Changes in hyperspectral reflectance signatures of lettuce leaves in response to macronutrient deficiencies

The adaptation of specific remote sensing and hyperspectral analysis techniques for the determination of incipient nutrient stress in plants could allow early detection and precision supplementation for remediation, important considerations for minimizing mass of advanced life support systems on space station and long term missions. This experiment was conducted to determine if hyperspectral reflectance could be used to detect nutrient stress in Lactuca sativa L. cv. Black Seeded Simpson. Lettuce seedlings were grown for 90 days in a greenhouse or growth chamber in vermiculite containing modified Hoagland’s nutrient solution with key macronutrient elements removed in order to induce a range of nutrient stresses, including nitrogen, phosphorus, potassium, calcium, and magnesium. Leaf tissue nutrient concentrations were compared with corresponding spectral reflectances taken at the end of 90 days. Spectral reflectances varied with growing location, position on the leaf, and nutrient deficiency treatment. Spectral responses of lettuce leaves under macronutrient deficiency conditions showed an increase in reflectance in the red, near red, and infrared wavelength ranges. The data obtained suggest that spectral reflectance shows the potential as a diagnostic tool in predicting nutrient deficiencies in general. Overlapping of spectral signatures makes the use of wavelengths of narrow bandwidths or individual bands for the discrimination of specific nutrient stresses difficult without further data processing.     

地基Headwall高谱影像大气校正方法

遥感影像大气校正是定量遥感研究的前提与难点之一.大气校正有多种方法和模型.本文研究了目前常用的大气校正方法,包括FLAASH模型、6S模型、ELC方法和QUAC方法,并应用这几种方法对Headwall野外高光谱成像仪获取的高光谱影像进行大气校正.通过对4种典型地物的表观反射率、校正后反射率以及实测反射率进行对比分析,发现4种模型均能有效去除大气的影响,能够较好地恢复地物光谱的典型特征.相对于其他3种大气校正方法,经验线性法对地基Headwall高光谱影像校正效果最好.      

The use of MODIS 250 m bands to improve the MODIS 1 km ocean color atmospheric correction algorithm in turbid water

“Clear water” is a scale-dependent concept, so it is more likely to successfully find the “clear water” from images with smaller scale than that with larger scale data. In this study, an optimal spectral relationship of moderate-resolution imaging spectroradiometer (MODIS) 250 m and 1 km resolution data at near-infrared bands (OSRLM) is constructed for converting pseudo “clear water” reflectance at 859 nm to those at 748 and 869 nm. According to scale effects, the satellite-observed pseudo “clear water” reflectance is greater than 5.18%, larger than that derived from OSRLM model. An atmospheric correction model for MODIS 1km data using pseudo “clear water” reflectance of MODIS 250 m data (ACMM) was developed for improving the performance of traditional “clear water” atmospheric correction model (CWAC). The model validation results indicate that ACMM model has a better performance than CWAC model. By comparison, the uncertainty decreases by 19.18% in the use of ACMM model over CWAC model for deriving water-leaving reflectance in Taihu Lake, China. This uncertainty is significantly reduced in water-leaving reflectance estimation due to partial removal of scale effects on “clear water”. These findings imply that satellite-derived aerosol scattering contribution at smaller scale usually has a better performance than that at larger scale.     

Distribution of chlorophyll and harmful algal blooms (HABs): A review on space based studies in the coastal environments of Chinese marginal seas

Monitoring of spatial and temporal distribution of chlorophyll (Chl-a) concentrations in the aquatic milieu is always challenging and often interesting. However, the recent advancements in satellite digital data play a significant role in providing outstanding results for the marine environmental investigations. The present paper is aimed to review ‘remote sensing research in Chinese seas’ within the period of 24 years from 1978 to 2002. Owing to generalized distributional pattern, the Chl-a concentrations are recognized high towards northern Chinese seas than the southern. Moreover, the coastal waters, estuaries, and upwelling zones always exhibit relatively high Chl-a concentrations compared with offshore waters. On the basis of marine Chl-a estimates obtained from satellite and other field measured environmental parameters, we have further discussed on the applications of satellite remote sensing in the fields of harmful algal blooms (HABs), primary production and physical oceanographic currents of the regional seas. Concerned with studies of HABs, satellite remote sensing proved more advantageous than any other conventional methods for large-scale applications. Probably, it may be the only source of authentic information responsible for the evaluation of new research methodologies to detect HABs. At present, studies using remote sensing methods are mostly confined to observe algal bloom occurrences, hence, it is essential to coordinate the mechanism of marine ecological and oceanographic dynamic processes of HABs using satellite remote sensing data with in situ measurements of marine environmental parameters. The satellite remote sensing on marine environment and HABs is believed to have a great improvement with popular application of technology.     

Advances on Technology and Application of Ocean Color Remote Sensing in China (2004 - 2006)

China has great progress in the technology and application of ocean color remote sensing during 2004-2006. In this report, firstly, four major technical advances are displaying, including (1) the vector radiative transfer numerical model of coupled ocean-atmosphere system; (2) the atmospheric correction algorithm specialized on Chinese high turbid water; (3) systematical research of hyper-spectrum ocean color remote sensing; (4) local algorithms of oceanic parameters, like ocean color components, ocean primary productivity, water transparency, water quality parameters, etc. On the foundation of technical advances, ocean color remote sensing takes effect on ocean environment monitoring, with four major kinds of application systems, namely, (1) the automatic multi-satellites data receiving, processing and application system; (2) the shipboard satellite data receiving and processing system for fishery ground information; (3) Coastal water quality monitoring system, integrating satellite and airborne remote sensing technology and ship measurement; (4) the preliminary system of airborne ocean color remote sensing application system. Finally, the prospective development of Chinese ocean color remote sensing is brought forward. With Chinese second ocean color satellite (HY-1B) orbiting, great strides will take place in Chinese ocean color information accumulation and application.     

Remote sensing of aerosol and radiation from geostationary satellites

The paper presents a high-level overview of current and future remote sensing of aerosol and shortwave radiation budget carried out at the US National Oceanic and Atmospheric Administration (NOAA) from the US Geostationary Operational Environmental Satellite (GOES) series. The retrievals from the current GOES imagers are based on physical principles. Aerosol and radiation are estimated in separate processing from the comparison of satellite-observed reflectances derived from a single visible channel with those calculated from detailed radiative transfer. The radiative transfer calculation accounts for multiple scattering by molecules, aerosol and cloud and absorption by the major atmospheric gases. The retrievals are performed operationally every 30 min for aerosol and every hour for radiation for pixel sizes of 4-km (aerosol) and 15- to 50-km (radiation). Both retrievals estimate the surface reflectance as a byproduct from the time composite of clear visible reflectances assuming fixed values of the aerosol optical depth. With the launch of GOES-R NOAA will begin a new era of geostationary remote sensing. The Advanced Baseline Imager (ABI) onboard GOES-R will offer capabilities for aerosol remote sensing similar to those currently provided by the Moderate Resolution Imaging Spectroradiometer (MODIS) flown on the NASA Earth Observing System (EOS) satellites. The ABI aerosol algorithm currently under development uses a multi-channel approach to estimate the aerosol optical depth and aerosol model simultaneously, both over water and land. Its design is strongly inspired by the MODIS aerosol algorithm. The ABI shortwave radiation budget algorithm is based on the successful GOES Surface and Insolation Product system of NOAA and the NASA Clouds and the Earth’s Radiant Energy System (CERES), Surface and Atmospheric Radiation Budget (SARB) algorithm. In all phases of the development, the algorithms are tested with proxy data generated from existing satellite observations and forward simulations. Final assessment of the performance will be made after the launch of GOES-R scheduled in 2012.     

Retrieval of aerosol optical characteristics from polarization measurements of reflected solar radiation above the oceans

The reflected near infrared solar radiation observed from space above the oceans is due mainly to the atmosphere scattering, as the ocean surface is nearly black. The molecular Rayleigh contribution is also minimized at infrared wavelengths and it can be evaluated. It is shown that the degree of polarization is much more sensitive to the aerosol properties than the radiance. Measurements of polarization at two wavelengths and with an angular scanning are simulated and an inversion algorithm is proposed. It aims at finding an “equivalent aerosol model,” which reproduces the optical thickness and the asymmetry factor of the actual aerosol at all wavelengths in the solar spectrum.     

基于非线性混合模型研究太空风化对月壤光谱的影响

月表太空风化会改变月壤光谱特征, 影响月壤元素遥感反演精度. 研究太空风化对月壤光谱的影响有助于开发月壤成熟度光谱解耦算法, 提高月壤成分遥感反演精度. 直接对比月壤风化前后光谱的变化能最真实反映太空风化对光谱的影响, 但无法获取未风化的月壤样品, 利用实验室模拟方法开展研究也存在缺陷. 本文提出了一种简便的方法来研究太空风化对月壤光谱的影响, 并以月海样品为例进行探讨. 利用Hapke模型对月海样品组成矿物光谱按照实测含量进行非线性混合, 并通过对比混合后的光谱与实测的月壤光谱, 研究太空风化过程对月壤光谱的影响. 研究结果表明, 月壤在遭受太空风化后反射率降低, 波长越短降低越显著; 月壤背景吸收斜率增大, 月壤变得更红, 月壤矿物特征吸收峰深度降低, 光谱对比度变弱, 长波吸收峰(2.0μm附近)深度降低程度超过短波吸收峰(1.0μm附近)深度. 未来在利用遥感技术反演月壤元素含量时, 必须考虑这些因素.      

On uncertainties in carbon flux modelling and remotely sensed data assimilation: The Brasschaat pixel case

Uncertainty on carbon fluxes is determined by the uncertainties of ecosystem model structure, data and model parameter uncertainties and the temporal and spatial inaccuracy of the input data retrieval. The objective of this paper is to understand the error propagation and uncertainty of evaporative fraction (EF), soil moisture content (SMC) and water limited net ecosystem productivity (NEP). In this respect, C-Fix and spaceborne remote sensing are used for the ‘Brasschaat’ pixel. A simple model based on error theory and a Monte-Carlo approach are used. Different error scenarios are implemented to assess input uncertainty on EF, SMC and NEP as estimated with C-Fix.     

Nonlinear mixture model of mixed pixels in remote sensing satellite images based on Monte Carlo simulation

A nonlinear mixture model for the interpretation of mixed pixels in remote sensing satellite images is proposed. The proposed model is a Monte Carlo ray-tracing model that takes into account interactions among the ground cover materials (multiple reflections among the materials on the surface). The proposed model also takes into account topographic features (slope) of the ground surface. As an example, Top of the Atmosphere (TOA) radiance of mixed pixels of forested areas which are composed of grasses and trees are simulated with the proposed model and compared to actual remote sensing satellite data of ASTER/VNIR over these forested areas. It was found that the influence due to multiple scattering interactions between trees depends on the tree distance and ranges from 8% to 10%. It is also found that the proposed model is useful to interpret mixed pixels. Namely, it is suggested that actual reflectance of the trees is higher than apparent reflectance that is calculated with the satellite data. Also it is suggested that it is possible to estimate forest parameters such as tree distance, tree shape.     

A modern robust approach to remotely estimate chlorophyll in coastal and inland zones

The chlorophyll concentration of a water body is an important proxy for representing the phytoplankton biomass. Its estimation from multi or hyper-spectral remote sensing data in natural waters is generally achieved by using (i) the waveband ratioing in two or more bands in the blue-green or (ii) by using a combination of the radiance peak position and magnitude in the red-near-infrared (NIR) spectrum. The blue-green ratio algorithms have been extensively used with satellite ocean color data to investigate chlorophyll distributions in open ocean and clear waters and the application of red-NIR algorithms is often restricted to turbid productive water bodies. These issues present the greatest obstacles to our ability to formulate a modern robust method suitable for quantitative assessments of the chlorophyll concentration in a diverse range of water types. The present study is focused to investigate the normalized water-leaving radiance spectra in the visible and NIR region and propose a robust algorithm (Generalized ABI, GABI algorithm) for chlorophyll concentration retrieval based on Algal Bloom index (ABI) which separates phytoplankton signals from other constituents in the water column. The GABI algorithm is validated using independent in-situ data from various regional to global waters and its performance is further evaluated by comparison with the blue-green waveband ratios and red-NIR algorithms. The results revealed that GABI yields significantly more accurate chlorophyll concentrations (with uncertainties less than 13.5%) and remains more stable in different waters types when compared with the blue-green waveband ratios and red-NIR algorithms. The performance of GABI is further demonstrated using HICO images from nearshore turbid productive waters and MERIS and MODIS-Aqua images from coastal and offshore waters of the Arabian Sea, Bay of Bengal and East China Sea.     

Assessment of plant vitality detection through fluorescence and reflectance imagery

Recent studies of the vegetation fluorescence show that it can be successfully used as an intrinsic indicator of plant photosynthetic activity. With respect to the vegetation spectral reflectance, the chlorophyll (Chl) fluorescence is more specific as an observable of basic biophysical processes in the plant cells. Laser induced fluorescence is widely used in near range remote sensing, but it is not suitable for the global monitoring of vegetation. Decades of active fluorometry studies have collected useful information of leaf reaction to natural and anthropogenic stress. Still the passive fluorescence, the one that could be registered from satellite orbit has still to prove its advantage over widely used reflectance signature. The weakness of the signal and the lack of experience with passive fluorescence measurements require extensive technical, theoretical and experimental studies. New imaging fluorometres are to be designed for measuring steady state fluorescence in controlled and natural conditions.

In order to compare reflectance and steady state fluorescence sensitivity to stress impact, a set of experiments have been conducted under controlled illumination conditions in a bio-chamber, designed by the author’s team. The equipment allows plant vitality to be monitored both by passive fluorescence and spectral reflectance imaging. Different types of stress factors (heat and drought stress, acid impact) were investigated to demonstrate equipments ability in monitoring changes of fluorescence signal. Selected fluorescence images of foliage illustrate an early detection of plant dysfunction and the temporal and spatial spreading of the stress impact. Analysis shows that fluorescence imaging of green plants can be developed as a highly effective early warning remote sensing method, which could have application for an ecosystems’ monitoring along with high-spectral reflectance imagery.     

Quantifying lunar soil composition with partial least squares modeling of reflectance

Retrieval of lunar soil composition is commonly achieved through optical remote sensing in which spectral characteristics of returned lunar samples are related to their constituents. Partial least squares (PLS) and principal component regression (PCR) were applied to the dataset characterized by the Lunar Soil Characterization Consortium (LSCC) to estimate the content of FeO, Al₂O₃ and TiO₂ in the soils. The goal of this study was to test whether the conversion of reflectance to single scattering albedo (SSA) via Hapke’s radiative transfer model is able to improve the performance of PLS and PCR. Results from PLS and PCR modeling of SSA spectra indicate that the conversion does not necessarily improve the performance of PLS and PCR, and this depends on the chemical considered, the way to select the number of optimal factors, and how the data were pretreated. The conversion failed to accommodate the large deviation of highland samples with low FeO, TiO₂ and high Al₂O₃.     

Discrimination of rock types and main rock-forming components in Bulgarian territories through spectral reflectance characteristics

Remote sensing studies on the spectral reflectance of natural formations – rocks, products of different physical and chemical processes in the Earth’s crust and its surface – are reported. Based on spectral reflectance characteristics (SRC) of selected representative rocks with different structure, mineral composition and colour characteristics – sedimentary (psephite-conglomerate) and metamorphic (kyanite schist) – and by applying statistical and deterministic methods the rock types and the main rock-forming components were discriminated. The spectral data were obtained in laboratory using a multichannel spectrometer developed in STIL-BAS, which delivers data in the spectral range 480–810 nm.The a priori mineralogical information about the specimens studied, the actual SRC data, affine and perspective transformations of the colour coordinates of SRC were all utilized to perform a primary classification of the main constituents of the specimens. Cluster analysis was applied and its results were used to design the necessary grouping variables as required for the implementation of linear discriminant analysis. The discriminant functions were constructed from the SRC values for a selected set of wavelengths and of transformed data. Classification of the main ingredients and the rock types were obtained. The proposed novel approach to the spectral discrimination of main rock-forming components is believed relevant for predictive classification of other specimens of rocks through discriminant functions.     

Lower and upper limits to comet p/halley solid material loss rate

A radiative hydrodynamic model of comet P/Halley is used to investigate quantitatively the constraints imposed onto the Comet loss rate in solids by both the in-situ data and the remote sensing data. In particular, for the first time, the in-situ data are used to fit composite spectra extending from near-IR wavelengths to the microwave region. Also, for the first time the uncertainty affecting the ejection velocity of large grains is taken into account. The results suggest that only future rendez-vous studies of the grain density in the vicinity of a comet would be able to provide definitely reliable values of the comet loss rate.     

多波段光谱辐亮度计量值溯源技术研究

光谱辐亮度计是实现空间遥感仪器在地面实验室内进行高精度光谱定标的关键设备之一，本文基于标准探测器的辐亮度传递原理，利用视场光阑、孔径光阑、窄带滤光片和光电二极管研制了10测量通道的遮光筒式多波段光谱辐亮度计，测量波长分布在（400~1 100）nm范围。具有校准通道，与积分球单色光源匹配使用，实现光谱辐亮度的量值溯源，测量不确定度优于2.2%。     

Remote sensing based continuous hydrologic modeling

There are two principal ways in which remote sensing can be used with continuous hydrological models: (1) by providing a cost effective way for obtaining input data and (2) by providing synoptic measurements of various state variables. This paper discusses existing hydrologic models and the modifications required to adapt them for using remotely sensed data that may significantly improve their simulation performance. Microwave and thermal infrared measurements show promise for use in hydrologic models because they can measure certain physical properties of the watershed (emissivity and temperature) from which a hydrologic condition can be inferred. Additional applications of remote sensing data include the use of spatial data, mechanisms for extrapolating point data and direct measurement of several hydrologic state variables such as soil moisture, surface temperature, snow water equivalent, frozen soils, and rainfall distribution. Results are presented from several aircraft flights where thermal infrared and microwave data were collected over a small research basin. These results are discussed with respect to their application in continuous hydrologic simulation models.     

基于多光谱测温优化的材料光谱发射率测量

针对高温材料红外光谱发射率测量中样品表面温度难以准确测量的问题,提出了直接使用光谱仪测量得出样品表面的光谱辐射能量信息,选取其中合适的光谱波段利用多光谱测温方法得到样品表面温度,进而计算出材料的光谱发射率.分析了多光谱测温中发射率模型的阶次和测量波段选取对测温准确度的影响,给出了温度计算的稳健算法,并对其主要不确定度的来源进行了评定.在1 100 K左右温度下以不锈钢材料进行实验验证,得出温度引起的光谱发射率相对不确定度在2～20 μm范围内低于2%,满足红外隐身和辐射测温等领域的要求,适合于导热性能差的材料或涂层材料的高温光谱发射率测量.     

Comparison of ground reflectance measurement with satellite derived atmospherically corrected reflectance: A case study over semi-arid landscape

Atmospheric corrections to satellite data are important for comparing multitemporal data sets over tropical regions with variable aerosol loading. In this study, we evaluated the potential of 6S radiative transfer model for atmospheric corrections of IRS-P6 AWiFS satellite data sets, in a semi-arid landscape. Ground measurements of surface reflectance representing different land use/land cover categories were conducted to relate IRS-P6 AWiFS top of atmospheric reflectance. The 6S radiative transfer model was calibrated for local conditions using ground measurements for aerosol optical depth, water vapor and ozone with a sun photometer. Surface reflectance retrieved from 6S code was compared with top of atmosphere (TOA) reflectance and ground based spectroradiometer measurements. Accurate parameterization of the 6S model using measurements of aerosol optical depth, water vapor and ozone plays an important role while comparing ground and satellite derived reflectance measurements.