Comparing airborne and terrestrial LiDAR with ground-based inventory metrics of vegetation structural complexity in oil palm agroforests

作者：Vannesa Montoya‐Sánchez, Nicolò Camarretta, Martin Ehbrecht, Michael Schlund, Gustavo B. Paterno, Dominik Seidel, Nathaly R. Guerrero‐Ramírez, Fabian Brambach, Dirk Hölscher, Holger Kreft, Bambang Irawan, Leti Sundawati, Delphine Clara Zemp · 发表于：Ecological Indicators · 年份：2024 · DOI：10.1016/j.ecolind.2024.112306 · 被引用次数：13 · 研究领域：Remote Sensing and LiDAR Applications、Remote Sensing in Agriculture、Oil Palm Production and Sustainability

• Compared ALS, TLS, and ground data in 52 tree islands in an oil palm landscape in Sumatra. • ALS and TLS similarly capture canopy gaps and tree height metrics. • LiDAR complements ground data, enhancing 3D vegetation structural characterization. Vegetation structural complexity is an important component of forest ecosystems, influencing biodiversity and functioning. Due to the heterogeneous distribution of vegetation elements, structural complexity underpins ecological dynamics, species composition, microclimate, and habitat diversity. Field measurements and Light Detection and Ranging (LiDAR) data, such as airborne (ALS) and terrestrial (TLS), can assess structural characteristics of forest and agroforestry systems at various spatial scales. This assessment is urgently needed for monitoring ecosystem restoration in degraded lands (e.g., in oil palm landscapes), where it is not well-known how structural measures derived from these different approaches relate to each other. Here, we compared the degree of correlation between individual and multivariate datasets of vegetation structural complexity metrics derived from ALS, TLS, and ground-based inventory approaches. The study was conducted in a 140 ha oil palm monoculture, enriched with 52 plots in the form of tree islands representing agroforestry systems of varying sizes and planted diversity levels in Sumatra, Indonesia. Our datasets comprised 25 ALS, five TLS, and nine ground-based inventory metrics. We studied correlatio...