Work

Towards the Generation of a Spatial Hydrological Soil Group Map Based on the Radial Basis Network Model and Spectral Reflectance Band Recognition

Year: 2022

Type: article

Abstract: Hydrological soil group is essential to soil information for several fields of modeling and applications. This information can affect suitable environmental, agricultural, and hydrological development. Laboratory analysis for soil sampling cannot efficiently provide the needed information because these analyses are commonly costly, time-consuming, and limited in retrieving the temporal and spatial variability. In this context, remote sensing is now solid to offer meaningful spatial data for studying soil characteristics on various spatial scales utilizing the different spectral reflectance. For this study, the integration of Geographic Information System (GIS) remote sensing data and survey data with the Artificial Neural Network (ANN) were used to generate a hydrological soil group map and to infer spatial patterns of soils across complete area converges for Alghadaf Wadi in the Western Desert of Iraq. The generated soil information was tested based on the sand, silt, and clay content. The testing result indicated that the differences between actual and predicted values to determine soil classes are agreed well. Therefore, this method is vital for mapping and monitoring soil texture by providing timely, fast repetitive data and relatively cheap.

Source: International Journal of Design & Nature and Ecodynamics

DOI: 10.18280/ijdne.170514

Authors: Khamis Naba Sayl, Sadeq Oleiwi Sulaiman, Ammar Hatem Kamel, Nadhir Al Ansari

Institutions: University of Anbar, Luleå University of Technology

Language: English

Topic: Soil Geostatistics and Mapping

Subfield: Soil Science

Field: Agricultural and Biological Sciences

Domain: Life Sciences

SDG: Life on land

Open Access status: bronze

Estimated APC paid: $505