Multitemporal satellite imagery analysis for soil organic carbon assessment in an agricultural farm in southeastern Brazil
| dc.contributor.author | Minhoni, Renata Teixeira de Almeida [UNESP] | |
| dc.contributor.author | Scudiero, Elia | |
| dc.contributor.author | Zaccaria, Daniele | |
| dc.contributor.author | Saad, João Carlos Cury [UNESP] | |
| dc.contributor.institution | Universidade Estadual Paulista (Unesp) | |
| dc.contributor.institution | Riverside | |
| dc.contributor.institution | U.S. Salinity Laboratory | |
| dc.contributor.institution | University of California | |
| dc.date.accessioned | 2021-06-25T11:15:59Z | |
| dc.date.available | 2021-06-25T11:15:59Z | |
| dc.date.issued | 2021-08-25 | |
| dc.description.abstract | Soil organic carbon (SOC) plays a crucial role for soil health. However, large datasets needed to accurately assess SOC at high resolution across scales are labor-intensive, time-consuming, and expensive. Ancillary geodata, including remote sensing spectral indices (RS-SIs) and topographic indicators (TIs), have been proposed as spatial covariates. Reported relationships between SOC and RS-SIs are erratic, possibly because single-date RS-SIs do not accurately capture SOC spatial variability due to transient confounding factors in the soil (e.g., moisture). However, multitemporal RS-SI data analysis may lead to noise reduction in SOC versus RS-SI relationships. This study aimed at: i) comparing single-date versus multitemporal RS-Sis derived from Sentinel-2 imagery for assessment of topsoil (0–0.2 m) SOC in two agricultural fields located in south-eastern Brazil; ii) comparing the performance of RS-SIs and TIs; iii) using adequate RS-SIs and TIs to compare sampling schemes defined on different collection grids; and iv) studying the temporal changes of SOC (0–0.2 m and 0.2–0.4 m). Results showed that: i) single-date RS-SIs were not reliable proxies for topsoil SOC at the study sites. For most of the tested RS-SIs, multitemporal data analysis produced accurate proxies for SOC; e.g., for the Normalized Difference Vegetation Index, the 4.5th multitemporal percentile predicted SOC with an R2 of 0.64; ii) The best TI was elevation (ranging from 643 to 684 m) with an R2 of 0.70; iii) The multitemporal SI and elevation maps indicated that the different sampling schemes were equally representative of the topsoil SOC's distribution across the entire area; and iv) From 2012 through 2019, topsoil SOC increased from 19.3 to 24.1 g kg−1. The ratio between SOC in the topsoil and subsoil (0.2–0.4 m) decreased from 1.7 to 1.1. Further testing of the proposed multitemporal RS-SI analysis is necessary to confirm its dependability for SOC assessment in Brazil and elsewhere. | en |
| dc.description.affiliation | São Paulo State University São Paulo State University (UNESP) School of Agronomical Sciences, Campus Botucatu, Av. Universitária, 3780 | |
| dc.description.affiliation | University of California Riverside Department of Environmental Sciences, 900 University Ave. | |
| dc.description.affiliation | United States Department of Agriculture – Agricultural Research Service U.S. Salinity Laboratory, 450 West Big Springs Rd. | |
| dc.description.affiliation | Department of Land Air and Water Resources University of California | |
| dc.description.affiliationUnesp | São Paulo State University São Paulo State University (UNESP) School of Agronomical Sciences, Campus Botucatu, Av. Universitária, 3780 | |
| dc.description.sponsorship | Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) | |
| dc.description.sponsorshipId | CNPq: 140676/2017-1 | |
| dc.identifier | http://dx.doi.org/10.1016/j.scitotenv.2021.147216 | |
| dc.identifier.citation | Science of the Total Environment, v. 784. | |
| dc.identifier.doi | 10.1016/j.scitotenv.2021.147216 | |
| dc.identifier.issn | 1879-1026 | |
| dc.identifier.issn | 0048-9697 | |
| dc.identifier.scopus | 2-s2.0-85105695483 | |
| dc.identifier.uri | http://hdl.handle.net/11449/208671 | |
| dc.language.iso | eng | |
| dc.relation.ispartof | Science of the Total Environment | |
| dc.source | Scopus | |
| dc.subject | Crop rotation | |
| dc.subject | Reduced tillage | |
| dc.subject | Remote sensing | |
| dc.subject | Sentinel-2 | |
| dc.subject | Spectral indices | |
| dc.subject | Sustainable agriculture | |
| dc.title | Multitemporal satellite imagery analysis for soil organic carbon assessment in an agricultural farm in southeastern Brazil | en |
| dc.type | Artigo | |
| dspace.entity.type | Publication | |
| unesp.department | Engenharia Rural - FCA | pt |
