Assessing the influence of floods over selected states of Eastern India with cloud-based geo-computing platforms

Ghosh, Sukanya; Kumar, Deepak; Kumari, Richa

doi:10.1080/10106049.2022.2047230

Cited by 3 publications

(1 citation statement)

References 49 publications

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“…Cluster 10, labeled "vegetation index" (very light red), has 14 nodes and 226 occurrences on the use of vegetation indices in cropland mapping [124]. Other topics include flood influence assessment [165] and the development of phenological and GEE-based algorithms [166]. It also provides automation methods for mapping paddy rice production [167].…”

Section: Author Abstract Co-occurrence Networkmentioning

confidence: 99%

Google Earth Engine: A Global Analysis and Future Trends

et al. 2023

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The continuous increase in the volume of geospatial data has led to the creation of storage tools and the cloud to process data. Google Earth Engine (GEE) is a cloud-based platform that facilitates geoprocessing, making it a tool of great interest to the academic and research world. This article proposes a bibliometric analysis of the GEE platform to analyze its scientific production. The methodology consists of four phases. The first phase corresponds to selecting “search” criteria, followed by the second phase focused on collecting data during the 2011 and 2022 periods using Elsevier’s Scopus database. Software and bibliometrics allowed to review the published articles during the third phase. Finally, the results were analyzed and interpreted in the last phase. The research found 2800 documents that received contributions from 125 countries, with China and the USA leading as the countries with higher contributions supporting an increment in the use of GEE for the visualization and processing of geospatial data. The intellectual structure study and knowledge mapping showed that topics of interest included satellites, sensors, remote sensing, machine learning, land use and land cover. The co-citations analysis revealed the connection between the researchers who used the GEE platform in their research papers. GEE has proven to be an emergent web platform with the potential to manage big satellite data easily. Furthermore, GEE is considered a multidisciplinary tool with multiple applications in various areas of knowledge. This research adds to the current knowledge about the Google Earth Engine platform, analyzing its cognitive structure related to the research in the Scopus database. In addition, this study presents inferences and suggestions to develop future works with this methodology.

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Section: Author Abstract Co-occurrence Networkmentioning

confidence: 99%

Google Earth Engine: A Global Analysis and Future Trends

et al. 2023

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Mapping flooded areas utilizing Google Earth Engine and open SAR data: a comprehensive approach for disaster response

Singh,

Rawat

2024

Discov Geosci

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One of the most destructive and frequent natural disasters in the world, flash floods cause millions of people to be displaced annually in addition to seriously harming livelihoods and infrastructure. It affects many ecological components and applications related to water management, natural resources, agriculture, human health, and economics. Himachal Pradesh saw an unprecedented amount of rainfall in June and July 2023, which resulted in exceptionally strong monsoon conditions from July 7 to July 10. Operating out of the Meteorological Centre in Shimla, the India Meteorological Department reported widespread, unusually heavy rainfall throughout the state during this time. Cloud cover often obstructs optical satellite data during the monsoon season, which has led to the investigation of alternate techniques for mapping floods. the whole satellite image processing process was carried out using Google Earth Engine (GEE). The Kangra District's 5739 km2 area was chosen as the study's area of interest. In these circumstances, traditional methods of mapping and monitoring flood-prone areas frequently fall short because of poor visibility and overcast skies during bad weather. Technology such as Synthetic Aperture Radar (SAR) becomes a ray of hope during these desperate times. When SAR data is combined with Google Earth Engine, it becomes even more user-friendly. Using SAR data and the powerful cloud processing platform Google Earth Engine (GEE), this study suggests a flood mapping technique. When it comes to mapping flood areas, the strength of SAR data and GEE surpasses boundaries and challenges. It is evidence of both technological advancement and human inventiveness. Such tools are more critical than ever as the world deals with the increasing effects of climate change and the rising frequency of extreme weather events.

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