scholarly journals Aerial Imagery Based on Commercial Flights as Remote Sensing Platform

Sensors ◽  
2020 ◽  
Vol 20 (6) ◽  
pp. 1658 ◽  
Author(s):  
Toni Mastelic ◽  
Josip Lorincz ◽  
Ivan Ivandic ◽  
Matea Boban
Keyword(s):  
Remote Sensing ◽  
Spatial Resolution ◽  
Aerial Photography ◽  
Storage Capacity ◽  
Image Data ◽  
Aerial Imagery ◽  
Unmanned Aerial Systems ◽  
Sensing Platform ◽  
Temporal And Spatial ◽  
Aerial Systems

Remote sensing is commonly performed via airborne platforms such as satellites, specialized aircraft, and unmanned aerial systems (UASs), which perform airborne photography using mounted cameras. However, they are limited by their coverage (UASs), irregular flyover frequency (aircraft), and/or low spatial resolution (satellites) due to their high altitude. In this paper, we examine the utilization of commercial flights as an airborne platform for remote sensing. Namely, we simulate a situation where all aircraft on commercial flights are equipped with a mounted camera used for airborne photography. The simulation is used to estimate coverage, the temporal and spatial resolution of aerial imagery acquired this way, as well as the storage capacity required for storing all imagery data. The results show that Europe is 83.28 percent covered with an average of one aerial photography every half an hour and a ground sampling distance of 0.96 meters per pixel. Capturing such imagery results in 20 million images or four petabytes of image data per day. More detailed results are given in the paper for separate countries/territories in Europe, individual commercial airlines and alliances, as well as three different cameras.

scholarly journals Identifying Species and Monitoring Understorey from UAS-Derived Data: A Literature Review and Future Directions

Drones ◽  
2019 ◽  
Vol 3 (1) ◽  
pp. 9 ◽  
Author(s):  
Lorna Hernandez-Santin ◽  
Mitchel L. Rudge ◽  
Renee E. Bartolo ◽  
Peter D. Erskine
Keyword(s):  
Remote Sensing ◽  
Spatial Resolution ◽  
Temporal Frequency ◽  
Species Discrimination ◽  
Unmanned Aerial Systems ◽  
Understorey Vegetation ◽  
Species Specific ◽  
Understorey Plants ◽  
Aerial Systems ◽  
Derived Data

Understorey vegetation plays an important role in many ecosystems, yet identifying and monitoring understorey vegetation through remote sensing has proved a challenge for researchers and land managers because understorey plants tend to be small, spatially and spectrally similar, and are often blocked by the overstorey. The emergence of Unmanned Aerial Systems (UAS) is revolutionising how vegetation is measured, and may allow us to measure understorey species where traditional remote sensing previously could not. The goal of this paper was to review current literature and assess the current capability of UAS to identify and monitor understorey vegetation. From the literature, we focused on the technical attributes that limit the ability to monitor understorey vegetation—specifically (1) spatial resolution, (2) spectral sensitivity, (3) spatial extent, and (4) temporal frequency at which a sensor acquires data. We found that UAS have provided improved levels of spatial resolution, with authors reporting successful classifications of understorey vegetation at resolutions of between 3 mm and 200 mm. Species discrimination can be achieved by targeting flights to correspond with phenological events to allow the detection of species-specific differences. We provide recommendations as to how UAS attributes can be tailored to help identify and monitor understorey species.

scholarly journals Error simulations of uncorrected NDVI and DCVI during remote sensing measurements from UAS

2014 ◽  
Vol 18 (2) ◽  
pp. 35-45 ◽  
Author(s):  
Michał T. Chiliński ◽  
Marek Ostrowski
Keyword(s):  
Remote Sensing ◽  
Radiative Transfer ◽  
Vegetation Index ◽  
Vegetation Mapping ◽  
Radiative Transfer Model ◽  
Unmanned Aerial Systems ◽  
Transfer Model ◽  
Digital Cameras ◽  
Aerial Systems

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.

scholarly journals A commentary review on the use of normalized difference vegetation index (NDVI) in the era of popular remote sensing

2020 ◽  
Vol 32 (1) ◽  
pp. 1-6 ◽  
Author(s):  
Sha Huang ◽  
Lina Tang ◽  
Joseph P. Hupy ◽  
Yang Wang ◽  
Guofan Shao
Keyword(s):  
Remote Sensing ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Unmanned Aerial Systems ◽  
Atmospheric Effect ◽  
Saturation Phenomenon ◽  
Near Ir ◽  
Critical Problems ◽  
Low Costs ◽  
Aerial Systems

AbstractThe Normalized Difference Vegetation Index (NDVI), one of the earliest remote sensing analytical products used to simplify the complexities of multi-spectral imagery, is now the most popular index used for vegetation assessment. This popularity and widespread use relate to how an NDVI can be calculated with any multispectral sensor with a visible and a near-IR band. Increasingly low costs and weights of multispectral sensors mean they can be mounted on satellite, aerial, and increasingly—Unmanned Aerial Systems (UAS). While studies have found that the NDVI is effective for expressing vegetation status and quantified vegetation attributes, its widespread use and popularity, especially in UAS applications, carry inherent risks of misuse with end users who received little to no remote sensing education. This article summarizes the progress of NDVI acquisition, highlights the areas of NDVI application, and addresses the critical problems and considerations in using NDVI. Detailed discussion mainly covers three aspects: atmospheric effect, saturation phenomenon, and sensor factors. The use of NDVI can be highly effective as long as its limitations and capabilities are understood. This consideration is particularly important to the UAS user community.

scholarly journals Long‐duration fully autonomous operation of rotorcraft unmanned aerial systems for remote‐sensing data acquisition

2019 ◽  
Vol 37 (1) ◽  
pp. 137-157 ◽  
Author(s):  
Danylo Malyuta ◽  
Christian Brommer ◽  
Daniel Hentzen ◽  
Thomas Stastny ◽  
Roland Siegwart ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Data Acquisition ◽  
Remote Sensing Data ◽  
Unmanned Aerial Systems ◽  
Sensing Data ◽  
Autonomous Operation ◽  
Long Duration ◽  
Aerial Systems

Making the invisible visible: using UAS-based high-resolution color-infrared imagery to identify buried medieval monastery walls

2015 ◽  
Vol 3 (2) ◽  
pp. 58-67 ◽  
Author(s):  
Jan Rudolf Karl Lehmann ◽  
Keturah Zoe Smithson ◽  
Torsten Prinz
Keyword(s):  
Remote Sensing ◽  
Water Stress ◽  
High Resolution ◽  
Vegetation Index ◽  
Archaeological Site ◽  
Unmanned Aerial Systems ◽  
Surrounding Water ◽  
Normalised Difference Vegetation Index ◽  
Remote Sensing Techniques ◽  
Aerial Systems

Remote sensing techniques have become an increasingly important tool for surveying archaeological sites. However, budgeting issues in archaeological research often limit the application of satellite or airborne imagery. Unmanned aerial systems (UAS) provide a flexible, quick, and more economical alternative to commonly used remote sensing techniques. In this study, the buried features of the archaeological site of the Kleinburlo monastery, near Münster, Germany, were identified using high-resolution color–infrared (CIR) images collected from a UAS platform. Based on these CIR images, a modified normalised difference vegetation index (NDVIblue) was calculated, showing reflectance spectra of vegetation anomalies caused by water stress. In the presented study, the vegetation growing on top of the buried walls was better nourished than the surrounding plants because very wet conditions over the days previous to data collection caused higher levels of water stress in the surrounding water-drenched land. This difference in water stress was a good indicator for detecting archaeological remains.

scholarly journals Generating high-temporal and spatial resolution TIR image data

2019 ◽  
Vol 78 ◽  
pp. 149-162
Author(s):  
M. Herrero-Huerta ◽  
S. Lagüela ◽  
S.M. Alfieri ◽  
M. Menenti
Keyword(s):  
Spatial Resolution ◽  
Image Data ◽  
Temporal And Spatial

Field Application of UAS-Based Bridge Inspection

2018 ◽  
Vol 2672 (12) ◽  
pp. 72-81 ◽  
Author(s):  
Junwon Seo ◽  
Luis Duque ◽  
James P. Wacker
Keyword(s):  
South Dakota ◽  
Structural Damage ◽  
Image Data ◽  
Field Application ◽  
Unmanned Aerial Systems ◽  
Department Of Transportation ◽  
Bridge Inspection ◽  
Bridge Damage ◽  
Efficient Alternative ◽  
Aerial Systems

The use of Unmanned Aerial Systems (UASs), commonly known as drones, has significantly increased over recent years in the field of civil engineering. In detail, the need for a more efficient alternative for bridge inspection has risen because of the increased interest from bridge owners. The primary goal of this paper is to evaluate the efficiency of a drone as a supplemental bridge inspection tool. To complete this study, a glued laminated (glulam) girder with a composite concrete deck bridge was chosen in South Dakota, and a Dà-Jiāng Innovations (DJI) Phantom 4 drone, was employed to perform the bridge inspection. Based on the literature review, an inspection procedure with a drone was developed to efficiently identify damage on the bridge. A drone-enabled inspection was performed following the procedure, and resulting images were checked with those available in the past inspection report from South Dakota Department of Transportation (DOT). This study includes UAS-based bridge inspection considerations to capture appropriate image data necessary for bridge damage determination. A key finding demonstrated throughout this project is that different types of structural damage on the bridge were identified using the UAS.

Use of Optical Remote Sensing for Detecting Herbicide Injury in Soybean

2004 ◽  
Vol 18 (2) ◽  
pp. 292-297 ◽  
Author(s):  
Kurt D. Thelen ◽  
A. N. Kravchenko ◽  
Chad D. Lee
Keyword(s):  
Remote Sensing ◽  
Vegetation Indices ◽  
Weather Conditions ◽  
Aerial Imagery ◽  
Optical Remote Sensing ◽  
Actual Application ◽  
Application Rates ◽  
Temporal And Spatial Variability ◽  
Untreated Check ◽  
Temporal And Spatial

Experiments were conducted from 2000 to 2002 at two locations each year to determine if lactofen and imazethapyr injury to soybean could be detected using digital aerial imagery and ground-based optical remote sensing. Lactofen and imazethapyr were applied at base rates of 105 and 71 g/ha, respectively, and at 0, 2X, and 4X rates. Treated plots were evaluated between 7 and 21 d after treatment for crop injury using a ground-based radiometer and a system using computer analysis of digital aerial imagery. Both the ground-based radiometer and the digital aerial imagery were effective in detecting herbicide injury under most conditions. The digital aerial imagery system was found to be more sensitive in detecting herbicide injury than the ground-based radiometer system. Herbicide or herbicide rate had a significant effect on normalized differential vegetation indices (NDVI) derived from digital aerial imagery in four of four site-years. NDVI values derived from a multispectral ground-based radiometer were significant for herbicide or herbicide rate in four of six site-years. NDVI values from treated plots were subtracted from the NDVI value of the untreated check to generate a ΔNDVI. The resulting ΔNDVI values from the ground-based radiometer system were significant for herbicide or herbicide rate in six of six site-years. Neither optical remote-sensing system was effective at estimating actual application rates of lactofen and imazethapyr across a broad range of field and weather conditions due to temporal and spatial variability in crop response to the herbicides.

Sign in / Sign up

Export Citation Format

Share Document