scholarly journals REMOTE SENSING FOR URBAN TREE CANOPY CHANGE DETECTION WITH LANDSAT SATELLITE DATA IN NNAMDI AZIKIWE UNIVERSITY AWKA – NIGERIA

2020 ◽  
Vol 7 (2) ◽  
pp. 99-112
Author(s):  
John Agbo Ogbodo ◽  
Loretta M. Obimdike ◽  
Yason Benison
Keyword(s):  
Confusion Matrix ◽  
Tree Canopy ◽  
Tree Cover ◽  
Land Area ◽  
Change Analysis ◽  
University Campuses ◽  
Urban Tree ◽  
Infrastructural Development ◽  
Urban Tree Canopy ◽  
Landsat Satellite

Urban tree canopy within a university boundary is a measure of the university's tree cover as a percentage of its total land area. The overall objective of the present study is to conduct a sSpatio-temporal change analysis of urban tree canopy in Nnamdi Azikiwe University Awka-Nigeria. Landsat data of years 1991, 2001, 2011 and 2019 were analysed using Maximum Likelihood Classifier and Confusion Matrix Spatial Analyst in ArcGIS 10.7.1 software. In terms of tree cover loss, there is a steady rate of decrease rate from -31.59 Hectares (ha) between 1991 and 2001; -82.32 ha (2001/2011) and -64.53 ha (2011/2019). Whereas, at an initial land area of 9.40 ha in 1991, physical infrastructural development is progressively increased with 16.92 ha between 1991 and 2001; 43.79 ha 2001/2011 and 12.37 ha between 2011 and 2019. The dominant drivers of tree cover change in the study area related to the expansion of physical infrastructures and sprawling agriculture as a result of encroachers into the study area. In conclusion, tropical forests within university campuses face many threats, such as those posed by unregulated physical infrastructural development and a lack of investment and management of forest relics. As a recommendation, Nigerian universities should invest and conserve their existing forested landscapes towards promoting land resources in line with Sustainable Development Goals number 15 (SDG-15) strategies.

scholarly journals The Legacy of Hurricanes, Historic Land Cover, and Municipal Ordinances on Urban Tree Canopy in Florida (United States)

2021 ◽  
Author(s):  
Andrew Koeser
Keyword(s):  
Urban Forest ◽  
Rapid Development ◽  
Tree Canopy ◽  
Tree Cover ◽  
P Value ◽  
Lower Intensity ◽  
Urban Tree ◽  
Canopy Coverage ◽  
Intensity Category ◽  
Urban Tree Canopy

Urban Tree Canopy (UTC) greatly enhances the livability of cities by reducing urban heat buildup, mitigating stormwater runoff, and filtering airborne particulates, among other ecological services. These benefits, combined with the relative ease of measuring tree cover from aerial imagery, have led many cities to adopt management strategies based on UTC goals. In this study, we conducted canopy analyses for the 300 largest cities in Florida to assess the impacts of development practices, urban forest ordinances, and hurricanes on tree cover. Within the cities sampled, UTC canopy ranged from 5.9% to 68.7% with a median canopy coverage of 32.3% Our results indicate that the peak gust speeds recorded during past hurricanes events were a significant predictor of canopy coverage (P-value = <0.001) across the sampled cities. As peak gust speeds increased from 152 km/h (i.e., a lower-intensity Category 1 storm) to 225 km/h (lower-intensity Category 4 and the maximum gusts captured in our data), predicted canopy in developed urban areas decreased by 7.7%. Beyond the impacts of hurricanes and tropical storms, we found that historic landcover and two out of eight urban forest ordinances were significant predictors of existing canopy coverage (P-landcover <0.001; P-tree preservation ordinance = 0.02, P-heritage tree ordinance = 0.03). Results indicate that local policies and tree protections can protect or enhance urban tree canopy, even in the face of rapid development and periodic natural disturbances.

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 Linking Urban Tree Cover Change and Local History in a Post-Industrial City

Land ◽  
2021 ◽  
Vol 10 (4) ◽  
pp. 403
Author(s):  
Lara A. Roman ◽  
Indigo J. Catton ◽  
Eric J. Greenfield ◽  
Hamil Pearsall ◽  
Theodore S. Eisenman ◽  
...  
Keyword(s):  
Land Cover ◽  
Low Income ◽  
Historical Context ◽  
Local History ◽  
Tree Canopy ◽  
Tree Cover ◽  
Open Spaces ◽  
Urban Tree ◽  
Suburban Areas ◽  
Post Industrial

Municipal leaders are pursuing ambitious goals to increase urban tree canopy (UTC), but there is little understanding of the pace and socioecological drivers of UTC change. We analyzed land cover change in Philadelphia, Pennsylvania (United States) from 1970–2010 to examine the impacts of post-industrial processes on UTC. We interpreted land cover classes using aerial imagery and assessed historical context using archival newspapers, agency reports, and local historical scholarship. There was a citywide UTC increase of +4.3 percentage points. Substantial UTC gains occurred in protected open spaces related to both purposeful planting and unintentional forest emergence due to lack of maintenance, with the latter phenomenon well-documented in other cities located in forested biomes. Compared to developed lands, UTC was more persistent in protected open spaces. Some neighborhoods experienced substantial UTC gains, including quasi-suburban areas and depopulated low-income communities; the latter also experienced decreasing building cover. We identified key processes that drove UTC increases, and which imposed legacies on current UTC patterns: urban renewal, urban greening initiatives, quasi-suburban developments, and (dis)investments in parks. Our study demonstrates the socioecological dynamism of intra-city land cover changes at multi-decadal time scales and the crucial role of local historical context in the interpretation of UTC change.

Cholera in London and Urban Tree Canopy in Baltimore

2015 ◽  
pp. 144-171
Author(s):  
J. Morgan Grove ◽  
Mary L. Cadenasso ◽  
Steward T. A. Pickett ◽  
Gary E. Machlis ◽  
William R. Burch
Keyword(s):  
Tree Canopy ◽  
Urban Tree ◽  
Urban Tree Canopy

scholarly journals Miami-Dade County Urban Tree Canopy Analysis

2021 ◽  
Author(s):  
Hartwig Hochmair ◽  
◽  
Adam Benjamin ◽  
Daniel Gann ◽  
Levente Juhasz ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Urban Development ◽  
Tree Canopy ◽  
Dade County ◽  
Impervious Surfaces ◽  
Vector Data ◽  
Bare Ground ◽  
Urban Tree ◽  
Wetland Water ◽  
Urban Tree Canopy

This assessment focuses on describing urban tree canopy (UTC) within the Urban Development Boundary of Miami-Dade County, as defined by the Miami-Dade County Transportation Planning Organization (Figure 1). The area (intracoastal water areas excluded) encompasses approximately 1147 km2 (443 mi2). A combination of remote sensing and publicly available vector data was used to classify the following land cover classes: tree canopy/shrubs, grass, bare ground, wetland, water, building, street/railroad, other impervious surfaces, and cropland.

scholarly journals Environmental Equity and Spatiotemporal Patterns of Urban Tree Canopy in Atlanta

2019 ◽  
pp. 0739456X1986414 ◽  
Author(s):  
Bon Woo Koo ◽  
Nico Boyd ◽  
Nisha Botchwey ◽  
Subhrajit Guhathakurta
Keyword(s):  
African Americans ◽  
Careful Analysis ◽  
Tree Canopy ◽  
Spatiotemporal Patterns ◽  
Environmental Equity ◽  
Positive Relationships ◽  
Urban Tree ◽  
Urban Tree Canopy ◽  
Demographic Attributes ◽  
The Relationship

While previous studies in environmental equity found positive relationships between tree canopy and socioeconomic/demographic status of neighborhoods, few examined how changes in tree canopy are associated with changes in socioeconomic/demographic status. This study confirms that the relationship between them in Atlanta is changing and the hypothesis of inequitable distribution of tree canopy concerning demographic attributes cannot be fully supported beyond 2000. In addition, the proportion of African Americans can have different effects on the estimated tree canopy as poverty rates vary. Planning to mitigate environmental inequities through tree plantings requires more careful analysis that goes beyond the socioeconomic/demographic attributes of the population.

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