Tag Archives: urban forestry

3-30-300

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The idea is you can see 3 trees from your window, your neighborhood has 30% tree canopy cover, and you are within 300 m of a half-hectare park.

Parks Please! Implementing the 3–30-300 green space rule in developing countries − The case of Surakarta, Indonesia

Interest in the 3–30–300 green space rule has recently emerged in urban forest scholarship, but its applicability in developing country contexts, especially in intermediate cities, remains largely unexplored. This study assesses the feasibility of the rule’s three components—visibility of three trees from every building, achieving 30 % neighborhood canopy cover, and ensuring 300-meter walking access to 0.5-hectare parks—using geospatial analysis. We employ a combination of remote sensing data, local administrative records, and open-source global datasets to evaluate tree canopy cover, greenspace distribution, and accessibility under different scenarios. Our case study focuses on Surakarta, an intermediate city recognized as Indonesia’s most livable city. Results show that only 29 % of buildings meet the visibility requirement, 2 % are in neighborhoods with 30 % canopy cover, and 25 % are within 300 m of a greenspace. However, accessibility could increase to 79 % if all greenspaces were fenceless and high quality. Our findings highlight disparities in urban greening, as smaller residential buildings tend to have lower scores than larger office buildings. These results underscore the role of park governance in shaping access to green spaces and the persistent challenges of achieving the 3–30–300 targets. We propose place-based recommendations tailored for each urban commune and advocate for the adoption of the 3–30–300 rule as a target for national and local development planning to enhance urban green space accessibility and equity. This framework has the potential to be used in participatory planning processes for consensus-based siting of green infrastructure and nature-based solutions in cities in developing countries.

My city (Philadelphia, USA) has set the 30% canopy goal in the past and failed to implement it. Not only failed, but failed to maintain the inadequate tree canopy we already have. Part of the reason is dysfunctional and uncoordinated government agencies, and part of the problem is the “sidewalks are private property” farce.

beech leaf disease

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A new disease is threatening beech trees (Philadelphia Inquirer, paywalled) in the U.S. We don’t want to lose our beeches like we did our chestnuts. Beeches have some similar features in that they make up a significant amount of our eastern forest canopy (like chestnuts used to), produce fatty nuts that feed birds and other species, and their leaves serve as host plants for insects that feed birds and other species. It is not clear yet what is causing this disease, but hopefully we can learn from the cautionary tale of the chestnut and try to get out in front of it.

urban (redevelopment) and trees

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Redevelopment of private property in urban areas is generally a good thing for the regional economy, as is renewal of public infrastructure. It can be good for people and the environment too, if there are well-thought-out and well-implemented policies in place to make sure that is the case. But when those policies are not in place, or when enlightened and well-intentioned policies founder on the rocks of change-resistant and dysfunctional institutions that are supposed to implement them, I think the default is that this is not the case. Case in point: Seattle is experiencing a redevelopment boom, and has set goals to increase its tree canopy, but the development boom has resulted in a loss of tree canopy. The city is considering measures to try to reverse that trend. I would like to see my city (Philadelphia), which is also experiencing a development boom and (anecdotally, at least, from what I see with my own eyes) also losing trees, take similar measures. But after seeing a number of enlightened and well-intentioned local policies founder on the rocks of poor implementation, my confidence in the city’s political and bureaucratic leadership at the moment is not particularly high.

the latest on trees and ecosystem services

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I don’t have to be sold on trees and ecosystem services at this point. Planting a ton of trees in cities, and maintaining them well, should be a priority given what we know at this point. I wish we were doing that and ready to move on to talk about adding other layers of vegetation in cities, and designing networks and corridors to connect urban green infrastructure to neighborhood and regional parks and larger reserves outside the city. We are not there, at least in my city, which is generally viewed as somewhat progressive. Anyway, here are some new papers and resources I have come across while perusing the various Elsevier journals:

Urban Heat Islands in Relation to Green Land Use in European Cities

Effect of native habitat on the cooling ability of six nursery-grown tree species and cultivars for future roadside plantings

The effects of trees on air pollutant levels in peri-urban near-road environments

Carbohydrate dynamics in roots, stems, and branches after maintenance pruning in two common urban tree species of North America

Wetlands and carbon revisited

Every breath you take, every move you make: Visits to the outdoors and physical activity help to explain the relationship between air pollution and subjective wellbeing

Physiological and psychological effects of viewing urban forest landscapes assessed by multiple measurements

trees and public health

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A new report from the Nature Conservancy makes the case for the value of urban trees to human health. They go through a number of economic valuation studies that are out there, and the literature on health benefits: air quality, heat stress, mental and physical health, climate change. Then they make a case that urban tree canopy in the U.S. is actually declining and that it is severely under-funded in most cities.

Also, on the tree front, here is a recent paper on the rate at which wood inside urban trees decays. I think one important concept with urban trees is to think of them as infrastructure that has to be maintained and replaced at some rate. They just don’t live as long as forest trees, because they are in stressful environments, performing functions for us, and getting worn out. And the cost of maintaining and replacing them is actually low, and their benefits high, compared to other types of infrastructure. But even though the engineering, planning and architecture professions have been talking a lot about green infrastructure for at least a decade, most of us still aren’t taking it seriously as infrastructure, and the construction industry, bureaucrats and politicians are not taking it seriously, if they have even absorbed the concepts at all. I think this is a case where wealthy private foundations or individuals could make an enormous difference if they wanted to, because the institutions to plant and maintain trees typically exist, but are just severely underfunded. So all I have to do is become a wealthy private individual and I will take care of this. Okay, a solution exists and I’ll get right on that.

The overlooked carbon loss due to decayed wood in urban trees

Decayed wood is a common issue in urban trees that deteriorates tree vitality over time, yet its effect on biomass yield therefore stored carbon has been overlooked. We mapped the occurrence and calculated the extent of decayed wood in standing Ulmus procera, Platanus × acerifolia and Corymbia maculata trees. The main stem of 43 trees was measured every metre from the ground to the top by two skilled arborists. All trees were micro-drilled in two to four axes at three points along the stem (0.3 m, 1.3 m, 2.3 m), and at the tree’s live crown. A total of 300 drilling profiles were assessed for decay. Simple linear regression analysis tested the correlation of decayed wood (cm2) against a vitality index and stem DBH. Decay was more frequent and extensive in U. procera, than P. acerifolia and least in C. maculata. Decay was found to be distributed in three different ways in the three different genera. For U. procera, decay did appear to be distributed as a column from the base to the live crown; whereas, decay was distributed as a cone-shape in P. acerifolia and was less likely to be located beyond 2.3 m. In C. maculata decay was distributed as pockets of variable shape and size. The vitality index showed a weak but not significant correlation with the proportion of decayed wood for P. acerifolia and C. maculata but not for U. procera. However, in U. procera, a strong and significant relationship was found between DBH and stem volume loss (R2 = 0.8006, P = 0.0046, n = 15). The actual volume loss ranged from 0.17-0.75 m3, equivalent to 5% to 25% of the stem volume. The carbon loss due to decayed wood for all species ranged between 69 to 110 kg per tree. Based on model’s calculation, the stem volume of U. procera trees with DBH ≥ 40 cm needs to be discounted by a factor of 13% due to decayed wood regardless of the vitality index. Decayed wood reduces significantly the tree’s standing volume and needs to be considered to better assess the carbon storage potential of urban forests.

street tree survey using Google Street View

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An automated analysis program can produce street tree data using Google Street View.

Google Street View shows promise for virtual street tree surveys

Geospatial technologies are increasingly relevant to urban forestry, but their use may be limited by cost and technical expertise. Technologies like Google Street View™ are appealing because they are free and easy to use. We used Street View to conduct a virtual survey of street trees in three municipalities, and compared our results to existing field data from the same locations. The virtual survey analyst recorded the locations of street trees, identified trees to the species level, and estimated diameter at breast height. Over 93% of the 597 trees documented in the field survey were also observed in the virtual survey. Tree identification in the virtual survey agreed with the field data for 90% of trees at the genus level and 66% of trees at the species level. Identification was less reliable for small trees, rare taxa, and for trees with multiple species in the same genus. In general, tree diameter was underestimated in the virtual survey, but estimates improved as the analyst became more experienced. This study is the first to report on manual interpretation of street tree characteristics using Street View. Our results suggest that virtual surveys in Street View may be suitable for generating some types of street tree data or updating existing data sets more efficiently than field surveys.

tree type and heat mitigation

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Here is an article on how the specific type of street tree affects the urban heat island locally, focusing on plant area index.

Microclimate benefits that different street tree species provide to sidewalk pedestrians relate to differences in Plant Area Index

The way a street tree is able to modify the local microclimate on pedestrian walkways may vary according to tree species according to key canopy and leaf characteristics, such as leaf angle, leaf size, canopy architecture or simply canopy density. Three similar north-south orientated streets, with three different tree species possessing different canopy and leaf characteristics were studied in summer 2014. Microclimatic parameters were measured on pedestrian walkways below and away from tree canopies between 06:00 and 20:00 on three cloudless days. Physiological Equivalent Temperature (PET) was estimated to indicate pedestrian thermal comfort. Microclimate conditions were measured below and away from trees at solar noon for a wide range of trees with different Plant Area Index (PAI) as determined using full-frame photography. In streets with Ulmus procera and Platanus x acerifolia trees, the microclimatic benefits were significantly greater than the street with Eucalyptus scoparia trees, however no significant differences in the estimated PET. Microclimate benefit increased with increasing PAI for all three tree species, however no significant difference in under-canopy microclimate amongst tree species when the PAI was similar. It appears that differences in PAI are paramount in determining the microclimatic and PET benefits. Obviously, certain tree species have a limit of the PAI they can achieve, and that should be considered when selecting or comparing tree species for shading and cooling benefits. This study assists urban planners and landscape professionals in selecting street tree species for cooling benefits based on the expected or managed tree canopy area.

I’d heard of Leaf Area Index before I read this abstract, but not Plant Area Index. A search for Plant Area Index on Google brings up a Wikipedia definition of Leaf Area Index as the top hit.

Leaf area index (LAI) is a dimensionless quantity that characterizes plant canopies. It is defined as the one-sided green leaf area per unit ground surface area (LAI = leaf area / ground area, m2 / m2) in broadleaf canopies.

The best explanation of the difference I could find on the internet is here:

Leaf (or needles in the case of conifers) should be seen here as a generic term for designing the above ground aeral extent of vegetation. if no distinction is made between leaves (needles) and the other elements, the proper term to use is PAI: Plant Area Index rather than LAI.

So I guess the plant area index accounts for the trunk, branches, stems, etc.

new technology for mapping street trees

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Philadelphia Parks and Rec has used a Google Street View-like technology to map street trees.

CycloMedia’s tool is “like Google Maps on steroids,” said Parks and Rec’s lead GIS Specialist Nora Dougherty, who spearheaded the project. It is a way of capturing all kinds of high-definition imagery that is geolocated, which means it can be used for a variety of projects. The tool is easy enough for non-experts to use, according to Mark Wheeler, Chief Geographic Information Officer for the Office of Innovation and Technology, plus the custom-captured imagery can be fully integrated with the city’s existing GIS software. CycloMedia’s tool captures an unprecedented level of detail in the images it records: You’re able to see features like address numbers and even deterioration of rooflines. Plus, every image is date and time stamped, so the user can verify that the images are consistent. This tool is also highly accurate for measuring distances and heights.

After all the streets in Philadelphia were captured using the technology, GIS technicians Tom McKeon and Stuart Olshevski virtually traveled down every street and dropped pins marking the location of each tree. The result is an inventory of nearly 112,000 street trees with geolocation data, which means street trees are now represented in a new layer of geographic information that can be mapped and analyzed. (Forest trees make up the other thousands of trees in Philadelphia, but it’s nearly impossible to accurately inventory them.) Information about the health and species of street trees is also being recorded…

The street tree inventory will be available on August 5 on Open Data Philly, and in an interactive map will be on the city’s website. Citizens can use that information to create their own maps and take action to monitor the trees in their neighborhood.

value of trees

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There have been a lot of studies on the value of urban trees. Well, here’s another. This one is notable for giving a canopy target at which value is maximized (30% at the property level, 38% at the county level).

The implicit value of tree cover in the U.S.: A meta-analysis of hedonic property value studies

Trees in residential neighborhoods and communities provide benefits for homeowners that are capitalized into residential property values. In this paper, we collected data from hedonic property value studies and merged these data with ancillary spatial data describing forest and socio-economic characteristics surrounding each study area to conduct a meta-analysis of the impact of tree canopy cover on the value of residential properties. The meta-analysis suggests that property-level tree cover of about 30% and county-level tree cover of about 38% maximize the implicit price of tree cover in property values. Currently, tree cover in the original study areas was about 14%, on average, around or near study properties. The empirical results, therefore suggest under investment of tree cover on private property from the perspective of individual property owners and from a societal perspective. The findings also have implications for community forest programs regarding planting trees and protection of mature trees to address potential changes in tree abundance, species diversity and stand age due to development and climate change.

tree canopy volume

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I had never thought about modeling tree canopy volume in 3D before. I’ve played around with simple algorithms to place trees on a map, assume a mature canopy area per tree, and estimate the total canopy area. This is useful because cities sometimes set targets and metrics in terms of number of trees, and sometimes in terms of tree canopy. The latter is better because it is more relatable to other goals a city might have related to the hydrologic cycle, carbon, heat, air quality, aesthetics and property values, biodiversity and habitat, and the financial cost to public offers of achieving these goals. Once you have an algorithm relating number of trees to canopy area, you can add more variables like type of tree, growth over time, and some assumed attrition rate or half life. Come to think of it, I have played around with leaf area index which is a quasi-3D concept. Anyway, without further ado here is the article that prompted my line of thought:

Local Impact of Tree Volume on Nocturnal Urban Heat Island: A Case Study in Amsterdam

The aim of this research is to quantify the local impacts of tree volumes on the nocturnal urban heat island intensity (UHI). Volume of each individual tree is estimated through a 3D tree model dataset derived from LIDAR data and modelled with geospatial technology. Air temperature is measured on 103 different locations of the city on a relatively warm summer night. We tested an empirical model, using multi-linear regression analysis, to explain the contribution of tree volume to UHI while also taking into account urbanization degree and sky view factor at each location. We also explored the scale effect by testing variant radii for the aggregated tree volume to uncover the highest impact on UHI. The results of this study indicate that, in our case study area, tree volume has the highest impact on UHI within 40 meters and that a one degree temperature reduction is predicted for an increase of 60,000 m3 tree canopy volume in this 40 meter buffer. In addition, we present how geospatial technology is used in automating data extraction procedures to enable scalability (data availability for large extents) for efficient analysis of the UHI relation with urban elements.