Towards the Assessment of Soil-Erosion-Related C-Factor on European Scale Using Google Earth Engine and Sentinel-2 Images
Soil erosion is a constant environmental threat for the entirety of Europe. Numerous studies have been published during the last years concerning assessing soil erosion utilising Remote Sensing (RS) and Geographic Information Systems (GIS). Such studies commonly employ empirical erosion models to es...
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| Language: | English |
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MDPI AG
2021-12-01
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| Series: | Remote Sensing |
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| Online Access: | https://www.mdpi.com/2072-4292/13/24/5019 |
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| author | Dimitrios D. Alexakis Stelios Manoudakis Athos Agapiou Christos Polykretis |
| author_facet | Dimitrios D. Alexakis Stelios Manoudakis Athos Agapiou Christos Polykretis |
| author_sort | Dimitrios D. Alexakis |
| collection | DOAJ |
| description | Soil erosion is a constant environmental threat for the entirety of Europe. Numerous studies have been published during the last years concerning assessing soil erosion utilising Remote Sensing (RS) and Geographic Information Systems (GIS). Such studies commonly employ empirical erosion models to estimate soil loss on various spatial scales. In this context, empirical models have been highlighted as major approaches to estimate soil loss on various spatial scales. Most of these models analyse environmental factors representing soil-erosion-influencing conditions such as the climate, topography, soil regime, and surface vegetation coverage. In this study, the Google Earth Engine (GEE) cloud computing platform and Sentinel-2 satellite imagery data have been combined to assess the vegetation-coverage-related factor known as cover management factor (C-factor) at a high spatial resolution (10 m) considering a total of 38 European countries. Based on the employment of the RS derivative of the Normalised Difference Vegetation Index (NDVI) for January and December 2019, a C-factor map was generated due to mean annual estimation. National values were then calculated in terms of different types of agricultural land cover classes. Furthermore, the European C-factor (C<sub>EUROPE</sub>) values concerning the island of Crete (Greece) were compared with relevant values estimated for the island (C<sub>CRETE</sub>) based on Sentinel-2 images being individually selected at a monthly time-step of 2019 to generate a series of 12 maps for the C-factor in Crete. Our results yielded identical C-factor values for the different approaches. The outcomes denote GEE’s high analytic and processing abilities to analyse massive quantities of data that can provide efficient digital products for soil-erosion-related studies. |
| first_indexed | 2024-03-10T03:12:16Z |
| format | Article |
| id | doaj.art-19387fef45894a69950d984839f37933 |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-03-10T03:12:16Z |
| publishDate | 2021-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-19387fef45894a69950d984839f379332023-11-23T10:23:43ZengMDPI AGRemote Sensing2072-42922021-12-011324501910.3390/rs13245019Towards the Assessment of Soil-Erosion-Related C-Factor on European Scale Using Google Earth Engine and Sentinel-2 ImagesDimitrios D. Alexakis0Stelios Manoudakis1Athos Agapiou2Christos Polykretis3Lab of Geophysical-Satellite Remote Sensing and Archaeo-Environment, Institute for Mediterranean Studies, Foundation for Research and Technology-Hellas, 74100 Rethymno, GreeceSchool of Chemical and Environmental Engineering, Technical University of Crete, 73100 Chania, GreeceEarth Observation Cultural Heritage Research Lab, Department of Civil Engineering and Geomatics, Faculty of Engineering and Technology, Cyprus University of Technology, Lemesos 3036, CyprusLab of Geophysical-Satellite Remote Sensing and Archaeo-Environment, Institute for Mediterranean Studies, Foundation for Research and Technology-Hellas, 74100 Rethymno, GreeceSoil erosion is a constant environmental threat for the entirety of Europe. Numerous studies have been published during the last years concerning assessing soil erosion utilising Remote Sensing (RS) and Geographic Information Systems (GIS). Such studies commonly employ empirical erosion models to estimate soil loss on various spatial scales. In this context, empirical models have been highlighted as major approaches to estimate soil loss on various spatial scales. Most of these models analyse environmental factors representing soil-erosion-influencing conditions such as the climate, topography, soil regime, and surface vegetation coverage. In this study, the Google Earth Engine (GEE) cloud computing platform and Sentinel-2 satellite imagery data have been combined to assess the vegetation-coverage-related factor known as cover management factor (C-factor) at a high spatial resolution (10 m) considering a total of 38 European countries. Based on the employment of the RS derivative of the Normalised Difference Vegetation Index (NDVI) for January and December 2019, a C-factor map was generated due to mean annual estimation. National values were then calculated in terms of different types of agricultural land cover classes. Furthermore, the European C-factor (C<sub>EUROPE</sub>) values concerning the island of Crete (Greece) were compared with relevant values estimated for the island (C<sub>CRETE</sub>) based on Sentinel-2 images being individually selected at a monthly time-step of 2019 to generate a series of 12 maps for the C-factor in Crete. Our results yielded identical C-factor values for the different approaches. The outcomes denote GEE’s high analytic and processing abilities to analyse massive quantities of data that can provide efficient digital products for soil-erosion-related studies.https://www.mdpi.com/2072-4292/13/24/5019C-factorGoogle Earth EngineSentinel-2soil erosionEuropean scale |
| spellingShingle | Dimitrios D. Alexakis Stelios Manoudakis Athos Agapiou Christos Polykretis Towards the Assessment of Soil-Erosion-Related C-Factor on European Scale Using Google Earth Engine and Sentinel-2 Images Remote Sensing C-factor Google Earth Engine Sentinel-2 soil erosion European scale |
| title | Towards the Assessment of Soil-Erosion-Related C-Factor on European Scale Using Google Earth Engine and Sentinel-2 Images |
| title_full | Towards the Assessment of Soil-Erosion-Related C-Factor on European Scale Using Google Earth Engine and Sentinel-2 Images |
| title_fullStr | Towards the Assessment of Soil-Erosion-Related C-Factor on European Scale Using Google Earth Engine and Sentinel-2 Images |
| title_full_unstemmed | Towards the Assessment of Soil-Erosion-Related C-Factor on European Scale Using Google Earth Engine and Sentinel-2 Images |
| title_short | Towards the Assessment of Soil-Erosion-Related C-Factor on European Scale Using Google Earth Engine and Sentinel-2 Images |
| title_sort | towards the assessment of soil erosion related c factor on european scale using google earth engine and sentinel 2 images |
| topic | C-factor Google Earth Engine Sentinel-2 soil erosion European scale |
| url | https://www.mdpi.com/2072-4292/13/24/5019 |
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