Back to Search Start Over

Estimating water erosion from the brightness index of orbital images: A framework for the prognosis of degraded pastures.

Authors :
Vieira AS
do Valle Junior RF
Rodrigues VS
da Silva Quinaia TL
Mendes RG
Valera CA
Fernandes LFS
Pacheco FAL
Source :
The Science of the total environment [Sci Total Environ] 2021 Jul 01; Vol. 776, pp. 146019. Date of Electronic Publication: 2021 Feb 23.
Publication Year :
2021

Abstract

The inadequate management of soils and the absence of conservation practices favor the degradation of pastures and can trigger adverse environmental alterations and damage under the terms of Brazilian Federal Law no. 6.938/1981. Based on this premise, this study aimed to estimate soil losses caused by water erosion in pasture areas using the brightness index (BI) from the annual series of Landsat 8 images in different geological formations. A specifically prepared Google Earth Engine (GEE) script automatically extracted the BI from the images. The study occurred in the Environmental Protection Area (EPA) of Uberaba River basin (Minas Gerais, Brazil). To accomplish the goal, 180 digital 500-wide random buffers were selected from 3 geologic types (60 points per type), and then analyzed for zonal statistics of USLE (Universal Soil Loss Equation) soil loss and BI in a Geographic Information System. The regression models BI versus USLE soil loss allowed estimating BI soil losses over the pastures of EPA. The model fittings were remarkable. The validation of soil loss maps in the EPA occurred in pasture phytophysiognomies through the probing of penetration resistance in 37 randomly selected locations. The results were satisfactory, mostly those based on the BI. The BI losses increased for greater resistances. Amplified losses also occurred in regions exposed to environmental land use conflicts (actual uses that deviate from land capability or natural use). Overall, the BI approach proved efficient to accurately track soil losses and pasture degradation over large areas, with the advantage of standing on a single parameter easily accessed through remote sensed data. From an environmental standpoint, this is an important result, because the accurate diagnosis and prognosis of degraded pastures is paramount to implement mitigation measures following the "polluter pays principle", even more in Brazil where the areas occupied by degraded pastures are enormous.<br />Competing Interests: Declaration of competing interest The authors declare no conflicts of interest. The funders had no role in the design of the study, in the collection, analyses, or interpretation of data, in the writing of the manuscript, or in the decision to publish the results.<br /> (Copyright © 2021 Elsevier B.V. All rights reserved.)

Details

Language :
English
ISSN :
1879-1026
Volume :
776
Database :
MEDLINE
Journal :
The Science of the total environment
Publication Type :
Academic Journal
Accession number :
33652307
Full Text :
https://doi.org/10.1016/j.scitotenv.2021.146019