Space-time coupling coordination analysis method for cultivated land quantity, quality, ecology and grain safety

Abstract

The invention discloses a cultivated land quantity, quality, ecology and grain safety time-space coupling coordination analysis method, which comprises a data collection module, a data statistics module and a coupling coordination analysis module, and is characterized in that the data collection module comprises a cultivated land quantity statistics module, a cultivated land quality statistics module and a cultivated land ecology statistics module; the data statistics module comprises a grain safety module and a spatio-temporal data statistics module, the actual area of the cultivated land is calculated according to the landform, soil conditions and hydrological condition changes of the cultivated land, and then the fertility of the cultivated land is layered through soil physics, soil chemistry and soil biology; according to the farmland fertility, the total grain output of the current year is estimated, the grain output reduction caused by the predicted major weather disasters of the current year is subtracted, and after the result is compared with the total grain output, the multiple cropping index, the grain self-sufficiency rate and the grain reserve data of the previous years, the grain gap of the current year can be analyzed to facilitate follow-up implementation of corresponding measures for supplementation.

Description

Technical Field

[0001] The present invention relates to the field of food security, and in particular to a method for analyzing the spatiotemporal coupling coordination of cultivated land quantity, quality, ecology and food security. Background Art

[0002] Faced with the increasingly serious trend of reduced amount of arable land, deteriorating quality of arable land and the gradual erosion of arable land production capacity by rapid urbanization and industrialization, how to protect the increasingly scarce arable land resources has become a focus of concern for the government and all sectors of society.

[0003] Traditional methods of farmland management and food security assessment often consider the quantity or quality of farmland in isolation, ignoring their dynamic relationship and spatiotemporal coupling characteristics with the ecological environment and food security. Therefore, it is necessary to integrate the previous years' data with the real-time situation and demand of farmland, and then comprehensively consider the current needs. Therefore, it is necessary to propose a spatiotemporal coupling coordination analysis method for farmland quantity, quality, ecology and food security. Summary of the invention

[0004] In response to the problems in the prior art, the present invention provides a method for analyzing the spatiotemporal coupling coordination of cultivated land quantity, quality, ecology and food security.

[0005] The technical solution adopted by the present invention to solve the technical problem is: a method for analyzing the spatiotemporal coupling coordination of cultivated land quantity, quality, ecology and food security, comprising a data collection module, a data statistics module and a coupling coordination analysis module, wherein the data collection module comprises a cultivated land quantity statistics module, a cultivated land quality statistics module and a cultivated land ecology statistics module, and the data statistics module comprises a food security module and a spatiotemporal data statistics module. The cultivated land quantity statistics module includes cultivated land area, per capita cultivated land area, cultivated land change rate, etc., which are used to reflect the quantity status of cultivated land resources; The farmland quality statistics module analyzes the farmland quality based on soil physics, soil chemistry and soil biology data, and sets multiple levels for the farmland quality; The farmland ecological statistics module is based on the topography, soil conditions, hydrological conditions and climate conditions of the farmland location; The food security module includes data on total food production, multiple cropping index, food self-sufficiency rate, and food reserves; The spatiotemporal data statistics module is used to collect historical statistics of various indicators of cultivated land quantity, quality, ecology and food security; The coupling coordination analysis module adopts appropriate mathematical models (such as coupling degree model, coordination degree model) to quantify the degree of coupling coordination between cultivated land quantity, quality, ecology and food security; When using: Step 1: First, collect real-time data on cultivated land area, cultivated land change rate, soil physics, soil chemistry, soil biology, as well as topography, soil conditions, hydrological conditions and climate conditions of the cultivated land area. Then collect data on total grain output, multiple cropping index, grain self-sufficiency rate and grain reserves in previous years. Step 2: Calculate the actual area of ​​cultivated land according to the changes in the topography, soil conditions, and hydrological conditions of the cultivated land, and then stratify the fertility of the actual cultivated land through soil physics, soil chemistry, and soil biology, and calculate the total grain output of the year based on the fertility of the actual cultivated land; Step 3: Remove the impact of previous years' climate conditions on grain planting, and add all of them to the total grain output of previous years to get the grain output calculation data of previous years. Then, according to the forecast of this year's climate conditions, predict major domestic weather disasters and calculate the impact of reduced production on grain planting on cultivated land, so as to roughly get the grain output calculation data of this year. Step 4: Calculate this year's grain self-sufficiency rate by using this year's grain output data, and then compare it with previous years' grain output data. Combined with grain reserves, the grain gap can be determined. After that, some arable land can be replanted to supplement the food gap or purchased from outside.

[0006] Preferably, the soil physical indicators include soil texture, structure and porosity, the soil chemistry includes pH value, organic matter content, nitrogen, phosphorus and potassium nutrient content, and the soil biology includes microbial diversity and enzyme activity.

[0007] Preferably, the calculation data for grain production this year is the total grain production that can be grown by the actual fertility of cultivated land this year minus the grain production reduction caused by major weather disasters predicted this year.

[0008] Preferably, the calculation data of grain production in previous years is the total grain production in previous years plus the grain production reduction caused by major weather disasters in previous years.

[0009] Preferably, the multiple cropping index is the average number of times crops are planted on the same plot of cultivated land within a certain period of time (generally 1 year), that is, the average number of times crops are planted on the cultivated land in a year, which is numerically equal to the ratio of the total sown area of ​​crops on the cultivated land in the year to the cultivated land area.

[0010] Preferably, the fertility of the land is analyzed based on soil physics, soil chemistry and soil biology data, and the land is divided into high-grade fields with sufficient fertility, medium-grade fields in normal use and low-grade fields that need to be left fallow and supplemented with fertilizer.

[0011] Preferably, low-grade fields with low fertility calculated through soil physics, soil chemistry, and soil biology, and low-grain yield, or fields in the fallow period and newly cultivated fields with low grain yield, can be used as supplementary fields for replanting when the estimated grain output is insufficient, and the low-grade fields that are fallow and fertilized should be rotated during replanting until they are restored to the medium-grade fields for normal use.

[0012] Preferably, the forecast of climate conditions is first to read the weather forecast for this year's planting period issued by the National Meteorological Administration, then collect weather data before and after planting, and judge whether the weather during this year's planting period will affect planting or harvesting by combining data from previous years, and secondly collect data on major domestic weather disasters predicted in the weather forecast issued by the National Meteorological Administration, and judge the percentage of production reduction based on the major weather disasters predicted in the weather forecast and the scope affected by the major weather disasters, and then judge the percentage of production reduction based on the scale of the major weather disasters combined with data from previous years, and then multiply the total grain output within the scope of the major weather disaster by the percentage of production reduction, so as to estimate the impact of major weather on grain planting.

[0013] Beneficial effects of the present invention: The spatiotemporal coupling coordination analysis method of cultivated land quantity, quality, ecology and food security described in the present invention, when used, calculates the actual area of ​​cultivated land according to changes in the topography, soil conditions and hydrological conditions of the cultivated land, and then stratifies the fertility of the actual cultivated land through soil physics, soil chemistry and soil biology, and calculates the total grain output of this year according to the fertility of the actual cultivated land, and then deducts the grain production reduction caused by major weather disasters predicted for this year, and then compares with the total grain output, multiple cropping index, grain self-sufficiency rate and grain reserve data of previous years, so as to analyze the grain gap of this year to facilitate the subsequent implementation of corresponding measures to supplement it. DETAILED DESCRIPTION

[0014] In order to make the technical means, creative features, objectives and effects achieved by the present invention easy to understand, the present invention is further explained below in conjunction with specific implementation methods.

[0015] The method for analyzing the spatiotemporal coupling coordination of cultivated land quantity, quality, ecology and food security described in the present invention comprises a data collection module, a data statistics module and a coupling coordination analysis module. The data collection module comprises a cultivated land quantity statistics module, a cultivated land quality statistics module and a cultivated land ecology statistics module. The data statistics module comprises a food security module and a spatiotemporal data statistics module. The cultivated land quantity statistics module includes cultivated land area, per capita cultivated land area, cultivated land change rate, etc., which is used to reflect the quantity status of cultivated land resources; The farmland quality statistics module analyzes the quality of farmland based on soil physics, soil chemistry and soil biology data, and sets multiple levels for the quality of farmland. The cultivated land ecological statistics module is based on the topography, soil conditions, hydrological conditions and climate conditions of the cultivated land location; The food security module includes data on total grain output, multiple cropping index, grain self-sufficiency rate, and grain reserves; The spatiotemporal data statistics module is used to collect historical statistics on various indicators of cultivated land quantity, quality, ecology and food security; The coupling coordination analysis module uses appropriate mathematical models (such as coupling degree model and coordination degree model) to quantify the degree of coupling coordination between cultivated land quantity, quality, ecology and food security; When using: Step 1: First, collect real-time data on cultivated land area, cultivated land change rate, soil physics, soil chemistry, soil biology, as well as topography, soil conditions, hydrological conditions and climate conditions of the cultivated land area. Then collect data on total grain output, multiple cropping index, grain self-sufficiency rate and grain reserves in previous years. Step 2: Calculate the actual area of ​​cultivated land according to the changes in the topography, soil conditions, and hydrological conditions of the cultivated land, and then stratify the fertility of the actual cultivated land through soil physics, soil chemistry, and soil biology, and calculate the total grain output of the year based on the fertility of the actual cultivated land; Step 3: Remove the impact of previous years' climate conditions on grain planting, and add all of them to the total grain output of previous years to get the grain output calculation data of previous years. Then, according to the forecast of this year's climate conditions, predict major domestic weather disasters and calculate the impact of reduced production on grain planting on cultivated land, so as to roughly get the grain output calculation data of this year. Step 4: Calculate this year's grain self-sufficiency rate by using this year's grain output data, and then compare it with previous years' grain output data. Combined with grain reserves, the grain gap can be determined. After that, some arable land can be replanted to supplement the food gap or purchased from outside.

[0016] Among them, soil physical indicators include soil texture, structure and porosity, soil chemistry includes pH value, organic matter content, nitrogen, phosphorus and potassium nutrient content, and soil biology includes microbial diversity and enzyme activity.

[0017] Among them, the calculation data for this year's grain output is the total grain output that can be grown by the actual fertility of the cultivated land this year minus the grain production reduction caused by major weather disasters predicted this year.

[0018] Among them, the calculation data of grain production in previous years is the total grain production in previous years plus the grain production reduction caused by major weather disasters in previous years.

[0019] Among them, the multiple cropping index is the average number of times crops are planted on the same plot of cultivated land within a certain period of time (generally one year), that is, the average number of times crops are planted on the cultivated land area within the year. The numerical value is equal to the ratio of the total sown area of ​​crops on the cultivated land to the cultivated land area within the year.

[0020] Among them, the fertility of the land is analyzed based on the data of soil physics, soil chemistry and soil biology, and it is divided into high-grade fields with sufficient fertility, medium-grade fields in normal use, and low-grade fields that need to be fallowed and supplemented with fertilizer.

[0021] Among them, low-grade fields with low fertility calculated through soil physics, soil chemistry, and soil biology, and low grain yield, or fields in the fallow period and newly cultivated fields with low grain yield, can be used as supplementary fields for replanting when the estimated grain output is insufficient, and the low-grade fields that are fallow and fertilized should be replanted in a rotation system until they are restored to normal use as medium fields.

[0022] Among them, the forecast of climate conditions is first to read the weather forecast for this year's planting period issued by the National Meteorological Administration, then collect weather data before and after planting, and combine data from previous years to judge whether the weather during this year's planting period will affect planting or harvesting. Secondly, collect data on major domestic weather disasters predicted in the weather forecast issued by the National Meteorological Administration, and judge the percentage of production reduction based on the major weather disasters predicted in the weather forecast and the scope of impact of the major weather disasters. Then, multiply the total grain output within the scope of the major weather disaster by the percentage of production reduction, so as to estimate the impact of major weather on grain planting.

[0023] The above shows and describes the basic principles, main features and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The above embodiments and descriptions are only for explaining the principles of the present invention. Without departing from the spirit and scope of the present invention, the present invention may have various changes and improvements, which fall within the scope of the present invention. The scope of the present invention is defined by the attached claims and their equivalents.

Claims

1. A spatiotemporal coupling coordination analysis method for cultivated land quantity, quality, ecology and food security, comprising a data collection module, a data statistics module and a coupling coordination analysis module, characterized in that: The data collection module includes a cultivated land quantity statistics module, a cultivated land quality statistics module and a cultivated land ecological statistics module, and the data statistics module includes a food security module and a spatiotemporal data statistics module. The cultivated land quantity statistics module includes cultivated land area, per capita cultivated land area, cultivated land change rate, etc., which are used to reflect the quantity status of cultivated land resources; The farmland quality statistics module analyzes the farmland quality based on soil physics, soil chemistry and soil biology data, and sets multiple levels for the farmland quality; The farmland ecological statistics module is based on the topography, soil conditions, hydrological conditions and climate conditions of the farmland location; The food security module includes data on total food production, multiple cropping index, food self-sufficiency rate, and food reserves; The spatiotemporal data statistics module is used to collect historical statistics of various indicators of cultivated land quantity, quality, ecology and food security; The coupling coordination analysis module adopts appropriate mathematical models (such as coupling degree model, coordination degree model) to quantify the degree of coupling coordination between cultivated land quantity, quality, ecology and food security; When using: Step 1: First, collect real-time data on cultivated land area, cultivated land change rate, soil physics, soil chemistry, soil biology, as well as topography, soil conditions, hydrological conditions and climate conditions of the cultivated land area. Then collect data on total grain output, multiple cropping index, grain self-sufficiency rate and grain reserves in previous years. Step 2: Calculate the actual area of ​​cultivated land according to the changes in the topography, soil conditions, and hydrological conditions of the cultivated land, and then stratify the fertility of the actual cultivated land through soil physics, soil chemistry, and soil biology, and calculate the total grain output of the year based on the fertility of the actual cultivated land; Step 3: Remove the impact of previous years' climate conditions on grain planting, and add all of them to the total grain output of previous years to get the grain output calculation data of previous years. Then, according to the forecast of this year's climate conditions, predict major domestic weather disasters and calculate the impact of reduced production on grain planting on cultivated land, so as to roughly get the grain output calculation data of this year. Step 4: Calculate this year's grain self-sufficiency rate by using this year's grain output data, and then compare it with previous years' grain output data. Combined with grain reserves, the grain gap can be determined. After that, some arable land can be replanted to supplement the food gap or purchased from outside.

2. The temporal and spatial coupling coordination analysis method of cultivated land quantity, quality, ecology and food security according to claim 1 is characterized by: The soil physical indicators include soil texture, structure and porosity; the soil chemistry includes pH value, organic matter content, nitrogen, phosphorus and potassium nutrient content; and the soil biology includes microbial diversity and enzyme activity.

3. The temporal and spatial coupling coordination analysis method of cultivated land quantity, quality, ecology and food security according to claim 1 is characterized by: The calculation data for this year's grain output is the total grain output that can be grown based on the actual fertility of the cultivated land this year minus the predicted grain production reduction caused by major weather disasters this year.

4. The temporal and spatial coupling coordination analysis method of cultivated land quantity, quality, ecology and food security according to claim 1 is characterized by: The calculation data for grain production in previous years is the total grain production in previous years plus the grain production reduction caused by major weather disasters in previous years.

5. The temporal and spatial coupling coordination analysis method of cultivated land quantity, quality, ecology and food security according to claim 1 is characterized by: The multiple cropping index refers to the average number of times crops are planted on the same plot of cultivated land within a certain period of time (generally one year), that is, the average number of times crops are planted on the cultivated land in a year. The numerical value is equal to the ratio of the total sown area of ​​crops on the cultivated land in the year to the cultivated land area.

6. The temporal and spatial coupling coordination analysis method of cultivated land quantity, quality, ecology and food security according to claim 1 is characterized by: The fertility of the land is analyzed based on the data of soil physics, soil chemistry and soil biology, and is divided into high-grade fields with sufficient fertility, medium-grade fields in normal use, and low-grade fields that need to be left fallow and supplemented with fertilizer.

7. The temporal and spatial coupling coordination analysis method of cultivated land quantity, quality, ecology and food security according to claim 6 is characterized by: Low-grade fields with low fertility calculated through soil physics, soil chemistry, and soil biology, and low grain yield, or fields in the fallow period and newly cultivated fields with low grain yield, can be used as supplementary fields for replanting when the estimated grain output is insufficient; and the low-grade fields that are fallow and fertilized should be rotated during replanting until they are restored to normal use as medium-grade fields.

8. The temporal and spatial coupling coordination analysis method of cultivated land quantity, quality, ecology and food security according to claim 1 is characterized by: The forecast of climate conditions is first to check the weather forecast for this year's planting period issued by the National Meteorological Administration, then collect weather data before and after planting, and combine data from previous years to determine whether the weather during this year's planting period will affect planting or harvesting. Secondly, collect data on major domestic weather disasters predicted in the weather forecast issued by the National Meteorological Administration, and determine the percentage of production reduction based on the scale of major weather disasters and the scope of impact predicted in the weather forecast. Then multiply the total grain output within the scope of the major weather disaster by the percentage of production reduction, so as to estimate the impact of major weather on grain planting.