Re-parameterization of a quasi-analytical algorithm for colored dissolved organic matter dominant inland waters

Quasi-Analytical Algorithms (QAAs) are based on radiative transfer equations and have been used to derive inherent optical properties (IOPs) from the above surface remote sensing reflectance (R_rs) in aquatic systems in which phytoplankton is the dominant optically active constituents (OACs). However, Colored Dissolved Organic Matter (CDOM) and Non Algal Particles (NAP) can also be dominant OACs in water bodies and till now a QAA has not been parametrized for these aquatic systems. In this study, we compared the performance of three widely used QAAs in two CDOM dominated aquatic systems which were unsuccessful in retrieving the spectral shape of IOPS and produced minimum errors of 350% for the total absorption coefficient (a), 39% for colored dissolved matter absorption coefficient (a_CDM) and 7566.33% for phytoplankton absorption coefficient (a_phy). We re-parameterized a QAA for CDOM dominated (hereafter QAA_CDOM) waters which was able to not only achieve the spectral shape of the OACs absorption coefficients but also brought the error magnitude to a reasonable level. The average errors found for the 400–750 nm range were 30.71 and 14.51 for a, 14.89 and 8.95 for a_CDM and 25.90 and 29.76 for a_phy in Funil and Itumbiara Reservoirs, Brazil respectively. Although QAA_CDOM showed significant promise for retrieving IOPs in CDOM dominated waters, results indicated further tuning is needed in the estimation of a(λ) and a_phy(λ). Successful retrieval of the absorption coefficients by QAA_CDOM would be very useful in monitoring the spatio-temporal variability of IOPS in CDOM dominated waters.     

低盐湖泊水体盐度光学遥感反演研究——以博斯腾湖为例

利用光学遥感反演盐度,可以充分利用遥感数据的空间代表性,以及目前高分率遥感数据的高时空精度。本文利用MERIS(Medium Resolution Imaging Spectrometer)300 m数据,以干旱区的博斯腾湖(博湖)为例,探讨了光学遥感数据反演低盐湖泊水体盐度的可行性。结果显示:在开都河入流影响的博湖西南角,存在光学遥感反演盐度利用的黄色物质(CDOM)与盐度的反比关系,但相关性不高,而且在博湖区域不同时间、不同区域CDOM与盐度的关系都不同。博湖盐度低于3 g·L-1,而遥感数据计算盐度的精度约为1.1 psu,因而用光学遥感数据计算博湖盐度的误差太大。博湖本身CDOM与盐度关系的时空异质性以及相关性不高,目前光学遥感反演精度有限,因此,在博湖用光学遥感数据反演整个湖区的盐度有困难。用光学数据反演水体盐度要求盐度足够高,盐度和CDOM存在梯度,并满足CDOM扩散守恒,因此用光学遥感反演低盐湖泊水体盐度较为困难。     

Dynamics of chromophoric dissolved organic matter in Mandovi and Zuari estuaries — A study through in situ and satellite data

The spatial and temporal distribution of absorption of chromophoric dissolved organic matter at 440 nm (a_CDOM (440)) in the Mandovi and Zuari estuaries situated along the west coast of India, has been analysed. The study was carried out using remotely sensed data, obtained from the Ocean Colour Monitor (OCM) on board the Indian Remote Sensing satellite — P4, together with in situ data during the period January to December 2005. Satellite retrieval of CDOM absorption was carried out by applying an algorithm developed for the site. A good correlation (R=0.98) was obtained between satellite derived CDOM and in situ data. Time series analysis revealed that spatial distribution of CDOM has a direct link with the seasonal hydrodynamics of the estuaries. The effect of remnant fresh water on CDOM distribution could be analysed by delineating a plume in the offshore region of the Zuari estuary. Though fresh water flux from terrestrial input plays a major role in the distribution of CDOM throughout the Mandovi estuary, its role in the Zuari estuary is significant up to the middle zone. Other processes responsible for feeding CDOM in both the estuaries are coastal advection, in situ production and resuspension of bottom settled sediments. The highest value of a_CDOM(440) was observed in the middle zone of the Mandovi estuary during the post-monsoon season. The relation between a_CDOM(440) and S (spectral slope coefficient of CDOM) could differentiate CDOM introduced in to estuaries through multiple sources. The algorithm developed for the Mandovi estuary is S=0.003 [a_CDOM(440)^−0.7091] while for the Zuari estuary, S=0.0031 [a_CDOM(440)^−0.777], respectively.     

An improved atmospheric correction algorithm for applying MERIS data to very turbid inland waters

Atmospheric correction (AC) is a necessary process when quantitatively monitoring water quality parameters from satellite data. However, it is still a major challenge to carry out AC for turbid coastal and inland waters. In this study, we propose an improved AC algorithm named N-GWI (new standard Gordon and Wang’s algorithms with an iterative process and a bio-optical model) for applying MERIS data to very turbid inland waters (i.e., waters with a water-leaving reflectance at 864.8 nm between 0.001 and 0.01). The N-GWI algorithm incorporates three improvements to avoid certain invalid assumptions that limit the applicability of the existing algorithms in very turbid inland waters. First, the N-GWI uses a fixed aerosol type (coastal aerosol) but permits aerosol concentration to vary at each pixel; this improvement omits a complicated requirement for aerosol model selection based only on satellite data. Second, it shifts the reference band from 670 nm to 754 nm to validate the assumption that the total absorption coefficient at the reference band can be replaced by that of pure water, and thus can avoid the uncorrected estimation of the total absorption coefficient at the reference band in very turbid waters. Third, the N-GWI generates a semi-analytical relationship instead of an empirical one for estimation of the spectral slope of particle backscattering. Our analysis showed that the N-GWI improved the accuracy of atmospheric correction in two very turbid Asian lakes (Lake Kasumigaura, Japan and Lake Dianchi, China), with a normalized mean absolute error (NMAE) of less than 22% for wavelengths longer than 620 nm. However, the N-GWI exhibited poor performance in moderately turbid waters (the NMAE values were larger than 83.6% in the four American coastal waters). The applicability of the N-GWI, which includes both advantages and limitations, was discussed.     

Retrieval of CDOM and DOC Using In Situ Hyperspectral Data: A Case Study for Potable Waters in Northeast China

Chromophoric dissolved organic matter (CDOM), the light absorbing fraction of dissolved organic carbon (DOC), together with phytoplankton and total suspended matter are the main optically active components could be retrieved by remote sensing data. Generally, different composition of DOC and CDOM corresponds to different water surface reflectance. Absorption properties of CDOM and retrieval models for CDOM and DOC were investigated with data from potable reservoirs located in the central of Jilin Province. Water sampling field surveys were conducted on 15, 16 and 19 of September 2012 across the Shitoukoumen, Erlonghu and Xilicheng reservoirs, respectively. Both empirical regression (single band model and band ratio model) and partial least squares coupled with back-propagation artificial neural models (PLSBPNN) were established to estimate CDOM absorption coefficient at 355 nm [a_CDOM(355)] and DOC concentration with in situ measured remote sensing reflectance. It was found that the band ratio models and PLSBPNN model performed well for estimating DOC concentration while the band ratio models yielded the best result in retrieval CDOM. Moreover, all the three models performed better on the DOC concentration estimation than the performance on a_CDOM(355). Band ratio models outperformed (R ² ?=?0.55) other models for estimating CDOM absorption coefficient, while PLSBPNN model outperformed other models with respect to DOC estimation (R ² ?=?0.93). High spectral slope values indicated that CDOM in the potable waters primarily comprised low molecular weight organic substances; while sources of DOC were mainly coming from exogenous input, which was the main reason lead to the difference of model performances on DOC and a_CDOM(355) estimation. The algorithms developed in this study is needed to be tested and refined with more in situ spectral data, also future work is still needed to be undertaken for characterizing the dynamic of the potable water quality with remotely sensed imagery.     

Ocean color reveals phase shift between marine plants and yellow substance

Daily high-resolution Sea-viewing Wide Field-of-view Sensor (SeaWiFS) images of the central North Atlantic Ocean (1998-2003) show that temporal changes in the absorption coefficient of colored dissolved organic matter (CDOM) or "yellow substance" follow changes in phytoplankton pigment absorption coefficient in time. CDOM peaks (between January and March) and troughs (late summer and fall) followed pigment peaks and troughs by approximately two and four weeks, respectively. This phase shift is additional strong evidence that CDOM in the marine environment is derived from phytoplankton degradation. The common assumption of linear covariation between chlorophyll and CDOM is a simplification even in this ocean gyre. Due to the temporal changes in CDOM, chlorophyll concentration estimated based on traditional remote sensing band-ratio algorithms may be overestimated by about 10% during the spring bloom and underestimated by a similar 10% during the fall. These observations are only possible through use of synoptic, precise, accurate, and frequent measurements afforded by space-based sensors because in situ technologies cannot provide the required sensitivity or synoptic coverage to observe these natural phenomena.     

Satellite sensor modeling and 3D geo-positioning using empirical models

The need for the use of general empirical mathematical models for satellite sensor modeling and 3D geo-positioning has increased recently, mainly because of the absence of the satellite sensor information of some of the high-resolution satellites. In addition, empirical mathematical models can be applied to different satellite sensors since they are time independent mathematical models and do not require specialized commercial software packages. This paper discusses the applicability of the empirical mathematical models presented by the 3D affine model and the 3D polynomial models for satellite sensor modeling and 3D geo-positioning. The objectives of the paper are to demonstrate that (a) the 3D affine model and its modifications of the 3D polynomial models are applicable to different satellite sensors and different types of terrain, and (b) under some conditions, the empirical models can produce accuracies close to those from rigorous mathematical models.     

Classification of boreal macrotidal littoral zone habitats in the Gulf of Maine: comparison of IKONOS and CASI multispectral imagery

Increasingly, remote sensing has become a useful tool for mapping and measuring terrestrial and aquatic environments. Advances in the spatial and spectral resolution of satellite-borne sensors have allowed affordable investigations of littoral macrotidal coastal systems that previously required more costly aircraft-based imagery. In this communication, we compare the results from analysis of a 4 m spatial resolution, multispectral IKONOS satellite image of the intertidal habitats of Islesboro, Maine, USA with that of an aerial compact airborne spectral imager survey of the same regions captured 4 years earlier. There was 72% agreement between the surveys in spite of the temporal gaps between the images. Accuracy varied by habitat class and the perceived error can be assigned to temporal and definitional issues rather than basic acquisition and analytic protocols. Most of the error can be explained by: (1) inadequacy of training sites, (2) temporal variations and (3) class definitions. We conclude that IKONOS imagery provides sufficient spatial and spectral resolution to map and monitor diverse intertidal habitats as found in the macrotidal Gulf of Maine.     

Evaluation and use of Resourcesat-I data for agricultural applications

Resourcesat-1 satellite offers a unique opportunity of simultaneous observations at three different spatial scales through LISS-IV, LISS-III^* (improved LISS-III) and AWiFS sensors from a common platform. The sensors have enhanced capabilities in terms of spectral, spatial and radiometric resolution as compared to earlier Indian Remote sensing Satellite sensors. This paper summarizes the results of various studies such as evaluation of sensor characteristics, inter-sensor comparison studies, derivation and validation of surface reflectance measurements, quantification of improvements due to Resourcesat-1 sensors, and their use for various agricultural applications. The studies presented in this paper demonstrate that suit of sensors onboard Resourcesat-1 satellite provides better prospects for several agricultural applications like crop identification, discrimination and crop inventory for some major Indian crops, than its predecessors on IRS satellites.     

利用青海湖水面辐射校正场对FY—1C气象卫星热红外传感器进行绝对辐射定标

利用青海湖水面场FY-1C气象卫星热红外窗区通道进行绝对辐射定标,由CE312野外热红外辐射计在水面测得辐亮度经大气订正传递到卫星入瞳处,考虑到大气吸收削弱影响,同时卫星观测路径大气产生热发散,这两部分对卫星信号的贡献由探空廓线和卫星观测几何输入MODTRAN37计算出来,同时进行CE312野外辐射计与卫星通道光谱响应匹配计算,最终得到卫星入瞳处的表观亮度.这个辐亮度与卫星通道的计数值比较得到该通道绝对定标系数.结果表明利用辐射校正场辐射定标与星上定标相差5%左右,相当于3K的亮温差.     

Is There a Physical Linkage Between Surface Emissive and Reflective Variables Over Non-Vegetated Surfaces?

For a satellite sensor with only one or two thermal infrared channels, it is difficult to retrieve the surface emissivity from the received emissive signal. Empirical linear relationship between surface emissivity and red reflectance are already established for deriving emissivity, but the inner physical mechanism remains unclear. The optical constants of various minerals that cover the spectral range from 0.44 to 13.5 μm in conjunction with modern radiative transfer models were used to produce corresponding surface reflectance and emissivity spectra. Compared to the commonly used empirical linear relationship, a more accurate multiple linear relationship between Landsat TM5 emissivity and optical reflectances was derived using the simulated data, which indicated the necessity of replacing the empirical relationship with the new one for improving surface emissivity estimate in the single channel algorithm. The significant multiple linear relationship between broadband emissivity (BBE, 8–13.5 μm) and MODIS spectral albedos was also derived using the same data. This paper demonstrates that there is a physical linkage between surface emissive and reflective variables, and provides a theoretical perspective on estimating surface emissivity for sensors with only one or two thermal infrared channels.     

Monitoring disasters with a constellation of satellites – type examples from the International Charter ‘Space and Major Disasters’

In the case of a major disaster, information derived from satellite observation is not only highly useful, it may at times be indispensable because of the damage caused by the disaster to ground infrastructure. The International Charter ‘Space and Major Disasters’ (‘the Charter’) has been one of the primary sources of satellite data for the past 11 years to cover events like floods, fires, tsunamis, ocean storms, earthquakes, volcanic eruptions and oil spills. With the growing membership of the Charter, an increasingly large number of sensors are now available, which can be planned with the required temporal frequency and spectral range to cover a disaster event. Some of the type Charter activation cases are reported in this article to demonstrate the innovative use of multi-satellite imagery for disaster response.     

Targeting rare earth element bearing mine tailings on Bangka Island,Indonesia, with Sentinel-2 MSI

A laboratory study on rare earth element bearing mine tailings, collected from Bangka Island, Indonesia, reported a new spectral absorption feature at 674 nm associated with Erbium. The present study aims to evaluate the capability of the European Space Agency’s Sentinel-2 MSI sensors to detect this absorption feature from space. An arithmetic band operation is performed on selected visible and near-infrared spectral bands of a Sentinel-2 image. The results show that Sentinel-2 MSI is capable of detecting the 674 nm Erbium-related absorption feature within the particular environmental setting of the study area.     

基于高光谱卫星遥感数据的UPDM分析方法

提出了一种用于处理多高光谱卫星数据的UPDM分析方法。研究结果证明．该方法应用干Landsat／TM(ETM^-)、Terra／MODIS和ADEOS—II／GLI等高光谱卫星传感器时．光谱重构均方根误差小于0．029适用于研究高光谱卫星遥感数据。     

资源一号02D高光谱影像内陆水体叶绿素a浓度反演

2019-09-12成功发射的资源一号02D卫星(ZY-102D)搭载了新一代可见短波红外高光谱相机AHSI(Advanced Hyperspectral Imager),其丰富的细分波段和较高的空间分辨率在内陆湖库水质监测方面具有较大潜力,但数据可用性有待分析和验证.本研究以中国华东和华北平原的典型富营养湖库(太湖、...     

An Algorithm to Determine the Slope of the Spectral Absorption of Colored Dissolved Organic Matter (CDOM) and Detritus

A simple method to determine the slope of spectral variations of combined absorption of the colored dissolved organic matter and detritus (CDM) is presented. This method uses the slope of total absorption spectrum excluding contribution of waters in lieu of slope for the CDM. The errors in slopes using the new method decreased with increase in contributions of CDM to the total absorption. The relative errors were less than 10% when CDM contributions were above 60% and even at very low contributions of CDM of 25%, errors in the slopes were less than 40%. For estuarine and coastal waters rich in CDM, the errors in the slopes for CDM were less than 10% using this simple method. Absorption of CDM derived using the slope with the new method in a semi-analytical algorithm QAAV6 showed improved performance with RMSE of 0.07, 0.0119 and 0.0027 at 405, 555 and 665 nm respectively and with R² > 0.95 at all spectral range. The method provided values of spectral absorption due to CDM with fewer errors when validated with the satellite derived data from MODIS and SeaWiFS. This method to determine the slope of CDM could be easily implemented in any model, as it was very generic in nature, simple, did not involve any mathematical model and avoids empirical methods. Since the method is also independent of any specific bands, it can be used for most ocean color satellites. Considering the performance of this new method and applicability for most water types, it was considered as a better option to derive the slope of CDM than using a constant value or deriving the slope with empirical method.     

Evaluating the potential of the red edge channel for C3 (Festuca spp.) grass discrimination using Sentinel-2 and Rapid Eye satellite image data

Integrating the Red Edge channel in satellite sensors is valuable for plant species discrimination. Sentinel-2 MSI and Rapid Eye are some of the new generation satellite sensors that are characterized by finer spatial and spectral resolution, including the red edge band. The aim of this study was to evaluate the potential of the red edge band of Sentinel-2 and Rapid Eye, for mapping festuca C3 grass using discriminant analysis and maximum likelihood classification algorithms. Spectral bands, vegetation indices and spectral bands plus vegetation indices were analysed. Results show that the integration of the red edge band improved the festuca C3 grass mapping accuracy by 5.95 and 4.76% for Sentinel-2 and Rapid Eye when the red edge bands were included and excluded in the analysis, respectively. The results demonstrate that the use of sensors with strategically positioned red edge bands, could offer information that is critical for the sustainable rangeland management.     

Spectral sensitivity of ALOS,ASTER, IKONOS,LANDSAT and SPOT satellite imagery intended for the detection of archaeological crop marks

This study compares the spectral sensitivity of remotely sensed satellite images, used for the detection of archaeological remains. This comparison was based on the relative spectral response (RSR) Filters of each sensor. Spectral signatures profiles were obtained using the GER-1500 field spectroradiometer under clear sky conditions for eight different targets. These field spectral signature curves were simulated to ALOS, ASTER, IKONOS, Landsat 7-ETM+, Landsat 4-TM, Landsat 5-TM and SPOT 5. Red and near infrared (NIR) bandwidth reflectance were re-calculated to each one of these sensors using appropriate RSR Filters. Moreover, the normalised difference vegetation index (NDVI) and simple ratio (SR) vegetation profiles were analysed in order to evaluate their sensitivity to sensors spectral filters. The results have shown that IKONOS RSR filters can better distinguish buried archaeological remains as a result of difference in healthy and stress vegetation (approximately 1–8% difference in reflectance of the red and NIR band and nearly 0.07 to the NDVI profile). In comparison, all the other sensors showed similar results and sensitivities. This difference of IKONOS sensor might be a result of its spectral characteristics (bandwidths and RSR filters) since they are different from the rest of sensors compared in this study.     

Role of Aerosol Absorption in Satellite Sensor Calibration

The importance of aerosol absorption in satellite sensor vicarious calibration and/or satellite measurement of physical parameters is reiterated in a sensitivity study performed using a radiative transfer model, with field-measured data as input. Broadband shortwave surface fluxes need to be measured according to new protocols, described herein, to infer atmospheric absorption to improve calibration accuracy to within the plusmn2% stated goal of next-generation sensors such as Visible/Infrared Imager/Radiometer Suite.     

黑体辐射定律遥感教学改革设计与实践

普朗克黑体辐射定律是遥感类课程教学的重点和难点,本文以定律分析为核心,从数值模拟大气层顶太阳光谱辐照度曲线、卫星传感器光谱响应函数卷积计算、地物行星反射率计算及地表温度反演4个方面入手,对黑体辐射定律理论教学和实践教学内容进行优化设计和教学实现。实践证明,该教学改革不仅可以使学生更容易理解和掌握黑体辐射定律揭示的基本规律,而且以此为基础,能够使学生通过实践加深对地物两大特性(反射特性和热辐射特性)的理解,提高学生对遥感类课程的兴趣。