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Crop growth and yield are influenced by the genetic potential of the cultivar, soil, weather, and cultivation practices, i.e., sowing date, irrigation and fertilizer amount, and biotic stresses. Temporal variation in yield and growth has been largely forecasted using climate as a predictor, which can be achieved by using either an empirical or crop simulation approach for a given location. Climate and soil data collected over agricultural land regularly aid in crop growth monitoring, as well as crop vitality assessment. Crop simulation models (CSM) that have been successful in field-scale applications are now being implemented in GIS framework to simulate and monitor crop growth with remote sensing inputs, allowing for sensitive evaluations of seasonal weather conditions, local variability, and crop management signals. This research was designed to monitor the growth of three varieties of kiwifruit, i.e., Hayward grafted, Green-flesh, and Hayward, in four different localities: Hazaro (Attock), Simli Dam (Pind Begwal), GPU (germ plasm unit) Arid Agriculture University Rawalpindi and ZTBL (Zarai Taraqiati Bank Limited) Farm Islamabad, each of which has different soil and weather conditions. Soil proximal sensors were used to measure soil characteristics, and data loggers were installed in each field to monitor the weather parameters to collect data that influences crops. In this study, we used a quantitative method and GIS-integrated data to assess the impact of soil and climate on kiwifruit growth. It can help policy makers and researchers to identify new agro-climatic zones in Pakistan’s semi-arid regions for kiwifruit farming based on this data. In this study, we found that kiwi is very susceptible to temperatures above 40 °C, which cause mortality in kiwifruits plants. Morphological data with respect to soil and climate results showed that green-fleshed and Hayward varieties performed slightly better than Hayward grafted, which was most susceptible to diseases and heat damage.