Understanding the change dynamics of land use and land cover (LULC) is critical for efficient ecological management modification and sustainable land-use planning. This work aimed to identify, simulate, and predict historical and future LULC changes in the Sohag Governorate, Egypt, as an arid region. In the present study, the detection of historical LULC change dynamics for time series 1984–2002, 2002–2013, and 2013–2022 was performed, as well as CA-Markov hybrid model was employed to project the future LULC trends for 2030, 2040, and 2050. Four Landsat images acquired by different sensors were used as spatial–temporal data sources for the study region, including TM for 1984, ETM+ for 2002, and OLI for 2013 and 2022. Furthermore, a supervised classification technique was implemented in the image classification process. All remote sensing data was processed and modeled using IDRISI 7.02 software. Four main LULC categories were recognized in the study region: urban areas, cultivated lands, desert lands, and water bodies. The precision of LULC categorization analysis was high, with Kappa coefficients above 0.7 and overall accuracy above 87.5% for all classifications. The results obtained from estimating LULC change in the period from 1984 to 2022 indicated that built-up areas expanded to cover 12.5% of the study area in 2022 instead of 5.5% in 1984. This urban sprawl occurred at the cost of reducing old farmlands in old towns and villages and building new settlements on bare lands. Furthermore, cultivated lands increased from 45.5% of the total area in 1984 to 60.7% in 2022 due to ongoing soil reclamation projects in desert areas outside the Nile Valley. Moreover, between 1984 and 2022, desert lands lost around half of their area, while water bodies gained a very slight increase. According to the simulation and projection of the future LULC trends for 2030, 2040, and 2050, similar trends to historical LULC changes were detected. These trends are represented by decreasing desert lands and increasing urban and cultivated newly reclaimed areas. Concerning CA-Markov model validation, Kappa indices ranged across actual and simulated maps from 0.84 to 0.93, suggesting that this model was reasonably excellent at projecting future LULC trends. Therefore, using the CA-Markov hybrid model as a prediction and modeling approach for future LULC trends provides a good vision for monitoring and reducing the negative impacts of LULC changes, supporting land use policy-makers, and developing land management.

Appropriate phosphorus (P) management techniques increase yield and nutritional properties while minimizing environmental concerns. The widespread use of nano-fertilizers (NFs) in agriculture endangers soil and plants. It is vital to research the behavior of nano-phosphors (nano-P) on plant growth and quality, as well as their technique of interaction with soil properties in order to obtain key ecosystem benefits. With this in mind, a field experiment was conducted using wheat as a test crop to explore the impact of nano phosphorus (nano-P) on soil. The study’s goal was to examine how the foliar application of nano-P to wheat affects its growth, yield and nutrient concentration. Treatments consisted of: T₁: 100% NPK (120:137:72 kg N:P₂O₅:K₂O ha⁻¹) by RDF (recommended dose of fertilizer); T₂: 100% NPK by RDF + 2 foliar sprays of nano-P @ 494.21 mL ha⁻¹; T₃: 100% NK + 0% P (no foliar); T₄: 100% NK + 75% P + 2 foliar sprays of nano-P @ 494.21 mL ha⁻¹; T₅: 100% NK + 50% P + 2 foliar sprays of nano-P @ 494.21 mL ha⁻¹;T₆: 100% NK + 0% P + 2 foliar sprays of nano-P @ 494.21 mL ha⁻¹; T₇: 100% NPK by RDF + 1 foliar spray of nano-P @ 494.21 mL ha⁻¹; T₈: 100% NK + 75% P + 1 foliar spray of nano-P @ 494.21 mL ha⁻¹; T₉: 100% NPK + 1 foliar spray of nano-P @ 494.21 mL ha⁻¹; T₁₀-100% NK + 75% P + 1 foliar spray of nano-P @ 494.21 mL ha⁻¹. According to the findings, applying 100% NK + 75% P + 2 foliar applications of nano-P at the tillering and panicle initiation stages increased yield over 100% RDF by 37.1%. Additionally, the highest micronutrient concentration (Zn (36.4 mg kg⁻¹), Cu (21.2 mg kg⁻¹), Mn (22.9 mg kg⁻¹) and Fe (61.1 mg kg⁻¹)) in grain were noticed in T₃ (100% NK + 0% P no foliar spray of nano-P) treatment, which was superior to T₁ (100% NPK). Furthermore, foliar application of nano-P fertilizer in combination with different levels of diammonium phosphate (DAP) slightly increased the amount of N, P and K, as well as micronutrients in post-harvest soil. In summary, the use of 100% NK + 75% + 2 foliar applications of nano-P saved 25% recommendation dose P if supplied as nano-P as a form of phosphorus, and can be a suitable substitute for DAP, especially in smart agriculture, as it possibly reduces P leaching into groundwater, while maintaining or increasing wheat crop yield over the 100% RDF.