Methods, devices, equipment and storage media for alarming weak forest and grassland fires

Abstract

This invention relates to the field of fire alarm technology, and discloses a method, device, equipment, and storage medium for alarming weak forest and grassland fires. It calculates the instantaneous ground surface temperature baseline field, reads the thermal infrared spectral data of the target satellite image, inverts to obtain the first instantaneous ground surface temperature field, converts it into the second instantaneous ground surface temperature field, calculates the sub-pixel thermal increment image, and uses the first and second band images from the target satellite image to perform false-color image synthesis to generate a weak forest and grassland fire alarm signal. Therefore, it proposes a method for rapidly identifying initial and small forest and grassland fires using thermal radiation increment images. By constructing a ground instantaneous thermal radiation brightness temperature baseline field synchronized with remote sensing, and reconstructing the sub-pixel thermal increment image, based on the thermal increment abruptness characteristics and the thermal steady-state characteristics of the forest and grassland distribution area, it characterizes and identifies early forest fires, effectively improving the monitoring efficiency and accuracy of fire points and enhancing the technological level of forest fire monitoring.

Description

Technical Field

[0001] This invention relates to the field of fire alarm technology, and in particular to a method, device, equipment, and storage medium for alarming weak forest and grassland fires. Background Technology

[0002] Because the thermal radiation brightness temperature of weak wildfires in their initial stages is low, even lower than that of strongly warming ground features such as clouds, bare rocks, sand and gravel, land, and valleys, existing remote sensing image-based forest fire identification technology frameworks are unable to identify weak forest and grassland fires. Currently, technology for identifying high-temperature ground heat sources based on absolute thermal radiation brightness temperature indices is relatively mature, but technology for forecasting forest fires based on "hotspots" is still immature. The industry generally uses visual interpretation and manual methods, relying on false-color images and bright red spots formed by high-temperature heat sources to identify and extract forest fires with high-temperature heat source effects; simultaneously, based on slightly reddish or dark red image spots in low-temperature background forest areas, it identifies forest fires without high-temperature heat source effects that are in their early stages of development. Current automatic hotspot extraction and monitoring technologies for forest and grassland fires often include a large number of non-forest fire land types in their hotspot sets, such as cloud reflections, bare rocks (bare ground), urban (town) heat islands, beaches, dry and hot river valleys, agricultural fires, and industrial heat sources. Because too many small fires are missed and too many false alarms (mistaking ordinary heat sources for forest fires) are made, the system cannot meet the needs of industry departments for early warning issuance, field verification and disposal, and emergency command, and therefore cannot be promoted and applied in actual work.

[0003] The "hotspot" identification method is effective for identifying "high-temperature forest fires," but many "low-temperature forest fires" may have a radiation brightness temperature below 315 K, rendering the hotspot identification method ineffective. Current "hotspot" identification theories and methods are unsuitable for identifying "low-temperature forest fires." Furthermore, the "high-temperature forest fires" identified by the "hotspot" identification algorithm are deeply confused with other heat sources, necessitating the exploration of more effective technical methods to address this issue. In fact, "low-temperature forest fires" include forest fires in their early stages. Forest fires located on shady slopes, in dense vegetation areas, and in valleys, as well as those with small burned areas, do not possess the characteristics of high-temperature heat sources. From the development process of forest fire ignition, combustion, and spread, the occurrence and development of a forest fire must go through a process of low temperature, short fireline, and small area. The characteristics of all forest fire occurrence and development determine that they always exist as a "fireline" strip several meters wide, gradually spreading and advancing towards the surrounding areas. When the length of a "fireline" with high-temperature characteristics reaches the kilometer level, its fireline area only occupies a few thousandths of the area of ​​a 1 km mixed pixel. For initial fires and small fires, the area proportion is even smaller. For forest fires in their development stage, although they have a certain burned area, the burned area is small. When they are located in densely vegetated forest areas, shady slopes, thick and dense forests, or virgin forests, the overall thermal radiation value of the pixels is extinguished, blocked, or masked due to the low background brightness temperature. Their thermal radiation brightness temperature cannot reach the level of a "high-temperature heat source," exhibiting low-temperature characteristics. When using 1 km pixel remote sensing data to represent and detect forest fires, only when the fireline and burned area in the mixed pixels are sufficiently large, and the background temperature is relatively high, can the forest fire appear as a "high-temperature heat source" on the ground and a "hot spot" on the remote sensing image. In short, "low-temperature forest fires" are a necessary process in the development of forest fires and represent a form of forest fire existence for some species. Identifying these fires is a major challenge in satellite forest fire monitoring, and research in this area is limited. Summary of the Invention

[0004] This invention provides a method, apparatus, equipment, and storage medium for weak forest and grassland fire alarm, aiming to solve at least one of the above-mentioned technical problems.

[0005] To achieve the above objectives, the present invention provides a method for alarming weak forest and grassland fires, comprising the following steps:

[0006] Acquire a target satellite image, and calculate the instantaneous surface temperature baseline field that is simultaneous with the target satellite image and satisfies the spatial resolution based on the imaging time of the target satellite image and the predefined sub-pixel decomposition target spatial resolution.

[0007] Read the thermal infrared spectral data of the target satellite image, and use the thermal infrared spectral data to invert and obtain the first instantaneous surface temperature field of the target satellite image;

[0008] The first instantaneous surface temperature field is converted into a second instantaneous surface temperature field with higher resolution by using sub-pixel decomposition and interpolation.

[0009] Based on the instantaneous surface temperature baseline field and the second instantaneous surface temperature field, a sub-pixel thermal increment image is calculated, and a false-color image is synthesized using the sub-pixel thermal increment image, the first band image and the second band image in the target satellite image;

[0010] A weak forest and grassland fire alarm signal is generated based on the pixel information in the synthesized false-color image.

[0011] Optionally, the step of acquiring a target satellite image and calculating the instantaneous surface temperature baseline field that is simultaneous with the target satellite image and satisfies the spatial resolution based on the imaging time of the target satellite image and the predefined sub-pixel decomposition target spatial resolution specifically includes:

[0012] Acquire the target satellite image, read the imaging time interval t0 from the header file of the target satellite image, and predefine the target spatial resolution R of sub-pixel decomposition;

[0013] The target satellite image's sub-pixels are decomposed and enhanced, and their spatial resolution is converted to R. Then, based on the converted target satellite image's sub-pixels and the imaging time scale t0 read from the header file, an instantaneous surface temperature baseline field A with imaging time scale t0 synchronized and spatial resolution R is constructed. t0 .

[0014] Optionally, the step of reading the thermal infrared spectral data of the target satellite image and using the thermal infrared spectral data to invert and obtain the first instantaneous surface temperature field of the target satellite image specifically includes: reading the thermal infrared spectral data of the target satellite image, and using the thermal infrared spectral data based on Planck's law and the single-wavelength brightness temperature correction method to invert and obtain the first instantaneous surface temperature field Bt0 of the target satellite image.

[0015] Optionally, the step of converting the first instantaneous surface temperature field into a second instantaneous surface temperature field with higher resolution using sub-pixel decomposition and interpolation methods specifically includes:

[0016] Obtain digital terrain model data, and use GIS bilinear interpolation to resample the digital terrain model data into a digital terrain model data (DEM) with a spatial resolution of R. R ;

[0017] The first instantaneous surface temperature field Bt0 of the target satellite image is subjected to sub-pixel decomposition and enhancement of the digital image to obtain the first instantaneous surface temperature field B with spatial resolution R. Rt0 ;

[0018] Using digital terrain model data (DEM) with spatial resolution R RCalculate the aspect data ASP, set a 3*3 sliding window, and determine the digital terrain model (DEM) data with a spatial resolution of R. R The maximum elevation difference Δele and aspect difference Δasp of the pixels within the window;

[0019] Based on the maximum elevation difference Δele and the aspect difference Δasp, the first instantaneous surface temperature field B with spatial resolution R is analyzed according to the temperature change rules of elevation and aspect. Rt0 After interpolation correction, the second instantaneous surface temperature field C with spatial resolution R is obtained. t0 .

[0020] Optional, temperature variation rules based on elevation and aspect, specifically including: a 100 m elevation difference corresponds to a 0.6℃ temperature change; a 10° aspect change corresponds to a 0.001℃ temperature change; and the first instantaneous surface temperature field B with spatial resolution R. Rt0 The expression for interpolation correction is as follows:

[0021] C t0 =B Rt0 +Δele×0.6+Δasp×0.001.

[0022] Optionally, based on the instantaneous surface temperature baseline field and the second instantaneous surface temperature field, a sub-pixel thermal increment image is calculated, and a false-color image synthesis step is performed using the sub-pixel thermal increment image, the first band image and the second band image from the target satellite image, specifically including:

[0023] The instantaneous surface temperature baseline field A t0 With the second instantaneous surface temperature field C t0 Perform interpolation to obtain the sub-pixel thermal increment image; the expression for the thermal increment ΔT of each sub-pixel is as follows:

[0024] ΔT = C t0 -A t0 ;

[0025] Near-infrared spectral images are read from target satellite images as the first band image G_Nir, and red light or other visible light band images are read as the second band image G_Red;

[0026] The digital image is decomposed into sub-pixel values ​​and enhanced at a spatial resolution of R. The first-band image G_Nir and the second-band image G_Red are resampled to generate images G_Nir_R and G_Red_R with a resolution of R. False-color image synthesis is performed using the RGB color mapping mode composed of ΔT, G_Nir_R, and G_Red_R to obtain the synthesized false-color image.

[0027] Optionally, the sub-pixel thermal increment image is configured as the red channel, the image G_Nir_R is configured as the green channel, and the image G_Red_R is configured as the blue channel; the step of generating a weak forest and grassland fire alarm signal based on the pixel information in the synthesized false-color image specifically includes: determining whether there are red spot pixels in the synthesized false-color image, and if so, generating a weak forest and grassland fire alarm signal based on the location information of the red spot pixels.

[0028] Furthermore, to achieve the above objectives, the present invention also provides a weak forest and grassland fire alarm device, comprising:

[0029] The calculation module is used to acquire target satellite images and, based on the imaging time of the target satellite images and the target spatial resolution of the predefined sub-pixel decomposition, calculate the instantaneous surface temperature baseline field that is simultaneous with the target satellite images and satisfies the spatial resolution.

[0030] The inversion module is used to read the thermal infrared spectral data of the target satellite image and use the thermal infrared spectral data to invert and obtain the first instantaneous surface temperature field of the target satellite image;

[0031] The conversion module is used to convert the first instantaneous surface temperature field into a second instantaneous surface temperature field with higher resolution by using sub-pixel decomposition and interpolation.

[0032] The synthesis module is used to calculate and obtain a sub-pixel thermal increment image based on the instantaneous surface temperature baseline field and the second instantaneous surface temperature field, and to perform false-color image synthesis using the sub-pixel thermal increment image, the first band image and the second band image in the target satellite image;

[0033] The alarm module is used to generate a weak forest and grassland fire alarm signal based on the pixel information in the synthesized false-color image.

[0034] In addition, to achieve the above objectives, the present invention also provides a weak forest and grassland fire alarm device, which includes: a memory, a processor, and a weak forest and grassland fire alarm program stored in the memory and executable on the processor. When the weak forest and grassland fire alarm program is executed by the processor, it implements the steps of the weak forest and grassland fire alarm method as described above.

[0035] In addition, to achieve the above objectives, the present invention also provides a storage medium storing a weak forest and grassland fire alarm program, which, when executed by a processor, implements the steps of the weak forest and grassland fire alarm method described above.

[0036] The beneficial effects of this invention are as follows: It proposes a method, device, equipment, and storage medium for weak forest and grassland fire alarm. Based on the imaging time of the target satellite image and the target spatial resolution of the predefined sub-pixel decomposition, the instantaneous surface temperature baseline field in the target satellite image that is synchronized with the remote sensing time and meets the spatial resolution is calculated. The thermal infrared spectrum data of the target satellite image is read, the first instantaneous surface temperature field of the target satellite image is obtained by inversion, and it is converted into a second instantaneous surface temperature field with higher resolution. Based on the instantaneous temperature baseline field and the second instantaneous surface temperature field, the sub-pixel thermal increment image is calculated. The first band image and the second band image in the target satellite image are used to perform false color image synthesis to generate a weak forest and grassland fire alarm signal. Therefore, a method for rapidly identifying initial and small forest and grassland fires using incremental thermal radiation images is proposed. By constructing a ground instantaneous thermal radiation brightness temperature baseline field synchronized with remote sensing, and using this as a benchmark to simulate and reconstruct sub-pixel incremental thermal images, early forest fires can be characterized and identified based on the characteristics of abrupt changes in thermal increments and the thermal steady-state characteristics of forest and grassland distribution areas. This method can identify weak fire points that are not easily detected within a single pixel of meteorological satellites such as MODIS, effectively improving the monitoring efficiency and accuracy of fire points and enhancing the technological level of forest fire monitoring. Attached Figure Description

[0037] Figure 1 This is a schematic diagram of the device structure of the hardware operating environment involved in the embodiments of the present invention;

[0038] Figure 2 This is a flowchart illustrating an embodiment of the weak forest and grassland fire alarm method of the present invention;

[0039] Figure 3 A schematic diagram of the instantaneous temperature field in the Himalayas and the Tibetan Plateau at a scale of 10m;

[0040] Figure 4 The instantaneous surface temperature field at 1000m obtained from MODIS inversion;

[0041] Figure 5 A schematic diagram of the initial ignition with weak heating, representing a sub-pixel thermal increment image;

[0042] Figure 6 This is a schematic diagram comparing the effects of the present invention with those of the prior art;

[0043] Figure 7 This is a structural block diagram of a weak forest and grassland fire alarm device according to an embodiment of the present invention. Detailed Implementation

[0044] It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.

[0045] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0046] like Figure 1 As shown, Figure 1 This is a schematic diagram of the device structure of the hardware operating environment involved in the embodiments of the present invention.

[0047] like Figure 1 As shown, the device may include: a processor 1001, such as a CPU; a communication bus 1002; a user interface 1003; a network interface 1004; and a memory 1005. The communication bus 1002 is used to enable communication between these components. The user interface 1003 may include a display screen or an input unit such as a keyboard; optionally, the user interface 1003 may also include a standard wired interface or a wireless interface. The network interface 1004 may optionally include a standard wired interface or a wireless interface (such as a Wi-Fi interface). The memory 1005 may be high-speed RAM or non-volatile memory, such as a disk drive. Optionally, the memory 1005 may also be a storage device independent of the aforementioned processor 1001.

[0048] Those skilled in the art will understand that Figure 1 The structure of the device shown does not constitute a limitation on the device and may include more or fewer components than shown, or combine certain components, or have different component arrangements.

[0049] like Figure 1 As shown, the memory 1005, which serves as a computer storage medium, may include an operating system, a network communication module, a user interface module, and a low-level forest and grassland fire alarm program.

[0050] exist Figure 1 In the terminal shown, network interface 1004 is mainly used to connect to the backend server and communicate with it; user interface 1003 is mainly used to connect to the client (user terminal) and communicate with it; while processor 1001 can be used to call the weak forest and grassland fire alarm program stored in memory 1005 and perform the following operations:

[0051] Acquire a target satellite image, and calculate the instantaneous surface temperature baseline field that is simultaneous with the target satellite image and satisfies the spatial resolution based on the imaging time of the target satellite image and the predefined sub-pixel decomposition target spatial resolution.

[0052] Read the thermal infrared spectral data of the target satellite image, and use the thermal infrared spectral data to invert and obtain the first instantaneous surface temperature field of the target satellite image;

[0053] The first instantaneous surface temperature field is converted into a second instantaneous surface temperature field with higher resolution by using sub-pixel decomposition and interpolation.

[0054] Based on the instantaneous surface temperature baseline field and the second instantaneous surface temperature field, a sub-pixel thermal increment image is calculated, and a false-color image is synthesized using the sub-pixel thermal increment image, the first band image and the second band image in the target satellite image;

[0055] A weak forest and grassland fire alarm signal is generated based on the pixel information in the synthesized false-color image.

[0056] The specific embodiments of the present invention applied to the device are basically the same as the embodiments of the application of the weak forest and grassland fire alarm method described below, and will not be repeated here.

[0057] This invention provides a method for alarming weak forest and grassland fires, referring to... Figure 2 , Figure 2 This is a flowchart illustrating an embodiment of the weak forest and grassland fire alarm method of the present invention.

[0058] In this embodiment, a method for alarming weak forest and grassland fires includes the following steps:

[0059] S100: Acquire a target satellite image, and calculate the instantaneous surface temperature baseline field that is simultaneous with the target satellite image and satisfies the spatial resolution based on the imaging time of the target satellite image and the predefined sub-pixel decomposition target spatial resolution.

[0060] S200: Read the thermal infrared spectral data of the target satellite image, and use the thermal infrared spectral data to retrieve the first instantaneous surface temperature field of the target satellite image;

[0061] S300: The first instantaneous surface temperature field is converted into a second instantaneous surface temperature field with higher resolution by using sub-pixel decomposition and interpolation.

[0062] S400: Based on the instantaneous surface temperature baseline field and the second instantaneous surface temperature field, calculate the sub-pixel thermal increment image, and use the sub-pixel thermal increment image, the first band image and the second band image in the target satellite image to perform false color image synthesis;

[0063] S500: Generates a weak forest and grassland fire alarm signal based on pixel information in the synthesized false-color image.

[0064] In a preferred embodiment, the step of acquiring a target satellite image and calculating the instantaneous surface temperature baseline field that is simultaneous with the target satellite image and satisfies the spatial resolution based on the imaging time of the target satellite image and the predefined sub-pixel decomposition target spatial resolution specifically includes:

[0065] S110: Acquire the target satellite image, read the imaging time interval t0 from the header file of the target satellite image, and predefine the target spatial resolution R of sub-pixel decomposition;

[0066] S120: Decompose and enhance the sub-pixels of the target satellite image, convert its spatial resolution to R, and then construct an instantaneous surface temperature baseline field A with imaging time t0 synchronized with imaging time t0 and spatial resolution R based on the converted sub-pixels of the target satellite image and the imaging time t0 read from the header file. t0 .

[0067] In a preferred embodiment, the step of reading the thermal infrared spectral data of the target satellite image and using the thermal infrared spectral data to invert and obtain the first instantaneous surface temperature field of the target satellite image specifically includes: reading the thermal infrared spectral data of the target satellite image, and using the thermal infrared spectral data based on Planck's law and the single-wavelength brightness temperature correction method to invert and obtain the first instantaneous surface temperature field B of the target satellite image. t0 .

[0068] In a preferred embodiment, the step of converting the first instantaneous surface temperature field into a second instantaneous surface temperature field with higher resolution using sub-pixel decomposition and interpolation specifically includes:

[0069] S310: Acquire digital terrain model data and resample the digital terrain model data into a digital terrain model (DEM) with a spatial resolution of R using GIS bilinear interpolation. R ;

[0070] S320: The first instantaneous surface temperature field B of the target satellite image t0 Sub-pixel decomposition and enhancement of the digital image are performed to obtain the first instantaneous surface temperature field B with spatial resolution R. Rt0 ;

[0071] S330: Utilizing Digital Terrain Model (DEM) data with spatial resolution R R Calculate the aspect data ASP, set a 3*3 sliding window, and determine the digital terrain model (DEM) data with a spatial resolution of R. R The maximum elevation difference Δele and aspect difference Δasp of the pixels within the window;

[0072] S340: Based on the maximum elevation difference Δele and aspect difference Δasp, the first instantaneous surface temperature field B with spatial resolution R is analyzed according to the temperature change rules of elevation and aspect. Rt0 After interpolation correction, the second instantaneous surface temperature field C with spatial resolution R is obtained. t0 .

[0073] In a preferred embodiment, the temperature variation rules based on altitude and slope aspect specifically include: a 100m change in altitude corresponds to a 0.6℃ temperature change; a 10° change in slope aspect corresponds to a 0.001℃ temperature change; and the first instantaneous surface temperature field B with spatial resolution R... Rt0 The expression for interpolation correction is as follows:

[0074] C t0 =B Rt0 +Δele×0.6+Δasp×0.001.

[0075] In a preferred embodiment, a sub-pixel thermal increment image is calculated based on the instantaneous surface temperature baseline field and the second instantaneous surface temperature field. A false-color image synthesis step is then performed using the sub-pixel thermal increment image, a first-band image from the target satellite image, and a second-band image. This step specifically includes:

[0076] S410: The instantaneous surface temperature baseline field A t0 With the second instantaneous surface temperature field C t0 Perform interpolation to obtain the sub-pixel thermal increment image; the expression for the thermal increment ΔT of each sub-pixel is as follows:

[0077] ΔT = C t0 -A t0 ;

[0078] S420: Read near-infrared spectral images from target satellite images as the first-band image G_Nir, and read red light or other visible light band images as the second-band image G_Red;

[0079] S430: Perform sub-pixel decomposition and enhancement of digital images with a spatial resolution of R. Resample the first band image G_Nir and the second band image G_Red to generate images G_Nir_R and G_Red_R with a resolution of R. Use the RGB color mapping mode composed of ΔT, G_Nir_R, and G_Red_R to perform false color image synthesis to obtain the synthesized false color image.

[0080] In a preferred embodiment, the sub-pixel thermal increment image is configured as the red channel, the image G_Nir_R is configured as the green channel, and the image G_Red_R is configured as the blue channel; the step of generating a weak forest and grassland fire alarm signal based on the pixel information in the synthesized false-color image specifically includes: determining whether there are red spot pixels in the synthesized false-color image; if so, generating a weak forest and grassland fire alarm signal based on the location information of the red spot pixels.

[0081] To more clearly explain this application, specific examples of weak forest and grassland fire alarms are provided below:

[0082] Step 1: Data Acquisition

[0083] Download the BIO1 product from the WorldClim version 2 global climate and meteorological dataset at https: / / worldclim.org to obtain global annual average temperature data with a spatial resolution of 1 km. After cropping, extract multi-year annual average temperature data for a specific location. Download the 12 m spatial resolution ALOS DEM digital terrain model for the location from the geospatial data cloud website. Download MODIS remote sensing imagery of the region at the target time.

[0084] Step 2: Computer simulation and representation of instantaneous surface temperature field data synchronized with optical satellites to form surface temperature baseline field data:

[0085] The target time is read from the MODIS satellite image header file. The surface temperature baseline field at the target time is calculated using the authorized invention patent "A Method for Constructing a Temporal Baseline of a Surface Temperature Field (Patent No.: ZL 202011327172.1)", with a spatial resolution of 1 km. The predefined target spatial resolution for sub-pixel decomposition is 10 m. The surface temperature baseline field with a 1 km spatial resolution is decomposed into a 10 m surface temperature baseline field using the sub-pixel decomposition method of "A Sub-pixel Decomposition and Enhancement Method for Digital Images (Patent No.: ZL200710066071.1)". Figure 3 As shown.

[0086] Step 3: Calculate the instantaneous surface temperature field using satellite thermal infrared spectral data:

[0087] Using MODIS imagery in band 7 as the primary data, and based on Planck's law, the instantaneous surface temperature field of MODIS was retrieved using a known single-wavelength brightness temperature correction method. This data has a spatial resolution of 1 km. Figure 4 As shown.

[0088] The instantaneous surface temperature field at 1 km resolution was decomposed into sub-pixel values ​​and interpolated to obtain an instantaneous surface temperature field at 10 m resolution. First, ALOS-12 m topographic data at 12 m resolution was obtained. The ALOS DEM was resampled to a spatial resolution of 10 m using conventional GIS bilinear interpolation. Second, using the aforementioned instantaneous surface temperature field at 1000 m resolution as input data, the instantaneous surface temperature field at 1 km resolution was decomposed into a spatial resolution of 10 m using a method for decomposing and enhancing sub-pixel values ​​of digital images (patent number: ZL200710066071.1). Third, slope aspect grids were extracted from the 10 m spatial resolution DEM data, and a 3×3 (or 5×5 or 7×7) sliding window was set to calculate the maximum elevation difference and slope aspect difference data of the pixels within the window. Finally, the data was calculated based on an elevation difference of 100 m and a temperature difference of 0.6 m. The rule is that for every 10° change in slope aspect, the temperature changes by 0.001°. The instantaneous surface temperature field with a spatial resolution of 10m is then subjected to a grid addition operation with a grid multiplied by 0.6 for elevation difference and 0.001 for slope aspect difference, to obtain the interpolated and corrected instantaneous surface temperature field with a spatial resolution of 10m.

[0089] Step 4: Calculate the sub-pixel thermal increment image:

[0090] The difference between the interpolated instantaneous surface temperature field and the 10 m surface temperature baseline field is calculated to obtain a sub-pixel thermal increment image. The image is then mapped using red-to-blue symbols, arranged from highest to lowest increment size, following the conventional GIS natural breakpoint method. The result is shown below. Figure 5 As shown, the red spots in the image represent weak fire, and the sub-pixel thermal increment image represents the initial ignition with weak heating, compared to... Figure 4 In comparison, 17 small fires were rediscovered.

[0091] Step 5: Sub-pixel thermal increment color synthesis:

[0092] Using the first and second bands of the concurrent MODIS satellite imagery as input, the images of the first and second bands were resampled using a method for sub-pixel decomposition and enhancement of digital images (patent number: ZL200710066071.1), generating images with a resolution of 10 m. Using the sub-pixel thermal increment image as the red channel, the first band after sub-pixel decomposition as the green channel, and the second band after sub-pixel decomposition as the blue channel, a false-color image was synthesized using an RGB color synthesis mode. The red spots then represent ground-level forest and grassland fires. Figure 6 As shown, compared with existing technologies, the top left and middle images are from the Southern Satellite Center system; the bottom left and right images are from weak fire monitoring, with white circles indicating newly added weak fires identified by this technology.

[0093] In this embodiment, a novel method for identifying "low-temperature forest fires" is based on the ground temperature field baseline and utilizes pixel temperature increment and pattern change characterization. Compared to high-temperature heat sources and other strongly reflective or high-radiation ground features, only ground features with "fire" characteristics (including clouds) experience sudden warming or changes in temperature patterns. Other features such as bare rock, urban heat islands, beaches, canyons, and industrial heat sources remain constant on the ground, regardless of their temperature. Therefore, by comparing temperature fields, sudden "fires" can be identified, with the ground temperature field baseline serving as the best benchmark. In fact, the ground temperature field baseline depicts the average temperature and spatial pattern relationships of various ground features. It is the result of the combined effects and characterization of factors such as altitude, slope, aspect, longitude, latitude, and the thermal radiation characteristics of ground features, and is also influenced by atmospheric medium and airflow, solar thermal radiation, etc. Assuming no abrupt changes in terrain features (unless there are earthquakes or large-scale land reclamation projects) and no surface fires, the spatial pattern of surface temperature is statistically steady-state. Classical studies also show that vertical lapse rate, horizontal lapse rate, and aspect effect rate are variables that characterize the stability of spatial patterns. Under the influence of atmospheric circulation and solar radiation, the warming and cooling patterns at each pixel are consistent, but the steady-state variables, such as the vertical and horizontal lapse rates, remain almost unchanged.

[0094] In practical applications, assuming that the ground (instantaneous) thermal radiation temperature field A obtained by remote sensing is statistically consistent with the instantaneous (remote sensing) baseline field B, a suitable function F can be found through individual calibration points such that F(A) = B. In other words, the information represented by F(A) - B is the amount of change in thermal radiation brightness temperature with a significant increment or spatial pattern. Excluding noise, the point of change expressed by F(A) - B is the fire point. Therefore, the main task of this invention is to identify weak fires by utilizing the relative change indicators and characteristics of brightness temperature in the spatial or frequency domains. This is a pioneering work with significant theoretical and practical value. By constructing a ground instantaneous thermal radiation brightness temperature baseline field synchronized with remote sensing, and using this as a benchmark to simulate and reconstruct sub-pixel thermal increment images, based on the characteristics of abrupt changes in thermal increment and the thermal steady-state characteristics of forest and grassland distribution areas, early forest fires can be characterized and identified. This enables the identification of weak fire points that are difficult to detect within a single pixel of meteorological satellites such as MODIS, effectively improving the monitoring efficiency and accuracy of fire points and enhancing the technological level of forest fire monitoring.

[0095] Therefore, this invention takes a different approach, breaking through the limitations of existing theoretical methods and technical paradigms in remote sensing image processing. It proposes a theoretical method for reconstructing sub-pixel thermal increment remote sensing images, which is used to characterize weak forest and grassland fires with abrupt changes in spatiotemporal patterns. This increases the identifiability of weak wildfires from below 15% to over 85%. It can significantly reduce the construction and maintenance investment in ground-based monitoring, such as manual patrols and lookout observations, ground visible light video and thermal infrared monitoring, large aircraft and near-ground UAV inspections, thermal sensing IoT detection, and network transmission.

[0096] Reference Figure 7 , Figure 7 This is a structural block diagram of an embodiment of the weak forest and grassland fire alarm device of the present invention.

[0097] like Figure 7 As shown, the weak forest and grassland fire alarm device proposed in this embodiment of the invention includes:

[0098] The calculation module 10 is used to acquire a target satellite image and, based on the imaging time of the target satellite image and the target spatial resolution of the predefined sub-pixel decomposition, calculate the instantaneous surface temperature baseline field that is simultaneous with the target satellite image and satisfies the spatial resolution.

[0099] Inversion module 20 is used to read the thermal infrared spectral data of the target satellite image and use the thermal infrared spectral data to invert and obtain the first instantaneous surface temperature field of the target satellite image;

[0100] The conversion module 30 is used to convert the first instantaneous surface temperature field into a second instantaneous surface temperature field with higher resolution by using sub-pixel decomposition and interpolation.

[0101] The synthesis module 40 is used to calculate and obtain a sub-pixel thermal increment image based on the instantaneous surface temperature baseline field and the second instantaneous surface temperature field, and to perform false color image synthesis using the sub-pixel thermal increment image, the first band image and the second band image in the target satellite image;

[0102] The alarm module 50 is used to generate a weak forest and grassland fire alarm signal based on the pixel information in the synthesized false color image.

[0103] Other embodiments or specific implementations of the weak forest and grassland fire alarm device of the present invention can be referred to the above-described method embodiments, and will not be repeated here.

[0104] Furthermore, the present invention also proposes a weak forest and grassland fire alarm device, which includes: a memory, a processor, and a weak forest and grassland fire alarm program stored in the memory and executable on the processor. When the weak forest and grassland fire alarm program is executed by the processor, it implements the steps of the weak forest and grassland fire alarm method described above.

[0105] The specific implementation method of the weak forest and grassland fire alarm device in this application is basically the same as the embodiments of the weak forest and grassland fire alarm method described above, and will not be repeated here.

[0106] Furthermore, this invention also proposes a readable storage medium, which includes a computer-readable storage medium storing a weak forest and grassland fire alarm program thereon. The readable storage medium may be... Figure 1 The memory 1005 in the terminal can also be at least one of ROM (Read-Only Memory) / RAM (Random Access Memory), magnetic disk, optical disk, etc. The readable storage medium includes several instructions to cause a weak forest and grassland fire alarm device with a processor to execute the weak forest and grassland fire alarm method described in various embodiments of the present invention.

[0107] The specific implementation methods in the readable storage medium of this application are basically the same as those in the above-described embodiments of the weak forest and grassland fire alarm method, and will not be repeated here.

[0108] It is understood that in the description of this specification, references to terms such as "one embodiment," "another embodiment," "other embodiments," or "first embodiment to Nth embodiment," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the present invention. In this specification, illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0109] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or system that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or system. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or system that includes that element.

[0110] The sequence numbers of the above embodiments of the present invention are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.

[0111] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods of the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) as described above, and includes several instructions to cause a terminal device (which may be a mobile phone, computer, server, or network device, etc.) to execute the methods described in the various embodiments of the present invention.

[0112] The above are merely preferred embodiments of the present invention and do not limit the scope of the patent. Any equivalent structural or procedural transformations made based on the description and drawings of the present invention, or direct or indirect applications in other related technical fields, are similarly included within the scope of patent protection of the present invention.

Claims

1. A method for alarming weak forest and grassland fires, characterized in that, The method comprises the following steps: Obtaining a target satellite image, calculating a baseline field of instantaneous land surface temperature at the same time as the target satellite image and meeting a target spatial resolution of sub-pixel resolution according to an imaging time of the target satellite image and the target spatial resolution of sub-pixel resolution; specifically comprising: Obtaining a target satellite image, reading an imaging time t0 from a header file of the target satellite image, and predefining a target spatial resolution of sub-pixel resolution R; The sub-pixels of the target satellite image are decomposed and enhanced, and the spatial resolution thereof is converted into R, and then based on the converted sub-pixels of the target satellite image and the imaging time scale t0 read from the header file, a baseline field A of the instantaneous ground surface temperature with the imaging time scale t0 synchronized and the spatial resolution of R is constructed t0 ; Reading thermal infrared spectral data of the target satellite image, and inversely obtaining a first instantaneous land surface temperature field of the target satellite image by using the thermal infrared spectral data; Converting the first instantaneous land surface temperature field into a second instantaneous land surface temperature field with higher resolution by using the sub-pixel resolution and difference value; Based on the baseline field of instantaneous land surface temperature and the second instantaneous land surface temperature field, a sub-pixel thermal increment image is calculated, and false color image synthesis is performed by using the sub-pixel thermal increment image, a first band image and a second band image in the target satellite image; specifically comprising: The instantaneous surface temperature baseline field A t0 The second instantaneous surface temperature field C t0 The difference operation is performed to obtain a sub-pixel thermal increment image; wherein, the expression of each sub-pixel thermal increment ΔT is specifically: ΔT = C t0 - A t0 ; Reading a near-infrared spectral image from the target satellite image as a first band image G_Nir, and reading a red light or other visible light band image as a second band image G_Red; Resampling the first band image G_Nir and the second band image G_Red by sub-pixel resolution and enhancement of digital images according to the size of the spatial resolution R, to generate images G_Nir_R and G_Red_R with a resolution of R, and performing false color image synthesis by using the RGB color mapping mode composed of ΔT, G_Nir_R and G_Red_R to obtain a synthesized false color image; According to the pixel information in the synthesized false color image, a weak forest fire alarm signal is generated; Wherein, the sub-pixel thermal increment image is configured as a red channel, the image G_Nir_R is configured as a green channel, and the image G_Red_R is configured as a blue channel; according to the pixel information in the synthesized false color image, the weak forest fire alarm signal is generated, specifically comprising: judging whether there is a red spot pixel in the synthesized false color image, if yes, generating a weak forest fire alarm signal based on the position information of the red spot pixel.

2. The method of claim 1, wherein the step of detecting a fire in the young forest is performed by a fire detection device. The step of reading the thermal infrared spectral data of the target satellite image and inversely obtaining the first instantaneous land surface temperature field Bt0 of the target satellite image by using the thermal infrared spectral data comprises: reading the thermal infrared spectral data of the target satellite image, and inversely obtaining the first instantaneous land surface temperature field Bt0 of the target satellite image by using the thermal infrared spectral data based on Planck's law and single-wavelength brightness temperature correction method.

3. The method of claim 2, wherein the step of detecting a fire in the young forest is performed by a fire detection device. The step of converting the first instantaneous land surface temperature field into a second instantaneous land surface temperature field with higher resolution by using the sub-pixel resolution and difference value comprises: obtaining digital terrain model data, resampling the digital terrain model data to digital terrain model data DEM with a spatial resolution of R using a GIS bilinear interpolation method R ; The first instantaneous land surface temperature field Bt0 of the target satellite image is sub-pixel decomposed and enhanced to obtain a first instantaneous land surface temperature field B Rt0 ; using a digital terrain model data DEM having a spatial resolution R R , calculating aspect data ASP, setting a 3*3 sliding window, determining a maximum elevation difference Dele and an aspect difference DasP of in-window pixels of the digital terrain model data DEM having a spatial resolution R R ; Based on the maximum elevation difference Δele and the aspect difference Δasp, the first instantaneous land surface temperature field B with a spatial resolution of R is corrected according to the temperature variation rules of elevation and aspect Rt0 An interpolation correction is performed to obtain the second instantaneous land surface temperature field C with a spatial resolution of R t0 .

4. The method of claim 3, wherein the step of detecting a fire in the young forest is performed by a fire detection device. The temperature variation rules of altitude and slope direction include: an altitude difference variation of 100 m and a temperature variation of 0.6 DEG C; a slope direction variation of 10 DEG and a temperature variation of 0.001 DEG C; and a first instantaneous ground temperature field B with a spatial resolution of R Rt0 The expression for interpolation correction is: C t0 =B Rt0 + Δele x 0.6 + Δasp x 0.

001.

5. A forest fire alarm device for low intensity grass fires, characterized in that The method comprises the following steps: The calculation module is configured to obtain a target satellite image, calculate a baseline field of instantaneous land surface temperature at the same time as the target satellite image and meeting a spatial resolution of sub-pixel resolution according to an imaging time of the target satellite image and the target spatial resolution of sub-pixel resolution; specifically comprising: acquire a target satellite image, read an imaging time scale t0 from a header file of the target satellite image, and predefine a target spatial resolution R of sub-pixel resolution; The sub-pixels of the target satellite image are decomposed and enhanced, and the spatial resolution thereof is converted into R, and then based on the converted sub-pixels of the target satellite image and the imaging time scale t0 read from the header file, a baseline field A of the instantaneous ground surface temperature with the imaging time scale t0 synchronized and the spatial resolution of R is constructed t0 ; an inversion module configured to read thermal infrared spectrum data of the target satellite image, and obtain a first instantaneous land surface temperature field of the target satellite image by inversion using the thermal infrared spectrum data; a conversion module configured to convert the first instantaneous land surface temperature field into a second instantaneous land surface temperature field with higher resolution by means of sub-pixel resolution and difference; a synthesis module configured to calculate a sub-pixel heat increment image based on the instantaneous land surface temperature baseline field and the second instantaneous land surface temperature field, and perform false color image synthesis using the sub-pixel heat increment image, a first band image and a second band image in the target satellite image; specifically including: The instantaneous surface temperature baseline field A t0 The second instantaneous surface temperature field C t0 The difference operation is performed to obtain a sub-pixel thermal increment image; wherein, the expression of each sub-pixel thermal increment ΔT is specifically: ΔT = C t0 - A t0 ; reading a near-infrared spectrum image from the target satellite image as the first band image G_Nir, and reading a red light or other visible light band image as the second band image G_Red; resampling the first band image G_Nir and the second band image G_Red by sub-pixel resolution and enhancement of digital images with a size of R spatial resolution to generate images G_Nir_R and G_Red_R with a resolution of R, and performing false color image synthesis using a RGB color mapping mode composed of ΔT, G_Nir_R and G_Red_R to obtain a synthesized false color image; an alarm module configured to generate a weak degree forest and grass fire alarm signal according to pixel information in the synthesized false color image; wherein the sub-pixel heat increment image is configured as a red channel, the image G_Nir_R is configured as a green channel, and the image G_Red_R is configured as a blue channel; the weak degree forest and grass fire alarm signal is generated according to pixel information in the synthesized false color image, specifically including: judging whether there is a red spot pixel in the synthesized false color image, and if yes, generating the weak degree forest and grass fire alarm signal based on position information of the red spot pixel.

6. A light forest grass fire alarm device characterized by comprising: The weak degree forest and grass fire alarm device includes a memory, a processor, and a weak degree forest and grass fire alarm program stored on the memory and executable on the processor, and the weak degree forest and grass fire alarm program implements the steps of the weak degree forest and grass fire alarm method in any one of claims 1 to 4 when executed by the processor.

7. A storage medium, characterized by The storage medium stores a weak degree forest and grass fire alarm program, and the weak degree forest and grass fire alarm program implements the steps of the weak degree forest and grass fire alarm method in any one of claims 1 to 4 when executed by the processor.

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