Geography Commons^™

A Remote Sensing Approach To Assess The Historical Invasion Of Phragmites Australis In A Brackish Coastal Marsh, Jason S. Hagani, John Y. Takekawa, Steven C. Chappell, Richelle L. Tanner, Adrienne R. Ernst, Karin M. Kettenring

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

Introduction: Coastal estuarine wetlands provide important habitats for a variety of endemic flora and fauna but are particularly vulnerable to biological invasions. Regular monitoring of changes in these vulnerable wetlands has become increasingly important for effective management, especially considering threats from climate change effects and human disturbance. Historical analyzes of plant invasions may guide targeted management strategies to eradicate harmful species. Estimating the distribution of invasive species has never been more accessible with the improved availability of high-resolution data and innovations in remote sensing, estimating the distribution of invasive species has never been more accessible.

Methods: We assessed the spread …

Timing And Magnitude Of Drought Impacts On Carbon Uptake Across A Grassland Biome, Andrew Felton, Gregory R. Goldsmith

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

Although drought is known to negatively impact grassland functioning, the timing and magnitude of these impacts within a growing season remains unresolved. Previous small-scale assessments indicate grasslands may only respond to drought during narrow periods within a year; however, large-scale assessments are now needed to uncover the general patterns and determinants of this timing. We combined remote sensing datasets of gross primary productivity and weather to assess the timing and magnitude of grassland responses to drought at 5 km² temporal resolution across two expansive ecoregions of the western US Great Plains biome: the C₄-dominated shortgrass steppe and …

Relative Importance Of Radar Variables For Nowcasting Heavy Rainfall: A Machine Learning Approach, Yi Victor Wang, Seung Hee Kim, Geunsu Lyu, Choeng-Lyong Lee, Gyuwon Lee, Ki-Hong Min, Menas C. Kafatos

Institute for ECHO Articles and Research

Highly short-term forecasting, or nowcasting, of heavy rainfall due to rapidly evolving mesoscale convective systems (MCSs) is particularly challenging for traditional numerical weather prediction models. To overcome such a challenge, a growing number of studies have shown significant advantages of using machine learning (ML) modeling techniques with remote sensing data, especially weather radar data, for high-resolution rainfall nowcasting. To improve ML model performance, it is essential first and foremost to quantify the importance of radar variables and identify pertinent predictors of rainfall that can also be associated with domain knowledge. In this study, a set of MCS types consisting of …

Possible Overestimation Of Nitrogen Dioxide Outgassing During The Beirut 2020 Explosion, Ashraf Farahat, Nayla El-Kork, Ramesh P. Singh, Feng Jing

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

On 4 August 2020, a strong explosion occurred near the Beirut seaport, Lebanon and killed more than 200 people and damaged numerous buildings in the vicinity. As Amonium Nitrate (AN) caused the explosion, many studies claimed the release of large amounts of NO₂ in the atmosphere may have resulted in a health hazard in Beirut and the vicinity. In order to reasonably evaluate the significance of NO₂ amounts released in the atmosphere, it is important to investigate the spatio-temporal distribution of NO₂ during and after the blast and compare it to the average day-to-day background emissions from …

Spatio-Temporal Changes In Vegetation In The Last Two Decades (2001–2020) In The Beijing–Tianjin–Hebei Region, Yuan Zou, Wei Chen, Siliang Li, Tiejun Wang, Le Yu, Min Xu, Ramesh P. Singh, Cong-Qiang Liu

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

In terrestrial ecosystems, vegetation is sensitive to climate change and human activities. Its spatial-temporal changes also affect the ecological and social environment. In this paper, we considered the Beijing–Tianjin–Hebei region to study the spatio-temporal vegetation patterns. The detailed analysis of a moderate-resolution imaging spectroradiometer (MODIS) data were carried out through the Google Earth Engine (GEE) platform. Our results show a slow and tortuous upward trend in the average leaf area index (LAI) in the study region for the periods 2001–2020. Specifically, Beijing had the highest LAI value, with an average of 1.64 over twenty years, followed by Hebei (1.30) and …

Hybrid U-Net: Semantic Segmentation Of High-Resolution Satellite Images To Detect War Destruction, Shima Nabiee, Matthew Harding, Jonathan Hersh, Nader Bagherzadeh

Economics Faculty Articles and Research

Destruction caused by violent conflicts play a big role in understanding the dynamics and consequences of conflicts, which is now the focus of a large body of ongoing literature in economics and political science. However, existing data on conflict largely come from news or eyewitness reports, which makes it incomplete, potentially unreliable, and biased for ongoing conflicts. Using satellite images and deep learning techniques, we can automatically extract objective information on violent events. To automate this process, we created a dataset of high-resolution satellite images of Syria and manually annotated the destroyed areas pixel-wise. Then, we used this dataset to …

Titaniferous-Vanadiferous, Magnetite-Ilmenite Mineralization In A Mafic Suite Within The Chhotanagpur Gneissic Complex, Bihar, India, Ashmeer Mohammad, Anup K. Prasad, Kehe-U Wetsah, Mohammad Azad, Vivek Aryan, Hesham El-Askary

Mathematics, Physics, and Computer Science Faculty Articles and Research

Titanium or vanadium metals or their alloys are important industrial metals/alloys. Because these resources are in short supply, the investigation of potential titaniferous-vanadiferous deposits needs special attention to bridge the supply-demand gap. The study integrates geological, geochemical, remote sensing, and geophysical data for assessing the potentiality of titaniferous-vanadiferous, magnetite-ilmenite mineralization in and around the Sudamakund and Paharpur areas, Gaya and Jehanabad districts, Bihar, India, and delineation of specific targets for detailed exploration. Field visits for large scale mapping on (1:12,500 scale) were used to conduct a reconnaissance survey for magnetite-ilmenite mineralization in parts of toposheet number 72G/04 in the Gaya …

Response Of Surface And Atmospheric Parameters Associated With The Iran M 7.3 Earthquake, Feng Jing, Ramesh P. Singh

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

Multiparameter observed from satellite, including microwave brightness temperature, skin temperature, air temperature, and carbon monoxide, have been analyzed to identify the anomalous signals associated with the M 7.3 Iran earthquake of November 12, 2017. Besides removing the multiyear variability of parameters as background, the effect of surface and atmosphere of a dust storm event in Middle East region during October 29–November 1 is considered to distinguish the possible anomalies associated with the earthquake. The characteristic behaviors of surface and atmospheric parameters clearly show the signals associated with the M 7.3 earthquake and the dust storm event. The multiple parameters at …

Pronounced Changes In Thermal Signals Associated With The Madoi (China) M 7.3 Earthquake From Passive Microwave And Infrared Satellite Data, Feng Jing, Lu Zhang, Ramesh P. Singh

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

Thermal variations in surface and atmosphere observed from multiple satellites prior to strong earthquakes have been widely reported ever since seismic thermal anomalies were discovered three decades ago. These thermal changes are related to stress accumulation caused by the tectonic activities in the final stage of earthquake preparation. In the present paper, we focused on the thermal changes associated with the 2021 Madoi M 7.3 earthquake in China and analyzed the temporal and spatial evolution of the Index of Microwave Radiation Anomaly (IMRA) and the Index of Longwave Radiation Anomaly (ILRA) based on 8-year microwave brightness temperature (MWBT) and 14-year …

Extreme Development Of Dragon Fruit Agriculture With Nighttime Lighting In Southern Vietnam, Shenyue Jia, Son V. Nghiem, Seung-Hee Kim, Laura Krauser, Andrea E. Gaughan, Forest R. Stevens, Menas Kafatos, Khanh D. Ngo

Institute for ECHO Faculty Books and Book Chapters

Dragon fruit is widely grown in Southeast Asia and other tropical or subtropical regions. As a high-value cash crop ideal for exportation, dragon fruit cultivation has boomed during the past decade in southern Vietnam. Light supplementing during the winter months using artificial lighting sources is a widely adopted cultivation technique to boost productivity in the major dragon fruit planting regions of Vietnam. The application of electric lighting at night leads to a significant increase of nighttime light (NTL) observable by satellite sensors. The strong seasonality signal of NTL in dragon fruit cultivation enables identifying dragon fruit plantations using NTL images. …

Accuracy Assessment, Comparative Performance, And Enhancement Of Public Domain Digital Elevation Models (Aster 30 M, Srtm 30 M, Cartosat 30 M, Srtm 90 M, Merit 90 M, And Tandem-X 90 M) Using Dgps, Kumari Preety, Anup K. Prasad, Atul K. Varma, Hesham El-Askary

Mathematics, Physics, and Computer Science Faculty Articles and Research

Publicly available Digital Elevation Models (DEM) derived from various space-based platforms (Satellite/Space Shuttle Endeavour) have had a tremendous impact on the quantification of landscape characteristics, and the related processes and products. The accuracy of elevation data from six major public domain satellite-derived Digital Elevation Models (a 30 m grid size—ASTER GDEM version 3 (Ast30), SRTM version 3 (Srt30), CartoDEM version V3R1 (Crt30)—and 90 m grid size—SRTM version 4.1 (Srt90), MERIT (MRT90), and TanDEM-X (TDX90)), as well as the improvement in accuracy achieved by applying a correction (linear fit) using Differential Global Positioning System (DGPS) estimates at Ground Control Points (GCPs) …

Landslide Detection In The Himalayas Using Machine Learning Algorithms And U-Net, Sansar Raj Meena, Lucas Pedrosa Soares, Carlos H. Grohmann, Cees Van Westen, Kushanav Bhuyan, Ramesh P. Singh, Mario Floris, Filippo Catani

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

Event-based landslide inventories are essential sources to broaden our understanding of the causal relationship between triggering events and the occurring landslides. Moreover, detailed inventories are crucial for the succeeding phases of landslide risk studies like susceptibility and hazard assessment. The openly available inventories differ in the quality and completeness levels. Event-based landslide inventories are created based on manual interpretation, and there can be significant differences in the mapping preferences among interpreters. To address this issue, we used two different datasets to analyze the potential of U-Net and machine learning approaches for automated landslide detection in the Himalayas. Dataset-1 is composed …

Snow Cover Variability And Trend Over The Hindu Kush Himalayan Region Using Modis And Srtm Data, Nirasindhu Desinayak, Anup K. Prasad, Hesham El-Askary, Menas Kafatos, Ghassem R. Asrar

Mathematics, Physics, and Computer Science Faculty Articles and Research

Snow cover changes have a direct bearing on the regional and global energy and water cycles and the change in the Earth's climate conditions. We studied the relatively long-term (2000–2017) altitudinal spatiotemporal changes in the coverage of snow and glaciers in one of the world's largest mountainous regions, the Hindu Kush Himalayan (HKH) region, including Tibet, using remote sensing data (5 km grid resolution) from the Moderate Resolution Imaging Spectroradiometer (MODIS) on board the Terra satellite. This dataset provided a unique opportunity to study zonal and hypsographic changes in the intra-annual (accumulating season and melting season) and interannual variations in …

Editorial: Geospace Observation Of Natural Hazards, Dimitar Ouzounov, Jann-Yenq Liu, Patrick T. Taylor, Katsumi Hattori

Mathematics, Physics, and Computer Science Faculty Articles and Research

"This collection of technical papers aims to bring recent data from many sources into the study of natural hazards. They represent a multi-instrumental approach using both ground observations: Global Navigation Satellite System (GNSS); and Low Earth Orbiting Electromagnetic (LEO EM) satellites missions together with Earth Observations (EO), which could reveal new information. Results from latest satellite missions, [(NPP/NASA/NOAA(US), CENTINEL, Swarm/ESA (EU), HIMAWARI (JMA, Japan), FORMOSAT-5 (Taiwan, August 2017), CSES1 (China/Italy, Feb 2018), and FORMOSAT-7/COSMIC-2 (Taiwan/United States, May 2019)], are represented in this volume."

Catastrophic Ice-Debris Flow In The Rishiganga River, Chamoli, Uttarakhand (India), Vijendra Kumar Pandey, Rajesh Kumar, Rupendra Singh, Rajesh Kumar, Suresh Chand Rai, Ramesh P. Singh, Arun Kumar Tripathi, Vijay Kumar Soni, S. Nawaz Ali, Dakshina Tamang, Syed Umer Latief

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

A catastrophic flood occurred on 7 February 2021 around 10:30 AM (local time) in the Rishiganga River, which has been attributed to a rockslide in the upper reach of the Raunthi River. The Resourcesat 2 LISS IV (8 February 2021) and CNES Airbus satellite imagery (9 February 2021) clearly show the location of displaced materials. The solar radiation observed was higher than normal by 10% and 25% on 6 and 7 February 2021, respectively, however, the temperature shows up to 34% changes. These conditions are responsible for the sudden change in instability in glacier blocks causing deadly rock-ice slides that …

Dynamic Relationship Study Between The Observed Seismicity And Spatiotemporal Pattern Of Lineament Changes In Palghar, North Maharashtra (India), Biswajit Nath, Ramesh P. Singh, Vineet K. Gahalaut, Ajay P. Singh

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

The Palghar region (north Maharashtra, India), located in the northwestern part of the stable continental region of India, experienced a low magnitude earthquake swarm, which was initiated in September 2018 and is continuing to date (as of October 2021). From December 2018 to December 2020, ~5000 earthquakes with magnitudes from M1.2 to M3.8 occurred in a small region of 20 × 10 km². These earthquakes were probably triggered by fluid migration during seasonal rainfall. In this study, we have used multi-temporal Landsat satellite data of the year 2000, 2015, 2018, 2019, and 2020, extracted lineaments, and studied the …

Progressive Destabilization And Triggering Mechanism Analysis Using Multiple Data For Chamoli Rockslide Of 7 February 2021, Wenfei Mao, Lixin Wu, Ramesh P. Singh, Yuan Qi, Busheng Xie, Yingjia Liu, Yifan Ding, Zilong Zhou, Jia Li

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

A catastrophic rockslide occurred on 7 February 2021 in Chamoli area in the high Himalaya. In the absence of field data, multiple satellites data of decade span have been used to investigate and understand the progressive destabilization of rockslide body. A 3D geometric model was developed using geospatial information about geology, terrain, and ice cover to understand the triggering mechanism. Several causes are uncovered as: the pronounced long-term change of land surface temperature facilitated local permafrost degradation and led to ice cover shrinking since 2010; the occurrence of ice avalanche nearby in 2016 accompanying with sidewall-to-bedrock fracturing enhanced the ice …

Pre-Earthquake Ionospheric Perturbation Identification Using Cses Data Via Transfer Learning, Pan Xiong, Cheng Long, Huiyu Zhou, Roberto Battiston, Angelo De Santis, Dimitar Ouzounov, Xuemin Zhang, Xuhui Shen

Mathematics, Physics, and Computer Science Faculty Articles and Research

During the lithospheric buildup to an earthquake, complex physical changes occur within the earthquake hypocenter. Data pertaining to the changes in the ionosphere may be obtained by satellites, and the analysis of data anomalies can help identify earthquake precursors. In this paper, we present a deep-learning model, SeqNetQuake, that uses data from the first China Seismo-Electromagnetic Satellite (CSES) to identify ionospheric perturbations prior to earthquakes. SeqNetQuake achieves the best performance [F-measure (F1) = 0.6792 and Matthews correlation coefficient (MCC) = 0.427] when directly trained on the CSES dataset with a spatial window centered on the earthquake epicenter with the Dobrovolsky …

Assessing The Vertical Displacement Of The Grand Ethiopian Renaissance Dam During Its Filling Using Dinsar Technology And Its Potential Acute Consequences On The Downstream Countries, Hesham El-Askary, Amr Fawzy, Rejoice Thomas, Wenzhao Li, Nicholas Lahaye, Erik Linstead, Thomas Piechota, Daniele Struppa, Mohamed Abdelaty Sayed

Mathematics, Physics, and Computer Science Faculty Articles and Research

The Grand Ethiopian Renaissance Dam (GERD), formerly known as the Millennium Dam, is currently under construction and has been filling at a fast rate without sufficient known analysis on possible impacts on the body of the structure. The filling of GERD not only has an impact on the Blue Nile Basin hydrology, water storage and flow but also poses massive risks in case of collapse. Rosaries Dam located in Sudan at only 116 km downstream of GERD, along with the 20 million Sudanese benefiting from that dam, would be seriously threatened in case of the collapse of GERD. In this …

Changes In The Flood Plains And Water Quality Along The Himalayan Rivers After The Chamoli Disaster Of 7 February 2021, Sansar Raj Meena, Kushanav Bhuyan, Akshansa Chauhan, Ramesh P. Singh

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

The Himalayan regions are vulnerable to all kinds of natural hazards. On 7 February 2021, a deadly disaster occurred near the Tapovan, in Uttarakhand, Himalayas. During the event, large volume of debris along with broken glacial fragments flooded the Rishi Ganga River and washed away the nearby hydropower plants (Rishi Ganga and Tapovan), which was revealed from detailed analysis of multi spectral and bi-temporal satellite data. We present the impact of the Chamoli disaster on the flood plains and water quality of Himalayan rivers, Rishi Ganga near Tapovan, Alaknanda near Srinagar and Ganga near Haridwar and Bijnor. We used four …

A Quantitative Validation Of Multi-Modal Image Fusion And Segmentation For Object Detection And Tracking, Nicholas Lahaye, Michael J. Garay, Brian D. Bue, Hesham El-Askary, Erik Linstead

Mathematics, Physics, and Computer Science Faculty Articles and Research

In previous works, we have shown the efficacy of using Deep Belief Networks, paired with clustering, to identify distinct classes of objects within remotely sensed data via cluster analysis and qualitative analysis of the output data in comparison with reference data. In this paper, we quantitatively validate the methodology against datasets currently being generated and used within the remote sensing community, as well as show the capabilities and benefits of the data fusion methodologies used. The experiments run take the output of our unsupervised fusion and segmentation methodology and map them to various labeled datasets at different levels of global …

Monitoring War Destruction From Space Using Machine Learning, Hannes Mueller, Andre Groeger, Jonathan Hersh, Andrea Matranga, Joan Serrat

Economics Faculty Articles and Research

Satellite imagery is becoming ubiquitous. Research has demonstrated that artificial intelligence applied to satellite imagery holds promise for automated detection of war-related building destruction. While these results are promising, monitoring in real-world applications requires high precision, especially when destruction is sparse and detecting destroyed buildings is equivalent to looking for a needle in a haystack. We demonstrate that exploiting the persistent nature of building destruction can substantially improve the training of automated destruction monitoring. We also propose an additional machine-learning stage that leverages images of surrounding areas and multiple successive images of the same area, which further improves detection significantly. …

Investigating Decadal Changes Of Multiple Hydrological Products And Land-Cover Changes In The Mediterranean Region For 2009–2018, Wenzhao Li, Sachi Perera, Erik Linstead, Rejoice Thomas, Hesham El-Askary, Thomas Piechota, Daniele Struppa

Mathematics, Physics, and Computer Science Faculty Articles and Research

Land-cover change is a critical concern due to its climatic, ecological, and socioeconomic consequences. In this study, we used multiple variables including precipitation, vegetation index, surface soil moisture, and evapotranspiration obtained from different satellite sources to study their association with land-cover changes in the Mediterranean region. Both observational and modeling data were used for climatology and correlation analysis. Famine Early Warning Systems Network (FEWS NET) Land Data Assimilation System (FLDAS) and Global Land Data Assimilation System (GLDAS) were used to extract surface soil moisture and evapotranspiration data. Intercomparing the results of FLDAS and GLDAS suggested that FLDAS data had better …

An Assessment Of The Filling Process Of The Grand Ethiopian Renaissance Dam And Its Impact On The Downstream Countries, Prakrut Kansara, Wenzhao Li, Hesham El-Askary, Venkat Lakshmi, Thomas Piechota, Daniele Struppa, Mohamed Abdelaty Sayed

Mathematics, Physics, and Computer Science Faculty Articles and Research

The Grand Ethiopian Renaissance Dam (GERD), formerly known as the Millennium Dam, has been filling at a fast rate. This project has created issues for the Nile Basin countries of Egypt, Sudan, and Ethiopia. The filling of GERD has an impact on the Nile Basin hydrology and specifically the water storages (lakes/reservoirs) and flow downstream. In this study, through the analysis of multi-source satellite imagery, we study the filling of the GERD reservoir. The time-series generated using Sentinel-1 SAR imagery displays the number of classified water pixels in the dam from early June 2017 to September 2020, indicating a contrasting …

Towards Advancing The Earthquake Forecasting By Machine Learning Of Satellite Data, Pan Xiong, Lei Tong, Kun Zhang, Xuhui Shen, Roberto Battiston, Dimitar Ouzounov, Roberto Iuppa, Danny Crookes, Cheng Long, Huyui Zhou

Mathematics, Physics, and Computer Science Faculty Articles and Research

Earthquakes have become one of the leading causes of death from natural hazards in the last fifty years. Continuous efforts have been made to understand the physical characteristics of earthquakes and the interaction between the physical hazards and the environments so that appropriate warnings may be generated before earthquakes strike. However, earthquake forecasting is not trivial at all. Reliable forecastings should include the analysis and the signals indicating the coming of a significant quake. Unfortunately, these signals are rarely evident before earthquakes occur, and therefore it is challenging to detect such precursors in seismic analysis. Among the available technologies for …

Rapid Mapping Of Landslides In The Western Ghats (India) Triggered By 2018 Extreme Monsoon Rainfall Using A Deep Learning Approach, Sansar Raj Meena, Omid Ghorbanzadeh, Cees J. Van Westen, Thimmaiah Gudiyangada Nachappa, Thomas Blaschke, Ramesh P. Singh, Raju Sarkar

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

Rainfall-induced landslide inventories can be compiled using remote sensing and topographical data, gathered using either traditional or semi-automatic supervised methods. In this study, we used the PlanetScope imagery and deep learning convolution neural networks (CNNs) to map the 2018 rainfall-induced landslides in the Kodagu district of Karnataka state in theWestern Ghats of India.We used a fourfold cross-validation (CV) to select the training and testing data to remove any random results of the model. Topographic slope data was used as auxiliary information to increase the performance of the model. The resulting landslide inventory map, created using the slope data with the …

An Assessment Of The Hydrological Trends Using Synergistic Approaches Of Remote Sensing And Model Evaluations Over Global Arid And Semi-Arid Regions, Wenzhao Li, Hesham El-Askary, Rejoice Thomas, Surya Prakash Tiwari, Karuppasamy Manikandan, Thomas Piechota, Daniele Struppa

Mathematics, Physics, and Computer Science Faculty Articles and Research

Drylands cover about 40% of the world’s land area and support two billion people, most of them living in developing countries that are at risk due to land degradation. Over the last few decades, there has been warming, with an escalation of drought and rapid population growth. This will further intensify the risk of desertification, which will seriously affect the local ecological environment, food security and people’s lives. The goal of this research is to analyze the hydrological and land cover characteristics and variability over global arid and semi-arid regions over the last decade (2010–2019) using an integrative approach of …

Multidecadal Analysis Of Beach Loss At The Major Offshore Sea Turtle Nesting Islands In The Northern Arabian Gulf, Rommel H. Maneja, Jeffrey D. Miller, Wenzhao Li, Rejoice Thomas, Hesham El-Askary, Sachi Perera, Ace Vincent B. Flandez, Abdullajid U. Basali, Joselito Francis A. Alcaria, Jinoy Gopalan, Surya Prakash Tiwari, Mubarak Al-Jedani, Perdana K. Prihartato, Ronald A. Loughlan, Ali Qasem, Mohamed A. Qurban, Wail Falath, Daniele Struppa

Mathematics, Physics, and Computer Science Faculty Articles and Research

Undocumented historical losses of sea turtle nesting beaches worldwide could overestimate the successes of conservation measures and misrepresent the actual status of the sea turtle population. In addition, the suitability of many sea turtle nesting sites continues to decline even without in-depth scientific studies of the extent of losses and impacts to the population. In this study, multidecadal changes in the outlines and area of Jana and Karan islands, major sea turtle nesting sites in the Arabian Gulf, were compared using available Kodak aerographic images, USGS EROS Declassified satellite imagery, and ESRI satellite images. A decrease of 5.1% and 1.7% …

Spatiotemporal Variations Of City-Level Carbon Emissions In China During 2000–2017 Using Nighttime Light Data, Yu Sun, Sheng Zheng, Yuzhe Wu, Uwe Schlink, Ramesh P. Singh

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

China is one of the largest carbon emitting countries in the world. Numerous strategies have been considered by the Chinese government to mitigate carbon emissions in recent years. Accurate and timely estimation of spatiotemporal variations of city-level carbon emissions is of vital importance for planning of low-carbon strategies. For an assessment of the spatiotemporal variations of city-level carbon emissions in China during the periods 2000–2017, we used nighttime light data as a proxy from two sources: Defense Meteorological Satellite Program’s Operational Linescan System (DMSP-OLS) data and the Suomi National Polar-orbiting Partnership satellite’s Visible Infrared Imaging Radiometer Suite (NPP-VIIRS). The results …

Long Term Air Quality Analysis In Reference To Thermal Power Plants Using Satellite Data In Singrauli Region, India, H. K. Romana, Ramesh P. Singh, D. P. Shukla

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

The exponentially growing population and related anthropogenic activities have led to modifications in local environment. The change in local environment, evolving pattern of land use, concentrations of greenhouse gases and aerosols alter the energy balance of our climate system. This alteration in climate is leading to pre-mature deaths worldwide. This study analyses the air quality of Singrauli region, Madhya Pradesh, India for the past 15 years. Otherwise known as Urjanchal “the energy capital” of India has been declared as critically polluted by CPCB. The study provides an updated list of thermal power plants in the study area and their emission …