Spectral monitoring of moorland plant phenology to identify a temporal window for hyperspectral remote sensing of peatland

Recognising the importance of the timing of image acquisition on the spectral response in remote sensing of vegetated ecosystems is essential. This study used full wavelength, 350–2500 nm, field spectroscopy to establish a spectral library of phenological change for key moorland species, and to investigate suitable temporal windows for monitoring upland peatland systems. Spectral responses over two consecutive growing seasons were recorded at single species plots for key moorland species and species sown to restore eroding peat. This was related to phenological change using narrowband vegetation indices (Red Edge Position, Photochemical Reflectance Index, Plant Senescence Reflection Index and Cellulose Absorption Index); that capture green-up and senescence related changes in absorption features in the visible to near infrared and the shortwave infrared. The selection of indices was confirmed by identifying the regions of maximum variation in the captured reflectance across the full spectrum. The indices show change in the degree of variation between species occurring from April to September, measured for plant functional types. A discriminant function analysis between indices and plant functional types determines how well each index was able to differentiate between the plant functional groups for each month. It identifies April and July as the two months where the species are most separable. What is presented here is not one single recommendation for the optimal temporal window for operational monitoring, but a fuller understanding of how the spectral response changes with the phenological cycle, including recommendations for what indices are important throughout the year.     

A GIHS-based spectral preservation fusion method for remote sensing images using edge restored spectral modulation

High spatial resolution and spectral fidelity are basic standards for evaluating an image fusion algorithm. Numerous fusion methods for remote sensing images have been developed. Some of these methods are based on the intensity–hue–saturation (IHS) transform and the generalized IHS (GIHS), which may cause serious spectral distortion. Spectral distortion in the GIHS is proven to result from changes in saturation during fusion. Therefore, reducing such changes can achieve high spectral fidelity. A GIHS-based spectral preservation fusion method that can theoretically reduce spectral distortion is proposed in this study. The proposed algorithm consists of two steps. The first step is spectral modulation (SM), which uses the Gaussian function to extract spatial details and conduct SM of multispectral (MS) images. This method yields a desirable visual effect without requiring histogram matching between the panchromatic image and the intensity of the MS image. The second step uses the Gaussian convolution function to restore lost edge details during SM. The proposed method is proven effective and shown to provide better results compared with other GIHS-based methods.     

A simple two-band semi-analytical model for retrieval of specific absorption coefficients in coastal waters

A non-linear iterative method is used to replace the traditional spectral slope technique in initializing the total absorption decomposition model. Based on comparison of absorption coefficient by QAA and two-band semi-analytical model (TSAA) models with field measurements collected from the West Florida Shelf waters and Bohai Sea, it is shown that both models are effective in estimating absorption coefficients from the West Florida Shelf waters, but the TSAA model is superior to the QAA model. Use of the TSAA model in estimating absorption coefficient in the West Florida Shelf and Bohai Sea decreases the uncertainty of estimation by 1.3–74.7% from the QAA model. The TSAA model’s sensitivity to the input parameters was evaluated by varying one parameter and keeping the others fixed at their default values. Our results indicate that the TSAA model has quite a strong noise tolerance to addressing the field data of the total absorption coefficient.     

Quantifying uncertainty in remote sensing-based urban land-use mapping

Land-use/land-cover information constitutes an important component in the calibration of many urban growth models. Typically, the model building involves a process of historic calibration based on time series of land-use maps. Medium-resolution satellite imagery is an interesting source for obtaining data on land-use change, yet inferring information on the use of urbanised spaces from these images is a challenging task that is subject to different types of uncertainty. Quantifying and reducing the uncertainties in land-use mapping and land-use change model parameter assessment are therefore crucial to improve the reliability of urban growth models relying on these data. In this paper, a remote sensing-based land-use mapping approach is adopted, consisting of two stages: (i) estimating impervious surface cover at sub-pixel level through linear regression unmixing and (ii) inferring urban land use from urban form using metrics describing the spatial structure of the built-up area, together with address data. The focus lies on quantifying the uncertainty involved in this approach. Both stages of the land-use mapping process are subjected to Monte Carlo simulation to assess their relative contribution to and their combined impact on the uncertainty in the derived land-use maps. The robustness to uncertainty of the land-use mapping strategy is addressed by comparing the most likely land-use maps obtained from the simulation with the original land-use map, obtained without taking uncertainty into account. The approach was applied on the Brussels-Capital Region and the central part of the Flanders region (Belgium), covering the city of Antwerp, using a time series of SPOT data for 1996, 2005 and 2012. Although the most likely land-use map obtained from the simulation is very similar to the original land-use map – indicating absence of bias in the mapping process – it is shown that the errors related to the impervious surface sub-pixel fraction estimation have a strong impact on the land-use map's uncertainty. Hence, uncertainties observed in the derived land-use maps should be taken into account when using these maps as an input for modelling of urban growth.     

Estimate of heavy metals in soil and streams using combined geochemistry and field spectroscopy in Wan-sheng mining area,Chongqing, China

Heavy metals contaminated soils and water will become a major environmental issue in the mining areas. This paper intends to use field hyper-spectra to estimate the heavy metals in the soil and water in Wan-sheng mining area in Chongqing. With analyzing the spectra of soil and water, the spectral features deriving from the spectral of the soils and water can be found to build the models between these features and the contents of Al, Cu and Cr in the soil and water by using the Stepwise Multiple Linear Regression (SMLR). The spectral features of Al are: 480 nm, 500 nm, 565 nm, 610 nm, 680 nm, 750 nm, 1000 nm, 1430 nm, 1755 nm, 1887 nm, 1920 nm, 1950 nm, 2210 nm, 2260 nm; The spectral features of Cu are: 480 nm, 500 nm, 610 nm, 750 nm, 860 nm, 1300 nm, 1430 nm, 1920 nm, 2150 nm, 2260 nm; And the spectral features of Cr are: 480 nm, 500 nm, 610 nm, 715 nm, 750 nm, 860 nm, 1300 nm, 1430 nm, 1755 nm, 1920 nm, 1950 nm. With these features, the best models to estimate the heavy metals in the study area were built according to the maximal R². The R² of the models of estimating Al, Cu and Cr in the soil and water are 0.813, 0.638, 0.604 and 0.742, 0.584, 0.513 respectively. And the gradient maps of these three types of heavy metals’ concentrations can be created by using the Inverse distance weighted (IDW).The gradient maps indicate that the heavy metals in the soil have similar patterns, but in the North-west of the streams in the study area, the contents are of great differences. These results show that it is feasible to predict contaminated heavy metals in the soils and streams due to mining activities by using the rapid and cost-effective field spectroscopy.     

Bulk organic δ13C and C/N ratios as palaeosalinity indicators within a Scottish isolation basin

Microfossils in isolation basin sediments are frequently used to reconstruct sea‐level change, but preservation problems and non‐analogue situations can limit their usefulness. Here we investigate the potential of stable carbon isotopes (δ¹³C) and C/N ratios from bulk organic matter, as an alternative proxy of salinity within isolation basin sediments from a basin in northwest Scotland. Within the Holocene sediment δ¹³C and C/N are determined largely by the mean weighted values of the predominant source of the organic material. Analysis of modern materials and comparison with the diatom record shows that the marine parts of the sequence are dominated by high δ¹³C and variable C/N. In the fresh water sequences the organic material is a mixture of both freshwater aquatic and terrestrial plant input that have relatively low δ¹³C and high C/N. The application of δ¹³C and C/N ratios in the studied basin in general follow the environmental change recorded by the diatoms and shows the potential of bulk organic matter in the investigation of salinity change in isolation basins. Copyright © 2005 John Wiley & Sons, Ltd.     

FR－Ⅰ和FR－Ⅱ型射电源的关系—谱特征

本文比较了两类射电源ＦＲ－Ⅰ和ＦＲ－Ⅱ型的射电－光学—Ｘ－ｒａｙ的谱特征。ＦＲ－Ⅰ射电源的射电－光学谱比ＦＲ－Ⅱ射电源平得多（△αｒｏ≈０．１９）；但对于光学－Ｘ－ｒａｙ和射电－Ｘ－ｒａｙ谱，ＦＲ－Ⅰ却比ＦＲ－Ⅱ陡得多（△αｏｘ≈０．４０；△αｒｘ≈０．１０）。初步结果表明，ＦＲ－Ⅱ（Ｇ）可能是ＦＲ－Ⅱ（Ｑ）向ＦＲ－Ⅰ过渡的中间状态。     

THE DEMOGRAPHIC CONSEQUENCES OF METROPOLITAN POPULATION DECONCENTRATION IN THE U.S.

Although the recent growth in the nonmetropolitan population of the U.S. is now well documented, little attention has been given to the consequences these trends will have on the future composition and growth of metropolitan and nonmetropolitan regions. This paper discusses the feedback effects of migration on the future age structure and population growth of both regions during the period 1975–2000.     

Spectral Characteristics and Correction of Long-Term Eddy-Covariance Measurements Over Two Mixed Hardwood Forests in Non-Flat Terrain

We present turbulence spectra and cospectra derived from long-term eddy-covariancemeasurements (nearly 40,000 hourly data over three to four years) and the transferfunctions of closed-path infrared gas analyzers over two mixed hardwood forests inthe mid-western U.S.A. The measurement heights ranged from 1.3 to 2.1 times themean tree height, and peak vegetation area index (VAI) was 3.5 to 4.7; the topographyat both sites deviates from ideal flat terrain. The analysis follows the approach ofKaimal et al. (Quart. J. Roy. Meteorol. Soc. 98, 563–589, 1972) whose results were based upon 15 hours of measurements atthree heights in the Kansas experiment over flatter and smoother terrain. Both thespectral and cospectral constants and stability functions for normalizing and collapsingspectra and cospectra in the inertial subrange were found to be different from those ofKaimal et al. In unstable conditions, we found that an appropriate stabilityfunction for the non-dimensional dissipation of turbulent kinetic energy is of the form ₍₎ = (1 - b^-)^-1/4 - c^-, where representsthe non-dimensional stability parameter. In stable conditions, a non-linear functionG_xy() = 1 + b_xy^c _xy (c_xy < 1) was found to benecessary to collapse cospectra in the inertial subrange. The empirical cospectralmodels of Kaimal et al. were modified to fit the somewhat more (neutraland unstable) or less (stable) sharply peaked scalar cospectra observed over forestsusing the appropriate cospectral constants and non-linear stability functions. Theempirical coefficients in the stability functions and in the cospectral models varywith measurement height and seasonal changes in VAI. The seasonal differencesare generally larger at the Morgan Monroe State Forest site (greater peak VAI) andcloser to the canopy.The characteristics of transfer functions of the closed-path infrared gas analysersthrough long-tubes for CO₂ and water vapour fluxes were studied empirically. This was done by fitting the ratio between normalized cospectra of CO₂ or watervapour fluxes and those of sensible heat to the transfer function of a first-order sensor.The characteristic time constant for CO₂ is much smaller than that for water vapour. The time constant for water vapour increases greatly with aging tubes. Three methods were used to estimate the flux attenuations and corrections; from June through August, the attenuations of CO₂ fluxes are about 3–4% during the daytime and 6–10% at night on average. For the daytime latent heat flux (Q_E), the attenuations are foundto vary from less than 10% for newer tubes to over 20% for aged tubes. Correctionsto Q_E led to increases in the ratio (Q_H + Q_E)/(Q^* - Q_G) by about 0.05 to0.19 (Q_H is sensible heat flux, Q^* is net radiation and Q_G is soil heat flux),and thus are expected to have an important impact on the assessment of energy balanceclosure.