Submitted Successfully!
To reward your contribution, here is a gift for you: A free trial for our video production service.
Thank you for your contribution! You can also upload a video entry or images related to this topic.
Version Summary Created by Modification Content Size Created at Operation
1 -- 2631 2023-08-17 03:24:09 |
2 format correct Meta information modification 2631 2023-08-17 03:26:35 |

Video Upload Options

Do you have a full video?


Are you sure to Delete?
If you have any further questions, please contact Encyclopedia Editorial Office.
Anderson, V.; Suneja, M.; Dunjic, J. Sensing and Measurement Techniques for Nature-Based Solutions Evaluation. Encyclopedia. Available online: (accessed on 17 June 2024).
Anderson V, Suneja M, Dunjic J. Sensing and Measurement Techniques for Nature-Based Solutions Evaluation. Encyclopedia. Available at: Accessed June 17, 2024.
Anderson, Vidya, Manavvi Suneja, Jelena Dunjic. "Sensing and Measurement Techniques for Nature-Based Solutions Evaluation" Encyclopedia, (accessed June 17, 2024).
Anderson, V., Suneja, M., & Dunjic, J. (2023, August 17). Sensing and Measurement Techniques for Nature-Based Solutions Evaluation. In Encyclopedia.
Anderson, Vidya, et al. "Sensing and Measurement Techniques for Nature-Based Solutions Evaluation." Encyclopedia. Web. 17 August, 2023.
Sensing and Measurement Techniques for Nature-Based Solutions Evaluation

Sensing and measurement techniques are necessary to study, evaluate, and understand the complex physical and chemical interactions that must occur for the successful deployment of nature-based solutions (NbS). Sensing and measurement techniques can provide useful meteorological and physiological data on nature-based interventions between different spatial, spectral, temporal, and thematic scales. Because NbS encompass research from across different fields, it is essential to reduce barriers to knowledge dissemination, and enable the circulation of information across different jurisdictions. 

nature-based solutions air quality biodiversity soil quality

1. Introduction

The notion that nature in and of itself can provide practical solutions to environmental issues is conceptually logical and intuitive across disciplines. Within public policy, the appreciation of the functional utility of nature-based solutions (NbS) has strengthened, while the concept has become a fixture within the scientific lexicon [1][2][3]. NbS have been classified by the International Union for the Conservation of Nature (IUCN) as “actions to protect, sustainably manage, and restore natural or modified ecosystems, that address societal challenges effectively and adaptively, simultaneously providing human well-being and biodiversity benefits” [4]. It is an interdisciplinary definition, comprising research across different fields.
For successful implementation of NbS projects at regenerative and landscape levels, it is necessary to understand the complex physical and chemical interactions that must transpire. Sensing and measurement techniques are essential to comprehending these processes. These techniques provide physiological and meteorological data across different scales from the spatial and spectral, to the temporal. Information and communication technologies have also dramatically reduced barriers to knowledge dissemination, thereby enabling the circulation of information more quickly and reliably.
Addressing socio-environmental challenges such as climate change using NbS, requires quantifiable data. NbS can support the achievement of the United Nations Sustainable Development Goals (UN SDGs) to increase environmental and health equity [5]. How NbS are measured can determine which solutions best address local socio-environmental challenges, and how they are prioritized, funded, and adopted by decision makers.

2. Opportunities and Challenges Associated with NBS Sensing Techniques

It is important to note that sensing data are often influenced by the type of sensors used. For example, the monitoring of NbS for flood attenuation using gauge sensors can only provide single-dimension physical variables, while the use of visual sensors provides dynamic and real onsite details. Cost also presents a challenge to the sensor-based monitoring of NbS performance. The second challenge associated with NbS monitoring relates to scale. For instance, when measuring NbS flood attenuation, only using monitoring stations can provide limited results [6]. Ground-based monitoring stations are limited in number and in coverage. Conversely, remote sensing is more cost-effective and comprehensive in the coverage of large areas. Emerging sensing techniques such as advanced very-high-resolution radiometer (AVHRR) data can be used for monitoring the regional dimensions of NbS for flood attenuation [6]. AVHRR has a high temporal resolution and allows for monitoring of NbS-based flood management in real time [7]. Airborne information on the other hand is cost-intensive and lacking in sufficient observational frequency [6].
Further, some NbS types (e.g., green walls, green roofs, and constructed wetlands) and some parameters (e.g., air quality, temperature, and storm water) are more easily sensed and measured, compared to others. For example, it is challenging to measure the storm surge protection benefits of NbS on account of the high variability, and uncertain storm trajectory, frequency, intensity, and impact [6]. Additionally, it is prudent to acknowledge that NbS are dynamic and therefore evaluating their performance over time is important. For instance, the thermal efficiency of green roofs varies with the growth and development of vegetation over time and across seasons. Modelling used in conjunction with NbS monitoring can provide greater insights as shown by Taleghani et. al. [8] into the evaluation of thermal performance of varied NbS combinations across scales.

3. Efficacy Evaluation

Establishing the efficiency and efficacy of NbS performance across types and scales is essential for building resilient and sustainable communities. Monitoring is crucial for understanding NbS performance over time. Best practices for techniques, instruments, and sensors to monitor NbS performance have been largely undefined.
Many studies adopt a simulation/modelling-based approach for evaluating NbS performance [9][10][11] as a monitoring approach is not encouraged when considering multiple scales on account of timing and the cost involved [12]. These differences can contribute to multiple knowledge gaps; therefore, cross-functional and interdisciplinary approaches need to be considered for the sensing and measurement of NbS performance across different functions and scales. It is crucial to note there are some NbS that deliver a host of co-benefits when upscaled. NbS performance monitoring is an important step in the identification of suitable NbS types for application at a given scale. For example, individual green roofs may be incentivised for their building energy efficiency benefits, but upscaling across a community can contribute co-benefits including habitat creation and water regulation [2][13]. Conversely, large-scale NbS interventions may not produce the desired benefits and empirical studies indicate that while natural water retention measures can be effective at a smaller scale, their efficacy may be reduced through upscaling [14].
Methods for assessing the co-benefits of NbS performance across scales and functions need to account for the dynamics of geographic and temporal scales [15][16][17][18]. The duration of NbS monitoring also needs to be considered. Long-term monitoring for evaluating NbS performance can provide insights into how NbS interventions perform throughout the seasons. This can also lead to active learning from failures that can improve future NbS implementation [19]. A more holistic approach is required that integrates observational data with remote sensing for higher accuracy in evaluating NbS performance. Additionally, more research is necessary to develop long-term sensing and measurement strategies for NbS performance at the landscape scale.
Other challenges in the in-situ sensing and measurement of NbS interventions include maintenance requirements, reading errors, and data acquisition gaps that can occur with sensor deployment. Sensors can produce reading errors depending on meteorological conditions, operational malfunction, vandalism, etc., while inputting data into a model data can be more flexible by providing a margin of error [9][20][21]. Studies have used field data alongside modelling simulations to establish the role of NbS in promoting thermal comfort and heat mitigation[9][22]. Joyce et al. [23] developed a multi-scale modelling system to establish the efficacy of green infrastructure.
Traditional urban meteorological networks can be useful in evaluating NbS efficacy. These networks are often distributed across different locations, respecting the morphological characteristics of the area, using the local climate zones concept. Such networks have sensors located in different areas, that can include different NbS interventions including urban parks, street trees, green corridors, riverbanks, and constructed wetlands. It should be noted that the main purpose of urban meteorological networks is not NbS evaluation; however, long-term sensor data can be quite useful in evaluating NbS efficacy. Urban meteorological networks that are well-reported in scientific articles include NSUNET in Novi Sad, Serbia [24][25]; MOCCA in Ghent, Belgium [26]; UMN in Szeged, Hungary [27]; ASTI-Network in Rome, Italy [28]; and the Beijing urban meteorological network in China [29]. There can be limitations in using sensing data from urban meteorological networks. For example, the assessment of NbS interventions for temperature regulation was not the original intended use for these networks. In addition, high maintenance and data transfer costs can render these networks obsolete and inoperative (e.g., NSUNET).
HOBO temperature loggers are a lower-cost device suitable for sensing and measurement of NbS [30][31]. These sensors can continuously record air temperature data for longer time periods ranging from a season to a year. Depending on the model of the HOBO sensor, they can record multiple climatic parameters.
State-of-the-art equipment for evaluating the temperature regulation function of NbS interventions include custom made micro-meteorological carts, introduced by Middel and Krayenhoff [32]. These custom-made stations are different from traditional stations in their capacity to record six-directional shortwave and longwave radiation, which can be useful in evaluating different surface types (i.e., natural, artificial, pervious, impervious). Limitations of these custom-made micrometeorological carts include their bulky size which limits portability, high cost [33] and personnel requirements. More recently, innovative low-cost sensors (e.g., “MaRTiny”) have been developed to overcome the limitations mentioned [33].
There are also simple-to-use and low-cost sensors for the assessment of the thermal performance of NbS that include Kestrel heat stress trackers (e.g., 5400). Their small size makes them convenient to use in almost any type of environment. Kestrel sensors are an established form of instrumentation in the scientific community, so data obtained with these devices have been well-reported in the literature [34][35][36]. Similar stations with multiple sensors include the AHLBORN thermal comfort set that can also be used to assess thermal conditions in urban areas [37][38].
For many of the sensing techniques used for measuring temperature regulation potential, the quantitative assessment of NbS interventions is not the primary purpose; rather, the primary purpose is the measurement of urban or micro-climatological conditions. Given that surface type and morphology significantly impact thermal conditions, such sensors can be useful in evaluating the efficacy of NbS interventions to regulate temperature.

4. Access to Sensing and Measurement Research and Technologies

This study has shown the majority of research on quantitative evaluation of NbS is focused on communities in the Global North (Figure 1). While communities in the Global South are more vulnerable to climate impacts, research on the quantitative evaluation of NbS as a multi-functional intervention is limited. For example, the 2030 agenda for sustainable development is essential for South Asian countries which account for nearly 37 percent of the world’s poor and NbS interventions are an important tool in achieving the UN SDGs [39].
Figure 1. Geographic distribution of NbS studies.
The specific cost of sensors and measurement equipment can vary according to geography as do the necessary knowledge and skill to operate the equipment. Access to NbS sensing and measurement knowledge and technologies in the Global South is a crucial challenge. Technology access is linked to economic development as demonstrated in the Global North [40][41][42]. There is a digital divide [43] between the Global North and South which can affect the widespread implementation and evaluation of NbS. The lack of infrastructure (e.g., electricity and data coverage) in remote areas and isolated communities also limits the use of NbS sensing and measurement technologies. For example, automated weather stations require a constant supply of power for the transmission of data [40]. Other accessibility challenges include sensor costs and a lack of expertise in data collation, processing, and analysis [40]. NbS measurements can contribute to cost-effective implementation of specific NbS, thereby preventing project implementation errors.

5. Supporting Achievement of the UN SDGs

Sensing and measurement techniques provide evidence-based information on the efficacy of NbS that can inform policy development for the achievement of the UN SDGs across communities. For example, urban trees have been shown to have a significant positive impact on air quality as evidenced in Canada and the U.S. through the annual removal of 16,500 and 711,000 metric tonnes of air pollutants, respectively [44][45][46]. Additionally, sensing and measurement have shown that green roofs and walls have a beneficial impact on both air quality and urban heat [31][47][48]. NbS interventions have associated health benefits that include reduced cardiovascular and respiratory mortality; enhanced post-operative healing; and improved health outcomes such as reduced heart and blood pressure rates, improved stress, and immune system response, and amplified parasympathetic nerve activity [49][50][51][52][53][54][55][56]. Such NbS interventions can address socio-environmental challenges, in addition to supporting the achievement of UN SDG 3 (good health and well-being) and UN SDG 11 (sustainable cities and communities).
The spread of infectious diseases has become a growing issue of public health concern. As a result, there is increased awareness of the correlation between the fragmentation of the landscape, disruption of habitat, and proliferation of disease within both animal and human populations [43][57][58][59][60]. NbS interventions are essential to reducing the spread of infectious diseases through the establishment of natural corridors for reservoir populations, and the restoration of wildlife habitat [43]. Within this context, NbS can support UN SDG 11 (sustainable cities and communities) and UN SDG 15 (life on land).
Ensuring clean water access is a global issue. For example, cyanobacteria contamination from eutrophic water bodies can lead to the consumption of and contact with contaminated drinking and recreational water sources. The sensing and measurement of NbS interventions such as riparian buffers and tree-based intercropping have shown that these systems can improve water quality in lakes and rivers [61][62][63]. Tree-based intercropping can also reduce pesticide and fertilizer use within conventional agricultural management that can lead to runoff and eutrophication [62][63]. Sensing and measurement have also shown that green walls can be used for onsite domestic greywater remediation [64]. These examples of NbS can support the achievement of UN SDG 3 (good health and well-being), and UN SDG 6 (clean water and sanitation), in addition to UN SDG 11 (sustainable cities and communities).

6. NbS Policy Implications

To facilitate widespread NbS implementation for sustainable development, quantifiable evidence for NbS efficacy is essential. Currently, existing evidence is scattered across physical, biological, and social science domains and is not readily accessible to policy makers [65]. Although various policy instruments mention NbS, they lack quantitative and measurable targets relating to NbS deployment [66]. Further, the upscaling of NbS interventions needs to be prioritized within environmental policies. While NbS deployment at the site level provides important benefits, landscape level implementation supports regenerative change. The sensing and measurement of the multifunctional benefits of NbS provides robust scientific evidence to support the adoption of NbS as a standard intervention within environmental policies.
In South Asia, specific frameworks for NbS implementation are lacking especially in India, Bangladesh and Nepal [67] although, there is an exhaustive list of national policies and guidelines that support NbS implementation writ large (e.g., The Indian Forest Act, 1927; The Wildlife (Protection) Act (WPA), 1972; The Environment (Protection) Act, 1986; The Forest Act, 1927; Bangladesh Environment Conservation Act, 1995; Bangladesh Climate Change Strategy and Action Plan (BCCSAP), 2009; Soil and Watershed Conservation Act, 1982; Agrobiodiversity Policy, 2007). Cities across the globe need to look at various means by which NbS are incorporated for augmenting the benefits that NbS offer. For example, in Canada, the City of Toronto has mandated green roofs in residential and commercial buildings [68]. Model Building By-Laws, 2016, in India encourage adoption of rainwater harvesting (RWH), with all buildings having a plot size of 100 sq m mandating rainwater harvesting in Indian cities (e.g., New Delhi) [69]. Apart from this, there exist separate legislations pertaining to RWH for different states and union territories in India [70].
In Canada, environmental policy for NbS implementation is not integrated, although there are broad associations between NbS and national climate policy. For example, Canada’s ‘Healthy Environment and a Healthy Economy’ plan recognizes that NbS are a key climate change intervention [71]. The Intergovernmental Panel on Climate Change (IPCC) has also emphasised the importance of NbS interventions in transforming the built environment and providing urban carbon sinks, while the European Union promotes NbS interventions to protect biodiversity and expand natural ecosystem services [72][73][74]. In the United States, NbS interventions are narrowly defined as an effective tool for stormwater management in the Clean Water Act [75].
While NbS are recognised as an important tool, evaluation through sensing and measurement is crucial to the development of NbS policies that effectively address societal and environmental challenges such as climate change. For example, sensing and measurement were used to support the sustainable water management objectives of the EU Water Reuse Directive, when green walls in urban settings were tested for an 18-month period by Pucher et al. [76] to monitor the effectiveness of using greywater instead of fresh water for irrigation. According to Katsou et al. [77] four main steps emerge in NbS implementation that include (i) planning, (ii) design, (iii) assessment and (iv) communication of results. The NbS assessment phase includes process performance monitoring (sensors, instrumentation, automation, and control) and the measurement or assessment of impacts.
The importance of quantitative NbS evaluation is becoming more apparent in policy development. For example, the European Commission published a handbook for practitioners on evaluating the impact of NbS that includes methods for evaluation [78][79]. These methods rely on sensing and measurement techniques as important tools for evaluating the efficacy of NbS projects to support resilience planning for cities.


  1. Kabisch, N.; Frantzeskaki, N.; Pauleit, S.; Naumann, S.; Davis, M.; Artmann, M.; Haase, D.; Knapp, S.; Korn, H.; Stadler, J.; et al. Nature-based solutions to climate change mitigation and adaptation in urban areas: Perspectives on indicators, knowledge gaps, barriers, and opportunities for action. Ecol. Soc. 2016, 21, 39.
  2. Raymond, C.M.; Frantzeskaki, N.; Kabisch, N.; Berry, P.; Breil, M.; Nita, M.R.; Geneletti, D.; Calfapietra, C. A framework for assessing and implementing the co-benefits of nature-based solutions in urban areas. Environ. Sci. Policy 2017, 77, 15–24.
  3. Keesstra, S.; Nunes, J.; Novara, A.; Finger, D.; Avelar, D.; Kalantari, Z.; Cerdà, A. The superior effect of nature based solutions in land management for enhancing ecosystem services. Sci. Total Environ. 2018, 610–611, 997–1009.
  4. Cohen-Shacham, E.; Walters, G.; Janzen, C.; Maginnis, S. (Eds.) Nature-Based Solutions to Address Global Societal Challenges; IUCN: Gland, Switzerland, 2016; Volume 13, p. 97. ISBN 978-2-8317-1812-5.
  5. Anderson, V.; Gough, W.A. Harnessing the four horsemen of climate change: A framework for deep resilience, decarbonization, and planetary health in Ontario, Canada. Sustainability 2021, 13, 379.
  6. Kumar, P.; Debele, S.E.; Sahani, J.; Rawat, N.; Marti-Cardona, B.; Alfieri, S.M.; Basu, B.; Basu, A.S.; Bowyer, P.; Charizopoulos, N.; et al. An overview of monitoring methods for assessing the performance of nature-based solutions against natural hazards. Earth-Sci. Rev. 2021, 217, 103603.
  7. Shang, H.; Jia, L.; Menenti, M. Analyzing the Inundation Pattern of the Poyang Lake Floodplain by Passive Microwave Data. J. Hydrometeorol. 2015, 16, 652–667.
  8. Taleghani, M.; Sailor, D.J.; Tenpierik, M.; van den Dobbelsteen, A. Thermal Assessment of Heat Mitigation Strategies: The Case of Portland State University, Oregon, USA. Build. Environ. 2014, 73, 138–150.
  9. Sayad, B.; Alkama, D.; Ahmad, H.; Baili, J.; Aljahdaly, N.H.; Menni, Y. Nature-Based Solutions to Improve the Summer Thermal Comfort Outdoors. Case Stud. Therm. Eng. 2021, 28, 101399.
  10. Chen, V.; Bonilla Brenes, J.R.; Chapa, F.; Hack, J. Development and Modelling of Realistic Retrofitted Nature-Based Solution Scenarios to Reduce Flood Occurrence at the Catchment Scale. Ambio 2021, 50, 1462–1476.
  11. Mosca, F.; Dotti Sani, G.M.; Giachetta, A.; Perini, K. Nature-Based Solutions: Thermal Comfort Improvement and Psychological Wellbeing, a Case Study in Genoa, Italy. Sustainability 2021, 13, 11638.
  12. Tillie, N.; van der Heijden, R. Advancing Urban Ecosystem Governance in Rotterdam: From Experimenting and Evidence Gathering to New Ways for Integrated Planning. Environ. Sci. Policy 2016, 62, 139–144.
  13. Bates, A.J.; Mackay, R.; Greswell, R.B.; Sadler, J.P. SWITCH in Birmingham, UK: Experimental Investigation of the Ecological and Hydrological Performance of Extensive Green Roofs. Rev. Environ. Sci. Bio/Technol. 2009, 8, 295–300.
  14. Collentine, D.; Futter, M.N. Realising the Potential of Natural Water Retention Measures in Catchment Flood Management: Trade-offs and Matching Interests. J. Flood Risk Manag. 2018, 11, 76–84.
  15. Gari, S.R.; Newton, A.; Icely, J.D. A Review of the Application and Evolution of the DPSIR Framework with an Emphasis on Coastal Social-Ecological Systems. Ocean Coast. Manag. 2015, 103, 63–77.
  16. Menz, M.H.M.; Dixon, K.W.; Hobbs, R.J. Hurdles and Opportunities for Landscape-Scale Restoration. Science 2013, 339, 526–527.
  17. Svarstad, H.; Petersen, L.K.; Rothman, D.; Siepel, H.; Wätzold, F. Discursive Biases of the Environmental Research Framework DPSIR. Land Use Policy 2008, 25, 116–125.
  18. Tscherning, K.; Helming, K.; Krippner, B.; Sieber, S.; y Paloma, S.G. Does Research Applying the DPSIR Framework Support Decision Making? Land Use Policy 2012, 29, 102–110.
  19. Connop, S.; Vandergert, P.; Eisenberg, B.; Collier, M.J.; Nash, C.; Clough, J.; Newport, D. Renaturing Cities Using a Regionally-Focused Biodiversity-Led Multifunctional Benefits Approach to Urban Green Infrastructure. Environ. Sci. Policy 2016, 62, 99–111.
  20. Elwy, I.; Ibrahim, Y.; Fahmy, M.; Mahdy, M. Outdoor Microclimatic Validation for Hybrid Simulation Workflow in Hot Arid Climates against ENVI-Met and Field Measurements. Energy Procedia 2018, 153, 29–34.
  21. Perini, K.; Chokhachian, A.; Dong, S.; Auer, T. Modeling and Simulating Urban Outdoor Comfort: Coupling ENVI-Met and TRNSYS by Grasshopper. Energy Build. 2017, 152, 373–384.
  22. Su, W.; Zhang, L.; Chang, Q. Nature-Based Solutions for Urban Heat Mitigation in Historical and Cultural Block: The Case of Beijing Old City. Build. Environ. 2022, 225, 109600.
  23. Joyce, J.; Chang, N.-B.; Harji, R.; Ruppert, T.; Imen, S. Developing a Multi-Scale Modeling System for Resilience Assessment of Green-Grey Drainage Infrastructures under Climate Change and Sea Level Rise Impact. Environ. Model. Softw. 2017, 90, 1–26.
  24. Šećerov, I.; Savić, S.; Milošević, D.; Marković, V.; Bajšanski, I. Development of an automated urban climate monitoring system in Novi Sad (Serbia). Geogr. Pannonica 2015, 19, 174–183.
  25. Šećerov, I.B.; Savić, S.M.; Milošević, D.D.; Arsenović, D.M.; Dolinaj, D.M.; Popov, S.B. Progressing urban climate research using a high-density monitoring network system. Environ. Monit. Assess. 2019, 191, 89.
  26. Caluwaerts, S.; Hamdi, R.; Top, S.; Lauwaet, D.; Berckmans, J.; Degrauwe, D.; Dejonghe, H.; De Ridder, K.; De Troch, R.; Duchêne, F.; et al. The urban climate of Ghent, Belgium: A case study combining a high-accuracy monitoring network with numerical simulations. Urban Clim. 2020, 31, 100565.
  27. Lelovics, E.; Unger, J.; Gál, T.; Gál, C.V. Design of an urban monitoring network based on Local Climate Zone mapping and temperature pattern modelling. Clim. Res. 2014, 60, 51–62.
  28. Cecilia, A.; Casasanta, G.; Petenko, I.; Conidi, A.; Argentini, S. Measuring the urban heat island of Rome through a dense weather station network and remote sensing imperviousness data. Urban Clim. 2023, 47, 101355.
  29. Wang, K.; Jiang, S.; Wang, J.; Zhou, C.; Wang, X.; Lee, X. Comparing the diurnal and seasonal variabilities of atmospheric and surface urban heat islands based on the Beijing urban meteorological network. J. Geophys. Res. Atmos. 2017, 122, 2131–2154.
  30. Anderson, V.; Gough, W.A.; Zgela, M.; Milosevic, D.; Dunjic, J. Lowering the Temperature to Increase Heat Equity: A Multi-Scale Evaluation of Nature-Based Solutions in Toronto, Ontario, Canada. Atmosphere 2022, 13, 1027.
  31. Anderson, V.; Gough, W.A. Nature-Based Cooling Potential: A Multi-Type Green Infrastructure Evaluation in Toronto, Ontario, Canada. Int. J. Biometeorol. 2022, 66, 397–410.
  32. Middel, A.; Krayenhoff, E.S. Micrometeorological determinants of pedestrian thermal exposure during record-breaking heat in Tempe, Arizona: Introducing the MaRTy observational platform. Sci. Total Environ. 2019, 687, 137–151.
  33. Kulkarni, K.K.; Schneider, F.A.; Gowda, T.; Jayasuriya, S.; Middel, A. MaRTiny—A Low-Cost Biometeorological Sensing Device With Embedded Computer Vision for Urban Climate Research. Front. Environ. Sci. 2022, 10, 550.
  34. Milošević, D.; Middel, A.; Savić, S.; Dunjić, J.; Lau, K.; Stojsavljević, R. Mask wearing behavior in hot urban spaces of Novi Sad during the COVID-19 pandemic. Sci. Total Environ. 2022, 815, 152782.
  35. Milošević, D.; Trbić, G.; Savić, S.; Popov, T.; Ivanišević, M.; Marković, M.; Ostojić, M.; Dunjić, J.; Fekete, R.; Garić, B. Biometeorological conditions during hot summer days in diverse urban environments of Banja Luka (Bosnia and Herzegovina). Geogr. Pannonica 2022, 26, 29–45.
  36. Majidi, A.N.; Vojinovic, Z.; Alves, A.; Weesakul, S.; Sanchez, A.; Boogaard, F.; Kluck, J. Planning nature-based solutions for urban flood reduction and thermal comfort enhancement. Sustainability 2019, 11, 6361.
  37. Lehnert, M.; Tokar, V.; Jurek, M.; Geletič, J. Summer thermal comfort in Czech cities: Measured effects of blue and green features in city centres. Int. J. Biometeorol. 2021, 65, 1277–1289.
  38. Lehnert, M.; Brabec, M.; Jurek, M.; Tokar, V.; Geletič, J. The role of blue and green infrastructure in thermal sensation in public urban areas: A case study of summer days in four Czech cities. Sustain. Cities Soc. 2021, 66, 102683.
  39. Session, I.V.; Efficiencies, R.-U. Achieving the Sustainable Development Goals in North and Central Asia. In Proceedings of the 2016 SPECA Economic Forum “Enhanced Implementation of SDGs through Cooperation”, Ganja, Azerbaijan, 2–23 November 2016; UN/Economic and Social Commission for Asia and the Pacific: Bangkok, Thailand, 2017. ISBN 9789211207460.
  40. Anderson, V.; Leung, A.; Mehdipoor, H.; Jänicke, B.; Milosevic, D.; Oliveira, A.; Manavvi, S.; Kabano, P.; Dzyuban, Y.; Aguilar, R.; et al. Technological Opportunities for Sensing of the Health Effects of Weather and Climate Change: A State-of-the-Art-Review. Int. J. Biometeorol. 2021, 65, 779–803.
  41. Çalışkan, H.K. Technological Change and Economic Growth. Procedia-Soc. Behav. Sci. 2015, 195, 649–654.
  42. Steenhuis, H.J.; De Bruijn, E.J. Technology and Economic Development: A Literature Review. Int. J. Innov. Technol. Manag. 2012, 9, 1–11.
  43. Fomunyam, K.G. Theorising Machine Learning as an Alternative Pathway for Higher Education in Africa. Int. J. Educ. Pract. 2020, 8, 268–277.
  44. Nowak, D.J. Institutionalizing urban forestry as a “biotechnology” to improve environmental quality. Urban For. Urban Green. 2006, 5, 93–100.
  45. Nowak, D.J.; Crane, D.E.; Stevens, J.C. Air pollution removal by urban trees and shrubs in the United States. Urban For. Urban Green. 2006, 4, 115–123.
  46. Coutts, C.; Hahn, M. Green Infrastructure, Ecosystem Services, and Human Health. Int. J. Environ. Res. Public Health 2015, 12, 9768–9798.
  47. Anderson, V.; Gough, W. Evaluating the Potential of Nature-Based Solutions to Reduce Ozone, Nitrogen Dioxide, and Carbon Dioxide through a Multi-Type Green Infrastructure Study in Ontario, Canada. City Environ. Interact. 2020, 6, 100043.
  48. Baik, J.-J.; Kwak, K.-H.; Park, S.-B.; Ryu, Y.-H. Effects of building roof greening on air quality in street canyons. Atmos. Environ. 2012, 61, 48–55.
  49. Vienneau, D.; de Hoogh, K.; Faeh, D.; Kaufmann, M.; Wunderli, J.M.; Röösli, M.; SNC Study Group. More than clean air and tranquillity: Residential green is independently associated with decreasing mortality. Environ. Int. 2017, 108, 176–184.
  50. Crouse, D.L.; Pinault, L.; Balram, A.; Hystad, P.; Peters, P.A.; Chen, H.; van Donkelaar, A.; Martin, R.V.; Ménard, R.; Robichaud, A.; et al. Urban greenness and mortality in Canada’s largest cities: A national cohort study. Lancet Planet. Health 2017, 1, e289–e297.
  51. James, P.; Hart, J.E.; Banay, R.F.; Laden, F. Exposure to Greenness and Mortality in a Nationwide Prospective Cohort Study of Women. Environ. Health Perspect. 2016, 124, 1344–1352.
  52. Ulrich, R.S. View through a window may influence recovery from surgery. Science 1984, 224, 420–421.
  53. Villeneuve, P.J.; Jerrett, M.; Su, J.G.; Burnett, R.T.; Chen, H.; Wheeler, A.J.; Goldberg, M.S. A cohort study relating urban green space with mortality in Ontario, Canada. Environ. Res. 2012, 115, 51–58.
  54. Lee, J.; Tsunetsugu, Y.; Takayama, N.; Park, B.-J.; Li, Q.; Song, C.; Komatsu, M.; Ikei, H.; Tyrväinen, L.; Kagawa, T.; et al. Influence of Forest Therapy on Cardiovascular Relaxation in Young Adults. Evid. Based Complement. Altern. Med. 2014, 2014, 834360.
  55. Song, C.; Ikei, H.; Miyazaki, Y. Physiological Effects of Nature Therapy: A Review of the Research in Japan. Int. J. Environ. Res. Public Health 2016, 13, 781.
  56. Jo, H.; Song, C.; Miyazaki, Y. Physiological Benefits of Viewing Nature: A Systematic Review of Indoor Experiments. Int. J. Environ. Res. Public Health. 2019, 16, 4739.
  57. Defries, R.S.; Foley, J.; Asner, G. Land-use choices: Balancing human needs and ecosystem function. Front. Ecol. Environ. 2004, 2, 249–257.
  58. Goldberg, T.L.; Gillespie, T.R.; Rwego, I.B.; Estoff, E.L.; Chapman, C.A. Forest Fragmentation as Cause of Bacterial Transmission among Nonhuman Primates, Humans, and Livestock, Uganda. Emerg. Infect. Dis. 2008, 14, 1375–1382.
  59. Ostfeld, R.S.; Keesing, F.; Eviner, V. Infectious Disease Ecology: Effects of Ecosystems on Disease and of Disease on Ecosystems; Princeton University Press: Princeton, NJ, USA, 2008.
  60. Gottdenker, N.L.; Streicker, D.; Faust, C.L.; Carroll, C.R. Anthropogenic Land Use Change and Infectious Diseases: A Review of the Evidence. EcoHealth 2014, 11, 619–632.
  61. Enanga, E.M.; Shivoga, W.A.; Maina-Gichaba, C.; Creed, I.F. Observing Changes in Riparian Buffer Strip Soil Properties Related to Land Use Activities in the River Njoro Watershed, Kenya. Water Air Soil Pollut. 2011, 218, 587–601.
  62. Wotherspoon, A.; Thevathasan, N.V.; Gordon, A.M.; Voroney, R.P. Carbon sequestration potential of five tree species in a 25-year-old temperate tree-based intercropping system in southern Ontario, Canada. Agrofor. Syst. 2014, 88, 631–643.
  63. Thevathasan, N.V.; Gordon, A.M. Ecology of tree intercropping systems in the North temperate region: Experiences from southern Ontario, Canada. New Vistas Agrofor. 2004, 1, 257–268.
  64. Abd-ur-Rehman, H.M.; Deletic, A.; Zhang, K.; Prodanovic, V. The Comparative Performance of Lightweight Green Wall Media for the Removal of Xenobiotic Organic Compounds from Domestic Greywater. Water Res. 2022, 221, 118774.
  65. Seddon, N.; Chausson, A.; Berry, P.; Girardin, C.A.J.; Smith, A.; Turner, B. Understanding the Value and Limits of Nature-Based Solutions to Climate Change and Other Global Challenges. Philos. Trans. R. Soc. B Biol. Sci. 2020, 375, 20190120.
  66. Davis, M.; Abhold, K.; Mederake, L.; Knoblauch, D. Nature-Based Solutions in European and National Policy Frameworks; Deliverable 1.5. NATURVATION; European Commission: Brussels, Belgium, 2020.
  67. Nature-Based Solutions for Urban Climate Resilience in South Asia: Cases from Bangladesh, India and Nepal (2022a) Relief Web. Available online: (accessed on 2 June 2023).
  68. City of Toronto. City of Toronto Green Roof By-Law. 2023. Available online: (accessed on 15 March 2023).
  69. Model Building Bye-Laws; Town and Country Planning Organization, Ministry of Urban Development, Government of India: New Delhi, India, 2016; pp. 111–119.
  70. Raut, S.; Lamsoge, B.R.; Labhane, N.M. Rainwater Harvesting for Metro Rail Projects in India—Scope for Efficiency Improvement. J. Geol. Soc. India 2022, 98, 937–946.
  71. Government of Canada. Healthy Environment and a Healthy Economy. 2021. Available online: (accessed on 15 December 2022).
  72. Revi, A.; Satterthwaite, D.E.; Aragón-Durand, F.; Corfee-Morlot, J.; Kiunsi, R.B.R.; Pelling, M.; Roberts, D.C.; Solecki, W. Urban areas. In Climate Change 2014: Impacts, Adaptation, and Vulnerability. Part A: Global and Sectoral Aspects. Contribution of Working Group II to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change; Field, C.B., Barros, V.R., Dokken, D.J., Mach, K.J., Mastrandrea, M.D., Bilir, T.E., Chatterjee, M., Ebi, K.L., Estrada, Y.O., Genova, R.C., et al., Eds.; Cambridge University Press: Cambridge, UK; New York, NY, USA, 2014; pp. 535–612.
  73. URBES. Green Infrastructure, a Wealth for Cities. Fact Sheet. 2014. Available online: (accessed on 14 December 2022).
  74. European Commission. Green Infrastructure (GI)—Enhancing Europe’s Natural Capital. 2013. Available online: (accessed on 14 December 2022).
  75. U.S. Environmental Protection Agency. What Is Green Infrastructure? Available online: (accessed on 1 December 2022).
  76. Pucher, B.; Zluwa, I.; Spörl, P.; Pitha, U.; Langergraber, G. Evaluation of the multifunctionality of a vertical greening system using different irrigation strategies on cooling, plant development and greywater use. Sci. Total Environ. 2022, 849, 157842.
  77. Katsou, E.; Nika, C.E.; Buehler, D.; Marić, B.; Megyesi, B.; Mino, E.; Babí Almenar, J.; Bas, B.; Bećirović, D.; Bokal, S.; et al. Transformation tools enabling the implementation of nature-based solutions for creating a resourceful circular city. Blue-Green Syst. 2020, 2, 188–213.
  78. EC. Evaluating the Impact of Nature-Based Solutions: A Handbook for Practitioners; European Commission: Brussels, Belgium, 2021.
  79. EC. Evaluating the Impact of Nature-Based Solutions: Appendix of Methods; European Commission: Brussels, Belgium, 2021.
Subjects: Remote Sensing
Contributors MDPI registered users' name will be linked to their SciProfiles pages. To register with us, please refer to : , ,
View Times: 158
Revisions: 2 times (View History)
Update Date: 17 Aug 2023
Video Production Service