Article
Geosciences, Multidisciplinary
Cheng Liu, Chengzhi Xing, Qihou Hu, Shanshan Wang, Shaohua Zhao, Meng Gao
Summary: This article reviews the recent advances in hyperspectral remote sensing techniques and discusses the future application prospects in air pollution monitoring. It recommends the use of a multi-means joint hyperspectral stereoscopic remote sensing monitoring mode for effective monitoring and regulation of air pollution.
EARTH-SCIENCE REVIEWS
(2022)
Article
Environmental Sciences
Mitchell S. Maguire, Christopher M. U. Neale, Wayne E. Woldt
Summary: Unmanned aerial systems have been increasingly used for remote sensing, with thermal infrared cameras being a common sensor choice. This study compared surface temperature measurements from a UAS thermal camera and field infrared thermometers, finding a RMSE of 2.24 degrees Celsius and a R-2 value of 0.85. Different models were explored for correcting the thermal imagery, with the linear model performing the best with a RMSE of 1.27 degrees Celsius and a R-2 value of 0.93. Additionally, laboratory experiments showed the need for a warm-up period to achieve measurement stability with the thermal camera.
Article
Environmental Sciences
Xiaokai Chen, Fenling Li, Botai Shi, Qingrui Chang
Summary: This study aimed to evaluate winter wheat plant nitrogen concentration (PNC) at different growth stages in the Guanzhong area using three different prediction methods based on UAV hyperspectral imagery. The machine learning regression method, especially SVMR and RFR, showed significant improvement in the estimation accuracy of PNC compared to parametric regression and linear nonparametric regression. It was concluded that estimating PNC at the flowering and filling stages from UAV hyperspectral imagery using machine learning methods, SVMR and RFR, provided the best estimation performance.
Article
Environmental Sciences
Christian J. Koppl, Radu Malureanu, Carsten Dam-Hansen, Sheng Wang, Hongxiao Jin, Stefano Barchiesi, Juan M. Serrano Sandi, Rafael Munoz-Carpena, Mark Johnson, Ana M. Duran-Quesada, Peter Bauer-Gottwein, Ursula S. McKnight, Monica Garcia
Summary: This study aims to improve hyperspectral imaging from UAS by addressing two challenges and introducing a new method to correct downwelling irradiance data for tilting effects. Experimental results demonstrate that the method significantly reduces systematic shifts caused by changes in flight direction and high-frequency tilting movements.
REMOTE SENSING OF ENVIRONMENT
(2021)
Article
Environmental Sciences
Robert Chancia, Terry Bates, Justine Vanden Heuvel, Jan van Aardt
Summary: This study aimed to identify the best spectral bands for monitoring grapevine nutrients by utilizing unmanned aerial systems and hyperspectral imaging spectrometers. Ensemble feature selection methods showed promise in identifying stable sets of wavelengths for assessing grapevine nutrient contents, with a set of biochemically consistent bands identified for predicting nitrogen content.
Article
Geography, Physical
Kathrin Maier, Andrea Nascetti, Ward van Pelt, Gunhild Rosqvist
Summary: This study proposes a novel method to determine the spatial distribution of snow depth in challenging alpine terrains using a combination of a multispectral camera and a UAV. The method enables fast, reliable, and affordable measurement of high-resolution 3D snow-covered surface models. The experiments suggest that the red components in the electromagnetic spectrum are crucial in photogrammetric processing, and applying Principal Component Analysis can reduce processing times and computational resources.
ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING
(2022)
Article
Engineering, Environmental
Xiaolan Cai, Luyao Wu, Yunmei Li, Shaohua Lei, Jie Xu, Heng Lyu, Junda Li, Huaijing Wang, Xianzhang Dong, Yuxing Zhu, Gaolun Wang
Summary: Due to rapid urbanisation, urban water quality has been degraded by increased pollutants. A remote sensing identification method for urban water pollution sources, using unmanned aerial vehicle (UAV) hyperspectral images, was established. By analyzing fluorescent components and spectral indices, four types of pollution sources (domestic sewage, terrestrial input, agricultural and algal, and industrial wastewater) were identified. Optical parameters were used to develop an identification method with a recognition accuracy exceeding 70% for the four pollution sources, expanding the application of remote sensing technologies for urban water quality management.
JOURNAL OF HAZARDOUS MATERIALS
(2023)
Article
Plant Sciences
Shanjun Luo, Xueqin Jiang, Kaili Yang, Yuanjin Li, Shenghui Fang
Summary: This study focuses on the application of unmanned aerial vehicle (UAV) multispectral remote sensing (RS) in precision agriculture. The researchers propose a new method for accurately acquiring the reflectance of multi-altitude images and compute vegetation indices to estimate rice growth parameters and yield. The results show significant differences in reflectance and vegetation indices at different altitudes, and the selection of a calibration method greatly affects the accuracy of rice phenotyping.
FRONTIERS IN PLANT SCIENCE
(2022)
Review
Remote Sensing
Lucas Prado Osco, Jose Marcato Junior, Ana Paula Marques Ramos, Lucio Andre de Castro Jorge, Sarah Narges Fatholahi, Jonathan de Andrade Silva, Edson Takashi Matsubara, Hemerson Pistori, Wesley Nunes Goncalves, Jonathan Li
Summary: This paper reviews the recent research on DNN algorithms applied in UAV-based image applications, focusing on the use of classification and regression techniques and discussing potential future directions in this field.
INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION
(2021)
Article
Environmental Sciences
Jianqiang Ren, Ningdan Zhang, Xingren Liu, Shangrong Wu, Dandan Li
Summary: The study focuses on obtaining spatial information on winter wheat D-HI using UAV hyperspectral data, with a proposed method showing high accuracy. It may serve as a technical reference for developing satellite-based indices to monitor large-scale crop HI information.
Article
Environmental Sciences
Bin Yang, Wanxue Zhu, Ehsan Eyshi Rezaei, Jing Li, Zhigang Sun, Junqiang Zhang
Summary: Unmanned aerial vehicles (UAV)-based multispectral remote sensing, combined with multi-temporal data, significantly improves the monitoring and prediction of crop yield accuracy in agro-ecosystems. Specific developmental stages of crops, such as tasseling, silking, milking, and dough stages, are critical for achieving the highest yield prediction accuracy. Additionally, certain spectral indices, such as NDRE and GNDVI, are crucial features for maize yield prediction.
Review
Environmental Sciences
Tarini Shukla, Wenwu Tang, Carl C. Trettin, Gang Chen, Shenen Chen, Craig Allan
Summary: Microtopography plays a crucial role in ecological, hydrological, and biogeochemical processes, but its quantification is a data-intensive challenge. Close-range remote sensing data and techniques have emerged as powerful tools to quantify microtopography. The main objective of this article is to provide a systematic framework for microtopographic studies using close-range remote sensing technologies.
Article
Chemistry, Analytical
Joaquim J. Sousa, Piero Toscano, Alessandro Matese, Salvatore Filippo Di Gennaro, Andrea Berton, Matteo Gatti, Stefano Poni, Luis Padua, Jonas Hruska, Raul Morais, Emanuel Peres
Summary: This study assesses the applicability and practicality of push-broom and snapshot hyperspectral sensors in the context of precision viticulture and provides reliable data collection protocols and methods. Through qualitative and quantitative analysis, the performance of the two sensors is compared. The results show excellent geometrical quality for both technologies and facilitate information exchange within the UAV hyperspectral community through multi-site assessment.
Article
Engineering, Environmental
Weiyang Chen, Yiyang Zhao, Tengfei You, Haifeng Wang, Yang Yang, Kun Yang
Summary: This study proposes a novel detection framework using small unmanned aerial vehicles (SUAVs) for low-altitude remote sensing to automatically detect scattered garbage regions. The framework includes steps such as image collection, data augmentation, and target detection, achieving a high accuracy rate on real datasets compared to existing methods.
ENVIRONMENTAL SCIENCE & TECHNOLOGY
(2021)
Article
Environmental Sciences
Xin Lyu, Xiaobing Li, Dongliang Dang, Huashun Dou, Kai Wang, Anru Lou
Summary: This paper provides a systematic and comprehensive review of the application of unmanned aerial vehicle (UAV) remote sensing in grassland ecosystem monitoring. It analyzes the application trends, introduces common UAV platforms and remote sensing sensors, reviews the application scenarios, and summarizes the current limitations and future development directions. The results are important for improving the understanding of UAV remote sensing application in grassland ecosystem monitoring and providing a scientific reference for ecological remote sensing research.
