Relationships between urbanization and the oak resource of the Minneapolis/St. Paul Metropolitan area from 1991 to 1998

Transformation of the oak forest spatial structure in the Minneapolis/St. Paul metropolitan area, Minnesota, USA over 7 years

“…However, image acquisition costs are much greater, and the geographic coverage is small compared to that of moderate resolution sensors. For this study, TM imagery was chosen for several reasons: its geographic coverage (one scene covered the seven-county study area), its seasonal and historical scope, the relatively low costs of acquisition and interpretation, the availability of datasets that were previously developed using TM imagery acquired in 1991 and 1998 in the TCMA (e.g., land cover, impervious surface) (Doyle, 2004;Yuan et al, 2005) and that were used in related research (Kromroy et al, 2007).…”

“…The 1991 and 1998 classifications were used in this study as the basis for the derivation of the oak forest landscape metrics, and were also used in a study by Loeffelholz (2003) to identify relationships between the change in oak forest area and condition and TCMA land use classes that varied in degree of urbanization. The oak forest metrics from Ward and Juzwik (2005) and from this study were used subsequently to determine associations between changes in the oak forest and several measures of urbanization, such as changes in area of impervious surface, and population density, and proximity to roads and to lakes or rivers (Kromroy et al, 2007).…”

Landscape Optimization in a Highly Urbanized Tourism Destination: An Integrated Approach in Nanjing, China

“…Landscape metrics was selected based on follows: (1) comparability with previous studies of landscape ecology [8,16,66]; (2) association with sustainability [5]; (3) low redundancy among the metrics [67]), and (4) reflection of the landscape pattern characteristics for the study area. Based on these, an index of the percentage of landscape (PLAND) at the patch level was selected to illustrate the landscape composition, while the number of total patches (NP), landscape fragmentation index (F), Shannon's diversity index (SHDI), dominance index (D), and connectivity index (C) at the landscape level represented the configuration.…”

Exploring coupling coordination between urbanization and ecosystem quality (1985–2010): a case study from Lianyungang City, China

“…The landscape metric selection was based on the following criteria (Su et al, 2012): 1) compared with previous landscape ecological studies (Botequilha and Ahern, 2002;Kromroy et al, 2007;Weng, 2007;Solon, 2009;Pôças et al, 2011;Su et al, 2011); 2) capable of revealing ecological conditions (Ribeiro and Lovett, 2009;Su et al, 2011); 3) low redundancy among landscape metrics (Botequilha & Ahern, 2002); and 4) capability to crystallize the characteristics of landscape patterns for the featured land use category (natural capital) and the whole study area. The selected class-level metrics in the natural capital category included the total core area (TCA), core area percentage of landscape (CPLAND), number of disjunct core area (NDCA), shape index (SHAPE_MN), effective mesh size (MESH), and contiguity index (CONTIG_MN).…”