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In 2016, the first processing of the semi-global digital surface models (DSMs) utilizing all the archives of stereo imageries derived from the Panchromatic Remote sensing Instrument for Stereo Mapping (PRISM) onboard the Advanced Land Observing Satellite (ALOS) was successfully completed. The dataset was freely released to the public in 30 m grid spacing as the 'ALOS World 3D - 30m (AW3D30)', which was generated from its original version processed in 5 m or 2.5 m grid spacing. The dataset has been updated since then to improve the absolute/relative height accuracies with additional calibrations. However, the most significant update that should be applied for improving the data usability is the filling of void areas, which correspond to approx. 10% of semiglobal coverage, mostly due to cloud covers. In 2020, we completed the filling process by using other open-access digital elevation models (DEMs) such as Shuttle Radar Topography Mission (SRTM) DEM, Advanced Spaceborne Thermal Emission and Reflection Radiometer Global DEM (ASTER GDEM), ArcticDEM, etc., except for Antarctica. In this paper, we report on the filling process of the remaining voids in Antarctica by using other open-access DEMs such as Reference Elevation Model of Antarctica (REMA) DSM, TerraSAR-X add-on for Digital Elevation Measurement (TanDEM-X, TDX) 90m DEM, and ASTER GDEM to complete the void-free semi-global AW3D30 datasets. [ABSTRACT FROM AUTHOR]

In 2016 we first completed the global data processing of digital surface models (DSMs) by using the whole archives of stereo imageries derived from the Panchromatic Remote sensing Instrument for Stereo Mapping (PRISM) onboard the Advanced Land Observing Satellite (ALOS). The dataset was freely released to the public in 30 m grid spacing as the 'ALOS World 3D - 30m (AW3D30)', which was generated from its original version processed in 5 m or 2.5 m grid spacing. The dataset has been updated since then to improve the absolute/relative height accuracies with additional calibrations. However the most significant update that should be applied for improving the data usability is the filling of void areas, which correspond to approx. 10% of global coverage, mostly due to cloud covers. In this paper we introduce the updates of AW3D30 filling the voids with other open-access DSMs such as Shuttle Radar Topography Mission (SRTM) Digital Elevation Model (DEM), Advanced Spaceborne Thermal Emission and Reflection Radiometer Global DEM (ASTER GDEM), ArcticDEM, etc., through inter-comparisons among these datasets. [ABSTRACT FROM AUTHOR]

The "Advanced Land Observing Satellite-3" (ALOS-3, nicknamed "DAICHI-3") is the next high-resolution optical mission as a successor of the optical mission by the Advanced Land Observing Satellite (ALOS, "DAICHI") in Japan Aerospace Exploration Agency (JAXA), and will be launched in Japanese Fiscal Year 2020. ALOS-3 is now under developing the flight model. The major missions of ALOS-3 are (1) to contribute safe and secure social including provision for natural disasters, and (2) to create and update geospatial information in land and coastal areas. To achieve the missions, the "WIde-Swath and High-resolution optical imager" (WISH, as a tentative name) is mounted on ALOS-3, which consists of the high-resolution panchromatic- and multispectral-bands.This paper introduces the overview of ALOS-3's mission and the calibration and validation plan at JAXA. The standard product is the system corrected data using the sensor models, which will be provided from the sensor development team. Therefore, the sensor calibration is directly affected to the accuracies of the standard product. In addition, the sensor model based the Rational Polynomial Coefficient will be contained with level 1B2 standard product that can be used to process an ortho rectification and three-dimensional measurement from ALOS-3 images. As the target accuracy of WISH's standard products, the geometric accuracies are less than 5 m in horizontal without ground control point (GCP), and 1.25 m in horizontal and 2.5 m in vertical with GCPs (1 sigma), and the radiometric accuracy is ± 10 % as absolutely and ± 5 % as relatively for multispectral band. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Accuracy assessment of forest type maps is essential to evaluate the classification of forest ecosystems quantitatively. However, map users do not understand in which regions those forest types are well classified from conventional static accuracy measures. Hence, the objective of this study is to unveil spatial heterogeneities of accuracies of forest type classification in a map. Four forest types (deciduous broadleaf forest (DBF), deciduous needleleaf forest (DNF), evergreen broadleaf forest (EBF), and evergreen needleleaf forest (ENF)) found in the JAXA's land use / cover map of Japan were assessed by a volunteered Site-based dataset for Assessment of Changing LAnd cover by JAXA (SACLAJ). A geographically weighted (GW) correspondence matrix was applied to them to calculate the degree of overall agreements of forest type classes (forest overall accuracy), and the degree of accuracy for each forest class (forest user's and producer's accuracies) in a spatially varying way. This study compared spatial surfaces of these measures with static ones of them. The results show that the forest overall accuracy of the forest map tends to be relatively more accurate in the central Japan, while less in the Kansai and Chubu regions and the northern edge of Hokkaido. Static forest user's accuracy measures for DBF, DNF, and ENF are better than forest producer's accuracy ones, while the GW approach tells us such characteristics vary spatially and some areas have opposite trends. This kind of spatial accuracy assessment provides a more informative description of the accuracy than the simple use of conventional accuracy measures. [ABSTRACT FROM AUTHOR]

Topographical information is fundamental to many geo-spatial related information and applications on Earth. Remote sensing satellites have the advantage in such fields because they are capable of global observation and repeatedly. Several satellite-based digital elevation datasets were provided to examine global terrains with medium resolutions e.g. the Shuttle Radar Topography Mission (SRTM), the global digital elevation model by the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER GDEM). A new global digital surface model (DSM) dataset using the archived data of the Panchromatic Remote-sensing Instrument for Stereo Mapping (PRISM) onboard the Advanced Land Observing Satellite (ALOS, nicknamed "Daichi") has been completed on March 2016 by Japan Aerospace Exploration Agency (JAXA) collaborating with NTT DATA Corp. and Remote Sensing Technology Center, Japan. This project is called "ALOS World 3D" (AW3D), and its dataset consists of the global DSM dataset with 0.15 arcsec. pixel spacing (approx. 5 m mesh) and ortho-rectified PRISM image with 2.5 m resolution. JAXA is also processing the global DSM with 1 arcsec. spacing (approx. 30 m mesh) based on the AW3D DSM dataset, and partially releasing it free of charge, which calls "ALOS World 3D 30 m mesh" (AW3D30). The global AW3D30 dataset will be released on May 2016. This paper describes the processing status, a preliminary validation result of the AW3D30 DSM dataset, and its public release status. As a summary of the preliminary validation of AW3D30 DSM, 4.40 m (RMSE) of the height accuracy of the dataset was confirmed using 5,121 independent check points distributed in the world. [ABSTRACT FROM AUTHOR]

Digital glacier inventories are invaluable data sets for revealing the characteristics of glacier distribution and for upscaling measurements from selected locations to entire mountain ranges. Here, we present a new inventory of Advanced Land Observing Satellite (ALOS) imagery and compare it with existing inventories for the Bhutan Himalaya. The new inventory contains 1583 glaciers (1487±235 km²), thereof 219 debris-covered glaciers (951±193 km²) and 1364 debris-free glaciers (536±42 km²). Moreover, we propose an index for quantifying consistency between two glacier outlines. Comparison of the overlap ratio demonstrates that the ALOS-derived glacier inventory contains delineation uncertainties of 10-20% which depend on glacier size, that the shapes and geographical locations of glacier outlines derived from the fourth version of the Randolph Glacier Inventory have been improved in the fifth version, and that the latter is consistent with other inventories. In terms of whole glacier distribution, each data set is dominated by glaciers of 1.0-5.0 km² area (31-34% of the total area), situated at approximately 5400m elevation (nearly 10% in 100m bin) with either north or south aspects (22 and 15 %). However, individual glacier outlines and their area exhibit clear differences among inventories. Furthermore, consistent separation of glaciers with inconspicuous termini remains difficult, which, in some cases, results in different values for glacier number. High-resolution imagery from Google Earth can be used to improve the interpretation of glacier outlines, particularly for debris-covered areas and steep adjacent slopes. [ABSTRACT FROM AUTHOR]

Most glaciological studies in Argentina have focused on the large outlet glaciers of the Southern Patagonia Icefield (SPI); the numerous smaller neighboring glaciers have received significantly less attention. We present an inventory of 248 medium- to small-size glaciers (0.01-25km2) adjacent to the northeast margin of the SPI, describe their change over the period 1979-2005 and assess local and regional climatic variations in an attempt to explain the observed glacier changes. Based on an ASTER mosaic from 20 February 2005 and the ASTER Global Digital Elevation Model, we identified a total glacier area of 187.2-7.4km2 between 600 and 2870ma.s.l. Glaciers are largely debris-free and are concentrated in the western, more humid sector adjacent to the SPI. Using a 20 March 1979 US military intelligence Hexagon KH-9 satellite photograph, we measured a total areal reduction of ∼33.7 km2 (15.2%) between 1979 and 2005. Ablation season temperatures from the study area have followed a regional warming trend that could partly explain the observed glacier shrinkage. Annual precipitation estimates show a gradual decrease between 1979 and 2002 that may also have contributed to the ice mass loss. [ABSTRACT FROM AUTHOR]

The Japan Aerospace Exploration Agency (JAXA) generated the global digital elevation/surface model (DEM/DSM) and orthorectified image (ORI) using the archived data of the Panchromatic Remote-sensing Instrument for Stereo Mapping (PRISM) onboard the Advanced Land Observing Satellite (ALOS, nicknamed "Daichi"), which was operated from 2006 to 2011. PRISM consisted of three panchromatic radiometers that acquired along-track stereo images. It had a spatial resolution of 2.5 m in the nadir-looking radiometer and achieved global coverage, making it a suitable potential candidate for precise global DSM and ORI generation. In the past 10 years or so, JAXA has conducted the calibration of the system corrected standard products of PRISM in order to improve absolute accuracies as well as to validate the high-level products such as DSM and ORI. In this paper, we introduce an overview of the global DEM/DSM dataset generation project, including a summary of ALOS and PRISM, in addition to the global data archive status. It is also necessary to consider data processing strategies, since the processing capabilities of the level 1 standard product and the high-level products must be developed in terms of both hardware and software to achieve the project aims. The automatic DSM/ORI processing software and its test processing results are also described. [ABSTRACT FROM AUTHOR]

Simultaneous field data collections and Advanced Land Observing Satellite/Phased Array type L-band Synthetic Aperture Radar (PALSAR) full polarimetry observations were performed in Ulaanbaatar (Mongolia) and Alaska (USA). Permafrost is present at the Alaska test sites. Backscattering copolarization ( σco-pol0) values derived from the PALSAR data were compared with those calculated using the integrated equation method (IEM) model, a popular theoretical model describing surface scattering. PALSAR data taken in Ulaanbaatar matched the IEM model results to within a few decibels, whereas data taken in Alaska were 5 to 7 dB lower than those calculated using the IEM model. On the other hand, the σcross-pol0 (σVH0) components estimated from the Oh model were well matched to the PALSAR data in both Ulaanbaatar and Alaska. Moisture levels of the sphagnum moss layer in Alaska were estimated to be about 10% while moisture levels of the underlying organic and mineral layers were 25% to 79%; the moisture values of the organic and mineral layers were factored into the IEM and Oh models. When surface moisture levels of 10% were assumed for Alaska ground conditions, the σco-pol0 values calculated using the IEM model and those derived from the PALSAR data were well matched. From these observations, we conclude that the sphagnum moss layer, which is a seasonally unfrozen layer that occurs above permafrost, plays an important role in radar backscattering processes in permafrost regions and is a main contributor to the σco-pol0 backscattering component; the underlying organic and mineral layers contribute mainly to the σcross-pol0 backscattering component. A two-layer model was applied to the data from a test site in Alaska; the model described the co- and cross-polarization backscatter (σ0) derived from PALSAR data with off-nadir angles of 21.5° and 34.3°. [ABSTRACT FROM AUTHOR]

The purpose of this letter is to present the results on the study of searching effective parameters that describe the relation between high-resolution synthetic aperture radar (SAR) images and forest parameters. The study is based on the non-Gaussian texture analysis of the polarimetric airborne Pi-SAR data over coniferous forests in Hokkaido, Japan. The radar cross section (RCS) in terms of a forest biomass is first analyzed. It is found that the L-band RCS increases steadily with the biomass and saturates at approximately 40 tons/ha. These results are similar to the previous studies. The probability density function of the image amplitude is then investigated, and among Rayleigh, log-normal, Weibull, and K-distributions, the K-distribution is found to fit best to the L-band data of all polarizations, although the Weibull distribution fits equally well. Further, the correlation between the tree biomass and the order parameter of the K-distribution in the cross-polarization images is found to be very high, and the order parameter increases consistently with the biomass to approximately 100 tons/ha, which is well beyond the saturation limit of the L-band RCS. Thus, the order parameter of the K-distribution can be a promising new parameter to estimate the forest biomass from high-resolution polarimetric SAR data in a much wider range than the conventional RCS method [ABSTRACT FROM PUBLISHER]

Land use land cover (LULC) maps are crucial for various applications, such as disaster management, natural resource conservation, biodiversity evaluation, climate modeling, etc. The Japan Aerospace Exploration Agency (JAXA) has released several high-resolution LULC maps for national and regional scales. Vietnam, due to its rich biodiversity and cultural diversity, is a target country for the production of high-resolution LULC maps. This study introduces a high-resolution and high-accuracy LULC map for Vietnam, utilizing a CNN approach that performs convolution over a time-feature domain instead of the typical geospatial domain employed by conventional CNNs. By using multi-temporal data spanning 6 seasons, the produced LULC map achieved a high overall accuracy of 90.5% ± 1.2%, surpassing other 10-meter LULC maps for Vietnam in terms of accuracy and/or the ability to capture detailed features. In addition, a straightforward and practical approach was proposed for generating cloud-free multi-temporal Sentinel-2 images, particularly suitable for cloudy regions. This study marks the first implementation of the time-feature CNN approach for the creation of a high-accuracy LULC map in a tropical cloudy country., (© 2024. The Author(s).)

Space-based remote sensing can make an important contribution toward monitoring greenhouse gas emissions and removals from the agriculture, forestry, and other land use (AFOLU) sector, and to understanding and addressing human-caused climate change through the UNFCCC Paris Agreement. Space agencies have begun to coordinate their efforts to identify needs, collect and harmonize available data and efforts, and plan and maintain a long-term roadmap for observations. International cooperation is crucial in developing and realizing the roadmap, and the Committee on Earth Observation Satellites (CEOS) is a key coordinating driver of this effort. Here, we first identify the data and information that will be useful to support the global stocktake (GST) of the Paris Agreement. Then, the paper explains how existing and planned space-based capabilities and products can be used and combined, particularly in the land use sector, and provides a workflow for their harmonization and contribution to greenhouse gas inventories and assessments at the national and global level., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2023 The Author(s).)

Extensive studies have highlighted a need for frequently consistent land cover information for interdisciplinary studies. This paper proposes a comprehensive framework for the automatic production of the first Vietnam-wide annual land use/land cover (LULC) data sets (VLUCDs) from 1990 to 2020, using available remotely sensed and inventory data. Classification accuracies ranged from 85.7 ± 1.3 to 92.0 ± 1.2% with the primary dominant LULC and 77.6 ± 1.2% to 84.7 ± 1.1% with the secondary dominant LULC. This confirmed the potential of the proposed framework for systematically long-term monitoring LULC in Vietnam. Results reveal that despite slight recoveries in 2000 and 2010, the net loss of forests (19,940 km 2 ) mainly transformed to croplands over 30 years. Meanwhile, productive croplands were converted to urban areas, which increased approximately ten times. A threefold increase in aquaculture was a major driver of the wetland loss (1914 km 2 ). The spatial-temporal changes varied, but the most dynamic regions were the western north, the southern centre, and the south. These findings can provide evidence-based information on formulating and implementing coherent land management policies. The explicitly spatio-temporal VLUCDs can be benchmarks for global LULC validation, and utilized for a variety of applications in the research of environmental changes towards the Sustainable Development Goals.

Early warning systems (EWS) have been proposed as a measure for controlling and preventing dengue fever outbreaks in countries where this infection is endemic. A vaccine is not available and has yet to reach the market due to the economic burden of development, introduction and safety concerns. Understanding how dengue spreads and identifying the risk factors will facilitate the development of a dengue EWS, for which a climate-based model is still needed. An analysis was conducted to examine emerging spatiotemporal hotspots of dengue fever at the township level in Taiwan, associated with climatic factors obtained from remotely sensed data in order to identify the risk factors. Machinelearning was applied to support the search for factors with a spatiotemporal correlation with dengue fever outbreaks. Three dengue fever hotspot categories were found in southwest Taiwan and shown to be spatiotemporally associated with five kinds of sea surface temperatures. Machine-learning, based on the deep AlexNet model trained by transfer learning, yielded an accuracy of 100% on an 8-fold cross-validation test dataset of longitudetime sea surface temperature images.

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.

The east Japan earthquake that occurred on March 11, 2011 was a big natural disaster, comprising the large earthquake shock, tsunami, and Fukushima Daiichi Nuclear Power Plant (FDNPP) accident. These disasters caused changes in the land use and land cover (LULC) in Japan's Tohoku district. While the LULC map created before the disaster is available, as yet there is no precise LULC map of the district after the disaster. In this study, we created a precise LULC map for the years 2013-2015 post-disaster with 30-m spatial resolution using the Landsat-8 with the Operational Land Imager (OLI) to evaluate the changes in LULC induced by the disaster. Our results indicate many changes in areas categorized as rice paddies primarily into grass categories along the coast damaged by the tsunami and in the evacuation zone around the FDNPP. Since there is a possibility of future LULC changes according to the change of the evacuation zone and implementation of reconstruction and revitalization efforts, we recommend continual monitoring of the changes in LULC by the use of satellite data in order to evaluate the long-term effects of the disaster.

Environmental surveillance supplements the surveillance of acute flaccid paralysis by monitoring wastewater for poliovirus circulation. Building on previous work, we analysed wastewater flow to optimise selection and placement of sampling sites with higher digital surface model (DSM) resolution. The newly developed 5-m mesh DSM from the panchromatic, remote-sensing instruments for stereo mapping on-board the Japanese advanced land observing satellite was used to estimate catchment areas and flow of sewage water based on terrain topography. Optimal sampling sites for environmental surveillance were identified to maximise sensitivity to poliovirus circulation. Population data were overlaid to prioritise selection of catchment areas with dense populations. The results for Kano City, Nigeria were compared with an analysis based on existing 30- and 90-m mesh digital elevation model (DEM). Analysis based on 5-m mesh DSM was also conducted for three cities in Niger to prioritise the selection of new sites. The analysis demonstrated the feasibility of using DSMs to estimate catchment areas and population size for programme planning and outbreak response with respect to polio. Alternative sampling points in Kano City that would cover a greater population size have been identified and potential sampling sites in Niger are proposed. Comparison with lower-resolution DEMs suggests that the use of a 5-m mesh DSMs would be useful where the terrain is flat or includes small-scale topographic changes not captured by 30-m data searches.

The aim of the present study was to identify geographical areas and time periods of potential clusters of dengue cases based on ecological, socio-economic and demographic factors in northern Sri Lanka from January 2010 to December 2013. Remote sensing (RS) was used to develop an index comprising rainfall, humidity and temperature data. Remote sensing data gathered by the AVNIR-2 instrument onboard the ALOS satellite were used to detect urbanisation, and a digital land cover map was used to extract land cover information. Other data on relevant factors and dengue outbreaks were collected through institutions and extant databases. The analysed RS data and databases were integrated into a geographical information system (GIS) enabling space-time clustering analysis. Our results indicate that increases in the number of combinations of ecological, socio-economic and demographic factors that are present or above the average contribute to significantly high rates of space-time dengue clusters. The spatio-temporal association that consolidates the two kinds of associations into one can ensure a more stable model for forecasting. An integrated spatiotemporal prediction model at a smaller level using ecological, socioeconomic and demographic factors could lead to substantial improvements in dengue control and prevention by allocating the right resources to the appropriate places at the right time.