Data underlying the manuscript: Morphology, Cognition, and Behaviour - Identifying the Rural Heritage in a Chinese Historic Village Cluster
Datacite citation style:
Bai, Nan; Nourian, Pirouz; Huang, Weixin; Wang, Lu; Raoul, Bunschoten et. al. (2021): Data underlying the manuscript: Morphology, Cognition, and Behaviour - Identifying the Rural Heritage in a Chinese Historic Village Cluster. Version 1. 4TU.ResearchData. dataset. https://doi.org/10.4121/13564292.v1
Other citation styles (APA, Harvard, MLA, Vancouver, Chicago, IEEE) available at Datacite
Dataset
choose version:
version 2 - 2021-09-27 (latest)
version 1 - 2021-02-17
usage stats
2137
views
1
citations
22307
downloads
categories
geolocation
Anyi, Jiangxi, China
time coverage
2018-2020
licence
CC BY-SA 4.0
This is the research data for the manuscript "Morphology, Cognition, and Behaviour - Identifying the Rural Heritage in a Chinese Historic Village Cluster".
The following is the original abstract:As a response to the drastic changes happening in rural China in the past decades, in 2018, the government released a five-year national strategy to better develop and preserve the rural environment. During the process of rural vitalization, valuable rural heritage was to be identified before decision-making on planning. However, the places perceived as most important can differ from the ones mostly occupied and used by people. This study took Anyi Historic Village Cluster as a case study to empirically investigate villages by integrating three distinct yet related perspectives: 1) Morphology: space syntax was applied to find out the central places based on spatial accessibility; 2) Cognition: semi-structured interviews and cognitive mapping were conducted to distinguish the Lynchian “image of the villages”; 3) Behaviour: Wi-Fi positioning tracking was used to monitor the spatiotemporal patterns of human behaviour. Significant correlations were found among indicators in all three perspectives, which were combined to identify the most important places as local rural heritage, proving the necessity of integrating the three perspectives in practice rather than studying them apart. The proposed methodology can assist future rural planning decision-making on what to preserve, what to enhance, and how to benefit from development without losing the local rural identity.
The following is the original abstract:As a response to the drastic changes happening in rural China in the past decades, in 2018, the government released a five-year national strategy to better develop and preserve the rural environment. During the process of rural vitalization, valuable rural heritage was to be identified before decision-making on planning. However, the places perceived as most important can differ from the ones mostly occupied and used by people. This study took Anyi Historic Village Cluster as a case study to empirically investigate villages by integrating three distinct yet related perspectives: 1) Morphology: space syntax was applied to find out the central places based on spatial accessibility; 2) Cognition: semi-structured interviews and cognitive mapping were conducted to distinguish the Lynchian “image of the villages”; 3) Behaviour: Wi-Fi positioning tracking was used to monitor the spatiotemporal patterns of human behaviour. Significant correlations were found among indicators in all three perspectives, which were combined to identify the most important places as local rural heritage, proving the necessity of integrating the three perspectives in practice rather than studying them apart. The proposed methodology can assist future rural planning decision-making on what to preserve, what to enhance, and how to benefit from development without losing the local rural identity.
history
- 2021-02-17 first online, published, posted
publisher
4TU.ResearchData
language
zh-hans
funding
- National Key Research and Development Program of China (NO. 2018YFD1100303)
organizations
TU Delft, Faculty of Architecture and the Built EnvironmentTsinghua University
Technische Universität Berlin
DATA
files (32)
- 21,974 bytesMD5:
32276553c262ab808b3547c1d95f6392
all_矩阵编码查询.xlsx - 5,276,368 bytesMD5:
30484838264b324cc1f4e518ec27133e
AnyiTrial.ipynb - 512 bytesMD5:
10d635ffa7984d5995631071b8c92b8c
aps.csv - 3,651 bytesMD5:
e1ff30f192a905449047c3984ff37d04
basic_information_基本情况.sav - 177,483 bytesMD5:
a471dc394642d818a75b3706bd01ee03
bipartite graph.gh - 1,412,119 bytesMD5:
2fa920d6125951c99854ed5929efc228
Bipartite Spatial Network.ipynb - 55,488 bytesMD5:
1289e182cb7f2e766bba27d0999141e6
bipartite.csv - 114,079 bytesMD5:
44098a72e621129acb5e1b27d0587137
bipartite.gephi - 25,702 bytesMD5:
d0b8dedb7ee77ad61a3b5c220ea2eced
CognitiveMapping_for_drawing村落意向绘图表.xlsx - 732,359 bytesMD5:
0b6e595b1ec2f480389c5a3605b80643
CognitiveMapping_认知地图.3dm - 60,390 bytesMD5:
3811f1214f76a12a6208c1c12a5969b3
CognitiveMapping_认知地图.gh - 126,379,494 bytesMD5:
4e6795874b9a81f0170762d43ae5bf2d
dataall.csv - 89,710,190 bytesMD5:
e37c4dfa7a9d16d541e55ee4024216ba
datanew.csv - 1,763 bytesMD5:
a04478e633ae4ef88d9a44eb4c8d2c50
DF.csv - 31,265 bytesMD5:
318abbc00ea319661845d054bb454bf0
flowdate0.csv - 4,363 bytesMD5:
2a6ac07d5691ac8228e1de883a5c5b80
flowlocalhour.csv - 795,343 bytesMD5:
3437a209f7c57236e4875e99e430f0f9
flowlocaltime.csv - 8,228,764 bytesMD5:
56ecaba07ca903bf566b05779481f59f
flowlocaltm.csv - 266,676 bytesMD5:
cdcc8c925b8528957c32818140acbb43
flowtime.csv - 5,739,937 bytesMD5:
d4305279eb555294f23dd66c5fb6474e
Interview_Transcript_补充材料.pdf - 14,286,582 bytesMD5:
4645ef66706d11134b52267d25469064
interview_完整问卷.pdf - 15,959 bytesMD5:
de2edd184441494558da4ddc753efa06
key_places_关键场所.sav - 423,870 bytesMD5:
c0745c9d86d9cccb4de7a57df1c35a3f
link_table.xlsx - 14,410 bytesMD5:
099ca8e5831529e5a48e874d1d702f9d
locals_村民矩阵编码查询.xlsx - 44,794 bytesMD5:
8727282cbf899e9871c49d914b494a64
localsum.xlsx - 17,227,237 bytesMD5:
5556f62e2b25195b6f9a67f2b4e5cc58
master_thesis_NanBAI.pdf - 138,360 bytesMD5:
a33c19eeeb7de037ec4825b91a7de2b6
metrics1.csv - 16,532 bytesMD5:
f62f589c88a58914e26b421ed9ddbaa9
monitoring_of_AP_点位状态.xlsx - 13,783 bytesMD5:
d179f37286b73b2402662321de8ffa9e
nominated_metrics.csv - 14,812 bytesMD5:
ef8a4e35ce76c56c38515e5e357fd82f
non_locals_非村民矩阵编码查询.xlsx - 8,397,869 bytesMD5:
d8de4bc0ecb267f0abaab83aba143608
surface.3dm - 114,138 bytesMD5:
9e0d21a8d595bbf82fb284be1e943913
Synthesis.xlsx -
download all files (zip)
279,746,266 bytes unzipped