Leaf-off Season Research Articles

Seasonal, Diurnal and Wind-Direction-Dependent Variations of the Aerodynamic Roughness Length in Two Typical Forest Ecosystems of China

Aerodynamic roughness length (z(subscript om)) is an important parameter for reliably simulating surface fluxes. The parameter varies with wind speed, atmospheric stratification, terrain and other factors; however, variations of this parameter are not properly considered in most models, which may result in uncertainties in simulating surface latent heat and sensible heat flux. There have been few studies of the diurnal and wind-direction dependent variations in z(subscript om). This study analyzes the seasonal, diurnal and wind-direction-dependent variations in z(subscript om) calculated from the profile of meteorological data for two forest systems of China, and explores the mechanism underlying these variations. Annually averaged and monthly averaged diurnal variations in z(subscript om) are obvious and similar at a Changbai Mountain (CBS) site located in northeast China and a Qianyanzhou (QYZ) site located in southeast China. z(subscript om) is much higher at night than during the day. The diurnal variation in z(subscript om) is due to a change in atmospheric stratification. The seasonality of z(subscript om) differs at two sites. (z(subscript om)) has sizable seasonal variation and is lower in the leaf-off season than in the growing season at CBS. At QYZ, z(subscript om) does not have an obvious seasonal pattern. However, at QYZ, the short-term fluctuation is greater than that at CBS. The obvious seasonal variation in z(subscript om) at CBS is related to the great seasonal change in the leaf area index. The noticeable short-term wind-direction-dependent variations in z(subscript om) at QYZ are attributed to the heterogeneous terrain there.

Analysis of Elevation Changes Detected from Multi-Temporal LiDAR Surveys in Forested Landslide Terrain in Western Oregon

Research Article| November 01, 2010 Analysis of Elevation Changes Detected from Multi-Temporal LiDAR Surveys in Forested Landslide Terrain in Western Oregon WILLIAM J BURNS; WILLIAM J BURNS 1Oregon Department of Geology and Mineral Industries, 800 NE Oregon Street, Portland, OR 97232 Search for other works by this author on: GSW Google Scholar JEFFREY A COE; JEFFREY A COE 2U.S. Geological Survey, Denver Federal Center, Mail Stop 966, Denver, CO 80225 Search for other works by this author on: GSW Google Scholar BASAK SENER KAYA; BASAK SENER KAYA 3Colorado School of Mines, Division of Engineering, Golden, CO 80401 Search for other works by this author on: GSW Google Scholar LINA MA LINA MA 4Oregon Department of Geology and Mineral Industries, 800 NE Oregon Street, Portland, OR 97232 Search for other works by this author on: GSW Google Scholar Author and Article Information WILLIAM J BURNS 1Oregon Department of Geology and Mineral Industries, 800 NE Oregon Street, Portland, OR 97232 JEFFREY A COE 2U.S. Geological Survey, Denver Federal Center, Mail Stop 966, Denver, CO 80225 BASAK SENER KAYA 3Colorado School of Mines, Division of Engineering, Golden, CO 80401 LINA MA 4Oregon Department of Geology and Mineral Industries, 800 NE Oregon Street, Portland, OR 97232 Publisher: Association of Environmental & Engineering Geologists First Online: 02 Mar 2017 Online ISSN: 1558-9161 Print ISSN: 1078-7275 Copyright © 2010 EEGS Environmental & Engineering Geoscience (2010) 16 (4): 315–341. https://doi.org/10.2113/gseegeosci.16.4.315 Article history First Online: 02 Mar 2017 Cite View This Citation Add to Citation Manager Share Icon Share Facebook Twitter LinkedIn MailTo Tools Icon Tools Get Permissions Search Site Citation WILLIAM J BURNS, JEFFREY A COE, BASAK SENER KAYA, LINA MA; Analysis of Elevation Changes Detected from Multi-Temporal LiDAR Surveys in Forested Landslide Terrain in Western Oregon. Environmental & Engineering Geoscience 2010;; 16 (4): 315–341. doi: https://doi.org/10.2113/gseegeosci.16.4.315 Download citation file: Ris (Zotero) Refmanager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex toolbar search Search Dropdown Menu toolbar search search input Search input auto suggest filter your search All ContentBy SocietyEnvironmental & Engineering Geoscience Search Advanced Search Abstract We examined elevation changes detected from two successive sets of Light Detection and Ranging (LiDAR) data in the northern Coast Range of Oregon. The first set of LiDAR data was acquired during leaf-on conditions and the second set during leaf-off conditions. We were able to successfully identify and map active landslides using a differential digital elevation model (DEM) created from the two LiDAR data sets, but this required the use of thresholds (0.50 and 0.75 m) to remove noise from the differential elevation data, visual pattern recognition of landslide-induced elevation changes, and supplemental QuickBird satellite imagery. After mapping, we field-verified 88 percent of the landslides that we had mapped with high confidence, but we could not detect active landslides with elevation changes of less than 0.50 m. Volumetric calculations showed that a total of about 18,100 m3 of material was missing from landslide areas, probably as a result of systematic negative elevation errors in the differential DEM and as a result of removal of material by erosion and transport. We also examined the accuracies of 285 leaf-off LiDAR elevations at four landslide sites using Global Positioning System and total station surveys. A comparison of LiDAR and survey data indicated an overall root mean square error of 0.50 m, a maximum error of 2.21 m, and a systematic error of 0.09 m. LiDAR ground-point densities were lowest in areas with young conifer forests and deciduous vegetation, which resulted in extensive interpolations of elevations in the leaf-on, bare-earth DEM. For optimal use of multi-temporal LiDAR data in forested areas, we recommend that all data sets be flown during leaf-off seasons. You do not have access to this content, please speak to your institutional administrator if you feel you should have access.

Influence of incidence angle on detecting flooded forests using C-HH synthetic aperture radar data

Hydrology is the single most important abiotic factor in the formation and functioning of a wetland. Many limitations still exist to accurately characterizing wetland hydrology over large spatial extents, especially in forested wetlands. Imaging radar has emerged as a viable tool for wetland flood mapping, although the limitations of radar data remain uncertain. The influence of incidence angle on the ability to detect flooding in different forest types was examined using C-HH Radarsat-1 data (23.5°, 27.5°, 33.5°, 39.0°, 43.5°, and 47.0°) during the leaf-off and leaf-on seasons. The ability to detect flooding under leaf-on conditions varied much more according to incidence angle while forest type (open canopy tupelo-cypress, tupelo-cypress, and bottomland hardwood) had a greater effect during the leaf-off season. When all forest types were considered together, backscatter generally decreased with increasing incidence angle under all conditions (2.45 dB between 23.5° and 47.0° flooded, leaf-off; 2.28 dB between 23.5° and 47.0° not flooded, leaf-off; 0.62 between 23.5° and 43.5° flooded, leaf-on; 1.73 dB between 23.5° and 43.5° not flooded, leaf-on; slope was not constant between incidence angles), but the distinction between flooded and non-flooded areas did not decline sharply with incidence angle. Differentiation of flooded and non-flooded forests was similar during the leaf-off and leaf-on seasons. The ability to detect inundation under forest canopies was less than expected at smaller incidence angles and greater than expected at larger incidence angles, based on the results of previous studies. Use of a wider range of incidence angles during the entire year increases the temporal resolution of imagery which may, in turn, enhance mapping of inundation beneath forest canopies.

Assessment of C-band synthetic aperture radar data for mapping and monitoring Coastal Plain forested wetlands in the Mid-Atlantic Region, U.S.A.

Multi-temporal C-band SAR data (C-HH and C-VV), collected by ERS-2 and ENVISAT satellite systems, are compared with field observations of hydrology (i.e., inundation and soil moisture) and National Wetland Inventory maps (U.S. Fish and Wildlife Service) of a large forested wetland complex adjacent to the Patuxent and Middle Patuxent Rivers, tributaries of the Chesapeake Bay. Multi-temporal C-band SAR data were shown to be capable of mapping forested wetlands and monitoring hydroperiod (i.e., temporal fluctuations in inundation and soil moisture) at the study site, and the discrimination of wetland from upland was improved with 10 m digital elevation data. Principal component analysis was used to summarize the multi-temporal SAR data sets and to isolate the dominant temporal trend in inundation and soil moisture (i.e., relative hydroperiod). Significant positive, linear correlations were found between the first principal component and percent area flooded and soil moisture. The correlation ( r 2) between the first principal component (PC1) of multi-temporal C-HH SAR data and average soil moisture was 0.88 ( p = < .0001) during the leaf-off season and 0.87 ( p = < .0001) during the leaf-on season, while the correlation between PC1 and average percent area inundated was 0.82 ( p = < .0001) and 0.47 ( p = .0016) during the leaf-off and leaf-on seasons, respectively. When compared to field data, the SAR forested wetland maps identified areas that were flooded for 25% of the time with 63–96% agreement and areas flooded for 5% of the time with 44–89% agreement, depending on polarization and time of year. The results are encouraging and justify further studies to attempt to quantify the relative SAR-derived hydroperiod classes in terms of physical variables and also to test the application of SAR data to more diverse landscapes at a broader scale. The present evidence suggests that the SAR data will significantly improve routine wooded wetland mapping.

Using C-Band Synthetic Aperture Radar Data to Monitor Forested Wetland Hydrology in Maryland's Coastal Plain, USA

<para xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> Hydrology (i.e., inundation and soil moisture) is the most important abiotic factor controlling wetland function and extent, and scientists predict that wetland hydrology can be significantly altered over relatively short timescales due to climate change and anthropogenic impact. Whereas broadscale hydrology is difficult to monitor in forested wetlands with ground-based and optical remote sensing methods, C-band synthetic aperture radar (SAR) systems have the potential to improve the capability to monitor forested wetland hydrology. In this study, we examined the use of Environmental Satellite Advanced SAR (C-HH and C-VV) data for monitoring levels of inundation and soil moisture throughout the year in a typical Mid-Atlantic floodplain and some of the main limitations inherent to C-band data (i.e., polarization and plant phenology) in this environment. The relationships between the backscatter coefficient <formula formulatype="inline"><tex>$\sigma^{0}$</tex></formula> and inundation, soil moisture, tree basal area, tree height, and forest canopy closure were examined. Significant differences in C-HH <formula formulatype="inline"><tex>$\sigma^{0}$</tex></formula> were found between forested areas of varying hydrology (0%–60% area inundated) throughout the year and in C-VV <formula formulatype="inline"><tex>$ \sigma^{0}$</tex></formula> during the leaf-off season. As expected, C-HH SAR backscatter was better correlated with inundation and soil moisture than was C-VV SAR backscatter, and the correlations between both polarizations of backscatter and hydrology were stronger during the leaf-off season (C-HH leaf-off <formula formulatype="inline"><tex> $r^{2} = 0.50$</tex></formula>, leaf-on <formula formulatype="inline"><tex>$r^{2} = 0.39$</tex></formula>; C-VV leaf-off <formula formulatype="inline"><tex>$r^{2} = 0.21$</tex></formula>, leaf-on <formula formulatype="inline"> <tex>$r^{2} = 0.19$</tex></formula>; all significant at <formula formulatype="inline"><tex>$p ≪ 0.0001$</tex> </formula> level). Based on our findings, we concluded that the C-HH data are useful for monitoring hydrology beneath forest canopies throughout the year, whereas the C-VV data can be used during the leaf-off season. Our findings support previous studies that concluded that C-band imagery can be used to monitor forested wetland hydrology in large floodplains that are fully inundated. However, this study used detailed <emphasis emphasistype="italic">in situ</emphasis> measurements and demonstrated that C-band SAR data can also be used to monitor forested wetland hydrology in smaller partially inundated floodplains, which are more common in the Mid-Atlantic. </para>

Use of a dark object concept and support vector machines to automate forest cover change analysis

An automated method was developed for mapping forest cover change using satellite remote sensing data sets. This multi-temporal classification method consists of a training data automation (TDA) procedure and uses the advanced support vector machines (SVM) algorithm. The TDA procedure automatically generates training data using input satellite images and existing land cover products. The derived high quality training data allow the SVM to produce reliable forest cover change products. This approach was tested in 19 study areas selected from major forest biomes across the globe. In each area a forest cover change map was produced using a pair of Landsat images acquired around 1990 and 2000. High resolution IKONOS images and independently developed reference data sets were available for evaluating the derived change products in 7 of those areas. The overall accuracy values were over 90% for 5 areas, and were 89.4% and 89.6% for the remaining two areas. The user's and producer's accuracies of the forest loss class were over 80% for all 7 study areas, demonstrating that this method is especially effective for mapping major disturbances with low commission errors. IKONOS images were also available in the remaining 12 study areas but they were either located in non-forest areas or in forest areas that did not experience forest cover change between 1990 and 2000. For those areas the IKONOS images were used to assist visual interpretation of the Landsat images in assessing the derived change products. This visual assessment revealed that for most of those areas the derived change products likely were as reliable as those in the 7 areas where accuracy assessment was conducted. The results also suggest that images acquired during leaf-off seasons should not be used in forest cover change analysis in areas where deciduous forests exist. Being highly automatic and with demonstrated capability to produce reliable change products, the TDA-SVM method should be especially useful for quantifying forest cover change over large areas.

Seasonal Home Range and Diurnal Movements of Sylvilagus obscurus (Appalachian Cottontail) at Dolly Sods, West Virginia

The purpose of the study was to estimate seasonal home ranges of Sylvilagus obscurus (Appalachian cottontail) within dense ericaceous and coniferous cover at its type locality, the Dolly Sods Scenic Area in West Virginia. Ninety-five percent adaptive kernel (AK) home ranges of rabbits ranged from 5.7–13.3 ha during the leaf-on season (May–September; n = 5) and 1.5–9.0 ha during the leaf-off season (October–April; n = 14). Fifty-percent AK core areas ranged from 0.9–2.5 ha during the leaf-on season and 0.1–2.5 ha during the leaf-off season. Males occupied larger home ranges during the leaf-on than leaf-off season, but female ranges did not differ seasonally. These results demonstrate seasonal differences in spatial and associated resource requirements of Appalachian cottontails and the need for large tracts of appropriate habitat for travel lanes to maintain viable populations of this species.

Flow divergence and density flows above and below a deciduous forest: Part II. Below-canopy thermotopographic flows

Downslope thermotopographic flows (drainage flows) and the resulting horizontal flow divergence and advection have been suggested to cause systematic underestimates to nighttime ecosystem–atmosphere exchange measurements of CO 2 and other scalars above tall vegetation in hilly terrain. Flux correction methods have been proposed using simple models which link measured vertical flow convergence above canopy to horizontal divergence. In Part I (Froelich, N.J., Schmid, H.P., Grimmond, C.S.B., Su, H.-B., Oliphant, A.J., 2005. Flow divergence and density flows above and below a deciduous forest. Part 1: non-zero mean vertical wind above canopy. Agric. For. Meteorol. 133, 140–152.), we examined vertical velocities above canopy at a flux tower in Morgan-Monroe State Forest (MMSF), Indiana, USA, and found evidence of vertical flow convergence and horizontal divergence. Here, we examine whether sub-canopy flow through a small gully in the vicinity of the flux tower was thermotopographically driven, and was linked to the flow divergence found above canopy. While flow in the gully was frequently aligned with the mean wind aloft, indicating dynamic coupling, there were periods when the wind in the gully appeared to be decoupled from the flow aloft and was consistent with thermotopographic flow forcings (including geometry, temperature gradient, and net radiation). During the leaf-off season, these episodes exhibited a classic thermotopographic pattern, with down-gully nighttime flow and up-gully daytime flow. However, during the leaf-on season, the pattern was reversed: during the daytime, flow was down-gully consistent with inversion conditions occurring below the dense leaf canopy; at night, flow was up-gully, consistent with below-canopy lapse conditions. The thermotopographic flow during the leaf-on season suggests horizontal flow convergence at night and divergence during the day, and is shown to be decoupled from the flow aloft. While this research focuses only on flow patterns and not explicitly on CO 2 gradients or fluxes, these findings suggest that inferences about drainage flow/advection and corrections to flux measurements based on above-canopy conditions alone may be inappropriate.

Flow divergence and density flows above and below a deciduous forest: Part I. Non-zero mean vertical wind above canopy

Ecosystem–atmosphere exchange flux measurements above tall vegetation in hilly terrain are well known to suffer from systematic underestimates of nighttime fluxes of CO 2 and other scalars with significant sources in or below the canopy. This bias is commonly attributed to advection driven by thermotopographic density flows and the resulting horizontal flow divergence. Flux correction methods have been proposed based on this notion. To examine the structure and dynamics of horizontal flow divergence and vertical convergence mean vertical velocities are analyzed. These are derived from sonic anemometers at 1.8 and 1.3 times canopy height for 3 years above a deciduous forest in hilly terrain at the Morgan–Monroe State Forest (Indiana, USA) Fluxnet site. Measured vertical velocities are linked to forcing parameters represented in the equations of motion and heat for sloping terrain. In the leaf-off season, the data suggest that the dynamics and daily patterns of horizontal flow divergence (implied from vertical convergence through continuity) are entirely consistent with the hypothesis that the divergence is driven by thermotopographic density flows. However, in the vegetative season with a full canopy, a more complex picture emerges, suggesting strong dynamic and thermal decoupling of the horizontal divergence below canopy from flow conditions above. Thus we conclude that flux correction methods based on above-canopy conditions alone may significantly misrepresent scalar transport below canopy during the vegetative season and should be avoided.

INFLUENCE OF PARTIAL TIMBER HARVESTING ON AMERICAN MARTENS IN NORTH-CENTRAL MAINE

We investigated habitat selection and home-range characteristics of American martens (Martes americana) that occupied home ranges with partially harvested stands characterized by basal area of trees <18 m2/ha and canopy closure <30%. During the leaf-on season (1 May–31 Oct), martens selected second-growth (80–140-years-old, >9-m tree height) forest stands (deciduous, coniferous, and mixed coniferous-deciduous) and mixed stands that were partially harvested (x̄ = 13 m2/ha residual basal area, >9-m tree height), and they selected against forests regenerating after clearcutting (≤6-m tree height, cuts ≤24-years-old). Marten home ranges included a greater proportion of partially harvested stands during the leaf-on season (maximum = 73%) than during leaf-off (1 Nov–30 Apr; maximum = 34%). Higher use of partially harvested stands during the leaf-on season coincided with greater canopy closure, higher use of small mammals, and greater relative densities of small mammals. During the leaf-off season, martens exhibited reduced relative selection for partially harvested and regenerating stands and increased selection for second-growth forest types. Partially harvested and regenerating clearcut stands had canopy closure <30% and basal area of trees >9-m tall of <13 m2/ha; both were below published thresholds required by martens. Coincidentally, home-range areas of martens increased during the leaf-off season to include a greater proportion of second-growth forest and less partially harvested forest. Further, martens with partial harvesting in their home ranges used areas almost twice as large during the leaf-off season as martens with no partial harvesting. Snowshoe hares (Lepus americanus) were prevalent prey for martens during the leaf-off season, and partially harvested stands had the lowest density of hares among all forest overstory types. Our findings suggest that the combination of insufficient basal area and overhead canopy closure, subnivean behavior of small mammals, increased reliance on hares, and reduced density of snowshoe hares relative to second-growth forest types reduced habitat quality in partially harvested stands during the leaf-off season. We suggest land managers retain basal areas >18 m2/ha and canopy closure >30% during winter to maximize use by martens in stands where partial harvesting is practiced.

Vegetation Inventory of a Temperate Biosphere Reserve in China by Image Fusion of Landsat TM and SPOT HRV

Vegetation cover types on Changbai Mountain, a natural biosphere reserve (2,000 km2) in northeast China, were derived by using multisensor satellite imagery fused with Landsat TM and SPOT HRV-XS. DEM data were used for improving classification accuracy. Cover types were classified into 20 groups. Bands 4 and 5 of Landsat TM image acquired on July 18, 1997, and band 1 of SPOT HRV-XS image acquired on Oct. 19, 1992, were fused to a false color image, and maximum likelihood supervised classification was performed. Data fusion showed high accuracy of identification, compared to individual images. The overall accuracy of classification of individual images by SPOT HRV-XS reached 56%, and TM 66%, while the fused data set provided accuracy of about 78%, which was raised to 81% after recoding by using DEM. There were five vegetation zones on the mountain, from the base to the peak: hardwood forest zone, mixed forest zone, conifer forest zone, birch forest zone, and tundra zone. Spruce-fir dominated conifer forest was the most prevalent (nearly 50%) vegetation type, followed by Korean pine and mixed forest (17%) and larch forest (5%). HRV image taken in leaf-off season is useful for discriminating forest from non-forest, and evergreen forest from hardwood forest, while the summer image (TM) provides detailed information on the difference in similar vegetation types, like hardwood forest with different compositions.

MIXLIGHT: a flexible light transmission model for mixed-species forest stands

We describe the calibration and structure of a multi-species, two-scale light transmission model, and demonstrate its effectiveness for predicting instantaneous light availability at the stand scale across a wide range of forest stand compositions. The model, MIXLIGHT, calculates light transmission through the forest overstory at the stand or microsite scale using standard forest inventory data and two other parameters, foliage area density and foliage inclination. Since MIXLIGHT simulations on both scales are based on a list of individual tree characteristics, it allows for simple manipulation of stand structure to study the effects of silvicultural options on light availability. The two scales allow the input of various kinds of data, allowing predictions from data of different sources and completeness. A simple and rapid method of calibrating the foliage parameters for the species of interest is presented, using measurements of direct-beam light transmission measurements made in the shadows of newly isolated trees. In an independent validation, MIXLIGHT predicted light transmission at the stand level closely for 17 forest inventory plots with a wide range of density and species composition, during leaf-on and leaf-off seasons and under sunny and cloudy conditions. A sensitivity analysis indicated that the influence of the parameters in the model on stand level light transmission predictions was (highest to lowest): foliage area density, crown radius, crown length, and foliage inclination. Nonetheless, a test of the common assumption that the foliage is spherically inclined caused significant underestimation of light transmission. With this flexibility and demonstrated accuracy, we believe MIXLIGHT will provide an accessible and effective tool for forest stand management and regeneration modeling.

Influence of Understory Characteristics on Snowshoe Hare Habitat Use and Density

The influence of forest understory characteristics on snowshoe hare (Lepus americanus) habitat use and density was studied in eastern (Cherryfield) and western (Pierce Pond) Maine during 1981-83. Fecal pellet counts indicated that hares at Cherryfield preferred hardwood and avoided mixedwood and open understories during the leaf-off season (Oct-May) (P < 0.05). At Pierce Pond, hares used softwood more and hardwood and open understories less than expected during leaf off (P < 0.05). Hardwood understories provided the densest cover at Cherryfield, whereas at Pierce Pond softwoods were the densest cover. Hares in both areas used dense understories less during the leaf-on season (Jun-Sep). Spring population densities (0.1-1.7/ha) were correlated with understory density (r = 0.94, P < 0.001). Overwinter survival also was associated with understory density (r = 0.74, P < 0.04). Dense understories provided escape and thermal