Recent droughts and the profound effects they have on ecosystems, agriculture, and forests in California highlighted a critical need to understand drought impacts and develop remote sensing-based methods for drought monitoring. The objectives of this work were to evaluate drought-affected areas of northern and central California using remote sensing and aid in drought mitigation and prediction efforts for sustainable forest resource management and planning. Remote sensing provides direct measurement of spectral properties at moderate spatial resolution (30m with Landsat) as compared to modeled environmental variables at 800m spatial resolution, scaled to 270m. Modified Perpendicular Drought Index derived from Landsat data and long term Climatic Water Deficit (CWD) data for the year 2014 were analyzed. MPDI was strongly correlated with CWD, precipitation and temperature data for various forest types with coefficient of determination in the range of 0.60-0.80. Our results demonstrate that MPDI is an effective and direct method to monitor vegetation stress and forest declines at landscape scale, thereby providing land managers and stakeholders guidance in forest management and planning.