Researches About Fractal Feature And Spatial Distribution Optimization Of Rural Residential Areas In Hilly And Mountainous Areas In Chongqing

Urbanization is the inevitable course for human development. Chinese urbanization is in an accelerated development stage at present. In order to solve agriculture, countryside and farmer issues, the concept of “integration of urban and rural development” was put forward in the urbanization process to combine new rural construction and urbanization construction and propel coordinated development of regions and realize the comprehensive construction of a moderately prosperous society. New rural construction will realize the goals of constructing rural areas to a new socialist countrywide with prosperous economy, complete facilities, beautiful environment, civilization and harmony. Rural residential areas are the carriers of rural population and the core of rural man-land relationship. Therefore, the construction of rural residential areas takes an indispensable position in new rural construction. Chinese rural residential areas have disadvantages such as small scale, scattered distribution, lack of planning and so on and they are even more prominent in hilly and mountain areas with complicated topography. This is mainly due to complicated topography in mountains, huge terrain fluctuation and significant elevation difference among regions, which makes residential areas distribution more scattered and restricted by topography, more varied construction scales of residential areas and huge differences of regional economic development, infrastructure construction, production environment and unreasonable residential area spatial arrangement. At present, some scholars have carried out large numbers of researches on residential area distribution optimization in hilly and mountain areas. However, measures of the researches are quite single, regional representativeness is not distinct and universality is not high. Therefore, it is of importantly practical significance to carry out different ecological types and scales of rural residential areas space fractal features, residential areas change driving force analysis and residential areas optimized distribution researches to agricultural and economic development in mountains.This study took hilly and mountain areas in Chongqing as research objects and carries out rural residential area fractal feature research in different ecological areas by using the fractal theory and then to the rural residential areas fractal rules. It also adopted logistic regression model and conducts quantitative analysis on change driving factors of residential changes under the support of Clue-S, thereby revealing the contribution degree of different driving factors on residential area changes. It relied on gravity model and potency model and realized residential areas optimized distribution in different ecological type regions under the support of GIS(Geographic Information System). Major conclusions were as follows:(1)Rural residential area distribution characteristics of different ecological districts in ChongqingRural residential area spatial distribution changes with changes of elevation and its distribution rules in different ecological districts did not agree. Over 80% of the rural residential areas in the shallow hilly and flatland region were distributed in below 300 meters. 45% of hilly area residential estates were distributed in 300-500 m and the next is below 300 m and in 500-800 m. The percentages of residential areas in the ecological district residential areas were 26% and 25.8% respectively. Residential areas of middle hilly areas were distributed between 300-500 and 500-800 m, and the percentages of two elevation residential areas were about 35%, and the smallest are over 800 m. The highest percentage of high altitude residential areas were in 300-800 m and the percentages in the research phase are about 42.5%, the next is housing residential areas in 800-1200 m, and the percentages were about 30.5%.Influences of gradient on the rural residential area spatial distribution were regular and its change rules in different ecological districts are consistent. 35% of residential areas in shallow hilly and flatland region.were.distributed in 6 ~ 15°. Over 35% of hilly area residential areas were distributed in 15~25°. Residential estates of over 25% of middle hilly areas were distributed in 6~15°, and about 33% of residential areas are distributed in 15~25°. Over 37% of residential areas of high altitude mountainous areas were distributed in 15~25°, and the percentage of residential areas in 6~15° is about 30%. Generally speaking, the rural residential areas were mainly distributed in the two gradients of 6~15° and 15~25°.The fractal features of the rural residential areas represented significant regional difference and inner difference, revealing the degree of residential area space occupying ability in different ecological districts. It reflected differences of economic development and natural conditions in different ecological districts indirectly. The more developed economy, the better the natural environment and the higher fractal dimension values. The residential area fractal dimensional numerical in shallow hilly and flatland region Tongnan County was the highest and it was above 1.6 averagely. Residential area fractal dimensional numerical in the high altitude mountainous district Pengshui County was the lowest, and it was below 1.47. Residential area fractal dimensional numerical in the hilly area Banan was about 1.58 and that of the middle hilly area Fuling is about 1.59. Residential areas distribution characteristics of various towns are: the highest is 1.563 and the lowest was 1.41 in shallow hilly and flatland region and fractal feature difference in each town was small. The highest was 1.579 and the lowest was 1.213 in the hilly areas and fractal feature difference in each town was huge. The highest was 1.552 and the lowest was 1.152 in the middle hilly areas; the highest among all towns in high altitude mountainous areas was 1.409 and the lowest was 1.110.There were also regional differences and differences inside the region as to the rural transportation fractal dimension. However, fractal dimensions were lower than fractal dimension of the rural residential areas and inter-annual variation degree of transportation fractal.dimension.was.also.lower.than.residential.areas,.showing.that.transportation.developm ent in all ecological districts were not balanced and could not satisfy real demands of rural residential areas. The middle hilly area was the highest 1.3742, and the lowest was 1.3538, and fractal dimension numerical values increased year by year. The lowest hilly area was 1.3282 and the highest was 1.3444. Fractal dimension numerical value of high altitude mountainous area was 1.2643. The lowest in shallow hilly and flatland region was 1.2583 and the highest was 1.2613 and it increases year by year. Transportation fractal feature of each town: fractal dimension of shallow hilly and flatland region was between 0.881—1.999, hilly area was between 0.166—1.317, middle hilly area was between 1.063—1.322 and high altitude mountainous area was between 0.869—1.22. Transportation balance of each town was imbalanced. Compared with residential areas, transportation fractal features were lower than fractal features of residential areas.Compared with the residential areas and transportation, the regional differences and differences within the region of rural drainage fractal dimensions were the largest, showing the abundance of water resources in different ecological districts indirectly. Those in the middle hilly areas were the highest and they are over 1.4537 averagely. The fractal dimension numerical values in shallow hilly and flatland region were 1.3983 averagely. Those in hilly areas were in 1.3484—1.3602 and they were the smallest in high altitude mountainous areas, which was 1.2579. The drainage system fractal features in each town: the highest in shallow hilly and flatland region is 1.366 and the lowest was 0.778. The highest in hilly areas was 1.498 and the lowest was 0.797. The highest in middle hilly areas was 1.536 and the lowest was 0.588. The highest in high altitude mountainous areas was 1.252 and the lowest was 0.728. The drainage fractal dimension agrees with the abundance degree of water resources in research areas basically.(2)Analysis of change driving force of rural residential areas change driving force in Chongqing hilly and mountain areasAn essential databank construction of township rural residential areas of different ecological districts in Chongqing had been constructed, including rural residential areas, present situation of land use, soil, basic farmland, cultivated land grade, infrastructure and topography and so on. Properties of database had been supplemented and the math basis and data formats were unified.Through the analysis of basic database of town-scale rural residential areas, it found out that basic conditions in different ecological areas were hugely different. Average area of residential areas in shallow hilly and flatland region and middle hilly areas were the largest, single largest residential area is 7.96 hectare and the smallest was less than 0.001 hectare. The largest land category area in shallow hilly and flatland region and middle hilly areas was cultivated land, and the largest land category area in hilly areas and high altitude mountainous areas was forest land. Soil texture of four ecological districts has huge differences. It was mainly red-stone and soil, mud land, half-mud and half soil in shallow hilly and flatland region. It is brown purple paddy soil and brown purple mud in hilly areas. Middle hilly areas were mainly sandy soil, tidal land and big-eye mud land while shallow hilly and flatland region is mainly mineral flavescent soil. Basic farmland in middle hilly areas was 5065.75 hectare at most, while 2524.08 hectare at least in high altitude mountainous area. The largest cultivated land grade in shallow hilly and flatland region was Grade 7, and that in hilly area was Grade 6, and Grade 4 in middle hilly area and Grade 10 in high altitude mountainous areas. Infrastructure in middle hilly area was the best, while that in high altitude mountainous area was the worst.Comprehensive changes, increase and decrease of rural residential areas were the common driving results of inner factors and outside factors. However, inner factors’ contribution values was higher than that of outside factors and changes of different ecological type residential areas all abide by this rule. For example, comprehensive changes of rural residential areas in shallow hilly and flatland region were mainly driven by 7 factors, which were elevation, average second industry value, effective irrigation area, grain yield, distance to roads, distance to towns and distance to drainage system and four of them were inner factors. The Wald statistics of distance to roads reached 1496.450. The increase of residential areas in middle-hilly areas is influenced by 6 factors, which were elevation, distance to roads, distance to towns and distance to drainage system, average second industry value and effective irrigation area, and four were inner factors. The decrease of residential areas in high altitude residential areas is influenced by four factors, which were gradient, distance to roads, distance to towns and effective irrigation area and three were inner factors.The number of driving factors of rural residential areas in different ecological districts was different and it changed singly with changes of ecological districts. From the perspective of comprehensive changes, increase and decrease of residential areas, it was clear that the number of driving factors of residential areas in shallow hilly and flatland region was the largest, and the next was in the hilly areas and middle hilly areas and the lastwas in the high altitude areas, which indicated that in ecological districts with poorer ecological development conditions and worse natural conditions, driving factors leading to residential areas changes were purer. In addition, The Wald contribution value of the same driving factor to different ecological type rural residential areas was different. For example, the contribution value of distance to roads of residential area comprehensive changes in shallow hilly and flatland region was 1496.450, while it was 107.407 and 40.081 in middle hilly areas and high altitude areas.Residential area changing influence factors analysis was under the influence of scale. In the level of county territory, the.spatial distribution of changing residential areas with elevation and gradient changed with rules. With the increase of rural per capita net income, rural area per capita also increased and there was significant positive correlations between them. However, from the perspective of town territory, the contribution value of elevation to rural residential area changing.was.not.the highest and elevation did not make due contribution of statistics scale in middle hilly areas rural residential area comprehensive changes. It indicated that under different scales, the driving impact of the same factor to residential area changes did not agree.(3)Rural residential area spatial arrangement optimization based on town scaleGravitation values of rural residential areas in different ecological districts were different and they showed some regularity with changes of economic conditions of ecological districts and natural environment. In ecological districts with advanced economy and good natural conditions, their gravitation values of residential areas being absorbed by towns were higher. As to residential areas whose gravitation result cluster of shallow hilly and flatland region was from 0.602 to 1, towns had huge attraction to them, and residential areas whose gravitation values are from 0 to 0.602, they were divided into non-urbanized type. The residential areas gravitation value standardization results of hilly areas in 0.54-1 range of threshold are divided into urbanized type; residential areas whose results are witin 0-0.54 were divided into non-urbanized type. Residential areas gravitation value standardization results of high altitude mountainous areas in 0.49-1 were divided into urbanized type while that in 0-0.49 range of threshold are divided into non-urbanized type.The functional mechanism of residential areas potency and influence factors in distribution optimization process was quite complicated and did not show obvious rules. The clustering results of the same potency element in different ecological districts were different and the clustering results of different potency elements in the same ecological types were different. Potency element clustering result was divided into three grades, which were good, general and bad. The demarcation points of good, general and bad development foundation in shallow hilly and flatland region were 0.21 and 0.35, that of production conditions were 0.23 and 0.48, that of living conditions were 0.38 and 0.45, that of ecological environment were 0.18 and 0.37 and that of comprehensive potentials were 0.26 and 0.47. The development demarcation points of hilly areas were 0.45 and 0.61, that of production conditions were 0.22 and 0.64, that of living conditions were 0.17 and 0.61, that of ecological environment were 0.38 and 0.58 and that of comprehensive potentials were 0.16 and 0.35. The development demarcation points of high altitude mountainous areas were 0.37 and 0.59, that of production conditions were 0.43 and 0.69, that of living conditions were 0.46 and 0.73,that of ecological environment were 0.42 and 0.63 and that of comprehensive potentials were 0.16 and 0.630.According to the results of gravitation and potency analysis, it realized the optimal rural residential area distribution optimization of different ecological types. According to the statistical results, local urbanized residential areas in shallow hilly and flatland region were 62, key development-type were 388, control expanded-type were 2105, and migrated merge-type were 91. The local urbanized residential areas in hilly areas were 183, key development-type was 950, control expanded-type were 1391, and migrated merge-type were 442. The local urbanized residential areas in high altitude mountainous areas were 149, key development-type was 278, control expanded-type were 453 and migrated merge-type were 302. According to the calculation results of all ecological districts, the number of control expanded-type residential areas was the largest while that of urbanized type and migrated merge-type were the smallest.