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Letters in Spatial and Resource Sciences最新文献

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Pandemetrics: modelling pandemic impacts in space 大流行病计量学:模拟大流行病在空间的影响
IF 1.8 Q2 GEOGRAPHY Pub Date : 2023-12-19 DOI: 10.1007/s12076-023-00368-2
Pui‐Hang Wong, K. Kourtit, Peter Nijkamp
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引用次数: 0
CSR and smart city progress: a proposed model for urban development 企业社会责任与智慧城市进展:城市发展的拟议模式
IF 1.8 Q2 GEOGRAPHY Pub Date : 2023-12-18 DOI: 10.1007/s12076-023-00367-3
Kuldeep Singh, Prasanna Kolar, Sireesha Nanduri, Vedantam Seetha Ram, Divyesh Kumar
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引用次数: 0
Spatial and temporal analysis of cyber-crime cases in India 印度网络犯罪案件的时空分析
IF 1.8 Q2 GEOGRAPHY Pub Date : 2023-12-04 DOI: 10.1007/s12076-023-00360-w
Avani Rachh
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引用次数: 0
Status and determinants of crop diversification: evidence from Indian States 作物多样化的现状和决定因素:印度各邦的证据
IF 1.8 Q2 GEOGRAPHY Pub Date : 2023-11-30 DOI: 10.1007/s12076-023-00366-4
C. Kumar, Chittaranjan Nayak, Ashis Kumar Pradhan
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引用次数: 0
The impact of COVID-19 on tourism, employment, and population of the Azores islands COVID-19 对亚速尔群岛旅游业、就业和人口的影响
IF 1.8 Q2 GEOGRAPHY Pub Date : 2023-11-28 DOI: 10.1007/s12076-023-00365-5
Karina Simone Sass, Raquel Ferreira Maciel, Tomaz Ponce Dentinho
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引用次数: 0
Regional unemployment dynamics in Indonesia: serial persistence, spatial dependence, and common factors 印度尼西亚的地区失业动态:序列持续性、空间依赖性和共同因素
IF 1.8 Q2 GEOGRAPHY Pub Date : 2023-11-24 DOI: 10.1007/s12076-023-00364-6
Carlos Mendez, T. Siregar
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引用次数: 0
Favorable credit to private agents and the local economies in the deprived regions of Brazil: a spatial panel analysis 巴西贫困地区对私营代理人的优惠信贷和地方经济:空间面板分析
IF 1.8 Q2 GEOGRAPHY Pub Date : 2023-11-24 DOI: 10.1007/s12076-023-00363-7
Luís Abel da Silva-Filho, C. Azzoni, André L. S. Chagas, Gustavo Castro
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引用次数: 0
Bayesian spatial panel models: a flexible Kronecker error component approach 贝叶斯空间面板模型:一种灵活的Kronecker误差分量方法
Q2 GEOGRAPHY Pub Date : 2023-11-14 DOI: 10.1007/s12076-023-00362-8
Yuheng Ling, Julie Le Gallo
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引用次数: 0
Determinants of migration in Jammu and Kashmir: A case study of floating population of Katra Region 查谟和克什米尔移民的决定因素:对卡特拉地区流动人口的个案研究
Q2 GEOGRAPHY Pub Date : 2023-10-25 DOI: 10.1007/s12076-023-00359-3
Meenakshi Gupta, Shriya Gupta
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引用次数: 0
Assessing geographical differences of the COVID-19 impact on fuel consumption: the case of Italy 评估COVID-19对燃料消耗影响的地理差异:以意大利为例
Q2 GEOGRAPHY Pub Date : 2023-10-25 DOI: 10.1007/s12076-023-00361-9
Riccardo Borgoni, Matteo Denova, Paolo Maranzano, Caterina Morelli
Abstract We propose a spatio-temporal analysis aiming at estimating the variation of gasoline and diesel consumption occurred in the Italian provinces as a consequence of the COVID-19 pandemic during 2020 and 2021. We employ generalized linear models and generalized additive models to predict business-as-usual per capita fuel consumption by means of socio-economic variables, such as demography, tourist stays, temperature and territorial characteristics. The province-specific impact of the restrictions is then estimated as the difference between the observed and model-predicted values. The spatio-temporal dynamics is introduced by means of appropriate spline basis functions allowing both spatial and time trend to be smooth surfaces. Moreover, we include a smooth spatio-temporal interaction that properly capture the seasonal characteristic of different areas. Our findings highlight that the national mobility restrictions imposed to fight the spread of COVID-19 in the first wave (March to May 2020) reduced gasoline and diesel consumption homogeneously nationwide, with some slight differences between northern and southern provinces. However, the second wave lockdown (Winter 2020–2021) determined heterogeneous impacts across Italian provinces. In particular, we highlight the existence of a divergence between North and South Italy in terms of reaction to the pandemic. Indeed, while southern provinces experienced the weakest and less variable reductions, the northern provinces recorded strong and persistent contractions of fuel consumption. Also, southern and tourism-devoted provinces recovered quickly and compact to the post-pandemic reopenings.
摘要:我们提出了一项时空分析,旨在估计2020年和2021年COVID-19大流行导致意大利各省汽油和柴油消费的变化。我们采用广义线性模型和广义加性模型,通过社会经济变量(如人口统计、游客停留、温度和地域特征)来预测照常营业的人均燃料消耗。然后用观测值和模型预测值之间的差值来估计限制措施对各省的具体影响。通过适当的样条基函数引入时空动力学,使空间和时间趋势都是光滑的表面。此外,我们包括一个平滑的时空相互作用,适当地捕捉不同地区的季节特征。我们的研究结果强调,在第一波(2020年3月至5月)为抗击COVID-19的传播而实施的全国交通限制措施,在全国范围内均匀地减少了汽油和柴油的消耗,北部和南部省份之间存在轻微差异。然而,第二波封锁(2020年至2021年冬季)确定了意大利各省的不同影响。我们特别强调,意大利北部和南部在对这一流行病的反应方面存在分歧。事实上,虽然南部省份经历了最弱和变化较小的减少,但北部省份的燃料消耗却出现了强劲和持续的收缩。此外,南部省份和以旅游为主的省份迅速恢复,适应了疫情后的重新开放。
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引用次数: 0
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Letters in Spatial and Resource Sciences
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