GRASS GIS 7:

Spatiotemporal Analytics and Visualization

Helena Mitasova, Anna Petrasova, Vaclav Petras, Brendan Harmon

Center for Geospatial Analytics, North Carolina State University

GRASS GIS: geospatial research platform

grass.osgeo.org

  • general purpose desktop GIS with updated wxPython GUI

  • backend processing for QGIS, R statistics, WebGIS

  • powerful geospatial 2D/3D raster, imagery and vector processing

  • single integrated software with 30 years of development

GRASS GIS 7: Spatiotemporal 3D GIS

  • Temporal framework for large raster and vector time series

  • 2D and 3D dynamic visualization

  • pyGRASS: python interface to the GRASS C library

  • spgrass7 for coupling with R

  • 350+ core modules and rapidly growing add-ons contributed by the community


Space-Time Framework: Analysis

  • New time series datatypes: Space-time raster, 3D raster and vector

  • Time series datasets managed in temporal database

  • New modules: query, aggregation, conversion, statistics, gap filling


North Carolina climate data analysis

Gebbert, S., Pebesma, E., 2014. TGRASS: A temporal GIS for field based environmental modeling. Environmental Modelling & Software 53, 1-12.

MODIS land surface temperature time series

  • 14 years of 4-times per day data (14x1440 maps) for entire Europe at 250m resolution

  • advanced statistical methods used to fill no-data areas and enhance resolution

  • multivariate regression including elevation, solar angle, annual precipitation

  • EuroLST: http://gis.cri.fmach.it/eurolst/


MODIS land surface temperature US

  • LST method applied to US

  • Metz, Rocchini, Neteler, 2014: Rem Sens, 6(5): 3822-3840

Space-Time Framework: Visualization

  • Simultaneous 2D, 3D dynamic visualization

  • Space-time cube voxel models


Coastal DEM time series visualization

DEM time series visualization:

Jockey's Ridge migration 1974 - 2012

Space-Time Cube visualization:

Jockey's Ridge 16m, 20m contour evolution isosurfaces

Interactive 270 degree visualization

Jockey's Ridge visualization in the Hunt Library teaching and visualization laboratory


On-line geospatial analytics:

Geomorphons

Basic landforms extracted for the entire US

Interactive search of landuse patterns, and patterns of landuse change

Spatial Informatics Laboratory, University of Cincinnati

http://sil.uc.edu/

Spatiotemporal modeling of processes

Path sampling method for solving the flow continuity equations

               

UAS data acquisition for high resolution modeling

  • NGAT Trimble UX5 system at NCSU Lake Wheeler experimental farms

  • Orthophoto (3cm res.) draped over a Digital Surface Model (DSM, 15cm res.)


       

Data acquired by NCSU NGAT, processed by Justyna Jeziorska, U. Wroclaw

UAS DSM and water flow modeling

  • DSM of tilled fields at NCSU Lake Wheeler experimental farms

  • Simulated surface water depth captures flow redirection by tillage


       

Centennial Campus case study

  • 3D data acquired by lidar in 2001 and 2013

  • used as study area for several courses

  • Lidar data processing, surface runoff assessment, trails planning

Centennial Campus

Solar radiation modeling: summer and winter solstice dynamics

Centennial Campus

Fire spread modeling using fuel estimates from lidar data and with a fire break:

Interactive Centennial Campus

Tangible landscape: overview

Exhibition booth 27 and 35

NCSU OSGeoREL

geospatial.ncsu.edu/osgeorel/

  • NCSU Open Source Geospatial Research and Education Laboratory

  • Member of Geo4all initiative: global network for foss4g education

  • 91 labs on all continents

  • NCSU NA leading lab: GRASS GIS development, courses, research projects

  • GitHub: https://github.com/ncsu-osgeorel