dissatisfaction, the other values ​​being partial
satisfactions.


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GIS and Decision Support (6): Theoretical Fundamentals (Part 2)

 

This article is the direct continuation of the: GIS and decision support (5): Theoretical Fundamentals (Part 1)

Aggregation example.

We consider the aggregation of the criterion “bathymetry” as it is shown in Figure 2, and another criterion, for example, the substrate that is defined according to a particle size scale:

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