Haryana Space Applications Center

Hisār, India

Haryana Space Applications Center

Hisār, India
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Tripathy B.R.,Kumaun University | Tiwari V.,Kumaun University | Pandey V.,Kumaun University | Elvidge C.D.,National Oceanic and Atmospheric Administration | And 4 more authors.
IEEE Sensors Journal | Year: 2017

Nocturnal lighting is a primary method for enabling human activities. Since the release of the digital archives of Defense Meteorological Satellite Program Operational Line Scanner (DMSP/OLS) radiance calibrated nighttime light data in 1992, a variety of data sets based on this database have been produced and applied to monitor and analyze human activities and natural phenomena. DMSP uses OLS sensor, which has an oscillating scan radiometer with a broad field of view and captures images at a nominal resolution. Correlations at aggregate scales and analysis of the saturated areas of the images showed the strong relation between light intensity and the populations. The demographics of the People's Republic of China are identified by a large population, whose population is about 19% of the total world population. Beijing, Guangdong, and Tianjin are the metropolises of China, which contribute the maximum population. Using the regression analysis, the metropolises population data can be extracted from the DMSP nighttime data (r2=0.96$ ). Consequently, the DMSP imagery may prove to be useful to inform a smart interpolation program to improve maps and data sets of human population distributions in the areas of the world, where good census data may not be available or do not exist. © 2016 IEEE.

Duhan D.,Haryana Space Applications Center | Pandey A.,Indian Institute of Technology Roorkee | Srivastava P.,Auburn University
Meteorology and Atmospheric Physics | Year: 2017

In this study, rainfall variability in connection with El Niño Southern Oscillation (ENSO) over the Tons River Basin which is a sub-basin of the Ganges River has been examined. The rainfall trends on annual and seasonal basis for 15 weather stations were examined using the data of 1951–2004. Furthermore, the association between ENSO and rainfall was analyzed using three methods, namely cumulative frequency distributions, correlation analysis, and composite analysis. The annual rainfall series analysis indicated a significant decrease at Govindgarh (5.5 mm/year) and Meja (6.6 mm/year) stations. Seasonal rainfall analysis indicated significant decreasing trends at fourteen stations in pre-monsoon season, ten stations in winter season, two stations in post-monsoon, and only one station in monsoon season. The average frequency of occurrence of drought is once in every 4–7 years. Only monsoon season rainfall showed a significant negative correlation with Niño 3.4 SST at almost all the stations. During El Niño, the probability of below normal rainfall is high. However, during La Niña, the probability of above normal or near normal rainfall is high in monsoon season. Furthermore, comparison of results before (Pre76) and after (Post76) the climate shift revealed that the relationship between rainfall and El Niño has strengthened after the climate shift. © 2017 Springer-Verlag Wien

Yadav M.,Haryana Space Applications Center | Sharma M.P.,Haryana Space Applications Center | Prawasi R.,Haryana Space Applications Center | Pal O.,Haryana Space Applications Center | Hooda R.S.,Haryana Space Applications Center
32nd Asian Conference on Remote Sensing 2011, ACRS 2011 | Year: 2011

The present paper highlights the methodology and results of agricultural biomass estimation in Haryana using geo-informatics and conventional surveys for power generation. Multi-date and multi-season Indian Remote Sensing Satellite (IRS) LISS-3 digital data of 23.5 m spatial resolution along with various spatial and non-spatial collateral data have been used to generate total cropped area (Monsoon and Winter season). Harvest Indices (HI) values of various crops and average yield data were used to assess crop wise total agricultural biomass, total non-grain (NG)/non-economic (NE) agricultural biomass. Surplus agricultural biomass available for power generation was calculated using the field survey in about 200 village locations. The crop-wise biomass requirement for generation of 1 MW electrical power for 6500 hrs in a year was used as available in literature. In Haryana district-level power generation potential was computed using the availability of crop-wise surplus agricultural biomass. The net surplus biomass available after the domestic use and subtraction of crops biomass used as fodder and selling by the farmers is 8416.47 thousand tonnes. The total power generation potential from this biomass is 1018.95 MW. It is expected that the maps and data will help in selecting suitable sites for setting up of small power generation plants using surplus agricultural biomass.

Bisht P.,Kumaun University | Kumar P.,Banasthali University | Yadav M.,Haryana Space Applications Center | Rawat J.S.,Kumaun University | And 2 more authors.
International Journal of Plant Production | Year: 2013

Agriculture resources reflected to be one of the most imperative renewable and dynamic natural resources. Agricultural sustainability has the premier priority in all countries, whether developed or developing. Cropping system analysis is indispensable for grinding the sustainability of agricultural science. Crop alternation is stated as growing one crop after another on the same piece of land in altered timings (seasons) without prejudicing the soil fertility. The study has been conducted for Fatehabad district of Haryana State of Indo-Gangetic plains in India. This paper generated cropping pattern and crop rotation maps of Fatehabad district. Multi-date IRS LISS-III digital data of different cropping seasons of 2007-08 have been used for this study. The present study relies on data from remote sensing combined with ground observations. Multi-date images of Rabi season images were geo-referenced using master images. Multi-date images of Kharif and single date image of summer seasons were geo-referenced with geo-referenced Rabi season image using image-to-image registrations and nearest neighborhood resampling method was applied. Multilayer stack were prepared for Kharif and Rabi cropping seasons. Stacked images of different seasons were classified using complete enumeration approach and unsupervised ISO-Data clustering classifier with district outside and non-agriculture mask based on some defined conditions such as the number of clusters, threshold, and number of iterations etc. A multiphased unsupervised ISODATA classification was used for seasonal cropping pattern mapping. The results showed that in the area, a monophonic crop pattern was found in summer and major part of the district is lying as fallow and major crops are fodder, dhaicha & sunflower, but in winter, areas under dissimilar crop pattern had changed melodramatically.

Kumar P.,Kumaun University | Pandey P.C.,University of Leicester | Singh B.K.,Extension Center | Katiyar S.,Banasthali University | And 4 more authors.
Egyptian Journal of Remote Sensing and Space Science | Year: 2016

Soil organic carbon (SOC) is a dynamic soil property that represents the key component of the forest ecosystems. The main objective of the present study is to evaluate SOC using the remote sensing images as well as field methods at Ranthambhore Tiger Reserve Forest area. The soil samples were collected randomly from the region at several field locations, to estimate the surface soil carbon concentrations in the laboratory. The study derived results for bare soil index, NDVI, SOC and relationship of SOC with NDVI using regression analysis, while comparing reference SOC (field measured SOC) and predicted SOC (estimated from satellite image). The remote sensing images were used to predict the precise carbon content associated with organic matter in the soil using NDVI and related equations, to prepare digital soil organic carbon map. The relationship between the NDVI and both reference/predicted SOC is established using the equation to derive the digital SOC for the study area using remote sensing data. The statistical relationship between reference SOC, pH concentrations, and NDVI values were presented against the predicted SOC to provide the variation between each variable. © 2015 Authority for Remote Sensing and Space Sciences.

Panigrahy S.,Space Applications Center | Ray S.S.,Space Applications Center | Manjunath K.R.,Space Applications Center | Pandey P.S.,Project Directorate of Cropping Systems Research | And 6 more authors.
Journal of the Indian Society of Remote Sensing | Year: 2011

Cropping system level study is not only useful to understand the overall sustainability of agricultural system, but also it helps in generating many important parameterswhich are useful in climate change impact assessment. Considering its importance, Space Applications Centre, took up a project for mapping and characterizing major cropping systems of Indo-Gangetic Plains of India. The study area included the five states of Indo-Gangetic Plains (IGP) of India, i.e. Punjab, Haryana, Uttar Pradesh, Bihar and West Bengal. There were two aspects of the study. The first aspect included state and district level cropping system mapping using multi-date remote sensing (IRS-AWiFS and Radarsat ScanSAR) data. The second part was to characterize the cropping system using moderate resolution multi-date remote sensing data (SPOT VGT NDVI) and ground survey. While the remote sensing data was used to compute three performance indices (namely, Multiple Cropping Index, Area Diversity Index and Cultivated Land Utilization Index), the ground survey was conducted using questionnaires filled up by 1,000 farmers selected from 103 villages based on the cropping systems map. Apart from ground survey, soil and water sampling and quality analysis was carried out to understand the effect of different cropping systems and their management practices. The results showed that, rice-wheat was the major cropping system of the Indo-Gangetic Plains, followed by Rice-Fallow-Fallow and Maize-Wheat. Othermajor cropping systems of IGP included Sugarcane based, Pearl millet-Wheat, Rice-Fallow-Rice, Cotton-Wheat. The ground survey could identify 77 cropping systems, out of which 38 are rice-based systems. Out of these 77 cropping systems, there were 5 single crop systems, occupying 6.5% coverage (of all cropping system area), 56 double crop systems with 72.7% coverage, and 16 triple crop systems with 20.8% coverage. The cropping system performance analysis showed that the crop diversity was found to be highest in Haryana, while the cropping intensity was highest in Punjab state. © 2011 Indian Society of Remote Sensing.

Arya V.S.,Haryana Space Applications Center | Singh H.,Haryana Space Applications Center | Hooda R.S.,Haryana Space Applications Center | Arya A.S.,Space Applications Center
International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives | Year: 2014

Desertification constitutes one of the international environment problems whose global importance has been recognized by the international community. Desertification is a problem that affects a number of regions of the world in the developed and developing countries. Desertification is even more closely associated with the development process insofar as it impacts on peoples livelihoods much more directly than other environmental problem. One of the central challenges of environment management in the coming years, the loss of productive land is of major concern in a world where hundreds millions of individuals already go hungry today. Availability of remote sensing data from earth observation satellite and GIS techniques has made it convenient to map and monitor land use/land cover of desertification areas. In the present study Desertification Change analysis in Panchkula district Haryana was carried out by using LISS-III satellite data of 2002 and 2011. The main objective of the study was to monitor the changes in degraded lands in the district. Onscreen digitization technique was followed to interpret the satellite data. The two dates maps were overlaid and changes in area under various degraded lands were calculated. It was observed that Total geographical area of under investigation is 1021.86 sq. km.

Murthy C.S.,Indian National Remote Sensing Centre | Yadav M.,Haryana Space Applications Center | Mohammed Ahamed J.,Indian National Remote Sensing Centre | Laxman B.,Indian National Remote Sensing Centre | And 3 more authors.
Environmental Monitoring and Assessment | Year: 2015

Drought is an important global hazard, challenging the sustainable agriculture and food security of nations. Measuring agricultural drought vulnerability is a prerequisite for targeting interventions to improve and sustain the agricultural performance of both irrigated and rain-fed agriculture. In this study, crop-generic agricultural drought vulnerability status is empirically measured through a composite index approach. The study area is Haryana state, India, a prime agriculture state of the country, characterised with low rainfall, high irrigation support and stable cropping pattern. By analysing the multiyear rainfall and crop condition data of kharif crop season (June–October) derived from satellite data and soil water holding capacity and groundwater quality, nine contributing indicators were generated for 120 blocks (sub-district administrative units). Composite indices for exposure, sensitivity and adaptive capacity components were generated after assigning variance-based weightages to the respective input indicators. Agricultural Drought Vulnerability Index (ADVI) was developed through a linear combination of the three component indices. ADVI-based vulnerability categorisation revealed that 51 blocks are with vulnerable to very highly vulnerable status. These blocks are located in the southern and western parts of the state, where groundwater quality is saline and water holding capacity of soils is less. The ADVI map has effectively captured the spatial pattern of agricultural drought vulnerability in the state. Districts with large number of vulnerable blocks showed considerably larger variability of de-trended crop yields. Correlation analysis reveals that crop condition variability, groundwater quality and soil factors are closely associated with ADVI. The vulnerability index is useful to prioritise the blocks for implementation of long-term drought management plans. There is scope for improving the methodology by adding/fine-tuning the indicators and by optimising the weights. © 2015, Springer International Publishing Switzerland.

Yadav M.,Haryana Space Applications Center | Prawasi R.,Haryana Space Applications Center | Jangra S.,Haryana Space Applications Center | Rana P.,Haryana Space Applications Center | And 5 more authors.
International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives | Year: 2014

The present paper describes the methodology and results of assessment of seasonal progress of rice stubble burning for 10 major rice growing districts of Haryana state in India. These 10 districts contribute about 84 per cent of total rice area of the state. As the rice fields are immediately required to be vacated for the sowing of next crop the farmers opt for mechanized harvesting and easy way out of burning the stubbles in the field. Such burning result in release of polluting gases and aerosols. Besides, the heating of the soil kills the useful micro-flora of the soil causing soil degradation. Multi-date AWiFS data from Resourcesat 1 and 2 satellites acquired between October 16, 2013 to November 26, 2013 were used for estimating paddy stubble burning areas at different intervals for the year 2013 crop growing season. In season collected ground truth data using hand held GPS along with field photographs were used to identify paddy stubble burning areas and other land features. Complete enumeration approach and Iterative Self-organizing Data Analysis Technique (ISODATA) unsupervised classifier was used for digital analysis. Normalized Difference Vegetation Index (NDVI) of each date was also used with other spectral bands of temporal images. To improve the classification accuracy the non-agricultural areas were masked out. The area was estimated by computing pixels under the classified image mask. Progress of paddy stubble burning was estimated at different intervals for the year 2013 using available cloud free multi-date IRS-P6 AWiFS data to identify the crucial period when stubbles burning takes place in major area so that preventive measures can be taken to curb the menace.

Yadav M.,Haryana Space Applications Center | Kaushik M.,Haryana Space Applications Center | Kumar M.,Haryana Space Applications Center | Kumar A.,Haryana Space Applications Center | Hooda R.S.,Haryana Space Applications Center
Annals of Agri Bio Research | Year: 2014

The significance of geoinformatics in groundwater exploration stems from the utility of satellite images in identifying and delineating various features like geomorphology, geology, lithology and hydrologic characteristics that may serve as direct or indirect indicators of the presence of ground water. This study establisheses the role of remote sensing, GIS and GPS for mapping and assessment of ground water prospect. The IRS-P6-LISS-III multi-spectral satellite data have been used for preparing ground water prospects map on 1 : 50,000 scale. The study area, Mahendergarh district, is located from 27°47' to 28°26' N latitude and 75°56' to 76°51' E longitude. The study area consists of 1939.13 sq. km area. Most area is covered by eolian plain. The major hydrogeomorphic units are hills (structural, denudational, residual), pediment, valley, dune complex, alluvial plain, eolian plain, flood plain, inselberg, sand dunes and lineament. After finalizing the spatial database and collecting the relevant information, a detailed analysis was carried out to demarcate the ground water prospects area. Overall, the ground water prospect of Mahendergarh district is very poor. Structural features found in this district are fault confirmed (minor), fracture/lineament confirmed, fracture/lineament inferred and trend line. The lineaments are trending in NE-SW direction. The structural feature map is highly useful for ground water prospects especially at intersection of lineaments.

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