scholarly journals ASSESSING THE IMPACT OF CANAL NETWORK ON SURFACE WATERLOGGING USING REMOTE SENSING DATASETS IN ROHTAK DISTRICT, HARYANA

2018 ◽  
Vol XLII-5 ◽  
pp. 261-266
Author(s):  
S. Kaushik ◽  
P. R. Dhote ◽  
P. K. Thakur ◽  
S. P. Aggarwal
Keyword(s):  
Remote Sensing ◽  
Sar Images ◽  
Monsoon Period ◽  
Band Ratio ◽  
Water Index ◽  
Radar Images ◽  
Post Monsoon ◽  
Normalized Difference Water Index ◽  
Surface Drains ◽  
The Impact

<p><strong>Abstract.</strong> Remote Sensing is a very reliable and expeditious technique for assessment and mapping of surface waterlogged areas. In this study band ratio based NDWI index (Normalized Difference Water Index) was used for extracting water pixels from optical imageries. To overcome the limitation of false positives and cloud penetration associated with optical imageries waterlogged areas was also extracted using SAR (Synthetic Aperture Radar) images. Thresholding of NDWI for optical image and Sigma0 for SAR images was done using their respective histograms to distinguish water and terrestrial features. The total surface waterlogged areas in the district was calculated by integrating the results from both optical and SAR images. It was found that surface waterlogged areas varies temporally from pre-monsoon to post-monsoon period in Rohtak district, Haryana. The surface waterlogged area for pre monsoon period is around 9.7<span class="thinspace"></span>km<sup>2</sup> and for post monsoon period is 17.86<span class="thinspace"></span>km<sup>2</sup>. The canal and surface drain network in the district was digitized using the high resolution Sentinel 2 MSS images. Since most of the canals in the area are unlined a buffer of 500<span class="thinspace"></span>m either side of the canals and surface drains was considered to assess the impact of seepage and leakage from canals and surface drains. It was found that more than 50% of the total surface waterlogged areas fall within this buffer, clearly indicating the contribution of leakages from canals and surface drains on surface waterlogging.</p>

scholarly journals Application of Remote Sensing on El Niño Extreme Effect in Normalized Difference Vegetation Index (NDVI) and Normalized Difference Water Index (NDWI)

2021 ◽  
Vol 6 (1) ◽  
pp. 46-56
Author(s):  
Ricky Anak Kemarau ◽  
Oliver Valentine Eboy
Keyword(s):  
Remote Sensing ◽  
El Niño ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Spatial Information ◽  
El Nino ◽  
Extreme Temperature ◽  
Water Index ◽  
Normalized Difference Water Index ◽  
The Impact

The years 1997/1998 and 2015/2016 saw the worst El Niño occurrence in human history. The occurrence of El Niño causes extreme temperature events which are higher than usual, drought and prolonged drought. The incident caused a decline in the ability of plants in carrying out the process of photosynthesis. This causes the carbon dioxide content to be higher than normal. Studies on the effects of El Niño and its degree of strength are still under-studied especially by researchers in the tropics. This study uses remote sensing technology that can provide spatial information. The first step of remote sensing data needs to go through the pre-process before building the NDVI (Normalized Difference Vegetation Index) and Normalized Difference Water Index (NDWI) maps. Next this study will identify the relationship between Oceanic Nino Index (ONI) with Application Remote Sensing in The Study Of El Niño Extreme Effect 1997/1998 and 2015/2016 On Normalized Difference Vegetation Index (NDVI) and Normalized Difference Water Index (NDWI)NDWI and NDWI landscape indices. Next will make a comparison, statistical and spatial information space between NDWI and NDVI for each year 1997/1998 and 2015/2016. This study is very important in providing spatial information to those responsible in preparing measures in reducing the impact of El Niño.

scholarly journals Delineating surface and sub surface waterlogged area using RS & GIS: a case study of Rachna Doab

2017 ◽  
Vol 5 (2) ◽  
pp. 81
Author(s):  
Hannan Mehmood ◽  
Mobushir Riaz Khan ◽  
Muhammad Amin ◽  
Rizwan Ali
Keyword(s):  
Remote Sensing ◽  
Geographical Information Systems ◽  
Geographical Information ◽  
Landsat 8 ◽  
Monsoon Period ◽  
Groundwater Levels ◽  
Water Index ◽  
Post Monsoon ◽  
Waterlogged Area ◽  
Gis Environment

Remote sensing (RS) combined with Geographical Information Systems (GIS) offers fabulous contrasting option to routine mapping strategies in observing and mapping of surface and sub-surface waterlogged areas. In the present study, a pre-monsoon and post-monsoon surface waterlogged area was delineated in the four districts of Rachna doab, using Landsat 8 data acquired for the year 2014. Modified Normalized Difference Water Index (MNDWI) was used mainly to delineate surface waterlogged areas. Perennial surface waterlogged areas were assessed for the study area by incorporating the waterlogged areas derived for both the pre-monsoon and post-monsoon seasons under GIS environment. Result shows that the total surface waterlogged area in pre-monsoon is 5,861 ha, which is 0.51 % of study area and for post-monsoon the surface waterlogging is 8,661 ha, which is 0.75% of study area respectively. Perennial surface waterlogging is 3,573 ha, which is 0.30% of the study area. Maximum waterlogged area was observed in Gujranwala district followed by Hafizabad, Sheikhupura and Nankana Sahib respectively. Further, waterlogged areas caused by rise in groundwater level were also assessed spatially under ArcGIS environment using the piezometric data pertaining of pre-monsoon and post-monsoon seasons for the year 2014 which were spread all over the study area. The analysis of both the seasons of groundwater levels indicates that the area under critical category during pre-monsoon period was 47,309 ha, which is 4% of the total area. Area under most critical category during post-monsoon period increased from 47,309 to 131,070 ha, which is 11% of the total. The study shows utility of remote sensing and GIS for evaluation of waterlogging areas especially where waterlogging situations occurs because of excessive irrigation and accumulation of rain and floodwater.

scholarly journals Observations of Winter Ablation on Glaciers in the Mount Everest Region in 2020–2021

2021 ◽  
Vol 13 (14) ◽  
pp. 2692
Author(s):  
Mauri Pelto ◽  
Prajjwal Panday ◽  
Tom Matthews ◽  
Jon Maurer ◽  
L. Baker Perry
Keyword(s):  
Remote Sensing Data ◽  
Time Data ◽  
Mount Everest ◽  
Monsoon Period ◽  
National Geographic ◽  
Freezing Level ◽  
Post Monsoon ◽  
Base Camp ◽  
Dry Conditions ◽  
The Impact

Recent observations of rising snow lines and reduced snow-covered areas on glaciers during the October 2020–January 2021 period in the Nepal–China region of Mount Everest in Landsat and Sentinel imagery highlight observations that significant ablation has occurred in recent years on many Himalayan glaciers in the post-monsoon and early winter periods. For the first time, we now have weather stations providing real-time data in the Mount Everest region that may sufficiently transect the post-monsoon snow line elevation region. These sensors have been placed by the Rolex National Geographic Perpetual Planet expedition. Combining in situ weather records and remote sensing data provides a unique opportunity to examine the impact of the warm and dry conditions during the 2020 post-monsoon period through to the 2020/2021 winter on glaciers in the Mount Everest region. The ablation season extended through January 2021. Winter (DJF) ERA5 reanalysis temperature reconstructions for Everest Base Camp (5315 m) for the 1950–February 2021 period indicate that six days in the January 10–15 period in 2021 fell in the top 1% of all winter days since 1950, with January 13, January 14, and January 12, being the first, second, and third warmest winter days in the 72-year period. This has also led to the highest freezing levels in winter for the 1950–2021 period, with the January 12–14 period being the only period in winter with a freezing level above 6000 m.

scholarly journals Defining a Trade-off Between Spatial and Temporal Resolution of a Geosynchronous SAR Mission for Soil Moisture Monitoring

2018 ◽  
Vol 10 (12) ◽  
pp. 1950 ◽  
Author(s):  
Luca Cenci ◽  
Luca Pulvirenti ◽  
Giorgio Boni ◽  
Nazzareno Pierdicca
Keyword(s):  
Soil Moisture ◽  
Spatial Resolution ◽  
Temporal Resolution ◽  
Added Value ◽  
Sar Images ◽  
Radar Images ◽  
Spatio Temporal ◽  
Set Up ◽  
The Impact ◽  
Hydrological Applications

The next generation of synthetic aperture radar (SAR) systems could foresee satellite missions based on a geosynchronous orbit (GEO SAR). These systems are able to provide radar images with an unprecedented combination of spatial (≤1 km) and temporal (≤12 h) resolutions. This paper investigates the GEO SAR potentialities for soil moisture (SM) mapping finalized to hydrological applications, and defines the best compromise, in terms of image spatio-temporal resolution, for SM monitoring. A synthetic soil moisture–data assimilation (SM-DA) experiment was thus set up to evaluate the impact of the hydrological assimilation of different GEO SAR-like SM products, characterized by diverse spatio-temporal resolutions. The experiment was also designed to understand if GEO SAR-like SM maps could provide an added value with respect to SM products retrieved from SAR images acquired from satellites flying on a quasi-polar orbit, like Sentinel-1 (POLAR SAR). Findings showed that GEO SAR systems provide a valuable contribution for hydrological applications, especially if the possibility to generate many sub-daily observations is sacrificed in favor of higher spatial resolution. In the experiment, it was found that the assimilation of two GEO SAR-like observations a day, with a spatial resolution of 100 m, maximized the performances of the hydrological predictions, for both streamflow and SM state forecasts. Such improvements of the model performances were found to be 45% higher than the ones obtained by assimilating POLAR SAR-like SM maps.

Mariculture Zones Extraction Using NDWI and NDVI

2013 ◽  
Vol 659 ◽  
pp. 153-155 ◽  
Author(s):  
Hong Jun Pan ◽  
Xue Xian Li ◽  
Guang Wei Wang ◽  
Chong Song Qi
Keyword(s):  
Remote Sensing ◽  
Spectral Characteristics ◽  
Remote Sensing Images ◽  
Distribution Planning ◽  
Surface Features ◽  
Water Index ◽  
Normalized Difference Water Index

On the analysis of spectral characteristics of Aoshan remote sensing images, we find the spectral differences between mariculture zones and other surface features. This paper combines normalized difference water index with mariculture zones distribution planning to complete the extraction and the statistics of the mariculture zones, in order to effectively achieve the regulation of mariculture zones.

scholarly journals Analysis of riverbank changes in Ho Chi Minh city in the period 1989 – 2015

2019 ◽  
Vol 2 (2) ◽  
pp. 80-88
Author(s):  
Thu Trang Hoang ◽  
Khoi Nguyen Dao ◽  
Loi Thi Pham ◽  
Hong Van Nguyen
Keyword(s):  
Remote Sensing ◽  
Remote Sensing Data ◽  
Ho Chi Minh City ◽  
Landsat 8 ◽  
River Bank ◽  
Water Index ◽  
Normalized Difference Water Index ◽  
Multi Temporal ◽  
Erosion And Accretion ◽  
Landsat Satellite

The objective of this study was to analyze the changes of riverbanks in Ho Chi Minh City for the period 1989-2015 using remote sensing and GIS. Combination of Modified Normalized Difference Water Index (MNDWI) and thresholding method was used to extract the river bank based on the multi-temporal Landsat satellite images, including 12 Landsat 4-5 (TM) images and 2 Landsat 8 images in the period 1989-2015. Then, DSAS tool was used to calculate the change rates of river bank. The results showed that, the processes of erosion and accretion intertwined but most of the main riverbanks had erosion trend in the period 1989-2015. Specifically, the Long Tau River, Sai Gon River, Soai Rap River had erosion trends with a rate of about 10.44 m/year. The accretion process mainly occurred in Can Gio area, such as Dong Tranh river and Soai Rap river with a rate of 8.34 m/year. Evaluating the riverbank changes using multi-temporal remote sensing data may contribute an important reference to managing and protecting the riverbanks.

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