Detecting Landscape Changes in High Latitude Environments Using Landsat Trend Analysis: 1. Visualization

Remote Sensing

Robert H. Fraser⁷  Ian Olthof⁷  Steven V. Kokelj²  Trevor C. Lantz⁶  Denis Lacelle³  Alexander Brooker³  Stephen Wolfe⁴  Steve Schwarz¹  Santonu Goswami⁵ 

[1] NWT Centre for Geomatics, Government of the Northwest Territories, Yellowknife, NWT X1A3S8, Canada; E-Mail:;Northwest Territories Geoscience Office, Yellowknife, NT X1A2L9, Canada; E-Mail:;Department of Geography, University of Ottawa, Ottawa, ON K1N6N5, Canada; E-Mails:;Geological Survey of Canada, Natural Resources Canada, Ottawa, ON K1A0E8, Canada; E-Mail:;Canada Centre for Mapping and Earth Observation (CCMEO), Natural Resources Canada, Ottawa, ON K1S5K2, Canada; E-Mail;School of Environmental Studies, University of Victoria, Victoria, BC V8W2Y2e, Canada; E-Mail:;Canada Centre for Mapping and Earth Observation (CCMEO), Natural Resources Canada, Ottawa, ON K1S5K2, Canada; E-Mail:

关键词: arctic;    change detection;    image stacks;    disturbance;    lakes;    slumps;    fires;    environmental monitoring;    cumulative impacts;   

DOI  :  10.3390/rs61111533

来源: mdpi

【 摘 要 】

Satellite remote sensing is a promising technology for monitoring natural and anthropogenic changes occurring in remote, northern environments. It offers the potential to scale-up ground-based, local environmental monitoring efforts to document disturbance types, and characterize their extents and frequencies at regional scales. Here we present a simple, but effective means of visually assessing landscape disturbances in northern environments using trend analysis of Landsat satellite image stacks. Linear trends of the Tasseled Cap brightness, greenness, and wetness indices, when composited into an RGB image, effectively distinguish diverse landscape changes based on additive color logic. Using a variety of reference datasets within Northwest Territories, Canada, we show that the trend composites are effective for identifying wildfire regeneration, tundra greening, fluvial dynamics, thermokarst processes including lake surface area changes and retrogressive thaw slumps, and the footprint of resource development operations and municipal development. Interpretation of the trend composites is aided by a color wheel legend and contextual information related to the size, shape, and location of change features. A companion paper in this issue (Olthof and Fraser) focuses on quantitative methods for classifying these changes.

【 授权许可】

CC BY   
© 2014 by the authors; licensee MDPI, Basel, Switzerland.