Utilizing 360° photography to assess forest recovery seven years after hurricane impact

Many forestry studies rely on obtaining measurements on forest vertical structure, canopy closure, ground cover, and other data types through the use of manual labor, which is time-consuming, expensive, labor-intensive, and may not be feasible following a major hurricane.

We established a total of 75 survey points across the trails of Las Casas de la Selva, a sustainable forestry plantation located in Patillas, Puerto Rico. The property took a direct hit from Hurricane Maria, a Category 4 storm with winds of up to 241 kph, on September 20, 2017. We took 360° photos at each survey point seven years later, which were then analyzed within a virtual reality environment to quantify forest vertical structure and transformed them into two batches of hemispherical photos, with one set focused on the canopy and the other on the ground. Collecting data in this way opens up the possibility for monitoring forest/vegetation health over time, as sites at trails are easy to access, and only 360° photos are needed.

We computed the Vertical Habitat Diversity Index (VHDI) from the amount of foliage in 4 strata: herbaceous, shrub, understory, and canopy.

Methods
Assessment of Forest Vertical Structure:

To assess the forest's vertical structure, we analyzed our 360° photos within an Oculus Go Virtual Reality Headset. For each photo, the presence of four layers was determined, which includes (1) Herbaceous Layer, (2) Shrub Layer, (3) Understory Layer, and (4) Canopy Layer. The different layers were primarily determined by the height of the vegetation. The herbaceous layer consisted of vegetation that had no woody stems, which included grass, ferns, and vines. For the herbaceous layer, the height ranged from 0.15 to 1.3 meters. The shrub layer consisted of plants with woody stems, such as shrubs and small trees. This layer's height ranged from 1.3 to 4.3 meters. The understory layer consists of vegetation in a wooded area where shrubs and trees are growing between the forest canopy and the forest floor. In this layer, the height ranged from 4.3 meters up to just below the canopy. Finally, the canopy layer consists of the top layer of a forest, which makes up the crowns of all the trees that overlap to form the roof over the rest of the forest. To determine the presence of these layers within the VR headset, Caslin first selected a landmark location (e.g., a tree or landscape feature). Next, turning clockwise, he recorded the presence of foliage in each of the 4 layers within 30° slices of the 360° view to capture the entire image. Throughout the analysis for each photo, the PI recorded himself and then listened to the recording later to enter the data within a spreadsheet. Following Bai’s (2024) method, we calculated a Vertical Habitat Diversity Index (VHDI) by applying the Shannon-Weiner Index to these data, using layer for “species” and frequency of each layer as “abundance”. 

Assessment of Ground Cover Vegetation: 

To analyze the ground cover, we transformed each 360° photo into a hemispherical photo focusing on the ground, using GIMP version 2.10.12. We batch processed images within GIMP using an additional plugin called BIMP (Batch Image Manipulation Plugin). Next, we created a systematic point sampling grid utilizing Krita version 5.2.6. A total of 51 sample points were overlaid on each hemispherical photo. The ground cover type was then determined at each of the 51 systematic point locations in each photo.

Assessment of Forest Canopy Closure: 

To measure canopy closure, we again transformed the 75 360° photos into hemispherical images pointing up rather than down, i.e., only focusing on the canopy and excluding the ground. Each photo was then separately analyzed utilizing the % Cover app. The % Cover app is an environmental application that was designed to be used on iOS devices and provides a direct estimate of canopy closure.