6 resultados para digital elevation model
em Digital Archives@Colby
Resumo:
http://digitalcommons.colby.edu/atlasofmaine2005/1013/thumbnail.jpg
Resumo:
http://digitalcommons.colby.edu/atlasofmaine2005/1000/thumbnail.jpg
Resumo:
http://digitalcommons.colby.edu/atlasofmaine2006/1020/thumbnail.jpg
Resumo:
This project constructs a structural model of the United States Economy. This task is tackled in two separate ways: first econometric methods and then using a neural network, both with a structure that mimics the structure of the U.S. economy. The structural model tracks the performance of U.S. GDP rather well in a dynamic simulation, with an average error of just over 1 percent. The neural network performed well, but suffered from some theoretical, as well as some implementation issues.
Resumo:
After declining steadily for several decades, the South China tiger (Panthera tigris amoyensis) is now thought to be extinct in the wild. However, there is some hope of reintroduction, with Hupingshan-Houhe and Mangshan-Nanling National Nature Reserves in southern China seeming to hold the most promise. Our study used slope, elevation, vegetation, and landcover variables to construct a rough habitat suitability index for tigers in these two parks. According to our model, there are areas of suitable habitat within both parks. However, there are some important variables that we were unable to include in our model, such as human population density and prey availability. Considerable in-depth research will be necessary to evaluate the suitability of these locations before reintroduction is considered.
Resumo:
Millions of unconscious calculations are made daily by pedestrians walking through the Colby College campus. I used ArcGIS to make a predictive spatial model that chose paths similar to those that are actually used by people on a regular basis. To make a viable model of how most travelers choose their way, I considered both the distance required and the type of traveling surface. I used an iterative process to develop a scheme for weighting travel costs which resulted in accurate least-cost paths to be predicted by ArcMap. The accuracy was confirmed when the calculated routes were compared to satellite photography and were found to overlap well-worn “shortcuts” taken between the paved paths throughout campus.