Method for crop rotation planting zoning based on Arc-GIS and meteorological factors

Abstract

The invention provides a crop rotation planting zoning method based on Arc-GIS and meteorological factors. The method comprises the steps of data collection, data processing, spatial analysis, suitability evaluation, visual output and continuous monitoring and updating. Meteorological data comprises a plurality of factors such as air temperature, day and night temperature difference, effective accumulated temperature, active accumulated temperature and precipitation, unary linear regression analysis is carried out through analytical statistics software, and interpolation is carried out through a Kriging interpolation method by utilizing Arc-GIS software, so that a surface element vector data graph of meteorological factors suitable for the growth period of crops is obtained. And crop planting regions are obtained through spatial analysis, and finally, the planting regions are classified according to crop suitability and visual output is carried out. The invention provides a scientific and systematic crop rotation planting zoning method.

Description

Technical Field

[0001] The invention belongs to the field of agricultural management and geographic information system (Arc-GIS), and more specifically relates to a method for crop rotation planting zoning based on Arc-GIS and meteorological factors. Background Art

[0002] Crop rotation is an important agricultural management measure to improve soil fertility, reduce pests and diseases, and increase crop yields. Traditional crop rotation zoning methods often rely on experience and lack scientific basis, resulting in waste of resources. Meteorological factors have a significant impact on crop growth and yield. Arc-GIS technology has comprehensive data processing capabilities, powerful spatial analysis functions, high-quality visualization capabilities, flexible data integration, real-time data analysis capabilities and a wide range of applications. With the development of GIS technology, it has become possible to use spatial analysis and meteorological factors for scientific crop rotation zoning, which can guide agricultural production more scientifically. After searching, Liu Xingyu et al. published a paper titled "Climate Zoning of Autumn Corn in Chongqing Based on GIS" in "Plateau Mountain Meteorological Research" in 2019, but no method of combining meteorological factors and Arc-GIS for crop rotation pattern planting zoning has been found. Summary of the invention

[0003] The present invention provides a crop planting zoning method based on Arc-GIS and meteorological factors, aiming to improve the scientificity and rationality of crop planting through spatial data analysis.

[0004] In order to achieve the above object, the present invention is implemented by adopting the following technical scheme: the method comprises: Data collection: Collect meteorological data from multiple weather stations in the area where crop rotation is being carried out for many years; Data processing: The temperature, day-night temperature difference, effective accumulated temperature, active accumulated temperature and the altitude of the meteorological station in the spring rotation crop planting area were analyzed by linear regression using the DPS data processing system software; Spatial analysis: to determine the planting zoning of a certain crop in a certain planting area; Suitability evaluation: Through field trials, the growth performance of crops under different accumulated temperature conditions is obtained, and their growth, development and yield are analyzed; the crop rotation zoning areas are classified according to the suitability of various crops; Visualization and output: The DEM digital elevation map of the crop rotation zoning area was called out in the Arc-GIS software, and the reclassified raster dataset was converted into a surface feature vector data map to obtain the major spring crop planting zoning map; Using Arc-GIS software and Kriging interpolation method, we obtained the surface element vector data map of suitable meteorological factors for the growth period of spring and early spring crops. Use Arc-GIS to produce and output planting zoning maps for various crops and various rotation patterns.

[0005] In one embodiment, the meteorological data include: air temperature, temperature difference between day and night, effective accumulated temperature, active accumulated temperature, precipitation, sunshine hours, and frost period days; Suitable temperature, day-night temperature difference, effective accumulated temperature, active accumulated temperature, precipitation, sunshine hours, and frost period days during the growth period of rotation crops; DEM digital elevation map of the crop rotation zoning area; altitude of meteorological stations in the crop rotation zoning area.

[0006] In one embodiment, the data processing includes: The altitude of the weather station is taken as the independent variable, and the meteorological factor is taken as the dependent variable. The independent variable and the dependent variable are edited and defined as data blocks. After selecting the data block, the DPS data processing system is entered to perform a univariate linear regression analysis, and a univariate linear regression equation of the meteorological factor and the altitude is obtained. In one scheme, the spatial analysis includes: superimposing the surface element vector datasets of suitable temperature, day and night temperature difference, effective accumulated temperature, and active accumulated temperature during the growth period of a certain crop and the surface element vector datasets of precipitation, sunshine hours, and frost period days through the intersection tool under the overlay analysis in the system toolbox analysis tool to obtain the planting zoning of a certain crop in a certain planting area; the rotation planting zoning is obtained by superimposing the planting zoning of various rotation crops using the intersection tool under the overlay analysis in the system toolbox analysis tool.

[0007] In one embodiment, the suitability evaluation utilizes the spatial analysis tool of Arc-GIS to classify the crop rotation zoning areas according to the suitability of various crops, and to demarcate the most suitable areas, suitable areas, sub-suitable areas and unsuitable areas for various crops and various rotation patterns.

[0008] Beneficial effects of the present invention: The present invention uses a method combining Arc-GIS with meteorological factors for analysis, and through a univariate linear regression analysis of temperature data and meteorological station (point) altitude, a univariate linear regression equation for temperature data and altitude is obtained, which can correspond the altitude corresponding to each grid on the DEM digital elevation map to the temperature data one by one, and then reclassify according to the suitable meteorological data for planting a certain crop, so as to accurately delineate the suitable planting area of ​​a certain crop in a certain area. Meteorological factors with low correlation with altitude, such as precipitation, sunshine hours, and frost days, can be used to delineate the suitable planting area of ​​a certain crop in a certain area through the Kriging interpolation method. The planting zoning of the rotation pattern can be obtained by intersecting and superimposing the suitability zoning maps of different rotation crops to obtain the suitable planting area of ​​a certain rotation pattern. BRIEF DESCRIPTION OF THE DRAWINGS

[0009] Figure 1 Flow chart for zoning for major spring crops; Figure 2 Flow chart for early spring crop planting zoning; Figure 3 Flow chart for cropping zones in rotational cropping patterns; Figure 4 This is a step-by-step diagram for zoning flue-cured tobacco planting; Figure 5 A step-by-step diagram for zoning corn planting areas; Figure 6 This is a step-by-step diagram for zoning autumn rapeseed planting areas; Figure 7 This is the suitability distribution map of the flue-cured tobacco-rapeseed-corn rotation pattern. DETAILED DESCRIPTION

[0010] In order to facilitate the understanding of the present invention, the present invention will be described more fully below with reference to the relevant drawings. Typical embodiments of the present invention are given in the drawings. However, the present invention can be implemented in many different forms and is not limited to the embodiments described in the present invention. On the contrary, the purpose of providing these embodiments is to make the disclosure of the present invention more thorough and comprehensive.

[0011] Unless otherwise defined, all technical and scientific terms used in the present invention have the same meaning as those commonly understood by those skilled in the art of the present invention. The terms used in the specification of the present invention are only for the purpose of describing specific embodiments and are not intended to limit the present invention.

[0012] The present invention provides a crop planting zoning method based on ArcGIS and meteorological factors, aiming to improve the scientificity and rationality of crop planting through spatial data analysis. The method comprises the following steps: S1. Data collection: Purchase multi-year multi-point meteorological and altitude data from the local meteorological bureau. Register and download DEM digital elevation maps from the geospatial data cloud website. Collect meteorological data (temperature, day and night temperature difference, effective accumulated temperature, active accumulated temperature, precipitation, sunshine hours, frost days, etc.) of multiple meteorological stations (points) in the rotation planting zoning area for many years (more than 10 years). Suitable temperature, day and night temperature difference, effective accumulated temperature, active accumulated temperature, precipitation, sunshine hours, frost days, etc. during the growth period of rotation crops. DEM digital elevation map of the rotation planting zoning area. Altitude of meteorological stations (points) in the rotation planting zoning area.

[0013] S2. Data processing: Since the determination coefficient of the univariate linear regression equation between temperature and altitude during the growing period of big spring crops is high, a univariate linear regression analysis was performed on the temperature, day-night temperature difference, effective accumulated temperature, active accumulated temperature and altitude of meteorological stations (points) in the planting area of ​​big spring rotation crops using analytical statistical software, and a univariate linear regression equation for temperature, day-night temperature difference, effective accumulated temperature, active accumulated temperature and altitude was obtained. The DEM digital elevation map of the crop rotation zoning area was called out in Arc-GIS software, and the raster calculator under the geographic algebra tool in the spatial analysis toolbox was used. The DEM digital elevation was used as the x value of the univariate linear regression equation, and the univariate linear regression equation was input into the raster calculator as a geographic algebra expression. After running the raster calculator, the air temperature, day and night temperature difference, effective accumulated temperature, and active accumulated temperature were interpolated onto the DEM digital elevation map. Then, the obtained raster data map was reclassified according to the suitable temperature, day and night temperature difference, effective accumulated temperature, and active accumulated temperature during the growth period of a certain crop. The reclassified raster data set was converted into a surface feature vector data map through the raster to surface tool under the raster conversion tool in the conversion toolbox to obtain the major spring crop planting zoning map.

[0014] Since the coefficient of determination of the linear regression equation of precipitation during the growth period of major spring crops, temperature and precipitation during the growth period of minor spring crops and altitude is low, the precipitation of multiple meteorological stations (points) in the major spring crop planting area, the temperature, day and night temperature difference, effective accumulated temperature, active accumulated temperature, precipitation, sunshine hours, and frost days of multiple meteorological stations (points) in the minor spring crop planting area are interpolated using the Kriging interpolation method using Arc-GIS software. The Excel table with coordinates and meteorological data of multiple meteorological stations (points) is converted into an ExcelToTable table through the Excel conversion tool in the conversion toolbox, and combined with the administrative division layer of the division area, the Kriging method of the interpolation analysis in the spatial analysis toolbox is used for interpolation calculation, and the meteorological data points of the division area are interpolated into a raster surface. Then, the obtained raster data surface is reclassified according to the suitable meteorological factors for planting during the growth period of a certain crop using the Reclassification tool in the Spatial Analysis Toolbox, and the reclassified raster dataset is converted into a surface feature vector data map using the Raster to Surface tool under the Raster to Surface tool in the Conversion Toolbox to obtain a planting zoning map for a certain crop growth period. The surface feature vector data map of the suitable meteorological factors for the growth period of the major and minor spring crops is obtained.

[0015] The univariate linear regression equation is expressed as y (meteorological factor) = A-Bx (elevation of the weather station).

[0016] The Excel table with multiple meteorological station (point) coordinates and meteorological data is converted into an ExcelToTable table through the Excel conversion tool in the conversion toolbox. Combined with the administrative division layer of the division area, the Kriging method of the interpolation analysis in the spatial analysis toolbox is used for interpolation calculation to interpolate the meteorological data points of the division area into a raster surface. Then, the reclassification tool in the spatial analysis toolbox is used to reclassify the obtained raster data surface according to the suitable meteorological factors for planting during the growth period of a certain crop, and a planting zoning map for the growth period of a certain crop is obtained.

[0017] Mathematical formula of Kriging interpolation method: Where: Z(si) is the measurement value at the i-th position, λi is the unknown weight of the measurement value at the i-th position, s0 is the predicted position, and N is the number of measurements.

[0018] S3. Spatial analysis: The surface feature vector datasets of suitable temperature, day-night temperature difference, effective accumulated temperature and active accumulated temperature during the growing period of a certain crop and the surface feature vector datasets of precipitation, sunshine hours and frost period days are superimposed using the Intersect tool under the Overlay Analysis in the system toolbox analysis tools to obtain the planting zoning of a certain crop in a certain planting area; the rotation planting zoning is obtained by superimposing the planting zoning of various rotation crops using the Intersect tool under the Overlay Analysis in the system toolbox analysis tools.

[0019] S4. Suitability evaluation: Using the spatial analysis tools of Arc-GIS, the crop rotation zoning areas were classified according to the suitability of various crops, and the most suitable areas, suitable areas, sub-suitable areas and unsuitable areas for various crops and various rotation patterns were demarcated.

[0020] S5. Visualization and output: The DEM digital elevation map of the crop rotation zoning area was called out in the Arc-GIS software, and the univariate linear regression equation of air temperature, day-night temperature difference, effective accumulated temperature, active accumulated temperature and altitude was inputted using the raster calculator in the toolbox. The air temperature, day-night temperature difference, effective accumulated temperature and active accumulated temperature were interpolated onto the DEM digital elevation map. Then, the obtained raster data map was reclassified according to the suitable temperature, day-night temperature difference, effective accumulated temperature and active accumulated temperature during the growth period of a certain crop. The reclassified raster data set was converted into a surface feature vector data map through the Raster to Surface tool under the Raster to Surface tool in the Conversion Toolbox, and the planting zoning map of major spring crops was obtained.

[0021] The precipitation of multiple meteorological stations (points) in the major spring crop planting area, and the temperature, day and night temperature difference, effective accumulated temperature, active accumulated temperature, precipitation, sunshine hours and frost days of multiple meteorological stations (points) in the minor spring crop planting area were interpolated using the Kriging interpolation method using Arc-GIS software. Then the obtained vector data maps were reclassified according to the suitable meteorological factors in the growth period of a certain crop. The reclassified raster datasets were converted into surface feature vector data maps through the Raster to Polygon tool under the Raster Conversion Tool in the Conversion Toolbox, and the surface feature vector data maps of the suitable meteorological factors in the growth period of major and minor spring crops were obtained.

[0022] Then, the surface element vector datasets of suitable temperature, day and night temperature difference, effective accumulated temperature, and active accumulated temperature during the growth period of a certain crop and the surface element vector datasets of precipitation, sunshine hours, and frost period days are superimposed through the intersection tool under the overlay analysis in the system toolbox analysis tool to obtain the planting zoning of a certain crop in a certain planting area. The rotation planting zoning can be obtained by superimposing the planting zoning of various rotation crops using the intersection tool. Finally, Arc-GIS is used to produce and output planting zoning maps of various crops and various rotation patterns.

[0023] Finally, Arc-GIS was used to insert titles, compasses, legends, and scales to produce and output planting zoning maps for various crops and various rotation patterns, and an analysis report was written to provide a basis for agricultural planting zoning decisions.

[0024] Embodiment 1: Planting zoning was carried out for the flue-cured tobacco-rapeseed-corn rotation pattern in Yunnan Province.

[0025] 1. Collect the altitude of 129 meteorological stations in Yunnan Province, the annual effective accumulated temperature ≥10℃ and the precipitation from October to April (autumn-sown rapeseed), and the accumulated temperature ≥10℃ from May to September (corn); DEM digital elevation map of Yunnan Province (30×30m); the suitable altitude range for flue-cured tobacco planting is 1200-2000m, the most suitable range of active accumulated temperature ≥10℃ for autumn-sown rapeseed is 3000-7000℃ and the most suitable range of precipitation during the growing period is 150-450mm, and the most suitable range of effective accumulated temperature ≥10℃ during the growing period of corn is ≥1300℃.

[0026] Second, use Arc-GIS software to import the Yunnan Province DEM digital elevation map, reclassify the digital elevation map according to the suitable altitude range of flue-cured tobacco planting, 1200-2000m, and then use the raster-to-surface tool to convert the reclassified raster data map into a surface feature vector data map to obtain the Yunnan Province flue-cured tobacco planting zoning map (see Figure 4 ).

[0027] The effective accumulated temperature of corn during the growth period ≥10℃ and the altitude of 129 meteorological stations in Yunnan Province were analyzed by univariate linear regression analysis using statistical analysis software, and the univariate linear regression equations of effective accumulated temperature of corn during the growth period ≥10℃ and altitude were obtained as y=2866.1272-0.71x (y is the effective accumulated temperature of corn during the growth period, x is the altitude). The DEM digital elevation map of Yunnan Province was called up in Arc-GIS software, and the univariate linear regression equation of effective accumulated temperature of corn during the growth period ≥10℃ and altitude was input using the raster calculator in the toolbox. The effective accumulated temperature of corn during the growth period ≥10℃ was interpolated to the DEM digital elevation map, and then the obtained raster data map was reclassified according to the effective accumulated temperature range of corn during the growth period ≥10℃, and the reclassified raster data set was converted into a surface feature vector data map through the raster to surface tool to obtain the corn planting zoning map (see Figure 5 ).

[0028] The annual active accumulated temperature ≥10℃ and the precipitation during the rapeseed growing period of 129 meteorological stations in Yunnan Province were interpolated using the Kriging interpolation method using Arc-GIS software. Then the obtained vector data map was reclassified according to the suitable meteorological factors during the rapeseed growing period and converted into a surface element vector data map of the suitable meteorological factors during the rapeseed growing period. The rapeseed planting zoning map was obtained (see Figure 6 ).

[0029] By intersecting and overlaying the flue-cured tobacco planting zoning map, corn planting zoning map and rapeseed planting zoning map, we can obtain the suitability distribution map of the flue-cured tobacco-rapeseed-corn rotation pattern in Yunnan Province (see Figure 7 ).

[0030] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiments can be implemented by instructing the relevant hardware through a computer program, and the program can be stored in a computer-readable storage medium, and when the program is executed, it can include the processes of the embodiments of the above-mentioned methods. The storage medium can be a disk, an optical disk, a read-only memory (ROM) or a random access memory (RAM).

[0031] It should be understood that the detailed description of the technical solutions of the present invention by means of the preferred embodiments is illustrative rather than restrictive. A person skilled in the art may modify the technical solutions described in the embodiments, or replace some of the technical features by equivalents, based on reading the specification of the present invention; and these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for crop rotation zoning based on ArcGIS and meteorological factors, characterized by: The method includes: Data collection: Collect meteorological data from multiple weather stations in the area where crop rotation is being carried out for many years; Data processing: The temperature, day-night temperature difference, effective accumulated temperature, active accumulated temperature and the altitude of the meteorological station in the spring rotation crop planting area were analyzed by linear regression using the DPS data processing system software; Spatial analysis: to determine the planting zoning of a certain crop in a certain planting area; Suitability evaluation: Through field trials, the growth performance of crops under different accumulated temperature conditions is obtained, and their growth, development and yield are analyzed; the crop rotation zoning areas are classified according to the suitability of various crops; Visualization and output: The DEM digital elevation map of the crop rotation zoning area was called out in the Arc-GIS software, and the reclassified raster dataset was converted into a surface feature vector data map to obtain the major spring crop planting zoning map; Using Arc-GIS software and Kriging interpolation method, we obtained the surface element vector data map of suitable meteorological factors for the growth period of spring and early spring crops. Use Arc-GIS to produce and output planting zoning maps for various crops and various rotation patterns.

2. The method for crop rotation zoning based on ArcGIS and meteorological factors according to claim 1, characterized in that: The meteorological data include: temperature, temperature difference between day and night, effective accumulated temperature, active accumulated temperature, precipitation, sunshine hours, and frost period days; Suitable temperature, day-night temperature difference, effective accumulated temperature, active accumulated temperature, precipitation, sunshine hours, and frost period days during the growth period of rotation crops; DEM digital elevation map of the crop rotation zoning area; altitude of meteorological stations in the crop rotation zoning area.

3. The method for crop rotation zoning based on ArcGIS and meteorological factors according to claim 1, characterized in that: The data processing includes: The altitude of the weather station is taken as the independent variable, and the meteorological factor is taken as the dependent variable. The independent variable and the dependent variable are edited and defined as data blocks. After selecting the data block, enter the DPS data processing system for univariate linear regression analysis to obtain the univariate linear regression equation of the meteorological factor and altitude.

4. The method for crop rotation zoning based on ArcGIS and meteorological factors according to claim 1, characterized in that: The spatial analysis includes: superimposing the surface element vector datasets of suitable temperature, day and night temperature difference, effective accumulated temperature and active accumulated temperature during the growth period of a certain crop and the surface element vector datasets of precipitation, sunshine hours and frost period days through the intersection tool under the overlay analysis in the system toolbox analysis tool to obtain the planting zoning of a certain crop in a certain planting area; the rotation planting zoning is obtained by superimposing the planting zoning of various rotation crops using the intersection tool under the overlay analysis in the system toolbox analysis tool.

5. The method for crop rotation zoning based on ArcGIS and meteorological factors according to claim 1, characterized in that: The suitability evaluation utilizes the spatial analysis tool of Arc-GIS to classify the crop rotation zoning areas according to the suitability of various crops, and demarcate the most suitable areas, suitable areas, sub-suitable areas and unsuitable areas for various crops and various rotation patterns.

Images