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.     

Assessing Similarity of Geographic Processes and Events

The increased availability of spatiotemporal data collected from satellite imagery and other remote sensors provides opportunities for enhanced analysis of geographic phenomena. Much of the new data includes regular snapshots of the environment. Comparison of these snapshots can provide information about changes to the phenomena of interest. However, conventional GIS data models and analytical tools lack capabilities to adequately handle massive multidimensional data. One of the fundamental tools necessary to meet such challenges is query support to retrieve and summarize data according to dynamic geographic phenomena, such as geographic events and processes, of interest. Such query support depends upon abilities to assess spatiotemporal similarity so that data representing geographic events that exhibit the spatiotemporal characteristics of interest can be identified in a GIS database. To this end, this paper introduces a method to assess similarity of geographic events and processes (such as storms) based on their spatiotemporal characteristics (such as distribution of precipitation). We developed six indices to capture static and dynamic characteristics of geographic events and applied the Dynamic Time Warping method to temporal sequences of the six indices to examine the similarity among these events. With a case study, we demonstrated the proposed indices and method capable of comparing spatiotemporal characteristics of events as recorded in a GIS database and categorizing spatiotemporal data into groups of events according to their behavior in space and time.     

Estimation of asymmetry and kurtosis coefficients in the process of geodetic network adjustment by the least-squares method

 This paper presents an extension of the geodetic network adjustment model. The proposed extension makes possible the estimation of the 3-rd and 4-th central moments for the vector of measurement errors in the process of network adjustment by the least-squares method with application of orthogonal matrices. It allows to estimate the asymmetry and kurtosis of the measurement errors distribution. Received 13 April 1993; Accepted 8 July 1996     

Multiplotting With Images from the Kodak DCS420 Digital Camera

This paper explores the potential of a digital camera to produce multiple images suitable for plotting. The objective was to build a three dimensional database by linking triangulated images from a Kodak DCS420 digital camera with a computer aided measurement system. The system then supplied X, Y, Z data from x, y image co-ordinates captured off two or more images. Relative accuracy in object space was around 1;50 000.     

PHOTOGRAMMETRIC DATA CAPTURE: AN INEXPENSIVE ALTERNATIVE

A case is made for the development of an inexpensive and portable data capturing unit which could be used with existing mirror stereoscopes and which could provide an accuracy sufficient for most digital map databases. The results of simulation experiments to test the accuracy of the system are presented.     

The stochastic estimation of satellite clock correction information in WADGPS

1 IntroductionChnventional DGPS is limited by the range overwhich the differential corrections are valid due tothe rapid decorrelation of the error sources with in-creasing distance from the reference station to user.In wide area differential GPS (WWPS) errorsources in GPS measurements are medeled sepa-rately,on the basis of a limited number of referencestaitOns, to overcome this drawback. The main er-ror sources are regarded as broadcast ephemeris er-ror,atmospheric refraction and satel…     

MoisturEC: A New R Program for Moisture Content Estimation from Electrical Conductivity Data

Noninvasive geophysical estimation of soil moisture has potential to improve understanding of flow in the unsaturated zone for problems involving agricultural management, aquifer recharge, and optimization of landfill design and operations. In principle, several geophysical techniques (e.g., electrical resistivity, electromagnetic induction, and nuclear magnetic resonance) offer insight into soil moisture, but data‐analysis tools are needed to “translate” geophysical results into estimates of soil moisture, consistent with (1) the uncertainty of this translation and (2) direct measurements of moisture. Although geostatistical frameworks exist for this purpose, straightforward and user‐friendly tools are required to fully capitalize on the potential of geophysical information for soil‐moisture estimation. Here, we present MoisturEC, a simple R program with a graphical user interface to convert measurements or images of electrical conductivity (EC) to soil moisture. Input includes EC values, point moisture estimates, and definition of either Archie parameters (based on experimental or literature values) or empirical data of moisture vs. EC. The program produces two‐ and three‐dimensional images of moisture based on available EC and direct measurements of moisture, interpolating between measurement locations using a Tikhonov regularization approach.