INTRODUCTION

Landscape metrics based on category, patch, and class representations developed in late 80’s are quantitative spatial measures of landscape pattern exhibiting variations in spatial characteristics ([1], [2], [3], [4], [5]). These metrics interpret and quantify geometric properties of a landscape and have been extensively used in landscape ecology [3]. These metrics are now finding their practical applications in the regional planning ([6], [7], [8], [9]) and monitoring ([10], [11], [12], [13], [14], [15]) of landscapes. Spatial characteristics of a landscape [1] are quantified as numeric through metrics and are interpreted, compared with the various ground data and investigating it further for diverse landscape. However, these exercises are without considering the spatial resolution and its effect in quantification of metrics. Spatial metrics bring out the pattern of change in a particular landscape and needs to be understood considering all aspects to understand the process ([16], [17]) as spatial metrics behave differently with different pattern of landscape [3].  Uuemaa et al., 2009 provides an account of spatial metrics and their relationships in the landscape planning and other activities.

Landscape metrics have been increasingly applied in understanding landscape dynamics with adequate explanations of the underlying processes. Aggregation Index, cohesion index, etc. are new indices being evaluated and considered [19] and exploration is in progress to apply these metrics for various purposes to link with the current scenarios. DPSIR (Driving force–pressure–state–impacts–response) approach [9] was used to evaluate the land use changes and related environmental impacts that have occurred in recent decades by integrating  the analytical and operational approaches with help of metrics to pursue sustainable management. Peng et al., [20] evaluated the effectiveness of landscape metrics in quantifying spatial patterns of 36 simulated landscapes as sample space through 23 widely used landscape metrics with the application of the multivariate linear regression analysis. The results highlight that metrics are effective in quantifying several components of spatial patterns.

Li et al., [21] examined landscape metrics based on its functions as landscape and class level metrics. 19 landscape level metrics and 17 class level metrics have been tried using five data sets and establish the factors that describe landscape dynamics. The resolution and scale are the two crucial factors considered in the landscape analysis, which are being explored among many factors ([22], [10], [23], [24], [25], [26]; [27]). The analysis of effectiveness of spatial resolution on various landscape fragmentation indices, state that spatial resolution, might have a role in analysing and understanding landscape patterns [28]. The integrity of the analysis of landscape depends on the selection of appropriate spatial metrics, the resolution of spatial data apart from careful interpretation of the results ([29], [21]). This communication analyses the role of the spatial resolution in quantifying the real world scenario.