Responses of landscape metrics to altering grain size in the Three Gorges Reservoir landscape in China

Abstract

Quantifying the response of landscape metrics to an altering observation scale is crucial to understanding environmental changes and managing ecosystem services. Whereas the scaling behaviors of landscape metrics in spatial heterogeneity analysis have been well identified by previous research, there remains a need to examine these effects in areas undergoing rapid change. Here, we aim to reveal the landscape scale effect in the Three Gorges Reservoir (TGR) area, China, using a case study on Zigui County. We applied a suite of common landscape metrics (12 indices at the class level and 17 indices at the landscape level) to characterize the landscape pattern and examine the response of the metrics to altering grain size using a series of land-use/land-cover data with gradient resolutions. The results reveal that significant scale effects exist in most pattern metrics in the TGR landscape. In addition, the different responses to the altering grain size occurred with different landscape metrics and various land-use/landcover types. With respect to changing grain size, all of the selected pattern metrics at the landscape level displayed high or medium sensitivity in response to changing grain size except the Fractal Dimension Index and the landscapediversity indices. The behavior of the metrics in response to altering grain size can be grouped into four types (Type 1, Type 2, Type 3, and Type 4). The class-level metrics with high sensitivity were Mean Patch Size, the Contiguity Index, the Euclidean Nearest-Neighbor Distance, the Perimeter-Area Ratio, and Patch Density for all landuse/land-cover types, whereas low sensitivities were detected in the response of the Fractal Dimension Index and the Largest Patch Index. Based on the response to the altering resolution of input data, the class-level metrics could be grouped into three types (Type a, Type b, and Type c). Considering the scaling behavior of landscape metrics, we suggest using a set of suitable remote-sensing images to quantify the landscape pattern in the TGR landscape and similar areas.

Landscape Grain Effect in Yancheng Coastal Wetland and Its Response to Landscape Changes

“…Only one landscape index (PR) was insensitive to the grain changes. Our conclusions were similar with the conclusions derived by Chen et al [52] and Teng et al [45]. In summary, area-edge indexes and shape indexes were more sensitive to the grain changes.…”

“…CV was used to reflect responses and sensitivity of different landscape indexes to grains. With reference to previous studies [45,52], response sensitivity was divided into five levels according to different numerical values of CV, namely, response insensitivity (CV ≤ 1%), weak response sensitivity (1% < CV ≤ 10%), moderate response sensitivity (10% < CV ≤ 50%), strong response sensitivity (50% < CV ≤ 100%), and extremely strong response sensitivity (CV > 100%).…”

“…Therefore, studying landscape pattern characteristics under different grains and dynamic analysis of responses of the grain effect to landscape changes at different time points are of important significance. Currently, there are universal static studies on grain effects [44,45]; dynamic studies on grain effects at different time points can supplement such studies to some extent. Moreover, a combination of dynamic studies at different scales with landscape area loss index can help to more objectively select an optimal grain for analysis.…”

Spatial Pattern Consistency among Different Remote-Sensing Land Cover Datasets: A Case Study in Northern Laos

“…Changes in the landscape scale may alter patch boundaries, divide or fuse patches, and may thus alter landscape patterns, leading to corresponding changes in the indices of these patterns [49,50]. The landscape pattern indices of each type of land cover data changed differently as the scale increased.…”

景观演化特征指数及其应用

“…)。景观斑块演变的主要类型包括： 新生、 消 亡、 生长、 收缩、 融合、 分裂和混合等 (O'Neill et al, 1988;Crist et al, 2000;Luck et al, 2002;陈 虹 等, 2008; 张阳阳等, 2010)。景观指数能描述特定时相 下景观的静态特征 (Manicacci et al, 1992;Doak et al, 1994;陈文波等, 2002;何鹏等, 2009;Teng et al, 2016)， 应用广泛 (Skinner, 1995;Ricotta et al, 1999;Smits et al, 1999;何原荣等, 2008;林孟龙等, 2008;游丽平等, 2008;高艳等, 2010) the infilling type, the edge-expansion type, and the outlying type, as well as for the isolated type, the adjacent type, and the surrounded type of urban shrinkage, and LEAI can perfectly reflect patch expansion/shrinkage intensity and landscape expansion/shrinkage direction; (2) Patch shrinkage of the hardened ground landscapes in the study area is clearly intensified. The recognition of shrinkage modes of these patches through LEPI can reveal the spatial distribution of urban ecological restoration and contribute to the construction of urban green infrastructure and residential land remediation;…”