CN-122022113-A - Land utilization classification area prediction method, device, equipment and storage medium

CN122022113ACN 122022113 ACN122022113 ACN 122022113ACN-122022113-A

Abstract

The application discloses a land utilization classification area prediction method, a device, equipment and a storage medium, which relate to the technical field of land resource management and prediction and comprise the steps of collecting and screening land utilization current situation change balance tables of continuous years and constructing an initial area transfer matrix; the method comprises the steps of supplementing the same land transfer area to obtain a target land utilization classification area transfer matrix, calculating each element value in the target land utilization classification area transfer matrix to obtain a transfer probability matrix, carrying out weighted average based on the historical transfer probability matrix to obtain a weighted average transfer probability matrix, and carrying out land utilization classification area prediction by combining a preset constraint matrix, an initial state matrix and the weighted average transfer probability matrix. According to the method, historical data are fused, scientific probability analysis and matrix operation are performed, and constraint matrixes are introduced to reflect the influence of different development directions on land utilization change, so that the accuracy of a prediction result is improved, and the scene adaptability of prediction is enhanced.

Inventors

ZHANG WENXIN
CHENG WEIYA
WANG HAN
CHEN QIANG
QIAO HONGBO
JIANG HONGLIANG
LU YUHANG
SHENG QIANKUN

Assignees

山东省国土空间规划院(山东省自然资源和不动产登记中心)
北京数慧时空信息技术有限公司

Dates

Publication Date: 20260512
Application Date: 20251205

Claims (10)

1. The land utilization classification area prediction method is characterized by comprising the following steps of: Collecting an initial land use current situation change balance table of continuous years in a target area, and screening the initial land use current situation change balance table according to prediction precision to obtain a target land use current situation change balance table; Constructing an initial land use classification area transfer matrix according to the current situation change balance table of the target land use; calculating the same-place class transfer area of the target land class, and writing the same-place class transfer area of the target land class into the position corresponding to the same-place class in the initial land use classification area transfer matrix to obtain a target land use classification area transfer matrix; calculating each element in the target land utilization classification area transfer matrix to obtain a transfer probability matrix; According to the historical annual land utilization area transition probability matrix, carrying out weighted average on the transition probability matrix to obtain a weighted average transition probability matrix; predicting land utilization classification area results by using a preset constraint matrix, a preset initial state matrix and the weighted average transition probability matrix.
2. The land use classification area prediction method according to claim 1, wherein the initial land use present change balance table includes a primary land class and a secondary land class, the prediction accuracy is the primary land class, and the step of screening the initial land use present change balance table based on the prediction accuracy to obtain a target land use present change balance table includes: and deleting the related data of the secondary land class in the initial land use current situation change balance table, and reserving the related data of the primary land class in the initial land use current situation change balance table to obtain a target land use current situation change balance table.
3. The land use classification area prediction method according to claim 1, wherein the step of constructing an initial land use classification area transfer matrix from the target land use present change balance table comprises: and extracting area transfer data among all the land data in the target land utilization current situation change balance table, and constructing an initial land utilization classification area transfer matrix.
4. The land use classification area prediction method of claim 1, wherein the step of calculating each element in the target land use classification area transition matrix to obtain a transition probability matrix comprises: taking the annual initial area of each land class corresponding to each column in the target land use classification area transfer matrix before transfer as a denominator, taking the transfer area of each land class in each column in the target land use classification area transfer matrix to the target land class as a molecule, and calculating to obtain the probability value of mutual transfer among the land classes; And constructing a transition probability matrix reflecting the transition relation of each place type based on the probability values of the transition between each place type.
5. The land use classification area prediction method of claim 1, wherein the step of weighted-averaging the transition probability matrix based on the historical annual land use area transition probability matrix to obtain a weighted-average transition probability matrix comprises: acquiring a plurality of historical annual land utilization area transfer probability matrixes; assigning a weight to each historical annual land utilization area transfer probability matrix, wherein the weight is determined according to the time interval between the historical year and the latest data year and through an exponential decay function; and carrying out weighted summation on the area transfer probability matrix of each historical annual land utilization based on the weight to obtain the weighted average transfer probability matrix.
6. The land use classification area prediction method of claim 1, wherein the predicting land use classification area result step using a preset constraint matrix, a preset initial state matrix, and the weighted average transition probability matrix comprises: Performing matrix multiplication operation on the preset constraint matrix, the preset initial state matrix and the weighted average transition probability matrix to obtain a first land utilization classification area prediction result and/or Performing power operation on the weighted average transition probability matrix to obtain a power operation result matrix; and performing matrix multiplication operation on the initial state matrix and the power operation result matrix, and performing matrix multiplication operation on an operation result and a preset constraint matrix to obtain a second land utilization classification area prediction result.
7. The land use classification area prediction method of claim 6, wherein the step of predicting a land use classification area result using a preset constraint matrix, a preset initial state matrix, and the weighted average transition probability matrix, further comprises: constructing a corresponding constraint matrix according to different scene assumptions; Wherein the scenario assumption comprises one or more of a historical trend continuation scenario, a protection scenario, a development scenario and an agricultural protection scenario.
8. A land utilization classification area prediction device is characterized in that, the land use classification area prediction apparatus includes: The screening module is used for collecting an initial land use current situation change balance table of continuous years in the target area, and screening the initial land use current situation change balance table according to the prediction precision to obtain a target land use current situation change balance table; The construction module is used for constructing an initial land utilization classification area transfer matrix according to the current situation change balance table of the target land utilization; the supplementing module is used for calculating the same-place class transfer area of the target land class, writing the same-place class transfer area of the target land class into the position corresponding to the same-place class in the initial land use classification area transfer matrix, and obtaining a target land use classification area transfer matrix; the calculation module is used for calculating each element in the target land utilization classification area transfer matrix to obtain a transfer probability matrix; The weighting module is used for carrying out weighted average on the transition probability matrix according to the historical annual land utilization area transition probability matrix to obtain a weighted average transition probability matrix; the prediction module is used for predicting land utilization classification area results by using a preset constraint matrix, a preset initial state matrix and the weighted average transition probability matrix.
9. A land use classification area prediction apparatus comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the computer program being configured to implement the steps of the land use classification area prediction method of any of claims 1 to 7.
10. A storage medium, characterized in that the storage medium is a computer-readable storage medium, on which a computer program is stored, which computer program, when being executed by a processor, implements the steps of the land use classification area prediction method according to any one of claims 1 to 7.

Description

Land utilization classification area prediction method, device, equipment and storage medium Technical Field The application relates to the technical field of land resource management and prediction, in particular to a land utilization classification area prediction method, a land utilization classification area prediction device, land utilization classification area prediction equipment and a storage medium. Background In the current land resource management work, accurately predicting land utilization classification area change trend has important significance for scientifically making land utilization planning, reasonably configuring land resources and guaranteeing sustainable development of a land utilization system. Traditional land utilization classification area prediction methods rely on empirical judgment or simple linear trend analysis, and have obvious limitations. Experience judgment mainly depends on past experience of staff to estimate land utilization change, influence of subjective factors is large, accuracy and objectivity of a prediction result are difficult to guarantee, and errors are large especially when complex land utilization change conditions are faced. The traditional Markov model defaults to a constant transition probability matrix calculated based on a certain fixed period in the whole prediction period, and the probability matrix of a single period cannot reflect the dynamic characteristics without considering the time accumulation effect of the earth class transition. In addition, land utilization changes are significantly affected by industry specification regulation, and the traditional Markov model only relies on historical class transfer data to construct a probability matrix, so that the industry specification constraint is not converted into quantifiable model parameters. At present, some researches try to predict by adopting other models, but most models have the problems of high data requirement, complex calculation, low applicability and the like, so that the prediction condition of land utilization classification areas is low in precision and weak in scene adaptability. Disclosure of Invention The application mainly aims to provide a land utilization classification area prediction method, a device, equipment and a storage medium, and aims to solve the technical problems that the land utilization classification area change trend prediction accuracy is insufficient and the scene adaptability is weak. In order to achieve the above object, the present application provides a land use classification area prediction method, which includes: Collecting an initial land use current situation change balance table of continuous years in a target area, and screening the initial land use current situation change balance table according to prediction precision to obtain a target land use current situation change balance table; Constructing an initial land use classification area transfer matrix according to the current situation change balance table of the target land use; calculating the same-place class transfer area of the target land class, and writing the same-place class transfer area of the target land class into the position corresponding to the same-place class in the initial land use classification area transfer matrix to obtain a target land use classification area transfer matrix; calculating each element in the target land utilization classification area transfer matrix to obtain a transfer probability matrix; According to the historical annual land utilization area transition probability matrix, carrying out weighted average on the transition probability matrix to obtain a weighted average transition probability matrix; predicting land utilization classification area results by using a preset constraint matrix, a preset initial state matrix and the weighted average transition probability matrix. In an embodiment, the initial land use current situation change balance table includes a primary land class and a secondary land class, the prediction accuracy is the primary land class, and the step of screening the initial land use current situation change balance table according to the prediction accuracy to obtain the target land use current situation change balance table includes: and deleting the related data of the secondary land class in the initial land use current situation change balance table, and reserving the related data of the primary land class in the initial land use current situation change balance table to obtain a target land use current situation change balance table. In one embodiment, the step of constructing an initial land use classification area transfer matrix according to the target land use current situation change balance table includes: and extracting area transfer data among all the land data in the target land utilization current situation change balance table, and constructing an initial land utilization classification area transfer matrix. In