Drone-based photogrammetry is widely used for high-accuracy results, but its application in low-contrast environments is less explored and poses challenges. This study investigates optimal flight parameters and contrast enhancement methods to improve photogrammetric quality in such conditions. Four drone missions were conducted at two altitudes with varying overlaps. Data analysis compared point density and accuracy to identify the best flight configuration. Images are then enhanced using CLAHE algorithm for contrast and using ISO adjustments. The enhancement results were compared with the optimal mission. Findings show that reducing flight altitude to its half value and increasing overlap produced 33% accurate results on the altimetric level. The study also highlighted the CLAHE effect that significantly improved image matching and point cloud density. It allowed 63% better density for 3D points and 33% improving the relative altimetric accuracy value. Adjusting ISO to 400 also increased point density but was less effective than CLAHE enhancement. Finally, practical recommendations are formulated for achieving accurate RGB surveys in low-contrast environments.