Preliminary Class Project
Date given: 10/23
Due: 11/6 noon
Part 1(30 points)
Do all the tutorials for BMEGUI 3.0. Summarize briefly what each tutorial is doing and what you have learned from them that you can apply to your project dataset.
Part 2 (30 points)
Using the ENVR468hwk6Part2.txt dataset use BMEGUI to obtain a map of the BME mean estimate and a map of the associated estimation error variance at time t=12 day.
Provide a brief but well written write-up describing the steps of your analysis, i.e. use or not of log-transform, time aggregation, mean trend (optional), covariance model, estimation parameters, etc., and the results you obtained. This write-up should provide you a template for the mapping analysis section of your project report.
Hints: Take advantage of the figures that are generated at all steps of the analysis (exploratory data analysis, mean trend modeling, covariance modeling, temporal estimation, spatial estimation) to describe your data (e.g. exploratory spatial and temporal data plots), your mean trend model if any is used (optional), your covariance model (e.g. exploratory plots and covariance plots), and your mapping results (estimated time series and estimated maps). Make good quality outputs, including maps that visually capture well the spatial variability of estimates. This can be done by choosing estimation parameters (such as the local mean type, the number of estimation points, the resolution of the estimation and display grids, etc) that produces the best maps. Furthermore, one can export the estimation results in ArcGIS to improve the visual quality of the spatial estimation maps (export estimation values, add them in an ArcGIS project, display XY data, save as a shapefile, use geostatistical analyst to interpolate the estimation values using inverse weighted distances).
Part 3 (40 points)
Do the same analysis as in Problem 2, but this time using the dataset for your class project. Provide a write up describing your analysis and the results you obtain, including a map of the BME mean estimate for a time that you select, as well as the associated map of mapping error variance. This write up should help you refine the mapping analysis section of your project report. This write-up should be a cumulative report that includes what you have produced in previous homework, i.e. it should lay out your research question with relevant citations, it should have an exploratory data analysis showing your project data, it should include your covariance analysis with citations showing that is was consistent with previous covariance works or generating new covariance results, it should include your mapping results with a description of the methods you used and with citations showing that is was consistent with previous mapping works or generating new mapping results This write-up will serve as a part of your final project report.
Following is a hypothetical example that you can use to inspire your own analysis. The variable is a hypothetical compound named agentX (measured in ppm). The dataset used is ENVR468hwk6Part3.txt. The steps of analysis of this dataset includes (1) an exploratory analysis, (2) the modeling of the space/time covariance, and (3) obtaining maps of estimated agentX for selected times. The following figure shows some brief results for each of these steps. Use this as an example that you will expand for the analysis of your own dataset.
Figure: (a) space/time covariance model of log-agentX, and (c) map of the BME mean estimate of log-agentX at time 2000.096 year.
Submit part 1 and 2 as a well-written word document named yourfirstname_yourlastname_hwk6_part12.doc that you send to the instructor. Submit parts 3 as a well-written word document named yourfirstname_yourlastname_hwk6_part3.doc that you also send to the instructor.