Hyperspectral remote sensing of evaporate minerals and associated sediments in Lake Magadi area, Kenya

Pleistocene to present evaporitic lacustrine sediments in Lake Magadi, East African Rift Valley, Kenya were studied and mapped using spectral remote sensing methods. This approach incorporated surface mineral mapping using space-borne hyperspectral Hyperion imagery together with laboratory analysis, including visible, near-infrared diffuse reflectance spectroscopy (VNIR) measurements and X-ray diffraction for selected rock and soil samples of the study area. The spectral signatures of Magadiite and Kenyaite, which have not been previously reported, were established and the spectral signatures of trona, chert series, volcanic tuff and the High Magadi bed were also analyzed.Image processing techniques, MNF (Minimum Noise Fraction) and MTMF (Mixture Tuned Matched Filtering) using a stratified approach (image analysis with and without the lake area), were used to enhance the mapping of evaporates. High Magadi beds, chert series and volcanic tuff were identified from the Hyperion image with an overall mapping accuracy of 84.3%. Even though, the spatial distribution of evaporites and sediments in Lake Magadi area change in response to climate variations, the mineralogy of this area has not been mapped recently. The results of this study shows the usefulness of the hypersspectral remote sensing to map the surface geology of this kind of environment and to locate promising sites for industrial open-pit trona mining in a qualitative and quantitative manner.     

Development of a 3-D urbanization index using digital terrain models for surface urban heat island effects

This study assesses surface urban heat island (SUHI) effects during heat waves in subtropical areas. Two cities in northern Taiwan, Taipei metropolis and its adjacent medium-sized city, Yilan, were selected for this empirical study. Daytime and night time surface temperature and SUHI intensity of both cities in five heat wave cases were obtained from MODIS Land-Surface Temperature (LST) and compared. In order to assess SUHI in finer spatial scale, an innovated three-dimensional Urbanization Index (3DUI) with a 5-m spatial resolution was developed to quantify urbanization from a 3-D perspective using Digital Terrain Models (DTMs). The correlation between 3DUI and surface temperatures were also assessed. The results obtained showed that the highest SUHI intensity in daytime was 10.2 °C in Taipei and 7.5 °C in Yilan. The SUHI intensity was also higher than that in non-heat-wave days (about 5 °C) in Taipei. The difference in SUHI intensity of both cities could be as small as only 1.0 °C, suggesting that SUHI intensity was enhanced in both large and medium-sized cities during heat waves. Moreover, the surface temperatures of rural areas in Taipei and Yilan were elevated in the intense heat wave cases, suggesting that the SUHI may reach a plateau when the heat waves get stronger and last longer. In addition, the correlation coefficient between 3DUI and surface temperature was greater than 0.6. The innovative 3DUI can be employed to assess the spatial variation of temperatures and SUHI intensity in much finer spatial resolutions than measurements obtained from remote sensing and weather stations. In summary, the empirical results demonstrated intensified SUHI in large and medium-sized cities in subtropical areas during heat waves which could result in heat stress risks of residents. The innovative 3DUI can be employed to identify vulnerable areas in fine spatial resolutions for formulation of heat wave adaptation strategies.     

基于PROSPECT＋SAIL模型的遥感叶面积指数反演

以PROSPECT+SAIL模型为基础，从物理机理角度反演植被叶面积指数(LAI)。首先，通过FLAASH模型进行大气校正，使得图像像元值表达植被冠层反射率； 然后，根据LOPEX 93数据库和JHU光谱数据库选择植物生化参数和光谱数据，以PROSPECT模型模拟出的植物叶片反射率和透射率作为SAIL模型的输入参数，得到植被冠层反射率，将结果与遥感影像的植被冠层反射率对应，回归出植被LAI； 最后，以地面实测数据对遥感反演数据进行验证，并分析了误差的可能来源。     

Determination of the factors governing soil erodibility using hyperspectral visible and near-infrared reflectance spectroscopy

Soil erodibility, which is difficult to estimate and upscaling, was determined in this study using multiple spectral models of soil properties (soil organic matter (SOM), water-stable aggregates (WSA) > 0.25 mm, the geometric mean radius (D_g)). Herein, the soil erodibility indicators were calculated, and soil properties were quantitatively analyzed based on laboratory simulation experiments involving two selected contrasting soils. In addition, continuous wavelet transformation was applied to the reflectance spectra (350–2500 nm) of 65 soil samples from the study area. To build the relationship, the soil properties that control erodibility were identified prior to the spectral analysis. In this study, the SOM, D_g and WSA >0.25 mm were selected to represent the most significant soil properties controlling erodibility and describe the erodibility indicator based on a logarithmic regression model as a function of SOM or WSA > 0.25 mm. Five, six and three wavelet features were observed to calibrate the estimated soil properties model, and the best performance was obtained with a combination feature regression model for SOM (R² = 0.86, p < 0.01), D_g (R² = 0.79, p < 0.01) and WSA >0.25 mm (R² = 0.61, p < 0.01), respectively. One part of the wavelet features captured amplitude variations in the broad shape of the reflectance spectra, and another part captured variations in the shape and depth of the soil dry substances. The wavelet features for the validated dataset used to predict the SOM, WSA >0.25 mm and D_g were not significantly different compared with the calibrated dataset. The synthesized spectral models of soil properties, and the formation of a new equation for soil erodibility transformed from the spectral models of soil properties are presented in this study. These results show that a spectral analytical approach can be applied to complex datasets and provide new insights into emerging dynamic variation with erodibility estimation.     

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.     

Assessing the performance of a large-scale irrigation system by estimations of actual evapotranspiration obtained by Landsat satellite images resampled with cubic convolution

Remote sensing techniques allow monitoring the Earth surface and acquiring worthwhile information that can be used efficiently in agro-hydrological systems. Satellite images associated to computational models represent reliable resources to estimate actual evapotranspiration fluxes, ET_a, based on surface energy balance. The knowledge of ET_a and its spatial distribution is crucial for a broad range of applications at different scales, from fields to large irrigation districts. In single plots and/or in irrigation districts, linking water volumes delivered to the plots with the estimations of remote sensed ET_a can have a great potential to develop new cost-effective indicators of irrigation performance, as well as to increase water use efficiency. With the aim to assess the irrigation system performance and the opportunities to save irrigation water resources at the “SAT Llano Verde” district in Albacete, Castilla-La Mancha (Spain), the Surface Energy Balance Algorithm for Land (SEBAL) was applied on cloud-free Landsat 5 Thematic Mapper (TM) images, processed by cubic convolution resampling method, for three irrigation seasons (May to September 2006, 2007 and 2008). The model allowed quantifying instantaneous, daily, monthly and seasonal ET_a over the irrigation district. The comparison between monthly irrigation volumes distributed by each hydrant and the corresponding spatially averaged ET_a, obtained by assuming an overall efficiency of irrigation network equal to 85%, allowed the assessment of the irrigation system performance for the area served by each hydrant, as well as for the whole irrigation district. It was observed that in all the investigated years, irrigation volumes applied monthly by farmers resulted generally higher than the corresponding evapotranspiration fluxes retrieved by SEBAL, with the exception of May, in which abundant rainfall occurred. When considering the entire irrigation seasons, it was demonstrated that a considerable amount of water could have been saved in the district, respectively equal to 26.2, 28.0 and 16.4% of the total water consumption evaluated in the three years.     

Occurrence and Distribution of Organic Contaminants in the Aquatic System in Berlin.Part II: Substituted Phenols in Berlin Surface Water

In a surface water screening, 30 representative surface water samples collected from rivers, canals, and lakes in Berlin were investigated for the presence of 22 substituted phenols. The phenols selected include the 11 phenols considered as “priority pollutants” by the US Environmental Protection Agency (US-EPA). Surface water samples were extracted applying solid-phase extraction with styrenedivinylbenzene adsorbent. The recoveries, determined in spiking experiments, were between 80 % and 103 %. After derivatization with N-(tert-butyldimethylsilyl)-N-methyl-trifluoroacetamide (MTBSTFA) the samples were analyzed by capillary gas chromatography-mass spectrometry (GC-MS). Phenol, cresols, 2-ethylphenol, 2-chlorophenol, 4-chloro-3-methylphenol, pentachlorophenol, 2-nitrophenol, and 4-nitrophenol were detected in the surface water samples at concentrations between 0.02 μg/L and 7.8 μg/L, respectively. The distribution of these residues in the Berlin surface waters showed that the phenolic residues, with the exception of pentachlorophenol and 2-ethylphenol, do not originate primarily from municipal sewage treatment plants discharges. Some of the phenols are formed naturally or occur as ubiquitous anthropogenic contaminants in the aquatic system.     

Hydrologic response of engineered media in living roofs and bioretention to large rainfalls: experiments and modeling

The hydrologic response of engineered media plays an important role in determining a stormwater control measure's ability to reduce runoff volume, flow rate, timing, and pollutant loads. Five engineered media, typical of living roof and bioretention stormwater control measures, were investigated in laboratory column experiments for their hydrologic responses to steady, large inflow rates. The inflow, medium water content response, and outflow were all measured. The water flow mechanism (uniform flow vs. preferential flow) was investigated by analyzing medium water content response in terms of timing, magnitude, and sequence with depth. Modeling the hydrologic process was conducted in the HYDRUS‐1D software, applying the Richards equation for uniform flow modeling, and a mobile–immobile model for preferential flow modeling. Uniform flow existed in most cases, including all initially dry living roof media with bimodal pore size distributions and one bioretention medium with unimodal pore size distribution. The Richards equation can predict the outflow hydrograph reasonably well for uniform flow conditions when medium hydraulic properties are adequately represented by appropriate functions. Preferential flow was found in two media with bimodal pore size distributions. The occurrence of preferential flow is more likely due to the interaction between the bimodal pore structure and the initial water content rather than the large inflow rate.     

Rock moisture content in the field and the laboratory and its relationship to mechanical weathering studies

Rock moisture content is a major control of mechanical weathering, particularly freeze-thaw, and yet almost no data exist from field situations. This study presents moisture content values for rocks, taken from a variety of positions and conditions, in the maritime Antarctic. Additional information regarding the amount of water the rock could take up, as observed from laboratory experiments, is also presented. The results show that the approaches used in simulation experiments, particularly that of soaking a rock for 24 hours, may produce exaggerated results. It was found that the saturation coefficient (S-value) was a good indicator of frost susceptibility (based on water content) but that the derivation of that value may underestimate the potential of some rocks. The distribution of moisture within rocks is seen as an important, but unkown, factor. The results of these field moisture contents suggest that for simulations of freeze-thaw or hydration to be meaningful then they should have rock water contents based on field observations.