Agricultural chemicals pose increasing risks to soil, water and living organisms. Remote sensing (RS) offers potential to monitor vegetation responses to chemical treatments, yet most existing studies rely on limited samples, optical data only, or controlled experiments. This study explores a plot-level methodology for detecting vegetation responses to herbicide applications in real-world conditions by integrating optical and radar satellite data with pesticide treatment records.</p> <p>Crop plot geometries and Pesticide Use Reports (PUR) from Kern County, California, served as basis for analysis of RS indices derived from Sentinel-1 Synthetic Aperture Radar (SAR) and Sentinel-2 Multispectral (MS) imagery. The analysis focuses on treatments in potato crops, where a manually enriched pesticide dataset is used to group treatment events by their likely purpose. Two herbicide application scenarios - pre-emergent weed control and vine desiccation - were assessed using slope (1^st derivative) and slope-change (2^nd derivative) analysis applied to time series of optical and radar indices before and after treatments.</p> <p>Results show distinct slope and slope-change patterns for both scenarios. Pre-emergent applications exhibit neutral to slightly positive post-treatment trends, while desiccation events are associated with pronounced negative slope changes shortly after treatment. Radar-based metric shows a delayed response compared to optical indices, consistent with differences in spectral and structural vegetation changes.</p> <p>The findings demonstrate the potential of combining optical and SAR time series with treatment records for large-scale, plot-level assessment of pesticide-related vegetation dynamics. The paper outlines methodological starting points for introducing phenological alignment and control plots to improve causal inference in future work.