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<p>Soil quality (SQ) is crucial for sustaining agricultural productivity, environmental health, and human well-being. Evaluating SQ involves analyzing soil properties and their spatial distribution. Utilization of geographic information systems (GIS) helps in understanding soil heterogeneity and provides a robust framework for SQ monitoring. This study focuses on the state of Mizoram, Northeast India, characterized by its hilly terrain, high rainfall, and diverse forest types. Soil samples were collected from 103 points across 11 districts, representing four different forest types, to assess SQ variability throughout the state using various physical, chemical, and biological parameters. Key soil parameters, including pH, electrical conductivity (EC), moisture content, bulk density (BD), available nitrogen (N), phosphorus (P), potassium (K), micronutrients (Fe, Mn, Zn, Cu), soil organic carbon (SOC), soil microbial biomass carbon (SMBC), and dehydrogenase activity (DHA), were measured. The GMA was employed to integrate these parameters into a comprehensive Soil Quality Index (SQI). The GIS-based spatial modeling facilitated the creation of detailed SQ maps with 84% overall accuracy, revealing significant variability in soil properties across the region. The SQ was classified into five grades, with grade III being the most extensive, covering 40.75% of Mizoram. Notably, the Assam subtropical pine forests exhibited overall higher soil quality compared to other forest types. This study emphasizes the critical role of GIS-based spatial analysis in capturing soil heterogeneity and developing an effective framework for SQ monitoring. The results provide valuable insights for land management and sustainable agricultural practices, aiding efforts to maintain soil health and improve productivity in Mizoram.</p>

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Assessment and mapping of soil quality in different forest types of Mizoram, Northeast India

  • 期刊论文

  • 发表日期：

    2025年8月29日

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  • Debaaditya Mukhopadhyay,
  • Gaurav Mishra,
  • Sk Mujibar Rahaman

摘要

Soil quality (SQ) is crucial for sustaining agricultural productivity, environmental health, and human well-being. Evaluating SQ involves analyzing soil properties and their spatial distribution. Utilization of geographic information systems (GIS) helps in understanding soil heterogeneity and provides a robust framework for SQ monitoring. This study focuses on the state of Mizoram, Northeast India, characterized by its hilly terrain, high rainfall, and diverse forest types. Soil samples were collected from 103 points across 11 districts, representing four different forest types, to assess SQ variability throughout the state using various physical, chemical, and biological parameters. Key soil parameters, including pH, electrical conductivity (EC), moisture content, bulk density (BD), available nitrogen (N), phosphorus (P), potassium (K), micronutrients (Fe, Mn, Zn, Cu), soil organic carbon (SOC), soil microbial biomass carbon (SMBC), and dehydrogenase activity (DHA), were measured. The GMA was employed to integrate these parameters into a comprehensive Soil Quality Index (SQI). The GIS-based spatial modeling facilitated the creation of detailed SQ maps with 84% overall accuracy, revealing significant variability in soil properties across the region. The SQ was classified into five grades, with grade III being the most extensive, covering 40.75% of Mizoram. Notably, the Assam subtropical pine forests exhibited overall higher soil quality compared to other forest types. This study emphasizes the critical role of GIS-based spatial analysis in capturing soil heterogeneity and developing an effective framework for SQ monitoring. The results provide valuable insights for land management and sustainable agricultural practices, aiding efforts to maintain soil health and improve productivity in Mizoram.