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991.
It is well known that Landsat TM images are the most widely used remote sensing data in various fields. Usually, it has 7 different electromagnetic spectrum bands, among which the sixth one has much lower ground resolution compared with the other six bands. Nevertheless, it is useful in the study of rock spectrum reflection, geo-thermal resources exploration, etc. To improve the ground resolution of TM6 to the level as that of the other six bands is a problem. This paper presents an algorithm based on the combination of multi-variate regression model with semi-variogram function which can improve the ground resolution of TM6 by “fusing” the data of other six bands. It includes the following main steps: (1) testing the correlation between TM6 and one of TM1-5, 7. If the correlation coefficient between TM6 and another one is greater than a give threshold value, then select the band to the regression analysis as an argument. (2) calculating the size of the template window within which some parameters needed by the regression model will be calculated; (3) replacing the original pixel values of TM6 by those obtained by regression analysis; (4) using image entropy as a measurement to evaluate the quality of the fused image of TM6. The basic mechanism of the algorithm is discussed and the V C++ program for implemeting this algorithm is also presented. A simple application example is given in the last part of this paper, showing the effectiveness of the algorithm. 相似文献
992.
This paper presents a semiparametric adjustment method suitable for general cases. Assuming that the regularizer matrix is positive definite, the calculation method is discussed and the corresponding formulae are presented. Finally, a simulated adjustment problem is constructed to explain the method given in this paper. The results from the semiparametric model and G-M model are compared. The results demonstrate that the model errors or the systematic errors of the observations can be detected correctly with the semiparametric estimate method. 相似文献
993.
Abstract Information on the number and type of new building structures is required by urban and transportation planners and the real estate industry. The goal of this paper is to explore the potential of high resolution imagery for meeting public and private sector demands for information on new buildings. The value of 1 m, 5 m, and 10 m panchromatic and 1 m color scanned aerial photography images acquired in 1997 and 1998 for a study area within the City of San Diego, California is assessed for general change detection and building enumeration. Both semi‐automated and interactive change‐detection approaches are evaluated. We demonstrate that interactive, visual‐based approaches appear to be the most accurate (within 1% of actual count) and efficient approach for generating information on the number of new buildings associated with single family residential land use. More automated approaches to detecting and enumerating image microfeatures may be useful as enhancements for visual‐based assessments and may be practical in areas composed mostly of large buildings associated with commercial and industrial land use. The highest accuracy for automated approaches was an undercounting of 11% for residential buildings and overcounting of 20% for those associated with commercial and industrial land use. 相似文献
994.
Advanced Land Observing Satellite Phased Array L-band Synthetic Aperture Radar (ALOS PALSAR) data from different observation modes were analysed to determine (1) which observation mode most accurately retrieves tropical forest biomass information and (2) whether different modes, when considered together, yield improved results in comparison to identical data-sets analysed independently. We performed regression analysis to estimate above-ground forest biomass using PALSAR backscatter data for natural and planted forests in south-eastern Bangladesh. The coefficient of determination (r 2) was lower or equal to 0.499 (n = 70) when PALSAR data from different observation modes were separately considered, but increased sharply when one class (rubber) is dropped and average backscatter of fine beam single (FBS) and polrimetric (PLR) modes are used in the analysis. The results presented in this article are useful for both regional and global forest biomass inventories and fixing acquisition modes for planned L-band SAR missions. 相似文献
995.
《水文科学杂志》2013,58(4):567-584
Abstract Reliable, real-time river flow forecasting in Africa on a time scale of days can provide enormous humanitarian and economic benefits. This study investigates the feasibility of using daily rainfall estimates based on cold cloud duration (CCD) derived from Meteosat thermal infrared imagery as input to a simple rainfall—runoff model and also whether such estimates can be improved by the inclusion of information from numerical weather prediction (NWP) analysis models. The Bakoye catchment in Mali, West Africa has been used as a test area. The data available for the study covered the main months of the rainy season for three years. The rainfall estimates were initially validated against gauge data. Improvements in quality were observed when information relating to African Easterly Wave phase and storm type was included in a multiple linear regression (MR) algorithm. The estimates were also tested by using them as input to a rainfall—runoff model. When contemporaneous calibrations from raingauges were available for calibration, both CCD-only and MR rainfall estimates gave more accurate river flow forecasts than when using raingauge data alone. In the absence of contemporaneous calibrations, the performance was reduced but the MR did better than the CCDonly input in all years. The use of satellite-derived vegetation index did not improve the quality of the river flow forecasts. 相似文献
996.
ABSTRACTNowadays, mathematical models are widely used to predict climate processes, but little has been done to compare the models. In this study, multiple linear regression (MLR), multi-layer perceptron (MLP) network and adaptive neuro-fuzzy inference system (ANFIS) models were compared for precipitation forecasting. The large-scale climate signals were considered as inputs to the applied models. After selecting the most effective climate indices, the effects of large-scale climate signals on the seasonal standardized precipitation index (SPI) of the Maharlu-Bakhtaran catchment, Iran, simultaneously and with a delay, was analysed using a cross-correlation function. Hence, the SPI time series was forecasted up to four time intervals using MLR, MLP and ANFIS. The results showed that most of the indices were significant with SPI of different lag times. Comparison of the SPI forecast results by MLR, MLP and ANFIS models showed better performance for the MLP network than the other two models (RMSE = 0.86, MAE = 0.74 for the first step ahead of SPI forecasting).
Editor D. Koutsoyiannis; Associate editor F. Pappenberger 相似文献
997.
《水文科学杂志》2013,58(3):365-370
Abstract Gauging stations where the stage—discharge relationship is affected by hysteresis due to unsteady flow represent a challenge in hydrometry. In such situations, the standard hydrometric practice of fitting a single-valued rating curve to the available stage—discharge measurements is inappropriate. As a solution to this problem, this study provides a method based on the Jones formula and nonlinear regression, which requires no further data beyond the available stage—discharge measurements, given that either the stages before and after each measurement are known along with the duration of each measurement, or a stage hydrograph is available. The regression model based on the Jones formula rating curve is developed by applying the monoclinal rising wave approximation and the generalized friction law for uniform flow, along with simplifying assumptions about the hydraulic and geometric properties of the river channel in conjunction with the gauging station. Methods for obtaining the nonlinear least-squares rating-curve estimates, while factoring in approximated uncertainty, are discussed. The broad practical applicability and appropriateness of the method are demonstrated by applying the model to: (a) an accurate, comprehensive and detailed database from a hydropower-generated highly dynamic flow in the Chattahoochee River, Georgia, USA; and (b) data from gauging stations in two large rivers in the USA affected by hysteresis. It is also shown that the model is especially suitable for post-modelling hydraulic and statistical validation and assessment. 相似文献
998.
999.
《The Professional geographer》2013,65(3):368-378
Economic base analysis is a cost-effective and accurate means of predicting employment impacts in relatively small and uncomplicated regional (community) economies. Extending previous research using the Arizona Community Data Set, this paper estimates economic base multipliers in different types of communities by introducing dummy variables into regression equations. Total employment, transfer payments, and population potential are used as explanatory variables. Manufacturing centers are shown to have larger multipliers than diversified places, mining settlements, service and trade communities, and utility towns. 相似文献
1000.
Over the past few decades, land use and land cover change has become a global concern. In the Lop Buri province of Thailand, rapid land cover change, specifically conversion of forests to agriculture, has occurred. The purpose of the study is to identify the predictors of land cover change in Lop Buri province for land that has been converted to upland crops or has undergone deforestation between 1989 and 2006. Four logistic regression models were constructed using spatially explicit biophysical and geo‐social data, to account for changes to upland crops and forest loss from1989–98 and 1998–2006. Across the four models, slope, distance to forest edge, distance to towns, distance to roads, population size, and population density in various stand‐alone and interactive forms were found to be the most consistent predictors of land cover change. 相似文献