AN ALGORITHM FOR ESTIMATING SURFACE SUSPENDED SEDIMENT CONCENTRATIONS WITH LANDSAT MSS DIGITAL DATA1

ABSTRACT: Algorithms for Landsat MSS digital data are needed to reduce the necessity of calibrating each Landsat scene if these data are to be useful in monitoring programs for surface suspended sediments. In this study digital data were extracted from 16 Landsat Multispectral Scanner (MSS) scenes collected between March 1987 and August 1988 over Enid Reservoir in North Central Mississippi. These data were converted to radiance and reflectance data for comparison with field measurements of surface suspended sediment concentrations. Concentrations ranged from 2 to 168 mg/1 during the study with only four greater than 100 mg/l. Linear and polynomial regression analyses were used to relate the surface suspended sediment concentrations with radiance and reflectance. Reflectance in MSS band 2 (0.6 to 0.7 μm) and MSS band 3 (0.7 to 0.8 μm) were best related to the surface suspended sediment concentrations with coefficients of determination accounting for 71 percent and 68 percent of the variation in the data, respectively. Regressions with radiance data accounted for 36 percent (band 2) or less of the variation. Logarithmic transformations of either reflectance or sediment concentrations increase the coefficients of determination for MSS band 2 reflectance data to 81 percent. Regressions between the ratio of MSS band 1 to MSS band 2 reflectances and concentrations also accounted for 80 percent of the variation. An equation Log_e SS (mg/l) = 9.21R½+ 2.71R½2 + 8.45, where S is surface suspended sediment concentrations and R¹/₂ is the ratio of MSS band 1 to MSS band 2 reflectances, provided the best fit to the data with a coefficient of determination of 0.82. This equation is essentially the same as an algorithm proposed by Topliss et at. (1990), for estimating surface suspended sediment concentrations in Canadian coastal waters. These equations for Enid Reservoir and Canadian waters suggest that it may be possible to develop an algorithm for widespread use for estimating surface suspended sediments.     

压力对镜质组反射率与烃类生成的影响

镜质组反射率是广泛使用的成熟度参数 ,长期以来人们普遍认为温度和时间是控制镜质组反射率的主要因素 ,而压力对反射率的影响人们知之甚少。本文综述了模拟实验和地质实例中压力对镜质组反射率和烃类生成影响的不同观点。介绍了过压造成镜质组反射率延尺的两个动力学模型     

Effects of soiling and cleaning on the reflectance and solar heat gain of a light-colored roofing membrane

A roof with high solar reflectance and high thermal emittance (e.g., a white roof) stays cool in the sun, reducing cooling power demand in a conditioned building and increasing summertime comfort in an unconditioned building. The high initial solar reflectance of a white membrane roof (circa 0.8) can be lowered by deposition of soot, dust, and/or biomass (e.g., fungi or algae) to about 0.6; degraded solar reflectances range from 0.3 to 0.8, depending on exposure. We investigate the effects of soiling and cleaning on the solar spectral reflectances and solar absorptances of 15 initially white or light-gray polyvinyl chloride membrane samples taken from roofs across the United States. Black carbon and organic carbon were the two identifiable strongly absorbing contaminants on the membranes. Wiping was effective at removing black carbon, and less so at removing organic carbon. Rinsing and/or washing removed nearly all of the remaining soil layer, with the exception of (a) thin layers of organic carbon and (b) isolated dark spots of biomass. Bleach was required to clear these last two features. At the most soiled location on each membrane, the ratio of solar reflectance to unsoiled solar reflectance (a measure of cleanliness) ranged from 0.41 to 0.89 for the soiled samples; 0.53 to 0.95 for the wiped samples; 0.74 to 0.98 for the rinsed samples; 0.79 to 1.00 for the washed samples; and 0.94 to 1.02 for the bleached samples. However, the influences of membrane soiling and cleaning on roof heat gain are better gauged by fractional variations in solar absorptance. Solar absorptance ratios (indicating solar heat gain relative to that of an unsoiled membrane) ranged from 1.4 to 3.5 for the soiled samples; 1.1 to 3.1 for the wiped samples; 1.0 to 2.0 for the rinsed samples; 1.0 to 1.9 for the washed samples; and 0.9 to 1.3 for the bleached samples.     

SeaWiFS资料水色辐射模式验证的研究

从１９９４ 年～１９９７ 年，作者对杭州湾与长江口海区、台湾至吕宋以东海区和渤海海区，进行了多次光谱测量和同步取样试验，将试验所得资料经计算机处理，确定了三种验证区域各种水色要素与遥感光谱值之间的关系，提出适用于我国验证区域各种水色的验证模式。其各水色模式验证偏差均小于２０％ ，并适用于我国海域ＳｅａＷｉＦＳ水色遥感应用。     

基于水面反射率光谱分类的太湖藻蓝蛋白浓度反演

藻蓝蛋白是蓝藻的标志性色素,利用遥感反演藻蓝蛋白浓度的时空分布对于蓝藻水华监测和预警具有重要意义.太湖水体光学特性时空差异较大,传统的藻蓝蛋白遥感反演方法在太湖各湖区各季节的适用性有限.因此,本文采用先分类再反演的策略,基于水面反射率光谱分类进行太湖藻蓝蛋白浓度反演建模.首先采用逐步迭代的K均值聚类方法实现光谱分类;然后分别利用每一类的训练样本光谱数据建立最适用于该类的藻蓝蛋白反演模型;最后利用每一类的检验样本光谱数据进行反演模型精度评价.为了对比,同时采用不分类的传统方法进行反演建模和精度评价.检验结果表明:基于不分类的传统建模方法得到的均方根误差RMSE=14.14μg·L-1,平均相对误差σ=59.1%,反演结果和实测数据可决系数为0.46;基于光谱分类的建模方法得到RMSE=8.47μg·L-1,σ=31.3%,反演结果和实测数据可决系数为0.87.因此,基于光谱分类的藻类蛋白反演方法有效地提高了反演精度,可以为其它水体的藻蓝蛋白浓度反演提供借鉴.     

Analysis of surface and aerosol polarized reflectance for aerosol retrievals from polarized remote sensing in PRD urban region

A precise estimate of polarization induced by surface is crucial for polarized remote sensing dedicated to monitoring aerosol properties over urban area. The accurate knowledge of interaction between surface and aerosol polarized reflectance is essential for accurately achieving aerosol properties. In order to study surface and aerosol polarized reflectance for aerosol retrievals over urban area, a new airborne directional polarimetric camera (DPC) with high spatial resolution (4 m at 4000 m a.g.l) was developed. The surface polarized reflectance over distinct surface covers of urban area (forest, shrub, and soil) were studied using DPC measurements during a field campaign in the Pearl River Delta (PRD), China. The large variations were found in surface polarized reflectance of distinct urban covers due to surface type variability. For all surface types, the empirical BPDF model cannot describe accurately surface polarized reflectance at all possible illumination and observation geometries. From the quantitatively study of relationship between surface and aerosol polarized contribution to DPC measurements, we show that the polarized contributions of aerosol, which optical properties were defined by ground-based measurements, are much larger than the polarized contribution of surface, and found that the polarized contribution of surface covers increases with decreasing NDVI. The effect of polarization accuracy of measurements on aerosol retrieval was also investigated using DPC measurements, and found that 0.1% polarization accuracy of measurements can be neglected when AOD is retrieved using polarized measurements. Based on the information of effects of polarized reflectance differences between distinct surface covers and polarization accuracy of polarized measurements on retrieved aerosols over urban area, we found that the accuracy of aerosol retrieval over forest covers is higher than other surface types using polarized remote sensing.     

Detecting deforestation with a spectral change detection approach using multitemporal Landsat data: a case study of Kinabalu Park, Sabah, Malaysia

Tropical deforestation is occurring at an alarming rate, threatening the ecological integrity of protected areas. This makes it vital to regularly assess protected areas to confirm the efficacy of measures that protect that area from clearing. Satellite remote sensing offers a systematic and objective means for detecting and monitoring deforestation. This paper examines a spectral change approach to detect deforestation using pattern decomposition (PD) coefficients from multitemporal Landsat data. Our results show that the PD coefficients for soil and vegetation can be used to detect deforestation using change vector analysis (CVA). CVA analysis demonstrates that deforestation in the Kinabalu area, Sabah, Malaysia has significantly slowed from 1.2% in period 1 (1973 and 1991) to 0.1% in period 2 (1991 and 1996). A comparison of deforestation both inside and outside Kinabalu Park has highlighted the effectiveness of the park in protecting the tropical forest against clearing. However, the park is still facing pressure from the area immediately surrounding the park (the 1km buffer zone) where the deforestation rate has remained unchanged.     

Rapid estimation of compost enzymatic activity by spectral analysis method combined with machine learning

The aim of this study was to investigate the feasibility of using visible near-infrared (VisNIR) diffuse reflectance spectroscopy (DRS) as an easy, inexpensive, and rapid method to predict compost enzymatic activity, which traditionally measured by fluorescein diacetate hydrolysis (FDA-HR) assay. Compost samples representative of five different compost facilities were scanned by DRS, and the raw reflectance spectra were preprocessed using seven spectral transformations for predicting compost FDA-HR with six multivariate algorithms. Although principal component analysis for all spectral pretreatments satisfactorily identified the clusters by compost types, it could not separate different FDA contents. Furthermore, the artificial neural network multilayer perceptron (residual prediction deviation = 3.2, validation r² = 0.91 and RMSE = 13.38 μg g^?1 h^?1) outperformed other multivariate models to capture the highly non-linear relationships between compost enzymatic activity and VisNIR reflectance spectra after Savitzky–Golay first derivative pretreatment. This work demonstrates the efficiency of VisNIR DRS for predicting compost enzymatic as well as microbial activity.     

A pilot study on the effect of Cu,Zn, and Cd on the spectral curves and chlorophyll of wheat canopy at tiller stage

The aim of this study was to investigate canopy spectral reflectance responses to different levels of heavy metals copper (Cu), zinc (Zn), and cadmium (Cd) induced stress. Random blocks design experiment was conducted to simulate Cu, Zn, and Cd at five concentration levels. Chlorophyll and visible and near infrared canopy reflectance were measured for each treatment 56 days after seeding using chlorophyll meter SPAD-502 and spectroradiometer, respectively. New vegetative indices termed ratio of inclination angles (RIA), MERIS (the medium resolution imaging spectrometer) terrestrial chlorophyll index (MTCI), and normalized difference vegetation index (NDVI) were used to assess the response of canopy spectral reflectance to different heavy metal levels. Significant spectral variability especially in blue, red, and near infrared reflectance was observed for different heavy metal treatments. One-sample test showed significant difference for NDVI, MTCI, and RIA among five-level treatments at the 0.01 level. Correlation analysis demonstrated that the two vegetative indices (RIA and MTCI) were significantly correlated with chlorophyll meter values for Cd, Cu, and Zn treatments. However, NDVI was only significantly correlated with chlorophyll meter values for Cu and Zn treatments. Linear regression analysis also illustrated that RIA and MTCI were potential indices for predicting chlorophyll concentration with significant F test under Cu-, Zn-, and Cd-mediated stress.     

MATCHING NATURAL WATER COLORS TO MUNSELL STANDARDS1

ABSTRACT: Color of natural waters strongly influences their aesthetic appeal, suitability for recreational use, and aquatic habitat, but methods for routine specification of color have been lacking. An improved method has been developed for specifying water colors in the field. The water color, seen through an underwater viewer, is matched directly to Munsell standard patches observed simultaneously. The Munsell color-matching method was verified versus measurements of the underwater light field, made with a submersible spectroradiometer in 20 different natural waters in New Zealand (mainly lakes), which varied widely in color and other optical characteristics. Hue, the most important color attribute of natural waters, could be matched accurately; the saturation and brightness less so. Color standard patches are not available covering the full range of typically dark water colors, but fortunately, brightness can be measured with simple submersible light sensors. The Munsell color matching method seems suitable for routine water resources survey and monitoring.