CN-121981564-A - Forest farm operation intelligent operation maintenance platform based on big data

CN121981564ACN 121981564 ACN121981564 ACN 121981564ACN-121981564-A

Abstract

The invention discloses a big data-based intelligent operation and maintenance platform for forest farm operation, which relates to the field of forest farm operation and solves the problem that the operation mode of a forest farm cannot be intelligently adjusted based on annual production capacity, and comprises a region dividing module, a data acquisition module, a forest farm analysis module and a production prediction module, wherein the region dividing module is used for dividing a target forest farm into a plurality of forest farm subareas, the data acquisition module is used for acquiring forest land data and forest data of the plurality of forest farm subareas in the target forest farm, the forest farm analysis module is used for analyzing the forest growth conditions of a plurality of forest farm partitions in a target forest farm, the production prediction module is used for predicting the forest production capacity of different forest farm partitions in the target forest farm, judging whether the predicted forest production capacity is enough to meet the average demand of the corresponding forest types, generating a modification signal or not performing any operation, and the invention realizes intelligent adjustment of the management mode of the forest farm based on annual production capacity.

Inventors

XIANG TAO
CUI LONGXIAO

Assignees

广东双木林科技有限公司

Dates

Publication Date: 20260505
Application Date: 20240410

Claims (8)

1. The intelligent operation and maintenance platform for forest farm operation based on big data is characterized by comprising a region dividing module, a data acquisition module, a forest farm analysis module, a production prediction module and a display terminal; The region dividing module is used for dividing the region of the target forest farm to obtain a plurality of forest farm partitions in the target forest farm, and sending the plurality of forest farm partitions in the target forest farm to the data acquisition module; The data acquisition module is used for acquiring forest land data and forest data of a plurality of forest field partitions in a target forest field, sending the forest land data of the plurality of forest field partitions in the target forest field to the forest field analysis module and the production prediction module, and sending the forest data to the production prediction module; The forest farm analysis module is used for analyzing the forest growth conditions of a plurality of forest farm partitions in the target forest farm, analyzing to obtain the forest farm production grades of the plurality of forest farm partitions in the target forest farm, and sending the forest farm production grades of the plurality of forest farm partitions in the target forest farm to the production prediction module; The production prediction module is used for predicting the forest production capacity of different forest farm partitions in the target forest farm, generating a modification signal or not performing any operation, and if the modification signal is generated and sent to the display terminal; The display terminal is used for receiving the modification signal and modifying the operation mode corresponding to the forest type.
2. The intelligent operation and maintenance platform for forest farm operation based on big data according to claim 1, wherein the working process of the area dividing module is specifically as follows: Obtaining the types of the forest in the target forest farm, and dividing the forest into a plurality of forest types according to the types of the forest; the trees are provided with identification plates, the types and the planting time of the corresponding trees on the identification plates are subtracted from the current time to obtain the ages of the trees corresponding to the trees; and dividing the target forest farm into a plurality of forest farm partitions according to the ages and types of the trees.
3. The big data based intelligent operation and maintenance platform for forest farm operations of claim 1, wherein the forest land data comprises a forest farm altitude, a soil thickness and a forest farm gradient, and the forest data comprises a crown volume and a forest density.
4. The intelligent operation and maintenance platform for forest farm operation based on big data according to claim 3, wherein the collection process of the data collection module is specifically as follows: Randomly selecting a specified number of longitude and latitude coordinates in each forest farm partition and marking the longitude and latitude coordinates as forest land acquisition points; Acquiring the altitude of a corresponding forest land acquisition point according to the longitude and latitude coordinates, and selecting the highest altitude as the forest land altitude of the corresponding forest land partition; Penetrating the soil surface by using a tool at a woodland acquisition point until reaching a bedrock position, and measuring the distance from the bedrock to the soil surface by using a graduated scale and marking the distance as the soil thickness; calculating the distance JL between the forest land acquisition points with the highest and lowest soil thickness, and subtracting the lowest soil thickness from the high soil thickness to obtain a height difference GDC between the two forest land acquisition points; the forest farm gradient of the corresponding forest farm partition is calculated by the formula lcp=gdc/jl×100%.
5. The intelligent operation and maintenance platform for forest farm operation based on big data according to claim 3, wherein the analysis process of the forest farm analysis module is specifically as follows: Acquiring forest land data and forest data of each forest farm partition in a target forest farm, and obtaining soil thickness and forest farm gradient of each forest farm partition; comparing the soil thickness with the thickness threshold to obtain the soil thickness grade of each forest farm partition, and similarly comparing the forest farm gradient with the gradient threshold to obtain the forest farm gradient grade of each forest farm partition; if the gradient grade of the forest farm is the first grade of the forest farm gradient or the soil thickness grade is the first grade of the soil thickness, the production grade of the forest farm corresponding to the forest farm subarea is determined to be the first grade; if the forest farm gradient grade is the secondary forest farm gradient and the soil thickness grade is the secondary soil thickness, the forest farm production grade of the corresponding forest farm partition is determined to be the secondary; If the gradient grade of the forest farm is three-stage gradient of the forest farm or the soil thickness grade is three-stage soil thickness, and meanwhile, the gradient grade of the forest farm is not one-stage gradient of the forest farm and the soil thickness grade is not one-stage soil thickness, the production grade of the forest farm corresponding to the forest farm subarea is determined to be three-stage.
6. The intelligent operation and maintenance platform for forest farm operation based on big data according to claim 5, wherein the comparison process of the soil thickness grade and the forest farm gradient grade is specifically as follows: If the soil thickness is greater than X1 cm, determining that the soil thickness grade of the forest farm partition is three-level soil thickness; if the soil thickness is between X1 cm and X2 cm, determining the soil thickness grade of the forest field subarea as the secondary soil thickness; If the soil thickness is less than X2 cm, determining the soil thickness grade of the forest farm partition as the first-level soil thickness; if the gradient of the forest farm is smaller than Y1, the gradient grade of the forest farm in the forest farm partition is determined to be three-level gradient of the forest farm; If the forest farm gradient is positioned between the Y1 and the Y2, the forest farm gradient grade of the forest farm partition is determined to be a secondary forest farm gradient; If the slope of the forest farm is greater than Y2, the slope level of the forest farm in the forest farm partition is determined to be the first-level slope of the forest farm, X1> X2, X1 and X2 are thickness thresholds, Y1< Y2, and Y1 and Y2 are slope thresholds; the higher the gradient grade of the forest farm and the grade of the soil thickness grade of the forest farm partition, the stronger the promotion capability of the corresponding forest farm partition on the growth of the forest.
7. The intelligent operation and maintenance platform for forest farm operation based on big data according to claim 5, wherein the prediction process of the production prediction module is specifically as follows: Acquiring tree data of different forest farm partitions in a target forest farm, and obtaining a crown volume SGT and a tree density LM in the forest farm partitions; comparing the tree density LM with a tree density threshold LMY; If LM < LMY, then the formula is passed Calculating predicted zone throughput YFC for a plurality of farm zones; If LM is more than or equal to LMY, determining that the trees in the corresponding forest farm subareas are in a competition relationship, and passing through the formula Calculating predicted partition throughput YFC of the corresponding forest farm partition; Adding and summing the predicted subarea production volumes corresponding to the subareas of the forest farm with the same forest types to obtain the predicted forest production volumes corresponding to the forest types; acquiring the forest demand of different forest types of a target forest farm in five years, and respectively adding and summing the forest demand of different forest types of the target forest farm in five years to obtain an average demand of the target forest farm on different forest types; comparing the predicted forest yield with the average demand of the same forest type, and if the predicted forest yield is greater than or equal to the average demand, not performing any operation; if the predicted forest throughput is less than the average demand, a modification signal is generated.
8. The intelligent operation and maintenance platform for forest farm operation based on big data according to claim 7, wherein lambda is a forest growth coefficient and CS is a forest farm growth promoting coefficient; If the forest farm production grade of the forest farm partition is first grade, the CS value is alpha 1; if the production grade of the forest farm partition is two-level, the CS value is alpha 2; If the forest farm production grade of the forest farm partition is three-level, the CS value is alpha 3, and alpha 1> alpha 2> alpha 3.

Description

Forest farm operation intelligent operation maintenance platform based on big data Technical Field The invention belongs to the field of forest farm management, relates to a big data technology, and particularly relates to an intelligent operation and maintenance platform for forest farm management based on big data. Background As one of important raw materials, the demand for wood is continuously increased along with population growth and economic development, and an effective woodland management and management mechanism needs to be established to meet the demand for wood supply, and woodland management refers to the activity of reasonably developing, managing and managing woodland resources. The method relates to a series of management and operation measures such as planning, planting, tending, pest control, harvesting, selling and the like of a forest land, aims at realizing sustainable utilization of the forest land and maximization of economic benefit, and needs to establish a scientific forest land operation management system to ensure sustainable development of resources in order to protect and sustainable use forest resources; However, when the management is carried out on a forest farm at the present stage, the forest planting and tending work is carried out in the forest farm, the future annual production of the forest farm cannot be predicted, the management mode of the forest farm cannot be intelligently adjusted based on the annual production, and whether the production of the forest farm can meet the requirements cannot be ensured; Therefore, we propose a forest farm operation intelligent operation maintenance platform based on big data. Disclosure of Invention The invention aims to provide a forest farm operation intelligent operation maintenance platform based on big data, which aims to solve the problem that the operation mode of the forest farm cannot be intelligently adjusted based on annual production in the background technology. In order to achieve the above purpose, the present invention adopts the following technical scheme: A forest farm operation intelligent operation maintenance platform based on big data comprises a region dividing module, a data acquisition module, a forest farm analysis module, a production prediction module and a display terminal; The region dividing module is used for dividing the region of the target forest farm to obtain a plurality of forest farm partitions in the target forest farm, and sending the plurality of forest farm partitions in the target forest farm to the data acquisition module; The data acquisition module is used for acquiring forest land data and forest data of a plurality of forest field partitions in a target forest field, sending the forest land data of the plurality of forest field partitions in the target forest field to the forest field analysis module and the production prediction module, and sending the forest data to the production prediction module; The forest farm analysis module is used for analyzing the forest growth conditions of a plurality of forest farm partitions in the target forest farm, analyzing to obtain the forest farm production grades of the plurality of forest farm partitions in the target forest farm, and sending the forest farm production grades of the plurality of forest farm partitions in the target forest farm to the production prediction module; The production prediction module is used for predicting the forest production capacity of different forest farm partitions in the target forest farm, generating a modification signal or not performing any operation, and if the modification signal is generated and sent to the display terminal; The display terminal is used for receiving the modification signal and modifying the operation mode corresponding to the forest type. Further, the working process of the area dividing module is specifically as follows: Obtaining the types of the forest in the target forest farm, and dividing the forest into a plurality of forest types according to the types of the forest; the trees are provided with identification plates, the types and the planting time of the corresponding trees on the identification plates are subtracted from the current time to obtain the ages of the trees corresponding to the trees; and dividing the target forest farm into a plurality of forest farm partitions according to the ages and types of the trees. Further, the woodland data includes a woodland altitude, a soil thickness, and a woodland gradient, and the woodland data includes a crown volume and a woodland density. Further, the data acquisition module has the following acquisition process: Randomly selecting a specified number of longitude and latitude coordinates in each forest farm partition and marking the longitude and latitude coordinates as forest land acquisition points; Acquiring the altitude of a corresponding forest land acquisition point according to the longitude and latitude coordinates, a