Plotting the estimated slopes, as in the question, is a great thing to do. Rather than filtering by significance, though--or in conjunction with it--why not map out some measure of how well each regression fits the data? For this, the mean squared error of the regression is readily interpreted and meaningful.
As an example, the R code below generates a ...
Uhm, you can work in PostGIS to give a better structure to the database.
Create a table S (stations) with the following fields:
Location (a point that specifies the coordinates)
Create another M (measurements) table with the fields:
MeasurementDT (date and time of the measurement)
Value (measured value)
Now, you can show all the ...
Historical OSM data is available in the OpenStreetMap Full History Dump file. You can dowload it as *.pbf or *.xml data. Extracs of selected countries can be downloaded from http://osm.personalwerk.de/full-history-extracts/ or from http://odbl.poole.ch/extracts/. I recommend you the OSM-history-splitter to generate extracts out of *.osh files and the OSM-...
Expression to_datetime("Date_Field") + to_interval('10 hours') will add 10 hours to the "Date_Field".
I have not tested fully, but it seems to_interval() accepts month(s) day(s) hour(s) and their combinations such as '1 day 2 hours'.
You could have a look at the Targomo API (formerly Route360˚), a pretty simple but powerful JS library which you can use with Leaflet (or even Google maps if you like).
It adds travel time polygons to your map for the travel times you require (e.g. 10, 20, 60 minutes) and for the following travel modes: walk, bike, car, transit.
There are quite a few ...
When remote sensing vegetation, the time of year is very important. In most climates, vegetation has significantly more biomass (i.e., leaves etc.) during the summer, which means that it is easier for the sensor to discern the health of vegetation at that time of year. Two NDVI images of the same location from different times of the year may look different ...
Your plan is fine. A traditional way to handing the "end date" is to leave it NULL, so every geometry has a start and end, and those that have been superseded have a non-NULL end point. Here's a very simple temporal model.
If you're going to be doing a lot of temporal querying, looking into ...
It's possible without using a python function, with a little bit of hacks:
minute( age( todatetime('2000-01-01 10:18:00'), todatetime(2000-01-01 10:16:30') ) )
will return "1.5".
To break it down, "age" returns the difference between two datetimes as an interval type. This needs to be wrapped in the "minute" function to extract the length of this interval ...
The current GeoJSON specification is geojson.org/geojson-spec.html and it defines "positions" as
A position is represented by an array of numbers. There must be at
least two elements, and may be more. The order of elements must follow
x, y, z order (easting, northing, altitude for coordinates in a
projected coordinate reference system, or longitude, ...
There is some detailed information here, on the ICSM page on datum modernisation.
Note importantly the two stage implementation:
The GDA2020 datum will result from a readjustment of the entire
national geodetic network to a reference epoch of 1 January 2020. This
will correct regional decimetre–level biases remaining in GDA94, ...
Yes, the CF 1.6 Conventions for NetCDF include the specification of collections of time series and it seems your data is similar to example H.2.1 "Orthogonal multidimensional array representation of time series":
If you store your data this way, IDV should be able to recognize this as "point data". Hopefully more applications in the future will take ...
Yep, it is totally possible! Here are two examples with the same dataset, one is for changing intensity over time,
The second is more like you request (I think) and shows cumulative amount over time
I don't think there is a way to do that for a particular date field, and this link provided by Get Spatial confirms it. However, if you turn on Editor Tracking, it will create fields for:
Last Edit Date
You have the option to name these fields to whatever you want. So, you could call the Created Date Field "Date Notified"...
There is an ArcGIS add-on developed by the USGS Upper Midwest Environmental Sciences Center called Curve Fit: A Pixel Level Raster Regression Tool that may be just what you are after. From the documentation:
Curve Fit is an extension to the GIS application ArcMap that allows
the user to run regression analysis on a series of raster datasets
Reproducing the map example you provided is primarily a cartographic effort and requires very little analysis if you have already calculated NDVI. I would use the following workflow to produce the map similar to the one you provided a link to.
Collect the NDVI data to use in your analysis. In the example, they
use "Summer" 1989 to 2001. In your case, you ...
Thanks for reply. I didn't know this log file. Really a great help!
Here is the solution for my problem:
Wow this is very fun and... extremely hard for me. Assuming "arrival" as your Arrival time field:
Wrapping the above into single expression, it ...
What you are describing is "Change Detection". There are many techniques for change detection using rasters. Probably the most common is image differencing where you subtract one image from another to produce a third. Though, it depends upon the type of data you are trying to compare. From your image, it looks like you're comparing changes in slope over ...
I suspect that you might actually want a WMS rather than a WCS (since you say raster images rather that raster data, and are currently using Google maps).
If all you want to do is display the images over time (using a slider or some such to control the time) then Openlayers and almost any WMS (GeoServer, MapServer, ArcGIS Server etc.) will handle this.
The date_trunc works in PostgreSQL:
# SELECT date_trunc('year', timestamp '2001-11-16 20:38:40' + interval '2 months');
While in SQLite it gives the error you get:
> SELECT date_trunc('year', timestamp '2001-11-16 20:38:40' + interval '2 months');
Error: near "'2001-11-16 20:38:40'...
Data sets like this can give very much information of course.
I would do this in a spatial database environment, preferably PostgreSQL/PostGIS.
What you want to do seems like a simple joining on both spatial and time data.
Then you do everything in one query. The tricky part might be to optimize the indexes for the time joining. I guess the data sets is ...
Yes, the NetCDF CF Metadata Conventions version 1.6 specifies how to store point and station time series data in chapter 9 "Discrete Sampling Geometries".
Since your data has the same sample times for all stations, I agree with Rich that you can base your netCDF structure on the example in section H.2.1 "Orthogonal multidimensional array representation of ...
You can try the hour() field calculator function with a nested age() function:
That should output the difference in hours. But you might have to re-create your input field as Date type and format them like YYYY-MM-DDTHH:MM:SS if not already.
I'm not sure if you can use more nested Conversion functions like tointerval() or ...
You need to edit the properties of yours fields Date and Time in QGIS.
Go to the properties of your layer.
Select the Fields tab.
In the line of your field (date and time), click on Line edit.
And then you can specify the format of your date or time -> it must be the same as defined in Qt Designer!
If the properties are the same in your ...
In GeoServer you can specify a start and an end date column, see the documentation at http://docs.geoserver.org/latest/en/user/webadmin/data/layers.html#edit-dimensions.
All you need is two date columns i.e. two columns with date datatype in your database.
You can try this, http://lib.heron-mc.org/heron/1.0.3/examples/timeslider/index.html
This example has an amazing slider, Hope it meets all your requirements.
UPDATE : Another Good Example:
basically use TIME=value& at the end of the WMS request. For a range of values you need to use TIME=start/end&. If you look in the GetCapabilities response you will see the values of time that will work.
See this tutorial for a brief explanation.
First go to your point layer and click the drop down arrow > perform analysis
Then go to Use Proximity and Create Drivetime Areas, change the measure to Walking Time
Seperate the parameters you need with commas and select overlap to create the rings as in your screenshot.
You can then open this feature layer in desktop for further tweeking such as better ...
For shapefiles, the time portion is truncated from the datetime value. So you should work inside a geodatabase if you need the time. If you really need to work in a shapefile, I suggest that you try it within a text field