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When generating a true orthophoto from aerial urban scenes, especially those containing man‐made features with large height differences, sawtooth effects in feature edges can occur in the rectified images. Aiming to eliminate such effects, this study proposes an advanced orthorectification method using line segment matches, allowing 3D building edges to be accurately reconstructed. The corresponding 2D line segments are first extracted and matched, enabling the reconstruction of 3D line segments by joining two planes and imposing a line end‐point constraint. The 3D line segments are then dissected into discrete 3D points to be incorporated into the 3D point cloud obtained by a dense matching algorithm. Finally, a more complete and accurate triangulated irregular network (TIN) model can be constructed to provide important basic data for true orthophoto production. Experimental results show that sawtooth effects can be eliminated, resulting in significantly improved quality in the true orthophotograph.
FTIR spectroscopy coupled with an Attenuated Total Reflection (ATR) sampling probe has been demonstrated as a technique for detecting disease in plants. Spectral differences were detected in Japanese Larch (Larix kaempferi) infected with Phytophthora ramorum at 3403cm(-1) and 1730cm(-1), from pine (Pinus spp.) infected with Bursaphelenchus xylophilus at 1070cm(-1), 1425cm(-)1, 1621cm(-1) and 3403cm(-1) and from citrus (Citrus spp.) infected with 'Candidatus liberibacter' at 960cm(-1), 1087cm(-1), 1109cm(-1), 1154cm(-1), 1225cm(-1), 1385cm(-1), 1462cm(-1), 1707cm(-1), 2882cm(-1), 2982cm(-1) and 3650cm(-1). A spectral marker in healthy citrus has been identified as Pentanone but is absent from the diseased sample spectra. This agrees with recent work by Aksenov, 2014. Additionally, the spectral signature of Cutin was identified in the spectra of Pinus spp. and Citrus spp. and is consistent with work by Dubis, 1999 and Heredia-Guerrero, 2014.
Precision agriculture, and more specifically Site-Specific Crop Management (SSCM), has been implemented in some form across nearly all agricultural production systems over the past 25 years. Adoption has been greatest in developed agricultural countries. In this review article, the current situation of SSCM adoption and application is investigated from the perspective of a developed (UK) and developing (China) agricultural economy. The current state-of-the art is reviewed with an emphasis on developments in position system technology and satellite-based remote sensing. This is augmented with observations on the differences between the use of SSCM technologies and methodologies in the UK and China and discussion of the opportunities for (and limitations to) increasing SSCM adoption in developing agricultural economies. A particular emphasis is given to the role of socio-demographic factors and the application of responsible research and innovation (RRI) in translating agritechnologies into China and other developing agricultural economies. Several key research and development areas are identified that need to be addressed to facilitate the delivery of SSCM as a holistic service into areas with low precision agriculture (PA) adoption. This has implications for developed as well as developing agricultural economies.
Abstract. The sea and land surface temperature radiometer (SLSTR) to be flown on the European Space Agency's (ESA) Sentinel-3 mission is a multichannel scanning radiometer that will continue the 21 year dataset of the along-track scanning radiometer (ATSR) series. As its name implies, measurements from SLSTR will be used to retrieve global sea surface temperatures to an uncertainty of <0.3 K traced to international standards. To achieve, these low uncertainties require an end-to-end instrument calibration strategy that includes prelaunch calibration at subsystem and instrument level, on-board calibration systems, and sustained postlaunch activities. The authors describe the preparations for the prelaunch calibration activities, including the spectral response, the instrument level alignment tests, and the solar and infrared radiometric calibrations. A purpose built calibration rig has been designed and built at the Rutherford Appleton Laboratory space department (RAL Space) that will accommodate the SLSTR instrument, the infrared calibration sources, and the alignment equipment. The calibration rig has been commissioned and results of these tests will be presented. Finally, the authors will present the planning for the on-orbit monitoring and calibration activities to ensure that the calibration is maintained. These activities include vicarious calibration techniques that have been developed through previous missions and the deployment of ship-borne radiometers. © The Authors. Published by SPIE under a Creative Commons Attribution 3.0 Unported License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI.
The desire for portable Raman spectrometers is continuously driving the development of novel spectrometer architectures where miniaturisation can be achieved without the penalty of a poorer detection performance. Spatial heterodyne spectrometers are emerging as potential candidates for challenging the dominance of traditional grating spectrometers, thanks to their larger etendue and greater potential for miniaturisation. This paper provides a generic analytical model for estimating and comparing the detection performance of Raman spectrometers based on grating spectrometer and spatial heterodyne spectrometer designs by deriving the analytical expressions for the performance estimator (signal-to-noise ratio, SNR) for both types of spectrometers. The analysis shows that, depending on the spectral characteristics of the Raman light and on the values of some instrument-specific parameters, the ratio of the SNR estimates for the two spectrometers ([Formula: see text]) can vary as much as by two orders of magnitude. Limit cases of these equations are presented for a subset of spectral regimes which are of practical importance in real-life applications of Raman spectroscopy. In particular, under the experimental conditions where the background signal is comparable or larger than the target Raman line and shot noise is the dominant noise contribution, the value of [Formula: see text] is, to a first order of approximation, dependent solely on the relative values of each spectrometer’s etendue and on the number of row pixels in the detector array. For typical values of the key instrument-specific parameters (e.g., etendue, number of pixels, spectral bandwidth), the analysis shows that spatial heterodyne spectrometer-based Raman spectrometers have the potential to compete with compact grating spectrometer designs for delivering in a much smaller footprint (10–30 times) levels of detection performance that are approximately only five to ten times poorer.
Leaf water content (LWC) of crops is a suitable parameter for evaluation of plant water status and arbuscular mycorrhizal effect on the host plant under drought stress. Remote sensing technology provides an effective avenue to estimate LWC in crops. However, few LWC retrieval models have been developed specifically for the arbuscular mycorrhizal inoculated crops. In this study, soybean with inoculation and non-inoculation treatments were planted under the severe drought, moderate drought and normal irrigation levels. The LWC changes under different treatments at the 30 th , 45 th and 64 th day after the inoculation were investigated, and the spectral response characteristics of inoculated and non-inoculated soybean leaves under the three drought stresses were analyzed. Five types of spectral variables/indices including: raw spectral reflectance (R), continuum-removed spectral reflectance (R C), difference vegetation index (DVI), normalized difference vegetation index (NDVI) and ratio vegetation index (RVI) were applied to determine the best estimator of LWC. The results indicate that LWC decreased as the aggravating of drought stress levels. However, LWC in inoculated leaves was higher than that in the counterparts under the same drought stress level, and the values of raw reflectance measured at inoculated leaves were lower than the non-inoculated leaves, especially around 1900 nm and 1410 nm. These water spectral features were more evident in the corresponding continuum-removed spectral reflectance. The newly proposed DVI C (2280, 1900) index, derived from the continuum-removed spectral reflectance at 2280 nm and the raw spectral reflectance at 1900 nm in DVI type of index, was the most robust for soybean LWC assessment, with R 2 value of 0.72 (p < 0.01) and root mean square error (RMSE) and mean absolute error (MAE) of 2.12% and 1.75%, respectively. This study provides a means to monitor the mycorrhizal effect on drought-induced crops indirectly and non-destructively.
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