About Me

 

My name is Emily Jackson, I am currently in the GIS Graduate Certificate program at University of West Florida, and I work full-time as a fisheries biologist on artificial reefs for Florida Fish and Wildlife Conservation Commission.

I love Florida's diverse and vibrant marine ecosystems! I did my BSc in Environmental Science and Policy in Tampa at University of South Florida and completed my MSc research over in California at Scripps Institution of Oceanography. I've worked around and with GIS off and on at different points through my career, it's been fascinating to watch it grow from a buggy not-well-understood (by our remote field station at least) mapmaking software into the powerhouse of geospatial data display, collection, and analysis it is in the field today. One of the driving passions in my career is the interconnected nature of complex productive trophic systems, nutrient cycling, and coastal communities. I love GIS and ESRI products because they give me additional tools for translating ecosystem science and making it accessible to those community stakeholders. 

 When I took my position with FWC I also took up responsibility for the archival geodatabase of all Florida's artificial reefs (the FARD). While I am comfortable enough with GIS to run the database and do maintenance, I want to be able to use the FARD to help make even more of our habitat and assessment data accessible and easily visualized by the public and county managers. My goal for enrolling in the UWF Certificate Program has been to be able to push the FARD to its full potential. This year during my GIS Internship I added new layers to the FARD for shipwrecks vs artificial reefs, as well as created a new data layer, custom symbology, and data entry system for our fish census surveys.

Here is an overview of some of the research I've done so far, and the places that matter to me:

GIS Internship - GIS Job Search

 As part of our internship course and forum we searched for GIS positions that are currently open, and reflected on them in the context of our own experience and areas for growth. 

I used the Conservation Job Board to conduct my search, it is a board I'm familiar with, and I typically use it as much to keep an eye on the listings and pay scale in my field of marine biology as much as I do to look out for new opportunities for myself. I was pleased to find GIS positions right away on the Conservation Job Board. Land and resource management is one of the primary fields that utilizes GIS, so this makes sense. Something that struck me however was how there were openings for geospatial information system work at nearly every level of experience. I feel like marine biology lately has become a little stratified in that there are a wealth of far-end entry level positions - postings that are unpaid or pay very little, asking for a dive certification or a bachelor's without prior experience. On the other hand there are also openings for Deans and Chairs of foundations and university programs that require a postdoc and over ten years of experience, but nothing for mid-level, experienced entry, or career climbing positions. This is what I have come to expect from the marine biology job market as of late.  

For GIS on the other hand, I noticed that there were experienced entry jobs (no far-end entry) and mid level positions, openings that looked to be 1-2 year contracts as well as government services and career positions in addition to the high level "Director of Geospatial Services" I had expected. I think this is a reflection of the newness of GIS as a career, and of the value that organizations are placing on the toolset, while there is still a relatively small pool of applicants with the skillset needed by the industry. One other thing I did notice while browsing GIS positions was the variability of value that different organizations seemed to have. In some cases a position that primarily did geodatabase management would be near-entry level, with an hourly pay, while another position with similar job description would be salaried, and titled as a Technician IV or GIS Manager. I can assume some of this is from the variability in workload, but it was interesting to see nonetheless, and is possibly another symptom of the newness of the field and the GIS job market as a whole. 

GIS Internship

 During my GIS internship I will be working with Florida Fish and Wildlife Conservation Commission to create a geodatabase and layers to capture fish surveys conducted at artificial reefs in Florida. 

FWC is responsible for recording the location and maintaining artificial reefs throughout Florida. In order to meet this requirement, the Commission conducts surveys on artificial reefs strategically in different regions of Florida. These surveys capture what species of fish were observed at the reef, the state of the reef structure, presence of natural hardbottom, and any boater activity on the reef. Currently these surveys are organized in an Excel database, however this lacks spatial data, and makes it difficult to visualize which reefs have been surveyed recently. 

Artificial reef locations as they are maintained by FWC. Notice no surveys are present, only reef locations. 

As part of my internship, in addition to working as part of the FWC GIS User Group and interacting with GIS professionals at FWC, I will build a layer and entry process for the artificial reef surveys, so they can be captured and displayed within ArcPro. 

In addition to the FWC GIS User Group, I have joined the American Water Resource Association, Florida chapter. This group is a network of spatial and water resource professionals in the region interested in hearing the latest news and issues associated with offshore, coastal, and urban water use in the state of Florida. More information can be found about the group at: https://www.awra.org/

Photo Interpretation and Remote Sensing - Supervised and Unsupervised Classification

 

The classified map of Germantown, showing land cover/a degree of land use based on ERDAS extrapolation of manually selected signatures. The Distance map shows areas where the classification may be uncertain.

This week's lab focused on conducting feature classification on aerial imagery using a computer-driven tool (unsupervised) and classification based on analyst inputs (supervised). Both methods require manual retooling before or after, and adjustment and manual assessment of the band representations to check that all features are displayed as clearly as possible. In particular, I used histograms and spectral plots to check for spectral confusion in the pixels I had classified - this is where one pixel may have a value that has been classified in two groups at the same time. At the end, I ran the entire process on an image from Germantown, Maryland, to practice supervised classification and the resulting recoding and display of land cover in Germantown.  

Photo Interpretation and Remote Sensing - Spatial Enhancement and Band Indices

To identify this feature we were given information about it's appearance in different spectral layers. From there we had to compare layers and select appropriate band combinations to highlight the feature and make it distinct from it's surroundings. 

 In this week's lab we examined techniques for manipulating the display of aerial imagery based on which areas of the visible spectrum we wished to emphasize. Using ERDAS and ArcPro, I explored the distribution of reflectance in satellite imagery from USGS, and adjusted the band assignments in the visible spectrum to identify different features. Much like the True Color and False Color Infrared from previous labs, the amount of different wavelengths reflected depends on the type of surface encountered by electromagnetic radiation. By changing how the bands of visible light are visualized, analysts can discern between different types of surfaces, such as water, compact ice, new ice, healthy vegetation, and dry vegetation.    

Photo Interpretation and Remote Sensing - Working with EMR and Digital Image Processing

 This week we explored and learned to work with ERDAS software, which is used for importing, displaying and analyzing images from aerial sensors. Though this software has been around for some time, learning the quirks and best practices was essential for beginning to analyze aerial images outside of ArcPro. In addition to working with ERDAS, we reviewed the types of electromagnetic radiation, and how wavelength, frequency, and energy are related as well as how this may influence a sensor's image of the Earth. By manipulating images in ERDAS and ArcPro I was able to discern and utilize different color models to focus on different points of image analysis. 

This map was created by selecting a subset of an aerial image from ERDAS and successfully importing it into ArcPro for further analysis and cartography. Note that "Cloud" is a type of cover, as it interferes with the sensor ability to see the ground.  

Photo Interpretation and Remote Sensing - Manual Land Use/Land Cover Assessment

Digitized polygons classified by land use or land cover.

For this module we each classified land use and land cover from an aerial photograph for a portion of Pascagoula, Mississippi. We were encouraged to classify land cover and land use down to a Level II classification, which included delineations such as Residential, Commercial, Evergreen Forest, Bays and Estuaries, but did not specify further to type of home, species of tree, use of waterway etc. 

In this exercise I used the photo interpretation techniques from the previous lab to make determinations on structures, vegetation, and feature boundaries. I determined an appropriate minimum mapping unit (MMU), digitized polygons based on my interpretation, and then conducted an accuracy analysis by comparing 30 randomly sampled points to the features at those locations in Google Maps/Streetview. Of 30 sampling points, only 2 were incorrectly classified, for an estimated accuracy of 93%.