基于扎根理论与文本分析的海洋旅游目的地意象研究

旅游目的地意象在旅游者决策与目的地开发中具有重要作用,也是旅游研究中的热点领域。海洋旅游目的地意象的研究对于提高目的地竞争力与吸引力具有重要意义。本文以夏威夷为例,基于国内旅游者发布在网络上的游记,利用扎根理论与文本分析法对夏威夷的认知意象、情感意象与总体意象进行分析。研究发现,“海洋自然吸引物”、“海洋人文吸引物”、“海洋旅游活动”、“目的地软环境”、“旅游服务”、“公共场所与服务”是构成海洋旅游目的地认知意象的六个主范畴;在此基础上,通过提取游记中的情感语句并结合“情感环状模型”发现夏威夷的情感意象以正面情感为主;从语义网络与重游意愿来看,夏威夷的总体意象较为积极,并未出现明显的负面感知要素。研究旨在为国内海洋旅游目的地的发展提供一定的经验与借鉴。     

黄土丘陵沟壑区典型村域土地利用变化及对区域乡村转型发展的启示

深入开展乡村地域土地利用变化和聚落发展规律的研究对于探究乡村地域系统优化、推进城乡融合与乡村可持续发展具有重要意义。论文以延安市碾庄流域为例,基于ENVI和GIS等软件技术,结合Landsat卫星影像、马尔科夫链模型和实地调查,从土地利用转移与交换变化、建筑用地空间转移、社会响应等角度探讨了黄土丘陵沟壑区典型村域土地利用变化特征以及对区域乡村发展转型的影响。研究表明：① 在一系列生态工程措施作用下,碾庄流域生态覆被发生明显改观,主要表现为大量的坡耕地及稀疏生态用地转化为林地,其中,林地面积占比由32.34%(2009年)增加至50.88%(2018年);② 在社会经济发展和延安新城“边缘效应”的影响下,碾庄建设用地呈现向流域的东南和西南方向拓展的趋势,10 a间建设用地面积增加了近75%;③ 在人类活动的主导作用下,黄土丘陵沟壑区的乡村正在朝着生态化和集约化的方向转型发展。研究结果有望为深入理解黄土丘陵沟壑区乡村地域系统结构和优化提供新参考。     

2010—2015年中东北非政局变动中的“政治性民意势力”及其影响

援引批判地缘政治学话语权和地缘政治想象分析方法,在对“民意”“政治性民意”“政治性民意势力”内涵界定的基础上,分析了2010—2015年中东北非地区相关国家政局变动中“政治性民意势力”的形成背景、过程及其影响。结果表明：中东北非国家“政治性民意势力”的形成有着深厚的国内背景和复杂的国际背景;“政治性民意势力”的形成经历了从民意事件客体的呈现,到民众聚集并上升为政治性议题,再到国内外势力借力博弈形成挑动抗议、推动政变的政治力量的过程;“政治性民意势力”形成以后,多行为体借力博弈下,在国别、区域上呈现不同的扩散轨迹和规律;“政治性民意势力”一方面造成了中东北非相关国家的政局变换,另一方面则推动区域地缘政治格局的变迁。这是对民意事件的地缘政治理论解读和分析,是一次较为有意义的尝试。     

丘陵区典型小流域地下水化学特征与补给来源分析

川中紫色土丘陵区频发的季节性干旱严重制约区域农村经济和社会可持续发展。地下水是丘陵区农村居民饮用和灌溉的主要水源,但迄今该区域地下水补给循环过程的相关研究报道极少。本研究选取盐亭大兴小流域(480 hm 2)为典型小流域进行综合水文观测与取样,比较了小流域内浅层地下水(2口泉水、14口井水)在不同覆被条件下雨季和旱季的水化学特征(包括D、 18 O)及水岩作用过程,并通过氯离子平衡法和二元混合模型法对比分析区域降水补给地下水规律。结果表明:(1)研究区内浅层地下水水化学类型为HCO 3 ·SO 4-Ca,主要控制因素为岩石风化水解;(2)由地下水同位素峰值响应特征可知该区域浅层地下水对雨季降水补给响应时间约为50~ 85 d;雨季浅层地下水交换作用比旱季强烈;(3)氯离子平衡法受人为干扰较大,计算结果可能偏小,二元混合模型法未包含更多水源,计算结果可能偏大;(4)优化估算结果表明浅层地下水全年接受降水补给率在12%~38%间变化,雨季单次降水补给地下水比例在4.3%~58.0%间变化。本研究通过揭示丘陵区浅层地下水水化学性质变化规律,初步估算了浅层地下水补给来源及比例,可为区域地下水资源评估提供科学基础。     

黑河上游山地土壤容重分布特征及影响因素

土壤容重不仅可用作计算土壤持水力和导水性,也是估算土壤养分和碳储量的重要变量。野外测定土壤容重一般费时费力,特别是在地形复杂的山区,因此山地土壤容重在国内外大多数清查数据库中缺失。本文以黑河上游山地为例,基于野外调查的124个土壤剖面,研究了山地土壤容重的空间分布特征及影响因素。结果表明:黑河上游山地0~10 cm和0~60 cm土壤容重分别为0.91±0.02 g·cm^-3 和1.04±0.01 g·cm^-3;不同植被类型下,高山寒漠容重最大,山地森林最小。随着土壤深度的增加,容重呈幂函数递增;随着土壤有机质含量的增加,容重呈指数递减。区域上,黑河上游从西北到东南,容重呈递减趋势,从高海拔到低海拔,容重呈先减小后增大趋势。主成分分析(PCA)和一般线性模型(GLM)表明,与土壤容重相关的环境因子中,海拔是影响土壤表层容重的第一主成分,土壤有机质含量是第二主成分,黏粒含量和大于2.0 mm砾石含量分别为第三、四主成分。第一、二、三、四主成分分别解释土壤容重空间变异的24.00%、29.40%、0.01%、6.20%。     

The spatial local accuracy of land cover datasets over the Qiangtang Plateau,High Asia

We analyzed the spatial local accuracy of land cover (LC) datasets for the Qiangtang Plateau, High Asia, incorporating 923 field sampling points and seven LC compilations including the International Geosphere Biosphere Programme Data and Information System (IGBPDIS), Global Land cover mapping at 30 m resolution (GlobeLand30), MODIS Land Cover Type product (MCD12Q1), Climate Change Initiative Land Cover (CCI-LC), Global Land Cover 2000 (GLC2000), University of Maryland (UMD), and GlobCover 2009 (Glob-Cover). We initially compared resultant similarities and differences in both area and spatial patterns and analyzed inherent relationships with data sources. We then applied a geographically weighted regression (GWR) approach to predict local accuracy variation. The results of this study reveal that distinct differences, even inverse time series trends, in LC data between CCI-LC and MCD12Q1 were present between 2001 and 2015, with the exception of category areal discordance between the seven datasets. We also show a series of evident discrepancies amongst the LC datasets sampled here in terms of spatial patterns, that is, high spatial congruence is mainly seen in the homogeneous southeastern region of the study area while a low degree of spatial congruence is widely distributed across heterogeneous northwestern and northeastern regions. The overall combined spatial accuracy of the seven LC datasets considered here is less than 70%, and the GlobeLand30 and CCI-LC datasets exhibit higher local accuracy than their counterparts, yielding maximum overall accuracy (OA) values of 77.39% and 61.43%, respectively. Finally, 5.63% of this area is characterized by both high assessment and accuracy (HH) values, mainly located in central and eastern regions of the Qiangtang Plateau, while most low accuracy regions are found in northern, northeastern, and western regions.

     

Spatial patch structure and adaptive strategy for desert shrub of Reaumuria soongorica in arid ecosystem of the Heihe River Basin

In many arid ecosystems, vegetation frequently occurs in high-cover patches interspersed in a matrix of low plant cover. However, theoretical explanations for shrub patch pattern dynamics along climate gradients remain unclear on a large scale. This context aimed to assess the variance of the Reaumuria soongorica patch structure along the precipitation gradient and the factors that affect patch structure formation in the middle and lower Heihe River Basin (HRB). Field investigations on vegetation patterns and heterogeneity in soil properties were conducted during 2014 and 2015. The results showed that patch height, size and plant-to-patch distance were smaller in high precipitation habitats than in low precipitation sites. Climate, soil and vegetation explained 82.5% of the variance in patch structure. Spatially, R. soongorica shifted from a clumped to a random pattern on the landscape towards the MAP gradient, and heterogeneity in the surface soil properties (the ratio of biological soil crust (BSC) to bare gravels (BG)) determined the R. soongorica population distribution pattern in the middle and lower HRB. A conceptual model, which integrated water availability and plant facilitation and competition effects, was revealed that R. soongorica changed from a flexible water use strategy in high precipitation regions to a consistent water use strategy in low precipitation areas. Our study provides a comprehensive quantification of the variance in shrub patch structure along a precipitation gradient and may improve our understanding of vegetation pattern dynamics in the Gobi Desert under future climate change.

     

Developing a comprehensive evaluation method for Interconnected River System Network assessment: A case study in Tangxun Lake group

Journal of Geographical Sciences - The Interconnected River System Network (IRSN) plays a crucial role in water resource allocation, water ecological restoration and water quality improvement. It...     

Does geographic distance have a significant impact on enterprise financing costs?

Journal of Geographical Sciences - As information technology has been applied more broadly and transportation infrastructure has improved, persistent debate has existed as to the question of...     

Multiscale geographically and temporally weighted regression: exploring the spatiotemporal determinants of housing prices

Understanding scale effects is important and indispensable for geography studies. However, spatial and spatiotemporal statistical tools for measuring the operational scales of different processes are rather limited. This article extends the popular geographically and temporally weighted regression (GTWR) model to consider operational scale effects by proposing multiscale GTWR (MGTWR), which offers a flexible and scalable framework for identifying and analysing multiscale processes by specifying flexible bandwidths for various covariates. Then, MGTWR is employed to explore spatiotemporal variations and how influential factors are associated with housing prices in Shenzhen. This article attempts to extend GTWR to MGTWR in consideration of scale effects, thereby highlighting the importance of different levels of spatiotemporal heterogeneity. Furthermore, the empirical results of this study can provide valuable policy implications for real estate development in areas where urban planning should address multiscale effects in both temporal and spatial dimensions.