Mapping of mangrove coverage and canopy height using LiDAR data at Sangkulirang District, East Kutai, East Borneo

Mahadi, Ariefianto Tri; Siregar, Vincentius P.; Nursugi,

doi:10.1088/1755-1315/176/1/012026

Cited by 3 publications

(3 citation statements)

References 6 publications

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“…In the United States, it has been used for the delimitation of individual deciduous trees, with a resolution of 2.3 points/m 2 (Shao et al, 2019). In Indonesia, the cover and height of the mangrove canopy were mapped, with a resolution of 4 points/ m 2 (Mahadi et al, 2018). In Malaysia, a model was developed to delineate individual trees in a tropical forest, with a resolution of 8.8 points/m 2 (Wan- Mohd et al, 2017).…”

Section: Discussionmentioning

confidence: 99%

LiDAR modeling to determine the height of shade canopy tree in cocoa agrosystems as available habitat for wildlife

Díaz¹

2022

International Journal of Engineering and Geosciences

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Conservation Canopy Height Humid Tropics Point Cloud ModelAgrosystems have different canopy strata due to shade trees that serve as available habitats for endangered species such as birds, reptiles, and mammals. LiDAR is a technology used to assess habitat quality as a support for designing conservation strategies. The objective of this research was to develop a model with data derived from LiDAR to obtain the height of the shade canopy in cocoa agrosystems, as a habitat available for wildlife species. Through the data of the height of the vegetation taken in the field and the data obtained from a LiDAR point cloud, the Canopy Height Model was generated. The data from the mapping of the canopy height model of the agrosystems taken as study sites were validated using the coefficient of determination (R 2 ), mean absolute error (MAE), and the RMSE. The mean canopy height at the study sites was 14.63, 13.84, and 13.95 m, and the results of the validation using the model predicted canopy height shows good agreement with the actual value with an R 2 of 0.86, and very low values of MAE=1.88, MSE=5.64, and RMSE=2.37, which indicates that they have an acceptable degree regarding the canopy height model between the LiDAR data and the data taken in the field. Research using LiDAR provides useful information to determine the height of the canopy, in the cocoa agrosystems up to 3 strata are found, this is due to the diversity of tree species used as shade, ranging from timber, fruit, ornamental, which are used as feeding, nesting, and resting of wildlife, in the study area populations of howler monkey species that are listed as endangered by the International Union for Conservation of Nature (IUCN), in addition to other species such as bats and birds, with the presence of these species indicate that the cocoa agrosystems, serve as a habitat for a diversity of species, which is why it is important to conserve these agrosystems in the humid tropics.

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Section: Discussionmentioning

confidence: 99%

LiDAR modeling to determine the height of shade canopy tree in cocoa agrosystems as available habitat for wildlife

Díaz¹

2022

International Journal of Engineering and Geosciences

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“…The area of interest in this study is located in the mangrove area, surrounding Tanjung Manis Village, Sangkulirang District (Figure 1). Mangrove coverage at Sangkulirang District, East Kutai, East Borneo has an area of 64.07 km 2 of mangrove distribution [9]. The tools used in this research were measuring tape, rope, and pipe for stakes to make the plot.…”

Section: Study Sitementioning

confidence: 99%

Estimation of carbon stock at the mangrove forest of Sangkulirang District, East Kutai Regency, East Kalimantan Province

Andari,

Komara,

Kurniawan

2023

IOP Conf. Ser.: Earth Environ. Sci.

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Mangrove forests provide environmental, economic, and social benefits such as fish breeding, lumber production, water purification, recreation, education, and carbon sequestration. Mangroves are important organic carbon sinks, and there is a lot of interest in using them to reduce greenhouse gas emissions. Future climate change and deforestation would have a negative impact on organic carbon storage potential, hence worldwide estimates of future change remain a major research subject. The carbon stock varies by location. The purpose of this study was to estimate the carbon stock of mangroves in Sangkulirang District, East Kutai, East Borneo. Mangrove sediment organic carbon, above-ground biomass, under-ground biomass, and necromass were the parameters studied. Carbon stock was conducted by surveying the mangrove species, diameter, and height on a plot of 20x20m for tree, 10x10m for pole, 5x5 m for sapling, and 2x2 m for seedling. The biomass and carbon stock estimation using an allometric equation. Necromass carbon was conducted by taking a necromas in 1x1m plot and weight them for wet and dry weight. The mangrove carbon estimation method of Indonesian National Standard SNI_7724-2011 was applied in this study. According to the research, the total average carbon in mangroves in Sangkulirang District is 1386,87 Mg C ha-1.

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“…Several recent studies have demonstrated the use of Lidar for high-quality digital surface models (Brédif et al, 2013;Huo et al, 2018;Mahadi et al, 2018;Margolis et al, 2017;Shirowzhan & Trinder, 2017). The increasing quality of digital airborne cameras and improvements in matching algorithms allow for an automatic image-based acquisition as a suitable alternative (Haala & Rothermel, 2012).…”

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confidence: 99%

Urban Feature Extraction from Merged Airborne LiDAR Data and Digital Camera Data

Taha

Ramzi

Syarawi

et al. 2021

Geoplanning: Journal of Geomatics and Planning

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Until recently, the most highly accurate digital surface models were obtained from airborne lidar. With the development of a new generation of large format digital photogrammetric aerial camera, a fully digital photogrammetric workflow became possible. Digital airborne images are sources for elevation extraction and orthophoto generation. This research concerned with the generation of digital surface models and orthophotos as applications from high-resolution images. In this research, the following steps were performed. A Benchmark data of LIDAR and digital aerial camera have been used. Firstly, image orientation, AT have been performed. Then the automatic digital surface model DSM generation has been produced from the digital aerial camera. Thirdly true digital ortho has been generated from the digital aerial camera also orthoimage will be generated using LIDAR digital elevation model (DSM). Leica Photogrammetric Suite (LPS) module of Erdsa Imagine 2014 software was utilized for processing. Then the resulted orthoimages from both techniques were mosaicked. The results show that automatic digital surface model DSM that been produced from digital aerial camera method has very high dense photogrammetric 3D point clouds compared to the LIDAR 3D point clouds. It was found that the true orthoimage produced from the second approach is better than the true orthoimage produced from the first approach. The five approaches were tested for classification of the best-orthorectified image mosaic using subpixel based (neural network) and pixel-based ( minimum distance and maximum likelihood).Multicues were extracted such as texture(entropy-mean),Digital elevation model, Digital surface model ,normalized digital surface model (nDSM) and intensity image. The contributions of the individual cues used in the classification have been evaluated. It was found that the best cue integration is intensity (pan) +nDSM+ entropy followed by intensity (pan) +nDSM+mean then intensity image +mean+ entropy after that DSM )image and two texture measures (mean and entropy) followed by the colour image. The integration with height data increases the accuracy. Also, it was found that the integration with entropy texture increases the accuracy. Resulted in fifteen cases of classification it was found that maximum likelihood classifier is the best followed by minimum distance then neural network classifier. We attribute this to the fine resolution of the digital camera image. Subpixel classifier (neural network) is not suitable for classifying aerial digital camera images.

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Mapping of mangrove coverage and canopy height using LiDAR data at Sangkulirang District, East Kutai, East Borneo

Cited by 3 publications

References 6 publications

LiDAR modeling to determine the height of shade canopy tree in cocoa agrosystems as available habitat for wildlife

LiDAR modeling to determine the height of shade canopy tree in cocoa agrosystems as available habitat for wildlife

Estimation of carbon stock at the mangrove forest of Sangkulirang District, East Kutai Regency, East Kalimantan Province

Urban Feature Extraction from Merged Airborne LiDAR Data and Digital Camera Data

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