eFarm: A Tool for Better Observing Agricultural Land Systems

文献类型： 外文期刊

第一作者： Yu, Qiangyi

作者： Yu, Qiangyi;Shi, Yun;Tang, Huajun;Yang, Peng;Xie, Ankun;Liu, Bin;Wu, Wenbin

作者机构：

关键词： smartphone;human sensing;social sensing;crowdsourcing;agriculture;land use;citizen science

期刊名称：SENSORS （ 影响因子：3.576； 五年影响因子：3.735 ）

ISSN： 1424-8220

年卷期： 2017 年 17 卷 3 期

页码：

收录情况： SCI

摘要： Currently, observations of an agricultural land system (ALS) largely depend on remotely-sensed images, focusing on its biophysical features. While social surveys capture the socioeconomic features, the information was inadequately integrated with the biophysical features of an ALS and the applications are limited due to the issues of cost and efficiency to carry out such detailed and comparable social surveys at a large spatial coverage. In this paper, we introduce a smartphone-based app, called eFarm: a crowdsourcing and human sensing tool to collect the geotagged ALS information at the land parcel level, based on the high resolution remotely-sensed images. We illustrate its main functionalities, including map visualization, data management, and data sensing. Results of the trial test suggest the system works well. We believe the tool is able to acquire the human-land integrated information which is broadly-covered and timely-updated, thus presenting great potential for improving sensing, mapping, and modeling of ALS studies.

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