{"id":5483,"date":"2018-06-11T21:11:44","date_gmt":"2018-06-11T19:11:44","guid":{"rendered":"http:\/\/www.sigterritoires.fr\/?p=5483"},"modified":"2021-08-11T11:15:46","modified_gmt":"2021-08-11T09:15:46","slug":"bivariate-display-with-arcgis","status":"publish","type":"post","link":"https:\/\/www.sigterritoires.fr\/index.php\/en\/bivariate-display-with-arcgis\/","title":{"rendered":"Bivariate display with ArcGis"},"content":{"rendered":"

It is not easy to visualize a\u00a0bivariate\u00a0map with ArcGis\u00a0, i.e a map where the entities are categorized according to two variables located in two independent layers.<\/p>\n

The colour assigned to each entity responds to a colour scale along two axes, X and Y:<\/p>\n

$\"\"$ <\/p>\n

Therefore each layer must be classified according to four classes.\u00a0The entities which belong to the first class of each of the layers share the colour located at the bottom and left, those belonging to the strongest class of each layer will have the colour located at the top and on the right.<\/p>\n

You do not have standard tools in\u00a0ArcGis\u00a0for this chore but a treatment model can resolve this\u00a0absence.\u00a0The treatment model that we propose is based on an original\u00a0TWSAdmin\u00a0idea\u00a0published at https:\/\/geonet.esri.com\/groups\/cartography-and-maps\/blog\/2015\/09\/09\/bivariate-mapping<\/a><\/p>\n

We have worked this model so that we can use it without prior editing, by supplementing it to take into account a classification of 4 \u00d7 4 and 6 \u00d7 6 classes and, finally, by translating and documenting it.<\/p>\n

Here is the basic model:<\/p>\n

$\"\"$ <\/p>\n

The principle is simple: with the tool create a grid, \u00a0we create a two-dimensional grid of 4 \u00d7 4 cells (or 6 \u00d7 6) covering the considered area.\u00a0The two rasters are reclassified according to the number of columns, then\u00a0by the number of rows.\u00a0One of the two values \u200b\u200bis multiplied by 10 and the two reclassified rasters are added together.\u00a0The raster is converted into polygons and combined with the two-dimensional mesh.\u00a0Finally, we merge\u00a0the polygons\u00a0according to the value of the mesh.<\/p>\n

Tool download <\/strong><\/h2>\nCllick here to download\u00a0\u00a0 TbxBivarie<\/a><\/p>\n
The file downloaded contains a\u00a0toolbox\u00a0with two models: one allowing a mesh of 4 \u00d7 4 cells and another a mesh of 6 \u00d7 6.<\/p>\n
You have a\u00a0toolbox\u00a0for\u00a0ArcGis\u00a010, another for 10.1-10.2 and one for 10.3.<\/p>\n
You also have two\u00a0symbology\u00a0files\u00a0, one for the 4 \u00d7 4 grid and another for the 6 \u00d7 6 grid.<\/p>\n
Finally you have two images representing the two grids to use as legend of the result obtained.<\/p>\n
Example and how to use the tool<\/strong><\/h2>\n
Let’s start with what you need to do before launching the tool:<\/p>\n
1-Load the two raster layers you want to process.<\/p>\n
For the example we will take the Slope layer and the ground Occupation layer that we used for Spatial\u00a0Analyst\u00a0articles\u00a0and fuzzy logic (\u00a0 Tutorial: create an aptitude map with\u00a0ArcMap\u00a0, with and without fuzzy criteria (1)<\/a>\u00a0) .<\/p>\n
$\"\"$ <\/p>\n
Land Occupation<\/p>\n
$\"\"$ <\/p>\n
Slope<\/p>\n
2-Locate the XY coordinates of the top left corner and bottom right corner of your rasters.<\/p>\n
$\"\"$ <\/p>\n
Add the Toolbox for your version of\u00a0ArcGis:<\/p>\n
$\"\"$ <\/p>\n
4-Decide what type of classification you want for each of the rasters.\u00a0You have the choice between three classification methods: classes of equal size, classes of equal areas and classes according to the natural thresholds.\u00a0The choice of method is related to the type of data and the objectives of your work.<\/p>\n
Here we will choose classes of equal size.\u00a0So the classification will be similar to the one we made with fuzzy number tools, ie classifying the slope into 4 classes, whose limits can be associated\u00a0with\u00a0satisfaction\u00a0values: null, modest, good, very good, and excellent.<\/p>\n
5-Create a\u00a0file\u00a0geodatabase\u00a0where intermediate operations will be performed.\u00a0You can also use an\u00a0existing\u00a0geodatabase\u00a0because only the result is retained after the model runs.<\/p>\n
You can launch the tool.\u00a0This setting window appears:<\/p>\n
$\"\"$ <\/p>\n
At the origin coordinate of the mesh you have to enter the XY coordinates of the top left corner marked in point 2.<\/p>\n
At the Y axis coordinates, remove a few meters at the X coordinate of the mesh origin and add a few meters to the Y coordinate of the mesh origin.<\/p>\n
In coordinates of the opposite corner, enter the coordinates listed in point 2.<\/p>\n
Select the two rasters to process and the ranking method to apply.<\/p>\n
Specify the\u00a0file\u00a0geodatabase\u00a0to use for intermediate calculations.<\/p>\n
Indicate the location and the output name of the resulting polygons layer.\u00a0You can specify a different\u00a0geodatabase\u00a0from the one used for intermediate calculations.<\/p>\n
Click OK.<\/p>\n
Usually, the result layer should be displayed, but that will have to wait for future versions of\u00a0ArcMap\u00a0to be sure.\u00a0So\u00a0if\u00a0it does not appear automatically, charge the result layer and import the legend provided with the toolbox (Bivariate_4_classes.lyr)<\/p>\n
$\"\"$ <\/p>\n
As for the tool, it’s over.\u00a0However, the legend used by\u00a0ArcMap\u00a0is not very explicit.\u00a0We will cheat a little to have a more meaningful presentation.<\/p>\n
We will add a legend image and a legend text, but in the map window.<\/p>\n
Add a copy of the image supplied with the tool (caption4classes.png).\u00a0You will get a message saying the image is not\u00a0georeferenced\u00a0.\u00a0Click OK.<\/p>\n
Add the\u00a0Georeferencing\u00a0toolbar.<\/p>\n
$\"\"$ <\/p>\n
In the menu that appears, make sure that you are well positioned on the image you just loaded.<\/p>\n
Open the\u00a0Georeferencing\u00a0menu\u00a0and click Fit to display.<\/p>\n
$\"\"$ <\/p>\n
This brings the image into the map window.<\/p>\n
$\"\"$ <\/p>\n
You will use the image moving tools to reduce and move the image next to your result layer<\/p>\n
$\"\"$ <\/p>\n
With\u00a0Scale\u00a0you reduce the size of the image and with Shift you move it next to your result layer.<\/p>\n
$\"\"$ <\/p>\n
When you are satisfied, open the\u00a0georeferencing\u00a0menu\u00a0and click Update\u00a0Georeferencing\u00a0.<\/p>\n
Your image is now\u00a0georeferenced\u00a0and each time you load it into\u00a0ArcMap\u00a0,\u00a0ArcScene\u00a0, and\u00a0so on\u00a0, it will be placed here.<\/p>\n
To complete the legend, you can create a layer of annotations and enter the texts you want.\u00a0Since the annotation layer is geographical, the texts will always be placed in the same place.<\/p>\n
On the result map, you can highlight any\u00a0area that\u00a0corresponds to a class in the legend by simply clicking the selection tool on one polygon of the class.\u00a0This highlights all the polygons in the class:<\/p>\n
$\"\"$ <\/p>\n\n","protected":false},"excerpt":{"rendered":"
It is not easy to visualize a\u00a0bivariate\u00a0map with ArcGis\u00a0, i.e a map where the entities are categorized according to two variables located in two independent layers. The colour assigned to each entity responds to a colour…<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"give_campaign_id":0,"_bbp_topic_count":0,"_bbp_reply_count":0,"_bbp_total_topic_count":0,"_bbp_total_reply_count":0,"_bbp_voice_count":0,"_bbp_anonymous_reply_count":0,"_bbp_topic_count_hidden":0,"_bbp_reply_count_hidden":0,"_bbp_forum_subforum_count":0,"sfsi_plus_gutenberg_text_before_share":"","sfsi_plus_gutenberg_show_text_before_share":"","sfsi_plus_gutenberg_icon_type":"","sfsi_plus_gutenberg_icon_alignemt":"","sfsi_plus_gutenburg_max_per_row":"","_monsterinsights_skip_tracking":false,"_monsterinsights_sitenote_active":false,"_monsterinsights_sitenote_note":"","_monsterinsights_sitenote_category":0,"_jetpack_newsletter_access":"","_jetpack_dont_email_post_to_subs":false,"_jetpack_newsletter_tier_id":0,"_jetpack_memberships_contains_paywalled_content":false,"_jetpack_memberships_contains_paid_content":false,"footnotes":"","jetpack_post_was_ever_published":false},"categories":[1260],"tags":[],"class_list":["post-5483","post","type-post","status-publish","format-standard","hentry","category-non-classe-en"],"aioseo_notices":[],"jetpack_featured_media_url":"","jetpack_shortlink":"https:\/\/wp.me\/p6XU0A-1qr","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/www.sigterritoires.fr\/index.php\/wp-json\/wp\/v2\/posts\/5483","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.sigterritoires.fr\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.sigterritoires.fr\/index.php\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.sigterritoires.fr\/index.php\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.sigterritoires.fr\/index.php\/wp-json\/wp\/v2\/comments?post=5483"}],"version-history":[{"count":0,"href":"https:\/\/www.sigterritoires.fr\/index.php\/wp-json\/wp\/v2\/posts\/5483\/revisions"}],"wp:attachment":[{"href":"https:\/\/www.sigterritoires.fr\/index.php\/wp-json\/wp\/v2\/media?parent=5483"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.sigterritoires.fr\/index.php\/wp-json\/wp\/v2\/categories?post=5483"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.sigterritoires.fr\/index.php\/wp-json\/wp\/v2\/tags?post=5483"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}