title: eFarm: A Tool for Better Observing Agricultural Land Systems.
abstract: 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.
authors.affiliation: Key Laboratory of Agricultural Remote Sensing (AGRIRS), Ministry of Agriculture/Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing 100081, China. yuqiangyi@caas.cn.
authors.forename: Qiangyi
authors.initials: Q
authors.lastname: Yu
authors.affiliation: Key Laboratory of Agricultural Remote Sensing (AGRIRS), Ministry of Agriculture/Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing 100081, China. shiyun@caas.cn.
authors.forename: Yun
authors.initials: Y
authors.lastname: Shi
authors.affiliation: Key Laboratory of Agricultural Remote Sensing (AGRIRS), Ministry of Agriculture/Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing 100081, China. tanghuajun@caas.cn.
authors.forename: Huajun
authors.initials: H
authors.lastname: Tang
authors.affiliation: Key Laboratory of Agricultural Remote Sensing (AGRIRS), Ministry of Agriculture/Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing 100081, China. yangpeng@caas.cn.
authors.forename: Peng
authors.initials: P
authors.lastname: Yang
authors.affiliation: Key Laboratory of Agricultural Remote Sensing (AGRIRS), Ministry of Agriculture/Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing 100081, China. xieankun@caas.cn.
authors.forename: Ankun
authors.initials: A
authors.lastname: Xie
authors.affiliation: Key Laboratory of Agricultural Remote Sensing (AGRIRS), Ministry of Agriculture/Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing 100081, China. liubin.caas@foxmail.com.
authors.forename: Bin
authors.initials: B
authors.lastname: Liu
authors.affiliation: Key Laboratory of Agricultural Remote Sensing (AGRIRS), Ministry of Agriculture/Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing 100081, China. wuwenbin@caas.cn.
authors.forename: Wenbin
authors.initials: W
authors.lastname: Wu
keywords: agriculture; citizen science; crowdsourcing; human sensing; land use; smartphone; social sensing