Mapping Forest Characteristics at Fine Resolution across Large Landscapes of the Southeastern United States Using NAIP Imagery and FIA Field Plot Data
| Autor: | Nathaniel Anderson, Joseph St. Peter, John Hogland, Paul Medley, Jason B. Drake |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2018 |
| Předmět: |
010504 meteorology & atmospheric sciences
Geography Planning and Development 0211 other engineering and technologies lcsh:G1-922 02 engineering and technology 01 natural sciences Plot (graphics) Basal area FIA remote sensing NAIP Earth and Planetary Sciences (miscellaneous) Fine resolution Computers in Earth Sciences 021101 geological & geomatics engineering 0105 earth and related environmental sciences Forest inventory Field (geography) Remote sensing (archaeology) forest measurements Spatial ecology Environmental science Cartography lcsh:Geography (General) |
| Zdroj: | ISPRS International Journal of Geo-Information; Volume 7; Issue 4; Pages: 140 ISPRS International Journal of Geo-Information, Vol 7, Iss 4, p 140 (2018) |
| ISSN: | 2220-9964 |
| DOI: | 10.3390/ijgi7040140 |
| Popis: | Accurate information is important for effective management of natural resources. In the field of forestry, field measurements of forest characteristics such as species composition, basal area, and stand density are used to inform and evaluate management activities. Quantifying these metrics accurately across large landscapes in a meaningful way is extremely important to facilitate informed decision-making. In this study, we present a remote sensing based methodology to estimate species composition, basal area and stand tree density for pine and hardwood tree species at the spatial resolution of a Forest Inventory Analysis (FIA) program plot (78 m by 70 m). Our methodology uses textural metrics derived at this spatial scale to relate plot summaries of forest characteristics to remotely sensed National Agricultural Imagery Program (NAIP) aerial imagery across broad extents. Our findings quantify strong relationships between NAIP imagery and FIA field data. On average, models of basal area and trees per acre accounted for 43% of the variation in the FIA data, while models identifying species composition had less than 15.2% error in predicted class probabilities. Moreover, these relationships can be used to spatially characterize the condition of forests at fine spatial resolutions across broad extents. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|