A field survey system for land consolidation based on 3S and speech recognition technology

A field survey system for land consolidation based on 3S and speech recognition technology was developed.Four models were applied to improve the decision-making feasibility of LCFSS.Our system could address a series of practical problems and make complex scene investigation work highly efficient. The main objective of this study is to develop a field survey system for land consolidation based on 3S (geographic information system, GIS; Global Positioning System, GPS; and remote sensing, RS) and speech recognition technology. Field survey in land consolidation is a complex and high-tech process. Traditional survey methods are difficult to use in locating, measuring, recording, and other related tasks. Through 3S and speech recognition technology, Android smart phones could address the aforementioned problems by providing a new method of land information collection. In this study, we present a land consolidation field survey system (LCFSS), which is developed on an Android mobile platform and integrates 3S and speech recognition technology to support the field survey of land consolidation. The proposed system is made advantageous by its low cost, high efficiency, portability, and user-friendliness. To improve the usability and feasibility of the LCFSS for decision making, we develop a data-adaptive development model, data compression model, three-parameter model for coordinate registration, and speech processing model. With the Unified Modeling Language, 5 functional modules and more than 16 application cases are described. On the basis of these models, the functions of system management, data import, project survey, coordinate registration, and data output are implemented by adopting the system architecture with four layers. The key achievement is tested and applied to a land consolidation survey in the provinces of Ningxia, Anhui, Shandong, and others. Results show that the efficiency of land information collection and other functions is improved with the use of the proposed system. Therefore, the approaches and methodology presented in this work could serve as a reference for those who are interested in developing mobile system applications based on 3S and speech recognition technology.