RESUMO
This paper introduces a comprehensive protocol leveraging open-access techniques to create small- to medium-scale 3D representations of the environment by using iPhone and iPad light detection and ranging (LiDAR). The protocol focuses on two capabilities of the iPhone LiDAR. The first capability is 3D modeling: iPhone LiDAR rapidly generates detailed indoor and outdoor 3D models, providing insights into object size, volume and geometry. The second capability is change detection: the 3D models created by the LiDAR sensor can be used for precise measurement of changes over time. Compared to other 3D topographic surveying methods, this method is rapid, high resolution, low cost and easy to use. The protocol outlines iPhone LiDAR scanning practices, model export and change detection. The expected results after executing the protocol are (i) a detailed 3D model of a small- to medium-sized object or area of interest and (ii) a distance point cloud revealing change between two point clouds of the same object or area between different times. The entire protocol can be conducted within 2 h by anyone with an iPhone with the LiDAR sensor and a computer. This protocol empowers scientists, students and community members conducting research with a cheap, easy-to-use method for addressing a range of questions and challenges, thus benefiting experts and the broader community.
RESUMO
Traditionally, topographic surveying in earth sciences requires high financial investments, elaborate logistics, complicated training of staff and extensive data processing. Recently, off-the-shelf drones with optical sensors already reduced the costs for obtaining a high-resolution dataset of an Earth surface considerably. Nevertheless, costs and complexity associated with topographic surveying are still high. In 2020, Apple Inc. released the iPad Pro 2020 and the iPhone 12 Pro with novel build-in LiDAR sensors. Here we investigate the basic technical capabilities of the LiDAR sensors and we test the application at a coastal cliff in Denmark. The results are compared to state-of-the-art Structure from Motion Multi-View Stereo (SfM MVS) point clouds. The LiDAR sensors create accurate high-resolution models of small objects with a side length > 10 cm with an absolute accuracy of ± 1 cm. 3D models with the dimensions of up to 130 × 15 × 10 m of a coastal cliff with an absolute accuracy of ± 10 cm are compiled. Overall, the versatility in handling outweighs the range limitations, making the Apple LiDAR devices cost-effective alternatives to established techniques in remote sensing with possible fields of application for a wide range of geo-scientific areas and teaching.
RESUMO
Soil erosion represents one of the most important processes of land degradation in the world and is considered a serious threat to the provision of food supply, to human health and to terrestrial ecosystems. In Europe, soil erosion by water and tillage is responsible for the loss of fertile topsoil and therefore productive land. Under Global Change scenarios climate and land use are expected to impact soil loss and sediment discharge rates distinctly in contrasting climatic regions, further influenced by tillage practices. Soil erosion modeling is a valuable tool to estimate future changes and elucidate opportunities to mitigate future threats to soil loss and crop yield, ultimately leading to the development of Best Management Practices (BMPs). In this study, future change of soil erosion processes under the IPCC Representative Concentration Pathways RCP2.6 and RCP6.0, as well as a conventional tillage (CT) and a reduced tillage (RT) practice are investigated in two small agricultural catchments in Europe under contrasting climate; Can Revull in Spain and Fugnitz in Austria. We applied GeoWEPP, the Geospatial Interface for the Water Erosion Prediction Project, to model these two agricultural catchments at a fine spatial resolution. We demonstrate that tillage practice, precipitation and runoff are driving factors for soil erosion at both locations. Furthermore, we illustrate that tillage practices have a greater effect on soil erosion than climate change scenarios. RT could reduce soil erosion by more than 75% compared to CT practices. Under RCP6.0, future changes in runoff, hillslope soil loss and sediment discharge would be greater compared to RCP2.6, with different responses depending on the investigated climatic region. Linking soil erosion models on a fine spatial scale and with different management practices to downscaled global circulation models, can provide valuable input for the development of future BMPs to reduce soil loss in agricultural landscapes.