Holocene land-cover reconstructions for studies on land cover-climate feedbacks

The major objectives of this paper are: (1) to review the pros and cons of the scenarios of past anthropogenic land cover change (ALCC) developed during the last ten years, (2) to discuss issues related to pollen-based reconstruction of the past land-cover and introduce a new method, REVEALS (Regional Estimates of VEgetation Abundance from Large Sites), to infer long-term records of past land-cover from pollen data, (3) to present a new project (LANDCLIM: LAND cover – CLIMate interactions in NW Europe during the Holocene) currently underway, and show preliminary results of REVEALS reconstructions of the regional land-cover in the Czech Republic for five selected time windows of the Holocene, and (4) to discuss the implications and future directions in climate and vegetation/land-cover modeling, and in the assessment of the effects of human-induced changes in land-cover on the regional climate through altered feedbacks. The existing ALCC scenarios show large discrepancies between them, and few cover time periods older than AD 800. When these scenarios are used to assess the impact of human land-use on climate, contrasting results are obtained. It emphasizes the need for methods such as the REVEALS model-based land-cover reconstructions. They might help to fine-tune descriptions of past land-cover and lead to a better understanding of how long-term changes in ALCC might have influenced climate. The REVEALS model is demonstrated to provide better estimates of the regional vegetation/land-cover changes than the traditional use of pollen percentages. This will achieve a robust assessment of land cover at regional- to continental-spatial scale throughout the Holocene. We present maps of REVEALS estimates for the percentage cover of 10 plant functional types (PFTs) at 200 BP and 6000 BP, and of the two open-land PFTs "grassland" and "agricultural land" at five time-windows from 6000 BP to recent time. The LANDCLIM results are expected to provide crucial data to reassess ALCC estimates for a better understanding of the land suface-atmosphere interactions.

A comparison of pixel and object-based land cover classification. A case study of the Asmara region, Eritrea

In this paper we compare the performance of two image classification paradigms (object- and pixel-based) for creating a land cover map of Asmara, the capital of Eritrea and its surrounding areas using a Landsat ETM+ imagery acquired in January 2000. The image classification methods used were maximum likelihood for the pixel-based approach and Bhattacharyya distance for the object-oriented approach available in, respectively, ArcGIS and SPRING software packages. Advantages and limitations of both approaches are presented and discussed. Classifications outputs were assessed using overall accuracy and Kappa indices. Pixel- and object-based classification methods result in an overall accuracy of 78% and 85%, respectively. The Kappa coefficient for pixel- and object-based approaches was 0.74 and 0.82, respectively. Although pixel-based approach is the most commonly used method, assessment and visual interpretation of the results clearly reveal that the object-oriented approach has advantages for this specific case-study.