Results 191 to 200 of about 8,269 (233)

Predicting wheat yield and grain quality with UAV multispectral imagery and deep learning. [PDF]

Front Plant Sci
Billah MM, Maimaitijiang M, Kaushal S, Millett B, Khan SN, Halder J, Kleinjan J, Sehgal SK.   +7 more
europepmc   +1 more source

RFE-YOLO: A Lightweight Receptive Field-Enhanced Network for UAV Imagery Object Detection. [PDF]

Sensors (Basel)
Peng Y, Ge X.
europepmc   +1 more source

Integrating Multi-Source and Multi-Temporal UAV Observations to Improve Wheat Yield Prediction Using Machine Learning. [PDF]

Plants (Basel)
Chen C, Liu J, Deng Y, Guo R, Yao W, Yang T, Zhang W, Liu T, Jin X, Xiong W, Li D.   +10 more
europepmc   +1 more source

Scale-Constrained Synthetic Construction for Small-Sample Satellite Power Tower Damage Assessment Under Cross-Scale Mismatch. [PDF]

Sensors (Basel)
Liu Y, Wen Q, Zhao J, Ma R, Rahman AU, Tian X.   +5 more
europepmc   +1 more source

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Remote Sensing to Uav-Based Digital Farmland

IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium, 2018
This study presents preliminary observations of the first year of a crop monitoring experiment occurred in two soybean agriculture fields in the Arkansas delta. The project focuses on developing image processing and data integration techniques for UAV-based images to optimize advanced farm management such as soil microbial amendments. In particular, we
Nicola Falco, Haruko M. Wainwright, Craig Ulrich, Baptiste Dafflon, Susan S. Hubbard, Malcolm Williamson, Jackson David Cothren, Richard G. Ham, Jay A. McEntire, McClain McEntire   +9 more
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Co-Observation and Analysis of UAV and Multispectral Remote Sensing

IGARSS 2020 - 2020 IEEE International Geoscience and Remote Sensing Symposium, 2020
In many remote sensing methods, the use of spectral information to obtain large-area soil salinization information has been a key focus of research. Typical samples of saline soil in Da'an city west of Jilin were selected as the research area, and co-observation was conducted using unmanned aerial vehicle (UAV) multispectral images and Sentinel-2 data.
Yishan Sun, Lei Li, Xiaojie Li
openaire   +1 more source

UAV Remote Sensing Image Stitching

2019
The majority of image stitching (include UAV remote sensing images stitching) models are homography matrix transformation function, which could effectively simulate the rigid transformation of 2D images in 3D coordinate system. In order to prevent the accumulation of alignment errors (drift) and the projection distortion in the multi-image stitching ...
Hui Wu, Jun Chen
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UAV-based remote sensing for NaTech accidents management

Earth Observing Systems XXIII, 2018
Recent major natural disasters highlighted the emergence of a new type of risk that manifests itself when the natural and technological worlds collide. The impact of a natural disaster on a facility storing or processing dangerous substances can result in the release of hazardous materials with possibly severe off-site consequences through toxic ...
Alessandra Marino, Mariano Ciucci, Linda Barbieri Vita, Chiara Piccirilli   +3 more
openaire   +1 more source

MINI-UAV borne hyperspectral remote sensing: A review

2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), 2017
In recent years, the science of hyperspectral remote sensing has huge development in virtue of the integration of low-cost lightweight hyperspectral sensors and unmanned aerial vehicles (UAVs). As an alternative of manned aircraft, UAV has some unique advantages enabling the researchers acquire the hyperspectral images of their interest area flexibly ...
Yanfei Zhong, Xinyu Wang 0003, Yao Xu, Tianyi Jia, Song Cui, Lifei Wei, Ailong Ma, Liangpei Zhang 0001   +7 more
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UAV Remote Sensing Assessment of Crop Growth

Photogrammetric Engineering & Remote Sensing, 2021
The introduction of unmanned-aerial-vehicle remote sensing for collecting high-spatial- and temporal-resolution imagery to derive crop-growth indicators and analyze and present timely results could potentially improve the management of agricultural businesses and enable farmers to apply appropriate solution, leading to a better food-security framework.
Freda Elikem Dorbu, Leila Hashemi-Beni, Ali Karimoddini, Abolghasem Shahbazi   +3 more
openaire   +1 more source