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Indonesia, a country located in the equatorial region with hilly and valley lands surrounded by vast oceans, has complex rainfall patterns that can generally be classified into three types: equatorial, monsoon, and local. Rainfall estimates have only been derived based on local data and characteristics so far, and have not yet been developed based on universal data for all of Indonesia. This study aimed to develop a rainfall estimation model based on weather radar data throughout Indonesia using ensemble machine learning with the gradient boosting algorithm. The proposed rainfall estimation model is universal, can be applied to different rainfall pattern areas, and has a temporal resolution of 10 min. It is based on determining the root mean square error (RMSE) and R-squared (R2) values. Research was conducted in six areas with different rainfall patterns: Bandar Lampung and Banjarmasin with monsoon rain patterns, Pontianak and Deli Serdang with equatorial rain patterns, and the Gorontalo and Biak areas with local rain patterns. The analysis of the proposed model reveals that the best hyperparameters for the learning rate, maximum depth, and number of trees are 0.7, 3, and 50, respectively. The results demonstrate that the estimated rainfall in the six areas was very accurate, with RMSE < 2 mm/h and R2 > 0.7. [ABSTRACT FROM AUTHOR]

The remote detection of hydrothermally altered grounds in geothermal exploration demands datasets capable of reliably detecting key outcrops with fine spatial resolution. While optical thermal or radar-based datasets have resolution limitations, airborne LiDAR offers point-based detection through its LiDAR return intensity (LRI) values, serving as a proxy for surface reflectivity. Despite this potential, few studies have explored LRI value variations in the context of hydrothermal alteration and their utility in distinguishing altered from unaltered rocks. Although the link between alteration degree and LRI values has been established under laboratory conditions, this relationship has yet to be demonstrated in airborne data. This study investigates the applicability of laboratory results to airborne LRI data for alteration detection. Utilising LRI data from an airborne LiDAR point cloud (wavelength 1064 nm, density 12 points per square metre) acquired over a prospective geothermal area in Bajawa, Indonesia, where rock sampling for a related laboratory study took place, we compare the airborne LRI values within each ground sampling area of a 3 m radius (due to hand-held GPS uncertainty) with laboratory LRI values of corresponding rock samples. Our findings reveal distinguishable differences between strongly altered and unaltered samples, with LRI discrepancies of approximately ~28 for airborne data and ~12 for laboratory data. Furthermore, the relative trends of airborne and laboratory-based LRI data concerning alteration degree exhibit striking similarity. These consistent results for alteration degree in laboratory and airborne data mark a significant step towards LRI-based alteration mapping from airborne platforms. [ABSTRACT FROM AUTHOR]

Located in a tropical area with abundant precipitation, Indonesia is highly prone to heavy rain hazards, in particular landslides and floods. Thus, rainfall observation is vital. Nonetheless, the topography, the fund availability, as well as the archipelagic state of Indonesia may raise difficulties for in-situ observation, such as rain gauge and weather radar. Currently, the advance of radiometer satellites, such as the Global Precipitation Mission delivers rain estimation and has proven to show good association with in-situ observation on a monthly basis, not daily over the Indonesia area. Therefore, it is vital to have additional measurement methods. For the first time, we apply L-band Interferometric Synthetic Aperture Radar (InSAR) to observe heavy rain in Indonesia. From our three study cases, we successfully identified localized anomalies due to the dense water vapor during heavy rain in the InSAR images. The localized anomalies vary from 10.9 cm in West Java, 7.8 cm in East Kalimantan, and 7.7 cm in West Kalimantan. Furthermore, we utilize the split-spectrum method for our InSAR result; the high-water vapor occurrence in the troposphere associated with heavy rain should be identified in the nondispersive term. Nevertheless, due to long temporal separation and thinner bandwidth, the split-spectrum method results display unsatisfactory results. We conclude that, while InSAR has the ability to identify heavy rain, having SSM to distinguish between non-dispersive and dispersive phases is not currently practical in Indonesia. [ABSTRACT FROM AUTHOR]

Mount Semeru, one of the world's most active volcanoes, experiences frequent eruptions and at least one significant eruption annually. Traditional monitoring methods, constrained by the existing geodetic infrastructure, have been augmented by Interferometry Synthetic Aperture Radar (InSAR) technology. Previous InSAR applications in Indonesia have primarily relied on Line-of-Sight (LOS) displacement measurements, utilizing a single orbital geometry. This study breaks new applications by leveraging two orbital geometries of the Sentinel-1 satellite, advancing beyond conventional one-dimensional observations to generate comprehensive multidimensional displacement time series. This approach enables the precise capture of vertical, east-west, and north-south components of surface motion at Semeru volcano. Our findings underscore the critical role of multitrack InSAR data in providing a nuanced understanding of volcanic deformation. By encompassing all three displacement components, our methodology delivers a more detailed and accurate depiction of the volcano's dynamics. Although the 2.5D displacement model proves adequate in certain scenarios, the full three-dimensional analysis reveals its superiority in monitoring slow surface deformation. This study not only demonstrates the enhanced capabilities of InSAR in volcanic monitoring but also sets a precedent for its application in other high-risk volcanic and tectonic regions. Furthermore, our research emphasizes the value of integrating InSAR data with other monitoring techniques, like the Global Navigation Satellite System (GNSS), for cross-validation and accuracy enhancement. The synergy of these technologies offers a powerful tool for geoscientists, potentially enhancing our understanding of surface motion and contributing to more effective risk management in geologically active areas. [ABSTRACT FROM AUTHOR]

Agricultural landscapes play a crucial role in global carbon sequestration and biodiversity conservation. The presence of trees outside forests has been recognized as a significant carbon pool, but it is crucial to acknowledge that these trees serve purposes beyond being a carbon sink. This study focuses on integrating border trees and home gardens as distinct land use classes in Indonesian Javanese agricultural land to assess their impact on carbon stock potential and biodiversity connections. The objective is to classify and quantify the tree composition of these classes, estimate their carbon stock potential, analyze plant species diversity, and identify the ecological connections between home gardens and field borders. To achieve this, high-resolution multispectral and Synthetic Aperture Radar images were used from four sampling areas covering 100 km2 each in Lamongan and Malang districts, East Java, Indonesia, for land cover/land use mapping. The land use function method was used to identify border trees and home gardens as separate land use classes. Carbon stock potential was estimated based on tree cover composition, while plant species diversity was analyzed through field surveys and farmer focus group discussions. Crops with border trees cover approximately 28% to 48% of the cropland area in the study sites, while home gardens represent about 74% to 85% of the settlement area. This suggests a potential to double tree presence in these sites by adopting border trees and home gardens practices across the entire area. The median tree cover ratio was around 27% for border trees and 33% for home gardens. This stratification approach identified 31% to 50% more carbon stock compared to calculations using standard classes. Furthermore, home gardens and border trees show a positive correlation with species richness, indicating their role as keepers of biodiversity. Therefore, home gardens and border trees could serve as a sustainability indicator for agricultural land in the Javanese farm system. This research contributes to sustainable agricultural practices and climate change mitigation. The stratification approach of identifying border trees and home gardens offers a cost-effective approach for the better computation of carbon stock and can lead to effective land use policies and conservation measures that promote ecological resilience. The study provides valuable insights for similar agricultural contexts worldwide, guiding efforts toward a more sustainable agricultural future. [Display omitted] • Trees outside forests constitute significant carbon pools and play diverse ecological roles, not just carbon sinks. • Proposed classification categories of "home gardens" & "border trees" can enhance our understanding of their functions. • Multispectral and Synthetic Aperture Radar images were used for the analysis of land use and land cover. • This stratification approach identifies 31–50% more carbon stock than the conventional approach. • The home gardens and border trees area have a positive correlation with the number of species richness. [ABSTRACT FROM AUTHOR]

In 2018, four deadly (Mw 6.2–6.9) earthquakes struck the north coast of Lombok Island on 28 July, 5 August, and 19 August. The slip distributions of the three mainshocks are modeled in this study by inverting the co-seismic deformation imaged using an interferometric analysis of Sentinel-1 synthetic aperture radar measurements (InSAR), based on rectangular dislocations embedded in a multi-layered elastic half-space. Our best-fit co-seismic slip model suggests the estimated maximum fault slips of 1.3 m, 2.2 m, and 2.5 m for the mainshocks from July to August, located at depths of 9.6 km, 13.6 km, and 22.2 km, respectively. We applied an unsupervised learning method (ST-DBSCAN) to cluster the relocated aftershocks so that we could identify the source of each aftershock. The clustered aftershocks are primarily distributed in the areas with increased Coulomb stress and are less abundant in the maximum slip patch on the three rupture faults, indicating consistency with our estimated co-seismic slip model. In addition, we use an InSAR time series, consisting of 337 descending and 177 ascending Sentinel-1 acquisitions to investigate the time-dependent, post-seismic deformation in the two years following the Lombok 2018 earthquake sequence, based on a pure afterslip model and a combined model that simulates viscoelastic relaxation and afterslip simultaneously. The best-fit combined model suggests a Maxwell viscosity of 1 × 1018 Pa s for both the lower crust and asthenosphere, and it reveals that the maximum of the cumulative afterslip within two years is ∼0.7 m, along the northwestward up-dip continuation of the co-seismic rupture area. • InSAR-derived rupture model for each earthquake estimated using layered half-space. • Coulomb stress triggering possible for the 2nd, less likely for the 3rd mainshock. • Aftershock clusters distinguished for each event and found to decay over 1–2 weeks. • InSAR time-series used to determine afterslip considering viscoelastic lower crust. • Afterslip persisted for many months, even after aftershock sequences decayed. [ABSTRACT FROM AUTHOR]

Since 2001, the Indonesian government has formulated and implemented several restoration programs to improve the Citarum's water quality. However, these programs were often contested, particularly concerning the meanings of 'water quality' and how those informed approaches to responsibility and involvement. This paper problematises river restoration in view of these controversies towards improving people's lives and their environment. Our investigation found (1) a selective use of scientific knowledge of water quality and related responsibilities; (2) a tension between broader inclusion and military involvement in river restoration; and (3) a diverse host of informal restoration practices that largely remain unnoticed in view of the government programs. The findings indicate that river governance can benefit from recognising and tuning into below-the-radar restoration practices to tackle river pollution. [ABSTRACT FROM AUTHOR]

This study proposes the entire detection of the surface deformation of a volcanic area using interferometric synthetic aperture radar (InSAR) with geostatistics to specify the locations and shapes of the sources causing the deformation. We selected the Tangkuban Parahu area, West Java, Indonesia, as our study site and used a Sentinel-1 dataset. In this study, we combine persistent scatterer and small baseline subset InSAR with a geostatistical technique, i.e., turning bands simulation. This combination can compensate for undetected displacement pixels and decompose the line-of-sight displacement into vertical and horizontal east–west displacements using both the ascending and descending mode results and the least-squares method. This two-dimensional geostatistics and multitemporal InSAR approach is referred to as 2D GMT-InSAR. A detailed displacement pattern is revealed by 2D GMT-InSAR for undetected pixels in low-coherence areas. Then, the vertical displacement pattern in the study period from 2014 to 2019, mainly uplift with local subsidence, is reproduced via the joint use of the Mogi and Okada models for circular and rectangular parallelepiped sources of the deformation, respectively. Via a Bayesian inversion, one circular source, equivalent to a magma reservoir, and one dyke source are identified. The displacement pattern is likely caused by pressure increases in the magma reservoir, associated with the volcanic activation, and in the dyke, associated with the gas and fluid flows from the reservoir, which induced a phreatic explosion in July 2019. A connection of the dyke with the old Sunda volcanic system is found; this new finding is a result of the caldera collapse during the Sunda volcanic eruption. • Up–down and east–west displacements were revealed via turning bands simulations • Volcanic uplift before a 2019 eruption was detected by InSAR with geostatistics • Inversion of interpolated InSAR data was effective to estimate magma reservoir system • Two shallow magma reservoirs were located at depths of ∼1100 m and 3700 m • These reservoirs were likely formed by collapse and evolution of a nearby volcano [ABSTRACT FROM AUTHOR]

The earthquake, which occurred in Yogyakarta, Indonesia, on May 26, 2006, at 22:53:58 UTC with Mw ∼6.4, was one of the most destructive earthquakes in Indonesia. The earthquake caused thousands of fatalities, tens of thousands of injuries, and hundreds of thousands of house damages in the Yogyakarta area and its surroundings at a loss of billions of dollars. Previous studies from seismic tomography and satellite radar imaging hypothesized that the earthquake was caused by activating a so far unknown fault east of the Opak Fault. Although, in the beginning, the Opak fault was suspected to be the source of the Yogyakarta earthquake in 2006. This assumption was made because the damage was maximum in the Bantul area west of the Opak Fault. This study demonstrates that our seismic tomography achieved a higher resolution than the previous study and could resolve a failed complex fault system. We utilized more aftershocks (2170 events) and smaller grid sizes for seismic tomography inversion. Four focal mechanisms from aftershocks for Mw ≥ 4.5 were also conducted to support structure interpretation in the study area. Our results successfully delineate the Opak Fault and the second fault, namely the Ngalang Fault, parallel to the eastern part of the fault at a depth of 9 km. Two faults could be indicated by the velocity contrast of Vp, Vp/Vs ratio, and Vs from a horizontal section tomogram. Our focal mechanisms also support seismic tomography, revealing two fault planes in our study area. The results show that the two faults are connected by the Oyo Fault, which is ruptured in the opposite direction compared to the two faults. [Display omitted] • We analyze aftershocks, seismic tomography, and focal mechanisms to image detailed subsurface structures and faults around the Yogyakarta earthquake zone 2006. • Imaging higher resolution of local seismic tomography beneath the earthquake zone in unprecedented detail • Focal mechanisms of selected aftershocks are conducted to support structure interpretation. • The Oyo Fault connects the Ngalang Fault (the earthquake source of the Yogyakarta 2006) and the Opak Fault. [ABSTRACT FROM AUTHOR]