InSAR as a tool for monitoring hydropower projects: A review

This paper provides a review of using Interferometric Synthetic Aperture Radar (InSAR), a microwave remote sensing technique, for deformation monitoring of hydroelectric power projects, a critical infrastructure that requires consistent and reliable monitoring. Almost all major dams around the world were built for the generation of hydropower. InSAR can enhance dam safety by providing timely settlement measurements at high spatial-resolution. This paper provides a holistic view of different InSAR deformation monitoring techniques such as Differential Synthetic Aperture Radar Interferometry (DInSAR), Ground-Based Synthetic Aperture Radar (GBInSAR), Persistent Scatterer Interferometric Synthetic Aperture Radar (PSInSAR), Multi-Temporal Interferometric Synthetic Aperture Radar (MTInSAR), Quasi-Persistent Scatterer Interferometric Synthetic Aperture Radar (QPSInSAR) and Small BAseline Subset (SBAS). PSInSAR, GBInSAR, MTInSAR, and DInSAR techniques were quite commonly used for deformation studies. These studies demonstrate the advantage of InSAR-based techniques over other conventional methods, which are laborious, costly, and sometimes unachievable. InSAR technology is also favoured for its capability to provide monitoring data at all times of day or night, in all-weather conditions, and particularly for wide areas with mm-scale precision. However, the method also has some disadvantages, such as the maximum deformation rate that can be monitored, and the location for monitoring cannot be dictated. Through this review, we aim to popularize InSAR technology to monitor the deformation of dams, which can also be used as an early warning method to prevent any unprecedented catastrophe. This study also discusses some case studies from southern India to demonstrate the capabilities of InSAR to indirectly monitor dam health

SUMMARY OF NATURAL DISASTER RESPONSES BY THE ADVANCED LAND OBSERVING SATELLITE-2 (ALOS-2)

The Advanced Land Observing Satellite-2 (ALOS-2) was launched on May 24, 2014, and it is operating very well in space more than 4.5 years. The designed mission life is five years as nominal operational phase and the target is over seven years since launch the satellite. The mission objectives of ALOS-2 are 1) disaster monitoring, 2) national land and infrastructure information, 3) cultivated area monitoring, and 4) global forest monitoring. To achieve the objectives, ALOS-2 carries on the Phased Array type L-band Synthetic Aperture Radar-2 (PALSAR-2), which is an active microwave radar using the 1.2 GHz frequency band and observes in day and night times even in bad weather conditions as successor PALSAR instrument onboard ALOS satellite operated from 2006 to 2011. PALSAR-2 instrument has several enhanced features from PALSAR e.g. finer spatial resolution, spotlight observing mode, dual-polarisation ScanSAR. This paper summarises an introduction of typical data analysis results for monitoring natural disasters by ALOS-2 during the operational phase. As the response natural disasters, more than 400 times of the emergency observations have been conducted to identify damages caused by volcanic activities, earthquakes, flooding etc. happened in Japan and the World

Satellite monitoring of harmful algal blooms (HABs) to protect the aquaculture industry

Harmful algal blooms (HABs) can cause sudden and considerable losses to fish farms, for example 500,000 salmon during one bloom in Shetland, and also present a threat to human health. Early warning allows the industry to take protective measures. PML's satellite monitoring of HABs is now funded by the Scottish aquaculture industry. The service involves processing EO ocean colour data from NASA and ESA in near-real time, and applying novel techniques for discriminating certain harmful blooms from harmless algae. Within the AQUA-USERS project we are extending this capability to further HAB species within several European countries

Applications of Satellite Earth Observations section - NEODAAS: Providing satellite data for efficient research

The NERC Earth Observation Data Acquisition and Analysis Service (NEODAAS) provides a central point of Earth Observation (EO) satellite data access and expertise for UK researchers. The service is tailored to individual users’ requirements to ensure that researchers can focus effort on their science, rather than struggling with correct use of unfamiliar satellite data

Space Based Data Usage for Smart Farming

Precision Agriculture and input optimization with knowledge sharing are key for smart farming. The use of new technologies such as satellites, drones, navigation, AI/ML, big data, IoT, cloud-computing makes farming and agriculture smarter and transparent. Use of such advanced technologies, governmental officers and farmers can create evidence-based prescription maps for variable rate application of inputs, such as fertilizers, pesticides, and irrigation. Also, smart farming improve efficiency, reduce costs, simplify forecasting, streamline recording and reporting, and boost the sustainability and environmentally friendly agriculture while addressing todays needs and helping future planning. This paper is a brief overview of space-based tools that are currently available for smart farming and also importance of earth observation for smart farming with some examples on rice crop in Asia

JAXA EARTH OBSERVATION DASHBOARD WITH COG AND WMS/WMTSS

JAXA has developed and implemented earth observation (EO) dashboard jointly with ESA and NASA. The development of the JAXA dashboard, along with the "Earth-graphy" website and the newly developed "JAXA Earth API" service, demonstrate JAXA's commitment to providing climate change and earth science information to users worldwide. The EO dashboard serves as a platform to deliver valuable data and information related to climate change. The WMS/WMTS technology allows users to visualize and interact with geospatial information by providing web-based mapping services. This technology enhances the user experience by enabling the display of satellite imagery, overlays, and other geospatial data layers within the EO dashboard. To further facilitate the efficient use of satellite data, JAXA has developed the JAXA Earth API service. This service offers a user-friendly interface for accessing and utilizing JAXA's Earth observation satellite image data. By providing an easy-to-use format, JAXA aims to promote the effective utilization of satellite data and encourage its widespread use. Overall, the development and operation of the JAXA dashboard, with its integration of COG format data, WMS/WMTS technology, Python-based API. This paper introduces the status of development of JAXA Earth Observation dashboard with COG format data, WMS/WMTS technology, phyton based API and JAXA Earth Observation missions

The European Space Agency BIOMASS mission: Measuring forest above-ground biomass from space

The primary objective of the European Space Agency's 7th Earth Explorer mission, BIOMASS, is to determine the worldwide distribution of forest above-ground biomass (AGB) in order to reduce the major uncertainties in calculations of carbon stocks and fluxes associated with the terrestrial biosphere, including carbon fluxes associated with Land Use Change, forest degradation and forest regrowth. To meet this objective it will carry, for the first time in space, a fully polarimetric P-band synthetic aperture radar (SAR). Three main products will be provided: global maps of both AGB and forest height, with a spatial resolution of 200 m, and maps of severe forest disturbance at 50 m resolution (where “global” is to be understood as subject to Space Object tracking radar restrictions). After launch in 2022, there will be a 3-month commissioning phase, followed by a 14-month phase during which there will be global coverage by SAR tomography. In the succeeding interferometric phase, global polarimetric interferometry Pol-InSAR coverage will be achieved every 7 months up to the end of the 5-year mission. Both Pol-InSAR and TomoSAR will be used to eliminate scattering from the ground (both direct and double bounce backscatter) in forests. In dense tropical forests AGB can then be estimated from the remaining volume scattering using non-linear inversion of a backscattering model. Airborne campaigns in the tropics also indicate that AGB is highly correlated with the backscatter from around 30 m above the ground, as measured by tomography. In contrast, double bounce scattering appears to carry important information about the AGB of boreal forests, so ground cancellation may not be appropriate and the best approach for such forests remains to be finalized. Several methods to exploit these new data in carbon cycle calculations have already been demonstrated. In addition, major mutual gains will be made by combining BIOMASS data with data from other missions that will measure forest biomass, structure, height and change, including the NASA Global Ecosystem Dynamics Investigation lidar deployed on the International Space Station after its launch in December 2018, and the NASA-ISRO NISAR L- and S-band SAR, due for launch in 2022. More generally, space-based measurements of biomass are a core component of a carbon cycle observation and modelling strategy developed by the Group on Earth Observations. Secondary objectives of the mission include imaging of sub-surface geological structures in arid environments, generation of a true Digital Terrain Model without biases caused by forest cover, and measurement of glacier and icesheet velocities. In addition, the operations needed for ionospheric correction of the data will allow very sensitive estimates of ionospheric Total Electron Content and its changes along the dawn-dusk orbit of the mission

Mapping Water Levels across a Region of the Cuvette Centrale Peatland Complex

Inundation dynamics are the primary control on greenhouse gas emissions from peatlands. Situated in the central Congo Basin, the Cuvette Centrale is the largest tropical peatland complex. However, our knowledge of the spatial and temporal variations in its water levels is limited. By addressing this gap, we can quantify the relationship between the Cuvette Centrale’s water levels and greenhouse gas emissions, and further provide a baseline from which deviations caused by climate or land-use change can be observed, and their impacts understood. We present here a novel approach that combines satellite-derived rainfall, evapotranspiration and L-band Synthetic Aperture Radar (SAR) data to estimate spatial and temporal changes in water level across a sub-region of the Cuvette Centrale. Our key outputs are a map showing the spatial distribution of rainfed and flood-prone locations and a daily, 100 m resolution map of peatland water levels. This map is validated using satellite altimetry data and in situ water table data from water loggers. We determine that 50% of peatlands within our study area are largely rainfed, and a further 22.5% are somewhat rainfed, receiving hydrological input mostly from rainfall (directly and via surface/sub-surface inputs in sloped areas). The remaining 27.5% of peatlands are mainly situated in riverine floodplain areas to the east of the Congo River and between the Ubangui and Congo rivers. The mean amplitude of the water level across our study area and over a 20-month period is 22.8 ± 10.1 cm to 1 standard deviation. Maximum temporal variations in water levels occur in the riverine floodplain areas and in the inter-fluvial region between the Ubangui and Congo rivers. Our results show that spatial and temporal changes in water levels can be successfully mapped over tropical peatlands using the pattern of net water input (rainfall minus evapotranspiration, not accounting for run-off) and L-band SAR data