2
views
0
recommends
+1 Recommend
1 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      ecoTeka, Urban Forestry Data Management

      , , ,

      Biodiversity Information Science and Standards

      Pensoft Publishers

      Read this article at

      ScienceOpenPublisher
      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          It is now well known that a healthy urban ecosystem is a crucial element to healthier citizens (Astell-Burt and Feng 2019), better air (Ning et al. 2016) and water quality (Livesley et al. 2016), and overall, to a more resilient urban environment (Huff et al. 2020). With ecoTeka, an open-source platform for tree management, we leverage the power of OpenStreetMap (Mooney 2015), Mappilary, and open data to allow decision makers to improve their urban forestry practices. To have the most comprehensive data about the ecosystems, we plan use all available sources from satellite imagery to LIDAR (light detection and ranging) and compute them with the DeepForest (Weinstein et al. 2020) learning algorithm. We also teamed with the French government to build an open standard for tree data to improve the interoperability of the system. Finally, we calculate a Shannon-Wiener diversity index (used by ecologists to estimate species diversity by their relative abundance in a habitat) to inform the decision making of urban ecosystems.

          Related collections

          Most cited references 6

          • Record: found
          • Abstract: found
          • Article: not found

          The Urban Forest and Ecosystem Services: Impacts on Urban Water, Heat, and Pollution Cycles at the Tree, Street, and City Scale.

          Many environmental challenges are exacerbated within the urban landscape, such as stormwater runoff and flood risk, chemical and particulate pollution of urban air, soil and water, the urban heat island, and summer heat waves. Urban trees, and the urban forest as a whole, can be managed to have an impact on the urban water, heat, carbon and pollution cycles. However, there is an increasing need for empirical evidence as to the magnitude of the impacts, both beneficial and adverse, that urban trees can provide and the role that climatic region and built landscape circumstance play in modifying those impacts. This special section presents new research that advances our knowledge of the ecological and environmental services provided by the urban forest. The 14 studies included provide a global perspective on the role of trees in towns and cities from five continents. Some studies provide evidence for the cooling benefit of the local microclimate in urban green space with and without trees. Other studies focus solely on the cooling benefit of urban tree transpiration at a mesoscale or on cooling from canopy shade at a street and pedestrian scale. Other studies are concerned with tree species differences in canopy interception of rainfall, water uptake from biofilter systems, and water quality improvements through nutrient uptake from stormwater runoff. Research reported here also considers both the positive and the negative impacts of trees on air quality, through the role of trees in removing air pollutants such as ozone as well as in releasing potentially harmful volatile organic compounds and allergenic particulates. A transdisciplinary framework to support future urban forest research is proposed to better understand and communicate the role of urban trees in urban biogeochemical cycles that are highly disturbed, highly managed, and of paramount importance to human health and well-being.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: found
            Is Open Access

            Urban green space, tree canopy and prevention of cardiometabolic diseases: a multilevel longitudinal study of 46 786 Australians

            Abstract Background Cross-sectional studies suggest that more green space may lower the odds of prevalent diabetes, hypertension and cardiovascular diseases (CVD) in cities. We assess if these results are replicable for tree canopy exposure and then extend the study longitudinally to examine incident cardiometabolic outcomes. Methods The study was set in the Australian cities of Sydney, Wollongong and Newcastle. Total green space and tree canopy as percentages of landcover within 1.6 km (1 mile) from home were linked to a residentially stable sample of 46 786 participants in the Sax Institute’s 45 and Up Study (baseline 2006–09; follow-up 2012–15). Separate multilevel models were used to investigate whether the odds of prevalent and incident doctor-diagnosed diabetes, hypertension and CVD were associated with total green space and tree canopy provision, adjusting for age, sex, income, education, employment and couple status. Results Lower odds of prevalent diabetes were observed with 1% increases in total green space [odds ratio (OR) 0.993, 95% confidence interval (CI) 0.988 to 0.998] and tree canopy (0.984, 0.978 to 0.989). Lower odds of prevalent CVD were found with a 1% increase in tree canopy only (0.996, 0.993 to 0.999). Lower odds of incident diabetes (0.988, 0.981 to 0.994), hypertension (0.993, 0.989 to 0.997) and CVD (0.993, 0.988 to 0.998) were associated with a 1% increase in tree canopy, but not total green space. At ≥30% compared with 0–9% tree canopy, there were lower odds of incident diabetes (0.687, 0.547 to 0.855), hypertension (0.828, 0.719 to 0.952) and CVD (0.782, 0.652 to 0.935). However, ≥30% compared with 0–4% total green space was associated with lower odds of prevalent diabetes only (0.695, 0.512 to 0.962). Conclusions Restoring local tree canopy in neighbourhoods may help to prevent the incidence of cardiometabolic diseases.
              Bookmark
              • Record: found
              • Abstract: not found
              • Article: not found

              DeepForest: A Python package for RGB deep learning tree crown delineation

                Bookmark

                Author and article information

                Contributors
                (View ORCID Profile)
                Journal
                Biodiversity Information Science and Standards
                BISS
                Pensoft Publishers
                2535-0897
                September 27 2021
                September 27 2021
                : 5
                Article
                10.3897/biss.5.75705
                © 2021

                Comments

                Comment on this article