Rstac: An R Package to Access Spatiotemporal Asset Catalog Satellite Imagery

Authors: Simoes, Rolf, de Souza, Felipe Carvalho, Zaglia, Matheus, de Queiroz, Gilberto Ribeiro, dos Santos, Rafael D. C., Ferreira, Karine Reis

Source: 2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS Geoscience and Remote Sensing Symposium IGARSS , 2021 IEEE International. :7674-7677 Jul, 2021

Relation: IGARSS 2021 - 2021 IEEE International Geoscience and Remote Sensing Symposium

China Data Cube (CDC) for Big Earth Observation Data: Lessons Learned from the Design and Implementation

Authors: Yao, Xiaochuang, Liu, Yingbo, Cao, Qianqian, Li, Junjie, Huang, Ruihong, Woodcock, Robert, Paget, Matt, Wang, Jian, Li, Guoqing

Source: 2018 International Workshop on Big Geospatial Data and Data Science (BGDDS) Big Geospatial Data and Data Science (BGDDS), 2018 International Workshop on. :1-3 Sep, 2018

Relation: 2018 International Workshop on Big Geospatial Data and Data Science (BGDDS)

All pixels are useful, but some are more useful: Efficient in situ data collection for crop-type mapping using sequential exploration methods

Authors: Jared Fowler, François Waldner, Zvi Hochman

Source: International Journal of Applied Earth Observations and Geoinformation, Vol 91, Iss , Pp 102114- (2020)

Subject Terms: Agriculture, Machine learning, Classification, Harmonised Landsat Sentinel, Big earth observation data, Field data, Physical geography, GB3-5030, Environmental sciences, GE1-350

File Description: electronic resource

Relation: http://www.sciencedirect.com/science/article/pii/S0303243419311948; https://doaj.org/toc/1569-8432

Access URL: https://doaj.org/article/e1b5edc4a63a4806a706b73f4567e44b

The Austrian Semantic EO Data Cube Infrastructure

Authors: Martin Sudmanns, Hannah Augustin, Lucas van der Meer, Andrea Baraldi, Dirk Tiede

Source: Remote Sensing, Vol 13, Iss 23, p 4807 (2021)

Subject Terms: semantic earth observation data cube, big earth observation data, sematic analysis, explainable artificial intelligence, semantic enrichment, scalable system architecture, Science

File Description: electronic resource

Relation: https://www.mdpi.com/2072-4292/13/23/4807; https://doaj.org/toc/2072-4292

Access URL: https://doaj.org/article/a39e0c03ce9b4fb0bdf38fd332a2f4c5

Satellite Image Time Series Analysis for Big Earth Observation Data

Authors: Rolf Simoes, Gilberto Camara, Gilberto Queiroz, Felipe Souza, Pedro R. Andrade, Lorena Santos, Alexandre Carvalho, Karine Ferreira

Source: Remote Sensing, Vol 13, Iss 13, p 2428 (2021)

Subject Terms: big Earth observation data, data cubes, satellite image time series, machine learning and deep learning for remote sensing, R package, Science

File Description: electronic resource

Relation: https://www.mdpi.com/2072-4292/13/13/2428; https://doaj.org/toc/2072-4292

Access URL: https://doaj.org/article/909f9f01f0dd4ca49c86a124f98d525f

An Overview of Platforms for Big Earth Observation Data Management and Analysis

Authors: Vitor C. F. Gomes, Gilberto R. Queiroz, Karine R. Ferreira

Source: Remote Sensing, Vol 12, Iss 8, p 1253 (2020)

Subject Terms: big Earth observation data, Google Earth Engine, Sentinel Hub, Open Data Cube, SEPAL, JEODPP, Science

File Description: electronic resource

Relation: https://www.mdpi.com/2072-4292/12/8/1253; https://doaj.org/toc/2072-4292

Access URL: https://doaj.org/article/51dbf5c854e943dd89141992ed0bee04

Big Earth Observation Data Integration in Remote Sensing Based on a Distributed Spatial Framework

Authors: Yinyi Cheng, Kefa Zhou, Jinlin Wang, Jining Yan

Source: Remote Sensing, Vol 12, Iss 6, p 972 (2020)

Subject Terms: big earth observation data, remote sensing data integration, distributed storage, ssi model, olc, remote sensing metadata, Science

File Description: electronic resource

Relation: https://www.mdpi.com/2072-4292/12/6/972; https://doaj.org/toc/2072-4292

Access URL: https://doaj.org/article/18ca9711837c4d0ca721709888998ae5

Enabling the Big Earth Observation Data via Cloud Computing and DGGS: Opportunities and Challenges

Authors: Xiaochuang Yao, Guoqing Li, Junshi Xia, Jin Ben, Qianqian Cao, Long Zhao, Yue Ma, Lianchong Zhang, Dehai Zhu

Source: Remote Sensing, Vol 12, Iss 1, p 62 (2019)

Subject Terms: big earth observation data, cloud computing, discrete global grid systems, Science

File Description: electronic resource

Relation: https://www.mdpi.com/2072-4292/12/1/62; https://doaj.org/toc/2072-4292

Access URL: https://doaj.org/article/4279fef202da4624963cde6795a56b2a

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