CN108537439A - A kind of multiple dimensioned landscape pattern in basin and water quality index relationship research method - Google Patents
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Abstract
本发明公开了一种基于遥感影像数据的流域多尺度景观格局与水质指标关系研究方法，该方法包括1)利用多光谱遥感影像与高分辨率遥感影像，融合“图谱”特征提取流域景观源汇格局信息；2)基于数字高程模型数据(DEM)与土地利用分类数据，在划分流域最小水文响应单元后，计算改进后的景观空间负荷对比指数；3)通过分别计算景观格局指数、水质指标的Spearman相关系数，构建全面且冗余度低的景观格局指数体系与水质指标体系；4)利用多变量分析与典范对应分析方法，分别在多时空尺度下研究景观格局指数与水质指标的关系。本发明通过改进一种景观指数，并在后续的分析中考虑时空等尺度对景观格局与非点源污染关系过程的影响，使得分析结果更具生态学效应，有效解决了传统分析方法在分析二者关系时最佳研究尺度不确定的问题。The invention discloses a method for researching the relationship between watershed multi-scale landscape patterns and water quality indicators based on remote sensing image data. The method includes 1) using multi-spectral remote sensing images and high-resolution remote sensing images, and fusing "atlas" features to extract watershed landscape sources and sinks pattern information; 2) Based on the digital elevation model data (DEM) and land use classification data, after dividing the minimum hydrological response unit of the watershed, calculate the improved landscape space load comparison index; 3) calculate the landscape pattern index and water quality index respectively Spearman correlation coefficient, to construct a comprehensive and low-redundancy landscape pattern index system and water quality index system; 4) Using multivariate analysis and canonical correspondence analysis methods, study the relationship between landscape pattern index and water quality indicators at multiple temporal and spatial scales. The present invention improves a landscape index and considers the impact of time and space on the relationship process between landscape pattern and non-point source pollution in the follow-up analysis, so that the analysis results have more ecological effects and effectively solve the problem of traditional analysis methods in the second analysis. The optimal research scale is uncertain when the relationship between
Description
技术领域technical field
本发明涉及遥感技术与景观生态学技术领域，具体来说，涉及一种基于遥感技术的流域多尺度景观格局与水质指标关系研究方法。The invention relates to the technical fields of remote sensing technology and landscape ecology, in particular to a method for researching the relationship between multi-scale landscape patterns and water quality indicators in a watershed based on remote sensing technology.
背景技术Background technique
流域的空间异质特性决定了景观结构复杂性，融合“图-谱”特征信息的互补优势，能够最大程度提升流域非点源污染景观源汇格局关键区提取的精准度和智能性。结合非点源污染生态过程，非点源污染物由产生地随地表径流等过程汇集到水体的过程中要经过不同的源汇类型景观格局，因此景观格局的源汇类型组成、空间结构及排列方式等势必会影响非点源污染物的传输，进而影响水质质量。流域在面对农业污染物质排放受到集约化农业发展的压力，难以实现减量的社会经济发展条件下，需要在流域非点源污染景观源汇格局空间结构及其配置对水质影响关系方面定量化科学理论与方法支持。现有的景观格局研究中，景观指数的计算结果不具备生态学意义，相比于网格化的源汇类型数据，以一个数值计算结果来反映研究尺度下的景观格局特点是不具备说服力的，究其根本，传统景观指数的计算结果不具备空间差异性。除此之外，现有的研究往往忽视景观格局与水质指标关系中的尺度效应，不同研究尺度下，景观格局对某类或某几类水质指标的作用会有显著差异。基于此的景观格局与水质指标关系研究结果必将存在一系列的问题The spatial heterogeneity of the watershed determines the complexity of the landscape structure. Combining the complementary advantages of "map-spectrum" feature information can maximize the accuracy and intelligence of key area extraction for the source-sink pattern of the non-point source pollution landscape in the watershed. Combined with the ecological process of non-point source pollution, non-point source pollutants must pass through different source-sink types of landscape patterns in the process of collecting non-point source pollutants from the place of generation to the water body through processes such as surface runoff. Therefore, the source-sink type composition, spatial structure and arrangement of the landscape pattern The way and so on will inevitably affect the transmission of non-point source pollutants, and then affect the water quality. Under the social and economic development conditions where agricultural pollutant emissions are under the pressure of intensive agricultural development and it is difficult to achieve reduction, it is necessary to quantify the relationship between the spatial structure of the source-sink pattern of the non-point source pollution landscape in the basin and its configuration on water quality. Scientific theory and method support. In the existing landscape pattern research, the calculation results of the landscape index do not have ecological significance. Compared with the gridded source-sink type data, it is not convincing to use a numerical calculation result to reflect the characteristics of the landscape pattern at the research scale. Basically, the calculation results of the traditional landscape index do not have spatial differences. In addition, existing research often ignores the scale effect in the relationship between landscape pattern and water quality indicators. Under different research scales, the effect of landscape pattern on certain types or several types of water quality indicators will be significantly different. There must be a series of problems in the research results of the relationship between landscape pattern and water quality indicators based on this.
发明内容Contents of the invention
针对相关技术中的上述技术问题，本发明提出了一种基于遥感技术的流域多尺度景观格局与水质指标关系研究方法，有效解决了传统分析方法在分析二者关系时最佳研究尺度不确定的问题。利用多光谱遥感影像与高分辨率遥感影像提取地表源汇类型信息，利用DEM数据与地表土地利用数据划分最小水文响应单元，在计算基于最小水文响应单元的景观空间负荷对比指数的基础上，利用秩分析方法构建全面且冗余度低的景观指数与水质指标体系，最后采用多变量相关分析与典范对应分析方法在不同的时空尺度下分析景观格局指数与水质指标间的相关关系。Aiming at the above-mentioned technical problems in related technologies, the present invention proposes a method for researching the relationship between multi-scale landscape patterns and water quality indicators based on remote sensing technology, which effectively solves the problem of uncertain optimal research scales when analyzing the relationship between the two in traditional analysis methods. question. Use multi-spectral remote sensing images and high-resolution remote sensing images to extract surface source-sink type information, use DEM data and surface land use data to divide the minimum hydrological response unit, and calculate the landscape space load contrast index based on the minimum hydrological response unit. The rank analysis method was used to construct a comprehensive and low-redundancy landscape index and water quality index system. Finally, multivariate correlation analysis and canonical correspondence analysis were used to analyze the correlation between landscape pattern index and water quality index at different spatial and temporal scales.
为实现上述技术目的，本发明的技术方案是这样实现的：For realizing above-mentioned technical purpose, technical scheme of the present invention is realized like this:
一种基于遥感技术的流域多尺度景观格局与水质指标关系研究方法，包括以下步骤：A method for researching the relationship between watershed multi-scale landscape patterns and water quality indicators based on remote sensing technology, comprising the following steps:
步骤S1，融合“图谱”特征的流域景观源汇格局信息提取；Step S1, extracting the source-sink pattern information of the watershed landscape combined with the "map" feature;
步骤S2，所述基于最小水文单元的景观空间负荷对比指数计算；Step S2, the calculation of the landscape space load contrast index based on the minimum hydrological unit;
步骤S3，所述景观格局指数与水质指标体系构建，用于构建全面且冗余度低的景观指数体系与水质指标体系；Step S3, constructing the landscape pattern index and water quality index system, which is used to construct a comprehensive and low-redundancy landscape index system and water quality index system;
步骤S4，所述景观格局指数与水质指标选取模块和景观格局指数与水质指标关系研究；Step S4, said landscape pattern index and water quality index selection module and research on the relationship between landscape pattern index and water quality index;
进一步的，步骤S1包括：Further, step S1 includes:
(1)遥感影像“图谱”特征提取，用于对高空间分辨率卫星影像的形状、纹理特征提取以及对中分辨率多光谱卫星影像的光谱波段信息提取工作；(1) Feature extraction of "atlas" of remote sensing images, which is used to extract the shape and texture features of high-spatial-resolution satellite images and the spectral band information extraction of medium-resolution multi-spectral satellite images;
(2)融合“图谱”特征的景观类型提取，用于根据不同景观特有的形状、纹理信息以及在不同波段反射率的变化来区分进而提取景观源汇类型信息；(2) Landscape type extraction that integrates "atlas" features, which are used to distinguish and extract landscape source and sink type information based on the unique shape and texture information of different landscapes and changes in reflectivity in different bands;
进一步的，步骤S2包括：Further, step S2 includes:
(1)最小水文响应单元划分，用于划分指数计算的最小研究尺度；(1) The minimum hydrological response unit division, which is used to divide the minimum research scale for index calculation;
(2)源汇景观类型修正及地理影响因素修正，用于衡量非点源污染物在流域内传输时受到地理因素的影响程度；(2) Source-sink landscape type correction and geographical influence factor correction, which are used to measure the degree to which non-point source pollutants are affected by geographical factors when they are transported within the watershed;
(3)景观空间负荷对比指数计算公式表示为：(3) The calculation formula of landscape space load contrast index is expressed as:
HRULCIi＝Wi*Ai HRULCI i =W i *A i
其中，i表示某一具体HRU，Ai表示该HRU的面积，Wi表示该HRU对非点源污染物的产生/抑制系数，Wi受土地利用方式、土壤性质、降水量以及化肥施用量等的影响，考虑非点源污染物由HRU产生/衰减并最终进入水体的过程，需对不同地理因素进行修正，Wi可表示为：Among them, i represents a specific HRU, Ai represents the area of the HRU, Wi represents the generation/inhibition coefficient of the HRU to non-point source pollutants, and Wi is affected by land use, soil properties, precipitation, and fertilizer application, etc. , considering the process of non-point source pollutants being generated/attenuated by HRU and finally entering the water body, different geographical factors need to be corrected, Wi can be expressed as:
Wi＝F(L,P,R,D,N,S,F,A)W i =F(L,P,R,D,N,S,F,A)
其中，L代表土地利用类型修正系数，P代表坡度修正系数，R代表年均降水量修正系数，D代表距离因素修正系数，N代表NDVI修正系数，S代表土壤质地修正系数，F代表化肥施用量修正系数，A代表土壤有效含水量的修正系数。Among them, L represents the correction coefficient of land use type, P represents the correction coefficient of slope, R represents the correction coefficient of annual average precipitation, D represents the correction coefficient of distance factor, N represents the correction coefficient of NDVI, S represents the correction coefficient of soil texture, and F represents the amount of fertilizer application Correction coefficient, A represents the correction coefficient of soil effective water content.
同时，为使不同HRU之间的空间负荷对比指数可以比较，对不同景观源汇类型的污染物修正系数进行标准化处理，即：At the same time, in order to make the spatial load comparison index between different HRUs comparable, the pollutant correction coefficients of different landscape source and sink types were standardized, namely:
其中Wi是某种土地利用景观的非点源污染物修正系数，WMAX是指流域景观内土地利用景观下非点源污染物修正系数的最大值。若HRU中有多种非点源污染物，则：Among them, Wi is the non-point source pollutant correction coefficient of a certain land use landscape, and WMAX refers to the maximum value of the non-point source pollutant correction coefficient under the land use landscape in the watershed landscape. If there are multiple non-point source pollutants in the HRU, then:
HRULCIXY＝HRULCIX+HRULCIY HRULCI XY = HRULCI X + HRULCI Y
其中，HRULCIY是非点源污染物Y在HRU中的景观负荷指数，HRULCIXY是污染物X和Y在HRU中的景观负荷指数总和。Among them, HRULCIY is the landscape load index of non-point source pollutant Y in HRU, and HRULCIXY is the sum of landscape load indices of pollutants X and Y in HRU.
对于子流域，非点源污染景观负荷指数的计算表示为：For sub-watersheds, the calculation of non-point source pollution landscape load index is expressed as:
其中N代表子流域中景观类型为源景观的HRU总数目，i代表HRU。Among them, N represents the total number of HRUs whose landscape type is the source landscape in the sub-basin, and i represents the HRUs.
进一步的，步骤S4包括：Further, step S4 includes:
(1)多时空研究尺度选择，用于根据研究区源汇景观及水文时期特点，选择具有代表性的时间尺度(植被关键物候期)和空间尺度(流域尺度、集水区尺度、缓冲区尺度)作为关系研究的研究尺度；(1) Multi-temporal and spatial research scale selection, used to select representative time scales (vegetation key phenological periods) and spatial scales (watershed scale, catchment scale, buffer zone scale) according to the characteristics of the source-sink landscape and hydrological periods in the study area ) as a research scale for relational research;
(2)景观格局指数体系与水文指标体关系分析，用于在多时空尺度下研究两者间的相关关系。(2) Analysis of the relationship between the landscape pattern index system and the hydrological index body, which is used to study the correlation between the two at multiple temporal and spatial scales.
采用上述技术方案后，本发明的有益效果：景观格局与水质指标的关系研究是遥感技术在流域非点源污染生态过程研究中的重要应用，考虑生态过程的尺度效应，研究在不同时空尺度下景观格局对水质指标的关系有助于选取研究的最佳尺度。本发明针对非点源污染时空差异性大的特点，改进了景观空间负荷对比指数，适用于各种尺度下的流域研究，其中景观格局指数与水质指标的构建环节解决了指标间冗余度高这一问题。本发明有助于优化流域内非点源污染景观源汇格局，同时对流域内生态评价及非点源污染防控具有重要意义。After adopting the above-mentioned technical scheme, the beneficial effect of the present invention is that the research on the relationship between the landscape pattern and the water quality index is an important application of remote sensing technology in the research on the ecological process of non-point source pollution in the watershed. Considering the scale effect of the ecological process, the research can be carried out under different temporal and spatial scales. The relationship between landscape pattern and water quality indicators is helpful to select the optimal scale for research. Aiming at the characteristics of large temporal and spatial differences in non-point source pollution, the present invention improves the landscape space load comparison index, which is applicable to watershed research at various scales, and the construction link of landscape pattern index and water quality index solves the high redundancy between indexes this problem. The invention helps to optimize the source-sink pattern of the non-point source pollution landscape in the watershed, and at the same time has great significance for the ecological evaluation and the prevention and control of the non-point source pollution in the watershed.
具体实施方式Detailed ways
下面将对本发明实施例中的技术方案进行清楚、完整地描述。基于本发明中的实施例，本领域普通技术人员所获得的所有其他实施例，都属于本发明保护的范围。本发明提出的一种基于遥感技术的流域多尺度景观格局与水质指标关系研究方法，技术方案是这样实现的：The technical solutions in the embodiments of the present invention will be clearly and completely described below. All other embodiments obtained by persons of ordinary skill in the art based on the embodiments of the present invention belong to the protection scope of the present invention. The present invention proposes a method for researching the relationship between watershed multi-scale landscape patterns and water quality indicators based on remote sensing technology, and the technical solution is realized in this way:
一种基于遥感技术的流域多尺度景观格局与水质指标关系研究方法，包括以下步骤：A method for researching the relationship between watershed multi-scale landscape patterns and water quality indicators based on remote sensing technology, comprising the following steps:
步骤S1，融合“图谱”特征的流域景观源汇格局信息提取；Step S1, extracting the source-sink pattern information of the watershed landscape combined with the "map" feature;
步骤S2，所述基于最小水文单元的景观空间负荷对比指数计算；Step S2, the calculation of the landscape space load contrast index based on the minimum hydrological unit;
步骤S3，所述景观格局指数与水质指标体系构建，用于构建全面且冗余度低的景观指数体系与水质指标体系；Step S3, constructing the landscape pattern index and water quality index system, which is used to construct a comprehensive and low-redundancy landscape index system and water quality index system;
步骤S4，所述景观格局指数与水质指标选取模块和景观格局指数与水质指标关系研究；Step S4, said landscape pattern index and water quality index selection module and research on the relationship between landscape pattern index and water quality index;
进一步的，步骤S1包括：Further, step S1 includes:
(1)遥感影像“图谱”特征提取，用于对高空间分辨率卫星影像的形状、纹理特征提取以及对中分辨率多光谱卫星影像的光谱波段信息提取工作；(1) Feature extraction of "atlas" of remote sensing images, which is used to extract the shape and texture features of high-spatial-resolution satellite images and the spectral band information extraction of medium-resolution multi-spectral satellite images;
(2)融合“图谱”特征的景观类型提取，用于根据不同景观特有的形状、纹理信息以及在不同波段反射率的变化来区分进而提取景观源汇类型信息；(2) Landscape type extraction that integrates "atlas" features, which are used to distinguish and extract landscape source and sink type information based on the unique shape and texture information of different landscapes and changes in reflectivity in different bands;
进一步的，步骤S2包括：Further, step S2 includes:
(1)最小水文响应单元划分，用于划分指数计算的最小研究尺度；(1) The minimum hydrological response unit division, which is used to divide the minimum research scale for index calculation;
(2)源汇景观类型修正及地理影响因素修正，用于衡量非点源污染物在流域内传输时受到地理因素的影响程度；(2) Source-sink landscape type correction and geographical influence factor correction, which are used to measure the degree to which non-point source pollutants are affected by geographical factors when they are transported within the watershed;
(3)景观空间负荷对比指数计算公式表示为：(3) The calculation formula of landscape space load contrast index is expressed as:
HRULCIi＝Wi*Ai HRULCI i =W i *A i
其中，i表示某一具体HRU，Ai表示该HRU的面积，Wi表示该HRU对非点源污染物的产生/抑制系数，Wi受土地利用方式、土壤性质、降水量以及化肥施用量等的影响，考虑非点源污染物由HRU产生/衰减并最终进入水体的过程，需对不同地理因素进行修正，Wi可表示为：Among them, i represents a specific HRU, Ai represents the area of the HRU, Wi represents the generation/inhibition coefficient of the HRU to non-point source pollutants, and Wi is affected by land use, soil properties, precipitation, and fertilizer application, etc. , considering the process of non-point source pollutants being generated/attenuated by HRU and finally entering the water body, different geographical factors need to be corrected, Wi can be expressed as:
Wi＝F(L,P,R,D,N,S,F,A)W i =F(L,P,R,D,N,S,F,A)
其中，L代表土地利用类型修正系数，P代表坡度修正系数，R代表年均降水量修正系数，D代表距离因素修正系数，N代表NDVI修正系数，S代表土壤质地修正系数，F代表化肥施用量修正系数，A代表土壤有效含水量的修正系数。Among them, L represents the correction coefficient of land use type, P represents the correction coefficient of slope, R represents the correction coefficient of annual average precipitation, D represents the correction coefficient of distance factor, N represents the correction coefficient of NDVI, S represents the correction coefficient of soil texture, and F represents the amount of fertilizer application Correction coefficient, A represents the correction coefficient of soil effective water content.
同时，为使不同HRU之间的空间负荷对比指数可以比较，对不同景观源汇类型的污染物修正系数进行标准化处理，即：At the same time, in order to make the spatial load comparison index between different HRUs comparable, the pollutant correction coefficients of different landscape source and sink types were standardized, namely:
其中Wi是某种土地利用景观的非点源污染物修正系数，WMAX是指流域景观内土地利用景观下非点源污染物修正系数的最大值。若HRU中有多种非点源污染物，则：Among them, Wi is the non-point source pollutant correction coefficient of a certain land use landscape, and WMAX refers to the maximum value of the non-point source pollutant correction coefficient under the land use landscape in the watershed landscape. If there are multiple non-point source pollutants in the HRU, then:
HRULCIXY＝HRULCIX+HRULCIY HRULCI XY = HRULCI X + HRULCI Y
其中，HRULCIY是非点源污染物Y在HRU中的景观负荷指数，HRULCIXY是污染物X和Y在HRU中的景观负荷指数总和。Among them, HRULCIY is the landscape load index of non-point source pollutant Y in HRU, and HRULCIXY is the sum of landscape load indices of pollutants X and Y in HRU.
对于子流域，非点源污染景观负荷指数的计算表示为：For sub-watersheds, the calculation of non-point source pollution landscape load index is expressed as:
其中N代表子流域中景观类型为源景观的HRU总数目，i代表HRU。Among them, N represents the total number of HRUs whose landscape type is the source landscape in the sub-basin, and i represents the HRUs.
进一步的，步骤S4包括：Further, step S4 includes:
(1)多时空研究尺度选择，用于根据研究区源汇景观及水文时期特点，选择具有代表性的时间尺度(植被关键物候期)和空间尺度(流域尺度、集水区尺度、缓冲区尺度)作为关系研究的研究尺度；(1) Multi-temporal and spatial research scale selection, used to select representative time scales (vegetation key phenological periods) and spatial scales (watershed scale, catchment scale, buffer zone scale) according to the characteristics of the source-sink landscape and hydrological periods in the study area ) as a research scale for relational research;
(2)景观格局指数体系与水文指标体关系分析，用于在多时空尺度下研究两者间的相关关系。(2) Analysis of the relationship between the landscape pattern index system and the hydrological index body, which is used to study the correlation between the two at multiple temporal and spatial scales.
以上所述仅为本发明的较佳实施例而已，并不用以限制本发明，凡在本发明的精神和原则之内，所作的任何修改、等同替换、改进等，均应包含在本发明的保护范围之内。The above descriptions are only preferred embodiments of the present invention, and are not intended to limit the present invention. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present invention shall be included in the scope of the present invention. within the scope of protection.
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