Monitoring 40-Year Lake Area Changes of the Qaidam Basin, Tibetan Plateau, Using Landsat Time Series

Areal changes of high-altitude inland lakes on the Qaidam Basin (QB) of the Tibetan Plateau are reliable indicators of climate change and anthropogenic disturbance. Due to the physical difficulties to access, our knowledge of the spatial patterns and processes of climatic and human impacts on the Basin has been limited. Focusing on lake area changes, this study used long-term Landsat images to map the patterns of lakes and glaciers in 1977, 1990, 2000, and 2015, and to monitor the spatially explicit changes of lakes between 1977 and 2015. Results revealed that the total number of lakes (area \u3e 0.5 km2 ) increased by 18, while their total area expanded by 29.8%, from 1761.5 ± 88.1 km2 to 2285.9 ± 91.4 km2 . Meanwhile, glaciers have decreased in area by 259.16 km2 in the past four decades. The structural equation model (SEM) was applied to examine the integrative effects of natural and anthropogenic factors on lake area. Precipitation change exhibited the most significant influence on lake area in the QB from 1977 to 2000, while human activities also played an important role in the expansion of lakes in the QB in the period 2000–2015. In particular, extensive exploitation of salt lakes as mining resources resulted in severe changes in lake area and landscape. The continuously expanding salt lakes inundated the road infrastructure nearby, posing great threats to road safety. This study shed new light on the impacts of recent environmental changes and human interventions on lakes in the Qaidam Basin, which could assist policy-making for protecting the lakes and for strengthening the ecological improvement of this vast, arid basin

Dynamic Monitoring of the Largest Freshwater Lake in China Using a New Water Index Derived from High Spatiotemporal Resolution Sentinel-1A Data

Poyang Lake is the largest freshwater lake in China and is well known for its ecological function and economic importance. However, due to the influence of clouds, it is difficult to dynamically monitor the changes in water surface areas using optical remote sensing. To address this problem, we propose a novel method to monitor these changes using Sentinel-1A data. First, the Sentinel-1A water index (SWI) was built using a linear model and a stepwise multiple regression analysis method with Sentinel-1A and Landsat-8 imagery acquired on the same day. Second, water surface areas of Poyang Lake from 24 May 2015 to 14 November 2016 were extracted by the threshold method utilizing time-series SWI data with an interval of 12 days. The results showed that the SWI threshold classification method could be applied to different regions during different periods with high quantity accuracy (approximately 99%). The water surface areas ranged between 1726.73 km2 and 3729.19 km2 during the study periods, indicating an extreme variability in the short term. The maximum and average values of the changed areas were 875.57 km2 (with a change rate of 35%) and 197.58 km2 (with a change rate of 8.2%), respectively, after 12 days. The changes in the mid-western region of Poyang Lake were more dramatic. These results provide baseline data for high-frequency monitoring of the ecological environment and wetland management in Poyang Lake

Mapeamento da dinâmica fluvial na Volta Grande do Xingu por meio de imagens multitemporais do satélite Sentinel-1

Dissertação (mestrado)—Universidade de Brasília, Instituto de Ciências Humanas, Departamento de Geografia, Programa de Pós-graduação, 2019.As áreas inundáveis na região da Volta Grande do Xingu, Pará, têm sido intensamente pressionadas e degradadas devido às políticas de integração adotadas na região e, mais recentemente, em decorrência da construção da Usina Hidrelétrica de Belo Monte. Para subsidiar o gerenciamento sustentável desses ecossistemas, este estudo visou detectar a dinâmica dos corpos d´água superficiais da Volta Grande do Xingu por meio da análise de imagens multitemporais de radar do satélite Sentinel-1 e o melhor threshold da água. Foram analisados o comportamento do retroespalhamento das amostras de água superficiais com os filtros espaciais Frost, Gamma e Lee, nas janelas 5x5, 7x7 e 9x9. A imagem de 26 de julho de 2017 com o filtro Frost 9x9 exibiu maior acurácia na delimitação de corpos d´água ao adotar um threshold de -20,71 dB usando a imagem Sentinel-2 de 28 de julho de 2017 como verdade (índice Kappa de 0,96 e exatidão global de 98,9%). Esse filtro e threshold foram empregados nas 34 imagens multitemporais Sentinel-1. A amplitude máxima do rio foi mapeada com as imagens da menor e maior vazão registrada pelo satélite durante o período de análise, sendo de 29 de setembro de 2016 (449 cm) e 04 de março de 2017 (848 cm), respectivamente. Além de representar a extensão da inundação, o mapa de ocorrência de água no pixel também representou o tempo que cada pixel ficou coberto por água, fornecendo um panorama do fluxo do rio ao longo do tempo. Isso permite um gerenciamento da vazão remanescente que garanta a manutenção dos ecossistemas aquáticos nos trechos de vazão reduzida, minimizando os impactos sociais, ambientais e econômicos. Os resultados demonstraram um grande potencial metodológico em extrair, de forma rápida, informações sobre a dinâmica de corpos d´água superficiais e em monitorar grandes extensões de áreas inundáveis.The flooded areas of the Volta Grande of Xingu have been intensely pressured and degraded due to the integration policies adopted in region and the construction of the Belo Monte Dam complex more recently. Therefore, the management of these ecosystems is crucial. So, this research aims to detect changes in the surface of the open water bodies from Volta Grande do Xingu, using multitemporal SAR images of Sentinel-1 satellite and best thresholding. The performance of Frost, Gamma and Lee filters in open water delineation was analyzed with windows size 5x5, 7x7 and 9x9. The image from July 26 of 2017 with Frost 9x9 filter exhibited greater accuracy in water bodies delineating. Adopting a -20,71 dB threshold, Kappa index result was 0.96 and overall accuracy 98.9%. This threshold was employed in 34 multitemporal Sentinel-1 images with Frost 9x9. The maximum amplitude of Xingu river was mapped with images demonstrating the smallest and largest flow during the analysis period, being September 29 of 2016 and March 4 of 2017, respectively. The pixel water map representing the time that each pixel was covered by water and show the extent of the flood, providing a panorama of river flow in the 34 images. This enables remnant flow management that ensures the maintenance of aquatic ecosystems in the reduced flow sections, minimizing social, environmental and economic impacts. The results demonstrated a great methodological potential to quickly extract information about the dynamics of surface water bodies and to monitor large areas of flooded areas

An integrated framework to assess compound flood risks for interdependent critical infrastructure in a coastal environment

Compound flooding refers to flood events caused by multiple factors, including marine processes (e.g. storm tides and waves), hydrometeorological signals (e.g. rainfall and river flows) among others. Saint Lucia is a tropical island in eastern Caribbean Sea, which is frequently affected by weather-related extreme events such as tropical storms and the associated risks are exacerbated due to its mountainous topography and high concentrations of infrastructure and human communities close to the coast. At the southern coast of Saint Lucia, significant infrastructures such as Hewanorra International Airport and Vieux Fort Seaport, and human settlements such as towns of Vieux Fort and La Tourney are located at low-lying areas and are at risk of compound flooding. A hydrologic model (i.e. HYdrological MODel) and a two-dimensional hydrodynamic model (i.e. LISFLOOD-FP) are set up and calibrated to investigate the combined effects of storm tides, wave run-up, rainfall, and river flows on flood risks in Saint Lucia. Results indicate the necessity to consider multiple contributing factors as well as to characterize the effects of uncertain boundary conditions. In flood-prone areas, there are infrastructures supporting major services in the study area, and by extension, the economy of the Island. A network-based model, which considers direct and indirect connections between infrastructures, is set up to explore risks of assets in conditions of non-flooding and flooding. Modelling results reveal the fundamental importance of various components including electricity distribution, flood control, information and communication services, transportation, housing and human settlements, tourism, and particularly the normal operations of Hewanorra International Airport. Prioritization of risks is critical for developing effective mitigation methods for infrastructure networks

Monitoring wetlands and water bodies in semi-arid Sub-Saharan regions

Surface water in wetlands is a critical resource in semi-arid West-African regions that are frequently exposed to droughts. Wetlands are of utmost importance for the population as well as the environment, and are subject to rapidly changing seasonal fluctuations. Dynamics of wetlands in the study area are still poorly understood, and the potential of remote sensing-derived information as a large-scale, multi-temporal, comparable and independent measurement source is not exploited. This work shows successful wetland monitoring with remote sensing in savannah and Sahel regions in Burkina Faso, focusing on the main study site Lac Bam (Lake Bam). Long-term optical time series from MODIS with medium spatial resolution (MR), and short-term synthetic aperture radar (SAR) time series from TerraSAR-X and RADARSAT-2 with high spatial resolution (HR) successfully demonstrate the classification and dynamic monitoring of relevant wetland features, e.g. open water, flooded vegetation and irrigated cultivation. Methodological highlights are time series analysis, e.g. spatio-temporal dynamics or multitemporal-classification, as well as polarimetric SAR (polSAR) processing, i.e. the Kennaugh elements, enabling physical interpretation of SAR scattering mechanisms for dual-polarized data. A multi-sensor and multi-frequency SAR data combination provides added value, and reveals that dual-co-pol SAR data is most recommended for monitoring wetlands of this type. The interpretation of environmental or man-made processes such as water areas spreading out further but retreating or evaporating faster, co-occurrence of droughts with surface water and vegetation anomalies, expansion of irrigated agriculture or new dam building, can be detected with MR optical and HR SAR time series. To capture long-term impacts of water extraction, sedimentation and climate change on wetlands, remote sensing solutions are available, and would have great potential to contribute to water management in Africa