CN112651145B - Urban diversity index analysis and visual modeling based on remote sensing data inversion - Google Patents
Urban diversity index analysis and visual modeling based on remote sensing data inversion Download PDFInfo
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Abstract
The invention provides an urban diversity index analysis and visual modeling system and a diversity analysis method based on remote sensing data inversion. The system comprises an urban data acquisition subsystem, a data scale selection subsystem, a data separation processing subsystem, a diversity index determination subsystem and a data inversion subsystem. The data scale selection subsystem automatically recommends the city data type and the city data scale required by the target diversity index; the data separation processing subsystem is used for separating target city data corresponding to the city data type and the city data scale from the city data acquisition subsystem; and the data inversion subsystem carries out inversion processing on the target city data based on a preset data inversion model to obtain a target diversity index, and displays a trend graph of different first diversity indexes along with time and space changes on a human-computer interaction interface. The invention can realize the visual display of different types of diversity indexes.
Description
Technical Field
The invention belongs to the technical field of urban diversity analysis, and particularly relates to an urban diversity index analysis and visual modeling system and a diversity analysis method based on remote sensing data inversion.
Background
The diversity is one of basic factors for human social survival, is an important measure for protecting the natural ecological environment of the human society, and is a fundamental guarantee for realizing the common and sustainable development goal of human and nature. Urban diversity is manifested in a number of ways, including biodiversity, functional diversity, landscape diversity, and land use diversity.
With the breakthrough of new scientific theory and research technology at home and abroad, the development of the remote sensing evaluation method and the model evaluation method from the traditional field evaluation to the recent years is realized, and the diversified evaluation and monitoring methods are more and more abundant and diversified and have various characteristics, so that the diversity research work is more rigorous and the achievement is more reliable. And the evaluation space-time scale is wider and more diversified, so that the diversity work is more macroscopic, the result is more scientific, and scientific basis and decision support are provided for the protection of diversity.
Through retrieval, in the patent literature, the chinese patent publication CN108665149A proposes a method for measuring and calculating based on city function mixedness, which comprises: the method comprises the steps of obtaining a POI data set, and classifying urban functions according to type information in the POI data set; drawing data of the urban road map layer, and extracting the central point of each road to be used as a measuring and calculating unit of the urban function mixedness; extracting adjacent blocks of the road where each measuring and calculating unit is located, and constructing city function mixing degree measuring and calculating indexes of each measuring and calculating unit; and establishing a function mixing degree measuring and calculating model, and measuring and calculating the city function mixing degree of each measuring and calculating unit.
Non-patents have studied more. The research on the function density and diversity of the urban blocks of the combined-fertilizer city by using big data (Zhanqiao. urban blocks of the combined-fertilizer city research on the function density and diversity [ D ]. Anhui architecture university, 2020.); jiadunxin takes happy coming ecological city of Chongqing as an example, a sample line is selected by comprehensively overlapping various landform and landform analysis results, 53 sample parties are selected along the sample line according to different types of plant communities, a plant attribute information database is constructed by means of GPS and GIS, and further, the ecological background conditions of the area are analyzed by applying statistical indexes (GIS-based city planning ecological background research, taking happy coming ecological city of Chongqing as an example [ J ], mapping and spatial geographic information, 2018,41(10): 156-.
However, in the actual decision making and application process, the solutions proposed in the above prior art are only analyzed for a specific type of single index. When a city decision maker needs to predict city diversity from multiple angles, data acquisition and evolution need to be performed one by one, so that the efficiency is low and the applicability is poor.
Disclosure of Invention
In order to solve the technical problems, the invention provides an urban diversity index analysis and visual modeling system and a diversity analysis method based on remote sensing data inversion. The system comprises an urban data acquisition subsystem, a data scale selection subsystem, a data separation processing subsystem, a diversity index determination subsystem and a data inversion subsystem. The data scale selection subsystem automatically recommends the city data type and the city data scale required by the target diversity index; the data separation processing subsystem is used for separating target city data corresponding to the city data type and the city data scale from the city data acquisition subsystem; and the data inversion subsystem carries out inversion processing on the target city data based on a preset data inversion model to obtain a target diversity index, and displays a trend graph of different first diversity indexes along with time and space changes on a human-computer interaction interface.
The invention further provides an urban diversity analysis method based on remote sensing data inversion, which is realized based on the system.
By adopting the technical scheme, the invention can realize the visual display of diversity indexes of different types.
Specifically, in a first aspect of the invention, an urban diversity index analysis system based on remote sensing data inversion is provided, and the system comprises an urban data acquisition subsystem, a data scale selection subsystem, a data separation processing subsystem, a diversity index determination subsystem and a data inversion subsystem.
The specific implementation functions and corresponding technical means of each subsystem are as follows:
the city data acquisition subsystem: obtaining a plurality of diversity sample data of the city, wherein the plurality of diversity sample data comprise satellite remote sensing space sample data, GIS geographic space sample data, laser radar point cloud data and unmanned aerial vehicle remote sensing data;
a data scale selection subsystem: storing a relation table of urban data scales of different diversity indexes and required corresponding types, determining a target diversity index type determined by a subsystem based on the diversity indexes, and automatically recommending the urban data types and the urban data scales required by the target diversity index;
the data separation processing subsystem: based on the city data type and the city data scale automatically recommended by the data scale selection subsystem, separating target city data corresponding to the city data type and the city data scale from the city data acquisition subsystem;
a data inversion subsystem: and performing inversion processing on the target city data based on a preset data inversion model to obtain the target diversity index.
As one of the choices of the diverse indexes of the present invention, the diverse indexes include an urban land use diverse index, an urban landscape diverse index, an urban functional diverse index, and an urban biodiverse index.
As one of the data inversion model selections for realizing the diversity indexes, the predetermined data inversion model comprises an NPP model, a GARP model, an InVest model, ENFA and a MAXENT model.
Corresponding to the model diversity and the index diversity, the data inversion subsystem carries out inversion processing on the target city data based on a preset data inversion model to obtain the target diversity index, and the inversion processing comprises the following steps:
the data inversion subsystem obtains at least two time-varying trend graphs of the same target diversity index through at least two preset data inversion models;
and displaying the at least two trend graphs changing along with time in the same coordinate system under the same data scale in a visualized mode.
The diversity index analysis system based on the first aspect provides a city diversity index visual modeling system based on remote sensing data inversion in the second aspect of the invention, wherein the visual modeling system comprises a human-computer interaction interface, and the human-computer interaction interface comprises an interface switching button and a diversity index type selection button;
the data inversion subsystem is connected with the human-computer interaction interface;
based on the first diversity index selected by the diversity index type selection button, the data inversion subsystem obtains at least two trend graphs of the first diversity index along with time and space changes based on at least two preset data inversion models.
And displaying the trend graphs of the different first diversity indexes along with the time and the space on the human-computer interaction interface through the interface switching button.
Based on the diversity index analysis system of the first aspect, the invention also provides an urban diversity analysis method based on remote sensing data inversion,
the method firstly establishes a corresponding relation table of different diversity indexes, required corresponding types of city data types and data scales, and then executes the following steps:
s100: determining urban diversity analysis requirements, and determining a target diversity index type based on the urban diversity analysis requirements;
s101: determining a city data type and a city data scale required by the city diversity analysis based on the target diversity index type;
in this step, based on the correspondence table, the city data type and the city data scale required by the target diversity index are determined.
S102: obtaining target city data corresponding to the city data type and the city data scale based on the city data type and the city data scale;
s103: and performing inversion processing on the target city data based on a preset data inversion model to obtain the target diversity index.
According to the technical scheme, data analysis matching and diversified multi-angle visual index analysis display can be automatically realized by acquiring sample data of different data scales and data types and based on analysis requirements of different types of diversity indexes.
Further advantages of the invention will be apparent in the detailed description section in conjunction with the drawings attached hereto.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings needed in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings without creative efforts.
FIG. 1 is a combined architecture diagram of a subsystem of an index analysis system of urban diversity based on remote sensing data inversion according to an embodiment of the present invention
FIG. 2 is a schematic diagram of a data source of a city data acquisition subsystem in the system of FIG. 1
FIG. 3 is a schematic diagram of the diversity index types supported by the diversity index determination subsystem in the system of FIG. 1
FIG. 4 is a representation of corresponding associations held by the data scale selection subsystem in the system of FIG. 1
FIG. 5 is an architecture diagram of a remote sensing data inversion-based urban diversity index visualization modeling system according to an embodiment of the present invention
FIG. 6 is a diagram of the main steps of a remote sensing data inversion-based urban diversity analysis method according to an embodiment of the present invention
Detailed Description
Referring to fig. 1, a subsystem combination architecture diagram of an urban diversity index analysis system based on remote sensing data inversion according to an embodiment of the present invention is shown.
In fig. 1, the system includes a city data acquisition subsystem, a data scale selection subsystem, a data separation processing subsystem, a diversity index determination subsystem, and a data inversion subsystem.
The city data acquisition subsystem is used for acquiring various diversity sample data of the city;
the data scale selection subsystem stores a relation table of different diversity indexes and required corresponding types of city data scales, determines a target diversity index type determined by the subsystem based on the diversity indexes, and automatically recommends the city data type and the city data scales required by the target diversity index;
the data separation processing subsystem is used for separating target city data corresponding to the city data type and the city data scale from the city data acquisition subsystem based on the city data type and the city data scale automatically recommended by the data scale selection subsystem;
and the data inversion subsystem carries out inversion processing on the target city data based on a preset data inversion model so as to obtain the target diversity index.
More specifically, on the basis of fig. 1, referring to fig. 2, fig. 2 shows a data source schematic diagram of the city data acquisition subsystem in the system shown in fig. 1.
In fig. 2, the multiple diversity sample data includes satellite remote sensing space sample data, GIS geospatial sample data, lidar point cloud data, and unmanned aerial vehicle remote sensing data.
Different sample data have different data scales, and the city data scale comprises a space scale and a time scale.
More specifically, the satellite remote sensing space sample data comprises a digital elevation model dataset, the digital elevation model dataset is a terrestrial dataset comprising the city, and the terrestrial dataset is updated according to a first preset period;
the GIS geospatial sample data is acquired from a pre-constructed geographic information system, the pre-constructed geographic information system comprises a plurality of databases, and the plurality of databases update the GIS geospatial sample data at a second preset period;
the laser radar point cloud data is acquired through a vehicle-mounted radar by a mobile radar measuring vehicle, and the mobile radar measuring vehicle moves on a first target route in the urban area;
the unmanned aerial vehicle remote sensing data is acquired based on the flight of the unmanned aerial vehicle in a range including the first target route;
wherein the first predetermined period is greater than the second predetermined period;
the spatial scale of the land data set is larger than that of the GIS geographic space sample data and that of the unmanned aerial vehicle remote sensing data;
the space scale of the unmanned aerial vehicle remote sensing data is larger than that of the laser radar point cloud data.
With continued reference to fig. 3, fig. 3 is a schematic diagram of the diversity index types supported by the diversity index determination subsystem in the system of fig. 1.
The diversity index comprises an urban land utilization diversity index, an urban landscape diversity index, an urban functional diversity index and an urban biodiversity index.
Diversity in land use, also known as multi-functional of land. The land use diversity index represents the evaluation scale of land use multifunctionality, and specifically comprises the steps of combining analysis means such as mathematical statistics and the like with spatial analysis technologies such as 3S and the like, measuring the land use multifunctionality of a certain time section, or a longer time sequence, or a specific area, and obtaining a measure index based on a preset index system;
generally speaking, there is some correlation between the urban land use diversity index and the urban landscape diversity index, but each has a weight, and similar introduction can be seen in the prior art:
zhang Lei, Qu Yong Hui, Nian Yuan, Zhao Fei, soil, land use diversity and its associated analysis with the related landscape index [ J ] ecology environmental science report, 2014,23(06):923-
Progress and projects of Multi-functional of land use research, LIU Chao, geosciences Advances 2016, 35 (9): 1087-.
The urban landscape diversity index is highly concentrated landscape pattern information and reflects simple quantitative indexes of certain aspects of characteristics of the structural composition and spatial configuration of the urban landscape pattern information; a spatial analysis method suitable for quantitatively expressing the correlation between landscape patterns and ecological processes.
In this embodiment, the city landscape diversity index includes a plurality of indexes or a weighted combination thereof, such as a landscape dominance index, a landscape evenness index, a landscape fragmentation index, and a landscape concentration index, wherein the landscape fragmentation index is associated with a subsequent city biodiversity index.
The introduction of the urban landscape diversity index can be seen in the following prior art:
research on relationship between the urban ecological service value and landscape diversity of Zhu Xiao Lei, Zhang Jian Jun, China mining industry, 2017,26(02):88-94.
The urban function diversity index, also called urban function mixedness, refers to the comprehensive composition status of urban function types closely related to the lives of residents in a specific urban area. The measuring, calculating and analyzing results have important practical significance in the aspects of urban resident traffic, land utilization perfection, urban planning layout and the like, and can provide important data support for urban traffic condition trip efficiency analysis, land utilization evaluation calculation, urban layout optimization analysis and the like.
Urban biodiversity index. Biodiversity is one of the most people focused on at the end 20, and is becoming a focus especially in cities, and its measure can be found in various prior art, such as the following:
sujing, city biodiversity index [ J ]. chinese environmental science, 2009,29(10):1110.
In the above embodiment of the present invention, the diversity index determining subsystem determines a target diversity index type, and the data scale selecting subsystem stores a city data scale relationship table of different diversity indexes and required corresponding types.
In particular, see fig. 4.
If the target diversity index determined by the diversity index determining subsystem is a land utilization diversity index or an urban landscape diversity index, the data separation processing subsystem acquires the satellite remote sensing space sample data and/or GIS geographic space sample data from the urban data acquiring subsystem;
and if the target diversity index determined by the diversity index determining subsystem is an urban function diversity index, the data separation processing subsystem acquires laser radar point cloud data and the unmanned aerial vehicle remote sensing data from the urban data acquiring subsystem.
And if the target diversity index determined by the diversity index determining subsystem is an urban biodiversity index, the data separation processing subsystem acquires satellite remote sensing space sample data, laser radar point cloud data and the unmanned aerial vehicle remote sensing data from the urban data acquiring subsystem.
The various diversity indexes are obtained by adopting the same or different data inversion models based on different sample data.
Specifically, the predetermined data inversion models include NPP models, GARP models, InVest models, ENFA, and MAXENT models.
Preferably, the data inversion subsystem performs inversion processing on the target city data based on a predetermined data inversion model to obtain the target diversity index, and specifically includes:
the data inversion subsystem obtains at least two time-varying trend graphs of the same target diversity index through at least two preset data inversion models;
and displaying the at least two trend graphs changing along with time in the same coordinate system under the same data scale in a visualized mode.
In the above model, different Net Primary Productivity (NPP) model methods can be used, based on Productivity being one of the main factors determining biodiversity; based on environmental factors, the model can adopt BIOCLIM, ENFA, GARP, MAXENT, INVEST and the like, which are collectively called as ecological niche models, and the ecological requirements of species are analyzed by utilizing known species distribution data and relevant environmental factor data, and the results are mapped into the space to predict actual distribution and potential distribution.
In addition, models based on ecological processes, including HSI, RAMAS, METAPHOR, VORTEX, etc.,
the model is mainly used for quantitatively analyzing the adaptability of species to a habitat space and the viability of the species.
The comprehensive model includes a "Driving force-State-Response" model (DSR), a Driving force-Pressure-State-influence-Response model (DPSIR), and the like.
On the basis of the above embodiment, fig. 5 is an architecture diagram of a remote sensing data inversion-based urban diversity index visualization modeling system according to an embodiment of the present invention.
In fig. 5, the visual modeling system is connected to the city diversity index analysis system based on remote sensing data inversion shown in fig. 1.
The visual modeling system comprises a human-computer interaction interface, wherein the human-computer interaction interface comprises an interface switching button and a diversity index type selection button;
the data inversion subsystem is connected with the human-computer interaction interface;
based on the first diversity index selected by the diversity index type selection button, the data inversion subsystem obtains at least two trend graphs of the first diversity index along with time and space changes based on at least two preset data inversion models.
Displaying the trend graphs of the different first diversity indexes along with the time and the space on the human-computer interaction interface through the interface switching button.
Finally, fig. 6 is a diagram showing the main steps of a city diversity analysis method based on remote sensing data inversion. The method can be implemented based on the system described in fig. 1.
The method of fig. 6 includes the steps of:
s100: determining urban diversity analysis requirements, and determining a target diversity index type based on the urban diversity analysis requirements;
s101: determining a city data type and a city data scale required by the city diversity analysis based on the target diversity index type;
s102: obtaining target city data corresponding to the city data type and the city data scale based on the city data type and the city data scale;
s103: performing inversion processing on the target city data based on a preset data inversion model to obtain the target diversity index;
wherein, as a critical component, before the step S100, the method comprises:
establishing a corresponding relation table of different diversity indexes, required corresponding types of city data types and data scales;
and the step S101 is to determine the city data type and the city data scale required by the target diversity index based on the corresponding relation table.
Practice proves that data analysis matching and diversified multi-angle visual index analysis display can be automatically realized by acquiring sample data of different data scales and data types and based on analysis requirements of different types of diversity indexes.
Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that changes, modifications, substitutions and alterations can be made in these embodiments without departing from the principles and spirit of the invention, the scope of which is defined in the appended claims and their equivalents.
Claims (10)
1. An urban diversity index analysis system based on remote sensing data inversion comprises an urban data acquisition subsystem, a data scale selection subsystem, a data separation processing subsystem, a diversity index determination subsystem and a data inversion subsystem,
the method is characterized in that:
the city data acquisition subsystem is used for acquiring various diversity sample data of the city, wherein the various diversity sample data comprises satellite remote sensing space sample data, GIS geographic space sample data, laser radar point cloud data and unmanned aerial vehicle remote sensing data;
the data scale selection subsystem stores a relation table of different diversity indexes and required corresponding types of city data scales, determines a target diversity index type determined by the subsystem based on the diversity indexes, and automatically recommends the city data type and the city data scales required by the target diversity index;
the data separation processing subsystem is used for separating target city data corresponding to the city data type and the city data scale from the city data acquisition subsystem based on the city data type and the city data scale automatically recommended by the data scale selection subsystem;
and the data inversion subsystem carries out inversion processing on the target city data based on a preset data inversion model so as to obtain the target diversity index.
2. The remote sensing data inversion-based urban diversity index analysis system according to claim 1,
the method is characterized in that:
the city data scale comprises a spatial scale and a temporal scale;
the city data type includes a combination of at least two of the plurality of diversity sample data.
3. The remote sensing data inversion-based urban diversity index analysis system according to claim 1,
the method is characterized in that:
the diversity index comprises an urban land utilization diversity index, an urban landscape diversity index, an urban functional diversity index and an urban biodiversity index.
4. The remote sensing data inversion-based urban diversity index analysis system as claimed in any one of claims 1-3,
the method is characterized in that:
the predetermined data inversion models include NPP models, GARP models, InVest models, ENFA and MAXENT models.
5. The remote sensing data inversion-based urban diversity index analysis system as claimed in any one of claims 1-3,
the method is characterized in that:
the satellite remote sensing space sample data comprises a digital elevation model data set, the digital elevation model data set is a land data set comprising the city, and the land data set is updated according to a first preset period;
the GIS geospatial sample data is acquired from a pre-constructed geographic information system, the pre-constructed geographic information system comprises a plurality of databases, and the plurality of databases update the GIS geospatial sample data at a second preset period;
the laser radar point cloud data is acquired through a vehicle-mounted radar by a mobile radar measuring vehicle, and the mobile radar measuring vehicle moves on a first target route in an urban range;
the unmanned aerial vehicle remote sensing data is acquired based on the flight of the unmanned aerial vehicle in a range including the first target route;
wherein the first predetermined period is greater than the second predetermined period;
the spatial scale of the land data set is larger than that of the GIS geographic space sample data and that of the unmanned aerial vehicle remote sensing data;
the space scale of the unmanned aerial vehicle remote sensing data is larger than that of the laser radar point cloud data.
6. The remote sensing data inversion-based urban diversity index analysis system according to claim 4,
the method is characterized in that:
if the target diversity index determined by the diversity index determining subsystem is a land utilization diversity index or an urban landscape diversity index, the data separation processing subsystem acquires the satellite remote sensing space sample data and/or GIS geographic space sample data from the urban data acquiring subsystem;
and if the target diversity index determined by the diversity index determining subsystem is an urban function diversity index, the data separation processing subsystem acquires laser radar point cloud data and the unmanned aerial vehicle remote sensing data from the urban data acquiring subsystem.
7. The city diversity index analysis system based on remote sensing data inversion as claimed in any one of claims 1-3 or 6,
the method is characterized in that:
the data inversion subsystem carries out inversion processing on the target city data based on a preset data inversion model to obtain the target diversity index, and the data inversion subsystem specifically comprises the following steps:
the data inversion subsystem obtains at least two time-varying trend graphs of the same target diversity index through at least two preset data inversion models;
and displaying the at least two trend graphs changing along with time in the same coordinate system under the same data scale in a visualized mode.
8. A city diversity index visual modeling system based on remote sensing data inversion, the visual modeling system is connected with the city diversity index analysis system based on remote sensing data inversion of any one of claims 1-6,
it is characterized in that the preparation method is characterized in that,
the visual modeling system comprises a human-computer interaction interface, wherein the human-computer interaction interface comprises an interface switching button and a diversity index type selection button;
the data inversion subsystem is connected with the human-computer interaction interface;
based on the first diversity index selected by the diversity index type selection button, the data inversion subsystem obtains at least two trend graphs of the first diversity index along with time and space changes based on at least two preset data inversion models.
9. The remote sensing data inversion-based urban diversity index visualization modeling system of claim 8,
the method is characterized in that:
displaying the trend graphs of the different first diversity indexes along with the time and the space on the human-computer interaction interface through the interface switching button.
10. A city diversity analysis method based on remote sensing data inversion,
the method is characterized in that:
the method comprises the following steps:
s100: determining urban diversity analysis requirements, and determining a target diversity index type based on the urban diversity analysis requirements;
s101: determining a city data type and a city data scale required by the city diversity analysis based on the target diversity index type;
s102: obtaining target city data corresponding to the city data type and the city data scale based on the city data type and the city data scale;
s103: performing inversion processing on the target city data based on a preset data inversion model to obtain the target diversity index;
prior to the step S100, the method comprises:
establishing a corresponding relation table of different diversity indexes, required corresponding types of city data types and data scales;
and the step S101 is to determine the city data type and the city data scale required by the target diversity index based on the corresponding relation table.
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