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Soil Quality (SQ), as outlined by (Larson and Pierce, Conservation and enhancement of soil quality. Evaluation of sustainable land management in the developing world, International Board for Soil Research and Management, 1991), has been defined by a variety of indicators, expressed mathematically as SQ = f(q₁,…,q). This chapter deals with several geospatial techniques, geoinformatics to assess the soil quality and several geostatistical and non-geostatistical techniques to formulate Digital Soil Map (DSM). DSM provides a precise evaluation of essential soil quality parameters, including organic matter, pH levels, texture, nutrient availability as well as Soil Quality Index (SQI). Several statistical approaches are also described in calculating Soil Quality Index (SQI) from multiple soil quality indices. Soil parameters can be determined either through traditional approaches or advanced sensor data-based predictive modeling techniques. As example, from the DSM, spatial distribution of DTPA-extractable Zinc can easily be evaluated and which is less than 1.32 kg ha−1 in most of the places in Cooch Behar district. The extent of soil loss per year was spatially determined from Paschim Kharagpur region which varies from slight (<10 t ha−1 year−1) to severe (> 40 t ha−1 year−1). This chapter has also highlighted the critical role of geospatial tools and DSM in providing actionable insights on soil health and quality to support farmers, policymakers in addressing soil degradation and promoting sustainable land restoration practices.

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Concept of Soil Quality, Its Assessment and Mapping Through Geoinformatics and GIS-Based Platforms

  • 章节

  • 发表日期：

    2026年

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  • Rohit Kumar Choudhury,
  • Sumana Balo,
  • Arkaprabha Sarkar,
  • Dibyendu Mukhopadhyay,
  • Kallol Bhattacharyya,
  • Shubhadip Dasgupta,
  • Amiya Biswas,
  • Asim Biswas

摘要

Soil Quality (SQ), as outlined by (Larson and Pierce, Conservation and enhancement of soil quality. Evaluation of sustainable land management in the developing world, International Board for Soil Research and Management, 1991), has been defined by a variety of indicators, expressed mathematically as SQ = f(q₁,…,q). This chapter deals with several geospatial techniques, geoinformatics to assess the soil quality and several geostatistical and non-geostatistical techniques to formulate Digital Soil Map (DSM). DSM provides a precise evaluation of essential soil quality parameters, including organic matter, pH levels, texture, nutrient availability as well as Soil Quality Index (SQI). Several statistical approaches are also described in calculating Soil Quality Index (SQI) from multiple soil quality indices. Soil parameters can be determined either through traditional approaches or advanced sensor data-based predictive modeling techniques. As example, from the DSM, spatial distribution of DTPA-extractable Zinc can easily be evaluated and which is less than 1.32 kg ha−1 in most of the places in Cooch Behar district. The extent of soil loss per year was spatially determined from Paschim Kharagpur region which varies from slight (<10 t ha−1 year−1) to severe (> 40 t ha−1 year−1). This chapter has also highlighted the critical role of geospatial tools and DSM in providing actionable insights on soil health and quality to support farmers, policymakers in addressing soil degradation and promoting sustainable land restoration practices.