Remote Quantification of Soil Organic Carbon: The Impact of Topography on Intra-Field Distribution

Liang Zoh^*
*Correspondence: Liang Zoh, Department of Civil and Environmental Engineering, University of Surrey, Guildford GU2 7XH, UK, Email:

Introduction

Soil Organic Carbon (SOC) plays a crucial role in the global carbon cycle and significantly impacts soil health, agricultural productivity, and climate change mitigation. The accurate quantification of SOC is vital for effective land management and policy-making. Traditional methods of SOC quantification, which rely on direct soil sampling and laboratory analysis, are often labor-intensive, time-consuming, and expensive, especially over large areas. Remote sensing technologies, combined with advanced data analysis techniques, offer a promising alternative for SOC quantification at larger scales. One of the critical factors influencing SOC distribution within fields is topography. This essay explores the methods and challenges of remote SOC quantification and delves into the impact of topography on the intra-field distribution of SOC [1].

Topography significantly affects the distribution of SOC within a field. The spatial variability of SOC is influenced by factors such as elevation, slope, aspect, and curvature of the landscape. These topographical features impact water movement, erosion, deposition, and organic matter accumulation, all of which contribute to SOC variability. Higher elevations often have thinner soils with less organic matter due to increased erosion and lower temperatures, which slow down the decomposition of organic material. Conversely, lower elevations can accumulate more SOC due to deposition from higher areas and potentially higher moisture levels, which enhance biomass production and organic matter decomposition. The steepness of the slope influences erosion and runoff. Steeper slopes tend to have lower SOC due to increased erosion rates, which remove topsoil rich in organic matter. Gentle slopes or flat areas are more likely to accumulate SOC as they are less prone to erosion and may receive organic material and sediments from upslope areas. The direction that a slope faces (aspect) affects solar radiation and microclimate, influencing vegetation growth and organic matter decomposition rates. South-facing slopes in the Northern Hemisphere (and north-facing slopes in the Southern Hemisphere) receive more sunlight, leading to higher temperatures and potentially lower SOC due to faster decomposition rates. Conversely, shaded slopes may have cooler, moister conditions that favour SOC accumulation. Curvature of the landscape, whether concave or convex, influences water accumulation and flow. Concave areas, such as depressions or valleys, tend to collect water and organic material, leading to higher SOC levels. Convex areas, such as ridges or hills, are more prone to erosion and typically have lower SOC [2,3].

Description

Researchers utilized hyperspectral and LiDAR data to map SOC distribution across varying topographical features. They found that SOC content was higher in lower elevation areas and concave landscapes due to organic matter deposition and moisture retention. A study integrating multispectral imagery with LiDAR-derived topographical maps revealed that SOC was significantly higher in flatter areas and lower in steep slopes. The findings helped in developing precision agriculture practices that enhance SOC sequestration by targeting specific topographical zones for organic amendments. In tropical forests, where SOC plays a crucial role in carbon cycling, RADAR and multispectral data were used to assess the impact of topography on SOC. Researchers found that SOC was higher in valley bottoms and lower on ridge tops, highlighting the importance of topographical context in carbon storage strategies. Remote sensing data must be calibrated and validated with ground truth measurements to ensure accuracy. This process can be resource-intensive and requires extensive fieldwork to collect representative soil samples. The presence of vegetation, surface litter, and soil moisture can interfere with the spectral signals used to estimate SOC [4]. Advanced algorithms and machine learning models are needed to disentangle these effects and improve SOC predictions. SOC levels can vary seasonally and annually due to changes in vegetation cover, soil moisture, and management practices. Continuous monitoring and time-series analysis are necessary to capture these dynamics and provide reliable SOC estimates. The spatial resolution of remote sensing data can limit the ability to detect fine-scale SOC variability. High-resolution sensors and data fusion techniques are essential to capture detailed spatial patterns of SOC distribution. Remote SOC quantification must be integrated with soil management practices to enhance soil health and carbon sequestration. This requires collaboration between researchers, policymakers, and land managers to develop and implement effective strategies [5].

Conclusion

The remote quantification of soil organic carbon, considering the impact of topography on its intra-field distribution, is a rapidly evolving field with significant implications for sustainable land management and climate change mitigation. Advances in remote sensing technologies, coupled with sophisticated data analysis techniques, provide new opportunities to accurately map and monitor SOC at large scales. Topographical features such as elevation, slope, aspect, and curvature play crucial roles in determining SOC distribution within fields, influencing erosion, deposition, water movement, and organic matter accumulation. Future research should focus on improving data calibration and validation methods, addressing spectral interference issues, and capturing temporal variability in SOC. Highresolution remote sensing data and advanced machine learning models will be essential to enhance the accuracy and spatial resolution of SOC estimates. Integrating remote SOC quantification with soil management practices will enable the development of targeted strategies to enhance soil health, increase agricultural productivity, and sequester carbon, contributing to global efforts to combat climate change.

Acknowledgement

None.

Conflict of Interest

None.

References

1. Caruso, Tancredi, Franciska T. De Vries, Richard D. Bardgett and Johannes Lehmann. "Soil organic carbon dynamics matching ecological equilibrium theory."Ecol Evol 8 (2018): 11169-11178.

   Google Scholar, Crossref, Indexed at

2. Lei, Zeyong, Dongwei Yu, Fengyan Zhou and  Yansong Zhang, et al. "Changes in soil organic carbon and its influencing factors in the growth of pinus sylvestris var. mongolica plantation in horqin sandy land, northeast China."Sci Rep 9 (2019): 16453.

   Google Scholar, Crossref, Indexed at

3. Fathololoumi, Solmaz, Ali Reza Vaezi, Seyed Kazem Alavipanah and Ardavan Ghorbani, et al. "Improved digital soil mapping with multitemporal remotely sensed satellite data fusion: A case study in Iran."Sci Total Environ 721 (2020): 137703.

   Google Scholar, Crossref, Indexed at

4. Kemper, Thomas and Stefan Sommer. "Estimate of heavy metal contamination in soils after a mining accident using reflectance spectroscopy."Environ Sci Technol 36 (2002): 2742-2747.

   Google Scholar, Crossref, Indexed at

5. Wang, Bin, Cathy Waters, Susan Orgill and Jonathan Gray, et al. "High resolution mapping of soil organic carbon stocks using remote sensing variables in the semi-arid rangelands of eastern Australia."Sci Total Environ 630 (2018): 367-378.

   Google Scholar, Crossref, Indexed at