Interferometric radar measurements of water level changes on the Amazon flood plain

Potential of APSIS-InSAR for measuring surface oscillations of tropical peatlands

Tropical peatland across Southeast Asia is drained extensively for production of pulpwood, palm oil and other food crops. Associated increases in peat decomposition have led to widespread subsidence, deterioration of peat condition and CO2 emissions. However, quantification of subsidence and peat condition from these processes is challenging due to the scale and inaccessibility of dense tropical peat swamp forests. The development of satellite interferometric synthetic aperture radar (InSAR) has the potential to solve this problem. The Advanced Pixel System using Intermittent Baseline Subset (APSIS, formerly ISBAS) modelling technique provides improved coverage across almost all land surfaces irrespective of ground cover, enabling derivation of a time series of tropical peatland surface oscillations across whole catchments. This study aimed to establish the extent to which APSIS-InSAR can monitor seasonal patterns of tropical peat surface oscillations at North Selangor Peat Swamp Forest, Peninsular Malaysia. Results showed that C-band SAR could penetrate the forest canopy over tropical peat swamp forests intermittently and was applicable to a range of land covers. Therefore the APSIS technique has the potential for monitoring peat surface oscillations under tropical forest canopy using regularly acquired C-band Sentinel-1 InSAR data, enabling continuous monitoring of tropical peatland surface motion at a spatial resolution of 20 m.

Water Resources in Africa under Global Change: Monitoring Surface Waters from Space

ABSTRACT

The African continent hosts some of the largest freshwater systems worldwide, characterized by a large distribution and variability of surface waters that play a key role in the water, energy and carbon cycles and are of major importance to the global climate and water resources. Freshwater availability in Africa has now become of major concern under the combined effect of climate change, environmental alterations and anthropogenic pressure. However, the hydrology of the African river basins remains one of the least studied worldwide and a better monitoring and understanding of the hydrological processes across the continent become fundamental. Earth Observation, that offers a cost-effective means for monitoring the terrestrial water cycle, plays a major role in supporting surface hydrology investigations. Remote sensing advances are therefore a game changer to develop comprehensive observing systems to monitor Africa's land water and manage its water resources. Here, we review the achievements of more than three decades of advances using remote sensing to study surface waters in Africa, highlighting the current benefits and difficulties. We show how the availability of a large number of sensors and observations, coupled with models, offers new possibilities to monitor a continent with scarce gauged stations. In the context of upcoming satellite missions dedicated to surface hydrology, such as the Surface Water and Ocean Topography (SWOT), we discuss future opportunities and how the use of remote sensing could benefit scientific and societal applications, such as water resource management, flood risk prevention and environment monitoring under current global change.

ARTICLE HIGHLIGHTS

The hydrology of African surface water is of global importance, yet it remains poorly monitored and understoodComprehensive review of remote sensing and modeling advances to monitor Africa's surface water and water resourcesFuture opportunities with upcoming satellite missions and to translate scientific advances into societal applications.

A review on the research progress of lake water volume estimation methods

Surface water provides a basic resource for life and is vital for maintaining climate stability, hydrological cycles, and natural ecosystems. Lakes, which are an important part of surface water, play a crucial role in sustaining the hydrological balance and maintaining a healthy environment. The onset of climate change and anthropogenic disturbance on lakes and the environment, however, have drastically changed the morphological characteristics of lakes, leading to undesirable negative effects on the ecological environment. In recent years, many lakes around the world are undergoing phenomenal changes due to climate change and human activities. These changes have greatly affected the availability of freshwater resources, leading to a series of regional ecological and environmental problems, which constrain the regional sustainable development. Changes in lake parameters often indicate environmental change. Therefore, it is of great practical significance to extract lake water information to reflect the water quantity changes in the lake, understand its implications, and come up with timely solutions. This paper summarizes the existing research methods of lake water estimation in China and abroad and draws the following conclusions: (1) In the study of lake water volume estimation, it can be roughly divided into with topographic data and without topographic data. The most representative methods are the estimation methods based on topographic parameters and the Triangle Irregular Network (TIN) model method. In the actual research process, most of the scarce data that are difficult to obtain are lake topographic data, prompting researchers to constantly put forward new methods; (2) From the perspective of research methods, estimation of lake water volume can be divided into remote sensing-based and non-remote sensing-based research. With the continuous improvement of scientific and technological levels, current geographical researchers tend to use remote sensing to monitor lake water volume; (3) Although researchers have proposed a series of models for lake water volume estimation for the long-time process. However, many models are based on the ideal static estimation process, which poses challenges for researchers to make a long-term dynamic estimation of lake storage capacity in the future. At the same time, the accuracy of the model can be a problem that researchers need to work out solutions in the future. Finally, combined with the current development of remote sensing technology, the application potential and the future prospect of remote sensing in lake monitoring are briefly discussed.

Spatiotemporal Change Detection of Coastal Wetlands Using Multi-Band SAR Coherence and Synergetic Classification

Synthetic aperture radar (SAR) signal can penetrate clouds and some vegetation canopies in all weather, and therefore, provides an important measurement tool for change detection and sustainable development of coastal wetland environments and ecosystems. However, there are a few quantitative estimations about the spatiotemporal coherence change with multi-band SAR images in complex coastal wetland ecosystems of the Yellow River Delta (YRD). In this study, C-band Sentinel-1 and L-band ALOS-2 PALSAR data were used to detect the spatiotemporal distribution and change pattern of interferometric coherence in the coastal wetlands of the YRD. The results show that the temporal baseline has a greater impact on the interferometric coherence than the perpendicular baseline, especially for short wavelength C-band SAR. Furthermore, the OTSU algorithm was proven to be able to distinguish the changing regions. The coherence mean and standard deviation values of different land cover types varied significantly in different seasons, while the minimum and maximum coherence changes occurred in February and August, respectively. In addition, considering three classical machine learning algorithms, namely naive Bayes (NB), random forest (RF), and multilayer perceptron (MLP), we proposed a method of synergetic classification with SAR coherence, backscatter intensity, and optical images for coastal wetland classification. The multilayer perceptron algorithm performs the best in synergetic classification with an overall accuracy of 98.3%, which is superior to a single data source or the other two algorithms. In this article, we provide an alternative cost-effective method for coastal wetland change detection, which contributes to more accurate dynamic land cover classification and to an understanding of the response mechanism of land features to climate change and human activities.

Remote Sensing of Geomorphodiversity Linked to Biodiversity—Part III: Traits, Processes and Remote Sensing Characteristics

Remote sensing (RS) enables a cost-effective, extensive, continuous and standardized monitoring of traits and trait variations of geomorphology and its processes, from the local to the continental scale. To implement and better understand RS techniques and the spectral indicators derived from them in the monitoring of geomorphology, this paper presents a new perspective for the definition and recording of five characteristics of geomorphodiversity with RS, namely: geomorphic genesis diversity, geomorphic trait diversity, geomorphic structural diversity, geomorphic taxonomic diversity, and geomorphic functional diversity. In this respect, geomorphic trait diversity is the cornerstone and is essential for recording the other four characteristics using RS technologies. All five characteristics are discussed in detail in this paper and reinforced with numerous examples from various RS technologies. Methods for classifying the five characteristics of geomorphodiversity using RS, as well as the constraints of monitoring the diversity of geomorphology using RS, are discussed. RS-aided techniques that can be used for monitoring geomorphodiversity in regimes with changing land-use intensity are presented. Further, new approaches of geomorphic traits that enable the monitoring of geomorphodiversity through the valorisation of RS data from multiple missions are discussed as well as the ecosystem integrity approach. Likewise, the approach of monitoring the five characteristics of geomorphodiversity recording with RS is discussed, as are existing approaches for recording spectral geomorhic traits/ trait variation approach and indicators, along with approaches for assessing geomorphodiversity. It is shown that there is no comparable approach with which to define and record the five characteristics of geomorphodiversity using only RS data in the literature. Finally, the importance of the digitization process and the use of data science for research in the field of geomorphology in the 21st century is elucidated and discussed.

Space-Based Detection of Significant Water-Depth Increase Induced by Hurricane Irma in the Everglades Wetlands Using Sentinel-1 SAR Backscatter Observations

Extreme rainfall, induced by severe weather events, such as hurricanes, impacts wetlands because rapid water-depth increases can lead to flora and fauna mortality. This study developed an innovative algorithm to detect significant water-depth increases (SWDI, defined as water-depth increases above a threshold) in wetlands, using Sentinel-1 SAR backscatter. We used Hurricane Irma as an example that made landfall in the south Florida Everglades wetlands in September 2017 and produced tremendous rainfall. The algorithm detects SWDI for during- and post-event SAR acquisition dates, using pre-event water-depth as a baseline. The algorithm calculates Normalized Difference Backscatter Index (NDBI), using pre-, during-, and post-event backscatter, at a 20-m SAR resolution, as an indicator of the likelihood of SWDI, and detects SWDI using all NDBI values in a 400-m resolution pixel. The algorithm successfully detected large SWDI areas for the during-event date and progressive expansion of non-SWDI areas (water-depth differences less than the threshold) for five post-event dates in the following two months. The algorithm achieved good performance in both ‘herbaceous dominant’ and ‘trees embedded within herbaceous matrix’ land covers, with an overall accuracy of 81%. This study provides a solution for accurate mapping of SWDI and can be used in global wetlands, vulnerable to extreme rainfall.

Surface Water Storage in Rivers and Wetlands Derived from Satellite Observations: A Review of Current Advances and Future Opportunities for Hydrological Sciences

Surface water storage (SWS), the amount of freshwater stored in rivers/wetlands/floodplains/lakes, and its variations are key components of the water cycle and land surface hydrology, with strong feedback and linkages with climate variability. They are also very important for water resources management. However, it is still very challenging to measure and to obtain accurate estimates of SWS variations for large river basins at adequate time/space sampling. Satellite observations offer great opportunities to measure SWS changes, and several methods have been developed combining multisource observations for different environments worldwide. With the upcoming launch in 2022 of the Surface Water and Ocean Topography (SWOT) satellite mission, which will provide, for the first time, direct estimates of SWS variations with an unprecedented spatial resolution (~100 m), it is timely to summarize the recent advances in the estimates of SWS from satellite observations and how they contribute to a better understanding of large-scale hydrological processes. Here, we review the scientific literature and present major results regarding the dynamic of surface freshwater in large rivers, floodplains, and wetlands. We show how recent efforts have helped to characterize the variations in SWS change across large river basins, including during extreme climatic events, leading to an overall better understanding of the continental water cycle. In the context of SWOT and forthcoming SWS estimates at the global scale, we further discuss new opportunities for hydrological and multidisciplinary sciences. We recommend that, in the near future, SWS should be considered as an essential water variable to ensure its long-term monitoring.

Monitoring of Water Level Change in a Dam from High-Resolution SAR Data

Accurate measurement of water levels and variations in lakes and reservoirs is crucial for water management. The retrieval of the accurate variations in water levels in lakes and reservoirs with small widths from high-resolution synthetic aperture radar (SAR) images such as the TerraSAR add-on for Digital Elevation Measurements (TanDEM-X) and COnstellation of small Satellites for the Mediterranean basin Observation (COSMO-SkyMed) are presented here. A detailed digital surface model (DSM) for the upstream face of the dam was constructed using SAR interferometry with TanDEM-X data to estimate the water level. The elevation of the waterline below that of the interferometric SAR (InSAR) DSM was estimated based on upstream face modeling. The waterline boundary detected using the SAR Edge Detection Hough Transform algorithm was applied to the restored DSM. The SAR-derived water level variations showed a high correlation coefficient of 0.99 and a gradient of 1.08 with the gauged data. The difference between the gauged data and SAR-derived data was within ±1 m, and the standard deviation of the residual was 0.60 m. These results suggest that water level estimation can be used as an operational supplement for traditional gauged data at remote sites.

InSAR Coherence Analysis for Wetlands in Alberta, Canada Using Time-Series Sentinel-1 Data

Wetlands are valuable natural resources which provide numerous services to the environment. Many studies have demonstrated the potential of various types of remote sensing datasets and techniques for wetland mapping and change analysis. However, there are a relatively low number of studies that have investigated the application of the Interferometric Synthetic Aperture Radar (InSAR) coherence products for wetland studies, especially over large areas. Therefore, in this study, coherence products over the entire province of Alberta, Canada (~661,000 km2) were generated using the Sentinel-1 data acquired from 2017 to 2020. Then, these products along with large amount of wetland reference samples were employed to assess the separability of different wetland types and their trends over time. Overall, our analyses showed that coherence can be considered as an added value feature for wetland classification and monitoring. The Treed Bog and Shallow Open Water classes showed the highest and lowest coherence values, respectively. The Treed Wetland and Open Wetland classes were easily distinguishable. When analyzing the wetland subclasses, it was observed that the Treed Bog and Shallow Open Water classes can be easily discriminated from other subclasses. However, there were overlaps between the signatures of the other wetland subclasses, although there were still some dates where these classes were also distinguishable. The analysis of multi-temporal coherence products also showed that the coherence products generated in spring/fall (e.g., May and October) and summer (e.g., July) seasons had the highest and lowest coherence values, respectively. It was also observed that wetland classes preserved coherence during the leaf-off season (15 August–15 October) while they had relatively lower coherence during the leaf-on season (i.e., 15 May–15 August). Finally, several suggestions for future studies were provided.

Displacement Analysis of Geothermal Field Based on PSInSAR And SOM Clustering Algorithms A Case Study of Brady Field, Nevada—USA

The availability of free and high temporal resolution satellite data and advanced SAR techniques allows us to analyze ground displacement cost-effectively. Our aim was to properly define subsidence and uplift areas to delineate a geothermal field and perform time-series analysis to identify temporal trends. A Persistent Scatterer Interferometry (PSI) algorithm was used to estimate vertical displacement in the Brady geothermal field located in Nevada by analyzing 70 Sentinel-1A Synthetic-Aperture Radar (SAR) images, between January 2017 and December 2019. To classify zones affected by displacement, an unsupervised Self-Organizing Map (SOM) algorithm was applied to classify points based on their behavior in time, and those clusters were used to determine subsidence, uplift, and stable regions automatically. Finally, time-series analysis was applied to the clustered data to understand the inflection dates. The maximum subsidence is –19 mm/yr with an average value of –6 mm/yr within the geothermal field. The maximum uplift is 14 mm/yr with an average value of 4 mm/yr within the geothermal field. The uplift occurred on the NE of the field, where the injection wells are located. On the other hand, subsidence is concentrated on the SW of the field where the production wells are located. The coupling of the PSInSAR and the SOM algorithms was shown to be effective in analyzing the direction and pattern of the displacements observed in the field.

Linking the Remote Sensing of Geodiversity and Traits Relevant to Biodiversity—Part II: Geomorphology, Terrain and Surfaces

The status, changes, and disturbances in geomorphological regimes can be regarded as controlling and regulating factors for biodiversity. Therefore, monitoring geomorphology at local, regional, and global scales is not only necessary to conserve geodiversity, but also to preserve biodiversity, as well as to improve biodiversity conservation and ecosystem management. Numerous remote sensing (RS) approaches and platforms have been used in the past to enable a cost-effective, increasingly freely available, comprehensive, repetitive, standardized, and objective monitoring of geomorphological characteristics and their traits. This contribution provides a state-of-the-art review for the RS-based monitoring of these characteristics and traits, by presenting examples of aeolian, fluvial, and coastal landforms. Different examples for monitoring geomorphology as a crucial discipline of geodiversity using RS are provided, discussing the implementation of RS technologies such as LiDAR, RADAR, as well as multi-spectral and hyperspectral sensor technologies. Furthermore, data products and RS technologies that could be used in the future for monitoring geomorphology are introduced. The use of spectral traits (ST) and spectral trait variation (STV) approaches with RS enable the status, changes, and disturbances of geomorphic diversity to be monitored. We focus on the requirements for future geomorphology monitoring specifically aimed at overcoming some key limitations of ecological modeling, namely: the implementation and linking of in-situ, close-range, air- and spaceborne RS technologies, geomorphic traits, and data science approaches as crucial components for a better understanding of the geomorphic impacts on complex ecosystems. This paper aims to impart multidimensional geomorphic information obtained by RS for improved utilization in biodiversity monitoring.

Monitoring Water Level Change and Seasonal Vegetation Change in the Coastal Wetlands of Louisiana Using L-Band Time-Series

Coastal wetlands are productive ecosystems driven by highly dynamic hydrological processes such as tides and river discharge, which operate at daily to seasonal timescales, respectively. The scientific community has been calling for landscape-scale measurements of hydrological variables that could help understand the flow of water and transport of sediment across coastal wetlands. While in situ water level gauge data have enabled significant advances, they are limited in coverage and largely unavailable in many parts of the world. In preparation for the NISAR mission, we investigate the use of spaceborne Interferometric Synthetic Aperture Radar (InSAR) observations of phase and coherence at L-band for landscape-scale monitoring of water level change and vegetation cover in coastal wetlands across seasons. We use L-band SAR images acquired by ALOS/PALSAR from 2007 to 2011 to study the impact of seasonal changes in vegetation cover on InSAR sensitivity to water level change in the wetlands of the Atchafalaya basin located in coastal Louisiana, USA. Seasonal variations are observed in the interferometric coherence ( γ ) time-series over wetlands, with higher coherence during the winter and lower coherence during the summer. We show with InSAR time-series that coherence is inversely correlated with Normalized Difference Vegetation Index (NDVI). Our analysis of polarimetric scattering mechanisms demonstrates that double-bounce is the dominant mechanism in swamps while its weakness in marshes hinders estimation of water level changes. In swamps, water level change maps derived from InSAR are highly correlated (r2 = 0.83) with in situ data from the Coastwide Reference Monitoring System (CRMS). From October to December, we observed that the water level may be below wetland elevation and thus not inundating wetlands significantly. Our analysis shows that water level can only be retrieved when both images used for InSAR are acquired when wetlands are inundated. The L-band derived-maps of water level change show large scale gradients originating from the Gulf Intracoastal Waterway rather than the main delta trunk channel, confirming its significant role as a source of hydrologic connectivity across these coastal wetlands. These results indicate that NISAR, with its InSAR observations every 12 days, will provide the measurements necessary to reveal large scale hydrodynamic processes that occur in swamps across seasons.

Spaceborne L-Band Synthetic Aperture Radar Data for Geoscientific Analyses in Coastal Land Applications: A Review

The coastal zone offers among the world’s most productive and valuable ecosystems and is experiencing increasing pressure from anthropogenic impacts: human settlements, agriculture, aquaculture, trade, industrial activities, oil and gas exploitation and tourism. Earth observation has great capability to deliver valuable data at the local, regional and global scales and can support the assessment and monitoring of land- and water-related applications in coastal zones. Compared to optical satellites, cloud-cover does not limit the timeliness of data acquisition with spaceborne Synthetic Aperture Radar (SAR) sensors, which have all-weather, day and night capabilities. Hence, active radar systems demonstrate great potential for continuous mapping and monitoring of coastal regions, particularly in cloud-prone tropical and sub-tropical climates. The canopy penetration capability with long radar wavelength enables L-band SAR data to be used for coastal terrestrial environments and has been widely applied and investigated for the following geoscientific topics: mapping and monitoring of flooded vegetation and inundated areas; the retrieval of aboveground biomass; and the estimation of soil moisture. Human activities, global population growth, urban sprawl and climate change-induced impacts are leading to increased pressure on coastal ecosystems causing land degradation, deforestation and land use change. This review presents a comprehensive overview of existing research articles that apply spaceborne L-band SAR data for geoscientific analyses that are relevant for coastal land applications.

Wetland Monitoring Using SAR Data: A Meta-Analysis and Comprehensive Review

Despite providing vital ecosystem services, wetlands are increasingly threatened across the globe by both anthropogenic activities and natural processes. Synthetic aperture radar (SAR) has emerged as a promising tool for rapid and accurate monitoring of wetland extent and type. By acquiring information on the roughness and moisture content of the surface, SAR offers unique potential for wetland monitoring. However, there are still challenges in applying SAR for mapping complex wetland environments. The backscattering similarity of different wetland classes is one of the challenges. Choosing the appropriate SAR specifications (incidence angle, frequency and polarization), based on the wetland type, is also a subject of debate and should be investigated more thoroughly. The geometric distortion of SAR imagery and loss of coherency are other remaining challenges in applying SAR and its processing techniques for wetland studies. Hence, this study provides a systematic meta-analysis based on compilation and analysis of indexed research studies that used SAR for wetland monitoring. This meta-analysis reviewed 172 papers and documented an upward trend in usage of SAR data, increasing usage of multi-sensor data, increasing integration of C- and L- bands over other configurations and higher classification accuracy with multi-frequency and multi-polarized SAR data. The highest number of wetland research studies using SAR data came from the USA, Canada and China. This meta-analysis highlighted the current challenges and solutions for wetland monitoring using SAR sensors.

Tracking annual changes of coastal tidal flats in China during 1986-2016 through analyses of Landsat images with Google Earth Engine

Tidal flats (non-vegetated area), along with coastal vegetation area, constitute the coastal wetlands (intertidal zone) between high and low water lines, and play an important role in wildlife, biodiversity and biogeochemical cycles. However, accurate annual maps of coastal tidal flats over the last few decades are unavailable and their spatio-temporal changes in China are unknown. In this study, we analyzed all the available Landsat TM/ETM+/OLI imagery (~ 44,528 images) using the Google Earth Engine (GEE) cloud computing platform and a robust decision tree algorithm to generate annual frequency maps of open surface water body and vegetation to produce annual maps of coastal tidal flats in eastern China from 1986 to 2016 at 30-m spatial resolution. The resulting map of coastal tidal flats in 2016 was evaluated using very high-resolution images available in Google Earth. The total area of coastal tidal flats in China in 2016 was about 731,170 ha, mostly distributed in the provinces around Yellow River Delta and Pearl River Delta. The interannual dynamics of coastal tidal flats area in China over the last three decades can be divided into three periods: a stable period during 1986-1992, an increasing period during 1993-2001 and a decreasing period during 2002-2016. The resulting annual coastal tidal flats maps could be used to support sustainable coastal zone management policies that preserve coastal ecosystem services and biodiversity in China.

Investigating the potential use of Sentinel-1 data for monitoring wetland water level changes in China's Momoge National Nature Reserve

Background

Interferometric Synthetic Aperture Radar (InSAR) has become a promising technique for monitoring wetland water levels. However, its capability in monitoring wetland water level changes with Sentine-1 data has not yet been thoroughly investigated.

Methods

In this study, we produced a multitemporal Sentinel-1 C-band VV-polarized SAR backscatter images and generated a total of 28 interferometric coherence maps for marsh wetlands of China's Momoge National Nature Reserve to investigate the interferometric coherence level of Sentinel-1 C-VV data as a function of perpendicular and temporal baseline, water depth, and SAR backscattering intensity. We also selected six interferogram pairs acquired within 24 days for quantitative analysis of the accuracy of water level changes monitored by Sentinel-1 InSAR. The accuracy of water level changes determined through the Sentinel-1 InSAR technique was calibrated by the values of six field water level loggers.

Results

Our study showed that (1) the coherence was mainly dependent on the temporal baseline and was little affected by the perpendicular baseline for Sentinel-1 C-VV data in marsh wetlands; (2) in the early stage of a growing season, a clear negative correlation was found between Sentinel-1 coherence and water depth; (3) there was an almost linear negative correlation between Sentinel-1 C-VV coherence and backscatter for the marsh wetlands; (4) once the coherence exceeds a threshold of 0.3, the stage during the growing season, rather than the coherence, appeared to be the primary factor determining the quality of the interferogram for the marsh wetlands, even though the quality of the interferogram largely depends on the coherence; (5) the results of water level changes from InSAR processing show no agreement with in-situ measurements during most growth stages. Based on the findings, we can conclude that although the interferometric coherence of the Sentinel-1 C-VV data is high enough, the data is generally unsuitable for monitoring water level changes in marsh wetlands of China's Momoge National Nature Reserve.

Analysis of Floodplain Dynamics in the Atrato River Colombia Using SAR Interferometry

Floodplain water flows have large volumetric flowrates and high complexity in space and time that are difficult to understand using water level gauges. We here analyze the spatial and temporal fluctuations of surface water flows in the floodplain of the Atrato River, Colombia, in order to evaluate their hydrological connectivity. The basin is one of the rainiest areas of the world with wetland ecosystems threatened by the expansion of agriculture and mining activities. We used 16 Differential Interferometric Synthetic Aperture Radars (DInSAR) phase observations from the ALOS-PALSAR L-band instrument acquired between 2008–2010 to characterize the flow of surface water. We were able to observe water level change in vegetated wetland areas and identify flooding patterns. In the lower basin, flow patterns are conditioned by fluctuations in the levels of the main river channel, whereas in the middle basin, topography and superficial channels strongly influence the flow and connectivity. We found that the variations in water level in a station on the main channel 87 km upstream explained more than 56% of the variations in water level in the floodplain. This result shows that, despite current expansion of agriculture and mining activities, there remain significant hydrological connectivity between wetlands and the Atrato River. This study demonstrates the use of DInSAR for a spatially comprehensive monitoring of the Atrato River basin hydrology. For the first time, we identified the spatiotemporal patterns of surface water flow of the region. We recommend these observations serve as a baseline to monitor the potential impact of ongoing human activities on surface water flows across the Atrato River basin.

A Sensing and Monitoring System for Hydrodynamic Flow Based on Imaging and Ultrasound

A built environment, that also includes infrastructures, needs to be taken under control to prevent unexpected modifications, otherwise it could react as a loose cannon. Sensing techniques and technologies can come to the rescue of built environments thanks to their capabilities to monitor appropriately. This article illustrates findings related to monitoring a channel hydrodynamic behavior by means of sensors based on imaging and ultrasound. The ultrasound approach is used here to monitor the height of the water with respect to a maximum limit. Imaging treatment is here proposed to understand the flow velocity under the area to be considered. Since these areas can be covered by trash, an enhanced version of the particle image velocimetry technique has been implemented, allowing the discrimination of trash from water flow. Even in the presence of the total area occupied by trash, it is able to detect the velocity of particles underneath. Rainfall and hydraulic levels have been included and processed to strengthen the study.

How Groundwater Level Fluctuations and Geotechnical Properties Lead to Asymmetric Subsidence: A PSInSAR Analysis of Land Deformation over a Transit Corridor in the Los Angeles Metropolitan Area

Los Angeles has experienced ground deformations during the past decades. These ground displacements can be destructive for infrastructure and can reduce the land capacity for groundwater storage. Therefore, this paper seeks to evaluate the existing ground displacement patterns along a new metro tunnel in Los Angeles, known as the Sepulveda Transit Corridor. The goal is to find the most crucial areas suffering from subsidence or uplift and to enhance the previous reports in this metropolitan area. For this purpose, we applied a Persistent Scatterer Interferometric Synthetic Aperture Radar using 29 Sentinel-1A acquisitions from June 2017 to May 2018 to estimate the deformation rate. The assessment procedure demonstrated a high rate of subsidence in the Inglewood field that is near the study area of the Sepulveda Transit Corridor with a maximum deformation rate of 30 mm/yr. Finally, data derived from in situ instruments as groundwater level variations, GPS observations, and soil properties were collected and analyzed to interpret the results. Investigation of geotechnical boreholes indicates layers of fine-grained soils in some parts of the area and this observation confirms the necessity of more detailed geotechnical investigations for future constructions in the region. Results of investigating line-of-sight displacement rates showed asymmetric subsidence along the corridor and hence we proposed a new framework to evaluate the asymmetric subsidence index that can help the designers and decision makers of the project to consider solutions to control the current subsidence.

A Multisensor Approach to Satellite Monitoring of Trends in Lake Area, Water Level, and Volume

Lakes in arid regions play an important role in regional water cycles and are a vital economic resource, but can fluctuate widely in area and volume. This study demonstrates the use of a multisensor satellite remote sensing method for the comprehensive monitoring of lake surface areas, water levels, and volume for the Toshka Lakes in southern Egypt, from lake formation in 1998 to mid-2017. Two spectral water indices were used to construct a daily time-series of surface area from the Advanced Very High Resolution Radiometer (AVHRR) and the Moderate Resolution Imaging Spectroradiometer (MODIS), validated by higher-resolution Landsat images. Water levels were obtained from analysis of digital elevation models from the Shuttle Radar Topography Mission (SRTM) and the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), validated with ICESat Geoscience Laser Altimeter System (GLAS) laser altimetry. Total lake volume peaked at 26.54 × 109 m3 in December 2001, and declined to 0.76 × 109 m3 by August 2017. Evaporation accounted for approximately 86% of the loss, and groundwater recharge accounted for 14%. Without additional inflows, the last remaining lake will likely disappear between 2020 and 2022. The Enhanced Lake Index, a water index equivalent to the Enhanced Vegetation Index, was found to have lower noise levels than the Normalized Difference Lake Index. The results show that multi-platform satellite remote sensing provides an efficient method for monitoring the hydrology of lakes.

A Newly Developed Unmanned Aerial Vehicle (UAV) Imagery Based Technology for Field Measurement of Water Level

Field measurement of water level is important for water conservancy project operation and hydrological forecasting. In this study, we proposed a new measuring technique by integrating the advantages of unmanned aerial vehicle (UAV) photogrammetry and image recognition technology. Firstly, the imagery of water fluctuation process was captured by an UAV airborne camera, and water surface line in the imagery was recognized and extracted using image recognition technology. Subsequently, successive water levels at a measuring section were calculated by parameter calibration. Statistical parameters of water levels, such as maximum, average, and minimum values during the capturing period were also calculated. Additionally, we introduced a correction method to offset the error caused by UAV drift. The newly proposed method was tested in field measurement for Miaowei hydropower station, China, and the results showed that the method is reliable and adoptable.

Remote Sensing of Floodpath Lakes and Wetlands: A Challenging Frontier in the Monitoring of Changing Environments

Monitoring of changing lake and wetland environments has long been among the primary focus of scientific investigation, technology innovation, management practice, and decision-making analysis. Floodpath lakes and wetlands are the lakes and associated wetlands affected by seasonal variations of water level and water surface area. Floodpath lakes and wetlands are, in particular, sensitive to natural and anthropogenic impacts, such as climate change, human-induced intervention on hydrological regimes, and land use and land cover change. Rapid developments of remote sensing science and technologies, provide immense opportunities and capacities to improve our understanding of the changing lake and wetland environments. This special issue on Remote Sensing of Floodpath Lakes and Wetlands comprise featured articles reporting the latest innovative research and reflects the advancement in remote sensing applications on the theme topic. In this editorial paper, we review research developments using state-of-the-art remote sensing technologies for monitoring dynamics of floodpath lakes and wetlands; discuss challenges of remote sensing in inventory, monitoring, management, and governance of floodpath lakes and wetlands; and summarize the highlights of the articles published in this special issue.

Wetlands and Malaria in the Amazon: Guidelines for the Use of Synthetic Aperture Radar Remote-Sensing

The prevention and control of mosquito-borne diseases, such as malaria, are important health issues in tropical areas. Malaria transmission is a multi-scale process strongly controlled by environmental factors, and the use of remote-sensing data is suitable for the characterization of its spatial and temporal dynamics. Synthetic aperture radar (SAR) is well-adapted to tropical areas, since it is capable of imaging independent of light and weather conditions. In this study, we highlight the contribution of SAR sensors in the assessment of the relationship between vectors, malaria and the environment in the Amazon region. More specifically, we focus on the SAR-based characterization of potential breeding sites of mosquito larvae, such as man-made water collections and natural wetlands, providing guidelines for the use of SAR capabilities and techniques in order to optimize vector control and malaria surveillance. In light of these guidelines, we propose a framework for the production of spatialized indicators and malaria risk maps based on the combination of SAR, entomological and epidemiological data to support malaria risk prevention and control actions in the field.

Ecomorphological correlates of twenty dominant fish species of Amazonian floodplain lakes

Fishes inhabiting Amazonian floodplain lakes exhibits a great variety of body shape, which was a key advantage to colonize the several habitats that compose these areas adjacent to the large Amazon rivers. In this paper, we did an ecomorphological analysis of twenty abundant species, sampled in May and August 2011, into two floodplain lakes of the lower stretch of the Solimões River. The analysis detected differences among species, which could be probably associated with swimming ability and habitat use preferences.

Overspill avalanching in a dense reservoir network

Sustainability of communities, agriculture, and industry is strongly dependent on an effective storage and supply of water resources. In some regions the economic growth has led to a level of water demand that can only be accomplished through efficient reservoir networks. Such infrastructures are not always planned at larger scale but rather made by farmers according to their local needs of irrigation during droughts. Based on extensive data from the upper Jaguaribe basin, one of the world's largest system of reservoirs, located in the Brazilian semiarid northeast, we reveal that surprisingly it self-organizes into a scale-free network exhibiting also a power-law in the distribution of the lakes and avalanches of discharges. With a new self-organized-criticality-type model we manage to explain the novel critical exponents. Implementing a flow model we are able to reproduce the measured overspill evolution providing a tool for catastrophe mitigation and future planning.

Drought impacts on the Amazon forest: the remote sensing perspective

Drought varies spatially and temporally throughout the Amazon basin, challenging efforts to assess ecological impacts via field measurements alone. Remote sensing offers a range of regional insights into drought-mediated changes in cloud cover and rainfall, canopy physiology, and fire. Here, we summarize remote sensing studies of Amazônia which indicate that: fires and burn scars are more common during drought years; hydrological function including floodplain area is significantly affected by drought; and land use affects the sensitivity of the forest to dry conditions and increases fire susceptibility during drought. We highlight two controversial areas of research centering on canopy physiological responses to drought and changes in subcanopy fires during drought. By comparing findings from field and satellite studies, we contend that current remote sensing observations and techniques cannot resolve these controversies using current satellite observations. We conclude that studies integrating multiple lines of evidence from physiological, disturbance-fire, and hydrological remote sensing, as well as field measurements, are critically needed to narrow our uncertainty of basin-level responses to drought and climate change.

Plant reproduction in the Central Amazonian floodplains: challenges and adaptations

BACKGROUND

The Central Amazonian floodplain forests are subjected to extended periods of flooding and to flooding amplitudes of 10 m or more. The predictability, the length of the flood pulse, the abrupt transition in the environmental conditions along topographic gradients on the banks of major rivers in Central Amazonia, and the powerful water and sediment dynamics impose a strong selective pressure on plant reproduction systems.

SCOPE

In this review, we examine how the hydrological cycle influences the strategies of sexual and asexual reproduction in herbaceous and woody plants. These are of fundamental importance for the completion of the life cycle. Possible constraints to seed germination, seedling establishment and formation of seed banks are also covered. Likewise, we also discuss the importance of river connectivity for species propagation and persistence in floodplains.

CONCLUSIONS

The propagation and establishment strategies employed by the highly diversified assortment of different plant life forms result in contrasting successional stages and a zonation of plant assemblages along the flood-level gradient, whose species composition and successional status are continuously changing not only temporally but also spatially along the river channel.

Applications of SAR Interferometry in Earth and Environmental Science Research

This paper provides a review of the progress in regard to the InSAR remote sensing technique and its applications in earth and environmental sciences, especially in the past decade. Basic principles, factors, limits, InSAR sensors, available software packages for the generation of InSAR interferograms were summarized to support future applications. Emphasis was placed on the applications of InSAR in seismology, volcanology, land subsidence/uplift, landslide, glaciology, hydrology, and forestry sciences. It ends with a discussion of future research directions.

Measuring water storage fluctuations in lake Dongting, China, by Topex/Poseidon satellite altimetry

Although satellite radar altimetry was developed and optimized for open oceans, it has been used to monitor variations in the level of inland water-bodies such as lakes and rivers. Here, for the first time, we have further used the altimetry-derived variation of water level for estimating the fluctuation of water storage as an addition to the present in situ water storage estimation systems to be used in remote areas and in emergency situation such as in the events flooding monitoring and for studying the effect of climate change. Lake Dongting, the second largest lake in China, influenced frequently by flooding, was, therefore, chosen to demonstrate the potential of the technique. By using the concept of an "assumed reference point", we converted Topex/Poseidon satellite altimetry data on water level variations in Lake Dongting to "water level" data. The "water level" time-series data and in situ water storage were used to establish a rating curve. From the rating curve, we converted data on "water level" derived from seven years (1993-1999) of Topex/Poseidon data to actual water storage in Lake Dongting. The result reveals that the seasonal and annual fluctuations of water storage occurred during the 1990s with a more frequent flooding at the late 1990s' especially the flooding in whole catchment level in 1998 and 1999. The study supports the usefulness of satellite altimetry for dense and continuous monitoring of the temporal variations in water dynamic in moderate to large lakes.