scholarly journals The status and decadal change of glaciers in Bhutan from the 1980s to 2010 based on satellite data

2014 ◽  
Vol 55 (66) ◽  
pp. 159-166 ◽  
Author(s):  
Samjwal Ratna Bajracharya ◽  
Sudan Bikash Maharjan ◽  
Finu Shrestha
Keyword(s):  
Land Cover ◽  
Image Classification ◽  
Satellite Data ◽  
Glacier Area ◽  
Decadal Change ◽  
Landsat Images ◽  
Equilibrium Line Altitude ◽  
Glacier Inventory ◽  
Object Based ◽  
The Status

AbstractIn order to monitor changes in the glaciers in the Bhutan Himalaya, a repeat decadal glacier inventory was carried out from Landsat images of 1977/78 (~1980), 1990, 2000 and 2010. The base map of glaciers was obtained by the object-based image classification method using the multispectral Landsat images of 2010. This method is used separately to delineate clean-ice and debris-covered glaciers with some manual editing. Glacier polygons of 2000,1990 and ~1980 were obtained by manual editing on 2010 by separately overlaying respective years. The 2010 inventory shows 885 glaciers with a total area of ~642 ± 16.1 km2. The glacier area is 1.6% of the total land cover in Bhutan. The result of a repeat inventory shows 23.3 ± 0.9% glacial area loss between ~1980 and 2010, with the highest loss (11.6 ±1.2%) between ~1980 and 1990 and the lowest (6.7 ±0.1%) between 2000 and 2010. The trend of glacier area change from the 1980s to 2010 is -6.4 ± 1.6%. Loss of glacier area was mostly observed below 5600 m a.s.l. and was greater for clean-ice glaciers. The equilibrium-line altitude has shifted upward from 5170 ± 110 m a.s.l. to 5350 ± 150 m a.s.l. in the years ~1980-2010.

scholarly journals Glacier area and volume changes of Hidden Valley, Mustang, Nepal from ~1980s to 2010 based on remote sensing

2015 ◽  
Vol 368 ◽  
pp. 57-62 ◽  
Author(s):  
L. Lama ◽  
R. B. Kayastha ◽  
S. B. Maharjan ◽  
S. R. Bajracharya ◽  
M. B. Chand ◽  
...  
Keyword(s):  
Automatic Method ◽  
Glacier Area ◽  
Landsat Images ◽  
Change Analysis ◽  
Manual Delineation ◽  
Object Based ◽  
Hidden Valley ◽  
The Status ◽  
Glacier Ice ◽  
Area And Volume

Abstract. Glaciers are one of the important natural resources of freshwater and sources of water for hydropower, agriculture and drinking whenever the water is scarce. This mapping and change analysis helps to understand the status and decadal changes of glaciers in Hidden Valley, Mustang district, Nepal. The investigation is carried out using Landsat images of the years 1977 (~1980s), 1990, 2000 and 2010. We mapped 10 glaciers of the Hidden Valley covering an area of 19.79 km2 based on the object-based image classification method using an automatic method and manual delineation by a Geographic Information System (GIS), separately. The glacier outlines for 2010, 2000, 1990 and 1980s in both methods are delineated from the multispectral Landsat images of the respective years. The total area losses of the glaciers from the automatic method are 1.713 and 0.625 km2 between 1990−2000 and 2000−2010 and from manual delineation are 2.021, 1.264, 1.041 km2 between ~1980s−1990, 1990−2000 and 2000−2010. The amount of average estimated glacier ice reserves lost is 0.326 km3 (26.26 %) and the total glacier area loss is 4.33 km2 (21.87 %) from the 1980s to 2010 based on manual delineation. The glaciers of Hidden Valley are shrinking and fragmented due to decrease in glacier area and ice reserves.

scholarly journals Hyperspectral Imagery Classification Based on Multiscale Superpixel-Level Constraint Representation

2020 ◽  
Vol 12 (20) ◽  
pp. 3342
Author(s):  
Haoyang Yu ◽  
Xiao Zhang ◽  
Meiping Song ◽  
Jiaochan Hu ◽  
Qiandong Guo ◽  
...  
Keyword(s):  
Image Classification ◽  
Satellite Data ◽  
Hyperspectral Image ◽  
Training Sample ◽  
Decision Fusion ◽  
Spatial Constraint ◽  
Hyperspectral Image Classification ◽  
Object Based ◽  
Sparse Coefficient ◽  
The Individual

Sparse representation (SR)-based models have been widely applied for hyperspectral image classification. In our previously established constraint representation (CR) model, we exploited the underlying significance of the sparse coefficient and proposed the participation degree (PD) to represent the contribution of the training sample in representing the testing pixel. However, the spatial variants of the original residual error-driven frameworks often suffer the obstacles to optimization due to the strong constraints. In this paper, based on the object-based image classification (OBIC) framework, we firstly propose a spectral–spatial classification method, called superpixel-level constraint representation (SPCR). Firstly, it uses the PD in respect to the sparse coefficient from CR model. Then, transforming the individual PD to a united activity degree (UAD)-driven mechanism via a spatial constraint generated by the superpixel segmentation algorithm. The final classification is determined based on the UAD-driven mechanism. Considering that the SPCR is susceptible to the segmentation scale, an improved multiscale superpixel-level constraint representation (MSPCR) is further proposed through the decision fusion process of SPCR at different scales. The SPCR method is firstly performed at each scale, and the final category of the testing pixel is determined by the maximum number of the predicated labels among the classification results at each scale. Experimental results on four real hyperspectral datasets including a GF-5 satellite data verified the efficiency and practicability of the two proposed methods.

scholarly journals Histogram Curve Matching Approaches for Object-based Image Classification of Land Cover and Land Use

2013 ◽  
Vol 79 (5) ◽  
pp. 433-440 ◽  
Author(s):  
Sory I. Toure ◽  
Douglas A. Stow ◽  
John R. Weeks ◽  
Sunil Kumar
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Image Classification ◽  
Curve Matching ◽  
Object Based

scholarly journals LAND USE AND LAND COVER MAPPING – A CASE STUDY OF AHMEDABAD DISTRICT

2020 ◽  
Vol XLIII-B3-2020 ◽  
pp. 189-193
Author(s):  
D. Rawal ◽  
A. Chhabra ◽  
M. Pandya ◽  
A. Vyas
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Land Cover ◽  
Image Classification ◽  
Spectral Reflectance ◽  
Land Cover Classification ◽  
Land Cover Mapping ◽  
Classification Algorithms ◽  
Classification Technique ◽  
Object Based

Abstract. Land cover mapping using remote-sensing imagery has attracted significant attention in recent years. Classification of land use and land cover is an advantage of remote sensing technology which provides all information about land surface. Numerous studies have investigated land cover classification using different broad array of sensors, resolution, feature selection, classifiers, Classification Techniques and other features of interest from over the past decade. One, Pixel based image classification technique is widely used in the world which works on their per pixel spectral reflectance. Classification algorithms such as parallelepiped, minimum distance, maximum likelihood, Mahalanobis distance are some of the classification algorithms used in this technique. Other, Object based image classification is one of the most adapted land cover classification technique in recent time which also considers other parameters such as shape, colour, smoothness, compactness etc. apart from the spectral reflectance of single pixel.At present, there is a possibility of getting the more accurate information about the land cover classification by using latest technology, recent and relevant algorithms according to our study. In this study a combination of pixel-by-pixel image classification and object based image classification is done using different platforms like ArcGIS and e-cognition, respectively. The aim of the study is to analyze LULC pattern using satellite imagery and GIS for the Ahmedabad district in the state of Gujarat, India using a LISS-IV imagery acquired from January to April, 2017. The over-all accuracy of the classified map is 84.48% with Producer’s and User’s accuracy as 89.26% and 84.47% respectively. Kappa statistics for the classified map are calculated as 0.84. This classified map at 1:10,000 scale generated using recent available high resolution space borne data is a valuable input for various research studies over the study area and also provide useful information to town planners and civic authorities. The developed technique can be replicated for generating such LULC maps for other study areas as well.

scholarly journals Brief Communication: Updated GAMDAM Glacier Inventory over the High Mountain Asia

2018 ◽  
Author(s):  
Akiko Sakai
Keyword(s):  
Snow Cover ◽  
Cloud Cover ◽  
High Mountain ◽  
Glacier Area ◽  
Landsat Images ◽  
Glacier Inventory ◽  
Final Version ◽  
Seasonal Snow ◽  
Steep Slopes ◽  
Seasonal Snow Cover

Abstract. The first version of the Glacier Area Mapping for Discharge from the Asian Mountains (GAMDAM) glacier inventory was the first methodologically consistent glacier inventory covering High Mountain Asia, and it underestimated glacier area because it did not include steep slopes covered with ice or snow and shadowed areas. During the process of revising the GAMDAM glacier inventory, source Landsat images were carefully selected to find images free of shadows, cloud cover, and seasonal snow cover taken from 1990 to 2010. Then, more than 90 % of the glacier area in the final version of the GAMDAM glacier inventory was delineated based on summer Landsat images. The total glacier area was 100,693±15,103 km2 and included 134,770 glaciers using 453 Landsat image scenes.

scholarly journals Brief communication: Updated GAMDAM glacier inventory over high-mountain Asia

2019 ◽  
Vol 13 (7) ◽  
pp. 2043-2049 ◽  
Author(s):  
Akiko Sakai
Keyword(s):  
Snow Cover ◽  
Landsat Imagery ◽  
High Mountain ◽  
Glacier Area ◽  
Landsat Images ◽  
Glacier Inventory ◽  
Seasonal Snow ◽  
Seasonal Snow Cover

Abstract. The original Glacier Area Mapping for Discharge from the Asian Mountains (GAMDAM) glacier inventory was the first methodologically consistent dataset for high-mountain Asia. Nonetheless, the GAMDAM inventory underestimated glacier area, as it did not include steep ice- and snow-covered slopes or shaded components. During revision of the inventory, Landsat imagery free of shadow, cloud, and seasonal snow cover was selected for the period 1990–2010, after which >90 % of the glacier area was delineated. The updated GAMDAM inventory, comprised of 453 Landsat images, includes 134 770 glaciers with a total area of 100 693±11 790 km2.

scholarly journals The analysis of spatial and temporal changes of land cover and land use in the reclaimed areas with the application of airborne orthophotomaps and LANDSAT images

2015 ◽  
Vol 64 (1) ◽  
pp. 75-86 ◽  
Author(s):  
Marta Szostak ◽  
Piotr Wężyk ◽  
Paweł Hawryło ◽  
Marcin Pietrzykowski
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Modern Technology ◽  
General Reference ◽  
Landsat Images ◽  
Corine Land Cover ◽  
Spoil Heap ◽  
Object Based ◽  
Mine Sites ◽  
Landsat Satellite

Abstract The aim of this study was to investigate the possible use of geoinformatics tools and generally available geodata for mapping land cover/use on the reclaimed areas. The choice of subject was dictated by the growing number of such areas and the related problem of their restoration. Modern technology, including GIS, photogrammetry and remote sensing are relevant in assessing the reclamation effects and monitoring of changes taking place on such sites. The LULC classes mapping, supported with thorough knowledge of the operator, is useful tool for the proper reclamation process evaluation. The study was performed for two post-mine sites: reclaimed external spoil heap of the sulfur mine Machów and areas after exploitation of sulfur mine Jeziórko, which are located in the Tarnobrzeski district. The research materials consisted of aerial orthophotos, which were the basis of on-screen vectorization; LANDSAT satellite images, which were used in the pixel and object based classification; and the CORINE Land Cover database as a general reference to the global maps of land cover and land use.

scholarly journals A glacier inventory for South Tyrol, Italy, based on airborne laser-scanner data

2009 ◽  
Vol 50 (53) ◽  
pp. 46-52 ◽  
Author(s):  
Christoph Knoll ◽  
Hanns Kerschner
Keyword(s):  
Laser Scanner ◽  
Glacier Area ◽  
Scanner Data ◽  
Equilibrium Line Altitude ◽  
Glacier Inventory ◽  
New Approach ◽  
Airborne Laser Scanner ◽  
South Tyrol ◽  
Airborne Laser ◽  
Digital Elevation

AbstractA new approach to glacier inventory, based on airborne laser-scanner data, has been applied to South Tyrol, Italy: it yields highly accurate results with a minimum of human supervision. Earlier inventories, from 1983 and 1997, are used to compare changes in area, volume and equilibrium-line altitude. A reduction of 32% was observed in glacier area from 1983 to 2006. Volume change, derived from the 1997 and 2006 digital elevation models, was –1.037 km3, and an ELA rise of 54 m, to almost 3000 m a.s.l., was calculated for this period. Losses vary widely for individual glaciers, but have accelerated for all South Tyrolean glaciers since the first inventory in 1983.

scholarly journals A review of supervised object-based land-cover image classification

2017 ◽  
Vol 130 ◽  
pp. 277-293 ◽  
Author(s):  
Lei Ma ◽  
Manchun Li ◽  
Xiaoxue Ma ◽  
Liang Cheng ◽  
Peijun Du ◽  
...  
Keyword(s):  
Land Cover ◽  
Image Classification ◽  
Cover Image ◽  
Object Based
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