Using Airborne Laser Scanning to Characterize Land-Use Systems in a Tropical Landscape Based on Vegetation Structural Metrics

2021-11-26 | journal article; research paper. A publication with affiliation to the University of Göttingen.

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​Using Airborne Laser Scanning to Characterize Land-Use Systems in a Tropical Landscape Based on Vegetation Structural Metrics​
Camarretta, N. ; Ehbrecht, M.; Seidel, D. ; Wenzel, A.; Zuhdi, M.; Merk, M. S. & Schlund, M. et al.​ (2021) 
Remote Sensing13(23) art. 4794​.​ DOI: 

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Camarretta, Nicolò ; Ehbrecht, Martin; Seidel, Dominik ; Wenzel, Arne; Zuhdi, Mohd.; Merk, Miryam Sarah; Schlund, Michael; Erasmi, Stefan; Knohl, Alexander 
Many Indonesian forests have been cleared and replaced by fast-growing cash crops (e.g., oil palm and rubber plantations), altering the vegetation structure of entire regions. Complex vegetation structure provides habitat niches to a large number of native species. Airborne laser scanning (ALS) can provide detailed three-dimensional information on vegetation structure. Here, we investigate the potential of ALS metrics to highlight differences across a gradient of land-use management intensities in Sumatra, Indonesia. We focused on tropical rainforests, jungle rubber, rubber plantations, oil palm plantations and transitional lands. Twenty-two ALS metrics were extracted from 183 plots. Analysis included a principal component analysis (PCA), analysis of variance (ANOVAs) and random forest (RF) characterization of the land use/land cover (LULC). Results from the PCA indicated that a greater number of canopy gaps are associated with oil palm plantations, while a taller stand height and higher vegetation structural metrics were linked with rainforest and jungle rubber. A clear separation in metrics performance between forest (including rainforest and jungle rubber) and oil palm was evident from the metrics pairwise comparison, with rubber plantations and transitional land behaving similar to forests (rainforest and jungle rubber) and oil palm plantations, according to different metrics. Lastly, two RF models were carried out: one using all five land uses (5LU), and one using four, merging jungle rubber with rainforest (4LU). The 5LU model resulted in a lower overall accuracy (51.1%) due to mismatches between jungle rubber and forest, while the 4LU model resulted in a higher accuracy (72.2%). Our results show the potential of ALS metrics to characterize different LULCs, which can be used to track changes in land use and their effect on ecosystem functioning, biodiversity and climate.
Issue Date
Remote Sensing 
SFB 990 | Project Ö (PR): Lehrerbildung für die Gesellschaft: Wissen aus EFForTS für Indonesien verfügbar machen 
SFB 990: Ökologische und sozioökonomische Funktionen tropischer Tieflandregenwald-Transformationssysteme (Sumatra, Indonesien) 
SFB 990 | A | A03: Untersuchung von Land-Atmosphäre Austauschprozesse in Landnutzungsänderungs-Systemen 
SFB 990 | B | B09: Oberirdische Biodiversitätsmuster und Prozesse in Regenwaldtransformations-Landschaften 
SFB 990 | Z | Z02: Central Scientific Support Unit 
SFB 990 | INF: Forschungsdatenmanagement und integrative statistische Datenanalyse 
Fakultät für Forstwissenschaften und Waldökologie ; Büsgen-Institut ; Burckhardt-Institut ; Abteilung Bioklimatologie ; Abteilung Räumliche Strukturen und Digitalisierung von Wäldern ; Abteilung Waldbau und Waldökologie der gemäßigten Zonen ; Fakultät für Agrarwissenschaften ; Department für Nutzpflanzenwissenschaften ; Abteilung Funktionelle Agrobiodiversität 
Open-Access-Publikationsfonds 2021



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