Special Issue "Earth Observation Technology Cluster: Innovative Sensor Systems for Advanced Land Surface Studies"
A special issue of Remote Sensing (ISSN 2072-4292).
Deadline for manuscript submissions: closed (30 November 2012).
Interests: remote sensing; land cover classification; scales of observation; environmental applications
Interests: Remote Sensing; Earth observation; Ecology; Biogeography; Earth System Science
This special issue focuses on innovative technology used in remote sensing of the terrestrial or land surface. The Earth Observation Technology Cluster is an initiative to promote development and communication in this field (www.eotechcluster.org.uk). The observation or measurement of some property of the land surface is central to a wide range of scientific investigations conducted in many different disciplines, and in practice there is much consistency in the instruments used for observation and the techniques used to map and model the environmental phenomena of interest. Using remote sensing technology as a unifying theme, this initiative provides an opportunity for presentation of novel developments from, and cross-fertilisation of ideas between, the many and diverse members of the terrestrial remote sensing community. The scope of the special issue covers the full range of remote sensing operation, from new platform and sensor development, through image retrieval and analysis, to data applications and environmental modelling. Example topics include novel remote sensing platforms such as unmanned aerial vehicles; emerging instrumentation such as fourier transform infrared spectroscopy and terrestrial LiDAR; modern image retrieval and storage techniques such as networked data transmission and distributed computing; new image analysis and modelling approaches such as hypertemporal observation; and contemporary and significant application areas such as circumpolar and cryospheric remote sensing. Research papers and innovative review papers are invited on any topic under the broad theme of technological developments in remote sensing of the land surface.
Dr. Paul Aplin
Dr. Doreen Sandra Boyd
Dr. Alison Marsh