In this paper we compare the energy efficiency of wireless sensor networks sampling a continuous sensor field in two different types of deployment, which we refer to as the High Density (HDSN) and the Low Density (LDSN) Sensor Network architectures. In the LDSN, a set of sensors with high resolution are critically deployed at sampling locations so that each sample is nearly uncorrelated and is transmitted to the central node in a separate channel. In HDSN, a simple zero-crossing detector is used at each sensor and the sensor field is reconstructed at the central node with the zero-crossing information extracted from the sensors' observations. By proposing a scalable data collection protocol for HDSN, we show that the reconstruction performance of the sensor field at the central processor can be achieved with low complexity at the same bandwidth and energy cost. Therefore, the longevity of the sensors is increased due to the reduced per node energy consumption and the reduced computational energy for the data representation at each sensor. Furthermore, we claim that the system versatility and fault tolerance of HDSN makes it an better alternative to the LDSN architecture.