CN110321784B - Method, apparatus, electronic device and computer medium for soil moisture estimation - Google Patents
Method, apparatus, electronic device and computer medium for soil moisture estimation Download PDFInfo
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Abstract
Embodiments of the present application provide a method, an apparatus, an electronic device, and a computer medium for soil moisture estimation, the method including: acquiring multiple groups of remote sensing data of a pixel area at preset time; drawing a plurality of two-dimensional distribution graphs of the surface temperature and the vegetation index, and fitting data points in each two-dimensional distribution graph to obtain a plurality of slopes corresponding to a target pixel, wherein the target pixel is a pixel in a pixel area; determining two extreme values in all slopes, wherein the two extreme values correspond to dry edges and wet edges of a feature space of the earth surface temperature and the vegetation index; and estimating the soil moisture content of the target pixel at the target time by using the two extreme values. The method and the device only aim at the data of the target pixel, time-consuming correction is not needed, and the accuracy of the final soil moisture content is also ensured due to the adoption of multiple groups of remote sensing data of long-time sequences.
Description
Technical Field
The present application relates to the field of remote sensing estimation of surface soil moisture, and more particularly, to a method, an apparatus, an electronic device, and a computer medium for estimating soil moisture.
Background
The surface soil moisture is a basic parameter in the research of the formation, conversion and consumption processes of land water resources, is a link for connecting surface water and underground water, is a basic element for researching surface energy exchange, and plays a very important role in climate change. Meanwhile, soil moisture is taken as important content concerned in the fields of soil science, hydrology, ecology and the like, and the soil physical hydrology characteristics can be better understood through the research on the soil moisture space-time mode, so that the hydrology model and the models of climate, ecology and the like are effectively combined on different scales, the understanding of the land surface process is enhanced, and the soil moisture space-time mode is important content applied in the aspects of regional resource environment dynamics, agricultural drought monitoring and the like.
In the current global change research, soil moisture is used as a key parameter in the process of exchanging substances and energy between the land and the atmospheric system, and the change of the soil moisture determines the change process of other relevant factors in the system, so that the whole land ecosystem is influenced.
Triangular/trapezoidal models based on surface temperature and vegetation index feature space have been widely used for remote sensing estimation of soil moisture. However, when the existing model is used for soil moisture estimation, the estimation of the dry edge in the model is usually carried out by a theoretical calculation method, and the estimation process needs more assistance of ground meteorological and vegetation data; in addition, since the surface temperature is affected not only by the soil moisture content, but also by meteorological factors such as solar radiation, air temperature, relative humidity and wind speed, the estimation of the soil moisture content using the existing model usually requires time-consuming calculation and calibration of the parameters each day. Therefore, certain uncertainty exists in the existing soil moisture estimation based on the earth surface temperature and vegetation index characteristic space model.
Disclosure of Invention
An object of the embodiments of the present application is to provide a method, an apparatus, an electronic device, and a computer medium for estimating soil moisture, which can improve the estimation accuracy of soil moisture content.
In a first aspect, an embodiment of the present application provides a soil moisture estimation method, including: acquiring multiple groups of remote sensing data of the pixel area within preset time, wherein each group of remote sensing data comprises the earth surface temperature and the vegetation index of the pixels in the pixel area within one satellite transit time; drawing a plurality of two-dimensional distribution graphs of the earth surface temperature and the vegetation index, and fitting data points in each two-dimensional distribution graph to obtain a plurality of slopes corresponding to a target pixel, wherein the two-dimensional distribution graph corresponds to a group of remote sensing data, and the target pixel is a pixel in a pixel area; determining two extreme values in all slopes, wherein the two extreme values correspond to dry edges and wet edges of a feature space of the earth surface temperature and the vegetation index; and estimating the soil moisture content of the target pixel at the target time by using the two extreme values.
Therefore, the slope values corresponding to the target pixel are determined through the multiple groups of remote sensing data of the pixel area in the preset time (or long time sequence), the dry edge and the wet edge of the characteristic space are determined based on two extreme values in the slope values corresponding to the target pixel, the soil moisture content corresponding to the target pixel in the target time is estimated by utilizing the two extreme values, the method is only specific to the data of the target pixel, time-consuming correction is not needed, and the accuracy of the final soil moisture content is also guaranteed due to the fact that the multiple groups of remote sensing data of the long time sequence are adopted.
In one embodiment, the two extremes include a maximum slope and a minimum slope, the two extremes corresponding to dry and wet edges of the feature space of the surface temperature and the vegetation index, including: respectively determining the maximum slope and the minimum slope as a wet edge and a dry edge of a feature space; the method for estimating the soil moisture content of the target pixel corresponding to the target time by using the two extreme values comprises the following steps: calculating a temperature vegetation drought index corresponding to the target pixel at the target time by utilizing the maximum slope, the minimum slope and the slope corresponding to the target pixel at the target time; and estimating the soil moisture content of the target pixel in the target time by using the temperature vegetation drought index.
In one embodiment, calculating the temperature vegetation drought index corresponding to the target pixel at the target time by using the maximum slope, the minimum slope and the slope corresponding to the target pixel at the target time comprises calculating the temperature vegetation drought index according to the following formula:
wherein TVDI is the temperature vegetation drought index of the target pixel at the target time, bWet edgeIs the maximum slope, bDry edgeB is the slope corresponding to the target pixel at the target time;
the method comprises the following steps of estimating the soil moisture content of a target pixel in a target time by utilizing a temperature vegetation drought index, wherein the soil moisture content is estimated according to the following formula:
SWC＝θfc-(θfc-θwp)*TVDI
wherein SWC is the soil moisture content of the target pixel at the target time, thetafcIs field water capacity, thetawpThe water content is wilting.
In one embodiment, the mapping of the plurality of two-dimensional maps of surface temperature and vegetation index comprises: and drawing a two-dimensional distribution diagram by taking the vegetation index as an abscissa and the earth surface temperature as an ordinate, wherein the two-dimensional distribution diagram comprises a plurality of data points which are in one-to-one correspondence with a plurality of pixels in a pixel area.
In a second aspect, the present application provides an apparatus for soil moisture estimation, the apparatus comprising: the acquisition module is used for acquiring multiple groups of remote sensing data of the pixel area within preset time, wherein each group of remote sensing data comprises the earth surface temperature and the vegetation index of the pixels in the pixel area within one satellite transit time; the system comprises a drawing module, a calculating module and a calculating module, wherein the drawing module is used for drawing a plurality of two-dimensional distribution graphs of the earth surface temperature and the vegetation index, and fitting data points in each two-dimensional distribution graph to obtain a plurality of slopes corresponding to a target pixel, the two-dimensional distribution graph corresponds to a group of remote sensing data, and the target pixel is a pixel in a pixel area; the determining module is used for determining two extreme values in all slopes, wherein the two extreme values correspond to dry edges and wet edges of a feature space of the earth surface temperature and the vegetation index; and the estimation module is used for estimating the soil moisture content of the target pixel corresponding to the target time by utilizing the two extreme values.
In one embodiment, the two extreme values include a maximum slope and a minimum slope, and the determining module is further configured to determine the maximum slope and the minimum slope as a wet edge and a dry edge of the feature space, respectively; wherein the estimation module comprises: the calculating module is used for calculating the temperature vegetation drought index of the target pixel at the target time by utilizing the maximum slope, the minimum slope and the slope corresponding to the target pixel at the target time; and the estimation submodule is used for estimating the soil moisture content of the target pixel at the target time by utilizing the temperature vegetation drought index.
In one embodiment, the calculation module is further configured to determine the temperature vegetation drought index according to the following formula:
wherein TVDI is the temperature vegetation drought index of the target pixel at the target time, bWet edgeIs the maximum slope, bDry edgeB is the slope corresponding to the target pixel at the target time;
wherein, the estimation submodule is also used for estimating the soil moisture content according to the following formula:
SWC＝θfc-(θfc-θwp)*TVDI
wherein SWC is the soil moisture content of the target pixel at the target time, thetafcIs field water capacity, thetawpThe water content is wilting.
In one embodiment, the drawing module is further configured to draw a two-dimensional distribution map with the vegetation index as an abscissa and the surface temperature as an ordinate, where the two-dimensional distribution map includes a plurality of data points corresponding to a plurality of pixels in the pixel area in a one-to-one manner.
In a third aspect, the present application provides an electronic device comprising a processor and a memory, the memory storing computer readable instructions that, when executed by the processor, perform a method as in the first aspect or any possible implementation manner of the first aspect.
In a fourth aspect, the present application provides a computer medium having stored thereon a program for soil moisture estimation, which when executed by a processor, implements a method as in the first aspect or any possible implementation manner of the first aspect.
In order to make the aforementioned and other objects, features and advantages of the present invention comprehensible, preferred embodiments accompanied with figures are described in detail below.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are required to be used in the embodiments of the present application will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present application and therefore should not be considered as limiting the scope, and that those skilled in the art can also obtain other related drawings based on the drawings without inventive efforts.
FIG. 1 is a flow chart of a method for soil moisture estimation provided by an embodiment of the present application;
FIG. 2 is a block diagram of an apparatus for soil moisture estimation provided by an embodiment of the present application;
fig. 3 is a schematic structural diagram of an apparatus according to an embodiment of the present disclosure.
Detailed Description
The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all of the embodiments. The components of the embodiments of the present application, generally described and illustrated in the figures herein, can be arranged and designed in a wide variety of different configurations. Thus, the following detailed description of the embodiments of the present application, presented in the accompanying drawings, is not intended to limit the scope of the claimed application, but is merely representative of selected embodiments of the application. All other embodiments, which can be derived by a person skilled in the art from the embodiments of the present application without making any creative effort, shall fall within the protection scope of the present application.
Referring to fig. 1, fig. 1 is a flow chart of a method for estimating soil moisture according to an embodiment of the present application, it should be understood that the method shown in fig. 1 may be performed by an apparatus for estimating soil moisture, which may correspond to the apparatus shown in fig. 2 below, which may be various devices capable of performing the method, such as a personal computer, a server, or a network device, for example, and the present application is not limited thereto, and in particular, the method shown in fig. 1 includes the following steps:
and S110, acquiring multiple groups of remote sensing data of the pixel area within preset time, wherein each group of remote sensing data comprises the earth surface temperature and the vegetation index of the pixels in the pixel area within one satellite transit time.
It should be understood that the preset time may also be referred to as a long time sequence, which is not limited in the present application.
In step S110, the earth surface temperature and the vegetation index corresponding to the long-time sequence of the region to be monitored of the earth surface can be remotely sensed by using the satellite.
For example, in the case that the area to be detected is the beijing city, a plurality of groups (or a plurality of groups) of remote sensing data of 10 years from 2001 to 2010 in the beijing city can be obtained by using satellite remote sensing, each group of remote sensing data comprises a surface temperature and a vegetation index, wherein one group of remote sensing data corresponds to one group of data acquired at one satellite transit time, and the application does not limit the data.
It should also be understood that the preset time may be set according to actual requirements. For example, the preset time may be 3 years, 10 years, 18 years, 25 years, etc., which is not limited in this application.
In addition, after the multiple groups of remote sensing data of the area to be detected are obtained, the multiple groups of remote sensing data of the area to be detected can be preprocessed in advance.
For example, the preprocessing process may include removing obvious abnormal data from multiple sets of remote sensing data, and may further include unifying resolutions of images of the area to be detected taken by different satellites, which is not limited in this application.
In addition, after the multiple groups of remote sensing data of the area to be detected are obtained, a target pixel can be selected from the image of the area to be detected, a pixel area containing the target pixel is selected by taking the target pixel as the center, and the multiple groups of remote sensing data of the same pixel area at different times are obtained.
For example, after the target image element is selected, the image element area is framed by taking the target image element as the center and through a sliding window with a certain size. And then, multiple groups of remote sensing data of the image element region at preset time can be acquired through ArcGIS software, which is not limited in the application.
It should also be understood that the position of the target pixel in the pixel area and the number of pixels included in the pixel area can be set according to actual requirements, as long as the pixels in the pixel area are adjacent, which is not limited in the present application. For example, an image of an area to be monitored is provided with a plurality of pixel areas, one of the pixel areas includes 9 adjacent pixels, and the target pixel is arranged outside the 9 adjacent pixels, which is not limited in this application.
And step S120, drawing a plurality of two-dimensional distribution graphs of the earth surface temperature and the vegetation index, and fitting data points in each two-dimensional distribution graph to obtain a plurality of slopes corresponding to a target pixel, wherein one two-dimensional distribution graph corresponds to one group of remote sensing data, and the target pixel is one pixel in a pixel area.
It should be understood that the two-dimensional distribution map may also be referred to as a two-dimensional distribution map, which is not limited in this application.
It should also be understood that for the same image element region, different two-dimensional distribution maps correspond to the remote sensing data of the same image element region at different satellite transit times. In step S120, after acquiring multiple sets of remote sensing data of the pixel region within a preset time, a two-dimensional distribution map may be constructed by using each set of remote sensing data.
In order to facilitate understanding of the technical solution of the present application, a two-dimensional distribution map is constructed by using a set of remote sensing data.
The soil moisture content can be estimated by the existing scheme through a characteristic space model of the earth surface temperature and the vegetation index, and the soil moisture content can be estimated by the characteristic space model only by taking the earth surface temperature and the vegetation index as input. However, when the image elements at the positions near the upper boundary in the feature space cannot reach the condition that all the relative soil is 1, in this case, the theoretical dry edge of the feature space does not exist, but the soil moisture content is estimated by inaccurate dry edge, so that the soil moisture content is also inaccurate. Correspondingly, the wet edges of the feature spaces are similar and will not be described in detail herein.
In addition, the slopes of different surface temperature and vegetation index relations at the target pixel can represent different soil water deficit degrees, wherein the target pixel can correspond to the target data point in the two-dimensional distribution map. Therefore, the extreme value of the slope corresponding to the target pixel determined by the multiple groups of remote sensing data can be used for determining the dry edge and the wet edge of the characteristic space, so that inaccuracy caused by the fact that the dry edge and the wet edge are determined only by the spatial information of the data at the satellite transit time is avoided. In addition, it should be understood that the slope of the relationship between the different surface temperatures and the vegetation indexes at the target pixel may also be referred to as a slope of the relationship between the different surface temperatures and the vegetation indexes corresponding to the target pixel, which is not limited in this application.
In addition, the two-dimensional distribution map can be drawn by taking the vegetation index in the same satellite transit time as an abscissa and taking the earth surface temperature in the same satellite transit time as an ordinate, or the two-dimensional distribution map can project the earth surface temperature and the vegetation index acquired in the first satellite transit time of the pixel area into a coordinate system of the two-dimensional distribution map.
In addition, since the plurality of data points in the two-dimensional distribution map correspond to the plurality of pixels in the pixel region, the plurality of data points in the two-dimensional distribution map are linearly fitted to obtain a fitted straight line, and then the slope of the fitted straight line is obtained. And taking the slope of the obtained fitting straight line as a slope corresponding to the target pixel, or taking the slope of the obtained fitting straight line as a slope of the target pixel.
Meanwhile, it should be understood that, because the target pixel is located in the pixel region, a slope corresponding to the target pixel may also be regarded as a slope corresponding to the pixel region or a slope of the pixel region, which is not limited in this application.
In addition, a plurality of slopes corresponding to the target pixel can be obtained by a linear regression method.
For example, in the case that the vegetation index is a normalized vegetation index, the slope corresponding to the target pixel may be calculated by a robust linear regression method. The linear relation equation of the earth surface temperature and the normalized vegetation index obtained by using the robust linear regression method is as follows:
LST＝a+b*NDVI
wherein LST is the surface temperature, NDVI is the normalized vegetation index, a is the intercept of the linear equation, and b is the slope corresponding to the target pixel.
It should also be understood that, although the vegetation index is taken as the normalized vegetation index in step S130 for example, a person skilled in the art may also obtain the slope corresponding to the target pixel by using other vegetation indexes, which is not limited in the present application.
Step S130, determining two extreme values in all slopes, wherein the two extreme values correspond to a dry edge and a wet edge of the feature space of the surface temperature and the vegetation index.
In step S130, under the condition that a plurality of slopes corresponding to the target pixel are obtained, two extreme values of the plurality of slopes may be obtained in a sorting manner, where the two extreme values are the maximum slope and the minimum slope.
In addition, the maximum slope corresponding to the target pixel can be determined as the wet edge of the feature space of the earth surface temperature and the vegetation index, and correspondingly, the minimum slope corresponding to the target pixel can be determined as the dry edge of the feature space. Alternatively, the maximum slope may correspond to the wet edge of the feature space and the minimum efficiency may correspond to the dry edge of the feature space.
And step S140, calculating a temperature vegetation drought index corresponding to the target pixel at the target time by using the maximum slope, the minimum slope and the slope corresponding to the target pixel at the target time, wherein the temperature vegetation drought index can reflect the soil water shortage degree.
It should be understood that the target time is a target time point of a satellite transit time, for example, the target time may be 1 day, 0.5 day, etc., which is not limited in this application.
It should also be understood that the temperature vegetation drought index of the target pixel at the target time may also be referred to as the temperature vegetation drought index of the target pixel at the target time, and the rest of the data are similar and are not limited in this application.
In step S140, the soil water shortage degree can be controlled by the temperatureThe drought index of the vegetation is TVDI, and the drought indexes of the vegetation at the dry edge and the wet edge are respectively recorded as TVDIDry edgeAnd TVDIWet edgeBased on the physical characteristics of the dry and wet edges, there is a TVDIDry edge＝1，TVDIWet edge＝0。
Optionally, under the condition that the maximum slope and the minimum slope corresponding to the target pixel are obtained, the temperature vegetation drought index may be calculated by the following formula:
wherein TVDI is the temperature vegetation drought index of the target pixel at the target time, bWet edgeIs the maximum slope, bDry edgeB is a slope corresponding to the target pixel at the target time. In addition, a slope corresponding to the target pixel at the target time may be obtained by the method of step S120, which is not limited in this application.
In addition, the calculation formula of the drought index of the temperature vegetation is converted into the following formula according to the physical characteristics of the dry edge:
therefore, the temperature vegetation drought index corresponding to the target pixel in the target time is obtained through the calculation formula of the temperature vegetation drought index.
In addition, although the calculation formula of the temperature vegetation index is exemplified in the embodiment, it should be understood by those skilled in the art that the temperature vegetation drought index can also be calculated by other formulas or a formula in which the above calculation formula is appropriately modified, and the present application does not limit this.
And S150, estimating the soil moisture content of the target pixel corresponding to the target time by using the temperature vegetation drought index.
In step S150, a corresponding relation between the temperature vegetation drought index and the soil moisture content may be obtained in advance, and then the soil moisture content may be estimated by using the relation.
Optionally, under the condition that the temperature vegetation drought index corresponding to the target pixel at the target time is obtained, estimating the soil moisture content corresponding to the target pixel at the target time by using the following formula:
SWC＝θfc-(θfc-θwp)*TVDI
wherein SWC is the soil moisture content of the target pixel at the target time, thetafcIs field water capacity, thetawpThe water content is wilting.
In addition, the unit of soil moisture content, the unit of field water capacity and the unit of wilting water content can be set according to actual requirements. For example, the unit of soil moisture content may be cm3/cm3The unit of field water capacity can be cm3/cm3The unit of wilting water content may be cm3/cm3This is not a limitation of the present application.
In addition, although the calculation formula of the soil moisture content is exemplified in the embodiment, it should be understood by those skilled in the art that the soil moisture content may also be obtained by other formulas or a formula appropriately modified from the above estimation formula, and the present application is not limited thereto.
Therefore, the slope values corresponding to the target pixel are determined through the multiple groups of remote sensing data of the pixel region in the preset time, the dry edge and the wet edge of the characteristic space are determined based on two extreme values in the slope values corresponding to the target pixel, the soil moisture content corresponding to the target pixel in the target time is estimated by utilizing the two extreme values, the method is only based on the data of the target pixel, time-consuming correction is not needed, and the accuracy of the final soil moisture content is also guaranteed due to the fact that the multiple groups of remote sensing data of the long-time sequence are adopted.
In addition, because the slopes of different surface temperature and vegetation index relations at the target pixel can represent different soil moisture deficiency degrees, the method and the device respectively determine the wet edge and the dry edge of the characteristic space through the maximum slope and the minimum slope of a plurality of slopes corresponding to the target pixel, estimate the soil moisture content through the dry edge and the wet edge of the characteristic space, and improve the accuracy of the soil moisture content.
Referring to fig. 2, fig. 2 is a block diagram illustrating a soil moisture estimation apparatus 200 according to an embodiment of the present disclosure. It should be understood that the apparatus 200 corresponds to the method embodiment of fig. 1, and can perform the steps related to the method embodiment, and the specific functions of the apparatus 200 can be referred to the description above, and the detailed description is appropriately omitted here to avoid redundancy. The device 200 includes at least one software functional module that can be stored in a memory in the form of software or firmware (firmware) or solidified in an Operating System (OS) of the device 200. Optionally, the apparatus 200 comprises:
the obtaining module 210 is configured to obtain multiple sets of remote sensing data of the pixel area at a preset time, where each set of remote sensing data includes a ground surface temperature and a vegetation index of a pixel in the pixel area within a satellite transit time; the drawing module 220 is used for drawing a plurality of two-dimensional distribution maps of the earth surface temperature and the vegetation index, and fitting data points in each two-dimensional distribution map to obtain a plurality of slopes corresponding to a target pixel, wherein one two-dimensional distribution map corresponds to one group of remote sensing data, and the target pixel is a pixel in a pixel area; a determining module 230 for determining two extreme values of all slopes, wherein the two extreme values correspond to a dry edge and a wet edge of the feature space of the surface temperature and the vegetation index; and the estimation module 240 is configured to estimate, by using the two extreme values, the soil moisture content of the target pixel at the target time.
In one embodiment, the two extreme values include a maximum slope and a minimum slope, and the determining module 230 is further configured to determine the maximum slope and the minimum slope as a wet edge and a dry edge of the feature space, respectively; wherein the estimation module comprises: a calculating module (not shown) for calculating a temperature vegetation drought index corresponding to the target pixel at the target time by using the maximum slope, the minimum slope and the slope corresponding to the target pixel at the target time; and the estimation submodule (not shown) is used for estimating the soil moisture content of the target pixel at the target time by using the temperature vegetation drought index.
In one embodiment, the calculation module is further configured to determine the temperature vegetation drought index according to the following formula:
wherein TVDI is the temperature vegetation drought index of the target pixel at the target time, bWet edgeIs the maximum slope, bDry edgeB is the slope corresponding to the target pixel at the target time;
wherein, the estimation submodule is also used for estimating the soil moisture content according to the following formula:
SWC＝θfc-(θfc-θwp)*TVDI
wherein SWC is the soil moisture content of the target pixel at the target time, thetafcIs field water capacity, thetawpThe water content is wilting.
In one embodiment, the drawing module 220 is further configured to draw a two-dimensional distribution map with the vegetation index as an abscissa and the surface temperature as an ordinate, where the two-dimensional distribution map includes a plurality of data points corresponding to a plurality of pixels in a pixel area in a one-to-one manner.
Fig. 3 is a block diagram of a structure of an apparatus 300 according to an embodiment of the present disclosure, as shown in fig. 3. The apparatus 300 may include at least one processor 310, such as a CPU, at least one communication interface 320, at least one memory 330, and at least one communication bus 340. Wherein the communication bus 340 is used for realizing direct connection communication of these components. The communication interface 320 of the device in the embodiment of the present application is used for performing signaling or data communication with other node devices. The memory 330 may be a high-speed RAM memory or a non-volatile memory (e.g., at least one disk memory). The memory 330 may optionally be at least one memory device located remotely from the aforementioned processor. The memory 330 stores computer readable instructions which, when executed by the processor 310, perform the method processes described above with reference to fig. 1.
The present application also provides a computer medium having stored thereon a computer program which, when executed by a processor, performs the methods of the method embodiments.
The present application also provides a computer program product which, when run on a computer, causes the computer to perform the methods of the method embodiments.
It can be clearly understood by those skilled in the art that, for convenience and brevity of description, the specific working process of the system described above may refer to the corresponding process in the foregoing method, and will not be described in too much detail herein.
It should be noted that, in the present specification, the embodiments are all described in a progressive manner, each embodiment focuses on differences from other embodiments, and the same and similar parts among the embodiments may be referred to each other. For the device-like embodiment, since it is basically similar to the method embodiment, the description is simple, and for the relevant points, reference may be made to the partial description of the method embodiment.
In the embodiments provided in the present application, it should be understood that the disclosed apparatus and method can be implemented in other ways. The apparatus embodiments described above are merely illustrative, and for example, the flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of apparatus, methods and computer program products according to various embodiments of the present application. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
In addition, functional modules in the embodiments of the present application may be integrated together to form an independent part, or each module may exist separately, or two or more modules may be integrated to form an independent part.
The functions, if implemented in the form of software functional modules and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present application or portions thereof that substantially contribute to the prior art may be embodied in the form of a software product stored in a storage medium and including instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present application. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes. It is noted that, herein, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other identical elements in a process, method, article, or apparatus that comprises the element.
The above description is only a preferred embodiment of the present application and is not intended to limit the present application, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, improvement and the like made within the spirit and principle of the present application shall be included in the protection scope of the present application. It should be noted that: like reference numbers and letters refer to like items in the following figures, and thus, once an item is defined in one figure, it need not be further defined and explained in subsequent figures.
The above description is only for the specific embodiments of the present application, but the scope of the present application is not limited thereto, and any person skilled in the art can easily conceive of the changes or substitutions within the technical scope of the present application, and shall be covered by the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.
Claims (6)
1. A method of soil moisture estimation, comprising:
acquiring multiple groups of remote sensing data of the pixel area within preset time, wherein each group of remote sensing data comprises the earth surface temperature and the vegetation index of the pixels in the pixel area within one satellite transit time;
drawing a plurality of two-dimensional distribution graphs of the earth surface temperature and the vegetation index, and fitting data points in each two-dimensional distribution graph to obtain a plurality of slopes corresponding to a target pixel, wherein one two-dimensional distribution graph corresponds to one group of remote sensing data, and the target pixel is a pixel in the pixel area;
determining two extreme values in all slopes, wherein the two extreme values correspond to dry edges and wet edges of a feature space of the earth surface temperature and the vegetation index;
estimating the soil moisture content of the target pixel at the target time by using the two extreme values;
the two extreme values include a maximum slope and a minimum slope, the two extreme values corresponding to dry and wet edges of a feature space of surface temperature and vegetation index, including:
determining the maximum slope and the minimum slope as a wet edge and a dry edge of the feature space, respectively;
wherein, the estimation of the soil moisture content of the target pixel corresponding to the target time by using the two extreme values comprises the following steps:
calculating a temperature vegetation drought index corresponding to the target pixel at the target time by using the maximum slope, the minimum slope and the slope corresponding to the target pixel at the target time;
estimating the soil moisture content of the target pixel corresponding to the target time by using the temperature vegetation drought index;
calculating the temperature vegetation drought index corresponding to the target pixel at the target time by using the maximum slope, the minimum slope and the slope corresponding to the target pixel at the target time, wherein the calculating the temperature vegetation drought index according to the following formula comprises the following steps:
wherein TVDI is the temperature vegetation drought index of the target pixel at the target time, bWet edgeIs the maximum slope, bDry edgeB is the slope corresponding to the target pixel at the target time;
wherein, the estimating the soil moisture content of the target pixel at the target time by using the temperature vegetation drought index comprises estimating the soil moisture content according to the following formula:
SWC＝θfc-(θfc-θwp)*TVDI
wherein SWC is the soil moisture content of the target pixel at the target time, thetafcIs field water capacity, thetawpThe water content is wilting.
2. The method of claim 1, wherein said plotting a plurality of two-dimensional maps of surface temperature and vegetation index comprises:
and drawing the two-dimensional distribution map by taking the vegetation index as an abscissa and the earth surface temperature as an ordinate, wherein the two-dimensional distribution map comprises a plurality of data points which are in one-to-one correspondence with a plurality of pixels in the pixel area.
3. An apparatus for soil moisture estimation, comprising:
the acquisition module is used for acquiring multiple groups of remote sensing data of the pixel area within preset time, wherein each group of remote sensing data comprises the earth surface temperature and the vegetation index of the pixels in the pixel area within one satellite transit time;
the system comprises a drawing module, a calculating module and a calculating module, wherein the drawing module is used for drawing a plurality of two-dimensional distribution graphs of the earth surface temperature and the vegetation index, and fitting data points in each two-dimensional distribution graph to obtain a plurality of slopes corresponding to a target pixel, one two-dimensional distribution graph corresponds to a group of remote sensing data, and the target pixel is a pixel in a pixel area;
a determining module for determining two extreme values of all slopes, wherein the two extreme values correspond to a dry edge and a wet edge of a feature space of the earth surface temperature and the vegetation index;
the estimation module is used for estimating the soil moisture content of the target pixel corresponding to the target time by using the two extreme values;
the determining module is further configured to determine the maximum slope and the minimum slope as a wet edge and a dry edge of the feature space, respectively;
wherein the estimation module comprises:
the calculation module is used for calculating the temperature vegetation drought index corresponding to the target pixel at the target time by utilizing the maximum slope, the minimum slope and the slope corresponding to the target pixel at the target time;
the estimation submodule is used for estimating the soil moisture content of the target pixel at the target time by utilizing the temperature vegetation drought index;
the calculation module is further configured to determine the temperature vegetation drought index according to the following formula:
wherein TVDI is the temperature vegetation drought index of the target pixel at the target time, bWet edgeIs the maximum slope, bDry edgeB is the slope corresponding to the target pixel at the target time;
wherein the estimation submodule is further configured to estimate the soil moisture content according to the following formula:
SWC＝θfc-(θfc-θwp)*TVDI
wherein SWC is the soil moisture content of the target pixel at the target time, thetafcIs field water capacity, thetawpThe water content is wilting.
4. The apparatus of claim 3, wherein the mapping module is further configured to map the two-dimensional map with the vegetation index as an abscissa and the surface temperature as an ordinate, wherein the two-dimensional map comprises a plurality of data points corresponding to a plurality of pixels in the pixel region.
5. An electronic device comprising a processor and a memory storing computer readable instructions that, when executed by the processor, perform the method of soil moisture estimation according to any of claims 1-2.
6. A computer medium, characterized in that the computer medium has stored thereon a program for soil moisture estimation, which when executed by a processor implements the soil moisture estimation method according to any one of claims 1 to 2.
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| CN114692378A (en) * | 2020-12-31 | 2022-07-01 | 南开大学 | T-shaped supportm-fcCalculation method of extreme temperature combination in trapezoidal frame |
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