Tingyi’s Geob479 blog

The focus of landscape ecology is to reveal the importance of spatial patterns to the dynamics of interacting ecosystems (Therefore, a homogenous area cannot be a landscape). Many factors have stimulated interest in landscape research, the most important of which is the urgent need to assess the impact of rapid, large-scale changes in our environment.

The ultimate aim of landscape ecology is to understand process through an examination of form (i.e., landscape pattern). In order to understand what quantification of pattern on the landscape can tell us about the processes that have occurred /are occurring on a landscape, we should first consider the causes of landscape pattern. Also, it is important to note that form itself can modify processes. Therefore, our ability to identify the process responsible for a particular form becomes even more difficult since there can be feedback between the two.

There are certain criteria when one analyze a landscape.  there are five classes of metrics (Riitters et al. 1995),

“Number of classes or cover types”
“Texture measures (fine or coarse)”
“Degree to which patches are compact or dissected”
“Patches are linear or planar”
“Patch perimeters are complicated or simple in shape”

One important type of landscape metric is spatial autocorrelation, which is divided into first and second order processes. A first order process would be where patterns develop in response to some underlying environmental factor, while a second order process is when patterns emerged as interactions between objects.

In this lab, we explored how the landscape around Edmonton, Alberta has changed over time (1966 to 1976). I examined some Fragstats metrics and created a transition matrix that explicitly shows the transformation of land uses over time. The report was written from the perspective of a consultant (who could be an urban planner, an agriculturalist, an environmentalist, an outdoor enthusiast, etc.

Maps included in the report:

Full text of the report:

lab1 report

This tutorial exercise we use CDC Wonder Data and Model Builder to create yearly hot spot
maps of Heart Disease. I used CDC Wonder Heart Disease data for the
Southern United States by Country then we create one model to process the data into individual feature classes, one for each year and create
a second model to perform hot spot analysis on each year’s feature class, finally we animate the yearly hot spot feature class maps showing below.

One fundamental issue in geography study is finding the correct scale. Modifiable Areal Unit Problem (MAUP) is endemic to all spatially aggregated data. If the inappropriate too small or large scale is selected, the analysis results would be greatly affected.  For example, human geography uses arbitrary units. , when natural physical units have their own issues, as they may have fuzzy or fractal borders.

Other issues such as grain and extent of a study area, the modifiable areal unit problem, the nature of the boundaries of a study area, and spatial dependence/heterogeneity are implicit in any spatial analysis.

The first week course’s introduces the five”p”s of  that we would focus during this this GIScience research application course: patterns, processes, places, people and perspectives.  We will learn about the spatial analytical research methods used in  in conservation biology(landscape ecology), health geography and crime. Also, I was introduced and start to thinking carefully about asking questions for research with a geographical perspective.

The first lab (tutorial 1) let me become a little bit familiar with health data(including obtain data) and its relation with spoliation data (as well as using spatial analysis).

This is my first UBC blog site~

So… I wish you enjoy this site and have a very nice day~