CN113269429B - Ecological environment quality evaluation method based on water ecological benefits - Google Patents

Ecological environment quality evaluation method based on water ecological benefits Download PDF

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CN113269429B
CN113269429B CN202110545482.9A CN202110545482A CN113269429B CN 113269429 B CN113269429 B CN 113269429B CN 202110545482 A CN202110545482 A CN 202110545482A CN 113269429 B CN113269429 B CN 113269429B
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矫志军
王凯
陈勇
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Qingdao Xingke Ruisheng Information Technology Co ltd
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Abstract

The invention discloses an ecological environment quality evaluation method based on water ecological benefits, which relates to the technical field of ecological environment quality evaluation and comprises the following steps of S1, constructing ecological indexes through the structure and the function of ecological environment; step S2, fusing multiple indexes based on entropy; the invention fully utilizes the characteristics of the ecological environment in the aspects of structure and function, constructs reasonable ecological indexes, particularly constructs and adds water ecological elements, and ensures that the WBEI can more accurately describe the complexity of the ecological environment. The concept of the information entropy is introduced, the interaction relation between the ecological environment and the ecological indexes is clearly disclosed, and the index weight obtained by the fusion method based on the information entropy is obtained by calculating the image information amount, so that the fusion method is more objective compared with the traditional fusion method, and can avoid the interference of human subjective factors.

Description

Ecological environment quality evaluation method based on water ecological benefits
Technical Field
The invention relates to an ecological environment quality evaluation method based on water ecological benefits, and belongs to the technical field of ecological environment quality evaluation.
Background
With the aggravation of global resource and environment problems, governments of all countries in the world pay great attention to the research of ecological environment. Particularly in developing countries, the contradiction between the rapid urban development and the fragile ecological environment is becoming more and more acute under the urgent development requirements. The ecological environment is a complex community formed by the mutual influence and restriction of various ecological factors through material exchange, energy flow and information transmission. In order to realize the coordinated development of cities and ecological environments, the accurate evaluation of the ecological environment quality becomes an important subject concerned by the current scientific community.
In the past research, researchers are always searching for methods for evaluating the quality of the ecological environment, but the complicated data acquisition method and the low-quality data limit accurate and objective exploration of the methods. With the rise of remote sensing technology, various ecological indexes based on remote sensing are widely applied to ecological environment quality evaluation due to the advantages of high image quality, convenience in data acquisition and the like. Among them, the Normalized Difference Vegetation Index (NDVI) is the most widely used single index in various ecological studies. Other single ecological indicators such as surface temperature (LST), Leaf Area Index (LAI), Normalized Differential Soil Index (NDSI), and Normalized Differential Water Index (NDWI) are also considered satisfactory ecological indicators. However, the influence of the interaction between the indexes on the ecological environment is comprehensive and cannot be separated independently. Therefore, the complexity of the relationship between the ecological environment and the ecological factors makes it difficult to accurately and objectively evaluate the quality of the ecological environment by only one index.
In order to achieve the goal of comprehensively evaluating the quality of the ecological environment, the multi-index fusion method becomes the focus of attention of researchers. Wherein the pressure-state-response (P-S-R) model describes the constituent elements of the ecological environment from three aspects of landscape change pressure, landscape ecosystem state and human response, and realizes the comprehensive evaluation of the quality of the ecological environment. But the indexes are selected complicatedly, and the model is constructed complicatedly, so that the method is not widely applied. In order to simplify indexes, a remote sensing-based ecological index (RSEI) realizes the visualization of spatial details of the ecological environment and evaluates the quality of the ecological environment from four aspects of green, wet, dry and hot.
However, the multi-index ecological environment quality evaluation method still has some problems. For example: the surface environment is a very complex system, and some main land covering types such as water, vegetation, impervious surfaces and soil are not only complex and variable in spatial distribution, but also have complex relationships of mutual influence and mutual restriction. When the ecological indexes are many and complex, the problem of index failure is easily caused, so how to select effective indexes to clearly characterize complex ecological environment is still one of the difficulties. Furthermore, the water ecological elements become particularly important due to their particular form of presence. It can not only guarantee the living of the living things but also improve the quality of the ecological environment through phase change. Therefore, the water ecological factors are indispensable indicators for evaluating the quality of ecological environment. In order to accurately evaluate the ecological environment condition, the multi-index ecological environment evaluation method needs to be improved.
Disclosure of Invention
The invention mainly aims to provide an ecological environment quality evaluation method based on water ecological benefits, an effective ecological index is constructed from two aspects of ecological environment structure and function, and a multi-ecological index is fused by combining information entropy to achieve the purpose of comprehensively evaluating the ecological environment quality. Firstly, the SPWI ecological index provided by the invention can accurately depict the spatial distribution of water ecological elements. The WBEI ecological index is particularly sensitive to the ecological environmental characterization of the water perimeter, precisely due to the addition of the SPWI ecological index. Secondly, effective ecological indexes can be clearly selected from the aspects of structural elements and functional elements, and the blindness of index selection is solved. And finally, fusing multiple ecological indexes by using a fusion method based on information entropy, so that the interference of subjective factors of people is avoided, and the interaction relation between the ecological indexes and the ecological environment can be reasonably explained.
The purpose of the invention can be achieved by adopting the following technical scheme:
an ecological environment quality evaluation method based on water ecological benefits comprises the following steps:
s1, constructing ecological indexes through the structure and the function of the ecological environment, wherein the construction of the ecological indexes specifically comprises the following steps:
s1.1, preprocessing an urban remote sensing image, wherein the preprocessing comprises radiation correction, image splicing and cutting;
s1.2, analyzing the structural elements and the functional elements of the ecological environment, and constructing an ecological environment evaluation index;
s1.3, inverting corresponding indexes according to the selected ecological indexes;
step S2, multi-index fusion based on entropy, the specific process comprises the following steps:
s2.1, calculating the information entropy of each ecological index, and giving weight to each ecological index according to the size of the information entropy;
s2.2, performing normalization processing on the same indexes obtained from data of different years in the same value range to realize dimensional unification of the indexes;
s2.3, determining the positive and negative effects of the indexes on the overall ecological environment, and completing multi-index fusion in a linear weighting mode;
preferably, the step S1.2 is specifically: the ecological indexes are divided into three categories of water ecological elements, thermal environments and surface covering types.
Preferably, the spatial distribution of the water ecological elements is expressed by constructing SPWI, and the SPWI is constructed by the following specific steps:
and S1.2.1, checking samples and selecting pure end members.
Step S1.2.2, calculating a spectral curve.
Step S1.2.3, analyzing the spectral feature of the surface feature
Through the spectral reflectance curve analysis of a sample, the spectral curve change trend of the sample is observed, the SPWI ecological index is constructed through effective band operation, and the ecological index inversion formula is as follows:
Figure BDA0003073465940000041
wherein, B2 is a blue light wave band, B5 is a near infrared wave band, and B7 is a second short wave infrared wave band.
Preferably, the water ecological elements include two ecological indicators of SPWI and NDLI, and the expression of NDLI is:
Figure BDA0003073465940000051
wherein, B3 is a green light wave band, B4 is a red light wave band, and B6 is a first short wave infrared wave band.
Preferably, the thermal environment comprises a surface temperature index, the surface temperature index is inverted by using a radiation transmission equation method, and the inversion process comprises the following steps:
thermal infrared radiation brightness value L received by satellite sensorzThe expression (c) can be written as (radiation transport equation):
Lz＝[εB(Ts)+(1-ε)Ld]τ+Lu
wherein ε is the ground surface emissivity, TsIs the true surface temperature (K), B (T)s) Is the black body heat radiation brightness, and tau is the transmission rate of the atmosphere in the thermal infrared band. The radiant brightness B (T) of the black body in the thermal infrared bands) Comprises the following steps:
B(Ts)＝[Lz-Lu-τ(1-ε)Ld]/τε
obtaining the actual surface temperature T by using the function of Planck formulas：
Ts＝K2/ln(K1/B(Ts)+1)
Wherein K1、K2A specific thermal conversion coefficient for the thermal infrared band.
Wherein the surface coverage type includes both RVI and NDSI indicators. The expressions are respectively:
Figure BDA0003073465940000061
wherein B4 is red light wave band, B5 is near infrared wave band.
Figure BDA0003073465940000062
Wherein B5 is near infrared band, B6 is first short wave infrared band.
Preferably, the step S2.1 specifically includes:
the smaller the information entropy of the ecological index is, the higher the weight is, and the information entropy calculation process of the ecological index specifically comprises the following steps:
Figure BDA0003073465940000063
Figure BDA0003073465940000064
wherein f isijRepresents the ratio of the gray value of the ith pixel of the jth ecological index to the total gray value, xijRepresenting the gray value of the ith pixel of the jth index,
Figure BDA0003073465940000065
the sum of the gray values representing the j-th index, ejThe information entropy of the j-th index is represented.
Figure BDA0003073465940000066
Wherein wjRepresents the weight of the j ecological index.
Preferably, the multi-index fusion calculation method in step S2.3 is,
WBEI＝w1×NDLI+w2×RVI+w3×SPWI-w4×LST-w5×NDSI，
wherein WBEI is ecological index based on water ecological benefit, i.e. fusion result, w1、w2、w3、w4、w5Respectively, represent weights calculated from the entropies of NDLI, RVI, SPWI, LST, NDSI.
The invention has the beneficial technical effects that:
1. the ecological environment quality evaluation method based on the water ecological benefits provided by the invention is characterized in that an urban remote sensing image is taken as a main data source, ecological indexes are constructed according to the characteristics of the ecological environment in the aspects of structure and function, and an interaction relation between the ecological environment and the indexes is represented by a fusion method based on information entropy, so that an ecological environment quality space distribution diagram is obtained.
2. The ecological environment quality evaluation method based on the water ecological benefits provided by the invention fully utilizes the characteristics of the ecological environment in the aspects of structure and function, constructs reasonable ecological indexes, particularly constructs and adds water ecological elements, so that the WBEI can more accurately describe the complexity of the ecological environment. The concept of the information entropy is introduced, the interaction relation between the ecological environment and the ecological indexes is clearly disclosed, and the index weight obtained by the fusion method based on the information entropy is obtained by calculating the image information amount, so that the fusion method is more objective compared with the traditional fusion method, and can avoid the interference of human subjective factors.
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FIG. 1 is a general structure diagram of the ecological environment quality evaluation method based on water ecological benefit according to the present invention;
FIG. 2 is a schematic flow chart of ecological index construction based on water ecological benefit;
FIG. 3 is a schematic flow chart of SPWI index construction;
fig. 4 is a sample spectral plot.
Detailed Description
In order to make the technical solutions of the present invention more clear and definite for those skilled in the art, the present invention is further described in detail below with reference to the examples and the accompanying drawings, but the embodiments of the present invention are not limited thereto.
As shown in fig. 1 to fig. 4, the method for evaluating ecological environment quality based on water ecological benefit provided by this embodiment includes the following steps:
s1, constructing ecological indexes through the structure and function of the ecological environment, wherein the indexes need to be selected from a clear and reasonable angle due to complex and various components of the ecological environment, so that the phenomenon of index failure or index insufficiency is avoided, and the construction of the ecological indexes specifically comprises the following steps:
s1.1, preprocessing an urban remote sensing image, wherein the preprocessing comprises radiation correction, image splicing and cutting;
the remote sensing image data used by the invention is 1T-level terrain correction data, so the pretreatment of the experiment comprises two key steps of radiometric calibration and atmospheric calibration, firstly, the experiment of the invention needs to compare the processing results of the remote sensing images in different time and different areas, therefore, the brightness value of the gray level image needs to be converted into absolute radiometric brightness, the conversion process is radiometric calibration, secondly, the radiometric error caused by atmospheric scattering and absorption can be found by knowing the image acquisition process of the satellite sensor, therefore, the radiometric error caused by atmospheric scattering and absorption in the remote sensing image is eliminated, the error elimination process is atmospheric calibration, and the radiometric calibration and the atmospheric calibration of the image are realized in ENVI5.3 software. After the image is corrected, the image can be used for scientific research after being cut in a research area;
s1.2, analyzing the structural elements and the functional elements of the ecological environment, and constructing an ecological environment evaluation index;
s1.3, inverting the corresponding index according to the selected ecological index to lay a foundation for comprehensive evaluation of ecological environment quality;
step S2, multi-index fusion based on entropy, the specific process comprises the following steps:
s2.1, calculating the information entropy of each ecological index, and giving weight to each ecological index according to the size of the information entropy;
s2.2, performing normalization processing on the same indexes obtained from data of different years in the same value range to realize dimensional unification of the indexes;
s2.3, determining the positive and negative effects of the indexes on the overall ecological environment, and completing multi-index fusion in a linear weighting mode;
in this embodiment: the step S1.2 is specifically as follows: the ecological indexes are divided into three categories of water ecological elements, thermal environments and surface coverage types; in order to select reasonable and effective ecological indexes from a plurality of complex ecological indexes, the invention analyzes the index composition of the ecological environment from two aspects of structural elements and functional elements, and divides the ecological indexes into three categories of water ecological elements, thermal environment and earth surface covering type.
In this embodiment: the spatial distribution of the water ecological elements is expressed by constructing SPWI, and the specific steps of the SPWI construction are as follows:
s1.2.1, checking samples, and selecting pure end members;
in order to construct SPWI, on the basis of analyzing spectral characteristics of two types of regions, a proper waveband is selected from landsat8 to construct an ecological index, in order to achieve the goal, a large number of pure samples are selected from an experimental region, the pure samples are respectively selected from the centers of land feature types, in order to ensure the purity and the representativeness of the samples, the samples are selected from the central region of the goal, because pixel points are uniform and can not be confused with other objects, for example, a water body sample is collected at the middle parts of rivers and reservoirs, a vegetation sample is collected in a dense forest grassland area, particularly, in coastal cities, bare soil is more present in farmlands and mudflats, the water content of the soil sample is obviously higher than that of dry lands, and therefore, the soil spectral curve is similar to that of the water body;
step S1.2.2, calculating a spectrum curve;
through selecting samples, for each type of land coverage, selecting more than 800 pure samples from three regions through manual digitization, calculating the mean value of the samples in each wave band by utilizing ENVI5.3 software, and constructing the spectrum curve of each sample, so that the obtained spectrum curve is more practical and convenient for subsequent analysis and calculation, and the obtained ground feature spectrum curve is shown in figure 4;
step S1.2.3, analyzing the spectral feature of the surface feature
The spectral reflectance curve analysis of the four basic characteristics can show that from the near infrared to the SWIR2 wave band, water bodies and vegetations have obvious downward trends, and the impervious surface has no obvious change trend, so that the difference of the water content of the land features can be distinguished by utilizing the two wave bands. The SWPI inversion result shows that the ecological index can better reflect the spatial difference of the surface water content, the spectral curve change trend of a sample is observed through the spectral reflectivity curve analysis of the sample, the SPWI ecological index is constructed through effective wave band operation, the ENVI5.3 software is utilized, a wave band calculation method is adopted, the basic index is inverted according to each index formula, and the formula specifically comprises the following steps:
Figure BDA0003073465940000111
wherein, B2 is a blue light wave band, B5 is a near infrared wave band, and B7 is a second short wave infrared wave band.
In this embodiment: the water ecological elements comprise two ecological indexes of SPWI and NDLI, and the expression of NDLI is as follows:
Figure BDA0003073465940000112
wherein, B3 is a green light wave band, B4 is a red light wave band, and B6 is a first short wave infrared wave band.
In this embodiment: the thermal environment comprises a surface temperature index, the surface temperature index is inverted by using a radiation transmission equation method, and the inversion process comprises the following steps:
thermal infrared radiation brightness value L received by satellite sensorzThe expression (c) can be written as (radiation transport equation):
Lz＝[εB(Ts)+(1-ε)Ld]τ+Luwherein ε is the ground surface emissivity, TsIs the true surface temperature (K), B (T)s) Is the black body heat radiation brightness, and tau is the transmission rate of the atmosphere in the thermal infrared band. The radiant brightness B (T) of the black body in the thermal infrared bands) Comprises the following steps:
B(Ts)＝[Lz-Lu-τ(1-ε)Ld]/τε
obtaining the actual surface temperature T by using the function of Planck formulas：
Ts＝K2/ln(K1/B(Ts)+1)
Wherein K1、K2A specific thermal conversion coefficient for the thermal infrared band.
Wherein the surface coverage type includes both RVI and NDSI indicators. The expressions are respectively:
Figure BDA0003073465940000121
wherein B4 is red light wave band, B5 is near infrared wave band.
Figure BDA0003073465940000122
Wherein B5 is near infrared band, B6 is first short wave infrared band.
In this embodiment: the smaller the information entropy of the ecological index in step S2.1 is, the higher the weight is, according to the basic theory of information, the information entropy is an index for measuring the degree of disorder of the system, and may represent the difference of information amount between different systems, and if the information entropy of the index is smaller, the larger the information amount provided by the index is, the larger the effect in the comprehensive evaluation is, the higher the weight is, and the calculation process specifically is that of the ecological index:
Figure BDA0003073465940000123
Figure BDA0003073465940000124
wherein f isijRepresents the ratio of the gray value of the ith pixel of the jth ecological index to the total gray value, xijRepresenting the gray value of the ith pixel of the jth index,
Figure BDA0003073465940000131
the sum of the gray values representing the j-th index, ejThe information entropy of the j-th index is represented.
Figure BDA0003073465940000132
Wherein wjIs shown asWeights of j ecological indicators.
In this embodiment: the multi-index fusion calculation mode in step S2.3 is,
WBEI＝w1×NDLI+w2×RVI+w3×SPWI-w4×LST-w5×NDSI，
wherein WBEI is ecological index based on water ecological benefit, i.e. fusion result, w1、w2、w3、w4、w5Respectively, represent weights calculated from the entropies of NDLI, RVI, SPWI, LST, NDSI.
In the present invention: SPWI to describe the spatial distribution of water ecological elements in combination with a normalized latent heat index; NDLI represents the ecological benefit brought by water ecological elements; on the basis, the invention also selects a ratio vegetation index of RVI, a normalized soil index of NDSI and a surface temperature of LST; WBEI to represent the ecological index of water ecological benefit.
The above description is only for the purpose of illustrating the present invention and is not intended to limit the scope of the present invention, and any person skilled in the art can substitute or change the technical solution of the present invention and its conception within the scope of the present invention.

Claims (3)

1. An ecological environment quality evaluation method based on water ecological benefits is characterized in that: the method comprises the following steps:
step S1, constructing ecological environment evaluation indexes through the structure and function of the ecological environment, wherein the ecological environment evaluation indexes specifically comprise the following steps:
s1.1, preprocessing an urban remote sensing image, wherein the preprocessing comprises radiation correction, image splicing and cutting;
s1.2, analyzing the structural elements and the functional elements of the ecological environment, and constructing an ecological environment evaluation index;
s1.3, inverting corresponding indexes according to the selected ecological environment evaluation indexes;
step S2, multi-index fusion based on entropy, the specific process comprises the following steps:
s2.1, calculating the information entropy of each ecological index, and giving weight to each ecological index according to the size of the information entropy;
s2.2, performing normalization processing on the same indexes obtained from data of different years in the same value range to realize dimensional unification of the indexes;
s2.3, determining the positive and negative effects of the indexes on the overall ecological environment, and completing multi-index fusion in a linear weighting mode;
the ecological indexes in the step S1.2 are divided into three categories of water ecological elements, thermal environments and earth surface coverage types;
the spatial distribution of the water ecological elements is expressed by constructing SPWI, and the specific steps of the SPWI construction are as follows:
s1.2.1, checking samples, and selecting pure end members;
step S1.2.2, calculating a spectrum curve;
step S1.2.3, analyzing the spectral characteristics of the ground objects;
through the spectral reflectance curve analysis of a sample, the spectral curve variation trend of the sample is observed, the SPWI index is constructed through effective band operation, and the index inversion formula is specifically as follows:
Figure FDA0003383212370000021
wherein B2 is a blue light waveband, B5 is a near infrared waveband, and B7 is a second short wave infrared waveband;
the water ecological elements comprise two ecological indexes of SPWI and NDLI, and the expression of NDLI is as follows:
Figure FDA0003383212370000022
wherein, B3 is a green light wave band, B4 is a red light wave band, and B6 is a first short wave infrared wave band;
in the step S2.1, the smaller the information entropy of the ecological index is, the higher the weight is, and the information entropy calculation process of the ecological index specifically includes:
Figure FDA0003383212370000023
Figure FDA0003383212370000024
wherein f isijRepresents the ratio of the gray value of the ith pixel of the jth ecological index to the total gray value, xijRepresenting the gray value of the ith pixel of the jth index,
Figure FDA0003383212370000025
the sum of the gray values representing the j-th index, ejInformation entropy representing the j index;
Figure FDA0003383212370000031
wherein wjRepresents the weight of the j ecological index.
2. The ecological environment quality evaluation method based on water ecological benefit according to claim 1, characterized in that: the thermal environment comprises a surface temperature index, the surface temperature index is inverted by adopting a radiation transmission equation method, and the inversion process comprises the following steps:
thermal infrared radiation brightness value L received by satellite sensorzThe expression (c) can be written as (radiation transport equation):
Lz＝[εB(Ts)+(1-E)Ld]τ+Lu
wherein ε is the ground surface emissivity, TsIs the true surface temperature (K), B (T)s) The black body thermal radiation brightness is shown, and tau is the transmittance of the atmosphere in a thermal infrared band; the radiant brightness B (T) of the black body in the thermal infrared bands) Comprises the following steps:
B(Ts)＝[Lz-Ku-τ(1-ε)Ld]/τε
obtaining the actual surface temperature T by using the function of Planck formulas：
Ts＝K2/ln(K1/B(Ts)+1)
Wherein K1、K2A thermal conversion coefficient specific to a thermal infrared band;
the surface coverage type comprises RVI and NDSI, and the expressions are respectively:
Figure FDA0003383212370000041
wherein B4 is a red light wave band, and B5 is a near infrared wave band;
Figure FDA0003383212370000042
wherein B5 is near infrared band, B6 is first short wave infrared band.
3. The ecological environment quality evaluation method based on water ecological benefit according to claim 1, characterized in that: the multi-index fusion calculation mode in step S2.3 is,
WBEI＝w1×NDLI+w2×RVI+w3×SPWI-w4×LST-w5×NDSI
wherein WBEI is ecological index based on water ecological benefit, i.e. fusion result, w1、w2、w3、w4、w5Respectively, represent weights calculated from the entropies of NDLI, RVI, SPWI, LST, NDSI.
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