The agricultural impact of the 2015–2016 floods in Ireland as mapped through Sentinel 1 satellite imagery

peer-reviewedIrish Journal of Agricultural and Food Research | Volume 58: Issue 1 The agricultural impact of the 2015–2016 floods in Ireland as mapped through Sentinel 1 satellite imagery R. O’Haraemail , S. Green and T. McCarthy DOI: https://doi.org/10.2478/ijafr-2019-0006 | Published online: 11 Oct 2019 PDF Abstract Article PDF References Recommendations Abstract The capability of Sentinel 1 C-band (5 cm wavelength) synthetic aperture radio detection and ranging (RADAR) (abbreviated as SAR) for flood mapping is demonstrated, and this approach is used to map the extent of the extensive floods that occurred throughout the Republic of Ireland in the winter of 2015–2016. Thirty-three Sentinel 1 images were used to map the area and duration of floods over a 6-mo period from November 2015 to April 2016. Flood maps for 11 separate dates charted the development and persistence of floods nationally. The maximum flood extent during this period was estimated to be ~24,356 ha. The depth of rainfall influenced the magnitude of flood in the preceding 5 d and over more extended periods to a lesser degree. Reduced photosynthetic activity on farms affected by flooding was observed in Landsat 8 vegetation index difference images compared to the previous spring. The accuracy of the flood map was assessed against reports of flooding from affected farms, as well as other satellite-derived maps from Copernicus Emergency Management Service and Sentinel 2. Monte Carlo simulated elevation data (20 m resolution, 2.5 m root mean square error [RMSE]) were used to estimate the flood’s depth and volume. Although the modelled flood height showed a strong correlation with the measured river heights, differences of several metres were observed. Future mapping strategies are discussed, which include high–temporal-resolution soil moisture data, as part of an integrated multisensor approach to flood response over a range of spatial scales

Riverine flooding using GIS and remote sensing

Floods are caused by extreme meteorological and hydrological changes that are influenced directly or indirectly by human activities within the environment. The flood trends show that floods will reoccur and shall continue to affect the livelihoods, property, agriculture and the surrounding environment. This research has analyzed the riverine flood by integrating remote sensing, Geographical Information Systems (GIS), and hydraulic and/or hydrological modeling, to develop informed flood mapping for flood risk management. The application of Hydrological Engineering Center River Analysis System (HEC RAS) and HEC HMS models, developed by the USA Hydrologic Engineering Center of the Army Corps of Engineers in a data-poor environment of a developing country were successful, as a flood modeling tools in early warning systems and land use planning. The methodology involved data collection, preparation, and model simulation using 30m Shuttle Radar Topographic Mission (SRTM) Digital Elevation Model (DEM) as a critical data input of HEC RAS model. The findings showed that modeling using HEC-RAS and HEC HMS models in a data-poor environment requires intensive data enhancements and adjustments; multiple utilization of open sources data; carrying out multiple model computation iterations and calibration; multiple field observation, which may be constrained with time and resources to get reasonable output

A Model for Evaluating Soil Vulnerability to Erosion Using Remote Sensing Data and A Fuzzy Logic System

Soil vulnerability is the capacity of one or more of the ecological functions of the soil system to be harmed. It is a complex concept which requires the identification of multiple environmental factors and land management at different temporal and space scales. The employment of geospatial information with good update capabilities could be a satisfactory tool to assess potential soil vulnerability changes in large areas. This chapter presents the application of two land degradation case studies which is simple, synoptic, and suitable for continuous monitoring model based on the fuzzy logic. The model combines topography and vegetation status information to assess soil vulnerability to land degradation. Topographic parameters were obtained from digital elevation models (DEM), and vegetation status information was derived from the computation of the normalized difference vegetation index (NDVI) satellite images. This spectral index provides relevance and is updated for each scene, evidences about the biomass and soil productivity, and vegetation density cover or vegetation stress (e.g., forest fires, droughts). Modeled output maps are suitable for temporal change analysis, which allows the identification of the effect of land management practices, soil and vegetation regeneration, or climate effects

Spatial Dimensions of Tower Karst and Cockpit Karst: A Case Study of Guilin, China

Tower karst (fenglin) and cockpit karst (fengcong) are two globally important representative styles of tropical karst. Previously proposed sequential and parallel development models are preliminary, and geomorphological studies to date do not provide enough satisfactory evidence to delineate the spatial and temporal relation between the two landscapes. This unclear interpretation of tower-cockpit relationships not only obscures understanding of the process-form dynamics of these tropical karst landforms, but also confuses their definition. Moreover, previous technological limitations, as well as the fragmental nature of the karst landscapes, has limited incorporation of geologic and other data into broad geospatial frameworks based on geographic information science (GIS) and remote sensing (RS), with such data being spatially and temporally disparate. This study incorporates various data sources to address the fenglin-fengcong relationship, particularly the recently postulated edge effect , which has not been examined in detail previously and which may hinge upon the interaction of multiple environmental variables, including geomorphology, vegetation and hydrology. To address these issues, this research combines geographic, geologic and hydrologic data, using GIS and RS technologies to test quantitatively the edge effect hypothesis. Specifically, there are four inter-related objectives of this study. The first is to develop a method to effectively differentiate fenglin and fengcong. The second is to extract optimally the vegetation information from satellite imagery, and investigate the correlation between tropical karst topography and its vegetation. The third is to combine the regional hydrologic data and solute transport models to estimate geochemicals control of fenglin and fengcong. The fourth one, perhaps the most important, is to test the edge effect hypothesis using the results from the other three objectives. There are several significant conclusions. First, DEM data are very useful for extracting profiles of complex surface landforms from satellite imagery. Second, the vegetation distribution varies between tower karst and cockpit karst and the differences correlate with topographic characteristics. The under-representation of vegetation on the south-southwest aspect of tower karst is remarkable, and its overall distribution is both less abundant and dispersed than in cockpit karst. Third, the edge effect exists in the Guilin area, with variable intensity and extension in different dimensions. In summary, the major contributions of the study include the following. First, the study has developed a method to classify fenglin-fengcong tropical karst effectively, even with the presence of shadows that would otherwise hinder traditional classification. Second, the study showed a variance of vegetation vitality within aspects of fenglin that might relate to its geomorphic difference from fengcong. Third, the study combined groundwater and solute transport models to estimate bicarbonate distributions, representing a novel systematic and quantitative approach to tropical karst studies

Inundações em múltiplas escalas na América do Sul : de áreas úmidas a áreas de risco

South America hosts some of the major river systems on Earth, often associated with large floodplains that are inundated every year, such as the Pantanal and many Amazon wetlands. Interfluvial wetland complexes are also found across the continent, with particular geomorphic settings and unique savanna or grassland vegetation. South American wetlands can provide distinctive ecosystem services such as biodiversity supporting, food provision and flood attenuation. On the other hand, humans have settled around wetlands for millennia, benefiting from all resources they provide, and have adapted to its flood regime as well adapted its landscape, defining what has been called human-water systems. Yet, an increasing number of South American people have been negatively affected by extreme floods. Moving from continental to local scales, this thesis invites the readers to a journey across major South American wetland systems and their unique hydrological dynamics, under the light of the satellite era and the breakthrough advances on hydrologic-hydrodynamic modeling in the last decades. This work is founded on the proposition of a continental wetland research agenda, and based on a comparative hydrology approach. Floods are studied through both natural wetland processes and hazard dimensions. The first part presents a set of studies on the Amazon basin wetlands, from the development of 1D and 2D models to simulate hydrological processes in contrasting wetland types in the Negro river basin to the basin-wide intercomparison of 29 inundation products and assessment of long-term inundation trends. While most wetland studies have been conducted over the central Amazon floodplains, major knowledge gaps remain for understanding the hydrological dynamics of interfluvial areas such as the Llanos de Moxos and Negro savannas, where the inundation is less predictable and shallower. The second part of the thesis leverages satellite-based datasets of multiple hydrological variables (water levels, total water storage, inundation extent, precipitation and evapotranspiration) to address the hydrology of 12 large wetland systems in the continent. It shows the major differences among river floodplains and interfluvial wetlands on the water level annual amplitude, time lag between precipitation and inundation, and evapotranspiration dynamics. Finally, the third part addresses the flood hazard component of human-wetland interactions through large-scale assessments of flood hazard dynamics and effects of built infrastructure (dams) on flood attenuation. The dynamics of the great 1983 floods, one of the most extreme years ever recorded in the continent, is assessed with a continental hydrological model. Then, the capabilities of continental models to simulate the river-floodplain-reservoir continuum that exists across large river basins are assessed with case studies for major river basins affected by human intervention (Itajaí-Açu and upper Paraná river basins in Brazil). While this thesis enlightens some relevant hydrological processes regarding South American floods and their positive and negative effects to human societies and ecosystems in general, major knowledge gaps persist and provide great research opportunities for the near future. The launching of many hydrology-oriented satellite missions, and an ever-growing computational capacity, make the continental hydrology agenda related to wetlands and floods a great research topic for the upcoming years.A América do Sul abriga alguns dos maiores sistemas hídricos do planeta, frequentemente associados a grandes planícies de inundação, como o Pantanal e várias áreas da Amazônia. Áreas úmidas (AU’s) interfluviais são também encontrados no continente, com características geomorfológicas particulares, e vegetações de savana e gramíneas únicas. As AU’s da América do Sul provêm diversos serviços ecossistêmicos, como suporte à biodiversidade, provisão de alimento e atenuação de cheias. Humanos têm se estabelecido ao redor de AU’s por milênios, se beneficiando dos recursos providos por elas. Eles se adaptaram ao seu regime de inundação, e adaptaram sua paisagem, definindo o que tem sido chamado de sistemas sociedade-água. Por outro lado, um número crescente de pessoas têm sido negativamente afetado por cheias extremas. Da escala continental à local, esta tese convida o leitor a uma jornada através de importantes AU’s da América do Sul e suas particulares dinâmicas de inundação, sob a luz da era dos satélites e dos grandes avanços em modelagem hidrológica-hidrodinâmica das últimas décadas. Este trabalho é baseado na proposta de uma escala continental de pesquisa sobre AU’s, e é baseado em uma abordagem de hidrologia comparativa. Inundações são estudadas em múltiplas dimensões, de processos de AU’s naturais à questão do perigo para humanos. A primeira parte apresenta uma série de estudos sobre as AU’s da bacia amazônica, desde o desenvolvimento de modelos 1D e 2D para simular processos hidrológicos em tipos contrastantes de AU’s na bacia do Rio Negro, até a intercomparação de 29 produtos de inundação e avaliação de tendências de inundações de longo prazo para a escala da bacia amazônica. Enquanto a maioria dos estudos de AU’s foi conduzida nas várzeas do rio Amazonas, importantes lacunas do conhecimento permanecem para a compreensão da dinâmica hidrológica de áreas interfluviais como Llanos de Moxos e as savanas do rio Negro, onde a inundação é menos previsível e mais rasa. A segunda parte da tese utiliza dados oriundos de satélites relacionados a múltiplas variáveis hidrológicas (níveis d’água, armazenamento total de água, extensão de áreas inundadas, precipitação e evapotranspiração) para estudar a hidrologia de 12 grandes sistemas de AU’s do continente. São destacadas as grandes diferenças entre planícies de inundação e AU’s interfluviais em termos de amplitude anual de níveis d’água, defasagem entre precipitação e inundação, e dinâmica de evapotranspiração. Por fim, a última parte da tese aborda o componente de perigo de inundação das interações sociedade-água através de avaliações em grande escala da dinâmica de inundação e dos efeitos de infraestruturas construídas (como barragens) na atenuação de cheias. A dinâmica das grandes cheias de 1983, um dos anos mais extremos já registrados no continente, é avaliada com um modelo hidrológico continental. Depois, a capacidade de modelos continentais para simular o continuum entre rios, planícies de inundação e reservatórios que existe em grandes bacias hidrográficas é avaliada com estudos de casos para importantes bacias afetadas pela intervenção humana (bacia dos rios Paraná e Itajaí-Açu). Enquanto esta tese avança a compreensão de relevantes processos hidrológicos relacionados a inundações na América do Sul em múltiplas escalas, bem como seus efeitos positivos e negativos nas sociedades humanas e ecossistemas em geral, importantes lacunas do conhecimento persistem e fomentam importantes oportunidades de pesquisa futuras. O lançamento de várias missões satelitais orientadas a hidrologia, e uma cada vez mais crescente capacidade computacional, faz da agenda continental de hidrologia relacionada a AU’s e inundações um grande tópico de pesquisa para os próximos anos

Cybergis-enabled remote sensing data analytics for deep learning of landscape patterns and dynamics

Mapping landscape patterns and dynamics is essential to various scientific domains and many practical applications. The availability of large-scale and high-resolution light detection and ranging (LiDAR) remote sensing data provides tremendous opportunities to unveil complex landscape patterns and better understand landscape dynamics from a 3D perspective. LiDAR data have been applied to diverse remote sensing applications where large-scale landscape mapping is among the most important topics. While researchers have used LiDAR for understanding landscape patterns and dynamics in many fields, to fully reap the benefits and potential of LiDAR is increasingly dependent on advanced cyberGIS and deep learning approaches. In this context, the central goal of this dissertation is to develop a suite of innovative cyberGIS-enabled deep-learning frameworks for combining LiDAR and optical remote sensing data to analyze landscape patterns and dynamics with four interrelated studies. The first study demonstrates a high-accuracy land-cover mapping method by integrating 3D information from LiDAR with multi-temporal remote sensing data using a 3D deep-learning model. The second study combines a point-based classification algorithm and an object-oriented change detection strategy for urban building change detection using deep learning. The third study develops a deep learning model for accurate hydrological streamline detection using LiDAR, which has paved a new way of harnessing LiDAR data to map landscape patterns and dynamics at unprecedented computational and spatiotemporal scales. The fourth study resolves computational challenges in handling remote sensing big data and deep learning of landscape feature extraction and classification through a cutting-edge cyberGIS approach

Flood Prediction and Mitigation in Data-Sparse Environments

In the last three decades many sophisticated tools have been developed that can accurately predict the dynamics of flooding. However, due to the paucity of adequate infrastructure, this technological advancement did not benefit ungauged flood-prone regions in the developing countries in a major way. The overall research theme of this dissertation is to explore the improvement in methodology that is essential for utilising recently developed flood prediction and management tools in the developing world, where ideal model inputs and validation datasets do not exist. This research addresses important issues related to undertaking inundation modelling at different scales, particularly in data-sparse environments. The results indicate that in order to predict dynamics of high magnitude stream flow in data-sparse regions, special attention is required on the choice of the model in relation to the available data and hydraulic characteristics of the event. Adaptations are necessary to create inputs for the models that have been primarily designed for areas with better availability of data. Freely available geospatial information of moderate resolution can often meet the minimum data requirements of hydrological and hydrodynamic models if they are supplemented carefully with limited surveyed/measured information. This thesis also explores the issue of flood mitigation through rainfall-runoff modelling. The purpose of this investigation is to assess the impact of land-use changes at the sub-catchment scale on the overall downstream flood risk. A key component of this study is also quantifying predictive uncertainty in hydrodynamic models based on the Generalised Likelihood Uncertainty Estimation (GLUE) framework. Detailed uncertainty assessment of the model outputs indicates that, in spite of using sparse inputs, the model outputs perform at reasonably low levels of uncertainty both spatially and temporally. These findings have the potential to encourage the flood managers and hydrologists in the developing world to use similar data sets for flood management

Modeling the role of reservoirs versus floodplains on large-scale river hydrodynamics

Large-scale hydrologic–hydrodynamic models are powerful tools for integrated water resources evaluation at the basin scale, especially in the context of flood hazard assessment. However, recent model developments have paid little attention to simulate reservoirs’ hydrodynamics within river networks. This study presents an adaptation of the MGB model to simulate reservoirs as an internal boundary condition, enabling the explicit simulation of hydrodynamic processes along reservoirs and their interaction with upstream and downstream floodplains in large basins. A case study is carried out in the Itajaí-Açu River Basin in Brazil, which has periodic flood-related disasters and three flood control dams. The model was calibrated for the 1950–2016 period forced with daily observed precipitation. The adjustment was satisfactory, with Nash–Sutcliffe metrics between 0.54 and 0.84 for the 11 gauges analyzed and with flood frequency curves also well represented. Simulation scenarios with and without floodplains and reservoirs were performed to evaluate the relative role of these factors on flood control basin-wide through evaluation of simulated discharges, water levels and flood extent. Itajaí do Oeste tributary and Itajaí-Açu mainstem present major floodplain attenuation, while in Itajaí do Sul and Itajaí do Norte tributaries the main flood control occurs due to reservoir attenuation. Downstream from the dams, results indicated that the reservoirs reach their maximum discharge reduction capacity for 5- to 10-year floods, decreasing it for larger floods. The developed model may be very useful for operational uses as flood forecasting and coordinated reservoir operation studies, as well as to enhance the comprehension of flood dynamics at basin scale

Evaluating Wetland Expansion In A Tallgrass Prairie-Wetland Restoration

Remote sensing is an effective tool to inventory and monitor wetlands at large spatial scales. This study examined the effect of wetland restoration practices at Glacial Ridge National Wildlife Refuge (GRNWR) in northwest Minnesota on the distribution, location, size and temporal changes of wetlands. A Geographic Object-Based Image Analysis (GEOBIA) land cover classification method was applied that integrated spectral data, LiDAR elevation, and LiDAR derived ancillary data of slope, aspect, and TWI. Accuracy of remote wetland mapping was compared with onsite wetland delineation. The GEOBIA method produced land cover classifications with high overall accuracy (88 – 91 percent). Wetland area from a June 12, 2007 classified image was 20.09 km2 out of a total area of 147.3 km2. Classification of a July 22, 2014 image, showed wetlands covering an area of 37.96 km2. The results illustrate how wetland areas have changed spatially and temporally within the study landscape. These changes in hydrologic conditions encourage additional wetland development and expansion as plant communities colonize rewetted areas, and soil conditions develop characteristics typical of hydric soils