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1.

001-es BibID:BIBFORM078729
Első szerző:Balázs Boglárka (geográfus)
Cím:Extracting water-related features using reflectance data and principal component analysis of Landsat images / Boglárka Balázs, Tibor Bíró, Gareth Dyke, Sudhir Kumar Singh, Szilárd Szabó
Dátum:2018
ISSN:0262-6667
Megjegyzések:This study aimed to map water features using a Landsat image rather than traditional land cover. We involved the original bands, spectral indices and principal components (PCs) of a principal component analysis (PCA) as input data, and performed random forest (RF) and support vector machine (SVM) classification with water, saturated soil and non-water categories. The aim was to compare the efficiency of the results based on various input data. Original bands provided 93% overall accuracy (OA) and bands 4?5?7 were the most informative in this analysis. Except for MNDWI (modified normalized differenced water index, with 98% OA), the performance of all water indices was between 60 and 70% (OA). The PCA-based approach conducted on the original bands resulted in the most accurate identification of all classes (with only 1% error in the case of water bodies). We therefore show that both water bodies and saturated soils can be identified successfully using this approach.
Tárgyszavak:Természettudományok Földtudományok idegen nyelvű folyóiratközlemény külföldi lapban
multivariate analysis
principal component analysis
remote sensing
Landsat
classification uncertainty analysis
spectral index
Megjelenés:Hydrological Sciences Journal. - 63 : 2 (2018), p. 269-284. -
További szerzők:Bíró Tibor Dyke, Gareth J. Singh, Sudhir Kumar (1970-) (geográfus) Szabó Szilárd (1974-) (geográfus)
Pályázati támogatás:TÁMOP 4.2.4.A/2-11-1-2012-0001
TÁMOP
SROP-4.2.2.B-15/1/KONV-2015-0001
egyéb
NKFIH 108755
egyéb
RH/751/2015
egyéb
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2.

001-es BibID:BIBFORM117608
035-os BibID:(WoS)001135261800001 (Scopus)85181237372
Első szerző:De Oliveira-Júnior, José Francisco
Cím:Impact of the El Niño on Fire Dynamics on the African Continent / José Francisco de Oliveira-Júnior, David Mendes, Szilard Szabo, Sudhir Kumar Singh, Punyawi Jamjareegulgarn, Kelvy Rosalvo Alencar Cardoso, Laszlo Bertalan, Marcos Vinicius da Silva, Alexandre Maniçoba da Rosa Ferraz Jardim, Jhon Lennon Bezerra da Silva, Gustavo Bastos Lyra, Marcel Carvalho Abreu, Washington Luiz Félix Correia Filho, Amaury de Sousa, Dimas de Barros Santiago, Iwldson Guilherme da Silva Santos, Vafaeva Khristina Maksudovna
Dátum:2024
ISSN:2509-9426 2509-9434
Megjegyzések:Several studies investigated the occurrence of fires in Africa with numerical modeling or applied statistics; however, only a few studies focused on the influence of El Nino on the fire risk using a coupled model. The study aimed to assess the influence of El Nino on wildfire dynamics in Africa using the SPEEDY-HYCOM model. El Nino events in the Eastern Tropical Pacific were classified via sea surface temperature (SST) anomaly based on a predefined climatology between 1961 and 2020 for the entire time series of SST, obtaining linear anomalies. The time series of the SST anomalies was created for the region between 5 degrees N and 5 degrees S and 110 degrees W and 170 degrees W. The events were defined in three consecutive 3-month periods as weak, moderate, and strong El Nino conditions. The Meteorological Fire Danger Index (MFDI) was applied to detect fire hazards. The MFDI simulated by the SPEEDY-HYCOM model for three El Nino categories across different lagged months revealed relevant distinctions among the categories. In the case of 'Weak', the maximum variability of fire risk observed at time lags (0, -3, -6, and -9 months) was primarily in Congo, Gabon, and Madagascar. The 'Moderate' pattern had similar characteristics to 'Weak' except for the lag-6 months and its occurrence in the equatorial zone of Africa. 'Strong' showed a remarkable impact in East Africa, resulting in high fire risk, regardless of time lags. Precipitation and evaporation simulations (SPEEDY-HYCOM) indicated that El Nino categories in Africa need particular attention in the central, southern, and southeastern regions emphasizing the significance of lag-0 and lag-6 (evaporation) as well as lag-0, lag-6, and lag-9 (precipitation). The SPEEDY-HYCOM coupled model in conjunction with the MFDI was efficient in assessing climate variabilities in Africa during El Nino events. This model allows the analysis and prediction of wildfire risks based on El Nino events, providing crucial information for wildfire management and prevention. Its simulations uncover significant variations in risks among different El Nino categories and lagged months, contributing to the understanding and mitigation of this environmental challenge.
Tárgyszavak:Természettudományok Földtudományok idegen nyelvű folyóiratközlemény külföldi lapban
folyóiratcikk
fire risk
coupled modelling
El Nino categories
SPEEDY-HYCOM model
Megjelenés:Earth Systems and Environment. - [Epub ahead of print] (2024). -
További szerzők:Mendes, David Szabó Szilárd (1974-) (geográfus) Singh, Sudhir Kumar (1970-) (geográfus) Jamjareegulgarn, Punyawi Cardoso, Kelvy Rosalvo Alencar Bertalan László (1989-) (geográfus) Da Silva, Marcos Vinicius Da Rosa Ferraz Jardim, Alexandre Manicoba Da Silva, Jhon Lennon Bezerra Lyra, Gustavo Bastos Abreu, Marcel Carvalho Filho, Washington Luiz Félix Correia De Sousa, Amaury De Barros Santiago, Dimas Da Silva Santos, Iwldson Guilherme Maksudovna, Vafaeva Khristina
Pályázati támogatás:K138079
Egyéb
RRF2.3.121202200008
Egyéb
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3.

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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4.

001-es BibID:BIBFORM116528
035-os BibID:(cikkazonosító)103507 (WoS)001135286500001 (Scopus)85179139332
Első szerző:Mahanta, Aiswarya Rani
Cím:Assessment of multi-source satellite products using hydrological modelling approach / Aiswarya Rani Mahanta, Kishan Singh Rawat, Nirmal Kumar, Szilard Szabo, Prashant K. Srivastava, Sudhir Kumar Singh
Dátum:2023
ISSN:1474-7065
Megjegyzések:Multi-source satellite products performance evaluation for varied geographical locations aids in quantification of hydrological variables and is useful in the strategy making and conservation of the hydrological resources available in a basin. The work was focused on assessing utility of multi-source satellite datasets to obtain the estimation of hydrologic variables and provide solution for areas that are poorly gauged. Assessment of the multisource-satellite products was performed for the poorly gauged river basin with the help of SWAT concerning the Palar River basin, India. We analysed time series at the monthly, seasonal, and annual scales to quantify surface runoff, water yield, ET, & PET at the calibration station and for the entire basin for the period 2003 to 2021. SWAT model estimated highest monthly water yield during November-December, with annual water yield being maximum (220 mm in 2010) and average (99.4 mm), which can be used to understand water resources for irrigation, drinking aspects, and net storage. Average monthly surface runoff patterns were similar for SWAT, TerraClimate, and FLDAS. The FLDAS and SWAT simulated surface runoff show a resemblance in pattern and magnitude for the monthly and annual time series of the average basin scenario. The monthly PET obtained from SWAT and ERA-5 show a similar pattern for the entire basin and at the calibration site. The ET derived from satellite observation has over-predicted the model output at both the calibration site and entire basin.
Tárgyszavak:Természettudományok Földtudományok idegen nyelvű folyóiratközlemény külföldi lapban
folyóiratcikk
FLDAS
SWAT
ERA-5
MODIS
MERRA-2
Water yield
Megjelenés:Physics And Chemistry Of The Earth. - 133 (2023), p. 1-18. -
További szerzők:Rawat, Kishan Singh Kumar, Nirmal Szabó Szilárd (1974-) (geográfus) Srivastava, Prashant K. Singh, Sudhir Kumar (1970-) (geográfus)
Pályázati támogatás:TKP2021-NKTA-32
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5.

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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6.

001-es BibID:BIBFORM084643
Első szerző:Rawat, Kishan Singh
Cím:Parameterizing the modified water cloud model to improve soil moisture data retrieval using vegetation models / Kishan Singh Rawat, Sudhir Kumar Singh, Ram L. Ray, Szilárd Szabó, Sanjeev Kumar
Dátum:2020
ISSN:2064-5031 2064-5147
Megjegyzések:The objective was to parameterize a modified water cloud model using crop coefficients (A and B). These crop coefficients were derived from Landsat-8 and Sentinel-2 data. Whereas the coefficients C and D are of soil parameters. The water cloud model was modified using crop coefficients by minimizing the RMSE between observed VV?0 and Sentinel-1 based simulated VV?0. The comparison with observed and simulated VV polarized ?0 showed low RMSE (0.81 dB) and strong R2 of 0.98 for NDVI-EVI combination. However, based on other possible combinations of vegetation indices VV?0 and simulated VV?0 do not show a good statistical agreement. It was observed that the errors in crop coefficients (A and B) are sensitive to errors in initial vegetation/canopy descriptor parameters.
Tárgyszavak:Természettudományok Földtudományok idegen nyelvű folyóiratközlemény hazai lapban
folyóiratcikk
NDVI
EVI
SAR
Sentinel
WCM
Megjelenés:Hungarian Geographical Bulletin. - 69 : 1 (2020), p. 17-26. -
További szerzők:Singh, Sudhir Kumar (1970-) (geográfus) Ray, Ram L. Szabó Szilárd (1974-) (geográfus) Kumar, Sanjeev
Pályázati támogatás:NKFIH-1150-6/2019
FIKP
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7.

001-es BibID:BIBFORM082565
035-os BibID:(cikkazonosító)100237
Első szerző:Shimrah, Tuisem
Cím:Quantitative assessment of landscape transformation using earth observation datasets in Shirui Hill of Manipur, India / Tuisem Shimrah, Kiranmay Sarma, Orsolya Gyöngyi Varga, Szilard Szabo, Sudhir Kumar Singh
Dátum:2019
ISSN:2352-9385
Megjegyzések:Shirui hill is situated at the north-eastern part of Manipur, India. This hill is not only the habitat of world famous endemic flower; Lilium mackliniae, but also home to many vulnerable and endangered floral and faunal species.. The aim of work was to assess the ecosystem diversity and landscape transformation Landsat satellite images of year 1988, 2001 and 2013 have been used to study the land use/land cover change and landscape fragmentation using FRAGSTATS. Several statistics such as principal component analysis (PCA) and spatial metrics are used to understand the results. The PCA was performed on the landscape metrics explained 93.0% of the total variance and justified three PCs; of these, both RMSR and AGFI fit very well (0.02 and 0.99, respectively), while PC1 accounted for 42% of the variance and was correlated with CA, TCA, NDCA and AREA_CV, PC2 explained 34% and was correlated with TE, SHAPE_MN, and PC3 explained 19% and was correlated with NP. The phyto-sociological study was carried out to assess the vegetation status. Participatory Rural Appraisal (PRA) method was adopted for socio-economic data collection. The finding of work suggests a rising pressure of human activities on the land and sizable portion of it have been converted into either shifting agriculture or wet paddy land.
Tárgyszavak:Természettudományok Földtudományok idegen nyelvű folyóiratközlemény külföldi lapban
folyóiratcikk
ecosystem diversity
fragmentation
Northeast India
Megjelenés:Remote Sensing Applications. - 15 (2019), p. 1-9. -
További szerzők:Sarma, Kiranmay Varga Orsolya Gyöngyi (1988-) (geográfus) Szabó Szilárd (1974-) (geográfus) Singh, Sudhir Kumar (1970-) (geográfus)
Pályázati támogatás:20428-3/2018/FEKUTSTRAT
FIKP
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8.

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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9.

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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10.

001-es BibID:BIBFORM083228
Első szerző:Szabó Gergely (geográfus)
Cím:Slope angle and aspect as influencing factors on the accuracy of the SRTM and the ASTER GDEM databases / Gergely Szabó, Sudhir Kumar Singh, Szilárd Szabó
Dátum:2015
ISSN:1474-7065
Megjegyzések:Presently, the application of digital elevation or surface models have increasing relevance in all areas of scientific research and in practical engineering applications. The ASTER GDEM and SRTM databases are the most widely used digital surface models, due to their free accessibility and global coverage. The SRTM model was produced using a radar-based technique and the ASTER GDEM was developed using optical stereo image-pairs. Therefore, as all models contain errors (i.e. differences stemming from real surface or vertical biases), errors in these models will also differ. Our aim was to examine these vertical biases and to calculate the rate of error variance. A TIN (Triangulated Irregular Network) model was used as a reference surface, derived from the contour lines of a large scale topographic map. Errors were evaluated with statistical and geoinformation techniques. We discovered significant differences between the surfaces. The mean difference between topographic elevations minus the SRTM-V2 is +2.6 +- 4 m, while the mean difference between topographic elevations minus the SRTM-V3 is +2.7 +- 2.5 m. With the GDEM, the mean difference was 2.7 +- 9.1 m. Furthermore, we found that in the case of SRTM, the differences were significant considering the aspects and the steepness of the slopes: southern and eastern directions and larger slope angles showed greater differences compared to the reference data. The GDEM V2 DEM had a larger error variance, but the error did not vary significantly with slope angle.
Tárgyszavak:Természettudományok Fizikai tudományok idegen nyelvű folyóiratközlemény külföldi lapban
folyóiratcikk
Digital surface models
Direction dependency
Steepness
Comparison
Hungary
Megjelenés:Physics and Chemistry of the Earth. - 83/84 (2015), p. 137-145. -
További szerzők:Singh, Sudhir Kumar (1970-) (geográfus) Szabó Szilárd (1974-) (geográfus)
Pályázati támogatás:TÁMOP 4.2.4. A/2-11-1-2012-0001
TÁMOP
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11.

001-es BibID:BIBFORM119489
035-os BibID:(cikkazonosító)111468
Első szerző:Szabó Szilárd (geográfus)
Cím:Classification Assessment Tool: A program to measure the uncertainty of classification models in terms of class-level metrics / Szilárd Szabó, Imre J. Holb, Vanda Éva Abriha-Molnár, Gábor Szatmári, Sudhir Kumar Singh, Dávid Abriha
Dátum:2024
ISSN:1568-4946
Megjegyzések:Accuracy assessments are important steps of classifications and get higher relevance with the soar of machine and deep learning techniques. We provided a method for quick model evaluations with several options: calculate the class level accuracy metrics for as many models and classes as needed; calculate model stability using random subsets of the testing data. The outputs are single calculations, summaries of the repetitions, and/or all accuracy results per repetitions. Using the application, we demonstrated the possibilities of the function and analyzed the accuracies of three experiments. We found that some popular metrics, the binary Overall Accuracy, Sensitivity, Precision, and Specificity, as well as ROC curve, can provide false results when the true negative cases dominate. F1-score, Intersection over Union and the Matthews correlation coefficient were reliable in all experiments. Medians and interquartile ranges (IQR) of the repeated sampling from the testing dataset showed that IQR were small when a model was almost perfect or completely unacceptable; thus, IQR reflected the model stability, reproducibility. We found that there were no general, statistically justified relationship with the median and IQR, furthermore, correlations of accuracy metrics varied by experiments, too. Accordingly, a multi-metric evaluation is suggested instead of a single metric.
Tárgyszavak:Természettudományok Földtudományok idegen nyelvű folyóiratközlemény külföldi lapban
folyóiratcikk
Model evaluation
Model stability
Testing
Repetitions
Python
Megjelenés:Applied Soft Computing. - 155 (2024), p. 1-15. -
További szerzők:Holb Imre (1973-) (agrármérnök) Molnár Vanda Éva (1994-) (környezetkutató) Szatmári Gábor Singh, Sudhir Kumar (1970-) (geográfus) Abriha Dávid (1995-) (geográfus)
Pályázati támogatás:K 138079
Egyéb
KKP 144068
OTKA
K 138503
OTKA
K 131478
OTKA
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12.

001-es BibID:BIBFORM076537
035-os BibID:(WoS)000458299900007 (Scopus)85059086542
Első szerző:Szabó Szilárd (geográfus)
Cím:NDVI dynamics as reflected in climatic variables: spatial and temporal trends : a case study of Hungary / Szilárd Szabó, László Elemér, Zoltán Kovács, Zoltán Püspöki, Ádám Kertész, Sudhir Kumar Singh, Boglárka Balázs
Dátum:2019
ISSN:1548-1603 1943-7226
Megjegyzések:Understanding climate change and revealing its future paths on a local level is a great challenge for the future. Beside the expanding sets of available climatic data, satellite images provide a valuable source of information. In our study we aimed to reveal whether satellite data are an appropriate way to identify global trends, given their shorter available time range. We used the CARPATCLIM (CC) database (1961-2010) and the MODIS NDVI images (2000-2016) and evaluated the time period covered by both (2000-2010). We performed a regression analysis between the NDVI and CC variables, and a time series analysis for the 1961-2008 and 2000-2008 periods at all data points. The results justified the belief that maximum temperature (TMAX), potential evapotranspiration and aridity all have a strong correlation with the NDVI; furthermore, the short period trend of TMAX can be described with a functional connection with its long period trend. Consequently, TMAX is an appropriate tool as an explanatory variable for NDVI spatial and temporal variance. Spatial pattern analysis revealed that with regression coefficients, macro-regions reflected topography (plains, hills and mountains), while in the case of time series regression slopes, it justified a decreasing trend from western areas (Transdanubia) to eastern ones (The Great Hungarian Plain). This is an important consideration for future agricultural and land use planning; i.e. that western areas have to allow for greater effects of climate change.
Tárgyszavak:Természettudományok Földtudományok idegen nyelvű folyóiratközlemény külföldi lapban
folyóiratcikk
climate change
trend
CARPATCLIM
principal component analysis
topographic variables
MODIS
Megjelenés:GIScience & Remote Sensing. - 56 : 4 (2019), p. 624-644. -
További szerzők:László Elemér (1987-) (meteorológus előrejelző szakiránnyal) Kovács Zoltán (1988-) (geográfus) Püspöki Zoltán (1972-) (geológus) Kertész Ádám (1948-) Singh, Sudhir Kumar (1970-) (geográfus) Balázs Boglárka (1985-) (geográfus)
Pályázati támogatás:TÁMOP-4.2.4.A/2-11-1-2012-0001
TÁMOP
NKFIH 108755
Egyéb
Internet cím:Szerző által megadott URL
DOI
Intézményi repozitóriumban (DEA) tárolt változat
Borító:
Rekordok letöltése1 2 
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