High resolution three dimensional spatial patterns of soil organic carbon storage in eroding agricultural landscapes

Soil Organic Carbon (SOC) is the largest terrestrial pool of carbon (1500Gt), and is an important factor controlling overall soil quality. The quantification of SOC and its change over time is crucial in a context of climate change and concerns about soil fertility. Current methods to assess SOC changes, however, pose some important limitations to our ability to accurately assess SOC dynamics in a spatial and temporal context. The overall aim of this thesis was therefore to improve our capability to assess 3D SOC storage patterns at spatial high resolution and to improve our understanding of the impact of soil movement on SOC storage in an agro-ecosystem. In this thesis, we developed and evaluated a method to predict the vertical SOC profile at a high resolution in a landscape affected by erosion. We show that the surface SOC content is related to soil redistribution processes whereas the shape of the vertical distribution is influenced by the soil moisture and temperature. In a second phase, we developed and evaluated a procedure to measure the surface SOC content at very high resolution using low altitude aerial sensing systems (UAV’s). The method developed permits to map the surface SOC content of arable fields at a resolution of c. 10cm with an accuracy that is similar to those obtained under laboratory conditions. Furthermore, we assessed the potential of combining the UAV-based sensors with the soil profile depth assessments for quantifying the three dimensional SOC distribution. We showed that the remote sensing technique proposed here has a strong potential for 3D mapping due to the strong correlation between the topsoil and subsoil SOC content. However, further research using more performing sensors are needed to control for soil variability (i.e. clay content) that may interfere with the SOC content. Using these new methodologies, we then quantified and evaluated the impact of soil redistribution on three dimensional SOC patterns and its impact on the net C balance for the period 1997-2014. We showed that the texture was a key factor controlling the SOC pattern, but due to the high variability of the SOC and its slow evolution over the time, detecting significant changes was challenging. Nevertheless, our methodology allowed detecting a significant decrease in SOC stock for the topsoil in the eroding areas and an increase in SOC stock for the subsoil layers of stable areas. This analysis was consistent with model-based estimates of changes in SOC stocks in response to erosion and deposition. Finally, this work showed that it is important to further improve methodologies and tools to assess 3D SOC storage in order to obtain a solid SOC baseline when detecting changes in SOC storage. The improvements presented in this thesis provided a significant step in this direction. We conclude that this thesis has improved our understanding of the consequences of erosion on SOC dynamics, and this may provide a basis to manage these impacts to enhance soil fertility but also mitigate climate change.(SC - Sciences) -- UCL, 201

Traitement de la topographie LiDAR pour la spatialisation de variables pédologiques : application au site de Seuilly (Indre-et-Loire)

The ANR VMCS Landsoil project aims to evaluate the evolution of soils and soil properties under changing landscape structures and climate. ln this framework, this study aims to characterise soil depth and soil organic carbon (SOC) stocks in the Seuilly study area (France). A soil survey was undertaken to measure soil depth and SOC stocks each 15 cm to a depth of 105 cm. A high resolution DEM was constructed from a LiDAR topographie survey. The aim is to estimate the variables of interest from topographie parameters. Two DEM filtering methods were confronted: resampling and wavelet analysis. The results of these treatments indicate that wavelet analysis can efficiently extract morphologic features represented at various scales. Two statistical models (MART and MLR) were applied to estimate soil depth and SOC stocks. The best external validation for soil depth is obtained with MLR (R2=0.65 and RMSE = 36.5 cm) thus allowing a mapping of soil depth over the whole study area. Validation results are poor for SOC stocks although weil calibrated, and did not allow mapping. Despite the poor results for SOC stocks, soil depth results are encouraging and show the relevance of wavelet analysis applied to high resolution topographie data for the mapping of soil properties.Le projet ANR VMCS Landsoil a pour objectif de modéliser l'évolution des sols et de leurs propriétés sous l'effet des changements d'occupation des sols et de climat. Dans ce contexte, la présente étude a plus spécifiquement pour objectif de caractériser l'épaisseur des sols ainsi que les stocks de carbone organique sur le site d'étude de Seuilly (Indre-et-Loire). Une campagne d'échantillonnage pour les mesures d'épaisseurs de sols et de stock de carbone (mesuré tous les 15 cm jusqu'à 105 cm de profondeur) a été réalisée. Un MNT haute résolution a été construit à partir d'un levé topographique LiDAR. L'objectif est d'estimer les variables d'intérêt à partir de paramètres topographiques. Deux méthodes de traitement du MNT sont comparées : le ré-échantillonnage et le filtrage par ondelette. Les résultats de ces traitements montrent que le filtrage par ondelette permet d'extraire les formes du relief à différentes longueurs d'onde. Les résultats des traitements de la topographie sont intégrés dans deux types de modèles statistiques (Arbres de Régression Multiple Additifs et Régression Linéaire Multiple). La RLM permet d'obtenir les meilleurs résultats pour la spatialisation des épaisseurs de sols (R2 : 0.65, RMSE: 36,5 cm) pour la validation externe permettant ainsi une cartographie des épaisseurs de sols sur le site d'étude. Les résultats de validation pour les stocks totaux de carbone organique ne sont pas satisfaisants malgré une bonne calibration et il n'est pas possible de les spatialiser. Il est donc nécessaire d'adapter les méthodes de spatialisation pour ce second paramètre. Malgré des résultats peu satisfaisants pour les stocks de carbone organique, ceux obtenus pour l'estimation des épaisseurs de sols sont encourageants et montrent tout l'intérêt de l'emploi des méthodes de filtrage par ondelette des données topographiques pour l'estimation spatiale de variables pédologiques

High resolution mapping of soil organic carbon content at landscape scale by multi-band imagery

n/

Estimating temporal and spatial changes in soil organic carbon stocks and its controlling factors in moraine landscapes in Denmark

Assessing temporal changes in soil organic carbon (SOC) stocks is important when evaluating the SOC sequestration potential of soil management strategies. The monitoring of SOC stocks is challenging, particularly in eroding landscapes where erosion-induced changes in SOC stocks are superimposed on changes related to management. In this study we focused on the spatio-temporal variations of SOC in eroding cropland soils of the northeast of the peninsula of Jutland (Denmark) at field scale. We examined soil redistribution processes as control factors of SOC changes (ΔSOC) during a 16-year period by using soil data (both spatial and with depth) collected over two distinct periods in 1998 and 2014. Topographic changes between 1998 and 2014, derived from high resolution digital elevation models, were used to identify eroded, stable and depositional areas within the field. There was a predominance of soil loss, with 44% of the sampling points corresponding to eroded sites and 28% to depositional sites, while the remainder was considered as stable soils. Substantial erosion was detected and at the field scale, soil deposition equalled (29.7 ± 17.5 Mg ha−1 y−1) while soil erosion rates were lower with a mean of 25.8 ± 12.9 Mg ha−1 y−1. Comparing SOC stocks over the 16 year-period showed that on average, and when considering the whole soil profile, SOC contents and stocks were stable. However, this masked substantial dynamics that were related to erosion processes. Despite the occurrence of net soil erosion at the field scale, there was an overall increase in SOC storage of 1.88 Mg ha (SOC2014:SOC1998 ratio ≥ 1). Losses of SOC in topsoils (6%) and SOC gain (34%) in soil layers below the plough depth (25–45 cm) could be related to soil disturbances caused by tillage and the significant downward transport of topsoil SOC within the soil profile. Soil disturbances caused by tillage practices (i.e. soil management) and SOC transportation from topsoil to subsoil may be responsible for the downward movement of organic carbon and consequent SOC accumulation in subsoils. In addition the successive deposition and deep burial of SOC rich topsoils at depositional sites due to the effect of topography and slope position favours the enrichment of SOC in subsoils. It was estimated that as much as 11% of the sampling points changed from eroded to depositional sites and 15% of them varied from erosion to stable sites, and this might have favoured SOC accumulation. These results clearly show that understanding and quantifying soil redistribution processes is key to assess SOC temporal changes in agricultural soils. This is important to develop site-specific management strategies that improve SOC sequestration at local scale

Evaluating the performance of UAV photogrammetry with PPK positioning in topographic reconstruction and change-detection

ISSN:1029-7006ISSN:1607-796

Bedrock and soil resistivity mapping as a tool for characterizing soil thickness on cultivated hillslopes. A case study in Seuilly, SW Parisian Basin, France

International audienceSoil apparent electrical resistivity, or its converse soil conductivity, is a parameter commonly used to predict soil properties, such as porosity, water content, particle size, clay content... It has also been used for soil thickness mapping, but the resulting data can be misinterpreted, due to interrelationships between soil resistivity and the physical and chemical properties of soils, which may be related to the bedrock lithology. Soil thickness mapping using resistivity measurements thus gives results only when the bedrock is electrically homogeneous and presents a high resistivity contrast related to soil. It therefore appears necessary to precisely characterise the bedrock resistivity variability before interpreting soil resistivity measurements. In this study, the relationships between surficial apparent resistivities at different depths of investigation and soil thickness-defined as the summation of organo-mineral and structural (A+B) horizons-were tested to predict soil thickness over large areas. The study site corresponds to a 100 ha cultivated hillslope located near the village of Seuilly (SW Parisian Basin, France). It covers 3 types of the Upper Cretaceous sedimentary formations: (a) Lower and Middle Turonian white chalk, (b) Upper Turonian yellow sandy limestone and (c) decarbonated yellow sandy limestone enriched in clay by deep weathering. The site shows a wide range of soil thicknesses (from 0.3 m to more than 2 m in lynchets) due to the fragmentation by field limit networks. The resistivity of the bedrock was measured using an electromagnetic survey with an EM31 conductivity meter (Slingram method), which gives a large investigation depth (about 5m), making this instrument quite insensitive to soil variability. 35 electrical soundings were also performed along a transect covering 800 m from top to bottom of the hillslope, allowing the establishment of a 2D resistivity cross section of the bedrock. The resistivity of the soil was measured using an ARP (Automatic Resistivity Profiling) survey at 3 different depths of investigation (0.5, 1 and 2 m). Inside the study site, a 16 ha test zone representative of the whole site was chosen for the establishment of the soil thickness / resistivity correlations. Soil thickness was measured at 686 points thanks to manual augering. Soil resistivity was also measured directly on 241 soil augerings using a Wenner array and the results were compared to the ARP interpolated data. Finally, soil properties (particle size, organic carbon and carbonate content) were analysed at 248 points and compared to soil resistivity to assess the relationships between soil resistivity and each soil property. The electromagnetic survey results and the electrical soundings show that the 3 bedrock types are characterized by different resisitivity values. The Upper Turonian yellow sandy limestone presents the highest resistivity (50 to 100 ohm.m). In this area, soil thickness / resistivity correlation is good (R2=0.66), allowing high resolution digital soil thickness mapping from ARP measurements. The Lower and Middle Turonian white chalk presents lower resistivity values (20 to 50 ohm.m) and is electrically heterogeneous, making the soil thickness / resistivity correlation insufficient (R2=0.3) to map soil thickness correctly. However, the ARP mapping gives precise information on bedrock heterogeneities. Finally, the decarbonated yellow sandy limestone is characterized by low resistivity values (< 20 ohm.m) similar to soil resistivity, making impossible soil thickness prediction. In this area the ARP results seem more correlated with the soil particle size. These results shows the importance of characterising precisely the electrical response of the bedrock (variability and resistivity contrast related to soil) before using soil apparent resistivity as a tool for digital soil thickness mapping, and more generally for soil properties mapping

Soil Organic Carbon depth profiles in relation to topographic parameters

We have to understand the spatial dynamics (horizontally and vertically) of the store of the Soil Organic Carbon (SOC) to manage soil resource. At large scale, a broad range of parameters is typically required. But regarding a smaller scale the bedrock and soils types are more homogenous. This study aims to characterize the relation of the vertical distribution of SOC content and the topography at the farm scale. For that, we sampled 19 cores up to 1m depth in different topographical contexts. We measured by spectroscopy the SOC content each 3cm along the core to establish a high resolution vertical distribution which we summa-rized by fitting of a cubic function. We show that these parameters are well explained by the slope and curva-ture (mean R² c. 0.5 for all parameters). These correlations were used to map the SOC content at GlobalSoil-Map depth layers

UAS-based soil carbon mapping using VIS-NIR (480–1000nm) multi-spectral imaging: Potential and limitations

Traditional methods to assess the soil organic carbon (SOC) content based on soil sampling and analysis are time consuming and expensive, and the results are influenced by the sampling design. The aim of this study was to investigate the potential of UAS (Unmanned Aerial Systems) multi-spectral imagery (480-1000 nm) for estimating the SOC content in bare cultivated soils at a high spatial resolution (12 cm). We performed UAS analysis on the Hoosfield Spring Barley experiment at Rothamsted (UK) where adjacent plots with distinctly different SOC contents, due to different long-term management practices, provide a valuable resource to evaluate this approach. We acquired images (wavelength: 480-550-670-780-880-1000 nm) at an altitude of 120 m over an area of 2 ha using a multi-spectral camera mounted on an UAS. The high-resolution images captured small-scale variations at the soil surface (e.g. shadows, tillage and wheels marks). After a projection in new dimensions by a PCA, we calibrated a support vector machine regression using observations from conventional soil sampling and SOC measurements. The performance of the calibration had a R2 of 0.98 and a RMSE of 0.17%C. A cross-validation showed that the model was robust, with an average R2 of 0.95 and a RMSE of 0.21%. An external validation dataset was used to evaluate the predicted spatial patterns of SOC content and a good fit with an RMSE 0.26%C was obtained. Although this study shows that the methodology has a clear potential for use in precision agriculture or monitoring important soil properties following changes in management, we also identify and discuss its limitations and current shortcomings. © 2016 Elsevier B.V

Evaluating the potential of post-processing kinematic (PPK) georeferencing for UAV-based structure- from-motion (SfM) photogrammetry and surface change detection

Images captured by unmanned aerial vehicles (UAVs) and processed by structure-from-motion (SfM) photogrammetry are increasingly used in geomorphology to obtain high-resolution topography data. Conventional georeferencing using ground control points (GCPs) provides reliable positioning, but the geometrical accuracy critically depends on the number and spatial layout of the GCPs. This limits the time and cost effectiveness. Direct georeferencing of the UAV images with differential GNSS, such as PPK (post-processing kinematic), may overcome these limitations by providing accurate and directly georeferenced surveys. To investigate the positional accuracy, repeatability and reproducibility of digital surface models (DSMs) generated by a UAV–PPK–SfM workflow, we carried out multiple flight missions with two different camera–UAV systems: a small-form low-cost micro-UAV equipped with a high field of view (FOV) action camera and a professional UAV equipped with a digital single lens reflex (DSLR) camera. Our analysis showed that the PPK solution provides the same accuracy (MAE: ca. 0.02 m, RMSE: ca. 0.03 m) as the GCP method for both UAV systems. Our study demonstrated that a UAV–PPK–SfM workflow can provide consistent, repeatable 4-D data with an accuracy of a few centimeters. However, a few flights showed vertical bias and this could be corrected using one single GCP. We further evaluated different methods to estimate DSM uncertainty and show that this has a large impact on centimeter-level topographical change detection. The DSM reconstruction and surface change detection based on a DSLR and action camera were reproducible: the main difference lies in the level of detail of the surface representations. The PPK–SfM workflow in the context of 4-D Earth surface monitoring should be considered an efficient tool to monitor geomorphic processes accurately and quickly at a very high spatial and temporal resolution

Digital soil mapping on heterogeneous bedrock using electrical resistivity measurements

International audienceGeophysics is commonly used to predict soil parameters (e.g. soil thickness, soil constituents and properties) over large areas in addition to punctual information given by soil augering. Among the various geophysical tools, the methods based on electrical resistivity measurements give good results providing that the bedrock is homogeneous. However, in the case of heterogeneous bedrock, the resulting data can be misinterpreted, due to interrelationships between soil resistivity and some soil properties, which may be related to the bedrock lithology. In this study we use electric and electromagnetic methods to (1) map soil thickness over an area with heterogeneous bedrock and (2) assess the relationships between soil resistivity and some constituents of soils (contents in silt, sand, organic carbon and CaCO3). The study site corresponds to a 100 ha cultivated hillslope located in the SW Parisian Basin (France) and covering 3 types of the Upper Cretaceous sedimentary formations characterised by contrasted resistivity values. The resistivity of the bedrock was measured using an electromagnetic prospection with an EM31 conductivity meter and 44 electrical soundings, whereas soil resistivity was precisely known from an ARP (Automatic Resistivity Profiling) survey at 3 different depths of investigation. Soil thickness was measured at 650 points by manual augering, and soil analyses were performed at 248 points. Geostatistical analyses were tested to assess the relative influence of the different soil properties on the resistivity data for each bedrock type