Development of farmland drought remote sensing dynamic monitoring system based on Android

doi:10.6046/gtzyyg.2020160

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Abstract

A farmland drought remote sensing dynamic monitoring system has been established on the Android mobile platform in order to meet the actual needs of users for observation of agricultural conditions such as farmland drought. For the problem of inefficiency in traditional manual field recording by users, the system combines the advantages of portable mobile devices and global positioning system (GPS) to realize the digital management of farmland data, and completes a set of processing flow from field data entry, processing to export. With the purpose of real-time drought dynamic monitoring, the system uses the massive remote sensing data management and powerful calculating ability advantages provided by the Google Earth Engine remote sensing cloud computing platform, utilizes multi-source remote sensing data such as Landsat, MODIS and Sentinel, applies the Flask framework to implement the Google Earth Engine platform Python service interface access scheme, and completes the function of dynamic drought monitoring for farmland, which provides users with a technical application platform for selecting the remote sensing data source, calculating the drought monitoring model and finally generating the grade thematic map of drought.

Keywords farmland drought dynamic monitoring Android cloud computing platform Flask

ZTFLH:

TP79

Corresponding Authors: QIN Qiming E-mail: longzehao@pku.edu.cn;qmqin@pku.edu.cn

Issue Date: 21 July 2021

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	Zehao LONG
	Tianyuan ZHANG
	Wei XU
	Qiming QIN

Cite this article:

Zehao LONG,Tianyuan ZHANG,Wei XU, et al. Development of farmland drought remote sensing dynamic monitoring system based on Android[J]. Remote Sensing for Land & Resources, 2021, 33(2): 256-261.

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https://www.gtzyyg.com/EN/10.6046/gtzyyg.2020160 OR https://www.gtzyyg.com/EN/Y2021/V33/I2/256

Fig.1 System overall architecture

Fig.2 System service functions

Fig.3 Scheme of farmland drought dynamic monitoring based on GEE platform

Fig.4 Calculation flow of drought monitoring model

Tab.1 GEE platform and flask server-side map service URL template

Tab.2 Remote sensing data source and band of GEE platform used in the system

Fig.5 Farmland data collection and management

Fig.6 Dynamic calculation of MPDI using Sentinel-2 data

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