|摘要: ||台灣在近年來社會和產業轉型的過程中，由於土地大量的需求，農地逐漸成為土地開發目標中重要的一環。農地價格除了對土地和都市開發會造成影響外，同時也對台灣農業的發展。瞭解農地價格對於國家農業政策的執行，農業的運作以及土地的利用開發都是相當重要的事情。早年農地的交易都是通過私人交易或是依靠當地的房產仲介進行交易，農委會為推行農業政策和透明化農地價格建立了台灣農地銀行，讓農民能透過此平台進行農地的交易，也能紀錄和瞭解當前各地農地的價格。 |
Because of more land demand in the progress of social and industrial transformation in recent years, agricultural land is becoming an important issue of the land use in Taiwan. Price of agricultural land has great impact not only on land and urban development, but also to the development of agriculture. It is important of learning the agricultural land price as a way of knowing agricultural policy, agricultural operations, and land use policy. Most of agricultural land transactions are done in private way or by real estate brokers. In order to mandating agricultural policy and transparence land prices, Council of Agriculture has been setting up a website, called Bank of Taiwan Agricultural Land, as a platform for farmers to sell, buy and lease their farm lands.
In this study, data from the website were collected and analyzed. The first step of the analysis is to find characteristics of the agricultural land prices, as well as the spatial correlation associated with each other data point. The second phase is to use soft-wares of geographic information system and statistical functions in analyzing the correlation between the agricultural land sale and purchase transaction data. Finally, land-location conditions from the view points of socio-economic and agricultural environments that may affect the prices were correlated. The analysis was separated into regional average price to average factor and specific point data to point condition.
The prices distribution in whole area has little regional association. The analysis of regional characteristics showing that the averaged prices and conditions, especially the socio-economic conditions include the degree of urbanization, real estate prices, population density, average income, as well as counties with more data points, might resulted in correlation coefficients up to 0.66. In particular, the degree of urbanization has the highest correlation coefficient of 0.77. On the other hand, agricultural land price and agricultural conditions such as the density of agricultural land and agricultural production showed lower correlations. The average correlation coefficient was around 0.4. No common correlation was found between the individual price and its corresponding condition in different counties, due to their different development progresses.
In the analysis of specific counties, the nearest urban center and urban planning area for the agricultural lands have higher price. The effective ranges differed with the development in each county. In addition, major commercial area made greater impact on agricultural land prices in counties which have higher degree of urbanization. The correlation coefficient could be as high as 0.99. On the contrary, agricultural conditions, the land productivity and the hierarchy of land importance, have no significant impact on the land prices, showing that agricultural land has no single factor to determine its price.