#GLIMS DEFINE CODE#

In comparison, the remaining 43.36% could be explained by the physical properties of glaciers themselves (i.e., degree-day factor on ice, degree-day factor on snow, glacier median height, aspect, and slope). The least absolute shrinkage and selection operator (LASSO) and random forest techniques were used to explore the contributions of climate factors and glacier physical properties to GR, and the results indicated that climate factors could explain 56.64% of the variation.

Most basins had continuously increasing tendencies of different magnitudes from 1961 to 2015. In this study, GR, including glacier meltwater runoff (MR) and delayed water runoff (DR) of the DAC, was quantitatively assessed at a catchment scale from 1961 to 2015. This study uses the regional individual glacier mass balance (GMB) dataset developed by digital elevation models (DEMs) to simulate the spatiotemporal regime of GR using atmospheric parameters considering both ablation and accumulation processes on glaciers. Due to the difficulty of observing GR, little attention has been given to the spatiotemporal change in GR at regional scales. The spatiotemporal regimes of glacier runoff (GR) under a warming climate are of great concern, especially in dryland areas in northwestern China (DAC). The results are an essential contribution to understanding the TAGs and guiding policies to mitigate climate change and the potential negative impact of freshwater shortage on the inhabitants and food production in the Andean region. 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

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.

Glims define