Changes between Version 5 and Version 6 of Grass7/TemporalGISAlgebra

Timestamp:

Jul 5, 2013, 5:45:56 AM (11 years ago)

Author:

huhabla

Comment:

--

Grass7/TemporalGISAlgebra

@@ -5 +5 @@
 === Temporal Algebra ===
 
-The idea of the temporal Algebra is to use operators that process space and time. 
-The spatial processing capabilities that are already implemented in GRASS GIS will be reused. 
-That are r.mapcalc for raster processing and v.buffer, v.over , v.patch for vector map processing. 
-Unfortunately the GRASS GIS temporal framework implements a separated time and space approach. 
-The only way to process several space time datasets in time is to use their temporal relationships, 
-since the time dimension has in our case an arbitrary layout.
-
-Here an example of the temporal Algebra that simply selects parts of a space time dataset without the processing raster or vector data:
+The idea is to implement a temporal algebra to process space time datasets, 
+the new spatio-temporal datatypes in GRASS GIS 7.
+Space time datasets represent time series of raster, 3D raster and vector maps. 
+The GRASS GIS temporal framework implements a snapshot approach, 
+so that time and space are separated from each other. 
+Hence, space time datasets are not truly 4 dimensional datatypes. 
+Time and space can only be processes separately from each other. 
+The spatial capabilities of GRASS GIS are used to perform the spatial 
+processing of the time stamped maps that are registered in the space time datasets. 
+Hence the modules r.mapcalc for raster processing and v.buffer, v.over , v.patch for vector map processing are used. 
+The temporal processing is provided by the GRASS GIS temporal framework that supports time intervals and time instances. 
+Mixing time instance and time intervals as well as gaps, overlapping or inclusion of intervals and instances is possible. Hence
+this framework allows an arbitrary layout of the time dimension,
+
+The only way to process several space time datasets with arbitrary temporal layout is to use their temporal relationships. Or more precisely, the temporal relationships of the time stamped maps that are registered in the space time datasets. 
+The spatial operations between maps (sum, union, ...) can be performed after the temporal related maps are identified.
+This concept leads the design of the temporal algebra. The algebra must provide the functionality to define spatio-temporal 
+operators that process time and space in a single expression.
+
+It should be possible to select maps based on their temporal relations. It must be possible to temporally shift the time stamps, 
+to create temporal buffer and to snap time instances to create a valid temporal topology. 
+Hence many operations that are common in spatial processing should have an equivalent in the temporal processing.
+
+Here an example of the temporal algebra that simply selects parts of a space time dataset without the processing raster or vector data:
 
 We define a selection operator ''':''' that by default selects parts of a space time dataset that are temporally equal to parts of a second, hence the following expression
@@ -19 +35 @@
 }}}
 means: Select all parts of space time dataset A that are equal to B and store it in space time dataset C. The parts are in this case time stamped maps. In addition we define the inverse selection operator '''!:''', hence the following expression
-
+{{{
 C = A !: B
-
+}}}
 means: select all parts of space time time dataset A that are not equal to B and store it in space time dataset (STDS) C.
 
@@ -51 +67 @@
 
 Buffer all maps of STDS A with a temporal buffer of one day.
-
 = Overview of all temporal algebra elements =