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A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Urban Remote Sensing".

Deadline for manuscript submissions: closed (15 December 2022) | Viewed by 20056

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Special Issue Editors

Dr. Nabin Malakar

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Guest Editor

Worcester State University, MA, USA
Interests: societal applications of remote sensing data; land surface temperature; air pollution; application of machine learning to earth sciences

Dr. Maheswar Rupakheti

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Guest Editor

Institute for Advanced Sustainability Studies (IASS), Potsdam, Germany
Interests: air pollution-climate interaction

Dr. Prajjwal Panday

E-Mail Website
Guest Editor

Nichols College, MA, USA
Interests: understand terrestrial and hydrological processes across various spatial and temporal scales based observations; satellite remote sensing; geospatial data; and process-based modeling

Special Issue Information

Dear Colleagues,

Satellite remote sensing plays a key role in earth observation. The spatial and temporal coverage provided by various satellite remote sensing platforms has made it possible to study various aspects of natural and anthropogenic factors affecting societal wellbeing from local to global scale. Examples include but are not limited to monitoring patterns and trends in atmospheric phenomena, air pollution, wildfires, land surface phenology, thermal environments in urban areas, environmental hazards, change in mountain glacier and sea-ice, resource exploitation and their direct impact on ecosystem balance, as well as human health. In order to reveal the underlying trends and patterns provided by “big data” earth observations, statistical and machine learning tools have been extensively used in recent years for a variety of Earth Science applications. These data-based methods not only allow us to objectively build mitigation strategies at the policy level to improve the wellbeing of the society but also have global significance. In this Special Issue, we welcome papers that cover a wide range of interdisciplinary subjects involving societal application of remote sensing earth observation. We encourage the submission of studies that use an integrated approach of combining satellite data, ground-based remote sensing data (for example, LIDAR, sun photometers), and numerical modeling (e.g., atmospheric simulations).

Dr. Nabin Malakar
Dr. Maheswar Rupakheti
Dr. Prajjwal Panday
Guest Editors

Manuscript Submission Information

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Keywords

Remote sensing
Societal applications
Climate change
Sustainability
Biodiversity
Socioeconomic issues
Big data
Machine learning
Air pollution, water pollution, marine pollution
Thermal remote sensing
Airborne remote sensing
Interdisciplinary studies
Land use land change

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Published Papers (5 papers)

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20 pages, 8927 KiB

Open AccessArticle

Explore the Mitigation Mechanism of Urban Thermal Environment by Integrating Geographic Detector and Standard Deviation Ellipse (SDE)

by Yifan Zhao, Qirui Wu, Panpan Wei, Hao Zhao, Xiwang Zhang and Chenkun Pang

Remote Sens. 2022, 14(14), 3411; https://doi.org/10.3390/rs14143411 - 15 Jul 2022

Cited by 55 | Viewed by 3580

Abstract

The urban surface temperature is a complex integrated natural-human geographic phenomena; with the development of geostatistical methods and the application of multisource data, its research has gradually shifted from a single perspective to a study that integrates multiple factors such as nature and humanity. However, based on the context of the integration of natural and human factors and mutual constraints of each factor, the research on the mechanism of influence on urban habitat thermal environment needs to be further deepened. Therefore, this paper explores the spatial and temporal heterogeneity of urban surface temperature in Zhengzhou City during the summer of 2013–2020 from the perspective of multi-source data fusion, and uses the Geodetector model to quantitatively reveal the main influencing factors of urban surface temperature and the impact of superimposed factors on the compound effect of surface temperature. The results show that: (1) the urban thermal environment in the central of Zhengzhou city (region within the first ring) is obvious, and it is mainly concentrated in commercial and densely populated areas. (2) According to trend analysis, the northwest-southeast direction of the city continues to increase in temperature from 2013–2020, coupled with the direction of urban development. (3) Among the factors affecting urban surface temperature, normalized difference built-up index (NDBI), normalized difference vegetation index (NDVI), tasseled cap wetness (TCW), and human elements are particularly typical. NDVI and TCW are strongly negatively correlated with the urban thermal environment, while NDBI and human elements are strongly positively correlated. (4) Mitigation of the urban thermal environment can start with the interaction mechanism of positive and negative factors. This study provides new ideas for the mechanism analysis of spatial and temporal evolution patterns of the urban thermal environment under multifactorial constraints, and provides suggestions and decisions for promoting green and sustainable urban development. Full article

(This article belongs to the Special Issue Societal Applications of Remote Sensing Data)

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13 pages, 3718 KiB

Open AccessCommunication

Observation of Maritime Traffic Interruption in Patagonia during the COVID-19 Lockdown Using Copernicus Sentinel-1 Data and Google Earth Engine

by Cristina Rodríguez-Benito, Isabel Caballero, Karen Nieto and Gabriel Navarro

Remote Sens. 2021, 13(6), 1119; https://doi.org/10.3390/rs13061119 - 16 Mar 2021

Cited by 4 | Viewed by 3866

Abstract

Human mobilization during the COVID-19 lockdown has been reduced in many areas of the world. Maritime navigation has been affected in strategic connections between some regions in Patagonia, at the southern end of South America. The purpose of this research is to describe this interruption of navigation using satellite synthetic aperture radar data. For this goal, three locations are observed using geoinformatic techniques and high-resolution satellite data from the Sentinel-1 satellites of the European Commission’s Copernicus programme. The spatial information is analyzed using the Google Earth Engine (GEE) platform as a global geographical information system and the EO Browser tool, integrated with several satellite data. The results demonstrate that the total maritime traffic activity in the three geographical hotspots selected along western Patagonia, the Chacao Channel, crossing of the Reloncavi Fjord and the Strait of Magellan was totally interrupted during April–May 2020. This fact has relevant repercussions for the population living in isolated areas, such as many places in Patagonia, including Tierra del Fuego. The study also demonstrates the relevance of satellite radar observations in coastal areas with severe cloud cover, such as the one evaluated here. Full article

(This article belongs to the Special Issue Societal Applications of Remote Sensing Data)

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18 pages, 13270 KiB

Open AccessArticle

Analysis of the Characteristics of Climate Change in the Ecologically Vulnerable Area of the Mu Us Dune Field under the Background of Global Warming

by Guanwen Huang, Hai Zhu, Juqing Zhang and Bohan Liu

Remote Sens. 2021, 13(4), 627; https://doi.org/10.3390/rs13040627 - 9 Feb 2021

Cited by 7 | Viewed by 3032

Abstract

The Mu Us dune field is one of China’s four major dune fields, which are ecologically vulnerable areas of northwest semiarid land across Shaanxi, Ningxia, and Inner Mongolia, also very sensitive to the global temperature rise and environmental changes. This paper uses data on the temperature, precipitation, and precipitable water vapor (PWV) in the Mu Us dune field and its surrounding areas to analyze and discuss the time series and spatial distribution characteristics of these three factors in this area. The results of the study show that, in recent years, the trend of temperature increase in the Mu Us dune field has been higher than the average level in China, but this trend has gradually subsided since 2000. The spatial distribution of temperature presents an obvious characteristic of gradual increase from north to south and is affected by latitude, altitude, and topography. The annual cumulative precipitation of the Mu Us dune field is lower than the average level in China. However, in recent years, the rate of the increase in precipitation in this area has been significantly higher than that of the average rate of increase in China. The eastern part of the dune field has the most precipitation, which gradually decreases to the west. The spatial distribution of precipitation is greatly affected by monsoon factors in the region and the distribution of rivers. In the research field, PWV has been rising in recent years, which is greatly related to the increase of vegetation coverage in this region. This demonstrates that the Mu Us dune field has experienced a “warmer and wetter” trend in recent years. Full article

(This article belongs to the Special Issue Societal Applications of Remote Sensing Data)

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16 pages, 5106 KiB

Open AccessArticle

Investigating the Impacts of the COVID-19 Lockdown on Trace Gases Using Ground-Based MAX-DOAS Observations in Nanjing, China

by Zeeshan Javed, Yuhang Wang, Mingjie Xie, Aimon Tanvir, Abdul Rehman, Xiangguang Ji, Chengzhi Xing, Awais Shakoor and Cheng Liu

Remote Sens. 2020, 12(23), 3939; https://doi.org/10.3390/rs12233939 - 1 Dec 2020

Cited by 17 | Viewed by 3284

Abstract

The spread of the COVID-19 pandemic and consequent lockdowns all over the world have had various impacts on atmospheric quality. This study aimed to investigate the impact of the lockdown on the air quality of Nanjing, China. The off-axis measurements from state-of-the-art remote-sensing Multi-Axis Differential Optical Absorption Spectroscope (MAX-DOAS) were used to observe the trace gases, i.e., Formaldehyde (HCHO), Nitrogen Dioxide (NO₂), and Sulfur Dioxide (SO₂), along with the in-situ time series of NO₂, SO₂ and Ozone (O₃). The total dataset covers the span of five months, from 1 December 2019, to 10 May 2020, which comprises of four phases, i.e., the pre lockdown phase (1 December 2019, to 23 January 2020), Phase-1 lockdown (24 January 2020, to 26 February 2020), Phase-2 lockdown (27 February 2020, to 31 March 2020), and post lockdown (1 April 2020, to 10 May 2020). The observed results clearly showed that the concentrations of selected pollutants were lower along with improved air quality during the lockdown periods (Phase-1 and Phase-2) with only the exception of O₃, which showed an increasing trend during lockdown. The study concluded that limited anthropogenic activities during the spring festival and lockdown phases improved air quality with a significant reduction of selected trace gases, i.e., NO₂ 59%, HCHO 38%, and SO₂ 33%. We also compared our results with 2019 data for available gases. Our results imply that the air pollutants concentration reduction in 2019 during Phase-2 was insignificant, which was due to the business as usual conditions after the Spring Festival (Phase-1) in 2019. In contrast, a significant contamination reduction was observed during Phase-2 in 2020 with the enforcement of a Level-II response in lockdown conditions i.e., the easing of the lockdown situation in some sectors during a specific interval of time. The observed ratio of HCHO to NO₂ showed that tropospheric ozone production involved Volatile Organic Compounds (VOC) limited scenarios. Full article

(This article belongs to the Special Issue Societal Applications of Remote Sensing Data)

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24 pages, 2976 KiB

Open AccessTechnical Note

Small Unmanned Aircraft (sUAS)-Deployed Thermal Infrared (TIR) Imaging for Environmental Surveys with Implications in Submarine Groundwater Discharge (SGD): Methods, Challenges, and Novel Opportunities

by Kyle S. R. Young and Soni M. Pradhanang

Remote Sens. 2021, 13(7), 1331; https://doi.org/10.3390/rs13071331 - 31 Mar 2021

Cited by 12 | Viewed by 4242

Abstract

Submarine Groundwater Discharge (SGD) represents a significant mode of chemical transport to water bodies, making it an important flux to understand. Small Unmanned Aircraft Systems-deployed thermal infrared sensors (sUAS-TIR) provide a financially and logistically inexpensive means of identifying SGD source zones and quantifying SGD thermal infrared (TIR) plume areas over regional scales at high spatial resolutions. sUAS-TIR additionally offers the unique capability of high temporal resolution measurements of SGD. As a developing science application, the use of sUAS-TIR to image SGD requires substantial background knowledge. We present a proposed methodological construct for implementing a sUAS-TIR program for SGD-TIR data gathering, with applications extending to other research fields that can benefit from airborne TIR. Several studies have used airborne TIR in combination with empirical SGD flux measurements to quantify SGD, reporting a consistently strong regression between SGD flux and SGD TIR plume area. We additionally discuss novel research opportunities for sUAS-TIR technologies, as applied to SGD flux. The combination of high spatial and temporal resolution capabilities, at relatively low costs, make sUAS-TIR a promising new technology to overcome the scaling challenges presented by empirical studies and modeling of SGD fluxes, and advance our understanding of the controls on SGD fluxes. Full article

(This article belongs to the Special Issue Societal Applications of Remote Sensing Data)

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