Cultivated land planting purpose monitoring method and system based on multi-source remote sensing data

Abstract

The invention discloses a cultivated land planting purpose monitoring method and system based on multi-source remote sensing data, and belongs to the technical field of planting purpose monitoring. Monitoring a vegetation index and soil humidity of a planting area of the cultivated land, calculating a cultivated land vegetation-soil index of the planting area, constructing an index time chain and an index time chain matrix of the planting area, and calculating an inter-chain coupling degree between adjacent index time chains; presetting an inter-chain coupling degree threshold value, obtaining all similar planting regions, and constructing a similar region set; calculating an index change trend of the index time chain; and presetting an index change trend threshold value, and analyzing and performing purpose monitoring on all the planting areas in the similar area set. According to the invention, through remote sensing monitoring, index modeling, time sequence analysis and regional similarity evaluation, accurate monitoring and intelligent early warning of cultivated land planting purposes are realized, related personnel can timely master cultivated land utilization conditions, and the sustainability and scientific decision-making ability of agricultural production are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of planting use monitoring, and specifically provides a method and system for monitoring the planting use of cultivated land based on multi-source remote sensing data. Background Technique

[0002] With the acceleration of the global agricultural modernization process, remote sensing technology has been increasingly widely used in cultivated land management and crop monitoring; traditional crop monitoring methods mainly rely on field surveys and statistical analysis, but are limited by high labor costs, limited coverage, and poor real-time performance, making it difficult to meet the needs of large-scale cultivated land dynamic monitoring; in recent years, using technologies such as satellite remote sensing, hyperspectral imaging, and unmanned aerial vehicle remote sensing to evaluate the planting status of cultivated land has become a research hotspot, among which, vegetation indices (such as NDVI) and soil moisture monitoring have become important parameters; the method for monitoring the use of cultivated land based on remote sensing data has made remarkable progress in aspects such as agricultural ecological assessment, crop growth monitoring, and land use classification, but there are still certain limitations, such as problems like the decline in monitoring accuracy caused by data heterogeneity, the lack of unified classification standards for cultivated land status, and the lack of multi-temporal data analysis methods.

[0003] The existing methods for monitoring the planting use of cultivated land do not fully consider the dynamic change characteristics of multi-source remote sensing data and the interaction between different monitoring indicators; for example, some studies only rely on vegetation indices to judge the use of cultivated land, but ignore the influence of soil moisture, resulting in a lower accuracy in distinguishing dry land from fallow land; in addition, traditional classification methods often rely on fixed thresholds or simple statistical regression models, lacking temporal evolution analysis and making it difficult to accurately identify the change trend of planting use; therefore, in practical applications, the existing methods cannot effectively adapt to complex agricultural planting patterns, especially in the case of different crop rotations, changes in irrigation management, or fluctuations in environmental conditions, and the reliability of their monitoring results is relatively low. Summary of the Invention

[0004] The purpose of the present invention is to provide a method and system for monitoring the planting use of cultivated land based on multi-source remote sensing data to solve the problems raised in the above background technique.

[0005] To solve the above technical problems, the present invention provides the following technical solutions:

[0006] A method for monitoring the planting use of cultivated land based on multi-source remote sensing data, the method comprising the following steps: Step S1: Divide the use range of the cultivated land for planting into several planting areas; monitor the planting data of the planting areas, the planting data including vegetation index and soil humidity; Step S2: Calculate the cultivated land vegetation-soil index of the planting area based on the vegetation index and soil humidity; construct an index time chain of the planting area based on the cultivated land vegetation-soil index of the planting area; Step S3: Obtain the index time chains of all planting areas, and construct an index time chain matrix; calculate the inter-chain coupling degree between adjacent index time chains based on the index time chain matrix; preset an inter-chain coupling degree threshold, obtain all similar planting areas, and construct a set of similar areas; Step S4: Calculate the index change trend of the index time chain based on the cultivated land vegetation-soil index; preset an index change trend threshold, and analyze and monitor the use of all planting areas in the set of similar areas.

[0007] As a preferred embodiment of the method for monitoring the planting use of cultivated land based on multi-source remote sensing data according to the present invention, use a high-precision GPS device to survey the use range of the cultivated land for planting, divide the use range of the cultivated land for planting into several planting areas by using a grid division technique, uniformly number the planting areas, classify the planting areas based on the numbering information, generate a set of planting areas, denoted as AR = {PA a |a ∈ [1, A]}, where PA a represents the a-th planting area, and A represents the total number of planting areas.

[0008] Carry a remote sensing survey device on an unmanned aerial vehicle to monitor the planting data of the planting area PA a , the planting data including vegetation index and soil humidity, and record the vegetation index and soil humidity in the planting area PA a as VI(PA a ) and SH(PA a ), respectively.

[0009] It should be noted that the vegetation index is usually used to evaluate the vegetation coverage, growth status and planting type. For example, a high vegetation index value usually corresponds to healthy green leaf crops, while a low vegetation index value may indicate bare soil, harvested fields or fallow status; soil humidity can determine whether it is suitable for rice planting or whether it is in a fallow state.

[0010] As a preferred embodiment of the method for monitoring the planting use of cultivated land based on multi-source remote sensing data according to the present invention, calculate the cultivated land vegetation-soil index of the planting area PA a based on the vegetation index VI(PA a ) and soil humidity SH(PA a ), and the calculation formula is as follows:

[0011]

[0012] Among them, CVSI(PA a ) represents the cropland vegetation-soil index of the planting area PA a , VI ref represents the preset vegetation index reference value, SH ref represents the preset soil moisture reference value, and α and β respectively represent the influencing factors of the preset vegetation index VI(PA a ) and soil moisture SH(PA a ).

[0013] Based on the cropland vegetation-soil index CVSI(PA a ) of the planting area PA a , an index time chain of the planting area PA a is constructed as follows:

[0014] Taking months as the unit, a data collection period is constructed, and the cropland vegetation-soil index of the planting area PA a is obtained under each data collection period. The cropland vegetation-soil index of the planting area PA a in the i-th data collection period is denoted as the cropland vegetation-soil cycle index CVSI i (PA a ).

[0015] The cropland vegetation-soil cycle indexes CVSI i (PA a ) are arranged in the chronological order of the data collection period, and all the arranged cropland vegetation-soil cycle indexes are denoted as the index time chain of the planting area PA a . The index time chain is denoted as {CVSI i (PA a )|i ∈ [1, I]}, where I represents the total number of data collection periods.

[0016] It should be noted that the cropland vegetation-soil index CVSI(PA a ) calculated by the vegetation index VI(PA a ) and the soil moisture SH(PA a ) can represent the planting area PA aDivide different cultivated land statuses, for example: Vigorous growth period (high vegetation index + suitable soil humidity): Crops growing normally, such as rice, corn, fruit trees, etc.; Drought stress (high vegetation index + low soil humidity): Dryland crops that may have insufficient irrigation or farmland affected by drought; Waterlogging and over-wetness (low vegetation index + high soil humidity): It may be a paddy field or an abnormal situation caused by waterlogging due to precipitation; Fallow / abandoned land (low vegetation index + low soil humidity): It may be fallow land, unplanted farmland or wasteland.

[0017] And, if the cultivated land vegetation-soil index CVSI(PA a ) is in a high value for a long time, it can be determined as a stable planting area (food crops / cash crops). If the cultivated land vegetation-soil index CVSI(PA a ) has obvious seasonal changes, it can be determined as a rotation planting area (wheat-corn, rapeseed-rice, etc.). If the cultivated land vegetation-soil index CVSI(PA a ) is in a low value for a long time, it can be determined as fallow land, abandoned land or grassland for grazing. If the cultivated land vegetation-soil index CVSI(PA a ) fluctuates abnormally in some periods, it can be determined as protected agriculture (such as greenhouse).

[0018] As a preferred scheme of the cultivated land planting use monitoring method based on multi-source remote sensing data described in the present invention, based on the index time chain {CVSI a (PA i (PA a )|i∈[1,I]} of the planting area PA

[0019]

[0020] wherein, CVSI I (PA A ) represents the cultivated land vegetation-soil cycle index of the A-th planting area PA A in the I-th data acquisition cycle.

[0021] Based on the index time chain matrix, calculate the coupling degree between adjacent index time chains, and the calculation formula is as follows:

[0022]

[0023] wherein, D(PA a ,PA b) represents the inter-chain coupling degree between the exponential time chains {CVSI i (PA a )|i ∈ [1, I]} and the exponential time chains {CVSI i (PA b )|i ∈ [1, I]}, and CVSI i (PA b ) represents the cultivated land vegetation - soil cycle index of the planting area PA b under the i-th data acquisition cycle.

[0024] A preset inter-chain coupling degree threshold. If the inter-chain coupling degree D(PA i (PA a )|i ∈ [1, I]} and the exponential time chains {CVSI i (PA b )|i ∈ [1, I]} is greater than or equal to the inter-chain coupling degree threshold, then it is determined that there is similarity between the planting area PA a , PA b ; Obtain all the planting areas similar to the planting area PA a and construct a set of similar areas of the planting area PA b . a a As a preferred solution of the method for monitoring the cultivated land planting use based on multi-source remote sensing data described in the present invention, based on the set of similar areas of the planting area PA

[0025] and the cultivated land vegetation - soil cycle index CVSI a of the planting area PA a under the i-th data acquisition cycle, calculate the exponential change trend of the exponential time chain {CVSI i (PA a )|i ∈ [1, I]}, and the calculation formula is as follows: i (PA a )|i ∈ [1, I]} of the exponential change trend, where CVSI

[0026]

[0027] Among them, G(PA a ) represents the exponential change trend of the exponential time chain {CVSI i (PA a )|i ∈ [1, I]}, and CVSI i-1 (PA a ) represents the cultivated land vegetation - soil cycle index of the planting area PA a under the (i - 1)-th data acquisition cycle.

[0028] A preset exponential change trend threshold. If the exponential time chain {CVSI​i (PA a ) | If the exponential change trend of {PA|i ∈ [1, I]} is less than the exponential change trend threshold, it indicates that the planting area PA a has an abnormal use (decline in agricultural productivity (decrease in yield, soil degradation, water shortage), the plot is being fallowed or abandoned, the land use may be changing (urbanization, aquaculture, ecological restoration, etc.), may be affected by extreme weather, pests and diseases or human damage), then it is determined that the planting area PA a has abnormal uses for all planting areas in the similar area set of, and a warning is sent to the staff.

[0029] A cultivated land planting use monitoring system based on multi-source remote sensing data. This system includes: a regional division and data acquisition module, an index calculation and time chain construction module, a matrix construction and coupling degree calculation module, and a trend calculation and analysis warning module.

[0030] The regional division and data acquisition module: divides the use range of cultivated land planting land into several planting areas; monitors the planting data of the planting areas, and the planting data includes vegetation index and soil humidity.

[0031] The index calculation and time chain construction module: calculates the cultivated land vegetation-soil index of the planting area based on the vegetation index and soil humidity; constructs the index time chain of the planting area based on the cultivated land vegetation-soil index of the planting area.

[0032] The matrix construction and coupling degree calculation module: obtains the index time chains of all planting areas and constructs an index time chain matrix; calculates the inter-chain coupling degree between adjacent index time chains based on the index time chain matrix; presets an inter-chain coupling degree threshold, obtains all similar planting areas, and constructs a similar area set.

[0033] The trend calculation and analysis warning module: calculates the exponential change trend of the index time chain based on the cultivated land vegetation-soil index; presets an exponential change trend threshold, analyzes and monitors the uses of all planting areas in the similar area set.

[0034] Furthermore, the regional division and data acquisition module includes a regional division unit and a data acquisition unit.

[0035] The regional division unit: uses a high-precision GPS device to survey the use range of cultivated land planting land, divides the use range of the cultivated land planting land into several planting areas by using grid division technology, uniformly numbers the planting areas, classifies the planting areas based on the numbering information, and generates a planting area set.

[0036] The data acquisition unit: A remote sensing survey device is carried on the drone to monitor the planting data of the planting area, and the planting data includes vegetation index and soil humidity.

[0037] Further, the index calculation and time chain construction module includes an index calculation unit and a time chain construction unit.

[0038] The index calculation unit: Based on the vegetation index and soil humidity, calculate the cultivated land vegetation-soil index of the planting area.

[0039] The time chain construction unit: Based on the cultivated land vegetation-soil index of the planting area, construct the index time chain of the planting area as follows: Taking months as the unit, construct a data acquisition cycle, obtain the cultivated land vegetation-soil index of the planting area under each data acquisition cycle, and record the cultivated land vegetation-soil index under a single data acquisition cycle as the cultivated land vegetation-soil cycle index; Arrange the cultivated land vegetation-soil cycle indexes in the chronological order of the data acquisition cycle, and record all the arranged cultivated land vegetation-soil cycle indexes as the index time chain of the planting area.

[0040] Further, the matrix construction and coupling degree calculation module includes a matrix construction unit and a coupling degree calculation unit.

[0041] The matrix construction unit: Based on the index time chain of the planting area, obtain the index time chains of all planting areas and construct an index time chain matrix. The rows of the index time chain matrix are the cultivated land vegetation-soil cycle indexes of a single planting area under all data acquisition cycles, and the columns of the index time chain matrix are the cultivated land vegetation-soil cycle indexes of all planting areas under a single data acquisition cycle.

[0042] The coupling degree calculation unit: Based on the index time chain matrix, calculate the inter-chain coupling degree between adjacent index time chains; Preset an inter-chain coupling degree threshold. If the inter-chain coupling degree between adjacent index time chains is greater than or equal to the inter-chain coupling degree threshold, it is determined that there is similarity between adjacent planting areas; Obtain all the planting areas similar to the current planting area and construct a set of similar areas of the current planting area.

[0043] Further, the trend calculation and analysis warning module includes a trend calculation unit and an analysis warning unit.

[0044] The trend calculation unit: Based on the set of similar areas of the current planting area and the cultivated land vegetation-soil cycle index of the current planting area under a single data acquisition cycle, calculate the index change trend of the index time chain.

[0045] The analysis and early warning unit: preset a threshold for the change trend of the index. If the change trend of the index in the index time chain is less than the threshold for the change trend of the index, it indicates that there is an abnormal use in the current planting area. Then, it is determined that there is an abnormal use in all the planting areas in the set of similar areas of the current planting area, and a warning is sent to the staff.

[0046] Compared with the prior art, the beneficial effects achieved by the present invention are as follows: In the method and system for monitoring the planting use of cultivated land based on multi-source remote sensing data provided by the present invention, a high-precision GPS device is used to survey the scope of cultivated land, and the cultivated land is divided into multiple planting areas by using a grid division technology. At the same time, a drone remote sensing device is used to monitor the vegetation index and soil humidity, so as to establish a basic data set of the planting area, providing accurate data support for subsequent analysis. Then, based on the vegetation index and soil humidity, the cultivated land vegetation-soil index is calculated, and an index time chain that changes with time is constructed, so as to be able to identify the cultivated land status of the planting area, including situations such as vigorous growth, drought stress, excessive waterlogging or fallow and abandonment, laying a foundation for subsequent use analysis. By constructing an index time chain matrix and calculating the coupling degree between adjacent time chains, areas with similar planting characteristics are identified, and a set of similar areas is constructed. This step not only improves the accuracy of planting area identification, but also can effectively screen out cultivated land with the same change trend, improving the stability and reliability of monitoring. Finally, based on the index time chain, the change trend of the index is calculated, and a threshold is set to detect abnormal situations of planting use, such as a decrease in agricultural productivity, land fallow or use conversion, etc., and a warning is sent to the management personnel when the use is abnormal, ensuring the reasonable utilization of agricultural resources and the high efficiency of land management. Generally speaking, through remote sensing monitoring, index modeling, time series analysis and regional similarity evaluation, this method realizes the accurate monitoring and intelligent early warning of the planting use of cultivated land, helping agricultural management departments and relevant personnel to timely master the cultivated land utilization situation and improving the sustainability of agricultural production and the scientific decision-making ability. Description of the Drawings

[0047] The drawings are used to provide a further understanding of the present invention, and constitute a part of the specification. They are used together with the embodiments of the present invention to explain the present invention, and do not constitute a limitation to the present invention.

[0048] Figure 1 It is a schematic diagram of the steps of a method for monitoring the planting use of cultivated land based on multi-source remote sensing data of the present invention;

[0049] Figure 2 It is a schematic diagram of the structure of a system for monitoring the planting use of cultivated land based on multi-source remote sensing data of the present invention. Detailed Embodiments

[0050] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0051] Please refer to Figure 1 , in the first embodiment: A method for monitoring the cultivated land planting use based on multi-source remote sensing data is provided. The method includes the following steps:

[0052] Step S1: Divide the use range of the cultivated land planting land into several planting areas; monitor the planting data of the planting areas, and the planting data includes vegetation index and soil humidity.

[0053] Specifically, use a high-precision GPS device to survey the use range of the cultivated land planting land, use the grid division technology to divide the use range of the cultivated land planting land into several planting areas, uniformly number the planting areas, classify the planting areas based on the numbering information, and generate a planting area set, denoted as AR = {PA a |a ∈ [1, A]}, where PA a represents the a-th planting area, and A represents the total number of planting areas.

[0054] Furthermore, carry a remote sensing survey device on the unmanned aerial vehicle to monitor the planting data of the planting area PA a , and the planting data includes vegetation index and soil humidity. Denote the vegetation index and soil humidity in the planting area PA a as VI(PA a ) and SH(PA a ), respectively.

[0055] It should be noted that the vegetation index is usually used to evaluate the vegetation coverage, growth status and planting type. For example, a high vegetation index value usually corresponds to healthy green leaf crops, while a low vegetation index value may indicate bare soil, harvested fields or fallow status; soil humidity can determine whether it is suitable for rice planting or whether it is in a fallow state.

[0056] Step S2: Calculate the cultivated land vegetation-soil index of the planting area based on the vegetation index and soil humidity; construct an index time chain of the planting area based on the cultivated land vegetation-soil index of the planting area.

[0057] Specifically, based on the vegetation index VI(PA a ) and soil humidity SH(PA a ), calculate the cultivated land vegetation-soil index of the planting area PA aThe cropland vegetation-soil index is calculated as follows:

[0058]

[0059] Among them, CVSI(PA a ) represents the cropland vegetation-soil index of the planting area PA a , VI ref represents the preset reference value of the vegetation index, SH ref represents the preset reference value of soil moisture, and α and β respectively represent the influence factors of the preset vegetation index VI(PA a ) and soil moisture SH(PA a ).

[0060] Furthermore, based on the cropland vegetation-soil index CVSI(PA a ) of the planting area PA a , an index time chain of the planting area PA a is constructed as follows:

[0061] Taking months as the unit, a data collection period is constructed, and the cropland vegetation-soil index of the planting area PA a is obtained for each data collection period. The cropland vegetation-soil index of the planting area PA a in the i-th data collection period is denoted as the cropland vegetation-soil cycle index CVSI i (PA a ).

[0062] The cropland vegetation-soil cycle indexes CVSI i (PA a ) are arranged in the chronological order of the data collection period, and all the arranged cropland vegetation-soil cycle indexes are denoted as the index time chain of the planting area PA a . The index time chain is denoted as {CVSI i (PA a )|i ∈ [1, I]}, where I represents the total number of data collection periods.

[0063] It should be noted that the cropland vegetation-soil index CVSI(PA a ) calculated through the vegetation index VI(PA a ) and soil moisture SH(PA a ) can represent the planting area PA aDivide different cultivated land statuses, for example: Vigorous growth period (high vegetation index + suitable soil humidity): Crops growing normally, such as rice, corn, fruit trees, etc.; Drought stress (high vegetation index + low soil humidity): Dryland crops that may have insufficient irrigation or farmland affected by drought; Waterlogging and excessive moisture (low vegetation index + high soil humidity): May be paddy fields or abnormal situations caused by precipitation waterlogging; Fallow / abandoned land (low vegetation index + low soil humidity): May be fallow land, unplanted farmland or wasteland.

[0064] And, if the cultivated land vegetation - soil index CVSI(PA a ) is in a high value for a long time, it can be determined as a stable planting area (food crops / cash crops). If the cultivated land vegetation - soil index CVSI(PA a ) has obvious seasonal changes, it can be determined as a rotation planting area (wheat - corn, rapeseed - rice, etc.). If the cultivated land vegetation - soil index CVSI(PA a ) is in a low value for a long time, it can be determined as fallow land, abandoned land or grassland. If the cultivated land vegetation - soil index CVSI(PA a ) fluctuates abnormally in some periods, it can be determined as protected agriculture (such as greenhouse).

[0065] Furthermore, traditional remote sensing monitoring usually only relies on the vegetation index and is easily affected by factors such as precipitation and soil type. The present invention combines soil humidity, improves the stability and accuracy of planting use monitoring, and many cultivated land analyses only focus on the status at a certain moment and do not consider the long - term change trend. The present invention integrates data at multiple time points through the index time chain, making the change trend of land use more interpretable.

[0066] Step S3: Obtain the index time chain of all planting areas and construct an index time chain matrix; Based on the index time chain matrix, calculate the inter - chain coupling degree between adjacent index time chains; Preset an inter - chain coupling degree threshold, obtain all similar planting areas, and construct a similar area set.

[0067] Specifically, based on the index time chain {CVSI a (PA i (PA a )|i ∈ [1, I]} of the planting area PA, obtain the index time chain of all planting areas and construct an index time chain matrix. The rows of the index time chain matrix are the cultivated land vegetation - soil cycle indexes of a single planting area in all data collection cycles, and the columns of the index time chain matrix are the cultivated land vegetation - soil cycle indexes of all planting areas in a single data collection cycle, specifically as follows:

[0068]

[0069] Among them, CVSII (PA A ) represents the cropland vegetation - soil cycle index of the A - th planting area PA under the I - th data acquisition cycle. A

[0070] Furthermore, based on the index time - chain matrix, calculate the inter - chain coupling degree between adjacent index time - chains. The calculation formula is as follows:

[0071]

[0072] where D(PA a , PA b ) represents the inter - chain coupling degree between the index time - chain {CVSI i (PA a )|i ∈ [1, I]} and the index time - chain {CVSI i (PA b )|i ∈ [1, I]}. CVSI i (PA b ) represents the cropland vegetation - soil cycle index of the planting area PA in the i - th data acquisition cycle. b

[0073] Preset an inter - chain coupling degree threshold. If the inter - chain coupling degree D(PA i (PA a )|i ∈ [1, I]} and the index time - chain {CVSI i (PA b )|i ∈ [1, I]} is greater than or equal to the inter - chain coupling degree threshold, then it is determined that there is similarity between the planting area PA a and the planting area PA b . Obtain all the planting areas similar to the planting area PA a , and construct a similar - area set of the planting area PA b . a a

[0074] It should be noted that traditional methods usually divide farmland based on geographical location, ignoring the similarity of planting patterns. The present invention introduces the calculation of coupling degree, so that even if the farmland is not continuous in space, as long as the planting patterns are similar, they can be classified into the same similar - area set. The index time - chain matrix provides a structured storage method, making data analysis more hierarchical, while avoiding redundant calculations and improving data - processing efficiency.

[0075] Step S4: Based on the cropland vegetation - soil index, calculate the index change trend of the index time - chain; preset an index change trend threshold, and analyze and monitor the uses of all planting areas in the similar - area set.

[0076] Specifically, based on the set of similar regions of the planting area PA a and the cultivated land vegetation-soil cycle index CVSI a of the planting area PA i (PA a ) in the i-th data collection cycle, calculate the index change trend of the index time chain {CVSI i (PA a )|i ∈ [1, I]}, and the calculation formula is as follows:

[0077]

[0078] where G(PA a ) represents the index change trend of the index time chain {CVSI i (PA a )|i ∈ [1, I]}, and CVSI i-1 (PA a ) represents the cultivated land vegetation-soil cycle index of the planting area PA a in the (i - 1)-th data collection cycle.

[0079] Furthermore, preset an index change trend threshold. If the index change trend of the index time chain {CVSI i (PA a )|i ∈ [1, I]} is less than the index change trend threshold, it means that there are abnormal uses in the planting area PA a (decline in agricultural productivity (decrease in yield, soil degradation, water shortage), the plot is being fallowed or abandoned, the land use may be changing (urbanization, aquaculture, ecological restoration, etc.), may be affected by extreme weather, pests and diseases or human damage), then it is determined that all planting areas in the set of similar regions of the planting area PA a have abnormal uses, and a warning is sent to the staff.

[0080] It should be noted that traditional monitoring of cultivated land use changes relies on annual statistical data and has strong hysteresis. Through index change trend analysis, the present invention realizes real-time monitoring, improves the dynamic management ability of land use, and the index change trend combined with the set of similar regions can more accurately judge abnormal situations of farmland use, such as production reduction due to drought, fallow due to policy adjustment, etc., so as to provide targeted agricultural management strategies.

[0081] Please refer to Figure 2, in the second embodiment: A cultivated land planting use monitoring system based on multi-source remote sensing data is provided. The system includes: a regional division and data acquisition module, an index calculation and time chain construction module, a matrix construction and coupling degree calculation module, and a trend calculation, analysis and early warning module.

[0082] The regional division and data acquisition module: divides the use scope of cultivated land planting land into several planting areas; monitors the planting data of the planting areas, and the planting data includes vegetation index and soil humidity.

[0083] The index calculation and time chain construction module: calculates the cultivated land vegetation-soil index of the planting area based on the vegetation index and soil humidity; constructs the index time chain of the planting area based on the cultivated land vegetation-soil index of the planting area.

[0084] The matrix construction and coupling degree calculation module: obtains the index time chains of all planting areas and constructs an index time chain matrix; calculates the inter-chain coupling degree between adjacent index time chains based on the index time chain matrix; presets an inter-chain coupling degree threshold, obtains all similar planting areas, and constructs a similar area set.

[0085] The trend calculation, analysis and early warning module: calculates the index change trend of the index time chain based on the cultivated land vegetation-soil index; presets an index change trend threshold, analyzes and monitors the use of all planting areas in the similar area set.

[0086] Further, the regional division and data acquisition module includes a regional division unit and a data acquisition unit.

[0087] The regional division unit: uses a high-precision GPS device to survey the use scope of cultivated land planting land, divides the use scope of the cultivated land planting land into several planting areas by using grid division technology, uniformly numbers the planting areas, classifies the planting areas based on the number information, and generates a planting area set.

[0088] The data acquisition unit: carries a remote sensing survey device on an unmanned aerial vehicle to monitor the planting data of the planting area, and the planting data includes vegetation index and soil humidity.

[0089] Further, the index calculation and time chain construction module includes an index calculation unit and a time chain construction unit.

[0090] The index calculation unit: calculates the cultivated land vegetation-soil index of the planting area based on the vegetation index and soil humidity.

[0091] The time chain construction unit: Based on the cultivated land vegetation-soil index of the planting area, construct the index time chain of the planting area as follows: Taking months as the unit, construct a data collection cycle, obtain the cultivated land vegetation-soil index of the planting area under each data collection cycle, and record the cultivated land vegetation-soil index of the planting area under a single data collection cycle as the cultivated land vegetation-soil cycle index; Arrange the cultivated land vegetation-soil cycle indexes in the order of time of the data collection cycle, and record all the arranged cultivated land vegetation-soil cycle indexes as the index time chain of the planting area.

[0092] Further, the matrix construction and coupling degree calculation module includes a matrix construction unit and a coupling degree calculation unit.

[0093] The matrix construction unit: Based on the index time chain of the planting area, obtain the index time chains of all planting areas and construct an index time chain matrix. The rows of the index time chain matrix are the cultivated land vegetation-soil cycle indexes of a single planting area under all data collection cycles, and the columns of the index time chain matrix are the cultivated land vegetation-soil cycle indexes of all planting areas under a single data collection cycle.

[0094] The coupling degree calculation unit: Based on the index time chain matrix, calculate the inter-chain coupling degree between adjacent index time chains; Preset an inter-chain coupling degree threshold. If the inter-chain coupling degree between adjacent index time chains is greater than or equal to the inter-chain coupling degree threshold, it is determined that there is similarity between adjacent planting areas; Obtain all planting areas similar to the current planting area and construct a set of similar areas of the current planting area.

[0095] Further, the trend calculation and analysis warning module includes a trend calculation unit and an analysis warning unit.

[0096] The trend calculation unit: Based on the set of similar areas of the current planting area and the cultivated land vegetation-soil cycle index of the current planting area under a single data collection cycle, calculate the index change trend of the index time chain.

[0097] The analysis warning unit: Preset an index change trend threshold. If the index change trend of the index time chain is less than the index change trend threshold, it indicates that there is an abnormal use in the current planting area, then it is determined that there is an abnormal use in all planting areas in the set of similar areas of the current planting area, and a warning is sent to the staff.

[0098] It should be noted that in this text, relational terms such as first and second are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the term "comprising", "including" or any other variant thereof is intended to cover non-exclusive inclusion, so that a process, method, article or device comprising a series of elements not only includes those elements, but also includes other elements not expressly listed, or further includes elements inherent to such process, method, article or device.

[0099] Finally, it should be noted that the above are only the preferred embodiments of the present invention and are not used to limit the present invention. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions recorded in the foregoing embodiments or perform equivalent replacements for some of the technical features. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present invention shall be included within the protection scope of the present invention.

Claims

1. A method for monitoring cultivated land planting use based on multi-source remote sensing data, characterized in that: The method comprises the following steps: Step S1: Divide the use range of cultivated land into several planting areas; monitor the planting data of the planting areas, wherein the planting data includes vegetation index and soil moisture; Step S2: Calculate the cultivated land vegetation-soil index of the planting area based on the vegetation index and soil moisture; construct an index time chain of the planting area based on the cultivated land vegetation-soil index of the planting area; Step S3: Obtain the index time chains of all planting areas and construct an index time chain matrix; based on the index time chain matrix, calculate the inter-chain coupling degree between adjacent index time chains; preset the inter-chain coupling degree threshold, obtain all similar planting areas, and construct a similar area set; Step S4: Based on the cultivated land vegetation-soil index, the index change trend of the index time chain is calculated; a threshold value of the index change trend is preset, and all planting areas in the similar area set are analyzed and the use is monitored.

2. The method for monitoring cultivated land planting use based on multi-source remote sensing data according to claim 1, characterized in that: The specific implementation process of step S1 includes: Use high-precision GPS equipment to survey the use range of cultivated land, use grid division technology to divide the use range of cultivated land into several planting areas, uniformly number the planting areas, classify the planting areas based on the number information, and generate a planting area set, recorded as AR = {PA a |a∈[1,A]}, where PA a represents the ath planting area, and A represents the total number of planting areas; Equipped with remote sensing equipment on drones to monitor the PA of planting areas a The planting data includes vegetation index and soil moisture, and the planting area PA a The vegetation index and soil moisture in the a ) and SH(PA a ).

3. The method for monitoring cultivated land planting usage based on multi-source remote sensing data according to claim 2 is characterized in that: The specific implementation process of step S2 includes: Based on the vegetation index VI (PA a ) and soil moisture SH(PA a ), calculate the planting area PA a The calculation formula of cultivated land vegetation-soil index is as follows: Among them, CVSI (PA a ) indicates the planting area PA a The arable land vegetation-soil index, VI ref Indicates the preset vegetation index reference value, SH ref represents the preset soil moisture reference value, α and β represent the preset vegetation index VI (PA a ) and soil moisture SH(PA a )’s impact factor; Based on the planting area PA a The arable land vegetation-soil index CVSI (PA a ), construct planting area PA a The exponential time chain is as follows: The data collection cycle is constructed in months, and the PA of the planting area in each data collection cycle is obtained. a The cultivated land vegetation-soil index is the PA of the planting area in the i-th data collection cycle. a The cultivated land vegetation-soil index is recorded as the cultivated land vegetation-soil cycle index CVSI i (PA a ); Cultivated land vegetation-soil cycle index CVSI i (PA a ) are arranged in the order of the time of the data collection cycle, and the vegetation-soil cycle index of all arranged cultivated land is recorded as the planting area PA a The exponential time chain is denoted as {CVSI i (PA a )|i∈[1,I]}, where I represents the total number of data collection cycles.

4. The method for monitoring cultivated land planting use based on multi-source remote sensing data according to claim 3 is characterized in that: The specific implementation process of step S3 includes: Based on the planting area PA a The exponential time chain {CVSI i (PA a )|i∈[1,I]}, obtain the index time chain of all planting areas, and construct an index time chain matrix, the rows of the index time chain matrix are the cultivated land vegetation-soil cycle index of a single planting area in all data collection cycles, and the columns of the index time chain matrix are the cultivated land vegetation-soil cycle index of all planting areas in a single data collection cycle, as follows: Among them, CVSI I (PA A ) represents the Ath planting area PA in the Ith data collection cycle A The cultivated land vegetation-soil cycle index; Based on the exponential time chain matrix, the inter-chain coupling degree between adjacent exponential time chains is calculated, and the calculation formula is as follows: Among them, D(PA a ,PA b ) represents the exponential time chain {CVSI i (PA a )|i∈[1,I]} and the exponential time chain {CVSI i (PA b )|i∈[1,I]}, CVSI i (PA b ) represents the planting area PA in the i-th data collection cycle b The cultivated land vegetation-soil cycle index; Preset inter-chain coupling threshold, if the exponential time chain {CVSI i (PA a )|i∈[1,I]} and the exponential time chain {CVSI i (PA b )|i∈[1,I]} between chains D(PA a ,PA b ) is greater than or equal to the inter-chain coupling degree threshold, then the planting area PA is determined a With planting area PA b There is a similarity between; get all and planting area PA a Similar planting areas, construct planting area PA a A collection of similar regions.

5. The method for monitoring cultivated land planting use based on multi-source remote sensing data according to claim 4 is characterized in that: The specific implementation process of step S4 includes: Based on the planting area PA a The similar area set and the planting area PA in the i-th data collection cycle a CVSI i (PA a ), calculate the index time chain {CVSI i (PA a )|i∈[1,I]}, the calculation formula is as follows: Among them, G(PA a ) represents the exponential time chain {CVSI i (PA a )|i∈[1,I]}, CVSI i-1 (PA a ) represents the planting area PA in the i-1th data collection cycle a The cultivated land vegetation-soil cycle index; Preset index change trend threshold, if the index time chain {CVSI i (PA a )|i∈[1,I]} is less than the exponential change trend threshold, indicating that the planting area PA a If there is an abnormal use, the planting area PA is determined a If all planting areas in the set of similar areas have abnormal uses, an early warning will be issued to the staff.

6. A system for monitoring cultivated land planting usage based on multi-source remote sensing data, which executes a method for monitoring cultivated land planting usage based on multi-source remote sensing data as described in any one of claims 1 to 5, characterized in that: The system includes: a regional division and data collection module, an index calculation and time chain construction module, a matrix construction and coupling degree calculation module, and a trend calculation and analysis warning module; The area division and data collection module: divides the use range of cultivated land into several planting areas; monitors the planting data of the planting areas, wherein the planting data includes vegetation index and soil moisture; The index calculation and time chain construction module: calculates the cultivated land vegetation-soil index of the planting area based on the vegetation index and soil moisture; constructs the index time chain of the planting area based on the cultivated land vegetation-soil index of the planting area; The matrix construction and coupling degree calculation module: obtains the exponential time chains of all planting areas and constructs an exponential time chain matrix; calculates the inter-chain coupling degree between adjacent exponential time chains based on the exponential time chain matrix; presets an inter-chain coupling degree threshold, obtains all similar planting areas, and constructs a similar area set; The trend calculation and analysis early warning module: based on the cultivated land vegetation-soil index, calculates the index change trend of the index time chain; presets the index change trend threshold, analyzes and monitors the use of all planting areas in the similar area set.

7. The system for monitoring cultivated land use based on multi-source remote sensing data according to claim 6, characterized in that: The area division and data acquisition module includes an area division unit and a data acquisition unit; The area division unit: uses a high-precision GPS device to survey the use range of the cultivated land, divides the use range of the cultivated land into several planting areas using a grid division technology, uniformly numbers the planting areas, classifies the planting areas based on the numbering information, and generates a planting area set; The data acquisition unit is equipped with a remote sensing survey device on the UAV to monitor the planting data of the planting area, wherein the planting data includes a vegetation index and soil moisture.

8. The system for monitoring cultivated land use based on multi-source remote sensing data according to claim 7, characterized in that: The index calculation and time chain construction module includes an index calculation unit and a time chain construction unit; The index calculation unit calculates the cultivated land vegetation-soil index of the planting area based on the vegetation index and soil moisture; The time chain construction unit: constructs an index time chain of the planting area based on the cultivated land vegetation-soil index of the planting area, specifically as follows: constructs a data collection cycle in months, obtains the cultivated land vegetation-soil index of the planting area under each data collection cycle, and records the cultivated land vegetation-soil index of the planting area under a single data collection cycle as the cultivated land vegetation-soil cycle index; arranges the cultivated land vegetation-soil cycle indexes in sequence according to the time sequence of the data collection cycles, and records all the arranged cultivated land vegetation-soil cycle indices as the index time chain of the planting area.

9. The system for monitoring cultivated land use based on multi-source remote sensing data according to claim 8, characterized in that: The matrix construction and coupling degree calculation module includes a matrix construction unit and a coupling degree calculation unit; The matrix construction unit: based on the index time chain of the planting area, obtains the index time chain of all the planting areas, and constructs an index time chain matrix, wherein the rows of the index time chain matrix are the cultivated land vegetation-soil cycle indexes of a single planting area in all data collection cycles, and the columns of the index time chain matrix are the cultivated land vegetation-soil cycle indexes of all the planting areas in a single data collection cycle; The coupling degree calculation unit: calculates the inter-chain coupling degree between adjacent exponential time chains based on the exponential time chain matrix; presets an inter-chain coupling degree threshold, and if the inter-chain coupling degree between adjacent exponential time chains is greater than or equal to the inter-chain coupling degree threshold, it is determined that there is similarity between adjacent planting areas; Get all the planting areas similar to the current planting area and build a set of similar areas to the current planting area.

10. The system for monitoring cultivated land use based on multi-source remote sensing data according to claim 9, characterized in that: The trend calculation and analysis warning module includes a trend calculation unit and an analysis warning unit; The trend calculation unit calculates the index change trend of the index time chain based on the similar area set of the current planting area and the cultivated land vegetation-soil cycle index of the current planting area in a single data collection cycle; The analysis and early warning unit: presets an index change trend threshold. If the index change trend of the index time chain is less than the index change trend threshold, it indicates that the current planting area has abnormal use. It is then determined that all planting areas in a set of similar areas to the current planting area have abnormal use, and an early warning is issued to the staff.

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