A. D. Prasad

Bio: A. D. Prasad is an academic researcher from National Institute of Technology, Raipur. The author has contributed to research in topics: Environmental science & Image fusion. The author has an hindex of 7, co-authored 19 publications receiving 82 citations.

A Review on Air Quality Measurement Using an Unmanned Aerial Vehicle

Abstract: In major cities, air quality is of significant concern because of its negative effect on the health of the region’s living conditions, climate, and economy. Recent studies show the significance of the data on microlevel pollution which includes severe air pollutants and their impacts on human. Conventional methods of measuring air quality need skilled personnel for accurate data measurement that are based on stationary and limited measuring station networks. However, it is costly to seize the spatio-temporal variability and to recognize pollution hotspots that are necessary to develop real-time exposure control strategies. Due to the restricted accessibility of information and the non-scalability of standard techniques for air pollution monitoring, a real-time system with both higher spatial and temporal resolution is crucial. In recent times, unmanned aerial vehicles (UAVs) mounted with various sensors have been implemented for on-site air quality surveillance as they can offer new methods and research possibilities in air pollution and emission tracking, as well as in the study of environmental developments. An extensive literature review has been conducted, and it was observed that there are types of UAVs and types of sensors that are used for air quality monitoring for the parameters like CO, SO2, NO2, O3, PM2.5, PM1.0, and black carbon. Low-cost wireless sensors have been using for monitoring purpose in the past studies, and when results obtained are validated with the stationary monitoring instruments, the coefficient of correlation (R2) is found to be varied from 0.3 to 0.9. The difficulties, however, are not just technical, but at present time, policies and laws, which vary from country to country, symbolize the major challenge to the extensive use of UAVs in air quality/monitoring studies.

Contrast Enhanced Multi Sensor Image Fusion Based on Guided Image Filter and NSST

Abstract: Multi sensor image fusion enhances the human visual perception and machine interpretation of the scene by integrating complementary and redundant information given by multi sensor data. In this paper, we proposed a multi sensor image fusion method that provides a high contrast fused image having no structural bias and which is more robust to different types of source images. These objectives are achieved through an intelligent ensemble of guided image filter, nonsubsampled shearlet transform, texture energy measures, and morphological operations. The proposed method is validated on medical, infrared-visible, and multi focus images. The qualitative and quantitative assessment proved the superiority of the proposed method compared to state of the art image fusion methods.

Mapping of Lineaments and Knowledge Base Preparation using Geomatics Techniques for part of the Godavari and Tapi Basins, India: A Case Study

Abstract: Earth consists of hard rock layers where water is restricted to secondary permeability, and thus to fractures and the weather zones. Structural geology studies, geologic lineaments and their pattern information are essential for better planning and execution of projects to avoid any natural hazards. Satellite images, aerial photographs and digital elevation models will give lineament information. Recent advances in digital image processing allow such lineament extraction to be accomplished in semi-automatic to fully automatic approaches. The accuracy of extracting lineaments depends strongly on the spatial resolution of the imagery, higher resolution imagery result in a higher quality of lineament map. In this paper, an attempt has been made for Mapping of lineaments and knowledge base preparation using geomatics techniques for part of the Godavari and Tapi Basins, India. A methodology for lineament extraction and the design of a knowledge-based lineament identification system has been proposed for geological aspects of any developmental activity. This methodology might potentially be adopted for the identification of several features of geological or anthropogenic origin. The study results of lineaments and the rose diagrams of the extracted lineaments can be applied to structural geology studies and their applications such as oreforming systems, mineral exploration, petroleum, nuclear energy facility sittings and water resource investigations, groundwater studies and also for finding suitable sites for dams and reservoirs. General Terms GIS, Knowledgebase.

Influence of land use/land cover change on land surface temperature using RS and GIS techniques

Abstract: Remote sensing (RS) and geographic information system (GIS) techniques have been extensively used over the world for the study of chronological changes in land use/land cover (LULC) and land surface temperature (LST). Moreover, understanding the relationship between them is the most important to manage lands. This study explores the application of RS/GIS for identifying LULC change and assessing its impact on LST using temperature-vegetation index (TVX) space in the east sub-basins of Urmia Lake basin, Iran. The results showed that most changes due to agricultural activities were observable as the pixel migrated from the high temperature-sparse vegetation condition to the low temperature-dense vegetation condition from 1989 to 2002; while, in addition to agricultural activities, due to urbanisation and human activities, the pixel migrated from the low temperature-dense vegetation condition to the high temperature-dense vegetation condition from 2002 to 2011 in the TVX space for entire case study. In general, the LULC change is a significant factor for LST increase or decrease, and LST changes mostly related with LULC changes in the study area.

DDcGAN: A Dual-Discriminator Conditional Generative Adversarial Network for Multi-Resolution Image Fusion

Abstract: In this paper, we proposed a new end-to-end model, termed as dual-discriminator conditional generative adversarial network (DDcGAN), for fusing infrared and visible images of different resolutions. Our method establishes an adversarial game between a generator and two discriminators. The generator aims to generate a real-like fused image based on a specifically designed content loss to fool the two discriminators, while the two discriminators aim to distinguish the structure differences between the fused image and two source images, respectively, in addition to the content loss. Consequently, the fused image is forced to simultaneously keep the thermal radiation in the infrared image and the texture details in the visible image. Moreover, to fuse source images of different resolutions, e.g. , a low-resolution infrared image and a high-resolution visible image, our DDcGAN constrains the downsampled fused image to have similar property with the infrared image. This can avoid causing thermal radiation information blurring or visible texture detail loss, which typically happens in traditional methods. In addition, we also apply our DDcGAN to fusing multi-modality medical images of different resolutions, e.g. , a low-resolution positron emission tomography image and a high-resolution magnetic resonance image. The qualitative and quantitative experiments on publicly available datasets demonstrate the superiority of our DDcGAN over the state-of-the-art, in terms of both visual effect and quantitative metrics. Our code is publicly available at https://github.com/jiayi-ma/DDcGAN .

A Review on Reverse Osmosis and Nanofiltration Membranes for Water Purification.

Abstract: Sustainable and affordable supply of clean, safe, and adequate water is one of the most challenging issues facing the world. Membrane separation technology is one of the most cost-effective and widely applied technologies for water purification. Polymeric membranes such as cellulose-based (CA) membranes and thin-film composite (TFC) membranes have dominated the industry since 1980. Although further development of polymeric membranes for better performance is laborious, the research findings and sustained progress in inorganic membrane development have grown fast and solve some remaining problems. In addition to conventional ceramic metal oxide membranes, membranes prepared by graphene oxide (GO), carbon nanotubes (CNTs), and mixed matrix materials (MMMs) have attracted enormous attention due to their desirable properties such as tunable pore structure, excellent chemical, mechanical, and thermal tolerance, good salt rejection and/or high water permeability. This review provides insight into synthesis approaches and structural properties of recent reverse osmosis (RO) and nanofiltration (NF) membranes which are used to retain dissolved species such as heavy metals, electrolytes, and inorganic salts in various aqueous solutions. A specific focus has been placed on introducing and comparing water purification performance of different classes of polymeric and ceramic membranes in related water treatment industries. Furthermore, the development challenges and research opportunities of organic and inorganic membranes are discussed and the further perspectives are analyzed.