ABSTRACT
Mapping and monitoring cropping patterns is essential for a sustainable agriculture. This study aims to map and monitor cropping patterns in the Multan district located in Pakistan. For this purpose, the dataset comprising 16-day composite products at a 250-m resolution from MODIS (onboard the Terra platform) and Landsat satellite images was used over a period of 20 years (2000-2020) for kharif and rabi seasons. The preprocessing and postprocessing of the dataset were performed using a Normalized Difference Vegetation Index, logical modeling and supervised classification techniques. The results indicated that the Normalized Difference Vegetation Index increased in both rabi and kharif seasons. The land-use/land-cover maps (2000-2016) indicate that rapid urbanization leads to an increase in settlements, while the land-use/land-cover map of 2020 shows an increase in crops and vegetation due to the implementation of afforestation projects and spreading awareness among people. Moreover, crop phenology maps showed that the cotton crop dominated in the kharif season and the wheat crop dominated in the rabi season over the year. In addition, the Normalized Difference Vegetation Index during the kharif and rabi seasons has been found in the range of 0.8281 (end of season), −0.1966 (total length of growing season) and 0.8699 (start of season), −0.1943 (end of season), respectively. The overall study results recommend using crop field and satellite data in mapping crop patterns.
