南海海上搜救困难性评价

为保障船舶海上航行安全,结合GIS与模糊层次分析法,从海上搜救的自然环境和人文搜救力量2个方面选取9个因子建立海上搜救困难性评价模型,对南海海上搜救困难性进行评价。结果表明：1）自然环境影响下,南海海域搜救困难性具有“V”字形分布的特点,由东北向西南难度等级逐渐降低。2）在人文搜救力量影响下,南海海域的搜救困难性整体呈“东北－西南条带式”,难度最大的区域主要位于南海东北―西南的连线上,呈不规则环状向连线两侧递减。3）综合两方面因素,南海部分岛屿周围搜救难度偏高,主要受台风等恶劣天气及远离搜救基地的影响,而远海海域搜救难度在整体上为“东北－西南递减式”空间分布格局,最高和较高的区域由研究区东北延伸至西南,然后向西北、东南两侧递减。总体而言,南海研究区中近21.1%的海域搜救难度≥7级,仍需加强对搜救力量的部署与建设。     

Assessment of recharge capacity potential of groundwater using comparative multi-criteria decision analysis approaches

Journal of Geographical Sciences - Groundwater resources have always been some of the most valuable resources of human settlements. Climate changes and ever-increasing water demands registered in...     

岷江上游流域环境脆弱性评价

以岷江上游流域TM遥感数据和地形数据为主要数据源,结合其他统计相关资料,尝试运用层次分析法(analytic hierarchy process,AHP)对复杂因素构成的脆弱性特征进行层次分解和重新构造,建立多目标要素的综合评价指标体系和模型。选取植被指数变化率、人口密度、地形起伏度、坡度及土壤类型5个要素作为评价指标因子,通过AHP确定各评价指标的权重,在Arc GIS平台下将各指标图层进行叠加分析,得出岷江上游区域环境脆弱性评价图,再根据环境脆弱性指数阈值分级,将研究区环境脆弱度分为5级。结果表明:岷江上游环境脆弱性表现较为强烈,自然因素和人文因素是造成该环境脆弱性的本质原因,该方法为岷江上游流域环境脆弱性模式和生态环境综合评价提供了一种定量分析的思路。     

湖相泥页岩基质储层直井压裂选层方法研究——以松辽盆地三肇凹陷松页油3井为例

湖相泥页岩基质储层是中国页岩油赋存的主要载体,相对于夹层型和裂缝型储层更难被压裂改造和实现工业开发,因而压裂层位的选择至关重要. 本文以松辽盆地三肇凹陷松页油3井为例,建立了一套湖相泥页岩基质储层直井压裂选层方法. 通过录井、测井解释优选出青山口组一段中的I类页岩油层,对I类页岩油层的电性、物性、含油气性、烃源岩性、脆性、可压性6项指标进行综合分析,基于上述6项指标,利用层次分析法对所有I类页岩油层进行综合排序,确定了27、25和23号层为最有利页岩油层. 松页油3井针对上述页岩油层进行了压裂试油,实现了三肇凹陷页岩油工业油流突破,证实选层方法可行有效,可推广应用于湖相基质型页岩油的甜点层优选和水平井部署.     

Holistic approach of GIS based Multi-Criteria Decision Analysis (MCDA) and WetSpass models to evaluate groundwater potential in Gelana watershed of Ethiopia

Appropriate quantification and identification of the groundwater distribution in a hydrological basin may provide necessary information for effective management, planning and development of groundwater resources. Groundwater potential assessment and delineation in a highly heterogeneous environment with limited Spatiotemporal data derived from Gelana watershed of Abaya Chamo lake basin is performed, using integrated multi-criteria decision analysis (MCDA), water and energy transfer between soil and plant and atmosphere under quasi-steady state (WetSpass) models. The outputs of the WetSpass model reveal a favorable structure of water balance in the basin studied, mainly using surface runoff. The simulated total flow and groundwater recharge are validated using river measurements and estimated baseflow at two gauging stations located in the study area, which yields a good agreement. The WetSpass model effectively integrates a water balance assessment in a geographical information system (GIS) environment. The WetSpass model is shown to be computationally reputable for such a remote complex setting as the African rift, with a correlation coefficient of 0.99 and 0.99 for total flow and baseflow at a significant level of p-value<0.05, respectively. The simulated annual water budget reveals that 77.22% of annual precipitation loses through evapotranspiration, of which 16.54% is lost via surface runoff while 6.24% is recharged to the groundwater. The calibrated groundwater recharge from the WetSpass model is then considered when determining the controlling factors of groundwater occurrence and formation, together with other multi-thematic layers such as lithology, geomorphology, lineament density and drainage density. The selected five thematic layers through MCDA are incorporated by employing the analytical hierarchy process (AHP) method to identify the relative dominance in groundwater potential zoning. The weighted factors in the AHP are procedurally aggregated, based on weighted linear combinations to provide the groundwater potential index. Based on the potential indexes, the area then is demarcated into low, moderate, and high groundwater potential zones (GWPZ). The identified GWPZs are finally examined using the existing groundwater inventory data (static water level and springs) in the region. About 70.7% of groundwater inventory points are coinciding with the delineated GWPZs. The weighting comparison shows that lithology, geomorphology, and groundwater recharge appear to be the dominant factors influence on the resources potential. The assessment of groundwater potential index values identify 45.88% as high, 39.38% moderate, and 14.73% as low groundwater potential zones. WetSpass model analysis is more preferable in the area like Gelana watershed when the topography is rugged, inaccessible and having limited gauging stations.     

GRA——FAHP模型的煤层底板突水危险性评价

矿井水害一直是制约我国煤炭安全生产的重要隐患之一,对其进行准确的预测评价具有十分重要的理论意义和实用价值。本文根据煤层底板突水各影响因素之间的关系是灰色关系并且具有非线性特征的特点,建立了定量与定性指标为一体的煤层底板突水评价指标体系及等级划分标准。同时将灰色关联分析法(GRA)和模糊层次分析法(FAHP)相结合。构建了能真实反映影响因素与底板突水之间灰色关系和非线性关系的底板突水危险性评价模型,并应用模型对某典型工作面突水危险性等级进行了评价,可为今后煤层底板突水预测评价的研究提供一定的借鉴和依据。     

从城市兴趣点中提取多层次地标方法探究

为了获取结构化空间知识,本文在前人研究基础上,提出一种依据显著度差异从城市POI数据中提取多层次地标的方法。分别从知名度、通达度以及个体特征三个方面量化分析了影响POI显著性的因素;然后利用这三个指标构建了POI显著性度量模型,并进行了武汉市武昌区地标提取实验。最后,以各层地标为种子生成Voronoi图,用来反映各层地标的空间影响范围及上下层地标之间蕴含的认知规律。     

Administrative hierarchy and urban land expansion in transitional China

In a growing body of literature on urbanization in China, scholars have emphasized the proactive role of the Chinese local state in urban land expansion. Drawing upon official land use change data from 1998 to 2008, this study investigates the relationship between the hierarchical structure of the Chinese urban administrative system and urban land expansion. We find that urban land expansion coincides with administrative hierarchy, and cities with higher administrative levels (ranked by central government) tend to expand more rapidly while controlling for other economic and demographic drivers of urban expansion. Spatial regime models reveal that economic and demographic drivers of urban growth are also sensitive to a city's administrative rank. By quantifying the link between a city's rank and urban land expansion, we conclude that considering the hierarchical structure of the Chinese cities will result in a fuller understanding of the rapid urban growth in China.     

中国典型旅游城市人居环境适宜度空间分异研究

运用模糊层次分析法,在中国101个拥有5个3A及以上旅游景区的城市中选取30个城市为研究对象。通过建立人居环境适宜度指标体系,运用熵值法计算得出30个典型旅游城市经济环境适宜度、生态环境适宜度、气候环境适宜度、服务环境适宜度和人居环境适宜度综合得分,并对典型旅游城市的人居环境适宜度进行排序和分析。结果显示:北京和上海在人居环境适宜度得分排名前两位且优势明显;长三角地区城市(苏州、杭州、南京等)人居环境适宜度综合排名与典型旅游城市综合排名差距不大且大部分排名前15,是城市人居环境与旅游资源协调发展的典范;沿海城市(大连、青岛、厦门等)和传统旅游城市(桂林、昆明、黄山)由于旅游季节单一等原因造成城市旅游综合指数得分的排名不高,但人居环境适宜度得分较高,优势主要体现在气候环境适宜度、生态环境适宜度和服务环境适宜度;以人文景观为主的旅游城市(西安、洛阳等)人居环境适宜度排名普遍不高;重庆、广州在典型旅游城市中排名靠前,但城市人居环境适宜度得分较低,此类城市在做好旅游发展的同时应注重城市生态、服务等方面的发展。     

Object-based class modelling for multi-scale riparian forest habitat mapping

Object-based class modelling allows for mapping complex, hierarchical habitat systems. The riparian zone, including forests, represents such a complex ecosystem. Forests within riparian zones are biologically high productive and characterized by a rich biodiversity; thus considered of high community interest with an imperative to be protected and regularly monitored. Satellite earth observation (EO) provides tools for capturing the current state of forest habitats such as forest composition including intermixture of non-native tree species. Here we present a semi-automated object based image analysis (OBIA) approach for the mapping of riparian forests by applying class modelling of habitats based on the European Nature Information System (EUNIS) habitat classifications and the European Habitats Directive (HabDir) Annex 1. A very high resolution (VHR) WorldView-2 satellite image provided the required spatial and spectral details for a multi-scale image segmentation and rule-base composition to generate a six-level hierarchical representation of riparian forest habitats. Thereby habitats were hierarchically represented within an image object hierarchy as forest stands, stands of homogenous tree species and single trees represented by sunlit tree crowns. 522 EUNIS level 3 (EUNIS-3) habitat patches with a mean patch size (MPS) of 12,349.64 m² were modelled from 938 forest stand patches (MPS = 6868.20 m²) and 43,742 tree stand patches (MPS = 140.79 m²). The delineation quality of the modelled EUNIS-3 habitats (focal level) was quantitatively assessed to an expert-based visual interpretation showing a mean deviation of 11.71%.