Accuracy assessment of aerial photographs acquired using lighter-than-air blimps: low-cost tools for mapping river corridors

1) Hemispherical photography (HP) is a long-standing tool for forest canopy characterization. Currently, there are low-cost fisheye lenses to convert smartphones into high-portable HP equipment; however, they cannot be used whenever since HP is sensitive to illumination conditions. To obtain sound results outside diffuse light conditions, a deep-learning-based system needs to be developed. A ready-to-use alternative is the multiscale color-based binarization algorithm, but it can provide moderate-quality results only for open forests. To overcome this limitation, I propose coupling it with the model-based local thresholding algorithm. I call this coupling the MBCB approach. 2) Methods presented here are part of the R package CAnopy IMage ANalysis (caiman), which I am developing. The accuracy assessment of the new MBCB approach was done with data from a pine plantation and a broadleaf native forest. 3) The coefficient of determination (R^2) was greater than 0.7, and the root mean square error (RMSE) lower than 20 %, both for plant area index calculation. 4) Results suggest that the new MBCB approach allows the calculation of unbiased canopy metrics from smartphone-based HP acquired in sunlight conditions, even for closed canopies. This facilitates large-scale and opportunistic sampling with hemispherical photography.

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ACCURACY ASSESSMENT OF UNDERWATER PHOTOGRAMMETRIC THREE DIMENSIONAL MODELLING FOR CORAL REEFS

ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences ◽

10.5194/isprs-archives-xli-b5-821-2016 ◽

2016 ◽

Vol XLI-B5 ◽

pp. 821-828 ◽

Cited By ~ 1

Author(s):

T. Guo ◽

A. Capra ◽

M. Troyer ◽

A. Gruen ◽

A. J. Brooks ◽

...

Keyword(s):

Coral Cover ◽

Accuracy Assessment ◽

Low Cost ◽

Three Dimensional ◽

Point Clouds ◽

3D Modelling ◽

Relative Accuracy ◽

3D Point Clouds ◽

The Individual ◽

Working Distance

Recent advances in automation of photogrammetric 3D modelling software packages have stimulated interest in reconstructing highly accurate 3D object geometry in unconventional environments such as underwater utilizing simple and low-cost camera systems. The accuracy of underwater 3D modelling is affected by more parameters than in single media cases. This study is part of a larger project on 3D measurements of temporal change of coral cover in tropical waters. It compares the accuracies of 3D point clouds generated by using images acquired from a system camera mounted in an underwater housing and the popular GoPro cameras respectively. A precisely measured calibration frame was placed in the target scene in order to provide accurate control information and also quantify the errors of the modelling procedure. In addition, several objects (cinder blocks) with various shapes were arranged in the air and underwater and 3D point clouds were generated by automated image matching. These were further used to examine the relative accuracy of the point cloud generation by comparing the point clouds of the individual objects with the objects measured by the system camera in air (the best possible values). Given a working distance of about 1.5 m, the GoPro camera can achieve a relative accuracy of 1.3 mm in air and 2.0 mm in water. The system camera achieved an accuracy of 1.8 mm in water, which meets our requirements for coral measurement in this system.

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Accuracy Assessment of Low Cost UAV Based City Modelling for Urban Planning

Tehnicki vjesnik - Technical Gazette ◽

10.17559/tv-20170904202055 ◽

2018 ◽

Vol 25 (6) ◽

Cited By ~ 1

Keyword(s):

Urban Planning ◽

Accuracy Assessment ◽

Low Cost

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Multi-Temporal Vineyard Monitoring through UAV-Based RGB Imagery

Remote Sensing ◽

10.3390/rs10121907 ◽

2018 ◽

Vol 10 (12) ◽

pp. 1907 ◽

Cited By ~ 18

Author(s):

Luís Pádua ◽

Pedro Marques ◽

Jonáš Hruška ◽

Telmo Adão ◽

Emanuel Peres ◽

...

Keyword(s):

Accuracy Assessment ◽

Low Cost ◽

Ground Truth ◽

Volume Estimation ◽

Height Range ◽

Ground Truth Data ◽

Operational Technique ◽

Digital Elevation ◽

Multi Temporal ◽

Aerial Vehicle

This study aimed to characterize vineyard vegetation thorough multi-temporal monitoring using a commercial low-cost rotary-wing unmanned aerial vehicle (UAV) equipped with a consumer-grade red/green/blue (RGB) sensor. Ground-truth data and UAV-based imagery were acquired on nine distinct dates, covering the most significant vegetative growing cycle until harvesting season, over two selected vineyard plots. The acquired UAV-based imagery underwent photogrammetric processing resulting, per flight, in an orthophoto mosaic, used for vegetation estimation. Digital elevation models were used to compute crop surface models. By filtering vegetation within a given height-range, it was possible to separate grapevine vegetation from other vegetation present in a specific vineyard plot, enabling the estimation of grapevine area and volume. The results showed high accuracy in grapevine detection (94.40%) and low error in grapevine volume estimation (root mean square error of 0.13 m and correlation coefficient of 0.78 for height estimation). The accuracy assessment showed that the proposed method based on UAV-based RGB imagery is effective and has potential to become an operational technique. The proposed method also allows the estimation of grapevine areas that can potentially benefit from canopy management operations.

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Land Use/Land Cover Changes Monitoring and Analysis of Dubai Emirate, UAE Using Multi-Temporal Remote Sensing Data

10.29007/jvz3 ◽

2018 ◽

Cited By ~ 2

Author(s):

Mohamed Mostafa Mohamed ◽

Samy Elmahdy

Keyword(s):

Land Use ◽

Land Cover ◽

Accuracy Assessment ◽

Low Cost ◽

Confusion Matrix ◽

Land Development ◽

Remote Sensing Data ◽

Land Use Land Cover ◽

Spectral Angle Mapper ◽

Fast Pace

Dubai is a rapidly urbanizing emirate with land development succeeding at a fast pace. The present study aims to develop a low-cost classifier based on the spectral angle mapper (SAM) and image difference (ID) algorithms. The proposed approach was developed in order to improve Land use/ Land cover (LULC) classification maps for the purpose of monitoring and analysing LULC change during the period from 2000 to 2015 for the Emirate of Dubai. The approach starts by collecting 320 training samples from high resolution images such as QuickBird with a spatial resolution of 60 cm followed by applying a 3×3 spatial convulsion filter, majority/ minority analysis, sieving classes and clump map of the produced LULC maps. After that, the accuracy of the maps were assigned using confusion matrix. The accuracy assessment demonstrated that the targeted 2000, 2005,2010 and 2015 LULC maps have 88.125%, 89.069%, 90.122% and 96.096% accuracy, respectively. The results exhibited that the built-up areas increased by 233.72 km2 (5.81%) from 2000 to 2005 and keeps to increase even up and till the present time. The results also showed that the changes in the periods 2000-2005 and 2010-2015 confirmed that net vegetation area loses were more obvious from 2005 to 2005 than from 2010 to 2015, reducing from 47.618 km2 to 40,820 km2, respectively. This study is of great help to urban planners and decision makers.

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Accuracy assessment of building point clouds automatically generated from iphone images

ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences ◽

10.5194/isprsarchives-xl-5-547-2014 ◽

2014 ◽

Vol XL-5 ◽

pp. 547-552 ◽

Cited By ~ 5

Author(s):

B. Sirmacek ◽

R. Lindenbergh

Keyword(s):

Measurement Errors ◽

Point Cloud ◽

Model Updating ◽

Accuracy Assessment ◽

Low Cost ◽

Point Clouds ◽

3D Models ◽

Map Updating ◽

Cloud Points ◽

Point To Point

Low-cost sensor generated 3D models can be useful for quick 3D urban model updating, yet the quality of the models is questionable. In this article, we evaluate the reliability of an automatic point cloud generation method using multi-view iPhone images or an iPhone video file as an input. We register such automatically generated point cloud on a TLS point cloud of the same object to discuss accuracy, advantages and limitations of the iPhone generated point clouds. For the chosen example showcase, we have classified 1.23% of the iPhone point cloud points as outliers, and calculated the mean of the point to point distances to the TLS point cloud as 0.11 m. Since a TLS point cloud might also include measurement errors and noise, we computed local noise values for the point clouds from both sources. Mean (μ) and standard deviation (&sigma;) of roughness histograms are calculated as (μ1 = 0.44 m., &sigma;1 = 0.071 m.) and (μ2 = 0.025 m., &sigma;2 = 0.037 m.) for the iPhone and TLS point clouds respectively. Our experimental results indicate possible usage of the proposed automatic 3D model generation framework for 3D urban map updating, fusion and detail enhancing, quick and real-time change detection purposes. However, further insights should be obtained first on the circumstances that are needed to guarantee a successful point cloud generation from smartphone images.

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Herstellung von Luftbildkarten in der Provinz Ta'izz (Arabische Republik Jemen)

Geographica Helvetica ◽

10.5194/gh-31-33-1976 ◽

1976 ◽

Vol 31 (1) ◽

pp. 33-38

Author(s):

H. Steffen

Keyword(s):

Field Survey ◽

Low Cost ◽

Aerial Photographs ◽

Control Points ◽

Simple Method ◽

Surface Features ◽

Triangulation Network ◽

Short Time ◽

Yemen Arab Republic

Abstract. This article deals with a simple method to produce photomaps of as yet unsurveyed areas. Since a triangulation network or a topographic inventory of the areas to be mapped did not exist, it was considered most suitable to produce some kind of «preliminary maps»: Maps of medium accuracy but high content of information which could be produced within a short time with modest technical means and at low cost. The following procedure was found to be most suitable for that purpose. A network of control points is established by means of the slotted templet method. Aerial photographs,dodged by the Log Etronic procedure, are assembled to semicontrolled mosaics. Grestlines, plateau edges and Symbols for mountain peaks, passes etc. as well as spot heights, roads, tracks, wells, market places and names of Settlements, districts and surface features are introduced into the photomosaics by means of transparent overlays. This latter Information was collected during a three months' field survey in the Yemen Arab Republic.

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Unmanned Aerial Vehicles for Operational Monitoring of Landfills

Drones ◽

10.3390/drones5040125 ◽

2021 ◽

Vol 5 (4) ◽

pp. 125

Author(s):

Timofey Filkin ◽

Natalia Sliusar ◽

Marco Ritzkowski ◽

Marion Huber-Humer

Keyword(s):

Unmanned Aerial Vehicles ◽

Low Cost ◽

Aerial Imagery ◽

Aerial Photographs ◽

Engineering Systems ◽

Aerial Vehicles ◽

Municipal Solid Waste Landfills ◽

Landfill Management ◽

Visually Based ◽

Solid Waste Landfills

This study justifies the prospect of using aerial imagery from unmanned aerial vehicles (UAVs) for technological monitoring and operational control of municipal solid waste landfills. It presents the results of surveys (aerial imagery) of a number of Russian landfills, which were carried out using low-cost drones equipped with standard RGB cameras. In the processing of aerial photographs, both photogrammetric data processing algorithms (for constructing orthophotoplans of objects and 3D modeling) and procedures for thematic interpretation of photo images were used. Thematic interpretation was carried out based on lists of requirements for the operating landfills (the lists were compiled on the basis of current legislative acts). Thus, this article proposes framework guidelines for the complex technological monitoring of landfills using relatively simple means of remote control. It shows that compliance with most of the basic requirements for landfill operations, which are listed in both Russian and foreign regulation, can be controlled by unmanned aerial imagery. Thus, all of the main technological operations involving waste at landfills (placement, compaction, intermediate isolation) are able to be controlled remotely; as well as compliance with most of the design and planning requirements associated with the presence and serviceability of certain engineering systems and structures (collection systems for leachate and surface wastewater, etc.); and the state of the landfill body. Cases where the compliance with operating standards cannot be monitored remotely are also considered. It discusses the advantages of air imagery in comparison with space imagery (detail of images, operational efficiency), as well as in comparison with ground inspections (speed, personnel safety). It is shown that in many cases, interpreting the obtained aerial photographs for technological monitoring tasks does not require special image processing and can be performed visually. Based on the analysis of the available world experience, as well as the results of the study, it was concluded that unmanned aerial imagery has great potential for solving problems of waste landfill management.

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