Characterizing watershed-delineated landscapes in Pennsylvania using conditional entropy profiles
Abstract When the objective is to characterize landscapes with respect to relative degree and type of forest (or other critical habitat) fragmentation, it is difficult to decide which variables to measure and what type of discriminatory analysis to apply. It is also desirable to incorporate multiple...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Johnson, Glen D. [verfasserIn] |
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| Format: |
Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2001 |
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| Anmerkung: |
© Kluwer Academic Publishers 2001 |
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| Übergeordnetes Werk: |
Enthalten in: Landscape ecology - Kluwer Academic Publishers, 1987, 16(2001), 7 vom: Okt., Seite 597-610 |
|---|---|
| Übergeordnetes Werk: |
volume:16 ; year:2001 ; number:7 ; month:10 ; pages:597-610 |
| Links: |
|---|
| DOI / URN: |
10.1023/A:1013145418980 |
|---|
| Katalog-ID: |
OLC2075219281 |
|---|
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| 520 | |a Abstract When the objective is to characterize landscapes with respect to relative degree and type of forest (or other critical habitat) fragmentation, it is difficult to decide which variables to measure and what type of discriminatory analysis to apply. It is also desirable to incorporate multiple measurement scales. In response, a new method has been developed that responds to changes in both the marginal and spatial distributions of land cover in a raster map. Multiscale features of the map are captured in a sequence of successively coarsened resolutions based on the random filter for degrading raster map resolutions. Basically, the entropy of spatial pattern associated with a particular pixel resolution is calculated, conditional on the pattern of the next coarser ‘parent’ resolution. When the entropy is plotted as a function of changing resolution, we obtain a simple two-dimensional graph called a ‘conditional entropy profile’, thus providing a graphical visualization of multi-scale fragmentation patterns. Using eight-category raster maps derived from 30-meter resolution LANDSAT Thematic Mapper images, the conditional entropy profile was obtained for each of 102 watersheds covering the state of Pennsylvania (USA). A suite of more conventional single-resolution landscape measurements was also obtained for each watershed using the FRAGSTATS program. After dividing the watersheds into three major physiographic provinces, cluster analysis was performed within each province using various combinations of the FRAGSTATS variables, land cover proportions and variables describing the conditional entropy profiles. Measurements of both spatial pattern and marginal land cover proportions were necessary to clearly discriminate the watersheds into distinct clusters for most of the state; however, the Piedmont province essentially only required the land cover proportions. In addition to land cover proportions, only the variables describing a conditional entropy profile appeared to be necessary for the Ridge and Valley province, whereas only the FRAGSTATS variables appeared to be necessary for the Appalachian Plateaus province. Meanwhile, the graphical representation of conditional entropy profiles provided a visualization of multi-scale fragmentation that was quite sensitive to changing pattern. | ||
| 700 | 1 | |a Myers, Wayne L. |4 aut | |
| 700 | 1 | |a Patil, Ganapati P. |4 aut | |
| 700 | 1 | |a Taillie, Charles |4 aut | |
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10.1023/A:1013145418980 doi (DE-627)OLC2075219281 (DE-He213)A:1013145418980-p DE-627 ger DE-627 rakwb eng 570 910 630 VZ 12 ssgn BIODIV DE-30 fid Johnson, Glen D. verfasserin aut Characterizing watershed-delineated landscapes in Pennsylvania using conditional entropy profiles 2001 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Kluwer Academic Publishers 2001 Abstract When the objective is to characterize landscapes with respect to relative degree and type of forest (or other critical habitat) fragmentation, it is difficult to decide which variables to measure and what type of discriminatory analysis to apply. It is also desirable to incorporate multiple measurement scales. In response, a new method has been developed that responds to changes in both the marginal and spatial distributions of land cover in a raster map. Multiscale features of the map are captured in a sequence of successively coarsened resolutions based on the random filter for degrading raster map resolutions. Basically, the entropy of spatial pattern associated with a particular pixel resolution is calculated, conditional on the pattern of the next coarser ‘parent’ resolution. When the entropy is plotted as a function of changing resolution, we obtain a simple two-dimensional graph called a ‘conditional entropy profile’, thus providing a graphical visualization of multi-scale fragmentation patterns. Using eight-category raster maps derived from 30-meter resolution LANDSAT Thematic Mapper images, the conditional entropy profile was obtained for each of 102 watersheds covering the state of Pennsylvania (USA). A suite of more conventional single-resolution landscape measurements was also obtained for each watershed using the FRAGSTATS program. After dividing the watersheds into three major physiographic provinces, cluster analysis was performed within each province using various combinations of the FRAGSTATS variables, land cover proportions and variables describing the conditional entropy profiles. Measurements of both spatial pattern and marginal land cover proportions were necessary to clearly discriminate the watersheds into distinct clusters for most of the state; however, the Piedmont province essentially only required the land cover proportions. In addition to land cover proportions, only the variables describing a conditional entropy profile appeared to be necessary for the Ridge and Valley province, whereas only the FRAGSTATS variables appeared to be necessary for the Appalachian Plateaus province. Meanwhile, the graphical representation of conditional entropy profiles provided a visualization of multi-scale fragmentation that was quite sensitive to changing pattern. Myers, Wayne L. aut Patil, Ganapati P. aut Taillie, Charles aut Enthalten in Landscape ecology Kluwer Academic Publishers, 1987 16(2001), 7 vom: Okt., Seite 597-610 (DE-627)130857424 (DE-600)1027798-5 (DE-576)052841901 0921-2973 nnns volume:16 year:2001 number:7 month:10 pages:597-610 https://doi.org/10.1023/A:1013145418980 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC FID-BIODIV SSG-OLC-ARC SSG-OLC-FOR GBV_ILN_62 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_2360 GBV_ILN_4012 GBV_ILN_4082 GBV_ILN_4219 GBV_ILN_4307 GBV_ILN_4330 AR 16 2001 7 10 597-610 |
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10.1023/A:1013145418980 doi (DE-627)OLC2075219281 (DE-He213)A:1013145418980-p DE-627 ger DE-627 rakwb eng 570 910 630 VZ 12 ssgn BIODIV DE-30 fid Johnson, Glen D. verfasserin aut Characterizing watershed-delineated landscapes in Pennsylvania using conditional entropy profiles 2001 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Kluwer Academic Publishers 2001 Abstract When the objective is to characterize landscapes with respect to relative degree and type of forest (or other critical habitat) fragmentation, it is difficult to decide which variables to measure and what type of discriminatory analysis to apply. It is also desirable to incorporate multiple measurement scales. In response, a new method has been developed that responds to changes in both the marginal and spatial distributions of land cover in a raster map. Multiscale features of the map are captured in a sequence of successively coarsened resolutions based on the random filter for degrading raster map resolutions. Basically, the entropy of spatial pattern associated with a particular pixel resolution is calculated, conditional on the pattern of the next coarser ‘parent’ resolution. When the entropy is plotted as a function of changing resolution, we obtain a simple two-dimensional graph called a ‘conditional entropy profile’, thus providing a graphical visualization of multi-scale fragmentation patterns. Using eight-category raster maps derived from 30-meter resolution LANDSAT Thematic Mapper images, the conditional entropy profile was obtained for each of 102 watersheds covering the state of Pennsylvania (USA). A suite of more conventional single-resolution landscape measurements was also obtained for each watershed using the FRAGSTATS program. After dividing the watersheds into three major physiographic provinces, cluster analysis was performed within each province using various combinations of the FRAGSTATS variables, land cover proportions and variables describing the conditional entropy profiles. Measurements of both spatial pattern and marginal land cover proportions were necessary to clearly discriminate the watersheds into distinct clusters for most of the state; however, the Piedmont province essentially only required the land cover proportions. In addition to land cover proportions, only the variables describing a conditional entropy profile appeared to be necessary for the Ridge and Valley province, whereas only the FRAGSTATS variables appeared to be necessary for the Appalachian Plateaus province. Meanwhile, the graphical representation of conditional entropy profiles provided a visualization of multi-scale fragmentation that was quite sensitive to changing pattern. Myers, Wayne L. aut Patil, Ganapati P. aut Taillie, Charles aut Enthalten in Landscape ecology Kluwer Academic Publishers, 1987 16(2001), 7 vom: Okt., Seite 597-610 (DE-627)130857424 (DE-600)1027798-5 (DE-576)052841901 0921-2973 nnns volume:16 year:2001 number:7 month:10 pages:597-610 https://doi.org/10.1023/A:1013145418980 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC FID-BIODIV SSG-OLC-ARC SSG-OLC-FOR GBV_ILN_62 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_2360 GBV_ILN_4012 GBV_ILN_4082 GBV_ILN_4219 GBV_ILN_4307 GBV_ILN_4330 AR 16 2001 7 10 597-610 |
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10.1023/A:1013145418980 doi (DE-627)OLC2075219281 (DE-He213)A:1013145418980-p DE-627 ger DE-627 rakwb eng 570 910 630 VZ 12 ssgn BIODIV DE-30 fid Johnson, Glen D. verfasserin aut Characterizing watershed-delineated landscapes in Pennsylvania using conditional entropy profiles 2001 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Kluwer Academic Publishers 2001 Abstract When the objective is to characterize landscapes with respect to relative degree and type of forest (or other critical habitat) fragmentation, it is difficult to decide which variables to measure and what type of discriminatory analysis to apply. It is also desirable to incorporate multiple measurement scales. In response, a new method has been developed that responds to changes in both the marginal and spatial distributions of land cover in a raster map. Multiscale features of the map are captured in a sequence of successively coarsened resolutions based on the random filter for degrading raster map resolutions. Basically, the entropy of spatial pattern associated with a particular pixel resolution is calculated, conditional on the pattern of the next coarser ‘parent’ resolution. When the entropy is plotted as a function of changing resolution, we obtain a simple two-dimensional graph called a ‘conditional entropy profile’, thus providing a graphical visualization of multi-scale fragmentation patterns. Using eight-category raster maps derived from 30-meter resolution LANDSAT Thematic Mapper images, the conditional entropy profile was obtained for each of 102 watersheds covering the state of Pennsylvania (USA). A suite of more conventional single-resolution landscape measurements was also obtained for each watershed using the FRAGSTATS program. After dividing the watersheds into three major physiographic provinces, cluster analysis was performed within each province using various combinations of the FRAGSTATS variables, land cover proportions and variables describing the conditional entropy profiles. Measurements of both spatial pattern and marginal land cover proportions were necessary to clearly discriminate the watersheds into distinct clusters for most of the state; however, the Piedmont province essentially only required the land cover proportions. In addition to land cover proportions, only the variables describing a conditional entropy profile appeared to be necessary for the Ridge and Valley province, whereas only the FRAGSTATS variables appeared to be necessary for the Appalachian Plateaus province. Meanwhile, the graphical representation of conditional entropy profiles provided a visualization of multi-scale fragmentation that was quite sensitive to changing pattern. Myers, Wayne L. aut Patil, Ganapati P. aut Taillie, Charles aut Enthalten in Landscape ecology Kluwer Academic Publishers, 1987 16(2001), 7 vom: Okt., Seite 597-610 (DE-627)130857424 (DE-600)1027798-5 (DE-576)052841901 0921-2973 nnns volume:16 year:2001 number:7 month:10 pages:597-610 https://doi.org/10.1023/A:1013145418980 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC FID-BIODIV SSG-OLC-ARC SSG-OLC-FOR GBV_ILN_62 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_2360 GBV_ILN_4012 GBV_ILN_4082 GBV_ILN_4219 GBV_ILN_4307 GBV_ILN_4330 AR 16 2001 7 10 597-610 |
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10.1023/A:1013145418980 doi (DE-627)OLC2075219281 (DE-He213)A:1013145418980-p DE-627 ger DE-627 rakwb eng 570 910 630 VZ 12 ssgn BIODIV DE-30 fid Johnson, Glen D. verfasserin aut Characterizing watershed-delineated landscapes in Pennsylvania using conditional entropy profiles 2001 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Kluwer Academic Publishers 2001 Abstract When the objective is to characterize landscapes with respect to relative degree and type of forest (or other critical habitat) fragmentation, it is difficult to decide which variables to measure and what type of discriminatory analysis to apply. It is also desirable to incorporate multiple measurement scales. In response, a new method has been developed that responds to changes in both the marginal and spatial distributions of land cover in a raster map. Multiscale features of the map are captured in a sequence of successively coarsened resolutions based on the random filter for degrading raster map resolutions. Basically, the entropy of spatial pattern associated with a particular pixel resolution is calculated, conditional on the pattern of the next coarser ‘parent’ resolution. When the entropy is plotted as a function of changing resolution, we obtain a simple two-dimensional graph called a ‘conditional entropy profile’, thus providing a graphical visualization of multi-scale fragmentation patterns. Using eight-category raster maps derived from 30-meter resolution LANDSAT Thematic Mapper images, the conditional entropy profile was obtained for each of 102 watersheds covering the state of Pennsylvania (USA). A suite of more conventional single-resolution landscape measurements was also obtained for each watershed using the FRAGSTATS program. After dividing the watersheds into three major physiographic provinces, cluster analysis was performed within each province using various combinations of the FRAGSTATS variables, land cover proportions and variables describing the conditional entropy profiles. Measurements of both spatial pattern and marginal land cover proportions were necessary to clearly discriminate the watersheds into distinct clusters for most of the state; however, the Piedmont province essentially only required the land cover proportions. In addition to land cover proportions, only the variables describing a conditional entropy profile appeared to be necessary for the Ridge and Valley province, whereas only the FRAGSTATS variables appeared to be necessary for the Appalachian Plateaus province. Meanwhile, the graphical representation of conditional entropy profiles provided a visualization of multi-scale fragmentation that was quite sensitive to changing pattern. Myers, Wayne L. aut Patil, Ganapati P. aut Taillie, Charles aut Enthalten in Landscape ecology Kluwer Academic Publishers, 1987 16(2001), 7 vom: Okt., Seite 597-610 (DE-627)130857424 (DE-600)1027798-5 (DE-576)052841901 0921-2973 nnns volume:16 year:2001 number:7 month:10 pages:597-610 https://doi.org/10.1023/A:1013145418980 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC FID-BIODIV SSG-OLC-ARC SSG-OLC-FOR GBV_ILN_62 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_2360 GBV_ILN_4012 GBV_ILN_4082 GBV_ILN_4219 GBV_ILN_4307 GBV_ILN_4330 AR 16 2001 7 10 597-610 |
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10.1023/A:1013145418980 doi (DE-627)OLC2075219281 (DE-He213)A:1013145418980-p DE-627 ger DE-627 rakwb eng 570 910 630 VZ 12 ssgn BIODIV DE-30 fid Johnson, Glen D. verfasserin aut Characterizing watershed-delineated landscapes in Pennsylvania using conditional entropy profiles 2001 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Kluwer Academic Publishers 2001 Abstract When the objective is to characterize landscapes with respect to relative degree and type of forest (or other critical habitat) fragmentation, it is difficult to decide which variables to measure and what type of discriminatory analysis to apply. It is also desirable to incorporate multiple measurement scales. In response, a new method has been developed that responds to changes in both the marginal and spatial distributions of land cover in a raster map. Multiscale features of the map are captured in a sequence of successively coarsened resolutions based on the random filter for degrading raster map resolutions. Basically, the entropy of spatial pattern associated with a particular pixel resolution is calculated, conditional on the pattern of the next coarser ‘parent’ resolution. When the entropy is plotted as a function of changing resolution, we obtain a simple two-dimensional graph called a ‘conditional entropy profile’, thus providing a graphical visualization of multi-scale fragmentation patterns. Using eight-category raster maps derived from 30-meter resolution LANDSAT Thematic Mapper images, the conditional entropy profile was obtained for each of 102 watersheds covering the state of Pennsylvania (USA). A suite of more conventional single-resolution landscape measurements was also obtained for each watershed using the FRAGSTATS program. After dividing the watersheds into three major physiographic provinces, cluster analysis was performed within each province using various combinations of the FRAGSTATS variables, land cover proportions and variables describing the conditional entropy profiles. Measurements of both spatial pattern and marginal land cover proportions were necessary to clearly discriminate the watersheds into distinct clusters for most of the state; however, the Piedmont province essentially only required the land cover proportions. In addition to land cover proportions, only the variables describing a conditional entropy profile appeared to be necessary for the Ridge and Valley province, whereas only the FRAGSTATS variables appeared to be necessary for the Appalachian Plateaus province. Meanwhile, the graphical representation of conditional entropy profiles provided a visualization of multi-scale fragmentation that was quite sensitive to changing pattern. Myers, Wayne L. aut Patil, Ganapati P. aut Taillie, Charles aut Enthalten in Landscape ecology Kluwer Academic Publishers, 1987 16(2001), 7 vom: Okt., Seite 597-610 (DE-627)130857424 (DE-600)1027798-5 (DE-576)052841901 0921-2973 nnns volume:16 year:2001 number:7 month:10 pages:597-610 https://doi.org/10.1023/A:1013145418980 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC FID-BIODIV SSG-OLC-ARC SSG-OLC-FOR GBV_ILN_62 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_2360 GBV_ILN_4012 GBV_ILN_4082 GBV_ILN_4219 GBV_ILN_4307 GBV_ILN_4330 AR 16 2001 7 10 597-610 |
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characterizing watershed-delineated landscapes in pennsylvania using conditional entropy profiles |
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Characterizing watershed-delineated landscapes in Pennsylvania using conditional entropy profiles |
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Abstract When the objective is to characterize landscapes with respect to relative degree and type of forest (or other critical habitat) fragmentation, it is difficult to decide which variables to measure and what type of discriminatory analysis to apply. It is also desirable to incorporate multiple measurement scales. In response, a new method has been developed that responds to changes in both the marginal and spatial distributions of land cover in a raster map. Multiscale features of the map are captured in a sequence of successively coarsened resolutions based on the random filter for degrading raster map resolutions. Basically, the entropy of spatial pattern associated with a particular pixel resolution is calculated, conditional on the pattern of the next coarser ‘parent’ resolution. When the entropy is plotted as a function of changing resolution, we obtain a simple two-dimensional graph called a ‘conditional entropy profile’, thus providing a graphical visualization of multi-scale fragmentation patterns. Using eight-category raster maps derived from 30-meter resolution LANDSAT Thematic Mapper images, the conditional entropy profile was obtained for each of 102 watersheds covering the state of Pennsylvania (USA). A suite of more conventional single-resolution landscape measurements was also obtained for each watershed using the FRAGSTATS program. After dividing the watersheds into three major physiographic provinces, cluster analysis was performed within each province using various combinations of the FRAGSTATS variables, land cover proportions and variables describing the conditional entropy profiles. Measurements of both spatial pattern and marginal land cover proportions were necessary to clearly discriminate the watersheds into distinct clusters for most of the state; however, the Piedmont province essentially only required the land cover proportions. In addition to land cover proportions, only the variables describing a conditional entropy profile appeared to be necessary for the Ridge and Valley province, whereas only the FRAGSTATS variables appeared to be necessary for the Appalachian Plateaus province. Meanwhile, the graphical representation of conditional entropy profiles provided a visualization of multi-scale fragmentation that was quite sensitive to changing pattern. © Kluwer Academic Publishers 2001 |
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Abstract When the objective is to characterize landscapes with respect to relative degree and type of forest (or other critical habitat) fragmentation, it is difficult to decide which variables to measure and what type of discriminatory analysis to apply. It is also desirable to incorporate multiple measurement scales. In response, a new method has been developed that responds to changes in both the marginal and spatial distributions of land cover in a raster map. Multiscale features of the map are captured in a sequence of successively coarsened resolutions based on the random filter for degrading raster map resolutions. Basically, the entropy of spatial pattern associated with a particular pixel resolution is calculated, conditional on the pattern of the next coarser ‘parent’ resolution. When the entropy is plotted as a function of changing resolution, we obtain a simple two-dimensional graph called a ‘conditional entropy profile’, thus providing a graphical visualization of multi-scale fragmentation patterns. Using eight-category raster maps derived from 30-meter resolution LANDSAT Thematic Mapper images, the conditional entropy profile was obtained for each of 102 watersheds covering the state of Pennsylvania (USA). A suite of more conventional single-resolution landscape measurements was also obtained for each watershed using the FRAGSTATS program. After dividing the watersheds into three major physiographic provinces, cluster analysis was performed within each province using various combinations of the FRAGSTATS variables, land cover proportions and variables describing the conditional entropy profiles. Measurements of both spatial pattern and marginal land cover proportions were necessary to clearly discriminate the watersheds into distinct clusters for most of the state; however, the Piedmont province essentially only required the land cover proportions. In addition to land cover proportions, only the variables describing a conditional entropy profile appeared to be necessary for the Ridge and Valley province, whereas only the FRAGSTATS variables appeared to be necessary for the Appalachian Plateaus province. Meanwhile, the graphical representation of conditional entropy profiles provided a visualization of multi-scale fragmentation that was quite sensitive to changing pattern. © Kluwer Academic Publishers 2001 |
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Abstract When the objective is to characterize landscapes with respect to relative degree and type of forest (or other critical habitat) fragmentation, it is difficult to decide which variables to measure and what type of discriminatory analysis to apply. It is also desirable to incorporate multiple measurement scales. In response, a new method has been developed that responds to changes in both the marginal and spatial distributions of land cover in a raster map. Multiscale features of the map are captured in a sequence of successively coarsened resolutions based on the random filter for degrading raster map resolutions. Basically, the entropy of spatial pattern associated with a particular pixel resolution is calculated, conditional on the pattern of the next coarser ‘parent’ resolution. When the entropy is plotted as a function of changing resolution, we obtain a simple two-dimensional graph called a ‘conditional entropy profile’, thus providing a graphical visualization of multi-scale fragmentation patterns. Using eight-category raster maps derived from 30-meter resolution LANDSAT Thematic Mapper images, the conditional entropy profile was obtained for each of 102 watersheds covering the state of Pennsylvania (USA). A suite of more conventional single-resolution landscape measurements was also obtained for each watershed using the FRAGSTATS program. After dividing the watersheds into three major physiographic provinces, cluster analysis was performed within each province using various combinations of the FRAGSTATS variables, land cover proportions and variables describing the conditional entropy profiles. Measurements of both spatial pattern and marginal land cover proportions were necessary to clearly discriminate the watersheds into distinct clusters for most of the state; however, the Piedmont province essentially only required the land cover proportions. In addition to land cover proportions, only the variables describing a conditional entropy profile appeared to be necessary for the Ridge and Valley province, whereas only the FRAGSTATS variables appeared to be necessary for the Appalachian Plateaus province. Meanwhile, the graphical representation of conditional entropy profiles provided a visualization of multi-scale fragmentation that was quite sensitive to changing pattern. © Kluwer Academic Publishers 2001 |
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