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Articles

Use of Landsat TM/ETM+ to monitor the spatial and temporal extent of spring breakup floods in the Lena River, Siberia

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Pages 719-733 | Received 30 Jun 2013, Accepted 25 Oct 2014, Published online: 05 Feb 2015
 

Abstract

A warmer-than-normal air temperature enhances the probability of extreme hydrologic events. A spring breakup flood is among the most serious hydrologic events in high-latitude regions. This study examined the use of Landsat Thematic Mapper/Enhanced Thematic Mapper Plus (TM/ETM+) to monitor the spatial and temporal extent of spring breakup floods in the Lena River, Siberia. Although the 30 m spatial resolution of Landsat produced a detailed mapping of the floodplain, acquisition of Landsat images at short-term intervals was difficult because of the long revisit time of Landsat (16 days) and the frequent cloud cover over Siberia. However, information from two sensors (i.e. TM and ETM+) was combined to essentially halve the revisit time. Moreover, frequent Landsat images were acquired at higher latitudes by using information from overlap areas between neighbouring path images. Therefore, the average revisit time was determined to be 2.6 (= 16/3/2) days in the triple overlap area using two sensors. Updated data sets with a high temporal frequency enhanced the ability to monitor the spatial and temporal extent of the spring breakup floods, although the area was small. In addition, the neighbouring Landsat images themselves were used for large-scale monitoring of breakup floods, given that Landsat overpasses from west to east operating in a near-polar sun-synchronous orbit with a progression speed that is almost the same as the speed of a spring breakup flood. In 2007, spring breakup floods were successively monitored from Solyanka to Yakutsk. Reliable and timely information for large-area monitoring of floods was crucial to understand better the influence on regional hydrology and climate. The images from Landsat TM/ETM+ sensors were regarded as a suitable data source for operational use in flood monitoring due to the wide geographic coverage, high temporal resolution, adequate spatial resolution, and minimal cost.

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