Brief Introduction: In order to quantitatively reveal the surface water-heat flux exchange characteristics of the main underlying surface of the Haihe River Basin, and also provide the pixel-scale “ground truth value” for the verification of surface evapotranspiration by remote sensing, since 2006, the forest land in the northern mountainous areas of the Haihe River Basin has been successively Beijing Miyun) has established a multi-scale surface flux and meteorological observation network with farmland (Hebei Huailai), central suburban farmland (Beijing Daxing), and southern plain farmland (Hebei Guantao), covering the main underlying surface of the Haihe River Basin.
Number of Datasets: 34
The data includes the county-level data of characteristic agriculture distribution in the Qinghai Tibet Plateau, which lays the foundation for the spatial distribution and development of characteristic agriculture in the Qinghai Tibet Plateau. The data are from the development plan of Tibet Plateau characteristic agricultural products base (2015-2020), Qinghai province's 13th five year plan, Sichuan Province's 13th five year plan for agricultural and rural economic development, Xinjiang Uygur Autonomous Region's 13th five year plan for targeted poverty alleviation of agricultural characteristic industries (2016-2020), Yunnan Province's overall plan for plateau characteristic agricultural modernization（ 2016-2020), implementation opinions on fostering and strengthening characteristic agricultural industries in Gansu Province to boost poverty alleviation, China National Geographic Indication product network (http://www.cgi.gov.cn/home/default/), regional layout planning of characteristic agricultural products (2013-2020). The data is the distribution of county-level characteristic agriculture, realizing the spatialization of county-level characteristic agriculture. The data can be applied to the research on the spatial distribution of characteristic agriculture and the development of characteristic agriculture in the future.
2020-01-09 4717 22 View Details
This data set contains 2018 global forest fire case data for the whole year and 2019, including the forest fire in California in November 2018, the forest fire in Attica, Greece in July 2018, and the forest fire in Shanxi Province in March 2019. Case data. Specific data include: fire intensity data of the monitoring range and data of vegetation index changes before and after the disaster. The data set is mainly used to describe the occurrence, development, impact and recovery of major global forest fire events in the first half of 2018-2019. The data mainly comes from NASA official website and EM-DAT database, it was processed by statistical and spatial analysis methods using EXCEL and ArcGIS tools. The data source is reliable, the processing method is scientific and rigorous, and it can be effectively applied to global (forest fire) disaster case analysis research.
2019-09-29 505 12 View Details