26 research outputs found

    Analyzing Remote Sensing Data in R: The landsat Package

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    Research and development on atmospheric and topographic correction methods for multispectral satellite data such as Landsat images has far outpaced the availability of those methods in geographic information systems software. As Landsat and other data become more widely available, demand for these improved correction methods will increase. Open source R statistical software can help bridge the gap between research and implementation. Sophisticated spatial data routines are already available, and the ease of program development in R makes it straightforward to implement new correction algorithms and to assess the results. Collecting radiometric, atmospheric, and topographic correction routines into the landsat package will make them readily available for evaluation for particular applications.

    The ecodist Package for Dissimilarity-based Analysis of Ecological Data

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    Ecologists are concerned with the relationships between species composition and environmental framework incorporating space explicitly is an extremely flexible tool for answering these questions. The R package ecodist brings together methods for working with dissimilarities, including some not available in other R packages. We present some of the features of ecodist, particularly simple and partial Mantel tests, and make recommendations for their effective use. Although the partial Mantel test is often used to account for the effects of space, the assumption of linearity greatly reduces its effectiveness for complex spatial patterns. We introduce a modification of the Mantel correlogram designed to overcome this restriction and allow consideration of complex nonlinear structures. This extension of the method allows the use of partial multivariate correlograms and tests of relationship between variables at different spatial scales. Some of the possibilities are demonstrated using both artificial data and data from an ongoing study of plant community composition in grazinglands of the northeastern United States.

    Analyzing Remote Sensing Data in R: The landsat Package

    Get PDF
    Research and development on atmospheric and topographic correction methods for multispectral satellite data such as Landsat images has far outpaced the availability of those methods in geographic information systems software. As Landsat and other data become more widely available, demand for these improved correction methods will increase. Open source R statistical software can help bridge the gap between research and implementation. Sophisticated spatial data routines are already available, and the ease of program development in R makes it straightforward to implement new correction algorithms and to assess the results. Collecting radiometric, atmospheric, and topographic correction routines into the landsat package will make them readily available for evaluation for particular applications

    Assessing performance of conservation-based Best Management Practices: Coarse vs. fine-scale analysis

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    Background/Questions/Methods
Animal agriculture in the Spring Creek watershed of central Pennsylvania contributes sediment to the stream and ultimately to the Chesapeake Bay. Best Management Practices (BMPs) such as stream bank buffers are intended to intercept sediment moving from heavy-use areas toward the stream. The placement of BMPs on a farm is generally based on untested assumptions about flow paths. Most often, a straight-line distance from the heavy-use area to the stream is assumed to be correct. Our objective was to compare the straight-line path to hydrologic flow paths calculated from fine-, medium- and coarse-grained Digital Elevation Models (DEMs; 1m, 10m, 30m) for 471 mapped heavy-use points within 100m of the stream. The 30m DEMs are the most widely available and require the least processing time. We anticipated that the flow path distance would be longer than the straight-line distance in all cases, that the finest resolution would lead to the most accurate measurement, but that the difference might not be great enough to justify the increased costs. Understanding the changes in path length and direction calculated using more complex methods and higher-resolution source data will enable us to make recommendations on methods to be used in developing conservation management plans.

Results/Conclusions
The medium-(10m DEM) and fine-resolution data (1m DEM) had the smallest differences between the hydrologic flow path and straight-line path: median differences in path length of 20 m for both the 1m and 10m DEMs, and 51m for the 30m DEM. Hydrologic flow paths were significantly longer than straight-line paths for all three scales; BMP placement based on straight-line distances may not be the most effective. Although the overall difference was significantly positive, calculations on the 30m DEMs sometimes produced straight-line paths that were longer than the hydrologic flow paths, apparently due to inaccuracies in the data. Where fine-scale DEMs are available, BMPs might be more effectively situated by considering the corresponding drainage pathways. The very different results produced at the three scales demonstrate that using the finest-grained elevation data may substantially improve placement of BMPs intended to mitigate for heavy animal use areas. The use of 30m DEMs for this purpose should be avoided. Fine-grained data such as 1m-resolution LiDAR-derived DEMs are available for Pennsylvania through PAMAP, and can be incorporated in the planning stages of BMP placement ultimately resulting in reducing agricultural sediment and nutrient loadings into local watersheds and the Chesapeake Bay

    Interview with Sarah Goslee Reed

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    The interview addresses song writing and traditional vs non-traditional music with Sarah Goslee Reed, a musician and folk song writerhttps://digital.kenyon.edu/kcm_interviews/1004/thumbnail.jp

    The ecodist Package for Dissimilarity-based Analysis of Ecological Data

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    Ecologists are concerned with the relationships between species composition and environmental framework incorporating space explicitly is an extremely flexible tool for answering these questions. The R package ecodist brings together methods for working with dissimilarities, including some not available in other R packages. We present some of the features of ecodist, particularly simple and partial Mantel tests, and make recommendations for their effective use. Although the partial Mantel test is often used to account for the effects of space, the assumption of linearity greatly reduces its effectiveness for complex spatial patterns. We introduce a modification of the Mantel correlogram designed to overcome this restriction and allow consideration of complex nonlinear structures. This extension of the method allows the use of partial multivariate correlograms and tests of relationship between variables at different spatial scales. Some of the possibilities are demonstrated using both artificial data and data from an ongoing study of plant community composition in grazinglands of the northeastern United States

    Plant Community Associations of Two Invasive Thistles

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    In order to combat the growing problems associated with biological invasions, many researchers have focused on identifying which communities are most vulnerable to invasion by exotic species. However, once established, invasive species can significantly change the composition of the communities that they invade. The first step to disentangling the direction of causality is to discern whether a relationship with other vegetation exists at all. Carduus nutans and C. acanthoides are similar invasive thistles, which have caused substantial economic damage worldwide. We assessed the associations between the thistles and the standing flora in four sites in central Pennsylvania in which they co-occur. After sampling nearly 2000 plots of 1 m2, we used partial Mantel tests to assess the differences in vegetation between thistle and non-thistle plots after accounting for location, and non-metric multidimensional scaling to visualize differences among plots and sites. We found significant differences in community composition in plots with and without Carduus thistles. The non-native species Sisymbrium officinale and Coronilla varia were consistently associated with the presence of Carduus thistles. Several species were associated with areas that were free of Carduus thistles, including an important non-native pasture species (Trifolium repens). We found no evidence for differences in composition between plots with C. nutans versus C. acanthoides, suggesting that they have similar associations with the vegetation community. We conclude that even at the within-field scale, areas invaded by Carduus thistles have different vegetation associations than uninvaded areas, allowing us to target future research about the role of vegetation structure in resisting and responding to invasion

    Plant Community Associations of Two Invasive Thistles

    Get PDF
    In order to combat the growing problems associated with biological invasions, many researchers have focused on identifying which communities are most vulnerable to invasion by exotic species. However, once established, invasive species can significantly change the composition of the communities that they invade. The first step to disentangling the direction of causality is to discern whether a relationship with other vegetation exists at all. Carduus nutans and C. acanthoides are similar invasive thistles, which have caused substantial economic damage worldwide. We assessed the associations between the thistles and the standing flora in four sites in central Pennsylvania in which they co-occur. After sampling nearly 2000 plots of 1 m2, we used partial Mantel tests to assess the differences in vegetation between thistle and non-thistle plots after accounting for location, and non-metric multidimensional scaling to visualize differences among plots and sites. We found significant differences in community composition in plots with and without Carduus thistles. The non-native species Sisymbrium officinale and Coronilla varia were consistently associated with the presence of Carduus thistles. Several species were associated with areas that were free of Carduus thistles, including an important non-native pasture species (Trifolium repens). We found no evidence for differences in composition between plots with C. nutans versus C. acanthoides, suggesting that they have similar associations with the vegetation community. We conclude that even at the within-field scale, areas invaded by Carduus thistles have different vegetation associations than uninvaded areas, allowing us to target future research about the role of vegetation structure in resisting and responding to invasion

    Assessment and Monitoring of Grazing Lands in the Northeastern United States

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    The Pasture Condition Score System (Cosgrove et al., 2001) was developed as a monitoring and management tool on grazing lands The system considers 10 indicators of soils, plants, and animals including percent desirable plants, plant cover, plant diversity, plant residue, plant vigor, percent legume, uniformity of use, livestock concentration areas, soil compaction, and soil erosion. The indicators are assigned a score according to detailed criteria and the scores are summed to give an overall score for a pasture, or relevant grazing unit. The score is then interpreted, indicating if some type of management change or treatment is necessary. We tested the Pasture Condition Score system on farms across the northeast USA
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