Papers by Rishikesh Bharti
Machine Learning-Driven Snow Cover Mapping Techniques using Google Earth Engine
2022 IEEE 19th India Council International Conference (INDICON)
Snow Permittivity and Density Estimation Using C-Band Dual Polarimetric Sentinel-1A Data
IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium
Snow Area Mapping using Feature-oriented Principal Component Analysis
IGARSS 2019 - 2019 IEEE International Geoscience and Remote Sensing Symposium
Climate change being in the verge of all discussions points most of its focus on the change in th... more Climate change being in the verge of all discussions points most of its focus on the change in the snow cover area which leads to increase in sea surface level in the long term and sometimes flood like scenario in the short term. So monitoring the snow areas with respect to time is a must to understand the effects of climate change more closely. This work demonstrate the application of Feature Oriented Principal Component Analysis (FPCA), also called as "Crosta technique" [1]. FPCA is a multivariate statistical technique used to transform the set of relatively correlated spectral bands of Landsat 8 to uncorrelated Principal Components. The statistical interpretation of the loadings of the SWIR wavelength band (sensitive to snow/glacier) in different PCs were used to generate a snow/glacier color composite image (Crosta image) of the Teesta river basin, Sikkim, India.
Scientific Reports
The present paper utilizes entropy theory and Google earth engine cloud computing technique to in... more The present paper utilizes entropy theory and Google earth engine cloud computing technique to investigate system state and river recovery potential in two large sub-basins of the Mahanadi River, India. The cross-sectional intensity entropy (CIE) is computed for the post-monsoon season (October–March) along the selected reaches. Further, a normalized river recovery indicator (NRRI) is formulated to assess the temporal changes in river health. Finally, NRRI is related to a process-based variable-LFE (low flow exceedance) to comprehend the dominating system dynamics and evolutionary adjustments. The results highlight the existence of both threshold-modulated and filter-dominated systems based on CIE and NRRI variabilities. In addition, the gradual decline in CIE and subsequent stabilization of vegetated landforms can develop an ‘event-driven’ state, where floods exceeding the low-flow channel possess a direct impact on the river recovery trajectory. Finally, this study emphasizes the ...
Impact of mine pit lake on metal mobility in groundwater
Environmental Earth Sciences, 2021
Open pit mines are potential source of metal contamination. Three types of open pit mines, i.e. c... more Open pit mines are potential source of metal contamination. Three types of open pit mines, i.e. copper, quartzite and granite were selected to understand the mobility and behaviour of metals. Metal contamination due to abandoned open pit copper mines (Average Cu = 64.57 ± 90 µg/L) is observed more comparative to quartzite (Average Cu = 20.42 ± 34.39 µg/L) and granite mines (Average Cu = 9.67 ± 7.94 µg/L). Acid mine drainage (AMD) from copper mines result in dissolution of metals and contaminates groundwater in the downstream direction. Correlation used for source assessment confirms the influence of anthropogenic or abandoned pit mine on metal concentration in groundwater. It is observed that the impact of abandoned pit mine is more compared to tailings and overburden dumps. Dissolution and precipitation process control the metal abundance in downstream groundwater. Precipitation dominates dissolution process with distance and results in decrease in metal concentration. It also confirms the self-neutralisation and self-attenuation capacity of the aquifer. The study recommends restoration of abandoned open pit mines to their natural conditions to avoid metal contamination in downstream.
Satellite imagery band ratio for mapping the open pit mines: A preliminary study
<p>Indices are designed to differentiate land use and land cover classes to... more <p>Indices are designed to differentiate land use and land cover classes to avoid misinterpretation of landscape features. The resemblances of spectral reflectance of mines with urban built-up and barren land cause difficulties in identification of objects. Open pit mines of Rampura-Agucha for Zn and Pb were selected for this study. The freely available data of Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) was selected from the year of 2001 and 2003. It is observed that b1-b5/b1+b5 equation of ASTER imagery significantly differentiate Zn-Pb mine from urban settlement and other features. The reflected range (µm) for b1 and b5 is 0.52-0.60 (Visible and Near-Infrared) and 2.145-2.185 (Shortwave Infrared) respectively. The pixel values indicate higher reflectance of open pit suggesting feasibility of equation for differentiating it from barren and built-up area. The mine is rich in sphalerite followed by galena, pyrite and pyrrhotite in different proportions of abundance. Spectral reflectance depends on type of minerals hence need further studies to develop the index according to specific minerals and mines. In the mining regions, the role of temperature, moisture content, vegetation covers and high concentration of pollutants in variation of spectral reflectance are highly important. The developed index would be beneficial for tracing the extent of overburden dumps, tailings and mines at faster rate.</p>
Point Mass Balance Regression using Deep Neural Networks: A Transfer Learning Approach
<p>The last few years have seen an increasing number of studies mod... more <p>The last few years have seen an increasing number of studies modeling glacier evolution using deep learning. Most of these techniques have focussed on artificial neural networks (ANN) that are capable of providing a regressed value of mass balance using topographic and meteorological input features. The large number of parameters in an ANN demands a large dataset for training the parameter values. This is relatively difficult to achieve for regions with a sparse in-situ data measurement set up such as the Himalayas. For example, of the 14326 point mass balance measurements obtained from the Fluctuations of Glaciers database for the period of 1950-2020 for glaciers between 60S and 60N, a mere 362 points over four glaciers exist for the Himalayan region. These are insufficient to train complex neural network architectures over the region. We attempt to overcome this data hurdle by using transfer learning. Here, the parameters are first trained over the 9584 points in the Alps following which the weights were used for retraining for the Himalayan data points. Fourteen meteorological from the ERA5Land monthly averaged reanalysis data were used as input features for the study. A 70-30 split of the training and testing set was maintained to ensure the authenticity of the accuracy estimates via independent testing. Estimates are assessed on a glacier scale in the temporal domain to assess the feasibility of using deep learning to fill temporal gaps in data. Our method is also compared with other machine learning algorithms such as random forest-based regression and support vector-based regression and we observe that the complexity of the dataset is better represented by the neural network architecture. With an overall normalized root mean squared loss consistently less than 0.09, our results suggest the capability of deep learning to fill the temporal data gaps over the glaciers and potentially reduce the spatial gap on a regional scale.</p>
Intercalibration of DMSP-OLS and NPP-VIIRS to Develop Enhanced Night-time Light Time-series for Evaluating the Urban Development Pattern of Major Indian Metropolitan cities
An Investigation of the Fluvial Geomorphology and Associated Minerals in the Syrtis Major, Mars
IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium, 2018
Syrtis Major Planum is a major volcanic construct on Mars ridden with a large number of fluvial c... more Syrtis Major Planum is a major volcanic construct on Mars ridden with a large number of fluvial channels mostly draining into the adjacent Isidis basin. These channels have been attributed to have formed by lava flows from the calderas of the construct onto the basin. However, with availability of high spatial and spectral resolution remote sensing datasets, new findings in the region over time have indicated possible presence of hydrological channels in Syrtis Major. We explore one such feature in the volcanic construct that seems to have been altered by hydrological activity. High abundance of hydroxylated and hydrated minerals have been found in the region which support this conclusion that lava might not be the only factor causing potential channel generation in the region.
Spatio-Temporal Distribution of Carbon Dioxide Partial Pressure in the Bay of Bengal
IGARSS 2019 - 2019 IEEE International Geoscience and Remote Sensing Symposium, 2019
Sea water carbon dioxide partial pressure is the major controlling factor in the air-sea CO2 gas ... more Sea water carbon dioxide partial pressure is the major controlling factor in the air-sea CO2 gas exchange. The seasonal and spatial distribution of Carbon Dioxide Partial Pressure (pCO2_sw) is vastly regulated by the physical, chemical and biological parameters of the ocean whereas alterations in the atmospheric pCO2 is minimal. Although the global ocean is a net CO2 sink, regional fluctuations in the CO2 partial pressures can have potential consequences on the universal trend. Being one of the least sampled oceanic region, the chief elements regulating the Bay of Bengal (BoB) partial pressures are yet to be understood. An attempt has been made to analyse the significance of biological and chemical properties in defining the spatial distribution of the sea surface partial pressures as well as the influence of monsoonal river influx in BoB. Results revealed an equal importance of the chemical and biological factors on the partial pressure distribution. The Multiple Linear Regression (MLR) and Support Vector Regression (SVR) algorithms developed from Sea Surface Salinity (SSS) and Sea Surface Temperature (SST) showed to give better output in the post monsoon, while they tend to underestimate the values in the pre-monsoon season due to interference by biological factors. A strong influence of the fresh water discharge on the surface salinity was observed which in turn has implications on the spatial distribution of sea water partial pressures where the pre-monsoon value range of 400–430µatm was decreased to 386–417µatm range in the post monsoon.
Jezero, an impact crater located in NE Syrtis is home to a large diversity of alteration minerals... more Jezero, an impact crater located in NE Syrtis is home to a large diversity of alteration minerals and fluvial features. The current study aims to map the abundance of rock-bearing mafic minerals in the region and analyze them with the estimated surface thermal inertia and thereby generate a hydrated mineral potential map. It is seen that the crater is made up of a central LCP unit characterized by higher thermal inertia values when compared to its surroundings which are dominant in Fe-rich phyllosilicates. It is evident from the result that the presence of large amounts of LCP deposits are possibly due to erosion from fluvial activities. The LCP spatial distribution indicates that mineral emplacement might have occurred over the volcanic floor due to flow from the western delta.
Source, Assessment, and Remediation of Metals in Groundwater
Groundwater Geochemistry, 2021
Urbanisation is an ever-evolving, complicated continuous process distinct from its surroundings, ... more Urbanisation is an ever-evolving, complicated continuous process distinct from its surroundings, having the tendency to create a micro-scale system with characteristic local environmental conditions. Large-scale urbanization near the coasts has a definite impact on the coastal processes due to dynamic interactions of the coastal waters with the urban atmospheric, hydrological and anthropogenic residues. This study focuses on understanding the contribution of immediate atmospheric variations due to urbanization on surface temperature of coastal waters along the Mumbai coast. Different meteorological and air quality parameters such as Air Temperature (AT), Land Surface Temperature (LST), Precipitation (P), Relative Humidity (RH), Wind Speed (WS) and Aerosol Optical Depth (AOD) collectively were used as determinants of local urban climatic environment; to analyse and understand the impact of urbanization on Sea Surface Temperature (SST) representing coastal system. ERA5 Reanalysis mete...
This article reviews the potential of Hyperspectral Remote Sensing (HRS) technique in various geo... more This article reviews the potential of Hyperspectral Remote Sensing (HRS) technique in various geological applications ranging from lithological mapping to exploration of economic minerals of lesser crustal abundance. This work updates understanding on the subject starting from spectroscopy of minerals to its application in exploring mineral deposits and hydrocarbon reservoirs through different procedures such as atmospheric correction, noise reduction, retrieval of pure spectral endmembers and unmixing. Besides linear unmixing, nonlinear unmixing and parameters attributed to nonlinear behaviour of reflected light are also addressed. A few case studies are included to demonstrate the efficacy of this technique in different geological explorations. Finally, recent developments in this field like ultra spectral imaging from unmanned aerial vehicles and its consequences are pointed out.
SN Applied Sciences, 2021
Soil erosion is a serious and continuous environmental problem in Ethiopia. Lack of land use plan... more Soil erosion is a serious and continuous environmental problem in Ethiopia. Lack of land use planning, environmental protection, over-cultivation, and overgrazing are prominent causes of erosion and sedimentation. This study is conducted in Anjeb watershed located in the Upper Blue Nile Basin, Ethiopia. In this study, the quantity and distribution of soil erosion, sediment delivery ratio (SDR), and sediment yield of the watershed were assessed by employing remote sensing, geographic information system (GIS), and revised universal soil loss equation analysis capabilities. Important data sets of topography, soil, conservations practices, cover management, and rainfall factors were processed and superimposed in GIS analysis, and soil loss rate, SDR, and sediment yield of the watershed were derived. Based on the result found, the watershed was categorized into six classes of erosion: slight (0–5), moderate (5–10), high (10–15), very high (15–30), severe (30–50), and very severe (> 50...
Smoulder Detection Using Split-Window Algorithm: A Case Study From Baghjan Oilfield, Assam, India
2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS, 2021
Land Surface Temperature (LST) plays a significant role in detecting surficial anomalies such as ... more Land Surface Temperature (LST) plays a significant role in detecting surficial anomalies such as sudden fire outbreak, geothermal leakage, volcanic activities etc. In this study, an attempt has been made to analyze the Baghjan oilfield blowout and its local impact using remote sensing as a tool. The blowout occurred due to hydrocarbon leakage on 27th May, 2020 in well-5 located at Tinsukhia district of Assam, India. Sentinel-2 MSI and Landsat-8 TIRS/OLI bands have been used to derive LST in order to identify smoulder using the split-window (SW) algorithm. The local damage to vegetation cover is quantified using normalized burn ratio (NBR) and the severity is calculated through ΔNBR. LST revealed hike in surface temperature of the nearby regions of well-5 possibly due to local heat trap resulting from heavy smoke and smoulder emission. This could be due to hydrocarbon combustion producing enormous amount of CO2 and water vapour creating a local heat island. The blowout resulted in significant damage to the nearby vegetation and forest cover affecting an area of 34,200 m2 out of which 15,300 m2 of area suffered severe damage.
Archives of Environmental Contamination and Toxicology, 2021
Khetri Copper Belt, Rajasthan is anthropogenically active and geologically belongs to the Delhi s... more Khetri Copper Belt, Rajasthan is anthropogenically active and geologically belongs to the Delhi supergroup. To study the active geochemical processes controlling the elemental mobility, representative groundwater samples were analysed for heavy metals and radionuclide (U). A maximum U concentration (average 87 µgL-1) is observed in the quartzite mine zone whereas minimum (average 13 µgL-1) is found to be in the copper mine zone samples. Despite the presence of Jaspura and Gothra granitoid in the copper mine zone, the abundance of U is low suggesting the scavenging of U by sulphides or iron oxides. Additionally, at the confluence of two geological groups, Fe concentration is found high with a low concentration of U which further confirms scavenging of U. In the region, aquifers are shallow which supports the weathering of minerals. Thus, a high concentration of U in groundwater is attributed to mineral dissolution, faults or fractures. It is evident from the results that in the absence of iron-bearing sulphides, U concentration in groundwater would be very high compared to the current concentration. It also indicates low concentration of U in the copper mine zone, area is covered with abundant quantity of Fe sulphide rich waste. The present study recommends further research to understand the feasibility of mining waste for the removal of U contamination from groundwater.
Provenance identification of soil at the confluence of Thar desert, Aravalli hills, and alluvial plain based on trace and rare earth elements geochemistry
Arabian Journal of Geosciences, 2021
Khetri Copper Belt (KBC), India, lies in the semi-arid region at the confluence of Aravalli range... more Khetri Copper Belt (KBC), India, lies in the semi-arid region at the confluence of Aravalli ranges and alluvial soil. A study is designed to understand the influence of aeolian processes on soil geochemistry (major oxides, trace elements and REE) at the edge of desert. Mines of copper, quartzite and granite are active in the region and for the study the region is divided into three zones such as copper mine zone (CMZ), quartzite mine zone (QMZ) and granite mine zone (GMZ). CMZ is located in the windward of Aravalli hills (considering Thar desert as a reference point) and significantly influenced by strong winds from Thar desert. Low values of CIA (60) at CMZ compared to PAAS (CIA = 70) are attributed to significant impact of aeolian processes. QMZ is quartzite enriched zone and low average value of CIA (60) is due to less weathering of parent quartzite rocks. Cu and Zn are major nutrient for plants and a positive correlation of Cu and Zn with N and C at QMZ indicates high fertility of soil (alluvial soil) and negligible influence of aeolian processes is attributed to its leeward location from Aravalli hills, the physical barrier. Eu anomaly and variations in trace elements (La/Th, Th/Sc and La/Sc) confirm the felsic source of soil. The UCC normalised plot for ∑REE shows the enrichment of REE at QMZ and GMZ as compared to CMZ is due to presence of heavy minerals. Thus, less impact of aeolian processes on QMZ lies in the leeward of Aravalli ranges indicating that the Aravalli ranges shield the transportation of aeolian sand.
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Papers by Rishikesh Bharti