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Rubina Parveen

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University of Zagreb

Uppsala University

University of East London

University of Leicester

Gwen Robbins Schug

University of North Carolina at Greensboro

Gabriel Gutierrez-Alonso

University of Salamanca

Macquarie University

Universidade Federal do Rio Grande do Sul

Swansea University

Jesper Hoffmeyer

University of Copenhagen

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Papers by Rubina Parveen

IRS‐1C LISS III画像を用いた低レベル視覚処理と植生抽出【Powered by NICT】

IEEE Conference Proceedings, 2016

IRS‐1C LISS III画像からの水塊の抽出と描写【Powered by NICT】

IEEE Conference Proceedings, 2016

Vocational Skill Development Imperative for Women Empowerment in India

Journal of Women Empowerment and Studies

This study focuses on identifying inherent skills in women and the need for women to develop voca... more This study focuses on identifying inherent skills in women and the need for women to develop vocational skills. Awareness of various government schemes and the benefits of being a skilled woman is highlighted. An empirical study has been made to collect information and statistical data. A strength, weakness, opportunity, and threat (SWOT) analysis is carried out. The findings are promising. Skill development teaches women about power from within, decision-making power, control over financial, physical, and knowledge-based assets, and power with ability. Homemakers will soon become breadwinners, and vice versa, depending on suitability and necessity. These days are not far. A skill-armed woman is a home to a self-sustaining life. Equipping women with employable vocational skills in India can certainly lead to an “equal skill, equal pay” scenario.

Exigency of establishment of Skills University in Kalyana-Karnataka region of Karnataka state

Skills University (SU) is crucial to improve the standard of living of youth by making them more ... more Skills University (SU) is crucial to improve the standard of living of youth by making them more employable in Kalyana-Karnataka (KK) region. Till now, very few research works have been conducted related to the establishment of SU in backward areas and very few SU exists pan India. The methodology is conceived by collecting primary inputs from the statistics available on the global open platforms and amount of practical knowledge acquisition is empirical. Analysis shows that there is exigency of SU in KK region to remove the perception of regional imbalance , avoid reluctance of youth to opt vocational education. Restructuring of youth thinking by removing inferior perception on skill education as compared to formal education. The study implies that after completion of this skill education in SU majority of the youth enhance their confidence level to start their own enterprise without depending on others/ to get jobs in local. 9. Conclusion Kalyana Karnataka (KK) region is on the wa...

Colour transformed clustering-based water body extraction using IRS-1C LISS III image

International Journal of Spatio-Temporal Data Science, 2019

The algorithm presented in this research article extracts and delineates the water areas using IR... more The algorithm presented in this research article extracts and delineates the water areas using IRS-1C LISS III images. Methods available in the literature are biased with user-defined thresholds. The objective of the proposed algorithm is to provide accurate information about surface water. Initially, the input image is subjected to colour transformation clustering to extract all the similar hydrological characteristics geo-spatial features in the picture. Every cluster is then submitted to surface water detection by considering spectral information. Finally, the surface water bodies are outlined with sharp interregional boundaries and made visually vibrant. Thus the task of identification of water bodies is made simple, accurate and easy for the user with satisfactory qualitative analysis. Results obtained are compared with statistics obtained by structural filtering, NDVI method, and spectral segmentation method. The excellent potential surface water areas can be extracted by using the proposed method.

Implementation and Comparison of Image Enhancement Techniques Using Low Resolution IRS-1C LISS III Image

Asian Journal of Computer Science and Technology, May 5, 2018

Image enhancement is the primary step in image processing. Image enhancement improves the interpr... more Image enhancement is the primary step in image processing. Image enhancement improves the interpretation and makes the image visually clear. In this process pixels of input image were fine-tuned, so that the results are more suitable for display or further image analysis. Numerical manipulation of digital image includes pre-processing as the preliminary step of analysis. Contrast manipulation, spatial filtering, noise suppression and color processing are different methods of image enhancement. Choosing suitable method for satellite image enhancement depends on the application. This paper aims to compare results of various image enhancement techniques using an IRS-1C LISS III satellite image. It attempts to assess enhancement techniques. Shortcomings and general requirements in enhancement techniques were also discussed. This study gives promising directions on research using IRS-1C LISS III image enhancement for future research.

Low level vision processing and vegetation extraction using IRS-1C LISS III image

2016 International Conference on Signal and Information Processing (IConSIP), 2016

Removal of noise is essential for remote sensing applications, as its existence in images is inev... more Removal of noise is essential for remote sensing applications, as its existence in images is inevitable and results in random misrepresentations to the region of interest, in the image. This paper proposes a method for low level vision processing and vegetation feature extraction for IRS-1C LISS III remote sensing images using a combination of partial differential equations (PDEs), and normalized band ratioing method in order pre-process and to extract vegetation features. The purpose of image low level vision processing was to remove the effect of noise, edge conservation, making the resulting segmented vegetation feature images approximate the ideal image. Effectiveness of the algorithm was proven statistically and visual interpretations of results are clearer. Results show that, the proposed algorithm obtains better performance on different frames of the study area with higher PSNR values, reduced RMSE and enhanced visual quality.

Vegetation extraction based on spectral deviations using an IRS-1C LISS III image

2016 International Conference on Wireless Communications, Signal Processing and Networking (WiSPNET), 2016

Analysis of remote sensing data is faced with number of challenges ranging from spectral response... more Analysis of remote sensing data is faced with number of challenges ranging from spectral responses of satellite sensors, resolutions in different domains and interpretations; it directly depends on uniqueness of above features. This paper reports on the extraction of vegetation in an urban environment, by applying Normalized Vegetation Index (NDVI) and proposed Color based vegetation extraction; with emphasis on spectral responses of satellite sensors. The multispectral image from IRS-1C LISS III sensor data has been used as the primary data to produce land cover vegetation extraction. The objective was to extract the land use vegetation pattern automatically by proposed color segmentation and results were compared with NDVI results. The study shows, NDVI output was threshold dependent, whereas proposed, color based feature extraction was an automatic method with greater degree of accuracy.

Initiatives of Skills University and significance for youth empowerment in India

Journal of extension systems, 2021

India can become a major skilled youth workforce provider catering to global needs and its own ne... more India can become a major skilled youth workforce provider catering to global needs and its own needs. In past, education and skilling stand as parallel and independent streams. Need based frame work has to be developed to upgrade skill education to global standards by working in the lines of Government of India`s Skill Mission. This study analyses how promoting excellence in Skill Education in close association with industry, and boost economic status of youth by enhancing employability or establish as an entrepreneur. So, setting up skills universities will address the challenge of student mobilization through National Standard Qualification Framework. A skills university must have the dynamism to follow a demand-driven model following the work-integrated training model or the institutional model or a combination of both. Findings provide a unique insight into the requirement of Skills University. Findings highlights that Skills University canemerge as one of the common platform to...

Vegetation extraction from multi sensor IRS-1C LISS III image by principle Component Analysis and comparative assessment

2016 2nd International Conference on Advances in Electrical, Electronics, Information, Communication and Bio-Informatics (AEEICB), 2016

Satellite Remote Sensing data analysis is faced with number of challenges ranging from spectral r... more Satellite Remote Sensing data analysis is faced with number of challenges ranging from spectral responses of satellite sensors, resolutions in different domains and qualitative and quantitative interpretation. Feature extraction from satellite imagery directly depends on uniqueness of above features. This study highlighted the usefulness of Principal Component Analysis in processing of multispectral satellite images for vegetation land cover feature. PCA method was employed for efficient vegetation extraction. Results were assessed by comparing with traditional vegetation extraction methods: normalized Difference Vegetation Index (NDVI) and RGB color based detection. In this algorithm, PCA was applied to Indian Remote Sensing-1C Linear Integrated self-scanning (IRS IC-LISS III) sensor data set with the objective of mapping the occurrence vegetation to achieve land cover vegetation classification. The results illustrated that PCA based technique had ability to provide vegetation info...

An approach for vegetation mapping and pixel-based change detection for IRS-1C LISS III data

Monitoring and tracking vegetation changes in vast and remote areas is a difficult task. Accurate... more Monitoring and tracking vegetation changes in vast and remote areas is a difficult task. Accurate extraction of existing vegetation is the primary step for better statistical assessment. An approach for vegetation mapping is proposed which automatically explores spectral characteristics of connected components in an image. Different frames of multi-spectral Indian Remote sensing IRS-1C LISS III (Linear Imaging Self-Scanning Sensor) data of different times were used for comprehensive view of vegetation cover. First, quantum of vegetation cover was extracted using band indexing and brightness manipulating techniques for geometrically registered multi-temporal image pair. Secondly, pixel based image differencing method was employed to determine the temporal changes. The accuracy of vegetation extraction was found to be satisfactory by comparing the results with Normalized Difference Vegetation Index vegetation extraction method. Pixel based change analysis technique was assessed statis...

Detection and Analysis of Urban Change in Remotely Sensed Imagery by Principal Component Analysis of Image Data

This paper exhibits the time variant multispectral transformation of image data for detection and... more This paper exhibits the time variant multispectral transformation of image data for detection and analysis of urban changes across two or more images over time. The technique covered, which appeal directly to the vector nature of the image, includes, the principal component analysis transformation (PCA). The usefulness of PCA in processing of multispectral satellite images has been highlighted. PCA reduces image dimensionality by defining new, uncorrelated bands composed of the principal components (PCs) of the input bands. Thus, this method transforms the original data set into a new dataset, which captures better the essential information. IRS IC LISS III images of 2002 and 2011 of Gulbarga area were geometrically co-registered on which PCA for the urban change Detection was undertaken. A colour composite of Eigen images from the resulting PCA was used for analysis of urban change. It has been experienced that PCA effectively summarize the dominant modes of spatial, spectral and t...

Interpretation of IRS-1C LISS Imagery for Vegetation Extraction: A Spectral Perspective

The ecological mapping and monitoring can be done by satellite remote sensing with repetitive, mu... more The ecological mapping and monitoring can be done by satellite remote sensing with repetitive, multispectral and synoptic viewing capabilities. This paper reports on the interpretation of vegetation by exploring of some of the existing interpretation methods such as NDVI and K-means clustering, with emphasis on spectral responses of vegetation features. Indian Remote Sensing IC Linear Integrated self-scanning (IRS IC-LISS III) imagery data set was used for the study. The results show that spectral responses play an important role for automatic vegetation feature extraction by setting the predefined thresholds. The interpretation was based on the spectral reflectance of the vegetation pixels. Visual analysis of the resultant image depicts vegetation features extracted from the study image and discriminable classification of the vegetation was also achieved.

Extraction and delineation of water bodies from IRS-1C LISS III imagery

2016 IEEE Annual India Conference (INDICON), 2016

Water resources monitoring and management plays a crucial role to maintain an ecological balance.... more Water resources monitoring and management plays a crucial role to maintain an ecological balance. Proper survey, extraction and delineation of water bodies has to be done before any land use planning. Existing methods in the literature are subjective. An automatic and accurate water extraction method was proposed in this paper. Objective of the study was to separate water and non-water features and to delineate the water source boundaries. Qualitative analysis was done visually and results were found to be satisfactory. Quantitative validation of results was done by statistical comparison with results reported from Normalized Difference Water index method. The proposed algorithm outcomes as a quick method for extraction and delineation water areas.

Automated extraction and discrimination of open land areas from IRS-1C LISS III imagery

International Journal of Computers and Applications, 2018

Availability of open land area is a key indicator in assessing and planning urban environments. H... more Availability of open land area is a key indicator in assessing and planning urban environments. However, accurate uninhabited surface extraction is still a challenge. In this paper an attempt is made to combine the advantages of partial differential equation (PDE) and random forest (RF) method for segmentation of IRS-1C LISS III satellite image for mapping and discrimination of open land areas. Spatial variations of the pixels in the image are analyzed to identify open land pixels. PDE method denoise and conserve finer details simultaneously by using correlation between the spectral bands and directions of the edges. Low-resolution resultant image patch is mapped to high-resolution image patch by linear regression model. Variance of classification is reduced by training many classifiers using interpolated RF method. This methods elevates the accuracy of the direct RF method and achieves 3.35 dB improvement in PSNR and 6.47 reduction in MSE. Further, discrimination of open land areas is done into distinct classes, using inherent spatial information. Accuracy assessment indicates an overall accuracy of 87% over direct RF method.

Urban land use dynamics and change implication by using low-resolution LISS III imagery

International Journal of Computers and Applications, 2019

Extension of urban areas is augmented reality. Identification of urban areas and mapping urban sp... more Extension of urban areas is augmented reality. Identification of urban areas and mapping urban sprawl is directly related to population growth. Very frequent identification and monitoring of urban change are needed for urban governance and planners. The objective of the proposed paper was to extract the urban land cover by locating the human settlement areas and to develop a model to map potential spatio-temporal urban expansion. Multi-temporal imagery of Kalaburgai, state of Karnataka, India has been used for the work. The imagery was subjected for supervised fuzzy classification to extract spatial information of the urban area, Principal Component Analysis to transform the correlated components and lastly, unsupervised post classification on composite PCA images to separate uncorrelated pixels. Uncorrelated pixels depict the temporal change data. Results were satisfying, with 5.53 percentage area of urban change implications. Finally, the accuracy assessment of the proposed method shows promising results with an overall accuracy to be 80% and 0.78 for the kappa coefficient. Quantification of urban areas and probabilities of villages changing into cities can be done accurately by the proposed method. Significant urban expansion was observed by the results in Kalaburagi city from 2010 to 2013 with mostly vegetation changing into urban encroachment.

The Vegetation Extraction and Hierarchical Classification using an IRS-1C LISS III Image

International Journal of Computer Applications, 2016

Extraction of vegetation is an important step for agricultural, forest and greenery mapping. The ... more Extraction of vegetation is an important step for agricultural, forest and greenery mapping. The proposed method examines the complex process of land cover vegetation pattern classification using an IRS-1C LISS III image. Pre-processing was done by employing partial differential equation (PDE). Normalized differential vegetation index (NDVI) was applied to separate vegetation features from the image. Agricultural and non-agricultural vegetation features were the major and divergent hierarchical trends, which were observed. Further, classification was done by generating grey Level Co-occurrence Matrix (GLCM). Goal of this paper was to explore vegetation patterns by masking other features and identification of different vegetation patterns. Firstly, area of different land covered features was calculated. Then vegetation occupancy was calculated. finally, hierarchal separation of vegetation types was done to extract various vegetation patterns. Further, ground truth verification was done by Google Earth Images of same period, of relatively same area. From the results, it was demonstrated that various vegetation patterns were extracted, accurately and automatically.

Study of IRS 1C-LISS III Image and Identification of land cover features based on Spectral Responses

Satellite Remote sensing with repetitive and pan viewing and multispectral capabilities, is a pow... more Satellite Remote sensing with repetitive and pan viewing and multispectral capabilities, is a powerful tool for mapping and monitoring the ecological changes. Analysis of the remote sensing data is faced with a number of challenges ranging from type of sensors, number of sensors, spectral responses of satellite sensors, resolutions in different domains and qualitative and quantitative interpretation. Any analysis of satellite imagery directly depends on the uniqueness of above features. The multispectral image from IRS LISS-III sensor has been used as the primary data to produce land cover classification. This paper reports on the study of LISS III image, with emphasis on spectral responses of satellite sensors. The aim of the study was to know all the relative details of the data as the primary requirement for any study. Indian Remote Sensing IC Linear Integrated self-scanning (IRS IC-LISS III) imagery data set specifications and its use for land cover classification were also discussed. This study can be used as a primary literature for analysis of IRS LISS III Image.

IRS‐1C LISS III画像を用いた低レベル視覚処理と植生抽出【Powered by NICT】

IEEE Conference Proceedings, 2016

IRS‐1C LISS III画像からの水塊の抽出と描写【Powered by NICT】

IEEE Conference Proceedings, 2016

Vocational Skill Development Imperative for Women Empowerment in India

Journal of Women Empowerment and Studies

This study focuses on identifying inherent skills in women and the need for women to develop voca... more This study focuses on identifying inherent skills in women and the need for women to develop vocational skills. Awareness of various government schemes and the benefits of being a skilled woman is highlighted. An empirical study has been made to collect information and statistical data. A strength, weakness, opportunity, and threat (SWOT) analysis is carried out. The findings are promising. Skill development teaches women about power from within, decision-making power, control over financial, physical, and knowledge-based assets, and power with ability. Homemakers will soon become breadwinners, and vice versa, depending on suitability and necessity. These days are not far. A skill-armed woman is a home to a self-sustaining life. Equipping women with employable vocational skills in India can certainly lead to an “equal skill, equal pay” scenario.

Exigency of establishment of Skills University in Kalyana-Karnataka region of Karnataka state

Skills University (SU) is crucial to improve the standard of living of youth by making them more ... more Skills University (SU) is crucial to improve the standard of living of youth by making them more employable in Kalyana-Karnataka (KK) region. Till now, very few research works have been conducted related to the establishment of SU in backward areas and very few SU exists pan India. The methodology is conceived by collecting primary inputs from the statistics available on the global open platforms and amount of practical knowledge acquisition is empirical. Analysis shows that there is exigency of SU in KK region to remove the perception of regional imbalance , avoid reluctance of youth to opt vocational education. Restructuring of youth thinking by removing inferior perception on skill education as compared to formal education. The study implies that after completion of this skill education in SU majority of the youth enhance their confidence level to start their own enterprise without depending on others/ to get jobs in local. 9. Conclusion Kalyana Karnataka (KK) region is on the wa...

Colour transformed clustering-based water body extraction using IRS-1C LISS III image

International Journal of Spatio-Temporal Data Science, 2019

The algorithm presented in this research article extracts and delineates the water areas using IR... more The algorithm presented in this research article extracts and delineates the water areas using IRS-1C LISS III images. Methods available in the literature are biased with user-defined thresholds. The objective of the proposed algorithm is to provide accurate information about surface water. Initially, the input image is subjected to colour transformation clustering to extract all the similar hydrological characteristics geo-spatial features in the picture. Every cluster is then submitted to surface water detection by considering spectral information. Finally, the surface water bodies are outlined with sharp interregional boundaries and made visually vibrant. Thus the task of identification of water bodies is made simple, accurate and easy for the user with satisfactory qualitative analysis. Results obtained are compared with statistics obtained by structural filtering, NDVI method, and spectral segmentation method. The excellent potential surface water areas can be extracted by using the proposed method.

Implementation and Comparison of Image Enhancement Techniques Using Low Resolution IRS-1C LISS III Image

Asian Journal of Computer Science and Technology, May 5, 2018

Image enhancement is the primary step in image processing. Image enhancement improves the interpr... more Image enhancement is the primary step in image processing. Image enhancement improves the interpretation and makes the image visually clear. In this process pixels of input image were fine-tuned, so that the results are more suitable for display or further image analysis. Numerical manipulation of digital image includes pre-processing as the preliminary step of analysis. Contrast manipulation, spatial filtering, noise suppression and color processing are different methods of image enhancement. Choosing suitable method for satellite image enhancement depends on the application. This paper aims to compare results of various image enhancement techniques using an IRS-1C LISS III satellite image. It attempts to assess enhancement techniques. Shortcomings and general requirements in enhancement techniques were also discussed. This study gives promising directions on research using IRS-1C LISS III image enhancement for future research.

Low level vision processing and vegetation extraction using IRS-1C LISS III image

2016 International Conference on Signal and Information Processing (IConSIP), 2016

Removal of noise is essential for remote sensing applications, as its existence in images is inev... more Removal of noise is essential for remote sensing applications, as its existence in images is inevitable and results in random misrepresentations to the region of interest, in the image. This paper proposes a method for low level vision processing and vegetation feature extraction for IRS-1C LISS III remote sensing images using a combination of partial differential equations (PDEs), and normalized band ratioing method in order pre-process and to extract vegetation features. The purpose of image low level vision processing was to remove the effect of noise, edge conservation, making the resulting segmented vegetation feature images approximate the ideal image. Effectiveness of the algorithm was proven statistically and visual interpretations of results are clearer. Results show that, the proposed algorithm obtains better performance on different frames of the study area with higher PSNR values, reduced RMSE and enhanced visual quality.

Vegetation extraction based on spectral deviations using an IRS-1C LISS III image

2016 International Conference on Wireless Communications, Signal Processing and Networking (WiSPNET), 2016

Analysis of remote sensing data is faced with number of challenges ranging from spectral response... more Analysis of remote sensing data is faced with number of challenges ranging from spectral responses of satellite sensors, resolutions in different domains and interpretations; it directly depends on uniqueness of above features. This paper reports on the extraction of vegetation in an urban environment, by applying Normalized Vegetation Index (NDVI) and proposed Color based vegetation extraction; with emphasis on spectral responses of satellite sensors. The multispectral image from IRS-1C LISS III sensor data has been used as the primary data to produce land cover vegetation extraction. The objective was to extract the land use vegetation pattern automatically by proposed color segmentation and results were compared with NDVI results. The study shows, NDVI output was threshold dependent, whereas proposed, color based feature extraction was an automatic method with greater degree of accuracy.

Initiatives of Skills University and significance for youth empowerment in India

Journal of extension systems, 2021

India can become a major skilled youth workforce provider catering to global needs and its own ne... more India can become a major skilled youth workforce provider catering to global needs and its own needs. In past, education and skilling stand as parallel and independent streams. Need based frame work has to be developed to upgrade skill education to global standards by working in the lines of Government of India`s Skill Mission. This study analyses how promoting excellence in Skill Education in close association with industry, and boost economic status of youth by enhancing employability or establish as an entrepreneur. So, setting up skills universities will address the challenge of student mobilization through National Standard Qualification Framework. A skills university must have the dynamism to follow a demand-driven model following the work-integrated training model or the institutional model or a combination of both. Findings provide a unique insight into the requirement of Skills University. Findings highlights that Skills University canemerge as one of the common platform to...

Vegetation extraction from multi sensor IRS-1C LISS III image by principle Component Analysis and comparative assessment

2016 2nd International Conference on Advances in Electrical, Electronics, Information, Communication and Bio-Informatics (AEEICB), 2016

Satellite Remote Sensing data analysis is faced with number of challenges ranging from spectral r... more Satellite Remote Sensing data analysis is faced with number of challenges ranging from spectral responses of satellite sensors, resolutions in different domains and qualitative and quantitative interpretation. Feature extraction from satellite imagery directly depends on uniqueness of above features. This study highlighted the usefulness of Principal Component Analysis in processing of multispectral satellite images for vegetation land cover feature. PCA method was employed for efficient vegetation extraction. Results were assessed by comparing with traditional vegetation extraction methods: normalized Difference Vegetation Index (NDVI) and RGB color based detection. In this algorithm, PCA was applied to Indian Remote Sensing-1C Linear Integrated self-scanning (IRS IC-LISS III) sensor data set with the objective of mapping the occurrence vegetation to achieve land cover vegetation classification. The results illustrated that PCA based technique had ability to provide vegetation info...

An approach for vegetation mapping and pixel-based change detection for IRS-1C LISS III data

Monitoring and tracking vegetation changes in vast and remote areas is a difficult task. Accurate... more Monitoring and tracking vegetation changes in vast and remote areas is a difficult task. Accurate extraction of existing vegetation is the primary step for better statistical assessment. An approach for vegetation mapping is proposed which automatically explores spectral characteristics of connected components in an image. Different frames of multi-spectral Indian Remote sensing IRS-1C LISS III (Linear Imaging Self-Scanning Sensor) data of different times were used for comprehensive view of vegetation cover. First, quantum of vegetation cover was extracted using band indexing and brightness manipulating techniques for geometrically registered multi-temporal image pair. Secondly, pixel based image differencing method was employed to determine the temporal changes. The accuracy of vegetation extraction was found to be satisfactory by comparing the results with Normalized Difference Vegetation Index vegetation extraction method. Pixel based change analysis technique was assessed statis...

Detection and Analysis of Urban Change in Remotely Sensed Imagery by Principal Component Analysis of Image Data

This paper exhibits the time variant multispectral transformation of image data for detection and... more This paper exhibits the time variant multispectral transformation of image data for detection and analysis of urban changes across two or more images over time. The technique covered, which appeal directly to the vector nature of the image, includes, the principal component analysis transformation (PCA). The usefulness of PCA in processing of multispectral satellite images has been highlighted. PCA reduces image dimensionality by defining new, uncorrelated bands composed of the principal components (PCs) of the input bands. Thus, this method transforms the original data set into a new dataset, which captures better the essential information. IRS IC LISS III images of 2002 and 2011 of Gulbarga area were geometrically co-registered on which PCA for the urban change Detection was undertaken. A colour composite of Eigen images from the resulting PCA was used for analysis of urban change. It has been experienced that PCA effectively summarize the dominant modes of spatial, spectral and t...

Interpretation of IRS-1C LISS Imagery for Vegetation Extraction: A Spectral Perspective

The ecological mapping and monitoring can be done by satellite remote sensing with repetitive, mu... more The ecological mapping and monitoring can be done by satellite remote sensing with repetitive, multispectral and synoptic viewing capabilities. This paper reports on the interpretation of vegetation by exploring of some of the existing interpretation methods such as NDVI and K-means clustering, with emphasis on spectral responses of vegetation features. Indian Remote Sensing IC Linear Integrated self-scanning (IRS IC-LISS III) imagery data set was used for the study. The results show that spectral responses play an important role for automatic vegetation feature extraction by setting the predefined thresholds. The interpretation was based on the spectral reflectance of the vegetation pixels. Visual analysis of the resultant image depicts vegetation features extracted from the study image and discriminable classification of the vegetation was also achieved.

Extraction and delineation of water bodies from IRS-1C LISS III imagery

2016 IEEE Annual India Conference (INDICON), 2016

Water resources monitoring and management plays a crucial role to maintain an ecological balance.... more Water resources monitoring and management plays a crucial role to maintain an ecological balance. Proper survey, extraction and delineation of water bodies has to be done before any land use planning. Existing methods in the literature are subjective. An automatic and accurate water extraction method was proposed in this paper. Objective of the study was to separate water and non-water features and to delineate the water source boundaries. Qualitative analysis was done visually and results were found to be satisfactory. Quantitative validation of results was done by statistical comparison with results reported from Normalized Difference Water index method. The proposed algorithm outcomes as a quick method for extraction and delineation water areas.

Automated extraction and discrimination of open land areas from IRS-1C LISS III imagery

International Journal of Computers and Applications, 2018

Availability of open land area is a key indicator in assessing and planning urban environments. H... more Availability of open land area is a key indicator in assessing and planning urban environments. However, accurate uninhabited surface extraction is still a challenge. In this paper an attempt is made to combine the advantages of partial differential equation (PDE) and random forest (RF) method for segmentation of IRS-1C LISS III satellite image for mapping and discrimination of open land areas. Spatial variations of the pixels in the image are analyzed to identify open land pixels. PDE method denoise and conserve finer details simultaneously by using correlation between the spectral bands and directions of the edges. Low-resolution resultant image patch is mapped to high-resolution image patch by linear regression model. Variance of classification is reduced by training many classifiers using interpolated RF method. This methods elevates the accuracy of the direct RF method and achieves 3.35 dB improvement in PSNR and 6.47 reduction in MSE. Further, discrimination of open land areas is done into distinct classes, using inherent spatial information. Accuracy assessment indicates an overall accuracy of 87% over direct RF method.

Urban land use dynamics and change implication by using low-resolution LISS III imagery

International Journal of Computers and Applications, 2019

Extension of urban areas is augmented reality. Identification of urban areas and mapping urban sp... more Extension of urban areas is augmented reality. Identification of urban areas and mapping urban sprawl is directly related to population growth. Very frequent identification and monitoring of urban change are needed for urban governance and planners. The objective of the proposed paper was to extract the urban land cover by locating the human settlement areas and to develop a model to map potential spatio-temporal urban expansion. Multi-temporal imagery of Kalaburgai, state of Karnataka, India has been used for the work. The imagery was subjected for supervised fuzzy classification to extract spatial information of the urban area, Principal Component Analysis to transform the correlated components and lastly, unsupervised post classification on composite PCA images to separate uncorrelated pixels. Uncorrelated pixels depict the temporal change data. Results were satisfying, with 5.53 percentage area of urban change implications. Finally, the accuracy assessment of the proposed method shows promising results with an overall accuracy to be 80% and 0.78 for the kappa coefficient. Quantification of urban areas and probabilities of villages changing into cities can be done accurately by the proposed method. Significant urban expansion was observed by the results in Kalaburagi city from 2010 to 2013 with mostly vegetation changing into urban encroachment.

The Vegetation Extraction and Hierarchical Classification using an IRS-1C LISS III Image

International Journal of Computer Applications, 2016

Extraction of vegetation is an important step for agricultural, forest and greenery mapping. The ... more Extraction of vegetation is an important step for agricultural, forest and greenery mapping. The proposed method examines the complex process of land cover vegetation pattern classification using an IRS-1C LISS III image. Pre-processing was done by employing partial differential equation (PDE). Normalized differential vegetation index (NDVI) was applied to separate vegetation features from the image. Agricultural and non-agricultural vegetation features were the major and divergent hierarchical trends, which were observed. Further, classification was done by generating grey Level Co-occurrence Matrix (GLCM). Goal of this paper was to explore vegetation patterns by masking other features and identification of different vegetation patterns. Firstly, area of different land covered features was calculated. Then vegetation occupancy was calculated. finally, hierarchal separation of vegetation types was done to extract various vegetation patterns. Further, ground truth verification was done by Google Earth Images of same period, of relatively same area. From the results, it was demonstrated that various vegetation patterns were extracted, accurately and automatically.

Study of IRS 1C-LISS III Image and Identification of land cover features based on Spectral Responses

Satellite Remote sensing with repetitive and pan viewing and multispectral capabilities, is a pow... more Satellite Remote sensing with repetitive and pan viewing and multispectral capabilities, is a powerful tool for mapping and monitoring the ecological changes. Analysis of the remote sensing data is faced with a number of challenges ranging from type of sensors, number of sensors, spectral responses of satellite sensors, resolutions in different domains and qualitative and quantitative interpretation. Any analysis of satellite imagery directly depends on the uniqueness of above features. The multispectral image from IRS LISS-III sensor has been used as the primary data to produce land cover classification. This paper reports on the study of LISS III image, with emphasis on spectral responses of satellite sensors. The aim of the study was to know all the relative details of the data as the primary requirement for any study. Indian Remote Sensing IC Linear Integrated self-scanning (IRS IC-LISS III) imagery data set specifications and its use for land cover classification were also discussed. This study can be used as a primary literature for analysis of IRS LISS III Image.