Saline-alkali soil tillage suitability grading method and system

Abstract

The invention discloses a saline-alkali soil tillage suitability grading method and system, and belongs to the technical field of agricultural land resource evaluation. The method comprises the following steps: firstly, collecting multi-dimensional data including a basic soil index, an environmental condition index and a crop adaptation index; secondly, index data are processed through an extreme value standardization method, and the dimensional influence is eliminated; an AHP-entropy weight combination weighting method is adopted to determine index weights, and subjective experience and objective data features are considered; calculating a suitability comprehensive index based on a weighted summation method; and finally, dividing the tillage suitability of the saline-alkali soil into four grades of high suitability, moderate suitability, mild suitability and unsuitability in combination with a comprehensive index and a dynamic threshold adjustment mechanism. The method solves the problems that an existing evaluation method is single in index, fixed in standard and low in efficiency, can provide an accurate and scientific basis for saline-alkali soil improvement and utilization and crop planting planning, and has remarkable economic and ecological benefits.

Description

Technical Field

[0001] This invention relates to the field of agricultural land resource assessment technology, and in particular to a method and system for classifying the suitability of saline-alkali land for cultivation. Background Technology

[0002] Saline-alkali land refers to soil types with excessively high salt and alkali content, which inhibit crop growth. It is widely distributed in arid, semi-arid, and coastal regions worldwide. With global population growth and decreasing arable land resources, the improvement and rational utilization of saline-alkali land has become an important way to ensure food security and expand agricultural production space.

[0003] Existing methods for assessing the suitability of saline-alkali land for cultivation have the following shortcomings:

[0004] First, the assessment indicators are too simplistic, often relying solely on soil salinity or pH as core indicators, neglecting the comprehensive impact of soil texture, fertility, groundwater level, and climate conditions on crop growth, resulting in a significant discrepancy between the assessment results and actual farming needs.

[0005] Secondly, the grading standards lack uniformity and flexibility. Different regions use fixed grading thresholds, which cannot adapt to the growth characteristics of different crops and regional environmental differences.

[0006] Third, the assessment process relies on manual sampling and laboratory analysis, which is inefficient and makes it difficult to achieve dynamic monitoring and real-time assessment of large-scale saline-alkali land.

[0007] Therefore, this invention proposes a multi-indicator fusion, standard-adaptable, efficient and accurate method and system for classifying the suitability of saline-alkali land for cultivation, in order to solve the defects of existing technologies and promote the scientific utilization of saline-alkali land resources. Summary of the Invention

[0008] The purpose of this invention is to provide a method and system for classifying the suitability of saline-alkali land for cultivation. By constructing a multi-dimensional evaluation index system and introducing a weight calculation and dynamic threshold adjustment mechanism, the method achieves accurate and efficient classification of the suitability of saline-alkali land for cultivation, providing reliable technical support for saline-alkali land improvement and crop planting planning.

[0009] A method for classifying the suitability of saline-alkali land for cultivation includes the following steps:

[0010] S1. Data Acquisition: Collect multi-dimensional assessment index data for the target saline-alkali area. These assessment indicators include basic soil indicators, environmental condition indicators, and crop suitability indicators. The basic soil indicators include at least total soil salinity (S), soil pH (pH), soil texture (T), and soil organic matter content (O). The environmental condition indicators include at least annual average precipitation (P), annual average evaporation (E), and groundwater level depth (G). The crop suitability indicators include at least the salt tolerance threshold (Sc) and alkali tolerance threshold (pH) of the target crop. c Suitable soil texture (Tc);

[0011] S2. Indicator Standardization Processing: The indicator data collected in step S1 is standardized using the extreme value standardization method to obtain the standardized value (X). i For positive indicators, according to the formula... Calculations, for negative indicators, are performed according to the formula. Calculation; for the classification index soil texture (T), based on the suitable soil texture (T) in the crop suitability index. c Assign values; if T = Tc, then Xi = 1; if T and Tc are different, then Xi = 1. c If they are similar, then X i =0.5, if T and T c If the difference is large, then X i =0;

[0012] S3. Determining Indicator Weights: A combined weighting method using the Analytic Hierarchy Process (AHP) and entropy weighting is employed to calculate the final weight (w) of each evaluation indicator. i First, a judgment matrix is ​​constructed using the AHP method, and the subjective weights (w) are obtained after a consistency check. i, (Subjective), and then based on standardized indicator data according to the formula Calculate information entropy (H) i ), and according to the formula Obtain objective weights (w) i,客观 Finally, according to formula w i =0.5×w i,主观 +0.5×w i,客观 The final weights are obtained through fusion;

[0013] S4. Calculation of the overall suitability index: based on the standardized value (X) from step S2. i ) and the final weight (w) of step S3 i According to the formula Calculate the overall suitability index (I);

[0014] S5. Suitability Level Classification: Based on the comprehensive index (I) obtained in step S4, and combined with regional agricultural production needs and crop growth characteristics, the suitability of saline-alkali land for cultivation is divided into four levels: Level 1 suitability corresponds to I∈[0.8,1.0], Level 2 suitability corresponds to I∈[0.5,0.8], Level 3 suitability corresponds to I∈[0.2,0.5], and Level 4 suitability corresponds to I∈[0,0.2]. A correction coefficient (k) is introduced, calculated according to formula I... 修正 =I×k dynamically adjusts the threshold for classifying grades, where k ranges from [0.8, 1.2].

[0015] Furthermore, in step S1, the data acquisition method combines "field sampling + remote sensing monitoring + database retrieval"; wherein, after obtaining soil samples through field sampling, the total salt content, pH value, and organic matter content of the soil are obtained through laboratory testing; the spatial distribution of regional soil texture is obtained based on remote sensing image data; annual average precipitation, evaporation, and groundwater depth data are retrieved from meteorological station databases and hydrological monitoring databases; and crop suitability indicators are obtained by querying agricultural crop characteristic databases.

[0016] Furthermore, in step S3, the target layer of the hierarchical model is "suitability for saline-alkali land cultivation," the criterion layer includes basic soil indicators, environmental condition indicators, and crop suitability indicators, and the indicator layer consists of the specific indicators mentioned in step S1; and in the formula, n is the sample size. X ij Let m be the standardized value of the i-th indicator for the j-th sample, and m be the total number of indicators.

[0017] Furthermore, in step S5, the cultivation conditions and improvement requirements corresponding to each level are as follows: Level 1 is suitable and requires no special improvement, with crop yield reaching more than 80% of normal cultivated land; Level 2 is suitable and requires slight improvement, with crop yield reaching 50%-80% of normal cultivated land after improvement; Level 3 is suitable and requires moderate improvement, with crop yield reaching 30%-50% of normal cultivated land after improvement; Level 4 is suitable and even with heavy improvement, crop yield is still less than 30% of normal cultivated land, and it is not suitable as cultivated land for the target crop.

[0018] A system for classifying the suitability of saline-alkali land for cultivation includes a data acquisition module, a data preprocessing module, a weight calculation module, a comprehensive index calculation module, a classification module, and a result output module.

[0019] The data acquisition module includes a sampling unit, a remote sensing data receiving unit, and a database interface unit. The sampling unit is used to control the sampling equipment to complete the collection of soil samples in the field. The remote sensing data receiving unit is used to receive satellite remote sensing image data and retrieve soil texture information. The database interface unit is used to establish connections with meteorological databases, hydrological databases, and crop characteristic databases and retrieve data.

[0020] The data preprocessing module includes a data cleaning unit and a standardization processing unit; the data cleaning unit is used to remove outliers and fill in missing data using the mean imputation method; the standardization processing unit is used to perform the standardization calculation in step S2 of claim 1 and output a standardized index dataset.

[0021] The weight calculation module includes an AHP weight calculation unit, an entropy weight calculation unit, and a combined weight fusion unit; the AHP weight calculation unit provides an expert judgment matrix input interface and automatically completes consistency verification and subjective weight calculation; the entropy weight calculation unit performs the objective weight calculation of step S3 of claim 1; the combined weight fusion unit performs the combined weight calculation of step S3 of claim 1 and outputs the final index weight.

[0022] The comprehensive index calculation module is used to call the formula in step S4 of claim 1, calculate the suitability comprehensive index based on the standardized indicator dataset and the final indicator weights, and generate a comprehensive index spatial distribution map.

[0023] The grading module has a built-in suitability grading standard, which can automatically match the initial threshold according to the target crop type, provide a correction coefficient input interface, complete the grading according to the comprehensive index and the adjusted threshold, and generate a grading result map.

[0024] The output module supports outputting text reports, charts, and database files, and has a visualization function, presenting the spatial distribution of different suitability levels through map overlay.

[0025] Furthermore, in the data cleaning unit of the data preprocessing module, the outlier judgment standard is data that exceeds the reasonable range of the indicators; among them, the reasonable range of soil total salinity is 0-3%, the reasonable range of soil pH value is 4.5-10.0, the reasonable range of annual average precipitation is 0-2000mm, the reasonable range of annual average evaporation is 500-3000mm, and the reasonable range of groundwater level depth is 0-10m.

[0026] Furthermore, the text report output by the result output module includes data source, calculation process, grading results and improvement suggestions; the output charts include comprehensive index distribution chart, grading chart, and indicator weight bar chart; the output database file can be imported into the agricultural planning system.

[0027] The beneficial effects of this invention are as follows:

[0028] 1. Multi-dimensional indicator system: This invention covers three categories of indicators: soil, environment, and crop suitability. Compared with existing single-indicator evaluation methods, it can better reflect the comprehensive influencing factors of the suitability of saline-alkali land for cultivation, and the evaluation results are more in line with actual cultivation needs.

[0029] 2. Scientific weight calculation: The AHP-entropy weight combination method is adopted, which takes into account both the subjective experience of experts and the objective characteristics of data, avoids the bias of a single weighting method, and makes the weight allocation more reasonable;

[0030] 3. Dynamic level adjustment: By introducing a correction coefficient, the level threshold can be adjusted according to the specific conditions of the region or technological progress, thereby enhancing the flexibility and adaptability of the method;

[0031] 4. Highly efficient and intelligent system: Through the collaborative work of multiple modules, it realizes automatic data collection, rapid calculation and visualization output, which greatly improves the evaluation efficiency and can meet the needs of dynamic monitoring and real-time evaluation of large-scale saline-alkali land. Attached Figure Description

[0032] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of the present invention and should not be regarded as a limitation of the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0033] Figure 1 This is a flowchart of the data acquisition process of the present invention;

[0034] Figure 2 This is a logic diagram of the weight calculation module of the present invention;

[0035] Figure 3 This is a system data flow diagram of the present invention. Detailed Implementation

[0036] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. The components of the embodiments of the present invention described and shown in the accompanying drawings can generally be arranged and designed in various different configurations.

[0037] A method for classifying the suitability of saline-alkali land for cultivation includes the following steps:

[0038] 1. Data Acquisition Steps

[0039] Multi-dimensional assessment index data were collected for the target saline-alkali land area. These assessment indicators include three categories: basic soil indicators, environmental condition indicators, and crop suitability indicators, as detailed below:

[0040] Basic soil indicators: total soil salt content (S, unit: %), soil pH value (pH), soil texture (T, classified into three levels: sandy, loamy and clayey, and assigned values ​​of 1, 2 and 3 respectively), and soil organic matter content (O, unit: g / kg).

[0041] Environmental condition indicators: annual average precipitation (P, unit: mm), annual average evaporation (E, unit: mm), groundwater level depth (G, unit: m);

[0042] Crop adaptation index: Salt tolerance threshold (S) of the target crop c (Unit: %), Alkali tolerance threshold (pHc), Suitable soil texture (T) c ).

[0043] The data acquisition method combines "field sampling + remote sensing monitoring + database retrieval": soil samples are obtained through field sampling, and the total salt content, pH value, and organic matter content of the soil are obtained through laboratory testing; the spatial distribution of regional soil texture is obtained based on remote sensing image data; annual average precipitation, evaporation and groundwater depth data are retrieved from meteorological station databases and hydrological monitoring databases; and crop suitability indicators are obtained by querying agricultural crop characteristic databases.

[0044] 2. Standardization Processing Steps for Indicators

[0045] Because the dimensions and value ranges of each evaluation indicator are different, the indicator data need to be standardized to eliminate the influence of dimensions. The extreme value standardization method is used to convert the indicator values ​​into standardized values ​​(X) within the interval [0,1]. i The specific formula is as follows:

[0046] For positive indicators (the higher the indicator value, the higher the suitability, such as soil organic matter content, average annual precipitation, and groundwater level depth):

[0047]

[0048] Where, x i x represents the actual value of the indicator. i,min x is the minimum value of this indicator. i,max This is the maximum value of the indicator;

[0049] For negative indicators (the higher the indicator value, the lower the suitability, such as total soil salinity, pH value, and annual average evaporation):

[0050]

[0051] Where, x i x represents the actual value of the indicator. i,min x is the minimum value of this indicator. i,max This is the maximum value of the indicator;

[0052] For classification indicators (such as soil texture): based on the suitable soil texture (T) in the crop suitability index. c If the actual soil texture T = T c Then the standardized value X i =1; if T and T c If similar (e.g., the target is loam, but the actual soil is sandy), then X i =0.5; if T and T c If the difference is significant (e.g., the target is loam but the actual material is clay), then X = 0.

[0053] 3. Steps for determining indicator weights

[0054] The weights (w) of each evaluation indicator are determined using a combined weighting method of the Analytic Hierarchy Process (AHP) and the entropy weighting method. i Taking into account both subjective experience and objective data characteristics, the specific steps are as follows:

[0055] Construct a hierarchical model: The target layer is "suitability for cultivation of saline-alkali land", the criterion layer consists of basic soil indicators, environmental condition indicators, and crop suitability indicators, and the indicator layer consists of the specific indicators collected above.

[0056] Subjective weight calculation (AHP method): Experts in agricultural resources, soil science, and agronomy are invited to conduct pairwise comparisons of the importance of each indicator, construct a judgment matrix, and calculate the subjective weight (w) after passing the consistency test. i,主观 Objective weight calculation (entropy weight method): Based on standardized indicator data, calculate the information entropy (H) of each indicator. i The smaller the information entropy, the greater the dispersion of the indicators, and the greater their impact on the evaluation results. Objective weights (w) i,客观 The calculation formula is as follows:

[0057]

[0058]

[0059] Where n is the number of samples. (X ij (where is the standardized value of the i-th indicator for the j-th sample), and m is the total number of indicators;

[0060] Combined weight calculation: Subjective weights and objective weights are combined in a ratio of 0.5:0.5 to obtain the final indicator weight (w). i ):

[0061] w i =0.5×w i,主观 +0.5×w i,客观 (5)

[0062] 4. Steps for calculating the comprehensive suitability index

[0063] Based on standardized index values ​​(Xi) and index weights (wi), the comprehensive index of suitability for saline-alkali land cultivation (I) is calculated using a weighted summation method, as shown in the following formula:

[0064]

[0065] The value of I ranges from [0,1]. The larger the value of I, the higher the suitability of saline-alkali land for the cultivation of target crops.

[0066] 5. Suitability Level Classification Steps

[0067] Based on the comprehensive suitability index (I), and combined with the actual needs of regional agricultural production and crop growth characteristics, the suitability of saline-alkali land for cultivation is divided into four levels, with the specific classification criteria as follows:

[0068] Level 1 Suitable (Highly Suitable): I∈[0.8,1.0], soil salinity, pH value and other indicators fully meet the growth requirements of the target crop, and can be cultivated directly without special improvement, and the crop yield can reach more than 80% of that of normal cultivated land;

[0069] Level 2 suitable (moderately suitable): I∈[0.5,0.8), the soil indicators basically meet the growth requirements of the target crop, and slight improvement is required (such as increasing the application of organic fertilizer and shallow tillage). After improvement, the crop yield can reach 50%-80% of that of normal cultivated land.

[0070] Level III suitable (slightly suitable): I∈[0.2,0.5), the soil indicators do not meet the growth requirements of the target crop, and moderate improvement is required (such as salt leaching and application of soil conditioners). After improvement, the crop yield can reach 30%-50% of that of normal cultivated land.

[0071] Level 4 Suitable (Unsuitable): I∈[0,0.2), soil salinity and pH are too high, or environmental conditions severely restrict crop growth. Even after intensive improvement, crop yield is still less than 30% of normal cultivated land, making it unsuitable as cultivated land for the target crop.

[0072] Simultaneously, a dynamic threshold adjustment mechanism is introduced: if special climatic conditions exist in the region (such as extreme precipitation or high temperature) or breakthroughs are made in soil improvement technology, the grading threshold can be adjusted through a correction coefficient (k). The correction formula is as follows:

[0073] I 修正 =I×k,

[0074] The value of k ranges from [0.8, 1.2] and is determined by experts based on the actual situation.

[0075] (II) Classification System for Suitability of Saline-Alkali Land for Cultivation

[0076] Based on the above classification method, the present invention also provides a system for classifying the suitability of saline-alkali land for cultivation, including a data acquisition module, a data preprocessing module, a weight calculation module, a comprehensive index calculation module, a classification module, and a result output module. The functions of each module are as follows:

[0077] 1. Data Acquisition Module

[0078] It includes a sampling unit, a remote sensing data receiving unit, and a database interface unit: the sampling unit is used to control the sampling equipment to complete the collection of soil samples in the field; the remote sensing data receiving unit is used to receive satellite remote sensing image data and retrieve soil texture information; the database interface unit is used to establish connections with meteorological databases, hydrological databases, and crop characteristic databases, and automatically retrieve the required environmental data and crop-adaptive data.

[0079] 2. Data Preprocessing Module

[0080] It includes a data cleaning unit and a standardization processing unit: the data cleaning unit is used to remove outliers in the collected data (such as soil total salinity data that exceeds the reasonable range) and use the mean imputation method to supplement missing data; the standardization processing unit is used to call the above formulas 1-2 to complete the standardization calculation of each indicator and output the standardized indicator dataset.

[0081] 3. Weight Calculation Module

[0082] It includes an AHP weight calculation unit, an entropy weight calculation unit, and a combined weight fusion unit: the AHP weight calculation unit provides an input interface for the expert judgment matrix and automatically completes the consistency check and subjective weight calculation; the entropy weight calculation unit calculates the objective weight based on the standardized dataset and calls formulas 3-4; the combined weight fusion unit calls formula 5 to fuse the subjective weight and the objective weight and output the final index weight.

[0083] 4. Composite Index Calculation Module

[0084] Formula 6 is used to calculate the suitability index for each sample point based on the standardized indicator dataset and the final indicator weights, generating a spatial distribution map of the comprehensive index.

[0085] 5. Grading Module

[0086] It has a built-in suitability level classification standard, which can automatically match the initial threshold according to the target crop type, and also provides a correction coefficient input interface to support dynamic adjustment of the threshold; based on the comprehensive index and the adjusted threshold, it completes the suitability level classification and generates a level classification result map.

[0087] 6. Result Output Module

[0088] It supports multiple output formats, including: text reports (including data sources, calculation process, grading results and improvement suggestions), charts (comprehensive index distribution map, grading map, indicator weight bar chart), and database files (which can be imported into agricultural planning systems); it also has a visualization function, which can intuitively present the spatial distribution of different suitability levels through map overlay.

[0089] This invention can be widely applied to scenarios such as agricultural land planning, evaluation of saline-alkali land improvement projects, and optimization of crop planting layout, providing scientific and reliable technical support for the efficient utilization of saline-alkali land resources, and has significant economic and ecological benefits.

[0090] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for classifying the suitability of saline-alkali land for cultivation, characterized in that, Includes the following steps: S1. Data Acquisition: Collect multi-dimensional assessment index data for the target saline-alkali area. These assessment indicators include basic soil indicators, environmental condition indicators, and crop suitability indicators. The basic soil indicators include at least total soil salinity (S), soil pH (pH), soil texture (T), and soil organic matter content (O). The environmental condition indicators include at least annual average precipitation (P), annual average evaporation (E), and groundwater level depth (G). The crop suitability indicators include at least the salt tolerance threshold (Sc) and alkali tolerance threshold (pH) of the target crop. c Suitable soil texture (Tc); S2. Indicator Standardization Processing: The indicator data collected in step S1 is standardized using the extreme value standardization method to obtain the standardized value (X). i For positive indicators, according to the formula... Calculations, for negative indicators, are performed according to the formula. Calculation; for the classification index soil texture (T), based on the suitable soil texture (T) in the crop suitability index. c Assign values; if T = Tc, then Xi = 1; if T and Tc are different, then Xi = 1. c If they are similar, then X i =0.5, if T and T c If the difference is large, then X i =0; S3. Determining Indicator Weights: A combined weighting method using the Analytic Hierarchy Process (AHP) and entropy weighting is employed to calculate the final weight (w) of each evaluation indicator. i First, a judgment matrix is ​​constructed using the AHP method, and the subjective weights (w) are obtained after a consistency check. i,主观 Then, based on standardized indicator data, according to the formula... Calculate information entropy (H) i ), and according to the formula Obtain objective weights (w) i,客观 Finally, according to formula w i =0.5×w i,主观 +0.5×w i,客观 The final weights are obtained through fusion; S4. Calculation of the overall suitability index: based on the standardized value (X) from step S2. i ) and the final weight (w) of step S3 i According to the formula Calculate the overall suitability index (I); S5. Suitability Level Classification: Based on the comprehensive index (I) obtained in step S4, and combined with regional agricultural production needs and crop growth characteristics, the suitability of saline-alkali land for cultivation is divided into four levels: Level 1 suitability corresponds to I∈[0.8,1.0], Level 2 suitability corresponds to I∈[0.5,0.8], Level 3 suitability corresponds to I∈[0.2,0.5], and Level 4 suitability corresponds to I∈[0,0.2]. A correction coefficient (k) is introduced, calculated according to formula I... 修正 =I×k dynamically adjusts the threshold for classifying grades, where k ranges from [0.8, 1.2].

2. The method for classifying the suitability of saline-alkali land for cultivation according to claim 1, characterized in that: In step S1, the data acquisition method combines "field sampling + remote sensing monitoring + database retrieval"; in particular, after obtaining soil samples through field sampling, the total salt content, pH value, and organic matter content of the soil are obtained through laboratory testing; the spatial distribution of regional soil texture is obtained based on remote sensing image data; the annual average precipitation, evaporation, and groundwater depth data are retrieved from meteorological station databases and hydrological monitoring databases; and crop suitability indicators are obtained by querying agricultural crop characteristic databases.

3. The method for classifying the suitability of saline-alkali land for cultivation according to claim 1, characterized in that: In step S3, the target layer of the hierarchical model is "suitability for cultivation in saline-alkali land," the criterion layer includes basic soil indicators, environmental condition indicators, and crop suitability indicators, and the indicator layer consists of the specific indicators described in step S1; and in the formula, n is the sample size. X ij Let m be the standardized value of the i-th indicator for the j-th sample, and m be the total number of indicators.

4. The method for classifying the suitability of saline-alkali land for cultivation according to claim 1, characterized in that: In step S5, the cultivation conditions and improvement requirements corresponding to each level are as follows: Level 1 is suitable and requires no special improvement, with crop yield reaching more than 80% of normal cultivated land; Level 2 is suitable and requires slight improvement, with crop yield reaching 50%-80% of normal cultivated land after improvement; Level 3 is suitable and requires moderate improvement, with crop yield reaching 30%-50% of normal cultivated land after improvement; Level 4 is suitable and even with heavy improvement, crop yield is still less than 30% of normal cultivated land, and it is not suitable as cultivated land for the target crop.

5. A system for classifying the suitability of saline-alkali land for cultivation, characterized in that, The method for implementing any one of claims 1-5 includes a data acquisition module, a data preprocessing module, a weight calculation module, a comprehensive index calculation module, a grade division module, and a result output module; The data acquisition module includes a sampling unit, a remote sensing data receiving unit, and a database interface unit. The sampling unit is used to control the sampling equipment to complete the collection of soil samples in the field. The remote sensing data receiving unit is used to receive satellite remote sensing image data and retrieve soil texture information. The database interface unit is used to establish connections with meteorological databases, hydrological databases, and crop characteristic databases and retrieve data. The data preprocessing module includes a data cleaning unit and a standardization processing unit; the data cleaning unit is used to remove outliers and fill in missing data using the mean imputation method; the standardization processing unit is used to perform the standardization calculation in step S2 of claim 1 and output a standardized index dataset. The weight calculation module includes an AHP weight calculation unit, an entropy weight calculation unit, and a combined weight fusion unit; the AHP weight calculation unit provides an expert judgment matrix input interface and automatically completes consistency verification and subjective weight calculation; the entropy weight calculation unit performs the objective weight calculation of step S3 of claim 1; the combined weight fusion unit performs the combined weight calculation of step S3 of claim 1 and outputs the final index weight. The comprehensive index calculation module is used to call the formula in step S4 of claim 1, calculate the suitability comprehensive index based on the standardized indicator dataset and the final indicator weights, and generate a comprehensive index spatial distribution map. The grading module has a built-in suitability grading standard, which can automatically match the initial threshold according to the target crop type, provide a correction coefficient input interface, complete the grading according to the comprehensive index and the adjusted threshold, and generate a grading result map. The output module supports outputting text reports, charts, and database files, and has a visualization function, presenting the spatial distribution of different suitability levels through map overlay.

6. The saline-alkali land suitability classification system according to claim 6, characterized in that, In the data cleaning unit of the data preprocessing module, the outlier judgment standard is data that exceeds the reasonable range of the indicators; among them, the reasonable range of soil total salinity is 0-3%, the reasonable range of soil pH value is 4.5-10.0, the reasonable range of annual average precipitation is 0-2000mm, the reasonable range of annual average evaporation is 500-3000mm, and the reasonable range of groundwater depth is 0-10m.

7. The saline-alkali land suitability classification system according to claim 6, characterized in that, The output report from the results module includes data sources, calculation process, grading results, and improvement suggestions; the output charts include a comprehensive index distribution chart, a grading chart, and an indicator weight bar chart; the output database file can be imported into an agricultural planning system.

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