Research Article: Using Unmanned Aerial Systems (UAS) to assay mangrove estuaries on the Pacific coast of Costa Rica

Date Published: June 5, 2019

Publisher: Public Library of Science

Author(s): Adam Yaney-Keller, Pilar Santidrián Tomillo, Jordan M. Marshall, Frank V. Paladino, Carlos Portillo-Quintero.

http://doi.org/10.1371/journal.pone.0217310

Abstract

Mangrove forests, one of the world’s most endangered ecosystems, are also some of the most difficult to access. This is especially true along the Pacific coast of Costa Rica, where 99% of the country’s mangroves occur. Unmanned Aerial Systems (UAS), or drones, have become a convenient tool for natural area assessment, and offer a solution to the problems of remote mangrove monitoring. This study is the first to use UAS to analyze the structure of a mangrove forests within Central America. Our goals were to (1) determine the forest structure of two estuaries in northwestern Costa Rica through traditional ground measurements, (2) assess the accuracy of UAS measurements of canopy height and percent coverage and (3) determine whether the normalized difference vegetation index (NDVI) could discriminate between the most abundant mangrove species. We flew a UAS equipped with a single NDVI sensor during the peak wet (Sept–Nov) and dry (Jan–Feb) seasons. The structure and species composition of the estuaries showed a possible transition between the wet mangroves of southern Costa Rica and the drier northern mangroves. UAS-derived measurements at 100 cm/pixel resolution of percent canopy coverage and maximum and mean canopy height were not statistically different from ground measurements (p > 0.05). However, there were differences in mean canopy height at 10 cm/pixel resolution (p = 0.043), indicating diminished returns in accuracy as resolution becomes extremely fine. Mean NDVI values of Avicennia germinans (most abundant species) changed significantly between seasons (p < 0.001). Mean NDVI of Rhizophora racemosa (second most abundant species) was significantly different from A. germinans and dry forest dominant plots during the dry season (p < 0.001), demonstrating NDVI’s capability of discriminating mangrove species. This study provides the first structural assessment of the studied estuaries and a framework for future studies of mangroves using UAS.

Partial Text

Mangrove forests are among one of the most rapidly disappearing ecosystems on earth, declining at a rate of 1–2% per year globally, a rate greater than or equal to declines in adjacent coral reefs and tropical rainforests [1]. Costa Rica alone contains 8% of the world’s mangrove forests, 99% of which are found on the Pacific coast [2]. These forests can provide a number of ecologically important services, including sequestering large amounts of carbon [3, 4], serving as nurseries for many marine fish and invertebrates, including economically important species [2, 4], and providing important stopover sites for migrating Nearctic birds [2, 5]. In areas with distinct dry seasons, such as the north Pacific coast of Costa Rica, these forests may also be important nesting and hunting habitats for a host of different wildlife species, including those displaced by human development in other coastal areas [2, 6]. Despite being protected in Costa Rica under the Coastal-Maritime Law (1977), Wildlife Law (1992) and Environmental Law (1995), mangrove forests in the country are increasingly under threat as human coastal populations grow [2, 7].

To answer these three questions, we used a small UAS equipped with an NDVI sensor to create georeferenced orthomosaic and three-dimensional maps of the Cabuyal and Zapotillal estuaries during both the wet and dry seasons.

This study is the first to accurately assess the mangrove forest structure and composition of a remote, neotropical mangrove forest using a UAS. The lack of statistically significant differences found between ground-survey and UAS-imagery derived measurements of canopy height and percent coverage for high resolution maps adds to the growing body of research indicating the usefulness and accuracy of UAS in the study of mangroves and other forest ecosystems [11, 12, 13, 14, 15, 16, 17, 24, 25, 53, 54, 55, 56].

 

Source:

http://doi.org/10.1371/journal.pone.0217310