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.     

Single frequency processing of Ørsted GPS radio occultation measurements

The Global Positioning System (GPS) radio occultation measurements obtained using the TurboRogue GPS receiver on the Danish satellite Ørsted have been processed using the single frequency method. Atmospheric profiles of refractivity and temperature are derived and validated against numerical weather prediction data from the European Centre for Medium-Range Weather Forecast (ECMWF). Results from the Ørsted GPS measurement campaign in February 2000 indicate that the single frequency method can provide retrievals with accuracy comparable to that of using two frequencies. From comparisons between measured dry temperature profiles and corresponding dry temperature profiles derived from ECMWF analysis fields, we find a mean difference of less than 0.5 K and a standard deviation of 2–4 K between 500 and 30 hPa in height. Above 30 hPa the impact of the ionosphere becomes more dominant and more difficult to eliminate using the single frequency method, and the results show degraded accuracy when compared to previous analysis results of occultation data from other missions using the dual frequency method. At latitudes less than 40° (denoted low latitudes), the standard deviation is generally smaller than at latitudes higher than 40° (denoted high latitudes). A small temperature bias is observed centered at 200 hPa for low latitudes and at 300 hPa for high latitudes. This indicates that the ECMWF analyses do not adequately resolve the tropopause temperature minimum. In the lowest part of the troposphere an observed warm bias is thought to be due to erroneous tracking of the GPS signal in cases of atmospheric multipath propagation.     

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).     

Innovations in Automation for Vision Metrology Systems

The advantages of vision metrology (VM) systems over their film-based counterparts, in terms of the degree of automation within the measurement process, were initially confined to the image mensuration stage. Of late, however, the potential of significantly raising the level of automation of offline and real time VM systems has been more fully exploited, to the point where full automation of the offline procedure has been realized. Innovative features such as automatic image point identification via coded targets, exterior orientation through automatically recognizable "control" groupings of target points, determination of image point correspondences within unlabelled point clouds, and real time tracking of multipoint, handheld measurement probes are now incorporated in industrial VM systems. Another significant innovation is the development of "smart" cameras with incorporated image processing and measurement capabilities which remove the necessity for transmitting image data to the host computer. This paper reviews recent innovations in automation and discusses their operational impact on practical VM applications. The concepts discussed are illustrated through reference to a modern VM system which supports offline and real time measurement.     

Response of GPS occultation signals to atmospheric gravity waves and retrieval of gravity wave parameters

We show that the amplitude of the Global Positioning System (GPS) signals in the radio occultation (RO) experiments is an indicator of the activity of the gravity waves (GW) in the atmosphere. The amplitude of the GPS RO signals is more sensitive to the atmospheric wave structures than is the phase. Early investigations used only the phase of the GPS occultation signals for statistical investigation of the GW activity in the height interval 10–40 km on a global scale. In this study, we use the polarization equations and Hilbert transform to find the 1-D GW radio image in the atmosphere by analyzing the amplitude of the RO signal. The radio image, also called the GW portrait, consists of the phase and amplitude of the GW as functions of height. We demonstrate the potential of this method using the amplitude data from GPS/Meteorology (GPS/MET) and satellite mission Challenge Mini-satellite Payload (CHAMP) RO events. The GW activity is nonuniformly distributed with the main contribution associated with the tropopause and the secondary maximums related to the GW breaking regions. Using our method we find the vertical profiles of the horizontal wind perturbations and its vertical gradient associated with the GW influence. The estimated values of the horizontal wind perturbations are in fairly good agreement with radiosonde data. The horizontal wind perturbations v(h) are ±1 to ±5 m s with vertical gradients dv/dh ±0.5 to ±15 m s km at height 10–40 km. The height dependence of the GW vertical wavelength was inferred through the differentiation of the GW phase. Analysis of this dependence using the dispersion relationship for the GW gives the estimation of the projection of the horizontal background wind velocity on the direction of the GW propagation. For the event considered, the magnitude of this projection changes between 1.5 and 10 m s at heights of 10–40 km. We conclude that the amplitude of the GPS occultation signals contain important information about the wave processes in the atmosphere on a global scale.     

An update on the IEM surface backscattering model

The integral equation approach to modeling scattering from rough surfaces was introduced in 1992. At that time, it was noted that there was a need to find a transition reflection coefficient that could change its argument from the incident angle to the specular angle as frequency or roughness scale got large. One such reflection coefficient was published in 2001. In this letter, we would like to include this reflection coefficient in the integral equation model to interpret several multifrequency backscattering measurements from surfaces with surface parameters defined by the investigators who acquired the data.     

An automated seamless mosaicing system of multi-charge coupled devices of panchromatic data

Panchromatic data of pixel resolution 5.8 m obtained from IRS-1C and IRS-1D satellites proved to be very useful for mapping purposes. One of the popular data product is the 70 km swath mosaic which is covered by a combination of 3 CCD line sensors, each with 4096 pixels. Each CCD-line sensor with different imaging times causes geometric problems of mosaicing three strips data together. In this paper, we propose the details of the design elements of system that caters to the need for accurate and automatic multi strip image registration without any second resampling of the data. The systematic geometric correction grid mapping is improved to facilitate accurate mosaicing by automatic image registration task that makes use of the overlap data within image strips and image registration is achieved up to sub-pixel level.     

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.