Geographical Analysis最新文献

Time Series Clustering for Exploring Neighborhood Dynamics: The Case of U.S. Neighborhood Racial and Ethnic Trends, 1990–2020 探索社区动态的时间序列聚类：以1990-2020年美国社区种族和民族趋势为例

IF 3.3 3区地球科学

Geographical Analysis Pub Date : 2025-05-05 DOI: 10.1111/gean.70006

Elizabeth C. Delmelle, Isabelle Nilsson, Nathan Duma

{"title":"Time Series Clustering for Exploring Neighborhood Dynamics: The Case of U.S. Neighborhood Racial and Ethnic Trends, 1990–2020","authors":"Elizabeth C. Delmelle, Isabelle Nilsson, Nathan Duma","doi":"10.1111/gean.70006","DOIUrl":"https://doi.org/10.1111/gean.70006","url":null,"abstract":"This article introduces a time-series clustering approach for classifying, visualizing, and exploring neighborhood dynamics. We illustrate the method for the case of racial and ethnic dynamics of neighborhoods in 64 U.S. metropolitan areas from 1990 to 2020. We establish typologies of continuous attribute trajectories for the share of Black, White, and Hispanic populations at the census tract level and explore generalizability versus specificity tradeoffs when varying the cluster analysis scale. Our results affirm a consistent decline in White population shares in neighborhoods across most metropolitan areas, accompanied by varied increases in Black and Hispanic populations. We also highlight the importance of metropolitan context in shaping neighborhood trends. While all cities show a trend towards increased diversity, the specific patterns and rates of change vary considerably, highlighting the unique demographic dynamics at play in each metropolitan area. The time-series clustering approach offers some advantages over previously used methods for visualizing and classifying longitudinal neighborhood dynamics like sequence analysis or growth change modeling in that it clusters the full continuous time series and does assume a pre-determined functional form.","PeriodicalId":12533,"journal":{"name":"Geographical Analysis","volume":"57 3","pages":"402-420"},"PeriodicalIF":3.3,"publicationDate":"2025-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/gean.70006","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144646794","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Fast Spatio-Temporally Varying Coefficient Modeling With Reluctant Interaction Selection 基于不情愿交互选择的快速时空变化系数建模

IF 3.3 3区地球科学

Geographical Analysis Pub Date : 2025-04-15 DOI: 10.1111/gean.70005

Daisuke Murakami, Shinichiro Shirota, Seiji Kajita, Mami Kajita

{"title":"Fast Spatio-Temporally Varying Coefficient Modeling With Reluctant Interaction Selection","authors":"Daisuke Murakami, Shinichiro Shirota, Seiji Kajita, Mami Kajita","doi":"10.1111/gean.70005","DOIUrl":"https://doi.org/10.1111/gean.70005","url":null,"abstract":"Spatially and temporally varying coefficient (STVC) models are attracting attention as a flexible tool to explore the spatio-temporal patterns in regression coefficients. However, these models often struggle with balancing the computational efficiency, flexibility, and interpretability of the coefficients. This study develops a fast and flexible STVC model to address this challenge. To enhance flexibility and interpretability, we assume multiple processes in each varying coefficient, including purely spatial, purely temporal, and spatio-temporal interaction processes with or without time cyclicity. We combine a pre-conditioning method with a model selection procedure, inspired by reluctant interaction modeling, to estimate the strength of each process in each coefficient in a computationally efficient manner, while removing redundant processes as necessary. Monte Carlo experiments demonstrate that the proposed method outperforms alternatives in terms of coefficient estimation accuracy and computational efficiency. We then apply the proposed method to a crime analysis. The result confirms that the proposed method provides reasonable estimates. The STVC model is implemented in the R package spmoran.","PeriodicalId":12533,"journal":{"name":"Geographical Analysis","volume":"57 3","pages":"521-539"},"PeriodicalIF":3.3,"publicationDate":"2025-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/gean.70005","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144646835","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Assessing the Number of Criteria in GIS-Based Multicriteria Evaluation: A Machine Learning Approach 基于gis的多标准评估中标准数量的评估：一种机器学习方法

IF 3.3 3区地球科学

Geographical Analysis Pub Date : 2025-03-27 DOI: 10.1111/gean.70004

Lan Qing Zhao, Suzana Dragićević, Shivanand Balram, Liliana Perez

{"title":"Assessing the Number of Criteria in GIS-Based Multicriteria Evaluation: A Machine Learning Approach","authors":"Lan Qing Zhao, Suzana Dragićević, Shivanand Balram, Liliana Perez","doi":"10.1111/gean.70004","DOIUrl":"https://doi.org/10.1111/gean.70004","url":null,"abstract":"The analytical hierarchy process (AHP) is a widely used approach and a decision rule to derive criteria weights in geographic information system-based multi-criteria evaluation (GIS-MCE). However, one limitation of the AHP method is that it constrains the number of criteria that can be meaningfully weighted to typically seven to nine criteria. Recently, machine learning (ML) techniques have emerged as a compelling alternative for deriving criteria weights. This research aims to assess the capabilities of ML-MCE in handling a larger number of criteria and is specifically applied to a case study of urban suitability analysis. The random forest (RF) ML technique is used to evaluate the ability of the MCE method to handle up to 27 criteria. Geospatial data from the Metro Vancouver Region, Canada, are used, with the criteria subdivided into 11 groups starting with the most basic seven criteria and incrementally adding two new criteria per group. The results indicate the RF-ML approach can manage a larger number of criteria compared to the traditional AHP approach, with 15 criteria providing a meaningful upper threshold, demonstrating its potential to accommodate a wider range of stakeholder preferences for complex urban suitability analysis contexts.","PeriodicalId":12533,"journal":{"name":"Geographical Analysis","volume":"57 3","pages":"489-506"},"PeriodicalIF":3.3,"publicationDate":"2025-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/gean.70004","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144647863","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Multiple Scales of Income Inequality: A Longitudinal Analysis of Swedish Regions 收入不平等的多重尺度：瑞典地区的纵向分析

IF 3.3 3区地球科学

Geographical Analysis Pub Date : 2025-03-18 DOI: 10.1111/gean.70003

Andreas Erlström, Markus Grillitsch, Nicklas Guldåker

{"title":"Multiple Scales of Income Inequality: A Longitudinal Analysis of Swedish Regions","authors":"Andreas Erlström, Markus Grillitsch, Nicklas Guldåker","doi":"10.1111/gean.70003","DOIUrl":"https://doi.org/10.1111/gean.70003","url":null,"abstract":"The subject of inequality and its geographical dimensions has seen a surge of interest in recent years. However, existing work tends to study inequality through single spatial scales, even though processes driving inequality operate at and across multiple scales. This article, therefore, investigates how inequality at the regional and local scale relates to phases of economic development in Sweden over three decades. The findings point towards a diverging trend of inequality between the regional and local scale, with a noticeable shift at the turn of the millennium. While the last decades were characterized by a slight regional convergence, inequality at the local scale continued to increase. Accounting for different regional contexts, economic growth and local inequality were most pronounced in the larger urban areas. Surprisingly, though, in the last decade, employment grew in urban areas without an increase in local inequality. In contrast, peripheral and sparsely populated regions experienced a rise in inequality without significant employment growth. This suggests that the link between economic development and inequality is not universal but dependent on, among others, the nature of structural change in the economy and institutional preconditions.","PeriodicalId":12533,"journal":{"name":"Geographical Analysis","volume":"57 3","pages":"370-388"},"PeriodicalIF":3.3,"publicationDate":"2025-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/gean.70003","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144647233","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Strict-Contiguity Criterion for Preventing County Splits in Redistricting 防止选区划分中县分裂的严格邻接标准

IF 3.3 3区地球科学

Geographical Analysis Pub Date : 2025-03-11 DOI: 10.1111/gean.70000

Eric Rosenberg, Brendan Ruskey

{"title":"A Strict-Contiguity Criterion for Preventing County Splits in Redistricting","authors":"Eric Rosenberg, Brendan Ruskey","doi":"10.1111/gean.70000","DOIUrl":"https://doi.org/10.1111/gean.70000","url":null,"abstract":"<div>\u0000 \u0000 The splitting of political subdivisions (in particular, counties) is a contentious aspect of the redistricting process. Though sometimes necessary, county-splitting districts are generally thought to be undesirable, and are typically prohibited by legislation unless required, e.g., to achieve equality of district populations. Some county-splitting districts are clear examples of gerrymandering, taking awkward non-compact shapes and stretching across several counties. However, even reasonably compact districts can exhibit county splits, and we provide five examples of reasonably compact districts exhibiting county splits. Thus there is a need for a criterion, unrelated to compactness, for evaluating whether a county-splitting district should be allowed. To disallow splits, we introduce a strict contiguity constraint specifying that a county can be used on a path between two precincts in a district only if the fraction of the county population assigned to the district exceeds a user-specified parameter <math>\u0000 <semantics>\u0000 <mrow>\u0000 <mi>ρ</mi>\u0000 <mo>∈</mo>\u0000 <mo>(</mo>\u0000 <mn>0</mn>\u0000 <mo>,</mo>\u0000 <mn>1</mn>\u0000 <mo>]</mo>\u0000 </mrow>\u0000 <annotation>$$ rho in left(0,1right] $$</annotation>\u0000 </semantics></math>. We provide a mathematical formulation of redistricting with strict contiguity and illustrate its numerical solution. Our definition of strict continuity is not limited to county splits; it can apply to any grouping of geographical units, or in a redistricting setting other than within the U.S.\u0000 </div>","PeriodicalId":12533,"journal":{"name":"Geographical Analysis","volume":"57 3","pages":"445-462"},"PeriodicalIF":3.3,"publicationDate":"2025-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144646935","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Geographical Gaussian Process Regression: A Spatial Machine-Learning Model Based on Spatial Similarity 地理高斯过程回归：一种基于空间相似性的空间机器学习模型

IF 3.3 3区地球科学

Geographical Analysis Pub Date : 2025-03-10 DOI: 10.1111/gean.12423

Zhenzhi Jiao, Ran Tao

{"title":"Geographical Gaussian Process Regression: A Spatial Machine-Learning Model Based on Spatial Similarity","authors":"Zhenzhi Jiao, Ran Tao","doi":"10.1111/gean.12423","DOIUrl":"https://doi.org/10.1111/gean.12423","url":null,"abstract":"<div>\u0000 \u0000 This study proposes a new spatial machine-learning model called geographical Gaussian process regression (GGPR). GGPR is extended from Gaussian process regression (GPR) by adopting the principle of spatial similarity for calibration, and it is designed to conduct spatial prediction and exploratory spatial data analysis (ESDA). GGPR addresses several key challenges in spatial machine learning. First, as a probabilistic model, GGPR avoids the conflict between spatial autocorrelation and the assumption of independent and identically distributed (i.i.d.), thus enhancing the model's objectivity and reliability in spatial prediction. Second, GGPR is suitable for small-sample prediction, a task that most existing models struggle with. Finally, when integrated with GeoShapley, GGPR is an explainable model that can measure spatial effects and explain the outcomes. Evaluated on two distinct datasets, GGPR demonstrates superior predictive performance compared to other popular machine-learning models across various sampling ratios, with its advantage becoming especially evident with smaller sample sizes. As an ESDA model, GGPR demonstrates enhanced accuracy, better computational efficiency, and a comparable ability to measure spatial effects against both multiscale geographically weighted regression and geographical random forests. In short, GGPR offers spatial data scientists a new method for predicting and exploring complex geographical processes.\u0000 </div>","PeriodicalId":12533,"journal":{"name":"Geographical Analysis","volume":"57 3","pages":"507-520"},"PeriodicalIF":3.3,"publicationDate":"2025-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144646833","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Data-Driven Approach to Spatial Interaction Models of Migration: Integrating and Refining the Theories of Competing Destinations and Intervening Opportunities 基于数据驱动的移民空间互动模型：整合和完善竞争目的地和干预机会理论

IF 3.3 3区地球科学

Geographical Analysis Pub Date : 2025-03-06 DOI: 10.1111/gean.70001

Mengyu Liao, Taylor M. Oshan

{"title":"A Data-Driven Approach to Spatial Interaction Models of Migration: Integrating and Refining the Theories of Competing Destinations and Intervening Opportunities","authors":"Mengyu Liao, Taylor M. Oshan","doi":"10.1111/gean.70001","DOIUrl":"https://doi.org/10.1111/gean.70001","url":null,"abstract":"Traditional spatial interaction (SI) models of migration are susceptible to misspecification when the spatial structure of locations is not properly incorporated. To address this, a novel SI model for migration is introduced that integrates the theories of competing destinations (CD) and intervening opportunities (IO) to capture multiscale spatial structure using the recent generalized additive spatial smoothing (GASS) framework. This GASS CDIO model can identify the appropriate spatial scales to represent the spatial structure of origins and destinations in a data-driven manner. Validation of the model was conducted through two simulation experiments. The first demonstrates that employing the incorrect scale to capture spatial structure in SI models biases the parameter estimates and increases uncertainty. The second demonstrates that the GASS approach reliably recovers accurate parameters by identifying optimal hyperparameters associated with multiple spatial scales. The GASS CDIO model was then applied to U.S. inter-county migration data and compared to several other model specifications. The results reveal the unique spatial structure from the perspective of origins and destinations and illustrate the improved recoverability of anticipated migration relationships. This work suggests that the GASS CDIO model better integrates spatial theories of migration and accounts for the multiscale nature of SI processes.","PeriodicalId":12533,"journal":{"name":"Geographical Analysis","volume":"57 3","pages":"540-554"},"PeriodicalIF":3.3,"publicationDate":"2025-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/gean.70001","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144647017","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Novel Approach to Assess the Distance Between the Settlement Patterns of Two Populations 一种评估两种群聚落模式之间距离的新方法

IF 3.3 3区地球科学

Geographical Analysis Pub Date : 2025-02-20 DOI: 10.1111/gean.70002

Massimo Mucciardi

{"title":"A Novel Approach to Assess the Distance Between the Settlement Patterns of Two Populations","authors":"Massimo Mucciardi","doi":"10.1111/gean.70002","DOIUrl":"https://doi.org/10.1111/gean.70002","url":null,"abstract":"Understanding settlement patterns and their spatial distribution is essential for various fields, including geography, demography, and sociology. This paper explores a novel approach to assess the distance between settlement patterns of two populations with a specific focus on territorial variation inequalities. Building upon the conceptual framework of the Lorenz curve, we introduce new indices and graphical representations that permit us to emphasize territorial differences in settlement between two populations. By emphasizing the distance between settlement patterns, this methodology captures variations and inequalities in territorial distribution. Rather than simply characterizing settlement patterns as concentrated or dispersed, this approach considers the extent to which populations are spatially separated or integrated. To test this new approach, three foreign reference communities were examined (Egyptians, Chinese, and Romanians) known in the literature for their markedly different settlement patterns in Italy. We identified three different patterns for these populations that highlight the importance of considering local variations and spatial interactions in the study of settlement patterns. The results obtained seem to agree with the theory of settlements of foreign populations in Italy, albeit with additional geographical information. Through this research, we aim to provide a new methodology for measuring the distance between the settlement patterns of two different populations, filling some gaps in traditional methods.","PeriodicalId":12533,"journal":{"name":"Geographical Analysis","volume":"57 3","pages":"389-401"},"PeriodicalIF":3.3,"publicationDate":"2025-02-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/gean.70002","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144647558","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Comparisons Between Robbery and Break-And-Enter: Area-Specific Trends, Socioeconomic Risk Factors, and Hotspots Analysis Using a Bayesian Spatial and Spatiotemporal Approach 基于贝叶斯时空方法的抢劫与入室抢劫的区域趋势、社会经济风险因素及热点分析

IF 3.3 3区地球科学

Geographical Analysis Pub Date : 2025-02-10 DOI: 10.1111/gean.12421

Jane Law, Abu Yousuf Md Abdullah

{"title":"Comparisons Between Robbery and Break-And-Enter: Area-Specific Trends, Socioeconomic Risk Factors, and Hotspots Analysis Using a Bayesian Spatial and Spatiotemporal Approach","authors":"Jane Law, Abu Yousuf Md Abdullah","doi":"10.1111/gean.12421","DOIUrl":"https://doi.org/10.1111/gean.12421","url":null,"abstract":"Robbery and break-and-enter (BE) crimes require investigations into how these contrasting crimes co-occur. Utilizing robbery and BE data from the City of Toronto in Canada, this study analyzed the mean and area-specific crime trends, their risk factors, and the shared and crime-specific risk and hotspot areas. Results suggest an increase in robbery (0.23, 95% credible interval (CI): 0.17–0.29) and BE (0.08, 95% CI: 0.04–0.12) crimes during 2021–2022, revealing the most prominent area-specific trends in northwest and northeastern Toronto. The findings suggest that spatially lagged variables can offer deeper insights into complex spatial interactions of real-life factors that influence crime. Robberies were positively associated with the household and dwellings indicator (2021 Ontario Marginalization Index) but not its spatial lag, while BE crimes had no direct association with it but showed a positive association with its spatial lag. Neighborhoods in northwestern, northeastern, and southcentral parts of Toronto were hotspots of robberies, while southcentral and northwestern parts were at elevated risk due to BE. The findings demonstrate the complexities associated with the co-occurrence of multiple crime types and highlight the need for more unified and integrated theories to contextualize neighborhood effects of crime determinants and their impact on crimes.","PeriodicalId":12533,"journal":{"name":"Geographical Analysis","volume":"57 3","pages":"463-477"},"PeriodicalIF":3.3,"publicationDate":"2025-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/gean.12421","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144646886","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Overlapping Landsat Scene Classifications and Focal Context to Identify Boreal Disturbance Mapping Uncertainty 重叠陆地卫星场景分类和焦点背景识别北方扰动映射的不确定性

IF 3.3 3区地球科学

Geographical Analysis Pub Date : 2025-01-28 DOI: 10.1111/gean.12422

Wesley J. Wu, Tarmo K. Remmel, Marc Ouellette

{"title":"Overlapping Landsat Scene Classifications and Focal Context to Identify Boreal Disturbance Mapping Uncertainty","authors":"Wesley J. Wu, Tarmo K. Remmel, Marc Ouellette","doi":"10.1111/gean.12422","DOIUrl":"https://doi.org/10.1111/gean.12422","url":null,"abstract":"<div>\u0000 \u0000 The BorealDB dataset provides annual fire and timber harvesting disturbance classifications for Ontario that are derived from a collection of independently classified Landsat scenes. This study assesses the confidence of BorealDB classifications within overlapping scene margins since multiple classifications for common locations are available. For each focal point in BorealDB, the disturbance state of its four nearest spatial orthogonal neighbors were extracted and used to produce classification tree (CT) and random forest (RF) predictions of the focal class. Uncertainty was assessed as being greatest when predictions by neighboring locations or overlapping disturbance classes disagree with the focal class. The assessment found that identified locations of uncertainty within BorealDB varied with disturbance class, with fire having lower uncertainty than timber harvesting. With the results of the analysis, we recommend the inclusion of the analysis outputs and comparisons to supplement existing ensemble confidence attribute in BorealDB.\u0000 </div>","PeriodicalId":12533,"journal":{"name":"Geographical Analysis","volume":"57 3","pages":"478-488"},"PeriodicalIF":3.3,"publicationDate":"2025-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144647771","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0