Kenya turns to earth observation technology to monitor forests

Source: Xinhua| 2019-02-26 19:29:59|Editor: xuxin
Video PlayerClose

NAIROBI, Feb. 26 (Xinhua) -- Kenya has resorted to the use of earth observation technology in order to enhance monitoring of degraded forests, an official said on Tuesday.

Jamleck Ndambiri, project manager at the Kenya Forest Service (KFS), said that earth observation technology will help protect and restore tropical forests through better monitoring.

"With the help of satellite data acquisition, ground verification and processing, we intend to assess and monitor national forest cover by mapping previously hard-to-assess forest areas more accurately and timely," said Ndambiri.

Ndambiri noted that parts of Kenya, particularly the coastal and western regions, experience persistent cloud cover for most of the year, due to their proximity to the Indian Ocean and Lake Victoria water bodies, respectively.

"We have relied on expensive and time-consuming ground surveys to assess and undertake inventory of our forests over the years but this has not worked well," said Ndambiri.

The official said that local personnel have been trained from several relevant institutions and disciplines to use the new computing technologies.

He noted that a national Geographic Information System lab has been established.

Ndambiri said that Kenya forest mapping project targets some 2,039 square kilometers of Kwale County as a pilot.

"This is a pilot run to develop a competent methodology that, if successful, could be replicated in the whole coastal region and other areas with persistent cloud cover," said Ndambiri.

The project is also doing biomass pilot study of Kenya's dryland forests and levels of degradation in the 1, 200 square-kilometer Cherangani forest in Rift Valley, northwestern Kenya.

KFS plans to roll out the tool for use at a national scale for forest and biomass monitoring as part of efforts to help increase the forest cover from the current seven percent to 10 percent.

TOP STORIES
EDITOR’S CHOICE
MOST VIEWED
EXPLORE XINHUANET
010020070750000000000000011100001378521911