Spatial mapping using electromagnetic (EM) conductivity can quickly define past sedimentary environments within meandering river floodplain settings and, most important, those most likely to include archaeological materials. Natural levee and uplifted fluvial terrace environments would have been the most likely areas for people to place permanent settlements, as these topographically high areaswould have remained dry during most annual floods.The spatialpatterning of high andlow electrical conductivity regions, when combined with geological core and auger information, can define a number of depositional environments in floodplains including channels, point bars, natural levees and oxbow lakes.Conductivity maps can then be used to predict the locations of prehistoric floodplain environments, and therefore the most likely locations for archaeological remains. Suitable areas can then be further tested for archaeological features using detailed geophysical surveys and other archaeological survey methods. Case studies are presented from California,Texas and Mississippi that integrate these methods fordepositionalenvironment mapping as awayofaccessing the archaeological potential in meandering river floodplains.

Ground-penetrating radar (GPR) lags behind other archaeogeophysical methods in terms of speed, efficiency and ability to produce clean site-wide composites owing to complex and time-consuming data processing requirements.Two North American case studies illustrate problems that occur when survey is conducted over long and short periods of time. Some GPR defects have been blamed on differential solar heating of antennae and battery power levels but we show these effects to be negligible. Major problems include gradual changes over time in ground moisture and low-level background noise, which can create discontinuities between adjacent survey blocks when data are collected at different times. These problems are often remedied by globally aligning traces using a stable trace position.Variations in ground moisture through time also cause differences in reflection amplitudes, necessitating different range gain curves to match amplitudes between survey blocks. In some cases changes in ground moisture cause noticeable differences in velocity between survey blocks requiring time-scales to be converted to depths to correctly match the data.These problems must be remedied before horizontal slicing can be considered. Subsequent image processing may also be necessary to generate a seamless mosaic and eliminate striping artefacts commonly seen in slicemaps.Thelatterareprobablycausedbyantennalift andtilt and can beremovedbya de-striping algorithmthatusesaone-dimensionallow-passfilter to characterize stripesfollowedby their subtraction from the data.

When multiple geophysical methods are used to survey an archaeological site, an integrated approach to interpreting the data is often pursued. The use of supervised and unsupervised classification methods are tested using ground-penetrating radar, magnetometry and magnetic susceptibility data sets from a site in the American Southwest. Pueblo Escondido was a large prehistoric village associated with the Mogollon culture in southern New Mexico, with peak occupation during the transition between pithouse and pueblo architectural periods (ca. 1280-1290 AD). Image classification has the benefit of producing unambiguous discrete maps and capitalizes on the multivariate relationships between data sets. Theoretically, unsupervised classification could identify new archaeological classes that were not anticipated but no such classes were identified. The K-means cluster analysis succeeded only in identifying weak, moderate and strong positive anomalies found in the original data sets. Supervised classification utilizing Mahalanobis distance produced much better results. Training sites based on archaeological excavations were used to classify all locations in the survey area, yielding a predictive model of archaeological features in three classes, plus a background class. The result shows features that were not easily identified in the original data sets but are made visible by the multivariate model. The model could be used for guiding future excavations and arguably leads to a better understanding of the site's subsurface content and spatial organization.

It has long been suggested that the near field zone in GPR data contains no usable information, and should be ignored.This paper shows that there can be usable information in the near-field zone when accurate time-zero is chosen, and near-surface reflections are processed.Reflection data from a Pueblo site in New Mexico were filtered and then re-gained to reveal floors within the upper 3 nanoseconds, and their presence was confirmed by excavation

Past human activities in cultural landscapes are often expressed by subtle variations in surface topography that reflect buried archaeological features.When seen from the air under low sunlight angles, resultant 'shadow marks' form a cornerstone of site detection in aerial archaeology. Past attempts to quantify and map such variations across large archaeological landscapes have resorted to aerial photogrammetry, electronic totalstations, air-and ground-basedlidar, and kinematic globalpositioning systems. The most commonly used surveying instrument is the total station, but its slow rate of data acquisition makes it poorly suited for collecting vast amounts of elevation data over large areas, althoughit isoftenused for that task.A robotic total station, examined here, is arelativelynew technology that provides a rapid survey solution. It requires only a single person to operate the total station by radio linkage from a control pad affixed to a wheeled reflector rod. As the rod is rolled over the landscape it is automatically tracked, and measurements of surface topography may be acquired to subcentimetre accuracy continuously, at a rate of one measurement per second. A case study from the Double Ditch State Historic Site in the Great Plains of North Dakota, a fortified earthlodge village with culturallysignificant surface expressions, exemplifiesthispotential.Thelociofprehistorichouses, borrow pits, fortification ditches, middens and defensive mounds are clearly revealed in the topographic mapping