{"id":840,"date":"2020-09-03T17:45:29","date_gmt":"2020-09-03T17:45:29","guid":{"rendered":"https:\/\/goetzlab.rc.nau.edu\/?p=840"},"modified":"2020-09-03T18:00:39","modified_gmt":"2020-09-03T18:00:39","slug":"from-coffee-tables-to-manhattan-drones-are-an-important-intermediate-step-to-understanding-arctic-greening","status":"publish","type":"post","link":"https:\/\/goetzlab.rc.nau.edu\/index.php\/2020\/09\/03\/from-coffee-tables-to-manhattan-drones-are-an-important-intermediate-step-to-understanding-arctic-greening\/","title":{"rendered":"From coffee tables to Manhattan, drones are an important intermediate step to understanding Arctic greening"},"content":{"rendered":"\n

Drones are an important addition to scientists\u2019 toolkits for measuring global change, concludes new study in Environmental Research Letters<\/em><\/p>\n\n\n\n

\"\"
In between flights, researchers backpack with their equipment plus drone over the spongy tundra of Qikiqtaruk. Credit: Jeff Kerby<\/figcaption><\/figure>\n\n\n\n

A scientist\u2019s toolkit for understanding Arctic vegetation change (primarily driven by Arctic \u201cgreening\u201d) has often relied on two main tools: field work and satellite imagery.<\/p>\n\n\n\n

Field work is highly detailed \u2013 researchers meticulously estimate vegetation cover, measure height, and weigh plants to determine their mass. Scientists come away with detailed and accurate data, but it comes at a price. This work is tedious and time consuming. And, in an area as remote as the Arctic, simply getting to field sites is costly, often involving lengthy flights or grueling hikes across challenging terrain.<\/p>\n\n\n\n

This work is extremely important because of the level of detail it contains \u2013 this data is as close to \u201ctrue\u201d as we can get. However, the scope is small. Field plots are often about the size of a coffee table. Consider the vastness of the Arctic and you can see why a few coffee tables scattered across the tundra do not capture the full picture.<\/p>\n\n\n\n

At the other extreme is satellite imagery. Using images beamed back to Earth from satellites that orbit constantly, scientists can look at pictures anywhere in the Arctic dating back to the 1980s. This tool provides excellent coverage, but it comes at the price of detail. Pixels from satellite imagery \u201care maybe the size of Manhattan,\u201d says Jeff Kerby, ecologist at Aarhus University in Denmark. These pixels can tell scientists which areas have gotten greener (or browner), but cannot provide much detail about the mechanisms that cause the greening.<\/p>\n\n\n\n

It is a big leap from detailed data the size of a coffee table, to a single \u201cgreenness\u201d value representing an area the size of Manhattan. \u201cYou end up with that gap in between,\u201d said Andrew Cunliffe, research fellow at the University of Exeter in the United Kingdom. In a new study in Environmental Research Letters, Cunliffe and his colleagues suggest drones might be the key to bridging this gap in scale and scope.<\/p>\n\n\n\n

Drones are relatively portable and inexpensive. Scientists can bring them to the field with them and collect imagery as they conduct field work. The result is an expanded view of the field site, the size of several football fields as opposed to a single coffee table. And the resolution is impressive too \u2013 scientists can obtain imagery with pixels as small as a single centimeter. This makes drones an important \u2018middle man\u2019 between field work and satellite imagery. Scientists can use drone imagery to peer inside a single satellite imagery pixel for more detail.<\/p>\n\n\n\n

What\u2019s more, new technology allows researchers to stitch together images from drone flights to create 3D reconstructions of sites. This adds a third dimension of information, not usually afforded by satellite imagery. These structural metrics, along with measures of greenness provide \u201can unprecedented opportunity to monitor changes both in tundra greenness and canopy structure such as canopy height and aboveground biomass,\u201d according to Alemu Gonsamo, a remote sensing vegetation and climate change scientist at McMaster University in Canada.<\/p>\n\n\n\n

GEODE lab members are also excited about drone potential. We in the GEODE lab know that \u201cScale is one of the key issues with remote sensing,\u201d as summed up nicely by GEODE lead Scott Goetz<\/strong>.<\/p>\n\n\n\n

 \u201cThere is tremendous potential for the sort of work that they have done to improve our understanding for what these changes in tundra greenness mean, why they\u2019re happening, and how the Arctic might change in the future,\u201d adds GEODE assistant research professor Logan Berner<\/strong>.<\/p>\n\n\n\n

Read more<\/a> about how Arctic researchers are using drone technology, or head straight to the science<\/a>.<\/p>\n\n\n\n

And check out the GEODE lab’s new drone fleet<\/a>!<\/p>\n","protected":false},"excerpt":{"rendered":"

Drones are an important addition to scientists\u2019 toolkits for measuring global change, concludes new study in Environmental Research Letters A scientist\u2019s toolkit for understanding Arctic vegetation change (primarily driven by Arctic \u201cgreening\u201d) has often relied on two main tools: field work and satellite imagery. Field work is highly detailed \u2013 researchers meticulously estimate vegetation cover, … <\/p>\n

Continue reading “From coffee tables to Manhattan, drones are an important intermediate step to understanding Arctic greening”<\/span><\/a><\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":[],"categories":[1],"tags":[],"_links":{"self":[{"href":"https:\/\/goetzlab.rc.nau.edu\/index.php\/wp-json\/wp\/v2\/posts\/840"}],"collection":[{"href":"https:\/\/goetzlab.rc.nau.edu\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/goetzlab.rc.nau.edu\/index.php\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/goetzlab.rc.nau.edu\/index.php\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/goetzlab.rc.nau.edu\/index.php\/wp-json\/wp\/v2\/comments?post=840"}],"version-history":[{"count":5,"href":"https:\/\/goetzlab.rc.nau.edu\/index.php\/wp-json\/wp\/v2\/posts\/840\/revisions"}],"predecessor-version":[{"id":853,"href":"https:\/\/goetzlab.rc.nau.edu\/index.php\/wp-json\/wp\/v2\/posts\/840\/revisions\/853"}],"wp:attachment":[{"href":"https:\/\/goetzlab.rc.nau.edu\/index.php\/wp-json\/wp\/v2\/media?parent=840"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/goetzlab.rc.nau.edu\/index.php\/wp-json\/wp\/v2\/categories?post=840"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/goetzlab.rc.nau.edu\/index.php\/wp-json\/wp\/v2\/tags?post=840"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}