Assessment of soil compaction and rutting in managed forests through an airborne LiDAR technique

• Published in: Land degradation & development 2023-03, Vol.34 (5), p.1558-1569
• Main Authors: Mohieddinne, Hamza, Brasseur, Boris, Gallet‐Moron, Emilie, Lenoir, Jonathan, Spicher, Fabien, Kobaissi, Ahmad, Horen, Hélène
• Format: Article
• Language: English
• Subjects: airborne LiDAR; Aquatic plants; Environmental monitoring; Flowers & plants; Forest management; Forests; Lidar; Life Sciences; Logging; Plant species; Plants (botany); Quality assessment; remote sensing; Sampling designs; Soil chemistry; Soil compaction; soil compaction and rutting; Soil management; Soil pH; Soil properties; Soil texture; Species composition; species response curves; Sustainability management; Sustainable forestry; Terrain models; Texture; Understory
• ISSN: 1085-3278; 1099-145X
• DOI: 10.1002/ldr.4553

To ensure sustainable forest management, the assessment and monitoring of soil compaction and rutting are essential. Here, we used airborne light detection and ranging‐derived digital terrain model (LiDAR‐derived DTM), available for the forest of Compiègne in northern France, to compute a spatial index of soil rutting. Following an environmental systematic sampling design, we selected 45 plots representative of the forest stand conditions where we subsequently extracted information from the DTM to compute the cumulative length of ruts (CLR). To assess the quality of this LiDAR‐derived index, we related the CLR index to in‐situ soil and vegetation parameters such as soil texture, soil pH, and understory plant species composition. Floristic surveys were carried out across all 45 plots to generate plant species response curves along the CLR gradient. We found soil texture, soil type, and soil pH to be important determinants of CLR. For instance, CLR was the highest in soils with the highest clay content. A total of 22 out of the 94 understory plant species we analyzed showed a significant response curve along the CLR gradient. Most important, the occurrence probability of species associated with wet soils and stagnant waters (e.g., Juncus effusus), like those found in ruts, increased with CLR. Other species associated with dry soils (e.g., Hedera helix) showed a negative response curve along the CLR gradient. In conclusion, the proposed index (CLR) has proven useful to remotely assess soil compaction and rutting after logging operations.