GLIMS DEFINE CODE

The multiannual validation showed accuracy values of 92.81%, 96.32%, 90.32%, 97.56%, and 88.54% for the metrics F1 score, accuracy, kappa, precision, and recall, respectively. We found a more significant percentage loss of glacier areas in countries with less coverage.

In addition, the time-series analysis showed more significant losses at altitudes below 5000 masl, and differentiated changes by slope, latitude, and longitude.

The TAGs reduced from 2429.38 km2 to 1409.11 km2 between 19, representing a loss of 42% of the total glacier area. The results of the multitemporal analysis of this study confirm the recent and dramatic recession of the TAGs in the last three decades, in base to physical and statistical significance. We also implemented temporal and spatial filters to have comparable maps at a multitemporal level and reduce noise and temporal inconsistencies. We used annual reductions of the Normalized Difference Snow Index (NDSI) and spectral bands to capture the pixels with minimum snow cover. This study aims to reconstruct the glacier coverage of the TAGs, using Landsat time-series images from 1985 to 2020, by digitally processing and classifying satellite images in the Google Earth Engine platform. The fast retreat of the tropical Andean glaciers (TAGs) is considered an important indicator of climate change impact on the tropics, since the TAGs provide resources to highly vulnerable mountain populations. Progress, our goal here is to provide a starting point for the GLIMS regional centers as well as for the wider glaciological community in terms of documentation on possible pitfalls along with potential solutions. While the list of proposed methods and recommendations is not comprehensive and is still a work in This paper summarizes the major results of the 2008 GLIMS workshop, with an emphasis on definitions, methods and recommendations for satellite data processing.

GLIMS DEFINE CODE

Special emphasis was given to establishing standard protocols for glacier delineation and analysis, creating illustrated tutorials and providing source code for available methods. Talks presented examples and work in progress for each of these topics, and focus groups worked on compiling a summary of availableĪlgorithms and procedures to address and avoid identified hurdles. This workshop identified six themes for consideration by focus groups: (1) mapping clean iceĪnd lakes (2) mapping ice divides (3) mapping debris-covered glaciers (4) assessing changes in glacier area and elevation through comparisons with older data (5) digital elevation model (DEM) generation from satellite stereo pairs and (6) accuracy and error analysis. Where automatic delineation of glacier boundaries in satellite imagery is difficult, error prone or timeconsuming. Despite the progress made in recent years, there still remain many cases Such accuracy is possible with the increasing volume of satellite imagery of glacierized regions, recent advances in tools and standards, and dedication to this important task.On 16–18 June 2008 the US National Snow and Ice Data Center held a GLIMS workshop inBoulder, CO, USA, focusing on formulating procedures and best practices for operational glaciermapping using satellite imagery. Understanding of glacier extents can become comprehensive and accurate. Current inaccuracies in glacier outlines hinder our ability to correctly quantify glacier change. Applying a simple hypsometry-dependent mass-balance model to different hypsometries results in a b n rate range of −1.0 to −3.1 m a −1 water equivalent (W.E.), a volume change range of −3.8 to −6.7 km 3 a −1 W.E., and a near doubling in contributions to sea level equivalent, 0.011 mm a −1 to 0.019 mm a −1. The use of different BGS hypsometries results in highly variable measures of volume change and net balance ( b n). We compared this new hypsometry with three different hypsometries to illustrate the errors that result from the widely varying estimates of BGS extent. Utilizing GLIMS tools and standards we have completed a new outline (3630 km 2) and analysis of the area-altitude distribution (hypsometry) of BGS using Landsat images from 20 and a US Geological Survey 15-min digital elevation model. Published measurements of BGS surface area vary from 1740 to 6200 km 2, depending on how the boundaries of this system have been defined.

BGS is a complex glacier system aggregated from multiple drainage basins, numerous tributaries, and many accumulation areas. To illustrate the importance of accurate glacier outlines and the effectiveness of GLIMS standards we conducted a case study on Bering Glacier System (BGS), Alaska. The Global Land Ice Measurements from Space (GLIMS) project has developed tools and methods that can be employed by analysts to create accurate glacier outlines.

Glims define