Special Issue "Remote Sensing of Peatlands"
A special issue of Remote Sensing (ISSN 2072-4292).
Deadline for manuscript submissions: closed (30 October 2013)
Prof. Dr. Florian Siegert
Biology Department II, Ludwig-Maximilians-Universitaet Munich, Grosshadenerstr. 2, 82152 Planegg-Martinsried, Germany
Fax: +49 (0) 89 5902 450
Interests: earth observation; global change; climate change; ecology; biodiversity; nature conservation; natural disasters; digital image processing; remote sensing; Geographical Information system (GIS)
Peat is dead organic matter occurring largely in poorly draining environments. It forms at all altitudes and climates. Peatlands cover only approx. 3% of the global land surface (about 4 million km²) but store one-third of the global soil carbon.
Worldwide peatlands are drained in order to expand agricultural land or for the plantation industry. If peat is drained for agriculture or plantations it quickly decomposes, resulting in large emissions of CO2 and N2O into the atmosphere. Drained and degrading peatlands produce 6% of all global anthropogenic CO2 emissions.
Of special importance in the context of GHG emissions are tropical peat swamp forests because of their huge carbon store. Due to fast conversion to oil palm and other huge emissions results from tropical peatlands.
Remote sensing as an advanced technique has been more and more applied to peatlands studies. This special issue is dedicated to publish state-of-the-art studies on remote sensing in peatlands as well as comprehensive literature reviews.
Prof. Dr. Florian Siegert
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. Papers will be published continuously (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are refereed through a peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Remote Sensing is an international peer-reviewed Open Access monthly journal published by MDPI.
mapping of peatlands drainage
peat carbon store
peat thickness measurements
fires on peatlands
impact of fire, drainage
Article: Monitoring Wetlands Ecosystems Using ALOS PALSAR (L-Band, HV) Supplemented by Optical Data: A Case Study of Biebrza Wetlands in Northeast Poland
Remote Sens. 2014, 6(2), 1605-1633; doi:10.3390/rs6021605
Received: 7 January 2014; in revised form: 21 January 2014 / Accepted: 12 February 2014 / Published: 20 February 2014| Download PDF Full-text (2585 KB) | Download XML Full-text
Article: Empirical Modelling of Vegetation Abundance from Airborne Hyperspectral Data for Upland Peatland Restoration Monitoring
Remote Sens. 2014, 6(1), 716-739; doi:10.3390/rs6010716
Received: 22 November 2013; in revised form: 20 December 2013 / Accepted: 31 December 2013 / Published: 9 January 2014| Download PDF Full-text (6736 KB) | View HTML Full-text | Download XML Full-text
Remote Sens. 2014, 6(1), 521-539; doi:10.3390/rs6010521
Received: 27 September 2013; in revised form: 13 December 2013 / Accepted: 23 December 2013 / Published: 3 January 2014| Download PDF Full-text (3862 KB) | View HTML Full-text | Download XML Full-text
Remote Sens. 2013, 5(12), 6501-6512; doi:10.3390/rs5126501
Received: 16 October 2013; in revised form: 22 November 2013 / Accepted: 28 November 2013 / Published: 2 December 2013| Download PDF Full-text (3155 KB) | View HTML Full-text | Download XML Full-text | Supplementary Files
Article: Quantifying Dynamics in Tropical Peat Swamp Forest Biomass with Multi-Temporal LiDAR Datasets
Remote Sens. 2013, 5(5), 2368-2388; doi:10.3390/rs5052368
Received: 25 March 2013; in revised form: 29 April 2013 / Accepted: 7 May 2013 / Published: 14 May 2013| Download PDF Full-text (6136 KB) | View HTML Full-text | Download XML Full-text
Last update: 17 April 2013