Estimasi Jumlah Carbon Stock Aboveground Menggunakan Data Backpack Lidar (Studi Kasus : Perkebunan Jati Tinapan, Kec. Todanan, Kabupaten Blora, Jawa Tengah)

Sitinjak, Aurelio Jeremi Basten (2026) Estimasi Jumlah Carbon Stock Aboveground Menggunakan Data Backpack Lidar (Studi Kasus : Perkebunan Jati Tinapan, Kec. Todanan, Kabupaten Blora, Jawa Tengah). Other thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Karbon (CO) merupakan unsur penting di atmosfer yang berkaitan dengan pemanasan global. Sektor pertanian menyumbangkan 10-14% dari total gas rumah kaca (GRK) yang berasal dari aktivitas manusia (antropogenik). Stok karbon tumbuhan semakin penting dalam konteks potensi energi terbarukan dan penyimpanan karbon. Lokasi penetilian berada hutan jati di Blora Teknologi LiDAR dapat membantu memprediksi stok karbon yang ada dalam masa mendatang. Backpack LiDAR dan lapangan mempunyai kesesuaian ketika dikalibrasi pada resolusi spasial. Sebagai teknik deteksi aktif, LiDAR (Light Detection and Ranging) memiliki keunggulan dibandingkan teknologi pengindraan jauh pasif dalam hal memperoleh informasi struktural tentang objek tiga dimensi (3D). LiDAR sebagai alat akuisisi disini digunakan untuk lebih teliti dalam hal segmentasi dan pembagian jenis vegetasi tegakan pohon. LiDAR terbagi menjadi dua yaitu LiDAR dan Aerial-Based LiDAR. Ground-Based LiDAR, juga dikenal menggunakan teknologi laser untuk mengukur jarak dan bentuk objek di permukaan bumi. Aerial-Based LiDAR menggunakan teknologi laser yang dipasang pada pesawat udara / drone untuk mengukur jarak dan bentuk objek dari udara. Penggunaan Ground-Based LiDAR ini memang lebih dipertimbangkan dikarenakan lebih dibutuhkan data detail dari pohon meliputi batang, diameter dan tinggi pohon sehingga Pointcloud bisa dilihat lebih detail dibanding menggunakan Aerial LiDAR. Pointcloud adalah hasil pengukuran dari LiDAR yang berupa titik-titik tiga dimensi yang merepresentasikan skena yang diukur. Pointcloud dapat dihasilkan oleh baik Ground-Based LiDAR maupun Aerial-Based LiDAR. Karena dalam Pointcloud tersebut bersifat 3 Dimensi yang mampu melakukan segmentasi antar tegakan pohon. Setelah akuisisi data didapatkan data pointcloud, dilakukan proses filtering, georeferencing dan remove noise agar didapat hasil pointcloud yang lebih baik dan menghilangkan data/noise yang mengganggu. Pada proses georeferencing digunakan 5 titik GCP. Dari data segmentasi didapatkan jumlah pohon sebanyak 940 pohon. Sehingga setelah proses segmentasi pohon dibagi atas 5 cluster DBH (Diameter at Breast Height) dengan masing-masing sebesar 0,14 m, 0,262 m, 0,483 m, 0,697 m dan 0,875 m. Perhitungan jumlah estimasi stok karbon dengan menggunakan data LiDAR yang telah disegmentasi. Dari informasi tersebut dapat dihitung estimasi jumlah stok karbon dengan akurasi RMSE (Root Mean Square Error) vertical sebesar 0,195 m dan ketelitian vertikal dengan nilai 0,322 m. Dengan melakukan segmentasi membagi semua pohon menjadi 5 cluster berdasarkan nilai DBH dilakukan perhitungan stok karbon dan biomassa dengan rata-rata sebesar masing-masing untuk stok karbon 137,143 ton.C.ha-1 dan biomassa 66,781 ton.ha. Lalu telah dilakukan validasi data di lapangan untuk data DBH dengan nilai RMSE 0,018 m.
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Carbon (CO) is an important gas in the atmosphere related to global warming. The agricultural sector contributes 10-14% of the total greenhouse gases (GHGs) derived from human activities (anthropogenic). The dynamics of GHG research on teak plantations in Indonesia are not as fast as other plantation commodities (such as rice and teak) and are relatively lagging behind some teak producing countries in the world. Plant carbon stocks are increasingly important in the context of renewable energy potential and carbon storage. LiDAR technology can help predict future carbon stocks. LiDAR backpacks and the field have a good fit when calibrated at spatial resolution. As an active detection technique, LiDAR (Light Detection and Ranging) has an advantage over passive remote sensing technology in terms of obtaining structural information about three-dimensional (3D) objects. LiDAR as an acquisition tool here is used to be more thorough in terms of segmentation and division of tree stand vegetation types. LiDAR is divided into two, namely LiDAR and Aerial-Based LiDAR. Ground-Based LiDAR, also known for using laser technology to measure the distance and shape of objects on the earth's surface. This system is usually mounted on a tripod and can generate up to millions of three-dimensional coordinate points representing the scene being measured. Aerial-Based LiDAR uses laser technology mounted on aircraft/ drones to measure the distance and shape of objects from the air. Aerial-Based LiDAR is usually used to measure very large areas, such as forests, rivers, and other large areas. The use of Ground-Based LiDAR is indeed more considered because more detailed data is needed from trees including trunks, diameters and tree heights so that Pointcloud can be seen in more detail than using Aerial LiDAR. Pointcloud is the result of measurements from LiDAR in the form of three-dimensional dots that represent the measured scene. Pointclouds can be generated by both Ground-Based LiDAR and Aerial-Based LiDAR. Because in the Pointcloud there are 3 Dimensions that are able to segment between tree stands. After the data acquisition is obtained from pointcloud data, a filtering, georeferencing and noise removal process is carried out in order to obtain better pointcloud results and eliminate annoying data/noise. From the segmentation data, the number of trees was 940 trees. So that after the segmentation process, the tree is divided into 5 classes of DBH (Diameter at Breast Height) with 0.14 m, 0.262 m, 0.483 m, 0.697 m and 0.875221125 m. Calculation of the estimated amount of carbon stock using segmented LiDAR data. From this information, it can be calculated to estimate the amount of carbon stock by doing an accuracy, namely RMSE (Root Mean Square Error) vertical with a value of 0.195 m and vertical accuracy with a value of 0.322 m. By segmenting all trees into 5 classes based on DBH values, carbon stocks and biomass are calculated with an average of 137.143 tons each. C.ha-1 and biomass 66.781 tons.ha. Then data validation has been carried out in the field for DBH data with an RMSE value of 0.018 m.

Item Type:	Thesis (Other)
Uncontrolled Keywords:	Aboveground Biomass, DBH, Backpack LiDAR, Stok karbon, Pointcloud, Segmentasi.
Subjects:	G Geography. Anthropology. Recreation > G Geography (General) > G70.5.I4 Remote sensing
Divisions:	Faculty of Civil Engineering and Planning > Geomatics Engineering > 29202-(S1) Undergraduate Thesis
Depositing User:	Aurelio Jeremi Basten Sitinjak
Date Deposited:	23 Jul 2026 07:27
Last Modified:	23 Jul 2026 07:27
URI:	http://repository.its.ac.id/id/eprint/136521

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