Digital image-processing activities in remote sensing for earth resources

Nagy, George

doi:10.1109/proc.1972.8879

Cited by 36 publications

(5 citation statements)

References 42 publications

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“…This game-changing visualization approach builds on a surprisingly long history of employing airborne video in EO studies (King, 1995). Indeed, some of the earliest satellite missions such as Landsat 1-3 (Townshend, 1981) used vidicons, a type of cathode-ray tube employed in capturing television images (Nagy and Nagy, 1972); although due to the temporal sampling limitations of the deployed systems, these were basically 2-D image snapshots, i.e. essentially television cameras providing still photographs (Vaughan and Johnson, 1994).…”

Section: High-definition Video From Spacementioning

confidence: 99%

The future of Earth observation in hydrology

McCabe

Rodell

Alsdorf

et al. 2017

Hydrol. Earth Syst. Sci.

372

279

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Abstract. In just the past 5 years, the field of Earth observation has progressed beyond the offerings of conventional space-agency-based platforms to include a plethora of sensing opportunities afforded by CubeSats, unmanned aerial vehicles (UAVs), and smartphone technologies that are being embraced by both for-profit companies and individual researchers. Over the previous decades, space agency efforts have brought forth well-known and immensely useful satellites such as the Landsat series and the Gravity Research and Climate Experiment (GRACE) system, with costs typically of the order of 1 billion dollars per satellite and with concept-to-launch timelines of the order of 2 decades (for new missions). More recently, the proliferation of smartphones has helped to miniaturize sensors and energy requirements, facilitating advances in the use of CubeSats that can be launched by the dozens, while providing ultra-high (3-5 m) resolution sensing of the Earth on a daily basis. Startup companies that did not exist a decade ago now operate more satellites in orbit than any space agency, and at costs that are a mere fraction of traditional satellite missions.With these advances come new space-borne measurements, such as real-time high-definition video for tracking air pollution, storm-cell development, flood propagation, precipitation monitoring, or even for constructing digital surfaces using structure-from-motion techniques. Closer to the surface, measurements from small unmanned drones and tethered balloons have mapped snow depths, floods, and estimated evaporation at sub-metre resolutions, pushing back on spatio-temporal constraints and delivering new process insights. At ground level, precipitation has been measured using signal attenuation between antennae mounted on cell phone towers, while the proliferation of mobile devices has enabled citizen scientists to catalogue photos of environmental conditions, estimate daily average temperatures from battery state, and sense other hydrologically important variables such as channel depths using commercially available wireless devices. Global internet access is being pursued via highaltitude balloons, solar planes, and hundreds of planned satellite launches, providing a means to exploit the "internet of things" as an entirely new measurement domain. Such globalPublished by Copernicus Publications on behalf of the European Geosciences Union. The future of Earth observation in hydrology access will enable real-time collection of data from billions of smartphones or from remote research platforms. This future will produce petabytes of data that can only be accessed via cloud storage and will require new analytical approaches to interpret. The extent to which today's hydrologic models can usefully ingest such massive data volumes is unclear. Nor is it clear whether this deluge of data will be usefully exploited, either because the measurements are superfluous, inconsistent, not accurate enough, or simply because we lack the capacity to process and analyse them. What is apparen...

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Section: High-definition Video From Spacementioning

confidence: 99%

The future of Earth observation in hydrology

McCabe

Rodell

Alsdorf

et al. 2017

Hydrol. Earth Syst. Sci.

372

279

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“…In [41], authors attempted to identify between welters of results to get unbeatable achievements also liked hurdles, also to assess the contribution to get expected image-processing operations in experimental and operational usage of the upcoming torrent of raw data.…”

Section: Advancement In Image Processing Computing Visionmentioning

confidence: 99%

An AI & ML Based Detection & Identification in Remote Imagery: State-of-the-Art

Hashmi¹,

Dwivedi²,

Kumar³

2022

JAMRIS

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Remote Imagery and the allied processing have been a matter of curiosity among researchers for a long, and have achieved various fruitful milestones in various facets. From the near past, due to the entrance and buzz of AI & ML based computing, remotely sensed imagery & allied processing technology are growing rapidly and continuously expanding towards multiple important services- like land surveying, traffic surveillance, and various earth science disciplines. As Artificial intelligence has become the charm of researchers, machine learning and deep learning have been proven as the most commonly used and highly effective techniques for object detection. AI & ML based object segmentation &detection makes this area hot and fond to the researchers again with the opportunities of enhanced accuracy in the same. A vast literature is available from a long past till now related to the development of various techniques proposed in this area. In this paper, we have explored the major techniques of image processing for object detection and identification from remote imagery, including the current research directions and future directives. This literature survey is basically focused on analyzing and summarizing the past and recent work done in this field through a chronological sequence of research done for object detection and identification in remotely sensed imagery.

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Section: High-definition Video From Spacementioning

confidence: 99%