Ethnic Architectural Heritage Identification Using Low-Altitude UAV Remote Sensing and Improved Deep Learning Algorithms by Ting Luo, Xiaoqiong Sun, Weiquan Zhao, Wei Li, Linjiang Yin, Dongdong Xie

“…Taking Buyi architecture in China as an example, this paper proposes a minority architectural heritage identification method that combines low-altitude unmanned aerial vehicle (UAV) remote sensing technology and an improved deep learning algorithm. …”
Get full text

Cooperative Overbooking-Based Resource Allocation and Application Placement in UAV-Mounted Edge Computing for Internet of Forestry Things by Xiaoyu Li, Long Suo, Wanguo Jiao, Xiaoming Liu, Yunfei Liu

“…Due to the high mobility and low cost, unmanned aerial vehicle (UAV)-mounted edge computing (UMEC) provides an efficient way to provision computing offloading services for Internet of Forestry Things (IoFT) applications in forest areas without sufficient infrastructure. …”
Get full text

RGB Composition Obtained by a UAV in the Monitoring of Sugarcane Row Gaps Using the Biophysical Index by Camila G. B. de Melo, Mário M. Rolim, Roberta Q. Cavalcanti, Marcos V. da Silva, Ana Lúcia B. Candeias, Pabrício M. O. Lopes, Pedro F. S. Ortiz, Renato P. de Lima

“…The objective of this study was to establish an alternative methodology for measuring the planting and regrowth of sugarcane rows using UAV (Unmanned Aerial Vehicle) images and to compare it with manual measurements. …”
Get full text

Improvement of Citrus Yield Prediction Using UAV Multispectral Images and the CPSO Algorithm by Wenhao Xu, Xiaogang Liu, Jianhua Dong, Jiaqiao Tan, Xulei Wang, Xinle Wang, Lifeng Wu

“…To accurately and quickly predict citrus yield, this study obtained multispectral images of citrus fruit maturity through an unmanned aerial vehicle (UAV) and extracted multispectral vegetation indices (VIs) and texture features (T) from the images as feature variables. …”
Get full text

Advanced Path Planning for UAV Swarms in Smart City Disaster Scenarios Using Hybrid Metaheuristic Algorithms by Mohammed Sani Adam, Nor Fadzilah Abdullah, Asma Abu-Samah, Oluwatosin Ahmed Amodu, Rosdiadee Nordin

“…The proposed method achieved up to 100% coverage in suburban settings with only eight unmanned aerial vehicle (UAV) swarms, and maintained superior performance in dense and high-rise urban environments, achieving 97% and 93% coverage, respectively, with 10 UAV swarms. …”
Get full text

Enhancing the estimation of cadmium content in rice leaves by integrating vegetation indices and color indices using machine learning by Xiaoyun Huang, Shengxi Chen, Tianling Fu, Chengwu Fan, Hongxing Chen, Song Zhang, Hui Chen, Song Qin, Zhenran Gao

“…This study presents an accurate, reliable, and generalized method to estimate LCd, providing valuable insights for assessing the large-scale heavy metal pollution status of rice using unmanned aerial vehicle remote sensing technology.…”
Get full text

The use of kinematic photogrammetry and LiDAR for reconstruction of a unique object with extreme topography: a case study of Dutchman’s Cap, Baltic seacoast, Lithuania by Birutė Ruzgienė, Lina Kuklienė, Indrius Kuklys, Dainora Jankauskienė, Dainora Jankauskienė, Sérgio Lousada, Sérgio Lousada, Sérgio Lousada, Sérgio Lousada, Sérgio Lousada

“…Nowadays, the development of Unmanned Aerial Vehicle in conjunction with Photogrammetry and LiDAR technologies, has revolutionized the collection of geospatial data. …”
Get full text

A Method for Quantifying Mung Bean Field Planting Layouts Using UAV Images and an Improved YOLOv8-obb Model by Kun Yang, Xiaohua Sun, Ruofan Li, Zhenxue He, Xinxin Wang, Chao Wang, Bin Wang, Fushun Wang, Hongquan Liu

“…In this work, an unmanned aerial vehicle (UAV) was employed to capture visible light images of mung bean seedlings in a field across three height gradients of 2 m, 5 m, and 7 m following a time series approach. …”
Get full text

Conservation and ecological screening of small water bodies in temperate riverine wetlands using UAV Photogrammetry (Middle Danube) by Dušanka Cvijanović, Maja Novković, Djuradj Milošević, Milica Stojković Piperac, Laszlo Galambos, Dubravka Čerba, Olivera Stamenković, Bojan Damnjanović, Minučer Mesaroš, Dragoslav Pavić, Vladica Simić, Ivana Trbojević, Ana Anđelković, Nusret Drešković, Barbara Stammel, Bernd Cyffka, Snežana Radulović

“…One potential solution is the use of UAV-based (Unmanned Aerial Vehicle) ecological indicators to complement existing monitoring frameworks. …”
Get full text

Dataset of aerial photographs acquired with UAV using a multispectral (green, red and near-infrared) camera for cherry tomato (Solanum lycopersicum var. cerasiforme) monitoringDrya... by Osiris Chávez-Martínez, Sergio Alberto Monjardin-Armenta, Jesús Gabriel Rangel-Peraza, Zuriel Dathan Mora-Felix, Antonio Jesus Sanhouse-García

“…A dataset of aerial photographs acquired with an Unmanned Aerial Vehicle (UAV) DJI Phantom 4 Pro is presented for monitoring a cherry tomato (Solanum lycopersicum var. cerasiforme) crop in Navolato, Mexico. …”
Get full text

Annotated image dataset with different stages of European pear rust for UAV-based automated symptom detection in orchardsMendeley Data by Virginia Maß, Pendar Alirezazadeh, Johannes Seidl-Schulz, Matthias Leipnitz, Eric Fritzsche, Rasheed Ali Adam Ibraheem, Martin Geyer, Michael Pflanz, Stefanie Reim

“…The development of a digital and UAV (unmanned aerial vehicle)-based phenotyping method for the assessment of genotype-specific susceptibility or resistance against diseases in orchards would significantly increase the efficiency of plant breeding. …”
Get full text

UAV Remote Sensing Technology for Wheat Growth Monitoring in Precision Agriculture: Comparison of Data Quality and Growth Parameter Inversion by Jikai Liu, Weiqiang Wang, Jun Li, Ghulam Mustafa, Xiangxiang Su, Ying Nian, Qiang Ma, Fengxian Zhen, Wenhui Wang, Xinwei Li

“…The quality of the image data and the potential to invert crop growth parameters are essential for effectively using unmanned aerial vehicle (UAV)-based sensor systems in precision agriculture (PA). …”
Get full text

Improving Fugitive Dust Emission Inventory from Construction Sector Using UAV Images Recognition by Yuyao He, Jicheng Jang, Yun Zhu, Pen-Chi Chiang, Jia Xing, Shuxiao Wang, Bin Zhao, Shicheng Long, Yingzhi Yuan

“…In this study, an innovative method was developed to compile a high-resolution spatiotemporal emission inventory from construction sector, utilizing unmanned aerial vehicle (UAV) images. This methodology offered detailed activity level information by distinguishing various types of construction lands and equipment. …”
Get full text

Identification of standing dead trees in Robinia pseudoacacia plantations across China’s Loess Plateau using multiple deep learning models by Li Zhang, Xiaodong Gao, Shuyi Zhou, Zhibo Zhang, Tianjie Zhao, Yaohui Cai, Xining Zhao

“…Therefore, this study leveraged unmanned aerial vehicle (UAV) remote sensing to capture high-resolution RGB images of Robinia pseudoacacia plantations. …”
Get full text

Iterative optimization annotation pipeline and ALSS-YOLO-Seg for efficient banana plantation segmentation in UAV imagery by Ang He, Ang He, Ximei Wu, Ximei Wu, Xing Xu, Xing Xu, Jing Chen, Jing Chen, Xiaobin Guo, Xiaobin Guo, Sheng Xu, Sheng Xu

“…Precise segmentation of unmanned aerial vehicle (UAV)-captured images plays a vital role in tasks such as crop yield estimation and plant health assessment in banana plantations. …”
Get full text

Hyperspectral imaging for precision nitrogen management: A comparative exploration of two methodological approaches to estimate optimal nitrogen rate in processing tomato by Vito Aurelio Cerasola, Francesco Orsini, Giuseppina Pennisi, Gaia Moretti, Stefano Bona, Francesco Mirone, Jochem Verrelst, Katja Berger, Giorgio Gianquinto

“…Canopy reflectance was measured by using an unmanned aerial vehicle at five growth stages of processing tomatoes grown under experimental plot conditions with different N rates. …”
Get full text

Hierarchical 2-D/3-D Object-Based Classification of Photogrammetric Textured Mesh Models by Zhongwen Hu, Jinhua Zhang, Zhigang Liu, Yinghui Zhang, Jingzhe Wang, Qian Zhang, Guofeng Wu

“…The photogrammetric 3-D textured mesh model (TMM) obtained by unmanned aerial vehicle provides accurate geometric shapes and realistic textures. …”
Get full text

NDVI Estimation Throughout the Whole Growth Period of Multi-Crops Using RGB Images and Deep Learning by Jianliang Wang, Chen Chen, Jiacheng Wang, Zhaosheng Yao, Ying Wang, Yuanyuan Zhao, Yi Sun, Fei Wu, Dongwei Han, Guanshuo Yang, Xinyu Liu, Chengming Sun, Tao Liu

“…To address these limitations, this study proposes an NDVI estimation method based on low-cost RGB (red, green, and blue) UAV (unmanned aerial vehicle) imagery combined with deep learning techniques. …”
Get full text

Combining UAV Remote Sensing with Ensemble Learning to Monitor Leaf Nitrogen Content in Custard Apple (<i>Annona squamosa</i> L.) by Xiangtai Jiang, Lutao Gao, Xingang Xu, Wenbiao Wu, Guijun Yang, Yang Meng, Haikuan Feng, Yafeng Li, Hanyu Xue, Tianen Chen

“…This study uses an ensemble learning technique based on multiple machine learning algorithms to effectively and precisely monitor the leaf nitrogen content in the tree canopy using multispectral canopy footage of custard apple trees taken via Unmanned Aerial Vehicle (UAV) across different growth phases. …”
Get full text

Remote sensing-based maize growth process parameters revel the maize yield: a comparison of field- and regional-scale by Minghan Cheng, Xiuliang Jin, Chenwei Nie, Kaihua Liu, Tianao Wu, Yuping Lv, Shuaibing Liu, Xun Yu, Yi Bai, Yadong Liu, Lin Meng, Xiao Jia, Yuan Liu, Lili Zhou, Fei Nan

“…Furthermore, past algorithms have not considered their applicability across different observational scales (e.g., unmanned aerial vehicle (UAV)- and satellite-observed). Considering this, we extracted four maize growth process parameters using Leaf Area Index (LAI) obtained from UAV (equipped with multispectral sensor, centimeter-level) and satellite (MODIS, 1 km) observations: PP_a (representing the duration of the crop growth period), PP_b (representing the peak growth stage of the crop), PP_c (representing the initial state of the crop), and LAImax (maximum LAI). …”
Get full text