Landform Units Research Articles

The RARCrec: A rapid riparian vegetation assessment method for use in river systems undergoing vegetative and geomorphic recovery

SummaryMonitoring the condition of returning vegetation over time is essential for effectively managing riparian vegetation. Rapid riparian assessment methods are standard tools for capturing a suite of variables relevant to river health and are accessible to a range of users with different levels of experience. Monitoring efforts are particularly important for rivers undergoing degrading impacts and subsequent management interventions. In coastal catchments of New South Wales, Australia, vegetation is returning to rivers that were historically cleared for agriculture and are now experiencing geomorphic recovery. We present a rapid riparian assessment method for rivers undergoing vegetative and geomorphic recovery in this region. It addresses a gap in available rapid assessments by providing a methodology that can be used at sites with no historical analogue. Our assessment method adapts and extends a widely used method called the Rapid Assessment of Riparian Condition (RARC) to capture the quality of returning riparian vegetation along recovering rivers (rec), including native species diversity and vegetation structure (hence the name RARCrec). The RARCrec incorporates four sub‐indices – vegetation cover, native species richness, proportion of native to exotic species, and features of vegetation health – to produce an overall vegetation condition score that classifies sites as poor, moderate, or good condition. Scores for each sub‐index are assessed for the vegetation strata (groundcover, graminoids, midstorey, vines, and canopy) on the landform units of river bars, benches, and floodplains. The RARCrec has been designed to be sufficiently general for use in the main Vegetation Formations in coastal New South Wales and has been trialled at 36 sites across this region. Assessments can be conducted within half a day by two technically competent users and can be used to monitor vegetation condition over time to inform where to prioritise implementation of management activities. Field methodology and data sheets, including a scoring system, are provided to support the implementation of the RARCrec.

Range of Terrain Suitability for the Development of the Aladi Tulabolo Road Network Gorontalo Province

This research aims to identify, analyze and develop a road route development model based on terrain suitability to establish a new road network connecting Aladi with Tulabolo, Bone Bolango Regency in Gorontalo Province. A GIS-based spatial approach is used to describe and measure terrain suitability. Based on the characteristics of the research object, survey methods are used; based on population characteristics, stratified proportional sampling is used as the mapping unit; and based on its relationship to analysis, scoring-based quantitative and qualitative methods are used. The research results show that (1) the characteristics of the distribution of terrain suitability for the development of the road network in the research area are based on the parameters that make up terrain units such as landform units, slope, rock type and soil type, resulting in zoning with 5 (five) levels of suitability. The five levels of suitability are S1 suitability (high suitability), S2 suitability (medium suitability), N1 suitability (temporarily not suitable), and N2 suitability (permanently not eligible). (2) The distribution of terrain suitability classes for developing the dominant road network for the Aladi-Tulabolo area is in suitability class S2 (medium suitability), covering an area of 99.25 km2 . (3) The road route development model based on the suitability of the terrain in the research area is formed with the formulation Terrain Unit (SM) = f (bl, kl, jb, jt), where bl = landform, kl = slope, jb = rock type, and jt = soil type

Reduction Of The Potential Of Landslides With Vegetative Methods In The Sub-DAS Of Kali Arus, Banyumas Regency

Abstract Landslides are one of the natural disasters that often occur. The magnitude of the potential for landslides is caused by several factors including geomorphological conditions, geology, soil, land use, and rainfall. The goal of this research is to investigate the technique of reducing the potential for landslides in the research area using the vegetative method with a geomorphological approach. The research method uses a survey method, which includes fieldwork and laboratory work. Data processing uses scoring or weighting techniques. Data analysis for landslide potential reduction techniques utilizing qualitative descriptive. Reducing the potential for landslide natural disasters vegetatively, namely by selecting the type of vegetation that is following the characteristics and quality of the landform. Plants can be used to control landslides as a result of the research. Mahoni, Jati, and Sengon are plants that can be used to control landslides in the suitable and marginally suitable land suitability classes, reducing the potential for landslides through the analysis of land characteristics and land quality in each landform unit. The results of the land characteristics and land quality analysis are used to map land suitability classes for a variety of annual crops.

Geomorphology mapping and landslide susceptibility for disaster risk reduction and sustainability environment in the Sub DAS Maspo, Mt. Welirang, East Java, Indonesia

Landslides are still problematic for areas with rough surface shapes and high rainfall. Landslides are still causing human life losses, so mitigation efforts for disaster risk reduction must be prioritized. The purpose of this study is geomorphological mapping and landslide hazard mapping as a basis for disaster risk reduction efforts. The method used integrates remote sensing data using geographic information systems. Geomorphology mapping is processed and analyzed using four geomorphological approaches, while for landslide susceptibility maps are analyzed using the Weight of Evidence (WoE) method using existing landslide variables and 17 landslide control factors. The geomorphological mapping results show that in the Maspo sub-watershed, there are 25 landform units based on geomorphological mapping. There are five classes of landslide vulnerability indices, i.e very low index (0.001-0.341) namely 9.38%; low index (0.341-0.471) that is 26.18%; moderate index (0.471-0.584) that is 28.49%; high index (0.584-0.741) that is 23.94% and very high index (0.714-1) that is 12.02%. The accuracy of the landslide hazard map results is 88%, indicating that the landslide hazard map has good accuracy. Dominant landslides of 26.98% and 23.59% occurred in the HS2V1/ME landform, which is the middle slope of the steep hills of the lava eruption of the 2nd Mt. Welirang with moderate geomorphic processes and HS2V1/VSE which is the middle slope of the steep hills of the 2nd eruption of Welirang volcano with the process strong geomorphism. The results of geomorphology mapping and landslide susceptibility can be used as an information base for disaster risk reduction strategies and sustainable environmental management.

Automated mapping of regolith units with support vector machine and artificial neural network using data from Landsat-8 OLI, ALOS PALSAR DEM, and Sentinel-1A radar images: the case of the Sissingué Gold Project, Northern Côte d’Ivoire

ABSTRACT The Sissingué Gold Project is in Northern Côte d’Ivoire and part of the southern extension, a large peneplain of the landscape in South Mali. The area has experienced extensive weathering and erosion over a long time, resulting in a widespread and complex regolith cover. This diverse and vast regolith cover poses considerable difficulties for exploration. To overcome this problem, we adopted mapping of regolith units using machine learning (ML) with support vector machine (SVM) and artificial neural network (ANN) algorithms. The main objectives were to (1) make the predictive regolith map of the study region using these algorithms with data obtained from Landsat-8 operational land imager, Advanced Land Observing Satellite Phased Array Type L-Band Synthetic Aperture Radar digital elevation model and Sentinel-1A; (2) show the method of pre-processing and processing the required data and (3) develop the regolith landform unit (RLU) map from the predictive regolith map and collected data based on the Relict – Erosional – Depositional model. Tests using the SVM and ANN algorithms showed that both ML tools could accurately map regolith landforms. An innovative method of optimizing data using parameters is presented. The results showed that ANN outperformed SVM with an overall accuracy of 87.01% and a kappa coefficient of 0.84, whereas the corresponding values for SVM were 86.69% and 0.84, respectively. However, the validation data obtained from SVM-based prediction exhibited a better score than that of validation data obtained from ANN-based prediction. The Sentinel-1A radar band combined with Landsat-8 data reduced the vegetation-masking effect and improved the classification results. The RLUs of this area are composed primarily of relicts at 24.91%, including lateritic residuum and soil, depositional material at 36.39% with exotic sediments and ferrierite and the remaining 38.7% of erosional material made of saprolite, colluvial fragments, and mottled zones on flanks.

Progress and prospects for research on Martian topographic features and typical landform identification

The study of Martian surface topography is important for understanding the geological evolution of Mars and revealing the spatial differentiation of the Martian landscape. Identifying typical landform units is a fundamental task when studying the origin and evolution of Mars and provides important information for landing on and exploring Mars, as well as estimating the age of the Martian surface and inferring the evolution of the Earth’s environment. In this paper, we first investigate Mars exploration, data acquisition and mapping, and the classification methods of Martian landforms. Then, the identification of several typical Martian landform types, such as aeolian landforms, fluvial landforms, and impact landforms, is shown in detail. Finally, the prospects of Mars data acquisition, landform mapping, and the construction and identification of the Martian landform classification system are presented. The construction of the Martian landform classification system and the identification of typical Martian landforms using deep learning are important development directions in planetary science.

Karst landform classification considering surface flow characteristics derived from digital elevation models

AbstractKarst landforms are one of the most typical geographical units with a specific physical process on the earth's surface. The classification of karst landforms is an important aspect for understanding their landform processes and mechanisms. However, influenced by various interior and external forces, karst landforms have an extremely complex surface morphology, increasing the difficulty of their automatic classification. In this study, we considered hydrological features as an important factor in characterizing karst landforms and proposed a method that considers surface flow for karst landform classification. In this method, terrain was reversed for hydrological analysis to achieve the landform units. Then, the watershed boundary of the reversed terrain is extracted by hydrological analysis. The boundary of the karst landform unit is determined by erasing the plain area from the watershed boundary. Thereafter, the graph theory segmentation method is employed to merge the landform units belonging to the same karst landform entity. The proposed approach is validated and applied in two sample karst areas, Fenglin and Fengcong, located in Guilin, China, using digital elevation model data with 30 m spatial resolution. In addition, a comparative analysis is conducted to evaluate the accuracy of the proposed method. The results demonstrated that the typical karst landform units of Fenglin and Fengcong can be effectively classified. The overall classification accuracy is 94.44%. The proposed method produced more reasonable and accurate boundaries compared with the contour tree and terrain feature point methods. Furthermore, the classification results indicate various landform development stages of the karst landform process in the study area. The proposed method considering surface flow characteristics can be further extended to other landform types with highly complex landforms.

Analysis of the level of groundwater environmental damage due to community activities in the Parangtritis coastal area, DIY Province

This study aimed to analyze the level of damage to the groundwater environment in terms of groundwater quality in the coastal area of Parangtritis and its surroundings. This research study unit is based on the landform unit and activities of the community. The research location is located in Parangtritis Village, Yogyakarta Special Region (DIY) Province. This study used a descriptive quantitative analysis as its method of analysis. This study used primary data obtained by testing groundwater samples in the laboratory. The groundwater sampling technique is carried out using the purposive sampling area. Groundwater sampling was carried out on eleven land units. The determination of the level of environmental damage to groundwater is carried out using the Pollution Index (IP) method referring to the Regulation of the Minister of Environment Number 115 of 2003. The results showed that the environmental damage to groundwater shows the quality status of lightly polluted water with pollutant index values ranging from 1.244-4.176 with variable pollutants chemical oxygen demand (COD), dissolved oxygen (DO), ammonia, nitrate, phosphate, and total coliform as well as with sources of pollutants from settlements, livestock, and agricultural activities.

Hydrochemical Characteristics and Human Health Risk Assessment of Surface Water in the Danjiang River Source Basin of the Middle Route of China’s South-to-North Water Transfer Project

The Danjiang River basin is an important water source for the Middle Route of the South-to-North Water Diversion Project. With the shortage of water resources and the increase in pollution pressure, it is of great significance to study the hydrochemical characteristics of surface water in the Danjiang River basin and the risk to human health posed by polluted water bodies for the protection and utilization of water resources. In this paper, 40 surface water samples were collected and analyzed by innovatively adopting the sampling principle of “geological structure unit + landform unit + small watershed unit”. Comprehensive mathematical statistical analysis, Piper trilinear diagrams, Gibbs diagrams, and ion ratio coefficients were used to analyze the hydrochemical composition, spatial distribution characteristics and influencing factors of surface water in the Danjiang River. The entropy weight comprehensive index method (EWQI) and the health risk assessment model recommended by the United States Environmental Protection Agency (HHRA model) were used to evaluate the water quality and potential non-carcinogenic risk of surface water in the Danjiang River source basin. The results showed that the pH of surface water in the study area was 7.02~8.77, with an average value of 8.26; and the TDS was ranged from 134 to 388 mg/L, with an average value of 252.75 mg/L. The main cations in the surface water were Ca2+ and Mg2+, accounting for 71% and 20% of the total cations, respectively, while the main anions were HCO3− and SO42−, accounting for 74% and 19% of the total anions, respectively. The hydrochemical type was HCO3− Ca·Mg. The hydrochemical genesis was mainly controlled by the weathering of carbonate rocks, while some ions were influenced by the weathering of silicate rocks, and human activities were also an important factor affecting the chemical characteristics of the water. The EWQI of surface water in the whole region was 8.95~25.69, and the health risk index (HI) of nitrate pollution ranged from 0.0122 to 0.2118, in which the HI ranges for children and adults were 0.0217~0.2118 and 0.0122~0.1333, respectively, indicating that the water quality of the entire study area met the Class I water standards, and the potential non-carcinogenic risk of nitrate was low. However, its impact on children was significantly higher than on adults, so it is recommended to monitor the water quality downstream of urban areas in the study area to reduce agricultural non-point source pollution and urban domestic sewage discharge and thereby reduce the potential health risks for young populations.

Geomorphological mapping and landform characterization of Semeru volcano after the eruption in 2021

The eruption of the Semeru volcano in 2021 has diverse impacts on the landscape and surroundings. It is essential to detect recent landscape features to promptly evacuate personnel and property near the volcano and take emergency treatment measures in case of sudden danger. This study presents a detailed geomorphological map on a 1:50.000 scale for the Semeru volcano after the eruption in 2021. The analysis of the hybrid approach and the on-screen image interpretation (OSII) method on DEM data, optical satellites, and lithology units was carried out to obtain morphological, morphochronological, and morphoarrangement information. While, morphoprocess information was obtained through field observations. We used DAS Rejali for our study area. The results of identifying geomorphological conditions divide the Rejali watershed area into 32 landforms consisting of landform units from volcanic, structural, fluvial, and marine processes. Twenty-three land units in the research location are landforms from volcanic processes. This condition causes morphological conditions, material availability, and processes that dominantly reflect the characteristics of an active volcano. In addition, the landform units from the fluvial process in the Rejali watershed area were identified as many as six units in the form of floodplains of lahar flows along the main river. Landforms with structural genesis were placed in Mandalika formation and diorite rock breakthrough. The structural formation in the Rejali watershed has retention and rock structures that are not easily eroded by water. It becomes a bottleneck formation as a barrier between the upstream and middle areas

Evolution of a coastal transgressive dunefield to a parabolic dunefield, Canunda dunes, South Australia

Various studies have detailed the evolution of barchan dunes to parabolic dunes and a very few studies describe the evolution of coastal transgressive dunefields and continental sand seas to parabolic dunefields. This study examines the evolution and transformation of a 12 km long portion of a formerly large (~50 km along-coast), active, transgressive dunefield (coastal sand sea or erg) dominated by transverse dunes to a coastal barrier dominated by parabolic dunes. A GIS study of vegetation cover change from 1950 to 2017 was conducted, and a stereographic analyses of 1945 to 2020 aerial photography was carried out to determine morphological changes across the dune system. Historical rainfall, aeolian drift potentials, and rabbit numbers are examined as possible drivers of change, and rabbit numbers most strongly correlate with vegetation change. The vegetation cover of the greater dunefield increased in the study area from 26 % cover in 1950 to 54 % by 2020. A largely unvegetated transgressive dunefield dominated by transverse dunes evolved into a parabolic dunefield in <70 years. Vegetation colonisation primarily took place from landward slipfaces, by nebkha formation on dune lobe crests, from interdune swales and flats, and within deflation basins and plains. Vegetation colonisation also occurred above the backshore in the same period. Aeolian landform units such as marginal ridges, nebkha fields, deflation basins and plains, dune ridges, remnant knobs, parabolic dunes, and a foredune-blowout complex were formed as the dune field was colonised and stabilised by vegetation growth. The study provides far greater detail on how vegetational and morphological changes take place as a transgressive dunefield evolves into a parabolic dunefield.

Detecting Influencing Factor of Vegetation NPP in Southwest China Based on Spatial Scale Effect

Vegetation net primary productivity (NPP) is an important parameter for evaluating the quality of terrestrial ecosystems. It is of great importance to study the spatio-temporal evolution of vegetation NPP and its driving force for regional ecological environment protection and sustainable development. On the basis of MODIS NPP data, meteorological data, DEM data, population density data, GDP data, and land use type data, this study used linear regression analysis, R/S analysis, and a Geodetector model to analyze the spatio-temporal variation in vegetation NPP and its future changing trend on both regional and landform scales and to detect the influencing factors that affect the spatial differentiation of vegetation NPP. The results showed that the vegetation NPP exhibited an extremely significant upward trend in southwest China from 2000 to 2020. On the landform scale, the vegetation NPP had showed an upward trend in all landforms, except for the southern Tibet Plateau; among them, the vegetation NPP in the Sichuan Basin showed the most obvious upward trend. The variation in vegetation NPP exhibited obvious spatial heterogeneity in southwest China, with the changing rate of "high in the east and low in the west." The areas with an upward trend of vegetation NPP were greater than the areas with a downward trend, but the changing trend was dominated by a decreasing trend in the future, both in southwest China and each landform unit. The Geodetector results showed that elevation was the dominant factor controlling the spatial differentiation of vegetation NPP in southwest China and all landform units, except for the Yunan-Guizhou Plateau, in which the spatial differentiation of vegetation NPP was mostly dominated by temperature. The interaction detection results showed that the interaction between the influencing factors was manifested as two-factor enhancement or nonlinear enhancement. The interaction between elevation and temperature showed the highest impact on vegetation NPP distribution. On the landform scale, the spatial differential of vegetation NPP was dominated by the interaction between elevation and climate factors or elevation and GDP in the Guangxi Hills, Sichuan Basin, Zoige Plateau, Hengduan Mountains, and southern Tibet Plateau and between climate factors in the Yunan-Guizhou Plateau. The above results indicated that vegetation NPP variation and the influencing factors that dominate its spatial differential in southwest China showed obvious scale effects. Therefore, exploring the dynamic variation in vegetation NPP and its influencing factors at different spatial scales has practical significance for a comprehensive understanding of the vegetation cover situation and formulating regional ecological restoration plans in southwest China.

Geoenvironment factors guided coastal urban growth prospect (UGP) delineation using heuristic and machine learning models

Unplanned urban growth along the coastal cities may disturb the balance between the ecosystem and urbanisation; thus, a development strategy guided by geoenvironmental factors is necessary. We have attempted to delineate suitable Urban Growth Prospect (UGP) zones within the coastal region of the Vishakhapatnam district of India, based on geoenvironmental factors. We conduct an initial assessment of the temporal urban growth pattern in last 15 years using Landsat data and published landuse maps, demonstrating that the urban growth has percolated to unstable geomorphic units, making it vulnerable to flooding. Geoenvironmental factors (geomorphology, lithology, structure, land use, soil, slope and groundwater) based multi-thematic data integration approach is adopted to delineate UGP zones using heuristic and machine learning techniques like Analytical Hierarchy Process (AHP), Artificial Neural Network (ANN), Random Forest (RF), Logistic Regression (LR). We used present-day field observations to train the predictive models like ANN, LR & RF and test the outcomes with accuracy assessment ratios (detection percentage, miss factor etc.). The ANN-derived result presents the best accuracy with a detection percentage of 85% and predicts a 55% spatial scope of urban expansion, which was further refined using the mask of the strategic and ecologically sensitive location with appropriate buffers. The final map represents the UGP zones within the city and surroundings, encompassing stable landform units. The study provides insight into the usefulness of the heuristic and machine learning models in predictive analysis, using geoenvironmental factors for urban expansion in fast-growing coastal cities.

Geomorphological Mapping for Land Suitability Evaluation

Geomorphology affects the potential of land. The geomorphological condition of an area has implications for physical characteristics, including: 1) type; 2) material; and 3) processes formed upon it. Understanding land capability allows for the evaluation of land suitability. Classification of land suitability is carried out by combining the results of land capability identification with requirements for plant growth or existing land use. Evaluation of land suitability can be done using the survey method. This study aimed to assess the suitability of land in Sumbersuko Village in Wagir District, Malang Regency. Land suitability was evaluated by matching the characteristics of the land with the land suitability class. This study used primary data taken from the regional morphology survey. Secondary data included: 1) digital elevation model data; 2) geological maps; 3) maps of soil types; and 4) Sentinel-2A images. The data from the field survey were then compiled using a geographic information system into maps using 2D and 3D modeling. The results of GIS analysis showed that Sumbersuko Village has six landform units, namely M1V1, M1V2, H2V2, U2V2, P2V2, and M3V3. Analysis of land capability and suitability of the six land units in a row gave the following results: 1) forest (highly suitable/S1); 2) forest and industry (suitable/S2); 3) plantation/agrotourism (moderately suitable /S3); 4) agriculture (not suitable/N); 5) residential area (less suitable/S3) S4); and 6) forest (highly suitable/S1).&#x0D; Keywords: scientific, approach, methodological, techniques, geography

Geology and the effect of compaction on base material disposal for the stability of coal disposal slopes in South Kalimantan, Indonesia

A mining activity generally removes overburden to extract minerals. Therefore, a certain area is needed to place the overburden material. One of the parameters that can affect the stability of the disposal is the base or the foundation of the disposal area which will later be stockpiled. This study is observe influence of base disposal to the stability of slope. Based on the lithological characteristics and observations of the outcrop, the writer arranges the stratigraphy of the study area in order to determine the stratigraphic arrangement and the distribution of the rock units laterally. In general, the study area is dominated by quartz sandstone, claystone, conglomerate and loose material from older rocks. The stratigraphic sequence of the study area from old to young includes Warukin Sandstone Unit (Tmw), Dahor Layang Member Conglomerate (TQdt) and Dahor Sandstone Unit (TQd). In general, the research area is included in the structural landform unit with geomorphological control that influences the tectonic process (endogenous). Based on the results of the study, there was a significant increase related to the stability of the coal disposal slope with compaction efforts carried out on the base material.

Geomorfologi Tanah Pada Transisi Geologi Formasi Wonosari dan Nglanggran di Kecamatan Purwosari Gunungkidul Yogyakarta

The transition zone of the Wonosari and Nglanggran Formation in Purwosari District has the characteristics of thick soil, steep slopes, and no outcrops. The different characteristics found in the Wonosari Formation Zone are characterized by polygonal karst formations with thin soil and limestone rocks, and the Nglanggran Formation in the form of thick soil, andesite rock outcrops, and steep slopes. Geomorphological mapping of the Nglanggran and Wonosari Formation can be done easily through morphological approaches and outcrops. Geomorphological mapping is quite difficult to do in the transition of the Wonosari and Nglanggran Formation because it does not have outcrops and is difficult to interpret from morphology. Soil geomorphological approach needs to be done to define landform units for areas that do not have outcrops dan difficult to interpret through morphology. The purpose of this study was to map the geomorphological distribution of soil characteristics in the geological transition zone. The methods used to identify landform units are morphological delineation and soil survey. The morphological delineation for landform units was obtained from aerial photographs. The results of the delineation of landforms from aerial photographs are detailed by soil surveys. The results of the delineation of landforms using aerial photography produce high resolution, smooth, and firm compared to other sources. The results of the delineation of landforms from aerial photos obtained two units of landforms, limestone karst hills, Wonosari formation and andesitic rocky hills, Nglanggran formation. There is a transitional transition zone in the TP7 soil sample with the color change from dark brown (karst) to light brown (old volcanic). The thickness of the soil in the old volcanic is more than 1 meter and deeper than the karst soil (&lt; 60 cm). The transition zone has three soil horizons A, B, and B/C which are classified as more developed than the karst region (A and B horizons). The soil texture in old volcanic is clay and silt, while the dominant karst area is clay.

Spatial Distribution Pattern and Natural Causes Analysis of Sandy Desertification Land in Ali Area

In order to explore the spatial distribution pattern and natural causes of the sandy desertification land in the Ali area, on the basis of clarifying the dynamic change laws of sandy desertification land areas, sandy desertification degree and spatial distribution pattern, the main controlling factors of sandy desertification land distribution are analyzed from three aspects of landform, climate and vegetation. During the 22 years from 1992 to 2014, the sandy desertification land area in the Ali area shows a law of first increase and then decrease, reaching a peak of 61,054.14 km2 in 2004, accounting for 20.57%, and decreasing to 60,892.65 km2 in 2014, accounting for 20.51%, which do not return to the level of 1992. Sandy land desertification is mainly slight and moderate, accounting for 53.29% and 45.73%, respectively, in 2014. Sandy desertification land in the Ali area is mainly distributed among intermountain basins, river valleys, lake basins, piedmont plains and other landform units. The landform and wind speed are the main natural factors that determine the spatial distribution pattern of sandy desertification land in the Ali area, that is, the spatial distribution pattern of sandy desertification land in the Ali area is the coupled result of sand source and wind speed.

Karakteristik Geomorfologi Daerah Posso Kabupaten Gorontalo Utara dan Sekitarnya

The landforms in the Gorontalo area are only limited to the physiographic division of Gorontalo. Therefore, this research aims to analyze the geomorphological characteristics of the research area to obtain detailed data that can be used as basic data for the theoretical purposes of Gorontalo geomorphology and disaster applications. The method used in this research is field observation and visual interpretation using satellite imagery, namely GeoEye (GoogleEarth) and Digital Elevation Model. Data analysis was carried out in the form of an analysis of the geomorphological condition of the research area supported by the results of image interpretation—determination of geomorphological units using the Van Zuidam classification. The results showed that the geomorphology of the study area consisted of six geomorphological units: structural hills, volcanic hills, denudational hills, denudational plains, fluvial plains, and marine plains. The morphography and morphometry of the research area are hilly, lowland, and coastal plains generally located at an altitude of 0-393 masl with slopes ranging from flat to extremely steep with a sloping pattern. The morphology of the landform units in the study area starts from the Early Miocene to the Holocene in the form of magmatism, volcanism, and exogenous processes. The presence of geological structures in the form of fractures and faults in geomorphological units and the influence of exogenous processes on landforms can be a reference in mapping the direction of mitigation in the research area, theoretically and practically.

Characteristics and Spatial Distribution of Vs30 Based on Microtremor Inversion and MASW Data through Landform Unit in Yogyakarta, Indonesia

The Yogyakarta region is located in the earthquake-prone areas of Indonesia. An earthquake hazard can be assessed by identifying the site conditions from Vs30 to estimate the potential amplification of ground shaking. Site conditions are affected by the earth surface relief and material composition. The landform is characterized by differences in geomorphological structures and processes, relief/topography, and material. This research aims to analyze the characteristics and spatial distribution of Vs30 based on MASW and microtremor inversion for each landform unit in the Yogyakarta region. We collected 545 microtremor and MASW responses from field measurements. Data inversion was performed to obtain a 1D Vs30 model and estimate the Vs30 value. The results are presented in the Vs30 spatial distribution map and site classification. They show that the value of Vs30 is varied in a range of 140 – 1092 m/s. The site classification ranges from SE to SB. The Vs30 value tends to be similar to the USGS model, except in the karst landform in the Gunungkidul area. Here, the site class ranges from SC to SB, while the USGS model ranges from SD to SC. Based on the landform analysis, the higher average values of Vs30 are for karst, followed by structural, denudational, volcanic, fluvial, marine, and aeolian landforms. This difference indicates that local conditions significantly affect the Vs30. The higher the elevation and the steeper the slope, the larger the Vs30 value. Moreover, the higher values of Vs30 are determined by harder and solid/consolidated material.

INDMF Based Regularity Calculation Method and Its Application in the Recognition of Typical Loess Landforms

The topographical morphology of the loess landform on the Loess Plateau exhibits remarkable textural features at different spatial scales. However, existing topographic texture analysis studies on the Loess Plateau are usually dominated by statistical characteristics and are missing structural characteristics. At the same time, there is a lack of regularity calculation methods for DEM digital terrain analysis. Taking the Loess Plateau as the study area, a regularity calculation method based on the improved normalized distance matching function (INDMF) is proposed and applied to the classification of a loess landform. The regularity calculation method used in this study (INDMF regularity) mainly includes two key steps. Step 1 calculates the INDMF sequence value and the peak and valley values for the terrain data. Step 2 calculates the significant peak and valley, constructs the significant peak and valley sequences, and then obtains the regularity using the normalised ratio value. The experimental results show that the proposed method has good anti-interference ability and can effectively extract the regularity of the main landform unit. Compared with previous methods, adding structural features (i.e., INDMF regularity) can effectively distinguish loess hill and loess ridge in the hilly and gully region. For the loess hill and loess ridge, the recognition rates of the proposed method are 84.62% and 92.86%, respectively. Combined with the existing topographic characteristics, the proposed INDMF regularity is a topographic structure feature extraction method that can effectively discriminate between loess hill and loess ridge areas on the Loess Plateau.