Internship- GIS Job Search

    As I have explored job opportunities throughout the program, I have been excited to see all the different ways GIS can be applied. It has always been my goal to find a position where I can contribute to environmental research or conservation efforts. With this in mind I have been focusing my search on various natural resources job boards, government positions and various research centers and non-profit organizations.

    My biggest takeaway is that these positions often require a range of skillsets- scientific communication, experience writing peer-reviewed research papers, proficiency with programming, background knowledge in ecology and natural resources, remote sensing, field work experience, statistics and data analysis, etc. I have even seen some positions that want further skills like website development and management, or social media management. This offers ample opportunity for continuous skill development and refinement, something I am excited about because it is important to me to find a position where I can continue to learn. 

Internship Course- Introductory Blog and User Groups

     I was selected for a Virtual Student Federal Service internship with USGS EROS Center analyzing post-fire recovery trends for the 2001 Jasper in the Black Hills Region of South Dakota from August 2024 through May 2025. I am utilizing a combination ESRI ArcGIS Pro, R studio, and Python to analyze datasets including climate, landcover, topography (derived from DEM), Landsat, Aerial LiDAR, Terrestrial LiDAR to assess spectral recovery almost 25 years after the devastating wildfire. I will utilize additional resources such as the USFS datasets, National Hydrography dataset, MTBS datasets and LandFire data to give additional perspective on the area.

Since the internship spans 9 months I have already laid some of the groundwork for spectral recovery and this semester will be building on what I have already done and presenting my findings. My big questions are “How do we define recovery” and “With that definition in mind, what areas are recovered and what factors may be influencing that recovery”. There is no specific standard for determining whether an area has recovered from fire damage and I am utilizing a variety of resources, definitions obtained through the literature, and trends pulled out from the data to assess the recovery patterns that can be observed.

 I also plan to apply deep learning and machine learning algorithms to the LiDAR data and Landsat data to try to recreate an idea of what the forest structure looked like pre-fire. This is important because LiDAR only became available for this area in 2019 so structural characteristics like tree height and canopy density are unable to be determined. If a DL or ML algorithm can make strong predictions based on what is observed spectrally in the Landsat compared to what is observed in the LiDAR data for the same time period, that algorithm can hypothetically be applied to previous Landsat scans as a rough estimation for comparison. It will be interesting to see if areas that are “spectrally recovered” are also recovering their pre-fire forest state, or if they are recovering spectrally while still being classified as “open canopy” as opposed to “closed” or “shrubs” as opposed to “trees”.

I chose to join two different GIS user groups for community engagement as I begin my GIS career. I joined the Women in GIS group and the GIS Association of Alabama. I joined the WIGIS because I appreciated the variety of professional development opportunities they offered. I joined the GIS Association of Alabama to connect with the broader Alabama GIS community.