Touseef Ahmad

Indian Space Research Organization | ISRO · Space Applications Centre (SAC)

Forest fires in the Western Himalaya region pose significant environmental and health challenges. The present communication examines the impact of these fires on air quality, focusing on elevated levels of carbon monoxide, formaldehyde and aerosols. Utilizing satellite inputs and chemistry transport models such as Hybrid Single Particle Lagrangian...

Remote sensing applications require high-resolution images to obtain precise information about the Earth???s surface. Multispectral images have high spatial resolution but low spectral resolution. Hyperspectral images have high spectral resolution but low spatial resolution. This study proposes a residual learning and attention-based parallel netwo...

The Italian Space Agency (ASI) and the Indian Space Research Organisation (ISRO) established the joint Earth Observation Working Group (EOWG) that is currently focusing on hyperspectral (HYP) activity. Eleven projects are investigating the use of ASI’s PRISMA data for agriculture, land cover classification, mineral and soil mapping, Martian analogu...

Visible-near-and-short-wave-infrared hyperspectral images (HSI) have proven helpful for mapping the soil types over bare soils pixels. However, the accuracy of the traditional pixel-based classification methods decreases due to the spectral mixing between the significant agricultural features such as vegetation, soil and crop residue. In this conte...

The limited spatial resolution of the hyperspectral (Hx) images corrupts the spectral information of pure materials and their distribution in an image. The accuracy of characterising or classifying the soil using Hx or Mx images decreases when surfaces are covered by vegetation. In the presence of vegetation, a single pixel can be labelled as eithe...

Nonlinear Unmixing using the Band-wise Generalized Bilinear Mixing (NU-BGBM) model specifies an acceptable mixing sce- nario up to the second-order interaction of light rays and also suppresses various types of mixed noise while performing un- mixing. However, NU-BGBM requires high computational time and multiple parameter tuning, which could pract...

Spectral signatures of the pure constituent materials vary across the hyperspectral image (HSI) due to variable illumination, atmospheric conditions, and intrinsic variability. Using a single endmember to represent the target material (or endmember) with high spectral variability will lead to errors in estimating abundance. Therefore, we propose a...

Hyperspectral imagery (HSI) in the visible to near-infrared wavelength region has a high potential for deciphering mineral compositions of terrestrial and planetary surfaces. Thus, ISRO's Imaging Infrared Spectrometer (IIRS) sensor onboard Chandrayaan-2 (Ch-2) orbiter provides an opportunity to utilise the hyperspectral observations to characterise...

The generalized bilinear model (GBM) has been one of the most representative models for nonlinear unmixing of hyperspectral images (HSI), which can consider the second-order scattering of photons. Recently, robust GBM-low-rank representation (RGBM-LRR) for nonlinear unmixing of HSI has been introduced to capture the spatial correlation of HSI using...

Spectral mixture modelling is one of the most important techniques for classifying hyperspectral data at sub-pixel resolution. The identification of spectrally pure endmembers for estimating their corresponding abundances is an important step in spectral unmixing. The application of spectral reduction prior to endmember extraction would optimize th...

In recent times, Hyperspectral(HS) and multispectral(MS) data fusion based on spectral unmixing methods has become an active area of research. Coupled non-negative matrix factorization (CNMF), one among many unmixing-based data fusion approaches, performs alternating unmixing of the HS and MS data while connecting the results by point spread functi...

Advanced Hyperspectral Data Analysis Software (AVHYAS) plugin is a python3 based quantum GIS (QGIS) plugin designed to process and analyse hyperspectral (Hx) images. It is developed to guarantee full usage of present and future Hx airborne or spaceborne sensors and provides access to advanced algorithms for Hx data processing. The software is freel...

A four-directional total variation technique is proposed to encapsulate the spatial contextual information for sparse hyperspectral image (HSI) unmixing. Traditional sparse total variation techniques explore gradient information along with the horizontal and vertical directions. As a result, spatial disparity due to high noise levels within the nei...

Indira Gandhi Canal Project has enhanced considerable food production in desert area of Rajasthan, it also brought problems such as waterlogging and secondary salinisation. Impounding of Ghaggar flood water in natural depression is the main cause of seepage. Villages are located at lower altitude than the level of water stored in depressions, which...

A temporal image analysis of the Larsen C iceshelf was carried out to study the rift propagation and ice calving in this region. MODIS data from 2000 to 2017 and Sentinel data from Oct 2014 to June 2017 were used. The detailed analysis shows that there is an increasing rate at which the rift propagation is increasing and a large portion to a tu...

The present paper deals with the solution of ordinary differential equations with various initial and boundary conditions. We start with the expansion of the highest derivative in terms of wavelets. Successive integrations give the approximations of the lower derivatives and finally the dependent variable. After substituting required values in the...