旅游口号设计的核心模式与尺度差异——基于对我国1133条优秀旅游目的地口号的内容分析

基于旅游口号的多特征和多学科原理互动的视角构建我国旅游口号设计的整合分析框架。以此框架为工具,采用内容分析法,从1133条旅游口号中提炼其核心设计模式和地域尺度差异性,并从"说什么"和"怎么说"的综合角度提出我国旅游口号系统化提升要求。

国土空间规划体系下县级规划的编制研究

建立国土空间规划体系是我国迈入生态文明新时代的一项重大变革,分级分类建立国土空间规划符合我国行政管理和城市发展的特征。当前,省级国土空间规划已全部公示,市级国土空间总体规划也在陆续公示,而县级国土空间规划正处在编制的探索阶段。本文首先概括了我国建立国土空间规划体系的背景与意义;其次,简要分析了县级国土空间总体规划在整个国土空间规划体系中的地位与作用;最后,以不同地域尺度的县级国土空间规划编制实践为例,提出在“基础评价、主要内容、统筹专项规划、编制机制”等方面尝试编制研究。

On the criteria to create a susceptibility map to debris flow at a regional scale using Flow-R

Studies on susceptibility to debris flows at regional scale （ioo-looo km2） are important for the protection and management of mountain areas. To reach this objective, routing models, mainly based on land topography, can be used to predict susceptible areas rapidly while necessitating few input data. In this research, Flow-R model is implemented to create the susceptibility map for the debris flow of the Vizze Valley （BZ, North-Eastern Italy; 134 km^2）. The analysis considers the model application at local scale for three sub-catchments and then it explores the model upsealing at the regional scale by verifying two methods to generate the source areas of debris-flow initiation. Using data of an extreme event occurred in the Vizze Valley （4 August 2012） and historical information, the modeling verification highlights that the propagation parameters are relatively simple to set in order to obtain correct runout distances. A double DTM filtering - using a threshold for the upslope contributing area （0.1 km^2） and a threshold for the terrain-slope angle （15°） provides a satisfactory prediction of source areas and susceptibility map within the geological conditions of the Vizze Valley.

Regional Scale Rainfall- and Earthquake-triggered Landslide Susceptibility Assessment in Wudu County, China

Wudu County in northwestern China frequently experiences large-scale landslide events. High-magnitude earthquakes and heavy rainfall events are the major triggering factors in the region. The aim of this research is to compare and combine landslide suseeptibility assessments of rainfall- triggered and earthquake-triggered landslide events in the study area using Geographical Information System （GIS） and a logistic regression model. Two separate susceptibility maps were produeed using inventories reflecting single landslide-triggering events, i.e., earthquakes and heavy rain storms. Two groups of landslides were utilized： one group eontaining all landslides triggered by extreme rainfall events between 1995 and 2003 and the other group containing slope failures caused by the 2008 Wenchuan earthquake. Subsequently, the individual maps were combined to illustrate the loeations of maximum landslide probability. The use of the resulting three landslide susceptibility maps for landslide forecasting, spatial planning and for developing emergency response actions are discussed. The eombined susceptibility map illustrates the total landslide susceptibility in the study area.

A multiscale spatio-temporal framework to regionalize annual precipitation using k-means and self-organizing map technique

Determination of homogenous precipitation-based regions is a very important task in effective management of water resources. The present study tried to propose an effective precipitation-based regionalization methodology by conjugating both temporal pre-processing and spatial clustering approaches in a way to take advantage of multiscale properties of precipitation time series. Annual precipitation data of 51 years(1960-2010) for 31 rain gauges(RGs) were collected and used in proposed clustering approaches. Discreet wavelet transform(DWT) was used to capture the time-frequency attributes of the time series and multiscale regionalization was performed by using k-means and Self Organizing Maps(SOM) clustering techniques. Daubechies function(db) was selected as mother wavelet to decompose the precipitation time series. Also, proper boundary extensions and decomposition level were applied. Different combinations of the approximation(A) and detail(D) coefficients were used to determine the input dataset as a basis of spatial clustering. The proposed model's efficiency in spatial clustering stage was verified using three different indexes namely, Silhouette Coefficient(SC), Dunn index and Davis Bouldin index(DB). Results approved superior performance of k-means technique in comparison to SOM. It was also deduced that DWT-based regionalization methodology showed improvements in comparison to historical-based models. Cross mutual information was used to investigate the RGs of cluster 3's homogeneousness in DWT-k-means approach. Results of non-linear correlation approach verified homogeneity of cluster 3. Verifications based on mean annual precipitation values of rain gauges in each cluster also approved the capability of multiscale approach in precipitation regionalization.

Combining CLUE-S and SWAT Models to Forecast Land Use Change and Non-point Source Pollution Impact at a Watershed Scale in Liaoning Province, China

Non-point source(NPS) pollution has become a major source of water pollution. A combination of models would provide the necessary direction and approaches designed to control NPS pollution through land use planning. In this study, NPS pollution load was simulated in urban planning, historic trends and ecological protection land use scenarios based on the Conversion of Land Use and its Effect at Small regional extent(CLUE-S) and Soil and Water Assessment Tool(SWAT) models applied to Hunhe-Taizi River Watershed, Liaoning Province, China. Total nitrogen(TN) and total phosphorus(TP) were chosen as NPS pollution indices. The results of models validation showed that CLUE-S and SWAT models were suitable in the study area. NPS pollution mainly came from dry farmland, paddy, rural and urban areas. The spatial distribution of TN and TP exhibited the same trend in 57 sub-catchments. The TN and TP had the highest NPS pollution load in the western and central plains, which concentrated the urban area and farm land. The NPS pollution load would increase in the urban planning and historic trends scenarios, and would be even higher in the urban planning scenario. However, the NPS pollution load decreased in the ecological protection scenario. The differences observed in the three scenarios indicated that land use had a degree of impact on NPS pollution, which showed that scientific and ecologically sound construction could effectively reduce the NPS pollution load in a watershed. This study provides a scientific method for conducting NPS pollution research at the watershed scale, a scientific basis for non-point source pollution control, and a reference for related policy making.

A Metapopulation Model with Patches Distributed in Two Geographical Scales

We propose a metapopulation model with two geographical scales. In a regional scale, the model describes the dynamics of a collection of habitats connected by migratory movements. In a local scale, we consider some granularity within each habitat, in the sense that each habitat is itself a collection of patches linked by dispersal. The whole ensemble can be seen as a metapopulation composed by local metapopulations. We analyze the synchronization of the model in the two geographical scales. We present an analytic criterion for synchronization where only the habitats in the regional scale evolve with the same dynamics. Through numerical simulations, we discuss the different synchronization modes. It depends on how the individuals are distributed in the local patches that compose a habitat after migration takes place in the regional scale.

Non-Algorithmically Integrating Land Use Type with Spatial Interpolation of Surface Soil Nutrients in an Urbanizing Watershed

Integrating land use type and other geographic information within spatial interpolation has been proposed as a solution to improve the performance and accuracy of soil nutrient mapping at the regional scale. This study developed a non-algorithm approach, i.e., applying inverse distance weighting （IDW） and ordinary kriging （OK）, to individual land use types rather than to the whole watershed, to determine if this improved the performance in mapping soil total C （TC）, total N （TN）, and total P （TP） in a 200-km2 urbanizing watershed in Southeast China. Four land use types were identified by visual interpretation as forest land, agricultural land, green land, and urban land. One hundred and fifty soil samples （0-10 cm） were taken according to land use type and patch size. Results showed that the non-algorithm approach, interpolation based on individual land use types, substantially improved the performance of IDW and OK for mapping TC, TN, and TP in the watershed. Root mean square errors were reduced by 3.9% for TC, 10.770 for TN, and 25.9% for TP by the application of IDW, while the improvements by OK were slightly lower as 0.9% for TC, 7.7% for TN, and 18.1% for TP. Interpolations based on individual land use types visually improved depiction of spatial patterns for TC, TN, and TP in the watershed relative to interpolations by the whole watershed. Substantial improvements might be expected with denser sampling points. We suggest that this non-algorithm approach might provide an alternative to algorithm-based approaches to depict watershed-scale nutrient patterns.