Module 1 Lab: Visual Interpretation

 

This week’s assignment focused on learning how to interpret aerial photographs using different visual cues such as tone, texture, shape, size, shadow, pattern, and association. Even though aerial images may seem like just pictures from above, this lab helped me understand how much information can be extracted when we look closely and intentionally.

In Exercise 1, I worked with a grayscale aerial photo to identify differences in tone and texture. I created a feature class for tone and labeled five areas ranging from very light to very dark. I also created another feature class for texture, identifying areas from very fine to very coarse. This process showed me how brightness and surface roughness can indicate different types of land cover. For example, paved areas appeared very light, while water bodies showed up very dark, and forests had more coarse textures. It made me realize that even without color, we can still interpret the landscape fairly well.

In Exercise 2, I practiced identifying features based on shape and size, shadow, pattern, and association. For this part, I worked with a different aerial image and created points for features that could be recognized based on each of those criteria. For example, shadows made tall objects easy to spot, repetitive rows helped identify patterns, and association involved recognizing features by their surroundings—like knowing a baseball diamond is likely part of a park. This exercise really emphasized how context helps with interpretation.

Finally, in Exercise 3, I compared a true-color image to a false-color infrared (CIR) image. This part helped me see how different types of imagery can highlight different land features. In the false-color image, healthy vegetation appeared bright red due to strong near-infrared reflectance. This made it easier to distinguish forests, marshes, and grasslands. Comparing the same features in both images helped me understand why CIR imagery is useful for environmental analysis, especially in areas like forestry and wetland studies.

Overall, this week’s lab helped me gain confidence in interpreting aerial images by paying close attention to visual characteristics. I learned that remote sensing is not just about looking at pictures—it’s about understanding what the patterns and colors mean in terms of the real world. This skill will be valuable as I continue studying GIS and environmental applications.