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

Application of Landsat-8 and ALOS-2 data for structural and landslide hazard mapping in Kelantan, Malaysia

Identification of high potential risk and susceptible zones for natural hazards of geological origin is one of the most important applications of advanced remote sensing technology. Yearly, several landslides occur during heavy monsoon rainfall in Kelantan River basin, Peninsular Malaysia. Flooding and subsequent landslide occurrences generated significant damage to livestock, agricultural produce, homes and businesses in the Kelantan River basin. In this study, remote sensing data from the recently launched Landsat-8 and Phased Array type L-band Synthetic Aperture Radar-2 (PALSAR-2) on board the Advanced Land Observing Satellite-2 (ALOS-2) were used to map geologic structural and topographical features in the Kelantan River basin for identification of high potential risk and susceptible zones for landslides and flooding areas. The data were processed for a comprehensive analysis of major geological structures and detailed characterizations of lineaments, drainage patterns and lithology at both regional and district scales. The analytical hierarchy process (AHP) approach was used for landslide susceptibility mapping. Several factors such as slope, aspect, soil, lithology, normalized difference vegetation index (NDVI), land cover, distance to drainage, precipitation, distance to fault and distance to the road were extracted from remote sensing satellite data and fieldwork to apply the AHP approach. Directional convolution filters were applied to ALOS-2 data for identifying linear features in particular directions and edge enhancement in the spatial domain. Results indicate that lineament occurrence at regional scale was mainly linked to the N-S trending of the Bentong-Raub Suture Zone (BRSZ) in the west and Lebir Fault Zone in the east of the Kelantan state. The combination of different polarization channels produced image maps that contain important information related to water bodies, wetlands and lithological units. The N-S, NE-SW and NNE-SSW lineament trends and dendritic, sub-dendritic and rectangular drainage patterns were detected in the Kelantan River basin. The analysis of field investigation data indicates that many of flooded areas were associated with high potential risk zones for hydrogeological hazards such as wetlands, urban areas, floodplain scroll, meander bend, dendritic and sub-dendritic drainage patterns, which are located in flat topographic regions. Numerous landslide points were located in a rectangular drainage system that is associated with a topographic slope of metamorphic and quaternary rock units. Consequently, structural and topographical geology maps were produced for Kelantan River basin using PALSAR-2 data, which could be broadly applicable for landslide hazard mapping and identification of high potential risk zone for hydrogeological hazards. Geohazard mitigation programs could be conducted in the landslide recurrence regions and flooded areas to reduce natural catastrophes leading to loss of life and financial investments in the Kelantan River basin. In this investigation, Landsat-8 and ALOS-2 have proven to successfully provide advanced Earth observation satellite data for disaster monitoring in tropical environments

On the use of temporal series of L-and X-band SAR data for soil moisture retrieval. Capitanata plain case study

This paper investigates the use of time series of ALOS/PALSAR-1 and COSMO-SkyMed data for the soil moisture retrieval (mv) by means of the SMOSAR algorithm. The application context is the exploitation of mv maps at a moderate spatial and temporal resolution for improving flood/drought monitoring at regional scale. The SAR data were acquired over the Capitanata plain in Southern Italy, over which ground campaigns were carried out in 2007, 2010 and 2011. The analysis shows that the mv retrieval accuracy is 5%-7% m^3/m^3 at L- and X band, although the latter is restricted to a use over nearly bare soil only

Development and Evaluation of a Multi-Year Fractional Surface Water Data Set Derived from Active/Passive Microwave Remote Sensing Data

abstract: The sensitivity of Earth’s wetlands to observed shifts in global precipitation and temperature patterns and their ability to produce large quantities of methane gas are key global change questions. We present a microwave satellite-based approach for mapping fractional surface water (FW) globally at 25-km resolution. The approach employs a land cover-supported, atmospherically-corrected dynamic mixture model applied to 20+ years (1992–2013) of combined, daily, passive/active microwave remote sensing data. The resulting product, known as Surface WAter Microwave Product Series (SWAMPS), shows strong microwave sensitivity to sub-grid scale open water and inundated wetlands comprising open plant canopies. SWAMPS’ FW compares favorably (R[superscript 2] = 91%–94%) with higher-resolution, global-scale maps of open water from MODIS and SRTM-MOD44W. Correspondence of SWAMPS with open water and wetland products from satellite SAR in Alaska and the Amazon deteriorates when exposed wetlands or inundated forests captured by the SAR products were added to the open water fraction reflecting SWAMPS’ inability to detect water underneath the soil surface or beneath closed forest canopies. Except for a brief period of drying during the first 4 years of observation, the inundation extent for the global domain excluding the coast was largely stable. Regionally, inundation in North America is advancing while inundation is on the retreat in Tropical Africa and North Eurasia. SWAMPS provides a consistent and long-term global record of daily FW dynamics, with documented accuracies suitable for hydrologic assessment and global change-related investigations.The final version of this article, as published in Remote Sensing, can be viewed online at: http://www.mdpi.com/2072-4292/7/12/1584

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

Exploiting growing stock volume maps for large scale forest resource assessment: Cross-comparisons of ASAR- and PALSAR-based GSV estimates with forest inventory in Central Siberia

Growing stock volume is an important biophysical parameter describing the state and dynamics of the Boreal zone. Validation of growing stock volume (GSV) maps based on satellite remote sensing is challenging due to the lack of consistent ground reference data. The monitoring and assessment of the remote Russian forest resources of Siberia can only be done by integrating remote sensing techniques and interdisciplinary collaboration. In this paper, we assess the information content of GSV estimates in Central Siberian forests obtained at 25m from ALOS-PALSAR and 1km from ENVISAT-ASAR backscatter data. The estimates have been cross-compared with respect to forest inventory data showing 34% relative RMSE for the ASAR-based GSV retrievals and 39.4% for the PALSAR-based estimates of GSV. Fragmentation analyses using a MODIS-based land cover dataset revealed an increase of retrieval error with increasing fragmentation of the landscape. Cross-comparisons of multiple SAR-based GSV estimates helped to detect inconsistencies in the forest inventory data and can support an update of outdated forest inventory stands