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This allows users of the map to quickly see the properties of numerous features. +The process of data classification lets you give features distinct symbols. i.e., various things in the same layer according to their characteristics. **This makes it possible for users to view the qualities of many features on the map rapidly**. Cartographic visualization that considers the individual and thematic elements of each layer is called data style. **It includes fundamental symbology features including fill color and presence, outline parameters, marker use, scale-dependent rendering, transparency of layers, and interactions with other layers**. + [Source](https://hub.packtpub.com/style-management-qgis/) -In QGIS, a style is a way of cartographic visualization that takes into account a layer’s individual and thematic features. It encompasses basic characteristics of symbology, such as the color and presence of fill, outline parameters, the use of markers, scale-dependent rendering, layer transparency, and interactions with other layers. [Source](https://hub.packtpub.com/style-management-qgis/) +## Single symbol classification -## The Goal of Data Classification +This is the default rendering, where all of the features in a layer are displayed using a single symbol. Additionally, it lets you select a single style that will be used for all of the layer's characteristics. -The basic goal of a classification scheme is to group together similar observations and split apart observations that are substantially different. In more technical terms, the goal is to find the optimal number of classes and where to put the breaks between those classes so as to minimize within group variance and maximize between group differences. For instance, if I had a data set with 4 observations of 1.3, 1.6, 3.5 and 3.9, many folks would be inclined to split those observations into 2 groups with 1.3 and 1.6 in the first group and 3.5 and 3.9 in the second because that pairing makes sense given the large numerical gap in the middle of the data range. Such an approach is common and is called “maximum breaks.” +This video demonstrate a single symbol classification. -However, there are often other considerations when classifying our data and simply maximizing between group differences may not be the primary goal: In the example above, it might be possible that 1.5 is a critical value and all that matters is to distinguish between locations above and below that critical break point (e.g., if a location has a reading below 1.5 they might be eligible for emergency funding). In this case, external constraints over-ride our mathematical solutions and despite being fairly close together 1.3 and 1.6 would now be placed in different classes since they straddle that breakpoint. + -```{Note} -Remember: -``` +Additionally, the below screenshot shows the steps from number 1 to number 10 on how to classify data from the Layer menu. -If you are going to classify your data you must decide both the number of classes and the method for breaking your data into ranges. +![](/fig/Single_symbol_classify.png) -[Source](https://www.axismaps.com/guide/data-classification) +## Categorized classification -## Importance of data classification +The discrete values of an attribute field that specify how each feature should be presented serve as the basis for categorized stylings. The layer's characteristics will display in various color tones according to distinct values in an attribute field. **Each category can have a different label, color, or symbol applied to it**, and QGIS will automatically divide your data into discrete groups. -Data Classification is used to group a large number of observations into data ranges or classes. It is a useful tool to structure the data for choropleth maps automatically and it helps to reduce the information content. It allows to make the presentation of values much clearer. Individual observations are lost, small differences can be reduced and large ones can be emphasized and evaluated better. Distributional characteristics and the psychology of perception are taken into account. [Source](https://cartography-playground.gitlab.io/playgrounds/data-classification-methods/) +This video demonstrate how the categorized classification can be done. -## How to classify data? - -To style or classify in Qgis, you must have an existing shapefile in your Qgis layer or upload the shapefile of the data you want to classify via Layer menu, then add layer, then add vector layer and under source botton, upload the shapefile that you intends to classify or style, then click ok and you can now see it in the layer panel. -The picture below shows the Sierra Leone food insecurity 2015 shapefile that we can to classify in the layers pannel. - -![](/fig/SierraLeone_shapefile_in_layer_pannel.png) - -* Right click on the shapefile in the layer pannel and then property - -![](/fig/View_of_properties_from_layer_pannel.png) - -* Then a layer properties will pump up. Click on symbology and select the type of classification or style that you want from circle 1. - -![](/fig/Layer_properties.png) + +The below screenshot shows the overview of the steps of the categorized classification. -* Additionally, you can choose from single symbol, categorized and graduated in order to classify your data. Just next to it you will see color where you can choose color of your choice. At the bottom left-down, there is classify icon which allow you to classify different features in the layer to your choice. This classify icon can only work if you choose categorized or graduated style from up. +![](/fig/Categorized_district_map_SierraLeone.png) -![](/fig/Style_selection.png) -* Below the syle option, you can also select the value, symbol and the color ramp that you want +## Graduated classification -![](/fig/Value_and_Symbol_selection.png) +Graduated styles dictate how each feature should be presented based on continuous values in an attribute field. Your data will be automatically classified into intervals or classes by QGIS, allowing you to give a variety of symbols, colors, or sizes to each value. When you want to clearly distinguish between features with attribute values in various value ranges, graduated symbols come in handy. The GIS Application will analyze the attribute data (height, for example) and construct groups for you based on how many classes you require. -* Once you click on classify, you can then now see all the classify features of your data. You can change the color of any of this categorized features by right click and go to change color and select any color that you want. Apply and click ok +See the below video of graduated classes classification -![](/fig/Change_feature_color.png) + +* This screenshot shows the steps of graduated classification by classes. -### Categorized classification +![](/fig/Graduated_classify_classes.png) -* The below screenshot shows the overview of the categorized map +From **step 1** where you select graduated uptill **step 13** where you can see the classified outcome. You can play and change variables within the stages and use any parameter that suits your goal. -![](/fig/Categorized_district_map_SierraLeone.png) +More so, there is no single correct number of classes, there is no single best way to classify you data into ranges. To acheive the goal of classification, the data can be best classify by **equal interval, quantile, natural breaks and or manual** depending on what suits your purpose. -See video of classification by categorized +![](/fig/Classification_methods.PNG) - +* Graduated classification by histogram +![](/fig/Graduated_classify_histogram.png) +You can show the mean value and standard deviation through this classification. +See outlook of histogram by graduated classification. -### Graduated classification +![](/fig/Graduated_histogram.png) -Graduated styles are based on continuous values of an attribute field that define how each feature should be rendered. You can assign a range of symbols, colors, or sizes to each value, and QGIS will automatically classify your data into intervals or classes. Graduated symbols are most useful when you want to show clear differences between features with attribute values in different value ranges. The GIS Application will analyse the attribute data (e.g. height) and, based on the number of classes you request, create groupings for you. -See the below video of graduated classes classification +See the video of graduated classes and histogram classification. - + diff --git a/content/Modul_3/en_qgis_data_classification.html b/content/Modul_3/en_qgis_data_classification.html index 0edd1ebc7..2a8c628a1 100644 --- a/content/Modul_3/en_qgis_data_classification.html +++ b/content/Modul_3/en_qgis_data_classification.html @@ -471,13 +471,9 @@
Data classification is the process that allows you to assign different symbols to features. i.e. different objects in the same layer based on their properties. This allows users of the map to quickly see the properties of numerous features.
-In QGIS, a style is a way of cartographic visualization that takes into account a layer’s individual and thematic features. It encompasses basic characteristics of symbology, such as the color and presence of fill, outline parameters, the use of markers, scale-dependent rendering, layer transparency, and interactions with other layers. Source
-The basic goal of a classification scheme is to group together similar observations and split apart observations that are substantially different. In more technical terms, the goal is to find the optimal number of classes and where to put the breaks between those classes so as to minimize within group variance and maximize between group differences. For instance, if I had a data set with 4 observations of 1.3, 1.6, 3.5 and 3.9, many folks would be inclined to split those observations into 2 groups with 1.3 and 1.6 in the first group and 3.5 and 3.9 in the second because that pairing makes sense given the large numerical gap in the middle of the data range. Such an approach is common and is called “maximum breaks.”
-However, there are often other considerations when classifying our data and simply maximizing between group differences may not be the primary goal: In the example above, it might be possible that 1.5 is a critical value and all that matters is to distinguish between locations above and below that critical break point (e.g., if a location has a reading below 1.5 they might be eligible for emergency funding). In this case, external constraints over-ride our mathematical solutions and despite being fairly close together 1.3 and 1.6 would now be placed in different classes since they straddle that breakpoint.
-Note
-Remember:
-If you are going to classify your data you must decide both the number of classes and the method for breaking your data into ranges.
- +The process of data classification lets you give features distinct symbols. i.e., various things in the same layer according to their characteristics. This makes it possible for users to view the qualities of many features on the map rapidly. Cartographic visualization that considers the individual and thematic elements of each layer is called data style. It includes fundamental symbology features including fill color and presence, outline parameters, marker use, scale-dependent rendering, transparency of layers, and interactions with other layers. +Source
Data Classification is used to group a large number of observations into data ranges or classes. It is a useful tool to structure the data for choropleth maps automatically and it helps to reduce the information content. It allows to make the presentation of values much clearer. Individual observations are lost, small differences can be reduced and large ones can be emphasized and evaluated better. Distributional characteristics and the psychology of perception are taken into account. Source
+This is the default rendering, where all of the features in a layer are displayed using a single symbol. Additionally, it lets you select a single style that will be used for all of the layer’s characteristics.
+This video demonstrate a single symbol classification.
+ +Additionally, the below screenshot shows the steps from number 1 to number 10 on how to classify data from the Layer menu.
+To style or classify in Qgis, you must have an existing shapefile in your Qgis layer or upload the shapefile of the data you want to classify via Layer menu, then add layer, then add vector layer and under source botton, upload the shapefile that you intends to classify or style, then click ok and you can now see it in the layer panel. -The picture below shows the Sierra Leone food insecurity 2015 shapefile that we can to classify in the layers pannel.
- -Right click on the shapefile in the layer pannel and then property
Then a layer properties will pump up. Click on symbology and select the type of classification or style that you want from circle 1.
Additionally, you can choose from single symbol, categorized and graduated in order to classify your data. Just next to it you will see color where you can choose color of your choice. At the bottom left-down, there is classify icon which allow you to classify different features in the layer to your choice. This classify icon can only work if you choose categorized or graduated style from up.
Below the syle option, you can also select the value, symbol and the color ramp that you want
Once you click on classify, you can then now see all the classify features of your data. You can change the color of any of this categorized features by right click and go to change color and select any color that you want. Apply and click ok
The below screenshot shows the overview of the categorized map
See video of classification by categorized
+The discrete values of an attribute field that specify how each feature should be presented serve as the basis for categorized stylings. The layer’s characteristics will display in various color tones according to distinct values in an attribute field. Each category can have a different label, color, or symbol applied to it, and QGIS will automatically divide your data into discrete groups.
+This video demonstrate how the categorized classification can be done.
+The below screenshot shows the overview of the steps of the categorized classification.
+Graduated styles are based on continuous values of an attribute field that define how each feature should be rendered. You can assign a range of symbols, colors, or sizes to each value, and QGIS will automatically classify your data into intervals or classes. Graduated symbols are most useful when you want to show clear differences between features with attribute values in different value ranges. The GIS Application will analyse the attribute data (e.g. height) and, based on the number of classes you request, create groupings for you.
+Graduated styles dictate how each feature should be presented based on continuous values in an attribute field. Your data will be automatically classified into intervals or classes by QGIS, allowing you to give a variety of symbols, colors, or sizes to each value. When you want to clearly distinguish between features with attribute values in various value ranges, graduated symbols come in handy. The GIS Application will analyze the attribute data (height, for example) and construct groups for you based on how many classes you require.
See the below video of graduated classes classification
-This screenshot shows the steps of graduated classification by classes.
From step 1 where you select graduated uptill step 13 where you can see the classified outcome. You can play and change variables within the stages and use any parameter that suits your goal.
+More so, there is no single correct number of classes, there is no single best way to classify you data into ranges. To acheive the goal of classification, the data can be best classify by equal interval, quantile, natural breaks and or manual depending on what suits your purpose.
+ +Graduated classification by histogram
+You can show the mean value and standard deviation through this classification. +See outlook of histogram by graduated classification.
+ +See the video of graduated classes and histogram classification.
+