Thermal Water Prospection with UAV, Low-Cost Sensors and GIS. Application to the Case of La Hermida

Sedano-Cibrián, Javier; Pérez-Álvarez, Rubén; Luis-Ruiz, Julio Manuel de; Pereda-García, Raúl; Salas-Menocal, Benito Ramiro

doi:10.3390/s22186756

Cited by 10 publications

(11 citation statements)

References 64 publications

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“…An important aspect of post-mining process monitoring is the study of water quality [20,21,86]. Sedano-Cibrián et al [87] and Koparan et al [88,89] indicate that water quality can be assessed by, among other things, temperature. Iezzi and Todisco [90] note that water temperature can be influenced by natural and anthropological factors.…”

Section: Identification Of Flowing Water On the Basis Of Thermal Orth...mentioning

confidence: 99%

“…Iezzi and Todisco [90] note that water temperature can be influenced by natural and anthropological factors. Various measurement techniques can be used to measure water temperature, primarily based on probing and measuring points [Ibidem], as well as modern methods based on the use of thermal infrared techniques [91] and also unmanned aerial vehicles [87]. A thermal orthophotomap makes it possible to know the temperature of the land surface and water, as any object that has a temperature greater than absolute zero is a source of infrared radiation [92].…”

Section: Identification Of Flowing Water On the Basis Of Thermal Orth...mentioning

confidence: 99%

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Towards a Long-Term Unmanned Aerial Vehicle (UAV) Monitoring Framework for Post-Mining Effects: Prosper-Haniel Case

Pawlik,

Haske,

Flores

et al. 2024

Mining

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Direct and indirect effects after mine operations cease operating must ideally be subjected to perpetual monitoring routines in order to detect possible risks or avoid adverse effects on the surrounding ecosystems at an early stage. In this contribution, mining subsidence lakes created inside the nature reserve Kirchheller Heide and Hilsfeld Forest are subjected to analysis for a long-term monitoring scheme. For this purpose, we employ high-resolution unmanned aerial system (UAS)-based multispectral and thermal mapping tools to provide a fast, non-invasive and multitemporal environmental monitoring method. Specifically, we propose to monitor vegetation evolution through multispectral analysis, biotypes identification using machine learning algorithms, and water surface extent detection, together with their thermal behavior. The aim of this contribution is to present the proposed workflow and first results to establish a baseline for future analyses and subsequent surveys for long-term multi-temporal monitoring.

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Section: Identification Of Flowing Water On the Basis Of Thermal Orth...mentioning

confidence: 99%

Section: Identification Of Flowing Water On the Basis Of Thermal Orth...mentioning

confidence: 99%

Towards a Long-Term Unmanned Aerial Vehicle (UAV) Monitoring Framework for Post-Mining Effects: Prosper-Haniel Case

Pawlik,

Haske,

Flores

et al. 2024

Mining

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“…In recent years, drones have become increasingly popular for close-range monitoring of forests to capture high-resolution images of focus areas [5][6][7][8]. Drones can be fitted with multiple-sensor instruments that take synchronized nadir images at regular intervals as the drone flies over areas to be imaged [9]. Optical sensors that capture information from various parts of the electromagnetic spectrum are commonly used for forest health monitoring applications [5].…”

Section: Introductionmentioning

confidence: 99%

Orthomosaicking Thermal Drone Images of Forests via Simultaneously Acquired RGB Images

et al. 2023

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Operational forest monitoring often requires fine-detail information in the form of an orthomosaic, created by stitching overlapping nadir images captured by aerial platforms such as drones. RGB drone sensors are commonly used for low-cost, high-resolution imaging that is conducive to effective orthomosaicking, but only capture visible light. Thermal sensors, on the other hand, capture long-wave infrared radiation, which is useful for early pest detection among other applications. However, these lower-resolution images suffer from reduced contrast and lack of descriptive features for successful orthomosaicking, leading to gaps or swirling artifacts in the orthomosaic. To tackle this, we propose a thermal orthomosaicking workflow that leverages simultaneously acquired RGB images. The latter are used for producing a surface mesh via structure from motion, while thermal images are only used to texture this mesh and yield a thermal orthomosaic. Prior to texturing, RGB-thermal image pairs are co-registered using an affine transformation derived from a machine learning technique. On average, the individual RGB and thermal images achieve a mutual information of 0.2787 after co-registration using our technique, compared to 0.0591 before co-registration, and 0.1934 using manual co-registration. We show that the thermal orthomosaic generated from our workflow (1) is of better quality than other existing methods, (2) is geometrically aligned with the RGB orthomosaic, (3) preserves radiometric information (i.e., surface temperatures) from the original thermal imagery, and (4) enables easy transfer of downstream tasks—such as tree crown detection from the RGB to the thermal orthomosaic. We also provide an open-source tool that implements our workflow to facilitate usage and further development.

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“…Advanced applications are permeating every area of human life, and they stimulate the development of new UAV technologies [ 1 ]. Due to their widespread availability and ease of use, unmanned aircraft systems drive the development of new military technologies, georeferencing applications, transport and environmental protection solutions [ 2 , 3 , 4 , 5 , 6 , 7 , 8 ]. An analysis of current military conflicts around the world indicates that the use of unmanned vehicle systems in air and on land has profound implications for combat.…”

Section: Introductionmentioning

confidence: 99%

Assessment of Accuracy in Unmanned Aerial Vehicle (UAV) Pose Estimation with the REAL-Time Kinematic (RTK) Method on the Example of DJI Matrice 300 RTK

Czyża

Szuniewicz

Kowalczyk

et al. 2023

Sensors

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The growing possibilities offered by unmanned aerial vehicles (UAV) in many areas of life, in particular in automatic data acquisition, spur the search for new methods to improve the accuracy and effectiveness of the acquired information. This study was undertaken on the assumption that modern navigation receivers equipped with real-time kinematic positioning software and integrated with UAVs can considerably improve the accuracy of photogrammetric measurements. The research hypothesis was verified during field measurements with the use of a popular Enterprise series drone. The problems associated with accurate UAV pose estimation were identified. The main aim of the study was to perform a qualitative assessment of the pose estimation accuracy of a UAV equipped with a GNSS RTK receiver. A test procedure comprising three field experiments was designed to achieve the above research goal: an analysis of the stability of absolute pose estimation when the UAV is hovering over a point, and analyses of UAV pose estimation during flight along a predefined trajectory and during continuous flight without waypoints. The tests were conducted in a designated research area. The results were verified based on direct tachometric measurements. The qualitative assessment was performed with the use of statistical methods. The study demonstrated that in a state of apparent stability, horizontal deviations of around 0.02 m occurred at low altitudes and increased with a rise in altitude. Mission type significantly influences pose estimation accuracy over waypoints. The results were used to verify the accuracy of the UAV’s pose estimation and to identify factors that affect the pose estimation accuracy of an UAV equipped with a GNSS RTK receiver. The present findings provide valuable input for developing a new method to improve the accuracy of measurements performed with the use of UAVs.

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Thermal Water Prospection with UAV, Low-Cost Sensors and GIS. Application to the Case of La Hermida

Cited by 10 publications

References 64 publications

Towards a Long-Term Unmanned Aerial Vehicle (UAV) Monitoring Framework for Post-Mining Effects: Prosper-Haniel Case

Towards a Long-Term Unmanned Aerial Vehicle (UAV) Monitoring Framework for Post-Mining Effects: Prosper-Haniel Case

Orthomosaicking Thermal Drone Images of Forests via Simultaneously Acquired RGB Images

Assessment of Accuracy in Unmanned Aerial Vehicle (UAV) Pose Estimation with the REAL-Time Kinematic (RTK) Method on the Example of DJI Matrice 300 RTK

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