Japan Aerospace Exploration Agency’s public-health monitoring and analysis platform: A satellite-derived environmental information system supporting epidemiological study

Since the 1970s, Earth-observing satellites collect increasingly detailed environmental information on land cover, meteorological conditions, environmental variables and air pollutants. This information spans the entire globe and its acquisition plays an important role in epidemiological analysis when in situ data are unavailable or spatially and/or temporally sparse. In this paper, we present the development of Japan Aerospace Exploration Agency’s (JAXA) Public-health Monitoring and Analysis Platform available from JAXA, a user-friendly, web-based system providing environmental data on shortwave radiation, rainfall, soil moisture, the normalized difference vegetation index, aerosol optical thickness, land surface temperature and altitude. This system has been designed so that users should be able to download and utilize data without the need for additional data processing. The website allows interactive exchange and users can request data for a specific geographic location and time using the information gained for epidemiological analysis

Relation between urban volume and land surface temperature: A comparative study of planned and traditional cities in Japan

The horizontal two-dimensional (2D) urban land use approach is not sufficient to trace rapid changes in urban environment. Hence, a three-dimensional (3D) approach that is different from the traditional geographical method is necessary to understand the mechanism of compound urban diversity. Using remote sensing data captured in 2010/2011 and geospatial tools and techniques, we quantified the urban volume (UV, consisting of urban built volume (UBV) and urban green volume (UGV)) and retrieved and mapped the land surface temperature (LST) of two cities in Japan (Tsukuba, a planned city, and Tsuchiura, a traditional city). We compared these two cities in terms of (1) UBV and UGV and their relationships with mean LST; and (2) the relationship of the UGV–UBV ratio with mean LST. Tsukuba had a total UBV of 74 million m3, while Tsuchiura had a total of 89 million m3. In terms of UGV, Tsukuba had a total of 52 million m3, while Tsuchiura had a total of 29 million m3. In both cities, UBV had a positive relationship with mean LST (Tsukuba: R2 = 0.31, p < 0.001; Tsuchiura: R2 = 0.42, p < 0.001), and UGV had a negative relationship with mean LST (Tsukuba: R2 = 0.53, p < 0.001; Tsuchiura: R2 = 0.19, p < 0.001). Tsukuba also had a higher UGV–UBV ratio of 54.9% in comparison with Tsuchiura, with 28.7%. Overall, the results indicate that mean LST was more intense in the traditional city (Tsuchiura). This could have been due to the difference in urban spatial structure. As a planned city, Tsukuba is still a relatively young city that has more dispersed green spaces and a well-spread (so far) built-up area

Global Mangrove Extent Change 1996–2020:Global Mangrove Watch Version 3.0

Mangroves are a globally important ecosystem that provides a wide range of ecosystem system services, such as carbon capture and storage, coastal protection and fisheries enhancement. Mangroves have significantly reduced in global extent over the last 50 years, primarily as a result of deforestation caused by the expansion of agriculture and aquaculture in coastal environments. However, a limited number of studies have attempted to estimate changes in global mangrove extent, particularly into the 1990s, despite much of the loss in mangrove extent occurring pre-2000. This study has used L-band Synthetic Aperture Radar (SAR) global mosaic datasets from the Japan Aerospace Exploration Agency (JAXA) for 11 epochs from 1996 to 2020 to develop a long-term time-series of global mangrove extent and change. The study used a map-to-image approach to change detection where the baseline map (GMW v2.5) was updated using thresholding and a contextual mangrove change mask. This approach was applied between all image-date pairs producing 10 maps for each epoch, which were summarised to produce the global mangrove time-series. The resulting mangrove extent maps had an estimated accuracy of 87.4% (95th conf. int.: 86.2–88.6%), although the accuracies of the individual gain and loss change classes were lower at 58.1% (52.4–63.9%) and 60.6% (56.1–64.8%), respectively. Sources of error included misregistration in the SAR mosaic datasets, which could only be partially corrected for, but also confusion in fragmented areas of mangroves, such as around aquaculture ponds. Overall, 152,604 km2 (133,996–176,910) of mangroves were identified for 1996, with this decreasing by -5245 km2 (-13,587–1444) resulting in a total extent of 147,359 km2 (127,925–168,895) in 2020, and representing an estimated loss of 3.4% over the 24-year time period. The Global Mangrove Watch Version 3.0 represents the most comprehensive record of global mangrove change achieved to date and is expected to support a wide range of activities, including the ongoing monitoring of the global coastal environment, defining and assessments of progress toward conservation targets, protected area planning and risk assessments of mangrove ecosystems worldwide

Development of an Operational Algorithm for Automated Deforestation Mapping via the Bayesian Integration of Long-Term Optical and Microwave Satellite Data

The frequent fine-scale monitoring of deforestation using satellite sensors is important for the sustainable management of forests. Traditional optical satellite sensors suffer from cloud interruption, particularly in tropical regions, and recent active microwave sensors (i.e., synthetic aperture radar) demonstrate the difficulty in data interpretation owing to their inherent sensor noise and complicated backscatter features of forests. Although the sensor integration of optical and microwave sensors is of compelling research interest, particularly in the conduct of deforestation monitoring, this topic has not been widely studied. In this paper, we introduce an operational algorithm for automated deforestation mapping using long-term optical and L-band SAR data, including a simple time-series analysis of Landsat stacks and a multilayered neural network with Advanced Spaceborne Thermal Emission and Reflection Radiometer and Phased Array-type L-band Synthetic Aperture Radar-2, followed by sensor integration based on the Bayesian Updating of Land-Cover. We applied the algorithm over a deciduous tropical forest in Cambodia in 2003–2018 for validation, and the algorithm demonstrated better accuracy than existing approaches, which only depend on optical data or SAR data. Owing to the cloud penetration ability of SAR, observation gaps of optical data under cloudy conditions were filled, resulting in a prompter detection of deforestation even in the tropical rainy season. We also investigated the effect of posterior probability constraints in the Bayesian approach. The land-cover maps (forest/deforestation) created by the well-tuned Bayesian approach achieved 94.0% ± 4.5%, 80.0% ± 10.1%, and 96.4% ± 1.9% for the user’s accuracy, producer’s accuracy, and overall accuracy, respectively. In the future, small-scale commission errors in the resultant maps should be improved by using more sophisticated machine-learning approaches and considering the reforestation effects in the algorithm. The application of the algorithm to other landscapes with other sensor combinations is also desirable

Rock Glaciers in the Patagonian Andes: An Inventory for the Monte San Lorenzo (Cerro Cochrane) Massif, 47° S

Although rock glaciers in the Central and Desert Andes of Argentina and Chile have been previously studied in detail, much less attention has been paid to the occurrence of these permafrost forms in Patagonia. Recently, however, the establishment of the Argentinean Glacier Inventory program, which intends to inventory and monitor all ice masses along the Argentinean Andes, has started a large amount of new geocryological research. The project is designed to provide reliable and worldwide comparable results, supported by well established technical procedures and background information. Presented here is the first rock glacier inventory of the Monte San Lorenzo (Cerro Cochrane) region in the southern Patagonian Andes. A total of 130 intact (9.86 km2) and 47 fossil (1.45 km2) landforms were inventoried using two 2.5 m resolution ALOS Panchromatic Remote-sensing Instruments for Stereo Mapping images. Since the Argentinean federal initiative described above legally protects all rock glaciers in the country as water reserves, and due to the little scientific knowledge concerning rock glaciers in the vast majority of the Patagonian Andes, this inventory provides an important basis for political decision-making and opens further geocryological research avenues for the Patagonian region in general.Fil: Falaschi, Daniel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mendoza. Instituto Argentino de Nivología, Glaciología y Ciencias Ambientales. Provincia de Mendoza. Instituto Argentino de Nivología, Glaciología y Ciencias Ambientales. Universidad Nacional de Cuyo. Instituto Argentino de Nivología, Glaciología y Ciencias Ambientales; ArgentinaFil: Tadono, Takeo. Japan Aerospace Exploration Agency; JapónFil: Masiokas, Mariano Hugo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mendoza. Instituto Argentino de Nivología, Glaciología y Ciencias Ambientales. Provincia de Mendoza. Instituto Argentino de Nivología, Glaciología y Ciencias Ambientales. Universidad Nacional de Cuyo. Instituto Argentino de Nivología, Glaciología y Ciencias Ambientales; Argentin