For those of you that need soil data for your modeling / analytics, This is to inform you that we have recently done a major update of our SoilGrids system (https://soilgrids.org). The new predictions are now available at 250 m globally for 7 standard depths (0, 5, 15, 30, 60, 100, 200 cm). We distribute predictions of standard chemical (soil pH, organic carbon, CEC) and physical soil properties (texture fractions, bulk density, coarse fragments, depth to bedrock) but also predictions of soil classes (USDA and WRB classification systems). These data are distributed under the Open Data Base License (i.e. the same license used by OpenStreetMap). You can download the data directly via FTP (ftp://ftp.soilgrids.org/data/recent/) or by using the Web Coverage Service (http://webservices.isric.org/geoserver/wcs). I wrote a short tutorial that explains how to grab blocks of data using GDAL WCS driver (http://gsif.isric.org/doku.php?id=wiki:tutorial_soilgrids#wcs_data_access). Let me know if you are aware of any 'easier' way to subset and resample SoilGrids via WCS. SoilGrids are also available via REST API (http://rest.soilgrids.org) hence at point locations you can fetch majority of values by using GSIF package (http://gsif.r-forge.r-project.org/REST.SoilGrids.html). Please try not to use this function to fetch values for large number of points as this can become very time consuming (the average response time per point is about 0.6 sec). I would also like to mention that this project was fully implemented in R / OSGeo software (which on the end worked out very smoothly even though we had to crunch terrabytes of remote sensing data). We are really grateful to all creators of packages we have used, especially to the authors of the ranger, xgboost, snowfall, caret, raster and rgdal packages and SAGA GIS and GDAL, which are the backbone of the spatial prediction system. I could spend a lifetime thanking the package authors for sharing their talent and creations with us. PS: We have a separate mailing list for SoilGrids (https://groups.google.com/forum/#!forum/global-soil-information) mainly used by soil scientists / soil data experts, but if it is a generic spatial analysis problem, then I will do my best to answer it via R-sig-geo. cheers, T. Hengl
Global gridded soil data (https://SoilGrids.org)
3 messages · Isaque Daniel, Tomislav Hengl
Incredible job T. Hengl!!! What data you use for South America? There are some documentation about the generation of data? Thanks in advance Isaque ------------------------------------------------------------------------------------------------------------------ Eng. Agr. Isaque Daniel Rocha Eberhardt Mestre em Sensoriamento Remoto - Instituto Nacional de Pesquisas Espaciais (INPE) Doutorando em Transportes - Universidade de Bras??lia (UNB) Mobile: +55 (061) 99015658 ------------------------------------------------------------------------------------------------------------------ Agronomist engineer Master in Remote Sensing - National Institute for Space Research (INPE) - Brazil PHD Student in Transport - Bras??lia University (UNB)
De: R-sig-Geo <r-sig-geo-bounces at r-project.org> em nome de Tomislav Hengl <tom.hengl at gmail.com>
Enviado: ter?a-feira, 26 de julho de 2016 22:47 Para: r-sig-geo at r-project.org Assunto: [R-sig-Geo] Global gridded soil data (https://SoilGrids.org) For those of you that need soil data for your modeling / analytics, This is to inform you that we have recently done a major update of our SoilGrids system (https://soilgrids.org). The new predictions are now SoilGrids | ISRIC<https://soilgrids.org/> soilgrids.org SoilGrids: global gridded soil information ... We use cookies to customize user experience and collect usage data. By using this app you agree to our use of cookies ... available at 250 m globally for 7 standard depths (0, 5, 15, 30, 60, 100, 200 cm). We distribute predictions of standard chemical (soil pH, organic carbon, CEC) and physical soil properties (texture fractions, bulk density, coarse fragments, depth to bedrock) but also predictions of soil classes (USDA and WRB classification systems). These data are distributed under the Open Data Base License (i.e. the same license used by OpenStreetMap). You can download the data directly via FTP (ftp://ftp.soilgrids.org/data/recent/) or by using the Web Coverage Service (http://webservices.isric.org/geoserver/wcs). I wrote a short tutorial that explains how to grab blocks of data using GDAL WCS driver (http://gsif.isric.org/doku.php?id=wiki:tutorial_soilgrids#wcs_data_access). Let me know if you are aware of any 'easier' way to subset and resample SoilGrids via WCS. SoilGrids are also available via REST API (http://rest.soilgrids.org) hence at point locations you can fetch majority of values by using GSIF package (http://gsif.r-forge.r-project.org/REST.SoilGrids.html). Please try not to use this function to fetch values for large number of points as this can become very time consuming (the average response time per point is about 0.6 sec). I would also like to mention that this project was fully implemented in R / OSGeo software (which on the end worked out very smoothly even though we had to crunch terrabytes of remote sensing data). We are really grateful to all creators of packages we have used, especially to the authors of the ranger, xgboost, snowfall, caret, raster and rgdal packages and SAGA GIS and GDAL, which are the backbone of the spatial prediction system. I could spend a lifetime thanking the package authors for sharing their talent and creations with us. PS: We have a separate mailing list for SoilGrids (https://groups.google.com/forum/#!forum/global-soil-information) mainly used by soil scientists / soil data experts, but if it is a generic spatial analysis problem, then I will do my best to answer it via R-sig-geo. cheers, T. Hengl _______________________________________________ R-sig-Geo mailing list R-sig-Geo at r-project.org https://stat.ethz.ch/mailman/listinfo/r-sig-geo
Isaque, You can access about 60% of point data used for training via the WoSIS Web Feature Service (http://www.isric.org/content/wosis-distribution-set) - I think most of points available for Latin America are available via this service. We are hoping that national government agencies will donate even more point data, so that we can gradually improve the maps as in: http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0105992#pone-0105992-g013 Thank you and BR,
On 27-7-2016 13:48, Isaque Daniel wrote:
Incredible job T. Hengl!!! What data you use for South America? There are some documentation about the generation of data? Thanks in advance Isaque ------------------------------------------------------------------------------------------------------------------ Eng. Agr. Isaque Daniel Rocha Eberhardt Mestre em Sensoriamento Remoto - Instituto Nacional de Pesquisas Espaciais (INPE) Doutorando em Transportes - Universidade de Bras??lia (UNB) Mobile: +55 (061) 99015658 ------------------------------------------------------------------------------------------------------------------ Agronomist engineer Master in Remote Sensing - National Institute for Space Research (INPE) - Brazil PHD Student in Transport - Bras??lia University (UNB) ------------------------------------------------------------------------ *De:* R-sig-Geo <r-sig-geo-bounces at r-project.org> em nome de Tomislav Hengl <tom.hengl at gmail.com> *Enviado:* ter?a-feira, 26 de julho de 2016 22:47 *Para:* r-sig-geo at r-project.org *Assunto:* [R-sig-Geo] Global gridded soil data (https://SoilGrids.org) For those of you that need soil data for your modeling / analytics, This is to inform you that we have recently done a major update of our SoilGrids system (https://soilgrids.org). The new predictions are now SoilGrids | ISRIC <https://soilgrids.org/> soilgrids.org SoilGrids: global gridded soil information ... We use cookies to customize user experience and collect usage data. By using this app you agree to our use of cookies ... available at 250 m globally for 7 standard depths (0, 5, 15, 30, 60, 100, 200 cm). We distribute predictions of standard chemical (soil pH, organic carbon, CEC) and physical soil properties (texture fractions, bulk density, coarse fragments, depth to bedrock) but also predictions of soil classes (USDA and WRB classification systems). These data are distributed under the Open Data Base License (i.e. the same license used by OpenStreetMap). You can download the data directly via FTP (ftp://ftp.soilgrids.org/data/recent/) or by using the Web Coverage Service (http://webservices.isric.org/geoserver/wcs). I wrote a short tutorial that explains how to grab blocks of data using GDAL WCS driver (http://gsif.isric.org/doku.php?id=wiki:tutorial_soilgrids#wcs_data_access). Let me know if you are aware of any 'easier' way to subset and resample SoilGrids via WCS. SoilGrids are also available via REST API (http://rest.soilgrids.org) hence at point locations you can fetch majority of values by using GSIF package (http://gsif.r-forge.r-project.org/REST.SoilGrids.html). Please try not to use this function to fetch values for large number of points as this can become very time consuming (the average response time per point is about 0.6 sec). I would also like to mention that this project was fully implemented in R / OSGeo software (which on the end worked out very smoothly even though we had to crunch terrabytes of remote sensing data). We are really grateful to all creators of packages we have used, especially to the authors of the ranger, xgboost, snowfall, caret, raster and rgdal packages and SAGA GIS and GDAL, which are the backbone of the spatial prediction system. I could spend a lifetime thanking the package authors for sharing their talent and creations with us. PS: We have a separate mailing list for SoilGrids (https://groups.google.com/forum/#!forum/global-soil-information <https://groups.google.com/forum/#%21forum/global-soil-information>) mainly used by soil scientists / soil data experts, but if it is a generic spatial analysis problem, then I will do my best to answer it via R-sig-geo. cheers, T. Hengl
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