No abstract

Information about land cover is required for economic, agricultural and environmental policy making. Therefore, reliable up-to-date information is always called upon. In this study, we developed a new approach for land cover mapping based on the information of vegetation phenology. The main objective of this approach was to generate a land cover map of large cropland dominated area with high classification accuracy. Our approach consisted of two steps: first, we divided the study area into three land use groups depending on the phenology trend of cereals. Second, we applied a supervised classification for each group using the Maximum Likelihood Classifier and multi-date satellite images. Recent multi-temporal Landsat 8 images and field survey data were used for the classification process. To assess the robustness of this approach, a conventional supervised classification was performed using single date and multi-date images. Results indicated that the proposed approach is able to discriminate between different land cover types which have a similar spectral reflectance such as cereals, vegetables and pasture with high accuracy. The accuracy assessment showed very promising results with an overall accuracy of 86 % and a Kappa of 0.85 (good agreement) as compared to the single date (54-55 %) and the multi-date approach (78 %). Indeed, the application of this method provides accurate information for ecologists, hydrologists and the land development decision-makers. It can also improve the accuracy of environmental models that require high resolution land cover maps as input data.

The Joumine Dam located in northern Tunisia has lost more than 20% of its initial storage capacity due to sedimentation, meaning that sediment management is necessary. The sediments at the reservoir bottom act as a sink for nutrients and chemicals originating from the upper agricultural lands and take the form of suspended particles. We proposed that the dredged sediments could be used to amend arid to semiarid soils, as this would partially cover the financial burden of dredging works and reduce the volume of these deposits. However, to check the feasibility of using the sediments as a fertilizer, it was necessary to assess the potential health risks from contaminants in the sediments. Therefore, the present study aimed to evaluate the human health risk (i.e., the hazard quotient, HQ) from heavy metals consumed due to the ingestion of Bromus ramosus (wild oat) grown in soil amended with the Joumine Dam sediments. Plant growth was monitored in macrocosm (amendment rate of 1.17%) and microcosm (amendment rate ≤ 10%) bioassays to elucidate the metal concentrations in roots, stems, leaves, and seeds. Zn, Cu, and Mn concentrations were analyzed in the plants grown in the macrocosm experiments, while the follow-up was only performed for Zn in the plants grown in the microcosm experiments. The human exposure to soil pollutants (HESP) evaluation model was adopted to evaluate the health risk (HQ) to humans through direct and indirect oral exposure to heavy metals in wild oat. At the macrocosm scale, Cu was found to be the main source of risk (HQ = 1.86) to children. At the microcosm scale, utilization of the sediment reduced the mobility and bioavailability of copper in the soil, thus decreasing the potential health risk from this metal. Graphic abstract

As wood pieces supplied by landslides and debris flows are one of the main components of ecological and geomorphic systems, the importance of quantifying the dimensions of the wood pieces is evident. However, the low accessibility of disturbed channels after debris flows generally impedes accurate and quick wood-piece investigations. Thus, remote-sensing measurements for wood pieces are necessitated. Focusing on sub-watersheds in coniferous and broadleaf forests in Japan (the CF and BF sites, respectively), we measured the lengths of wood pieces supplied by landslides (> 0.2 m length and > 0.03 m diameter) from orthophotos acquired using a small unmanned aerial vehicle (UAV). The measurement accuracy was analyzed by comparing the lengths derived from the UAV method with direct measurements. The landslides at the CF and BF sites were triggered by extremely heavy rainfalls in 2017 and 2018, respectively. UAV flights were operated during February and September 2019 at the CF site and during November 2018 and December 2019 at the BF site. Direct measurements of wood pieces were carried out on the date of the respective second flight date in each site. When both ends of a wood piece are satisfactorily extracted from an orthophoto acquired by the UAV, the wood-piece lengths at the CF site can be measured with an accuracy of approximately ±0.5 m. At the BF site, most of the extracted lengths were shorter than the directly measured lengths, probably because the complex structures of the root wad and tree crown reduced the visibility. Most wood pieces were discharged from landslide scars at the BF site, but at the CF site, approximately 750 wood pieces remained in the landslide scars approximately 19 months after the landslide occurrence. The number of wood pieces in the landslide scars of the CF site increased with increasing landslide area, suggesting that some wood pieces can be left even if large landslides occur. The lengths and locations of the entrapped wood pieces at both sites were not significantly changed between the two UAV flight dates. However, during this period, the rainfall intensities around the CF site measured by the closest rain-gauge of the Japan Meteorological Agency reached their second highest values from 1976 to 2019, which exceeded the 30-year return period. This suggests that most of the entrapped wood pieces rarely migrated even under intense rainfall.

No abstract

As large wood (LW) supplied by landslides and debris flows is one of the main components of watershed ecosystems, the importance of quantifying the dimensions of the LW is evident. However, the low accessibility of disturbed channels after landslides and debris flows generally impedes accurate and quick LW investigations. Recent advances in photogrammetry techniques may overcome such issues. In this study, we used ortho-photographs acquired using a small unmanned aerial vehicle (UAV) to measure the lengths of LW (wood pieces > 0.2-m long and > 0.03-m diameter) entrapped mainly by closed-type check-dams. We focused on two channels that are located in coniferous and broadleaf forests and affected by two different landslides events. The measurement accuracy was analyzed by comparing the lengths derived from the UAV method with direct measurements. When the both ends of a piece LW are satisfactorily extracted from an ortho-photograph acquired via the UAV, the LW lengths of coniferous trees can be measured with an accuracy of approximately ±0.5 m. For broadleaf trees, most of the extracted lengths were shorter than the directly measured lengths, probably due to the low visibility arising from the complex structures of the root wad and the tree crown. Most LW pieces were discharged from landslide scars in the broadleaf forest, whereas approximately 750 LW pieces were left in the landslide scars of the coniferous forest. The number of LW pieces in the landslide scars increased with the increase in the landslide area, suggesting that some LW pieces can be left even if large landslides occur. There were no significant changes in the lengths or locations of the entrapped LW, at either site seven months after the first UAV flight. In the coniferous forests, the rainfall that triggered landslides in 2017 exceeded the 100-year return level, which was an abnormally intense rainfall. Although the 2019 rainfall event that occurred between UAV flights did not provide enough rainfall to trigger landslides, rainfall intensities with different durations reached the second-highest value from 1976 to 2019, exceeding the 30-year return period. This suggests that most of the entrapped LW rarely migrate even under extreme rainfall.

As wood pieces supplied by landslides and debris flows are one of the main components of ecological and geomorphic systems, the importance of quantifying the dimensions of the wood pieces is evident. However, the low accessibility of disturbed channels after landslides and debris flows generally impedes accurate and quick wood-piece investigations. Recent advances in photogrammetry techniques may overcome such issues. In this study, we used orthophotos acquired using a small unmanned aerial vehicle (UAV) to measure the lengths of wood pieces (> 0.2-m long and > 0.03-m diameter) entrapped mainly by check-dams. We focused on channels that are located in coniferous and broadleaf forests and affected by two different landslide events. The measurement accuracy was analyzed by comparing the lengths derived from the UAV method with direct measurements. When the both ends of a wood piece are satisfactorily extracted from an orthophoto acquired via the UAV, the wood-piece lengths of coniferous trees can be measured with an accuracy of approximately ±0.5 m. For broadleaf trees, most of the extracted lengths were shorter than the directly measured lengths, probably due to the low visibility arising from the complex structures of the root wad and tree crown. Most wood pieces were discharged from landslide scars in the broadleaf forest, whereas approximately 750 wood pieces were left in the landslide scars of the coniferous forest. The number of wood pieces in the landslide scars increased with the increase in the landslide area, suggesting that some wood pieces can be left even if large landslides occur. There were no significant changes in the lengths or locations of the entrapped wood pieces, at either site seven months after the first UAV flight. In the coniferous forests, the rainfall that triggered landslides in 2017 exceeded the 100-year return level, which was an abnormally intense rainfall. Although the 2019 rainfall event that occurred between UAV flights did not provide enough rainfall to trigger landslides, rainfall intensities with different durations reached the second-highest value from 1976 to 2019, exceeding the 30-year return period. This suggests that most of the entrapped wood pieces rarely migrate even under extreme rainfall.

<p>Precipitation extremes affect the landscape differently and often drive numerous landslides widespread with disparate densities and features. Revealing the factors that govern this spatial variability is critical for understanding landslide susceptibility and developing prediction models. To this end, examining the peculiarities of the triggering rainfall event at spatial and temporal scales emerges as a promising method. Here, we relied on radar gauge-analyzed (R/A) rainfall estimates (period > 30 years, spatial resolution ≈ 5 km) and a landslide inventory for studying the spatial relationship between rainfall anomalies and triggered landslide density. The landslide inventory counts more than 7,600 shallow landslides distributed in about 550 km<sup>2</sup> and triggered by an extreme rainfall event that hit the Kyushu area in southern Japan in July 2017. A total of 23 R/A cells with different landslide densities were identified from the landslide inventory. A standard period of 72 h (P<sub>std</sub>), where the cumulative rainfall during the triggering event is maximum, was used to evaluate the spatial rainfall peculiarities at short (1 – 24 h) and long (48 – 72) timescales. Subsequently, rainfall anomalies were discussed by plotting the mean intensities computed at multiple timescales within the P<sub>std</sub> in the intensity duration frequency (IDF) curves developed for each R/A cell. The spatial density of triggered landslides was strongly influenced by the rainfall intensities that exceeded the 100-years return levels at disparate timescales and demonstrated anomalies. More than 65 % of the triggered landslides were located in only three R/A cells. In these cells, rainfall intensities of the triggering event exceeded the 100-years return level at the various timescales (from short to long) within the P<sub>std</sub>, favoring numerous landslides of different geometric features. Rainfall intensities in cells with low landslide density reached the 100-years return levels at short timescales (3 – 24 h). However, this was not necessarily achieved in all low landslide density R/A cells. These preliminary results highlighted the spatial impacts of rainfall anomalies computed at multiple timescales on landslide densities and features and motivated further analysis.</p>