Big data helps protect Yunlong Tianchi Nature Reserve

From paper reports submitted by rangers and analyzed by professional software, to today’s patrol assistant APP, the real-time positioning of resource data information, acquisition and network transmission and big data analytics are gradually realized in the nature reserve

“Open the patrol assistant app and input data on found animals and plants, the longitude, latitude, altitude and other geographical information will generate automatically. What I need to do is to upload the information timely.”Zhang Zhiyun, a professional administrator of Yunlong Tianchi National Nature Reserve in Yunnan, showed the app to the reporter.

“The patrol assistant APP is a patrol and management system developed jointly with Yunnan University. In recent years, we have been devoted to building a digital nature reserve. Through big data analysis we continuously improve the management tools and methods,” said Xu Huiming, head of the research institute of the Nature Reserve.

Yunlong Tianchi Nature Reserve has 15 professional forest administrators and 27 forest guards. In April, the Management and Protection Bureau equipped each ranger with a patrol monitoring terminal for timely recording and transmission of information obtained during their patrols.

“The information collected is mainly on various animals and plants, ecological environment, human disturbance and information related to protection. Professional analytics and studies are conducted on the collected data to provide more accurate protection and management,” said Xu Huiming.

In fact, Yunlong Tianchi Nature Reserve started patrol data collection and analytics in 2010. From paper reports submitted by patrollers and analyzed by professional software, to today’s patrol assistant APP, the real-time positioning of resource data information, acquisition and network transmission and big data analytics are gradually realized.

According to monitoring data over the past years, the black bear activities were predicted and alerts were given to avoid casualties and reduce property losses.Through analytics of the patrol data from 2011 to 2014, they made rational adjustments to patrol area to make the patrol more scientific and efficient.(Cheng Sanjuan) 

Editor: Eric Wang