International Journal of Remote Sensing

Kniveton, D. R.; De Graff, P. J.; Granica, K.; Hardy, R. J.

doi: 10.1080/014311600210669pmid: N/A

The effects of mass movements, including debris flows, on the inhabitants of mountainous regions can often be catastrophic, causing serious casualties and property damage. These impacts could potentially be reduced with the development of early warning systems. Debris flows are generally initiated by either heavy rainfall or snow melt. In the past, prediction of debris flow events has been limited to the moment of the flow onset and dependant on the accurate description of free flowing water conditions at the time of initiation. This has remained problematic not least because of the high spatial and temporal variabilities of the triggering phenomena, making their accurate measurement by conventional means, such as by raingauges, difficult. Remote sensing data offers an ideal opportunity to provide information on debris flow triggering conditions, including details of the evolution of triggering rainfall conditions before they initiate a debris flow event. In this paper we outline the development of a remote sensing technique to provide early warning of debris flow triggering conditions using infrared data measured from the Meteosat satellite series, for the Bachelard Valley in the French Alps. The relatively simple relationship and short time interval between the onset of heavy rainfall, and the initiation, movement and deposition of a debris flow allows information on the triggering conditions to be considered as early warning of the actual debris flow event itself, in locations of known debris flow hazard. Predictive information of triggering conditions of a particular hazard is of vital importance to the development of an effective early warning system. The technique outlined in this paper was developed using the debris flow initiation model, of Blijenberg et al ., linked to automated raingauges over a four year period from 1991 to 1994. Of the six case studies identified warning times of 1-12 hours were given in five of these. A false alarm test over a month period for the region revealed false alarms on two days, only. This paper shows that high temporal resolution remote sensing data can be used to provide early warning of atmospheric conditions likely to initiate debris flow events. This information is of importance to the development of a debris flow hazard early warning system.

Le Hegarat-Mascle, S.; Quesney, A.; Vidal-Madjar, D.; Taconet, O.; Normand, M.; Loumagne, C.

doi: 10.1080/014311600210678pmid: N/A

More and more remote sensing data corresponding to various wavelength domains is becoming available. Visible/infrared data were first used for land cover classification. However, radar data are becoming more widely used for hydrological and agricultural applications. This paper discusses the performance, for land cover type discrimination, of an optical image acquisition and a multitemporal radar series. For the majority of land cover types existing within the test site (representative of northern European agricultural areas), both ERS multitemporal SAR and Landsat multispectral visible/infrared classifications lead to good results, with the latter being more robust. For better identification of cultures that are less represented, the complementarity of the two datasets may be exploited using an efficient data fusion algorithm based on the Dempster-Shafer evidence theory. The performance of this combination was verified on two successive vegetation cycles.

Koch, M.

doi: 10.1080/014311600210687pmid: N/A

The focus of the work reported in this paper is on the way in which land degradation processes affecting semi-arid Mediterranean environments are enhanced by the operation of external (human-induced) factors. A study of landscape change in the Los Monegros area of Aragon, north-east Spain, over the period 1984-1997 has been undertaken in order to evaluate the effects of the extension of irrigation on the expansion of arable agriculture, and to estimate the consequential effects on the landscape. Radiometrically-calibrated Landsat TM data were combined with ground-based observations (soil and geology maps, plus hydrogeological data) with the aim of analysing temporal change in land cover. A combination of remote sensing methods (linear spectral unmixing and principal components analysis) was used to determine the proportions of individual soil types. Change detection techniques were employed to pick out areas at risk from land degradation processes (increased soil erosion and soil salinization) and to explain the ways in which agricultural land-use practices interact with the geological and hydrogeological characteristics of the study area.

Ramasamy, S. M.; Kumanan, C. J.

doi: 10.1080/014311600210696pmid: N/A

It has been established beyond doubt that the drainage architecture and the fluvial histories of river systems give excellent indications not only on the surficial lithology but also on the ongoing morphotectonic processes of the planet Earth. Among the various drainage patterns, the 'eyed drainage' pattern is considered to be one of the most significant anomalies and such 'mega eyed' drainages interpreted from IRS-1A imagery in some of the major river systems in Tamil Nadu, Indian Peninsula, are found to signify ongoing tectonic movements in an otherwise seismically inert shield area.

Nagarajan, R.

doi: 10.1080/014311600210704pmid: N/A

Surface-cover status of the catchment, reservoir and dam site, before, during and after the completion of a water resources project, plays a vital role in an Environmental Impact Assessment (EIA). Orbital satellite data, along with theme and site-based information, were used in an EIA of Dudhganga Dam in India. The collection and analysis of these data in the monitoring of on-going projects is highlighted in this study.

Sahoo, Pradeep K.; Kumar, Sandeep; Singh, Ramesh P.

doi: 10.1080/014311600210713pmid: N/A

The Ganga and Yamuna rivers emerge from the Himalayas along two major faults known as the Ganga and Yamuna Tear Faults respectively. The two major strike-slip faults transverse to the Siwalik range are clearly seen in satellite imagery of the Dehradun area. Earthquake records, landslide and recent changes in geomorphological features indicate that the area between the Main Boundary Thrust and the Main Frontal Thrust is tectonically active. An effort has been made to study the tectonic evolution and neotectonism of the Ganga and Yamuna tear faults. Spectral and spatial enhancement techniques have been employed to the digital data of IRS-1B LISS-I to delineate the lineaments and major faults of the area. Based on Mohr's theory, failure criteria and statistical analysis of remotely sensed lineament data, horizontal compressive stress values (SHmax) have been estimated at various sites of the study area. These data are found to be consistent with the published SHmax orientation determined from earthquake focal mechanism solutions. Active faults and lineaments have been extracted from the remotely sensed lineament data. Past earthquake data and depth to basement contour data have been used in an integrated approach with available Geographic Information System (GIS) techniques to reconstruct a present-day regional geodynamic model. Attempts have been made to investigate the genesis of Ganga and Yamuna Tear Faults and possible causes of recent tectonic activities of the area with the help of the proposed geodynamic model.

Sujatha, G.; Dwivedi, R. S.; Sreenivas, K.; Venkataratnam, L.

doi: 10.1080/014311600210722pmid: N/A

Apart from soil erosion by wind and water, the major land degradation processes operating in irrigated commands in arid and semi-arid regions are waterlogging and subsequent salinization/alkalinization. Remote sensing data have been used successfully in studies of the spatial extent, magnitude and temporal behaviour of lands affected by such processes. In this work we interpreted Landsat Multispectral Scanner images acquired during 1975 and Landsat Thematic Mapper data acquired during 1993, in conjunction with ancillary information and adequate ground data, to derive information on the extent and spatial distribution of various degraded lands, namely salt-affected soils, waterlogged areas and eroded lands in part of the Jaunpur district of Uttar Pradesh. The results indicate a significant shrinkage in the spatial extent of salt-affected soils (of the order of 49.76%) over the period 1975 to 1993. A similar trend was observed in the temporal behaviour of waterlogged areas, but an increase (6.45%) was found in the spatial extent of eroded lands. The methodology employed and the observations made are described here in detail.

Bendix, J.

doi: 10.1080/014311600210731pmid: N/A

The formation, dynamics and spatial distribution of heavy precipitation during the 1991/92 El Nino in Ecuador and northern Peru were examined by means of Meteosat-3 imagery, NOAA-AVHRR-based multichannel sea surface temperatures (MCSST) and additional meteorological observations. The Convective and Stratiform Technique (CST) was used for rain retrieval by means of Meteosat IR data and a cross-correlation approach was applied to Meteosat image sequences to derive cloud motion winds (CMW) which are essential for the analysis of circulation patterns leading to severe precipitation. From an analysis of 45 days with severe precipitation it is proven that three mechanisms were responsible for the formation of heavy rains. Each mechanism reveals a specific localized impact. (1) The most frequent mechanism (frequency of ∼61%) represents an extended land-sea breeze system. During such weather conditions, predominantly locally confined precipitation patterns occured. Areas affected by the sea wind front during the day were the coastal plains up to the 1000 m contour line on the western Andean slope. Local maxima in the frequency of cloudiness leading to precipitation could be found at isolated peaks of a lower coastal cordillera. At night the highest frequency of precipitation was found over the warm water surface of the Gulf of Guayaquil, mainly due to its coastal shape which significantly favours convergence of the nocturnal land breeze. (2) Convection, initiated in the coastal plain and on the western Andean slopes during the afternoon, was significantly intensified by an entrainment of remainders of cirrus shields from the Amazon basin. These cloud fragments spilled over the Andes with well-developed trades in the mid/upper troposphere which blew in the opposite direction to the daily sea/up-slope breeze. The spill over points were characterized by areas of deep convection on the western Andean slopes and were frequently valley axes perpendicular to the mountain chain as well as the Andean depression in southern Ecuador. (3) During the main El Nino phase (March-April), heavy and persistent precipitation was extended over wide areas of the coastal plain showing neither a distinct diurnal cycle nor preferential areas. Deep convection was frequently organized in mesoscale convective complexes (MCC) and was spatially correlated with MCSST > 27 . The extensive instability of the troposphere during these weather conditions was marked by convective cloud streets and an intensification of the meridional Hadley circulation off the coast of southern Ecuador and Peru.

Bruzzone, L.; Serpico, S. B.

doi: 10.1080/014311600210740pmid: N/A

One of the main phases in the development of a system for the classification of remote sensing images is the definition of an effective set of features to be given as input to the classifier. In particular, it is often useful to reduce the number of features available, while saving the possibility to discriminate among the different land-cover classes to be recognized. This paper addresses this topic with reference to applications that involve more than two land-cover classes (multiclass problems). Several criteria proposed in the remote sensing literature are considered and compared with one another and with the criterion presented by the authors. Such a criterion, unlike those usually adopted for multiclass problems, is related to an upper bound to the error probability of the Bayes classifier. As the objective of feature selection is generally to identify a reduced set of features that minimize the errors of the classifier, the aforementioned property is very important because it allows one to select features by taking into account their effects on classification errors. Experiments on two remote sensing datasets are described and discussed. These experiments confirm the effectiveness of the proposed criterion, which performs slightly better than all the others considered in the paper. In addition, the results obtained provide useful information about the behaviour of different classical criteria when applied in multiclass cases.

Kushwaha, S. P. S.; Dwivedi, R. S.; Rao, B. R. M.

doi: 10.1080/014311600210759pmid: N/A

One of the problems associated with synthetic aperture radar (SAR) data analysis is the presence of random noise or speckle SAR data, being achromatic in nature, which offers very limited scope for the detection and delineation of various terrain features. ERS-1 SAR data for the coastal region of West Bengal, India were processed (a) to suppress the random noise using various filters, (b) to generate the intensity, hue and saturation (IHS) transform from temporal SAR data, and (c) to study the synergism of SAR data with optical sensor data. The results indicate that the Gamma MSP filter with a 5 5 pixel kernel size has been the most efficient in suppressing the noise and concurrently improving the image contrast. The IHS transform of temporal SAR data made it easier to discriminate between various wetland categories. This was also the case with hybrid image generated by the Indian Remote Sensing Satellite (IRS-1B) Linear Imaging and Self-scanning Sensor (LISS-II) data when compared to SAR data alone.