Biological-based and remote sensing techniques to link vegetative and reproductive development and assess pollen emission in Mediterranean grasses

Rojo, Jesús; Romero-Morte, Jorge; Lara, Beatriz; Quirós, E.; Richardson, Andrew D.; Pérez-Badía, Rosa

doi:10.1016/j.ecoinf.2022.101898

Cited by 11 publications

(3 citation statements)

References 59 publications

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“…In this context, since vegetation indices are influenced by many factors other than vegetation (e.g., soil moisture, atmospheric conditions, and shadows), MT PS data produced an improvement to capture changes in vegetation cover and reduced the impact of non-vegetation factors. Vegetation indices derived from the MT data are related to the biological behavior of the different species during the year, i.e., the phenological pattern associated with each species [73]. Similar to this research, MLP outperformed other ML classifiers using MT PS imagery [74], but with additional GLCM features, XGB performed the best.…”

Section: Most Suitable Classification Methodssupporting

confidence: 73%

Mapping of Allergenic Tree Species in Highly Urbanized Area Using PlanetScope Imagery—A Case Study of Zagreb, Croatia

Gašparović

Dobrinić

Pilaš

2023

Forests

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Mapping and identifying allergenic tree species in densely urbanized regions is vital for understanding their distribution and prevalence. However, accurately detecting individual allergenic tree species in urban green spaces remains challenging due to their smaller site and patchiness. To overcome these issues, PlanetScope (PS) satellite imagery offers significant benefits compared with moderate or high-resolution RS imagery due to its daily temporal resolution and 3 m spatial resolution. Therefore, the primary objectives of this research were to: assess the feasibility of mapping allergenic tree species in the highly urbanized area using high-resolution PS imagery; evaluate and compare the performance of the most important machine learning and feature selection methods for accurate detection of individual allergenic tree species. The research incorporated three classification scenarios based on ground truth data: The first scenario (CS1) used single-date PS imagery with vegetation indices (VI), while the second and third scenarios (CS2 and CS3) used multitemporal PS imagery with VI, and GLCM and VI, respectively. The study demonstrated the feasibility of using multitemporal eight-band PlanetScope imagery to detect allergenic tree species, with the XGB method outperforming others with an overall accuracy of 73.13% in CS3. However, the classification accuracy varied between the scenarios and species, revealing limitations including the inherent heterogeneity of urban green spaces. Future research should integrate high-resolution satellite imagery with aerial photography or LiDAR data along with deep learning methods. This approach has the potential to classify dominant tree species in highly complex urban environments with increased accuracy, which is essential for urban planning and public health.

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Section: Most Suitable Classification Methodssupporting

confidence: 73%

Mapping of Allergenic Tree Species in Highly Urbanized Area Using PlanetScope Imagery—A Case Study of Zagreb, Croatia

Gašparović

Dobrinić

Pilaš

2023

Forests

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“…Therefore, this work inevitably overestimated summer pollen emissions from deciduous broadleaf forests. Additionally, grass pollen emission rates reach the highest when the main vegetation type dominated by grass goes through the final stage of vegetation development in its biological aging period or equivalent stage (Rojo et al., 2022), suggesting that grass pollen emissions may be also overestimated in summer. Similarly, due to the limitations of the simplified scheme, pollen emission in the tropics covered by the model domain is higher than the true value, in which tree densities in tropical forests are too high for wind pollination (Dick et al., 2008; Harrison, 2005; Regal, 1977).…”

Section: Results and Analysismentioning

confidence: 99%

An Investigation on Potential Dispersal of Airborne Pollen Over China and Their Impact on Climate as Ice Nuclei Using RegCM‐Pollen

Song,

Wang,

et al. 2024

JGR Atmospheres

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Pollen can serve as an effective ice‐nuclei (IN), altering cloud microphysical and radiative properties, thus precipitation and cloud life cycles. Here, a nationwide pollen emission inventory with a horizontal resolution of 5 km was established based on a parameterization scheme of mass balance of pollen grain fluxes surrounding the plant crowns, and using satellite observational data sets (including leaf area index and fractional vegetation cover) as well as pollen emission rates. The potential emission is then implemented in RegCM‐pollen model which treated pollen as aerosol tracers. Besides, pollen‐IN parameterization schemes were incorporated in RegCM‐pollen to simulate the interactions between pollen and ice clouds. Investigations show that the mean annual pollen emission in China is 2.65 × 107 grains m−2 yr−1, mainly distributed in the south and northeast of China. The IN magnitude is mainly determined by a combination of temperature and pollen concentration. Notably, an increasing number concentration of pollen grains produces opposite effects in Southern China (SC) and Northern China (NC). The weakened upward motion and vertical transport of water vapor in NC made ice clouds hardly form, resulting in cloud forcing (CF) of +0.86 W/m2. In contrast, it generates a CF of −0.84 W/m2 in SC mainly owing to expanded cloud cover. The changes in shortwave radiative forcing is more significant compared to longwave radiative forcing in the two regions. At the surface, the net radiative forcing in NC is +0.74 W/m2, while it is a −0.51 W/m2 in SC. Among them, downward shortwave radiative forcing is approximately twice that of upward longwave radiative forcing in SC and 1.4 times in NC. Surface temperature shows rising over NC, ranging from 0.05 to 0.25 K. In SC, it is primarily decreasing by −0.12 to −0.03 K. The pollen‐IN effect also causes a decline of precipitation in NC (−0.17 mm/day) and a rise in SC (0.09 mm/day). Our results suggest that the pollen effect on ice clouds is complex, yet significant in understanding its impact on radiation and climate of the atmosphere.

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“…is an exception (Wozniak & Steiner, 2017) , with little knowledge of the mechanisms of their flowering phenology. We assumed that their flowering time is associated with the senescence phases of vegetative development, similar to other late-flowering species (Rojo et al, 2022) .…”

Section: Inferring Pollen Phenology On the City Levelmentioning

confidence: 99%

Predicting reproductive phenology of wind-pollinated trees via PlanetScope time series

Song,

Katz,

Zhu

et al. 2024

Preprint

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Airborne pollen triggers allergic reactions which result in public health consequences. A better understanding of flowering and pollen phenology could improve airborne pollen predictions and reduce pollen exposure. Data on the timing of flowering and pollen release are needed to improve models of airborne pollen concentrations, but existingin-situdata collection efforts are expensive and spatially sparse. Satellite-based estimates of plant phenology could potentially enable large-scale data collection, but it is difficult to detect the reproductive phenology of wind-pollinated flowers from space. Here, we infer the reproductive phenology of wind-pollinated plants usingPlanetScopetime series with a spatial resolution of 3 m and a daily revisit cycle, complemented byin-situflower and pollen observations, leveraging the correlation between vegetative and reproductive phenology. On the individual tree level, we extracted PlanetScope-derived green-up time and validated its correlation to flowering time using flower observations in a national-scale observatory network. Scaling up to the city level, we developed a novel approach to characterize pollen phenology from PlanetScope-derived vegetative phenology, by optimizing two tuning parameters: the threshold of green-up or green-down and the time lag between green-up/down and flowering. We applied this method to seven cities in the US and seven key wind-pollinated tree genera, calibrated by measurements of airborne pollen concentrations. Our method characterized pollen phenology accurately, not only in-sample (Spearman correlation: 0.751, nRMSE: 13.5%) but also out-of-sample (Spearman correlation: 0.691, nRMSE: 14.5%). Using the calibrated model, we further mapped the pollen phenology landscape within cities, showing intra-urban heterogeneity. Using high spatiotemporal resolution remote sensing, our novel approach enables us to infer the flowering and pollen phenology of wind-pollinated plant taxa on a large scale and a fine resolution, including areas with limited priorin-situflower and pollen observations. The use of PlanetScope time series therefore holds promise for developing process-based pollen models and targeted public health strategies to mitigate the impact of allergenic pollen exposure.

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Biological-based and remote sensing techniques to link vegetative and reproductive development and assess pollen emission in Mediterranean grasses

Cited by 11 publications

References 59 publications

Mapping of Allergenic Tree Species in Highly Urbanized Area Using PlanetScope Imagery—A Case Study of Zagreb, Croatia

Mapping of Allergenic Tree Species in Highly Urbanized Area Using PlanetScope Imagery—A Case Study of Zagreb, Croatia

An Investigation on Potential Dispersal of Airborne Pollen Over China and Their Impact on Climate as Ice Nuclei Using RegCM‐Pollen

Predicting reproductive phenology of wind-pollinated trees via PlanetScope time series

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