Carbon sequestration service of Mediterranean forest and other wooded land is threatened by their fragile, complex, and highly evolving nature, due to both human disturbances and climate change. Remote-sensing methods for forest biomass estimation have gained increased attention, and substantial research has been conducted worldwide over the past four decades. Yet, the literature body focused on Mediterranean forests is rather limited as a result of their small extent compared to other biomes. We discuss the remote-sensing studies over the Mediterranean forest and other wooded land, discriminating research based on the primary data source used, such as optical imagery, datasets from active sensors, and combination of multisource data. The review indicates that there is a significant research gap in terms of the studies, as well as a need for a reduction of the errors and uncertainty of estimates, which are associated with both the sensors’ characteristics and the Mediterranean forest and other wooded land structure. Biomass estimates based on optical data were generally less accurate (R² close to 0.70, where R² is the coefficient of determination), however, when data from active sensors were involved, accuracy of estimations was considerably greater (usually R² greater than 0.80). With respect to scale, most of the local scale studies established relationships with R² over 0.70 and as high as 0.98, while the few regional scale studies exhibited R² close to 0.80. Further, in-depth analysis can provide more efficient data fusion, classification methods, and procedures for operational regional and national assessment of forest biomass over such Mediterranean areas.

Forest fires constitute a natural disturbance factor and an agent of environmental change with local to global impacts on Earth’s processes and functions. Accurate knowledge of forest fuel extent and properties can be an effective component for assessing the impacts of possible future wildfires on ecosystem services. Our study aims to evaluate and compare the spectral and spatial information inherent in the EO-1 Hyperion, Quickbird and Landsat TM imagery. The analysis was based on a support vector machine classification approach in order to discriminate and map Mediterranean fuel types. The fuel classification scheme followed a site-specific fuel model within the study area, which is suitable for fire behavior prediction and spatial simulation. The overall accuracy of the Quickbird-based fuel type mapping was higher than 74% with a quantity disagreement of 9% and an allocation disagreement of 17%. Both classifications from the Hyperion and Landsat TM fuel type maps presented approximately 70% overall accuracy and 16% allocation disagreement. The McNemar’s test indicated that the overall accuracy differences between the three produced fuel type maps were not significant (p < 0.05). Based on both overall and individual higher accuracies obtained with the use of the Quickbird image, this study suggests that the high spatial resolution might be more decisive than the high spectral resolution in Mediterranean fuel type mapping.

Transhumance, the seasonal movement of herds between highlands and lowlands following precise, repeated routes, is a common practice in many Mediterranean regions. This livestock movement exploits natural vegetation in both winter and summer pastures. In Greece transhumant herders, drawn by relatively abundant vegetation, usually relocate to mountainous areas between April and October. Mount Vermio was an ideal summer pasture for the nomadic, ethnic group Sarakatsanoi of Thessaly, who used to own big herds. Socio-economic conditions of the 20th century led to the gradual decline of transhumance, resulting in reduction in grazing pressure and changes in vegetation dynamics. The purpose of this study was to monitor changes in landscape patterns in response to transhumance abandonment. Landscape metrics were employed to estimate land use/cover in two altitudinal zones. Results reveal that due to the abandonment of transhumance in the highlands landscape fragmentation increased. Meanwhile, in the lowlands, due to the uninterrupted presence of animals, landscape structure is more stable and diversified. Grasslands and agroforestry systems became smaller and more isolated. In conclusion, the abandonment of transhumance led to the overall deterioration of the rural landscape in the highlands.

Transhumant flocks graze the vegetation of medium and high elevation rangelands during late spring to autumn depending on the geographical area and climatic conditions. This study aimed to assess and interpret the impacts of transhumance decline on the land use/cover on Mountain Vermio, for the period 1985-2009. For many years, this area has received high stocking rates from transhumant livestock. However, during the last 30 years transhumance has been dramatically decreased. Land cover changes have been identified using a post classification comparison approach within a Geographical Information Systems environment. Moreover, the rate and the spatial differentiation of land use/cover were determined by means of the Dynamic Degree Index. According to the results, the acreage of grasslands and grazed open forests has decreased during the study period (3% and 83% respectively), while shrublands demonstrated an opposite trend with an increase of 25%. Furthermore, based on the Dynamic Degree Index, the greatest changes occurred in the conversion of grazed open forests and shrublands, compared to other land use/cover categories. This can be attributed to changes in sheep and goats populations grazing in the area, also related to the dispersion of flocks in local rangelands. Moreover, this article presents the results of a questionnaire survey on transhumant herders. These results, combined with the assessment of changes in the Dynamic Degree Index, reflect the difficulties that farmers face in terms of access to rangelands and their increased awareness regarding the environmental role of transhumance.