Hi devs,
The TGRASS concept is a great enhancement to GRASS which already proved it`s usefulness for my daily work with raster data in many cases. Now I am discovering the vector part of it. If I understand correctly, the concept for vector data is identically to the raster part, namely using whole, time stamped vector datasets.
In long term monitoring, where time series play a central role, one often has a fixed location and only attributes are updated (as it is the case in e.g. detailed vegetation studies, temperature logger, wildlife camera traps…). In such cases having geometries for each registration of data would lead to significant redundancy of data and unnecessary computation (building topology, spatially matching each map…).
My question is now, how much work would it cause to introduce a new type of space time dataset with fixed geometries and a linked attribute table which contains the temporal information along with (variable) attribute values (“Space Time Vector Attribute Datasets”)?
What would have to be changed?
Is it more appropriate to stick to database solutions (e.g. PostGIS) or R (or a combination of the two) and eventually fetch data from STRDS?
Kind regards,
Stefan
Dear Stefan,
The GRASS GIS temporal framework supports the time stamping of vector
layers/tables (former called fields). Hence, you can create any number
of layers for a single vector map and assign a different attribute
table to each layer. This leads to the ability to separately time
stamp each layer&table of a vector map.
The temporal module t.vect.oberve.strds uses this feature.
However, since the analysis capabilities of space time vector datasets
are limited in the temporal framework, i would suggest to use a
temporal database for this task.
Best regards
Soeren
Btw:
You can try to use the Grass-Data-Explorer to analyse GRASS GIS time
series data in Qgis inclusively statistical analsys:
https://bitbucket.org/huhabla/grass-data-explorer
2015-12-11 15:49 GMT+01:00 Blumentrath, Stefan <Stefan.Blumentrath@nina.no>:
Hi devs,
The TGRASS concept is a great enhancement to GRASS which already proved it`s
usefulness for my daily work with raster data in many cases. Now I am
discovering the vector part of it. If I understand correctly, the concept
for vector data is identically to the raster part, namely using whole, time
stamped vector datasets.
In long term monitoring, where time series play a central role, one often
has a fixed location and only attributes are updated (as it is the case in
e.g. detailed vegetation studies, temperature logger, wildlife camera
traps...). In such cases having geometries for each registration of data
would lead to significant redundancy of data and unnecessary computation
(building topology, spatially matching each map...).
My question is now, how much work would it cause to introduce a new type of
space time dataset with fixed geometries and a linked attribute table which
contains the temporal information along with (variable) attribute values
(“Space Time Vector Attribute Datasets”)?
What would have to be changed?
Is it more appropriate to stick to database solutions (e.g. PostGIS) or R
(or a combination of the two) and eventually fetch data from STRDS?
Kind regards,
Stefan
_______________________________________________
grass-dev mailing list
grass-dev@lists.osgeo.org
http://lists.osgeo.org/mailman/listinfo/grass-dev
Hi Sören,
Thanks for your reply.
I shall think about a temporal DB and how it might be used in order to interact with TGRASS...
The GRASS data explorer for QGIS looks indeed cool...
Cheers
Stefan