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Thematic Mapping – Data Classification Methods

Module 4 for Computer Cartography contrasts 2010 Census Data for Miami-Dade County, Florida using multiple data classification methods. Our objective is to distribute quantitative data into thematic maps based upon two criteria. The first series of maps shows the percentage of the total population per Census Tract of the number of seniors aged 65 and older. The second map array uses normalized data to partition Census Tracts based upon [...]

By |2024-04-08T11:08:54-04:00April 7th, 2024|GIS|0 Comments

Cartographic Design – Gestalt Principles of Perceptual Organization

Module 3 for Computer Cartography builds on Module 2, where we started developing a routine for good map design with guidelines for labeling, annotation and layout text. Building upon that knowledge base, we focus on cartographic design, the method with which maps are conceived and created. The Gestalt Principles of perceptual organization factor into the design process for the Module 3 lab assignment. There are several key concepts integral [...]

By |2024-04-08T11:02:43-04:00April 2nd, 2024|GIS|0 Comments

Cartography, Designing a good map

The second module for Computer Cartography expounds upon some of the lessons learned from the first module. These include a refresher of the essential map elements (map title, scale bar, north arrow [orientation], data source information, etc.) from Introduction to GIS (GIS 4043), and general typography principles in cartography ranging from type placement, variation dependent upon features and appropriate type size. The concept of map clutter from module 1 [...]

By |2024-04-08T10:51:54-04:00March 21st, 2024|GIS|0 Comments

Cartography, the Good and the Bad

Advancing to our second week of Computer Cartography, the first module requires us to think about how we look at and interpret a map. Our task was to select for critical analysis and evaluation, both a map that we consider well designed, and another that is poorly designed. What a task that was, as there have been several over the years that fit both contexts. Trying to recall any [...]

By |2024-04-08T10:47:54-04:00March 15th, 2024|GIS|0 Comments

Computer Cartography, the next step on the GIS Road to Fruition.

When I saw that Computer Cartography was my next class in the UWF GIS Certificate Program, I got pretty excited. Cartography has been an interest of mine going well back to childhood. When my siblings got a sketch pad to draw art, mine instead was used to draw maps. This passion stayed with me into high school and then college, where I would often doodle a small map in [...]

By |2024-04-08T10:42:50-04:00March 11th, 2024|GIS|0 Comments

Supervised Image Classification – Germantown, Maryland

The fifth module for Remote Sensing and Photo Interpretation introduced Supervised and Unsupervised Digital Image Classification techniques. These are automated processes for converting a spectral class, a group or cluster of spectrally similar pixels, into an information class, i.e. land use/land cover class of interest. Using multi-spectral data and spectral pattern recognition techniques, the algorithm may take many spectral classes to describe a single information class. Similarly one spectral [...]

By |2024-04-08T10:34:35-04:00November 21st, 2023|GIS|0 Comments

Multispectral Data Analysis – Olympic Pensinula, Washington

This week's Remote Sensing and Photo Interpretation lectures and lab assignment introduced a myriad of information related to image preprocessing. Functionality and various atmospheric correction techniques were discussed, followed by in depth look at several vegetation indices. The textbook provided great detail of the spectral characteristics of vegetation, including how visible light interacts with tree leaves and canopies. The lab introduced data acquisition and the USGS Global Visualization Viewer [...]

By |2024-04-08T10:35:31-04:00November 12th, 2023|GIS|0 Comments

Introduction to ERDAS Image – Washington Forest Thematic Data

The third lab assignment for Remote Sensing/Photo Interpretation introduces ERDAS (Earth Resources Data Analysis System) Image. The first part of the lab provided a basic overview of the program, initially with some rudimentary tasks involving Advanced Very High Resolution Radiometer (AVHRR) imagery and a LANDSAT Thematic Mapper (TM) satellite image of forestland in Washington State. Working with the data from the Olympic Peninsula in Washington, learned how to add [...]

By |2023-11-03T16:55:10-04:00November 3rd, 2023|GIS|0 Comments

Land Use/Land Cover (LULC) Identification for Pascagoula, MS

The second module for GIS4035 Remote Sensing/Photo Interpretation introduces the USGS Land Use/Land Cover (LULC) classification system. Originally compiled by James R. Anderson and associates, A Land Use and Land Cover Classification System for Use with Remote Sensor Data was published by the United States Government Printing Office in 1976. There are four levels in the hierarchy, with Level I categorizing LULC on air photos with small scale and low spatial [...]

By |2023-11-03T16:58:52-04:00October 27th, 2023|GIS|0 Comments

Remote Sensing – Visual Image Interpretation Basics

A short two days following the completion of the Final Project for GIS4043, I am delving into Photo Interpretation and Remote Sensing (GIS4035). The first lab provides an overview on elements of visual image interpretation, with historical black and white air photos of Pensacola Airport and Pensacola Beach in Northwest Florida. The first aspect of aerial photography interpretation references the tone, or the shades of gray from light/white to [...]

By |2023-11-03T16:47:46-04:00October 22nd, 2023|GIS|0 Comments
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