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Ubiquitous GIS-Based Forest Fire Susceptibility Mapping Using Artificial Intelligence Methods

Seyed Vahid Razavi-Termeh, Abolghasem Sadeghi-Niaraki, Soo-Mi Choi
2020 Remote Sensing  
SA) algorithms (ANFIS-GA-SA) and an ensemble of radial basis function (RBF) with an imperialist competitive algorithm (ICA) (RBF-ICA) model in Chaharmahal and Bakhtiari Province, Iran.  ...  After the FFSM was prepared, the maps were designed and implemented for web GIS and mobile application.  ...  SA Algorithm The SA algorithm is an optimization algorithm that is easy and efficient to use for solving optimization issues.  ... 
doi:10.3390/rs12101689 fatcat:zbwmvfb5ffezvdrrkvx3opx5mi

Prediction and Uncertainty Capabilities of Quantile Regression Forests in Estimating Spatial Distribution of Soil Organic Matter

Melpomeni Nikou, Panagiotis Tziachris
2022 ISPRS International Journal of Geo-Information  
One of the core tasks in digital soil mapping (DSM) studies is the estimation of the spatial distribution of different soil variables.  ...  Moreover, its uncertainty capabilities as presented in the uncertainty maps, shows that it can also provide a good estimation of the uncertainty with distinct representation of the local variation in specific  ...  Acknowledgments: The authors are grateful to the staff of the Soil and Water Resources Institute of Hellenic Agricultural Organization-Demeter in Thessaloniki, Greece for their support in this study (I  ... 
doi:10.3390/ijgi11020130 fatcat:jxv64etj2zbvrabqutaa45zmhq

Developing Statewide Optimal RWIS Density Guidelines Using Space-Time Semivariogram Models

Simita Biswas, Tae J. Kwon
2020 Journal of Sensors  
The optimal RWIS density for different topographic and weather severity regions was then determined via one of the most successful combinatorial optimization techniques—particle swarm optimization.  ...  The findings of this study revealed a strong dependency of optimal RWIS density on varying environmental characteristics of the region under investigation.  ...  The authors would also like to thank research assistants, Lian Gu and Mingjian Wu, of the transportation group at the University of Alberta for their help in data processing and analysis.  ... 
doi:10.1155/2020/1208692 fatcat:6gcgmrtmxzfeddnxxeyziw7owe

Measuring Hyperscale Topographic Anisotropy as a Continuous Landscape Property

Daniel Newman, John Lindsay, Jaclyn Cockburn
2018 Geosciences  
Therefore, we present a method for measuring topographic anisotropy in the landscape that has the computational efficiency required for hyperscale analysis by using the integral image filtering approach  ...  Recent research has made progress in measuring topographic anisotropy as a distributed field in natural landscapes.  ...  Leveraging more processing power, while offering a powerful option to reduce execution time, is not as practical or scalable compared to algorithmic efficiency.  ... 
doi:10.3390/geosciences8080278 fatcat:4j467mdlqbe5dgmvw4b56jiaxq

Evaluation of the evolving stress field of the Yellowstone volcanic plateau, 1988 to 2010, from earthquake first-motion inversions

E. Russo, G.P. Waite, A. Tibaldi
2017 Tectonophysics  
for areas 9 and 10, outlined in red in the map.  ...  The final step is to find the data misfit for the preferred mechanism.  ... 
doi:10.1016/j.tecto.2017.02.009 fatcat:3nxyxihcfzbodj73xvx33qomni

Remote Sensing Based Binary Classification of Maize. Dealing with Residual Autocorrelation in Sparse Sample Situations

Mario Gilcher, Thorsten Ruf, Christoph Emmerling, Thomas Udelhoven
2019 Remote Sensing  
The focus of this study is to apply established classification algorithms to estimate maize abundance for each independent pixel, while at the same time accounting for their spatial relationship.  ...  to every site, and hard to generalize for larger administrative aggregates.  ...  Acknowledgments: We kindly thank Petra Seiffert, Planet Labs Germany and the German Aerospace Center for providing RapidEye satellite images.  ... 
doi:10.3390/rs11182172 fatcat:qggky4qqsfgw7geg6h3nwfjlf4

Prediction of Soil Organic Carbon based on Landsat 8 Monthly NDVI Data for the Jianghan Plain in Hubei Province, China

Yangchengsi Zhang, Long Guo, Yiyun Chen, Tiezhu Shi, Mei Luo, QingLan Ju, Haitao Zhang, Shanqin Wang
2019 Remote Sensing  
Digital soil mapping plays an important role in efficiently obtaining the spatial distribution of SOC, which contributes to precision agriculture.  ...  This finding indicated that the time series characteristics of NDVI were conducive for predicting SOC in plains.  ...  Digital soil mapping plays an important role in efficiently obtaining the spatial distribution of SOC, which contributes to precision agriculture.  ... 
doi:10.3390/rs11141683 fatcat:lct7m7klffhyvkajhdbijnaj64

Geostatistical approach for identifying scale-specific correlations between soil thickness and topographic attributes

Hocine Bourennane, Sébastien Salvador-Blanes, Alain Couturier, Caroline Chartin, Catherine Pasquier, Florent Hinschberger, Jean-Jacques Macaire, Joël Daroussin
2014 Geomorphology  
The effects of topographic attribute data sources as explanatory variables for modeling ST are less significant than the effects of the two models for mapping.  ...  extrapolation for mapping beyond the area where the model was established.  ...  Wide use of digital elevation models (DEMs) for modeling environmental processes has resulted in several research papers regarding the following topics: (1) digital elevation data sources, (2) DEM accuracy  ... 
doi:10.1016/j.geomorph.2014.05.026 fatcat:5xgg3324bvbdjoziwniad66plq

Spatial modeling of soil salinity using kriging interpolation techniques: A study case in the Great Hungarian Plain

Ghada Sahbeni, Balázs Székely
2022 Eurasian Journal of Soil Science  
The world's current task is to ensure food security for an ever-growing population of 7.674 billion in 2019.  ...  The study demonstrated co-kriging efficiency by reducing the mean squared error (MSE) of ordinary kriging (OK) from 0.8 g/kg and 0.85 g/kg for LOOCV and the holdout cross-validation to 0.3 g/kg.  ...  Pásztor for his valuable support in acquiring field data from the Research Institute of Soil Science and Agricultural Chemistry (RISSAC).  ... 
doi:10.18393/ejss.1013432 doaj:2b29acf1cf144eae8862576727d9cd0d fatcat:qlf32u7xnva5fg6anqzgf4xvha

Geostatistical study of precipitation series in Austria: time and space

F. Holawe, R. Dutter
1999 Journal of Hydrology  
From the database of each station, we first calculated the most essential properties of the variogram in its general form, namely sill, range and nugget effect.  ...  For this study, the daily data from more than 400 precipitation stations in Austria recorded over a period of 20 years was used.  ...  In both directions, we find approximately the same sill, nugget effect and range. This means that the variable range is not really influenced by a distinct topographical structure.  ... 
doi:10.1016/s0022-1694(99)00046-3 fatcat:5t7ij6uqe5apzmdev4f3l7miuy

A Comparative Assessment of Geostatistical, Machine Learning, and Hybrid Approaches for Mapping Topsoil Organic Carbon Content

Lin Chen, Chunying Ren, Lin Li, Yeqiao Wang, Bai Zhang, Zongming Wang, Linfeng Li
2019 ISPRS International Journal of Geo-Information  
This study is aimed at comparing six typical methods in three types of DSM techniques for SOC mapping in an area surrounding Changchun in Northeast China.  ...  Environmental variables, including soil properties, climatic, topographic, and remote sensing data, were used for modeling.  ...  The authors are grateful to the colleagues who participated in the field surveys and data collection.  ... 
doi:10.3390/ijgi8040174 fatcat:6mly5oe44vhwhcgpbzaoyjjg4a

Computing water flow through complex landscapes – Part 2: Finding hierarchies in depressions and morphological segmentations

Richard Barnes, Kerry L. Callaghan, Andrew D. Wickert
2020 Earth Surface Dynamics  
Depressions – inwardly draining regions of digital elevation models – present difficulties for terrain analysis and hydrological modeling.  ...  Here we provide a new data structure – the depression hierarchy – that captures the full topologic and topographic complexity of depressions in a region.  ...  Introduction Depressions (see Lindsay, 2015 , for a typology) are inwarddraining regions of a digital elevation model (DEM) that lack an outlet to an ocean, map edge, or some other designated boundary  ... 
doi:10.5194/esurf-8-431-2020 fatcat:5itbj42onnd6xawmf4jlzsi4sq

Decision Tree and Texture Analysis for Mapping Debris-Covered Glaciers in the Kangchenjunga Area, Eastern Himalaya

Adina Racoviteanu, Mark W. Williams
2012 Remote Sensing  
) for mapping debris cover in the eastern Himalaya using two independent approaches: (a) a decision tree algorithm, and (b) texture analysis.  ...  Overall, for ten glacier tongues in the Kangchenjunga area, there was an area difference of 16.2 km 2 (25%) between the ASTER and the QB areas, with mapping errors mainly due to clouds and shadows.  ...  Decision Tree Results The decision tree algorithm based on multi-spectral and topographic variables, and the criteria and thresholds used, are summarized in Table 2 and Figure 7 .  ... 
doi:10.3390/rs4103078 fatcat:pc5jhb2pdfby7ok74rwygbjwa4

Mapping Spatial Variations of Structure and Function Parameters for Forest Condition Assessment of the Changbai Mountain National Nature Reserve

Chen, Ren, Zhang, Wang, Wang
2019 Remote Sensing  
This study mapped structure and function parameters for forest condition assessment in the Changbai Mountain National Nature Reserve (CMNNR).  ...  It is crucial to develop modeling approaches in mapping forest assessment parameters from satellite remote sensing.  ...  We thank the National Earth System Science Data Center ( for providing geographic information data. This study is  ... 
doi:10.3390/rs11243004 fatcat:vksfufrafja3vmg2pov6ckqsf4

Spatial distribution of soil organic carbon stock in Moso bamboo forests in subtropical China

Xiaolu Tang, Mingpeng Xia, César Pérez-Cruzado, Fengying Guan, Shaohui Fan
2017 Scientific Reports  
In addition, site specific maps of SOC stocks for scientific management of Moso bamboo forests are still lacking in our study area.  ...  of SOC stocks; and (4) examining the accuracy of spatial maps.  ...  This finding may be attributed to the sampling design and the nature of the algorithm of OK (see the discussion section for more details). Spatial prediction of SOC stock.  ... 
doi:10.1038/srep42640 pmid:28195207 pmcid:PMC5307386 fatcat:itt233rsvnh7jlawp3ybmsvicy
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