| 1. | Title | Title | Consistency Of Forest Presence And Biomass Predictions Modeled Across Overlapping Spatial And Temporal Extents |
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| 2. | Creator | Author / affiliation / country | Mark D. Nelson; USDA Forest Service, Northern Research Station, FIA, USA; United States |
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| 2. | Creator | Author / affiliation / country | Sean P. Healey; USDA Forest Service, Rocky Mountain Research Station, I. and M., USA; United States |
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| 2. | Creator | Author / affiliation / country | Warren Keith Moser; USDA Forest Service, Northern Research Station, FIA, USA; United States |
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| 2. | Creator | Author / affiliation / country | Jeffrey G. Masek; GFSC, National Aeronautics and Space Administration, USA; United States |
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| 2. | Creator | Author / affiliation / country | Warren Cohen; USDA Forest Service, Pacific Northwest Research Station, USA; United States |
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| 3. | Subject | Keywords | Consistency analyses; North American Forest Dynamics; NAFD; Landsat; Random Forests; forest inventory; FIA |
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| 3. | Subject | Discipline(s) | Remote sensing |
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| 4. | Description | Abstract | We assessed the consistency across space and time of spatially explicit models of forest presence and biomass in southern Missouri, USA, for adjacent, partially overlapping satellite image Path/Rows, and for coincident satellite images from the same Path/Row acquired in different years. Such consistency in satellite image-based classification and estimation is critical to national and continental monitoring programs that depend upon processed satellite imagery, such as the North American Forest Dynamics Program. We tested the interchangeability of particular image acquisitions across time and space in the context of modeling forest biomass and forest presence with a non-parametric Random Forests-based approach. Validation at independent USA national forest inventory plots suggested statistically consistent model accuracy, even when the images used to apply the models were acquired in different years or in different image frames from the images used to build the models. For mapping projects using near-anniversary date imagery and employing careful radiometric correction, advantages of image interchangeability include the ability to build models with more ground data by combining adjacent image frames and the ability to apply models of assessed accuracy to early satellite images for which no corresponding field data may be available. |
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| 5. | Publisher | Publisher | Contemporary Journal Concept Press |
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| 6. | Contributor | Contributors / supporting agencies | U.S. Forest Service |
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| 7. | Date | Publication date | 2011-08-28 |
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| 8. | Type | Type | Text.Serial.Journal; Image anaysis; Random Forests |
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| 9. | Format | Format | PDF; application/pdf |
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| 10. | Identifier | Article URL | https://mcfns.com/index.php/Journal/en/article/view/3.14 |
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| 11. | Source | Journal / volume / issue / year / pages | Mathematical and Computational Forestry & Natural-Resource Sciences (MCFNS); Vol. 3 No. 2: MCFNS August 28, 2011; 102-113 (12) |
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| 11. | Source | Online ISSN | 1946-7664 |
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| 12. | Language | Language | en |
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| 13. | Relation | Supplementary files | |
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| 14. | Coverage | Geographical coverage | |
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| 15. | Rights | Rights / copyright | |
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