When using leaflet-react WMSTileLayer (with Geoserver as the WMS server) I appear to have different contrasts for the various tiles, creating visible 'borders' between tiles as below.
Leaflet-React:
If i use the layer view within Geoserver i get a nice flat set of tiles.
Built-in GeoServer viewer:
I'm using a very simple example just as a test for now:
I'm not super up to speed with all of the intricacies of react, or leaflet, so I have struggled a bit with the leaflet-react docs, so I've likely missed something pretty simple, for example I haven't found out how to use png instead of jpeg.
After 3 days, I decide to post. Then solve it 2 hours later.
Issue here is due to GeoServer (helpfully) applying its own ColorMap to each tile that is being requested. Solution is to specify a fixed ColorMap in the relevant Style:
<ColorMap>
<ColorMapEntry color="#323232" quantity="-300" label="label1" opacity="1"/>
<ColorMapEntry color="#BBBBBB" quantity="200" label="label2" opacity="1"/>
</ColorMap>
Solution from here:
https://gis.stackexchange.com/questions/308217/geotiff-rendered-in-openlayers-using-geoserver-tiles-have-different-brightness
Related
Mapbox studio has a style with an Albers projection (https://www.mapbox.com/elections/albers-usa-projection-style):
I need to use another style with waterbodies like this:
but in the Albers projection. When I start with the Albers style, and then add water, they of course don't line up:
How can I get the tile I used in my waterbody example to be in the Albers project? I ultimately am wanting to use it in a leaflet map and add markers to it (using R).
The example you cited above is actually showing a workaround to make data appear as if it is projected in Albers but it's really just altered polygons being displayed in webmercator. This was a workaround/hack to get the desired visual using the tools available at the time. If you want to do the same workaround for your water bodies data so it will appear this way in leaflet, follow the steps of the tutorial which uses third party tools (QGIS, Dirty Reprojectors, Tippecanoe)
Mapbox has since added support for non-webmercator projections, which means you don't need to modify your source data to reproject them for use in a mapboxgl-js map: https://docs.mapbox.com/mapbox-gl-js/example/projections/
Disregard the earlier example, and just change the projection to Albers in Mapbox Studio.
Bear in mind that changing the projection in Mapbox Studio does not actually modify your data, it just renders it differently on the screen.
I am trying to plot both the labels and the ECG using Web Flutter. ECG plotting is happening properly but not the annotations. Can someone suggest me something for this? It should look something like this.
Found a library call syncfusion. It shows how to add multiple annotations. But the annotation that I am using is a list.
We have created a simple sample by using annotations in the chart. We have provided two annotations in the annotation list such as high and low texts for the high and low values in the chart. The two annotations are provided in the annotation property available in the chart which takes a list of type CartesianChartAnnotation.
The sample for reference can be found below.
Sample
And, we have analyzed the mentioned query ECG plotting is happening properly but not the annotations, but we are not sure of what exactly you are conveying. So, we request you to provide more detailed information for this query so that it will be helpful in providing the solution sooner.
I want to create a polarplot() on which I want to plot custom bitmaps/images as marker.
Also, I want to animate the polarplot() by updating these marker's location in regular time intervals(500milliseconds).
Please see the below attached image to get an idea what I want.
SamplePlotExample.jpg
I have made a similar application using 'polar()' and 'imagesc()'.
But I feel 'polarplot()' is better and recommended by Matlab.
Also there are so many customization options available with polarplot().
But I am unable to use imagesc() with polarplot because of some polar coordinate-to-cartersian coordinate conversion problem.
Pleas give solution.
Is there any other better methods to follow?
I have been rendering a FeatureCollection of polygons into the Map (in one GeoJSONLayer). The size of each polygon is big (5mb, 10mb). With user interactions, the colours of polygons would be re-calculated & changed constantly. We are using data-driven method and keeping the data in properties of each feature. So GeoJSONLayer has to call .setData(geojson) everytime the data and colours changed (they are kept in properties).
I find above approach is lead to performance issue since the size of geojsons is big and calling .setData() is expensive.
I'm thinking of separating the geojson source and the data, style, colouring and calling direct function (setPaintProperty) whenever colours changed would be better than.
Someone told me that .setData and .setPaintProperty would do the same thing, both 2 will trigger re-rendering whole polygons.
Kindly need help to advice on this matter
Thanks a lot!
If I understand you correctly, you're asking which of these two is faster:
map.setData(mylayer, mygeojson)
map.setPaintProperty(mylayer, 'fill-color', ...mydatadrivenproperty)
I haven't tested, but I'd assume the second is faster, because the first one has to:
Parse the GeoJSON
Convert it to vector tiles
Repaint
whereas the second just has to parse the property repaint. Try them both out to see.
You may also consider a third way, which is to have a second layer which is a highlight, which you update by calling map.setFilter(mylayer, ...).
I have 2 shapefiles. One is the contors of an area and the other the spot heights. Both of them has a altitude attribute. In ArcGIS there is a tool called topo to raster were you can use both these features to create a dem. In qgis I have only found tools were you can only use one.
Any Ideas?
There is only the interpolation tool that I know of which will create a DEM. Depending on the resolution you're after, you could BUFFER the spot heights, then MERGE SHAPE FILES and run the interpolation tool on that.
Using the graphical modeler would prevent the buffer layer being created making the process a little tidier (and i'm sure there's a better way using the python console). Hope this helps.