Archaeology is a discipline influenced by emerging cultural trends, especially with regard to theoretical approaches to interpretation and practice. Public archaeology is a relatively young approach, still finding its feet, and loose definitions of it have opened the door to multiple perspectives and opportunities. When research agendas include the issue of public engagement, we need to approach our practices critically from the beginning, and consider the consequences of 'doing' public archaeology. Moving beyond an understanding of the theoretical backdrop to our work, we first need to situate our work socially, politically and economically. This article will bring necessary critique to some current trends in public archaeology, proposing that commitment to sustainability, inclusivity and ethics are the basis for a responsible practice. Trends in public archaeologyPublic archaeology can be defined as both a disciplinary practice and a theoretical position, which can be exercised through the democratization of archaeological communication, activity or administration, through communication with the public, involvement of the public or the preservation and administration of archaeological resources for public benefit by voluntary or statutory organizations. Broadly understood as a sub-discipline, public archaeology is as much Lorna-Jane Richardson and Jaime Almansa-Sánchez are current co-chairs of the Working Group in Public Archaeology at the European Association of Archaeology.World Archaeology Vol. 47(2): 194-211 Public Archaeology This article was originally published with errors. This version has been amended.Please see Corrigendum (http://dx.

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The new very high-resolution space satellite images, such as QuickBird and Ikonos, open new possibilities in cartographic applications. This work has as its main aim the assessment of a methodology to achieve the best possible geometric accuracy in orthorectified imagery products obtained from QuickBird basic imagery which will include an assessment of the methodology's reliability. Root Mean Square Error (RMSE), mean error or bias, and maximum error in 79 independent check points are computed and utilized as accuracy indicators. The ancillary data were generated by high accuracy methods: (a) check and control points were measured with a differential global positioning system, and (b) a dense digital elevation model (DEM) with grid spacing of 2 m and RMSE z of about 0.31 m generated from a photogrammetric aerial flight at an approximate scale of 1:5000 that was used for image orthorectification. Two other DEMs with a grid spacing of 5 m (RMSE z = 1.75 m) and 20 m (RMSE z = 5.82 m) were also used. Four 3D geometric correction models were used to correct the satellite data: two terrain-independent rational function models refined by the user, a terrain-dependent model, and a rigorous physical model. The number and distribution of the ground control points (GCPs) used for the sensor orientation were studied as well, testing from 9 to 45 GCPs. The best results obtained about the geometric accuracy of the orthorectified images (two dimensional RMSE of about 0.74 m) were computed when the dense DEM was used with the 3D physical and terrain-dependent models. The use of more than 18 GCPs does not improve the results when those GCPs are extracted by stratified random sampling.

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