eFarm: A Tool for Better Observing Agricultural Land Systems.
eFarm: A Tool for Better Observing Agricultural Land Systems.
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eFarm：更好地观察农业土地系统的工具
DOI：
10.3390/s17030453
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发表时间：
2017-02-24
期刊：
影响因子：
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通讯作者：
Wu W
中科院分区：
文献类型：
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作者：
Yu Q;Shi Y;Tang H;Yang P;Xie A;Liu B;Wu W
目前，对农用地系统(ALS)的观测在很大程度上依赖于遥感图像，侧重于其生物物理特征。虽然社会调查捕捉到了社会经济特征，但这些信息没有与肌萎缩侧索硬化症的生物物理特征充分结合，由于在大空间范围内进行这种详细和可比较的社会调查的成本和效率问题，应用受到限制。在本文中，我们介绍了一个基于智能手机的应用程序eFarm：一个众包和人类感知工具，用于在高分辨率遥感图像的基础上收集地块级别的地理标记的ALS信息。我们阐述了它的主要功能，包括地图可视化、数据管理和数据传感。试运行结果表明，该系统运行良好。我们相信，该工具能够获取覆盖面广、更新及时的人地综合信息，从而为改进ALS研究的传感、制图和建模提供了巨大的潜力。
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.