Ivan Plašćak
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View article: Machine Learning Assessment of Soil Carbon Sequestration Potential: Integrating Land Use, Pedology, and Machine Learning in Croatia
Machine Learning Assessment of Soil Carbon Sequestration Potential: Integrating Land Use, Pedology, and Machine Learning in Croatia Open
Spatially quantifying the soil carbon sequestration potential (SCSP) is crucial for targeting climate change mitigation strategies like carbon farming. However, static mapping approaches often fail by assuming that the drivers of soil orga…
View article: A Systematic Review of Intelligent Navigation in Smart Warehouses Using Prisma: Integrating AI, SLAM, and Sensor Fusion for Mobile Robots
A Systematic Review of Intelligent Navigation in Smart Warehouses Using Prisma: Integrating AI, SLAM, and Sensor Fusion for Mobile Robots Open
This systematic review focuses on intelligent navigation as a core enabler of autonomy in smart warehouses, where mobile robots must dynamically perceive, reason, and act in complex, human-shared environments. By synthesizing advancements …
View article: Randomness in Data Partitioning and Its Impact on Digital Soil Mapping Accuracy: A Comparison of Cross-Validation and Split-Sample Approaches
Randomness in Data Partitioning and Its Impact on Digital Soil Mapping Accuracy: A Comparison of Cross-Validation and Split-Sample Approaches Open
Digital soil mapping has become increasingly important for large-scale soil organic carbon (SOC) assessments, yet the choice of accuracy assessment method significantly influences model performance interpretation. This study investigates t…
View article: A Comparative Assessment of Regular and Spatial Cross-Validation in Subfield Machine Learning Prediction of Maize Yield from Sentinel-2 Phenology
A Comparative Assessment of Regular and Spatial Cross-Validation in Subfield Machine Learning Prediction of Maize Yield from Sentinel-2 Phenology Open
The aim of this study is to determine the reliability of regular and spatial cross-validation methods in predicting subfield-scale maize yields using phenological measures derived by Sentinel-2. Three maize fields from eastern Croatia were…
View article: Evolution of Deep Learning Approaches in UAV-Based Crop Leaf Disease Detection: A Web of Science Review
Evolution of Deep Learning Approaches in UAV-Based Crop Leaf Disease Detection: A Web of Science Review Open
The integration of unmanned aerial vehicles (UAVs) and deep learning (DL) has significantly advanced crop disease detection by enabling scalable, high-resolution, and near real-time monitoring within precision agriculture. This systematic …
View article: Application of an Unmanned Aerial System (UAS) for Precise Fertilization
Application of an Unmanned Aerial System (UAS) for Precise Fertilization Open
The unmanned aerial system (UAS) eBee Plus, the eMotion guidance software and the Pix4dfields data processing software were investigated on two plots of wheat in PPK Valpovo. By using normalized difference vegetation index (NDVI), applicat…
View article: Phenology-Based Maize and Soybean Yield Potential Prediction Using Machine Learning and Sentinel-2 Imagery Time-Series
Phenology-Based Maize and Soybean Yield Potential Prediction Using Machine Learning and Sentinel-2 Imagery Time-Series Open
Unlike traditional yield mapping, which is conducted using costly yield sensors mounted on combine harvesters to collect post-harvest data, yield potential prediction using remote sensing data is considered a low-cost alternative. In this …
View article: Fusion of Sentinel-2 Phenology Metrics and Saturation-Resistant Vegetation Indices for Improved Correlation with Maize Yield Maps
Fusion of Sentinel-2 Phenology Metrics and Saturation-Resistant Vegetation Indices for Improved Correlation with Maize Yield Maps Open
To authors’ knowledge, no previous studies thoroughly focused on determining the single optimal combination of vegetation index and phenology metric for maize yield assessment based on ground truth yield map from combine harvester. Therefo…
View article: Assessing Whole-Body Vibrations in an Agricultural Tractor Based on Selected Operational Parameters: A Machine Learning-Based Approach
Assessing Whole-Body Vibrations in an Agricultural Tractor Based on Selected Operational Parameters: A Machine Learning-Based Approach Open
This paper presents whole-body vibration prediction in an agricultural tractor based on selected operational parameters using machine learning. Experiments were performed using a Landini Powerfarm 100 model tractor on farmlands and service…
View article: The Impact of Vibrations on the Hand–Arm System and Body of Agricultural Tractor Operators in Relation to Operational Parameters, Approach: Analytical Hierarchical Process (AHP)
The Impact of Vibrations on the Hand–Arm System and Body of Agricultural Tractor Operators in Relation to Operational Parameters, Approach: Analytical Hierarchical Process (AHP) Open
This paper presents research on the impact of vibrations on the hand–arm and body system of agricultural tractor operators as ergonomic indicators in relation to certain operational parameters. The measurements were conducted on a LANDINI …
View article: The Impact of Noise on Agricultural Tractor Operator in Relation to Certain Operational Parameters: An Analytical Hierarchy Process (AHP) Approach
The Impact of Noise on Agricultural Tractor Operator in Relation to Certain Operational Parameters: An Analytical Hierarchy Process (AHP) Approach Open
This study examines the impact of noise inside the cabin of an agricultural tractor on the operator, focusing on operational parameters: agrotechnical surfaces, speed of movement, and tire pressure. Noise measurements were conducted on a L…
View article: Fuel Consumption of the Tractor-Machine Aggregate Conditioned by the Navigation Systems
Fuel Consumption of the Tractor-Machine Aggregate Conditioned by the Navigation Systems Open
This paper presents a study regarding fuel consumption, distance traveled and aggregate operation time during agrotechnical harrowing operation with and without a navigation system in the company. The measurement was carried out on an area…
View article: A Machine-Learning Approach for the Assessment of Quantitative Changes in the Tractor Diesel-Engine Oil During Exploitation
A Machine-Learning Approach for the Assessment of Quantitative Changes in the Tractor Diesel-Engine Oil During Exploitation Open
To evaluate the potential of a machine-learning approach in the assessment of quantitative changes in the tractor diesel-engine oil during exploitation, this study aspired to propose a machine-learning regression method to reduce the frequ…
View article: Prediction of Noise Levels According to Some Exploitation Parameters of an Agricultural Tractor: A Machine Learning Approach
Prediction of Noise Levels According to Some Exploitation Parameters of an Agricultural Tractor: A Machine Learning Approach Open
The paper presents research on measuring and the possibility of prediction of noise levels on the left and right sides of the operator within the cabin of an agricultural tractor when moving across various agrotechnical surfaces, consideri…
View article: Phenology analysis for detection of vegetation changes based on Landsat 8 images in Nature Park Kopački rit, Croatia
Phenology analysis for detection of vegetation changes based on Landsat 8 images in Nature Park Kopački rit, Croatia Open
This study proposed a method for detecting vegetation changes and establishing geospatial management zones based on the 10-year phenology analysis using normalized difference vegetation index (NDVI) long-term trends from Landsat 8 multispe…
View article: Global Navigation Satellite Systems as State-of-the-Art Solutions in Precision Agriculture: A Review of Studies Indexed in the Web of Science
Global Navigation Satellite Systems as State-of-the-Art Solutions in Precision Agriculture: A Review of Studies Indexed in the Web of Science Open
Global Navigation Satellite Systems (GNSS) in precision agriculture (PA) represent a cornerstone for field mapping, machinery guidance, and variable rate technology. However, recent improvements in GNSS components (GPS, GLONASS, Galileo, a…
View article: An Independent Validation of SoilGrids Accuracy for Soil Texture Components in Croatia
An Independent Validation of SoilGrids Accuracy for Soil Texture Components in Croatia Open
While SoilGrids is an important source of soil property data for a wide range of environmental studies worldwide, there is currently an extreme lack of studies evaluating its accuracy against independent ground truth soil sampling data. Th…
View article: A Micro-Scale Approach for Cropland Suitability Assessment of Permanent Crops Using Machine Learning and a Low-Cost UAV
A Micro-Scale Approach for Cropland Suitability Assessment of Permanent Crops Using Machine Learning and a Low-Cost UAV Open
This study presents a micro-scale approach for the cropland suitability assessment of permanent crops based on a low-cost unmanned aerial vehicle (UAV) equipped with a commercially available RGB sensor. The study area was divided into two …
View article: GIS-Based Visitor Count Prediction and Environmental Susceptibility Zoning in Protected Areas: A Case Study in Plitvice Lakes National Park, Croatia
GIS-Based Visitor Count Prediction and Environmental Susceptibility Zoning in Protected Areas: A Case Study in Plitvice Lakes National Park, Croatia Open
The most valuable protected natural areas, including national parks, are subjected to the increased visitors count and density, threatening the environmental sustainability and biodiversity conservation. To establish a basis for land manag…
View article: A Multiscale Cost–Benefit Analysis of Digital Soil Mapping Methods for Sustainable Land Management
A Multiscale Cost–Benefit Analysis of Digital Soil Mapping Methods for Sustainable Land Management Open
With the emergence of machine learning methods during the past decade, alternatives to conventional geostatistical methods for soil mapping are becoming increasingly more sophisticated. To provide a complete overview of their performance, …
View article: A UAS and Machine Learning Classification Approach to Suitability Prediction of Expanding Natural Habitats for Endangered Flora Species
A UAS and Machine Learning Classification Approach to Suitability Prediction of Expanding Natural Habitats for Endangered Flora Species Open
In this study, we propose integrating unmanned aerial systems (UASs) and machine learning classification for suitability prediction of expanding habitats for endangered flora species to prevent further extinction. Remote sensing imaging of…
View article: A Low-Cost Global Navigation Satellite System Positioning Accuracy Assessment Method for Agricultural Machinery
A Low-Cost Global Navigation Satellite System Positioning Accuracy Assessment Method for Agricultural Machinery Open
The high-precision positioning and navigation of agricultural machinery represent a backbone for precision agriculture, while its worldwide implementation is in rapid growth. Previous studies improved low-cost global navigation satellite s…
View article: Smart Agriculture Development and Its Contribution to the Sustainable Digital Transformation of the Agri-Food Sector
Smart Agriculture Development and Its Contribution to the Sustainable Digital Transformation of the Agri-Food Sector Open
This study analyses the importance of the connection between the development of smart agriculture and sustainable digital transformation (DT) of the agri-food sector. The sustainability of DT depends on a number of complex components, espe…
View article: An Overview of Precision Irrigation Systems Used in Agriculture
An Overview of Precision Irrigation Systems Used in Agriculture Open
The introduction of precision agriculture increased the efficiency of plant production, while simultaneously reducing the production cost. Precision irrigation can be considered as the combination of sensors, computer software and irrigati…
View article: Sensors and Their Application in Precision Agriculture
Sensors and Their Application in Precision Agriculture Open
The paper depicts sensors in precision agriculture. It encompasses the most significant and frequently used sensors in agriculture. Furthermore, the paper explains the main sensor types according to their design, the recorded range of elec…
View article: Application of Robots and Robotic Systems in Agriculture
Application of Robots and Robotic Systems in Agriculture Open
The paper depicts agricultural robots that can perform complex tasks. Fast development and application of agricultural robotics is a result of increased development of agricultural machinery. Robots are complex and intelligent systems with…
View article: Cropland Suitability Assessment Using Satellite-Based Biophysical Vegetation Properties and Machine Learning
Cropland Suitability Assessment Using Satellite-Based Biophysical Vegetation Properties and Machine Learning Open
The determination of cropland suitability is a major step for adapting to the increased food demands caused by population growth, climate change and environmental contamination. This study presents a novel cropland suitability assessment a…
View article: A Comparison of Precise Fertilization Prescription Rates to a Conventional Approach Based on the Open Source GIS Software
A Comparison of Precise Fertilization Prescription Rates to a Conventional Approach Based on the Open Source GIS Software Open
Fertilization is one of the most important components of precision agriculture, ensuring high and stable crop yields. The process of spatial interpolation of soil sample data is recognized as a reliable method of determining the prescripti…
View article: An Overview of Precision Irrigation Systems Used in Agriculture
An Overview of Precision Irrigation Systems Used in Agriculture Open
The introduction of precision agriculture increased the efficiency of plant production, while simultaneously reducing the production cost. Precision irrigation can be considered as the combination of sensors, computer software and irrigati…