Focus on the important tourism cities and agricultural and pastoral areas relying on Sichuan Tibet and Qinghai Tibet line on the Qinghai Tibet Plateau, record and collect the image data of the current situation of node cities and villages along the line, the planning and construction of urban tourism and rural tourism, evaluate the supporting capacity of existing important node cities and villages for the construction of world tourism destinations on the Qinghai Tibet Plateau, and put forward the optimization and improvement scheme of urban and rural tourism development path and supporting cities of important nodes of world tourism destinations. The data sources are VR panoramic camera, panoramic HD vehicle recorder and digital camera. After collecting the data, the data are classified according to different collection locations. The data has been checked for many times to ensure its authenticity. It is an important part of the image database of the urban and rural tourism resource support system on the Qinghai Tibet Plateau.
FAN Shucai
Through the investigation of tourist spots, tourist routes and tourist areas at different levels, form photos and video data of tourism resources, tourism services and tourism facilities of scenic spots, scenic spots, corridors and important tourism transportation nodes, tourism villages and tourism towns, record the tourism development status, find problems in tourism development, and form corresponding ideas for the construction of world tourism destinations; The data sources are UAV, tachograph and camera, mobile phone and GPS, and are divided into different folders according to scenic spots and data categories; The data has been checked for many times to ensure its authenticity; This data can provide a traceable basis for the construction of world tourism destinations on the Qinghai Tibet Plateau.
SHI Shanshan
By archaeological investigation and excavation in the Tibet Plateau and neighbouring areas, we discovered Xichengyi site, Jinchankou site, Shannashuzha site, Jiangxifen site, Zongri site, Bangga site and so on. In this dataset, there are some basic informations about these sites, such as location, longitude, latitude, altitude, material culture and so on. On this Basis, we identified and analysed stone artifacts, animal remains, plant fossil, sedimentary sample, and obtained a batch of dating data of radiocarbon dating; pollen data; identification and isotopic composition and quality indicators of animal remains and plant fossil. At the same time, the relevant animal and plant remains and isotopes in the Tibet Plateau and neighbouring areas are sorted out. Based on natural geographical factors and sites in different periods, the method of realizing cumulative connection between nodes under the control of the lowest cost uses GIS(R language) tool to carry out spatial numerical calculation, and the result is used as the communication route in prehistoric times (Neolithic-bronze age). The shape of the route developed from the northeast-east-southeast-southwest edge of Neolithic Age in crescent shape to the trend of network development from the edge to the hinterland of Bronze Age, which is a manifestation of the gradual evolution from the exchange of plateau edge to the exchange of edge-hinterland, which is constantly strengthened. A total of 49 dung samples of grazing livestock (30 yak dung samples, 11 horse dung samples and 8 sheep dung samples) were collected in the alpine meadow area of the eastern Qinghai-Tibet Plateau, and the pollen analysis of dung samples was carried out on the basis of regional vegetation investigation. This dataset provide important basic data for understanding when and how human lived in the Tibet Plateau and neighbouring areas during the Neolithic Age and the Bronze age.
DONG Guanghui , HOU Guangliang, YANG Xiaoyan
Through the investigation in selinco basin and Datong River and the excavation of sugE site, the basic information of longitude and latitude, distribution range, topographic characteristics, altitude, cultural attributes and cultural relics of 11 Paleolithic Mesolithic sites are obtained; In addition, the artificial relics, animal and plant remains and soil samples during the site excavation were scientifically collected, extracted and analyzed in the laboratory, and a batch of radiocarbon dating data, stone product measurement data and environmental test data were obtained. The data set enriches the information of Paleolithic sites on the Qinghai Tibet Plateau, provides an important basis for the construction of temporal and spatial framework and cultural sequence, and provides data support for the further study of prehistoric human activities and career patterns in the hinterland of the Qinghai Tibet Plateau.
ZHANG Xiaoling, ZHANG Dongju
This data set records the altitude elevation of the main tourist attractions in Qinghai Province from 2002 to 2020. The data are based on the main tourist attractions in Qinghai Province, such as thar temple, Qinghai Lake, Qutan temple, kambula National Forest Park, the former residence of the 10th Panchen Lama, Mengda Tianchi, longbaotan black necked Crane nature reserve, the source of the Yangtze River, Chaerhan Salt Lake, bird island, Huzhu Beishan National Forest Park, the source of the Yellow River and a Nimaqing mountain, Jinyintan grassland scenery, bukadaban peak, Kunlun mountain pass, BeiChan temple, Qinghai Museum, Laoye Mountain, Huzhu Beishan National Forest Park, Jiezi mosque, Wendu temple, xiazong temple, Xiaqiong temple, Youning temple, Riyue mountain, Daotang River, Longyang Gorge, Qinghai Lake Resort, Yuhuangge, Chaka Salt Lake, atomic City, Lijiaxia gorge, Nanzong temple, Longwu temple Maixiu forest farm, Tubo burial tomb, Dulan international hunting ground and Hoh Xil no man's land. The data are compiled from the statistical yearbook of Qinghai Province issued by Qinghai Provincial Bureau of statistics. The dataset contains 19 data tables: The elevation of the main tourist attractions in the province was in 2002 xls The elevation of the main tourist attractions in the province was in 2003 xls The elevation of the main tourist attractions in the province was in 2004 xls The elevation of the main tourist attractions in the province was in 2006 xls The elevation of the main tourist attractions in the province was in 2007 xls The elevation of the main tourist attractions was in 2007 xls The elevation of the main tourist attractions in 2008 xls The elevation of main tourist attractions was in 2009 xls The elevation of main tourist attractions was in 2010 xls Elevation of main tourist attractions in 2011 xls Elevation of main tourist attractions in 2012 xls Elevation of main tourist attractions in 2013 xls Elevation of main tourist attractions in 2015 xls Elevation of main tourist attractions in 2016 xls Elevation of main tourist attractions in 2017 xls The elevation of the main tourist attractions will be in 2019 xls Elevation of main tourist attractions in Qinghai Province (2019) xls Elevation of main tourist attractions in Qinghai Province (2020) xls The elevation of the main tourist attractions in Qinghai Province (2020) is 1 xls , the data table structure is the same. For example, there are three fields in the elevation (2003) data table of major tourist attractions in the province: Field 1: name of tourist attraction Field 2: altitude (m) Field 3: geographic location
Qinghai Provincial Bureau of Statistics
This data set records the statistical data of tourism development in Qinghai Province from 1999 to 2020. Data according to the number at the end of the travel agency (a), at the end of the travel agency employees (people), the total number of hotel (a), tourist trips combined (people), tourism revenue (one hundred million yuan) cost (RMB) per capita, domestic tourists, international tourist foreign exchange income (usd), international travel costs ($) per capita, etc. The data are collected from qinghai Statistical Yearbook released by Qinghai Provincial Bureau of Statistics. The dataset contains 19 data tables, which are: Tourism development 1999-2005. XLS Development of tourism industry 20002006. XLS Development of tourism industry 20012007. XLS Development of tourism 20012008. XLS Development of Tourism 2005-2009. XLS Development of Tourism industry 2006-2010. XLS Tourism development 2007-2011. XLS Development of Tourism 2008-2012. XLS Development of Tourism industry 2009-2013 XLS Development of Tourism 2010-2014. XLS Development of Tourism 2011-2015. XLS Tourism development 2012-2016. XLS Tourism development 2013-2017. XLS Development of Tourism 2014-2018. XLS Development of Tourism 2015-2020. XLS Tourism 2000-2001. XLS Tourism 2001-2002. XLS Tourism 2002-2003.xls Tourism 2004 year. XLS The data table structure is similar. For example, the tourism data table 2000-2001 has three fields: Field 1: indicator Field 2:2000 Field 3:2001
Qinghai Provincial Bureau of Statistics
This data set records the statistics of the number of overnight guests and foreign exchange income of tourism hotels in Qinghai Province from 1981 to 1999. The data are divided by industry, region, affiliation and registration type. The data are collected from the statistical yearbook of Qinghai Province issued by the Bureau of statistics of Qinghai Province. The data set consists of three data tables The number of overnight guests and foreign exchange income in foreign hotels 1981-1998.xls The number of overnight guests and tourism foreign exchange income of foreign hotels in Qinghai Province, 1981-1999.xls The number of overnight foreign tourists in hotels of Qinghai Province by country and region, 1998-1999.xls The data table structure is the same. For example, there are seven fields in the 1981-1998 data table of the number of overnight guests and foreign exchange income from tourism Field 1: 1981 Field 2: 1993 Field 3: 1994 Field 4: 1995 Field 5: 1996 Field 6: 1997 Field 7: 1998
Qinghai Provincial Bureau of Statistics
The data set records the statistical data of the ranking of the main source areas of tourists from Qinghai province to Qinghai province from 2012 to 2020. The data are divided by the source areas of tourists from Gansu, Jiangsu, Guangdong, Xinjiang, Shaanxi, Henan, Beijing, Sichuan, Shandong and Shanghai. The data are collected from qinghai Statistical Yearbook released by Qinghai Provincial Bureau of Statistics. The dataset contains eight data tables, which are: Main source of tourists into Qinghai ranked in 2012. XLS Main source of tourists into Qinghai ranked in 2018. XLS Main source of tourists into Qinghai ranked in 2013. XLS Main source of tourists into Qinghai ranked in 2014. XLS Main source of tourists into Qinghai ranked 2015. XLS The main source of tourists into Qinghai ranked in 2016. XLS Main source of tourists into Qinghai ranked in 2017. XLS Main source of tourists into Qinghai ranked 2020. XLS The data table structure is the same. For example, there are four fields in the 2012 data table of the ranking of main source of tourists in Qinghai: Field 1: region Field 2: Out-of-province visitors Field 3: Proportion Field 4: rank
Qinghai Provincial Bureau of Statistics
The data set records the statistics of the number of self-driving cars entering Qinghai province from 2008 to 2020. The data are divided by industry, region, affiliation and registration type. The data are collected from qinghai Statistical Yearbook released by Qinghai Provincial Bureau of Statistics. The dataset contains 12 data tables, which are: Enter Qinghai autonomous driving volume in 2018. XLS Enter qinghai autonomous driving volume and ranking 2009. XLS Enter qinghai autonomous driving volume and ranking 2010 2010. XLS Enter qinghai autonomous driving volume and ranking 2011. XLS Enter qinghai autonomous driving volume and ranking in 2012. XLS Enter qinghai autonomous driving volume and ranking in 2013. XLS Enter qinghai autonomous driving volume and ranking in 2014. XLS Enter qinghai autonomous driving volume and ranking 2015. XLS Enter qinghai autonomous driving volume and ranking 2016. XLS Enter qinghai autonomous driving volume and ranking 2008. XLS Enter qinghai autonomous driving volume and ranking 2017. XLS Enter qinghai autonomous driving volume and ranking 2020. XLS The data table structure is the same. For example, there are three fields in the 2018 data table of autonomous driving in Qinghai Province: Field 1: Vehicle source land Field 2: Number of self-driving cars Field 3: Year-over-year increase
Qinghai Provincial Bureau of Statistics
The data set records the statistics of the number of foreign tourists received by Qinghai Province from 2000 to 2020 (by country), and the data are divided by the origin of Japan, South Korea, Indonesia, Malaysia, the Philippines, Singapore, Thailand, the United Kingdom, France and other countries. The data are collected from qinghai Statistical Yearbook released by Qinghai Provincial Bureau of Statistics. The dataset contains 19 data tables, which are: The number of foreign tourists received by country in 2000-2001. XLS Number of foreign tourists received by country in 2001-2002. XLS Number of foreign tourists received by country in 2003-2005. XLS The number of foreign tourists received by country in 2004-2006. XLS Number of foreign tourists received by country in 2005-2007. XLS Number of foreign tourists received by country in 2005-2008. XLS Number of foreign tourists received by country in 2006-2009. XLS Number of foreign tourists received by country 2007-2010. XLS Number of foreign tourists received by country 2008-2011. XLS The number of foreign tourists by country in 2011-2012. XLS Number of foreign tourists received by country in 2012-2013. XLS The number of foreign tourists received by country in 2013-2014. XLS Number of foreign tourists received by country in 2014-2015. XLS The number of foreign tourists received by country in 2015-2016. XLS The number of foreign tourists received by country in 2016-2017. XLS The number of foreign tourists received by country in 2017-2018. XLS The number of foreign tourists received by country in 2018-2020. XLS Number of foreign tourists in 2004. XLS Number of foreign tourists received by country by 2002-2003.xls The data table structure is the same. For example, the number of foreign tourists received by country for 2000-2001 has three fields: Field 1: Country region Field 2:2000 Field 3:2001
Qinghai Provincial Bureau of Statistics
This data set records the statistics of the number of overnight foreign tourists received by urban tourism accommodation facilities in Qinghai Province from 1999 to 2000. According to the country and year, China covers Japan, Philippines, Singapore, Thailand, Indonesia and other Asian countries, and the United States, Canada and other American countries. The data are collected from the statistical yearbook of Qinghai Province issued by the Bureau of statistics of Qinghai Province. The data set contains a data table, which is: the number of overnight foreign tourists by country (region) in urban tourism accommodation facilities, 1999-2000.xls. The data table structure is the same. For example, there are two fields in the data table from 1999 to 2000 Field 1: year Field 2: Country / Region
Qinghai Provincial Bureau of Statistics
This data set records the statistical data of the number of overnight visitors and foreign exchange income from tourism in urban tourist accommodation facilities of Qinghai Province from 1990 to 2000. The data are divided by the total number of visitors (person time), the total number of person days (person day) and foreign exchange income (ten thousand US dollars). The unit of foreign exchange income in 1990 is ten thousand yuan of foreign exchange voucher. The data are collected from the statistical yearbook of Qinghai Province issued by the Bureau of statistics of Qinghai Province. The data set contains a data table: the number of overnight visitors and foreign exchange income of tourism in urban tourism accommodation facilities, 1990-2000.xls. For example, the 1990-2000 data table has four fields: Field 1: year Field 2: number of people Field 3: amount Field 4: other
Qinghai Provincial Bureau of Statistics
The data set recorded the statistical data of the list of A-level scenic spots in Qinghai Province, and the data were divided into 4A level scenic spots, 3A level scenic spots and 2A level scenic spots. The data are collected from qinghai Statistical Yearbook released by Qinghai Provincial Bureau of Statistics. The dataset contains 15 data tables, which are: Directory of Qinghai A-Level Scenic Spots 2009. XLS, Directory of Qinghai A-Level Scenic Spots 2011. XLS, Directory of Qinghai A-Level Scenic Spots 2008. XLS, Directory of Qinghai A-Level Scenic Spots 2010. List of Qinghai A-Class Scenic Spots 2014. XLS, List of Qinghai A-Class Scenic Spots 2015. XLS, List of Qinghai A-Class Scenic Spots 2016. XLS, List of Qinghai A-Class Scenic Spots 2017. XLS, List of Qinghai A-Class Scenic Spots 2018. List of A-level Scenic Spots of Qinghai Province 2019. XLS, List of A-Level Scenic Spots of Qinghai Province (2020), List of A-Level Scenic Spots of Qinghai Province (2020) 1, List of A-Level Scenic Spots of Qinghai Province (2020) 2, List of A-level Scenic Spots of Qinghai Province (2020) 3. The data table structure is the same. For example, the 2009 table has two fields: Field 1: Scenic spot name Field 2: Address
Qinghai Provincial Bureau of Statistics
This data set records the statistical data of foreign investment and tourism in different regions of China (2001-2004), which are divided by year. The data are collected from the statistical yearbook of Qinghai Province issued by the Bureau of statistics of Qinghai Province. The data set contains four data tables with the same structure. For example, the data table in 2003 has five fields: Field 1: Province (city, district) Field 2: foreign contractual investment (USD 10000) Field 3: actual foreign investment (USD 10000) Field 4: number of tourists (10000 person times) Field 5: total foreign exchange earnings from tourism (US $100 million)
Qinghai Provincial Bureau of Statistics
The data set records the statistical data of tourism situation and ranking (2006-2010) of various regions in China, and the data are divided by year. The data are collected from the statistical yearbook of Qinghai Province issued by the Bureau of statistics of Qinghai Province. The data set consists of seven data tables with the same structure. For example, the data table in 2011 has four fields: Field 1: Province (city, district) Field 2: number of inbound tourists (10000 person times) Field 3: foreigners (10000 person times) Field 4: total foreign exchange earnings from international tourism (US $100 million)
Qinghai Provincial Bureau of Statistics
The dataset recorded statistics on tourism development by region in Qinghai province from 2010 to 2020, and included xining, Haidong, Haibei prefecture, Huangnan Prefecture, Hainan Prefecture, Goluo Prefecture, Yushu Prefecture, Haixi prefecture and Qinghai Lake Administration. The data are collected from qinghai Statistical Yearbook released by Qinghai Provincial Bureau of Statistics. The dataset contains 10 data tables with the same structure. For example, the 2012 data table has 4 fields: Field 1: region Field 2: Total tourism revenue Field 3: Number of tourists Field 4: Per capita expenditure
Qinghai Provincial Bureau of Statistics
"The data set records the opening up to the mountains of qinghai province in 2002-2020 statistical data, the data is in accordance with the nima QingFeng, each pull dandong peak, the two presidents of the peak, the new qingfeng-xiangguang fracture, the peak, wrong, the deep, yuzhu peak, jade virtual essential is peak, horse aperture, hubei ice, five xuefeng mountain, big xuefeng, mount tunggula, dragon ara peak, etc. The data are collected from qinghai Statistical Yearbook released by Qinghai Provincial Bureau of Statistics. The dataset contains 18 data tables with the same structure. For example, the table for 2019 has four fields: Field 1: Mountain name Field 2: Altitude Field 3: Mountain system Field 4: Geographic location"
Qinghai Provincial Bureau of Statistics
By archaeological investigation and excavation in the Tibet Plateau and neighbouring areas, we discovered Jinchankou site, Zongri site, Xinancheng cemetery, bangga site and Tshem gzhung kha thog. In this dataset, there are some basic informations about these sites, such as location, longitude, latitude, altitude, material culture and so on. On this Basis, we identified and analysed stone artifacts, animal remains and plant fossil, and obtained a batch of dating data of radiocarbon and optically stimulated luminescence dating;identification and isotopic composition and quality indicators of animal remains and plant fossil. At the same time, the relevant animal and plant remains and isotopes in the Tibet Plateau and neighbouring areas are sorted out. This dataset provide important basic data for understanding when and how human lived in the Tibet Plateau and neighbouring areas during the Neolithic Age and historical period.
DONG Guanghui , YANG Xiaoyan, Lü Hongliang,
By archaeological investigation and excavation in the Tibet Plateau and neighbouring areas, we discovered Jinchankou site, Zongri site, Xinancheng cemetery, bangga site and Tshem gzhung kha thog. In this dataset, there are some basic informations about these sites, such as location, longitude, latitude, altitude, material culture and so on. On this Basis, we identified and analysed stone artifacts, animal remains and plant fossil, and obtained a batch of dating data of radiocarbon and optically stimulated luminescence dating;identification and isotopic composition and quality indicators of animal remains and plant fossil. At the same time, the relevant animal and plant remains and isotopes in the Tibet Plateau and neighbouring areas are sorted out. This dataset provide important basic data for understanding when and how human lived in the Tibet Plateau and neighbouring areas during the Neolithic Age and historical period.
DONG Guanghui , YANG Xiaoyan, Lü Hongliang,
By archaeological investigation and excavation in the Tibet Plateau and neighbouring areas, we discovered Jinchankou site, Zongri site, Xinancheng cemetery, bangga site and Tshem gzhung kha thog. In this dataset, there are some basic informations about these sites, such as location, longitude, latitude, altitude, material culture and so on. On this Basis, we identified and analysed stone artifacts, animal remains and plant fossil, and obtained a batch of dating data of radiocarbon and optically stimulated luminescence dating;identification and isotopic composition and quality indicators of animal remains and plant fossil. At the same time, the relevant animal and plant remains and isotopes in the Tibet Plateau and neighbouring areas are sorted out. This dataset provide important basic data for understanding when and how human lived in the Tibet Plateau and neighbouring areas during the Neolithic Age and historical period.
DONG Guanghui , YANG Xiaoyan, Lü Hongliang,
By archaeological investigation and excavation in Tibetan Plateau, we discovered 8 Paleolithic-Epipaleolithic sites, including Baishiya karst cave, Jiangjunfu site, Meilongdapu cave, Xiaqulong site and so on. In this dataset, there are some basic informations about these sites, such as location, longitude, latitude, altitude, material culture and so on. On this Basis, we identified and analysed stone artifacts, animal remains and plant fossil, and obtained a batch of dating data of uranium series, radiocarbon and optically stimulated luminescence. This dataset provide important basic data for understanding when and how prehistoric human lived in the Tibetan Plateau during the Paleolithic.
ZHANG Dongju , CHEN Fahu, ZHANG Xiaoling
By archaeological investigation and excavation in Tibetan Plateau, we discovered 14 Paleolithic sites, including 151, Baishiya karst cave，Meilongdapu cave, Hejishihuotang and Tangda. In this dataset, there are some basic informations about these sites, such as location, longitude, latitude, altitude, material culture and so on. On this Basis, we identified and analysed stone artifacts, animal remains and plant fossil, and obtained a batch of dating data of uranium series, radiocarbon and optically stimulated luminescence. This dataset provide important basic data for understanding when and how prehistoric human lived in the Tibetan Plateau during the Paleolithic.
CHEN Fahu, ZHANG Dongju , LIU Xiangjun, HOU Guangliang
According to the characteristics of the Qinghai Tibet Plateau and the principles of scientificity, systematization, integrity, operability, measurability, conciseness and independence, the human activity intensity evaluation index system suitable for the Qinghai Tibet Plateau has been constructed, which mainly includes the main human activities such as agricultural and animal husbandry activities, industrial and mining development, urbanization development, tourism activities, major ecological engineering construction, pollutant discharge, etc, On the basis of remote sensing data, ground observation data, meteorological data and social statistical yearbook data, the positive and negative effects of human activities are quantitatively evaluated by AHP, and the intensity and change characteristics of human activities are comprehensively evaluated. The data can not only help to enhance the understanding of the role of human activities in the vegetation change in the sensitive areas of global change, but also provide theoretical basis for the sustainable development of social economy in the Qinghai Tibet Plateau, and provide scientific basis for protecting the ecological environment of the plateau and building a national ecological security barrier.
ZHANG Haiyan, XIN Liangjie, FAN Jiangwen, YUAN Xiu
1. Overview of data Based on the Google earth image data in 2012, the land use types of wetland parks were vectorized by visual interpretation method, which provided the data basis for wetland ecosystem service assessment. 2. Data content Land use types include wetland, farmland (corn, vegetables, wheat), water area, forest land, construction land, bare land, etc. Scale: 1: 50,000; Coordinate system: WGS84; Data type: vector polygon; Storage format: Dbf/Shp/Jpeg 3. Space-time range Coverage: Zhangye National Wetland Park; Total area: 46.02 square kilometers.
XU Zhongmin
Taking Landsat series data as the main data source, including KH in 1965 (only including Gurinai and Guaizi Lake), MSS in 1975, TM in 1990, 1995, 2006 and 2010, and ETM in 2000. Before information extraction, remote sensing images are preprocessed by image synthesis, mosaic, fusion, geometric correction and image enhancement. In the process of correction, ETM + image in 2000 is corrected by 1:100000 topographic map and used as reference image. The 4, 3 and 2 band standard pseudocolor synthesis scheme is selected for image synthesis; during correction, 7 × 8 control points are evenly selected on each image, and the average positioning error is less than 1 pixel, that is, the ground distance is less than 30m. In other years, the datum image of 2000 is used as the reference image for image registration, so that the pixels with the same name on different images have the same geographical coordinates. After correction and registration, the whole image maintains the 30 m spatial resolution of TM. Through field correction, the accuracy of qualitative analysis can be ensured to be over 95%.
XIAO Shengchun
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