Investigation of the High Mountain Vegetation Using Satellite Imagery, Kyrgyzstan

Author(s):  
Zheenbek E. Kulenbekov ◽  
Sagynbek Zh. Orunbaev ◽  
Baktyiar D. Asanov
2015 ◽  
pp. 96-124
Author(s):  
E. G. Zibzeev ◽  
T. A. Nedovesova

The mountain systems are characterized by diverse ecological conditions (climate, geomorphological, soil, etc.). The wide spectrum of environmental conditions entails a rich diversity of plant communities growing on the small territory and determines the different flora and vegetation geneses. The uniqueness of floristic and coenotic diversities of the high-mountain vegetation of the south of Western Altai (Ivanovskiy, Prokhodnoi, and Rossypnoi Ranges) are associated with the effect of two climate-forcing factors such as the westerly humid air mass and dry warm airflow from the inner Kazakhstan regions. The paper summarizes the data on coenotic diversity (Zibzeev, 2010, 2012) and gives a syntaxonomic analysis of the high-mountain vege­tation in the Ivanovskii, Prokhodnoi, and Rossypnoi Ranges (Western Altai, Kazakhstan). The classification of plant communities was carried out using the Braun-Blanquet approach (Westhoff, van der Maarel, 1973). The relevés records were stored in the TURBOVEG database and classified by ­TWINSPAN (Hill 1979).


2021 ◽  
Vol 38 ◽  
pp. 00102
Author(s):  
Ekaterina Popova ◽  
Evgeniy Sinkovskiy

The paper presents a taxonomic, areographic and belt-andzonal analysis of the high-mountain flora of the Kurai Ridge. The flora of the region in question contains 312 species of plants, referred to 143 genera belonging to 48 families. Analysis of the taxonomic structure of the high-mountain flora of the Kurai Ridge has shown the following most abundant plant families: Asteraceae, Ranunculaceae, and Poaceae. For the variety of the genera, the following genera are predominant: Carex, Pedicularis, Salix, and Oxytropis. The areographic analysis has demonstrated that the said species are of the North Asian (21 %), South Siberian (19.4 %) and Holarctic (17.4 %) origins. Dominant in the belt-and-zonal range are the following species: high-mountain (23.2 %), light-coniferous forest (17.7 %) and Arctic Alpine (17.4 %) species. In general, the composition and structure of the high-mountain flora of the Kurai Ridge are determined by its geographic position at the boundary of Central and South-Eastern Altai and by decrease in the amount of precipitation in the south-eastern direction.


2021 ◽  
Author(s):  
Leif S. Anderson ◽  
William H. Armstrong ◽  
Robert S. Anderson ◽  
Dirk Scherler

<p>Many glaciers in High Mountain Asia are experiencing the debris-cover anomaly. The Kennicott Glacier, a large Alaskan Glacier, is also thinning most rapidly under debris cover. This contradiction has been explained by melt hotspots, such as ice cliffs, streams, or ponds scattered within the debris cover or by declining ice flow in time. We collected abundant in situ measurements of debris thickness, sub-debris melt, and ice cliff backwasting, allowing for extrapolation across the debris-covered tongue. A newly developed automatic ice cliff delineation method is the first to use only optical satellite imagery. The adaptive binary threshold method accurately estimates ice cliff coverage even where ice cliffs are small and debris color varies. We also develop additional remotely-sensed datasets of ice dynamical variables, other melt hot spots, and glacier thinning.</p><p>Kennicott Glacier exhibits the highest fractional area of ice cliffs (11.7 %) documented to date. Ice cliffs contribute 26 % of total melt across the glacier tongue. Although the <em>relative</em> importance of ice cliffs to area-average melt is significant, the<em> absolute</em> area-averaged melt is dominated by debris. At Kennicott Glacier, glacier-wide melt rates are not maximized in the zone of maximum thinning. Declining ice discharge through time therefore explains the rapid thinning. Through this study, Kennicott Glacier is the first glacier in Alaska, and the largest glacier globally, where melt across its debris-covered tongue has been rigorously quantified.</p><p>We also carefully explore the relationship between debris, melt hotspots, ice dynamics, and thinning across the debris-covered tongue. In doing so we reveal a chain of linked processes that can explain the striking patterns expressed on the debris-covered tongue of Kennicott Glacier.</p>


2002 ◽  
Vol 50 (3) ◽  
pp. 217-228 ◽  
Author(s):  
ROSARIO G. GAVILÁN ◽  
DANIEL SÁNCHEZ-MATA ◽  
ADRIÁN ESCUDERO ◽  
AGUSTÍN RUBIO

2020 ◽  
Author(s):  
César Deschamps-Berger ◽  
Simon Gascoin ◽  
Etienne Berthier ◽  
Jeffrey Deems ◽  
Ethan Gutmann ◽  
...  

Abstract. An accurate knowledge of snow depth distribution in mountain catchments is critical for applications in hydrology and ecology. A recent new method was proposed to map the snow depth at meter-scale resolution from very-high resolution stereo satellite imagery (e.g., Pléiades) with an accuracy close to 0.50 m. However, the validation was mainly done using probe measurements which sampled a limited fraction of the topographic and snow depth variability. We deepen this evaluation using accurate maps of the snow depth derived from ASO airborne lidar measurements in the Tuolumne river basin, USA. We find a good agreement between both datasets over a snow-covered area of 137 km2 on a 3 m grid with a positive bias for Pléiades snow depth of 0.08 m, a root-mean-square error of 0.80 m and a normalized median absolute deviation of 0.69 m. Satellite data capture the relationship between snow depth and elevation at the catchment scale, and also small-scale features like snow drifts and avalanche deposits. The random error on snow depth can be reduced by a factor two (up to approximately 0.40 m) when the snow depth map is spatially averaged to a ~ 20 m grid. The random error at the pixel level is lower on snow-free areas than on snow-covered areas, but errors on both terrain type converge at coarser resolutions, which is important for further applications of the method in areas without snow depth reference data. We conclude that satellite photogrammetry stands out as an efficient method to estimate the spatial distribution of snow depth in high mountain catchments.


2018 ◽  
Vol 21 (3) ◽  
pp. 477-487 ◽  
Author(s):  
Marian Cabrera ◽  
Viviana Samboni-Guerrero ◽  
Joost F. Duivenvoorden

2020 ◽  
Vol 14 (9) ◽  
pp. 2925-2940 ◽  
Author(s):  
César Deschamps-Berger ◽  
Simon Gascoin ◽  
Etienne Berthier ◽  
Jeffrey Deems ◽  
Ethan Gutmann ◽  
...  

Abstract. Accurate knowledge of snow depth distributions in mountain catchments is critical for applications in hydrology and ecology. Recently, a method was proposed to map snow depth at meter-scale resolution from very-high-resolution stereo satellite imagery (e.g., Pléiades) with an accuracy close to 0.5 m. However, the validation was limited to probe measurements and unmanned aircraft vehicle (UAV) photogrammetry, which sampled a limited fraction of the topographic and snow depth variability. We improve upon this evaluation using accurate maps of the snow depth derived from Airborne Snow Observatory laser-scanning measurements in the Tuolumne river basin, USA. We find a good agreement between both datasets over a snow-covered area of 138 km2 on a 3 m grid, with a positive bias for a Pléiades snow depth of 0.08 m, a root mean square error of 0.80 m and a normalized median absolute deviation (NMAD) of 0.69 m. Satellite data capture the relationship between snow depth and elevation at the catchment scale and also small-scale features like snow drifts and avalanche deposits at a typical scale of tens of meters. The random error at the pixel level is lower in snow-free areas than in snow-covered areas, but it is reduced by a factor of 2 (NMAD of approximately 0.40 m for snow depth) when averaged to a 36 m grid. We conclude that satellite photogrammetry stands out as a convenient method to estimate the spatial distribution of snow depth in high mountain catchments.


2020 ◽  
Vol 102 ◽  
pp. 103504
Author(s):  
Marian Cabrera ◽  
Joost F. Duivenvoorden

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