25 research outputs found

    Modelling a Historic Oil-Tank Fire Allows an Estimation of the Sensitivity of the Infrared Receptors in Pyrophilous Melanophila Beetles

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    Pyrophilous jewel beetles of the genus Melanophila approach forest fires and there is considerable evidence that these beetles can detect fires from great distances of more than 60 km. Because Melanophila beetles are equipped with infrared receptors and are also attracted by hot surfaces it can be concluded that these infrared receptors are used for fire detection

    Early Diagnosis of Vegetation Health From High-Resolution Hyperspectral and Thermal Imagery: Lessons Learned From Empirical Relationships and Radiative Transfer Modelling

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    [Purpose of Review] We provide a comprehensive review of the empirical and modelling approaches used to quantify the radiation–vegetation interactions related to vegetation temperature, leaf optical properties linked to pigment absorption and chlorophyll fluorescence emission, and of their capability to monitor vegetation health. Part 1 provides an overview of the main physiological indicators (PIs) applied in remote sensing to detect alterations in plant functioning linked to vegetation diseases and decline processes. Part 2 reviews the recent advances in the development of quantitative methods to assess PI through hyperspectral and thermal images.[Recent Findings] In recent years, the availability of high-resolution hyperspectral and thermal images has increased due to the extraordinary progress made in sensor technology, including the miniaturization of advanced cameras designed for unmanned aerial vehicle (UAV) systems and lightweight aircrafts. This technological revolution has contributed to the wider use of hyperspectral imaging sensors by the scientific community and industry; it has led to better modelling and understanding of the sensitivity of different ranges of the electromagnetic spectrum to detect biophysical alterations used as early warning indicators of vegetation health.[Summary] The review deals with the capability of PIs such as vegetation temperature, chlorophyll fluorescence, photosynthetic energy downregulation and photosynthetic pigments detected through remote sensing to monitor the early responses of plants to different stressors. Various methods for the detection of PI alterations have recently been proposed and validated to monitor vegetation health. The greatest challenges for the remote sensing community today are (i) the availability of high spatial, spectral and temporal resolution image data; (ii) the empirical validation of radiation–vegetation interactions; (iii) the upscaling of physiological alterations from the leaf to the canopy, mainly in complex heterogeneous vegetation landscapes; and (iv) the temporal dynamics of the PIs and the interaction between physiological changes.The authors received funding provided by the FluorFLIGHT (GGR801) Marie Curie Fellowship, the QUERCUSAT and ESPECTRAMED projects (Spanish Ministry of Economy and Competitiveness), the Academy of Finland (grants 266152, 317387) and the European Research Council Synergy grant ERC-2013-SyG-610028 IMBALANCE-P.Peer reviewe

    Stimmulation von Mikroorganismen durch Sexualhormone

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    Calibration of uncooled thermal infrared cameras

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    The calibration of uncooled thermal infrared (IR) cameras to absolute temperature measurement is a time-consuming, complicated process that significantly influences the cost of an IR camera. Temperature-measuring IR cameras display a temperature value for each pixel in the thermal image. Calibration is used to calculate a temperature-proportional output signal (IR or thermal image) from the measurement signal (raw image) taking into account all technical and physical properties of the IR camera. The paper will discuss the mathematical and physical principles of calibration, which are based on radiometric camera models. The individual stages of calibration will be presented. After start-up of the IR camera, the non-uniformity of the pixels is first corrected. This is done with a simple two-point correction. If the microbolometer array is not temperature-stabilized, then, in the next step the temperature dependence of the sensor parameters must be corrected. Ambient temperature changes are compensated for by the shutter correction. The final stage involves radiometric calibration, which establishes the relationship between pixel signal and target object temperature. Not all pixels of a microbolometer array are functional. There are also a number of defective, so-called "dead" pixels. The discovery of defective pixels is a multistep process that is carried out after each stage of the calibration process

    Robust next release problem

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    Improving the shutter-less compensation method for TEC-less microbolometer-based infrared cameras

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    Shutter-less infrared cameras based on microbolometer focal plane arrays (FPAs) are the most widely used cameras in thermography, in particular in the fields of handheld devices and small distributed sensors. For acceptable measurement uncertainty values the disturbing influences of changing thermal ambient conditions have to be treated corresponding to temperature measurements of the thermal conditions inside the camera. We propose a compensation approach based on calibration measurements where changing external conditions are simulated and all correction parameters are determined. This allows to process the raw infrared data and to consider all disturbing influences. The effects on the pixel responsivity and offset voltage are considered separately. The responsivity correction requires two different, alternating radiation sources. This paper presents the details of the compensation procedure and discusses relevant aspects to gain low temperature measurement uncertainty

    Two-channel NIR camera system to detect foreign matter in raw cotton

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    Abstract Up to now the spinning mills use camera systems in the visible range of light to detect foreign matter like packaging materials in the raw cotton stream during cotton processing. These systems are limited to colored materials since they can not detect white or transparent foils. In this paper a two channels near infrared camera system capable to recognize these types of extraneous substances is presented. The newly developed camera system is based on two InGaAs line-scan sensors operating in the near infrared range. Both are installed in one single camera head. A 1520nm/1720nm filter pair makes each sensor selective for a specific spectral line within the NIR absorption spectrum that is characteristic for the materials to be detected
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