Swapnamita Choudhury

Cover: Satellite detects surface thermal anomalies associated with the Algerian earthquakes of May 2003

On 21 May 2003, Algeria was hit by a powerful shallow focus earthquake of magnitude Mw56.8 (http://neic.usgs.gov/neis/bulletin/03_EVENTS/eq_030521/) at 18:44 (UTC) which led to the death of 2276 people, injured more than 11 000 people and left 200 000 people homeless (http://www.reliefweb.int/w/ rwb.nsf/6686f45896f15dbc852567ae00530132/b49cf0730dc7884149256d480021ee90? OpenDocument). The geographical location of the epicentre was 36.90uN latitude and 3.71uE longitude (figure 1), just offshore from the province of Boumerdes, and about 60 km ENE of the capital city of Algiers. The province of Boumerdes, including the coastal city of Boumerdes, Thenia, Rouiba and the eastern district of Algiers are among the heavily damaged regions by this ‘Boumerdes earthquake’ (www.Reliefweb.int/w/ rwb.Nsf/6686f45896f15dbc852567ae00530132/b342fd7d3ea5bb285256d4000671dce? OpenDocument). The earthquake has been named after the worst hit region, Boumerdes in Algeria. Notable large-scale concrete structure damage was witnessed in this earthquake. Since Algeria’s independence from France in 1962, the country has seen a rapid rise in urbanization. There has been a growth in the building of concrete structures in the cities. The heavily damaged or collapsed buildings were mainly built within the last decade, some just completed or in the process of completion. Widespread liquefaction, rock falls, landslides and ground cracking were reported in the earthquake-affected region. However, no clear case of fault rupturing was reported (www-megacities.physik.uni-karlsruhe.de/wwwmega/downloads/QuakeReport1_2June03.pdf). A tsunami generated with an estimated wave height of 2 m caused damage to boats and underwater telephonic cables off the Balearic Islands, Spain (http://neic.usgs.gov/neis/bulletin/03_EVENTS/eq_030521/). This major earthquake was followed by a number of low intensity earthquakes (table 1), which continued till 29 May 2003. Minutes after the 6.8 magnitude earthquake played havoc in northern Algeria, a 5.7 Mw earthquake occurred at 18:51 (UTC), with an epicentre at 36.97uN latitude and 3.85uE longitude (http:// neic.usgs.gov/neis/bulletin/03_EVENTS/eq_030527/neic_uhbj_m.html). Other aftershocks of magnitude greater than 5 (Mw) occurred on 22, 27 and 28 May 2003. More than 21 aftershocks (table 1) were reported within nine days beginning from 21 May 2003, ranging in magnitude from 2.4 to 5.8 (Mw). Land Surface Temperature (LST) maps generated from thermal images of NOAA-AVHRR datasets can be used to monitor the Earth’s thermal regime for any

GIS based surface hydrological modelling in identification of groundwater recharge zones

Digital elevation model (DEM) is a storehouse of a variety of hydrological information along with terrain characteristics. In recent years, automatic extraction of drainage network from DEM with the help of Geographical Information System (GIS) has become possible and is now being practised the world over for hydrological studies. In the present study, a comparative analysis of the drainage network derived from DEM and drainage extracted from surveyed topographical maps has been carried out. A comparative analysis based on nearest neighbour analysis on an intersection theme of two drainage networks showed that there is clustering (randomness<1) existing at places which show potential groundwater recharge zones. The suitable groundwater recharge zones identified in the drainage comparative analysis also show good correlation with the suitable recharge maps derived from remote sensing and GIS based procedure. In this study, two different watersheds (a) Dwarkeshwar in Bankura district, West Bengal, India, and (b) Kethan in Vidisha districts of Madhya Pradesh, India have been taken to analyse for identification of suitable groundwater recharge zones. The drainage comparative analysis approach developed and tested successfully in the present study is quick and reliable for the identification of suitable groundwater recharge zones particularly in a hard rock terrain.

Cover: NOAA‐AVHRR detects thermal anomaly associated with the 26 January 2001 Bhuj earthquake, Gujarat, India

The earthquake of 26 January 2001, USGS magnitude Ms57.9 and epicentre at 23u239570 latitude and 70u189510 longitude (figure 1), struck the state of Gujarat at 8:46 a.m. (IST) while India was celebrating her 51st Republic Day. The death toll was estimated at 20 083 according to Gujarat Government figures and was accompanied by wide scale damage to the property and economy of the state of Gujarat. Places like Bhuj, Anjar, Bhachau and Rapar faced near total destruction and Gandhidham, Morvi, Rajkot and Jamnagar faced extensive damage to concrete structures. A total of 7633 villages of 181 talukas in 11 districts were affected (Saraf et al. 2002). Thermal channels (4 and 5) of AVHRR onboard the NOAA series of satellites can be used to monitor the Earth’s thermal regime. Prior to an earthquake, crustal

Remote sensing observations of pre‐earthquake thermal anomalies in Iran

Stresses acting before an earthquake in tectonically active regions can augment the near ground temperature of the region. Such changes detected through thermal remote sensing can provide important clues about future earthquakes. A post‐earthquake analysis through NOAA‐AVHRR data showed pre‐earthquake thermal anomalies prior to the Bam earthquake on 26 December 2003 and the Dahoeieh‐Zarand earthquake on 21 February 2005 in Iran. It was observed in these earthquakes that there was short‐term temporal increase in land surface temperature (LST) of the regions around the epicenters. The rise in temperature was about 5–10°C. Further, temperature variation curves prepared from air temperature data collected from several meteorological stations around epicentres confirmed the appearance of thermal anomalies prior to several earthquakes between February and March 2005 in Iran. The thermal anomalies went away along with the earthquake events. Release of greenhouse gases from rocks due to the induced pressure before earthquakes can create a localized greenhouse effect. Charge carriers in rocks can be free electrons, which dissociate under high pressure. When they again recombine to attain electron stability they release heat, which can increase the LST of the region.

MODIS land surface temperature data detects thermal anomaly preceding 8 October 2005 Kashmir earthquake

During the morning (03:50:40 UTC) of 8 October 2005 a major (M w 7.6) shallow focus (26 km) earthquake struck Kashmir (Himalayan region). Its epicentre was located 10 km NNE of Muzaffarabad (USGS 2005, Magnitude 7.6—Pakistan, available online at http://earthquake.usgs.gov/eqcenter/eqinthenews/2005/usdyae/). The present manuscript is an attempt to study the development of thermal anomaly in land surface temperature (LST) preceding this earthquake. Using data from Moderate Resolution Imaging Spectroradiometer (MODIS) onboard National Aeronautics and Space Administration (NASA) Terra satellite, the daily daytime LST images have been analysed for the correlation between LST variations and Kashmir earthquakes. An evident correlation of thermal anomaly in LST that is apparently related to pre‐seismic activity has been identified. An attempt has also been made to quantify the change in LST (in °C) with reference to previous day temperature values and background data (MODIS LST data from 2000–2004). A 4–8°C rise in LST to the south of the earthquake epicentre has been observed seven days before the major event. Air temperature data from two meteorological stations (Islamabad and Srinagar) also supports the observations made through MODIS LST data. The role of terrain parameters like rock types, vegetation and topography upon the spatial and temporal variations of anomalous temperature area have been studied.

Technical Note: Mapping and forecasting of North Indian winter fog: an application of spatial technologies

In India, the Indo‐Gangetic plain (part of Northern India) is invariably affected by dense fog in the winter months every year due to typical meteorological, environmental and prevailing terrain conditions. Pollution also plays an important role in the formation of fog (smoke+fog = smog) in India. Using National Oceanic and Space Administration‐advanced very high resolution radiometer data the fog‐affected regions in Northern India were delineated and the spatial extent of fog for the winter months of the years 2002–03, 2003–04 and 2004–05 (December–February) were studied and mapped. Forecast for future fog based on the analysis of satellite and meteorological (air temperature, relative humidity and wind speed) data was also done. The fog‐affected areas were classified into maximum‐fog‐affected area, moderately fog‐affected area and least fog‐affected area. It has been found that in the winter months of the years 2002–03, 2003–04 and 2004–05, the fog‐affected area in Northern India was about 867 000 km2, 625 000 km2 and 706 800 km2 respectively. The maximum fog‐affected area was found to be 606 400 km2, the moderately fog‐affected area was found to be 230 400 km2 and the least fog‐affected area was found to be 404 500 km2. Further, based on meteorological parameters, such as temperature, humidity and wind speed along with elevation data was used to derive an approach for future fog prediction in this region.

Cover: Development of a new image correction technique to remove false topographic perception phenomena

Generally, almost all Sun-synchronous satellites’ orbits are designed in such a way that their equatorial crossing timings are during morning hours (normally between 09:30 to 10:30 hours). Remote sensing data from such satellites of any rugged terrain will always suffer from topographic effects and in such cases people frequently perceive reverse topography, which means valleys as ridges and vice versa in the optical images of Sun-synchronous satellites (Saraf et al. 1996). The appearance of inverse topography in such satellite data has been first identified and termed as False Topographic Perception phenomena (FTPP) by Saraf et al. (1996). Further, FTPP have been observed in various satellite images such as Landsat, IRS, SPOT and NOAA series of satellites. As described by Saraf et al. (1996), FTPP are usually caused by the combination of various interrelated factors; among them are topographic relief, Sun elevation, the azimuth angle, viewing angle, and hatching or engraving features present on the valley slopes. Once satellite data of rugged terrain are acquired, all FTPP-influencing factors are frozen, except for the viewing angle of the observer. Saraf et al. (1996) also proposed two methods to remove FTPP from satellite images. One is to rotate the image by 180u and mark the north upside down. The other method was to invert the DN values of the pixels i.e. to make the negative of the image. In this paper, a new shaded relief model (SRM) based FTPP correction technique has been developed and successfully demonstrated. Concern about the causes of FTPP has been discussed extensively by Saraf et al. (1996). However, two main questions arise. Whether this is due to the behaviour of human eye and mind; or is this due to the change in the reflectance of grey values of the pixels? Perception of topographic depth from a satellite image is a complex factor depending upon four physical cues; (a) accommodation; (b) convergence; (c) binocular disparity; and (d ) motion parallax; and six psychological cues e.g. retinal image size, linear perspective, area perspective, overlapping, shades-shadows and texture gradient (Toutin 1998). As discussed by Toutin (1998), depth perception is a sophisticated process, which actively combines physiological and psychological cues with a mental model. Human visual experience of the world is based on two-dimensional images (Ramachandran 1988). For example the flat patterns of varying light intensity and colour that fall on the single layer of cells in the retina of the human eye. Yet our brains come to perceive the solidity and depth. A number of cues about depth are

A new technique to remove false topographic perception phenomenon and its impacts in image interpretation

All Sun‐synchronous remote sensing satellites, during day passes always acquire images when the illumination source (i.e. Sun position) is from the SE direction. The typical solar–illumination–source–observer position creates a false topographic perception phenomenon (FTPP) in the images of any rugged terrain (e.g. Himalayas, Alps etc.). Due to the presence of FTPP, valleys appear as ridges and vice versa, especially in rugged terrain. The correction of FTPP is necessary because it creates confusion in the minds of interpreters due to inherent inverse topographic perception. This paper explains the development of a new approach to remove FTPP. It has been successfully demonstrated using an IRS‐1D‐LISS‐III image of part of the Himalayas, which represents highly rugged terrain. In this newly developed image‐processing technique; a red–green–blue (RGB) image is first transformed into intensity–hue–saturation (IHS) channels, then the original intensity channel is inverted and later retransformed back from an IHS to a RGB image. After this retransformation, the RGB image is then colour balanced with original false colour composite. The final image product is free from FTPP and also contains almost the same image information. This method is an easy and quicker method to remove FTPP in comparison to the already available methods (e.g. image rotation by 180°; creating an image negative; using an opposite illuminated shaded relief model as an intensity image during IHS to RGB retransformation) for FTPP correction. Further, this paper discusses the relative advantages of this new method in comparison to previous methods in light of image classification and lineament interpretation carried out using images with and without FTPP.

Technical Note and Cover

The advent of Earth Resources Technology has added a new dimension to observing, studying and interpreting the ground objects of an area. Since the inception of operational remote sensing researchers have made continuous efforts to generate elevation data from satellite images, thus producing a digital elevation model (DEM). A DEM is a surface generated from the elevation data which is used for various geospatial analyses. However, high spatial resolution and an accurate DEM of the entire globe is still not available to the user community. Furthermore, requirements of DEMs of rugged terrain are very high since other DEM generation approaches have severe limitations in highly rugged terrains like the Himalayas. Several studies have been carried out in this direction, but have mainly focused on stereo pair data of the same sensor, deriving the DEM from these datasets. In recent years Synthetic Aperture Radar (SAR) interferometry technique has been developed to generate DEM, but without any success in highly rugged terrains like the Himalayas. There is a general understanding that elevation and temperature values are inversely related. The present study attempts to exploit this inverse relationship between elevation and temperature values, generating a relatively coarse resolution DEM from National Oceanic & Atmospheric Administration Advanced Very High Resolution Radiometer (NOAA‐AVHRR) night‐time thermal infrared data. A visual and statistical comparison between NOAA‐AVHRR night‐time thermal infrared data and US Geological Survey (USGS)‐DEM clearly illustrates the existence of this inverse relationship. It indicates that the temperature of an area decreases with an increase in elevation. NOAA‐AVHRR night‐time thermal infrared data were used so as to avoid the effects of differential solar heating, which is very common during daytime in a highly rugged terrain like the Himalayas. Furthermore, the main advantages of using USGS DEM for this comparative analysis are: (a) its spatial resolution (1 km), which is very close to the spatial resolution of the NOAA‐AVHRR thermal data (1.1 km); and (b) its availability through the Internet. This technique of generating DEM from NOAA‐AVHRR night‐time thermal infrared data is most applicable to hilly terrain where human interference is less. Applicability of the present approach is enormous and can be highly efficacious when using relatively high spatial resolution (60 m) Landsat ETM+ night‐time thermal infrared data of highly rugged terrains.The advent of Earth Resources Technology has added a new dimension to observing, studying and interpreting the ground objects of an area. Since the inception of operational remote sensing researchers have made continuous efforts to generate elevation data from satellite images, thus producing a digital elevation model (DEM). A DEM is a surface generated from the elevation data which is used for various geospatial analyses. However, high spatial resolution and an accurate DEM of the entire globe is still not available to the user community. Furthermore, requirements of DEMs of rugged terrain are very high since other DEM generation approaches have severe limitations in highly rugged terrains like the Himalayas. Several studies have been carried out in this direction, but have mainly focused on stereo pair data of the same sensor, deriving the DEM from these datasets. In recent years Synthetic Aperture Radar (SAR) interferometry technique has been developed to generate DEM, but without any success in highly...

Seismicity and reservoir induced crustal motion study around the Tehri Dam, India

The Tehri Dam is located in a seismotectonically active region in the Indian Himalayan belt. This 260.5 m high dam has a live water storage of 2615 × 106 m3 and is capable of generating crustal deformation corresponding to water fluctuation. Filling of the reservoir started in October 2005. Seismic data around the dam between 2000 and 2010 shows that seismicity is corresponding to drawdown levels of the reservoir rather than to higher water levels. GPS data at twelve local benchmarks were collected from 2006 to 2008 during filling and drawdown reservoir levels. The velocity vectors show ground motion to be between ∼0.69–1.50 mm in the different filling-drawdown cycles with reference to the permanent station at Ghuttu. The motion appears to be inwards into the reservoir when the reservoir is filled and outwards when the reservoir is drained. This ground motion corresponds to elastic deformation and rebound due to effect of the oscillating water levels.