Delineation of Soil Texture Suitability Zones for Soybean Cultivation: A Case Study in Continental Croatia

Radočaj, Dorijan; Jurišić, Mladen; Zebec, Vladimir; Plaščak, Ivan

doi:10.3390/agronomy10060823

Cited by 18 publications

(7 citation statements)

References 71 publications

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“…In this regard, we decided to learn about the soil texture of the study area by integrating artificial intelligence algorithms into digital agriculture and to work on a methodology that can be used in similar regions. The soil texture class is a critical characteristic in determining the suitability of a site and selecting appropriate cultivation plants (Radocaj et al, 2020). The created digital soil texture map may be simply used by planners and farmers to identify ideal plots for promotion and to select the crop to plant based on analytical factors.…”

Section: Implications For Land Management and Soil Propertiesmentioning

confidence: 99%

Digital mapping of soil texture classes for efficient land management in the Piedmont plain of Iran

Keshavarzi

Árbol

Kaya

et al. 2022

Soil Use and Management

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Accurate prediction of digital soil maps allows for the evaluation of larger areas with respect to the design of efficient land management plans at the regional scale. Nowadays, there is an increasing demand for high spatial resolution‐gridded soil data for crop planning and management because it saves time and costs. One of the most essential soil physical properties affecting water holding capacity, nutrient availability and crop growth is soil texture. It exhibits a high spatial variability, but accurate maps for larger scales are lacking. The aim of this research was to produce gridded maps of soil texture fractions (clay, silt and sand) using regression‐based approaches and to establish soil texture classes using classification‐based techniques for the semi‐arid Piedmont plain of Iran. To this end, a digital elevation model and derived topographic indices, vegetation and soil‐based indices generated from 4‐year timeseries of remote sensing products of Landsat 8 OLI were used as covariates. The decision tree (linear) and its improved version of random forest (nonlinear) algorithms were used for both the regression and classification analysis. For both algorithms, the topography‐based indices and remotely sensed products were the most important predictors for the soil particle fractions. For the estimation of the different textural classes with multiple algorithms, we recorded a moderate overall accuracy rate of 54% and a Kappa coefficient of 17% for the validation datasets. It was observed that the nonlinear classification method of the random forest was more effective, and this was also the case for the regression modelling. In general, the random forest algorithm produced a more useful gridded map to help to design regional management plans based on soil properties.

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Section: Implications For Land Management and Soil Propertiesmentioning

confidence: 99%

Digital mapping of soil texture classes for efficient land management in the Piedmont plain of Iran

Keshavarzi

Árbol

Kaya

et al. 2022

Soil Use and Management

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“…Regarding a spatial character of the criteria important for agricultural production, GIS is imposed as a favorable environment for the implementation of multicriteria spatial data analysis (Malczewski, 2006). Various forms of a multicriteria analysis are successfully applied to the agricultural crops, resulting in the recommendations for better agricultural land management (Radočaj et al, 2020b). An analytical hierarchical process (AHP) is one of the multicriteria analysis methods with a broad application in numerous activities worldwide (Cobuloglu and Büyüktahtakın, 2015;Jurišić et al, 2020).…”

Section: Gis-based Multicriteria Analysis For Suitability Evaluationmentioning

confidence: 99%

“…Preparatory activities for the application of remote All discrete point data (soil samples, meteorological station data) should be interpolated by an optimal interpolation method, depending on the existence of a normal distribution, stationarity, or a data value trend (Radočaj et al, 2020b). The land suitability evaluation for crop cultivation is founded on a multicriteria analysis procedure while using the AHP method, and the first step in its implementation is a definition of all spatial criteria that may be modeled in a GIS environment and that influence the crop growth.…”

Section: Implementation On a Macro-levelmentioning

confidence: 99%

Current status and perspective of remote sensing application in crop management

Jurišić¹,

Radočaj²,

Šiljeg³

et al. 2021

JCEA

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Knowledge of the spatial distribution of agricultural crops and crop rotation is necessary for the understanding of the farming practices concerning the long-term sustainability of agricultural production. Agricultural crops are increasingly subject to drought due to the effects of global climate change, and the same is true for Croatia due to the constant rise in mean annual temperatures and uneven rainfall distribution. Remote sensing methods have proven to be superior in the detection and monitoring of drought compared to conventional methods of observation from meteorological stations. Information on the condition of crops in the early stages of development indicates potential irregularities in the development of agricultural crops. The objective of this paper is to provide a perspective for the application of remote sensing in crop management using state-of-the-art methods. Analysis of the possible implementation of these methods in Croatia was performed on a macro-and micro-level. Spatial classification, cropland suitability multicriteria analysis, drought assessment, weed detection and crop density calculation were evaluated according to the necessary equipment and data processing segments. Remote sensing application in crop management offers a potential basis for better crop management both at the macro-level for land use planning and at the micro-level for family farms.

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“…For each pixel, eight neighboring pixels were observed, and the final values of the flow accumulation model represent the total surface from which precipitation or water potentially flows from higher elevations. This model represents a single component of the hydrographic analysis of the terrain, as precipitation drainage and water flow depend on several factors, such as land cover class or soil texture [66]. The topographic openness index indicates the horizon exposure for a single pixel, which is applicable for spatial planning in the construction and analysis of animal and plant habitats.…”

Section: Modelling Of Terrain Topographic Parametersmentioning

confidence: 99%

Global Open Data Remote Sensing Satellite Missions for Land Monitoring and Conservation: A Review

Radočaj

Obhođaš

Jurišić

et al. 2020

Land

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The application of global open data remote sensing satellite missions in land monitoring and conservation studies is in the state of rapid growth, ensuring an observation with high spatial and spectral resolution over large areas. The purpose of this study was to provide a review of the most important global open data remote sensing satellite missions, current state-of-the-art processing methods and applications in land monitoring and conservation studies. Multispectral (Landsat, Sentinel-2, and MODIS), radar (Sentinel-1), and digital elevation model missions (SRTM, ASTER) were analyzed, as the most often used global open data satellite missions, according to the number of scientific research articles published in Web of Science database. Processing methods of these missions’ data consisting of image preprocessing, spectral indices, image classification methods, and modelling of terrain topographic parameters were analyzed and demonstrated. Possibilities of their application in land cover, land suitability, vegetation monitoring, and natural disaster management were evaluated, having high potential in broad use worldwide. Availability of free and complementary satellite missions, as well as the open-source software, ensures the basis of effective and sustainable land use management, with the prerequisite of the more extensive knowledge and expertise gathering at a global scale.

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Delineation of Soil Texture Suitability Zones for Soybean Cultivation: A Case Study in Continental Croatia

Cited by 18 publications

References 71 publications

Digital mapping of soil texture classes for efficient land management in the Piedmont plain of Iran

Digital mapping of soil texture classes for efficient land management in the Piedmont plain of Iran

Current status and perspective of remote sensing application in crop management

Global Open Data Remote Sensing Satellite Missions for Land Monitoring and Conservation: A Review

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