Contenido de agua volumétrico a una succión de 10 kPa, 33 kPa y 1, 500 kPa en 10^-3 cm³/cm³ (0.1 v% o 1 mm/m) a 6 profundidades estándar (0-5 cm, 5-15 cm, 15-30 cm, 30-60 cm, 60-100 cm, 100-200 cm). Las predicciones se obtuvieron con un enfoque de cartografía digital del suelo basado en el bosque aleatorio de cuantiles, que se basa en una recopilación global de datos de perfiles de suelo y capas ambientales.
Este conjunto de datos incluye predicciones para tres niveles de succión diferentes, lo que proporciona estadísticas sobre la disponibilidad de agua en el suelo.
El conjunto de datos se organiza en tres recursos principales: /wv0010, /wv0033 y /wv1500. Cada uno de estos recursos contiene bandas que representan las propiedades del suelo en diferentes profundidades y cuantiles. Los nombres de las bandas siguen el patrón val_<depth>_<quantile>, en el que depth representa un rango de profundidad del suelo (p.ej., 0-5 cm, 5-15 cm, 15-30 cm, 30-60 cm, 60-100 cm, 100-200 cm) y quantile representa una medida estadística (p.ej., media, Q0.05, Q0.5, Q0.95).
Aún no se incluye la banda de incertidumbre. Es posible calcular la incertidumbre a partir de la proporción entre el rango intercuantil (ancho del intervalo de predicción del 90%) y la mediana: (Q0.95-Q0.05)/Q0.50.
Mapeo global de la retención de agua volumétrica a 100, 330 y 15,000 cm de succión con la base de datos de WoSIS
Turek M.E., Poggio L., Batjes N.H., Armindo R.A., de Jong van Lier Q.,
de Sousa L., Heuvelink G.B.M. (2023)
International Soil and Water Conservation Research, 11 (2), pp. 225-239.
Contenido de agua volumétrico a una succión de 10 kPa, 33 kPa y 1, 500 kPa en 10^-3 cm³/cm³ (0.1% vol. o 1 mm/m) a 6 profundidades estándar (0-5 cm, 5-15 cm, 15-30 cm, 30-60 cm, 60-100 cm, 100-200 cm). Las predicciones se obtuvieron con un enfoque de asignación digital de suelos basado en el método de bosque aleatorio de cuantiles, que se basa en una recopilación global de datos de perfiles de suelo…
[null,null,[],[],[],null,["# SoilGrids250m 2.0 - Volumetric Water Content\n\nDataset Availability\n: 1905-04-01T00:00:00Z--2016-07-05T00:00:00Z\n\nDataset Provider\n:\n\n\n [ISRIC - World Soil Information](https://www.isric.org/explore/soilgrids)\n\nTags\n:\n[soil](/earth-engine/datasets/tags/soil) [soil-moisture](/earth-engine/datasets/tags/soil-moisture) [water](/earth-engine/datasets/tags/water) \n\n#### Description\n\nVolumetric Water Content at 10kPa, 33kPa, and 1500kPa suction in\n10\\^-3 cm\\^3/cm\\^3 (0.1 v% or 1 mm/m) at 6 standard depths (0-5cm, 5-15cm,\n15-30cm, 30-60cm, 60-100cm, 100-200cm). Predictions were derived using a\ndigital soil mapping approach based on Quantile Random Forest, drawing on a\nglobal compilation of soil profile data and environmental layers.\nThis dataset includes predictions for three different suction levels,\nproviding insights into soil water availability.\n\nThe dataset is organized into three main assets: `/wv0010`, `/wv0033`,\nand `/wv1500`. Each of these assets contains bands representing soil\nproperties at different depths and quantiles. The band names follow the\npattern `val_\u003cdepth\u003e_\u003cquantile\u003e`, where `depth` represents a soil depth\nrange (e.g., 0-5cm, 5-15cm, 15-30cm, 30-60cm, 60-100cm, 100-200cm) and\n`quantile` represents a statistical measure (e.g., mean, Q0.05, Q0.5,\nQ0.95).\n\nThe uncertainty band is not yet included. It is possible to calculate\nthe uncertainty from the ratio between the inter-quantile range\n(90% prediction interval width) and the median: (Q0.95-Q0.05)/Q0.50.\n\nDocumentation:\n\n- [Scientific Paper](https://www.sciencedirect.com/science/article/pii/S2095633922000636?via%3Dihub)\n\n### Bands\n\n\n**Pixel Size**\n\n250 meters\n\n**Bands**\n\n| Name | Units | Pixel Size | Description |\n|-----------------------|-------------|------------|--------------------------------------------------|\n| `val_0_5cm_mean` | cm\\^3/cm\\^3 | meters | Mean Volumetric Water Content (0-5cm depth) |\n| `val_0_5cm_Q0_05` | cm\\^3/cm\\^3 | meters | Q0.05 Volumetric Water Content (0-5cm depth) |\n| `val_0_5cm_Q0_5` | cm\\^3/cm\\^3 | meters | Q0.5 Volumetric Water Content (0-5cm depth) |\n| `val_0_5cm_Q0_95` | cm\\^3/cm\\^3 | meters | Q0.95 Volumetric Water Content (0-5cm depth) |\n| `val_5_15cm_mean` | cm\\^3/cm\\^3 | meters | Mean Volumetric Water Content (5-15cm depth) |\n| `val_5_15cm_Q0_05` | cm\\^3/cm\\^3 | meters | Q0.05 Volumetric Water Content (5-15cm depth) |\n| `val_5_15cm_Q0_5` | cm\\^3/cm\\^3 | meters | Q0.5 Volumetric Water Content (5-15cm depth) |\n| `val_5_15cm_Q0_95` | cm\\^3/cm\\^3 | meters | Q0.95 Volumetric Water Content (5-15cm depth) |\n| `val_15_30cm_mean` | cm\\^3/cm\\^3 | meters | Mean Volumetric Water Content (15-30cm depth) |\n| `val_15_30cm_Q0_05` | cm\\^3/cm\\^3 | meters | Q0.05 Volumetric Water Content (15-30cm depth) |\n| `val_15_30cm_Q0_5` | cm\\^3/cm\\^3 | meters | Q0.5 Volumetric Water Content (15-30cm depth) |\n| `val_15_30cm_Q0_95` | cm\\^3/cm\\^3 | meters | Q0.95 Volumetric Water Content (15-30cm depth) |\n| `val_30_60cm_mean` | cm\\^3/cm\\^3 | meters | Mean Volumetric Water Content (30-60cm depth) |\n| `val_30_60cm_Q0_05` | cm\\^3/cm\\^3 | meters | Q0.05 Volumetric Water Content (30-60cm depth) |\n| `val_30_60cm_Q0_5` | cm\\^3/cm\\^3 | meters | Q0.5 Volumetric Water Content (30-60cm depth) |\n| `val_30_60cm_Q0_95` | cm\\^3/cm\\^3 | meters | Q0.95 Volumetric Water Content (30-60cm depth) |\n| `val_60_100cm_mean` | cm\\^3/cm\\^3 | meters | Mean Volumetric Water Content (60-100cm depth) |\n| `val_60_100cm_Q0_05` | cm\\^3/cm\\^3 | meters | Q0.05 Volumetric Water Content (60-100cm depth) |\n| `val_60_100cm_Q0_5` | cm\\^3/cm\\^3 | meters | Q0.5 Volumetric Water Content (60-100cm depth) |\n| `val_60_100cm_Q0_95` | cm\\^3/cm\\^3 | meters | Q0.95 Volumetric Water Content (60-100cm depth) |\n| `val_100_200cm_mean` | cm\\^3/cm\\^3 | meters | Mean Volumetric Water Content (100-200cm depth) |\n| `val_100_200cm_Q0_05` | cm\\^3/cm\\^3 | meters | Q0.05 Volumetric Water Content (100-200cm depth) |\n| `val_100_200cm_Q0_5` | cm\\^3/cm\\^3 | meters | Q0.5 Volumetric Water Content (100-200cm depth) |\n| `val_100_200cm_Q0_95` | cm\\^3/cm\\^3 | meters | Q0.95 Volumetric Water Content (100-200cm depth) |\n\n### Terms of Use\n\n**Terms of Use**\n\n[CC-BY-4.0](https://spdx.org/licenses/CC-BY-4.0.html)\n\n### Citations\n\nCitations:\n\n- Global mapping of volumetric water retention at 100, 330 and 15000 cm\n suction using the WoSIS database\n Turek M.E., Poggio L., Batjes N.H., Armindo R.A., de Jong van Lier Q.,\n de Sousa L., Heuvelink G.B.M. (2023)\n International Soil and Water Conservation Research, 11 (2), pp. 225-239.\n\n### DOIs\n\n- \u003chttps://doi.org/10.1016/j.iswcr.2022.08.001\u003e\n\n### Explore with Earth Engine\n\n| **Important:** Earth Engine is a platform for petabyte-scale scientific analysis and visualization of geospatial datasets, both for public benefit and for business and government users. Earth Engine is free to use for research, education, and nonprofit use. To get started, please [register for Earth Engine access.](https://console.cloud.google.com/earth-engine)\n\n### Code Editor (JavaScript)\n\n```javascript\nvar dataset = ee.Image('ISRIC/SoilGrids250m/v2_0/wv0010').select('val_0_5cm_Q0_95');\n\nMap.setCenter(-105.25, 52.5, 3);\n\nMap.addLayer(\n dataset, {\n min: -0.061,\n max: 0.636,\n palette: [\n '#440154', '#482878', '#3E4A89', '#31688E', '#26828E', '#1F9E89',\n '#35B779', '#6DCD59', '#B4DE2C', '#FDE725'\n ]\n },\n 'SoilGrids250m 10kPa Q0.95 0-5cm');\n```\n[Open in Code Editor](https://code.earthengine.google.com/?scriptPath=Examples:Datasets/ISRIC/ISRIC_SoilGrids250m_v2_0) \n[SoilGrids250m 2.0 - Volumetric Water Content](/earth-engine/datasets/catalog/ISRIC_SoilGrids250m_v2_0) \nVolumetric Water Content at 10kPa, 33kPa, and 1500kPa suction in 10\\^-3 cm\\^3/cm\\^3 (0.1 v% or 1 mm/m) at 6 standard depths (0-5cm, 5-15cm, 15-30cm, 30-60cm, 60-100cm, 100-200cm). Predictions were derived using a digital soil mapping approach based on Quantile Random Forest, drawing on a global compilation of soil profile data ... \nISRIC/SoilGrids250m/v2_0, soil,soil-moisture,water \n1905-04-01T00:00:00Z/2016-07-05T00:00:00Z \n-56 -180 84 180 \nGoogle Earth Engine \nhttps://developers.google.com/earth-engine/datasets\n\n- [https://doi.org/10.1016/j.iswcr.2022.08.001](https://doi.org/https://www.isric.org/explore/soilgrids)\n- [https://doi.org/10.1016/j.iswcr.2022.08.001](https://doi.org/https://developers.google.com/earth-engine/datasets/catalog/ISRIC_SoilGrids250m_v2_0)"]]
