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Using geospatial data and principles of landscape ecology to identify field sites and characterize landscapes

机译:利用地理空间数据和景观生态学原理识别野外地点并表征景观

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We explored the utility of using readily available geospatial datasets to assist in field site identification. Specifically, we used readily available geospatial data to locate potential field sites that represented specific points along an urban-rural gradient of development intensity at landscape and regional scales. We also incorporated development age (young versus mature) in our site selection. Using publicly available spatial datasets, we computed a set of variables that characterized the landscape at two spatial scales and combined these to develop a gradient of urbanization. We then used maps of these gradients, digital orthophotographs, and ancillary geospatial data layers to identify candidate field sites of the requisite landscape- and regional-scale development intensity. These field sites were then visited to verify the current condition, and acceptable sites were used in companion studies to survey avian communities. We were also interested in how land cover estimates derived from different data sources varied. We compared estimates of percent land cover at two spatial scales derived from coarse scale land cover maps and fine scale screen-digitized from aerial photographs. At finer spatial scales, it appears the added costs associated with screen-digitizing yield much more precise estimates of land cover, whereas at coarser scales, although satellite-based land cover classifications may be somewhat less accurate, they may be sufficiently correlated with aerial photo-interpreted classifications that the expenditure is not worthwhile.View full textDownload full textKeywordslandscape pattern, land cover, land use, development intensityRelated var addthis_config = { ui_cobrand: "Taylor & Francis Online", services_compact: "citeulike,netvibes,twitter,technorati,delicious,linkedin,facebook,stumbleupon,digg,google,more", pubid: "ra-4dff56cd6bb1830b" }; Add to shortlist Link Permalink http://dx.doi.org/10.1080/19475683.2011.558020
机译:我们探索了使用随时可用的地理空间数据集来协助现场识别的实用程序。具体来说,我们使用了现成的地理空间数据来定位潜在的野外站点,这些站点代表了沿景观和区域尺度的发展强度在城乡梯度上的特定点。我们还在网站选择中纳入了发展年龄(年轻与成熟)。使用公开可用的空间数据集,我们计算了一组变量,这些变量在两个空间尺度上表征了景观,并将它们结合起来以形成城市化梯度。然后,我们使用这些梯度图,数字正射照片和辅助地理空间数据层来确定具有必要的景观和区域规模开发强度的候选野外站点。然后访问了这些现场,以验证当前状况,并在陪伴研究中使用了可接受的地点来调查鸟类群落。我们还对从不同数据源得出的土地覆盖率估算值如何变化感兴趣。我们比较了从粗略的土地覆盖图和从航空照片数字化的精细比例屏幕在两个空间尺度上的土地覆盖率估计值。在更精细的空间尺度上,似乎与将土地数字化的屏幕数字化相关的额外成本要精确得多,而在较粗的尺度上,尽管基于卫星的土地覆盖分类可能不太精确,但它们可能与航拍图充分相关。解释的分类是支出不值得。查看全文下载全文关键字景观格局,土地覆盖,土地利用,发展强度相关var addthis_config = {ui_cobrand:“泰勒和弗朗西斯在线”,service_compact:“ citeulike,netvibes,twitter,technorati,delicious ,linkedin,facebook,stumbleupon,digg,google,更多”,发布号:“ ra-4dff56cd6bb1830b”};添加到候选列表链接永久链接http://dx.doi.org/10.1080/19475683.2011.558020

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