Generation and validation of DEM using SAR interferometry and differential GPS supported by multispectral optical data

Digital elevation model (DEM) and the derived terrain parameters e.g. contour, slope, aspect, drainage pattern, etc are required for natural resources management, infrastructure planning and disaster management. The present paper aims at generating DEM from ERS tandem pair using interferometric technique supported by differential GPS measurements (DGPS) and multispectral optical data. Validation of DEM has been carried out by DGPS measurements. Ground Control Points (GCP) established by DGPS measurements have been used to georeference the IRS-1D optical data that has finally been co-registered with SAR amplitude image. Optical data, co-registered with ERS - I SAR data has helped in locating the GCP’s and check points, precisely, for refinement of DEM and its validation.     

Distribution analysis of salt affected soils under canal and non-canal command area in a part of Etah district,U. P., using remote sensing technique

A World Bank-aided project on sodic land reclamation in Uttar Pradesh is being executed by U.P. Bhumi Sudhar Nigam, Lucknow, and Remote Sensing Applications Centre, U.P., Lucknow has the responsibility of sodic land mapping for the execution of land reclamation programme at the cadastral level. Sodic lands are mainly concentrated in the Gangetic alluvial plains but the problem of sodicity is particularly acute in the canal-irrigated areas. A study of the distribution pattern of sodic lands in canal and noncanal command areas in a reclamation site (covering 60 villages out of which sodic lands were mapped in 51 villages) of Etah district in Uttar Pradesh, indicates that 18.39 per cent area of the canal command villages was barren sodic which was 13.41 per cent of the total geographical area of the site (15417 ha), however, 11.69 per cent area was recorded to be barren sodic in the non-canal command villages which was only 3.16 per cent of the geographical area of the site. The results of soil chemical analysis indicate that barren sodic lands of canal command area are saline-sodic with higher concentration of soluble salts (pH₂ >8.5, EC₂ >4 dSm⁻¹), however, those of non-canal command area are sodic (pH₂ >8.5, EC₂ <4 dSm⁻¹). The post-monsoon ground level in the canal-irrigated areas was in the critical and semicritical zone (< 3.0 mbgl) whereas it was well below the semi-critical zone in the non-canal command area, which indicates that the high ground water level is a major factor to higher the area under sodicity.     

Approaches for comparative evaluation of raster GIS-based landslide susceptibility zonation maps

Evaluation of maps generated from different conceptual models or data processing approaches at spatial level has importance in many geoenvironmental applications. This paper addresses the spatial comparison of different landslide susceptibility zonation (LSZ) raster maps of the same area derived from various procedures.     

Using spectral information from the NIR water absorption features for the retrieval of canopy water content

Canopy water content (CWC) is important for mapping and monitoring the condition of the terrestrial ecosystem. Spectral information related to the water absorption features at 970 nm and 1200 nm offers possibilities for deriving information on CWC. In this study, we compare the use of derivative spectra, spectral indices and continuum removal techniques for these regions. Hyperspectral reflectance data representing a range of canopies were simulated using the combined PROSPECT + SAILH model. Best results in estimating CWC were obtained by using spectral derivatives at the slopes of the 970 nm and 1200 nm water absorption features. Real data from two different test sites were analysed. Spectral information at both test sites was obtained with an ASD FieldSpec spectrometer, whereas at the second site HyMap airborne imaging spectrometer data were also acquired. Best results were obtained for the derivative spectra. In order to avoid the potential influence of atmospheric water vapour absorption bands the derivative of the reflectance on the right slope of the canopy water absorption feature at 970 nm can best be used for estimating CWC.     

Evaluation of the geometric stability and the accuracy potential of digital cameras — Comparing mechanical stabilisation versus parameterisation

Recent tests on the geometric stability of several digital cameras that were not designed for photogrammetric applications have shown that the accomplished accuracies in object space are either limited or that the accuracy potential is not exploited to the fullest extent. A total of 72 calibrations were calculated with four different software products for eleven digital camera models with different hardware setups, some with mechanical fixation of one or more parts. The calibration procedure was chosen in accord to a German guideline for evaluation of optical 3D measuring systems [VDI/VDE, VDI/VDE 2634 Part 1, 2002. Optical 3D Measuring Systems–Imaging Systems with Point-by-point Probing. Beuth Verlag, Berlin]. All images were taken with ringflashes which was considered a standard method for close-range photogrammetry. In cases where the flash was mounted to the lens, the force exerted on the lens tube and the camera mount greatly reduced the accomplished accuracy. Mounting the ringflash to the camera instead resulted in a large improvement of accuracy in object space. For standard calibration best accuracies in object space were accomplished with a Canon EOS 5D and a 35 mm Canon lens where the focusing tube was fixed with epoxy (47  μm maximum absolute length measurement error in object space). The fixation of the Canon lens was fairly easy and inexpensive resulting in a sevenfold increase in accuracy compared with the same lens type without modification. A similar accuracy was accomplished with a Nikon D3 when mounting the ringflash to the camera instead of the lens (52  μm maximum absolute length measurement error in object space). Parameterisation of geometric instabilities by introduction of an image variant interior orientation in the calibration process improved results for most cameras. In this case, a modified Alpa 12 WA yielded the best results (29  μm maximum absolute length measurement error in object space). Extending the parameter model with FiBun software to model not only an image variant interior orientation, but also deformations in the sensor domain of the cameras, showed significant improvements only for a small group of cameras. The Nikon D3 camera yielded the best overall accuracy (25  μm maximum absolute length measurement error in object space) with this calibration procedure indicating at the same time the presence of image invariant error in the sensor domain. Overall, calibration results showed that digital cameras can be applied for an accurate photogrammetric survey and that only a little effort was sufficient to greatly improve the accuracy potential of digital cameras.     

ARCHITECTURE AND COMPONENTS OF PHOTOGRAMMETRIC WORKSTATIONS

Several generations of photogrammetric workstations have followed one another since the analytical plotter was developed at the beginning of the 1960s. The outcome of this evolution, resulting from important developments in mini- and microcomputers, is illustrated today by more and more powerful photogrammetric workstations based on distributed processing architecture. This paper introduces present day architectures, as well as hardware and software aspects of the various components of these systems including graphics workstation, real time processor, superimposition system, correlation system and special input/output devices. Finally, an attempt is made to outline the prospects for further evolution.     

Significance of the remotely sensed thermal infrared measurements obtained over a citrus orchard

In this work we have developed a theoretical model that helps the interpretation of the remotely sensed thermal infrared measurements carried out over citrus orchards. A detailed analysis of the different factors which take part in the definition of the effective emissivity and temperature (observation height, viewing angle, type of soil, dimensions and separation between orange trees) is made. The model was validated under vertical observation in a citrus orchard during seven nights. In this situation we have determined that the model performs to an accuracy of about 1%.     

A comparative study of supervised classifiers on a subscene in Junagadh district,Gujarat

This paper describes the results of a comparative study of five classifiers viz., maximum likelihood, modified maximum likelihood, minimum distance to mean. Fisher and min-max, for classifying a subscene of Junagadh district using Landsat Thematic Mapper (TM) data. The kappa coefficient of agreement (k) and per cent correctly classified pixels for training data are used as measures of overall performance. It is observed that maximum likelihood and modified maximum likelihood classifiers perform better than the other three classifiers for this data set. Band combinations (3, 4, S) and (2, 3, 4, S) perform better than the usual combination (1,2,3,4), possibly because of presence of middle infrared band (band 5) on a scene dominated by vegetation cover. The band combination (1, 2, 3, 4, 5, 7) performed the best.     

Triangulated spherical splines for geopotential reconstruction

We present an alternate mathematical technique than contemporary spherical harmonics to approximate the geopotential based on triangulated spherical spline functions, which are smooth piecewise spherical harmonic polynomials over spherical triangulations. The new method is capable of multi-spatial resolution modeling and could thus enhance spatial resolutions for regional gravity field inversion using data from space gravimetry missions such as CHAMP, GRACE or GOCE. First, we propose to use the minimal energy spherical spline interpolation to find a good approximation of the geopotential at the orbital altitude of the satellite. Then we explain how to solve Laplace’s equation on the Earth’s exterior to compute a spherical spline to approximate the geopotential at the Earth’s surface. We propose a domain decomposition technique, which can compute an approximation of the minimal energy spherical spline interpolation on the orbital altitude and a multiple star technique to compute the spherical spline approximation by the collocation method. We prove that the spherical spline constructed by means of the domain decomposition technique converges to the minimal energy spline interpolation. We also prove that the modeled spline geopotential is continuous from the satellite altitude down to the Earth’s surface. We have implemented the two computational algorithms and applied them in a numerical experiment using simulated CHAMP geopotential observations computed at satellite altitude (450 km) assuming EGM96 (n _max = 90) is the truth model. We then validate our approach by comparing the computed geopotential values using the resulting spherical spline model down to the Earth’s surface, with the truth EGM96 values over several study regions. Our numerical evidence demonstrates that the algorithms produce a viable alternative of regional gravity field solution potentially exploiting the full accuracy of data from space gravimetry missions. The major advantage of our method is that it allows us to compute the geopotential over the regions of interest as well as enhancing the spatial resolution commensurable with the characteristics of satellite coverage, which could not be done using a global spherical harmonic representation. The results in this paper are based on the research supported by the National Science Foundation under the grant no. 0327577.     

A comparison of three image-object methods for the multiscale analysis of landscape structure

Within the conceptual framework of Complex Systems, we discuss the importance and challenges in extracting and linking multiscale objects from high-resolution remote sensing imagery to improve the monitoring, modeling and management of complex landscapes. In particular, we emphasize that remote sensing data are a particular case of the modifiable areal unit problem (MAUP) and describe how image-objects provide a way to reduce this problem. We then hypothesize that multiscale analysis should be guided by the intrinsic scale of the dominant landscape objects composing a scene and describe three different multiscale image-processing techniques with the potential to achieve this. Each of these techniques, i.e., Fractal Net Evolution Approach (FNEA), Linear Scale-Space and Blob-Feature Detection (SS), and Multiscale Object-Specific Analysis (MOSA), facilitates the multiscale pattern analysis, exploration and hierarchical linking of image-objects based on methods that derive spatially explicit multiscale contextual information from a single resolution of remote sensing imagery. We then outline the weaknesses and strengths of each technique and provide strategies for their improvement.