On the effects of spatial resolution on effective distance measurement in digital landscapes

作     者：Rachel Mundeli Murekatete Takeshi Shirabe 

作者机构：KTH Royal Institute of TechnologySchool of Architecture and the Built EnvironmentTeknikringen 10A11428 StockholmSweden University of RwandaCollege of Science and TechnologyCentre for Geographic Information Systems and Remote SensingKN 67 Street NyarugengeKigaliRwanda 

出 版 物：《Ecological Processes》 (生态过程（英文）)

年 卷 期：2021年第10卷第1期

页      面：659-677页

核心收录：

学科分类：0710[理学-生物学] 0830[工学-环境科学与工程（可授工学、理学、农学学位）] 07[理学] 0815[工学-水利工程] 0713[理学-生态学] 

基　　金：This work was part of the doctoral study of Rachel Mundeli Murekatete,which was supported by the Swedish International Development Cooperation Agency(Sida)(grant number:51160059-06) This work was also part of the research project“Drawing with Geography”,which was fully supported by the Swedish Research Council for Sustainable Development Formas(grant number:942-2015-1513). 

主　　题：Landscape connectivity Effective distance Raster-based least-cost path model Accuracy Spatial resolution 

摘      要：Background:Connectivity is an important landscape attribute in ecological studies and conservation practices and is often expressed in terms of effective distance.If the cost of movement of an organism over a landscape is effectively represented by a raster surface,effective distances can be equated with the cost-weighted distance of least-cost paths.It is generally recognized that this measure is sensitive to the grid’s cell size,but little is known if it is always sensitive in the same way and to the same degree and if not,what makes it more(or less)sensitive.We conducted computational experiments with both synthetic and real landscape data,in which we generated and analyzed large samples of effective distances measured on cost surfaces of varying cell sizes derived from those data.The particular focus was on the statistical behavior of the ratio—referred to as‘accuracy indicator’—of the effective distance measured on a lower-resolution cost surface to that measured on a higher-resolution cost surface.Results:In the experiment with synthetic cost surfaces,the sample values of the accuracy indicator were generally clustered around 1,but slightly greater with the absence of linear sequences(or barriers)of high-cost or inadmissible cells and smaller with the presence of such sequences.The latter tendency was more dominant,and both tendencies became more pronounced as the difference between the spatial resolutions of the associated cost surfaces increased.When two real satellite images(of different resolutions with fairly large discrepancies)were used as the basis of cost estimation,the variation of the accuracy indicator was found to be substantially large in the vicinity(1500 m)of the source but decreases quickly with an increase in distance from it.Conclusions:Effective distances measured on lower-resolution cost surfaces are generally highly correlated with—and useful predictors of—effective distances measured on higher-resolution cost surfaces.This relationship tends to be weakened when linear barriers to dispersal(e.g.,roads and rivers)exist,but strengthened when moving away from sources of dispersal and/or when linear barriers(if any)are detected by other presumably more accessible and affordable sources such as vector line data.Thus,if benefits of high-resolution data are not likely to substantially outweigh their costs,the use of lower resolution data is worth considering as a cost-effective alternative in the application of least-cost path modeling to landscape connectivity analysis.