Land Processes Research Articles

Formulation of Rice Accounting Cycle in Indonesia

Objective: This research aims to formulate the accounting cycle for rice in Indonesia, facilitating the resolution of complex issues in rice management and finance from upstream to downstream. Stakeholders, especially the Indonesian government, can utilize appropriate policies to enhance rice management and accounting practices. Theoretical Framework: Addressing the rice issue in Indonesia requires systematic policy interventions to serve as solutions for farmers' challenges. This study will delve into the complexity of these issues using the concept of (Purnamasari et al., 2023), encompassing land area, seed costs, and labor costs as determinants of technical efficiency. It expands on (Purnamasari et al., 2023), analyzing it from an accounting perspective. Method: Employing a phenomenological approach, the researcher conducts observations and direct interviews with a selection of farmers, utilizing ethnographic methods to map out the rice management system in Indonesia. Results and Discussion: The researcher successfully formulates the accounting cycle for rice, offering a comprehensive solution for rice management in Indonesia. The rice accounting cycle comprises seedling, land processing, planting and maintenance, and harvesting and distribution phases. Research Implications: The government plays a pivotal role in implementing the Management Control System (MCS) for the rice accounting cycle to improve farmers' welfare and ensure rice self-sufficiency from production to distribution. Originality/Value: This research is the first to comprehensively examine rice management and accounting practices in Indonesia. Previous studies have been partial in their approach, thus failing to provide effective solutions for rice management and accounting in the country.

Modern Agriculture Development Case in Gobleg Village Banjar Subdistrict Buleleng Regency, Bali Province

The challenges of Indonesia's agricultural development today are climate change and potential droughts. This research aims to analyze the modern agricultural development of the Gobleg Village Case of Banjar district of Buleleng. This research uses a qualitative method with a case study approach. Determination of informants using snowball sampling and data collection methods is done with in-depth interviews, observations, and documentation. Data analysis using interactive model analysis of Miles, Huberman and Saldana (2014). The results of the research show the selection of commodities based on potential income, level of market demand, knowledge, land characteristics and socio-cultural characteristics. The agricultural production process ranges from land processing to post-harvest harvesting. Farmers have already implemented eco-friendly farming by implementing IoT-based fertigation. Institutional support consists of marketing, financing, technical guidance and social capital. The marketing of products is facilitated by the Gobleg PMK cooperation in cooperation with Bali Organic Subak, the marketing is done online with the Fresh Boss application. The cooperation provides facilitation of means of production with the payment system after harvest. In terms of social capital, farmers still exist doing gotong royong in land processing. Farmers are already able to leverage technology like smartphones that are integrated with IoT-based fertigation.

Modern Agriculture Development Case in Gobleg Village Banjar Subdistrict Buleleng Regency, Bali Province

The challenges of Indonesia's agricultural development today are climate change and potential droughts. This research aims to analyze the modern agricultural development of the Gobleg Village Case of Banjar district of Buleleng. This research uses a qualitative method with a case study approach. Determination of informants using snowball sampling and data collection methods is done with in-depth interviews, observations, and documentation. Data analysis using interactive model analysis of Miles, Huberman and Saldana (2014). The results of the research show the selection of commodities based on potential income, level of market demand, knowledge, land characteristics and socio-cultural characteristics. The agricultural production process ranges from land processing to post-harvest harvesting. Farmers have already implemented eco-friendly farming by implementing IoT-based fertigation. Institutional support consists of marketing, financing, technical guidance and social capital. The marketing of products is facilitated by the Gobleg PMK cooperation in cooperation with Bali Organic Subak, the marketing is done online with the Fresh Boss application. The cooperation provides facilitation of means of production with the payment system after harvest. In terms of social capital, farmers still exist doing gotong royong in land processing. Farmers are already able to leverage technology like smartphones that are integrated with IoT-based fertigation.

KELAYAKAN FINANSIAL AGROFORESTRI DAN KEBUTUHAN HIDUP LAYAK PETANI DI DESA LAMBUSANGO KECAMATAN KAPONTORI KABUPATEN BUTON

The increase in population and basic needs has led to an increase in the need for larger agricultural areas and to be cultivated more intensively. Based on this, optimal land processing activities are needed for maximum results to address increasing needs, by implementing an agroforestry system. Agroforestry provides increased harvest intensity which in the end is able to provide additional output, even though the area of ​​cultivated land is very limited. The aim of this research is to determine the financial feasibility of agroforestry and the needs for a decent living in Lambusango Village, Kapontori District, Buton Regency. The population in this study were people who had an agroforestry planting pattern in Lambusango Village, consisting of 25 heads of families (HoF). Thus, the sample size in this study was determined using the census method. The data analysis used is analysis of financial feasibility and decent living needs (DLN). The results of this research indicate that agroforestry activities in Lambusango Village are financially feasible, with the agroforestry pattern that provides the greatest benefits, namely the Agrosilvopostura II pattern with an NPV value of Rp. 121,310,123,- BCR value of 2.74 and IRR value of 9%. Business of agroforestry systems in Lambusango Village with net income of IDR. 10,576,369/year has not been met based on Decent Living Needs (KHL) of IDR 24,000,000/year. Keywords: Agroforestry, Decent Living Feasibility, Financial Feasibility, Lambusango Village

Numerical simulation of plume–surface interaction and lunar dust dispersion during lunar landing using four engines

As the lander approaches the lunar surface, the engine plumes impinge on the lunar regolith and entrain lunar dust from the surface. This plume–surface interaction and the resulting dispersion of lunar dust form a multi-physics, multi-scale problem, which becomes even more complex under multi-engine conditions. This study employed the direct simulation Monte Carlo method to simulate the plume–surface interaction flow field of a four-engine lunar lander at various landing altitudes and lunar surface angles. Flow characteristics were analyzed, and the impact of the plume and backflow on the lander was assessed. Subsequently, lunar dust simulation was conducted using the plume field as a basis. The study determined the spatial distribution of particles with different diameters at various landing altitudes and surface angles, as well as their impact velocities on the lander. Furthermore, taking into account the variations in the lander's altitude and attitude, a dynamic simulation of lunar dust during the landing process was conducted. This process resulted in the dynamic distribution of lunar dust during landing, laying the groundwork for real-time simulation of lunar dust distribution and reliable visualization during landing simulations. These findings are valuable for assessing and mitigating the hazards posed by lunar dust.

Quantifying Compound and Nonlinear Effects of Hurricane‐Induced Flooding Using a Dynamically Coupled Hydrological‐Ocean Model

AbstractWe recently developed a dynamically coupled hydrological‐ocean modeling system that provides seamless coverage across the land‐ocean continuum during hurricane‐induced compound flooding. This study introduced a local inertial equation and a diagonal flow algorithm to the overland routing of the coupled system’s hydrology model (WRF‐Hydro). Using Hurricane Florence (2018) as a test case, the performance of the coupled model was significantly improved, evidenced by its enhanced capability of capturing backwater and increased water level simulation accuracy and stability. With four model experiments, we present a framework to detangle, define, and quantify compound and nonlinear effects. The results revealed that the flood peaks in the lower Cape Fear River Basin and the coastal waters were contributed by inland flooding and storm surge, respectively. These two processes had comparable contributions to the flooding in the Cape Fear River Estuary. The compound effect was identified when the flood levels resulting from the combination of land and ocean processes surpassed those caused by an individual process alone. The compound effect during Hurricane Florence exhibited limited impact on flood peaks, primarily due to the time lag between the peaks of the storm surge and the inland flooding. In the period between the two peaks, the compound effect was salient and significantly impacted the magnitude and variation of the flood level. The nonlinear effect, defined as the difference between the compound flood level and the superposition of storm surge and inland flooding water levels, reduced flood levels in the river channels while increasing flood levels on the floodplain.

Ground Coverage Classification in UAV Image Using a Convolutional Neural Network Feature Map

Background: To understand land transformation at the local level, there is a need to develop new strategies appropriate for land management policies and practices. In various geographical research, ground coverage plays an important role particularly in planning, physical geography explorations, environmental analysis, and sustainable planning. Objective: The research aimed to analyze land cover using vegetation density data collected through remote sensing. Specifically, the data assisted in land processing and land cover classification based on vegetation density. Methods: Before classification, image was preprocessed using Convolutional Neural Network (CNN) architecture's ResNet 50 and DenseNet 121 feature extraction methods. Furthermore, several algorithm were used, namely Decision Tree, Naí¯ve Bayes, K-Nearest Neighbor, Random Forest, Support Vector Machine (SVM), and eXtreme Gradient Boosting (XGBoost). Results: Classification comparison between methods showed that using CNN method obtained better results than machine learning. By using CNN architecture for feature extraction, SVM method, which adopted ResNet-50 for feature extraction, achieved an impressive accuracy of 85%. Similarly using SVM method with DenseNet121 feature extraction led to a performance of 81%. Conclusion: Based on results comparing CNN and machine learning, ResNet 50 architecture performed the best, achieving a result of 92%. Meanwhile, SVM performed better than other machine learning method, achieving an 84% accuracy rate with ResNet-50 feature extraction. XGBoost came next, with an 82% accuracy rate using the same ResNet-50 feature extraction. Finally, SVM and XGBoost produced the best results for feature extraction using DenseNet-121, with an accuracy rate of 81%. Keywords: Classification, CNN Architecture, Feature Extraction, Ground Coverage, Vegetation Density.

Assessment of Agricultural Drought Using Vegetation Condition Index and Vegetation Health Index in Niger River Basin, Nigeria

Soil moisture indicates the dryness of the ground surface. This phenomenon is directly tied to vegetation quality and Land Surface Temperature in a specific place. As a result, these characteristics indirectly describe the dryness of the ground surface. This study assessed agricultural drought in Niger River in Nigeria. Data used include MODIS driven MOD13Q1 (NDVI), and MOD11A2 (LST) datasets obtained from Land Processes Distributed Active Archive Center. These datasets were used to compute Vegetation Condition Index (VCI) and Vegetation Health Index (VHI) in Niger River Basin, Nigeria. Additionally, correlation and regression analyses were used to check the relationship between LST and NDVI. Results revealed that the mean NDVI for the year 2002 is 0.494, 0.477 in 2007, 0.468 in 2012, 0.458 in 2017 and 0.430 in 2022. The mean LST in Niger River Basin for year 2002 is 32.28 oC, 32.12 oC in 2007, 32.35 oC in 2012, 33.20 oC in 2017 and 33.41 oC in 2022. For the statistical relationship between NDVI and LST, results exhibited negative correlation, with -0.33 in 2002, -0.43 in 2007, -0.42 in 2012, -0.36 in 2017 and -0.27 in 2022. For the VCI results, findings revealed that the mean VCI in the basin was 83.73 in 2002, 64.26 in 2007, 56.76 in 2012, 45.32 in 2017, and 14.93 in 2023. Also, the VHI results revealed that the mean VHI in the basin was 75.44 in 2002, 69.54 in 2007, 61.02 in 2010, 37.22 in 2017 and 18.87 in 2022. The study therefore concluded that vegetation is decreasing in the basin, while land surface temperature is increasing.

The legged asteroid probe: Touchdown on locally refined rocky terrains and landing safety assessment

Studying the landing of a legged probe on asteroids with widely distributed rocks is of great significance. However, the landing safety of legged probes with flexible appendages (solar panels and touchdown legs) on the rocky terrain of asteroids is still unclear. In this study, we establish a complete rigid-flexible coupling touchdown dynamics model for an asteroid probe, and propose a new method for constructing locally refined rocky terrain. Moreover, two criteria for safe touchdown of the probe are established. Monte Carlo simulations are performed to analyze the landing success probability of the probe on different locally refined rocky terrains. The validity of the rock generation method and safety assessment is confirmed through repeated landing simulations. The simulation results show that the effect of the flexible appendages on the probe landing process cannot be ignored. With the same propulsion force of the probe, the landing success probability first increases and then decreases with increasing probe mass. Based on the original terrain, increases in rock size, quantity and power- index lead to the increase of the root-mean-square (RMS) height and RMS slope of rocky terrain, and then cause a decrease in the landing success probability of the legged probe. The results are expected to provide guidance for asteroid touchdown missions.

Analisis Saluran Distribusi Rantai Pasokan Padi di Desa Mruwak Dagangan Kabupaten Madiun

Mruwak is one of the villages in Madiun Regency where the majority of residents work as farmers. The food commodity most widely grown in the village is rice, while the rest are corn, sweet potatoes and peanuts. With the existence of a supply chain system, it is hoped that it can help farmers determine rice marketing routes effectively and efficiently. The aim of this research is to determine the supply chain system for rice produced by farmers in Mruwak Village. This research is qualitative in nature and the sample was selected purposively and using snowball sampling. The research results show the rice process, starting from land processing, rice planting, to maintenance and harvest. The farmers in the village have experience in growing rice, on average they have been growing rice for more than 10 years so they understand how to grow rice properly, including selecting superior seeds. The supply chain distribution channel used is a simple distribution channel model (1 to 3 level distribution channel model). Determination of selling prices based on agreements between farmers and buyers through demand and supply mechanisms (market mechanisms).

LUCA: A Sentinel-1 SAR-Based Global Forest Land Use Change Alert

The Land Use Change Alert (LUCA) dataset was developed for effective and timely monitoring of global forest changes that are mostly associated with human activities. Near- real-time changes of forest land use are mapped at 0.05 ha minimum mapping unit for all forest types across the Earth’s ecoregions, every two weeks. LUCA is based on Sentinel-1 cloud penetrating synthetic aperture radar (SAR) observations to circumvent limitations of optical imagery from pervasive cloud cover over forested areas globally, and especially in the tropics. The methodology is based on a combination of time-series change detection and machine learning analytics to achieve high accuracy of alerts across all ecoregions and landscapes globally with an average area-adjusted users and producers accuracy of 83% and 63%, respectively. The bi-weekly global alert maps capture forest clearing associated with deforestation and industrial timber harvesting, along with forest degradation associated with selective logging, fragmentation, fire, and roads. The product was developed and released publicly through Google Earth Engine to allow for the rapid assessment of land use change activities, quantifying patterns and processes driving forest change and dynamics across forest ecoregions. LUCA is designed to help monitor a variety of emission reduction programs at the local to regional scales and play a key role in implementing regulations on deforestation-free products.

Research on Unmanned Aerial Vehicle (UAV) Visual Landing Guidance and Positioning Algorithms

Considering the weak resistance to interference and generalization ability of traditional UAV visual landing navigation algorithms, this paper proposes a deep-learning-based approach for airport runway line detection and fusion of visual information with IMU for localization. Firstly, a coarse positioning algorithm based on YOLOX is designed for airport runway localization. To meet the requirements of model accuracy and inference speed for the landing guidance system, regression loss functions, probability prediction loss functions, activation functions, and feature extraction networks are designed. Secondly, a deep-learning-based runway line detection algorithm including feature extraction, classification prediction and segmentation networks is designed. To create an effective detection network, we propose efficient loss function and network evaluation methods Finally, a visual/inertial navigation system is established based on constant deformation for visual localization. The relative positioning results are fused and optimized with Kalman filter algorithms. Simulation and flight experiments demonstrate that the proposed algorithm exhibits significant advantages in terms of localization accuracy, real-time performance, and generalization ability, and can provide accurate positioning information during UAV landing processes.

Sustainability analysis and decision-making strategy for swamp buffalo (Bubalus bubalis carabauesis) conservation in Jambi Province, Indonesia

Abstract The objective of this study is to analyze the sustainability of swamp buffalo cultivation and develop decision-making strategies. Data were collected through focus group discussions with key informants in swamp buffalo cultivation and surveys of buffalo farmers in three regencies in Jambi Province. This study examines 37 attributes contained in four dimensions: ecological, economic, social, and technological dimensions. Data were analyzed using multidimensional scaling through the Rapid appraisal for buffalo technique and analytical hierarchy process (AHP) The results showed that the sustainability index of swamp buffalo cultivation in Sarolangun Regency was 59.39%, Batanghari 58.23%, and Tebo 55.93%. This study identified 12 leverage attributes obtained from 37 attributes that affect the sustainability of swamp buffalo, i.e., forage feed, agricultural waste, land use, agricultural infrastructure, land ownership, buffalo manure, buffalo ownership, livestock motivation, environmental impact, agricultural waste treatment, land processing, and post-harvest technology. Then, from the results of four-dimensional weighting with 12 attributes using AHP, there are 5 alternative strategies in decision making, namely, (1) build internet network infrastructure, (2) determine the number of livestock that can be raised in an area, (3) establish buffalo farming institutions, (4) prevent land use conflicts, and (5) increase farmer participation in raising buffalo livestock. This research provides input to policy makers to develop swamp buffalo cultivation by considering ecological, economic, social, and technological dimensions.

Effects of Terrain on the Landing of Locusta migratoria migratoria (Orthoptera: Acrididae) at the China–Kazakhstan Border1

Abstract We conducted a case study on the severe damage caused by the transboundary migration of Locusta migratoria (L.) (Orthoptera: Acrididae) in the Tacheng Prefecture and the Altay Prefecture at the China–Kazakhstan border by examining the effects of terrain on their landing behaviors. Based on the time and location of the locusts’ mass landings, we used mesoscale weather research and forecasting models to test the sensitivity (horizontal wind, vertical wind, temperature, and rainfall) of the terrain and simulate the effects of different terrain heights (terrain leveling, half terrain height, and actual terrain height) on landing. The results showed that changes in the regional terrain of the Tacheng and Altay prefectures did not enhance the vertical airflow over the landing area. With an elevation of the terrain, the precipitation intensity in the landing area of locusts also did not increase. We did detect a direct impact of wind direction and changes in temperature in the regional terrain on the landing process of L. m. migratoria. With an increase in terrain altitude, the wind direction over the landing area changed and the temperature decreased, resulting in large-scale forced landing. The results of this study have important value in predicting and forecasting the arrival of migratory locusts.

Response of Growth and Yield of Samhong King Curly Mustard Greens (Brassica juncea L.) to Land Tillage and Differences in Mulch Application

Land processing intensively and over an extended period can lead to a decline in cultivated land quality, resulting in suboptimal plant growth. The utilization of mulch is anticipated to enhance soil quality, enabling mustard plants to thrive and yield effectively. This study investigates the most effective type of mulch in conjunction with land tillage to maximize the growth and productivity of Samhong King curly mustard greens. The experiment was conducted at the Mapena Agricultural and Livestock Polytechnic experimental garden from November 2023 to March 2024. A factorial (3x2) experiment was set up in a randomized complete block design with four blocks. The first factor, mulch type, comprised three levels: straw, silver-black, and no mulch. On the other hand, the second factor, land tillage, consisted of two levels: tillage and no-tillage. Observations encompassed growth parameters, harvest variables, and environmental factors. The data underwent statistical analysis using analysis of variance (ANOVA), with Tukey's statistic calculated at a significance level of 5%. The findings revealed that the combination of tillage with silver-black mulch application facilitated superior growth and yield of curly mustard greens compared to the application of straw mulch or no mulch with tillage and no-tillage.

Spatial-Temporal Process of Land Use/Land Cover and Desertification in the Circum-Tarim Basin during 1990–2020

The problem of desertification in the Tarim Basin, an area with a unique geography and climatic conditions, has received extensive research attention not only in China but also around the world. Between natural factors and human activities, the latter are considered the main cause of desertification, with the excessive use of land resources accelerating its risk. This study classified the degree of desertification into five types, no, light, moderate, severe, and extremely severe desertification, and focused on the spatio-temporal changes in LULC, desertification development, and their relationship in the Circum-Tarim Basin during the period of 1990–2020, and the results indicated the following. (1) Over the 30-year study period, farmland development was frequent in the basin. The total farmland area increased significantly by 1.40 × 104 km2, which resulted from the occupation of grassland (mainly low-covered and medium-covered grassland) and unused land (mainly saline–alkali land). (2) There was a general alleviation of the effects of desertification, but also local deterioration. The area of no-desertification land has significantly increased (an increase of 2.10 × 104 km2), and the degree of desertification has shifted significantly to adjacent lighter degrees, but the area of extremely severe desertification in certain regions has increased (an increase of 7.89 × 104 km2). (3) There was an inseparable relationship between LULC and desertification. Oasisization and desertification were two processes that interacted and were interrelated. There was an approximately 54.42% increase in no-desertification land area mainly occurring in the region where LULC types changed (Region II), although this area only accounted for 9.71% of the total area of the basin. There was an approximately 98.28% increase in the area of extremely severe desertification occurring where there were no changes in LULC types (Region I). Region II demonstrated the best effects of desertification prevention and control in the 30-year study period in the Circum-Tarim Basin. Land development and oasis expansion have led to concentrated water use, resulting in water scarcity in certain areas, which cannot support the needs of vegetation growth, thus aggravating the degradation. Hence, “adapting measures to local conditions, rational planning, zoning policies, precise prevention and control” will be the way forward for desertification control in the future in the Circum-Tarim Basin.

Crater Triangle Matching Algorithm Based on Fused Geometric and Regional Features

Craters are regarded as significant navigation landmarks during the descent and landing process in small body exploration missions for their universality. Recognizing and matching craters is a crucial prerequisite for visual and LIDAR-based navigation tasks. Compared to traditional algorithms, deep learning-based crater detection algorithms can achieve a higher recognition rate. However, matching crater detection results under various image transformations still poses challenges. To address the problem, a composite feature-matching algorithm that combines geometric descriptors and region descriptors (extracting normalized region pixel gradient features as feature vectors) is proposed. First, the geometric configuration map is constructed based on the crater detection results. Then, geometric descriptors and region descriptors are established within each feature primitive of the map. Subsequently, taking the salience of geometric features into consideration, composite feature descriptors with scale, rotation, and illumination invariance are generated through fusion geometric and region descriptors. Finally, descriptor matching is accomplished by computing the relative distances between descriptors and adhering to the nearest neighbor principle. Experimental results show that the composite feature descriptor proposed in this paper has better matching performance than only using shape descriptors or region descriptors, and can achieve a more than 90% correct matching rate, which can provide technical support for the small body visual navigation task.

Soft-landing dynamics of a type of four-legged space lander

Analyzing the landing dynamics response is essential for enhancing the success rate of surface explorations on celestial bodies like Mars, the moon, and asteroids. This paper develops a comprehensive dynamics model for a space lander equipped with four sets of buffer legs. Each set comprises a primary strut, two secondary struts, and a footpad. The compression force of the buffer struts is determined through interpolation of real experimental data, while the contact force between the footpad and the ground is calculated using Archimedes law for granular media. The Lagrange equation of the second kind is employed to construct the dynamical model for the lander with minimal degrees of freedom. The proposed dynamics model is validated through experiments involving touchdowns of a single legged lander and a four legged lander. Moreover, key physical quantities such as the buffer force, energy absorption and body acceleration are computed for both 1-2-1 and 2-2 landing configurations. The results indicate that the buffer strut is capable of absorbing approximately half of the impact energy, leading to a 50-fold reduction in the shock acceleration of the main body in both landing configurations. However, it is observed that the maximum compression of the buffer strut is greater in the 1-2-1 landing configuration than in the 2-2 landing configuration. Furthermore, these simulations can be completed within seconds, enabling extensive simulations for the design and optimization of soft landing processes.

Aplikasi Pestisida Nabati pada Budidaya Tanaman Cabai Merah (Capsium Annum L) di Desa Ujung Bandar, Kabupaten Langkat

Chili has become a necessity for Indonesian people as an ingredient used as a cooking spice, thus making the demand for chili on the market very high. However, high market demand is often not matched by the supply of chilies on the market which is not sufficient to meet market needs. The lack of availability on the market is caused by several factors, one of which is crop failure caused by diseases and pests of chili plants. The first method of land processing is to loosen the land until it is fertile, after that it is sown with compost, usually with chicken, cow, and goat pui. After that, it is sprinkled and watered using a composter. The fertilizers used are synthetic and organic chemicals such as humic acid, trikoderma, PSE, and micro barter. Usually, the harvest produces an average of 300-500 grams per tree per cycle, not reaching 1 kg per tree in the harvest cycle. And some of the harvest is consumed and some is sold, and is usually sold through middlemen and to the market.

Combined onshore and offshore wide-scale seismic data acquisition and imaging for carbon capture and storage exploration in Havnsø, Denmark

Strong global actions for climate change include carbon capture and storage (CCS) as a feasible solution to reach carbon neutrality and raise opportunities for detailed subsurface investigations. An acquisition set-up designed for onshore-offshore zones was maximized for wide-scale high-resolution structural imaging and implemented to cover a domal structure of interest for CCS utilization close to the town of Havnsø (Denmark). The challenges of the combined acquisition and processing of land and marine multisensor data along a 42 km seismic profile are analyzed, the suggested solutions are applied, and the limitations are discussed. On the onshore side, a nodal array and a seismic landstreamer system were simultaneously used, whereas along the transition zone, a marine seismic streamer and ocean-bottom seismometers were added to record the seismic response generated by two seismic vibrator sources. The adopted sensing domains (velocity, acceleration, and pressure) were studied, and different processing steps were evaluated to enable their processing and subsequent data set merging. Results suggest, as the best approach, a separate prestack processing of the different data sets and the computation of new geometries and new surface-consistent residual static correction after their merging. The data acquired in the transition zone illuminate, for the first time, the subsurface geology of the region, delineating an expected domal closure. The final seismic section shows high continuity of the reflections with good resolution along the entire profile, identifying the main reservoir structure and the surrounding areas, which are important to ensure reservoir integrity and safe exploitation over longer time scales. Shallow and deep reflections are consistent with the stratigraphic column from a well log near the profile. The presented study shows a comprehensive workflow for processing such a multisensor data set in onshore and transition zone settings.