Improving methods to calculate the loss of ecosystem services provided by urban trees using LiDAR and aerial orthophotos

Zięba-Kulawik, Karolina; Hawryło, Paweł; Wężyk, Piotr; Przewoźna, Patrycja; Inglot, Adam

doi:10.1016/j.ufug.2021.127195

Cited by 19 publications

(14 citation statements)

References 32 publications

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“…According to a large number of experimental data and related literature, in order to facilitate relevant workers to quickly understand the urban green space based on drone monitoring, the study area should be divided into different categories by comprehensively considering environmental factors and the characteristics of the research object. The green space can be preliminarily divided into forests [53], plantations [33,41], parks [30], street trees [35], community internal greening [54], and private land [55]. This division will help understand the necessity and particularity of urban park green space monitoring and management, and provide a reference for drone-based green space monitoring and management.…”

Section: Discussionmentioning

confidence: 99%

Drone Photogrammetry-Based Meticulous Monitoring and Management of Urban Park Green Space

Jin,

Xiao

2023

Preprint

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Urban park green spaces combine multiple ecological benefits and meet the entertainment and leisure needs of residents, and have attracted the attention of urban managers and various stakeholders. The benefits of urban park green space mainly come from vegetation, facilities, and the spaces they create. To better monitor and manage individual urban parks with data, suitable remote sensing methods and suitable protocols are needed for recording, evaluation, and visualization. Drones have become a potential tool for future monitoring and management of individual urban parks due to their ease of operation, cost-effectiveness, and ability to derive multiple types of data. However, previous relevant studies have not considered the particularity of urban park green space vegetation and the facilities and spaces that provide cultural value. Monitoring of vegetation mainly focused on homogeneous green spaces such as artificial forests, orchards, and street trees. Research on facilities focused on campus, cultural heritage, and road-supporting facilities. Therefore, it is necessary to explore how drones can be used to assess objects of concern (vegetation, facilities, and spaces) in urban park monitoring and management. This study draws inspiration from a variety of drone processing methods to explore a processing workflow and effective data suitable for heterogeneous urban park green spaces, making full use of all data that can be derived from drones. The results show that drones can effectively estimate tree heights through three-dimensional point clouds in heterogeneous green spaces. Missions with high-quality flight parameters have an accuracy comparable to missions targeting homogeneous green areas. At the same time, drones can effectively estimate crown width through orthophotos in heterogeneous green spaces. In addition, drones demonstrate excellent accuracy, efficiency, and good visualization when monitoring facilities and spaces. Therefore, it is feasible and effective to apply various data from drones (i.e., aerial photos, point clouds, orthophotos, and digital surface model (DSM)) in urban park green space monitoring and management. This will contribute significantly to the digital development of urban park green spaces, as well as the advancement of urban landscape ecology, landscape architecture, urban planning, and urban forestry disciplines.

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Section: Discussionmentioning

confidence: 99%

Drone Photogrammetry-Based Meticulous Monitoring and Management of Urban Park Green Space

Jin,

Xiao

2023

Preprint

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“…Improvement of urban ecosystem services was reported to increase housing prices by about 23.67% in 284 cities in China from 2015 to 2018 [ 102 ]. With temporal liberalization of urban forests regulations, trees on private properties are massively removed by house owners, leading to the loss of tree canopy cover and the associated ES and structural values benefiting urban residents [ 103 , 104 ]. Thus, a city's forest conservation regulations and strategies should always enforce the retention of trees on private properties and forested conservation lands near residential development, as a potential method for maximizing property and community tree cover [ 24 ] to protect and sustain urban forests ES for city residents.…”

Section: Discussionmentioning

confidence: 99%

Influence of urban forests on residential property values: A systematic review of remote sensing-based studies

Ewane,

Bajaj,

Velasquez-Camacho

et al. 2023

Heliyon

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“…By 2030, The Chinese urban population will account for about three-quarters of the total population [ 8 ]. Rapid urbanization has brought about a series of problems related to urban expansion, which might lead to inefficient LUCC, the heat island effect, soil erosion and human settlement deterioration [ 9 , 10 , 11 ]. According to the Millennium Ecosystem Assessment (MA), more than 60% of global Ecosystem Services (ES) were degraded or overutilized, and LUCC change caused by human activities was one of the important driving factors leading to the degradation of ES [ 12 ].…”

Section: Introductionmentioning

confidence: 99%

Spatio-Temporal Evolution, Prediction and Optimization of LUCC Based on CA-Markov and InVEST Models: A Case Study of Mentougou District, Beijing

Yang

Zhang²,

Zhu

et al. 2022

IJERPH

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With the rapid advancement of urbanization and industrialization, the contradiction between the social economy and resources and the environment has become increasingly prominent. On the basis of limited land resources, the way to promote multi-objective comprehensive development such as economic, social development and ecological and environmental protection through structure and layout regulation, so as to maximize regional comprehensive benefits, is an important task of current land spatial planning. Our aim is to obtain land-use-change data in the study area using remote-sensing data inversion and multiple-model simulation. Based on land suitability evaluation, we predict and optimize the land use structure of the study area in 2030 and evaluate and compare ecosystem services. Based on remote-sensing images and eco-environmental data from 1985 to 2014 in the study area, land use/land cover change (LUCC) and future simulation data were obtained by using supervised classification, landscape metrics and the CA-Markov model. The ecosystem services were evaluated by the InVEST model. The analytic hierarchy process (AHP) method was used to evaluate the land suitability for LUCC. Finally, the LUCC in 2030 under two different scenarios, Scenario_1 (prediction) and Scenario_2 (optimization), were evaluated, and the ecosystem service functions were compared. In the last 30 years, the landscape in the study area has gradually fragmented, and the built-up land has expanded rapidly, increased by one-third, mainly at the cost of cropland, orchards and wasteland. According to the suitability evaluation, giving priority to the land use types with higher environmental requirements will ensure the study area has a higher ecosystem service value. The rapid development of urbanization has a far-reaching impact on regional LUCC. Intensive land resources need reasonable and scientific land use planning, and land use planning should be based on the suitability evaluation of land resources, which can improve the regional ecosystem service function.

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Improving methods to calculate the loss of ecosystem services provided by urban trees using LiDAR and aerial orthophotos

Cited by 19 publications

References 32 publications

Drone Photogrammetry-Based Meticulous Monitoring and Management of Urban Park Green Space

Drone Photogrammetry-Based Meticulous Monitoring and Management of Urban Park Green Space

Influence of urban forests on residential property values: A systematic review of remote sensing-based studies

Spatio-Temporal Evolution, Prediction and Optimization of LUCC Based on CA-Markov and InVEST Models: A Case Study of Mentougou District, Beijing

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