- 标题
- 摘要
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- 实验方案
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Selection of a Spectral Index for Detection of Orange Spotting Disease in Oil Palm (Elaeis guineensis Jacq.) Using Red Edge and Neural Network Techniques
摘要： Spectral screening can play an important role in successful detection of viroid-infected oil palm seedlings from nursery stage prior to transplanting into the ?eld. Coconut cadang–cadang viroid (CCCVd) is the main causal agent of orange spotting (OS) disease. OS disease is an emerging disease in Malaysian plantation. In this study, a glasshouse experiment was conducted with ?fteen CCCVd-inoculated and ?ve healthy oil palm seedlings in the growing season of 2015. Spectral screening was performed using a hyperspectral spectroradiometer, Analytic Spectral Device HandHeld 2 (325–1075 nm). The red edge, a steep gradient in re?ectance between red and near-infrared bands (680–780 nm), was used for selection of red edge bands. A maximum point (i.e., 700 nm) and minimum point (i.e., 768 nm) of red edge were selected from healthy and inoculated spectra. Shifts of red edge in?ection point from healthy to inoculated spectra were also studied. Four well-known spectral indices, namely simple ratio, red edge normalized difference vegetation index, two-band enhanced vegetation index 2 (EVI2), and chlorophyll index red edge, were evaluated using selected red edge bands. The multilayer perceptron neural network model was used to establish a nonlinear relationship between selected spectral bands and each spectral index. EVI2 was selected as a best spectral index which resulted in zero errors at the training, testing, and validation datasets. The highest coef?cient of correlation (r = 1) was recorded between spectral bands (input values) and EVI2 (target values).
关键词： Orange spotting,Red edge,EVI2,Spectroradiometer,MLPNN
更新于2025-09-23 15:23:52
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How qualitative spectral information can improve soil profile classification?
摘要： Soil classification is important to organize the knowledge of soil characteristics. Spectroscopy has increased in the last years as a technique for descriptive and quantitative evaluation of soils. Thus, our objective was to assess qualitative and quantitative methods on soil classification, based on model profiles. Soils in different environments in the Roraima state, Brazil, were evaluated and represented by 16 profiles, providing 109 soil samples, which were analyzed for particle size distribution, chemical attributes and spectral measurement. Visible-near infrared spectra (350–2500 nm) of soil samples were interpreted in terms of intensity, shape and features. The soil color obtained using a spectroradiometer and a colorimeter, and by a soil expert was compared. Descriptive and qualitative analyses were performed for all spectra of the soil profile samples. The descriptive evaluations of the spectral curves from all horizons of the same profile were used to identify the diagnostic attributes and assign a profile to a taxonomic class. This was possible because spectra of samples had specific shapes, features and intensities that combined to present a specific signature. The Outil Statistique d’Aide à la Cartogénèse Automatique and cluster quantitative analyses could not correctly group similar soil classes and they still need to be improved in order to extract all the variability of the spectral data to discriminate soil classes. Soil color quantification by the Munsell system using both equipments showed greater R2 and lower error than that achieved by a soil expert, due to influences of subjectivity inherent in human assessments. Based on this specific case, it was clear that the automatic system may be more consistent than the pedologist’s visual method. Future studies should focus on the development of an online tool that integrates a descriptive approach and spectral information of a given soil profile to determine its probable taxonomic class.
关键词： Munsell color system,soil classification,expert,NIR,colorimeter,spectroradiometer
更新于2025-09-23 15:22:29
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Adaption of an array spectroradiometer for total ozone column retrieval using direct solar irradiance measurements in the UV spectral range
摘要： A compact array spectroradiometer that enables precise and robust measurements of solar UV spectral direct irradiance is presented. We show that this instrument can retrieve total ozone column (TOC) accurately. The internal stray light, which is often the limiting factor for measurements in the UV spectral range and increases the uncertainty for TOC analysis, is physically reduced so that no other stray-light reduction methods, such as mathematical corrections, are necessary. The instrument has been extensively characterised at the Physikalisch-Technische Bundesanstalt (PTB) in Germany. During an international total ozone measurement intercomparison at the Iza?a Atmospheric Observatory in Tenerife, the high-quality applicability of the instrument was verified with measurements of the direct solar irradiance and subsequent TOC evaluations based on the spectral data measured between 12 and 30 September 2016. The results showed deviations of the TOC of less than 1.5 % from most other instruments in most situations and not exceeding 3 % from established TOC measurement systems such as Dobson or Brewer.
关键词： stray-light reduction,direct solar irradiance measurements,array spectroradiometer,total ozone column,UV spectral range
更新于2025-09-23 15:21:21
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[IEEE 2018 VII. Lighting Conference of the Visegrad Countries (Lumen V4) - Trebic, Czech Republic (2018.9.18-2018.9.20)] 2018 VII. Lighting Conference of the Visegrad Countries (Lumen V4) - Analysis of Liquid Dielectrics by Photometric Instruments
摘要： The liquid dielectrics are used as an electrical insulation or as a medium for heat transfer in the power energy and high voltage devices such as transformers, HV cables or bushings. However dielectric degradations of these liquids are formed in time, most often caused by chemical pollution, thermal destruction or by the electric field influences. Especially electric strength and dissipation factor of insulating oil are affected by these negative influences. The result is the deterioration of devices isolation, which may cause the termination of devices life or even fire or explosion. To avoid loss of the device and further damage, the oil is periodically sampled from the device. The sample of oil is then analyzed, diagnosed and measured in the laboratory. Electrical parameters, mechanical and optical properties are the most common measured quantities. The optical analysis is usually very fast and reliable. There are many commercial analysis devices available on the market. However, none of them can measure all the parameters according to the standards with user settings. The design and realization of optical diagnostic equipment for analysis of liquid dielectrics according ISO 2049 and EN 60422 are the main contribution of this paper. Next monitored parameter is the spectral absorption and transparency of these liquids in the visible and UV spectrum. The proper function and accuracy of the measured methods will be verified in the Light laboratory and in the CVVOZEPower Laboratory in Brno University of Technology.
关键词： spectroradiometer,D-lamp,insulating oil,silicone oil,UV-vis,mineral oil,spectrophotometer,liquid dielectric,spectroscopy,spectrum
更新于2025-09-23 15:21:21
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[IEEE 2018 10th IAPR Workshop on Pattern Recognition in Remote Sensing (PRRS) - Beijing (2018.8.19-2018.8.20)] 2018 10th IAPR Workshop on Pattern Recognition in Remote Sensing (PRRS) - An Elegant End-to-End Fully Convolutional Network (E3FCN) for Green Tide Detection Using MODIS Data
摘要： Using remote sensing (RS) data to monitor the onset, proliferation and decline of green tide (GT) has great significance for disaster warning, trend prediction and decision-making support. However, remote sensing images vary under different observing conditions, which bring big challenges to detection missions. This paper proposes an accurate green tide detection method based on an Elegant End-to-End Fully Convolutional Network (E3FCN) using Moderate Resolution Imaging Spectroradiometer (MODIS) data. In preprocessing, RS images are firstly separated into subimages by a sliding window. To detect GT pixels more efficiently, the original Fully Convolutional Neural Network (FCN) architecture is modified into E3FCN, which can be trained end-to-end. The E3FCN model can be divided into two parts, contracting path and expanding path. The contracting path aims to extract high-level features and the expanding path aims to provide a pixel-level prediction by using a skip technique. The prediction result of whole image is generated by merging the prediction results of subimages, which can also improve the final performance. Experiment results show that the average precision of E3FCN on the whole data sets is 98.06%, compared to 73.27% of Support Vector Regression (SVR), 71.75% of Normalized Difference Vegetation Index (NDVI), and 64.41% of Enhanced Vegetation Index (EVI).
关键词： green tide,Elegant End-to-End Fully Convolutional Network (E3FCN),deep learning,remote sensing,Moderate Resolution Imaging Spectroradiometer (MODIS)
更新于2025-09-23 15:21:01
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An Evaluation of MODIS-Retrieved Aerosol Optical Depth over AERONET Sites in Alaska
摘要： The air quality monitoring network in Alaska is currently limited to ground-based observations in urban areas and national parks, leaving a large proportion of the state unmonitored. The use of Moderate Resolution Imaging Spectroradiometer MODIS aerosol optical depth (AOD) to estimate ground-level particulate pollution concentrations has been successfully demonstrated around the world and could potentially be used in Alaska. In this work, MODIS AOD measurements at 550 nm were validated against AOD derived from two ground-based Aerosol Robotic Network (AERONET) sunphotometers in Alaska, located at Utqiagvik (previously known as Barrow) and Bonanza Creek, to determine if MODIS AOD from the Terra and Aqua satellites could be used to estimate ground-level particulate pollution concentrations. The MODIS AOD was obtained from MODIS collection 6 using the dark target Land and Ocean algorithms from years 2000 to 2014. MODIS data could only be obtained between the months of April and October; therefore, it was only evaluated for those months. Individual and combined Terra and Aqua MODIS data were considered. The results showed that MODIS collection 6 products at 10-km resolution for Terra and Aqua combined are not valid over land but are valid over the ocean. Note that the individual Terra and Aqua MODIS collection 6 AOD products at 10-km resolution are valid over land individually but not when combined. Results also suggest the MODIS collection 6 AOD products at 3-km resolution are valid over land and ocean and perform better over land than the 10-km product. These findings indicate that MODIS collection 6 AOD products can be used quantitatively in air quality applications in Alaska during the summer months.
关键词： Alaska,Aerosol Optical Depth,Moderate Resolution Imaging Spectroradiometer,Aerosol Robotic Network,air quality
更新于2025-09-23 15:21:01
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Error Budget for Geolocation of Spectroradiometer Point Observations from an Unmanned Aircraft System
摘要： We investigate footprint geolocation uncertainties of a spectroradiometer mounted on an unmanned aircraft system (UAS). Two microelectromechanical systems-based inertial measurement units (IMUs) and global navigation satellite system (GNSS) receivers were used to determine the footprint location and extent of the spectroradiometer. Errors originating from the on-board GNSS/IMU sensors were propagated through an aerial data georeferencing model, taking into account a range of values for the spectroradiometer field of view (FOV), integration time, UAS flight speed, above ground level (AGL) flying height, and IMU grade. The spectroradiometer under nominal operating conditions (8° FOV, 10 m AGL height, 0.6 s integration time, and 3 m/s flying speed) resulted in footprint extent of 140 cm across-track and 320 cm along-track, and a geolocation uncertainty of 11 cm. Flying height and orientation measurement accuracy had the largest influence on the geolocation uncertainty, whereas the FOV, integration time, and flying speed had the biggest impact on the size of the footprint. Furthermore, with an increase in flying height, the rate of increase in geolocation uncertainty was found highest for a low-grade IMU. To increase the footprint geolocation accuracy, we recommend reducing flying height while increasing the FOV which compensates the footprint area loss and increases the signal strength. The disadvantage of a lower flying height and a larger FOV is a higher sensitivity of the footprint size to changing distance from the target. To assist in matching the footprint size to uncertainty ratio with an appropriate spatial scale, we list the expected ratio for a range of IMU grades, FOVs and AGL heights.
关键词： geolocation,error propagation,UAV,spectroradiometer,footprint,UAS,aerial spectroscopy
更新于2025-09-19 17:15:36
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Retrieval of Maize Leaf Area Index Using Hyperspectral and Multispectral Data
摘要： Field spectra acquired from a handheld spectroradiometer and Sentinel-2 images spectra were used to investigate the applicability of hyperspectral and multispectral data in retrieving the maize leaf area index in low-input crop systems, with high spatial and intra-annual variability, and low yield, in southern Mozambique, during three years. Seventeen vegetation indices, comprising two and three band indices, and nine machine learning regression algorithms (MLRA) were tested for the statistical approach while five cost functions were tested in the look-up-table (LUT) inversion approach. The three band vegetation indices were selected, specifically the modified difference index (mDId: 725; 715; 565) for the hyperspectral dataset and the modified simple ratio (mSRc: 740; 705; 865) for the multispectral dataset of field spectra and the three band spectral index (TBSIb: 665; 865; 783) for the Sentinel-2 dataset. The relevant vector machine was the selected MLRA for the two datasets of field spectra (multispectral and hyperspectral) while the support vector machine was selected for the Sentinel-2 data. When using the LUT inversion technique, the minimum contrast estimation and the Bhattacharyya divergence cost functions were the best performing. The vegetation indices outperformed the other two approaches, with the TBSIb as the most accurate index (RMSE = 0.35). At the field scale, spectral data from Sentinel-2 can accurately retrieve the maize leaf area index in the study area.
关键词： hyperspectral,multispectral,vegetation indices,Sentinel-2,machine learning regression algorithms,PROSAIL,field-spectroradiometer,LUT inversion,leaf area index
更新于2025-09-19 17:15:36
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Screw-Shaped Plastic Optical Fibers for Refractive Index Sensing
摘要： This paper reports a novel nonlinear algorithm for retrieving near surface air temperature over a large area using support vector machines with satellite remote sensing and other types of data. The steps include the following. 1) Establish the 1st sub model learning dataset and validation dataset, then obtain the 2nd to f th sub model learning datasets and validation datasets, using unmanned weather station data and prede?ned in?uential variables. 2) Retrieve Ta of the target area. 3) Correct the generated Ta images based on prediction errors using the inverse distance weighting interpolation. The novelty of this algorithm is to apply multiple sources of remote sensing data combined with data of unmanned weather stations, topography, ground cover, DEM, and astronomy and calendar rules. The results indicated that the model has high accuracy, reliability, and generalization ability. Factors such as cloudiness, ground vegetation, and water vapor show little interference, so the model seems suitable for large area retrieving under natural conditions. The required high-performance computation was achieved by a CPU + GPU isomery and synergy parallel computation system that improved computing speed by more than 1000-fold, with easily extendable computing capability. We found that the current algorithm is superior to seven major split-window algorithms and their best combined algorithms based on prediction errors, root-mean-square errors, and the percentage of data points with <3 ?C absolute error. Our SVM approach overcomes shortcomings of classical temperature remote sensing technologies, and is the ?rst report of such application.
关键词： high-performance computation (HPC),moderate-resolution imaging spectroradiometer (MODIS),digital elevation model (DEM),Area-wide retrieving,GIS spatial analysis,remote sensing,satellite,multivariable analysis,support vector machine (SVM)
更新于2025-09-16 10:30:52
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A Long-Term Historical Aerosol Optical Depth Data Record (1982-2011) Over China From AVHRR
摘要： A long-term historical aerosol optical depth (AOD) data (15–45° N; 75–135° E) with 0.1 spatial resolution has been produced from Advanced Very High Resolution Radiometer (AVHRR) Pathfinder Atmospheres—Extended level-2B data. The spatial distribution pattern shows that high AOD values are found in central and eastern China over the entire period with AODs larger in summer and spring than in autumn and winter. As the high-quality products from AERONET were absent for this period over mainland China, AOD data obtained using the broadband extinction method from solar radiation stations have been used to verify the quality of the AVHRR AOD data set over China. The intercomparison results show that the interannual variation of AOD has been well captured in the variation curve of the AOD monthly mean and the variation trend is also consistent over the whole period. The correlation coefficient of the monthly mean is mostly larger than 0.55, the agreement index is larger than 0.57, and the relative error is less than 21%. Both AVHRR and visibility data sets show high values in regions with rapid economic development. Using Moderate Resolution Imaging Spectroradiometer AOD data as references, it is found that AVHRR AOD from this paper has better accuracy in general than that from Deep Blue (DB) algorithm over China, especially over eastern and southern China, while DB provides more coverage especially over bright surface such as northwest China. This long-term historic AOD data set can be used together with other AOD data sets to study the climate and environmental changes, especially in the 1980s and 1990s.
关键词： Aerosol optical depth (AOD),Advanced Very High Resolution Radiometer (AVHRR),solar radiation,multiple regression method,Moderate Resolution Imaging Spectroradiometer (MODIS)
更新于2025-09-10 09:29:36