Find research datasets worth reusing

openCC0Sep 2004View details →

Comparisons among five canopy-cover estimating methods in five Douglas-fir/western hemlock structure types in the western Oregon Cascades

Estimates of forest canopy cover are widely used in forest research and management, yet methods used to quantify canopy cover and the estimates they provide vary greatly. Four ground-based techniques for estimating overstory cover -line- intercept, spherical densiometer, moosehorn, and hemispherical photography-and cover estimates generated using the Forest Vegetation Simulator (FVS) were compared in five Douglas- fir/western hemlock structure types in western Oregon. Differences in cover estimates among the ground-based methods did not depend on the structure type in which they were measured (p=0.33). As expected, estimates of cover increased and within-stand variability decreased with increasing angle of view among techniques. However, the moosehorn provided the most conservative estimates of vertical-projection overstory cover. The FVS-generated cover was consistently lower (by up to 44%, 17% on average) than the ground-based estimates and is not advised as a substitute for ground-based measures in these forest types. Regression equations are provided to allow conversion among canopy cover estimates developed with the four ground-based methods.

openOpenDec 2013View details →

Far northeastern Siberia boreal forest data: Canopy cover across a larch forest density gradient

This dataset includes canopy cover within four larch stands near Cherskii, Siberia collected in 2012-2013. Data have not been published.

openCC (other)Jun 2020View details →

Canopy cover data from the Ice Storm Experiment (ISE) plots

Large-scale disturbances such as ice storms may increase in frequency and intensity as climate changes. While disturbances are a natural component of forest ecosystems, climatically driven alteration to historical patterns may impart fundamental change to ecosystem function. At Hubbard Brook Experimental Forest, NH, experimental ice storms of varying severity were applied to replicate plots of mature northern hardwoods to quantify their effects on forested ecosystems. We assessed ice storm treatment effects on insectivorous foliage-gleaning birds and their interactions with larval Lepidoptera. These birds are charismatic, of conservation concern, and are a major predator of caterpillars. In turn, lepidopterans are the dominant herbivores in temperate forests and are integral to ecosystem function. We predicted that avian abundance would increase due to additional structural heterogeneity caused by ice treatments, with a concomitant increase in caterpillar predation. Point counts were used to measure insectivorous bird activity in the ice storm experiment plots and additional control plots before and after treatments. Point counts were conducted in June 2015 and June 2016. Icing occurred in January-February 2016. We deployed and retrieved plasticine model caterpillars and estimated predation from characteristic marks to these surrogates. Abundance of foliage-gleaning birds was higher in the ice storm plots and birds responded to treatments as a single diffuse disturbance rather than on an individual plot level. All species except one were observed both before and after the ice treatments. Surprisingly, predation on caterpillar models was unaffected by ice storm treatments but rather was a function of caterpillar density. The increase in avian abundance in the ice storm treatment plots corroborates other studies of bird responses to relatively small-scale disturbances in forests and the limited change in species composition was expected given the plot size. We conclud

openCC (other)Sep 2019View details →

Perennial species canopy cover across grazed/ungrazed fencelines at the Jornada Basin LTER, 1986-ongoing

This ongoing data set contains percent canopy cover estimates of perennial plant species from transects that cross a grazed/ungrazed boundary fenceline of a single exclosure on the New Mexico State University Chihuahuan Desert Rangeland Research Center in Dona Ana County, New Mexico, USA. In the spring of 1982, as part of the establishment of the Jornada Long-Term Ecological Research site in southern New Mexico, a 135 ha portion of a 1500 ha, internally drained, watershed was exclosed from grazing by domestic livestock. Prior to exclosure the watershed, as well as the rest of the Jornada basin, had been moderately to heavily grazed for the past 100 years. Concurrent with grazing, the vegetation had undergone a dramatic change from desert grassland, with an almost continuous cover of C4 perennial grasses, to isolated patches of the original grassland in a mosaic with desert shrub dominated plant communities (Buffington and Herbel, 1965). The exclosure lies along a northeast facing piedmont slope at the base of a steep isolated mountain peak, and covers a variety of component landforms from the foot of the mountain to the basin floor. This provided the opportunity to investigate the response of vegetation with respect to landscape characteristics as well as release from grazing. This summary data set consists of percent canopy cover of all perennial plant species from the plant line intercept measurements on either side of the LTER-I exclosure East and West boundary fence. Sampling occurs approximately every five years; it was last conducted in November 2015 and will take place again in 2020.

openCC (other)Sep 2019View details →

Canopy cover for 9 perennial plant taxa across grazed/ungrazed fencelines at the Jornada Basin LTER, 1982-ongoing

This ongoing data set contains percent canopy cover estimates of 6 perennial plant species and 3 genera from transects that cross a grazed/ungrazed boundary fenceline of a single exclosure on the New Mexico State University Chihuahuan Desert Rangeland Research Center in Dona Ana County, New Mexico, USA. In the spring of 1982, as part of the establishment of the Jornada Long-Term Ecological Research site in southern New Mexico, a 135 ha portion of a 1500 ha, internally drained, watershed was exclosed from grazing by domestic livestock. Prior to exclosure the watershed, as well as the rest of the Jornada basin, had been moderately to heavily grazed for the past 100 years. Concurrent with grazing, the vegetation had undergone a dramatic change from desert grassland, with an almost continuous cover of C4 perennial grasses, to isolated patches of the original grassland in a mosaic with desert shrub dominated plant communities (Buffington and Herbel, 1965). The exclosure lies along a northeast facing piedmont slope at the base of a steep isolated mountain peak, and covers a variety of component landforms from the foot of the mountain to the basin floor. This provided the opportunity to investigate the response of vegetation with respect to landscape characteristics as well as release from grazing. This data set is limited to 6 perennial species and 3 genera because of the limited taxonomic resolution of the initial sampling in 1982. See data package knb-lter-jrn.210120001 for a dataset that contains all perennial species encountered but begins in 1986 instead of 1982. Sampling occurs approximately every five years; it was last conducted in November 2015 and will take place again in 2020.

opencc-zeroSep 2022View details →

Effects of canopy cover on fruiting intensity and fruit removal of a tropical invasive weed

Lantana camara (hereafter, Lantana) is among the worst invasive alien plants spread extensively across Africa, Australia and Asia at an alarming rate, posing significant challenges to conservation of native biodiversity. While, Lantana invasion is widely recognised to be more pronounced in open-canopy habitats (including deciduous forests, forest edges and gaps), the potential role of variation in seed dispersal across habitats varying in overstory canopy cover is poorly understood. Avian frugivores are among primary seed dispersers of the fleshy-fruited Lantana. We monitored 45 Lantana shrubs across a gradient of overstory canopy cover to determine the relationship between fruiting intensity and canopy cover. We watched 80 Lantana shrubs (240 h) across a canopy cover gradient to determine 1) differences in frugivore assemblage visiting Lantana across open- and closed-canopy habitats, 2) drivers of frugivore visitation on Lantana, and 3) relationship between seed disperser visitation rate and overstory canopy cover. We found that Lantana shrubs under low overstory canopy cover had higher fruit abundance than those in high canopy cover. Frugivore assemblage differed between Lantana shrubs in open- versus closed-canopy cover habitats. Drivers of frugivore visitation on Lantana varied across different frugivore species with a greater probability of occurrence of bulbuls (the primary seed dispersers of Lantana) on shrubs under low overstory canopy cover. Visitation rates of the effective seed dispersers were higher on shrubs under low overstory canopy cover. Thus, there was greater chances of dispersal of seeds in habitats with low overstory canopy cover. The study demonstrates variable fruiting intensity and fruit removal rate as a driver of differences in dispersal of seeds across habitats. It highlights greater vulnerability of open habitats to invasion and the need to prioritise Lantana management efforts in open habitats. Anthropogenic activities that lead to canopy openings (e.g. tree lopping and logging) likely facilitate Lantana invasion through greater fruit production and seed dispersal.

opencc-by-4.0Jun 2024View details →

Data from: Investigating the Association of Seasonal Dynamics in GEDI Canopy Cover Profiles and Sentinel-1 Backscatter in Temperate Forests

This dataset supports the analysis about Investigating the Association of Seasonal Dynamics in GEDI Canopy Cover Profiles and Sentinel-1 Backscatter in Temperate Forests

opencc-zeroJul 2024View details →

Data from: Canopy cover and soil moisture influence forest understory plant responses to experimental summer drought

Extreme droughts are globally increasing in frequency and severity. Most research on drought in forests focuses on the response of trees, while less is known about the impacts of drought on forest understory species and how these effects are moderated by the local environment. We assessed the impacts of a 45-day experimental summer drought on the performance of six boreal forest understory plants, using a transplant experiment with rainout shelters replicated across 25 sites. We recorded growth, vitality and reproduction immediately, two months, and one year after the simulated drought, and examined how differences in ambient soil moisture and canopy cover among sites influenced the effects of drought on the performance of each species. Drought negatively affected the growth and/or vitality of all species, but the effects were stronger and more persistent in the bryophytes than in the vascular plants. The two species associated with older forests, the moss Hylocomiastrum umbratum and the orchid Goodyera repens, suffered larger effects than the more generalist species included in the experiment. The drought reduced reproductive output in the moss Hylocomium splendens in the next growing season, but increased reproduction in the graminoid Luzula pilosa. Higher ambient soil moisture reduced some negative effects of drought on vascular plants. Both denser canopy cover and higher soil moisture alleviated drought effects on bryophytes, likely through alleviating cellular damage. Our experiment shows that boreal understory species can be adversely affected by drought and that effects might be stronger for bryophytes and species associated with older forests. Our results indicate that the effects of drought can vary over small spatial scales and that forest landscapes can be actively managed to alleviate drought effects on boreal forest biodiversity. For example, by managing the tree canopy and protecting hydrological networks.

embargoedcc-by-4.0Aug 2024View details →

ForestPaths: European canopy cover map

This repository contains a 10 m resolution canopy cover (at 5m height) map of the year 2020 over Europe derived from Sentinel-1 and Sentinel-2 data. The map is available as COGs over a 100 km grid in the spatial reference system EPSG 3035 (ETRS89 / LAEA Europe).   Known issues -        Due to the lack of GEDI data over the north of Europe, the accuracy of the model is expected to be lower above 52 degrees latitude.

opencc-zeroJul 2021View details →

The role of canopy cover dynamics over a decade of changes in the understory of an Atlantic beech-oak forest

This dataset hosts the main data and R codes of the analyses carried out to study the role of canopy cover dynamics over a decade of changes in the understory of an Atlantic Beech-Oak forest. We measured changes in understory taxonomical and functional composition, richness and diversity between 2006 and 2016, and relate those changes to changes in canopy coverage between both years. The data show changes between 2006 and 2016 in the species abundance, richness and diversity of 102 understory communities, and in the functional composition, richness and diversity for five functional traits (Leaf dry matter content, Specific leaf area, Leaf size, Plant height and Seed mass). Changes in canopy coverage between 2006 and 2016 were studied as an explanatory variable. The R codes show the main analyses carried out in the study: 1) The calculation of the functional composition, richness and diversity of the five traits studied (Leaf dry matter content, Specific leaf area, Leaf size, Plant height and Seed mass), 2) a Dunnett's modified Tukey-Kramer test used to test for significant relationships between four plot categories defined according to the presence or absence of canopy gaps (no gaps, gap closure, gap opening and gap persistence) and changes in the taxonomical and functional composition and diversity of the understory from 2006 to 2016. 3) An Indicator Species Analysis used to study the species that were indicators of gap opening or closure in the Atlantic Beech-Oak forest studied. 4) The calculation of the Standardized Effect Size for the functional traits of the indicator species, used to see if the species selected as gap indicators shared similar values of functional traits and had values significantly different from non-indicator species.

opencc-zeroOct 2021View details →

Canopy cover and ecological restoration increase natural regeneration of rainforest trees in the Western Ghats, India

Restoration of canopy cover through tree planting can assist in overcoming barriers to natural regeneration and catalyze recovery of degraded tropical forests. India has made international pledges to restore millions of hectares of degraded forests by 2030, but lacks empirical research on regeneration under different types of planted and natural overstories to guide this mission. We conducted a field study (65 plots of 25 m2) to examine the influence of overstory type and canopy cover on naturally regenerating tree seedlings across degraded rainforests (DR), mixed-native species ecological restoration sites (ER), monoculture eucalypt plantations (MP), and mature "benchmark" rainforests (BR) in the Western Ghats mountains of peninsular India. ER had higher native tree seedling densities and recovered community composition towards BR levels compared to DR, while communities in MP shifted in the opposite direction. Densities of native late-successional species increased with canopy cover (particularly in ER), but greater canopy cover was also associated with increases in alien species, a few of which are shade-tolerant. Further, in a nursery experiment comprising four rainforest species, seed germination and early survival increased with shade, but did not vary across soils originating from DR, ER, and MP. Our findings show that while improving canopy cover is important, doing so by planting diverse native species, and controlling invasive alien species, can benefit rainforest recovery in degraded rainforest fragments. Conversely, planting non-native monocultures in degraded forests, which is a prevalent practice in India, could prove counterproductive for forest recovery in the long term.

Relative Density Canopy Cover Outputs for Leon Lidar data in the Florida Panhandle 2018

Forest cover and density metrics (RDCC) extracted from 2018 Lidar in the Florida panhandle Leon. These 5m horizontal resolution rasters consist of 28 bands of forest cover and density metrics created using the lidR R software package from 2018 Lidar data. The 28 bands are listed in the following table:  <table> <tbody> <tr> <td> RDCC Band </td> <td> lidR short name </td> <td> Metric Description </td> </tr> <tr> <td> Band 1 </td> <td> Num_Returns </td> <td> Total number of returns in cell </td> </tr> <tr> <td> Band 2  </td> <td> Num_GrndRet </td> <td> Number of ground returns in cell </td> </tr> <tr> <td> Band 3 </td> <td> Num_1stRet </td> <td> Number of first returns in cell </td> </tr> <tr> <td> Band 4 </td> <td> Grnd_Elev </td> <td> Ground Elevations (above geoid, etc) </td> </tr> <tr> <td> Band 5 </td> <td> Mn_RH </td> <td> Mean of all Relative Heights </td> </tr> <tr> <td> Band 6 </td> <td> SD_RH </td> <td> Std. Dev of all Relative heights </td> </tr> <tr> <td> Band 7 </td> <td> RHt_95th </td> <td> Relative Height 95% </td> </tr> <tr> <td> Band 8 </td> <td> RHt_90th </td> <td> Relative Height 90% </td> </tr> <tr> <td> Band 9 </td> <td> RHt_75th </td> <td> Relative Height 75% </td> </tr> <tr> <td> Band 10 </td> <td> RHt_50th </td> <td> Relative Height 50% </td> </tr> <tr> <td> Band 11 </td> <td> RHt_25th </td> <td> Relative Height 25% </td> </tr> <tr> <td> Band 12 </td> <td> RHt_10th </td> <td> Relative Height 10% </td> </tr> <tr> <td> Band 13 </td> <td> RHt_05th </td> <td> Relative Height  5% </td> </tr> <tr> <td> Band 14 </td> <td> RD_2to10ft </td> <td> Relative Density 2 to 10 ft (Shrubs) </td> </tr> <tr> <td> Band 15 </td> <td> RD_10to20ft </td> <td> Relative Density 10 to 20 ft (High shrub/low midstory) </td> </tr> <tr> <td> Band 16 </td> <td> RD_20to49ft </td> <td> Relative Density 20 to 49 ft (High midstory) </td> </tr> <tr> <td> Band 17 </td> <td> RD_gt2ft </td> <td> Relative Density all returns gt 2 ft (for comp w/ CC) </td> </tr> <tr> <td> Band 18 </td> <td> RD_gt10ft </td> <td> Relative Density all returns gt 10 ft (for comp w/ CC) </td> </tr> <tr> <td> Band 19 </td> <td> RD_gt20ft </td> <td> Relative Density all returns gt 20 ft (for comp w/ CC) </td> </tr> <tr> <td> Band 20 </td> <td> RD_gt49ft </td> <td> Relative Density greater than 49 ft (Canopy) </td> </tr> <tr> <td> Band 21 </td> <td> CC_gt2ft </td> <td> Canopy Cover gt 2 ft (based only on first returns) </td> </tr> <tr> <td> Band 22 </td> <td> CC_gt10ft </td> <td> Canopy Cover gt 10 ft (based only on first returns) </td> </tr> <tr> <td> Band 23 </td> <td> CC_gt20ft </td> <td> Canopy Cover gt 20 ft (based only on first returns) </td> </tr> <tr> <td> Band 24 </td> <td> CC_gt49ft </td> <td> Canopy Cover gt 49 ft (based only on first returns) </td> </tr> <tr> <td> Band 25 </td> <td> MnRHgt2ft </td> <td> Mean of all relative heights gt 2 ft (includes shrubs, midstory and upper canopy) </td> </tr> <tr> <td> Band 26 </td> <td> MnRHgt10ft </td> <td> Mean of all relative heights gt 10 ft (includes all midstory and upper canopy) </td> </tr> <tr> <td> Band 27 </td> <td> MnRHgt20ft </td> <td> Mean of all relative heights gt 20 ft (includes high midstory and upper canopy) </td> </tr> <tr> <td> Band 28 </td> <td> MnRHgt49ft </td> <td> Mean of all relative heights gt 49 ft (includes upper canopy) </td> </tr> </tbody> </table> Full descriptions of the creation of these raster outputs is available in the companion publication - https://www.mdpi.com/2072-4292/13/23/4763

Relative Density Canopy Cover Outputs for Choctawhatchee Lidar data in the Florida Panhandle 2018

Forest cover and density metrics (RDCC) extracted from 2018 Lidar in the Florida panhandle Choctawhatchee. These 5m horizontal resolution rasters consist of 28 bands of forest cover and density metrics created using the lidR R software package from 2018 Lidar data. The 28 bands are listed in the following table:  <table> <tbody> <tr> <td> RDCC Band </td> <td> lidR short name </td> <td> Metric Description </td> </tr> <tr> <td> Band 1 </td> <td> Num_Returns </td> <td> Total number of returns in cell </td> </tr> <tr> <td> Band 2  </td> <td> Num_GrndRet </td> <td> Number of ground returns in cell </td> </tr> <tr> <td> Band 3 </td> <td> Num_1stRet </td> <td> Number of first returns in cell </td> </tr> <tr> <td> Band 4 </td> <td> Grnd_Elev </td> <td> Ground Elevations (above geoid, etc) </td> </tr> <tr> <td> Band 5 </td> <td> Mn_RH </td> <td> Mean of all Relative Heights </td> </tr> <tr> <td> Band 6 </td> <td> SD_RH </td> <td> Std. Dev of all Relative heights </td> </tr> <tr> <td> Band 7 </td> <td> RHt_95th </td> <td> Relative Height 95% </td> </tr> <tr> <td> Band 8 </td> <td> RHt_90th </td> <td> Relative Height 90% </td> </tr> <tr> <td> Band 9 </td> <td> RHt_75th </td> <td> Relative Height 75% </td> </tr> <tr> <td> Band 10 </td> <td> RHt_50th </td> <td> Relative Height 50% </td> </tr> <tr> <td> Band 11 </td> <td> RHt_25th </td> <td> Relative Height 25% </td> </tr> <tr> <td> Band 12 </td> <td> RHt_10th </td> <td> Relative Height 10% </td> </tr> <tr> <td> Band 13 </td> <td> RHt_05th </td> <td> Relative Height  5% </td> </tr> <tr> <td> Band 14 </td> <td> RD_2to10ft </td> <td> Relative Density 2 to 10 ft (Shrubs) </td> </tr> <tr> <td> Band 15 </td> <td> RD_10to20ft </td> <td> Relative Density 10 to 20 ft (High shrub/low midstory) </td> </tr> <tr> <td> Band 16 </td> <td> RD_20to49ft </td> <td> Relative Density 20 to 49 ft (High midstory) </td> </tr> <tr> <td> Band 17 </td> <td> RD_gt2ft </td> <td> Relative Density all returns gt 2 ft (for comp w/ CC) </td> </tr> <tr> <td> Band 18 </td> <td> RD_gt10ft </td> <td> Relative Density all returns gt 10 ft (for comp w/ CC) </td> </tr> <tr> <td> Band 19 </td> <td> RD_gt20ft </td> <td> Relative Density all returns gt 20 ft (for comp w/ CC) </td> </tr> <tr> <td> Band 20 </td> <td> RD_gt49ft </td> <td> Relative Density greater than 49 ft (Canopy) </td> </tr> <tr> <td> Band 21 </td> <td> CC_gt2ft </td> <td> Canopy Cover gt 2 ft (based only on first returns) </td> </tr> <tr> <td> Band 22 </td> <td> CC_gt10ft </td> <td> Canopy Cover gt 10 ft (based only on first returns) </td> </tr> <tr> <td> Band 23 </td> <td> CC_gt20ft </td> <td> Canopy Cover gt 20 ft (based only on first returns) </td> </tr> <tr> <td> Band 24 </td> <td> CC_gt49ft </td> <td> Canopy Cover gt 49 ft (based only on first returns) </td> </tr> <tr> <td> Band 25 </td> <td> MnRHgt2ft </td> <td> Mean of all relative heights gt 2 ft (includes shrubs, midstory and upper canopy) </td> </tr> <tr> <td> Band 26 </td> <td> MnRHgt10ft </td> <td> Mean of all relative heights gt 10 ft (includes all midstory and upper canopy) </td> </tr> <tr> <td> Band 27 </td> <td> MnRHgt20ft </td> <td> Mean of all relative heights gt 20 ft (includes high midstory and upper canopy) </td> </tr> <tr> <td> Band 28 </td> <td> MnRHgt49ft </td> <td> Mean of all relative heights gt 49 ft (includes upper canopy) </td> </tr> </tbody> </table> Full descriptions of the creation of these raster outputs is available in the companion publication - https://www.mdpi.com/2072-4292/13/23/4763

Relative Density Canopy Cover Outputs for Block3 Lidar data in the Florida Panhandle 2018

Forest cover and density metrics (RDCC) extracted from 2018 Lidar in the Florida panhandle Block 3. These 5m horizontal resolution rasters consist of 28 bands of forest cover and density metrics created using the lidR R software package from 2018 Lidar data. The 28 bands are listed in the following table:  <table> <tbody> <tr> <td> RDCC Band </td> <td> lidR short name </td> <td> Metric Description </td> </tr> <tr> <td> Band 1 </td> <td> Num_Returns </td> <td> Total number of returns in cell </td> </tr> <tr> <td> Band 2  </td> <td> Num_GrndRet </td> <td> Number of ground returns in cell </td> </tr> <tr> <td> Band 3 </td> <td> Num_1stRet </td> <td> Number of first returns in cell </td> </tr> <tr> <td> Band 4 </td> <td> Grnd_Elev </td> <td> Ground Elevations (above geoid, etc) </td> </tr> <tr> <td> Band 5 </td> <td> Mn_RH </td> <td> Mean of all Relative Heights </td> </tr> <tr> <td> Band 6 </td> <td> SD_RH </td> <td> Std. Dev of all Relative heights </td> </tr> <tr> <td> Band 7 </td> <td> RHt_95th </td> <td> Relative Height 95% </td> </tr> <tr> <td> Band 8 </td> <td> RHt_90th </td> <td> Relative Height 90% </td> </tr> <tr> <td> Band 9 </td> <td> RHt_75th </td> <td> Relative Height 75% </td> </tr> <tr> <td> Band 10 </td> <td> RHt_50th </td> <td> Relative Height 50% </td> </tr> <tr> <td> Band 11 </td> <td> RHt_25th </td> <td> Relative Height 25% </td> </tr> <tr> <td> Band 12 </td> <td> RHt_10th </td> <td> Relative Height 10% </td> </tr> <tr> <td> Band 13 </td> <td> RHt_05th </td> <td> Relative Height  5% </td> </tr> <tr> <td> Band 14 </td> <td> RD_2to10ft </td> <td> Relative Density 2 to 10 ft (Shrubs) </td> </tr> <tr> <td> Band 15 </td> <td> RD_10to20ft </td> <td> Relative Density 10 to 20 ft (High shrub/low midstory) </td> </tr> <tr> <td> Band 16 </td> <td> RD_20to49ft </td> <td> Relative Density 20 to 49 ft (High midstory) </td> </tr> <tr> <td> Band 17 </td> <td> RD_gt2ft </td> <td> Relative Density all returns gt 2 ft (for comp w/ CC) </td> </tr> <tr> <td> Band 18 </td> <td> RD_gt10ft </td> <td> Relative Density all returns gt 10 ft (for comp w/ CC) </td> </tr> <tr> <td> Band 19 </td> <td> RD_gt20ft </td> <td> Relative Density all returns gt 20 ft (for comp w/ CC) </td> </tr> <tr> <td> Band 20 </td> <td> RD_gt49ft </td> <td> Relative Density greater than 49 ft (Canopy) </td> </tr> <tr> <td> Band 21 </td> <td> CC_gt2ft </td> <td> Canopy Cover gt 2 ft (based only on first returns) </td> </tr> <tr> <td> Band 22 </td> <td> CC_gt10ft </td> <td> Canopy Cover gt 10 ft (based only on first returns) </td> </tr> <tr> <td> Band 23 </td> <td> CC_gt20ft </td> <td> Canopy Cover gt 20 ft (based only on first returns) </td> </tr> <tr> <td> Band 24 </td> <td> CC_gt49ft </td> <td> Canopy Cover gt 49 ft (based only on first returns) </td> </tr> <tr> <td> Band 25 </td> <td> MnRHgt2ft </td> <td> Mean of all relative heights gt 2 ft (includes shrubs, midstory and upper canopy) </td> </tr> <tr> <td> Band 26 </td> <td> MnRHgt10ft </td> <td> Mean of all relative heights gt 10 ft (includes all midstory and upper canopy) </td> </tr> <tr> <td> Band 27 </td> <td> MnRHgt20ft </td> <td> Mean of all relative heights gt 20 ft (includes high midstory and upper canopy) </td> </tr> <tr> <td> Band 28 </td> <td> MnRHgt49ft </td> <td> Mean of all relative heights gt 49 ft (includes upper canopy) </td> </tr> </tbody> </table> Full descriptions of the creation of these raster outputs is available in the companion publication - https://www.mdpi.com/2072-4292/13/23/4763

Relative Density Canopy Cover Outputs for Block2 Lidar data in the Florida Panhandle 2018

Forest cover and density metrics (RDCC) extracted from 2018 Lidar in the Florida panhandle Block 2. These 5m horizontal resolution rasters consist of 28 bands of forest cover and density metrics created using the lidR R software package from 2018 Lidar data. The 28 bands are listed in the following table:  <table> <tbody> <tr> <td>RDCC Band</td> <td>lidR short name</td> <td>Metric Description</td> </tr> <tr> <td>Band 1</td> <td>Num_Returns</td> <td>Total number of returns in cell</td> </tr> <tr> <td>Band 2 </td> <td>Num_GrndRet</td> <td>Number of ground returns in cell</td> </tr> <tr> <td>Band 3</td> <td>Num_1stRet</td> <td>Number of first returns in cell</td> </tr> <tr> <td>Band 4</td> <td>Grnd_Elev</td> <td>Ground Elevations (above geoid, etc)</td> </tr> <tr> <td>Band 5</td> <td>Mn_RH</td> <td>Mean of all Relative Heights</td> </tr> <tr> <td>Band 6</td> <td>SD_RH</td> <td>Std. Dev of all Relative heights</td> </tr> <tr> <td>Band 7</td> <td>RHt_95th</td> <td>Relative Height 95%</td> </tr> <tr> <td>Band 8</td> <td>RHt_90th</td> <td>Relative Height 90%</td> </tr> <tr> <td>Band 9</td> <td>RHt_75th</td> <td>Relative Height 75%</td> </tr> <tr> <td>Band 10</td> <td>RHt_50th</td> <td>Relative Height 50%</td> </tr> <tr> <td>Band 11</td> <td>RHt_25th</td> <td>Relative Height 25%</td> </tr> <tr> <td>Band 12</td> <td>RHt_10th</td> <td>Relative Height 10%</td> </tr> <tr> <td>Band 13</td> <td>RHt_05th</td> <td>Relative Height  5%</td> </tr> <tr> <td>Band 14</td> <td>RD_2to10ft</td> <td>Relative Density 2 to 10 ft (Shrubs)</td> </tr> <tr> <td>Band 15</td> <td>RD_10to20ft</td> <td>Relative Density 10 to 20 ft (High shrub/low midstory)</td> </tr> <tr> <td>Band 16</td> <td>RD_20to49ft</td> <td>Relative Density 20 to 49 ft (High midstory)</td> </tr> <tr> <td>Band 17</td> <td>RD_gt2ft</td> <td>Relative Density all returns gt 2 ft (for comp w/ CC)</td> </tr> <tr> <td>Band 18</td> <td>RD_gt10ft</td> <td>Relative Density all returns gt 10 ft (for comp w/ CC)</td> </tr> <tr> <td>Band 19</td> <td>RD_gt20ft</td> <td>Relative Density all returns gt 20 ft (for comp w/ CC)</td> </tr> <tr> <td>Band 20</td> <td>RD_gt49ft</td> <td>Relative Density greater than 49 ft (Canopy)</td> </tr> <tr> <td>Band 21</td> <td>CC_gt2ft</td> <td>Canopy Cover gt 2 ft (based only on first returns)</td> </tr> <tr> <td>Band 22</td> <td>CC_gt10ft</td> <td>Canopy Cover gt 10 ft (based only on first returns)</td> </tr> <tr> <td>Band 23</td> <td>CC_gt20ft</td> <td>Canopy Cover gt 20 ft (based only on first returns)</td> </tr> <tr> <td>Band 24</td> <td>CC_gt49ft</td> <td>Canopy Cover gt 49 ft (based only on first returns)</td> </tr> <tr> <td>Band 25</td> <td>MnRHgt2ft</td> <td>Mean of all relative heights gt 2 ft (includes shrubs, midstory and upper canopy)</td> </tr> <tr> <td>Band 26</td> <td>MnRHgt10ft</td> <td>Mean of all relative heights gt 10 ft (includes all midstory and upper canopy)</td> </tr> <tr> <td>Band 27</td> <td>MnRHgt20ft</td> <td>Mean of all relative heights gt 20 ft (includes high midstory and upper canopy)</td> </tr> <tr> <td>Band 28</td> <td>MnRHgt49ft</td> <td>Mean of all relative heights gt 49 ft (includes upper canopy)</td> </tr> </tbody> </table> Full descriptions of the creation of these raster outputs is available in the companion publication - https://www.mdpi.com/2072-4292/13/23/4763