Regionalization for large area crop estimates by remote sensing

The crop estimates by remote sensing, developing quickly in recent decades, is a up-to-date technique. Regionalization for large area crop estimates by remote sensing, a special applied regionalization, is the foundation of crop estimates in a large area by remote sensing. According to the actual demands of wheat yield estimation by remote sensing and wheat agroclimatic demarcation of China, this paper first puts forward some principles upheld in this regionalization and analyses its main bases. Secondly, it works out the classificatory schemes about the optimum temporal for estimating wheat yield by remote sensing, information sources of space remote sensing and landuse structure in China. Finally, According to the regionalization indices, this study divides the wheat plantable region of China into 14 regions of crop yield estimates and 31 subregions of crop yield estimates.     

Correcting systematic effects in a large set of photometric light curves

We suggest a new algorithm to remove systematic effects in a large set of light curves obtained by a photometric survey. The algorithm can remove systematic effects, such as those associated with atmospheric extinction, detector efficiency, or point spread function changes over the detector. The algorithm works without any prior knowledge of the effects, as long as they linearly appear in many stars of the sample. The approach, which was originally developed to remove atmospheric extinction effects, is based on a lower rank approximation of matrices, an approach which has already been suggested and used in chemometrics, for example. The proposed algorithm is especially useful in cases where the uncertainties of the measurements are unequal. For equal uncertainties, the algorithm reduces to the Principal Component Analysis (PCA) algorithm. We present a simulation to demonstrate the effectiveness of the proposed algorithm and we point out its potential, in the search for transit candidates in particular.     

Use of multi‐platform,multi‐temporal remote‐sensing data for calibration of a distributed hydrological model: an application in the Arno basin,Italy

Images from satellite platforms are a valid aid in order to obtain distributed information about hydrological surface states and parameters needed in calibration and validation of the water balance and flood forecasting. Remotely sensed data are easily available on large areas and with a frequency compatible with land cover changes. In this paper, remotely sensed images from different types of sensor have been utilized as a support to the calibration of the distributed hydrological model MOBIDIC, currently used in the experimental system of flood forecasting of the Arno River Basin Authority. Six radar images from ERS‐2 synthetic aperture radar (SAR) sensors (three for summer 2002 and three for spring–summer 2003) have been utilized and a relationship between soil saturation indexes and backscatter coefficient from SAR images has been investigated. Analysis has been performed only on pixels with meagre or no vegetation cover, in order to legitimize the assumption that water content of the soil is the main variable that influences the backscatter coefficient. Such pixels have been obtained by considering vegetation indexes (NDVI) and land cover maps produced by optical sensors (Landsat‐ETM). In order to calibrate the soil moisture model based on information provided by SAR images, an optimization algorithm has been utilized to minimize the regression error between saturation indexes from model and SAR data and error between measured and modelled discharge flows. Utilizing this procedure, model parameters that rule soil moisture fluxes have been calibrated, obtaining not only a good match with remotely sensed data, but also an enhancement of model performance in flow prediction with respect to a previous calibration with river discharge data only. Copyright © 2006 John Wiley & Sons, Ltd.     

REMOTE SENSING FOREST BIOMASS: AN EVALUATION USING HIGH RESOLUTION REMOTE SENSOR DATA AND LOBLOLLY PINE PLOTS

Eight-year-old Loblolly pine (Pinus taeda) plots located in South Carolina were evaluated using high resolution aircraft multispectral scanner data to determine if biomass could be accurately measured. Sixteen pine plots located on both sandy and clay soils were treated with 0, 180, or 360 kg. (approximately 0, 400, or 800 lb.) of nitrogen per plot. Indices of biomass from remote sensing data were significantly correlated with in situ biomass measurements made in each plot. A ratio of infrared (.9–1.1 μm) and red (.65–.70 μm) channels yielded the best correlation. The indices were not sensitive to differences in soil type (sandy or clay).     

Distance estimate and progenitor characteristics of SN 2005cs in M51

We present the excitation energies and lifetimes for the  3 s 3 p 3 d  ⁴ F  _7/2,9/2  levels for five aluminium-like ions of the iron group. Apart from the wavelengths, this also includes the transition probabilities and branching ratios for the electric-dipole allowed (E1) and forbidden (M1, E2, M2) lines into the energetically lower lying levels of the  3 s ²3 d , 3 s 3 p ²  and  3 s 3 p 3 d   configurations. Applying systematically enlarged multiconfiguration Dirac–Fock (MCDF) wavefunctions, here the effects of relativity and the electron–electron correlation are treated within the same (computational) model.     

A Faraday rotation template for the Galactic sky

Using a set of compilations of measurements for extragalactic radio sources, we construct all-sky maps of the Faraday rotation produced by the Galactic magnetic field. In order to generate the maps, we treat the radio source positions as a kind of 'mask' and construct combinations of spherical harmonic modes that are orthogonal on the masked sky. As long as relatively small multipoles are used, the resulting maps are quite stable to changes in the selection criteria for the sources, and show clearly the structure of the local Galactic magnetic field. We also suggest the use of these maps as templates for cosmic microwave background (CMB) foreground analysis, illustrating the idea with a cross-correlation analysis between the Wilkinson Microwave Anisotropy Probe ( WMAP ) data and our maps. We find a significant cross-correlation, indicating the presence of a significant residual contamination.