This paper presents the results of a zoning study involving the metropolitan city of Naples, for the purpose of identifying the areas within which to perform a comparable search by applying the synthetic-comparative market value procedure of appraisal. Moreover, an analysis was carried out of the values of agricultural land reported by two official sources, i.e. average land values (VFM) and average agricultural values (VAM), and by an unofficial source, i.e. the values of the Observatory of Agricultural Values (VAO). The results show that for some area/crop quality combinations, the values recorded can provide a significant indication of the agricultural value to be estimated. Vice versa, for estimating the agricultural value of land cultivated with the most profitable crops, the official values showed to be unreliable, meaning that the appraisal requires an accurate field survey. As for the differences between the different homogeneous areas, VAO prove to be more reliable, while VAM are the least significant values.
{"title":"A zoning of the Metropolitan City of Naples and analysis of land values","authors":"P. Cupo, Erasmo Dell'Isola","doi":"10.36253/aestim-13580","DOIUrl":"https://doi.org/10.36253/aestim-13580","url":null,"abstract":"This paper presents the results of a zoning study involving the metropolitan city of Naples, for the purpose of identifying the areas within which to perform a comparable search by applying the synthetic-comparative market value procedure of appraisal. Moreover, an analysis was carried out of the values of agricultural land reported by two official sources, i.e. average land values (VFM) and average agricultural values (VAM), and by an unofficial source, i.e. the values of the Observatory of Agricultural Values (VAO). The results show that for some area/crop quality combinations, the values recorded can provide a significant indication of the agricultural value to be estimated. Vice versa, for estimating the agricultural value of land cultivated with the most profitable crops, the official values showed to be unreliable, meaning that the appraisal requires an accurate field survey. As for the differences between the different homogeneous areas, VAO prove to be more reliable, while VAM are the least significant values.","PeriodicalId":53999,"journal":{"name":"Aestimum","volume":"53 3","pages":""},"PeriodicalIF":0.8,"publicationDate":"2023-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138588281","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
L. Rocchi, L. Paolotti, Arianna Tiralti, Paolo Stranieri, A. Boggia
The Italian National Strategy for Sustainable Development plays an important role in the national implementation of the 17 Goals for sustainable development set globally through the 2030 Agenda of the United Nations. The achievement of such goals in Italy is linked to the strategic choices and objectives established at the national level. The purpose of this work is to monitor the performance of the 20 Italian regions in 4 of the 5 areas of the Agenda (People, Planet, Prosperity, Peace) over a period of time ranging from the implementation of the National Strategy to the post-pandemic. To do this, a set of representative indicators was created and a geographical sustainability assessment tool (SSAM) was used, which operates through a multicriteria analysis model perfectly integrated into a GIS environment. The results showed a strong regional variability and a radicalized North-South gap. Moreover, the monitoring between the different years (2017-2019-2021) showed the initially positive impact of the strategy, mainly due to the Planet dimension, but also the negative one that COVID-19 caused to all the regions, with different intensity depending on the dimensions considered.
{"title":"The Italian National Strategy for Sustainable Development and the Covid-19 impact: a regional analysis","authors":"L. Rocchi, L. Paolotti, Arianna Tiralti, Paolo Stranieri, A. Boggia","doi":"10.36253/aestim-14374","DOIUrl":"https://doi.org/10.36253/aestim-14374","url":null,"abstract":"The Italian National Strategy for Sustainable Development plays an important role in the national implementation of the 17 Goals for sustainable development set globally through the 2030 Agenda of the United Nations. The achievement of such goals in Italy is linked to the strategic choices and objectives established at the national level. The purpose of this work is to monitor the performance of the 20 Italian regions in 4 of the 5 areas of the Agenda (People, Planet, Prosperity, Peace) over a period of time ranging from the implementation of the National Strategy to the post-pandemic. To do this, a set of representative indicators was created and a geographical sustainability assessment tool (SSAM) was used, which operates through a multicriteria analysis model perfectly integrated into a GIS environment. The results showed a strong regional variability and a radicalized North-South gap. Moreover, the monitoring between the different years (2017-2019-2021) showed the initially positive impact of the strategy, mainly due to the Planet dimension, but also the negative one that COVID-19 caused to all the regions, with different intensity depending on the dimensions considered.","PeriodicalId":53999,"journal":{"name":"Aestimum","volume":"7 17","pages":""},"PeriodicalIF":0.8,"publicationDate":"2023-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138586520","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The aim of this study is to develop a value-based GeoValueIndex with AHP weights and GIS for the criteria of the Mersin University (MEU) Çiftlikköy Campus real properties, and it is referred to as the “GeoValueIndex” in this study. GeoValueIndex is a symbolic value that combines geographic and non-geographic features of real properties. The data of the real properties on the campus were collected and arranged for mass appraisal. One of the Multi Criteria Decision Analysis (MCDA) methodologies, Analytic Hierarchy Process (AHP), was used to weight the criteria. GeoValueIndex was calculated by multiplying each parcel’s geographic and non-geographic data by their weights and adding them. GeoValueIndex Map is obtained by associating GeoValueIndex and parcel in GIS software. GeoValueIndex of real properties save time, effort, and cost in mass appraisal processes. There are many techniques for doing GeoValueIndex operations, and the ones presented in this study are only proposals.
本研究的目的是为Mersin University (MEU) Çiftlikköy校园房产的标准开发一个基于价值的、AHP权重和GIS的GeoValueIndex，在本研究中称为“GeoValueIndex”。GeoValueIndex是一个结合了不动产的地理和非地理特征的符号值。收集校园内房产资料，整理整理，进行批量评估。多准则决策分析(MCDA)方法之一，层次分析法(AHP)，被用来衡量标准。GeoValueIndex是通过将每个包裹的地理和非地理数据乘以它们的权重并将它们相加来计算的。GeoValueIndex地图是在GIS软件中将GeoValueIndex与包裹关联得到的。不动产的GeoValueIndex在大规模评估过程中节省了时间、精力和成本。进行GeoValueIndex操作的技术有很多，本研究中介绍的技术只是建议。
{"title":"GeoValueIndex map of public property assets generating via Analytic Hierarchy Process and Geographic Information System for Mass Appraisal","authors":"F. B. Unel, L. Kuşak, Murat Yakar","doi":"10.36253/aestim-14110","DOIUrl":"https://doi.org/10.36253/aestim-14110","url":null,"abstract":"The aim of this study is to develop a value-based GeoValueIndex with AHP weights and GIS for the criteria of the Mersin University (MEU) Çiftlikköy Campus real properties, and it is referred to as the “GeoValueIndex” in this study. GeoValueIndex is a symbolic value that combines geographic and non-geographic features of real properties. The data of the real properties on the campus were collected and arranged for mass appraisal. One of the Multi Criteria Decision Analysis (MCDA) methodologies, Analytic Hierarchy Process (AHP), was used to weight the criteria. GeoValueIndex was calculated by multiplying each parcel’s geographic and non-geographic data by their weights and adding them. GeoValueIndex Map is obtained by associating GeoValueIndex and parcel in GIS software. GeoValueIndex of real properties save time, effort, and cost in mass appraisal processes. There are many techniques for doing GeoValueIndex operations, and the ones presented in this study are only proposals.","PeriodicalId":53999,"journal":{"name":"Aestimum","volume":"32 13","pages":""},"PeriodicalIF":0.8,"publicationDate":"2023-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138587671","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Maurizio D'Amato, G. Cucuzza, Giampiero Bambagioni
For International Valuation Standards (IVS) the estimate of the “forced sale” value implies a value judgment with reference to a degeneration of the market value basis, since “a forced sale” is a description of the situation in which the exchange takes place, not a distinct basis of value (IVS 2022, Par. 170.1).The paper illustrates a model that can be used to measure the difference between market value and forced sale value, as an aid to real estate valuations related to real estate executions. The proposed method is aimed at determining the difference between the estimated values and the final sales values obtained through the executive process, on the basis of the Short Table Market Comparison Approach (MCA). This method contributes more appropriately to the estimate of the value obtainable from the outcome of the enforcement process than arbitrary reductions in the market value. An application on a small sample of residential properties undergoing enforcement procedure highlights the possibility of using the Short Table MCA even with a limited number of comparables.
{"title":"Appraising forced sale value by the method of short table market comparison approach","authors":"Maurizio D'Amato, G. Cucuzza, Giampiero Bambagioni","doi":"10.36253/aestim-13808","DOIUrl":"https://doi.org/10.36253/aestim-13808","url":null,"abstract":"For International Valuation Standards (IVS) the estimate of the “forced sale” value implies a value judgment with reference to a degeneration of the market value basis, since “a forced sale” is a description of the situation in which the exchange takes place, not a distinct basis of value (IVS 2022, Par. 170.1).The paper illustrates a model that can be used to measure the difference between market value and forced sale value, as an aid to real estate valuations related to real estate executions. The proposed method is aimed at determining the difference between the estimated values and the final sales values obtained through the executive process, on the basis of the Short Table Market Comparison Approach (MCA). This method contributes more appropriately to the estimate of the value obtainable from the outcome of the enforcement process than arbitrary reductions in the market value. An application on a small sample of residential properties undergoing enforcement procedure highlights the possibility of using the Short Table MCA even with a limited number of comparables.","PeriodicalId":53999,"journal":{"name":"Aestimum","volume":"2 7","pages":""},"PeriodicalIF":0.8,"publicationDate":"2023-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138586327","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Citizen communication creates the foundation for sustainable development by adopting the notions of social life, space and human behavior. Furthermore, the perceptions of the cultural landscape, and the social sustainability of the neighborhoods are assessed through the participation of the citizens. As such, to gain a more in-depth understanding of the issues, the passage of the Fil Bazaar in Eshagh Beig neighborhood and Haj Zainal passage in Sang-e Siah neighborhood in the historical context of Shiraz has been selected. This research used a mixed-methodology. Due to necessity, using the questionnaire method and the Likert scale, with the help of architectural and urban planning specialists, a survey was conducted. Lastly, the collected data were analyzed using MAXQDA-software and using the Halprin-cycle, criteria were analyzed and assessed. With the aid of the Halprin-cycle, it is established that factors, correlation, Communication, and social life will impact the social stability.
{"title":"Evaluation of the quality of participatory landscape perception in neighborhoods of cultural landscape to achieve social sustainability","authors":"Nafiseh Golestani, M. Khakzand, Mohsen Faizi","doi":"10.36253/aestim-13527","DOIUrl":"https://doi.org/10.36253/aestim-13527","url":null,"abstract":"Citizen communication creates the foundation for sustainable development by adopting the notions of social life, space and human behavior. Furthermore, the perceptions of the cultural landscape, and the social sustainability of the neighborhoods are assessed through the participation of the citizens. As such, to gain a more in-depth understanding of the issues, the passage of the Fil Bazaar in Eshagh Beig neighborhood and Haj Zainal passage in Sang-e Siah neighborhood in the historical context of Shiraz has been selected. This research used a mixed-methodology. Due to necessity, using the questionnaire method and the Likert scale, with the help of architectural and urban planning specialists, a survey was conducted. Lastly, the collected data were analyzed using MAXQDA-software and using the Halprin-cycle, criteria were analyzed and assessed. With the aid of the Halprin-cycle, it is established that factors, correlation, Communication, and social life will impact the social stability.","PeriodicalId":53999,"journal":{"name":"Aestimum","volume":"1 1","pages":""},"PeriodicalIF":0.8,"publicationDate":"2023-02-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41716755","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Agricultural planning is a very complex task, since there are numerous goals, which should be achieved simultaneously, and various components and elements, which must be considered at the same time. The process of agricultural suitability evaluation for crop production requires specialized geo-environmental information and the expertise of a computer scientist to analyze and interpret the information. The main objective of this paper is to test a new model (based on Iranian ecological and FAO models) for ecological capability evaluation with geometric mean evaluation for better planning management of irrigated lands. Next, the proposed method was verified and compared with other well-known methods such as the Iranian ecological model with Boolean logic, arithmetic mean, and WLC. To test the models, we used the normalized difference vegetation index (NDVI). The test results indicated that the method revised by geometric mean evaluation (overall accuracy %=95 and Kappa coefficient =0.91) was the best among the used methods, and the arithmetic mean method (overall accuracy %=46 and Kappa coefficient =0) had the lowest accuracy. Thus, this method (Geometric mean evaluation) has high flexibility in locating agricultural lands. Overall, this study can be used as a basic method to evaluate ecological suitability for other regions with similar conditions owing to its simplicity and high precision.
{"title":"Developing a new model for ecological capability evaluation of irrigated lands in Firouzabad Township, Iran","authors":"M. Masoudi, Elmira Asadifard","doi":"10.36253/aestim-13390","DOIUrl":"https://doi.org/10.36253/aestim-13390","url":null,"abstract":"Agricultural planning is a very complex task, since there are numerous goals, which should be achieved simultaneously, and various components and elements, which must be considered at the same time. The process of agricultural suitability evaluation for crop production requires specialized geo-environmental information and the expertise of a computer scientist to analyze and interpret the information. The main objective of this paper is to test a new model (based on Iranian ecological and FAO models) for ecological capability evaluation with geometric mean evaluation for better planning management of irrigated lands. Next, the proposed method was verified and compared with other well-known methods such as the Iranian ecological model with Boolean logic, arithmetic mean, and WLC. To test the models, we used the normalized difference vegetation index (NDVI). The test results indicated that the method revised by geometric mean evaluation (overall accuracy %=95 and Kappa coefficient =0.91) was the best among the used methods, and the arithmetic mean method (overall accuracy %=46 and Kappa coefficient =0) had the lowest accuracy. Thus, this method (Geometric mean evaluation) has high flexibility in locating agricultural lands. Overall, this study can be used as a basic method to evaluate ecological suitability for other regions with similar conditions owing to its simplicity and high precision.","PeriodicalId":53999,"journal":{"name":"Aestimum","volume":" ","pages":""},"PeriodicalIF":0.8,"publicationDate":"2023-02-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47264412","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
M. Agosta, Caterina Patrizia Di Franco, E. Schimmenti, A. Asciuto
The Land Cadastre, as an inventory of all relevant real estate in a territory, and most importantly, as a national tax system is, or at least should be, the protagonist of fiscal, social and civil implications affecting the Italian context. According to unitary farmland incomes, the last revision dates back to 1978-1979, a period that no longer reflects the country’s current socioeconomic situation and does not consider the changes the land market has undergone over the years. Through the analysis of 183 purchases and sales of agricultural land in two districts in western Sicily, this research aims at verifying the adequacy or inadequacy of the current cadastral tariffs. Based on the prices surveyed and the cadastral farmland incomes, some indicators were constructed showing, on the one hand the absence of a strict correspondence between these two values and on the other hand the actual presence of fiscal inequality for all the crop qualities examined; and, consequently, the need for revising cadastral tariffs or for reforming tax system of Italian Cadastre by replacing tariffs with market values.
{"title":"The The Land Cadastre in Italy and some fiscal implications: a case study","authors":"M. Agosta, Caterina Patrizia Di Franco, E. Schimmenti, A. Asciuto","doi":"10.36253/aestim-13522","DOIUrl":"https://doi.org/10.36253/aestim-13522","url":null,"abstract":"The Land Cadastre, as an inventory of all relevant real estate in a territory, and most importantly, as a national tax system is, or at least should be, the protagonist of fiscal, social and civil implications affecting the Italian context. According to unitary farmland incomes, the last revision dates back to 1978-1979, a period that no longer reflects the country’s current socioeconomic situation and does not consider the changes the land market has undergone over the years. Through the analysis of 183 purchases and sales of agricultural land in two districts in western Sicily, this research aims at verifying the adequacy or inadequacy of the current cadastral tariffs. Based on the prices surveyed and the cadastral farmland incomes, some indicators were constructed showing, on the one hand the absence of a strict correspondence between these two values and on the other hand the actual presence of fiscal inequality for all the crop qualities examined; and, consequently, the need for revising cadastral tariffs or for reforming tax system of Italian Cadastre by replacing tariffs with market values.","PeriodicalId":53999,"journal":{"name":"Aestimum","volume":" ","pages":""},"PeriodicalIF":0.8,"publicationDate":"2023-02-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42447002","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In the literature, there are two basic approaches regarding the determination of house prices. One of them is the prediction of house price using macroeconomic variables in the country where the house is produced, and another one is the price prediction models, which we can express as micro-variables, by considering the features of the house. In this study, the price of the house was attempted to be predicted using machine learning methods by establishing a model with micro variables that reveal the features of the house. The study was conducted in Turkey’ Antalya province, where household housing demand of foreigners is also high. The house advertisements in locations belonging to the lower, middle- and upper-income groups were selected as the sample. In the results, it was observed that the artificial neural network (ANN) method made predictions with more meaningful results compared to support vector regression (SVR) and multiple linear regression (MLR). These results appear to be a viable model for institutions that supply housing, mediate housing sales, and provide housing financing and valuation. It is considered that this model, which can be used to predict fluctuating house prices, especially in developing countries, will regulate the housing market.
{"title":"House price prediction modeling using machine learning techniques: a comparative study","authors":"Ayten Yağmur, M. Kayakuş, M. Terzioğlu","doi":"10.36253/aestim-13703","DOIUrl":"https://doi.org/10.36253/aestim-13703","url":null,"abstract":"In the literature, there are two basic approaches regarding the determination of house prices. One of them is the prediction of house price using macroeconomic variables in the country where the house is produced, and another one is the price prediction models, which we can express as micro-variables, by considering the features of the house. In this study, the price of the house was attempted to be predicted using machine learning methods by establishing a model with micro variables that reveal the features of the house. The study was conducted in Turkey’ Antalya province, where household housing demand of foreigners is also high. The house advertisements in locations belonging to the lower, middle- and upper-income groups were selected as the sample. In the results, it was observed that the artificial neural network (ANN) method made predictions with more meaningful results compared to support vector regression (SVR) and multiple linear regression (MLR). These results appear to be a viable model for institutions that supply housing, mediate housing sales, and provide housing financing and valuation. It is considered that this model, which can be used to predict fluctuating house prices, especially in developing countries, will regulate the housing market.","PeriodicalId":53999,"journal":{"name":"Aestimum","volume":" ","pages":""},"PeriodicalIF":0.8,"publicationDate":"2023-02-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47452045","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Culture, creativity and circularity are driving forces for the transition of cities towards sustainable development models. This contribution proposes a data-driven quantitative methodology to compute cultural performance indices of cities (C4 Index) and thus compare results derived by subjective and objective assessment methods within the case study of the Metropolitan City of Naples. After data processing with Machine-Learning (ML) algorithms, two methods for weighting the indicators were compared: principal component analysis (PCA) and geographically weighted linear combination (WLC) with budget allocation. The results highlight similar trends among higher performance in seaside cities and lower levels in the inner areas, although some divergences between rankings. The proposed methodology was addressed to fill the research gap in comparing results obtained with different aggregation methods, allowing a choice consistent with the decision-making environment.
{"title":"Circular, Cultural and Creative City Index: a Comparison of Indicators-based Methods with a Machine-Learning Approach","authors":"G. Poli, Eugenio Muccio, M. Cerreta","doi":"10.36253/aestim-13880","DOIUrl":"https://doi.org/10.36253/aestim-13880","url":null,"abstract":"Culture, creativity and circularity are driving forces for the transition of cities towards sustainable development models. This contribution proposes a data-driven quantitative methodology to compute cultural performance indices of cities (C4 Index) and thus compare results derived by subjective and objective assessment methods within the case study of the Metropolitan City of Naples. After data processing with Machine-Learning (ML) algorithms, two methods for weighting the indicators were compared: principal component analysis (PCA) and geographically weighted linear combination (WLC) with budget allocation. The results highlight similar trends among higher performance in seaside cities and lower levels in the inner areas, although some divergences between rankings. The proposed methodology was addressed to fill the research gap in comparing results obtained with different aggregation methods, allowing a choice consistent with the decision-making environment.","PeriodicalId":53999,"journal":{"name":"Aestimum","volume":" ","pages":""},"PeriodicalIF":0.8,"publicationDate":"2023-02-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46003672","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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