Drought monitoring method and device for target area, electronic equipment and storage medium

Abstract

The invention provides a drought monitoring method and device for a target area, electronic equipment and a storage medium, and relates to the technical field of drought monitoring, and the method comprises the steps: for each pixel corresponding to the target area, obtaining meteorological reanalysis data, a normalized vegetation index and a target land surface temperature corresponding to the pixel in a first preset time period; for each pixel, determining a hot boundary and a cold boundary corresponding to the pixel based on the meteorological reanalysis data and the normalized vegetation index corresponding to the pixel; and determining a drought monitoring result corresponding to the target area based on the hot boundaries, the cold boundaries and the target surface temperature corresponding to all the pixels. According to the technical scheme, for the target area, the hot boundary and the cold boundary are determined pixel by pixel through the meteorological reanalysis data, the situation that the weather conditions of the large area with the complex terrain are different is considered, accurate drought monitoring can also be carried out in the large area with the complex terrain, the applicability of drought monitoring is widened, and the drought monitoring accuracy is improved. Moreover, the method does not need to divide the region, and is simpler in steps.

Description

Technical Field

[0001] The present invention relates to the technical field of drought monitoring, and particularly to a drought monitoring method, device, electronic device and storage medium for a target area. Background Art

[0002] Drought causes huge losses to human society, especially agricultural production. Therefore, drought monitoring for a specific area is very important. The prior art reflects the drought situation of a specific area through the Vegetation Temperature Condition Index (VTCI).

[0003] In the process of determining VTCI in the prior art solution, a Normalized Difference Vegetation Index-Land Surface Temperature (NDVI-LST) two-dimensional scatter plot needs to be constructed. However, the prior art assumes a homogeneous atmospheric condition in the study area when constructing the NDVI-LST two-dimensional scatter plot. Therefore, it is only applicable to drought monitoring in small areas. Due to different atmospheric conditions in large areas with complex terrains, the uncertainty of drought monitoring in large areas with complex terrains is relatively high. For VTCI drought monitoring in large areas with complex terrains, the prior art needs to divide the entire area into multiple small areas and calculate VTCI for each small area one by one, which is laborious and the calculation steps are cumbersome. Summary of the Invention

[0004] The present invention provides a drought monitoring method, device, electronic device and storage medium for a target area to solve the defects in the prior art that due to different atmospheric conditions in large areas with complex terrains, the uncertainty of drought monitoring in large areas with complex terrains is relatively high, and the prior art needs to divide the entire area into multiple small areas and calculate VTCI for each small area one by one, which is laborious and the calculation steps are cumbersome. The technical solution of the present invention determines the thermal boundary and cold boundary for each pixel in the target area through meteorological reanalysis data, considering the different weather conditions in large areas with complex terrains. Accurate drought monitoring can also be carried out in large areas with complex terrains, broadening the applicability of drought monitoring. Moreover, the technical solution of the present invention does not need to divide the area, and the steps are more concise.

[0005] The present invention provides a drought monitoring method for a target area, including the following steps.

[0006] For each pixel corresponding to the target area, obtain the meteorological reanalysis data, Normalized Difference Vegetation Index and target land surface temperature corresponding to the pixel within a first preset time period; For each of the pixels, determine the thermal boundary and cold boundary corresponding to the pixel based on the meteorological reanalysis data and Normalized Difference Vegetation Index corresponding to the pixel; Determine the drought monitoring result corresponding to the target area based on the thermal boundary, cold boundary and target land surface temperature corresponding to all the pixels.

[0007] According to a drought monitoring method for a target area provided by the present invention, the meteorological reanalysis data includes sub-meteorological analysis data corresponding to each natural day within the first preset period; Determining the thermal boundary and the cold boundary corresponding to the pixel based on the meteorological reanalysis data and the normalized vegetation index corresponding to the pixel includes: For each natural day within the first preset period, determining a first surface temperature, a second surface temperature, and a third surface temperature corresponding to the pixel based on the sub-meteorological analysis data corresponding to the natural day; the first surface temperature represents the surface temperature when the pixel corresponds to bare land and the soil water content corresponding to the pixel reaches the maximum value; the second surface temperature represents the surface temperature when the pixel corresponds to a vegetation fully covered area and the soil water content corresponding to the pixel reaches the maximum value; the third surface temperature represents the surface temperature when the pixel corresponds to bare land and the soil water content corresponding to the pixel reaches the minimum value; Based on all the first surface temperatures, all the second surface temperatures, and all the third surface temperatures within the first preset period, and the normalized vegetation index corresponding to the pixel, determining the thermal boundary and the cold boundary corresponding to the pixel.

[0008] According to a drought monitoring method for a target area provided by the present invention, the first preset period includes a plurality of second preset periods, and all the second preset periods include all the natural days within the first preset period; Determining the thermal boundary and the cold boundary corresponding to the pixel based on all the first surface temperatures, all the second surface temperatures, and all the third surface temperatures within the first preset period, and the normalized vegetation index corresponding to the pixel includes: For each second preset period within the first preset period, determining the maximum first surface temperature within the second preset period based on all the first surface temperatures within the second preset period, and respectively performing projection processing and resampling processing on the maximum first surface temperature according to a preset spatial resolution to obtain a processed maximum first surface temperature with the spatial resolution of the preset spatial resolution; For each second preset period, determining the maximum second surface temperature within the second preset period based on all the second surface temperatures within the second preset period, and respectively performing projection processing and resampling processing on the maximum second surface temperature according to a preset spatial resolution to obtain a processed maximum second surface temperature with the spatial resolution of the preset spatial resolution; For each of the second preset time periods, determine the minimum third surface temperature within the second preset time period based on all the third surface temperatures within the second preset time period, and perform projection processing and resampling processing on the minimum third surface temperature respectively according to a preset spatial resolution to obtain a processed minimum third surface temperature with the spatial resolution being the preset spatial resolution; Based on all the processed maximum first surface temperatures, all the processed maximum second surface temperatures, and all the processed minimum third surface temperatures within the first preset time period, and the normalized vegetation index corresponding to the pixel, determine the thermal boundary and the cold boundary corresponding to the pixel.

[0009] According to a drought monitoring method for a target area provided by the present invention, the normalized vegetation index includes sub-normalized vegetation indices respectively corresponding to each natural day within the first preset time period; The determining the thermal boundary and the cold boundary corresponding to the pixel based on all the processed maximum first surface temperatures, all the processed maximum second surface temperatures, and all the processed minimum third surface temperatures within the first preset time period, and the normalized vegetation index corresponding to the pixel includes: Determine the maximum processed maximum first surface temperature among all the processed maximum first surface temperatures within the first preset time period as the maximum bare land surface temperature; Determine the maximum processed maximum second surface temperature among all the processed maximum second surface temperatures within the first preset time period as the maximum vegetation surface temperature; Determine the maximum sub-normalized vegetation index among the sub-normalized vegetation indices respectively corresponding to each natural day within the first preset time period as the maximum normalized vegetation index; Based on the maximum bare land surface temperature, the maximum vegetation surface temperature, and the maximum normalized vegetation index, determine the thermal boundary corresponding to the pixel; Determine the minimum processed minimum third surface temperature among all the processed minimum third surface temperatures within the first preset time period as the cold boundary corresponding to the pixel.

[0010] According to a drought monitoring method for a target area provided by the present invention, the determining the thermal boundary corresponding to the pixel based on the maximum bare land surface temperature, the maximum vegetation surface temperature, and the maximum normalized vegetation index includes: Wherein, represents the pixel corresponding to the thermal boundary, represents the pixel corresponding to the maximum bare land surface temperature, represents the pixel The corresponding maximum vegetation surface temperature, represents a pixel The corresponding maximum normalized difference vegetation index.

[0011] According to a drought monitoring method for a target area provided by the present invention, determining the drought monitoring result corresponding to the target area based on the thermal boundary, cold boundary, and target surface temperature corresponding to all the pixels includes: For each of the pixels, determining the conditional vegetation temperature index corresponding to the pixel based on the thermal boundary, cold boundary, and target surface temperature corresponding to the pixel; Determining the drought monitoring result corresponding to the target area based on the conditional vegetation temperature indices corresponding to all the pixels.

[0012] According to a drought monitoring method for a target area provided by the present invention, determining the conditional vegetation temperature index corresponding to the pixel based on the thermal boundary, cold boundary, and target surface temperature corresponding to the pixel includes: Wherein, represents a pixel The corresponding conditional vegetation temperature index, represents a pixel The corresponding thermal boundary, represents a pixel The corresponding cold boundary, represents a pixel The corresponding target surface temperature.

[0013] The present invention also provides a drought monitoring device for a target area, including the following modules: An acquisition module, configured to acquire, for each pixel corresponding to the target area, the meteorological reanalysis data, normalized difference vegetation index, and target surface temperature corresponding to the pixel within a first preset time period; A determination module, configured to determine, for each of the pixels, the thermal boundary and cold boundary corresponding to the pixel based on the meteorological reanalysis data and normalized difference vegetation index corresponding to the pixel; A drought monitoring module, configured to determine the drought monitoring result corresponding to the target area based on the thermal boundary, cold boundary, and target surface temperature corresponding to all the pixels.

[0014] The present invention also provides an electronic device, including a memory, a processor, and a computer program stored on the memory and executable on the processor, where when the processor executes the computer program, the drought monitoring method for a target area as described in any one of the above is implemented.

[0015] The present invention also provides a non-transitory computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, it implements the drought monitoring method for the target area as described in any one of the above.

[0016] The present invention also provides a computer program product, including a computer program, and when the computer program is executed by a processor, it implements the drought monitoring method for the target area as described in any one of the above.

[0017] The drought monitoring method, device, electronic device and storage medium for the target area provided by the present invention, for each pixel corresponding to the target area, obtain the meteorological reanalysis data, normalized difference vegetation index and target surface temperature corresponding to the pixel within the first preset period; for each pixel, based on the meteorological reanalysis data and normalized difference vegetation index corresponding to the pixel, determine the thermal boundary and cold boundary corresponding to the pixel; based on the thermal boundary, cold boundary and target surface temperature corresponding to all pixels, determine the drought monitoring result corresponding to the target area. The technical solution of the present invention, for the target area, determines the thermal boundary and cold boundary pixel by pixel through the meteorological reanalysis data, considers the different weather conditions in large areas with complex terrain, can also perform accurate drought monitoring in large areas with complex terrain, broadens the applicability of drought monitoring, and the technical solution of the present invention does not need to divide the area, and the steps are more concise. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the drawings in the following description are some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0019] Figure 1 It is a schematic flow chart of the drought monitoring method for the target area provided by the present invention.

[0020] Figure 2 It is a schematic structural diagram of the drought monitoring device for the target area provided by the present invention.

[0021] Figure 3 It is a schematic structural diagram of the electronic device provided by the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0022] To make the objectives, technical solutions, and advantages of the present invention clearer, the technical solutions in the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, rather than all of the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments in the present invention without creative efforts belong to the scope of protection of the present invention.

[0023] In view of the above problems in the prior art, the present invention provides a drought monitoring method for a target area. Figure 1 It is a schematic flowchart of the drought monitoring method for the target area provided by the present invention. As Figure 1 shown, the method includes the following steps 110, 120, and 130.

[0024] Step 110: For each pixel corresponding to the target area, obtain the meteorological reanalysis data, normalized vegetation index, and target surface temperature corresponding to the pixel within a first preset time period.

[0025] Exemplarily, the obtaining of the meteorological reanalysis data, normalized vegetation index, and target surface temperature corresponding to the pixel within the first preset time period may include: Obtain the meteorological reanalysis data corresponding to the pixel within the first preset time period from the ERA5-Land dataset; Obtain the normalized vegetation index corresponding to the pixel through the Aqua MODIS surface reflectance product; Obtain the target surface temperature corresponding to the pixel through the Aqua MODIS surface temperature product.

[0026] Specifically, the target area includes multiple pixels, and each pixel can be, for example, a pixel of 0.1° by 0.1°. For each pixel corresponding to the target area, meteorological reanalysis data corresponding to the pixel within the first preset period can be obtained from the ERA5-Land dataset. The ERA5-Land dataset is a global meteorological reanalysis dataset, and the first preset period can be set as needed. For example, the first preset period can be 10 years. It should be noted that the spatial resolution of the meteorological reanalysis data can be 0.1°. The normalized difference vegetation index (NDVI) corresponding to the pixel within the first preset period can also be obtained through the Aqua MODIS surface reflectance product. Aqua MODIS (Aqua Moderate-Resolution Imaging Spectroradiometer) is a moderate-resolution imaging spectroradiometer carried on the Aqua satellite. The model of the Aqua MODIS surface reflectance product can be, for example, MYD09GA. The target surface temperature corresponding to the pixel can also be obtained through the Aqua MODIS surface temperature product. The model of the Aqua MODIS surface temperature product can be, for example, MYD11A1. It should be noted that the spatial resolution of the normalized difference vegetation index and the target surface temperature can be 1000 meters. It is easy to understand that the spatial resolution of the meteorological reanalysis data is different from that of the normalized difference vegetation index and the target surface temperature.

[0027] Optionally, the meteorological reanalysis data corresponding to each pixel within the first preset period can also be obtained through the China Meteorological Administration Land Data Assimilation System (CLDAS). The normalized difference vegetation index and the target surface temperature corresponding to each pixel can also be obtained through high-temporal-resolution satellites such as Sentinel-3 and FY-3.

[0028] In the above embodiment, the meteorological reanalysis data corresponding to each pixel within the first preset period can be obtained through the ERA5-Land dataset, and the process is relatively simple, and the meteorological reanalysis data is more authoritative and reliable. Relatively accurate normalized difference vegetation index and target surface temperature can also be obtained through the Aqua MODIS surface reflectance product and the Aqua MODIS surface temperature product.

[0029] Step 120: For each of the pixels, based on the meteorological reanalysis data and the normalized difference vegetation index corresponding to the pixel, determine the thermal boundary and the cold boundary corresponding to the pixel.

[0030] Specifically, the hot boundary characterizes the maximum land surface temperature corresponding to the pixel within the first preset time period, and the cold boundary characterizes the minimum land surface temperature corresponding to the pixel within the first preset time period.

[0031] In one embodiment, the meteorological reanalysis data includes sub-meteorological analysis data corresponding to each natural day within the first preset time period; Determining the hot boundary and the cold boundary corresponding to the pixel based on the meteorological reanalysis data and the normalized difference vegetation index corresponding to the pixel includes: For each of the natural days within the first preset time period, determining a first land surface temperature, a second land surface temperature, and a third land surface temperature corresponding to the pixel on the natural day based on the sub-meteorological analysis data corresponding to the natural day; the first land surface temperature characterizes the land surface temperature when the pixel corresponds to bare land and the soil water content corresponding to the pixel reaches the maximum value; the second land surface temperature characterizes the land surface temperature when the pixel corresponds to a fully vegetated area and the soil water content corresponding to the pixel reaches the maximum value; the third land surface temperature characterizes the land surface temperature when the pixel corresponds to bare land and the soil water content corresponding to the pixel reaches the minimum value; Determining the hot boundary and the cold boundary corresponding to the pixel based on all the first land surface temperatures, all the second land surface temperatures, and all the third land surface temperatures within the first preset time period, and the normalized difference vegetation index corresponding to the pixel.

[0032] Specifically, the meteorological reanalysis data includes sub-meteorological analysis data corresponding to each natural day within the first preset time period. For example, if the first preset time period is 10 years, the meteorological reanalysis data includes sub-meteorological analysis data corresponding to each day of the 10 years. For each of the natural days within the first preset time period, within the natural day, the land surface temperature when the pixel corresponds to bare land and the soil water content corresponding to the pixel reaches the maximum value can be determined as the first land surface temperature corresponding to the pixel. Within the natural day, the land surface temperature when the pixel corresponds to a fully vegetated area and the soil water content corresponding to the pixel reaches the maximum value can be determined as the second land surface temperature corresponding to the pixel. Within the natural day, the land surface temperature when the pixel corresponds to bare land and the soil water content corresponding to the pixel reaches the minimum value can be determined as the third land surface temperature corresponding to the pixel.

[0033] Exemplarily, the first land surface temperature 、the second land surface temperature and the third land surface temperature can be calculated by the following formulas: Among them, represents the aerodynamic impedance, represents the net surface radiation, and the net surface radiation is the difference between the net solar radiation and the net long-wave surface radiation, represents the volumetric specific heat capacity of air, is , represents the psychrometric constant, represents the slope of the saturated water vapor pressure curve, represents the canopy impedance when the stomata of the vegetation leaves in the fully vegetated area are nearly completely closed, represents the saturation water vapor pressure deficit, represents the sensible heat flux, represents the base of the natural logarithm, represents the surface temperature corresponding to the pixel on the natural day. The surface temperature on the natural day can be the surface temperature at a preset time, for example, it can be the surface temperature at 14:00 on the natural day, represents the air temperature more than two meters above the surface of the pixel on the natural day, represents the dew point temperature, represents the air pressure. It is easy to understand that the above parameters used to calculate the first surface temperature, the second surface temperature, and the third surface temperature all belong to the sub-meteorological analysis data.

[0034] Furthermore, based on all the first surface temperatures, all the second surface temperatures, and all the third surface temperatures corresponding to the pixel within the first preset period, as well as the normalized difference vegetation index corresponding to the pixel, the thermal boundary and the cold boundary corresponding to the pixel can be determined.

[0035] In the above embodiment, the first surface temperature, the second surface temperature, and the third surface temperature corresponding to the pixel on the natural day can be determined more accurately, laying a foundation for determining the thermal boundary and the cold boundary corresponding to each pixel.

[0036] In one embodiment, the first preset period includes a plurality of second preset periods, and all the second preset periods include all the natural days within the first preset period; The determining of the thermal boundary and the cold boundary corresponding to the pixel based on all the first surface temperatures, all the second surface temperatures, and all the third surface temperatures within the first preset period, as well as the normalized difference vegetation index corresponding to the pixel, includes: For each of the second preset time periods within the first preset time period, based on all the first surface temperatures within the second preset time period, determine the maximum first surface temperature within the second preset time period, and perform projection processing and resampling processing on the maximum first surface temperature respectively according to a preset spatial resolution to obtain a processed maximum first surface temperature with a spatial resolution of the preset spatial resolution; For each of the second preset time periods, based on all the second surface temperatures within the second preset time period, determine the maximum second surface temperature within the second preset time period, and perform projection processing and resampling processing on the maximum second surface temperature respectively according to a preset spatial resolution to obtain a processed maximum second surface temperature with a spatial resolution of the preset spatial resolution; For each of the second preset time periods, based on all the third surface temperatures within the second preset time period, determine the minimum third surface temperature within the second preset time period, and perform projection processing and resampling processing on the minimum third surface temperature respectively according to a preset spatial resolution to obtain a processed minimum third surface temperature with a spatial resolution of the preset spatial resolution; Based on all the processed maximum first surface temperatures, all the processed maximum second surface temperatures, and all the processed minimum third surface temperatures within the first preset time period, as well as the normalized difference vegetation index corresponding to the pixel, determine the thermal boundary and cold boundary corresponding to the pixel.

[0037] Specifically, the first preset time period may include multiple second preset time periods, and each second preset time period may respectively include multiple natural days. The preset spatial resolution can be set as needed. It is easy to understand that for the convenience of subsequent calculations, the preset spatial resolution should be the same as the spatial resolution of the normalized difference vegetation index and the target surface temperature.

[0038] Exemplarily, the first preset period is 10 years, the second preset period is each ten-day period of each month within 10 years, the preset spatial resolution is 1000 meters. For each ten-day period within 10 years, the maximum first surface temperature in that ten-day period can be determined as the maximum first surface temperature, and projection processing and resampling processing are respectively performed on the maximum first surface temperature to obtain the processed maximum first surface temperature with a spatial resolution of 1000 meters. The determination processes of the processed maximum second surface temperature and the processed minimum third surface temperature are similar to the above process, and will not be elaborated in this embodiment. Further, based on all the processed maximum first surface temperatures, all the processed maximum second surface temperatures, and all the processed minimum third surface temperatures within 10 years, and the normalized difference vegetation index corresponding to this pixel, the thermal boundary and the cold boundary corresponding to this pixel can be determined. It is easy to understand that the number of processed maximum first surface temperatures, processed maximum second surface temperatures, and processed minimum third surface temperatures within 10 years is 360 (10 years multiplied by 12 months and then multiplied by 3 ten-day periods).

[0039] In the above embodiment, maximum value composition or minimum value composition is performed on the first surface temperature, the second surface temperature, and the third surface temperature, and the spatial resolution of each surface temperature is adjusted to be the same as the spatial resolution of the normalized difference vegetation index, so that the thermal boundary and the cold boundary of the pixel can be calculated and determined subsequently.

[0040] In one embodiment, the normalized difference vegetation index includes sub-normalized difference vegetation indices respectively corresponding to each natural day within the first preset period; The determination of the thermal boundary and the cold boundary corresponding to the pixel based on all the processed maximum first surface temperatures, all the processed maximum second surface temperatures, and all the processed minimum third surface temperatures within the first preset period, and the normalized difference vegetation index corresponding to the pixel includes: Determining the maximum processed maximum first surface temperature among all the processed maximum first surface temperatures within the first preset period as the maximum bare land surface temperature; Determining the maximum processed maximum second surface temperature among all the processed maximum second surface temperatures within the first preset period as the maximum vegetation surface temperature; Determining the maximum sub-normalized difference vegetation index among the sub-normalized difference vegetation indices respectively corresponding to each natural day within the first preset period as the maximum normalized difference vegetation index; Determining the thermal boundary corresponding to the pixel based on the maximum bare land surface temperature, the maximum vegetation surface temperature, and the maximum normalized difference vegetation index; Determining the minimum processed minimum third surface temperature among all the processed minimum third surface temperatures within the first preset period as the cold boundary corresponding to the pixel.

[0041] Specifically, the normalized difference vegetation index includes sub-normalized difference vegetation indices corresponding to each natural day within the first preset period. For example, when the first preset period is 10 years, the normalized difference vegetation index includes sub-normalized difference vegetation indices corresponding to each day within 10 years. Selecting the maximum processed maximum first land surface temperature, the maximum processed maximum second land surface temperature, and the maximum sub-normalized difference vegetation index within the first preset period can calculate and determine the thermal boundary corresponding to the pixel. The minimum processed minimum third land surface temperature within the first preset period can also be directly selected as the cold boundary corresponding to the pixel.

[0042] In the above embodiment, the maximum value synthesis is performed on the processed maximum first land surface temperature, the processed maximum second land surface temperature, and the sub-normalized difference vegetation index, further obtaining an accurate thermal boundary, and the minimum value synthesis is performed on the processed minimum third land surface temperature to obtain an accurate cold boundary.

[0043] In one embodiment, determining the thermal boundary corresponding to the pixel based on the maximum bare land surface temperature, the maximum vegetation land surface temperature, and the maximum normalized difference vegetation index includes: wherein, represents the thermal boundary corresponding to the pixel ; represents the maximum bare land surface temperature corresponding to the pixel ; represents the maximum vegetation land surface temperature corresponding to the pixel ; represents the maximum normalized difference vegetation index corresponding to the pixel ;

[0044] In the above embodiment, the specific method for determining the thermal boundary corresponding to each pixel is described, and the thermal boundary calculated by the above formula is more accurate.

[0045] Step 130: Determine the drought monitoring result corresponding to the target area based on the thermal boundary, cold boundary, and target land surface temperature corresponding to all the pixels.

[0046] In one embodiment, determining the drought monitoring result corresponding to the target area based on the thermal boundary, cold boundary, and target land surface temperature corresponding to all the pixels includes: For each pixel, determine the conditional vegetation temperature index corresponding to the pixel based on the thermal boundary, cold boundary, and target land surface temperature corresponding to the pixel; Determine the drought monitoring result corresponding to the target area based on the conditional vegetation temperature indices corresponding to all the pixels.

[0047] Specifically, for each pixel, the conditional vegetation temperature index corresponding to the pixel can be determined based on the thermal boundary, cold boundary, and target surface temperature corresponding to the pixel. Further, the drought monitoring result corresponding to the target area can be determined based on the conditional vegetation temperature indices corresponding to all pixels.

[0048] In the above embodiment, the conditional vegetation temperature index can better reflect the drought situation of the area, and the conditional vegetation temperature index determined by the method of the present invention introduces meteorological reanalysis data. Therefore, the conditional vegetation temperature index determined by the method of the present invention further improves the accuracy of the drought monitoring result.

[0049] In one embodiment, the determining the conditional vegetation temperature index corresponding to the pixel based on the thermal boundary, cold boundary, and target surface temperature corresponding to the pixel includes: wherein, represents the conditional vegetation temperature index corresponding to the pixel ; represents the thermal boundary corresponding to the pixel ; represents the cold boundary corresponding to the pixel ; represents the target surface temperature corresponding to the pixel .

[0050] Specifically, the surface temperature corresponding to the pixel within the first preset period obtained in step 110 may also include, for example, the sub-surface temperatures corresponding to each natural day within the first preset period, and the maximum sub-surface temperature is determined as the target surface temperature corresponding to the pixel .

[0051] In the above embodiment, the specific manner of determining the conditional vegetation temperature index corresponding to each pixel is described, and the conditional vegetation temperature index calculated by the above formula is more accurate.

[0052] The drought monitoring method for the target area provided by the present invention obtains the meteorological reanalysis data, normalized vegetation index, and target surface temperature corresponding to each pixel in the first preset period for each pixel corresponding to the target area; for each pixel, based on the meteorological reanalysis data and normalized vegetation index corresponding to the pixel, determines the thermal boundary and cold boundary corresponding to the pixel; determines the drought monitoring result corresponding to the target area based on the thermal boundaries, cold boundaries, and target surface temperatures corresponding to all pixels. The technical solution of the present invention determines the thermal boundary and cold boundary pixel by pixel through meteorological reanalysis data for the target area, considers the different weather conditions in large areas with complex terrains, can also perform accurate drought monitoring in large areas with complex terrains, broadens the applicability of drought monitoring, and the technical solution of the present invention does not require regional division and the steps are more concise.

[0053] The drought monitoring device for the target area provided by the present invention will be described below. The drought monitoring device for the target area described below can be mutually referred to the drought monitoring method for the target area described above.

[0054] Figure 2 is a schematic structural diagram of the drought monitoring device for the target area provided by the present invention, as Figure 2 shown, the drought monitoring device 200 for the target area includes the following modules: An acquisition module 210, configured to obtain the meteorological reanalysis data, normalized vegetation index, and target surface temperature corresponding to each pixel in the first preset period for each pixel corresponding to the target area; A determination module 220, configured to determine the thermal boundary and cold boundary corresponding to each pixel based on the meteorological reanalysis data and normalized vegetation index corresponding to the pixel; A drought monitoring module 230, configured to determine the drought monitoring result corresponding to the target area based on the thermal boundaries, cold boundaries, and target surface temperatures corresponding to all pixels.

[0055] In an embodiment, the meteorological reanalysis data includes sub-meteorological analysis data corresponding to each natural day in the first preset period; the determination module 220 is specifically configured to: For each natural day in the first preset period, determine the first surface temperature, second surface temperature, and third surface temperature corresponding to the pixel on the natural day based on the sub-meteorological analysis data corresponding to the natural day; the first surface temperature represents the surface temperature when the pixel corresponds to bare land and the soil water content corresponding to the pixel reaches the maximum value; the second surface temperature represents the surface temperature when the pixel corresponds to a vegetation fully covered area and the soil water content corresponding to the pixel reaches the maximum value; the third surface temperature represents the surface temperature when the pixel corresponds to bare land and the soil water content corresponding to the pixel reaches the minimum value; Based on all the first surface temperatures, all the second surface temperatures, and all the third surface temperatures within the first preset time period, as well as the normalized difference vegetation index corresponding to the pixel, determine the thermal boundary and the cold boundary corresponding to the pixel.

[0056] In one embodiment, the first preset time period includes a plurality of second preset time periods, and all the second preset time periods include all the natural days within the first preset time period; the determining module 220 is further specifically configured to: For each of the second preset time periods within the first preset time period, based on all the first surface temperatures within the second preset time period, determine the maximum first surface temperature within the second preset time period, and perform projection processing and resampling processing on the maximum first surface temperature respectively according to a preset spatial resolution to obtain a processed maximum first surface temperature with the spatial resolution being the preset spatial resolution; For each of the second preset time periods, based on all the second surface temperatures within the second preset time period, determine the maximum second surface temperature within the second preset time period, and perform projection processing and resampling processing on the maximum second surface temperature respectively according to a preset spatial resolution to obtain a processed maximum second surface temperature with the spatial resolution being the preset spatial resolution; For each of the second preset time periods, based on all the third surface temperatures within the second preset time period, determine the minimum third surface temperature within the second preset time period, and perform projection processing and resampling processing on the minimum third surface temperature respectively according to a preset spatial resolution to obtain a processed minimum third surface temperature with the spatial resolution being the preset spatial resolution; Based on all the processed maximum first surface temperatures, all the processed maximum second surface temperatures, and all the processed minimum third surface temperatures within the first preset time period, as well as the normalized difference vegetation index corresponding to the pixel, determine the thermal boundary and the cold boundary corresponding to the pixel.

[0057] In one embodiment, the normalized difference vegetation index includes sub-normalized difference vegetation indices respectively corresponding to each of the natural days within the first preset time period; the determining module 220 is further specifically configured to: Determine the maximum processed maximum first surface temperature among all the processed maximum first surface temperatures within the first preset time period as the maximum bare land surface temperature; Determine the maximum processed maximum second surface temperature among all the processed maximum second surface temperatures within the first preset time period as the maximum vegetation surface temperature; Determine the maximum sub-normalized difference vegetation index among the sub-normalized difference vegetation indices respectively corresponding to each of the natural days within the first preset time period as the maximum normalized difference vegetation index; Determine the thermal boundary corresponding to the pixel based on the maximum bare land surface temperature, the maximum vegetation surface temperature, and the maximum normalized difference vegetation index; Determine the cold boundary corresponding to the pixel by taking the minimum processed minimum third surface temperature among all the processed minimum third surface temperatures within the first preset period.

[0058] In one embodiment, the determining module 220 is further specifically configured to: Wherein, represents the thermal boundary corresponding to the pixel ; represents the maximum bare land surface temperature corresponding to the pixel ; represents the maximum vegetation surface temperature corresponding to the pixel ; represents the maximum normalized difference vegetation index corresponding to the pixel ;

[0059] In one embodiment, the drought monitoring module 330 is specifically configured to: For each pixel, determine the conditional vegetation temperature index corresponding to the pixel based on the thermal boundary, cold boundary, and target surface temperature corresponding to the pixel; Determine the drought monitoring result corresponding to the target area based on the conditional vegetation temperature indices corresponding to all the pixels.

[0060] In one embodiment, the drought monitoring module 330 is further specifically configured to: Wherein, represents the conditional vegetation temperature index corresponding to the pixel ; represents the thermal boundary corresponding to the pixel ; represents the cold boundary corresponding to the pixel ; represents the target surface temperature corresponding to the pixel ;

[0061] The drought monitoring device for the target area provided by the present invention acquires the meteorological reanalysis data, normalized difference vegetation index, and target surface temperature corresponding to each pixel in the target area for a first preset period. For each pixel, based on the meteorological reanalysis data and normalized difference vegetation index corresponding to the pixel, the thermal boundary and cold boundary corresponding to the pixel are determined. Based on the thermal boundaries, cold boundaries, and target surface temperatures corresponding to all pixels, the drought monitoring result corresponding to the target area is determined. The technical solution of the present invention determines the thermal boundary and cold boundary pixel by pixel through meteorological reanalysis data for the target area, considering the different weather conditions in large areas with complex terrain, and can also perform accurate drought monitoring in large areas with complex terrain, broadening the applicability of drought monitoring. Moreover, the technical solution of the present invention does not require regional division, and the steps are more concise.

[0062] Figure 3 An example of the physical structure diagram of an electronic device is shown as Figure 3 shown. The electronic device may include: a processor 310, a communication interface 320, a memory 330, and a communication bus 340. Among them, the processor 310, the communication interface 320, and the memory 330 complete mutual communication through the communication bus 340. The processor 310 can call the logical instructions in the memory 330 to execute the drought monitoring method for the target area, and the method includes: For each pixel corresponding to the target area, acquiring the meteorological reanalysis data, normalized difference vegetation index, and target surface temperature corresponding to the pixel within a first preset period; For each of the pixels, based on the meteorological reanalysis data and normalized difference vegetation index corresponding to the pixel, determining the thermal boundary and cold boundary corresponding to the pixel; Based on the thermal boundaries, cold boundaries, and target surface temperatures corresponding to all the pixels, determining the drought monitoring result corresponding to the target area.

[0063] In addition, when the logical instructions in the above-mentioned memory 330 are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on such an understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or a part of this technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in various embodiments of the present invention. The aforementioned storage medium includes: various media such as USB flash drives, mobile hard disks, read-only memories (ROM, Read-Only Memory), random access memories (RAM, Random Access Memory), magnetic disks, or optical discs that can store program codes.

[0064] On the other hand, the present invention also provides a computer program product. The computer program product includes a computer program that can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer can execute the drought monitoring method for the target area provided by the above-mentioned various methods. The method includes: For each pixel corresponding to the target area, obtain the meteorological reanalysis data, normalized vegetation index, and target surface temperature corresponding to the pixel within a first preset time period; For each of the pixels, based on the meteorological reanalysis data and normalized vegetation index corresponding to the pixel, determine the thermal boundary and cold boundary corresponding to the pixel; Based on the thermal boundaries, cold boundaries, and target surface temperatures corresponding to all the pixels, determine the drought monitoring result corresponding to the target area.

[0065] On another aspect, the present invention also provides a non-transitory computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, it is implemented to execute the drought monitoring method for the target area provided by the above-mentioned various methods. The method includes: For each pixel corresponding to the target area, obtain the meteorological reanalysis data, normalized vegetation index, and target surface temperature corresponding to the pixel within a first preset time period; For each of the pixels, based on the meteorological reanalysis data and normalized vegetation index corresponding to the pixel, determine the thermal boundary and cold boundary corresponding to the pixel; Based on the thermal boundaries, cold boundaries, and target surface temperatures corresponding to all the pixels, determine the drought monitoring result corresponding to the target area.

[0066] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed to multiple network units. Some or all of the modules can be selected according to actual needs to achieve the purpose of the solution of this embodiment. Those of ordinary skill in the art can understand and implement it without creative efforts.

[0067] Through the description of the above embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus a necessary general hardware platform, and of course, it can also be implemented by hardware. Based on this understanding, the essence of the above technical solution, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions for causing a computer device (which can be a personal computer, server, or network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.

[0068] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit them. Although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions recorded in the foregoing embodiments or equivalently replace some of the technical features. These modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of each embodiment of the present invention.

Claims

1. A drought monitoring method for a target area, characterized in that, Including: For each pixel corresponding to the target area, obtaining the meteorological reanalysis data, normalized difference vegetation index, and target surface temperature corresponding to the pixel within a first preset period; For each of the pixels, based on the meteorological reanalysis data and normalized difference vegetation index corresponding to the pixel, determining the thermal boundary and cold boundary corresponding to the pixel; Based on the thermal boundaries, cold boundaries, and target surface temperatures corresponding to all the pixels, determining the drought monitoring result corresponding to the target area.

2. The drought monitoring method for the target area according to claim 1, wherein The meteorological reanalysis data includes sub-meteorological analysis data corresponding to each natural day within the first preset period; The determining the thermal boundary and cold boundary corresponding to the pixel based on the meteorological reanalysis data and normalized difference vegetation index corresponding to the pixel includes: For each natural day within the first preset period, based on the sub-meteorological analysis data corresponding to the natural day, determining the first surface temperature, second surface temperature, and third surface temperature corresponding to the pixel on the natural day; the first surface temperature represents the surface temperature when the pixel corresponds to bare land and the soil water content corresponding to the pixel reaches the maximum value; the second surface temperature represents the surface temperature when the pixel corresponds to a fully vegetated area and the soil water content corresponding to the pixel reaches the maximum value; the third surface temperature represents the surface temperature when the pixel corresponds to bare land and the soil water content corresponding to the pixel reaches the minimum value; Based on all the first surface temperatures, all the second surface temperatures, and all the third surface temperatures within the first preset period, and the normalized difference vegetation index corresponding to the pixel, determining the thermal boundary and cold boundary corresponding to the pixel.

3. The drought monitoring method for the target area according to claim 2, wherein The first preset period includes a plurality of second preset periods, and all the second preset periods include all the natural days within the first preset period; The determining the thermal boundary and cold boundary corresponding to the pixel based on all the first surface temperatures, all the second surface temperatures, and all the third surface temperatures within the first preset period, and the normalized difference vegetation index corresponding to the pixel includes: For each second preset period within the first preset period, based on all the first surface temperatures within the second preset period, determining the maximum first surface temperature within the second preset period, and respectively performing projection processing and resampling processing on the maximum first surface temperature according to a preset spatial resolution to obtain a processed maximum first surface temperature with the spatial resolution of the preset spatial resolution; For each second preset period, based on all the second surface temperatures within the second preset period, determining the maximum second surface temperature within the second preset period, and respectively performing projection processing and resampling processing on the maximum second surface temperature according to a preset spatial resolution to obtain a processed maximum second surface temperature with the spatial resolution of the preset spatial resolution; For each of the second preset time periods, determine the minimum third surface temperature within the second preset time period based on all the third surface temperatures within the second preset time period, and perform projection processing and resampling processing on the minimum third surface temperature respectively according to the preset spatial resolution to obtain the processed minimum third surface temperature with the spatial resolution of the preset spatial resolution; Based on all the processed maximum first surface temperatures, all the processed maximum second surface temperatures, and all the processed minimum third surface temperatures within the first preset time period, and the normalized difference vegetation index corresponding to the pixel, determine the thermal boundary and the cold boundary corresponding to the pixel.

4. The drought monitoring method for the target area according to claim 3, wherein The normalized difference vegetation index includes sub-normalized difference vegetation indices corresponding to each natural day within the first preset time period; The determining the thermal boundary and the cold boundary corresponding to the pixel based on all the processed maximum first surface temperatures, all the processed maximum second surface temperatures, and all the processed minimum third surface temperatures within the first preset time period, and the normalized difference vegetation index corresponding to the pixel includes: Determine the maximum bare land surface temperature as the maximum processed maximum first surface temperature among all the processed maximum first surface temperatures within the first preset time period; Determine the maximum vegetation surface temperature as the maximum processed maximum second surface temperature among all the processed maximum second surface temperatures within the first preset time period; Determine the maximum normalized difference vegetation index as the maximum sub-normalized difference vegetation index among the sub-normalized difference vegetation indices corresponding to each natural day within the first preset time period; Based on the maximum bare land surface temperature, the maximum vegetation surface temperature, and the maximum normalized difference vegetation index, determine the thermal boundary corresponding to the pixel; Determine the minimum processed minimum third surface temperature among all the processed minimum third surface temperatures within the first preset time period as the cold boundary corresponding to the pixel.

5. The drought monitoring method for the target area according to claim 4, wherein The determining the thermal boundary corresponding to the pixel based on the maximum bare land surface temperature, the maximum vegetation surface temperature, and the maximum normalized difference vegetation index includes: Among them, represents the pixel corresponding thermal boundary represents the pixel corresponding maximum bare land surface temperature represents the pixel corresponding maximum vegetation surface temperature represents the pixel corresponding maximum normalized difference vegetation index 6. The drought monitoring method for the target area according to any one of claims 1 to 5, characterized in that, The determining the drought monitoring result corresponding to the target area based on the thermal boundary, the cold boundary, and the target surface temperature corresponding to all the pixels includes: For each pixel, based on the thermal boundary, the cold boundary, and the target surface temperature corresponding to the pixel, determine the conditional vegetation temperature index corresponding to the pixel; Based on the conditional vegetation temperature indices corresponding to all the pixels, determine the drought monitoring result corresponding to the target area.

7. The drought monitoring method for the target area according to claim 6, characterized in that The determining the conditional vegetation temperature index corresponding to the pixel based on the thermal boundary, the cold boundary, and the target surface temperature corresponding to the pixel includes: Among them, represents the pixel corresponding conditional vegetation temperature index, represents the pixel corresponding thermal boundary, represents the pixel corresponding cold boundary, represents the pixel corresponding target surface temperature.

8. A drought monitoring device for a target area, characterized in that, Includes: An acquisition module, configured to acquire, for each pixel corresponding to the target area, the meteorological reanalysis data, the normalized difference vegetation index, and the target surface temperature corresponding to the pixel within the first preset time period; A determination module, configured to determine, for each pixel, the thermal boundary and the cold boundary corresponding to the pixel based on the meteorological reanalysis data and the normalized difference vegetation index corresponding to the pixel; A drought monitoring module for determining a drought monitoring result corresponding to the target area based on the thermal boundary, cold boundary, and target surface temperature corresponding to all the pixels.

9. An electronic device, comprising a memory, a processor, and a computer program stored on the memory and running on the processor, wherein, When the processor executes the computer program, it implements the drought monitoring method for the target area according to any one of claims 1 to 7.

10. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the drought monitoring method for the target area according to any one of claims 1 to 7.

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