Environmental geochemistry and health · 2026
Integrating geostatistics and landsat-8 OLI imagery for regional-scale spatial mapping and remote assessment of soil and foliar nitrogen status in citrus agroecosystem.
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Ahmed Humair, Hameed Muhammad Asad, Javed Nabeeha, Yousra Munazza, Niaz Maria, Baloch Bushra, Muminov Muydinjon, Razak Sarah Abdul, Abdelmohsen Shaimaa A M, Naseem Muhammad Tahir
Аннотация
Nitrogen (N) deficiency and inefficient fertilizer use pose serious challenges to sustainable citrus production in Pakistan, particularly in major citrus-growing regions such as Sargodha. This study integrated pedometric mapping, geostatistics, and satellite remote sensing to diagnose the nitrogen status of citrus orchards in District Sargodha, Pakistan. Geo-referenced soil samples were collected from 90 orchard sites at three depths (0-20, 20-40, and 40-60 cm) and analyzed for plant-available nitrate-N (NO3--N), while diagnostic leaf samples were analyzed for total nitrogen content. Spatial variability was assessed using semivariogram modeling and ordinary kriging to generate digital nutrient distribution maps. Landsat-8 OLI imagery was used to compute 43 vegetation indices (VIs) involving two and three spectral bands, and their relationships with soil NO3--N and foliage N were evaluated through correlation and regression analyses. Results revealed widespread deficiency of plant-available NO₃⁻-N in soils and total N in foliage across the study area. Surface soil NO3--N showed significant positive relationships with deeper soil layers, indicating that surface soil analysis can reliably predict N availability within the 0-60 cm soil profile. Geostatistical analysis indicated moderate to strong spatial dependence for soil NO3--N and strong spatial dependence for foliage N content. Several vegetation indices, particularly Ratio Vegetation Indices (RVI-1, RVI-2, RVI-3), NDVI-based indices, and soil-adjusted indices, exhibited strong correlations with both soil NO3--N and foliage N, explaining up to 70% of variability. The findings demonstrate the strong potential of combining pedometric mapping and Landsat-based remote sensing for regional-scale diagnosis of nitrogen status in citrus orchards, providing a foundation for site-specific and precision nitrogen management strategies.