scholarly journals A Simple, Inexpensive Method for Using Unmanned Aerial Vehicle Photograph Analysis to Quantify Green Color and Enhance Ratings in Field Research Plots

2019 ◽  
Vol 20 (2) ◽  
pp. 128-130
Author(s):  
Trey Price ◽  
Sebe Brown ◽  
Randy Price
Keyword(s):  
Unmanned Aerial Vehicle ◽  
Field Research ◽  
Aerial Photographs ◽  
Inexpensive Method ◽  
Efficacy Trials ◽  
Recent Developments ◽  
Aerial Vehicle ◽  
Small Plot ◽  
Vehicle Technology ◽  
Lower Variability

Agricultural small-plot research is necessary to determine pesticide efficacy and develop integrated pest management programs for stakeholders. Many efficacy trials are rated visually using scales of foliage affected by a given pest. Human estimations introduce variability, and researchers continue explore methods of reducing variability in research trials. Recent developments in unmanned aerial vehicle technology allow novices to outfit inexpensive drones with inexpensive modified cameras to obtain aerial photographs that can be analyzed with any number of free image manipulation programs. Measuring reflected color from photographs provides data with lower variability that can be correlated with foliar disease ratings.

scholarly journals THE INFLUENCE OF DRONES ON THE DEVELOPMENT OF ARCHITECHTURAL PHOTOGRAPHY CULTURAL WORKS

Jurnal KATA ◽  
2020 ◽  
Vol 4 (1) ◽  
pp. 1
Author(s):  
Yandri Yandri ◽  
Maulid Hariri Gani ◽  
Putri Khairina Masta ◽  
Eldiapma Syahdiza ◽  
Fadlul Rahman
Keyword(s):  
Unmanned Aerial Vehicle ◽  
Qualitative Method ◽  
Field Research ◽  
Point Of View ◽  
Aesthetic Value ◽  
Library Research ◽  
Aerial Vehicle ◽  
Vehicle Technology ◽  
The Aesthetic ◽  
High Flexibility

<em>Culture of architectural photography is a branch of photography that exposes the aesthetic value of an architectural object of a building<strong>.</strong> The presence of drone technology in the culture of photography recently brings changes to the results of the photography itself and one of them is in the area of architectural photography.  This study aims at verifying the influence of Unmanned Aerial Vehicle technology (Drone) on the artwork of architectural photography. The method used in this research was qualitative method with descriptive technique. Data were collected through library research and field research with observation and interview techniques. The culture using drones offer significant results in architectural photography artworks. The high flexibility of the drone gives results on a very detail architectural artwork. Using a drone also provides a very dazzling point of view that cannot be obtained by using only a DSLR camera. Furthermore by using drone, the artworks of photography are no longer limited by areas that cannot be reached. Therefore by using a drone, the photographer can make architectural photography works with unlimited perspective dimensions. There are some weaknesses of using this drone that the camera and lens are not adjustable and they also cannot be changed.</em>

scholarly journals Application of Deep-Learning Methods to Bird Detection Using Unmanned Aerial Vehicle Imagery

Sensors ◽  
2019 ◽  
Vol 19 (7) ◽  
pp. 1651 ◽  
Author(s):  
Suk-Ju Hong ◽  
Yunhyeok Han ◽  
Sang-Yeon Kim ◽  
Ah-Yeong Lee ◽  
Ghiseok Kim
Keyword(s):  
Deep Learning ◽  
Unmanned Aerial Vehicle ◽  
Migratory Bird ◽  
Aerial Images ◽  
Aerial Photographs ◽  
Detection Methods ◽  
Single Shot ◽  
Convolutional Network ◽  
Aerial Vehicle ◽  
Bird Detection

Wild birds are monitored with the important objectives of identifying their habitats and estimating the size of their populations. Especially in the case of migratory bird, they are significantly recorded during specific periods of time to forecast any possible spread of animal disease such as avian influenza. This study led to the construction of deep-learning-based object-detection models with the aid of aerial photographs collected by an unmanned aerial vehicle (UAV). The dataset containing the aerial photographs includes diverse images of birds in various bird habitats and in the vicinity of lakes and on farmland. In addition, aerial images of bird decoys are captured to achieve various bird patterns and more accurate bird information. Bird detection models such as Faster Region-based Convolutional Neural Network (R-CNN), Region-based Fully Convolutional Network (R-FCN), Single Shot MultiBox Detector (SSD), Retinanet, and You Only Look Once (YOLO) were created and the performance of all models was estimated by comparing their computing speed and average precision. The test results show Faster R-CNN to be the most accurate and YOLO to be the fastest among the models. The combined results demonstrate that the use of deep-learning-based detection methods in combination with UAV aerial imagery is fairly suitable for bird detection in various environments.

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 INDEKS VEGETASI UNTUK ESTIMASI KANDUNGAN KALIUM PADA TANAMAN NANAS (Ananas comosus) MENGGUNAKAN UAV (Unmanned Aerial Vehicle) DI PT. GREAT GIANT PINEAPPLE, LAMPUNG

2020 ◽  
Vol 8 (1) ◽  
pp. 91-99
Author(s):  
Dita Khairunnisa ◽  
Mochtar Lutfi Rayes ◽  
Christanti Agustina
Keyword(s):  
Unmanned Aerial Vehicle ◽  
Vegetation Index ◽  
Nutrient Status ◽  
Nutrient Content ◽  
Aerial Photographs ◽  
Ananas Comosus ◽  
P Value ◽  
Distribution Maps ◽  
Significant Difference ◽  
Aerial Vehicle

PT Great Giant Pineapple (PT. GGP) is the largest pineapple production company in Indonesia. One of the nutrients that pineapple plants really need is potassium (K). K plays a key role in carbohydrate metabolism and transport of photosynthates from source to sink. Remote sensing technology has been developed to estimate nutrient status, one of which is using an Unmanned Aerial Vehicle (UAV). This study aims to estimate the K nutrient content in pineapple plants using vegetation indexes in the form of NDVI (Normalyzed Difference Vegetation Index), SAVI (Soil Adjusted Vegetation Index), and OSAVI (Optimized of Soil Adjusted Vegetation Index). The research was carried out by taking aerial photographs and samples of pineapple plants in the 5 months phase before forcing up to 2 months after forcing (F-5 to F + 2), laboratory analysis, statistical analysis, and making distribution maps. The results showed that the relationship between the vegetation index value and K plant was the strongest and most significant is in 1 month before forcing phase (F-1) with the same r value for the three indices vegetation (r=0.867). The results of the regression analysis between the NDVI, SAVI and OSAVI values with K plant were 75.17%, 75.18% and 75.17%, respectively. The calculation of the K estimate using three methods yields no different values. The validation results using paired t test (t count -0.63; t table 2.31; p-value 0.544) where the K content in the measured plants and the estimation results showed no significant difference with the measurement results.

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

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