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Ιδρυματικό Αποθετήριο [SANDBOX]
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Πολυτεχνείο Κρήτης
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| URI | http://purl.tuc.gr/dl/dias/4AFECADE-8504-4392-9575-5F0EB8F73A9D | - |
| Αναγνωριστικό | https://doi.org/10.3390/resources8020070 | - |
| Αναγνωριστικό | https://www.mdpi.com/2079-9276/8/2/70 | - |
| Γλώσσα | en | - |
| Μέγεθος | 17 pages | en |
| Τίτλος | GIS and remote sensing aided information for soil moisture estimation: a comparative study of interpolation techniques | en |
| Δημιουργός | Srivastava Prashant K. | en |
| Δημιουργός | Pandey Prem Chandra | en |
| Δημιουργός | Petropoulos Georgios | en |
| Δημιουργός | Πετροπουλος Γεωργιος | el |
| Δημιουργός | Kourgialas Nektarios N. | en |
| Δημιουργός | Pandey Varsha H.R. | en |
| Δημιουργός | Singh Ujjwal | en |
| Εκδότης | MDPI | en |
| Περίληψη | Soil moisture represents a vital component of the ecosystem, sustaining life-supporting activities at micro and mega scales. It is a highly required parameter that may vary significantly both spatially and temporally. Due to this fact, its estimation is challenging and often hard to obtain especially over large, heterogeneous surfaces. This study aimed at comparing the performance of four widely used interpolation methods in estimating soil moisture using GPS-aided information and remote sensing. The DistanceWeighting (IDW), Spline, Ordinary Kriging models and Kriging with External Drift (KED) interpolation techniques were employed to estimate soil moisture using 82 soil moisture field-measured values. Of those measurements, data from 54 soil moisture locations were used for calibration and the remaining data for validation purposes. The study area selected was Varanasi City, India covering an area of 1535 km2. The soil moisture distribution results demonstrate the lowest RMSE (root mean square error, 8.69%) for KED, in comparison to the other approaches. For KED, the soil organic carbon information was incorporated as a secondary variable. The study results contribute towards efforts to overcome the issue of scarcity of soil moisture information at local and regional scales. It also provides an understandable method to generate and produce reliable spatial continuous datasets of this parameter, demonstrating the added value of geospatial analysis techniques for this purpose. | en |
| Τύπος | Peer-Reviewed Journal Publication | en |
| Τύπος | Δημοσίευση σε Περιοδικό με Κριτές | el |
| Άδεια Χρήσης | http://creativecommons.org/licenses/by/4.0/ | en |
| Ημερομηνία | 2020-11-03 | - |
| Ημερομηνία Δημοσίευσης | 2019 | - |
| Θεματική Κατηγορία | Geographical information systems | en |
| Θεματική Κατηγορία | Geoinformation | en |
| Θεματική Κατηγορία | Mapping | en |
| Θεματική Κατηγορία | Monitoring soil moisture | en |
| Θεματική Κατηγορία | Soil water management | en |
| Θεματική Κατηγορία | Spatial interpolation | en |
| Βιβλιογραφική Αναφορά | P.K. Srivastava, P.C. Pandey, G.P. Petropoulos, N.N. Kourgialas, V. Pandey and U. Singh, "GIS and remote sensing aided information for soil moisture estimation: a comparative study of interpolation techniques," Resources, vol. 8, no. 2, Apr. 2019. doi: 10.3390/resources8020070 | en |
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