CN112686861A - Land utilization change remote sensing monitoring analysis method and device and intelligent terminal - Google Patents
Land utilization change remote sensing monitoring analysis method and device and intelligent terminal Download PDFInfo
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Abstract
The application relates to a method and a device for monitoring and analyzing land utilization change by remote sensing and an intelligent terminal. The method comprises the steps of obtaining remote sensing images of a place to be researched n years ago and n years later; carrying out image processing on the remote sensing images of the place to be researched n years ago and the place to be researched n years later so as to enable the remote sensing images of the place to be researched n years ago and the place to be researched n years later to be easier to compare; comparing the remote sensing images of the place to be researched n years ago and the place to be researched n years later to obtain a comparison result, wherein the comparison result comprises a plurality of kinds of change information; judging the development trend of the to-be-researched area according to the comparison result; and recommending the building layout of the ground to be researched according to the development trend. The method has the advantages of providing theoretical basis for city construction and building layout, and having scientific effect on city development or building layout.
Description
Technical Field
The application relates to the field of remote sensing technology, in particular to a method and a device for monitoring and analyzing land utilization change by remote sensing and an intelligent terminal.
Background
In recent years, by developing the national land change survey monitoring and remote sensing monitoring checking work, the annual land utilization change conditions of a plurality of provinces of the country are comprehensively mastered, and the change conditions are updated to land survey databases in various regions and a land resource comprehensive information supervision platform, so that the present situation of the national land survey data is maintained.
The current urban development or building layout lacks certain basis, which leads to the lack of scientific basis for urban building arrangement.
Disclosure of Invention
In order to enable the urban development or the building layout to be more scientific, the application provides a method and a device for remote sensing monitoring and analyzing of land utilization change and an intelligent terminal.
In a first aspect, the remote sensing monitoring and analyzing method for land utilization change provided by the application adopts the following technical scheme: a land utilization change remote sensing monitoring and analyzing method comprises the following steps:
acquiring remote sensing images of a place to be researched n years ago and n years after the place to be researched;
carrying out image processing on the remote sensing images of the place to be researched n years ago and the place to be researched n years later so as to enable the remote sensing images of the place to be researched n years ago and the place to be researched n years later to be easier to compare;
comparing the remote sensing images of the place to be researched n years ago and the place to be researched n years later to obtain a comparison result, wherein the comparison result comprises a plurality of kinds of change information;
judging the development trend of the to-be-researched area according to the comparison result;
and according to the development trend, carrying out building layout on the ground to be researched.
By adopting the technical scheme, the remote sensing images before and after the ground to be researched are obtained, the remote sensing images are subjected to image processing, the remote sensing images are clearer and easier to compare, the land utilization change of the ground to be researched is judged by comparing the remote sensing images, so that the economic development condition, namely the development trend, of the ground to be researched is judged, the buildings of the ground to be researched are distributed according to the speed of the development trend, and the remote sensing monitoring images are compared by time sequence association and spatial position association to perform multi-dimensional comprehensive correlation analysis by combining with business data of the industries such as China soil, statistics, traffic, water conservancy and the like, so that the urban development or building layout is more scientific.
The present invention in a preferred example may be further configured to: the image processing comprises cloud haze processing, the method comprising:
acquiring a two-dimensional function f (x, y) of the remote sensing image;
according to the two-dimensional function f (x, y), obtaining a function influencing the definition of the remote sensing image;
and reducing the function value influencing the definition of the remote sensing image so as to enable the remote sensing image to be clearer.
By adopting the technical scheme, the factors influencing the definition of the remote sensing image are obtained by obtaining the two-dimensional function of the remote sensing image, the influencing factors are controlled and adjusted according to the influencing factors, the influencing degree of the influencing factors is reduced, the remote sensing image is clearer and is easier to compare.
The present invention in a preferred example may be further configured to: the image processing comprises image contrast enhancement, the method comprising:
acquiring a correction value of the remote sensing image;
correcting the remote sensing image according to the correction value so as to eliminate errors caused by atmospheric radiation influence of the remote sensing image; and acquiring the corrected remote sensing image, and checking a correction result.
By adopting the technical scheme, the remote sensing image is obtained through the satellite, the atmospheric radiation has certain influence on the remote sensing image, the correction value of the influence of the atmospheric radiation on the remote sensing image is obtained, the remote sensing image is corrected according to the correction value, the corrected remote sensing image is obtained, whether the correction result is in accordance with the expectation or not is checked according to the degree of influence of the atmospheric radiation on the remote sensing image, and the influence of the atmospheric radiation on the remote sensing image is eliminated so as to facilitate further comparison.
The present invention in a preferred example may be further configured to: and if the correction result does not reach the expectation, re-processing by using a regression analysis method until the correction result reaches the expectation.
By adopting the technical scheme, the remote sensing image is processed again by utilizing the rule that the near infrared and infrared wave bands are slightly influenced by the atmosphere through a regression analysis method, so that the influence of atmospheric radiation on the remote sensing image is further reduced, and comparison is facilitated.
The present invention in a preferred example may be further configured to: the step of judging the development trend of the to-be-researched area according to the comparison result comprises the following steps:
obtaining a relational expression between the comparison result and the development trend;
judging the development trend of the to-be-researched area according to the relational expression;
if the comparison result shows that the land utilization rate of the land to be researched is increased, judging that the land to be researched is in a development state;
if the comparison result shows that the land utilization rate of the land to be researched is not changed, judging that the land to be researched is in a stagnation state;
and if the comparison result shows that the land utilization rate of the land to be researched is reduced, judging that the land to be researched is in a reverse state.
By adopting the technical scheme, the relational expression between the comparison result and the development trend is obtained, and the development trend of the to-be-researched land is judged according to the relational expression and the comparison result, so that a theoretical basis is provided for the building layout of the to-be-researched land.
The present invention in a preferred example may be further configured to: the building layout of the ground to be researched according to the development trend comprises the following steps:
acquiring the attribute of the place to be researched, wherein the attribute is used for describing the future development direction of the place to be researched;
and monitoring and analyzing the place to be researched according to the development trend and the attribute of the place to be researched.
By adopting the technical scheme, the attributes of the places to be researched are obtained, and monitoring recommendation is carried out on the places to be researched by combining the development trend, so that the monitoring of the places to be researched has more scientific basis.
The present invention in a preferred example may be further configured to: according to the n years, further supplementing the relational expression to obtain the supplemented relational expression;
and judging the development speed of the to-be-researched area according to the supplemented relational expression.
By adopting the technical scheme, the relational expression is further supplemented according to the comparison of the remote sensing images of the places to be researched among n years and the years, the development speed of the places to be researched is judged according to the time attribute, and the scientificity of the building layout suggestion is further improved.
In a second aspect, the remote sensing monitoring and analyzing device for land utilization change provided by the application adopts the following technical scheme: a land utilization change remote sensing monitoring and analyzing device comprises:
the acquisition module is used for acquiring remote sensing images of a place to be researched n years ago and n years later;
the image processing module is used for carrying out image processing on the remote sensing images of the place to be researched n years ago and the place to be researched n years later so as to enable the remote sensing images of the place to be researched n years ago to be easier to compare with the remote sensing images of the place to be researched n years later;
the comparison module is used for comparing the remote sensing images of the place to be researched n years ago with the remote sensing images of the place to be researched n years later to obtain a comparison result, and the comparison result comprises a plurality of kinds of change information;
the judging module is used for judging the development trend of the to-be-researched area according to the comparison result;
and the layout module is used for recommending the building layout to the ground to be researched according to the development trend.
By adopting the technical scheme, the remote sensing images before and after the ground to be researched are obtained, the remote sensing images are subjected to image processing, the remote sensing images are clearer and easier to compare, the land utilization change of the ground to be researched is judged by comparing the remote sensing images, so that the economic development condition, namely the development trend, of the ground to be researched is judged, the buildings of the ground to be researched are distributed according to the speed of the development trend, and the remote sensing monitoring images are compared by time sequence association and spatial position association to perform multi-dimensional comprehensive correlation analysis by combining with business data of the industries such as China soil, statistics, traffic, water conservancy and the like, so that the urban development or building layout is more scientific.
In a third aspect, the present application provides an intelligent terminal, which adopts the following technical scheme:
an intelligent terminal is characterized by comprising a memory and a processor, wherein the memory is stored with a computer program which can be loaded by the processor and can execute a land utilization change remote sensing monitoring and analyzing method.
In a fourth aspect, the present application provides a computer readable storage medium storing a computer program that can be loaded by a processor and execute any one of the methods for remote sensing, monitoring and analyzing land use changes.
By adopting the technical scheme, the land use change remote sensing monitoring and analyzing method can be stored in the readable storage medium, so that the computer program of the land use change remote sensing monitoring and analyzing method stored in the readable storage medium can be executed by the processor, and the effect of improving the stability of the processing system is realized.
In summary, the present application includes at least one of the following beneficial technical effects:
1. in the scheme, the land utilization change is acquired by remote sensing images n years before and n years after the land to be researched, and the economic development condition of the land to be researched is predicted, so that the urban development or building layout is more scientific;
2. in the scheme, the remote sensing image is acquired by the satellite, and the cloud removing processing and atmospheric radiation influence correction are carried out on the remote sensing image, so that the remote sensing image is clearer and easier to compare, and the prediction accuracy is improved;
3. according to the scheme, the development trend of the place to be researched is further predicted from the time and space angles according to the n-year time and the attributes of the place to be researched, so that the prediction is more accurate, and a theoretical basis is provided for building layout recommendation of the place to be researched.
Drawings
Fig. 1 is a schematic flow chart in the first embodiment of the present application.
Fig. 2 is a graph of the effect of removing noise by fourier transform in the first embodiment of the present application.
Fig. 3 is a schematic diagram of histogram radiation correction of the first embodiment in the present application.
FIG. 4 is a graph of a first embodiment radiation corrected regression analysis of the present application (left graph is a schematic diagram and right graph is a regression analysis scatter plot).
Fig. 5 is a schematic view of the apparatus in a second embodiment of the present application.
Fig. 6 is a schematic diagram of an intelligent terminal in a third embodiment of the present application.
Description of reference numerals: 201. an acquisition module; 202. an image processing module; 203. a comparison module; 204. a judgment module; 205. a layout module; 301. a memory; 302. a processor.
Detailed Description
The present application is described in further detail below with reference to figures 1-3.
The present embodiment is only for explaining the present invention, and it is not limited to the present invention, and those skilled in the art can make modifications of the present embodiment without inventive contribution as needed after reading the present specification, but all of them are protected by patent law within the scope of the claims of the present invention.
The first embodiment is as follows:
a method for monitoring and analyzing land utilization change by remote sensing, referring to figure 1, comprises the following steps:
101. and acquiring remote sensing images of the place to be researched n years ago and n years later.
Specifically, a remote sensing image is obtained through a sensor on a remote sensing platform, the remote sensing platform is a satellite, an airplane, an airship and the like, the remote sensing image of a to-be-researched land is obtained through a hyperspectral sensor, and the remote sensing image comprises rich information such as vegetation information, soil moisture content, water quality parameters, surface temperature, ocean temperature and the like of the to-be-researched land;
after acquiring remote sensing images of a place to be researched every year, storing the remote sensing images into a database, and storing the remote sensing images in a form of corresponding year and corresponding monitoring place names;
remote sensing images of a place to be researched n years ago and n years later are called in a database, for example, remote sensing images of Sichuan 5 years ago are called in the database, and remote sensing images of Sichuan in the same year are called, for example, remote sensing images of Sichuan 2015 and remote sensing images of Sichuan 2020 are called.
102. And carrying out image processing on the remote sensing images of the place to be researched n years ago and the place to be researched n years later so as to enable the remote sensing images of the place to be researched n years ago and the place to be researched n years later to be easier to compare.
Specifically, referring to fig. 2, the original image is inspected for quality factors such as cloud amount, noise, yaw angle, coverage, overlap, and contrast by using a human-computer interaction method. Processing image noise by methods such as Fourier transform, minimum noise separation transform and the like; removing the cloud and mist on the image by utilizing algorithms such as wavelet transformation, homomorphic filtering and the like; removing the influence of thick clouds by utilizing mosaic complementation of multi-scene images; the image quality is improved by adopting information enhancement technical methods such as histogram adjustment, linear expansion and the like, and a good basis is provided for human-computer interaction visual interpretation, so that remote sensing images before and after n years of a to-be-researched place can be compared more easily.
Due to the influence of Rayleigh scattering, Mie scattering and errors of the sensor, serious noise exists in part of original remote sensing images, particularly in a blue light wave band. In the case where there is no better data source, it is necessary to de-noise this portion of the data.
Specifically, a fourier transform spatial filtering method is adopted for most of the strip noise existing in the image, and in addition, fourier transform denoising does not cause adverse effects on the shape of the reflection spectrum curve of the ground object on the image, and the spectral information of the ground object on the image is reserved. The frequency in the image space domain describes the variation of pixel values with distance in a two-dimensional plane, and the Fourier transform is used for transforming the image from the space domain to the frequency domain. The fourier transform, also called mathematical triple prism, can transform the remote sensing image from the spatial domain into the frequency domain containing only different frequency information, just as the white light is decomposed into 7 monochromatic lights with different frequencies by the triple prism. The Fourier transform denoising processing is to transform an image into a frequency domain and then process the image on the frequency domain, so as to achieve the purposes of removing noise and enhancing spatial filtering.
According to the Fourier transform theory, after carrying out Fourier transform on a remote sensing image, a transform domain, namely a frequency domain plane, the distribution form of which is completely different from that of an original image is obtained. After Fourier transformation, most of information of gray level mutation parts, areas with complex image structures, image details, interference noise and the like on an original image is concentrated in a high-frequency area; on the other hand, the parts of the original image where the gradation change is gradual, such as the regional topographic information, are fourier-transformed and then mostly concentrated in the low frequency region in the frequency domain. In the frequency domain plane, the low frequency region is located at the center portion, and the high frequency region is located at the periphery of the low frequency region, i.e., the edge portion. The information distribution characteristic in the frequency domain of an image is referred to as the spectrum of the image. The stripe error belongs to high-frequency information, and another important characteristic is that the signal of the stripe error is in a periodic distribution after Fourier transformation.
Further, the image processing comprises cloud haze processing, and a two-dimensional function f (x, y) of the remote sensing image is obtained; according to the two-dimensional function f (x, y), obtaining a function influencing the definition of the remote sensing image;
and reducing the function value influencing the definition of the remote sensing image so as to enable the remote sensing image to be clearer.
Specifically, under the condition of thin cloud, the image information received by the sensor comprises two parts, namely sunlight reflected by the cloud layer and sunlight reflected by a ground scene and then penetrates through the cloud layer. The image corresponds to a two-dimensional function f (x, y) and can be represented by the following equation:
wherein: f (x, y) is an image received by the sensor, and r (x, y) is the reflectivity of the ground object scene and represents a signal; t (x, y) is the transmission of the cloud layer, representing noise; l is the intensity of sunlight; a is the attenuation coefficient of sunlight in the atmospheric transmission process; the values of r (x, y), t (x, y) and a lie between 0 and 1.
The image received on the sensor can be seen to be determined by 2 factors. One is the effect of, for example, clouds, fog, atmosphere, etc., and the other is the difference in the reflection characteristics of the ground. If other factors are ignored, the former is mainly caused by the cloud. Generally, scenes are mainly at high frequency, reflecting the detailed content of the image; the irradiation component generally has small difference on the whole remote sensing image except individual shadow areas, shows the characteristic of slow change, is related to low frequency in a frequency domain, and the thinning cloud is to properly reduce the influence of a light source irradiation quantity function and simultaneously strengthen the components of a ground reflectivity function so as to weaken the influence of the thinning cloud.
Specifically, an HIS conversion method is adopted, the brightness component in an HIS space mainly reflects the total energy of ground object radiation and the spatial distribution thereof, namely, the brightness component is represented as geometric characteristics, and the cloud information is concentrated on a brightness channel; and the chromaticity and saturation mainly reflect the spectral characteristics of the ground features. Therefore, the process of removing the thin cloud of the color remote sensing image based on HIS transformation comprises the steps of firstly carrying out HIS transformation on the color remote sensing image containing the thin cloud, and converting R, G, B three color channels of the image into an I brightness channel and H, S two color information channels; and then keeping H, S channel information and processing only aiming at the I channel containing the cloud information. The most common application of the prior art is to carry out cloud removal processing on an I channel by adopting a homomorphic filtering and high-pass filter method; and finally, re-synthesizing the I channel subjected to the cloud removal processing with the reserved H, S channel. The processing achieves the aim of removing the thin cloud, and meanwhile, the color is not distorted.
Further, the image processing comprises image contrast enhancement, and a correction value of the remote sensing image is obtained;
correcting the remote sensing image according to the correction value so as to eliminate errors caused by atmospheric radiation influence of the remote sensing image; and acquiring the corrected remote sensing image, and checking a correction result.
Specifically, referring to fig. 3, the image brightness and contrast are improved by eliminating the error caused by the influence of the atmospheric path radiation, and the histogram method is mainly adopted.
The histogram correction method is to find a correction amount by gray histogram comparison. Since atmospheric scattering effects only act on short bands, there is little effect on infrared bands other than visible light. Therefore, if there is a ground feature with zero gray value (e.g. deep water, mountain shadow, etc.) in the image range, the gray histogram should start from the origin, and the other band gray histograms are at a distance from the origin (e.g. line segment a in the graph)1) And the distance is the gray level histogram drift value caused by atmospheric scattering. The correction is performed accordingly as a correction amount, which is equivalent to subtracting this value from the gray value of each pixel. In actual operation, the band histogram drift value of each scene image is automatically extracted by using PCI software and corrected. The result of the histogram correction is then checked by means of human-computer interaction.
Further, if the correction result does not reach the expectation, the regression analysis method is used for processing again until the correction result reaches the expectation.
Specifically, referring to fig. 4, the images that cannot be improved are processed again by using a regression analysis method, which also uses the rule that the near-infrared and infrared bands are less affected by the atmosphere. In a wave band (such as a near infrared wave band) which is not influenced by atmosphere and a certain wave band image to be corrected, a series of targets from the brightest to the darkest are selected, and two wave band gray values to be compared of each target are extracted for regression analysis. For example, a regression line graph is made by comparing the blue band with the near infrared band in the satellite multi-spectral data. The regression equation is:
in the formula
Average values of blue light and near infrared wave bands respectively; t1 and T5 represent gray values of blue light and near infrared bands; a is1I.e., the correction amount for the blue band, i.e., the intercept in the regression analysis map. The correction amount is subtracted from each pixel of the blue band. According to the method, the green light wave band and the red light wave band are corrected in sequence.
103. And comparing the remote sensing images of the place to be researched n years ago and the place to be researched n years later to obtain a comparison result, wherein the comparison result comprises a plurality of kinds of change information.
Specifically, compare the remote sensing image after the image processing, the remote sensing image is more clear this moment, and the mode of comparison mainly includes artifical visual translation, specifically is:
and the images of the front time phase and the rear time phase are placed in the same window of the data processing software in parallel, and the change of the ground feature information is identified through visual comparison and observation. The operator is required to cover the ground object with prior knowledge, so that the corresponding relation can be searched on the remote sensing image. The method is very flexible, but needs certain experience of operators, and has more requirements on professional business when the ground features are interpreted.
The comparison mode can also be automatic identification and monitoring of the change information, and specifically comprises the following steps:
the method is characterized in that the change information of the front time phase and the rear time phase of the ground feature is automatically identified based on spectral characteristics, at present, the extraction of the change information is automatically realized mainly by carrying out various technical processes on a remote sensing image, and the automatic identification and monitoring of the change information mainly comprises the following methods: (a) image direct comparison method:
the image direct comparison method is the most common basic method, and is to directly perform operation or transformation processing on all pixel values in the remote sensing images of different time phases after correction and registration to find out the changed area, and mainly includes an image difference method, an image ratio method, a pseudo-color synthesis method, a waveband replacement method and the like.
(b) Post-classification comparison method:
the classified result comparison method is to perform supervision classification or various classifications on the corrected and registered remote sensing images in different time phases respectively, and finally perform comparison analysis on the classification results to obtain change detection information. The core of the method is to discover change information based on classification basis.
(c) Direct classification method:
the method combines the ideas of a direct image comparison method and a classified result comparison method. The method is to confirm the corresponding changed wave band value in the image with changed ground object attributes and find the interval range of the difference value, thereby finding out the change information. Such as the common principal component analysis and classification method of anterior-posterior phase or multi-phase.
The comparison mode can also be a man-machine mutual aid comprehensive method, which specifically comprises the following steps:
the manual visual interpretation usually consumes time and labor due to large workload, greatly increases the working cost and is greatly influenced by artificial subjective factors. The automatic identification of the change information greatly improves the efficiency of monitoring work, and effectively improves the identification precision of the land use change information, but the automatic identification result only reflects the distribution and the size of the change and is difficult to automatically acquire the property of the changed land feature, so the use of the method still needs manual participation. Therefore, the current land use change information identification and monitoring still takes a man-machine mutual-aid comprehensive method as a main part, so that the working rate is improved, the cost is reduced, and the information identification and monitoring precision is also improved.
The land utilization information is extracted, and the comparison result is specifically the change of the number of buildings in the remote sensing image and specifically the change of the density of the building pattern spots;
wherein, the comparison result includes various change information, which specifically includes:
the front time phase image has vegetation coverage or obvious non-construction traces, and the rear time phase image has obvious construction characteristics (such as foundations, buildings, structures, squares, parks and the like);
the front time phase image has vegetation coverage or obvious non-construction traces, and the rear time phase image has obvious construction push-fill characteristics;
the front time phase image has obvious construction push-filling characteristics, and the rear time phase image has obvious construction characteristics (such as foundations, buildings, structures, squares, parks and the like); or the front time phase image is a short building, and the rear time phase image is converted into a large-scale building, such as a residential district, a high-rise building or a large-scale chemical plant;
the front time phase image has vegetation coverage or no obvious construction, and the rear time phase image has obvious road or large-scale ditch characteristics (including bulldozing under construction, bridge pier construction and the like); or the front time phase image road or the large ditch is built, and the rear time phase image is obviously built into the characteristics (including road surface hardening, traffic running and the like). And measuring the width of the road surface on the new road in a required drawing.
104. And judging the development trend of the place to be researched according to the comparison result.
Specifically, the land utilization change of the land to be researched is obtained according to the comparison result, and the future development trend of the land to be researched is judged according to the land utilization change of the land to be researched.
The development direction of the place to be researched can be further determined according to the change information, for example, the change information is that the front time phase image has vegetation coverage or obvious non-construction traces, and the rear time phase image has obvious construction characteristics, which indicates that the place to be researched is ready to be developed into towns.
Further, obtaining a relational expression between the comparison result and the development trend;
judging the development trend of the to-be-researched area according to the relational expression;
if the comparison result shows that the land utilization rate of the land to be researched is increased, judging that the land to be researched is in a development state;
if the comparison result shows that the land utilization rate of the land to be researched is not changed, judging that the land to be researched is in a stagnation state;
and if the comparison result shows that the land utilization rate of the land to be researched is reduced, judging that the land to be researched is in a reverse state.
Specifically, the development tendency specifically includes a development state indicating a state in which the place to be studied is in development during the research age; the method also comprises a stagnation state which indicates that the ground to be researched is in a stagnation state in the research age; a reverse state is also included, indicating that the place to be studied is in a reverse state during the study years.
Wherein, a relational expression is obtained according to the comparison result and the development trend, and the relational expression specifically comprises the following steps:
if the number of the image spots of the remote sensing image after n years is divided by the number of the image spots of the remote sensing image before n years is 1, judging that the remote sensing image to be researched is in a stagnation state;
judging that the remote sensing image to be researched is in a development state if the number of the image spots of the remote sensing image after n years is divided by the number of the image spots of the remote sensing image before n years is more than 1;
and judging that the remote sensing image to be researched is in a backward state if the number of the image spots of the remote sensing image after n years is divided by the number of the image spots of the remote sensing image before n years is less than 1.
Further, according to the n years, further supplementing the relational expression, and acquiring the supplemented relational expression; and judging the development speed of the to-be-researched area according to the supplemented relational expression.
Specifically, after further supplementing the relational expression, the method specifically includes:
the development speed is divided by the number of the remote sensing image spots after n years (the number of the remote sensing image spots before n years multiplied by n years);
if the development speed is 1/n, the state of the ground to be researched is in a stagnation state;
if the development speed is more than 1/n and less than 1, the land to be researched is in a development state, and the development speed is low;
if the development speed is more than 1 and less than 2, the research place is in a development state, and the development speed is general;
if the development speed is less than 2, the ground to be researched is in a development state, and the development speed is higher;
if the development speed is less than 1/n, the condition that the research site is in a reverse state is indicated.
105. And recommending the building layout of the ground to be researched according to the development trend.
Specifically, if the development trend is a development state, recommending to be researched: the method shows that the place to be researched is in a development stage, more entertainment places and shopping malls are recommended to be established in the place to be researched, and as the population is continuously increased, places for people to entertain and enjoy in the place to be researched are provided, so that the happiness is improved, the economic development of the place to be researched is promoted, the population density is increased, and the development is further promoted.
And if the development trend is in a stagnation state, recommending the place to be researched: the method shows that the land to be researched hardly develops in the period of n years, recommends that the land to be researched properly establishes an office building and an industrial park, provides employment and entrepreneurship opportunities for the land to be researched, and attracts employees to reside so as to promote economic development.
And if the development trend is in a reverse state, recommending the site to be researched: the method shows that the population of the to-be-researched land is migrated or the building is dismantled, and the land for photovoltaic power stations, golf courses, steel enterprises and the like can be established, so that the to-be-researched land is reasonably utilized, and the waste of land resources is avoided.
Further, acquiring the attribute of the ground to be researched, wherein the attribute is used for describing the future development direction of the ground to be researched;
and monitoring and analyzing the place to be researched according to the development trend and the attribute of the place to be researched.
Specifically, after the change of the pattern spots is obtained according to the comparison of the remote sensing images before and after n years, the pattern spots are specifically the units used for representing one building in the remote sensing images; and judging the attribute of the ground to be researched according to the increased or decreased pattern spots.
For example, if the added pattern spots are railways, airports, etc., which indicate that the future development direction of the place to be researched is a national major investment project, it is recommended to continuously track and count the railway, airport pattern spots and surroundings, analyze the engineering construction condition and the surrounding influence condition, and provide supervision basis for the administrative department such as development committee, etc.
For example, if the added pattern spots are large-scale ditches and other pattern spots related to the construction of water conservancy facilities, it indicates that the future development direction of the to-be-researched field is the construction of water conservancy, and the construction conditions of the water conservancy infrastructure in each region can be timely mastered by monitoring the added pattern spots.
The implementation principle of the embodiment of the application is as follows: the remote sensing images before and after n years of a to-be-researched place are obtained, and the remote sensing images are subjected to image processing, specifically noise reduction, cloud removal and image contrast enhancement, so that the remote sensing images are clearer and easier to compare; obtaining a comparison result by comparing the remote sensing images, judging the land utilization change of the land to be researched through the comparison result so as to judge the economic development condition, namely the development trend, of the land to be researched, obtaining a relational expression, and providing a theoretical basis for the future building layout of the land to be researched by developing, stagnating or backing up according to the development trend according to the relational expression;
furthermore, the development speed of the place to be researched is obtained by substituting the monitoring age into the relational expression, and the future building layout is further modified, so that the analysis is more accurate;
furthermore, the monitoring condition of the place to be researched is further analyzed by acquiring the attribute of the place to be researched, the remote sensing monitoring images are compared by time sequence association and spatial position association, and multi-dimensional comprehensive correlation analysis is carried out by combining business data of the industries such as homeland, statistics, traffic, water conservancy and the like, so that the urban development or building layout is more scientific.
Example two:
a device for remote sensing monitoring and analyzing changes in land use, referring to fig. 5, which corresponds to the method for remote sensing monitoring and analyzing changes in land use in the first embodiment one by one, specifically comprising:
the acquisition module 201 is used for acquiring remote sensing images of a place to be researched n years ago and n years later.
The image processing module 202 is configured to perform image processing on the remote sensing images of the place to be researched n years ago and the place to be researched n years later, so that the remote sensing images of the place to be researched n years ago and the place to be researched n years later are easier to compare.
Further, the image processing comprises cloud haze processing, and a two-dimensional function f (x, y) of the remote sensing image is obtained; according to the two-dimensional function f (x, y), obtaining a function influencing the definition of the remote sensing image;
and reducing the function value influencing the definition of the remote sensing image so as to enable the remote sensing image to be clearer.
Further, the image processing comprises image contrast enhancement, and a correction value of the remote sensing image is obtained;
correcting the remote sensing image according to the correction value so as to eliminate errors caused by atmospheric radiation influence of the remote sensing image; and acquiring the corrected remote sensing image, and checking a correction result.
Further, if the correction result does not reach the expectation, the regression analysis method is used for processing again until the correction result reaches the expectation.
The comparison module 203 is configured to compare the remote sensing images of the place to be researched n years ago and the place to be researched n years later, and obtain the comparison result, where the comparison result includes a plurality of kinds of change information.
And the judging module 204 is configured to judge the development trend of the place to be researched according to the comparison result.
Further, obtaining a relational expression between the comparison result and the development trend;
judging the development trend of the to-be-researched area according to the relational expression;
if the comparison result shows that the land utilization rate of the land to be researched is increased, judging that the land to be researched is in a development state;
if the comparison result shows that the land utilization rate of the land to be researched is not changed, judging that the land to be researched is in a stagnation state;
and if the comparison result shows that the land utilization rate of the land to be researched is reduced, judging that the land to be researched is in a reverse state.
Further, according to the n years, further supplementing the relational expression, and acquiring the supplemented relational expression; and judging the development speed of the to-be-researched area according to the supplemented relational expression.
And the layout module 205 is used for recommending the building layout to the ground to be researched according to the development trend.
Further, acquiring the attribute of the ground to be researched, wherein the attribute is used for describing the future development direction of the ground to be researched;
and monitoring and analyzing the place to be researched according to the development trend and the attribute of the place to be researched.
Example three:
an intelligent terminal, referring to fig. 6, includes a memory 301, a processor 302, and a computer program stored in the memory 301 and executable on the processor 302, wherein the memory 301 stores training data, algorithm formula, filtering mechanism, and the like in a training model. The processor 302 is configured to provide computing and control capabilities, and the processor 302 when executing the computer program performs the steps of:
101. and acquiring remote sensing images of the place to be researched n years ago and n years later.
102. And carrying out image processing on the remote sensing images of the place to be researched n years ago and the place to be researched n years later so as to enable the remote sensing images of the place to be researched n years ago and the place to be researched n years later to be easier to compare.
Further, the image processing comprises cloud haze processing, and a two-dimensional function f (x, y) of the remote sensing image is obtained; according to the two-dimensional function f (x, y), obtaining a function influencing the definition of the remote sensing image;
and reducing the function value influencing the definition of the remote sensing image so as to enable the remote sensing image to be clearer.
Further, the image processing comprises image contrast enhancement, and a correction value of the remote sensing image is obtained;
correcting the remote sensing image according to the correction value so as to eliminate errors caused by atmospheric radiation influence of the remote sensing image; and acquiring the corrected remote sensing image, and checking a correction result.
Further, if the correction result does not reach the expectation, the regression analysis method is used for processing again until the correction result reaches the expectation.
103. And comparing the remote sensing images of the place to be researched n years ago and the place to be researched n years later to obtain a comparison result, wherein the comparison result comprises a plurality of kinds of change information.
104. And judging the development trend of the place to be researched according to the comparison result.
Further, obtaining a relational expression between the comparison result and the development trend;
judging the development trend of the to-be-researched area according to the relational expression;
if the comparison result shows that the land utilization rate of the land to be researched is increased, judging that the land to be researched is in a development state;
if the comparison result shows that the land utilization rate of the land to be researched is not changed, judging that the land to be researched is in a stagnation state;
and if the comparison result shows that the land utilization rate of the land to be researched is reduced, judging that the land to be researched is in a reverse state.
Further, according to the n years, further supplementing the relational expression, and acquiring the supplemented relational expression; and judging the development speed of the to-be-researched area according to the supplemented relational expression.
105. And recommending the building layout of the ground to be researched according to the development trend.
Further, acquiring the attribute of the ground to be researched, wherein the attribute is used for describing the future development direction of the ground to be researched;
and monitoring and analyzing the place to be researched according to the development trend and the attribute of the place to be researched.
Example four:
a computer readable storage medium storing a computer program capable of being loaded by a processor 302 and executing the land use change remote sensing monitoring and analyzing method, the computer program when executed by the processor 302 implementing the steps of: 101. and acquiring remote sensing images of the place to be researched n years ago and n years later.
102. And carrying out image processing on the remote sensing images of the place to be researched n years ago and the place to be researched n years later so as to enable the remote sensing images of the place to be researched n years ago and the place to be researched n years later to be easier to compare.
Further, the image processing comprises cloud haze processing, and a two-dimensional function f (x, y) of the remote sensing image is obtained; according to the two-dimensional function f (x, y), obtaining a function influencing the definition of the remote sensing image;
and reducing the function value influencing the definition of the remote sensing image so as to enable the remote sensing image to be clearer.
Further, the image processing comprises image contrast enhancement, and a correction value of the remote sensing image is obtained;
correcting the remote sensing image according to the correction value so as to eliminate errors caused by atmospheric radiation influence of the remote sensing image; and acquiring the corrected remote sensing image, and checking a correction result.
Further, if the correction result does not reach the expectation, the regression analysis method is used for processing again until the correction result reaches the expectation.
103. And comparing the remote sensing images of the place to be researched n years ago and the place to be researched n years later to obtain a comparison result, wherein the comparison result comprises a plurality of kinds of change information.
104. And judging the development trend of the place to be researched according to the comparison result.
Further, obtaining a relational expression between the comparison result and the development trend;
judging the development trend of the to-be-researched area according to the relational expression;
if the comparison result shows that the land utilization rate of the land to be researched is increased, judging that the land to be researched is in a development state;
if the comparison result shows that the land utilization rate of the land to be researched is not changed, judging that the land to be researched is in a stagnation state;
and if the comparison result shows that the land utilization rate of the land to be researched is reduced, judging that the land to be researched is in a reverse state.
Further, according to the n years, further supplementing the relational expression, and acquiring the supplemented relational expression; and judging the development speed of the to-be-researched area according to the supplemented relational expression.
105. And recommending the building layout of the ground to be researched according to the development trend.
Further, acquiring the attribute of the ground to be researched, wherein the attribute is used for describing the future development direction of the ground to be researched;
and monitoring and analyzing the place to be researched according to the development trend and the attribute of the place to be researched.
It should be noted that: in the device for remote sensing monitoring and analyzing of land use change provided by the above embodiment, when the method for remote sensing monitoring and analyzing of land use change is executed, only the division of the above functional modules is taken as an example, and in practical application, the above function distribution can be completed by different functional modules according to needs, that is, the internal structure of the equipment and the device is divided into different functional modules so as to complete all or part of the above described functions. In addition, the remote sensing monitoring and analyzing method, the remote sensing monitoring and analyzing device and the intelligent terminal for the land use change provided by the embodiment belong to the same concept, and the specific implementation process is detailed in the method embodiment and is not repeated herein.
It will be understood by those skilled in the art that all or part of the steps for implementing the above embodiments may be implemented by hardware, or may be implemented by a program instructing relevant hardware, where the program may be stored in a computer-readable storage medium, and the above-mentioned storage medium may be a read-only memory, a magnetic disk or an optical disk, etc.
The above description is only exemplary of the present application and should not be taken as limiting the present application, as any modification, equivalent replacement, or improvement made within the spirit and principle of the present application should be included in the protection scope of the present application.
Claims (10)
1. A land utilization change remote sensing monitoring and analyzing method is characterized by comprising the following steps:
acquiring remote sensing images of a place to be researched n years ago and n years after the place to be researched;
carrying out image processing on the remote sensing images of the place to be researched n years ago and the place to be researched n years later so as to enable the remote sensing images of the place to be researched n years ago and the place to be researched n years later to be easier to compare;
comparing the remote sensing images of the place to be researched n years ago and the place to be researched n years later to obtain a comparison result, wherein the comparison result comprises a plurality of kinds of change information;
judging the development trend of the to-be-researched area according to the comparison result;
and recommending the building layout of the ground to be researched according to the development trend.
2. The method of claim 1, wherein the image processing comprises cloud haze processing, the method comprising:
acquiring a two-dimensional function f (x, y) of the remote sensing image;
according to the two-dimensional function f (x, y), obtaining a function influencing the definition of the remote sensing image;
and reducing the function value influencing the definition of the remote sensing image so as to enable the remote sensing image to be clearer.
3. A method as claimed in claim 1 or 2, wherein the image processing comprises image contrast enhancement, the method comprising:
acquiring a correction value of the remote sensing image;
correcting the remote sensing image according to the correction value so as to eliminate errors caused by atmospheric radiation influence of the remote sensing image;
and acquiring the corrected remote sensing image, and checking a correction result.
4. The method of claim 3, comprising:
and if the correction result does not reach the expectation, re-processing by using a regression analysis method until the correction result reaches the expectation.
5. The method according to claim 1, wherein the determining the trend of the research site according to the comparison result comprises:
obtaining a relational expression between the comparison result and the development trend;
judging the development trend of the to-be-researched area according to the relational expression;
if the comparison result shows that the land utilization rate of the land to be researched is increased, judging that the land to be researched is in a development state;
if the comparison result shows that the land utilization rate of the land to be researched is not changed, judging that the land to be researched is in a stagnation state;
and if the comparison result shows that the land utilization rate of the land to be researched is reduced, judging that the land to be researched is in a reverse state.
6. The method of claim 5, wherein said building layout recommendation for said site under study according to said trend of development comprises:
acquiring the attribute of the place to be researched, wherein the attribute is used for describing the future development direction of the place to be researched;
and monitoring and analyzing the place to be researched according to the development trend and the attribute of the place to be researched.
7. The method of claim 5, comprising:
according to the n years, further supplementing the relational expression to obtain the supplemented relational expression;
and judging the development speed of the to-be-researched area according to the supplemented relational expression.
8. The utility model provides a land utilization change remote sensing monitoring analytical equipment which characterized in that includes:
the system comprises an acquisition module (201) for acquiring remote sensing images of a place to be researched n years ago and n years later;
the image processing module (202) is used for carrying out image processing on the remote sensing images of the place to be researched n years ago and the place to be researched n years later so as to enable the remote sensing images of the place to be researched n years ago to be easier to compare with the remote sensing images of the place to be researched n years later;
the comparison module (203) is used for comparing the remote sensing images of the place to be researched before n years and the place to be researched after n years to obtain a comparison result, and the comparison result comprises a plurality of kinds of change information;
the judging module (204) is used for judging the development trend of the place to be researched according to the comparison result;
and the layout module (205) is used for recommending the building layout to the ground to be researched according to the development trend.
9. An intelligent terminal, characterized in that it comprises a memory (301) and a processor (302), said memory (301) having stored thereon a computer program that can be loaded by the processor (302) and that executes the method according to any one of claims 1 to 7.
10. A computer-readable storage medium, characterized in that a computer program is stored which can be loaded by a processor (302) and which performs the method according to any of claims 1 to 7.
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| CN114387530A (en) * | 2022-01-13 | 2022-04-22 | 山东土地集团数字科技有限公司 | Land use attribute monitoring method based on remote sensing image technology |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107301633A (en) * | 2017-06-29 | 2017-10-27 | 常州工学院 | The emulation mode of remotely sensed image under cloud and mist interference |
| CN109376600A (en) * | 2018-09-20 | 2019-02-22 | 中国农业大学 | Multi-spectrum remote sensing image comprehensive characteristics cloud detection method of optic and device |
| CN110705449A (en) * | 2019-09-27 | 2020-01-17 | 佛山科学技术学院 | Land utilization change remote sensing monitoring analysis method |
-
2020
- 2020-12-30 CN CN202011604328.6A patent/CN112686861A/en active Pending
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107301633A (en) * | 2017-06-29 | 2017-10-27 | 常州工学院 | The emulation mode of remotely sensed image under cloud and mist interference |
| CN109376600A (en) * | 2018-09-20 | 2019-02-22 | 中国农业大学 | Multi-spectrum remote sensing image comprehensive characteristics cloud detection method of optic and device |
| CN110705449A (en) * | 2019-09-27 | 2020-01-17 | 佛山科学技术学院 | Land utilization change remote sensing monitoring analysis method |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114387530A (en) * | 2022-01-13 | 2022-04-22 | 山东土地集团数字科技有限公司 | Land use attribute monitoring method based on remote sensing image technology |
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