Riparian canopy expansion in an urban landscape: Multiple drivers of vegetation change along headwater streams near Sacramento, California

Solins, Joanna P.; Thorne, James H.; Cadenasso, Mary L.

doi:10.1016/j.landurbplan.2017.12.005

Cited by 20 publications

(19 citation statements)

References 54 publications

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“…This study is an initial effort to understand the impact of COVID-19 mitigation efforts on air pollution and several related factors still have not been quantitatively considered. For example, the patterns of air pollution could also be influenced by climate and geographical changes, such as global warming ( Williams et al, 2019 ) and vegetation ( Solins et al, 2018 ). Although these effects are partially accounted for by comparing with previous years and observing anomalies, they cannot be entirely eliminated from the results, leading to complex interaction of influential variables in some regions.…”

Section: Discussionmentioning

confidence: 99%

Spatiotemporal impacts of COVID-19 on air pollution in California, USA

Liu

Harris

Chiu

et al. 2021

Science of The Total Environment

100

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Various recent studies have shown that societal efforts to mitigate (e.g. “lockdown”) the outbreak of the 2019 coronavirus disease (COVID-19) caused non-negligible impacts on the environment, especially air quality. To examine if interventional policies due to COVID-19 have had a similar impact in the US state of California, this paper investigates the spatiotemporal patterns and changes in air pollution before, during and after the lockdown of the state, comparing the air quality measurements in 2020 with historical averages from 2015 to 2019. Through time series analysis, a sudden drop and uptick of air pollution are found around the dates when shutdown and reopening were ordered, respectively. The spatial patterns of nitrogen dioxide (NO 2 ) tropospheric vertical column density (TVCD) show a decreasing trend over the locations of major powerplants and an increasing trend over residential areas near interactions of national highways. Ground-based observations around California show a 38%, 49%, and 31% drop in the concentration of NO 2 , carbon monoxide (CO) and particulate matter 2.5 (PM 2.5 ) during the lockdown (March 19–May 7) compared to before (January 26–March 18) in 2020. These are 16%, 25% and 19% sharper than the means of the previous five years in the same periods, respectively. Our study offers evidence of the environmental impact introduced by COVID-19, and insight into related economic influences.

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Section: Discussionmentioning

confidence: 99%

Spatiotemporal impacts of COVID-19 on air pollution in California, USA

Liu

Harris

Chiu

et al. 2021

Science of The Total Environment

100

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“…Vegetation changes can be attributed to climate variations and human activities [33]. Given the two-step analytical processes involved in LSAA-TC, it is reasonable to conclude that the patterns shown in the STOs denote the impact on urban greenness mainly from human activities.…”

Section: Possible Explanations For Stomentioning

confidence: 99%

“…The changes in urban greenness can generally be driven by climate fluctuations and human activities [33]. Climate changes (e.g., in precipitation or temperature) usually incur variations of vegetation cover over a vast area, known as large-scale impact.…”

Section: Introductionmentioning

confidence: 99%

Mapping the Changes in Urban Greenness Based on Localized Spatial Association Analysis under Temporal Context Using MODIS Data

Sha

Ali

Wang

et al. 2018

IJGI

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Vegetation plays an irreplaceable role for urban ecosystem services. Urban greenness represents all vegetation cover in and around cities. Understanding spatiotemporal patterns of the changes in urban greenness (CUG) provides fundamental clues for urban planning. The impact on CUG can be roughly categorized as being climate-induced and human-induced. Methods for mapping human-induced CUG (H-CUG) are rare. In this paper, a new framework, known as Localized Spatial Association Analysis under Temporal Context (LSAA-TC), was proposed to explore H-CUG. Localized spatial association analysis (LSAA) was performed first to extract local spatial outliers (LSOs), or locations that differ significantly in urban greenness from those located in the neighborhood. LSOs were then analyzed under the temporal context to map their intertemporal variations known as spatiotemporal outliers. We applied LSAA-TC to mapping H-CUG in the Wuhan Metropolitan Area, China during 2000–2015 using the vegetation index from Moderate-resolution Imaging Spectroradiometer (MODIS) 13Q1 as the proxy for urban greenness. The computed H-CUG demonstrated apparent spatiotemporal patterns. The result is consistent with the fact that the traditional downtown area presents the lowest H-CUG, while it is found that the peripheral area in the circular belt within 14–20 km from the urban center demonstrates the most significant H-CUG. We conclude that LSAA-TC can be a widely applicable framework to understand H-CUG patterns and is a promising tool for informative urban planning.

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“…active channel width or sinuosity, gravel bar area (Gilvear et al, 2000;Ollero, 2010;Michalková et al, 2011;Rollet et al, 2013;Toone et al, 2014;Arnaud et al, 2015;Lallias-Tacon et al, 2017;Scorpio et al, 2018) and landscape unit characteristics (e.g. Dufour et al, 2015;Solins et al, 2018). Image georeferencing and vectorization of river features from historical datasets are still mostly manual and time-consuming tasks which require real expertise.…”

Section: Reach-scale Changesmentioning

confidence: 99%

Remotely sensed rivers in the Anthropocene: state of the art and prospects

Piégay

Arnaud

Belletti

et al. 2020

Earth Surf Processes Landf

168

103

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The rivers of the world are undergoing accelerated change in the Anthropocene, and need to be managed at much broader spatial and temporal scales than before. Fluvial remote sensing now offers a technical and methodological framework that can be deployed to monitor the processes at work and to assess the trajectories of rivers in the Anthropocene. In this paper, we review research investigating past, present and future fluvial corridor conditions and processes using remote sensing and we consider emerging challenges facing fluvial and riparian research. We introduce a suite of remote sensing methods designed to diagnose river changes at reach to regional scales. We then focus on identification of channel patterns and acting processes from satellite, airborne or ground acquisitions. These techniques range from grain scales to landform scales, and from real time scales to inter-annual scales. We discuss how remote sensing data can now be coupled to catchment scale models that simulate sediment transfer within connected river networks. We also consider future opportunities in terms of datasets and other resources which are likely to impact river management and monitoring at the global scale. We conclude with a summary of challenges and prospects for remotely sensed rivers in the Anthropocene.

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Riparian canopy expansion in an urban landscape: Multiple drivers of vegetation change along headwater streams near Sacramento, California

Cited by 20 publications

References 54 publications

Spatiotemporal impacts of COVID-19 on air pollution in California, USA

Spatiotemporal impacts of COVID-19 on air pollution in California, USA

Mapping the Changes in Urban Greenness Based on Localized Spatial Association Analysis under Temporal Context Using MODIS Data

Remotely sensed rivers in the Anthropocene: state of the art and prospects

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