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◆ Environmental geochemistry and health2026-08-19

Integrating geostatistics and landsat-8 OLI imagery for regional-scale spatial mapping and remote assessment of soil and foliar nitrogen status in citrus agroecosystem.

Humair Ahmed, Muhammad Asad Hameed, Nabeeha Javed, Munazza Yousra, Maria Niaz, Bushra Baloch, Muydinjon Muminov, Sarah Abdul Razak, Shaimaa A M Abdelmohsen, Muhammad Tahir Naseem

原始摘要(英文原文)· Original abstract
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.
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Integrating geostatistics and landsat-8 OLI imagery for regional-scale spatial mapping and remote assessment of soil and foliar nitrogen status in citrus agroecosystem. — 科研速览 Science Skim