RASPBERRY PI 3 MULTISPECTRAL LOW-COST SENSOR FOR UAV BASED REMOTE SENSING. CASE STUDY IN SOUTH-WEST NIGER

11 citations as recorded by crossref.

1. Method for fluvial and pluvial flood risk assessment in rural settlements M. Tiepolo et al. 10.1016/j.mex.2021.101463
2. Remote Sensing for Urban Biodiversity: A Review and Meta-Analysis M. Finizio et al. 10.3390/rs16234483
3. Automatic Features Detection in a Fluvial Environment through Machine Learning Techniques Based on UAVs Multispectral Data E. Pontoglio et al. 10.3390/rs13193983
4. A Customisable Data Acquisition System for Open-Source Hyperspectral Imaging Y. Mao et al. 10.3390/s23208622
5. UAV-g 2019: Unmanned Aerial Vehicles in Geomatics F. Nex 10.3390/drones3030074
6. Hydrological Model Application in the Sirba River: Early Warning System and GloFAS Improvements G. Passerotti et al. 10.3390/w12030620
7. Community and Impact Based Early Warning System for Flood Risk Preparedness: The Experience of the Sirba River in Niger V. Tarchiani et al. 10.3390/su12051802
8. Weed Detection from Unmanned Aerial Vehicle Imagery Using Deep Learning—A Comparison between High-End and Low-Cost Multispectral Sensors A. Seiche et al. 10.3390/s24051544
9. Land Cover Classification from Very High-Resolution UAS Data for Flood Risk Mapping E. Belcore et al. 10.3390/s22155622
10. Identification of pathogens in corn using near-infrared UAV imagery and deep learning A. Antolínez García & J. Cáceres Campana 10.1007/s11119-022-09951-x
11. Participatory risk assessment of pluvial floods in four towns of Niger M. Tiepolo et al. 10.1016/j.ijdrr.2022.103454