DOI: 10.5281/zenodo.17429911
title: Dataset of Spatial - Pattern Evolution of Rural Settlements in Tongzhou District, Beijing, 1961–2030

description:  

Dataset of Spatial–Pattern Evolution of Rural Settlements in Tongzhou District, Beijing, 1961–2030

 

Wei Song1*, Huanhuan Li2

1. Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China

2. School of Geography and Tourism, Luoyang Normal University, Luoyang 471000, China

* Corresponding author. E-mail address: songw@igsnrr.ac.cn (W. Song).

 

Abstract: Based on a long-term series (1961–2015) of rural-settlement data for Tongzhou District, Beijing, this dataset integrates remote-sensing interpretation results, landscape-pattern metrics and 2030 simulation outputs to systematically reveal the size, spatial distribution and evolution of rural settlements. From 1961 to 2015 the number of settlement patches declined by 43.30 %, whereas total area increased by 146.64 % and patch shapes became continually more regular. The 2030 simulation indicates that diffuse expansion will dominate, adding about 40.25 km². The dataset can support rural-settlement planning, urban–rural land-use optimisation and new-type urbanisation policymaking.

Keywords: rural settlements; spatial pattern; landscape metrics; LTM model; Tongzhou District

 

1 Data sources and processing

1.1 Basic data

Table 1 Description of the basic datasets








Data type



Period



Source



Resolution/ accuracy



Main purpose





Rural-settlement RS data



1961



Declassified KeyHole imagery



2m



Extract early settlement outlines





Rural-settlement RS data



1980/2000/2015



Data Center for Resources & Environmental Sciences, CAS



30m



Acquire mid- and late-term distributions





Ancillary (population, GDP)



1980-2015



Tongzhou Statistical Yearbook, Beijing Statistical Yearbook



 



Analyse driving forces





Vector (roads, rivers, admin. boundaries)



2000/2015



Data Center for Resources & Environmental Sciences, CAS



30m



Landscape analysis & simulation constraints






 

1.2 Processing methods

(1) Quantity-change analysis

Remote-sensing interpretation: Radiometric and geometric correction of 1961 KeyHole imagery (polynomial rectification against the 1980 land-use map); interpretation keys established; 2 m data resampled to 30 m and unified to GCS_Krasovsky_1940.

Landscape metrics: Fragstats extracted NP, Mean Patch Size (MPS), etc.; ArcGIS computed Average Nearest-Neighbour Index (ANNI) and Kernel Density Estimation (KDE):

                                           (1)

where D₀ is observed mean distance, Dₑ expected distance under randomness, A minimum enclosing-rectangle area.

                                              (2)

where h is bandwidth, dᵢ distance from sample point to target.

LTM simulation: Townships as basic units; six drivers (distance to water, town, railway, etc.); urban land & water as constraints; artificial-neural-network training (30 000 iterations per round); 2030 expansion simulated; accuracy assessed with Kappa.

2 Core results

2.1 Settlement-size change (1961–2015)

Table 2 Settlement-size change in Tongzhou, 1961–2015








Metric



1961



1980



2000



2015



55-year change





Number of patches(NP)



417



365



341



291



-43.30%





Total area(TA,hm²)



9765.63



11061.85



13554.10



24086.39



+146.64%





Mean patch size(MPS,hm²)



23.42



30.31



39.75



82.77



+253.42%





Largest patch index(LPI)



2.32



2.35



5.69



5.42



+133.62%





Landscape shape index(LSI)



34.79



26.26



25.31



24.40



-29.87%





Mean shape index(SHAPE_MN)



1.79



1.44



1.47



1.62



-9.05%






2.2 Spatial-distribution characteristics

ANNI: 1961 (0.9649), 1980 (1.005), 2000 (1.0001), 2015 (0.9637)—all ≈1, indicating random distribution throughout the 55 years.

KDE peak (/km²): 1961 3.01, concentrated around old Tongzhou town (present Beiyuan, Zhongcang, Yuqiao sub-districts); 1980–2000 peak 2.34, “multi-core dispersion”; 2015 peak 3.44, concentrated at the junction of Lucheng, Xiji and Zhangjiawan towns and along main roads.

Evolution modes (1961–2015): diffusion (outward expansion from existing patches, ~60 %) dominant; aggregation (small patches merging into large ones) evident in Songzhuang (1961–1980) and Yongshun (1980–2000); extinction (conversion to urban land) mainly around urban fringes (e.g., Beiyuan sub-district 1961–1980).

2.3 2030 expansion simulation

Table 3 Key characteristics of 2030 settlement-expansion simulation








Parameter



Value



Key feature





Projected rural population 2030



530 000



Referenced from Beijing Master Plan (2016–2030)





Predicted expansion area



40.25km²



Estimated by population–land coefficient





Overall simulation accuracy



53.90%



Kappa validation; township-scale 41 %–60 %Kappa





Dominant expansion mode



Diffusion 90 %



Outward growth from current patches





No-/low-expansion zones



Eastern Xiji, southeastern Huoxian



Far from town centres





Priority expansion areas



Songzhuang, Lucheng, Huoxian



Clustering along Jingshen Expressway & 6th Ring Road






 

3 Data notes and applications

3.1 Limitations

1961 data after resampling show ~0.18 % area bias, possibly causing minor error in early settlement-size estimates; simulation does not account for sudden policies (e.g., new ecological red-lines), so 2030 results should be updated with latest planning adjustments.

3.2 Application directions

Planning practice: provides evidence for “shrinking & quality-improvement” strategies, e.g., prioritising integration of low-density, small settlements;

Policy analysis: supports evaluation of new-type urbanisation policies, e.g., quantifies cultivated land expected to be occupied (≈35 km², 2015–2030);

Academic research: offers a long-term baseline for investigating driving mechanisms, enabling multi-factor regression with population and economic data.