Use of Bi-Temporal ALS Point Clouds for Tree Removal Detection on Private Property in Racibórz, Poland
Abstract
:1. Introduction
1.1. Regulations Concerning Tree Removal on Private Property
1.2. Remote Sensing Data in UTC Change Analysis
2. Materials and Methods
2.1. The City of Racibórz Case Study
2.2. Input Data
2.2.1. Remote Sensing Data
2.2.2. Administrative Data
2.3. Creating the Urban Tree Cover Loss Layers
2.3.1. Generating Normalized Digital Surface Models and Canopy Height Models
2.3.2. Initial Classification of Areas Covered by Trees
2.3.3. Segmentation of Individual Trees Based on Canopy Height Models
2.3.4. Generating UTC Loss Layers
2.4. Comparing Administrative Decisions Regarding the Number of Removed Trees with ALS-Derived UTC Loss Layers
3. Results
3.1. Number of Trees Removed from 2011 to 2016
3.2. Number of Trees Removed in the Period of January–February 2017
4. Discussion
4.1. Influence of Tree Removal Policy on the UTC Change on Private Properties
4.2. Combing Information of UTC Change with Permits Issued for Tree Removal
4.3. Limitations of the Study
5. Conclusions
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
References
- Costanza, R.; d’Arge, R.; de Groot, R.; Farber, S.; Grasso, M.; Hannon, B.; Limburg, K.; Naeem, S.; O’Neill, R.V.; Paruelo, J.; et al. The value of the world’s ecosystem services and natural capital. Nature 1997, 387, 253–260. [Google Scholar] [CrossRef]
- Jennings, V.; Larson, L.; Yun, J. Advancing Sustainability through Urban Green Space: Cultural Ecosystem Services, Equity, and Social Determinants of Health. Int. J. Environ. Res. Public Health 2016, 13, 196. [Google Scholar] [CrossRef] [Green Version]
- Biernacka, M.; Kronenberg, J. Urban green space availability, accessibility and attractiveness, and the delivery of ecosystem services. Cities Env. 2019, 12, 5. [Google Scholar]
- Reid, W.; Mooney, H.; Cropper, A.; Capistrano, D.; Carpenter, S.; Chopra, K.; Millennium Ecosystem Assessment. Ecosystems and Human Well-Being: Synthesis. 2005. Available online: www.islandpress.org/bookstore/details.php?prod_id=1119 (accessed on 16 February 2021).
- Haines-Young, R.; Potschin, M. Common International Classification of Ecosystem Services (CICES, Version 4.1); European Environment Agency: Copenhagen, Denmark, 2012. [Google Scholar]
- Takács, Á.; Kiss, M.; Hof, A.; Tanács, E.; Gulyás, Á.; Kántor, N. Microclimate Modification by Urban Shade Trees—An Integrated Approach to Aid Ecosystem Service Based Decision-making. Procedia Environ. Sci. 2016, 32, 97–109. [Google Scholar] [CrossRef] [Green Version]
- Hasselström, L.; Visch, W.; Gröndahl, F.; Nylund, G.M.; Pavia, H. The impact of seaweed cultivation on ecosystem services—A case study from the west coast of Sweden. Mar. Pollut. Bull. 2018, 133, 53–64. [Google Scholar] [CrossRef] [PubMed]
- Nowak, D.J.; Greenfield, E.J. Declining urban and community tree cover in the United States. Urban For. Urban Green. 2018, 32, 32–55. [Google Scholar] [CrossRef]
- Croeser, T.; Ordóñez, C.; Threlfall, C.; Kendal, D.; van der Ree, R.; Callow, D.; Livesley, S.J. Patterns of tree removal and canopy change on public and private land in the City of Melbourne. Sustain. Cities Soc. 2020, 56, 102096. [Google Scholar] [CrossRef]
- Daniel, C.; Morrison, T.H.; Phinn, S. The governance of private residential land in cities and spatial effects on tree cover. Environ. Sci. Policy 2016, 62, 79–89. [Google Scholar] [CrossRef]
- Guo, T.; Morgenroth, J.; Conway, T.; Xu, C. City-wide canopy cover decline due to residential property redevelopment in Christchurch, New Zealand. Sci. Total Environ. 2019, 681, 202–210. [Google Scholar] [CrossRef]
- Mincey, S.K.; Schmitt-Harsh, M.; Thurau, R. Zoning, land use, and urban tree canopy cover: The importance of scale. Urban For. Urban Green. 2013, 12, 191–199. [Google Scholar] [CrossRef]
- Hartmann, T.; Slavíková, L.; McCarthy, S. (Eds.) Nature-Based Flood Risk Management on Private Land; Springer International Publishing: Cham, Switzerland, 2019. [Google Scholar] [CrossRef] [Green Version]
- Kamal, S.; Grodzińska-Jurczak, M.; Brown, G. Conservation on private land: A review of global strategies with a proposed classification system. J. Environ. Plan. Manag. 2014, 58, 576–597. [Google Scholar] [CrossRef] [Green Version]
- Kaspar, J.; Kendal, D.; Sore, R.; Livesley, S. Random point sampling to detect gain and loss in tree canopy cover in response to urban densification. Urban For. Urban Green. 2017, 24, 26–34. [Google Scholar] [CrossRef]
- Heynen, N.; Perkins, H.A.; Roy, P. The Political Ecology of Uneven Urban Green Space. Urban Affairs Rev. 2006, 42, 3–25. [Google Scholar] [CrossRef]
- Goddard, M.A.; Dougill, A.J.; Benton, T.G. Scaling up from gardens: Biodiversity conservation in urban environments. Trends Ecol. Evol. 2010, 25, 90–98. [Google Scholar] [CrossRef] [PubMed]
- Braaker, S.; Moretti, M.; Boesch, R.; Ghazoul, J.; Obrist, M.K.; Bontadina, F. Assessing habitat connectivity for ground-dwelling animals in an urban environment. Ecol. Appl. 2014, 24, 1583–1595. [Google Scholar] [CrossRef]
- Hale, J.D.; Fairbrass, A.J.; Matthews, T.J.; Sadler, J.P. Habitat Composition and Connectivity Predicts Bat Presence and Activity at Foraging Sites in a Large UK Conurbation. PLoS ONE 2012, 7, e33300. [Google Scholar] [CrossRef] [Green Version]
- Ossola, A.; Locke, D.; Lin, B.; Minor, E. Yards increase forest connectivity in urban landscapes. Landsc. Ecol. 2019, 34, 2935–2948. [Google Scholar] [CrossRef]
- Mincey, S.K.; Vogt, J.M. Watering strategy, collective action, and neighborhood-planted trees: A case study of Indianapolis, Indiana, US. Arboric. Urban For. 2014, 40, 84–95. [Google Scholar]
- Marschall, M.J. Citizen Participation and the Neighborhood Context: A New Look at the Coproduction of Local Public Goods. Political Res. Q. 2004, 57, 231–244. [Google Scholar] [CrossRef]
- Lyytimäki, J.; Sipilä, M. Hopping on one leg—The challenge of ecosystem disservices for urban green management. Urban For. Urban Green. 2009, 8, 309–315. [Google Scholar] [CrossRef]
- Speak, A.; Escobedo, F.J.; Russo, A.; Zerbe, S. An ecosystem service-disservice ratio: Using composite indicators to assess the net benefits of urban trees. Ecol. Indic. 2018, 95, 544–553. [Google Scholar] [CrossRef]
- Kirkpatrick, J.; Davison, A.; Daniels, G. Resident attitudes towards trees influence the planting and removal of different types of trees in eastern Australian cities. Landsc. Urban Plan. 2012, 107, 147–158. [Google Scholar] [CrossRef]
- Conway, T.M.; Bang, E. Willing partners? Residential support for municipal urban forestry policies. Urban For. Urban Green. 2014, 13, 234–243. [Google Scholar] [CrossRef]
- Pandit, R.; Polyakov, M.; Sadler, R. Valuing public and private urban tree canopy cover. Aust. J. Agric. Resour. Econ. 2013, 58, 453–470. [Google Scholar] [CrossRef] [Green Version]
- Saphores, J.D.; Li, W. Estimating the value of urban green areas: A hedonic pricing analysis of the single family housing market in Los Angeles, CA. Landsc. Urban Plan. 2012, 104, 373–387. [Google Scholar] [CrossRef]
- Adams, L.W.; Van Druff, L.W.; Luniak, M. Managing urban habitats and wildlife. In Techniques for Wildlife Investigations and Management, 6th ed.; The Wildlife Society: Bethesda, MD, USA, 2005; pp. 714–739. [Google Scholar]
- Narducci, J.; Quintas-Soriano, C.; Castro, A.; Som-Castellano, R.; Brandt, J.S. Implications of urban growth and farmland loss for ecosystem services in the western United States. Land Use Policy 2019, 86, 1–11. [Google Scholar] [CrossRef]
- Rimal, B.; Sharma, R.; Kunwar, R.; Keshtkar, H.; Stork, N.E.; Rijal, S.; Rahman, S.A.; Baral, H. Effects of land use and land cover change on ecosystem services in the Koshi River Basin, Eastern Nepal. Ecosyst. Serv. 2019, 38, 100963. [Google Scholar] [CrossRef]
- Wang, W.; Wu, T.; Li, Y.; Xie, S.; Han, B.; Zheng, H.; Ouyang, Z. Urbanization Impacts on Natural Habitat and Ecosystem Services in the Guangdong-Hong Kong-Macao “Megacity”. Sustainability 2020, 12, 6675. [Google Scholar] [CrossRef]
- Nasemann, A. Fällen Verboten. Available online: https://www.sueddeutsche.de/geld/baeume-faellen-verboten-1.3585349 (accessed on 30 September 2020).
- Lavy, B.L.; Hagelman, R.R. Protecting the urban forest: Variations in standards and sustainability dimensions of municipal tree preservation ordinances. Urban For. Urban Green. 2019, 44, 126394. [Google Scholar] [CrossRef]
- Benton-Short, L.; Keeley, M.; Rowland, J. Green infrastructure, green space, and sustainable urbanism: Geography’s important role. Urban Geogr. 2017, 40, 330–351. [Google Scholar] [CrossRef]
- Guo, T.; Morgenroth, J.; Conway, T. Redeveloping the urban forest: The effect of redevelopment and property-scale variables on tree removal and retention. Urban For. Urban Green. 2018, 35, 192–201. [Google Scholar] [CrossRef]
- Green Spaces. Available online: https://www.r3-trees.com/ (accessed on 30 September 2020).
- Feltynowski, M.; Kronenberg, J.; Bergier, T.; Kabisch, N.; Łaszkiewicz, E.; Strohbach, M.W. Challenges of urban green space management in the face of using inadequate data. Urban For. Urban Green. 2018, 31, 56–66. [Google Scholar] [CrossRef]
- Krynicki, M.; Witkoś Gnach, K. Monitoring standardów w zarządzaniu zielenią wysoką w największych miastach Polski. Technical Report. 2016. Available online: http://drzewa.org.pl/publikacja/1075-2/ (accessed on 30 September 2020).
- The Act of December 16, 2016 Amending the Act on Nature Protection and the Act on Forests. 2016. Available online: http://isap.sejm.gov.pl/isap.nsf/DocDetails.xsp?id=WDU20160002249 (accessed on 30 September 2020).
- Wagner, W.; Ullrich, A.; Melzer, T.; Briese, C.; Kraus, K. From Single-Pulse to Full-Waveform Airborne Laser Scanners: Potential and Practical Challenges. 2004. Available online: https://www.isprs.org/proceedings/XXXV/congress/comm3/papers/267.pdf (accessed on 16 February 2021).
- Wezyk, P. The integration of the terrestrial and airborne laser scanning technologies in the semi-automated process of retrieving selected trees and forest stand parameters Integração das tecnologias terrestre e aerotransportada de scanner laser no processo semi. Ambiencia 2012, 8, 533–548. [Google Scholar]
- Conway, T.M.; Urbani, L. Variations in municipal urban forestry policies: A case study of Toronto, Canada. Urban For. Urban Green. 2007, 6, 181–192. [Google Scholar] [CrossRef]
- Landry, S.; Pu, R. The impact of land development regulation on residential tree cover: An empirical evaluation using high-resolution IKONOS imagery. Landsc. Urban Plan. 2010, 94, 94–104. [Google Scholar] [CrossRef]
- Sung, C.Y. Mitigating surface urban heat island by a tree protection policy: A case study of The Woodland, Texas, USA. Urban For. Urban Green. 2013, 12, 474–480. [Google Scholar] [CrossRef]
- Sung, C.Y. Evaluating the efficacy of a local tree protection policy using LiDAR remote sensing data. Landsc. Urban Plan. 2012, 104, 19–25. [Google Scholar] [CrossRef]
- Grove, J.M.; Locke, D.H.; O’Neil-Dunne, J.P.M. An Ecology of Prestige in New York City: Examining the Relationships Among Population Density, Socio-economic Status, Group Identity, and Residential Canopy Cover. Environ. Manag. 2014, 54, 402–419. [Google Scholar] [CrossRef] [PubMed]
- Lee, S.J.; Longcore, T.; Rich, C.; Wilson, J.P. Increased home size and hardscape decreases urban forest cover in Los Angeles County’s single-family residential neighborhoods. Urban For. Urban Green. 2017, 24, 222–235. [Google Scholar] [CrossRef]
- Biuletyn Informacji Publicznej. Available online: https://www.bipraciborz.pl (accessed on 30 September 2020).
- IT System of the Country Protection. Available online: https://isok.gov.pl/index.html (accessed on 30 September 2020).
- Head Office of Geodesy and Cartography. Available online: http://www.gugik.gov.pl/ (accessed on 30 September 2020).
- Ordinance of the Minister of Regional Development and Construction of March 29, 2001 on Land and Building Records. Available online: http://isap.sejm.gov.pl/isap.nsf/DocDetails.xsp?id=wdu20010380454 (accessed on 5 January 2021).
- McGaughey, R.J. FUSION/LDV: Software for LIDAR Data Analysis and Visualization; US Department of Agriculture, Forest Service, Pacific Northwest Research Station: Seattle, WA, USA, 2009; p. 123. [Google Scholar]
- Castilla, G.; Hay, G. Image objects and geographic objects. In Object-Based Image Analysis; Springer: Berlin/Heidelberg, Germany, 2008; pp. 91–110. [Google Scholar]
- Shojanoori, R.; Shafri, H.Z. Review on the use of remote sensing for urban forest monitoring. Arboric. Urban For. 2016, 42, 400–417. [Google Scholar]
- Blaschke, T. Object based image analysis for remote sensing. ISPRS J. Photogramm. Remote Sens. 2010, 65, 2–16. [Google Scholar] [CrossRef] [Green Version]
- Vincent, L.; Soille, P. Watersheds in digital spaces: An efficient algorithm based on immersion simulations. IEEE Trans. Pattern Anal. Mach. Intell. 1991, 13, 583–598. [Google Scholar] [CrossRef] [Green Version]
- Wang, K.; Wang, T.; Liu, X. A Review: Individual Tree Species Classification Using Integrated Airborne LiDAR and Optical Imagery with a Focus on the Urban Environment. Forests 2018, 10, 1. [Google Scholar] [CrossRef] [Green Version]
- Conway, T.M. Tending their urban forest: Residents’ motivations for tree planting and removal. Urban For. Urban Green. 2016, 17, 23–32. [Google Scholar] [CrossRef]
- Redyuk, S.; Schelter, S.; Rukat, T.; Markl, V.; Biessmann, F. Learning to Validate the Predictions of Black Box Machine Learning Models on Unseen Data. In Proceedings of the Workshop on Human-In-the-Loop Data Analytics; ACM Press: New York, NY, USA, 2019. [Google Scholar] [CrossRef]
- Nowak, D.J.; Hirabayashi, S.; Bodine, A.; Greenfield, E. Tree and forest effects on air quality and human health in the United States. Environ. Pollut. 2014, 193, 119–129. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Kuželka, K.; Slavík, M.; Surový, P. Very High Density Point Clouds from UAV Laser Scanning for Automatic Tree Stem Detection and Direct Diameter Measurement. Remote Sens. 2020, 12, 1236. [Google Scholar] [CrossRef] [Green Version]
- Bello, S.A.; Yu, S.; Wang, C.; Adam, J.M.; Li, J. Review: Deep Learning on 3D Point Clouds. Remote Sens. 2020, 12, 1729. [Google Scholar] [CrossRef]
- Timilsina, S.; Sharma, S.K.; Aryal, J. Mapping Urban Trees Within Cadastral Parcels Using An Object-Based Convolutional Neural Network. ISPRS Ann. Photogramm. Remote Sens. Spat. Inf. Sci. 2019, IV-5/W2, 111–117. [Google Scholar] [CrossRef] [Green Version]
- Timilsina, S.; Aryal, J.; Kirkpatrick, J.B. Mapping Urban Tree Cover Changes Using Object-Based Convolution Neural Network (OB-CNN). Remote Sens. 2020, 12, 3017. [Google Scholar] [CrossRef]
- Phelan, K.; Hurley, J.; Bush, J. Land-Use Planning’s Role in Urban Forest Strategies: Recent Local Government Approaches in Australia. Urban Policy Res. 2018, 37, 215–226. [Google Scholar] [CrossRef]
Data Type | Data Acquisition Date | Resolution | Flight Altitude |
---|---|---|---|
ALS point clouds | 11 June 2011 | ≥12 ppsqm | ∼1000 m AGL |
ALS point clouds | 5 March 2017 | ≥12 ppsqm | ∼1000 m AGL |
Aerial orthophoto RGB | 1 September 2016 | 0.15 m | — |
(Google Earth) |
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. |
© 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
Share and Cite
Przewoźna, P.; Hawryło, P.; Zięba-Kulawik, K.; Inglot, A.; Mączka, K.; Wężyk, P.; Matczak, P. Use of Bi-Temporal ALS Point Clouds for Tree Removal Detection on Private Property in Racibórz, Poland. Remote Sens. 2021, 13, 767. https://doi.org/10.3390/rs13040767
Przewoźna P, Hawryło P, Zięba-Kulawik K, Inglot A, Mączka K, Wężyk P, Matczak P. Use of Bi-Temporal ALS Point Clouds for Tree Removal Detection on Private Property in Racibórz, Poland. Remote Sensing. 2021; 13(4):767. https://doi.org/10.3390/rs13040767
Chicago/Turabian StylePrzewoźna, Patrycja, Paweł Hawryło, Karolina Zięba-Kulawik, Adam Inglot, Krzysztof Mączka, Piotr Wężyk, and Piotr Matczak. 2021. "Use of Bi-Temporal ALS Point Clouds for Tree Removal Detection on Private Property in Racibórz, Poland" Remote Sensing 13, no. 4: 767. https://doi.org/10.3390/rs13040767