Observing the impact of urban morphology and building geometry on thermal environment by high spatial resolution thermal images

Abstract. The aim of this paper is two-fold: to provide guidance on how to best interpret TROPOMI trace gas retrievals and to highlight how TROPOMI trace gas data can be used to understand event-based impacts on air quality from regional to city-scales around the globe. For this study, we present the observed changes in the atmospheric column amounts of five trace gases (NO2, SO2, CO, HCHO and CHOCHO) detected by the Sentinel-5P TROPOMI instrument, driven by reductions of anthropogenic emissions due to COVID-19 lockdown measures in 2020. We report clear COVID-19-related decreases in NO2 concentrations on all continents. For megacities, reductions in column amounts of tropospheric NO2 range between 14 % and 63 %. For China and India supported by NO2 observations, where the primary source of anthropogenic SO2 is coal-fired power generation, we were able to detect sector-specific emission changes using the SO2 data. For HCHO and CHOCHO, we consistently observe anthropogenic changes in two-week averaged column amounts over China and India during the early phases of the lockdown periods. That these variations over such a short time scale are detectable from space, is due to the high resolution and improved sensitivity of the TROPOMI instrument. For CO, we observe a small reduction over China which is in concert with the other trace gas reductions observed during lockdown, however large, interannual differences prevent firm conclusions from being drawn. The joint analysis of COVID-19 lockdown-driven reductions in satellite observed trace gas column amounts, using the latest operational and scientific retrieval techniques for five species concomitantly is unprecedented. However, the meteorologically and seasonally driven variability of the five trace gases does not allow for drawing fully quantitative conclusions on the reduction of anthropogenic emissions based on TROPOMI observations alone. We anticipate that in future, the combined use of inverse modelling techniques with the high spatial resolution data from S5P/TROPOMI for all observed trace gases presented here, will yield a significantly improved sector-specific, space-based analysis of the impact of COVID-19 lockdown measures as compared to other existing satellite observations. Such analyses will further enhance the scientific impact and societal relevance of the TROPOMI mission.

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Interpreting high spatial resolution line observations of planet-forming disks with gaps and rings: the case of HD 163296

Astronomy and Astrophysics ◽

10.1051/0004-6361/202038712 ◽

2020 ◽

Vol 642 ◽

pp. A165

Author(s):

Ch. Rab ◽

I. Kamp ◽

C. Dominik ◽

C. Ginski ◽

G. A. Muro-Arena ◽

...

Keyword(s):

Spatial Resolution ◽

High Spatial Resolution ◽

Line Emission ◽

High Angular Resolution ◽

Back Side ◽

Gas Temperature ◽

Disk Model ◽

Gas Density ◽

The Impact ◽

Gas Properties

Context. Spatially resolved continuum observations of planet-forming disks show prominent ring and gap structures in their dust distribution. However, the picture from gas observations is much less clear and constraints on the radial gas density structure (i.e. gas gaps) remain rare and uncertain. Aims. We want to investigate the importance of thermo-chemical processes for the interpretation of high-spatial-resolution gas observations of planet-forming disks and their impact on the derived gas properties. Methods. We applied the radiation thermo-chemical disk code PRODIMO (PROtoplanetary DIsk MOdel) to model the dust and gas disk of HD 163296 self-consistently, using the DSHARP (Disk Substructure at High Angular Resolution) gas and dust observations. With this model we investigated the impact of dust gaps and gas gaps on the observables and the derived gas properties, considering chemistry, and heating and cooling processes. Results. We find distinct peaks in the radial line intensity profiles of the CO line data of HD 163296 at the location of the dust gaps. Our model indicates that those peaks are not only a consequence of a gas temperature increase within the gaps but are mainly caused by the absorption of line emission from the back side of the disk by the dust rings. For two of the three prominent dust gaps in HD 163296, we find that thermo-chemical effects are negligible for deriving density gradients via measurements of the rotation velocity. However, for the gap with the highest dust depletion, the temperature gradient can be dominant and needs to be considered to derive accurate gas density profiles. Conclusions. Self-consistent gas and dust thermo-chemical modelling in combination with high-quality observations of multiple molecules are necessary to accurately derive gas gap depths and shapes. This is crucial to determine the origin of gaps and rings in planet-forming disks and to improve the mass estimates of forming planets if they are the cause of the gap.

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The developement of red mud flood environmental information system and the methodology for the spatial analysis of the degraded area

Landscape & Environment ◽

10.21120/le/9/1/1 ◽

2015 ◽

Vol 9 (1) ◽

pp. 1-11

Author(s):

Gábor Bakó ◽

Gábor Kovács ◽

Zsolt Molnár ◽

Judit Kirisics ◽

Eszter Góber ◽

...

Keyword(s):

Remote Sensing ◽

Spatial Resolution ◽

Red Mud ◽

High Spatial Resolution ◽

Three Dimensional ◽

Environmental Information ◽

Evaluation Methodology ◽

Aerial Photogrammetry ◽

Impact Area ◽

The Impact

The red mud disaster occurred on 4th October 2010 in Hungary has raised the necessity of rapid intervention and drew attention to the long-term monitoring of such threat. Both the condition assessment and the change monitoring indispensably required the prompt and detailed spatial survey of the impact area. It was conducted by several research groups - independently - with different recent surveying methods. The high spatial resolution multispectral aerial photogrammetry is the spatially detailed (high resolution) and accurate type of remote sensing. The hyperspectral remote sensing provides more information about material quality of pollutants, with less spatial details and lower spatial accuracy, while LIDAR ensures the three-dimensional shape and terrain models. The article focuses on the high spatial resolution, multispectral electrooptical method and the evaluation methodology of the deriving high spatial resolution ortho image map, presenting the derived environmental information database

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Satellite imagery of lengthy territories with complex configuration with the account of attitude and positioning errors

E3S Web of Conferences ◽

10.1051/e3sconf/20197501013 ◽

2019 ◽

Vol 75 ◽

pp. 01013

Author(s):

Dmitriy Mozgovoy ◽

Dmitriy Svinarenko ◽

Roman Tsarev ◽

Tatiana Yamskikh

Keyword(s):

Spatial Resolution ◽

Satellite Imagery ◽

High Spatial Resolution ◽

Program Control ◽

Complex Configuration ◽

Positioning Errors ◽

Satellite Attitude ◽

The Impact

A method for monitoring attitude and positioning errors when taking satellite imagery of lengthy territories with complex configuration using an ultra-high spatial resolution optical-electronic scanner is described in the article. The results of modeling the system of automatic satellite attitude program control during the process of imagery are presented. Given these results, the impact of attitude and positioning errors during satellite imagery was estimated on the coverage percentage of the territory to be imaged.

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An evaluation of the potential of Sentinel 1 for improving flash flood predictions via soil moisture–data assimilation

Advances in Geosciences ◽

10.5194/adgeo-44-89-2017 ◽

2017 ◽

Vol 44 ◽

pp. 89-100 ◽

Cited By ~ 8

Author(s):

Luca Cenci ◽

Luca Pulvirenti ◽

Giorgio Boni ◽

Marco Chini ◽

Patrick Matgen ◽

...

Keyword(s):

Soil Moisture ◽

Data Assimilation ◽

Spatial Resolution ◽

Temporal Resolution ◽

Hydrological Model ◽

High Spatial Resolution ◽

Flash Flood ◽

Soil Moisture Data ◽

Time Period ◽

The Impact

Abstract. The assimilation of satellite-derived soil moisture estimates (soil moisture–data assimilation, SM–DA) into hydrological models has the potential to reduce the uncertainty of streamflow simulations. The improved capacity to monitor the closeness to saturation of small catchments, such as those characterizing the Mediterranean region, can be exploited to enhance flash flood predictions. When compared to other microwave sensors that have been exploited for SM–DA in recent years (e.g. the Advanced SCATterometer – ASCAT), characterized by low spatial/high temporal resolution, the Sentinel 1 (S1) mission provides an excellent opportunity to monitor systematically soil moisture (SM) at high spatial resolution and moderate temporal resolution. The aim of this research was thus to evaluate the impact of S1-based SM–DA for enhancing flash flood predictions of a hydrological model (Continuum) that is currently exploited for civil protection applications in Italy. The analysis was carried out in a representative Mediterranean catchment prone to flash floods, located in north-western Italy, during the time period October 2014–February 2015. It provided some important findings: (i) revealing the potential provided by S1-based SM–DA for improving discharge predictions, especially for higher flows; (ii) suggesting a more appropriate pre-processing technique to be applied to S1 data before the assimilation; and (iii) highlighting that even though high spatial resolution does provide an important contribution in a SM–DA system, the temporal resolution has the most crucial role. S1-derived SM maps are still a relatively new product and, to our knowledge, this is the first work published in an international journal dealing with their assimilation within a hydrological model to improve continuous streamflow simulations and flash flood predictions. Even though the reported results were obtained by analysing a relatively short time period, and thus should be supported by further research activities, we believe this research is timely in order to enhance our understanding of the potential contribution of the S1 data within the SM–DA framework for flash flood risk mitigation.

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The impact of wind drift on the utility of very high spatial resolution radar data over urban areas

Physics and Chemistry of the Earth Part B Hydrology Oceans and Atmosphere ◽

10.1016/s1464-1909(99)00099-4 ◽

1999 ◽

Vol 24 (8) ◽

pp. 889-893 ◽

Cited By ~ 25

Author(s):

C.G. Collier

Keyword(s):

Spatial Resolution ◽

Urban Areas ◽

High Spatial Resolution ◽

Radar Data ◽

Wind Drift ◽

Very High Spatial Resolution ◽

The Impact ◽

Very High

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Assessing the impact of soil surface characteristics on vineyard erosion from very high spatial resolution aerial images (Côte de Beaune, Burgundy, France)

CATENA ◽

10.1016/j.catena.2013.12.002 ◽

2014 ◽

Vol 116 ◽

pp. 163-172 ◽

Cited By ~ 25

Author(s):

Amélie Quiquerez ◽

Emmanuel Chevigny ◽

Pascal Allemand ◽

Pierre Curmi ◽

Christophe Petit ◽

...

Keyword(s):

Spatial Resolution ◽

High Spatial Resolution ◽

Soil Surface ◽

Surface Characteristics ◽

Aerial Images ◽

Very High Spatial Resolution ◽

The Impact ◽

Very High

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RCSANet: A Full Convolutional Network for Extracting Inland Aquaculture Ponds from High-Spatial-Resolution Images

Remote Sensing ◽

10.3390/rs13010092 ◽

2020 ◽

Vol 13 (1) ◽

pp. 92

Author(s):

Zhe Zeng ◽

Di Wang ◽

Wenxia Tan ◽

Gongliang Yu ◽

Jiacheng You ◽

...

Keyword(s):

Remote Sensing ◽

Spatial Resolution ◽

Large Scale ◽

High Spatial Resolution ◽

Convolutional Network ◽

Water Index ◽

Inland Lakes ◽

Natural Lakes ◽

Aquaculture Ponds ◽

The Impact

Numerous aquaculture ponds are intensively distributed around inland natural lakes and mixed with cropland, especially in areas with high population density in Asia. Information about the distribution of aquaculture ponds is essential for monitoring the impact of human activities on inland lakes. Accurate and efficient mapping of inland aquaculture ponds using high-spatial-resolution remote-sensing images is a challenging task because aquaculture ponds are mingled with other land cover types. Considering that aquaculture ponds have intertwining regular embankments and that these salient features are prominent at different scales, a Row-wise and Column-wise Self-Attention (RCSA) mechanism that adaptively exploits the identical directional dependency among pixels is proposed. Then a fully convolutional network (FCN) combined with the RCSA mechanism (RCSANet) is proposed for large-scale extraction of aquaculture ponds from high-spatial-resolution remote-sensing imagery. In addition, a fusion strategy is implemented using a water index and the RCSANet prediction to further improve extraction quality. Experiments on high-spatial-resolution images using pansharpened multispectral and 2 m panchromatic images show that the proposed methods gain at least 2–4% overall accuracy over other state-of-the-art methods regardless of regions and achieve an overall accuracy of 85% at Lake Hong region and 83% at Lake Liangzi region in aquaculture pond extraction.

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Assessing the Impact of Land Cover Changes on Surface Urban Heat Islands with High-Spatial-Resolution Imagery on a Local Scale: Workflow and Case Study

Sustainability ◽

10.3390/su11195188 ◽

2019 ◽

Vol 11 (19) ◽

pp. 5188 ◽

Cited By ~ 1

Author(s):

Peng Ren ◽

Xinxin Zhang ◽

Haoyan Liang ◽

Qinglin Meng

Keyword(s):

Land Cover ◽

Spatial Resolution ◽

Land Surface ◽

High Spatial Resolution ◽

Spatial Configuration ◽

Central Area ◽

Local Scale ◽

Systematic Analysis ◽

Urban Heat ◽

The Impact

Low-altitude remote sensing platform has been increasingly applied to observing local thermal environments due to its obvious advantage in spatial resolution and apparent flexibility in data acquisition. However, there is a general lack of systematic analysis for land cover (LC) classification, surface urban heat island (SUHI), and their spatial and temporal change patterns. In this study, a workflow is presented to assess the LC’s impact on SUHI, based on the visible and thermal infrared images with high spatial resolution captured by an unmanned airship in the central area of the Sino-Singapore Guangzhou Knowledge City in 2012 and 2015. Then, the accuracy assessment of LC classification and land surface temperature (LST) retrieval are performed. Finally, the commonly-used indexes in the field of satellites are applied to analyzing the spatial and temporal changes in the SUHI pattern on a local scale. The results show that the supervised maximum likelihood algorithm can deliver satisfactory overall accuracy and Kappa coefficient for LC classification; the root mean square error of the retrieved LST can reach 1.87 °C. Moreover, the LST demonstrates greater consistency with land cover type (LCT) and more fluctuation within an LCT on a local scale than on an urban scale. The normalized LST classified by the mean and standard deviation (STD) is suitable for the high-spatial situation; however, the thermal field level and the corresponded STD multiple need to be judiciously selected. This study exhibits an effective pathway to assess SUHI pattern and its changes using high-spatial-resolution images on a local scale. It is also indicated that proper landscape composition, spatial configuration and materials on a local scale exert greater impacts on SUHI.

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Using Sounder Data to Improve Cirrus Cloud Height Estimation from Satellite Imagers

Journal of Atmospheric and Oceanic Technology ◽

10.1175/jtech-d-18-0079.1 ◽

2019 ◽

Vol 36 (7) ◽

pp. 1331-1342 ◽

Cited By ~ 3

Author(s):

Andrew K. Heidinger ◽

Nicholas Bearson ◽

Michael J. Foster ◽

Yue Li ◽

Steve Wanzong ◽

...

Keyword(s):

Spatial Resolution ◽

High Spatial Resolution ◽

Optimal Estimation ◽

Additional Constraint ◽

Spectral Information ◽

Cirrus Cloud ◽

Absorption Bands ◽

Cloud Height ◽

Cross Track ◽

The Impact

AbstractModern polar-orbiting meteorological satellites provide both imaging and sounding observations simultaneously. Most imagers, however, do not have H2O and CO2 absorption bands and therefore struggle to accurately estimate the height of optically thin cirrus clouds. Sounders provide these needed observations, but at a spatial resolution that is too coarse to resolve many important cloud structures. This paper presents a technique to merge sounder and imager observations with the goal of maintaining the details offered by the imager’s high spatial resolution and the accuracy offered by the sounder’s spectral information. The technique involves deriving cloud temperatures from the sounder observations, interpolating the sounder temperatures to the imager pixels, and using the sounder temperatures as an additional constraint in the imager cloud height optimal estimation approach. This technique is demonstrated using collocated VIIRS and Cross-track Infrared Sounder (CrIS) observations with the impact of the sounder observations validated using coincident CALIPSO/CALIOP cloud heights These comparisons show significant improvement in the cloud heights for optically thin cirrus. The technique should be generally applicable to other imager/sounder pairs.

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