Temporal changes in boreal forest tree canopy cover along a gradient of gamma radiation

1985 ◽  
Vol 63 (1) ◽  
pp. 15-20 ◽  
Author(s):  
B. D. Amiro ◽  
J. R. Dugle
Keyword(s):  
Gamma Radiation ◽  
Boreal Forest ◽  
Gamma Rays ◽  
Forest Canopy ◽  
Canopy Cover ◽  
Woody Species ◽  
Tree Canopy ◽  
Forest Site ◽  
Dose Rates ◽  
Tree Canopy Cover

A forest site in southeastern Manitoba has been irradiated by a point source of gamma rays continuously since 1973, and measurements have been made yearly to study the change in boreal forest canopy cover along the radiation gradient. After 10 years of chronic irradiation, a zone of total tree death has resulted from mean dose rates between 25 and 62 mGy h−1. Tree canopy cover was reduced at mean dose rates exceeding ~ 4.5 mGy h−1 and the largest reduction occurred in the first 2 years of irradiation. The temporal responses of seven woody species to gamma radiation are presented. Bebb's willow, trembling aspen, speckled alder, and paper birch were less sensitive to radiation than black spruce, balsam fir, and jack pine. The results confirm that gymnosperms are more sensitive to gamma rays than angiosperms.

scholarly journals Estimating Forest Canopy Cover by Multiscale Remote Sensing in Northeast Jiangxi, China

Land ◽  
2021 ◽  
Vol 10 (4) ◽  
pp. 433
Author(s):  
Xiaolan Huang ◽  
Weicheng Wu ◽  
Tingting Shen ◽  
Lifeng Xie ◽  
Yaozu Qin ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Large Scale ◽  
Forest Canopy ◽  
Canopy Cover ◽  
Google Earth ◽  
Tree Canopy ◽  
Landsat Data ◽  
High Resolution Data ◽  
Modis Ndvi ◽  
Tree Canopy Cover

This research was focused on estimation of tree canopy cover (CC) by multiscale remote sensing in south China. The key aim is to establish the relationship between CC and woody NDVI (NDVIW) or to build a CC-NDVIW model taking northeast Jiangxi as an example. Based on field CC measurements, this research used Google Earth as a complementary source to measure CC. In total, 63 sample plots of CC were created, among which 45 were applied for modeling and the remaining 18 were employed for verification. In order to ascertain the ratio R of NDVIW to the satellite observed NDVI, a 20-year time-series MODIS NDVI dataset was utilized for decomposition to obtain the NDVIW component, and then the ratio R was calculated with the equation R = (NDVIW/NDVI) *100%, respectively, for forest (CC >60%), medium woodland (CC = 25–60%) and sparse woodland (CC 1–25%). Landsat TM and OLI images that had been orthorectified by the provider USGS were atmospherically corrected using the COST model and used to derive NDVIL. R was multiplied for the NDVIL image to extract the woody NDVI (NDVIWL) from Landsat data for each of these plots. The 45 plots of CC data were linearly fitted to the NDVIWL, and a model with CC = 103.843 NDVIW + 6.157 (R2 = 0.881) was obtained. This equation was applied to predict CC at the 18 verification plots and a good agreement was found (R2 = 0.897). This validated CC-NDVIW model was further applied to the woody NDVI of forest, medium woodland and sparse woodland derived from Landsat data for regional CC estimation. An independent group of 24 measured plots was utilized for validation of the results, and an accuracy of 83.0% was obtained. Thence, the developed model has high predictivity and is suitable for large-scale estimation of CC using high-resolution data.

scholarly journals ASSESSING URBAN FOREST CANOPY COVER IN GREAT PLAIN CONSERVATION AREA (DÜZCE CITY, TURKEY) BETWEEN 1984 AND 2015

2021 ◽  
Vol XLVI-4/W5-2021 ◽  
pp. 539-544
Author(s):  
Z. Uçar ◽  
R. Eker ◽  
A. Aydin
Keyword(s):  
Ecosystem Services ◽  
Forest Canopy ◽  
Urban Forest ◽  
Canopy Cover ◽  
Tree Canopy ◽  
Urban Trees ◽  
Conservation Area ◽  
Urban Tree ◽  
Tree Canopy Cover ◽  
Urban Tree Canopy

Abstract. Urban trees and forests are essential components of the urban environment. They can provide numerous ecosystem services and goods, including but not limited to recreational opportunities and aesthetic values, removal of air pollutants, improving air and water quality, providing shade and cooling effect, reducing energy use, and storage of atmospheric CO2. However, urban trees and forests have been in danger of being lost by dense housing resulting from population growth in the cities since the 1950s, leading to increased local temperature, pollution level, and flooding risk. Thus, determining the status of urban trees and forests is necessary for comprehensive understanding and quantifying the ecosystem services and goods. Tree canopy cover is a relatively quick, easy to obtain, and cost-effective urban forestry metric broadly used to estimate ecosystem services and goods of the urban forest. This study aimed to determine urban forest canopy cover areas and monitor the changes between 1984–2015 for the Great Plain Conservation area (GPCA) that has been declared as a conservation Area (GPCA) in 2017, located on the border of Düzce City (Western Black Sea Region of Turkey). Although GPCA is a conservation area for agricultural purposes, it consists of the city center with 250,000 population and most settlement areas. A random point sampling approach, the most common sampling approach, was applied to estimate urban tree canopy cover and their changes over time from historical aerial imageries. Tree canopy cover ranged from 16.0% to 27.4% within the study period. The changes in urban canopy cover between 1984–1999 and 1999–2015 were statistically significant, while there was no statistical difference compared to the changes in tree canopy cover between 1984–2015. The result of the study suggested that an accurate estimate of urban tree canopy cover and monitoring long-term canopy cover changes are essential to determine the current situation and the trends for the future. It will help city planners and policymakers in decision-making processes for the future of urban areas.

Laboratory experiments to estimate interception of infrared radiation by tree canopies

2016 ◽  
Vol 25 (9) ◽  
pp. 1009 ◽  
Author(s):  
Bill J. Mathews ◽  
Eva K. Strand ◽  
Alistair M. S. Smith ◽  
Andrew T. Hudak ◽  
B. Dickinson ◽  
...  
Keyword(s):  
Laboratory Experiments ◽  
Forest Canopy ◽  
Detection Threshold ◽  
Canopy Cover ◽  
Tree Canopy ◽  
Radiative Energy ◽  
Prescribed Fires ◽  
Total Biomass ◽  
Tree Canopy Cover ◽  
Radiative Power

Estimates of biomass-burning in wildfires or prescribed fires are needed to account for the production of trace gases and aerosols that enter the atmosphere during combustion. Research has demonstrated that the biomass consumption rate is linearly related to fire radiative power (FRP), and that total biomass consumed is linearly related to fire radiative energy (FRE). Measurement of these is biased by certain characteristics of a forest canopy, such as foliar moisture content and tree canopy cover. Laboratory experiments were conducted to assess the influence of canopy cover on the FRP observed from an overhead sensor (e.g. an aircraft or satellite). A range of canopy cover from 0 to 90% and two classes of canopy (non-transpiring living and desiccated branches) were used in the experiments. Experiments suggest that in cases of complete or nearly complete canopy closure, fires obscured by the canopy may be below the detection threshold of above-canopy FRP sensors. Results from this research will reduce uncertainties in estimates of biomass consumption in surface fires burning under forest canopies.

scholarly journals Mapping Land Cover and Tree Canopy Cover in Zagros Forests of Iran: Application of Sentinel-2, Google Earth, and Field Data

2020 ◽  
Vol 12 (12) ◽  
pp. 1912 ◽  
Author(s):  
Saeedeh Eskandari ◽  
Mohammad Reza Jaafari ◽  
Patricia Oliva ◽  
Omid Ghorbanzadeh ◽  
Thomas Blaschke
Keyword(s):  
Land Cover ◽  
Forest Canopy ◽  
Pearson Correlation ◽  
Canopy Cover ◽  
Google Earth ◽  
Tree Canopy ◽  
Zagros Forests ◽  
Tree Canopy Cover ◽  
Field Plots ◽  
Sentinel 2

The Zagros forests in Western Iran are valuable ecosystems that have been seriously damaged by human interference (harvesting the wood and forest sub-products, converting the forests to the agricultural lands, and grazing) and natural events (drought events and fire). In this study, we generated accurate land cover (LC), and tree canopy cover percentage (TCC%) maps for the forests of Shirvan County, a part of Zagros forests in Western Iran using Sentinel-2, Google Earth, and field data for protective management. First, we assessed the accuracy of Google Earth data using 300 random field plots in 10 different land cover types. For land cover mapping, we evaluated the performance of four supervised classification algorithms (minimum distance (MD), Mahalanobis distance (MaD), neural network (NN), and support vector machine (SVM)). The accuracy of the land cover maps was assessed using a set of 150 stratified random plots in Google Earth. We mapped the forest canopy cover by using the normalized difference vegetation index (NDVI) map, and field plots. We calculated the Pearson correlation between the NDVI values and the TCC% (obtained from field plots). The linear regression between the NDVI values and the TCC% was used to obtain the predictive model of TCC% based on the NDVI. The results showed that Google Earth data yielded an overall accuracy of 94.4%. The SVM algorithm had the highest accuracy for the classification of Sentinel-2 data with an overall accuracy of 81.33% and a kappa index of 0.76. The results of the forest canopy cover analysis showed a Pearson correlation coefficient of 0.93 between the NDVI and TCC%, which is highly significant. The results also showed that the linear regression model is a good predictive model for TCC% estimation based on the NDVI (r2 = 0.864). The results can be used as a baseline for decision-makers to monitor land cover change in the region, whether produced by human activities or natural events and to establish measures for protective management of forests.

Zoning, land use, and urban tree canopy cover: The importance of scale

2013 ◽  
Vol 12 (2) ◽  
pp. 191-199 ◽  
Author(s):  
Sarah K. Mincey ◽  
Mikaela Schmitt-Harsh ◽  
Richard Thurau
Keyword(s):  
Land Use ◽  
Canopy Cover ◽  
Tree Canopy ◽  
Urban Tree ◽  
Tree Canopy Cover ◽  
Urban Tree Canopy

scholarly journals Diversity of Medicinal Plants among Different Tree Canopies

2021 ◽  
Vol 13 (5) ◽  
pp. 2640
Author(s):  
Muhammad Zubair ◽  
Akash Jamil ◽  
Syed Bilal Hussain ◽  
Ahsan Ul Haq ◽  
Ahmad Hussain ◽  
...  
Keyword(s):  
Medicinal Plants ◽  
Coniferous Forest ◽  
Canopy Cover ◽  
Local Communities ◽  
Tree Canopy ◽  
Tree Cover ◽  
Open Spaces ◽  
Floral Diversity ◽  
Tree Canopy Cover ◽  
Closed Canopy

The moist temperate forests in Northern Pakistan are home to a variety of flora and fauna that are pivotal in sustaining the livelihoods of the local communities. In these forests, distribution and richness of vegetation, especially that of medicinal plants, is rarely reported. In this study, we carried out a vegetation survey in District Balakot, located in Northeastern Pakistan, to characterize the diversity of medicinal plants under different canopies of coniferous forest. The experimental site was divided into three major categories (viz., closed canopy, open spaces, and partial tree cover). A sampling plot of 100 m2 was established on each site to measure species diversity, dominance, and evenness. To observe richness and abundance, the rarefaction and rank abundance curves were plotted. Results revealed that a total of 45 species representing 34 families were available in the study site. Medicinal plants were the most abundant (45%) followed by edible plants (26%). Tree canopy cover affected the overall growth of medicinal plants on the basis of abundance and richness. The site with partial canopy exhibited the highest diversity, dominance, and abundance compared to open spaces and closed canopy. These findings are instrumental in identifying the wealth of the medicinal floral diversity in the northeastern temperate forest of Balakot and the opportunity to sustain the livelihoods of local communities with the help of public/private partnership.

scholarly journals Natural Regeneration of the Tree Stand in the Bilberry Spruce Forest—Clear-Cutting Ecotone Complex in the First Post-Logging Decade

Forests ◽  
2021 ◽  
Vol 12 (11) ◽  
pp. 1542
Author(s):  
Nadezhda V. Genikova ◽  
Viktor N. Mamontov ◽  
Alexander M. Kryshen ◽  
Vladimir A. Kharitonov ◽  
Sergey A. Moshnikov ◽  
...  
Keyword(s):  
Natural Regeneration ◽  
Forest Canopy ◽  
Forest Cover ◽  
Forest Type ◽  
Ground Cover ◽  
Woody Species ◽  
Forest Edge ◽  
Tree Canopy ◽  
Clear Cut ◽  
Clear Cutting

Bilberry spruce forests are the most widespread forest type in the European boreal zone. Limiting the clear-cuttings size leads to fragmentation of forest cover and the appearance of large areas of ecotone complexes, composed of forest (F), a transition from forest to the cut-over site under tree canopy (FE), a transition from forest to the cut-over site beyond tree canopy (CE), and the actual clear-cut site (C). Natural regeneration of woody species (spruce, birch, rowan) in the bilberry spruce stand—clear-cut ecotone complex was studied during the first decade after logging. The effects produced by the time since cutting, forest edge aspect, and the ground cover on the emergence and growth of trees and shrubs under forest canopy and openly in the clear-cut were investigated. Estimating the amount and size of different species in the regeneration showed FE and CE width to be 8 m—roughly half the height of first-story trees. Typical forest conditions (F) feature a relatively small amount of regenerating spruce and birch. The most favorable conditions for natural regeneration of spruce in the clear-cut—mature bilberry spruce stand ecotone are at the forest edge in areas of transition both towards the forest and towards the clear-cut (FE and CE). Clear-cut areas farther from the forest edge (C) offer an advantage to regenerating birch, which grows densely and actively in this area.

scholarly journals Environmental Factors Associated With Loa loa Microfilaria Prevalence and Intensity in Diverse Bioecological Zones of Cameroon

2021 ◽  
Vol 2 ◽  
Author(s):  
Xavier Badia-Rius ◽  
Hannah Betts ◽  
Samuel Wanji ◽  
David Molyneux ◽  
Mark J. Taylor ◽  
...  
Keyword(s):  
Environmental Factors ◽  
Regression Models ◽  
Polynomial Regression ◽  
Canopy Cover ◽  
Nonparametric Tests ◽  
Tree Canopy ◽  
Mean Annual Temperature ◽  
Loa Loa ◽  
Factors Associated ◽  
Tree Canopy Cover

Loiasis (African Eye Worm) is a filarial infection caused by Loa loa and transmitted by Chrysops vectors, which are confined to the tropical rainforests of Central and West Africa. Loiasis is a major impediment to control and elimination programmes that use the drug ivermectin due to the risk of serious adverse events. There is an urgent need to better refine and map high-risk communities. This study aimed to quantify and predict environmental factors associated with loiasis across five bioecological zones in Cameroon. The L. loa microfilaria (mf) prevalence (%) and intensity (mf number/ml) data from 42 villages within an Equatorial Rainforest and Savannah region were examined in relation to climate, topographic and forest-related data derived from satellite remote sensing sources. Differences between zones and regions were examined using nonparametric tests, and the relationship between L. loa mf prevalence, mf intensity, and the environmental factors using polynomial regression models. Overall, the L. loa mf prevalence was 11.6%, L. loa intensity 927.4 mf/ml, mean annual temperature 23.7°C, annual precipitation 2143.2 mm, elevation 790 m, tree canopy cover 46.7%, and canopy height 19.3m. Significant differences between the Equatorial Rainforest and Savannah region were found. Within the Equatorial Rainforest region, no significant differences were found. However, within the Savannah region, significant differences between the three bioecological zones were found, and the regression models indicated that tree canopy cover and elevation were significant predictors, explaining 85.1% of the L. loa mf prevalence (adjusted R2 = 0.851; p<0.001) and tree cover alone was significant, explaining 58.1% of the mf intensity (adjusted R2 = 0.581; p<0.001). The study highlights that environmental analysis can help delineate risk at different geographical scales, which may be practical for developing larger scale operational plans for mapping and implementing safe effective interventions.

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