Use of remote sensing techniques for agricultural land use survey,classification and planning     

B. M. Singh  M. L. Manchanda  H. S. Iyer  L. M. Pande  Jitendra Prasad  B. R. M. Rao 《Journal of the Indian Society of Remote Sensing》1983,11(3):1-13

A critical appraisal of the need and use of remote sensing techniques for land use mapping with particular reference to Indian conditions have been made. Land use classification system based on physiography, utility, management and identification have been suggested using remote sensing techniques at different levels of mapping.  相似文献   

Multi level land use surveys using remote sensing techniques     

M. L. Manchanda  H. S. Iyer  B. M. Singh  Jitendra Prasad 《Journal of the Indian Society of Remote Sensing》1983,11(3):67-74

The use of Landsat imagery at 1:1 M and 1:250,000 and aerial photos on 1:65,000 and 1:20,000 scale have been used to study landuse. It has been possible to achieve identification using Landsat imagery up to utility level ( level 1 and II ) and with the aerial photographs further subdivisions of utility into management and identification (level III and IV) .  相似文献   

On the origin of the low energy cosmic rays from stellar sources     

S Biswas  N Durgaprasad  Sushma S Trivedi 《Journal of Earth System Science》1981,90(3):337-344

The model of stellar origin of the anomalous component in the low energy cosmic rays for He to Fe ions observed in space vehicles is studied in the light of recent results. The model of heliospheric origin by Fisket al which has several attractive features cannot explain the long-term variations of intensity observed during 1974 to 1978 as pointed out by Nagashima and Morishita. The stellar origin model of Durgaprasad and Biswas, on the other hand, can easily account for the sudden appearance of the anomalous component in 1972 and its large decrease in intensity in 1978 on the basis of polarity reversal of the solar magnetic field as discussed by Nagashima and Morishita (1980). In this work, we show that in the stellar model energetic ions of He, C, N, O, etc. could originate in O-type stars which manifest very strong stellar wind with mass loss rate of 3·10^?6 M_⊙ per year. These have terminal velocities of about 1200 to 4000 km/sec and are typically a few times their escape velocity. These velocities correspond to ion energies of 10 to 100 keV/amu. These ions are in partly ionised state and are accelerated in the interstellar shock fronts to about 1 to 50 MeV/amu and thus account for the observed anomalous component of low energy cosmic rays.  相似文献   

Performance of large area x-ray proportional counters in a balloon experiment     

J. Roy  P. C. Agrawal  D. K. Dedhia  R. K. Manchanda  P. B. Shah  V. R. Chitnis  V. M. Gujar  J. V. Parmar  D. M. Pawar  V. B. Kurhade 《Experimental Astronomy》2016,42(2):249-270

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X-ray observation of two gamma-ray source fields with the Einstein Observatory     

K. P. Singh  K. M. V. Apparao  R. K. Manchanda 《Astrophysics and Space Science》1982,82(2):477-479

Two gamma ray source fields CG 189+1 and CG 075+00, centered on the corresponding UHURU Point X-ray source positions, were observed with the IPC onboard Einstein Observatory. An unidentified weak X-ray source is detected from the direction of CG 189+1 only.  相似文献   

Holocene climate forcings and lacustrine regime shifts in the Indian summer monsoon realm     

Sushma Prasad  Norbert Marwan  Deniz Eroglu  Bedartha Goswami  Praveen K. Mishra  Birgit Gaye  A. Anoop  N. Basavaiah  Martina Stebich  Arshid Jehangir 《地球表面变化过程与地形》2020,45(15):3842-3853

Extreme climate events have been identified both in meteorological and long-term proxy records from the Indian summer monsoon (ISM) realm. However, the potential of palaeoclimate data for understanding mechanisms triggering climate extremes over long time scales has not been fully exploited. A distinction between proxies indicating climate change, environment, and ecosystem shift is crucial for enabling a comparison with forcing mechanisms (e.g. El-Niño Southern Oscillation). In this study we decouple these factors using data analysis techniques [multiplex recurrence network (MRN) and principal component analyses (PCA)] on multiproxy data from two lakes located in different climate regions – Lonar Lake (ISM dominated) and the high-altitude Tso Moriri Lake (ISM and westerlies influenced). Our results indicate that (i) MRN analysis, an indicator of changing environmental conditions, is associated with droughts in regions with a single climate driver but provides ambiguous results in regions with multiple climate/environmental drivers; (ii) the lacustrine ecosystem was ‘less sensitive’ to forcings during the early Holocene wetter periods; (iii) archives in climate zones with a single climate driver were most sensitive to regime shifts; (iv) data analyses are successful in identifying the timing of onset of climate change, and distinguishing between extrinsic and intrinsic (lacustrine) regime shifts by comparison with forcing mechanisms. Our results enable development of conceptual models to explain links between forcings and regional climate change that can be tested in climate models to provide an improved understanding of the ISM dynamics and their impact on ecosystems. © 2020 John Wiley & Sons, Ltd.  相似文献   

Crop Residue Discrimination Using Ground-Based Hyperspectral Data   总被引：1，自引：0，他引：1  

Rimjhim Bhatnagar Singh  S. S. Ray  S. K. Bal  B. S. Sekhon  G. S. Gill  Sushma Panigrahy 《Journal of the Indian Society of Remote Sensing》2013,41(2):301-308

Crop residue has become an increasingly important factor in agriculture management. It assists in the reduction of soil erosion and is an important source of soil organic carbon (soil carbon sequestration). In recent past, remote sensing, especially narrowband, data have been explored for crop residue assessment. In this context, a study was carried out to identify different narrow-bands and evaluate the performance of SWIR region based spectral indices for crop residue discrimination. Ground based hyperspectral data collected for wheat crop residue was analyzed using Stepwise Discriminant Analysis (SDA) technique to select significant bands for discrimination. Out of the seven best bands selected to discriminate between matured crop, straw heap, combine-harvested field with stubbles and soil, four bands were from SWIR (1980, 2030, 2200, 2440 nm) region. Six spectral indices were computed, namely CAI, LCA, SINDRI, NDSVI, NDI5 and hSINDRI for crop residue discrimination. LCA and CAI showed to be best (F?>?115) in discriminating above classes, while LCA and SINDRI were best (F?>?100) among all indices in discriminating crop residue under different harvesting methods. Comparison of different spectral resolution (from 1 nm to 150 nm) showed that for crop residue discrimination a resolution of 100 nm at 2100–2300 m region would be sufficient to discriminate crop residue from other co-existing classes.  相似文献   

Discrimination of Spectrally-Close Crops Using Ground-Based Hyperspectral Data     

K. R. Manjunath  Shibendu Shankar Ray  Sushma Panigrahy 《Journal of the Indian Society of Remote Sensing》2011,39(4):599-602

Hyperspectral remote sensing, because of its large number of narrow bands, has shown possibility of discriminating the crops. Current study was carried out to select the optimum bands for discrimination among pulses, cole crops and ornamental plants using the ground-based Hyperspectral data in Patha village, Lalitpur district, Uttar Pradesh state and Kolkata, West Bengal state. The field observations of reflectance were taken using a 512-channel spectroradiometer with a range of 325–1075 nm. The stepwise discriminant analysis was carried out and separability measures, such as Wilks’ lambda and F-Value were used as criteria for identifying the narrow bands. The analysis showed that, the best four bands for pulse crop discrimination lie mostly in NIR and early MIR regions i.e. 750, 800, 940 and 960 nm. Within cole crops discrimination is primarily determined by the green, red and NIR bands of 550, 690, 740, 770 and 980 nm. The separability study showed the bands 420,470,480,570,730,740, 940, 950, 970, 1030 nm are useful for discriminating flowers.  相似文献   

A Spatial Database of Cropping System and its Characteristics to Aid Climate Change Impact Assessment Studies     

Sushma Panigrahy  Shibendu Shankar Ray  K. R. Manjunath  P. S. Pandey  S. K. Sharma  Anil Sood  Manoj Yadav  P. C. Gupta  N. Kundu  Jai Singh Parihar 《Journal of the Indian Society of Remote Sensing》2011,39(3):355-364

Cropping system study is not only useful to understand the overall sustainability of agricultural system, but also it helps in generating many important parameters which 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 spatial resolution multi-date remote sensing data (SPOT VGT NDVI) and ground survey. The remote sensing data was used to compute three cropping system performance indices (Multiple Cropping Index, Area Diversity Index and Cultivated Land Utilization Index). 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 were 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 IGP, followed by Rice-Fallow-Fallow and Maize-Wheat. Other major 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.  相似文献   

Evaluation of classifiers for processing Hyperion (EO-1) data of tropical vegetation     

Dhaval Vyas  N.S.R. Krishnayya  K.R. Manjunath  S.S. Ray  Sushma Panigrahy 《International Journal of Applied Earth Observation and Geoinformation》2011

There is an urgent necessity to monitor changes in the natural surface features of earth. Compared to broadband multispectral data, hyperspectral data provides a better option with high spectral resolution. Classification of vegetation with the use of hyperspectral remote sensing generates a classical problem of high dimensional inputs. Complexity gets compounded as we move from airborne hyperspectral to Spaceborne technology. It is unclear how different classification algorithms will perform on a complex scene of tropical forests collected by spaceborne hyperspectral sensor. The present study was carried out to evaluate the performance of three different classifiers (Artificial Neural Network, Spectral Angle Mapper, Support Vector Machine) over highly diverse tropical forest vegetation utilizing hyperspectral (EO-1) data. Appropriate band selection was done by Stepwise Discriminant Analysis. The Stepwise Discriminant Analysis resulted in identifying 22 best bands to discriminate the eight identified tropical vegetation classes. Maximum numbers of bands came from SWIR region. ANN classifier gave highest OAA values of 81% with the help of 22 selected bands from SDA. The image classified with the help SVM showed OAA of 71%, whereas the SAM showed the lowest OAA of 66%. All the three classifiers were also tested to check their efficiency in classifying spectra coming from 165 processed bands. SVM showed highest OAA of 80%. Classified subset images coming from ANN (from 22 bands) and SVM (from 165 bands) are quite similar in showing the distribution of eight vegetation classes. Both the images appeared close to the actual distribution of vegetation seen in the study area. OAA levels obtained in this study by ANN and SVM classifiers identify the suitability of these classifiers for tropical vegetation discrimination.  相似文献