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.

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 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 Application and Evaluation of a Deep Learning Architecture to Urban Tree Canopy Mapping

2021 ◽  
Vol 13 (9) ◽  
pp. 1749
Author(s):  
Zhe Wang ◽  
Chao Fan ◽  
Min Xian
Keyword(s):  
Deep Learning ◽  
High Resolution ◽  
Land Cover ◽  
Urban Forest ◽  
Spatial Scales ◽  
Tree Canopy ◽  
Urban Tree ◽  
Wide Range ◽  
Urban Tree Canopy ◽  
Overall Performance

Urban forest is a dynamic urban ecosystem that provides critical benefits to urban residents and the environment. Accurate mapping of urban forest plays an important role in greenspace management. In this study, we apply a deep learning model, the U-net, to urban tree canopy mapping using high-resolution aerial photographs. We evaluate the feasibility and effectiveness of the U-net in tree canopy mapping through experiments at four spatial scales—16 cm, 32 cm, 50 cm, and 100 cm. The overall performance of all approaches is validated on the ISPRS Vaihingen 2D Semantic Labeling dataset using four quantitative metrics, Dice, Intersection over Union, Overall Accuracy, and Kappa Coefficient. Two evaluations are performed to assess the model performance. Experimental results show that the U-net with the 32-cm input images perform the best with an overall accuracy of 0.9914 and an Intersection over Union of 0.9638. The U-net achieves the state-of-the-art overall performance in comparison with object-based image analysis approach and other deep learning frameworks. The outstanding performance of the U-net indicates a possibility of applying it to urban tree segmentation at a wide range of spatial scales. The U-net accurately recognizes and delineates tree canopy for different land cover features and has great potential to be adopted as an effective tool for high-resolution land cover mapping.

Recent Distribution of Coyotes Across an Urban Landscape in Southeastern Michigan

2013 ◽  
Vol 4 (2) ◽  
pp. 377-385 ◽  
Author(s):  
William B. Dodge ◽  
Daniel M. Kashian
Keyword(s):  
Land Cover ◽  
Urban Areas ◽  
Open Space ◽  
Urban Landscape ◽  
Canis Latrans ◽  
Wildlife Habitat ◽  
Economic Conditions ◽  
Tree Cover ◽  
Suburban Areas ◽  
Mobile Species

Abstract Human–wildlife interactions in urban areas are widely reported by ecologists to be the result of human encroachment on wildlife habitat. Highly mobile species, however, have been documented by both wildlife biologists and casual observers to occupy areas heavily populated by humans. Range expansion and population growth of coyotes (Canis latrans) has led to their increased presence in metropolitan Detroit, Michigan, where poor economic conditions over the last several decades have resulted in the reversion of numerous recreational areas and abandoned parcels to more wooded or vegetated conditions that have provided potential wildlife habitat. We performed an extensive survey for coyote evidence (i.e., carcasses, den sites, scats, sightings, or tracks) across metropolitan Detroit to examine distribution across both the general region and specific land cover types. We found 58% of all coyote evidence on unpaved trails, paths, and unimproved roads within edge habitats (e.g., grassland adjacent to urban non-vegetative land cover), with den sites and tracks the only types of evidence found strictly in interior habitats. Land cover around evidence points included more wooded land cover than expected in suburban areas, suggesting the importance of tree cover for coyote occupancy, and more open space and wooded land cover than expected in urban areas, highlighting the coyotes' avoidance of heavily populated areas. We speculate that habitat characterized by tree cover has likely never been limiting within metropolitan Detroit, and that reoccupation of southeastern Michigan by coyotes is more likely a consequence of expanding coyote populations outside of suburban and urban areas rather than newly available habitat resulting from land cover change.

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.

scholarly journals Contrasting tree-cover loss and subsequent land cover in two neotropical forest regions: sample-based assessment of the Mexican Yucatán and Argentine Chaco

2018 ◽  
Vol 13 (6) ◽  
pp. 549-564 ◽  
Author(s):  
Alexander Krylov ◽  
Marc K. Steininger ◽  
Matthew C. Hansen ◽  
Peter V. Potapov ◽  
Stephen V. Stehman ◽  
...  
Keyword(s):  
Land Cover ◽  
Tree Cover ◽  
Neotropical Forest ◽  
Forest Regions

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 Quantifying Tree Cover Loss in Urban Forests within Nairobi City Metropolitan Area from Earth Observation Data

2020 ◽  
Vol 3 (1) ◽  
pp. 78
Author(s):  
Francis Oloo ◽  
Godwin Murithi ◽  
Charlynne Jepkosgei
Keyword(s):  
Land Cover ◽  
Metropolitan Area ◽  
Land Surface ◽  
Urban Forest ◽  
Urban Forests ◽  
Earth Observation ◽  
Tree Cover ◽  
Observation Data ◽  
Vegetation Health ◽  
Earth Observation Data

Urban forests contribute significantly to the ecological integrity of urban areas and the quality of life of urban dwellers through air quality control, energy conservation, improving urban hydrology, and regulation of land surface temperatures (LST). However, urban forests are under threat due to human activities, natural calamities, and bioinvasion continually decimating forest cover. Few studies have used fine-scaled Earth observation data to understand the dynamics of tree cover loss in urban forests and the sustainability of such forests in the face of increasing urban population. The aim of this work was to quantify the spatial and temporal changes in urban forest characteristics and to assess the potential drivers of such changes. We used data on tree cover, normalized difference vegetation index (NDVI), and land cover change to quantify tree cover loss and changes in vegetation health in urban forests within the Nairobi metropolitan area in Kenya. We also used land cover data to visualize the potential link between tree cover loss and changes in land use characteristics. From approximately 6600 hectares (ha) of forest land, 720 ha have been lost between 2000 and 2019, representing about 11% loss in 20 years. In six of the urban forests, the trend of loss was positive, indicating a continuing disturbance of urban forests around Nairobi. Conversely, there was a negative trend in the annual mean NDVI values for each of the forests, indicating a potential deterioration of the vegetation health in the forests. A preliminary, visual inspection of high-resolution imagery in sample areas of tree cover loss showed that the main drivers of loss are the conversion of forest lands to residential areas and farmlands, implementation of big infrastructure projects that pass through the forests, and extraction of timber and other resources to support urban developments. The outcome of this study reveals the value of Earth observation data in monitoring urban forest resources.

scholarly journals Integrating structure and function: mapping the hierarchical spatial heterogeneity of urban landscapes

2020 ◽  
Vol 9 (1) ◽  
Author(s):  
Yuguo Qian ◽  
Weiqi Zhou ◽  
Steward T. A. Pickett ◽  
Wenjuan Yu ◽  
Dingpeng Xiong ◽  
...  
Keyword(s):  
Land Cover ◽  
Spatial Heterogeneity ◽  
Urban Ecosystem ◽  
Tree Canopy ◽  
Urban Landscapes ◽  
Shenzhen City ◽  
Object Based ◽  
Level 3 ◽  
Industrial Zones ◽  
Level 2

Abstract Background Cities are social-ecological systems characterized by remarkably high spatial and temporal heterogeneity, which are closely related to myriad urban problems. However, the tools to map and quantify this heterogeneity are lacking. We here developed a new three-level classification scheme, by considering ecosystem types (level 1), urban function zones (level 2), and land cover elements (level 3), to map and quantify the hierarchical spatial heterogeneity of urban landscapes. Methods We applied the scheme using an object-based approach for classification using very high spatial resolution imagery and a vector layer of building location and characteristics. We used a top-down classification procedure by conducting the classification in the order of ecosystem types, function zones, and land cover elements. The classification of the lower level was based on the results of the higher level. We used an object-based methodology to carry out the three-level classification. Results We found that the urban ecosystem type accounted for 45.3% of the land within the Shenzhen city administrative boundary. Within the urban ecosystem type, residential and industrial zones were the main zones, accounting for 38.4% and 33.8%, respectively. Tree canopy was the dominant element in Shenzhen city, accounting for 55.6% over all ecosystem types, which includes agricultural and forest. However, in the urban ecosystem type, the proportion of tree canopy was only 22.6% because most trees were distributed in the forest ecosystem type. The proportion of trees was 23.2% in industrial zones, 2.2% higher than that in residential zones. That information “hidden” in the usual statistical summaries scaled to the entire administrative unit of Shenzhen has great potential for improving urban management. Conclusions This paper has taken the theoretical understanding of urban spatial heterogeneity and used it to generate a classification scheme that exploits remotely sensed imagery, infrastructural data available at a municipal level, and object-based spatial analysis. For effective planning and management, the hierarchical levels of landscape classification (level 1), the analysis of use and cover by urban zones (level 2), and the fundamental elements of land cover (level 3), each exposes different respects relevant to city plans and management.

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