A LIGHT-WEIGHT HYPERSPECTRAL MAPPING SYSTEM FOR UNMANNED AERIAL VEHICLES - THE FIRST RESULTS

被引：0

作者：

Suomalainen, Juha ^{[1
]}

Anders, Niels ^{[2
]}

Iqbar, Shahzad ^{[3
]}

Franke, Jappe ^{[4
]}

Wenting, Philip ^{[1
]}

Bartholomeus, Harm ^{[1
]}

Becker, Rolf ^{[3
]}

Kooistra, Lammert ^{[1
]}

机构：

[1] Wageningen Univ, Lab Geoinformat Sci & Remote Sensing, Wageningen, Netherlands

[2] Wageningen Univ, Soil Phys & Land Management Grp, Wageningen, Netherlands

[3] Hsch Rhein Waal, Kleve, Germany

[4] Alterra, Wageningen, Netherlands

来源：

2013 5TH WORKSHOP ON HYPERSPECTRAL IMAGE AND SIGNAL PROCESSING: EVOLUTION IN REMOTE SENSING (WHISPERS) | 2013年

关键词：

UAV; Hyperspectral; DSM; Orthoimage;

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

Research opportunities using UAV remote sensing techniques are limited by the payload of the platform. Therefore small UAV's are typically not suitable for hyperspectral imaging due to the weight of the mapping system. In this research, we are developing a light-weight hyperspectral mapping system (< 2 kg) suitable to be mounted on small UAVs. The system is able to produce georeferenced and georectified hyperspectral data cubes in 400-1000nm spectral range at 10-50cm resolution. The georeferenced reflectance factor spectra cubes are to be used in e.g. precision agriculture and soil erosion research. In this paper we describe prototype of the system, the processing chain, and present preliminary results

引用

页数：4

共 50 条

[31] A light-weight multi-spectral aerial imaging system for nitrogen crop monitoring
Lebourgeois, V.
Begue, A.
Labbe, S.
Houles, M.
Martine, J. F.
PRECISION AGRICULTURE, 2012, 13 (05) : 525 - 541
[32] An Embedded System for Aerial Image Processing from Unmanned Aerial Vehicles
da Silva, Jonas Fernandes
Brito, Alisson V.
Gomes de Lima, Jose Antonio
de Moura, Helder Nogueira
2015 BRAZILIAN SYMPOSIUM ON COMPUTING SYSTEMS ENGINEERING (SBESC), 2015, : 154 - 157
[33] Hyperspectral sensor for civil applications to Unmanned Aerial Vehicles within a monitoring scenario
Fusaro, R.
Casti, M.
Aleina, S. Cresto
Viola, N.
Catella, P.
Butera, F.
Chiarantini, L.
2015 IEEE 1ST INTERNATIONAL FORUM ON RESEARCH AND TECHNOLOGIES FOR SOCIETY AND INDUSTRY (RTSI 2015) PROCEEDINGS, 2015,
[34] Electric-field Coupled Wireless Power Transfer System With Misalignment-tolerance and Light-weight Characteristics for Unmanned Aerial Vehicle Applications
Wu S.
Chen X.
Meng X.
Cai C.
Chai W.
Yang S.
Zhongguo Dianji Gongcheng Xuebao/Proceedings of the Chinese Society of Electrical Engineering, 2023, 43 (06): : 2404 - 2412
[35] Attention Residual Hybrid Network for Unmanned Aerial Vehicles Hyperspectral Image Classification
Zhang, Zhen
Jiang, Linhuan
Tang, Bo-Hui
Liu, Jianchen
Wang, Qingwang
Hu, Yabin
Huang, Liang
Fu, Zhitao
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2025, 18 : 7662 - 7681
[36] Assessing Grapevine Biophysical Parameters From Unmanned Aerial Vehicles Hyperspectral Imagery
Matese, Alessandro
Di Gennaro, Salvatore Filippo
Orlandi, Giorgia
Gatti, Matteo
Poni, Stefano
FRONTIERS IN PLANT SCIENCE, 2022, 13
[37] Power Efficient Visible Light Communication With Unmanned Aerial Vehicles
Yang, Yang
Chen, Mingzhe
Guo, Caili
Feng, Chunyan
Saad, Walid
IEEE COMMUNICATIONS LETTERS, 2019, 23 (07) : 1272 - 1275
[38] Data Fusion and Unmanned Aerial Vehicles (UAVs) for First Responders
Corrado, Casey
Panetta, Karen
2017 IEEE INTERNATIONAL SYMPOSIUM ON TECHNOLOGIES FOR HOMELAND SECURITY (HST), 2017,
[39] First Results of a Tandem Terrestrial-Unmanned Aerial mapKITE System with Kinematic Ground Control Points for Corridor Mapping
Molina, Pere
Blazquez, Marta
Cucci, Davide A.
Colomina, Ismael
REMOTE SENSING, 2017, 9 (01):
[40] A Lightweight Prototype of a Magnetometric System for Unmanned Aerial Vehicles
Pisciotta, Antonino
Vitale, Giovanni
Scudero, Salvatore
Martorana, Raffaele
Capizzi, Patrizia
D'Alessandro, Antonino
SENSORS, 2021, 21 (14)

← 1 2 3 4 5 →