Evidence map›Paper›PMID 39687372›Full record

ArticleData in brief2024

Unlocking insights in real estate markets: Integrating geo-spatial data for comprehensive property valuation and urban planning.

Serkan Varol, Serkan Catma

Abstract read
In one paragraph

Article in Data in brief, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Serkan VarolEngineering Management and Technology Department, Serkan Varol, University of Tennessee at Chattanooga, TN 37403, USA.
Serkan CatmaDepartment of Business Administration, Serkan Catma, University of South Carolina Beaufort, Bluffton, SC 29910, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This article summarizes a database for analyzing the impact of structural and environmental characteristics on residential property values in Hamilton County, TN. The original dataset consists of house characteristics data for 873 residential sales between January 1, 2023, and September 25, 2023. Using Google's API tools and Point to Edge computations, several geographical variables-including the distance to green recreational areas, surrounding facilities, restaurants, air quality index, walk score-were gathered. The aggregated information can help forecast Hamilton County's housing market with accuracy and correctly assess the environmental impact on housing prices. More specifically, the value of any environmental amenity in the study area can be implicitly estimated using this dataset.

Indexed as

Air qualityGeo-spatial variablesHousing dataProximity to green recreational spacesReal estate marketsUrban planning

Identifiers

PMID39687372
PMCPMC11647156

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.