scholarly journals Fine-Scale Population Estimation Based on Building Classifications: A Case Study in Wuhan

2021 ◽  
Vol 13 (10) ◽  
pp. 251
Author(s):  
Shunli Wang ◽  
Rui Li ◽  
Jie Jiang ◽  
Yao Meng
Keyword(s):  
Urban Population ◽  
Spatial Information ◽  
Residential Buildings ◽  
Population Estimation ◽  
Accurate Estimation ◽  
Fine Scale ◽  
Estimation Model ◽  
Rapid Urbanization ◽  
Administrative Division ◽  
Scale Population

In the context of rapid urbanization, the refined management of cities is facing higher requirements. In improving urban population management levels and the scientific allocation of resources, fine-scale population data plays an increasingly important role. The current population estimation studies mainly focus on low spatial resolution, such as city-scale and county scale, without considering differences in population distributions within cities. This paper mines and defines the spatial correlations of multi-source data, including urban building data, point of interest (POI) data, census data, and administrative division data. With populations mainly distributed in residential buildings, a population estimation model at a subdistrict scale is established based on building classifications. Composed of spatial information and attribute information, POI data are spaced irregularly. Based on this characteristic, the text classification method, frequency-inverse document frequency (TF-IDF), is applied to obtain functional classifications of buildings. Then we screen out residential buildings, and quantify characteristic variables in subdistricts, including perimeter, area, and total number of floors in residential buildings. To assess the validity of the variables, the random forest method is selected for variable screening and correlation analysis, because this method has clear advantages when dealing with unbalanced data. Under the assumption of linearity, multiple regression analysis is conducted, to obtain a linear model of the number of buildings, their geometric characteristics, and the population in each administrative division. Experiments showed that the urban fine-scale population estimation model established in this study can estimate the population at a subdistrict scale with high accuracy. This method improves the precision and automation of urban population estimation. It allows the accurate estimation of the population at a subdistrict scale, thereby providing important data to support the overall planning of regional energy resource allocation, economic development, social governance, and environmental protection.

scholarly journals Fine-Scale Population Estimation by 3D Reconstruction of Urban Residential Buildings

Sensors ◽  
2016 ◽  
Vol 16 (10) ◽  
pp. 1755 ◽  
Author(s):  
Shixin Wang ◽  
Ye Tian ◽  
Yi Zhou ◽  
Wenliang Liu ◽  
Chenxi Lin
Keyword(s):  
3D Reconstruction ◽  
Residential Buildings ◽  
Population Estimation ◽  
Fine Scale ◽  
Scale Population

scholarly journals Urban population estimation based on residential buildings volume using IKONOS-2 images and lidar data

2015 ◽  
Vol 37 (sup1) ◽  
pp. 1-28 ◽  
Author(s):  
Lívia Tomás ◽  
Leila Fonseca ◽  
Cláudia Almeida ◽  
Fernando Leonardi ◽  
Madalena Pereira
Keyword(s):  
Urban Population ◽  
Residential Buildings ◽  
Population Estimation ◽  
Lidar Data

scholarly journals Mapping Fine-Scale Urban Spatial Population Distribution Based on High-Resolution Stereo Pair Images, Points of Interest, and Land Cover Data

2020 ◽  
Vol 12 (4) ◽  
pp. 608 ◽  
Author(s):  
Min Xu ◽  
Chunxiang Cao ◽  
Peng Jia
Keyword(s):  
High Resolution ◽  
Land Cover ◽  
Urban Population ◽  
Population Distribution ◽  
Housing Price ◽  
Population Estimation ◽  
Google Earth ◽  
Stereo Pair ◽  
Fine Scale ◽  
Building Height

Fine-scale population distribution is increasingly becoming a research hotspot owing to its high demand in many applied fields. It is of great significance in urban emergency response, disaster assessment, resource allocation, urban planning, market research, and transportation route design. This study employed land cover, building address, and housing price data, and high-resolution stereo pair remote sensing images to simulate fine-scale urban population distribution. We firstly extracted the residential zones on the basis of land cover and Google Earth data, combined them with building information including address and price. Then, we employed the stereo pair analysis method to obtain the building height on the basis of ZY3-02 high-resolution satellite data and transform the building height into building floors. After that, we built a sophisticated, high spatial resolution model of population density. Finally, we evaluated the accuracy of the model using the survey data from 12 communities in the study area. Results demonstrated that the proposed model for spatial fine-scale urban population products yielded more accurate small-area population estimation relative to high-resolution gridded population surface (HGPS). The approach proposed in this study holds potential to improve the precision and automation of high-resolution population estimation.

Genome-Wide Single Nucleotide Polymorphisms are Robust in Resolving Fine-Scale Population Genetic Structure of the Small Brown Planthopper, Laodelphax striatellus (Fallén) (Hemiptera: Delphacidae)

2019 ◽  
Vol 112 (5) ◽  
pp. 2362-2368
Author(s):  
Yan Liu ◽  
Lei Chen ◽  
Xing-Zhi Duan ◽  
Dian-Shu Zhao ◽  
Jing-Tao Sun ◽  
...  
Keyword(s):  
Population Structure ◽  
Discriminant Analysis ◽  
Genetic Structure ◽  
Population Genetic ◽  
Brown Planthopper ◽  
Fine Scale ◽  
Nucleotide Polymorphisms ◽  
Single Nucleotide ◽  
Small Brown Planthopper ◽  
Scale Population

Abstract Deciphering genetic structure and inferring migration routes of insects with high migratory ability have been challenging, due to weak genetic differentiation and limited resolution offered by traditional genotyping methods. Here, we tested the ability of double digest restriction-site associated DNA sequencing (ddRADseq)-based single nucleotide polymorphisms (SNPs) in revealing the population structure relative to 13 microsatellite markers by using four small brown planthopper populations as subjects. Using ddRADseq, we identified 230,000 RAD loci and 5,535 SNP sites, which were present in at least 80% of individuals across the four populations with a minimum sequencing depth of 10. Our results show that this large SNP panel is more powerful than traditional microsatellite markers in revealing fine-scale population structure among the small brown planthopper populations. In contrast to the mixed population structure suggested by microsatellites, discriminant analysis of principal components (DAPC) of the SNP dataset clearly separated the individuals into four geographic populations. Our results also suggest the DAPC analysis is more powerful than the principal component analysis (PCA) in resolving population genetic structure of high migratory taxa, probably due to the advantages of DAPC in using more genetic variation and the discriminant analysis function. Together, these results point to ddRADseq being a promising approach for population genetic and migration studies of small brown planthopper.

scholarly journals RAD sequencing of common whelk, Buccinum undatum, reveals fine‐scale population structuring in Europe and cryptic speciation within the North Atlantic

2021 ◽  
Vol 11 (6) ◽  
pp. 2616-2629
Author(s):  
Jake Goodall ◽  
Kristen Marie Westfall ◽  
Hildur Magnúsdóttir ◽  
Snæbjörn Pálsson ◽  
Erla Björk Örnólfsdóttir ◽  
...  
Keyword(s):  
North Atlantic ◽  
Cryptic Speciation ◽  
Rad Sequencing ◽  
Fine Scale ◽  
Buccinum Undatum ◽  
The North ◽  
Scale Population ◽  
Population Structuring ◽  
The North Atlantic

scholarly journals Stirred but not shaken: population and recruitment genetics of the scallop (Pecten fumatus) in Bass Strait, Australia

2016 ◽  
Vol 73 (9) ◽  
pp. 2333-2341 ◽  
Author(s):  
Jennifer R. Ovenden ◽  
Bree J. Tillett ◽  
Michael Macbeth ◽  
Damien Broderick ◽  
Fiona Filardo ◽  
...  
Keyword(s):  
Genetic Structure ◽  
Population Genetic Structure ◽  
Population Genetic ◽  
Allelic Variation ◽  
Open Water ◽  
Marine Species ◽  
Population Connectivity ◽  
Valuable Insight ◽  
Fine Scale ◽  
Scale Population

Abstract We report population genetic structure and fine-scale recruitment processes for the scallop beds (Pecten fumatus) in Bass Strait and the eastern coastline of Tasmania in southern Australia. Conventional population pairwise FST analyses are compared with novel discriminant analysis of principal components (DAPC) to assess population genetic structure using allelic variation in 11 microsatellite loci. Fine-scale population connectivity was compared with oceanic features of the sampled area. Disjunct scallop beds were genetically distinct, but there was little population genetic structure between beds connected by tides and oceanic currents. To identify recruitment patterns among and within beds, pedigree analyses determined the distribution of parent–offspring and sibling relationships in the sampled populations. Beds in northeastern Bass Strait were genetically distinct to adjacent beds (FST 0.003–0.005) and may not contribute to wider recruitment based on biophysical models of larval movement. Unfortunately, pedigree analyses lacked power to further dissect fine-scale recruitment processes including self-recruitment. Our results support the management of disjunct populations as separate stocks and the protection of source populations among open water beds. The application of DAPC and parentage analyses in the current study provided valuable insight into their potential power to determine population connectivity in marine species with larval dispersal.

scholarly journals Multiperiod Hierarchical Location Problem of Transit Hub in Urban Agglomeration Area

2017 ◽  
Vol 2017 ◽  
pp. 1-15
Author(s):  
Ting-ting Li ◽  
Rui Song ◽  
Shi-wei He ◽  
Ming-kai Bi ◽  
Wei-chuan Yin ◽  
...  
Keyword(s):  
Travel Time ◽  
Urban Population ◽  
Location Problem ◽  
Clonal Selection ◽  
Urban Agglomeration ◽  
Population Migration ◽  
Clonal Selection Algorithm ◽  
Rapid Urbanization ◽  
Transportation Demand ◽  
Hierarchical Location

With the rapid urbanization in developing countries, urban agglomeration area (UAA) forms. Also, transportation demand in UAA grows rapidly and presents hierarchical feature. Therefore, it is imperative to develop models for transit hubs to guide the development of UAA and better meet the time-varying and hierarchical transportation demand. In this paper, the multiperiod hierarchical location problem of transit hub in urban agglomeration area (THUAA) is studied. A hierarchical service network of THUAA with a multiflow, nested, and noncoherent structure is described. Then a multiperiod hierarchical mathematical programming model is proposed, aiming at minimizing the total demand weighted travel time. Moreover, an improved adaptive clonal selection algorithm is presented to solve the model. Both the model and algorithm are verified by the application to a real-life problem of Beijing-Tianjin-Hebei Region in China. The results of different scenarios in the case show that urban population migration has a great impact on the THUAA location scheme. Sustained and appropriate urban population migration helps to reduce travel time for urban residents.

Sign in / Sign up

Export Citation Format

Share Document