Best Grok prompts for Cartographers and Photogrammetrists

I have a dataset of aerial images taken over a rugged terrain with varying levels of relief displacement, and I need to optimize the orthorectification parameters to minimize residual distortions, taking into account the sensor's calibration parameters, the platform's altitude and velocity, and the terrain's digital elevation model; provide a step-by-step workflow to achieve this, including the mathematical formulas and software tools required, assuming a rational function model and aDEM with 1-meter resolution.

Given two sets of satellite images of an urban area taken at different times, with different spectral and spatial resolutions, I need to perform a change detection analysis to identify areas of new construction, land use conversion, or infrastructure development, using a combination of spectral and spatial analysis techniques, such as image differencing, regression analysis, and object-based image analysis; provide a detailed methodology, including the pre-processing steps, feature extraction, and classification algorithms, as well as the software tools and libraries required, assuming a multispectral image with 4 bands and a spatial resolution of 5 meters.

I have a non-metric camera with unknown interior orientation parameters, and I need to perform a geometric calibration to determine the camera's focal length, principal point, and distortion coefficients, using a set of images taken of a calibration target with known 3D coordinates; provide a step-by-step guide on how to extract the calibration parameters, including the mathematical models and software tools required, assuming a pinhole camera model and a calibration target with a checkerboard pattern.

I need to create a high-resolution terrain map of a flood-prone area, using a combination of LiDAR point cloud data and aerial imagery, to identify areas of high flood risk and prioritize mitigation efforts, taking into account the terrain's topography, land use, and soil type; provide a detailed workflow, including the data pre-processing steps, point cloud classification, and terrain modeling algorithms, as well as the software tools and libraries required, assuming a LiDAR point cloud with 10 points per square meter and an aerial image with 0.5-meter resolution.