CN111667183A - Method and system for monitoring cultivated land quality - Google Patents
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Abstract
The invention discloses a method and a system for monitoring the quality of cultivated land, which relate to the field of cultivated land monitoring. Through the combination of multiple monitoring schemes, the complex and changeable environments can be detected simultaneously, the warning condition and the evolution trend of the current situation of the land ecological safety can be dynamically mastered in real time, so that corresponding regulation measures and strategies can be provided, the deterioration or the disorderly development of the land ecological system can be effectively controlled, and the policy operation of the land ecological system and the sustainable utilization of land resources can be maintained.
Description
Technical Field
The invention relates to a method and a system for monitoring the quality of cultivated land, and mainly relates to the field of cultivated land monitoring.
Background
In areas with large relief and complex slope shapes, how to effectively monitor different terrains is a problem which is urgently needed to be solved at present.
Disclosure of Invention
Aiming at the defects of the prior art, the invention provides the cultivated land quality monitoring method and the cultivated land quality monitoring system, which can detect multiple complex and changeable environments simultaneously by combining multiple monitoring schemes and can dynamically master the warning condition and the evolution trend of the current state of the ecological safety of the land in real time.
In order to achieve the purpose, the technical scheme of the invention is as follows: the monitoring dimension comprises a monitoring area, a monitoring unit and a monitoring point.
Preferably, the monitoring area includes terrain, landscape, farmland, etc., economic and social.
Preferably, the monitoring unit comprises an over-the-year detection unit, a gradual change type region, natural at various levels, etc., and a land utilization plan.
Preferably, the monitoring points include hierarchical sampling and spatial optimization.
Preferably, the period of monitoring: the macro monitoring is to extract the farmland quality monitoring index information such as terrain factors, soil factors, vegetation factors and the like by remote sensing technology, GIS technology, network technology and the like, macroscopically grasp the farmland quality spatial distribution of the monitored land and the change trend of different periods, and determine a key monitoring area. The typical area key monitoring mainly aims at the cultivated land quality conditions and the change trend of different zones of a monitored area, and by sampling in a cultivated land quality mobile monitoring laboratory on the spot, the high-precision images, the soil rapid-testing results, the soil sample laboratory analysis results and the like of the unmanned aerial vehicle are obtained, the cultivated land quality monitoring index information such as high-precision soil components, crop production states, peripheral environment changes and the like is obtained, the key area periodic monitoring is performed, and data support is provided for further analyzing the cultivated land quality change conditions of the monitored area. The macro monitoring of the farmland quality monitoring takes one year as a monitoring period, the typical area key monitoring period is dynamically adjusted according to the conditions such as requirements, technologies, expenses and the like, and proper and targeted continuous monitoring is carried out according to different monitoring indexes.
Preferably, a cultivated land type-based remote sensing spectrum database is established, spectra of different ground features and different phenological periods in a sample area are collected, the spectra comprise spectral reflectivity, various vegetation indexes, vegetation coverage, leaf area indexes and the like, and the spectral characteristic difference of the different phenological periods is analyzed. The optimal time phase height division image is selected by combining the crop phenology, the planting structure texture characteristics and the like, on the basis of the existing land cover information extraction technical result, the technical result comprises a separation ridge, an object-oriented deep learning method and a multi-level field clustering method, the distribution conditions of different crops are extracted by a man-machine interaction interpretation method, and the space-time change characteristic analysis is carried out.
Preferably, the collected spectra include typical crop spectra, non-spectral data and demand analysis, business process design, and the following steps are performed based on the collected spectra: 1. preprocessing typical crop spectral data; 2. performing data auditing on the preprocessed data and matched non-spectral data, wherein the data auditing specifically comprises data integrity and normalization check; 3. if the inspection does not meet the requirements, data preprocessing is carried out again; 4. if the inspection is in accordance with the requirements, recording a typical crop spectrum database; 5. designing a database structure, a data model and a physical structure of a data table according to demand analysis and business process design, and establishing a database data table; 6. and importing the database data table into a typical crop spectrum database.
Preferably, the method comprises high-resolution satellite remote sensing image monitoring, unmanned aerial vehicle bottom-space photography monitoring, wireless sensor network monitoring and in-situ monitoring; the domestic high-resolution satellite remote sensing image monitoring comprises high-resolution satellite image data, ground spectrum measurement data and farmland quality factor ground investigation data; the unmanned aerial vehicle low-altitude photography monitoring comprises unmanned aerial vehicle low-altitude photography data, ground spectrum measurement data and farmland quality factor ground investigation data; the wireless sensor network monitoring comprises soil surface characteristic data, earth surface characteristic data and meteorological data; the in-situ monitoring includes soil characteristic data, irrigation water data and vegetation characteristic data.
The technical effect of the technical scheme is as follows: according to the scheme, multiple monitoring schemes are combined, multiple complex and changeable environments can be detected simultaneously, the warning condition and the evolution trend of the current situation of the land ecological safety can be dynamically mastered in real time, so that corresponding regulation measures and strategies can be provided, the land ecosystem deterioration or disorderly development can be effectively controlled, and the policy operation of the land ecosystem and the sustainable utilization of land resources can be maintained.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings needed to be used in the description of the embodiments will be briefly introduced below, it is obvious that the drawings in the following description are only three of the present invention, and for those skilled in the art, other drawings can be obtained according to these drawings without creative efforts.
FIG. 1 is a monitoring area relationship diagram according to an embodiment of the present invention;
FIG. 2 is a technical roadmap for building a spectral database according to an embodiment of the present invention;
FIG. 3 is a process of integrated monitoring of arable land quality based on a mobile laboratory according to an embodiment of the present invention.
Detailed Description
The technical solutions in the present invention will be described clearly and completely with reference to the accompanying drawings, and it is to be understood that the described embodiments are merely preferred embodiments of the present invention, rather than all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Examples
As shown in fig. 1, the monitoring dimension of the embodiment of the present invention includes a monitoring area, a monitoring unit, and a monitoring point.
The monitoring area comprises the features of terrain, landform, arable land and the like, economy and society.
The monitoring unit comprises a detection unit for years, a gradual change type area, nature at each level and the like and land utilization planning.
The monitoring points comprise hierarchical sampling and space optimization.
The collected spectrum comprises a typical crop spectrum, matched non-spectral data and demand analysis and business process design, and the operation is carried out according to the collected spectrum according to the following steps: 1. preprocessing typical crop spectral data; 2. performing data auditing on the preprocessed data and matched non-spectral data, wherein the data auditing specifically comprises data integrity and normalization check; 3. if the inspection does not meet the requirements, data preprocessing is carried out again; 4. if the inspection is in accordance with the requirements, recording a typical crop spectrum database; 5. designing a database structure, a data model and a physical structure of a data table according to demand analysis and business process design, and establishing a database data table; 6. and importing the database data table into a typical crop spectrum database.
The method comprises the steps of high-resolution satellite remote sensing image monitoring, unmanned aerial vehicle bottom-space photography monitoring, wireless sensor network monitoring and in-situ monitoring; the domestic high-resolution satellite remote sensing image monitoring comprises high-resolution satellite image data, ground spectrum measurement data and farmland quality factor ground investigation data; the unmanned aerial vehicle low-altitude photography monitoring comprises unmanned aerial vehicle low-altitude photography data, ground spectrum measurement data and farmland quality factor ground investigation data; the wireless sensor network monitoring comprises soil surface characteristic data, earth surface characteristic data and meteorological data; the in-situ monitoring includes soil characteristic data, irrigation water data and vegetation characteristic data.
According to the scheme, multiple monitoring schemes are combined, multiple complex and changeable environments can be detected simultaneously, the warning condition and the evolution trend of the current situation of the land ecological safety can be dynamically mastered in real time, so that corresponding regulation measures and strategies can be provided, the land ecosystem deterioration or disorderly development can be effectively controlled, and the policy operation of the land ecosystem and the sustainable utilization of land resources can be maintained.
Establishing a farmland quality monitoring and evaluating index system
On the basis of the farmland quality monitoring work, monitoring areas are divided, monitoring units are determined, monitoring points are distributed, monitoring contents are determined, a multi-dimensional and three-dimensional farmland quality investigation evaluation and monitoring index system is constructed, long-term monitoring network construction of farmland quality change of a monitored area is promoted, technical specifications of farmland quality monitoring of the monitored area are formulated, and standard acquisition of monitoring data and deep analysis of a large amount of data are promoted.
(I) monitoring an object
Existing cultivated lands (including adjustable forest lands) in the region of the monitored area are monitored, and newly-increased cultivated lands in various land improvement projects of each department are monitored in an important mode.
(II) monitoring content and method
Based on the agricultural quality classification regulations (GB/T28407-2012), by combining with core supervision indexes of departments such as agriculture and environmental protection, factor indexes such as landform, soil characteristics, limiting factors, farmland ecological environment, infrastructure construction and farmland management measures are screened by a method of combining a relevant mathematical model and expert judgment, as shown in Table 1.
(III) monitoring evaluation System
Monitoring area division is carried out on the monitored land according to the farmland quality survey data of the past year and by combining the regional characteristics of the monitored land, monitoring units are determined on the basis of the monitoring area division, monitoring points are distributed according to a layered sampling and space optimization method, monitoring indexes are determined, and therefore a monitoring system is constructed, and the technical route is shown in figure 2.
1. Partitioning monitoring type zones
On a county-level farmland quality grade unit graph, factors such as geographic environment space difference, land utilization mode, soil type boundary line, agricultural division, farmland quality grade distribution and the like are combined, a monitoring area is preliminarily defined, and a gradual change type is determined.
The gradual change type and the distribution range are adjusted and gradually improved in the later specific practice of farmland quality monitoring work and the like.
2. Determining a monitoring unit
On the basis of a 1:1 ten thousand land utilization current situation diagram, a monitoring unit is determined according to the classification distribution conditions of the land types, the soil types, the different landforms, the land quality and the like, and the social and economic conditions, the land utilization mode and the like are taken into consideration.
3. Arrangement of monitoring points
The monitoring points can be divided into fixed monitoring points and temporary monitoring points, at least 1 fixed monitoring point is distributed in each monitoring unit, and the fixed monitoring points are preferentially distributed in the global land comprehensive improvement project area. And a plurality of random monitoring units are selected in the monitoring units in cooperation with the fixed monitoring units. The attribute value of the fixed monitoring point is the average value of the attributes of the fixed monitoring point and the random monitoring point in different equal distribution ranges of each quality gradient type.
The relationship between the monitoring type area, the monitoring unit and the monitoring point is shown in figure 1.
4. Monitoring period
According to the change trend of the farmland quality, the existing farmland quality monitoring management foundation and the administrative management level of the monitored land are combined, and the city wide-range macro monitoring and the typical area key monitoring which mainly adopt the high-resolution remote sensing technology are adopted.
The macro monitoring is to extract the farmland quality monitoring index information such as terrain factors, soil factors, vegetation factors and the like by remote sensing technology, GIS technology, network technology and the like, macroscopically grasp the farmland quality spatial distribution of the monitored land and the change trend of different periods, and determine a key monitoring area.
The typical area key monitoring mainly aims at the cultivated land quality conditions and the change trend of different zones of a monitored area, and by sampling in a cultivated land quality mobile monitoring laboratory on the spot, the high-precision images, the soil rapid-testing results, the soil sample laboratory analysis results and the like of the unmanned aerial vehicle are obtained, the cultivated land quality monitoring index information such as high-precision soil components, crop production states, peripheral environment changes and the like is obtained, the key area periodic monitoring is performed, and data support is provided for further analyzing the cultivated land quality change conditions of the monitored area.
Therefore, the macro monitoring of the farmland quality monitoring takes one year as a monitoring period, the typical area key monitoring period is dynamically adjusted according to the needs, the technology, the expenses and other conditions, and the proper and targeted continuous monitoring is carried out according to the difference of monitoring indexes.
Intelligent monitoring means for farmland quality and the like
On the basis of ground in-situ monitoring on a farmland quality partition monitoring point, the method combines the high-resolution spatial resolution of domestic high-resolution remote sensing, the large-area information of high-spectrum and high-time-phase images, an unmanned aerial vehicle, a wireless sensor, a rapid dynamic monitoring method for farmland quality mobile laboratories and a modern network information technology, develops research on a farmland quality multispectral feature database, constructs an integrated farmland quality dynamic monitoring system of a sky ground network, dynamically masters a farmland quality change rule, realizes the precision of whole-area farmland protection management work, further promotes a natural resource management technology, and provides a decision basis for farmland protection management.
Remote sensing monitoring and evaluation of cultivated land quality
1. Establishing remote sensing spectrum database based on cultivated land type
And collecting spectra of different ground features and different phenological stages in the sample area, wherein the spectra comprise spectral reflectivity, various vegetation indexes, vegetation coverage, leaf area indexes and the like, and analyzing the spectral characteristic difference of different phenological stages. The optimal time phase height-divided image is selected by combining the crop phenology, the texture characteristics of the planting structure and the like, and the distribution conditions of different crops are extracted by a human-computer interaction interpretation method on the basis of the existing land cover information extraction technical achievements (such as a separation ridge, an object-oriented method, a deep learning method, a multi-level field clustering method and the like) to perform space-time change characteristic analysis.
According to the actual requirements of the farmland quality model construction, open source software such as MySQL, JBoss and Dojo is used as a development basis to develop a surface feature spectrum library system based on Python language. While the distribution of the sampling points is displayed, corresponding surface feature information and spectral data are visually displayed to a user, and a simple data processing function can be realized, as shown in fig. 2.
2. Screening and modeling of farmland quality monitoring evaluation remote sensing indexes
And further optimizing and screening the spectrum and remote sensing variables which have representativeness and independence and can reflect the quality of the cultivated land and the like by using a stepwise regression and variance expansion factor method according to the principles of dominance, scientificity, feasibility and the like, reducing the redundancy of information between the spectrum and the remote sensing variables, and finishing the contribution ordering and variable screening of different spectrum and remote sensing indexes to the quality of the cultivated land.
Based on the remote sensing indexes for farmland quality contribution sorting and variable screening results, an optimized farmland quality monitoring remote sensing inversion model is constructed by adopting a modeling method (such as a partial least square method, a support vector machine, a neural network, Logistic-based geographical weighted regression and the like), and farmland quality remote sensing monitoring evaluation mapping is completed.
(II) mobile laboratory construction of cultivated land quality
1. Development and application of mobile laboratory
The integrated computer, unmanned aerial vehicle, high-resolution remote sensing lens, wireless sensor network, tachymeter, soil rapid monitoring, equipment such as workstation are equipped with arable land quality monitoring system, supply water simultaneously, power supply, hardware transformation such as take a breath to local area network in the car, external network are equipped with, realize that the different grade type is observed unified integration, high-efficient management, the analysis of calling fast of data.
2. Mobile laboratory operation and monitoring data collection
The method has the advantages that firstly, remote sensing data such as satellite images, multispectral data and hyperspectral data of large areas and repeated measurement are obtained by utilizing a high-resolution remote sensing satellite, and by combining cultivated land quality ground spectrum and ground survey data, large-area and periodic satellite remote sensing cultivated land quality monitoring indexes can be generated, and macroscopic dynamic monitoring of cultivated land quality is realized.
And secondly, the multi-rotor and fixed-wing unmanned aerial vehicle carries a sensor to acquire low-altitude remote sensing data such as images, multispectral data, hyperspectral data, three-dimensional models and the like of the cultivated land with high spatial and temporal resolution in a specific area, so that the defect of satellite remote sensing data can be effectively overcome, and local high-precision measurement of cultivated land quality monitoring indexes is realized.
And thirdly, the three-dimensional wireless sensor network consisting of the ground acquisition node and the unmanned aerial vehicle airborne convergent node can acquire cultivated land quality monitoring data of soil, irrigation water, weather and crop images of cultivated land sampling points, and long-term continuous acquisition of surface characteristic data of key monitoring areas is realized.
And fourthly, by utilizing in-situ measuring instruments such as a portable spectrometer, a tachymeter and the like, sample data such as soil, irrigation water, crops and the like can be analyzed on site, and cultivated land quality monitoring indexes such as soil characteristics of sampling points and the like can be rapidly obtained. The specific flow is shown in fig. 3.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents, improvements and the like that fall within the spirit and principle of the present invention are intended to be included therein.
Claims (8)
1. A farmland quality monitoring method is characterized in that monitoring dimensions comprise a monitoring area, a monitoring unit and a monitoring point.
2. The method for monitoring the cultivated land quality according to claim 1, characterized in that: the monitoring area comprises the features of terrain, landform, arable land and the like, economy and society.
3. The method for monitoring the cultivated land quality according to claim 1, characterized in that: the monitoring unit comprises a detection unit for years, a gradual change type area, nature at each level and the like and land utilization planning.
4. The method for monitoring the cultivated land quality according to claim 1, characterized in that: the monitoring points comprise hierarchical sampling and space optimization.
5. The method for monitoring the cultivated land quality according to claim 1, characterized in that: the monitoring period is as follows:
the macro monitoring is to extract the farmland quality monitoring index information such as terrain factors, soil factors, vegetation factors and the like by remote sensing technology, GIS technology, network technology and the like, macroscopically grasp the farmland quality spatial distribution of the monitored land and the change trend of different periods, and determine a key monitoring area.
The typical area key monitoring mainly aims at the cultivated land quality conditions and the change trend of different zones of a monitored area, and by sampling in a cultivated land quality mobile monitoring laboratory on the spot, the high-precision images, the soil rapid-testing results, the soil sample laboratory analysis results and the like of the unmanned aerial vehicle are obtained, the cultivated land quality monitoring index information such as high-precision soil components, crop production states, peripheral environment changes and the like is obtained, the key area periodic monitoring is performed, and data support is provided for further analyzing the cultivated land quality change conditions of the monitored area.
The macro monitoring of the farmland quality monitoring takes one year as a monitoring period, the typical area key monitoring period is dynamically adjusted according to the conditions such as requirements, technologies, expenses and the like, and proper and targeted continuous monitoring is carried out according to different monitoring indexes.
6. The method for monitoring the cultivated land quality according to claim 1, characterized in that: establishing a remote sensing spectrum database based on the cultivated land type:
and collecting spectra of different ground features and different phenological stages in the sample area, wherein the spectra comprise spectral reflectivity, various vegetation indexes, vegetation coverage, leaf area indexes and the like, and analyzing the spectral characteristic difference of different phenological stages. The optimal time phase height division image is selected by combining the crop phenology, the planting structure texture characteristics and the like, on the basis of the existing land cover information extraction technical result, the technical result comprises a separation ridge, an object-oriented deep learning method and a multi-level field clustering method, the distribution conditions of different crops are extracted by a man-machine interaction interpretation method, and the space-time change characteristic analysis is carried out.
7. The method for monitoring the cultivated land quality according to claim 6, characterized in that: the collected spectrum comprises a typical crop spectrum, matched non-spectral data and demand analysis and business process design, and the operation is carried out according to the collected spectrum according to the following steps:
1. preprocessing typical crop spectral data;
2. performing data auditing on the preprocessed data and matched non-spectral data, wherein the data auditing specifically comprises data integrity and normalization check;
3. if the inspection does not meet the requirements, data preprocessing is carried out again;
4. if the inspection is in accordance with the requirements, recording a typical crop spectrum database;
5. designing a database structure, a data model and a physical structure of a data table according to demand analysis and business process design, and establishing a database data table;
6. and importing the database data table into a typical crop spectrum database.
8. The cultivated land quality monitoring system according to claim 6, characterized by comprising high-resolution satellite remote sensing image monitoring, Unmanned Aerial Vehicle (UAV) bottom-space photography monitoring, wireless sensor network monitoring and in-situ monitoring;
the domestic high-resolution satellite remote sensing image monitoring comprises high-resolution satellite image data, ground spectrum measurement data and farmland quality factor ground investigation data;
the unmanned aerial vehicle low-altitude photography monitoring comprises unmanned aerial vehicle low-altitude photography data, ground spectrum measurement data and farmland quality factor ground investigation data;
the wireless sensor network monitoring comprises soil surface characteristic data, earth surface characteristic data and meteorological data;
the in-situ monitoring includes soil characteristic data, irrigation water data and vegetation characteristic data.
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