Influence of micro-topography and crown characteristics on tree height estimations in tropical forests based on LiDAR canopy height models.

Tree or canopy height is an important attribute for carbon stock estimation, forest management and habitat quality assessment. Airborne Laser Scanning (ALS) based on Light Detection and Ranging (LiDAR) has advantages over other remote sensing techniques for describing the structure of forests. However, sloped terrain can be challenging for accurate estimation of tree locations and heights based on a Canopy Height Model (CHM) generated from ALS data; a CHM is a height-normalised Digital Surface Model (DSM) obtained by subtracting a Digital Terrain Model (DTM) from a DSM. On sloped terrain, points at the same elevation on a tree crown appear to increase in height in the downhill direction, based on the ground elevations at these points. A point will be incorrectly identified as the treetop by individual tree crown (ITC) recognition algorithms if its height is greater than that of the actual treetop in the CHM, which will be recorded as the tree height. In this study, the influence of terrain slope and crown characteristics on the detection of treetops and estimation of tree heights is assessed using ALS data in a tropical forest with complex terrain (i.e. micro-topography) and tree crown characteristics. Locations and heights of 11,442 trees based on a DSM are compared with those based on a CHM. The horizontal (DH) and vertical displacements (DV) increase with terrain slope (r: 0.47 and r: 0.54 respectively, p < 0.001). The overestimations in tree height are up to 16.6 m on slopes greater than 50° in our study area in Sumatra. The errors in locations (DH) and tree heights (DV) are modelled for trees with conical and spherical tree crowns. For a spherical tree crown, DH can be modelled as R sin θ, and DV as R (sec θ – 1). In this study, a model is developed for an idealised conical tree crown, DV = R (tan θ – tan ψ), where R is the crown radius, and θ and ψ are terrain and crown angles respectively. It is shown that errors occur only when terrain angle exceeds the crown angle, with the horizontal displacement equal to the crown radius. Errors in location are seen to be greater for spherical than conical trees on slopes where crown angles of conical trees are less than the terrain angle. The results are especially relevant for biomass and carbon stock estimations in tropical forests where there are trees with large crown radii on slopes

LiDAR patch metrics for object-based clustering of forest types in a tropical rainforest

Tropical rainforests support a large proportion of the Earth’s plant and animal species within a restricted global distribution, and play an important role in regulating the Earth’s climate. However, the existing knowledge of forest types or habitats is relatively poor and there are large uncertainties in the quantification of carbon stock in these forests. Airborne Laser Scanning, using LiDAR, has advantages over other remote sensing techniques for describing the three-dimensional structure of forests. With respect to the habitat requirements of different species, forest structure can be defined by canopy height, canopy cover and vertical arrangement of biomass. In this study, forest patches were identified based on classification and hierarchical merging of a LiDAR-derived Canopy Height Model in a tropical rainforest in Sumatra, Indonesia. Attributes of the identified patches were used as inputs for k-medoids clustering. The clusters were then analysed by comparing them with identified forest types in the field. There was a significant association between the clusters and the forest types identified in the field, to which arang forests and mixed agro-forests contributed the most. The topographic attributes of the clusters were analysed to determine whether the structural classes, and potentially forest types, were related to topography. The tallest clusters occurred at significantly higher elevations (> 850 m) and steeper slopes (> 26°) than the other clusters. These are likely to be remnants of undisturbed primary forests and are important for conservation and habitat studies and for carbon stock estimation. This study showed that LiDAR data can be used to map tropical forest types based on structure, but that structural similarities between patches of different floristic composition or human use histories can limit habitat separability as determined in the field

Fine-scale vertical position as an indicator of vegetation in alkaligrasslands – Case study based on remotely sensed data

tVertical position is an important driver of vegetation zonation at multiple scales, via determining abioticenvironmental parameters, such as climate, soil properties and water balance. In inland alkali landscapes,elevation is a key factor for understanding patterns of salt accumulation and water table which is thereforeconsidered a good indicator of alkali vegetation types. Remote sensing techniques offer viable solutionsfor linking elevation data to vegetation patterns by providing an elevation model of extended areas.Our goal was to test the relationships between fine-scale differences in vertical position and vegetationpatterns in inland alkali landscapes by vegetation data collected in the field and elevation data generatedusing airborne laser scanning (ALS). We studied whether vertical position influences vegetation patternsat the level of main vegetation groups (based on alliances) or even at the level of associations. Our studysites were situated in a lowland alkali landscape in Hortobágy National Park (East-Hungary). We groupedthe associations into four main vegetation groups: loess grasslands, alkali steppes, open alkali swards andalkali meadows. Even though we detected a very limited range (121 cm) in the vertical position of the mainvegetation groups, they were well separated by their vertical positions. At the level of associations, a moredetailed elevation-based distinction was also possible in many cases. The revealed elevation–vegetationcorrelations show that high-resolution mapping based on ALS remote sensing techniques is an idealsolution in complex lowland areas, such as alkali landscapes. Our findings suggest that in other typesof lowland landscapes, characterised by elevation differences, the applied method might hold a greatpotential as a supporting tool for vegetation mapping

Sleeping trees and sleep-related behaviours of the siamang (Symphalangus syndactylus) in a tropical lowland rainforest, Sumatra, Indonesia

Sleeping tree selection and related behaviours of a family group and a solitary female siamang (Symphalangus syndactylus) were investigated over a 5-month period in northern Sumatra, Indonesia. We performed all day follows, sleeping tree surveys and forest plot enumerations in the field. We tested whether: (1) physical characteristics of sleeping trees and the surrounding trees, together with siamang behaviours, supported selection based on predation risk and access requirements; (2) the preferences of a solitary siamang were similar to those of a family group; and (3) sleeping site locations within home ranges were indicative of home range defence, scramble competition with other groups or other species, or food requirements. Our data showed that (1) sleeping trees were tall, emergent trees with some, albeit low, connectivity to the neighbouring canopy, and that they were surrounded by other tall trees. Siamangs showed early entry into and departure from sleeping trees, and slept at the ends of branches. These results indicate that the siamangs’ choice of sleeping trees and related behaviours were strongly driven by predator avoidance. The observed regular reuse of sleeping sites, however, did not support anti-predation theory. (2) The solitary female displayed selection criteria for sleeping trees that were similar to those of the family group, but she slept more frequently in smaller trees than the latter. (3) Siamangs selected sleeping trees to avoid neighbouring groups, monopolise resources (competition), and to be near their last feeding tree. Our findings indicate selectivity in the siamangs’ use of sleeping trees, with only a few trees in the study site being used for this purpose. Any reduction in the availability of such trees might make otherwise suitable habitat unsuitable for these highly arboreal small apes

PENGEMBANGAN AUDIBLE BOOKS BERBASIS ETNOMATEMATIKA SEBAGAI MEDIA LITERASI UNTUK SISWA DI SEKOLAH DASAR

Rendahnya kemampuan matematika siswa dapat disebabkan oleh berbagai aspek, salah satunya kuranya inovasi dalam buku pembelajaran siswa. Penelitian ini merupakan penelitian pengembangan (Research & Development) yang bertujuan untuk mengembangkan buku digital matematika Audible Books yang berbasis etnomatematika untuk siswa Sekolah Dasar. Penelitian ini menggunakan model pengembangan Plomp yang terdiri dari tiga fase yaitu, fase penelitian awal fase pengembangan, dan fase penilaian. Teknik pengumpulan data dilakukan dengan menggunakan angket. Validasi Audible Books dilakukan oleh 4 orang validator, hasil validasi media diperoleh nilai validitas sebesar 0,90 dengan kategori “Sangat Valid”. Uji praktikalitas diberikan kepada siswa dan guru, hasil dari uji praktikalitas siswa diperoleh persentase sebesar 83,54% dengan kategori “Sangat Praktis”. Hasil uji praktikalitas guru diperoleh persentase sebesar 88,75% dengan kategori “Sangat Praktis”. Berdasarkan hasil validasi dan praktikalitas yang diperoleh, dapat disimpulkan bahwa media Audible Books yang dikembangkan memenuhi kriteria valid dan praktis.Kata Kunci: Audible Books, Buku Digital Matematia, Model Plom

PENGARUH PENGGUNAAN MEDIA AUDIBLE BOOKS TERHADAP KEMAMPUAN COMPUTATION THINKING SISWA DI SEKOLAH DASAR

Computation Thinking adalah kemampuan yang melibatkan penalaran secara logis dalam pemecahan masalah dalam kehidupan sehari-hari yang harus dimiliki oleh setiap individu. Penelitian ini dilaksanakan untuk melihat pengaruh dari penggunaan media buku digital bersuara yang disebut dengan Audible Books terhadap kemampuan Computation Thinking siswa kelas V di Sekolah Dasar Pekanbaru. Penelitian ini menggunakan pendekatan kuantitatif kuasi eksperimen. Berdasarkan penelitian yang telah dilakukan, diperoleh perhitungan persentase secara keseluruhan dari Computation Thinking siswa pada tahap pretest sebesar 50,97% yang berarti masih berada pada tahap rendah. Setelah siswa diberi perlakuan dengan menggunakan media Audible Books yang memuat materi matematika, diperoleh hasil dari posttest dengan persentase sebesar 65,16% hal ini berarti kemampuan Computation Thinking siswa meningkat dan berada pada kategori sedang. Perolehan hasil uji T diperoleh nilai Sig.(2-tailed) sebesar 0,00 dan Uji Wilcoxon diperoleh hasil selisih Mean Rank sebesar 14.00 dan perolehan Asymp. Sig. (2-tailed) sebesar 0,00 hal ini berarti terdapat peningkatan sesudah diberikan perlakuan dan sesuai dengan uji hipotesis jika Sig. (2-tailed) < 0,05 maka H0 ditolak dan H1 diterima dan disimpulkan bahwa terdapat pengaruh yang signifikan dari penggunaan audible books terhadap kemampuan Computation Thinking siswa. Untuk hasil perhitungan mean N Gain diperoleh sebesar 0,343 hal ini berarti nilai gain berada diantara 0,3-0,7 yang berarti penggunaan Audible Books efektif untuk meningkatkan kemampuan Computation Thinking siswa. Penggunaan Audible Books memiliki pengaruh yang signifikan terhadap kemampuan Computation Thinking siswa dan media Audible Books cukup efektif untuk digunakan sebagai media dalam meningkatkan kemampuan Computation Thinking siswa

Structural attributes of individual trees for identifying homogeneouspatches in a tropical rainforest

Mapping and monitoring tropical rainforests and quantifying their carbon stocks are important, bothfor devising strategies for their conservation and mitigating the effects of climate change. AirborneLaser Scanning (ALS) has advantages over other remote sensing techniques for describing the three-dimensional structure of forests. This study identifies forest patches using ALS-based structural attributesin a tropical rainforest in Sumatra, Indonesia. A method to group trees with similar attributes into forestpatches based on Thiessen polygons and k-medoids clustering is developed, combining the advantagesof both raster and individual tree–based methods. The structural composition of the patches could be anindicator of habitat type and quality. The patches could also be a basis for developing allometric modelsfor more accurate estimation of carbon stock than is currently possible with generalised models

Locating emergent trees in a tropical rainforest using data from an Unmanned Aerial Vehicle (UAV)

Emergent trees, which are taller than surrounding trees with exposed crowns, provide crucial services to several rainforest species especially to endangered primates such as gibbons and siamangs (Hylobatidae). Hylobatids show a preference for emergent trees as sleeping sites and for vocal displays, however, they are under threat from both habitat modifications and the impacts of climate change. Traditional plot-based ground surveys have limitations in detecting and mapping emergent trees across a landscape, especially in dense tropical forests. In this study, a method is developed to detect emergent trees in a tropical rainforest in Sumatra, Indonesia, using a photogrammetric point cloud derived from RGB images collected using an Unmanned Aerial Vehicle (UAV). If a treetop, identified as a local maximum in a Digital Surface Model generated from the point cloud, was higher than the surrounding treetops (Trees_EM), and its crown was exposed above its neighbours (Trees_SL; assessed using slope and circularity measures), it was identified as an emergent tree, which might therefore be selected preferentially as a sleeping tree by hylobatids. A total of 54 out of 63 trees were classified as emergent by the developed algorithm and in the field. The algorithm is based on relative height rather than canopy height (due to a lack of terrain data in photogrammetric point clouds in a rainforest environment), which makes it equally applicable to photogrammetric and airborne laser scanning point cloud data