Design of terrace drainage networks using UAV-based high-resolution topographic data

Hillslope viticulture has a long history in Mediterranean Europe, and still holds important cultural and economic value. Steep hillsides have widely been levelled by terraces, in order to control surface water flow and facilitate cultivation. However, under unsustainable management and growing rainfall aggressiveness, terraced vineyards have become one of the most erosion-prone agricultural landscapes. The Valcamonica valley in Lombardy (Italy) presents a typical example of an ancient wine production region where rural land abandonment has previously caused widespread degradation of the traditional terracing systems. Recently, a local revival of wine production led to restoration plans of the terraces and their drainage functioning, to safeguard productivity and hydrogeologic safety. In this study, an Unmanned Aerial Vehicle (UAV) survey was carried out to reconstruct an accurate and precise 3D terrain model of a Valcamonica vineyard. through photogrammetry. The resulting high-resolution topographic data allowed insights of surface flow-induced soil erosion patterns based on the Relative Path Impact Index (RPII). Three diverse drainage networks were designed and digitally implemented, allowing scenario analysis of the costs and benefits in terms of potential erosion mitigation. The presented methodology could likely improve the time-efficiency and cost-effectiveness of similar restoration plans in degraded landscapes

Multi-Temporal Image Co-Registration Of Uav Blocks: A Comparison Of Different Approaches

Traditionally, data co-registration of survey epochs in photogrammetry relied on Ground Control Points (GCP) to keep the reference system unchanged. In the last years, Unmanned Aerial Systems (UAV) are increasingly used in photogrammetric environmental monitoring. The diffusion of affordable UAV platforms equipped with GNSS (Global Navigation Satellite System) centimetre-grade receivers might reduce, but not eliminate, the need for GCP. Conversely, if GNSS-assisted orientation cannot be used or if additional ground control and reliability checks are required, alternatives to repeated GCP survey have been proposed, taking advantage of Structure from Motion (SfM) photogrammetry. In particular, co-registering different epochs image blocks together, identifying corresponding features, has been demonstrated as a viable and efficient approach. In this paper four different strategies easily implementable in a generic commercial photogrammetric software are presented and compared considering three different test sites in Italy subject to different amounts of environmental changes. The influence of the amount and distribution of inter-epoch corresponding points on the accuracy of the reconstruction is investigated. The results show that some of the tested strategies obtains very good results and can be used (although not needed) also in RTK centimetre-grade UAV surveys, leveraging the additional information coming from previous epochs survey to actually increase the survey accuracy and reliability

MULTI-TEMPORAL IMAGE CO-REGISTRATION OF UAV BLOCKS: A COMPARISON OF DIFFERENT APPROACHES

Abstract. Traditionally, data co-registration of survey epochs in photogrammetry relied on Ground Control Points (GCP) to keep the reference system unchanged. In the last years, Unmanned Aerial Systems (UAV) are increasingly used in photogrammetric environmental monitoring. The diffusion of affordable UAV platforms equipped with GNSS (Global Navigation Satellite System) centimetre-grade receivers might reduce, but not eliminate, the need for GCP. Conversely, if GNSS-assisted orientation cannot be used or if additional ground control and reliability checks are required, alternatives to repeated GCP survey have been proposed, taking advantage of Structure from Motion (SfM) photogrammetry. In particular, co-registering different epochs image blocks together, identifying corresponding features, has been demonstrated as a viable and efficient approach. In this paper four different strategies easily implementable in a generic commercial photogrammetric software are presented and compared considering three different test sites in Italy subject to different amounts of environmental changes. The influence of the amount and distribution of inter-epoch corresponding points on the accuracy of the reconstruction is investigated. The results show that some of the tested strategies obtains very good results and can be used (although not needed) also in RTK centimetre-grade UAV surveys, leveraging the additional information coming from previous epochs survey to actually increase the survey accuracy and reliability

UAV-Based Quantification of Dynamic Lahar Channel Morphology at Volcán de Fuego, Guatemala

This study quantified erosional and depositional processes for secondary lahars in Las Lajas drainage at Volcán de Fuego, Guatemala, during the rainy season from May to October 2021. Abundant pyroclastic material from ongoing eruptive activity is remobilized seasonally during heavy precipitation, which can impact infrastructure and populations living near Fuego. Our region of focus was in an agricultural zone 6 to 10 km from the summit, surveyed with an unoccupied aerial vehicle (UAV) quadcopter at monthly intervals. Imagery was processed into overlapping time-lapse structure from motion digital elevation models (DEMs). DEMs were differenced to find volumetric changes as a function of the channel flow path distance (quantified in 500 m sections) to track channel morphology changes over time. The largest measured volume changes were a 490 m3/day loss in the upper section (~6 km from summit) and a 440 m3/day gain in the lower sections (~10 km from summit). We discussed how the natural channel’s constriction and widening of Las Lajas in more distal sections control the behavior and stability of the stream evolution. Above the constriction, the channel is primarily downcutting and meandering within an old flood plain, which had been filled in by pyroclastic materials deposited by the June 2018 paroxysm

Multi-Sensor UAV Application for Thermal Analysis on a Dry-Stone Terraced Vineyard in Rural Tuscany Landscape

Italian dry-stone wall terracing represents one of the most iconic features of agricultural landscapes across Europe, with sites listed among UNESCO World Heritage Sites and FAO Globally Important Agricultural Heritage Systems (GIAHS). The analysis of microclimate modifications induced by alterations of hillslope and by dry-stone walls is of particular interest for the valuation of benefits and drawbacks of terraces cultivation, a global land management technique. The aim of this paper is to perform a thermal characterization of a dry-stone wall terraced vineyard in the Chianti area (Tuscany, Italy), to detect possible microclimate dynamics induced by dry-stone terracing. The aerial surveys were carried out by using two sensors, in the Visible (VIS) and Thermal InfraRed (TIR) spectral range, mounted on Unmanned Aerial Vehicles (UAVs), with two different flights. Our results reveal that, in the morning, vineyard rows close to dry-stone walls have statistically lower temperatures with respect to the external ones. In the afternoon, due to solar insulation, temperatures raised to the same value for each row. The results of this early study, jointly with the latest developments in UAV and sensor technologies, justify and encourage further analyses on local climatic modifications in terraced landscapes

VGC 2023 - Unveiling the dynamic Earth with digital methods: 5th Virtual Geoscience Conference: Book of Abstracts

Conference proceedings of the 5th Virtual Geoscience Conference, 21-22 September 2023, held in Dresden. The VGC is a multidisciplinary forum for researchers in geoscience, geomatics and related disciplines to share their latest developments and applications.:Short Courses 9 Workshops Stream 1 10 Workshop Stream 2 11 Workshop Stream 3 12 Session 1 – Point Cloud Processing: Workflows, Geometry & Semantics 14 Session 2 – Visualisation, communication & Teaching 27 Session 3 – Applying Machine Learning in Geosciences 36 Session 4 – Digital Outcrop Characterisation & Analysis 49 Session 5 – Airborne & Remote Mapping 58 Session 6 – Recent Developments in Geomorphic Process and Hazard Monitoring 69 Session 7 – Applications in Hydrology & Ecology 82 Poster Contributions 9

Volume estimation of soil stored in agricultural terrace systems : a geomorphometric approach

High-resolution topographic (HRT) techniques allow the mapping and characterization of geomorphological features with wide-ranging perspectives at multiple scales. We can exploit geomorphometric information in the study of the most extensive and common landforms that humans have ever produced: agricultural terraces. We can only develop an understanding of these historical landform through in-depth knowledge of their origin, evolution and current state in the landscape. These factors can ultimately assist in the future preservation of such landforms in a world increasingly affected by anthropogenic activities. From HRT surveys, it is possible to produce high-resolution Digital Terrain Models (DTMs) from which important geomorphometric parameters such as topographic curvature, to identify terrace edges can be extracted, even if abandoned or covered by uncontrolled vegetation. By using riser bases as well as terrace edges (riser tops) and through the computation of minimum curvature, it is possible to obtain environmentally useful information on these agricultural systems such as terrace soil thickness and volumes. The quantification of terrace volumes can provide new benchmarks for soil erosion models, new perspectives to stakeholders for terrace management in terms of natural hazard and offer a measure of the effect of these agricultural systems on soil organic carbon sequestration. This paper presents the realization and testing of an innovative and rapid methodological workflow to estimate the anthropogenic reworked and moved soil of terrace systems in different landscapes. We start with remote terrace mapping at large scale and then utilize more detailed HRT surveys to extract geomorphological features, from which the original theoretical slope-surface of terrace systems were derived. These last elements were compared with sub-surface information obtained from the excavations across the study sites that confirm the reliability of the methodology used. The results of this work have produced accurate DTMs of Difference (DoD) for three terrace sites in central Europe in Italy and Belgium. Differences between actual and theoretical terraces from DTM and excavation evidence have been used to estimate the soil volumes and masses used to remould slopes. The utilization of terrace and lynchet volumetric data, enriched by geomorphometric analysis through indices such as sediment conductivity provides a unique and efficient methodology for the greater understanding of these globally important landforms, in a period of increasing land pressure

Analyzing the Adoption, Cropping Rotation, and Impact of Winter Cover Crops in the Mississippi Alluvial Plain (MAP) Region through Remote Sensing Technologies

This dissertation explores the application of remote sensing technologies in conservation agriculture, specifically focusing on identifying and mapping winter cover crops and assessing voluntary cover crop adoption and cropping patterns in the Arkansas portion of the Mississippi Alluvial Plain (MAP). In the first chapter, a systematic review using the PRISMA methodology examines the last 30 years of thematic research, development, and trends in remote sensing applied to conservation agriculture from a global perspective. The review uncovers a growing interest in remote sensing-based research in conservation agriculture and emphasizes the necessity for further studies dedicated to conservation practices. Among the 68 articles examined, 94% of studies utilized a pixel-based classification method, while only 6% employed an object-based approach. The analysis also revealed a thematic shift over time, with tillage practices being extensively studied before 2005, followed by a focus on crop residue from 2004 to 2012. From 2012 to 2020, there was a renewed emphasis on cover crops research. These findings highlight the evolving research landscape and provide insights into the trends within remote sensing-based conservation agriculture studies. The second chapter presents a methodological framework for identifying and mapping winter cover crops. The framework utilizes the Google Earth Engine (GEE) and a Random Forest (RF) classifier with time series data from Landsat 8 satellite. Results demonstrate a high classification accuracy (97.7%) and a significant increase (34%) in model-predicted cover crop adoption over the study period between 2013 and 2019. Additionally, the study showcases the use of multi-year datasets to efficiently map the growing season\u27s length and cover crops\u27 phenological characteristics. The third chapter assesses the voluntary adoption of winter cover crops and cropping patterns in the MAP region. Remote sensing technologies, USDA-NRCS government cover crop data sources, and the USDA Cropland Data Layer (CDL) are employed to identify cover crop locations, analyze county-wide voluntary adoption, and cropping rotations. The result showed a 5.33% increase in the overall voluntary adoption of cover crops in the study region between 2013 and 2019. The findings also indicate a growing trend in cover crop adoption, with soybean-cover crop rotations being prominent. This dissertation enhances our understanding of the role of remote sensing in conservation agriculture with a particular focus on winter cover crops. These insights are valuable for policymakers, stakeholders, and researchers seeking to promote sustainable agricultural practices and increased cover crop adoption. The study also underscores the significance of integrating remote sensing technologies into agricultural decision-making processes and highlights the importance of collaboration among policymakers, researchers, and producers. By leveraging the capabilities of remote sensing, it will enhance conservation agriculture contribution to long-term environmental sustainability and agricultural resilience. Keywords: Remote sensing technologies, Conservation agriculture, Winter cover crops, Voluntary adoption, Cropping patterns, Sustainable agricultural practice

Analyzing the Adoption, Cropping Rotation, and Impact of Winter Cover Crops in the Mississippi Alluvial Plain (MAP) Region through Remote Sensing Technologies

This dissertation explores the application of remote sensing technologies in conservation agriculture, specifically focusing on identifying and mapping winter cover crops and assessing voluntary cover crop adoption and cropping patterns in the Arkansas portion of the Mississippi Alluvial Plain (MAP). In the first chapter, a systematic review using the PRISMA methodology examines the last 30 years of thematic research, development, and trends in remote sensing applied to conservation agriculture from a global perspective. The review uncovers a growing interest in remote sensing-based research in conservation agriculture and emphasizes the necessity for further studies dedicated to conservation practices. Among the 68 articles examined, 94% of studies utilized a pixel-based classification method, while only 6% employed an object-based approach. The analysis also revealed a thematic shift over time, with tillage practices being extensively studied before 2005, followed by a focus on crop residue from 2004 to 2012. From 2012 to 2020, there was a renewed emphasis on cover crops research. These findings highlight the evolving research landscape and provide insights into the trends within remote sensing-based conservation agriculture studies. The second chapter presents a methodological framework for identifying and mapping winter cover crops. The framework utilizes the Google Earth Engine (GEE) and a Random Forest (RF) classifier with time series data from Landsat 8 satellite. Results demonstrate a high classification accuracy (97.7%) and a significant increase (34%) in model-predicted cover crop adoption over the study period between 2013 and 2019. Additionally, the study showcases the use of multi-year datasets to efficiently map the growing season\u27s length and cover crops\u27 phenological characteristics. The third chapter assesses the voluntary adoption of winter cover crops and cropping patterns in the MAP region. Remote sensing technologies, USDA-NRCS government cover crop data sources, and the USDA Cropland Data Layer (CDL) are employed to identify cover crop locations, analyze county-wide voluntary adoption, and cropping rotations. The result showed a 5.33% increase in the overall voluntary adoption of cover crops in the study region between 2013 and 2019. The findings also indicate a growing trend in cover crop adoption, with soybean-cover crop rotations being prominent. This dissertation enhances our understanding of the role of remote sensing in conservation agriculture with a particular focus on winter cover crops. These insights are valuable for policymakers, stakeholders, and researchers seeking to promote sustainable agricultural practices and increased cover crop adoption. The study also underscores the significance of integrating remote sensing technologies into agricultural decision-making processes and highlights the importance of collaboration among policymakers, researchers, and producers. By leveraging the capabilities of remote sensing, it will enhance conservation agriculture contribution to long-term environmental sustainability and agricultural resilience. Keywords: Remote sensing technologies, Conservation agriculture, Winter cover crops, Voluntary adoption, Cropping patterns, Sustainable agricultural practice

Historical Channel Change Caused by a Century of Flow Alteration on Sixth Water Creek and Diamond Fork River, UT

Changes in the amount of water and sediment that enter a river can change its shape and size. The way that rivers change is affected by a variety of factors, including the size of the sediment in the river, and past changes to the river. The Diamond Fork River in central Utah has been altered by water deliveredfromthe Colorado River system for over a century. Beginning in 1915, water used for irrigation was delivered through a tributary, Sixth Water Creek, with daily summer flows that were much larger than natural flows. This caused drastic change to the rivers, as they became wider and vegetation along the channel margin and floodplain was destroyed. Management changes in 1997 and 2004 reduced the amount of water and sediment added to the river. In this study, we sought to understand how Sixth Water and Diamond Fork changed in the past and what the implications are for the future. We used data from a variety of sources to describe how and why the river changed in the past. Our results indicate that parts of the river that are not confined by valley walls became very wide during the period of elevated flows and narrowed after the change in management in 1997. Confined reaches experienced minor changes over the period of record. Areas of the channel that were most dynamic in the past are the most susceptible to future change because they have finer sediment that is more easily erodible. Areas that did not experience past changes are unlikely to change in the future without direct intervention from humans or beaver. The findings of this study improve our understanding of Sixth Water and Diamond Fork, and confirm the importance of past changes and valley confinement