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Hyperspectral Distinction of Two Caribbean Shallow-Water Corals Based on Their Pigments and Corresponding Reflectance  [PDF]
Juan L. Torres-Pérez,Liane S. Guild,Roy A. Armstrong
Remote Sensing , 2012, DOI: 10.3390/rs4123813
Abstract: The coloration of tropical reef corals is mainly due to their association with photosynthetic dinoflagellates commonly known as zooxanthellae. Combining High Performance Liquid Chromatography (HPLC), spectroscopy and derivative analysis we provide a novel approach to discriminate between the Caribbean shallow-water corals Acropora cervicornis and Porites porites based on their associated pigments. To the best of our knowledge, this is the first time that the total array of pigments found within the coral holobiont is reported. A total of 20 different pigments were identified including chlorophylls, carotenes and xanthophylls. Of these, eleven pigments were common to both species, eight were present only in A. cervicornis, and three were present only in P. porites. Given that these corals are living in similar physical conditions, we hypothesize that this pigment composition difference is likely a consequence of harboring different zooxanthellae clades with a possible influence of endolithic green or brown algae. We tested the effect of this difference in pigments on the reflectance spectra of both species. An important outcome was the correlation of total pigment concentration with coral reflectance spectra up to a 97% confidence level. Derivative analysis of the reflectance curves showed particular differences between species at wavelengths where several chlorophylls, carotenes and xanthophylls absorb. Within species variability of spectral features was not significant while interspecies variability was highly significant. We recognize that the detection of such differences with actual airborne or satellite remote sensors is extremely difficult. Nonetheless, based on our results, the combination of these techniques (HPLC, spectroscopy and derivative analysis) can be used as a robust approach for the development of a site specific spectral library for the identification of shallow-water coral species. Studies (Torres-Pérez, NASA Postdoctoral Program) are currently underway to further apply this approach to other Caribbean benthic coral reef features. The data will be used with planned and future airborne and satellite studies of the site and for algorithm development to advance the use of future airborne and satellite instrument capabilities (NASA PRISM and HyspIRI) for discrimination of coral reef benthic composition.
Quantitative Hyperspectral Reflectance Imaging  [PDF]
Marvin E. Klein,Bernard J. Aalderink,Roberto Padoan,Gerrit De Bruin,Ted A.G. Steemers
Sensors , 2008, DOI: 10.3390/s8095576
Abstract: Hyperspectral imaging is a non-destructive optical analysis technique that can for instance be used to obtain information from cultural heritage objects unavailable with conventional colour or multi-spectral photography. This technique can be used to distinguish and recognize materials, to enhance the visibility of faint or obscured features, to detect signs of degradation and study the effect of environmental conditions on the object. We describe the basic concept, working principles, construction and performance of a laboratory instrument specifically developed for the analysis of historical documents. The instrument measures calibrated spectral reflectance images at 70 wavelengths ranging from 365 to 1100 nm (near-ultraviolet, visible and near-infrared). By using a wavelength tunable narrow-bandwidth light-source, the light energy used to illuminate the measured object is minimal, so that any light-induced degradation can be excluded. Basic analysis of the hyperspectral data includes a qualitative comparison of the spectral images and the extraction of quantitative data such as mean spectral reflectance curves and statistical information from user-defined regions-of-interest. More sophisticated mathematical feature extraction and classification techniques can be used to map areas on the document, where different types of ink had been applied or where one ink shows various degrees of degradation. The developed quantitative hyperspectral imager is currently in use by the Nationaal Archief (National Archives of The Netherlands) to study degradation effects of artificial samples and original documents, exposed in their permanent exhibition area or stored in their deposit rooms.
Modelling Chlorophyll-a Concentration in Taihu Lake from Hyperspectral Reflectance Data
基于高光谱遥感反射比的太湖水体叶绿素a含量估算模型

JIAO Hong-bo,ZHA Yong,LI Yun-mei,HUANG Jia-zhu,WEI Yu-chun,
焦红波
,查勇,李云梅,黄家柱,韦玉春

遥感学报 , 2006,
Abstract: The study aims to search for the hyperspectral remote sensing bands most sensitive to chlorophyll-a concentration.Through repeated measurements in Taihu Lake,a large quantity of hyperspectral reflectance data and water quality data of the Lake were obtained from June to August of 2004.Those data acquired in unfavorable or abnormal monitoring conditions were removed from the dataset.The remaining ones were analyzed to calculate water-leaving radiance and reflectance of water in Taihu Lake.Chlorophyll-a concentration was then regressed against the reflectance data to identify the most sensitive hyperspectral bands.The established regression model was then used to estimate chlorophyll-a concentration in the Lake.Finally,accuracy of the model was assessed using other independent data.The result generated with the given monitoring method indicates that there are two reflectance peaks at 719nm & 725nm.Of them,the one at 719nm is more enhanced and stable.Through comparative analysis it is found that hyperspectral reflectance at these two peaks can improve the accuracy of estimating chlorophyll-a.Moreover,the accuracy of estimation is the highest using the ratio R_(719)/R_(670) as the independent variable in the linear model.
Performance of Three Reflectance Calibration Methods for Airborne Hyperspectral Spectrometer Data  [PDF]
Tomoaki Miura,Alfredo R. Huete
Sensors , 2009, DOI: 10.3390/s90200794
Abstract: In this study, the performances and accuracies of three methods for converting airborne hyperspectral spectrometer data to reflectance factors were characterized and compared. The “reflectance mode (RM)” method, which calibrates a spectrometer against a white reference panel prior to mounting on an aircraft, resulted in spectral reflectance retrievals that were biased and distorted. The magnitudes of these bias errors and distortions varied significantly, depending on time of day and length of the flight campaign. The “linear-interpolation (LI)” method, which converts airborne spectrometer data by taking a ratio of linearly-interpolated reference values from the preflight and postflight reference panel readings, resulted in precise, but inaccurate reflectance retrievals. These reflectance spectra were not distorted, but were subject to bias errors of varying magnitudes dependent on the flight duration length. The “continuous panel (CP)” method uses a multi-band radiometer to obtain continuous measurements over a reference panel throughout the flight campaign, in order to adjust the magnitudes of the linear-interpolated reference values from the preflight and post-flight reference panel readings. Airborne hyperspectral reflectance retrievals obtained using this method were found to be the most accurate and reliable reflectance calibration method. The performances of the CP method in retrieving accurate reflectance factors were consistent throughout time of day and for various flight durations. Based on the dataset analyzed in this study, the uncertainty of the CP method has been estimated to be 0.0025 ± 0.0005 reflectance units for the wavelength regions not affected by atmospheric absorptions. The RM method can produce reasonable results only for a very short-term flight (e.g., < 15 minutes) conducted around a local solar noon. The flight duration should be kept shorter than 30 minutes for the LI method to produce results with reasonable accuracies. An important advantage of the CP method is that the method can be used for long-duration flight campaigns (e.g., 1-2 hours). Although this study focused on reflectance calibration of airborne spectrometer data, the methods evaluated in this study and the results obtained are directly applicable to ground spectrometer measurements.
Hyperspectral field reflectance measurements to estimate wheat grain yield and plant height
Xavier, Alexandre Candido;Rudorff, Bernardo Friedrich Theodor;Moreira, Mauricio Alves;Alvarenga, Brummer Seda;Freitas, José Guilherme de;Salomon, Marcus Vinicius;
Scientia Agricola , 2006, DOI: 10.1590/S0103-90162006000200004
Abstract: hyperspectral crop reflectance data are useful for several remote sensing applications in agriculture, but there is still a need for studies to define optimal wavebands to estimate crop biophysical parameters. the objective of this work is to analyze the use of narrow and broad band vegetation indices (vi) derived from hyperspectral field reflectance measurements to estimate wheat (triticum aestivum l.) grain yield and plant height. a field study was conducted during the winter growing season of 2003 in campinas, s?o paulo state, brazil. field canopy reflectance measurements were acquired at six wheat growth stages over 80 plots with four wheat cultivars (iac-362, iac-364, iac-370, and iac-373), five levels of nitrogen fertilizer (0, 30, 60, 90, and 120 kg of n ha-1) and four replicates. the following vi were analyzed: a) hyperspectral or narrow-band vi (1. optimum multiple narrow-band reflectance, omnbr; 2. narrow-band normalized difference vegetation index, nb_ndvi; 3. first- and second-order derivative of reflectance; and 4. four derivative green vegetation index); and b) broad band vi (simple ratio, sr; normalized difference vegetation index, ndvi; and soil-adjusted vegetation index, savi). hyperspectral indices provided an overall better estimate of biophysical variables when compared to broad band vi. the omnbr with four bands presented the highest r2 values to estimate both grain yield (r2 = 0.74; booting and heading stages) and plant height (r2 = 0.68; heading stage). best results to estimate biophysical variables were observed for spectral measurements acquired between tillering ii and heading stages.
Hyperspectral field reflectance measurements to estimate wheat grain yield and plant height  [cached]
Xavier Alexandre Candido,Rudorff Bernardo Friedrich Theodor,Moreira Mauricio Alves,Alvarenga Brummer Seda
Scientia Agricola , 2006,
Abstract: Hyperspectral crop reflectance data are useful for several remote sensing applications in agriculture, but there is still a need for studies to define optimal wavebands to estimate crop biophysical parameters. The objective of this work is to analyze the use of narrow and broad band vegetation indices (VI) derived from hyperspectral field reflectance measurements to estimate wheat (Triticum aestivum L.) grain yield and plant height. A field study was conducted during the winter growing season of 2003 in Campinas, S o Paulo State, Brazil. Field canopy reflectance measurements were acquired at six wheat growth stages over 80 plots with four wheat cultivars (IAC-362, IAC-364, IAC-370, and IAC-373), five levels of nitrogen fertilizer (0, 30, 60, 90, and 120 kg of N ha-1) and four replicates. The following VI were analyzed: a) hyperspectral or narrow-band VI (1. optimum multiple narrow-band reflectance, OMNBR; 2. narrow-band normalized difference vegetation index, NB_NDVI; 3. first- and second-order derivative of reflectance; and 4. four derivative green vegetation index); and b) broad band VI (simple ratio, SR; normalized difference vegetation index, NDVI; and soil-adjusted vegetation index, SAVI). Hyperspectral indices provided an overall better estimate of biophysical variables when compared to broad band VI. The OMNBR with four bands presented the highest R2 values to estimate both grain yield (R2 = 0.74; Booting and Heading stages) and plant height (R2 = 0.68; Heading stage). Best results to estimate biophysical variables were observed for spectral measurements acquired between Tillering II and Heading stages.
Hyperspectral Reflectance and Fluorescence Imaging to Detect Scab Induced Stress in Apple Leaves  [PDF]
Stephanie Delalieux,Annemarie Auwerkerken,Willem W. Verstraeten,Ben Somers,Roland Valcke,Stefaan Lhermitte,Johan Keulemans,Pol Coppin
Remote Sensing , 2009, DOI: 10.3390/rs1040858
Abstract: Apple scab causes significant losses in the production of this fruit. A timely and more site-specific monitoring and spraying of the disease could reduce the number of applications of fungicides in the fruit industry. The aim of this leaf-scale study therefore lies in the early detection of apple scab infections in a non-invasive and non-destructive way. In order to attain this objective, fluorescence- and hyperspectral imaging techniques were used. An experiment was conducted under controlled environmental conditions, linking hyperspectral reflectance and fluorescence imaging measurements to scab infection symptoms in a susceptible apple cultivar (Malus x domestica Borkh. cv. Braeburn). Plant stress was induced by inoculation of the apple plants with scab spores. The quantum efficiency of Photosystem II (PSII) photochemistry was derived from fluorescence images of leaves under light adapted conditions. Leaves inoculated with scab spores were expected to have lower PSII quantum efficiency than control (mock) leaves. However, besides scab-induced, also immature leaves exhibited low PSII quantum efficiency. Therefore, this study recommends the simultaneous use of fluorescence imaging and hyperspectral techniques. A shortwave infrared narrow-waveband ratio index (R1480/R2135) is presented in this paper as a promising tool to identify scab stress before symptoms become visible to the naked eye. Low PSII quantum efficiency attended by low narrow waveband R1480/R2135 index values points out scab stress in an early stage. Apparent high PSII quantum efficiency together with high overall reflectance in VIS and SWIR spectral domains indicate a severe, well-developed scab infection.
Based on remote sensing spectral reflectance inversion of suspended sediment concentration model of surfase water at the Yellow River Estuary
基于遥感光谱反射率反演黄河口海域Ⅱ类水体悬浮泥沙浓度模型

FAN Yan-guo,MENG Zhi-he,ZHANG Lei,LIU Fu-sheng,ZHU Hao,
樊彦国
,孟志河,张 磊,刘复生,朱 浩

海洋科学 , 2010,
Abstract: Based on the experimental data of spectral reflectance at the Yellow River Estuary, a regression model was established, combining spectral data of the water surface, which can be used to estimate suspended sediment concentrations and suspended sediment figures can be accessed. It is of great significance to analysis of changes in estuarine and coastal erosion and deposition process.
Evaluation of Hyperspectral Indices for Chlorophyll-a Concentration Estimation in Tangxun Lake (Wuhan, China)  [PDF]
Yaohuan Huang,Dong Jiang,Dafang Zhuang,Jingying Fu
International Journal of Environmental Research and Public Health , 2010, DOI: 10.3390/ijerph7062437
Abstract: Chlorophyll- a (Chl- a) concentration is a major indicator of water quality which is harmful to human health. A growing number of studies have focused on the derivation of Chl- a concentration information from hyperspectral sensor data and the identification of best indices for Chl- a monitoring. The objective of this study is to assess the potential of hyperspectral indices to detect Chl- a concentrations in Tangxun Lake, which is the second largest lake in Wuhan, Central China. Hyperspectral reflectance and Chl- a concentration were measured at ten sample sites in Tangxun Lake. Three types of hyperspectral methods, including single-band reflectance, first derivative of reflectance, and reflectance ratio, were extracted from the spectral profiles of all bands of the hyperspectral sensor. The most appropriate bands for algorithms mentioned above were selected based on the correlation analysis. Evaluation results indicated that two methods, the first derivative of reflectance and reflectance ratio, were highly correlated (R 2 > 0.8) with the measured Chl- a concentrations. Thus, the spatial and temporal variations of Chl- a concentration could be conveniently monitored with these hyperspectral methods.
Relationship between Algal Chlorophyll Concentration and Spectral Reflectance of Inland Water
内陆水体藻类叶绿素浓度与反射光谱特征的关系

SHU Xiao zhou,YIN Qiu,KUANG Ding bo,
疏小舟
,尹球,匡定波

遥感学报 , 2000,
Abstract: Algal chlorophyll measurement is usually used to assess trophic status of lakes. The development of hyperspectral imaging enable it possible to detect spectral features of algal chlorophyll with high spectral resolution and to map the spatial distribution of algae in large lakes with great precision. This study was conducted to establish correlation between hyperspectral reflectance and algal chlorophyll concentration. The problem is complicated by the numerous suspensions and dissolved organic matters in inland water because optical effects of these pollutant substances often overwhelm spectral features of algae. The area studied in this paper is the Lake Taihu in the Yantze river delta, which becomes enriched quickly in nutrients and supports excessive growths of blue alga in summer. Reflectance spectrum of water in the range of 350 to 1050nm was measured by a GER\|1500 radiometer with a bandwidth of 1.6nm. The water was also sampled simultaneously to determine algal chlorophyll concentration and other water quality parameters in the laboratory. The position of reflectance peak near 700nm and reflectance ratio of R 705nm / R 675nm were found to be significantly correlated with algal chlorophyll concentration. Chlorophyll algorithms based on these spectral features are presented.
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