Resourcesat (IRS-P6) value added data products

Remote sensing data products need to meet stringent geodetic and geometric accuracy specifications irrespective of intended user applications. Georeferencing is the basic processing step towards achieving this goal. Having known the imaging geometry and mechanism, the mathematical models built with the use of orbit and attitude information of the spacecraft can correct the remote sensing data for its geometric degradations only up to system level accuracy (IRS-P6 DP Team, 2000). The uncertainties in the orbit and attitude information will not allow the geometric correction model to generate products of accuracy that can meet user requirements unless Ground Control Points (GCP) are used as reference geo-location landmarks. IRS-P6 data processing team has been entrusted with developing a software system to generate data products that will have desired geodetic and geometric accuracies with known limitations. The intended software system is called the Value Added Data Products System (VADS). Precision corrected, Template Registered, Merged and Ortho Rectified products are the value added products planned with VADS.     

Simulating the effect of Nitrogen application on Wheat Yield by linking remotely sensed measurements with wtgrows simulation model

A field experiment was conducted on wheat at New Delhi with five treatments of Nitrogen (N) fertilizer application (0, 30, 60, 90 and 120 kgha^-1). Relationship has been established between observed leaf area index (LAI) and remotely sensed vegetation indices. These relationships are inverted and used for predicting LAI from vegetation indices on different days after sowing. The “re-initialization” strategy is implemented in model WTGROWS in which initial conditions of model are changed so that the model simulated LAI match remote sensing predicted LAI. The model performance with re-initialization has been evaluated by comparing the simulated grain yield and total above-ground dry matter (TDM) values with the actual observations. The results show that in-season re-initialization is effective in model course correction by improving the simulated results of yield and TDM for different N treatments even though the model was run with no N stress condition. Model re-initialization at different days shows that the closer is the day of re-initialization to crop anthesis the more effective is model course correction. Also, the treatment showing maximum error in yield simulation without re-initialization shows maximum reduction in error by re-initialization. The approach shows that the remote sensing inputs can substitute for some of the inputs or errors in inputs required by crop models for yield prediction.     

Derivation of indices using remote sensing data to evaluate cropping systems

This paper presents the work done in Bathinda District of Punjab state of India for evaluating the cropping system efficiency using multi-date, multi-year and multi-sensor satellite based remote sensing data along with various spatial and non-spatial collateral data. Three efficiency indices, such as Multiple Cropping Index (MCI), Area Diversity Index (DI), Cultivated Land Utilization Index (CLUI), have been worked out to characterize the cropping systems. The salient findings point out that, the MCI has, increased remarkably. A further increase is possible by only taking a third crop. The ADI has increased in kharif (rainy) season, due to introduction of rice in the cotton belt, however in rabi (winter) season the ADI has reduced nearly to one, showing it to be a mono-cropped situation. The CLUI is low (> 0.5) in many blocks, showing there is a great scope to improve it. Since in summer the land is remaining unutilized, a summer crop can very well be taken up to improve it.     

Comparison of ERS-SAR and spot data for sugar beet crop cover assessment

The present work was aimed to compare the abilities of radar and optical satellite data to estimate crop canopy cover, which is a key component of productivity estimates. Three ERS-1 SAR images were obtained of East Anglia (UK) in 1995 and one ERS-2 SAR image in 1996. The images covered a study area around the IACR Brooms Barn Sugar Beet Research Institute. Field data comprising radiometric and biophysical measurements of the crop canopy were collected in two fields from June 22 to August 3, 1995 to coincide with ERS-1 SAR overpass dates. In 1996, field data were collected in two fields from June 11 to July 29 on a weekly basis. A previously calibrated version of the water cloud model was inverted to estimate Leaf Area Index (LAI) from ERS-1 and ERS-2 SAR backscatter and soil moisture samples. Canopy cover was estimated from the radar-estimated LAI using a standard exponential relationship that has a well-established coefficient for sugar beet. Radio-metrically and atmospherically corrected data from three SPOT images in 1995 and one SPOT image in 1996 were used to calculate the Optimised Soil Adjusted Vegetation Index (OSAVI), from which crop canopy cover was estimated using a relationship determined previously by canopy modelling. The crop cover values estimated by satellite were in good agreement with those measured on ground with the Parkinson radiometer. Radar data may be able to provide useful estimates of canopy cover for crop production modelling, especially in the case of loss of optical data due to cloud.     

Check dam positioning by prioritization of micro-watersheds using SYI model and morphometric analysis — Remote sensing and GIS perspective

Sediment Yield Index (SYI) model and results of morphometric analysis have been used to prioritize watersheds and to locate sites for checkdam positioning in Tarafeni watershed in Midnapur district. West Bengal. Various thematic maps such as land use/land cover, slope, drainage, soil etc. were prepared from 1RS ID LISS III digital data, SOI toposheets of 1:50,000 scale and other reference maps. Morphometric parameters such as bifurcation ratio (R_b). drainage density (D_d), texture ratio (T), length of overland flow (L_o), stream frequency (F_u), compactness coefficient (C_c), circularity ratio (R_c), elongation ratio (E_r), shape factor (B_s) and form factor (R_f) were computed. Automated demarcation of prioritization of micro-watersheds was done by using GIS overlaying technique by assigning weight factors to all the identified features in each thematic map and ranks were assigned to the morphometric parameters. Five categories of priority viz., very high, high, medium, low and very low, were given to all the watersheds in both the methods. Sixty-two micro-watersheds using SYI method and twenty-three micro-watersheds using morphometric have been prioritized as very high priority. Final priority map was prepared by considering the commonly occurred very high-prioritized micro-watersheds in both SYI model and morphometric analysis. Twenty-four suitable sites were identified for check dam construction in 21 highly prioritized watersheds. It is proved that integrated study of SYI model and morphometric analysis yield good result in prioritization of watersheds.     

GPS新近发展及其军事应用

本文简述了GPS的最新发展动态，着重分析了GPS在精确制导武器上的应用形式和效果，指出了GPS制导技术存在的局限性及其未来发展趋势。     

测绘情报工作发展战略思考

本文通过对“十五”期间测绘情报工作的回顾，分析了目前测绘情报研究存在的主要问题，讨论了今后测绘情报工作的发展对策。     

Non-tidal variations in the deflection of the vertical at Beijing Observatory

At Beijing Observatory both astrometric and gravimetric observations are available to study the non-tidal variations in the deflections of the vertical (or non-tidal plumbline variations, PLVs). From repeated gravimetric observations performed in a network around the observatory, the PLVs at Beijing Observatory during the period 1987.0–1996.0 have been calculated. After comparison with the observational residuals (which also contain the PLV components) of the photoelectric astrolabe located at the observatory, the accuracy of the obtained PLV results has been examined. It is shown that, due to the asymmetry of the gravimetric network, the qualities of the two different PLV components are not equal. The longitude component of the PLV at Beijing has been determined successfully, to be of the order of 0.05, with a contribution of about 0.02 in the inter-annual time scale. The result for the latitude PLV component is not good enough to draw a conclusion. Although both techniques are able to measure the PLV, the result of the determination depends very much on the availability of observational data.     

Multi-reference evaluation of uncertainty in earth orientation parameter measurements

Uncertainties in polar motion and length-of-day measurements are evaluated empirically using several data series from the space-geodetic techniques of the global positioning system (GPS), satellite laser ranging (SLR), and very long baseline interferometry (VLBI) during 1997–2002. In the evaluation procedure employed here, known as the three-corner hat (TCH) technique, the signal common to each series is eliminated by forming pair-wise differences between the series, thus requiring no assumed values for the “truth” signal. From the variances of the differenced series, the uncertainty of each series can be recovered when reasonable assumptions are made about the correlations between the series. In order to form the pair-wise differences, the series data must be given at the same epoch. All measurement data sets studied here were sampled at noon (UTC); except for the VLBI series, whose data are interpolated to noon and whose UT1 values are also numerically differentiated to obtain LOD. The numerical error introduced to the VLBI values by the interpolation and differentiation is shown to be comparable in magnitude to the values determined by the TCH method for the uncertainties of the VLBI series. The TCH estimates for the VLBI series are corrupted by such numerical errors mostly as a result of the relatively large data intervals. Of the remaining data sets studied here, it is found that the IGS Final combined series has the smallest polar motion and length-of-day uncertainties.