居民收入与通信网络市场经济效益研究--以河北省通信网络为实例

利用Logisitic曲线模型和扩展支撑模型对居民可支配收入预测和单项消费预测，以河北省居民的收入及其消费支出为实例，研究了城镇居民和农民的可支配收入分配和单项边际消费倾向，合理建立了预测模型，并理论计算了1999～2003年的通信消费方面的边际消费倾向、预测了2004～2008年通信消费情况。最后，根据预测结果对通信网络建设提出了一些有价值的建议。     

Doline probability map using logistic regression and GIS technology in the central Ebro Basin (Spain)

In the surroundings of Zaragoza, karstification processes are especially intense in covered karst areas where fluvial terraces lie directly on Tertiary evaporites. Since the beginning of Quaternary, these processes have lead to the development of collapse and subsidence dolines with a wide range of sizes, which have significant economic impacts. To reduce economic impact and increase safety, a regional analysis of this phenomenon is needed for spatial management. Therefore, a probability map of dolines was developed using logistic regression and geographic information system (GIS) techniques. This paper covers the selection of input data, manipulation of data using the GIS technology, and the use of logistic regression to generate a doline probability map. The primary variable in the doline development in this area is geomorphology, represented by the location of endorheic areas and different terrace levels. Secondary variables are the presence of irrigation and the water table gradient.     

Assessment of disaster resilience capacity of hillslope communities with high risk for geological hazards

This study presents a novel preparedness assessment method for assessing hazard mitigation and environmental planning of hillslope communities. A professional questionnaire was utilized to weight each indicator. Communities in Hsinchu, Taichung and Nantou counties with debris flow hazards were taken as study samples. Debris flow risk and landslide susceptibility for each community were determined using Geographic Information System (GIS) technology and logistic regression analysis. Thus, a novel risk assessment method for evaluating disaster resilience capacity of hillslope communities was established. This method was then applied to assess casualties caused by Typhoon Herb in 1996 and Typhoon Mindulle in 2004. Additionally, the analytical results generated by this assessment method were discussed with the aim of developing references for implementation of risk analysis, increasing the effectiveness of disaster mitigation, and reducing future loss of life and property.     

Rain-induced debris and mudflow triggering factors assessment in the Santiago cordilleran foothills,Central Chile

Debris and mudflows are some of the main geological hazards in the mountain foothills of the Chilean capital city of Santiago. There, the risk of flows triggered in the basins of ravines that drain the range into the city increases with time due to the city growth. A multivariate statistical study based on the logistic regression method is presented. The model provides equations that allow the computation of combined meteorological triggering factors associated with a probability of rain-induced flow occurrence. Daily rainfall, accumulated rainfall and the snowfall level, traditionally considered as the relevant factors, are analysed for a 25-year period. The results show a strong relevance of the rainfall on the day of the flow event over the other factors. However, the relatively low probabilities returned for some real flow events suggest that the model does not capture all the significant variables and the problem is more complex than as it has been traditionally assumed, and further investigations are needed to develop predictive models of flow triggering.     

A Reconnaissance Method for Delineation of Tracts for Regional-Scale Mineral-Resource Assessment Based on Geologic-Map Data

The U.S. Geological Survey (USGS) is proposing to conduct a global mineral-resource assessment using geologic maps, significant deposits, and exploration history as minimal data requirements. Using a geologic map and locations of significant pluton-related deposits, the pluton-related-deposit tract maps from the USGS national mineral-resource assessment have been reproduced with GIS-based analysis and modeling techniques. Agreement, kappa, and Jaccard's C correlation statistics between the expert USGS and calculated tract maps of 87%, 40%, and 28%, respectively, have been achieved using a combination of weights-of-evidence and weighted logistic regression methods. Between the experts' and calculated maps, the ranking of states measured by total permissive area correlates at 84%. The disagreement between the experts and calculated results can be explained primarily by tracts defined by geophysical evidence not considered in the calculations, generalization of tracts by the experts, differences in map scales, and the experts' inclusion of large tracts that are arguably not permissive. This analysis shows that tracts for regional mineral-resource assessment approximating those delineated by USGS experts can be calculated using weights of evidence and weighted logistic regression, a geologic map, and the location of significant deposits. Weights of evidence and weighted logistic regression applied to a global geologic map could provide quickly a useful reconnaissance definition of tracts for mineral assessment that is tied to the data and is reproducible.     

A GIS Analysis to Evaluate Areas Suitable for Crushed Stone Aggregate Quarries in New England,USA

Aggregate is a low unit-value mineral commodity. Costs to move aggregate from the mine site to the point of use is a large fraction of the resource cost to users. Production sites for aggregate occur where suitable source materials exist and where transportation and market conditions are favorable. The increasing demand for aggregate and the difficulty of developing and permitting new sites and of renewal of permits on existing sites of aggregate production indicates that aggregate will be supplied from sources yet to be developed or delineated in many areas. Site development and permitting for aggregate production is difficult because many land management plans and zoning actions fail to anticipate prospective source areas for aggregate in a way that is consistent with both the source rock quality and the transportation and socioeconomic factors that define the economic viability of the industry. Spatial analysis provides a method to integrate both geology and economic (transportation and marketplace) parameters in a regional model. Weights of evidence (WofE) analysis has been used to measure the spatial correlation of geologic map, transportation network, and population data with current production sites for crushed stone aggregate in the New England region of the northeastern United States. Weighted logistic regression (WLR) is used with the WofE results to rank areas in terms of their relative suitability for production of crushed stone. Spatial analysis indicates that 85% of the 106 crushed stone aggregate quarries in New England are sited within 1.6 km (1 mile) of either a principal highway or rail line in the region. Seventy-eight percent of crushed stone aggregate quarries are sited in census tracts with population densities exceeding 100 people/mile². These relations illustrate the importance of proximity to both transportation corridors and developing areas where aggregate is predominately used. Only one active crushed stone quarry is located in a census tract with a population density less than 15 people/mile², reflecting the lack of sufficient market demand in many rural areas to develop an operation there. However, since 1990, almost all new quarries have been developed in census tracts with population densities less than 200 people/mile², indicating the difficulty of permitting new quarry sites in highly populated areas. Crushed stone aggregate is produced predominately from three hard rock types that are distributed widely in New England; 28% of sites use granitic rock, 25% use carbonate rocks, and 25% use mafic rock types that are categorized as trap rock by the aggregate industry. The other crushed stone aggregate sources include a variety of fine-grained metamorphic rock types. Carbonate rocks and Jurassic basalt (the primary trap rock source) are the most prevalent source rocks on an area-weighted basis. Spatial analysis can be used on a regional scale to rank areas by their relative suitabilityfor crushed stone aggregate production based on geology, transportation, and population parameters. The results of this regional analysis can identify areas for more detailed evaluation. As transportation or population features change, the model can be revised easily to reflect these changes.     

历史遗址类旅游地的生命周期研究——以美国14家历史遗址公园为例

实证研究中旅游地生命周期理论的运用潜力备受质疑。论文选取美国14家国家历史遗址公园为例,采用旅游研究中较少使用的四参数Logistic模型结合一次函数、二次函数、三次函数、高斯多峰分析法拟合旅游地的生命周期。研究发现：四参数Logistic模型结合一次函数、二次函数、三次函数能较好地拟合旅游地的生命周期;利用四参数Logistic曲线的上弯点、拐点、下弯点能定量的划分出旅游地的起步探索、发展、巩固、停滞阶段,一次函数、二次函数、三次函数能拟合旅游地的衰退或复兴阶段,这回答了学者们对生命周期阶段难以定量划分的质疑。根据旅游地停滞期之后的发展趋势还能归纳出该类旅游地的生命周期类型;高斯多峰分析法将旅游地的生命周期拟合成一个个波动的高斯峰,更大程度上保留了旅游地演进的波动特征;将高斯多峰分析法与四参数Logistic模型结合起来,不仅能定量划分旅游地的生命周期阶段,还能准确地描述在生命周期阶段内的波动情况,甚至分析各生命周期阶段对整个生命周期的影响和作用。     

2010年北京市流动人口预测

针对北京市流动人口样本数据量小、不连续等特点,本文采用Logistic曲线拟合和等维递补灰色预测理论,预测“十一五”期间北京流动人口的增长情况。首先,通过Logistic曲线拟合与外推,掌握流动人口增长的总趋势;其次,选定不同长度的人口序列以建立多个等维递补灰色模型,检验并分析各种预测结果的合理性与不足;最终确定北京市流动人口增长预测的高、中、低方案。实践表明,灰色等维递补预测法对“小样本”、“贫信息”的人口预测是切实可行的。     

Estimating the starting time and identifying the type of urbanization based on dense time series of landsat-derived Vegetation-Impervious-Soil (V-I-S) maps – A case study of North Taiwan from 1990 to 2015

Land cover and land use change (LCLUC) is a global phenomenon, and LCLUC in urbanizing regions has substantial impacts on humans and their environments. In this paper, a semi-automatic approach to identifying the type and starting time of urbanization was developed and tested based on dense time series of Vegetation-Impervious-Soil (V-I-S) maps derived from Landsat surface reflectance imagery. The accuracy of modeled V-I-S fractions and the estimated time of initial change in impervious cover were assessed. North Taiwan, one of the regions of the island of Taiwan that experienced the greatest urban LCLUC, was chosen as a test area, and the study period is 1990 to 2015, a period of substantial urbanization. In total, 295 dates of Landsat imagery were used to create 295 V-I-S fraction maps that were used to construct fractional cover time series for each pixel. Root Mean Square Error (RMSE)s for the modeled Vegetation, Impervious, and Soil were 25 %, 22 %, 24 % respectively. The time of Urban Expansion is estimated by logistic regression applied to Impervious cover time series, while the time of change for Urban Renewal is determined by the period of brief Soil exposure. The identified location and estimated time for newly urbanized lands were generally accurate, with 80% of Urban Expansion estimated within ±2.4 years. However, the accuracy of identified Urban Renewal was relatively low. Our approach to identifying Urban Expansion with dense time series of Landsat imagery is shown to be reliable, while Urban Renewal identification is not.     

Integration of remote sensing,county-level census,and machine learning for century-long regional cropland distribution data reconstruction

The Lower Mississippi Alluvial Valley (LMAV) was home to about ten million hectare bottomland hardwood (BLH) forests in the Southern U.S. It experienced over 80 % area loss of the BLH forests in the past centuries and large-scale afforestation in recent decades. Due to the lack of a high-resolution cropland dataset, impacts of land use change (LUC) on the LMAV ecosystem services have not been fully understood. In this study, we developed a novel framework by integrating the machine learning algorithm, county-level agricultural census, and satellite-based cropland products to reconstruct the LMAV cropland distribution during 1850–2018 at a 30-m resolution. Results showed that the LMAV cropland area increased from 0.78 × 10⁴ km² in 1850 to 6.64 × 10⁴ km² in 1980 and then decreased to 6.16 × 10⁴ km² in 2018. Cropland expansion rate was the largest in the 1960s (749 km² yr⁻¹) but decreased rapidly thereafter, whereas cropland abandonment rate increased substantially in recent decades with the largest rate of 514 km² yr⁻¹ in the 2010s. Our dataset has three notable features: (1) the depiction of fine spatial details, (2) the integration of the county-level census, and (3) the inclusion of a machine-learning algorithm trained by satellite-based land cover product. Most importantly, our dataset well captured the continuous increasing trend in cropland area from 1930–1960, which was misrepresented by other cropland datasets reconstructed from the state-level census. Our dataset would be important to accurately evaluate the impacts of historical deforestation and recent afforestation efforts on regional ecosystem services, attribute the observed hydrological changes to anthropogenic and natural driving factors, and investigate how the socioeconomic factors control regional LUC pattern. Our framework and dataset are crucial to developing managerial and policy strategies for conserving natural resources and enhancing ecosystem services in the LMAV.