Remotely sensed data play an essential role in environmental analysis and crop management. The arid agriculture region of Thal, Pakistan, is the major chickpea-growing region of the world. It was important to analyze the chickpea growth rate and yield with modern growing technology for better production in the changing climate. This study compared unmanned aerial vehicle (UAV) and Landsat imagery to monitor the crop growth and environmental parameters throughout the growing season. Twelve plots (2 x 2 m) were established in the field to monitor seven environmental parameters (plant height, number of pods and plant density, and final yield) for chickpea crop growth. A UAV drone mounted with Zenmuse X3 camera with four spectral was flown over the chickpea field on a biweekly basis to capture images with a spatial resolution of 1.86 m. The Landsat imagery (30 m spatial resolution) was also obtained, having the same UAV flight date. In spatio-temporal analysis, various vegetation indices, i.e., normalized difference vegetation index (NDVI) and soil-adjusted vegetation index (SAVI), were derived from UAV and Landsat imageries. The environmental impact parameters for crop growth were compared with the estimated final yield of chickpea crop. A coefficient of correlation (r(2) = 0.67; p <= 0.05) between observed chickpea crop yield and UAV-derived SAVI was significant (p <= 0.05). In comparison, a non-significant coefficient (r(2) = 0.21; p >= 0.05) was found between NDVI derived from Landsat imagery with yield. The chickpea crop yield was analyzed by estimating simple linear regression between NDVI and actual yield of chickpea crop during 30-40 days before the harvesting period. The average difference between actual yield and predicted yield through SAVI-D and NDVI-L was 558.42, 553.12, 556.84 kg/ha, respectively.