Low-cost UAV-based thermal infrared remote sensing: Platform, calibration and applications

Hu, Sheng; Huo, Chao; Coopmans, Calvin; Han, Jinlu; McKee, Mac; Chen, YangQuan

doi:10.1109/mesa.2010.5552031

Cited by 63 publications

(46 citation statements)

References 16 publications

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“…FH indicators on the plot and field scale [212][213][214][215][216][217] UAVs can carry different sensor types and thus contribute to a more comprehensive, rapid, cost-effective, comparable and repetitive recording of FH indicators at very high resolution. LiDAR, thermal infrared, multispectral, RGB, hyperspectral, real time video.…”

Section: Application Example Studies Main Findingsmentioning

confidence: 99%

Understanding Forest Health with Remote Sensing-Part II—A Review of Approaches and Data Models

et al. 2017

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Stress in forest ecosystems (FES) occurs as a result of land-use intensification, disturbances, resource limitations or unsustainable management, causing changes in forest health (FH) at various scales from the local to the global scale. Reactions to such stress depend on the phylogeny of forest species or communities and the characteristics of their impacting drivers and processes. There are many approaches to monitor indicators of FH using in-situ forest inventory and experimental studies, but they are generally limited to sample points or small areas, as well as being time-and labour-intensive. Long-term monitoring based on forest inventories provides valuable information about changes and trends of FH. However, abrupt short-term changes cannot sufficiently be assessed through in-situ forest inventories as they usually have repetition periods of multiple years. Furthermore, numerous FH indicators monitored in in-situ surveys are based on expert judgement. Remote sensing (RS) technologies offer means to monitor FH indicators in an effective, repetitive and comparative way. This paper reviews techniques that are currently used for monitoring, including close-range RS, airborne and satellite approaches. The implementation of optical, RADAR and LiDAR RS-techniques to assess spectral traits/spectral trait variations (ST/STV) is described in detail. We found that ST/STV can be used to record indicators of FH based on RS. Therefore, the ST/STV approach provides a framework to develop a standardized monitoring concept for FH indicators using RS techniques that is applicable to future monitoring programs. It is only through linking in-situ and RS approaches that we will be able to improve our understanding of the relationship between stressors, and the associated spectral responses in order to develop robust FH indicators.

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Section: Application Example Studies Main Findingsmentioning

confidence: 99%

Understanding Forest Health with Remote Sensing-Part II—A Review of Approaches and Data Models

et al. 2017

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“…In the last decade, one development in the field of volcanic remote sensing (other than by satellite) has been the use of unmanned aerial vehicles (UAVs) mounted with infrared cameras (e.g., [129]). The chief advantage of such an approach, over that of using satellites, is a higher spatial resolution, given that the UAVs may be a few metres from the surface of interest.…”

Section: Prospects For the Futurementioning

confidence: 99%

An Overview of Infrared Remote Sensing of Volcanic Activity

Blackett

2017

J. Imaging

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Volcanic activity consists of the transfer of heat from the interior of the Earth to the surface. The characteristics of the heat emitted relate directly to the geological processes underway and can be observed from space, using the thermal sensors present on many Earth-orbiting satellites. For over 50 years, scientists have utilised such sensors and are now able to determine the sort of volcanic activity being displayed without hazardous and costly field expeditions. This review will describe the theoretical basis of the discipline and then discuss the sensors available and the history of their use. Challenges and opportunities for future developments are then discussed.

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“…For the last few years CSOIS has been actively been developing the AggieAir architecture (see References [2] [15] [16] [17]), a cohesive framework and system design to bring PRS SUAS to a higher level of safety and functionality. An overview of the AggieAir system is seen in Fig.…”

Section: Aggieair Architecturementioning

confidence: 99%

“…This data can be of any variety; aerial imagery, multispectral analysis (published previously [2]), airborne particle collection, RFID tag locations, etc. These small yet versatile platforms are designed to be controlled by non-experts, yet still provide the highest level of performance for its given mission.…”

Section: Introductionmentioning

confidence: 99%

A payload verification and management framework for small UAV-based personal remote sensing systems

Coopmans

Stark

Coffin

2012

2012 5th International Symposium on Resilient Control Systems

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Small, unmanned aerial systems are becoming more important in many fields, including civilian, scientific applications. Affordable systems that allow remote sensing at a small scale-personal remote sensing-are possible with proper system design. To assure data mission success (i.e., reliable and safe data collection) with low-cost or consumer-level sensor hardware, a well-designed payload management system is needed, along with sensor interface development and standardized testing frameworks for verification. This payload management system ensures a level of airworthiness for Data Mission Assurance. This paper presents such a system, along with motivations and choices such as system architecture and implementation, as well as standardized testing and verification. Data results from flight of a fixed-wing example payload is also included.

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Low-cost UAV-based thermal infrared remote sensing: Platform, calibration and applications

Cited by 63 publications

References 16 publications

Understanding Forest Health with Remote Sensing-Part II—A Review of Approaches and Data Models

Understanding Forest Health with Remote Sensing-Part II—A Review of Approaches and Data Models

An Overview of Infrared Remote Sensing of Volcanic Activity

A payload verification and management framework for small UAV-based personal remote sensing systems

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