An application of MODIS data to snow cover monitoring in a pastoral area: A case study in Northern Xinjiang, China

2008 ◽  
Vol 112 (4) ◽  
pp. 1514-1526 ◽  
Author(s):  
T LIANG ◽  
X HUANG ◽  
C WU ◽  
X LIU ◽  
W LI ◽  
...  
2021 ◽  
Vol 973 (7) ◽  
pp. 21-31
Author(s):  
Е.А. Rasputina ◽  
A.S. Korepova

The mapping and analysis of the dates of onset and melting the snow cover in the Baikal region for 2000–2010 based on eight-day MODIS “snow cover” composites with a spatial resolution of 500 m, as well as their verification based on the data of 17 meteorological stations was carried out. For each year of the decennary under study, for each meteorological station, the difference in dates determined from the MODIS data and that of weather stations was calculated. Modulus of deviations vary from 0 to 36 days for onset dates and from 0 to 47 days – for those of stable snow cover melting, the average of the deviation modules for all meteorological stations and years is 9–10 days. It is assumed that 83 % of the cases for the onset dates can be considered admissible (with deviations up to 16 days), and 79 % of them for the end dates. Possible causes of deviations are analyzed. It was revealed that the largest deviations correspond to coastal meteorological stations and are associated with the inhomogeneity of the characteristics of the snow cover inside the pixels containing water and land. The dates of onset and melting of a stable snow cover from the images turned out to be later than those of weather stations for about 10 days. First of all (from the end of August to the middle of September), the snow is established on the tops of the ranges Barguzinsky, Baikalsky, Khamar-Daban, and later (in late November–December) a stable cover appears in the Barguzin valley, in the Selenga lowland, and in Priolkhonye. The predominant part of the Baikal region territory is covered with snow in October, and is released from it in the end of April till the middle of May.


2016 ◽  
Vol 47 (12) ◽  
pp. 3955-3977 ◽  
Author(s):  
Pierfrancesco Da Ronco ◽  
Carlo De Michele ◽  
Myriam Montesarchio ◽  
Paola Mercogliano

2019 ◽  
Vol 2 (3) ◽  
pp. 645-664
Author(s):  
Ann Elias

This article explores the case study of a coal mine that was first tunneled under Sydney Harbour in 1897 but closed in 1931. Specifically, it examines how the history of the mine intersects with aesthetics, race, colonialism, and Indigenous dispossession. Centered on the story of an English mining company that first sought a mine site in a pastoral area of the city, but under public pressure was forced to select instead a grimy working class suburb on the opposite harbor shore, the article argues that environmental aesthetics and tastes in beauty collaborated with extractivism. The argument emerges that economics, art, and aesthetics are inextricably linked in this history and further, that while the mine excited the industrial imagination through the aesthetic of the sublime, and associations with darkness and vastness, it conflicted with colonial settler tastes for the pastoral imagination defined by the aesthetics of the beautiful and its associations with light. The article discusses the context of a settler economy in lands stolen from Indigenous peoples, and how conceptualizations of the sublime and beautiful, as well as dark and light, were aligned with the racialization of the properties of coal and space above and below ground.


2020 ◽  
Vol 12 (21) ◽  
pp. 3577
Author(s):  
Siyong Chen ◽  
Xiaoyan Wang ◽  
Hui Guo ◽  
Peiyao Xie ◽  
Jian Wang ◽  
...  

Seasonal snow cover is closely related to regional climate and hydrological processes. In this study, Moderate Resolution Imaging Spectroradiometer (MODIS) daily snow cover products from 2001 to 2018 were applied to analyze the snow cover variation in northern Xinjiang, China. As cloud obscuration causes significant spatiotemporal discontinuities in the binary snow cover extent (SCE), we propose a conditional probability interpolation method based on a space-time cube (STCPI) to remove clouds completely after combining Terra and Aqua data. First, the conditional probability that the central pixel and every neighboring pixel in a space-time cube of 5 × 5 × 5 with the same snow condition is counted. Then the snow probability of the cloud pixels reclassified as snow is calculated based on the space-time cube. Finally, the snow condition of the cloud pixels can be recovered by snow probability. The validation experiments with the cloud assumption indicate that STCPI can remove clouds completely and achieve an overall accuracy of 97.44% under different cloud fractions. The generated daily cloud-free MODIS SCE products have a high agreement with the Landsat–8 OLI image, for which the overall accuracy is 90.34%. The snow cover variation in northern Xinjiang, China, from 2001 to 2018 was investigated based on the snow cover area (SCA) and snow cover days (SCD). The results show that the interannual change of SCA gradually decreases as the elevation increases, and the SCD and elevation have a positive correlation. Furthermore, the interannual SCD variation shows that the area of increase is higher than that of decrease during the 18 years.


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