Rural Houses Classification And Optimal Utilization Of Chujia And Xuma Village

Rural settlement is a product of special conditions under urban-rural dual economicstructure and an important part of China’s rural land use. Large base of rural populationdetermined the necessity of rural settlements existment will lasts quite a long time. As ruralresidents most basic and directive unit, rural house land is the subject of rural residential landuse, with living, production, ecological and cultural functions.It is a concrete manifestation ofrural characteristics and rural life, reflecting changes of rural society development. Therefore,based on the status of rural house site analysis, land use classification of houses can provide atheoretical basis for the scientific stage village renovation and has an important role in urbanand rural development.In this study, taking Shandong plain area rural house sites as the subject, selectingDongying’s Chujia village, Liaocheng’s Xu Ma village two villages, use field surveys,constructing network model,GIS technology and other methods integratly to analyze thestatus of the study area house sites and make single classification; Build houses factorcomprehensive classification system, using principal component analysis (PCA) methodresearch house land driving force; Using self-organizing feature map (SOFM) network,classified comprehensive division and named house type; Propose solutions for optimal use ofdifferent types of houses and villages homestead renovation and managementrecommendations. The main results were as follows:(1) Analysis of the study area house land status and single classificationBased on the survey data, analyzed land status and characteristics of two villages.Results shows that per capita land area of two villages was higher than the state’s higheststandards, the average homestead was also high, respectively347.41m2and396.22m2.Volume rate is generally low, the volume over0.50in Chujia village was27.50%of the totalnumber, Xuma village volume higher than0.50took78units, accounting for48.45percent ofthe survey units.Based on the results of K-means clustering analysis method, according to floor area ratio,house land size, total household income respectively to make single classification of studyarea. Divided by the volume rate,there was high, medium and low three grades, Chujiavillage utilization accounted for11.72%of high use efficiency, while Xuma village accountedfor5.59%. Overall,most lower volume rate house had a small building area, relatively old.Divided by the size of the land, except for the Chujia Village corps, the overall differencebetween the house was smaller. Xuma village except breeding and sales of outdoor plants,there is some houses merger situation, but the overall difference between was also smaller.Divided by total income, the overall income level of Chujia was higher than Xuma village, Itis mainly due to the types of practitioners and income structure, some houses of Chujia villageby engineering contract incomed higher, the others difference was smaller, duing to thestructure of the general practitioners of Xuma village differed little, mainly depending onagriculture or workers, the income was not high. Overall, the village house land efficiencywas low, use of the potential was large.(2) Construction of comprehensive classification factors system of house landUsing participatory rural appraisal (PRA)method, asked for the experts advice, obtainingdata for each factor by researching area villagers, through household surveys in-depth, andthen selected comprehensively the impact of a internal factors differences between houses,including household population, effective occupancy rate, homestead area, per capita livingarea of the building, various economic of payments, and total15indicators.Using PCA method to analyze driving force of land houses affecting factors, influencingfactors of Chujia village houses included the economic situation factors, family structuralfactors, factors and circumstances, house building house use total four aspects. Xuma villagewithin the scope of investigation, house influencing factors included land house demographicand economic factors, family structural factors, house building situation and house utilizationfactors total4aspects. Although two villages were at different geographical location,thehouse land use factors were same roughly.(3)House land classification based on SOFMBased on principal component analysis results, using self-organizing feature map neuralnetwork model of matlab7.0, after repeated training,defined the appropriate networkparameters, and got the house classification results. Chujia village had five types, namelyrespectively:S5-1: new house type of general income and multi-population, S5-2: lowincome-high efficiency mainly agriculture house, S5-3: single income structure house, S5-4:low population witn high-income non-agricultural house type, S5-5: high-income withinefficient use house type. Xuma village house land surveyed was divided into three types,namly as: S3-1: high-income with big population,effectively used new houses type, S3-2:middle-income with concurrent-business stsble courtyard, S3-3: Small family low income andutilization agricultural courtyard. The results show that courtyard classification using SOFMnetwork met the study area village house unit status overall and this study is feasible. (4) Optimal Utilization of different development houses typesBased on the type of house land types,proposed both classification and comprehensiveproposals for rural houses development.The first recommendations included: new typeemphasis on development of house sites and improvement utilization efficiency; small familyhouses in inefficient use emphasis on transformation; efficient high-income house types tomaintain the status quo; single income house type transformated appropriately; other housetypes, on the basis of analyzing the status quo, combing with the family actual livingconditions to seek suitable development mode. Utilization recommendations include:emphasis on house development and utilization, improve house income; develop reasonablehouse structure model to improve the utilization efficiency of houses; strictly control newhomestead scale, and improve village planning; improve the rural homestead managementlaws and regulations, and improve rural land use legally and so on.