THE NEW DECADE: DIGITS AND DIVERSITY

The President of the Photogrammetric Society, Mr. I Newton, chaired a panel discussion concerned with those developments in photogrammetry which may take place during the 1990s.     

Selection of spectral band combination for land cover/land use classification using a brightness value overlapping index (BVOI)

A simply defined, accurate and efficient criterion of selecting a spectral-band combination for improved land use/land cover classification using remote sensing data is discussed. Results indicate that Brightness Value Overlapping Index (BVOI) is very effective in measuring the degree of overlap in brightness values among land cover types and in selecting suitable spectral-band combination for landuse classification. The results of BVOI are also compared with the results of another band-combination selecting index - Optimum Index Factor (OIF).     

Wet tropospheric effects on precise relative GPS height determination

Summary Considerable interest has been generated recently in the use of the Global Positioning System (GPS) for precise height determination. A major error source in these measurements is the propagation delay due to atmospheric water vapour. In order to achieve the high precisions required for such applications as absolute sea-level monitoring improvement of wet delay modelling is necessary. Results from a GPS campaign show a significant correlation (0.91) between the variability of the wet delay measured using a water vapour radiometer (WVR) at the Onsala site and the absolute value of the residual error in the height determination of a 134 km baseline from Onsala to Jönköping. This correlation indicates that the atmosphericvariability as inferred from the WVR data includes information on the quality of the GPS height estimate. During periods of high atmospheric activity, e.g., during the passage of a weather front, the use of a six-parameter gradient model reduces the spread for the vertical coordinate from 40 mm to 20 mm (with standard deviations of 17 mm and 9 mm respectively) over the 134 km baseline (less than 1 × 10^–7) using 8 hour data spans on 11 different days over a six month period.     

Quantification of suspended solids in Dal lake,Srinagar using remote sensing technology

Indian Remote Sensing satellite (IRS)-1B, Linear Imaging Self Scanner (LISS)-II spectral digital data was analysed to determine the feasibility of quantifying the concentration of suspended solids in the surface water of inland water body, Dal lake, in Srinagar, India. The water samples collected in concurrent with IRS-1B overpass, were analysed to determine the concentration of suspended solids. The results indicate that a positive functional relationship exist between the concentration of suspended solids and the visible wave length bands 1 and 3 and near infrared band 4. It has been observed that as the concentration of suspended solids increase, the spectral response also increases. It is concluded that IRS LISS-H data can be effectively used to quantify suspended sediment concentration in the Dal lake surface water.     

Neuralizing target superresolution algorithms

Tatem et al. (2001) have designed a Hopfield network-based algorithm for superresolving discrete targets that are larger than the sample spacing of an image. The algorithm iteratively minimizes a criterion function that contains a sigmoidal activation term. We have altered their algorithm to bring it in line with Hopfield's original network by reducing the pseudotemperature of the sigmoid. We found that smaller values of the pseudotemperature lead to faster convergence to a solution and resulting solutions that are more accurate.     

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 of horticultural plantations in Kumarsain tehsil in Shimla district, Himachal Pradesh

The favourable agroclimatic conditions for orchards especially apples have increased the acreages in Himachal Pradesh (HP) which has significantly contributed in the growth of state economy. Realizing the importance of horticulture in HP and its changing scenario of the land use/land cover, a study was conducted to identify and map apple and almond plantations in the Kumarsain tehsil of Shimla district using Remote Sensing (RS) techniques. IRS-IB LISS-II False Colour Composite (FCC) diapositives of October 27, March 30 and April 20, 1992 were visually analysed for mapping apple and almond plantations. The results indicate that IRS LISS-II data of April 20 on 1∶50,000 scale was found very useful for identification and mapping of apple and almond plantations in this region. Accuracy of interpretation was also tested on sample basis assuming a binomial distribution for the probability of success/failure of sample points. The overall interpretation accuracy assessed based on 40 sample points was found to be 87 per cent at 90 per cent confidence limits.     

Crop acreage estimation using ERS-1 SAR data

Synthetic Aperture Radar (SAR) data from the European Remote Sensing Satellite (ERS-1) acquired in July, October and November, 1992 covering the kharif season of the region were used separately and in combination to identify the major crops and for estimation of their acreage before harvest Separability indices were calculated for major cover types and it was found that single-date SAR data cannot be used for accurate identification of various crops. Multi-temporal colour composite facilitated better identification of crop types. Comparison of area estimates made with ERS-1 SAR and IRS-1B LISS II data showed that the commonly used digital data analysis techniques (per pixel classifiers) are not adequate for accurate estimation of crop acreage using SAR data.     

Forest cover mapping of East district,Sikkim using IRS-1A LISS II satellite data

Remote sensing techniques have been applied to classify tour density classes within each of the forest type along with other major landuse/landcover classes in the East district, Sikkim using IRS-1A LISS II satellite data pertaining to the period of November, 1988. The shadow problem in rugged terrain and difficulty in acquiring cloud free data for different seasons pose problems to achieve considerable mapping accuracy. In the present study, the forests of the district were delineated through supervised classification techniques using maximum likelihood algorithm into five forest types as sal forests, subtropical broad-leaved forests, Himalayan wet temperate forests, Rhododendron forests and alpine forests. The alpine forests were further stratified into two categories as moist alpine scrub and dry alpine scrub. The statistical data obtained from the present study shows that 55.47 percent of the total geographical area of the East district was under forest cover. An overall accuracy of more than 85 percent in correctly delineating forest classes was achieved.     

Corridor analysis in Rajaji-Corbett elephant reserve — A Remote sensing and GIS approach

This paper deals with corridor analysis in Rajaji-Corbett Elephant Reserve in the Shivaliks of Uttaranchal state. Efforts were made to detect changes in the state of forest covervis- à -vis the status of corridors during the three periods i.e. 1967. 1986 and 1998 using remote sensing and GIS. TheERDAS Imagine digital image processing andArcView GIS software packages were used for this purpose. Temporal satellite imagery and ground observations in the Rajaji-Corbett Elephant Reserve revealed forest loss, degradation and disturbances in the corridor areas, hindering elephant movement and restricting them to forests islands. Motichur-Chilla corridor, despite being a highly favoured habitat for the elephants was found to be highly threatened followed by Kotdwar and Ramnagar corridors. Construction of wide bridges across Kunao-Chilla Canal, recreation of corridors through reforestation, reduction of all kinds of pressures in the corridor areas and providing higher protection to corridors are recommended.