Zobrazeno 1 - 10
of 257
pro vyhledávání: '"Chuanrong Zhang"'
Publikováno v:
Journal of Maps, Vol 19, Iss 1, Pp 1-9 (2023)
ABSTRACTGovernment agencies have utilized Web Geographic Information Systems (GIS) dashboards to collect and disseminate spatial information on COVID-19. However, not all maps on these dashboards adhere to established cartographic principles. This ar
Externí odkaz:
https://doaj.org/article/44239a4fc5d74982b8b069a5513562a7
Publikováno v:
Frontiers in Public Health, Vol 11 (2023)
Externí odkaz:
https://doaj.org/article/d63a4dfe0c82477da1956c85be4c941c
Publikováno v:
Frontiers in Public Health, Vol 10 (2022)
Externí odkaz:
https://doaj.org/article/a676a051ca6f43a4ad15863d36f041cb
Publikováno v:
Remote Sensing, Vol 14, Iss 23, p 6117 (2022)
Implementation of a measuring, reporting, and verifying (MRV) framework is essential for reducing emissions from deforestation and forest degradation (REDD+). According to the United Nations Framework Convention on Climate Change, MRV can be regarded
Externí odkaz:
https://doaj.org/article/30375379401d49468563ce91040a4cde
Autor:
Sabina Bhandari, Chuanrong Zhang
Publikováno v:
Land, Vol 11, Iss 11, p 2074 (2022)
The rapid population growth and unplanned urbanization within Kathmandu Metropolitan City (KMC) have induced land use and land cover (LULC) changes that have exacerbated problems of air pollution and the Urban Heat Island (UHI) effect. These issues,
Externí odkaz:
https://doaj.org/article/d2cca33b88ab46d5b200ff48af9c9f9a
Autor:
Chuanrong Zhang, Xinba Li
Publikováno v:
Land, Vol 11, Iss 10, p 1692 (2022)
We are currently living in the era of big data. The volume of collected or archived geospatial data for land use and land cover (LULC) mapping including remotely sensed satellite imagery and auxiliary geospatial datasets is increasing. Innovative mac
Externí odkaz:
https://doaj.org/article/3181354c384f4bb0b645bb2c4573b16a
Publikováno v:
International Journal of Digital Earth, Vol 12, Iss 5, Pp 566-582 (2019)
The Markov chain random field (MCRF) model is a spatial statistical approach for modeling categorical spatial variables in multiple dimensions. However, this approach tends to be computationally costly when dealing with large data sets because of its
Externí odkaz:
https://doaj.org/article/d5dc1e35cb7a4bb1bdb6e80e29d685d9
Publikováno v:
International Journal of Digital Earth, Vol 11, Iss 6, Pp 609-634 (2018)
Spatiotemporal clustering is one of the most advanced research topics in geospatial data mining. It has been challenging to discover cluster features with different spatiotemporal densities in geographic information data set. This paper presents an e
Externí odkaz:
https://doaj.org/article/7d8ca31bf535431298f2c5cd882f6f5b
Publikováno v:
Zbornik radova Ekonomskog fakulteta u Rijeci : časopis za ekonomsku teoriju i praksu, Vol 36, Iss 1, Pp 11-28 (2018)
Economic development has largely contributed to the increment of CO2 emission. This study uses spatial econometric models to investigate the relationship between economic growth and carbon emission in China with data of 30 provinces of China durin
Externí odkaz:
https://doaj.org/article/aac4f3e3a38a43a889009c0012144ed9
Publikováno v:
GIScience & Remote Sensing, Vol 54, Iss 6, Pp 819-835 (2017)
Land-use maps are important references for urban planning and urban studies. Given the heterogeneity of urban land-use types, it is difficult to differentiate different land-use types based on overhead remotely sensed data. Google Street View (GSV) i
Externí odkaz:
https://doaj.org/article/4fc93d670d7e4e6996f51ada47d799f1