| Issue |
E3S Web Conf.
Volume 431, 2023
XI International Scientific and Practical Conference Innovative Technologies in Environmental Science and Education (ITSE-2023)
|
|
|---|---|---|
| Article Number | 07033 | |
| Number of page(s) | 8 | |
| Section | Environmental Economic, Policy and Law | |
| DOI | https://doi.org/10.1051/e3sconf/202343107033 | |
| Published online | 13 October 2023 | |
Design of methodology for estimation of parcel investment attractiveness using spatially adjusted predictive modelling
Moscow State University of Geodesy and Cartography, Scientific and research laboratory of urban technology and spatial development, Kazakova st. 13, 105064 Moscow, Russia
* Corresponding author: kurlov-av@yandex.ru
Determining investment attractiveness is an important task, in the meaning of economic and administration operation. The investment attractiveness of a land parcel can be assessed quantitatively as a value of dynamics in its sale price. In addition, spatial parameters can be accounted when estimating the investment attractiveness. To ensure prediction of land parcel sale prices and their dynamics we implemented ensemble regression analysis. Methodology was tested on publically accessible data of Russian cadastral agency. To elaborate an investment attractiveness clustering of cadastral units depending on price and spatial parameters, we conducted k-means clustering with Silhouette metric control.
© The Authors, published by EDP Sciences, 2023
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.