GIS4930 - Module 2.2 - Interpolation

-

For this lab, we used three different interpolation methods: Thiessen, Inverse Distance Weighting (IDW), and Spline, to map Biochemical Oxygen Demand (BOD) across Tampa Bay, and compared how each method handles spatial variation and data distribution.

The easiest and most simple method was Thiessen interpolation, which assigns each location the value of its nearest sample point, which means the interpolated surface matches the exact values at the sample sites. This wasn't the best type of interpolation though as it creates abrupt transitions between the polygons which made it not as good at modeling the continuous environmental data like BOD.

Spline interpolation fits a curved surface that must pass directly through all of the input points. This created a smoothed, and honestly, very visually appealing interpolation, but seemed to be overestimating or underestimating values in areas with low data. This is what was happening in certain splots of the study area which is why it wasn't the best fit for the data either. 

Finally, Inverse Distance Weighted IDW estimates values by weighting nearby points more strongly than distant ones which creates a realistic surface and works well when data is evenly distributed and sampling density is high, which actually made it the best for this dataset.

 


IDW Interpolation

 


Comments

Post a Comment

Popular posts from this blog

About Me

-
Hi everyone! My name is Dalton Inman, I'm a full time marine bio undergraduate at UWF, and just switched from the minor to the certificate in GIS and will be graduating this December! I really enjoyed the introductory classes and wanted to dive deeper into understanding and using GIS for marine conservation and rehabilitation. My aim in taking these GIS Courses for my certificate is to add to my current GIS skill set. I noticed some LiDAR labs later in this course which makes me excited since I've been interested in learning about it. I am currently an intern at the Escambia County Marine Resource Division where I help organize data in Excel and create maps from Boat Data and deployed artificial reef condition data. When I'm not spending time outdoors flying drones or snorkeling in the ocean, I typically spend it inside with my now fiancé!! and my three cats: Kiwi, Pumpkin, and Mango. I hope to learn a bunch from this course and from everyone I meet in GIS!  If you want to ...
Read more

GIS4048 - Module 6 - Suitability Analysis (Part 2)

-
Image
For the second part of this module, we were tasked to identify a least cost wildlife corridor between two sections of the Coronado National Forest. The goal was to identify potential movement routes for black bears by combining environmental criteria into a suitability model, converting that model into a travel cost surface, and then using corridor analysis to locate low cost connection areas between the parks.  I did this by creating three suitability rasters on a scale of 1 - 10 using the reclassify tool. These were the distance to roads, elevation, and land cover, with values assigned according to their relative importance for black bear habitat. I then used the Weighted Overlay tool to combine these layers, assigning weights of land cover 60%, elevation 20%, and distance to roads 20% creating a suitability map. I then inverted the suitability raster (10 – suitability) to create a cost surface where highly suitable areas became low cost travel zones. I calculated the cost d...
Read more