This study presents a new climatology of monthly temperature for mainland Spain (1951–2010), performed with the highest quality and spatially dense, up-to-date monthly temperature dataset available in the study area (MOTEDAS).
Three different interpolation techniques were evaluated: the Local Weighted Linear Regression (LWLR), the Regression-Kriging (RK) and the Regression-Kriging with stepwise selection (RKS), a modification of RK. The performances of the different models were evaluated by the leave-one-out validation procedure, comparing the results from the models with the original data and calculating different error measurements.
The three techniques performed better for Tmax than for Tmin, and for the cold, rather than warmer months, also at lower altitude than highland areas. The best results were achieved with LWLR applied for the first time on temperatures in the Spanish mainland. This method improved the accuracy of the temperature reconstruction with respect to RK and RKS.
We present a collection of Tmax and Tmin monthly charts, using the same temperature legend to prevent any visual bias in the interpretation of the results. The dataset is available upon request. 相似文献
The main objective of the study was to evaluate and compare the overall performance of three methods, frequency ratio (FR), certainty factor (CF) and index of entropy (IOE), for rainfall-induced landslide susceptibility mapping at the Chongren area (China) using geographic information system and remote sensing. First, a landslide inventory map for the study area was constructed from field surveys and interpretations of aerial photographs. Second, 15 landslide-related factors such as elevation, slope, aspect, plan curvature, profile curvature, stream power index, sediment transport index, topographic wetness index, distance to faults, distance to rivers, distance to roads, landuse, NDVI, lithology and rainfall were prepared for the landslide susceptibility modelling. Using these data, three landslide susceptibility models were constructed using FR, CF and IOE. Finally, these models were validated and compared using known landslide locations and the receiver operating characteristics curve. The result shows that all the models perform well on both the training and validation data. The area under the curve showed that the goodness-of-fit with the training data is 79.12, 80.34 and 80.42% for FR, CF and IOE whereas the prediction power is 80.14, 81.58 and 81.73%, for FR, CF and IOE, respectively. The result of this study may be useful for local government management and land use planning. 相似文献
The article is composed of two sections. In the first section, the authors describe the application of minimum line dimensions which are dependent on line shape, width and the operational scale of the map. The proposed solutions are based on the Euclidean metric space, for which the minimum dimensions of Saliszczew’s elementary triangle (Elementary triangle – is the term pertaining to model, standard triangle of least dimensions securing recognizability of a line. Its dimensions depend on scale of the map and width of the line representing it. The use of a triangle in the simplification process is as follows: triangles with sides (sections) on an arbitrary line and bases (completing the sides) are compared with lengths of the shorter side and the base of the elementary triangle.) were adapted. The second part of the article describes an application of minimum line dimensions for verifying and assessing generalized data. The authors also propose a method for determining drawing line resolution to evaluate the accuracy of algorithm simplification. Taking advantage of the proposed method, well-known simplification algorithms were compared on the basis of qualitative and quantitative evaluation. Moreover, corresponding with the methods of simplified data accuracy assessment the authors have extended these solutions with the rejected data. This procedure has allowed the identification of map areas where graphic conflicts occurred. 相似文献