Analysis of fine-scale spatial pattern of a grassland from remotely-sensed imagery and field collected data
21 pages, 11 figures, 4 tables, appendix
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Kluwer Academic Publishers
1998-04
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Subjects: | Vegetation pattern, Serpentine grassland, Disturbance, Thomomys bottae, Geostatistics, Remote sensing, Fractal, Spatial simulation, NDVI, Fast Fourier Transform, |
Online Access: | http://hdl.handle.net/10261/275484 |
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dig-icm-es-10261-2754842022-07-14T08:21:36Z Analysis of fine-scale spatial pattern of a grassland from remotely-sensed imagery and field collected data Lobo, Agustín Moloney, Kirk A. Chic, Óscar Chiariello, Nona Vegetation pattern Serpentine grassland Disturbance Thomomys bottae Geostatistics Remote sensing Fractal Spatial simulation NDVI Fast Fourier Transform 21 pages, 11 figures, 4 tables, appendix An important practical problem in the analysis of spatial pattern in ecological systems is that requires spatially-intensive data, with both fine resolution and large extent. Such information is often difficult to obtain from field-measured variables. Digital imagery can offer a valuable, alternative source of information in the analysis of ecological pattern. In the present paper, we use remotely-sensed imagery to provide a link between field-based information and spatially-explicit modeling of ecological processes. We analyzed one digitized color infrared aerial photograph of a serpentine grassland to develop a detailed digital map of land cover categories (31.24 m x 50.04 m of extent and 135 mm of resolution), and an image of vegetation index (proportional to the amount of green biomass cover in the field). We conducted a variogram analysis of the spatial pattern of both field-measured (microtopography, soil depth) and image-derived (land cover map, vegetation index, gopher disturbance) landscape variables, and used a statistical simulation method to produce random realizations of the image of vegetation index based upon our characterization of its spatial structure. The analysis revealed strong relationships in the spatial distribution of the ecological variables (e.g., gopher mounds and perennial grasses are found primarily on deeper soils) and a non-fractal nested spatial pattern in the distribution of green biomass as measured by the vegetation index. The spatial pattern of the vegetation index was composed of three basic components: an exponential trend from 0 m to 4 m, which is related to local ecological processes, a linear trend at broader scales, which is related to a general change in topography across the study site, and a superimposed periodic structure, which is related to the regular spacing of deeper soils within the study site. Simulations of the image of vegetation index confirmed our interpretation of the variograms. The simulations also illustrated the limits of statistical analysis and interpolations based solely on the semivariogram, because they cannot adequately characterize spatial discontinuities 2022-07-14T08:10:13Z 2022-07-14T08:10:13Z 1998-04 2022-07-14T08:10:13Z artículo issn: 0921-2973 e-issn: 1572-9761 Landscape Ecology 13: 111-131 (1998) http://hdl.handle.net/10261/275484 10.1023/A:1007938526886 https://doi.org/10.1023/A:1007938526886 Sí none Kluwer Academic Publishers |
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Vegetation pattern Serpentine grassland Disturbance Thomomys bottae Geostatistics Remote sensing Fractal Spatial simulation NDVI Fast Fourier Transform Vegetation pattern Serpentine grassland Disturbance Thomomys bottae Geostatistics Remote sensing Fractal Spatial simulation NDVI Fast Fourier Transform |
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Vegetation pattern Serpentine grassland Disturbance Thomomys bottae Geostatistics Remote sensing Fractal Spatial simulation NDVI Fast Fourier Transform Vegetation pattern Serpentine grassland Disturbance Thomomys bottae Geostatistics Remote sensing Fractal Spatial simulation NDVI Fast Fourier Transform Lobo, Agustín Moloney, Kirk A. Chic, Óscar Chiariello, Nona Analysis of fine-scale spatial pattern of a grassland from remotely-sensed imagery and field collected data |
description |
21 pages, 11 figures, 4 tables, appendix |
format |
artículo |
topic_facet |
Vegetation pattern Serpentine grassland Disturbance Thomomys bottae Geostatistics Remote sensing Fractal Spatial simulation NDVI Fast Fourier Transform |
author |
Lobo, Agustín Moloney, Kirk A. Chic, Óscar Chiariello, Nona |
author_facet |
Lobo, Agustín Moloney, Kirk A. Chic, Óscar Chiariello, Nona |
author_sort |
Lobo, Agustín |
title |
Analysis of fine-scale spatial pattern of a grassland from remotely-sensed imagery and field collected data |
title_short |
Analysis of fine-scale spatial pattern of a grassland from remotely-sensed imagery and field collected data |
title_full |
Analysis of fine-scale spatial pattern of a grassland from remotely-sensed imagery and field collected data |
title_fullStr |
Analysis of fine-scale spatial pattern of a grassland from remotely-sensed imagery and field collected data |
title_full_unstemmed |
Analysis of fine-scale spatial pattern of a grassland from remotely-sensed imagery and field collected data |
title_sort |
analysis of fine-scale spatial pattern of a grassland from remotely-sensed imagery and field collected data |
publisher |
Kluwer Academic Publishers |
publishDate |
1998-04 |
url |
http://hdl.handle.net/10261/275484 |
work_keys_str_mv |
AT loboagustin analysisoffinescalespatialpatternofagrasslandfromremotelysensedimageryandfieldcollecteddata AT moloneykirka analysisoffinescalespatialpatternofagrasslandfromremotelysensedimageryandfieldcollecteddata AT chicoscar analysisoffinescalespatialpatternofagrasslandfromremotelysensedimageryandfieldcollecteddata AT chiariellonona analysisoffinescalespatialpatternofagrasslandfromremotelysensedimageryandfieldcollecteddata |
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1777667790633697280 |