scholarly journals Optimalisasi Foto Udara Unmanned Aerial Vehicle (UAV) Sebagai Media Pembelajaran Penginderaan Jauh

2019 ◽  
Vol 8 (1) ◽  
pp. 45
Author(s):  
Kristhoper Simanungkalit ◽  
Muhammad Ridha Syafii Damanik ◽  
Darwin Parlaungan Lubis
Keyword(s):  
Remote Sensing ◽  
Unmanned Aerial Vehicle ◽  
Aerial Photography ◽  
Student Response ◽  
Aerial Photographs ◽  
Aerial Image ◽  
Distortion Factor ◽  
Student Responses ◽  
Assessment Score ◽  
Aerial Vehicle

AbstractThis study aims (1) To find out how the accuracy of Unmanned Aerial Vehicle (UAV) aerial image quality using the Omission-Commission method. (2) How to use UAV aerial imagery as remote sensing learning media when viewed from the aspects of media feasibility, material worthiness, and student response. This research was conducted at the Medan State University Campus located at Jalan William Iskandar, Pasar V, Medan Estate Village, Medan North Sumatra. This location was chosen based on strategic location considerations for mapping. The results of this study indicate that the quality of the level of precision aerial photographs obtained from aerial photography results in the level of precision aerial photographs reaching above 95% with excellent categories, and aerial photographs obtained are more inclined towards omission which is influenced by the camera distortion factor , and the feasibility of UAV aerial photography learning media in terms of the aspects of the feasibility of the media achieving an assessment score of 85%, the feasibility aspects of the Material achieving an assessment score of 85% and, the results of the feasibility of instructional media based on material experts and media experts reach a score level of 85% and deserve to be used as a medium learning. The results of student responses obtained received an 89% assessment score, which results from the assessment of student responses that have been said to be good.Keywords: UAV, Remote Sensing, Unimed, Learning Media AbstrakPenelitian ini bertujuan (1) Untuk mengetahui bagaimana kualitas akurasi citra foto udara Unmanned Aerial Vehicle (UAV) dengan menggunakan metode Omisi-Komisi. (2) Bagaimana pemanfaatan citra foto udara UAV sebagai media pembelajaran penginderaan jauh bila di lihat dari aspek kelayakan media, kelayakan materi, dan respon mahasiswa. Penelitian ini dilaksanakan di Kampus Universitas Negeri Medan terletak di Jalan William Iskandar, Pasar V, Kelurahan Medan Estate, Medan Sumatera Utara. Lokasi ini dipilih atas pertimbangan lokasi yang strategis untuk melakukan pemetaan. Hasil penelitian ini menunjukkan bahwa Kualitas tingkat presisi foto udara yang didapatkan dari hasil pemotretan foto udara menghasilkan tingkat presisi foto udara mencapai diatas 95% dengan kategori sangat baik, dan foto udara yang didapatkan lebih condong ke arah omisi yang mana hal ini dipengaruhi oleh faktor distorsi kamera, dan Kelayakan media pembelajaran foto udara UAV ditinjau dari aspek kelayakan Media mencapai skor penilaian 85%, Aspek kelayakan Materi mencapai  skor penilaian 85% dan, hasil dari kelayakan media pembelajaran berdasarkan ahli materi dan ahli media mencapai tingkat skor 85% dan layak dijadikan sebagai media pembelajaran. hasil respon mahasiswa yang didapatkan mendapat skor penilaian 89% yang mana hasil dari penilaian respon mahasiswa sudah dikatakan bagus.Kata Kunci: UAV, Penginderaan Jauh, Unimed, Media Pembelajaran

scholarly journals Analysis Of Aerial Photography With Drone Type Fixed Wing In Kotabaru, Lampung

2018 ◽  
Vol 2 (1) ◽  
pp. 102-107
Author(s):  
Indreswari Suroso ◽  
Erwhin Irmawan
Keyword(s):  
Unmanned Aerial Vehicle ◽  
Aerial Photography ◽  
Ground Level ◽  
Aerial Photographs ◽  
Aerial Photos ◽  
Above Ground Level ◽  
The World ◽  
Air Capture ◽  
Aerial Vehicle ◽  
Operational Time

In the world of photography is very closely related to the unmanned aerial vehicle called drones. Drones mounted camera so that the plane is pilot controlled from the mainland. Photography results were seen by the pilot after the drone aircraft landed. Drones are unmanned drones that are controlled remotely. Unmanned Aerial Vehicle (UAV), is a flying machine that operates with remote control by the pilot. Methode for this research are preparation assembly of drone, planning altitude flying, testing on ground, camera of calibration, air capture, result of aerial photos and analysis of result aerial photos. There are two types of drones, multicopter and fixed wing. Fixed wing  has an airplane like shape with a wing system. Fixed wing use bettery 4000 mAh . Fixed wing drone in this research used   mapping in  This drone has a load ability of 1 kg and operational time is used approximately 30 minutes for an areas 20 to 50 hectares with a height of 100 m  to 200 m and payload 1 kg  above ground level. The aerial photographs in Kotabaru produce excellent aerial photographs that can help mapping the local government in the Kotabaru region.

scholarly journals Pemanfaatan Foto Udara Format Kecil untuk Ekstraksi Digital Elevation Model dengan Metode Stereoplotting

2017 ◽  
Vol 31 (1) ◽  
pp. 73 ◽  
Author(s):  
Taufik Hery Purwanto
Keyword(s):  
Digital Elevation Model ◽  
Unmanned Aerial Vehicle ◽  
Aerial Photography ◽  
Digital Camera ◽  
Aerial Photographs ◽  
Test Results ◽  
Accuracy Test ◽  
Digital Elevation ◽  
Aerial Vehicle ◽  
Elevation Model

Perkembangan Unmanned Aerial Vehicle (UAV) sebagai wahana dan kamera digital non-metrik sebagai sensor semakin mempermudah dalam akuisisi data foto udara Foto Udara Format Kecil (FUFK). Penelitian ini bertujuan menerapkan metode stereoplotting digital untuk menghasilkan Digital Elevation Model (DEM) dari FUFK hasil pemotretan udara dengan wahana UAV sebagian bukit Jering yang merupakan lokasi pembangunan perumahan murah bersubsidi Godean Jogja Hill’s. Metode penelitian ini meliputi: proses perencanaan (perencanaan jalur terbang, pelaksanaan pemotretan udara), pengolahan data (kalibrasi kamera, koreksi foto udara, stereoplotting, interpolasi), dan uji akurasi. Hasil penelitian adalah blok FUFK dan DEM dengan metode stereoplotting. Kesimpulan dari penelitian ini adalah FUFK yang diperoleh dari UAV memiliki distorsi lensa yang cukup besar, oleh karena itu stereoplotting interaktif dapat diterapkan pada FUFK dengan hasil yang cukup baik jika FUFK yang digunakan telah terkoreksi dari distorsi, terutama distorsi lensa. Akurasi absolut DEM yang dihasilkan memiliki HRMSE sebesar 0.073 meter dengan horizontal accuracy yang mencapai 0.121 meter, sedangkan RMSEz yang dimiliki hanya mampu mencapai 0.482 meter dengan vertical accurasi yang mencapai 0.793 meter pada tingkat kepercayaan 90%. Berdasarkan DEM yang diperoleh, maka dapat digunakan untuk merepresentasikan konfigurasi permukaan bukit dan menghitung volume sebagian bukit Jering yang telah dikeruk sebesar 55.953,813 m3. The development of Unmanned Aerial Vehicle (UAV) as a vehicle and non-metric digital camera as a sensor further simplify the data acquisition of Small Format Aerial Photography (SFAP). This study aims to apply digital stereoplotting method for generating Digital Elevation Model (DEM) of SFAP results of aerial photography with UAV on the Jering hill which is cheap subsidized housing location named Godean Yogyakarta Hill’s. This research method includes: flight planning (flight paths, aerial photography acquisition), data processing (camera calibration, correction of aerial photographs, stereoplotting, interpolation), and accuracy test. Results of the research was SFAP block and DEM generated from stereoplotting method. The conclusion of this study is SFAP obtained from UAV has a lens distortion is large, and therefore can be applied to interactive stereoplotting SFAP with fairly good results if SFAP used has been corrected of distortion, especially distortion lens (idealized). The absolute accuracy of the resulting DEM have HRMSE of 0,073 meters with a horizontal accuracy which reaches 0,121 meters, while RMSEz only able to reach 0,482 meters with a vertical accuracy which reaches 0793 meters at 90% confidence level. Based on the DEM obtained, it can be used to represent the surface configuration and to calculate the volume partially Jering hill that has been dredged out for is 55.953,813 m3.  

scholarly journals UAV (Unmanned Aerial Vehicle) for Landslide Analysis Case Study in Grenggeng Village, Kebumen District, Central Java

2021 ◽  
Vol 887 (1) ◽  
pp. 012036
Author(s):  
M. A. Afif ◽  
D. A. Wibowo ◽  
P. D. Raharjo ◽  
S. Winduhutomo ◽  
E. Puswanto
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Unmanned Aerial Vehicle ◽  
Aerial Photography ◽  
Cost Effective ◽  
Ground Level ◽  
Geological Structure ◽  
Aerial Photographs ◽  
Aerial Vehicles ◽  
Aerial Vehicle ◽  
Rock Lithology

Abstract Remote sensing technology has developed rapidly; one of them is data acquisition techniques using UAV (Unmanned Aerial Vehicle). With high-resolution aerial photographs, an unmanned aerial vehicle (UAV) can be a flexible, cost-effective, and accurate monitoring of landslide technique. This research aimed to determine and test the utilization of unmanned aerial vehicles (UAVs) in congested areas. Data was collected at Grenggeng Village, Kebumen Regency, using unmanned aerial vehicles cruising altitude of 90 – 110 meters above ground level and a spatial resolution of 5 – 10 cm over a 0.200 km2 area. In November 2020, the research site will be a landslide area with similar rock lithology to the Halang Formation’s sandstone and claystone layers. Direct field observations revealed the geological structures involved and the rock lithology that produced the slip field, seepage, and the sorts of vegetation that the community had planted. According to aerial photography data, the relief appears to be a straight-line pattern in the direction of the geological structure, the slope of the layers, and different vegetation. Aerial photography using UAV can also be used to carry out rehabilitation and reconstruction techniques.

scholarly journals Pemetaan Cepat Kawasan Terdampak Bencana Longsor dan Banjir di Kabupaten Bangli, Provinsi Bali

2017 ◽  
Vol 31 (2) ◽  
pp. 44 ◽  
Author(s):  
Theresia Retno Wulan ◽  
Wiwin Ambarwulan ◽  
Anggara S. Putra ◽  
Mega D Putra ◽  
Dwi Maryanto ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Unmanned Aerial Vehicle ◽  
Aerial Photography ◽  
Field Survey ◽  
Rapid Mapping ◽  
Remote Sensing Technology ◽  
Sensing Technology ◽  
Landslide Event ◽  
Aerial Vehicle ◽  
Post Disaster

Abstrak Teknologi penginderaan jauh mengalami perkembangan yang sangat pesat. Salah satunya adalah teknologi akuisisi data dengan menggunakan UAV (Unmanned Aerial Vehicle).  Teknologi UAV dapat dipergunakan dalam berbagai bidang, salah satunya adalah bidang kebencanaan. Tujuan penelitian ini adalah untuk melakukan pemetaan secara cepat kawasan terdampak bencana banjir dan longsor di Kabupaten Bangli, Bali dengan menggunakan teknologi UAV. Metode yang digunakan adalah pemotretan udara dengan UAV, survei lapangan dan analisis laboratorium. Pemotretan udara dilakukan satu hari pasca kejadian longsor dengan ketinggian jelajah pesawat antara 100-120 meter di atas permukaan tanah. Resolusi spasial yang dihasilkan antara 4,5 - 6,5 cm. Wilayah yang berhasil dipetakan adalah wilayah yang terdampak banjir dan longsor di Desa Songan A serta Songan B, wilayah terdampak banjir bandang Yeh Mampeh di Desa Batur Selatan, serta wilayah terdampak longsor di Desa Sukawana dan Desa Awan. Berdasarkan hasil pemotretan udara, dapat diketahui luasan daerah terdampak longsor. Lebih lanjut, strategi rehabilitasi dan rekonstruksi dapat dilakukan dengan menggunakan hasil pemotretan udara.  Abstrak Remote sensing technology is experiencing rapid developments. One of which is in the field of data acquisition that has currently adopted the use of Unmanned Aerial Vehicle (UAV). UAV technology is, for instance, employed in various studies related to disasters. This research aimed to perform a rapid mapping of flood- and landslide-affected areas in Bangli Regency, Bali using UAV technology. The applied methods included UAV-assisted aerial photography, field survey, and laboratory analysis. The aerial photography was conducted one day after the landslide event and at a recording altitude of 100-120 m above the ground. The spatial resolution produced in the photography was 4.5-6.5 cm. The mapped areas were the ones affected by floods and landslides in Songa A and Songa B Villages, flash floods in Yeh Mampeh, Batur Selatan Village, and landslides in Sukawana and Awan Villages. The aerial photography also provided the extent of the landslide-affected areas. Therefore, the post-disaster rehabilitation and reconstruction strategies can be implemented using the results of the aerial photography.  

scholarly journals Recent Advances in Unmanned Aerial Vehicle Forest Remote Sensing—A Systematic Review. Part I: A General Framework

Forests ◽  
2021 ◽  
Vol 12 (3) ◽  
pp. 327 ◽  
Author(s):  
Riccardo Dainelli ◽  
Piero Toscano ◽  
Salvatore Filippo Di Gennaro ◽  
Alessandro Matese
Keyword(s):  
Remote Sensing ◽  
Unmanned Aerial Vehicle ◽  
Relevant Information ◽  
Forest Monitoring ◽  
Machine Learning Techniques ◽  
Planted Forests ◽  
Systematic Analysis ◽  
Aerial Photogrammetry ◽  
Wide Range ◽  
Aerial Vehicle

Natural, semi-natural, and planted forests are a key asset worldwide, providing a broad range of positive externalities. For sustainable forest planning and management, remote sensing (RS) platforms are rapidly going mainstream. In a framework where scientific production is growing exponentially, a systematic analysis of unmanned aerial vehicle (UAV)-based forestry research papers is of paramount importance to understand trends, overlaps and gaps. The present review is organized into two parts (Part I and Part II). Part II inspects specific technical issues regarding the application of UAV-RS in forestry, together with the pros and cons of different UAV solutions and activities where additional effort is needed, such as the technology transfer. Part I systematically analyzes and discusses general aspects of applying UAV in natural, semi-natural and artificial forestry ecosystems in the recent peer-reviewed literature (2018–mid-2020). The specific goals are threefold: (i) create a carefully selected bibliographic dataset that other researchers can draw on for their scientific works; (ii) analyze general and recent trends in RS forest monitoring (iii) reveal gaps in the general research framework where an additional activity is needed. Through double-step filtering of research items found in the Web of Science search engine, the study gathers and analyzes a comprehensive dataset (226 articles). Papers have been categorized into six main topics, and the relevant information has been subsequently extracted. The strong points emerging from this study concern the wide range of topics in the forestry sector and in particular the retrieval of tree inventory parameters often through Digital Aerial Photogrammetry (DAP), RGB sensors, and machine learning techniques. Nevertheless, challenges still exist regarding the promotion of UAV-RS in specific parts of the world, mostly in the tropical and equatorial forests. Much additional research is required for the full exploitation of hyperspectral sensors and for planning long-term monitoring.

scholarly journals Road Extraction from Unmanned Aerial Vehicle Remote Sensing Images Based on Improved Neural Networks

Sensors ◽  
2019 ◽  
Vol 19 (19) ◽  
pp. 4115 ◽  
Author(s):  
Yuxia Li ◽  
Bo Peng ◽  
Lei He ◽  
Kunlong Fan ◽  
Zhenxu Li ◽  
...  
Keyword(s):  
Neural Network ◽  
Remote Sensing ◽  
Neural Networks ◽  
Unmanned Aerial Vehicle ◽  
Computational Efficiency ◽  
Neural Nets ◽  
Road Extraction ◽  
Remote Sensing Images ◽  
Feature Maps ◽  
Aerial Vehicle

Roads are vital components of infrastructure, the extraction of which has become a topic of significant interest in the field of remote sensing. Because deep learning has been a popular method in image processing and information extraction, researchers have paid more attention to extracting road using neural networks. This article proposes the improvement of neural networks to extract roads from Unmanned Aerial Vehicle (UAV) remote sensing images. D-Linknet was first considered for its high performance; however, the huge scale of the net reduced computational efficiency. With a focus on the low computational efficiency problem of the popular D-LinkNet, this article made some improvements: (1) Replace the initial block with a stem block. (2) Rebuild the entire network based on ResNet units with a new structure, allowing for the construction of an improved neural network D-Linknetplus. (3) Add a 1 × 1 convolution layer before DBlock to reduce the input feature maps, reducing parameters and improving computational efficiency. Add another 1 × 1 convolution layer after DBlock to recover the required number of output channels. Accordingly, another improved neural network B-D-LinknetPlus was built. Comparisons were performed between the neural nets, and the verification were made with the Massachusetts Roads Dataset. The results show improved neural networks are helpful in reducing the network size and developing the precision needed for road extraction.

Sign in / Sign up

Export Citation Format

Share Document