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1.

001-es BibID:BIBFORM078725
Első szerző:Lamine, Salim
Cím:Quantifying land use/land cover spatio-temporal landscape pattern dynamics from Hyperion using SVMs classifier and FRAGSTATS / Salim Lamine, George P. Petropoulos, Sudhir Kumar Singh, Szilárd Szabó, Nour El Islam Bachari, Prashant K. Srivastava, Swati Suman
Dátum:2018
ISSN:1010-6049 1752-0762
Megjegyzések:This study aims to quantify the landscape spatio-temporal dynamics including Land Use/Land Cover (LULC) changes occurred in a typical Mediterranean ecosystem of high ecological and cultural significance in central Greece covering a period of 9 years (2001-2009). Herein, we examined the synergistic operation among Hyperion hyperspectral satellite imagery with Support Vector Machines, the FRAGSTATS® landscape spatial analysis programme and Principal Component Analysis (PCA) for this purpose. The change analysis showed that notable changes reported in the experimental region during the studied period, particularly for certain LULC classes. The analysis of accuracy indices suggested that all the three classification techniques are performing satisfactorily with overall accuracy of 86.62, 91.67 and 89.26% in years 2001, 2004 and 2009, respectively. Results evidenced the requirement for taking measures to conserve this forest-dominated natural ecosystem from human-induced pressures and/or natural hazards occurred in the area. To our knowledge, this is the first study of its kind, demonstrating the Hyperion capability in quantifying LULC changes with landscape metrics using FRAGSTATS® programme and PCA for understanding the land surface fragmentation characteristics and their changes. The suggested approach is robust and flexible enough to be expanded further to other regions. Findings of this research can be of special importance in the context of the launch of spaceborne hyperspectral sensors that are already planned to be placed in orbit as the NASA's HyspIRI sensor and EnMAP.
Tárgyszavak:Természettudományok Földtudományok idegen nyelvű folyóiratközlemény külföldi lapban
Hyperspectral remote sensing
Support vector machines
FraGStatS
landscape fragmentation
Principal component analysis
Megjelenés:Geocarto International. - 33 : 8 (2018), p. 862-878. -
További szerzők:Petropoulos, George P. Singh, Sudhir Kumar (1970-) (geográfus) Szabó Szilárd (1974-) (geográfus) Bachari, Nour El Islam Srivastava, Prashant K. Suman, Swati
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2.

001-es BibID:BIBFORM115591
035-os BibID:(cikkazonosító)2252709 (WoS)001084667700001 (Scopus)85174256643
Első szerző:Lulla, Kamlesh
Cím:Recognizing our editorial colleagues M Duane Nellis and Prashant Srivastava / Kamlesh Lulla, Brad Rundquist, Szilárd Szabó
Dátum:2023
ISSN:1010-6049 1752-0762
Tárgyszavak:Természettudományok Földtudományok szerkesztőségi anyag
folyóiratcikk
Megjelenés:Geocarto International. - 38 : 1 (2023), p. 1-2. -
További szerzők:Rundquist, Bradley Szabó Szilárd (1974-) (geográfus)
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3.

001-es BibID:BIBFORM097533
Első szerző:Lulla, Kamlesh
Cím:Mission to Earth : LANDSAT 9 will continue to view the world / Kamlesh Lulla, M. Duane Nellis, Bradley Rundquist, Prashant Srivastava, Szilard Szabo
Dátum:2021
ISSN:1010-6049 1752-0762
Tárgyszavak:Természettudományok Földtudományok idegen nyelvű folyóiratközlemény külföldi lapban
folyóiratcikk
Megjelenés:Geocarto International. - 36 : 20 (2021), p. 2261-2263. -
További szerzők:Nellis, M. Duane Rundquist, Bradley Srivastava, Prashant K. Szabó Szilárd (1974-) (geográfus)
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4.

001-es BibID:BIBFORM086927
Első szerző:Rawat, Kishan Singh
Cím:Parameterization of the modified water cloud model (MWCM) using normalized difference vegetation index (NDVI) for winter wheat crop : a case study from Punjab, India / Kishan Singh Rawat, Sudhir Kumar Singh, Ram L. Ray, Szilard Szabo
Dátum:2020
ISSN:1010-6049 1752-0762
Megjegyzések:Soil moisture is essential for water resources management, yet accurate information of soil moisture has been a challenge. The major goal was to parametrize the Modified Water Cloud Model (MWCM). The Sentinel-1A data of winter wheat crop was collected for two weeks. Concurrently, in-situ soil moisture data was collected using Time Domain Reflectometer (TDR). A parametric scheme was used for the retrieval of the VV polarization of Sentinel-1A. The effect of NDVI as a vegetation descriptors (V1 and V2) on total VV backscatter (r0) was analyzed. The calibration showed NDVI has the potential to influence Water Cloud Model (WCM) and vegetation descriptors; hence it is recommended to calibrate the MWCM. The coefficient of determination (R2 ? 0.83) showed a good agreement between observed and estimated soil moisture. Therefore, this approach help improve soil moisture prediction, and can be applied to determine soil moisture more accurately for winter crops, grasses, and pasture lands.
Tárgyszavak:Természettudományok Földtudományok idegen nyelvű folyóiratközlemény külföldi lapban
folyóiratcikk
Optimization
water cloud model
backscattering coefficients
soil moisture
ndvi
Megjelenés:Geocarto International. - [Epub ahead of print] (2020), p. 1-15. -
További szerzők:Singh, Sudhir Kumar (1970-) (geográfus) Ray, Ram L. Szabó Szilárd (1974-) (geográfus)
Pályázati támogatás:NKFIH-1150-6/2019
FIKP
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5.

001-es BibID:BIBFORM078726
Első szerző:Singh, Sudhir Kumar (geográfus)
Cím:Modelling of land use land cover change using earth observation data-sets of Tons River Basin, Madhya Pradesh, India / Sudhir Kumar Singh, Prosper Basommi Laari, Sk. Mustak, Prashant K. Srivastava, Szilárd Szabó
Dátum:2018
ISSN:1010-6049 1752-0762
Megjegyzések:An integrated Markov Chain and Cellular Automata modelling (CA MARKOV), multicriteria evaluation techniques have been applied to produce transition probability. The unsupervised method was employed to classify the satellite images of year 1985, 1995, 2005 and 2015 to meet the magnitude of LULC change. Results showing the spatial pattern of the sub-basin is largely influenced by the biophysical and socio-economic drivers leading to growth of agricultural lands and built-up area in the basin. Simulated plausible future LULC changes for 2025 which is based on a CA MARKOV that integrates Markovian transition probabilities computed from satellite-derived LULC maps and a CA contiguity spatial filter (5 x 5). Further, the fragmentation analysis was performed to check the fragmentation scenario in the year 2025. The result for year 2025 with reasonably good accuracy will be useful to the planners, policy- and decision-makers.
Tárgyszavak:Természettudományok Földtudományok idegen nyelvű folyóiratközlemény külföldi lapban
earth observation
LULC change
cellular automata
Markov chain analysis
India
Megjelenés:Geocarto International. - 33 : 11 (2018), p. 1202-1222. -
További szerzők:Laari, Prosper Basommi Mustak, Sk. Srivastava, Prashant K. Szabó Szilárd (1974-) (geográfus)
Pályázati támogatás:RH/751/2015
egyéb
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6.

001-es BibID:BIBFORM068022
Első szerző:Singh, Sudhir Kumar (geográfus)
Cím:Landscape transform and spatial metrics for mapping spatiotemporal land cover dynamics using Earth Observation data-sets / Sudhir Kumar Singh, Prashant K. Srivastava, Szilárd Szabó, George P. Petropoulos, Manika Gupta, Tanvir Islam
Dátum:2017
ISSN:1010-6049 1752-0762
Megjegyzések:Analysis of Earth observation (EO) data, often combined with geographical information systems (GIS), allows monitoring of land cover dynamics over different ecosystems, including protected or conservation sites. The aim of this study is to use contemporary technologies such as EO and GIS in synergy with fragmentation analysis, to quantify the changes in the landscape of the Rajaji National Park (RNP) during the period of 19 years (1990?2009). Several statistics such as principal component analysis (PCA) and spatial metrics are used to understand the results. PCA analysis has produced two principal components (PC) and explained 84.1% of the total variance, first component (PC1) accounted for the 57.8% of the total variance while the second component (PC2) has accounted for the 26.3% of the total variance calculated from the core area metrics, distance metrics and shape metrics. Our results suggested that notable changes happened in the RNP landscape, evidencing the requirement of taking appropriate measures to conserve this natural ecosystem.
Tárgyszavak:Természettudományok Földtudományok idegen nyelvű folyóiratközlemény külföldi lapban
geographic information system
protected ecosystem
remote sensing
landscape pattern
fragmentation
ecological metrics
Megjelenés:Geocarto International 32 : 2 (2017), p. 113-127. -
További szerzők:Srivastava, Prashant K. Szabó Szilárd (1974-) (geográfus) Petropoulos, George P. Gupta, Manika Islam, Tanvir
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7.

001-es BibID:BIBFORM078724
Első szerző:Yadav, Sandeep Kumar
Cím:Prioritisation of sub-watersheds based on earth observation data of agricultural dominated northern river basin of India / Sandeep Kumar Yadav, Alok Dubey, Szabo Szilard, Sudhir Kumar Singh
Dátum:2018
ISSN:1010-6049 1752-0762
Megjegyzések:The Upper Tons River Basin of North India has been selected for prioritisation of sub-watersheds (SW) based on morphometric parameters with respect to groundwater derived from topographic sheets and CARTOSAT data. There are 10 SW have been delineated in the region, high stream frequency (Fs) values of SW (1-5) and SW-9 indicated the occurrence of steep slopes, less permeable rocks, greater runoff, less infiltration possibility. Further, these regions have been predicted as poor groundwater potentialities. SW-2 has been identified as poorest groundwater potential zone, whereas SW-4 and SW (6-8) regions possess good permeable bed rocks. The Drainage density (Dd) map demonstrated that the middle south-west region possesses higher Dd whereas northeastern regions contain lower Dd. Further, the areal parameters indicate elongated shape of the basin, hilly region has moderate to steeper ground slope. The outcomes of work have potential to manage groundwater and to ameliorate the flash flood and droughts.
Tárgyszavak:Természettudományok Földtudományok idegen nyelvű folyóiratközlemény külföldi lapban
Upper tons Basin
morphometric analysis
prioritisation
DEM
sub-watershed
Megjelenés:Geocarto International. - 33 : 4 (2018), p. 338-356. -
További szerzők:Dubey, Alok Szabó Szilárd (1974-) (geográfus) Singh, Sudhir Kumar (1970-) (geográfus)
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