The Influence of Human Demography on Land Cover Change in the Great Lakes States, USA
Abstract The Great Lakes region contains productive agricultural and forest lands, but it is also highly urbanized, with 32 of its 52 million residents living in nine large metropolitan areas. Urbanization of undeveloped areas may adversely affect the productivity of agricultural and forest lands, a...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Ducey, Mark J. [verfasserIn] |
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| Format: |
Artikel |
|---|---|
| Sprache: |
Englisch |
| Erschienen: |
2018 |
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| Schlagwörter: |
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| Anmerkung: |
© Springer Science+Business Media, LLC, part of Springer Nature 2018 |
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| Übergeordnetes Werk: |
Enthalten in: Environmental management - Springer US, 1976, 62(2018), 6 vom: 26. Sept., Seite 1089-1107 |
|---|---|
| Übergeordnetes Werk: |
volume:62 ; year:2018 ; number:6 ; day:26 ; month:09 ; pages:1089-1107 |
| Links: |
|---|
| DOI / URN: |
10.1007/s00267-018-1102-x |
|---|
| Katalog-ID: |
OLC2060649730 |
|---|
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| 520 | |a Abstract The Great Lakes region contains productive agricultural and forest lands, but it is also highly urbanized, with 32 of its 52 million residents living in nine large metropolitan areas. Urbanization of undeveloped areas may adversely affect the productivity of agricultural and forest lands, and the provision of ecosystem services. We combine demographic and remote sensing data to evaluate land cover change in the region using a two-phase statistical modeling approach that predicts the incidence and extent of land cover change for each of the region’s 10,579 county subdivisions. Observed patterns are spatially uneven, and the probability of land cover change is influenced by current land use, human habitation, industry, and demographic change. Pseudo R2 values varied from 0.053 to 0.338 for the first-phase logistic models predicting the presence of land cover change; second-stage beta models predicting the rate of change were more reliable, with pseudo R2 ranging from 0.225 to 0.675. Overall, changes from agriculture or greenspace to development were much more predictable than changes from agriculture to greenspace or vice versa, and demographic variables were much more important in models predicting change to development. Although models successfully predicted the general location of land cover change, and models from before the Great Recession were useful for predicting the location but not the amount of change during the recession, fine-grained prediction remained challenging. Understanding where future changes are most probable can inform planning and policy-making, which may reduce the impact of development on resource production, environmental health, and ecosystem services. | ||
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| 700 | 1 | |a Cook, Barbara D. |4 aut | |
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10.1007/s00267-018-1102-x doi (DE-627)OLC2060649730 (DE-He213)s00267-018-1102-x-p DE-627 ger DE-627 rakwb eng 370 350 330 VZ 570 690 333.7 VZ 12 ssgn Ducey, Mark J. verfasserin (orcid)0000-0002-2027-1188 aut The Influence of Human Demography on Land Cover Change in the Great Lakes States, USA 2018 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer Science+Business Media, LLC, part of Springer Nature 2018 Abstract The Great Lakes region contains productive agricultural and forest lands, but it is also highly urbanized, with 32 of its 52 million residents living in nine large metropolitan areas. Urbanization of undeveloped areas may adversely affect the productivity of agricultural and forest lands, and the provision of ecosystem services. We combine demographic and remote sensing data to evaluate land cover change in the region using a two-phase statistical modeling approach that predicts the incidence and extent of land cover change for each of the region’s 10,579 county subdivisions. Observed patterns are spatially uneven, and the probability of land cover change is influenced by current land use, human habitation, industry, and demographic change. Pseudo R2 values varied from 0.053 to 0.338 for the first-phase logistic models predicting the presence of land cover change; second-stage beta models predicting the rate of change were more reliable, with pseudo R2 ranging from 0.225 to 0.675. Overall, changes from agriculture or greenspace to development were much more predictable than changes from agriculture to greenspace or vice versa, and demographic variables were much more important in models predicting change to development. Although models successfully predicted the general location of land cover change, and models from before the Great Recession were useful for predicting the location but not the amount of change during the recession, fine-grained prediction remained challenging. Understanding where future changes are most probable can inform planning and policy-making, which may reduce the impact of development on resource production, environmental health, and ecosystem services. Demography Development Ecosystem services Land cover Land-use change Johnson, Kenneth M. aut Belair, Ethan P. aut Cook, Barbara D. aut Enthalten in Environmental management Springer US, 1976 62(2018), 6 vom: 26. Sept., Seite 1089-1107 (DE-627)129322970 (DE-600)131372-1 (DE-576)014557207 0364-152X nnns volume:62 year:2018 number:6 day:26 month:09 pages:1089-1107 https://doi.org/10.1007/s00267-018-1102-x lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-UMW SSG-OLC-ARC SSG-OLC-TEC SSG-OLC-FOR SSG-OPC-GGO GBV_ILN_2018 GBV_ILN_4012 AR 62 2018 6 26 09 1089-1107 |
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10.1007/s00267-018-1102-x doi (DE-627)OLC2060649730 (DE-He213)s00267-018-1102-x-p DE-627 ger DE-627 rakwb eng 370 350 330 VZ 570 690 333.7 VZ 12 ssgn Ducey, Mark J. verfasserin (orcid)0000-0002-2027-1188 aut The Influence of Human Demography on Land Cover Change in the Great Lakes States, USA 2018 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer Science+Business Media, LLC, part of Springer Nature 2018 Abstract The Great Lakes region contains productive agricultural and forest lands, but it is also highly urbanized, with 32 of its 52 million residents living in nine large metropolitan areas. Urbanization of undeveloped areas may adversely affect the productivity of agricultural and forest lands, and the provision of ecosystem services. We combine demographic and remote sensing data to evaluate land cover change in the region using a two-phase statistical modeling approach that predicts the incidence and extent of land cover change for each of the region’s 10,579 county subdivisions. Observed patterns are spatially uneven, and the probability of land cover change is influenced by current land use, human habitation, industry, and demographic change. Pseudo R2 values varied from 0.053 to 0.338 for the first-phase logistic models predicting the presence of land cover change; second-stage beta models predicting the rate of change were more reliable, with pseudo R2 ranging from 0.225 to 0.675. Overall, changes from agriculture or greenspace to development were much more predictable than changes from agriculture to greenspace or vice versa, and demographic variables were much more important in models predicting change to development. Although models successfully predicted the general location of land cover change, and models from before the Great Recession were useful for predicting the location but not the amount of change during the recession, fine-grained prediction remained challenging. Understanding where future changes are most probable can inform planning and policy-making, which may reduce the impact of development on resource production, environmental health, and ecosystem services. Demography Development Ecosystem services Land cover Land-use change Johnson, Kenneth M. aut Belair, Ethan P. aut Cook, Barbara D. aut Enthalten in Environmental management Springer US, 1976 62(2018), 6 vom: 26. Sept., Seite 1089-1107 (DE-627)129322970 (DE-600)131372-1 (DE-576)014557207 0364-152X nnns volume:62 year:2018 number:6 day:26 month:09 pages:1089-1107 https://doi.org/10.1007/s00267-018-1102-x lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-UMW SSG-OLC-ARC SSG-OLC-TEC SSG-OLC-FOR SSG-OPC-GGO GBV_ILN_2018 GBV_ILN_4012 AR 62 2018 6 26 09 1089-1107 |
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370 350 330 VZ 570 690 333.7 VZ 12 ssgn The Influence of Human Demography on Land Cover Change in the Great Lakes States, USA Demography Development Ecosystem services Land cover Land-use change |
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The Influence of Human Demography on Land Cover Change in the Great Lakes States, USA |
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The Influence of Human Demography on Land Cover Change in the Great Lakes States, USA |
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Ducey, Mark J. |
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Environmental management |
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Ducey, Mark J. Johnson, Kenneth M. Belair, Ethan P. Cook, Barbara D. |
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the influence of human demography on land cover change in the great lakes states, usa |
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The Influence of Human Demography on Land Cover Change in the Great Lakes States, USA |
| abstract |
Abstract The Great Lakes region contains productive agricultural and forest lands, but it is also highly urbanized, with 32 of its 52 million residents living in nine large metropolitan areas. Urbanization of undeveloped areas may adversely affect the productivity of agricultural and forest lands, and the provision of ecosystem services. We combine demographic and remote sensing data to evaluate land cover change in the region using a two-phase statistical modeling approach that predicts the incidence and extent of land cover change for each of the region’s 10,579 county subdivisions. Observed patterns are spatially uneven, and the probability of land cover change is influenced by current land use, human habitation, industry, and demographic change. Pseudo R2 values varied from 0.053 to 0.338 for the first-phase logistic models predicting the presence of land cover change; second-stage beta models predicting the rate of change were more reliable, with pseudo R2 ranging from 0.225 to 0.675. Overall, changes from agriculture or greenspace to development were much more predictable than changes from agriculture to greenspace or vice versa, and demographic variables were much more important in models predicting change to development. Although models successfully predicted the general location of land cover change, and models from before the Great Recession were useful for predicting the location but not the amount of change during the recession, fine-grained prediction remained challenging. Understanding where future changes are most probable can inform planning and policy-making, which may reduce the impact of development on resource production, environmental health, and ecosystem services. © Springer Science+Business Media, LLC, part of Springer Nature 2018 |
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Abstract The Great Lakes region contains productive agricultural and forest lands, but it is also highly urbanized, with 32 of its 52 million residents living in nine large metropolitan areas. Urbanization of undeveloped areas may adversely affect the productivity of agricultural and forest lands, and the provision of ecosystem services. We combine demographic and remote sensing data to evaluate land cover change in the region using a two-phase statistical modeling approach that predicts the incidence and extent of land cover change for each of the region’s 10,579 county subdivisions. Observed patterns are spatially uneven, and the probability of land cover change is influenced by current land use, human habitation, industry, and demographic change. Pseudo R2 values varied from 0.053 to 0.338 for the first-phase logistic models predicting the presence of land cover change; second-stage beta models predicting the rate of change were more reliable, with pseudo R2 ranging from 0.225 to 0.675. Overall, changes from agriculture or greenspace to development were much more predictable than changes from agriculture to greenspace or vice versa, and demographic variables were much more important in models predicting change to development. Although models successfully predicted the general location of land cover change, and models from before the Great Recession were useful for predicting the location but not the amount of change during the recession, fine-grained prediction remained challenging. Understanding where future changes are most probable can inform planning and policy-making, which may reduce the impact of development on resource production, environmental health, and ecosystem services. © Springer Science+Business Media, LLC, part of Springer Nature 2018 |
| abstract_unstemmed |
Abstract The Great Lakes region contains productive agricultural and forest lands, but it is also highly urbanized, with 32 of its 52 million residents living in nine large metropolitan areas. Urbanization of undeveloped areas may adversely affect the productivity of agricultural and forest lands, and the provision of ecosystem services. We combine demographic and remote sensing data to evaluate land cover change in the region using a two-phase statistical modeling approach that predicts the incidence and extent of land cover change for each of the region’s 10,579 county subdivisions. Observed patterns are spatially uneven, and the probability of land cover change is influenced by current land use, human habitation, industry, and demographic change. Pseudo R2 values varied from 0.053 to 0.338 for the first-phase logistic models predicting the presence of land cover change; second-stage beta models predicting the rate of change were more reliable, with pseudo R2 ranging from 0.225 to 0.675. Overall, changes from agriculture or greenspace to development were much more predictable than changes from agriculture to greenspace or vice versa, and demographic variables were much more important in models predicting change to development. Although models successfully predicted the general location of land cover change, and models from before the Great Recession were useful for predicting the location but not the amount of change during the recession, fine-grained prediction remained challenging. Understanding where future changes are most probable can inform planning and policy-making, which may reduce the impact of development on resource production, environmental health, and ecosystem services. © Springer Science+Business Media, LLC, part of Springer Nature 2018 |
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The Influence of Human Demography on Land Cover Change in the Great Lakes States, USA |
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