Snow Cover Region Detection from a Distance

Hydrology: Current Research

ISSN: 2157-7587

Open Access

Short Communication - (2022) Volume 13, Issue 12

Snow Cover Region Detection from a Distance

Chien Cheng*
*Correspondence: Chien Cheng, Guilin University of Technology, Guilin 541000, China, Email:
Guilin University of Technology, Guilin 541000, China

Received: 01-Dec-2022, Manuscript No. hycr-23-86794; Editor assigned: 03-Dec-2022, Pre QC No. P-86794; Reviewed: 17-Dec-2022, QC No. Q-86794; Revised: 23-Dec-2022, Manuscript No. R-86794; Published: 02-Jan-2023 , DOI: 10.37421.2157-7587.2022.13.444
Citation: Cheng, Chien. “Snow Cover Region Detection from a Distance.” Hydrol Current Res 13 (2022): 444.
Copyright: © 2022 Cheng C. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.


As to environment aridity of the Moroccan Atlas zone, processes overseeing the condition of snowpack and its advancement are very factor both in space and in time, and snow can fall and liquefy in one week or less [1]. To think about the boundaries controlling these changes, it is prescribed to obtain snow and environment data preferably at a high transient and spatial goal [2].


The absence of in situ estimations drove us to utilize remote detecting, particularly optical remote detecting, to concentrate on the spatiotemporal elements of snow cover over the Atlas Mountains. We zeroed in on optical remote detecting since the particular optical properties of snow (high noticeable and low medium infrared reflectance properties) give a precise means to determine the snow cover region [3].

In early works, we fostered a methodology that joins information got from two sorts of instruments: low spatial and high transient goal (SPOT VEGETATION, day to day return to time and pixel size of 1 km2) and high spatial and low fleeting goal (Landsat-TM, 16 days return to time and 30 m pixel size). The methodology comprised of aligning a pixel-based connection between a low-goal multispectral record and a high-goal snow cover region to infer the subpixel snow cover part at low goal. This relationship was then applied to a progression of SPOT-VEGETATION pictures covering the 1998- 2005 period, north of five subwatersheds of the Tensift catchment inside the High Atlas to plan the snow cover region [3].

Quite a while series of SCA covering the 1998-2005 period was created for the five subbasin of the Tensift catchment. These investigations featured areas of strength for the of occasional and interannual SCA starting with one bowl then onto the next connected with the altitudinal and composition impacts. Without a doubt, the snowfall time frame (determined from the date of appearance of snow surfaces until its vanishing) is truly factor: the beginning of the snow season changes between the finish of September and the finish of December, while the last snowfall occasions were recorded between the finish of January and the start of April. The base snow cover heights are roughly 1400 m for wet seasons contrasted with 1800 m for dry seasons [4].

In view of a comparative procedure, a changed standardized contrast snow file (MNDSI) was proposed to determine the SCA. The dissipate plots shows the relationship between's SPOT-VEGETATION and MODIS SCA divisions over the mountain part of the Tensift River bowl during the 2003/2004 snow season. This date-by-date intercomparison uncovers the high relationship between's the two items with a typical R2 coefficient of 0.84 and RMSE of 1.29%.

The unreservedly dispersed snow item assortment given by the National Snow and Ice Data Center got from Moderate Resolution Imaging Spectroradiometer (MODIS) perceptions was evaluated in the quickly changing snow front of the Atlas. With a general precision of 89%, this item was viewed as suitable to portray the high elements of snowpack in the bone-dry to semiarid setting of the Moroccan Atlas Mountains on account of its spatial goal (500 m) and its short return to time(1 day). By the by, it is uncovered that this low spatial goal item isn't proficient in catching the nearby fluctuation of the snow degree, connected with the territory angle impact actuated by sun powered radiation [5].

The high exactness of this item (above 80% snow location for sans cloud pictures) was featured by a few examinations however they likewise brought up two fundamental shortcomings the observing of snow might be exceptionally irregular in regions with high darkness because of a nearby ghostly mark in the noticeable space, a misclassification among snow and mists might prompt up to 12% bogus up-sides (snow identified yet not present) and up to 15% SCA misjudgment. Inside this unique circumstance, a spatiotemporal channel expecting to expand the quantity of usable pictures and to work on the snow/ cloud characterization adjusted for semiarid snow cover was created. The channel decreases the quantity of pixels distinguished as a cloud (accurately or not) by 96% over the Atlas mountain range.


The rectified items were likewise evaluated against five in situ programmed snow profundity stations and a progression of 19 snow-cover maps got from Formosat-2 pictures obtained during winter 2009 over the high Atlas in the Tensift catchment. Concerning great exactness of the rectified items, they have been utilized to portray the snow cover changeability in seven catchments covering the Moroccan Atlas mountain reach to survey the spatiotemporal patterns (utilizing a Mann-Kendall trial of snow-cover regions at the size of all Moroccan catchments with snow-downpour working.

Conflict of Interest



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