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

2021 ◽  
Vol 13 (23) ◽  
pp. 4794
Author(s):  
Nicolò Camarretta ◽  
Martin Ehbrecht ◽  
Dominik Seidel ◽  
Arne Wenzel ◽  
Mohd. Zuhdi ◽  
...  
Keyword(s):  
Land Use ◽  
Oil Palm ◽  
Vegetation Structure ◽  
Native Species ◽  
Laser Scanning ◽  
Airborne Laser Scanning ◽  
Rubber Plantations ◽  
Airborne Laser ◽  
Jungle Rubber ◽  
Structural Metrics

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.

Using Airborne Laser Scanning to characterize different land uses in a tropical landscape based on their structural complexity

2021 ◽  
Author(s):  
Nicoló Camarretta ◽  
Martin Ehbrecht ◽  
Arne Wenzel ◽  
Mohd Zuhdi ◽  
Miryam S. Merk ◽  
...  
Keyword(s):  
Land Use ◽  
Tropical Forest ◽  
Tropical Forests ◽  
Forest Structure ◽  
Oil Palm ◽  
Vegetation Structure ◽  
Laser Scanning ◽  
Structural Complexity ◽  
Airborne Laser ◽  
Structural Metrics

<p>Accurate characterization of land use and land cover (LULC) is important in a rapidly changing environment such as the Indonesian tropics. Over the past 30 years, native tropical forests have been cleared and replaced by fast-growing cash-crops, such as oil palm and rubber plantations. This change in land use dramatically alters the vegetation structure of the entire region. Vegetation structural complexity is highly variable in tropical forests, and provides habitat to a large number of native species. In addition, vegetation structure has an impact on micro-climate and the exchange of greenhouse gases (GHG), water and energy. Measuring vegetation structure in the field can be costly and time consuming, particularly in remote, inaccessible areas of tropical forest. In contrast, Airborne Laser Scanning (ALS) can provide very detailed three-dimensional information on forest structure without the need to reach remote areas in the field. Here, we aim to study the potential of ALS-derived measures of structural complexity as ecological indicators to highlight differences in forest structure across a gradient of LULC in Sumatra, Indonesia. We analysed the structural complexity of four main LULC types relevant to the region: tropical secondary forests, rubber agroforests, oil palm plantations and shrublands. Several structural metrics have been extracted from ALS data over 136 circular 0.1 ha plots (34 plots per LULC type): top height, height percentiles, rumple index, leaf area index (LAI), effective number of layers (ENL), vegetation cover, number of gaps. Results from a Principal Component Analysis (PCA) indicated number of gaps to be a major driver associated with the occurrence of oil palm plantations, while higher values of key structural metrics, such as top height, LAI and ENL were strongly linked with the presence of secondary tropical forest plots. Furthermore, a clear separation in metrics behaviour between forest and oil palm plots was evident from the pairwise comparison of these metrics, with rubber and shrubland plots behaving similarly to either forests or oil palm plantings according to different metrics. Our results show clear distinctions in several structural attributes among different LULC, which indicate the need for careful considerations regarding the impact of land-use change on ecosystem functioning, biodiversity and climate.</p>

scholarly journals Tropical Peatland Vegetation Structure and Biomass: Optimal Exploitation of Airborne Laser Scanning

2018 ◽  
Vol 10 (5) ◽  
pp. 671 ◽  
Author(s):  
Chloe Brown ◽  
Doreen Boyd ◽  
Sofie Sjögersten ◽  
Daniel Clewley ◽  
Stephanie Evers ◽  
...  
Keyword(s):  
Vegetation Structure ◽  
Laser Scanning ◽  
Airborne Laser Scanning ◽  
Tropical Peatland ◽  
Airborne Laser ◽  
Optimal Exploitation

scholarly journals Forest Inventory and Diversity Attribute Modelling Using Structural and Intensity Metrics from Multi-Spectral Airborne Laser Scanning Data

2020 ◽  
Vol 12 (13) ◽  
pp. 2109 ◽  
Author(s):  
Tristan R.H. Goodbody ◽  
Piotr Tompalski ◽  
Nicholas C. Coops ◽  
Chris Hopkinson ◽  
Paul Treitz ◽  
...  
Keyword(s):  
Random Forest ◽  
Forest Inventory ◽  
Laser Scanning ◽  
Near Infrared ◽  
Basal Area ◽  
Shannon Index ◽  
Airborne Laser Scanning ◽  
Spectral Indices ◽  
Airborne Laser ◽  
Structural Metrics

Airborne laser scanning (ALS) systems tuned to the near-infrared (NIR; 1064 nm) wavelength have become the best available data source for characterizing vegetation structure. Proliferation of multi-spectral ALS (M-ALS) data with lasers tuned at two additional wavelengths (commonly 532 nm; green, and 1550 nm; short-wave infrared (SWIR)) has promoted interest in the benefit of additional wavelengths for forest inventory modelling. In this study, structural and intensity based M-ALS metrics were derived from wavelengths independently and combined to assess their value for modelling forest inventory attributes (Lorey’s height (HL), gross volume (V), and basal area (BA)) and overstorey species diversity (Shannon index (H), Simpson index (D), and species richness (R)) in a diverse mixed-wood forest in Ontario, Canada. The area-based approach (ABA) to forest attribute modelling was used, where structural- and intensity-based metrics were calculated and used as inputs for random forest models. Structural metrics from the SWIR channel (SWIRstruc) were found to be the most accurate for H and R (%RMSE = 14.3 and 14.9), and NIRstruc were most accurate for V (%RMSE = 20.4). The addition of intensity metrics marginally increased the accuracy of HL models for SWIR and combined channels (%RMSE = 7.5). Additionally, a multi-resolution (0.5, 1, 2 m) voxel analysis was performed, where intensity data were used to calculate a suite of spectral indices. Plot-level summaries of spectral indices from each voxel resolution alone, as well as combined with structural metrics from the NIR wavelength, were used as random forest predictors. The addition of structural metrics from the NIR band reduced %RMSE for all models with HL, BA, and V realizing the largest improvements. Intensity metrics were found to be important variables in the 1 m and 2 m voxel models for D and H. Overall, results indicated that structural metrics were the most appropriate. However, the inclusion of intensity metrics, and continued testing of their potential for modelling diversity indices is warranted, given minor improvements when included. Continued analyses using M-ALS intensity metrics and voxel-based indices would help to better understand the value of these data, and their future role in forest management.

scholarly journals Estimation of 3D vegetation structure from waveform and discrete return airborne laser scanning data

2012 ◽  
Vol 118 ◽  
pp. 151-161 ◽  
Author(s):  
Eva Lindberg ◽  
Kenneth Olofsson ◽  
Johan Holmgren ◽  
Håkan Olsson
Keyword(s):  
Vegetation Structure ◽  
Laser Scanning ◽  
Airborne Laser Scanning ◽  
Airborne Laser

scholarly journals Diversity of butterflies (Lepidoptera) across rainforest transformation systems in Jambi, Sumatra, Indonesia

2020 ◽  
Vol 21 (11) ◽  
Author(s):  
RAWATI PANJAITAN ◽  
JOCHEN DRESCHER ◽  
DAMAYANTI BUCHORI ◽  
DJUNIJANTI PEGGIE ◽  
IDHAM SAKTI HARAHAP ◽  
...  
Keyword(s):  
Land Use ◽  
Oil Palm ◽  
Rapid Assessment ◽  
High Rate ◽  
Rubber Plantation ◽  
Butterfly Species ◽  
Rubber Plantations ◽  
Animal Populations ◽  
Jungle Rubber ◽  
Transformation Systems

Abstract. Panjaitan R, Drescher J, Buchori D, Peggie D, Harahap IS, Scheu S, Hidayat P. 2020. Diversity of butterflies (Lepidoptera) across rainforest transformation systems in Jambi, Sumatra, Indonesia. Biodiversitas 21: 5119-5127. The high rate of land conversion has put pressure on biodiversity, especially in the tropics. The lowlands of Sumatra, for example, are dominated by increasingly extensive areas of oil palm and rubber monoculture plantations, while rainforests are continuously vanishing. The status of many rainforest animal populations, including iconic insect groups such as butterflies, is largely unclear. With a rapid assessment approach, we studied butterflies along land-use gradients from lowland rainforest, via jungle rubber plantations (rubber agroforest system), to monocultures of rubber and oil palm in Jambi Province, Sumatra. Butterflies were caught in a nested replication design at eight research plots at each of the forest, jungle rubber, and rubber and oil palm locations. Butterfly abundance was the highest in the rainforest (204.3±82.1), slightly lower in the jungle rubber and oil palm areas (164.9±61 and 169.3±94.9, respectively), and the lowest in the rubber plantation (108.8±38.5). Similarly, butterfly species richness was the highest in the forest and jungle rubber areas (47.1±7.7 and 38.8±7.6, respectively), followed by the oil palm area (33.3±9.8), and the lowest in the rubber plantation (26.1±9.1). Likewise, Shannon-Wiener diversity was the highest in the rainforest, at an intermediate level in the jungle rubber, and lowest in the oil palm and rubber plantations. Butterfly community composition in the rainforest was very different from that in the other three land-use systems, in which it was similar. Overall, the study demonstrates that rainforest butterfly communities cannot be sustained in agricultural systems, highlighting the importance of rainforests for conserving the diversity of arthropods.

scholarly journals New Advances in Automated Urban Modelling from Airborne Laser Scanning Data

2011 ◽  
Vol 5 (3) ◽  
pp. 196-208 ◽  
Author(s):  
D. F. Laefer ◽  
T. Hinks ◽  
H. Carr ◽  
L. Truong-Hong
Keyword(s):  
Laser Scanning ◽  
Airborne Laser Scanning ◽  
Airborne Laser ◽  
Urban Modelling

scholarly journals Archaeological Surveying of Subarctic and Arctic Landscapes: Comparing the Performance of Airborne Laser Scanning and Remote Sensing Image Data

2021 ◽  
Vol 13 (4) ◽  
pp. 1917
Author(s):  
Alma Elizabeth Thuestad ◽  
Ole Risbøl ◽  
Jan Ingolf Kleppe ◽  
Stine Barlindhaug ◽  
Elin Rose Myrvoll
Keyword(s):  
Remote Sensing ◽  
Laser Scanning ◽  
Digital Terrain Model ◽  
Image Data ◽  
Remote Sensing Image ◽  
Airborne Laser Scanning ◽  
Aerial Images ◽  
Detection Rates ◽  
Airborne Laser ◽  
Pros And Cons

What can remote sensing contribute to archaeological surveying in subarctic and arctic landscapes? The pros and cons of remote sensing data vary as do areas of utilization and methodological approaches. We assessed the applicability of remote sensing for archaeological surveying of northern landscapes using airborne laser scanning (LiDAR) and satellite and aerial images to map archaeological features as a basis for (a) assessing the pros and cons of the different approaches and (b) assessing the potential detection rate of remote sensing. Interpretation of images and a LiDAR-based bare-earth digital terrain model (DTM) was based on visual analyses aided by processing and visualizing techniques. 368 features were identified in the aerial images, 437 in the satellite images and 1186 in the DTM. LiDAR yielded the better result, especially for hunting pits. Image data proved suitable for dwellings and settlement sites. Feature characteristics proved a key factor for detectability, both in LiDAR and image data. This study has shown that LiDAR and remote sensing image data are highly applicable for archaeological surveying in northern landscapes. It showed that a multi-sensor approach contributes to high detection rates. Our results have improved the inventory of archaeological sites in a non-destructive and minimally invasive manner.

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