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dc.creatorHumagain, Kamal
dc.creatorPortillo-Quintero, Carlos
dc.creatorCox, Robert D.
dc.creatorCain, James W. III
dc.date.accessioned2021-07-12T19:37:03Z
dc.date.available2021-07-12T19:37:03Z
dc.date.issued2021
dc.identifier.citationHumagain K, Portillo-Quintero C, Cox RD, Cain JW III. Mapping Tree Density in Forests of the Southwestern USA Using Landsat 8 Data. Forests. 2017; 8(8):287. https://doi.org/10.3390/f8080287en_US
dc.identifier.urihttps://doi.org/10.3390/f8080287
dc.identifier.urihttps://hdl.handle.net/2346/87413
dc.descriptionThis is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly citeden_US
dc.description.abstractThe increase of tree density in forests of the American Southwest promotes extreme fire events, understory biodiversity losses, and degraded habitat conditions for many wildlife species. To ameliorate these changes, managers and scientists have begun planning treatments aimed at reducing fuels and increasing understory biodiversity. However, spatial variability in tree density across the landscape is not well-characterized, and if better known, could greatly influence planning efforts. We used reflectance values from individual Landsat 8 bands (bands 2, 3, 4, 5, 6, and 7) and calculated vegetation indices (difference vegetation index, simple ratios, and normalized vegetation indices) to estimate tree density in an area planned for treatment in the Jemez Mountains, New Mexico, characterized by multiple vegetation types and a complex topography. Because different vegetation types have different spectral signatures, we derived models with multiple predictor variables for each vegetation type, rather than using a single model for the entire project area, and compared the model-derived values to values collected from on-the-ground transects. Among conifer-dominated areas (73% of the project area), the best models (as determined by corrected Akaike Information Criteria (AICc)) included Landsat bands 2, 3, 4, and 7 along with simple ratios, normalized vegetation indices, and the difference vegetation index (R2 values for ponderosa: 0.47, piñon-juniper: 0.52, and spruce-fir: 0.66). On the other hand, in aspen-dominated areas (9% of the project area), the best model included individual bands 4 and 2, simple ratio, and normalized vegetation index (R2 value: 0.97). Most areas dominated by ponderosa, pinyon-juniper, or spruce-fir had more than 100 trees per hectare. About 54% of the study area has medium to high density of trees (100–1000 trees/hectare), and a small fraction (4.5%) of the area has very high density (>1000 trees/hectare). Our results provide a better understanding of tree density for identifying areas in need of treatment and planning for more effective treatment. Our analysis also provides an integrated method of estimating tree density across complex landscapes that could be useful for further restoration planning.en_US
dc.language.isoengen_US
dc.subjectFire Suppressionen_US
dc.subjectTree Densityen_US
dc.subjectLandsat 8en_US
dc.subjectWildfireen_US
dc.subjectRestorationen_US
dc.subjectJemez Mountainsen_US
dc.titleMapping Tree Density in Forests of the Southwestern USA Using Landsat 8 Dataen_US
dc.typeArticleen_US


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