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<p>The integration of unmanned aerial vehicles (UAVs) into environmental and agricultural research&#xa0; has transformed&#xa0; spatial data acquisition, thereby&#xa0;offering exceptional&#xa0; precision and cost-effectiveness. This study demonstrates the application of UAVs to assess&#xa0; Jhum cultivation in Khawrihnim village, Mamit district, India, responding to the&#xa0;increasing demand for fine-scale, real-time spatial data&#xa0;in&#xa0;agriculture, water resources, and forest management&#xa0;in the region. UAVs facilitated&#xa0;in&#xa0;the development of high-resolution land use-land cover (LULC) maps, showing&#xa0;that moderately dense forests covered the largest portion&#xa0;of&#xa0;the area (38.37%), followed by current Jhum land (7.96%) and older Jhum land (5.71%). Digital elevation models (DEMs) indicated&#xa0; that Jhum cultivation was predominantly&#xa0;concentrated at lower elevations (149–600&#xa0;m). Soil nutrient mapping using Kriging demonstrated key spatial trends, with nitrogen (N) increasing from hilltops to lower slopes, phosphorus (P) concentrated on backslope areas, and potassium (K) in lower slopes. Site suitability analysis using multi-criteria decision-making classified 18.97% of the area as very highly suitable for Jhum cultivation, with most zones in the northern and northwestern regions. A significant advancement from this study&#xa0;is the development of the “Heliware” online portal, which integrates UAV-derived data with advanced geospatial tools. The platform enables crop and soil nutrient mapping, 3D visualization, hydrological modeling, and real-time scenario planning. The findings from this study,&#xa0;highlight the transformative potential of UAVs and geospatial platforms for localized agricultural and environmental challenges, thereby&#xa0;offering a replicable framework for precision agriculture and sustainable resource management. Future work should incorporate advanced imaging techniques, machine learning algorithms, and long-term monitoring to enhance mapping accuracy and decision-making capabilities.</p>

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Integrating UAVs and Geospatial Technologies for Assessing Jhum Cultivation and Soil Dynamics in Mizoram: A Framework for Sustainable Agricultural Resource Management

  • 期刊论文

  • 发表日期：

    2025年7月25日

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  • Jeetendra Dixit,
  • Tauseef Ahmad,
  • Shruti Kanga,
  • Suraj Kumar Singh,
  • Gowhar Meraj,
  • Pankaj Kumar,
  • Md.Nazrul Islam,
  • Jatan Debnath,
  • Dhrubajyoti Sahariah,
  • Mohamed Yehia Abouleish,
  • Tarig Ali,
  • L. T. Sasang Guite

摘要

The integration of unmanned aerial vehicles (UAVs) into environmental and agricultural research  has transformed  spatial data acquisition, thereby offering exceptional  precision and cost-effectiveness. This study demonstrates the application of UAVs to assess  Jhum cultivation in Khawrihnim village, Mamit district, India, responding to the increasing demand for fine-scale, real-time spatial data in agriculture, water resources, and forest management in the region. UAVs facilitated in the development of high-resolution land use-land cover (LULC) maps, showing that moderately dense forests covered the largest portion of the area (38.37%), followed by current Jhum land (7.96%) and older Jhum land (5.71%). Digital elevation models (DEMs) indicated  that Jhum cultivation was predominantly concentrated at lower elevations (149–600 m). Soil nutrient mapping using Kriging demonstrated key spatial trends, with nitrogen (N) increasing from hilltops to lower slopes, phosphorus (P) concentrated on backslope areas, and potassium (K) in lower slopes. Site suitability analysis using multi-criteria decision-making classified 18.97% of the area as very highly suitable for Jhum cultivation, with most zones in the northern and northwestern regions. A significant advancement from this study is the development of the “Heliware” online portal, which integrates UAV-derived data with advanced geospatial tools. The platform enables crop and soil nutrient mapping, 3D visualization, hydrological modeling, and real-time scenario planning. The findings from this study, highlight the transformative potential of UAVs and geospatial platforms for localized agricultural and environmental challenges, thereby offering a replicable framework for precision agriculture and sustainable resource management. Future work should incorporate advanced imaging techniques, machine learning algorithms, and long-term monitoring to enhance mapping accuracy and decision-making capabilities.