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Hyperspectral biomonitoring: air quality and the city (HYPERCITY)

Onderzoeksproject SR/00/303 (Onderzoeksactie SR)


Personen :

  • Dr.  SAMSON Roeland - Universiteit Gent (UGent)
    Coördinator van het project
    Betoelaagde Belgische partner
    Duur: 1/12/2014-30/11/2018
  • Dr.  VALCKE Roland - Universiteit Hasselt (UHASSELT)
    Betoelaagde Belgische partner
    Duur: 1/12/2014-30/11/2018
  • Prof. dr.  VEROUSTRAETE Frank - Vlaamse Instelling voor Technologisch Onderzoek (VITO)
    Betoelaagde Belgische partner
    Duur: 1/12/2014-30/11/2018
  • Dr.  MORENO José - University of Valencia (UNI-VAL)
    Betoelaagde buitenlandse partner
    Duur: 1/12/2014-30/11/2018

Beschrijving :

CONTEXT AND OBJECTIVES

A significant proportion of Europe’s population lives in urban areas where exceedances of air quality standards occur and pose serious health risks. A major contribution to the urban air pollution is provided by burning of fossil fuels in road transport, with the emission of particulate matter (PM). PM pollution is causing tremendous costs to society due to a significant increase in health problems and morbidity. To be able to make reliable risk assessments and take adequate urban management decisions, it is therefore important to get a detailed insight in the spatial distribution of air pollution.
As conventional air pollution monitoring stations only provide coarse-scale information on exposure to pollutants, a growing interest has risen in monitoring and modelling urban air pollution in ways to obtain information with a high spatial resolution. A possibilities for high spatial resolution monitoring is biomonitoring of urban vegetation.
During the last three decades, remote sensing techniques are frequently applied within the context of environmental monitoring. However, many techniques needs further development, or were never tested for their biomonitoring potential. The dorsiventral leaf asymmetry (the difference between the upper and lower leaf side), and the resulting differences in hyperspectral leaf reflectance, is hardly considered in any (remote sensing) biomonitoring approach. Therefore, the overall objective of this research proposal is to develop, test and validate a plant-based passive biomonitoring methodology based on hyperspectral observations and considering leaf asymmetry. In this project we will make use of a dual approach, i.e.: (1) large solitary trees growing in various contrasting urban environments in terms of air pollution used for scaling up exercises from leaf to canopy, and (2) trees spatially distributed over the entire urban area for mapping purposes.
This overall objective is split up into the following objectives:
(i) Map the urban environmental air quality at high spatial resolution based on passive NO2 sensors and by biomagnetic leaf monitoring;
(ii) Scale up hyperspectral leaf reflectance to canopy level reflectance for trees growing in sites with contrasting air quality, taking leaf asymmetry into account and based on a modelling approach;
(iii) Map urban air quality based on physiological and reflectance based leaf characteristics and validate these maps against the maps obtained in (i) and simulated air pollution maps;
(iv) Develop a hyperspectral Normalised Difference Asymmetry Index (NDAI) at leaf level for different species growing at various levels of air quality as assessed in (i);
(v) Further develop and optimise the possibilities and applications of chlorophyll content mapping based on advanced machine learning regression algorithms that deal efficiently with hyperspectral data, and based on intensive physiological leaf measurements and additional validation data obtained in (i) and (iv); and (vi) Formulate a protocol to estimate urban air quality based on high spatial resolution leaf/canopy data and/or airborne measurements.

The project will be deployed in two urban environments which mainly differ in climatic conditions. The study sites selected are Antwerp (Belgium) and Valencia (Spain).

METHODOLOGY

To reach the objectives defined in the former section an experimental set-up considering large, individual trees for up-scaling from leaf to canopy level, and spatially well distributed trees for mapping of leaf physiological and reflectance parameters to correlate with spatial maps of urban air pollution, will be developed as described below. The project will be structured along several focussed and well-organised work packages (WPs).

WP1. Selection of study areas, tree species and sampling points
Study areas
The research will be conducted in two study areas. The first study area is the city of Antwerp (Belgium).
This area is selected because this is the largest Flemish city comprising diverse land use classes with various, contrasting air pollution sources as the Ring road through the city and a major sea harbour with intensive industrial activities. Moreover, the research group of the promoter has ample biomonitoring experience in this city. The second city is the city of Valencia (Spain) which also includes a wide variety of distinct land use classes. The project consortium has already experience in this city, which is the home city of the foreign partner (University of Valencia, UV). Valencia is located in a Mediterranean climate whereas Antwerp is located in a mild sea climate. The study area will be split up in about different land use classes. The actual status of air pollution will be checked in these land use classes (see also WP2).
Species selection
Because a prerequisite for biomonitoring based on airborne or spaceborne remote sensing needs large vegetation units, this project will deal with urban trees. As mentioned before several tree species will be selected in line with some major selection criteria. At least one species, i.e. Platanus x. acerifolia, will be selected in common at both test sites to check the robustness of the methodology.
Sampling points
For the mapping approach sampling points will be selected using a partially random partially grid system.
Species selection (see above) needs also to consider their spatial distribution over the study area. As one species seldom covers the entire study area, the approach based on co-located species will be used.
About 150 sampling points will be selected to cover the entire urban study area. For the up-scaling approach large (large crown diameter), solitary trees will be selected of two species with a contrasting dorsiventral leaf asymmetry (i.e. a distinct visual difference between both leaf sides). For each of both selected species two test sites will be selected, i.e. one with a low and one with a high urban air pollution load.

WP2. Mapping the spatial variation in urban air quality
The spatial variation in urban air quality will be mapped as necessary background data for the selected sample points (see WP1), and also to be able to interpret the measured physiological and reflectance data in function of urban air quality. Air quality will be assessed in two ways which showed to be important in previous research projects. First the atmospheric NO2 concentration will be measured as indicator of traffic intensity. Secondly, urban air pollution and more specifically traffic generated particulate matter will be assessed by biomagnetic leaf monitoring (SIRM: Saturated Isothermal Remanent Magnetisation). This methodology proved already relevant in temperate, Mediterranean and tropical climates. These points measurements will be geostatistically scaled up to the level of the entire city using simple kriging with varying local means. For the up-scaling approach leaf biomagnetic signals will be assessed at different heights and azimuths (wind directions) for the selected trees. As such the exposure at the considered heights and directions can be assessed in detail.

WP3. Up-scaling hyperspectral leaf reflectance to canopy level
Measurement campaigns
This WP focusses on large solitary trees of two different species with a contrasting dorsiventral leaf asymmetry; growing at a site with moderate and high urban air pollution (see also WP1 and WP2). For each selected tree hyperspectral leaf reflectance will be measured in vivo at three different heights and at each height at four perpendicular wind directions at the out- and inside of the canopy. Moreover, for each of these positions leaf reflectance at both leaf sides and leaf SIRM (see WP2) will be measured, besides chlorophyll fluorescence and absolute chlorophyll content. For each sampled position also specific leaf area (SLA, leaf area over leaf dry weight) will be determined and leaf cross-sections will be made in order to get a detailed insight of the intracanopy variation in leaf anatomy, and its dorsiventral asymmetry. Hyperspectral reflectance will also be assessed at canopy level where hyperspectral reflectance will be measured at various heights, azimuths and elevation angles with the same spectroradiometer as used for the leaf level measurements. Measurements will range between nadir measurements on top of canopy to horizontal measurements at the bottom of the canopy.
Measurements will be conducted at four different perpendicular wind directions at high solar elevations around the summer solstice. Previous research indicated that leaf SIRM at the beginning of summer (around summer solstice) already clearly differentiated between moderate and heavily polluted sites.
The sampling positions will be reached with a boom lift. A EUFAR campaign (APEX/CASI) will be organized to obtain the required airborne hyperspectral data.
Up-scaling strategy
Canopy level and airborne spectral measurements will be simulated into the ARTMO toolbox.
Simulations and matching with real observations allows untangling the reflectance into its state variables, and assessing the role each variable play in the spectral signal. The ARTMO toolbox holds a suite of radiative transfer models at leaf and canopy level with low to high complexity (see also: http://ipl.uv.es/artmo/). For instance, the reflectance of both homogeneous grasslands, as well more complicated forest scenes can be simulated in a semi-automatic fashion. Both reflectance as well as associated chlorophyll-induced fluorescence can be simulated and studied.

WP4. Mapping urban air pollution based on physiological and reflectance based leaf characteristics
Chlorophyll fluorescence is known as a highly sensitive stress indicator. Therefore, it will be measured in vivo at both leaf sides for each tree selected for the spatial mapping (see WP1). Measurements will be conducted during late summer as to maximize the duration of the exposure and maximize the difference between sampling sites. In vivo chlorophyll fluorescence measurements will be performed using three different approaches: (1) the fast fluorescence transient will be measured using a portable ‘Plant Efficiency Analyser’ system (Hansatech), (2) the fluorescence photochemical and non-photochemical quenching mechanisms will be measured and analysed using a portable ‘pulse amplitude modulated fluorometer’ (Walz) and (3) the spatial two-dimensional fluorescence of leaves will be imaged and processed using the Fluorescence Imaging System. Hyperspectral leaf fluorescence will be measured as in WP3. In order to interpret the obtained results in terms of air quality, data will be correlated with the air quality indicators obtained in WP2. Moreover, the obtained physiological and reflectance parameters will be geostatistically mapped (see also WP2), and compared with the available air pollution maps from the urban environmental services and with the maps produced in WP2. This comparison might validate the available air quality maps/indicators or be the starting point for a critical reflection on the meaning of the physiological/reflectance data, the maps and the representativeness of air pollution indicators.

WP5. Development and optimization of a hyperspectral Normalised Difference Asymmetry Index (NDAI)
Based on the data (see WP4) obtained at the defined sampling points (WP1), the NDAI originally based on multi-spectral leaf reflectance data, will be developed for chlorophyll fluorescence and hyperspectral reflectance measurements. The NDAI(s) will be critically compared against the available air pollution maps used by the urban environmental services (e.g. of PM10, NO2).

WP6. Developing and validating of optimized mapping approach for urban chlorophyll mapping as indicator of air pollution
Within ARTMO, recently various retrieval toolboxes have been developed that enables optimized mapping of urban chlorophyll content. These retrieval toolboxes are organized according to the nature of their algorithms: (1) parametric regression, such as the NAOC (Normalised Area Over reflectance Curve) approach [NAOC-based mapping earlier showed to work well for chlorophyll mapping in Valencia]; (2) non-parametric regression; and (3) inversion of radiative transfer models. More info on the methodologies can be found in Form 6. In a first stage an optimized mapping approach will be assessed and validated by using the toolboxes and collected data [field and airborne (WP3)]. Chlorophyll content will be sampled in Valencia on a broad variety of urban (tree) species in relation to their growing conditions (e.g. degree of air pollution, see WP2) and canopy architecture. In a second stage a broad range of species with various leaf characteristics will be sampled for their chlorophyll content in contrasting growing conditions at the city of Antwerp to test whether the optimized mapping approach is portable in a broad climatic range and for many species with contrasting leaf characteristics. The calibration curves obtained for both sites (Valencia and Antwerp) as well the associated uncertainties will be tested at the other site (cross-calibration), to ascertain the general validity of the approach.

WP7. Description and optimisation of a sampling methodology for the estimation of urban air quality
Meetings will be organized with responsible policy makers of both test cities and the authorities responsible for environmental monitoring at the local, regional or national level, as they can help in the interpretation of the obtained results (i.e. the obtained maps). Based on these meetings and the former WPs a sampling methodology for each test site will be developed.

EXPECTED SCIENTIFIC RESULTS

The overall outcome of the project will be a (primer of a) methodology for the monitoring of urban habitat quality and urban air quality based on airborne hyperspectral and chlorophyll fluorescence measurements.
The scientific outcome of the project will be a thorough knowledge of the correlation between tree characteristics at the sub-leaf, leaf and canopy level with air and soil pollution. Moreover, there will be a deep knowledge of the correlation between the characteristics measured at the different tree levels, and especially on the relevance and potential of airborne hyperspectral and chlorophyll fluorescence data.
Scientific publications:
The project is organised as such that WP2 – WP6 will lead to at least one, but often several peer reviewed publications in international journals.
Other scientific dissemination:
The outcome of this project will also be spread in the scientific community by active participation (posters and oral presentations) in relevant (inter)national workshops and symposia.

EXPECTED PRODUCTS AND SERVICES

A generic passive biomonitoring protocol for performing an inventory in urban environment will be delivered, including a motivated list of the most suitable parameters, sampling locations, species and sampling time as also the maps related to these parameters for the cities of Antwerp and Valencia.
Dissemination among policy makers:
As already mentioned in WP7, results will be discussed with the relevant policy makers and administration of both cities and environmental monitoring agencies for: (i) a better interpretation of the results, and (ii) a feedback on the needs of the administration and policy makers to come to a generic methodology that eventually can be used by these policy makers and agencies.
Final workshop:
At the end of the project a workshop will be organised for policy makers and scientists on biomonitoring of the urban air quality.


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