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importance is the remote sensing and geographic information system (GIS) technique. Remote sensing is now recognized as an essential tool for viewing, analyzing, characterizing, and making decisions about land, water and atmospheric components. From a general perspective, remote sensing is the science of acquiring and analyzing information about objects or phenomena from a distance (Jensen, 1986; Lillesand and Keifer, 1987). Today, we define satellite remote sensing as the use of satellite borne sensors to observe, measure, and record the electromagnetic radiation (EMR) reflected or emitted by the earth and its environment for subsequent analysis and extraction of information. EMR sensors includes visible light, near-, mid- and far-infrared (thermal), microwave, and long-wave radio energy. The capability of multiple sources of information is unique to remote sensing. Of specific advantage is the spectral, temporal, and spatial resolution. Spectral resolution refers to the width or range of each spectral band being recorded. Since each target affects different wavelengths of incident energy differently, they are absorbed, reflected or transmitted in different proportions. Currently, there are many land resource remote sensing satellites that have sensors operating in the green, red, near infrared and short wave Infra red regions of the electromagnetic spectrum giving a definite spectral signature of various targets due to difference in radiation absorption and reflectance of targets. These sensors are of common use for land cover studies, including wetlands. Figure 1 shows typical spectral signature of few targets from green to SWIR region. Converted to image, in a typical false colour composite (FCC) created using NIR, red and green bands assigned as red, green and blue colour, the features become very distinct as shown in Figure 2 - a typical wetland located in Purba Champaran district. In FCC, the vegetation thus appears invariably red (due to high reflection in NIR from green leaves). Since the early 1960s, numerous satellite sensors have been launched into orbit to observe and monitor the earth and its environment. Most early satellite sensors acquired data for meteorological purposes. The advent of earth resources satellite sensors (those with a primary objective of mapping and monitoring land cover) occurred, when the first Landsat satellite was launched in July 1972. Currently, more than a dozen orbiting satellites of various types provide data crucial to improving our knowledge of the earth’s atmosphere, oceans, ice and snow, and land. Of particular interest to India is the indigenous series of satellites called Indian Remote Sensing satellites (IRS-Series). Since the launch of the first satellite IRS 1A in 1987, India has now a number of satellites providing data in multi-spectral bands with different spatial resolution. IRS P6/RESOURCESAT 1 is the current generation satellite that provides multi-spectral images in spatial resolution of 5.8 m (LISS IV), 23.5 m (LISS III) and 56m (AWiFS). Over the past few decades, IRS series data has been successfully used in various fields of natural resources ( Navalgund et al, 2002 ). Development of technologies like Geographic Information System (GIS) has enhanced the use of RS data to obtain accurate geospatial database. GIS specialises in handling related, spatially referenced data, combining mapped information with other data and acts as analytical tool for research and decision making. During the past few decades, technological advances in the field of satellite remote sensing (RS) sensors, computerized mapping techniques, global positioning system (GPS) and geographic information system (GIS) has enhanced the ability to capture more detailed and timely information about the natural resources at various scales catering to local, regional, national and global level study. Figure 1: Spectral Signature of various targets 2
Green Red NIR NIR RED GREEN SWIR Figure 2: Various wetland features as they appear in four spectral bands and in a typical three band FCC 3
Page 1 and 2: NATIONAL WETLAND ATLAS: BIHAR Spons
Page 3 and 4: Atlas SAC/RESA/AFEG/NWIA/ATLAS/23/2
Page 5: MESSAGE It gives me great pleasure
Page 9: ACKNOWLEDGEMENTS The project “Nat
Page 13 and 14: CONTENTS 1.0 INTRODUCTION 1.1 Wetla
Page 15: Table 35: Area estimates of wetland
Page 20 and 21: 1.3 Wetland Inventory of India Indi
Page 22 and 23: • Aquatic vegetation spread: The
Page 24 and 25: Figure 3: Location Map Figure 4: Sp
Page 26 and 27: Ground truth data Remotely sensed d
Page 28 and 29: The indices were generated using st
Page 30 and 31: 6.0 ACCURACY ASSESSMENT A comprehen
Page 33: MAPS AND STATISTICS 17
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Page 46: 7.1.2 Purba Champaran The Purba Cha
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7.1.8 Kishanganj The Kishanganj dis
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7.1.10 Katihar The district Katihar
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7.1.12 Saharsa The district lies be
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7.1.14 Muzaffarpur The district lie
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7.1.16 Siwan Siwan district lies be
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7.1.18 Vaishali Vaishali district l
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7.1.20 Begusarai The district lies
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7.1.21 Khagaria The district lies b
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7.1.22 Bhagalpur Bhagalpur district
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7.1.23 Banka The district lies betw
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7.1.24 Munger The district lies bet
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7.1.25 Lakhisarai The district lies
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7.1.26 Sheikhpura The district lies
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7.1.27 Nalanda The district lies be
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7.1.28 Patna Patna district lies be
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7.1.29 Bhojpur The district lies be
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7.1.30 Buxar The district lies betw
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7.1.31 Kaimur (Bhabua) The district
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7.1.32 Rohtas The district lies bet
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7.1.33 Jehanabad The district lies
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7.1.34 Aurangabad The district lies
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7.1.35 Gaya The district lies betwe
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7.1.36 Nawada The district lies bet
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7.1.37 Jamui The district lies betw
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Sr. No. Description Field Photograp
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Sr. No. Description Field Photograp
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9.1 Khabar Tal Wetland Type: Natura
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9.2 Moti Jheel Wetland Type: Ox-bow
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9.3 Mora Mahananda Tal Wetland Type
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9.4 Bawlee Chaur Wetland Type: Natu
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9.5 Kosi/Belasi Dam Wetland Type: R
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1202 Tanks/Ponds: A term used in Ce
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Space Applications centre Indian Sp
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