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Large debris avalanche and associated eruptive event at Samalas volcano, Lombok, Indonesia

Publication Friday, 19 April 2024

Malawani, Mukhamad Ngainul | Lavigne, Franck | Kelfoun, Karim | Lahitte, Pierre | Hadmoko, Danang Sri | Gomez, Christopher | Wassmer, Patrick | Syamsuddin, Syamsuddin | Faral, Audrey

Bulletin of Volcanology, Volume 86, Issue 3, March 2024, Article number 24

Abstract

We propose a vast area in the middle of Lombok, Indonesia, dominated by hummock hills, is a debris avalanche deposit (DAD). We define this > 500 km2 area as Kalibabak DAD that may originate from Samalas volcano. No descriptions of the morphology, stratigraphy, mechanism, and age of this DAD have yet been reported; this contribution bridges this research gap. Here we present morphological and internal architecture analysis, radiocarbon dating, paleotopographic modeling, and numerical simulation of the DAD. We also present geospatial data e.g., topographical and geological maps, digital elevation models (DEMs), satellite imagery – in combination with stratigraphic data constructed from field surveys, archived data, and electrical resistivity data. Results show that the DAD was formed by a sector-collapse of Samalas volcano and covers an area of 535 km2, with a deposit width of 41 km and a runout distance up to 39 km from the source. The average deposit thickness is 28 m, reaching a measured local maximum of 58 m and a calculated volume of ~ 15 km3. Andesitic breccia boulders and a sandy matrix dominate the deposit. Using ShapeVolc, we reconstructed the pre-DAD paleotopography and then used the reconstructed DEM to model the debris avalanche using VolcFlow. The model provides an estimate of the flow characteristics, but the extent of the modelled deposit does not match the present-day deposit, for at least two reasons: (i) the lack of information on the previous edifice topography that collapsed, and (ii) limited understanding of how DADs translate across the landscape. Fourteen radiocarbon dating samples indicate that the DAD was emplaced between 7,000–2,600 BCE. The DAD’s enormous volume, vast extent and poorly weathered facies strongly suggest that it was not triggered by a Bandai-type debris avalanche (solely phreatic eruption), but more likely by a Bezymianny-type (magmatic eruption). This event was potentially triggered by a sub-Plinian or Plinian eruption (high eruption column with umbrella-like cloud) dated ~ 3,500 BCE, which produced the Propok pumice fall deposits. © International Association of Volcanology & Chemistry of the Earth’s Interior 2024. read more

SYNERGIZING LANDSAT-8 AND MODIS DATA FOR ENHANCED PADDY PHENOLOGY ASSESSMENT AND CROP FREQUENCY MAPPING: A FUSION OF PHENOLOGICAL INSIGHTS AND MACHINE LEARNING ALGORITHMS

Publication Friday, 19 April 2024

Kartika Ningrum, Putri Laila | Satrio Pratama, Bimo Adi | Arjasakusuma, Sanjiwana

Geographia Technica, Open Access, Volume 19, Issue 1, Pages 121 – 134, March 2024

Abstract

The increasing demand for food and the impact of climate change underscore the need for intensified food production processes to continually address the growing population’s requirements. A critical aspect of food planning involves the identification of cropping frequency, serving as a key strategy for enhancing food production. Remote sensing plays a pivotal role in capturing cropping frequency information by analyzing phenological characteristics recorded in band transformations. Furthermore, the integration of machine learning allows for the categorization of patterns derived from index responses, eliminating the need to individually detect each phenological phase. The study aims to assess the accuracy of multi-sensor data fusion using the STARFM algorithm and machine learning to produce dense time-series images combining Landsat-8 and MODIS downscaled imagery for mapping paddy’s phenology and identifying paddy cropping frequencies. The phenology identification results demonstrate an accuracy range of 3-4 months for the Landsat dataset and less than 1 (one) month for the dataset resulting from its fusion with MODIS. Concurrently, the cropping frequency identification reveals an accuracy of 60%, 42.5%, 95%, 85%, and 100%, respectively, for Landsat phenology, fusion phenology, Landsat Decision Tree, fusion Decision Tree, and Random Forest for both datasets. This underscores the profound impact of data availability and quality on the accuracy of the obtained results. Dense time-series remote sensing data can be used for mapping cropping frequency to indicate the productive paddy areas which should be protected to ensure food security in the future. © 2024, Asociatia Geographia Technica. All rights reserved. read more

PROJECTIONS OF FUTURE METEOROLOGICAL DROUGHT IN JAVA–NUSA TENGGARA REGION BASED ON CMIP6 SCENARIO

Publication Friday, 19 April 2024

Safura, Afifah Huda | Sekaranom, Andung Bayu

Geographia Technica, Open Access, Volume 19, Issue 1, Pages 43 – 60, 1 March 2024

Abstract

Between 2018 and 2022, the primary regions for rice production in Indonesia were Java, Bali, and Nusa Tenggara, collectively contributing to approximately 61% of the annual rice production. Unfortunately, these islands are also most vulnerable to crop failure due to drought-induced water shortages. Therefore, this study predicted the occurrence, duration, and severity of meteorological drought in Java, Bali, and Nusa Tenggara using rainfall data from six climate models within the CMIP6 framework under the SSP245 and SSP585 scenarios. The observed data of 20 BMKG rainfall stations in the study area was acquired to adjust the output of the CMIP6 models using the Linear Scaling (LS) method. The Standardized Precipitation Index (SPI) at a 3-month scale (SPI-3) was used to analyze meteorological drought characteristics, such as frequency, duration, and intensity. The results showed that drought frequency increased and persisted for longer durations, particularly in the Nusa Tenggara region. However, compared to the observation period, drought intensity was predicted to decline in both scenarios compared to the observed period. The SSP585 scenario also indicated a higher level of drought compared to SSP245. © 2024, Asociatia Geographia Technica. All rights reserved. read more

Mangrove area degradation and management strategies in Indonesia: A review

Publication Friday, 19 April 2024

Utami, Westi | Sugiyanto, Catur | Rahardjo, Noorhadi

Journal of Degraded and Mining Lands Management, Open Access, Volume 11, Issue 3, Pages 6037 – 6047, April 2024

Abstract

Coastal communities are particularly vulnerable to the effects of climate change. This study aimed to review the impact of land use change and mangrove degradation on coastal areas and analyze the problems and strategies of mangrove management in Indonesia. Journal data sources were obtained from the Scopus and Google Scholar databases. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) method was used in the study. The results indicate that economic activities such as mining, industry, and ponds are the main cause of mangrove damage, which in turn leads to increased disasters, CO2 emissions, and decreased community income. To address this issue, mangrove management strategies that take into account social, economic, and environmental factors are necessary. Successful mangrove restoration requires increased inclusion, community capacity, budgeting, and stakeholder involvement. Government policies regulating sustainable spatial planning, law enforcement, and institutional frameworks are crucial components of mangrove management. The study’s results are expected to serve as the foundation for developing sustainable coastal management strategies that enhance the safety of coastal communities from disasters and improve their welfare. © 2024 Brawijaya University. All rights reserved. read more

Dynamics of the aeolian landform at the coastal geosite of Parangtritis sand dune area, Yogyakarta

Publication Friday, 19 April 2024

Malawani, Mukhamad Ngainul | Mardiatno, Djati | Mutaqin, Bachtiar Wahyu | Suhendro, Indranova | Setiawan, Nicky | Muharram, Fajrun Wahidil | Rhosadi, Iwan

Journal of Degraded and Mining Lands Management, Open Access, Volume 11, Issue 3, Pages 5839 – 5847, April 2024

Abstract

In 2014, Kelud, an active volcano in East Java, ejected ashes (hereafter termed KA; Kelud ash) that reportedly reached as far as Central Java and the Special Region of Yogyakarta (DIY). The KA deposits are observable in, among others, the coastal sand dune area in Parangtritis. Due to the active aeolian process, the KA layers can be found at different depths five years after the eruption. Thus, the KA can be used as a marker of the post-2014 aeolian activities at the Parangtritis dune, which was once classified as a degraded land and later recognized as a coastal geosite, ultimately allowing us to calculate the volume and sand transport rate. The research surveys performed at 25 points discovered volcanic ash layers at 1 cm to 26 cm below the surface. At some observed points, the ash deposits were found on the surface and continuously transported. This research observed an area of 60,000 m2 with an average of 8.5 cm thick sand layers lying above the KA layer. Based on the calculation, the total volume of the transported sand at the Parangtritis sand dune from 2014 to 2019 was approximately 5,100 m3. This volume is considerably small owing to various obstacles in the transport zones. Based on the five-year dynamic of the sand dune, this study suggested that restoration needs to be conducted immediately particularly in eliminating vegetation barriers to maintain the sediment balance (erosion-transport-sedimentation) of the coastal sand dune area. © 2024 Brawijaya University. All rights reserved. read more

Estimated changes in carbon stock due to changes in land use around Yogyakarta International Airport

Publication Friday, 19 April 2024

Utami, Westi | Sugiyanto, Catur | Rahardjo, Noorhadi

Journal of Degraded and Mining Lands Management, Open Access, Volume 11, Issue 3, Pages 5727 – 5740, April 2024

Abstract

Land use plays an important role in maintaining carbon stock balance, ecosystem sustainability, and the environment. Massive land use changes in forest areas, peatlands, mangroves, and greenways result in an increase in CO2 release. This research aimed to analyze the impact of land use changes on the value of carbon stock study around Yogyakarta International Airport. The data used were Pleiades images in 2014, 2018 and 2022. Image analysis was carried out visually to produce detailed and accurate land use classification. Meanwhile, multitemporal map overlays were carried out to find out land use changes. Changes in carbon stock were obtained from the land use formula multiplied by the value of the Greenhouse Gas Constant (GGC). The results showed that the construction of an airport and its supporting infrastructure triggered land use changes that had implications for the decreasing carbon stock. The decrease in the area of vegetation cover in fields, community plantations, and mixed plantations from 2014 to 2022, amounting to -640.99 ha, increased carbon emissions. The results of the analysis showed that there had been changes in carbon stock. In 2014, the value was 150,286.57 t C/ha; in 2018, it decreased to 136,631.56 t C/ha; and in 2022, it reduced to 133,554.36 t C/ha. Massive economic activity and infrastructure development trigger reduced vegetation cover, resulting in increased carbon and increased carbon being released into the atmosphere. The problem of land conversion that affects changes in carbon stock and impacts on climate change requires mitigation, among which is by proper land use management and sustainable spatial planning. © 2024 Brawijaya University. All rights reserved. read more

Assessing karst landscape degradation based on the void development of karst aquifers in Gunungsewu, Indonesia

Publication Friday, 19 April 2024

Naufal, Muhammad | Adji, Tjahyo Nugroho | Haryono, Eko | Cahyadi, Ahmad

Journal of Degraded and Mining Lands Management, Open Access, Volume 11, Issue 3, Pages 5707 – 57 15, April 2024

Abstract

Compared to other landforms, karst areas are among those emerging from the dissolution process that have a higher risk of land degradation. The likelihood of karst landforms being harmed is increased by urbanization and other human activities like extensive agriculture. Subsurface streams’ water quality gets worse when surface pollutants infiltrate through developed karst features like sinkholes and karst ponors. There is a greater risk of land degradation as more karst features, in this case void size, develop. The purpose of this research is to assess how void development, or the degree of karstification, relates to the potential for karst spring pollution in the event that land degradation occurs on the surface of the Karst Drainage System (KDS). This research was conducted at the KDS of Beton and Gremeng Spring in the Gunungsewu karst area, Indonesia. In addition, this study also provides recommendations related to environmental management on the basis of the level of development of voids at both sites. The degree of karstification represents the phase at which a hydrogeological system has been developing, and this information was later considered in formulating strategies for protecting karst groundwater from contamination. The results show that Beton and Gremeng had a complex discharge regime with degrees of karstification at 8 and 5.5, respectively. Based on flood hydrograph components, it was further confirmed that both areas were in the mature phase. The higher the degree of karstification, the higher the vulnerability to ollution © 2024 Brawijaya University. All rights reserved. read more

Should we build a metaverse for the new capital of Indonesia?

Publication Friday, 19 April 2024

Sunindyo, Wikan Danar | Alfrojems | Septian, Doddi | Rachmawati, Rini | Sensuse, Dana Indra

Heliyon, Volume 10, Issue 7, 15 April 2024, Article number e29037

Abstract

Moving the capital of Indonesia from the Jakarta area to the island of Kalimantan is an inevitable necessity due to economic, political, socio-cultural and environmental factors, which require other areas of the archipelago to be developed. It has been decided that the green city and smart city concepts will be applied in the development of the new capital, using a state-of-the-art approach, including metaverse technology. The methodology employed in this study includes in-depth interviews, focus group discussions, direct field observations, and documentation. The findings of this research consist of an analysis of the readiness of IKN and its surrounding area for the implementation of metaverse technology in IKN. This paper examines whether metaverse technology is needed in the construction of the new capital city. If so, what are the needs for the development of the new capital’s metaverse, and what are the advantages (and disadvantages) of using the metaverse. The results are expected to provide a more comprehensive view of the use of metaverse technology in the new capital. © 2024 The Authors read more

Monitoring vegetation patterns and their drivers to infer resilience: Automated detection of vegetation and megaherbivores from drone imagery using deep learning

Publication Friday, 19 April 2024

James, Rebecca K. | Daniels, Freek | Chauhan, Aneesh | Wicaksono, Pramaditya | Hafizt, Muhammad | Harahap, Setiawan Djody | Christianen, Marjolijn J.A.

Ecological Informatics, Open Access, Volume 81, July 2024, Article number 102580

Abstract

Ecological pattern theory has highlighted spatial vegetation patterns that can be used as indicators of ecosystem resilience. Combining this spatial pattern theory with aerial imagery from drones and automated image processing with deep learning methods, we show how monitoring of natural ecosystems can be enhanced through quantifying vegetation spatial patterns. We demonstrate this approach in a tropical seagrass ecosystem with a high abundance of turtles that generate vegetation patches when grazing. Past field observations suggest that patch size and density reflect the seagrass meadow resilience, but understanding the natural variation in vegetation patchiness is crucial. Employing the deep learning methods of semantic segmentation and object detection, we quantify vegetation patchiness metrics and turtle distribution across 12 ha of seagrass meadow in the years 2012 and 2022. The resulting output facilitates spatial and temporal comparisons, revealing areas of low resilience. In 2012, turtle grazing across the entire site yielded vegetation patch sizes averaging 2 ± 0.2 m2 (95% confidence interval). Reduced patch sizes of 0.24 ± 0.05 m2 and 0.67 ± 0.6 m2 at the reef edge and beach slope respectively, in conjunction with a reduced patch density, indicated lower resilience at the seagrass meadow edges. Analysis of the 2022 dataset indicates a general decrease in patch size over time, suggesting declining resilience. A retraining experiment of the semantic segmentation model was conducted where the initial model was retrained on the 2022 dataset and demonstrated the adaptability of the deep learning methods. Despite using different equipment, the model achieved high accuracy with only 5–10 additional training images. By providing the tools to conduct these analyses, we aim to stimulate the uptake of deep learning for enhancing the data obtained from aerial imagery to improve the monitoring and conservation of natural ecosystems. © 2024 The Authors read more

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Job Summary:

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News Released

  • Large debris avalanche and associated eruptive event at Samalas volcano, Lombok, Indonesia
  • SYNERGIZING LANDSAT-8 AND MODIS DATA FOR ENHANCED PADDY PHENOLOGY ASSESSMENT AND CROP FREQUENCY MAPPING: A FUSION OF PHENOLOGICAL INSIGHTS AND MACHINE LEARNING ALGORITHMS
  • PROJECTIONS OF FUTURE METEOROLOGICAL DROUGHT IN JAVA–NUSA TENGGARA REGION BASED ON CMIP6 SCENARIO
  • Mangrove area degradation and management strategies in Indonesia: A review
  • Dynamics of the aeolian landform at the coastal geosite of Parangtritis sand dune area, Yogyakarta
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