Current Science

Ranen Sen ¹, Sharadindra Chakrabarti ², Somdatta Chakravortty ³

Affiliations
1 Formerly at Department of Metallurgical Engineering, Colorado School of Mines, US
2 Department of Applied Geology and Environment Systems Management, Presidency University, Kolkata 700 073, IN
3 Department of Computer Science and Engineering and Information Technology, Government College of Engineering and Ceramic Technology, Kolkata 700 010, IN

Abstract

The objective of this study is to (a) test the proposition that the variance of water quality from undefined sources is a function of land use within the watershed, and (b) examine the premise that the impact of land use near the stream is more important than that far away from the stream in affecting the water quality from non-point sources. Results obtained using this approach support both these hypotheses. Moreover, these tests suggest the importance of considering the means by which chemical elements are delivered to the streams. Nitrate-nitrogen and phosphorus can probably be intercepted by different means because of their varying delivery systems. Nitrate-nitrogen can be intercepted by removal of fast-growing floodplain crops and phosphorus by sediment barriers at sites outside the floodplain. Further evidences suggest that reservoir trap-efficiency is considerably important in improving the downstream water quality as the former entraps clay nanominerals (with adsorbed particulates of phosphorus) that are found to be responsible for the fate and transport of phosphorus. The methodology of analysis of stream loads is ordinary least square regression analysis. Stream loads of nitratenitrogen and total phosphorus have been studied as a function of land use.

Keywords

Land Use, Non-Point Source, Nitratenitrogen, Phosphorus, Water Quality.

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Somdatta Chakravortty ¹, Devadatta Sinha ²

Affiliations
1 Department of Information Technology, Government College of Engineering and Ceramic Technology, Kolkata 700 010, IN
2 Department of Computer Science and Engineering, Calcutta University, Kolkata 700 098, IN

Abstract

The present article analyses the accuracy of application of higher-order nonlinear interaction models on hyperspectral data to identify mangrove mixtures present in the Sunderbans Delta - a World Heritage Site in West Bengal, India. It is observed that intra-species interaction between similar mangrove species (interaction between the same type of end-members) in a homogeneous mangrove stand is more accurately modelled by the linear-quadratic model and hence results in more accurate fractional abundance estimations after unmixing when compared with linear-unmixing models. Specifically, we observe that quadratic models provide more accurate estimates than linear and bilinear models for the study area (Henry Island of Sunderbans), which is mostly dominated by pure and mixed mangrove species of Avicennia marina, Excoecaria agallocha, Avicennia alba, Phoenix paludosa, Avicennia officinalis, Ceriops decandra, Bruguiera cylindrica and Aegialitis. In this study, the quadratic nonlinear model successfully characterizes the interaction of endmember mixtures comprising E. agallocha, A. officinalis, B. cylindrica and A. alba in the study area.

Keywords

Higher-Order Interaction Models, Hyperspectral Data, Mangrove Species, Nonlinear Interactions.

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Somdatta Chakravortty ¹, Dipanwita Ghosh ¹

Affiliations
1 Department of Information Technology, Government College of Engineering and Ceramic Technology, Kolkata - 700 010, IN

Abstract

In this study we apply hyperspectral imagery to identify saline blank patterns within the mixed mangrove forest of Sunderban Bio-geographic Province, West Bengal, India. We use derivative analysis to identify hyperspectral wavelengths that are sensitive to the presence of minerals comprising saline blanks. These wavelengths have been considered for development of a novel saline blank identification model. The wavelength showing derivative value with maximum absorption in the SWIR region at 1780 nm and maximum reflection in the red region at 690 nm has been extracted for development of saline blank index. This index has been compared with the existing salinity indices and a detailed analysis has been carried out. It is found that the index outperforms existing salinity indices – normalized differential salinity index and salinity index, and accurately detects the saline blank areas of Henry Island of the Sunderbans Delta. The accuracy of pixels identified as saline blank pixels has been assessed by comparing the overall accuracy with other existing indices. Physical sampling has also been carried out and the salinity results have been compared with the image-derived results.

Keywords

Saline Blanks, Hyperspectral Data, Mangroves, Derivative Analysis.

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Prem Kumar ¹, Somdatta Chakravortty ¹

Affiliations
1 Maulana Abul Kalam Azad University of Technology, Haringhata, Nadia 721 249, IN

Abstract

Hyperspectral data can find wide applications in classification and mapping of pure and mixed pixels in images of different land-cover types. Hyperspectral data of high spectral resolution enhance discrimination of target objects; but the low spatial resolution poses a challenge due to creation of mixed pixels. The cost of acquiring images at high resolution from sensors is high and rarely available. With images of coarser spatial resolution, it is difficult to identify the endmembers and their locations within the mixed pixel. This study utilizes the fractional abundance values of target endmembers obtained from linear spectral unmixing in locating the sub-pixels of a mixed pixel. The study illustrates the preparation of classified maps of finer spatial resolution by locating the sub-pixels through different mapping algorithms. A comparative analysis of these mapping algorithms, viz. attraction model-based sub-pixel mapping, simulated annealing, neighbourhood connectivity, cosine similarity-based mapping and Markov random fieldbased mapping has been made and an output generated. The algorithms have been implemented on standard hyperspectral datasets of Indian Pines having 200 spectral channels, Pavia University of 103 spectral channels and Jasper Ridge of 198 spectral channels. It has been observed that simulated annealing-based mapping produces higher accuracy rate than the other algorithms, whereas in terms of execution time, attraction model takes lesser time. The accuracy has been validated with the ground reference map of available standard hyperspectral datasets on which each algorithm has been tested and analysed.

Keywords

Hyperspectral Data, Mapping Algorithms, Pure and Mixed Pixels, Spectral Channels.

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