Saran S.,Indian Institute of Remote Sensing |
Joshi R.,Indian Institute of Remote Sensing |
Sharma S.,G B Pant Institute Of Himalayan Environments And Development |
Padalia H.,Regional Remote Sensing Service Center |
Dadhwal V.K.,Indian National Remote Sensing Centre
Journal of the Indian Society of Remote Sensing | Year: 2010
The study explores the use of multiple criteria decision techniques in predicting spatial niche of Brown oak (also known as Kharsu oak, Quercus semecarpifolia Sm.) formation in midaltitude (2,400-3,500 meter amsl) Kumaun Himalaya. Predictive models using various climatic and topographical factors influencing Brown oak's growth and survival were developed to define its current ecological niche. Analytical Hierarchical Process (AHP) method involving Saaty's pair-wise comparison was performed to rank the explanatory powers of each compared variable. Variables were suitably weighted using fuzzy factor standardization scheme to reflect their relative importance in defining species niche. An optimum indicator was then chosen for deriving a site suitability map of brown oak. This study establishes the role of aspect in the current distribution of the species along with known influence of altitude. Future niches of oak has been tracked in the projected climate change scenario of +1°C and +2°C rise in temperature and 20 mm in precipitation. The results show that on predicted +1°C and +2°C increase in temperature, present habitat of brown oak distribution may be reduced by 40 per cent and 76 per cent respectively. © 2010 Indian Society of Remote Sensing.
Gupta A.K.,National Institute of Technology Jalandhar |
Sharma J.R.,Regional Remote Sensing Service Center |
Sreenivasan G.,Regional Remote Sensing Service Center
International Journal of Remote Sensing | Year: 2011
Digitally processed satellite images have unearthed the hidden course of a major lost river below the sands of the Thar Desert, in the India-Pakistan (Indo-Pak) region. The great Himalayan river of the Vedic period (10 000-8000 BP) is mentioned in ancient Indian literature. It was called the 'Saraswati' in India and the 'Hakra' in Pakistan and it dried up during 4000-3500 BP. Large numbers of archaeological sites from the Harappan civilization occur along the dry river bed. The mapped course of the river is 4-10 km wide and conforms to the size described in the Rigveda. The newly described course is validated through the drilling of tube wells in the channels and through archaeological, hydrogeological and sedimentary data. An enormous quantity of potable water has been found along these channels. The path of the (main) river course, the likelihood of the river shift and the reasons for its disappearance are discussed. © 2011 Taylor & Francis.
Singh N.J.,Regional Remote Sensing Service Center |
Singh N.J.,Indian Institute of Technology Roorkee |
Kudrat M.,Regional Remote Sensing Service Center |
Jain K.,Indian Institute of Technology Roorkee |
Pandey K.,Regional Remote Sensing Service Center
International Journal of Remote Sensing | Year: 2011
The cropping pattern (rotation) of a region depends on the soil, water availability, economic conditions and climatic factors. Remote sensing is one of the effective tools that can provide precise and up-to-date information on the performance of agricultural systems. Four seasons data from the Indian Remote Sensing Satellite (IRS)-P6 AdvancedWide Field Sensor (AWiFS) were used for the generation of the cropping pattern of Uttar Pradesh by geographic information system (GIS)-aided integration of digitally classified crop and land use inventories of the kharif, rabi and zaid crop seasons. Twelve different cropping patterns were delineated and mapped in the Indo-Gangetic plain of Uttar Pradesh. The forests covered about 6.32% of the total geographical area. The net cropped area was 20 282 159.46 ha (84.18% of the total geographical area) and the non-agricultural area observed was 3 437 376.00 ha (14.26% of the total geographical area). Rice was the single most dominant crop of the state, occupying about 32.94% of the total geographical area during the kharif season. Maize/jowar was the second major cereal crop, accounting for 13.77% of the total geographical area of the state. The major crops grown during the rabi season were wheat and pulses/oilseed, covering areas of 7 979 267.71 ha (33.12%) and 5 974 742.58 ha (24.80%), respectively. Rice-wheat, sugarcane and rice-pulses were the major cropping patterns, occupying about 3 958 739.85 ha (16.43%), 3 609 939.74 ha (14.98%) and 2 511 298.24 ha (10.42%), respectively. The areas under pulses/oilseed were significantly higher in the rabi season. Sugarcane-wheat and pulses shared an almost equal area (6.49%). The maize/jowar-wheat cropping pattern occupied 6.14% of the total geographical area of the state. Single cropping patterns (i.e. rice-fallow, fallow-pulses, fallow-wheat, maize-fallow and sugarcane-fallow) were minor, occupying 6.08, 2.94, 4.06, 2.69 and 2.51%, respectively. Waste land, including gulley, salt-affected, waterlogged and rock land, accounted for 3.80% of the total geographical area. The results of this study indicate that temporal IRS-P6 (AWiFS) data are very useful for studying spatial cropping patterns. The values of the Multiple Cropping Index (MCI) and the Cultivated Land Utilization Index (CLUI) show that the study area has a high cropping intensity. © 2011 Taylor & Francis.
Bhunia G.S.,Rajendra Memorial Research Institute of Medical Sciences |
Kesari S.,Rajendra Memorial Research Institute of Medical Sciences |
Jeyaram A.,Regional Remote Sensing Service Center |
Kumar V.,Rajendra Memorial Research Institute of Medical Sciences |
Das P.,Rajendra Memorial Research Institute of Medical Sciences
Geospatial Health | Year: 2010
Kala-azar, a fatal infectious disease in many Indian states, particularly in Bihar, West Bengal, Uttar Pradesh, and Jharkhand, is caused by the protozoan parasite Leishmania donovani and transmitted by the sandfly vector Phlebotomus argentipes. The vector is distributed all over the country but the disease is confined to particular zones since before the last century. In this study, parameters such as altitude, temperature, humidity, rainfall and the normalized difference vegetation index (NDVI) were investigated for correlation with the distribution of the disease in the northeastern corner of the Indian sub-continent. Data analysis on Kala-azar prevalence during the period 2005-2007 in the four states showed that the highest prevalence was below 150 m of altitude with very few cases located above the 300 m level. Low NDVI value ranges (0.03-0.015) correlated with a high occurrence of the disease. The maximum temperatures in the affected sites varied between an upper level of 25-29°C and a minimum of 16-20°C. The rainfall in these areas fluctuated between 1154 and 1834 mm. As the disease showed a high correlation with the prevailing topographic conditions, an attempt was made to improve the relative strength of the approach to predict the potential for endemicity of leishmaniasis by introducing satellite imagery complemented with a geographical information system database.
Rajitha K.,Civil Engineering Group |
Mukherjee C.K.,Indian Institute of Technology Kharagpur |
Chandran R.V.,Regional Remote Sensing Service Center |
International Journal of Remote Sensing | Year: 2010
The present study focuses on the identification and quantification of land-cover changes occurring in the coastal stretches of the East Godavari delta, Andhra Pradesh, India. The analysis of series of multi-temporal satellite data provides an accurate quantification and therefore a better understanding of the process of land-cover changes during 1990-2005. Land-cover changes were quantified based on normalized difference vegetation index (NDVI) image differencing and a post-classification comparison approach. The change detection results were examined in terms of the proportion of land-cover classes and change trajectories with particular emphasis on coastal aquaculture development within the study area. The study shows that the total area under aquacultural ponds increased from 2985 ha in 1990 to 7067 ha in 2005. The major changes in the study area occurred during 1990-1994, when 2873 ha of agricultural land and 762 ha of degraded mangroves were converted into aquacultural ponds. The prediction of landcover distribution in 2010 on the basis of a Markov chain shows a continuing upward trend of the aquaculture area (8267 ha) with less impact on the mangrove area. The analysis predicts that the agricultural land area will continue to decrease from 50 122 to 46 978 ha during 2005-2010. © 2010 Taylor & Francis.
Bijalwan A.,Allahabad University |
Swamy S.L.,Indira Gandhi Agricultural University |
Sharma C.M.,Hemwati Nandan Bahuguna Garhwal University |
Sharma N.K.,Jharkhand Space Application Center |
Tiwari A.K.,Regional Remote Sensing Service Center
Journal of Forestry Research | Year: 2010
A study was conducted to characterize the land use, biomass and carbon status of dry tropical forest in Raipur district of Chhattisgarh, India using satellite remote sensing data and GIS techniques in the year of 2001-2002. The main forest types observed in the area are Teak forest, mixed forest, degraded forest and Sal mixed forest. The aspect and slope of the sites influenced the forest vegetation types, biomass and carbon storage in the different forests. The standing volume, above ground biomass and carbon storage varied from 35.59 to 64.31 m3·ha-1, 45.94 to 78.31 Mg·ha-1, and 22.97 to 33.27 Mg·ha-1, respectively among different forest types. The highest volumes, above ground biomass and carbon storage per hectare were found in the mixed forest and lowest in the degraded forest. The total standing carbon present in the entire study area was 78170.72 Mg in mixed forest, 81656.91 Mg in Teak forest, 7833.23 Mg in degraded forest and 7470.45 Mg in Sal mixed forest, respectively. The study shows that dry tropical forests of the studied area in Chhattisgarh are in growing stage and have strong potential for carbon sequestration. © 2010 Northeast Forestry University and Springer-Verlag Berlin Heidelberg.