Teachers in earth, environmental, biological, and general science are increasingly incorporating geospatial technologies into their lesson plans. The growing use of these tools in an array of social studies and STEM subjects supports authentic, problem-based instruction, helping students tackle real social and environmental research projects in their communities. The editors of eSchool News have compiled this special collection of news stories, best practices, and other resources designed to help educators integrate GIS and other geospatial technologies into classrooms and district offices.
“Another concept I’ve been exploring is what I’m calling sprawl inequality. This comes out of the famous Pareto Principle, that 80 percent of any phenomenon is due to 20 percent of the people. How much of habitat loss in cities is due to a small proportion of folks living in suburbs or exurbs? After a bunch of GIS work, the answer appears to be: 80 percent of urban development (in terms of area) is due to 35 percent of folks who live at the lowest densities. We may all have a responsibility to move toward more sustainable cities, but we aren’t all equally to blame for sprawl.”
…from The Australian…
“WHEN Europeans first encountered Australia, they saw a continent ablaze as Aboriginal ‘firestick farmers’ lit up the bush with controlled burns that prevented destructive wildfires. Now a hi-tech version of the land management practice, which is possibly tens of thousands of years old, could form part of Australia’s strategy to tackle a modern problem: global warming.
“The prescribed burning of the future probably will be ‘a combination of traditional knowledge and Western science’, says the CSIRO’s Heckbert.
“‘It would include a fire management plan based on sophisticated GIS (geographic information systems), precision weather forecasting and biomass models. Implementation of the plan would involve the deployment of helicopters and fire crews using the latest equipment, and the effects would be monitored with high-resolution satellite imagery.'”
“Fossil fuel emissions lead to a host of degradations of our planet including global warming. Forest researchers are offering a means of monitoring and counterbalancing civilization’s need for manufactured goods with nature’s ability to cleanse the atmosphere of harmful emissions resulting from production. A key tool to measure these trade-offs and provide the basis for designing sustainable plans is the use of geographic technologies. GIS can combine many layers of data, model that data in many ways, and generate reports and maps that make it easy to comprehend a complex problem.”
Global climate change is a difficult, complex, politically charged, and vitally important issue. Yet from a knowledge perspective, we are at a distinct disadvantage: at this point in time, we still do not have a clear idea of everything we need to know in order to address the problem in a measured, rational, and above all, scientific manner.
When you think about the multitude of issues surrounding climate change science—from root causes to resultant impacts—geography is clearly an elemental factor in the equation. Every aspect of climate change affects or is affected by geography, be it at a global, regional, or local level. As a tool for helping us to better understand such geographies, GIS is the single most powerful integrating tool for inventorying, analyzing, and ultimately managing this extremely complex problem.
A GIS-based approach called “Whole Earth Systems” provides a framework for understanding and addressing the entire breadth of climate change science issues in a holistic manner. What do we mean by “Whole Earth Systems”? Scientists have long classified various phenomena into logical groupings or “systems.” These classifications have helped greatly to advance the understanding of component physical, biological, and social systems. While advancing the understanding of each of these systems individually is vitally important, ultimately we need to bring all of these systems together, to understand how they are interrelated and dependent upon one other.
Whole Earth Systems science offers an opportunity to advance the science and understanding of climate change by providing a framework for a comprehensive, interdisciplinary, integrated view of our planetary system. Aggregating complex physical, biological, and social data and models within a unified framework will give us single view of the whole Earth system and provide us with the tools to manage—and ultimately design—our future in the most effective, efficient, and morally defensible way.
If you read my recent interview with Konstantin Krivoruchko and got excited about the multitude of opportunities to use statistics, spatial statistics, and geostatistics in your research, but didn’t know where to start, then check out these free training opportunities.
Integrating SAS Software with ArcGIS [Recorded Training Seminar; 60 minutes]
Integrating SAS and ArcGIS software enables organizations to streamline workflows and improve spatial analysis. The SAS Bridge for ESRI creates a connection between ArcGIS and SAS software, giving users access to spatial, numeric, and textual data through a single interface. With the SAS Bridge for ESRI, ArcGIS users can view SAS tables, geographically display SAS tabular data, symbolize geospatial data with SAS data, and export attribute data to SAS data sets to conduct statistical analyses.
This seminar highlights how ArcMap, the SAS Bridge for ESRI, and SAS software were used to focus the search for debris from the Space Shuttle Columbia. The seminar describes various ways to work with SAS tables and data in ArcCatalog and ArcMap, such as predictive modeling and trend analysis, and also provides other examples of how integrating ArcGIS and SAS software can help users solve real-world problems.
The presenters discuss
- The Space Shuttle Columbia debris recovery effort.
- Working with the SAS Bridge for ESRI.
- Using SAS Enterprise Guide.
- Performing linear and logistic regression in SAS software.
- Using SAS tables in ArcMap and ArcCatalog.
- Predictive modeling using SAS and ArcGIS software.
Regression Analysis Basics in ArcGIS 9.3 [Recorded Training Seminar; 60 minutes]
Regression analysis techniques are used to examine how phenomena vary over space (where things occur), predict where phenomena may occur, and help explain the factors behind observed spatial patterns.
By finding answers to questions such as:
- Where are people persistently dying young in the United States?
- Where are children consistently achieving high test scores?
You can then explore questions such as:
- Why are people dying young?
- What factors contribute to consistently high test scores?
In ArcGIS 9.3, new advanced tools allow you to apply Ordinary Least Squares Regression and Geographically Weighted Regression analysis techniques. This seminar covers the process for building a regression model and explores a typical regression analysis workflow.
The presenter discusses
- When you should use regression analysis and what kinds of questions it can answer.
- Characteristics of a properly specified Ordinary Least Squares model and how to interpret results.
- How to use Geographically Weighted Regression to refine remediation strategies and inform policy.
Understanding Spatial Statistics in ArcGIS 9 [Recorded Training Seminar; 60 minutes]
Spatial statistics tools are exploratory tools that help you measure spatial processes, spatial distributions, and spatial relationships. There are many different types of spatial statistics, but they are all designed to examine spatial patterns and processes.
This training seminar introduces you to the spatial statistics tools included as core functionality with ArcGIS 9. The presenter demonstrates how the tools can easily identify the geographic center of a set of features, determine if a set of features is clustered or dispersed, find hot spots or spatial outliers, and other critical analysis functions.
The presenter discusses
- An overview of spatial statistics.
- Measuring geographic distributions.
- Spatial autocorrelation.
- Hot spot analysis.
Introduction to ArcGIS 9 Geostatistical Analyst [Online Self-Study Course; 3 hours]
With ArcGIS Geostatistical Analyst, GIS users can explore, visualize, and create sophisticated optimal prediction surfaces, as well as statistical surfaces of probability and standard error. This free course introduces some fundamental concepts of geostatistics and teaches how to create and compare interpolated surfaces.