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A spatiotemporal dataset for knowledge discovery on
population, environment and development in China
Alt title:
1. Abstract
Descriptions of the spatial and temporal variations in population and their
interactions with the environment and development are highly required to better
respond to the population problems associated with social, political and
environmental issues. Here, we present a dataset for knowledge discovery on
correlations between population, environment and development in China. The dataset
comprises items of population, basic geography, climate, topography, landform,
land use and land cover, vegetation, natural resources, infrastructure, economy,
nighttime light. The data is expressed as raster or vector format covering a
remarkably long period from 1980 to 2010. The dataset is collected from multiple
international and national data-sharing canters, official statistics, etc. All of
the data items are quality controlled and unified into an identical dataset with
the same spatial scope, resolution and period using GIS techniques. The database
is expected to be useful in demographic and environmental studies such as
extracting the knowledge of the relationship between population and naturalsocial-economic conditions, simulating how population influences the environment
and society, etc.
(1) Population: This dataset contains 5 years (1995, 2000, 2003, 2005, 2010)
population distributions cover the whole land region in China. The data is
expressed as raster format with 1 km resolution and a projection of Albers.
Attribute information mainly includes population density (unit: number of people
per square kilometer). The source data are originally provided by Data Center for
Resources and Environmental Sciences, Chinese Academy of Sciences (RESDC)
(http://www.resdc.cn) and Data Sharing Infrastructure of Earth System Science
(http://www.geodata.cn).
(2) Basic Geography: This dataset contains vector data and attribute table about
boundary, county, river, railway and road of China. The source data are originally
obtained from National Geometrics Center of China (http://ngcc.sbsm.gov.cn) and
Data Sharing Infrastructure of Earth System Science (http://www.geodata.cn). The
spatial reference of the original data has been transformed to projection of
Albers.
1) Boundary: China’s land borders and provincial borders with a scale of 1:400
and a projection of Albers. The data is expressed as shapefile polygon. Attribute
information includes provinces’ CODE, NAME, AREA (m2) and PERIMETER (m). The
boundaries are produced in 1988 and different from the newest borders.
2) County: China’s county borders with a scale of 1:400 and a projection of
Albers. The data is expressed as shapefile polygon. Attribute information includes
county’ CODE, CNAME, ENAME, AREA (m2) and PERIMETER (m). The boundaries are
produced in 1993 and different from the newest borders.
3) Countyp: China’s county capital with a scale of 1:400 and a projection of
Albers. The data is expressed as shapefile point. Attribute information includes
county’ CODE, CNAME, ENAME, AREA (m2) and PERIMETER (m). The boundaries are
produced in 1993 and different from the newest borders.
4) Railway: China’s railway distribution with a scale of 1:400 and a projection
of Albers. The data is expressed as shapefile line. Attribute information mainly
includes RAILWAY_ID, CLASS, FNODE, TNODE, LENGTH (m). The railways are produced in
1988 and different from the newest railways.
5) Road: China’s road distribution with a scale of 1:400 and a projection of
Albers. The data is expressed as shapefile line. Attribute information mainly
includes Road_ID, FNODE, TNODE, LENGTH (m). The roads are produced in 1988 and
different from the newest roads.
(3) Climate: This dataset contains raster data of main climate element cover the
whole land region in China with 1 km resolution and a projection of Albers.
Projection transformation is applied to assure the dataset are with the same
spatial reference with other dataset. In addition, time serial data integration is
conducted to calculate the ten-year average climate conditions.
1) Precipitation: This dataset contains 21 years (1980-2000) and two ten-year
average (1980s, 1990s) of precipitation cover the whole land region in China.
Attribute information mainly includes precipitation (mm). The source data are
originally provided by Thematic Database for Human-earth System
(http://www.data.ac.cn).
2) Temperature: This dataset contains 21 years (1980-2000) and two ten-year
average (1980s, 1990s) of temperature cover the whole land region in China.
Attribute information mainly includes average temperature (mm), yearly highest
temperature (mm), yearly lowest temperature (mm). The source data are originally
provided by Thematic Database for Human-earth System (http://www.data.ac.cn).
3) Relative Humidity: This dataset contains an averaged relative humidity from
1956 to 2000 cover the whole land region in China. Attribute information mainly
includes relative humidity (%). The source data are originally provided by Chinese
Ecosystem Research Network (http://www.cerndata.ac.cn/).
4) Warm Index: This dataset contains an averaged warm index from 1956 to 2000
cover the whole land region in China. Attribute information mainly includes warm
index (-). The source data are originally provided by Chinese Ecosystem Research
Network (http://www.cerndata.ac.cn/).
(4) Topography: This dataset contains raster data of DEM, slope and aspect cover
the whole land region in China with 1 km resolution and a projection of Albers.
1) DEM: This dataset contains digital elevation data cover the whole land region
in China. Attribute information mainly includes elevation (m). The source data are
originally provided by Environmental and Ecological Science Data Center for West
China (http://westdc.westgis.ac.cn).
2) Slope: This dataset contains slope cover the whole land region in China.
Attribute information mainly includes slope gradient (%). This dataset is
calculated by maximum slope method based on DEM data stated above. The surface
analysis tool of ArcGIS 10.1 is used to derive slope gradient.
3) Aspect: This dataset contains aspect cover the whole land region in China.
Attribute information mainly includes aspect (°). This dataset is calculated by
maximum slope method based on DEM data stated above. The surface analysis tool of
ArcGIS 10.1 is used to derive aspect.
(5) Landform: This dataset contains China’s landform classification with a scale
of 1:400 and a projection of Albers. Attribute information includes GEOMOR_ID,
AREA (m2) and PERIMETER (m). The data is produced in 1994. The source data are
originally provided by Environmental and Ecological Science Data Center for West
China (http://westdc.westgis.ac.cn).
(6) Land use and Land Cover: This dataset contains 3 time serial China’s land use
and land cover (1980s, 1995, 2000) area a LUCC classification extracted from GLC
2000.
The data are with 1 km resolution and a projection of Albers.
1) Land use and land cover area: this data contains China’s land use and land
cover area of 1980s, 1995, 2000. Attribute information includes the area ratio of
land use and land cover type (%/km2). The LUCC code and its meaning are listed in
Table 1. The source data are originally obtained from Data Sharing Infrastructure
of Earth System Science (http://www.geodata.cn).
Land use and land cover of GLC 2000 is extracted from the global land use and land
cover. Attribute information of this data is land use and land cover
classification type. The source data is obtained from the International Scientific
& Technical Data Mirror Site, Computer Network Information Center, Chinese Academy
of Sciences. The data was initially developed by the GLOBAL LAND COVER 2000
Project, which is a collaboration of partners around the world with the general
objective of providing a harmonized land cover database across the world for the
year 2000.
(7) Vegetation: This dataset contains vegetation classification and vegetation
dynamic cover the whole land region in China with a projection of Albers.
1) Vegetation classification: China’s vegetation classification with a scale of
1:400. The data is expressed as vector and in the format of shapefile polygon.
Attribute information includes vegetation_ID, AREA (m2) and PERIMETER (m). The
boundaries are produced in 1979. They can only be used for scientific researches,
but not for demarcation.
2) Vegetation dynamics: This dataset contains 28 years (1982-2010) vegetation
index with a projection of Albers. This data is expressed as raster format. The
main attribute information includes Normalized Difference Vegetation Index (NDVI).
The NDVI data from 1982 to 2006 with a resolution of 8 km are integrated from
half-monthly GIMMS (Global Inventory Modelling and Mapping Studies) NDVI product.
The source GIMMS NDVI data is obtained from Environmental and Ecological Science
Data Center for West China (http://westdc.westgis.ac.cn). The NDVI data from 20072010 are integrated from monthly MODIS NDVI product, which are obtained from
International Scientific & Technical Data Mirror Site, Computer Network
Information Center, Chinese Academy of Sciences (http://www.gscloud.cn). In the
NDVI data, the normal value is from 0 to 1 and water pixels have a value of -10.
(8) Natural Resources: This dataset includes water resources, land resources and
forest resources. The data is expressed as raster format with 1km resolution and
projection of albers. Attribute information mainly includes amount of water
resources distribution, quality of the cultivated land, and NPP distribution. The
amount of water resources is acquired from the Data Sharing Infrastructure of
Earth System Science. The quality of the cultivated land in China is obtained from
the Data Sharing Infrastructure of Earth System Science. The original NPP data are
acquired from the LAADS Web of the Goddard Space Flight Center, NASA
(http://ladsweb.nascom.nasa.gov/index.html). The original data are integrated both
on spatial and time scale, and then transformed to the same projection with other
data.
(9) Infrastructure: This dataset contains two data items including the distance to
the railway and the distance to the river. The two data items are both expressed
as raster format with 1km resolution and a projection of Albers. The two item
cannot bedirectly achieved from existing observed data. To calculate the indicator
of distance to railway and distance to river, we firstly convert a raster dataset
with a spatial resolution of 1 km into a point feature. Then we overlay the
feature with the feature of river or railway, and calculate the nearest distance
for each point. The ‘Near’ analysis in the proximity analysis tools provided by
ArcGIS 10.1 is used to calculate the two indicators.
(10) Economy: This dataset contains 5 years (1995, 2000, 2003, 2005, 2010) Gross
Domestic Product (GDP) distributions cover the whole land region in China. The
data is expressed as raster format with 1 km resolution and a projection of
Albers. Attribute information mainly includes gross annual GDP value (unit: ten
million yuan per square kilometer). The source data are originally provided by
Data Sharing Infrastructure of Earth System Science (http://www.geodata.cn).
(11) Nighttime Light: This dataset contains 18 years China’s night time light
with 10 km resolution and a projection of Albers. The attribute information is
digital number with a range of 0 to 63. The source data is obtained from NOAA
national geophysical data center Earth Observation Group
(http://www.ngdc.noaa.gov/eog/). We extracted the nighttime light of China from
the original global scale data.
2. Keywords
o
Theme:population, environment, development, Population-environment-development,
knowledge discovery,
o
Place:China, Mainland,
o
Temporal:1956-2010,
o
Discipline:Geography, Human Geography,
3. Detail
1. Scale: 0
2. Project: +proj=longlat +datum=WGS84 +no_defs
3. Data volume: 7135MB
4. Data Format: text
4. Geographic Extent
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North: 53
-
West: 73
-
East: 134
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South: 21
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5. Temporal Range
0. Start: 1956-01-01T15:55:00
1. End: 2010-12-31T15:56:00
6. Citation
Wang LZ., Chen LJ, Zhu YQ. A spatiotemporal dataset for knowledge discovery
on population, environment and development in China. Cold and Arid Regions
Science Data Center at Lanzhou, 2014. Doi:10.3972/card.001.2015.db
7. Recommended Publications
8. DOI
o
10.3972/card.001.2015.db
9. Fund
10.
Limitation
0. The dataset can only be used for scientific researches, but not for
demarcation.
11.
Online Resources
0. ：http://card.westgis.ac.cn
1. ：http://card.westgis.ac.cn
12.
Thumbnail
13.
Resource Provider
0. Man:

Name: Wang Lizhe

Organization: Institute of Remote Sensing and Digital Earth, CAS

Address: China--Beijing--Beijing--No.9 Dengzhuang South Road, Haidian
District

Zip code: 100094
1. Man:

Name: Chen Lajiao

Organization: Institute of Remote Sensing and Digital Earth, CAS

Address: China--Beijing--Beijing--No.9 Dengzhuang South Road, Haidian
District

Zip code: 100094
2. Man:

Name: Zhu Yunqiang

Organization: Institute of Geographic Sciences and Natural Resources
Research, CAS

Address: China--Beijing--Beijing--11A, Datun Road, Chaoyang District

Zip code: 100101
14.
Metadata Author
0. Author:

Name: Wang Lizhe

Organization: Institute of Remote Sensing and Digital Earth, CAS

Address: --Beijing--Beijing--No.9 Dengzhuang South Road, Haidian District

Zip code: 100094

Email: [email protected]

Phone:
15.
Distributor
0. Man:

Name: Cold and Arid Regions Science Data Center

Organization: Cold and Arid Regions Environmental and Engineering Research
Institute, Chinese Academy of Sciences

Address: China--Gansu--Lanzhou--320 Donggang Road

Zip code: 730000

Email: [email protected]

Phone: 0931-4967287

Fax: