Zobrazeno 1 - 10
of 782
pro vyhledávání: '"UAV remote sensing"'
Autor:
Wentao Liu, Ziran Xie, Jun Du, Yuanhang Li, Yongbing Long, Yubin Lan, Tianyi Liu, Si Sun, Jing Zhao
Publikováno v:
Frontiers in Plant Science, Vol 15 (2024)
Pine wilt disease (PWD) is a highly destructive infectious disease that affects pine forests. Therefore, an accurate and effective method to monitor PWD infection is crucial. However, the majority of existing technologies can detect PWD only in the l
Externí odkaz:
https://doaj.org/article/ebc9899912a544b8b094ca2d00727c38
Publikováno v:
Ecological Indicators, Vol 167, Iss , Pp 112645- (2024)
Urban green space (UGS) monitoring is significant in optimizing urban planning, protecting the ecological environment, and improving residents’ quality of life. However, in urban environments, shadow interference and the emergence of new constructi
Externí odkaz:
https://doaj.org/article/dd32c294cd22459f8089f85db1dd7f68
Publikováno v:
Ecological Indicators, Vol 166, Iss , Pp 112516- (2024)
Sparse vegetation is a key factor in maintaining the health and sustainability of oasis ecosystems under extreme drought conditions. Combining the advantages of both satellites and drones, using image processing and machine learning technology, it ca
Externí odkaz:
https://doaj.org/article/2cc0c3587ca644a49c91e2a59a89b84e
Publikováno v:
Jisuanji kexue yu tansuo, Vol 18, Iss 5, Pp 1301-1317 (2024)
To solve the large proportion of small targets and complex background in UAV (unmanned aerial vehicle) aerial image, the current object detection model has the problems of low accuracy and missed detection of small targets. Based on the YOLOv8s model
Externí odkaz:
https://doaj.org/article/b62fb837d0d14d3ab3811dcba1036f88
Publikováno v:
International Journal of Applied Earth Observations and Geoinformation, Vol 132, Iss , Pp 104052- (2024)
Accurate and non-destructive estimation of leaf chlorophyll content (LCC) is crucial for optimizing cotton production. This study enhances the SCOPE model by integrating unmanned aerial vehicle (UAV)-derived multispectral data with leaf area index (L
Externí odkaz:
https://doaj.org/article/f19eeaa9b2df4ff193aaacc1cebfe9da
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 17, Pp 16744-16754 (2024)
In recent years, UAV object tracking has provided technical support across various fields. Most existing work relies on convolutional neural networks (CNNs) or visual transformers. However, CNNs have limited receptive fields, resulting in suboptimal
Externí odkaz:
https://doaj.org/article/e48b5f825e3148b79175f327d4c9a43e
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 17, Pp 16041-16050 (2024)
Wide-range multiscale object detection for multispectral scene perception from a drone perspective is challenging. Previous RGB-T perception methods directly use backbone pretrained on RGB for thermal infrared feature extraction, leading to unexpecte
Externí odkaz:
https://doaj.org/article/bf1b8e5e33d948039c20deb46e22562f
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 17, Pp 829-841 (2024)
Currently, numerous studies have reported that the invasion of Cassytha filiformis has affected both above and below ground communities, resulting in difficulties in the growth of original vegetation. Meanwhile, Cassytha filiformis was observed on th
Externí odkaz:
https://doaj.org/article/bfde66a6808643e98f1fb6836892b2df
Autor:
Zixuan Qiu, Hao Liu, Lu Wang, Shuaibo Shao, Can Chen, Zijia Liu, Song Liang, Cai Wang, Bing Cao
Publikováno v:
Drones, Vol 8, Iss 11, p 665 (2024)
Most rice growth stage predictions are currently based on a few rice varieties for prediction method studies, primarily using linear regression, machine learning, and other methods to build growth stage prediction models that tend to have poor genera
Externí odkaz:
https://doaj.org/article/ea99f99cd63c4d54acc377e3fbc0ac65
Publikováno v:
ISPRS International Journal of Geo-Information, Vol 13, Iss 11, p 402 (2024)
The visual evaluation and characteristic analysis of urban rivers are pivotal for advancing our understanding of urban waterscapes and their surrounding environments. Unmanned aerial vehicles (UAVs) offer significant advantages over traditional satel
Externí odkaz:
https://doaj.org/article/5751881d662c44e8a2f60e600e15bae5