A Review of IRS-1C Applications in Urban and Regional Studies, and Infrastructure Planning
Abstract The multifaceted data from Indian remote sensing satellite (IRS)-1C with Panchromatic (PAN, 5.8 m, 0.50–0.75 μm), Linear Imaging Self-Scanning Sensor-III (LISS-III, 23.5 m, four multi-spectral bands) and Wide Field Sensor (WiFS, 188 m, red and near-infrared bands) sensors onboard, along wit...
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| Autor*in: |
Kumar, Pramod [verfasserIn] Rao, K. Venugopala [verfasserIn] Ravindranath, Sudha [verfasserIn] Maithani, Sandeep [verfasserIn] Siddiqui, Asfa [verfasserIn] Bharath, B. D. [verfasserIn] Bhavani, S. V. L. [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2021 |
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| Schlagwörter: |
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| Übergeordnetes Werk: |
Enthalten in: Journal of the Indian Society of Remote Sensing - Neu Delhi : Springer India, 2008, 49(2021), 1 vom: Jan., Seite 161-177 |
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| Übergeordnetes Werk: |
volume:49 ; year:2021 ; number:1 ; month:01 ; pages:161-177 |
| Links: |
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| DOI / URN: |
10.1007/s12524-020-01283-5 |
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| Katalog-ID: |
SPR043423558 |
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| 520 | |a Abstract The multifaceted data from Indian remote sensing satellite (IRS)-1C with Panchromatic (PAN, 5.8 m, 0.50–0.75 μm), Linear Imaging Self-Scanning Sensor-III (LISS-III, 23.5 m, four multi-spectral bands) and Wide Field Sensor (WiFS, 188 m, red and near-infrared bands) sensors onboard, along with stereo imaging and 5-day revisit capability have been effectively utilised for mapping, monitoring, planning and development of urban and regional areas. It made possible to explore urban and regional areas either independently or in combination with other remote sensing data for base map preparation, land use survey and planning, growth modelling, environment and hazards analysis, utilities and infrastructure planning, etc. This review article articulates the scale and mapping potential of IRS-1C data for urban and regional areas, data fusion methods and information retrieval based on visual or digital image processing techniques, including advanced classifiers. It recapitulates the application potential demonstrated in last 25 years in urban and regional studies, and for infrastructure planning. | ||
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| 650 | 4 | |a Urban growth |7 (dpeaa)DE-He213 | |
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| 700 | 1 | |a Siddiqui, Asfa |e verfasserin |4 aut | |
| 700 | 1 | |a Bharath, B. D. |e verfasserin |4 aut | |
| 700 | 1 | |a Bhavani, S. V. L. |e verfasserin |4 aut | |
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10.1007/s12524-020-01283-5 doi (DE-627)SPR043423558 (DE-599)SPRs12524-020-01283-5-e (SPR)s12524-020-01283-5-e DE-627 ger DE-627 rakwb eng 550 ASE Kumar, Pramod verfasserin aut A Review of IRS-1C Applications in Urban and Regional Studies, and Infrastructure Planning 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract The multifaceted data from Indian remote sensing satellite (IRS)-1C with Panchromatic (PAN, 5.8 m, 0.50–0.75 μm), Linear Imaging Self-Scanning Sensor-III (LISS-III, 23.5 m, four multi-spectral bands) and Wide Field Sensor (WiFS, 188 m, red and near-infrared bands) sensors onboard, along with stereo imaging and 5-day revisit capability have been effectively utilised for mapping, monitoring, planning and development of urban and regional areas. It made possible to explore urban and regional areas either independently or in combination with other remote sensing data for base map preparation, land use survey and planning, growth modelling, environment and hazards analysis, utilities and infrastructure planning, etc. This review article articulates the scale and mapping potential of IRS-1C data for urban and regional areas, data fusion methods and information retrieval based on visual or digital image processing techniques, including advanced classifiers. It recapitulates the application potential demonstrated in last 25 years in urban and regional studies, and for infrastructure planning. IRS-1C (dpeaa)DE-He213 Urban (dpeaa)DE-He213 Regional (dpeaa)DE-He213 Image classification (dpeaa)DE-He213 Urban growth (dpeaa)DE-He213 Urban environment (dpeaa)DE-He213 Rao, K. Venugopala verfasserin aut Ravindranath, Sudha verfasserin aut Maithani, Sandeep verfasserin aut Siddiqui, Asfa verfasserin aut Bharath, B. D. verfasserin aut Bhavani, S. V. L. verfasserin aut Enthalten in Journal of the Indian Society of Remote Sensing Neu Delhi : Springer India, 2008 49(2021), 1 vom: Jan., Seite 161-177 (DE-627)573088853 (DE-600)2439566-3 0974-3006 nnns volume:49 year:2021 number:1 month:01 pages:161-177 https://dx.doi.org/10.1007/s12524-020-01283-5 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OPC-FOR SSG-OPC-ASE GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 49 2021 1 01 161-177 |
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10.1007/s12524-020-01283-5 doi (DE-627)SPR043423558 (DE-599)SPRs12524-020-01283-5-e (SPR)s12524-020-01283-5-e DE-627 ger DE-627 rakwb eng 550 ASE Kumar, Pramod verfasserin aut A Review of IRS-1C Applications in Urban and Regional Studies, and Infrastructure Planning 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract The multifaceted data from Indian remote sensing satellite (IRS)-1C with Panchromatic (PAN, 5.8 m, 0.50–0.75 μm), Linear Imaging Self-Scanning Sensor-III (LISS-III, 23.5 m, four multi-spectral bands) and Wide Field Sensor (WiFS, 188 m, red and near-infrared bands) sensors onboard, along with stereo imaging and 5-day revisit capability have been effectively utilised for mapping, monitoring, planning and development of urban and regional areas. It made possible to explore urban and regional areas either independently or in combination with other remote sensing data for base map preparation, land use survey and planning, growth modelling, environment and hazards analysis, utilities and infrastructure planning, etc. This review article articulates the scale and mapping potential of IRS-1C data for urban and regional areas, data fusion methods and information retrieval based on visual or digital image processing techniques, including advanced classifiers. It recapitulates the application potential demonstrated in last 25 years in urban and regional studies, and for infrastructure planning. IRS-1C (dpeaa)DE-He213 Urban (dpeaa)DE-He213 Regional (dpeaa)DE-He213 Image classification (dpeaa)DE-He213 Urban growth (dpeaa)DE-He213 Urban environment (dpeaa)DE-He213 Rao, K. Venugopala verfasserin aut Ravindranath, Sudha verfasserin aut Maithani, Sandeep verfasserin aut Siddiqui, Asfa verfasserin aut Bharath, B. D. verfasserin aut Bhavani, S. V. L. verfasserin aut Enthalten in Journal of the Indian Society of Remote Sensing Neu Delhi : Springer India, 2008 49(2021), 1 vom: Jan., Seite 161-177 (DE-627)573088853 (DE-600)2439566-3 0974-3006 nnns volume:49 year:2021 number:1 month:01 pages:161-177 https://dx.doi.org/10.1007/s12524-020-01283-5 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OPC-FOR SSG-OPC-ASE GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 49 2021 1 01 161-177 |
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10.1007/s12524-020-01283-5 doi (DE-627)SPR043423558 (DE-599)SPRs12524-020-01283-5-e (SPR)s12524-020-01283-5-e DE-627 ger DE-627 rakwb eng 550 ASE Kumar, Pramod verfasserin aut A Review of IRS-1C Applications in Urban and Regional Studies, and Infrastructure Planning 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract The multifaceted data from Indian remote sensing satellite (IRS)-1C with Panchromatic (PAN, 5.8 m, 0.50–0.75 μm), Linear Imaging Self-Scanning Sensor-III (LISS-III, 23.5 m, four multi-spectral bands) and Wide Field Sensor (WiFS, 188 m, red and near-infrared bands) sensors onboard, along with stereo imaging and 5-day revisit capability have been effectively utilised for mapping, monitoring, planning and development of urban and regional areas. It made possible to explore urban and regional areas either independently or in combination with other remote sensing data for base map preparation, land use survey and planning, growth modelling, environment and hazards analysis, utilities and infrastructure planning, etc. This review article articulates the scale and mapping potential of IRS-1C data for urban and regional areas, data fusion methods and information retrieval based on visual or digital image processing techniques, including advanced classifiers. It recapitulates the application potential demonstrated in last 25 years in urban and regional studies, and for infrastructure planning. IRS-1C (dpeaa)DE-He213 Urban (dpeaa)DE-He213 Regional (dpeaa)DE-He213 Image classification (dpeaa)DE-He213 Urban growth (dpeaa)DE-He213 Urban environment (dpeaa)DE-He213 Rao, K. Venugopala verfasserin aut Ravindranath, Sudha verfasserin aut Maithani, Sandeep verfasserin aut Siddiqui, Asfa verfasserin aut Bharath, B. D. verfasserin aut Bhavani, S. V. L. verfasserin aut Enthalten in Journal of the Indian Society of Remote Sensing Neu Delhi : Springer India, 2008 49(2021), 1 vom: Jan., Seite 161-177 (DE-627)573088853 (DE-600)2439566-3 0974-3006 nnns volume:49 year:2021 number:1 month:01 pages:161-177 https://dx.doi.org/10.1007/s12524-020-01283-5 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OPC-FOR SSG-OPC-ASE GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 49 2021 1 01 161-177 |
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10.1007/s12524-020-01283-5 doi (DE-627)SPR043423558 (DE-599)SPRs12524-020-01283-5-e (SPR)s12524-020-01283-5-e DE-627 ger DE-627 rakwb eng 550 ASE Kumar, Pramod verfasserin aut A Review of IRS-1C Applications in Urban and Regional Studies, and Infrastructure Planning 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract The multifaceted data from Indian remote sensing satellite (IRS)-1C with Panchromatic (PAN, 5.8 m, 0.50–0.75 μm), Linear Imaging Self-Scanning Sensor-III (LISS-III, 23.5 m, four multi-spectral bands) and Wide Field Sensor (WiFS, 188 m, red and near-infrared bands) sensors onboard, along with stereo imaging and 5-day revisit capability have been effectively utilised for mapping, monitoring, planning and development of urban and regional areas. It made possible to explore urban and regional areas either independently or in combination with other remote sensing data for base map preparation, land use survey and planning, growth modelling, environment and hazards analysis, utilities and infrastructure planning, etc. This review article articulates the scale and mapping potential of IRS-1C data for urban and regional areas, data fusion methods and information retrieval based on visual or digital image processing techniques, including advanced classifiers. It recapitulates the application potential demonstrated in last 25 years in urban and regional studies, and for infrastructure planning. IRS-1C (dpeaa)DE-He213 Urban (dpeaa)DE-He213 Regional (dpeaa)DE-He213 Image classification (dpeaa)DE-He213 Urban growth (dpeaa)DE-He213 Urban environment (dpeaa)DE-He213 Rao, K. Venugopala verfasserin aut Ravindranath, Sudha verfasserin aut Maithani, Sandeep verfasserin aut Siddiqui, Asfa verfasserin aut Bharath, B. D. verfasserin aut Bhavani, S. V. L. verfasserin aut Enthalten in Journal of the Indian Society of Remote Sensing Neu Delhi : Springer India, 2008 49(2021), 1 vom: Jan., Seite 161-177 (DE-627)573088853 (DE-600)2439566-3 0974-3006 nnns volume:49 year:2021 number:1 month:01 pages:161-177 https://dx.doi.org/10.1007/s12524-020-01283-5 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OPC-FOR SSG-OPC-ASE GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 49 2021 1 01 161-177 |
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10.1007/s12524-020-01283-5 doi (DE-627)SPR043423558 (DE-599)SPRs12524-020-01283-5-e (SPR)s12524-020-01283-5-e DE-627 ger DE-627 rakwb eng 550 ASE Kumar, Pramod verfasserin aut A Review of IRS-1C Applications in Urban and Regional Studies, and Infrastructure Planning 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract The multifaceted data from Indian remote sensing satellite (IRS)-1C with Panchromatic (PAN, 5.8 m, 0.50–0.75 μm), Linear Imaging Self-Scanning Sensor-III (LISS-III, 23.5 m, four multi-spectral bands) and Wide Field Sensor (WiFS, 188 m, red and near-infrared bands) sensors onboard, along with stereo imaging and 5-day revisit capability have been effectively utilised for mapping, monitoring, planning and development of urban and regional areas. It made possible to explore urban and regional areas either independently or in combination with other remote sensing data for base map preparation, land use survey and planning, growth modelling, environment and hazards analysis, utilities and infrastructure planning, etc. This review article articulates the scale and mapping potential of IRS-1C data for urban and regional areas, data fusion methods and information retrieval based on visual or digital image processing techniques, including advanced classifiers. It recapitulates the application potential demonstrated in last 25 years in urban and regional studies, and for infrastructure planning. IRS-1C (dpeaa)DE-He213 Urban (dpeaa)DE-He213 Regional (dpeaa)DE-He213 Image classification (dpeaa)DE-He213 Urban growth (dpeaa)DE-He213 Urban environment (dpeaa)DE-He213 Rao, K. Venugopala verfasserin aut Ravindranath, Sudha verfasserin aut Maithani, Sandeep verfasserin aut Siddiqui, Asfa verfasserin aut Bharath, B. D. verfasserin aut Bhavani, S. V. L. verfasserin aut Enthalten in Journal of the Indian Society of Remote Sensing Neu Delhi : Springer India, 2008 49(2021), 1 vom: Jan., Seite 161-177 (DE-627)573088853 (DE-600)2439566-3 0974-3006 nnns volume:49 year:2021 number:1 month:01 pages:161-177 https://dx.doi.org/10.1007/s12524-020-01283-5 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OPC-FOR SSG-OPC-ASE GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 49 2021 1 01 161-177 |
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Kumar, Pramod |
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550 ASE A Review of IRS-1C Applications in Urban and Regional Studies, and Infrastructure Planning IRS-1C (dpeaa)DE-He213 Urban (dpeaa)DE-He213 Regional (dpeaa)DE-He213 Image classification (dpeaa)DE-He213 Urban growth (dpeaa)DE-He213 Urban environment (dpeaa)DE-He213 |
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A Review of IRS-1C Applications in Urban and Regional Studies, and Infrastructure Planning |
| abstract |
Abstract The multifaceted data from Indian remote sensing satellite (IRS)-1C with Panchromatic (PAN, 5.8 m, 0.50–0.75 μm), Linear Imaging Self-Scanning Sensor-III (LISS-III, 23.5 m, four multi-spectral bands) and Wide Field Sensor (WiFS, 188 m, red and near-infrared bands) sensors onboard, along with stereo imaging and 5-day revisit capability have been effectively utilised for mapping, monitoring, planning and development of urban and regional areas. It made possible to explore urban and regional areas either independently or in combination with other remote sensing data for base map preparation, land use survey and planning, growth modelling, environment and hazards analysis, utilities and infrastructure planning, etc. This review article articulates the scale and mapping potential of IRS-1C data for urban and regional areas, data fusion methods and information retrieval based on visual or digital image processing techniques, including advanced classifiers. It recapitulates the application potential demonstrated in last 25 years in urban and regional studies, and for infrastructure planning. |
| abstractGer |
Abstract The multifaceted data from Indian remote sensing satellite (IRS)-1C with Panchromatic (PAN, 5.8 m, 0.50–0.75 μm), Linear Imaging Self-Scanning Sensor-III (LISS-III, 23.5 m, four multi-spectral bands) and Wide Field Sensor (WiFS, 188 m, red and near-infrared bands) sensors onboard, along with stereo imaging and 5-day revisit capability have been effectively utilised for mapping, monitoring, planning and development of urban and regional areas. It made possible to explore urban and regional areas either independently or in combination with other remote sensing data for base map preparation, land use survey and planning, growth modelling, environment and hazards analysis, utilities and infrastructure planning, etc. This review article articulates the scale and mapping potential of IRS-1C data for urban and regional areas, data fusion methods and information retrieval based on visual or digital image processing techniques, including advanced classifiers. It recapitulates the application potential demonstrated in last 25 years in urban and regional studies, and for infrastructure planning. |
| abstract_unstemmed |
Abstract The multifaceted data from Indian remote sensing satellite (IRS)-1C with Panchromatic (PAN, 5.8 m, 0.50–0.75 μm), Linear Imaging Self-Scanning Sensor-III (LISS-III, 23.5 m, four multi-spectral bands) and Wide Field Sensor (WiFS, 188 m, red and near-infrared bands) sensors onboard, along with stereo imaging and 5-day revisit capability have been effectively utilised for mapping, monitoring, planning and development of urban and regional areas. It made possible to explore urban and regional areas either independently or in combination with other remote sensing data for base map preparation, land use survey and planning, growth modelling, environment and hazards analysis, utilities and infrastructure planning, etc. This review article articulates the scale and mapping potential of IRS-1C data for urban and regional areas, data fusion methods and information retrieval based on visual or digital image processing techniques, including advanced classifiers. It recapitulates the application potential demonstrated in last 25 years in urban and regional studies, and for infrastructure planning. |
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| title_short |
A Review of IRS-1C Applications in Urban and Regional Studies, and Infrastructure Planning |
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https://dx.doi.org/10.1007/s12524-020-01283-5 |
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Rao, K. Venugopala Ravindranath, Sudha Maithani, Sandeep Siddiqui, Asfa Bharath, B. D. Bhavani, S. V. L. |
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Rao, K. Venugopala Ravindranath, Sudha Maithani, Sandeep Siddiqui, Asfa Bharath, B. D. Bhavani, S. V. L. |
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10.1007/s12524-020-01283-5 |
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| score |
7.399687 |