[ARANGKADA@30] Colloquia on Spatial Technologies in Advancing Research Techniques

Everyone is invited to

The Geography Lab Core Group Technical Colloquia’s

Spatial Technologies in Advancing Research Techniques (START)

Date: September 12, 2013

Time: 5:30-7:30pm

Venue:  Palma Hall 207, Roxas Avenue, UP Diliman, Quezon City

Topics:

Session 1: Modeling Geographic Distributions with MaxEnt 

Discussant: Mart Geronia, MS Geology student

MaxEnt (Maximum Entropy) is a java-based free software that is capable of producing ecological models of the geographic distributions of species based on variables using the maximum entropy method of probability. The maximum entropy method ensures that the probability distribution the model estimates is closest to uniform and the most spread out, subject to the constraints set by the variables; i.e., the model assumes that a species can be found uniformly across space subject to the constraints set. This software is written by Steven Phillips, Miro Dudik and Rob Schapire, with support from AT&T Labs-Research, Princeton University, and the Center for Biodiversity and Conservation, American Museum of Natural History. This software generates models of a species’ geographic distribution using the constraint features or the environmental variables describing the background landscape and by using the collection of presence-only data of the distribution of the species in question. It can also integrate both categorical and continuous data for the variables and will not diminish its capability to produce a good model.

  

Aside from its application in modeling the geographic distributions of species habitats in ecology and biogeography, the maximum entropy method has been used in the fields of linguistics (for natural language processing), economics (mainly in game theory), climate research (modeling a species habitat based on future climatic scenarios), and in political science and sociology (application of ecological inferences or drawing conclusions about individual behavior from aggregate data).

Session 2: Grid Analysis and Display System (GrADS) for Earth Science Data Processing and Visualization

Discussant: Robert Badrina, MS Meteorology student

Grid analysis and display system (GrADS) is an open source, interactive desktop tool that is used for easy access, manipulation and visualization of earth science data. It can handle various data file format such as binary (stream or sequential), GRID, NetCDF, HDF and BUFR (for station data). GrADS has been implemented worldwide and currently being used by researchers around the globe, it has an online group forum where community of users exchange information about the software.

Outputs of climate models (Regional Climate Model (RegCM) and Global Climate Model) are

can be utilized using GrADS. It uses four convention environmental dimensions: longitude,

latitude, vertical level and time. There are also data available for free such as resources

from the Tropical Rainfall Measuring Mission (TRMM) which can provide rainfall estimates

that can be processed using GrADS. Data can be displayed using variety of graphical

technique: line and bar graphs, scatter plots, smoothed contours, shaded contours,

streamlines, wind vectors, grid boxes, shaded boxes and station model plots. GrADS is

supported by the Institute of Global Environment and Society dedicated for climate research

in the service of the society.

S.T.A.R.T. aims to provide a venue for young researchers to present various techniques for visualizing and analyzing spatial data using recent technologies and data processing software to aid in further enhancing social science research methodologies.

As spatial information is integral in addressing the pressing environmental and social issues we deal with at both local and global scales, these colloquia seek to facilitate exchanges among young academics on the potentials of available technologies to deliver useful information to the public for more informed decision-making.

The Lab Core Group of the UP Department of Geography was formed in 2009 by student

volunteers who wanted to help manage the then small GIS laboratory of the institution. 

Beyond serving as the lab technical assistance team, it initiated other projects such as the Geography1 Open Lab which rovided introductory training on Google Earth image interpretation, GIS, and GPS, and the drafting of he GIS laboratory user guidelines and its file management and data security scheme.