TROPOMI NO2 retrieval: December 2020 (v1.4) and April 2021 (v2.2) upgrades, and comparisons with OMI and ground-based remote sensing

2021 ◽  
Author(s):  
Jos van Geffen ◽  
Henk Eskes ◽  
Maarten Sneep ◽  
Gaia Pinardi ◽  
Tijl Verhoelst ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Power Plants ◽  
Remote Sensing Data ◽  
High Signal ◽  
Cloud Height ◽  
Industrial Complexes ◽  
Global Coverage ◽  
The Impact ◽  
Small Cloud ◽  
Level 2

<p>The Tropospheric Monitoring Instrument (TROPOMI) on the Sentinel-5 Precursor (S5P) satellite is a unique instrument, combining daily global coverage, very high signal-to-noise, a broad spectral range and very small pixels up to 3.5 x 5.5 km<sup>2</sup>. Retrievals are available for a large number of species, including NO<sub>2</sub>. Due to the very small pixels and daily revisit, TROPOMI provides detailed information on individual sources and source sectors like individual power plants, industrial complexes, cities and suburbs, highways, and even individual ships. The TROPOMI Level-2 NO<sub>2</sub> product is available from 30 April 2018 onwards.</p><p>Validation exercises of TROPOMI v1.2 & v1.3 data (2018-2020) with OMI and ground-based remote sensing observations have shown that TROPOMI's tropospheric NO<sub>2</sub> column are low by up to 50% over highly polluted areas compared to independent data. In contrast, the underlying slant columns of TROPOMI agree well with OMI and independent SAOZ observations. Differences between OMI and TROPOMI have been mainly attributed to the different cloud height retrieval, using the O<sub>2</sub>-O<sub>2</sub> versus O<sub>2</sub>-A bands respectively.</p><p>In our presentation we discuss recent improvements in the TROPOMI NO<sub>2</sub> retrieval and the impact these have on the tropospheric columns and on the comparisons with OMI and ground-based remote-sensing data.</p><p>Version v1.4, which became operational on 2 December 2020, entails a major improvement in the cloud height retrieval, based on a modification of the FRESCO-S cloud retrieval using the O<sub>2</sub>-A band observations. In particular the cloud height over scenes with a small cloud coverage have increased, resulting in larger tropospheric columns in the retrievals over polluted areas.</p><p>Version v2.2, to become operational in April/May 2021, includes similar cloud retrieval modifications. Furthermore, it provides a better treatment of saturation issues and transients, is using improved (ir)radiance measurements (level-1b v2 spectra) including degradation corrections, and includes a new albedo treatment.</p><p>The TROPOMI NO<sub>2</sub> retrievals are compared with OMI retrievals (from the QA4ECV product) and to ground-based observations with MAXDOAS and PANDORA instruments.</p>

scholarly journals Analysing the Impact of Climate Change on Hydrological Ecosystem Services in Laguna del Sauce (Uruguay) Using the SWAT Model and Remote Sensing Data

2021 ◽  
Vol 13 (10) ◽  
pp. 2014
Author(s):  
Celina Aznarez ◽  
Patricia Jimeno-Sáez ◽  
Adrián López-Ballesteros ◽  
Juan Pablo Pacheco ◽  
Javier Senent-Aparicio
Keyword(s):  
Climate Change ◽  
Remote Sensing ◽  
Ecosystem Services ◽  
Water Resources ◽  
Swat Model ◽  
Remote Sensing Data ◽  
Erosion Control ◽  
Sensing Data ◽  
Extreme Precipitation Events ◽  
The Impact

Assessing how climate change will affect hydrological ecosystem services (HES) provision is necessary for long-term planning and requires local comprehensive climate information. In this study, we used SWAT to evaluate the impacts on four HES, natural hazard protection, erosion control regulation and water supply and flow regulation for the Laguna del Sauce catchment in Uruguay. We used downscaled CMIP-5 global climate models for Representative Concentration Pathways (RCP) 2.6, 4.5 and 8.5 projections. We calibrated and validated our SWAT model for the periods 2005–2009 and 2010–2013 based on remote sensed ET data. Monthly NSE and R2 values for calibration and validation were 0.74, 0.64 and 0.79, 0.84, respectively. Our results suggest that climate change will likely negatively affect the water resources of the Laguna del Sauce catchment, especially in the RCP 8.5 scenario. In all RCP scenarios, the catchment is likely to experience a wetting trend, higher temperatures, seasonality shifts and an increase in extreme precipitation events, particularly in frequency and magnitude. This will likely affect water quality provision through runoff and sediment yield inputs, reducing the erosion control HES and likely aggravating eutrophication. Although the amount of water will increase, changes to the hydrological cycle might jeopardize the stability of freshwater supplies and HES on which many people in the south-eastern region of Uruguay depend. Despite streamflow monitoring capacities need to be enhanced to reduce the uncertainty of model results, our findings provide valuable insights for water resources planning in the study area. Hence, water management and monitoring capacities need to be enhanced to reduce the potential negative climate change impacts on HES. The methodological approach presented here, based on satellite ET data can be replicated and adapted to any other place in the world since we employed open-access software and remote sensing data for all the phases of hydrological modelling and HES provision assessment.

scholarly journals Capacity Development for Use of Remote Sensing for REDD+ MRV Using Online and Offline Activities: Impacts and Lessons Learned

2021 ◽  
Vol 13 (11) ◽  
pp. 2172
Author(s):  
Sarah Carter ◽  
Martin Herold ◽  
Inge Jonckheere ◽  
Andres Espejo ◽  
Carly Green ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Forest Cover ◽  
Hybrid Approach ◽  
Remote Sensing Data ◽  
Lessons Learned ◽  
Multiple Partners ◽  
Large Audience ◽  
Forest Cover Changes ◽  
The Impact ◽  
And Training

Four workshops and a webinar series were organized, with the aim of building capacity in countries to use Earth Observation Remote Sensing data to monitor forest cover changes and measure emissions reductions for REDD+ results-based payments. Webinars and workshops covered a variety of relevant tools and methods. The initiative was collaboratively organised by a number of Global Forest Observations Initiative (GFOI) partner institutions with funding from the World Bank’s Forest Carbon Partnership Facility (FCPF). The collaborative approach with multiple partners proved to be efficient and was able to reach a large audience, particularly in the case of the webinars. However, the impact in terms of use of tools and training of others after the events was higher for the workshops. In addition, engagement with experts was higher from workshop participants. In terms of efficiency, webinars are significantly cheaper to organize. A hybrid approach might be considered for future initiatives; and, this study of the effectiveness of both in-person and online capacity building can guide the development of future initiatives, something that is particularly pertinent in a COVID-19 era.

scholarly journals Retrieving Forest Canopy Elements Clumping Index Using ICESat GLAS Lidar Data

2021 ◽  
Vol 13 (5) ◽  
pp. 948
Author(s):  
Lei Cui ◽  
Ziti Jiao ◽  
Kaiguang Zhao ◽  
Mei Sun ◽  
Yadong Dong ◽  
...  
Keyword(s):  
Large Scale ◽  
Forest Canopy ◽  
Remote Sensing Data ◽  
Alternative Methods ◽  
High Signal ◽  
Laser Altimeter ◽  
Waveform Data ◽  
Forest Park ◽  
Clumping Index ◽  
The Impact

Clumping index (CI) is a canopy structural variable important for modeling the terrestrial biosphere, but its retrieval from remote sensing data remains one of the least reliable. The majority of regional or global CI products available so far were generated from multiangle optical reflectance data. However, these reflectance-based estimates have well-known limitations, such as the mere use of a linear relationship between the normalized difference hotspot and darkspot (NDHD) and CI, uncertainties in bidirectional reflectance distribution function (BRDF) models used to calculate the NDHD, and coarse spatial resolutions (e.g., hundreds of meters to several kilometers). To remedy these limitations and develop alternative methods for large-scale CI mapping, here we explored the use of spaceborne lidar—the Geoscience Laser Altimeter System (GLAS)—and proposed a semi-physical algorithm to estimate CI at the footprint level. Our algorithm was formulated to leverage the full vertical canopy profile information of the GLAS full-waveform data; it converted raw waveforms to forest canopy gap distributions and gap fractions of random canopies, which was used to estimate CI based on the radiative transfer theory and a revised Beer–Lambert model. We tested our algorithm over two areas in China—the Saihanba National Forest Park and Heilongjiang Province—and assessed its relative accuracies against field-measured CI and MODIS CI products. We found that reliable estimation of CI was possible only for GLAS waveforms with high signal-to-noise ratios (e.g., >65) and at gentle slopes (e.g., <12°). Our GLAS-based CI estimates for high-quality waveforms compared well to field-based CI (i.e., R2 = 0.72, RMSE = 0.07, and bias = 0.02), but they showed less correlation to MODIS CI (e.g., R2 = 0.26, RMSE = 0.12, and bias = 0.04). The difference highlights the impact of the scale effect in conducting comparisons of products with huge differences resolution. Overall, our analyses represent the first attempt to use spaceborne lidar to retrieve high-resolution forest CI and our algorithm holds promise for mapping CI globally.

scholarly journals ANALYSIS OF THE IMPACT OF OIL PRODUCT SPILLS ON NATURAL OBJECTS BASED ON SENTINEL-2 REMOTE SENSING DATA IN EASTERN SIBERIA

2021 ◽  
Vol 6 ◽  
pp. 24-31
Author(s):  
Dmitry A. Baikin
Keyword(s):  
Remote Sensing ◽  
Oil Spills ◽  
Remote Sensing Data ◽  
Oil Products ◽  
Eastern Siberia ◽  
Sensing Data ◽  
Sensing System ◽  
Natural Objects ◽  
The Impact ◽  
Sentinel 2

The article analyzes the impact of oil spills on natural objects according to the remote sensing system Sentinel-2 in Eastern Siberia. Remote sensing data analysis is used to detect traces of oil products in the accident area. Conclusions about the usage of Sentinel-2 data for detecting traces of oil products were made.

scholarly journals An Event-Based Inventory Approach in Landslide Hazard Assessment: The Case of the Skolis Mountain, Northwest Peloponnese, Greece

2020 ◽  
Vol 9 (7) ◽  
pp. 457
Author(s):  
Aspasia Litoseliti ◽  
Ioannis K. Koukouvelas ◽  
Konstantinos G. Nikolakopoulos ◽  
Vasiliki Zygouri
Keyword(s):  
Remote Sensing ◽  
Aspect Ratio ◽  
Remote Sensing Data ◽  
Historical Seismicity ◽  
Landslide Hazard ◽  
Disaster Mitigation ◽  
Earthquake Activity ◽  
Sensing Data ◽  
Reach Angle ◽  
The Impact

Assessment of landslide hazard across mountains is imperative for public safety. Pre- and post-earthquake landslide mapping envisage that landslides show significant size changes during earthquake activity. One of the purposes of earthquake-induced landslide investigation is to determine the landslide state and geometry and draw conclusions on their mobility. This study was based on remote sensing data that covered 72 years, and focused on the west slopes of the Skolis Mountains, in the northwest Peloponnese. On 8 June 2008, during the strong Movri Mountain earthquake (Mw = 6.4), we mapped the extremely abundant landslide occurrence. Historical seismicity and remote sensing data indicate that the Skolis Mountain west slope is repeatedly affected by landslides. The impact of the earthquakes was based on the estimation of Arias intensity in the study area. We recognized that 89 landslides developed over the last 72 years. These landslides increased their width (W), called herein as inflation or their length (L), termed as enlargement. Length and width changes were used to describe their aspect ratio (L/W). Based on the aspect ratio, the 89 landslides were classified into three types: I, J, and Δ. Taluses, developed at the base of the slope and belonging to the J- and Δ-landslide types, are supplied by narrow or irregular channels. During the earthquakes, the landslide channels migrated upward and downward, outlining the mobility of the earthquake-induced landslides. Landslide mobility was defined by the reach angle. The reach angle is the arctangent of the landslide’s height to length ratio. Furthermore, we analyzed the present slope stability across the Skolis Mountain by using the landslide density (LD), landslide area percentage (LAP), and landslide frequency (LF). All these parameters were used to evaluate the spatial and temporal landslide distribution and evolution with the earthquake activity. These results can be considered as a powerful tool for earthquake-induced landslide disaster mitigation

The Massive New Year 2020 pyroCb Event in Australia: Observations of Unprecedented Stratospheric Smoke

2020 ◽  
Author(s):  
Michael Fromm ◽  
George Kablick III
Keyword(s):  
Remote Sensing ◽  
Pacific Northwest ◽  
Satellite Remote Sensing ◽  
Remote Sensing Data ◽  
Early Spring ◽  
Fire Season ◽  
Smoke Plume ◽  
South Wales ◽  
Stratospheric Composition ◽  
The Impact

&lt;p&gt;The 2019/2020 fire season in Australia has been unusually energetic since early spring. In the last days of December and early January an unprecedented number of pyrocumulonimbus (pyroCb) storms erupted in New South Wales and Victoria, creating a seemingly unrivaled stratospheric smoke plume as well as devastation on the ground. Preliminary indications from satellite remote sensing are that the clustering of active pyroCbs and smoke injection heights exceeded all previous Australian pyroCb events, and perhaps pyroCb events worldwide. Similar to another extraordinary pyroCb event, the so-called Pacific Northwest Event in 2017, the Australian smoke plume has been observed to rise above its injection altitude by several kilometers. We report on the active blowups and quantify the impact on stratospheric composition using satellite remote sensing. Our analysis also consists of a quantitative comparison of the 2019/20 Australian pyrocb event with other major pyroCb events such as Black Saturday, Victoria, Australia in 2009. At the time of submission of this abstract, this is an unfolding episode; our report will characterize the unusual nature of this pyroCb event as the evolving plume and satellite remote sensing data permit.&lt;/p&gt;

Moderate-Resolution Remote Sensing and Geospatial Analyses of Microclimates, Mounds, and Maize in the Northern Great Lakes

2014 ◽  
Vol 2 (3) ◽  
pp. 195-207 ◽  
Author(s):  
Meghan C.L. Howey ◽  
Michael Palace ◽  
Crystal H. McMichael ◽  
Bobby Braswell
Keyword(s):  
Remote Sensing ◽  
Great Lakes ◽  
Remote Sensing Data ◽  
Sensing Data ◽  
Inland Lakes ◽  
Maize Cultivation ◽  
Geospatial Analyses ◽  
Moderate Resolution ◽  
Burial Mounds ◽  
The Impact

AbstractRemote sensing applications are increasingly common in archaeology but they often focus on high resolution imagery and direct archaeological site detection. Moderate spatial resolution remote sensing instruments, which have (near) daily repeat intervals, but contain less detailed spectral and spatial information, have been employed much less frequently in archaeology. However, moderate remote sensing data offer distinct advantages for archaeological research as they can be used to relate archaeological, ecological, and climactic data at vast spatial scales. To show this potential, we use moderate remote sensing data to examine the impact of landscape heterogeneity on the spread of indigenous maize horticulture in the northern Great Lakes during Late Precontact (ca. AD 1200-1600). Analyzing National Aeronautics and Space Administration (NASA) Moderate Resolution Imaging Spectroradiometer (MODIS) imagery, we identify differences in freeze/thaw cycles across inland lakes in Michigan, showing that some large inland lakes produce a microclimatic amelioration, possibly extending the growing season for prehistoric maize cultivation. Conducting geospatial analyses, we find that burial mounds and maize cultivation practices were associated preferentially with larger inland lakes with microclimates. We could not have found these dynamic interrelationships between microclimates, burial mounds, and maize cultivation if not for both the frequent temporal imaging and large spatial coverage provided by moderate resolution remote sensing imagery.

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