The mapping of natural and semi-natural habitats is increasingly required in environmental policies, as well as in spatial planning, land management, and the designation of protected areas. Habitats are effective indicators of biodiversity and their periodic and consistent monitoring, in terms of extent, status, and changes can provide an effective tool for policy makers engaged in the conservation plans. This is in accordance with the GEO strategies planned for 2016–2025 period and the attainment of SDG 15 for preserving biodiversity and ecosystem sustainability.
Remote sensing data and techniques offer significant opportunities for long-term habitats monitoring because of the availability of a large amount of multi-temporal data from past and current spaceborne missions with continuity provided by planned future missions. Routinely, mapping can be generated and intra-annual and inter-annual changes quantified providing synoptic spatial views of expansive landscapes and regions from the integration of remote sensed (RS) data with in situ and ancillary data.
Due to the great relevance and interest in this theme, there are a great deal of questions to be answered concerning, for example, the best methods and standards to use in acquiring and processing data, habitat classification terms and systems, as well as the reliability of the maps produced depending on the scale adopted, this Special Issue is inviting manuscripts on the following topics:
- RS data and techniques for identification, mapping, and assessment of different habitat types, their conditions and/or conservation, at different spatial and temporal scales;
- Remote sensing and habitats characterization for different marine and terrestrial environments, from coastal areas to mountain regions, from large, homogenous, and spatially continuous units to highly fragmented, heterogeneous and spatially discontinuous landscapes (e.g., mosaics);
- Satellite time series analysis for long-term habitat mapping;
- Habitat change maps from RS data;
- Integration of RS data with in situ data and expert knowledge;
- Habitat taxonomies and semantics in a framework of integration of RS data and in situ data;
- Indicators from RS data for the habitat modeling.
Dr. Cristina Tarantino (CNR)
Dr. Maria Adamo (CNR)
Dr. Valeria Tomaselli (CNR)
Deadline for manuscript submission: 31 January 2021