Training Field Soil Data for Annual Mapping of Soil Organic Carbon Stock (0–30 cm) in Brazil, 1985–2023 (MapBiomas Soil Collection 2, Beta Version) (doi:10.60502/SoilData/SXCSDK)

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Part 1: Document Description
Part 2: Study Description
Part 3: Data Files Description
Part 4: Variable Description
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Training Field Soil Data for Annual Mapping of Soil Organic Carbon Stock (0–30 cm) in Brazil, 1985–2023 (MapBiomas Soil Collection 2, Beta Version)

doi:10.60502/SoilData/SXCSDK

SoilData

2024-12-14

1

MapBiomas, 2024, "Training Field Soil Data for Annual Mapping of Soil Organic Carbon Stock (0–30 cm) in Brazil, 1985–2023 (MapBiomas Soil Collection 2, Beta Version)", https://doi.org/10.60502/SoilData/SXCSDK, SoilData, V1, UNF:6:PKK9HmpVEly47sjSf0e/PQ== [fileUNF]

Training Field Soil Data for Annual Mapping of Soil Organic Carbon Stock (0–30 cm) in Brazil, 1985–2023 (MapBiomas Soil Collection 2, Beta Version)

doi:10.60502/SoilData/SXCSDK

MapBiomas (MapBiomas)

Ferreira, Laerte

Samuel-Rosa, Alessandro

Horst, Taciara Zborowski

Shimbo, Julia

Rosa, Marcos

Anjos, Marcos Alexandre dos

Huf dos Reis, Aline Mari

Kerber, Débora Liriel

Peruzzi, Vitor

Serena, Gabriele Vitória Silva

Pretto, Ana Caroline

Pontes, David Oliveira

Silva, Luciana da Luz

Cardoso, Marcos Vinícius Souza

Cardoso, Maria Eduarda Ferreira

Alencastro, Mary Evelyn Santos

Sobucki, Lisiane

Parizzi, Talita

Capoane, Viviane

Souza, Deórgia

Tornquist, Carlos Gustavo

Rocha, Anderson Sandro da

Oliveira, Sergio

Munsberg, Glauco

Azevedo, Tasso

SoilData

MapBiomas

Samuel-Rosa, Alessandro

2024-12-06

2024-12-06

https://doi.org/10.60502/SoilData/SXCSDK

Ciências Agrárias, Ciências da Terra e do meio ambiente, Soil organic carbon, Topsoil, Brazilian biomes

Collection of 12,575 georeferenced points containing field data used to train regression models for mapping soil organic carbon stock (0–30 cm) in Brazil. These data were utilized to prepare the annual maps of soil organic carbon stocks in Collection 2 of the MapBiomas Soil project, covering the period 1985–2023 (beta version). Each record includes spatial and temporal coordinates, the year of soil collection, and the soil organic carbon stock (grams per square meter) calculated for the 0–30 cm soil layer.

<b>Detailed description</b>: Soil data were collected from 262 studies published in the Brazilian soil data repository SoilData (<a href=\"https://soildata.mapbiomas.org\">https://soildata.mapbiomas.org</a>). After analysis, a total of 250 datasets was selected for the spatial-temporal modeling of soil organic carbon stock. These data represent 15,729 points distributed across Brazil, with information on 29,881 soil layers. Some properties, such as the amount of coarse fragments and soil density, were missing in many samples. These missing values were estimated using statistical models known as pedotransfer functions. After this step, 12,575 points and 19,028 layers from 236 datasets were considered suitable for the spatial-temporal modeling of soil organic carbon stock. To calculate the soil organic carbon stock, the percentage of coarse fragments (% by weight) was converted to volume (% by volume) using a density of 2.65 g/cm³. The soil organic carbon stock (g/m²) for each layer was then calculated using the following equation: carbon content × (1 - coarse fragments) × soil density × layer thickness. For sampling points with multiple layers up to 30 cm depth, the carbon stocks from each layer were summed to obtain the total soil organic carbon stock at the point.<br/><br/>The dataset includes the following columns:<ul><li><b>point_id:</b> An alphanumeric code that identifies the source dataset ("ctb" followed by four numbers, such as ctb0003) and the ID of the soil profile, observation, or sampling point (event) in that dataset.</li><li><b>latitude and longitude:</b> Decimal geographic coordinates in the WGS84 coordinate reference system (EPSG:4326).</li><li><b>year:</b> The year of soil collection in the field.</li><li><b>soc_stock_g_m2:</b> Soil organic carbon stock in grams per square meter (g/m²) in the 0–30 cm layer.</li></ul><br/>The code used to process the data is available at <a href=\"https://github.com/Laboratorio-de-Pedometria/mapbiomas-soc\">https://github.com/Laboratorio-de-Pedometria/mapbiomas-soc</a>.

1958-2023

1958-2023

Brazil

Country

survey data

geo-referenced data

aggregated data

compiled data

• Number of cases: 12575

• No. of variables per record: 5

• Type of File: text/tab-separated-values

UNF:6:PKK9HmpVEly47sjSf0e/PQ==

• point_id - point_id
• longitude - longitude
• latitude - latitude
• year - year
• soc_stock_g_m2 - soc_stock_g_m2

f730 Location:

Variable Format: character

Notes: UNF:6:BJFqg+02aNr2Sxyp3ifQKA==

f730 Location:

Summary Statistics: Mean -52.67367778707137; Min. -73.78333; StDev 8.564905054778958; Max. -34.8833; Valid 12575.0

Variable Format: numeric

Notes: UNF:6:vXmE7CX3JvdHNh3UJYvi4A==

f730 Location:

Summary Statistics: StDev 8.92854895815797; Max. 4.633333; Mean -16.254727448441724; Valid 12575.0; Min. -33.55901

Variable Format: numeric

Notes: UNF:6:NiwJsmS3ZD5TAQeKWzpkUA==

f730 Location:

Summary Statistics: Mean 1997.2628320866656; StDev 14.970718115260595; Min. 1958.0; Max. 2023.0; Valid 11631.0;

Variable Format: numeric

Notes: UNF:6:+Mdt8Ra24IbuVOU5MWHeBw==

f730 Location:

Summary Statistics: Max. 118374.0; Min. 52.0; StDev 4513.889223328365; Valid 12575.0; Mean 4806.930417495032;

Variable Format: numeric

Notes: UNF:6:R3hYeaPIUiaaXtstq4v+RQ==