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This dataset is about cities in Beijing, China. It has 1 row. It features 7 columns including country, population, latitude, and longitude.
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Population: Beijing: Changping data was reported at 2,267.000 Person th in 2022. This records a decrease from the previous number of 2,270.000 Person th for 2021. Population: Beijing: Changping data is updated yearly, averaging 1,908.000 Person th from Dec 2006 (Median) to 2022, with 17 observations. The data reached an all-time high of 2,270.000 Person th in 2021 and a record low of 492.000 Person th in 2006. Population: Beijing: Changping data remains active status in CEIC and is reported by Beijing Municipal Bureau of Statistics. The data is categorized under China Premium Database’s Socio-Demographic – Table CN.GW: Population: Municipality District.
Metropolitan area from resources and environment science and social economic data, including data center, the Beijing municipal emergency administration, China's seismic data set download: 2015 beijing-tianjin-hebei, Yangtze river delta urban agglomeration (flow) of the floating population and large bay area characteristic research data sets, the density of population data (2000-2005-2010-2015-2020), human settlements, 1978-2017 (30 m by 30 m), the seventh in 2020 census data with vector (form), GDP raster data (2019), the data of the construction land expansion in 1978, 1985-2017 (30 m by 30 m), the population birth rate (1 km x 1 km) in 2015, the population spatial distribution of the 2000-2005-2010-2015-2020 (100 m by 100 m), and other social and economic data, statistical yearbook, three large scale urban agglomeration districts and counties, villages and towns social economic statistics and metropolis POI data (20 cities).
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<ul style='margin-top:20px;'>
<li>Total population for China in 2024 was <strong>1,425,178,782</strong>, a <strong>1.03% increase</strong> from 2023.</li>
<li>Total population for China in 2023 was <strong>1,410,710,000</strong>, a <strong>0.1% decline</strong> from 2022.</li>
<li>Total population for China in 2022 was <strong>1,412,175,000</strong>, a <strong>0.01% decline</strong> from 2021.</li>
</ul>Total population is based on the de facto definition of population, which counts all residents regardless of legal status or citizenship. The values shown are midyear estimates.
This polygon dataset represents county boundaries and population data in China from the 2000 Census. This dataset also includes detailed demographic data such as: sex and age statistics, litteracy, employment, and professions, and birth and death rates. These data were primarily based on the "The Administrative Maps of the People's Republic of China, published by China Map Press.This dataset is intended for researchers, students, and policy makers for reference and mapping purposes, and may be used for basic applications such as viewing, querying, and map output production, or to provide a basemap to support graphical overlays and analysis with other spatial data.Read More
This point shapefile represents the locations of townships with 2000 Population Census Data, 9.95% Long Form data, table L7-L8) for the Beijing province of China for 2000. These data are represented at 1:1,000,000 scale. This layer is part of the China 2000 township population census dataset.
This point shapefile represents the district locations, with 2000 population census data, for the Beijing province of China for 2000. These data are represented at 1:1,000,000 scale. This layer is part of the China 2000 township population census dataset.
This shapefile represents the rivers for the Beijing province of China for 2000. These data are represented at 1:1,000,000 scale. This layer is part of the China 2000 township population census dataset.
This point shapefile represents the prefecture city locations, with 2000 population census data, for the Guangxi Zhuangzu Zizhiqu province of China for 2000. These data are represented at 1:1,000,000 scale. This layer is part of the China 2000 township population census dataset.The 2000 China township maps are developed for matching 2000 China population Census data, which should only be used as references for research or education instead of used as official maps.
This point shapefile represents the prefecture city locations, with 2000 population census data, for the Jiangsu Sheng province of China for 2000. These data are represented at 1:1,000,000 scale. This layer is part of the China 2000 township population census dataset.The 2000 China township maps are developed for matching 2000 China population Census data, which should only be used as references for research or education instead of used as official maps.
This line shapefile represents the highways for the Beijing province of China for 2000. These data are represented at 1:1,000,000 scale. This layer is part of the China 2000 township population census dataset.
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Based on time series of Landsat images, this study uses the Google Earth Engine cloud platform to extract built-up land in the Beijing-Tianjin-Hebei region, and integrates the results with GlobeLand30, GHS-Built, GAIA and GLC_FCS-2020 land cover products to derive the built-up land data set during the period 2000-2020 in the region. An overall accuracy higher than 90% was obtained. Based on this data set, the SDG 11.3.1 indicators-land consumption rate(LCR), population growth rate(PGR) and ratio of land consumption rate to population growth rate(LCRPGR) were calculated for each city.
This polygon shapefile represents the provincial boundary for the Beijing province of China for 2000. These data are represented at 1:1,000,000 scale. This layer is part of the China 2000 township population census dataset.
This point shapefile represents the district locations, with 2000 population census data, for the Guangdong Sheng province of China for 2000. These data are represented at 1:1,000,000 scale. This layer is part of the China 2000 township population census dataset.The 2000 China township maps are developed for matching 2000 China population Census data, which should only be used as references for research or education instead of used as official maps.
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This database contains the recordings of 500 Chinese Mandarin speakers from Northern China (250 males and 250 females), from 18 to 60 years’ old, recorded in quiet studios located in Shenzhen and in Hong Kong Special Administrative Region, People’s Republic of China. Demographics of native speakers from Northern China is as follows:- Beijing: 200 speakers (100 males, 100 females)- North of Beijing: 101 speakers (50 males, 51 females)- Shandong: 149 speakers (75 males, 74 females)- Henan: 50 speakers (25 males, 25 females)Speaker profile includes the following information: unique ID, place of birth, place where speaker lived the longest by the age of 16, and the number of years that the speaker lived there, age, gender, recording place.Recordings were made through microphone headsets (ATM73a / AUDIO TECHNICA) and consist of 172 hours of audio data (about 30 minutes per speaker), stored in .WAV files as sequences of 48 KHz Mono, 16 bits, Linear PCM. Recording script consists of :• Phoneme balance statement: 785 sentences• Travel conversation: 1618 sentences• About 200 sentences per speaker including: 134 sentences of travel conversation, 66 sentences of phoneme balance
This shapefile represents railways the for the Beijing province of China for 2000. These data are represented at 1:1,000,000 scale. This layer is part of the China 2000 township population census dataset.
This point shapefile represents the locations of townships with 2000 Population Census Data, 9.95% Long Form data, table L1-L6) for the Jilin Sheng province of China for 2000. These data are represented at 1:1,000,000 scale. This layer is part of the China 2000 township population census dataset.The 2000 China township maps are developed for matching 2000 China population Census data, which should only be used as references for research or education instead of used as official maps.
Dataset for the textbook Computational Methods and GIS Applications in Social Science (3rd Edition), 2023 Fahui Wang, Lingbo Liu Main Book Citation: Wang, F., & Liu, L. (2023). Computational Methods and GIS Applications in Social Science (3rd ed.). CRC Press. https://doi.org/10.1201/9781003292302 KNIME Lab Manual Citation: Liu, L., & Wang, F. (2023). Computational Methods and GIS Applications in Social Science - Lab Manual. CRC Press. https://doi.org/10.1201/9781003304357 KNIME Hub Dataset and Workflow for Computational Methods and GIS Applications in Social Science-Lab Manual Update Log If Python package not found in Package Management, use ArcGIS Pro's Python Command Prompt to install them, e.g., conda install -c conda-forge python-igraph leidenalg NetworkCommDetPro in CMGIS-V3-Tools was updated on July 10,2024 Add spatial adjacency table into Florida on June 29,2024 The dataset and tool for ABM Crime Simulation were updated on August 3, 2023, The toolkits in CMGIS-V3-Tools was updated on August 3rd,2023. Report Issues on GitHub https://github.com/UrbanGISer/Computational-Methods-and-GIS-Applications-in-Social-Science Following the website of Fahui Wang : http://faculty.lsu.edu/fahui Contents Chapter 1. Getting Started with ArcGIS: Data Management and Basic Spatial Analysis Tools Case Study 1: Mapping and Analyzing Population Density Pattern in Baton Rouge, Louisiana Chapter 2. Measuring Distance and Travel Time and Analyzing Distance Decay Behavior Case Study 2A: Estimating Drive Time and Transit Time in Baton Rouge, Louisiana Case Study 2B: Analyzing Distance Decay Behavior for Hospitalization in Florida Chapter 3. Spatial Smoothing and Spatial Interpolation Case Study 3A: Mapping Place Names in Guangxi, China Case Study 3B: Area-Based Interpolations of Population in Baton Rouge, Louisiana Case Study 3C: Detecting Spatiotemporal Crime Hotspots in Baton Rouge, Louisiana Chapter 4. Delineating Functional Regions and Applications in Health Geography Case Study 4A: Defining Service Areas of Acute Hospitals in Baton Rouge, Louisiana Case Study 4B: Automated Delineation of Hospital Service Areas in Florida Chapter 5. GIS-Based Measures of Spatial Accessibility and Application in Examining Healthcare Disparity Case Study 5: Measuring Accessibility of Primary Care Physicians in Baton Rouge Chapter 6. Function Fittings by Regressions and Application in Analyzing Urban Density Patterns Case Study 6: Analyzing Population Density Patterns in Chicago Urban Area >Chapter 7. Principal Components, Factor and Cluster Analyses and Application in Social Area Analysis Case Study 7: Social Area Analysis in Beijing Chapter 8. Spatial Statistics and Applications in Cultural and Crime Geography Case Study 8A: Spatial Distribution and Clusters of Place Names in Yunnan, China Case Study 8B: Detecting Colocation Between Crime Incidents and Facilities Case Study 8C: Spatial Cluster and Regression Analyses of Homicide Patterns in Chicago Chapter 9. Regionalization Methods and Application in Analysis of Cancer Data Case Study 9: Constructing Geographical Areas for Mapping Cancer Rates in Louisiana Chapter 10. System of Linear Equations and Application of Garin-Lowry in Simulating Urban Population and Employment Patterns Case Study 10: Simulating Population and Service Employment Distributions in a Hypothetical City Chapter 11. Linear and Quadratic Programming and Applications in Examining Wasteful Commuting and Allocating Healthcare Providers Case Study 11A: Measuring Wasteful Commuting in Columbus, Ohio Case Study 11B: Location-Allocation Analysis of Hospitals in Rural China Chapter 12. Monte Carlo Method and Applications in Urban Population and Traffic Simulations Case Study 12A. Examining Zonal Effect on Urban Population Density Functions in Chicago by Monte Carlo Simulation Case Study 12B: Monte Carlo-Based Traffic Simulation in Baton Rouge, Louisiana Chapter 13. Agent-Based Model and Application in Crime Simulation Case Study 13: Agent-Based Crime Simulation in Baton Rouge, Louisiana Chapter 14. Spatiotemporal Big Data Analytics and Application in Urban Studies Case Study 14A: Exploring Taxi Trajectory in ArcGIS Case Study 14B: Identifying High Traffic Corridors and Destinations in Shanghai Dataset File Structure 1 BatonRouge Census.gdb BR.gdb 2A BatonRouge BR_Road.gdb Hosp_Address.csv TransitNetworkTemplate.xml BR_GTFS Google API Pro.tbx 2B Florida FL_HSA.gdb R_ArcGIS_Tools.tbx (RegressionR) 3A China_GX GX.gdb 3B BatonRouge BR.gdb 3C BatonRouge BRcrime R_ArcGIS_Tools.tbx (STKDE) 4A BatonRouge BRRoad.gdb 4B Florida FL_HSA.gdb HSA Delineation Pro.tbx Huff Model Pro.tbx FLplgnAdjAppend.csv 5 BRMSA BRMSA.gdb Accessibility Pro.tbx 6 Chicago ChiUrArea.gdb R_ArcGIS_Tools.tbx (RegressionR) 7 Beijing BJSA.gdb bjattr.csv R_ArcGIS_Tools.tbx (PCAandFA, BasicClustering) 8A Yunnan YN.gdb R_ArcGIS_Tools.tbx (SaTScanR) 8B Jiangsu JS.gdb 8C Chicago ChiCity.gdb cityattr.csv ...
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This dataset is used for urban informal settlements classification. The dataset contains a total of 1833 sets of samples, each of which includes a remote sensing image of size 3×224×224 and four street view images of size 3×512×1024. The remote sensing images come from Google Earth 18-level high-resolution remote sensing image with a resolution of 1.19m. The street view images come from Baidu Street View API. The samples in this dataset are divided into two categories, namely urban informal settlements (UIS) and non-urban informal settlements (Not-UIS). The dataset contains a total of 643 UIS samples and 1190 Not-UIS samples. All samples come from China’s eight megacities with a permanent urban population of more than 10 million (Beijing, Shanghai, Guangzhou, Shenzhen, Tianjin, Chengdu, Wuhan, and Chongqing).
This point shapefile represents the district locations, with 2000 population census data, for the Anhui Sheng province of China for 2000. These data are represented at 1:1,000,000 scale. This layer is part of the China 2000 township population census dataset.The 2000 China township maps are developed for matching 2000 China population Census data, which should only be used as references for research or education instead of used as official maps.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
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This dataset is about cities in Beijing, China. It has 1 row. It features 7 columns including country, population, latitude, and longitude.