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The purpose of this study is to analyze the horizontal expansion of Burayu Town between 1990 and 2020. The study typically acts as a baseline for integrated spatial planning in small- and medium-sized towns, which will help to plan sustainable utilization of land.

Landsat5-TM, Landsat7 ETM+, Landsat5 TM and Landsat8 OLI were used in the study, along with other auxiliary data. The LULC map classifications were generated using the Random Forest Package from the Comprehensive R Archive Network. Post-classification, spatial metrics, and per capita land consumption rate were used to understand the manner and rate of expansion of Burayu Town. Focus group discussions and key informant interviews were also used to validate land use classes through triangulation.

The study found that the built-up area was the most dynamic LULC category (85.1%) as it increased by over 4,000 ha between 1990 and 2020. Furthermore, population increase did not result in density increase as per capita land consumption increased from 0.024 to 0.040 during the same period.

As a result of financial limitations, there were no high-resolution satellite images available, making it challenging to pinpoint the truth as it is on the ground. Including senior citizens in the study region allowed this study to overcome these restrictions and detect every type of land use and cover.

Data on urban growth are useful for planning land uses, estimating growth rates and advising the government on how best to use land. This can be achieved by monitoring and reviewing development plans using satellite imaging data and GIS tools.

The use of Random Forest for image classification and the employment of local knowledge to validate the accuracy of land cover classification is a novel approach to properly customize remote sensing applications.

This study aims to examine farmers' decision to use smartphone agricultural applications (SAAs) and how SAAs adoption impact their land transfer behaviors in terms of the current land transfer-in area (LTA) and the future willingness to renew land transfer-in after it expires (WTR).

This study provides empirical evidence on the relationship between farmers' use of SAAs and land transfer choice, using a field survey data of 752 rural farm households in 2020 from Sichuan province of China. The endogenous switching models are employed to address potential self-selection bias associated with voluntary SAAs use and to quantitatively examine the impacts of SAAs use on land transfer choice.

The empirical results reveal that SAAs significantly improves the probability of transfer-in of more land by 39.10%. We find SAAs use has heterogeneous impacts on land transfer-in choice in the groups of agricultural technology, extension service, marketing and credit. Besides, we also find that SAAs use exerts highly positive and significant impact on farmers with less land area transfer-in. Moreover, SAAs can increase the probability of farmers' willingness to renew the land transfer-in by 30%.

To the best of our knowledge, this study is the first to explore the quantitative relationship between the use of SAAs and farm households' land transfer choice. The findings of this work can provide policy-related insights to help government promote the development of digital applications in the agricultural sector.

Land value varies at a micro level depending on the location’s economic, geographical and political determinants. The purpose of this study is to present a comprehensive assessment of the determinants affecting land value in the Indian city of Thiruvananthapuram in the state of Kerala.

The global influence of the identified 20 explanatory variables on land value is measured using the traditional hedonic price modeling approach. The localized spatial variations of the influencing parameters are examined using the non-parametric regression method, geographically weighted regression. This study used advertised land value prices collected from Web sources and screened through field surveys.

Global regression results indicate that access to transportation facilities, commercial establishments, crime sources, wetland classification and disaster history has the strongest influence on land value in the study area. Local regression results demonstrate that the factors influencing land value are not stationary in the study area. Most variables have a different influence in Kazhakootam and the residential areas than in the central business district region.

This study confirms findings from previous studies and provides additional evidence in the spatial dynamics of land value creation. It is to be noted that advanced modeling approaches used in the research have not received much attention in Indian property valuation studies. The outcomes of this study have important implications for the property value fixation of urban Kerala. The regional variation of land value within an urban agglomeration shows the need for a localized method for land value calculation.

The purpose of this study is to conduct a thorough empirical investigation of the intricate relationship between urban housing sales prices and land supply prices in China, with the aim of elucidating the underlying economic principles governing this dynamic interplay.

Using monthly data of China, the authors use the asymmetry nonlinear autoregressive distributed lag (NARDL) model to test for nonlinearity in the relationship between land supply price and urban housing prices.

The empirical results confirm the existence of an asymmetric relationship between land supply price and urban housing prices. The authors find that land supply price has a positive and statistically significant impact on urban housing prices when land supply is increasing. Policymakers should strive to strike a balance between safeguarding residents’ housing rights and maintaining market stability.

Although the asymmetric effect of land supply price has been identified as a significant contributor in this study, it is important to note that the research primarily relies on time series data and focuses on analysis at the national level. Although time series data offer a macroscopic perspective of overall trends within a country, they fail to adequately showcase the structural variations among different cities.

To ensure a stable housing market and meet residents’ housing needs, policymakers must reexamine current land policies. Solely relying on restricting land supply to control housing prices may yield counterproductive results. Instead, increasing land supply could be a more viable option. By rationally adjusting land supply prices, the government can not only mitigate excessive growth in housing prices but also foster the healthy development of the housing market.

First, the authors have comprehensively evaluated the impact of land supply prices in China on urban housing sales prices, examining whether they play a facilitating or mitigating role in the fluctuation of these prices. Second, departing from traditional linear analytical frameworks, the authors have explored the possibility of a nonlinear relationship existing between land supply prices and urban housing sales prices in China. Finally, using an advanced NARDL model, the authors have delved deeper into the asymmetric effects of land supply prices on urban housing sales prices in China.

This paper aims to analyze the legal framework of land degradation in Asia and provide market shared liability as a new theory to solve a problem regarding the difficulty for judges to determine the percentage of compensation for corporations responsible for land degradation. This paper aims also presents a theory to solve the problem of the vacuum of legal responsibility theory, which can make corporations proportionally responsible in terms of causing land degradation.

This was done through legal research methods, mainly with systematical interpretation. The approach used in this paper is conceptual, statute and comparative approach.

By analyzing the related legal norms, it can be understood that in Asian countries, such as Indonesia, Thailand and Malaysia, there are regulations regarding land degradation. However, the regulations in these countries are not specific and tend to focus on nature conservation, which has an impact on handling land degradation. Therefore, it needs special regulation to deal with land degradation. One of the things that need to be regulated about land degradation is a market shared liability.

This research is limited to regulation in the Asia region. By analyzing the regulation, this paper will provide an analysis about the land degradation regulation mechanism in Asia and give an analysis about market shared liability as one of the solution to handling land degradation. Having the same ground rules will create synergies between countries in Asia to handle land degradation.

This paper is the first systematic legal research comparing regulations from three nations in Asia on land degradation and the first paper to provide market shared liability as a solution to handling land degradation.

This study aims to investigate key aspects of public ownership of land, expropriation and compensation laws and practices in Ethiopia with special reference to Burayu Town.

A mixed research technique of descriptive and analytic approach is applied in the research. This study used a purposive sampling technique to select case study counties and a systematic method for sampling households. Questionnaire surveys, focus group discussions, interviews and observations were used to collect empirical data. Average, percentage and paired-sample t-test analyses are used for quantitative data analysis.

Significant discrepancies exist between the expropriation laws and how property valuation and compensation are practiced in Ethiopia. The findings include the arbitrariness in designating public interest status to projects; unfair property valuation practice that neglects location factor to determine market value due to a skewed understanding of public ownership of land; and the assignment of property valuators who have no valuation expertise and proper knowledge of expropriation related laws. Findings revealed the socio-economic status of expropriated households has deteriorated due to the expropriation of their landholding.

It was difficult to locate the relocated persons as they were resettled in different localities. Furthermore, the town officers were not forthcoming to provide complete information on the expropriation and compensation procedures they followed. However, this study overcame the limitations through persistent requests and availing time for the data gathering.

The findings indicated the need to redefine relationships between public ownership of land, public interest and expropriation of landholding. A proper understanding of the triad will pave the way for better expropriation practice in Ethiopia and in countries where land is under public ownership.

The social implication of the study revealed that the socio-economic situation of relocated persons was adversely affected due to the poor implementation of laws.

The disparity between public ownership of land and the rights of citizens on landholding is misunderstood by policymakers. Research has shown for the first time the root cause for the discontent of expropriated persons in Ethiopia.

Unstructured data such as images have defied usage in property valuation for a long time. Instead, structured data in tabular format are commonly employed to estimate property prices. This study attempts to quantify the shape of land lots and uses the resultant output as an input variable for subsequent land valuation models.

Imagery data containing land lot shapes are fed into a convolutional neural network, and the shape of land lots is classified into two categories, regular and irregular-shaped. Then, the intermediate output (regularity score) is utilized in four downstream models to estimate land prices: random forest, gradient boosting, support vector machine and regression models.

Quantification of the land lot shapes and their exploitation in valuation led to an improvement in the predictive accuracy for all subsequent models.

The study findings are expected to promote the adoption of elusive price determinants such as the shape of a land lot, appearance of a house and the landscape of a neighborhood in property appraisal practices.

There is a long-standing debate about the relationship between land title registration and tenure security. Studies in the developing world point to a tenuous link between land registration and stable land tenure. The reason why people continue to register therefore becomes a mystery if tenure security is not entirely assured. This article focuses on the increase in property value as one such factor that induces title registration. Previous studies have quantified the economic impact of title registration on property values. However, the impact varies from city or country to another. The authors seek to investigate the extent of property value increment in Accra attributable to land title registration.

The authors statistically analyzed a data set from two institutions (First National Bank and the Lands Commission) in Ghana using a quantitative technique.

The authors discovered that, holding all other factors constant, the value of the land in Accra increases by 22.6% due to land title registration. This shows that lessees must register to enhance property values, even though the essential due diligence must be done to make sure the acquisition is free from liens and legal disputes.

This article highlights the implication of the findings for land administration as well as the practice of property valuation, development and brokerage in Ghana and Global South more broadly.

This is one of the first studies in Ghana to investigate the specific premium that housing markets put on land title registration.

Land value in urban areas in India is influenced by regulations, bylaws and the amenities associated with them. Planning interventions play a significant role in enhancing the quality of the neighbourhood, thereby resulting in a change in its value. Land is a distinct commodity due to its fixed location, and planning interventions are also specific to certain locations. Consequently, the factors influencing land value will vary across different areas. While recent literature has explored some determinants of land value individually, conducting a comprehensive study specific to each location would be more beneficial for making informed policy decisions. Therefore, this article aims to examine and identify the critical factors that impact the value of residential land in the National Capital Territory of Delhi, India.

The study employed a combination of semi-structured and structured interview methods to construct a Relative Importance Index (RII) and ascertain the critical determinants affecting residential land value. A sample of 36 experts, comprising property valuers, urban planners and real estate professionals operating within the National Capital Territory of Delhi, India, were selected using snowball sampling techniques. Subsequently, rank correlation and ANOVA methods were employed to evaluate the obtained results.

Location and stage of urban development are the most critical determinants in determining residential land values in the National Capital Territory of Delhi, India. The study identifies a total of 13 critical determinants.

A scenario planning approach can be developed to achieve an equitable distribution of values and land use entropy. A land value assessment model can also be developed to assist professional valuers.

There has been a lack of emphasis on assessing the impact of planning interventions and territorial regulation on land values in the context of Delhi. This study will contribute to policy decision-making by developing a rank list of planning-based determinants of land value.

The results indicate that land prices exert pressure on retail performance (RP) and that the enhancement of digital means has a positive effect on RP. Additionally, digital instruments (DI) play a significant moderating role in the relationship between land prices and RP.

This paper empirically examines the impact of land prices on RP using panel data from 239 Chinese cities between 2011 and 2022.

The use of lagged land prices as instrumental variables effectively alleviates endogeneity issues. Both two-stage least squares (2SLS) and generalized method of moments (GMM) regression results suggest that higher land prices are associated with improved RP. Further analysis reveals that the increase in land prices leads to scale effects, structural effects and technological effects, contributing to the enhancement of RP. The impact of land prices on RP becomes more pronounced in larger cities and economically developed regions experience the pressure from land prices earlier.

The findings of this study have practical implications for discussions on retail industry development, site selection for retail businesses and the establishment of sustainable mechanisms for expanding domestic demand.