Characterization and quantification of data voids in the shuttle Radar topography mission data

The goal of this study was to characterize and quantify the occurrence of data voids in data from the Shuttle Radar Topography Mission (SRTM) for the conterminous United States. For this purpose, SRTM data and corresponding data from the national elevation data were downloaded in 21 samples spatially organized to cover the main topography of the U.S. Void locations in SRTM data were compared to terrain attributes and subsequently the area of individual data voids to the same attributes. It was found that data voids amounted to 0.3% of the total dataset. Data voids were found in all topographic settings but more often in slopes steeper than approximately 20/spl deg/ that face south (170/spl deg/), and also in flat areas such as lakes and rivers. It was also found that more than 50% of all data voids were composed of connected pixels in groups less than six pixels. The largest data voids could be attributed to water bodies, while the rest could be explained by terrain-radar interaction characteristics.     

The negative alpha filter: a new Processing technique for polarimetric SAR interferometry

In this letter we develop a new concept, the negative alpha filter, which we suggest has application for quantitative estimation of surface parameters beneath vegetation using polarimetric synthetic aperture radar (SAR) interferometry (POLInSAR). We first derive the filter and then validate it using simulations of L-band coherent forest scattering. We then show initial results of applying the filter to airborne data from the German Aerospace Center's E-SAR L-band sensor.     

Digital topography models for Martian surfaces

We propose to use an unsupervised automated classification of topographic features on Mars in order to speed up geomorphic and geologic mapping of the planet. We construct a digital topography model (DTM), a multilayer grid that stores various kinds of topographical information for every pixel in a site. The method uses a probabilistic clustering algorithm to assign topographically meaningful labels to all pixels in the DTM. The results are displayed as a thematic map of topography. Resultant topographical features are characterized and compared using statistics of their constituent pixels. We demonstrate the usage of our method by classifying and characterizing the topography of a landscape in the Tisia Valles region on Mars. We discuss extensions and further applications of our method.     

Retrieving cloud fraction in the field-of-view of a high-spectral resolution infrared radiometer

The combination of radiance from both clear and cloudy regions of sky within the instrument's field of view (FOV) adds significant uncertainty to retrievals of atmospheric state profiles and cloud microphysical properties from infrared spectroradiometers. In this letter, we use observations of radiance from both the 8-13 and 3-5 /spl mu/m bands to retrieve estimates of the cloud fraction in the instrument's FOV, as well as microphysical cloud properties, from high-spectral-resolution infrared radiometers. Cloud fraction derived from imagers as well as high-time-resolution observations show good agreement and high correlation with our derived cloud fraction values. This is shown for both ground-based and aircraft-based observations. We also demonstrate that the use of the additional information in the 3-5 /spl mu/m band extends the dynamic range and accuracy of microphysical properties that can be retrieved from infrared radiance data.     

A GIS numerical framework to study the process basis of scaling statistics in river networks

A new geographic information system (GIS) numerical framework (NF), called CUENCAS, for flows in river networks is presented. The networks are extracted from digital elevation models (DEMs). The program automatically partitions a basin into hillslopes and channel links that are required to correspond to these features in an actual terrain. To investigate the appropriate DEM resolution for this correspondence, we take a high-resolution DEM at 10-m pixel size, and create DEMs at eight different resolutions in increments of 10 m by averaging. The extracted networks from 10-30 m remain about the same, even though there is a tenfold reduction in the number of pixels. By contrast, the extracted networks show increasing distortions of the original network from 40-90 m DEMs. We show the presence of statistical self-similarity (scaling) in the probability distributions of drainage areas in a Horton-Strahler framework using CUENCAS. The NF for flows takes advantage of the hillslope-link decomposition of an actual terrain and specifies mass and momentum balance equations and physical parameterizations at this scale. These equations are numerically solved. An application of NF is given to test different physical assumptions that produce statistical self-similarity in spatial peak flow statistics in a Horton-Strahler framework.     

Habitat evaluation for sarus crane in the Keoladeo National Park using IRS LISS III and pan merged data and GIS

The Keoladeo National Park, Bharatpur, a man-made fresh water wetland carved out of a natural depression on the floodplain of two minor tributaries of the Yamuna-Gambhir and the Banganga is the country’s finest waterfowl habitat. This important wetland was set aside as a bird sanctuary in 1956 and it was elevated to the status of a National Park in 1981. It was also designated a Ramsar site- a wetland of international importance under the Ramsar convention. This important wetland has distinction of being the only Indian wetland to be included under both the Ramsar and the World Heritage convention. The attempt has been made to evaluate the habitat of Sarus crane in the Keoladeo National Park using satellite data — IRS LISS III and PAN merged product and GIS. Geocoded data of IRS —1C LISS III of 21 March 1999 on 1: 50,000 scale and PAN data of March 17, 1999 were used to generate the vegetation cover type map and open water. The maps showing drainage, human habitations, contours, roads, etc. were prepared using the Survey of India topographical sheets and contour map of park area. Information regarding habitat parameters was collected from the existing literature and field observations. The Sarus crane mainly fed in the wetland on the rhizome ofNymphaea sp.,Scirpus tuberosus andEleocharis plantaginea. As there were changes in their habitat requirements at different seasons, the sighting of Sarus crane in each habitat were recorded along with the time and activity during observation. The most utilized habitat for the entire period of study was moderately wet grassland followed by pools. The pools were used mainly during the summer. The water depth requirement observed was between 30–40 cm and 20–40 cm. The suitability maps for Sarus crane were then generated using all remote sensing based and conventional information using rule based equations in the GIS within the Keoladeo National Park.     

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.     

A 500 hPa synoptic wildland fire climatology for large Canadian forest fires, 1959–1996

Summary In Canada, the average annual area of burned forest has increased from around 1 million ha in the 1970’s to over 2.5 million ha in the 1990’s. A previous study has identified the link between anomalous mid-tropospheric circulation at 500 hPa over northern North America and wildland fire severity activity in various large regions of Canada over the entire May to August fire season. In this study, a northern North American study region of the hemispheric gridded 5° latitude by 10° longitude 500 hPa dataset is identified and analysed from 1959 to 1996 for a sequence of six monthly periods through the fire season, beginning in April and ending in September. Synoptic types, or modes of upper air behavior, are determined objectively by the eigenvector method employing K-means cluster analysis. Monthly burned areas from the Canadian Large Fire Database (LFDB) for the same period, 1959 to 1996, are analysed in conjunction with the classified monthly 500 hPa synoptic types. Relationships between common monthly patterns of anomalous upper flow and spatial patterns of large fire occurrence are examined at the ecozone level. Average occurrence of a monthly synoptic type associated with very large area burned is approximately 18% of the years from 1959 to 1996. The largest areas burned during the main fire (May to August) season occur in the western Boreal and Taiga ecozones – the Taiga Plains, Taiga Shield, Boreal West Shield and Boreal Plains. Monthly burned areas are also analysed temporally in conjunction with a calculated monthly zonal index (Zi_m) for two separate areas defined to cover western and eastern Canada. In both western and eastern Canada, high area burned is associated with synoptic types with mid-tropospheric ridging in the proximity of the affected region and low Zi_m with weak westerlies and strong meridional flow over western Canada. Received April 3, 2001 Revised July 13, 2001