Browsing by Author "Ahmed, Ishtiaq"
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Item Analysis Of Land-Use Land-Cover Change In Rajouri District, Jammu And Kashmir(Central University of Punjab, 2018) Ahmed, Ishtiaq; Guite,L.T. SasangAn attempt was made in this study to detect the land use and land cover changes in Rajouri district of J&K during the period from November 2008 to December 2016. The LULC change over a span of 08 years (2008-2016) was investigated through remote sensing approach using two different time satellite images. Supervised classification in GIS software has been adopted in LISS-III (2008) and Landsat-8 (2016) images of the study area. To identify LULC changes from these pictures, post classification are used. The findings of Land-use Land-cover change shown that the study has experienced a decrease in forests by 6 percent and with an increase in agricultural land and open fields and settlement areas during the study period. These amendments in the land-use and land cover of the study area convey us that this change is due to rising anthropogenic burden on forests and high level of deforestation is responsible. Nonstop assessments of land-use/land-covers changes in this city and the implementation of proper land use planning are mandatory for ideal and systematic development.Item Assessment of Existing Himalayan Glacier Inventories for Glacier Studies: A Case Study from the Ravi Basin of North-Western Himalaya (India)(Springer International Publishing, 2023-03-10T00:00:00) Ahmed, Ishtiaq; Sharma, Vikram; Kumar, Rinku; Lal, Devi; Bhandari, Rajan; Chand, PritamOutside of the polar regions, the Hindukush-Karakoram-Himalaya (HKH) has the highest cluster of snow cover and glaciers, which offer various ecosystem services, including water, to the billions of people who live across this region. A glacier inventory is a vital prerequisite for researching a wide range of diverse phenomena, processes, and effects of such glacier changes across these regions. In recent years, several glacier inventories are available for the HKH region, namely, the Geological Survey of India (GSI) Glacier Inventory, the Space Application Center (SAC) Glacier Inventory, the International Centre for Integrated Mountain Development (ICIMOD) Glacier Inventory, Randolph Glacier Inventory (RGI), and Glacier Area Mapping for Discharge from the Asian Mountains (GAMDAM) Glacier Inventory (GGI). Prior to being used for any glacier investigations, it�s critical to evaluate the quality and consistency of these inventory datasets. Thus, the current study provides a detailed quality assessment of all these available glacier inventories by comparing them with the detailed Ravi basin glacier inventory (RBGI). The comprehensive RBGI was created using the Landsat Enhanced Thematic Mapper (ETM+) images (2002) with a supplement of medium- to high-resolution imagery and field validations. The RBGI consists of 285 glaciers in 2002 with a mapped area of 164.5 � 7.5 km2. There are 71 glaciers out of the total glaciers that have debris-covered parts, which occupy 36.1 � 2.1 km2 (~22% of the whole area covered by glaciers). Large variations were found in the glacial area (ranging from 202 to 112.7 km2) and a total number of glaciers (ranging from 299 to 192) mapped within the Ravi basin among these available glacier inventories. With few spatial differences in the total number of the glacier, their extent, and median elevation, it was found that the recently updated GGI inventory, which is incorporated into the revised version of RGI V6 for the Himalayan region, is most comparable to our RBGI inventory. Likely causes of the significant difference among these inventories include standard glacier definition (minimum area of glacier mapping and headwall definition), misinterpretation of the seasonal snow cover, demarcation of debris-covered areas, and consequences of excluding glacier sections in the shaded regions. � The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.Item Quantitative assessment of present and the future potential threat of coastal erosion along the Odisha coast using geospatial tools and statistical techniques(Elsevier B.V., 2023-02-28T00:00:00) Mishra, Manoranjan; Chand, Pritam; Beja, Santosh Kumar; Santos, Celso Augusto Guimar�es; Silva, Richarde Marques da; Ahmed, Ishtiaq; Kamal, Abu Hena MustafaThe eastern coast of India is one of the regions where most of the population resides in urban areas in the low-elevation coastal zone, making it vulnerable to frequent extreme weather events. The objectives of this study are to assess the short- to long-term shoreline changes of the Odisha coast, to understand how anthropogenic influences, and particularly extreme natural events, affect these changes, and to predict shoreline changes for 2050. This study utilized multi-temporal/spectral/spatial resolution satellite images and a digital shoreline analysis (DSAS) tool to appraise the short- (at five/six-year intervals) and long-term (1990�2019) shoreline dynamics along the coastal part of Odisha over the past three decades (1990�2019). The long-term shoreline analysis shows that the mean shoreline change is about 0.67 m/year and highlights that 52.47 % (227.4 km), 34.70 % (150.4 km), and 12.83 % (55.6 km) of the total Odisha coastline exhibit erosion, accretion, and stability, respectively. During the short-term analysis, the 2000�2005 period had the highest percentage of erosion (64.27 %), followed by the 2005�2010 period with an erosional trend of 59.06 %. The 1995�2000 period showed an accretion trend, whereas, during the last period, i.e., 2015�2019, the percentage of transects depicting erosion and accretion was almost similar. In 2050, 55.85 % of the transects are expected to show accretion, while 44.15 % would show erosion or a constant trend. The study identified the hotspots of coastal erosion along delineated study zones by synthesizing data from previous studies as well. The regional analysis of shoreline change along the Odisha coast would not only provide coastal managers with critical information on shoreline dynamics but also draw attention to vulnerable areas linked to shoreline dynamicity along the coast. � 2023 Elsevier B.V.