scholarly journals Forest Cover Change within the Russian European North after the Breakdown of Soviet Union (1990–2005)

2012 ◽  
Vol 2012 ◽  
pp. 1-11 ◽  
Author(s):  
Peter Potapov ◽  
Svetlana Turubanova ◽  
Ilona Zhuravleva ◽  
Matthew Hansen ◽  
Alexey Yaroshenko ◽  
...  
Keyword(s):  
Soviet Union ◽  
Forest Cover ◽  
Spatial Information ◽  
Regional Scale ◽  
Canopy Cover ◽  
Tree Canopy ◽  
Forest Cover Change ◽  
European North ◽  
Tree Canopy Cover ◽  
Forest Cover Loss

Forest cover dynamics (defined as tree canopy cover change without regard to forest land use) within the Russian European North have been analyzed from 1990 to 2005 using a combination of results from two Landsat-based forest cover monitoring projects: 1990–2000 and 2000–2005. Results of the forest cover dynamics analysis highlighted several trends in forest cover change since the breakdown of the Soviet planned economy. While total logging area decreased from the 1990–2000 to the 2000–2005 interval, logging and other forms of anthropogenically-induced clearing increased within the Central and Western parts of the region. The most populated regions of European Russia featured the highest rates of net forest cover loss. Our results also revealed intensive gross forest cover loss due to forest felling close to the Russian-Finland border. The annual burned forest area almost doubled between the two time intervals. The 2000–2005 gross forest cover gain results suggest that tree encroachment on abandoned agriculture land is a wide-spread process over the region. The analysis demonstrates the value of regional-scale Landsat-based forest cover and change quantification. Our results supplemented official data by providing independently derived spatial information that could be used for assessing on-going trends and serve as a baseline for future forest cover monitoring.

scholarly journals Historic HOLC Redlining in Indianapolis and the Legacy of Environmental Impacts

2020 ◽  
Vol 1 (1) ◽  
Author(s):  
Donovan Moxley ◽  
Burnell Fischer
Keyword(s):  
Financial Risk ◽  
Forest Cover ◽  
Canopy Cover ◽  
The United States ◽  
Tree Canopy ◽  
Superfund Sites ◽  
Tree Canopy Cover ◽  
Method Evidence ◽  
Ecological Legacies ◽  
Loan Corporation

Redline mapping was adopted by the Home Owner’s Loan Corporation (HOLC) in the 1930s to help assess its lending risk based on observable characteristics in urban neighborhoods across the United States, but the practice has been criticized for evident racial discrimination in addition to financial risk assessment. Researchers have demonstrated that modern urban tree canopy cover is lower in the historically redlined zones of four US cities. This article focuses on Indianapolis, Indiana, where a HOLC map was developed in 1937. Analysis using a geographic information system (GIS) was conducted in order to detect evidence of ecological legacies of redlining. Using this method, evidence of relatively high-intensity development, low greenspace and forest cover, and disproportionately high incidences of brownfield sites, Superfund sites, industrial waste sites, and Interstate highways were detected in historically redlined zones in Indianapolis. While opportunities for further and more detailed research are considered, the method employed here should be developed such that it is replicable for other cities with redlining histories in Indiana and other surrounding states with comparable spatial datasets. This example protocol can be adopted and refined by various stakeholders to establish where the need may exist for programmatic solutions and to better inform policy recommendations.

scholarly journals Determining a Threshold to Delimit the Amazonian Forests from the Tree Canopy Cover 2000 GFC Data

Sensors ◽  
2019 ◽  
Vol 19 (22) ◽  
pp. 5020 ◽  
Author(s):  
Kaio Allan Cruz Gasparini ◽  
Celso Henrique Leite Silva Junior ◽  
Yosio Edemir Shimabukuro ◽  
Egidio Arai ◽  
Luiz Eduardo Oliveira Cruz e Aragão ◽  
...  
Keyword(s):  
Amazon Basin ◽  
Forest Cover ◽  
Accuracy Assessment ◽  
Canopy Cover ◽  
Brazilian Amazon ◽  
Forest Degradation ◽  
Tree Canopy ◽  
Tree Canopy Cover ◽  
Amazonian Forests ◽  
Year 2000

Open global forest cover data can be a critical component for Reducing Emissions from Deforestation and Forest Degradation (REDD+) policies. In this work, we determine the best threshold, compatible with the official Brazilian dataset, for establishing a forest mask cover within the Amazon basin for the year 2000 using the Tree Canopy Cover 2000 GFC product. We compared forest cover maps produced using several thresholds (10%, 30%, 50%, 80%, 85%, 90%, and 95%) with a forest cover map for the same year from the Brazilian Amazon Deforestation Monitoring Project (PRODES) data, produced by the National Institute for Space Research (INPE). We also compared the forest cover classifications indicated by each of these maps to 2550 independently assessed Landsat pixels for the year 2000, providing an accuracy assessment for each of these map products. We found that thresholds of 80% and 85% best matched with the PRODES data. Consequently, we recommend using an 80% threshold for the Tree Canopy Cover 2000 data for assessing forest cover in the Amazon basin.

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 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 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.

scholarly journals Do Trees in Halifax Grow on Money?: A Comparison of Urban Tree Canopy Cover and Median Household Income in North End and South End Halifax

2018 ◽  
Vol 14 ◽  
Author(s):  
Kendra Marshman
Keyword(s):  
Population Density ◽  
Household Income ◽  
Urban Forest ◽  
Canopy Cover ◽  
Tree Canopy ◽  
Median Household Income ◽  
Tree Canopy Cover ◽  
Urban Tree Canopy ◽  
Statistics Canada ◽  
North End

Trees in the city provide numerous ecological, health, and social benefits to urban residents. Studies from large North American cities have confirmed a spatial pattern that higher urban forest tree canopy positively correlates with higher levels of affluence. The just distribution of trees will become increasingly important for urban planners and foresters as there is a national trend towards living in cities. This research report investigates the equity of distribution of urban tree canopy cover in two neighbourhoods on the peninsula of Halifax, Nova Scotia. High spatial resolution land cover data from 2007 and 2006 Statistics Canada census data was used to create maps and tables to answer the research question. The socio-economic indicators of median household income and population density are represented based on census tract dissemination areas from the 2006 Statistics Canada long survey. Preliminary results indicate lower median household income and higher population density in the chosen study area of North End Halifax compared to higher median household income and lower population density in the chosen study area of South End Halifax. Tree canopy cover density is slightly lower in North End Halifax (5.3%) than in South End Halifax (7.6%). These preliminary results coincide with findings of other researchers that higher household income and lower population density at the neighbourhood level may result in increased urban forest canopy. However, further research and more reliant tree canopy cover data is needed to determine the accuracy of these findings. 

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