Zoning and monitoring dominant mangrove communities of a part of The Marine National Park, Gulf of Kachchh

Mangroves of the Marine National Park constitute the second largest patch of mangroves in Gujarat, extending up to 11,000 ha, comprising six species of mangroves. Earlier studies carried out using remote sensing data pertained to baseline data generation and mapping and monitoring the mangroves (density-wise) of the Park from 1975 to 1993. Using IRS IC/ID LISS III data (1998–2001) supported by ground data, the distribution of different mangrove communities in the Park has been attempted. Amongst various image-processing techniques, band ratioing followed by supervised classification gave the best result (classification accuracy was 92%).Avicennia community is the most dominant community accounting for more than 70% of the area. TheRhizophora community occupies the inward margins of the creeks and theCeriops community is present in the interior regions. The ecotone between the marsh and mangrove communities has been identified as the transitional mangroves (Avicennia alba, Sueada), representing the transition from the less saline mangrove to the highly saline marsh community. The zoning of the mangroves has also helped in assessing the diversity of the region. Based on the richness of species, three areas, namely Bhains Bid, North-east Dide Ka Bet and South-east Chhad Island have been identified as highly diverse (most suitable area for preservation).     

Comparative evaluation of Indian remote sensing satellite and landsat thematic mapper data for geological and geomorphological applications

In order to evaluate the potentials of IRS‐1A Linear Imaging Self‐scanning Sensor (LISS‐I) data for geological and geomorphological applications and also to compare the IRS‐1A LISS‐I data with Landsat Thematic Mapper (TM) data, a study has been attempted for parts of Uttar Pradesh and Madhya Pradesh in Northern India. The first four spectral bands of Landsat TM sensor data which are similar and close to IRS‐1A LISS‐I senor have been utilised for the comparative evaluation. Various techniques employed for both the data set to derive the required geology and geomorphology related information include (i) band combination (ii) spectral response analysis (iii) principal component analysis (iv) supervised classification techniques and (v) visual observation of various outputs generated by the above methods. The Optimum Index Factor (OIF) method adopted for selecting suitable band combinations showed similar OIF rankings for IRS‐1A LISS‐I data and Landsat TM data. It has been visually observed that the band combination 1, 3 & 4 offers relatively better feature display. The spectral responses derived for various major geologic rock units such as Deccan Trap, Vindhyan Formation, Bundelkhand Granite and for a few landcovers such as surface water bodies and black soil show striking similarity in pattern for both LISS‐I and TM. The Principal Component (PC) analysis of both data sets suggested that the total scene brightness tends to dominate in the first PC. The percentage information contributed by PCs 1&2 as also by PCs 1,2 & 3 in both the LISS‐I and TM are comparable. It was observed from the classified image generated by performing supervised classification with a maximum likelihood algorithm that major geomorphic landforms were clearly distinguishable. Thus the qualitative and quantitative evaluation of both IRS‐1A LISS‐I and Landsat TM data showed that significant similarities exist between them. The study also revealed that IRS‐1A LISS‐I data can be effectively used for deriving geology and geomorphology related details.     

Mapping and characterization of inland wetlands using remote sensing and GIS

Sustainable management of wetland ecosystem is necessary as it serves the important functions such as food storage, water quality maintenance and providing habitat for different species of wildlife. Hence, an inventory of wetlands in any given area is a pre-requisite for their conservation and management. A study has been carried out to delineate the wetlands of east Champaran district of Bihar, India, using IRS ID LISS III data. The data for the pre and post monsoon seasons have been analysed and the wetlands have been qualitatively characterized based on the turbidity and aquatic vegetation status. The extent of water logging problem in the study area was inferred from the seasonal variation of waterspread during both the seasons. The three categories of wetlands (ponds/lakes, water logged areas and oxbow lakes) have been identified. From the analysis, it has been observed that the inland wetlands constitute 2.7% of the study area, of which 1.8% is subjected to water logging. Thus, this study highlights the usefulness of remotely sensed data for wetland mapping, seasonal monitoring and characterization.     

Comparison of MODIS vegetation continuous field — based forest density maps with IRS-LISS III derived maps

The study compared forest cover maps derived using coarse resolution vegetation continuous fields (MODIS VCF; 500m resolution) with the maps derived from medium resolution (24m; IRS LISS-III) data. The comparison of VCF, per cent tree cover product, for the years 2000 to 2004 with LISS III forest density class maps of 2001 and 2003 was carried out for two sites representing hilly (Uttarakhand) and undulating terrains (Madhya Pradesh). Slicing VCF to corresponding forest crown cover, i.e., 0–10%, 10–40%, 40–70% and >70% produced considerable difference in forest area estimates when compared to original LISS III derived crown cover area. The corresponding value range in VCF for 0–10% of actual forest cover were 0–31% and 0–25% in 2 sites respectively, and the respective limit was consistent at 1–20% when VCF range were sliced with respect to upscaled LISS III at 500m resolution. Similarly, all other class limits were also found through iterative process. These limits were similar, within a site, across five years. Spatial Kappa match between these two data indicated higher match in 40–70% class, and also in undulating site. When compared at same resolution, similar forest area cover estimated with weighted area upscaling gave closest match. The study is useful in knowing the usability and limits of VCF product, and utility of spatial Kappa.     

Evaluation of Cartographic accuracy of IRS-1A LISS II data for upgrading linear details on the existing maps (A case study of Chandigarh area)

Considering the fest pace of development, up-to-date maps have become imperative in developmental planning. Conventional map updating techniques are expensive and time consuming. The present paper makes an attempt to tackle the problem using GIS techniques. Maps generated from IRS-1A LISS II data and Survey of India (SOI) toposheets were used as input maps in GIS. These maps were overlaid to obtain the positional errors at road junction points. The area statistics of each sector were calculated taking the SOI map as reference data. The results show that the areas calculated from LISS II data and SOI map are well comparable and the deviations are within 10%, whereas the positional accuracy (MSE) of points is within 30 m. The study demonstrates that the IRS-1A LISS II data can be used for updating of maps on scale 1:100,000 and smaller in areas where linear features are identifiable in the IRS LISS II image.     

Effect of seasonal spectral variations on land cover classification

The supervised classification (Maximum likelihood) on three dates of IRS (LISS III) satellite data was performed to study the effect of seasonal spectral variation on land cover classification for the study area falling in the Solan district of Himachal Pradesh at latitude 30° 50’ N to 31° ’N and longitude 77° 00’ E to 77° 15’ E. It was found that the summer dataset was better with overall classification accuracy of 76% as compared to winter and spring dataset with classification accuracy of 49 and 46%, respectively.     

Monitoring of forest fires in Bhadra wildlife sanctuary

The Western Ghats constitute one of the three biodiversity hot spots in India, which is under constant threat from various quarters. Among the several anthropogenic causes, fire is one of the important anthropogenic factor, which plays a pivotal role in vegetation succession and ecosystem processes. It is very important to understand the ecological changes due to fire and other anthropogenic factors for conservation and management of biodiversity. Because of its synoptic, multi-spectral and multi-temporal nature remote sensing data can be a good source for forest fire monitoring. In the present study, an effort has been made to monitor the burnt areas using March 2000 and 2004 IRS LISS — III data. The study revealed that an area of 2.15 km² and 4.46 km² was affected by fire in 2000 and 2004 respectively. Repeated drought, followed by mass flowering and dying of bamboo accelerated the spread of fire from ground to canopy in areas with high bamboo density.     

Remote sensing and GIS in identification of soil constraints for sustainable development in Bhilwara district,Rajasthan

Soil is an integral part of ecosystem nurturing the biological system. Sustainable management of soil resources based on the consideration of constraints is the key to check land degradation and maintain productivity of biological system. To meet the objective remote sensing and GIS technology has been employed for identification of soil constraints in resource potential Bhilwara district. IRS LISS-III FCC images were interpreted for soil constraints using physiography soil approach, verified through field checking and laboratory analysis. On IRS LISS-III FCC images the salt affected soils of Kotri and Taswaria appeared in bright white to light grey tone, smooth texture with white mottles. These were also verified during ground truth and soil analysis for salinity (EC 2.90–3.32 dS m⁻¹) and sodicity (pH 9.50–9.86 and ESP 17.60–19.05). Similarly on the LISS III FCC, constraints due to water erosion near Bir, Sareri and Vijaypura soil series were apparent in light grey to whitish tone, intercepted by medium grey streaks indicating streams and exposed sub-soil. The constraints due to shallow depth associated with rock out crops and hilly areas of Balda and Delwara series appeared in greenish grey tone and coarse texture. There was close relationship between image characteristics, field observation and analytical data.     

Loktak notified Wetland ecosystem and its catchment

Conservation of wetland is considered paramount in view of its ecological significance. The availability of reliable and up-to-date data on seasonal water spread, tropic state of wetland and bio-physical parameters besides the landuse/cover of the catchment area is a prerequisite for ‘wise use’ of any wetland ecosystem. The present study is carried out to identify the above parameters of Loktak notified wetland through visual interpretation of 1RS IA/IB LISS II FCC of 1990 and 1994/95. It indicates that the water spread of the lake is showing a declining trend and an increasing trend for aquatic vegetation. In 1990 post-monsoon data water spread was 15441 ha which become 11166 ha in October 1994. The extent of water spread further decreases by pre-monsoon season and was found to be 7875 ha in the IRS LISS II data of March 1995. Like-wise area under aquatic vegetation and associated marshy/ swamps was 10499 ha in October 1990 and 13506 ha in October 1994. Catchment of Loktak lake (104872 ha) is highly degraded and forest covers only 7205 ha area. Agriculture is the main land use (35576 ha) in the catchment and substantial area is also under land with or without scrub. Thus, there is a need to rehabilitate the catchment by way of planting trees for reducing silt load in the Loktak lake and ensuring its ‘wise use’.     

Habitat analysis for sambar in corbett national park using remote sensing and gis

Habitat analysis for sambar in terms of food, cover, water, space and extent of edge in Corbett National Park using remote sensing and GIS has been attempted. Other physical parameters include climate, topography, fire history, disturbance regimes, weeds etc. IRS-IB LISS II data (FCC, hardcopy) on 1:50.000 scale was interpreted to generate vegetation cover and density map. Other maps showing drainage, water bodies, roads, human habitations and contours were prepared using Survey of India topographical maps. During evaluation of sambar habitat information regarding habitat parameters and their tolerance was collected from existing literature as well as during field observations. Twenty-two transects of one km. length were laid down in all the strata randomly to collect information regarding the structure and composition of the forest and also habitat use (direct and indirect evidences) by sambar. This was then integrated using condition-based equations in the GIS domain to generate suitability maps. Actual sightings on the ground to a large extent supported the results.     

Assessment of sedimentation in harakud reservoir using digital remote sensing technique

As per recommendations of Working Group for National Action for Reservoir Sedimentation Assessment, National Institute of Hydrology has taken up study on sedimentation for 25 reservoirs in India during X plan period using remote sensing technique. One such study for Hirakud reservoir in Mahanadi basin in Orissa for year 1999–2001 is described here. Reservoir’s original utilizable and gross volumes were 5818 and 8136 M m³, respectively. Minimum draw down level (MDDL) and full reservoir level (FRL) for reservoir are 179.83 and 192.02 m, respectively. Linear Imaging Self Scanning (LISS)- III data of Indian Remote Sensing Satellites (IRS) 1C and 1D, covering elevation range between 180.68 and 191.89 m, were used. Rule based classification was applied to ‘water index’ and radiances of near infrared band to determine water spread area. Revised live storage capacity was 4842 M m³. The silt index for the live storage area was 2.623 ha m (100 km² year)^-1 (0.376 % of live storage or 21.9 M m³ year^-1). Total live storage lost in sedimentation was 984 M m³ (16.90 % of live storage).     

Land degradation mapping in the upper catchment of river Tons

A study on land degradation in the upper catchment of river Tons, a tributary of Yamuna river, in Uttarkashi district of the Uttarakhand state, was carried out using on-screen visual interpretation of IRS LISS-III + PAN merged data. The study area, which is largely mountainous, includes Govind Wildlife Sanctuary and National Park. Vegetation cover, slope and erosion status were used as criteria for the delineation of four major land degradation categories viz., undegraded, moderately degraded, degraded and severely degraded. More than 50 per cent of the study area is reported to be covered with snow and grassland. The moderate to severely degraded area worked out to be 42.4 per cent of the total area. The 32.8 per cent of area was found to be moderately degraded, followed by degraded (6.63%) and severely degraded (2.88%) areas. The depletion of vegetation cover on mountainous terrain and subsequent cultivation without proper protection measures is the reason for severe soil erosion and land degradation. In view of the existing land degradation situation, the catchment requires immediate treatment on priority for the sustenance of agriculture and wild life. It is expected that these measures will reduce the silt load in the river Tons and eventually, in river Yamuna.     

Identification of Loriya Fault,Its Reactivation Due to 2001 Bhuj Earthquake, (Using Remote Sensing Data) and Its Bearing on the Kachchh Mainland Fault,Kachchh District,Gujarat

The 2001 Bhuj earthquake (M_w 7.7), one of the most severe earthquakes in the recent history of India, reactivated various existing active faults. It is manifested in the form of coseismic ground fissures/cracks and upheaval of land in the form of bumps. Identification and reactivation of Loriya Fault is established by 1—Geomorphic changes with the help of digital imagery (LISS III images). 2—Coseismic changes through ground checks and 3—Geophysical signatures through magnetic and gravity survey. A lineament cutting the north-western part of the Pur River alluvial fan has been revealed by satellite imagery. The streams flowing along the lineament add to the evidences of a weak plane, while the occurrence of coseismic ground fissures confirms the existence of an active fault. No dip slip movement is recorded in the trenches made across the Loriya active fault while the en-echelon pattern of ground fissures suggest strike slip movement along the fault due to 2001 earthquake.     

Validations of suspended sediment concentration (ssc) derived using ocean colour monitor (ocm) data off Chennai coast, India

Indian Remote Sensing Satellite (IRS) — P4 Ocean Colour Monitor (OCM) data were used to estimate Suspended Sediment Concentration (SSC) in the coastal waters off Chennai and to study the distribution along the coast. Surface water samples were collected during May and October 2000 synchronized with satellite overpass, and quantitative estimates of Suspended Sediment Concentration (SSC) were done. OCM — Data Analysis System (DAS) software developed by the Space Applications Centre, Ahmedabad was used for OCM data processing and analysis. The field data and OCM derived SSC showed a correlation of r = 0.85 and r = 0.95 for the months of May and October respectively.     

Analysis of temporal sar and optical data for rice mapping

This study investigates the potential of multi-temporal signature analysis of satellite imagery to map rice area in South 24 Paraganas district of West Bengal. Two optical data (IRS ID LISS III) and three RADARSAT SAR data of different dates were acquired during 2001. Multi-temporal SAR backscatter signatures of different landcovers were incorporated into knowledge based decision rules and kharif landcover map was generated. Based on the spectral variation in signature, the optical data acquired during rabi (January) and summer (March) season were classified using supervised maximum likelihood classifier. A co-incidence matrix was generated using logical approach for a combined “rabi-summer” and “kharif-rabi-summer” landcover mapping. The major landcovers obtained in South 24 Paraganas using remote sensing data are rice, water, aquaculture ponds, homestead, mangrove, and urban area. The classification accuracy of rice area was 98.2% using SAR data. However, while generating combined “kharif-rabi-summer” landcovers, the classification accuracy of rice area was improved from 81.6% (optical data) to 96.6% (combined SAR-Optical). The primary aim of the study is to achieve better accuracy in classifying rice area using the synergy between the two kinds of remotely sensed data.     

Remote sensing and gis applications in the identification of aquaculture hotspots at village level

Interpretation of IRS LISS II and LISS III imagery has revealed the various landforms as well as land use/land cover features in a part of the Godavari delta coastal belt. A comparative analysis of geomorphological vs. land use/land cover maps suggested that the landforms exert a certain degree of control over human land use activities even in this monotonously plain area. Further, an analysis of the sequential imagery pertaining to 1992 and 2001 aimed at detecting the land use/land cover change has indicated that the aquaculture has phenomenally increased by 9,293.5 ha during the 9-year period. At the same time, the cropland which occupied about 29,104 ha in 1992 has been reduced to 19,153.9 ha by 2001 mainly due to the encroachment of aquaculture. Village level data on temporal variation in land use/land cover extracted through GIS analysis revealed that in 14 out of the total 39 villages in the area, the conversion of cropland into aquaculture ponds was more than 30% with the highest conversion rate of 89.8% in Gondi village. These fourteen villages, which are designated as ‘aquaculture hotspots’ are grouped into 4 priority classes based on the intensity of conversion.     

Evaluation of the spatial changes in seagrass cover in the lagoons of Lakshadweep islands,India, using IRS LISS III satellite images

A study was conducted in Lakshadweep islands to determine the feasibility of using Indian Remote Sensing (IRS) satellites for detecting changes in the seagrass from other coastal features. IRS ID and IRS P6 LISS III having spatial resolution of 23.5 m with lower cost compared to all other contemporary satellites with the same spatial resolution have not been widely used for monitoring the changes in seagrass cover. In this context, the present study attempted to explore the effectiveness of LISS III data for mapping seagrasses and to inform the international community about the usefulness of these low-cost imageries for coastal resource monitoring. Supervised classification and change detection studies found a significant decrease in seagrass cover of 73.03 ha in the Lakshadweep group of islands. An overall accuracy of 67.5% was obtained for the change maps, and seagrass cover and its changes vary at different islands.     

Evaluation of spectral bands and spatial resolution of LISS II and LISS III sensors on-board IRS satellites for crop identification

The present study evaluates the performance of Indian Remote Sensing (JRS) LISS Jl and LISS III data having spatial resolutions of 36 m and 23.5 m respectively in the Classification accuracy of rice, mustard and potato crops grown in West Bengal, India. The role of Middle infra-red (MIR.) band, of IRS 1C LISS III was also investigated in this context. The results indicated that in case of crop like rice which was grown over large contiguous fields, no significant change in classification accuracy was observed between LISS II and LISS III data. However, the accuracy increased by 5–7 per cent with the inclusion of MIR band mainly due to better separability between lowland rice and other hill vegetation. In case of crops like mustard and potato which were grown on small size or less contiguous fields, the classification accuracy increased by 5–8 per cent due to higher spatial resolution of LISS III. Inclusion of MIR band did not improve the accuracy of these crops.     

Land Cover/Land use Mapping Using Different Wavelet Packet Transforms for LISS IV Madurai Imagery

Texture in high resolution satellite images requires substantial improvement in the conventional segmentation algorithms. The use of wavelet packet transforms for texture analysis and image classification of high spatial resolution LISS IV imagery provide more details about the urban areas. This paper analyses the performance of a combination of Wavelet Packet Statistical Features (WPSFs) and Wavelet Packet Co-occurrence Features (WPCFs) for the classification of LISS IV images. The classification accuracy per pixel is improved in this paper by varying the window size. Four indices—user’s accuracy, producer’s accuracy, overall accuracy and kappa co-efficient are used to assess the accuracy of the classified data. Experimental results show that a multi-band and multi-level wavelet packet approach can be used to drastically increase the classification accuracy.     

Landscape characterization of Sariska National Park (India) and its surroundings

Landscape characterization gives an overall information on the status of Land Use and Land Cover(LULC),changes in its composition and the impact of natural and human influences operating at different spatial and temporal scales.This information can be used to monitor changes in natural forest resources and protected areas,delineate potential conservation areas and can serve in effective management of ecologically fragile landscapes.In the present study,geo-spatial tools were used to characterize the landscape of Sariska National Park and its surroundings.Satellite data was used to prepare LULC maps for 1989 and 2000,change detection analysis and computation of landscape metrics.Climatic data,field records and modeling tools were used to map the po-tential spread of two invasive species,Prosopis juliflora and Adhatoda vasica.The results show that the forest area increased from 1989 to 2000,indicating better management practices.Landscape metrics(PAFRAC,PLADJ and AI)also support this argument.Improvements in the degraded forest can further enhance this effect.The entire reserve however is suitable for the invasion of P.juliflora and A.vasica but is more pronounced in Boswellia serrata and Anogeissus pendula-Acacia catechu(open)forests.A detailed landscape characterization map can help forest managers to make important policy decisions concerning issues such as in-vasive species.