CN116976692A - Traditional village classification partition protection control method based on adaptive circulation path - Google Patents

Abstract

The invention discloses a traditional village classification zoning protection and control method based on adaptive circulation paths, which includes: acquiring basic data and importing it into a GIS platform to establish a traditional village database; constructing a traditional village database through the three characteristic attributes of locality, mobility and resilience. The traditional village adaptability comprehensive index system obtains the weight of each indicator based on the entropy method, calculates three characteristic attribute values, and evaluates the adaptive cycle path of traditional villages; performs rapid clustering based on the three characteristic attribute values to classify traditional villages Zoning and determining planning strategies for protection control. This invention considers the local unit attributes, fluid spatial structure and resilience dynamic trends of different traditional villages from a macro-overall perspective, and based on the adaptive cycle path, forms a method with the advantages of comprehensive elements, time continuity and development stages. , providing basis and reference for policy formulation and rural governance for the protection and development of villages.

Description

A classification and zoning protection control method for traditional villages based on adaptive cycle paths

Technical Field

The present invention relates to technical fields such as information technology, urban and rural planning, rural revitalization, regional planning, and human geography, and in particular to a traditional village classification and zoning protection and control method based on an adaptive cycle path.

Background Art

Under the background of urbanization, traditional villages have gradually moved away from the state of self-sufficient small-scale peasant economy and integrated into the regional network through transportation, economy, information and other links. The injection of capital and the innovation of production tools have promoted the transformation of traditional villages from the original endogenous and passive human-land adaptation model to the exogenous, complex and active human-land multiple adaptation model. The factors affecting the overall protection and adaptive development of traditional villages have become increasingly complex. However, with the acceleration of economic and social development and urbanization in recent years, the phenomenon of traditional villages suffering from construction damage, natural damage and disorderly development damage has become increasingly serious, and the protection situation is very serious.

The classification and zoning protection and control of traditional villages is an important part of the content of rural protection planning, protection measures, protection policy management, and protection legal responsibility division. It is also an important way to reasonably control and manage and coordinate various construction activities such as maintenance, arrangement, restoration and internal renewal of traditional villages according to the protection and utilization status of different parts of traditional villages. It reflects the relevance and difference of traditional villages in the regional protection system, and is also an important means to shape the buildings, lanes, environment and various spatial landscapes that constitute the historical style in traditional villages. The classification and zoning protection and control of traditional villages is conducive to the integrity, systematic and structural protection of various types of traditional villages on the regional scale, and promotes the protection and restoration of historical authenticity, style integrity and cultural life continuity of traditional villages. It is the basic basis for the formulation of traditional village policies, planning and construction, and rural governance.

However, at present, many traditional villages classification and zoning protection and control methods are based on type and regional characteristics. Some are based on settlement morphology and structure, and traditional villages are divided into types such as spool type, bead type, center type, balanced type, star point type, etc.; some are based on geographical environment and terrain as classification factors, and traditional villages are divided into coastal fishing villages, basin block type, plain waterside type, etc.; some are based on resource conditions, and traditional villages are divided into material cultural heritage type, intangible cultural heritage type and comprehensive type (both); some are divided according to traditional industries and functions, and traditional villages are divided into seven types such as farming type, industrial and trade type, and administrative type. However, the above classification and zoning methods only analyze from a single dimension such as nature, economy, society, and culture, and do not take into account the current development stage and current status characteristics of the village, nor do they effectively make diachronic judgments from the dynamic perspective of the temporal and spatial evolution of the village, and lack methodological judgments based on comprehensive factors, time continuity, and development stages.

In addition, most of the traditional village classification and zoning protection and control methods are targeted at different traditional village cases. According to the structural form, artistic characteristics, historical characteristics, construction age and rarity of traditional buildings, the protection scope is divided into core protection areas and construction control areas in a subjective form to implement zoning protection. There are also classification guidance methods based on whether the style is concentrated in the core protection area, construction control area and environmental coordination area. The resource endowment, integrity and preservation of the village have become important indicators of the protection and control methods.

However, this classification and zoning protection and control method has turned into a simple division, stacking and patchwork of different traditional village elements, often ignoring the correlation and systematicity between the various elements, and turning into an isolated classification and zoning method. At the same time, the isolated classification and zoning method has caused the traditional villages to be separated from the natural and social environment in which they are located. The method is too focused on whether the "prescribed actions" such as the principle and content of traditional village protection have been completed, and it is unable to form an overall, objective and targeted protection and development strategy for traditional villages with different characteristics and facing different problems. This has led to the dilution and disappearance of the characteristics of traditional villages to a certain extent.

In general, the technical means for the protection and control of traditional villages through classification and zoning are mostly targeted at a single scale, especially focusing on micro or meso scales such as individual buildings, communities, and rural settlements, but lack the protection and control methods for traditional villages through classification and zoning in macro-scale regional planning to deal with the traditional villages as a whole at regional scales, cross-regional scales, and even national spatial scales. The current methods mostly adopt an isolated classification and zoning form, lacking a multi-dimensional comprehensive perspective on environment, economy, culture, politics, and the relationship between different elements, resulting in a separation between traditional villages and the environment. In addition, the existing classification and zoning control methods for traditional villages are mostly based on qualitative design guidance and case analysis, lacking effective and universal quantitative methods, and the methods have not judged the current development stage of the villages based on the diachronic changes of traditional villages. Therefore, the classification and zoning protection and control of villages are the results of the current static time profile, ignoring the historical relevance and development continuity.

Summary of the invention

In view of the above-mentioned existing problems and shortcomings, the present invention provides a classification and zoning protection and control method for traditional villages based on an adaptive cycle path. The method is based on objective and rational analysis, and conducts a relatively comprehensive and comprehensive consideration from a macro-overall perspective, and takes into account the local characteristics, mobility correlation and resilience recovery among different elements. Based on the adaptive cycle path, the adaptation process and current development stage of the village are analyzed from a temporal dynamic perspective. The method has a wide range of applications and data is easy to obtain, so that the solidification phenomenon of traditional villages in a pathological state can be effectively judged, and a basis and reference for policy formulation and rural governance can be provided for which villages should be protected first and from which dimensions.

To achieve the above-mentioned invention object, the present invention adopts the following technical solution: a traditional village classification and zoning protection control method based on adaptive cycle path, comprising the following steps:

Step 1: Obtain basic data and standardize the data, and import all data into the Geographic Information System (GIS) platform to establish a traditional village database. The basic data include: point vector data of traditional village history and culture, point vector data of different functional spaces of traditional villages, natural geographic vector and raster data, and socio-economic development vector and raster data.

Step 2: Based on the three characteristic attributes of locality, mobility, and resilience, a comprehensive index system for the adaptability of traditional villages is constructed. Based on the entropy method, the weight of each indicator is obtained from an objective perspective, the values of the three characteristic attributes are calculated, and the adaptive cycle path of traditional villages is evaluated.

Step 3: Rapidly cluster the locality, mobility and resilience values of traditional villages obtained in step 2, classify and zone the traditional villages, and determine the planning strategy for protection and control based on the classification and zoning of traditional villages.

Furthermore, the specific steps of step 1 are as follows:

Step 1.1, obtain basic data, including: (1) vector data of historical and cultural points of traditional villages: traditional village points, cultural relics protection unit points, religious temple points, intangible cultural heritage points, and intangible cultural heritage inheritors points; (2) vector data of different functional spaces of traditional villages: school points, medical facility points, government points, railway station points, and national A-level scenic spots; (3) natural geographic vector and raster data: river system vector data, terrain relief raster data, vegetation net primary productivity raster data, annual precipitation distribution raster data, cultivated land multiple cropping area raster data, solar radiation raster data, and annual average temperature raster data; (4) socio-economic development vector and raster data: road vector data, annual population density distribution raster data, and prefecture-level city per capita GDP vector data. The above data are imported into the GIS platform, where the vector data uses the shp format and the raster data uses the img format, and geometric correction is performed according to the World Geodetic System (WGS 1984 version) to accurately match the unified spatial reference coordinate system.

Step 1.2: Based on the four types of basic data in step 1.1, use the neighborhood analysis tools, spatial analysis tools, spatial connection tools and other analysis tools in GIS to calculate the distance of the traditional village point data from the nearest cultural relic protection unit, the spatial distance from the nearest religious temple, the distance from the intangible cultural heritage and the terrain undulation of the location, which will be used as the traditional village locality index in the subsequent steps; then calculate the spatial distance of the traditional village point data from the nearest school point, the spatial distance from the nearest medical facility point, the spatial distance from the nearest government point, the spatial distance from the nearest highway, the spatial distance from the nearest railway station point and the spatial distance from the nearest national A-level scenic spot, which will be used as the traditional village mobility index in the subsequent steps; finally, calculate the change of vegetation net primary productivity, precipitation value, population density, multiple cropping area of cultivated land, solar radiation, temperature, per capita regional GDP of the prefecture-level city, distance from the river system and distance from the location of the intangible cultural heritage inheritor, which will be used as the traditional village resilience index in the subsequent steps. The above data are standardized and imported into the GIS platform to establish a traditional village database.

Furthermore, the specific steps of step 2 are as follows:

Step 2.1, construct a comprehensive index system for the adaptability of traditional villages: Taking traditional village sites as the object, the dynamic response process of the development path of the system adaptability cycle stage of traditional villages in response to external interference can be expressed through the changes in the three characteristic attributes of locality, mobility and resilience. Locality, mobility and resilience represent the three aspects of the adaptability of traditional villages: unit attributes, spatial structure and dynamic trend.

(1) Locality refers to the unit attribute of traditional villages as a system and its internal growth potential, which is mainly manifested in three aspects, including the material spatial characteristics of villages such as architectural forms with unique regional characteristics and street textures, the poetic landscape pattern of village location and layout such as backing mountains and facing water, and hiding wind and gathering energy, and the intangible culture with regional characteristics such as living customs, religious sacrifices, and festivals.

(2) Mobility refers to the interaction process and relationship between individuals within the traditional village system, including the flow of people, economy, information, etc., reflecting the spatial structure of the traditional village system. In the historical period, the reasons for the mobility of traditional villages included avoiding disasters, doing business, and finding a livelihood. The social interaction scope formed by market transactions laid the foundation for mobility. Therefore, the mobility of traditional villages was about ten miles and eight villages, and generally did not exceed a one-day round trip. Nowadays, in order to obtain resources such as children's education, medical treatment, administrative services, and employment opportunities, residents of traditional villages will use modern transportation to go to county towns, provincial capitals, or migrate to longer distances. At the same time, outsiders may arrive in traditional villages for leisure tourism, nature education, scientific research, industrial development, etc., which has created an inward and outward mobility relationship in traditional villages.

(3) Resilience refers to the ability of the traditional village system to recover its steady state after being disturbed, reflecting the dynamic trend of the traditional village system in the time dimension, including the three aspects of life, production and ecology. The ecological base is an important resource that affects the resilience of traditional villages. The high value of ecological services can provide a variety of ecological products for the village; the population is the core component that affects the resilience of traditional villages. Families centered on marriage and blood relations and clans of the same clan build a village living space of mutual growth and integration; the economy is an important guarantee that affects the resilience of traditional villages. The primary industry, which is mainly based on agriculture and animal husbandry, is an important supporting pillar of the village. With the development of urbanization, the primary industry has gradually integrated with the secondary and tertiary industries. Traditional villages with a prosperous economy have the resilience to quickly rebuild, heal, and migrate.

The adaptive cycle path evaluation of traditional villages includes three criteria layers: locality, mobility and resilience. Each criterion layer includes different indicator layers, as follows:

(1) The local index layer includes four indicators, namely, architectural courtyards, sacred spaces, traditional customs, and landscape patterns, which respectively represent the scarcity of courtyards and buildings, the dependence on religion and beliefs, the uniqueness of traditional folk customs, and the regionality of the village environment. The selected data are the distance to the nearest cultural relic protection unit, the distance to the nearest religious temple space, the distance to the intangible cultural heritage, and the terrain undulation. The data are obtained from step 1.2;

(2) The indicator layer of mobility includes 6 indicators, namely, education mobility, medical mobility, administrative mobility, employment mobility (short distance), employment mobility (long distance), and tourism behavior, which respectively indicate the opportunity cost of villagers obtaining their children's education, the opportunity cost of villagers obtaining medical services, the opportunity cost of villagers obtaining administrative services, the opportunity cost of villagers obtaining resources in surrounding counties and towns, the opportunity cost of villagers obtaining resources in distant cities, and the probability of tourists arriving in the village. The selected data are the spatial distance to the nearest school point, the spatial distance to the nearest medical facility point, the spatial distance to the nearest government point, the spatial distance to the nearest highway, the spatial distance to the nearest railway station point, and the spatial distance to the nearest national A-level scenic spot. The data are obtained in step 1.2;

(3) The index layer of resilience includes nine indicators, namely vegetation cover, precipitation, distance to rivers, intergenerational inheritance, population, production, sunshine, temperature, and economy, which respectively describe the trend of resilience to natural disturbances, precipitation abundance, supply of ecological products, inheritance of intangible cultural heritage, intensity of human capital, degree of intensive use of cultivated land, regionality of village sunshine, regionality of village environment, and capacity for self-repair and financial security. The selected data are the trend of vegetation net primary productivity, precipitation, distance to river systems, distance to the location of intangible cultural heritage inheritors, population density, multiple cropping area of cultivated land, solar radiation, temperature, and per capita GDP of prefecture-level cities. The data are obtained from step 1.2.

Step 2.2, based on the entropy method, obtain the weight of each indicator from an objective perspective, and calculate the three characteristic attribute values of locality, mobility, and resilience of traditional villages: In order to obtain the indicator weights of locality, mobility, and resilience, use the entropy method to objectively weight each indicator in step 2.1. Before weighting, the data has been uniformly standardized. The entropy method is a mathematical method to determine the degree of dispersion of indicators. The greater the degree of dispersion, the greater the impact of the indicator on the comprehensive evaluation. The entropy value can be used to judge the degree of dispersion of an indicator. The smaller the information entropy, the greater the importance of the indicator in the comprehensive evaluation, and the greater the weight. The formula is as follows:

d _j =1-e _j (3)

In the formula, _Xij is the weight of the jth indicator of the i-th village, _Xij is the standardized indicator value, _ej is the indicator information entropy, _dj is the information redundancy, _Wj is the indicator weight, m is the total number of traditional villages in the research scope, and n is the number of indicators. According to the different indicator layers contained in the three-aspect criterion layer of traditional village locality, mobility and resilience in step 2.1, combined with the weights of each indicator, the three-aspect criterion layer indicators of traditional village locality, mobility and resilience are calculated. The calculation formula is as follows:

Where _Wj is the weight of the j-th indicator; _Pj is the value of the j-th indicator; _Li , _Mi , and _Ri are the values of the three criterion layers of traditional village locality, mobility, and resilience, that is, the three characteristic attribute values of traditional villages; l, m, and n are the total number of indicator layers contained in the three criterion layers of traditional village locality, mobility, and resilience, respectively. As mentioned above, they are 4, 6, and 9, respectively.

Step 2.3: Evaluate the adaptive cycle path of traditional villages: Based on the characteristic attribute values of locality, mobility, and resilience calculated in step 2.2, generate an adaptive cycle path model of "locality-mobility-resilience" for traditional villages. The high H and low L characteristic values of locality, mobility, and resilience jointly determine the adaptability. The calculation formula is as follows:

Where A _i is the value of the locality, mobility, and resilience attribute index of the ith village, which is _Li , _Mi , _Ri in formula (5); s is the total number of traditional villages within the research scope, H is the high value set, and L is the low value set.

According to the table below, the adaptive cycle path of traditional villages is divided into two states: cycle stage and pathological state, including eight development stages of traditional villages (development (r), protection (K), release (Ω), renewal (α), poverty dilemma, rigid dilemma, locked dilemma, unknown dilemma), which are eight types of traditional villages. The specific classification is as follows:

The cycle stages of traditional villages include: first, the development (r) stage, which corresponds to the rapid development period of traditional villages under policy protection and capital injection; second, the protection (K) stage, which is the mature stage of development of traditional villages, but at this time there will be more interference, which makes the system very easy to collapse; third, the release (Ω) stage, which is the overload period of development of traditional villages, during which social reorganization or innovation is prone to occur; fourth, the renewal (α) stage, after which the system enters a new round of cycle.

The pathological states of traditional villages include: first, poverty dilemma, which often occurs in the development stage, due to reasons such as over-exploitation of resources and economic collapse; second, rigidity dilemma, which is the opposite of poverty dilemma and is characterized by high resilience, high locality and high mobility; rigidity dilemma generally occurs in the protection stage. If it cannot enter the renewal or release stage normally, it will continue to maintain high resource and capital consumption and enter the rigidity dilemma; third, lock-in dilemma, which is characterized by low locality, high mobility and high resilience. The lock-in trap generally occurs in the release stage. If traditional villages still stick to the old ways and maintain the existing development model in the high-load and high-consumption stage, they may enter the lock-in trap; fourth, the unknown dilemma, which is characterized by high locality, low mobility and low resilience. The reasons for the unknown dilemma are relatively complex and there is no unified conclusion yet.

Step 3: Rapidly cluster the three characteristic attribute values of locality, mobility and resilience of traditional villages obtained in step 2, classify and zone the traditional villages, and determine the planning strategy for protection and control based on the classification and zoning of traditional villages.

Furthermore, the specific steps of step 3 are as follows:

Step 3.1, fast clustering of traditional villages based on Euclidean distance: The values of locality, mobility and resilience indicators of traditional villages obtained in step 2 are combined with the spatial location coordinates of traditional village points in step 1. The four values of spatial location, locality, mobility and resilience of traditional villages are imported into SPSS statistical analysis software for fast (K-means) clustering. The fast clustering method based on Euclidean distance is as follows:

Wherein, d( _xij , _yij ) is the Euclidean distance between traditional village i and traditional village j, _xi , _yi are the horizontal and vertical coordinates of the point vector data of traditional village i, _andxj , _yj are the horizontal and vertical coordinates of the point vector data of traditional village j.

Rapid clustering first determines the number of clusters p according to the actual needs of traditional village division; next, randomly select the centroid for each cluster and assign all traditional village data points to the cluster with the closest distance to this centroid; then, recalculate the centroid of each newly formed cluster, repeat the step of assigning all traditional village data points to the cluster with the closest distance to this centroid, and recalculate the centroid of each newly formed cluster, and repeat the above steps continuously, iterating until three stopping criteria can be used to stop the rapid clustering algorithm: (1) The centroid of the newly formed cluster will not change the traditional village data points remaining in the same cluster for the maximum number of iterations. If the centroid of the newly formed cluster does not change, the algorithm can be stopped. Even after multiple iterations, all clusters still have the same centroid, which means that the algorithm has not learned any new patterns and it is a sign to stop training; (2) After multiple iterations of training, if the traditional village data points are still in the same cluster without change, the algorithm can be stopped. (3) If the maximum number of iterations is reached, the algorithm can be stopped. The number of iterations is usually set to 100, which means that the above process will be repeated 100 times before stopping. For ease of operation, a fast clustering algorithm is used in the statistical analysis software to classify traditional villages based on the principle of the shortest distance.

Step 3.2, determine the classification and zoning of traditional village protection and control: import the clustering results in step 3.1 into the traditional village point vector data in step 1 through the GIS platform attribute connection tool. According to the clustering results displayed by the GIS platform, determine the protection and control zoning of traditional villages based on adaptive cycle paths, and conduct statistics on the types of traditional villages in 2 states and 8 development stages within the zoning.

Step 3.3: Carry out protection and control planning of traditional villages according to different development stages. The principles are as follows:

Traditional villages in the cycle stage are in the process of active growth: (1) For traditional villages in the development (r) stage, the economy and population are in a state of rapid growth. Therefore, it is necessary to focus on the rationalization of land planning and resource utilization, protect the ecological environment, strengthen infrastructure and public service construction, improve village functions, promote the development of characteristic industries, and strengthen brand publicity; (2) For traditional villages in the protection (K) stage, traditional villages have entered a mature development stage and have begun to pay attention to ecological environment protection and cultural heritage maintenance. Therefore, it is necessary to strengthen cultural heritage protection, protect buildings, cultural landscapes, etc.; encourage the protection and development of traditional handicrafts, create rural characteristic products; promote green travel methods, and reduce the impact on the ecological environment; (3) For traditional villages in the release (Ω) stage, traditional villages have undergone major changes in some aspects, and the original economic and population models have been broken, and they are in a state of disorder. Therefore, it is necessary to strengthen resource and environmental protection, stimulate ecological awareness, promote the development of emerging industries, promote economic development, integrate and standardize land management, and ensure the sustainable development of land use. (4) For traditional villages in the renewal (α) stage, after the release state, traditional villages will be re-integrated and reorganized to enter the next stage of development. Therefore, it is necessary to formulate scientific plans, strengthen infrastructure construction, guide villages to become livable and modern, strengthen social services and public management, and improve the quality of life of residents.

Traditional villages in a pathological state are in a process of negative decline: (1) For traditional villages in poverty, the economy and population of traditional villages have experienced stagnation or shrinkage, which usually leads to reduced income of villagers, lower living standards, and weakened village governance. They need to be guided back into the development (r) state, which can reduce the intensity of resource development related to the industry; based on the carrying capacity of resources and the environment, make softer economic compensation and development methods; reduce the disturbance of construction activities to the ecosystem; establish an ecological compensation mechanism; and encourage villagers to participate in village governance; (2) For traditional villages in a rigid state, traditional villages are rigid in many aspects and cannot adapt to changes in the external environment. Therefore, it is necessary to encourage villagers to participate in village governance and improve their sense of autonomy; introduce new technologies and new ideas to promote the innovative development of traditional villages; increase policy support and encourage investment and social capital intervention; (3) For traditional villages in a locked-in state, traditional villages are rigid or stagnant in some aspects and are difficult to develop further. Therefore, it is necessary to encourage traditional villages to transform their industries and strengthen the protection of intangible cultural heritage; increase the protection of cultural heritage and improve the management mechanism of historical and cultural heritage; formulate and implement development plans and promote regional coordinated development; (4) For traditional villages facing unknown difficulties, problems that are difficult to predict and solve have emerged in the process of development of traditional villages. These problems may come from changes in the external environment or from internal structural adjustments. In this case, traditional villages need to adopt innovative ideas to find new development opportunities. Specifically, case analysis is required, and innovative thinking is needed to introduce new concepts and technologies and explore new development paths.

Compared with the prior art, the present invention has the following advantages: it proposes a classification and zoning protection and control method for traditional villages based on an adaptive cycle path, constructs an adaptive cycle path for traditional villages from three aspects: unit attributes, spatial structure, and dynamic trends of traditional villages, namely, locality, mobility, and resilience. Through the high and low numerical combination relationship of the three, it can effectively judge the solidification phenomenon of traditional villages in a pathological state, and provide a basis and reference for policy formulation and rural governance for which villages should be protected first and from which dimensions. Specifically:

(1) From the perspective of adaptive index selection: This method not only considers the multi-dimensional spatial and non-spatial elements of traditional villages, such as individual ecology, economy, environment, and culture; it also constructs the correlation relationship based on different inflow and outflow resource elements from the perspective of the mobility correlation network between traditional villages, and considers the regional correlation and system integrity between individuals and individuals, individuals and groups, and groups and groups in traditional villages; it also analyzes the future development potential of life, production, and ecology from the perspective of the dynamic trend of the traditional village system in the time dimension, and quantitatively reflects the ability of traditional villages to quickly rebuild, treat, migrate, and restore steady state in response to various uncertain interferences. The selection of indicators is rational and objective, and a comprehensive analysis is carried out using a digital technology platform, so as to more scientifically and effectively evaluate the adaptive cycle path of traditional villages as a whole from a macro and global perspective.

(2) From the perspective of adaptive cycle paths: At present, many methods for the protection and control of traditional villages are based on types and regional characteristics. The technology of the present invention can effectively make diachronic judgments from the dynamic perspective of the spatiotemporal evolution of villages, forming a method with the advantages of comprehensive elements, time continuity and development stages. Through the current characteristics of traditional villages, the traditional villages are divided into two current development states and eight development stages based on adaptive cycle paths. The development stages of villages are classified and zoned based on comprehensive diachronic changes. It is no longer a static time section protection and control, but focuses on the historical relevance and development continuity of traditional villages.

(3) From the perspective of method applicability and implementation: This method is not targeted at individual traditional villages, but rather forms a holistic, objective, and targeted protection and development strategy for traditional villages with different characteristics and facing different problems from a regional perspective. The overall judgment and classification and zoning protection and control of village development are conducive to the connection with the national land space planning system and the strengthening of strategic layout such as policy inclination and financial support. The method has a wide range of applications and data is easy to obtain, so it can effectively judge the solidification phenomenon of traditional villages in a pathological state, and provide a basis and reference for policy formulation and rural governance for which villages should be protected first and from which dimensions.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG1 is a flowchart of a traditional village classification and zoning protection control method based on an adaptive cycle path provided by the present invention.

FIG. 2 is a spatial distribution diagram of the 1st to 5th batches of 6,819 traditional villages in China according to an embodiment of the present invention.

FIG. 3 is an adaptive cycle path of a traditional village according to an embodiment of the present invention.

Figures 4A to 4C are respectively graphs of the spatial distribution changes of locality, mobility, and resilience of 6,819 traditional villages from 2000 to 2020 according to an embodiment of the present invention.

FIG5 is a diagram showing the dynamic changes in the number of classifications of 6819 traditional villages in eight stages of adaptability from 2000 to 2020 according to an embodiment of the present invention.

FIG6A is a spatial classification diagram of the adaptive cycle stages of 6,819 traditional villages from 2000 to 2020 according to an embodiment of the present invention.

FIG6B is a spatial classification diagram of the adaptive pathological status of 6819 traditional villages from 2000 to 2020 according to an embodiment of the present invention.

FIG. 7 is a clustering result (upper figure) of 6819 traditional villages based on adaptive cycle paths and a protection and control classification zoning map (lower figure) according to an embodiment of the present invention.

DETAILED DESCRIPTION

The present invention is further illustrated below in conjunction with the accompanying drawings and specific embodiments. It should be understood that these embodiments are only used to illustrate the present invention and are not intended to limit the scope of the present invention. After reading the present invention, modifications to various equivalent forms of the present invention by those skilled in the art all fall within the scope defined by the appended claims of the present application.

The present invention is a traditional village classification and zoning protection and control method based on adaptive cycle paths. First, basic data such as the locations of traditional Chinese villages are obtained, and the data is standardized. All data are imported into the geographic information system platform to establish a database. Through the three characteristic attributes of locality, mobility, and resilience, a comprehensive index system for the adaptability of traditional villages is constructed. The weight of each index is obtained based on the entropy method, and the adaptive cycle path of traditional villages is evaluated. Then, the three characteristic values of adaptability are quickly clustered based on the Euclidean distance, and the traditional villages are classified and zoned, thereby formulating a traditional village protection and control planning strategy for classification and zoning. As shown in Figure 1, the process of the present invention is as follows:

Step 1: The research area is set as 6819 traditional villages, as shown in Figure 2. To construct the adaptive cycle path of traditional villages, relevant data are obtained from various online open access platforms, including:

1.1) Chinese traditional village point vector data: from the Global Change Science Research Data Publishing System (https://www.resdc.cn/). The spatial coordinates of the data were extracted with reference to Baidu Maps and Google Earth images, based on the village name prompts and the geometric center of the village graphics, and the images of the roofs of ancient buildings as auxiliary judgment materials to extract the spatial location of the village. The data includes the first to fifth batches of traditional villages in China, a total of 6,819, and the main fields include the province, city, county, township, village, longitude, and latitude of the village.

1.2) Vector data of cultural relics protection units: The highest level of immovable cultural relics protection units approved by the State Council’s cultural relics administration department (State Administration of Cultural Heritage) are obtained through Python program from the AutoNavi Map application program interface (https://lbs.amap.com) to obtain the location data of 5,062 national key cultural relics protection units in the 1st to 8th batches, including name, type, latitude, longitude and other information.

1.3) Intangible cultural heritage point vector data, intangible cultural heritage inheritor point vector data: The State Council announced five batches of national project lists in 2006, 2008, 2011, 2014 and 2021, including ten categories: folk literature, traditional music, traditional dance, traditional drama, folk art, traditional sports, entertainment and acrobatics, traditional fine arts, traditional skills, traditional medicine, and folklore. Through Python program, a name simulation query was performed from the Amap application program interface (https://lbs.amap.com) to obtain five batches of 3068 intangible cultural heritage inheritors and 3610 intangible cultural heritage point data in China, including name, type, latitude, longitude and other information.

1.4) Religious temple point vector data, school point vector data, medical facility point vector data, government point vector data, railway station point vector data, national A-level scenic spot point vector data: This type of data comes from Point of Interest (POI), which refers to geographic points with attribute labels and locations, which can reflect the geographical distribution of different functional spaces in traditional villages. The points of interest come from China's large-scale map service provider AutoNavi Map. Through the Python program, 525,043 POI point data in traditional villages in 2021 were obtained from the AutoNavi Map application programming interface (https://lbs.amap.com), including 324,611 schools (kindergartens, primary schools, middle schools, colleges and universities, general colleges and universities, national adult colleges and universities) POI point data, 176,783 medical services (clinics, health service centers, hospitals, national tertiary hospitals, etc.) POI point data, 3,204 municipal, county and district government POI point data, 3,066 railway station POI point data, 13,604 national A-level scenic spots POI point data, 3,775 temples, Taoist temples, churches, mosques and other religious temple space POI point data.

1.5) Terrain relief raster data: First, obtain the spatial distribution data of China's altitude (DEM), which comes from the radar topography SRTM (Shuttle Radar Topography Mission, SRTM) data of the US Space Shuttle Endeavour. Then, in GIS, calculate the slope, aspect and slope length through the spatial analysis tool, and then use the focal statistics tool under the neighborhood analysis in the spatial analysis tool to extract the maximum and minimum values of the altitude data, and then use the "raster calculator" to subtract the minimum value of the altitude from the maximum value of the altitude, which is the terrain relief, thus obtaining the terrain relief raster data.

1.5) Road vector data: Road network data includes vector data of high-speed rail, railway, expressway, national highway (including urban expressway, trunk road, etc.), provincial highway (including urban secondary trunk road, etc.), county road (including urban branch road), township road (urban pedestrian road), etc. The data comes from Peking University Geographic Data Platform (https://geodata.pku.edu.cn).

1.6) River system vector data: The river network data is a Chinese river basin and river network dataset extracted based on altitude, including all river networks in the country and all sub-basins with an area greater than 100 ^km2 . The river network data used comes from the Resource and Environmental Science and Data Center of the Chinese Academy of Sciences (https://www.resdc.cn/data.aspx?DATAID=335).

1.7) Annual precipitation distribution raster data, solar radiation raster data, and annual average temperature raster data: They are sourced from the National Earth System Science Data Center (http://www.geodata.cn), the Meteorological Data Network, and the China Surface Climate Data Daily Dataset. The spatial resolution of the three most important meteorological data (precipitation, solar radiation, and temperature) raster data is 1 km.

1.8) Vegetation Net Primary Productivity raster data: Vegetation Net Primary Productivity (NPP) refers to the energy absorbed by plants through photosynthesis during primary production, minus the energy consumed by respiration, which can be used to measure plant growth and reproduction. The data comes from the Moderate Resolution Imaging Spectroradiometer MODIS (https://lpdaac.usgs.gov/product_search/?view=listhttps://lpdaac.usgs.gov/product_search/?view=list), with a spatial resolution of 500m.

1.9) Grid data of multiple cropping area of cultivated land: The multiple cropping index of cultivated land is an indicator that describes how many crops are planted in succession in the same farmland within a year. It is an important indicator to measure the intensive utilization of cultivated land resources. The data comes from the Global Agricultural Remote Sensing Rapid Report of the Institute of Space Information Innovation, Chinese Academy of Sciences. The spatial resolution of the raster data is 30m.

1.10) Annual population density distribution grid data: This is the kilometer grid data of China’s population distribution based on spatial statistical units from the Resource and Environmental Science Data Center of the Chinese Academy of Sciences. The spatial resolution of this dataset is 1km, and the unit is person/square kilometer, which can better reflect the spatial distribution of the population.

1.11) Vector data of per capita GDP of prefecture-level cities: derived from China City Statistical Yearbook, China City Construction Statistical Yearbook, China Statistical Yearbook, China City Economic Yearbook and local statistical yearbooks and development reports.

1.12) The above basic data include: point vector data of traditional village history and culture, point vector data of traditional village different functional spaces, natural geographic vector and raster data, and socio-economic development vector and raster data. All vector data are imported into the GIS platform in shp format, and raster data in img format, and geometrically corrected to a unified spatial reference coordinate system according to the World Geodetic System (WGS 1984 version).

1.13) Based on the four types of basic data in step 1.12), use the neighborhood analysis tool, spatial analysis tool, spatial link tool and other analysis tools in GIS to calculate the distance of the traditional village point data to the nearest cultural relic protection unit, the spatial distance to the nearest religious temple, the distance to the intangible cultural heritage and the terrain undulation of the location, which will be used as the traditional village locality index in the subsequent step 2.1); then calculate the spatial distance of the traditional village point data to the nearest school point, the spatial distance to the nearest medical facility point, the spatial distance to the nearest government point, the spatial distance to the nearest highway, the spatial distance to the nearest railway station point and the spatial distance to the nearest national A-level scenic spot, which will be used as the traditional village mobility index in the subsequent step 2.1); finally, calculate the change in vegetation net primary productivity, precipitation value, population density, multiple cropping area of arable land, solar radiation, temperature, per capita regional GDP of the prefecture-level city, distance to the river system and distance to the location of the intangible cultural heritage inheritor, which will be used as the traditional village resilience index in the subsequent step 2.1). The above data are standardized and then imported into the GIS platform to establish a traditional village database.

Step 2: Based on the three characteristic attributes of locality, mobility, and resilience, a comprehensive index system of adaptability of 6,819 traditional villages was constructed. The weights of 19 indicators were obtained from an objective perspective based on the entropy method, and the values of the three characteristic attributes were calculated to evaluate the adaptive cycle path of traditional villages, as shown in Figure 3. Specifically, it includes:

2.1) Constructing a comprehensive index system for the adaptability of traditional villages: Taking 6,819 traditional village sites as the object, the three characteristic attributes of locality, mobility, and resilience are calculated to characterize the unit attributes, spatial structure, and dynamic trends, as shown in Figures 4A to 4C. The comprehensive index system for the adaptability of traditional villages is as follows:

2.2) Obtain the weights of each indicator from an objective perspective based on the entropy method: To obtain the weights of the indicators of locality, mobility, and resilience, the entropy method (Formula (1) to Formula (4)) is used to objectively weight each indicator in step 2.1). Before weighting, the data is uniformly standardized. The weighting results are as follows:

2.3) According to the different indicator layers contained in the three-aspect criterion layer of traditional village locality, mobility and resilience in step 2.1), combined with the weights of each indicator in step 2.2), the indicator values of the three-aspect criterion layer of traditional village locality, mobility and resilience of 6819 traditional villages were calculated by formula (5).

2.4) Evaluate the adaptive cycle path of traditional villages: Based on the three characteristic attributes of adaptability of traditional villages, namely locality, mobility and resilience, calculated in step 2.3), generate the adaptive cycle path model of traditional villages "locality-mobility-resilience". According to formula (6) to formula (7), the adaptability is determined by the high H and low L characteristic values of locality, mobility and resilience. According to the table below, the adaptive cycle paths of 6189 traditional villages are divided into two states: cycle stage and pathological state, including a total of 8 development stages of traditional villages (development (r), protection (K), release (Ω), renewal (α), poverty dilemma, rigid dilemma, locked dilemma, unknown dilemma). The specific classification is as follows:

Figures 5 and 6A and 6B show the classification quantity and spatial distribution of the two states and eight development stages of the adaptive cycle paths of 6,819 traditional villages from 2000 to 2020.

As shown in Figure 5, the proportion of the eight development stage types of 6,819 traditional villages from 2000 to 2020 remained basically stable, and the order from large to small is: poverty dilemma, development (r), unknown dilemma, renewal (α), lock-in dilemma, release (Ω), protection (K), and rigid dilemma. The number of villages in the cyclic state and the pathological state remained basically the same in the five years. From 2000 to 2020, the cycle stage of some traditional villages was in a cyclic transformation, but the overall dynamic stability remained. The transformation of the four cycle states of development (r), protection (K), release (Ω), and renewal (α) was relatively strong, while the transformation of the four pathological states of poverty dilemma, unknown dilemma, lock-in dilemma, and rigid dilemma was relatively weak, indicating that the list of villages in the pathological state was basically stable and gradually solidified. When traditional villages in most cycle stages were disturbed by the outside world, they entered the next cycle stage from the previous cycle stage and maintained a dynamic healthy state. Only a small number of them broke through the threshold of the adaptive cycle and entered a pathological state. The transformation from 2000 to 2005 was the most drastic, while the transformation in other years was relatively balanced. This shows that the degree of external interference to traditional villages was the greatest from 2000 to 2005, and other periods basically showed a relatively stable cycle transformation. The transformation paths of protection (K), release (Ω), rigid dilemma, and locked dilemma from 2000 to 2020 were relatively stable, and only a few villages were in a cycle of transformation. Development (r) and poverty dilemma are two types with relatively high transformation degrees. In the past 20 years, there are villages in the development (r) and poverty dilemma that have been stably transformed into each other. In addition, the number of villages that have transformed from renewal (α) to unknown dilemma is also relatively obvious.

As shown in Figure 6A and Figure 6B, according to the cycle stages of 6819 traditional villages: the main states are the development (r) stage and the renewal (α) stage. The development (r) stage is mainly distributed in the southern provinces, indicating that the traditional villages in the southern provinces are in a period of rapid development under policy protection and capital injection; the renewal (α) stage is mainly distributed in Yunnan, Zhejiang, and Fujian. The traditional villages in these three provinces have passed the rapid development period and entered an unstable reorganization or innovation period after development overload; protection (K) and release (Ω) are randomly distributed in the whole region. From 2000 to 2005, Yunnan's trend from renewal (α) to protection (K) is very obvious, indicating that Yunnan has entered the second cycle of development maturity from the uncertain state in the first cycle. According to the pathological status of 6,819 traditional villages: the main status is poverty and unknown dilemma. The poverty dilemma is mainly distributed in the central and northern provinces. Due to over-exploitation of resources, economic collapse and other reasons, these provinces broke through the threshold of the cycle in the development stage and fell into poverty. The distribution of unknown dilemma has obvious agglomeration characteristics, mainly distributed in the central and western regions, especially concentrated in Yunnan and Shanxi; locked-in dilemma covers the central, southern and eastern regions, especially concentrated in Anhui-Zhejiang-Fujian-Guangdong. The degree of policy protection and capital injection in these regions is very high, but due to the limited resources of the traditional villages themselves, they cannot be better upgraded and optimized; the proportion of traditional villages in rigid dilemma is relatively small, and the distribution is relatively random.

Step 3: Rapidly cluster the locality, mobility and resilience values of the 6,819 traditional villages obtained in step 2, classify and zone the traditional villages, and determine the planning strategy for protection and control based on the classification and zoning of traditional villages.

3.1) Rapid clustering of traditional villages based on Euclidean distance: According to the locality, mobility and resilience values of 6819 traditional villages, the spatial position coordinates are obtained through the traditional village point vector data in step 1, and the four values of spatial position, locality, mobility and resilience of traditional villages are imported into SPSS statistical analysis software for rapid clustering. The number of clusters is determined to be 10, and the number of iterations is set to 100. Based on the Euclidean distance method, according to the principle of closest distance, a rapid clustering algorithm is used to divide traditional villages into 10 categories. Through the GIS platform attribute connection tool, the traditional village point vector data in step 1 are imported. According to the clustering results of the GIS platform, Figure 7 shows the protection and control classification and zoning results of 6819 traditional villages based on adaptive cycle paths.

3.2) According to Figure 7, carry out the protection and control planning of traditional villages according to the following principles:

(1) For traditional villages in the development (r) and protection (K) stages, they are in a process of active growth and can maintain the protection and development of the existing industries, enhance and improve the living environment of residents, and promote the improvement of ecological value;

(2) For traditional villages in the release (Ω) and renewal (α) states, this stage is easily disturbed by the outside world and undergoes system reorganization. Based on the current characteristics of the ecological industry, it is necessary to comprehensively consider land use, industrial development, settlement layout, human settlement environment improvement, ecological protection, and historical and cultural heritage, and strengthen the coordination between ecology and industry;

(3) For traditional villages in poverty, reduce the intensity of industrial resource development, base on the carrying capacity of resources and the environment, adopt a softer economic compensation and development approach, reduce the disturbance of construction activities to the ecosystem, establish an ecological compensation mechanism, and guide them to re-enter the development (r) state;

(4) For traditional villages that are in a rigid and locked-in dilemma, in order to maintain a high resource and capital consumption process, they need to transform their industrial structure. In view of the current situation of scarce rural ecological resources, they need to emphasize bottom-line control, formulate a negative list for village development, and build a more complex and green endogenous economic system;

(5) For traditional villages facing unknown difficulties, case analysis is needed to provide targeted planning, development, management, and policy guidance from the perspective of regional ecosystem balance and industrial development.

The above is a specific implementation mode of the present invention, but the protection scope of the present invention is not limited to the above implementation mode. For those skilled in the art, without departing from the principle and spirit of the present invention, changes, modifications, replacements, integrations and variations to these embodiments still fall within the protection scope of the present invention.

Claims (6)

1. A traditional village classification zoning protection control method based on adaptive circulation paths, including the following steps: 1) Obtain basic data, standardize the data, and import all data into the geographic information system platform to establish a traditional village database; among which, the basic data includes: traditional village historical and cultural point vector data, different traditional villages There are four categories: functional space point vector data, physical geography vector and raster data, and social and economic development vector and raster data; 2) Construct a comprehensive indicator system for the adaptability of traditional villages through the three characteristic attributes of locality, mobility, and resilience. Based on the entropy method, obtain the weight of each indicator from an objective perspective, calculate the three characteristic attribute values, and evaluate the adaptability of traditional villages. Cycle path evaluation; 3) Perform rapid clustering based on the locality, mobility and resilience values of traditional villages obtained in step 2), classify and partition the traditional villages, and determine the planning strategy for protection and control according to the classification and zoning of traditional villages. 2. The method of claim 1, wherein step 1) includes: 1.1) Obtain basic data from various online open access platforms, including: (I) Traditional village historical and cultural point vector data: traditional village points, cultural relic protection unit points, religious temple points, and intangible cultural heritage points location, and the location of inheritors of intangible culture; (II) vector data of different functional spatial locations of traditional villages: school locations, medical facility locations, government locations, train station locations, and national A-level scenic spot locations; (III) Physical geography vector and raster data: river system vector data, terrain relief raster data, vegetation net primary productivity raster data, annual precipitation distribution raster data, cultivated land multiple cropping area raster data, solar radiation raster data, annual Average temperature raster data; (IV) Social and economic development vector and raster data: road vector data, annual population density distribution raster data, prefecture-level city per capita regional GDP vector data; import the above data into the geographic information system platform , the vector data adopts shp format, and the raster data adopts img format. The geometric correction is performed according to the world geodetic system and is accurate to a spatially unified reference coordinate system; 1.2) Based on the four types of basic data in step 1.1), use the neighborhood analysis tools, spatial analysis tools and spatial connection tools in the geographic information system to calculate the distance between the traditional village point data and the nearest cultural relic protection unit and the nearest religious temple. Spatial distance, distance from intangible cultural heritage and terrain relief of the location are used as local indicators of traditional villages in subsequent steps; then the spatial distance from the traditional village point data to the nearest school point and the nearest medical facility point are calculated respectively The spatial distance, the spatial distance to the nearest government point, the spatial distance to the nearest highway, the spatial distance to the nearest train station and the spatial distance to the nearest national A-level scenic spot are used as traditional village mobility indicators in subsequent steps; Finally, the changes in vegetation net primary productivity, precipitation value, population density, cultivated land multiple cropping area, solar radiation, temperature, per capita regional GDP of the location-level city, distance to river systems and distance to intangible cultural heritage were calculated for the location of the traditional village point data. The distance between people's locations is used as an indicator of traditional village resilience in subsequent steps; the above data is standardized and then imported into a geographic information system platform to establish a traditional village database. 3. The method of claim 1, wherein step 2) includes: 2.1) Construct a comprehensive indicator system for traditional village adaptability: Taking traditional village points as objects, the development path of traditional villages in the system adaptability cycle stage in response to external interference is expressed through changes in the three characteristic attributes of locality, mobility, and resilience. Dynamic response process, in which locality refers to the unit attributes of a traditional village as a system, mobility refers to the interaction process and correlation between individuals within the traditional village system, and resilience refers to the ability of the traditional village system to restore its steady state after being disturbed. , reflecting the dynamic trend of the traditional village system in the time dimension; each of the three criterion layers of locality, mobility and resilience contains multiple different indicator layers; 2.2) Obtain the weight of each indicator from an objective perspective based on the entropy method: Use the entropy method to objectively weight each indicator of locality, liquidity, and resilience in step 2.1). The formula is as follows: d _j =1-e _j (3) _{Among them , _ _} The total number of villages, n is the number of indicators; According to the different indicator layers included in the three criteria layers of locality, mobility and resilience of traditional villages in step 2.1), and combined with the weight of each indicator, the three criteria layer indicators of traditional villages' locality, mobility and resilience are calculated; the calculation formula is as follows: Among them, W _j is the weight of the j-th indicator; P _j is the value of the j-th indicator; L _i , M _i , and R _i are the values of the three criterion-level indicators of locality, mobility, and resilience of traditional villages, that is, the traditional Three characteristic attribute values of the village; l, m, n are respectively the total number of indicator layers included in the three criterion layers of locality, mobility and resilience of traditional villages; 2.3) Evaluate the adaptive cycle path of traditional villages: Based on the three characteristic attribute values of traditional village adaptability of locality, mobility, and resilience calculated in step 2.2), generate the "locality-mobility-resilience" of traditional villages. The adaptive cycle path model of , the adaptability is determined by the high H and low L characteristic values of locality, mobility and resilience; the calculation formula is as follows: Among them, A _i is the locality, mobility and resilience attribute index value of the i-th village, which is Li _, M _i and R _i in formula (5); s is the total number of traditional villages within the study scope, and H is the high-value set , L is the low value set; According to the table below, the adaptive cycle path of traditional villages is divided into two states: cycle stage and pathological state; Among them, the cycle stage includes the four development stages of development, protection, release, and renewal, and the pathological state includes the four development stages of poverty dilemma, rigid dilemma, locked dilemma, and unknown dilemma, which are the classification of 8 traditional villages. 4. The method of claim 3, wherein in step 2), the local indicator layer includes four categories: building courtyards, sacred spaces, traditional customs, and landscape patterns, which represent the scarcity of courtyards and buildings respectively. , the dependence on religion and belief, the uniqueness of traditional folk customs, and the regional nature of the village environment. The selected data are the distance to the nearest cultural relic protection unit, the spatial distance to the nearest religious temple, the distance to intangible cultural heritage, and the terrain relief; the so-called The indicator layer describing mobility includes educational mobility, medical mobility, administrative mobility, short-distance employment mobility, long-distance employment mobility, and tourism behavior, which respectively indicate the opportunity cost of villagers’ access to children’s education, the opportunity cost of villagers’ access to medical services, and the villagers’ access to The opportunity cost of administrative services, the opportunity cost for villagers to obtain resources from surrounding counties and towns, the opportunity cost for villagers to obtain long-distance urban resources, and the probability of tourists arriving at the village. The selection data are respectively the spatial distance to the nearest school and the distance to the nearest medical facility. The spatial distance to the location, the spatial distance to the nearest government point, the spatial distance to the nearest highway, the spatial distance to the nearest train station, the spatial distance to the nearest national A-level scenic spot; the resilience indicator layer includes vegetation coverage, Precipitation, river distance, intergenerational inheritance, population, production, sunshine, temperature, and economy respectively describe the trend of resilience against natural disturbance, precipitation abundance, supply of ecological products, inheritance of intangible culture, and intensity of human capital. The selected data include the degree of intensive utilization of cultivated land, the regional nature of village sunshine, the regional nature of village environment, the ability of self-repair and financial security. The selected data are the change trend of vegetation net primary productivity, precipitation, distance from river systems, and distance from inheritors of intangible culture. Location distance, population density, cultivated land area, solar radiation, temperature, and per capita regional GDP of prefecture-level cities. 5. The method of claim 3, wherein step 3) includes: 3.1) Rapid clustering of traditional villages based on Euclidean distance: According to the locality, mobility and resilience index values of traditional villages obtained in step 2), combined with the traditional village point vector data in the basic data in step 1), the spatial location coordinates are obtained. Import the four values of the spatial location, locality, mobility and resilience of traditional villages into SPSS statistical analysis software for rapid clustering; the rapid clustering method based on Euclidean distance, the formula is as follows: Among them, d(x _ij , y _ij ) is the Euclidean distance between traditional village i and traditional village j, x _i , y _i are respectively the horizontal and vertical coordinates of the point vector data of traditional village i, x _j , y _j are the traditional villages respectively. The horizontal and vertical coordinates of the vector data of point j; determine the number of clusters p according to the actual zoning needs of traditional villages. Next, randomly select the centroid for each cluster, and assign all traditional village data points to the cluster with the closest distance to this centroid. class; then, recalculate the centroid of each newly formed cluster, repeat the step of assigning all traditional village data points to the cluster closest to the centroid, and then recalculate the centroid of each newly formed cluster, By analogy, the above steps are repeated in the statistical analysis software according to the principle of closest distance, and so on, until the clustering group to which the traditional village belongs no longer changes; 3.2) Determine the classification and zoning of traditional village protection control: Import the clustering results in step 3.1) into the traditional village point vector data in the basic data in step 1) through the geographic information system platform attribute connection tool. According to the geographic information system The clustering results of the platform show that the protection and control zones of traditional villages based on adaptive circulation paths are determined, and the statistics of traditional village types in 2 states and 8 development stages within the zones are carried out; 3.3) Carry out classification and zoning protection and control planning for traditional villages according to different development stages. 6. The method according to claim 5, characterized in that step 3.3) carries out traditional village classification zoning protection and control planning according to the following principles: (a) For traditional villages in the development stage, it is necessary to pay attention to the rationalization of land planning and resource utilization, protect the ecological environment, strengthen the construction of infrastructure and public services, improve village functions, promote the development of specialty industries, and strengthen brand promotion; (b) For traditional villages in the protection stage, it is necessary to strengthen the protection of cultural heritage, protect buildings and cultural landscapes; encourage the protection and development of traditional handicrafts to create rural specialty products; promote green travel methods to reduce the impact on the ecological environment; (c) For traditional villages in the release stage, it is necessary to strengthen resource and environmental protection and stimulate ecological awareness; promote the development of emerging industries and promote economic development; conduct land integration and standardized management to ensure the sustainable development of land use; (d) For traditional villages in the renewal stage, it is necessary to formulate scientific plans and strengthen infrastructure construction; guide the villages towards livability and modernization; strengthen social services and public management, and improve the quality of life of residents; (e) For traditional villages in poverty, it is necessary to guide them to re-enter the development state and reduce the intensity of industrial-related resource development; to implement softer economic compensation and development methods based on the carrying capacity of resources and the environment; to reduce the disturbance of construction activities to the ecosystem ; Establish an ecological compensation mechanism; encourage villagers to participate in village governance; (f) For traditional villages in a rigid dilemma, it is necessary to encourage villagers to participate in village governance and improve their awareness of autonomy; introduce new technologies and new ideas to promote the innovative development of traditional villages; increase policy support and encourage the intervention of investment and social capital; (g) For traditional villages in trouble, it is necessary to encourage traditional villages to carry out industrial transformation and strengthen the protection of intangible cultural heritage; increase the protection of cultural heritage and improve the historical and cultural heritage management mechanism; formulate and implement development plans and promote coordinated regional development ; (h) For traditional villages in trouble, it is necessary to encourage traditional villages to undergo industrial transformation and strengthen the protection of intangible cultural heritage; increase the protection of cultural heritage and improve the historical and cultural heritage management mechanism; formulate and implement development plans to promote coordinated regional development .