Creating a quantitative, ecosystem-service-based index of nature in the highly urbanized and arid Los Angeles Country

2021 ◽  
pp. 239980832110038
Author(s):  
Amy Freitag ◽  
Heidi Burkart ◽  
Chloe S Fleming ◽  
Seann D Regan
Keyword(s):  
Los Angeles ◽  
Natural Resources ◽  
Spatial Data ◽  
Natural Hazard ◽  
Risk Mitigation ◽  
Canopy Cover ◽  
Tree Canopy ◽  
Mitigation And Adaptation ◽  
Tree Canopy Cover ◽  
Local Partnerships

Before evaluating the abundance and quality of nature in a city, one must define the concept of nature according to resident experience and climatological conditions. For Los Angeles (L.A.) County, home to a sociologically diverse and highly developed city in a Mediterranean climate that experienced drought conditions for the last decade, this represents a formidable theoretical and empirical challenge. In support of an Integrated Vulnerability Assessment, we developed an index of natural resources with the aid of local partnerships. This effort required local expert participation and resulted in the creation of a large database of available regional data. This index was created to investigate the spatial footprint of natural resources in relation to predicted high risk natural hazard areas. This paper demonstrates analytical applications of this index, which consists of six component indicators: greenness, biodiversity, habitat fragmentation, significant ecological areas, tree canopy cover, and wetland cover. Data for each component were compiled into a geodatabase, scaled, aggregated to Census block group areas, and combined to create the natural resources index (the Index). The Index can then be compared with natural hazard spatial data to determine relative vulnerability to these hazards, interactions with other types of vulnerabilities, and where adaptive capacity may be lacking. Results highlight areas of opportunity for multifaceted risk mitigation and adaptation efforts.

Los Angeles 1-Million tree canopy cover assessment

2008 ◽  
Author(s):  
Gregory E. McPherson ◽  
James R. Simpson ◽  
Qingfu Xiao ◽  
Wu Chunxia
Keyword(s):  
Los Angeles ◽  
Canopy Cover ◽  
Tree Canopy ◽  
Tree Canopy Cover

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. 

scholarly journals Making Way for Trees? Changes in Land-Use, Habitats and Protected Areas in Great Britain under “Global Tree Restoration Potential”

2020 ◽  
Vol 12 (14) ◽  
pp. 5845
Author(s):  
Martin A. Wilkes ◽  
James Bennett ◽  
Sara Burbi ◽  
Sue Charlesworth ◽  
Katharina Dehnen-Schmutz ◽  
...  
Keyword(s):  
Great Britain ◽  
Protected Areas ◽  
Urban Areas ◽  
Canopy Cover ◽  
Tree Canopy ◽  
Tree Planting ◽  
Substantial Contribution ◽  
Trade Offs ◽  
Tree Canopy Cover ◽  
Restoration Potential

Numerous tree planting initiatives have been launched worldwide, based on the idea that carbon capture by trees can help to limit global warming. A recent study estimated the additional tree canopy cover that could be established given the growing conditions in every square kilometre of land on earth that is not already forested, urbanised, or used for crop production. It reported a total “tree restoration potential” of >900 million ha worldwide and identified hotspots where opportunities for tree planting initiatives may be the greatest. With the potential for an estimated 4.2 million ha of additional canopy cover, one such hotspot is Great Britain. We quantify the extent of habitats, land uses, and protected areas that would be impacted by tree planting on this scale in Great Britain and discuss the potential social–ecological trade-offs involved. Our findings show that realising the “tree restoration potential” would mean a considerable upheaval for the British landscape with 30–50% of ecologically valuable habitats lost and a reduction of 44% in the area of improved grassland. Up to 21% of land protected by law for its ecological, scientific, scenic, or cultural value would be impacted. Importantly, we demonstrate that an alternative approach based on increasing tree canopy cover by up to 20% in urban areas and on cropland could make a substantial contribution to tree planting targets, potentially offsetting losses elsewhere. Such shifts in the structure and function of the British landscape will depend on deep changes in the food system, evidence-based decisions about which existing habitats to protect, and a long-term commitment to tree planting and maintenance.

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