Special Issue "Monitoring of Land Changes"
A special issue of Remote Sensing (ISSN 2072-4292).
Deadline for manuscript submissions: closed (31 May 2016).
Interests: Remote Sensing; Mapping; Climate change; Machine learning; vegetation species detection
Special Issues and Collections in MDPI journals
Interests: remote sensing methodology for carbon balance estimation; monitoring of African drylands; spectral measurements for calibration/validation; satellite time series analysis for seasonality information and smoothing of remotely sensed data; forest disturbances research using remotely sensed data
Humankind has changed the land cover throughout its existence by different land uses, but also by contributing to climate variations around the world. Remote sensing is the most cost-efficient method to monitor land cover and land uses changes, as well as impacts of climate change, which may be identified as glacier changes, changes in vegetation phenology or advance of new plant species to higher latitudes or elevations, for example. In addition to “traditional” satellite imagery to cover large areas we can also use advanced hyperspectral remote sensing data or laser scanning data for land change studies.
Fairly long time-series of Earth Observation data already exist for the whole area of the Earth. These time-series data make up an invaluable source of information for better understanding and management of our environment. It is a challenge and a critical need to understand the methods for extracting useful information from the data, as well as to interpret the time-series signals correctly. We need to be able to interpret both slow variations due to gradual ecosystem transformations, and faster variations due to disturbances or other rapid events. Methods based on remote sensing theory, process modelling, and statistical data analysis will help developing this understanding.
This Special Issue aims to review and synthesize the latest progress in land change monitoring using various remote sensing data types for various purposes. Prospective authors are invited to contribute to this Special Issue of Remote Sensing by submitting an original manuscript. Contributions may focus on, but are not limited to:
- Theoretical aspects of remote sensing of land change (land use/land cover)
- Methodological aspects in data processing
- Phenological studies of vegetation and agricultural areas
- Use of satellite imagery time series
- Long-term and short-term variations
- Land change monitoring in agriculture, forestry, grassland management
- Linking land change to climate change
- Urban studies
- Cryospheric land cover monitoring (water, snow, sea ice, glaciers)
Prof. Petri Pellikka
Prof. Lars Eklundh
Manuscript Submission Information
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. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short 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 thoroughly refereed through a single-blind 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 semimonthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2000 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.