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Siddiqui, Asfa
- Characterization and Retrieval of Snow and Urban Land Cover Parameters using Hyperspectral Imaging
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PDF Views:94
Authors
S. K. Singh
1,
Gaurav Jain
1,
Asfa Siddiqui
2,
Smruti Naik
1,
B. P. Rathore
1,
Vaibhav Garg
2,
Snehmani
3,
Vinay Kumar
2,
I. M. Bahuguna
1,
S. A. Sharma
1,
Chander Shekhar
3,
Praveen K. Thakur
2,
Kavach Mishra
2,
Pramod Kumar
2,
T. H. Painter
4,
J. Dozier
5
Affiliations
1 Space Applications Centre, Indian Space Research Organisation (ISRO), Ahmedabad 380 015, IN
2 Indian Institute of Remote Sensing, ISRO, Dehradun 248 001, IN
3 Snow and Avalanche Study Establishment, Chandigarh 160 036, IN
4 University of California, Los Angeles, CA, US
5 University of California, Santa Barbara, CA, US
1 Space Applications Centre, Indian Space Research Organisation (ISRO), Ahmedabad 380 015, IN
2 Indian Institute of Remote Sensing, ISRO, Dehradun 248 001, IN
3 Snow and Avalanche Study Establishment, Chandigarh 160 036, IN
4 University of California, Los Angeles, CA, US
5 University of California, Santa Barbara, CA, US
Source
Current Science, Vol 116, No 7 (2019), Pagination: 1182-1195Abstract
Snow and urban land cover are important due to their role in hydrological management and utility, climate response, social aspects and economic viability, along with influencing the Earth’s environment at local, regional and global scale. Hyperspectral data enable identification, characterization and retrieval of these land-cover features based on physical and chemical properties of compositional materials. AVIRISNG hyperspectral airborne data, with synchronous ground observations using field spectroradiometer and collateral instruments, were collected over two widely varied land-cover types, viz. a relatively homogenous area covered by snow in the extreme cold environment of the Himalaya (Bhaga sub-basin, Himachal Pradesh), and a completely heterogeneous urban area of a metropolitan city (Ahmedabad, Gujarat).
AVIRIS-NG airborne data were analysed to understand the effect of terrain parameters such as slope and aspect on snow reflectance. Snow grain index using visible and near-infrared (VNIR) bands and absorption peak in the near-infrared (NIR) were used to retrieve grain size in parts of the Himalayan region. A radiative transfer model was used to understand the grain size variability and its effect on absorption peak in NIR. Continuum removal was performed for snow spectral observations obtained from airborne, modelled and field platforms to estimate band depth at 1030 nm. Grain size was observed to vary with altitude from 100 to 500 μm using AVIRIS-NG image. In the urban area, the data also separated pervious and impervious surface cover using spectral unmixing technique, identified several urban features over multispectral data such as buildings with red tiled roofs, metallic surfaces and tarpaulin sheets using the material spectral profiles. Two single-frame superresolution methods namely sparse regression and natural prior (SRP), and gradient profile prior (GPP) were applied on AVIRIS-NG data for the mixed environment around Kankaria Lake in the city of Ahmedabad, which revealed that SRP method was better than GPP, and affirmed by eight indices. Preliminary analysis of AVIRIS-NG imaging over snow-covered areas and densely populated cities indicated utility of future spaceborne hyperspectral missions, particularly for hydrological and climatological applications in such diverse environments.
Keywords
AVIRIS-NG, Hyperspectral Imaging, Snow Reflectance, Super-Resolution Method, Terrain Parameters, Urban Land Cover.Full Text
References
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- Effect of COVID-19 Lockdown on the Spatio-temporal Distribution of Nitrogen Dioxide Over India
Abstract Views :238 |
PDF Views:92
Authors
Affiliations
1 Marine and Atmospheric Sciences Department, Indian Institute of Remote Sensing, Dehradun 248 001, IN
1 Marine and Atmospheric Sciences Department, Indian Institute of Remote Sensing, Dehradun 248 001, IN
Source
Current Science, Vol 120, No 2 (2021), Pagination: 368-375Abstract
The nationwide lockdown was implemented in India from 25 March 2020 onwards to control the spread of deadly Coronavirus disease 2019 (COVID-19). A sudden shutdown of anthropogenic activities resulted in abrupt decrease of nitrogen dioxide (NO2) across the Indian region. OMI (Ozone Monitoring Instrument) tropospheric column NO2 observations show significantly decreased values during 2020 compared to previous years during 25 March to 19 April. The spatiotemporal variation of tropospheric column NO2 difference between 2020 and average 2017–2019 shows reduction by more than 1 × 1015 molecules/cm2 over the Indo Gangetic Plain, eastern and southern India due to lockdown. However, the western Indian region shows slight enhancement which may be attributed to combined effect of transport of polluted air from Middle East and Pakistan, and relatively higher biomass burning activity during 2020. A significant reduction is also observed on the surface distribution of NOx (NO + NO2) over different Indian cities due to COVID-19 lockdown. Maximum reduction in daily average surface NOx is observed over Kolkata (65.2 ± 18.7 ppbv to 30.3 ± 4.6 ppbv) followed by New Delhi (38.8 ± 17.5 ppbv to 11.5 ± 2.9 ppbv) which may be attributed to vehicle fleet, type of fuel used, power plants and industrial emissions.Keywords
COVID-19 Lockdown, Nitrogen Dioxide, NOx, OMI.Full Text
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