Applying a Land Valuation Model Using the Standard Plot Reference Method for Urban Land Valuation: A Case Study of Phung, Dan Phuong, Ha Noi, Vietnam
Publication: Journal of Urban Planning and Development
Volume 151, Issue 1
Abstract
Currently, land valuation is being interested in the process of amending the Land Law in Vietnam. Choosing an appropriate land valuation method is one of the important factors in determining the correct land value. The study conducted experiments with the standard parcel reference method to determine land value based on the land valuation experience in South Korea. The method is applied in Phung town, the economic center of Dan Phuong district, where the real estate market is currently flourishing. In the study area, 13 factors affecting land prices have been identified, as follows: (1) legal status of the land plot; (2) business advantages; (3) transportation; (4) location; (5) frontage; (6) area; (7) shape; (8) technical infrastructure; (9) environment; (10) education, healthcare; (11) security; (12) intellectual level; and (13) Feng Shui. This study selected 209 standard parcels for the mass land valuation of 3,786 land parcels. The obtained results showed that the highest-valued land parcel was 72.5 million VND located on Road 32, and the lowest-valued land parcel was 5.9 million VND placed at House number 4 on Thuy Ung Street. The research findings have been verified through the actual investigation value combined with the opinions of experts. The mass land valuation based on the standard plot reference method will contribute to improving the valuation of residential land in particular and the land valuation in general to meet the demand for issuing land prices close to the current market prices.
Get full access to this article
View all available purchase options and get full access to this article.
Data Availability Statement
Some or all data, models, or codes that support the findings of this study are available from the corresponding author upon reasonable request.
Acknowledgments
Thanks to the two anonymous reviewers their valuable comments in the previous version, which helped us to improve the quality of the paper.
References
Alfiyatin, A. N., R. E. Febrita, H. Taufiq, and W. F. Mahmudy. 2017. “Modeling house price prediction using regression analysis and particle swarm optimization case study: Malang, East Java, Indonesia.” Int. J. Adv. Comput. Sci. Appl. 8 (10): 323–326. https://doi.org/10.14569/IJACSA.2017.081042.
Aloqaily, M., R. Hussain, D. Khalaf, D. Slehat, and A. Oracevic. 2022. “On the role of futuristic technologies in securing UAV-supported autonomous vehicles.” IEEE Consum. Electron. Mag. 11 (6): 93–105. https://doi.org/10.1109/MCE.2022.3141065.
Ayalke, Z., and A. Sisman. 2022. “Nominal land valuation with best-worst method using geographic information system: A case of Atakum, Samsun.” ISPRS Int. J. Geo-Inf. 11 (4): 213. https://doi.org/10.3390/ijgi11040213.
Aziz, A., and M. M. Anwar. 2019. “Assessing land values and proximity using hedonic model—A case study of green town Gujrat, Pakistan.” Eur. J. Geogr. 10 (4): 149–164.
Bailey, M. J., R. F. Muth, and H. O. Nourse. 1963. “A regression method for real estate price index construction.” J. Am. Stat. Assoc. 58 (304): 933–942. https://doi.org/10.2307/2283324.
Bilgilioğlu, S. S., and H. M. Yılmaz. 2023. “Comparison of different machine learning models for mass appraisal of real estate.” Surv. Rev. 55 (388): 32–43. https://doi.org/10.1080/00396265.2021.1996799.
Bourassa, S., E. Cantoni, and M. Hoesli. 2010. “Predicting house prices with spatial dependence: A comparison of alternative methods.” J. Real Estate Res. 32 (2): 139–160. https://doi.org/10.1080/10835547.2010.12091276.
Cellmer, R., M. Belej, S. Zrobek, and M. Š. Kovač. 2014. “Urban land value maps—A methodological approach.” Geodetski Vestn. 58 (3): 535–551. https://doi.org/10.15292/geodetski-vestnik.2014.03.535-551.
Cellmer, R., K. Kobylińska, and M. Bełej. 2019. “Application of hierarchical spatial autoregressive models to develop land value maps in urbanized areas.” ISPRS Int. J. Geo-Inf. 8 (4): 195. https://doi.org/10.3390/ijgi8040195.
Cellmer, R., and S. Źróbek. 2017. The Cokriging method in the process of developing land value maps. In Proc., 2017 Baltic Geodetic Congress (BGC Geomatics). New York: IEEE.
Demetriou, D. 2016. “The assessment of land valuation in land consolidation schemes: The need for a new land valuation framework.” Land Use Policy 54: 487–498. https://doi.org/10.1016/j.landusepol.2016.03.008.
Doan, Q. C. 2023. “Determining the optimal land valuation model: A case study of Hanoi, Vietnam.” Land Use Policy 127: 106578. https://doi.org/10.1016/j.landusepol.2023.106578.
Duc, T. T. 2012. “Application of GIS in assigning state-regulated prices to land parcels.” J. Geod. Cartogr. 11 (3): 41–59. https://doi.org/10.46326/JMES.2021.62(1).04.
Everest, T., A. Sungur, and H. Özcan. 2022. “Applying the best–worst method for land evaluation: A case study for paddy cultivation in northwest Turkey.” Int. J. Environ. Sci. Technol. 19 (4): 3233–3246. https://doi.org/10.1007/s13762-021-03373-4.
Gouriéroux, C., and A. Laferrère. 2009. “Managing hedonic housing price indexes: The French experience.” J. Hous. Econ. 18 (3): 206–213. https://doi.org/10.1016/j.jhe.2009.07.012.
Gunes, T., and U. Yildiz. 2015. “Mass valuation techniques used in land registry and cadastre modernization project of Republic of Turkey.” FIG working week: From the Wisdom of the Ages to the Challenges of the Modern World. Sofia, Bulgaria: National Palace of Culture – Congress Centre Sofia.
Hair, J., R. Anderson, R. Tatham, and W. Black. 1998. Multivariate data analysis. 5th ed. Upper Saddle River, NJ: Prentice Hall International, Pearson College Div.
Hoa, N. Q. 2015. “Application of mass valuation methods in state management of land.” [In Vietnamese.] J. Dev. Integr. Vietnamese 22 (32): 39–53. https://doi.org/10.26459/hueunijard.v129i3C.5931.
Huan, N. T. 2009. Curriculum on land and other real estate valuation. [In Vietnamese.]. Ha Noi, Vietnam: Agricultural Publishing House.
IAAO (International Association of Assessing Officers). 2013. Standard on ratio studies. Kansas, MO: IAAO.
Igbaria, M., J. Iivari, and H. Maragahh. 1995. “Why do individuals use computer technology? A Finnish case study.” Inf. Manage. 29 (5): 227–238. https://doi.org/10.1016/0378-7206(95)00031-0.
Kim BongJoon, K. B., and K. T. Kim TaeYoung. 2016. “A study on estimation of land value using spatial statistics: Focusing on real transaction land prices in Korea.” Sustainability 8 (3): 203. https://doi.org/10.3390/su8030203.
Kolbe, J., R. Schulz, M. Wersing, and A. Werwatz. 2019. “Land value appraisal using statistical methods.” Z. für Immobilienökonomie 5: 131–154. https://doi.org/10.18452/19722.
Liu, B., B. Mavrin, D. Niu, and L. Kong. 2016. “House price modeling over heterogeneous regions with hierarchical spatial functional analysis.” In Proc., 16th Int. Conf. on Data Mining. New York: IEEE.
Mete, M. O., and T. Yomralioglu. 2021. “Implementation of serverless cloud GIS platform for land valuation.” Int. J. Digital Earth 14 (7): 836–850. https://doi.org/10.1080/17538947.2021.1889056.
Mize, S. 2017. Using regression analysis to predict single family home values/prices in the Belmont/Eastside areas of Pueblo. Pueblo, CO: Colorado State University-Pueblo.
Ngoc, B. T. C. 2021. Research, propose a mechanism to operate and effectively exploit the land price database of the land database system. Ministry-level scientific project. Hanoi, Vietnam: Hanoi Univ. of Natural Resources and Environment.
Nguyen, H. C. 2022. “Application of decision tree model in mass land valuation: A case study in Vung Tau city.” VNU J. Sci.: Earth Environ. Sci. 38 (1): 1–12. https://doi.org/10.25073/2588-1094/vnuees.4588.
Páez, A. 2009. “Recent research in spatial real estate hedonic analysis.” J. Geogr. Syst. 11 (4): 311. https://doi.org/10.1007/s10109-009-0103-y.
Pham, T. G., C. T. M. Tran, H. T. Nguyen, H. N. Trinh, N. B. Nguyen, H. K. N. Nguyen, T. T. Tran, H. D. Le, and Q. N. P. Le. 2022. “Land evaluation for Acacia (Acacia mangium × Acacia auriculiformis) plantations in the mountainous regions of central Vietnam.” Land 11 (12): 2184. https://www.mdpi.com/2073-445X/11/12/2184/pdf.
People’s Committee of Dan Phuong District. 2022. General report on land management in Phung town in 2022. [In Vietnamese.]
Phuong, T. T., H. V. Hoang, N. Van Viet, N. B. Ngoc, and H. Van Chuong. 2020. “Mass appraisal application for land valuation using regression model: A case study in the C zone of Nam hoi an project, Thang Binh district, Quang Nam Province, Central Vietnam.” Hue Univ. J. Sci.: Agric. Rural Dev. 129 (3C): 39–53. https://doi.org/10.26459/hueunijard.v129i3C.5931.
Quynh, T. D., and B. N. Hanh. 2015. “Hedonic model and software for land pricing and selecting key feature of land price.” J. Sci. Dev. 13 (6): 989–998.
Sampathkumar, V., M. H. Santhi, and J. Vanjinathan. 2015. “Evaluation of the trend of land price using regression and neural network models.” Asian J. Sci. Res. 8 (2): 182. https://doi.org/10.3923/ajsr.2015.182.194.
Son, N. P., L. Van Manh, N. T. Thuy, T. N. Vu, and N. T. Hanh. 2020. “Factors that affect land values and the development of land value maps for strengthening policy making in Vietnam: The case study of non-agricultural land in Quang Ninh province, Vietnam.” EQA-Int. J. Environ. Qualit. 36: 23–35. https://doi.org/10.6092/issn.2281-4485/9771.
Tezcan, A., K. Büyüktaş, and ŞTA Aslan. 2018. “Determination of parcel value number with detailed method in the land consolidation.” Asian Res. J. Agric. 9 (4): 1–10. https://doi.org/10.9734/ARJA/2018/43371.
Tezcan, A., K. Büyüktaş, and ŞTA Aslan. 2020. “A multi-criteria model for land valuation in the land consolidation.” Land Use Policy 95: 104572. https://doi.org/10.1016/j.landusepol.2020.104572.
Tomić, H., H. Matijević, S. Mastelić Ivić, and A. Rončević. 2006. “Development of land valuation system.” In Proc., 23th Int. FIG Congress: Shaping the Change. Munich, Germany: INTERGEO.
Tsutsumi, M., A. Shimada, and D. Murakami. 2011. “Land price maps of Tokyo metropolitan area.” Procedia-Social Behav. Sci. 21: 193–202. https://doi.org/10.1016/j.sbspro.2011.07.046.
Yeh, I.-C., and T.-K. Hsu. 2018. “Building real estate valuation models with comparative approach through case-based reasoning.” Appl. Soft Comput. 65: 260–271. https://doi.org/10.1016/j.asoc.2018.01.029.
Yilmazer, S., and S. Kocaman. 2020. “A mass appraisal assessment study using machine learning based on multiple regression and random forest.” Land Use Policy 99: 104889. https://doi.org/10.1016/j.landusepol.2020.104889.
Zakaria, F., and F. A. Fatine. 2021. “Towards the hedonic modelling and determinants of real estates price in Morocco.” Social Sci. Humanit. Open 4 (1): 100176. https://doi.org/10.1016/j.ssaho.2021.100176.
Zhou, G., Y. Ji, X. Chen, and F. Zhang. 2018. “Artificial neural networks and the mass appraisal of real estate.” Int. J. Online Eng. 14: 3. https://doi.org/10.3991/ijoe.v14i03.8420.
Zhou, W.-X., and D. Sornette. 2008. “Analysis of the real estate market in Las Vegas: Bubble, seasonal patterns, and prediction of the CSW indices.” Physica A 387 (1): 243–260. https://doi.org/10.1016/j.physa.2007.08.059.
Information & Authors
Information
Published In
Copyright
© 2024 American Society of Civil Engineers.
History
Received: Jan 19, 2024
Accepted: Jul 24, 2024
Published online: Oct 17, 2024
Published in print: Mar 1, 2025
Discussion open until: Mar 17, 2025
Authors
Metrics & Citations
Metrics
Citations
Download citation
If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.