BibTex Citation Data :
@article{geoplanning40534, author = {Walter de Vries}, title = {Trends in The Adoption of New Geospatial Technologies for Spatial Planning and Land Management in 2021}, journal = {Geoplanning: Journal of Geomatics and Planning}, volume = {8}, number = {2}, year = {2021}, keywords = {Geospatial technologies; Spatial planning; Land Management}, abstract = { Changes in spatial planning and land management practices, regulations and operations have frequently relied on the uptake of innovations in geospatial technologies. This article reviews which ones the spatial planning and land management domains has effectively adopted and which new ones might potentially disrupt the domain in the near future of 2021 and beyond. Based on an extensive concept-centric trends synthesis and meta-review, the analysis demonstrates that whilst geospatial technologies are clearly gaining wider societal recognition and while private companies are indeed developing promising applications, its adoption in office work of public officials and public decision makers remains almost as limited as before. The potentially most disruptive technologies for the domain are however BIM, Block chain and Machine learning. }, issn = {2355-6544}, pages = {85--98} doi = {10.14710/geoplanning.8.2.85-98}, url = {https://ejournal.undip.ac.id/index.php/geoplanning/article/view/40534} }
Refworks Citation Data :
Changes in spatial planning and land management practices, regulations and operations have frequently relied on the uptake of innovations in geospatial technologies. This article reviews which ones the spatial planning and land management domains has effectively adopted and which new ones might potentially disrupt the domain in the near future of 2021 and beyond. Based on an extensive concept-centric trends synthesis and meta-review, the analysis demonstrates that whilst geospatial technologies are clearly gaining wider societal recognition and while private companies are indeed developing promising applications, its adoption in office work of public officials and public decision makers remains almost as limited as before. The potentially most disruptive technologies for the domain are however BIM, Block chain and Machine learning.
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