Distribution Of Land Prices Research Articles

Lessons learned from spatiotemporal effect of COVID on the population density in the CBD

Alonso in 1964 developed the land use and transport interaction theory based on the bid and rent concept. It tells that the central core part of urban areas has the highest housing rental prices, and it gradually decays as it is further away from the centre. The city’s district is divided based on the distribution of land prices according to distance from the city centre. This fundamental relationship provides a basic insight into how people behave rationally subject to their living budgets. Based on this relationship, this paper aims to investigate the temporal and spatial changes in the de facto population of Seoul caused by coronavirus disease 2019 (COVID-19). The de facto population has declined significantly since 2020. A major decrease has been found in areas within 2.5 km of travel distance from the city centre. The de facto population decreased the most during the night hours (18:00–24:00) on weekdays and the daytime (10:00–18:00) on weekends. These findings could be postulated to foresee how people might select their housing locations in terms of transport costs in the post–COVID-19 era.

Land Price Classification Map in Jakarta Using Random Forest and Ordinary Kriging

This research provides information about land prices in Jakarta by classifying using the Random Forest method. Where Random Forest is a data mining technique that is usually used to perform classification and regression. Random Forest is one of the best classification methods. It is found that classification accuracy will increase dramatically as a result of voting to select class types and ensemble tree growth. The method helps in providing information about the classification of land prices with the class of land prices per meter less than IDR 15 million, land prices per meter with a price range of IDR 15 to 25 million and land prices per meter more than IDR 25 million. With a fairly good accuracy of 82%, this method can classify where the permeter land price data that is tested will match the predicted classification accurately. Classification is performed on unbalanced data which is then oversampled using the ADASYN method. Assisted by doing spatial interpolation with the Ordinary Kriging method using Semivariogram, information about the classification of land prices can be seen on the distribution of the Jakarta area map. Ordinary Kriging can predict the estimated price per meter of land around the area of land that has a known price. The Root Mean Square Error (RMSE) results of the best Semivariogram model are obtained from the lowest RMSE value, namely the Spherical model with a value of 1.014896e7. The contribution of this research is to provide information about a reliable classification method, namely Random Forest and Ordinary Kriging performance as a spatial analysis method that can predict land prices per meter at unknown points so as to provide information about the distribution of land prices in Jakarta with each price class.

A TALE OF TWO POLICIES: THE DISTRIBUTIONAL IMPACTS OF MIGRATION AND LAND POLICY IN CHINA

In this paper, we study the distributional impacts of regional land and migration policies on housing, land markets and resource re-allocation in the context of the Chinese economy. The distribution of both housing prices and population is endogenously determined in a general equilibrium framework. We calibrate the model into the Chinese economy during 2010–2015 to match certain key moments regarding migration flow and land supply policies among 278 prefectural cities. Counterfactual exercises suggest that a uniformly tightened land policy distracts population from flowing into large to median-size cities; hence, housing price growth slows down in large cities. A uniformly tightened migration policy leads to more population recipient cities at an overall smaller scale, which causes housing prices to grow in most cities. Housing and population distribution become less dispersed under both exercises. If land supply distribution becomes less dispersed, housing and land prices become lower in most cities, and land price distribution becomes more even.

The Design of the Benchmark Land Price Release and Management Information System Based on Webgis

The In this paper, on the premise of benchmark land price production data and, starting from the management and application direction of technology based on JavaScript, Java Web technology and ArcGIS for Server technology, the WebGIS system design, the MVC development mode, B/S (browser/Server) multi-tier architecture model design to achieve the collection of maps, land management, land price data query, data statistical analysis, and system integrated management and so on five big modules as one of the benchmark land price distribution and management information system.

Spatiotemporal pattern and coordination relationship between urban residential land price and land use intensity in 31 provinces and cities in China.

The trend towards efficient and intensive use of land resources is an inevitable outcome of current social development. The rational matching of urban land prices and land use intensity has become an important factor under accelerating urbanization, and promotes the healthy development of the social economy. Using data on residential land price and on land use intensity for 31 provinces and cities in China, we employ the E-G cointegration test and quadrant map classification to determine the coordination relationship between land price and land use intensity. We then employ HR coordination to calculate the coordination degree of land price and land use intensity, and classify the coordination type accordingly. Our results are as follows. (1) The spatio-temporal distribution of urban land price shows high variability with multiple maxima, and follows a decreasing trend from the southeast coastal area to the northwest inland area and the northeast. (2) The overall land use intensity is at or above the middle level, and shows large spatial differences between provinces, but the agglomeration between provinces is increasing. (3) From the perspective of the relationship between urban land price and land use intensity at the inter-provincial scale, we find that the land price and land use intensity are well coordinated, and the number of provinces has been dynamically changing during different development periods. There is an east-west difference in the spatial distribution of land price and land use intensity coordination level. Different provinces and cities with the same coordination stage show differences in their land price and land use intensity level.

Modeling fine-scale residential land price distribution: An experimental study using open data and machine learning

Modeling the fine-scale spatiotemporal distribution of residential land prices (RLPs) is the basis for scientifically allocating land resources, managing the residential market and improving urban planning. The accurate mapping of the RLP dynamics require reliable land price prediction models and data with fine spatial and temporal resolution. With the aid of point of interest (POI) data and nighttime light (NTL) images, this paper attempts to explore the ability of machine learning algorithms (MLAs) to model grid-level RLPs using the case of Wuhan in China. Several land price prediction models were built using five MLAs and various geographic variables. The experimental results show that the extra-trees regression algorithm and the radial basis function-based support vector regression algorithm perform best in Period Ⅰ (2010–2014) and Period Ⅱ (2015–2019), respectively; therefore, they were selected to estimate the RLPs of the grids without observations in the corresponding period. Based on the estimated results, we found that the spatial pattern of the RLP in Wuhan transitioned from monocentric to polycentric between the two periods, and RLPs grew rapidly near newly formed urban subcenters and waterscapes. The relative importance of the predictor variables shows that commercial and educational facilities are important determinants of the RLP distribution in Wuhan; moreover, the relative importance of natural amenities and education facilities increased over time, while that of commercial facilities and public transportation decreased slightly. The case of Wuhan confirms the feasibility of MLAs and openly accessible urban data in modeling fine-scale RLP distributions. Our proposed framework provides a new approach to monitor the urban land price dynamics accurately and closely, which is beneficial for improving the infrastructure layout and achieve smart city growth.

Modeling urban residential land price distribution using multi-source data and ensemble learning: A case of Wuhan City

Modeling urban residential land price distribution using multi-source data and ensemble learning: A case of Wuhan City

Exploring spatio-temporal hot spots of land price change with housing transaction data in Seoul

Abstract. Evaluating residential property prices or land values is quite important for urban planning and government taxation as well. But it is generally difficult to predict land values accurately due to the dynamics of land prices, particularly in urban areas. Urban land values are mostly affected by natural environmental changes and various social and economic factors (Colwell & Munneke, 1997). Also, such socio economic factors are influencing both temporal and spatial aspects of land value, and therefore spatio-temporal clusters of land price changes will show local variations of land values very well. Specifically, the spatio-temporal hot spots might indicate highly increasing demand of lands in the urban area. In those areas, regulation against real estate speculation must be needed from the public perspective because such areas might impact on other area land prices and ultimately national economic status. Therefore, analyzing spatio-temporal aspects of the land price is essential for efficient urban planning and policy making. In this study, we attempt to detect spatio-temporal hot spots which are constantly increasing the value of residential property among real estate. Although there are many types of differently designated lands including such as commercial, agricultural, and lands for other usage, we focus on the residential lands to estimate land values in this research. The reason for this is because residential house price is substantially increasing and becoming one of sensitive issues of Seoul house market. Therefore, poor people or younger generation cannot afford such high housing expenses in Seoul. Also, house transaction data is much larger than other land usage data, and therefore it can be utilized for estimating land values more precisely. From 2011 to 2016, over 1.8 million housing transactions of lease and sale happened in Seoul. This big data on housing lease and sale transactions indicates the value of each location where the transaction occurred. Specifically, we utilize spatial interpolation method including Kriging and differential local Moran’s I approach based on housing transaction data in Seoul. Housing transaction data includes every transaction for sales and leases of the house for the particular period. By applying these methodologies, we can visualize spatio-temporal clusters of highly increasing land prices and interpret significant clusters in terms of social factors. In fact, land price distribution has been widely discussed associated with smart growth and urban development (American Planning Association, 2002; Kaiser et al., 1995). However, most studies have focused on urban development and expansion, rather than the changes in the land price. Moreover, many studies have applied remote sensing approach to analyze urban land expansion (Xiao et al., 2006; Magigi & Drescher, 2010). Notably, Hu et al., (2013) applied IDW to interpolate and estimating land prices with land samples. However, IDW has a shortcoming to interpolate the value which is distant from the sample points. In addition, even studies focusing on the land price have dealt with only one temporal period. From this research gap, we use the ordinary Kriging and differential local Moran’s I to detect and forecast local hot spots of land price changes. This research has conducted the following steps. At the first step, several transactions for the residential area are consolidated into a single land value indicator. Suppose that the residential rent consists of three factors that are housing price (P), deposit (D), and monthly rent (R). Each factor can be transformed into the value index (V) by the transformation formula below. After calculating the land value index from the transformation, the global trend of the value index is overlaid on each period. Figure 1. Shows the mean value index increased from 2011 to 2016. Then, square cells regularly spaced by 100 meters are generated over study area to perform the ordinary Kriging. After the ordinary Kriging, the land value index is assigned to each grid cell. Finally, differential local Moran’s I index is calculated based on the difference that value index change between each year. V = 0.75 * 0.005 * P + 0.005 * D + R As a result, the global trend of land value changes from 2011 to 2016 in Seoul is shown in Figure. 1. The mean value index is increasing constantly. The spatio-temporal hot spots of land price change are found where the value index increment exceeds the average value index increasing over Seoul. As a result, seven clusters are detected (Figure. 2).

Why do warehouses decentralize more in certain metropolitan areas?

Over the last decade, warehousing and distribution centers have decentralized to the urban peripheries where land is cheaper and readily available. This change in location patterns has been driven by the demand to build more modernized and larger facilities to accommodate an ever-increasing influx of freight. Since efficient freight movement is essential for the smooth functioning of metropolitan areas, decentralization should occur everywhere. However, this is not necessarily true. It is hypothesized that depending on the volume of goods movement and the spatial distribution of land prices, the extent of decentralization varies across metropolitan areas. This hypothesis is tested using 48 US metropolitan areas. Results provide robust evidence that high land prices push large warehouses away from central locations. When freight demand and land prices are not as high, the effect becomes insignificant. Indeed, not only is decentralization linked with large metro areas but also with very large warehouses.

The Dieng ‘hazardscape’: a political ecology of vulnerability to natural hazards in Java’s highlands

ABSTRACTThis research article describes the construction of vulnerability to natural hazards in the Dieng Plateau of Central Java, Indonesia. The Dieng Plateau is a volcanically hazardous landscape, featuring a series of craters with a history of recurrent phreatic eruptions and emission of poisonous gases. Drawing on four months of in-depth fieldwork, this article applies the ‘hazardscape’ as a conceptual lens to describe how economic necessity and political processes frame volcanic risk, and how this influences vulnerability. Vulnerability in Dieng is linked to its history of upland settlement, the unequal spatial distribution of land prices, and the impact of internal state-led territorialisation strategies. Territorialisation strategies are characterised by the spatial designation of certain areas as ‘hazardous’, a process that historically led to the relocation of upland Javanese farmers to the outer islands as part of the politically significant transmigration programme. However, these territorial zones were locally contested, leading to the reoccupation of hazardous land with mixed outcomes for conditions of vulnerability. By unpacking the political construction of risk, through the concepts of territoriality and the hazardscape, this article demonstrates how the utilisation of hazardous land can bring economic opportunity alongside disadvantage in Java’s volcanic landscapes.

Changes in the distribution of land prices in urban China during 2007–2012

This paper examines the changes in the prices of land parcels in urban China between 2007 and 2012. The average land price in 2012 is found to be 57%, 24% and 41% higher than that in 2007 for residential, industrial and commercial land parcels, respectively. However, this price gap is not uniform throughout the price distribution of each type of land. Using decomposition methods, we disentangle the distributional land price differentials between 2007 and 2012 into a composition effect attributable to the varying land characteristics and a coefficient effect due to changes in the gradients on the underlying land price function. We show that the contributions of the composition effect and the coefficient effect to raw price gaps vary with the part of the price distribution and also differ by the type of land.

A Study on the Method for the Classification of Homogeneous Land Price Areas*

The Official Announcement System of Land Price involves the announcement of the Reference Prices of 500,000 standard lots among a total of 32 million lots across the nation, followed by the assessment of the land prices of individual lots based on the Reference Prices of standard lots and the land price index table. Although it has been twenty five years since the introduction of the system, several problems still remain regarding the unequal distribution of standard lots, the imbalance between Announced Reference Prices and assessed individual lot prices and among assessed individual lot prices. Dividing lands into homogeneous land price areas (HLPAs) has previously been proposed; however, implementation of the method was difficult due to the difficulty in determining the proper spatial boundaries of the homogeneous price area. This study aims to propose a method for and examine the validity and effectiveness of utilizing computers to classify HLPAs, categorizing into the same group lands of the same usage and the same land-use zone within the same administrative area, regardless of the spatial proximity of lands. The result shows that it is possible to classify HLPAs in a prompt and consistent manner, and to sub-classify the price layers according to the regional land price distribution, fitting the characteristics of each region. This study demonstrates that the proposed method can enhance efficiency in allocating and distributing standard lots, while restoring the balance between the standard lot price and assessed individual lot prices, and among assessed individual lot prices. It also shows that the systematic utilization of market prices allows assessed land prices to be closer to the market price.

공시지가의 균형성 제고를 위한 유사가격권 구분방법의 실증 분석 연구

The Public Notification System of Land Price involves announcement of the Reference Land Price of 500,000 standard lots among a total of 32 million, followed by assessment of the land price of individual lots based on Reference Prices of standard lot and the Land Price Index Table. Although it has been twenty five years since the introduction of the system, several problems still remain regarding unequal distribution of standard lots, imbalance between Notified Reference Land Prices and individual lot prices, and among individual lot prices. Dividing lands into homogeneous price areas has previously been proposed; however, implementation of the method was made difficult due to the difficulty in determining the proper spatial boundaries of the homogeneous price area. This study aims to propose methods and verify the validity and effectiveness of utilizing computers to classify the homogeneous price, categorizing lands into groups of land located in the same administrative area, with the same usage in the same zone, regardless of the spatial proximity of the land. The result shows that it is possible to classify the Homogeneous Land Price Area in a quick, consistent manner, and to sub-classify the price layers according to the regional land price distribution, fitting the characteristics of each region. This study demonstrates that the proposed method can enhance efficiency in allocating and distributing standard lots, while restoring the imbalance between prices of standard and individual lots, and those among individual lots. It also shows that systematic utilization of real transaction prices allows assessed land price to be closer to the market price.

A GIS-Based Web Approach for Serving Land Price Information

Participants in the land market are usually hampered to browse and analyze the land price information due to the lack of information sources and available analysis tools. A service-oriented GIS-based web system was developed to provide a practical solution, its essential data sources contain basic geographic elements and benchmark land price (BLP)-related information. Core models for land price analysis were implemented, including land price index, spatial distribution, and parcel appraisal. The system was developed based on a four-level Browse Server (B/S) architecture using GIS and web service technologies, which enables the publishing, browsing, and analysis of the land price information via the Internet. With effective functionalities, the system has been employed in a project for updating BLP in a case study city located in China. The main advantage of the GIS-based web approach lies in its integration of spatial-temporal analysis models and web GIS technology, which allows more investors and administrators with limited domain knowledge to obtain further understanding on the change pattern and spatial distribution of land price by an online means. The experience in the case study city demonstrates that the approach has strong practicality for land price information services.

Modeling land price distribution using multifractal IDW interpolation and fractal filtering method

Characterizing the spatial distribution of urban land price is essential for improving urban planning and management, as well as for effectively modeling and predicting changes in urban land use. Previous studies have shown that in using conventional geostatistics methods to characterize the local structure of land price, there is controversy regarding the effectiveness of interpolation. In this paper, a recently developed Multifractal Inverse Distance Weighted (MIDW) interpolation method is applied to characterize the spatial structure of land price, and a spectrum analysis method (S–A) based on a fractal filtering technique is applied to separate the singularity from the background of land price distribution; these methods are applied to a study site in the city of Wuhan (China). It is shown that the MIDW interpolation method is a valid and effective alternative for characterizing land price distribution by comparison with ordinary IDW and Kriging methods. Based on deviation and parameters, the results of the MIDW method not only fit better with the surveyed values, but they also incorporate both the singularity and spatial association in data interpolation. The singularity of land price, which could be attributed to local special landscapes, such as the Yangtze River and East Lake, was successfully separated from its background by the S–A method. The background, which represents the overall spatial trend of land price distribution, was reclassified by the fractal concentration–area method. The derived singularity and background will better aid the decision-making process for urban planning.

POWER LAWS IN REAL ESTATE PRICES DURING BUBBLE PERIODS

How can we detect real estate bubbles? In this paper, we propose making use of information on the cross-sectional dispersion of real estate prices. During bubble periods, prices tend to go up considerably for some properties, but less so for others, so that price inequality across properties increases. In other words, a key characteristic of real estate bubbles is not the rapid price hike itself but a rise in price dispersion. Given this, the purpose of this paper is to examine whether developments in the dispersion in real estate prices can be used to detect bubbles in property markets as they arise, using data from Japan and the U.S. First, we show that the land price distribution in Tokyo had a power-law tail during the bubble period in the late 1980s, while it was very close to a lognormal before and after the bubble period. Second, in the U.S. data we find that the tail of the house price distribution tends to be heavier in those states which experienced a housing bubble. We also provide evidence suggesting that the power-law tail observed during bubble periods arises due to the lack of price arbitrage across regions.

Multifractal characterization of urban residential land price in space and time

The spatial and temporal distribution of land price plays a key role in urban development and redevelopment processes. Identifying the features of land price distribution (LPD) is essential for improving urban planning and modeling land use changes. The purposes of this study were to determine if LPD can be characterized by multifractal models and to develop multifractal methods for characterizing the properties of LPD at various scales. An analysis was performed for a study site in Wuhan City, central China. Land prices were sampled in the years 2001, 2004, and 2007. The LPD patterns were represented by multifractal spectra estimated using the method of moments and characterized by five quantitative multifractal parameters. The results showed that the dimension spectra calculated from the LPD data in various regions and at different times indeed depict multifractality, the curves of the multifractal spectra are continuous, displaying the same characteristics of asymmetric and convex curves at the same times in different regions, where the common transitional trend was from shorter toward the left but much longer toward the right in 2001, comparatively symmetric with a slight right deviation in 2004, shorter toward the right but much longer toward the left in 2007, which implying continuous multifractality observed for LPD, and this trend indicates that the singularity of land prices in the different areas keeps step with urban development. In addition, the horizontal characteristics of the curves also differed in different development stages in the city. These results also demonstrated that we may characterize the spatial and temporal differences of different LPD patterns using multifractal methods, which may thus be utilized as a quantitative measure in understanding how land price affects changes in urban land use.

Self-organizing dual clustering considering spatial analysis and hybrid distance measures

Dual clustering performs object clustering in both spatial and non-spatial domains that cannot be dealt with well by traditional clustering methods. However, recent dual clustering research has often omitted spatial outliers, subjectively determined the weights of hybrid distance measures, and produced diverse clustering results. In this study, we first redefined the dual clustering problem and related concepts to highlight the clustering criteria. We then presented a self-organizing dual clustering algorithm (SDC) based on the self-organizing feature map and certain spatial analysis operations, including the Voronoi diagram and polygon aggregation and amalgamation. The algorithm employs a hybrid distance measure that combines geometric distance and non-spatial similarity, while the clustering spectrum analysis helps to determine the weight of non-spatial similarity in the measure. A case study was conducted on a spatial database of urban land price samples in Wuhan, China. SDC detected spatial outliers and clustered the points into spatially connective and attributively homogenous sub-groups. In particular, SDC revealed zonal areas that describe the actual distribution of land prices but were not demonstrated by other methods. SDC reduced the subjectivity in dual clustering.

Land price maps of Tokyo Metropolitan Area

The spatial distribution of land price is indicative of the urban structure of a region. However, since most information on land price is in the form of point data and not area data, a certain process must be established for the creation of a land price map. The authors have already developed a computer-aided system that enables the creation of precise land price maps on the basis of residential land price data for metropolitan areas in Japan at low cost but with precision. In this paper, the system is applied to Tokyo metropolitan area and creates several land price maps using the officially assessed land prices provided by the Japanese government and data from the land price surveys conducted by prefectural governments.

Land market mechanisms for preservation of space for coastal ecosystems: An agent-based analysis

This paper presents an agent-based model of a land market, which is used to explore the effects of land taxes on the land use in a coastal zone. The model simulates the emergence of land prices and urban land patterns from bottom-up via interactions of individual agents in a land market. A series of model experiments helps visualize and explore how economic incentives in a land market may influence the spatial distribution of land prices and urban developments, either leaving space for coastal ecosystems or not. We demonstrate that economic incentives do affect urban form and pattern, land prices and welfare measures. However, they may not always be sufficient to reduce the pressure on coastal ecosystems. Our results show that preservation of ecosystems may involve difficult trade-offs between economic and ecological priorities, as well as between healthy ecosystems and social equity. We also show how conventional economic modelling based on a representative agent, which is usually employed by policy makers, overestimates both environmental benefits and economic costs associated with the tax meant to preserve coastal ecosystems.