This study assesses the relationships between vegetation dynamics and climatic variations in Pakistan from 2000 to 2023. Employing high-resolution Landsat data for Normalized Difference Vegetation Index (NDVI) assessments, integrated with climate variables from CHIRPS and ERA5 datasets, our approach leverages Google Earth Engine (GEE) for efficient processing. It combines statistical methodologies, including linear regression, Mann-Kendall trend tests, Sen's slope estimator, partial correlation, and cross wavelet transform analyses.
View Article and Find Full Text PDFGlobal warming and food security have led to increasing concern about agricultural crop production efficiency, especially wheat and rice farming. The purpose of the current study is to measure wheat and rice production efficiency scores with environmental quality in China, India, and Pakistan by using a data envelopment analysis (DEA) model. The DEA results show that China and India are more efficient in wheat and rice production but it is not efficient in the environment in the study period.
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