Generative AI and 'text to GIS' are coming to ArcGIS Pro. GenAI is coming to replace most of the small-scale and basic analysis tasks, probably within 2-3 years. Here is a video of ArcGIS ecosystem using GenAI Assistant. https://mediaspace.esri.com/media/t/1_opret32t https://highearthorbit.com/articles/announcing-ai-assistants-for-arcgis/ And here is an updated roadmap for ArcGIS Pro - https://community.esri.com/t5/arcgis-pro-documents/arcgis-pro-roadmap-may-2024/ta-p/1419528/redirect_from_archived_page/true  

my previous post address your first question actually 😁 I saw that you already got the the equation for the band value and the depth, so it should be okay you directly apply it to get depth value 

Can you please address my question ?) is there any previous steps before calculation of models?

Researchers at the University of Science and Technology of China (USTC) have developed a compact and lightweight single-photon LiDAR system that can be deployed in the air to generate high-resolution three-dimensional images with a low-power laser. The technology could be used for terrain mapping, environmental monitoring, and object identification, according to a press release.  LiDAR, which stands for Light Detection And Ranging, is extensively used to determine geospatial information. The system uses light emitted by pulse lasers and measures the time taken by the reflected light to be received to determine the range, creating digital twins of objects and examining the surface of the earth.  A common application of the system has been to help autonomous driving systems or airborne drones determine their environments. However, this requires an extended setup of LIDAR sensors, which is power-intensive. To minimize such sensors’ energy consumption, USTC researchers devised a single-photon lidar system and tested it in an airborne configuration. The single-photon lidar The single-photon lidar system is made possible by detection systems that can measure the small amounts of light given out by the laser when it is reflected. The researchers had to shrink the entire LiDAR system to develop it.  It works like a regular LiDAR system when sending light pulses toward its targets. To capture the small amounts of light reflected, the team used highly sensitive detectors called single-photon avalanche diode (SPAD) arrays, which can detect single photons.  To reduce the overall system size, the team also used small telescopes with an optical aperture of 47 mm as receiving optics. The time-of-flight of the photons makes it possible to determine the distance to the ground, and advanced computer algorithms help generate detailed three-dimensional images of the terrain from the sensor.  “A key part of the new system is the special scanning mirrors that perform continuous fine scanning, capturing sub-pixel information of the ground targets,” said Feihu Xu, a member of the research team at USTC. “Also, a new photon-efficient computational algorithm extracts this sub-pixel information from a small number of raw photon detections, enabling the reconstruction of super-resolution 3D images despite the challenges posed by weak signals and strong solar noise.” Testing in real-world scenario To validate the new system, the researchers conducted daytime tests onboard a small airplane in Yiwu City, Zhejiang Province. In pre-flight ground tests, the LiDAR demonstrated a resolution of nearly six inches (15 cm) from nearly a mile (1.5 km). The team then implemented sub-pixel scanning and 3D deconvolution and found the resolution improved to 2.3 inches (six cm) from the same distance.  “We were able to incorporate recent technology developments into a system that, in comparison to other state-of-the-art airborne LiDAR systems, employs the lowest laser power and the smallest optical aperture while still maintaining good performance in detection range and imaging resolution,” added Xu.  The team is now working to improve the system’s performance and integration so that a small satellite can be equipped with such tech in the future.  “Ultimately, our work has the potential to enhance our understanding of the world around us and contribute to a more sustainable and informed future for all,” Xu said in the press release. “For example, our system could be deployed on drones or small satellites to monitor changes in forest landscapes, such as deforestation or other impacts on forest health. It could also be used after earthquakes to generate 3D terrain maps that could help assess the extent of damage and guide rescue teams, potentially saving lives.”