Using Ordinary Digital Cameras in Place of Near-Infrared Sensors to Derive Vegetation Indices for Phenology Studies of High Arctic Vegetation

Helen Anderson,Lennart Nilsen,Stein Karlsen,Elisabeth Cooper,Hans Tømmervik,Shin Nagai

doi:10.3390/rs8100847

Abstract

To remotely monitor vegetation at temporal and spatial resolutions unobtainable with satellite-based systems, near remote sensing systems must be employed. To this extent we used Normalized Difference Vegetation Index NDVI sensors and normal digital cameras to monitor the greenness of six different but common and widespread High Arctic plant species/groups (graminoid/Salix polaris; Cassiope tetragona; Luzula spp.; Dryas octopetala/S. polaris; C. tetragona/D. octopetala; graminoid/bryophyte) during an entire growing season in central Svalbard. Of the three greenness indices (2G_RBi, Channel G% and GRVI) derived from digital camera images, only GRVI showed significant correlations with NDVI in all vegetation types. The GRVI (Green-Red Vegetation Index) is calculated as (GDN − RDN)/(GDN + RDN) where GDN is Green digital number and RDN is Red digital number. Both NDVI and GRVI successfully recorded timings of the green-up and plant growth periods and senescence in all six plant species/groups. Some differences in phenology between plant species/groups occurred: the mid-season growing period reached a sharp peak in NDVI and GRVI values where graminoids were present, but a prolonged period of higher values occurred with the other plant species/groups. In particular, plots containing C. tetragona experienced increased NDVI and GRVI values towards the end of the season. NDVI measured with active and passive sensors were strongly correlated (r > 0.70) for the same plant species/groups. Although NDVI recorded by the active sensor was consistently lower than that of the passive sensor for the same plant species/groups, differences were small and likely due to the differing light sources used. Thus, it is evident that GRVI and NDVI measured with active and passive sensors captured similar vegetation attributes of High Arctic plants. Hence, inexpensive digital cameras can be used with passive and active NDVI devices to establish a near remote sensing network for monitoring changing vegetation dynamics in the High Arctic.

Highlights

Recording the changing phenology of vegetation has been a long term aim of many researchers in efforts to understand ecosystem processes and the drivers of environmental change [1]
Derived from red-green-blue wavelength (RGB) images to record changes in plant greenness during the growing season by comparison with Normalised Difference Vegetation Index (NDVI) values obtained from the Decagon and Greenseeker devices
We found the best result with the RGB derived GRVI, which was significantly and strongly correlated with NDVI values despite fluctuations in the RGB camera derived index

Summary

Introduction

Recording the changing phenology of vegetation has been a long term aim of many researchers in efforts to understand ecosystem processes and the drivers of environmental change [1]. Field-based manual phenological observations in Arctic, Antarctic and alpine areas have been ongoing for a number of years at single sites [10,11] and multiple sites through coordinated networks such as the International Tundra Experiment [12,13]. Such traditional approaches can be problematic due to the time constraints imposed by short summer periods, the highly labour-intensive nature of the work, high financial costs and difficulties in accessing remote locations

Methods

Results

Discussion

Conclusion