National Remote Sensing Agency Research Articles

Three Decades of Nationwide Forest Cover Mapping Using Indian Remote Sensing Satellite Data: A Success Story of Monitoring Forests for Conservation in India

India is a biodiversity-rich country. The panorama of Indian forests ranges from tropical evergreen rain forests in the Andaman and Nicobar Islands, the Western Ghats, and the north-eastern States, to Dry Alpine Scrub high in the Himalayas in the north. On the other extreme, tropical dry deciduous and thorn forest is found in the deserts and dry areas of Rajasthan and Gujarat. The variety and distribution of forest vegetation are large, and India is one of the 17 mega biodiversity regions of the world. Forestry in India supports a sizeable non-wood forest product-based economy apart from timber and fuelwood. In forested landscapes people are integrated with forest and make living out of it. On the other hand urbanization and infrastructure development are putting considerable pressure on forests. These issues need effective and efficient forest monitoring system. Hence in late 1980s, India entrusted Forest Survey of India to evolve robust and scientific method of forest monitoring. Thus, India has taken an early lead in establishing a forest monitoring system. The history of forest cover mapping using satellite images in the country goes back to 1983 when National Remote Sensing Agency (NRSA—now known as NRSC-ISRO) prepared the first-ever forest cover map of India. Later, Forest Survey of India has been mandated with the forest cover mapping of the country in the biennial cycle since 1987. Three decades of forest cover mapping on a regular basis have been a remarkable achievement in the field of natural resource monitoring. India’s remote sensing-based periodic monitoring of forest cover, which is unique in the world, has played a major role in conservation and enhancement of forest cover of the country. Evolving with satellite data improvement and technological advancements, the methodology of forest cover mapping by FSI has seen significant changes over the years, wherein Indian remote sensing data, particularly the IRS 1C/1D LISS III data, have been the primary input in the time series mapping. This paper reviews the chronology and significance of this important forest monitoring programme of India.

Mapping the Spatial Distributions of Water Quality and Their Interpolation with Land Use/Land Cover Using GIS and Remote Sensing in Noyyal River Basin, Tamil Nadu, India

Noyyal River is historically, ecologically and culturally significant river in Kongu region of western Tamilnadu. More than 100 villages are situated along the banks of the Noyyal River and it’s the was the best site of inhabitation on both the sides of the river up to 3 km from the river before the emergence of the issue of industrial pollution. But now river Noyyal was highly polluted by domestic and industrial growth by discharging of both domestic and industrial are discharged without any treatment. So methodology was proposed to identify the suitable zone for groundwater quality by using land use/land cover data along with groundwater quality in analytic hierarchy process. Suitability of groundwater for drinking was identified in the study area by collecting 63 samples in both postmonsoon and premonsoon as per Indian standards. To evaluate the land use pattern of the study area, land use/land cover map was prepared from satellite images of LISS III by using supervised classification according to National Remote Sensing Agency (NRSA) using Erdas imagine 8.4 software. Using ArcGIS software, weighted overlay analyses were carried out to identify the suitable zones for groundwater quality in postmonsoon and premonsoon and finally these two thematic maps were integrated with land use/land cover map to identify the suitable zone for quality of water. The interpretation shows that groundwater in most of the locations were unsuitable for drinking purposes.

Turnaround Challenges of a State-owned Enterprise: A Case Study of Orissa Remote Sensing Application Centre, India

Orissa Remote Sensing Applications Centre (ORSAC), an autonomous technology organization established by the Government of Orissa, had grown tremendously; developing competencies in the fields of remote sensing, geographic information system (GIS) and space technology. Since ORSAC was established by the Government of Orissa, ORSAC’s relationship with the state, Department of Science (DoS), National Remote Sensing Agency (NRSA) and Space Application Centre (SAC) helped it to secure remote sensing and GIS projects effortlessly, thereby ensuring a steady revenue stream for ORSAC during the early days of its inception. Upon assuming the role of Chief Executive Officer (CEO), Amiya Kumar Mohapatra, an Indian Forest Service officer, realized that he was unable to bring desired changes within the organization. Low motivation amongst the employees prevented the organization from growing and winning large-scale projects. ORSAC faced stiff competition from private players and other government agencies in the ever-advancing remote sensing and GIS market in India. The CEO realized that dependence on the government for patronage and funding had had a detrimental impact on ORSAC. The organization was unable to recognize the need for developing competencies in marketing its products and services to users until it was too late, and it had already lost large-scale projects in the manufacturing industry to private players. However, an increase in the salary expenses and the salary shortfall in comparison with Department of Science and Technology funding was forcing ORSAC to sustain its operational expenses by securing more projects from the open market. The organization was facing diverse challenges ranging from high operating costs, especially salary expenses, to low productivity of employees, which were affecting ORSAC’s competitiveness negatively. Additionally, the organization faced a near-permanent recruitment ban by the state government preventing it from sourcing key competencies from the market to keep pace with the changing technologies and customer demands. Thus, this case study aims to present diverse challenges of a state-owned enterprise by highlighting internal factors such as structural, financial and human resource challenges, as well as external factors such as technological change and competition in the industry, which influences organizational competitiveness and makes organizational turnaround a difficult task.

Supervised/ Unsupervised Classification of LULC Using Remotely Sensed data for Coimbatore city, India

Landuse / Landcover system espoused by almost all Organisations and scientists, engineers and remote sensing community who are involved in mapping of earth surface features, is a system which is derived from the united States Geological Survey (USGS) LULC classification system. The application of RS and GIS involves determining of homogeneous zones, trend analysis of land use integration of new area changes or change detection etc., National Remote Sensing Agency(NRSA) Govt. of India has devised a generalized LULC classification system respect to the Indian conditions based on the various categories of Earth surface features , resolution of available satellite data, capabilities of sensors and present and future applications.

Dynamics of the Ganga in West Bengal, India (1764–2007): Implications for science–policy interaction

Understanding of the fluvial dynamics of the Ganga, especially in its lower reach, is incomplete to present. Questions such as why the river changes its course so frequently, or what are the impacts of major structural intervention at Farakka, have not been addressed properly. Open scientific research is impeded by the governmental attitude to conceal water-related data. The present paper deals with the changing courses of the Ganga in West Bengal since the second half of the 18th century. The source materials of this research are maps published by different agencies since the colonial period and a recent satellite image provided by the National Remote Sensing Agency of India. The Ganga enters the Maldah district of West Bengal after touching the outlier of Rajmahal Hills, and swings across the deltaic plain. In the reach between Rajmahal and Farakka, the Ganga has been flowing through a series of distributaries alternately and those channels have now been abandoned. The sequential maps help to understand how the Ganga has changed its course during the known historical period. Since the construction of Farakka barrage, the Ganga has migrated eastward appreciably and has formed a mighty bend. Trapped sediment load above the Farakka barrage has largely induced the recent change. The continuous oscillation of the Ganga in Maldah district, and also along the Indo-Bangladesh border has posed many problems, including land reallocation, population displacement, and border disputes. There should be a paradigm shift in the governmental attitude to look into the matter, not as a purely engineering problem but also as a social issue.

Evaluation of suitable tiger habitat in Chandoli National Park, India, using spatial modelling of environmental variables

Application of remote sensing and Geographic Information System (GIS) as a tool has assumed an immense significance in habitat suitability modelling for various wildlife species and now a days these are widely used in conservation biology and wildlife management. This paper evaluates habitat suitability for tigers ( Panthera tigris tigris) in Chandoli National Park, India. This research provides information about potential areas that can be declared as Tiger Reserve, a federal designation of protection. Habitat evaluation was completed in the Chandoli National Park (17° 04′ 00″ N to 17° 19′ 54″ N and 73° 40′ 43″ E to 73° 53′ 09″ E) using habitat suitability index (HSI). Remotely sensed data of satellite IRS-P6, LISS-III of 25th February 2005 was procured from National Remote Sensing Agency, India. The satellite imagery data was digitally processed and collateral data were generated from topographic maps in a GIS framework. Various layers of different variables such as landuse land cover, forest density, measures of proximity to disturbances and water resources and a digital terrain model were created based on ground truthing. These layers, GPS location of animal's presence and “binomial multiple logistic regression (BMLR)” techniques were integrated in a GIS environment for the HSI modelling. Results indicate that approximately 160.48 km 2 (55%) of the forest of Chandoli National Park is highly suitable for herbivores population, and 176.52 km 2 (50%) of the Park is suitable for tigers. Therefore, this study concludes that forest areas within the Chandoli National Park are appropriate for consideration as Tiger Reserve. Furthermore, the identification and mapping of wildlife corridors and other forest patches lying in between neighboring protected area like Koyana sanctuary, suggests that these region of Sahyadri range of Western Ghats should be included into the proposed Tiger Reserve. This will be a benefit for tigers, as tigers require larger and least disturbed forest habitats for establishing and maintaining their high-density population. Fortunately, in May 2008 the Government of India declared Chandoli NP as tiger reserve. Thus declaration of Chandoli National Park as a Tiger Reserve reflects that the habitat suitability model developed by us for tiger was not only statistically sound but also has potential to be considered while taking any decision regarding wildlife habitat management.

Developments in Earth Observation data reception, dissemination and archival at National Remote Sensing Agency

With the rapid advancement in remote sensing technology and corresponding applications, the Earth Observation Ground Segment has undergone a significant change at NRSA. From dedicated data acquisition and processing systems, we have realized multi-mission data acquisition quick look and browse systems and also multi-mission integrated information management systems. Front end of data reception station has been upgraded to handle wider bandwidth and data rates up to 320 Mbps for near future missions such as the Radar Imaging Satellite (RISAT). Antenna, feed, down converters and RF chain have been upgraded. To cater to multi-mission scenario mission independent, fully configurable demodulator/bit synchs have been deployed. For handling data acquisition in multi-satellite scenario where in data from 5 to 6 remote sensing satellites are to be received almost simultaneously, automation of operations has been incorporated towards station configuration to avoid manual errors. From media-based data handling, there has been a shift towards net centric data handling among the various work centers such as user order processing, data processing systems, special processing systems, data quality evaluation, and product quality control work centers. The turn around time for dissemination of user desired data products has been improved from two weeks to one day. Presently a state of the art integrated environment has been envisaged which will bring down the turn around time for the supply of data products significantly. Automation has been incorporated at both data acquisition and data processing to improve the product throughput. Presently NRSA is catering to a demand of about 30,000 data products per annum and in the next two years it is aimed to reach a level of 50,000 products per annum by realizing the integrated multi-mission ground system for earth observation (IMGEOS). This will significantly modify the entire data production and dissemination chain so that data can be made available to user within 1 h from data acquisition at Shadnagar in some cases. Some of these novel developments planned in the near future will be discussed in this paper.

Computerized database of salt affected soils for Peninsular India using GIS

A computerized database of salt affected soils was prepared for five states – Andhra Pradesh, Karnataka, Tamil Nadu, Kerala and Orissa – based on the analogue maps of the National Remote Sensing Agency (NRSA), Hyderabad, India. The salt affected soil maps at 1:250,000 scale were georeferenced and digitized to prepare the digital polygons of salt affected soils using ILWIS software. The Survey of India State map at 1:1,000,000 scale was georeferenced and features for administrative and political boundaries (state/district), infrastructure (road/railway), irrigation and drainage (river/canal) and settlements (state/district capitals) were digitized to prepare the thematic layers for the basemap. These were overlaid onto the salt affected soil layer to prepare the state map of salt affected soils. A composite (master) database comprising salt affected soils in five states was prepared using GIS. The soil characteristics such as nature and degree of salinity/sodicity and its ground coverage were entered in an attribute table and linked with the digitized polygons to prepare a relational database. Four agroclimatic regions (ACRs) and 42 agroclimatic zones (ACZs) were identified by the Planning Commission of India for regional planning and development of natural resources in Peninsular India. The boundaries of the ACRs and ACZs were delineated from the primary (master) database using ILWIS GIS. Superimposing digitized boundaries of ACRs and ACZs over the master database, the salt affected soils were delineated to show the distribution of salt affected soils at regional and zonal scales. The state-, region- and zone-wise extent of salt affected soils was calculated. The soils were essentially saline in Orissa and Kerala state, distributed in the coastal, deltaic plains and mud flats/mangrove swamps. In Andhra Pradesh, soils were saline (53%) and sodic (47%), distributed in the peninsular (64%), coastal (24%) plains and mud flats/mangrove swamps (12%). The salt affected soils in Karnataka were primarily sodic (99%), located in the alluvial plain. In Tamil Nadu, soils were dominantly sodic (96%), distributed in the peninsular (95%) plain. Soils with variable salinity were also found in the coastal (74%) and deltaic (16%) plains and mudflats/mangrove swamps (10%) of Orissa and in the coastal plain (3%) of Tamil Nadu. A significant area under salt affected soils (69%) was found in ACR XI (East Coast Plains and Hills Region), distributed in Tamil Nadu (34%), Andhra Pradesh (19%) and Orissa (15%); followed by 26% in ACR X (Southern Plateau and Hills Region), located in Karnataka (16%), Andhra Pradesh ((9%) and Tamil Nadu (2%) and 5% in ACR XII (West Coast Plain and Ghat Region), comprising Kerala (2%) and Tamil Nadu (3%) States. The zonal distribution showed that the extent of salt affected soils was higher in the semiarid regions (rainfall <1000 mm) of Karnataka (84%), Tamil Nadu (93%) and Andhra Pradesh (64%). State maps of salt affected soils in digital format were overlaid with agroecosubregions, landforms, geology and rainfall data to show the relation between the extent of salt affected soils and the characteristics of agroregions, climatic parameters and the nature of parent materials. Thus the digitization of salt affected soil maps in GIS format provides a georeferenced, easy-to-access and retrieve, relational database comprising thematic and attribute information of salt affected soils at state, regional and zonal levels and facilitates overlay and map calculation of related data for planning and decision making in the reclamation and management of salt affected soils in Peninsular India and other similar regions.

Computerized database on salt affected soils in western and central India using GIS

Salt affected soils occupy significant areas in western and central India manifested by the arid and semiarid climate, sandy/clayey soil texture, absence of natural drainage, and inadequate infrastructure and irrigation development. These soils are productive following reclamation and appropriate management. The National Remote Sensing Agency, Hyderabad (India) published state-wise maps of salt affected soils in India on 1:250,000 scale using a legend that includes physiography, soil characteristics, and the aerial extent of the mapping units. In the analogue form, voluminous data contained in such maps were difficult to handle by users of varied backgrounds. An attempt was made to prepare a computerized database of salt affected soils for easy access, retrieval, and manipulation of spatial and attribute data useful for management of salt affected soils. The salt affected soils maps were prepared, for Rajasthan, Gujarat, Madhya Pradesh, and Maharashtra states, overlaying digitized layers of SAS polygons and the Survey of India basemap using the ILWIS (Integrated Land and Water Information System) software. GIS was used to prepare a composite (master) database of western and central India that showed the extent and distribution of salt affected soils. A relational database was prepared combining the digitized polygons with soil characteristics such as nature and degree of salinity (presence of higher concentration of neutral salts and neutral soil reaction), sodicity (presence of higher concentration of basic salts and alkaline reaction) and ground coverage. The regional and zonal databases of salt affected soils were prepared at a suitable scale overlaying agro-climatic regions agro-climatic zones. Spatial relation of salt affected soils with physiography, climate, geology, and agro-eco-sub-regions were evaluated employing map calculations in GIS. Saline soils were prevalent in Gujarat, and Rajasthan while sodic soils were dominant in Maharashtra and Madhya Pradesh. These were distributed primarily in the arid (B) plain of Rajasthan, alluvial (A) and coastal (D) plains of Gujarat, and peninsular plain (F) of Maharashtra and Madhya Pradesh. It occupied 2,596,942 ha (78%) in the western (Rajasthan and Gujarat) and 733,608 ha (22%) in the central (Madhya Pradesh and Maharashtra) regions. The SAS occupied 3.3 million ha in the western and central region constituting 50% of the total salt affected soils in India. The saline and sodic soils occupied 2,069,285 ha (62%) and 1,261,266 ha (38%), respectively.

Advanced studies in strip pair processing of Cartosat‐1 data

AbstractWith the launch of the Indian remote sensing satellite Cartosat‐1, an along‐track stereoscopic imaging mission of the Indian Space Research Organisation (ISRO), new possibilities for operational availability of high‐resolution stereo‐imagery from space for the remote sensing and cartography user communities have emerged. The high‐resolution stereo data beamed from twin cameras on board the Cartosat‐1 mission facilitates topographic mapping up to 1:25 000 scale. The primary advantage of the Cartosat‐1 mission is seen in the generation of digital elevation models (DEMs) and the production of ortho‐images in an operational set‐up. This also facilitates 3D terrain visualisation for very large tracts of land. Stereo Strip Triangulation (SST) is a software system developed and perfected at the Space Applications Centre of ISRO for operational generation of secondary control and appropriate DEMs for subsequent use in the generation of ortho‐images. This system has been in use for almost 2 years at the National Remote Sensing Agency in Hyderabad, India, and has generated a wealth of data for use in topographic mapping. An initiative to generate a database of seamless, homogeneous DEMs and associated ortho‐image tiles at country level has been undertaken by ISRO. This data‐set has been named CartoDEM. The Cartosat‐1 data processing team has completed the design and testing of software for the generation of the CartoDEM. This software system has undergone detailed evaluation and currently is in the final stage of development of the operational procedures required to make maximum use of the capabilities of the Cartosat‐1 sensors. A data dissemination software system is currently under development. As part of the large‐scale evaluation exercises to finalise the specifications of CartoDEM, it is established that with the 2·5 m ground resolution, a base‐to‐height ratio of 0·62 and with capability to register conjugate points in the stereopair to sub‐pixel level, DEMs can be generated at 0·3 arc second intervals, with a height accuracy of 3 to 4 m, over tracts of undulating land mass up to 15 000 km2 with the use of 10 to 20 ground control points. The Cartosat‐1 data processing and evaluation team regularly monitors the radiometric quality of images. As part of the radiometric characterisation of sensors, the team computed point spread functions (PSFs) for the two cameras of Cartosat‐1. Special filters based on the PSFs then work to improve the radiometric quality of the images. Initial results from these exercises show good promise in image restoration based on PSFs for Cartosat‐1. This paper presents a summary of activities and exercises related to (i) Stereo Strip Triangulation, (ii) CartoDEM, (iii) image quality improvement using the PSF‐based image restoration and (iv) block adjustment exercises using a COTS software package. Also reported are the results of post‐launch experiments, study and evaluation of DEMs vis‐à‐vis ortho‐images from Cartosat‐1.

Modified patchwork-based watermarking scheme for satellite imagery

As a major global satellite data provider, National Remote Sensing Agency, Department of Space, Government of India, needs to protect copyright associated with the data. In this paper, we propose a modified patchwork-based watermarking (MPW) scheme in the spatial domain. The proposed MPW algorithm is capable of embedding a watermark with minimal manipulation of the original image pixel values. The watermark contains information about the provider and the intended recipient of the data. The MPW watermark embedding process does not create any visual artifacts and is imperceptible. The watermark retrieval process operates with the help of a key and does not require the original image. Our results demonstrate that the presented scheme successfully incorporates copyright requirements for satellite imagery.

Evapotranspiration using MODIS data and limited ground observations over selected agroecosystems in India

Plant growth processes and productivity of agroecosystems depend highly on evapotranspiration from the land (soil‐crop cover complex) surface. A study was carried out using MODIS TERRA optical and thermal band data and ground observations to estimate evaporative fraction and daily actual evapotranspiration (AET) over agroecosystems in India. Five study regions, each covering a 10 km×10 km area falling in agricultural land use, were selected for ground observations at a time closest to TERRA overpasses. The data on radiation and crop parameters in paddy (irrigated and rainfed), cotton (rainfed), groundnut (residual moisture) crops were recorded at 14‐day intervals between August 2003 to January 2004 from 2 km×2 km homogeneous crop patches within each study region. Eight MODIS scenes in seven optical (1, 2, 3, 4, 5, 6, 7) and two thermal bands (31, 32) level 1B data acquired from the National Remote Sensing Agency, Hyderabad, India and resampled at 1 km, were used to generate surface albedo (α), land surface temperature (T s, MODIS) and emissivity (εs). Evaporative fraction and daily AET were generated using a single source energy balance approach with (i) ground based observations only (‘stand alone’ approach), and (ii) ‘fusion’ of MODIS derived land surface variables on cloud free dates and coincident ground observations. Land cover classes were assigned using a hierarchical decision rule applied to multi‐date Normalized Difference Vegetation Index (NDVI). The exponential model could be fitted between 1‐EFins, ground (ground based evaporative fraction) and difference between T s, MODIS and air temperature (T a) with R 2 = 0.77. Linear fit (R 2 = 0.74) could be obtained between 1‐EFins, ground and temperature vegetation dryness index (TVDI), derived from T s, MODIS‐NDVI triangle. Energy balance daily AET from the ‘fusion’ approach was found to deviate from water balance AET by between 4.3% to 24.5% across five study sites with a mean deviation of 11.6%. The root mean square error (RMSE) from the energy balance AET was found to be 8% of the mean water balance AET. The satellite based energy balance approach can be used to generate spatial AET, but needs more refinements before operational use in the light of progress in algorithms and their validation with huge datasets.

Malaria Control: Current Concepts.

Malaria Control: Current Concepts.

Multi Mission Data Simulator for Checking Ground Segment Elements of Indian Remote Sensing (IRS) Satellite Ground Stations

This paper describes the design and development of Multi Mission Data Simulator at National Remote Sensing Agency (NRSA), which is used for checking various Ground Segment Elements like Down Converter, Demodulator, Bit Synchroniser, High Density Digital Tape Recorder (HDTR) and Front End Hardware of Indian Remote Sensing Satellite (IRS) Ground Stations, during prelaunch and normal phase of satellite acquisition operations and Data Products (Imageries) generation.

Inflight calibration of IRS-1C imaging geometry for data products

The Indian remote sensing satellite IRS-1C was launched in December 1995. Since June 1996 various data products have been operationally available from National Remote Sensing Agency in India. They are available through various international ground stations of EOSAT in other parts of the world. Knowledge of camera geometry as well as inter-camera alignment is critical to the operational generation of data products with high geometric quality. The imaging geometry is derived from measurements carried out on the spacecraft during the qualification stage. However, it was felt that there is a need to re-establish the IRS-1C imaging geometry from image data itself. This was successfully carried out during the initial phase of IRS-1C operations. Significant improvement in geometric quality of data products is achieved as a result of the procedures reported in this paper.

Observed high temperatures in the sunglint area over the North Indian Ocean

Abstract Sea surface temperatures (SSTs) have been derived operationally at the National Remote Sensing Agency using NOAA AVHRR data since early 1991. The channel 4 temperature variations in the sunglint area and its surroundings are presented. The SSTs derived using satellite data with those of ship observations are compared in the sunglint area. The errors in sea surface temperature estimations using satellite data in an area of sunglint are described.

Indian tracking and data acquisition facilities for low Earth and geosynchronous satellites

To support its satellite program, the Indian Space Research Organization (ISRO) has an extensive infrastructure of ground support facilities throughout the country and abroad. The major elements include the ISRO Telemetry Tracking and Command Network (ISTRAC), the National Remote Sensing Agency (NRSA), and the Indian National Satellite (INSAT) control facilities. These facilities and their important role in supporting the Indian Space Program are described. The locations of the principal ISRO space control facilities within India are shown.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

Indian National Remote Sensing Agency

The functions and capabilities of the Indian National Remote Sensing Agency are summarized. The principal goals of the Indian National Remote Sensing Agency are: the development and implementation of the indigenous remote sensing satellite program; continuous buildup and improvement of the facilities for generation of products from various sensor data; and development and utilization of new applications techniques for resource monitoring to facilitate technology transfer to the many user agencies.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

Study of drought indices in relation to rice crop Production over some States of India

Drought monitoring indices used by India Meteorological Department (IMD) and National Remote Sensing Agency (NRSA) have been discussed in relation to crop estimates during kharif seasons of 1989 and 1990 for some States over India. It was found that index used IMD showed moderate to severe drought over certain areas during certain periods, while NRSA reported non-drought conditions. On the other hand, the preliminary estimated rice crop by the respective States during 1989 suggested higher values in four States and lower in one State, with reference to the mean values based, on the previous eight years data. A high degree of correlation between NRSA and IMD drought indices was found, which agree partially with the yield estimates during 1989.&#x0D;

Correlation of turbidity with Indian Remote Sensing Satellite-1A data

Abstract Indian Remote Sensing Satellite-1A Linear Imaging Self Scanning System (IRS-1A-LISS-I) multispectral digital data acquired over the Tawa reservoir region have been analysed to evaluate the turbidity in the surface water. Tawa reservoir water samples were collected on 20 October 1988 concurrent with an IRS-1A overpass. The turbidity was measured at each sampling point in the field with a nephelometer. Reservoir water samples were analysed for total suspended matter, grain size and mineralogy. IRS-1A-LISS-I computer-compatible tapes were obtained from the National Remote Sensing Agency (NRSA), India. The relationship between the LISS-I digital data of 20 October 1988 and the measured values of turbidity was established. The results indicate that, in the turbidity range between 15–45 NTU (nephelometric turbidity units), a positive relationship exists between the turbidity and the visible wavelength band 1, 2 and 3 (0.45 to 0.68 μm) mean pixel values. Shorter wavelengths, especially in band 3 (0.62–0...