Landscape ecology has generated much excitement in the past two decades. One reason was that it brought spatial analysis and modeling to the forefront of ecological research. However, high expectations for landscape analysis to improve our understanding and prediction of ecological processes have largely been unfulfilled. We identified three kinds of critical issues: conceptual flaws in landscape pattern analysis, inherent limitations of landscape indices, and improper use of pattern indices. For example, many landscape analyses treat quantitative description of spatial pattern as an end itself and fail to explore relationships between pattern and process. Landscape indices and map data are sometimes used without testing their ecological relevance, which may not only confound interpretation of results, but also lead to meaningless results. In addition, correlation analysis with indices is impeded by the lack of data because of difficulties in large-scale experimentation and by complicated behavior of indices as a result of their varying responses to changes in scale and spatial pattern. These problems represent significant challenges to landscape pattern analysis, especially in terms of relating pattern to process. In this perspective paper, we examine the underlying problems of these challenges and offer some solutions.

Landscape ecology is mainly based on the patch-corridor-matrix model. Although this model is efficient and has been successfully used in landscape ecology studies, but it is believed that this model cannot consider the continuous heterogeneity. This fact has encouraged researchers in the field to find new indicators for landscape analysis in a continuous framework. The aim of this study is a comparison of continuous and discrete indices in measuring Gorgan forest landscape fragmentation based on the moving window technique. This technique was performed on a classified map derived from SPOT satellite image in year 2010 using a maximum likelihood algorithm and on NDVI vegetation index from a Landsat satellite image of the year 2010. Window sizes were considered in 60, 90, 150 and 300 meters and six landscape class-level metrics were selected for the comparison including LPI, LSI, SPLIT, MESH, AI and PLAND. To assess the correlation between the output images of each of these metrics, the Spearman rank correlation coefficient was used. The results of the statistical comparisons of different window sizes showed that the values of the correlation coefficient were increased with increasing window size, as the high correlation values were seen when the window size was 300m belonging to PLAND and SPLIT metrics. All of the metrics had minimum correlation values in the window size 60m and the LSI metric had the lowest correlation (0.33).

Hot spots are often associated with places where an abnormal process has occurred. Accordingly, their identification can help experts and managers to scrutinize the state of health and sustainability, from an ecological point of view. The present study was therefore conducted to analyze the spatial autocorrelation and identify hot spots of 11 landscape metrics, the new Runoff Landscape Index (RLI), and its related factors in 28 watersheds of Ardabil province. The average positive values of the z score obtained from Moran's index indicate the presence of spatial correlation in the studied watersheds. In addition, the results of local Moran's showed that the landscape metrics have a structured spatial pattern and are not randomly distributed. A completely unipolar pattern was obtained for land cover factor (λC), soil factor (λK), and RLI. Furthermore, the negative values of the local Moran's index for the topographic factor (λS) proved the scattered pattern. Spatial distribution of hot and cold spots, using the Getis-Ord-Gi index, showed no significant pattern in the λC of Ahmadkandi, Akbardavod, Deru, Mashiran, Firozabad, Lai, Nir, and Hir watersheds. Cold spots were observed in the Eiril, Namin, and Nanehkaran watersheds at the 90% confidence level and the rest of watersheds had hot spots at a 95% confidence level. The RLIs of Ahmadkandi, Akbardavod, Deru, Mashiran, Firozabad, Lai, Nir, and Hir watersheds lack a significant pattern, and the rest of watersheds showed the hot spots at a 95% confidence level.

Development of remote sensing (RS) and GIS techniques and that of landscape metrics in the late 1980s have caused to introduce a new dimension in the landscape ecology arena (the relationship between spatial patterns and ecological processes). However, scale dependence of some of landscape metrics and RS systems of different spatial resolution has resulted in particular attention into selection of an appropriate scale in the landscape ecology studies and correct interpretation of ecological processes. Hence, the present study has investigated the behaviors of some landscape metrics in relation to changes in scale. Accordingly, the effects of the scale (pixel size and extent) on those landscape metrics which indicate trends of vegetation cover class was discussed applying Landsat images in Isfahan city and its surrounding (an area of ​​960 thousand hectares). For this purpose, behavior of NP, PD, LSI, MPS, ED, MNN, MSI and TCAI have studied through changing the size from 30 m to 60, 120, 240 and 480 and extent from 300 ha to 600, 1200, 2400 and 4800. The results of this study indicated sensitivity of these metrics except TCAI in relation to the scale factor. This type of studies and attention to the spatial scale have indicated that it could play an important role in identifying the impacts of ecological processes, predicting the ecological functions (landscape modeling) and reducing the uncertainty in landscape ecology studies.

Landscape is one of the main factors influencing hydrological processes of the watershed. Changes in structure and spatial pattern of land use play important role in surface runoff and sediment yield. Determining the relationship between landscape patterns and hydrological processes can be used as an indicator of watershed soil erosion and sediment yield. Therefore, due to the problems in field measurement of sediment yield, its estimation using landscape properties and land use pattern is an appropriate alternative for current estimation methods. The purpose of this research is to determine the relationship between watershed sediment yield and landscape metrics in the selected sub-watersheds of Golestan Province. To this end, suspended sediment concentration data for all hydrometric stations of the studied province were obtained from the relevant resources and appropriate sub-watersheds were selected. Then, using the land use map of Golestan Province, 15 landscape metrics related to sediment yield were determined for different land uses by Fragstats 4.2 software. In order to determine the relationship between watershed sediment yield and landscape metrics, a partial least squares regression was used which combines the methods of principal component analysis and multiple linear regression. The relative importance of landscape metrics was determined through examining the values of Variable Importance for the Projection (VIP) and Regression Coefficients (RCs). The results of this study indicated that the watershed sediment yield is densely associated with land use patterns. The main indices in reducing sediment yield were the Largest Patch Index (LPI), the average of the nearest neighbor distance (ENN-MN) and the average of perimeter-area ratio (PARA –MN) with values of VIPs of 1.296, 1.184 and 1.747,  and regression coefficients of -0.014, -0.039, and -0.002, respectively. The main indices in incrising sediment yield were Landscape Shape Index (LSI) and mean patch size (AREA-MN) with regression coefficients of 0.020 and 0.017, respectively. The landscape characteristics in watersheds could account for as much as 71% of the variation in sediment yield of watershed. The results of study showed that the landscape characteristics can be used for watershed sediment yield modeling.

Urban societies are complex landscapes that face unbalanced and exogenous growth and are rapidly changing as a result of population growth and urbanization. That is to say, non-urban, large swaths of land are consumed by cities and urban settlements, and over time they are fragmented into smaller pieces. Therefore, the present study was designed to detect and evaluate changes in the landscape structure of Tabriz metropolitan area and to evaluate the performance of landscape metrics in analyzing changes. To this end, first the land use maps for 1984, 2000 and 2018 were prepared using Landsat satellite imagery. Then, in order to analyze the changes, a combination of Landscape metrics including NP, CA, PLAND, LPI, ED, MPS, LSI, and COHESION was computed at two levels of land class and landscape using Fragstats4.2 software. The results showed that the lands used for urban settlement during this period have had the most changes and growth, in contrast to agricultural farms, gardens and green-space which have had a downward trend and have been converted to other uses. Also, the number and density of patches have increased over time, leading to the fragmentation of the landscape. On the other hand, the average size of patches belonging to constructed lands and agricultural and horticultural lands respectively increased and decreased, and caused more distortion and complexity of Tabriz city landscape through an increase in the landscape shape index. In general, the analysis of land use maps and landscape metrics clearly reveals the effects of human activities and urbanization on the surrounding environment, and the results indicate that the landscape of Tabriz has got more granular, more complex and geometrically more irregular. Then, with this decreasing connectivity, it has become more fragmented.

Habitat fragmentation is a concern in conservation biology that sometimes leading to habitat destruction. In this study, the effects of landscape variables on bird's aboundance were studied in forest patches in Gorgan Township. All variable were surveyed in 26 different patch sizes (300 ha). Also landscape index was calculated by FRAGSTAT software. Birds were detected within a 25m radius of each of 74 sampling points. The Results showed that Red breasted flycatcher and bolbol had negative correlation with size of patches but GreatTit had positive correlation with size, para and shape of patches. According this study Red breasted flycatcher and bolbol were detected as Forest interior and GreatTit was detected as Forestedge.The results of this study indicated the importance of forest patches for conserving and enhancing of avian and following it conserving biodiversity of the forest ecosystems.

In order to evaluate the socioeconomic and ecological functions of a city, it is essential to quantify the pattern of the land. In this regard, the use of gradient analysis is also a very effective method. Accordingly, the aim of this study is to quantify the landform of Behbahan county using the combination of land metrics and gradient analysis. For this purpose, land use changes over a period of 14 years (2000-2014) were studied. Gradient analysis for two transects in the North South and East West were designed. Both the class and landscape metrics were calculated using a moving window. The results showed that during transects, in addition to land use changes, shape and density of the patches have changed and these changes are different in the two transects. Also, the results of the analysis in both transects in the class indicate that the patch density and edge density have increased towards the city center. The results of landscape metrics based on the items show that the distribution of land in 2014, distribution of agricultural and residential land, especially land, has more distribution levels; Behbehan is the county landscape. This reflects the development of urban and agricultural land and pasture land decreased in 2014 compared to 2000 is in the region. According to the trend of metrics, it can be said that the entire north-south transect of the east-west pattern is symmetrical.

Green spaces in urban areas, especially in large industrial cities entail different implications. The green space improves the environment of the cities and on the other hand it creates proper conditions for the recreation and leisure of the citizens in terms of distribution of urban green space. In this research, maps of parks was depicted by digital atlas of Tehran parks and by using of ArcMap and IDRISI software, Then by using applying selected landscape metrics including (CA, PD, PLAND, MPS, LPI, LSI, MNN, Shape-MN), and using Fragstats software, a series of quantitative data about spatial pattern of Tehran parks was resulted. Composition, configuration, expanse and continuity of parks were also analyzed. Only six percent of the landscape was assigned by the green space activity studied in three neighborhood, district, and regional parks classes. Neighborhood parks have the best spatial pattern in comparison with other classes and spatial pattern of regional parks were unfavorable in comparison with neighborhood and district parks.

Water is one of the critical needs of human life and living things. Therefore, proper planning is important for its consumption all over the world, especially in Iran. This study was conducted to evaluate the impacts of land use change on water yield in the Teraz watershed, Khuzestan province, Iran, from 1990 to 2050. Water yield was evaluated using integrated valuation of ecosystem services and tradeoffs (InVEST) tool and land use was mapped using the maximum likelihood classification in the ENVI 5.3, and CA-Markov in the TerrSet environment. Moreover, the relationship between water yield and landscape metrics, including the number of patches (NP), patch density (PD), landscape shape index (LSI), and Largest Patch Index (LPI), was considered based on the Geographically Weighted Regression (GWR) method in the Arc GIS 10.5. The results showed that the area of ​​forest and rangeland in the studied area decreased in the last 30 years, by 3199 and 1611 ha, respectively, and the area of ​​agriculture and construction land uses increased by 4388 and 387 ha, respectively. It is predicted that in the next 30 years, 2442 ha of forests will decrease and the area of ​​agriculture, rangeland, and construction land uses will increase by 1651, 687, and 102 ha, respectively. It was found that the total volume of available water yield in the region is equal to 26.5 Mm3 in 2020, on average of 857 m3 ha-1, and based on that, the ranking of land uses is as follows: 1. Construction, 2. Rangeland, 3. Forest, 4. agriculture. The results of GWR confirmed that water yield had a significant and negative spatial relationships with the NP, PD, and LSI metrics (R2>=0.83, p-value>0.05), while its relationship with the LPI metric was a significant and positive relationship (R2>0.84, p-value>0.05). It can be concluded that the landscape features and land use pattern can determine the production and yield of water in the study area.