Assessment of the vegetation indices on Sentinel-2A images for predicting the soil productivity potential in Bursa, Turkey
- 8 December 2019
- journal article
- research article
- Published by Springer Science and Business Media LLC in Environmental Monitoring and Assessment
- Vol. 192 (1), 16
- https://doi.org/10.1007/s10661-019-7989-8
Abstract
Although field surveys represent an essential method for determining soil productivity, the use of remote sensing techniques has become a popular option over recent years due to its economic and practical applications. The fundamental basis of this approach is the estimation of soil productivity by using the vegetation indices as an indicator, with reference to the yield. In this study, it is aimed to estimate the productivity potential of the agriculture areas from biomass density in case of limited pedological and parcel-based data. For this purpose, relationships between the FAO Soil Productivity Rating (SPR) and different vegetation indices were investigated. The indices NDVI, RE-OSAVI, and REMCARI were used with Sentinel-2A images. Wheat was selected as an indicator plant to estimate the yield because it is the most occupied (27.47%) cultigen in the field. The study was conducted at the Karacabey State Farm with an area of 87 km2 and is located in Bursa province, Turkey. The research showed a positive relationship between SPR and 2018 yield values (r2 = 0.616). During the tillering period, the r2 for RE-OSAVI was 0.629. In the heading stage, the r2 for NDVI was 0.577. The index REMCARI provided yield estimations with low accuracy coefficient (0.216 ≤ r2 ≤ 0.258) during all vegetation periods. These findings can be interpreted as the monitoring of the land quality with multispectral satellite images via NDVI and RE-OSAVI. In this way, we could decide the time to re-definition of soil properties with land surveys for determination of soil productivity when the detection of a decrease using the indices during some vegetation periods. However, further investigations are needed in controlled trial patterns with differential reference plants, although the findings obtained from the study are promising for the use of spectral vegetation indices to prediction and/or monitoring of soil productivity. Thus, the possibilities of using spectral indices in different ecologies and different plant species can be evaluated from a broad perspective. It was also suggested that Sentinel-2A images may be used for similar studies due to their spectral capabilities with the ESA-SNAP tool.Keywords
This publication has 58 references indexed in Scilit:
- A framework for assessing agricultural soil quality on a global scaleArchives of Agronomy and Soil Science, 2012
- Agriculture and resource availability in a changing world: The role of irrigationWater Resources Research, 2010
- Using High-Resolution Satellite Imaging to Evaluate Nitrogen Status of Winter WheatJournal of Plant Nutrition, 2007
- Use of remote sensing data for estimation of winter wheat yield in the United StatesInternational Journal of Remote Sensing, 2007
- Agricultural and forest productivity for modelling policy scenarios: Evaluating approaches for New Zealand greenhouse gas mitigationJournal of the Royal Society of New Zealand, 2006
- Spectroscopic Determination of Leaf Biochemistry Using Band-Depth Analysis of Absorption Features and Stepwise Multiple Linear RegressionRemote Sensing of Environment, 1999
- Effects of free-air carbon dioxide enrichment on PAR absorption and conversion efficiency by cottonAgricultural and Forest Meteorology, 1994
- Remote Sensing of Biotic and Abiotic Plant StressAnnual Review of Phytopathology, 1986
- The fertility capability soil classification system: Interpretation, applicability and modificationGeoderma, 1982
- Red and photographic infrared linear combinations for monitoring vegetationRemote Sensing of Environment, 1979