An investigation of the spectral and radiometric characteristics of low-cost digital cameras for use in UAV remote sensing

2018 ◽  
Vol 39 (15-16) ◽  
pp. 4891-4909 ◽  
Author(s):  
Gordon S.J. Logie ◽  
Craig A. Coburn
2015 ◽  
Vol 77 (20) ◽  
Author(s):  
Nasruddin Abu Sari ◽  
A Ahmad ◽  
MY Abu Sari ◽  
S Sahib ◽  
AW Rasib

The need to produce high temporal remote sensing imagery for supporting precision agriculture in oil palm deserves a new low-altitude remote sensing (LARS) technique. Consumer over the shelf unmanned aerial vehicles (UAV) and digital cameras have the potential to serve as Personal Remote Sensing Toolkits which are low-cost, efficient, rapid and safe. The objectives of this study were to develop and test a new technique to rapidly capturing nadir images of large area oil palm plantation (1 km2 ~ 4 km2). Using 5 different multi-rotor UAV models several imagery missions were carried out. Multi-rotors were chosen as a platform due to its vertical take-off and landing (VTOL) feature. Multi-rotor’s VTOL was crucial for imagery mission success. Post processing results showed that for an area of 1 km2, it needs 2 to 6 sorties of quad-rotor UAV with 4000x3000 pixel digital cameras flying at altitude of 120m above ground level and an average of 50m cross-path distance. The results provide a suitability assessment of low-cost digital aerial imagery acquisition system. The study has successfully developed a decent workhorse quad-rotor UAV for Rapid Aerial Photogrammetry Imagery and Delivery (RAPID) in oil palm terrain. Finally we proposed the workhorse UAV as Low-Altitude Personal Remote Sensing (LAPERS) basic founding element.


2011 ◽  
Vol 79 (12) ◽  
pp. 1240-1245 ◽  
Author(s):  
Joel F. Campbell ◽  
Michael A. Flood ◽  
Narasimha S. Prasad ◽  
Wade D. Hodson

2017 ◽  
Vol 11 (1) ◽  
pp. 016006 ◽  
Author(s):  
David D. W. Ren ◽  
Siddhant Tripathi ◽  
Larry K. B. Li

Sensors ◽  
2016 ◽  
Vol 16 (10) ◽  
pp. 1750 ◽  
Author(s):  
Daniele Giordan ◽  
Paolo Allasia ◽  
Niccolò Dematteis ◽  
Federico Dell’Anese ◽  
Marco Vagliasindi ◽  
...  

Author(s):  
Charles Marseille ◽  
Martin Aubé ◽  
Africa Barreto Velasco ◽  
Alexandre Simoneau

The aerosol optical depth is an important indicator of aerosol particle properties and associated radiative impacts. AOD determination is therefore very important to achieve relevant climate modeling. Most remote sensing techniques to retrieve aerosol optical depth are applicable to daytime given the high level of light available. The night represents half of the time but in such conditions only a few remote sensing techniques are available. Among these techniques, the most reliable are moon photometers and star photometers. In this paper, we attempt to fill gaps in the aerosol detection performed with the aforementioned techniques using night sky brightness measurements during moonless nights with the novel CoSQM: a portable, low cost and open-source multispectral photometer. In this paper, we present an innovative method for estimating the aerosol optical depth by using an empirical relationship between the zenith night sky brightness measured at night with the CoSQM and the aerosol optical depth retrieved at daytime from the AErosol Robotic NETwork. Such a method is especially suited to light-polluted regions with light pollution sources located within a few kilometers of the observation site. A coherent day-to-night aerosol optical depth and Ångström Exponent evolution in a set of 354 days and nights from August 2019 to February 2021 was verified at the location of Santa Cruz de Tenerife on the island of Tenerife, Spain. The preliminary uncertainty of this technique was evaluated using the variance under stable day-to-night conditions, set at 0.02 for aerosol optical depth and 0.75 for Ångström Exponent. These results indicate the set of CoSQM and the proposed methodology appear to be a promising tool to add new information on the aerosol optical properties at night, which could be of key importance to improve climate predictions.


2014 ◽  
Vol 18 (2) ◽  
pp. 35-45 ◽  
Author(s):  
Michał T. Chiliński ◽  
Marek Ostrowski

Abstract Remote sensing from unmanned aerial systems (UAS) has been gaining popularity in the last few years. In the field of vegetation mapping, digital cameras converted to calculate vegetation index (DCVI) are one of the most popular sensors. This paper presents simulations using a radiative transfer model (libRadtran) of DCVI and NDVI results in an environment of possible UAS flight scenarios. The analysis of the results is focused on the comparison of atmosphere influence on both indices. The results revealed uncertainties in uncorrected DCVI measurements up to 25% at the altitude of 5 km, 5% at 1 km and around 1% at 0.15 km, which suggests that DCVI can be widely used on small UAS operating below 0.2 km.


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